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The transition to a low carbon future is starting to affect landscapes around the world. In order for this landscape transformation to be sustainable, renewable energy technologies should not cause critical trade-offs between the provision of energy and that of other ecosystem services such as food production. This literature review advances the body of knowledge on sustainable energy transition with special focus on ecosystem services-based approaches and methods. Two key issues emerge from this review: only one sixth of the published applications on the relation between renewable energy and landscape make use of the ecosystem service framework. Secondly, the applications that do address ecosystem services for landscape planning and design lack efficient methods and spatial reference systems that accommodate both cultural and regulating ecosystem services. Future research efforts should be directed to further advancing the spatial reference systems, the use of participatory mapping and landscape visualizations tools for cultural ecosystem services and the elaboration of landscape design principles.

Since 2007, a range of new modeling approaches and tools have been developed for sustainability impact assessment (SIA), but a lack of universal acceptance of SIA tools in applied policy making is observed. The current article gives an overview of experiences from several European and international projects, critically reviews the selected SIA tools and then discusses a number of reasons for the observed disconnect of the tools with the potential users. Largely based on the experiences of the presented SIA tools focusing land use policy advice, a decision tree is designed, which may facilitate an adequate, region and developmental phase specific selection of tool-box components for the development of SIA tools in future. Elements to ensure end-user participation are also integrated in the decision tree in order to increase the likelihood of the tool in applied land use policy advice. In addition, the Challenges in SIA tool development and use are further discussed.

The Vietnamese Mekong Delta (VMD) is one of the world’s most vulnerable deltas to climate change and sea level rise. Adequate understandings of future hydrological changes are crucial for effective water management and risk-proofing, however, this knowledge body is currently very limited. This study quantifies the responses of the VMD’s river flow regime to multiple stimuli, namely future upstream inflow variation, local climate change, and sea level rise. The one-dimensional hydrodynamic model MIKE 11 was used to simulate discharges and water levels across the delta. We developed four scenarios to represent changes in the upstream discharges, precipitation changes and sea level rise, covering the 2036–2065 period. We downscaled climate data and applied three bias-correction methods for five General Circulation Models (GCM), and two Representative Concentration Pathways (RCPs). The climate change projections show similar trends of increasing wet season precipitation and decreasing dry season precipitation. However, cross-scenario variations are sometimes large, depending on the individual GCMs, the RCPs and specific locations. The hydraulic simulation results indicate that, under discharge changes between −20% and +10%, combined with in-delta precipitation variations during the dry season, river discharges at the four representative stations could reduce substantially from −2.5% to −100.2%. During the wet season, the calculated river discharges show increase between 7.3% and 46.7% under four considered scenarios. Substantial changes in the VMD’s river flow regime could have potentially serious implications for water management, especially saltwater intrusion, and therefore calling for timely adaptation measures.

Estuaries are among the most valuable aquatic systems by their services to human welfare. However, increasing human activities at the watershed along with the pressure of climate change are fostering the co-occurrence of multiple environmental drivers, and warn of potential negative impacts on estuaries resources. At present, no clear understanding of how coastal ecosystems will respond to the non-stationary effect of multiple drivers. Here we analysed the temporal interaction among multiple environmental drivers and their changing priority on shaping phytoplankton response in the Bahía Blanca Estuary, SW Atlantic Ocean. The interaction among environmental drivers and the number of significant direct and indirect effects on chlorophyll concentration increased over time in concurrence with enhanced anthropogenic stress, changing winter climate and wind patterns. Over the period 1978-1993, proximal variables such as nutrients, water temperature and salinity, showed a dominant effect on chlorophyll, whereas in more recent years (1993-2009) climate signals (SAM and ENSO) boosted indirect effects through its influence on precipitation, wind, water temperature and turbidity. Turbidity emerged as the dominant driver of chlorophyll while in recent years acted synergistically with the concentration of dissolved nitrogen. As a result, chlorophyll concentration showed a significant negative trend and a loss of seasonal peaks reflecting a pronounced reorganisation of the phytoplankton community. We stress the need to account for the changing priority of drivers to understand, and eventually forecast, biological responses under projected scenarios of global anthropogenic change.

Available methods for measuring the impact of ocean acidification (OA) and leakage from carbon capture and storage (CCS) on marine sedimentary pH profiles are unsuitable for replicated experimental setups. To overcome this issue, a novel optical sensor application is presented, using off-the-shelf optode technology (MOPP). The application is validated using microprofiling, during a CCS leakage experiment, where the impact and recovery from a high CO2 plume was investigated in two types of natural marine sediment. MOPP offered user-friendliness, speed of data acquisition, robustness to sediment type, and large sediment depth range. This ensemble of characteristics overcomes many of the challenges found with other pH measuring methods, in OA and CCS research. The impact varied greatly between sediment types, depending on baseline pH variability and sediment permeability. Sedimentary pH profile recovery was quick, with profiles close to control conditions 24 h after the cessation of the leak. However, variability of pH within the finer sediment was still apparent 4 days into the recovery phase. Habitat characteristics need therefore to be considered, to truly disentangle high CO2 perturbation impacts on benthic systems. Impacts on natural communities depend not only on the pH gradient caused by perturbation, but also on other processes that outlive the perturbation, adding complexity to recovery.

Nest site selection is a critical behaviour, particularly in species with no parental care, as it can greatly impact offspring survival. Marine turtles depend on sandy beaches to nest, where they select from a range of microhabitats that may differently affect hatchling survival and phenotype. Here we describe the degree of nest site selection at one of the largest green turtle rookeries globally, in Guinea-Bissau, West Africa, and how this impacts offspring. In 2013 and 2014 we recorded the spatial distribution of 1559 nests, and monitored 657 females during oviposition, to assess population and individual preferences on nesting site. Overall, females tended to nest close to the vegetation, at a preferred elevation of 4.8–5.0 m, which was above the highest spring tide (4.7 m), enhancing clutch survival. Individuals displayed high repeatability in nesting microhabitat type (open sand, forest border and forest), distance along the beach, distance to the vegetation and elevation, which may result from this behaviour having a genetic basis or from fine-scale nest site philopatry. Hatchlings from cooler nests were larger, potentially dispersing faster and more able to evade predators, while smaller hatchlings, from warmer nests, retained more energetic reserves (residual yolk), which may also be advantageous for initial dispersal, particularly if food is scarce. Thus, individual preferences in nest site selection led to trade-offs in offspring phenotype, but overall, most nesting females selected sites that increased offspring survival, suggesting that nest site selection is an adaptive trait that has been under selection. As under future climate change scenarios females nesting in upper shaded areas should have higher fitness, individual consistency in nesting microhabitat provides opportunity for natural selection to occur.

The growing interest in forest biomass has made chipping increasingly popular all across Europe. Many operators have equipped for the purpose, but the large variety of working conditions found in the European forests makes it difficult to correctly estimate the productivity of each specific operation, leading to uncertainty in crucial decisions, such as: operation scheduling, price setting, machinery selection and acquisition. In 2001, the Italian National Council for Research (CNR) and the University of California (UC) developed a spreadsheet freeware capable of returning reliable estimates of chipping productivity and cost, on the basis of user-defined input data. The model is still available from the CNR website and is the object of frequent downloading and inquiries. Such model contains a set of predictive equations derived from the results of 102 field trials, conducted with 30 different machines, under a range of working conditions. In order to facilitate comparison with other estimates and to achieve methodological transparency, the equations are assembled into a simple Microsoft Excel workbook, and the costs are calculated with standard costing methods currently used in Forest and Agricultural Engineering. Since then CNR has continued to work on the subject, with the goal of updating and refining the model. Such work has included 45 validation tests and a separate study on the delay (idle) time typical for different chipping operation layouts. The study was concluded in 2009 and confirms that the model developed by CNR can provide reliable estimates of chipper productivity under a range of operational conditions. Authors believe that such a model can assist European foresters in keeping ahead with the growing biomass sector, thus helping them to seize an important business opportunity.