Dispersal is a ubiquitous trait in living organisms. Evolutionary theory postulates that the loss or death of propagules during dispersal episodes (cost of dispersal) should select against dispersal. The cost of dispersal is expected to be a strong selective force in fragmented habitats. We analyzed patchy populations of the weed Crepis sancta occupying small patches on sidewalks, around trees planted within the city of Montpellier (South of France), to investigate the recent evolutionary consequences of the cost of dispersal. C. sancta produces both dispersing and nondispersing seeds. First, we showed that, in urban patches, dispersing seeds have a 55% lower chance of settling in their patch compared with nondispersing seeds and, thus, fall on a concrete matrix unsuitable for germination. Second, we showed that the proportion of nondispersing seeds in urban patches measured in a common environment is significantly higher than in surrounding, unfragmented populations. Third, by using a quantitative genetic model, we estimated that the pattern is consistent with short-term evolution that occurs over Ϸ5-12 generations of selection, which is generated by a high cost of dispersal in urban populations. This study shows that a high cost of dispersal after recent fragmentation causes rapid evolution toward lower dispersal.fragmentation ͉ short-term evolution ͉ human-altered habitat D ispersal has evolved in almost all living organisms and is thus considered as a central life-history trait (1, 2). The evolution of dispersal is usually understood as the result of a cost-benefit process. On the one hand, three main factors selecting for dispersal have been identified (3): reduction of the competition among kin (4, 5); the temporal heterogeneity of the environment, such as local population extinction (6, 7); and last, the avoidance of inbreeding depression when mating occurs between related individuals (8). However, various costs of dispersal have been postulated in theoretical models. For instance, dispersal structures can be costly for organisms [e.g., fleshy fruits dispersed by animals (9)]. More generally, dispersing organisms may pay a high cost of dispersal because they may get lost during the displacement. This phenomenon is encapsulated under the term ''cost of dispersal.'' Various theoretical models have been studied, including various selective factors (3). These theoretical models conclude that increasing the cost of dispersal selects for lower dispersal. Although this cost may appear as obvious in natural populations, the strength of this selection pressure on dispersal traits is almost unknown in the wild because of the difficulties of measuring it in natural systems. When dispersal is passive (wind or water transport) and habitat choice is random, the probability of settling in a suitable site is positively dependent on the frequency of suitable sites in the landscape. Many empirical studies have reported a reduction in dispersal structures in organisms that live on islands, such as plants (10) or insects (ho...

The study of natural ecosystems and experiments using mixtures of plant species demonstrates that both species and genetic diversity generally promote ecosystem functioning. Therefore, mixing crop varieties is a promising alternative practice to transform modern high-input agriculture that is associated with a drastic reduction of within-field crop genetic diversity and is widely recognized as unsustainable. Here, we review the effects of mixtures of varieties on ecosystem functioning, and their underlying ecological mechanisms, as studied in ecology and agronomy, and outline how this knowledge can help designing more efficient mixtures. We recommend the development of two complementary strategies to optimize variety mixtures by fostering the ecological mechanisms leading to a positive relationship between biodiversity and ecosystem functioning and its stability through time, i.e., sampling and complementarity effects. (1) In the "trait-blind" approach, the design of high-performance mixtures is based on estimations of the mixing abilities of varieties. While this approach is operational because it does not require detailed trait knowledge, it relies on heavy experimental designs to evaluate mixing ability. (2) The trait-based approach is particularly efficient to design mixtures of varieties to provide particular baskets of services but requires building databases of traits for crop varieties and documenting the relations between traits and services. The performance of mixtures requires eventually to be evaluated in real economic, social, and agronomic contexts. We conclude that the need of a multifunctional low-input agriculture strongly increases the attractiveness of mixtures but that new breeding approaches are required to create varieties with higher mixing abilities, to foster complementarity and selection effects through an increase in the variance of relevant traits and to explore new combinations of trait values

Questions How does above‐ground grassland biomass production respond to change in multiple climate drivers over a 4‐yr period? Can climate‐induced patterns of biomass response be explained by shifts in plant community structure? Does sustained climate change affect the relationships between abundance of functional groups, community‐scale leaf traits and above‐ground production? Location Perennial grassland in the French Massif Central. Methods Monoliths extracted from the study grassland were exposed to a simulated climate change corresponding to the air temperature, atmospheric CO 2 and summer rainfall conditions projected for 2080. We examined impacts of climate treatments on above‐ground biomass and community structure for 4 yr, and investigated the relationship between biomass production, species diversity and three key functional traits: specific leaf area, leaf dry matter content and leaf N content. Results Both warming and simultaneous application of warming, summer drought and elevated CO 2 were associated with an increase in annual above‐ground biomass at the start of the study, but biomass responses became progressively negative over the course of the experiment. Decreases in vegetation N exports were also observed over time, possibly due to reduced soil N availability under climate change. Taxonomic diversity showed no response to climate treatments, but the relative abundance of grasses decreased under both warming and simultaneous application of warming, summer drought and elevated CO 2 after 3 yr. In parallel, legume relative abundance increased in all warmed treatments. Functional diversity responses varied depending on climate treatment and leaf trait. In the control treatment, patterns of variation in annual plant biomass were best explained by functional diversity during the study period. However, in warmed treatments, variation in annual plant biomass was more closely linked to the functional traits of dominant species. Conclusions Continuous, multi‐year exposure to projected climate conditions has a negative impact on above‐ground biomass in our grassland study system. Our data suggest that climate‐induced decreases in above‐ground biomass may be driven by changes in the relative abundance of plant functional groups, and could also reflect changes in soil nutrient availability. Unlike species diversity, community‐level leaf traits and functional diversity appear to play an important role for above‐ground biomass production, and may have indirect effects on ecosystem stability in changing climates.

It has long been recognized that plant species and soil microorganisms. are tightly linked, but understanding how different species vary in their effects on soil is currently limited. In this study, we identified those. plant characteristics (identity, specific functional traits, or resource acquisition strategy) that were the best predictors of nitrification and denitrification processes. Ten plant populations representing eight species collected from three European grassland sites were chosen for their contrasting plant trait values and resource acquisition strategies. For each individual plant, leaf and root traits and the associated potential microbial activities (i.e., potential denitrification rate [DEA], maximal nitrification rate [NEA], and NH4+ affinity of the microbial community [NHScom]) were measured at two fertilization levels under controlled growth conditions. Plant traits were powerful predictors of plant-microbe interactions, but relevant plant traits differed in relation to the microbial function studied. Whereas denitrification was linked to the relative growth rate of plants, nitrification was strongly correlated to root trait characteristics (specific root length, root nitrogen concentration, and plant affinity for NH4+) linked to plant N cycling. The leaf economics spectrum (LES) that commonly serves as an indicator of resource acquisition strategies was not correlated to microbial activity. These results suggest that the LES alone is not a good predictor of microbial activity, whereas root traits appeared critical in understanding plant-microbe interactions.