22 resultados para Clark-Wilson model
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:
The remote South Sandwich arc is an archipelago of small volcanic islands and seamounts entirely surrounded by deep water and about 600 km away from the closest island, South Georgia. As some of the youngest islands (< 5 m.y.) in the Southern Ocean they are ideal for studying colonization processes of the seabed by benthic fauna, but are rarely investigated because of remoteness and extreme weather. The current study attempted to quantify the richness and abundance of the epibenthic macrofauna around the Southern Thule group by taking five epibenthic sledge samples along a depth transect including three shelf (one at 300 m and two at 500 m) and two slope stations (1000 and 1500 m). Our aim was to investigate higher taxon richness and community composition in an isolated Antarctic locality, since recent volcanic eruptions between 1964 and 1997. We examined patterns across all epibenthic macrofauna at phylum and class levels, and investigated trends in some model groups of crustaceans to order and family level. We found that abundance was highest in the shallowest sample and decreased with depth. Shelf samples (300 and 500 m) were dominated by molluscs and malacostracans while at the deeper stations (1000 and 1500 m) nematodes were the most abundant taxon. Surprisingly, the shallow shelf was dominated by animals with restricted dispersal abilities, such as direct developing brooders (malacostracans) or those with lecithotrophic larvae (bivalves of the genus Yoldiella, most bryozoan species). Despite Southern Thule's geological youth, recent eruptions, and its remoteness the shallow shelf was rich in higher taxa (phyla/classes) as well as orders and families of our model groups. Future work at higher taxonomic resolution (species level) should greatly increase understanding of how life has reached and established on these young and highly disturbed seabeds.
Resumo:
Greenland ice core records indicate that the last deglaciation (~7-21 ka) was punctuated by numerous abrupt climate reversals involving temperature changes of up to 5°C-10°C within decades. However, the cause behind many of these events is uncertain. A likely candidate may have been the input of deglacial meltwater, from the Laurentide ice sheet (LIS), to the high-latitude North Atlantic, which disrupted ocean circulation and triggered cooling. Yet the direct evidence of meltwater input for many of these events has so far remained undetected. In this study, we use the geochemistry (paired Mg/Ca-d18O) of planktonic foraminifera from a sediment core south of Iceland to reconstruct the input of freshwater to the northern North Atlantic during abrupt deglacial climate change. Our record can be placed on the same timescale as ice cores and therefore provides a direct comparison between the timing of freshwater input and climate variability. Meltwater events coincide with the onset of numerous cold intervals, including the Older Dryas (14.0 ka), two events during the Allerød (at ~13.1 and 13.6 ka), the Younger Dryas (12.9 ka), and the 8.2 ka event, supporting a causal link between these abrupt climate changes and meltwater input. During the Bølling-Allerød warm interval, we find that periods of warming are associated with an increased meltwater flux to the northern North Atlantic, which in turn induces abrupt cooling, a cessation in meltwater input, and eventual climate recovery. This implies that feedback between climate and meltwater input produced a highly variable climate. A comparison to published data sets suggests that this feedback likely included fluctuations in the southern margin of the LIS causing rerouting of LIS meltwater between southern and eastern drainage outlets, as proposed by Clark et al. (2001, doi:10.1126/science.1062517).