Land-use change: assessing the net climate forcing, and options for climate change mitigation and adaptation
This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement number 603542.
The potential effects of land-based mitigation on the
climate system and the wider environment: A synthesis
of current knowledge in support of policy
Ylva Longva, University of Edinburgh
Mark D.A. Rounsevell, University of Edinburgh and Karlsruhe Institute of Technology
Almut Arneth, Karlsruhe Institute of Technology
Elizabeth Clarke, University of Edinburgh
Jo House, University of Bristol
Annalisa Savaresi, University of Edinburgh
Lucia Perugini, CMCC (Centro Euro-Mediterraneo sui Cambiamenti Climatici)
Peter Verburg, VU Amsterdam
September 2017
luc4c.eu
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Executive Summary Land-based options to mitigate climate change are expected to deliver approximately a quarter of
emissions reductions pledged by countries in their Nationally Determined Contributions (NDCs) under
the Paris Climate Agreement, and is key to achieving the zero balance target between anthropogenic
emissions and removals in the second half of the 21st Century. We review new scientific knowledge on
land-based mitigation options, the effect of these options on land-use and land-cover change (LULCC)
and their interplay with other environmental concerns. Land-based mitigation provides policy-makers
with competing demands and trade-offs, but also possible co-benefits, and it is through this policy lens
that we synthesise the state of the current knowledge. The primary mitigation options considered in this
summary are: (i) afforestation-reforestation and avoided deforestation, and (ii) bioenergy with carbon
capture and storage (BECCS)1.
Message 1: Land-based mitigation competes for land with food production, other
ecosystem services & biodiversity
There is evidence to suggest that land-based mitigation already has increased food prices, and models
predict further increases, due to the competition for land and the direct use of food crops as a
bioenergy feedstock. The land area required to achieve emission reductions from land-based mitigation
consistent with most 2°C scenarios, is substantially higher than the available land area currently
identified as marginal or abandoned. However, potential land allocation for climate change mitigation
depends on other claims on the same lands, the degree of climate change, technological developments
and dietary preferences. Intensification of agricultural land use could free up more land for climate
mitigation, but this can have other environmental impacts if not done sustainably.
Land-based mitigation policies and strategies in one location affect land use elsewhere due to
displacement; an example of indirect land-use change (iLUC). iLUC can be a major source of GHG
emissions that are not always reported, particularly when the displacement happens in countries with
limited reporting of GHG fluxes. When iLUC is included in life-cycle analyses of different bioenergy
feedstocks, it alters the feedstock’s relative GHG mitigation performance, which has the potential to
undermine conventional bioenergy crops as a sustainable energy source. EU legislation assumes that
the biomass used for electricity generation is carbon-neutral, as it assumes that the land sector captures
both direct and indirect LUC emissions. Not reporting the land sector emissions embodied in the goods
produced within a country can lead to substantial emissions under-reporting. Labelling and certification
schemes for biofuel feedstocks could decrease iLUC and embodied emissions. Furthermore, recent
changes in EU policy seek to limit the share of food-based biofuels and to promote advanced feedstocks.
Terrestrial ecosystems provide a range of ecosystem services, but land-based mitigation impacts on
the ability of ecosystems to provide both the amount and the quality of some of these services. For
instance, bioenergy production has a higher water demand than any other alternative energy source,
1 A third important option, reducing greenhouse gas emissions (esp. N2O and CH4) through agricultural practices was not within
the remit of the LUC4C project.
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and can compete with other water uses unless managed carefully. Intensification of food production
could lead to more land being available for other uses, but is associated with large nitrogen losses to the
atmosphere and water pollution from fertilisers. Provisioning services, such as food and biomass
production, and regulating services, such as carbon sequestration or flood protection, are currently
often not compatible, but could be with more integrated approaches to land management. Provisioning
services are often more tangible and easier to exchange in the market than regulating services, cultural
services or the protection of biodiversity. European policies and emissions targets raise the demand for
woody biomass, consequently reducing forest carbon sinks. However, the carbon sink reduction would
be small if advanced bioenergy crops rather than forest removals were used to meet energy demand.
Land-based mitigation competes for land with biodiversity, but there is potential for achieving co-
benefits. Some land-based mitigation options are incompatible with biodiversity goals. Afforestation
using monoculture plantations reduces species richness when introduced into (semi-)natural grasslands;
a habitat that is prioritised by EU policies on biodiversity. Evidence suggests that when faced with
conflicting mitigation and biodiversity goals, biodiversity is typically given a lower priority, especially if
the mitigation option is considered risk-free and economically feasible. Approaches that promote
synergies, such as avoided deforestation, land sparing and sustainable farming practices in bioenergy
production, and longer rotation-times and mixed-species forests in afforestation-reforestation, can
avoid the loss of biodiversity from land-based mitigation. Systematic land-use planning would help to
achieve land-based mitigation options that also limit trade-offs with biodiversity.
Message 2: Biophysical effects are significant and can have important co-benefits
LULCC affects climate not only through greenhouse gas emissions and uptake, but also through
biophysical effects, especially at the regional scale. Biophysical effects include the reflectance of
sunlight from the Earth’s surface (albedo), cooling from evapotranspiration and the absorbance of wind
energy. Changes in vegetation cover alter the reflection of sunlight (albedo); crops and pastures tend to
be more reflective than darker forests, and this has a cooling effect. However, forests have higher
evapotranspiration rates than crops and pastures, which cools the land surface as well as recycling water
to fall as rain. Forests also absorb wind energy and this has implications for local surface temperatures.
The net effects of these processes play out differently in different parts of the world. Satellite
observations show that large-scale regional deforestation has a predominantly warming effect in the
tropics, and parts of the temperate zone, due to reduced evapotranspiration. However, deforestation
causes cooling in the boreal regions, due to increased reflection of sunlight, especially in winter and
spring, but unlike the tropics, in boreal regions the agreement between measurements and models is
less clear. Uncertainties remain regarding the magnitude of the effect, especially for seasonal variables
(e.g., maximum summer temperatures), and for the effects on precipitation, but it is now well
established that the regional biophysical effects of land-cover change are substantial. Furthermore,
biophysical effects on local temperature are more rapid than warming arising from global atmospheric
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CO2 levels. Thus, mitigation actions taken at the regional level would benefit from considering the
consequences of biophysical effects on local temperature as well as the impacts of GHG emissions. There
are major benefits in doing so, since accounting for the biophysical climate effects of LULCC can support
both mitigation and adaptation objectives and thus, make policy more effective.
Current global, policy frameworks do not consider biophysical effects, and hence opportunities exist
for policy to realise co-benefits. Although local biophysical climate impacts from LULCC are large, they
tend to be much smaller when aggregated globally and this has implications for global policy. The
process of including land-based mitigation in the UNFCCC context has been a matter of long and complex
negotiations. Hence, the relatively small and currently uncertain global biophysical effects make it
difficult to justify efforts to include these effects in the complex negotiations of the UNFCCC process, at
present. However, it is now possible to evaluate the regional biophysical impacts (changes in local
temperature) of land cover transitions, following a tiered method similar to that of the IPCC to estimate
the effects of GHG emissions. The method applies three levels of increasing complexity, from Tier 1 (i.e.
default method and factors) to Tier 3 (i.e. country-specific methods and factors). The procedures
proposed for each tier method are transparent, taking into consideration the UNFCCC reporting
principles and could inform mitigation efforts at regional or national scales to realise the co-benefits of
accounting for biophysical effects.
Policies that support avoided deforestation, especially in tropical regions, have especially large co-
benefits. Avoided deforestation mitigates global climate change by reducing CO2 emissions. It also
affects the local climate in a positive way by maintaining cooler surface temperatures through
biophysical effects. Future climate change will also increase vegetation growth through the effect of
atmospheric CO2 fertilisation and this will further enhance the biophysical cooling effects of forests.
Thus, avoided deforestation as a land-based mitigation option benefits from positive effects on both the
regional and global climate systems.
Message 3: Time lags and multiple goals strongly limit the effectiveness of land-based
mitigation, but there is potential for improvement and co-benefits can be achieved
The relative contribution to climate mitigation of different land-based mitigation options changes
through time. Avoided deforestation provides immediate mitigation gains by reducing rapid carbon
emissions that take place when forests are cut or burnt (as well as having co-benefits with multiple
ecosystem services). Afforestation-reforestation can take-up carbon immediately upon planting, but
with varying, relatively small annual gains due to the slow rate of forest growth, especially as forests
approach maturity. The current carbon sink of EU forests due to past afforestation will likely decline due
to forest ageing. Harvesting and replanting, with carbon storage in harvested wood products or use as
bioenergy, can enable the same land to continue to contribute to mitigation, but care has to be taken
to sustainably manage repeated harvesting in order not to deplete soil carbon stocks. Overall, bioenergy
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(especially lignocellulosic) is expected to contribute more to mitigation scenarios in the second half of
the century, but this will depend on the availability of advanced technologies.
Time lags in policy implementation and uptake strongly influence the effectiveness of land-based
mitigation policy. There are large uncertainties associated with the development and implementation
of BECCS, and other land-based mitigation options. Barriers arising from the rate of technological
development and the considerable need for financial investment mean that the large scale
implementation of BECCS is not likely until around the middle of the 21st century, at the very earliest.
Furthermore, the rate of uptake of bioenergy crops by farmers can be slow in spite of the existence of
financial support. Such barriers could limit the success of bioenergy as a land-based mitigation option.
This demonstrates the importance of immediate policy action, and measures to support more rapid
policy intervention and uptake.
The success of afforestation-reforestation and avoided deforestation as mitigation options are subject
to the changing risks from disturbances that affect forest permanence and depend on continued
monitoring and management of forest stands over the long term. Disturbances arising from climate
extremes, wild fires, pest and diseases affect afforestation-reforestation and avoided deforestation, but
also yields of bioenergy crops. The risk of these disturbances will also change with future climate change.
Better understanding disturbances and how to manage them in a changing climate would reduce
uncertainty and therefore the risks associated with investment in mitigation options. Monitoring,
Reporting and Verification (MRV) of forest carbon and other land based mitigation schemes need to be
able to account for disturbances (and associated carbon losses) to provide confidence that land-based
mitigation projects will meet their long-term objectives. Recent advances in satellites and modelling
capabilities can support MRV, along with capacity building in developing countries.
There are potential synergies between land-based mitigation and adaptation that would allow co-
benefits to be achieved. Primary forests, in contrast to monoculture plantations, provide a wide range
of ecosystem services and have more biodiversity, which are characteristics of a resilient forest
ecosystem. Hence, avoided deforestation of primary forests could benefit both mitigation (retaining
carbon) and adaptation (greater resilience) to climate change. Furthermore, planting trees in urban
areas has mitigation benefits (carbon storage) as well as adaptation benefits (cooling effects, and
reducing surface water run-off and flooding). Changing food consumption patterns (e.g. through low-
meat diets, reducing over-eating and waste, and eating alternative protein sources) reduces the land
area needed for food production providing opportunities for land-based mitigation. This also builds
resilience to climate change, since the additional availability of land could offset the negative impact of
climate change on crop yields and thus food production. These examples demonstrate potential
opportunities, but there is little scientific evidence to support understanding of the full extent of
mitigation-adaptation synergies (or trade-offs), which is a major knowledge gap.
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Developing policies that systematically cut across policy sectors would achieve co-benefits for
multiple policy goals. Co-benefits are not always realised, and a single sector focus can often cause
unintended negative impacts on other sectors, e.g. by promoting land clearing, which is associated with
negative impacts on carbon and flooding. Well-grounded, land-based mitigation strategies can have
positive social benefits, but conversely, land-based mitigation can have negative environmental and
social impacts if poorly planned. There is considerable potential for rural development and job creation
linked to European bioenergy markets. However, entry into the sector often requires economies of scale
(excluding smallholders) and time lags in implementation and up-take are also constraints (as outlined
above).
In Summary
Land-based mitigation is not a ‘silver-bullet’ to avoid climate change, but alongside drastic reductions
in fossil fuel emissions, it can contribute to delivering the “balance of sources and sinks” in the Paris
Agreement. Land-based mitigation is currently the only way to remove CO2 from the atmosphere at a
scale that is potentially relevant to climate mitigation. The land sector will not be emissions free due to
the emissions necessarily associated with food production. Moreover, there is a real danger that land-
based mitigation will compete with food production, the provision of other ecosystem services and
biodiversity. Further analysis is required to understand fully the many trade-offs, beyond climate
mitigation that arise from land management and to identify policy options that support co-benefits.
Land-based mitigation could potentially enable the land sector as a whole to approach a balance of
sources and sinks, and, if barriers are overcome and sustainability ensured, it could further offset some
of the more unavoidable emissions from fossil fuels.
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Table of Contents
Executive Summary ...................................................................................................................... 2
Introduction .................................................................................................................................. 10
Box 1: Introducing the LUC4C Project ............................................................................................... 11
Box 2: Defining land-based mitigation options ................................................................................. 14
Box 3: Projected bioenergy trends in Europe ................................................................................... 15
Topic 1: Land-based mitigation competes for land and this has negative
consequences .................................................................................................................. 16
1a. Land-based mitigation increases food prices because of land competition and the direct
use of food crops as a bioenergy feedstock ......................................................................... 16
1b. Land-based mitigation competes for land with ‘nature’ and the maintenance of
biodiversity .................................................................................................................................. 18
1c. Land-based mitigation in one location can directly affect land use elsewhere due to
displacement effects, an example of indirect land-use change ......................................... 20
Topic 2: Land-based mitigation has trade-offs with, but also co-benefits for, the
provision of ecosystem services .................................................................................. 22
2a. Land-based mitigation impacts on the ability of ‘nature’ to provide other ecosystem
services ....................................................................................................................................... 22
2b. Co-benefits between land-based mitigation and ecosystem service provision are
feasible ........................................................................................................................................ 24
2c. There are trade-offs between energy generation and carbon stocks for different land-
based mitigation options........................................................................................................... 27
Topic 3: Biophysical and biochemical cycles ......................................................................... 28
3a. LULCC affects climate not only through greenhouse gas emissions and uptake, but also
through biophysical effects, especially at the regional scale, but this is not accounted
for in policy ................................................................................................................................. 28
Topic 4: The longevity and timing of land-based mitigation strategies ............................. 31
4a. The relative contribution of different land-based mitigation options changes through
time. ............................................................................................................................................. 31
4b. Time lags in the science-policy-society exchange process influence the effectiveness
of land-based mitigation policy ................................................................................................ 32
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4c. The success of A/R and AD as mitigation options depends on continued monitoring and
management of forest stands .................................................................................................. 34
4d. The success of avoided deforestation and reforestation depends on the changing risks
from disturbances, such as climate extremes, wild fires and pest and diseases, which
affect forest permanence ......................................................................................................... 36
Topic 5: Landscape management and alternate land-use futures ...................................... 37
5a. Forest management is increasingly recognised as an important contributor to land
sector carbon fluxes in both science and policy communities ............................................ 37
5b. Livestock and cropping systems are significant contributors to global emissions of non-
CO2 GHGs. The management of these systems has the potential to reduce GHG
emissions .................................................................................................................................... 40
5c. There are a number of alternative scenarios of land-based mitigation that are rarely
explored since most future scenarios are based on a limited set of conventional
options such as agricultural management, A/R and BECCS ............................................. 45
Topic 6: Multiple policy goals and co-benefits ....................................................................... 47
6a. There are potential synergies between land-based mitigation and adaptation that would
allow co-benefits to be achieved ............................................................................................. 47
6b. Positive social benefits can be derived from well-grounded land-based mitigation
strategies, but, conversely, land-based mitigation can have negative social impacts
if poorly planned ........................................................................................................................ 49
6c. Co-benefits are possible across a set of policy targets if policy is developed
systematically across sectors rather than in isolation .......................................................... 51
6d. The implementation of BECCS is uncertain ............................................................................... 53
6e. Land-based mitigation is not a ‘silver-bullet’ to avoid climate change and must be part
of a policy framework that also reduces fossil fuel based emissions ................................ 54
Abbreviations ............................................................................................................................... 57
Annex 1: Relevant International Climate Policies .................................................................. 58
A1.1 Climate Change within the UN policy framework .................................................................... 58
A1.2 Biodiversity and Ecosystem Services with the UN policy framework .................................. 59
A1.3 Sustainable Development Goals ............................................................................................... 59
Annex 2: Relevant European Policies ...................................................................................... 59
A2.1 EU Climate and Energy Package .............................................................................................. 59
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A2.2 European ETS .............................................................................................................................. 60
A2.3 European Effort-Sharing Decision and Effort-Sharing Regulation ....................................... 60
A2.4 European Land Use Decision .................................................................................................... 61
A2.5 Renewable Energy Directive and Fuel Quality Directive ....................................................... 61
A2.6 Forest 2013 strategy .................................................................................................................... 62
A2.7 Common Agricultural Policy ....................................................................................................... 63
References .................................................................................................................................... 64
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Introduction Land-use and land-cover change (LULCC) impacts the climate regionally, as a consequence of biophysical
changes (see [1]), and globally, as a consequence of greenhouse gas (GHG) emissions/sequestration
(biogeochemical processes) (see [2]). LULCC emissions from activities such as deforestation, logging and
intensive agriculture constitute the second largest anthropogenic source of CO2 [2]). Houghton et al.
1999 [3] estimates that 124 PgC were released to the atmosphere as a consequence of LULCC between
1850 and 1990; approximately one-third of total anthropogenic emissions. Between 1990 and 2000,
LULCC derived CO2 emissions represented 20% of total anthropogenic CO2 emissions [2], decreasing to
9% between 2006 and 2015 [4]. If non-CO2 GHG emissions, such as methane (CH4) and nitrous oxide
(N2O), are included, this number rises to nearly a quarter [5].
The land use, land-use change and forestry (LULUCF) sector has the potential to both emit and store
carbon. Citing the United Nations Framework Convention on Climate Change (UNFCCC) inventory data,
Frank et al. (2016) [6] estimate the European land-use based carbon sink to have been approximately
329 MtCO2 in 2012, that is, the sector absorbed more carbon than it emitted. This ability to store and
sequester carbon makes the land sector an important contributor to mitigating climate change.
The Paris Climate Agreement is committed to limiting global temperature rise to less than 2 °C relative
to pre-industrial levels (Art. 2) (UNFCCC, 2017). The LULUCF sector is a key component of the (Intended)
Nationally Determined Contributions ((I)NDCs) proposed by parties to the agreement. On a global scale,
the sector must be converted from a net anthropogenic source (1.3 ± 1.1 GtCO2eq/yr between 1990
and 2010) to a net sink (up to -1.1 ± 0.5 GtCO2eq/yr) by 2030 [7]. In relative terms, the sector must
provide approximately one quarter of total emissions reductions planned in the (I)NDCs [7]. This
importance of negative emissions is further emphasised in the Intergovernmental Panel on Climate
Change (IPCC) climate scenarios. Of the 116 scenarios in the IPCC AR5 database that are consistent with
a greater than 66% probability of keeping warming within 2°C, 87% apply negative emissions
technologies (NETs) in the second half of this century [8]. Bioenergy with carbon capture and storage
(BECCS) is currently one of the most commonly considered NETs, and of the abovementioned IPCC AR5
scenario, 104 utilise the largescale deployment of this technology [9].
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Box 1: Introducing the LUC4C Project
The EU funded LUC4C project (Land-use change: assessing the net climate forcing, and options for
climate change mitigation and adaptation), aims to advance our knowledge of the interactions of
climate change and land-use change. The scientists in LUC4C are working on the development of
complex earth system models, tools for providing an integrated assessment of the land-use change-
climate change interplay, and options for policy and other societal stakeholders. LUC4C seeks to
identify and understand the societal and environmental drivers of land-use and land-cover change, as
well as why they are relevant to climate change. The project evaluates different mitigation and
adaptation policies in view of how these affect important ecosystem processes, and whether
(unintended) conflict with other ecosystem services related to land-use and land-cover change arise
from the implementation of such policies.
In international policy frameworks, land-based mitigation is primarily the preserve of UN climate
frameworks such as the UNFCCC, Paris Agreement and Kyoto Protocol (KP) (Table 1 and Annex 1.1).
However, as will be exemplified in this synthesis, land-based mitigation has the potential to be both
synergistic with and counter to multiple non-climate, environment and sustainability conventions and
policies. At the EU level, emissions from the LULUCF sector are presently accounted for, but do not
contribute to achieving the EU emission reduction targets for 2020 (Table 2 and Annex 2.4). The EU has,
however, made plans to use the LULUCF sector to achieve its 2030 targets [10, 11] (see Issue 5a).
Land-based mitigation is cross-sectoral (forestry and agriculture), with influences on water, biodiversity,
and ecosystem services. Land-based mitigation strategies have the potential to interact with a diversity
of EU policies that do not focus on the climate or land sectors, for example the Water Framework
Directive, National Emissions Ceiling Directive (clean Air Policy Package) and Circular economy package.
We review new scientific knowledge on land-based options to mitigate climate change, the effect of
these options on land-use and land-cover change (LULCC) and their interplay with other environmental
concerns. Land-based mitigation presents policy-makers with competing demands and trade-offs, but
also possible co-benefits, and it is through this policy lens that we synthesise the state of the current
knowledge. The primary focus is on land-based mitigation through: (i) afforestation-reforestation (A/R)
and avoided deforestation (AD), and (ii) bioenergy with carbon capture and storage (BECCS). A third
important option, reduced greenhouse gas emissions (especially N2O and CH4) through agricultural
practices, was not within the remit of the LUC4C project, but is explored in a review of external literature
(Issue 5b). Additional negative emission technologies, such as the direct air capture of CO2, enhanced
mineral weathering (and storage), the modification of ocean CO2 uptake, aquatic biomass and biochar
storage [8, 9] are not explicitly explored here. While representing distinct processes, the terms land-use
(management/use) and land-cover (biophysical materials) change (LULCC) will be treated as
synonymous for the purpose of this review.
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Table 1: International climate policy relevant to the land sector and land-based mitigation [10, 11, 12]
Policy Land Sector Relevance
UNFCCC Reporting of LULUCF sector GHG emissions/sinks associated with land-use
conversions and management activities.
Kyoto Protocol (KP)
Kyoto Protocol 1 (KP1): 2008-2012
Kyoto Protocol 2 (KP2): 2013-2020
Parties must report emissions/sinks from afforestation, reforestation,
deforestation and forest management (mandatory in KP2). Parties can
optionally report on human-induced revegetation, grassland management
and cropland management.
Paris Climate Agreement Land-based mitigation to be included in countries’ NDCs.
REDD+ Scheme for reducing emissions from deforestation and forest degradation
in developing countries, through funding pledged by developed countries.
Parties have to develop a national strategy or action plan, national forest
monitoring system national forest reference emission level and/or forest
reference level, and safeguard information system.
Table 2: European climate policy relevant to the land sector and land-based mitigation [10, 13, 14, 15]
Policy Land Sector Relevance
2020 Climate and Energy Framework
(COM(2008) 30 final; [16])
Outlines three key targets: (i) to reduce GHG emissions by 20% (on 1990 levels),
(ii) to increase the share of renewable energy to 20%, and (iii) improve energy
efficiency by 20%. Renewable energy targets are one driver of future land use
(Box 2).
2030 Climate and Energy Framework
(COM(2014) 15 final; [17])
Outlines three key targets: (i) to reduce GHG emissions by 40% (on 1990 levels),
(ii) to increase the share of renewable energy to 27%, and (iii) improve energy
efficiency by 27%. Renewable energy targets are one driver of future land use
(Box 2).
Effort Sharing Decision (EU-ESD)
(406/2009/EC; [18])
The EU-ESD for 2013-2020 encompasses non-ETS sectors such as transport,
buildings, agriculture (non-CO2 only) and waste, but excludes CO2 emissions
from the LULUCF sector.
Effort Sharing Regulation (EU-ESR)
(COM(2016) 479 final; [19])
The proposed EU-ESR for 2021-2030 provides additional flexibilities enabling
all Member States to use removals from the LULUCF sector to offset EU-ESR
emissions, and for some Member States (based on eligibility criteria) to use
part of their EU-ETS to meet EU-ESR targets.
LULUCF Accounting Rules
(529/2013/EU; [20])
Requires Member States to prepare and maintain GHG accounts
(emissions/sequestration) for forests, cropland and grasslands. In the 2013-
2020 accounting period, only the reporting of forest activities (A/R, D and FM)
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is mandatory. Member States must report CM and DM emissions/removals
from 2015 onwards including an outline on the intended improvements in
these reporting systems; prior to their mandatory inclusion from 2021
onwards.
Renewable Energy Directive (EU-
RED),
(2009/28/EC; [21])
Requires that Member States use renewable sources to fulfil at least 20% of all
energy needs and ensure that at least 10% of transport fuels are derived from
renewable sources. by 2020. This directive has implications for biofuel use.
Also relevant to the land sector are the specified biofuel sustainability criteria.
Revised Renewable Energy Directive
(EU-REDII)
(2016/0382; [22])
This proposal sets an EU target of at least 27% renewable energy sources by
2030, and requires that the share of food-based biofuels is limited to 3.8% and
that the share of advanced biofuels increases to 3.6% by 2030.
Fuel Quality Directive (FQD)
(2009/30/EC; [23])
Mandates a carbon intensity reduction of transport fuels within the EU by 6%,
compared to the GHG emissions of conventional fossil-fuel based fuels.
2015 Biofuel Legislation Directive
(2015/1513; [24])
Amends current biofuel legislation (EU-RED, EU-FQD). Of relevance to the land
sector, this amendment (i) limits the share of biofuels and bioliquids derived
from cereal, starch-rich crops, sugars and oil crops and crops grown primarily
grown for energy purposes on agricultural land to no greater than 7% of
specified targets by 2020, and (ii) sets indicative targets for advanced biofuel
use by 2017, (iii) specifies and harmonises the list of biofuels which contribute
double to 2020 transport energy targets.
EU Forest strategy
(COM(2013) 659; [25, 26])
Provides a framework for forest related policies promoting a coherent and
holistic management approach. It identifies principles to strengthen forest
management whilst also ensuring forest protection and the maintenance of
ecosystem services.
Common Agricultural Policy (EU-
CAP) [27]
Considered central for steering farm level decisions in support of climate
protection in Europe. The new EU-CAP (2014-2020) is centred around three
long-term objectives: (i) viable food production, (ii) sustainable management
of natural resources and climate action, and (iii) balanced territorial
development. Pillar one supports the income of farmers via direct payments.
Included within this pillar are a set of three ‘greening measures’, namely, (i)
the maintenance of permanent grassland, (ii) ecological focus areas, and (iii)
crop diversification. Pillar two supports rural development and requires that
national and/or regional rural development programs (RDPs), be based upon
common EU priorities; which include the restoration of ecosystems and shifts
towards low carbon/climate resilient agricultural systems.
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Box 2: Defining land-based mitigation options
Bioenergy is a term referring to multiple types of biomass used for fuel, electricity or heat generation.
Liquid biofuels (most commonly bioethanol and biodiesel) can be used as a replacement for, or
additive to, conventional transport fuels. Bioethanol is obtained from the fermentation of sugar or
starch rich crops (sugarcane, sugar beet, wheat) [28]. Biodiesel is produced through the
transesterification of animal and vegetable fats (rapeseed, soybeans, palm oil, Jatropha) [28]. The EU,
as of 2011, was the largest producer and consumer of biodiesel [28].
Bioenergy feedstocks can be referred to as first (conventional) or second (advanced) generation.
Second generation bioenergy sources are derived from feedstocks that are not food crops. The only
food crops that can be used in second generation processes are those that have already fulfilled their
food purpose, that is, wastes or residues. Third and fourth generation biofuels are typically algal or
microbe based and do not require arable land for their production [29]. Currently an area of
experimental research, third and fourth generation biofuels are not included in this synthesis.
In future development scenarios, bioenergy use is typically deployed in parallel with carbon capture
and storage (CCS), referred to as bioenergy with carbon capture and storage (BECCS). The
combination of biomass and CCS is based on the principle that CO2 sequestered by the biomass during
its production is prevented from re-entering the atmosphere when that biomass is harvested/used.
Instead, the CO2 is captured, transported and deposited in long-term geological storage. The highest
potential for BECCS has been identified in the electricity sector [30].
In the context of the Kyoto Protocol (see Annex 1.1), afforestation is defined as the “direct human-
induced conversion of land that has not been forested for a period of at least 50 years to forest land
through planting, seeding and/or the human-induced promotion of natural seed sources” [31].
Reforestation has a similar Kyoto Protocol definition in that it is a consequence of human-induced
planting, seeding and/or natural seed source promotion. However, reforestation is defined to occur
on land “that was forested that has been converted to non-forested land2” [31]. Deforestation is “the
direct human-induced conversion of forested land to non-forested land” [31].
2 Within first commitment period (KP1) reforestation activities were limited to “reforestation occurring on those lands that did
not contain forest on 31 December 1989” [31].
15
Box 3: Projected bioenergy trends in Europe
In Europe, renewable energy sources are projected to increase in line with legislative targets.
Bioenergy is a key element in this renewable energy portfolio with projections estimating it will
account for 56% of renewable energy supply, in the EU-27, by 2020 [32]. It is expected that dedicated
energy crops will contribute most to this energy source with estimates of the resource increasing to
4.3-6.0 EJyr-1 in 2030, 3-56 EJyr-1 in 2050 and 22-34 EJyr-1 by 2100. This is in comparison to 2010 levels,
which are estimated to be between 0.8-2.0 EJyr-1 [32]. Agricultural residues, predominantly from
cereals (wheat, maize, barley and rye), are utilised as an alternate biomass source in Europe.
However, Bentsen and Felby (2012) [32] could identify no unanimous future trend in the continued
and/or expanding use of this resource. High levels of uncertainty were also associated with the
estimation of current and future forest biomass trends (Bentsen and Felby, 2012) [32].
Based on 23 National Renewable Energy Action Plans (NREAPs) defined under the EU-RED, Bowyer et
al. (2011) [33] estimates that, by 2020, a total of 26 MtOe (Million tonnes of oil equivalent) of biofuels,
72% biodiesel, will be used by the transport sector of these EU Member States. The same Member
States used approximately 9.4 MtOe in 2008. Over 92% of this projected biofuel increase is estimated
to come from conventional (first generation) feedstocks with a high reliance on imports; the 23
Member States anticipate importing 50% and 41% of bioethanol and biodiesel, respectively, in 2020
[33]. Despite the inclusion of incentives to promote second generation (or advanced) biofuel use
under the EU-RED, their increased adoption was not apparent in the NREAPs. NREAPs anticipated that
advanced biofuels would account for only 0.6% of total transport energy inputs in 2020. However,
increased variability was observed at the scale of the Member States [33].
16
Topic 1: Land-based mitigation competes for land and this has negative consequences 1a. Land-based mitigation increases food prices because of land
competition and the direct use of food crops as a bioenergy feedstock
Land-based mitigation, biodiversity conservation and agricultural production represent competing land-
use demands. For a given CO2 sequestration rate, land competition will, in part, be a function of the
land-use intensity of the mitigation strategy employed; the area of land required per CO2 equivalent
removed from the atmosphere. BECCS land-use intensities, while variable (1 - 1.7 ha t-1 Ceq yr-1 for forest
residuals to 0.1 - 0.4 ha t-1 Ceq yr-1 for bioenergy crops [8], are typically higher than for A/R [34] A median
BECCS deployment of 3.3 GtCyr-1, as typical of 2 °C consistent scenarios, would require 7-25% of
agricultural land as of 2000, if achieved with highly productive bioenergy crops [8]. A/R removals of 1.1
GtCyr-1 or 3.3 GtCyr-1 require 6-20% or 21-64% of agricultural land, respectively, and are largely
considered unrealistic [8]. None of the stated land requirements can be accommodated in current
agricultural areas identified as being abandoned or marginal, as they exceed these land categories by
two to four times [8].
Biofuel production competes with food production both directly, that is, food crops are diverted into
first generation biofuels, and indirectly, through resource (land, labour, inputs) competition [28] In 2011,
bioenergy feedstocks represented approximately 1.8% of total agricultural area, an expansion of 36%
since 19943 [35]. Evidence suggests that food prices, particularly during 2002 and 2007, were influenced
by increased biofuel production; biofuel expansion may have contributed up to 30% of the observed rise
in cereal prices [28].
Cereal based biofuel targets will significantly disrupt food/feed production; model projections conclude
that cereal price increases of 5%, 20% and 34% may be observed where first generation biofuels
constitute 2%, 4% and 6% of the transport fuel mix, respectively, by 2020 [36]. Price impacts are not
uniform, with a greater concentration of impacts in developing countries. NREAPs demonstrate that
bioenergy demand in the EU-27 will require an increase in biomass to 10.0 EJ by 2020. This requirement
includes approximately 0.1 EJ of EU grown food crops (first generation biofuels) and 0.5 EJ from
countries external to the EU-27 [32]. These results support the consensus that there is insufficient land
to meet biofuel feedstock demand within the EU [32, 37] and demonstrates the international reach of
EU policy on the use of foodstuffs as a renewable energy source.
Restrictions on agricultural expansion, as a consequence of A/R and AD policies, may have substantial
effects on food pricing [34, 38]. Kreidenweis et al. (2016) [34] demonstrate a 40% increase in global food
prices where AD mitigation policies are prioritised. In modelled scenarios, unrestricted A/R policies were
projected to result in a 400% food price increase up until 2100; a consequence of substantial
3 While expanding significantly, bioenergy represented less than one-tenth of the increase in agricultural land demand globally;
change is primarily driven by dietary preferences (see Issue 5c) (Alexander et al., 2015).
17
land/resource competition. Geographically targeting A/R policies within the tropics, the zone of highest
cooling effectiveness (see Issue 3), minimised food price impacts at a global, but not regional, scale.
Land-based mitigation is one factor in a complex set of drivers of food production, food pricing and
agricultural change. Future agricultural expansion will be a function of a complex interaction of
intensification dynamics, endogenous factors (population dynamics, consumption, wastage,
technologies, political decisions) and exogenous factors (international trade) [39, 40].
Climate change at lower levels and associated influences on crop productivity (CO2 fertilisation and crop
water efficiency), has been associated with reduced global demand for agricultural land (330 Mha in
2100) (Humpenoder et al., 2015) [41]. This agricultural reduction translated into a greater retention of
forests (62 Mha) and increased availability of land on which natural vegetation regrowth could be
permitted (268 Mha); outcomes that increase land-based carbon sequestration [41].
Technological developments and the intensification of food production could also reduce the arable
area required to meet demand and, consequently, provide additional space for land-based mitigation
measures. Yield increases, it is argued, are required in the presence of afforestation [34] and BECCS [42]
policies. Required bioenergy yield increases (of 1-1.38% yr-1 up until 2100) are lower than historic
change. However, it is unclear whether future yield increases in the agricultural sector will be applicable
to bioenergy crops; food production targets the edible parts as opposed to carbon accumulation pools
of the crop [42]. Increased research and development is required if projected yield requirements are to
be met in both food and energy crops [34, 42]. However, while increasing yields may be advantageous
from a land resource perspective, agricultural intensification must not be considered in isolation.
Caution must be exercised when such increases require substantial increases in agricultural inputs
(energy, fertiliser); inputs associated with GHG emissions and environmental impacts (see Issue 2a).
Yield increases may also be associated with rebound-effects, that is, increased consumption. Increasing
consumption is a benefit where it reduces hunger, but is less positive in the context of excessive
consumption and obesity [43].
Policy implications
Resource competition between food and bioenergy has led many countries to prohibit the use of first
generation (food-based) biofuels. Legislative approaches include the incentivising of non-food crops
(Molasses/Jatropha in India) or use of low-quality stockpiled food crops (corn in China) [44] for biofuel
production. In Europe, the 2015 RED directive (2015/1513 [23]) limits the share of food based biofuels
(7% of specified targets by 2020), sets indicative targets for and incentivises advanced (second
generation) biofuel use. European agricultural policy also has a direct influence on biofuel trends with
an increasing trend towards short rotation (1-10 year) energy crops (lignocellulose) due (in part) to
financial support under the CAP [32].
18
Multiple studies have demonstrated a causal link between future land-based mitigation policies and
food production/pricing [40-42, 44]. Stevanovic et al. (2017) [40] demonstrate that incentive-based
policies (carbon taxes, forest protection) have a greater impact on food prices than preference-based
approaches (dietary change, waste reduction) despite their similar mitigation potentials. Incentive-
based policies increase land and resource competition and thereby food production costs. Conversely,
preference-based mitigation increases land availability and concentrates agricultural production in the
most productive areas, lowering the costs [40]. Policies targeting consumer preferences, consumer
education programmes, and transparent markets should be considered in tandem with production or
supply-side mitigation approaches [40] (see Issue 5c). Incentive-driven policy, with an aim of food price
stabilisation, would benefit from some form of social safety programme in order to exclude food price
impacts on poorer communities [40, 41].
The food-energy nexus of land-based mitigation requires integrated policy to balance cross-sectoral
synergies and trade-offs. Land-based mitigation measures linked to improved food production (and
potentially food security), such as agroforestry, sustainable intensification of agricultural production and
integrated systems, should be explored as potential co-benefits [43].
1b. Land-based mitigation competes for land with ‘nature’ and the
maintenance of biodiversity
The magnitude of habitat loss, change and degradation associated with bioenergy driven LULCC, is a
function of multiple factors, including: (i) the type of LULCC conversion, for example the conversion of
natural ecosystems will have greater biodiversity impacts than a change in crop within currently
cultivated areas [44]; (ii) the spatial extent and pattern of this conversion [45]; (iii) the feedstock being
produced, as for example some feedstock species have been identified as invasive [28, 44]; and (iv)
changing hydrological regimes (see Issue 2a).
A/R cannot be assumed to be synergistic with biodiversity protection and/or enhancement. In Europe,
temperate forest extent has increased as a consequence of A/R policies and the successional
development of abandoned semi-natural grasslands (grasslands created/maintained by low-intensity
management). While above-ground carbon stocks will increase with the establishment of woody
vegetation, the implications for biodiversity and soil carbon are less clear; plant species richness has
been shown to decrease [46]. In European production forests, policies designed to support climate
change adaptation and mitigation are increasingly being identified as counterproductive to biodiversity
goals [47]. Mitigation strategies that reduce the native species composition/diversity of forests (e.g.
conversion to introduced conifers), the removal of important habitat structures (e.g. the removal of
19
coarse woody debris as logging residue), or change natural disturbance regimes (e.g. shortened rotation
times) have been found incompatible with national biodiversity policies, exemplified by Sweden [47].
Competition for land can be satisfied by fulfilling multiple demands at once (multi-functional land
systems) or the specialisation of landscapes in terms of the goods/services they provide [48]. Eitelberg
et al. (2016) [48] conclude that biodiversity conservation and/or carbon storage are likely to benefit
from the specialisation (and spatial segregation) of land systems, although results are region specific. In
Europe, the authors conclude that the protection of biodiversity is likely to increase cropland
intensification within a constrained and contracting area when compared to carbon storage or reference
scenarios [48]. The role of specialisation and intensification of land systems in a biodiversity context is
debated. Several authors propose that intensification is an inevitable step towards protecting
biodiversity [49, 50] while others argue that such specialisation does not account for the complexity of
species/ecosystem interactions [51, 52].
Policy implications
From a policy perspective, biodiversity protection is typically used as a criterion in sustainability
standards; see, for, example EU-RED [21] and EU-FQD [23]. Voluntary sustainability standards in a
biofuel context include the Roundtable on Sustainable Biofuels or those relating to a particular feedstock
(e.g., Roundtable on Sustainable Palm Oil). Such initiatives have a significant influence on the
development of the biofuels sector [28]. While such frameworks are advantageous in terms of their
simplicity, Gasparatos et al. (2011) [28] argue that a discrete list of sustainability criteria/targets excludes
the interrelations between, and dynamic nature of, criteria within social-ecological systems. It is in this
context that authors argue for the integration of biofuels within an ecosystem services narrative.
Adaptation and mitigation strategies inconsistent with biodiversity goals will, Felton et al. (2016) [47]
argue, continue to be used (and expanded) as long as they are perceived to (i) carry a reduced risk, (ii)
increase production capacities, or (iii) are associated with increased economic returns. In plantation
forests, for example, the removal of logging residues is risk free in terms of continued production and
produces an additional income [47]. In the context of forest management, feasible pathways that
through targeted regulations or policy incentives support continued forest production, climate
adaptation/mitigation strategies and biodiversity, can be identified [47]. Such pathways (i) prioritise and
incentivise the use of strategies consistent with both goals, (ii) adjust conservation practices to
compensate for mitigation strategies inconsistent with biodiversity goals, and (iii) ensure forest
management at a landscape scale encompasses a range of techniques, including those beneficial to
biodiversity [47].
The introduction of fast-growing, short rotation woody biofuel crops, as seen in Europe, in part due to
CAP incentives [32], has mixed biodiversity impacts; a function of the species introduced and
20
management practices implemented [47]. Short rotation times are inconsistent with biodiversity goals
that aim to increase the age-diversity of forests and emulate natural disturbance regimes [47]. Crop
rotation length, from an energy perspective, characterises the flexibility (regarding crop selection),
productivity, and growth pattern of the bioenergy resource [32]. Combining the characteristics of
different woody biofuel crops may therefore be beneficial to the development of a productive and
secure energy supply [32]. Increased crop diversity also resonates with biodiversity/sustainability goals
[47]. Such a synergy highlights the ability of policies to encompass energy security, land-based mitigation
and biodiversity.
Multiple European biodiversity policies specifically address the maintenance of semi-natural grasslands,
for example the Natura 2000 network and LIFE+ programme [46]. However, conflicting climate-driven
policies, which prioritise A/R within these regions, have the potential to further risk biodiversity loss
[46]. Conflicting policy objectives and outcomes are ineffective. An integrated, cross-sectoral policy
framework is fundamental in promoting synergies and balancing trade-offs.
1c. Land-based mitigation in one location can directly affect land use
elsewhere due to displacement effects, an example of indirect land-
use change
Indirect land use change (iLUC) is caused when existing arable land is used to grow, for example,
bioenergy crops, pushing food and feed production into new areas such as forests and grasslands [54].
iLUC is associated with substantial GHG emissions, as there are major initial emissions from converting
natural ecosystems into cropland through the release of locked up carbon in biomass [55] and soil [56].
In croplands, regular harvest undermines carbon storage over time [55]. When replacing natural
vegetation, it can take between 1 and 162 years to achieve GHG savings as compared to continued fossil
fuel use, depending on the LULCC conversion, crop, management intensity and geographical location;
GHG payback times tend to be longer in tropical regions [55]. iLUC derived GHG emissions have the
potential to undermine conventional biofuel technologies as a sustainable and renewable energy source
[33].
When GHG emissions from iLUC are included in life-cycle analyses (LCA) of biofuels, it can alter the
relative performance of crops [37]. Evidence suggests that bioethanol feedstocks such as cereals and
sugar perform better than biodiesel crops when iLUC is included in the analysis [37]. When accounting
for iLUC, the transport biofuel targets put forward by the EU-RED could lead to between 80.5% and
166.5% more GHG emissions than if the same fuel needs were met from fossil fuel sources.4 However,
the inclusion of iLUC in LCAs of biofuel production and use is variable, as these factors are often
associated with great uncertainty.
4 This estimate represents a mean of three emission estimates each based on different default emission values associated with
a land use conversion to arable lands. Results encompass 23 EU Member States [35].
21
The displaced production can move to distant geographical locations, and in the EU, iLUC will take place
outside the union’s borders almost in its entirety [33]. As deforestation inside the EU is negligible, the
concept of ‘embodied deforestation’ aims to link deforestation to consumption, by considering the life-
cycle of imported commodities [57]. The EU (EU-27) was the largest net global importer of embodied
deforestation in 2013, and particular concern has been highlighted with regard to the continued use and
intensification of palm oil derived biodiesel inside the European market, a principal commodity
associated with embodied deforestation. However, the introduction of sustainability standards (see
Table 3) is expected to reduce the overall iLUC of palm oil [37].
Farm-management intensification significantly influences soil organic carbon losses and the GHG
emissions of resource inputs (machinery, fertiliser). Models have associated cultivating biofuels under
high input (fertiliser and irrigation) systems has been with shortened GHG payback times in a majority
of locations due to the offset of GHG emissions by higher crop yields [55]. However, agricultural
intensification cannot be considered in isolation with potential trade-offs with environmental
sustainability criteria (see Issue 2a).
Displacement, also referred to as forest leakage, has been a key criticism of REDD+ [38]. Equally, the
exclusive protection of forests could increase (i) conversion pressures on non-forest, high-carbon,
ecosystems (shrubland/savannah), or (ii) result in the conversion of grassland and pasture (which
maintain vegetation cover and are associated with higher levels of soil carbon) [38]. Popp et al., (2014)
[38] estimate a sink (uptake) of 55Gt CO2 (until 2100) under a REDD+ type (forest-only) conservation
policy. This is in comparison to 191Gt CO2 under a more inclusive global, terrestrial carbon policy (a
universal carbon tax). Policies that are inclusive of all land cover types minimise forest and non-forest
leakage. However, in the absence of such an encompassing approach, there is a need to protect non-
forest ecosystems of high value for carbon storage and biodiversity [38].
Policy implications
It can be argued that iLUC, and associated GHG emissions, necessitate policies to be refocussed towards
alternate routes of delivering the 2020 EU-RED transport targets, for example, by using advanced
biofuels or promoting energy efficiencies within the sector [33]. To some extent, this change was
enacted in the 2015 EU-RED directive (2015/1513; [23]), which limits the share of food based biofuels
(7% of specified targets by 2020) and sets indicative targets for advanced (second-generation) biofuel
use. However, with a consensus that there is insufficient land to meet biofuel feedstock demand within
the EU [37], strong EU-RED sustainability criteria (and associated policies) will be required to prevent
iLUC.
Under current EU legislation, biomass used in the generation of electricity, heating or cooling is
considered carbon neutral in respect to emission targets, for example in the EU-ETS, as it assumes that
both direct and indirect LUC emissions will be captured in the land sector. This assumption of carbon-
neutrality underestimates total GHG emissions by failing to consider biomass production (and associated
22
iLUC), processing and transportation. Such exclusions can result in substantive emissions under-
reporting, for example, Murphy and McDonnell (2017) [58] demonstrate a 30% increase in EU-ETS
emissions reported at a single co-fired power station with the inclusion of biomass accounting.
In reviewing the INDCs for Malaysia, Indonesia and Ukraine, significant biomass sources within the Irish
energy sector, Murphy and McDonnell (2017) [58] reflect on how post-COP21 (Paris Agreement) pledges
might influence indirect (iLUC) GHG emissions. Of the INDCs analysed, only the Indonesian INDC
mentioned measures with the potential to reduce GHG emissions within exported biomass (in this
instance, a moratorium on the clearing of primary forests and prohibition of peatland conversion) [58].
If achieved, such measures were demonstrated to decrease indirect GHG emissions from Indonesian
palm kernel shell feedstocks by 32%. It is in this context that the Paris Agreement, and its associated
legislative instruments, has the potential to reduce existing carbon leakage [58].
In Europe, adjustments in trade policy, labelling schemes and voluntary certification schemes could
significantly decrease embodied emissions from European imports [37]. Specific policy options are: (i)
biofuel sustainability criteria are extended (by regulatory measures, market-based instruments and
voluntary agreements) to multiple agricultural crops (food, vegetable oils, feed crops, products); (ii) that
the forest law enforcement, governance and trade mechanism apply to commodities derived from
illegally (iLUC) created agricultural fields in addition to timber products; (iii) that a forest footprint is
compulsorily labelled on food products imported into the EU; and (iv) that sustainability criteria be
introduced on products associated with deforestation (for example, import tariffs) with the potential to
ban those linked to high levels of iLUC [37].
Promoting cross-sectoral, integrated and coherent policies is fundamental. For example, a strengthening
of the CAP could, Massey et al. (2015) [37] argue, promote the conversion of land removed from
agricultural production (that is, abandoned agricultural areas) to biofuel production. Such a policy has
the potential to decrease agricultural expansion, and/or iLUC, as a function of growth in the biofuel
sector.
Topic 2: Land-based mitigation has trade-offs with, but also co-benefits for, the provision of ecosystem services 2a. Land-based mitigation impacts on the ability of ‘nature’ to provide
other ecosystem services
Ecosystem services can be defined as the benefits people derive from ecosystems, and include
provisioning, regulating, cultural and supporting services [59]. LULCC has the potential to (i) exclude
ecosystem service provision, for example, due to the removal of natural ecosystems, and/or (ii) impair
the quality and quantity of a service provided by an ecosystem.
Biofuels influence both the quantity and quality of the water provisioning ecosystem service. The water
footprint of biofuels is larger than for alternative forms of energy, ranging from 1,400 to 20,000 litres of
23
water per litre of biofuel produced5, and aggregate water demand is expected to double by the end of
the century6. Increased water consumption must be framed within the context of a changing climate;
high temperatures necessitate more irrigation to maintain crop yields [62], and extensively irrigated
bioethanol production has the potential to deplete aquifers vulnerable to water shortages under future
climate scenarios [63]. The water demand of biofuels can be constrained with water protection policies,
but increasing land demand and yield technology investment are characteristics of scenarios with
stringent water policies [61, 64]. In the presence of extensive water protection policies (excluding
irrigated bioenergy production) the land required to meet the same biofuel target (300 EJ/yr) increases
substantially (+41%), typically at the expense of pasture areas and tropical forests [61].
The influence of land-based mitigation strategies on the hydrological cycle is not confined to bioenergy
feedstock production, with changes also attributed to A/R, forest management and deforestation [43].
Tree species selection can influence the water balance, for example, species roughness and species type
influence evapotranspiration (see Issue 3). Plantation forests, and the use of exotic species, can
negatively impact water availability within a region due to modified evapotranspiration regimes,
particularly in the context of a changing climate regime [65]. For example, species conversion from pine
to hardwood species was found to decrease streamflow by approximately 200 mmyr-1 [66].
The climate-regulating function of forests (precipitation, temperature) at local and regional scales
should be recognised in addition to their role in carbon storage, timber and non-timber service
production [65]. In an alternate perspective, proposed by Ellison et al. (2017) [65], the carbon-
sequestration potential of forests could be seen as a co-benefit of reforestation targeted to protect the
hydrological cycle and increase localised cooling.
Feedstock production requires fertiliser and agrochemical use; chemicals that can enter natural
ecosystems, in particular water bodies, and disrupt ecosystem functions (see exemplar studies citied in
[28] and [44]). Increasing land-use intensities, due to LULCC and/or changing management practices,
increase potential nitrogen losses [43]. Nitrogen losses to the atmosphere (NH3, NOx) and water bodies
(eutrophication) contribute to issues of both air and water quality. The removal of biomass from an
agricultural or natural ecosystem, for use as a bioenergy feedstock, removes nutrients from the site. This
soil nutrient depletion necessitates future fertiliser inputs, which links to GHG emissions and nitrogen
loss [8].
LULCC is currently a source of GHG emissions and hence impairs the ecosystem service of climate
regulation. The magnitude of these emissions is a function of the LULCC conversion and subsequent
crop/land management practices which influences the soil carbon balance, for example perennial
biofuel feedstocks (Miscanthus, sugar cane) sequester more soil carbon than annual species [32]. Biofuel
production emits N2O primarily through fertilisation of the crop during feedstock cultivation.
Uncertainty remains in both the quantification and inclusion of N2O emissions within biofuel LCA [28].
As with other plants, biofuel feedstocks emit volatile organic compounds, in particular isoprene, during
cultivation. Studies have demonstrated that such emissions may be greater over tree plantations (for
example, oil palm) than natural ecosystems. Other emissions from biofuel cultivation that can impact
5 These numbers represent 12 of the most common bioenergy crops [60]. 6 If bioenergy demand is expected to reach 300 EJ/yr [61].
24
air quality include particulate pollution resulting from land clearance, particularly where clearance is via
slash/burn methods [28].
Policy implications
Mitigation measures identified to reduce the impact of bioenergy on ecosystems and biodiversity
include the adoption of environmentally friendly production practices, the locating of bioenergy
production in marginal/degraded lands, and the design of multi-functional landscapes. Therefore, there
is a need for systematic land-use planning in achieving bioenergy production targets while also balancing
trade-offs [44]. Measures designed to minimise biofuel impacts could be promoted through both
regulatory instruments and market-based mechanisms such as certification.
Complexities within (i) the biofuel production chain, for example in terms of the feedstock or land
management approach, and (ii) biofuel markets which are driven by multiple incentives/drivers, make
sustainable policy-making challenging. Gasparatos et al. (2011) [28] contend that markets cannot
provide an institutional framework sufficiently able to communicate and value ecosystems and the
services they provide. There is, therefore, a need to establish a set of sustainable development standards
for biofuels grounded in the ecosystem service concept.
Integrated policy frameworks (explored further in Issue 6b) are fundamental to sustainable
environmental management. As exemplified above, policies that incentivise rain-fed bioenergy
production, while useful in protecting water resources, neglect the trade-off with land resources [63,
64]. Rather than universally promoting rain-fed bioenergy production, policies could promote
sustainable levels of water use as defined at a site-specific scale [63], for example by environmental
flows [61]. The incorporation of bioenergy in an integrated water (and land) management strategy
should minimise the land area of bioenergy crops by increasing yields under irrigation while protecting
freshwater from over-extraction and natural ecosystems from iLUC [61]. A further element of the policy
nexus is, however, identified, one of sustainable development; where water management strategies are
put in place, policies must consider the economic implications of increased land competition and their
resultant implications for, for example, food prices [64].
2b. Co-benefits between land-based mitigation and ecosystem service
provision are feasible
While discords between EU forest based adaptation/mitigation strategies and biodiversity policies has
been identified, synergies are clearly evident (Felton et al., 2016). Increased rotation times within
plantation forests can increase carbon storage while also increasing tree age-diversity, increasing coarse
woody debris and providing disturbance regimes more similar to natural conditions; all aspects
identified as important in forest biodiversity goals (Felton et al., 2016). Mixed species forests may be
25
more productive and resilient ecosystems than monocultures and often appear to be characterised by
improved drought resilience and tree growth [65].
Biofuel feedstocks can be used to purify wastewater, restore aquifers and improve marginal lands.
Jatropha, for example, has the potential to improve soil quality and control soil erosion [28]. Second
generation biofuel crops also have the potential to provide species habitats and/or enhance ecosystem
service provision, for example, through pollination or biocontrol [28]. However, the expansion of second
generation biofuels into non-cultivated areas would impact biodiversity, irrespective of these co-
benefits [44]. The biodiversity impacts of biofuel feedstock cultivation can be lowered where techniques
such as land sparing and sustainable farming approaches are employed, for example the exclusion of
extensive monocultures [28].
REDD+ programmes to reduce climate change emissions are designed to provide co-benefits through
forest conservation and sustainable forest management. The maintenance of intact forest ecosystems,
habitats and species diversity supports purification of the air/water, soil conservation and provides
benefits to the local community (health, spiritual, access to food, fibre) [67]. Upland reforestation, at a
catchment scale, has been shown to regulate water flows [65] and improve water quality [32]. Tree-
planting (A/R) can create wind-breaks that improve soil retention and support salinity remediation [43].
Synergies between A/R, AD and their associated co-benefits must be effectively designed and managed.
The scale of carbon-sequestration from afforested climate-resilient genotypes is dependent on the
ability of the new species to sequester carbon [68]. Equally, tree species selection can affect carbon
allocation to above- and below- ground stocks; soil carbon stocks are larger under hardwoods or
nitrogen-fixing tree species [39]. Woodland establishment on upland grasslands, while increasing above-
ground carbon storage, may under certain soil/tree species conditions result in soil carbon losses and/or
the removal of land from agricultural systems [69]. While woodland ecosystems as a whole (above-
ground biomass and soil carbon) have a greater carbon storage potential, silvo-pasture systems
(agroforestry), which integrate farming and forestry on the same area of land, have similar or higher soil
carbon stocks [68]. Silvo-pastoral systems, therefore, offer increased carbon stock benefits (in
comparison to pasture) without the exclusion of livestock and loss of agricultural land [69]. Silvio-
pastoral systems have also been shown to reduce wind erosion, promote soil fertility, control land
degradation/erosion and increase productivity while also co-benefiting biodiversity [43].
Protecting biodiversity can improve carbon stocks, contributing to land-based mitigation, where
degraded (high-carbon) ecosystems are restored and retained [70]. The protection, maintenance and
restoration of these ecosystems would also align with indicators and objectives in the EU 2020
biodiversity strategy [71]. Climate-smart conservation, the identification of regions with high
biodiversity and high soil carbon content, but low land price, is a cost-efficient approach to climate-
biodiversity management. Protected areas within the Natura 2000 network (EU-28 excluding Croatia
and Cyprus), although not designed for this function, capture a proportionally higher (10%) top soil
carbon than unprotected sites [70].
26
Harnessing synergies within multi-functional landscapes offers the potential to reduce resource (land,
water) competition. For example, the low-intensity management (and restoration) of semi-natural
habitats (meadows, dunes, grasslands, heaths and wetlands) in the Natura 2000 network could produce
harvestable bioenergy feedstock; estimated at 12.0 to 14.7 Tg (dry matter) annually [72] Biomass
production within these ecosystems has the potential to contribute to rural livelihoods by raising and
diversifying farm incomes and increase employment. As Natura 2000 sites do not overlap with food
production areas, the use of Natura 2000 bioenergy could offset iLUC; sites with bioenergy potential are
estimated to be between 1.2 and 2.8 Mha. The active management (in addition to delineation) of
protected areas in semi-natural ecosystems, characteristics of the Natura 2000 network, is essential in
preventing their degradation and preventing biodiversity loss [72]. Such management can also support
land-based mitigation policies.
Within agricultural dominant ecosystems, grassland restoration and protection, the conversion of arable
land to grassland, rewetting and expansions of agricultural peatlands (mires, bogs, fens) and reduced
peat use, have been identified as important LULCC conversions that can support multiple co-benefits,
including land-based mitigation [37]. Grazing can increase/decrease soil carbon stocks; as a function of
the grazing intensity. Crop residue management (removal or retention), tillage practices can influence
GHG emissions, and soil carbon [39].
Policy implications
There are few explicit references to, or analyses of, the within- and cross-sectoral impacts of climate
adaptation and mitigation measures; synergies and conflicts are under-represented [68]. The need for
cross-sectoral integration and the identification of co-benefits is acknowledged in current international
adaptation policies; the EU strategy on adaptation to climate change highlights the increasing
importance and recognition of ecosystem-based approaches. There is, however, a need to consider
within- and cross-sectoral interactions when implementing mitigation policies, to enhance positive
outcomes and avoid unintended consequences. The realisation of co-benefits and synergies will provide
opportunities for more efficient and cost-effective land-based mitigation (and climate adaptation)
strategies [68].
Different policies and policy mechanisms (e.g. uniform, discriminatory, and targeted sectors payments)
can be devised to support both carbon sequestration (land-based mitigation) and biodiversity co-
benefits. In a comparison of alternate policy scenarios, Bryan et al. (2015) [73] argue that discriminatory
(rather than uniform) payment schemes, which take advantage of land-use competition and seek
multiple (multi-functional) outcomes, are the most cost-effective with an ability to be tailored to achieve
a combination of carbon and biodiversity co-benefits. Uniform payments with land competition
between carbon sequestration and biodiversity goals achieved significant carbon sequestration, but
minimal biodiversity benefits [73]. Policy design and implementation is therefore fundamental in
ensuring policy mechanisms that balance both land-based mitigation and targeted co-benefits.
27
2c. There are trade-offs between energy generation and carbon stocks
for different land-based mitigation options
Land-based mitigation strategies, such as BECCS, A/R and AD, each demand land. Combining mitigation
strategies has the potential to increase overall carbon sequestration rates [42]. However, the strategies
may also compete for resources [6, 42]. Land-based mitigation strategies currently propose the use of
forests (i) as a source of woody biomass for bioenergy production, and (ii) to maximise carbon
sequestration via forest management techniques. Forests are therefore required to provide both
provisioning (bioenergy) and regulating (sequestration) ecosystem services. This multifaceted strategy
has the potential to result in trade-offs [74].
In Finland, current policies have been found to promote forest bioenergy more than, and at the
detriment of, carbon sequestration; indirectly policies are reducing the carbon sink [74]. Bioenergy
demand was found to be supported by specific national policy instruments as a direct consequence of
the assumption that forest biomass is “carbon neutral”. Conversely, no operationalised instruments
were found to govern carbon sequestration (the carbon sink) which was governed only by national
strategies and international frameworks (KP). Makkonen et al. (2015) [74] argue that forest bioenergy
as a provisioning service is a tangible ecosystem services more readily encompassed in a market than
other types of ecosystem services; characteristics that support direct/positive governance through
explicit instruments. This is in contrast to carbon sequestration, a regulating and less tangible ecosystem
service.
At a broader European scale, European policies (and emissions targets, see Table 2) could impact the
current LULUCF sector carbon sink; a function of increased woody biomass demand, changing forest
management and LULCC [6]. In a modelled comparison of the impacts of the proposed 40% GHG
reduction target and energy efficiency/renewable energy policy scenarios, Frank et al. (2016) [6]
conclude that the target will have a small (-1%) negative impact on the European LULUCF sector sink if
biomass demand is largely met through lignocellulosic (advanced biofuel) energy crops rather than
forest removals. Where forest harvest increases (in high biomass scenarios) the LULUCF sink is reduced
by a greater amount (-3%). The European LULUCF sector sink may therefore be vulnerable to policies
that result in increased woody biomass use.
Where ecosystems are both tangible and intangible, as in forests, which provide provisioning
(bioenergy) and regulating (sequestration) services, there is a need to ensure policies balance the need
for both types of services. Tangible ecosystem services are more rigorously governed (as they sit within
established markets) than less tangible ecosystem services, for which markets are emergent and
uncertain [74]. Policy design would benefit therefore from ensuring that synergies and trade-offs are
fully explored, and that the multiple ecosystem services and land-based mitigation strategies are
balanced [74].
28
Topic 3: Biophysical and biochemical cycles 3a. LULCC affects climate not only through greenhouse gas emissions
and uptake, but also through biophysical effects, especially at the
regional scale, but this is not accounted for in policy
Biophysical effects include the reflectance of sunlight from the Earth’s surface (albedo), cooling from
evapotranspiration and the absorbance of wind energy. Changes in vegetation cover alter the reflection
of sunlight (albedo); crops and pastures tend to be more reflective than darker forests, and this has a
cooling effect. However, forests have higher evapotranspiration rates than crops and pastures, which
cools the land surface as well as recycling water to fall as rain. Forests also absorb wind energy and this
has implications for local surface temperatures.
Between 2003 and 2012, variation in forest cover generated a mean biophysical warming equivalent to
approximately 18% of global biogeochemical warming caused by CO2 emissions from land-use change
over the same period [1]. The net effects of these processes play out differently in different parts of the
world. Satellite observations show that large-scale regional deforestation has a predominantly warming
effect in the tropics, and parts of the temperate zone, due to reduced evapotranspiration [75]. However,
deforestation causes cooling in the boreal regions, due to increased reflection of sunlight, especially in
winter and spring, but unlike the tropics, in boreal regions the agreement between measurements and
models is less clear [1, 75]. Uncertainties remain regarding the magnitude of the effect, especially for
seasonal variables (e.g., maximum summer temperatures), and for the effects on precipitation, but it is
now well established that the regional biophysical effects of land-cover change are substantial.
Furthermore, biophysical effects on local temperature are more rapid than warming arising from global
atmospheric CO2 levels. Thus, mitigation actions taken at the regional level would benefit from
considering the consequences of biophysical effects on local temperature as well as the impacts of GHG
emissions. There are major benefits in doing so, since accounting for the biophysical climate effects of
LULCC can support both mitigation and adaptation objectives and thus, make policy more effective.
Biogeochemical and biophysical effects vary as a function of the specific management action and/or
dominant land use/cover (Fehler! Verweisquelle konnte nicht gefunden werden.) [39]. Such
management-driven effects operate on a range of timescales; for example, a deforestation event is
associated with immediate emissions and biophysical changes, and, over longer timescales, soil organic
carbon losses [39].
29
Figure 1: The magnitude and extent of biogeochemical and biophysical effects as a function of different ecosystem management regimes [39].
Agricultural practices have the potential to modify surface biophysical properties. Grazing can change
albedo if, for example, plant biomass is reduced and an underlying light/dark soil exposed. Pasture
roughness may also have a small influence on turbulent fluxes. Crop harvest changes surface albedo
while subsequent residue management and/or tillage can affect surface roughness. Soil moisture
changes, due to crop harvest, tillage and/or irrigation, can change both evapotranspiration from, and
the albedo of, the surface [39].
Crops vary in their biophysical properties, in particular albedo (surface reflectance), which has a
dominant effect, in comparison to other biophysical factors, at a global scale; particularly in mid-latitude
temperate and high-latitude boreal regions [76]. The large-scale expansion of bioenergy crops, and
resultant LULCC, will influence albedo driven surface warming/cooling. Projected corn ethanol
expansion in the US has been associated with a net cooling effect (-1.8 g CO2eq per MJ of biofuel
produced), although regionally this varies between 2.0 g CO2eq per MJ (net warming) and -5.7 CO2eq
30
per MJ. Switchgrass expansion is associated with a significant warming effect, on average, 12.1 CO2eq
per MJ and a regional maximum of 21.0 g CO2eq per MJ. While the albedo effect of LULCC is relatively
small for corn, its inclusion in the life-cycle analysis of switchgrass reduces the relative performance of
this bioenergy source; from an 81% (without albedo) to 68% (with albedo) emissions reduction (when
compared to petroleum-derived gasoline) [58]. While albedo effects, resulting from bioenergy driven
LULCC, can be relatively large, they are spatially variable (heterogeneous) as a function of the LULCC
conversion, biofuel type and geographic region [76]. An improved understanding is required of the
biophysical effects of crop selections at local to regionals scales in support of spatial planning and policy
design [76].
Forests are fundamental in driving evapotranspiration and associated rainfall [65]. Forests also influence
rainfall intensity, by providing biological particles for moisture condensation, and have an important role
in moisture transport. Large-scale deforestation has been modelled as resulting in rainfall reductions of
up to 30% [65]. Such characteristics have important policy implications as they imply LULCC in one
location can have significant impacts in spatially disparate areas. Impacts occur over both short and long
distances, for example, long distance dependencies include the Congo and Ethiopian Highlands, or
Amazon and Argentinian Andes [65]. Such dependencies require a greater knowledge and
understanding of evapotranspiration/precipitation triggers, regional scale catchment management and
a greater recognition of forest-water-energy linkages. Integrated policies would benefit from being
placed in policy frameworks that link forests, water and energy at both local and continental scales [65].
Policy implications
Global policy frameworks do not, to date, consider biophysical effects, and hence opportunities exist for
policy to realise co-benefits. Although local biophysical climate impacts from LULCC are large, they tend
to be much smaller when aggregated globally and this has implications for global policy [75]. The process
of including land-based mitigation in the UNFCCC context has been a matter of long and complex
negotiations. Hence, the relatively small and currently uncertain global biophysical effects make it
difficult to justify efforts to include these effects in the complex negotiations of the UNFCCC process, at
present. However, it is now possible to evaluate the regional biophysical impacts (changes in local
temperature) of land cover transitions, following a tiered method similar to that of the IPCC to estimate
the effects of GHG emissions. The method applies three levels of increasing complexity, from Tier 1 (i.e.
default method and factors) to Tier 3 (i.e. country-specific methods and factors). The procedures
proposed for each tier method are transparent, taking into consideration the UNFCCC reporting
principles and could inform mitigation efforts at regional or national scales to realise the co-benefits of
accounting for biophysical effects. Biophysical effects are important for regional scale ecosystem,
biodiversity and water-cycle management (see 0).
Policies that support avoided deforestation, especially in tropical regions, have especially large co-
benefits. Avoided deforestation mitigates global climate change by reducing CO2 emissions. It also
affects the local climate in a positive way by maintaining cooler surface temperatures through
31
biophysical effects. Future climate change will also increase vegetation growth through the effect of
atmospheric CO2 fertilisation and this will further enhance the biophysical cooling effects of forests.
Thus, avoided deforestation as a land-based mitigation option benefits from positive effects on both the
regional and global climate systems.
Topic 4: The longevity and timing of land-based mitiga-tion strategies 4a. The relative contribution of different land-based mitigation
options changes through time
AD provides immediate mitigation gains, whereas afforestation-reforestation can take-up carbon
immediately, but with relatively small annual gains due to the slow rate of forest growth, especially as
forests approach maturity. BECCS enables land to be used indefinitely for carbon mitigation, but barriers
and technology/policy time lags mean large-scale implementation is not likely until around the middle
of the century.
AD requires minimal technology-based input and provides immediate mitigation gains. Implementation
costs vary as a function of both the legislative requirements to protect the forest, and lost opportunity
costs (that is, the benefits which would have been gained by the LULCC) [77]. In contrast, BECCS
deployment is slower, with large-scale implementation unlikely until the middle of the century (see Issue
6d); a consequence of uptake barriers (social, technological and political) and time-lags (see Issue 4b).
As a land-based mitigation option, A/R offers a high carbon sequestration potential at moderate cost
(Kreidenweis et al., 2016) and, as a consequence, becomes cost-effective at a relatively low carbon price
[42]. This contrasts with BECCS, which only becomes cost-effective when the carbon price increases
significantly. As such, land-based mitigation strategies are sensitive to GHG emission taxes and their
trajectories [42], and different strategies become cost-efficient at different points in time, resulting in
different mitigation potentials over a longer time-frame.
In contrast to BECCS, A/R (and soil carbon increases) is associated with CO2 saturation over time [78].
This saturating behaviour of A/R is a consequence of declining carbon removal rates as forests reach
maturity and the land available for A/R becomes constrained [42]. Proposals have been made to mitigate
this effect, for example, Zeng et al. (2013) [79] suggest a cyclical, carbon sequestration strategy in which
A/R trees are harvested and buried, preventing decomposition. Such an approach mitigates (or delays)
the saturating behaviour of mature forests, as a single area can be replanted multiple times.
Alternatively, A/R forest may become a BECCS feedstock where the profitability of carbon removal is
greater under BECCS than A/R [42].
32
As a direct result of increasing woodland harvest and forest aging, the EU LULUCF sink is projected, under
current policy/wood product consumption levels, to decline from -303 MtCO2 in 2010 to -126 MtCO2 in
2030 in managed forests [6]. Compensating factors for this decline are projected A/R, decreasing
deforestation and the long-term storage of carbon in harvested wood products (see Issue 5a).
Consequently, the resultant decrease in the LULUCF carbon sink is estimated to be approximately 18%
(-235 MtCO2 in 2010 to -192 MtCO2 in 2030) [6].
4b. Time lags in the science-policy-society exchange process influence
the effectiveness of land-based mitigation policy
Lags occur in developing science knowledge, exchanging this knowledge with decision makers, policy
implementation, policy uptake (e.g. farmers changing to bioenergy land use), the response of the earth
system to new measures (e.g. the slow rate of tree growth or the take up of carbon dioxide and heat by
land and oceans) and the feedback of policy needs driving the generation of new science knowledge.
Longer-term emission reduction pathways are bounded by multiple factors, including technology
lifetimes, the inertia of change in societal/consumer preferences, policy formation and technology
deployment rates [80]. These processes, and their interaction, influence the effectiveness of land-based
mitigation pathways.
Technology development is further modified by the rate of adoption. The transport sector, and in
particular the vehicle fleet, is typically characterised by a higher technological turn-over rate than, for
example, other industrial sectors, and is, as a consequence, quicker to respond to carbon pricing or
policy mechanisms [81]. It is in this context that von Stechow et al. (2016) [81] conclude that a higher
fuel diversity by 2050 is achievable within this sector, even in the presence of delayed (rather than
optimal) 2°C mitigation pathways.
Financial constraints may impair land-based mitigation uptake. Delayed income returns, a need to
secure start-up finance and project transaction costs constrain the uptake of A/R projects [82]. As forests
require a significant amount of time to become established and yield net carbon sequestration
outcomes, income revenues are delayed; a factor identified as a major constraint to the KP’s Clean
Development Mechanism (CDM) project uptake (see Annex 1.1) [82]. A/R income returns are slower
than both alternate renewable energy programmes and/or land-use types (agriculture). The profitability
of forest-based carbon sequestration is dependent upon multiple factors including carbon prices, on-
going project monitoring/validation costs, and the ability of owners to access additional (agroforestry)
income. High carbon prices, in comparison to timber prices, provide an economic incentive for forest
maintenance. However, where carbon prices fall and timber or other land-use activities become more
profitable, there is an increased risk of deforestation [82]. This is an issue of project permanence (see
Issue 4c).
33
It has traditionally been assumed that land-use systems decisions are based on economically rational
behaviour; an approach which neglects both individual and social behaviours [83, 84]. Increasingly,
evidence shows that mitigation (and adaptation) responses depend on a wider range of social and
political factors both at the scale of the individual and institutions [83]. Societal behaviour has the
potential to influence both the rate and pattern of future LULCC [84].
The spatial diffusion of agricultural practices and technologies is an important behavioural factor driving
patterns of LULCC [85] and, in the context of land-based mitigation, policy effectiveness. According to
the “diffusion of innovation” theory (Rogers, 2003 [86] cited in Niles et al., 2015 [87]), diffusion is a
function of the technology/innovation, social context and communication channels through which the
innovation spreads. The heterogeneity of both the innovation and agricultural space limit universal
predictors of behavioural change in agriculture [87].
Despite financial incentives in the UK bioenergy sector, the area of perennial energy crops is limited
(around 17,000 ha for short rotation coppice willow and miscanthus in 2009) [88] with continued slow
uptake (an area of 1305 ha received establishment grants between 2007 and 2011) [89]. Based on
modelled behaviours and historical analogues (UK oilseed-rape adoption), it can be shown that the
complete adoption of bioenergy crops, to the level identified/proposed for the UK in 2020, could take
20 years or more; even in the presence of favourable policies and subsidies [85]. This has important
implications for policy effectiveness and implies that even with favourable conditions, time lags exist in
the uptake of crops or technologies [85]. Time-lags are evident across land-based mitigation strategies.
Woodland expansion, also incentivised in multiple grant schemes in the UK, is currently insufficient to
meet A/R targets [90]. Farmers and other landholders are critically important in achieving A/R targets.
However, a survey of Scottish farmers demonstrated that those not intending to undertake future A/R
projects outnumbered those who would consider/were intending to expand woodland by more than six
to one [90].
Land-based mitigation depends, through financial incentives, on the support of farmers and landholders;
actors who are influenced by more than economic factors. While economic factors were deemed
important for the uptake of biofuel, in north-east Scotland, non-economic factors were also shown to
be important to respondents; 23% were willing to sacrifice a percentage of their revenue if it meant a
reduction in GHG emissions [91]. Research is increasingly looking to characterise “farmer-types”, a key
set of farmer characteristics that may identify willingness to engage in biofuel [91] and A/R [90] policy
initiatives. As an example, farmers who reported an intent to implement A/R policies were typically
already operating forestry (or another type of diversification), involved in environmental schemes, more
educated, employing higher numbers of people and ‘new’ to farming [90]. Such insights enable
integrated policy formation; for example, support for new entrants to farming, farm diversification and
environmental scheme participation may indirectly encourage A/R [90].
Farmer attitudes and preferences do not exist in isolation, for example, while farmer-types characterise
attitudes to biofuel adoption, uptake is also a function of farming enterprise [91]. In Scotland, for
34
example, cereal farmers were willing to adopt bioenergy crops at a significantly lower incentive level
than other farmers (£210 ha-1 under a subsidy/tax incentive, compared to, for example, £670 for mixed
farmers). Equally, dairy farmers did not adopt biofuels under any financial (subsidy and tax) mechanism.
Policy adoption is a complex interaction of decision-making influences [91].
Policy implications
In characterising decision-making behaviour, it is possible to identify policy mechanisms/instruments
that may influence adoption rates. In the UK, for example, A/R policy could be refocused towards
forestry being an activity that complements and benefits farming, possibly through the avocation of
smaller areas of woodland [90]. Equally, the establishment of strong markets and/or government
supported demand (in the form of subsidies), as a means of ensuring income security and stability, have
been identified as important factors in the establishment of bioenergy crops [91].
Caution is, however, required, when characterising decision making behaviours, as a disparity exists
between intended and actual adoption practices; a disparity that makes policies based on intended
actions ineffective [87]. Drivers of intended and actual adoption of climate change mitigation practices
are different; a belief in climate change was found to be correlated with intentions, but not actions
among New Zealand farmers. Only perceived capacity and self-efficacy were proven to be important
predictors of both a farmers intentions and actions. In this context, policies that build capacity and
support behaviour change could be important in designing and promoting the adoption of mitigation
policies [87].
Different rates of adoption, as a function of farmer-type or enterprise, can lead to inequality within the
farming sector. Farmers who adopt early at a low subsidy/incentive/carbon tax price will gain more, in
terms of their differential income, than those who adopt later, but at a higher price. Increasing financial
incentives, which aim to increase adoption, over compensate those who have already adopted [91].
Such issues highlight a need for equitable policy design.
4c. The success of A/R and AD as mitigation options depends on
continued monitoring and management of forest stands
The inclusion of land use in mitigation policy and reporting frameworks is complex. For forests,
challenges to the policy design stem from the issues of: (i) additionality, a need to show that the land-
use change, for example AD, is additional to “business-as-usual” and separate from non-anthropogenic
effects; (ii) leakage, the displacement of land-use activities to other areas, for example, AD in a given
region could result in iLUC (see Issue 1c); (iii) the heterogeneous nature in which forests sequester
carbon as a function of climate, hydrology and species; (iv) uncertainty in growth conditions (and
therefore sequestration rates) due to variable weather; and (v) permanence, the need to ensure
continued carbon storage [92].
35
Forest based trading in carbon markets, while increasing from 2.1 MtCO2eq in 2005 to 32.7 MtCO2eq in
2013 [129], is only a small proportion (approximately 0.5%) of carbon emissions traded [93]. Forest
trading can be categorised under (a) voluntary schemes (e.g. REDD+), or (b) compliance markets (e.g.
Australia and California), with the average 2013 price of each being USD 4.8/tonne CO2eq and USD
9.7/tonne CO2eq, respectively. However, prices are variable [94].
Forest based trading has, to date, predominantly used project-by-project differentiated carbon
payments [92]. This differentiated payment is at the exclusion of a uniform price per unit (forest area or
management practice). While differentiated systems do not have the efficiency losses associated with
the uniform price approach, transaction costs do increase, that is, the cost of monitoring and verification
on a project-by-project basis. Transaction costs for REDD+ projects, for example, can be considerable,
amounting to up to 25% of the total cost [92].
A further policy mechanism to handle issues of heterogeneity and uncertainty in forest carbon markets
is the inclusion of a risk discount. This approach is exemplified by the New Zealand Emissions Trading
Scheme in which two tonnes of forest carbon are required to offset a single tonne of CO2eq emissions
[92]. In addition to accounting for uncertainty/heterogeneity in the rates of carbon sequestration, this
discount ratio can also encompass the uncertainty associated with non-additionality and/or
permanence.
Standards are a common approach utilised to manage and test for non-additionality; the Verified Carbon
Standard was identified as the most common voluntary standard, accounting for 46% of transaction
volumes in 2013 [94]. Compliance market equivalents include, for example, the Carbon Farming
Initiative of Australia [92].
Two main credit-based approaches, used in practice, have been identified to alleviate issues of
permanence. The first approach is to buffer credits; credits set aside as an insurance against future
carbon reversal (typically within the contract period) whereby liability is transferred to the seller [92].
The second approach differentiates between temporary and permanent credits, an approach utilised by
the CDM. In addition to credit-based approaches, schemes, such as REDD+, also utilise performance
payments to incentivise due diligence in forest management/permanence [92].
Forests are heterogeneous in their carbon sequestration rate leading to uncertainty in forest-based
carbon pricing mechanisms. As A/R mitigation projects are typically based on long rotations, climate
change (temperature, precipitation, CO2 concentration) could both impact future forest carbon stocks
[41]; an additional source of uncertainty. Negative impacts (declining forest carbon sequestration rates)
have the potential to offset carbon sequestration benefits in future time-steps. However, stopping an
A/R project, and converting the land to an alternate use, is prohibitive; the standing forest has a CO2
emissions cost. It is in this context, that A/R projects introduce a path-dependent land-use policy; a path-
dependency which prohibits abrupt land-use change [41].
36
4d. The success of avoided deforestation and reforestation depends
on the changing risks from disturbances, such as climate extremes,
wild fires and pest and diseases, which affect forest permanence
The land-based mitigation strategies of A/R and AD are based on the sequestration of carbon into
standing forest biomass. This sequestration is, however, reversible if natural systems are disturbed; a
process to which they are inherently vulnerable [78]. It is in this context that land-based mitigation
strategies should incorporate risk management, that is, a consideration of those events/factors that may
reverse carbon storage; factors such as wildfires, extreme weather events, pests and diseases [9].
Natural disturbances affect the carbon dynamics and age-structures of terrestrial ecosystems. Such
impacts are largely carbon neutral (over the longer-term) under natural disturbance regimes; a
consequence of ecosystem recovery [95]. Increased climate extremes (heat, waves, storms and
droughts) have the potential to increase the risk of natural disturbance events. A warmer climate could
increase insect outbreaks and/or shift the range of pest species, increase the risks of fires and/or wind
throw. As a consequence, climate change could impact/impair mitigation strategies that are dependent
on the maintenance of long-term terrestrial carbon sinks.
European carbon stocks are significantly influenced by natural disturbances, particularly storms, and the
management strategies (e.g. salvage logging) applied following the event [96]. To date, storms have had
a greater (5-10 times) impact on forest carbon stocks than fire.
Strategies can be employed in an attempt to mitigate natural disturbance threats and ensure robust
land-based mitigation policies. Forest structural changes, such as the promotion of single-species
(conifer) over mixed-species stands, have been shown to increase the susceptibility of forests to natural
disturbances [97]. Tree species selection and appropriate mixes can be used to prevent the spread of
diseases and/or pests, which are factors that can cause tree mortality and a significant release of carbon
[39].
Policy implications
Altered natural disturbance (hurricane, fire, droughts) regimes have critical implications for the
efficiency and pace of societal/technological change required within mitigation pathways [95]. Higher
disturbance regimes lower strategy efficiencies and require larger-scale investments in adaptive
infrastructure and technological investment/deployment. Technology has to be deployed sooner when
it is more expensive and less efficient. Mitigating climate change (to a 3.7 Wm-2 level) under increasing
disturbance regimes is both more demanding and costly; up to 2.5 times more costly in the case of
doubled disturbance rates [95]. Conversely, in the presence of decreasing disturbance rates, the costs
of climate change mitigation strategies are potentially reduced. Understanding future disturbance
regimes is therefore key in understanding and formulating policies for future climate mitigation
pathways.
37
Risks to forest survival jeopardise the permanence of A/R projects, an important consideration in terms
of their associated policy and funding mechanisms. Where policy mechanisms issue temporary credits,
for example, for forest sequestration, natural disturbances pose a risk to the financial income of a given
project; when forests are lost, so too are their associated income. Such risks, and the threat they pose
in terms of income losses, could act as a disincentive to engagement in the scheme [82].
Topic 5: Landscape management and alternate land-use futures 5a. Forest management is increasingly recognised as an important
contributor to land sector carbon fluxes in both science and policy
communities
Forest Management (FM), in the context of the UNFCCC and KP, is defined as “a system of practices for
stewardship and use of forest land aimed at fulfilling relevant ecological (including biological diversity),
economic and social functions of the forest in a sustainable manner” [31]. Also associated with FM,
within UNFCCC and KP, is the Harvested Wood Products (HWP). The HWP constitutes wood and paper
products harvested from forests as part of their management [31].
When considering all activities (FM, A/R, D and HWP), EU forests (i) correspond to approximately 8% of
total EU GHG emissions (without LULUCF), and (ii) are a net sink equal to, on average, -409 MtCO2/yr
between 2000 and 2012. FM accounts for approximately 90% of this sink, with A/R representing the
remaining 10%. The sink is primarily associated with the living biomass carbon pool (80%) with the
remaining proportion in the dead organic matter pool (10%) and HWP pool (10%) [96].
Forest management can influence both the biogeochemical properties of a forest, that is, the sink can
increase or decrease, and its biophysical structure, also a determinant of local climate (see Issue 3). In a
reconstruction of historic European land cover and land use, Naudts et al. (2016) [98] argue that recent
FM in the EU has not resulted in a cooler climate.
Despite the current strength of EU forests as a carbon sink [96], Naudts et al. (2016) [98] conclude that
EU forests are associated with a carbon debt of 3.1 PgC when compared to carbon stocks at the start of
the time series, that is, the year 1750. This carbon debt is a consequence of deforestation, species
conversion and wood extraction from previously unmanaged forests. An associated increase in summer
boundary-layer temperatures, of 0.12K, is primarily associated with a conversion to coniferous (as
opposed to broadleaf) species. A/R had a more influential effect on the radiative imbalance simulated
(0.12 Wm-2) at the top of the atmosphere. A net increase in forest area (by 10%) and conversion (of 85%)
of forests to managed forestry has not resulted in a net CO2 removal from the atmosphere (due to wood
extraction). Furthermore, a change to coniferous species has had a warming effect.
38
Based on the composition of the current forest sink (90% of which is attributed to FM [Pilli et al., 2016])
and influence of forest biophysical structure on climate change mitigation [98], land-based mitigation
strategies should, it is argued, consider both A/R and FM. Under the second KP period, (i) the reporting
of FM is mandatory, through a forest management reference level (FMRL), (ii) FM accounting must
include carbon stock change in the HWP, and (iii) natural disturbance emissions may be excluded, under
certain circumstances, for accounting purposes [96]. The Paris Agreement leaves it to States to
determine how they intend to mitigate their emissions in this sector while reaffirming the importance
of incentivising, as appropriate, any non-carbon benefits.
The EU is considering integrating emissions from land use in the European 2030 climate and energy
strategy (COM(2016) 479 final; [10]) by allowing Member States to (i) use excess LULUCF sector
removals (above the no-debit limit) within EU-ERS accounting, and (ii) meet their “no-debit”
commitment with excess EU-ERS allocations (COM(2016) 479 final; [10]).
To date (and under future proposals), LULUCF-generated carbon credits cannot be traded within the EU-
ETS. Equally, CDM forest-based credits, in contrast to other CDM credits, cannot be traded in the EU-
ETS. This exclusion of the LULUCF sector from current EU policy, in combination with substantive
UNFCCC and Kyoto-based limitations on domestic forest-based carbon credits, (i) isolates the potential
impact of the forestry sector on the EU climate policy framework [99], (ii) leaves a significant land-based
mitigation source untapped [99], and (iii) could lead to forests becoming a biofuel feedstock, that is, a
source of carbon emissions rather than a sink [100].
The inclusion of LULUCF within the EU-ETS has been identified as difficult due to issues of uncertainty
(in carbon sequestration rates and their inter-annual variability), required administrative apparatus and
disparities in the annual compliance cycles of the EU-ETS and longer-term cycles of national forest
inventories [99] (see Issue 4c for a further discussion of these policy issues). Furthermore, concerns have
been raised as to whether the inclusion of LULUCF could weaken the EU-ETS by reducing pressure on
high-emitting industries to reduce fossil fuel use [99].
Forest and FM represent a cost-effective approach to achieving emissions targets. Vass and Elofsson
(2016) [100] assess the cost-effectiveness of forest-based carbon sequestration (at the expense of
bioenergy and the harvesting of forest products) in terms of achieving the EU 2050 carbon reduction
target. In particular, the authors consider whether abatement costs could be reduced by recognising
additional sequestration by standing forest biomass within EU climate policy. Results point to cost-
efficiency in using forest carbon sequestration as a mitigation approach; the inclusion of forest carbon-
sequestration is associated with a 23% reduction in the cost of achieving EU carbon targets [100].
FM accounting, which is mandatory under KP2, is based on a FMRL, that is, a quantified amount against
which performance is compared in the reporting period [13]. The FMRL precludes the definition of a
single base (or reference) year. Proponents of the FMRL argue that it provides a flexible approach able
to accommodate diverse forest sectors and forest age structures in mandatory KP2 reporting. Equally,
the FMRL, as a function of its definition, has the potential to incentivise mitigation actions within the
39
forestry sector. Concerns, in respect to the FMRL, focus on its definition, difference in approach to other
sectors and that it allows real emissions (under the FMRL) to remain unaccounted for. The FRML is
applied, within KP2, in combination with a credit cap, that is, emission removals from FM are capped at
3.5% of 1990 baseline emissions without LULUCF [11].
In a European context, Ellison et al. (2014) [99] criticise the FMRL and cap as, the authors argue, the cap
is (i) preferential to high per capita emitters at the baseline, (ii) unrelated to forest cover/forest potential
growth, and (iii) does not include the adjustments possible under KP1 (3% of 1990 emissions or 15% of
net removals in forests). The authors argue that the FRML and cap system leads to inequalities across
EU Member States and imbalances in the carbon accounting system. Imbalances which could result in
future forest growth not being mobilised and harvest being encouraged [99].
Ellison et al. (2014) [99] provide a discussion on the relationship between the FMRL and set of incentives
it creates. Based on this analysis, it is evident that a conflict exists between the incentives of EU Members
(Parties) and landowners; while Parties face KP2 incentives these are not transferred to landowners.
This, the authors argue, could result in landowners following potentially contradictory incentives, for
example, the harvesting of forests (and their replacement with biofuels). Ellison et al. (2014) [99] argue
that this would, to some extent, be mitigated by the full inclusion of LULUCF within EU climate policy
frameworks. However, this stance remains contested.
Pilli et al. (2016) [95] estimate that in five of the 26 EU Member States analysed (Cyprus and Malta are
excluded from the EU-28) the HWP pool contributes greater than 20% of the current total FM carbon
sink. The HWP sink, which in the future can be maintained or further increased (by increasing harvest
rates or the proportion of harvest held in long-lived products), represents an important component of
land-based mitigation. Policies and mitigation strategies should, however, consider the HWP with
caution. In four of the EU countries analysed, Pilli et al. (2016) [95] find that the current HWP is an
emissions source (due to industrial roundwood harvest). Careful management of the HWP, and its
balance between being an emissions source or sink, is therefore required. This is particularly pertinent
where the HWP is influenced by other policies. Ellison et al. (2014) [99] demonstrate, for example, that
in Sweden, the average HWP carbon pool represents approximately 14% of removals. The authors do,
however, argue that the KP2 cap, which applies equally to FM removals and HWP, marginalises almost
the entire HWP carbon pool.
EU policy is criticised for a lack of centrally coordinated forest management, in particular, national
forests plans (NFP) development by Member States [37]. Such decentralised and uncoordinated policy
development could pose a threat in terms of conflicting forest practices and regional climatic effects.
This decentralisation is further emphasised by the high proportion (over 50%) of privately owned and
managed forests. Fostering communication between forest owners and NFPs should be an important
element of future EU Forest Strategy updates [37].
40
5b. Livestock and cropping systems are significant contributors to
global emissions of non-CO2 GHGs. The management of these systems
has the potential to reduce GHG emissions
Land-based mitigation in the form of reducing GHG emissions from agricultural systems was not within
the remit of the LUC4C project, but is explored in this section through a review of external literature.
Agricultural GHG emissions are predominantly from non-CO2 sources; methane (CH4), nitrous oxide
(N2O), nitric oxide (NO) and ammonia (NH3). In 2014, agriculture contributed approximately 10% of
Europe’s non-CO2 GHG emissions; this is in comparison to 0.13% of CO2 emissions (EU-28 and ISL) [11].
In the EU, nitrous oxide accounts for 58% of non-CO2 agricultural emissions, while methane represents
42% [11].
Methane emissions, associated with livestock (enteric fermentation and manure management), are
strongly determined by ruminant feedstock, in particular, the fraction of grass biomass [39]. Nitrogen
fertilisers, both organic (derived from manure/slurry) or mineral (synthetic), are a significant source of
nitrous oxide, nitric oxide and ammonia emissions. Nitrate emission rates, from agricultural fertilisation,
are a function of the application rate, fertiliser type, crop type and environmental conditions [39].
However, a fertilised cropland will typically emit two to three times more nitrogen than it would under
non-fertilised conditions, or three to four times more N2O for grasslands [39]. EU non-CO2 agricultural
emissions can be attributed to three primary sources: enteric fermentation (42%), agricultural soil
management (38%) and manure management (15.4%) [11].
GHG emissions derived from agriculture are highly variable across EU Member States, as national
emissions in 2013 ranged from 3% (in Malta) to 32% [11]. This variability is a consequence of
heterogeneous farming systems, management practices and biogeographic characteristics across the
region. Agricultural producers are equally as heterogeneous. Grosjean et al. (2016) [101] demonstrate
that 38% of emissions within the sector are generated by the top 10% of emitters, and the top 20% of
emitters generate 58% of sectoral emissions, indicating the uneven distribution of emissions across the
sector. In terms of absolute emissions, three countries (France, Germany and the UK) contribute
approximately 44% of total EU-28 agricultural emissions [11].
Agricultural non-CO2 emissions fell by 21% (113 MtCO2eq) between 1990 and 2014, a decline largely
attributable to a reduction in ruminant livestock numbers [11]. With a stabilisation/slowing in the
reduction of livestock numbers, this declining emissions trend has slowed over time; a 16% decline
observed between 1990 and 2000 fell to 8% between 2001 and 2012 [11].
Climate change mitigation in the agricultural sector can be achieved by emissions reductions (CO2 and
non-CO2), increased carbon sequestration and contribution to the renewable energy sector. Such
mitigation actions must, however, be balanced with other aspects of sustainable development (food
production, air/water quality, biodiversity) and placed in the context of global agricultural systems (for
a discussion on iLUC, see 1c). Of major concern to the agricultural sector is the potential for mitigation
41
to impair production. It is in this context that mitigation has tended to focus on those strategies with
the least production impacts or those that are economically beneficial to the sector, for example, by
increasing efficiency (e.g. reduced/targeted fertiliser application) [11].
Tubiello et al. (2015) [5] argue that (i) an increasing GHG emissions trend from the agricultural sector
(ca 12% globally between 1990 and 2010) in contrast to a declining emissions trend from forestry and
other land-use activities, (ii) the dominance of agriculture (11%) within agriculture, forestry and other
land use emissions (FOLU; 10%), and (iii) high proportion of deforestation driven by agricultural
expansion, indicates an increasing need for emissions reductions within the sector.
Policy implications
Mitigation in the agricultural sector remains a challenge to climate negotiations. Agriculture has been
identified as a priority sector for the UNFCCC; however, discussions on the contribution and potential
inclusion of the sector remain (following COP17 in 2011) an agenda item for the UNFCCC Subsidiary Body
for Scientific and Technical Advice [11]. In the absence of this COP scale integration, agriculture is
included under a set of different UNFCCC sections (Nairobi Work Programme, Cancun Adaptation
framework, finance mechanism, technology mechanism). This disaggregated approach has led to
concerns that synergies and trade-offs cannot be addressed [11].
The European 2050 Roadmap (COM (2011) 112 final; [102]) sets a (non-binding) reduction target for
non-CO2 agricultural emissions of between 42% and 49% (relative to 1990) by 2050. Non-CO2 agricultural
emissions are included in the EU-ESD (406/2009/EC; [18)]. Agriculture could, therefore, represent an
important sector in terms of EU Member States achieving their EU-ESD targets. For example, 43% of EU-
ESD emissions in Ireland are attributable to the agricultural sector. Consequently, Ireland may need to
apply significant mitigation in this sector, overachieve in other EU-ESD sectors or make use of other
flexibility mechanisms to meet its current EU-ESD emission reduction target of 20% [11]. Agriculture is
not included in the EU-ETS; however, emissions from, for example, fertiliser production facilities
(indirectly linked to agriculture) would be. CO2 emissions from CM and GM are covered by both the EU
2013 Land Use Decision (mandatory; (529/2013/EU; [20]) and KP2 accounting (voluntary). In summary,
beyond monitoring and reporting requirements, there are no legislative targets for the agricultural
sector within the current EU or international policy frameworks.
Hart et al. (2017) [11] demonstrate that, in their UNFCCC/KP reporting, 26 EU Member States identify
agricultural soils as key sources of nitrous oxide emissions, and 20 to 22 Member States identify manure
management and enteric fermentation as a significant source of methane. However, in spite of this clear
link between the agricultural sector and GHG emissions, Hart et al. (2017) [11] argue that policies to
address these sources are disproportionally lacking. The authors conclude that 13 Member States will
be unable to meet their respective 2020 and 2030 EU-ESD targets without modifications to agricultural
emissions policies/measures or consideration of flexibility mechanisms. However, Member States
expect EU-ESD targets to be met within current policy structures, as agriculture is rarely mentioned in
42
reported Policies and Measures, the mechanism through which Member States express how they expect
to meet emission reduction targets [11].
Impact assessments accompanying the 2016 EU-ERS proposal (COM(2016) 479 final; [19]) indicate that
little change would be required in the agricultural sector to meet specified targets, contrasting the 2030
climate change package assessment, which indicated that agricultural emissions would need to be
reduced by approximately 28%. This, however, is a consequence of differing assumptions [11].
Matthews (2016) [103] highlights eight EU Member States7 Where significant additional efforts might be
required within the agricultural sector. Foreseen agricultural action in the identified countries is, Hart et
al. (2017) [11] conclude, highly variable. For example, while France set specific agricultural sector
reductions, none are stipulated for the sector in Ireland.
Agricultural practices in the EU are significantly influenced by the CAP. Climate action is, following the
2013 CAP reform, included in the three core CAP objectives and central to both CAP Pillars [27]. Hart et
al. (2017) [11] have identified the following CAP key instruments as having the potential to support
climate change mitigation:
Standard for Good Agricultural and Environmental Condition (GAEC): Implemented by farmers
receiving payments under both CAP Pillars, these standards have the potential to protect soil organic
carbon (e.g. by the establishment of watercourse buffer strips or minimum soil cover standard),
reduce the risk of wetland losses (e.g. through improved irrigation practices), and promote carbon
sequestration (e.g. by the retention of woody landscape features).
Pillar 1 Greening Payments: Greening payments support agricultural practices that are beneficial to
both the climate and environment. Greening obligations include: crop diversification, grassland
maintenance and Ecological Focus Areas (EFAs); land-use types designed to safeguard and improve
biodiversity, which must be included within the farmed area. Climate mitigation can be realised
where permanent grasslands are retained and ploughing prohibited. While EFAs are defined to
protect diversity, climate mitigation co-benefits can be identified, for example, carbon sequestration
(woodlands, agro-forestry) or soil carbon protection.
Farm Advisory System: It is compulsory that this advisory service, in each Member State, cover all
aspects of the CAP. However, there is the potential for Member States to also offer information on
a broader set of topics, including farm-based climate mitigation measures.
Rural Development Programmes (RDPs): All RDPs must address at least four of the six EU level
priorities for rural development in addition to a set of cross-cutting objectives. Priority five, which
promotes resource efficiency and a shift towards a low carbon and climate resilient economy, is
particularly relevant to climate change mitigation. The authors identify several RDP measures with
a high potential for climate change mitigation and adaptation.
Several CAP measures have climate mitigation benefits, although issues with these have been
highlighted; Massey et al. (2015) [37], in a synthesis of policy relevant literature, conclude that (i) GAECs
is not an explicit condition of greening payments, (ii) organic soils are not effectively managed or
7 Austria, Belgium, Denmark, France, Germany, Ireland, Luxembourg and The Netherlands [103].
43
unmanaged outside Natura 2000 areas, (iii) grassland protection is not consistent, (iv) sanction systems
are not binding, and (v) LULCC in support of climate mitigation is not supported.
Within the CAP, there is considerable flexibility in terms of the implementation of these measures. As a
consequence, the realisation of climate benefits is highly dependent on both Member States and the
farming community. Hart et al. (2017) [11] provide a full review of the CAP measures in terms of their
reach, scope (area of potential implementation) and potential climate benefits. In conclusion, they argue
that the implementation of CAP instruments, in support of climate mitigation, is highly variable across
Member States and, in many instances, minimal. For example, (i) the RDP budget allocations for climate
priorities (at 8%) are lower than other priorities, and (ii) targets are set low; only 1.8% of EU agricultural
land is projected to be under RDP contracts contributing to carbon sequestration by 2020. In the context
of the three mandatory “greening” elements of the reformed CAP, Westhoek et al. (2012) [104] conclude
that they will have limited emission reduction impacts (2% between 2010 and 2020), and emissions may
even increase due to leakage to regions outside of the EU.
The EU 2050 Roadmap allocates approximately 500 kg CO2eq per capita per year to agricultural nitrous
oxide and methane emissions, and Bryngelsson et al. (2016) [105] compare four broad strategies for
achieving such a target: (i) agricultural productivity/efficiency gains, (ii) technology options for emissions
reduction, (iii) changing demand (diets), and (iv) food waste reductions. Using Sweden as a European
proxy, they conclude that even under optimistic technological change, current and future projected
dietary preferences cannot achieve EU agricultural emissions targets; emissions remain at about 600-
900 kg CO2eq per capita per year. Dietary change, in particular reduced ruminant based diets, is,
therefore, identified as an important mitigation strategy. Smaller, yet significant, technology based
emissions reductions for methane and nitrous oxide sources can be achieved [105]. However, to meet
EU non-CO2 targets with a high degree of certainty, a 50% or greater reduction in ruminant meat
consumption is required. While ruminant based meat sources must be reduced to meet emissions
targets, the authors find that meat consumption need not be curtailed/significantly reduced if diets are
primarily based on non-ruminant sources [105]. High ruminant meat and dairy based diets, Bryngelsson
et al. (2016) [105] conclude, are incompatible with the EU non-CO2 targets unless accompanied by
significant technological advancements (animal productivity, manure-management). Food waste was
found, even under optimistic conditions, to have a lower impact on future emissions pathways; halving
current waste production in Sweden reduced emissions by only an additional 1% to 3%. It is in this
context that authors have argued for policy interventions in favour of guiding diets towards lower non-
CO2 GHG emissions pathways [105] (see Issue 5c).
Energy use is a dominant cause of CO2 emissions from agricultural production. As such, the de-
carbonisation of the energy supply has the potential to result in significant emissions reductions [105].
Equally, net CO2 emissions from CM and GM activities are greater than emissions from FM in some EU
Member States8, indicating that the inclusion of these in agricultural emissions targets could significantly
impact future management practices [99].
8 Emissions from CM and GM exceed emissions from FM in The Netherlands, Denmark and Germany [99].
44
Technical and political challenges of achieving cost-efficient GHG emissions in the agricultural sector,
and a lack of clear emissions targets, have led to little large-scale action on climate mitigation in this
sector [11]. Current policy discourses also contrast, for example, the EU’s current subsidisation of beef
and mutton production with recommendations of shifting demand towards lower GHG emission diets
[105]. The CAP direct payments and coupled support for the livestock sector continue to favour high
yield areas, which has significant implications for GHG emissions in the livestock sector [11].
Massey et al. (2015) [37] argue that the significant potential of the CAP to support climate mitigation
remains untapped, for example grassland protection and/or climate-friendly land conversion (reed-
grass cultivation, rewetting). Hart et al. (2015) [11] contend that the currently proposed EU-ESR and
integration of LULUCF into EU emission policies will have limited impact on the agricultural sector in
terms of incentivising emissions reductions. However, in the absence of targets, short-term adaptation
measures are increasingly being adopted in the sector; a trend not observed for mitigation measures.
The reform of the CAP post 2020 has been identified by several authors as an opportunity to strengthen
climate action in the agricultural sector [11, 37]. Hart et al., (2017) [11] identify six CAP priorities post
2020 in the context of climate mitigation: (i) the protection of carbon-rich soils, (ii) the management of
soil organic matter (minimising losses and increasing stores), (iii) measures to encourage efficient
management of nutrients, (iv) inclusion of climate mitigation within the Farm Advisory System, (v) the
inclusion of climate mitigation within the CAPs monitoring and evaluation framework, and (vi) a review
and change in the orientation of CAP towards emission-neutral production. Massey et al. (2015) [37]
further add, (vii) a review of incentivised LULCC conversions, to increase the protection of grassland and
promote climate mitigation strategies, (viii) favourable economic and financial conditions for climate
actions (modified sanctions and incentivised biofuels, rewetting) and (ix) increased capacity building and
communication.
The EU-ETS does not currently cover the agricultural emissions. However, some authors highlight the
cost-efficient mitigation potential of the agricultural sector using such market-based instruments [101].
However, this remains a contested stance, as the potential scope of the EU-ETS is disputed, and other
mechanisms might be better suited in the LULUCF sector. Grosjean et al. (2016) [101] identify three key
obstacles or barriers to a market-based agricultural mitigation policy; transaction costs, leakage risks
and potential distributional impacts on farmers/consumers.
45
5c. There are a number of alternative scenarios of land-based
mitigation that are rarely explored since most future scenarios are
based on a limited set of conventional options such as agricultural
management, A/R and BECCS
In addition to population dynamics and economic growth, future land-use change trajectories depend
on socio-economic conditions such as, for agricultural systems, technological change and investment,
dietary patterns and demand, trade, and interactions with other competing land use sectors [106]. The
IPCC shared socio-economic pathways (SSPs), Popp et al. (2017) [106] argue, provide a diverse set of
socio-economic conditions and potential land-use futures. Under ambitious mitigation scenarios, for
example in SSP4, cropland is projected to expand by up to 1413 Mha (until in 2100), an expansion
associated with bioenergy, whereas in SSP5, pasture decreases by up to 940 Mha [106]. Such results
demonstrate the importance of socio-economic context in future land-use pathways.
Future scenarios, and those of land-based mitigation implementation, tend to follow conventional
development pathways. However, a number of “less-conventional” pathways, which have the potential
to profoundly affect land use and land-based emissions, can be envisaged.
A comparison of the relative importance of dietary change towards animal based products and
bioenergy expansion in driving agricultural land-use change since 1994 are compared, the rates of
change (35.7 Mha/year for diet versus 3.2 Mha/year for bioenergy) suggest that changing diets have
had an impact eleven times greater than bioenergy [35]. Food production and the influence dietary
change has on demand are, therefore, significant drivers of LULCC. Furthermore, in considering food
production demand, Alexander et al., (2016) [107] show that the types of commodities consumed (diet)
is more important than the quantity (per-capita) consumption in determining agricultural area
requirements. In 2011, 635% of land per capita required to sustain an Indian diet was required to sustain
a typical US diet. The US diet had a 65% greater (or 99% greater in terms of protein) energy content; a
significant disparity compared to the differing land requirements [107]. This difference is attributable to
the commodities consumed, with 30% versus 9% of energy derived from animal products in the US and
India, respectively [107].
Diet and dietary trends have the potential, therefore, to significantly influence the extent of agricultural
land required to fulfil demand. Alexander et al. (2016) [107] conclude that the global adoption of an
Indian diet would require 55% less agricultural land to fulfil demand than what is currently the case.
Conversely, the global adoption of a diet typical of the United States would require six times current
agricultural area. The global adoption of two contrasting (but not extreme) diets could therefore lead to
a magnitude of change greater than doubling or halving current agricultural land areas. The authors note
that while a global shift to a diet resembling a typical US diet is unlikely in the shorter term, this is the
prevailing trend in terms of recent consumption patterns. This is a consequence of, among other factors,
46
increasing per capita income in developing countries (China, Brazil), rural-urban migration and a greater
consumption of animal products. However, given current yields and production systems, a global
adoption of a typical US diet would prove impossible, as it would require 98 per cent of all land. An
Indian diet, while more desirable from an environmental perspective, implies a shift in consumption
away from both current trends and those typically observed with an increasing per capita income [107].
Limiting agricultural land requirements has direct and positive climate change mitigation impacts, as it
minimises LULCC and reduces the competition with land-based mitigation strategies for land resources.
Equally, reduced agricultural production demand may, indirectly, reduce production based emissions
(fertiliser, mechanisation, manure management).
Erb et al. (2016) [108] explore the food production option space, in terms of supply-side (cropland
intensification, cropland expansion into grazing areas, livestock system efficiency gains) and demand-
side (dietary changes) measures, within the constraints of a hypothetical zero-deforestation boundary
constraint. Approximately two-thirds of the 500 scenario combinations considered by the authors were
deemed feasible or probably feasible, that is, food demand could be met within the zero-deforestation
constraint; deforestation is not a requirement to meet food demand in 2050 [108]. The authors conclude
that human diets are more important than yield (crop or livestock intensity) and cropland expansion in
determining the feasible option space; vegan and low-livestock diet variants showed the highest
proportion of feasible scenarios [108]. The authors also identify scenario combinations where Western
diets could be adopted if associated with increasing yields and the expansion of cropland into current
grazing areas. Equally, low-yield (e.g. organic) production is feasible in a zero-deforestation scenario if
paired with changing diets (to vegetarian/vegan) and/or cropland expansion.
Animal based production is associated with high levels of water consumption, GHG emissions (see Issue
5b) and land-use change [107]. Relative to their land-use footprint, constituted of pasture lands (68% of
all agricultural lands in 2011) and arable feeds (33% of croplands in 2011), animal products contribute a
disproportionally low amount of energy (18%) and protein (39%) to human diets [35]. Diets based on
low levels of meat intake are associated with lower land requirements (such as the Indian diet of
Alexander et al., 2015 [35]) and more “plausible” alternatives with the food production option space of
[108]. Reduced meat consumption has also been linked to multiple health benefits, particularly where
consumption is currently above recommended levels [43]. While associated with a larger GHG emissions
footprint, livestock, Erb et al. (2016) [108] argue, do provide non-food resources (wool, draught power)
and are able to increase society’s food resource by converting marginal land into a protein source.
Changing food preferences and demand may be possible through either behaviour change (portion
sizes) and/or economic approaches (e.g. sugar taxes versus fruit/vegetable subsides). Authors argue,
however, that taxation and subsidies alone are unlikely to be sufficient to change diets without policies
targeted across society [109]. The trade-offs in yield, expansion and diet explored by Erb et al. (2016)
[108] also have an important trade-off with national food security or self-sufficiency. The option space
47
identified, the authors argue, would be substantially reduced in the presence of socio-economic trade-
barriers (subsidy systems, tariffs, regulations).
Topic 6: Multiple policy goals and co-benefits 6a. There are potential synergies between land-based mitigation and
adaptation that would allow co-benefits to be achieved
Linkages exist between the mitigation of, and adaptation to, climate change. When land-based
mitigation in the form of avoided deforestation retains primary forests, emissions from deforestation
are prevented and, as a co-benefit, biodiversity and ecosystem service provision are maintained. These
are both characteristics of a resilient ecosystem. Conversely, secondary forest, and particularly
monocultures, can reduce biodiversity, thereby diminishing the adaptive capacity of the ecosystem to
respond to climate change [43]. Furthermore, planting trees in urban areas (see Figure 1) has mitigation
benefits through the capacity for carbon storage, as well as adaptation benefits through cooling effects,
and reducing surface water run-off and flooding [110]. Adaptive measures are also synergistic with
mitigation; the adaptive management of fire-regimes, for example, may ensure the permanence of
carbon stocks [43].
Changing food consumption patterns, for example through low-meat diets, reducing over-eating and
waste, and eating alternative protein sources (see 5c), reduces the land area needed for food
production, thereby providing opportunities for using this land for land-based mitigation [43, 111, 112].
This also builds resilience to climate change, since the additional availability of land could offset the
negative impact of climate change on crop yields and thus food production.
These examples demonstrate potential opportunities, but there is limited scientific evidence to support
the understanding of the full extent of mitigation-adaptation synergies and trade-offs, constituting a
major knowledge gap.
48
Figure 1: Known and potential relationships between mitigation and adaptation measures and their impacts on biodiversity. Urban tree planning is identified as a win-win-win situation, being beneficial for biodiversity, mitigation and adaptation [110].
Policy implications
The co-benefits of integrating adaptation and mitigation to realise sustainable development goals have
been recognised both within the (i) IPCC 5th Assessment Report, through the definition of climate-
resilient pathways, and (ii) the Paris Agreement, for example, Articles 4 (NDCs) and 5 (forest sector). The
Paris Agreement also highlights the two-way nature of this synergy (Article 7) [11].
The integration of mitigation and adaptation objectives, governance structures and policy-making
processes is essential in ensuring coherent land sector policies [113]. Full integration requires that the
policy intends, from the outset, to contribute to both outcomes; synergies are exploited and trade-offs
minimised. It does not require the merger of institutions, actions or policies, only that the objectives are
considered simultaneously. Di Gregorio et al. (2017) [113] define adaptation/mitigation policy
integration across four dimensions (Table 3): (i) Internal – the integration of mitigation and adaptation,
that is, benefits are observed for both aims within the policy sector (i.e. forestry); (ii) External – the
consideration and exploitation of synergies between the climate change aims (mitigation or adaptation)
and non-climate objectives; (iii) Vertical – integration within a single policy sector (i.e. forestry); and (iv)
49
Horizontal – integration across policy sectors (i.e. forestry and agriculture). A policy environment based
on all four of these dimensions is essential in facilitating climate resilient land-use pathways [113].
Table 3: The four dimensions of climate policy integration as proposed by [113].
6b. Positive social benefits can be derived from well-grounded land-
based mitigation strategies, but, conversely, land-based mitigation
can have negative social impacts if poorly planned
Land tenure and land rights are important considerations in the expansion and deployment of land-
based mitigation. Insecure land tenure, vague property rights, and uncertain government policies and
carbon market prices can make carbon sequestration policies ineffective; seller-uncertainty prevents
participation in the market [92]. Weak land tenure rights can lead to the exclusion of smallholders and
indigenous communities from the market [28, 43]. Land tenure issues can also be linked to the large-
scale leasing of land by foreign governments or firms for, in part, feedstock production, so-called ‘land-
grabbing’ [37]. Such leases remove land from smallholder/local food production systems with products
often being exported [28], and raise concerns about sustainable development and equity [43] Land rents
and food pricing are important sustainable development concerns for land-based mitigation (see Issue
1a). One factor potentially driving land prices/rents upwards is phantom production; the purchasing of
land, and its removal from the land resource without any subsequent development, market exchanges
or expected environmental/social benefits [114]
50
Land-based mitigation can impair ecosystem service provisioning (see Issue 2a). Impaired water
availability, water quality, air quality and increased agrochemical use have all been linked to issues of
social well-being and human health impacts. Exclusion from, or access to, degraded ecosystem services
may disproportionally impact poorer members of society, leading to inequalities. Cultural services, a set
of less tangible ecosystem services, may be impacted upon by LULCC changing people’s perception and
use of a landscape [28].
The development of bioenergy markets supports rural development and job creation; evidence for this
can be found in both developing and developed countries [28]. The EC biofuel impact assessment [115]
estimates that, in 2020, employment related to biofuels in the EU could be approximately 400,000 jobs
distributed across the supply chain; agriculture, logistics and at processing/production facilities. Farmer
income, within bioenergy markets, is dependent upon the feedstock production model, for example,
plantations, contract farming, independent smallholder farming or subsistence farming [114]. A
conversion to cash crops (feedstocks) by rural populations may not represent a net income gain as cash
crop prices are highly vulnerable to world markets. Equally, biofuel production has the potential to lock
both labour and land resources into inflexible contracts in which risks are borne by the smallholder [114].
Biofuel production favours economies of scale [28]. In such circumstances, additional benefits may not
be seen by smallholders who cannot compete in large-scale markets. Smallholders may be further
excluded by the risk/uncertainty typically associated with land-based mitigation markets [28].
Land-based mitigation measures can promote equality when implemented within a transparent,
participatory policy system that distributes socio-economic, economic and technological benefits,
shares the burden of implementation and ensures equal access to decision-making. In the absence of
such mechanisms, land-based mitigation has been associated with both inter- and intra-generational
inequality [43]. Multiple authors have, summarised in [28], demonstrated the potential gender
imbalance of impacts arising from biofuel expansion; women being more likely to face the negative
socio-economic and environmental impacts.
Land-based mitigation policies can engender inequalities between regions and/or states. The inclusion
of forest sequestration as an abatement method in EU policies, could lower the cost of achieving 2020
abatement targets by between 53% and 85% [116]. However, the inclusion of forest based sequestration
(particularly under certain conditions), when assessed against six equality measures, leads to greater
disparities between EU Member States in terms of their burden sharing. Such negative impacts on
equality may require the revision of targets, allocations or allowances to support those disadvantaged
[116].
Small scale biofuel initiatives can, through access to energy, poverty reduction and rural capacity
development, improve human well-being [28]. Biofuel production by rural communities can also
produce co-benefits, for example, Riera and Swinnen (2016) [117] conclude that castor biofuel contract
farming in Ethiopia was correlated with food production improvements, perhaps due to improved
fertiliser access, improved soil quality (from the biofuel production) and increased technical assistance
51
from the project agents. Biofuels offer countries an opportunity to establish both national and local scale
security in their energy supply [28]. Land-based mitigation measures offer the potential to clarify and
harmonise land rights/tenure in the presence of regulating institutions and enforcement [43].
Policy implications
Sustainable development and positive social outcomes can result from land-based mitigation [28, 43,
114]. Buck (2016) [114] argues that markets are unable to deliver outcomes that are beneficial to broad
sectors of society and that, in this context, strong policies, support and guidance are needed.
The take-up of A/R projects within the CDM has historically been low (0.2% of total activity within the
CDM) [82]. Implemented projects are characterised by initial funding support, the provision of design
and implementation technical expertise by large organisations, secured property rights and cooperation
of local communities, including the redirection of CDM benefits back to local people. Such insights can
support effective policy design. Thomas et al. (2010) [82] argue that such insights should, for example,
inform the reform of the CDM, namely (i) to increase the flexibility of institutional mechanisms to reflect
the varying conditions of Member States and notion that LULUCF measures are context-specific, (ii) to
build technical and organisational capacity within Member States, and (iii) simplify methodological and
documentation procedures, (iv) strengthen the economic environment in which the policy operates so
as to provide long-term price signals and lower the risk, and (iv) broaden the definition of both forests
and projects applicable within the mechanism. Successful projects, it is argued, will engage local people
and be mediated by trusted institutions. Furthermore, the environmental, social and economic goals of
projects have an increased chance of being achieved where the technical capacity is developed locally,
within local populations [82]. As it stands, the nature of a replacement for the CDM under the Paris
Agreement is uncertain and undecided.
6c. Co-benefits are possible across a set of policy targets if policy is
developed systematically across sectors rather than in isolation
Numerous socio-economic issues are linked to climate change. However, despite the recognition that
these issues are not mutually exclusive, strategies are frequently discussed and implemented
independently; synergies are not often considered within policy [118]. Co-benefits have the potential to
maximise efficiency while achieving the objectives of both land-based mitigation and other international
and national sustainability agendas [43].
Climate policies have the potential to interact and overlap with non-climate and sustainable
development policies/goals. Sustainable development is fundamental to the Paris Agreement, and
avoiding dangerous climate change is a Sustainable Development Goal (SDG 13) [14, 81]. Land-based
mitigation has the potential to interact with multiple SDGs related to poverty, hunger, health and well-
being (SDGs 1, 2 and 3), water and land (SDGs 6, 14 and 15), and energy (SDG 7). As von Stechow et al.
52
(2016) [81] state, “sustainable development hinges on the successful implementation of non-climate
policies that complement or support climate policies in other dimensions” (pp. 2).
The ability of society to achieve the SDGs, and the risk of the goals not being met, varies as a function of
the pathways deployed to achieve the 2°C target [81]. Meeting the 2°C target can significantly influence
the risk associated with meeting other SDGs and sustainable energy objectives. Reduced fossil fuel and
energy demand, in the short-term, is associated with a range of longer-term non-climate co-benefits,
such as air quality, energy security, water use, reduced pollution, health benefits (associated with
declining fuel poverty and improved mobility patterns) and local employment; such co-benefits are
reduced in the presence of weak short-term climate policies, similar to the low short-term ambition
pathways of the INDCs [81]. Adding technological constraints can minimise the risks associated with
particular energy technologies. However, other risk levels may be exacerbated, particularly those risks
associated with socio-economic SDGs. For example, while limiting the global deployment of biofuels
reduces environmental risks, risks of not meeting socio-economic SDGs increase. In some pathways, the
climate SDG itself is threatened; the 2°C target is not achieved. The achievement of low energy growth,
that is, energy efficiency improvements across sectors, and a societal change away from current high-
energy lifestyles, is, von Stechow et al. (2016) [81] argue, essential in increasing synergies and managing
trade-offs between climate and non-climate SDGs. This interaction between climate and non-climate
SDGs, and their associated policies, supports the integration of climate and SDG agendas into a single,
integrated monitoring framework [81].
Ecosystem-based management approaches are increasingly recognised as fundamental to climate
change adaptation and mitigation; functional ecosystems are vital in supporting and increasing climate
change resilience and minimising risk at multiple spatial scales [28, 118, 119]. The link between
ecosystem-based mitigation9 and biodiversity has been established in multiple decisions (X/33; XII/20)
of the Convention on Biological Diversity (CBD) [119]. Parties were invited to implement an ecosystem-
based approach to mitigation through, for example, the conservation, sustainable management and
restoration of natural forests, grasslands, peatlands, mangroves, seagrass beds and salt marshes
(Decision X/33). Aichi Target 15 of the CBD is directly relevant to climate change mitigation and
adaptation in that it calls on Parties to enhance ecosystem resilience and the contribution of biodiversity
to carbon stocks [119]. Ecosystem-based mitigation also has synergies with Aichi targets 5 (habitat loss),
7 (sustainable agriculture/forestry), 11 (protected area extent) and 14 (ecosystem services) [119].
Ecosystem-based mitigation approaches can be significantly enhanced when incorporated into
landscape-scale planning mechanisms, that is, planning which considers different sectoral/stakeholder
demands in addition to the interactions between ecosystems and the services they provide [119].
Barriers to integrated management can be overcome by including mechanisms to support multiple
stakeholder planning, clarifying land tenure, including regulatory instruments/incentives appropriate to
the national/local context, and adaptive management. National and sectoral policy harmonisation
across climate change, agriculture, forestry, biodiversity conservation and economic development will
9 Ecosystem-based mitigation and adaptation, that is, the management of ecosystems and biodiversity in such a way as to
mitigate climate change emissions or help people adapt to climate change, are synergistic [119].
53
enable ecosystem-based mitigation to be integrated with other land-use functions at a landscape scale
[119].
6d. The implementation of BECCS is uncertain
As previously discussed, of the 116 IPCC AR5 scenarios that are consistent with a greater than 66%
probability of keeping warming below 2°C, 87% apply NETs in the second half of this century [7]. Equally,
of these 116 IPCC AR5 scenarios, 104 utilise the large-scale deployment of BECCS [9] necessarily
assuming that this implementation is technologically, economically and socially viable [120] If BECCS is
excluded as a NETs option, the 2°C goal is not attained, or reached only at substantially higher costs [30].
The speculative nature and development stages of NETs (particularly BECCS, in the context of land-based
mitigation) has raised alarm in the academic literature and elicited multiple commentaries as to whether
such scenarios are feasible. Multiple authors have argued that scenarios, and integrated assessment
models (IAMs), are too dependent on BECCs, given its scientific (technical, scale, cost) and political
uncertainties [120, 30, 8, 9].
IAMs and scenarios relying on BECCs deployment are founded on a set of assumptions. Vaughan and
Gough (2016) [121] in a survey of expert opinions with regard to these assumptions, conclude that IAMs
are unrealistic in their assumptions as to (i) the extent of bioenergy deployment possible (available land,
future yields, contribution to energy system), and (ii) the establishment of adequate policy frameworks
and social acceptance in support of large-scale NETs. Conversely, the expert review panel deemed the
technological assumptions for CCS (storage capacity, technology uptake, capture rate) to be more
realistic. Of the ten assumptions considered, seven were defined as falling in a perceived “danger-zone”,
that is, assumptions had a high degree of influence on modelling outcomes, but a low pedigree in terms
of support across the expert panel [121]. The implication of unrealistically ambitious BECCS targets
and/or reliance on these NETs in mitigation pathways is the exceedance of cumulative carbon budgets
and, consequently, an inability to achieve emission targets associated with a 2°C pathway [30, 121].
CCS is not solely a land-based mitigation technology, it is for example used in combination with fossil
fuel based industries. A review of the ethical (see Medvecky et al., 2014 [122]) and social (see Fridahl,
2017 [30]) implications surrounding the large-scale implementation of CCS technologies is considered
beyond the scope of this document. While understanding the social aspects of CCS is important in
exploring BECCS [114], Fridahl (2017) [30] argues that BECCS is distinct from CCS, for example, it is
associated with the benefits of negative emissions, different uncertainties and risks. Such differences
justify a need for targeted research on the public/political acceptance of BECCS [30]. Political, public and
industrial priorities can significantly influence the deployment of BECCS; conditions that disfavour large-
scale deployment could significantly impede the scale of deployment required by IAM 2°C scenarios.
Fridahl (2017) [30] conclude that among climate change informed stakeholders, governmental and non-
governmental stakeholders at UNFCCC conferences, BECCS has a lower priority than other renewable
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energy technologies. Preference varies with geographic region, aligning to some extent, with the
technological potential of the region. However, the authors argue that the low preferences observed,
could be a barrier to BECCS inclusion (and incentives) in carbon pricing policies [30].
Fridahl (2017) [30] argues that current market conditions prohibit the commercialisation of BECCS.
Mobilisation of BECCS at the scale suggested in models will, the authors argue, be dependent on national
or regional policy decisions acting to regulate the market in favour of BECCS. Fridahl (2017) [30] also
identifies a set of key uncertainties in conceptualising BECCS deployment, namely (i) the ability to
sustainably produce biomass and the scale of this resource; (ii) knowledge gaps and uncertainties in the
magnitude of the global CO2 storage capacity available, the risks associated with this storage, and, as
Peters et al. (2017) [123] add, the development trajectory of this technology, which is slower than that
expected; (iii) economies of scale regarding BECCS deployment and infrastructural requirements; and
(iv) the carbon price at which BECCS is commercially viable.
The production of bioenergy with CCS has only been implemented in a limited number of projects. In
contrast, experience has generated a breadth of knowledge on the implementation and monitoring of
A/R strategies at scale [9]. However, under these contrasting uncertainties, it would be incorrect to
assume A/R is a silver bullet. Kreidenweis et al. (2016) [34] argue that A/R is rather a part of a set of
mitigation strategies; the context and location of A/R must still be right.
Anderson and Peters (2016) [120] argue that a reliance on NETs, in particular BECCS, to realise the Paris
Agreement is an issue of risk and inequality; if NETs fail, impacts are most likely to occur in low-emitting
communities that are geographically and financially vulnerable to climate change. This leads the authors
to argue that “negative emission technologies are not an insurance policy but rather an unjust and high-
stakes gamble” (pp. 183), further stating that the equity and risk aversion principles of the Paris
Agreement preclude NETs as the focal point of a mitigation agenda [120]. Smith et al. (2016) [8], in a
review of NETs, argue that there is “[…] no NET (or combination of NETs) currently available that could
be implemented to meet the <2°C target without significant impact on either land, energy, water,
nutrients, albedo or cost […]” (pp. 49). This statement is supported by the synergies and trade-offs
explored in this synthesis document and discussed above.
6e. Land-based mitigation is not a ‘silver-bullet’ to avoid climate
change and must be part of a policy framework that also reduces fossil
fuel based emissions
Land-mitigation effects are site-specific and challenging to generalise; a consequence of their
development context and scale of implementation [43]. The impacts of land-based mitigation may not
overlap spatially, temporally or socially with the site of implementation. Equally, estimating the
55
magnitude of these benefits, co-benefits, adverse impacts and their trade-offs is challenging, as no
standardised metrics or attribution methodologies have been agreed on [43].
Kameyama and Kawamoto (2016) [124] propose that NDC progress can be assessed by comparison to
four intermediate, energy based policy goals for emissions mitigation; (i) decarbonising energy, (ii)
improving energy efficiency, (iii) minimising energy demand, and (iv) sequestering carbon and reducing
non-CO2 GHG emissions. In a review of current policies, they highlight that the number of policies
categorised as goal (iv), which is the most applicable to land-based mitigation, is low (Figure 2). Policies
in goal (i) may or may not include BECCS. The relatively low number of land-based mitigation policies is,
it is argued, indicative of the extent of policy changes required to fully support large-scale, land-based
mitigation deployment.
Figure 2: Number of absolute policies CHN (113), GER (185), JPN (119), UK (130), US (265), derived from [124].
Institutional capacity (strong, transparent and accountable institutions) and international agreement,
Bustamante et al. (2014) [43] argue, are important for a framework supporting the wider
implementation of land-based mitigation strategies. Frameworks must support equitable social benefits
and strengthen land rights (see Issue 6b).
Ecological barriers to land-based mitigation strategies are site-specific and dependent upon the
mitigation strategy, its scale and implementation mechanisms. However, as demonstrated in this
synthesis, land-based mitigation must be integrated with non-climate policies to fully support
sustainable development. Land-based mitigation is not unconstrained; ecological barriers include, for
example, the saturating behaviour of A/R or limits on the land available for biofuel feedstocks.
As identified in this synthesis, economic barriers are one contributing factor in land-based mitigation
deployment. Equally, land-based mitigation strategies are sensitive to the differing trajectories of GHG
emission taxes, that is, the different strategies become cost-efficient at different points in time resulting
in different mitigation potentials and pathways by the end of the century [42].
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Bustamante et al. (2014) [43] summarise that for the full realisation of land-based mitigation policy
potential, financing mechanisms must be put in place to cover the costs of (i) monitoring/transactions
and (ii) opportunity costs, that is, mitigation strategies must be as attractive as other land-use
alternatives.
The long-term effectiveness of NETs is uncertain both as a function of their deployment but also within
the context of the Earth system. Jones et al. (2016) [125] argue that there is a need to better understand
the interaction between NETs and carbon cycle feedbacks. The authors find that Earth system models
suggest a significant weakening, and possible reversal, of ocean and land sinks under NETs in the 23rd
Century; such patterns may limit the longer-term (although not shorter-term) effectiveness of NETs.
Short-term decisions change long-term commitments within the context of the 2°C target. For example,
low range emission reduction targets up to 2050 imply more rapid reduction pathways (and greater
NETs deployment) beyond 2050, if the target is to be achieved [126]. Conversely, rapid emission
reductions and/or the large-scale deployment of NETs pathways implies trade-offs with other policy
objectives. In this context, the mitigation pathway followed significantly influences both climate change
impacts and policy risks [126].
Fuss et al. (2014) argue that “the reliance of current scenarios on negative emissions, despite very limited
knowledge calls for a major new transdisciplinary research agenda” (pp. 851) and “determining how safe
it is to bet on negative emissions in the second half of this century to avoid dangerous climate change
should be among our top priorities” (pp. 852). Furthermore, Rogelj et al. (pp. 222) [127] state that
“exploring futures in which a global balance of GHG emissions can be achieved in the second half of this
century with technically feasible and societally acceptable technologies represents a major research
challenge emerging from the Paris Agreement”.
A key message, across this synthesis, has been the need for integrated, coherent mitigation policies.
Mitigation strategies should not be planned in isolation, but within integrated ecosystem-based
approaches. Synergies, and trade-offs, should be explored both across climate and non-climate policies,
and across land use sectors. Land-based mitigation must be judged within the context of the Earth-
system in which its sits; benefits and impacts can be multi-scalar, and spatially dissociated. Land-based
mitigation represents one option within a mix of policy options. This includes the aggressive reduction
of fossil fuel based GHG emissions reductions.
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Abbreviations
AD – Avoided Deforestation
A/R – Afforestation/Reforestation
BECCS – Bioenergy with carbon capture and storage
CAP – Common Agricultural Policy
CBD – Convention on biological diversity
CDM – Clean Development Mechanism
CM – Cropland management
CSS – Carbon capture and storage
EU-ESD – EU Effort Sharing Decision
EU-ESR – EU Effort Sharing Regulation
EU-ETS – EU Emissions Trading Scheme
FM – Forest management
FQD – Fuel Quality Directive
GHG – Greenhouse gas
GM – Grassland management
IAMs – Integrated Assessment Models
iLUC – Indirect land-use change
INDCs – Intended Nationally Determined Contributions
IPCC – Intergovernmental Panel on Climate Change
KP – Kyoto Protocol
LCA – Life-cycle analysis
LULCC – Land-use and land-cover change
LULUCF – Land use, land-use change and forestry
NDCs – Nationally Determined Contributions
NETs – Negative emissions technologies
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NREAPs – National Renewable Energy Action Plans
SDGs – Sustainable Development Goals
UNFCCC – The United Nations Framework Convention on Climate Change
Annex 1: Relevant International Climate Policies A1.1 Climate Change within the UN policy framework
The United Nations Framework Convention on Climate Change (UNFCCC) requires signatories to (i)
adopt national-scale policies to limit anthropogenic greenhouse-gas (GHG) emissions, (ii) protect and
maintain GHG stores, and (iii) periodically publish national inventories, outlining these emissions/sinks
according to methodologies developed by the Intergovernmental Panel on Climate Change (IPCC). The
land use, land-use change and forestry (LULUCF) sector report emissions/sinks associated with
conversions between land-use types and the management of activities on these lands [13].
Parties to the UNFCCC may also have ratified the 1997 Kyoto Protocol (KP); a legally binding set of
emission targets for developed countries for the period between 2008 and 2012 (KP1) and subsequently,
but not formally in force and legally binding, for 2013 and 2020 (KP2). Emissions/sinks must be reported
from the activities of afforestation, reforestation (A/R), deforestation and forest management (FM)
(mandatory in KP2) [13]. Additionally, parties can select to report on human-induced revegetation,
grassland management (GM) and cropland management (CM) [13].
The Clean Development Mechanism (CDM) is a market-based mechanism implemented under the KP.
The CDM allows emission-reduction projects in developing countries to earn certified emission
reduction (CER) credits. CER credits can be traded and used, in part, by developing countries to meet
their KP emission targets.
The Paris Climate Agreement, ratified by 132 parties (as of February 2017), entered into force in
November 2016 and includes commitments to keep global temperatures “well below” 2 °C, while
pursuing a target of 1.5 °C, and to achieve GHG neutrality (a balance between sources and sinks) by the
second half of the century [13]. The Paris agreement also establishes binding Nationally Determined
Contributions (NDCs) which parties must prepare, communicate and maintain [14]. Unlike the KP,
emission targets as specified in the NDCs are not legally binding. Currently, these is uncertainty as to
what mechanisms, accounting approaches and differentiation (between developed/developing
countries) rules are to be included in the Paris Agreement with negotiations on-going.
Reducing Emissions from Deforestation and Forest Degradation (REDD+) is a mechanism, developed
under the UNFCCC, aimed at incentivising forest conservation, sustainable management and
enhancement [12].
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A1.2 Biodiversity and Ecosystem Services with the UN policy
framework
The Convention on Biological Diversity (CBD) aims to (i) conserve, and (ii) use sustainably biological
diversity, while also (iii) ensuring the fair and equitable sharing of those benefits which arise from the
use of genetic resources [96]. The CBD is one of seven international treaties relating to biodiversity [128,
129].
The 10th Conference of the Parties (COP) for the CBD included decision X/2, the strategic plan for
biodiversity between 2011 and 2020 [130].This decision included the Aichi Biodiversity Targets (Aichi
Targets); a set of 20 global targets which can be grouped into five strategic goals: (i) the mainstreaming
of biodiversity across government and society so to address the drivers of biodiversity loss, (ii) to reduce
pressure on biodiversity and promote sustainable use, (iii) to safeguard ecosystems, species and genetic
diversity, (iv) the enhancement of ecosystem services, and (v) to improve implementation of the CBD
through knowledge management and capacity building [130].
A1.3 Sustainable Development Goals
The Sustainable Development Goals (SDGs) arose from the UN Conference on Sustainable Development
in Rio de Janeiro. Replacing and building on the Millennium Development Goals, the SDGs are defined
with the UN strategy; “Transforming our world: the 2030 Agenda for Sustainable Development”. The
SDGs are defined around 17 goals and 169 targets (UN, 2015) [131].
Annex 2: Relevant European Policies A2.1 EU Climate and Energy Package
Arising from the earlier European Climate Change Programmes, the 2020 climate and energy
framework was introduced in 2007 (COM (2008) 30 final; [16]). This framework introduces three key
targets, which are also aligned with the Europe 2020 strategy: (i) to reduced GHG emissions by 20% (on
1990 levels), (ii) to increase the share of renewable energy to 20%, and (iii) improve energy efficiencies
by 20% (EC, 2008). These targets will be achieved by a 21% reduction in sectors covered by the EU
Emissions Trading Scheme (EU-ETS) and 10% reduction in non-ETS (EU-ESD) schemes.
To place the 2020 framework into a broader context, particularly in relation to the KP, the EU has
developed a roadmap to deliver a low-carbon economy by 2050 (COM (2011) 112 final; [102]). While
non-binding, the roadmap outlines a set of suggested actions and targets which, if undertaken, would
allow Europe to achieve its longer term climate targets.
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A renewed 2030 climate and energy framework was adopted in 2014 (COM (2014) 15 final; [17]). This
framework, which aligns with the 2050 roadmap, establishes GHG reduction targets of 40% (on 1990
levels) by 2030 and increases in both renewable energy and energy efficiencies of 27% [14]. Targets are
distributed across both EU-ETS (43% emission reductions on 2005) and non-ETS (30% emission
reductions on 2005) sectors.
A2.2 European ETS
The European Emissions Trading Scheme (EU-ETS) is a “cap and trade” scheme operational within 31
countries (EU-28, Iceland, Liechtenstein and Norway). While the EU-ETS has the potential to cover
multiple sectors, it is currently focused on those sectors where emission can be measured, reported and
verified with a high level of accuracy. In this context, the EU-ETS limits emissions (CO2, N2O and PFCs)
from high-energy industries and airlines operating between these countries [24].
A2.3 European Effort-Sharing Decision and Effort-Sharing Regulation
The European Effort Sharing Decision (EU-ESD), which came into force as part of the 2020 climate and
energy package, establishes binding annual GHG emission targets for each Member state between 2013
and 2020 (406/2009/EC; [18]). EU-ESD emission reporting encompasses non-ETS sectors such as
transport, buildings, agriculture (non-CO2 only) and waste. National scale targets will collectively achieve
a 10% reduction in EU emissions (on 2005 levels). National targets were defined as a function of the
Member States relative wealth (GDP per capita) and range from a reduction of 20% (IE, DK) to permitted
increases (emission ceilings) of 20% (BG) [18]. It is worth noting that the EU-ESD excludes CO2 emissions
from the LULUCF sector.
The EU-ESD covers multiple sectors with flexibility on how overall emissions targets are reached.
Geographic flexibility allows Member States to transfer up to 5% of their GHG emissions to another
Member state. Temporal flexibility allows Member States to bank or borrow emission allocations
between years in the trading period. Additional flexibility, is achieved by allowing Member state to use
project activity credits, for example, from the CDM, towards reduction targets (up to 3% of 2005
emission levels) [11].
The Effort Sharing Regulation (EU-ESR) is a follow-up to the EU-ESD, defined in-line with the 2030
climate and energy framework. The EU-ESR, which is at the proposal stage, continues the definition of
national binding GHG emissions targets (for 2021-2030) for non-ETS sectors (COM(2016) 479 final; [19])
The EU-ESR retains the geographic and temporal flexibilities of the EU-ESD. However, credits from non-
EU project activities (CDM) would be excluded. Additional proposed flexibilities would enable Member
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States to use removals from the LULUCF sector to offset EU-ESR emissions, and for a subset of Member
States (based on eligibility criteria) to use part of their EU-ETS to meet their EU-ESR targets [11].
A2.4 European Land Use Decision
At present the LULUCF (land use, land-use change and forestry) sector while included in KP accounting,
remains outside EU climate policies and emission reduction targets; the sector does not contribute to
the 20% GHG reduction by 2020 target. There are however a number of salient decisions and proposals
within this sector.
The European 2013 Land Use Decision (529/2013/EU; [20]) requires all Member States to prepare and
maintain GHG accounts (emissions/sequestration) for forests, cropland and grasslands in a manner
comparable to the IPCC guidelines for National GHG inventory reporting. Within the 2013-2020
accounting period only the reporting of forest activities (A/R, D and FM) is mandatory. The preparation
of cropland (CM) and grassland (GM) accounts is required as a first step towards ensuring the inclusion
of these sectors (as mandatory) in 2021 onwards. As a consequence, Member States must report CM
and GM emissions/removals from 2015 onwards including an outline on the intended improvements in
these reporting systems. The EU 2013 land use decision also allows Member States to prepare and
maintain emission accounts from revegetation and the drainage/rewetting of wetlands.
During July 2016 a legislative proposal was presented by the EC to integrate the LULUCF sector into the
2030 climate and energy framework (COM(2016) 479 final; [10]). The proposal sets a legally binding
commitment for all Member States to ensure a “no debit rule” within the LULUCF sector, that is,
emissions should be equivalent to removals. While this “no debit” commitment is already part of the
KP, the proposal would place the same commitment into EU law for the period between 2021 and 2030.
The introduction of greater flexibilities within the proposed LULUCF decision would allow Member
States to use excess allocations from the EU-ESR to meet the intended “no-debit” commitment, and
temporal flexibility in terms of the banking or borrowing of emissions between years (as per the EU-ESD)
[11].
A2.5 Renewable Energy Directive and Fuel Quality Directive
The Renewable Energy Directive (EU-RED), (2009/28/EC; [21]), requires that the EU (through Member
States national targets) use renewable sources to fulfil at least 20% of all its energy requirements by
2020. Also included in the EU-RED is the mandate that all EU Member States must ensure at least 10%
of transport fuels are derived from renewable sources by 2020 [21].
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The Fuel Quality Directive (FQD), (2009/30/EC; [23]) mandates a carbon intensity reduction of transport
fuels within the EU by 6% (when compared to the GHG emissions of conventional fossil-fuel based fuels).
In the context of these policies, the EU has defined a set of biofuel (transport) and bioliquid (electricity
and heating) sustainability criteria. Only biofuels compliant with these criteria count towards renewable
energy targets as specified in the EU-RED and EU-FQD (2010/C 160/02; [132]). The main sustainability
criteria are, (i) that biofuels achieve a specified GHG saving when compared to fossil fuel sources, (ii)
that biofuels cannot be grown on converted land which previously have a high carbon stock (wetlands,
forest), and (iii) that biofuel feedstocks cannot be obtained from lands with a high biodiversity status
(primary forests or high biodiverse grasslands). Compliance with these criteria is assessed by adherence
to either a national and/or recognised voluntary scheme [133].
A 2015 directive (2015/1513; [22]) amended current biofuel legislation (EU-RED, EU-FQD) so to reduce
the risk of indirect LULCC arising from biofuel production, and support the development of advanced
(second-generation) biofuels. This amendment (i) limits the share of biofuels and bioliquids derived from
cereal, starch-rich crops, sugars and oil crops and crops grown primarily grown for energy purposes on
agricultural land to no greater than 7% of specified targets by 2020, (ii) sets indicative targets for
advanced biofuel use by 2017, (iii) specified and harmonises the list of biofuels which contribute double
to 2020 transport energy targets, (iv) sets GHG emission targets for new biofuel installations, and (v)
supports the inclusion of renewable electricity sources within 2020 transport targets [22, 134].
The 2016 European Strategy for low-emission mobility, (COM(2016) 501; [135], highlights that there is
a need for an assessment of the investment needs for advanced biofuels and that, at this time, these
biofuels cannot compete with fossil fuels or food-based biofuels [135].
A 2016 directive of the European Parliament publishes a proposal for a revised Renewable Energy
Directive (EU-REDII), (2016/0382; [15]) for the period 2020 to 2030. This proposed framework sets an
EU target of at least 27% renewable energy sources by 2030 [15]. This directive also includes a proposal
to limit the share of food-based biofuels to 3.8% by 2030 (starting in 2021) and increase the share of
advanced biofuels to 3.6% by 2030.
A2.6 Forest 2013 strategy
No specific forest provisions are made in the EU Treaty. However, the EU contributes to sustainable
forest management and national policy decisions, by Member’s states, through developments in, for
example, rural development policy, the EU climate and energy package, industrial policy, the Europe
2020 strategy and so on [25].
The EU forest strategy (COM(2013) 659; [25]), published in 2013, has been adopted (as a resolution
2014/2223(INI)) by the European Parliament. The forest strategy provides a framework for forest related
63
policies promoting a coherent and holistic forest management approach. It identified the principles to
strengthen forest management whilst also ensuring forest protection and the maintenance of
ecosystem service delivery [25, 26].
The EU Forest Action Plan (2007 – 2011) was implemented in support of a more pro-active and coherent
approach to forest management within the EU. The Action Plan was based on the principles and
objectives of the earlier 1998 EU Forest strategy (EC, 2016d). The action plan focussed on a vision of
long-term multifunctional forestry which fulfilled the needs of society now and in the future and
supported forest-related livelihoods [136]. The key objectives of the plan were: (i) improving long-term
competitiveness, (ii) environmental protection and improvement, (iii) contributing to the quality of life,
and (iv) fostering coordination and communication. These objectives were translated into 18 key actions
to be implemented over the five-year implementation period. The EU Forest Action Plan was reviewed
both during (mid-term) and following (ex-post) its implementation; a summary of the review findings is
provided in [24].
A2.7 Common Agricultural Policy
The Common Agricultural Policy (EU-CAP), is considered central for steering farm level decisions in
support of climate protection in Europe [37].
The new EU-CAP (2014-2020), agreed in 2013 [27], is centred around three long-term objectives: (i)
viable food production, (ii) sustainable management of natural resources and climate action, and (iii)
balanced territorial development. CAP 2014-2020 comprises two pillars. Pillar one supports the income
of farmers via direct payments. Included within this pillar are a set of three ‘greening measures’ namely,
(i) the maintenance of permanent grassland, (ii) ecological focus areas, and (iii) crop diversification [27].
Greening payments must constitute at least 30% of Member state direct payments [137] EU-CAP
environmental objectives are continued under the second pillar, of rural development. Rural
development, implemented through national and/or regional rural development programs (RDPs), must
be based upon four of six common EU priorities; priorities which include (amongst others) the
restoration of ecosystems and shifts towards low carbon/climate resilient agricultural systems [27].
Member States must make at least 30% of their budget for RDPs available for those voluntary measures
which are environment/climate beneficial, for example, climate payments, organic farming, areas of
natural constraints (ANC), Natura 2000 areas, and forestry measures [27].
64
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