The role of habitat configuration in shaping social structure: a gap in studies of animal social complexity

Behavioral Ecology and Sociobiology, Journal Year: 2019, Volume and Issue: 73(1)

Published: Jan. 1, 2019

Animal societies are shaped both by social processes and the physical environment in which interactions take place. While many studies observed patterns of inter-individual as products proxies pure processes, or links between resource availability structure, role configuration habitat features shaping system group-living animals remains largely overlooked. We hypothesise that decisions about when where to move, will impact individuals more frequently encounter one another doing so overall structure organization populations. first discuss how spatial arrangement components (i.e. configuration) can shape animal movements using empirical cases literature. Then, we draw from literature movement mediate highlight network-based approaches identifying, evaluating partitioning effects on organization. illustrate combination these mechanisms a simple simulation. Finally, implications ecology evolution offer framework for future studies. directions increasingly important widely human-modified landscapes, particular habitat-driven evolution. There is now clear evidence generate apparent complex structure. However, while such those collective behaviour networks have been focused involving individual decision-making, broader also be factors fundamental impacts animals. One set related amount biotic abiotic live. Examples include formed patches connected through corridors, presence hard boundaries types uneven distribution resources, mates competitors across space. In this contribution, potential these, becoming start being able track populations spanning larger landscapes.

Language: Английский

---

Consistent Individual Behavioral Variation: What Do We Know and Where Are We Going?

Annual Review of Ecology Evolution and Systematics, Journal Year: 2022, Volume and Issue: 53(1), P. 161 - 182

Published: Aug. 8, 2022

The study of individual behavioral variation, sometimes called animal personalities or types, is now a well-established area research in ecology and evolution. Considerable theoretical work has developed predictions about its ecological evolutionary causes consequences, studies testing these theories continue to grow. Here, we synthesize the current empirical shed light on which are well supported need further refinement. We find that major frameworks explaining existence pace-of-life syndrome hypothesis state-dependent feedbacks models, have mixed support. consequences variation studied at level but less known higher levels such as among species communities. focus this review reevaluate reestablish foundation research: What do know? questions remain? And where going next?

Language: Английский

---

Going through the motions: incorporating movement analyses into disease research

Ecology Letters, Journal Year: 2018, Volume and Issue: 21(4), P. 588 - 604

Published: Feb. 14, 2018

Abstract Though epidemiology dates back to the 1700s, most mathematical representations of epidemics still use transmission rates averaged at population scale, especially for wildlife diseases. In simplifying contact process, we ignore heterogeneities in host movements that complicate real world, and overlook their impact on spatiotemporal patterns disease burden. Movement ecology offers a set tools help unpack letting researchers more accurately model how animals within interact spread pathogens. Analytical techniques from this growing field can also expose reverse process: infection impacts movement behaviours, therefore other ecological processes like feeding, reproduction, dispersal. Here, synthesise contributions research, with particular focus studies have successfully used movement‐based methods quantify individual heterogeneity exposure risk. Throughout, highlight rapid growth both comment promising but unexplored avenues research overlap. Ultimately, suggest, including empowers ecologists pose new questions, expanding our understanding host–pathogen dynamics improving predictive capacity even human

Language: Английский

---

Animal personality and behavioral syndromes in amphibians: a review of the evidence, experimental approaches, and implications for conservation

Behavioral Ecology and Sociobiology, Journal Year: 2018, Volume and Issue: 72(5)

Published: May 1, 2018

Language: Английский

---

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

---

Observing the unwatchable: Integrating automated sensing, naturalistic observations and animal social network analysis in the age of big data

Journal of Animal Ecology, Journal Year: 2020, Volume and Issue: 90(1), P. 62 - 75

Published: Oct. 6, 2020

In the 4.5 decades since Altmann (1974) published her seminal paper on methods for observational study of behaviour, automated detection and analysis social interaction networks have fundamentally transformed ways that ecologists behaviour. Methodological developments collecting data remotely behaviour involve indirect inference associations, direct recordings interactions machine vision. These recent technological advances are improving scale resolution with which we can dissect among animals. They also revealing new intricacies animal at spatial temporal resolutions as well in ecological contexts been hidden from humans, making unwatchable seeable. We first outline how these applications permitting researchers to collect exquisitely detailed information little observer bias. further recognize emerging challenges reality-mining approaches. While automating collection its moving an unprecedented rate, urge thoughtfully combine tools classic behavioural monitoring place our understanding within fundamental biological contexts.

Language: Английский

---

Defining an epidemiological landscape that connects movement ecology to pathogen transmission and pace‐of‐life

Ecology Letters, Journal Year: 2022, Volume and Issue: 25(8), P. 1760 - 1782

Published: July 5, 2022

Pathogen transmission depends on host density, mobility and contact. These components emerge from pathogen movements that themselves arise through interactions with the surrounding environment. The environment, emergent movements, subsequent patterns of contact form an 'epidemiological landscape' connecting environment to specific locations where transmissions occur. Conventionally, epidemiological landscape has been described in terms geographical coordinates hosts or pathogens are located. We advocate for alternative approach relates those attributes local Environmental descriptions can strengthen forecasts by allowing predictions even when data not available. more accessible than ever thanks new tools movement ecology, we introduce a 'movement-pathogen pace life' heuristic help identify aspects have most influence spatial epidemiology. By linking directly offers efficient path using environmental information inform models describing will

Language: Английский

---

A review of the role of parasites in the ecology of reptiles and amphibians

Austral Ecology, Journal Year: 2018, Volume and Issue: 44(3), P. 433 - 448

Published: Dec. 20, 2018

Abstract A great diversity of parasites, from viruses and bacteria to a range remarkable eukaryotic organisms, exploit reptile amphibian hosts. Recent increases in the emergence infectious disease have revealed importance understanding effects interactions between hosts their parasites. Here we review parasite infection on demographic, behavioural, genomic physiological factors species. Reviewing these roles collectively, prioritising areas for research, advances our ecological guides direction conservation time rapid species decline. Poorly resolved systems include Gymnophionan amphibians Crocodilian hosts, addition viral bacterial Future research should seek understand processes enabling population recovery examining synergistic parasites with fragmentation, climate change other that threaten persistence.

Language: Английский

---

You’re Just My Type: Mate Choice and Behavioral Types

Trends in Ecology & Evolution, Journal Year: 2020, Volume and Issue: 35(9), P. 823 - 833

Published: May 22, 2020

Language: Английский

---

A guide to choosing and implementing reference models for social network analysis

Biological reviews/Biological reviews of the Cambridge Philosophical Society, Journal Year: 2021, Volume and Issue: 96(6), P. 2716 - 2734

Published: July 3, 2021

ABSTRACT Analysing social networks is challenging. Key features of relational data require the use non‐standard statistical methods such as developing system‐specific null, or reference, models that randomize one more components observed data. Here we review a variety randomization procedures generate reference for network analysis. Reference provide an expectation hypothesis testing when analysing We outline key stages in producing effective model and detail four approaches generating distributions: permutation, resampling, sampling from distribution, generative models. highlight each type approach would be appropriate note potential pitfalls researchers to avoid. Throughout, illustrate our points with examples simulated system. Our aim deeper understanding analytical enhance their confidence tailoring specific research questions.

Language: Английский

---