Abstract: Matrix population models are widely used to predict population dynamics, but when applied to species-rich ecosystems with many rare species, the small population sample sizes hinder a good fit of species-specific models. This issue can be overcome by assigning species to groups to increase the size of the calibration data sets. However, the species classification is often disconnected from the matrix modelling and from the estimation of matrix parameters, thus bringing species groups that may not be optimal with respect to the predicted community dynamics. We proposed here a method that jointly classified species into groups and fit the matrix models in an integrated way. The model was a special case of mixture with unknown number of components and was cast in a Bayesian framework. An MCMC algorithm was developed to infer the unknown parameters: the number of groups, the group of each species and the dynamics parameters. We applied the method to simulated data and showed that the algorithm efficiently recovered the model parameters. We applied the method to a data set from a tropical rain forest in French Guiana. The mixture matrix model classified tree species into well-differentiated groups with clear ecological interpretations. It also accurately predicted the forest dynamics over the 16-year observation period. Our model and algorithm can straightforwardly be adapted to any type of matrix model, using the life cycle diagram. It can be used as an unsupervised classification technique to group species with similar population dynamics. © 2012 The Authors. Methods in Ecology and Evolution © 2012 British Ecological Society.

Abstract: Cocoa black pod rot, a disease caused by Stramenopiles of the genus Phytophthora, and particularly by the pan-tropical species P. palmivora, causes serious production losses worldwide. In order to reduce the impact of these pests and diseases, preference is given to genetic control using resistant varieties and, to that end, breeders seek sources of resistance in wild cocoa trees. For instance, surveys of spontaneous cocoa trees in French Guiana between 1985 and 1995 led to the collection of abundant plant material forming a particular genetic group (the “Guiana” group). Following numerous one-off studies demonstrating the merits of this group as a source of resistance to Phytophthora, this article presents the results of a comprehensive study assessing the resistance of 186 “Guiana” clones in relation to the Guianan strain (GY 27) of P. palmivora. This study, undertaken in French Guiana, using an efficient methodology (ten series of tests and a statistical test adapted to the ordinal nature of the data) confirmed that the “Guiana” genetic group does indeed constitute an important source of resistance to P. palmivora, though with some variations depending on the demes of origin. Numerous clones (59) proved to be as resistant as the SCAVINA 6 resistance control, whilst nine were statistically more resistant. The “Resistant” and “Moderately Resistant” Guianan clones totalled 108 (58% of the total tested). Some of the clones more resistant than SCAVINA 6 could be incorporated into numerous cocoa breeding programmes, particularly those that also display other notable qualities. The same applies for numerous other clones equivalent to SCAVINA 6, especially the “elite”' clones GU 134-B, GU 139-A and GU 285-A. © 2012 Thevenin et al.

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: Tropical soils are a major contributor to the balance of greenhouse gas (GHG) fluxes in the atmosphere. Models of tropical GHG fluxes predict that both the frequency of drought events and changes in atmospheric deposition of nitrogen (N) will significantly affect dynamics of soil carbon dioxide (CO2) and methane (CH4) production and consumption. In this study, we examined the combined effect of a reduction in precipitation and an increase in nutrient availability on soil CO2 and CH4 fluxes in a primary French Guiana tropical forest. Drought conditions were simulated by intercepting precipitation falling through the forest canopy with tarpaulin roofs. Nutrient availability was manipulated through application of granular N and/or phosphorus (P) fertilizer to the soil. Soil water content (SWC) below the roofs decreased rapidly and stayed at continuously low values until roof removal, which as a consequence roughly doubled the duration of the dry season. After roof removal, SWC slowly increased but remained lower than in the control soils even after 2.5 months of wet-season precipitation. We showed that drought-imposed reduction in SWC decreased the CO2 emissions (i.e., CO2 efflux), but strongly increased the CH4 emissions. N, P, and N × P (i.e., NP) additions all significantly increased CO2 emission but had no effect on CH4 fluxes. In treatments where both fertilization and drought were applied, the positive effect of N, P, and NP fertilization on CO2 efflux was reduced. After roof removal, soil CO2 efflux was more resilient in the control plots than in the fertilized plots while there was only a modest effect of roof removal on soil CH4 fluxes. Our results suggest that a combined increase in drought and nutrient availability in soil can locally increase the emissions of both CO2 and CH4 from tropical soils, for a long term.

Abstract: Key message: Forest disturbance affects the within-population distribution of genetic diversity, but not its overall levels, in a tropical pioneer tree species. In particular, clumps of related saplings with impoverished diversity are found in canopy gaps but not under forest cover. Context: Forest disturbances can have long-term consequences on the genetic structure of tree populations, because they can alter the demographic properties of the regeneration process and favour some subpopulations/genotypes, both by stochastic processes and by selection. Intermediate disturbances tend to favour species diversity, at least in highly diverse communities, but their effect on intra-specific diversity is unknown. Aims: In this study, we have looked at the genetic consequences of forest disturbance in a stand of the long-lived Neotropical pioneer species, Jacaranda copaia. Methods: The study site was experimentally logged in 1984, and the canopy gaps generated by the logging were mapped. Seedlings of J. copaia colonised the gaps, as expected, at a higher density than in the surrounding forest. In 2006, we exhaustively sampled all saplings and adult trees available in a 25-ha area. The samples were genotyped at nine microsatellite loci, and the distribution of genetic diversity was inspected by analyses of spatial autocorrelation, automated Bayesian assignment and comparisons of diversity between cohorts by bootstrap (RaBoT). Results: Spatial autocorrelation was found to extend farther in post-disturbance saplings than in the undisturbed population (100 m and beyond versus less than 50 m), and divergent clumps (F<inf>ST</inf> = 0.05) of related genotypes were found; genetic diversity was found to be impoverished in each clump relative to the global population at about half of the loci. Conclusion: Overall, our results suggest that forest disturbance has changed the patterns of distribution of genetic diversity, with potential consequences on long-term population viability. © 2015, INRA and Springer-Verlag France.