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Breeding transients in capture-recapture modeling and their consequences for local population dynamics
Daniel Oro1,2,3, Daniel F Doak4
1IMEDEA (CSIC-UIB), 07190, Esporles, Spain. d.oro@csic.es.
Scientific Reports
|September 26, 2020
Summary
Transience effects in capture-mark-recapture (CMR) studies, often linked to reproduction costs, impact population dynamics. Understanding transients is crucial for accurate population modeling and conservation efforts.
Area of Science:
- Ecology
- Population Biology
- Quantitative Biology
Background:
- Capture-mark-recapture (CMR) modeling is standard for animal demography.
- Poor model fit in CMR is often due to transience effects, where individuals new to the study have different survival rates.
- Transience is frequently linked to dispersal or increased mortality, potentially reflecting costs of first reproduction.
Purpose of the Study:
- To review the ecological and evolutionary significance of transience in CMR studies.
- To quantify transience in a long-lived bird species and assess its population-level consequences.
- To highlight the importance of accounting for transients in population dynamics and conservation.
Main Methods:
- Literature review of nearly 1000 CMR papers to identify studies detecting transients.
- Analysis of a long-term (1988-2012) individual monitoring dataset for a long-lived bird.
- Life table response experiment (LTRE) to measure population consequences of transience.
Main Results:
- Approximately 40% of reviewed CMR studies detected transients, but few explored their ecological meaning.
- Transience increased with harsher environments and density-dependence in the studied bird population.
- LTRE revealed that changes in transient probabilities significantly affect population growth, even more than adult survival.
Conclusions:
- Transience in CMR studies is a common phenomenon with significant ecological and evolutionary implications.
- Interpreting transience as a cost of reproduction provides valuable insights into population dynamics.
- Incorporating transient states into population models can improve predictions for endangered and harvested species.
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