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Matthew Mumma

Publications and source records attributed to Matthew Mumma.

2 recordsLinked to original sources

Examining spatial patterns of selection and use for an altered predator guild

Anthropogenic disturbances have altered species’ distributions potentially impacting interspecific interactions. Interference competition is when one species denies a competing species access to a resource. One mechanism of interference competition is aggression, which can result in altered space-use of a subordinate species due to the threat of harm, otherwise known as a ‘landscape of fear’. Alternatively, subordinates might outcompete dominant species in resource-poor environments via a superior ability to extract resources. Our goal was to evaluate spatial predictions of the ‘landscape of fear’ hypothesis for a carnivore guild in Newfoundland, Canada, where coyotes recently immigrated. Native Newfoundland carnivores include red foxes, Canada lynx, and black bears. We predicted foxes and lynx would avoid coyotes because of their larger size and similar dietary niches. We used scat-detecting dogs and genetic techniques to locate and identify predator scats. We then built resource selection functions and tested for avoidance by incorporating predicted values of selection for the alternative species into the best supported models of each species. We found multiple negative relationships, but notably did not find avoidance by foxes of areas selected by coyotes. While we did find that lynx avoided coyotes, we also found a reciprocal relationship. The observed patterns suggest spatial partitioning and not coyote avoidance, although avoidance could still be occurring at different spatial or temporal scales. Furthermore, Newfoundland’s harsh climate and poor soils may swing the pendulum of interspecific interactions from interference competition to exploitative competition, where subordinates outcompete dominant competitors through a superior ability to extract resources.

Newfoundland

Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern

The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially-explicit, individual-based program to simulate gene flow in a spatially continuous population inhabiting a landscape with gradual spatial changes in resistance to movement. We simulated a wide range of combinations of number of loci, number of alleles per locus and number of individuals sampled from the population. We assessed how these three aspects of study design influenced the statistical power to successfully identify the generating process among competing hypotheses of isolation-by-distance, isolation-by-barrier, and isolation-by-landscape resistance using a causal modelling approach with partial Mantel tests. We modelled the statistical power to identify the generating process as a response surface for equilibrium and non-equilibrium conditions after introduction of isolation-by-landscape resistance. All three variables (loci, alleles and sampled individuals) affect the power of causal modelling, but to different degrees. Stronger partial Mantel r correlations between landscape distances and genetic distances were found when more loci were used and when loci were more variable, which makes comparisons of effect size between studies difficult. Number of individuals did not affect the accuracy through mean equilibrium partial Mantel r , but larger samples decreased the uncertainty (increasing the precision) of equilibrium partial Mantel r estimates. We conclude that amplifying more (and more variable) loci is likely to increase the power of landscape genetic inferences more than increasing number of individuals.

Molecular Ecology Resources