Using near-infrared-enabled digital repeat photography to track structural and physiological phenology in mediterranean tree–grass ecosystems

Tree–grass ecosystems are widely distributed. However, their phenology has not yet been fully characterized. The technique of repeated digital photographs for plant phenology monitoring (hereafter referred as PhenoCam) provide opportunities for long-term monitoring of plant phenology, and extracting phenological transition dates (PTDs, e.g., start of the growing season). Here, we aim to evaluate the utility of near-infrared-enabled PhenoCam for monitoring the phenology of structure (i.e., greenness) and physiology (i.e., gross primary productivity—GPP) at four tree–grass Mediterranean sites. We computed four vegetation indexes (VIs) from PhenoCams: (1) green chromatic coordinates (GCC), (2) normalized difference vegetation index (CamNDVI), (3) near-infrared reflectance of vegetation index (CamNIRv), and (4) ratio vegetation index (CamRVI). GPP is derived from eddy covariance flux tower measurement. Then, we extracted PTDs and their uncertainty from different VIs and GPP. The consistency between structural (VIs) and physiological (GPP) phenology was then evaluated. CamNIRv is best at representing the PTDs of GPP during the Green-up period, while CamNDVI is best during the Dry-down period. Moreover, CamNIRv outperforms the other VIs in tracking growing season length of GPP. In summary, the results show it is promising to track structural and physiology phenology of seasonally dry Mediterranean ecosystem using near-infrared-enabled PhenoCam. We suggest using multiple VIs to better represent the variation of GPP.
The authors acknowledge the Alexander von Humboldt Foundation for supporting this research with the Max-Planck Prize to Markus Reichstein. Y.L. and M.M. gratefully acknowledge financial support from the China Scholarship Council. We are also thankful for financial support from the Spanish Ministry of Economy and Competitiveness through the FLUXPEC project “Monitoring changes in water and carbon fluxes from remote and proximal sensing in a Mediterranean dehesa ecosystem” (CGL2012-34383). The development of PhenoCam has been supported by the Northeastern States Research Cooperative, NSF’s Macrosystems Biology program (award EF-1065029 and EF-1702697), DOE’s Regional and Global Climate Modeling program (award DE-SC0016011), and the US National Park Service Inventory and Monitoring Program and the USA National Phenology Network (grant number G10AP00129 from the United States Geological Survey). The authors thank Sujan Koirala for relevant technical assistance and comments on graphics. The authors thank two anonymous reviewers and the editor for constructive comments to improve the earlier manuscript. The authors thank Andrew Durso for final proofreading for English.