Meeting global commitments to conservation, climate, and sustainable development goals requires consideration of synergies and tradeoffs among targets. We evaluate the spatial congruence of ecosystems providing globally high levels of nature’s contributions to people, biodiversity, and areas with high development potential across several sectors. We find that conserving 44% of global land area through protection or sustainable management could provide 90% of current levels of ten of nature’s contributions to people and meet minimum representation targets for 26,709 terrestrial vertebrate species. This finding supports recent commitments by national governments under the Global Framework for Biodiversity to conserve at least 30% of global lands and waters. More than one-third of areas required for conserving nature’s contributions to people and species are also highly suitable for agriculture, renewable energy, oil and gas, mining, or urban expansion. This indicates potential conflicts among conservation, climate and development goals.
Biological Sciences - Article
Mapping the planet's critical areas for biodiversity and people
https://doi.org/10.21203/rs.3.rs-2786809/v1
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Nature provides a diversity of benefits to people, including climate mitigation, hazard risk reduction, water quality regulation, provision of food and raw materials, and recreation1–3. To date, international targets related to biodiversity conservation, climate, and sustainable development have largely ignored nature’s many other contributions to people due to lack of spatially explicit, quantitative data4,5. Building on previous work1, we map spatial priorities for ten of nature’s contributions to people as well as Area of Habitat for 26,709 birds, mammals, reptiles and amphibians6. Here we show that conserving or sustainably managing 44% of global land area could provide 90% of current levels of nature’s contributions to people and achieve minimum species representation targets. Other effective area-based conservation measures, including strengthening tenure of Indigenous peoples and local communities, will be critical for achieving targets because only 18% of prioritized areas are currently protected. More than one-third of prioritized areas also have high suitability for commercial agriculture, renewable energy, oil and gas, mining, or urban expansion. If carefully planned and sited, development can be compatible with conservation7. Because prioritized areas and development pressures are not evenly distributed among countries, international coordination and financial support will be essential for achieving targets.
Rapid transformation of ecosystems combined with anthropogenic climate change are driving global declines in biodiversity and nature’s contributions to people (NCP)8. While habitat conversion for economic development has raised standards of living for many, the loss of NCP has negatively impacted millions of people3. In an attempt to prevent further losses of biodiversity and NCP, nearly 200 nations have recently committed to conserving 30% of lands and waters by 2030 under the Kunming-Montreal Global Biodiversity Framework4 and similar national targets (e.g. “America the Beautiful”5). Other proposals call for conserving 50% of global land area, or “half earth”, to safeguard biodiversity and avert the most devastating effects of climate change9,10. National governments have also initiated efforts to achieve targets related to the Paris Climate Agreement and the UN Sustainable Development Goals. There is a growing recognition that biodiversity, climate, and development goals are intertwined: addressing climate change is necessary to avoid further losses of biodiversity8, nature-based solutions are essential for mitigating and adapting to climate change11, and conserving natural assets and addressing climate are both foundational for achieving sustainable development12. At the same time, ensuring food, energy, and livelihood security will require carefully planned development of agriculture, energy, urban expansion, and other sectors13.
Building on recent work1, we present maps of joint priorities for ten important NCP as well as terrestrial biodiversity. We include one NCP with global benefits, due to its importance for mitigating climate change: vulnerable terrestrial ecosystem carbon storage, defined as the proportion of total ecosystem carbon that could be lost in a typical disturbance event14. We also include nine NCP with local or regional benefits1: coastal risk reduction, flood regulation, sediment retention (important for reducing erosion and improving water quality), nitrogen retention for water quality regulation, crop pollination, fodder production for livestock (including grazing), fuel wood production, timber production, and access to nature (important for recreation as well as physical and mental well-being). All NCP are “realized,” either as an end use or benefit (e.g., timber harvest or livestock fodder production), or, where possible given current data, weighted by number of beneficiaries (e.g. count of people downstream, or count of people with reduced risk from coastal storm surge). We define areas providing 90% of all ten NCP as “critical natural assets”1.
As a measure of biodiversity, we use “Area of Habitat” (AOH) for each of 26,709 terrestrial vertebrate species15. We conducted a global spatial optimization at a spatial resolution of 10 km to identify “prioritized areas” that simultaneously achieve target levels of all ten NCP and also achieve minimum species representation targets. Species targets were consistent between all scenarios, and were intended to represent both restricted-range and wide-ranging species, following previous studies6,15–17. To identify potential areas of conflict between conservation and development objectives, we overlaid the prioritized areas with estimates of development potential across major sectors including commercial agriculture, renewable energy, mining, oil and gas, and urban expansion7. We also calculated the percentage of prioritized areas that currently fall within protected areas and other effective area-based conservation measures (OECM) areas.
Prioritized areas for nature’s contributions to people and biodiversity
Our results indicate that conserving 44% of global land area, excluding Antarctica could provide 90% of current levels of ten NCP and meet minimum representation targets for 26,709 terrestrial vertebrate species, if spatially optimized and coordinated among nations (Fig. 1). If prioritized together, slightly more land area (8%) is required to achieve all species targets, while also providing 90% of NCP, demonstrating the opportunity for synergies between maintaining NCP and conserving biodiversity (Fig. 1).
Critical natural assets for NCP include portions of the Amazon and Congo basins, Papua New Guinea and Indonesia, and southeastern Australia, due in part to high levels of vulnerable ecosystem carbon storage14 (Fig. 2A). Other notable regions include the Himalayas (important for water quality, flood regulation, and fuelwood production), the Andes (grazing and water quality), western Europe (nature access, pollination and grazing), New Zealand (water quality, grazing), Caribbean islands (water quality, pollination, nature access, and grazing), and the Yangtze basin (water quality, flood regulation, pollination, fuelwood, and timber).
Prioritized areas for both NCP and species include many of the regions mentioned above, including species-rich areas within the Amazon and Congo basins (Fig. 2B). Prioritized areas also include regions with unusually high endemism or restricted-range species, including Papua New Guinea, New Zealand, eastern Madagascar, the Andes and Himalayan mountains, montane regions of Central America, western India, and islands in Oceania (Fig S7, Table S7).
While species targets can be achieved with relatively little additional land area, the inclusion of species targets changes priority areas when compared to areas prioritized solely for NCP (Fig. 3). For example, sparsely vegetated arid lands (e.g. southwestern USA, western Australia) and northern latitudes (e.g. northern Canada and Russia), contain important biodiversity but relatively lower levels of the NCP modeled here due to sparse vegetation and/or lower human population densities. The NCP included in this analysis, which can be modeled with globally available data, tend to be concentrated in regions with dense vegetation and in areas accessible to, or upstream of, human populations1.
Only 18% of the prioritized areas for NCP and biodiversity are currently protected, based on the World Database on Protected Areas (WDPA), which includes other effective area-based conservation measures (OECM)18 (Fig. S3). We ran a separate prioritization analysis to identify areas required to achieve targets beyond the current system of protected areas and OECM, by “locking in” such areas to the prioritization results (Fig. S4). We found that conserving or sustainably managing an additional 34% of land area beyond the current system of protected areas and OECM (49% of global land area) would be required to provide 90% of current levels of NCP and meet species representation targets (Fig. S5).
Threats from development
More than one-third (37%) of areas prioritized for NCP and biodiversity also have high development potential for commercial agriculture, renewable energy, oil and gas, or urban expansion (equivalent to 16% of global land area) (Fig. 3, Table S6). Only 11% of such areas are currently protected, which may result in future conflicts between development and conservation objectives. The renewable energy sector (concentrated solar power, photovoltaic solar, wind, and hydropower) comprises the largest share of areas with high development potential globally7, and overlaps with 10% of prioritized areas (4% of global land area) (Fig 3). Though renewable energy is needed to avert catastrophic effects of climate change and can be implemented in ways that are compatible with NCP19 our findings underscore the need to carefully plan, site, and evaluate tradeoffs with other objectives20,21. Constraining new projects to already cleared or degraded lands, for example, would reduce conflicts between renewable energy and conservation goals19,21,22.
Areas with high suitability for commercial agriculture (including crops and biofuels) overlap with 7% of prioritized areas (3% of global land area) (Fig. 3). While agricultural expansion can support food security, if not implemented sustainably, conversion of natural ecosystems to croplands may undermine nature’s other contributions23. These include benefits to existing agricultural systems such as pollination, sediment retention, and flood mitigation. Policies promoting food security should therefore consider the contributions of both croplands as well as natural and semi-natural habitats to food systems. If implemented carefully, agricultural development can be compatible with the ongoing provision of NCP and biodiversity conservation24. Mining, which overlaps with 6% of prioritized areas (3% of global land area), and oil and gas development (5% of prioritized areas, 2% of global land area) could create more localized but severe hazards for NCP and species and are a cause for concern in parts of Western Asia, North America, and the Amazon.
Six of the world’s fourteen biomes (broad habitat types) contain prioritized areas that are highly suitable for development across at least one-quarter of their area, making these habitats of special concern. These include mangroves (32%), temperate broadleaf and mixed forests (30%), flooded grasslands and savannas (30%), tropical and subtropical dry broadleaf forests (29%), temperate conifer forests (27%), and temperate grasslands, savannas and shrublands (25%) (Fig. S9, Table S8).
Geographically, prioritized areas overlap with areas of high development potential across 31% of the land area of Oceania, 25% of South America, 23% of Europe, 20% of North America, 17% of Africa, 15% of Australia, and 11% of Asia (Table S8). These patterns are driven by the co-occurrence of NCP, species, and development pressures. For example, areas with dense vegetation (such as tropical forests) in proximity to, or upstream of, human populations may be simultaneously important for biodiversity, NCP (carbon storage, provision of timber and fuelwood, access for recreation), and also highly suitable for certain kinds of development, such as palm oil.
The co-occurrence of NCP, biodiversity and development pressures aren’t limited to forests, however. New Zealand, for example, contains large numbers of endemic species as well as extensive areas important for grazing, pollination, and sediment retention, all overlapping with areas of high potential for expansion by oil and gas, mining, and renewable energy. European countries such as Ireland, the UK, Estonia, Latvia, Finland, and the Netherlands contain extensive areas important for grazing, access to nature, and sediment and nitrogen retention that overlap with areas with high development potential for agriculture, renewable energy, and mining.
Our study offers a starting point to identify global targets and broad priority regions for conservation and sustainable use investments. We build on a history of efforts to define "global biodiversity hotspots"25 by adding two important new considerations: the diverse contributions of nature to people and potential conflicts with expansion of agriculture, energy, extractive industries, or urban development projects. To our knowledge, this is the most comprehensive effort to bring together data on NCP, biodiversity, and development pressures at a global scale, and our results lend support to proposals to conserve at least 30% of the planet by 2030.
By providing consistent and comparable data across countries, global maps can support the establishment of international targets and highlight where broad action may be most impactful26. Finer-scale information related to conservation feasibility, costs, and the rights and preferences of local people is also needed to identify appropriate interventions for particular locations. Conservation and development should always be implemented in partnership with Indigenous peoples and local communities to respect local sovereignty, diverse values of nature, and to result in more effective and equitable outcomes27. Because strict protection precludes human use and access, which are necessary for the ongoing provision of many NCP, other effective area-based conservation measures, including strengthening Indigenous and local land tenure, will be essential for achieving targets.
The large disparities between regions in terms of levels of NCP, biodiversity, and development pressures highlights the importance of international cooperation. Countries with larger conservation responsibilities but without sufficient domestic resources will require access to international funding from their wealthier peers, via mechanisms such as the Global Environmental Facility. For example, the Global Biodiversity Framework includes a target of increasing biodiversity related funding from developed countries to developing countries to at least USD 30 billion per year by 20304.
Our estimate of the proportion of global land area needed to achieve species and NCP targets is conservative, given that estimates based on biodiversity conservation alone range from 34-44%6,28. Biodiversity priorities could be complemented with additional taxa such as plants29 amd marine taxa30 as well as data on evolutionary processes, species traits31, intactness of ecosystems32, and ecosystem representation33. Advances in NCP modeling and data availability will soon make it possible to model additional NCP at global scales34. Projected future demand for NCP due to changes in climate and population dynamics could help identify NCP that will become critical in the future2. More powerful computing resources could advance our understanding of finer-scale priorities.
To date, international agreements such as the recently adopted Global Biodiversity Framework and the Paris Climate Agreement have largely ignored nature’s many other contributions to human life and well-being. Given that every person on the planet benefits from nature, and ~87% of the global population, 6.4 billion people, benefit locally from critical natural assets1, conservation and climate targets should more explicitly incorporate the many other benefits that nature provides to humanity. Future global negotiations must move beyond considering biodiversity, climate, and sustainable development in isolation to jointly consider the multitude of nature’s contributions to life, livelihoods, and cultures on earth.
Data Availability
All final outputs and code are available, by request, on Zenodo: https://zenodo.org/record/7803242. Once published, outputs and code will be made open access. Data on nature’s contributions to people are available from https://osf.io/5nfje and can be visualized at https://bit.ly/3Jk8vDo.
Acknowledgments
We thank Christopher Barrett, Pamela Collins, Alexandra Goldstein, Catherine Kling, Jeffrey Milder, Monica Noon, and Will Turner for their insight and intellectual contributions.
Funding
The Marcus and Marianne Wallenberg Foundation (RAN, RCK)
Betty and Gordon Moore (RAN, PRR, DH)
Conservation International (RAN, PRR, DH)
The Cornell University Department of Natural Resources and the Environment (RAN)
The Cornell Lab of Ornithology (RAN, MSM, ADR)
NSF Graduate Research Fellowship 2019067768 (RAN)
The Natural Capital Project (RCK, RPS)
SPRING (RCK, RPS)
EC Horizon 2020 ReSET project grant 101017857 (MM, AS)
UKRI/F4B Nature Finance Seed Corn Grant (MM, AS)
Environment and Climate Change Canada (ECCC) (JOH)
Nature Conservancy of Canada (JOH, RS)
Liber Ero Fellowship (RS)
The Nature Conservancy (CMK, JRO)
One Earth (CMK, JRO)
Author contributions
Conceptualization: RAN, RCK, DH, SP, ADR
Methodology: RAN, RCK, RS, RPS, MSM, PRR, MM, AS, CMK, JRO, JAJ, SP, JOH
Software: RPS, MM, JOH
Formal analysis: RAN, RCK, RS, MSM, PRR
Data curation: RAN, RS, MSM
Writing – original draft: RAN, RCK, ADR
Writing – review & editing: RAN, RCK, RS, MSM, PRR, MM, AS, CMK, JRO, JAJ, JK, SP, JOH, DH, ADR
Visualization: RAN
Supervision: RAN, RCK, ADR
Competing interests
Authors declare that they have no competing interests.
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Nature’s Contributions to People
We included global maps of ten NCP including vulnerable ecosystem carbon storage, coastal risk reduction, flood regulation, sediment retention, nitrogen retention, crop pollination, fodder production for livestock (including grazing), fuel wood production, timber production, and access to nature1. Vulnerable ecosystem carbon storage is mapped as the above-ground and below-ground ecosystem carbon lost in a ‘typical’ disturbance event2. This includes terrestrial and coastal (mangrove, salt marsh, seagrass) ecosystem carbon pools (aboveground, belowground, and soils), based on what carbon is likely to be released if the ecosystem were converted. Coastal protection, sediment retention, nitrogen retention, and crop pollination were modeled using InVEST models, adapted to be run at global scales1,3,4. Fodder production for livestock, timber production, fuelwood production were modeled using Version 3 of Co$ting Nature5,6. Flood regulation was modeled using Version 2 of WaterWorld7–9. Access to nature is expressed as the number of urban and rural people10 within one hour travel of natural and semi-natural habitat, taking the least-cost path (by foot, road, rail or boat) across a friction layer11. Data sources, units of measurement, and the original spatial resolution of each modeled NCP are summarized in Table S1. Full model details are available in the supplementary materials from Chaplin-Kramer et al.1
All NCP are “realized,” either as an end use or benefit (e.g., timber harvest or livestock fodder production per unit area of land), or, where possible given current data, weighted by number of beneficiaries. Beneficiaries include people downstream of habitats providing flood regulation or water quality benefits, coastal populations protected from coastal storm surge, or people within a certain travel time of natural habitats. We attributed all NCP to the natural and semi-natural land cover classes providing the benefit, excluding developed lands (croplands and urban areas) and unvegetated areas (Table S3). We excluded Antarctica due to lack of data on NCP from that continent.
Biodiversity (Area of Habitat, AOH)
As a measure of biodiversity, we used species “Area of Habitat” (AOH) for 26,709 terrestrial vertebrate species12. AOH are based on species range maps from IUCN but refined using habitat preferences and elevational limits from IUCN Red List data12. AOH are more specific than extent-of-occurrence (EOO) which can overestimate species range sizes13. AOH areas “exclude areas of unsuitable habitat from each species’ range, which reduces commission errors and more closely approximates the actual occurrence of the species”14.
Species AOH ranges were produced for 10,774 species of birds, 5,219 mammals, 4,462 reptiles and 6,254 amphibians with available IUCN range polygon data12. Species range polygons obtained from the IUCN Red List spatial data portal15 and the Birdlife International spatial data zone16 were first filtered for ‘extant’ range then rasterized to a global one km grid in the Eckert IV equal area projection. Individual species range rasters were then modified to only include land cover classes that match the habitat associations for each species. Habitat associations were obtained from the IUCN Red List species habitat classification scheme and were matched to ESA land cover classes for the year 201817. ESA land cover classification data was aggregated from its native 300 m resolution to match the global ten km grid using a majority rule. Species ranges were additionally filtered so that only areas within a species accepted elevational range were included. Global elevation data derived from SRTM was obtained from WorldClim v. 218. For bird species, seasonal range codes 1-3 (1=year-round; 2=breeding range; 3=non-breeding range) were processed individually and stored as separate range files where applicable.
Spatial optimization
We used integer linear programming techniques19 to estimate how much land area is needed to provide different levels of NCP and/or achieve species representation targets. We identified areas that provide the highest value across all ten NCP using spatial prioritization procedures. Specifically, we generated prioritizations using the minimum set formulation of the reserve selection problem, and completing optimization procedures using integer linear programming techniques20. These procedures were completed using the prioritizr R package20,21 and Gurobi22.
The objective function (equation 1) is to minimize the cost of selected planning units. Constraints (equation 2) are used to ensure that the representation targets are met.
To explore the land area required to maintain different levels of NCP provision, we ran the optimization using 19 different targets ranging from 5% to 95% of total NCP value, across all ten NCP, at 5% increments. To explore how much additional area is required to conserve biodiversity, we generated an additional 19 scenarios which added species representation targets, using data on extent of suitable habitat, or Area of Habitat (AOH) data for mammals, reptiles, amphibians, and birds12. We followed previous studies which established targets based on species’ habitat size, with the goal of ensuring that both restricted-range and wide-ranging species are represented12,20,23,24. We assigned a 100% threshold to species with less than 1,000 km2 of suitable habitat, a 10% threshold to species with more than 250,000 km2 of suitable habitat, and log-linearly interpolated thresholds for species with intermediate amounts of suitable habitat. We also assigned a cap of 1,000,000 km2 for species with a large amount of suitable habitat (>10,000,000 km2). These targets should be considered minimum representation targets as they do not account for habitat connectivity, ecological intactness25, species traits26, evolutionary processes, ecosystem representation 27, genetic diversity, or other important dimensions of biodiversity.
Separately, we also ran scenarios in which protected areas from the World Database on Protected Areas28 were “locked in” to the spatial prioritization (that is, protected areas were required as part of the solution in each scenario). This allowed us to estimate how much additional land area would be required to achieve NCP and species representation targets, beyond the current system of protected areas (Figs. S5-S6, Table S4).
For the scenarios that included NCP (but not species), we ran the optimizations globally and at a spatial resolution of 2 km. Due to computational constraints and the large number of species (26,709), 10 km was the finest resolution at which we were able to run optimizations for scenarios that contained both NCP and species targets. NCP models assume low or no provision of NCP in sparsely vegetated areas (e.g. deserts) and human-modified habitats (e.g. croplands.) However, many species rely on deserts and modified landscapes. After running the optimizations, we masked the 10 km optimization results using natural and semi-natural landcover data29 at 2 km. This allowed us to more precisely map and quantify the natural and semi-natural habitats providing NCP, and to align our results with NCP-only scenarios run at a higher spatial resolution1. As a second step, we re-included the prioritized areas for species (at 10 km) to ensure that species that rely on deserts and human-modified habitats were included.
In the present study, solutions which achieved all targets in the least amount of land area (minimum land area) are used in place of a minimum cost objective. Current globally available data on costs (e.g. Naidoo and Iwamura30) have limitations and were considered unsuitable for this analysis. Proxy indicators such as gridded GDP were also considered a poor measure of cost, since costs of safeguarding NCP and biodiversity may be poorly correlated with national or local estimates of economic productivity. Instead of a measure of cost, therefore, we separately include data on development potential across 14 major sectors, as areas with high value for NCP and biodiversity that also have high suitability for development may have high opportunity costs for alternative land uses.
For subsequent analyses, we focused on “prioritized areas”, defined as areas providing 90% of current levels of all ten NCP which also meet all species targets. We overlaid prioritized areas with data on development potential to examine overall conversion risk as well as risks from major sectors.
Development Potential Index
We also integrated spatially-explicit estimates of the potential for habitat conversion by development across several economic sectors31. To create an development pressure map (Fig. S7), we used published Development Potential Indices (DPIs)31 for renewable energy (concentrated and photovoltaic solar power, wind power, and hydropower), oil and gas (conventional and unconventional oil and gas), mining (coal, metallic and non-metallic mining), and commercial agriculture (crop and biofuels expansion). For urban expansion pressure, we created an Urban Pressure Index (UPI) based on global urban growth projections from 2020 to 205032 (see Supplementary Materials for details on the UPI).
DPIs are global, spatially-explicit 1-km resolution maps that depict the suitability of land for potential expansion development expansion by agriculture, renewable energy, oil and gas, mining, and urbanization. Each DPI has standardized 0–1 values that account for sector-specific land constraints that restrict development (e.g., suitable land cover, slope); land suitability for sector expansion based on resource availability (sector-specific yields); and siting feasibility of new development (e.g., ability to transport resources or materials, access to demand centers, existing development, and other economic costs associated with resource siting). For each of the 14 DPIs, we binned the range of values represented into six categories based on standardized z-score ranges to characterize development pressure as “very low” (≤10th percentile), “low” (>10th – 25th percentile), “medium-low” (>25th – 50th percentile), “medium-high” (>50th – 75th percentile), “high” (>75th – 90th percentile), and “very high” (>90th percentile). We calculated z-scores by mean-standardizing values per country to capture national-level domestic demand coupled with global-level demand likely to drive national-level resource extraction to occur within each countries’ highest development suitability for that resource. To identify regions of high development pressure (HDP), we retained the highest value within the 14 classified DPIs (Fig. S7A) and then selected the “high” and “very high” classified cells (i.e., values 5 and 6) (Fig. S7B).
Protected areas
We evaluated the extent to which currently protected areas and other effective area-based conservation measures (OECM) might achieve targets and maintain NCP, and how much additional land area might require conservation or stewardship. For this step, we compiled spatial data to delineate the boundaries of protected areas and other conservation areas worldwide. To achieve this, we obtained the World Database on Protected Areas (WDPA) and the World Database on Other Effective Area-Based Conservation Measures (WDOECM)28. We prepared these data for analysis following standard practices (using the wdpar R package)33. Briefly, we (i) excluded sites within an unknown or proposed designation, (ii) excluded UNESCO Biosphere Reserves34, (iii) transformed the site boundaries to avoid numerical issues associated with geometries that cross the dateline, (iv) reprojected the data to an equal-area coordinate reference system (World Behrmann; ESRI:54017), (v) replaced sites represented as point localities with circular reserves matching their reported area35, (vi) removed slivers and (vii) excluded marine protected areas. Additionally, throughout this process, we implemented routines to detect and repair invalid geometries.
We included WDPA and OECM areas in our analysis in two different ways. First, to calculate the percentage of prioritized areas that are currently protected or effectively conserved, we overlaid prioritized areas with the combined WDPA and OECM areas (Fig. S3). Second, to calculate how much additional land area would be required to achieve NCP and species representation targets, beyond the current system of protected areas, we ran separate spatial optimization scenarios in which WDPA and OECM areas were “locked in” (Fig. S4). Because protected areas and OECM do not necessarily overlap with prioritized areas, locking them in to the prioritization solutions results in larger total land areas to achieve targets (Fig S5).
Methods References
1. Chaplin-Kramer, R. et al. Mapping the planet’s critical natural assets. Nat Ecol Evol 7, 51–61 (2022).
2. Noon, M. L. et al. Mapping the irrecoverable carbon in Earth’s ecosystems. Nat Sustain 5, 37–46 (2022).
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There is NO Competing Interest.
- ExtendedDataMappingtheplanetscriticalareasforbiodiversityandpeople6April2023.docx
Extended Data Figures S1 to S9 and Tables S1 to S6