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Recent severe drought in California, USA, has killed tens of millions of trees in the Sierra Nevada mountains, increasing the risk of catastrophic wildfires. A new set of rigorously validated maps of forest vulnerability to drought produced by the U.S. Geological Survey’s Western Ecological Research Center with partners at the U.S. Forest Service, U.S. National Park Service, and Arizona State University, can help forest resource managers prioritize forest treatments to mitigate fire risk and mortality from future drought.

Forest managers can use a variety of tools to mitigate the effects of severe drought, including thinning and prescribed burning, but limited resources may require these managers to make choices about which parts of the landscape to target for treatment. Vulnerability maps can be an important resource for managers, but many existing vulnerability analyses are unvalidated and not grounded in robust empirical datasets. Contemporary maps based on high-resolution remotely sensed data and an extensive ground-based, plot-level dataset were developed to provide a more accurate tool for managers.

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The remotely-sensed data came from the Global Airborne Observatory (https://gao.asu.edu) and included values for normalized differential vegetation index (NDVI; a measure of “greenness”) and canopy water content. The plot-level data came from a large, ground-based forest dynamics study that followed the fates of 970 trees in mixed-conifer forests of Sequoia and Kings Canyon National Parks during and after the drought. These data were used to develop models that predict risk of mortality based on NDVI, elevation, and tree species. A separate dataset of 1179 trees spread throughout the study area was used to validate the models. Finally, the models were used to predict and map forest vulnerability across an 8x33 km band of mixed conifer forests in the parks.

The maps serve as a snapshot of drought vulnerability in anticipation of future droughts and as a prediction of where to expect mortality as derived from the 2012-2016 drought. Areas of high vulnerability marked as red and orange on the map can be assessed as to whether they are good candidates for forest treatment or too compromised for management action to be effective, while low vulnerability areas might be considered a lower priority. As severe droughts continue to impact Sierra Nevada forests  the models can be used with current and future remote-sensing data to detect changes in vulnerability into the future.

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Management Takeaways

• New forest vulnerability maps show where trees are most at risk of drought mortality across Sequoia and Kings Canyon National Parks
• The models used to produce the vulnerability maps indicate that tree survival probability decreased with lower NDVI (a remotely sensed measure of greenness) and elevation
• The models can be used with future NDVI values to detect changes in forest vulnerability
• The strong predictive value NDVI, a relatively easy measure to obtain, indicates the potential of this measure for future vulnerability assessments for forests beyond the Sierra Nevada
• Models indicated that drought vulnerability varied among species and that including species identity can improve model performance. The models performed the best for white fir (Abies concolor), which comprises the majority of the trees in many Sierra Nevada forests, but tended to overestimate mortality risk for incense cedar (Calocedrus decurrens) and underestimate risk for pine species

This spotlight refers to the following publication and data release:

Das, A.J., M.R. Slaton, J. Mallory, G.P. Asner, R.E. Martin, P. Hardwick. 2021. Empirically validated drought vulnerability mapping in the mixed conifer forests of the Sierra Nevada. Ecological Applications. 32(2):e2514.

Das, A.J., Slaton, M.R., Mallory, J., Asner, G.P., Martin, R.E., and Hardwick, P., 2021, Calibration and validation data and model coefficients for mixed conifer vulnerability project from Sequoia and Kings Canyon National Park 2015 to 2019: U.S. Geological Survey data release, https://doi.org/10.5066/P9P6JKJW.

 

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