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.     

Correction of a bootstrap approach to testing for evolution along lines of least resistance

Testing for an association between the leading vectors of multivariate trait (co)variation within populations (the ‘line of least resistance’) and among populations is an important tool for exploring variational bias in evolution. In a recent study of stickleback fish populations, a bootstrap‐based test was introduced that takes into account estimation error in both vectors and hence improves the previously available bootstrap method. Because this test was implemented incorrectly, however, I here describe the correct test protocol and provide a reanalysis of the original data set. The application of this new test protocol should improve future investigations of evolution along lines of least resistance and other vector comparisons.     

Long‐term population dynamics of a coral reef gastropod and responses to disturbance

The age‐specific density of the red‐lipped stromb Strombus luhuanus (Mollusca: Gastropoda) was monitored over 13 years (1981–1993) at four locations on the intertidal reef flat at Heron Island, Great Barrier Reef. Densities were highly variable, but there were persistent, location‐specific differences in population density, age structure and adult body size, the latter indicating that the populations were not extensively linked by adult movement. There was relatively high recruitment at most locations in 1984, 1989 and 1993, each occurring approximately 2 years after El Niño/Southern Oscillation events, although recruit density during these years varied in both space and time. The studied strombs experienced three disturbance events: (i) experimental harvesting at two locations (1984–1985); (ii) siltation from a harbour dredging operation (1987–1988); and (iii) a severe cyclone (1992). Resilience to harvesting at a local scale (0.5–2 ha) was high: density had recovered within a year, due to immigration of adults and older juveniles. Strombus luhuanus responded much more strongly to broad‐scale changes to its environment than to localized harvesting. After dredging, there was a progressive density decline coupled with low recruitment at two locations, and a later decline at a third location, followed by a recruitment‐driven rebound after the cyclone. Generalized environmental effects of siltation and the cyclone were also reflected in substantial changes in algal cover. Long‐term variations in environmental conditions probably cause high temporal variation over large spatial scales through effects on the survival of larvae or recruits. Localized short‐term field monitoring of such species would give a misleading picture of key factors affecting population dynamics.     

Diversity and distribution of reptiles in Romania

The reptile fauna of Romania comprises 23 species, out of which 12 species reach here the limit of their geographic range. We compiled and updated a national database of the reptile species occurrences from a variety of sources including our own field surveys, personal communication from specialists, museum collections and the scientific literature. The occurrence records were georeferenced and stored in a geodatabase for additional analysis of their spatial patterns. The spatial analysis revealed a biased sampling effort concentrated in various protected areas, and deficient in the vast agricultural areas of the southern part of Romania. The patterns of species richness showed a higher number of species in the warmer and drier regions, and a relatively low number of species in the rest of the country. Our database provides a starting point for further analyses, and represents a reliable tool for drafting conservation plans.     

Mate detection success of maleClethrionomys rufocanus in relation to the spatial distribution of sexually receptive females

Summary Mate detection success of male grey-sided voles,Clethrionomys rufocanus, in relation to the spatial distribution of sexually receptive females was studied in an experimental island population. The spatiotemporal distribution of receptive females was controlled by containing females in small, mobile wire-mesh cages, whereas the response by free-ranging males was monitored by means of radiotelemetry. Males were on average more successful in finding oestrous females when females were spatially clumped than when females were spatially overdispersed. In addition, the variance (CV) in male mate detecting success was highest when females had an overdispersed spatial distribution. These results are consistent with predictions from a theoretical model (Ims, 1988b) analysing the effect of mate distribution on male mating success, and with empirical results on prey detection success of predators searching for prey.     

Influences of temporal independence of data on modelling species distributions

Modelling species distributions has been widely used to understand present and future potential distributions of species, and can provide adaptation and mitigation information as references for conservation and management under climate change. However, various methods of data splitting to develop and validate functions of the models do not get enough attention, which may mislead the interpretation of predicted results. We used the Taiwanese endemic birds to test the influences of temporal independence of datasets on model performance and prediction. Training and testing data were considered to be independent if they were collected during different survey periods (1993–2004 and 2009–2010). The results indicated no significant differences of six model performance measures (AUC, kappa, TSS, accuracy, sensitivity, and specificity) among the combinations of training and testing datasets. Both species- and grid cell-based assessments differed significantly between predictions by the annual and pooled training data. We also found an average of 85.8% similarity for species presences and absences in different survey periods. The remaining dissimilarity was mostly caused by species observed in the late survey period but not in the early one. The method of data splitting, yielding training and testing data, is critical for resulting model species distributions. Even if similar model performance exists, different methods can lead to different species distributional maps. More attention needs to be given to this issue, especially when amplifying these models to project species distributions in a changing world.