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      A function-based typology for Earth’s ecosystems

      1 , 2 , 3 , ,   1 , 3 , 3 , 4 , 5 , 6 , 7 , 8 , 1 , 2 , 9 , 10 , 11 , 12 , 13 , 4 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 9 , 21 , 22 , 3 , 4 , 23 , 24 , 1 , 25 , 26 , 27 , 18 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 3 , 36 , 37 , 38 , 22 , 39 , 1 , 3 , 40 , 41 , 42 , 43 , 44 , 1
      Nature Publishing Group UK
      Biodiversity, Conservation biology, Ecosystem ecology

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          The new IUCN Global Ecosystem Typology is a comprehensive classification framework for Earth’s ecosystems that integrates their functional and compositional features.

          This new typology will help identify the ecosystems that are most critical for biodiversity conservation, research, management and human wellbeing into the future.

          The IUCN Global Ecosystem Typology comprises six hierarchical levels, with the three upper levels developed on the global-ecosystems website, allowing navigation from global to local scales. The three upper levels – realms, functional biomes and ecosystem functional groups – classify ecosystems based on their functional characteristics (such as structural roles of foundation species, water regime, climatic regime or food web structure), rather than based on which species live in them.

          The three lower levels of classification – biogeographic ecotypes, global ecosystem types and subglobal ecosystem types – are often already in use and incorporated into policy infrastructure at national levels and can be linked to these upper levels. This is crucial, as important conservation action occurs at local levels, where most ecosystem-specific knowledge and data reside.


          As the United Nations develops a post-2020 global biodiversity framework for the Convention on Biological Diversity, attention is focusing on how new goals and targets for ecosystem conservation might serve its vision of ‘living in harmony with nature’ 1, 2 . Advancing dual imperatives to conserve biodiversity and sustain ecosystem services requires reliable and resilient generalizations and predictions about ecosystem responses to environmental change and management 3 . Ecosystems vary in their biota 4 , service provision 5 and relative exposure to risks 6 , yet there is no globally consistent classification of ecosystems that reflects functional responses to change and management. This hampers progress on developing conservation targets and sustainability goals. Here we present the International Union for Conservation of Nature (IUCN) Global Ecosystem Typology, a conceptually robust, scalable, spatially explicit approach for generalizations and predictions about functions, biota, risks and management remedies across the entire biosphere. The outcome of a major cross-disciplinary collaboration, this novel framework places all of Earth’s ecosystems into a unifying theoretical context to guide the transformation of ecosystem policy and management from global to local scales. This new information infrastructure will support knowledge transfer for ecosystem-specific management and restoration, globally standardized ecosystem risk assessments, natural capital accounting and progress on the post-2020 global biodiversity framework.


          The International Union for Conservation of Nature’s Global Ecosystem Typology has been developed to provide a systematic framework for data on all of Earth’s ecosystems in a unified theoretical context to support biodiversity conservation and ecosystem services.

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          Most cited references51

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          High-resolution global maps of 21st-century forest cover change.

          Quantification of global forest change has been lacking despite the recognized importance of forest ecosystem services. In this study, Earth observation satellite data were used to map global forest loss (2.3 million square kilometers) and gain (0.8 million square kilometers) from 2000 to 2012 at a spatial resolution of 30 meters. The tropics were the only climate domain to exhibit a trend, with forest loss increasing by 2101 square kilometers per year. Brazil's well-documented reduction in deforestation was offset by increasing forest loss in Indonesia, Malaysia, Paraguay, Bolivia, Zambia, Angola, and elsewhere. Intensive forestry practiced within subtropical forests resulted in the highest rates of forest change globally. Boreal forest loss due largely to fire and forestry was second to that in the tropics in absolute and proportional terms. These results depict a globally consistent and locally relevant record of forest change.
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            Primary forests are irreplaceable for sustaining tropical biodiversity.

            Human-driven land-use changes increasingly threaten biodiversity, particularly in tropical forests where both species diversity and human pressures on natural environments are high. The rapid conversion of tropical forests for agriculture, timber production and other uses has generated vast, human-dominated landscapes with potentially dire consequences for tropical biodiversity. Today, few truly undisturbed tropical forests exist, whereas those degraded by repeated logging and fires, as well as secondary and plantation forests, are rapidly expanding. Here we provide a global assessment of the impact of disturbance and land conversion on biodiversity in tropical forests using a meta-analysis of 138 studies. We analysed 2,220 pairwise comparisons of biodiversity values in primary forests (with little or no human disturbance) and disturbed forests. We found that biodiversity values were substantially lower in degraded forests, but that this varied considerably by geographic region, taxonomic group, ecological metric and disturbance type. Even after partly accounting for confounding colonization and succession effects due to the composition of surrounding habitats, isolation and time since disturbance, we find that most forms of forest degradation have an overwhelmingly detrimental effect on tropical biodiversity. Our results clearly indicate that when it comes to maintaining tropical biodiversity, there is no substitute for primary forests.
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              High-resolution mapping of global surface water and its long-term changes.

              The location and persistence of surface water (inland and coastal) is both affected by climate and human activity and affects climate, biological diversity and human wellbeing. Global data sets documenting surface water location and seasonality have been produced from inventories and national descriptions, statistical extrapolation of regional data and satellite imagery, but measuring long-term changes at high resolution remains a challenge. Here, using three million Landsat satellite images, we quantify changes in global surface water over the past 32 years at 30-metre resolution. We record the months and years when water was present, where occurrence changed and what form changes took in terms of seasonality and persistence. Between 1984 and 2015 permanent surface water has disappeared from an area of almost 90,000 square kilometres, roughly equivalent to that of Lake Superior, though new permanent bodies of surface water covering 184,000 square kilometres have formed elsewhere. All continental regions show a net increase in permanent water, except Oceania, which has a fractional (one per cent) net loss. Much of the increase is from reservoir filling, although climate change is also implicated. Loss is more geographically concentrated than gain. Over 70 per cent of global net permanent water loss occurred in the Middle East and Central Asia, linked to drought and human actions including river diversion or damming and unregulated withdrawal. Losses in Australia and the USA linked to long-term droughts are also evident. This globally consistent, validated data set shows that impacts of climate change and climate oscillations on surface water occurrence can be measured and that evidence can be gathered to show how surface water is altered by human activities. We anticipate that this freely available data will improve the modelling of surface forcing, provide evidence of state and change in wetland ecotones (the transition areas between biomes), and inform water-management decision-making.

                Author and article information

                Nature Publishing Group UK (London )
                12 October 2022
                12 October 2022
                : 610
                : 7932
                : 513-518
                [1 ]GRID grid.1005.4, ISNI 0000 0004 4902 0432, Centre for Ecosystem Science, , University of New South Wales, ; Sydney, New South Wales Australia
                [2 ]New South Wales Department of Planning, Industry and Environment, Hurstville, New South Wales Australia
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                [24 ]GRID grid.410389.7, ISNI 0000 0001 0943 6642, Instituto Español de Oceanografía, , Centro Oceanográfico de Baleares, ; Palma, Spain
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                [28 ]GRID grid.8391.3, ISNI 0000 0004 1936 8024, College of Life and Environmental Sciences Geography, , University of Exeter, ; Exeter, UK
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                [30 ]GRID grid.410335.0, ISNI 0000 0001 2288 7106, Hellenic Centre for Marine Research (HCMR), , Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), ; Heraklion, Greece
                [31 ]GRID grid.449127.d, ISNI 0000 0001 1412 7238, Department of Environment, Faculty of Environment, , Ionian University, ; Zakynthos, Greece
                [32 ]GRID grid.7872.a, ISNI 0000000123318773, School of Biological Earth and Environmental Sciences, , University College Cork, ; Cork, Ireland
                [33 ]GRID grid.263785.d, ISNI 0000 0004 0368 7397, School of Life Sciences, , South China Normal University, ; Guangzhou, China
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                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                : 20 October 2019
                : 2 September 2022
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                © The Author(s), under exclusive licence to Springer Nature Limited 2022

                The datasets generated during and/or analysed during the current study are available in the repository: https://osf.io/68syg/
                Environmental economics & Politics,Environmental change,Ecology,Environmental studies,Environmental management, Policy & Planning,Life sciences
                conservation biology,biodiversity,ecosystem ecology
                The datasets generated during and/or analysed during the current study are available in the repository: https://osf.io/68syg/
                Environmental economics & Politics, Environmental change, Ecology, Environmental studies, Environmental management, Policy & Planning, Life sciences
                conservation biology, biodiversity, ecosystem ecology


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