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ECOSTRESS‐derived semi‐arid forest temperature and evapotranspiration estimates demonstrate drought and thinning impacts

T. Sankey,T. Kyaw,Julia Tatum,George W. Koch,T. Kolb,Rayni Lewis,H. Poulos,Andrew M Barton,Blase LaSala,Andrea Thode

Published 2025 in Remote Sensing in Ecology and Conservation

ABSTRACT

Southwestern US forests are experiencing increasing wildfire activity, and land managers are implementing large‐scale forest thinning treatments. We investigated semi‐arid ponderosa pine forest thinning treatment and regional drought impacts on ECOSTRESS land surface temperature (LST) and evapotranspiration (ET). Our study period at a northern Arizona study site included an average precipitation year, 2019, a regional drought period of 2020–2022, and a record winter snowfall year 2023. We examined ECOSTRESS LST and ET during spring seasons when the region experiences an annual dry period, and plant water stress is heightened. Our results indicate that ECOSTRESS LST data are sensitive to forest thinning, regional drought and their interaction. Consistent with high‐resolution UAV images, ECOSTRESS LST data indicate the thinned forest had significantly greater temperature across years, regardless of precipitation patterns. During drought, ECOSTRESS LST increased in both thinned and non‐thinned forests (by up to 10°C) and then declined in 2023. ECOSTRESS ET was similarly sensitive to forest thinning and regional drought. Consistent with in situ ET measurements, ECOSTRESS ET was significantly greater in the non‐thinned forest compared to the thinned forest. ECOSTRESS ET significantly decreased during drought in both forests. Our analysis of EMIT data indicates that EMIT trends are not consistent with ground‐based hyperspectral data that documented thinned forest moisture content is greater than that of the non‐thinned forest. While quality filtering reduces ECOSTRESS data temporal resolution, both ECOSTRESS LST and ET data can be used across large spatial extents to examine impacts of regional drought and management treatments in semi‐arid ponderosa pine forests.

PUBLICATION RECORD

  • Publication year

    2025

  • Venue

    Remote Sensing in Ecology and Conservation

  • Publication date

    2025-08-20

  • Fields of study

    Not labeled

  • Identifiers
    DOI 10.1002/rse2.70026
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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