2 resultados para CANCER CURRENT STATUS
em Publishing Network for Geoscientific
Resumo:
Documenting changes in distribution is necessary for understanding species' response to environmental changes, but data on species distributions are heterogeneous in accuracy and resolution. Combining different data sources and methodological approaches can fill gaps in knowledge about the dynamic processes driving changes in species-rich, but data-poor regions. We combined recent bird survey data from the Neotropical Biodiversity Mapping Initiative (NeoMaps) with historical distribution records to estimate potential changes in the distribution of eight species of Amazon parrots in Venezuela. Using environmental covariates and presence-only data from museum collections and the literature, we first used maximum likelihood to fit a species distribution model (SDM) estimating a historical maximum probability of occurrence for each species. We then used recent, NeoMaps survey data to build single-season occupancy models (OM) with the same environmental covariates, as well as with time- and effort-dependent detectability, resulting in estimates of the current probability of occurrence. We finally calculated the disagreement between predictions as a matrix of probability of change in the state of occurrence. Our results suggested negative changes for the only restricted, threatened species, Amazona barbadensis, which has been independently confirmed with field studies. Two of the three remaining widespread species that were detected, Amazona amazonica, Amazona ochrocephala, also had a high probability of negative changes in northern Venezuela, but results were not conclusive for Amazona farinosa. The four remaining species were undetected in recent field surveys; three of these were most probably absent from the survey locations (Amazona autumnalis, Amazona mercenaria and Amazona festiva), while a fourth (Amazona dufresniana) requires more intensive targeted sampling to estimate its current status. Our approach is unique in taking full advantage of available, but limited data, and in detecting a high probability of change even for rare and patchily-distributed species. However, it is presently limited to species meeting the strong assumptions required for maximum-likelihood estimation with presence-only data, including very high detectability and representative sampling of its historical distribution.
Resumo:
Historical, i.e. pre-1957, upper-air data are a valuable source of information on the state of the atmosphere, in some parts of the World back to the early 20th century. However, to date reanalyses have only partially made use of these data, and only of observations made after 1948. Even for the period between 1948 (the starting year of the NCEP/NCAR reanalysis) and the International Geophysical Year in 1957 (the starting year of the ERA-40 reanalysis), when the global upper-air coverage reached more or less its current status, many observations have not been digitised until now. The Comprehensive Historical Upper-Air Network (CHUAN) already compiled a large collection of pre-1957 upper-air data. In the framework of the European project ERA-CLIM, significant amounts of additional upper-air data have been catalogued (> 1.3 mio station days), imaged (> 200,000 images) and digitised (> 700,000 station days) in order to prepare a new input dataset for upcoming reanalyses. The records cover large parts of the globe, focussing on so far less well covered regions such as the Tropics, the polar regions and the Oceans, and on very early upper-air data from Europe and the US. The total number of digitised/inventoried records is 61/101 for moving upper-air data, i.e. data from ships etc., and 735/1,783 for fixed upper-air stations. Here, we give a detailed description of the resulting dataset including the metadata and the quality checking procedures applied. The data will be included in the next version of CHUAN.