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Received：31 December 2017，
Accepted：28 April 2018，
Published：2019-01
移动端阅览
干旱区生态系统极易受到气候及土地利用变化的影响，其生物多样性格局及其形成机制是重要的生态学问题。基于新疆地区鸟类及哺乳动物物种多样性数据，结合气候、地形和长时间序列的植被遥感参数产品FAPAR数据等，主要在不同的土地利用类型及海拔带上采用单因子相关分析方法探讨了物种丰富度格局的形成机制。总体来说，不同生境类型中，植被遥感参数因子(DHI、NDVI等)与两种类群物种丰富度分布的相关性强于与气候因子(温度、降水)的相关性。具体而言，植被遥感参数因子中，基于FAPAR的生境指数因子与丰富度的相关性大于基于植被指数的因子(DHI_cum>NDVI_cum>EVI_cum)；气候因子中，在草地生境或者较低的海拔上，年均降水因子对于丰富度分布的解释力强于年均温度因子。这表明在新疆地区，影响鸟类与哺乳类动物物种丰富度分布的主导理论是生境异质性假说与环境稳定性假说，其解释力在多种生境内均强于生产力与环境热量。
The distinction of local biodiversity in arid areas is complicated and controversial. Hence
the investigation of the spatial pattern of species richness and its causes in Xinjiang can be used as the basis for biodiversity conservation in the region
and it is also important for regional biodiversity research. On the basis of the data on the distribution of birds and mammals in Xinjiang and long-time series environmental data
such as climate
topography
and remote sensing (FAPAR)
this study investigated the species richness and environmental spatial pattern of birds and mammals. Furthermore
the forming mechanism of the disparity pattern of species richness was evaluated through a single-factor correlation analysis used in various land-use types and elevation zones. This research was based on the analysis of the richness of bird and mammal species and the temporal and spatial distribution of environmental factors in Xinjiang. A range of relevant environmental elements were utilized. Then
correlation and linear regression analyses were used to investigate the independent influence of environmental factors on the overall abundance pattern of birds and mammals in a specific living environment in Xinjiang. Finally
the main environmental factors that determine the richness pattern of birds and mammals in specific habitats were selected according to the correlation coefficient. Statistical analysis was realized via the MATLAB software. In general
among the various habitat types
the remote sensing parameter factors (e.g.
DHI
NDVI
etc.) are more closely related to the species richness distribution of the two groups than to the climatic factors (e.g.
temperature and precipitation). Specifically
among remote sensing parameter factors
the correlation between the habitat index factor based on FAPAR and richness was greater than that of the environmental factor based on vegetation index (DHI_cum>NDVI-cum>EVI-cum). Among the climatic factors
in grassland habitats or at low altitudes
the average annual precipitation factor was better than the average annual temperature factor in verifying the richness distribution. In Xinjiang
the dominant factors affecting the distribution of the richness of bird and mammal species were habitat heterogeneity and environmental stability. Their explanatory power was stronger than the productivity and the environment heat in many types of generation territories. Habitat heterogeneity was the main factor affecting the spatial distribution pattern of richness of birds and mammalian species in Xinjiang
where 70% of the arid areas are not covered by vegetation. Hence
habitat heterogeneity was the main factor affecting the spatial distribution pattern of the richness of bird and mammal species in Xinjiang. Species resources in Xinjiang were abundant
and the overall pattern was complex. The covariation trend of various species and environmental factors was not completely consistent. However
a considerable number of species.
阿布力米提·阿布都卡迪尔. 2002. 新疆哺乳类(兽纲)名录. 北京: 科学出版社
Abramite AbuQadir. 2002. A list of mammals (Oryzae) in Xinjiang. Beijing: science Press
Clarke A, Gaston KJ. 2006. Climate, energy and diversity. Proceedings of the Royal Society B: Biological Sciences, 273: 2257–2266
Coops N C, Wulder M A, Duro D C, Han T and Berry S. 2008. The development of a Canadian dynamic habitat index using multi-temporal satellite estimates of canopy light absorbance. Ecological Indicators, 8(5): 754–766
Currie DJ. 1991. Energy and large-scale patterns of animal and plant-species richness. The American Naturalist, 137: 27–49
Diniz-Filho JAF, Bini LM, Hawkins BA. 2003. Spatial autocorrelation and red herrings in geographical ecology. Global Ecology and Biogeography, 12: 53–64
Goward, S.N., Tucker, C.J., Dye, D.G 1985. North American vegetation patterns observed with the NOAA-7 advanced very high resolution radiometer. Vegetation, 64: 3–14
Hawkins B A, Field R, Cornell H V, Currie D J, Guégan J F, Kaufman D M, Kerr J T, Mittelbach G G, Oberdorff T, O’Brien E M, Porter E E and Turner J R G. 2003b. Energy, water, and broad-scale geographic patterns of species richness. Ecology, 84(12): 3105–3117
He F L and Legendre P. 1996. On species–area relations. The American Naturalist, 148(4): 719–737
Hobi M L, Dubinin M, Graham C H, Coops N C, Clayton M K, Pidgeon A M and Radeloff V C. 2017. A comparison of Dynamic Habitat Indices derived from different MODIS products as predictors of avian species richness. Remote Sensing of Environment, 195: 142–152
Kerr J T and Packer L. 1997. Habitat heterogeneity as a determinant of mammal species richness in high-energy regions. Nature, 385(6613): 252–254
Klopfer P H and MacArthur R. 1960. Niche size and faunal diversity. The American Naturalist, 94(877): 293–300
李利平, 尹林克, 唐志尧. 2011. 新疆野生动植物物种丰富度的分布格局. 干旱区研究, 28(1): 1–9
Li L P, Yin L K and Tang Z Y. 2011. Distribution patterns of the species richness of plants and animals in Xinjiang, China. Arid Zone Research, 28(1): 1–9 (
林鑫, 王志恒, 唐志尧, 赵淑清, 方精云. 2009. 中国陆栖哺乳动物物种丰富度的地理格局及其与环境因子的关系. 生物多样性, 17(6): 652–663
Lin X, Wang Z H, Tang Z Y, Zhao S Q and Fang J Y. 2009. Geographic patterns and environmental correlates of terrestrial mammal species richness in China. Biodiversity Science, 17(6): 652–663 (
Livingston M, Shaw W W and Harris L K. 2003. A model for assessing wildlife habitats in urban landscapes of eastern Pima county, Arizona (USA). Landscape and Urban Planning, 64(3): 131–144
马鸣. 2001. 新疆鸟类名录. 北京: 科学出版社
Ma Ming. 2001. List of Birds in Xinjiang. Beijing: science Press
Mackey B, Bryan J and Randall L. 2004. Australia’s dynamic habitat template 2003 // Proceedings of the MODIS Vegetation Workshop II. Missoula, MT, American: [s.l.]
Rosenzweig M L. 1995. Species Diversity in Space and Time. Cambridge: Cambridge University Press
Schwartz, C. C., Haroldson, M. A., White, G. C., Harris, R. B., Cherry, S ., Keating, K. A., Moody, D ., Servheen, C . 2006. Temporal spatial and environmental influences on the demographics of grizzly bears in the Greater Yellowstone Ecosystem. Wildlife Monogr, 161: 1–68
Shmida A and Wilson M V. 1985. Biological determinants of species diversity. Journal of Biogeography, 12(1): 1–20
Simpson G G. 1964. Species density of North American recent mammals. Systematic Zoology, 13(2): 57–73
Turner W, Spector S, Gardiner N, Fladeland M, Sterling E and Steininger M. 2003. Remote sensing for biodiversity science and conservation. Trends in Ecology and Evolution, 18(6): 306–314
Wright D H. 1983. Species–energy theory: an extension of species–area theory. Oikos, 41(3): 496–506
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