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Physiologically based landscape use model for large herbivores

Authors
Journal
Ecological Modelling
0304-3800
Publisher
Elsevier
Publication Date
Volume
61
Identifiers
DOI: 10.1016/0304-3800(92)90020-f
Disciplines
  • Biology
  • Design
  • Ecology
  • Geography

Abstract

Abstract This paper describes the development and initial validation of a simulation model designed to predict patterns of landscape use by cattle as a function of environmental conditions and spatial distribution of key landscape attributes. The model consists of environmental, physiological, behavioral, and landscape submodels. Information on climatic conditions from the environmental submodel is used by the physiological submodel to determined current physiological status of animals in terms of heat balance, water balance, and hunger status. Information on physiological status is used by the behavioral submodel to select and subsequently perform activities. Performance of activities then affects physiological state. The landscape submodel provides information concerning spatial relationships among and within different habitat patches. Landscape attributes influence animal behavior, and animal behavior then influences landscape characteristics. Several aspects of model performance were evaluated using new field data and literature information. Predicted animal water losses via respiration, sweat, urine, and feces, total time spent in various daily activities, and the sequence of these activities all are in general agreement with field data and literature information. However, more accurate prediction of respiration rate, which controls shade seeking behavior in the model, may require more sophisticated representation of the combined effect of temperature and relative humidity. Initial simulations, which examined seasonal differences in the effect of distance between shade and water on landscape use, demonstrated the capability of the model to address a wide variety of questions concerning utilization of heterogeneous landscapesby grazing animals.

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