西南喀斯特地貌区两栖动物丰富度分布格局与环境因子的关系

doi:10.17520/biods.2018125

生物多样性 ›› 2018, Vol. 26 ›› Issue (9): 941-950. DOI: 10.17520/biods.2018125 cstr: 32101.14.biods.2018125

• 研究报告: 动物多样性 • 上一篇下一篇

西南喀斯特地貌区两栖动物丰富度分布格局与环境因子的关系

王波^1,⁴, 黄勇², 李家堂³, 戴强³, 王跃招³, 杨道德^1,^*()

1 (中南林业科技大学野生动植物保护研究所, 长沙 410004)
2 (广西中医药大学, 南宁 530200)
3 (中国科学院成都生物研究所, 成都 610041)
4 (广西渌金生态科技有限公司, 南宁 530028);

收稿日期:2018-04-22 接受日期:2018-07-05 出版日期:2018-09-20 发布日期:2019-01-05
通讯作者: 杨道德
作者简介:# 共同第一作者
基金资助:
国家自然科学基金(31472021, 31460559)

Amphibian species richness patterns in karst regions in Southwest China and its environmental associations

Bo Wang^1,⁴, Yong Huang², Jiatang Li³, Qiang Dai³, Yuezhao Wang³, Daode Yang^1,^*()

1 Institute of Wildlife Conservation, Central South University of Forestry and Technology, Changsha 410004
2 Guangxi University of Chinese Medicine, Nanning 530200
3 Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu 610041
4 Guangxi Lujin Ecological Technology Company, Nanning 530028

Received:2018-04-22 Accepted:2018-07-05 Online:2018-09-20 Published:2019-01-05
Contact: Yang Daode
About author:# Co-first authors

摘要/Abstract

摘要：

物种丰富度分布格局的成因机制一直是宏观生态学研究的热点问题之一。中国西南地区喀斯特地貌区(以广西、云南和贵州为主)是世界上面积最大的喀斯特地貌区, 也是全球范围内34个生物多样性热点地区之一。为了解该区域两栖动物物种丰富度分布格局及其与环境因子之间的关系, 本研究根据中国科学院成都生物研究所标本馆、中国科学院昆明动物研究所标本馆、广西壮族自治区自然博物馆和中南林业科技大学动物标本室收藏的标本数据, 以及公开发表的文献数据, 共获得18,246条两栖动物记录(219个物种), 然后运用生态位模型估测每个物种的潜在分布区, 并把每个物种的潜在分布区叠加起来, 最终得到该区域在10 km ´10 km生态位模型空间尺度上的两栖物种丰富度地理分布格局图, 最后进行多元回归和模型选择分析。结果表明: 有12种两栖动物仅在喀斯特地貌区分布, 占物种总数的5.48%; 有104种两栖动物仅在非喀斯特地貌区分布, 占物种总数的47.49%; 有103种两栖动物在喀斯特地貌区和非喀斯特地貌区均有分布, 占物种总数的47.03%; 两栖动物物种丰富度随纬度的增高而降低; 地貌类型(喀斯特地貌和非喀斯特地貌)对两栖动物物种丰富度的分布格局有显著影响(χ² = 36.47, P < 0.0001), 但模型拟合效果差(McFadden’s Rho square = 0.0037)。影响该区域两栖动物物种丰富度分布格局最大的环境因子是年均降雨量(R²= 0.232, P < 0.001), 其次是最干月平均降雨量(R²= 0.221, P < 0.001)。该区域两栖动物物种丰富度的格局主要是由地貌和不同的环境因子共同相互作用的结果, 不过仍有相当一部分物种丰富度的分布格局未被解释。因此, 要更全面地认识该区域两栖动物物种丰富度格局的形成机制, 有必要加强干扰、捕食、竞争等其他生物因子的影响研究。

关键词: 生物地理学, 两栖动物, 物种多样性, 喀斯特地貌, 生态位模型

Abstract

Patterns in the distribution of species richness have always been a central theme in macroecology. The karst landforms in Southwest China (mainly Guangxi, Yunnan and Guizhou provinces) are among the largest of the global biodiversity hotspots. In this study, we sought to understand spatial patterns of amphibian species richness and its relationship with environmental factors. We compiled a large dataset of 18,246 records of point location data for 219 amphibian species occurring in China. We retrieved this data from published literature, Herpetology museums of Chengdu Institute of Biology and Kunming Institute of Zoology, Chinese Academy of Sciences, Guangxi Zhuang Autonomous Region Museum of Nature and the Central South University of Forestry and Technology, and published sources. We used this data to generate the potential distributions of each species using ecological niche modeling. We combined the potential distributions maps of all species into a composite map to describe species richness patterns on the grid cell of 10 km × 10 km, and then conducted multivariate regression and model selection. Our results showed that 12 species were distributed only in karst area, accounting for 5.48% of the total species pool, 104 species were found in non-karst area (47.49% of total species), and 103 species were found in both karst area and non-karst area (47.03% of total species). Based on the raw data of museum collections data and MaxEnt species distribution modeling, we found that amphibian species richness in the study area decreased at higher latitudes. Karst landforms and non-karst landforms differed in their distribution patterns of amphibian species richness (χ² = 36.47, P < 0.0001), but the model was a poor fit to the data (McFadden’s Rho square = 0.0037). The most significant environmental predictors of species richness were mean annual rainfall (R² = 0.232, P < 0.001) and precipitation of driest Month (R² = 0.221, P < 0.001). The results based on model selection showed that underlying mechanisms related to landforms and different ecological hypotheses might simultaneously explain patterns of amphibian species richness in the study area. Future research should examine other biological factors such as interference, predation, and competition to understand the mechanisms controlling patterns of amphibian species richness.

Key words: biogeography, amphibia, species diversity, karst landforms, MaxEnt model

王波, 黄勇, 李家堂, 戴强, 王跃招, 杨道德 (2018) 西南喀斯特地貌区两栖动物丰富度分布格局与环境因子的关系. 生物多样性, 26, 941-950. DOI: 10.17520/biods.2018125.

Bo Wang, Yong Huang, Jiatang Li, Qiang Dai, Yuezhao Wang, Daode Yang (2018) Amphibian species richness patterns in karst regions in Southwest China and its environmental associations. Biodiversity Science, 26, 941-950. DOI: 10.17520/biods.2018125.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.biodiversity-science.net/CN/10.17520/biods.2018125

https://www.biodiversity-science.net/CN/Y2018/V26/I9/941

图/表 7

参考文献 50

[1]	Ahmed SE, McInerny G, O’Hara K, Harper R, Salido L, Emmott S, Joppa LN (2015) Scientists and software—surveying the species distribution modelling community. Diversity and Distributions, 21, 258-267.
[2]	Ahn CH, Tateishi R (1994) Development of a global 30-minute grid potential evapotranspiration data set. Journal of the Japan Society of Photogrammetry, 33, 12-21.
[3]	Anderson DR, Burnham KP, Thompson WL (2000) Null hypothesis testing: Problems, prevalence, and an alternative. Journal of Wildlife Management, 64, 912-923.
[4]	Andrews P, O’Brien EM (2000) Climate, vegetation, and predictable gradients in mammal species richness in southern Africa. Journal of Zoology, 251, 205-231.
[5]	Badgley C, Fox DL (2000) Ecological biogeography of North American mammals: Species density and ecological structure in relation to environmental gradients. Journal of Biogeography, 27, 1437-1467.
[6]	Bohning-Gaese K (1997) Determinants of avian species richness at different spatial scales. Journal of Biogeography, 24, 49-60.
[7]	Buckley LB, Jetz W (2007) Environmental and historical constraints on global patterns of amphibian richness. Proceedings of the Royal Society B: Biological Sciences, 274, 1167-1173.
[8]	Burnham KP, Anderson DR (1998) Model Selection and Inference: A Practical in Formation Theoretic Approach. Springer-Verlag, New York.
[9]	Costa GC, Nogueira C, Machado RB, Colli GR (2007) Squamate richness in the Brazilian Cerrado and its environmental-climatic associations. Diversity and Distributions, 6, 714-724.
[10]	Currie DJ (1991) Energy and large-scale patterns of animal- and plant-species richness. The American Naturalist, 137, 27-49.
[11]	Diniz-Filho JAF, Bini LM, Hawkins BA (2003) Spatial autocorrelation and red herrings in geographical ecology. Global Ecology & Biogeography, 12, 53-64.
[12]	Fei L, Ye CY, Jiang JP (2012) Colored Atlas of Chinese Amphibians and Their Distributions. Sichuan Science and Technology Press, Chengdu. (in Chinese)
	[费梁, 叶昌媛, 江建平 (2012) 中国两栖动物及其分布彩色图鉴. 四川科学技术出版社, 成都.]
[13]	Ford DC, Williams PW (1989) Karst Geomorphology and Hydrology. Unwin Hyman, London.
[14]	Gaston KJ (2000) Global patterns in biodiversity. Nature, 405, 220-227.
[15]	Guo Q, Kelt DA, Sun Z, Liu H, Hu L, Ren H, Wen J (2013) Global variation in elevational diversity patterns. Scientific Reports, 3, 3007.
[16]	Hanley JA, Mcneil BJ (1982) The meaning and use of the area under a Receiver Operating Characteristic (ROC) curve. Radiology, 143, 29-36.
[17]	Hawkins BA, Diniz-Filho JA, Jaramillo CA, Soeller SA (2007) Climate, niche conservatism, and the global bird diversity gradient. The American Naturalist, 170, S16-S27.
[18]	Hawkins BA, Field R, Cornell HV, Currie DJ, Guegan JF, Kaufman DM, Kerr JT, Mittelbach GG, Oberdorff T, O’Brien EM, Porter EE, Turner JRG (2003b) Energy, water, and broad-scale geographic patterns of species richness. Ecology, 84, 3105-3117.
[19]	Hawkins BA, Porter EE, Diniz JAF (2003a) Productivity and history as predictors of the latitudinal diversity gradient of terrestrial birds. Ecology, 84, 1608-1623.
[20]	Hou MF, López-pujol J, Qin HN, Wang LS, Liu Y (2010) Distribution pattern and conservation priorities for vascular plants in Southern China: Guangxi Province as a case study. Botanical Studies, 51, 377-386.
[21]	Huang Y, Dai Q, Chen Y, Wan HF, Li JT, Wang YZ (2011) Lizard species richness patterns in China and its environmental associations. Biodiversity and Conservation, 7, 1399-1414.
[22]	Jiménez-Valverde A, Peterson AT, Soberón J, Overton JM, Arago?n P, Lobo JM (2011) Use of niche models in invasive species risk assessments. Biological Invasions, 13, 2785-2797.
[23]	Kerr JT, Packer L (1997) Habitat heterogeneity as a determinant of mammal species richness in high-energy regions. Nature, 385, 252-254.
[24]	Legendre P (1993) Spatial autocorrelation: Trouble or new paradigm. Ecology, 74, 1659-1673.
[25]	Li JJ, Zhou CH, Cheng WM (2009) 1 : 1000000 Geomorphological Atlas of the People’s Republic of China. Science Press, Beijing. (in Chinese)
	[李吉均, 周成虎, 程维明 (2009) 中华人民共和国1 : 100万地貌图. 科学出版社, 北京.]
[26]	Luo ZH, Tang SH, Jiang ZG, Chen J, Fang HX, Li CW (2016) Conservation of terrestrial vertebrates in a global hotspot of karst area in Southwestern China. Scientific Reports, 6, 25717.
[27]	Mo YM, Wei ZY, Chen WC (2014) Color Atlas of Amphibians in Guangxi. Guangxi Science and Technology Press, Nanning. (in Chinese)
	[莫运明, 韦振逸, 陈伟才 (2014) 广西两栖动物彩色图鉴. 广西科学技术出版社, 南宁.]
[28]	New M, Lister D, Hulme M, Makin I (2002) A high-resolution data set of surface climate over global land areas. Climate Research, 21, 1-25.
[29]	Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190, 231-259.
[30]	Phillips SJ, Dudík MM (2008) Modeling of species distributions with Maxent: New extensions and a comprehensive evaluation. Ecography, 31, 161-175.
[31]	Powney GD, Grenyer R, Orme CDL, Owens IPF, Meiri S (2010) Hot, dry and different Australian lizard richness is unlike that of mammals, amphibians, and birds. Global Ecology & Biogeography, 19, 386-396.
[32]	Rahbek C, Graves GR (2001) Multiscale assessment of patterns of avian species richness. Proceedings of the National Academy of Sciences, USA, 98, 4534-4539.
[33]	Rangel TF, Diniz-Filho JAF, Bini LM (2010) SAM: A comprehensive application for spatial analysis in macroecology. Ecography, 33, 46-50.
[34]	Ricklefs RE (1987) Community diversity: Relative roles of local and regional processes. Science, 235, 167-171.
[35]	Ruggiero A, Kitzberger T (2004) Environmental correlates of mammal species richness in South America: Effects of spatial structure, taxonomy and geographic range. Ecography, 27, 401-417.
[36]	Schall JJ, Pianka ER (1978) Geographical trends in numbers of species. Science, 201, 679-686.
[37]	Schoener TW (1976) The species-area relationship within archipelagoes: Models and evidence from island birds. Proceedings of XVI International Ornithological Congress, Australian Academy of Science, Canberra, Australia.
[38]	Shen YH, Yang DD, Mo XY (2014) Fauna of Hunan: Amphibian. Hunan Science and Technology Press, Changsha. (in Chinese)
	[沈猷慧, 杨道德, 莫小阳 (2014) 湖南动物志: 两栖纲. 湖南科学技术出版社, 长沙.]
[39]	Shmida A, Wilson MV (1985) Biological determinants of species diversity. Journal of Biogeography, 12, 1-20.
[40]	Stuart SN, Chanson JS, Cox NA, Young BE, Rodrigues AS, Fischman DL, Waller RW (2004) Status and trends of amphibian declines and extinctions worldwide. Science, 306, 1783-1786.
[41]	Su ZM, Li XK (2003) The types of natural vegetation in karst region of Guangxi and its classified system. Guihaia, 23, 289-293. (in Chinese with English abstract)
	[苏宗明, 李先琨 (2003) 广西岩溶植被类型及其分类系统. 广西植物, 23, 289-293.]
[42]	Terribile LC, Olalla-Tárraga MA, Morales-Castilla I, Rueda M, Vidanes RM, Rodríguez MA, Diniz-Filho JA (2009) Global richness patterns of venomous snakes reveal contrasting influences of ecology and history in two different clades. Oecologia, 159, 617-626.
[43]	Tognelli MF, Kelt DA (2004) Analysis of determinants of mammalian species richness in South America using spatial autoregressive models. Ecography, 27, 427-436
[44]	Wang SJ, Lu HM, Zhou YC, Xie LP, Xiao DA (2007) Spatial variability of soil organic carbon and representative soil sampling method in Maolan karst virgin forest. Acta Pedologica Sinica, 44, 475-483. (in Chinese with English abstract)
	[王世杰, 卢红梅, 周运超, 谢丽萍, 肖德安 (2007) 茂兰喀斯特原始森林土壤有机碳的空间变异性与代表性土样采集方法. 土壤学报, 44, 475-483.]
[45]	Wright DH (1983) Species-energy theory: An extension of species-area theory. Oikos, 41, 496-506.
[46]	Wu L, Dong Q, Xu RH (1987) Amphibians in Guizhou. Guizhou People’s Press, Guiyang. (in Chinese)
	[伍律, 董谦, 须润华 (1987) 贵州两栖类志. 贵州人民出版社, 贵阳.]
[47]	Xiong KN, Xiao SZ, Liu ZQ, Chen PD (2008) Comparative analysis on world natural heritage value of South China Karst. Engineering Science, 10, 17-28. (in Chinese with English abstract)
	[熊康宁, 肖时珍, 刘子琦, 陈品冬 (2008) “中国南方喀斯特”的世界自然遗产价值对比分析. 中国工程科学, 10, 17-28.]
[48]	Yang DT, Rao DQ (2008) Amphibians and Reptiles in Yunnan. Yunnan Science and Technology Press, Kunming. (in Chinese)
	[杨大同, 饶定齐 (2008) 云南两栖爬行动物. 云南科技出版社, 昆明.]
[49]	Yuan TX, Zhang HP, Ou ZY, Tan YB (2014) Effects of topography on the diversity and distribution pattern of ground plants in karst montane forests in Southwest Guangxi, China. Chinese Journal of Applied Ecology, 25, 2803-2810. (in Chinese with English abstract)
	[袁铁象, 张合平, 欧芷阳, 谭一波 (2014) 地形对桂西南喀斯特山地森林地表植物多样性及分布格局的影响. 应用生态学报, 25, 2803-2810.]
[50]	Zheng Z, Gong DJ, Sun CX, Li XJ, Li WJ (2014) Elevational pattern of amphibian and reptile diversity in Qinling Range and explanation. Biodiversity Science, 22, 596-607. (in Chinese with English abstract)
	[郑智, 龚大洁, 孙呈祥, 李晓军, 李万江 (2014) 秦岭两栖、爬行动物物种多样性海拔分布格局及其解释. 生物多样性, 22, 596-607.]

相关假说 Hypothesis	环境变量 Environmental variable	变量缩写 Abbreviation
能量假说 Energy availability	年均温度 Annual mean temperature (℃)	BIO1
	平均日温差 Mean diurnal range (℃)	BIO2
	等温性 Isothermality (℃)	BIO3
	季节性温度变化 Temperature seasonality	BIO4
	最高气温 Max temperature of warmest month (℃)	BIO5
	最低气温 Min temperature of coldest month (℃)	BIO6
	年均温差 Temperature annual range (℃)	BIO7
	最湿季平均温度 Mean temperature of wettest quarter (℃)	BIO8
	最干季平均温度 Mean temperature of driest quarter (℃)	BIO9
	最暖季平均温度 Mean temperature of warmest quarter (℃)	BIO10
	最冷季平均温度 Mean temperature of coldest quarter (℃)	BIO11
	年均日照时数(白昼长的百分比) Mean annual sunshine (percent of daylength)	SUNP
	年均霜日频率 Mean annual frost-day frequency (days)	FF
	年均潜在蒸散量 Mean annual potential evapotranspiration (mm/yr)	PET
	年均风速 Mean annual wind speed (m/s)	WIND
水分假说 Water availability	年均降雨量 Annual precipitation (mm/yr)	BIO12
	最湿月平均降雨量 Precipitation of wettest month (mm/yr)	BIO13
	最干月平均降雨量 Precipitation of driest month (mm/yr)	BIO14
	季节性降雨量 Precipitation seasonality	BIO15
	最湿季平均降雨量 Precipitation of wettest quarter (mm/yr)	BIO16
	最干季平均降雨量 Precipitation of driest quarter (mm/yr)	BIO17
	最暖季平均降雨量 Precipitation of warmest quarter (mm/yr)	BIO18
	最冷季平均降雨量 Precipitation of coldest quarter (mm/yr)	BIO19
	年均相对湿度 Mean annual relative humidity (%)	REH
生产力假说 Productive energy	归一化植被指数 Normalized difference vegetation index	NDVI
	年均实际蒸散量 Mean annual actual evapotranspiration (mm/yr)	AET
	年均太阳辐射量 Mean annual solar radiation (W/m²)	RAD
生境异质性假说 Habitat heterogeneity	海拔 Elevation	ELE
	植被类型数 Vegetation (number of vegetation classes/quadrat)	VEG
	地貌类型 Landform	LANDF

相关假说 Hypothesis	环境变量 Environmental variable	变量缩写 Abbreviation
能量假说 Energy availability	年均温度 Annual mean temperature (℃)	BIO1
	平均日温差 Mean diurnal range (℃)	BIO2
	等温性 Isothermality (℃)	BIO3
	季节性温度变化 Temperature seasonality	BIO4
	最高气温 Max temperature of warmest month (℃)	BIO5
	最低气温 Min temperature of coldest month (℃)	BIO6
	年均温差 Temperature annual range (℃)	BIO7
	最湿季平均温度 Mean temperature of wettest quarter (℃)	BIO8
	最干季平均温度 Mean temperature of driest quarter (℃)	BIO9
	最暖季平均温度 Mean temperature of warmest quarter (℃)	BIO10
	最冷季平均温度 Mean temperature of coldest quarter (℃)	BIO11
	年均日照时数(白昼长的百分比) Mean annual sunshine (percent of daylength)	SUNP
	年均霜日频率 Mean annual frost-day frequency (days)	FF
	年均潜在蒸散量 Mean annual potential evapotranspiration (mm/yr)	PET
	年均风速 Mean annual wind speed (m/s)	WIND
水分假说 Water availability	年均降雨量 Annual precipitation (mm/yr)	BIO12
	最湿月平均降雨量 Precipitation of wettest month (mm/yr)	BIO13
	最干月平均降雨量 Precipitation of driest month (mm/yr)	BIO14
	季节性降雨量 Precipitation seasonality	BIO15
	最湿季平均降雨量 Precipitation of wettest quarter (mm/yr)	BIO16
	最干季平均降雨量 Precipitation of driest quarter (mm/yr)	BIO17
	最暖季平均降雨量 Precipitation of warmest quarter (mm/yr)	BIO18
	最冷季平均降雨量 Precipitation of coldest quarter (mm/yr)	BIO19
	年均相对湿度 Mean annual relative humidity (%)	REH
生产力假说 Productive energy	归一化植被指数 Normalized difference vegetation index	NDVI
	年均实际蒸散量 Mean annual actual evapotranspiration (mm/yr)	AET
	年均太阳辐射量 Mean annual solar radiation (W/m²)	RAD
生境异质性假说 Habitat heterogeneity	海拔 Elevation	ELE
	植被类型数 Vegetation (number of vegetation classes/quadrat)	VEG
	地貌类型 Landform	LANDF

环境变量 Enviromental predictor	AICc	ΔAICc	Wi	t	R²	P
年均降雨量 Annual precipitation (mm/yr)	41,710	0	1	48.465	0.232	< 0.001
最干月平均降雨量 Precipitation of driest month (mm/yr)	41,820	110	0	46.963	0.221	< 0.001
日照时数(白昼长的百分比) Mean annual sunshine (percent of daylength)	43,021	1,311	0	-27.903	0.091	0
年均实际蒸散量 Mean annual actual evapotranspiration (mm/yr)	43,071	1,361	0	26.895	0.085	< 0.001
年均相对湿度 Mean annual relative humidity (%)	43,479	1,769	0	17.021	0.036	0
年均风速 Mean annual wind speed	43,666	1,956	0	-9.861	0.012	< 0.001
年均潜在蒸散量 Mean annual potential evapotranspiration (mm/yr)	43,753	2,043	0	3.129	0.001	0.002
年均温度 Annual mean temperature (℃)	43,568	1,858	0	14.043	0.025	< 0.001
植被类型数 Vegetation (number of vegetation classes/quadrat)	43,758	2,048	0	-2.251	< 0.001	0.024
归一化植被指数 Normalized difference vegetation index	43,761	2,051	0	1.38	< 0.001	0.168
年均太阳辐射量 Mean annual solar radiation (W/m²)	43,761	2,051	0	-1.453	< 0.001	0.146

环境变量 Enviromental predictor	AICc	ΔAICc	Wi	t	R²	P
年均降雨量 Annual precipitation (mm/yr)	41,710	0	1	48.465	0.232	< 0.001
最干月平均降雨量 Precipitation of driest month (mm/yr)	41,820	110	0	46.963	0.221	< 0.001
日照时数(白昼长的百分比) Mean annual sunshine (percent of daylength)	43,021	1,311	0	-27.903	0.091	0
年均实际蒸散量 Mean annual actual evapotranspiration (mm/yr)	43,071	1,361	0	26.895	0.085	< 0.001
年均相对湿度 Mean annual relative humidity (%)	43,479	1,769	0	17.021	0.036	0
年均风速 Mean annual wind speed	43,666	1,956	0	-9.861	0.012	< 0.001
年均潜在蒸散量 Mean annual potential evapotranspiration (mm/yr)	43,753	2,043	0	3.129	0.001	0.002
年均温度 Annual mean temperature (℃)	43,568	1,858	0	14.043	0.025	< 0.001
植被类型数 Vegetation (number of vegetation classes/quadrat)	43,758	2,048	0	-2.251	< 0.001	0.024
归一化植被指数 Normalized difference vegetation index	43,761	2,051	0	1.38	< 0.001	0.168
年均太阳辐射量 Mean annual solar radiation (W/m²)	43,761	2,051	0	-1.453	< 0.001	0.146

假说 Hypothesis	R²	AICc	ΔAICc	K	Wi
生产力假说 Productivity energy	0.004	6,908	4,268	4	0
生境异质性假说 Habitat heterogeneity	0.005	6,898	4,258	3	0
能量假说 Ambient energy	0.173	5,462	2,822	5	0
水分-能量假说 Water-energy balance hypothesis	0.34	3,706	1,066	4	0
混合模型 Mixed model*	0.425	2,640	0	12	1

西南喀斯特地貌区两栖动物丰富度分布格局与环境因子的关系

Amphibian species richness patterns in karst regions in Southwest China and its environmental associations

RichHTML

PDF (PC)

可视化

被引次数

摘要/Abstract

引用本文

使用本文

图/表 7

参考文献 50

相关文章 15

编辑推荐

Metrics

本文评价

[1]	吴晓晴张美惠葛苏婷李漫淑宋坤沈国春达良俊张健. 上海近自然林重建过程中木本植物物种多样性与地上生物量的时空动态——以闵行区生态岛为例[J]. 生物多样性, 2025, 33(5): 24444-.
[2]	王太, 宋福俊, 张永胜, 娄忠玉, 张艳萍, 杜岩岩. 河西走廊内陆河水系鱼类多样性及资源现状[J]. 生物多样性, 2025, 33(4): 24387-.
[3]	张晶晶, 黄文彬, 陈奕廷, 杨泽鹏, 柯伟业, 彭昭杰, 魏世超, 张志伟, 胡怡思, 余文华, 周文良. 广东南澎列岛海洋生态国家级自然保护区造礁石珊瑚多样性及分布特征[J]. 生物多样性, 2025, 33(4): 24424-.
[4]	尚华丹, 张楚晴, 王梅, 裴文娅, 李国宏, 王鸿斌. 中国杨树害虫物种多样性及其地理分布[J]. 生物多样性, 2025, 33(2): 24370-.
[5]	吴昱萱, 王平, 胡晓生, 丁一, 彭甜恬, 植秋滢, 巴德木其其格, 李文杰, 关潇, 李俊生. 呼伦贝尔草地退化现状评估与植被特征变化[J]. 生物多样性, 2025, 33(2): 24118-.
[6]	李华亮, 张明军, 张熙斌, 谭荣, 李诗川, 冯尔辉, 林雪云, 陈珉, 颜文博, 曾治高. 海南东寨港国家级自然保护区两栖类群落组成及影响因素[J]. 生物多样性, 2025, 33(2): 24350-.
[7]	陈自宏, 张翼飞, 陈凯, 陈见影, 徐玲. 高黎贡山南段昆虫病原真菌物种多样性及影响因素[J]. 生物多样性, 2025, 33(1): 24228-.
[8]	谭珂, 宁瑶, 王仁芬, 王晴, 梁丹萍, 辛子兵, 温放. 中国苦苣苔科植物名录与地理分布数据集[J]. 生物多样性, 2025, 33(1): 23275-.
[9]	韩佳楠, 苏杨, 李霏, 刘君妍, 赵依林, 李琳, 赵建成, 梁红柱, 李敏. 河北省苔藓植物多样性[J]. 生物多样性, 2024, 32(9): 24096-.
[10]	李东红, 郝媛媛, 甘辉林, 张航, 刘耀猛, 他富源, 胡桂馨. 祁连山北麓中段不同类型草地蝗虫种类及分布[J]. 生物多样性, 2024, 32(9): 24119-.
[11]	牛红玉, 陈璐, 赵恒月, 古丽扎尔·阿不都克力木, 张洪茂. 城市化对动物的影响: 从群落到个体[J]. 生物多样性, 2024, 32(8): 23489-.
[12]	白雪, 李正飞, 刘洋, 张君倩, 张多鹏, 罗鑫, 杨佳莉, 杜丽娜, 蒋玄空, 武瑞文, 谢志才. 西江流域大型底栖无脊椎动物物种多样性及维持机制[J]. 生物多样性, 2024, 32(7): 23499-.
[13]	许佳, 崔小娟, 张翼飞, 吴昌, 孙远东. 南岭地区鱼类多样性及其地理分布[J]. 生物多样性, 2024, 32(7): 23482-.
[14]	董云伟, 鲍梦幻, 程娇, 陈义永, 杜建国, 高养春, 胡利莎, 李心诚, 刘春龙, 秦耿, 孙进, 王信, 杨光, 张崇良, 张雄, 张宇洋, 张志新, 战爱斌, 贺强, 孙军, 陈彬, 沙忠利, 林强. 中国海洋生物地理学研究进展和热点: 物种分布模型及其应用[J]. 生物多样性, 2024, 32(5): 23453-.
[15]	邝起宇, 胡亮. 广东东海岛与硇洲岛海域底栖贝类物种多样性及其地理分布[J]. 生物多样性, 2024, 32(5): 24065-.