Agent-based modelling, molluscan population dynamics, and archaeomalacology
Authored by Alex E Morrison, Melinda S Allen
Date Published: 2017
DOI: 10.1016/j.quaint.2015.09.004
Sponsors:
Marsden Fund New Zealand
Royal Society of New Zealand
Platforms:
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Model Documentation:
Other Narrative
Mathematical description
Model Code URLs:
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Abstract
Agent-based modelling (ABM) is an emerging archaeological tool that
offers insights into processes which are archaeologically invisible or
difficult to detect. Here we illustrate the potential of ABM for
archaeomalacology, posing two research questions and comparing ABM
results with Pacific archaeological sequences. The first analysis
considers how molluscan energetic return rates (ERR) and age of
reproductive maturity (ARM), singularly or in combination, influence
prey population resilience. The second analysis assesses how prey
spatial structure affects foraging efficiency and prey susceptibility to
resource depression. Consistent with expectations from evolutionary
ecology and life history theory, the ABM results demonstrate that both
ERR and ARM influence prey population resilience (or vulnerability).
However, the analysis also demonstrates that ARM is the more important
variable and taxa with high ERR (i.e., large-bodied) are
disproportionately affected by human harvesting. Not only are efficient
foragers more likely to target high ERR taxa, but these prey often have
delayed ARM and un-foraged individuals are more likely to be smaller and
immature, with disadvantages for population stability and recovery. In
short, early-maturing taxa are highly resilient, while late-maturing
organisms are more vulnerable; these outcomes also are observed
archaeologically. The ABM analyses also demonstrate the effects of prey
spatial structure on molluscan susceptibility to resource depression.
High prey aggregation initially allows for high foraging efficiency, but
prey abundance and encounter rates often rapidly decline. In contrast,
when prey are dispersed, search time is greater, leading to lower
encounter rates and reduced foraging efficiency, but greater prey
population stability. Our ABM and archaeological examples further
illustrate that while general principles can be derived, the resilience
and spatial structure of specific prey populations, as well as foraging
outcomes, are context dependent and continuously evolving. Finally, we
note that model departures from theoretical expectations serve to
stimulate further research, including use of additional parameters,
consideration of novel contextual evidence, and/or investigation of
social, technological or environmental hypotheses. (C) 2015 Elsevier Ltd
and INQUA. All rights reserved.
Tags
Agent-based modelling
Life-history
Northern australia
Benthic marine-invertebrates
Spatial
structure
Marine mollusc resilience
Life history traits
Prey spatial structure
Foraging dynamics
Pacific islands
Blue mud bay
Southern
africa
Giant clam
Behavioral depression
California coast
Tridacna-maxima