Retrieval of the photochemical reflectance index for assessing xanthophyll cycle activity: a comparison of near-surface optical sensors
Bibliographic record
Abstract
Abstract. Unattended optical sensors are increasingly being deployed on eddy covariance flux towers and are often used to complement existing vegetation and micrometeorological measurements to enable assessment of biophysical states and biogeochemical processes over a range of spatial scales. Of particular interest are sensors that can measure the photochemical reflectance index (PRI), which can provide information pertaining to leaf pigments and photosynthetic activity. This interest has facilitated the production of a new range of lower-cost multispectral sensors specifically designed to measure temporal changes in the PRI signal. However, little is known about the characteristics (spectral, radiometric and temporal) of many of these PRI sensors, making it difficult to compare data obtained from these sensors across time, geographical locations and instruments. Furthermore, direct testing of the capability of these sensors to actually detect the conversion of the xanthophyll cycle, which is the original biological basis of the PRI diurnal signal, is largely absent, often resulting in an unclear interpretation of the signal, particularly given the wide range of factors now known to influence PRI. Through a series of experiments, we assess the sensitivity of one of the leading brands of PRI sensor (Skye SKR 1800) to changes in vegetation photosynthetic activity in response to changing irradiance. We compare the results with those obtained using a more expensive industry-standard visible to near-infrared hyperspectral spectrometer (PP Systems UniSpec) and determine the radiometric compatibility of measurements made by the different instruments. Results suggest that the SKR 1800 instrument is able to track rapid (seconds to minutes) and more gradual diurnal changes in photosynthetic activity associated with xanthophyll cycle pigment conversion. Measurements obtained from both the high and lower cost instrument were significantly linearly correlated but were subject to a large systematic bias, illustrating that differences in instrument configuration (e.g. spectral response functions and band positions) can have a large impact on the PRI measurement values obtained. Despite differences in absolute PRI values, significant correlations were observed between the canopy PRI derived from both the SKR 1800 and the UniSpec instruments, and the epoxidation state of the xanthophyll cycle (r2 = 0.46 p < 0.05 and r2 = 0.76 p < 0.01, respectively). However, the dynamic range of the SKR 1800 PRI signal was often lower than more expensive instruments and thus the lower cost multispectral instrument may be less sensitive to pigment dynamics related to photosynthetic activity. Based on our findings, we make a series of recommendations for the effective use of such sensors under field conditions and advocate that sensors should be fully characterized prior to their field deployment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".