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Abstract Dispersal evolves as an adaptive mechanism to optimize individual fitness across the landscape. Specifically, dispersal represents a mechanism to escape fitness costs resulting from changes in environmental conditions. Decades of empirical work suggest that individuals use local habitat cues to make movement decisions, but theory predicts that dispersal can also evolve as a fixed trait, independent of local conditions, in environments characterized by a history of stochastic spatiotemporal variation. Until now, however, both conditional and fixed models of dispersal evolution have primarily been evaluated using emigration data (stay vs. leave), and not dispersal distances: a more comprehensive measure of dispersal. Our goal was to test whether conditional or fixed models of dispersal evolution predict variation in dispersal distance in the stream salamanderGyrinophilus porphyriticus.We quantified variation in habitat conditions using measures of salamander performance from 4 yr of spatially explicit, capture–mark–recapture (CMR) data across three headwater streams in the Hubbard Brook Experimental Forest in central New Hampshire, USA. We used body condition as an index of local habitat quality that individuals may use to make dispersal decisions, and survival probability estimated from multistate CMR models as an index of mortality risk resulting from the long‐term history of environmental variation. We found that dispersal distances increased with declining survival probability, indicating that salamanders disperse further in risky environments. Dispersal distances were unrelated to spatial variation in body condition, suggesting that salamanders do not base dispersal distance decisions on local habitat quality. Our study provides the first empirical support for fixed models of dispersal evolution, which predict that dispersal evolves in response to a history of spatiotemporal environmental variation, rather than as a conditional response to current habitat conditions. More broadly, this study underscores the value of assessing alternative scales of environmental variation to gain a more complete and balanced understanding of dispersal evolution.
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Breeding transients in capture–recapture modeling and their consequences for local population dynamics
Abstract Standard procedures for capture–mark–recapture modelling (CMR) for the study of animal demography include running goodness-of-fit tests on a general starting model. A frequent reason for poor model fit is heterogeneity in local survival among individuals captured for the first time and those already captured or seen on previous occasions. This deviation is technically termed a transience effect. In specific cases, simple, uni-state CMR modeling showing transients may allow researchers to assess the role of these transients on population dynamics. Transient individuals nearly always have a lower local survival probability, which may appear for a number of reasons. In most cases, transients arise due to permanent dispersal, higher mortality, or a combination of both. In the case of higher mortality, transients may be symptomatic of a cost of first reproduction. A few studies working at large spatial scales actually show that transients more often correspond to survival costs of first reproduction rather than to permanent dispersal, bolstering the interpretation of transience as a measure of costs of reproduction, since initial detections are often associated with first breeding attempts. Regardless of their cause, the loss of transients from a local population should lower population growth rate. We review almost 1000 papers using CMR modeling and find that almost 40% of studies fitting the searching criteria (N = 115) detected transients. Nevertheless, few researchers have considered the ecological or evolutionary meaning of the transient phenomenon. Only three studies from the reviewed papers considered transients to be a cost of first reproduction. We also analyze a long-term individual monitoring dataset (1988–2012) on a long-lived bird to quantify transients, and we use a life table response experiment (LTRE) to measure the consequences of transients at a population level. As expected, population growth rate decreased when the environment became harsher while the proportion of transients increased. LTRE analysis showed that population growth can be substantially affected by changes in traits that are variable under environmental stochasticity and deterministic perturbations, such as recruitment, fecundity of experienced individuals, and transient probabilities. This occurred even though sensitivities and elasticities of these parameters were much lower than those for adult survival. The proportion of transients also increased with the strength of density-dependence. These results have implications for ecological and evolutionary studies and may stimulate other researchers to explore the ecological processes behind the occurrence of transients in capture–recapture studies. In population models, the inclusion of a specific state for transients may help to make more reliable predictions for endangered and harvested species.
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- Award ID(s):
- 1753954
- PAR ID:
- 10225242
- Date Published:
- Journal Name:
- Scientific Reports
- Volume:
- 10
- Issue:
- 1
- ISSN:
- 2045-2322
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1038/s41598-020-72778-x
