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      Landscape Dynamics (landDX) an open-access spatial-temporal database for the Kenya-Tanzania borderlands

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          Abstract

          The savannas of the Kenya-Tanzania borderland cover >100,000 km 2 and is one of the most important regions globally for biodiversity conservation, particularly large mammals. The region also supports >1 million pastoralists and their livestock. In these systems, resources for both large mammals and pastoralists are highly variable in space and time and thus require connected landscapes. However, ongoing fragmentation of (semi-)natural vegetation by smallholder fencing and expansion of agriculture threatens this social-ecological system. Spatial data on fences and agricultural expansion are localized and dispersed among data owners and databases. Here, we synthesized data from several research groups and conservation NGOs and present the first release of the Landscape Dynamics (landDX) spatial-temporal database, covering ~30,000 km 2 of southern Kenya. The data includes 31,000 livestock enclosures, nearly 40,000 kilometres of fencing, and 1,500 km 2 of agricultural land. We provide caveats and interpretation of the different methodologies used. These data are useful to answer fundamental ecological questions, to quantify the rate of change of ecosystem function and wildlife populations, for conservation and livestock management, and for local and governmental spatial planning.

          Abstract

          Measurement(s) livestock enclosures • agriculture • fence
          Technology Type(s) digital curation
          Sample Characteristic - Environment savanna
          Sample Characteristic - Location East Africa

          Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.16828204

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          Most cited references18

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          Global patterns of terrestrial vertebrate diversity and conservation.

          Identifying priority areas for biodiversity is essential for directing conservation resources. Fundamentally, we must know where individual species live, which ones are vulnerable, where human actions threaten them, and their levels of protection. As conservation knowledge and threats change, we must reevaluate priorities. We mapped priority areas for vertebrates using newly updated data on >21,000 species of mammals, amphibians, and birds. For each taxon, we identified centers of richness for all species, small-ranged species, and threatened species listed with the International Union for the Conservation of Nature. Importantly, all analyses were at a spatial grain of 10 × 10 km, 100 times finer than previous assessments. This fine scale is a significant methodological improvement, because it brings mapping to scales comparable with regional decisions on where to place protected areas. We also mapped recent species discoveries, because they suggest where as-yet-unknown species might be living. To assess the protection of the priority areas, we calculated the percentage of priority areas within protected areas using the latest data from the World Database of Protected Areas, providing a snapshot of how well the planet's protected area system encompasses vertebrate biodiversity. Although the priority areas do have more protection than the global average, the level of protection still is insufficient given the importance of these areas for preventing vertebrate extinctions. We also found substantial differences between our identified vertebrate priorities and the leading map of global conservation priorities, the biodiversity hotspots. Our findings suggest a need to reassess the global allocation of conservation resources to reflect today's improved knowledge of biodiversity and conservation.
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            Extreme Wildlife Declines and Concurrent Increase in Livestock Numbers in Kenya: What Are the Causes?

            There is growing evidence of escalating wildlife losses worldwide. Extreme wildlife losses have recently been documented for large parts of Africa, including western, Central and Eastern Africa. Here, we report extreme declines in wildlife and contemporaneous increase in livestock numbers in Kenya rangelands between 1977 and 2016. Our analysis uses systematic aerial monitoring survey data collected in rangelands that collectively cover 88% of Kenya’s land surface. Our results show that wildlife numbers declined on average by 68% between 1977 and 2016. The magnitude of decline varied among species but was most extreme (72–88%) and now severely threatens the population viability and persistence of warthog, lesser kudu, Thomson’s gazelle, eland, oryx, topi, hartebeest, impala, Grevy’s zebra and waterbuck in Kenya’s rangelands. The declines were widespread and occurred in most of the 21 rangeland counties. Likewise to wildlife, cattle numbers decreased (25.2%) but numbers of sheep and goats (76.3%), camels (13.1%) and donkeys (6.7%) evidently increased in the same period. As a result, livestock biomass was 8.1 times greater than that of wildlife in 2011–2013 compared to 3.5 times in 1977–1980. Most of Kenya’s wildlife (ca. 30%) occurred in Narok County alone. The proportion of the total “national” wildlife population found in each county increased between 1977 and 2016 substantially only in Taita Taveta and Laikipia but marginally in Garissa and Wajir counties, largely reflecting greater wildlife losses elsewhere. The declines raise very grave concerns about the future of wildlife, the effectiveness of wildlife conservation policies, strategies and practices in Kenya. Causes of the wildlife declines include exponential human population growth, increasing livestock numbers, declining rainfall and a striking rise in temperatures but the fundamental cause seems to be policy, institutional and market failures. Accordingly, we thoroughly evaluate wildlife conservation policy in Kenya. We suggest policy, institutional and management interventions likely to succeed in reducing the declines and restoring rangeland health, most notably through strengthening and investing in community and private wildlife conservancies in the rangelands.
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              Expansion of human settlement in Kenya's Maasai Mara: what future for pastoralism and wildlife?

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                Author and article information

                Contributors
                peterdavidtyrrelll@gmail.com
                Journal
                Sci Data
                Sci Data
                Scientific Data
                Nature Publishing Group UK (London )
                2052-4463
                18 January 2022
                18 January 2022
                2022
                : 9
                : 8
                Affiliations
                [1 ]South Rift Association of Land Owners, Nairobi, Kenya
                [2 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, University of Oxford Wildlife Conservation Research Unit, ; Oxford, UK
                [3 ]GRID grid.10604.33, ISNI 0000 0001 2019 0495, University of Nairobi, Department of Geography and Environmental Sciences, ; Nairobi, Kenya
                [4 ]Kenya Wildlife Trust, P.O. Box 86-00502 Karen, Nairobi, Kenya
                [5 ]GRID grid.7048.b, ISNI 0000 0001 1956 2722, Section for Ecoinformatics and Biodiversity, Department of Biology, , Aarhus University, ; Aarhus, Denmark
                [6 ]GRID grid.7048.b, ISNI 0000 0001 1956 2722, Center for Biodiversity Dynamics in a Changing World (BIOCHANGE), Department of Biology, , Aarhus University, ; Aarhus, Denmark
                [7 ]GRID grid.47894.36, ISNI 0000 0004 1936 8083, Colorado State University, Graduate Degree Program in Ecology, ; Fort Collins, USA
                [8 ]Ramani Geosystems Ltd, Nairobi, Kenya
                [9 ]Independent (Rijperweg 91, 1462 MD Middenbeemster, The Netherlands
                [10 ]GRID grid.7048.b, ISNI 0000 0001 1956 2722, Department of Archaeology and Heritage Studies & IMC, , Aarhus University, ; Aarhus, Denmark
                [11 ]GRID grid.452812.8, Save the Elephants, ; Nairobi, Kenya
                [12 ]Mara Elephant Project, Nairobi, Kenya
                [13 ]GRID grid.467700.2, ISNI 0000 0001 2182 2028, Smithsonian National Zoo & Conservation Biology Institute, Conservation Ecology Center, ; Washington, USA
                [14 ]GRID grid.49697.35, ISNI 0000 0001 2107 2298, Mammal Research Institute and Department of Zoology & Entomology, , University of Pretoria, ; Pretoria, South Africa
                [15 ]GRID grid.53857.3c, ISNI 0000 0001 2185 8768, Department of Wildland Resources, , Utah State University, ; Logan, USA
                [16 ]GRID grid.47894.36, ISNI 0000 0004 1936 8083, Colorado State University, Dept. of Fish, Wildlife and Conservation Biology, ; Fort Collins, USA
                [17 ]GRID grid.4818.5, ISNI 0000 0001 0791 5666, Wildlife Ecology and Conservation Group, , Wageningen University and Research, ; 6708 PB Wageningen, The Netherlands
                Author information
                http://orcid.org/0000-0002-9599-8138
                http://orcid.org/0000-0002-4216-8819
                http://orcid.org/0000-0003-3356-2301
                http://orcid.org/0000-0003-1429-6722
                http://orcid.org/0000-0002-3084-0524
                http://orcid.org/0000-0003-0705-7117
                Article
                1100
                10.1038/s41597-021-01100-9
                8766582
                35042854
                95485378-dc4d-4f78-81bf-2c5f6412a871
                © 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/.

                The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article.

                History
                : 15 December 2020
                : 2 November 2021
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                © The Author(s) 2022

                conservation biology,developing world
                conservation biology, developing world

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