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1. Ecological and behavioral mechanisms of density‐dependent habitat expansion in a recovering African ungulate population

   https://doi.org/10.1002/ecm.1476  

   Becker, Justine A.; Hutchinson, Matthew C.; Potter, Arjun B.; Park, Shinkyu; Guyton, Jennifer A.; Abernathy, Kyler; Americo, Victor F.; da Conceiçāo, Anagledis; Kartzinel, Tyler R.; Kuziel, Luca; et al (August 2021, Ecological Monographs)

   Abstract Major disturbances can temporarily remove factors that otherwise constrain population abundance and distribution. During such windows of relaxed top‐down and/or bottom‐up control, ungulate populations can grow rapidly, eventually leading to resource depletion and density‐dependent expansion into less‐preferred habitats. Although many studies have explored the demographic outcomes and ecological impacts of these processes, fewer have examined the individual‐level mechanisms by which they occur. We investigated these mechanisms in Gorongosa National Park, where the Mozambican Civil War devastated large‐mammal populations between 1977 and 1992. Gorongosa’s recovery has been marked by proliferation of waterbuck (Kobus ellipsiprymnus), an historically marginal 200‐kg antelope species, which is now roughly 20‐fold more abundant than before the war. We show that after years of unrestricted population growth, waterbuck have depleted food availability in their historically preferred floodplain habitat and have increasingly expanded into historically avoided savanna habitat. This expansion was demographically skewed: mixed‐sex groups of prime‐age individuals remained more common in the floodplain, while bachelors, loners, and subadults populated the savanna. By coupling DNA metabarcoding and forage analysis, we show that waterbuck in these two habitats ate radically different diets, which were more digestible and protein‐rich in the floodplain than in savanna; thus, although individuals in both habitats achieved positive net energy balance, energetic performance was higher in the floodplain. Analysis of daily activity patterns from high‐resolution GPS‐telemetry, accelerometry, and animal‐borne video revealed that savanna waterbuck spent less time eating, perhaps to accommodate their tougher, lower‐quality diets. Waterbuck in savanna also had more ectoparasites than those in the floodplain. Thus, plasticity in foraging behavior and diet selection enabled savanna waterbuck to tolerate the costs of density‐dependent spillover, at least in the short term; however, the already poorer energetic performance of these individuals implies that savanna occupancy may become prohibitively costly as heterospecific competitors and predators continue to recover in Gorongosa. Our results suggest that behavior can provide a leading indicator of the onset of density‐dependent limitation and the likelihood of subsequent population decline, but that reliable inference hinges on understanding the mechanistic basis of observed behavioral shifts. 

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2. Hidden Markov models identify major movement modes in accelerometer and magnetometer data from four albatross species

   https://doi.org/10.1186/s40462-021-00243-z  

   Conners, Melinda G.; Michelot, Théo; Heywood, Eleanor I.; Orben, Rachael A.; Phillips, Richard A.; Vyssotski, Alexei L.; Shaffer, Scott A.; Thorne, Lesley H. (December 2021, Movement Ecology)

   Abstract Background Inertial measurement units (IMUs) with high-resolution sensors such as accelerometers are now used extensively to study fine-scale behavior in a wide range of marine and terrestrial animals. Robust and practical methods are required for the computationally-demanding analysis of the resulting large datasets, particularly for automating classification routines that construct behavioral time series and time-activity budgets. Magnetometers are used increasingly to study behavior, but it is not clear how these sensors contribute to the accuracy of behavioral classification methods. Development of effective  classification methodology is key to understanding energetic and life-history implications of foraging and other behaviors. Methods We deployed accelerometers and magnetometers on four species of free-ranging albatrosses and evaluated the ability of unsupervised hidden Markov models (HMMs) to identify three major modalities in their behavior: ‘flapping flight’, ‘soaring flight’, and ‘on-water’. The relative contribution of each sensor to classification accuracy was measured by comparing HMM-inferred states with expert classifications identified from stereotypic patterns observed in sensor data. Results HMMs provided a flexible and easily interpretable means of classifying behavior from sensor data. Model accuracy was high overall (92%), but varied across behavioral states (87.6, 93.1 and 91.7% for ‘flapping flight’, ‘soaring flight’ and ‘on-water’, respectively). Models built on accelerometer data alone were as accurate as those that also included magnetometer data; however, the latter were useful for investigating slow and periodic behaviors such as dynamic soaring at a fine scale. Conclusions The use of IMUs in behavioral studies produces large data sets, necessitating the development of computationally-efficient methods to automate behavioral classification in order to synthesize and interpret underlying patterns. HMMs provide an accessible and robust framework for analyzing complex IMU datasets and comparing behavioral variation among taxa across habitats, time and space. 

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3. Livestock Informatics Toolkit: A Case Study in Visually Characterizing Complex Behavioral Patterns across Multiple Sensor Platforms, Using Novel Unsupervised Machine Learning and Information Theoretic Approaches

   https://doi.org/10.3390/s22010001  

   McVey, Catherine; Hsieh, Fushing; Manriquez, Diego; Pinedo, Pablo; Horback, Kristina (January 2022, Sensors)

   Large and densely sampled sensor datasets can contain a range of complex stochastic structures that are difficult to accommodate in conventional linear models. This can confound attempts to build a more complete picture of an animal’s behavior by aggregating information across multiple asynchronous sensor platforms. The Livestock Informatics Toolkit (LIT) has been developed in R to better facilitate knowledge discovery of complex behavioral patterns across Precision Livestock Farming (PLF) data streams using novel unsupervised machine learning and information theoretic approaches. The utility of this analytical pipeline is demonstrated using data from a 6-month feed trial conducted on a closed herd of 185 mix-parity organic dairy cows. Insights into the tradeoffs between behaviors in time budgets acquired from ear tag accelerometer records were improved by augmenting conventional hierarchical clustering techniques with a novel simulation-based approach designed to mimic the complex error structures of sensor data. These simulations were then repurposed to compress the information in this data stream into robust empirically-determined encodings using a novel pruning algorithm. Nonparametric and semiparametric tests using mutual and pointwise information subsequently revealed complex nonlinear associations between encodings of overall time budgets and the order that cows entered the parlor to be milked. 

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4. Ecology and social biology of the southern three-banded armadillo ( Tolypeutes matacus ; Cingulata: Chlamyphoridae)

   https://doi.org/10.1093/jmammal/gyaa117  

   Attias, N; Gurarie, E; Fagan, W F; Mourão, G (October 2020, Journal of Mammalogy)

   Vieira, Marcus (Ed.)

   Abstract Basic knowledge of species biology and ecology is essential for the assessment of species conservation status and planning for efficient conservation strategies; however, this information is not always readily available. Here we use movement behavior to understand the ecology and social biology of the poorly known southern three-banded armadillo (Tolypeutes matacus). We used VHF and GPS telemetry to monitor 26 individuals from two sites in the Pantanal wetlands of Brazil. We characterized armadillo activity patterns, evaluated the relationship between sex and body mass with home range size and mean daily distance traveled, and examined home and core range overlap. Three-banded armadillos were active on average for 5.5 ± 2.8 h/day, with most of their activity concentrated in the first half of the night. Adult males were heavier and had larger home ranges than adult females. Home range size scaled positively with body mass for males, but not for females. Core ranges for females overlapped little (< 1%) regardless of age, but home ranges for males overlapped both with other males (12%) and females (18%). Our data suggest that three-banded armadillos are mainly a nocturnal species. Home range and spacing patterns point to a generally asocial behavior and a polygynous or promiscuous mating system. We hope that the data generated as a result of this project will contribute to this species’ conservation in Brazil and elsewhere by guiding future management and research efforts. 

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5. Deer Vigilance and Movement Behavior Are Affected by Edge Density and Connectivity

   https://doi.org/10.1111/eth.13574  

   Bartel, Savannah_L; Hakkila, Leotie; Orrock, John_L (May 2025, Ethology)

   ABSTRACT Animal behavior is an important component of individual, population, and community responses to anthropogenic habitat alteration. For example, antipredator behavior (e.g., vigilance) and animal movement behavior may both be important behavioral responses to the increased density of habitat edges and changes in patch connectivity that characterize highly modified habitats. Importantly, edge density and connectivity might interact, and this interaction is likely to mediate animal behavior: linear, edge‐rich landscape features often provide structural connectivity between patches, but the functional connectedness of patches for animal use could depend upon how edge density modifies animal vigilance and movement. Using remote cameras in large‐scale experimental landscapes that manipulate edge density (high‐ vs. low‐density edges) and patch connectivity (isolated or connected patches), we examined the effects of edge density and connectivity on the antipredator behavior and movement behavior of white‐tailed deer (Odocoileus virginianus). Deer vigilance was 1.38 times greater near high‐density edges compared to low‐density edges, regardless of whether patches were connected or isolated. Deer were also more likely to move parallel to connected high‐density edges than all other edge types, suggesting that connectivity promotes movement along high‐density edges. These results suggest that increases in edge density that accompany human fragmentation of existing habitats may give rise to large‐scale changes in the antipredator behavior of deer. These results also suggest that conservation strategies that simultaneously manipulate edge density and connectivity (i.e., habitat corridors) may have multiple effects on different aspects of deer behavior: linear habitat corridors were areas of high vigilance, but also areas where deer movement behavior implied increased movement along the habitat edge. 

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