Adaptation options for marine industries and coastal communities using community structure and dynamics

Identifying effective adaptation strategies for coastal communities dependent on marine resources and impacted by climate change can be difficult due to the dynamic nature of marine ecosystems. The task is more difficult if current and predicted shifts in social and economic trends are considered. Information about social and economic change is often limited to qualitative data. A combination of qualitative and quantitative models provide the flexibility to allow the assessment of current and future ecological and socio-economic risks and can provide information on alternative adaptations. Here, we demonstrate how stakeholder input, qualitative models and Bayesian belief networks (BBNs) can provide semi-quantitative predictions, including uncertainty levels, for the assessment of climate and non-climate-driven change in a case study community. Issues are identified, including the need to increase the capacity of the community to cope with change. Adaptation strategies are identified that alter positive feedback cycles contributing to a continued decline in population, local employment and retail spending. For instance, the diversification of employment opportunities and the attraction of new residents of different ages would be beneficial in preventing further population decline. Some impacts of climate change can be combated through recreational bag or size limits and monitoring of popular range-shifted species that are currently unmanaged, to reduce the potential for excessive removal. Our results also demonstrate that combining BBNs and qualitative models can assist with the effective communication of information between stakeholders and researchers. Furthermore, the combination of techniques provides a dynamic, learning-based, semi-quantitative approach for the assessment of climate and socio-economic impacts and the identification of potential adaptation strategies.     

Development and Use of a Sedimentation Risk Index for Unpaved Road‐Stream Crossings in the Choctawhatchee Watershed1

Abstract: Unpaved road‐stream crossings increase sediment yields in streams and alter channel morphology and stability. Before restoration and sedimentation reduction strategies can be implemented, a priority listing of unpaved road‐stream crossings must be created. The objectives of this study were to develop a sedimentation risk index (SRI) for unpaved road‐stream crossings and to prioritize 125 sites in the Choctawhatchee watershed (southeastern Alabama) using this model. Field surveys involved qualitative and quantitative observations of 73 metrics related to waterway conditions, crossing structures, road approaches, and roadside soil erosion. The road‐stream crossing risk analyses involved elimination of candidate metrics based on redundancy, skewness, lack of data, professional judgment, lack of nonzero values, unbalanced box plots, and limited ranges of values. A final selection of 12 metrics formed the SRI and weighed factors involving soil erodibility, road sedimentation abatement features, and stream morphology alteration. The SRI was organized into narrative categories (excellent, good, fair, poor, and very poor) based on the distribution of scores. No excellent sites (scores ≥55) were found in this study, 17 (20.7%) were good (low sedimentation risk), 37 (45.1%) were fair (moderate sedimentation risk), 26 (31.7%) were poor (high sedimentation risk), and two (2.5%) were very poor (high sedimentation risk). There was no significant difference in SRI scores among crossing structure type (round culverts, box culverts, and bridges) (H = 4.31, df = 2, p = 0.058). A future study of the Choctawhatchee watershed involving the same study sites could assess the success of restoration plans and activities based on site score improvement or decline.     

Valuing lives equally in a benefit-coast analysis of safety projects: A method to reconcile theory and practice

A value of statistical life (VSL) is used in cost-benefit analysis (CBA) as a monetary measure of the benefits to people from small risk reductions that arise from safety projects. Despite its widespread use in a number of countries, the concept of a VSL remains controversial, not least because it implies acceptance of the underlying ethical assumptions of CBA together with the idea that ‘social welfare’ can be measured and aggregated in some manner. In addition, to comply with theory, variable VSLs for different groups within society would be advocated. However, without fail, empirically, it is the case that those countries that employ a willingness to pay based approach to cost-benefit analysis of a safety project appraisal tend to use a single value for that accident context that is independent of the per capita income level, or indeed other personal characteristics, of the sub-group in society to which the safety improvement will actually apply. This article presents a straightforward, but theoretically justified adaptation to the calculation of a VSL which allows empirical practice by policymakers i.e. the application of a “common” VSL for any particular hazard within a given society, to be compatible with a CBA decision making approach.     

Microtargeting for conservation

Widespread human action and behavior change is needed to achieve many conservation goals. Doing so at the requisite scale and pace will require the efficient delivery of outreach campaigns. Conservation gains will be greatest when efforts are directed toward places of high conservation value (or need) and tailored to critical actors. Recent strategic conservation planning has relied primarily on spatial assessments of biophysical attributes, largely ignoring the human dimensions. Elsewhere, marketers, political campaigns, and others use microtargeting—predictive analytics of big data—to identify people most likely to respond positively to particular messages or interventions. Conservationists have not yet widely capitalized on these techniques. To investigate the effectiveness of microtargeting to improve conservation, we developed a propensity model to predict restoration behavior among 203,645 private landowners in a 5,200,000 ha study area in the Chesapeake Bay Watershed (U.S.A.). To isolate the additional value microtargeting may offer beyond geospatial prioritization, we analyzed a new high-resolution land-cover data set and cadastral data to identify private owners of riparian areas needing restoration. Subsequently, we developed and evaluated a restoration propensity model based on a database of landowners who had conducted restoration in the past and those who had not (n = 4978). Model validation in a parallel database (n = 4989) showed owners with the highest scorers for propensity to conduct restoration (i.e., top decile) were over twice as likely as average landowners to have conducted restoration (135%). These results demonstrate that microtargeting techniques can dramatically increase the efficiency and efficacy of conservation programs, above and beyond the advances offered by biophysical prioritizations alone, as well as facilitate more robust research of many social–ecological systems.     

Improving the risk–risk trade-off method for use in safety project appraisal responses

Environmental Economics and Policy Studies - The risk–risk trade-off method is a technique used to elicit the relative trade-off between changes in morbidity and mortality risks in stated...     

Environmental performance measurement: A case study

Based on information derived in a benchmark study of corporate environmental programs and their performance measurement systems and stakeholder concerns, an environmental performance measurement system was developed to be used by the utility industry. Pilot studies were conducted to evaluate the usefulness of the proposed system, as well as to solicit feedback from individuals in the field. The pilot studies were necessary to tailor the system to the utility industry.     

Analysis of the cyanotoxins anatoxin-a and microcystins in Lesser Flamingo feathers†

Feathers from carcasses of the Lesser Flamingo (Phoeniconaias minor), which had died after ingesting cyanobacterial toxins (cyanotoxins) contained between 0.02 and 30.0?µg microcystin-LR equivalents per gram of feather according to HPLC and ELISA analysis of feather extracts. Anatoxin-a was detected less frequently in the Lesser Flamingo feathers, up to 0.8?µg anatoxin-a per gram of feather being recorded. When feathers from different body regions were analysed and compared for microcystins and anatoxin-a, wing feathers were found to contain the highest concentrations of these cyanotoxins, the order of concentration and frequency of analytical detection being wing?>?breast?>?head. Consistent with the presence of the microcystins and anatoxin-a in gut contents and the livers of the dead birds and negligible in vitro adsorption to feathers, the cyanotoxins associated with the feathers of the dead wild flamingos are inferred to be primarily of dietary origin.     

Comparison of four methods for the extraction of lipopolysaccharide from cyanobacteria

Four procedures were compared for the extraction of lipopolysaccharide (LPS) from 10 laboratory strains of cyanobacteria. LPS yields as a percentage of cyanobacterial dry weight ranged from 0.03 to 6.13. The heterotrophic bacterial LPS marker 2-keto-3-deoxyoctonoic (KDO) acid was not detectable in any of the cyanobacterial LPS preparations. All methods yielded LPS that contained biologically- and toxicologically-significant quantities of the cyanotoxin microcystin, when applied to some, but not all, microcystin-producing cyanobacterial strains. Of the four methods used, a procedure including Proteinase K, plus RNase and DNase, performed best overall on the basis of minimum time required, higher percentage yields of LPS, and minimal co-extraction of microcystin.