Investigating the drivers that support species richness (S) in insular contexts can give insights for the conservation of insular biodiversity. Our aim was to decouple the effect of drivers (island area, distance from mainland and habitat diversity) accounted in three hypotheses or a combination of them in explaining S in seven islands of the Tuscan Archipelago: Area (species–area relationship, SAR), area and distance from mainland (equilibrium hypothesis, EQH) and habitat (habitat diversity hypothesis, HDH). We used published and original datasets to assess S (except aliens) for 42 taxa (14 animal and 28 plant taxa) in each island, and we used S as the dependent variable and the drivers as covariates in regression models. In 31 taxa, the data supported one of the tested hypotheses or a combination of them, and the most commonly supported hypotheses were SAR (12 taxa) and EQH (10 taxa). The effect of the area was also evident in SAR + HDH (five taxa) and EQH + HDH (one taxon), making it the prevailing driver in explaining S. Since distances are relatively short, and three out of four islands are land-bridge islands, the effect of distance was significant for 12 taxa. The effects of habitat diversity were evident for just nine taxa. The multi-taxon approach allowed us to understand the differential effect of drivers among taxa in influencing S in a single archipelago. Moreover, the multi-taxonomic rank approach highlighted how the information contained within higher taxonomic ranks (e.g., Division) can be substantially different from that derived from lower ranks (e.g., Family). These insights are of particular importance from a conservation perspective of the archipelago’s biodiversity, and this approach can be transferred to mainland fragmented systems.

Small populations are more prone to extinction if the dispersal among them is not adequately maintained by ecological connections. The degree of isolation between populations could be evaluated measuring their genetic distance, which depends on the respective geographic (isolation by distance,IBD) and/or ecological (isolation by resistance,IBR) distances. The aim of this study was to assess the ecological connectivity of fire salamanderSalamandra salamandrapopulations by means of a landscape genetic approach. The species lives in broad‐leaved forest ecosystems and is particularly affected by fragmentation due to its habitat selectivity and low dispersal capability. We analyzed 477 biological samples collected in 47 sampling locations (SLs) in the mainly continuous populations of the Prealpine and Eastern foothill lowland (PEF) and 10 SLs in the fragmented populations of the Western foothill (WF) lowland of Lombardy (northern Italy). Pairwise genetic distances (Chord distance,D_C) were estimated from allele frequencies of 16 microsatellites loci. Ecological distances were calculated using one of the most promising methodology in landscape genetics studies, the circuit theory, applied to habitat suitability maps. We realized two habitat suitability models: one without barriers (EcoD) and a second one accounting for the possible barrier effect of main roads (EcoD_b). Mantel tests between distance matrices highlighted how the Log‐D_CinPEFpopulations was related to log‐transformed geographic distance (confirming a prevalence ofIBD), while it was explained by the Log‐EcoD, and particularly by the Log‐EcoD_b, inWFpopulations, even when accounting for the confounding effect of geographic distance (highlighting a prevalence ofIBR). Moreover, we also demonstrated how considering the overall population, the effect of Euclidean or ecological distances on genetic distances acting at the level of a single group (PEForWFpopulations) could not be detected, when population are strongly structured.