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Ding P, Song Z, Liu Y, Halimubieke N, Székely T, Shi L. Nesting Habitat Suitability of the Kentish Plover in the Arid Lands of Xinjiang, China. Animals (Basel) 2023; 13:3369. [PMID: 37958123 PMCID: PMC10648522 DOI: 10.3390/ani13213369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Revised: 10/28/2023] [Accepted: 10/29/2023] [Indexed: 11/15/2023] Open
Abstract
Understanding the main ecological factors of the nesting habitat of shorebirds is of great significance in relation to their protection and habitat management. Habitat loss and change due to a lack of water threaten the biodiversity of shorebirds, with impacts likely to be most pronounced in arid lands. We collected the data of 144 nesting sites and 10 ecological factors during the breeding season from April to July each year in 2019 and 2020 in nine river districts in Xinjiang. The MaxEnt model was applied to assess the suitability of nesting habitats for Kentish plovers (Charadrius alexandrinus) in the study area to examine the main factors affecting their nesting habitat. The most suitable nesting habitats are mostly distributed in plain reservoirs in the middle part of the Northern Slope of the Tianshan Mountains, Ebinur Lake and its eastern position in the southwestern Junggar Basin, near Ulungur Lake of the Ulungur river area and the southern Irtysh river area. The distance from water, normalized difference vegetation index, mean temperature of the breeding season, slope, and land use were the main factors affecting the nesting habitat selection of Kentish plovers. It was found that the proportion of suitable nesting habitat protected for the Kentish plovers in the study area was low (851.66 km2), accounting for only 11.02% of the total suitable nesting habitat area. In view of the scarcity and importance of water bodies in arid lands and the lack of protection for Kentish plovers at present, it is suggested to strengthen the conservation and management of the regional shorebirds and their habitats by regulating and optimizing the allocation of water resources.
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Affiliation(s)
- Peng Ding
- College of Animal Sciences, Xinjiang Agricultural University, Urumqi 830052, China;
- Xinjiang Key Laboratory for Ecological Adaptation and Evolution of Extreme Environment Biology, College of Life Sciences, Xinjiang Agricultural University, Urumqi 830052, China
| | - Zitan Song
- State Key Laboratory of Biocontrol, School of Ecology, Sun Yat-sen University, Shenzhen 518107, China; (Z.S.); (Y.L.)
- Comparative Socioecology Group, Max Planck Institute of Animal Behavior, 78467 Konstanz, Germany
| | - Yang Liu
- State Key Laboratory of Biocontrol, School of Ecology, Sun Yat-sen University, Shenzhen 518107, China; (Z.S.); (Y.L.)
| | - Naerhulan Halimubieke
- Milner Centre for Evolution, Department of Biology and Biochemistry, University of Bath, Bath BA1 7AY, UK; (N.H.); (T.S.)
| | - Tamás Székely
- Milner Centre for Evolution, Department of Biology and Biochemistry, University of Bath, Bath BA1 7AY, UK; (N.H.); (T.S.)
- Department of Evolutionary Zoology and Human Biology, University of Debrecen, H-4032 Debrecen, Hungary
| | - Lei Shi
- College of Animal Sciences, Xinjiang Agricultural University, Urumqi 830052, China;
- Xinjiang Key Laboratory for Ecological Adaptation and Evolution of Extreme Environment Biology, College of Life Sciences, Xinjiang Agricultural University, Urumqi 830052, China
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Wang Z, Kang Y, Wang Y, Tan Y, Yao B, An K, Su J. Himalayan Marmot ( Marmota himalayana) Redistribution to High Latitudes under Climate Change. Animals (Basel) 2023; 13:2736. [PMID: 37684999 PMCID: PMC10486415 DOI: 10.3390/ani13172736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 08/23/2023] [Accepted: 08/25/2023] [Indexed: 09/10/2023] Open
Abstract
Climate warming and human activities impact the expansion and contraction of species distribution. The Himalayan marmot (Marmota himalayana) is a unique mammal and an ecosystem engineer in the Qinghai-Tibet Plateau (QTP). This pest aggravates grassland degradation and is a carrier and transmitter of plagues. Therefore, exploring the future distribution of Himalayan marmots based on climate change and human activities is crucial for ecosystem management, biodiversity conservation, and public health safety. Here, a maximum entropy model was explored to forecast changes in the distribution and centroid migration of the Himalayan marmot in the 2050s and 2070s. The results implied that the human footprint index (72.80%) and altitude (16.40%) were the crucial environmental factors affecting the potential distribution of Himalayan marmots, with moderately covered grassland being the preferred habitat of the Himalayan marmot. Over the next 30-50 years, the area of suitable habitat for the Himalayan marmot will increase slightly and the distribution center will shift towards higher latitudes in the northeastern part of the plateau. These results demonstrate the influence of climate change on Himalayan marmots and provide a theoretical reference for ecological management and plague monitoring.
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Affiliation(s)
- Zhicheng Wang
- College of Grassland Science, Gansu Agricultural University, Lanzhou 730070, China; (Z.W.); (K.A.)
- Key Laboratory of Grassland Ecosystem (Ministry of Education), Gansu Agricultural University, Lanzhou 730070, China
- Gansu Agricultural University-Massey University Research Centre for Grassland Biodiversity, Gansu Agricultural University, Lanzhou 730070, China
| | - Yukun Kang
- College of Grassland Science, Gansu Agricultural University, Lanzhou 730070, China; (Z.W.); (K.A.)
- Key Laboratory of Grassland Ecosystem (Ministry of Education), Gansu Agricultural University, Lanzhou 730070, China
- Gansu Agricultural University-Massey University Research Centre for Grassland Biodiversity, Gansu Agricultural University, Lanzhou 730070, China
| | - Yan Wang
- College of Grassland Science, Gansu Agricultural University, Lanzhou 730070, China; (Z.W.); (K.A.)
- Key Laboratory of Grassland Ecosystem (Ministry of Education), Gansu Agricultural University, Lanzhou 730070, China
- Gansu Agricultural University-Massey University Research Centre for Grassland Biodiversity, Gansu Agricultural University, Lanzhou 730070, China
| | - Yuchen Tan
- College of Grassland Science, Gansu Agricultural University, Lanzhou 730070, China; (Z.W.); (K.A.)
- Key Laboratory of Grassland Ecosystem (Ministry of Education), Gansu Agricultural University, Lanzhou 730070, China
- Gansu Agricultural University-Massey University Research Centre for Grassland Biodiversity, Gansu Agricultural University, Lanzhou 730070, China
| | - Baohui Yao
- College of Grassland Science, Gansu Agricultural University, Lanzhou 730070, China; (Z.W.); (K.A.)
- Key Laboratory of Grassland Ecosystem (Ministry of Education), Gansu Agricultural University, Lanzhou 730070, China
- Gansu Agricultural University-Massey University Research Centre for Grassland Biodiversity, Gansu Agricultural University, Lanzhou 730070, China
| | - Kang An
- College of Grassland Science, Gansu Agricultural University, Lanzhou 730070, China; (Z.W.); (K.A.)
- Key Laboratory of Grassland Ecosystem (Ministry of Education), Gansu Agricultural University, Lanzhou 730070, China
- Gansu Agricultural University-Massey University Research Centre for Grassland Biodiversity, Gansu Agricultural University, Lanzhou 730070, China
| | - Junhu Su
- College of Grassland Science, Gansu Agricultural University, Lanzhou 730070, China; (Z.W.); (K.A.)
- Key Laboratory of Grassland Ecosystem (Ministry of Education), Gansu Agricultural University, Lanzhou 730070, China
- Gansu Agricultural University-Massey University Research Centre for Grassland Biodiversity, Gansu Agricultural University, Lanzhou 730070, China
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Cao B, Bai C, Wu K, La T, Su Y, Che L, Zhang M, Lu Y, Gao P, Yang J, Xue Y, Li G. Tracing the future of epidemics: Coincident niche distribution of host animals and disease incidence revealed climate-correlated risk shifts of main zoonotic diseases in China. GLOBAL CHANGE BIOLOGY 2023; 29:3723-3746. [PMID: 37026556 DOI: 10.1111/gcb.16708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 03/13/2023] [Accepted: 03/18/2023] [Indexed: 06/06/2023]
Abstract
Climate has critical roles in the origin, pathogenesis and transmission of infectious zoonotic diseases. However, large-scale epidemiologic trend and specific response pattern of zoonotic diseases under future climate scenarios are poorly understood. Here, we projected the distribution shifts of transmission risks of main zoonotic diseases under climate change in China. First, we shaped the global habitat distribution of main host animals for three representative zoonotic diseases (2, 6, and 12 hosts for dengue, hemorrhagic fever, and plague, respectively) with 253,049 occurrence records using maximum entropy (Maxent) modeling. Meanwhile, we predicted the risk distribution of the above three diseases with 197,098 disease incidence records from 2004 to 2017 in China using an integrated Maxent modeling approach. The comparative analysis showed that there exist highly coincident niche distributions between habitat distribution of hosts and risk distribution of diseases, indicating that the integrated Maxent modeling is accurate and effective for predicting the potential risk of zoonotic diseases. On this basis, we further projected the current and future transmission risks of 11 main zoonotic diseases under four representative concentration pathways (RCPs) (RCP2.6, RCP4.5, RCP6.0, and RCP8.5) in 2050 and 2070 in China using the above integrated Maxent modeling with 1,001,416 disease incidence records. We found that Central China, Southeast China, and South China are concentrated regions with high transmission risks for main zoonotic diseases. More specifically, zoonotic diseases had diverse shift patterns of transmission risks including increase, decrease, and unstable. Further correlation analysis indicated that these patterns of shifts were highly correlated with global warming and precipitation increase. Our results revealed how specific zoonotic diseases respond in a changing climate, thereby calling for effective administration and prevention strategies. Furthermore, these results will shed light on guiding future epidemiologic prediction of emerging infectious diseases under global climate change.
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Affiliation(s)
- Bo Cao
- Core Research Laboratory, The Second Affiliated Hospital, School of Medicine, Xi'an Jiaotong University, Xi'an, China
- College of Life Sciences, Shaanxi Normal University, Xi'an, China
| | - Chengke Bai
- College of Life Sciences, Shaanxi Normal University, Xi'an, China
| | - Kunyi Wu
- Core Research Laboratory, The Second Affiliated Hospital, School of Medicine, Xi'an Jiaotong University, Xi'an, China
| | - Ting La
- National-Local Joint Engineering Research Center of Biodiagnosis & Biotherapy, The Second Affiliated Hospital, School of Medicine, Xi'an Jiaotong University, Xi'an, China
| | - Yiyang Su
- College of Life Sciences, Shaanxi Normal University, Xi'an, China
| | - Lingyu Che
- College of Life Sciences, Shaanxi Normal University, Xi'an, China
| | - Meng Zhang
- College of Life Sciences, Shaanxi Normal University, Xi'an, China
| | - Yumeng Lu
- College of Life Sciences, Shaanxi Normal University, Xi'an, China
| | - Pufan Gao
- College of Life Sciences, Shaanxi Normal University, Xi'an, China
| | - Jingjing Yang
- College of Life Sciences, Shaanxi Normal University, Xi'an, China
| | - Ying Xue
- College of Life Sciences, Shaanxi Normal University, Xi'an, China
| | - Guishuang Li
- College of Life Sciences, Shaanxi Normal University, Xi'an, China
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Yousefi M, Mohammadi S, Kafash A. Modeling global habitat suitability and environmental predictor of distribution of a Near Threatened avian scavenger at a high spatial resolution. Front Ecol Evol 2023. [DOI: 10.3389/fevo.2023.1112962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023] Open
Abstract
Vultures are among the most vulnerable birds in the world. The bearded vulture (Gypaetus barbatus) is among the threatened species of vultures and listed as Near Threatened. The species is widely distributed across the Palearctic, Afrotropical, and Indomalayan regions. The species faces several threats such as poisoning, direct persecution, habitat degradation, and collisions with powerlines and wind power farms. Thus, knowing the global habitat suitability of the species and environmental predictors of the species distribution can facilitate the species conservation. In this study, we applied a maximum entropy approach, 10,585 distribution records, and 10 environmental variables to model the bearded vulture's global habitat suitability at high spatial resolution [30-arc-second (1 km)]. We also estimated protected area coverage for the species' suitable habitats. We identified 8,117,231 km2 of suitable habitat for the species across its global range in Europe, Asia, and Africa. The results showed that topographic diversity is the most important predictor of the species distribution across its distribution range. Results of estimating the area of suitable habitats of the bearded vulture within protected areas revealed that only 16.26% of the species' suitable habitats are protected. The areas that were identified to have the highest suitability for the species have high priority for the conservation of this iconic species thus these areas should be included in the network of protected areas.
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Projected Shifts in Bird Distribution in India under Climate Change. DIVERSITY 2023. [DOI: 10.3390/d15030404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
Abstract
Global climate change is causing unprecedented impacts on biodiversity. In India, there is little information available regarding how climate change affects biodiversity at the taxon/group level, and large-scale ecological analyses have been lacking. In this study, we demonstrated the applicability of eBird and GBIF (Global Biodiversity Information Facility), and produced national-scale forecasts to examine the possible impacts of climate change on terrestrial avifauna in India. Using data collected by citizen scientists, we developed fine-tuned Species Distribution Models (SDMs) and predicted 1091 terrestrial bird species that would be distributed in India by 2070 on two climatic surfaces (RCP 4.5 and 8.5), using Maximum Entropy-based species distribution algorithms. Of the 1091 species modelled, our findings indicate that 66–73% of bird species in India will shift to higher elevations or shift northward, and 58–59% of bird species (RCP 4.5 and 8.5) would lose a portion of their distribution ranges. Furthermore, distribution ranges of 41–40% of bird species would increase. Under both RCP scenarios (RCP 4.5 and 8.5), bird species diversity will significantly increase in regions above 2500 m in elevation. Both RCP scenarios predict extensive changes in the species richness of the western Himalayas, Sikkim, northeast India, and the western Ghats regions by 2070. This study has resulted in novel, high-resolution maps of terrestrial bird species richness across India, and we predict predominantly northward shifts in species ranges, similar to predictions made for avifauna in other regions, such as Europe and the USA.
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Barnacle geese Branta leucopsis breeding on Novaya Zemlya: current distribution and population size estimated from tracking data. Polar Biol 2022. [DOI: 10.1007/s00300-022-03110-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
AbstractThe Russian breeding population of barnacle geese Branta leucopsis has shown a rapid increase in numbers since 1980, which has coincided with a southwest-wards breeding range expansion within the Russian Arctic. Here barnacle geese also started to occupy coastal and marsh land habitats, in which they were not know to nest on their traditional breeding grounds. While these changes have been well documented by studies and observations throughout the new breeding range of barnacle geese, observations are lacking from the traditional breeding grounds on Novaya Zemlya, as this area is remote and difficult to access. This is especially relevant given rapid climate warming in this area, which may impact local distribution and population size. We used GPS-tracking and behavioural biologging data from 46 individual barnacle geese captured on their wintering grounds to locate nest sites in the Russian Arctic and study nesting distribution in 2008–2010 and 2018–2020. Extrapolating from nest counts on Kolguev Island, we estimate the breeding population on Novaya Zemlya in 2018–2020 to range around 75,250 pairs although the confidence interval around this estimate was large. A comparison with the historical size of the barnacle goose population suggests an increase in the breeding population on Novaya Zemlya, corresponding with changes in other areas of the breeding range. Our results show that many barnacle geese on Novaya Zemlya currently nest on lowland tundra on Gusinaya Zemlya Peninsula. This region has been occupied by barnacle geese only since 1990 and appears to be mainly available for nesting in years with early spring. Tracking data are a valuable tool to increase our knowledge of remote locations, but counts of breeding individuals or nests are needed to further corroborate estimates of breeding populations based on tracking data.
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Zhang MX, Chen Y, Guo JX, Zhang R, Bi YQ, Wei XX, Niu H, Zhang CH, Li MH. Complex ecological and socioeconomic impacts on medicinal plant diversity. Front Pharmacol 2022; 13:979890. [PMID: 36339592 PMCID: PMC9627218 DOI: 10.3389/fphar.2022.979890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Accepted: 10/10/2022] [Indexed: 11/21/2022] Open
Abstract
Medicinal plant diversity (MPD) is an important component of plant diversity. Over-collection based on medicinal and economic value has the potential to damage the stability of the regional ecosystem. It is important to understand the current distribution of MPD and the factors influencing it. However, it is still unclear whether environmental and socioeconomic conditions have an impact on their distribution. We selected the Inner Mongolia as a representative study area which covers a wide area, accounting for 12.29% of China’s national land area and 0.79% of the world’s land area. At the same time, the region is a long-standing traditional medicinal area for Mongolians in China. Therefore, the region is significantly influenced by changes in environmental factors and socio-economic factors. We used 9-years field survey of the distribution of medicinal plants in Inner Mongolia for assessing the distribution of MPD as influenced by environmental and socioeconomic activities by combining spatial analyses, species distribution models, and generalized additive models. The results from the spatial analysis show that the western region of Inner Mongolia is the main cold spot area of the MPD, and the central-eastern and northeastern regions of Inner Mongolia are the main hot spot areas of the MPD. At the same time, the distribution of cold spots and hot spots of MPD is more obvious at large spatial scales, and with the refinement of spatial scales, the cold spots in scattered areas are gradually revealed, which is indicative for the conservation and development of MPD at different spatial scales. Under the future climate change of shared socioeconomic pathways (SSP), areas with high habitat suitability for medicinal plants remain mainly dominated by the Yellow River, Yin Mountains, and Greater Khingan Range. Notably, the SSP245 development pathway remains the most significant concern in either long- or short-term development. The nonlinear relationship between the driving factors of MPD at different spatial scales shows that temperature, precipitation and socioeconomic development do have complex effects on MPD. The presence of a certain temperature, altitude, and precipitation range has an optimal facilitation effect on MPD, rather than a single facilitation effect. This complex nonlinear correlation provides a reference for further studies on plant diversity and sustainable development and management. In this study, the spatial distribution of medicinal plant resources and the extent to which they are driven by ecological and socioeconomic factors were analyzed through a macroscopic approach. This provides a reference for larger-scale studies on the environmental and socioeconomic influences on the distribution of plant resources.
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Affiliation(s)
- Ming-Xu Zhang
- Inner Mongolia Hospital of Traditional Chinese Medicine, Hohhot, China
- Inner Mongolia Institute of Traditional Chinese and Mongolian Medicine, Hohhot, China
- Baotou Medical College, Baotou, China
| | - Yuan Chen
- Inner Mongolia Medical University, Hohhot, China
| | | | - Ru Zhang
- Baotou Medical College, Baotou, China
| | - Ya-Qiong Bi
- Inner Mongolia Institute of Traditional Chinese and Mongolian Medicine, Hohhot, China
| | | | - Hui Niu
- Baotou Medical College, Baotou, China
| | - Chun-Hong Zhang
- Baotou Medical College, Baotou, China
- *Correspondence: Chun-Hong Zhang, ; Min-Hui Li,
| | - Min-Hui Li
- Inner Mongolia Hospital of Traditional Chinese Medicine, Hohhot, China
- Inner Mongolia Institute of Traditional Chinese and Mongolian Medicine, Hohhot, China
- Baotou Medical College, Baotou, China
- Inner Mongolia Medical University, Hohhot, China
- Inner Mongolia University, Hohhot, China
- Inner Mongolia Key Laboratory of Characteristic Geoherbs Resources Protection and Utilization, Baotou, China
- *Correspondence: Chun-Hong Zhang, ; Min-Hui Li,
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