Estimating plant-available nitrogen release from manures, composts, and specialty products

Recent adoption of national rules for organic crop production have stimulated greater interest in meeting crop N needs using manures, composts, and other organic materials. This study was designed to provide data to support Extension recommendations for organic amendments. Specifically, our objectives were to (i) measure decomposition and N released from fresh and composted amendments and (ii) evaluate the performance of the model DECOMPOSITION, a relatively simple N mineralization/immobilization model, as a predictor of N availability. Amendment samples were aerobically incubated in moist soil in the laboratory at 22 degrees C for 70 d to determine decomposition and plant-available nitrogen (PAN) (n = 44), and they were applied preplant to a sweet corn crop to determine PAN via fertilizer N equivalency (n = 37). Well-composted materials (n = 14) had a single decomposition rate, averaging 0.003 d(-1). For uncomposted materials, decomposition was rapid (>0.01 d(-1)) for the first 10 to 30 d. The laboratory incubation and the full-season PAN determination in the field gave similar estimates of PAN across amendments. The linear regression equation for lab PAN vs. field PAN had a slope not different from one and a y-intercept not different than zero. Much of the PAN released from amendments was recovered in the first 30 d. Field and laboratory measurements of PAN were strongly related to PAN estimated by DECOMPOSITION (r(2) > 0.7). Modeled PAN values were typically higher than observed PAN, particularly for amendments exhibiting high initial NH(4)-N concentrations or rapid decomposition. Based on our findings, we recommend that guidance publications for manure and compost utilization include short-term (28-d) decomposition and PAN estimates that can be useful to both modelers and growers.     

Mapping ground water vulnerability to pesticide leaching with a process-based metamodel of EuroPEARL

To support EU policy, indicators of pesticide leaching at the European level are required. For this reason, a metamodel of the spatially distributed European pesticide leaching model EuroPEARL was developed. EuroPEARL considers transient flow and solute transport and assumes Freundlich adsorption, first-order degradation and passive plant uptake of pesticides. Physical parameters are depth dependent while (bio)-chemical parameters are depth, temperature, and moisture dependent. The metamodel is based on an analytical expression that describes the mass fraction of pesticide leached. The metamodel ignores vertical parameter variations and assumes steady flow. The calibration dataset was generated with EuroPEARL and consisted of approximately 60,000 simulations done for 56 pesticides with different half-lives and partitioning coefficients. The target variable was the 80th percentile of the annual average leaching concentration at 1-m depth from a time series of 20 yr. The metamodel explains over 90% of the variation of the original model with only four independent spatial attributes. These parameters are available in European soil and climate databases, so that the calibrated metamodel could be applied to generate maps of the predicted leaching concentration in the European Union. Maps generated with the metamodel showed a good similarity with the maps obtained with EuroPEARL, which was confirmed by means of quantitative performance indicators.     

Factors of Dynamics of Plankton Crustacean Communities under Eutrophic Conditions

Russian Journal of Ecology - It has been shown that the main drivers of the dynamics of cladoceran and copepod abundances can be predators (fish), the quantity and/or quality of food in terms of...     

The Effect of Vaccinium vitis-idaea on Properties of Mountain-Meadow Soil under Alpine Lichen Heath

Russian Journal of Ecology - Abstract—The study of the effect of mycorrhiza symbiosis on the transformation of carbon and nitrogen compounds in soils is important in view of the necessity to...     

Spatial population structure of rare orchid species in rich fens in the central part of Murmansk oblast

The spatial structure of 10 populations of rare orchid species (Dactylorhiza incarnata, D. traunsteineri, Listera ovata) has been studied in rich fens sporadically occurring in Murmansk oblast. Two levels of plant aggregation within populations have been distinguished: (1) clusters of individuals and (2) isolated population subsets consisting of clusters. General spatial demographic features of orchid populations in the fens are small area (77 m²) and low ecological density (0.009 ind./m²). Characteristics of the population subsets (their number, area, composition, and distance to the neighboring subset) are species-specific and reflect the degree of species rarity in plant communities.     

Epigenetic variation in the American mink, <Emphasis Type="Italic">Neovison vison</Emphasis>, from eastern Europe: A search for factors of polymorphism

A comparative analysis of epigenetic variation has been performed in nine European populations and population groups of the American mink. It has been shown that differentiation of samples in nonmetric characters is due mainly to endogenous processes that have occurred in introduced populations in the course of colonization of new territory by the invasive species. Environmental factors have played a secondary role, with the influence of the geographic (latitudinal) origin of a given sample being considerable and stronger than that of macroclimatic factors.     

Characteristics of stone moroko population dynamics at different stages of naturalization in lake- and steam-type Dnieper reservoirs

The probable source of stone moroko, Pseudorasbora parva (Temminck & Schlegel, 1846), populations in lake- and stream-type Dnieper reservoirs was revealed. The dynamics and specific growth rates of these populations over 20 years were analyzed. The dynamic phase portrait method was used to determine the timing of stages in the process of invader naturalization and the periods when its populations were in equilibrium. The potential growth rates of P. parva populations in the Kremenchug and Dneprodzerzhinsk reservoirs were estimated.     

Predicting land cover using GIS, Bayesian and evolutionary algorithm methods

Modelling land cover change from existing land cover maps is a vital requirement for anyone wishing to understand how the landscape may change in the future. In order to test any land cover change model, existing data must be used. However, often it is not known which data should be applied to the problem, or whether relationships exist within and between complex datasets. Here we have developed and tested a model that applied evolutionary processes to Bayesian networks. The model was developed and tested on a dataset containing land cover information and environmental data, in order to show that decisions about which datasets should be used could be made automatically. Bayesian networks are amenable to evolutionary methods as they can be easily described using a binary string to which crossover and mutation operations can be applied. The method, developed to allow comparison with standard Bayesian network development software, was proved capable of carrying out a rapid and effective search of the space of possible networks in order to find an optimal or near-optimal solution for the selection of datasets that have causal links with one another. Comparison of land cover mapping in the North-East of Scotland was made with a commercial Bayesian software package, with the evolutionary method being shown to provide greater flexibility in its ability to adapt to incorporate/utilise available evidence/knowledge and develop effective and accurate network structures, at the cost of requiring additional computer programming skills. The dataset used to develop the models included GIS-based data taken from the Land Cover for Scotland 1988 (LCS88), Land Capability for Forestry (LCF), Land Capability for Agriculture (LCA), the soil map of Scotland and additional climatic variables.