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Project runs from 01 January 2006 to 31 December 2010
Added on January 12, 2006
The Intergovernmental Panel for Climate Change (IPCC 2001a) concluded that by increasing the concentration of greenhouse gasses, man has a discernible influence on climate, expected to be a long-term phenomenon affecting the environment in the forthcoming decades or even centuries. Since climate is a key driving force for ecological processes, climate change is likely to exert considerable effects on current biodiversity conservation goals. Indications for impacts were found in many species over a wide range of taxa (Parmesan and Yohe 2003, Thomas et al 2004). One of the major concerns (e.g. IPCC 2001a) is that nature can not adapt adequately, because the rate of climate change is unprecedented and because the effects of climate change are expected to be aggravated by habitat deterioration and fragmentation and by spatial barriers (Opdam & Wascher 2004). However, there are also indications that mobile species in the Netherlands might profit from climate change, whereas temperature increase can regionally expand the habitat network of species, causing the opposite effect of fragmentation (Thomas et al. 1999). The Third Assessment Report on Climate Change (IPCC 2001b) predicts a global temperature increase of maximally 5.2°C – with regional peaks of more than 8°C. This change of climate is thought to lead to an increase in average global temperature, changes in the frequency and distribution of precipitation, and changes in the pattern and occurrence of droughts and floods (Parry & Swaminathan 1992). In terms of potential risks to biodiversity, these changes can be classified under two headings: rise in average temperature, and an increased fluctuation of weather conditions, leading to increased perturbations in ecosystems. While temperature rise is affecting all ecosystem types, weather fluctuations (extreme rainfall, dry and hot summers) may be particularly important in wet ecosystems, in the lower parts of catchment areas and in river deltas, but also in open dry ecosystems. Native pinewoods, calcareous grassland, mesotrophic lakes, riverine and wetland ecosystems have been identified as particularly vulnerable (Van Ierland et al. 2001). Still, there is large uncertainty about the magnitude and concrete impact patterns that have to be expected (Hossel et al. 2000).
The Dutch National Ecological Network (EHS) is a strategy to conserve biodiversity in a highly fragmented landscape, which is under heavy pressure of increasing economy and growth of human population. The EHS also incorporates European nature policy targets, e.g. the protection of habitats according to the Habitat Directive. Large parts of the Netherlands are highly urbanised, with massive infrastructure connecting economic hot spots. The Dutch people however attribute much significance to nature quality, and the Dutch policy has developed clear-cut aims and ambition levels. The EHS is the backbone of this policy, and the main spatial structure for realising these aims. Considerable investments have been made in the last decade to expand and connect the network of existing nature. Additional robust ecological corridors were introduced in the renewed nature policy plan (LNV 1999) to improve the spatial cohesion of the EHS. For a selection of species, the development of the EHS was shown to improve the perspectives for persistence considerably (Nature Policy Agency, 1999). It has also been shown that the EHS has considerable economic value, for example due to its recreation function. However, although climate change is predicted to be a potential threat to the ecological functioning of the EHS in relation to the ambitions of the current policy (Nature Policy Agency 2003), its potential risks for the long-term conservation of biodiversity in the EHS-network have not been addressed in a quantitative way, and specified to location, species and ecosystem type. Current EHS evaluation models are based on assumptions of network stability and moderate environmental stochasticity, which no longer hold for conditions expected under climate change scenarios (Opdam & Klijn 2003). Therefore the effects of climate change on reaching the prospected ambition level of nature quality are unknown, and consequently the effectiveness of the current investments in the Dutch Ecological Network is unsure.
The research problem is:
• To explore which ecosystems and species are at risk, where the most important bottlenecks are situated, and which spatial and management strategies are available and effective for solving these problems.
• To adapt existing methodology for the evaluation of the EHS for persistence of target species populations by including new knowledge on the spatial conditions by which species can persist under climate change;
In this analysis we also include the potential opportunities that species might encounter due to climate change.
The ecological knowledge of the effects of climate change on species populations in fragmented systems is largely insufficient to predict effects at the species level (Opdam and Wascher 2004). Therefore we chose a more general approach focussing on ecological groups of species and ecosystems for which on theoretical grounds the combination of climate change and habitat fragmentation causes high risks (described in Opdam and Klijn 2003). To give this analysis an empirical basis, we use some of these groups in empirical analyses of current data sets from monitoring programmes, using available ecological models to extrapolate the results in time and space, and generalise the risks to other groups. We will express the outcome of the project in relative risk levels of ecosystems and species groups rather than in quantitative species-specific predictions. We expect that for defining effective spatial measures of adaptation, given the uncertainty of the multifunctional planning process, this level of certainty is adequate for a first round of problem definition.
Building on this, we distinguish three specific aims:
1. To explore and quantify the potential risks and opportunities of climate change for populations of a selection of animal species in the EHS, as a firm empirical basis to build the risk management strategies on.
2. To generalize these results to other ecosystems and species groups.
3. To identify, within this context, where in the EHS loss of target species is at risk or is likely to increase.
We will mainly base our approach on selected bird and butterfly species. Butterflies and birds encompass a wide variety of life history traits in relation to habitat fragmentation and climate change pressures. Butterflies are ectothermic, and therefore more liable to weather variability than birds. Their population fluctuations are stronger. Both groups inhabit a wide range of ecosystems, and great differences between species exist with respect to dispersal distances. Another, pragmatic, reason for selecting these groups is that comprehensive, long time-series of distribution data (> 20 years) are available. Many butterfly species already show effects in their distribution as a result of temperature rise (Thomas and Hanski 2004). For bird species it is expected that especially marshland birds will react strongly to variable habitat quality effects as a result of increased climatic fluctuations (Foppen et al 1999). Marshland ecosystems in the Netherlands are of international importance for European biodiversity.
Population responses and effects on local and regional species persistence.
Studies exploring spatial responses to climate change often disregarded the role of the landscape pattern (Ellis et al. 1997, Hill et al. 1999, Parmesan et al. 1999, Conrad et al. 2002). Although in some literature range expansions driven by climate change were treated in a spatial context (Sykes and Prentice 1996, Lindner et al. 1997, Rupp et al. 2000), little attention was paid to the synergetic effects of habitat fragmentation and climate change (but see Thomas and Hanski 2004). However, in a human-dominated world, natural or semi-natural ecosystems are embedded in tracts of unsuitable landscape, and populations of species restricted to those habitat types are spatially dissected. Often, such populations show characteristics of a metapopulation structure (Hanski 1999, Vos et al. 2001, Opdam and Wiens 2002). The persistence and dynamics of such metapopulations are determined by the spatial cohesion of the habitat networks in such landscapes (Opdam et al. 2003).
General approach. We combine a spatially explicit correlation analysis of distribution patterns with some experimental work to test some of the assumptions, and modelling work to extrapolate the results in time and space. Distribution data are delivered by two of the project partners. Spatial cohesion indicators are computed with existing methods. Existing metapopulation (Verboom et al. 2001, Etienne et al. 2004) and dispersal models (Vos et al 2002) will be adapted to explore population dynamics and viability of species in fragmented habitat undergoing a geographical shift of optimal habitat conditions or increased climatic fluctuations.
Determining effects of temperature increase due to climate change interacts with ecological processes in fragmented landscapes (Opdam and Wascher 2004). What is described as a shifting species range is in fact the result of extinction of (meta)populations at the warm range limit, and colonisation and growth of (meta)populations into regions that newly came within the cold range limit (Parmesan et al. 1999, Bakkenes et al. 2002). The increasing fragmentation may prevent such adaptation (Warren et al. 2001). On the other hand, climate change may also cause an increase in the amount of habitat, and consequently a decrease in fragmentation (Thomas et al. 1999). We will combine shifting “climate envelopes” (Pearson et al 2002) with ecosystem patterns to predict maximum and realized response to temperature change, and compare these with actual changes in distribution. We expect to find a mismatch between where species can live and species do live. This mismatch is interpreted in terms of bottleneck areas.
Furthermore, increased variability in climate conditions may cause increased oscillations in population numbers, which may be reinforced by habitat fragmentation, causing higher extinction rates and increased recovery time (Foppen et al. 1999). Consequently, species may disappear from the EHS. This aspect of climate change has hardly been considered in literature. We will analyse differences in fluctuations in species numbers and occurrence in ecosystem patterns varying in the presence of a large key area, total network area, network density and connectivity. Expected differences are modelled with metapopulation models, and compared with time series of distribution data, for example BMP-plots provided by SOVON. The result of this step is a relationship between parameters of ecosystem network cohesion and the resilience of populations to recover from climate change induced disturbance patterns. We expect to find critical threshold levels in that relationship.
Building the bridge to planning and design: identification of strong and weak parts of the EHS. This aim is achieved by combining the above mentioned results in terms of strong and weak patterns of the EHS with respect to climate change. This will be based on an extrapolation of the results to other species and ecosystems, including target species for the EHS.
For this task we assume that species can be arranged according to their vulnerability to habitat fragmentation and climate change. Ecoprofiles have been developed and made applicable for planning and design on the basis of area requirements for viable populations and dispersal capacity (Vos et al. 2001, Van Rooij et al. 2003). The system of ecoprofiles, based on capacity to respond to habitat fragmentation, will be extended with a climate change dimension (so called eco-environmental profiles). It will be determined which ecoprofiles are most vulnerable to the combined pressure of habitat fragmentation and climate change. In which ecosystems do most vulnerable species occur?
The project is financed by the BSIK programme "Klimaat voor Ruimte"
Last modified on Jun 8, 2009 02:56:13 PM by Ad van Dommelen
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