whose priorities? providing decision-support for finnish forest conservation decision-making

Whose priorities?Providing decision-support for Finnish forest conservation decision-making

Joona LehtomäkiHelsingin yliopisto, Finnish Environment InstituteEEB seminar 2015-01-28

@jlehtoma

1. Suitability of commonly available forest inventory data for informative spatial conservation prioritization in Finnish forests

2. Effects of scale and connectivity at regional and national extents

3. Develop, demonstrate, and implement a practical workflow using Zonation

Dissertation

Objectives

4. Providing support for Finnish forest conservation decision-making

Dissertation

Objectives

• Whose priorities?

• Have the results provided support for decision

making?•

• Additional considerations

• Science-policy interfaces

• Knowledge systems

• Policy X (research, relevance etc.)

This talk

Objectives

knowyourmeme.com

Extending the PA network on public land

Emphasize here what the talk is about and what are they key themes against which the

listener can compare things.


Software for spatial conservation prioritization

Input data

GIS

Experts

Ecologicalknowledge

Features

Weights

Costs

Connectivity

Higher/lowerpriority areas

for conservation

Performance/potential for

protection

Data collection

Data preparation

Data analysis

Inference/ Decision


Typical Zonation workflow

~10 000 ha on public land

~100 ha / location

1 view

Lehtomäki et al. 2009


Objectives

DECISION

SLL


Decision-making



Decision-support

~20 000 ha on public land

~100 ha / location

1 view

DECISION

SLL

DECISION


Decision-making

Input data

GIS

Experts

Ecologicalknowledge

Features

Weights

Costs

Connectivity

Higher/lowerpriority areas

for conservation

Performance/potential for

protection

Data collection

Data preparation

Data analysis

Inference/ Decision


Typical Zonation workflow

Data

Scientists

Policymakers

Stakeholders and the public

Knowledge

Decisions

Models of science-policy interaction

The deficit-linear model of science-policy interaction

Soranno et al. 2014; Young et al. 2014

Basic science

Applied science

Societal need

”The Pure Scientist”

”The Science Arbiter”

Basic science

Applied science

Societal need

Societal need Science

Policy A

Policy B

”The Issue Advocate”

”The Honest Broker”

Societal need

Science

Policy A

Policy B

Policy C

Pielke 2008; Calow 2014

”The Science Arbiter”

Basic science

Applied science

Societal need

Societal need

SciencePolicy A

Policy B

”The Issue Advocate”

Stealth advocacy

Pielke 2008; Calow 2014

Extending the PA network on private

land

Ecological Decision Analysis in METSO-implementation

Private

Reserves

State

ForestryPrivate

State

Lehtomäki et al. in prep

Extending the PA network on private land

Objectives

Lehtomäki et al. in prep

Kainuu

Pohjois-Pohjanmaa

Etelä-Savo

Keski-Suomi

Pohjois-Savo

Pirkanmaa

Lapin METSO-alue

Pohjois-Karjala

Etelä- ja Keski-Pohjanmaa ja Ra

Lounais-Suomi ja Rannikko

Häme-Uusimaa ja Rannikko

Kaakkois-Suomi

Kuva: Joona Lehtomäki, CC-BY-3.0

CredibilityThe scientific adequacy of the technical evidence and arguments.

SalienceThe relevance of the assessment to the needs of decision makers.

LegitimacyThe perception that the production of information and technology has been respectful of stakeholders’ divergent values and beliefs, unbiased in its conduct, and fair in its treatment of opposing views and interests.

Cash et al. 2003


Attributes of science-policy interface

• Data• Knowledge• Decisions

Scientis

ts

Policym

akersPublic

Stakeholders


The roundtable model of science-policy interaction

Soranno et al. 2014; Lynman et al. 2007

CredibilityIncreased by bringing multiple types of expertise to the table.

SalienceIncreased by engaging end-users early in defining data needs.

LegitimacyIncreased by providing multiple stakeholders with more, and more transparent, access to the information production process.

Cash et al. 2003


Attributes of science-policy interface

Credibility

Quality assessment

Communication of uncertainties

Supply-driven

Salience

Timely

Simple

Demand-driven

Legitimacy

Consensus

Wide participation

Range of views

Sarkki et al. 2013


Trade-offs

Lehtomäki 2014

BLACK BOX

Providing support for conservation decision making

Whose priorities?

• Credibility• Results genuinely useful for tackling complex issues• Objective vs. subjective (careful here…)

• Salience• Types of information is actually needed• Types of data actually available• Values and preferences

• Legitimacy• Involvement can mean acceptance can understanding• Explicit path of choices for decision-making


Alternative/complementary models

Dicks et al. 2014


Scientists’ role

The Science Arbiter / The honest broker

Whistleblower

ReferencesCash, D.W. et al. (2003) Knowledge systems for sustainable development. Proceedings of the National Academy of Sciences of the United States of

America 100, 8086–91Dicks, L. V et al. (2014) Organising evidence for environmental management decisions: a “4S” hierarchy. Trends in Ecology & Evolution 29, 607–613Lehtomäki, J. (2014) , Spatial conservation prioritization for Finnish forest conservation management. , University of HelsinkiLehtomäki, J. et al. (2009) Applying spatial conservation prioritization software and high-resolution GIS data to a national-scale study in forest

conservation. Forest Ecology and Management 258, 2439–2449Lynam, T. et al. (2007) A Review of Tools for Incorporating Community Knowledge , Preferences , and Values into Decision Making in Natural

Resources Management. Ecology And Society 12, 5Sarkki, S. et al. (2013) Balancing credibility, relevance and legitimacy: A critical assessment of trade-offs in science-policy interfaces. Science and Public

PolicySoranno, P.A. et al. (2015) It’s good to share: Why environmental scientists' ethics are out of date. BioScience 65, 69–73Pielke Jr, R.A. (2007) The Honest Broker: Making Sense of Science in Policy and Politics, Cambridge University Press.Young, J.C. et al. (2014) Improving the science-policy dialogue to meet the challenges of biodiversity conservation: Having conversations rather than

talking at one-another. Biodiversity and Conservation 23, 387–404

References – conservation biologyCook, C.N. et al. (2013) Achieving conservation science that bridges the knowledge-action boundary. Conservation Biology 27, 669–678Opdam, P. (2010) Learning science from practice. Landscape Ecology 25, 821–823Reyers, B. et al. (2010) Conservation Planning as a Transdisciplinary Process. Conservation biology 24, 957–65