Predicting global dynamics from local interactions: individual-based models predict complex features of marine epibenthic communities
Dunstan, Piers K. and Johnson, Craig R. (2005) Predicting global dynamics from local interactions: individual-based models predict complex features of marine epibenthic communities. Ecological Modelling, 186 (2). pp. 221-233. ISSN 0304-3800 | PDF - Full text restricted - Requires a PDF viewer 177Kb | |
Official URL: http://dx.doi.org/10.1016/j.ecolmodel.2005.01.016 AbstractSpatially explicit community models often generate a wide range of complex dynamics and behaviours, but the predictions
of community structure and dynamics from many of these models are rarely compared with the natural communities they are
intended to represent. Here, we develop a spatially explicit individual-based model of a complex marine epibenthic community
and test its ability to predict the dynamics and structure of the natural community on which the model is based. We studied
a natural epibenthic community on small-scale patches of jetty wall to estimate the outcomes of pair-wise interactions among
individuals of different species, neighbour-specific growth rates, and species-specific recruitment and mortality rates. The model
is defined with rules acting at two spatial scales: (1) between individual cells on the spatial landscape that define the nature of
interactions, growth and recruitment at a scale of 1 cm2, and (2) at the scale of whole colonies (blocks of contiguous cells) that
define size-specific mortality and limitations to the maximum size of colonies for some species for scales up to 1000 cm2. The
model is compared to the existing patches on the jetty wall and proves to be a good descriptor of the large range of possible
communities on the jetty, and of the multivariate variances of the patches. The high variability in community structure predicted
by the model, which is similar to that observed in the natural community, arises from observed variability in parameters of
interaction outcomes, growth, recruitment, and mortality of each species. Thus if the processes we modelled operate similarly
in nature, our results suggest that it is difficult to attempt to predict the precise trajectory of the community in a particular patch.
Our results show that it is possible to develop a testable, predictive spatial model where the patch-scale community patterns of
structure and dynamics are emergent, arising from local processes between colonies and species-specific demography. Repository Staff Only: item control page
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