Probing Early and Long-Term Drought Responses in Kauri Using Canopy Hyperspectral Imaging

Global increases in drought frequency and severity pose growing risks to forest resilience, particularly for long-lived endemic tree species such as kauri (Agathis australis). Building on prior leaf-level work, this study assessed the utility of multitemporal canopy-scale hyperspectral imaging to characterise water stress in both controlled nursery and field conditions. Two complementary experiments were undertaken: (i) a 10-week controlled-environment experiment comparing drought and control groups, and (ii) a field-based assessment of juvenile kauri trees across multiple time points with contrasting soil volumetric water content. In the controlled-environment experiment, drought-treated seedlings exhibited delayed physiological responses, with reductions in stomatal conductance and assimilation emerging only after three weeks. In contrast, time-series analysis of narrow band hyperspectral indices (NBHIs) revealed detectable stress signatures within one week after drought initiation, with early sensitivity driven by structural and pigment-related indices. As stress progressed, pigment-specific indices became the dominant predictors. These findings were consistent with the field-based experiment. Variation in leaf equivalent water thickness (EWT) was strongly explained by pigment-sensitive indices, including Pigment Specific Simple Ratio Carotenoid (PSSRc) and Carotenoid Reflectance indices (CRI700 and CRI550), which together accounted for ca. 87% of the variance. Structural indices such as the Normalised Difference Vegetation Index (NDVI) also ranked among the top 20 predictors, but had comparatively lower explanatory power (<75%). Overall, the two experiments show that canopy-based hyperspectral imaging provides early, sensitive, and consistent detection of water stress in kauri. The findings highlight a scalable approach for monitoring drought impacts on kauri and offer a foundation for developing operational forest health tools under increasing climate pressure.

Authors

Institutions

Publication Details

Journal
Remote Sensing
Published
2025-12-03
DOI
https://doi.org/10.3390/rs17233914
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Probing Early and Long-Term Drought Responses in Kauri Using Canopy Hyperspectral Imaging

Taoho Patuawa, Mark Jayson B. Felix, Russell Main, Michael S. Watt
Remote Sensing
Remote Sensing in Agriculture
article

Probing Early and Long-Term Drought Responses in Kauri Using Canopy Hyperspectral Imaging

Taoho Patuawa, Mark Jayson B. Felix, Russell Main, Michael S. Watt
article en

Abstract

Global increases in drought frequency and severity pose growing risks to forest resilience, particularly for long-lived endemic tree species such as kauri (Agathis australis). Building on prior leaf-level work, this study assessed the utility of multitemporal canopy-scale hyperspectral imaging to characterise water stress in both controlled nursery and field conditions. Two complementary experiments were undertaken: (i) a 10-week controlled-environment experiment comparing drought and control groups, and (ii) a field-based assessment of juvenile kauri trees across multiple time points with contrasting soil volumetric water content. In the controlled-environment experiment, drought-treated seedlings exhibited delayed physiological responses, with reductions in stomatal conductance and assimilation emerging only after three weeks. In contrast, time-series analysis of narrow band hyperspectral indices (NBHIs) revealed detectable stress signatures within one week after drought initiation, with early sensitivity driven by structural and pigment-related indices. As stress progressed, pigment-specific indices became the dominant predictors. These findings were consistent with the field-based experiment. Variation in leaf equivalent water thickness (EWT) was strongly explained by pigment-sensitive indices, including Pigment Specific Simple Ratio Carotenoid (PSSRc) and Carotenoid Reflectance indices (CRI700 and CRI550), which together accounted for ca. 87% of the variance. Structural indices such as the Normalised Difference Vegetation Index (NDVI) also ranked among the top 20 predictors, but had comparatively lower explanatory power (<75%). Overall, the two experiments show that canopy-based hyperspectral imaging provides early, sensitive, and consistent detection of water stress in kauri. The findings highlight a scalable approach for monitoring drought impacts on kauri and offer a foundation for developing operational forest health tools under increasing climate pressure.

Remote SensingVol. 17(23)
Rotorua Hospital (NZ), New Zealand Institute for Public Health and Forensic Science (NZ), Department of Conservation (NZ)
Ministry of Business, Innovation and Employment, Serono Symposia International Foundation
Openalex Percentile: Top 63%
Remote Sensing in Agriculture
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.