Dataset Information

Resilience to climate variation in a spatially structured amphibian population.

ABSTRACT: Understanding the impact of weather fluctuations on demographic parameters is of crucial interest to biodiversity research in a context of global climate change. Amphibians are valuable candidates for investigating this topic due to their strong physiological dependence on water availability and temperature. In this study, we took advantage of data from a long-term capture-mark-recapture (CMR) monitoring program of a great crested newt (Triturus cristatus) population inhabiting a 12-pond archipelago in southeastern France. We investigated the interactions between vital rates (survival and recruitment), the internal structure of the population, and climatic variables both at a local and a regional (North Atlantic Oscillation: NAO) scale. Overall, we found a weak relationship between climatic variables and the survival of large-bodied newts. The only strong relationship was found to be a high NAO index during the post-breeding period, suggesting that dry, hot summers negatively impact survival. In terms of recruitment, the results indicated that hot weather during the activity period had delayed deleterious effects on adult recruitment two years later, suggesting high larval and juvenile mortality due to unsuitable growing conditions. Recruitment was also impacted by a high NAO index during the overwintering period preceding recruitment, suggesting that mild weather increases the mortality of juveniles, probably by enhancing the depletion of energy reserves without any possibility of refueling.

SUBMITTER: Weinbach A

PROVIDER: S-EPMC6168496 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Resilience to climate variation in a spatially structured amphibian population.

Weinbach A A Cayuela H H Grolet O O Besnard A A Joly P P

Scientific reports 20181002 1

Understanding the impact of weather fluctuations on demographic parameters is of crucial interest to biodiversity research in a context of global climate change. Amphibians are valuable candidates for investigating this topic due to their strong physiological dependence on water availability and temperature. In this study, we took advantage of data from a long-term capture-mark-recapture (CMR) monitoring program of a great crested newt (Triturus cristatus) population inhabiting a 12-pond archipe ...[more]

PMID: 30279562

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Project description:Increasingly imperative objectives in ecology are to understand and forecast population dynamic and evolutionary responses to seasonal environmental variation and change. Such population and evolutionary dynamics result from immediate and lagged responses of all key life-history traits, and resulting demographic rates that affect population growth rate, to seasonal environmental conditions and population density. However, existing population dynamic and eco-evolutionary theory and models have not yet fully encompassed within-individual and among-individual variation, covariation, structure and heterogeneity, and ongoing evolution, in a critical life-history trait that allows individuals to respond to seasonal environmental conditions: seasonal migration. Meanwhile, empirical studies aided by new animal-tracking technologies are increasingly demonstrating substantial within-population variation in the occurrence and form of migration versus year-round residence, generating diverse forms of 'partial migration' spanning diverse species, habitats and spatial scales. Such partially migratory systems form a continuum between the extreme scenarios of full migration and full year-round residence, and are commonplace in nature. Here, we first review basic scenarios of partial migration and associated models designed to identify conditions that facilitate the maintenance of migratory polymorphism. We highlight that such models have been fundamental to the development of partial migration theory, but are spatially and demographically simplistic compared to the rich bodies of population dynamic theory and models that consider spatially structured populations with dispersal but no migration, or consider populations experiencing strong seasonality and full obligate migration. Second, to provide an overarching conceptual framework for spatio-temporal population dynamics, we define a 'partially migratory meta-population' system as a spatially structured set of locations that can be occupied by different sets of resident and migrant individuals in different seasons, and where locations that can support reproduction can also be linked by dispersal. We outline key forms of within-individual and among-individual variation and structure in migration that could arise within such systems and interact with variation in individual survival, reproduction and dispersal to create complex population dynamics and evolutionary responses across locations, seasons, years and generations. Third, we review approaches by which population dynamic and eco-evolutionary models could be developed to test hypotheses regarding the dynamics and persistence of partially migratory meta-populations given diverse forms of seasonal environmental variation and change, and to forecast system-specific dynamics. To demonstrate one such approach, we use an evolutionary individual-based model to illustrate that multiple forms of partial migration can readily co-exist in a simple spatially structured landscape. Finally, we summarise recent empirical studies that demonstrate key components of demographic structure in partial migration, and demonstrate diverse associations with reproduction and survival. We thereby identify key theoretical and empirical knowledge gaps that remain, and consider multiple complementary approaches by which these gaps can be filled in order to elucidate population dynamic and eco-evolutionary responses to spatio-temporal seasonal environmental variation and change.

Project description:Variation in movement across time and space fundamentally shapes the abundance and distribution of populations. Although a variety of approaches model structured population dynamics, they are limited to specific types of spatially structured populations and lack a unifying framework. Here, we propose a unified network-based framework sufficiently novel in its flexibility to capture a wide variety of spatiotemporal processes including metapopulations and a range of migratory patterns. It can accommodate different kinds of age structures, forms of population growth, dispersal, nomadism and migration, and alternative life-history strategies. Our objective was to link three general elements common to all spatially structured populations (space, time and movement) under a single mathematical framework. To do this, we adopt a network modeling approach. The spatial structure of a population is represented by a weighted and directed network. Each node and each edge has a set of attributes which vary through time. The dynamics of our network-based population is modeled with discrete time steps. Using both theoretical and real-world examples, we show how common elements recur across species with disparate movement strategies and how they can be combined under a unified mathematical framework. We illustrate how metapopulations, various migratory patterns, and nomadism can be represented with this modeling approach. We also apply our network-based framework to four organisms spanning a wide range of life histories, movement patterns, and carrying capacities. General computer code to implement our framework is provided, which can be applied to almost any spatially structured population. This framework contributes to our theoretical understanding of population dynamics and has practical management applications, including understanding the impact of perturbations on population size, distribution, and movement patterns. By working within a common framework, there is less chance that comparative analyses are colored by model details rather than general principles.

Dataset Information

Resilience to climate variation in a spatially structured amphibian population.

Publications

Resilience to climate variation in a spatially structured amphibian population.

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