Assessing the freshwater distribution of yellow eel

In the global context of the decline in wild species, modeling the distribution of populations is a crucial aspect of ecological management. This can be a major challenge, especially for species, such as the European eel, that have complex life cycles, exhibit cryptic behavior, or migrate over long distances. A review of the literature suggests that eel size data could be used to assess and analyze freshwater distribution of eel. We argue that analyses based on small yellow eels (≤ 300 mm) along the longitudinal course of rivers could provide a valuable tool for population monitoring. We propose a standardized catchment recruitment index and a colonization index based on the probability of occurrence (presence/absence data) using logistic models for different size classes. The model developed here provides a convenient guide for assessing yellow eel stages in freshwater areas, and should have concrete applications for management of the species

Combining parameter values or pp-values

We review the methods to combine several measurements, in the form of parameter values or $p$-values.Comment: 15 pages, 4 figure

Patterns in fish assemblages in the Loire floodplain: the role of hydrological connectivity and implications for conservation

Hydrological connectivity is known to determine biodiversity patterns across large river floodplains, but it is often greatly altered by human activities. Indicators and predictors of the response of river alteration or restoration are therefore needed. Recent papers suggested that fish environmental guilds – based on species flow preferences – could be used as a tool to assess ecological status of rivers. In the Loire floodplain, we described fish assemblages across the floodplain at the onset of the dry season and we determined whether observed spatial patterns could be related to environmental variables, especially connectivity. Based on specific composition of 46 electrofished waterbodies, a hierarchical typology of the Loire floodplain assemblages was built using self-organizing maps. Each assemblage of the typology was characterized by a set of species using the indicator value method. These species sets and the composition of the assemblages revealed a gradient of flow preferences in the different assemblages identified. A stepwise discriminant analysis showed that the most important variable determining assemblage composition was the hydrological connectivity. Finally, the conclusion was made that a high connectivity level is needed to conserve native fish diversity in the Loire floodplain, notably because the number of protected and native species increased with connectivity, and because the number of exotic species increased with isolation

Practical targeted learning from large data sets by survey sampling

We address the practical construction of asymptotic confidence intervals for smooth (i.e., path-wise differentiable), real-valued statistical parameters by targeted learning from independent and identically distributed data in contexts where sample size is so large that it poses computational challenges. We observe some summary measure of all data and select a sub-sample from the complete data set by Poisson rejective sampling with unequal inclusion probabilities based on the summary measures. Targeted learning is carried out from the easier to handle sub-sample. We derive a central limit theorem for the targeted minimum loss estimator (TMLE) which enables the construction of the confidence intervals. The inclusion probabilities can be optimized to reduce the asymptotic variance of the TMLE. We illustrate the procedure with two examples where the parameters of interest are variable importance measures of an exposure (binary or continuous) on an outcome. We also conduct a simulation study and comment on its results. keywords: semiparametric inference; survey sampling; targeted minimum loss estimation (TMLE