7 resultados para Probit estimations

em Plymouth Marine Science Electronic Archive (PlyMSEA)


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The performance of four common estimators of diversity are investigated using calanoid copepod data from the Continuous Plankton Recorder (CPR) survey. The region of the North Atlantic and the North Sea was divided into squares of 400 nautical miles for each 2-month period. For each 144 possible cases, Pielou's pooled quadrat method was performed with the aims of determining asymptotic diversity and investigating the CPR sample-size dependence of diversity estimators. It is shown that the performance of diversity indices may greatly vary in space and time (at a seasonal scale). This dependence is more pronounced in higher diverse environments and when the sample size is small. Despite results showing that all estimators underestimate the `actual' diversity, comparison of sites remained reliable from a few pooled CPR samples. Using more than one CPR sample, the Gini coefficient appears to be a better diversity estimator than any other indices and spatial or temporal comparisons are highly satisfactory. In situations where comparative studies are needed but only one CPR sample is available, taxonomic richness was the preferred method of estimating diversity. Recommendations are proposed to maximise the efficiency of diversity estimations with the CPR data.

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The distribution of dissolved, soluble and colloidal fractions of Al and Ti was assessed by ultrafiltration studies in the upper water column of the eastern tropical North Atlantic. The dissolved fractions of both metals were found to be dominated by the soluble phase smaller than 10 kDa. The colloidal associations were very low (0.2–3.4%) for Al and not detectable for Ti. These findings are in some contrast to previous estimations for Ti and to the predominant occurrence of both metals as hydrolyzed species in seawater. However, low tendencies to form inorganic colloids can be expected, as in seawater dissolved Al and dissolved Ti are present within their inorganic solubility levels. In addition, association with functional organic groups in the colloidal phase is unlikely for both metals. Vertical distributions of the dissolved fractions showed surface maxima with up to 43 nM of Al and 157 pM of Ti, reflecting their predominant supply from atmospheric sources to the open ocean. In the surface waters, excess dissolved Al over dissolved Ti was present compared to the crustal source, indicating higher solubility and thus elevated inputs of dissolved Al from atmospheric mineral particles. At most stations, subsurface minima of Al and Ti were observed and can be ascribed to scavenging processes and/or biological uptake. The dissolved Al concentrations decreased by 80–90% from the surface maximum to the subsurface minimum. Estimated residence times in the upper 100 m of the water column ranged between 1.6 and 4 years for dissolved Al and between 14 and 17 years for dissolved Ti. The short residence times are in some contrast to the low colloidal associations of Al and Ti and the assumed role of colloids as intermediates in scavenging processes. This suggests that either the removal of both metals occurs predominantly via direct transfer of the hydrolyzed species into the particulate fraction or that the colloidal phase is rapidly turned over in the upper water column.

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Mechanistic models such as those based on dynamic energy budget (DEB) theory are emergent ecomechanics tools to investigate the extent of fitness in organisms through changes in life history traits as explained by bioenergetic principles. The rapid growth in interest around this approach originates from the mechanistic characteristics of DEB, which are based on a number of rules dictating the use of mass and energy flow through organisms. One apparent bottleneck in DEB applications comes from the estimations of DEB parameters which are based on mathematical and statistical methods (covariation method). The parameterisation process begins with the knowledge of some functional traits of a target organism (e. g. embryo, sexual maturity and ultimate body size, feeding and assimilation rates, maintenance costs), identified from the literature or laboratory experiments. However, considering the prominent role of the mechanistic approach in ecology, the reduction of possible uncertainties is an important objective. We propose a revaluation of the laboratory procedures commonly used in ecological studies to estimate DEB parameters in marine bivalves. Our experimental organism was Brachidontes pharaonis. We supported our proposal with a validation exercise which compared life history traits as obtained by DEBs (implemented with parameters obtained using classical laboratory methods) with the actual set of species traits obtained in the field. Correspondence between the 2 approaches was very high (>95%) with respect to estimating both size and fitness. Our results demonstrate a good agreement between field data and model output for the effect of temperature and food density on age-size curve, maximum body size and total gamete production per life span. The mechanistic approach is a promising method of providing accurate predictions in a world that is under in creasing anthropogenic pressure.

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Despite its importance to ocean–climate interactions, the metabolic state of the oligotrophic ocean has remained controversial for 415 years. Positions in the debate are that it is either hetero- or autotrophic, which suggests either substantial unaccounted for organic matter inputs, or that all available photosynthesis (P) estimations (including 14C) are biased. Here we show the existence of systematic differences in the metabolic state of the North (heterotrophic) and South (autotrophic) Atlantic oligotrophic gyres, resulting from differences in both P and respiration (R). The oligotrophic ocean is neither auto- nor heterotrophic, but functionally diverse. Our results show that the scaling of plankton metabolism by generalized P:R relationships that has sustained the debate is biased, and indicate that the variability of R, and not only of P, needs to be considered in regional estimations of the ocean’s metabolic state.

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The effect of different factors (spawning biomass, environmental conditions) on recruitment is a subject of great importance in the management of fisheries, recovery plans and scenario exploration. In this study, recently proposed supervised classification techniques, tested by the machine-learning community, are applied to forecast the recruitment of seven fish species of North East Atlantic (anchovy, sardine, mackerel, horse mackerel, hake, blue whiting and albacore), using spawning, environmental and climatic data. In addition, the use of the probabilistic flexible naive Bayes classifier (FNBC) is proposed as modelling approach in order to reduce uncertainty for fisheries management purposes. Those improvements aim is to improve probability estimations of each possible outcome (low, medium and high recruitment) based in kernel density estimation, which is crucial for informed management decision making with high uncertainty. Finally, a comparison between goodness-of-fit and generalization power is provided, in order to assess the reliability of the final forecasting models. It is found that in most cases the proposed methodology provides useful information for management whereas the case of horse mackerel is an example of the limitations of the approach. The proposed improvements allow for a better probabilistic estimation of the different scenarios, i.e. to reduce the uncertainty in the provided forecasts.