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Colombian biodiversity is governed by a rich and diverse policy mix

Nature Ecology & Evolution volume 7, pages 382–392 (2023)Cite this article

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Abstract

We lack an understanding of how diverse policymakers interact to govern biodiversity. Taking Colombia as a focal case, we examined six decades of biodiversity governance (1959–2018). Here we analysed the composition of the policy mix, and how it has evolved over time, how policies differ among lead actors and ecosystems, and whether the policy mix addresses the primary threats to biodiversity. We identified 186 biodiversity-related policies that govern multiple ecosystems, use different instruments and address the main threats to biodiversity (that is, agriculture and aquaculture, and biological resource use). We found policy gaps in the governance of invasive species and wildlife trade. Biodiversity policy integration into some sectoral policies, such as climate change, poverty and pollution, has become more common in the past decade. Our results point to an increased need for effective coordination across sectors and actors, as new ones influence and implement the policy mix.

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Fig. 1: Multiple policies address biodiversity conservation in Colombia.
Fig. 2: The biodiversity policy mix has increased exponentially since the 1960s and has become more diverse over time.
Fig. 3: The biodiversity policy mix is diverse; and different policy instruments prevail in policy mixes grouped by lead actors, governance scales and ecosystems.
Fig. 4: The policy mix targets the main threats to biodiversity in similar proportions to the extent of the threats.

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Data availability

All source data for analyses are available at https://doi.org/10.5061/dryad.0gb5mkm47 (ref. 59). Source data are provided with this paper.

Code availability

All R scripts and code to run analyses and reproduce figures are available at https://doi.org/10.5061/dryad.0gb5mkm47 (ref. 59).

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Acknowledgements

The views and opinions expressed in this article are those of the authors and do not reflect the official policy or position of the Colombian Government, AIDA Americas or the Global Green Growth Institute. We are indebted for the comments and advice of S.J. Alvarez, A. Baresch, L. Buitrago Garzón, P. Franco, A.M. Fuentes, C. Gutiérrez Chacón, S. Melo Leon and D. Moncada Rasmussen. We thank members of the Daily lab, land use change lab, Mordecai lab and evolvert lab, as well as colleagues from the Natural Capital Project for great insights on our project. We thank the Gordon and Betty Moore Foundation for awarding a research grant to M.R., G.C.D., A.E., S.M. and L.M.

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Authors and Affiliations

  1. Department of Biology, Stanford University, Stanford, CA, USA

    Alejandra Echeverri, Lisa Mandle & Gretchen C. Daily

  2. Center for Conservation Biology, Stanford University, Stanford, CA, USA

    Alejandra Echeverri, Lisa Mandle & Gretchen C. Daily

  3. The Natural Capital Project, Stanford University, Stanford, CA, USA

    Alejandra Echeverri, Sydney Moss, Lisa Mandle, Mary Ruckelshaus & Gretchen C. Daily

  4. Woods Institute for the Environment, Stanford University, Stanford, CA, USA

    Alejandra Echeverri, Paul R. Furumo, Sydney Moss, Lisa Mandle, Mary Ruckelshaus, Gretchen C. Daily & Eric F. Lambin

  5. Stanford Doerr School of Sustainability, Stanford University, Stanford, CA, USA

    Paul R. Furumo & Eric F. Lambin

  6. Blum Center for Developing Economies, University of California Berkeley, Berkeley, CA, USA

    Sydney Moss

  7. Stanford School of Engineering, Stanford University, Stanford, CA, USA

    Alan G. Figot Kuthy

  8. AIDA Americas (Interamerican Association for Environmental Defense), Bogotá, Colombia

    Daniela García Aguirre

  9. Global Green Growth Institute Colombia, Bogotá, Colombia

    Ivan Darío Valencia

  10. Georges Lemaître Earth and Climate Research Centre, Earth, and Life Institute, University of Louvain, Louvain, Belgium

    Eric F. Lambin

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Contributions

A.E., P.R.F., L.M., M.R., G.C.D. and E.F.L. conceived the study. A.E., S.M., A.G.F.K. and D.G.A. collected data. A.E., P.R.F., S.M., A.G.F.K. and E.F.L. performed qualitative coding analysis. A.E., D.G.A., P.R.F. and E.F.L. performed environmental policy integration analysis. A.E., P.R.F. and A.G.F.K. visualized data. A.E., L.M., P.R.F., M.R., G.C.D. and E.F.L. conceptualized the statistical analyses. A.E. performed statistical analyses. A.E., P.R.F., D.G.A., I.D.V. and M.R. wrote the policy implications section. E.F.L., M.R. and G.C.D. supervised the study. A.E., P.R.F. and E.F.L. wrote the manuscript with contribution from all the authors.

Corresponding author

Correspondence to Alejandra Echeverri.

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The authors declare no competing interests.

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Peer review information

Nature Ecology & Evolution thanks Gwen Iacona, Yves Zinngrebe and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 The individual growth curves for each policy theme indicate two main growth periods, one between 1993 and 2014, and another between 2015 and 2020.

Individual panels (a-o) represent the cumulative number of policies per policy theme. The vertical red lines in these graphs represent 3 key years in sustainable development policy. First is 1987 as the year when the ‘Our Common Future’ report from the Brundtland Commission was published. Second is 1992, when the United Nations Conference on Environment and Development, also known as, Earth Summit was held. Third is 2015, when two events occurred. The first, being the Paris Agreement on Climate Change, and the second being the United Nations Sustainable Development Summit, that released the 2030 agenda for sustainable development with its 17 Sustainable Development Goals.

Source data

Extended Data Fig. 2 Policy integration of biodiversity in environmental pollution policies.

Thirty-seven policies are at the intersection of biodiversity and environmental pollution. The graph shows the policy sequencing over time, since the first policy introduced in 1974. Icons refer to policy instruments. Policies denoted with a ($) sign indicate policies with budgets assigned to them or with a fiscal mechanism in place. The legal hierarchy is structured in the y-axis, where the top half of the graph indicates the policies with legal character, and the bottom half those without legal character.

Extended Data Fig. 3 The total number of policies governing ecosystems at different scales indicates that forests have the highest number of policies governing at the national scale.

Different colors indicate the governance scales as outlined in the figure key. The height of the bars represents the total number of policies governing each ecosystem.

Source data

Supplementary information

Supplementary Information

Supplementary Table 1, Supplementary results and discussion

Reporting Summary

Peer Review File

Source data

Source Data Fig. 1

Count data representing the number of policies per code and subcode.

Source Data Fig. 2

Panel A contains the data for cumulative frequencies for instrument types across the years. Panel B contains the data for the spider chart with cumulative frequencies per policy theme in 3 time intervals. Panel C contains the data for cumulative frequencies for policies issued by each lead actor across the years. Panel D contains the data for cumulative frequencies for policies issued with different conservation paradigms across the years.

Source Data Fig. 3

Panel A contains the contingency table reporting the count data at the intersection of policy instrument and lead actor. Panel B contains the contingency table reporting the count data at the intersection of policy instrument and governance scale. Panel C contains the contingency table reporting the count data at the intersection of policy instrument and ecosystem type.

Source Data Fig. 4

Panel A contains the source data for the Sankey diagram 1. Panel B contains the source data for the Sankey diagram 2. Panel C contains the source data of the IPBES threats.

Source Data Extended Data Fig. 1

Source data for cumulative frequency plots for each policy theme are in each tab to reproduce 17 panels (A–Q).

Source Data Extended Data Fig. 3

Contingency table data at the intersection of the number of policies governing different ecosystems at different governance scales.

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Echeverri, A., Furumo, P.R., Moss, S. et al. Colombian biodiversity is governed by a rich and diverse policy mix. Nat Ecol Evol 7, 382–392 (2023). https://doi.org/10.1038/s41559-023-01983-4

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