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      Least concern to endangered: Applying climate change projections profoundly influences the extinction risk assessment for wild Arabica coffee

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          Abstract

          Arabica coffee ( Coffea arabica) is a key crop in many tropical countries and globally provides an export value of over US$13 billion per year. Wild Arabica coffee is of fundamental importance for the global coffee sector and of direct importance within Ethiopia, as a source of harvestable income and planting stock. Published studies show that climate change is projected to have a substantial negative influence on the current suitable growing areas for indigenous Arabica in Ethiopia and South Sudan. Here we use all available future projections for the species based on multiple general circulation models (GCMs), emission scenarios, and migration scenarios, to predict changes in Extent of Occurrence (EOO), Area of Occupancy (AOO), and population numbers for wild Arabica coffee. Under climate change our results show that population numbers could reduce by 50% or more (with a few models showing over 80%) by 2088. EOO and AOO are projected to decline by around 30% in many cases. Furthermore, present‐day models compared to the near future (2038), show a reduction for EOO of over 40% (with a few cases over 50%), although EOO should be treated with caution due to its sensitivity to outlying occurrences. When applying these metrics to extinction risk, we show that the determination of generation length is critical. When applying the International Union for Conservation of Nature's Red list of Threatened Species (IUCN Red List) criteria, even with a very conservative generation length of 21 years, wild Arabica coffee is assessed as Threatened with extinction (placed in the Endangered category) under a broad range of climate change projections, if no interventions are made. Importantly, if we do not include climate change in our assessment, Arabica coffee is assessed as Least Concern (not threatened) when applying the IUCN Red List criteria.

          Abstract

          Arabica coffee ( Coffea arabica) is a key crop in many tropical countries and globally provides an export value of over US$13 billion per year. Wild Arabica coffee is of fundamental importance for the global coffee sector and of direct importance within Ethiopia, as a source of harvestable income and planting stock. In this paper we show that under climate change alone, population numbers could reduce by 50% or more (with a few models showing over 80%) by 2088. When applying the International Union for Conservation of Nature’s Red list of Threatened Species (IUCN Red List) criteria, even with a very conservative generation length of 21 years, wild Arabica coffee is assessed as Threatened with extinction (placed in the Endangered category) under a broad range of climate change projections, if no interventions are made. Importantly, if we do not include climate change in our assessment, Arabica coffee is assessed as Least Concern (not threatened) when applying the IUCN Red List criteria.

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          Most cited references27

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          An Overview of CMIP5 and the Experiment Design

          The fifth phase of the Coupled Model Intercomparison Project (CMIP5) will produce a state-of-the- art multimodel dataset designed to advance our knowledge of climate variability and climate change. Researchers worldwide are analyzing the model output and will produce results likely to underlie the forthcoming Fifth Assessment Report by the Intergovernmental Panel on Climate Change. Unprecedented in scale and attracting interest from all major climate modeling groups, CMIP5 includes “long term” simulations of twentieth-century climate and projections for the twenty-first century and beyond. Conventional atmosphere–ocean global climate models and Earth system models of intermediate complexity are for the first time being joined by more recently developed Earth system models under an experiment design that allows both types of models to be compared to observations on an equal footing. Besides the longterm experiments, CMIP5 calls for an entirely new suite of “near term” simulations focusing on recent decades and the future to year 2035. These “decadal predictions” are initialized based on observations and will be used to explore the predictability of climate and to assess the forecast system's predictive skill. The CMIP5 experiment design also allows for participation of stand-alone atmospheric models and includes a variety of idealized experiments that will improve understanding of the range of model responses found in the more complex and realistic simulations. An exceptionally comprehensive set of model output is being collected and made freely available to researchers through an integrated but distributed data archive. For researchers unfamiliar with climate models, the limitations of the models and experiment design are described.
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            Supporting Red List threat assessments with GeoCAT: geospatial conservation assessment tool

            Abstract GeoCAT is an open source, browser based tool that performs rapid geospatial analysis to ease the process of Red Listing taxa. Developed to utilise spatially referenced primary occurrence data, the analysis focuses on two aspects of the geographic range of a taxon: the extent of occurrence (EOO) and the area of occupancy (AOO). These metrics form part of the IUCN Red List categories and criteria and have often proved challenging to obtain in an accurate, consistent and repeatable way. Within a familiar Google Maps environment, GeoCAT users can quickly and easily combine data from multiple sources such as GBIF, Flickr and Scratchpads as well as user generated occurrence data. Analysis is done with the click of a button and is visualised instantly, providing an indication of the Red List threat rating, subject to meeting the full requirements of the criteria. Outputs including the results, data and parameters used for analysis are stored in a GeoCAT file that can be easily reloaded or shared with collaborators. GeoCAT is a first step toward automating the data handling process of Red List assessing and provides a valuable hub from which further developments and enhancements can be spawned.
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              Mapping species distributions

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                Author and article information

                Contributors
                J.Moat@kew.org
                Journal
                Glob Chang Biol
                Glob Chang Biol
                10.1111/(ISSN)1365-2486
                GCB
                Global Change Biology
                John Wiley and Sons Inc. (Hoboken )
                1354-1013
                1365-2486
                16 January 2019
                February 2019
                : 25
                : 2 ( doiID: 10.1111/gcb.2019.25.issue-2 )
                : 390-403
                Affiliations
                [ 1 ] Royal Botanic Gardens, Kew Richmond UK
                [ 2 ] School of Geography University of Nottingham Nottingham UK
                [ 3 ] Environment, Climate Change and Coffee Forest Forum (ECCCFF) Addis Ababa Ethiopia
                Author notes
                [*] [* ] Correspondence

                Justin Moat, Royal Botanic Gardens, Kew, Richmond, Surrey, TW9 3AE, UK.

                Email: J.Moat@ 123456kew.org

                Author information
                http://orcid.org/0000-0002-5513-3615
                https://orcid.org/0000-0001-9213-4353
                Article
                GCB14341
                10.1111/gcb.14341
                6900256
                30650240
                f343ed82-239d-4b6a-89e1-87597451d6f3
                © 2019 The Authors. Global Change Biology published by John Wiley & Sons Ltd

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 07 December 2017
                : 06 June 2018
                : 30 April 2018
                Page count
                Figures: 6, Tables: 1, Pages: 15, Words: 10233
                Funding
                Funded by: Strategic Climate Institutions Programme (SCIP) Fund
                Funded by: Building a Climate Resilient Coffee Economy for Ethiopia
                Funded by: Darwin Initiative
                Funded by: Toyota Motor Corporation , open-funder-registry 10.13039/501100004405;
                Funded by: Amar‐Franses Foster‐Jenkins Trust
                Categories
                Primary Research Article
                Primary Research Articles
                Custom metadata
                2.0
                February 2019
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.7.2 mode:remove_FC converted:06.12.2019

                area of occupancy,climate change,coffee,extent of occurrence,generation length,iucn red list,population metrics

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