Derivation of aquatic predicted no-effect concentration (PNEC) for 2,4-dichlorophenol: comparing native species data with non-native species data

2,4-Dichlorophenol (2,4-DCP) is known as an important chemical intermediate and an environmental endocrine disruptor. There is no paper dealing with the predicted no-effect concentration (PNEC) of 2,4-DCP, mainly due to shortage of chronic and site-specific toxicity data. In the present study, toxicity data was obtained from the tests using six Chinese native aquatic species. The HC₅ (hazardous concentration for 5% of species) was derived based on the constructed species sensitivity distribution (SSD), which was compared with that derived from literature toxicity data of non-native species. For invertebrates, the survival no-observed effect concentrations (NOECs) were 0.05 and 1.00 mg L⁻¹ for Macrobrachium superbum and Corbicula fluminea, respectively. NOECs based on fishes’ growth were 0.10, 0.20 and 0.40 mg L⁻¹ for Mylopharyngodon piceus, Plagiognathops microlepis and Erythroculter ilishaeformis, respectively. For aquatic plant Soirodela polyrhiza, NOEC based on concentration of chlorophyll was 1.00 mg L⁻¹. A final PNEC calculated using the SSD approach with a 50% certainty based on different taxa ranged between 0.008 and 0.045 mg L⁻¹. There is no significant difference between HC₅ derived from native and that from non-native taxa.     

Comparison of community composition and species diversity of understorey and overstorey tree species in a dry tropical forest of northern India

The study focuses on understorey-overstorey plant community dynamics in a dry tropical forest to facilitate appropriate management decisions. We compare community composition and species diversity of the understorey vegetation among five dry tropical forest sites in northern India. A total of 1500 quadrats distributed over 15 one-ha permanent plots in five sites differing in the degree of disturbance, were used to enumerate the understorey tree species and the results were compared with overstorey tree layer. The non-metric multidimensional scaling (NMS) ordination revealed that human disturbance intensity, as well as the overall disturbance regimes, and soil water holding capacity controlled the organisation of dry tropical forest understorey composition through effects on soil organic matter. The alpha-diversity and its components decreased with increasing human disturbance intensity, reflecting utilisation pressure and decreased soil fertility, as also revealed by the analysis of overstorey tree layer. There was a significant positive relationship between overstorey and understorey diversity. Results suggest that in the future, the existing understorey tree communities may replace the current dry tropical forest communities under prevailing environmental conditions. The study also asserts that the rate of species accumulation will be greater in more disturbed sites as well as at small spatial scale within each disturbance level.     

Grassland Plant Composition Alters Vehicular Disturbance Effects in Kansas,USA

Many “natural” areas are exposed to military or recreational off-road vehicles. The interactive effects of different types of vehicular disturbance on vegetation have rarely been examined, and it has been proposed that some vegetation types are less susceptible to vehicular disturbance than others. At Fort Riley, Kansas, we experimentally tested how different plant community types changed after disturbance from an M1A1 Abrams tank driven at different speeds and turning angles during different seasons. The greatest vegetation change was observed because of driving in the spring in wet soils and the interaction of turning while driving fast (vegetation change was measured with Bray-Curtis dissimilarity). We found that less vegetation change occurred in communities with high amounts of native prairie vegetation than in communities with high amounts of introduced C₃ grasses, which is the first experimental evidence we are aware of that suggests plant communities dominated by introduced C₃ grasses changed more because of vehicular disturbance than communities dominated by native prairie grasses. We also found that vegetation changed linearly with vehicular disturbance intensity, suggesting that at least initially there was no catastrophic shift in vegetation beyond a certain disturbance intensity threshold. Overall, the intensity of vehicular disturbance appeared to play the greatest role in vegetation change, but the plant community type also played a strong role and this should be considered in land use planning. The reasons for greater vegetation change in introduced C₃ grass dominated areas deserve further study.     

Sensitivity of species-distribution models to error,bias, and model design: An application to resource selection functions for woodland caribou

Models that predict distribution are now widely used to understand the patterns and processes of plant and animal occurrence as well as to guide conservation and management of rare or threatened species. Application of these methods has led to corresponding studies evaluating the sensitivity of model performance to requisite data and other factors that may lead to imprecise or false inferences. We expand upon these works by providing a relative measure of the sensitivity of model parameters and prediction to common sources of error, bias, and variability. We used a one-at-a-time sample design and GPS location data for woodland caribou (Rangifer tarandus caribou) to assess one common species-distribution model: a resource selection function. Our measures of sensitivity included change in coefficient values, prediction success, and the area of mapped habitats following the systematic introduction of geographic error and bias in occurrence data, thematic misclassification of resource maps, and variation in model design. Results suggested that error, bias and model variation have a large impact on the direct interpretation of coefficients. Prediction success and definition of important habitats were less responsive to the perturbations we introduced to the baseline model. Model coefficients, prediction success, and area of ranked habitats were most sensitive to positional error in species locations followed by sampling bias, misclassification of resources, and variation in model design. We recommend that researchers report, and practitioners consider, levels of error and bias introduced to predictive species-distribution models. Formal sensitivity and uncertainty analyses are the most effective means for evaluating and focusing improvements on input data and considering the range of values possible from imperfect models.     

Incorporating anthropogenic variables into a species distribution model to map gypsy moth risk

This paper presents a novel methodology for multi-scale and multi-type spatial data integration in support of insect pest risk/vulnerability assessment in the contiguous United States. Probability of gypsy moth (Lymantria dispar L.) establishment is used as a case study. A neural network facilitates the integration of variables representing dynamic anthropogenic interaction and ecological characteristics. Neural network model (back-propagation network [BPN]) results are compared to logistic regression and multi-criteria evaluation via weighted linear combination, using the receiver operating characteristic area under the curve (AUC) and a simple threshold assessment. The BPN provided the most accurate infestation-forecast predictions producing an AUC of 0.93, followed by multi-criteria evaluation (AUC = 0.92) and logistic regression (AUC = 0.86) when independently validating using post model infestation data. Results suggest that BPN can provide valuable insight into factors contributing to introduction for invasive species whose propagation and establishment requirements are not fully understood. The integration of anthropogenic and ecological variables allowed production of an accurate risk model and provided insight into the impact of human activities.     

Simultaneous measurement of aqueous redox-sensitive elements and their species across the soil-water interface

The redox-sensitive elements, such as iron, manganese, sulfur, phosphorus, and arsenic, shift their speciation every millimeter (mm) across the soil-water interface in the flooded soil environments. Monitoring of element speciation at this high-resolution (HR) within the SWI is still difficult. The key challenge lies in obtaining sufficient porewater samples at specific locations along the soil gradient for downstream analysis. Here with an optimized inductively coupled plasma mass spectrometry (ICP-MS) method and a HR porewater sampler, we demonstrate mm-scale element profiles mapping across the SWI in paddy soils. High-concentrations of iron and manganese (> 10 mg/L) were measured by ICP-MS in an extended dynamic range mode to avoid signal overflow. The iron profile along the SWI generated by the ICP-MS method showed no significant difference (p < 0.05) compared to that measured independently using a colorimetric method. Furthermore, four arsenic (arsenite, arsenate, monomethylarsonic and dimethylarsinic acid), two phosphorus (phosphite and phosphate) and two sulfur (sulfide and sulfate) species were separated in 10 min by ion chromatography -ICP-MS with the NH₄HCO₃ mobile phase. We verified the technique using paddy soils collected from the field, and present the mm-scale profiles of iron, manganese, and arsenic, phosphorus, sulfur species (relative standard deviation < 8%). The technique developed in this study will significantly promote the measurement throughput in limited samples (e.g. 100 μL) collected by HR samplers, which would greatly facilitate redox-sensitive elements biogeochemical cycling in saturated soils.     

Disentangling the effects of heterogeneity, stochastic dynamics and sampling in a community of aquatic insects

A dynamic and heterogeneous species abundance model generating the lognormal species abundance distribution is fitted to time series of species data from an assemblage of stoneflies and mayflies (Plecoptera and Ephemeroptera) of an aquatic insect community collected over a period of 15 years. In each year except one, we analyze 5 parallel samples taken at the same time of the season giving information about the over-dispersion in the sampling relative to the Poisson distribution. Results are derived from a correlation analysis, where the correlation in the bivariate normal distribution of log abundance is used as measurement of similarity between communities. The analysis enables decomposition of the variance of the lognormal species abundance distribution into three components due to heterogeneity among species, stochastic dynamics driven by environmental noise, and over-dispersion in sampling, accounting for 62.9, 30.6 and 6.5% of the total variance, respectively. Corrected for sampling the heterogeneity and stochastic components accordingly account for 67.3 and 32.7% of the among species variance in log abundance. By using this method, it is possible to disentangle the effect of heterogeneity and stochastic dynamics by quantifying these components and correctly remove sampling effects on the observed species abundance distribution.     

Socioeconomic evaluation of the impact of natural resource stressors on human-use services in the Great Lakes environment: A Lake Michigan case study

The Great Lakes watershed is home to over 40 million people (Canadian and U.S.) who depend on a healthy Great Lakes ecosystem for economic, societal, and personal vitality. The challenge to policymakers and the public is to balance economic benefits with the need to conserve and replenish regional natural resources in a manner that ensures long term prosperity. Nine critical broad-spectrum stressors of ecological services are identified, which include pollution and contamination, agricultural erosion, non-native species, degraded recreational resources, loss of wetlands habitat, climate change, risk of clean water shortage, vanishing sand dunes, and population overcrowding. Many of these stressors overlap. For example, mining activities alone can create stress in at least five of these categories. The focus groups were conducted to examine the public’s awareness of, concern with, and willingness to expend resources on these stressors. This helped generate a grouping of stressors that the public is especially concerned about, those they care little about, and everything else in between. Stressors that the respondents have direct contact with tend to be the most important to them. This approach of using focus groups is a critical first step in helping natural resource managers such as Trustees and NGOs understand what subsequent steps to take and develop policy measures that are of most interest and value to the public. Skipping or glossing over this key first task could lead to difficulties with respect to survey design and model development in a non-market valuation study. The focus group results show that concern related to pollution and contamination is much higher than for any of the others. It is thus clear that outreach programs may be necessary to educate the public about the severity of some low-ranked stressors including climate change.     

Short Note

This study was aimed to investigate the role of two exotic bivalves ( Ruditapes philippinarum and Musculista senhousia ) on the trophic enrichment and the nutritional quality of sediments from the Sacca di Goro (northern Adriatic Sea) through manipulative experiments. The concentrations of sedimentary total organic matter, biopolymeric carbon, carbohydrates, proteins, lipids, and chlorophyll- a were determined through a 64 days-long period. The experimental setup consisted in three replicated treatments ( R. philippinarum , M. senhousia and simply sand), with treatments and time as fixed factors. All the biochemical classes showed wide fluctuation, and significant differences among treatments were detected during the experimental period. Both bivalve species played a role in sediment enrichment process. At the end of the experimental period, proteins represented the main biochemical class of organic compounds in the treatments with bivalves (48.5 and 44.5% of the biopolymeric fraction in the M. senhousia and R. philippinarum treatments, respectively), while in the control treatment they were only 32.7%. The accumulation of proteic nitrogen increased the nutritional quality of the sedimentary organic matter. Moreover, the presence of M. senhousia also enhanced the accumulation of microphytobenthic carbon.