Ecoregions, in the simplest definition, are ecosystems of regional extent. Specifically, ecoregions represent distinct assemblages of biodiversity―all taxa, not just vegetation―whose boundaries include the space required to sustain ecological processes. Ecoregions provide a useful basemap for conservation planning in particular because they draw on natural, rather than political, boundaries, define distinct biogeographic assemblages and ecological habitats within biomes, and assist in representation of Earth’s biodiversity.This dataset is based on recent advances in biogeography - the science concerning the distribution of plants and animals. The original ecoregions dataset has been widely used since its introduction in 2001, underpinning the most recent analyses of the effects of global climate change on nature by ecologists to the distribution of the world's beetles to modern conservation planning.The 846 terrestrial ecoregions are grouped into 14 biomes and 8 realms. Six of these biomes are forest biomes and remaining eight are non-forest biomes. For the forest biomes, the geographic boundaries of the ecoregions (Dinerstein et al., 2017) and protected areas (UNEP-WCMC 2016) were intersected with the Global Forest Change data (Hansen et al. 2013) for the years 2000 to 2015, to calculate percent of habitat in protected areas and percent of remaining habitat outside protected areas. Likewise, the boundaries of the non-forest ecoregions and protected areas (UNEP-WCMC 2016) were intersected with Anthropogenic Biomes data (Anthromes v2) for the year 2000 (Ellis et al., 2010) to identify remaining habitats inside and outside the protected areas. Each ecoregion has a unique ID, area (sq. degrees), and NNH (Nature Needs Half) categories 1-4. NNH categories are based on percent of habitat in protected areas and percent of remaining habitat outside protected areas.Half Protected: More than 50% of the total ecoregion area is already protected.Nature Could Reach Half: Less than 50% of the total ecoregion area is protected but the amount of remaining unprotected natural habitat could bring protection to over 50% if new conservation areas are added to the system.Nature Could Recover: The amount of protected and unprotected natural habitat remaining is less than 50% but more than 20%. Ecoregions in this category would require restoration to reach Half Protected.Nature Imperilled: The amount of protected and unprotected natural habitat remaining is less than or equal to 20%. Achieving half protected is not possible in the short term and efforts should focus on conserving remaining, native habitat fragments.The updated Ecoregions 2017 is the most-up-to-date (as of February 2018) dataset on remaining habitat in each terrestrial ecoregion. It was released to chart progress towards achieving the visionary goal of Nature Needs Half, to protect half of all the land on Earth to save a living terrestrial biosphere.Note - a number of ecoregions are very complex polygons with over a million vertices, such as Rock & Ice.

QUEST projects both used and produced an immense variety of global data sets that needed to be shared efficiently between the project teams. These global synthesis data sets are also a key part of QUEST's legacy, providing a powerful way of communicating the results of QUEST among and beyond the UK Earth System research community. This dataset contains a map of a ecosystem. This map depicts the 825 terrestrial ecoregions of the globe. Ecoregions are relatively large units of land contain ing distinct assemblages of natural communities and species, with boundaries that approximate the original extent of natural communities prior to major land-use change. This comprehensive, global map provides a useful framework for conducting biogeographical or macroecological research, for identifying areas of outstanding biodiversity and conse rvation priority, for assessing the representation and gaps in conservation efforts worldwide, and for communicating the global distribution of natural communities on earth.

The World Terrestrial Ecosystems map classifies the world into areas of similar climate, landform, and land cover, which form the basic components of any terrestrial ecosystem structure. This map is important because it uses objectively derived and globally consistent data to characterize the ecosystems at a much finer spatial resolution (250-m) than existing ecoregionalizations, and a much finer thematic resolution (431 classes) than existing global land cover products. This item was updated on Apr 14, 2023 to distinguish between Boreal and Polar climate regions in the terrestrial ecosystems. Cell Size: 250-meter Source Type: ThematicPixel Type: 16 Bit UnsignedData Projection: GCS WGS84Extent: GlobalSource: USGS, The Nature Conservancy, EsriUpdate Cycle: NoneWhat can you do with this layer?This map allows you to query the land surface pixels and returns the values of all the input parameters (landform type, landcover/vegetation type, climate region) and the name of the terrestrial ecosystem at that location.This layer can be used in analysis at global and local regions. However, for large scale spatial analysis, we have also provided an ArcGIS Pro Package that contains the original raster data with multiple table attributes. For simple mapping applications, there is also a raster tile layer. This layer can be combined with the World Protected Areas Database to assess the types of ecosystems that are protected, and progress towards meeting conservation goals. The WDPA layer updates monthly from the United Nations Environment Programme.Developing the World Terrestrial EcosystemsWorld Terrestrial Ecosystems map was produced by adopting and modifying the Intergovernmental Panel on Climate Change (IPCC) approach on the definition of Terrestrial Ecosystems and development of standardized global climate regions using the values of environmental moisture regime and temperature regime. We then combined the values of Global Climate Regions, Landforms and matrix-forming vegetation assemblage or land use, using the ArcGIS Combine tool (Spatial Analyst) to produce World Ecosystems Dataset. This combination resulted of 431 World Ecosystems classes.Each combination was assigned a color using an algorithm that blended traditional color schemes for each of the three components. Every pixel in this map is symbolized by a combination of values for each of these fields.The work from this collaboration is documented in the publication:Sayre et al. 2020. An assessment of the representation of ecosystems in global protected areas using new maps of World Climate Regions and World Ecosystems - Global Ecology and Conservation More information about World Terrestrial Ecosystems can be found in this Story Map.

Our primary aim was to assess the hypothesis that distinctive features of the patterns of vegetation change during successive Quaternary glacial–interglacial cycles reflect climatic differences arising from forcing differences. We addressed this hypothesis using 207 half-degree resolution global biome pattern simulations, for time slices between 800 ka and 2 ka, made using the LPJ-GUESS dynamic global vegetation model. Simulations were driven using ice-core atmospheric CO2 concentrations, Earth's obliquity, and outputs from a pre-industrial and 206 palaeoclimate experiments; four additional simulations were driven using projected future CO2 concentrations. Climate experiments were run using HadCM3. Using a rule-based approach, above-ground biomass and leaf area index of LPJ-GUESS plant functional types were used to infer each grid cell's biome. The hypothesis is supported by the palaeobiome simulations.

To enable comparisons with the climatic forcing, multivariate analyses were performed of global vegetation pattern dissimilarities between simulations. Results showed generally similar responses to glacial–interglacial climatic variations during each cycle, although no two interglacials or glacials had identical biome patterns. Atmospheric CO2 concentration was the strongest driver of the dissimilarity patterns. Dissimilarities relative to the time slice with the lowest atmospheric CO2 concentration show the log–linear relationship to atmospheric CO2 concentration expected of an index of ecocarbon sensitivity.

For each simulation, extent and total above-ground biomass of each biome were calculated globally and for three longitudinal segments corresponding to the major continental regions. Mean and minimum past extents of forest biomes, notably Temperate Summergreen Forest, in the three major continental regions strongly parallel relative tree diversities, hence supporting the hypothesis that past biome extents played an important role in determining present diversity.

Albeit that they reflect the climatic consequences only of the faster Earth system components, simulated potential future biome patterns are unlike any during the past 800 ky, and likely will continue to change markedly for millennia if projected CO2 concentrations are realised.

The RESOLVE Ecoregions dataset, updated in 2017, offers a depiction of the 846 terrestrial ecoregions that represent our living planet. View the stylized map at https://ecoregions2017.appspot.com/ or in Earth Engine. Ecoregions, in the simplest definition, are ecosystems of regional extent. Specifically, ecoregions represent distinct assemblages of biodiversity-all taxa, not just …

This dataset includes the original version of the indicative distribution maps and profiles for Ecosystem Functional Groups - Level 3 of IUCN Global Ecosystem Typology (v2.0). Please refer to Keith et al. (2020).

The descriptive profiles provide brief summaries of key ecological traits and processes for each functional group of ecosystems to enable any ecosystem type to be assigned to a group.

Maps are indicative of global distribution patterns are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Most maps were prepared using a coarse-scale template (e.g. ecoregions), but some were compiled from higher resolution spatial data where available (see details in profiles). Higher resolution mapping is planned in future publications.

We emphasise that spatial representation of Ecosystem Functional Groups does not follow higher-order groupings described in respective ecoregion classifications. Consequently, when Ecosystem Functional Groups are aggregated into functional biomes (Level 2 of the Global Ecosystem Typology), spatial patterns may differ from those of biogeographic biomes. Differences reflect the distinctions between functional and biogeographic interpretations of the term, “biome”.

A map of 73 global biome clusters, geographic areas that were grouped to optimize the global 100m land cover processing.

In order to group Earth Observation data for faster processing or adaptation of algorithms to specific regions, the 100m global land cover (CGLS-LC100) algorithm uses a Global Biome Cluster layer. The term biome cluster hereby refers to a geographic area which has similar bio-geophysical parameters and, therefore, can be grouped for processing. In other words, the biome cluster layer can be seen as an ecological regionalisation which outlines areas of similar environmental conditions, ecological processes, and biotic communities (Coops et al., 2018). There are already several global regionalisation layers existing, e.g. Ecoregions 2017 global dataset (Dinerstein et al., 2017), Geiger-Koeppen global ecozones after Olofsson update (Olofsson et al., 2012), Global ecological zones for FAO forest reporting with update 2010 (FAO, 2012). But several tests in the CGLS-LC100 workflow have shown that the existing layers did not provide the required global and continental classification accuracy. These findings go along with Coops et al. (2018) who stated that "Most regionalisations are made based on subjective criteria, and cannot be readily revised, leading to outstanding questions with respect to how to optimally develop and define them."

Therefore, we decided to develop a customized ecological regionalisation layer which performs best with the given PROBA-V remote sensing data and the specifications of the CGLS-LC100 product. It groups spectral similar areas and helps to optimize the later classification/regression to regional patterns. Input into the layer creation were well-known existing datasets which were combined, re-grouped and advanced based on prior CGLS-LC100 classification results and local mapping knowledge of the workflow developer. To ensure that this layer is clearly separable from other existing regionalisations and not mistakenly interpreted as an eco-region layer, we decide to call it biome clusters layer.

The following steps outline the global biome clusters layer generation:

Spatial union of Ecoregions 2017 dataset (Dinerstein et al., 2017), Geiger-Koeppen dataset (Olofsson et al., 2012) and Global FAO eco-regions datasets (FAO, 2012);

Regrouping and dissolving by using experience from first global CGLS-LC100 mapping results and subjective mapping experience of the developer;

Refinement of the biome clusters in the High North latitudes via incorporation of a Global tree-line layer (Alaska Geobotany Center, 2003);

Manual improvement of borders between biome clusters to reduce classification artefacts by using a DEM and mapping experience from previous projects and continental test runs;

Usage of a global land/sea mask, the Sentinel-2 tiling grid and PROBA-V imaging extent to extend the borders of the biome clusters into the sea to make sure that also small islands on the coastline are correctly processed.

When developing a regionalisation, the definition of the clusters and the boundaries that delineate them in time and space is the key challenge. Overall, the map distinguishes 73 global biome clusters.

This data set is part of a time series for the years 1700, 1800, 1900, and 2000 that provides global patterns of historical transformation of the terrestrial biosphere during the Industrial Revolution.The Anthropogenic Biomes of the World, Version 2 data set describes anthropogenic transformations within the terrestrial biosphere caused by sustained direct human interaction with ecosystems, including agriculture and urbanization. Potential natural vegetation, biomes, such as tropical rainforests or grasslands, are based on global vegetation patterns related to climate and geology. Anthropogenic transformation within each biome is approximated using population density, agricultural intensity (cropland and pasture) and urbanization. Also includes Version 1:The Anthropogenic Biomes of the World, Version 1 data set describes globally-significant ecological patterns within the terrestrial biosphere caused by sustained direct human interaction with ecosystems, including agriculture, urbanization, forestry and other land uses. Conventional biomes, such as tropical rainforests or grasslands, are based on global vegetation patterns related to climate. Now that humans have fundamentally altered global patterns of ecosystem form, process, and biodiversity, anthropogenic biomes provide a contemporary view of the terrestrial biosphere in its human-altered form. Anthropogenic biomes may also be termed "anthromes" to distinguish them from conventional biome systems, or "human biomes" (a simpler but less precise term).This data set is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).A compliant implementation of WMS plus most of the SLD extension (dynamic styling). Can also generate PDF, SVG, KML, GeoRSS

This contains the Tortonian data-model hybrid global map of vegetation (figure 6B of Pound et al., 2011). Please remember to cite the original journal article when using it.

For full details on the construction of this global biome map for 11.6-7.25 million years ago, please see:

Pound, M.J., Haywood, A.M., Salzmann, U., Riding, J.B., Lunt, D.J. and Hunter, S.J., 2011. A Tortonian (late Miocene, 11.61–7.25 Ma) global vegetation reconstruction. Palaeogeography, Palaeoclimatology, Palaeoecology, 300 (1-4), pp.29-45. https://doi.org/10.1016/j.palaeo.2010.11.029

The Conservation Science Program of the World Wildlife Fund (WWF-US) has completed an ecoregion-based assessments of the status of biodiversity around the world. Building on previous efforts, and incorporating data collected by more than 1,500 biologists, bio-geographers, and other experts around the world over the past several years, scientists at WWF-US (Olson et al., 2001) have produced a new map which divides the terrestrial world into 14 biomes and eight biogeographic realms containing 867 ecoregions. The new map -- Terrestrial Ecoregions of the World -- is more than four times the 193 terrestrial ecoregions depicted on the most detailed global bio-geographic maps to date. Instead of being defined by political boundaries, each ecoregion is distinguished by its shared ecological features, climate, and plant and animal communities. This detailed map of global biodiversity is well-suited for identifying areas of outstanding biodiversity and representative communities for conservation.

Terrestrial Ecoregions of the World is available online as an interactive map at [http://www.worldwildlife.org/wildworld/] and for download at [http://www.worldwildlife.org/science/data/terreco.cfm]. Descriptions and photographs of ecoregions of the world are also available online.

WWF’s Global 200 project analyzed global patterns of biodiversity to identify a set of the Earth's terrestrial, freshwater, and marine ecoregions that harbor exceptional biodiversity and are representative of its ecosystems.

We placed each of the Earth's ecoregions within a system of 30 biomes and biogeographic realms to facilitate a representation analysis. Biodiversity features were compared among ecoregions to assess their irreplaceability or distinctiveness. These features included species richness, endemic species, unusual higher taxa, unusual ecological or evolutionary phenomena, and the global rarity of habitats.

This process yielded 238 ecoregions--the Global 200--comprised of 142 terrestrial, 53 freshwater, and 43 marine priority ecoregions.

Effective conservation in these ecoregions would help conserve the most outstanding and representative habitats for biodiversity on this planet.

This is a MaxEnt model map of the global distribution of the seagrass biome. Species occurrence records were extracted from the Global Biodiversity Information Facility (GBIF), United Nations Environment Programme-World Conservation Monitoring Centre (UNEP-WCMC) Ocean Data Viewer and Ocean biogeographic information system (OBIS). This map shows the suitable habitats for the seagrass distribution at global scale.

Citation: Jayathilake D.R.M., Costello M.J. 2018. A modelled global distribution of the seagrass biome. Biological Conservation. https://doi.org/10.1016/j.biocon.2018.07.009

Use Constraints: Creative Commons Attribution 4.0 Unported (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/.

Free to (1) copy and redistribute the material in any medium or format, (2) remix, transform, and build upon the material for any purpose, even commercially. You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Ecoregions, in the simplest definition, are ecosystems of regional extent. Specifically, ecoregions represent distinct assemblages of biodiversity―all taxa, not just vegetation―whose boundaries include the space required to sustain ecological processes. Ecoregions provide a useful basemap for conservation planning in particular because they draw on natural, rather than political, boundaries, define distinct biogeographic assemblages and ecological habitats within biomes, and assist in representation of Earth’s biodiversity.This dataset is based on recent advances in biogeography - the science concerning the distribution of plants and animals. The original ecoregions dataset has been widely used since its introduction in 2001, underpinning the most recent analyses of the effects of global climate change on nature by ecologists to the distribution of the world's beetles to modern conservation planning.The 846 terrestrial ecoregions are grouped into 14 biomes and 8 realms. Six of these biomes are forest biomes and remaining eight are non-forest biomes. For the forest biomes, the geographic boundaries of the ecoregions (Dinerstein et al., 2017) and protected areas (UNEP-WCMC 2016) were intersected with the Global Forest Change data (Hansen et al. 2013) for the years 2000 to 2015, to calculate percent of habitat in protected areas and percent of remaining habitat outside protected areas. Likewise, the boundaries of the non-forest ecoregions and protected areas (UNEP-WCMC 2016) were intersected with Anthropogenic Biomes data (Anthromes v2) for the year 2000 (Ellis et al., 2010) to identify remaining habitats inside and outside the protected areas. Each ecoregion has a unique ID, area (sq. degrees), and NNH (Nature Needs Half) categories 1-4. NNH categories are based on percent of habitat in protected areas and percent of remaining habitat outside protected areas.Half Protected: More than 50% of the total ecoregion area is already protected.Nature Could Reach Half: Less than 50% of the total ecoregion area is protected but the amount of remaining unprotected natural habitat could bring protection to over 50% if new conservation areas are added to the system.Nature Could Recover: The amount of protected and unprotected natural habitat remaining is less than 50% but more than 20%. Ecoregions in this category would require restoration to reach Half Protected.Nature Imperilled: The amount of protected and unprotected natural habitat remaining is less than or equal to 20%. Achieving half protected is not possible in the short term and efforts should focus on conserving remaining, native habitat fragments.The updated Ecoregions 2017 is the most-up-to-date (as of February 2018) dataset on remaining habitat in each terrestrial ecoregion. It was released to chart progress towards achieving the visionary goal of Nature Needs Half, to protect half of all the land on Earth to save a living terrestrial biosphere.Note - a number of ecoregions are very complex polygons with over a million vertices, such as Rock & Ice.

The World Terrestrial Ecosystems map classifies the world into areas of similar climate, landform, and land cover, which form the basic components of any terrestrial ecosystem structure. This map is the important because it uses objectively derived and globally consistent data to characterize the ecosystems at a much finer spatial resolution (250-m) than existing ecoregionalizations, and a much finer thematic resolution (431 classes) than existing global land cover products.Cell Size: 250-meter Source Type: ThematicPixel Type: 16 Bit UnsignedData Projection: GCS WGS84Extent: GlobalSource: USGS, The Nature Conservancy, EsriUpdate Cycle: NoneWhat can you do with this layer?This map allows you to query of the land surface pixels and returns the values of all the input parameters (landform type, landcover/vegetation type, climate region) and the name of the terrestrial ecosystem at that location.This layer can be used in analysis at global and local regions. However, for large scale spatial analysis, we have also provided an ArcGIS Pro Package that contains the original raster data with multiple table attributes. For simple mapping applications, there is also a raster tile layer. This layer can be combined with the World Protected Areas Database to assess the types of ecosystems that are protected, and progress towards meeting conservation goals. The WDPA layer updates monthly from the United Nations Environment Programme.Developing the World Terrestrial EcosystemsWorld Terrestrial Ecosystems map was produced by adopting and modifying the Intergovernmental Panel on Climate Change (IPCC) approach on the definition of Terrestrial Ecosystems and development of standardized global climate regions using the values of environmental moisture regime and temperature regime. We then combined the values of Global Climate Regions, Landforms and matrix-forming vegetation assemblage or land use, using the ArcGIS Combine tool (Spatial Analyst) to produce World Ecosystems Dataset. This combination resulted of 431 World Ecosystems classes.Each combination was assigned a color using an algorithm that blended traditional color schemes for each of the three components. Every pixel in this map is symbolized by a combination of values for each of these fields.The work from this collaboration is documented in the publication:Sayre et al. 2020. An assessment of the representation of ecosystems in global protected areas using new maps of World Climate Regions and World Ecosystems - Global Ecology and Conservation More information about World Terrestrial Ecosystems can be in this Story Map.

Author: Ann Wurst, consultantGrade/Audience: high schoolResource type: activitySubject topic(s): environmental, geographic thinkingRegion: worldStandards: (4) Geography. The student understands the patterns and characteristics of major landforms, climates, and ecosystems of Earth and the interrelated processes that produce them. The student is expected to:

(C) explain the influence of climate on the distribution of biomes in different regions. Objectives: Students will be able to understand the patterns and characteristics of major landforms, climates, and ecosystems of Earth and the interrelated processes that produce them.

Students will be able to explain the influence of climate on the distribution of biomes in different regions.Summary: This story map will help students connect the locations of biomes and human activities around the world

The United States Geological Survey has published a new global ecosystems map of unprecedented detail that lets you explore a tapestry of World ecosystems. The map was produced by a team led by Roger Sayre, Ph.D., Senior Scientist for Ecosystems at the USGS Land Change Science Program. It is a mosaic of almost 4,000 unique ecological areas called Ecological Land Units (ELUs) based on four factors that are key in determining the makeup of ecosystems. Three of these—bioclimate, landforms, and rock type—are physical phenomena that drive the formation of soils and the distribution of vegetation. The fourth, land cover, is the vegetation that is found in a location as a response to the physical factors. This Story Map Journal has two main features, an ecosystems browser and an ecosystem tour. In the ecosystem browser, point and click at any location on the map and the name of that ecosystem appears in a pop-up box. In general, tans are deserts, yellows and light greens are savannas, darker greens are forests, mountainous regions have texture, reddish is warm and bluish is cold. The browser includes pan and zoom functions. ​The ecosystem tour starts on the next page of this map journal. It features places on Earth where the diversity of Ecological Facets (EFs), the building blocks of ELUs, is highly concentrated in an area. The world is divided up into 3.5 billion cells, each one 250 meters on a side, and each of these cells represents one of 47,500 types of EFs. The areas described in the following pages are all locations with relatively high numbers of EFs. While these are areas of high ecological landscape diversity, they are not necessarily areas of high biodiversity. Many EFs have naturally low species diversity, or have been heavily modified by human activity. The areas in the ecosystem tour below include many interesting and beautiful locations that are widely scattered across our hugely diverse planet.

What happens in the vast stretches of the world's oceans - both wondrous and worrisome - has too often been out of sight, out of mind. The sea represents the last major scientific frontier on planet earth - a place where expeditions continue to discover not only new species, but even new phyla. The role of these species in the ecosystem, where they sit in the tree of life, and how they respond to environmental changes really do constitute mysteries of the deep. Despite technological advances that now allow people to access, exploit or affect nearly all parts of the ocean, we still understand very little of the ocean's biodiversity and how it is changing under our influence. The goal of the research presented here is to estimate and visualize, for the first time, the global impact humans are having on the ocean's ecosystems. Our analysis, published in Science, February 15, 2008 (http://doi.org/10.1126/science.1149345), shows that over 40% of the world's oceans are heavily affected by human activities and few if any areas remain untouched. Global data for marine ecosystems are largely non-existent; here we used available data for several ecosystems, modeled the distribution of many other ecosystems, and assumed a uniform distribution for several intertidal ecosystems for which no data exist. We recognize that differences exist in how people classify ecosystems; for example, estuaries are often considered an ecosystem, but here we focus on the ecosystems (also often labeled ‘habitats’) that occur within estuaries (salt marsh, intertidal mud, beach, soft sediment, mangroves, etc.). All ecosystem data were represented at 1 km2 resolution. This dataset contains maps for 20 distinct marine ecosystems used in the impacts model. More information on data sources can be found in the methods section.

The Global Ecosystem Typology is a taxonomy of ecosystems based on their unique characteristics. It is a global classification system that provides a consistent framework for describing and classifying ecological ecosystems. The Global Ecosystem Typology has six levels. The top three levels (realms, functional biomes, and ecosystem functional groups) classify ecosystems based on their overall characteristics, such as their location, dominant plant life, and ecological processes. The bottom three levels (regional ecosystem subgroups, global ecosystem types, and subglobal ecosystem types) focus on specific geographic variants within ecosystem functional groups and complexes of organisms and their associated physical environment, providing a more detailed understanding of particular ecosystems. This dataset focuses on the third level of the Global Ecosystem Typology: Ecosystem Functional Group. It's defined as a group of related ecosystems within a biome that share common ecological drivers, which in turn promote similar biotic traits that characterise the group. Derived from the top-down by subdivision of biomes. NOTE: Due to the size of some geometries, a simpification algorithm was applied to each one to reduce their complexity. As many vertices as possible were discarded without moving the distance from the original shape more than 100 m. As a result, approximately two dozen rows in the table collapsed into geometries with 0 area and were removed.

Probability and uncertainty maps showing the potential current and future natural vegetation on a global scale under three different climate change scenarios (RCP 2.6, RCP 4.5 and RCP 8.5) predicted using ensemble machine learning. Current (2022 - 2023) conditions are calculated on historical long term averages (1979 - 2013), while future projections cover two different epochs: 2040 - 2060 and 2061 - 2080.

Files are named according to the following naming convention, e.g.:

biomes_graminoid.and.forb.tundra.rcp85_p_1km_a_20610101_20801231_go_epsg.4326_v20230410

with the following fields:

generic theme: biomes,

variable name: graminoid.and.forb.tundra.rcp85,

variable type, e.g. probability ("p"), hard class ("c"), model deviation ("md")

spatial resolution: 1km,

depth reference, e.g. below ("b"), above ("a") ground or at surface ("s"),

begin time (YYYYMMDD): 20610101,

end time: 20801231,

bounding box, e.g. global land without Antarctica ("go"),

EPSG code: epsg.4326,

version code, e.g. creation date: v20230410.

We provide probability and hard class layers using a revised classification system of the BIOME 6000 project explained in the work of Hengl et al. (2018). The 20 classes from this classification system have then been aggregated in 6 biome classes following the IUCN Global Ecosystem Typology classification system.

For probability layers, the uncertainty (model deviation: md) is calculated as the standard deviation of the predicted values of the base learners of the ensemble model. The higher the standard deviation the more uncertain the model is regarding the right value to assign to the pixel.

For hard class layers the uncertainty is calculated using the margin of victory (Calderón-Loor et al., 2021) defined as the difference between the first and the second highest class probability value in a given pixel. High values would be measures of low uncertainty, while low values would indicate a high uncertainty. It is highly recommended to use the md layers to properly interpret the results of the map.

Styling files are provided in both .SLD and .QML format; two different styling files are provided for the uncertainty of the probability layers and the hard classes due to the different interpretation of the chosen uncertainty metrics.

The R scripts and a tutorial will be uploaded to the PNVmaps Github repository, where previous versions of the biomes maps from Hengl et al. (2018) is currently hosted. To cite the maps and the methodology, it is possible to refer to the scientific publication:

Bonannella C, Hengl T, Parente L, de Bruin S. 2023. Biomes of the world under climate change scenarios: increasing aridity and higher temperatures lead to significant shifts in natural vegetation. PeerJ 11:e15593 https://doi.org/10.7717/peerj.15593

The Palaeovegetation Mapping Project (generally known as BIOME 6000) was inaugurated in 1994 with the aim of providing global maps describing the vegetation patterns at 6000±500 yr B.P. (on the radiocarbon time scale) and the last glacial maximum (defined as 18,000±1000 yr B.P. on the radiocarbon time scale, equivalent to 21,000 yr B.P. on the calendar time scale) for use by the modelling community.

The BIOME 6000 project has used a standard methodology to map vegetation patterns using fossil pollen and plant-macrofossil data from individual sites. The taxa represented in the pollen or plant-macrofossil assemblages are first allocated to plant functional types (PFTs) on the basis of the life form, leaf form, phenology and bioclimatic tolerance of the plant species included within the taxon. Because of the lack of taxonomic resolution in pollen identification, some taxa can be classified into more than one PFT. Biomes (i.e. major vegetation types at a regional scale) are defined by combinations of PFTs, where these combinations usually include both characteristic and dominant groups. Some PFTs which are known to occur within a given biome are not included in the biome definition because they occur in too many biomes to provide discriminatory power. Once the taxon to PFT and PFT to biome classifications are made, the affinity of pollen or plant-macrofossil assemblages from individual sites for each biome is calculated. Each assemblage is allocated to the biome for which it has the highest affinity. In cases where the assemblage has equal affinity for more than one biome, which can occur when one biome is defined by a subset of the PFTs that characterise another biome, the assemblage is allocated to the biome defined by the subset.

For more information, see Also see Harrison, S. P., and I. C. Prentice. 2003. Climate and CO2 controls on global vegetation distribution at the last glacial maximum: analysis based on palaeovegetation data, biome modelling and palaeoclimate simulations. Global Change Biology 9, 983-1004.