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Connor T, Viña A, Winkler JA, Hull V, Tang Y, Shortridge A, Yang H, Zhao Z, Wang F, Zhang J, Zhang Z, Zhou C, Bai W, Liu J. Interactive spatial scale effects on species distribution modeling: The case of the giant panda. Sci Rep 2019; 9:14563. [PMID: 31601927 PMCID: PMC6787011 DOI: 10.1038/s41598-019-50953-z] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2018] [Accepted: 09/19/2019] [Indexed: 11/08/2022] Open
Abstract
Research has shown that varying spatial scale through the selection of the total extent of investigation and the grain size of environmental predictor variables has effects on species distribution model (SDM) results and accuracy, but there has been minimal investigation into the interactive effects of extent and grain. To do this, we used a consistently sampled range-wide dataset of giant panda occurrence across southwest China and modeled their habitat and distribution at 4 extents and 7 grain sizes. We found that increasing grain size reduced model accuracy at the smallest extent, but that increasing extent negated this effect. Increasing extent also generally increased model accuracy, but the models built at the second-largest (mountain range) extent were more accurate than those built at the largest, geographic range-wide extent. When predicting habitat suitability in the smallest nested extents (50 km2), we found that the models built at the next-largest extent (500 km2) were more accurate than the smallest-extent models but that further increases in extent resulted in large decreases in accuracy. Overall, this study highlights the impacts of the selection of spatial scale when evaluating species' habitat and distributions, and we suggest more explicit investigations of scale effects in future modeling efforts.
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Affiliation(s)
- Thomas Connor
- Center for Systems Integration and Sustainability, Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA.
| | - Andrés Viña
- Center for Systems Integration and Sustainability, Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA
- Department of Geography, University of North Carolina, Chapel Hill, NC, USA
| | - Julie A Winkler
- Department of Geography, Environment, and Spatial Sciences, Michigan State University, East Lansing, MI, USA
| | - Vanessa Hull
- Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, FL, USA
| | - Ying Tang
- Department of Geography, Environment, and Spatial Sciences, Michigan State University, East Lansing, MI, USA
| | - Ashton Shortridge
- Department of Geography, Environment, and Spatial Sciences, Michigan State University, East Lansing, MI, USA
| | - Hongbo Yang
- Center for Systems Integration and Sustainability, Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA
| | - Zhiqiang Zhao
- Center for Systems Integration and Sustainability, Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA
| | - Fang Wang
- Department of Geography, University of North Carolina, Chapel Hill, NC, USA
| | - Jindong Zhang
- Key Laboratory of Southwest China Wildlife Resources Conservation, China West Normal University, Ministry of Education, Nanchong, China
| | - Zejun Zhang
- Key Laboratory of Southwest China Wildlife Resources Conservation, China West Normal University, Ministry of Education, Nanchong, China
| | - Caiquan Zhou
- Key Laboratory of Southwest China Wildlife Resources Conservation, China West Normal University, Ministry of Education, Nanchong, China
| | - Wenke Bai
- Key Laboratory of Southwest China Wildlife Resources Conservation, China West Normal University, Ministry of Education, Nanchong, China
| | - Jianguo Liu
- Center for Systems Integration and Sustainability, Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA
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Ma T, Hu Y, Russo IRM, Nie Y, Yang T, Xiong L, Ma S, Meng T, Han H, Zhang X, Bruford MW, Wei F. Walking in a heterogeneous landscape: Dispersal, gene flow and conservation implications for the giant panda in the Qinling Mountains. Evol Appl 2018; 11:1859-1872. [PMID: 30459834 PMCID: PMC6231463 DOI: 10.1111/eva.12686] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2018] [Revised: 07/14/2018] [Accepted: 07/16/2018] [Indexed: 01/04/2023] Open
Abstract
Understanding the interaction between life history, demography and population genetics in threatened species is critical for the conservations of viable populations. In the context of habitat loss and fragmentation, identifying the factors that underpin the structuring of genetic variation within populations can allow conservationists to evaluate habitat quality and connectivity and help to design dispersal corridors effectively. In this study, we carried out a detailed, fine‐scale landscape genetic investigation of a giant panda population from the Qinling Mountains for the first time. With a large microsatellite data set and complementary analysis methods, we examined the role of isolation‐by‐barriers (IBB), isolation‐by‐distance (IBD) and isolation‐by‐resistance (IBR) in shaping the pattern of genetic variation in this giant panda population. We found that the Qinling population comprises one continuous genetic cluster, and among the landscape hypotheses tested, gene flow was found to be correlated with resistance gradients for two topographic factors, slope aspect and topographic complexity, rather than geographical distance or barriers. Gene flow was inferred to be facilitated by easterly slope aspect and to be constrained by topographically complex landscapes. These factors are related to benign microclimatic conditions for both the pandas and the food resources they rely on and more accessible topographic conditions for movement, respectively. We identified optimal corridors based on these results, aiming to promote gene flow between human‐induced habitat fragments. These findings provide insight into the permeability and affinities of giant panda habitats and offer important reference for the conservation of the giant panda and its habitat.
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Affiliation(s)
- Tianxiao Ma
- Key Laboratory of Animal Ecology and Conservation Biology Institute of Zoology Chinese Academy of Sciences Beijing China.,University of Chinese Academy of Sciences Beijing China
| | - Yibo Hu
- Key Laboratory of Animal Ecology and Conservation Biology Institute of Zoology Chinese Academy of Sciences Beijing China.,Center for Excellence in Animal Evolution and Genetics Chinese Academy of Sciences Kunming China
| | | | - Yonggang Nie
- Key Laboratory of Animal Ecology and Conservation Biology Institute of Zoology Chinese Academy of Sciences Beijing China.,Center for Excellence in Animal Evolution and Genetics Chinese Academy of Sciences Kunming China
| | - Tianyou Yang
- School of Life Sciences Guizhou Normal University Guiyang Guizhou China
| | - Lijuan Xiong
- School of Life Sciences Guizhou Normal University Guiyang Guizhou China
| | - Shuai Ma
- Key Laboratory of Animal Ecology and Conservation Biology Institute of Zoology Chinese Academy of Sciences Beijing China.,University of Chinese Academy of Sciences Beijing China
| | - Tao Meng
- Guangxi Forest Inventory & Planning Institute Nanning Guangxi China
| | - Han Han
- Key Laboratory of Animal Ecology and Conservation Biology Institute of Zoology Chinese Academy of Sciences Beijing China
| | | | - Michael W Bruford
- Cardiff School of Biosciences Cardiff University Cardiff UK.,Sustainable Places Research Institute Cardiff University Cardiff UK
| | - Fuwen Wei
- Key Laboratory of Animal Ecology and Conservation Biology Institute of Zoology Chinese Academy of Sciences Beijing China.,University of Chinese Academy of Sciences Beijing China.,Center for Excellence in Animal Evolution and Genetics Chinese Academy of Sciences Kunming China
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Gong M, Guan T, Hou M, Liu G, Zhou T. Hopes and challenges for giant panda conservation under climate change in the Qinling Mountains of China. Ecol Evol 2017; 7:596-605. [PMID: 28116056 PMCID: PMC5243786 DOI: 10.1002/ece3.2650] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2016] [Revised: 11/09/2016] [Accepted: 11/14/2016] [Indexed: 11/08/2022] Open
Abstract
One way that climate change will impact animal distributions is by altering habitat suitability and habitat fragmentation. Understanding the impacts of climate change on currently threatened species is of immediate importance because complex conservation planning will be required. Here, we mapped changes to the distribution, suitability, and fragmentation of giant panda habitat under climate change and quantified the direction and elevation of habitat shift and fragmentation patterns. These data were used to develop a series of new conservation strategies for the giant panda. Qinling Mountains, Shaanxi, China. Data from the most recent giant panda census, habitat factors, anthropogenic disturbance, climate variables, and climate predictions for the year 2050 (averaged across four general circulation models) were used to project giant panda habitat in Maxent. Differences in habitat patches were compared between now and 2050. While climate change will cause a 9.1% increase in suitable habitat and 9% reduction in subsuitable habitat by 2050, no significant net variation in the proportion of suitable and subsuitable habitat was found. However, a distinct climate change-induced habitat shift of 11 km eastward by 2050 is predicted firstly. Climate change will reduce the fragmentation of suitable habitat at high elevations and exacerbate the fragmentation of subsuitable habitat below 1,900 m above sea level. Reduced fragmentation at higher elevations and worsening fragmentation at lower elevations have the potential to cause overcrowding of giant pandas at higher altitudes, further exacerbating habitat shortage in the central Qinling Mountains. The habitat shift to the east due to climate change may provide new areas for giant pandas but poses severe challenges for future conservation.
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Affiliation(s)
- Minghao Gong
- Research Institute of WetlandBeijing Key Laboratory of Wetland Services and RestorationChinese Academy of ForestryBeijingChina
| | | | - Meng Hou
- Academy of Forestry Inventory and PlanningState Forestry AdministrationBeijingChina
| | - Gang Liu
- Research Institute of WetlandBeijing Key Laboratory of Wetland Services and RestorationChinese Academy of ForestryBeijingChina
| | - Tianyuan Zhou
- Academy of Forestry Inventory and PlanningState Forestry AdministrationBeijingChina
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Wei F, Swaisgood R, Hu Y, Nie Y, Yan L, Zhang Z, Qi D, Zhu L. Progress in the ecology and conservation of giant pandas. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2015; 29:1497-1507. [PMID: 26372302 DOI: 10.1111/cobi.12582] [Citation(s) in RCA: 87] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2014] [Accepted: 04/15/2015] [Indexed: 06/05/2023]
Abstract
Giant panda (Ailuropoda melanoleuca) conservation is a possible success story in the making. If extinction of this iconic endangered species can be avoided, the species will become a showcase program for the Chinese government and its collaborators. We reviewed the major advancements in ecological science for the giant panda, examining how these advancements have contributed to panda conservation. Pandas' morphological and behavioral adaptations to a diet of bamboo, which bear strong influence on movement ecology, have been well studied, providing knowledge to guide management actions ranging from reserve design to climate change mitigation. Foraging ecology has also provided essential information used in the creation of landscape models of panda habitat. Because habitat loss and fragmentation are major drivers of the panda population decline, efforts have been made to help identify core habitat areas, establish where habitat corridors are needed, and prioritize areas for protection and restoration. Thus, habitat models have provided guidance for the Chinese governments' creation of 67 protected areas. Behavioral research has revealed a complex and efficient communication system and documented the need for protection of habitat that serves as a communication platform for bringing the sexes together for mating. Further research shows that den sites in old-growth forests may be a limiting resource, indicating potential value in providing alternative den sites for rearing offspring. Advancements in molecular ecology have been revolutionary and have been applied to population census, determining population structure and genetic diversity, evaluating connectivity following habitat fragmentation, and understanding dispersal patterns. These advancements form a foundation for increasing the application of adaptive management approaches to move panda conservation forward more rapidly. Although the Chinese government has made great progress in setting aside protected areas, future emphasis will be improved management of pandas and their habitat.
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Affiliation(s)
- Fuwen Wei
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beichenxilu 1-5, Chaoyang District, Beijing, 100101, China
| | - Ronald Swaisgood
- Applied Animal Ecology, San Diego Zoo Institute for Conservation Research, 15600 San Pasqual Valley Road, Escondido, CA, 92027, U.S.A
| | - Yibo Hu
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beichenxilu 1-5, Chaoyang District, Beijing, 100101, China
| | - Yonggang Nie
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beichenxilu 1-5, Chaoyang District, Beijing, 100101, China
| | - Li Yan
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beichenxilu 1-5, Chaoyang District, Beijing, 100101, China
| | - Zejun Zhang
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beichenxilu 1-5, Chaoyang District, Beijing, 100101, China
| | - Dunwu Qi
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beichenxilu 1-5, Chaoyang District, Beijing, 100101, China
| | - Lifeng Zhu
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beichenxilu 1-5, Chaoyang District, Beijing, 100101, China
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Hull V, Roloff G, Zhang J, Liu W, Zhou S, Huang J, Xu W, Ouyang Z, Zhang H, Liu J. A synthesis of giant panda habitat selection. URSUS 2014. [DOI: 10.2192/ursus-d-13-00011.1] [Citation(s) in RCA: 75] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Zhang Z, Sheppard JK, Swaisgood RR, Wang G, Nie Y, Wei W, Zhao N, Wei F. Ecological scale and seasonal heterogeneity in the spatial behaviors of giant pandas. Integr Zool 2014; 9:46-60. [PMID: 24447661 DOI: 10.1111/1749-4877.12030] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
We report on the first study to track the spatial behaviors of wild giant pandas (Ailuropoda melanoleuca) using high-resolution global positioning system (GPS) telemetry. Between 2008 and 2009, 4 pandas (2 male and 2 female) were tracked in Foping Reserve, China for an average of 305 days (± 54.8 SE). Panda home ranges were larger than those of previous very high frequency tracking studies, with a bimodal distribution of space-use and distinct winter and summer centers of activity. Home range sizes were larger in winter than in summer, although there was considerable individual variability. All tracked pandas exhibited individualistic, unoriented and multiphasic movement paths, with a high level of tortuosity within seasonal core habitats and directed, linear, large-scale movements between habitats. Pandas moved from low elevation winter habitats to high elevation (>2000 m) summer habitats in May, when temperatures averaged 17.5 °C (± 0.3 SE), and these large-scale movements took <1 month to complete. The peak in panda mean elevation occurred in Jul, after which they began slow, large-scale movements back to winter habitats that were completed in Nov. An adult female panda made 2 longdistance movements during the mating season. Pandas remain close to rivers and streams during winter, possibly reflecting the elevated water requirements to digest their high-fiber food. Panda movement path tortuosity and first-passage-time as a function of spatial scale indicated a mean peak in habitat search effort and patch use of approximately 700 m. Despite a high degree of spatial overlap between panda home ranges, particularly in winter, we detected neither avoidance nor attraction behavior between conspecifics.
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Affiliation(s)
- Zejun Zhang
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China; San Diego Zoo Institute for Conservation Research, Escondido, California, USA; Institute of Rare Animals and Plants, China West Normal University, Nanchong, China
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