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Abstract Freshwater fishes are among the most threatened taxa worldwide owing to changes in land use, species introductions, and climate change. Although more than half of the freshwater fishes in the Chilean Mediterranean ecoregion are considered vulnerable or endangered, still little is known about their biogeography. Fishes of the family Perciliidae are endemic of this region and ideal cases to study potential implications of global warming given their endangered conservation status, small size, restricted range, and limited dispersal capacity in fragmented habitats. Here, we model the spatial distribution of habitats for Percilia irwini and P. gillissi under current (1970–2000) and future (2050–2080) climatic scenarios (SSP245, SSP585). We implement maximum entropy (MaxEnt) models adapted for stream networks using high-resolution datasets of selected geophysical and climatic variables. At present, both species inhabit relatively low-quality habitats. In the future (SSP585), suitable habitats for P. irwini are predicted to be reduced drastically (99%) with potential local extirpations in its northern range. Similarly, up to 62% of suitable habitats for P. gillissi would also be reduced in the future. Our study provides insights about assessing future threats and vulnerability of endemic, endangered, range-restricted, and small-bodied freshwater species in this region and elsewhere.

Abstract The planned construction of 38 hydropower dams will impact the fish species inhabiting freshwater ecosystems in the megadiverse African country of Gabon. Many of Gabon's most culturally and economically important fish species are marine‐associated, moving between fresh and salt or brackish waters. However, we know little about their life histories or movement patterns, which makes it difficult to predict the impacts of dam development on biodiversity and fisheries in Gabon. Here, we apply MaxEnt distribution modeling to predict the distribution of marine‐associated fishes in Gabon's freshwaters. The model predicts a high likelihood of these fishes occurring in every coastal watershed, throughout the undammed Nyanga drainage, and extending ~400 km into the Ogooué River and its tributaries Ngounie and Abanga. If all 38 dams are constructed, marine‐associated fishes will lose approximately 17% of riverine habitats (7400 km) including 7% of the best quality habitat (460 km). Proposed dams pose a substantial threat to Gabon's most culturally and economically important fishes.

The introduction of non-native species can negatively impact native species through reduced genetic fitness resulting from hybridization. The lack of spatiotemporal data on hybrid occurrences makes hybridization risk assessment difficult. Here, we developed a spatially-explicit Hybridization Risk Model (HRM) between native Oregon bull trout, an Endangered Species Act-listed Oregon species, and introduced brook trout by combining an intrinsic potential model (IPM) of brook trout spawning habitat and existing bull trout distribution and habitat use datasets in Oregon, United States. We created an expert-based brook trout IPM classification score (0–1) of streams based on the potential of geophysical attributes (i.e., temperature, discharge, gradient, and valley confinement) to sustain spawning habitats. The HRM included a risk matrix based on the presence/absence of both species as well as the type of habitat (spawning versus other) at 100-m stream segment resolution. We defined the hybridization risk as “extreme” when stream reaches contained bull trout spawning habitat and brook trout were present with IPM moderate or greater scores (IPM >0.5). Conversely, “low” risk reaches contained historic or non-spawning bull trout habitat, brook trout were absent, and IPM scores were low (IPM