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Abstract The evolution of sexual dimorphism (SD) is driven by intricate interplays between sexual and natural selection. When it comes to SD variation within populations, however, environmental factors play a major role. Sexually selected traits are expected to be strongly dependent on individual body condition, which is influenced by the local environment that individuals experience. As a consequence, the degree of SD may also depend on resource availability. Here, we investigated the potential drivers of SD expression at two sexually dimorphic morphometric traits, body size (snout vent length) and head shape (head geometric morphometrics), in the Italian wall lizard (Podarcis siculus). We assessed the existence of condition- and context-dependent SD across ten islands of the Aeolian archipelago (southern Italy), at within- and among-population scales. We observed strong geographical variation of SD among islands, and tested three potential SD predictors related to resource availability (individual body condition, ecosystem productivity, temperature). Body condition and ecosystem productivity were the main drivers of body size SD variation, and body condition was also the main driver for head shape SD. Our results highlight that the expression of SD in the Italian wall lizard is both condition- and context-dependent. These results are congruent at within- and among-populations scales highlighting that spatial multi-scale analysis represents a useful approach to understand patterns of SD expression.

Abstract Accurate measures of species abundance are essential to identify conservation strategies. N-mixture models are increasingly used to estimate abundance on the basis of species counts. In this study we tested whether abundance estimates obtained using N-mixture models provide consistent results with more traditional approaches requiring capture (capture-mark recapture and removal sampling). We focused on endemic, threatened species of amphibians and reptiles in Italy, for which accurate abundance data are needed for conservation assessments: the Lanza’s Alpine salamander Salamandra lanzai, the Ambrosi’s cave salamander Hydromantes ambrosii and the Aeolian wall lizard Podarcis raffonei. In visual counts, detection probability was variable among species, ranging between 0.14 (Alpine salamanders) and 0.60 (cave salamanders). For all the species, abundance estimates obtained using N-mixture models showed limited differences with the ones obtained through capture-mark-recapture or removal sampling. The match was particularly accurate for cave salamanders in sites with limited abundance and for lizards, nevertheless non-incorporating heterogeneity of detection probability increased bias. N-mixture models provide reliable abundance estimates that are comparable with the ones of more traditional approaches, and offer additional advantages such as a smaller sampling effort and no need of manipulating individuals, which in turn reduces the risk of harming animals and spreading diseases.