Climate change risk management: a Mental Modeling application

The potential impacts of climate change are varied and highly uncertain, and pose a significant challenge to agencies charged with managing environmental risks. This paper presents a comprehensive and structured Mental Modeling approach to elicit, organize and present relevant information from experts and stakeholders about the factors influencing environmental risk management in the face of climate change. We present and review an initiative undertaken by the United States Army Corps of Engineers (USACE) to characterize climate change challenges to USACE environmental risk management activities, and to identify gaps with respect to science, engineering, and organizational processes for addressing these challenges. By employing Mental Modeling, the research has characterized the influences of climate change on USACE environmental risk management, and aggregating recommendations from 28 experts. In addition, the study identifies the most important opportunities to improve organizational response to climate change, ranging from focused research and development of technical capabilities to broad paradigm shifts and systemic organizational improvements within the USACE environmental risk management programs. This study demonstrates that Mental Modeling is a useful tool for understanding complex problems, identifying gaps, and formulating strategies, and can be used by a multitude of organizations and agencies.     

Working Wetland Potential: An index to guide the sustainable development of African wetlands

Past experience shows that inappropriate agricultural development in wetlands can undermine sustainability and may have profound social and economic repercussions for people dependent on the range of ecosystem services provided by those wetlands. Nonetheless, there is escalating pressure to expand agriculture within wetlands due to increasing population, in conjunction with efforts to increase food security. This paper describes the development of a semi-analytical framework for identifying, organizing and analyzing the complex factors that link people, agriculture and wetland ecosystems — an index of Working Wetland Potential (WWP). The method is based on a form of multi-criteria analysis that integrates biophysical and socio-economic aspects of wetland utilization. The WWP index emerges from the aggregation of two values: the first arising from an appraisal of both the biophysical and socio-economic suitability of using the wetland for agriculture; and the second resulting from an assessment of the possible hazards, in relation to both social welfare and the ecological character of the wetland. Hence, the approach provides a way to explicitly integrate biophysical and social aspects of wetland utilization in a single index to enable an initial assessment of the suitability of using a wetland for agriculture. Results from three contrasting wetlands in sub-Saharan Africa are presented.     

Associations between Water Physicochemistry and Prymnesium parvum Presence,Abundance, and Toxicity in West Texas Reservoirs

Toxic blooms of golden alga (Prymnesium parvum) have caused substantial ecological and economic harm in freshwater and marine systems throughout the world. In North America, toxic blooms have impacted freshwater systems including large reservoirs. Management of water chemistry is one proposed option for golden alga control in these systems. The main objective of this study was to assess physicochemical characteristics of water that influence golden alga presence, abundance, and toxicity in the Upper Colorado River basin (UCR) in Texas. The UCR contains reservoirs that have experienced repeated blooms and other reservoirs where golden alga is present but has not been toxic. We quantified golden alga abundance (hemocytometer counts), ichthyotoxicity (bioassay), and water chemistry (surface grab samples) at three impacted reservoirs on the Colorado River; two reference reservoirs on the Concho River; and three sites at the confluence of these rivers. Sampling occurred monthly from January 2010 to July 2011. Impacted sites were characterized by higher specific conductance, calcium and magnesium hardness, and fluoride than reference and confluence sites. At impacted sites, golden alga abundance and toxicity were positively associated with salinity‐related variables and blooms peaked at ~10°C and generally did not occur above 20°C. Overall, these findings suggest management of land and water use to reduce hardness or salinity could produce unfavorable conditions for golden alga.     

Overcoming challenges to struvite recovery from anaerobically digested dairy manure

Recovering struvite from dairy manure has consistently posed problems for researchers. This study separated solids from anaerobically digested dairy manure using a filtration system. Filtrate was rich in free magnesium (160 to 423 mg/L), ammonium (320 to 1800 mg N/L) and orthophosphate (93 to 332 mg P/L). High concentrations of free calcium (128 to 361 mg/L) and alkalinity (3309 to 6567 mg/L as CaCO3), however, may hinder struvite precipitation. Batch precipitation tests were conducted to identify and overcome factors that interfere with struvite formation. Precipitation tests at pH 9 identified calcium and ionic strength as most probable interferences. Calcium addition did not significantly change phosphorus removal efficiency, but decreased struvite purity because of formation of calcium phosphates when Ca:P activity ratio was greater than 0.5 to 1. Batch tests demonstrated effective calcium removal from anaerobically digested dairy manure through precipitation of calcium carbonate at pH 9 to 10 while retaining magnesium and orthophosphate, lessening hindrance to struvite formation.     

The oil and gas sector: from climate laggard to climate leader?

ABSTRACT

The oil and gas industry has traditionally been reticent to engage with the issues surrounding climate change, typically being cast as a laggard. Yet, over recent years, the sector has begun taking on a more active role in climate governance, doing so in a variety of capacities – as initiators, catalysts and participants in industry-led or multi-stakeholder efforts. The Oil and Gas Climate Initiative is reviewed, as a case study to illustrate emerging climate leadership within the global oil and gas industry. In 2015, its members committed to a two-degree pathway. The paucity of research on the nascent role of oil and gas firms in climate governance is addressed.     

Divestment discourse: war,justice, morality and money

The fossil fuel divestment movement has been a vibrant novel development in climate change politics in recent years, particularly in North America. Here, the character of the discourse used to promote divestment as a strategy is explored. The divestment discourse is shown to rest on four overlapping narratives, those of war and enemies, morality, economics and justice. All four are clearly discernible in statements from movement activists, in coverage of divestment campaigns by major news sources and in the movement’s aims, objectives and strategies covered in alternative media. The war narrative, with the formulation of fossil fuel companies as enemies to be overcome to ensure survival, is the dominant narrative. By polarising climate action and identifying an antagonist against which to mobilise, divestment discourse has articulated climate change as an explicitly political phenomenon, in contrast to the primarily consensus and collaboration-based approaches that have predominated in climate politics.     

Evaluation of a Regional Monitoring Program’s Statistical Power to Detect Temporal Trends in Forest Health Indicators

Forests are socioeconomically and ecologically important ecosystems that are exposed to a variety of natural and anthropogenic stressors. As such, monitoring forest condition and detecting temporal changes therein remain critical to sound public and private forestland management. The National Parks Service’s Vital Signs monitoring program collects information on many forest health indicators, including species richness, cover by exotics, browse pressure, and forest regeneration. We applied a mixed-model approach to partition variability in data for 30 forest health indicators collected from several national parks in the eastern United States. We then used the estimated variance components in a simulation model to evaluate trend detection capabilities for each indicator. We investigated the extent to which the following factors affected ability to detect trends: (a) sample design: using simple panel versus connected panel design, (b) effect size: increasing trend magnitude, (c) sample size: varying the number of plots sampled each year, and (d) stratified sampling: post-stratifying plots into vegetation domains. Statistical power varied among indicators; however, indicators that measured the proportion of a total yielded higher power when compared to indicators that measured absolute or average values. In addition, the total variability for an indicator appeared to influence power to detect temporal trends more than how total variance was partitioned among spatial and temporal sources. Based on these analyses and the monitoring objectives of the Vital Signs program, the current sampling design is likely overly intensive for detecting a 5 % trend·year^?1 for all indicators and is appropriate for detecting a 1 % trend·year^?1 in most indicators.     

A Comparative Assessment of Runoff Nitrogen from Turf,Forest, Meadow,and Mixed Landuse Watersheds

Landscaping paradigms that encourage high‐input, intensively managed and mono‐culture turf/lawn landscapes have raised concerns about water quality. We conducted a watershed‐scale assessment of landscaping practices that included turf, urban, forest, native meadow, and mixed landuse watersheds with a professional golf course and a parking lot. The turf site was moderately managed and had lower fertilizer inputs than those typically used by homeowners and golf courses. Stream water sampling was performed during base flow and storm events. Highest nitrate and total nitrogen concentrations in runoff were observed for the mixed watershed draining the golf course. In contrast, concentrations in base flow from the turf watershed were lower than expected and were comparable to those measured in the surrounding meadow and forest sites. Total nitrogen concentrations from the turf site increased sharply during the first storms following fertilization, suggesting that despite optimal management there exists a risk for nutrient runoff following fertilization. Overall, this study suggests that turf or lawns, when managed properly, pose minimal water quality risk to surface waters. Rate, timing of application, and the type of fertilizer appear to be the key factors affecting water quality. Better education of homeowners and landscaping professionals with regard to these factors may be a cost‐effective strategy to reduce nonpoint source pollution.     

Growth of the Decision Tree: Advances in Bottom‐Up Climate Change Risk Management

There has recently been a return in climate change risk management practice to bottom‐up, robustness‐based planning paradigms introduced 40 years ago. The World Bank's decision tree framework (DTF) for “confronting climate uncertainty” is one incarnation of those paradigms. In order to better represent the state of the art in climate change risk assessment and evaluation techniques, this paper proposes: (1) an update to the DTF, replacing its “climate change stress test” with a multidimensional stress test; and (2) the addition of a Bayesian network framework that represents joint probabilistic behavior of uncertain parameters as sensitivity factors to aid in the weighting of scenarios of concern (the combination of conditions under which a water system fails to meet its performance targets). Using the updated DTF, water system planners and project managers would be better able to understand the relative magnitudes of the varied risks they face, and target investments in adaptation measures to best reduce their vulnerabilities to change. Next steps for the DTF include enhancements in: modeling of extreme event risks; coupling of human‐hydrologic systems; integration of surface water and groundwater systems; the generation of tradeoffs between economic, social, and ecological factors; incorporation of water quality considerations; and interactive data visualization.