A biology-based dynamic approach for the reconciliation of acute and chronic toxicity tests: application to Daphnia magna

There is the need to integrate existing toxicity data in a coherent framework for extending their domain of applicability as well as their extrapolation potential. This integration would also reduce time and cost-consuming aspects of these tests and reduce animal usage. In this work, based on data extracted from literature, we have assessed the advantages that a dynamic biology-toxicant fate coupled model for Daphnia magna could provide when assessing toxicity data, in particular, the possibility to obtain from short-term (acute) toxicity test long-term (chronic) toxicity values taking into account the inherent variability of D. magna populations and the multiple sources of data. The results show that this approach overcomes some of the limitations of existing toxicity tests and that the prediction errors are considerably reduced when compared with the factor from 2 to 5 obtained using acute-to-chronic ratios.     

Carry-over of dietary organochlorine pesticides, PCDD/Fs, PCBs, and brominated flame retardants to Atlantic salmon (Salmo salar L.) fillets

Information on carry-over of contaminants from feed to animal food products is essential for appropriate human risk assessment of feed contaminants. The carry-over of potentially hazardous persistent organic pollutants (POPs) from feed to fillet was assessed in consumption sized Atlantic salmon (Salmo salar). Relative carry-over (defined as the fraction of a certain dietary POP retained in the fillet) was assessed in a controlled feeding trial, which provided fillet retention of dietary organochlorine pesticides (OCPs), dioxins (PCDD/Fs), polychlorinated biphenyls (PCBs), and brominated flame retardants (BFRs). Highest retention was found for OCPs, BFRs and PCBs (31-58%), and the lowest retentions were observed for PCDD/Fs congeners (10-34%). National monitoring data on commercial fish feed and farmed Atlantic salmon on the Norwegian market were used to provide commercially relevant feed-to-fillet transfer factors (calculated as fillet POP level divided by feed POP level), which ranged from 0.4 to 0.5, which is a factor 5-10 times higher than reported for terrestrial meat products. For the OCP with one of the highest relative carry-over, toxaphene, uptake and elimination kinetics were established. Model simulations that are based on the uptake and elimination kinetics gave predicted levels that were in agreement with the measured values. Application of the model to the current EU upper limit for toxaphene in feed (50 μg kg⁻¹) gave maximum fillet levels of 22 μg kg⁻¹, which exceeds the estimated permissible level (21 μg kg⁻¹) for toxaphene in fish food samples in Norway.     

Using the land transformation model to forecast vacant land

Growing or shrinking cities can experience increases in vacant land. As urban populations and boundaries fluctuate, holes can open in once tight urban areas. Many cities chase growth-oriented approaches to dealing with vacancies. It is critical to understand land-use alteration to accurately predict transformations of physical change in order to make better informed decisions about this phenomenon. This research utilizes the land transformation model (LTM), an artificial neural networking mechanism in Geographic Information Systems, to forecast vacant land. Variable influence on vacant land prediction and accuracy of the LTM is assessed by comparing input factors and patterns, using time-series data from 1990 to 2010 in Fort Worth, Texas, USA. Results indicate that the LTM can be useful in simulating vacant land-use changes but more precise mechanisms are necessary to increase accuracy. This will allow for more proactive decisions to better regulate the process of urban decline and regeneration.     

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.     

Vertical migration of radionuclides in undisturbed grassland soils

Literature data on numerical values obtained for the parameters of the two most popular models for simulating the migration of radionuclides in undisturbed soils have been compiled and evaluated statistically. Due to restrictions on the applicability of compartmental models, the convection–dispersion equation and its parameter values should be preferred. For radiocaesium, recommended values are derived for its effective convection velocity and dispersion coefficient. Data deficiencies still exist for radionuclides other than caesium and for soils of non-temperate environments.     

Modelling plant species richness using functional groups

Conservation biologists increasingly rely on spatial predictive models of biodiversity to support decision-making. Therefore, highly accurate and ecologically meaningful models are required at relatively broad spatial scales. While statistical techniques have been optimized to improve model accuracy, less focus has been given to the question: How does the autecology of a single species affect model quality? We compare a direct modelling approach versus a cumulative modelling approach for predicting plant species richness, where the latter gives more weight to the ecology of functional species groups. In the direct modelling approach, species richness is predicted by a single model calibrated for all species. In the cumulative modelling approach, the species were partitioned into functional groups, with each group calibrated separately and species richness of each group was cumulated to predict total species richness. We hypothesized that model accuracy depends on the ecology of individual species and that the cumulative modelling approach would predict species richness more accurately. The predictors explained plant species richness by ca. 25%. However, depending on the functional group the deviance explained varied from 3 to 67%. While both modelling approaches performed equally well, the models of the different functional groups highly varied in their quality and their spatial richness pattern. This variability helps to improve our understanding on how plant functional groups respond to ecological gradients.     

Projected Climate Impacts for the Amphibians of the Western Hemisphere

Abstract: Given their physiological requirements, limited dispersal abilities, and hydrologically sensitive habitats, amphibians are likely to be highly sensitive to future climatic changes. We used three approaches to map areas in the western hemisphere where amphibians are particularly likely to be affected by climate change. First, we used bioclimatic models to project potential climate‐driven shifts in the distribution of 413 amphibian species based on 20 climate simulations for 2071–2100. We summarized these projections to produce estimates of species turnover. Second, we mapped the distribution of 1099 species with restricted geographic ranges. Finally, using the 20 future climate‐change simulations, we mapped areas that were consistently projected to receive less seasonal precipitation in the coming century and thus were likely to have altered microclimates and local hydrologies. Species turnover was projected to be highest in the Andes Mountains and parts of Central America and Mexico, where, on average, turnover rates exceeded 60% under the lower of two emissions scenarios. Many of the restricted‐range species not included in our range‐shift analyses were concentrated in parts of the Andes and Central America and in Brazil's Atlantic Forest. Much of Central America, southwestern North America, and parts of South America were consistently projected to experience decreased precipitation by the end of the century. Combining the results of the three analyses highlighted several areas in which amphibians are likely to be significantly affected by climate change for multiple reasons. Portions of southern Central America were simultaneously projected to experience high species turnover, have many additional restricted‐range species, and were consistently projected to receive less precipitation. Together, our three analyses form one potential assessment of the geographic vulnerability of amphibians to climate change and as such provide broad‐scale guidance for directing conservation efforts.     

Bayesian Small Area Models for Assessing Wildlife Conservation Risk in Patchy Populations

Abstract:  Species conservation risk assessments require accurate, probabilistic, and biologically meaningful maps of population distribution. In patchy populations, the reasons for discontinuities are not often well understood. We tested a novel approach to habitat modeling in which methods of small area estimation were used within a hierarchical Bayesian framework. Amphibian occurrence was modeled with logistic regression that included third-order drainages as hierarchical effects to account for patchy populations. Models including the random drainage effects adequately represented species occurrences in patchy populations of 4 amphibian species in the Oregon Coast Range (U.S.A.). Amphibian surveys from other locations within the same drainage were used to calibrate local drainage-scale effects. Cross-validation showed that prediction errors for calibrated models were 77% to 86% lower than comparable regionally constructed models, depending on species. When calibration data were unavailable, small area and regional models performed similarly, although poorly. Small area estimation models complement wildlife ecology and habitat studies, and can help managers develop a regional picture of the conservation status for relatively rare species.     

An assessment methodology for successional systems. I. Null models and the regulatory framework

Standard procedures for evaluating environmental impact involve comparison between before and after conditions or scenarios or between treatment and control site pairs. In many cases, however, endogenous directional change (natural succession) is expected to occur at a significant rate over the period of concern, particularly for manmade systems such as impoundments. Static evaluations do not provide an adequate approach to such problems. A new evaluation frame is proposed. Nominal system behavior over time is characterized by a stochastic envelope around a nominal trajectory. We show that both the state variance and the sampling variance can change over time. In this context, environmental regulations can be framed as constraints, targets, or conformance to ideal trajectories. Statistical tests for determining noncompliance are explored relative to process variance, sample error, and sample size. Criteria are elucidated for choosing properties to monitor, sample size, and sampling interval.     

Differences among model simulations of climate change on the scale of resource regions

The climate simulations from atmospheric general circulation models (GCMs) are often used to analyze the potential effects of climate change on environmental resources. It has been demonstrated that there are differences among the simulations from various GCMs, on spatial scales ranging from global to regional. This paper quantifies the differences in temperature and precipitation simulated by three major GCMs for four specific regions: an agricultural region (the North American winter wheat belt), a hydrologic region (the Great Basin), a demographic region (the high-density population corridor of the northeast United States), and a political region (the state of Texas). Both the current (control) climate and the climatic response to a doubling of atmospheric carbon dioxide (CO₂) are consideredIn each region, even when the data are averaged on a seasonal basis, marked differences occurred in the areal average climate simulated by the different GCMs for both the control climate and the doubled-CO₂ climate. Thus, climate impact studies based on the simulations of more than one GCM could easily yield a range of possible results