IntroductionAn organism’s thermal biology is determined in part by its size and shape (Angilletta, 2009). For ectotherms, in particular, body surface area and volume mediate the exchange of heat with the environment (Kühsel et al., 2017; Pincebourde et al., 2021). Small-bodied organisms like insects have high surface area-to-volume ratios, and thus experience accelerated heat loss over their proportionally larger body surface (Gunderson, 2024; Kühsel et al., 2017). This relationship is also influenced by morphology, with more elongated body forms having higher proportional surface area than more compact forms (Castro et al., 2021; Okie, 2013). Quantifying these relationships between morphology and thermal biology is essential for predicting differential responses to climate conditions across phenotypically diverse taxa.Biophysical models provide useful frameworks for linking morphology to thermal performance under varying environmental conditions (Johnson et al., 2022, 2025; Stabentheiner & Kovac, 2023; Stupski & Schilder, 2021). Heat budgets, for example, are biophysical models that estimate rates of heat flux attributable to environmental sources (e.g., radiation, conduction, convection) and internal physiological processes (e.g., metabolic heat production, evaporative cooling). Body size and morphology are key parameters in these models because they directly influence rates of heat loss and gain. Specifically, body surface area represents the interface through which insects interact with the thermal environment, regulating the degree of radiative heat gain, convective heat loss to moving air, conductive heat exchange, and evaporative heat loss. Relatedly, body volume and mass determine an individual’s thermal inertia, or the degree of energy required to change body temperature.Consequently, biophysical models depend on our ability to accurately quantify insect size and form. Traditionally, bee body surface area and volume have been quantified indirectly by conceptualizing body segments (tagmata) as ideal solid shapes, for example, by assuming the thorax represents a sphere of a given diameter and estimating surface area and volume from geometric equations (Cooper et al., 1985a; Roberts et al., 1998; Roberts & Harrison, 1999). These methods provide useful alternatives to empirical measurements, which have been hindered by practical difficulties of measuring small, fragile, and complex forms. Consequently, these methods have not yet been empirically validated; the error in geometric size estimates is unknown. Recent advancements in 3D surface modeling of small objects at relatively low cost place these empirical measurements within reach (Doan & Nguyen, 2024; Kühsel et al., 2017; Ströbel et al., 2018). One such technique, photogrammetry, reconstructs a 3D model from a series of 2D images of an object taken from multiple angles. These methods may represent important improvements over traditional geometric estimates that ignore complex variation in 3D morphology (Ostwald et al., 2025).We asked how honey bee (Apis mellifera Linnaeus 1758) size measurements from 3D models differ from those estimated from geometric equations, and what the implications of these differences are for downstream biophysical modelling. Honey bees are a classic model system for understanding mechanisms of thermoregulation insects (Cooper et al., 1985b; Glass et al., 2024; Glass & Harrison, 2024; Roberts & Harrison, 1999; Stabentheiner & Kovac, 2023). We used photogrammetry to construct 3D models of honey bee specimens, from which we collected empirical measurements of body surface area and volume. We compared these measurements to geometric estimates from linear measurements of the same specimens, to estimate the percent error in these estimation methods. Finally, we incorporated our error estimates into a biophysical model using published data for honey bees in flight (Roberts & Harrison, 1999), to understand how size error influences estimates of heat flux across a realistic temperature range. Together, these results clarify the consequences of size assumptions for understanding routes of heat exchange in these ecologically important pollinators.

IntroductionInferring generalizable patterns in species dynamics, distributions, and functional variation are central aims of ecology and evolutionary biology (MacArthur, 1972). Trait-based approaches, which quantify phenotypic characteristics that impact organisms’ fitness and/or functional role, provide a tractable comparative framework for understanding communities, ecosystems, and evolutionary processes (Mcgill et al., 2006; Violle et al., 2007). Functional trait studies have proliferated over the past two decades, addressing foundational questions in community ecology (Cadotte et al., 2015; Mcgill et al., 2006; Violle and Jiang, 2009), biogeography (Violle et al., 2014), and conservation biology (Cadotte et al., 2011; Wellnitz and Poff, 2001) across taxonomic groups. These works emphasize the promise of trait-based research for generating novel insights into central ecological concepts and theories.Increasingly, bee researchers are recognizing the utility of trait-based approaches for a wide variety of applications in ecological research. Bees (Hymenoptera: Apoidea: Anthophila) represent more than 20,000 species worldwide and display dramatic interspecific variation in morphology and behavior (Figure 1), including traits that mediate pollination services and responses to global environmental change (Supplementary Table 1). Exploration of functional traits has long been a cornerstone of bee research, yet only recently have these traits been systematically applied in bee ecological studies as a comparative framework for understanding community-level processes. Given their major functional role as the primary animal pollinators of terrestrial ecosystems (Ollerton et al., 2011), the bees represent a group ripe for exploration through a functional ecological lens.Here, we review an emerging body of literature that quantifies functional traits across bee communities to address questions in bee ecology. In doing so, we address the following questions: How have functional traits been used to study bee ecology? What have been the major outcomes and limitations in bee functional trait research? How might this framework be leveraged to address urgent questions in the study of global bee declines? We review the variety of methods used to quantify bee trait variation, highlight common methodological problems and inconsistencies, and recommend best practices. Additionally, we describe geographic, taxonomic, and trait biases across the body of bee functional trait work, and highlight research areas that merit particular attention in future studies. Finally, we emphasize the value of open trait data sharing, and propose a roadmap toward a global bee functional trait database, including an initial aggregated dataset of 3369 morphological measurements from 1209 bee species.

Authors: Madeleine M. Ostwald1*, Kathryn Chen1, Nicholas Alexander1, Luning Ding1, Victor H. Gonzalez2, Katja C. Seltmann1

Abstract

Madeleine M. Ostwald*, Valentina A. Venegas, and Katja C. Seltmann

Abstract1.     Climatic factors are known to mediate the expression of social behaviors. Likewise, variation in social behavior can dictate climate responses. Understanding interactions between climate and sociality is crucial for predicting impacts of climate change on animal populations.

Phenotypic divergence is an important consequence of restricted gene flow in insular populations. This divergence can be challenging to detect when it occurs through subtle shifts in morphological traits, particularly in traits with complex geometries, like insect wing venation. Here, we employed geometric morphometrics to assess the extent of variation in wing venation patterns across reproductively isolated populations of the social sweat bee, Halictus tripartitus. We examined wing morphology of specimens sampled from a reproductively isolated population of H. tripartitus on Santa Cruz Island (Channel Islands, Southern California). Our analysis revealed significant differentiation in wing venation in this island population relative to conspecific mainland populations. We additionally found that this population-level variation was less pronounced than the species-level variation in wing venation among three sympatric congeners native to the region, Halictus tripartitus, Halictus ligatus, and Halictus farinosus. Together, these results provide evidence for subtle phenotypic divergence in an island bee population. More broadly, these results emphasize the utility and potential of wing morphometrics for large-scale assessment of insect population structure.