Change-point models for identifying behavioral transitions in wild animals

K.P. Gundermann; Duane R. Diefenbach; W. David Walter; A Corondi; J.E. Banfield; B.D. Wallingford; D.P. Stainbrook; C.S. Rosenberry; F.E. Buderman

doi:10.1186/s40462-023-00430-0

USGS · 70256488

Change-point models for identifying behavioral transitions in wild animals

K.P. Gundermann·Duane R. Diefenbach·W. David Walter·A Corondi·J.E. Banfield·B.D. Wallingford·D.P. Stainbrook·C.S. Rosenberry·F.E. Buderman

View original source ↗Export metadata ↓

Abstract

Animal behavior can be difficult, time-consuming, and costly to observe in the field directly. Innovative modeling methods, such as hidden Markov models (HMMs), allow researchers to infer unobserved animal behaviors from movement data, and implementations often assume that transitions between states occur multiple times. However, some behavioral shifts of interest, such as parturition, migration initiation, and juvenile dispersal, may only occur once during an observation period, and HMMs may not be the best approach to identify these changes. We present two change-point models for identifying single transitions in movement behavior: a location-based change-point model and a movement metric-based change-point model. We first conducted a simulation study to determine the ability of these models to detect a behavioral transition given different amounts of data and the degree of behavioral shifts. We then applied our models to two ungulate species in central Pennsylvania that were fitted with global positioning system collars and vaginal implant transmitters to test hypotheses related to parturition behavior. We fit these models in a Bayesian framework and directly compared the ability of each model to describe the parturition behavior across species. Our simulation study demonstrated that successful change point estimation using either model was possible given at least 12 h of post-change observations and 15 min fix interval. However, our models received mixed support among deer and elk in Pennsylvania due to behavioral variation between species and among individuals. Our results demonstrate that when the behavior follows the dynamics proposed by the two models, researchers can identify the timing of a behavioral change. Although we refer to detecting parturition events, our results can be applied to any behavior that results in a single change in time.

Explore related subjects

Movement Ecology Article

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

K.P. Gundermann, Duane R. Diefenbach, W. David Walter, A Corondi, J.E. Banfield, B.D. Wallingford, D.P. Stainbrook, C.S. Rosenberry, F.E. Buderman. 2023-10-20. Change-point models for identifying behavioral transitions in wild animals. https://doi.org/10.1186/s40462-023-00430-0

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

USGS2025

Linking bathythermal habitat selection to management of a migratory freshwater fish

Background For migratory fishes, habitat selection in dimensions of temperature and depth may be jointly used to define the bathythermal niche. Seasonal and long-term changes in the availability of bathythermal habitat can cause behavioral responses that have consequences for managing interjurisdictional fisheries that target migratory fishes. Management of such fisheries typically relies on standardized surveys to provide knowledge of stock status, yet changes in fish behavior may complicate interpretation of survey results. For example, changes in bathythermal habitat selection could uncouple fish availability from surveys designed to intercept migrating fish in predefined bathythermal habitats. Methods We applied electronic tagging methods to Lake Erie walleye ( Sander vitreus ) to address spatial management and stock assessment questions regarding bathythermal habitat. Specifically, we sought to determine if bathythermal habitat use varied in relation to body size, season, and time of day, with a particular focus on how these may influence availability to fisheries-independent surveys conducted during September-November. Results As predicted, bathythermal habitat distribution fluctuated substantially throughout the year, was most limited during spawning months, and most expansive during fall migration. During the summer stratified months, walleye primarily selected epilimnetic habitats, despite the prevailing notion that colder hypolimnetic waters would be preferred during this time. Conclusions While our results did not support a previous hypothesis that smaller fish were more available to assessment survey gears, our results did support previous assertions that walleye were more active and available to suspended gill nets during late crepuscular periods in fall. Considering uncertainties in water quality and long-term warming trends, our case study could improve decisions regarding spatial management of this species in the context of independent water quality management objectives.

Detroit River, Lake Erie, Lake St. Clair↗

USGS2025

Lake sturgeon behavioral diversity in the Laurentian Great Lakes: Migratory patterns across populations and habitats

Background Characterizing the diversity of migration behaviors from the individual to the population level is essential for understanding how organisms respond to environmental variation and how these responses affect survival and habitat use. Lake sturgeon ( Acipenser fulvescens ) is a species of special concern in the Laurentian Great Lakes that are long-lived and generally classified as intermittent, adfluvial spawners. Observations of lake sturgeon movements at ecologically relevant spatiotemporal scales have shown that migration behavior often varies among individuals within the same population. However, studies on individual populations, particularly when focused only on a part of the life cycle (e.g., often spawning), provide just a partial understanding of the species’ full migratory scope and processes underlying expression of different migratory behaviors. To better understand lake sturgeon migratory diversity, we characterized and compared migratory behaviors of six lake sturgeon populations occupying environments that varied in habitat availability and connectivity in different Laurentian Great Lakes. Methods Sequence analysis combined with agglomerative hierarchical clustering and visual inspection of daily location data were used to identify distinct lake sturgeon migratory behaviors present in each population. Results Seven distinct migratory behaviors were identified based on differential patterns of lake and river use that encompass spawning and other seasonal periods. Behaviors were categorized as annual spring river, intermittent spring river, intermittent two-step, annual summer river, annual winter river, and annual interlake migrants along with river residents. The presence and frequency of migratory behaviors varied substantially among populations. Conclusions Our study demonstrated that migratory diversity is a general feature of lake sturgeon life history that may be partially shaped by habitat availability and connectivity. Given these results, we propose a conceptual model that links habitat availability and connectivity to migratory diversity and predict a positive association between them. This updated framework provides a cohesive basis for understanding lake sturgeon migratory behavior across variable ecological contexts in the Laurentian Great Lakes and will help promote future research to refute or refine the model.

Laurentian Great Lakes↗

USGS2025

Identifying presence or absence of grizzly and polar bear cubs from the movements of adult females with machine learning

Background Information on reproductive success is crucial to understanding population dynamics but can be difficult to obtain, particularly for species that birth while denning. For grizzly ( Ursus arctos ) and polar bears ( U. maritimus ), den visits are impractical because of safety and logistical considerations. Reproduction is typically documented through direct observation, which can be difficult, costly, and often occurs long after den departure. Reproduction could be documented remotely, however, from post-denning movement data if discernable differences exist between females with and without cubs. Methods We trained support vector machines (SVMs) with eight variables derived from telemetry data of female grizzly (2000–2022) and polar bears (1985–2016) with or without cubs during seven periods with lengths ranging from 5 to 60 days starting at den departure. We assessed SVM classification accuracy by withholding two samples (one cub-present, one cub-absent), training SVMs with the remaining data, predicting classification of the withheld samples, and repeating this process for each sample combination. Additionally, we evaluated how classification accuracy for grizzly bears was influenced by sample size, length of the post-departure period, and frequency of standardized location estimates. Results Accuracy of predicting cub presence or absence was 87% for grizzly bears with only 5 days of post-departure data and increased to a maximum of 92% with 20 days of data. For polar bears, accuracy was 86% at 5 days post-departure and increased to a maximum of 93% at 50 days. Classification accuracy for grizzly bears increased from 76 to 90% when sample size increased from 10 to 30 bears while holding period length constant (30 days) but did not increase at larger sample sizes. When sample size was held constant, increasing the length of the post-departure period did not affect classification accuracy markedly. Conclusion Presence or absence of grizzly and polar bear cubs can be identified with high accuracy even when SVM models are trained with limited data. Detecting cub presence or absence remotely could improve estimates of reproductive success and litter survival, enhancing our understanding of factors affecting cub recruitment.

Alaska, Idaho, Montana, Wyoming↗