Hybridization, defined as breeding between two distinct taxonomic units, can have an important effect on the evolutionary patterns in cross-breeding taxa. Although interspecific hybridization has frequently been considered as a maladaptive process, which threatens species genetic integrity and survival via genetic swamping and outbreeding depression, in some cases hybridization can introduce novel adaptive variation and increase fitness. Most studies to date focused on documenting hybridization events and analyzing their causes, while relatively little is known about the consequences of hybridization and its impact on the parental species. To address this knowledge gap, we conducted a systematic review of studies on hybridization in mammals published in 2010–2021, and identified 115 relevant studies. Of 13 categories of hybridization consequences described in these studies, the most common negative consequence (21% of studies) was genetic swamping and the most common positive consequence (8%) was the gain of novel adaptive variation. The total frequency of negative consequences (49%) was higher than positive (13%) and neutral (38%) consequences. These frequencies are biased by the detection possibilities of microsatellite loci, the most common genetic markers used in the papers assessed. As negative outcomes are typically easier to demonstrate than positive ones (e.g., extinction vs hybrid speciation), they may be over-represented in publications. Transition towards genomic studies involving both neutral and adaptive variation will provide a better insight into the real impacts of hybridization.

Background Humans have altered fire regimes across ecosystems due to climate change, land use change, and increasing ignition. Unprecedented shifts in fire regimes affect animals and contribute to habitat displacement, reduced movement, and increased mortality risk. Mitigating these effects require the identification of habitats that are susceptible to wildfires. We designed an analytical framework that incorporates fire risk mapping with species distribution modeling to identify key habitats of Ursus arctos with high probability of fire in Iran. We applied the random forest algorithm for fire risk mapping. We also modeled brown bear habitats and predicted connectivity between them using species distribution models and connectivity analysis, respectively. Finally, the fire risk map, critical habitats, and corridors were overlaid to spatially identify habitats and corridors that are at high risk of fire. Results We identified 17 critical habitats with 5245 km2 of corridors connecting them, 40.06% and 11.34% of which are covered by conservation areas, respectively. Our analysis showed that 35.65% of key habitats and 23.56% of corridors are at high risk of fire. Conclusions Since bears habitat in this semi-arid landscape rely on forests at higher altitudes, it is likely that shifting fire regimes due to changing climate and land use modifications reduce the extent of habitats in the future. While it is not well known how fire affects bears, identifying its key habitat where wildfires are likely to occur is the first step to manage potential impacts from increasing wildfires on this species.