Dobson, F. S. | bioRxiv Science

bioRxiv2023

Trade-offs in dormancy phenology in endotherms and ectotherms

Seasonal animal dormancy, hibernation or diapause, is widely interpreted as a physiological response for surviving energetic challenges during the harshest times of the year (the physiological constraint hypothesis). However, there are other mutually non-exclusive hypotheses to explain the timing of animal dormancy, that is, entry into and emergence from hibernation (i.e. dormancy phenology). Other survival advantages of dormancy that have been proposed are reduced risks of predation and competition (the "life-history" hypothesis), but comparative tests across animal species are not yet available. Under this hypothesis, dormancy phenology is influenced by a trade-off between reproductive advantages of being active and survival benefits of dormancy. Within a species, males and females differ in the amount of time and energy they invest in reproduction. Thus, the trade-off between reproduction and survival may be reflected by within-species sex differences in the phenology of dormancy. To examine this hypothesis, we used two complementary approaches: (i) a set of phylogenetic comparative analyses on mammals (mainly holarctic rodents), and (ii) a comparison between endotherm and ectotherm dormancy, via analyses of endotherms (including mainly holoarctic rodents) and the existing literature on ectotherms. Using the phylogenetic comparative method applied to more than 20 hibernating mammalian species, we found support for both hypotheses as explanations for the phenology of dormancy. In accordance with the life history hypotheses, sex differences in emergence and immergence were favored by the sex difference in reproductive effort. In addition, physiological constraint may influence the trade-off between survival and reproduction such that, low temperature and precipitation as well as smaller body mass influence sex differences in phenology. We also compiled initial evidence that ectotherm dormancy (invertebrates and reptiles) may be 1) less temperature dependent than previously thought and 2) associated with trade-offs consistent with the life history hypothesis. Dormancy in some endotherms and ectotherms show staggered phenology with respect to the growing season (earlier emergence and immergence than expected) which illustrates the selection pressure exerted by the trade-off between reproduction (earlier emergence than expected) and adult survival (earlier immergence than expected). Thus, dormancy during non-life-threatening periods that are unfavorable for reproduction may be more widespread than previously appreciated.

evolutionary biology↗

bioRxiv2021

Reliable hypotheses testing in animal social network analyses: global index, index of interactions and residual regression

Animal social network analyses (ASNA) have led to a foundational shift in our understanding of animal sociality that transcends the disciplinary boundaries of genetics, spatial movements, epidemiology, information transmission, evolution, species assemblages and conservation. However, some analytical protocols (i.e., permutation tests) used in ASNA have recently been called into question due to the unacceptable rates of false negatives (type I error) and false positives (type II error) they generate in statistical hypothesis testing. Here, we show that these rates are related to the way in which observation heterogeneity is accounted for in association indices. To solve this issue, we propose a method termed the "global index" (GI) that consists of computing the average of individual associations indices per unit of time. In addition, we developed an "index of interactions" (II) that allows the use of the GI approach for directed behaviours. Our simulations show that GI: 1) returns more reasonable rates of false negatives and positives, with or without observational biases in the collected data, 2) can be applied to both directed and undirected behaviours, 3) can be applied to focal sampling, scan sampling or "gambit of the group" data collection protocols, and 4) can be applied to first- and second-order social network measures. Finally, we provide a method to control for non-social biological confounding factors using linear regression residuals. By providing a reliable approach for a wide range of scenarios, we propose a novel methodology in ASNA with the aim of better understanding social interactions from a mechanistic, ecological and evolutionary perspective.

animal behavior and cognition↗