Geochemical baseline study of gold mineralization in the Barsele Area, North Sweden

Two lake sediment cores and 10 lake water samples were sampled at different depths to assess trace metal content and water quality prior to the possibility of mining two orogenic gold deposits at Barsele, North Sweden. Existing regional water data sampled at different seasonal conditions was provided. Data from the Swedish Environmental Protection Agency (SEPA), the Kalix River and Lake Kutsasjärvi were also used as reference data to quantify metal pollution and assess their possible impact on aquatic systems. Bedrock composition, location of ore body and existing assay data were equally reviewed. Till close to gold deposits has high As but low base metal enrichment. Streams B7and B4 interacting with the ore bodies and mineralized till has a neutral pH and a good buffering capacity due to the weathering of calcite veins associated with ore bodies. Arsenic (18.2µg/l, SEPA class 4, Stream B7) is the most elevated in the drainage basin while Zn, Ni, Cu Hg, Mo, Cd and Pb in all surface waters are within the tolerance limit (SEPA class 1or2). Sorption onto Fe- oxy hydroxides in addition to a near neutral pH seems to limit greatly the mobility of heavy metals but less on the mobility of As due to its ability to form mobile complex anions. Lake water has a relatively low metal content due to its neutral pH and its near stable oxygen concentration. Arsenic (SEPA class 4) is particularly enriched in lake sediments, in association with precipitation of Fe- oxyhdroxide. Copper and Ni are equally elevated in lake sediments. Generally, metal enrichment in lake sediment is higher at sampling station A compared to station B and reflects variations in redox processes and the recycling of Fe-Mn. Although lake water and mineralized streams have a good buffering capacity, their metal content could be upgraded once mining begins because large volumes of rocks will be exposed to weathering. Thus, adequate measures should be taken to dispose waste rocks and monitor water chemistry.Validerat; 20101217 (root

Spatial Shifts in Species Richness in Response to Climate and Environmental Change: An Adaption of the EUROMOVE Model in the Czech Republic

Climate change has greatly altered plant habitats, resulting in greater biodiversity loss at different scales. Therefore, it is important to quantify such changes for better monitoring and conservation. In this study, we adapt the EUROMOVE model and its mean stable area indicator (MSAi) to the conditions in the Czech Republic. Our objective was to predict change in species richness from a representative pool of 687 species from 1990 to 2100 under the RCP 8.5 climate scenario, focusing on the current period (2018). Another objective was to assess the effectiveness of the MSAi as a tool for quantifying landscape vulnerability. Our result shows that species habitat expanded between 1990 and 2018, although about 2 per cent of species were lost. The average MSAi of the most favourable highland habitats may decrease from 0.85 to 0.65 by 2100 as >20% of baseline species may be lost. Indicator species of Alnus (alder) and Festuca (fescue), typical of lowland habitats, are among the most vulnerable, already showing a net loss of their current habitat extent. The MSAi can be applied as a comprehensive tool to quantify the impact of climate change on landscape vulnerability as more survey data becomes available

Assessing Habitat Vulnerability and Loss of Naturalness: Applying the GLOBIO3 Model in the Czech Republic

Global and regional biodiversity loss is caused by several drivers including urban development, land use intensification, overexploitation of natural resources, environmental pollution, and climate change. The main aim of our study was to adapt the GLOBIO3 model to the conditions of the Czech Republic (CR) to assess loss of naturalness and biodiversity vulnerability at the habitat level on a detailed scale across the entire CR. An additional aim was to assess the main drivers affecting the biodiversity of habitat types. The GLOBIO3 model was adapted to CZ-GLOBIO by adapting global to local scales and using habitat quality and naturalness data instead of species occurrence data. The total mean species abundance (MSA) index of habitat quality, calculated from the spatial overlay of the four MSA indicators by our new equation, reached the value 0.62. The total value of MSA for natural and near-natural habitats was found to be affected mainly by infrastructure development and fragmentation. Simultaneously, intensity of land use change and atmospheric nitrogen deposition contributed primarily to the low total value of MSA for distant natural habitats. The CZ-GLOBIO model can be an important tool in political decision making to reduce the impact of the main drivers on habitat biodiversity in the CR