000			01845nam a22002177a 4500
003			OSt
005			20260302082952.0
008			260302b |||||||| |||| 00| 0 eng d
020			_a9781613245675
040			_aDLC _ben _cDLC
050			_aDUCE QH541.15.S5 E275
100			_aZhang, WenJun _qWenJun Zhang
245			_aEcological modeling/ _cBy WenJun Zhang
260			_aNew York _bNova Science Publishers, _c2012.
300			_axiii, 405 p. : _bill. ; _c27 cm.
500			_aIncludes bibliographical references and index
520			_aEcological modeling is a quantitative approach used to understand, simulate, and predict the structure and dynamics of ecological systems. By integrating mathematics, statistics, and computational techniques, ecological models represent interactions among organisms, populations, communities, and their environments. These models range from simple analytical frameworks, such as population growth equations and predator–prey systems (e.g., the Lotka–Volterra equations), to complex, spatially explicit simulations that incorporate climate, land use, and biogeochemical processes. Ecological modeling plays a crucial role in addressing contemporary environmental challenges, including biodiversity loss, habitat fragmentation, climate change impacts, and resource management. Models are used to test ecological hypotheses, forecast species distributions, evaluate ecosystem services, and inform conservation and policy decisions. Advances in remote sensing, geographic information systems (GIS), and machine learning have enhanced model accuracy and scalability _uhttp://172.20.27.22:4000/handle/123456789/125
700			_a Zhang,Wen-Jun _eeditor _qWen-Jun Zhang
856			_yhttp://172.20.27.22:4000/handle/123456789/125 _uhttp://172.20.27.22:4000/handle/123456789/125
942			_2lcc _cBK _n0
999			_c4399 _d4399