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Joseph Kiesecker Lead Scientist The Nature Conservancy From Paris to Practice: Energy Sprawl Solutions

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Page 1: Lead Scientist - Home | National Academies › cs › groups › ... · National PAs 2011 Eastern Grasslands 64,000 km2 (41%) 2013 Gobi region 34,900 km2 (19%) 2016 West & Central

Joseph Kiesecker – Lead Scientist

The Nature Conservancy

From Paris to Practice: Energy Sprawl Solutions

Page 2: Lead Scientist - Home | National Academies › cs › groups › ... · National PAs 2011 Eastern Grasslands 64,000 km2 (41%) 2013 Gobi region 34,900 km2 (19%) 2016 West & Central

“Buy land, they're not making it anymore.” - Mark Twain

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20%

DEVELOPMENT

THREAT

CATEGORIES

NATURAL

LANDS

OF LANDS AT HIGH RISK

5%

OF LANDS PROTECTED

Global Assessment: Lands at Risk

Oakleaf, Kennedy, Baruch-Mordo & Kiesecker (2015) A World at Risk: Aggregating Development Trends to Forecast Global Habitat Conversion. PLoS ONE 10 (10): e0138334. doi:10.1371/journal.pone.0138334

Page 5: Lead Scientist - Home | National Academies › cs › groups › ... · National PAs 2011 Eastern Grasslands 64,000 km2 (41%) 2013 Gobi region 34,900 km2 (19%) 2016 West & Central
Page 6: Lead Scientist - Home | National Academies › cs › groups › ... · National PAs 2011 Eastern Grasslands 64,000 km2 (41%) 2013 Gobi region 34,900 km2 (19%) 2016 West & Central
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Potential

Impact

Residual

Impact

Mitigation Hierarchy

Restore

Offset

No

Net

Loss

Minimize

Kiesecker, J.M, H. Copeland, A. Pocewicz, N. Nibbelink, B. McKenney J. Dahlke, M. Holloran and D. Stroud 2009 A Framework for

Implementing Biodiversity Offsets: Selecting Sites and Determining Scale. BioScience 59:77-84.

Impact

+

- Avoid

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Page 10: Lead Scientist - Home | National Academies › cs › groups › ... · National PAs 2011 Eastern Grasslands 64,000 km2 (41%) 2013 Gobi region 34,900 km2 (19%) 2016 West & Central

Avoid

Minimize

Restore

Offset

What needs to change?

GO BIG

-Connect Global commitments to Local Scales

-Site based to landscape scale

-Revise current EIA process?

GO EARLY

-Advanced planning

-Project future potential development

-Develop quantitative conservation goals

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FINE FILTER

Species

Other Goals i.e. Eco. Services

Social/Cultural

(X) Acres of habitat needed to maintain viability

( Y ) Acres of habitat or point locations (i.e. nests)

needed to maintain viability

Select BIODIVERSITY ELEMENTS Set GOALS

assess ECOLOGICAL CONDITION Conservation Portfolio Design:

Development Portfolio Design: Cost / Suitability Index

•Road & RR Density

• Population Density

• Converted Land Cover

• Irrigated Land Cover

• Housing density

Future development pressure

automated

site selection

(MARXAN with ZONES)

Integrated Conservation & Development Planning

COARSE FILTER

Vegetation Types

( Z ) Amount of production

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Achieving Conservation Goals in the Face of Development

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endemic / restricited range

Landform classification

wet/salty depressions

key evolutionary processes

unique ecosystems

source: McCarthy et al. (2009)

source: : McCarthy (2000)

globally and nationally endangered

conservation portfolio = critical habitat

congretory and migratory

+

=

Figure 4. Identification of critical habitat in the Gobi region for the purposes of implementation of the IFC Performance Standard 6. Critical habitats are areas important for Globally or

nationally Critically Endangered or Endangered species; Restricted-range or endemic species; Concentrations of migratory and congregator species; Highly threatened and unique

ecosystems; and Key evolutionary processes. These features can be built into the design of a conservation portfolio and serve to identify critical habitat.

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Initial portfolio and existing mineral leases

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Areas of potential conflict with mineral development

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Initial portfolio re-designed to minimize conflict with mineral development

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Portfolio re-designed to minimize conflict with mineral development

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National PAs

2011 Eastern Grasslands

64,000 km2 (41%)

2013 Gobi region

34,900 km2 (19%)

2016 West & Central Mongolia

48,400 km2 (18%)

Mongolia:

conservation portfolio

National PAs

study area

Science that works

new PAs in portfolio

conservation portfolio

National PAs

study area

new PAs in portfolio

conservation portfolio

National PAs

study area

new PAs in portfolio

conservation portfolio

National PAs

study area

[1] Heiner, M., Y. Bayarjargal, J.M. Kiesecker, D. Galbadrakh, N. Batsaikhan, M. Ganbaatar, I. Odonchimeg, O. Enkhtuya, D. Enkhbat, H. von Wehrden, R. Reading, K. Olson, R. Jackson, J. Evans, B. McKenney, J. Oakleaf, K. Sochi, E. Oidov. (2013) Applying conservation priorities in the face of future development: Applying development by design in the Mongolian Gobi. The Nature Conservancy. Ulanbaatar. [Also available in Mongolian]

[2] Heiner, M., D. Galbadrakh, J.M. Kiesecker, B. McKenney, J. Evans, E. Tuguldur, D. Zumburelmaa, V. Ulziisaikhan, B. Oyungerel, D. Sanjmyatav, R. Gankhuyag, D. Enkhbat, L. Ocirhuyag, G. Sergelen, E. Girvetz and R. McDonald. (2011) Identifying Conservation Priorities in the Face of Future Development: Applying Development by Design in the Grasslands of Mongolia. The Nature Conservancy. Ulanbaatar. [Also available in Mongolian]

43% of the portfolio

9% of Mongolia

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Achieving Development Goals in the Face of Conservation

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Achieving Development Goals in the Face of Conservation

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Obermeyer B, Manes R, Kiesecker J, Fargione J, Sochi K (2011) Development by Design: Mitigating Wind

Development’s Impacts on Wildlife in Kansas. PLoS ONE 6(10): e26698. doi:10.1371/journal.pone.0026698

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Achieving Development Objectives

and Conservation Goals

Simultaneously

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Cattle ranching Sugarcane

• Cerrado: Global biodiversity hotspot, with less than 50% natural habitat & < 2 % protected (Klink & Machado 2005)

• Land use: cattle ranching and increasingly sugarcane production (Lapola et al. 2010)

• Nature conservation on agricultural (private) lands is vital and regulated by the Brazilian Forest Code (FC) (Soares-Filho et al. 2014)

• Case study: Evaluate land use patterns to meet the FC and to optimize agricultural production, biodiversity, & ecosystem services

Cerrado

Case Study

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Brazilian Forest Code

Brazil pilot River

Agriculture

Agriculture

Rural Property

Permanent Preservation Area (PPA): ~5%

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• Economic return ($) (Using spatial profit models of annual

revenue – annual costs)

• 539 terrestrial birds & mammal species

(Using Polasky et al. 2008 biologic model)

• Nutrients & sediments (N, P, S loads) in surface waterways

(Using InVEST models, Tallis et al. 2013)

Economic & Environmental Modeling

Agriculture Cattle ranching

Sugar cane

Biodiversity

Terrestrial Surface Water Quality

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current

20

025

030

035

040

0

#S

pecie

s (

bird

s &

ma

mm

als

)

0 10 20 30 40

Agricultural profit (in million USD)

current

0

20

040

060

0

N r

edu

ctio

n (

in to

ns)

0 10 20 30 40

Agricultural profit (in million USD)

Improved BD

+ 94 species

Improved water quality

(N, P, S loads reduced by 50%, 30%, 7%)

Brazil pilot: Optimizing land use decision-making

Current Landscape

Kennedy, C.M., P.L. Hawthorne, D.A. Miteva, L. Baumgarten, K. Sochi, M. Matsumoto, J.S. Evans, S. Polasky, P. Hamel, E.M. Vieira, P.F. Develey, C.H. Sekercioglu, A.D. Davidson, E.M. Ulhorn, & J. Kiesecker (i2016). Optimizing land use decision-making to sustain Brazilian Agricultural profits, biodiversity and ecosystem services. Biological Conservation, 2016 http://dx.doi.org/10.1016/j.biocon.2016.10.039

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Optimized for Biodiversity

Optimized for Water Quality

Average WQ reduced by 30%

• N loads increased by 41% • S loads increased by 8% • P loads increased by 42%

Species reduced by 58%

• 122 fewer species

Brazil pilot Optimizing land use decision-making

Optimized for Biodiversity and Water Quality

94% species

77-100% of average water quality

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ABCs for Resolving Land Use Conflicts

• Ahead of the impacts

• Bigger scale – landscape-level planning

• Conservation outcome

• Development objectives

Avoid

Minimize

Restore

Offset

Predicting The Future

Examining Tradeoffs

Policy Drivers

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Biofuels

Solar

Wind

Hydropower

Conventional oil & gas

Unconventional oil & gas

Coal

Agriculture

Urban

Mining

Oakleaf, James R, Christina M Kennedy, Sharon Baruch-Mordo, Paul C West, James S Gerber, Larissa Jarvis, and Joseph Kiesecker. 2015. “A World at Risk: Aggregating Development Trends to Forecast Global Habitat Conversion.” PloS One 10 (10). Public Library of Science: e0138334. doi:10.1371/journal.pone.0138334.

What, Where, How Much? Global Development Risk Assessment

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18% (n=360) of “sensitive” watersheds will transition into a higher impact status 7% (n=130) will move into a “nonsupporting” or “urban” drainage impact status.

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Putting Science to Work

Science

Geomorphometrics Toolbox

Gobi Ecoregional Assessment Web Map

Riparian / Wetland Model Toolbox

Policy

Mongolia Mitigation Design Tool Brazil LegalGeo

Stakeholder Engagement

Biodiversity and Ecosystem Services Trends and Conditions Assessment Tool Central Appalachians Critical Habitat Assessment

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Policy Assessments

0

5

10

15

20

25

30

35

40

IA Avoidance Minim-rest Offsets Monitoring

For more details see: Villarroya A, Barros AC, Kiesecker J (2014) Policy Development for Environmental Licensing and Biodiversity Offsets in Latin America. PLoS ONE 9(9): e107144. doi:10.1371/journal.pone.0107144

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Snow Leopards of the World: The Science, Politics, and Conservation of Panthera Uncia

Thomas McCarthy and David Mallon, Editors

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Global Lands Program: www.nature.org/ourinitiatives/urgentissues/smart-development/index.htm