Combining isotope ratios for provenancing Viking Age iron artefacts in the British Isles: a pilot study.

Stable and radiogenic isotope analysis - particularly using lead isotope analysis (LIA) - has previously been shown to be a useful tool for the provenancing of ancient metal artefacts of silver and copper and its alloys, but less progress has been made in the provenancing of iron artefacts, despite their importance and frequency in the archaeological record. In this pilot study we investigate for the first time the possibilities of iron isotope analysis in combination with trace strontium isotope analysis and LIA for the provenancing of iron objects believed to be from the Viking Age in the British Isles. Previous studies have shown that analysis of each of these isotopes can contribute to provenancing iron artefacts, but they are not individually resolutory. In this proof-of-concept study, we examine the Fe, Sr and Pb isotopes of 7 artefacts believed to derive from the Viking Age: 3 from Meols - a former Viking seaport on Wirral and 4 samples from the probable location of the AD 1066 Battle of Fulford in North Yorkshire. We also examine an additional artefact of unknown antiquity from Bebington Heath - a possible location of the AD 937 Battle of Brunanburh. Although the pilot data set is too small to make definitive conclusions, it has paved the way for a fuller study involving 100 samples (including 30 from the former Viking camp of Torksey, Lincolnshire) funded by the NEIF fund of the UK National Environmental Research Council. The high range of 87Sr/86Sr values in the present data set of 8 is beyond what would be expected for bog iron (with a cut-off ∼ 0.709) and suggests that mined ore was being used, a preliminary conclusion supported by the narrow range of Fe isotope data.

National hydrologic connectivity classification links wetlands with stream water quality.

Wetland hydrologic connections to downstream waters influence stream water quality. However, no systematic approach for characterizing this connectivity exists. Here using physical principles, we categorized conterminous US freshwater wetlands into four hydrologic connectivity classes based on stream contact and flowpath depth to the nearest stream: riparian, non-riparian shallow, non-riparian mid-depth and non-riparian deep. These classes were heterogeneously distributed over the conterminous United States; for example, riparian dominated the south-eastern and Gulf coasts, while non-riparian deep dominated the Upper Midwest and High Plains. Analysis of a national stream dataset indicated acidification and organic matter brownification increased with connectivity. Eutrophication and sedimentation decreased with wetland area but did not respond to connectivity. This classification advances our mechanistic understanding of wetland influences on water quality nationally and could be applied globally.

Performance on the CVLT-2 during induced pain.

Objective: Chronic pain patients frequently report cognitive problems including learning and memory. However, recent research involving induced pain has demonstrated an absence of reliably detectable decrements on several standard cognitive measures, suggesting that factors other than pain likely explain perceived cognitive deficits in chronic pain patients. This study examined potential effects of induced pain on verbal learning and memory as measured by the California Verbal Learning Test (CVLT-2). Potential effects of self-reported pain intensity were also evaluated. Method: Participants (111 non-clinical undergraduate students in the Southwestern United States) completed one version (Standard or Alternate) of the CVLT-2 under normal conditions, and then were administered the other version (Alternate or Standard) either while experiencing cold pressor-induced pain (Pain condition) or non-painful warm water immersion (Control condition). Results: For the Pain condition decrements in performance across most CVLT-2 variables were observed, including a mean T-score decrease of 10.98 (SD = 10.99) for Trials 1-5, whereas the comparable decrease in the Control condition was an average of 1.5 words (SD = 8.27). Self-reported pain intensity was significantly correlated with the degree of Time 1 to Time 2 performance decrement for Short-Delay Free Recall (r = -.51, p < .050), but not for Trials 1-5 (r = -.37, p = .160). Conclusion: Induced pain produces detectable decrements in performance on a standard clinical measure of verbal learning and memory performance, suggesting that pain in clinical populations may contribute to learning and memory deficits apart from potential neurological conditions.

Using hydrologic landscape classification and climatic time series to assess hydrologic vulnerability of the western U.S. to climate.

We apply the hydrologic landscape (HL) concept to assess the hydrologic vulnerability of the western United States (U.S.) to projected climate conditions. Our goal is to understand the potential impacts of hydrologic vulnerability for stakeholder-defined interests across large geographic areas. The basic assumption of the HL approach is that catchments that share similar physical and climatic characteristics are expected to have similar hydrologic characteristics. We use the hydrologic landscape vulnerability approach (HLVA) to map the HLVA index (an assessment of climate vulnerability) by integrating hydrologic landscapes into a retrospective analysis of historical data to assess variability in future climate projections and hydrology, which includes temperature, precipitation, potential evapotranspiration, snow accumulation, climatic moisture, surplus water, and seasonality of water surplus. Projections that are beyond 2 standard deviations of the historical decadal average contribute to the HLVA index for each metric. Separating vulnerability into these seven separate metrics allows stakeholders and/or water resource managers to have a more specific understanding of the potential impacts of future conditions. We also apply this approach to examine case studies. The case studies (Mt. Hood, Willamette Valley, and Napa-Sonoma Valley) are important to the ski and wine industries and illustrate how our approach might be used by specific stakeholders. The resulting vulnerability maps show that temperature and potential evapotranspiration are consistently projected to have high vulnerability indices for the western U.S. Precipitation vulnerability is not as spatially uniform as temperature. The highest-elevation areas with snow are projected to experience significant changes in snow accumulation. The seasonality vulnerability map shows that specific mountainous areas in the west are most prone to changes in seasonality, whereas many transitional terrains are moderately susceptible. This paper illustrates how HL and the HLVA can help assess climatic and hydrologic vulnerability across large spatial scales. By combining the HL concept and HLVA, resource managers could consider future climate conditions in their decisions about managing important economic and conservation resources.

Embedding co-production and addressing uncertainty in watershed modeling decision-support tools: successes and challenges.

Decision-support tools (DSTs) are often produced from collaborations between technical experts and stakeholders to address environmental problems and inform decision making. Studies in the past two decades have provided key insights on the use of DSTs and the importance of bidirectional information flows among technical experts and stakeholders - a process that is variously referred to as co-production, participatory modeling, structured decision making, or simply stakeholder participation. Many of these studies have elicited foundational insights for the broad field of water resources management; however, questions remain on approaches for balancing co-production with uncertainty specifically for watershed modeling decision support tools. In this paper, we outline a simple conceptual model that focuses on the DST development process. Then, using watershed modeling case studies found in the literature, we discuss successful outcomes and challenges associated with embedding various forms of co-production into each stage of the conceptual model. We also emphasize the "3 Cs" (i.e., characterization, calculation, communication) of uncertainty and provide evidence-based suggestions for their incorporation in the watershed modeling DST development process. We conclude by presenting a list of best practices derived from current literature for achieving effective and robust watershed modeling decision-support tools.

Bayesian analysis of multimethod ego-depletion studies favours the null hypothesis.

Ego-depletion refers to the purported decrease in performance on a task requiring self-control after engaging in a previous task involving self-control, with self-control proposed to be a limited resource. Despite many published studies consistent with this hypothesis, recurrent null findings within our laboratory and indications of publication bias have called into question the validity of the depletion effect. This project used three depletion protocols involved three different depleting initial tasks followed by three different self-control tasks as dependent measures (total n = 840). For each method, effect sizes were not significantly different from zero When data were aggregated across the three different methods and examined meta-analytically, the pooled effect size was not significantly different from zero (for all priors evaluated, Hedges' g = 0.10 with 95% credibility interval of [-0.05, 0.24]) and Bayes factors reflected strong support for the null hypothesis (Bayes factor > 25 for all priors evaluated).