基于MAXENT模型的秦岭山系黑熊潜在生境评价

doi:10.3724/SP.J.1003.2011.10288

生物多样性 ›› 2011, Vol. 19 ›› Issue (3): 343-352. DOI: 10.3724/SP.J.1003.2011.10288

基于MAXENT模型的秦岭山系黑熊潜在生境评价

齐增湘¹^,², 徐卫华²^,^*(), 熊兴耀¹, 欧阳志云², 郑华², 甘德欣¹

1 (湖南农业大学园艺园林学院, 长沙 410128)
2 (中国科学院生态环境研究中心城市与区域生态国家重点实验室, 北京 100085)

收稿日期:2010-12-02 接受日期:2011-04-14 出版日期:2011-05-20 发布日期:2013-12-10
通讯作者: 徐卫华
作者简介:*E-mail:xuweihua@rcees.ac.cn
基金资助:
国家自然科学基金(40901289);国家重点基础研究发展计划项目(2009CB421104);世界自然基金会(WWF)项目

Assessment of potential habitat for Ursus thibetanus in the Qinling Moun- tains

Zengxiang Qi¹^,², Weihua Xu²^,^*(), Xingyao Xiong¹, Zhiyun Ouyang², Hua Zheng², Dexin Gan¹

1 College of Horticulture & Landscape, Hunan Agricultural University, Changsha 410128
2 State Key Laboratory of Regional and Urban Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085

Received:2010-12-02 Accepted:2011-04-14 Online:2011-05-20 Published:2013-12-10
Contact: Weihua Xu

摘要/Abstract

摘要：

明确物种生境空间分布格局及其与环境因子的关系, 对制定合理有效的保护对策十分重要。本文以黑熊(Ursus thibetanus)为研究对象, 以其重要栖息地秦岭山系为研究区域, 选取68个黑熊分布点数据和34个环境因子, 应用MAXENT模型分析其生境空间分布及主要影响因子, 以最大化Kappa值的生境适宜性指数为阈值划分适宜生境, 结合已建自然保护区进行保护空缺分析, 并通过构建阻力面和最小成本路径分析, 开展黑熊生境廊道规划。结果表明: 人类干扰和土地利用类型是影响黑熊生境选择的主要生态因子, 居民点密度、到荒草地距离、到耕地距离3个因子对黑熊生境选择有重要影响, 其综合贡献值分别为21.4%、17.5%和15.9%, 到阔叶林距离、到水体距离等因子次之。黑熊的适宜生境主要集中分布在秦岭山系主脊的中西部地区, 占整个秦岭山系面积的19.23%。空缺分析表明: 已建自然保护区群覆盖了23.49%的适宜生境, 但尚有8,480 km²处于保护区之外。为更有效保护秦岭黑熊及其生境, 建议建设12条生境廊道, 同时结合其他物种进行系统保护规划。

关键词: 黑熊, GAP分析, 生境评价, 最小成本路径分析, 生境廊道

Abstract

Understanding the distribution of suitable habitat of target species and their relationship with environment are critical to formulating effective protective measures. The Qinling Mountains contain important habitat for Ursus thibetanus. A predictive habitat distribution map of this species was estimated using the Maximum Entropy (MAXENT) model with a total of 68 recorded points of known bear occurrence and 34 environmental factors. The distribution of potential habitat and its relationship with major environmental factors were analyzed and a gap analysis was carried out in light of existing nature reserves. Habitat corridor networks were also planned using resistance surface and least-cost analysis. Results showed that human interference and landuse type were the main factors influencing habitat choice of U. thibetanus. Three variables including residential density, distance to grassland and distance to cultivated land had the greatest effect on habitat selection, with a contribution of 21.4%, 17.5% and 15.9% respectively, followed by the distance to broad-leaf forest and distance to water. Estimated suitable habitat for U. thibetanus was distributed mainly in the middle and western portions of the Qinling Mountains and occupied 19.23% of the Mountains’ total area. Gap analysis showed that approximately 23.49% of the bear’s predicted suitable habitat was protected within the nature reserves, but that 8,480 km² of suitable habitat was outside these reserves. In order to protect U. thibetanus and its habitat more effectively, suggestions for the construction of 12 habitat corridors and a systematic conservation planning process integrating other species’ needs were proposed.

Key words: Ursus thibetanus, GAP analysis, habitat evaluation, least cost path analysis, habitat corridor

齐增湘, 徐卫华, 熊兴耀, 欧阳志云, 郑华, 甘德欣 (2011) 基于MAXENT模型的秦岭山系黑熊潜在生境评价. 生物多样性, 19, 343-352. DOI: 10.3724/SP.J.1003.2011.10288.

Zengxiang Qi, Weihua Xu, Xingyao Xiong, Zhiyun Ouyang, Hua Zheng, Dexin Gan (2011) Assessment of potential habitat for Ursus thibetanus in the Qinling Moun- tains. Biodiversity Science, 19, 343-352. DOI: 10.3724/SP.J.1003.2011.10288.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.biodiversity-science.net/CN/10.3724/SP.J.1003.2011.10288

https://www.biodiversity-science.net/CN/Y2011/V19/I3/343

图/表 8

参考文献 38

[1]	Araújo MB, Pearson RG, Thuiller W, Erhard M (2005) Validation of species-climate impact models under climate change. Global Change Biology, 11, 1504-1513.
[2]	Boubli JP, Lima MG (2009) Modeling the geographical distribution and fundamental niches of Cacajao spp. and Chiropotes israelita in northwestern Amazonia via a Maximum Entropy Algorithm. International Journal of Primatology, 30, 217-228.
[3]	Brotons L, Thuiller W, Araújo MB, Hirzel AH (2004) Presence-absence versus presence-only modelling methods for predicting bird habitat suitability. Ecography, 27, 437-448.
[4]	Cao MC (曹铭昌), Liu GH (刘高焕), Shan K (单凯), Hou YX (侯银蓄), Wang MC (王明春), Li DL (李东来), Shen WM (申文明) (2010) A multi-scale assessment of habitat suitability of red-crowned crane at the Yellow River Delta Nature Reserve, Shandong, China. Biodiversity Science (生物多样性), 18, 283-291. (in Chinese with English abstract)
[5]	Carr M, Yoshizaki J, Van Manen FT, Pelton MR, Huygens OC, Hayashi H, Maekawa M (2002) A multi-scale assessment of habitat used by Asiatic black bears in central Japan. Ursus, 13, 1-9.
[6]	Chen Y (陈洋), Xia Q (夏茜), Wang W (王文), Shen GS (沈广爽) (2010) Habitat selection of black bear in spring in Longkou Nature Reserve. Chinese Journal of Wildlife (野生动物), 31(2), 63-68. (in Chinese with English abstract)
[7]	Fahrig L (2003) Effects of habitat fragmentation on biodiversity. Annual Review of Ecology, Evolution, and Systematics, 34, 487-515.
[8]	Garneau DE, Boudreau T, Keech M, Post E (2008) Habitat use by black bears in relation to conspecifics and competitors. Mammalian Biology, 73, 48-57.
[9]	Hernandez PA, Graham CH, Master LL, Albert DL (2006) The effect of sample size and species characteristics on performance of different species distribution modeling methods. Ecography, 29, 773-785.
[10]	Heywood VH (1995) Global Biodiversity Assessment. Cambridge University Press, Cambridge.
[11]	Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A (2005) Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25, 1965-1978.
[12]	Hirzel AH, Le Lay G, Helfer V, Randin C, Guisan A (2006) Evaluating the ability of habitat suitability models to predict species presences. Ecological Modelling, 199, 142-152.
[13]	Hostetler JA, McCown JW, Garrison EP, Neils AM, Barrett MA, Sunquist ME, Simek SL, Oli MK (2009) Demographic consequences of anthropogenic influences: Florida black bears in north-central Florida. Biological Conservation, 142, 2456-2463.
[14]	Hou WR (侯万儒), Hu JC (胡锦矗) (1997) The present situations of China’s bear resources and protection. Journal of Sichuan Normal University (Natural Science)(四川师范学院学报(自然科学版)), 18, 287-292. (in Chinese with English abstract)
[15]	Hou WR (侯万儒), Zhang ZJ (张泽钧), Hu JC (胡锦矗) (2001) A preliminary analysis on population viability for black bear in Wolong. Zoological Research (动物学研究), 22, 357-361. (in Chinese with English abstract)
[16]	Li HL, Li DH, Li T, Qiao Q, Yang J, Zhang HM (2010) Application of least-cost path model to identify a giant panda dispersal corridor network after the Wenchuan earthquake —Case study of Wolong Nature Reserve in China. Ecological Modelling, 221, 944-952.
[17]	Lu QB (鲁庆彬), Hu JC (胡锦矗) (2002) Population analysis for Selenarctos thibelanus in the Minshan Mountains. Chinese Journal of Ecology (生态学杂志), 21(4), 12-14. (in Chinese with English abstract)
[18]	Lu QB (鲁庆彬), Hu JC (胡锦矗) (2003) Preliminary analysis on the habitat selection of black bears in the Minshan Mountains. Acta Theriologica Sinica (兽类学报), 23, 98-103. (in Chinese with English abstract)
[19]	Lyons AL, Gaines WL, Servheen C (2003) Black bear resource selection in the northeast Cascades, Washington. Biological Conservation, 113, 55-62.
[20]	Ma YQ (马逸清), Hu JC (胡锦矗), Zhai QL (翟庆龙) (1994) Chinese Bears (中国黑熊), pp. 54-68. Sichuan Science & Technology Press, Chengdu. (in Chinese)
[21]	Morrison ML, Marcot BG, Mannan RW (1998) Wildlife-Habitat Relationships: Concepts and Applications, 2nd edn., pp. 3-15. The University of Wisconsin Press, Wisconsin.
[22]	Oli MK, Jacobson HA, Leopold BD (2002) Pattern of space use by female black bears in the White River National Wildlife Refuge, Arkansas, USA. Journal for Nature Conservation, 10, 87-93.
[23]	Ouyang ZY (欧阳志云), Liu JG (刘建国), Xiao H (肖寒), Tan YC (谭迎春), Zhang HM (张和民) (2001) An assessment of giant panda habitat in Wolong Nature Reserve. Acta Ecologica Sinica (生态学报), 21, 1869-1874. (in Chinese with English abstract)
[24]	Pearson RG, Raxworthy CJ, Nakamura M, Peterson AT (2007) Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar. Journal of Biogeography, 34, 102-117.
[25]	Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modelling of species geographic distributions. Ecological Modelling, 190, 231-259.
[26]	Schadt S, Revilla E, Wiegand T, Knauer F, Kaczensky P, Breitenmoser U, Bufka L, Červený J, Koubek P, Huber T, Staniša C, Trepl L (2002) Assessing the suitability of central European landscapes for the reintroduction of Eurasian lynx. Journal of Applied Ecology, 39, 189-203.
[27]	Servheen C (1990) The status and conservation of the bears of the world. International Conference Bear Research and Management Monograph, 2, 1-32
[28]	Stachura-Skierczynska K, Tumiel T, Skierczyński M (2009) Habitat prediction model for three-toed woodpecker and its implication for the conservation of biologically valuable forests. Forest Ecology and Management, 258, 697-703.
[29]	Swets JA (1988) Measuring the accuracy of diagnostic systems. Science, 240, 1285-1293.
[30]	Viña A, Tuanmu MN, Xu WH, Li Y, Ouyang ZY, DeFries R, Liu JG (2010) Range-wide analysis of wildlife habitat: implications for conservation. Biological Conservation, 143, 1960-1969.
[31]	Wang S (汪松) (1998) China Red Data Book of Endangered Animals: Mammalia (中国濒危动物红皮书) , pp. 177-179. Science Press, Beijing, Hong Kong, New York. (in Chinese)
[32]	Wang XZ (王学志), Xu WH (徐卫华), Ouyang ZY (欧阳志云), Liu JG (刘建国), Xiao Y (肖燚), Chen YP (陈佑平), Zhao LJ (赵联军), Huang JZ (黄俊忠) (2008) The application of ecological-niche factor analysis in giant pandas (Ailuropoda melanoleuca) habitat assessment. Acta Ecologica Sinica (生态学报), 28, 821-828. (in Chinese with English abstract)
[33]	White TH, Bowman JL, Leopold BD, Jacobson HA, Smith WP, Vilella FJ (2000) Influence of Mississippi alluvial valley rivers on black bear movements and dispersal: implications for Louisiana black bear recovery. Biological Conservation, 95, 323-331.
[34]	Xu WH (徐卫华), Luo C (罗翀) (2010) Application of MAXENT Model in Rhinopithecus roxllanae habitat assessment in Qinling Mountain. Forest Engineering (森林工程), 26(2), 1-4. (in Chinese with English abstract)
[35]	Xu WH (徐卫华), Ouyang ZY (欧阳志云), Jiang ZY (蒋泽银), Zheng H (郑华), Liu JG (刘建国) (2006) Assessment of giant panda habitat in the Daxiangling Mountain Range, Sichuan, China. Biodiversity Science (生物多样性), 14, 223-231. (in Chinese with English abstract)
[36]	Yu KJ (俞孔坚), Qiao Q (乔青), Li DH (李迪华), Yuan H (袁弘), Wang SS (王思思) (2009) Ecological land use in three towns of eastern Beijing: a case study based on landscape security pattern analysis. Chinese Journal of Applied Ecology (应用生态学报), 20, 1932-1939. (in Chinese with English abstract) URL PMID
[37]	Zhan RL (战如亮), Wang W (王文), Chen Y (陈洋), Feng Y (冯妍) (2010) Habitat selection of black bears in Ulahun forest farm, Heilongjiang. Chinese Journal of Wildlife (野生动物), 31(2), 69-73. (in Chinese with English abstract)
[38]	Zheng SW (郑生武), Yu YQ (余玉群), Zuo H (左华), Cao YH (曹永汉), Yuan W (袁伟), Fu WK (傅文凯) (1995) The present status, distribution and conservation measures of the black bear in Hanzhong prefecture, Shaanxi Province. Acta Theriologica Sinica (兽类学报), 15, 93-97. (in Chinese with English abstract)

准则层1 Rule layer 1	权重 Weight	准则层2 Rule layer 2	权重 Weight	准则层3 Rule layer 3	对总目标的权重 Weights for the target	相对阻力 Relative resistance
物理环境因子 Physical environment factors	0.2120	坡度阻力因子 Resistance factor of slope (R_s) (°)	0.4241	>50	0.0899	400
				40-50		300
				30-40		200
				21-30		100
				<21		50
		坡向阻力因子 Resistance factor of aspect (R_a)	0.2214	阳坡 Sunny slope	0.0469	50
				半阳半阴坡 Semi-sunny slope		100
				阴坡 Cloudy slope		200
		海拔阻力因子 Resistance factor of elevation (R_e) (m)	0.1640	>2,200	0.0348	400
				1,600-2,200		300
				1,150-1,600		200
				600-1,150		100
				<600		50
		到水体距离阻力因子 Resistance factor of distance to water (R_w) (m)	0.1905	>800	0.0404	400
				600-800		300
				400-600		200
				200-400		100
				<200		50
生物环境因子 Biological environment factors	0.3162	土地利用类型阻力因子 Resistance factor of land use (R_l)	0.3162	阔叶林 Broad-leaf forest	0.3162	0
				混交林 Mixed forest		20
				针叶林 Coniferous forest		50
				灌丛 Brushwood		100
				草甸 Meadow		150
				荒草地 Grassland		200
				耕地 Cultivated land		300
				水体 Water		400
				居民地 Residential areas		500
人为干扰因子 Human disturbance factors	0.4718	到主要公路距离阻力因子 Resistance factor of distance to main roads (R_r) (m)	0.1483	>1,000	0.0700	50
				1,000-600		100
				600-300		200
				100-300		300
				<100		400
		居民点密度阻力因子 Resistance factor of residential density (R_j)	0.5627	>2.5	0.2655	500
				1.0-2.5		400
				0.4-1.0		200
				0.08-0.4		100
				<0.08		50
		到耕地距离阻力因子 Resistance factor of distance to cultivated land (R_c) (m)	0.2889	>1,200	0.1363	50
				1,200-800		100
				800-500		200
				500-100		300
				<100		400

准则层1 Rule layer 1	权重 Weight	准则层2 Rule layer 2	权重 Weight	准则层3 Rule layer 3	对总目标的权重 Weights for the target	相对阻力 Relative resistance
物理环境因子 Physical environment factors	0.2120	坡度阻力因子 Resistance factor of slope (R_s) (°)	0.4241	>50	0.0899	400
				40-50		300
				30-40		200
				21-30		100
				<21		50
		坡向阻力因子 Resistance factor of aspect (R_a)	0.2214	阳坡 Sunny slope	0.0469	50
				半阳半阴坡 Semi-sunny slope		100
				阴坡 Cloudy slope		200
		海拔阻力因子 Resistance factor of elevation (R_e) (m)	0.1640	>2,200	0.0348	400
				1,600-2,200		300
				1,150-1,600		200
				600-1,150		100
				<600		50
		到水体距离阻力因子 Resistance factor of distance to water (R_w) (m)	0.1905	>800	0.0404	400
				600-800		300
				400-600		200
				200-400		100
				<200		50
生物环境因子 Biological environment factors	0.3162	土地利用类型阻力因子 Resistance factor of land use (R_l)	0.3162	阔叶林 Broad-leaf forest	0.3162	0
				混交林 Mixed forest		20
				针叶林 Coniferous forest		50
				灌丛 Brushwood		100
				草甸 Meadow		150
				荒草地 Grassland		200
				耕地 Cultivated land		300
				水体 Water		400
				居民地 Residential areas		500
人为干扰因子 Human disturbance factors	0.4718	到主要公路距离阻力因子 Resistance factor of distance to main roads (R_r) (m)	0.1483	>1,000	0.0700	50
				1,000-600		100
				600-300		200
				100-300		300
				<100		400
		居民点密度阻力因子 Resistance factor of residential density (R_j)	0.5627	>2.5	0.2655	500
				1.0-2.5		400
				0.4-1.0		200
				0.08-0.4		100
				<0.08		50
		到耕地距离阻力因子 Resistance factor of distance to cultivated land (R_c) (m)	0.2889	>1,200	0.1363	50
				1,200-800		100
				800-500		200
				500-100		300
				<100		400

生境类型 Habitat type	斑块面积 Patch area (ha)	斑块数目 Number of patches	斑块密度 Patch density (个/100 ha)	最大斑块指数Largest patch index	平均斑块面积 Mean patch area (ha)
适宜生境 Suitable	1,108,441	9,481	0.857	40.355	116.637
不适宜生境 Unsuitable	4,653,365	8,751	0.188	97.201	531.433

生境类型 Habitat type	斑块面积 Patch area (ha)	斑块数目 Number of patches	斑块密度 Patch density (个/100 ha)	最大斑块指数Largest patch index	平均斑块面积 Mean patch area (ha)
适宜生境 Suitable	1,108,441	9,481	0.857	40.355	116.637
不适宜生境 Unsuitable	4,653,365	8,751	0.188	97.201	531.433

基于MAXENT模型的秦岭山系黑熊潜在生境评价

Assessment of potential habitat for Ursus thibetanus in the Qinling Moun- tains

RichHTML

PDF (PC)

可视化

被引次数

摘要/Abstract

引用本文

使用本文

图/表 8

参考文献 38

相关文章 7

编辑推荐

Metrics

本文评价

[1]	和梅香, 陈俪心, 罗概, 古晓东, 王戈, 冉江洪. 凉山山系大熊猫和黑熊适宜生境预测及重叠分析[J]. 生物多样性, 2018, 26(11): 1180-1189.
[2]	梁健超, 丁志锋, 张春兰, 胡慧建, 朵海瑞, 唐虹. 青海三江源国家级自然保护区麦秀分区鸟类多样性空间格局及热点区域研究[J]. 生物多样性, 2017, 25(3): 294-303.
[3]	张殷波, 傅靖轩, 刘莹立, 白帆, 桑卫国. 我国珍稀濒危植物保护红线的划定[J]. 生物多样性, 2015, 23(6): 733-739.
[4]	闻丞, 顾垒, 王昊, 吕植, 胡若成, 钟嘉. 基于最受关注濒危物种分布的国家级自然保护区空缺分析[J]. 生物多样性, 2015, 23(5): 591-600.
[5]	林杰, 徐文轩, 杨维康, 夏参军, 刘伟. 卡拉麦里山有蹄类自然保护区蒙古野驴生境适宜性评价[J]. 生物多样性, 2012, 20(4): 411-419.
[6]	唐小平. 中国自然保护区网络现状分析与优化设想[J]. 生物多样性, 2005, 13(1): 81-88.
[7]	李迪强, 宋延龄. 热点地区与GAP分析研究进展[J]. 生物多样性, 2000, 08(2): 208-214.