Future Distribution of Arctic Char <Emphasis Type="Italic">Salvelinus alpinus</Emphasis> in Sweden under Climate Change: Effects of Temperature,Lake Size and Species Interactions

Novel communities will be formed as species with a variety of dispersal abilities and environmental tolerances respond individually to climate change. Thus, models projecting future species distributions must account for species interactions and differential dispersal abilities. We developed a species distribution model for Arctic char Salvelinus alpinus, a freshwater fish that is sensitive both to warm temperatures and to species interactions. A logistic regression model using lake area, mean annual air temperature (1961–1990), pike Esox lucius and brown trout Salmo trutta occurrence correctly classified 95 % of 467 Swedish lakes. We predicted that Arctic char will lose 73 % of its range in Sweden by 2100. Predicted extinctions could be attributed both to simulated temperature increases and to projected pike invasions. The Swedish mountains will continue to provide refugia for Arctic char in the future and should be the focus of conservation efforts for this highly valued fish.     

Non-selective signal loss in the 13C CPMAS NMR spectra of soil organic matter. Investigations of particle size fractions

In 13C cross-polarisation magic angle spinning (CPMAS) spectra of soil samples, the paramagnetic soil constituents partially discriminate against the signal intensity of the 13C atoms. The aim of the present study was to check to what extent this signal depression depends on the paramagnetic ion content and if it is selective for a certain kind of carbon species. The spectra of a variety of particle size fractions of five quite different soils were recorded. A procedure was developed to compare quantitatively the relative carbon content of the different spectra. It was found that iron ions differ in their efficiency to discriminate against the carbon signals. Nevertheless a strong linear correlation between the detectability of carbon and cube root(wt.%Fe) was observed for both the total signal and the signal of the different carbon species as well. This underlines that iron ions mainly influence the depression of the 13C signal in soil spectra. Furthermore we found, that for C: Fe ratios of 1.5 to 20 non-selective signal losses dominate. Despite a high percentage of non-detectable carbon (up to 90%), the 13C CPMAS spectra of our soil samples correctly reflect the relative composition of soil organic matter.     

Future distribution of Arctic char Salvelinus alpinus in Sweden under climate change: effects of temperature, lake size and species interactions

Novel communities will be formed as species with a variety of dispersal abilities and environmental tolerances respond individually to climate change. Thus, models projecting future species distributions must account for species interactions and differential dispersal abilities. We developed a species distribution model for Arctic char Salvelinus alpinus, a freshwater fish that is sensitive both to warm temperatures and to species interactions. A logistic regression model using lake area, mean annual air temperature (1961-1990), pike Esox lucius and brown trout Salmo trutta occurrence correctly classified 95?% of 467 Swedish lakes. We predicted that Arctic char will lose 73?% of its range in Sweden by 2100. Predicted extinctions could be attributed both to simulated temperature increases and to projected pike invasions. The Swedish mountains will continue to provide refugia for Arctic char in the future and should be the focus of conservation efforts for this highly valued fish.     

Aryl hydrocarbon receptor (AhR) inducers and estrogen receptor (ER) activities in surface sediments of Three Gorges Reservoir,China evaluated with in vitro cell bioassays

Two types of biological tests were employed for monitoring the toxicological profile of sediment cores in the Three Gorges Reservoir (TGR), China. In the present study, sediments collected in June 2010 from TGR were analyzed for estrogen receptor (ER)- and aryl hydrocarbon receptor (AhR)-mediated activities. The estrogenic activity was assessed using a rapid yeast estrogen bioassay, based on the expression of a green fluorescent reporter protein. Weak anti-estrogenic activity was detected in sediments from an area close to the dam of the reservoir, and weak estrogenic activities ranging from 0.3 to 1 ng 17β-estradiol (E2) equivalents (EQ) g^?1 dry weight sediment (dw) were detected in sediments from the Wanzhou to Guojiaba areas. In the upstream areas Wanzhou and Wushan, sediments demonstrated additive effects in co-administration of 1 nM E2 in the yeast test system, while sediments from the downstream Badong and Guojiaba areas showed estrogenic activities which seemed to be more than additive (synergistic activity). There was an increasing tendency in estrogenic activity from upstream of TGR to downstream, while this tendency terminated and converted into anti-estrogenic activity in the area close to the dam. The AhR activity was detected employing rat hepatoma cell line (H4IIE). EROD activities were found homogenously distributed in sediments in TGR ranging from 200 to 311 pg 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) EQ g^?1 dw for total AhR agonists and from 45 to 76 pg TCDD EQ g^?1 dw for more persistent AhR agonists. The known AhR agonists polycyclic aromatic hydrocarbon, polychlorinated biphenyl, and PCDD/F only explained up to 8 % of the more persistent AhR agonist activity in the samples, which suggests that unidentified AhR-active compounds represented a great proportion of the TCDD EQ in sediments from TGR. These findings of estrogenic potential and dioxin-like activity in TGR sediments provide possible weight-of-evidence of potential ecotoxicological causes for the declines in fish populations which have been observed during the past decades in TGR.     

Place-based management at different spatial scales

Place-based management is any management action having implications for a specified area. Place-based management is seen as a key component to practical implementation of ecosystem approach to management, with marine spatial planning (MSP) being the currently most promoted approach. In the present paper we address the challenges of place-based management at local, regional and global (oceanic) spatial scales using case studies from the Northeast Atlantic with examples from Norway. Both ecological, governance and management complexity increases with increasing geographic scale, with associated increases in uncertainty and thus increasing need for managing under the precautionary approach. A process where (ecologically) valuable and vulnerable areas are defined early on is essential to successful place-based management under the ecosystem approach. Integrating across sectors and achieving necessary cooperation between involved institutions and stakeholders is also necessary.     

Uncertainty analysis in integrated assessment: the users’ perspective

Integrated Assessment (IA) models aim at providing information- and decision-support to complex problems. This paper argues that uncertainty analysis in IA models should be user-driven in order to strengthen science–policy interaction. We suggest an approach to uncertainty analysis that starts with investigating model users’ demands for uncertainty information. These demands are called “uncertainty information needs”. Identifying model users’ uncertainty information needs allows focusing the analysis on those uncertainties which users consider relevant and meaningful. As an illustrative example, we discuss the case of examining users’ uncertainty information needs in the SEAMLESS Integrated Framework (SEAMLESS-IF), an IA model chain for assessing and comparing alternative agricultural and environmental policy options. The most important user group of SEAMLESS-IF are policy experts at the European and national level. Uncertainty information needs of this user group were examined in an interactive process during the development of SEAMLESS-IF and by using a questionnaire. Results indicate that users’ information requirements differed from the uncertainty categories considered most relevant by model developers. In particular, policy experts called for addressing a broader set of uncertainty sources (e.g. model structure and technical model setup). The findings highlight that investigating users’ uncertainty information needs is an essential step towards creating confidence in an IA model and its outcomes. This alone, however, may not be sufficient for effectively implementing a user-oriented uncertainty analysis in such models. As the case study illustrates, it requires to include uncertainty analysis into user participation from the outset of the IA modelling process.