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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.

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 repercussions of climate change will be felt in various ways throughout both natural and human systems in Sub-Saharan Africa. Climate change projections for this region point to a warming trend, particularly in the inland subtropics; frequent occurrence of extreme heat events; increasing aridity; and changes in rainfall—with a particularly pronounced decline in southern Africa and an increase in East Africa. The region could also experience as much as one meter of sea-level rise by the end of this century under a 4 °C warming scenario. Sub-Saharan Africa’s already high rates of undernutrition and infectious disease can be expected to increase compared to a scenario without climate change. Particularly vulnerable to these climatic changes are the rainfed agricultural systems on which the livelihoods of a large proportion of the region’s population currently depend. As agricultural livelihoods become more precarious, the rate of rural–urban migration may be expected to grow, adding to the already significant urbanization trend in the region. The movement of people into informal settlements may expose them to a variety of risks different but no less serious than those faced in their place of origin, including outbreaks of infectious disease, flash flooding and food price increases. Impacts across sectors are likely to amplify the overall effect but remain little understood.

As a fast-growing food production industry, aquaculture is dealing with the need for intensification due to the global increasing demand for fish products. However, this also implies the use of more sustainable practices to reduce negative environmental impacts currently associated with this industry, including the use of wild resources, destruction of natural ecosystems, eutrophication of effluent receiving bodies, impacts due to inadequate medication practices, among others. Using multi-species systems, such as integrated multi-trophic aquaculture, allows to produce economically important species while reducing some of these aquaculture concerns, through biomitigation of aquaculture wastes and reduction of diseases outbreaks, for example. Applying mathematical models to these systems is crucial to control and understand the interactions between species, maximizing productivity, with important environmental and economic benefits. Here, the application of some equations and models available in the literature, regarding basic parameters, is discussed – population dynamics, growth, waste production, and filtering rate – when considering the description and optimization of a theoretical integrated multi-trophic aquaculture operation composed by three trophic levels.

This work examines the causal relationship between the value of the ground–air temperature offset and the precipitation changes for monitored 5-min data series together with their hourly and daily averages obtained at the Sporilov Geophysical Observatory (Prague). Shallow subsurface soil temperatures were monitored under four different land cover types (bare soil, sand, short-cut grass and asphalt). The ground surface temperature (GST) and surface air temperature (SAT) offset, ΔT(GST–SAT), is defined as the difference between the temperature measured at the depth of 2 cm below the surface and the air temperature measured at 5 cm above the surface. The results of the Granger causality test did not reveal any evidence of Granger causality for precipitation to ground–air temperature offsets on the daily scale of aggregation except for the asphalt pavement. On the contrary, a strong evidence of Granger causality for precipitation to the ground–air temperature offsets was found on the hourly scale of aggregation for all land cover types except for the sand surface cover. All results are sensitive to the lag choice of the autoregressive model. On the whole, obtained results contain valuable information on the delay time of ΔT(GST–SAT) caused by the rainfall events and confirmed the importance of using autoregressive models to understand the ground–air temperature relationship.