A Rapid Method for Assessing the Environmental Performance of Commercial Farms in the Pampas of Argentina

The generation of reliable updated information is critical to support the harmonization of socio-economic and environmental issues in a context of sustainable development. The agro-environmental assessment and management of agricultural systems often relies on indicators that are necessary to make sound decisions. This work aims to provide an approach to (a) assess the environmental performance of commercial farms in the Pampas of Argentina, and (b) propose a methodological framework to calculate environmental indicators that can rapidly be applied to practical farming. 120 commercial farms scattered across the Pampas were analyzed in this study during 2002 and 2003. Eleven basic indicators were identified and calculation methods described. Such indicators were fossil energy (FE) use, FE use efficiency, nitrogen (N) balance, phosphorus (P) balance, N contamination risk, P contamination risk, pesticide contamination risk, soil erosion risk, habitat intervention, changes in soil carbon stock, and balance of greenhouse gases. A model named Agro-Eco-Index was developed on a Microsoft-Excel support to incorporate on-farm collected data and facilitate the calculation of indicators by users. Different procedures were applied to validate the model and present the results to the users. Regression models (based on linear and non-linear models) were used to validate the comparative performance of the study farms across the Pampas. An environmental dashboard was provided to represent in a graphical way the behavior of farms. The method provides a tool to discriminate environmentally friendly farms from those that do not pay enough attention to environmental issues. Our procedure might be useful for implementing an ecological certification system to reward a good environmental behavior in society (e.g., through tax benefits) and generate a commercial advantage (e.g., through the allocation of green labels) for committed farmers.     

monitoring bioaccumulation of contaminants in the belted kingfisher (ceryle alcyon)

The belted kingfisher (Ceryle alcyon), acommon piscivore in the eastern United States, hasbecome a common endpoint in ecological riskassessments (ERA) because of their high consumptionof potentially contaminated aquatic prey. Whilebioaccumulation data and biosurveys may be used tosupport conclusions of ERAs for kingfishers, thereare currently no published data on contaminantconcentrations in kingfishers. Additionally,methods available for collecting biological samples(e.g., feathers, eggs, food debris, etc.) fromkingfisher burrows can be detrimental to thereproductive success of the birds. We present amethod for obtaining samples from burrows during orfollowing the nesting season. The method wasapplied to kingfisher burrows on the Oak RidgeReservation (ORR) in eastern Tennessee. Feathers,eggshells, and nestlings were collected from burrows and analyzed. In addition, carcasses ofthree adult kingfishers found dead on the ORR wereanalyzed. Metals and radionuclides were accumulatedby both juvenile and adult birds. Body burdens ofcadmium, lead, and cesium-137 in adult birds were belowlevels associated with toxicity. Concentrations of selenium and mercury were observed at potentiallytoxic levels. Contaminants in eggshells andnestling feathers indicate exposure, however, thereis insufficient information to evaluate thetoxicological significance of this contamination.National Laboratory Oak Ridge National Laboratory is managed for the U.S. Department of Energy by Lockheed Martin Energy Research Corp. under contract DE-AC05-96OR22464     

Pond bank access as an approach for managing toxic cyanobacteria in beef cattle pasture drinking water ponds

Forty-one livestock drinking water ponds in Alabama beef cattle pastures during were surveyed during the late summer to generally understand water quality patterns in these important water resources. Since livestock drinking water ponds are prone to excess nutrients that typically lead to eutrophication, which can promote blooms of toxigenic phytoplankton such as cyanobacteria, we also assessed the threat of exposure to the hepatotoxin, microcystin. Eighty percent of the ponds studied contained measurable microcystin, while three of these ponds had concentrations above human drinking water thresholds set by the US Environmental Protection Agency (i.e., 0.3 μg/L). Water quality patterns in the livestock drinking water ponds contrasted sharply with patterns typically observed for temperate freshwater lakes and reservoirs. Namely, we found several non-linear relationships between phytoplankton abundance (measured as chlorophyll) and nutrients or total suspended solids. Livestock had direct access to all the study ponds. Consequently, the proportion of inorganic suspended solids (e.g., sediment) increased with higher concentrations of total suspended solids, which underlies these patterns. Unimodal relationships were also observed between microcystin and phytoplankton abundance or nutrients. Euglenoids were abundant in the four ponds with chlorophyll concentrations >?250 μg/L (and dominated three of these ponds), which could explain why ponds with high chlorophyll concentrations would have low microcystin concentrations. Based on observations made during sampling events and available water quality data, livestock-mediated bioturbation is causing elevated total suspended solids that lead to reduced phytoplankton abundance and microcystin despite high concentrations of nutrients, such as phosphorus and nitrogen. Thus, livestock could be used to manage algal blooms, including toxic secondary metabolites, in their drinking water ponds by allowing them to walk in the ponds to increase turbidity.     

Air Quality Modeling Using the PSO-SVM-Based Approach,MLP Neural Network,and M5 Model Tree in the Metropolitan Area of Oviedo (Northern Spain)

The main aim of this study was to construct several regression models of air quality using techniques based on the statistical learning, in the metropolitan area of Oviedo, in northern Spain. In this research, a hybrid particle swarm optimization-based evolutionary support vector regression is implemented to predict the air quality from the experimental dataset (specifically, nitrogen oxides, carbon monoxide, sulfur dioxide, ozone, and dust) collected from 2013 to 2015 in the metropolitan area of Oviedo. Furthermore, a multilayer perceptron network (MLP) and the M5 model tree were also fitted to the experimental dataset for comparison purposes. Finally, the predicted results show that the hybrid proposed model is more robust than the MLP and M5 model tree prediction methods in terms of statistical estimators and testing performances.     

Normal development in two six-year-old boys born after prenatal diagnosis of trisomy 20 mosaicism

Prenatal diagnosis of trisomy 20 mosaicism was made in two pregnancies by chromosome analysis of cultured amniotic fluid cells. In both cases, the pregnancy continued to term and a healthy male infant was delivered. Regular assessments up to the age of 6-5 years revealed normal physical and intellectual development in both children.     

Effects of tree size and spatial distribution on growth of ponderosa pine forests under alternative management scenarios

Forest ecosystems may be actively managed toward heterogeneous stand structures to provide both economic (e.g., wood production and carbon credits) and environmental benefits (e.g., invasive pest resistance). In order to facilitate wider adoption of possibly more sustainable forest stand structures, defining growth expectations among alternative management scenarios is crucial. To estimate the effect of tree size and spatial distributions on growth for forest structures commonly considered in uneven-aged forest stand management, large (0.2 ha+) plots were established in 14 uneven-aged ponderosa pine stands in eastern Montana. All study trees were stem-mapped and measured for diameter and 10-year sapwood and basal area increment. A generalized growth model was developed to predict both total and merchantable 10-year basal area increment for nine hypothetical stand structures [three diameter distributions (reverse-J, irregular, flat) × three spatial distributions (clumpy, partial clumpy, uniform)]. Results indicate that the size and spatial distributions of individual trees have a considerable effect on overall stand growth. The greatest total stand growth was in stands with reverse “J” shaped tree size distributions, while the greatest merchantable stand growth was in stands with “flat” diameter distributions and uniform spatial distributions. Through better comprehension of generalized uneven-aged stand growth dynamics, forest managers may better assess the effects of alternative stand structures on stand growth while providing forest stand structures that may be more resilient in a changing climate.