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Abstract The expansion of Sargassum muticum in the Danish estuary Limfjorden between 1984 and 1997 was followed by a decrease in abundance of native perennial macroalgae such as Halidrys siliquosa. Although commonly associated with the expansion of exotic species, it is unknown whether such structural changes affect ecosystem properties such as the production and turnover of organic matter and associated nutrients. We hypothesized that S. muticum possesses ‘ephemeral’ traits relative to the species it has replaced, potentially leading to faster and more variable turnover of organic matter. The biomass dynamics of S. muticum and H. siliquosa was therefore compared in order to assess the potential effects of the expansion of Sargassum. The biomass of Sargassum was highly variable among seasons while that of Halidrys remained almost constant over the year. Sargassum grew faster than Halidrys and other perennial algae and the annual productivity was therefore high (P/B = 12 year−1) and exceeded that of Halidrys (P/B = 5 year−1) and most probably also that of other perennial algae in the system. The major grazer on macroalgae in Limfjorden, the sea urchin Psammechinus miliaris, preferred Sargassum to Halidrys, but estimated losses due to grazing were negligible for both species and most of the production may therefore enter the detritus pool. Detritus from Sargassum decomposed faster and more completely than detritus from Halidrys and other slow-growing perennial macrophytes. High productivity and fast decomposition suggest that the increasing dominance of S. muticum have increased turnover of organic matter and associated nutrients in Limfjorden and we suggest that the ecological effects of the invasion to some extent resemble those imposed by increasing dominance of ephemeral algae following eutrophication.

The spatial dependency of pesticide emissions to air, surface water and groundwater is illustrated and quantified using PestLCI 2.0, an updated and expanded version of PestLCI 1.0. PestLCI is a model capable of estimating pesticide emissions to air, surface water and groundwater for use in life cycle inventory (LCI) modelling of field applications. After calculating the primary distribution of pesticides between crop and soil, specific modules calculate the pesticide’s fate, thus determining the pesticide emission pattern for the application. PestLCI 2.0 was developed to overcome the limitations of the first model version, replacement of fate calculation equations and introducing new modules for macropore flow and effects of tillage. The accompanying pesticide database was expanded, the meteorological and soil databases were extended to include a range of European climatic zones and soil profiles. Environmental emissions calculated by PestLCI 2.0 were compared to results from the risk assessment models SWASH (surface water emissions), FOCUSPEARL (groundwater via matrix leaching) and MACRO (groundwater including macropore flow, only one scenario available) to partially validate the updated model. A case study was carried out to demonstrate the spatial variation of pesticide emission patterns due to dependency on meteorological and soil conditions. Compared to PestLCI 1.0, PestLCI 2.0 calculated lower emissions to surface water and higher emissions to groundwater. Both changes were expected due to new pesticide fate calculation approaches and the inclusion of macropore flow. Differences between the SWASH and FOCUSPEARL and PestLCI 2.0 emission estimates were generally lower than 2 orders of magnitude, with PestLCI generally calculating lower emissions. This is attributed to the LCA approach to quantify average cases, contrasting with the worst-case risk assessment approach inherent to risk assessment. Compared to MACRO, the PestLCI 2.0 estimates for emissions to groundwater were higher, suggesting that PestLCI 2.0 estimates of fractions leached to groundwater may be slightly conservative as a consequence of the chosen macropore modelling approach. The case study showed that the distribution of pesticide emissions between environmental compartments strongly depends on local climate and soil characteristics. PestLCI 2.0 is partly validated in this paper. Judging from the validation data and case study, PestLCI 2.0 is a pesticide emission model in acceptable accordance with both state-of-the-art pesticide risk assessment models. The case study underlines that the common pesticide emission estimation practice in LCI may lead to misestimating the toxicity impacts of pesticide use in LCA.

The aim of this study was to investigate a combination of satellite images of leaf area index (LAI) with process-based vegetation modeling for the accurate assessment of the carbon balances of Swedish forest ecosystems at the scale of a landscape. Monthly climatologic data were used as inputs in a dynamic vegetation model, the Lund Potsdam Jena-General Ecosystem Simulator. Model estimates of net primary production (NPP) and the fraction of absorbed photosynthetic active radiation were constrained by combining them with satellite-based LAI images using a general light use efficiency (LUE) model and the Beer-Lambert law. LAI estimates were compared with satellite-extrapolated field estimates of LAI, and the results were generally acceptable. NPP estimates directly from the dynamic vegetation model and estimates obtained by combining the model estimates with remote sensing information were, on average, well simulated but too homogeneous among vegetation types when compared with field estimates using forest inventory data.

This review provides a synthesis of limnological data and conclusions from studies on ponds and small lakes at our research sites in Subarctic and Arctic Canada, Alaska, northern Scandinavia, and Greenland. Many of these water bodies contain large standing stocks of benthic microbial mats that grow in relatively nutrient-rich conditions, while the overlying water column is nutrient-poor and supports only low concentrations of phytoplankton. Zooplankton biomass can, however, be substantial and is supported by grazing on the microbial mats as well as detrital inputs, algae, and other plankton. In addition to large annual temperature fluctuations, a short growing season, and freeze-up and desiccation stress in winter, these ecosystems are strongly regulated by the supply of organic matter and its optical and biogeochemical properties. Dissolved organic carbon affects bacterial diversity and production, the ratio between pelagic and benthic primary productivity via light attenuation, and the exposure and photoprotection responses of organisms to solar ultraviolet radiation. Climate warming is likely to result in reduced duration of ice-cover, warmer water temperatures, and increased nutrient supplies from the more biogeochemically active catchments, which in turn may cause greater planktonic production. Predicted changes in the amount and origin of dissolved organic matter may favour increased microbial activity in the water column and decreased light availability for the phytobenthos, with effects on biodiversity at all trophic levels, and increased channelling of terrestrial carbon to the atmosphere in the form of greenhouse gases.

Abstract Climate change mitigation requires a shift from fossil energy resources to renewables, and bioenergy crops are considered one of the major potential resources. At the same time future energy supplies are expected to be sustainable, but the sustainability of energy crop production is challenged by concerns over its potential competition for arable land and disruption of food and feed markets. Protein in plant biomass is a challenge for sustainability, but also an opportunity. The challenge with protein is a disproportionately large land use foot print associated with its biosynthesis. Bioenergy exploits solar energy temporarily stored in biomass compounds such as carbohydrate, lipid, lignin, protein and organic acids. Here we review energy cost estimates for photosynthesis and growth and maintenance respiration and show – by comparing energy costs with the amount of energy stored in different plant compounds – that protein conservation could improve the sustainability of energy crop production by reducing land use impacts. The opportunity with protein in plant biomass comes from the fact that favored energy crops like switch grass, reed grass and Miscanthus are excellent protein producers on par with soybean and other protein-rich crops. Due to the scale of potential future bioenergy deployment we find that energy strategies involving large amounts of herbaceous energy crops will not be sustainable unless the proteins are conserved in some way.

Development of sustainable energy is a pivotal step towards solutions for today's global challenges, including mitigating the progression of climate change and reducing dependence on fossil fuels. Biofuels derived from agricultural crops have already been commercialized. However the impacts on environmental sustainability and food supply have raised ethical questions about the current practices. Cyanobacteria have attracted interest as an alternative means for sustainable energy productions. Being aquatic photoautotrophs they can be cultivated in non-arable lands and do not compete for land for food production. Their rich genetic resources offer means to engineer metabolic pathways for synthesis of valuable bio-based products. Currently the major obstacle in industrial-scale exploitation of cyanobacteria as the economically sustainable production hosts is low yields. Much effort has been made to improve the carbon fixation and manipulating the carbon allocation in cyanobacteria and their evolutionary photosynthetic relatives, algae and plants. This review aims at providing an overview of the recent progress in the bioengineering of carbon fixation and allocation in cyanobacteria; wherever relevant, the progress made in plants and algae is also discussed as an inspiration for future application in cyanobacteria.

The proliferation of ever-larger wind turbines poses risks to wildlife, especially from avian collision, yet avoidance behaviour of large-bodied, long-lived bird species in relation to wind turbines remains little studied away from collision "black spots" and offshore marine environments. Here, three-dimensional flight trajectory data are reported from a laser range-finder study of local movements of large-bodied birds (e.g. swans, geese, gulls, cormorants, raptors and cranes, whose populations are relatively more demographically sensitive to collision mortality) in relation to seven terrestrial 150-222 m high (mean 182 m) wind turbines constructed in Denmark in a N-S line. Comparisons of two-dimensional flight passages between turbines pre- (n = 287) and post-construction (n = 1210) showed significant (P 182 m) were significantly greater (P < 0.0001) post-construction than prior to construction. These are the first results from tracking large-bodied bird flight trajectories to show the magnitude of their vertical and horizontal adjustments to the presence of turbines, which have implications for assumptions of even flight densities made by collision risk models currently used to predict avian turbine collision rates.