Impact of Climate Change on Fish Population Dynamics in the Baltic Sea: A Dynamical Downscaling Investigation

Understanding how climate change, exploitation and eutrophication will affect populations and ecosystems of the Baltic Sea can be facilitated with models which realistically combine these forcings into common frameworks. Here, we evaluate sensitivity of fish recruitment and population dynamics to past and future environmental forcings provided by three ocean-biogeochemical models of the Baltic Sea. Modeled temperature explained nearly as much variability in reproductive success of sprat (Sprattus sprattus; Clupeidae) as measured temperatures during 1973-2005, and both the spawner biomass and the temperature have influenced recruitment for at least 50 years. The three Baltic Sea models estimate relatively similar developments (increases) in biomass and fishery yield during twenty-first century climate change (ca. 28 % range among models). However, this uncertainty is exceeded by the one associated with the fish population model, and by the source of global climate data used by regional models. Knowledge of processes and biases could reduce these uncertainties.     

Future land-use change scenarios for the Black Sea catchment

Plausible future scenarios have been created for the Black Sea catchment, focussing on spatially explicit alternatives for land-use changes. Four qualitative storylines (HOT, ALONE, COOP and COOL) were first developed, based on interpretation of the respective global scenarios (A1, A2, B1 and B2) produced by the Intergovernmental Panel on Climate Change. Quantitative statistical downscaling techniques were then used to disaggregate the outputs of global scenarios at a regional level. The resulting land-use maps were spatially allocated at 1 km resolution in the Metronamica model, using a set of factors related to the identified drivers of change. The land-use change model was calibrated on historical trends of land-cover change (MODIS 2001 and 2008) translated into spatial allocation rules, and future land-use projections (IMAGE, 2001) were adopted. Suitability and constraint maps and population trends were used to regulate the modelling process. The calibrated model was validated by statistical procedures, visual evaluation and stakeholder involvement in order to ensure its plausibility and accuracy. This methodology bridged the gap between the global and regional scales. Four simulated future states were produced for the main land-use classes–forest, grassland, cropland and built-up areas, as well as scrublands, crops/natural vegetation and barren land–for 2025 and 2050. The results suggest that the features highlighted in these scenarios are guided by global trends, such as population rise and decreasing agriculture, but with different growth rates and a variety of spatial patterns, with regional variations resulting from local backgrounds and policy objectives. This study aims to provide future land-use data as a potential geographical tool to assist policy makers in addressing environmental emergencies such as water stress and pollution. In particular, the exploration of plausible futures can support future assessments to comply with the EU Water Framework Directive and Integrated Coastal Zone Management policies around the Black Sea.     

Assessment of future scenarios of climate and land-use changes in the IMPRINTS test-bed areas

The main objective of this work is to identify and evaluate the potential impacts produced by climate and land-use changes in six European test-bed basins (Llobregat, Guadalhorce, Gardon d’Anduze, Linth, Verzasca and Sambuco). Data to build future scenarios that can modify the different basins’ flash flood and debris flow risk level has been analyzed in this paper. High resolution climate scenarios have been obtained from several European projects and/or National initiatives, depending on each case. Climatic variables have been widely analyzed, with a special focus on extreme precipitation. Typical generalized extreme value (GEV) distributions have been fitted to observed and projected rainfall data to assess impacts in the frequency distributions of extreme rainfall up to 2100. Regarding climate, the main conclusion is the importance of using data at the maximum spatial and temporal resolution applying downscaling methodologies adapted to basin scale (test-bed areas ranging from approx 200 to 5000 km²) and oriented to obtain extreme rainfall values.In general, high variability has been detected, obtaining very different results for the different models and scenarios. Data corrections may lead to better representations of present situations and, therefore, more reliable future projections, but currently some of them are not suitable for extreme precipitation assessment.Regarding land-use changes, a cellular automata-based model has been used (MOLAND) to simulate the 2000–2040 period taking the CORINE land-use dataset as input data. Llobregat, Guadalhorce and Gardon d’Anduze basins have been identified as potentially interesting for simulating urban land-use dynamics due to the existence of important urban areas within their limits. The assessment of the rural land-use changes has been carried out using the results from the EURURALIS project (2000–2030 period), available for all the basins.The results of this paper are framed in the FP7 project IMPRINTS that has the aim of analyzing impacts of future changes to provide guidelines for mitigation and adaptation measures and, in general, to improve the application of the EC Flood Risk Management Directive.     

Projecting Canadian Prairie Runoff for 2041–2070 with North American Regional Climate Change Assessment Program (NARCCAP) Data

The South Saskatchewan River Basin (SSRB) of Alberta, Canada, is semiarid and under severe water stress due to increasing human demands. We present the first examination of projected changes in SSRB runoff from a large set of North American Regional Climate Change Assessment Program regional climate models (RCMs) plus one Coordinated Regional Climate Downscaling Experiment RCM. We used six different runoff estimation methods: total surface and subsurface runoff (total runoff), surface runoff, and four estimations based on Budyko functions. Most RCM estimations showed substantial biases and distribution differences when compared to observed data; thus bias correction was necessary. Total runoff was the best of the six variables in modeling observed runoff for each of the four SSRB subbasins. Projected total runoff for 2041–2070 shows a geographic gradient in the SSRB, with possible drying in the southern Oldman River subbasin and possible increased runoff in the northernmost Red Deer River subbasin. A shift to an earlier spring peak in runoff and drier late summer, with a need for increased irrigation, should be expected. In a first examination of the important question of projected changes in interannual variability, we show increasing magnitude. This result further adds to adaptation challenges over the course of this century in this basin, which is already largely closed to further allocation.