Spatiotemporal dynamics and risk factors of oak decline and Mortality in the Missouri Ozarks of the United States based on repeatedly measured FIA data

Abstract

 

During recent decades there has been widespread oak decline and mortality in the Missouri Ozarks, USA. We extracted data of 18,403 oak trees measured during 1999–2019 from the US Forest Service’s Forest Inventory and Analysis (FIA) database to examine the spatiotemporal patterns of oak decline and mortality and associated risk factors. The Missouri Ozarks were classified into three spatial clusters with low (<1.0%), moderate (1.0–1.5%) and high (>1.5%) annual oak mortality rates using kernel smoothing and the Jenks natural breaks method. Oaks within each spatial cluster were further divided into four, five and three risk groups respectively with differentiated annual mortalities (0.35%–3.05%) using a classification and regression tree model. The Kaplan-Meier survival analyses showed that oak trees from individual spatial clusters and risk groups responded differently to droughts, a major regional or sub-regional inciting factor of oak decline. Droughts could have a three to nine year lagged impact on tree mortality in the high risk groups, whereas had little effect on oak mortality in the low risk groups. Tree species, crown class, and stand age were the regionwide predisposing factors of oak decline. However, localized disturbances and geographic/vegetation conditions (e.g., drought, fire, insects, aspect, elevation, ecoregions, historical forest types) could either incite or alleviate the decline process and the fate of declining trees depending on the differentiated spatial clusters or risk groups. Resource managers can base associated risk factors and spatial clusters to rank risk levels to prioritize and plan management activities to mitigate oak decline and mortality.

  • Citation: Yang S., Spetich M.A., Fan Z. 2021. Spatiotemporal dynamics and risk factors of oak decline and Mortality in the Missouri Ozarks of the United States based on repeatedly measured FIA data. Ecology and Management. https://doi.org/10.1016/j.foreco.2021.119745
  • Keywords: Oak risk groups, Kernel smoothing, Logistic regression, Classification and regression tree, Survival, Drought
  • Posted Date: October 5, 2021
  • Modified Date: October 5, 2021
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