Previous work has shown that tree turnover, tree biomass and large liana densities have increased in mature tropical forest plots in the late twentieth century. These results point to a concerted shift in forest ecological processes that may already be having significant impacts on terrestrial carbon stocks, fluxes and biodiversity. However, the findings have proved controversial, partly because a rather limited number of permanent plots have been monitored for rather short periods. The aim of this paper is to characterize regional-scale patterns of 'tree turnover' (the rate with which trees die and recruit into a population) by using improved datasets now available for Amazonia that span the past 25 years. Specifically, we assess whether concerted changes in turnover are occurring, and if so whether they are general throughout the Amazon or restricted to one region or environmental zone. In addition, we ask whether they are driven by changes in recruitment, mortality or both. We find that: (i) trees 10 cm or more in diameter recruit and die twice as fast on the richer soils of southern and western Amazonia than on the poorer soils of eastern and central Amazonia; (ii) turnover rates have increased throughout Amazonia over the past two decades; (iii) mortality and recruitment rates have both increased significantly in every region and environmental zone, with the exception of mortality in eastern Amazonia; (iv) recruitment rates have consistently exceeded mortality rates; (v) absolute increases in recruitment and mortality rates are greatest in western Amazonian sites; and (vi) mortality appears to be lagging recruitment at regional scales. These spatial patterns and temporal trends are not caused by obvious artefacts in the data or the analyses. The trends cannot be directly driven by a mortality driver (such as increased drought or fragmentation-related death) because the biomass in these forests has simultaneously increased. Our findings therefore indicate that long-acting and widespread environmental changes are stimulating the growth and productivity of Amazon forests.

Abstract:The dynamics of tropical forest woody plants was studied at the Nouragues

Aim Leaf traits strongly impact biogeochemical cycles in terrestrial ecosystems. Understanding leaf trait variation along environmental gradients is thus essential to improve the representation of vegetation in Earth system models. Our aims were to quantify relationships between leaf traits and climate in permanent grasslands at a biogeographical scale and to test whether these relationships were sensitive to (a) the level of nitrogen inputs and (b) the inclusion of information pertaining to plant community organization. Location Permanent grasslands throughout France. Methods We combined existing datasets on climate, soil, nitrogen inputs (fertilization and deposition), species composition and four traits, namely specific leaf area, leaf dry matter content and leaf nitrogen and phosphorus concentrations, for 15,865 French permanent grasslands. Trait–climate relationships were tested using the following four climatic variables available across 1,833 pixels (5 km × 5 km): mean annual temperature (MAT) and precipitation (MAP), and two indices accounting for the length of the growing season. We compared these relationships at the pixel level using either using community-level or species’ trait means. Results Our findings were as follows: (a) leaf traits related to plant nutrient economy shift consistently along a gradient of growing season length accounting for temperature and soil water limitations of plant growth (GSLtw); (b) weighting leaf traits by species abundance in local communities is pivotal to capture leaf trait–environment relationships correctly at a biogeographical scale; and (c) the relationships between traits and GSLtw weaken for grasslands with a high nitrogen input. Main conclusions The effects of climate on plant communities are better described using composite descriptors than coarse variables such as MAT or MAP, but appear weaker for high-nitrogen grasslands. Using information at the community level tends to strengthen trait–climate relationships. The interplay of land management, community assembly and bioclimate appears crucial to the prediction of leaf trait variations and their effects on biogeochemical cycles

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Summary Projects that restore river flows can be considered as in situ experiments and should be used to test predictions of the effects of flow changes on fish populations and communities. However, flow restoration projects often lack appropriate monitoring and replication. The Rhône restoration project has included repeated flow changes, in four bypassed reaches of the river, where the increase in minimum daily flow varied from minimal change to a tenfold increase. Fish communities (>55 000 individuals of 36 species) were electrofished at nine sites in the main channels of the four bypassed reaches, for 2–9 years before and for 5–10 years after the flow restoration. An instream hydraulic habitat model, published before restoration and based on observations of fish microhabitat preferences in independent reaches, was applied to the bypassed reaches to predict density changes for 14 species that accounted for 94% of the total fish abundance. In the two bypassed reaches where minimum flow was considerably increased (fivefold and tenfold), the abundance of species preferring fast‐flowing and deep microhabitats increased by factors of 1.9 and 2.4, respectively, whereas the abundance of other species strongly decreased. Predicted changes in density made using the habitat model for these two reaches agreed with the observations at several sites and involved several fish species. In contrast, in the two bypassed reaches where flow changes were less, the observed changes in density were weak and less related to the model predictions. Hydraulic habitat models predicted changes of fish populations and the predictions also explained observed community responses to the changed flows. Ten years after the first flow restoration, our results suggest that the Rhône restoration generated perennial changes of the fish community structure, reversing community patterns that were observed prior to the flow restoration.

Aim The characterization of trait–environment relationships over broad‐scale gradients is a critical goal for ecology and biogeography. This implies the merging of plot and trait databases to assess community‐level trait‐based statistics. Potential shortcomings and limitations of this approach are that: (i) species traits are not measured where the community is sampled and (ii) the availability of trait data varies considerably across species and plots. Here we address the effect of trait data representativeness [the sampling effort per species and per plot] on the accuracy of (i) species‐level and (ii) community‐level trait estimates and (iii) the consequences for the shape and strength of trait–environment relationships across communities. Innovation We combined information existing in databases of vegetation plots and plant traits to estimate community‐weighted means [CWMs] of four key traits [specific leaf area, plant height, seed mass and leaf nitrogen content per dry mass] in permanent grasslands at a country‐wide scale. We propose a generic approach for systematic sensitivity analyses based on random subsampling and data reduction to address the representativeness of incomplete and heterogeneous trait information when exploring trait–environment relationships across communities. Main conclusions The accuracy of the CWMs was little affected by the number of individual trait values per species [NIV] but strongly affected by the cover proportion of species with available trait values [PCover]. A PCover above 80% was required for all four traits studied to obtain an estimation bias below 5%. Our approach therefore provides more conservative criteria than previously proposed. Restrictive criteria on both NIV and PCover primarily excluded communities in harsh environments, and such reduction of the sampled gradient weakened trait–environment relationships. These findings advocate systematic measurement campaigns in natural environments to increase species coverage in global trait databases, with special emphasis on species occurring in under‐sampled and harsh environmental conditions.

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