A hybrid method for inverse characterization of subsurface contaminant flux

The methods presented in this work provide a potential tool for characterizing contaminant source zones in terms of mass flux. The problem was conceptualized by considering contaminant transport through a vertical "flux plane" located between a source zone and a downgradient region where contaminant concentrations were measured. The goal was to develop a robust method capable of providing a statement of the magnitude and uncertainty associated with estimated contaminant mass flux values. In order to estimate the magnitude and transverse spatial distribution of mass flux through a plane, the problem was considered in an optimization framework. Two numerical optimization techniques were applied, simulated annealing (SA) and minimum relative entropy (MRE). The capabilities of the flux plane model and the numerical solution techniques were evaluated using data from a numerically generated test problem and a nonreactive tracer experiment performed in a three-dimensional aquifer model. Results demonstrate that SA is more robust and converges more quickly than MRE. However, SA is not capable of providing an estimate of the uncertainty associated with the simulated flux values. In contrast, MRE is not as robust as SA, but once in the neighborhood of the optimal solution, it is quite effective as a tool for inferring mass flux probability density functions, expected flux values, and confidence limits. A hybrid (SA-MRE) solution technique was developed in order to take advantage of the robust solution capabilities of SA and the uncertainty estimation capabilities of MRE. The coupled technique provided probability density functions and confidence intervals that would not have been available from an independent SA algorithm and they were obtained more efficiently than if provided by an independent MRE algorithm.     

Water quality of runoff from revegetated mine spoil

Permanent vegetation plots were established on mixed overburden and topsoiled overburden on a lignite test pit in eastern Texas in 1982. Vegetative treatments included two grass-legume treatments [switchgrass (panicum virgattun) — sideoats grama (Bouteloua curtipendula) — subterrancan elover (Trifolitun subterranean) and litte bluestem (Schizachyriun scoparium) — sideoats grama (Bouteloua curtipendula) — Illinois hundleflower (Dessmanthus illinoiensis)] and three monocultures [Coastal bermudagrass (Cynodon dactylon), bahia grass (paspalum notatum) and yellow Indiangrass (Sorghastrum nutans)]. Water was applied to the 0.5m² plots using a sprinklertype rainfall simulator and quality of runoff was determined for each plot. Parameters analyzed included: settleable solids, total filterable solids, sediment production, infiltration rate, nitrites, nitrates, total iron and total manganese. Topsoiling significantly increased inliltration and significantly decreased filterable sediments, sediment production and settleable solids. The hydrologie qualities of the switchgrass-sideoats grama-subterranean elover mixture coincided closely with those of the Coastal bermudagrass monoculture.     

Predicting biodiversity change: outside the climate envelope, beyond the species-area curve

Efforts to anticipate threats to biodiversity take the form of species richness predictions (SRPs) based on simple correlations with current climate and habitat area. We review the major approaches that have been used for SRP, species-area curves and climate envelopes, and suggest that alternative research efforts may provide more understanding and guidance for management. Extinction prediction suffers from a number of limitations related to data and the novelty of future environments. We suggest additional attention to (1) identification of variables related to biodiversity that are diagnostic and potentially more predictable than extinction, (2) constraints on species dispersal and reproduction that will determine population persistence and range shifts, including limited sources or potential immigrants for many regions, and (3) changes in biotic interactions and phenology. We suggest combinations of observational and experimental approaches within a framework available for ingesting heterogeneous data sources. Together, these recommendations amount to a shift in emphasis from prediction of extinction numbers to identification of vulnerabilities and leading indicators of change, as well as suggestions for surveillance tools needed to evaluate important variables and the experiments likely to provide most insight.     

Genetic divergence of Maldivian and Micronesian demes of the damselfishes Stegastes nigricans,Chrysiptera biocellata,C. glauca and C. leucopoma (Pomacentridae)

Samples representing the damselfishes (Perciformes: Pomacentridae) Stegastes nigricans, Chrysiptera biocellata, C. glauca, and C. leucopoma from North Male Atoll, Republic of Maldives, and Guam, Southern Marianas, were surveyed electrophoretically. A sample representing C. leucopoma from Ngemelis Island, Republic of Palau, was included in the analysis to provide a within-Micronesia comparison. On average, products of 23 presumptive protein-coding loci were examined in each sample. In comparisons of Maldivian and Guamanian samples, absolute or virtually fixed allelic differences were detected at: (1) ADA ^* and PEPS ^* for Stegastes nigricans; (2) ADA ^*, AAT-1 ^*, AAT-2 ^*, and mMDH ^* for C. biocellata, and; (3) ADA ^*, AAT-1 ^*, and AAT-2 ^* for C. glauca. At three polymorphic loci, ADA ^*, sMDH-1 ^*, and sMDH-2 ^*, similar allele frequencies were found in Palauan and Guamanian samples representing C. leucopoma, suggesting that these samples share a gene pool. Significantly different allele frequencies at ADA ^* and sMDH-1 ^* and a virtually fixed allelic difference at sMDH-2 ^* were detected between the Maldivian samples and each of the Micronesian samples representing C. leucopoma. The observed patterns of allele frequency differentiation suggest that Maldivian and Micronesian samples of each of the four study species represent separate demes.     

Making Sense of the Policy Process for Carnivore Conservation

Grizzly bears ( Ursus arctos horribilis ), mountain lions ( Puma concolor ), wolverines ( Gulo gulo ), wolves ( Canis lupus ), and lynx ( Felis lynx ) are all top-level carnivores in the Rocky Mountains of the northern U.S. and southern Canada. Because of their body size and high trophic position, these species require abundant prey species and large habitat areas—requirements that make their conservation a controversial public policy problem. Because the challenge of conserving these species extends beyond biological issues, it is necessary to involve other relevant disciplines and perspectives in understanding and solving the problem. Our examination of the context, content, and process of large carnivore conservation policies suggests more effective and active roles for scientists in designing solutions to the problem of landscape-level carnivore conservation. Scientists must develop an understanding of the range of participants in the policy process and the ways in which these participants receive and utilize information. This knowledge of the policy process could help scientists to better understand their roles in framing and clarifying policy questions, projecting the consequences of various alternatives, and presenting policy information in appropriate fora.     

Extinction risk of the endemic vascular flora of Kauai,Hawaii, based on IUCN assessments

The International Union for Conservation of Nature's Red List of Threatened Species (IUCN Red List) is the world's most comprehensive information source on the global conservation status of species. Governmental agencies and conservation organizations increasingly rely on IUCN Red List assessments to develop conservation policies and priorities. Funding agencies use the assessments as evaluation criteria, and researchers use meta-analysis of red-list data to address fundamental and applied conservation science questions. However, the circa 143,000 IUCN assessments represent a fraction of the world's biodiversity and are biased in regional and organismal coverage. These biases may affect conservation priorities, funding, and uses of these data to understand global patterns. Isolated oceanic islands are characterized by high endemicity, but the unique biodiversity of many islands is experiencing high extinction rates. The archipelago of Hawaii has one of the highest levels of endemism of any floristic region; 90% of its 1367 native vascular plant taxa are classified as endemic. We used the IUCN's assessment of the complete single-island endemic (SIE) vascular plant flora of Kauai, Hawaii, to assess the proportion and drivers of decline of threatened plants in an oceanic island setting. We compared the IUCN assessments with federal, state, and other local assessments of Kauai species or taxa of conservation concern. Finally, we conducted a preliminary assessment for all 1044 native vascular plants of Hawaii based on IUCN criterion B by estimating area of occupancy, extent of occurrence, and number of locations to determine whether the pattern found for the SIE vascular flora of Kauai is comparable to the native vascular flora of the Hawaiian Islands. We compared our results with patterns observed for assessments of other floras. According to IUCN, 256 SIE vascular plant taxa are threatened with extinction and 5% are already extinct. This is the highest extinction risk reported for any flora to date. The preliminary assessment of the native vascular flora of Hawaii showed that 72% (753 taxa) is threatened. The flora of Hawaii may be one of the world's most threatened; thus, increased and novel conservation measures in the state and on other remote oceanic islands are urgently needed.     

Computing sustainable manufacturing index with fuzzy analytic hierarchy process

The growing industrial interest in adopting sustainability programmes has ushered in studies regarding sustainability indicators which have continually flourished in current literature. However, limited attention is given to the development of priority ranking, which is an important input for any adopting firm. This paper presents a hybrid multi-criteria approach in determining priority areas in sustainable manufacturing (SM). Using fuzzy analytic hierarchy process to address uncertainty in hierarchical decision-making, this paper determines SM priority strategies and eventually identifies even lower level strategies. The computed sustainable manufacturing index is presented at both the organizational and operational levels for a real case study of an industrial plastic manufacturing firm. This work provides a detailed and transparent hierarchical decision-making approach based on SM framework, the use of which could be valuable to practicing managers across industries in their pursuit of greater sustainability.