Untangling Sampling Bias From Lemur Dietary Specialization
Anna Vasenina, Camille M. M. DeSisto, Peter J. Mucha

TL;DR
This paper explores how sampling bias affects the understanding of lemur dietary specialization and its ecological roles.
Contribution
The study introduces a method to separate sampling bias effects from lemur traits in dietary richness estimates.
Findings
Sampling effort was found to be a better predictor of dietary richness than lemur traits.
Accounting for sampling bias improves understanding of ecological roles and trophic interactions.
The study highlights the importance of considering sampling effort in trait-based ecological analyses.
Abstract
Identifying the drivers of wildlife dietary specialization is fundamental to understanding trophic interactions and species' functional roles in their environment. However, sampling bias is pervasive in trophic interaction research, especially in biodiverse areas with cryptic species. We aim to investigate the role of sampling bias in mediating the estimated effects of functional traits on dietary specialization. Specifically, we improve estimates of observed lemur dietary richness by analyzing trait‐based biases in lemur–plant ecological interactions. First, we quantified undersampling of plants and their interactions with lemurs. Next, we tested the inclusion of sampling effort on the estimated effects of trait predictors by comparing three negative binomial regression models with the following predictors: (i) five lemur traits (body mass, litter size, group size, diurnality,…
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Taxonomy
TopicsPrimate Behavior and Ecology · Wildlife Ecology and Conservation · Amphibian and Reptile Biology
