Abstract
Determining the factors responsible for population change in threatened populations and the degree to which changing climates might put those populations at risk is one of the most pressing roles of conservation science. In the climatically variable grasslands of North America, songbirds are rapidly declining, and widespread habitat loss alone does not fully explain these declines. Theory predicts that increased variability in population growth rate, which could be generated by increased variability in weather conditions, should result in lower population sizes. We tested whether increasing variability in weather could have driven recent declines in songbird population numbers using detailed demographic data collected between 2013 and 2021 from grasshopper sparrows ( Ammodramus savannarum ) at the Konza Prairie Biological Station, Kansas, USA. To assess the effect of variability in weather on historical vital rates and population growth rate, we used results from an integrated population model to estimate sensitivity of population growth rate to weather and to conduct path analyses. We also used climate projections to predict population growth rate at our site and potential extirpation risk in a future climate. We found that historical population growth rate was over twice as sensitive to changes in adult apparent survival than other vital rates, and lagged population growth rate was lower following wetter years. Projections of future population size predicted that grasshopper sparrows may be locally extirpated within the next century, consistent with the expectation that increasingly variable precipitation patterns will reduce long‐term viability of songbird populations. Combining sophisticated modeling with detailed demographic data is critical for predicting trends in population growth and guiding conservation approaches in declining or at‐risk species.
| Original language | English |
|---|---|
| Article number | e72195 |
| Journal | Ecology and Evolution |
| Volume | 15 |
| Issue number | 11 |
| Early online date | 24 Nov 2025 |
| DOIs | |
| Publication status | Published - 24 Nov 2025 |
Keywords
- survival
- sensitivity
- fecundity
- population projection
- IPM
- rainfall