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Biodiversity in DrylandsToward a Unified Framework$
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Moshe Shachak, Stewart T. A. Pickett, James R. Gosz, and Avi Perevolotski

Print publication date: 2005

Print ISBN-13: 9780195139853

Published to Oxford Scholarship Online: November 2020

DOI: 10.1093/oso/9780195139853.001.0001

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PRINTED FROM OXFORD SCHOLARSHIP ONLINE (oxford.universitypressscholarship.com). (c) Copyright Oxford University Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 27 November 2021

(p.70) 5 Shalom: A Landscape Simulation Model for Understanding Animal Biodiversity

(p.70) 5 Shalom: A Landscape Simulation Model for Understanding Animal Biodiversity

(p.70) 5 Shalom: A Landscape Simulation Model for Understanding Animal Biodiversity
Biodiversity in Drylands

Michael L. Rosenzweig

Robert D. Holt

Oxford University Press

The ecological complexity of landscape components of biodiversity may be understood by examining relatively simple landscapes such as those of arid and semiarid lands. It is believed that such lands provide easy recognition of their components and a relatively simple interaction between their different diversities (Safriel et al. 1989). In general, ecological complexity emerges from the existence of environmental heterogeneity and scaling effects. The effects of scaling include the differential changes in observed patterns produced by processes that operate and interact at different tempospatial scales. For example, interspecific competition may have a strong influence on species coexistence and, therefore, diversity, at a local scale, may be insignificant for determining species diversity compared with a regional scale, where colonization–extinction dynamics may be the major determinant for species diversity. Environmental heterogeneity mainly results from three components: habitat diversity (the number of different habitats), habitat size (the size of each habitat’s patch), and habitat patchiness (the distribution of the different habitats’ patches in the landscape). Each component may affect species diversity by providing specific processes for coexistence, colonization, extinction, and population-size dependent effects. Additionally, as emphasized by Kotliar and Wiens (1990), different scales (Wiens 1989) should introduce different levels of heterogeneity that may influence the way organisms respond to their environment. Morris (1987) suggested that an organism that does not respond to a particular heterogeneity presented at one scale may respond to the heterogeneity presented at another scale. This concept has led ecologists to accept the idea that ecological processes and patterns are not fixed, but rather depend on the scale under study (e.g., Addicott et al. 1987, Kotliar and Wiens 1990, Dunning et al. 1992, Wiens et al. 1993). In this chapter we describe a spatially explicit, multispecies, process-based landscape simulation model, SHALOM (Species-Habitat Arrangement-Landscape-Oriented-Model) that has been designed to explore ecological complexity of large scales. After describing the model, we will present several simulation results to demonstrate the strengths of using such models for understanding biodiversity processes and patterns. We believe that this model can serve an important tool for exploring biodiversity in arid and semiarid lands.

Keywords:   Colonization-extinction dynamics, Fitness, Ideal-free distribution, Landscape cell, Metabolic maintenance cost, Object-Oriented Programming, Rate birth, Scale landscape

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