Altered Hippocampal-Prefrontal Neural Dynamics in Mouse Models of Down Syndrome

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Validating Landsat-based landscape metrics with fine-grained land cover data

ContextModerate-grained data may not always represent landscape structure in adequate detail which could cause misleading results. Certain metrics have been shown to be predictable with changes in scale; however, no studies have verified such predictions using independent fine-grained data.ObjectivesOur objective was to use independently derived land cover datasets to assess relationships between metrics based on fine- and moderate-grained data for a range of analysis extents. We focus on metrics that previous literature has shown to have predictable relationships across scales.MethodsThe study area was located in eastern Connecticut. We compared a 1 m land cover dataset to a 30 m resampled dataset, derived from the 1 m data, as well as two Landsat-based datasets. We examined 11 metrics which included cover areas and patch metrics. Metrics were analyzed using analysis extents ranging from 100 to 1400 m in radius.ResultsThe resampled data had very strong linear relationships to the 1 m data, from which it was derived, for all metrics regardless of the analysis extent size. Landsat-based data had strong correlations for most cover area metrics but had little or no correlation for patch metrics. Increasing analysis areas improved correlations.ConclusionsRelationships between coarse- and fine-grained data tend to be much weaker when comparing independent land cover datasets. Thus, trends across scales that are found by resampling land cover are likely to be unsuitable for predicting the effects of finer-scale elements in the landscape. Nevertheless, coarser data shows promise in predicting fine-grained for cover area metrics provided the analysis area used is sufficiently large.     

The Amount of BCL6 in B Cells Shortly after Antigen Engagement Determines Their Representation in Subsequent Germinal Centers

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Spatial distribution and mortality process ofAnoplophora malasiaca (Coleoptera: Cerambycidae) eggs in citrus groves

The study was carried out in two (A and B) citrus groves to clarify the spatial distribution patterns of eggs and larvae, and to analyse the mortality process of eggs. From the analysis by using the mean density and the mean crowding, it was clarified that the distributions of eggs were contagious and that larvae were more contagiously distributed than eggs. The τ and z indices showed that the operation of egg mortality was inversely density-dependent in both groves, and that the degree of inverse density-dependence was greater in A than in B grove. The spatial correlations between the emergence holes and the eggs or larvae in each tree, which were analysed by using ω index, showed that the distributions were more overlapping between the emergence holes and the larvae than the eggs. As the result of dividing trees into several groups according to the number of emergence holes, it was clarified that the survival rates of eggs were positively correlated with the number of emergence holes. In conclusion, inversely density-dependent mortality process was considered to be caused by lower mortality rates of eggs in the trees with more emergence holes. Especially in A grove, because the trees with more emergence holes were larger in diameter and more egg oviposition, the inversely density-dependent mortality process was considered to be detected more conspicuously than in B grove.     

The impacts of agricultural payments on groundwater quality: Spatial analysis on the case of Slovenia

The European Common Agricultural Policy still follows its primary goals, i.e. quality food at affordable prices and a decent standard of living for farmers, fifty years after its adoption. Moreover, this policy adapts to the changing needs of society and the new challenges, mostly preservation of the environment, nature and biodiversity in rural areas. Although the Common Agricultural Policy receives the largest share of European budget, the funds are decreasing over time, especially direct payments, which aim to provide basic income support to farmers in the European Union. On the other hand, agri-environmental payments are gaining importance. Policy decision-makers should be interested in the question of impacts of growing eco-conditionality of agricultural spending. New insights would help them to be successful in achieving the goals of sustainable agriculture. The purpose of this paper is to estimate the impacts of production support payments and rural development payments on the quality of groundwater. We use the small EU country Slovenia as an example. The baseline indicators are the level of nitrates and pesticides in groundwater, while the impacts were estimated using spatial error model. The results show that direct payments, coupled subsidies and investment grants raise the level of pesticides in groundwater, but do not have any statistically significant impact on the level of nitrates in groundwater. Furthermore, we did not find any statistically significant effects of agri-environmental payments on decrease of groundwater pollution with nitrates. However, our findings revealed that agri-environmental payments are effective in reducing pesticides in groundwater, although only to a limited extent. These results imply a problem of insufficient targeting of agri-environmental measures on the one hand, and suggest that greening of direct payments is necessary and entirely justified.     

Amygdala Reward Neurons Form and Store Fear Extinction Memory

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