Suchergebnisse

This rapid climate risk assessment for the Southern Africa Development Community (SADC) uses the Intergovernmental Panel on Climate Change (IPCC) 2014 risk analysis framework to assess the distribution of climate hazards and social and biophysical vulnerability to those hazards in order to identify climate risk hotspots. The assessment uses regional climate models from CORDEX-Africa to map rainfall extremes and drought hazards to 2031–2059. Ten social and biophysical vulnerability indicators are identified from across the capital assets (human, physical, social, financial, natural), using data from the Global Multidimensional Poverty Index (MPI), to develop a vulnerability index. The vulnerability index and distribution of climate hazards are mapped to identify hotspots. Hotspots of vulnerability to and risk of extreme rainfall are shown in northern Madagascar and in south west Tanzania, under both the RCP4.5 and 8.5 scenarios. These hotspots also correspond to the hotspots for drought risk under RCP4.5 and 8.5. However, it is clear that medium-high climate risk (high vulnerability, medium-high climate hazard) is widespread across Angola, Democratic Republic of the Congo (DRC), Tanzania, Mozambique, and Madagascar.

Context Recovery of Australian rabbit populations from the impact of rabbit haemorrhagic disease virus (RHDV) contrasts with more prolonged suppression of wild rabbits in Europe, and has been widely discussed in the scientific community, but not yet documented in formal scientific literature. The underlying causes of recovery remain unclear, but resistance to RHDV infection has been reported in laboratory studies of wild-caught rabbits. Aims We document numerical changes in two South Australian wild rabbit populations that were initially suppressed by RHDV, and examine serological data to evaluate several alternative hypotheses for the cause of recovery. Methods Rabbit numbers were assessed from spotlight transect counts and dung mass transects between 1991 and 2011, and age and RHDV antibody sero-prevalence were estimated from rabbits shot in late summer. Key results Rabbit numbers were heavily suppressed by RHDV between 1995 and 2002, then increased 5- to 10-fold between 2003 and 2010. During the period of increase, annual RHDV infection rates remained stable or increased slightly, average age of rabbits remained stable and annual rainfall was below average. Conclusions Rabbit populations recovered but neither avoidance of RHDV infection, gradual accumulation of long-lived RHD-immune rabbits, nor high pasture productivity were contributing factors. This leaves increased annual survival from RHDV infection as the most likely cause of recovery. Implications Previously documented evidence of resistance to RHDV infection may be of little consequence to post-RHD recovery in rabbit numbers, unless the factors that influence the probability of infection also shape the course of infection and affect survival of infected rabbits.

This corrigendum should replace the corresponding section 8.4 of the 38 th Plenary meeting report of the Scientific, Technical and Economic Committee for Fisheries (PLEN-11-03). Publications Office of the European Union, Luxembourg, EUR 25033 EN, JRC67714.

6 pages, 5 figures, supporting information https://doi.org/10.1073/pnas.1900194116.-- All data reported in this paper are archived and publicly available at http://dataservices.gfz-potsdam.de/pik/showshort.php?id=escidoc:2956913. ; While the physical dimensions of climate change are now routinely assessed through multimodel intercomparisons, projected impacts on the global ocean ecosystem generally rely on individual models with a specific set of assumptions. To address these single-model limitations, we present standardized ensemble projections from six global marine ecosystem models forced with two Earth system models and four emission scenarios with and without fishing. We derive average biomass trends and associated uncertainties across the marine food web. Without fishing, mean global animal biomass decreased by 5% (±4% SD) under low emissions and 17% (±11% SD) under high emissions by 2100, with an average 5% decline for every 1 °C of warming. Projected biomass declines were primarily driven by increasing temperature and decreasing primary production, and were more pronounced at higher trophic levels, a process known as trophic amplification. Fishing did not substantially alter the effects of climate change. Considerable regional variation featured strong biomass increases at high latitudes and decreases at middle to low latitudes, with good model agreement on the direction of change but variable magnitude. Uncertainties due to variations in marine ecosystem and Earth system models were similar. Ensemble projections performed well compared with empirical data, emphasizing the benefits of multimodel inference to project future outcomes. Our results indicate that global ocean animal biomass consistently declines with climate change, and that these impacts are amplified at higher trophic levels. Next steps for model development include dynamic scenarios of fishing, cumulative human impacts, and the effects of management measures on future ocean biomass trends ; Financial support was provided by the German Federal Ministry of Education and Research through ISI-MIP (Grant01LS1201A1), the European Union's Horizon 2020 Research and Innovation Program (Grant 678193), and the Ocean Frontier Institute (Module G). We acknowledge additional financial support as follows: to H.K.L., W.W.L.C., and B.W. from the Natural Sciences and Engineering Research Council (NSERC) of Canada; to D.P.T. from the Kanne Rasmussen Foundation Denmark; to A.B.-B. from the NSERC Transatlantic Ocean Science and Technology Program; to W.W.L.C. and T.D.E. from the Nippon Foundation-Nereus Program; to E.D.G., M.C. and J. Steenbeek from the European Union's Horizon 2020 Re-search and Innovation Program (Grants 682602 and 689518); to E.A.F., J.L.B., andT.R. from Commonwealth Scientific and Industrial Research Organization and the Australian Research Council; to N.B., L.B., and O.M. from the French Agence Nationale de la Recherche and Pôle de Calcul et de Données pour la Mer; and to S.J. from the UK Department of Environment, Food and Rural Affairs ; Peer Reviewed

Not Available ; Many coastal communities rely on living marine resources for livelihoods and food security. These resources are commonly under stress from overfishing, pollution, coastal development and habitat degradation. Climate change is an additional stressor beginning to impact coastal systems and communities, but may also lead to opportunities for some species and the people they sustain. We describe the research approach for a multi-country project, focused on the southern hemisphere, designed to contribute to improving fishing community adaptation efforts by characterizing, assessing and predicting the future of coastal-marine food resources, and codeveloping adaptation options through the provision and sharing of knowledge across fast-warming marine regions (i.e. marine 'hotspots'). These hotspots represent natural laboratories for observing change and concomitant human adaptive responses, and for developing adaptation options and management strategies. Focusing on adaptation options and strategies for enhancing coastal resilience at the local level will contribute to capacity building and local empowerment in order to minimise negative outcomes and take advantage of opportunities arising from climate change. However, developing comparative approaches across regions that differ in political institutions, socio-economic community demographics, resource dependency and research capacity is challenging. Here, we describe physical, biological, social and governance tools to allow hotspot comparisons, and several methods to evaluate and enhance interactions within a multi-nation research team. Strong partnerships within and between the focal regions are critical to scientific and political support for development of effective approaches to reduce future vulnerability. Comparing these hotspot regions will enhance local adaptation responses and generate outcomes applicable to other regions. ; Not Available