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Yang C, Li Q, Wang X, Cui A, Chen J, Liu H, Ma W, Dong X, Shi T, Meng F, Yan X, Ding K, Wu G. Human Expansion-Induced Biodiversity Crisis over Asia from 2000 to 2020. RESEARCH (WASHINGTON, D.C.) 2023; 6:0226. [PMID: 37746659 PMCID: PMC10513745 DOI: 10.34133/research.0226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 08/21/2023] [Indexed: 09/26/2023]
Abstract
Asia stands out as a priority for urgent biodiversity conservation due to its large protected areas (PAs) and threatened species. Since the 21st century, both the highlands and lowlands of Asia have been experiencing the dramatic human expansion. However, the threat degree of human expansion to biodiversity is poorly understood. Here, the threat degree of human expansion to biodiversity over 2000 to 2020 in Asia at the continental (Asia), national (48 Asian countries), and hotspot (6,502 Asian terrestrial PAs established before 2000) scales is investigated by integrating multiple large-scale data. The results show that human expansion poses widespread threat to biodiversity in Asia, especially in Southeast Asia, with Malaysia, Cambodia, and Vietnam having the largest threat degrees (∼1.5 to 1.7 times of the Asian average level). Human expansion in highlands induces higher threats to biodiversity than that in lowlands in one-third Asian countries (most Southeast Asian countries). The regions with threats to biodiversity are present in ∼75% terrestrial PAs (including 4,866 PAs in 26 countries), and human expansion in PAs triggers higher threat degrees to biodiversity than that in non-PAs. Our findings provide novel insight for the Sustainable Development Goal 15 (SDG-15 Life on Land) and suggest that human expansion in Southeast Asian countries and PAs might hinder the realization of SDG-15. To reduce the threat degree, Asian developing countries should accelerate economic transformation, and the developed countries in the world should reduce the demands for commodity trade in Southeast Asian countries (i.e., trade leading to the loss of wildlife habitats) to alleviate human expansion, especially in PAs and highlands.
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Affiliation(s)
- Chao Yang
- MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China
- School of Architecture and Urban Planning,
Shenzhen University, Shenzhen 518060, China
| | - Qingquan Li
- MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China
- College of Civil and Transportation Engineering,
Shenzhen University, Shenzhen 518060, China
- Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen 518107, China
| | - Xuqing Wang
- Center for Hydrogeology and Environmental Geology, China Geological Survey, Baoding 071051, China
| | - Aihong Cui
- Department of Geography, Hong Kong Baptist University, Hong Kong Special Administrative Region 999077, China
| | - Junyi Chen
- Faculty of Land Resource Engineering,
Kunming University of Science and Technology, Kunming 650093, China
| | - Huizeng Liu
- MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China
- Institute for Advanced Study and Tiandu-Shenzhen University Deep Space Joint Laboratory, Shenzhen University, Shenzhen 518060, China
| | - Wei Ma
- School of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074, China
| | - Xuanyan Dong
- Department of Civil and Environmental Engineering,
Tohoku University, Sendai 980-8579, Japan
| | - Tiezhu Shi
- MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China
- School of Architecture and Urban Planning,
Shenzhen University, Shenzhen 518060, China
| | - Fanyi Meng
- MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China
- College of Civil and Transportation Engineering,
Shenzhen University, Shenzhen 518060, China
| | - Xiaohu Yan
- School of Artificial Intelligence,
Shenzhen Polytechnic, Shenzhen 518055, China
| | - Kai Ding
- School of Computer Science and Technology,
Dongguan University of Technology, Dongguan 523419, China
| | - Guofeng Wu
- MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China
- School of Architecture and Urban Planning,
Shenzhen University, Shenzhen 518060, China
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2
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Gao Y, Lee ATL, Luo Y, Alexander JS, Shi X, Sangpo T, Clark SG. Large carnivore encounters through the lens of mobile videos on social media. CONSERVATION SCIENCE AND PRACTICE 2023. [DOI: 10.1111/csp2.12907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/18/2023] Open
Affiliation(s)
- Yufang Gao
- School of the Environment Yale University New Haven Connecticut USA
- Department of Anthropology Yale University New Haven Connecticut USA
- China Conservation Support Beijing China
| | - Andy T. L. Lee
- China Conservation Support Beijing China
- RESOLVE Washington District of Columbia USA
| | - Yu Luo
- Department of Sociology and Anthropology University of Puget Sound Tacoma Washington USA
| | - Justine Shanti Alexander
- The Snow Leopard Trust Seattle Washington USA
- Department of Ecology and Evolution University of Lausanne Lausanne Switzerland
| | - Xiangying Shi
- Shanshui Conservation Center Beijing China
- College of Environmental Science and Engineering Peking University Beijing China
| | - Tashi Sangpo
- Nyanpo Yutse Conservation Association Jiuzhi China
| | - Susan G. Clark
- School of the Environment Yale University New Haven Connecticut USA
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Rule A, Dill SE, Sun G, Chen A, Khawaja S, Li I, Zhang V, Rozelle S. Challenges and Opportunities in Aligning Conservation with Development in China's National Parks: A Narrative Literature Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:12778. [PMID: 36232085 PMCID: PMC9566203 DOI: 10.3390/ijerph191912778] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Revised: 09/26/2022] [Accepted: 10/04/2022] [Indexed: 06/16/2023]
Abstract
As part of its effort to balance economic development with environmental objectives, China has established a new national park system, with the first five locations formally established in 2021. However, as the new parks all host or are proximate to human populations, aligning the socioeconomic needs and aspirations of local communities with conservation aims is critical for the long-term success of the parks. In this narrative review, the authors identify the ecological priorities and socioeconomic stakeholders of each of the five national parks; explore the tensions and synergies between these priorities and stakeholders; and synthesize the policy recommendations most frequently cited in the literature. A total of 119 studies were reviewed. Aligning traditional livelihoods with conservation, limiting road construction, promoting education and environmental awareness, and supporting the development of a sustainable tourism industry are identified as important steps to balance conservation with economic development in the new national parks.
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Yang C, Liu H, Li Q, Wang X, Ma W, Liu C, Fang X, Tang Y, Shi T, Wang Q, Xu Y, Zhang J, Li X, Xu G, Chen J, Su M, Wang S, Wu J, Huang L, Li X, Wu G. Human expansion into Asian highlands in the 21st Century and its effects. Nat Commun 2022; 13:4955. [PMID: 36002452 PMCID: PMC9402921 DOI: 10.1038/s41467-022-32648-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2021] [Accepted: 08/09/2022] [Indexed: 11/08/2022] Open
Abstract
Most intensive human activities occur in lowlands. However, sporadic reports indicate that human activities are expanding in some Asian highlands. Here we investigate the expansions of human activities in highlands and their effects over Asia from 2000 to 2020 by combining earth observation data and socioeconomic data. We find that ∼23% of human activity expansions occur in Asian highlands and ∼76% of these expansions in highlands comes from ecological lands, reaching 95% in Southeast Asia. The expansions of human activities in highlands intensify habitat fragmentation and result in large ecological costs in low and lower-middle income countries, and they also support Asian developments. We estimate that cultivated land net growth in the Asian highlands contributed approximately 54% in preventing the net loss of the total cultivated land. Moreover, the growth of highland artificial surfaces may provide living and working spaces for ∼40 million people. Our findings suggest that highland developments hold dual effects and provide new insight for regional sustainable developments.
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Affiliation(s)
- Chao Yang
- MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong-Hong Kong-Macau Joint Laboratory for Smart Cities & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen, 518060, China
- School of Architecture and Urban Planning, Shenzhen University, Shenzhen, 518060, China
| | - Huizeng Liu
- MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong-Hong Kong-Macau Joint Laboratory for Smart Cities & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen, 518060, China
- Institute for Advanced Study, Shenzhen University, Shenzhen, 518060, China
| | - Qingquan Li
- MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong-Hong Kong-Macau Joint Laboratory for Smart Cities & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen, 518060, China.
| | - Xuqing Wang
- Center for Hydrogeology and Environmental Geology, China Geological Survey, Nanjing, 210000, China
| | - Wei Ma
- School of Civil Engineering, Chongqing Jiaotong University, Chongqing, 400074, China
| | - Cuiling Liu
- MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong-Hong Kong-Macau Joint Laboratory for Smart Cities & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen, 518060, China
- School of Architecture and Urban Planning, Shenzhen University, Shenzhen, 518060, China
| | - Xu Fang
- MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong-Hong Kong-Macau Joint Laboratory for Smart Cities & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen, 518060, China
- College of Electronics and Information Engineering, Shenzhen University, Shenzhen, 518060, China
| | - Yuzhi Tang
- MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong-Hong Kong-Macau Joint Laboratory for Smart Cities & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen, 518060, China
| | - Tiezhu Shi
- MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong-Hong Kong-Macau Joint Laboratory for Smart Cities & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen, 518060, China
- School of Architecture and Urban Planning, Shenzhen University, Shenzhen, 518060, China
| | - Qibiao Wang
- Anhui Zhonghui Urban Planning Survey & Design Institute, Tongling, 244000, China
| | - Yue Xu
- MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong-Hong Kong-Macau Joint Laboratory for Smart Cities & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen, 518060, China
| | - Jie Zhang
- College of Information and Electrical Engineering, China Agricultural University, Beijing, 100083, China
| | - Xuecao Li
- College of Land Science and Technology, China Agricultural University, Beijing, 100083, China
| | - Gang Xu
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, 430079, China
| | - Junyi Chen
- Key Laboratory of Virtual Geographic Environment of the Ministry of Education, Nanjing Normal University, Nanjing, 210000, China
| | - Mo Su
- Shenzhen Urban Planning and Land Resource Research Center, Shenzhen, 518034, China
| | - Shuying Wang
- MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong-Hong Kong-Macau Joint Laboratory for Smart Cities & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen, 518060, China
| | - Jinjing Wu
- MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong-Hong Kong-Macau Joint Laboratory for Smart Cities & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen, 518060, China
| | - Leping Huang
- MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong-Hong Kong-Macau Joint Laboratory for Smart Cities & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen, 518060, China
| | - Xue Li
- MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong-Hong Kong-Macau Joint Laboratory for Smart Cities & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen, 518060, China
| | - Guofeng Wu
- MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong-Hong Kong-Macau Joint Laboratory for Smart Cities & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen, 518060, China.
- School of Architecture and Urban Planning, Shenzhen University, Shenzhen, 518060, China.
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Anthropogenic food: an emerging threat to polar bears. ORYX 2022. [DOI: 10.1017/s0030605322000278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Abstract
Supplemental food from anthropogenic sources is a source of conflict with humans for many wildlife species. Food-seeking behaviours by black bears Ursus americanus and brown bears Ursus arctos can lead to property damage, human injury and mortality of the offending bears. Such conflicts are a well-known conservation management issue wherever people live in bear habitats. In contrast, the use of anthropogenic foods by the polar bear Ursus maritimus is less common historically but is a growing conservation and management issue across the Arctic. Here we present six case studies that illustrate how negative food-related interactions between humans and polar bears can become either chronic or ephemeral and unpredictable. Our examination suggests that attractants are an increasing problem, exacerbated by climate change-driven sea-ice losses that cause increased use of terrestrial habitats by bears. Growing human populations and increased human visitation increase the likelihood of human–polar bear conflict. Efforts to reduce food conditioning in polar bears include attractant management, proactive planning and adequate resources for northern communities to reduce conflicts and improve human safety. Permanent removal of unsecured sources of nutrition, to reduce food conditioning, should begin immediately at the local level as this will help to reduce polar bear mortality.
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Hairong D, Xiaoliang Z, Minghai Z, Xiangdong R, Lee TM. Spatial Distribution and Conservation Strategies of Large Carnivores in Human-Dominated Landscape: A Case Study of Asiatic Black Bear in Jilin, China. Front Ecol Evol 2022. [DOI: 10.3389/fevo.2022.882282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Large carnivores maintain the balance of ecosystems. Understanding distribution and population changes are necessary prerequisites for scientific conservation strategy. The east of Jilin Province is the habitat of endangered Amur tiger (Panthera tigris altaica). The Chinese government has focused the monitoring on protecting the Amur tiger. However, little is known about Asiatic black bear (ABB, Ursus thibetanus) distribution, population dynamics in the wild, and protection awareness of local residents in Jilin Province, China. We conducted a integrative survey in mountain areas of eastern Jilin to determine ABB distribution. We explored the drivers of the distribution of ABB in Jilin using logstic regression, we further predicted the habitat suitability and potential suitable habitat of the ABB. Totally, we surveyed 112 grids (15 km × 15 km) from November 2015 to January 2019. Logistic regression analysis revealed that the main factors driving ABB distribution in Jilin are forest coverage, distance from protected areas, distance from main roads (railways and highways), and distance from water bodies. The results of questionnaire survey showed that the local residents’ understanding of ABB distribution is congruent with our field research. They believed that the number of ABBs has gradually increased in the past ten years. Nevertheless, the local residents have a negative attitude toward the ABBs, which may adversely affect efforts to protect them, possibly leading to more conflicts between humans and bears. Therefore, there is a need to consider ways to change the attitude of the locals through the strengthening of the protection propaganda and advocating management as being critical for the protection of ABBs. Our research provides a scientific basis for future conservation planning. We recommend taking local people’s attitude into consideration during conservation management strategy making to reduce human-bear conflicts and promote the coexistence of humans and bears.
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Affiliation(s)
- Duo Yin
- School of Geography and Remote Sensing, Guangzhou University, Higher Education Mega Center, Guangzhou, 510006, China
| | - Zhenjie Yuan
- School of Geography and Remote Sensing, Guangzhou University, Higher Education Mega Center, Guangzhou, 510006, China
| | - Jie Li
- School of Geography and Remote Sensing, Guangzhou University, Higher Education Mega Center, Guangzhou, 510006, China
| | - Hong Zhu
- School of Geography and Remote Sensing, Guangzhou University, Higher Education Mega Center, Guangzhou, 510006, China.
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Maheshwari A, Kumar AA, Sathyakumar S. Assessment of changes over a decade in the patterns of livestock depredation by the Himalayan Brown Bear in Ladakh, India. JOURNAL OF THREATENED TAXA 2021. [DOI: 10.11609/jott.7177.13.7.18695-18702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Abstract
Conflicts between large carnivores and shepherds constitute a major socio-ecological concern across the Himalaya and affects community attitudes and tolerance toward carnivores. We assessed the extent and intensity of Human-Brown Bear interactions in the same villages of Zanskar and Suru Valleys, Ladakh, in the Indian Trans-Himalaya during two time periods (2001–2003 and 2009–2012) through field and questionnaire surveys. During 2001–2003, 180 families of 32 villages in Zanskar, and 232 families of 49 villages in Suru were interviewed, and during 2009–2012, 145 families of 23 villages in Zanskar and 115 families of 33 villages in Suru were interviewed. Overall, 475 (119/year) and 454 (151/year) heads of livestock were reportedly killed by Brown Bears. The surveys of 2009–2012 revealed that livestock predation in ‘doksas’ (summer grazing camps) was higher (68 %) compared to the surveys carried out during 2001–2003 (42 %). The increased livestock depredation in doksas might be due to the extended stay and use of pastures by the local communities during spring and autumn. Damage to property in the form of breaking open of doors and windows by Brown Bear were reported during both the surveys. Economic losses and declining tolerance of people may trigger retaliatory killings of Brown Bear in Ladakh. We recommend compensation for livestock loss and improved husbandry practices in the conflict zones for bear-human coexistence.
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Dai Y, Hacker CE, Cao Y, Cao H, Xue Y, Ma X, Liu H, Zahoor B, Zhang Y, Li D. Implementing a comprehensive approach to study the causes of human-bear (Ursus arctos pruinosus) conflicts in the Sanjiangyuan region, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 772:145012. [PMID: 33581527 DOI: 10.1016/j.scitotenv.2021.145012] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2020] [Revised: 01/01/2021] [Accepted: 01/02/2021] [Indexed: 06/12/2023]
Abstract
Personal injury and property loss caused by wildlife often deteriorates the relationship between humans and animals, prompting retaliatory killings that threaten species survival. Conflicts between humans and Tibetan brown bears (Ursus arctos pruinosus) (Human-Bear Conflicts, HBC) in the Sanjiangyuan region have recently dramatically increased, seriously affecting community enthusiasm for brown bears and the conservation of other species. In order to understand the driving mechanisms of HBC, we proposed six potential drivers leading to increased occurrences of HBC. We conducted field research in Zhiduo County of the Sanjiangyuan region from 2017 to 2019 to test hypotheses through semi-constructed interviews, marmot (Marmota himalayana) density surveys and brown bear diet analysis based on metagenomic sequencing. Analysis of herder perceptions revealed that the driving factors of HBC were related to changes in their settlement practice and living habits, changes in foraging behavior of brown bears and recovery of the brown bear population. Since the establishment of winter homes, brown bears have gradually learned to utilize the food in unattended homes. Although 91.4% (n = 285) of the respondents no longer store food in unattended homes, brown bears were reported to still frequently approach winter homes for food due to improper disposal of dead livestock and household garbage. The frequency and abundance of marmots were found to be high in brown bear diet, indicating that marmots were the bears' primary food. However, marmot density had no significant effect on brown bears utilizing human food (P = 0.329), and HBC appears to not be caused by natural food shortages. Distance to rocky outcrops (P = 0.022) and winter homes (P = 0.040) were the key factors linked to brown bears pursuing human food. The number of brown bears has increased over the past decade, and HBC is likely linked to its population recovery. Our findings will provide scientific basis for formulating effective mitigation measures and protection countermeasures for brown bears.
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Affiliation(s)
- Yunchuan Dai
- Institute for Ecology and Environmental Resources, Chongqing Academy of Social Sciences, Chongqing 400020, China; Research Center for Ecological Security and Green Development, Chongqing Academy of Social Sciences, Chongqing 400020, China; Research Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Beijing 100091, China
| | - Charlotte E Hacker
- Department of Biological Sciences, Duquesne University, Pittsburgh, PA 15282, USA
| | - Yu Cao
- School of Public Administration, Chongqing University, Chongqing 400000, China
| | - Hanning Cao
- The High School Affiliated to Renmin University of China, Beijing 100084, China
| | - Yadong Xue
- Research Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Beijing 100091, China
| | - Xiaodong Ma
- Research and Development Center for Grass and Environment, Beijing Academy of Agriculture and Forestry Sciences, Beijing 10097, China
| | - Haodong Liu
- Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China
| | - Babar Zahoor
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Yuguang Zhang
- Research Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Beijing 100091, China.
| | - Diqiang Li
- Research Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Beijing 100091, China.
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