Francoise Vertes

Evaluation of SPOT imagery for the estimation of grassland biomass

In many regions, a decrease in grasslands and change in their management, which are associated with agricultural intensification, have been observed in the last half-century. Such changes in agricultural practices have caused negative environmental effects that include water pollution, soil degradation and biodiversity loss. Moreover, climate-driven changes in grassland productivity could have serious consequences for the profitability of agriculture. The aim of this study was to assess the ability of remotely sensed data with high spatial resolution to estimate grassland biomass in agricultural areas. A vegetation index, namely the Normalized Difference Vegetation Index (NDVI), and two biophysical variables, the Leaf Area Index (LAI) and the fraction of Vegetation Cover (fCOVER) were computed using five SPOT images acquired during the growing season. In parallel, ground-based information on grassland growth was collected to calculate biomass values. The analysis of the relationship between the variables derived from the remotely sensed data and the biomass observed in the field shows that LAI outperforms NDVI and fCOVER to estimate biomass (R2 values of 0.68 against 0.30 and 0.50, respectively). The squared Pearson correlation coefficient between observed and estimated biomass using LAI derived from SPOT images reached 0.73. Biomass maps generated from remotely sensed data were then used to estimate grass reserves at the farm scale in the perspective of operational monitoring and forecasting.

Modeling the potential benefits of catch-crop introduction in fodder crop rotations in a Western Europe landscape

Among possible mitigation options to reduce agricultural-borne nitrate fluxes to water bodies, introduction of catch crop before spring crops is acknowledged as a cost-efficient solution at the plot scale, but it was rarely assessed at the catchment level. This study aims to evaluate a set of catch crop implantation scenarios and their consequences in a coastal catchment prone to eutrophication. The objectives are (i) to discuss the potential benefits of catch crop introduction taking into account the limitations due to the physiographic and agricultural context of the area (ii) to propose a multicriteria classification of these scenarios as a basis for discussion with stakeholders. We used the distributed agro-hydrological model TNT2 to simulate 25 scenarios of catch crop management, differing in length of catch crop growing period, place in the crop rotation and residue management. The scenarios were classified considering the variations in main crop yields and either nitrogen fluxes in stream or the global nitrogen mass balance at the catchment level. The simulations showed that in the catchment studied, little improvement can be expected from increasing the catch crop surface. Catch crop cultivation was always beneficial to reduce nitrogen losses, but led to adverse effects on main crop yields in some cases. Among the scenarios involving additional catch crop surface, introducing catch crop between two winter cereals appeared as the most promising. The classification of scenarios depended on the chosen criteria: when considering only the reduction of nitrogen fluxes in streams, exporting catch crop residues was the most efficient while when considering the global nitrogen mass balance, soil incorporation of catch crop residues was the most beneficial. This work highlights the interest, while using integrated models, of assessing simulated scenarios with multicriteria approach to provide stakeholder with a picture as complete as possible of the consequences of prospective policies.

Evaluation of an operational method for the estimation of emissions of nitrogen compounds for a group of farms

The aim of this article is to evaluate a practical method for estimating nitrogen emissions on the scale of a group of farms, to be used in Life Cycle Assessment (LCA). The method rests on the estimation of nitrogen inputs and outputs to calculate the surplus of the annual nitrogen balance on the scale of a farm. The different gaseous nitrogen losses (NH3, NO, N2O, N3) are then estimated for each livestock or cropping system. The leaching losses in the form of NO3 are assumed to correspond to the surplus of the apparent nitrogen balance to which are added the atmospheric depositions, minus the gaseous losses. The feasibility of this method was studied on 24 farms in the Naizin catchment area (Brittany, France). An analysis of the sensitivity of NO3 estimates to different parameters used to calculate gaseous losses was carried out. Lastly the robustness of the NO3 estimates was examined by comparing them with measurements of NO3 collected within this catchment area.

Data strategy for environmental assessment of agricultural regions via LCA: case study of a French catchment

PurposeVarious approaches have been carried out to extrapolate environmental assessments of farms to the regional level, some of them oversimplified and thus leading to high uncertainty. Key challenges include selection of a representative sample, construction of a farm/land use typology, the extrapolation strategy and dealing with data limitations. This work proposes a method for addressing these issues by means of statistically supported approaches.MethodsWe applied a novel approach combining a sampling strategy, estimation of farm-level environmental impacts via life cycle assessment (LCA), a farm typology based on principal component analysis, a statistical method for extending the farm sample given data constraints and finally linear extrapolation based on regional production and land use, taking into account the regional import–export balance. The approach was applied to a French case study, the Lieue de Grève catchment in the dairy-intensive Brittany region. A decision flowchart was developed to generalise the approach for similar applications dealing with farm and LCA data constraints. Additionally, innovative farm practices were modelled and their impacts propagated to the regional level.Results and discussionThe typology developed identified “dairy”, “beef”, “dairy + beef” and “swine” farms as the dominant farm types in the region. While swine farms had the highest mean impacts per hectare, dairy and dairy + beef farms had impacts two to five times as high as those of beef and swine farms, when extrapolated to the entire catchment. Multiple linear regressions based on an extended farm and LCA dataset were used to predict environmental impacts of dairy farms lacking LCA results, thus increasing their sample size before extrapolation. The inclusion of farm and LCA data from a neighbouring region did not contribute to the accuracy of predicted impacts, as determined by comparing them to those of the farm closest to the dairy cluster’s centre, but rather produced significantly larger coefficients of variation. Results of tests of including two extra-regional farm and LCA datasets helped determine decision rules for the decision flowchart. Modelling of innovative agricultural practices yielded regional impacts consistent with previous estimates.ConclusionsThis approach provides a generalisable approach for farm typologies, data handling and regional extrapolation of farm-level LCAs, applicable to estimate environmental impacts of any agricultural area if requirements of a representative farm sample are met. We demonstrate the utility of the method for estimating effects of innovative agricultural practices on a region’s impacts by modelling practices on virtual farms and extrapolating their results.

Relative nitrogen efficiency, a new indicator to assess crop livestock farming systems

Improving nitrogen (N) efficiency is a priority for increasing food production while reducing its environmental impacts. N efficiency indicators are needed to achieve this goal, but current indicators have some limitations. In particular, current N efficiency indicators are not appropriate tools to compare farming systems with different types of production because animal N efficiency is, by nature, lower than crop N efficiency. A novel N efficiency indicator called “relative N efficiency” was developed to address this issue. It was calculated as the ratio of the actual N efficiency of the farming system to the weighted mean of the potential efficiency of each type of product output provided in literature reviews. Relative N efficiency was calculated for 557 farms of various types from France and Italy. The relative N efficiency indicator was validated by comparison with a statistical approach based on multiple linear regression. Statistical analysis showed that relative N efficiency was independent of production type and could therefore be used for unbiased comparison of different farming systems. Relative N efficiency was particularly interesting when comparing mixed farming systems with different proportions of animal and crop production.

Agricultural practices in grasslands detected by spatial remote sensing

The major decrease in grassland surfaces associated with changes in their management that has been observed in many regions of the earth during the last half century has major impacts on environmental and socio-economic systems. This study focuses on the identification of grassland management practices in an intensive agricultural watershed located in Brittany, France, by analyzing the intra-annual dynamics of the surface condition of vegetation using remotely sensed and field data. We studied the relationship between one vegetation index (NDVI) and two biophysical variables (LAI and fCOVER) derived from a series of three SPOT images on one hand and measurements collected during field campaigns achieved on 120 grasslands on the other. The results show that the LAI appears as the best predictor for monitoring grassland mowing and grazing. Indeed, because of its ability to characterize vegetation status, LAI estimated from remote sensing data is a relevant variable to identify these practices. LAI values derived from the SPOT images were then classified based on the K-Nearest Neighbor (KNN) supervised algorithm. The results points out that the distribution of grassland management practices such as grazing and mowing can be mapped very accurately (Kappa index = 0.82) at a field scale over large agricultural areas using a series of satellite images.

‘I am an Intensive Guy’: The Possibility and Conditions of Reconciliation Through the Ecological Intensification Framework

The need for better conciliation between food production and environmental protection calls for new conceptual approaches in agronomy. Ecological intensification (EI) is one of the most encouraging and successful conceptual frameworks for designing more sustainable agricultural systems, though relying upon semantic ambivalences and epistemic tensions. This article discusses abilities and limits of the EI framework in the context of strong social and environmental pressure for agricultural transition. The purpose is thus to put EI at stake in the light of the results of an interdisciplinary and participatory research project that explicitly adopted EI goals in livestock semi-industrialized farming systems. Is it possible to maintain livestock production systems that are simultaneously productive, sustainable, and viable and have low nitrate emissions in vulnerable coastal areas? If so, how do local stakeholders use these approaches? The main steps of the innovation process are described. The effects of political and social dynamics on the continuity of the transition process are analyzed, with a reflexive approach. This experiment invites one to consider that making EI operational in a context of socio-technical transition toward agroecology represents system innovation, requiring on-going dialogue, reflexivity, and long-term involvement by researchers.

Origin, quantities and fate of nitrogen flows associated with animal production

The nitrogen efficiency is the ratio between the output of nitrogen in the animal products and the input required for the livestock production. This ratio is a driver of the economic profitability and can be calculated at various levels of the production system: animal, field or farm. Calculated at the scale of the animal, it is generally low with less than half-ingested nitrogen remaining in the milk, the eggs or the meat in the form of proteins; the major part of the nitrogen being rejected in the environment. Significant gains were achieved in the past via the genetic improvement and the adjustment of feed supply. At the farm level, the efficiency increases to 45% to 50%, thanks to the recycling of animal excreta as fertilisers. From excretion to land application of manure, the losses of nitrogen are very variable depending on the animal species and the manure management system. Considering the risks of pollution swapping, all management and handling steps need to be considered. Collective initiatives or local rules on agricultural practices allow new opportunities to restore nitrogen balances on local territory.

Tools for evaluating and regulating nitrogen impacts in livestock farming systems

This article describes several indicators and methods for estimating nitrogen flows and balance sheets. It reviews their strengths and weaknesses according to user types and their objectives. The nitrogen balance sheets, based on the difference between inputs and outputs are by far the most-often used estimator of nitrogen management on livestock farms. Among those, the soil surface balance helps in guiding the fertilisation and the farmgate balance is logically higher. The indicators of practices are easy to use but are poor predictors of nitrogen losses, whereas the indicators of emissions allow for estimating nitrogen losses using either direct measurements or models thereby providing a dynamic assessment of these flows. The coupling of balance sheets and indicators of emissions offers a certain potential for improvement of diagnosis and support of decision making. Finally, the indicators of impacts, including the life cycle analyses are currently the most popular for qualifying the impacts of animal production.