Abstract: P>1. Modelling growth strategies among tropical trees is an important objective in predicting the response of tree dynamics to selective logging and in gaining insights into the ecological processes that structure tree communities in managed tropical forests. 2. We developed a disturbance index to model the effects of distance to and area of logging gaps on stem radial growth rates. This index was tested using census data of 43 neotropical tree species, representing a variety of life-history strategies and developmental stages, from a selectively logged forest at Paracou, French Guiana. Growth strategies were analyzed in light of two indicators: the inherent species growth rate (when disturbance index is null) and the species reaction (change in growth rate) to logging gaps. 3. Across species, the predicted inherent growth rates in unlogged forest ranged from 0 center dot 25 to 6 center dot 47 mm year-1, with an average growth of 2 center dot 29 mm year-1. Ontogenetic shifts in inherent growth rate were found in 26 of the 43 species. 4. Species growth response to logging gaps varied widely among species but was significantly positive for 27 species. The effect of ontogeny on growth response to logging was retained for 14 species, and species with inherent fast growth rate (5 mm year-1) responded less to logging gap disturbances than did species with slow inherent growth (1 mm year-1). 5. Functional traits explained 19-42% of the variation in the inherent growth rate and in species' response across all developmental stages. Whereas maximum diameters and seed mass were strong predictors of inherent growth rate, maximum height, wood density, mode of germination and stem architecture were additionally involved in tree growth response. 6. Synthesis and applications: This study provides a necessary framework for developing predictive post-logging growth models for the thousands of species comprising tropical forests and is sufficiently general to apply to a broad range of managed tropical forests.

Abstract: Plant phenology characterises the seasonal cyclicity of biological events such as budburst, flowering, fructification, leaf senescence and leaf fall. These biological events are genetically pre-determined but also strongly modulated by climatic conditions, particularly temperature, daylength and water availability. Therefore, the timing of these events is considered as a good indicator of climate change impacts and as a key parameter for understanding and modelling vegetation-climate interactions. In situ observations, empirical or bioclimatic models and remotely sensed time-series data constitute the three possible ways for monitoring the timing of plant phenological events. Remote sensing has the advantage of being the only way of surface sampling at high temporal frequency and, in the case of satellite-based remote sensing, over large regions. Nevertheless, exogenous factors, particularly atmospheric conditions, lead to some uncertainties on the seasonal course of surface reflectance and cause bias in the identification of vegetation phenological events. Since 2005, a network of forest and herbaceous sites has been equipped with laboratory made NDVI sensors to monitor the temporal dynamics of canopy structure and phenology at an intra-daily time step. In this study, we present recent results obtained in several contrasting biomes in France, French Guiana, Belgium and Congo. These sites represent a gradient of vegetation ecosystems: the main evergreen and deciduous forest ecosystems in temperate climate region, an evergreen tropical rain forest in French Guiana, an herbaceous savanna ecosystem in Congo, and a succession of three annual crops in Belgium. In this paper, (1) we provide an accurate description of the seasonal dynamics of vegetation cover in these different ecosystems (2) we identify the most relevant remotely sensed markers from NDVI time-series for determining the dates of the main phenological events that characterize these ecosystems and (3) we discuss the relationships between temporal canopy dynamics and climate factors. In addition to its importance for phenological studies, this ground-based Network of NDVI measurement provides data needed for the calibration and direct validation of satellite observations and products. © 2012 Elsevier Inc.

Abstract: Plant functional traits, in particular specific leaf area (SLA), wood density and seed mass, are often good predictors of individual tree growth rates within communities. Individuals and species with high SLA, low wood density and small seeds tend to have faster growth rates. If community-level relationships between traits and growth have general predictive value, then similar relationships should also be observed in analyses that integrate across taxa, biogeographic regions and environments. Such global consistency would imply that traits could serve as valuable proxies for the complex suite of factors that determine growth rate, and, therefore, could underpin a new generation of robust dynamic vegetation models. Alternatively, growth rates may depend more strongly on the local environment or growth-trait relationships may vary along environmental gradients. We tested these alternative hypotheses using data on 27 352 juvenile trees, representing 278 species from 27 sites on all forested continents, and extensive functional trait data, 38% of which were obtained at the same sites at which growth was assessed. Data on potential evapotranspiration (PET), which summarizes the joint ecological effects of temperature and precipitation, were obtained from a global data base. We estimated size-standardized relative height growth rates (SGR) for all species, then related them to functional traits and PET using mixed-effect models for the fastest growing species and for all species together. Both the mean and 95th percentile SGR were more strongly associated with functional traits than with PET. PET was unrelated to SGR at the global scale. SGR increased with increasing SLA and decreased with increasing wood density and seed mass, but these traits explained only 3.1% of the variation in SGR. SGR-trait relationships were consistently weak across families and biogeographic zones, and over a range of tree statures. Thus, the most widely studied functional traits in plant ecology were poor predictors of tree growth over large scales. Synthesis. We conclude that these functional traits alone may be unsuitable for predicting growth of trees over broad scales. Determining the functional traits that predict vital rates under specific environmental conditions may generate more insight than a monolithic global relationship can offer. The most widely studied functional traits in plant ecology, specific leaf area, wood density and seed mass, were only weakly associated with tree growth rates over broad scales. Assessing trait-growth relationships under specific environmental conditions may generate more insight than a global relationship can offer. © 2015 British Ecological Society.

Abstract: Plant functional traits directly affect ecosystem functions. At the species level, trait combinations depend on trade-offs representing different ecological strategies, but at the community level trait combinations are expected to be decoupled from these trade-offs because different strategies can facilitate co-existence within communities. A key question is to what extent community-level trait composition is globally filtered and how well it is related to global versus local environmental drivers. Here, we perform a global, plot-level analysis of trait–environment relationships, using a database with more than 1.1 million vegetation plots and 26,632 plant species with trait information. Although we found a strong filtering of 17 functional traits, similar climate and soil conditions support communities differing greatly in mean trait values. The two main community trait axes that capture half of the global trait variation (plant stature and resource acquisitiveness) reflect the trade-offs at the species level but are weakly associated with climate and soil conditions at the global scale. Similarly, within-plot trait variation does not vary systematically with macro-environment. Our results indicate that, at fine spatial grain, macro-environmental drivers are much less important for functional trait composition than has been assumed from floristic analyses restricted to co-occurrence in large grid cells. Instead, trait combinations seem to be predominantly filtered by local-scale factors such as disturbance, fine-scale soil conditions, niche partitioning and biotic interactions.

Abstract: The majority of variation in six traits critical to the growth, survival and reproduction of plant species is thought to be organised along just two dimensions, corresponding to strategies of plant size and resource acquisition. However, it is unknown whether global plant trait relationships extend to climatic extremes, and if these interspecific relationships are confounded by trait variation within species. We test whether trait relationships extend to the cold extremes of life on Earth using the largest database of tundra plant traits yet compiled. We show that tundra plants demonstrate remarkably similar resource economic traits, but not size traits, compared to global distributions, and exhibit the same two dimensions of trait variation. Three quarters of trait variation occurs among species, mirroring global estimates of interspecific trait variation. Plant trait relationships are thus generalizable to the edge of global trait-space, informing prediction of plant community change in a warming world. © 2020, Crown.