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Abstract BackgroundKangaroo rats are small mammals that are among the most abundant vertebrates in many terrestrial ecosystems in Western North America and are considered both keystone species and ecosystem engineers, providing numerous linkages between other species as both consumers and resources. However, there are challenges to studying the behavior and activity of these species due to the difficulty of observing large numbers of individuals that are small, secretive, and nocturnal. Our goal was to develop an integrated approach of miniaturized animal-borne accelerometry and radiotelemetry to classify the cryptic behavior and activity cycles of kangaroo rats and test hypotheses of how their behavior is influenced by light cycles, moonlight, and weather. MethodsWe provide a proof-of-concept approach to effectively quantify behavioral patterns of small bodied (< 50 g), nocturnal, and terrestrial free-ranging mammals using large acceleration datasets by combining low-mass, miniaturized animal-borne accelerometers with radiotelemetry and advanced machine learning techniques. We developed a method of attachment and retrieval for deploying accelerometers, a non-disruptive method of gathering observational validation datasets for acceleration data on free-ranging nocturnal small mammals, and used these techniques on Merriam’s kangaroo rats to analyze how behavioral patterns relate to abiotic factors. ResultsWe found that Merriam’s kangaroo rats are only active during the nighttime phases of the diel cycle and are particularly active during later light phases of the night (i.e., late night, morning twilight, and dawn). We found no reduction in activity or foraging associated with moonlight, indicating that kangaroo rats are actually more lunarphilic than lunarphobic. We also found that kangaroo rats increased foraging effort on more humid nights, most likely as a mechanism to avoid cutaneous water loss. ConclusionsSmall mammals are often integral to ecosystem functionality, as many of these species are highly abundant ecosystem engineers driving linkages in energy flow and nutrient transfer across trophic levels. Our work represents the first continuous detailed quantitative description of fine-scale behavioral activity budgets in kangaroo rats, and lays out a general framework for how to use miniaturized biologging devices on small and nocturnal mammals to examine behavioral responses to environmental factors. 

Abstract Background Many snakes are low-energy predators that use crypsis to ambush their prey. Most of these species feed very infrequently, are sensitive to the presence of larger vertebrates, such as humans, and spend large portions of their lifetime hidden. This makes direct observation of feeding behaviour challenging, and previous methodologies developed for documenting predation behaviours of free-ranging snakes have critical limitations. Animal-borne accelerometers have been increasingly used by ecologists to quantify activity and moment-to-moment behaviour of free ranging animals, but their application in snakes has been limited to documenting basic behavioural states (e.g., active vs. non-active). High-frequency accelerometry can provide new insight into the behaviour of this important group of predators, and here we propose a new method to quantify key aspects of the feeding behaviour of three species of viperid snakes ( Crotalus spp.) and assess the transferability of classification models across those species. Results We used open-source software to create species-specific models that classified locomotion, stillness, predatory striking, and prey swallowing with high precision, accuracy, and recall. In addition, we identified a low cost, reliable, non-invasive attachment method for accelerometry devices to be placed anteriorly on snakes, as is likely necessary for accurately classifying distinct behaviours in these species. However, species-specific models had low transferability in our cross-species comparison. Conclusions Overall, our study demonstrates the strong potential for using accelerometry to document critical feeding behaviours in snakes that are difficult to observe directly. Furthermore, we provide an ‘end-to-end’ template for identifying important behaviours involved in the foraging ecology of viperids using high-frequency accelerometry. We highlight a method of attachment of accelerometers, a technique to simulate feeding events in captivity, and a model selection procedure using biologically relevant window sizes in an open-access software for analyzing acceleration data (AcceleRater). Although we were unable to obtain a generalized model across species, if more data are incorporated from snakes across different body sizes and different contexts (i.e., moving through natural habitat), general models could potentially be developed that have higher transferability.