Anne Biarnès

Describing and locating cropping systems on a regional scale. A review.

At regional scale issues such as diffuse pollution, water scarcity and pollen transfer are closely related to the diversity and location of cropping systems because agriculture interacts with many other activities. Although sustainable land use solutions for territorial development and natural resource management are needed, very few agro-environmental studies account for both the coherence and the spatial variability of cropping systems. The originality of this article is to review methods that describe and locate cropping systems within large areas. We mainly based our analysis on four case studies using the concept of cropping systems on a regional scale, but differing in their objectives and extents. We found that describing and locating cropping systems in space meets not only decision-making stakes but also a scientific stake that allows multi-simulations over large areas when models require cropping system information. Simulation models are indeed necessary when the study aims at estimating cropping system externalities. Then, the involved process determines the extent, and the model determines the support unit, unless socio-economic considerations prevail. In this case, as well as when no model is involved, it is often considerations related to stakeholders that determine extent and support unit choices. On a regional scale, the cropping system must be described by only a few variables whose selection depends on the study objective and the involved processes. Collecting cropping system information for all support units is often simplified by identifying determining factors of cropping systems. However, obtaining deterministic relations between easily accessible factors and cropping system variables is not always possible, and sometime accessing modalities of determining factors for all support units is also difficult. We found that describing and locating cropping systems relied very much on expertise and detailed survey data. The development of land management practice monitoring would facilitate this description work.

Describing and Locating Cropping Systems on a Regional Scale

At regional scale issues such as diffuse pollution, water scarcity and pollen transfer are closely related to the diversity and location of cropping systems because agriculture interacts with many other activities. Although sustainable land use solutions for territorial development and natural resource management are needed, very few agro-environmental studies account for both the coherence and the spatial variability of cropping systems. The originality of this article is to review methods that describe and locate cropping systems within large areas. We mainly based our analysis on four case studies using the concept of cropping systems on a regional scale, but differing in their objectives and extents. We found that describing and locating cropping systems in space meets not only decision- making stakes but also a scientific stake that allows multi-simulations over large areas when models require cropping system information. Simulation models are indeed necessary when the study aims at estimating cropping system externalities. Then, the involved process determines the extent, and the model determines the support unit, unless socio-economic considerations prevail. In this case, as well as when no model is involved, it is often considerations related to stakeholders that determine extent and support unit choices. On a regional scale, the cropping system must be described by only a few variables whose selection depends on the study objective and the involved processes. Collecting cropping system information for all support units is often simplified by identifying determining factors of cropping systems. However, obtaining deterministic relations between easily accessible factors and cropping system variables is not always possible, and sometime accessing modalities of determining factors for all support units is also difficult. We found that describing and locating cropping systems relied very much on expertise and detailed survey data. The development of land management practice monitoring would facilitate this description work.

Spatial modeling of man-made drainage density of agricultural landscapes

In agricultural landscapes, drainage networks can be greatly extended by man-made linear features such as ditches. Modifying the density of these man-made drainage networks can be a valuable tool to modulate hydrological processes. The objective of this paper is to determine the spatial variability of man-made drainage density in agricultural landscapes and to quantify the extent to which this density depends on the landscape attributes. We performed field surveys of man-made drainage networks, identified potential explanatory variables, and modeled the density of drainage networks by employing multiple linear regression and kriging. The explanatory variables were related to the topography, soil type, density of roads, and density of the field boundaries. These explanatory variables accounted for 55% of the variability in the density. The remaining 45% of the variability were assumed to be related to socioeconomic factors, and represent the latitude in modifying these networks.

Modelling Management Practices in Viticulture while Considering Resource Limitations: The Dhivine Model

Many farming-system studies have investigated the design and evaluation of crop-management practices with respect to economic performance and reduction in environmental impacts. In contrast, little research has been devoted to analysing these practices in terms of matching the recurrent context-dependent demand for resources (labour in particular) with those available on the farm. This paper presents Dhivine, a simulation model of operational management of grape production at the vineyard scale. Particular attention focuses on representing a flexible plan, which organises activities temporally, the resources available to the vineyard manager and the process of scheduling and executing the activities. The model relies on a generic production-system ontology used in several agricultural production domains. The types of investigations that the model supports are briefly illustrated. The enhanced realism of the production-management situations simulated makes it possible to examine and understand properties of resource-constrained work-organisation strategies and possibilities for improving them.

Spatial Simulation of Agricultural Practices using a Robust Extension of Randomized Classification Tree Algorithms

In this paper, extensions of the classification tree algorithm and analysis for spatial data are proposed. These extensions focus on: (1) a robust manner to prune a classification tree to smooth sampling (e.g., spatial sampling effects), (2) an assessment of tree spatial prediction performances with respect to its ability to satisfactorily represent the actual spatial distribution of the variable of interest, and (3) a unified framework to aid in the interpretation of the classification tree results due to variable correlations. These methodological developments are studied on an agricultural practices classification problem at an agricultural plot scale, specifically, the weed control practices on vine plots over a 75 km2 catchment in the South of France. The results show that, with these methodological developments, we obtain an explicit view of the uncertainty associated with the classification process through the simulation of the spatial distribution of agricultural practices. Such an approach may further facilitate the assessment of model sensitivities to categorical variable map uncertainties when using these maps as input data in environmental impact assessment modelling.