Forest fires cluster detection with space-time scan statistics

Forest fires are defined as uncontrolled fires often occurring in wildland areas, but that can also affect houses or agricultural resources. Causes are both natural (e.g.,lightning phenomena) and anthropogenic (human negligence or arsons).Major environmental factors influencing the fire ignition and propagation are climate and vegetation. Wildfires are most common and severe during drought period and on windy days. Moreover, under water-stress conditions, which occur after a long hot and dry period, the vegetation is more vulnerable to fire. These conditions are common in the United State and Canada, where forest fires represent a big problem. We focused our analysis on the state of Florida, for which a big dataset on forest fires detection is readily available. USDA Forest Service Remote Sensing Application Center, in collaboration with NASA-Goddard Space Flight Center and the University of Maryland, has compiled daily MODIS Thermal Anomalies (fires and biomass burning images) produced by NASA using a contextual algorithm that exploits the strong emission of mid-infrared radiation from fires. Fire classes were converted in GIS format: daily MODIS fire detections are provided as the centroids of the 1 kilometer pixels and compiled into daily Arc/INFO point coverage.

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.

ESCMID postgraduate technical workshop on intracellular bacteria: from biology to clinic.

Infection by intracellular bacteria can lead to several diseases in both veterinary and human medicine. Unfortunately, the biology of these intracellular bacteria is highly complex due to their interactions with their host cells. Thus, it is very important to develop several tools in order to better understand the complex intracellular life of these pathogens, so allowing to improve the diagnosis options and the treatments of infectious diseases that they are causing. The workshop organised in Villars-sur-Ollon (Switzerland) by the ESCMID Study group on intracellular bacteria was a good opportunity to enhance our knowledge on these fastidious pathogens. During 5 days, 15 speakers gave 41 talks, covering all fields, from biology to clinic of different intracellular bacteria such as Bartonella, Chlamydia, Coxiella, Ehrlichia, Listeria, Parachlamydia, Rickettsia, and Waddlia. The format of this postgraduate course, which took place in the Swiss mountains, allowed interactive sessions and living discussions between the participants coming from all around the world. One of the major strength was to gather epidemiologists, clinical microbiologists, infectious diseases specialists, entomologists, veterinarians as well as bioinformaticians, biochemists and biologists to deliver a unique "one-health science" on intracellular bacteria. Here, we summarise the main take-home messages delivered during this meeting.

Hémato-oncologie pédiatrique: de la biologie cellulaire aux traitements ciblés et individualisés [Pediatric hemato-oncology: from cellular biology to individualized targeted therapies].

Progresses in pediatric oncology over the last decades have been dramatic and allow current cure rates above 80%. There are mainly due to multicentre clinical trials aiming at optimizing chemotherapy protocols as well as local therapies in a stepwise approach. Most of the new anticancer drugs currently in development are based on targeted therapies, directed to specific targets present only in or on tumor cells, like growth factor receptors, mechanisms involved in proliferation, DNA repair, apoptosis, tumor invasion or angiogenesis. Concerning bone marrow transplantation also, new strategic approaches are in advanced development. They aim at reducing treatment induced toxicity and enhancing efficacy at the same time. This short paper would like to point out these new technologies, which should be known by the general practitioner.

FIB-SEM tomography in biology.

Three-dimensional information is much easier to understand than a set of two-dimensional images. Therefore a layman is thrilled by the pseudo-3D image taken in a scanning electron microscope (SEM) while, when seeing a transmission electron micrograph, his imagination is challenged. First approaches to gain insight in the third dimension were to make serial microtome sections of a region of interest (ROI) and then building a model of the object. Serial microtome sectioning is a tedious and skill-demanding work and therefore seldom done. In the last two decades with the increase of computer power, sophisticated display options, and the development of new instruments, an SEM with a built-in microtome as well as a focused ion beam scanning electron microscope (FIB-SEM), serial sectioning, and 3D analysis has become far easier and faster.Due to the relief like topology of the microtome trimmed block face of resin-embedded tissue, the ROI can be searched in the secondary electron mode, and at the selected spot, the ROI is prepared with the ion beam for 3D analysis. For FIB-SEM tomography, a thin slice is removed with the ion beam and the newly exposed face is imaged with the electron beam, usually by recording the backscattered electrons. The process, also called "slice and view," is repeated until the desired volume is imaged.As FIB-SEM allows 3D imaging of biological fine structure at high resolution of only small volumes, it is crucial to perform slice and view at carefully selected spots. Finding the region of interest is therefore a prerequisite for meaningful imaging. Thin layer plastification of biofilms offers direct access to the original sample surface and allows the selection of an ROI for site-specific FIB-SEM tomography just by its pronounced topographic features.

HER2 shedding and serum HER2 extracellular domain: Biology and clinical utility in breast cancer.

The transmembrane protein HER2 is over-expressed in approximately 15% of invasive breast cancers as a result of HER2 gene amplification. HER2 proteolytic cleavage (HER2 shedding) generates soluble truncated HER2 molecules that include only the extracellular domain and the concentration of which can be measured in the serum fraction of blood. HER2 shedding also generates a constitutively active truncated intracellular receptor of 95kDa (p95(HER2)). Another soluble truncated HER2 protein (Herstatin), which can also be found in serum, is the product of an alternatively spliced HER2 transcript. Recent preclinical findings may provide crucial insights into the biological and clinical relevance of increased sHER2 concentrations for the outcome of HER2-positive breast cancer and sensitivity to trastuzumab and lapatinib treatment. We present here the most recent findings about the role and biology of sHER2 based on data obtained using a standardized test, which has been cleared by FDA in 2000, for measuring sHER2. This test includes quality control assessments and has been already widely used to evaluate the clinical utility of sHER2 as a biomarker in breast cancer. We will describe in detail data concerning the assessment of sHER2 as a surrogate maker to optimize the evaluation of the HER2 status of a primary tumor and as a prognosis and predictive marker of response to therapies, both in early and metastatic breast cancer.

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.

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.