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.     

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.     

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.     

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.     

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.     

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.     

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     

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.