Sulfur and Carbon Cycling in a Flue Gas Desulfurization Sludge Disposal Site

Abstract

Products of a power plant flue gas desulfurization scrubber are discharged into a pond as sludge consisting of calcite (initial δ¹³C 3.2–3.8‰), gypsum (initial δ³⁴S 7.6–8.6‰), and aqueous solution. Reducing conditions exist below a boundary that appears to move vertically as a function of changes in pond water level. Under reducing conditions, bacteria partially reduce aqueous sulfate to low-δ³⁴S sulfide, consuming organic carbon and generating low-δ¹³C bicarbonate. Under oxidizing conditions, sulfide is converted to sulfate, leading to calcite dissolution, gypsum precipitation, and isotopic re-equilibration of remaining calcite with dissolved bicarbonate near the pond surface. The gypsum has δ³⁴S near 6‰, and calcite has δ¹³C as low as -1.7‰; the changes from initial values correspond to predictions based on isotopic balance and reaction stoichiometry. The pond largely contains the products of bacterial reduction. After the pond is abandoned, these products may adversely affect attempts to revegetate the site. Future bacterial reduction may be best controlled by dewatering and limiting the supply of organic matter in percolating surface water.     

Ocean fertilization for geoengineering: A review of effectiveness,environmental impacts and emerging governance

Dangerous climate change is best avoided by drastically and rapidly reducing greenhouse gas emissions. Nevertheless, geoengineering options are receiving attention on the basis that additional approaches may also be necessary. Here we review the state of knowledge on large-scale ocean fertilization by adding iron or other nutrients, either from external sources or via enhanced ocean mixing. On the basis of small-scale field experiments carried out to date and associated modelling, the maximum benefits of ocean fertilization as a negative emissions technique are likely to be modest in relation to anthropogenic climate forcing. Furthermore, it would be extremely challenging to quantify with acceptable accuracy the carbon removed from circulation on a long term basis, and to adequately monitor unintended impacts over large space and time-scales. These and other technical issues are particularly problematic for the region with greatest theoretical potential for the application of ocean fertilization, the Southern Ocean. Arrangements for the international governance of further field-based research on ocean fertilization are currently being developed, primarily under the London Convention/London Protocol.     

An experimental test of alternative population augmentation scenarios

Human land use is fragmenting habitats worldwide and inhibiting dispersal among previously connected populations of organisms, often leading to inbreeding depression and reduced evolutionary potential in the face of rapid environmental change. To combat this augmentation of isolated populations with immigrants is sometimes used to facilitate demographic and genetic rescue. Augmentation with immigrants that are genetically and adaptively similar to the target population effectively increases population fitness, but if immigrants are very genetically or adaptively divergent, augmentation can lead to outbreeding depression. Despite well‐cited guidelines for the best practice selection of immigrant sources, often only highly divergent populations remain, and experimental tests of these riskier augmentation scenarios are essentially nonexistent. We conducted a mesocosm experiment with Trinidadian guppies (Poecilia reticulata) to test the multigenerational demographic and genetic effects of augmenting 2 target populations with 3 types of divergent immigrants. We found no evidence of demographic rescue, but we did observe genetic rescue in one population. Divergent immigrant treatments tended to maintain greater genetic diversity, abundance, and hybrid fitness than controls that received immigrants from the source used to seed the mesocosms. In the second population, divergent immigrants had a slightly negative effect in one treatment, and the benefits of augmentation were less apparent overall, likely because this population started with higher genetic diversity and a lower reproductive rate that limited genetic admixture. Our results add to a growing consensus that gene flow can increase population fitness even when immigrants are more highly divergent and may help reduce uncertainty about the use of augmentation in conservation.     

Comparison of conservation metrics in a case study of lemurs

Conservation planning is important to protect species from going extinct now that natural habitats are decreasing owing to human activity and climate change. However, there is considerable controversy in choosing appropriate metrics to weigh the value of species and geographic regions. For example, the added value of phylogenetic conservation‐selection criteria remains disputed because high correlations between them and the nonphylogenetic criteria of species richness have been reported. We evaluated the commonly used conservation metrics species richness, endemism, phylogenetic diversity (PD), and phylogenetic endemism (PE) in a case study on lemurs of Madagascar. This enabled us to identify the conservation target of each metric and consider how they may be used in future conservation planning. We also devised a novel metric that uses a phylogeny scaled according to the rate of phenotypic evolution as a proxy for a species’ ability to adapt to change. High rates of evolution may indicate generalization or specialization. Both specialization and low rates of evolution may result in an inability to adapt to changing environments. We examined conservation priorities by using the inverse of the rate of body mass evolution to account for species with low rates of evolution. In line with previous work, we found high correlations among species richness and PD (r = 0.96), and endemism and PE (r = 0.82) in Malagasy lemurs. Phylogenetic endemism in combination with rates of evolution and their inverse prioritized grid cells containing highly endemic and specialized lemurs at risk of extinction, such as Avahi occidentalis and Lepilemur edwardsi, 2 endangered lemurs with high rates of phenotypic evolution and low‐quality diets, and Hapalemur aureus, a critically endangered species with a low rate of body mass evolution and a diet consisting of very high doses of cyanide.     

Simulating property exchange in estuarine ecosystem models at ecologically appropriate scales

A computational scheme has been developed and tested to simulate property exchange by advection and dispersion in estuaries at time and space scales that are well suited to ecological and management simulations, but are coarse relative to the demands of physical hydrodynamic models. An implementation of the Regional Ocean Model System (ROMS) for the Providence River and Narragansett Bay (RI, USA) was used to determine property exchanges between the spatial elements of an ecological box model. The basis for the method is the statistical tabulation of numerical dye experiments done with the full ROMS physical model. The ROMS model domain was subdivided into fifteen coarse boxes, each with two vertical layers, defining 30 elements that were used for the box model simulations. Dye concentrations were set to arbitrary initial concentrations for all ROMS grids in the large elements, and the ROMS model was run for 24 h. The final distribution of the dye among the elements was used as a tracer for property exchange over that day and was used to develop an exchange matrix. Box model predictions of salinity over 77 days in each element compared favorably with ROMS simulated salinity averaged over the same spatial elements, although the disparity was greater in areas where large river inflows caused strong gradients in ROMS within elements assumed to be homogeneous in the box model. The 77-day simulation included periods of high and low river flow. Despite the large size of the spatial elements, dispersion artifacts were small, much less than the modeled daily exchanges. While others have taken a similar approach, we found a number of theoretical and practical considerations deserved careful attention for this approach to perform satisfactorily. Whereas the full ROMS model takes 9 days on a powerful computing cluster to compute the physics simulation for 77 days, the box model simulates physics and biology for the same interval in 5 s on a personal computer, and a full year in under 1 min. The exchange matrix mixing model is a fast, cost effective, and convenient way to simulate daily variation of complex estuarine physics in ecological modeling at appropriate scales of space and time.     

基于自然环境中优选药物的毒性和生态毒理风险研究

在如今超过1 500种在用原料药中,环境中发现几率明确和对环境影响明确的原料药所占比例很小。由于很难监管所有在用原料药,众多先前的研究提议将原料药按照受关注程度排序,从而可以将研究资源集中于那些最受瞩目的药物。然而这些研究都存在局限性,本文从之前优先性方法的实践经验出发,提出了一种更为全面的原料药排序方法。该方法基于对水生生物、土壤生物、鸟类、野生哺乳动物和人类的风险,综合考虑了食物链顶端存在的生态毒理学研究终点和由这些治疗性药物作用机制带来的非顶端效果。对于在英国社区以及医院设置中使用的146种活性药物的分析可以更为详细地说明该方法的运用。根据这一方法,我们将16种化合物列为优先考虑的药物。这些药物包括了抗生素、抗抑郁药、抗炎药、抗糖尿病药、抗肥胖药、雌激素类化合物以及相关的代谢产物。我们建议这种优先性方法在将来可以更广泛地应用于世界上不同的地区。
精选自Jiahua Guo, Chris J. Sinclair, Katherine Selby, Alistair B.A. Boxall. Toxicological and ecotoxicological risk based prioritisation of pharmaceuticals in the natural environment. Environmental Toxicology and Chemistry: Volume 35, Issue 7, pages 1550–1559, July 2016. DOI: 10.1002/etc.3319
详情请见http://onlinelibrary.wiley.com/doi/10.1002/etc.3319/full
     

Strategic directions for agent-based modeling: avoiding the YAAWN syndrome

In this short communication, we examine how agent-based modeling has become common in land change science and is increasingly used to develop case studies for particular times and places. There is a danger that the research community is missing a prime opportunity to learn broader lessons from the use of agent-based modeling (ABM), or at the very least not sharing these lessons more widely. How do we find an appropriate balance between empirically rich, realistic models and simpler theoretically grounded models? What are appropriate and effective approaches to model evaluation in light of uncertainties not only in model parameters but also in model structure? How can we best explore hybrid model structures that enable us to better understand the dynamics of the systems under study, recognizing that no single approach is best suited to this task? Under what circumstances – in terms of model complexity, model evaluation, and model structure – can ABMs be used most effectively to lead to new insight for stakeholders? We explore these questions in the hope of helping the growing community of land change scientists using models in their research to move from ‘yet another model’ to doing better science with models.     

Species, functional groups, and thresholds in ecological resilience

The cross-scale resilience model states that ecological resilience is generated in part from the distribution of functions within and across scales in a system. Resilience is a measure of a system's ability to remain organized around a particular set of mutually reinforcing processes and structures, known as a regime. We define scale as the geographic extent over which a process operates and the frequency with which a process occurs. Species can be categorized into functional groups that are a link between ecosystem processes and structures and ecological resilience. We applied the cross-scale resilience model to avian species in a grassland ecosystem. A species' morphology is shaped in part by its interaction with ecological structure and pattern, so animal body mass reflects the spatial and temporal distribution of resources. We used the log-transformed rank-ordered body masses of breeding birds associated with grasslands to identify aggregations and discontinuities in the distribution of those body masses. We assessed cross-scale resilience on the basis of 3 metrics: overall number of functional groups, number of functional groups within an aggregation, and the redundancy of functional groups across aggregations. We assessed how the loss of threatened species would affect cross-scale resilience by removing threatened species from the data set and recalculating values of the 3 metrics. We also determined whether more function was retained than expected after the loss of threatened species by comparing observed loss with simulated random loss in a Monte Carlo process. The observed distribution of function compared with the random simulated loss of function indicated that more functionality in the observed data set was retained than expected. On the basis of our results, we believe an ecosystem with a full complement of species can sustain considerable species losses without affecting the distribution of functions within and across aggregations, although ecological resilience is reduced. We propose that the mechanisms responsible for shaping discontinuous distributions of body mass and the nonrandom distribution of functions may also shape species losses such that local extinctions will be nonrandom with respect to the retention and distribution of functions and that the distribution of function within and across aggregations will be conserved despite extinctions.     

Costs of expanding the network of protected areas as a response to climate change in the Cape Floristic Region

The expansion of protected areas is a critical component of strategies to promote the continued existence of biodiversity (i.e., life at all levels of biological organization) as climate changes, but scientific, social, and economic uncertainties associated with climate change are some of the major obstacles preventing such expansion. New models of climate change and species distribution and new methods of conservation planning now make it possible to explore the uncertainties associated with climate changes and species responses. Yet few reliable estimates of the costs of expanding protected areas and methods for determining these costs exist, largely because of the many (and uncertain) determinants of these costs. We developed a cost-accounting model to estimate the range in costs of various options for expanding protected areas and to explore the variables that drive these costs. Model development was informed by an existing plan to expand protected areas in the Cape Floristic Region of South Africa to address species conservation under a scenario of climate change. The 50-year present value of total costs varied from US$260 million ($1077/ha) for an off-reserve option that involves agreements with landowners and no compensation of forgone production and associated revenue to $1020 million ($4228/ha) for an on-reserve option that involves land acquisition and protection. The costs of acquiring land or compensating landowners for forgone production and development opportunities were the major drivers of the total costs across all options because most of the area identified in the protected-area expansion plan consisted of urban and high-quality agricultural lands. Total costs were also affected by changes in protected area extent and discount rate. Model-generated outputs such as these may be useful for informing implementation strategies and the allocation of future efforts in monitoring, data collection, and model development.     

A generalized approach for producing,quantifying, and validating citizen science data from wildlife images

Citizen science has the potential to expand the scope and scale of research in ecology and conservation, but many professional researchers remain skeptical of data produced by nonexperts. We devised an approach for producing accurate, reliable data from untrained, nonexpert volunteers. On the citizen science website www.snapshotserengeti.org , more than 28,000 volunteers classified 1.51 million images taken in a large‐scale camera‐trap survey in Serengeti National Park, Tanzania. Each image was circulated to, on average, 27 volunteers, and their classifications were aggregated using a simple plurality algorithm. We validated the aggregated answers against a data set of 3829 images verified by experts and calculated 3 certainty metrics—level of agreement among classifications (evenness), fraction of classifications supporting the aggregated answer (fraction support), and fraction of classifiers who reported “nothing here” for an image that was ultimately classified as containing an animal (fraction blank)—to measure confidence that an aggregated answer was correct. Overall, aggregated volunteer answers agreed with the expert‐verified data on 98% of images, but accuracy differed by species commonness such that rare species had higher rates of false positives and false negatives. Easily calculated analysis of variance and post‐hoc Tukey tests indicated that the certainty metrics were significant indicators of whether each image was correctly classified or classifiable. Thus, the certainty metrics can be used to identify images for expert review. Bootstrapping analyses further indicated that 90% of images were correctly classified with just 5 volunteers per image. Species classifications based on the plurality vote of multiple citizen scientists can provide a reliable foundation for large‐scale monitoring of African wildlife.