61 resultados para multisouce forest inventory
Resumo:
Two endangered tetraonids, the capercaillie (Tetrao urogallus) and the hazel grouse (Bonasa bonasia rupestris), are sympatric throughout part of their distribution range in central Europe. Precise information on their specific habitat requirements is needed if the coexistence of both species in exploited forests is to be maintained. We quantified winter habitat selection for both species in the upper part (1100-1600 m) of the Jura mountains (Switzerland). No preference for altitude or exposure could be detected. Capercaillie preferred open forests (including grazed forests) with a sparse canopy dominated by spruce (Picea abies) and fir (Abies alba), and avoided dense undercanopy and understorey, especially when dominated by spruce and beech (Fagus sylvatica). By contrast, hazel grouse preferred feeding sites with a dense understorey of rowan (Sorbus aucuparia), willow (Salix sp.), beech and spruce. These preferences can be related to the feeding habits and predator avoidance behaviour of both species. Coexistence thus requires a mosaic distribution of habitat types, with a matrix of open forests (30% canopy cover) where fir is favoured, and understorey kept sparse (20%). Group-cuts of mature trees should allow regeneration patches, where a dense understorey (50% cover) should provide suitable habitats for hazel grouse
Resumo:
OBJECTIVE: To describe chronic disease management programs active in Switzerland in 2007, using an exploratory survey. METHODS: We searched the internet (Swiss official websites and Swiss web-pages, using Google), a medical electronic database (Medline), reference lists of pertinent articles, and contacted key informants. Programs met our operational definition of chronic disease management if their interventions targeted a chronic disease, included a multidisciplinary team (>/=2 healthcare professionals), lasted at least six months, and had already been implemented and were active in December 2007. We developed an extraction grid and collected data pertaining to eight domains (patient population, intervention recipient, intervention content, delivery personnel, method of communication, intensity and complexity, environment, clinical outcomes). RESULTS: We identified seven programs fulfilling our operational definition of chronic disease management. Programs targeted patients with diabetes, hypertension, heart failure, obesity, psychosis and breast cancer. Interventions were multifaceted; all included education and half considered planned follow-ups. The recipients of the interventions were patients, and healthcare professionals involved were physicians, nurses, social workers, psychologists and case managers of various backgrounds. CONCLUSIONS: In Switzerland, a country with universal healthcare insurance coverage and little incentive to develop new healthcare strategies, chronic disease management programs are scarce. For future developments, appropriate evaluations of existing programs, involvement of all healthcare stakeholders, strong leadership and political will are, at least, desirable.
Resumo:
Forest fire sequences can be modelled as a stochastic point process where events are characterized by their spatial locations and occurrence in time. Cluster analysis permits the detection of the space/time pattern distribution of forest fires. These analyses are useful to assist fire-managers in identifying risk areas, implementing preventive measures and conducting strategies for an efficient distribution of the firefighting resources. This paper aims to identify hot spots in forest fire sequences by means of the space-time scan statistics permutation model (STSSP) and a geographical information system (GIS) for data and results visualization. The scan statistical methodology uses a scanning window, which moves across space and time, detecting local excesses of events in specific areas over a certain period of time. Finally, the statistical significance of each cluster is evaluated through Monte Carlo hypothesis testing. The case study is the forest fires registered by the Forest Service in Canton Ticino (Switzerland) from 1969 to 2008. This dataset consists of geo-referenced single events including the location of the ignition points and additional information. The data were aggregated into three sub-periods (considering important preventive legal dispositions) and two main ignition-causes (lightning and anthropogenic causes). Results revealed that forest fire events in Ticino are mainly clustered in the southern region where most of the population is settled. Our analysis uncovered local hot spots arising from extemporaneous arson activities. Results regarding the naturally-caused fires (lightning fires) disclosed two clusters detected in the northern mountainous area.
Resumo:
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.
Resumo:
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.
Resumo:
BACKGROUND: Peer pressure is regarded as an important determinant of substance use, sexual behavior and juvenile delinquency. However, few peer pressure scales are validated, especially in French or German. Little is known about the factor structure of such scales or the kind of scale needed: some scales takes into account both peer pressure to do and peer pressure not to do, while others consider only peer pressure to do. The aim of the present study was to adapt French and German versions of the Peer Pressure Inventory, which is one of the most widely used scales in this field. We considered its factor structure and concurrent validity. METHODS: Five thousand eight hundred and sixty-seven young Swiss men filled in a questionnaire on peer pressure, substance use, and other variables (conformity, involvement) in a cohort study. RESULTS: We identified a four-factor structure, with the three factors of the initial Peer Pressure Inventory (involvement, conformity, misconduct) and adding a new one (relationship with girls). A non-valued scale (from no peer pressure to peer pressure to do only) showed stronger psychometric qualities than a valued scale (from peer pressure not to do to peer pressure to do). Concurrent validity was also good. Each behavior or attitude was significantly associated with peer pressure. CONCLUSION: Peer pressure seems to be a multidimensional concept. In this study, peer pressure to do showed the strongest influence on participants. Indeed, peer pressure not to do did not add anything useful. Only peer pressure to do affected young Swiss men's behaviors and attitudes and was reliable.
Resumo:
This article presents the Antenatal Perceived Stress Inventory. The originality of this scale is to assess the impact of events experienced during pregnancy on the stress perceived by mothers. Scale validation was performed using data from 150 French-speaking nulliparous mothers and collected between 36 and 39 weeks of gestation (T1), and between 2 days (T2) and 6 weeks postpartum (T3). Factor analysis revealed a hierarchical three-factor structure that closely fit the data, including medical and obstetric risks/fetal health (F1), psychosocial changes (F2), and the prospect of childbirth (F3). The Antenatal Perceived Stress Inventory is a valid French prenatal stress scale with good psychometric properties.
Resumo:
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.
Resumo:
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.
Resumo:
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.