Predicting the Impact of Climate Change on the Selection of Reintroduction Sites for the South China Tiger (Panthera tigris amoyensis) in China
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Data Sources and Processing
2.1.1. Prey Species Screening
2.1.2. Species Distribution Data Search and Screening
2.1.3. Environmental Variable Data Sources and Processing
2.2. Model Optimization and Construction
2.3. Drawing of Distribution Map of Prey and Habitat Suitable for South China Tiger
2.4. Discussion of the Protection Status of Core Alternative Sites
2.5. Estimation of Carrying Capacity of Core Candidate Sites
3. Results
3.1. Changes in Suitable Habitats for Prey under Climate Change
3.2. Distribution and Changes of the Reintroduction Area of the South China Tiger under Climate Change
3.3. Identify Core Candidate Sites for Priority Protection
3.4. Core Candidate Sites Can Support the Survival of Small- and Medium-Sized Populations of South China Tigers
4. Discussion
4.1. Selection of Prey
4.2. Impacts of Climate Change on Prey and the South China Tiger
4.3. The Reintroduction of the South China Tiger into the Wild Requires a Larger and More Stable Habitat
4.4. Assurance for Reintroduction Projects
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Family | Genus | Species | English Name | Weight Range (kg) | National Protection Level | Number of Distribution Points |
---|---|---|---|---|---|---|
Bovidae | Capricornis | Capricornis milneedwardsi | Chinese serow | 85–140 | II | 53 |
Naemorhedus | Naemorhedus griseus | Chinese goral | 40–50 | II | 36 | |
Cervidae | Elaphodus | Elaphodus cephalophus | Tufted deer | 15–28 | II | 95 |
Hydropotes | Hydropotes inermis | Water deer | 15–20 | II | 20 | |
Muntiacus | Muntiacus reevesi | Chinese muntjac | 9–18 | — | 69 | |
Muntiacus vaginalis | Red muntjac | 20–33 | — | 102 | ||
Rusa | Rusa unicolor | Sambar | 100–200 | II | 26 | |
Suidae | Sus | Sus scrofa | Wild boar | 90–200 | — | 98 |
Category | Code | Environmental Factors | Resolution | Data Sources |
---|---|---|---|---|
Climatic factors | bio01 | Annual mean temperature | 30 s | WorldClim (https://worldclim.org/, accessed on 12 July 2023) |
bio02 | Mean diural range | |||
bio03 | Isothermality | |||
bio04 | Temperature seasonality | |||
bio05 | Max temperature of warmest month | |||
bio06 | Min temperature of coldest month | |||
bio07 | Temperature annual range | |||
bio08 | Mean temperature of wettest quarter | |||
bio09 | Mean temperature of driest quarter | |||
bio10 | Mean temperature of warmest quarter | |||
bio11 | Mean temperature of coldest quarter | |||
bio12 | Annual precipitation | |||
bio13 | Precipitation of wettest month | |||
bio14 | Precipitation of driest month | |||
bio15 | Precipitation seasonality | |||
bio16 | Precipitation of wettest quarter | |||
bio17 | Precipitation of driest quarter | |||
bio18 | Precipitation of warmest quarter | |||
bio19 | Precipitation of coldest quarter | |||
Terrain factors | altitude | Altitude | 90 m | Geospatial Data Cloud (https://www.gscloud.cn/, accessed on 26 July 2023) |
slope | Slope | |||
aspect | Aspect | |||
Water source and vegetation factors | ndvi | Normalized Dierential Vegetation Index | 1 km | Resource and Environment Science and Data Center (https://www.resdc.cn/, accessed on 26 July 2023) |
veg | Vegetation type | |||
dis_river | Distance from water sources | 90 m | Geospatial Data Cloud (https://www.gscloud.cn/, accessed on 26 July 2023) | |
Human disturbance factors | dis_human | Distance from residential areas | 1 km | National Catalogue Service For Geographic Information (https://www.webmap.cn/main.do?method=index, accessed on 3 August 2023) |
dis_road | Distance from road | / | open street map (http://download.geofabrik.de/, accessed on 3 August 2023) |
Species | Habitat Suitability | Habitat Area Now (km2) | Habitat Area in 2050 (km2) | Habitat Area in 2070 (km2) | Habitat Change by 2050 (%) | Habitat Change by 2070 (%) |
---|---|---|---|---|---|---|
Capricornis milneedwardsi | High suitable | 54,876 | 50,138 | 27,868 | −8.63% | −49.21% |
Medium suitable | 170,466 | 179,324 | 174,466 | 5.19% | 2.34% | |
Low suitable | 467,156 | 568,799 | 526,289 | 21.75% | 12.65% | |
Naemorhedus griseus | High suitable | 369,149 | 170,345 | 92,282 | −53.85% | −75.00% |
Medium suitable | 640,326 | 493,868 | 397,301 | −22.87% | −37.95% | |
Low suitable | 1,834,674 | 1,400,069 | 1,167,314 | −23.68% | −36.37% | |
Elaphodus cephalophus | High suitable | 213,434 | 236,695 | 76,661 | 10.89% | −64.08% |
Medium suitable | 372,400 | 366,222 | 306,692 | −1.65% | −17.64% | |
Low suitable | 735,084 | 738,912 | 676,538 | 0.52% | −7.96% | |
Hydropotes inermis | High suitable | 1,004,282 | 958,594 | 435,657 | −4.54% | −56.62% |
Medium suitable | 647,448 | 789,096 | 1,158,562 | 21.87% | 78.94% | |
Low suitable | 2,014,916 | 2,081,083 | 1,850,296 | 3.28% | −8.17% | |
Muntiacus reevesi | High suitable | 82,783 | 11,159 | 5184 | −86.52% | −93.73% |
Medium suitable | 249,809 | 58,842 | 29,950 | −76.45% | −88.01% | |
Low suitable | 606,564 | 330,524 | 241,320 | −45.51% | −60.21% | |
Muntiacus vaginalis | High suitable | 45,199 | 132,459 | 120,919 | 193.05% | 167.52% |
Medium suitable | 131,419 | 208,282 | 189,466 | 58.48% | 44.16% | |
Low suitable | 479,220 | 443,652 | 392,290 | −7.42% | −18.13% | |
Rusa unicolor | High suitable | 414,874 | 694,872 | 770,772 | 67.48% | 85.78% |
Medium suitable | 1,074,348 | 1,518,966 | 1,760,765 | 41.38% | 63.89% | |
Low suitable | 1,969,101 | 2,364,065 | 2,512,421 | 20.05% | 27.59% | |
Sus scrofa | High suitable | 645,192 | 609,309 | 522,649 | −5.56% | −18.99% |
Medium suitable | 1,665,352 | 1,598,482 | 1,439,938 | −4.01% | −13.53% | |
Low suitable | 1,715,613 | 2,010,754 | 2,047,950 | 17.20% | 19.37% | |
Panthera tigris amoyensis | High suitable | 240,184 | 169,345 | 85,496 | −29.49% | −64.40% |
Medium suitable | 962,382 | 904,320 | 716,603 | −6.03% | −25.53% | |
Low suitable | 2,176,002 | 2,665,639 | 2,829,683 | 22.50% | 30.04% |
Patch Number | Patch Area/km2 | Protected Areas Involved | Number of Tigers |
---|---|---|---|
1 | 10,054.10 | Cibagou NNR | 23 M, 66 F |
2 | 7518.06 | Giant Panda NP, Heizhugou NNR, Mabian Dafengding NNR, Meigu Dafengding NNR, Bayuelin NR, Mamize NR, Maanshan NR | 17 M, 49 F |
3 | 7002.50 | Giant Panda NP | 16 M, 46 F |
4 | 3667.27 | / | 8 M, 23 F |
5 | 3608.42 | / | 8 M, 23 F |
6 | 2769.58 | Wuyishan NP, Tongbo mountain NR | 6 M, 18 F |
7 | 2736.27 | Giant Panda NP, Jiuzhaigou NR | 6 M, 18 F |
8 | 2619.86 | Jiulongshan NNR | 5 M, 17 F |
9 | 2311.22 | Baima Snow Mountain NNR | 5 M, 15 F |
10 | 1995.02 | Huaping NNR, Maoershan NNR, Nanshan NP | 4 M, 13 F |
11 | 1932.74 | Giant Panda NP | 4 M, 12 F |
12 | 1433.13 | Bamian Mountain NNR, Taoyuandong NNR, Jinggangshan NNR | 3 M, 9 F |
13 | 1234.82 | / | 2 M, 8 F |
14 | 1091.61 | Gaoligong Mountain NNR | 2 M, 7 F |
15 | 1078.57 | Meihuashan NNR | 2 M, 7 F |
16 | 1021.09 | / | 2 M, 6 F |
17 | 1018.29 | Yarlung Zangbo Grand Canyon NNR | 2 M, 6 F |
18 | 991.45 | Hubeishan NNR, Houhe NNR, Mulinzi NNR | 2 M, 6 F |
19 | 925.61 | Nanling NNR, Mangshan NNR | 2 M, 6 F |
20 | 793.57 | Qizimei Mountain NNR, Badagongshan NNR | 1 M, 5 F |
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Luo, Y.; Xu, J.; Zhang, X.; Hou, Y. Predicting the Impact of Climate Change on the Selection of Reintroduction Sites for the South China Tiger (Panthera tigris amoyensis) in China. Animals 2024, 14, 2477. https://doi.org/10.3390/ani14172477
Luo Y, Xu J, Zhang X, Hou Y. Predicting the Impact of Climate Change on the Selection of Reintroduction Sites for the South China Tiger (Panthera tigris amoyensis) in China. Animals. 2024; 14(17):2477. https://doi.org/10.3390/ani14172477
Chicago/Turabian StyleLuo, Yueqing, Jin Xu, Xinyi Zhang, and Yulin Hou. 2024. "Predicting the Impact of Climate Change on the Selection of Reintroduction Sites for the South China Tiger (Panthera tigris amoyensis) in China" Animals 14, no. 17: 2477. https://doi.org/10.3390/ani14172477