A Dirty Dozen Ways to Die: Metrics and Modifiers of Mortality Driven by Drought and Warming for a Tree Species - Breshears, David D.; Carroll, Charles J. W.; Redmond, Miranda D.; Wion, Andreas P.; Allen, Craig D.; Cobb, Neil S.; Meneses, Nashelly; Field, Jason P.; Wilson, Luke A.; Law, Darin J.; McCabe, Lindsie M.; Newell-Bauer, Olivia (Frontiers in Forests and Global Change, 2018)
Tree mortality events driven by drought and warmer temperature, often amplified by pests and pathogens, are emerging as one of the predominant climate change impacts on plants. Understanding and predicting widespread tree mortality events in the future is vital as they affect ecosystem goods and services provided by forests and woodlands, including carbon storage needed to help offset warming. Additionally, if extensive enough, tree die-off events can influence not only local climate but also climate and vegetation elsewhere via climate teleconnections. Consequently, recent efforts have focused on improving predictions of tree mortality. The most commercially important genera of trees is Pinus, and the most studied species for tree mortality is the piñon pine, Pinus edulis. Numerous metrics have been developed in association with predicting mortality thresholds or variations in mortality for this species. In this Mini Review we compiled metrics associated with drought and warming related mortality that were developed for P. edulis or for which P. edulis was a key example species used in a calculation or prediction. We grouped these metrics into four categories: (i) those related to simple climate variables, (ii) those related to physiological responses, (iii) those that require multi-step calculations or modeling using climate, ecohydrological, and/or ecophysiological data, and (iv) modifiers of rates or sensitivities of mortality. We identified the spatial-temporal scale of each of these metrics. The metrics to predict mortality include empirical ones which often have implicit linkages to expected mechanisms, and more mechanistic ones related to physiological drivers. The metrics for P. edulis have similarities with those available for other species of Pinus. Expected future mortality events will provide an opportunity to observationally and experimentally test and compare these metrics related to tree mortality for P. edulis via near-term ecological forecasting. The metrics for P. edulis may also be useful as potential analogs for other genera. Improving predictions of tree mortality for this species and others will be increasingly important as an aid to move towards anticipatory management.