Ecological studies of global warming impacts have many constraints. Organisms are often exposed to higher temperatures for short periods of time, probably underestimating their ability to acclimate or adapt relative to slower but real rates of warming. Many studies also focus on a limited number of traits and miss the multifaceted effects that warming may have on organisms, from physiology to behaviour. Organisms exhibit different movement traits, some of which are primarily driven by metabolic processes and others by decision‐making, which should influence the extent to which temperature affects them. We collected snails from streams that have been differentially heated by geothermal activity for decades to determine how long‐term exposure to different temperatures affected their metabolism and movement. Additionally, we collected snails from a cold stream (5°C) and measured their metabolism and movement at higher temperatures (short‐term exposure). We used respirometry to measure metabolic rates and automated in situ image‐based tracking to quantify several movement traits from 5 to 21°C. Long‐term exposure to higher temperatures resulted in a greater thermal sensitivity of metabolic rate compared to snails exposed for short durations, highlighting the need for caution when conducting acute temperature exposures in global warming research. Average speed, which is largely driven by metabolism, also increased more with temperature for long‐term exposure compared to short‐term exposure. Movement traits we interpret as more decision‐based, such as time spent moving and trajectory shape, were less affected by temperature. Step length increased and step angle decreased at higher temperatures for both long‐ and short‐term exposure, resulting in overall straighter trajectories. The power‐law exponent of the step length distributions and fractal dimension of trajectories were independent of temperature, however, suggesting that snails retained the same movement strategy. The observed changes in snail movement at higher temperatures should lead to higher encounter rates and more efficient searching, providing a behavioural mechanism for stronger plant–herbivore interactions in warmer environments. Our research is among the first to show that temperature has contrasting effects on different movement traits, which may be determined by the metabolic contribution to those behaviours.
Understanding animal movement often relies upon telemetry and biologging devices. These data are frequently used to estimate latent behavioural states to help understand why animals move across the landscape. While there are a variety of methods that make behavioural inferences from biotelemetry data, some features of these methods (e.g. analysis of a single data stream, use of parametric distributions) may limit their generality to reliably discriminate among behavioural states. To address some of the limitations of existing behavioural state estimation models, we introduce a nonparametric Bayesian framework called the mixed‐membership method for movement (M4), which is available within the open‐source The Bayesian framework estimated breakpoints more accurately than the other segmentation methods for tracks of different lengths. Likewise, the Bayesian framework provided more accurate estimates of behaviour than the other state estimation methods when simulations were generated from less frequently considered distributions (e.g. truncated normal, beta, uniform). Three behavioural states were estimated from snail kite movements, which were labelled as ‘encamped’, ‘area‐restricted search’ and ‘transit’. Changes in these behaviours over time were associated with known dispersal events from the nest site, as well as movements to and from possible breeding locations. Our nonparametric Bayesian framework estimated behavioural states with comparable or superior accuracy compared to the other methods when step lengths and turning angles of simulations were generated from less frequently considered distributions. Since the most appropriate parametric distributions may not be obvious a priori, methods (such as M4) that are agnostic to the underlying distributions can provide powerful alternatives to address questions in movement ecology.
- Award ID(s):
- 2040819
- NSF-PAR ID:
- 10367391
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Methods in Ecology and Evolution
- Volume:
- 13
- Issue:
- 2
- ISSN:
- 2041-210X
- Page Range / eLocation ID:
- p. 432-446
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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