Area of Habitat (AOH) is “the habitat available to a species, that is, habitat within its range”. It complements a geographic range map for a species by showing potential occupancy and reducing commission errors. AOH maps are produced by subtracting areas considered unsuitable for the species from their range map, using information on each species’ associations with habitat and elevation. We present AOH maps for 5,481 terrestrial mammal and 10,651 terrestrial bird species (including 1,816 migratory bird species for which we present separate maps for the resident, breeding and non-breeding areas). Our maps have a resolution of 100 m. On average, AOH covered 66 ± 28% of the range maps for mammals and 64 ± 27% for birds. The AOH maps were validated independently, following a novel two-step methodology: a modelling approach to identify outliers and a species-level approach based on point localities. We used AOH maps to produce global maps of the species richness of mammals, birds, globally threatened mammals and globally threatened birds.
Area of Habitat
Sample Characteristic - Organism
Mammalia • Aves
Sample Characteristic - Environment
Background & Summary
Knowing the distribution of species is crucial for effective conservation action. However, accurate and high-resolution spatial data are only available for a limited number of species1,2. For mammals and birds, the most comprehensive and widely used global distribution dataset is the set of range maps compiled as part of the assessments for the International Union for Conservation of Nature (IUCN) Red List. These represent each species’ distributional limits and tend to minimize omission errors (i.e. false absences) at the expense of commission errors (i.e. false presences)3,4. Therefore, they often contain sizeable areas not regularly occupied by the species.
Maps of the Area of Habitat (AOH; previously known as Extent of Suitable Habitat, ESH) complement range maps by indicating potential occupancy within the range, thereby reducing commission errors5. AOH is defined as ‘the habitat available to a species, that is, habitat within its range’5. These models are produced by subtracting areas unsuitable for the species within their range, using information on each species’ associations with habitat and elevation5,6,7,8. Comprehensive sets of AOH maps have been produced in the past for mammals6 and amphibians7, as well as subsets of birds8,9. The percentage of a species’ range covered by the AOH varies depending on the methodology used to associate species to their habitats, and their habitats to land-cover, the coarseness of the range map, the region in which the species is distributed, and the species’ habitat specialization and elevation limits5. For example, Rondinini et al.6 found that, when considering elevation and land cover features for terrestrial mammals, the AOH comprised, on average, 55% of the range. Ficetola et al.7 obtained a similar percentage when analyzing amphibians (55% for forest species, 42% for open habitat species and 61% for habitat generalists). Beresford et al.8 found that AOH covered a mean of 27.6% of the range maps of 157 threatened African bird species. In 2019, Brooks et al.5 proposed a formal definition and standardized methodology to produce AOH, limiting the inputs to habitat preferences, elevation limits, and geographical range.
AOH production requires knowledge of which habitat types a species occurs in and their location within the range1. Information on habitat preference is documented for each species assessed in the IUCN Red List10, following the IUCN Habitats Classification Scheme11. However, the IUCN does not define habitat classes in a spatially explicit way, therefore, we used a recently published translation table that associates IUCN Habitat Classification Scheme classes with land cover classes12. Species’ elevation limits were also extracted from the IUCN Red List.
We developed AOH maps for 5,481 terrestrial mammal species and 10,651 terrestrial bird species (Fig. 1). For 1,816 bird species defined by BirdLife International as migratory, we developed separate AOH maps, for the resident, breeding, and non-breeding ranges, according to the migratory distribution of the species (Fig. 2). The maps are presented in a regular latitude/longitude grid with an approximate 100 m resolution at the equator. On average, the AOH covers 66 ± 28% of the geographical range for mammals and 64 ± 27% for birds. We used the resulting AOH maps to produce four global species richness layers for: mammals, birds, globally threatened mammals and globally threatened birds13 (Fig. 3).
The AOH maps presented in this paper are more useful for some purposes than global species distribution models, as they reduce and standardize commissions14. They are especially useful for not well-known and wide-range species. However, we note that for well-known species alternative sources may have more accurate distributions15. Moreover, AOHs are affected by the bias and errors of the underlying data, especially relevant errors associated with documentation of species’ habitats and elevations, and the translation of habitats into land cover classes, given that habitat is a complex multidimensional concept that is challenging to match to land-cover classes12, and that the current version of the IUCN Habitat Classification Scheme on IUCN’s website is described as a draft version11.
The AOH maps have multiple conservation applications5,16,17, such as assessing species’ distributions and extinction risk, improving the accuracy of conservation planning, monitoring habitat loss and fragmentation, and guiding conservation actions. AOH has been proposed as an additional spatial metric to be documented in the Red List5, and is used for the identification of Key Biodiversity Areas18.
We produced maps for extant species associated with at least one terrestrial habitat in the IUCN Habitat Classification Scheme11. We excluded a total of 342 species of mammals and 495 species of birds (6.2% and 4.6% out of 5,481 and 10,651 species, respectively). These comprised 135 mammals and 168 birds exclusively associated with marine habitats (i.e., marine neritic, marine oceanic, marine deep ocean floor, marine intertidal or marine coastal/supratidal), 29 mammals exclusively associated with caves and subterranean habitats, 131 mammals with no associated habitat codes, 8 mammals and 162 birds categorized as Extinct, 1 mammal and 5 birds categorized as Extinct in the Wild, 12 mammal and 142 birds that are restricted to small islands not included in the land-cover map we used, and 26 mammals and 18 birds that had null AOH, caused by errors in the coding of habitat and elevation19.
Species may have more than one range polygon, coded according to presence (the species is or was in the area), origin (why and how the species is in the area) and seasonality (seasonal presence of the species in the area)20. We used as a base for the AOH maps a predetermined subset of the IUCN Red List range21 polygons for each species15. Similarly to the Global Standard for the Identification of Key Biodiversity Areas Guidelines22, we selected range polygons with extant and probably extant presence; native, reintroduced, and assisted colonization origin; and resident seasonality for non-migratory species (all mammals and the 8,979 non-migratory birds). For migratory birds (1,816 species), we kept separated the ranges for breeding (1,446 species), non-breeding (1,550 species) and a combination of resident and uncertain (1,290 species) seasonality. We provide an R script to merge the AOH sub-maps into a single composite map for each species. We could not add separate AOH maps for migratory mammals to our dataset, as IUCN Red List provided insufficient data on migratory mammals’ range in different seasons17.
For 18 mammal and 22 bird species categorized as Critical Endangered, there were no presence polygons coded as extant or probably extant. To assist the conservation of these species, we produced AOH maps using the possibly extinct polygon for these taxa.
AOH maps are produced by subtracting unsuitable areas from range maps, using data on each species’ associated habitat (Fig. 4). Habitat and elevation information was obtained from the IUCN Red list Version 2020-221. As habitats in the IUCN Red List are not spatially explicit, although we note the existence of recently published maps23, we used a recently published translation table12 based on the Copernicus Global Land Service Land Cover (CGLS-LC100)24,25 and the European Space Agency Climate Change Initiative land cover 2015 (ESA-CCI)26. We developed the AOH maps based on CGLS-LC100 as CGLS-lC100 has a higher resolution and accuracy than ESA-CCI. CGLS-LC100 is in a regular latitude/longitude grid (EPSG:4326) with the ellipsoid WGS 1984 and a grid resolution of 1°/1008 or approximately 100 m at the equator, defining the resolution of the AOH maps. The translation table presented the relation between each habitat in the IUCN Classification Scheme and each land-cover class as a continuous variable. To create a binary table of association or non-association, Lumbierres et al.12 proposed three potential thresholds based on the tertiles of the positive association values of the table. We produced maps for the three proposed thresholds and evaluated the ratio of AOH area to range area. As the threshold increased, the ratio decreased, and the results were more similar to previous AOH maps6. Dahal et al.19 evaluated these three thresholds and corroborated that an increase in the threshold did not reduce the performance of the AOH maps during validation. Therefore, we present the maps produced using the highest threshold (odds ratio >1.7). Species’ elevation limits were extracted from the IUCN Red List21. To subtract the parts of the range outside the elevation limits, we used the Shuttle Radar Topography Mission (SRTM)27 map, resampled at the resolution of the CGLS-LC100 (Fig. 4).
One of the main complexities of this analysis was the large amount of data generated in the process. Therefore, the AOH maps were produced using the GRASS GIS28 software, which allows processing of large amounts of raster data efficiently. The AOH production procedure consisted of four steps, following Rondinini et al.6: (1) Transforming the habitat codes of each species into land cover classes using the translation table12. (2) Creating a base map that combines the information on land cover and elevation. (3) Creating reclassification files containing the information on land cover and elevation preferences for each species. (4) Reclassifying the base map based on the reclassification files to create the AOH for each species. Once the AOH were produced, we calculated richness maps by stacking the AOH maps, producing maps representing the number of species at each grid of 100 × 100 m. Migratory species’ AOH maps were merged before calculating richness to ensure each species counted once.
The AOH data, including tables and maps, are stored in the Dryad Open Access Repository https://doi.org/10.5061/dryad.02v6wwq4829. The data are organized by taxonomic Class with zipped folders by taxonomic Order. In the case of birds, we separated migratory species from non-migratory species. We added a folder containing the richness maps for each class of all species and of globally threatened species. In each folder, we included a table with information about the excluded species, indicating the reason for exclusion(Mammls_list_excluded.csv, Birds_list_excluded.csv); and a table with the included species, the model prevalence (AOH range ratio) and the results of the validation developed by Dahal et al.19 Mammals_list_AOH.csv, Birds_list_AOH.csv). For migratory birds, we included a table specifying which maps (breeding, non-breeding and resident) each species has (Birds_Migratory_list_AOH.csv) and code to merge the different parts of the AOH (merge_migratory_AOH_code.R).
The accuracy of the AOH maps was assessed using a novel methodology developed by Dahal et al.19 and full details of the validation are provided there. This methodology allowed validation of AOH maps for species with or without point localities. Previous AOH maps were validated only using point localities and polygons of occurrence6,7,8, leaving some of the AOH maps unvalidated.
Our method employed a two-step approach. The first step identified potential systematic errors in the AOH maps using a modelling approach. This approach flagged 178 and 64 AOH maps for birds and mammals respectively that were carefully studied to identify the sources of potential errors. These potential errors were caused by inaccuracies in species’ elevation limits, habitat coding or the translation table12 used to assign habitat to land cover. Work is currently underway to address these issues, and improved AOH maps will be available in the future for download at https://www.iucnredlist.org/resources/grid/spatial-data. A complete list of flagged maps can be found in Dahal et al.19.
The second step used point localities to validate the maps at the species level. Point data for mammals were downloaded from GBIF30 and for birds from eBIRD31. Dahal et al.19 applied several filters to ensure that only high-accuracy points were used for the validation. Only points with coordinate uncertainty lower than 300 m were retained for mammals and only stationary points were selected for birds as they have a coordinate uncertainty of less than 30 m. Also, it was ensured that points fell inside the mapped distribution and that at least 10 point were available for each species. A temporal filter of 2019–2020 was applied because the point localities from 2005–2018 were used to calibrate the habitat-land cover model by Lumbierres et al.12. This resulted in 4889 birds (46% of all bird species) and 420 mammals (8% of all mammal species) that had enough available point locality data for validation. For mammals, this represented 157 species more than in a previous set of AOH6 maps published in 2011.
To validate the AOH maps, the proportion of points localities falling inside the AOH (point prevalence) was compared with the AOH/range ratio (model prevalence). If point prevalence exceeded model prevalence, the AOH was assumed to be better than a random distribution within the species’ range6. We found that AOH maps were better than random for 95.9% bird and 95% of mammal species, among those with validation data. The unavailability of point locality data for half of bird species and most mammal species remains a major limitation of the validation analysis. However, the first step of the method allowed us to assess at least the general soundness of AOH maps for species that did not have suitable point localities for validation.
The maps are presented in raster byte GeoTIFF format. The values of the maps are 1 for the AOH area and Null for the background. The geographical extent of each map is defined by the species’ range. Each species map is presented separately with the species binomial name, and the genus and specific epithet separated by an underscore. For migratory birds we produced three different maps, that are coded using, R, B and N for resident, breeding and non-breeding AOH maps, respectively. We present code written in R to merge the different AOH maps for migratory species according to the needs of the user. For species with null AOH we recommend using the mapped range.
The base map is the map that is reclassified to produce the AOH. Each cell value is a combination of land cover and elevation, where the three first digits represent land cover and the three last digits elevation in m/10.
The GRASS reclass function has a specific format for the reclassification instructions. The script produces reclass files to apply to the base map in GRASS to produce maps of area of habitat for terrestrial species. It reads a file that contains land cover associations, with the following column headers: species name, one column per land cover class (with numeric column names for land cover; e.g., 10, 20, 210), and two columns representing elevation range (elevation_min and elevation_max). If the elevation range for a species is unrecorded, it is set to 0–9000 m.
AOH is confined inside the geographical range. The geographical range maps can be downloaded from https://www.iucnredlist.org for mammals, and http://datazone.birdlife.org/species/requestdis for birds. The ranges are imported into GRASS and rasterized. The ranges are used to mask the area outside the species distribution. Inside the non-masked areas, the base map is reclassified using the reclassification file.
The code to produce the AOH is derived from code produced by Rondinini et al.6. AOH maps are produced reclassifying a base map that contains information on elevation and land cover. The geographical range maps are used to mask the areas outside the distribution of the species. Each species has a reclassification file that indicates which land cover classes and elevations are suitable. To transform the habitat information into land cover we used the translation table12. The code is both in GRASS and R.
Rondinini, C. & Boitani, L. Mind the map: trips and pitfalls in making and reading maps of carnivore distribution. in Carnivore Ecology and Conservation A Handbook of Techniques 31–46, https://doi.org/10.1093/acprof:oso/9780199558520.003.0003 (Oxford University Press, 2013).
Rondinini, C., Stuart, S. & Boitani, L. Habitat suitability models and the shortfall in conservation planning for African vertebrates. Conservation Biology 19, 1488–1497 (2005).
Di Marco, M., Watson, J. E. M., Possingham, H. P. & Venter, O. Limitations and trade-offs in the use of species distribution maps for protected area planning. Journal of Applied Ecology 54, 402–411 (2017).
Ficetola, G. F. et al. An evaluation of the robustness of global amphibian range maps. J Biogeogr 41, 211–221 (2014).
Brooks, T. M. et al. Measuring Terrestrial Area of Habitat (AOH) and Its Utility for the IUCN Red List. Trends Ecol Evol 34, 977–286 (2019).
Rondinini, C. et al. Global habitat suitability models of terrestrial mammals. Philosophical Transactions of the Royal Society B: Biological Sciences 366, 2633–2641 (2011).
Ficetola, G. F., Rondinini, C., Bonardi, A., Baisero, D. & Padoa-Schioppa, E. Habitat availability for amphibians and extinction threat: A global analysis. Divers Distrib 21, 302–311 (2015).
Beresford, A. E. et al. Poor overlap between the distribution of Protected Areas and globally threatened birds in Africa. Anim Conserv 14, 99–107 (2011).
Tracewski, Ł. et al. Toward quantification of the impact of 21st-century deforestation on the extinction risk of terrestrial vertebrates. Conservation biology 30, 1070–1079 (2016).
IUCN. Documentation standards and consistency checks for IUCN Red List assessments and species accounts. Version 2. vol. 2 (2013).
IUCN. Habitats Classification Scheme (Version 3.1). (2012).
Lumbierres, M. et al. Translating habitat class to land cover to map area of habitat of terrestrial vertebrates. Conservation Biology e13851, https://doi.org/10.1111/COBI.13851 (2021).
Mair, L. et al. A metric for spatially explicit contributions to science-based species targets. Nature Ecology & Evolution 2021 5:6 5, 836–844 (2021).
Boitani, L. et al. What spatial data do we need to develop global mammal conservation strategies? Philosophical Transactions of the Royal Society B: Biological Sciences 366, 2623–2632 (2011).
Rondinini, C., Wilson, K. A., Boitani, L., Grantham, H. & Possingham, H. P. Tradeoffs of different types of species occurrence data for use in systematic conservation planning. Ecol Lett 9, 1136–1145 (2006).
Strassburg, B. B. N. et al. Global priority areas for ecosystem restoration. Nature 586, 724–729 (2020).
Hanson, J. O. et al. Global conservation of species’ niches. Nature 580, 232–234 (2020).
IUCN. A Global Standard for the Identification of Key Biodiversity Areas, Version 1.0. (IUCN, 2016).
Dahal, P. R., Lumbierres, M., Butchart, S. H. M., Donald, P. F. & Rondinini, C. A validation standard for area of habitat maps for terrestrial birds and mammals. Geosci. Model Dev 15, 5093–5105 (2022).
IUCN. Mapping standards and data quality for the IUCN Red List Categories and Criteria. Version 1.16. Prepared by Red List Technical Working Group 16, 30 (2018).
IUCN. The IUCN Red List of Threatened Species. Version 2020-2. The IUCN Red List of Threatened Species. Version 2020-2. https://www.iucnredlist.org. Downloaded on 09 May (2020).
KBA Standards and Appeals Committee. Guidelines for using a Global Standard for the Identification of Key Biodiversity Areas. Version 1.0. Prepared by the KBA Standards and Appeals Committee of the IUCN Species Survival Commission and IUCN World Commission on Protected Areas. (2019).
Jung, M. et al. A global map of terrestrial habitat types. Sci Data 7, 1–8 (2020).
Buchhorn, M. et al. Copernicus Global Land Service: Land Cover 100m: collection 3: epoch 2015: Globe 2020 https://doi.org/10.5281/zenodo.3939038 (2020).
Buchhorn, M. et al. Copernicus Global Land Service: Land Cover 100m: Version 2.02 Globe 2015–2019: Product User Manual. Version V2. 0.2 Preprint at, https://doi.org/10.5281/zenodo.3938963. (2019).
ESA (European Space Agency). Land Cover CCI Product User Guide Version 2. Tech. Rep. Preprint at (2017).
USGS EROS Archive. Digital Elevation - Shuttle Radar Topography Mission (SRTM) 1 Arc-Second Global. Preprint at, https://doi.org/10.5066/F7PR7TFT (2019).
GRASS Development Team. Geographic Resources Analysis Support System (GRASS) Software, Version 7.8.5. (2020).
Lumbierres, M. et al. Area of Habitat maps for the world’s terrestrial birds and mammals. Dryad. https://doi.org/10.5061/dryad.02v6wwq48 (2022).
Robertson, T. et al. The GBIF integrated publishing toolkit: Facilitating the efficient publishing of biodiversity data on the internet. PLoS One 9 (2014).
Cornell Lab of Ornithology. eBird Basic Dataset. Version: EBD_Jan 2020, Ithaca, New York, 2020. (2020).
This research is part of the Inspire4Nature Innovative Training Network, funded by the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska‐Curie grant agreement no. 766417. MDM acknowledges support from the M.U.R. Rita Levi Montalcini programme.
The authors declare no competing interests.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Lumbierres, M., Dahal, P.R., Soria, C.D. et al. Area of Habitat maps for the world’s terrestrial birds and mammals. Sci Data 9, 749 (2022). https://doi.org/10.1038/s41597-022-01838-w