Search

International audience; Building predictive maps of assemblage habitat, a widely used method in conservation and landscape management, is based on fitting habitat model on a training area, corresponding to a limited region in the environmental space. Model predictive performances need to be robustly evaluated on test data set. This is often realized at the landscape level, i.e taking as test data set one part of the original sample or a resampling one. Predicting assemblage occurrences at a regional level requires a step further in the modelling validation stage: testing model extrapolation performances. We estimated and compared the predictive performances of two scales of predictive mapping of small mammals assemblages in a remote area of Sichuan province. Small mammal assemblages were defined in two distant areas and differed between both areas. Their habitats were modelled, predicted and mapped using ETM bands at two different spatial scales: local (in each area) versus regional (including both areas). While locally trained models provided large predictive errors on independent data sets, the regionally trained model more accurately predicted assemblage occurrences and could be considered at this state of the research as an appropriate method to map assemblage regionally.

International audience; Biological mechanisms known to affect space-time dynamics of infectious diseases may be impacted by ecosystem change and the last 50 years have seen the greatest changes in ecosystem structure and function in human history (Patz and Confalonieri 2005). Alveolar echinococcosis (AE) is a disease lethal to humans caused by a Cestod parasite. The parasite is transmitted through a life-cycle including small mammal intermediate hosts (rodents and lagomorphs) and carnivore definitive hosts, mostly foxes and domestic dogs. Over the last 15 years it appears that the parasite has spread its geographic range in the red fox populations of western and eastern Europe and large foci of AE have been discovered in Western China at the Eastern border of the Tibetan plateau. Transmission systems have been studied in eastern France and Western China combining quantified analysis of landscape changes, small mammal communities and AE prevalence in humans and foxes (Giraudoux et al. 2002; Giraudoux et al. 2006). Evidence has been provided that at the regional scale landscape can affect human disease distribution through interaction with small mammal communities and their population dynamics. Regional models have been proposed where satellite imagery was used to describe landscapes and evaluate transmission risk. Here we review those studies and discuss their results with perspectives for studies of pathogenic organism transmission grounded on systems approach and landscape ecology concepts.

International audience; The Llanos de Ojuelos is an extensive llanura at the southern end of the Chihuahuan Desert. The original composition of the land is mostly grasslands, with interspread shrublands, and small water bodies. Currently, 80% of the area is used for crop production and/or grazing of livestock. As a result, natural habitats have been severely fragmented, and the overall biodiversity affected to an unknown degree. The present work aims at understanding the relationship between rodent assemblages and different types of habitat patches to integrate a landscape approach of small mammal diversity. In the spring of 2008 we inventoried the rodents at 74 locations in the area, through the use of Sherman live-traps (40 traps during two nights, per site; total=5920 night-traps). We covered the major perennial vegetation types. We captured 458 individuals of 20 species of rodents (Perognathus flavus, Chaetodipus hispidus, Chaetodipus nelsoni, C. pennicillatus, Dipodomys ordii, D. merriami, D. phillipsii, Liomys irroratus, Peromyscus boylii, P. difficilis, P. eremicus, P. gratus, P. maniculatus, P. melanophrys, Reithrodontomys fulvescens, R. megalotis, Baiomys taylori, Neotoma goldmani, N. leucodoni, and Onychomys arenarius). We defined a priori 11 rodent habitat categories based on the cover, structure and dominant plant species. Species presence/absences were modeled jointly through a multinomial model, and then used to pool habitats by merging all habitat classes pair-wise and selecting the most parsimonious model by the Akaike Information Criterion for each iteration. This produced 7 habitat classes: Closed arboreal nopalera, mixed nopalera, grassland, leguminous scrubland, Dodonaea scrubland, cultivated nopalera, and oak scrub. Rodent communities analyzed have low levels of organization, with most species thriving in a variety of conditions, although some of them exhibited a certain habitat preference. Communities were distributed according to a gradient from "low open vegetation" to "dense tall vegetation," with fuzzy borders between them. The highest rodent richness was in nopaleras; mid richness, in leguminous scrub communities, and lower richness, in grasslands. This might have resulted from differences in habitat structure and within-habitat heterogeneity. Habitat types seemed also to be structured differently. We are exploring models employing reflectance data to classify satellite images according to habitat classes and to analyze their spatial relationship. Given the patchiness and the low organization level of the communities, biological conservation cannot be carried out in homogeneous areas, but must consider the entire landscape

International audience; Although Mexico's central arid and semiarid lands face numerous conservation problems, they have largely been neglected from conservation, despite their apparent biological importance. We studied the semiarid Llanos de Ojuelos, where the original plant communities of grasslands, shrublands, and patches of oaks have been modified strongly by cattle grazing and for cultivation, affecting animal populations and communities, as well as the landscape-level ecological dynamics. Very little about the populations of wild animals in the area and the processes underlying their distribution and dynamics is known. We focused on whether satellite information was useful to explain rodent distributions and abundances in this area with a complex landscape of diffuse plant communities. In the spring of 2008 we inventoried the rodents at 74 locations in the area, through the use of Sherman live-traps (40 traps during two nights, per site; total=5920 night-traps). We covered the major perennial vegetation types. The existence of a complex landscape of intergrading grasslands, Opuntia comunities and shrublands (dominated by Acacia, Mimosa, Dodonaea, and Quercus) of different types and composition creates rich habitat mosaic that promotes a rich rodent fauna. We captured 20 species of rodents (458 individuals), while richness was estimated at 21-25 species. Reithrodontomys fulvescens, Chaetodipus nelsoni, Dipodomys phillipsii, Peromyscus melanophrys, Peromyscus gratus, and Peromyscus difficilis were very common at our sites, while Chaetodipus pennicillatus, Liomys irroratus, Perognathus flavus, Dipodomys merriami, Reithrodontomys megalotis, Peromyscus boylii, Neotoma leucodon, Peromyscus eremicus, Dipodomys ordii, and Peromyscus manicultatus were common, and Neotoma goldmani, Chaetodipus hispidus, Onychomys arenarius, and Baiomys taylori were rare. To explore the value of satellite information to understand and predict the rodents' distributions, we derived reflectance data from all bands of a Landsat5 TM Image (5 March 2008) for each trapline's midpoint. We will compare each rodent species' abundance with this data as well as with the normalized difference vegetation index (NDVI) and tasseled cap transformations (TCs: brightness, greenness, and wetness). We will link rodent presence/absences to reflectance values through linear and non-linear discriminant analysis, as well as through general linear models and multiple adaptive regression splines. Satellite images classified following the best models will then be interpreted according to field expertise. As end results we expect to have a better understanding on the rodent species' ecology, an adequate image classification procedure, and potential distribution maps for the rodent species in the study area.

Methodology applied is the first of its kind in Croatia and has a potential to form the basis for the sustainable management of natural resources and protection of biodiversity and landscape protection.