TRANSMUTATION AND FUNCTIONAL REPRESENTATION OF HETEROGENEOUS LANDSCAPES

被引:63
作者
KING, AW
JOHNSON, AR
ONEILL, RV
机构
[1] Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, 37831-6335, TN
关键词
D O I
10.1007/BF00141438
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Models of local small-scale ecological processes can be used to describe related processes at larger spatial scales if the influences of increased scale and heterogeneity are carefully considered. In this paper we consider the changes in the functional representation of an ecological process that can occur as one moves from a local small-scale model to a model of the aggregate expression of that process for a larger spatial extent. We call these changes "spatial transmutation". We specifically examine landscape heterogeneity as a cause of transmutation. Spatial transmutation as a consequence of landscape heterogeneity is a source of error in the prediction of aggregate landscape behavior from smaller scale models. However, we also demonstrate a procedure for taking advantage of spatial transmutation to develop appropriately scaled landscape functions. First a mathematical function describing the process of interest as a local function of local variables is defined. The spatial heterogeneity of the local variables is described by their statistical distribution in the landscape. The aggregate landscape expression of the local process is then predicted by calculating the expected value of the local function, explicitly integrating landscape heterogeneity. Monte Carlo simulation is used to repeat the local-to-landscape extrapolation for a variety of landscape patterns. Finally, the extrapolated landscape results are regressed on landscape variables to define response functions that explain a useful fraction of the total variation in landscape behavior. The response functions are hypotheses about the functional representation of the local process at the larger spatial scale.
引用
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页码:239 / 253
页数:15
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  • [1] Allen T.F.H., Starr T.B., Hierarchy: Perspectives for Ecological Complexity, (1982)
  • [2] Cale W.G., Odell P.L., Concerning aggregation in ecosystem modeling, Theoretical Systems Ecology, pp. 55-77, (1979)
  • [3] Cale W.G., Odell P.L., Behavior of aggregate state variables in ecosystem models, Math. Biosci., 49, pp. 121-137, (1980)
  • [4] Cale W.G., O'Neill R.V., Gardner R.H., Aggregation error in nonlinear ecological models, J. Theor. Biol., 100, pp. 539-550, (1983)
  • [5] Dale V.H., Jager H.I., Gardner R.H., Rosen A.E., Using sensitivity and uncertainty analyses to improve predictions of broad-scale forest development, Ecol. Model., 42, pp. 165-178, (1988)
  • [6] Dickinson R.E., Global climate and its connections to the biosphere, Climate Vegetation Interactions, pp. 5-8, (1986)
  • [7] DeAngelis D.L., Waterhouse J.C., Post W.M., O'Neill R.V., Ecological modelling and disturbance evaluation, Ecol. Model., 29, pp. 399-419, (1985)
  • [8] DeAngelis D.L., Post W.M., Travis C.C., Positive Feedbacks in Natural Systems, (1986)
  • [9] Forman R.T.T., Godron M., Landscape Ecology, (1986)
  • [10] Gardner R.H., Trabalka J.R., Methods of uncertainty analysis for a global carbon dioxide model, (1985)