Institut Agro Montpellier

Plant functional traits are the features (morphological, physiological, phenological) that represent ecological strategies and determine how plants respond to environmental factors, affect other trophic levels and influence ecosystem properties. Variation in plant functional traits, and trait syndromes, has proven useful for tackling many important ecological questions at a range of scales, giving rise to a demand for standardised ways to measure ecologically meaningful plant traits. This line of research has been among the most fruitful avenues for understanding ecological and evolutionary patterns and processes. It also has the potential both to build a predictive set of local, regional and global relationships between plants and environment and to quantify a wide range of natural and human-driven processes, including changes in biodiversity, the impacts of species invasions, alterations in biogeochemical processes and vegetation–atmosphere interactions. The importance of these topics dictates the urgent need for more and better data, and increases the value of standardised protocols for quantifying trait variation of different species, in particular for traits with power to predict plant- and ecosystem-level processes, and for traits that can be measured relatively easily. Updated and expanded from the widely used previous version, this handbook retains the focus on clearly presented, widely applicable, step-by-step recipes, with a minimum of text on theory, and not only includes updated methods for the traits previously covered, but also introduces many new protocols for further traits. This new handbook has a better balance between whole-plant traits, leaf traits, root and stem traits and regenerative traits, and puts particular emphasis on traits important for predicting species’ effects on key ecosystem properties. We hope this new handbook becomes a standard companion in local and global efforts to learn about the responses and impacts of different plant species with respect to environmental changes in the present, past and future.

There is growing recognition that classifying terrestrial plant species on the basis of their function (into 'functional types') rather than their higher taxonomic identity, is a promising way forward for tackling important ecological questions at the scale of ecosystems, landscapes or biomes. These questions include those on vegetation responses to and vegetation effects on, environmental changes (e.g. changes in climate, atmospheric chemistry, land use or other disturbances). There is also growing consensus about a shortlist of plant traits that should underlie such functional plant classifications, because they have strong predictive power of important ecosystem responses to environmental change and/or they themselves have strong impacts on ecosystem processes. The most favoured traits are those that are also relatively easy and inexpensive to measure for large numbers of plant species. Large international research efforts, promoted by the IGBP–GCTE Programme, are underway to screen predominant plant species in various ecosystems and biomes worldwide for such traits. This paper provides an international methodological protocol aimed at standardising this research effort, based on consensus among a broad group of scientists in this field. It features a practical handbook with step-by-step recipes, with relatively brief information about the ecological context, for 28 functional traits recognised as critical for tackling large-scale ecological questions.

Significance Agricultural production is vulnerable to climate change. Understanding climate change, especially the temperature impacts, is critical if policymakers, agriculturalists, and crop breeders are to ensure global food security. Our study, by compiling extensive published results from four analytical methods, shows that independent methods consistently estimated negative temperature impacts on yields of four major crops at the global scale, generally underpinned by similar impacts at country and site scales. Multimethod analyses improved the confidence in assessments of future climate impacts on global major crops, with important implications for developing crop- and region-specific adaptation strategies to ensure future food supply of an increasing world population.

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

INTRODUCTION: The PCR-based analysis of homologous genes has become one of the most powerful approaches for species detection and identification, particularly with the recent availability of Next Generation Sequencing platforms (NGS) making it possible to identify species composition from a broad range of environmental samples. Identifying species from these samples relies on the ability to match sequences with reference barcodes for taxonomic identification. Unfortunately, most studies of environmental samples have targeted ribosomal markers, despite the fact that the mitochondrial Cytochrome c Oxidase subunit I gene (COI) is by far the most widely available sequence region in public reference libraries. This is largely because the available versatile ("universal") COI primers target the 658 barcoding region, whose size is considered too large for many NGS applications. Moreover, traditional barcoding primers are known to be poorly conserved across some taxonomic groups. RESULTS: We first design a new PCR primer within the highly variable mitochondrial COI region, the "mlCOIintF" primer. We then show that this newly designed forward primer combined with the "jgHCO2198" reverse primer to target a 313 bp fragment performs well across metazoan diversity, with higher success rates than versatile primer sets traditionally used for DNA barcoding (i.e. LCO1490/HCO2198). Finally, we demonstrate how the shorter COI fragment coupled with an efficient bioinformatics pipeline can be used to characterize species diversity from environmental samples by pyrosequencing. We examine the gut contents of three species of planktivorous and benthivorous coral reef fish (family: Apogonidae and Holocentridae). After the removal of dubious COI sequences, we obtained a total of 334 prey Operational Taxonomic Units (OTUs) belonging to 14 phyla from 16 fish guts. Of these, 52.5% matched a reference barcode (>98% sequence similarity) and an additional 32% could be assigned to a higher taxonomic level using Bayesian assignment. CONCLUSIONS: The molecular analysis of gut contents targeting the 313 COI fragment using the newly designed mlCOIintF primer in combination with the jgHCO2198 primer offers enormous promise for metazoan metabarcoding studies. We believe that this primer set will be a valuable asset for a range of applications from large-scale biodiversity assessments to food web studies.

This paper provides an analysis of the potential environmental impacts of biodiesel production from microalgae. High production yields of microalgae have called forth interest of economic and scientific actors but it is still unclear whether the production of biodiesel is environmentally interesting and which transformation steps need further adjustment and optimization. A comparative LCA study of a virtual facility has been undertaken to assessthe energetic balance and the potential environmental impacts of the whole process chain, from the biomass production to the biodiesel combustion. Two different culture conditions, nominal fertilizing or nitrogen starvation, as well as two different extraction options, dry or wet extraction, have been tested. The best scenario has been compared to first generation biodiesel and oil diesel. The outcome confirms the potential of microalgae as an energy source but highlights the imperative necessity of decreasing the energy and fertilizer consumption. Therefore control of nitrogen stress during the culture and optimization of wet extraction seem to be valuable options. This study also emphasizes the potential of anaerobic digestion of oilcakes as a way to reduce external energy demand and to recycle a part of the mineral fertilizers.

A new method for assigning individuals of unknown origin to populations, based on the genetic distance between individuals and populations, was compared to two existing methods based on the likelihood of multilocus genotypes. The distribution of the assignment criterion (genetic distance or genotype likelihood) for individuals of a given population was used to define the probability that an individual belongs to the population. Using this definition, it becomes possible to exclude a population as the origin of an individual, a useful extension of the currently available assignment methods. Using simulated data based on the coalescent process, the different methods were evaluated, varying the time of divergence of populations, the mutation model, the sample size, and the number of loci. Likelihood-based methods (especially the Bayesian method) always performed better than distance methods. Other things being equal, genetic markers were always more efficient when evolving under the infinite allele model than under the stepwise mutation model, even for equal values of the differentiation parameter F(st). Using the Bayesian method, a 100% correct assignment rate can be achieved by scoring ca. 10 microsatellite loci (H approximately 0.6) on 30-50 individuals from each of 10 populations when the F(st) is near 0.1.

The spider mite Tetranychus urticae is a cosmopolitan agricultural pest with an extensive host plant range and an extreme record of pesticide resistance. Here we present the completely sequenced and annotated spider mite genome, representing the first complete chelicerate genome. At 90 megabases T. urticae has the smallest sequenced arthropod genome. Compared with other arthropods, the spider mite genome shows unique changes in the hormonal environment and organization of the Hox complex, and also reveals evolutionary innovation of silk production. We find strong signatures of polyphagy and detoxification in gene families associated with feeding on different hosts and in new gene families acquired by lateral gene transfer. Deep transcriptome analysis of mites feeding on different plants shows how this pest responds to a changing host environment. The T. urticae genome thus offers new insights into arthropod evolution and plant–herbivore interactions, and provides unique opportunities for developing novel plant protection strategies. The genome of the spider mite Tetranychus urticae is sequenced, providing insights into its polyphagous feeding, silk production, hormonal repertoire and reduced Hox cluster. The spider mite (Tetranychus urticae) is a common agricultural pest that feeds on a wide range of hosts — including maize (corn), soya, tomatoes and peppers — and is notoriously resistant to pesticides. Its genome has now been sequenced and analysed, providing insights into its hormonal repertoire and the evolution of silk production. Transcriptome analysis of mites feeding on different plants reveals how this pest defends itself in a changing host environment and gives pointers to possible non-pesticide plant-protection strategies. The genome encodes 17 fibroin genes, and physical tests of spider-mite silk show it to be a natural nanomaterial with fibres that are more than 100 times thinner than those produced by silk spiders.

There is an ongoing debate on what constitutes sustainable intensification of agriculture (SIA). In this paper, we propose that a paradigm for sustainable intensification can be defined and translated into an operational framework for agricultural development. We argue that this paradigm must now be defined-at all scales-in the context of rapidly rising global environmental changes in the Anthropocene, while focusing on eradicating poverty and hunger and contributing to human wellbeing. The criteria and approach we propose, for a paradigm shift towards sustainable intensification of agriculture, integrates the dual and interdependent goals of using sustainable practices to meet rising human needs while contributing to resilience and sustainability of landscapes, the biosphere, and the Earth system. Both of these, in turn, are required to sustain the future viability of agriculture. This paradigm shift aims at repositioning world agriculture from its current role as the world's single largest driver of global environmental change, to becoming a key contributor of a global transition to a sustainable world within a safe operating space on Earth.

Aquaporins are membrane channels that facilitate the transport of water and small neutral molecules across biological membranes of most living organisms. In plants, aquaporins occur as multiple isoforms reflecting a high diversity of cellular localizations, transport selectivity, and regulation properties. Plant aquaporins are localized in the plasma membrane, endoplasmic reticulum, vacuoles, plastids and, in some species, in membrane compartments interacting with symbiotic organisms. Plant aquaporins can transport various physiological substrates in addition to water. Of particular relevance for plants is the transport of dissolved gases such as carbon dioxide and ammonia or metalloids such as boron and silicon. Structure-function studies are developed to address the molecular and cellular mechanisms of plant aquaporin gating and subcellular trafficking. Phosphorylation plays a central role in these two processes. These mechanisms allow aquaporin regulation in response to signaling intermediates such as cytosolic pH and calcium, and reactive oxygen species. Combined genetic and physiological approaches are now integrating this knowledge, showing that aquaporins play key roles in hydraulic regulation in roots and leaves, during drought but also in response to stimuli as diverse as flooding, nutrient availability, temperature, or light. A general hydraulic control of plant tissue expansion by aquaporins is emerging, and their role in key developmental processes (seed germination, emergence of lateral roots) has been established. Plants with genetically altered aquaporin functions are now tested for their ability to improve plant tolerance to stresses. In conclusion, research on aquaporins delineates ever expanding fields in plant integrative biology thereby establishing their crucial role in plants.

The geminiviruses are a family of small, non-enveloped viruses with single-stranded, circular DNA genomes of 2500-5200 bases. Geminiviruses are transmitted by various types of insect (whiteflies, leafhoppers, treehoppers and aphids). Members of the genus Begomovirus are transmitted by whiteflies, those in the genera Becurtovirus, Curtovirus, Grablovirus, Mastrevirus and Turncurtovirus are transmitted by specific leafhoppers, the single member of the genus Topocuvirus is transmitted by a treehopper and one member of the genus Capulavirus is transmitted by an aphid. Geminiviruses are plant pathogens causing economically important diseases in most tropical and subtropical regions of the world. This is a summary of the International Committee on Taxonomy of Viruses (ICTV) Report on the taxonomy of the Geminiviridae which is available at www.ictv.global/report/geminiviridae.

The green chemistry era has pushed the scientific community to investigate and implement new solvents in phenolic compounds (PC) extraction as alternatives to organic solvents, which are toxic and may be dangerous. Recently, deep eutectic solvents (DES) have been applied as extraction solvents for PC. They have the advantages of biodegradability and ease of handling with very low toxicity. Nevertheless, the extraction process is affected by several factors: affinity between DES and the target compounds, the water content, the mole ratio between DES' starting molecules, the liquid/solid ratio between the DES and sample, and the conditions and extraction method. On the other hand, PC recovery from DES is a challenge because they can establish a strong hydrogen bond network. Alternatively, another possibility is to use DES as solvent extraction as well as formulation medium. In this way, DES can be suitable for cosmetics, pharmaceutical, or food applications.

Multiple sequence alignment is a prerequisite for many evolutionary analyses. Multiple Alignment of Coding Sequences (MACSE) is a multiple sequence alignment program that explicitly accounts for the underlying codon structure of protein-coding nucleotide sequences. Its unique characteristic allows building reliable codon alignments even in the presence of frameshifts. This facilitates downstream analyses such as selection pressure estimation based on the ratio of nonsynonymous to synonymous substitutions. Here, we present MACSE v2, a major update with an improved version of the initial algorithm enriched with a complete toolkit to handle multiple alignments of protein-coding sequences. A graphical interface now provides user-friendly access to the different subprograms.

Almost half of the total organic carbon (C) in terrestrial ecosystems is stored in forest soils. By altering rates of input or release of C from soils, forest management activities can influence soil C stocks in forests. In this review, we synthesize current evidence regarding the influences of 13 common forest management practices on forest soil C stocks. Afforestation of former croplands generally increases soil C stocks, whereas on former grasslands and peatlands, soil C stocks are unchanged or even reduced following afforestation. The conversion of primary forests to secondary forests generally reduces soil C stocks, particularly if the land is converted to an agricultural land-use prior to reforestation. Harvesting, particularly clear-cut harvesting, generally results in a reduction in soil C stocks, particularly in the forest floor and upper mineral soil. Removal of residues by harvesting whole-trees and stumps negatively affects soil C stocks. Soil disturbance from site preparation decreases soil C stocks, particularly in the organic top soil, however improved growth of tree seedlings may outweigh soil C losses over a rotation. Nitrogen (N) addition has an overall positive effect on soil C stocks across a wide range of forest ecosystems. Likewise, higher stocks and faster accumulation of soil C occur under tree species with N-fixing associates. Stocks and accumulation rates of soil C also differ under different tree species, with coniferous species accumulating more C in the forest floor and broadleaved species tending to store more C in the mineral soil. There is some evidence that increased tree species diversity could positively affect soil C stocks in temperate and subtropical forests, but tree species identity, particularly N-fixing species, seems to have a stronger impact on soil C stocks than tree species diversity. Management of stand density and thinning have small effects on forest soil C stocks. In forests with high populations of ungulate herbivores, reduction in herbivory levels can increase soil C stocks. Removal of plant biomass for fodder and fuel is related to a reduction in the soil C stocks. Fire management practices such as prescribed burning reduce soil C stocks, but less so than wildfires which are more intense. For each practice, we identify existing gaps in knowledge and suggest research to address the gaps.

Stomata play a key role in plant adaptation to changing environmental conditions as they control both water losses and CO(2) uptake. Particularly, in the context of global change, simulations of the consequences of drought on crop plants are needed to design more efficient and water-saving cropping systems. However, most of the models of stomatal conductance (g(s)) developed at the leaf level link g(s) to environmental factors or net photosynthesis (A(net)), but do not include satisfactorily the effects of drought, impairing our capacity to simulate plant functioning in conditions of limited water supply. The objective of this review was to draw an up-to-date picture of the g(s) models, from the empirical to the process-based ones, along with their mechanistic or deterministic bases. It focuses on models capable to account for multiple environmental influences with emphasis on drought conditions. We examine how models that have been proposed for well-watered conditions can be combined with those specifically designed to deal with drought conditions. Ideas for future improvements of g(s) models are discussed: the issue of co-regulation of g(s) and A(net); the roles of CO(2), absissic acid and H(2)O(2); and finally, how to better address the new challenges arising from the issue of global change.

For the past 20 years, the recombination detection program (RDP) project has focused on the development of a fast, flexible, and easy to use Windows-based recombination analysis tool. Whereas previous versions of this tool have relied on considerable user-mediated verification of detected recombination events, the latest iteration, RDP5, is automated enough that it can be integrated within analysis pipelines and run without any user input. The main innovation enabling this degree of automation is the implementation of statistical tests to identify recombination signals that could be attributable to evolutionary processes other than recombination. The additional analysis time required for these tests has been offset by algorithmic improvements throughout the program such that, relative to RDP4, RDP5 will still run up to five times faster and be capable of analyzing alignments containing twice as many sequences (up to 5000) that are five times longer (up to 50 million sites). For users wanting to remove signals of recombination from their datasets before using them for downstream phylogenetics-based molecular evolution analyses, RDP5 can disassemble detected recombinant sequences into their constituent parts and output a variety of different recombination-free datasets in an array of different alignment formats. For users that are interested in exploring the recombination history of their datasets, all the manual verification, data management and data visualization components of RDP5 have been extensively updated to minimize the amount of time needed by users to individually verify and refine the program's interpretation of each of the individual recombination events that it detects.

Mapping aboveground forest biomass is central for assessing the global carbon balance. However, current large-scale maps show strong disparities, despite good validation statistics of their underlying models. Here, we attribute this contradiction to a flaw in the validation methods, which ignore spatial autocorrelation (SAC) in data, leading to overoptimistic assessment of model predictive power. To illustrate this issue, we reproduce the approach of large-scale mapping studies using a massive forest inventory dataset of 11.8 million trees in central Africa to train and validate a random forest model based on multispectral and environmental variables. A standard nonspatial validation method suggests that the model predicts more than half of the forest biomass variation, while spatial validation methods accounting for SAC reveal quasi-null predictive power. This study underscores how a common practice in big data mapping studies shows an apparent high predictive power, even when predictors have poor relationships with the ecological variable of interest, thus possibly leading to erroneous maps and interpretations.

Detailed knowledge about the geographical pathways followed by propagules from their source to the invading populations--referred to here as routes of invasion-provides information about the history of the invasion process and the origin and genetic composition of the invading populations. The reconstruction of invasion routes is required for defining and testing different hypotheses concerning the environmental and evolutionary factors responsible for biological invasions. In practical terms, it facilitates the design of strategies for controlling or preventing invasions. Most of our knowledge about the introduction routes of invasive species is derived from historical and observational data, which are often sparse, incomplete and, sometimes, misleading. In this context, population genetics has proved a useful approach for reconstructing routes of introduction, highlighting the complexity and the often counterintuitive nature of the true story. This approach has proved particularly useful since the recent development of new model-based methods, such as approximate Bayesian computation, making it possible to make quantitative inferences in the complex evolutionary scenarios typically encountered in invasive species. In this review, we summarize some of the fundamental aspects of routes of invasion, explain why the reconstruction of these routes is useful for addressing both practical and theoretical questions, and comment on the various reconstruction methods available. Finally, we consider the main insights obtained to date from studies of invasion routes.

Soils are the product of the activities of plants, which supply organic matter and play a pivotal role in weathering rocks and minerals. Many plant species have a distinct ecological amplitude that shows restriction to specific soil types. In the numerous interactions between plants and soil, microorganisms also play a key role. Here we review the existing literature on interactions between plants, microorganisms and soils, and include considerations of evolutionary time scales, where possible. Some of these interactions involve intricate systems of communication, which in the case of symbioses such as the arbuscular mycorrhizal symbiosis are several hundreds of millions years old; others involve the release of exudates from roots, and other products of rhizodeposition that are used as substrates for soil microorganisms. The possible reasons for the survival value of this loss of carbon over tens or hundreds of millions of years of evolution of higher plants are discussed, taking a cost-benefit approach. Co-evolution of plants and rhizosphere microorganisms is discussed, in the light of known ecological interactions between various partners in terrestrial ecosystems. Finally, the role of higher plants, especially deep-rooted plants and associated microorganisms in the weathering of rocks and minerals, ultimately contributing to pedogenesis, is addressed. We show that rhizosphere processes in the long run are central to biogeochemical cycles, soil formation and Earth history. Major anticipated discoveries will enhance our basic understanding and allow applications of new knowledge to deal with nutrient deficiencies, pests and diseases, and the challenges of increasing global food production and agroecosystem productivity in an environmentally responsible manner.

SUMMARY: QDD is an open access program providing a user-friendly tool for microsatellite detection and primer design from large sets of DNA sequences. The program is designed to deal with all steps of treatment of raw sequences obtained from pyrosequencing of enriched DNA libraries, but it is also applicable to data obtained through other sequencing methods, using FASTA files as input. The following tasks are completed by QDD: tag sorting, adapter/vector removal, elimination of redundant sequences, detection of possible genomic multicopies (duplicated loci or transposable elements), stringent selection of target microsatellites and customizable primer design. It can treat up to one million sequences of a few hundred base pairs in the tag-sorting step, and up to 50,000 sequences in a single input file for the steps involving estimation of sequence similarity. AVAILABILITY: QDD is freely available under the GPL licence for Windows and Linux from the following web site: http://www.univ-provence.fr/gsite/Local/egee/dir/meglecz/QDD.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.