Summary The lack of affordable mineral fertilizers and scarcity of organic materials cause decline in soil fertility for smallholder farmers and producers in the highlands of Madagascar, challenging crop productivity. To fulfill plant growth and nutrition, we explored the effect of 132 combinations of 17 different fertilizing resources, both organic and mineral, on rice growth and nutrition using a greenhouse experiment. Two clustering approaches were used to evaluate the effects of fertilizing resources: elemental clustering and functional clustering. Elemental clustering grouped resources based on their elemental intrinsic composition, while functional clustering grouped resources based on their effect in improving plant growth and nutrition when combined in soil. We found that some resources closely grouped based on their elemental composition exhibited different effects on plant growth and nutrition when combined in soil. Zebu horn emerged as a particular organic resource in elemental clustering, and a key resource in functional clustering by promoting plant growth and nutrition when combined with other resources in soil. Its unique elemental composition played a significant role in driving positive interactions with other resources. We proposed to extend the concept of ‘assembly motif’ within soil fertilization strategy, suggesting that the combination of functional groups of resources determines better their fertilizing effect than their elemental composition. Resources inducing high interaction effects should be combined with those having high elemental composition to optimize crop productivity.

The priming effect (PE) occurs when fresh organic matter (FOM) supplied to soil alters the rate of decomposition of older soil organic matter (SOM). The PE can be generated by different mechanisms driven by interactions between microorganisms with different live strategies and decomposition abilities. Among those, stoichiometric decomposition results from FOM decomposition, which induces the decomposition of SOM by the release of exoenzymes by FOM-decomposers. Nutrient mining results from the co-metabolism of energy-rich FOM with nutrient-rich SOM by SOM-decomposers. While existing statistical approaches enable measurement of the effect of community composition (linear effect) on the PE, the effect of interactions among co-occurring populations (non-linear effect) is more difficult to grasp. We compare a non-linear, clustering approach with a strictly linear approach to separately and comprehensively capture all linear and non-linear effects induced by soil microbial populations on the PE and to identify the species involved. We used an already published data set, acquired from two climatic transects of Madagascar Highlands, in which the high-throughput sequencing of soil samples was applied parallel to the analysis of the potential capacity of microbial communities to generate PE following a 13C-labeled wheat straw input. The linear and clustering approaches highlight two different aspects of the effects of microbial biodiversity on SOM decomposition. The comparison of the results enabled identification of bacterial and fungal families, and combinations of families, inducing either a linear, a non-linear, or no effect on PE after incubation. Bacterial families mainly favoured a PE proportional to their relative abundances in soil (linear effect). Inversely, fungal families induced strong non-linear effects resulting from interactions among them and with bacteria. Our findings suggest that bacteria support stoichiometric decomposition in the first days of incubation, while fungi support mainly the nutrient mining of soil's organic matter several weeks after the beginning of incubation. Used together, the clustering and linear approaches therefore enable the estimation of the relative importance of linear effects related to microbial relative abundances, and non-linear effects related to interactions among microbial populations on soil properties. Both approaches also enable the identification of key microbial families that mainly regulate soil properties.

Biomass production in ecosystems is a complex process regulated by several facets of biodiversity and species identity, but also species interactions such as competition or complementarity between species. For studying these different facets separately, ecosystem biomass is generally partitioned in two biodiversity effects. The composition effect is a simple, linear effect, and the interaction effect is a more subtle, nonlinear effect. Here we used a clustering approach (1) to separately and comprehensively capture all linear and nonlinear effects induced by both biodiversity effects on ecosystem functioning, and (2) to determine the functional composition at the origin of each biodiversity effect. We used data from the long-term Cedar Creek BioDIV experiment carried out over 22 yr, and we partitioned multiplicatively the biomass in composition and interaction effects. Both biodiversity effects were weakly correlated. Our clustering approach accurately explains and predicts each diversity effect over time: each one is modeled by a different functional composition. Even if environmental conditions and the strength of interaction effect strongly varied over time, the functional clusters of species that govern the interaction effect do not change over the 22 yr of the experiment. The functional composition governing the interaction effect is therefore very robust. In contrast, the functional clusters of species that govern the composition effect are less robust and change with environmental conditions. Understanding ecosystem functioning therefore requires that ecological properties are first partitioned by type, then each type of property is analyzed and modeled separately. Approaches without a priori groupings of species, such as functional clustering, appear particularly efficient and robust to unravel the web of species interactions, and identify the role played by species on biodiversity effects.

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Qualitative modelling of microbial community functioning Benoît Jaillard, Jérôme Harmand, Alain Rapaport

The assessment of soil quality is a scientific issue that has been widely debated in the literature for the last twenty years. We developed the Biofunctool (R) framework to assess soil quality based on an integrative approach that accounts for the link between the physico-chemical properties and the biological activity of soils. Biofunctool (R) consists in a set of twelve in-field, time- and cost-effective indicators to assess three main soil functions: carbon transformation, nutrient cycling and structure maintenance. The indicators were applied in a network of mostly rubber plantations compared with three other land uses in Thailand. We collected 1952 indicators values in 180 sampling points over a wide range of pedo-climatic and agronomic contexts in order to assess the validity of the indicators. A reliability, redundancy and sensitivity analysis was performed to validate the capacity of the set of indicators to assess the impact of land management on soil quality. The results showed the relevance and consistence of each of the twelve indicators to assess the soil functioning. Improvements are finally discussed to guide further implementation of the indicators in various contexts and build a soil quality index.

Understanding the relationship between biodiversity and ecosystem functioning has so far resulted from two main approaches: the analysis of species' functional traits, and the analysis of species interaction networks. Here we propose a third approach, based on the association between combinations of species or of functional groups, which we term assembly motifs, and observed ecosystem functioning. Each assembly motif describes a biotic environment in which species interactions have particular effects on a given ecosystem function. Clustering species in functional groups generates a classification of ecosystems based on their assembly motif. We evaluate the quality of each species clustering, that is its ability to predict an ecosystem function, by the coefficient of determination of the ecosystem classification. An iterative process then enables identifying the species clustering in functional groups that best accounts for the functioning of the observed ecosystems. We test this approach using experimental and simulated datasets. We show that our combinatorial analysis makes it possible to identify the combinations of functional groups of species whose interactions govern ecosystem functioning without any a priori knowledge of the species themselves or their interactions. Our combinatorial approach reproduces the associative learning of empirical ecologists, and proves to be powerful and parsimonious.

The assessment of soil quality is a scientific issue that has been widely debated in the literature for the last twenty years. We developed the Biofunctool® framework to assess soil quality based on an integrative approach that accounts for the link between the physico- chemical properties and the biological activity of soils. Biofunctool® consists of a set of twelve in-field, time- and cost- effective indicators to assess three main soil functions: carbon transformation, nutrient cycling and structure maintenance. Firstly, a reliability, redundancy and sensitivity analysis was performed to validate the capacity of the set of indicators to assess the impact of land management on soil quality. The results showed the relevance and consistence of each of the twelve indicators to assess the soil functioning. Secondly, we applied Biofunctool® to assess the impact of various land use contexts and agricultural practices on soil quality. In order to consolidate the information gathered by all the indicators, we aggregated it through a Soil Quality Index. The Biofunctool® index was applied in rubber tree plantations along three study sites in Thailand, as well as in forests and intensive cash crops to cover various land use changes and management practices in various pedo-climatic contexts. The results were analyzed site by site to investigate the impact of land use change, management practices and rubber stand ages on soil quality. The results proved that Biofunctool® index can provide an aggregated synthetic soil functioning score that is sensitive to land management and is robust in various pedo-climatic contexts. First, the index revealed the impact of the conversion from annual crop to rubber plantations and order rubber plantation regarding to a natural forest reference. Then, it showed the positive effect of legume cover-crop on the soil functioning. Finally, it highlighted a similar improvement of the soil quality with the age of rubber plantations in contrasted pedo-climatic contexts. Therefore, the Biofunctool® index is a reliable and relevant descriptor of the soil integrated functioning, i.e., soil quality, and could be included in more global approaches of environmental impact assessment.

Quantifying the effects of species interactions is key to understanding the relationships between biodiversity and ecosystem functioning but remains elusive due to combinatorics issues. Functional groups have been commonly used to capture the diversity of forms and functions and thus simplify the reality. However, the explicit incorporation of species interactions is still lacking in functional group‐based approaches. Here, we propose a new approach based on an a posteriori clustering of species to quantify the effects of species interactions on ecosystem functioning. We first decompose the observed ecosystem function using null models, in which species diversity does not affect ecosystem function, to separate the effects of species interactions and species composition. This allows the identification of a posteriori functional groups that have contrasting diversity effects on ecosystem functioning. We then develop a formal combinatorial model of species interactions in which an ecosystem is described as a combination of co‐occurring functional groups, which we call an assembly motif. Each assembly motif corresponds to a particular biotic environment. We demonstrate the relevance of our approach using datasets from a microbial experiment and the long‐term Cedar Creek Biodiversity II experiment. We show that our a posteriori approach is more accurate, more efficient and more parsimonious than a priori approaches. The discrepancy between a priori and a posteriori approaches results from the way each clustering is set up: a priori approaches are based on ecosystem or species properties, such as ecosystem size (number of species or functional groups) or species’ functional traits, whereas our a posteriori approach is based only on the observed interaction and composition effects on ecosystem functioning. Our findings demonstrate that an a posteriori approach is highly explanatory: it identifies who interacts with whom, and quantifies the effects of species interactions on ecosystem functioning. They also highlight that a combinatorial modelling of ecosystem functioning can predict the functioning of an ecosystem without any hypothesis about the biotic or environmental determinants or any information on species functional traits. It only requires the species composition of the ecosystem and the observed functioning of others that share the same assembly motif.

Tuber melanosporum belongs to the genus Tuber that only includes mycorrhizal fungi living and fruiting underground within the soil environment. T. melanosporum prefers sites in ridges or slopes, where water does not accumulate, and fractured parent materials where water can drain well. Rocky soils with crumb or subangular blocky structure, whose aggregates are stable to fast water immersion, are preferable for truffle cultivation, mostly when their texture is balanced and their clay content moderate. Tuber fungi thrive in alkaline soils with their exchange complex saturated by calcium or magnesium and high in well-mineralised organic matter. These soil conditions are all common in the landscape, but they seldom occur all at the same site. This is what makes natural truffle habitat scarce and disperse. Yet several of these soil characteristics can be modified and many farmlands can become excellent truffle orchards with the adequate soil management practices. These include liming, tilling or adding rock fragments and well-decomposed organic matter in soil.

Summary A major question in ecology is to know how ecosystem function is affected by the number of species. After two decades of research, the nature, shape, and causes of the relationships between biodiversity and ecosystem functioning remain unresolved. Huston ( ) suggested that a statistical ‘sampling effect’ for a few dominant species produced the patterns observed in experiments, while Tilman et al . ( ) argued that the observed responses were due to the number of species rather than the properties of a few. Here, we present a general, theoretical and parsimonious model using combinatorial probabilities to describe the assembly effect as a probabilistic process. Our basic assumption is that community function is determined by random drawing from a fixed species pool composed of three classes of species. The species classes differ in their effect on community function and are ordered in a simple dominance hierarchy (subordinate, dominant and super‐dominant species). Community function is determined by prevalent dominance rules: the dominance by the majority of species mimics the effect of dominant species, i.e . the function is determined by the dominant or super‐dominant species class the most numerous within the community; the dominance by the presence of species mimics the effect of keystone species, i.e . the function is determined by the species that is ranked highest in the dominance hierarchy. The model produces significant fits to four experimental data sets obtained for plant and microbial communities, including monotonic and hump‐shaped curves. The results indicate that the model gave good fits under both the dominance rules in any data set, suggesting that the random sampling effect provides a parsimonious explanation for the various relationships observed in diversity‐ecosystem functioning experiments. The model describes a random assembly process that produces variation in ecosystem functioning in response to number of species selected from a regional species pool composed of several classes of species differing in their ecosystem effects and relative dominance. This simple model reproduces all shapes of diversity‐ecosystem functioning relationships reported in the experimental literature. The results suggest that the multi‐faceted response of ecosystems to biodiversity may be nothing more than manifestations of random assembly effects and variation in species properties.

Aim of study: The program "Typology of truffle stations in the Pyrenean Regions" aimed to define the ecological conditions and culture practices that favor Tuber melanosporum growth and fruiting in this area.Area of study: Navarra, Catalonia, Midi-Pyrénées and Languedoc-Roussillon.Material and methods: The program was based on the survey of 212 wild and cultivated truffle beds of evergreen oaks (Quercus ilex). The data collected in the field consisted of photographs, samples of soil, roots and mycorrhizae, and information on cultural practices followed by truffle growers.Main results: (i) truffle soils are alkaline, from neutral, dolomitic, to moderately or very calcareous soils; (ii) truffle soils are light, well-structured and stable to water immersion; (iii) mycelium that colonizes roots survives in suboptimal conditions, but it does not necessarily bear ascocarps. Finally our results suggest that T. melanosporum is a relatively ubiquitous fungus able to grow, or at least to persist, in a wide range of physical and chemical soil conditions. We propose a probabilistic model of the environment favorable for fruiting, built around a two-dimensional graph with an axis for the chemical conditions, like soil alkalinity, and another axis for the physical conditions, like soil structure. Research highlights: Soil alkalinity and structure allow to built a convenient representation of the ecological capacity of a place to be good T. melanosporum habitat, and thus of the probability for truffle growers to harvest truffles according to the environmental properties of their truffle orchards.Keywords: dolomite; limestone; mycorrhizae; Quercus ilex; field survey; Tuber melanosporum.

In order to assess the relation between symbiotic nitrogen fixation and soil phosphorus, a multi-local test was proposed to producers of Tizi Ouzou area in Algeria, without modification of their cultivation practises. The nodulation and growth of the cultivar traditionally used by farmers, was studied with seven potentially interesting recombinant inbred lines selected among the crossing of BAT 477 and DOR 364 in addition. The sampling was performed at the flowering stage. The major finding in this work is that nodule biomasss were positively correlated with Olsen-P. Although, the curvilinear regressions of nodule biomass and shoot biomass as a function of Olsen-P suggest the existence of 2 ranges of Olsen-P among studied sites that are separated by critical P values. It is concluded that the low nodulation of the RILs was partly compensated by increasing the efficiency in use of the rhizobial symbiosis.

truffières des Régions pyrénéennes” (TrufPyr, 2009-2011) visait à préciser les conditions écologiques qui favorisent la croissance et la fructification de Tuber melanosporum. Ce programme s’est appuyé sur l’étude de 212 truffières de chênes-verts, sauvages et plantées, en Navarre, Catalogne, Midi-Pyrénées et Languedoc-Roussillon, et a permis de préciser les propriétés écologiques des truffières les plus productives. Les résultats confirment que T. melanosporum est un champignon ubiquiste, c’est-à-dire qu’il est capable de se développer dans des sols variés. La présence du champignon est évidemment nécessaire, mais elle ne suffit pas à déterminer l’entrée en production de la truffière. Par contre, nous avons montré que l’alcalinité et la structure du sol sont des propriétés qui déterminent la production de truffes. Ces résultats nous amènent à développer une approche probabiliste de la fructification de T. melanosporum, c’est-à-dire à estimer le risque pour un trufficulteur de produire ou de ne pas produire de truffes étant données les propriétés de sa parcelle. Cette approche permet de mieux comprendre l’effet sur la production de pratiques culturales comme l’amendement organique ou le travail superficiel du sol des truffières, pratiques qu’il est urgent de réhabiliter et d’encourager pour modifier si besoin l’alcalinité du sol et maintenir à des niveaux élevés la stabilité structurale des sols truffiers, et donc la production de truffes.