Biodiversity & Nature-related data
This page is dedicated to Biodiversity data, and more broadly, nature-related dependancies, risks, impacts and opportunities in the context of sustainable economics and finance.
Country level Biodiversity index
A more specific description of the data than "Biodiversity index" would be "Risk index representing the risks tied to the degradation and the dependencies of nature-related services". Thus, it focuses mainly on the financial materiality of these ecosystemic services and does not address corporate impacts, nor the overall state of the biodiversity/ecosystems.
For additional information, please refer to the corresponding paper: Huang et al. (2024) “Biodiversity Risk, Firm Performance, and Market Mispricing”, SSRN 4765039.
Users are required to cite as follows: “Research work based on Huang et al. (2023), supported by the EquipEx Pladifes (ANR-21-ESRE-0036) and hosted at the Institut Louis Bachelier".
Country level biodiversity index
by Huang et al. is licensed under CC BY 4.0
Biodiversity Data Inventory
The Biodiversity Data Inventory aims to consolidate and document existing biodiversity datasets. Its purpose is to support research on the financial impacts of biodiversity and to better understand how biodiversity loss influences financial and economic activities. Categories represent types of land or water use linked to biodiversity, ranging from areas exploited for food, resources, and livestock (fishing grounds, cropland, grazing land, forest products) to human-occupied spaces (built-up land), and forest areas that provide essential carbon uptake.
| Data Source | Content | Temporal coverage | Spatial coverage | Description | Potential use | Category |
|---|---|---|---|---|---|---|
| A dataset for pollinator diversity | Pollinator abundance, diversity, and plant interactions. | 2005-2017 | province | Contains 67,954 individual pollinator records, including 937 morphospecies across 105 families, covering bees, wasps, butterflies, moths, and flies. | Assess interactions between plants and pollinators. | Species |
| Biodiversity Intactness Index | BII summaries under various scenarios. | 1970-2050 | global, region, country, state | Uses the PREDICTS database of local biodiversity measures at thousands of sites worldwide. Statistically models how total abundance of organisms and compositional similarity respond to land use and related pressures. | BII gauges ecosystem health by tracking native species abundance, helping companies identify biodiversity impacts and associated risks. | Indicator |
| BioTIME | Species identities and abundances in ecological assemblages over time. | 1874-2018 | global | Contains over 12 million records of almost 50,000 species from over 600,000 locations, supporting understanding and prediction of biodiversity change. | Quantify biodiversity trends over time to link ecosystem changes with financial and operational risks. | Species |
| BirdLife | Threatened and non-threatened bird species. | 2018-2024 | global, region, country | Provides bird species IUCN Red List category, extent of occurrence, migratory status, and distribution. | Access global IBA and KBA data, along with species distribution and threat-status maps, to assess corporate impacts on vulnerable biodiversity and flag operations in high-risk areas for regulatory, reputational, or legal challenges. | Species |
| CEFAS | Marine biodiversity datasets in the UK. | early 20th century-2024 | country | Comprises 5,500 datasets including fish, species migration data, habitat and sediment information, ecosystem change indicators, and human activities such as marine litter. | Use species abundance, distribution, and habitat condition data to compute biodiversity metrics and carbon sequestration potential (e.g., blue carbon ecosystems, saltmarshes, seagrasses). | Species, fishing grounds |
| Center for Sustainability and the global Environment | Global land use and cropland. | Varies | global | Contains modeled built-up areas (based on nighttime lights) and observed built-up areas (based on IGBP land cover data). | Track conversion of natural or semi-natural land to built-up areas, highlighting where corporate operations displace or fragment ecosystems. Overlaying facilities and supply chains onto these layers identifies reliance on intact habitats and regions facing regulatory, reputational, or ecosystem-service pressures. | Cropland, land use |
| Corine Land Cover | Land cover for France. | 1990, 2000, 2006, 2012, 2018 | country | Based on visual interpretation of satellite images, supported by additional data. Maps land parcels of at least 25 hectares (5 ha for changes) and minimum 100 m width, provided they are homogeneous in land cover type. Mapping is done at 1:100,000 scale using a three-level hierarchical nomenclature with 44 land cover classes. | Map corporate activities onto natural habitats to reveal land conversion, ecosystem dependence, and biodiversity-related risks. | Land cover |
| Corinne | Global land cover types (forests, grasslands, croplands, lakes, wetlands). | 1990-2018 | region | Provides pan-European CORINE Land Cover inventory for 44 thematic classes for the 2018 reference year. The dataset has a Minimum Mapping Unit (MMU) of 25 hectares (ha) for areal phenomena and a Minimum Mapping Width (MMW) of 100 m for linear phenomena and is available as vector and as 100 m raster data. | Use CORINE time-series land cover data to track corporate impacts, dependencies on ecosystems, and nature-related risks. | Land use/land cover |
| CPC Pollinator Database | Plants and their pollinators. | nan | country | Contains information on plant-pollinator interactions, focusing on rare and endangered plant species, including confirmed and potential pollinators. | Identify pollinator-plant relationship. | Species |
| Cropland area database by country circa 2020 | Global cropland area estimates. | 2020 | global | Global coverage with data for 221 countries and territories, and 34 regional aggregates. Provides mean cropland area estimates with uncertainties, and cropland area categorized by six agreement classes. | Assess land use changes, habitat fragmentation, and agricultural impacts on biodiversity. Integrating with species distribution models and conservation tools improves understanding of agricultural expansion effects. | Cropland |
| CropPol | Crop flower visitors, pollinators, and pollination measurements. | 2001-2005, 2006-2010, 2011-2015, 2016-2020 | region | Includes measurements from 202 crop studies covering 3,394 field observations, 2,552 yield measurements (berry mass, number of fruits, fruit density), and 47,752 insect records from 48 commercial crops. | Evaluate pollinator impacts on crop yields across regions and time periods. | Species |
| CSIRO | Biodiversity Habitat Index: spatial distribution of habitat loss and expected impacts on terrestrial biodiversity. | 2000, 2005, 2010, 2015, 2020 | global | BHI estimates the proportion of diversity that can be maintained in a given area. | Assess financial exposure through changes in natural ecosystem conditions and ecosystem services (e.g., water provisioning, pollination, soil fertility, habitat stability) that affect operations, asset productivity, or regulatory liability. | Species |
| CSIRO | Multiple categories: agricultural, earth, environmental, economic sciences. | 2012-2025 | global, country | Contains several datasets on forest ecosystem structure, function, and biodiversity, including BILBI (global biodiversity indicators at 1 km resolution) and ALA (Australian plants, animals, and fungi repository). | BILBI provides biodiversity indicators, and ALA offers species occurrence data. | Species |
| Digital Observatory for Protected Areas | Coverage of terrestrial and marine ecoregions by protected areas. | 2015-2019 (only marine in 2019) | global | Provides information on protected areas and protection percentages. | Map company operations near protected or key biodiversity areas to reveal reliance on natural capital and potential biodiversity-related risks. | Marine ecoregions coverage |
| Documenting pollinator communities, floral hosts, and plant-pollinator interactions in Pacific Northwest US | Pollinator communities, floral hosts, and plant-pollinator interactions in the Pacific Northwest. | 2014-2016 | region | Focuses on both managed and wild pollinator species and their interactions with various plant species within agricultural landscapes. | Evaluate pollinator species richness and abundance and analyze plant-pollinator network structures. | Species |
| Earth Data, ORNL DAAC | LUH2 (land use Harmonisation Version 2) | 850?-2019 | global | Includes 0.25-degree gridded global maps of fractional land use states, transitions, and management practices. | Track corporate land-use changes over time, linking ecosystem conditions to business dependencies and regional risk hotspots. | Forest carbon up take |
| Earth Stat | Cropland and pasture areas, harvested area and yield, GHG emissions, climate impacts, yield trends, water depletion, nutrient applications, carbon stocks, crop allocations. | 1995-2005 | global | Provides cropland and pasture area, harvested area, yield for 175 crops, and greenhouse gas emissions from croplands. | Use land use and crop distribution data to evaluate habitat fragmentation and its effects on biodiversity. | Cropland |
| EarthEnv | Global 1-km consensus land cover. | 2005? | global | Integrates multiple global remote sensing-derived land-cover products to provide consensus information on the prevalence of 12 land-cover classes at 1 km resolution. | Map company assets against species richness, endemism, and habitat integrity layers to quantify reliance on healthy ecosystems. | Land cover |
| FAO | Forest area, growing stock, and carbon statistics. | 1990-2020 | global, region, country | Provides statistics on forest areas, regenerated and planted forest areas, and other forest metrics. | FRA data reveal corporate dependence on forests and ecosystem services, highlighting areas with potential biodiversity-related risks. | Land use/land cover |
| FAO | Crops and livestock products | 1961-2025 | global, region, country | Provides data for all countries and crops and livestock commodities, including production, harvested areas, and numbers of live and slaughtered animals. | Link commodity production to habitat loss and ecosystem dependence to highlight biodiversity pressures and related corporate risks. | Crops |
| ForC | Forest carbon stocks and fluxes, site info, stand characteristics. | 1934-2015 | global | Global forest carbon database with information about sites and disturbance history. | Examine relationships between forest carbon dynamics and biodiversity. | Forest carbon up take |
| GBIF (global Biodiversity Information Facility) | Species occurrence records, taxonomy, geospatial coordinates. | 1800-2023 | global | Aggregates biodiversity data from institutions worldwide, offering a comprehensive repository for species distribution and occurrence information. | Compute potential biodiversity indices using ecological and land-use data. | Species |
| Geo-Wiki | Land cover validation, field size, and forest management mapping. | 2009, varies | global | Includes land cover validation, agricultural field size mapping, and forest management mapping. | Use accurate land cover and forest management data for habitat quality evaluation and species distribution modeling. | Land use/land cover |
| GLAD (global Land Analysis and Discovery) | Global land cover and land use change. | 2000-2020 | global | Quantifies changes in forest extent and height, cropland, built-up lands, surface water, and perennial snow and ice from 2000 to 2020 at 30-meter resolution. | Apply GLAD alerts to track tree-cover loss and land-use change, revealing corporate impacts on biodiversity and associated risks. | Land cover |
| Global Bee Interaction Data | Compilation of bee-plant interaction records. | nan | global | Provides interaction types such as pollination events, floral visitation, and nesting behaviors. | Analyze species richness, interaction diversity, and network structures to derive indices reflecting ecosystem health. | Species |
| global Dynamic Land Cover | Land cover and land use changes. | 2015-2019 | global | Detailed view of land cover at three classification levels, including continuous field layers that provide proportional estimates for vegetation and ground cover. | Use GDLC annual land-cover change maps to assess corporate impacts, ecosystem reliance, and potential environmental or regulatory risks. | Forest, land use/land cover |
| Global Forest Aboveground Carbon stocks and fluxes | Global gridded forest aboveground carbon stocks and potential fluxes. | 2018-2021 | global | Global gridded estimates of forest aboveground carbon stocks and potential fluxes. | Estimate forest aboveground carbon stocks and fluxes and integrate with species distribution models and ecological datasets. | Forest carbon up take |
| Global Forest Ecosystem structure and function data for carbon balance research | Forest ecosystem carbon budgets and traits. | nan | global | Encompasses carbon budget variables (fluxes and stocks) and ecosystem traits (biomass, leaf area index) for 529 forest sites across eight biomes. | Use standing biomass, leaf area index, and age to model habitat quality and assess ecosystem services. | Forest carbon up take |
| global Forest Watch | Forest changes, land cover, land use, climate, and biodiversity status. | 2000-2020 | global, region, country, state | Provides key statistics on global forests, including rates of forest change, extent, and drivers of deforestation. | GFW provides near real-time forest loss and degradation data to reveal corporate impacts and dependence on forest ecosystem services. | Climate, fires, forest change, land use |
| global Land and Bioversity Data | Land use change impacts on biodiversity trends. | 2005, 2010, 2021, 2024 | global | Contains land use and biodiversity data. | Track land-use changes and protected area trends to assess corporate impacts on biodiversity and ecosystem-service risks. | Land use/land cover |
| Global Pollinator Database | Interactions between 80 crops and 256 pollinator species. | nan | global | Includes more than 80 agricultural crops and over 250 pollinator species, focusing on the type and frequency of pollination interactions. Aggregates observations from scientific literature and field studies. | Analyze crop dependencies on animal pollinators and estimate extinction-related risks. | Land use, species |
| GLOBIO (global Biodiversity model for policy support) | Mean Species Abundance (MSA) under land use/cover scenarios. | 1990-2020 | global | Provides scenario-based projections of biodiversity indicators under different land-use and policy scenarios. | GLOBIO uses MSA and ecosystem-service scenarios to quantify corporate biodiversity footprints and related financial exposures. | Land use, species |
| GLOBIO (global Biodiversity model for policy support) | Nitrogen impact data, urban ecosystem service assessments, hunting impact data. | 2017, 2018+projections | global | Quantifies effects of human-induced pressures on biodiversity via the MSA indicator, reflecting the average abundance of original species relative to undisturbed ecosystems. | Use the MSA indicator as a proxy for ecosystem integrity and to inform other biodiversity indices and tools (e.g., GBS) for evaluating sectoral and regional biodiversity footprints. | Land use, species |
| HILDA+ | Global land use change. | 1960-2019 | global | Shows annual global land use/cover and transitions from 1960 to 2019 at 1 km resolution, derived from satellite data and national statistics. | HILDA+ maps corporate-driven land-cover changes to assess biodiversity footprints, ecosystem dependencies, and associated risks. | Land use/land cover |
| IBGE | Estimated annual soy production, yield, and exploited area. | 2006-2019 | country | Provides estimated annual soy production, annual soy yield. | IBGE data track agricultural land-use, yields, and trends to assess corporate impacts on biodiversity and ecosystem-service dependencies. | Crops |
| IIASA Global Forest Database | Forest biomass and carbon stocks. | 2005? | global | Presents FAO’s Global Forest Resources data at 0.5-degree resolution, including forest growing stock, above- and below-ground biomass, and carbon stock. | Integrate ecological and species distribution data to model corporate impacts and dependencies. | Forest carbon up take and general information about forests |
| IUCN | Threatened species | 2023 | global | Global standard for assessing conservation status of species. Provides assessments (Critically Endangered, Endangered, Vulnerable, etc.) based on population size, trends, range, and threats, including range maps. | Use the Red List to identify threatened species and ecosystems, quantifying corporate biodiversity footprints and related risks. | Species |
| LPI (Living Planet Index) | Vertebrate population time-series. | 1970-2024 | global | The Living Planet Database contains tens of thousands of vertebrate population time-series worldwide. | LPI tracks long-term wildlife population trends to assess biodiversity degradation, ecosystem-service risks, and corporate exposure. | Species |
| Map of Life | Global biodiversity data: species distributions, indicators, conservation metrics, richness, endemism, predictive models. | 2000-2024 | global, country | Aggregates and models biodiversity information for near-global coverage of species distributions, changes, and conservation priorities. Combines observational data, ecological modeling, and conservation science. | Map biodiversity hotspots and overlay corporate impacts to assess footprints and spatial risk. | Species |
| MapBiomas | Land use and land cover classifications, including urban, agriculture, and natural vegetation. | 1985-2023 | country | Provides annual, high-resolution spatial data on deforestation, land use change, wetlands, mangroves, and grasslands. | MapBiomas links company assets with land-use data to quantify biodiversity footprints and associated risks. | Land use |
| Ocean Biodiversity Information System | Marine organism diversity, distribution, and abundance. | 1900-2025 | global | Includes global ocean biodiversity and biogeographic data. | Assess corporate impacts and dependencies on marine biodiversity, mapping ecological risks and supporting scenario analysis. | Species |
| Our world in data | Global forest share and land coverage. | 1990-2020 | global, country | Provides tables, maps, or charts on forest distribution and coverage. | Use forest area and loss data to evaluate corporate biodiversity footprints, ecosystem reliance, and related risks. | Forest, land use/land cover |
| Plant community data | Species counts (trees, herbs). | Collected in 1949-1951. | region | Includes sampling locations, species lists, herb and shrub data, tree data, and resampled site coordinates. | Map corporate sites onto Whittaker plots to assess ecological sensitivity, species diversity, and biodiversity-related risks. | Species |
| PolLimCrop | Pollination experiments with hand supplementation and natural treatments. | 1950-2020 | global | Comprises 294 studies and 1,169 pollen supplementation experiments, providing pollen limitation values for 108 crops across 50 years and 62 countries. | Assess pollen limitation where crops receive insufficient pollination, often due to declining pollinator populations, leading to reduced yields. | Species |
| Pollination supply models | Modeled pollinator visitation rates to crops using empirical, ML, and ensemble approaches. | 2001-2023 | global | Uses CropPol database, including pollinator abundance and richness, crop varieties, and sampling methods. | Support evaluation of financial exposure to pollination service decline and quantify a company’s or asset’s dependency on biodiversity. | Species |
| Pollinator Hub | Pollination services, pollinator health, and beekeeping productivity. | depends on the dataset | global | Data depends on the dataset and may include records such as daily bee exits/entrances or nearby weather station measurements. | Simultaneously assess financial risks tied to declining pollination services (yield losses, input cost volatility) and positive biodiversity impacts of conservation measures. | Species |
| PPBio | Species occurrence, abundance, environmental, and temporal data. | 2001-2024 | region | Data are organized by site in structured grids with uniformly distributed plots, ensuring comparability across regions and time periods. | Analyze species richness, Shannon diversity, and evenness. | Species |
| Predicis+ | Data on 3,862 invertebrate species and 640 pollinators. | nan | country | Compiles occurrence records of invertebrate and plant species within agricultural landscapes, primarily in France, including standardized observations of species presence and abundance. | Evaluate the impact of soil use intensity on pollinator biodiversity. | Species |
| RAISG | Georeferenced Amazon socio-environmental data (forest coverage, protected areas). | 2020-2024 | region | Provides geospatial information on the Amazon, including indigenous territories, protected areas, and infrastructure. | RAISG provides detailed geospatial data on the Amazon, including forests, protected areas, indigenous territories, and deforestation fronts. Overlaying infrastructure such as mining, roads, and oil extraction allows businesses to quantify contributions to biodiversity loss and exposure to regulatory, social, and reputational risks. | Forest |
| Trase | Supply chain data linking commodity trade (soy, beef, palm oil) to deforestation and land-use change risks. | 2012 | global, region, country | Trase integrates customs, logistics, company ownership, and production data to model supply chains, identify sourcing regions, quantify deforestation risk in commodity exports, and trace production-consumption links. | Link commodity production areas with deforestation and habitat loss to identify regions and actors with high biodiversity risk exposure, supporting corporate biodiversity risk assessment and ESG reporting. | Crops |
| UNECE | Environmental statistics for Europe, Central Asia, and North America: land use, protection, water, forests, biodiversity, policy metrics. | 1990-2023 | region | Includes standardized indicators developed in collaboration with the UN and Eurostat. | Evaluate land use trends and pressures on ecosystems, monitor protected area extent and effectiveness, and analyze environmental governance affecting biodiversity outcomes. | Land use |
| USDA | Ground-based forest carbon stock and sink estimates. | 1990-2024 | global, region, country | Provides regional and country-level estimates of forest areas, carbon stocks, and carbon sinks based on ground measurements of trees worldwide. | Use forest carbon stock and sink data to assess corporate impacts, ecosystem dependence, and climate-related biodiversity risks. | Forest carbon up take |
| USFWS National Wetlands Inventory (USA) | Wetlands and deepwater habitat extent, type, and location. | 1977-2024 | country | Provides detailed information on national wetlands, supporting conservation and land-use planning. | Assess dependencies and impacts related to wetland ecosystems, highlighting financial risks (e.g., flood mitigation loss) and ecological impacts (e.g., habitat degradation). | Habitat, land cover |
| Victorian Government Biodiversity Data (Australia) | Species occurrences, habitat types, and conservation status. | 1990-2024 | state | Offers comprehensive biodiversity data for Victoria, aiding conservation planning and environmental assessments. | Identify biodiversity risks and impacts linked to business operations or investments, supporting double materiality assessments and ESG reporting, including in Victoria. | Land use, species |
| WRI. Global Pasture Watch | Global 30m annual maps distinguishing cultivated and natural/semi-natural grasslands with probability surfaces. | 2000-2022 | global | Global annual maps at 30 m resolution distinguish cultivated grassland from natural/semi-natural grassland, including probability surfaces for each class. | Map natural versus cultivated grasslands to identify habitat conversion, fragmentation, and associated biodiversity risks. | Grassland |
References
- Huang et al. (2024) “Biodiversity Risk, Firm Performance, and Market Mispricing”, SSRN, 4765039.
- Cardinale et al. (2012). Biodiversity loss and its impact on humanity. Nature, 486(7401), 59-67.
- Borucke et al. (2013). Accounting for demand and supply of the biosphere's regenerative capacity: The National Footprint Accounts’ underlying methodology and framework. Ecological indicators, 24, pp.518-533. doi:10.1016/j.ecolind.2012.08.005
- Lin et al. (2018). Ecological footprint accounting for countries: updates and results of the national footprint accounts, 2012–2018. Resources, 7(3), p.58. doi:10.3390/resources7030058
- Svartzman et al. (2021). A'Silent Spring'for the Financial System? Exploring Biodiversity-Related Financial Risks in France
Reports
- NGFS (2024), “Nature-related Financial Risks: a Conceptual Framework to guide Action by Central Banks and Supervisors” and “Nature-related litigation: emerging trends and lessons learned from climate-related litigation”, NGFS.
- Dasgupta, P. (2021). The economics of biodiversity: The dasgupta review. United Kingdom, Her Majesty’s Treasury: London, UK
Datasets
- Dworatzek et al. (2024) National Ecological Footprint and Biocapacity Accounts , 2024 Edition (Version 1.0), Produced for Footprint Data Foundation by York University, Ecological Footprint Initiative in partnership with Global Footprint Network.