Predicting occurrence of juvenile shark habitat to improve conservation planning

Fishing and habitat degradation have increased the extinction risk of sharks, and conservation strategies recognize that survival of juveniles is critical for the effective management of shark populations. Despite the rapid expansion of marine protected areas (MPAs) globally, the paucity of shark‐monitoring data on large scales (100s–1000s km) means that the effectiveness of MPAs in halting shark declines remains unclear. Using data collected by baited remote underwater video systems (BRUVS) in northwestern Australia, we developed generalized linear models to elucidate the ecological drivers of habitat suitability for juvenile sharks. We assessed occurrence patterns at the order and species levels. We included all juvenile sharks sampled and the 3 most abundant species sampled separately (grey reef [Carcharhinus amblyrhynchos], sandbar [Carcharhinus plumbeus], and whitetip reef sharks [Triaenodon obesus]). We predicted the occurrence of juvenile sharks across 490,515 km² of coastal waters and quantified the representation of highly suitable habitats within MPAs. Our species‐level models had higher accuracy (? ≥ 0.69) and deviance explained (≥48%) than our order‐level model (? = 0.36 and deviance explained of 10%). Maps of predicted occurrence revealed different species‐specific patterns of highly suitable habitat. These differences likely reflect different physiological or resource requirements between individual species and validate concerns over the utility of conservation targets based on aggregate species groups as opposed to a species‐focused approach. Highly suitable habitats were poorly represented in MPAs with the most restrictions on extractive activities. This spatial mismatch possibly indicates a lack of explicit conservation targets and information on species distribution during the planning process. Non‐extractive BRUVS provided a useful platform for building the suitability models across large scales to assist conservation planning across multiple maritime jurisdictions, and our approach provides a simple for method for testing the effectiveness of MPAs.     

Prevalence of the Crayfish Plague Pathogen Aphanomyces astaci in Invasive American Crayfishes in the Czech Republic

Abstract:  In Central Europe invasive North American crayfishes are carriers of the oomycete Aphanomyces astaci, which causes crayfish plague. This lethal disease currently represents one of the major threats to native European crayfishes. We used molecular methods—species-specific amplification and sequencing of the pathogen DNA—to investigate the prevalence of individuals latently infected with A. astaci in 28 populations of two invasive American crayfish species (6 of the signal crayfish [ Pacifastacus leniusculus ] and 22 of the spiny-cheek crayfish [ Orconectes limosus ]) in the Czech Republic. The pathogen occurred in 17 investigated populations. We recorded a high variation in positive reactions, ranging from 0% to 100%, in populations of O. limosus . In P. leniusculus, however, only one individual out of 124 tested positive for the pathogen. There was a clear relationship between the water body type and pathogen prevalence in O. limosus . Infection ratios in isolated standing waters were usually low, whereas in running waters, pathogen prevalence often exceeded 50%. Other evaluated characteristics of potential plague pathogen carriers (size, sex, and the presence of melanized spots in the cuticle) seemed to be unrelated to infection. Our data suggest that in contrast to other European countries, O. limosus seems to be the primary reservoir of crayfish plague in the Czech Republic. Although all populations of alien American crayfishes may be potential sources of infections and should be managed as such, knowledge on the prevalence of the plague pathogen at various localities may allow managers to focus conservation efforts on the most directly endangered populations of native crayfishes.     

Distribution,fate and formation of non-extractable residues of a nonylphenol isomer in soil with special emphasis on soil derived organo-clay complexes

Anthropogenic contaminants like nonylphenols (NP) are added to soil, for instance if sewage-sludge is used as fertilizer in agriculture. A commercial mixture of NP consists of more than 20 isomers. For our study, we used one of the predominate isomers of NP mixtures, 4-(3,5-dimethylhept-3-yl)phenol, as a representative compound. The aim was to investigate the fate and distribution of the isomer within soil and soil derived organo-clay complexes. Therefore, ¹⁴C- and ¹³C-labeled NP was added to soil samples and incubated up to 180 days. Mineralization was measured and soil samples were fractionated into sand, silt and clay; the clay fraction was further separated in humic acids, fulvic acids and humin. The organo-clay complexes pre-incubated for 90 or 180 days were re-incubated with fresh soil for 180 days, to study the potential of re-mobilization of incorporated residues. The predominate incorporation sites of the nonylphenol isomer in soil were the organo-clay complexes. After 180 days of incubation, 22 % of the applied ¹⁴C was mineralized. The bioavailable, water extractable portion was low (9 % of applied ¹⁴C) and remained constant during the entire incubation period, which could be explained by an incorporation/release equilibrium. Separation of organo-clay complexes, after extraction with solvents to release weakly incorporated, bioaccessible portions, showed that non-extractable residues (NER) were preferentially located in the humic acid fraction, which was regarded as an effect of the chemical composition of this fraction. Generally, 27 % of applied ¹⁴C was incorporated into organo-clay complexes as NER, whereas 9 % of applied ¹⁴C was bioaccessible after 180 days of incubation. The re-mobilization experiments showed on the one hand, a decrease of the bioavailability of the nonylphenol residues due to stronger incorporation, when the pre-incubation period was increased from 90 to 180 days. On the other hand, a shift of these residues from the clay fraction to other soil fractions was observed, implying a dynamic behavior of incorporated residues, which may result in bioaccessibility of the NER of nonylphenol.     

APPLICATION OF ENHANCED ANNEALING TO GROUND WATER REMEDIATION DESIGN1

ABSTRACT: A methodology for ground water remediation design has been developed that interfaces ground water simulation models with an enhanced annealing optimizer. The ground water flow and transport simulators provide the ability to consider site‐specific contamination and geohydrologic conditions directly in the assessment of alternative remediation system designs. The optimizer facilitates analysis of tradeoffs between technical, environmental, regulatory, and financial risks for alternative design and operation scenarios. A ground water management model using an optimization method referred to as “enhanced annealing” (simulated annealing enhanced to include “directional search” and “memory” mechanisms) has been developed and successfully applied to an actual restoration problem. The demonstration site is the contaminated unconfined aquifer referred to as N‐Springs located at Han‐ford, Washington. Results of the demonstration show the potential for improving groundwater restoration system performance while reducing overall system cost.     

Species distribution modelling—Effect of design and sample size of pseudo-absence observations

We explored the effect of varying pseudo-absence data in species distribution modelling using empirical data for four real species and simulated data for two imaginary species. In all analyses we used a fixed study area, a fixed set of environmental predictors and a fixed set of presence observations. Next, we added pseudo-absence data generated by different sampling designs and in different numbers to assess their relative importance for the output from the species distribution model. The sampling design strongly influenced the predictive performance of the models while the number of pseudo-absences had minimal effect on the predictive performance. We attribute much of these results to the relationship between the environmental range of the pseudo-absences (i.e. the extent of the environmental space being considered) and the environmental range of the presence observations (i.e. under which environmental conditions the species occurs). The number of generated pseudo-absences had a direct effect on the predicted probability, which translated to different distribution areas. Pseudo-absence observations that fell within grid cells with presence observations were purposely included in our analyses. We discourage the practice of excluding certain pseudo-absence data because it involves arbitrary assumptions about what are (un)suitable environments for the species being modelled.     

Agricultural technology,wealth, and responsibility

Responsibility as a dual to human rights is presented as a moral alternative to extended, complex systems of animal and ecological rights. This simple idea of responsibility is then applied to four levels of agricultural technology: animal (nature) rights, conservation, organization of agriculture, and people versus planet relationships. The stewardship argument is freed from at least some of the complications of animal rights and ecology, but leaves responsibility with humans to do the right thing.The views expressed are the author's and do not necessarily represent policies or views of the U.S. Department of Agriculture.     

A NEW LOOK AT FLOOD RISK DETERMINATION1

ABSTRACT: The probability distributions of annual peak flows used in flood risk analysis quantify the risk that a design flood will be exceeded. But the parameters of these distributions are themselves to a degree uncertain and this uncertainty increases the risk that the flood protection provided will in fact prove to be inadequate. The increase in flood risk due to parameter uncertainty is small when a fairly long record of data is available and the annual flood peaks are serially independent, which is the standard assumption in flood frequency analysis. But standard tests for serial independence are insensitive to the type of grouping of high and low values in a time series, which is measured by the Hurst coefficient. This grouping increases the parameter uncertainty considerably. A study of 49 annual peak flow series for Canadian rivers shows that many have a high Hurst coefficient. The corresponding increase in flood risk due to parameter uncertainty is shown to be substantial even for rivers with a long record, and therefore should not be neglected. The paper presents a method of rationally combining parameter uncertainty due to serial correlation, and the stochastic variability of peak flows in a single risk assessment. In addition, a relatively simple time series model that is capable of reproducing the observed serial correlation of flood peaks is presented.     

A COMPARISON OF STREAMFLOW GENERATION MODELS FOR RESERVOIR CAPACITY-YIELD ANALYSIS1

ABSTRACT: An analysis of four streamflow generation schemes for the use in the estimation of the required conservation storage for a single reservoir is presented. The comparison of the generating schemes should aid in the selection of an appropriate model type for the reservoir sizing problem. The streamflow generation models are compared using two criteria. The first comparison is between the statistics of the generated streamflow sequences and the corresponding statistics from the historical record. The second evaluation compares the median reservoir size determined by each model with the required storage based on the historical flow sequence. The results of a comparative analysis for monthly streamflow data for the Rzav River in Yugoslavia are presented and discussed. The results indicate that both evaluation criteria are required to discriminate between the various options.     

COMPARISON OF RESERVOIR LINEAR OPERATION RULES USING LINEAR AND DYNAMIC PROGRAMMING1

ABSTRACT: Mathematical optimization techniques are used to study the operation and design of a single, multi-purpose reservoir system. Optimal monthly release policies are derived for Hoover Reservoir, located in Central Ohio, using chance-constrained linear programming and dynamic programming-regression methodologies. Important characteristics of the former approach are derived, discussed, and graphically illustrated using Hoover Reservoir as a case example. Simulation procedures are used to examine and compare the overall performance of the optimal monthly reservoir release policies derived under the two approaches. Results indicate that, for the mean detention time and the corresponding safe yield target water supply release under existing design of Hoover Reservoir, the dynamic programming policies produce lower average annual losses (as defined by a two-sided quadratic loss function) while achieving at least as high reliability levels when compared to policies derived under the chance-constrained linear programming method. In making this comparison, the reservoir release policies, although not identical, are assumed to be linear. This restricted form of the release policy is necessary to make the chance-constrained programming method mathematically tractable.