Renewable forms of energy production can have major societal benefits including reduced carbon pollution and decreased dependence on fossil fuels but are not without associated costs. For example, habitat degradation at renewable energy production sites may affect the persistence of wildlife populations. We assessed the effects of wind farms in the San Gorgonio Wind Resource Area near Palm Springs, California, 2013–2015, on local populations of the side‐blotched lizard (Uta stansburiana). The side‐blotched lizard is a common and ubiquitous desert reptile that is a major consumer of invertebrates and, in turn, represents a key prey base for many avian, reptilian, and mammalian predators. We used spatially explicit capture‐recapture methods to compare a comprehensive set of population‐level vital signs (i.e., abundance, population growth rate, survival, recruitment, body condition, age structure, activity area size, movement rates) among populations at 4 wind farms and at 5 reference areas. Although our models indicate that wind facilities have a weak negative effect on side‐blotched lizard survival, our overall results suggest that wind farms do not substantially influence the demography or behavior of these small lizards. Population response to general anthropogenic disturbance (quantified as an index of road type and density) was more pronounced, with lower population growth rates, adult‐skewed age structure, and reduced body condition at highly disturbed wind farm and reference sites. We therefore conclude that wind‐power facilities can support healthy populations of side‐blotched lizards, indicating that wind energy development is compatible with a native Mojave Desert species. However, our results show that anthropogenic disturbance, as measured by the type and density of roadways, has a negative effect on lizard populations, and should be carefully planned whether associated with energy development or not. Our study demonstrates a methodological approach that can be applied to other species, including those with lower tolerances to disturbance, to measure their response to renewable energy development.