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Abstract In later years the potential contribution of forest bioenergy to mitigate climate change has been increasingly questioned due to temporal displacement between CO 2 emissions when forest biomass is used for energy and subsequent sequestration of carbon in new biomass. Also disturbance of natural decay of dead biomass when used for energy affect the carbon dynamics of forest ecosystems. These perturbations of forest ecosystems are summarized under the concept of carbon debt and its payback time. Narrative reviews demonstrate that the payback time of apparently comparable forest bioenergy supply scenarios vary by up to 200 years allowing amble room for confusion and dispute about the climate benefits of forest bioenergy. This meta-analysis confirm that the outcome of carbon debt studies lie in the assumptions and find that methodological rather than ecosystem and management related assumptions determine the findings. The study implies that at the current development of carbon debt methodologies and their lack of consensus the concept in it-self is inadequate for informing and guiding policy development. At the management level the carbon debt concept may provide valuable information directing management principles in a more climate benign directions.

Effective societal responses to rapid climate change in the Arctic rely on an accurate representation of region-specific ecosystem properties and processes. However, this is limited by the scarcity and patchy distribution of field measurements. Here, we use a comprehensive, geo-referenced database of primary field measurements in 1,840 published studies across the Arctic to identify statistically significant spatial biases in field sampling and study citation across this globally important region. We find that 31% of all study citations are derived from sites located within 50 km of just two research sites: Toolik Lake in the USA and Abisko in Sweden. Furthermore, relatively colder, more rapidly warming and sparsely vegetated sites are under-sampled and under-recognized in terms of citations, particularly among microbiology-related studies. The poorly sampled and cited areas, mainly in the Canadian high-Arctic archipelago and the Arctic coastline of Russia, constitute a large fraction of the Arctic ice-free land area. Our results suggest that the current pattern of sampling and citation may bias the scientific consensuses that underpin attempts to accurately predict and effectively mitigate climate change in the region. Further work is required to increase both the quality and quantity of sampling, and incorporate existing literature from poorly cited areas to generate a more representative picture of Arctic climate change and its environmental impacts.

AbstractDrought affects more people than any other natural disaster but there is little understanding of how ecosystems react to droughts. This study jointly analyzed spatio‐temporal changes of drought patterns with vegetation phenology and productivity changes between 1999 and 2010 in major European bioclimatic zones. The Standardized Precipitation and Evapotranspiration Index (SPEI) was used as drought indicator whereas changes in growing season length and vegetation productivity were assessed using remote sensing time‐series of Normalized Difference Vegetation Index (NDVI). Drought spatio‐temporal variability was analyzed using a Principal Component Analysis, leading to the identification of four major drought events between 1999 and 2010 in Europe. Correspondence Analysis showed that at the continental scale the productivity and phenology reacted differently to the identified drought events depending on ecosystem and land cover. Northern and Mediterranean ecosystems proved to be more resilient to droughts in terms of vegetation phenology and productivity developments. Western Atlantic regions and Eastern Europe showed strong agglomerations of decreased productivity and shorter vegetation growing season length, indicating that these ecosystems did not buffer the effects of drought well. In a climate change perspective, increase in drought frequency or intensity may result in larger impacts over these ecosystems, thus management and adaptation strategies should be strengthened in these areas of concerns.

SUMMARYTime discounting – the degree to which individuals value current more than future resources – is an important component of natural resource conservation. As a response to climate change impacts in island communities, such as sea level rise, discounting the future can be a rational response due to increased stress on natural resources and uncertainty about whether future generations will have the same access to the same resources. By incorporating systematic responses of discount rates into models of resource conservation, realistic expectations of future human responses to climate change and associated resource stress may be developed. This paper illustrates the importance of time discounting through a theoretical agent-based model of resource use in island communities. A discount rate change can dramatically change projections about future migration and community-based conservation efforts. Our simulation results show that an increase in discount rates due to a credible information shock about future climate change impacts is likely to speed resource depletion. The negative impacts of climate change are therefore likely to be underestimated if changes in discount rates and emerging migration patterns are not taken into account.

Climate change has irrevocable consequences for the otherwise well-preserved archaeological deposits in the Arctic. Vegetation changes are expected to impact archaeological sites, but currently the effects are poorly understood. In this article we investigate five archaeological sites and the surrounding natural areas along a climate gradient in Southwest Greenland in terms of vegetation types, above- and below-ground biomass, soil geochemistry and spectral properties. The investigations are based on data from site-sampling and optical remote sensing from an unmanned aerial vehicle (UAV) and satellites. Results show that the archaeological sites are dominated by graminoids with approximately two times more above- and below-ground biomass than the surrounding areas, where the vegetation is more heterogeneous. This difference is associated with a 2-6 times higher content of plant available phosphorus and water extractable nitrate and ammonium in the archaeological deposits compared to the surrounding soil. Furthermore, the vegetation at archaeological sites is less affected by the regional climate variations than the surrounding natural areas. This suggests that soil-vegetation interactions at archaeological sites are markedly different from the natural environment. Thus, the long-term vulnerability of buried archaeological remains cannot be assessed based on existing projections of Arctic vegetation change. Finally, the study demonstrates that vegetation within archaeological sites has distinct spectral properties, and there is a great potential for using satellite imagery for large scale vegetation monitoring of archaeological sites and for archaeological prospection in the Arctic.

Heavy metals are some of the most persistent and potent anthropogenic environmental contaminants. Although heavy metals may compromise microbial communities and soil fertility, it is challenging to causally link microbial responses to heavy metals due to various confounding factors, including correlated soil physicochemistry or nutrient availability. A solution is to investigate whether tolerance to the pollutant has been induced, called Pollution Induced Community Tolerance (PICT). In this study, we investigated soil microbial responses to a century-old gradient of metal ore pollution in an otherwise pristine subarctic birch forest generated by a railway source of iron ore transportation. To do this, we determined microbial biomass, growth, and respiration rates, and bacterial tolerance to Zn and Cu in replicated distance transects (1 m-4 km) perpendicular to the railway. Microbial biomass, growth and respiration rates were stable across the pollution gradient. The microbial community structure could be distinguished between sampled distances, but most of the variation was explained by soil pH differences, and it did not align with distance from the railroad pollution source. Bacterial tolerance to Zn and Cu started from background levels at 4 km distance from the pollution source, and remained at background levels for Cu throughout the gradient. Yet, bacterial tolerance to Zn increased 10-fold 100 m from the railway source. Our results show that the microbial community structure, size and performance remained unaffected by the metal ore exposure, suggesting no impact on ecosystem functioning.

Excessive nutrient loadings into rivers are a well-known ecological problem. Implemented mitigation measures should ideally be cost-effective, but perfectly ranking alternative nutrient mitigation measures according to cost-effectiveness is a difficult methodological challenge. Furthermore, a particularly practical challenge is that cost-effective measures are not necessarily favoured by local stakeholders, and this may impede their successful implementation in practice. The objective of this study was to evaluate the cost-effectiveness of mitigation measures using a methodology that includes a participatory process and social learning to ensure their successful implementation. By combining cost data, hydrological modelling and a bottom-up approach for three different European catchment areas (the Latvian Berze, the Swedish Helge and the German Selke rivers), the cost-effectiveness of 16 nutrient mitigation measures were analysed under current conditions as well as under selected scenarios for future climate and land-use changes. Fertiliser reduction, wetlands, contour ploughing and municipal wastewater treatment plants are the measures that remove nutrients with the highest cost-effectiveness in the respective case study context. However, the results suggest that the cost-effectiveness of measures not only depends on their design, specific location and the conditions of the surrounding area, but is also affected by the future changes the area may be exposed to. Climate and land-use changes do not only affect the cost-effectiveness of measures, but also shape the overall nutrient loads and potential target levels in a catchment.

Forests' potential to mitigate carbon emissions to the atmosphere is heavily debated and a key question is if forests left unmanaged to store carbon in biomass and soil provide larger carbon emission reductions than forests kept under forest management for production of wood that can substitute fossil fuels and fossil fuel intensive materials. We defined a modelling framework for calculation of the carbon pools and fluxes along the forest energy and wood product supply chains over 200 years for three forest management alternatives (FMA): 1) a traditionally managed European beech forest, as a business-as-usual case, 2) an energy poplar plantation, and 3) a set-aside forest left unmanaged for long-term storage of carbon. We calculated the cumulative net carbon emissions (CCE) and carbon parity times (CPT) of the managed forests relative to the unmanaged forest. Energy poplar generally had the lowest CCE when using coal as the reference fossil fuel. With natural gas as the reference fossil fuel, the CCE of the business-as-usual and the energy poplar was nearly equal, with the unmanaged forest having the highest CCE after 40 years. CPTs ranged from 0 to 156 years, depending on the applied model assumptions. CCE and CPT were especially sensitive to the reference fossil fuel, material alternatives to wood, forest growth rates for the three FMAs, and energy conversion efficiencies. Assumptions about the long-term steady-state levels of carbon stored in the unmanaged forest had a limited effect on CCE after 200 years. Analyses also showed that CPT was not a robust measure for ranking of carbon mitigation benefits.