Long-term Impact of sewage sludge application on rhizobium leguminosarum biovar trifolii: an evaluation using meta-analysis

The Long-Term Sludge Experiment (LTSE) began in 1994 at nine UK field sites as part of continuing research into the effects of sludge-borne heavy metals on soil fertility. The long-term effects of Zn, Cu, and Cd on the most probable numbers of cells (MPN) of Rhizobium leguminosarum biovar trifolii were monitored for 8 yr in sludge-amended soils. To assess the statutory limits set by the UK Sludge (Use in Agriculture) Regulations, the experimental data were reviewed using statistical methods of meta-analysis. Previous LTSE studies have focused predominantly on statistical significance rather than effect size, whereas meta-analysis focuses on the magnitude and direction of an effect, i.e., the practical significance rather than its statistical significance. Results showed Zn to be the most toxic element causing an overall significant decrease in Rhizobium MPN of −26.6% during the LTSE. The effect of Cu showed no significant effect on Rhizobium MPN at concentrations below the UK limits, although a −5% decrease in Rhizobium MPN was observed in soils where total Cu ranged from 100 to <135 mg kg−1. Overall, there was nothing to indicate that Cd had a significant effect on Rhizobium MPN below the current UK statutory limit. In summary, the UK statutory limit for Zn appears to be insufficient for protecting Rhizobium from Zn toxicity effects

Empirical test of an agricultural landscape model: the importance of farmer preference for risk aversion and crop complexity

Developing models to predict the effects of social and economic change on agricultural landscapes is an important challenge. Model development often involves making decisions about which aspects of the system require detailed description and which are reasonably insensitive to the assumptions. However, important components of the system are often left out because parameter estimates are unavailable. In particular, measurements of the relative influence of different objectives, such as risk, environmental management, on farmer decision making, have proven difficult to quantify. We describe a model that can make predictions of land use on the basis of profit alone or with the inclusion of explicit additional objectives. Importantly, our model is specifically designed to use parameter estimates for additional objectives obtained via farmer interviews. By statistically comparing the outputs of this model with a large farm-level land-use data set, we show that cropping patterns in the United Kingdom contain a significant contribution from farmer’s preference for objectives other than profit. In particular, we found that risk aversion had an effect on the accuracy of model predictions, whereas preference for a particular number of crops grown was less important. While nonprofit objectives have frequently been identified as factors in farmers’ decision making, our results take this analysis further by demonstrating the relationship between these preferences and actual cropping patterns

Combining two national‐scale datasets to map soil properties, the case of available magnesium in England and Wales

Given the costs of soil survey it is necessary to make the best use of available datasets, but data that differ with respect to some aspect of the sampling or analytical protocol cannot be combined simply. In this paper we consider a case where two datasets were available on the concentration of plant‐available magnesium in the topsoil. The datasets were the Representative Soil Sampling Scheme (RSSS) and the National Soil Inventory (NSI) of England and Wales. The variable was measured over the same depth interval and with the same laboratory method, but the sample supports were different and so the datasets differ in their variance. We used a multivariate geostatistical model, the linear model of coregionalization (LMCR), to model the joint spatial distribution of the two datasets. The model allowed us to elucidate the effects of the sample support on the two datasets, and to show that there was a strong correlation between the underlying variables. The LMCR allowed us to make spatial predictions of the variable on the RSSS support by cokriging the RSSS data with the NSI data. We used cross‐validation to test the validity of the LMCR and showed how incorporating the NSI data restricted the range of prediction error variances relative to univariate ordinary kriging predictions from the RSSS data alone. The standardized squared prediction errors were computed and the coverage of prediction intervals (i.e. the proportion of sites at which the prediction interval included the observed value of the variable). Both these statistics suggested that the prediction error variances were consistent for the cokriging predictions but not for the ordinary kriging predictions from the simple combination of the RSSS and NSI data, which might be proposed on the basis of their very similar mean values. The LMCR is therefore proposed as a general tool for the combined analysis of different datasets on soil properties

Rural Development Programme measures on cultivated land in Europe to mitigate greenhouse gas emissions – regional ‘hotspots’ and priority measures

© 2016 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.Agriculture is a significant source of GHG emissions, contributing 10% of total emissions within the EU-28. Emissions from European agriculture have been reduced, albeit at the expense of crop yield and the risk of production displacement (the transfer of production, and associated emissions, to land outside of Europe). This article assesses the impact on GHG emissions of selected European Rural Development Program measures, representative of a diversity of management strategies implemented on cultivated land, within nine European Member States. Climatic zone and underlying spatial environmental variables were accounted for using a novel technique, “Regional Variation Categories,” developed with European-scale GIS data sets. Production displacement is assessed with two benchmarks: (1) compared with existing crop production and (2) relative to a “minimum requirement” land management scenario, where an emissions reduction of less than this does not constitute mitigation. Most measures reduce emissions relative to the baseline crop scenario; however, many do not reduce emissions beyond the “minimum requirement,” this being limited to measures such as catch crops and within-field grass areas to prevent soil erosion. The selection and targeting of measures to maximize agricultural GHG mitigation on cultivated land within Europe is discussed...Peer reviewedFinal Published versio

Patterns of presence and concentration of pesticides in the main course of the Júcar River (Eastern Spain)

The Júcar River, in a typical Mediterranean Basin, is expected to suffer a decline in water quality and quantity as a consequence of the climate change. This study is focused on the presence and distribution of pesticides in water and fish, using the first extensive optimization and application of the QuEChERS method to determine pesticides in river fish. Majority pesticides in water -in terms of presence and concentration- were dichlofenthion, chlorfenvinphos, imazalil, pyriproxyfen and prochloraz (associated with a frequent use in farming activities), as well as buprofezin, chlopyriphos and hexythiaxoz. In fish, the main compounds were azinphos-ethyl, chlorpyriphos, diazinon, dimethoate and ethion. The analysis of bio-concentration in fish indicated differences by species. The maximum average concentration was detected in European eel (a critically endangered fish species). The wide presence of pesticides in water and fish suggests potential severe effects on fish populations and other biota in future scenarios of climate change, in a river basin with several endemic and endangered fish species. The potential effects of pesticides in combination with multiple stressors require further research to prioritize the management of specific chemicals and suggest effective restoration actions at the basin scale.This study was funded by the Spanish Ministry of Economy and Competitiveness with the project SCARCE (Consolider-Ingenio 2010 CSD2009-00065). Authors also thank the help of the confederacion Hidrografica del Jucar (Gobierno de Esparia) which provided environmental data, and to all the colleagues who collaborated in sampling campaigns, R. Munoz-Mas, R.M.S. Costa and J.D. Alcaraz-Hernandez.Belenguer, V.; Martinez-Capel, F.; Masiá, A.; Picó, Y. (2014). Patterns of presence and concentration of pesticides in the main course of the Júcar River (Eastern Spain). Journal of Hazardous Materials. 265:271-279. https://doi.org/10.1016/j.jhazmat.2013.11.016S27127926

Transactions costs in rural decision-making: The cases of funding and monitoring in rural development in England

Public domain decisions in rural England have become more complex as the number of stakeholders having a say in them has increased. Transactions costs can be used to explore this increasing complexity. The size and distribution of these costs are higher in rural areas. Grouping transactions costs into four - organizations, belief systems, knowledge and information, and institutions - two of the latter are evaluated empirically: growth in the bid culture, and monitoring and evaluation. Amongst 65 Agents of Rural Governance (ARGs) in Gloucestershire, both were found to be increasing over time, but those relating to finance were a greater burden than those of monitoring: the latter can improve ARG performance. Increasing transactions costs in rural decision-making appears to be at variance with ambitions of achieving 'smaller government' through, for example, the Big Society. Smaller government is likely to be shifting the incidence of these costs, rather than reducing them. © 2011 Blackwell Publishing Ltd

Effects of water re-allocation in the Ebro river basin: A multiregional input-output and geographical analysis

The quality and availability of water are affected by numerous variables, through which the evaluation of water uses from different perspectives, and policy proposals to save water have now become essential. This paper aims to study water use and the water footprint from a river basin perspective, taking into account regions, sectors, and municipalities, while considering the physical frontier along with the administrative sectors. To this end, we have constructed a multi-regional input-output table for the Ebro river basin, disaggregating the primary sector into 18 different crops and 6 livestock groups. We pay special attention to crop production because it is the most water-consuming industry. The construction of the multi-regional input-output model represents an important contribution to the literature, in itself, since, to the best of our knowledge, it is the first to be built for this large basin. We extend this multi-regional input-output model to assess the water footprint by sectors and regions within the basin. We use these data to propose two scenarios: reallocating final demand to reduce the blue water footprint (scenario 1), and increasing value added (scenario 2). These scenarios outline the opportunity costs of saving water in socioeconomic terms in the basin. In another application, we downscale the multi-regional input-output model results at the municipal level and depict them using a geographical information system, identifying the hotspots and the areas that would pay for the socioeconomic opportunity costs of saving water. Our results suggest that saving 1 hm 3 of blue water could cost around €41, 500 of value added if we consider the entire basin. However, this water re-allocation implies losses and gains at the municipal level: some municipalities would reduce value added by more than €30, 000, while others would gain more than €85, 000 of value added. These tools and results can be useful for policy makers when considering re-allocating water. The contribution and the novelty of this paper is the construction of the multiregional input-output model for the Ebro river basin, and its link with geographical systems analysis at the municipal level