Public Perceptions of Climate Change and Its Health Impacts : Taking Account of People’s Exposure to Floods and Air Pollution

Climate change-related exposures such as flooding and ambient air pollution place people’s health at risk. A representative UK survey of adults investigated associations between reported flooding and air pollution (in the participants’ local area, by the participant personally, and/or by family and close friends) and climate change concerns (CCC) and perceptions of its health impacts (PIH). In regression analyses controlling for socio-demographic factors and health status, exposure was associated with greater CCC and more negative PIH. Compared to those with low CCC, participants who reported local-area exposure were significantly more likely to be fairly (OR 2.07, 95%CI 1.26, 3.40) or very concerned (OR 3.40, 95%CI 2.02, 5.71). Odds of greater CCC were higher for those reporting personal and/or family exposure (‘fairly concerned’: OR 2.83, 95%CI 1.20, 6.66; ‘very concerned’: OR 4.11, 95%CI 1.69, 10.05) and for those reporting both local and personal/family exposure (‘fairly concerned’: OR 3.35, 95%CI 1.99, 5.63; ‘very concerned’: OR 6.17, 95%CI 3.61, 10.55). For PIH, local exposure significantly increased the odds of perceiving impacts as ‘more bad than good’ (1.86, 95%CI 1.22, 2.82) or ‘entirely bad’ (OR 1.88; 95%CI 1.13, 3.13). Our study suggests that public awareness of climate-related exposures in their local area, together with personal exposures and those of significant others, are associated with heightened concern about climate change and its health impacts

Supporting local diversity of habitats and species on farmland: a comparison of three wildlife-friendly schemes

Restoration and maintenance of habitat diversity have been suggested as conservation priorities in farmed landscapes, but how this should be achieved and at what scale are unclear. This study makes a novel comparison of the effectiveness of three wildlife-friendly farming schemes for supporting local habitat diversity and species richness on 12 farms in England. The schemes were: (i) Conservation Grade (Conservation Grade: a prescriptive, non-organic, biodiversity-focused scheme), (ii) organic agriculture and (iii) a baseline of Entry Level Stewardship (Entry Level Stewardship: a flexible widespread government scheme). Conservation Grade farms supported a quarter higher habitat diversity at the 100-m radius scale compared to Entry Level Stewardship farms. Conservation Grade and organic farms both supported a fifth higher habitat diversity at the 250-m radius scale compared to Entry Level Stewardship farms. Habitat diversity at the 100-m and 250-m scales significantly predicted species richness of butterflies and plants. Habitat diversity at the 100-m scale also significantly predicted species richness of birds in winter and solitary bees. There were no significant relationships between habitat diversity and species richness for bumblebees or birds in summer. Butterfly species richness was significantly higher on organic farms (50% higher) and marginally higher on Conservation Grade farms (20% higher), compared with farms in Entry Level Stewardship. Organic farms supported significantly more plant species than Entry Level Stewardship farms (70% higher) but Conservation Grade farms did not (10% higher). There were no significant differences between the three schemes for species richness of bumblebees, solitary bees or birds. Policy implications. The wildlife-friendly farming schemes which included compulsory changes in management, Conservation Grade and organic, were more effective at increasing local habitat diversity and species richness compared with the less prescriptive Entry Level Stewardship scheme. We recommend that wildlife-friendly farming schemes should aim to enhance and maintain high local habitat diversity, through mechanisms such as option packages, where farmers are required to deliver a combination of several habitats

Larval dispersal and fishing pressure influence recruitment in a coral reef fishery

Understanding larval connectivity patterns in exploited fishes is a fundamental prerequisite for developing effective management strategies and assessing the vulnerability of a fishery to recruitment overfishing and localised extinction. To date, however, researchers have not considered how regional variations in fishing pressure also influence recruitment. We used genetic parentage analyses and modelling to infer the dispersal patterns of bumphead parrotfish Bolbometopon muricatum larvae in the Kia fishing grounds, Isabel Province, Solomon Islands. We then extrapolated our Kia dispersal model to a regional scale by mapping the available nursery and adult habitat for B. muricatum in six regions in the western Solomon Islands, and estimated the relative abundance of adult B. muricatum populations in each of these regions based on available adult habitat and historical and current fishing pressure. Parentage analysis identified 67 juveniles that were the offspring of parents sampled in the Kia fishing grounds. A fitted larval dispersal kernel predicted that 50% of larvae settled within 30 km of their parents, and 95% settled within 85 km of their parents. After accounting for unsampled adults, our model predicted that 34% of recruitment to the Kia fishery was spawned locally. Extrapolating the spatial resolution of the model revealed that a high proportion of the larvae recruiting into the Kia fishing grounds came from nearby regions that had abundant adult populations. Other islands in the archipelago provided few recruits to the Kia fishing grounds, reflecting the greater distances to these islands and lower adult abundances in some regions. Synthesis and applications. This study shows how recruitment into a coral reef fishery is influenced by larval dispersal patterns and regional variations in historical fishing pressure. The scales of larval connectivity observed for bumphead parrotfish indicate that recruitment overfishing is unlikely if there are lightly exploited reefs up to 85 km away from a heavily fished region, and that small (<1 km2) marine-protected areas (MPAs) are insufficient to protect this species. We recommend greater efforts to understand the interactions between larval dispersal and gradients of fishing pressure, as this will enable the development of tailored fisheries management strategies

Ecological implications of a flower size/number trade-off in tropical forest trees

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How Modelers Model: the Overlooked Social and Human Dimensions in Model Intercomparison Studies

There is a growing realization that the complexity of model ensemble studies depends not only on the models used but also on the experience and approach used by modelers to calibrate and validate results, which remain a source of uncertainty. Here, we applied a multi-criteria decision-making method to investigate the rationale applied by modelers in a model ensemble study where 12 process-based different biogeochemical model types were compared across five successive calibration stages. The modelers shared a common level of agreement about the importance of the variables used to initialize their models for calibration. However, we found inconsistency among modelers when judging the importance of input variables across different calibration stages. The level of subjective weighting attributed by modelers to calibration data decreased sequentially as the extent and number of variables provided increased. In this context, the perceived importance attributed to variables such as the fertilization rate, irrigation regime, soil texture, pH, and initial levels of soil organic carbon and nitrogen stocks was statistically different when classified according to model types. The importance attributed to input variables such as experimental duration, gross primary production, and net ecosystem exchange varied significantly according to the length of the modeler’s experience. We argue that the gradual access to input data across the five calibration stages negatively influenced the consistency of the interpretations made by the modelers, with cognitive bias in “trial-and-error” calibration routines. Our study highlights that overlooking human and social attributes is critical in the outcomes of modeling and model intercomparison studies. While complexity of the processes captured in the model algorithms and parameterization is important, we contend that (1) the modeler’s assumptions on the extent to which parameters should be altered and (2) modeler perceptions of the importance of model parameters are just as critical in obtaining a quality model calibration as numerical or analytical details.info:eu-repo/semantics/acceptedVersio

Collaborative approaches in initial teacher education: lessons from approaches to developing student teachers’ use of the Internet in science teaching

In many countries, governments are keen to persuade teachers at all levels to seek to enhance the learning of their students by incorporating information and communication technologies within their classrooms. This paper reports on the development of collaborative approaches to supporting use of the Internet by Post Graduate Certificate of Education (PGCE) science students on initial teacher education (ITE) courses in England, drawing on data from five higher education institution (HEI)–school partnerships across four years. A mixed-method approach was used, involving questionnaires, structured interviews, lesson observations and case studies. The outcomes of the first three years identified barriers to practice and suggested the need to develop more collaborative approaches to development. The focus of this paper is on examining ways in which university faculty tutors and mentors or cooperating teachers can work together with students on PGCE courses in developing practice. The lessons from this focus on the Internet, no longer a new technology, have enabled us to identify implications for HEI partnerships in ITE and suggest a need for further collaborative structures in order to support and develop practices, including those involving the innovative use of new technologies in the post-industrial society

Ensemble modelling, uncertainty and robust predictions of organic carbon in long-term bare-fallow soils

ACKNOWLEDGEMENTS This study was supported by the project “C and N models inter-comparison and improvement to assess management options for GHG mitigation in agro-systems worldwide” (CN-MIP, 2014- 2017), which received funding by a multi-partner call on agricultural greenhouse gas research of the Joint Programming Initiative ‘FACCE’ through national financing bodies. S. Recous, R. Farina, L. Brilli, G. Bellocchi and L. Bechini received mobility funding by way of the French Italian GALILEO programme (CLIMSOC project). The authors acknowledge particularly the data holders for the Long Term Bare-Fallows, who made their data available and provided additional information on the sites: V. Romanenkov, B.T. Christensen, T. Kätterer, S. Houot, F. van Oort, A. Mc Donald, as well as P. Barré. The input of B. Guenet and C. Chenu contributes to the ANR “Investissements d’avenir” programme with the reference CLAND ANR-16-CONV-0003. The input of P. Smith and C. Chenu contributes to the CIRCASA project, which received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement no 774378 and the projects: DEVIL (NE/M021327/1) and Soils‐R‐GRREAT (NE/P019455/1). The input of B. Grant and W. Smith was funded by Science and Technology Branch, Agriculture and Agri-Food Canada, under the scope of project J-001793. The input of A. Taghizadeh-Toosi was funded by Ministry of Environment and Food of Denmark as part of the SINKS2 project. The input of M. Abdalla contributes to the SUPER-G project, which received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement no 774124.Peer reviewedPostprin