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Abstract <bold>Background</bold>Existing software for comparison of species delimitation models do not provide a (true) metric or distance functions between species delimitation models, nor a way to compare these models in terms of relative clustering differences along a lattice of partitions. <bold>Results</bold>is a Python package for analyzing and visualizing species delimitation models in an information theoretic framework that, in addition to classic measures of information such as the entropy and mutual information [1], provides for the calculation of the Variation of Information (VI) criterion [2], a true metric or distance function for species delimitation models that is aligned with the lattice of partitions. <bold>Conclusions</bold>is available under the MIT license from its public repository (https://github.com/jeetsukumaran/piikun), and can be installed locally using the Python package manager ‘pip‘. 

Abstract Climate change has the potential to disrupt species interactions across global ecosystems. Ectotherm–endotherm interactions may be especially prone to this risk due to the possible mismatch between the species in physiological response and performance. However, few studies have examined how changing temperatures might differentially impact species' niches or available suitable habitat when they have very different modes of thermoregulation. An ideal system for studying this interaction is the predator–prey system. In this study, we used ecological niche modeling to characterize the niche overlap and examine biogeography in past and future climate conditions of prairie rattlesnakes (Crotalus viridis) and Ord's kangaroo rats (Dipodomys ordii), an endotherm–ectotherm pair typifying a predator–prey species interaction. Our models show a high niche overlap between these two species (D = 0.863 andI = 0.979) and further affirm similar paleoecological distributions during the last glacial maximum (LGM) and mid‐Holocene (MH). Under future climate change scenarios, we found that prairie rattlesnakes may experience a reduction in overall suitable habitat (RCP 2.6 = −1.82%, 4.5 = −4.62%, 8.5 = −7.34%), whereas Ord's kangaroo rats may experience an increase (RCP 2.6 = 9.8%, 4.5 = 11.71%, 8.5 = 8.37%). We found a shared trend of stable suitable habitat at northern latitudes but reduced suitability in southern portions of the range, and we propose future monitoring and conservation be focused on those areas. Overall, we demonstrate a biogeographic example of how interacting ectotherm–endotherm species may have mismatched responses under climate change scenarios and the models presented here can serve as a starting point for further investigation into the biogeography of these systems. 

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. 

The “multispecies” coalescent (MSC) model that underlies many genomic species-delimitation approaches is problematic because it does not distinguish between genetic structure associated with species versus that of populations within species. Consequently, as both the genomic and spatial resolution of data increases, a proliferation of artifactual species results as within-species population lineages, detected due to restrictions in gene flow, are identified as distinct species. The toll of this extends beyond systematic studies, getting magnified across the many disciplines that rely upon an accurate framework of identified species. Here we present the first of a new class of approaches that addresses this issue by incorporating an extended speciation process for species delimitation. We model the formation of population lineages and their subsequent development into independent species as separate processes and provide for a way to incorporate current understanding of the species boundaries in the system through specification of species identities of a subset of population lineages. As a result, species boundaries and within-species lineages boundaries can be discriminated across the entire system, and species identities can be assigned to the remaining lineages of unknown affinities with quantified probabilities. In addition to the identification of species units in nature, the primary goal of species delimitation, the incorporation of a speciation model also allows us insights into the links between population and species-level processes. By explicitly accounting for restrictions in gene flow not only between, but also within, species, we also address the limits of genetic data for delimiting species. Specifically, while genetic data alone is not sufficient for accurate delimitation, when considered in conjunction with other information we are able to not only learn about species boundaries, but also about the tempo of the speciation process itself.