Hierarchic species-area relationships and the management of forest habitat islands in intensive farmland

Habitat loss and fragmentation due to land use changes are major threats to biodiversity in forest ecosystems, and they are expected to have important impacts on many taxa and at various spatial scales. Species richness and area relationships (SARs) have been used to assess species diversity patterns and drivers, and thereby in the establishment of conservation and management strategies. Here we propose a hierarchical approach to achieve deeper insights on SARs in small forest islets in intensive farmland and to address the impacts of decreasing naturalness on such relationships. In the intensive dairy landscapes of Northwest Portugal, where small forest stands (dominated by pines, eucalypts or both) represent semi-natural habitat islands, 50 small forest stands were selected and surveyed for vascular plant diversity. A hierarchical analytical framework was devised to determine species richness and inter- and intra-patch SARs for the whole set of forest patches (general patterns) and for each type of forest (specific patterns). Differences in SARs for distinct groups were also tested by considering subsets of species (native, alien, woody, and herbaceous). Overall, values for species richness were confirmed to be different between forest patches exhibiting different levels of naturalness. Whereas higher values of plant diversity were found in pine stands, higher values for alien species were observed in eucalypt stands. Total area of forest (inter-patch SAR) was found not to have a significant impact on species richness for any of the targeted groups of species. However, significant intra-patch SARs were obtained for all groups of species and forest types. A hierarchical approach was successfully applied to scrutinise SARs along a gradient of forest naturalness in intensively managed landscapes. Dominant canopy tree and management intensity were found to reflect differently on distinct species groups as well as to compensate for increasing stand area, buffering SARs among patches, but not within patches. Thus, the maintenance of small semi-natural patches dominated by pines, under extensive practices of forest management, will promote native plant diversity while at the same time contributing to limit the expansion of problematic alien invasive species.

Statistical discrimination of steroid profiles in doping control with support vector machines.

Due to their performance enhancing properties, use of anabolic steroids (e.g. testosterone, nandrolone, etc.) is banned in elite sports. Therefore, doping control laboratories accredited by the World Anti-Doping Agency (WADA) screen among others for these prohibited substances in urine. It is particularly challenging to detect misuse with naturally occurring anabolic steroids such as testosterone (T), which is a popular ergogenic agent in sports and society. To screen for misuse with these compounds, drug testing laboratories monitor the urinary concentrations of endogenous steroid metabolites and their ratios, which constitute the steroid profile and compare them with reference ranges to detect unnaturally high values. However, the interpretation of the steroid profile is difficult due to large inter-individual variances, various confounding factors and different endogenous steroids marketed that influence the steroid profile in various ways. A support vector machine (SVM) algorithm was developed to statistically evaluate urinary steroid profiles composed of an extended range of steroid profile metabolites. This model makes the interpretation of the analytical data in the quest for deviating steroid profiles feasible and shows its versatility towards different kinds of misused endogenous steroids. The SVM model outperforms the current biomarkers with respect to detection sensitivity and accuracy, particularly when it is coupled to individual data as stored in the Athlete Biological Passport.

Shifts in species and phylogenetic diversity between sapling and tree communities indicate negative density dependence in a lowland rain forest

1. As trees in a given cohort progress through ontogeny, many individuals die. This risk of mortality is unevenly distributed across species because of many processes such as habitat filtering, interspecific competition and negative density dependence. Here, we predict and test the patterns that such ecological processes should inscribe on both species and phylogenetic diversity as plants recruit from saplings to the canopy. 2. We compared species and phylogenetic diversity of sapling and tree communities at two sites in French Guiana. We surveyed 2084 adult trees in four 1-ha tree plots and 943 saplings in sixteen 16-m2 subplots nested within the tree plots. Species diversity was measured using Fisher's alpha (species richness) and Simpson's index (species evenness). Phylogenetic diversity was measured using Faith's phylogenetic diversity (phylogenetic richness) and Rao's quadratic entropy index (phylogenetic evenness). The phylogenetic diversity indices were inferred using four phylogenetic hypotheses: two based on rbcLa plastid DNA sequences obtained from the inventoried individuals with different branch lengths, a global phylogeny available from the Angiosperm Phylogeny Group, and a combination of both. 3. Taxonomic identification of the saplings was performed by combining morphological and DNA barcoding techniques using three plant DNA barcodes (psbA-trnH, rpoC1 and rbcLa). DNA barcoding enabled us to increase species assignment and to assign unidentified saplings to molecular operational taxonomic units. 4. Species richness was similar between saplings and trees, but in about half of our comparisons, species evenness was higher in trees than in saplings. This suggests that negative density dependence plays an important role during the sapling-to-tree transition. 5. Phylogenetic richness increased between saplings and trees in about half of the comparisons. Phylogenetic evenness increased significantly between saplings and trees in a few cases (4 out of 16) and only with the most resolved phylogeny. These results suggest that negative density dependence operates largely independently of the phylogenetic structure of communities. 6. Synthesis. By contrasting species richness and evenness across size classes, we suggest that negative density dependence drives shifts in composition during the sapling-to-tree transition. In addition, we found little evidence for a change in phylogenetic diversity across age classes, suggesting that the observed patterns are not phylogenetically constrained.

Detection of Optimal Models in Parameter Space with Support Vector Machines

The paper proposes an approach aimed at detecting optimal model parameter combinations to achieve the most representative description of uncertainty in the model performance. A classification problem is posed to find the regions of good fitting models according to the values of a cost function. Support Vector Machine (SVM) classification in the parameter space is applied to decide if a forward model simulation is to be computed for a particular generated model. SVM is particularly designed to tackle classification problems in high-dimensional space in a non-parametric and non-linear way. SVM decision boundaries determine the regions that are subject to the largest uncertainty in the cost function classification, and, therefore, provide guidelines for further iterative exploration of the model space. The proposed approach is illustrated by a synthetic example of fluid flow through porous media, which features highly variable response due to the parameter values' combination.

Thermal energetics of the New-Guinean moss-forest rat (Rattus niobe) in comparison with other tropical murid rodents.

The thermal energetics of rodents from cool, wet tropical highlands are poorly known. Metabolic rate, body temperature and thermal conductance were measured in the moss-forest rat, Rattus niobe (Rodentia), a small murid endemic to the highlands of New Guinea. These data were evaluated in the context of the variation observed in the genus Rattus and among tropical murids. In 7 adult R. niobe, basal metabolic rate (BMR) averaged 53.6±6.6mLO2h(-1), or 103% of the value predicted for a body mass of 42.3±5.8g. Compared to other species of Rattus, R. niobe combines a low body temperature (35.5±0.6°C) and a moderately low minimal wet thermal conductance cmin (5.88±0.7mLO2h(-1)°C(-1), 95% of predicted) with a small size, all of which lead to reduced energy expenditure in a constantly cool environment. The correlations of mean annual rainfall and temperature, altitude and body mass with BMR, body temperature and cmin were analyzed comparatively among tropical Muridae. Neither BMR, nor cmin or body temperature correlated with ambient temperature or altitude. Some of the factors which promote high BMR in higher latitude habitats, such as seasonal exposure to very low temperature and short reproductive season, are lacking in wet montane tropical forests. BMR increased with rainfall, confirming a pattern observed among other assemblages of mammals. This correlation was due to the low BMR of several desert adapted murids, while R. niobe and other species from wet habitats had a moderate BMR.

Molecular machines governing exocytosis of synaptic vesicles.

Calcium-dependent exocytosis of synaptic vesicles mediates the release of neurotransmitters. Important proteins in this process have been identified such as the SNAREs, synaptotagmins, complexins, Munc18 and Munc13. Structural and functional studies have yielded a wealth of information about the physiological role of these proteins. However, it has been surprisingly difficult to arrive at a unified picture of the molecular sequence of events from vesicle docking to calcium-triggered membrane fusion. Using mainly a biochemical and biophysical perspective, we briefly survey the molecular mechanisms in an attempt to functionally integrate the key proteins into the emerging picture of the neuronal fusion machine.

Improving generalized regression analysis for the spatial prediction of forest communities

Aim This study used data from temperate forest communities to assess: (1) five different stepwise selection methods with generalized additive models, (2) the effect of weighting absences to ensure a prevalence of 0.5, (3) the effect of limiting absences beyond the environmental envelope defined by presences, (4) four different methods for incorporating spatial autocorrelation, and (5) the effect of integrating an interaction factor defined by a regression tree on the residuals of an initial environmental model. Location State of Vaud, western Switzerland. Methods Generalized additive models (GAMs) were fitted using the grasp package (generalized regression analysis and spatial predictions, http://www.cscf.ch/grasp). Results Model selection based on cross-validation appeared to be the best compromise between model stability and performance (parsimony) among the five methods tested. Weighting absences returned models that perform better than models fitted with the original sample prevalence. This appeared to be mainly due to the impact of very low prevalence values on evaluation statistics. Removing zeroes beyond the range of presences on main environmental gradients changed the set of selected predictors, and potentially their response curve shape. Moreover, removing zeroes slightly improved model performance and stability when compared with the baseline model on the same data set. Incorporating a spatial trend predictor improved model performance and stability significantly. Even better models were obtained when including local spatial autocorrelation. A novel approach to include interactions proved to be an efficient way to account for interactions between all predictors at once. Main conclusions Models and spatial predictions of 18 forest communities were significantly improved by using either: (1) cross-validation as a model selection method, (2) weighted absences, (3) limited absences, (4) predictors accounting for spatial autocorrelation, or (5) a factor variable accounting for interactions between all predictors. The final choice of model strategy should depend on the nature of the available data and the specific study aims. Statistical evaluation is useful in searching for the best modelling practice. However, one should not neglect to consider the shapes and interpretability of response curves, as well as the resulting spatial predictions in the final assessment.

State power and protected areas: Dynamics and contradictions of forest conservation in Madhya Pradesh, India

The traditionally coercive and state-controlled governance of protected areas for nature conservation in developing countries has in many cases undergone change in the context of widespread decentralization and liberalization. This article examines an emerging "mixed" (coercive, community- and market-oriented) conservation approach in managed-resource protected areas and its effects on state power through a case study on forest protection in the central Indian state of Madhya Pradesh. The findings suggest that imperfect decentralization and partial liberalization resulted in changed forms, rather than uniform loss, of state power. A forest co-management program paradoxically strengthened local capacity and influence of the Forest Department, which generally maintained its territorial and knowledge-based control over forests and timber management. Furthermore, deregulation and reregulation enabled the state to withdraw from uneconomic activities but also implied reduced place-based control of non-timber forest products. Generally, the new policies and programs contributed to the separation of livelihoods and forests in Madhya Pradesh. The article concludes that regulatory, community- and market-based initiatives would need to be better coordinated to lead to more effective nature conservation and positive livelihood outcomes.

Old ferricrete landscape dismantling in Central Africa rain forest zone: formation of the present downslope iron accumulations.

Present downslope iron accumulations were investigated in the rainforest zone in southern Cameroon. Six clay and Fe-hydroxide dominated patterns have been identified and occur on the lower part of hill slopes. They can be subdivided in three different sequences, related to gentle, moderate or steep slopes. They are discontinuous with respect to the dismantling zone of the old ferricrete cap formed at Cretaceous period. They show a gradual development from a soft Fe-crust (carapace) to a vesicular facies that will, with time, cover the whole landscape again.