Abstract

Pine forests in the southern United States are a major contributor to the global economy. Through the last three decades, however, there have been concerns about the decline of pine forests attributed mostly to pests and pathogens. A combination of biotic agents and environmental factors and their interaction often influences outbreaks and the resultant damage in the forests. Southern pines experience periodic mortality from bark beetles and root rot fungi and losses from fusiform rust and pitch canker have long been important for management. In recent years, there is also growing evidence of increasing damage from foliar disease in southern pines. Early detection of diseases following changes in foliar characteristics and assessment of potential risks will help us better utilize our resources and manage these forests sustainably. In this study, we used Forest Inventory and Analysis (FIA) data to explore the intensity of foliar disease in three common pines: loblolly (Pinus taeda L.), longleaf (Pinus palustris Mill.), and slash (Pinus elliottii Engelm.) in spatial and temporal terms using tree-level and climatic variables. Results from a tree-level model suggests that crown ratio may be an important factor in pine foliar disease (p < 0.1). We applied the MaxEnt model, a presence-only species distribution model (SDM), to explore any association of foliar disease incidences with the climatic variables at a landscape level. Results indicate that mean dew point temperature, maximum vapor pressure deficit, and precipitation during cold months had more influence over disease incidences than other climatic variables. While the sample size is limited as this is an emerging disease in the region, our study provides a basis for further exploration of disease detection methods, disease etiology studies, and hazard mapping.

Highlights

  • A deeper understanding of forest health consequences from global economic trade, changing land use, climate change, and management practices is a key area for investigation to provide accurate projections of forest carbon storage and productivity

  • The MaxEnt species distribution model (SDM) model developed in this study suggested an association of the climatic variables with the emergence of needle casts on southern pines

  • We explored whether tree-level variables could be related to foliar disease in the southeastern pine species

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Summary

Introduction

A deeper understanding of forest health consequences from global economic trade, changing land use, climate change, and management practices is a key area for investigation to provide accurate projections of forest carbon storage and productivity. Emerging pests and pathogens pose a large threat to the ecological and economic stability of forested ecosystems. A triangular interaction between host trees, pests/pathogens, and environmental factors is often described as a major contributor in potential disease outbreaks [1]. With predicted changes in climate, there will be potential shifts in favorable environments for both hosts and pests or pathogens; there are counter arguments on whether there would be significant increase in damage from these biotic factors [2]. Forests 2020, 11, 1155 slowing or eradicating novel pests or pathogens [3,4,5]. As datasets get bigger and computing power grows, so should our ability to catch emergent problems [6,7]

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