Abstract: How tropical tree species respond to disturbance is a central issue of forest ecology, conservation and resource management. We define a hierarchical model to investigate how functional traits measured in control plots relate to the population change rate and to demographic rates for recruitment and mortality after disturbance by logging operations. Population change and demographic rates were quantified on a 12-year period after disturbance and related to seven functional traits measured in control plots. The model was calibrated using a Bayesian Network approach on 53 species surveyed in permanent forest plots (37.5 ha) at Paracou in French Guiana. The network analysis allowed us to highlight both direct and indirect relationships among predictive variables. Overall, 89% of interspecific variability in the population change rate after disturbance were explained by the two demographic rates, the recruitment rate being the most explicative variable. Three direct drivers explained 45% of the variability in recruitment rates, including leaf phosphorus concentration, with a positive effect, and seed size and wood density with negative effects. Mortality rates were explained by interspecific variability in maximum diameter only (25%). Wood density, leaf nitrogen concentration, maximum diameter and seed size were not explained by variables in the analysis and thus appear as independent drivers of post-disturbance demography. Relationships between functional traits and demographic parameters were consistent with results found in undisturbed forests. Functional traits measured in control conditions can thus help predict the fate of tropical tree species after disturbance. Indirect relationships also suggest how different processes interact to mediate species demographic response.

Abstract: Climate models predict significant rainfall reduction in Amazonia, reducing water availability for trees. We present how functional traits modulate the tree growth response to climate. We used data from 3 years of bimestrial growth measurements for 204 trees of 53 species in the forest of Paracou, French Guiana. We integrated climate variables from an eddy covariance tower and functional trait values describing life history, leaf, and stem economics. Our results indicated that the measured functional traits are to some extent linked to the response of trees to climate but they are poor predictors of the tree climate-induced growth variation. Tree growth was affected by water availability for most of the species with different species growth strategies in drought conditions. These strategies were linked to some functional traits, especially maximum height and wood density. These results suggest that (i) trees seem adapted to the dry season at Paracou but they show different growth responses to drought, (ii) drought response is linked to growth strategy and is partly explained by functional traits, and (iii) the limited part of the variation of tree growth explained by functional traits may be a strong limiting factor for the prediction of tree growth response to climate. © 2014 Fabien Wagner et al.

Abstract: Herbivory is viewed as a major driver of plant evolution and the most important energy pathway from plants to higher trophic levels. Therefore, understanding patterns of herbivory on plants remains a key focus in evolution and ecology. The evolutionary impacts of leaf herbivory include altering plant fitness, local adaptation, the evolution of defenses, and the diversification of plants as well as natural enemies. Leaf herbivory also impacts ecological processes such as plant productivity, community composition, and ecosystem nutrient cycling. Understanding the impact of herbivory on these ecological and evolutionary processes requires species-specific, as opposed to community-level, measures of herbivory. In addition, species-specific data enables the use of modern comparative methods to account for phylogenetic non-independence. Although hundreds of studies have measured natural rates of leaf consumption, we are unaware of any accessible compilation of these data. We created such a data set to provide the raw data needed to test general hypotheses relating to plant?herbivore interactions and to test the influence of biotic and abiotic factors on herbivory rates across large spatial scales. A large repository will make this endeavor more efficient and robust. In total, we compiled 2641 population-level measures for either annual or daily rates of leaf herbivory across 1145 species of vascular plants collected from 189 studies. All damage measures represent natural occurrences of herbivory that span numerous angiosperm, gymnosperm, and fern species. To enable researchers to explore the causes of variation in herbivory and how these might interact, we added information about the study sites including: geolocation, climate classification, habitat descriptions (e.g., seashore, grassland, forest, agricultural fields), and plant trait information concerning growth form and duration (e.g., annual vs. perennial). We also included extensive details of the methodology used to measure leaf damage, including seasons and months of sampling, age of leaves, and the method used to estimate percentage area missing. We anticipate that these data will make it possible to test important hypotheses in the plant?herbivore literature, including the plant apparency hypothesis, the latitudinal-herbivory defense hypothesis, the resource availability hypothesis, and the macroevolutionary escalation of defense hypothesis.

Abstract: Advances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation). Though broad-scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8-50 ha) globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass density (AGBD in Mg ha-1) at spatial scales ranging from 5 to 250 m (0.025-6.25 ha), and to evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that local spatial variability in AGBD is large for standard plot sizes, averaging 46.3% for replicate 0.1 ha subplots within a single large plot, and 16.6% for 1 ha subplots. AGBD showed weak spatial autocorrelation at distances of 20-400 m, with autocorrelation higher in sites with higher topographic variability and statistically significant in half of the sites. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGBD leads to a substantial “dilution” bias in calibration parameters, a bias that cannot be removed with standard statistical methods. Our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise.

Abstract: Atmospheric carbon dioxide records indicate that the land surface has acted as a strong global carbon sink over recent decades, with a substantial fraction of this sink probably located in the tropics, particularly in the Amazon. Nevertheless, it is unclear how the terrestrial carbon sink will evolve as climate and atmospheric composition continue to change. Here we analyse the historical evolution of the biomass dynamics of the Amazon rainforest over three decades using a distributed network of 321 plots. While this analysis confirms that Amazon forests have acted as a long-term net biomass sink, we find a long-term decreasing trend of carbon accumulation. Rates of net increase in above-ground biomass declined by one-third during the past decade compared to the 1990s. This is a consequence of growth rate increases levelling off recently, while biomass mortality persistently increased throughout, leading to a shortening of carbon residence times. Potential drivers for the mortality increase include greater climate variability, and feedbacks of faster growth on mortality, resulting in shortened tree longevity. The observed decline of the Amazon sink diverges markedly from the recent increase in terrestrial carbon uptake at the global scale, and is contrary to expectations based on models. © 2015 2015 Macmillan Publishers Limited.