Panmictic and Clonal Evolution on a Single Patchy Resource Produces Polymorphic Foraging Guilds

Abstract

We develop a stochastic, agent-based model to study how genetic traits and experiential changes in the state of agents and available resources influence individuals’ foraging and movement behaviors. These behaviors are manifest as decisions on when to stay and exploit a current resource patch or move to a particular neighboring patch, based on information of the resource qualities of the patches and the anticipated level of intraspecific competition within patches. We use a genetic algorithm approach and an individual’s biomass as a fitness surrogate to explore the foraging strategy diversity of evolving guilds under clonal versus hermaphroditic sexual reproduction. We first present the resource exploitation processes, movement on cellular arrays, and genetic algorithm components of the model. We then discuss their implementation on the Nova software platform. This platform seamlessly combines the dynamical systems modeling of consumer-resource interactions with agent-based modeling of individuals moving over a landscapes, using an architecture that lays transparent the following four hierarchical simulation levels: 1.) within-patch consumer-resource dynamics, 2.) within-generation movement and competition mitigation processes, 3.) across-generation evolutionary processes, and 4.) multiple runs to generate the statistics needed for comparative analyses. The focus of our analysis is on the question of how the biomass production efficiency and the diversity of guilds of foraging strategy types, exploiting resources over a patchy landscape, evolve under clonal versus random hermaphroditic sexual reproduction. Our results indicate greater biomass production efficiency under clonal reproduction only at higher population densities, and demonstrate that polymorphisms evolve and are maintained under random mating systems. The latter result questions the notion that some type of associative mating structure is needed to maintain genetic polymorphisms among individuals exploiting a common patchy resource on an otherwise spatially homogeneous landscape.

Temporal variation in resource selection of African elephants follows long‐term variability in resource availability

“…We also note that the emergence of discrete movement strategies, with an absence of intermediates is related to the evolution of behavioral guilds, where each strategy is a member of an “ideal free distribution” with regard to maximizing fitness, so that intermediate strategies are less fit (Getz et al. , ). Discrete movement behavioral types have also been observed in other species (Abrahms et al.…”

Making ecological models adequate

“…One can then model the same system at the refined level of an individual-based approach (Getz 2013). In this latter case, one can show that if individuals have different propensities to move, to avoid competitors, and to plan moves ahead, then several different movement behavioural types emerge (Getz et al 2015b. Thus, the consumers can then be organized into several syndromic movement groups (Spiegel et al 2017) that can be modelled using a more nuanced system of differential equations than the original by now taking into account this new group structure.…”

“…Scales: Multiscale models are challenging to implement from both modelling and computational points of view (Levin 1992;Leibold et al 2004;Slingo et al 2009;Dada & Mendes 2011;Getz 2013), but notable examples exist (Fig. 2): individual tree growth models have been scaled up to simulate landscape-level ecosystem dynamics (Seidl et al 2012); Michaelis-Menton soil microbial process models have been incorporated into earth system models (ESMs) to link the micro scales in the soil with landscape macro scales to make multi-decadal climate change projections (Wieder et al 2015;Luo et al 2016); and BTW processes (mentioned above) have been studied at evolutionary time scales revealing processes that lead to the emergence of foraging guilds (Getz et al 2015b. The study of systems that include evolutionary processso-called complex adaptive systems (CAS)has become a research field in its own right (Holland 2006;Miller & Page 2009).…”

Going through the motions: incorporating movement analyses into disease research

“…In practice, animal movement is driven by decisions that balance this trade‐off between habitat quality and disease risk, and behavioural polymorphisms might even evolve as a consequence (Getz et al . ). For example, in an anthrax‐endemic region of Namibia, zebra ( Equus quagga ) demonstrate a pattern of partial migration, where dominant herds appear to migrate away from high‐quality habitat during the anthrax season, leaving behind lower‐ranking resident herds to graze despite the higher disease risk (Zidon et al .…”

“…For example, ecological theory suggests that the source-sink dynamics that naturally emerge between high-and low-quality habitat (respectively) can be reversed by an environmentally-transmitted disease, which turns high-quality habitat into an ecological 'trap' (Leach et al 2016). In practice, animal movement is driven by decisions that balance this trade-off between habitat quality and disease risk, and behavioural polymorphisms might even evolve as a consequence (Getz et al 2015). For example, in an anthrax-endemic region of Namibia, zebra (Equus quagga) demonstrate a pattern of partial migration, where dominant herds appear to migrate away from high-quality habitat during the anthrax season, leaving behind lower-ranking resident herds to graze despite the higher disease risk (Zidon et al 2017).…”