Using the Rao's Q diversity index as an indicator of protected area effectiveness in conserving biodiversity |
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| Institution: | 1. M.A.P Scientific Services, Pretoria 0081, South Africa;2. South African National Biodiversity Institute, Pretoria 0184, South Africa; School of Life Sciences, University of KwaZulu-Natal, Durban 4041, South Africa;3. Limpopo Department of Economic Development, Environment and Tourism, Private Bag X477, Polokwane 0700, South Africa;4. Department of Forestry, Fisheries and the Environment, Private Bag X477, Pretoria, 0001, South Africa;5. Department of Zoology and Entomology, University of Pretoria, 0083, South Africa;1. Department of Zoology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada;2. Department of Biology, University of Oklahoma, Norman, OK 73019-0235, USA;3. Sam Noble Oklahoma Museum of Natural History, University of Oklahoma, 2401 Chautauqua Ave., Norman, OK 73072-7029, USA;1. Department of Natural Resources Engineering, Faculty of Agriculture & Natural Resources, University of Hormozgan, Bandar Abbas, Iran;2. Department of Rehabilitation of Arid and Mountainous, Faculty of Natural Resources, University of Tehran, Karaj, Iran;3. Department of Forest Engineering, Forest Management Planning and Terrestrial Measurements, Faculty of Silviculture and Forest Engineering, Transilvania University of Brasov, 500123 Brasov, Romania;4. School of Forest, Fisheries and Geomatics Sciences, University of Florida, Gainesville, FL 32611, USA;5. Faculty of Civil Engineering, Transilvania University of Brasov, 900152 Brasov, Romania;1. Gazi University, Graduate School of Natural and Applied Sciences, Teknikokullar, 06500 Ankara, Turkey;2. Ba?kent University, Faculty of Commercial Sciences, Management Information Science, 06790 Ankara, Turkey;3. Gazi University, Faculty of Education, Teknikokullar, 06500 Ankara, Turkey;1. Department of Sensing, Information and Mechanization Engineering, Institute of Agricultural Engineering, Agricultural Research Organization, Volcani Institute, Rishon LeZion, Israel;2. Department of Entomology, The Robert H. Smith Faculty of Agriculture, Food and Environment, The Hebrew University of Jerusalem, Rehovot, Israel;3. Department of Entomology, Institute of Plant Protection, Agricultural Research Organization, Volcani Institute, Rishon LeZion, Israel;4. Department of Natural Resources, Newe Ya''ar Research Center, Agricultural Research Organization - Volcani Institute, Ramat Yishay, Israel;5. The plant protection and inspection services, Ministry of Agriculture and Rural Development, Rishon LeZion, Israel;1. Environmental Systems Engineering, Faculty of Engineering and Applied Science, University of Regina, Saskatchewan S4S 0A2, Canada;2. Indigenous Knowledge & Science, First Nations University of Canada, Regina Saskatchewan, S4S 7K2, Canada |
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| Abstract: | Developing innovative monitoring systems for biodiversity outcomes in protected areas (PAs) are important to enable effective adaptive management. Here we show how to quantitatively detect and monitor temporal and spatial patterns in environmental heterogeneity, an important indicator of ecological integrity and biodiversity patterns. We used a 28-year time series (1991–2018) generated from freely available Landsat satellite imagery and Rao's quadratic index to calculate relative heterogeneity and trends in heterogeneity for 41 PAs across South Africa. We selected PAs where mega-herbivore assemblages were similar and where management objectives were broadly aligned with South African legislation to protect biodiversity. There was a three-fold difference in heterogeneity among PAs, mainly linked to variation in topography and rainfall. Heterogeneity decreased in 12 (29%), increased in three (7%) and remained stable in 26 (64%) PA's. These trends were not explained by overall heterogeneity, PA size, or rainfall – i.e., PAs that were smaller, drier, and more homogenous were not more likely to show decreasing trends than PAs that were larger, wetter, and generally more heterogenous. Rather trends in heterogeneity are likely the result of interactions between regional process (e.g., rainfall) and local factors such fire regimes, megaherbivore densities, and park management. The framework presented here can be extended to include every PA nationally, or even globally, and the data product fully automated. This presents an opportunity for conservation management to incorporate this important biodiversity indicator in PA monitoring programs as well as other large-scale ecological monitoring initiatives. |
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