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Direct negative density‐dependence in a pond‐breeding frog population
Authors:Raluca I Băncilă  Arpat Ozgul  Tibor Hartel  Tibor Sos  Benedikt R Schmidt
Institution:1. Inst. of Evolutionary Biology and Environmental Studies, Univ. of Zurich, Zurich, Switzerland;2. Univ. Ovidius Constan?a, Faculty of Natural Sciences, Al. Universit??ii, corp B, Constan?a, Romania;3. ‘Emil Racovi??‘ Inst. of Speleology of Romanian Academy, Bucharest, Romania;4. Faculty of Sustainability, Leuphana Univ. Lueneburg, Lüneburg, Germany;5. Dept of Environmental Sciences, Sapientia Univ., Cluj‐Napoca, Romania;6. Milvus Group, Bird and Nature Protection Association, Targu‐Mure?, Romania;7. KARCH, Neuchatel, Switzerland
Abstract:Understanding population dynamics is critical for the management of animal populations. Comparatively little is known about the relative importance of endogenous (i.e. density‐dependent) and exogenous (i.e. density‐independent) factors on the population dynamics of amphibians with complex life cycles. We examined the potential effects of density‐dependent and ‐independent (i.e. climatic) factors on population dynamics by analyzing a 15‐yr time series data of the agile frog Rana dalmatina population from Târnava Mare Valley, Romania. We used two statistical models: 1) the partial rate correlation function to identify the feedback structure and the potential time lags in the time series data and 2) a Gompertz state‐space model to simultaneously investigate direct and delayed density dependence as well as climatic effects on population growth rate. We found evidence for direct negative density dependence, whereas delayed density dependence and climate did not show a strong influence on population growth rate. Here we demonstrated that direct density dependence rather than delayed density dependence or climate determined the dynamics of our study population. Our results confirm the findings of many experimental studies and suggest that density dependence may buffer amphibian populations against environmental stress. Consequently, it may not be easy to scale up from individual‐level effects to population‐level effects.
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