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Climate change adds an additional layer of complexity to existing sustainable development and biodiversity conservation challenges. The impacts of global climate change are felt locally, and thus local governance structures will increasingly be responsible for preparedness and local responses. Ecosystem-based adaptation (EbA) options are gaining prominence as relevant climate change solutions. Local government officials seldom have an appropriate understanding of the role of ecosystem functioning in sustainable development goals, or access to relevant climate information. Thus the use of ecosystems in helping people adapt to climate change is limited partially by the lack of information on where ecosystems have the highest potential to do so. To begin overcoming this barrier, Conservation South Africa in partnership with local government developed a socio-ecological approach for identifying spatial EbA priorities at the sub-national level. Using GIS-based multi-criteria analysis and vegetation distribution models, the authors have spatially integrated relevant ecological and social information at a scale appropriate to inform local level political, administrative, and operational decision makers. This is the first systematic approach of which we are aware that highlights spatial priority areas for EbA implementation. Nodes of socio-ecological vulnerability are identified, and the inclusion of areas that provide ecosystem services and ecological resilience to future climate change is innovative. The purpose of this paper is to present and demonstrate a methodology for combining complex information into user-friendly spatial products for local level decision making on EbA. The authors focus on illustrating the kinds of products that can be generated from combining information in the suggested ways, and do not discuss the nuance of climate models nor present specific technical details of the model outputs here. Two representative case studies from rural South Africa demonstrate the replicability of this approach in rural and peri-urban areas of other developing and least developed countries around the world. [ABSTRACT FROM AUTHOR]

The Middle Stone Age (MSA) of southern Africa, and in particular its Still Bay and Howiesons Poort lithic traditions, represents a period of dramatic subsistence, cultural, and technological innovation by our species, Homo sapiens. Climate change has frequently been postulated as a primary driver of the appearance of these innovative behaviours, with researchers invoking either climate instability as a reason for the development of buffering mechanisms, or environmentally stable refugia as providing a stable setting for experimentation. Testing these alternative models has proved intractable, however, as existing regional palaeoclimatic and palaeoenvironmental records remain spatially, stratigraphically, and chronologically disconnected from the archaeological record. Here we report high-resolution records of environmental shifts based on stable carbon and oxygen isotopes in ostrich eggshell (OES) fragments, faunal remains, and shellfish assemblages excavated from two key MSA archaeological sequences, Blombos Cave and Klipdrift Shelter. We compare these records with archaeological material remains in the same strata. The results from both sites, spanning the periods 98–73 ka and 72–59 ka, respectively, show significant changes in vegetation, aridity, rainfall seasonality, and sea temperature in the vicinity of the sites during periods of human occupation. While these changes clearly influenced human subsistence strategies, we find that the remarkable cultural and technological innovations seen in the sites cannot be linked directly to climate shifts. Our results demonstrate the need for scale-appropriate, on-site testing of behavioural-environmental links, rather than broader, regional comparisons. [ABSTRACT FROM AUTHOR]

The seasonal occurrence of white sharks visiting Gansbaai, South Africa was investigated from 2007 to 2011 using sightings from white shark cage diving boats. Generalized linear models were used to investigate the number of great white sharks sighted per trip in relation to sex, month, sea surface temperature and Multivariate El Niño/Southern Oscillation (ENSO) Indices (MEI). Water conditions are more variable in summer than winter due to wind-driven cold water upwelling and thermocline displacement, culminating in colder water temperatures, and shark sightings of both sexes were higher during the autumn and winter months (March–August). MEI, an index to quantify the strength of Southern Oscillation, differed in its effect on the recorded numbers of male and female white sharks, with highly significant interannual trends. This data suggests that water temperature and climatic phenomena influence the abundance of white sharks at this coastal site. In this study, more females were seen in Gansbaai overall in warmer water/positive MEI years. Conversely, the opposite trend was observed for males. In cool water years (2010 to 2011) sightings of male sharks were significantly higher than in previous years. The influence of environmental factors on the physiology of sharks in terms of their size and sex is discussed. The findings of this study could contribute to bather safety programmes because the incorporation of environmental parameters into predictive models may help identify times and localities of higher risk to bathers and help mitigate human-white shark interactions. [ABSTRACT FROM AUTHOR]