Using triple bottom line metrics and multi-criteria methodology in corporate settings

With the growing importance of environmental sustainability in the corporate sector, businesses are compelled to progress from assessing and benchmarking their environmental impact to making decisions on how to prioritize impact reduction alternatives. Most often, business decisions are driven by financial metrics, but with sustainability improvements becoming a business goal, it is also important to assess metrics from environmental and social spheres; nevertheless, practically and systematically performing such an assessment is challenging. We present an application of a multi-criteria decision analysis (MCDA) method that addresses the aforementioned challenges in a corporate setting. Our case study company – one of the largest inland marine freight carriers in the United States – promotes a business culture focused on financially viable, yet socially and environmentally responsible solutions. Thus, we combine life cycle analysis (LCA), financial calculation methods, and corporate surveys to quantify environmental, economic, and social performance measures, respectively. Multiattribute utility theory is integrated with analytic hierarchy processes (AHPs) and fuzzy analysis to create a carefully designed framework for corporations with diverse groups of stakeholders. With company leadership, implementation is feasible and successful at prioritizing alternatives among diverse stakeholders. The process provides a platform for negotiation and promotes discussions on decision drivers. The use of MCDA methodologies promoted the inclusion of a suite of metrics that aligned with the company's sense of social and environmental responsibility, generating an in-depth analysis of the alternatives that factored in other things besides economics. Return-on-investments (ROI) calculations, the typical approach used in the corporate setting, would have required significantly less time and effort from the company, but the results of our MCDA application indicated that inclusion of triple bottom line metrics delve deeper into stakeholder preferences. Thus, our case study company gained a holistic view of the candidate alternatives, in addition to creating a platform for structured discussions about company goals and priorities.     

Long-term behavior at foraging sites of adult female loggerhead sea turtles (Caretta caretta) from three Florida rookeries

We used satellite telemetry to study behavior at foraging sites of 40 adult female loggerhead sea turtles (Caretta caretta) from three Florida (USA) rookeries. Foraging sites were located in four countries (USA, Mexico, the Bahamas, and Cuba). We were able to determine home range for 32 of the loggerheads. One turtle moved through several temporary residence areas, but the rest had a primary residence area in which they spent all or most of their time (usually >11 months per year). Twenty-four had a primary residence area that was <500 km² (mean = 191). Seven had a primary residence area that was ≥500 km² (range = 573–1,907). Primary residence areas were mostly restricted to depths <100 m. Loggerheads appeared to favor areas with larger-grained sediment (gravel and rock) over areas with smaller-grained sediment (mud). Short-term departures from primary residence areas were either looping excursions, typically involving 1–2 weeks of continuous travel, or movement to a secondary residence area where turtles spent 25–45 days before returning to their primary residence area. Ten turtles had a secondary residence area, and six used it as an overwintering site. For those six turtles, the primary residence area was in shallow water (<17 m) in the northern half of the Gulf of Mexico (GOM), and overwintering sites were farther offshore or farther south. We documented long winter dive times (>4 h) for the first time in the GOM. Characterizing behaviors at foraging sites helps inform and assess loggerhead recovery efforts.     

Disasters and ‘conditions of possibility’: rethinking causation through an analysis of earthquakes in Nepal

What causes a disaster's aftermath? Scholars have increasingly turned to historical approaches that link outcomes to pre-disaster sociopolitical dynamics. Disasters lead to ‘critical junctures’ that ‘trigger’ events that unfold in the wake of the initial phenomenon. This paper argues that the ‘critical junctures’ paradigm shares limitations with ‘path dependency’ theory from which it is derived, namely a tendency towards historicism—a functionalist teleology better able to explain continuity than change. As an alternative, this analysis draws on Michel Foucault's understanding of ‘conditions of possibility’ as a way of rethinking agency/causation, moving away from individual subjects, events, or even historical conditions towards, instead, the new, radically destabilised ‘epistemological field’ emerging in the disaster's aftermath. This paper examines a series of devastating earthquakes in Nepal to consider how post-disaster ‘epistemological fields’ present new ‘conditions of possibility’ within which new ideas, actions, and outcomes become thinkable and possible in ways that pre-disaster historical conditions could not have predicted.     

多种聚氧乙烯牛脂胺混合物MON 0818的水生环境危害评估：实验室急性暴露实验基础上的物种敏感度分布

本实验利用标准短期(48- 96 h)实验室测试测定了包括初级生产者，底栖无脊椎动物，水蚤类动物，软体动物和鱼类在内的15种水生生物对于MON 0818的敏感性。MON 0818是一种商业表面活性剂，由多种聚氧乙烯牛脂胺混合而成。此外本实验使用模糊网纹蚤(Ceriodaphnia dubia)潜在的长期(8 d)毒性，确定了暴露浓度。长期毒性测试中未在任何终端指标中发现显著效果。利用得出的数据和文献记载得到物种敏感度在4种暴露条件下的分布，通过对比物种敏感度分布进行了tier-1危害评估。评估显示在本研究规划下(以综述为原型，研究林业除草剂；12 L标准每公顷，等于4.27 kg每公顷) 最差的情况(无意中以最大标签使用速率直接过量喷洒到15 cm深的水体中)会造成中等危害(43.1%的物种处于暴露中，高于中位有效浓度水平)。在更多以最大使用速率使用的典型情况下，受到损害的物种降至20.9%(6 L标准每公顷，相当于2.14 kg每公顷)，在更频繁的雇佣施用速率(2.5 L标准每公顷，相当于0.89 kg每公顷)下，受损物种比例降至6.9%。通过草甘膦在环境中的最大测定浓度计算得到MON 0818的浓度，最终受损物种比例(3.8%)则小于此浓度下受损物种比例(5%)。
精选自Jose L. Rodriguez-Gil, Ryan Prosser, David Poirier, Linda Lissemore, Dean Thompson, Mark Hanson, Keith R. Solomon. Aquatic hazard assessment of MON 0818, a commercial mixture of alkylamine ethoxylates commonly used in glyphosate-containing herbicide formulations. Part 1: Species sensitivity distribution from laboratory acute exposures. Environmental Toxicology and Chemistry: Volume 36, Issue 2, pages 501–511, July 2017. DOI: 10.1002/etc.3559
详情请见http://onlinelibrary.wiley.com/wol1/doi/10.1002/etc.3559/full
     

Value of information and monitoring in conservation biology

In this paper we consider uses of value of information studies in conservation biology. It is a common assumption that more and better quality data will lead to better conservation management decisions. Indeed, this assumption lies behind, and motivates, a great deal of current work in conservation biology. Of course, more data can lead to better decisions in some cases but decision-theoretic models of the value of information show that this need not always be the case: sometimes the cost of data collection is too high. While such value of information studies are well known in economics and decision theory circles, their applications in conservation biology are relatively new. These studies are a valuable tool for conservation management, and we outline some of the potential applications. We also offer some advice about, and problems with, implementing value of information studies in conservation settings.     

Valuation of human health: An integrated model of willingness to pay for mortality and morbidity risk reductions

This paper develops and applies an integrated model of mortality and morbidity valuation that is consistent with the principles of welfare economics. To obtain the integrated model, the standard one-period expected utility model of one person facing the prospect of either being alive or dead is extended to incorporate (1) a third health state (sick) with a utility level that is intermediate to utility if healthy and utility if dead, (2) a family perspective in which a parent makes choices about risk exposure both for herself and for a child, and (3) a multi-period framework that allows for possible parent/child differences in illness latency. Monetary benefits of health risk reduction obtained from the integrated model are compared with those that would be computed using the standard model. The integrated model then is applied using data obtained from two field studies of skin cancer and leukemia to demonstrate how it can be used to estimate health benefits of reduced illness and death risks.