4
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Life-history traits of voles in a fluctuating population respond to the immediate environment.

      Nature
      Animals, Arvicolinae, growth & development, physiology, Body Weight, Ecosystem, England, Environment, Female, Life Cycle Stages, Male, Population Dynamics, Seasons

      Read this article at

      ScienceOpenPublisherPubMed
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Life-history traits relating to growth and reproduction vary greatly among species and populations and among individuals within populations. In vole populations, body size and age at maturation may vary considerably among locations and among years within the same location. Individuals in increasing populations are typically larger and start reproduction earlier in the spring than those in declining populations. The cause of such life-history variation within populations has been subject of much discussion. Much of the controversy concerns whether the memory of past conditions, leading to delayed effects on life-history traits, resides in the environment (for example, predators, pathogens or food) or intrinsically within populations or individuals (age distribution, physiological state, genetic or maternal effects). Here we report from an extensive field transplant experiment in which voles were moved before the breeding season between sites that differed in average overwintering body mass. Transplanted voles did not retain the characteristics of their source population, and we demonstrate an over-riding role of the immediate environment in shaping life-history traits of small rodents.

          Related collections

          Most cited references21

          • Record: found
          • Abstract: not found
          • Article: not found

          Modeling Survival and Testing Biological Hypotheses Using Marked Animals: A Unified Approach with Case Studies

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            State-dependent life histories.

            Life-history theory is concerned with strategic decisions over an organism's lifetime. Evidence is accumulating about the way in which these decisions depend on the organism's physiological state and other components such as external circumstances. Phenotypic plasticity may be interpreted as an organism's response to its state. The quality of offspring may depend on the state and behaviour of the mother. Recent theoretical advances allow these and other state-dependent effects to be modelled within the same framework.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              A likelihood-based approach to capture-recapture estimation of demographic parameters under the robust design.

              The Jolly-Seber method has been the traditional approach to the estimation of demographic parameters in long-term capture-recapture studies of wildlife and fish species. This method involves restrictive assumptions about capture probabilities that can lead to biased estimates, especially of population size and recruitment. Pollock (1982, Journal of Wildlife Management 46, 752-757) proposed a sampling scheme in which a series of closely spaced samples were separated by longer intervals such as a year. For this "robust design," Pollock suggested a flexible ad hoc approach that combines the Jolly-Seber estimators with closed population estimators, to reduce bias caused by unequal catchability, and to provide estimates for parameters that are unidentifiable by the Jolly-Seber method alone. In this paper we provide a formal modelling framework for analysis of data obtained using the robust design. We develop likelihood functions for the complete data structure under a variety of models and examine the relationship among the models. We compute maximum likelihood estimates for the parameters by applying a conditional argument, and compare their performance against those of ad hoc and Jolly-Seber approaches using simulation.
                Bookmark

                Author and article information

                Journal
                11429603
                10.1038/35082553

                Chemistry
                Animals,Arvicolinae,growth & development,physiology,Body Weight,Ecosystem,England,Environment,Female,Life Cycle Stages,Male,Population Dynamics,Seasons

                Comments

                Comment on this article