Increasing the uptake of ecological model results in policy decisions to improve biodiversity outcomes

Sarah R. Weiskopf; Zuzana V. Harmáčková; Ciara G. Johnson; María Cecilia Londoño-Murcia; Brian W. Miller; Bonnie J.E. Myers; Laura Pereira; Maria Isabel Arce-Plata; Julia L. Blanchard; Simon Ferrier; Elizabeth A. Fulton; Mike Harfoot; Forest Isbell; Justin A. Johnson; Akira S. Mori; Ensheng Weng; Isabel M.D. Rosa

doi:10.1016/j.envsoft.2022.105318

Increasing the uptake of ecological model results in policy decisions to improve biodiversity outcomes

Sarah R. Weiskopf
, Zuzana V. Harmáčková
, Ciara G. Johnson
, María Cecilia Londoño-Murcia
, Brian W. Miller
, Bonnie J.E. Myers
, Laura Pereira
, Maria Isabel Arce-Plata
, Julia L. Blanchard
, Simon Ferrier
, Elizabeth A. Fulton
, Mike Harfoot
, Forest Isbell
, Justin A. Johnson
, Akira S. Mori
, Ensheng Weng
, Isabel M.D. Rosa

Ecology, Evolution and Behavior

Research output: Contribution to journal › Article › peer-review

28 Scopus citations

Abstract

Models help decision-makers anticipate the consequences of policies for ecosystems and people; for instance, improving our ability to represent interactions between human activities and ecological systems is essential to identify pathways to meet the 2030 Sustainable Development Goals. However, use of modeling outputs in decision-making remains uncommon. We share insights from a multidisciplinary National Socio-Environmental Synthesis Center working group on technical, communication, and process-related factors that facilitate or hamper uptake of model results. We emphasize that it is not simply technical model improvements, but active and iterative stakeholder involvement that can lead to more impactful outcomes. In particular, trust- and relationship-building with decision-makers are key for knowledge-based decision making. In this respect, nurturing knowledge exchange on the interpersonal (e.g., through participatory processes) and institutional level (e.g., through science-policy interfaces across scales) represents a promising approach. To this end, we offer a generalized approach for linking modeling and decision-making.

Original language	English (US)
Article number	105318
Journal	Environmental Modelling and Software
Volume	149
DOIs	https://doi.org/10.1016/j.envsoft.2022.105318
State	Published - Mar 2022

Bibliographical note

Funding Information:
Sarah Weiskopf reports financial support was provided by National Socio-Environmental Synthesis Center.This work was supported by the National Socio-Environmental Synthesis Center (SESYNC) under funding received from the National Science Foundation DBI-1639145. A portion of this research was supported by the U.S. Geological Survey National and North Central Climate Adaptation Science Centers. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. We thank A. Cravens for her helpful review comments.

Funding Information:
This work was supported by the National Socio-Environmental Synthesis Center ( SESYNC ) under funding received from the National Science Foundation DBI-1639145. A portion of this research was supported by the U.S. Geological Survey National and North Central Climate Adaptation Science Centers . Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. We thank A. Cravens for her helpful review comments.

Publisher Copyright:
© 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 8 Decent Work and Economic Growth
SDG 16 Peace, Justice and Strong Institutions
SDG 17 Partnerships for the Goals

Keywords

Biodiversity-ecosystem function relationships
Co-production
Ecological modeling
Policy relevance
Stakeholder engagement

Publisher link

10.1016/j.envsoft.2022.105318

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Cite this

Weiskopf, S. R., Harmáčková, Z. V., Johnson, C. G., Londoño-Murcia, M. C., Miller, B. W., Myers, B. J. E., Pereira, L., Arce-Plata, M. I., Blanchard, J. L., Ferrier, S., Fulton, E. A., Harfoot, M., Isbell, F., Johnson, J. A., Mori, A. S., Weng, E., & Rosa, I. M. D. (2022). Increasing the uptake of ecological model results in policy decisions to improve biodiversity outcomes. Environmental Modelling and Software, 149, Article 105318. https://doi.org/10.1016/j.envsoft.2022.105318

Weiskopf, SR, Harmáčková, ZV, Johnson, CG, Londoño-Murcia, MC, Miller, BW, Myers, BJE, Pereira, L, Arce-Plata, MI, Blanchard, JL, Ferrier, S, Fulton, EA, Harfoot, M, Isbell, F , Johnson, JA, Mori, AS, Weng, E & Rosa, IMD 2022, 'Increasing the uptake of ecological model results in policy decisions to improve biodiversity outcomes', Environmental Modelling and Software, vol. 149, 105318. https://doi.org/10.1016/j.envsoft.2022.105318

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abstract = "Models help decision-makers anticipate the consequences of policies for ecosystems and people; for instance, improving our ability to represent interactions between human activities and ecological systems is essential to identify pathways to meet the 2030 Sustainable Development Goals. However, use of modeling outputs in decision-making remains uncommon. We share insights from a multidisciplinary National Socio-Environmental Synthesis Center working group on technical, communication, and process-related factors that facilitate or hamper uptake of model results. We emphasize that it is not simply technical model improvements, but active and iterative stakeholder involvement that can lead to more impactful outcomes. In particular, trust- and relationship-building with decision-makers are key for knowledge-based decision making. In this respect, nurturing knowledge exchange on the interpersonal (e.g., through participatory processes) and institutional level (e.g., through science-policy interfaces across scales) represents a promising approach. To this end, we offer a generalized approach for linking modeling and decision-making.",

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note = "Funding Information: Sarah Weiskopf reports financial support was provided by National Socio-Environmental Synthesis Center.This work was supported by the National Socio-Environmental Synthesis Center (SESYNC) under funding received from the National Science Foundation DBI-1639145. A portion of this research was supported by the U.S. Geological Survey National and North Central Climate Adaptation Science Centers. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. We thank A. Cravens for her helpful review comments. Funding Information: This work was supported by the National Socio-Environmental Synthesis Center ( SESYNC ) under funding received from the National Science Foundation DBI-1639145. A portion of this research was supported by the U.S. Geological Survey National and North Central Climate Adaptation Science Centers . Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. We thank A. Cravens for her helpful review comments. Publisher Copyright: {\textcopyright} 2022",

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AU - Londoño-Murcia, María Cecilia

AU - Miller, Brian W.

AU - Myers, Bonnie J.E.

AU - Pereira, Laura

AU - Arce-Plata, Maria Isabel

AU - Blanchard, Julia L.

AU - Ferrier, Simon

AU - Fulton, Elizabeth A.

AU - Harfoot, Mike

AU - Isbell, Forest

AU - Johnson, Justin A.

AU - Mori, Akira S.

AU - Weng, Ensheng

AU - Rosa, Isabel M.D.

N1 - Funding Information: Sarah Weiskopf reports financial support was provided by National Socio-Environmental Synthesis Center.This work was supported by the National Socio-Environmental Synthesis Center (SESYNC) under funding received from the National Science Foundation DBI-1639145. A portion of this research was supported by the U.S. Geological Survey National and North Central Climate Adaptation Science Centers. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. We thank A. Cravens for her helpful review comments. Funding Information: This work was supported by the National Socio-Environmental Synthesis Center ( SESYNC ) under funding received from the National Science Foundation DBI-1639145. A portion of this research was supported by the U.S. Geological Survey National and North Central Climate Adaptation Science Centers . Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. We thank A. Cravens for her helpful review comments. Publisher Copyright: © 2022

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N2 - Models help decision-makers anticipate the consequences of policies for ecosystems and people; for instance, improving our ability to represent interactions between human activities and ecological systems is essential to identify pathways to meet the 2030 Sustainable Development Goals. However, use of modeling outputs in decision-making remains uncommon. We share insights from a multidisciplinary National Socio-Environmental Synthesis Center working group on technical, communication, and process-related factors that facilitate or hamper uptake of model results. We emphasize that it is not simply technical model improvements, but active and iterative stakeholder involvement that can lead to more impactful outcomes. In particular, trust- and relationship-building with decision-makers are key for knowledge-based decision making. In this respect, nurturing knowledge exchange on the interpersonal (e.g., through participatory processes) and institutional level (e.g., through science-policy interfaces across scales) represents a promising approach. To this end, we offer a generalized approach for linking modeling and decision-making.

AB - Models help decision-makers anticipate the consequences of policies for ecosystems and people; for instance, improving our ability to represent interactions between human activities and ecological systems is essential to identify pathways to meet the 2030 Sustainable Development Goals. However, use of modeling outputs in decision-making remains uncommon. We share insights from a multidisciplinary National Socio-Environmental Synthesis Center working group on technical, communication, and process-related factors that facilitate or hamper uptake of model results. We emphasize that it is not simply technical model improvements, but active and iterative stakeholder involvement that can lead to more impactful outcomes. In particular, trust- and relationship-building with decision-makers are key for knowledge-based decision making. In this respect, nurturing knowledge exchange on the interpersonal (e.g., through participatory processes) and institutional level (e.g., through science-policy interfaces across scales) represents a promising approach. To this end, we offer a generalized approach for linking modeling and decision-making.

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KW - Policy relevance

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ER -

Increasing the uptake of ecological model results in policy decisions to improve biodiversity outcomes

Abstract

Bibliographical note

UN SDGs

Keywords

Publisher link

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