Jean-Pierre Theau

Leaf traits capture the effects of land use changes and climate on litter decomposability of grasslands across Europe

Land use and climate changes induce shifts in plant functional diversity and community structure, thereby modifying ecosystem processes. This is particularly true for litter decomposition, an essential process in the biogeochemical cycles of carbon and nutrients. In this study, we asked whether changes in functional traits of living leaves in response to changes in land use and climate were related to rates of litter potential decomposition, hereafter denoted litter decomposability, across a range of 10 contrasting sites. To disentangle the different control factors on litter decomposition, we conducted a microcosm experiment to determine the decomposability under standard conditions of litters collected in herbaceous communities from Europe and Israel. We tested how environmental factors (disturbance and climate) affected functional traits of living leaves and how these traits then modified litter quality and subsequent litter decomposability. Litter decomposability appeared proximately linked to initial litter quality, with particularly clear negative correlations with lignin-dependent indices (litter lignin concentr tion, lignin:nitrogen ratio, and fiber component). Litter quality was directly related to community-weighted mean traits. Lignin-dependent indices of litter quality were positively correlated with community-weighted mean leaf dry matter content (LDMC), and negatively correlated with community-weighted mean leaf nitrogen concentration (LNC). Consequently, litter decomposability was correlated negatively with community-weighted mean LDMC, and positively with community-weighted mean LNC. Environmental factors (disturbance and climate) influenced community-weighted mean traits. Plant communities experiencing less frequent or less intense disturbance exhibited higher community-weighted mean LDMC, and therefore higher litter lignin content and slower litter decomposability. LDMC therefore appears as a powerful marker of both changes in land use and of the pace of nutrient cycling across 10 contrasting sites.

Characterizing potential flexibility in grassland use. Application to the French Aubrac area

Farmers increasingly need to adjust their management practices to accommodate unexpected events such as drought, and preserve the sustainability of their production. This flexibility requires background knowledge about where and when freedom of choice can be exercised. Here, we designed an analysis framework for grassland-based farming systems in mountainous and less-favored areas. An expert-based discrimination tree characterizes organizational flexibility by determining the range of possible types of grassland use under various topographic and farming constraints such as suitability for mechanization, and ease of access to a field. A set of time windows evaluates the timing flexibility in grassland use, each associated with a combination of a grassland community type and a type of grassland use. Our results show that the outputs of the discrimination tree match for 139 of 165 grassland fields, by comparison with field data obtained in the French Aubrac region. For a particular type of grassland use, the set of time windows proves that timing flexibility in grassland use between grassland community types can increase by 15 days over a 37-day time range. When applying the two components of the analysis framework to a farm case, it shows that 24% of the farm area offers organizational flexibility, with several possibilities for grassland use. Timing flexibility for bringing forward or delaying the use of the grassland fields is unused in the farm. Most of the dates of grassland first use are similar irrespective of the diversity of grassland communities. The application of the analysis framework offers a sound evaluation of the potential flexibility to establish where and when it is possible to adjust management practices to cope with unexpected events. It can also be helpful in setting up coherent alternatives to the observed management strategies that can then be expanded in dynamic simulation models enabling deeper analysis.

Comparison of methods for assessing the impact of different disturbances and nutrient conditions upon functional characteristics of grassland communities

BACKGROUND AND AIMS Predicting the response of plant communities to variation in resources and disturbance is still a challenge, because findings depend on how ecological gradients are characterized and how grassland functional composition is assessed. Focusing on leaf dry matter content (LDMC), the efficacy of different methods for evaluating the best response of plant communities to either environmental or disturbance change is examined. METHODS Data were collected on 69 grasslands located at four sites in the Pyrenees and Massif Central. N-Ellenberg indices and plant nutrient content (Ni) were compared to assess fertility, and either LDMC (meas) measured or calculated from a trait database for which traits were measured under the same environmental conditions (db). Management regime (MR) was characterized in terms of categories (grazing, cutting) and plant height. KEY RESULTS LDMCdb was positively correlated to LDMCmeas, but depended significantly on site temperature. N-Ellenberg and Ni were significantly correlated, and there was a significant effect of MR and temperature. LDMC responded to fertility, MR and temperature. Replacing MR by plant height in an REML analysis reduced the uncertainty of the LDMC prediction. LDMC was correlated to plant height at community level, whereas the correlation was weak at species level. Differences in LDMC between plant communities under any of the management regimes were significantly correlated to the standing herbage mass. CONCLUSION The N-Ellenberg index is a better indicator of fertility than Ni which is short-term and environment-dependent. LDMC taken from a database allows plant trait variation due to species abundance (excluding variation due to trait plasticity in response to management) to be captured. So the former is better suited for assessing agricultural services that mainly depend on plant phenology and tissue composition. LDMC responded to defoliation regime in addition to fertility because plant height is roughly correlated with LDMC at plant community level.

Defining management rules for grasslands using weed demographic characteristics

Abstract The study objective was to use demographic information to adjust forage production practices to control the invasive weeds golden chervil and yellow-rattle without herbicides by defining the population dynamics traits that are directly involved in weed responses to farming practices. The principal population traits are capacity for dominance, sensitivity and accessibility of targeted developmental stages, and variation in weed population reactions from year to year. On the basis of demographic surveys of these two weed species when subjected experimentally to various cutting regimes (by date and number), we used matrix simulation models to describe each weed in terms of these traits and to construct species-specific management strategies. Management strategies for golden chervil need to prevent new recruitment by focusing on limiting or eliminating seed production and seedling survival because adult mortality is insensitive to cutting. Grazing to a low residual height is proposed in spring, when seedling emergence is maximal, or when adults reach their apex height to prevent the development of reproductive stems. Cutting before flowering may also efficiently limit seed production. The annual life cycle of yellow-rattle allows more flexibility in its management, even when density fluctuates and is unpredictable. If cutting is scheduled to coincide with peak juvenile height, this can drastically reduce population density the next year, and the population can be eradicated within 3 yr. Nomenclature: Golden chervil, Chaerophyllum aureum L.; yellow-rattle, Rhinanthus minor L.

Diagnosis and simulation: a suitable combination to support farming systems design

Designing or improving farming systems requires understanding their dynamics so as to predict their behaviour in response to management. Simulation tools can potentially support the process by which farmers and scientists might obtain such an encompassing understanding. The usability of these tools is, however, partially inhibited by the inherent complexity of the interactions at work in farm-scale models. Whereas such models are generally used in isolation, here we present an approach in which a field-scale diagnosis method complements a farm-scale simulation model. This diagnosis method lends itself easily to an intelligible presentation of field-specific knowledge that can be fed to the simulation tool for more encompassing considerations. Our approach is used to support the design of novel management strategies in grassland-based beef systems and proved to be effective when applied to two farms in the French Pyrenees. Thanks to the integrative representation of the various processes, including the management ones, simulation contributed to deeper learning of both scientists and farmers about room for manoeuvre for increasing self-sufficiency for forage. The diagnosis phase enhanced the learning process by providing a simpler framework in which elementary problems at field scale could be considered separately before being examined concurrently at farm scale in the simulation phase.

A Method to Analyse Decision-making Processes for Land Use Management in Livestock Farming

In order to maintain their income, using European Union grants, mountain livestock farms need to have a production plan based on animal production and environmental objectives. To help farmers to do this, we develop a method allowing the evaluation of land management strategies that are compatible with both objectives. The strategies set up by farmers were examined from four aspects: forage production to feed livestock, grassland sustainability, avoiding dominance of invasive species and enhancing species diversity, and field characteristics which restrict the range of possible uses. Using this method on four suckling cow farms in the Central Pyrenees (SW France), chosen from 40 farms differing in stocking rate per ha and on their ability to grow their own forage, we identify three land management strategies differing in their balance between animal production and grassland improvement objectives. The first and second were focused on animal production and land sustainability, respectively. The third is a compromise between the two objectives. We show that the relative importance of planning and monitoring rules differed for the three strategies. For the first, the planning process is very important, whereas there is not much monitoring required. The converse is true for the other strategies.