Social-ecological system resonance: a theoretical framework for brokering sustainable solutions

Sustainability science is a solution-oriented discipline. Yet, there are few theory-rich discussions about how this orientation structures the efforts of sustainability science. We argue that Niklas Luhmann’s social system theory, which explains how societies communicate problems, conceptualize solutions, and identify pathways towards implementation of solutions, is valuable in explaining the general structure of sustainability science. From Luhmann, we focus on two key concepts. First, his notion of resonance offers us a way to account for how sustainability science has attended and responded to environmental risks. As a product of resonance, we reveal solution-oriented research as the strategic coordination of capacities, resources, and information. Second, Luhmann’s interests in self-organizing processes explain how sustainability science can simultaneously advance multiple innovations. The value logic that supports this multiplicity of self-organizing activities as a recognition that human and natural systems are complex coupled and mutually influencing. To give form to this theoretical framework, we offer case evidence of renewable energy policy formation in Texas. Although the state’s wealth is rooted in a fossil-fuel heritage, Texas generates more electricity from wind than any US state. It is politically antagonistic towards climate-change policy, yet the state’s reception of wind energy technology illustrates how social and environmental systems can be strategically aligned to generate solutions that address diverse needs simultaneously. This case demonstrates that isolating climate change—as politicians do as a separate and discrete problem—is incapable of achieving sustainable solutions, and resonance offers researchers a framework for conceptualizing, designing, and communicating meaningfully integrated actions.     

Net Present Biodiversity Value and the Design of Biodiversity Offsets

There is an urgent need to develop sound theory and practice for biodiversity offsets to provide a better basis for offset multipliers, to improve accounting for time delays in offset repayments, and to develop a common framework for evaluating in-kind and out-of-kind offsets. Here, we apply concepts and measures from systematic conservation planning and financial accounting to provide a basis for determining equity across type (of biodiversity), space, and time. We introduce net present biodiversity value (NPBV) as a theoretical and practical measure for defining the offset required to achieve no-net-loss. For evaluating equity in type and space we use measures of biodiversity value from systematic conservation planning. Time discount rates are used to address risk of non-repayment, and loss of utility. We illustrate these concepts and measures with two examples of biodiversity impact–offset transactions. Considerable further work is required to understand the characteristics of these approaches.     

Estimating the normal background rate of species extinction

A key measure of humanity's global impact is by how much it has increased species extinction rates. Familiar statements are that these are 100–1000 times pre‐human or background extinction levels. Estimating recent rates is straightforward, but establishing a background rate for comparison is not. Previous researchers chose an approximate benchmark of 1 extinction per million species per year (E/MSY). We explored disparate lines of evidence that suggest a substantially lower estimate. Fossil data yield direct estimates of extinction rates, but they are temporally coarse, mostly limited to marine hard‐bodied taxa, and generally involve genera not species. Based on these data, typical background loss is 0.01 genera per million genera per year. Molecular phylogenies are available for more taxa and ecosystems, but it is debated whether they can be used to estimate separately speciation and extinction rates. We selected data to address known concerns and used them to determine median extinction estimates from statistical distributions of probable values for terrestrial plants and animals. We then created simulations to explore effects of violating model assumptions. Finally, we compiled estimates of diversification—the difference between speciation and extinction rates for different taxa. Median estimates of extinction rates ranged from 0.023 to 0.135 E/MSY. Simulation results suggested over‐ and under‐estimation of extinction from individual phylogenies partially canceled each other out when large sets of phylogenies were analyzed. There was no evidence for recent and widespread pre‐human overall declines in diversity. This implies that average extinction rates are less than average diversification rates. Median diversification rates were 0.05–0.2 new species per million species per year. On the basis of these results, we concluded that typical rates of background extinction may be closer to 0.1 E/MSY. Thus, current extinction rates are 1,000 times higher than natural background rates of extinction and future rates are likely to be 10,000 times higher. Estimación de la Tasa Normal de Extinción de Especies     

Effect of soil sterilization by mercuric chloride on herbicide sorption by soil

Microbial inhibitors such as mercuric chloride are frequently used to sterilize soil or soil-water slurries in experimental studies on the fate of xenobiotics in the environment. This study examined the influence of mercuric chloride additions to soil-water slurries on the sorptive behaviour of a phenoxy herbicide (2,4-D) in soil. The results demonstrated that mercuric chloride strongly decreased the capacity of the soil to retain herbicides, and that the interference of mercuric chloride with herbicide sorption increased with increasing soil organic carbon contents. Because of the competitive sorption between mercuric chloride and the phenoxy herbicide, we conclude that mercuric chloride may not be a good soil sterilization procedure for use in xenobiotic fate studies.     

An analytical solution for vertical transport of volatile chemicals in the vadose zone

An analytical solution is presented for one-dimensional vertical transport of volatile chemicals through the vadose zone to groundwater. The solution accounts for the important transport mechanisms of the steady advection of water and gas, diffusion and dispersion in water and gas, as well as adsorption, and first-order degradation. By assuming a linear, equilibrium partitioning between water, gas and the adsorbed chemical phases, the dependent variable in the mathematical model becomes the total resident concentration. The general solution was derived for cases having a constant initial total concentration over a discrete depth interval and a zero initial total concentration elsewhere. A zero concentration gradient is assumed at the groundwater table. Examples are given to demonstrate the application of the new solution for calculating the case of a non-uniform initial source concentration, and estimating the transport of chemicals to the groundwater and the atmosphere. The solution was also used to verify a numerical code called VLEACH. We discovered an error in VLEACH, and found that the new solution agreed very well with the numerical results by corrected VLEACH. A simplified solution to predict the migration of volatile organic chemical due to the gas density effect has shown that a high source concentration may lead to significant downward advective gas-phase transport in a soil with a high air-permeability.     

Gas-phase mercury reduction to measure total mercury in the flue gas of a coal-fired boiler

Gaseous elemental and total (elemental + oxidized) mercury (Hg) in the flue gas from a coal-fired boiler was measured by a modified ultraviolet (UV) spectrometer. Challenges to Hg measurement were the spectral interferences from other flue gas components and that UV measures only elemental Hg. To eliminate interference from flue gas components, a cartridge filled with gold-coated sand removed elemental Hg from a flue gas sample. The Hg-free flue gas was the reference gas, eliminating the spectral interferences. To measure total Hg by UV, oxidized Hg underwent a gas-phase, thermal-reduction in a quartz cell heated to 750 degrees C. Simultaneously, hydrogen was added to flash react with the oxygen present forming water vapor and preventing Hg re-oxidation as it exits the cell. Hg concentration results are in parts per billion by volume Hg at the flue gas oxygen concentration. The modified Hg analyzer and the Ontario Hydro method concurrently measured Hg at a field test site. Measurements were made at a 700-MW steam turbine plant with scrubber units and selective catalytic reduction. The flue gas sampled downstream of the selective catalytic reduction contained 2100 ppm SO2 and 75 ppm NOx. Total Hg measured by the Hg analyzer was within 20% of the Ontario Hydro results.     

Transport company safety climate—The impact on truck driver behavior and crash involvement

Objective: The present study investigated the relationships between safety climate and driving behavior and crash involvement.

Methods: A total of 339 company-employed truck drivers completed a questionnaire that measured their perceptions of safety climate, crash record, speed choice, and aberrant driving behaviors (errors, lapses, and violations).

Results: Although there was no direct relationship between the drivers' perceptions of safety climate and crash involvement, safety climate was a significant predictor of engagement in risky driving behaviors, which were in turn predictive of crash involvement.

Conclusions: This research shows that safety climate may offer an important starting point for interventions aimed at reducing risky driving behavior and thus fewer vehicle collisions.     

Model selection and model averaging in behavioural ecology: the utility of the IT-AIC framework

Behavioural ecologists often study complex systems in which multiple hypotheses could be proposed to explain observed phenomena. For some systems, simple controlled experiments can be employed to reveal part of the complexity; often, however, observational studies that incorporate a multitude of causal factors may be the only (or preferred) avenue of study. We assess the value of recently advocated approaches to inference in both contexts. Specifically, we examine the use of information theoretic (IT) model selection using Akaike’s information criterion (AIC). We find that, for simple analyses, the advantages of switching to an IT-AIC approach are likely to be slight, especially given recent emphasis on biological rather than statistical significance. By contrast, the model selection approach embodied by IT approaches offers significant advantages when applied to problems of more complex causality. Model averaging is an intuitively appealing extension to model selection. However, we were unable to demonstrate consistent improvements in prediction accuracy when using model averaging with IT-AIC; our equivocal results suggest that more research is needed on its utility. We illustrate our arguments with worked examples from behavioural experiments.