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Research on using climate information has often focused on the interaction between users and producers and the technical fit of information for real decision-making. However, due to resource and capacity constraints within both user and producer communities, this approach will not always be feasible or indeed necessary depending on the decisions at hand. These contexts have been relatively under-explored by scholars, and this paper provides an original empirical contribution using three case studies of sub-national governments in India, Kenya and Uganda. In the paper, we analyse how social learning supports changing the usability of climate information and the role of intermediary organisations in these processes. Firstly, the paper shows that intermediaries often choose to build the commitment to project aims rather than using climate information as an entry point to working on climate change, and this allows them to instigate challenging learning processes. Secondly, there are barriers to iterative processes and critical reflection with government stakeholders but these processes can gain traction when built into institutional practices such as formal M&E processes. Lastly, social learning can broaden the framing of climate change from a single sector issue to a multi-sectoral one. We conclude by arguing that bringing together scholarship on social learning with that on the usability of climate information can deepen understanding of the dynamic context in which the information becomes usable. The evidence from the case studies shows that learning processes can alter this context across scales. [ABSTRACT FROM AUTHOR]

Almost all climate change studies of plants and animals adopt an 'equilibrium assumption' that analyses of natural distributions provide reliable estimates of species climatic requirements. Yet commercial forestry trials around the world have shown that many tree species can grow successfully under climatic conditions somewhat different from those of their natural distributions. Under climate change it is reasonable to assume that a long-lived tree species, already well-established at particular sites, may be able to display some of the climatic adaptability shown in trials outside its natural distribution. The purpose of this paper is to outline how some species distribution modelling (SDM) and ecological niche modelling (ENM) studies have estimated species climatic requirements beyond those shown by conventional analyses of just their natural distributions, and to show how recent developments are facilitating these analyses. Some of the earliest SDM studies of trees demonstrated the desirability of assessing species climatic requirements using data from outside, as well as within, their natural distributions. In recent years, with the advent of large biodiversity databases and some revised SDM analysis methods, there has been a revival of interest in measuring species climatic requirements using data from beyond their realized niches. It is recommended that at least for tree species, natural distribution data, and where possible results from plantings beyond natural distributions, should be analysed in climate change studies. When this is not possible, some alternative methods of estimating species climatic requirements are identified and some of their advantages and disadvantages are considered. [ABSTRACT FROM AUTHOR]

Adaptation and mitigation are complementary strategies for addressing the impacts of climate change, yet are often considered separately. This paper examines the literature for evidence of the interactions of adaptation and mitigation measures across the agriculture, biodiversity, coasts, forests, urban and water sectors, focusing on Europe. It found that often adaptation and mitigation synergies and conflicts were not explicitly mentioned within a sector, let alone between sectors. Most measures, however, were found to have an effect on another sector, resulting in neutral, positive (synergies) or negative (conflicts) interactions within and between sectors. Many positive cross-sectoral interactions involved biodiversity or water and thus these could represent good starting places for the implementation of integrated, cross-sectoral strategies. Previous studies suggest that adaptation and mitigation are undertaken on different time and geographical scales; this study found many local scale measures which could facilitate integration between both adaptation and mitigation. It is important that cross-sectoral interaction of adaptation and mitigation measures are explicitly recognised if they are to be mainstreamed into policy, so that positive outcomes are enhanced and unintended consequences avoided. [ABSTRACT FROM AUTHOR]

Integrated cross-sectoral impact assessments facilitate a comprehensive understanding of interdependencies and potential synergies, conflicts, and trade-offs between sectors under changing conditions. This paper presents a sensitivity analysis of a European integrated assessment model, the CLIMSAVE integrated assessment platform (IAP). The IAP incorporates important cross-sectoral linkages between six key European land- and water-based sectors: agriculture, biodiversity, flooding, forests, urban, and water. Using the IAP, we investigate the direct and indirect implications of a wide range of climatic and socio-economic drivers to identify: (1) those sectors and regions most sensitive to future changes, (2) the mechanisms and directions of sensitivity (direct/indirect and positive/negative), (3) the form and magnitudes of sensitivity (linear/non-linear and strong/weak/insignificant), and (4) the relative importance of the key drivers across sectors and regions. The results are complex. Most sectors are either directly or indirectly sensitive to a large number of drivers (more than 18 out of 24 drivers considered). Over twelve of these drivers have indirect impacts on biodiversity, forests, land use diversity, and water, while only four drivers have indirect effects on flooding. In contrast, for the urban sector all the drivers are direct. Moreover, most of the driver-indicator relationships are non-linear, and hence there is the potential for 'surprises'. This highlights the importance of considering cross-sectoral interactions in future impact assessments. Such systematic analysis provides improved information for decision-makers to formulate appropriate adaptation policies to maximise benefits and minimise unintended consequences. [ABSTRACT FROM AUTHOR]