Mitigation of climate change impacts on raptors by behavioural adaptation: ecological buffering mechanisms

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Abstract

The predicted climate change causes deep concerns on the effects of increasing temperatures and changing precipitation patterns on species viability and, in turn, on biodiversity. Models of Population Viability Analysis (PVA) provide a powerful tool to assess the risk of species extinction. However, most PVA models do not take into account the potential effects of behavioural adaptations. Organisms might adapt to new environmental situations and thereby mitigate negative effects of climate change. To demonstrate such mitigation effects, we use an existing PVA model describing a population of the tawny eagle (Aquila rapax) in the southern Kalahari. This model does not include behavioural adaptations. We develop a new model by assuming that the birds enlarge their average territory size to compensate for lower amounts of precipitation. Here, we found the predicted increase in risk of extinction due to climate change to be much lower than in the original model. However, this “buffering” of climate change by behavioural adaptation is not very effective in coping with increasing interannual variances. We refer to further examples of ecological “buffering mechanisms” from the literature and argue that possible buffering mechanisms should be given due consideration when the effects of climate change on biodiversity are to be predicted.

Introduction

Global change describes all phenomena of rapidly and dramatically changing environments that we have experienced in the recent past and that we face in the near future all over the earth. The term “global change” signifies that environmental modification is no longer restricted to local effects but instead occurs on large spatial scales (e.g., IPCC, 2001a, O'Neill et al., 2001, Van Jaarsveld and Chown, 2001, Walther et al., 2002). Consequently, society faces new and fundamental challenges in ecology and nature conservation. A major concern in this context is that increasing temperatures, changing precipitation patterns and the change of other environmental parameters might have a negative impact on population viability and, in turn, on biodiversity.

Since these concerns arose almost two decades ago (Roberts, 1988), population ecologists studied the dynamics and extinction risk of biotic populations with explicit respect to climatic parameters. Most of these studies suggest severe impacts of climate change on population dynamics resulting in a considerably increased risk of extinction which would lead to a considerable loss of species diversity. Climate change affects populations by changing basic life conditions, for example, food availability, and by causing habitat loss and fragmentation (e.g., Crick and Sparks, 1999, Post et al., 1999, Rutherford et al., 1999, Moss et al., 2001, Madens and Shine, 2001, Hannah et al., 2002, Wichmann et al., 2003a, Thomas et al., 2004; however, compare Erasmus et al., 2002, Wang et al., 2002).

An important tool of conservation biology to assess population viability, is Population Viability Analysis (PVA; Soulé, 1986, Beissinger and Westphal, 1998), which is based on models. However, in most PVAs, only the values of model parameters are varied, while model structure, i.e., the processes modelled, remains unchanged. This may bias results because in reality, organisms may have a high potential to adapt their behaviour to changing environmental conditions and thereby mitigate negative effects of environmental change. Here we demonstrate the potential effect of adaptive behaviour using an existing PVA model which describes a population of the tawny eagle (Aquila rapax) in the southern Kalahari (Wichmann et al., 2003a). This model (AQUIQUA) predicted a very high sensitivity of the population's viability to event moderate climate change scenarios. This surprising finding prompted the current study: would viability drop less dramatically if we include behavioural adaptations? Here, we develop a new model, AQUI_ADAPT, where we assume that the birds enlarge average territory size to compensate for negative effects of decreasing precipitation in southern Africa. It turns out that, under certain conditions, the adaptive behaviour is able to mitigate, or “buffer” environmental changes to some degree. In the context of PVA, “buffering mechanisms” have been defined as mechanism which reduce the effect of environmental fluctuations on the variation of a population's growth rate (Grimm et al., in press).

Section snippets

Methods

The new model, AQUI_ADAPT, is based on an earlier model, AQUIQUA (Wichmann et al., 2003a). The two models are solely distinguished by the behavioural adaptation incorporated in AQUI_ADAPT and described in Section 2.2.

Results

Our results clearly show deviations of the projected persistence time between the two models AQUIQUA and AQUI_ADAPT. For the first climate change scenario, i.e., decreasing annual average precipitation, we observe longer persistence times Tm for the new AQUI_ADAPT model compared to the original model (Fig. 2a, left). Assuming, however, an increase in average precipitation (in contrast to climate change projections) AQUI_ADAPT predicts lower Tm than the original model (Fig. 2a, right). For the

Discussion

In this study, we stress the importance of possible ecological buffering mechanisms for predictions of population survival under global change. We consider the projected survival of a population of tawny eagles in the southern Kalahari as a case study. Based on an earlier model of population dynamics of this species, we develop a new model implementing a possible adaptive behaviour, which might act as ecological buffering mechanism. Our results show that such buffering mechanisms can

Acknowledgements

The results described in this paper were first presented at the “International Young Scientists Global Change Conference” at Trieste, Italy, November 2003, and MCW wishes to thank the organizing committee chaired by P. Tyson and the START Scientific Steering Committee, Washington, for organizing and securing financial support of this conference. This work was partly funded by the Germany Ministry of Science (BMBF: BIOTA South Africa, 01LC0024). We are grateful to W.RJ. Dean who helped to

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