Long-term numerical changes and regulation in a river stock of European eel Anguilla anguilla

1. The objective was to explore the regulatory mechanisms underlying the numerical dynamics of a river stock of European eel Anguilla anguilla based on a purely observational study. We used a 21-year data set on the Rio Esva (Asturias, northwestern Spain) stock of eels, encompassing eel density at an estuary site and at nine sites distributed among three tributaries selected to differ in the distance from the tidal limit and fishery data on glass eels from the nearby Rio Nalón estuary.
2. The abundance of glass eels and estuarine and in-stream densities declined simultaneously over a 15-year period. However, following a historical minimum in the abundance of glass eels around the year 2000, the density continued to decline in the estuary whereas density in the streams began an increase that has continued to the present.
3. In-stream cohort mortality rate ( Z ) varied from 0.0016 day⁻¹ to only 0.0003 day⁻¹ (on an annual basis from 0.57 to 0.099 year⁻¹). The negative effects of intra-cohort and inter-cohort densities on mortality rate emphasized the responses of the riverine stock to compensatory density-dependence. As a consequence, the number of eels surviving to commence the silvering stage was similar in magnitude in the strongest and weakest cohorts.
4. These results suggest that, even if the low abundance of glass eels persists, in-stream density may increase towards a stable value regulated by in-stream density-dependence.     

Areas of endemism of Mexican mammals: reanalysis applying the optimality criterion

In order to test Mexican areas of endemism of mammals identified by previous parsimony analyses of endemicity (PAEs), we applied the optimality criterion to three data matrices (based on point records, potential distributional models and the fill option in software NDM). We modelled the ecological niches of 429 terrestrial mammal species using the genetic algorithm for rule-set prediction (GARP) and models were projected as potential distributional areas. We overlapped the point occurrence data and the individual maps of potential distributions to a grid of 1° latitude–longitude. Three matrices of 247 grid cells (areas) and 429 species were built: (1) a binary matrix with '0' for absence and '1' for presence of at least one record of the species inside the grid-cell; (2) a three-state matrix similar to (1) but assigning the state '2' to the assumed presence in the model of potential distribution; and (3) a three-state matrix similar to (2), but applying the fill option of software NDM instead of using a model. The optimality criterion was performed in NDM version 2.7 and results were examined with VNDM version 2.7. The first and second matrices showed 13 areas of endemism and the third identified 16 areas of endemism. NDM provided a better resolution than PAE, allowing us to identify several new areas of endemism, previously undetected. Ecological niche models, projected as potential distributional areas, and the optimality criterion are very useful to identify areas of endemism, although they should be used with caution because they may overpredict potential distributional areas. PAE seems to underestimate the areas of endemism identified.  © 2009 The Linnean Society of London, Biological Journal of the Linnean Society , 2009, 98 , 468–478.