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Hybridisation between domestic cats, Felis catus, and wildcats, Felis silvestris, could lead to the genetic extinction of the latter; therefore, checking hybridisation rates in wild populations is of vital conservation importance. However, detecting hybridisation in the field is particularly challenging. Here, we aim to test the success of morphological-based procedures for discriminating wildcats from their hybrids and domestic cats, against genetic methods. We checked 17 putative Spanish wildcats by using two different classification systems based on coat patterns. None of the putative wildcats analysed in this study seemed to have an admixed genotype. Concordance between genetic and pelage approaches was almost total: only one coat classification produced mixed results with detection of one potential hybrid. Assignment was worse when performed in the field after a rapid examination of coat characters. We conclude that classification systems using coat traits could serve as surrogates of genetic approaches, but only after careful examination of those characters with more discriminatory power. Thus, the control of hybrid populations in the field as a management tool to preserve the genetic identity of wild forms is problematic if based on crude approaches or incomplete classification systems. [ABSTRACT FROM AUTHOR]

Capsule Birds at dispersal areas consumed more rabbits than adult territorial eagles. [ABSTRACT FROM AUTHOR]

An important issue in population ecology is to disentangle different density-dependent mechanisms that may limit or regulate animal populations. This goal is further complicated when studying long-lived species for which experimental approaches are not feasible, in whose cases density-dependence hypotheses are tested using long-term monitored populations. Here we respond to some criticisms and identify additional problems associated with these kinds of observational studies. Current caveats are related to the temporal and spatial scales covered by population monitoring data, which may question its suitability for density-dependence tests, and to statistical flaws such as the incorrect control for confounding variables, low statistical power, the distribution of demographic variables, the interpretation of spurious correlations, and the often used stepwise series of univariate analyses. Generalised linear mixed models are recommended over other more traditional approaches, since they help to solve the above statistical problems and, more importantly, allow to properly test several hypotheses simultaneously. Finally, several management actions aimed to recover endangered species, such as supplementary feeding, might be considered as field experiments for further testing density-dependence hypotheses in long-lived study models. We expect these opportunities, together with the most adequate statistical tools now available, will help to better our understanding of density-dependent effects in wild populations. [ABSTRACT FROM AUTHOR]