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Wild animals are used for research and management purposes in Sweden and throughout the world. Animals are often subjected to similar procedures and risks of compromised welfare from capture, anesthesia, handling, sampling, marking, and sometimes selective removal. The interpretation of the protection of animals used for scientific purposes in Sweden is based on the EU Directive 2010/63/EU. The purpose of animal use, irrespective if the animal is suffering or not, decides the classification as a research animal, according to Swedish legislation. In Sweden, like in several other European countries, the legislation differs between research and management. Whereas, animal research is generally well-defined and covered in the legislation, wildlife management is not. The protection of wild animals differs depending on the procedure they are subjected to, and how they are classified. In contrast to wildlife management activities, research projects have to implement the 3Rs and must undergo ethical reviews and official animal welfare controls. It is often difficult to define the dividing line between the two categories, e.g., when marking for identification purposes. This gray area creates uncertainty and problems beyond animal welfare, e.g., in Sweden, information that has been collected during management without ethical approval should not be published. The legislation therefore needs to be harmonized. To ensure consistent ethical and welfare assessments for wild animals at the hands of humans, and for the benefit of science and management, we suggest that both research and management procedures are assessed by one single Animal Ethics Committee with expertise in the 3Rs, animal welfare, wildlife population health and One Health. We emphasize the need for increased and improved official animal welfare control, facilitated by compatible legislation and a similar ethical authorization process for all wild animal procedures.

Adaptation research and practice too often overlooks the wider social context within which climate change is experienced. Mainstream approaches frame adaptation problems in terms of the consequences that flow from biophysical impacts and as a result, we argue, ask the wrong questions. A complementary approach gaining ground in the field, foregrounding the social, economic and political context, reveals differentiation in adaptation need, and how climate impacts interconnect with wider processes of change. In this paper, we illustrate how this kind of approach frames a different set of questions about adaptation using the case of Nepal. Drawing on fieldwork and a review of literature, we contrast the questions that emerge from adaptation research and practice that take climate risk as a starting point with the questions that emerge from examination of contemporary rural livelihoods. We find that while adaptation efforts are often centred around securing agricultural production and are predicated on climate risk management, rural livelihoods are caught in a wider process of transformation. The numbers of people involved in farming are declining, and households are experiencing the effects of rising education, abandonment of rural land, increasing wages, burgeoning mechanisation, and high levels of migration into the global labour market. We find the epistemological framing of adaptation too narrow to account for these changes, as it understands the experiences of rural communities through the lens of climate risk. We propose that rather than seeking to integrate local understandings into a fixed, impacts-orientated epistemology, it is necessary to premise adaptation on an epistemology capable of exploring how change occurs. Asking the right questions thus means opening up adaptation by asking: 'what are the most significant changes taking place in people's lives?', along with the more standard: 'what are the impacts of climate change?' Viewing adaptation as occurring between and within these two perspectives has the potential to reveal new vulnerabilities and opportunities for adaptation practice to act upon.

With continued pressure on biodiversity and ever-growing conflicts with human development, qualified systems for scenario modelling, impact assessment and decision support are urgently needed. Such systems must be able to integrate complex models and information from many sources and do so in a flexible and transparent way. To that end, as well as for other complicated and data-intensive biodiversity research purposes, the concept of LifeWatch has emerged. The idea of LifeWatch is to construct e-infrastructure and virtual laboratories by integrating large data sources, computational capacities, and tools for analysis and modelling in an open, serviceoriented architecture. To be efficient and accurate, a continuous inflow of large quantities of data is essential. However, even with new techniques, government-funded monitoring data and research data will not feed the system with up-to-date species information of sufficient scale and resolution. To fill this void, skilled amateur observers (citizen scientists) can contribute to a very valuable extent. After a preparatory phase, a Swedish LifeWatch (SLW) consortium was initiated in 2011. Swedish LifeWatch developed an infrastructure where all components are accessible through open web services. At the SLW Analysis portal, different formats of species and environmental data can be accessed instantly, and integrated, analysed, visualized and downloaded at selected temporal, spatial or taxonomic scales. Swedish LifeWatch currently provides 46 million species observations from eight different databases, all harmonized according to standardized formats and the Dyntaxa taxonomic backbone database. Almost 40 million of these observations were provided by citizens through the online reporting system named the Species Observation System (SOS) or Artportalen. This paper describes this system, as well as the incentives that make it so successful. The citizen science data in the SOS are accessible, together with data from research and monitoring, in the SLW infrastructure, making the latter a powerful instrument for large-scale data extraction, visualization and analysis.