Behavioural ecology at the spatial–social interface

Biological reviews/Biological reviews of the Cambridge Philosophical Society, Journal Year: 2023, Volume and Issue: 98(3), P. 868 - 886

Published: Jan. 23, 2023

ABSTRACT Spatial and social behaviour are fundamental aspects of an animal's biology, their spatial environments indelibly linked through mutual causes shared consequences. We define the ‘spatial–social interface’ as intersection individuals' phenotypes environments. Behavioural variation at spatial–social interface has implications for ecological evolutionary processes including pathogen transmission, population dynamics, evolution systems. link a foundation theory, vocabulary, methods. provide examples future directions integration introduce key concepts approaches that either implicitly or explicitly integrate processes, example, graph density‐dependent habitat selection, niche specialization. Finally, we discuss how movement ecology helps interface. Our review integrates behavioural identifies testable hypotheses

Language: Английский

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Unifying spatial and social network analysis in disease ecology

Journal of Animal Ecology, Journal Year: 2020, Volume and Issue: 90(1), P. 45 - 61

Published: Sept. 28, 2020

Abstract Social network analysis has achieved remarkable popularity in disease ecology, and is sometimes carried out without investigating spatial heterogeneity. Many investigations into sociality may nevertheless be subject to cryptic variation, so ignoring processes can limit inference regarding dynamics. Disease analyses gain breadth, power reliability from incorporating both social behavioural data. However, the tools for collecting analysing these data simultaneously complex unintuitive, it often unclear when variation must accounted for. These difficulties contribute scarcity of simultaneous spatial‐social ecology thus far. Here, we detail scenarios that benefit analysis. We describe procedures collection data, outline statistical approaches control estimate covariance analyses. hope researchers will expand more include components questions. measures increase scope such analyses, allowing accurate model estimates, better transmission modes, susceptibility effects contact scaling patterns, ultimately effective interventions.

Language: Английский

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Animal tracking moves community ecology: Opportunities and challenges

Journal of Animal Ecology, Journal Year: 2022, Volume and Issue: 91(7), P. 1334 - 1344

Published: April 7, 2022

Abstract Individual decisions regarding how, why and when organisms interact with one another their environment scale up to shape patterns processes in communities. Recent evidence has firmly established the prevalence of intraspecific variation nature its relevance community ecology, yet challenges associated collecting data on large numbers individual conspecifics heterospecifics have hampered integration into ecology. Nevertheless, recent technological statistical advances GPS‐tracking, remote sensing behavioural ecology offer a toolbox for integrating processes. More than simply describing where go, movement provide unique information about interactions environmental associations from which true individual‐to‐community framework can be built. By linking paths both data, ecologists now simultaneously quantify interspecific Eltonian (biotic interactions) Grinnellian (environmental conditions) factors underpinning assemblage dynamics, substantial logistical analytical must addressed these approaches realize full potential. Across communities, empirical support conservation applications reveal metacommunity dynamics via tracking‐based dispersal data. As multi‐species tracking are surmounted, we envision future movements ecological signatures will bring resolution many enduring issues

Language: Английский

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A comprehensive framework for handling location error in animal tracking data

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2020, Volume and Issue: unknown

Published: June 14, 2020

Abstract Animal tracking data are being collected more frequently, in greater detail, and on smaller taxa than ever before. These hold the promise to increase relevance of animal movement for understanding ecological processes, but this potential will only be fully realized if their accompanying location error is properly addressed. Historically, coarsely-sampled have proved invaluable large scale processes (e.g., home range, habitat selection, etc.), modern fine-scale unlock far information. While GPS can often ignored coarsely sampled data, require care, tools do not kept pace. Current approaches dealing with largely fall into two categories—either discarding least accurate estimates prior analysis or simultaneously fitting parameters a hidden-state model. In some cases these provide level correction, they known limitations, worse doing nothing. Here, we general framework account triangulated trilatcralizcd which includes GPS, Argos Doppler-shift, VHF, trilatcralized acoustic cellular data. We apply our error-modelselection 190 cellular, devices representing 27 models from 14 manufacturers. Collectively, were used track wide range comprising birds, fish, reptiles, mammals different sizes behaviors, urban, suburban, wild settings. almost half tested device models, error-model selection was necessary obtain best performing model, quarter reported DOP values actually misinformative. Then, using empirical multiple species, an overview modern, error-informed analyses, including continuous-time path reconstruction, home-range distribution, overlap, speed, distance estimation. Adding techniques, introduce new estimators outlier detection autocorrelation visualization. Because error-induced biases depend many factors—sampling schedule, characteristics, device, habitat, etc.—differential bias easily confound biological inference lead researchers draw false conclusions. demonstrate how analyses calibrated that insensitive error, allow use all

Language: Английский

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A guide to sampling design for GPS‐based studies of animal societies

Methods in Ecology and Evolution, Journal Year: 2022, Volume and Issue: 14(8), P. 1887 - 1905

Published: Oct. 11, 2022

Abstract GPS‐based tracking is widely used for studying wild social animals. Much like traditional observational methods, using GPS devices requires making a number of decisions about sampling that can affect the robustness study's conclusions. For example, fewer individuals per group across more distinct groups may not be sufficient to infer group‐ or subgroup‐level behaviours, while limits ability draw conclusions populations. Here, we provide quantitative recommendations when designing studies animal societies. We focus on trade‐offs between three fundamental axes effort: (1) coverage—the and allocation among in one groups; (2) duration—the total amount time over which collect data (3) frequency—the temporal resolution at record data. first test tags under field conditions quantify how these aspects design both accuracy (error absolute positional estimates) precision estimate relative position two individuals), demonstrating error have profound effects inferring distances individuals. then use from whole‐group tracked vulturine guineafowl Acryllium vulturinum demonstrate trade‐off frequency duration impact inferences interactions coverage common measures behaviour groups, identifying types are less robust lower Finally, data‐informed simulations extend insights different sizes cohesiveness. Based our results, able offer range strategies address research questions organizational scales systems—from movement network structure collective decision‐making. Our study provides practical advice empiricists navigate their decision‐making processes highlights importance optimal deployment drawing informative

Language: Английский

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A model for leveraging animal movement to understand spatio‐temporal disease dynamics

Ecology Letters, Journal Year: 2022, Volume and Issue: 25(5), P. 1290 - 1304

Published: March 8, 2022

The ongoing explosion of fine-resolution movement data in animal systems provides a unique opportunity to empirically quantify spatial, temporal and individual variation transmission risk improve our ability forecast disease outbreaks. However, we lack generalizable model that can leverage how it affects pathogen invasion persistence on heterogeneous landscapes. We developed flexible 'Movement-driven modelling spatio-temporal infection risk' (MoveSTIR) leverages diverse derive metrics direct indirect contact by decomposing into constituent processes formation duration deposition acquisition. use MoveSTIR demonstrate ignoring fine-scale movements actual landscapes mis-characterize epidemiological dynamics. unifies previous work networks address applied theoretical questions at the nexus ecology.

Language: Английский

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Deriving spatially explicit direct and indirect interaction networks from animal movement data

Ecology and Evolution, Journal Year: 2023, Volume and Issue: 13(3)

Published: March 1, 2023

Abstract Quantifying spatiotemporally explicit interactions within animal populations facilitates the understanding of social structure and its relationship with ecological processes. Data from tracking technologies (Global Positioning Systems [“GPS”]) can circumvent longstanding challenges in estimation interactions, but discrete nature coarse temporal resolution data mean that ephemeral occur between consecutive GPS locations go undetected. Here, we developed a method to quantify individual spatial patterns interaction using continuous‐time movement models (CTMMs) fit data. We first applied CTMMs infer full trajectories at an arbitrarily fine scale before estimating thus allowing inference occurring observed locations. Our framework then infers indirect interactions—individuals same location, different times—while identification vary context based on CTMM outputs. assessed performance our new simulations illustrated implementation by deriving disease‐relevant networks for two behaviorally differentiated species, wild pigs ( Sus scrofa ) host African Swine Fever mule deer Odocoileus hemionus chronic wasting disease. Simulations showed derived be substantially underestimated when exceeds 30‐min intervals. Empirical application suggested underestimation occurred both rates their distributions. CTMM‐Interaction method, which introduce uncertainties, recovered majority true interactions. leverages advances ecology fine‐scale spatiotemporal individuals lower It leveraged dynamic networks, transmission potential disease systems, consumer–resource information sharing, beyond. The also sets stage future predictive linking environmental drivers.

Language: Английский

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ctmm: Continuous-Time Movement Modeling

Published: July 31, 2015

Language: Английский

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Intrinsic traits, social context, and local environment shape home range size and fidelity of sleepy lizards

Ecological Monographs, Journal Year: 2022, Volume and Issue: 92(3)

Published: March 24, 2022

Abstract Home ranges (HRs), the regions within which animals interact with their environment, constitute a fundamental aspect of ecology. HR sizes and locations commonly reflect costs benefits associated diverse social, biotic, abiotic factors. Less is known, however, about how these factors affect intraspecific variation in size or fidelity (the individual's tendency to maintain same location over time) whether features emerge from consistent differences among individuals sites they occupy. To address this knowledge gap, we used an extensive GPS‐tracking data set long‐lived lizard, sleepy lizard ( Tiliqua rugosa ), included repeated observations multiple across years. We tested three categories predictors—(1) characteristics (sex, aggressiveness, parasitic tick counts), (2) environmental (precipitation, food, refuge quality), (3) social conditions (conspecific overlap number neighbors)—affected fidelity. found that differed consistently annual HRs (with repeatability 0.58 0.33, respectively), all predictors affected both For example, were smaller areas more males had larger than females. In addition, aggressive lizards tended have HRs. Conspecific interacted (social network degree) interactive effect on where whose overlapped neighbors HRs, was particularly strong for neighbors. declined time (HR drifted year year), but rate drift. The fact despite drifting suggests individual traits (e.g., habitat choice criteria differ individuals), rather simple heterogeneity sites. Overall, findings demonstrate (1) strong, long‐term, within‐individual consistency between‐individual space use combined effects traits, conditions, animal implications ecological processes.

Language: Английский

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Deep learning for Amur tiger re-identification in camera traps: A tool assisting population monitoring and spatio-temporal analysis

Ecological Indicators, Journal Year: 2025, Volume and Issue: 171, P. 113227 - 113227

Published: Feb. 1, 2025

Language: Английский

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