Spatial patterns of plant functional types and environmental proxies of plant richness in alpine region of Western Himalaya, India

被引:4
作者
Padalia, Hitendra [1 ]
Bushra, Aimon [1 ]
Singh, Gajendra [2 ]
Nandy, Subrata [1 ]
Rai, Ishwari Datt [3 ]
Rawat, Gopal S. [3 ]
机构
[1] Indian Inst Remote Sensing, Forestry & Ecol Dept, 4 Kalidas Rd, Dehra Dun 248001, Uttar Pradesh, India
[2] Uttarakhand Space Applicat Ctr, Forestry & Climate Change Div, 93-2 Vasant Vihar, Dehra Dun 248006, Uttar Pradesh, India
[3] Wildlife Inst India, PB 18, Dehra Dun 248002, Uttar Pradesh, India
关键词
GLM; Landscape metrics; PFTs; Predictive modelling; Remote sensing; SPECIES RICHNESS; DISTRIBUTION MODELS; CLASSIFICATION; GRADIENTS; FOREST; SPACE; DISTRIBUTIONS; DETERMINANTS; EXPLANATION; PERFORMANCE;
D O I
10.1007/s10531-018-1664-1
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
The geographical patterns of species richness and underlying mechanisms are among the central issues of ecology. The Himalaya, a global biodiversity hotspot, lacks spatially explicit representation of plant richness patterns and predictor environmental covariates. The rugged Himalayan terrain limits large-scale field surveys, we, therefore, disentangle the role of remotely sensed environmental proxies for characterization of Plant Functional Types (PFTs) and prediction of plant richness in an alpine area in WesternHimalaya. Alpine plant richness was recorded in cluster plots (10 random quadrants of 1m(2) in approximately 1-ha area) across 97 sites in Pithoragarh district in part of the Western Himalaya(India). The dominant PFTs were mapped based on support vector machine classification of Landsat 8 image. Thesatellite-derived climate, landscape,and topographic variables were correlated to plant richness using generalized linear model (GLM) with poisson distribution to unravel species richness-environment linkages in the study area. The dominant PFTs mapped were herbaceous meadow, Danthonia grassland, Kobresia sedge meadow, moist scrub, and dry scrub. The GLM based plant richness model explained 70% variation in alpine plant richness. The environmental factorssuch as vegetation vigor, elevation, landscape diversity and moisturewere observed to influence alpine plant richness of the study area. The study presents a valuable baseline spatial database for judicious management of alpine plant resources and climate change studies.
引用
收藏
页码:2221 / 2244
页数:24
相关论文
共 75 条
  • [51] Polunin O., 1997, Flowers of the Himalaya
  • [52] Plant functional type classification for earth system models: results from the European Space Agency's Land Cover Climate Change Initiative
    Poulter, B.
    MacBean, N.
    Hartley, A.
    Khlystova, I.
    Arino, O.
    Betts, R.
    Bontemps, S.
    Boettcher, M.
    Brockmann, C.
    Defourny, P.
    Hagemann, S.
    Herold, M.
    Kirches, G.
    Lamarche, C.
    Lederer, D.
    Ottle, C.
    Peters, M.
    Peylin, P.
    [J]. GEOSCIENTIFIC MODEL DEVELOPMENT, 2015, 8 (07) : 2315 - 2328
  • [53] Spatial pattern of vascular plant diversity in North America north of Mexico and its floristic relationship with Eurasia
    Qian, H
    [J]. ANNALS OF BOTANY, 1999, 83 (03) : 271 - 283
  • [54] Rana SK, 2017, DATA, V2, DOI 10.3390/data2040036
  • [55] Geospatial modelling approach for identifying disturbance regimes and biodiversity rich areas in North Western Himalayas, India
    Rashid, Irfan
    Romshoo, Shakil Ahmad
    Vijayalakshmi, Tartiparti
    [J]. BIODIVERSITY AND CONSERVATION, 2013, 22 (11) : 2537 - 2566
  • [56] Rawat GS, 2007, Alpine vegetation of the Western Himalaya: species diversity, community structure, dynamics and aspects of conservation
  • [57] Rawat GS, 2005, Alpine meadows of Uttaranchal: Ecology, Landuse and Status of Madicinal and Aromatic Plants
  • [58] Rion V, 2010, THESIS
  • [59] Rodgers W.A., 1988, PLANNING WILDLIFE PR, VI
  • [60] Species richness of multiple functional groups peaks in alpine tundra in subarctic Alaska
    Roland, Carl A.
    Stehn, Sarah E.
    Schmidt, Joshua H.
    [J]. ECOSPHERE, 2017, 8 (06):