Optimizing the biodiversity gain from agri-environment schemes

How best to optimize the biodiversity gain from agri-environment schemes (AES) has recently been identified as a key policy-relevant question. Here, the effects of two features of lowland agricultural landscapes on the abundance and diversity of larger moths are contrasted. Although both features bring about positive effects, hedgerow trees have a larger impact than 6 m wide grassy field margins. Whilst AES payments are given to create and maintain grass margins, no financial reward is currently offered for the retention of hedgerow trees. Furthermore, it was only in areas where the amount of land under AES was experimentally increased, by targeting farmers, that the presence of hedgerow trees resulted in a substantially higher abundance (+60%) and diversity (+38%) of moths. Thus, by using larger moths as bio-indicators of landscape-scale quality, it is demonstrated that improvements to the cost-effectiveness of AES could be achieved, firstly, by providing more appropriate financial rewards to farmers for different landscape features, and secondly, through landscape-scale targeting of farmers to encourage participation in AES.     

Dissolved phosphorus transport from soil to surface water in catchments with different land use

Diffuse phosphorus (P) export from agricultural land to surface waters is a significant environmental problem. It is critical to determine the natural background P losses from diffuse sources, but their identification and quantification is difficult. In this study, three headwater catchments with differing land use (arable, pasture and forest) were monitored for 3 years to quantify exports of dissolved (<0.45 µm) reactive P and total dissolved P. Mean total P exports from the arable catchment ranged between 0.08 and 0.28 kg ha^?1 year^?1. Compared with the reference condition (forest), arable land and pasture exported up to 11-fold more dissolved P. The contribution of dissolved (<0.45 µm) unreactive P was low to negligible in every catchment. Agricultural practices can exert large pressures on surface waters that are controlled by hydrological factors. Adapting policy to cope with these factors is needed for lowering these pressures in the future.     

Predictability of marine nematode biodiversity

In this paper, we investigated: (1) the predictability of different aspects of biodiversity, (2) the effect of spatial autocorrelation on the predictability and (3) the environmental variables affecting the biodiversity of free-living marine nematodes on the Belgian Continental Shelf. An extensive historical database of free-living marine nematodes was employed to model different aspects of biodiversity: species richness, evenness, and taxonomic diversity. Artificial neural networks (ANNs), often considered as “black boxes”, were applied as a modeling tool. Three methods were used to reveal these “black boxes” and to identify the contributions of each environmental variable to the diversity indices. Since spatial autocorrelation is known to introduce bias in spatial analyses, Moran's I was used to test the spatial dependency of the diversity indices and the residuals of the model. The best predictions were made for evenness. Although species richness was quite accurately predicted as well, the residuals indicated a lack of performance of the model. Pure taxonomic diversity shows high spatial variability and is difficult to model. The biodiversity indices show a strong spatial dependency, opposed to the residuals of the models, indicating that the environmental variables explain the spatial variability of the diversity indices adequately. The most important environmental variables structuring evenness are clay and sand fraction, and the minimum annual total suspended matter. Species richness is also affected by the intensity of sand extraction and the amount of gravel of the sea bed.     

Anaerobic degradation of nonylphenol in soil

This study investigated the effects of various factors on the anaerobic degradation of nonylphenol (NP) in soil. The results show that the optimal pH for NP degradation was 7.0 and that the degradation rate was enhanced when the temperature was increased. The addition of compost enhanced NP degradation. The individual addition of the electron donors lactate, acetate, and pyruvate inhibited NP degradation. The high-to-low order of NP degradation rates under three anaerobic conditions was sulfate-reducing conditions > methanogenic conditions > nitrate-reducing conditions. The results show that sulfate-reducing bacteria, methanogen, and eubacteria are involved in the anaerobic degradation of NP, with sulfate-reducing bacteria being a major component of the soil. Of the anaerobic strains isolated from the soil samples, strain AT3 expressed the best ability to biodegrade NP.     

Null models reveal preferential sampling, spatial autocorrelation and overfitting in habitat suitability modelling

Nowadays, species are driven to extinction at a high rate. To reduce this rate it is important to delineate suitable habitats for these species in such a way that these areas can be suggested as conservation areas. The use of habitat suitability models (HSMs) can be of great importance for the delineation of such areas. In this study MaxEnt, a presence-only modelling technique, is used to develop HSMs for 223 nematode species of the Southern Bight of the North Sea. However, it is essential that these models are beyond discussion and they should be checked for potential errors. In this study we focused on two categories (1) errors which can be attributed to the database such as preferential sampling and spatial autocorrelation and (2) errors induced by the modelling technique such as overfitting, In order to quantify these adverse effects thousands of nulls models were created. The effect of preferential sampling (i.e. some areas where visited more frequenty than others) was investigated by comparing model outcomes based from null models sampling the actual sampling stations and null models sampling the entire mapping area (Raes and ter Steege, 2007). Overfitting is exposed by a fivefold cross-validation and the influence of spatial autocorrelation is assessed by separating test and training sets in space. Our results clearly show that all these effects are present: preferential sampling has a strong effect on the selection of non-random species models. Crossvalidation seems to have less influence on the model selection and spatial autocorrelation is also strongly present. It is clear from this study that predefined thresholds are not readily applicable to all datasets and additional tests are needed in model selection.     

Factors controlling sediment and phosphorus export from two Belgian agricultural catchments

Sediment and total phosphorus (TP) export vary through space and time. This study was conducted to determine the factors controlling sediment and TP export in two agricultural catchments situated in the Belgian Loess Belt. At the outlet of these catchments runoff discharge was continuously measured and suspended sediment samples were taken during rainfall events. Within the catchments vegetation type and cover, soil surface parameters, erosion features, sediment pathways, and rainfall characteristics were monitored. Total P content and sediment characteristics such as clay, organic carbon, and suspended sediment concentration were correlated. Total sediment and TP export differ significantly between the monitored catchments. Much of the difference is due to the occurrence of an extreme event in one catchment and the morphology and spatial organization of land use in the catchments. In one catchment, the direct connection between erosive areas and the catchment outlet by means of a road system contributed to a high sediment delivery ratio (SDR) at the outlet. In the other catchment, the presence of a wide valley in the center of the catchment caused sediment deposition. Vegetation also had an effect on sediment production and deposition. Thus, many factors control sediment and TP export from small agricultural catchments; some of these factors are related to the physical catchment characteristics such as morphology and landscape structure and are (semi)permanent, while others, such as vegetation cover and land use, are time dependent.     

Predictions of in situ solid/liquid distribution of radiocaesium in soils

Previous work has demonstrated that plant uptake of radiocaesium (RCs) is related to the activity concentration of RCs in soil solution, which is linked to the soil/soil solution distribution coefficient, K(D). The solid-liquid distribution of RCs is generally studied in soil suspensions in the laboratory and there are few reported measurements for in situ soil solutions. From a data set of 53 different soils (contaminated with either 134CsCl or 137CsCl) used in pot trials to investigate grass uptake of RCs, we analysed the variation of in situ K(D) with measured soil properties. The soils differed widely in % clay (0.5-58%), organic matter content (1.9-96%) and pH (2.4-7.0, CaCl2). The K(D) varied between 29 and 375,000 L kg-' (median 1460 L kg(-1)). Stepwise multiple regression analysis showed a significant correlation between the log K(D) and pH (p < 0.001), log %clay (p < 0.01) and log exchangeable K (p < 0.001) (overall R2 = 0.70). The in situ K(D) values were further compared to K(D)S predicted using an existing model, which assumes that RCs sorption occurs on specific sites and regular ion-exchange sites on the soil solid phase. Sorption of RCs on specific sites was quantified from the radiocaesium interception potential (RIP) measured for each soil and the soil solution concentrations of K+ and NH4+. The in situ log K(D) correlated well with the predicted K(D) (R2 = 0.85 before plant growth, R2 = 0.83 after plant growth). However, the observations were fivefold to eightfold higher than the predictions, particularly for the mineral soils. We attribute the under-prediction to the long contact times (minimum 4 weeks) between the RCs tracers and our experimental soils relative to the short (24 h) contact times used in RIP measurements. We conclude that our data confirmed the model but that ageing of RCs in soil is a factor that needs to be considered to better predict in situ KD values.     

Assessment of labile phosphorus fractions and adsorption characteristics in relation to soil properties of West African savanna soils

A large proportion of total P in the soils of the area is unavailable to plants and consequently P is the second most limiting nutrient. The labile and moderately labile phosphorus fractions and adsorption characteristics of surface and subsurface horizons of eleven soil profiles in the derived savanna (DS) and the northern Guinea savanna (NGS) of West Africa were assessed. The labile P fractions are the resin and HCO₃-extractable inorganic (Pi) and organic (Po) P. The moderately labile fractions are the NaOH-extractable portion of soil P in the Hedley sequential procedure. In the DS soils, the resin P, considered the most readily available fraction, varied from 1 to 14 mg kg⁻¹, HCO₃-Pi ranged from 3.3 to 11, and HCO₃-PO was between 4 and 12 mg kg⁻¹ in the surface horizon. In the NGS, the topsoil contained 1.5–3 mg kg⁻¹ of resin P, 5–8 mg kg⁻¹ of HCO₃-Pi, and 7.5–9.7 mg kg⁻¹ of HCO₃-Po. Sodium hydroxide-Po was the largest of the fractions in all the soils studied. It ranged from 23 to 55 mg kg⁻¹ in the topsoil. In general, the labile P levels were higher in soils of the DS than of the NGS and were related to the oxalate-extractable Fe (Fe_ox), and Al (Al_ox) as well as to soil texture. The subsoil of Kasuwan Magani (profile KS 9–21 cm) required 153 mg P kg⁻¹ to maintain 0.2 mg P l⁻¹ in solution (standard P requirement), and Danayamaka (profile DD 7–32 cm) required 145 mg P kg⁻¹. These could translate to 214 and 200 kg P ha⁻¹ if a plow layer of 10 cm is assumed. Because these are within the plow layer, more P fertilizer would be needed for crop production than in the other soils. The standard P requirement and the adsorption maxima were related to Fe_ox and Al_ox, dithionite-Fe (Fe_d), and texture. The increase in labile P content with decreasing Fe_ox and Al_ox could imply that management practices capable of reducing the activities of Fe and Al in solution might improve P availability.     

Anaerobic degradation of five polycyclic aromatic hydrocarbons from river sediment in Taiwan

This study investigated the anaerobic degradation of five polycyclic aromatic hydrocarbons (PAHs) from Erren River sediment in southern Taiwan. The degradation rates of PAH were in the order: acenaphthene > fluorene > phenanthrene > anthracene > pyrene. The degradation rate was enhanced when the five compounds were present simultaneously in river sediment. Comparison of the PAH degradation rates under three reducing conditions showed the following order: sulfate-reducing conditions > methanogenic conditions > nitrate-reducing conditions. The addition of electron donors (acetate, lactate and pyruvate) enhanced PAH degradation under methanogenic and sulfate-reducing conditions. However, the addition of acetate, lactate or pyruvate inhibited PAH degradation under nitrate-reducing conditions. The addition of heavy metals, nonylphenol and phthalate esters (PAEs) inhibited PAH degradation. Our results show that sulfate-reducing bacteria, methanogen and eubacteria are involved in the degradation of PAH; sulfate-reducing bacteria constitute a major microbial component in PAH degradation. Of the microorganism strains isolated from the sediment samples, we found that strain ER9 expressed the greatest biodegrading ability.     

Anaerobic degradation of five polycyclic aromatic hydrocarbons from river sediment in Taiwan

This study investigated the anaerobic degradation of five polycyclic aromatic hydrocarbons (PAHs) from Erren River sediment in southern Taiwan. The degradation rates of PAH were in the order: acenaphthene > fluorene > phenanthrene > anthracene > pyrene. The degradation rate was enhanced when the five compounds were present simultaneously in river sediment. Comparison of the PAH degradation rates under three reducing conditions showed the following order: sulfate-reducing conditions > methanogenic conditions > nitrate-reducing conditions. The addition of electron donors (acetate, lactate and pyruvate) enhanced PAH degradation under methanogenic and sulfate-reducing conditions. However, the addition of acetate, lactate or pyruvate inhibited PAH degradation under nitrate-reducing conditions. The addition of heavy metals, nonylphenol and phthalate esters (PAEs) inhibited PAH degradation. Our results show that sulfate-reducing bacteria, methanogen and eubacteria are involved in the degradation of PAH; sulfate-reducing bacteria constitute a major microbial component in PAH degradation. Of the microorganism strains isolated from the sediment samples, we found that strain ER9 expressed the greatest biodegrading ability.