Éditeur(s) : HAL CCSD Wiley Open Access
Résumé : Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species' threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project - and avert - future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups - including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems - ). We make site-level summary data available alongside this article. The full database will be publicly available in 2015.
ISSN: 2045-7758

hal-01204216
https://hal.archives-ouvertes.fr/hal-01204216
DOI : 10.1002/ece3.1303
PRODINRA : 280886

Éditeur(s) : HAL CCSD Springer Verlag/EDP Sciences
Résumé : Le développement de modèles de dynamique forestière adaptés aux forêts tropicales humides est compliqué par la très grande diversité spécifique caractérisant ces forêts. Les modélisateurs ont souvent eu recours, pour simplifier le problème, à des techniques de regroupement d'espèces. Il existe des méthodes diverses de regroupement, qui relèvent de trois grands types de stratégie : (i) stratégie écologique subjective, (ii) stratégie écologique basée sur l'analyse de données, (iii) stratégie des processus de dynamique populationnelle. Dans le cadre des deux premières stratégies, une espèce est affectée à un groupe et un seul alors que dans le cadre de la troisième, des groupes d'espèces sont définis pour chacun des processus de dynamique (recrutement, croissance, mortalité) pris séparément, et chaque espèce est affectée à trois groupes. Dans la littérature, on trouve peu d'exemples de congruence ou de convergence entre les groupes définis par ces différentes méthodes. Ceci peut être expliqué par l'indépendance existant entre les caractères utilisés pour fabriquer tel ou tel groupe, ou encore par la grande variabilité intra-spécifique de ces caractères. Nous argumentons et concluons sur le fait que le recours à la stratégie des processus de dynamique paraît être la meilleure pour construire des groupes d'espèces adaptés à la prédiction de la dynamique des forêts tropicales.
ISSN: 1286-4560

hal-01032060
https://hal.archives-ouvertes.fr/hal-01032060
DOI : 10.1051/forest:2005084

Éditeur(s) : HAL CCSD European Geosciences Union
Résumé : International audience
The seasonal climate drivers of the carbon cycle in tropical forests remain poorly known, although these forests account for more carbon assimilation and storage than any other terrestrial ecosystem. Based on a unique combination of seasonal pan-tropical data sets from 89 experimental sites (68 include aboveground wood productivity measurements and 35 litter productivity measurements), their associated canopy photosynthetic capacity (enhanced vegetation index, EVI) and climate, we ask how carbon assimilation and aboveground allocation are related to climate seasonality in tropical forests and how they interact in the seasonal carbon cycle. We found that canopy photosynthetic capacity seasonality responds positively to precipitation when rainfall is < 2000 mm yr(-1) (water-limited forests) and to radiation otherwise (light-limited forests). On the other hand, independent of climate limitations, wood productivity and litterfall are driven by seasonal variation in precipitation and evapotranspiration, respectively. Consequently, light-limited forests present an asynchronism between canopy photosynthetic capacity and wood productivity. First-order control by precipitation likely indicates a decrease in tropical forest productivity in a drier climate in water-limited forest, and in current light-limited forest with future rainfall < 2000 mm yr(-1).
ISSN: 1726-4170

hal-01557759
https://hal.univ-lorraine.fr/hal-01557759
https://hal.univ-lorraine.fr/hal-01557759/document
https://hal.univ-lorraine.fr/hal-01557759/file/bg-13-2537-2016.pdf
DOI : 10.5194/bg-13-2537-2016

Éditeur(s) : HAL CCSD Wiley
Résumé : While attention on logging in the tropics has been increasing, studies on the long-term effects of silviculture on forest dynamics and ecology remain scare and spatially limited. Indeed, most of our knowledge on tropical forests arises from studies carried out in undisturbed tropical forests. This bias is problematic given that logged and disturbed tropical forests are now covering a larger area than the so-called primary forests. A new network of permanent sample plots in logged forests, the Tropical managed Forests Observatory (TmFO), aims to fill this gap by providing unprecedented opportunities to examine long-term data on the resilience of logged tropical forests at regional and global scales. TmFO currently includes 24 experimental sites distributed across three tropical regions, with a total of 490 permanent plots and 921ha of forest inventories.
ISSN: 1402-2001

hal-01204230
https://hal.archives-ouvertes.fr/hal-01204230
DOI : 10.1111/avsc.12125
PRODINRA : 323838