Abstract: Modelling the local density of tropical saplings can provide insights into the ecological processes that drive species regeneration and thereby help predict population recovery after disturbance. Yet, few studies have addressed the challenging issues in autocorrelation and zero-inflation of local density. This paper presents Hierarchical Bayesian Modelling (HBM) of sapling density that includes these two features. Special attention is devoted to variable selection, model estimation and comparison. We developed a Zero-Inflated Poisson (ZIP) model with a latent correlated spatial structure and compared it with non-spatial ZIP and Poisson models that were either autocorrelated (Spatial Generalized Linear Mixed, SGLM) or not (generalized linear models, GLM). In our spatial models, local density autocorrelation was modeled by a Conditional Auto-Regressive (CAR) process. 13 explicative variables described ecological conditions with respect to topography, disturbance, stand structure and intraspecific processes. Models were applied to six tropical tree species with differing biological attributes: Oxandra asbeckii, Eperua falcata, Eperua grandiflora, Dicorynia guianensis, Qualea rosea, and Tachigali melinonii. We built species-specific models using a simple method of variable selection based on a latent binary indicator. Our spatial models showed a close correlation between observed and estimated densities with site spatial structure being correctly reproduced. By contrast, the non-spatial models showed poor fits. Variable selection highlighted species-specific requirements and susceptibility to local conditions. Model comparison overall showed that the SGLM was the most accurate explanatory and predictive model. Surprisingly, zero-inflated models performed less well. Although the SZIP model was relevant with respect to data distribution, and more flexible with respect to response curves, its model complexity caused marked variability in parameter estimates. In the SUM, the spatial process alone accounted for zero-inflation in the data. A refinement of the hypotheses employed at the process level could compensate for distribution flaws at the data level. This study emphasized the importance of the HBM framework in improving the modelling of density-environment relationships. (C) 2008 Elsevier B.V. All rights reserved.

Abstract: Understanding the effects of logging activity on genetic diversity is an important aspect of establishing the sustainability of selective logging management operations in tropical forests. Genetic variation is affected by selective logging directly, through the removal of and damage to trees within the population, and indirectly, through a change in the forest structure and environment in which the remaining population lives. Eco-Gene is a population genetics model applied to tropical forests over a scale of hundreds of hectares. SYMFOR is a modelling framework for individual-based spatially explicit ecological and management models applied to tropical forests over a scale of 0.25 4 ha. We have linked the models to enable simulations using processes involved in both models. To overcome problems of scale, the spatially explicit competition index calculated in SYMFOR simulations has been modelled such that it can be applied at scales representing much larger areas for which the data are not available, as required by Eco-Gene. The competition index is modelled as a distribution on a grid-square basis, and implemented in the linked Eco-Gene/SYMFOR system. Each tree within a grid-square is given a “relative competition” within the distribution, biased according to species. A competition index value is obtained for the tree by transforming the grid-square distribution to be relevant to the size of the tree, and extracting a value according to the tree's relative competition within the distribution. The distribution and each tree's relative competition within it change according to the effects of growth, mortality and logging activity. The model was calibrated using data from the Tapajos region of the Eastern Amazon forest. This paper describes the model, its calibration and validation and the implications of scaling up from an explicit representation to a modelled quantity. (C) 2004 Elsevier B.V. All rights reserved.

Abstract: A major challenge for forest managers is to define the optimal cutting cycle to ensure that the resource is sustained in the long term. Matrix models of forest dynamics allow time-projection of diameter-class distributions and thus assessment of the time needed, after logging, to recover a given part of the exploitable stock. They are easy to build and they only require, as input variables, the diameter structure of the population(s) under scope. However, such models are based on a coarse description of tree population dynamics and must be used with caution. In particular, as trees are only described from a diameter threshold (usually 10 cm dbh), recruitment of a new tree cannot be linked with the preceding generation since too much time elapsed between seed dispersal and the installation of a 10-cm recruit. This causes predictions of matrix models to be highly questionable in the long term when ingrowth to larger dbh classes greatly depends on the way recruitment has been modelled. We used a case study from French Guiana to test whether or not a simple matrix model is reliable enough to help forest managers choose between management alternatives. We focused on the major timber species Dicorynia guianensis Amshoff (Caesalpiniaceae) harvested under a selective cutting regime. We compared predictions of D. guianensis stock recovery in the short and long term provided by two models: StoMat, a non-regulated matrix model, and SELVA, a single-tree distance dependent model explicitly simulating the entire species life cycle. Both models were independently calibrated on data from Paracou permanent sample plots. We showed that: (i) the short-term recovery of the exploitable stock predicted by StoMat is reliable for a large range of disturbance conditions; (ii) recruitment implementation in StoMat does not influence projections until the third felling cycle; (iii) for shared initial stand conditions SELVA and StoMat give consistent mid- and long-term predictions: the simple recruitment model used into StoMat could efficiently summarise the regeneration processes of the species under low felling intensity. Our results indicate that the current felling regime used in French Guiana may not be sustainable on a long-term basis. In any case, no more than 60% of the initial stock would be recovered after logging. We conclude that simple models can provide as reliable predictions as more complicated ones. They may be sufficient to assess the recovery of a species' exploitable stock even in the long term, or at least assess the (un)sustainability of particular harvesting regimes. (c) 2005 Elsevier B.V. All rights reserved.

Abstract: Oak chloroplast DNA (cpDNA) variation was studied in a grid-based inventory in western Central Europe, including Belgium, The Netherlands, Luxembourg, Germany, the Czech Republic, and the northern parts of Upper and Lower Austria. A total of 2155 trees representing 426 populations of Quercus robur L. and Q. petraea (Matt.) Liebl. were screened for polymorphism in up to four PCR-amplified cpDNA fragments. Eleven haplotypes belonging to four lineages were detected; these lineages were formerly restricted to glacial refugia in the Iberian Peninsula, the Apennine Peninsula and the Balkan Peninsula. The haplotypes originating from the Apennines are particularly well represented in the study region, but there is also a significant contribution from the other refugia, which explain the high overall level of cpDNA diversity. The strong human impact in western Central Europe during the past centuries, which has resulted in the clearance of most forests, was followed by reforestation, sometimes involving seed transfers. Despite this strong human impact, broad geographic patterns of lineages and haplotypes could still be detected. To evaluate further the consequences of the former human activities on the present day oak cpDNA genetic structure, four regions where increasingly strong human impact was anticipated (ranging from hilly regions in southern Germany to roadsides plantations in The Netherlands) were selected. There, a comparison of the levels of intrapopulation cpDNA diversity and spatial structuring was made. Over the whole area, within stand diversity was significantly higher in Q. robur than in Q. petraea (h(S) = 0.24 vs. 0.16). Since total diversity is identical for both species, this results in a significantly lower level of fixation for Q. robur than for Q. petraea (G(ST) = 0.68 vs. 0.79). The analyses also reveal a decrease of fixation with increasing human impact on oak populations. The Dutch roadside plantations (Q. robur) exhibit a very low level of fixation (G(ST) = 0.28) as compared to Q. petraea in southern Germany (G(ST) = 0.91). The significance of the spatial genetic structure was tested using geostatistical methods. For the complete data set, a strong spatial genetic structure is confirmed, with higher than average genetic similarities between populations distant from up to 270 km, whereas there is no spatial structure in the roadside plantations in The Netherlands or in the northern German lowlands. These results should help to differentiate introduced from autochthonous populations, and provide a framework for the identification of the geographic origin of seed lots. (C) 2002 Elsevier Science B.V. All rights reserved.

Abstract: The effect of alkaloid extracts from two Amazonian trees (Guatteria ouregou and Simira tinctoria) on low carbon steel corrosion was investigated in acidic solutions by using electrochemical techniques. All of these plant extracts inhibit the corrosion of low carbon steel in 0.1 M HCl solutions. As their concentration increases to 250 mg/L, the inhibition efficiencies of S. tinctoria and G. ouregou alkaloid extracts reach approximately 92% in 0.1 M HCl solutions. The adsorption of the inhibitor molecules was in accordance with the Langmuir adsorption isotherm. The results obtained show that these plant extracts could be serve as an effective inhibitor for the corrosion of low carbon steel in hydrochloric acid media. Furthermore, harmane was identified as the main component of S. tinctoria extract and that suggests that it is the active ingredient against corrosion of low carbon steel. (C) 2010 Elsevier B.V. All rights reserved.