Search

How weed communities assemble represents one the key issues of weed science. For a decade, functional approaches have been applied to investigate the processes that govern weed community assembly. In most previous studies, trait values have been generally averaged over multiple populations and habitats. Consequently, conspecifics display similar trait values while neglecting the considerable influence of intraspecific variability to detect changes in functional diversity in response to environmental drivers. However, this influence has been shown to be critical, especially, at local scales. Here, we studied changes in weed functional diversity at the field scale in four crop sequences. We focused on intra- and interspecific variability of four key functional traits involved in response to resource acquisition processes, the latter being modified by climate, management and competition. The relative influence of intra- and interspecific variability among the crop sequence types was highlighted using a diversity partitioning approach. It provides evidence for substantial amount of intraspecific variability in the weed community and underlines its essential role in response to fine-scale environmental drivers. In addition, we investigated the response of the three most abundant species to competition with the crop, the growing season and the crop sequence type. We highlighted that these species showed a wide range of combinations of trait values, suggesting the co-existence of several successful strategies. Based on these results, we emphasise that neglecting intraspecific variability can lead to substantial underestimations of the functional weed response to management and crop-weed competition at the field scale. [ABSTRACT FROM AUTHOR]

Whether the success of alien species can be explained by their functional or phylogenetic characteristics remains unresolved because of data limitations, scale issues and weak quantifications of success. Using permanent grasslands across France (50 000 vegetation plots, 2000 species, 130 aliens) and building on the Rabinowitz's classification to quantify spread, we showed that phylogenetic and functional similarities to natives were the most important correlates of invasion success compared to intrinsic functional characteristics and introduction history. Results contrasted between spatial scales and components of invasion success. Widespread and common aliens were similar to co-occurring natives at coarse scales (indicating environmental filtering), but dissimilar at finer scales (indicating local competition). In contrast, regionally widespread but locally rare aliens showed patterns of competitive exclusion already at coarse scale. Quantifying trait differences between aliens and natives and distinguishing the components of invasion success improved our ability to understand and potentially predict alien spread at multiple scales., (© 2015 John Wiley & Sons Ltd/CNRS.)

The effect of biodiversity on ecosystem functioning has been widely acknowledged, and the importance of the functional roles of species, as well as their diversity, in the control of ecosystem processes has been emphasised recently. However, bridging biodiversity and ecosystem science to address issues at a biogeographic scale is still in its infancy. Bridging this gap is the primary goal of the emerging field of functional biogeography. While the rise of Big Data has catalysed functional biogeography studies in recent years, comprehensive evidence remains scarce. Here, we present the rationale and the first results of a country-wide initiative focused on the C3 permanent grasslands. We aimed to collate, integrate and process large databases of vegetation relevés, plant traits and environmental layers to provide a country-wide assessment of ecosystem properties and services which can be used to improve regional models of climate and land use changes. We outline the theoretical background, data availability, and ecoinformatics challenges associated with the approach and its feasibility. We provide a case study of upscaling of leaf dry matter content averaged at ecosystem level and country-wide predictions of forage digestibility. Our framework sets milestones for further hypothesis testing in functional biogeography and earth system modelling., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Predicting the population dynamics of annual plants is a challenge due to their hidden seed banks in the field. However, such predictions are highly valuable for determining management strategies, specifically in agricultural landscapes. In agroecosystems, most weed seeds survive during unfavourable seasons and persist for several years in the seed bank. This causes difficulties in making accurate predictions of weed population dynamics and life history traits (LHT). Consequently, it is very difficult to identify management strategies that limit both weed populations and species diversity. In this article, we present a method of assessing weed population dynamics from both standing plant time series data and an unknown seed bank. We use a Hidden Markov Model (HMM) to obtain estimates of over 3,080 botanical records for three major LHT: seed survival in the soil, plant establishment (including post-emergence mortality), and seed production of 18 common weed species. Maximum likelihood and Bayesian approaches were complementarily used to estimate LHT values. The results showed that the LHT provided by the HMM enabled fairly accurate estimates of weed populations in different crops. There was a positive correlation between estimated germination rates and an index of the specialisation to the crop type (IndVal). The relationships between estimated LHTs and that between the estimated LHTs and the ecological characteristics of weeds provided insights into weed strategies. For example, a common strategy to cope with agricultural practices in several weeds was to produce less seeds and increase germination rates. This knowledge, especially of LHT for each type of crop, should provide valuable information for developing sustainable weed management strategies.