SHALOM – A community-level object-oriented landscape simulation model
Major progress has been made in our understanding of large-scale ecological processes and patterns. SHALOM is a spatially explicit, multi-species, process-based, object-oriented landscape simulation model, built upon major lessons from fields such as metapopulation dynamics and landscape ecology. Consistent with the current landscape ecology terminology, SHALOM has physical classes (landscape, habitat, cell, patch) and biological classes (population, species, community). Each class has functions and characteristics that are strongly based on ecological realism. At the local scale, populations grow continuously, and are affected by: (1) a community-level saturation effect; (2) a species-habitat match; and (3) demographic stochasticity. The global-scale processes of the model include fitness-optimizing migration and catastrophic stochasticity that can be controlled for its probability, intensity, and spatial range. The processes of the model use allometric relationships and energy as a common currency to bridge differences between species of different body sizes located in habitats of different productivities. These processes also allow both intraspecific and interspecific effects to take place simultaneously without assuming any specific relationship between the two. Hence, SHALOM, with its functions and procedures, opens new opportunities to study combined ecosystem, community and population processes. Simulation results on species composition and diversity show that the integration of interspecific competition, demographic stochasticity and dispersal revealed different predictions when different combinations of these processes were used. One novel prediction is that the complex relationship between dispersal and demographic stochasticity caused the global extinction of the largest species. This, in turn, might have further implications for conservation. Overall, the model represents a synthetic approach that provides ways to explore high-level ecological complexity and suggests predictions for future studies of macroecological questions.
