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      Species distribution modeling reveals strongholds and potential reintroduction areas for the world’s largest eagle

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          Abstract

          The highly interactive nature of predator-prey relationship is essential for ecosystem conservation; predators have been extirpated, however, from entire ecosystems all over the Earth. Reintroductions comprise a management technique to reverse this trend. Species Distribution Models (SDM) are preemptive tools for release-site selection, and can define levels of habitat quality over the species distribution. The Atlantic Forest of South America has lost most of its apex predators, and Harpy Eagles Harpia harpyja—Earth’s largest eagle—are now limited to few forest pockets in this domain. Harpy Eagles are supposedly widespread in the Amazon Forest, however, where habitat loss and degradation is advancing at a rapid pace. We aim to describe the suitability of threatened Amazonian landscapes for this eagle. We also aim to assess the suitability of remaining Atlantic Forest sites for Harpy Eagle reintroductions. Here we show that that considerable eagle habitat has already been lost in Amazonia due to the expansion of the “Arc of Deforestation”, and that Amazonian forests currently represent 93% of the current distribution of the species. We also show that the Serra do Mar protected areas in southeastern Brazil is the most promising region for Harpy Eagle reintroductions in the Atlantic Forest. Reintroduction and captive breeding programs have been undertaken for Harpy Eagles, building the technical and biological basis for a successful restoration framework. Our distribution range for this species represents a 41% reduction of what is currently proposed by IUCN. Furthermore, habitat loss in Amazonia, combined with industrial logging and hunting suggest that the conservation status of this species should be reassessed. We suggest researchers and conservation practitioners can use this work to help expand efforts to conserve Harpy Eagles and their natural habitats.

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          Selecting pseudo-absences for species distribution models: how, where and how many?

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            Mapping forest canopy height globally with spaceborne lidar

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              Selective logging in the Brazilian Amazon.

              Amazon deforestation has been measured by remote sensing for three decades. In comparison, selective logging has been mostly invisible to satellites. We developed a large-scale, high-resolution, automated remote-sensing analysis of selective logging in the top five timber-producing states of the Brazilian Amazon. Logged areas ranged from 12,075 to 19,823 square kilometers per year (+/-14%) between 1999 and 2002, equivalent to 60 to 123% of previously reported deforestation area. Up to 1200 square kilometers per year of logging were observed on conservation lands. Each year, 27 million to 50 million cubic meters of wood were extracted, and a gross flux of approximately 0.1 billion metric tons of carbon was destined for release to the atmosphere by logging.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: VisualizationRole: Writing – original draft
                Role: Formal analysisRole: Methodology
                Role: Data curation
                Role: Funding acquisitionRole: ResourcesRole: Writing – review & editing
                Role: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                13 May 2019
                2019
                : 14
                : 5
                : e0216323
                Affiliations
                [1 ] Universidade Estadual de Mato Grosso, Alta Floresta, Mato Grosso, Brazil
                [2 ] School of Life Sciences, University of KwaZulu-Natal, Pietermaritzburg, South Africa
                [3 ] Programa de Pós-graduação em Ecologia, IB, Universidade de Brasília, Brasília, Distrito Federal, Brazil
                [4 ] Mitrani Department of Desert Ecology, Ben Gurion University of the Negev, Beersheba, Israel
                [5 ] Faculdade de Medicina Veterinária, Universidade Federal de Mato Grosso, Cuiabá, Mato Grosso, Brazil
                [6 ] SouthWild, Várzea Grande, Mato Grosso, Brazil
                [7 ] Center for Ecology, Evolution and Conservation, School of Environmental Sciences, University of East Anglia, Norwich, United Kingdom
                Michigan State University, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0003-2198-4742
                Article
                PONE-D-18-07065
                10.1371/journal.pone.0216323
                6513255
                31083656
                d2ee98e9-6e09-4b8f-b740-41e5d05f1fff
                © 2019 Miranda et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 6 March 2018
                : 18 April 2019
                Page count
                Figures: 5, Tables: 1, Pages: 19
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100007463, Rufford Foundation;
                Award ID: 18743-1
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100007463, Rufford Foundation;
                Award ID: 23022-2
                Award Recipient :
                Funded by: Rainforest Biodiversity Group
                Award ID: 2016/2
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100007142, Idea Wild;
                Award ID: 2016/1
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100007142, Idea Wild;
                Award ID: 2017/2
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100002861, Explorers Club;
                Award ID: The Mamont Scholars Program 2016/2
                Award Recipient :
                Funded by: Cleveland Metroparks Zoo
                Award ID: 2018/1
                Award Recipient :
                Funded by: South Wild
                Award ID: SouthWild.com Conservation Travel System 2017-Present
                Award Recipient :
                Funded by: Global Innovation Initiative
                Award ID: GII 111
                Award Recipient :
                We greatly appreciate the generous financial support of the following donors: Rufford Small Grants Foundation (18743-1 and 23022-2), Rainforest Biodiversity Group, Idea Wild, The Mamont Scholars Program of the Explorer’s Club Exploration Fund, Cleveland Metroparks Zoo, and the SouthWild.com Conservation Travel System. CAP’s work in Mato Grosso was funded by a Global Innovation Initiative (grant GGI 111).
                Categories
                Research Article
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Vertebrates
                Amniotes
                Birds
                Raptors
                Eagles
                Biology and Life Sciences
                Ecology
                Ecosystems
                Forests
                Ecology and Environmental Sciences
                Ecology
                Ecosystems
                Forests
                Ecology and Environmental Sciences
                Terrestrial Environments
                Forests
                Ecology and Environmental Sciences
                Conservation Science
                Biology and Life Sciences
                Ecology
                Forest Ecology
                Ecology and Environmental Sciences
                Ecology
                Forest Ecology
                People and places
                Geographical locations
                South America
                Brazil
                Biology and Life Sciences
                Psychology
                Behavior
                Habits
                Nesting Habits
                Social Sciences
                Psychology
                Behavior
                Habits
                Nesting Habits
                Biology and Life Sciences
                Ecology
                Community Ecology
                Trophic Interactions
                Predation
                Ecology and Environmental Sciences
                Ecology
                Community Ecology
                Trophic Interactions
                Predation
                Biology and Life Sciences
                Ecology
                Ecosystems
                Ecology and Environmental Sciences
                Ecology
                Ecosystems
                Custom metadata
                Data is available in S1 Table.

                Uncategorized
                Uncategorized

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