Can morphological traits explain species‐specific differences in meta‐analyses? A case study of forest beetles

Author:

Staton Tom123ORCID,Girling Robbie D.1ORCID,Redak Richard A.4ORCID,Smith Sandy M.2,Allison Jeremy D.23ORCID

Affiliation:

1. School of Agriculture, Policy and Development University of Reading Reading UK

2. Institute of Forestry & Conservation University of Toronto Toronto Ontario Canada

3. Natural Resources Canada, Canadian Forest Service Great Lakes Forestry Centre Sault Ste Marie Ontario Canada

4. Department of Entomology University of California Riverside Riverside California USA

Abstract

AbstractMeta‐analyses have become a valuable tool with which to synthesize effects across studies, but in ecology and evolution, they are often characterized by high heterogeneity, where effect sizes vary between studies. Much of this heterogeneity can be attributed to species‐specific differences in responses to predictor variables. Here, we aimed to incorporate a novel trait‐based approach to explain species‐specific differences in a meta‐analysis by testing the ability of morphological traits to explain why the effectiveness of flight‐intercept trap design varies according to beetle species, a critical issue in forest pest management. An existing morphological trait database for forest beetles was supplemented, providing trait data for 97 species, while data from a previous meta‐analysis on capture rates of bark or woodboring beetles according to different trap designs were updated. We combined these sources by including nine morphological traits as moderators in meta‐analysis models, for five different components of trap design. Traits were selected based on theoretical hypotheses relating to beetle movement, maneuverability, and sensory perception. We compared the performance of morphological traits as moderators versus guild, taxonomic family, and null meta‐analysis models. Morphological traits for the effect of trap type (panel vs. multiple‐funnel) on beetle capture rates improved model fit (AICc), reduced within‐study variance (σ2), and explained more variation (McFadden's pseudo‐R2) compared with null, guild, and taxonomic family models. For example, morphological trait models explained 10% more of the variance (pseudo‐R2) when compared with a null model. However, using traits was less informative to explain how detailed elements of trap design such as surface treatment and color influence capture rates. The reduction of within‐study variance when accounting for morphological traits demonstrates their potential value for explaining species‐specific differences. Morphological traits associated with flight efficiency, maneuverability, and eye size were particularly informative for explaining the effectiveness of trap type. This could lead to improved predictability of optimal trap design according to species. Therefore, morphological traits could be a valuable tool for understanding species‐specific differences in community ecology, but other causes of heterogeneity across studies, such as forest type and structure, require further investigation.

Funder

Mitacs

Publisher

Wiley

Subject

Ecology

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