Data for: A policy mix approach to biodiversity governance in Colombia
Data files
Aug 05, 2022 version files 328.71 KB
-
Echeverri_2022_database_for_logistic_regression.csv
-
Echeverri_2022_Frequencies_BPD.csv
-
Echeverri_2022_IPBES_main_threats_to_biodiversity_in_the_Americas.csv
-
Echeverri_2022_Policy_analysis_database.xlsx
-
Echeverri_2022_Policy_mix_DB.csv
-
Echeverri_2022_Source_data_Sankey1.csv
-
Echeverri_2022_Source_data_Sankey2.csv
-
README.txt
Abstract
We lack an understanding of how diverse policymakers interact to govern biodiversity. Taking Colombia as a focal case, we asked: (i) What is the composition of today’s policy mix?; (ii) How has the policy mix evolved over time?; (iii) How do policies differ among actors and ecosystems?; and (iv) Does the policy mix address the primary threats to biodiversity? We found 186 biodiversity-related policies that govern multiple ecosystems, use different instruments, and evolve as a mix to address the main threats to biodiversity (i.e., agriculture and aquaculture, biological resource use). We notice policy gaps in the governance of invasive species. Biodiversity policy integration into some sectoral policies, such as climate change 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 become part of the policy mix.
Methods
We had personal communication with people working in public sector agencies, bi(multi)lateral development agencies, environmental NGOs, and private sector leaders who pointed us to master lists of policies that they issue or implement in their respective roles. For each actor we sampled policies as follows:
Public sector-We identified the following actors as leaders (i.e., agenda setters, funders, or policy initiators) of Colombian public policies: (a) central government, (b) subnational and regional governments, and (c) Indigenous Peoples and Local Communities. The collective property rights of ethnic groups are protected in the Colombian constitution, granting them authority to lead or co-lead policies that govern their territories. Additionally, (d) municipalities (3rd administrative tier) issue their own plans and strategies for conservation planning. We only included the strategies issued by the top 4 largest municipalities (Bogotá, Medellín, Barranquilla, Cali) as the innovators of urban sustainability policies that are mirrored by smaller cities49.
We used a snowball sampling approach, starting with a master list of the environmental policies listed on the Ministry of Environment website50. These included international treaties adopted by Colombia, laws, decrees, resolutions, and municipal planning strategies. We began with the country’s first comprehensive national environmental policy established in 1959, and included policies introduced through 2020. We included biodiversity-specific policies, such as endangered species regulations, protected areas, payments for ecosystem services, and habitat banks, among others11. We also applied broader inclusion criteria to consider any public environmental policy with clear influence on biodiversity in all its forms. This included climate, pollution, and sectoral (e.g., agriculture, forestry, mining, oil, and gas) policies targeting terrestrial and coastal ecosystems. We excluded strictly marine policies, as they are often done in coordination with other countries.
As recurring policies are periodically superseded (e.g., the national development plan changes after each presidential election), we only included their most recent versions in our database. We only included policies led by the legislative and executive branches of government and excluded policies from the judicial branch, such as supreme court rulings, although admittedly several of them have important policy implications.
Private sector and supply chain initiatives—For policies initiated and funded by private actors, we included those in the forestry, agriculture, energy and mining sectors, as these sectors are the main ones affecting biodiversity in Colombia52. We included certifications led by international corporations and non-profits that were mentioned in the state of sustainable markets report (2020) and in the state of sustainability initiatives review for the extractive economy53 that operate in Colombia. We included certifications that apply to individual commodities (e.g., C.A.F.E Starbucks for coffee), as well as those that certify multiple commodities (e.g., Rainforest Alliance).
The Colombian private sector is organized by “gremios empresariales”, which are clusters of businesses or trade associations that are formally regulated together54. The largest business cluster in the country is ANDI, which is a conglomerate of 1400 businesses that represent 50% of the national GDP32. We coded the policies led by ANDI as clusters of projects implemented in key regions (e.g., Amazon, Caribbean, Andean). We excluded projects and initiatives led by individual companies. Although many companies have in-house, corporate sustainability strategies, we only included policies that were issued by multiple companies in the same sector, or by various sectors adopting the same sustainability standards.
Bi(Multi)lateral development sector—To identify key development banks and cooperation agencies active in Colombia, we consulted a list of donors and projects (n=988) from Aid Atlas, representing US$56.6 billion in development finance sent to Colombia between 2002 and 2018, out of which $1.36 billion was specifically designated as biodiversity finance55. The largest donors were World Bank, Inter-American Development Bank, Agence Française de Développement (France), GIZ (Germany), USAID (USA), and the United Nations Global Environment Facility. We only considered financial strategies that were co-developed with the Colombian government, such as bank country strategies that determine investment priorities.
Sampling bias: We were not able to estimate the proportion of policies sampled in our study, as there is no information about the total number of public, private, and multilateral policies that govern Colombia. Thus, our sampling bias is based on documents that are available online and that officials working on different agencies were able to identify. While our policy list is likely not complete, it is, to our knowledge the most comprehensive one. We were able to identify 126 more policies than the BIOFIN report56, which is the most recent assessment of Colombian biodiversity policies.
Usage notes
This includes the following files:
Policy_mix_database.xlsx: A database in Excel format with the 186 policies included in the study. Each row represents and individual policy, and columns are information about the unique policy ID (ranging from ID_1 to ID_186), name of the policy, url links to the original policy, policy goals, years the policies were introduced, lead actors, scale of governance, among others.
Policy_mix_DB.csv: A csv file of binary trait data. Each row represents a unique policy, with columns being the unique policy ID, and dummy variables for the eight axial codes in the study. Columns B-G refer to the biodiversity scale subcategories; Columns H-P refer to ecosystem subcategories; Columns Q-U refer to Policy instrument subcategories; Columns V-AA refer to conservation paradigm subcategories; Columns AB-AR refer to Policy theme subcategories; Columns AS-AW refer to governance scale subcategories; Columns AX-BC refer to lead actor subcategories; Column BD refers to the year when the policy became effective; Columns BE-BN refer to biodiversity threats sucategories.
Frequencies_BPD.csv: A csv file with the contingency table of dummy variables in the Policy_mix_DB.csv file and the count (number of policies) of policies for each variable.
BPD_for_logistic_regression.csv: A csv file of the database in long format used for figures and files
Sankey1.csv: Source data for the Figure 4 panel A
Sankey2.csv: Source data for the Figure 4 panel B
IPBES.csv: Source data for the Figure 4 panel C
Echeverri_main_analysis_biodiversity_policy_mix: R script for all quantitative data analysis and for making figures 1,2,3 and all supplementary figures
Echeverri_et_al_Figure4.jpynb: Script with Python code in a jupiter notebook for making Figure 4