Tue, Aug 16, 2022: 1:30 PM-1:45 PM
515C
Background/Question/MethodsClimate change is expected to shift patterns of spatial synchrony across populations of multiple species. For instance, warming temperatures may increase the spatial synchrony of forest growth, which may signal highly vulnerable populations. However, evidence of climate change-induced synchrony is often conflicting, suggesting that climate change impacts may be more nuanced than predicted. Further, traditional correlative methods have been shown to bias results. To overcome this challenge, we used a 119-year time series of whitebark pine (Pinus albicaulis) tree rings to detect synchrony patterns in tree growth across various timescales. We used wavelet phasor mean fields and spatial coherence to characterize the timescale dependence of synchrony within 20 plots across the Sierra Nevada whitebark pine population. We ask: 1) is climate change increasing spatial synchrony within the whitebark pine population and 2) is climate change shifting the timescales at which synchrony occurs?
Results/ConclusionsUsing spatial coherence, we were able to identify periods of strong synchrony versus independent fluctuations, or strong asynchrony, at timescales ranging from short (2-4 years) to long (greater than 32 years) across 20 plots. We also identified how these patterns change across the time series. In general, the wavelet phasor mean fields showed a moderate sustained increase in short-term synchrony at 2 - 4 year timescales across the time series and a sharp increase in long-term synchrony at 4 - 16 year timescales after 1950. In parallel, we see a decrease in synchrony at timescales longer than 32 years. The increase in synchrony in the latter half of the time series at both short and longer-length timescales could be a result of anthropogenic climate change with a continuing upward trend in CO2 and temperature. Our results suggest spatial synchrony is strongly time-scale dependent, with stable patterns at shorter timescales, but changing trends at long timescales. In general, our results emphasize the importance of long-term data for characterizing species’ responses to climate and changing conditions, with potential implications for long-term whitebark pine population growth and stability.
Results/ConclusionsUsing spatial coherence, we were able to identify periods of strong synchrony versus independent fluctuations, or strong asynchrony, at timescales ranging from short (2-4 years) to long (greater than 32 years) across 20 plots. We also identified how these patterns change across the time series. In general, the wavelet phasor mean fields showed a moderate sustained increase in short-term synchrony at 2 - 4 year timescales across the time series and a sharp increase in long-term synchrony at 4 - 16 year timescales after 1950. In parallel, we see a decrease in synchrony at timescales longer than 32 years. The increase in synchrony in the latter half of the time series at both short and longer-length timescales could be a result of anthropogenic climate change with a continuing upward trend in CO2 and temperature. Our results suggest spatial synchrony is strongly time-scale dependent, with stable patterns at shorter timescales, but changing trends at long timescales. In general, our results emphasize the importance of long-term data for characterizing species’ responses to climate and changing conditions, with potential implications for long-term whitebark pine population growth and stability.