Genomics: moving behavioural ecology beyond the phenotypic gambit

Rittschof, Clare C.; Robinson, Gene E.

doi:10.1016/j.anbehav.2014.02.028

Cited by 56 publications

(44 citation statements)

References 108 publications

(140 reference statements)

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Section: Discussionmentioning

confidence: 99%

“…Rather, an integrative approach encompassing genetic, behavioural and environmental data is required. Efforts to integrate different types of data sets are now emerging (Rittschof & Robinson 2014;Selkoe et al 2016). Further methodological development for integrating data in a way that is ecological meaningful and the continued forging of collaborations between researchers provide promising avenues for enhancing our understanding of the evolutionary and ecological mechanisms underlying genetic population structure and will also provide information essential for conservation and management.…”

Section: Implications For Management At Multiple Scalesmentioning

confidence: 99%

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Multiple processes drive genetic structure of humpback whale (Megaptera novaeangliae) populations across spatial scales

et al. 2017

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Elucidating patterns of population structure for species with complex life histories, and disentangling the processes driving such patterns, remains a significant analytical challenge. Humpback whale (Megaptera novaeangliae) populations display complex genetic structures that have not been fully resolved at all spatial scales. We generated a data set of nuclear markers for 3575 samples spanning the seven breeding stocks and substocks found in the South Atlantic and western and northern Indian Oceans. For the total sample, and males and females separately, we assessed genetic diversity, tested for genetic differentiation between putative populations and isolation by distance, estimated the number of genetic clusters without a priori population information and estimated rates of gene flow using maximum-likelihood and Bayesian approaches. At the ocean basin scale, structure is governed by geographical distance (IBD P < 0.05) and female fidelity to breeding areas, in line with current understanding of the drivers of broadscale population structure. Consistent with previous studies, the Arabian Sea breeding stock was highly genetically differentiated (F 0.034-0.161; P < 0.01 for all comparisons). However, the breeding stock boundary between west South Africa and east Africa was more porous than expected based on genetic differentiation, cluster and geneflow analyses. Instances of male fidelity to breeding areas and relatively high rates of dispersal for females were also observed between the three substocks in the western Indian Ocean. The relationships between demographic units and current management boundaries may have ramifications for assessments of the status and continued protections of populations still in recovery from commercial whaling.

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Section: Discussionmentioning

confidence: 99%

Section: Implications For Management At Multiple Scalesmentioning

confidence: 99%

Multiple processes drive genetic structure of humpback whale (Megaptera novaeangliae) populations across spatial scales

et al. 2017

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“…As such, their approach requires the measurement of fitness-related traits, including fertility. Although many human behavioral ecologists recognize the potential for an evolutionary mismatch, central to the behavioral ecological approach is the application of the phenotypic gambit and, more recently, the behavioral gambit (Borgerhoff Mulder and Schacht 2012; Fawcett et al 2013; Grafen 1984; Rittschof and Robinson 2014): the assumption that there are no (or very few) constraints (genetic or otherwise) on humans’ ability to arrive at a fitness-maximizing solution. That is, humans are argued to be sufficiently plastic to track environmental changes in fitness-enhancing ways (Borgerhoff Mulder and Schacht 2012), especially given that we have engineered those environments for ourselves via a process of niche construction (Laland and Brown 2006).…”

Section: On Why We Should Study Fertility Within Industrial Societiesmentioning

confidence: 99%

The Reproductive Ecology of Industrial Societies, Part I

Stulp

Sear

Barrett

2016

Hum Nat

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Is fertility relevant to evolutionary analyses conducted in modern industrial societies? This question has been the subject of a highly contentious debate, beginning in the late 1980s and continuing to this day. Researchers in both evolutionary and social sciences have argued that the measurement of fitness-related traits (e.g., fertility) offers little insight into evolutionary processes, on the grounds that modern industrial environments differ so greatly from those of our ancestral past that our behavior can no longer be expected to be adaptive. In contrast, we argue that fertility measurements in industrial society are essential for a complete evolutionary analysis: in particular, such data can provide evidence for any putative adaptive mismatch between ancestral environments and those of the present day, and they can provide insight into the selection pressures currently operating on contemporary populations. Having made this positive case, we then go on to discuss some challenges of fertility-related analyses among industrialized populations, particularly those that involve large-scale databases. These include “researcher degrees of freedom” (i.e., the choices made about which variables to analyze and how) and the different biases that may exist in such data. Despite these concerns, large datasets from multiple populations represent an excellent opportunity to test evolutionary hypotheses in great detail, enriching the evolutionary understanding of human behavior.

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“…The identification of co-variance patterns within and between axes representing mechanisms and those representing functional significance will likely reveal robust and representative measures of causal mechanisms associated with behavioral variation. Unfortunately, few if any such empirical studies have been conducted, despite that fact that we now have the analytical means to do so [86].…”

Section: Internal Attributes: Life-history Traitsmentioning

confidence: 99%

An evolutionary framework for studying mechanisms of social behavior

Hofmann

Beery

Blumstein³

et al. 2014

Trends in Ecology & Evolution

172

133

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Social interactions are central to most animals and have a fundamental impact upon the phenotype of an individual. Social behavior (social interactions among conspecifics) represents a central challenge to the integration of the functional and mechanistic bases of complex behavior. Traditionally, studies of proximate and ultimate elements of social behavior have been conducted by distinct groups of researchers, with little communication across perceived disciplinary boundaries. However, recent technological advances, coupled with increased recognition of the substantial variation in mechanisms underlying social interactions, should compel investigators from divergent disciplines to pursue more integrative analyses of social behavior. We propose an integrative conceptual framework intended to guide researchers towards a comprehensive understanding of the evolution and maintenance of mechanisms governing variation in sociality.The study of social behavior in the 21st century All animals interact with conspecifics at some point in their lives. Members of the same species tend to be each other's fiercest competitors and strongest allies, as evidenced by the intense cooperation and conflict that characterize many intraspecific interactions [1]. These interactions are the products of genetic, epigenetic, endocrine, and neural mechanisms that -in conjunction with environmental conditions -affect Darwinian fitness and evolve via natural selection. Building upon Aristotle's four questions, Tinbergen [2] posited that understanding behavior requires the integration of studies of mechanism and function. Only by asking questions both from a proximate perspective (i.e., focusing on causation and development) and an ultimate perspective (i.e., focusing on adaptive value and evolutionary descent) can behavior be fully understood. Social behavior in particular lends itself to such an integrative approach not only because it commands the attention of many disciplines [3] but also because even many behaviors commonly considered nonsocial often occur in a social context (e.g., mating, fighting, parental care). Social behavior is also special because the selective agents are other members of the same species, and this results in intriguing evolutionary dynamics. Nevertheless, in the intervening decades since Tinbergen's

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Genomics: moving behavioural ecology beyond the phenotypic gambit

Cited by 56 publications

References 108 publications

Multiple processes drive genetic structure of humpback whale (Megaptera novaeangliae) populations across spatial scales

Multiple processes drive genetic structure of humpback whale (Megaptera novaeangliae) populations across spatial scales

The Reproductive Ecology of Industrial Societies, Part I

An evolutionary framework for studying mechanisms of social behavior

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