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Rivers form the most important natural corridors through the landscape. Certain plant species grow mainly or exclusively in these corridors as it has been observed for about 150 years in Central European lowlands. However, these species do not form a homogenous group in terms of biogeography, site requirements, life form, or any other feature this distribution pattern. Accordingly, first, we give a review of the various hypotheses which have been proposed to explain the river corridor distribution pattern. This includes (1) river corridors acting as routes of migration or invasion, (2) floodplain-specific disturbance providing open sites, (3) temporary anoxic conditions during floods, (4) deviating meso-climatic conditions, (5) specific substrate and nutrient supply, and (6) water supply. In particular, the above hypotheses (2-5) imply that river corridor plants may be well-adapted to specific stress and regeneration conditions in floodplains while other species may be not. This may lead to reduced competition in river corridors. We suggest this mechanism to constitute actual benefits for river corridor plants. Secondly, we present a simple model of multi-species population dynamics to show, that our competition-related framework is, in principle, able to explain river corridor plant species distribution patterns. As, however, none of the above hypotheses (1-6) have been tested experimentally we thirdly present a currently running experimental study on the river corridor plant Juncus atratus (black rush) in north- eastern Germany. We emphasize that much more experimental evidence must be gained on population ecology and meta- population dynamics to understand the distribution patterns of river corridor plants.
In a selected literature survey we reviewed studies on the habitat heterogeneity-animal species diversity relationship and evaluated whether there are uncertainties and biases in its empirical support. We reviewed 85 publications for the period 1960-2003. We screened each publication for terms that were used to define habitat heterogeneity, the animal species group and ecosystem studied, the definition of the structural variable, the measurement of vegetation structure and the temporal and spatial scale of the study. The majority of studies found a positive correlation between habitat heterogeneity/diversity and animal species diversity. However, empirical support for this relationship is drastically biased towards studies of vertebrates and habitats under anthropogenic influence. In this paper we show that ecological effects of habitat heterogeneity may vary considerably between species groups depending on whether structural attributes are perceived as heterogeneity or fragmentation. Possible effects may also vary relative to the structural variable measured. Based upon this, we introduce a classification framework that may be used for across-studies comparisons. Moreover, the effect of habitat heterogeneity for one species group may differ in relation to the spatial scale. In several studies, however, different species groups are closely linked to 'keystone structures' that determine animal species diversity by their presence. Detecting crucial keystone structures of the vegetation has profound implications for nature conservation and biodiversity management.
The impact of temporally correlated fluctuating environments (coloured noise) on the extinction risk of populations has become a main focus in theoretical population ecology. In this study we particularly focus on the extinction risk in strongly autocorrelated environments. Here, in contrast to moderate autocorrelation, we found the extinction risk to be highly dependent on the process of noise generation, in particular on the method of variance scaling. Such variance scaling is commonly applied to avoid variance-driven biases when comparing the extinction risk for white and coloured noise. In this study we found an often-used scaling technique to lead to high variability in the resulting variances of different time series for strong auto-correlation eventually leading to deviations in the projected extinction risk. Therefore, we present an alternative method that always delivers the target variance, even in the case of strong temporal correlation. Furthermore, in contrast to the earlier method, our very intuitive method is not bound to auto-regressive processes but can be applied to all types of coloured noises. We recommend the method introduced here to be used when the target of interest is the effect of noise colour on extinction risk not obscured by any variance effects.
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. (c) 2004 Elsevier B.V. All rights reserved