Weather is thought to influence raptor reproduction through effects on prey availability, condition of adults, and survival of nests and young; however, there are few long-term studies of the effects of weather on raptor reproduction. We investigated the effects of weather on Northern Goshawk (Accipiter gentilis; henceforth goshawk) breeding rate, productivity, and fledging date in south-central Idaho and northern Utah, USA. Using data from 42 territories where we found evidence of breeding attempts in ≥1 yr from 2011–2019, we analyzed breeding rates using 315 territory–season combinations, analyzed productivity for 134 breeding attempts, and analyzed fledging date for 118 breeding attempts. We examined 35 predictor variables from four categories: precipitation, temperature, wind, and snowpack. Of the variables we evaluated, April precipitation, previous year's April–July precipitation, April–May mean temperature, and March–May mean temperature were related to measures of goshawk reproduction. Greater April–July precipitation in the previous year and lower April precipitation in the current year were associated with higher breeding rates. Years with warmer average April–May temperatures were associated with increased goshawk productivity. Years with greater April–July precipitation during the previous year and lower mean March–May temperatures were associated with later fledging dates. Based on these relationships, we considered projected changes in weather in the northern Great Basin over the next 50 yr as a result of climate change (without directly accounting for habitat changes caused by climate change), and predicted that climate change will: (a) have no significant effect on goshawk breeding rate, (b) have a positive effect on goshawk productivity, and (c) cause a shift toward earlier goshawk breeding. Our results indicate that weather is significantly related to goshawk reproduction in the northern Great Basin, and we suggest that the relationship between raptor breeding and weather be further investigated to enable higher resolution predictions of how changes in the climate may influence their populations, particularly changes that may not have been captured by our study.

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