Individual-based modeling of ecological and evolutionary processes

By D. DeAngelis, Wolf M. Mooij. 2005

696 citations recorded by the source corpus.

Subfields: Genetics, Nature and Landscape Conservation, Public Health, Environmental and Occupational Health

View Paper: https://www.semanticscholar.org/paper/13e29d4c04e2e9e5b8673aca73416cf668c2d5e7

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In Genetics

In Nature and Landscape Conservation

In Public Health, Environmental and Occupational Health

Citations in the corpus

Global change and climate‐driven invasion of the Pacific oyster (Crassostrea gigas) along European coasts: a bioenergetics modelling approach (2016, methodology): “In addition, individual-based modelling (IBM) has now been recognized as a valuable approach in ecology and evolutionary biology, including bioenergetics modelling of life history traits (DeAngelis & Mooij, 2005).”
Symmetric competition causes population oscillations in an individual-based model of forest dynamics (2008, methodology): “Unlike earlier IBMs of plant competition (e.g., Huston and mith, 1987), FORSITE takes dispersal explicitly into account. ree height also interacts with dispersal distance, resulting in n interaction between local density and global distribution of rees.”
The Robust Volterra Principle* (2008, background): “(See also Donalson and Nisbet 1999; DeAngelis and Mooij 2005; Grimm and Railsback 2005.)”
End-To-End Models for the Analysis of Marine Ecosystems: Challenges, Issues, and Next Steps (2010, positive): “The individual-based approach has been used in single-and multiple-species models (DeAngelis and Mooij 2005), but far less in community-level analyses because of computational costs (Rose and Sable 2009).”
A standard protocol for describing individual-based and agent-based models (2006, methodology): “…that describe individual organisms or, more generally, “agents”, have become a widely used tool, not only in ecology (DeAngelis and Gross, 1992; DeAngelis and Mooij, 2005; Grimm, 1999; Grimm and Railsback, 2005; Huse et al., 2002; Shugart et al., 1992; Van Winkle et al., 1993) but also in…”
Predicting monarch butterfly (Danaus plexippus) movement and egg-laying with a spatially-explicit agent-based model: The role of monarch perceptual range and spatial memory (2018, background): “Agent-based modeling is well-suited to address the effects of different spatially-explicit landscape configurations on animal 4 population dynamics (DeAngelis and Mooij, 2005, Grimm et al., 2005, Railsback et al., 2006; Railsback and Grimm, 2011).”
Agent-based Simulation Platforms: Review and Development Recommendations (2006, background): “For example, a steady, sharp increase in the number of ecology publications using IBMs started in about 1990 [1].”
Trends and management implications of human-influenced life-history changes in marine ectotherms (2016, background): “Models that explicitly consider evolution are typically constrained to small species complexes 556 (DeAngelis and Mooij 2005; Miethe et al. 2009) or explore evolution of food webs (e.g. Rossberg et al.557 2005) rather than life-history traits.”
Next-generation dynamic global vegetation models: learning from community ecology. (2013, methodology): “An individual-based approach (DeAngelis & Mooij, 2005) allows a simulation run to consider many individual plants, each of which can potentially have a unique set of trait values (see Fig.”
Exploring, exploiting and evolving diversity of aquatic ecosystem models: a community perspective (2015, background): “Renewed interest in large ecosystem models occurred in the past decades, not the least as a result of the increased and distributed computational power, but this time with the tendency to link the models with individual-based and traitbased approaches (DeAngelis and Mooij 2005) and compare their beh”
Habitat, environment and niche: what are we modelling? (2006, background): “Nutritional and metabolic niche models must also be integrated with other individual-based models of processes such as dispersal and adaptation (DeAngelis and Mooij 1995, Pulliam 2000).”