Impacts of climate change on Swiss biodiversity: An indicator taxa approach

Biological Conservation (Impact Factor: 3.76). 02/2011; 144(2):866-875. DOI: 10.1016/j.biocon.2010.11.020

ABSTRACT We present a new indicator taxa approach to the prediction of climate change effects on biodiversity at the national level in Switzerland. As indicators, we select a set of the most widely distributed species that account for 95% of geographical variation in sampled species richness of birds, butterflies, and vascular plants. Species data come from a national program designed to monitor spatial and temporal trends in species richness. We examine some opportunities and limitations in using these data. We develop ecological niche models for the species as functions of both climate and land cover variables. We project these models to the future using climate predictions that correspond to two IPCC 3rd assessment scenarios for the development of ‘greenhouse’ gas emissions. We find that models that are calibrated with Swiss national monitoring data perform well in 10-fold cross-validation, but can fail to capture the hot-dry end of environmental gradients that constrain some species distributions. Models for indicator species in all three higher taxa predict that climate change will result in turnover in species composition even where there is little net change in predicted species richness. Indicator species from high elevations lose most areas of suitable climate even under the relatively mild B2 scenario. We project some areas to increase in the number of species for which climate conditions are suitable early in the current century, but these areas become less suitable for a majority of species by the end of the century. Selection of indicator species based on rank prevalence results in a set of models that predict observed species richness better than a similar set of species selected based on high rank of model AUC values. An indicator species approach based on selected species that are relatively common may facilitate the use of national monitoring data for predicting climate change effects on the distribution of biodiversity.

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Available from: Antoine Guisan, Sep 28, 2015
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    • "If climate change threatens only local lineages, these threats would go undetected when considering the generic pan-European niche, or unrealistic modeled shifts could be predicted. Hence, national level studies are commonly carried out based on the portion of the range which falls within the national territory [40,41,42]. Regarding all these controversial issues decisions need to be taken and the implications discussed, bearing in mind that any modeling exercise will only produce estimates which make it possible to contrast projected range shifts between communities and set conservation priorities in a relative and comparative way. "
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    ABSTRACT: Coastal dunes worldwide harbor threatened habitats characterized by high diversity in terms of plant communities. In Italy, recent assessments have highlighted the insufficient state of conservation of these habitats as defined by the EU Habitats Directive. The effects of predicted climate change could have dramatic consequences for coastal environments in the near future. An assessment of the efficacy of protection measures under climate change is thus a priority. Here, we have developed environmental envelope models for the most widespread dune habitats in Italy, following two complementary approaches: an "indirect" plant-species-based one and a simple "direct" one. We analyzed how habitats distribution will be altered under the effects of two climate change scenarios and evaluated if the current Italian network of protected areas will be effective in the future after distribution shifts. While modeling dune habitats with the "direct" approach was unsatisfactory, "indirect" models had a good predictive performance, highlighting the importance of using species' responses to climate change for modeling these habitats. The results showed that habitats closer to the sea may even increase their geographical distribution in the near future. The transition dune habitat is projected to remain stable, although mobile and fixed dune habitats are projected to lose most of their actual geographical distribution, the latter being more sensitive to climate change effects. Gap analysis highlighted that the habitats' distribution is currently adequately covered by protected areas, achieving the conservation target. However, according to predictions, protection level for mobile and fixed dune habitats is predicted to drop drastically under the climate change scenarios which we examined. Our results provide useful insights for setting management priorities and better addressing conservation efforts to preserve these threatened habitats in future.
    PLoS ONE 07/2013; 8(7):e68850. DOI:10.1371/journal.pone.0068850 · 3.23 Impact Factor
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    • "In Switzerland, an increase in mean temperature of 2 K by 2050 might lead to a decrease of 3–15 species per km 2 in lowlands because of the upward shift and to a slight increase above 1200 m (Bureau de coordination du Monitoring de la biodiversité en Suisse 2009). But, on subalpine–alpine ridges, this increase will correspond to an almost complete species turnover (Pearman et al. 2011). "
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    ABSTRACT: A noticeable increase in mean temperature has already been observed in Switzerland and summer temperatures up to 4.8 K warmer are expected by 2090. This article reviews the observed impacts of climate change on biodiversity and considers some perspectives for the future at the national level. The following impacts are already evident for all considered taxonomic groups: elevation shifts of distribution towards mountain summits, spread of thermophilous species, colonisation by new species from warmer areas and phenological shifts. Additionally, in the driest areas, increasing droughts are affecting tree survival and fish species are suffering from warm temperatures in lowland regions. These observations are coherent with model projections, and future changes will probably follow the current trends. These changes will likely cause extinctions for alpine species (competition, loss of habitat) and lowland species (temperature or drought stress). In the very urbanised Swiss landscape, the high fragmentation of the natural ecosystems will hinder the dispersal of many species towards mountains. Moreover, disruptions in species interactions caused by individual migration rates or phenological shifts are likely to have consequences for biodiversity. Conversely, the inertia of the ecosystems (species longevity, restricted dispersal) and the local persistence of populations will probably result in lower extinction rates than expected with some models, at least in 21st century. It is thus very difficult to estimate the impact of climate change in terms of species extinctions. A greater recognition by society of the intrinsic value of biodiversity and of its importance for our existence will be essential to put in place effective mitigation measures and to safeguard a maximum number of native species.
    Journal for Nature Conservation 06/2013; 21(3):154-162. DOI:10.1016/j.jnc.2012.12.002 · 1.65 Impact Factor
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    • "However, no intensive and extensive indicator species monitoring program exists for detecting the impacts of climate change on plants. Species distribution models (SDMs) are useful tools for assessing the potential impacts of climate change on species' distributions (Matsui et al., 2004a; Thuiller et al., 2005) and for selecting monitoring sites over extensive areas (Pearman et al., 2011; Urban, 2000). However, three types of prediction uncertainty of SDMs need to be assessed to selecting adequate indicators. "
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    ABSTRACT: To develop a long-term volunteer-based system for monitoring the impacts of climate change on plant distributions, potential indicator plants and monitoring sites were assessed considering habitat prediction uncertainty. We used species distribution models (SDMs) to project potential habitats for 19 popular edible wild plants in Japan. Prediction uncertainties of SDMs were assessed using three high-performance modeling algorithms and 19 simulated future climate data. SDMs were developed using presence/absence records, four climatic variables, and five non-climatic variables. The results showed that prediction uncertainties for future climate simulations were greater than those from the three different modeling algorithms. Among the 19 edible wild plant species, six had highly accurate SDMs and greater changes in occurrence probabilities between current and future climate conditions. The potential habitats of these six plants under future climate simulations tended to shift northward and upward, with predicted losses in potential southern habitats. These results suggest that these six plants are candidate indicators for long-term biological monitoring of the impacts of climate change. If temperature continuously increases as predicted, natural populations of these plants will decline in Kyushu, Chugoku and Shikoku districts, and in low altitudes of Chubu and Tohoku districts. These results also indicate the importance of occurrence probability and prediction uncertainty of SDMs for selecting target species and site locations for monitoring programs. Sasa kurilensis, a very popular and widespread dominant scrub bamboo in the cool-temperate regions of Japan, was found to be the most effective plant for monitoring.
    Ecological Indicators 06/2013; 29:307-315. DOI:10.1016/j.ecolind.2013.01.010 · 3.44 Impact Factor
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