RAPID: Leveraging the 2015-2016 El Nino to evaluate drought legacy effects on tree growth responses to rare wet events

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The U.S. Southwest is an arid region that experiences large interannual variation in precipitation. The region has experienced a series of severely dry years in the past two decades, most recently in 2012. However in an El Nino year, such as 2016, winter precipitation can be several times greater than average. Drought years increase mortality in forest and woodland trees, and the trees that survive drought require a period of several years before regaining normal growth capacity. Although high winter precipitation generally promotes better growth, it may be the case that a tree's ability to take advantage of a good year depends on its drought history. This is because the anatomical and physiological changes in trees that survive seem to reduce a tree?s ability to transport water and support high rates of photosynthesis and new growth. This project will use a set of study sites in the Four-Corners region of the southwest that span a wide range of increased winter precipitation from the current El Niño. Because previous studies at these same sites have documented the growth impacts of recent droughts, this project can now test whether trees that suffered larger drought impacts are less able to respond positively to the increased water provided by the El Niño. The study species include aspen, piñon pine, and juniper, species that differ in drought tolerance and ability to use shallow versus deeper soil moisture. The results from this project will strengthen understanding of how precipitation variability, which is expected to increase with continued climate warming, affects productivity of southwestern ecosystems. This study will provide research experience for multiple undergraduate students including individuals from underrepresented groups.The current El Niño has produced a rare gradient in winter (Oct 2015-Feb 2016) precipitation across the Four-Corners region, spanning 25% to over 400% of the long-term mean. Four years prior, the 2011-2012 drought significantly and negatively impacted tree populations, soil moisture availability, and ecosystem carbon sequestration. Recent work has demonstrated that it takes 3-5 years for tree growth, ecosystem carbon fluxes, and net ecosystem productivity to recover from past, severe droughts. What is unknown is whether these prolonged impacts of past droughts affect how trees and ecosystems respond to extreme increase in precipitation created by an El Niño. Thus, this project seeks to determine the extent to which past climatic conditions, especially droughts, govern tree physiological and growth responses during wet periods. To accomplish this, the project will sample multiple U.S. Forest Service forest inventory (FIA) sites representative of the climate variability in the Four-Corners region and for which complementary tree- and plot-level data are available. These sites support three focal, foundational tree species (aspen, piñon, juniper) that differ in their drought tolerance strategies. The study will employ a unique combination of repeated physiological measurements, dendrochronology approaches, and statistical modeling that will enable new insight into climate legacies, their impact on tree physiological processes, and subsequent implications for tree growth during potentially ?favorable? conditions. This study will generate a unique and extensive dataset over a relatively short time period, which can be used to test the naïve assumption that high precipitation significantly stimulates tree growth. It is expected to demonstrate that tree growth responses to rare wet years are controlled by past climatic influences. Field campaigns and laboratory studies will involve multiple undergraduates, an early career research associate, and will seek to involve individuals from under-represented groups. Findings from the study will be disseminated via the scientific literature and popular media; tree-ring data will be contributed to the freely accessible International Tree-Ring Data Bank.