3 resultados para hierarchical Bayesian models
em Publishing Network for Geoscientific
Resumo:
Models and data used to describe species-area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species-area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species-level Poisson processes and estimate patch-level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early-successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species-area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density-area relationships and occurrence probability-area relationships can alter the form of species-area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied to a variety of study designs and allows the inclusion of additional environmental covariates.
Resumo:
We introduce two probabilistic, data-driven models that predict a ship's speed and the situations where a ship is probable to get stuck in ice based on the joint effect of ice features such as the thickness and concentration of level ice, ice ridges, rafted ice, moreover ice compression is considered. To develop the models to datasets were utilized. First, the data from the Automatic Identification System about the performance of a selected ship was used. Second, a numerical ice model HELMI, developed in the Finnish Meteorological Institute, provided information about the ice field. The relations between the ice conditions and ship movements were established using Bayesian learning algorithms. The case study presented in this paper considers a single and unassisted trip of an ice-strengthened bulk carrier between two Finnish ports in the presence of challenging ice conditions, which varied in time and space. The obtained results show good prediction power of the models. This means, on average 80% for predicting the ship's speed within specified bins, and above 90% for predicting cases where a ship may get stuck in ice. We expect this new approach to facilitate the safe and effective route selection problem for ice-covered waters where the ship performance is reflected in the objective function.
Resumo:
Background: Octopods have successfully colonised the world's oceans from the tropics to the poles. Yet, successful persistence in these habitats has required adaptations of their advanced physiological apparatus to compensate impaired oxygen supply. Their oxygen transporter haemocyanin plays a major role in cold tolerance and accordingly has undergone functional modifications to sustain oxygen release at sub-zero temperatures. However, it remains unknown how molecular properties evolved to explain the observed functional adaptations. We thus aimed to assess whether natural selection affected molecular and structural properties of haemocyanin that explains temperature adaptation in octopods. Results: Analysis of 239 partial sequences of the haemocyanin functional units (FU) f and g of 28 octopod species of polar, temperate, subtropical and tropical origin revealed natural selection was acting primarily on charge properties of surface residues. Polar octopods contained haemocyanins with higher net surface charge due to decreased glutamic acid content and higher numbers of basic amino acids. Within the analysed partial sequences, positive selection was present at site 2545, positioned between the active copper binding centre and the FU g surface. At this site, methionine was the dominant amino acid in polar octopods and leucine was dominant in tropical octopods. Sites directly involved in oxygen binding or quaternary interactions were highly conserved within the analysed sequence. Conclusions: This study has provided the first insight into molecular and structural mechanisms that have enabled octopods to sustain oxygen supply from polar to tropical conditions. Our findings imply modulation of oxygen binding via charge-charge interaction at the protein surface, which stabilize quaternary interactions among functional units to reduce detrimental effects of high pH on venous oxygen release. Of the observed partial haemocyanin sequence, residue 2545 formed a close link between the FU g surface and the active centre, suggesting a role as allosteric binding site. The prevalence of methionine at this site in polar octopods, implies regulation of oxygen affinity via increased sensitivity to allosteric metal binding. High sequence conservation of sites directly involved in oxygen binding indicates that functional modifications of octopod haemocyanin rather occur via more subtle mechanisms, as observed in this study.