Sources and major biogeochemical pathways of organic matter in the mangrove system of Rufiji estuary

Fatty acids were extracted from the surface sediments (10 cm) of three sampling sites of Rufiji estuary to infer their sources and biogeochemical pathways. The fatty acids ranging from C₈ to C₂₄ were distinguished from this study, and were broadly classified into saturated (SFAs), monounsaturated (MUFAs) and polyunsaturated fatty acids (PUFAs). SFAs were found to be the major fraction at station 1 and 3 where as at station 2, MUFAs dominated. A total of 19 fatty acids with a total concentration of 64.91 μg/g dry weight were characterised at station 1. C_16:0 was the most abundant fatty acid contributing 21.94% of total fatty acids (TFAs). C_22:2 was the second most abundant, which accounted for 9.46% of TFAs. Fatty acids ranging from C₁₂ to C₂₄ were identified at station 2. C₂₀ fatty acid was the most abundant fatty acid contributing 21.94%, followed by C_16:0. At station 3, fatty acids ranging from C₈ to C₂₄ were obtained. The PUFA C_20:5n-3 was the most abundant fatty acid contributing 21.65%, followed by C_24:0 (15.00% of TFAs). The ratio of lower molecular weight (LMW) to higher molecular weight (HMW) biomarkers was used as an indicators to distinguish higher plants organic matter from algae-derived fatty acids.     

A performance-based tabular approach for joint systematic improvement of risk control and resilience applied to telecommunication grid,gas network,and ultrasound localization system

Environment Systems and Decisions - Organizational and technical approaches have proven successful in increasing the performance and preventing risks at socio-technical systems at all scales....     

Using expert knowledge to support Endangered Species Act decision-making for data-deficient species

Many questions relevant to conservation decision-making are characterized by extreme uncertainty due to lack of empirical data and complexity of the underlying ecologic processes, leading to a rapid increase in the use of structured protocols to elicit expert knowledge. Published ecologic applications often employ a modified Delphi method, where experts provide judgments anonymously and mathematical aggregation techniques are used to combine judgments. The Sheffield elicitation framework (SHELF) differs in its behavioral approach to synthesizing individual judgments into a fully specified probability distribution for an unknown quantity. We used the SHELF protocol remotely to assess extinction risk of three subterranean aquatic species that are being considered for listing under the U.S. Endangered Species Act. We provided experts an empirical threat assessment for each known locality over a video conference and recorded judgments on the probability of population persistence over four generations with online submission forms and R-shiny apps available through the SHELF package. Despite large uncertainty for all populations, there were key differences between species’ risk of extirpation based on spatial variation in dominant threats, local land use and management practices, and species’ microhabitat. The resulting probability distributions provided decision makers with a full picture of uncertainty that was consistent with the probabilistic nature of risk assessments. Discussion among experts during SHELF's behavioral aggregation stage clearly documented dominant threats (e.g., development, timber harvest, animal agriculture, and cave visitation) and their interactions with local cave geology and species’ habitat. Our virtual implementation of the SHELF protocol demonstrated the flexibility of the approach for conservation applications operating on budgets and time lines that can limit in-person meetings of geographically dispersed experts.     

Focus and social contagion of environmental organization advocacy on Twitter

Agriculture, overexploitation, and urbanization remain the major threats to biodiversity in the Anthropocene. The attention these threats garner among leading environmental nongovernmental organizations (eNGOs) and the wider public is critical in fostering the political will necessary to reverse biodiversity declines worldwide. I analyzed the advocacy of leading eNGOs on Twitter by scraping account timelines, screening content for advocacy relating to biodiversity threats and, for prevalent threats, further screening content for positive and negative emotional language with a sentiment lexicon. Twitter advocacy was dominated by the major threats of climate change and overexploitation and the minor threat of plastic pollution. The major threats of agriculture, urbanization, invasions, and pollution were rarely addressed. Content relating to overexploitation and plastic pollution was more socially contagious than other content. Increasing emotional negativity further increased social contagion, whereas increasing emotional positivity did not. Scientists, policy makers, and eNGOs should consider how narrowly focused advocacy on platforms like Twitter will contribute to effective global biodiversity conservation.     

Soils from abandoned shooting range facilities as contamination source of potentially toxic elements: distribution among soil geochemical fractions

Environmental Geochemistry and Health - Civilian and military shooting range facilities cause environmental issues in several countries due to the accumulation of Potentially Toxic Elements; as a...     

Improving species status assessments under the U.S. Endangered Species Act and implications for multispecies conservation challenges worldwide

Despite its successes, the U.S. Endangered Species Act (ESA) has proven challenging to implement due to funding limitations, workload backlog, and other problems. As threats to species survival intensify and as more species come under threat, the need for the ESA and similar conservation laws and policies in other countries to function efficiently has grown. Attempts by the U.S. Fish and Wildlife Service (USFWS) to streamline ESA decisions include multispecies recovery plans and habitat conservation plans. We address species status assessment (SSA), a USFWS process to inform ESA decisions from listing to recovery, within the context of multispecies and ecosystem planning. Although existing SSAs have a single-species focus, ecosystem-based research can efficiently inform multiple SSAs within a region and provide a foundation for transition to multispecies SSAs in the future. We considered at-risk grassland species and ecosystems within the southeastern United States, where a disproportionate number of rare and endemic species are associated with grasslands. To initiate our ecosystem-based approach, we used a combined literature-based and structured World Café workshop format to identify science needs for SSAs. Discussions concentrated on 5 categories of threats to grassland species and ecosystems, consistent with recommendations to make shared threats a focus of planning under the ESA: (1) habitat loss, fragmentation, and disruption of functional connectivity; (2) climate change; (3) altered disturbance regimes; (4) invasive species; and (5) localized impacts. For each threat, workshop participants identified science and information needs, including database availability, research priorities, and modeling and mapping needs. Grouping species by habitat and shared threats can make the SSA process and other planning processes for conservation of at-risk species worldwide more efficient and useful. We found a combination of literature review and structured discussion effective for identifying the scientific information and analysis needed to support the development of multiple SSAs. Article impact statement: Species status assessments can be improved by an ecosystem-based approach that groups imperiled species by shared habitats and threats.     

Metacommunity dynamics over 16 years in a pyrogenic shrubland

Metacommunity theory allows predictions about the dynamics of potentially interacting species' assemblages that are linked by dispersal, but strong empirical tests of the theory are rare. We analyzed the metacommunity dynamics of Florida rosemary scrub, a patchily distributed pyrogenic community, to test predictions about turnover rates, community nestedness, and responses to patch size, arrangement, and quality. We collected occurrence data for 45 plant species from 88 rosemary scrub patches in 1989 and 2005 and used growth form, mechanism of regeneration after fire, and degree of habitat specialization to categorize species by life history. We tested whether patch size, fire history, and structural connectivity (a measure of proximity and size of surrounding patches) could be used to predict apparent extinctions and colonizations. In addition, we tested the accuracy of incidence-function models built with the patch survey data from 1989. After fire local extinction rates were higher for herbs than woody plants, higher for species that regenerated only from seed than species able to resprout, and higher for generalist than specialist species. Fewer rosemary specialists and a higher proportion of habitat generalists were extirpated on recently burned patches than on patches not burned between 1989 and 2005. Nestedness was highest for specialists among all life-history groups. Estimated model parameters from 1989 predicted the observed (1989-2005) extinction rates and the number of patches with persistent populations of individual species. These results indicate that species with different life-history strategies within the same metacommunity can have substantially different responses to patch configuration and quality. Real metacommunities may not conform to certain assumptions of simple models, but incidence-function models that consider only patch size, configuration, and quality can have significant predictive accuracy.     

Anaerobic digestion of chicken feather with swine manure or slaughterhouse sludge for biogas production

Biogas production from anaerobic digestion of chicken feathers with swine manure or slaughterhouse sludge was assessed in two separate experiments. Ground feathers without any pre-treatment were added to 42-L digesters inoculated with swine manure or slaughterhouse sludge, representing 37% and 23% of total solids, respectively and incubated at 25 °C in batch mode. Compared to the control without feather addition, total CH₄ production increased by 130% (P < 0.001) and 110% (P = 0.09) in the swine manure and the slaughterhouse sludge digesters, respectively. Mixed liquor NH₄N concentration increased (P < 0.001) from 4.8 and 3.1 g/L at the beginning of the digestion to 6.9 and 3.5 g/L at the end of digestion in the swine manure and the slaughterhouse sludge digesters, respectively. The fraction of proteolytic microorganisms increased (P < 0.001) during the digestion from 12.5% to 14.5% and 11.3% to 13.0% in the swine manure and the slaughterhouse sludge digesters with feather addition, respectively, but decreased in the controls. These results are reflective of feather digestion. Feather addition did not affect CH₄ yields of the swine manure digesters (P = 0.082) and the slaughterhouse sludge digesters (P = 0.21), indicating that feathers can be digested together with swine manure or slaughterhouse sludge without negatively affecting the digestion of swine manure and slaughterhouse sludge.     

Chemical defenses, nutritional quality, and structural components in three sponge species: Ircinia felix, I. campana, and Aplysina fulva

Allocating chemical defenses to regions or tissues most at risk for predatory attack may provide protection while simultaneously minimizing associated metabolic costs. Chemical defense allocation patterns were investigated in the aspiculate sponges Ircinia felix, I. campana, and Aplysina fulva collected between July 2005 and April 2006 from J Reef off the coast of Georgia, U.S.A. It was predicted that chemical defenses would be (1) higher in the outermost 2 mm layer of the sponge; (2) positively correlated with tissue nutritional quality; and (3) correlated with structural components such as spongin fibers. Whereas defensive chemicals were concentrated in the outer 2 mm of A. fulva, the Ircinia species had higher concentrations in deeper tissue layers. Furthermore, no significant positive or negative correlation between chemical defenses and nutritional quality or levels of structural components was observed in these sponges. Overall, these results do not support the prediction that predation pressure by fish and large mobile invertebrates significantly impacts chemical defense allocation in these sponges.     

Emergy algebra: Improving matrix methods for calculating transformities

Transformity is one of the core concepts in Energy Systems Theory and it is fundamental to the calculation of emergy. Accurate evaluation of transformities and other emergy per unit values is essential for the broad acceptance, application and further development of emergy methods. Since the rules for the calculation of emergy are different from those for energy, particular calculation methods and models have been developed for use in the emergy analysis of networks, but double counting errors still occur because of errors in applying these rules when estimating the emergies of feedbacks and co-products. In this paper, configurations of network energy flows were classified into seven types based on commonly occurring combinations of feedbacks, splits, and co-products. A method of structuring the network equations for each type using the rules of emergy algebra, which we called “preconditioning” prior to calculating transformities, was developed to avoid double counting errors in determining the emergy basis for energy flows in the network. The results obtained from previous approaches, the Track Summing Method, the Minimum Eigenvalue Model and the Linear Optimization Model, were reviewed in detail by evaluating a hypothetical system, which included several types of interactions and two inputs. A Matrix Model was introduced to simplify the calculation of transformities and it was also tested using the same hypothetical system. In addition, the Matrix Model was applied to two real case studies, which previously had been analyzed using the existing method and models. Comparison of the three case studies showed that if the preconditioning step to structure the equations was missing, double counting would lead to large errors in the transformity estimates, up to 275 percent for complex flows with feedback and co-product interactions. After preconditioning, the same results were obtained from all methods and models. The Matrix Model reduces the complexity of the Track Summing Method for the analysis of complex systems, and offers a more direct and understandable link between the network diagram and the matrix algebra, compared with the Minimum Eigenvalue Model or the Linear Optimization Model.