Social Barriers in Ecological Landscapes: The Social Resistance Hypothesis

Armansin, Nicolette C.; Stow, Adam J.; Cantor, Maurício; Leu, Stephan T.; Klarevas‐Irby, James A.; Chariton, Anthony A.; Farine, Damien R.

doi:10.1016/j.tree.2019.10.001

Cited by 61 publications

(66 citation statements)

References 89 publications

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“…The population occurs along two adjoining creeks, currently totalling ~ 4 km of approximately linear flood plain forest. Our genetic data show some minor population genetic substructure along each creek, likely to reflect resistance to dispersal caused by territorial aggression, as commonly observed in territorial mammals ( Figure S4; Armansin et al, 2020).…”

Section: The Influence Of Population Genetic Substructure On Estimasupporting

confidence: 60%

Accounting for cryptic population substructure enhances detection of inbreeding depression with genomic inbreeding coefficients: an example from a critically endangered marsupial

et al. 2020

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Characterizing inbreeding depression in wildlife populations can be critical to their conservation. Coefficients of individual inbreeding can be estimated from genome‐wide marker data. The degree to which sensitivity of inbreeding coefficients to population genetic substructure alters estimates of inbreeding depression in wild populations is not well understood. Using generalized linear models, we tested the power of two frequently used inbreeding coefficients that are calculated from genome‐wide SNP markers, FH and F^III, to predict four fitness traits estimated over two decades in an isolated population of the critically endangered Leadbeater's possum. FH estimates inbreeding as excess observed homozygotes relative to equilibrium expectations, whereas F^III quantifies allelic similarity between the gametes that formed an individual, and upweights rare homozygotes. We estimated FH and F^III from 1,575 genome‐wide SNP loci in individuals with fitness trait data (N = 179–237 per trait), and computed revised coefficients, FHby group and F^IIIby group, adjusted for population genetic substructure by calculating them separately within two different genetic groups of individuals identified in the population. Using FH or F^III in the models, inbreeding depression was detected for survival to sexual maturity, longevity and whether individuals bred during their lifetime. F^IIIby group (but not FHby group) additionally revealed significant inbreeding depression for lifetime reproductive output (total offspring assigned to each individual). Estimates of numbers of lethal equivalents indicated substantial inbreeding load, but differing between inbreeding estimators. Inbreeding depression, declining population size, and low and declining genetic diversity suggest that genetic rescue may assist in preventing extinction of this unique Leadbeater's possum population.

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Section: The Influence Of Population Genetic Substructure On Estimasupporting

confidence: 60%

Accounting for cryptic population substructure enhances detection of inbreeding depression with genomic inbreeding coefficients: an example from a critically endangered marsupial

et al. 2020

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“…the social landscape) in shaping the movement and prospecting behaviours of dispersers (e.g. Armansin et al 2020) which can, in turn, alter patch-level social structure through settlement.…”

Section: Dispersal Behaviourmentioning

confidence: 99%

The importance of individual-to-society feedbacks in animal ecology and evolution

Cantor

Chaparro²,

Beck

et al. 2019

Preprint

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1.The social decisions that individuals make, in terms of where to move, who to interact with and how frequently, scale up to generate social structure. Such structure has profound consequences: individuals each have a unique social environment, social interactions can amplify or dampen individual differences at the population level, and population-level ecological and evolutionary processes can be governed by higher-level ‘emergent properties’ of animal societies.2.Here we review how explicitly accounting for social structure in animal populations has generated new hypotheses and has revised existing predictions in ecology and evolution. That is, we synthesize the insights gained by applying ‘network-thinking’ rather than the utility of applying social network analysis as a methodological tool. 3.We start with what has been learned about the generative mechanisms that underpin social structure. We then outline the major implications that social structure has been found to have on population processes, on how selection operates and organisms can evolve, and on co-evolutionary dynamics between social structure and population processes. Finally, we highlight areas for which there is clear evidence that accounting for social structure will refine current thinking, but where examples remain scarce.4.Applying ‘network thinking’ in biology presents not only new challenges, but also many opportunities to advance different areas of research. Addressing the question of how social structure changes the biological relationships linking individuals to populations, and populations to processes, is revealing commonalities across scientific disciplines. In doing so, animal social networks can bridge otherwise disparate research topics and, in the future, we hope will allow for more unified theories in biology.

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“…However, sociality and behaviour can also shape space use, and space use and habitat quality together can impact demography (Alberts, 2019; Thompson, 2019). Research focusing on the relationship between spatial organization, sociality, and the abiotic and biotic environment has fed a central debate in ecology, and recent work highlights that spatial and social organization cannot be ignored when considering population dynamics or individual fitness (Armansin et al., 2019; He, Maldonado‐Chaparro, & Farine, 2019; Paniw, Maag, Cozzi, Clutton‐Brock, & Ozgul, 2019). For example, Yellowstone wolves infected with sarcoptic mange have substantially higher survival when they are associated with larger packs and there are higher prey densities (Almberg et al., 2015); however, access to prey and hunting success is influenced by territory location and topography (Kauffman et al., 2007; Nelson et al., 2012).…”

Section: Introductionmentioning

confidence: 99%

Group density, disease, and season shape territory size and overlap of social carnivores

Brandell

Fountain-Jones

Gilbertson

et al. 2020

Journal of Animal Ecology

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1. The spatial organization of a population can influence the spread of information, behaviour and pathogens. Group territory size and territory overlap and components of spatial organization, provide key information as these metrics may be indicators of habitat quality, resource dispersion, contact rates and environmental risk (e.g. indirectly transmitted pathogens). Furthermore, sociality and behaviour can also shape space use, and subsequently, how space use and habitat quality together impact demography.

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Social Barriers in Ecological Landscapes: The Social Resistance Hypothesis

Cited by 61 publications

References 89 publications

Accounting for cryptic population substructure enhances detection of inbreeding depression with genomic inbreeding coefficients: an example from a critically endangered marsupial

Accounting for cryptic population substructure enhances detection of inbreeding depression with genomic inbreeding coefficients: an example from a critically endangered marsupial

The importance of individual-to-society feedbacks in animal ecology and evolution

Group density, disease, and season shape territory size and overlap of social carnivores

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