Abstract
Monitoring vegetation is extremely relevant in the context of climate change, and digital repeat photography is a method that has gained momentum due to a low cost–benefit ratio. This work aims to demonstrate the possibility of using digital cameras instead of field spectroradiometers (FS) to track understory vegetation phenology in Mediterranean cork oak woodlands. A commercial camera was used to take monthly photographs that were processed with the Phenopix package to extract green chromatic coordinates (GCC). GCC showed good agreement with the normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) obtained with FS data. The herbaceous layer displayed a very good fit between GCC and NDVI (coefficient of determination, represented by r2 = 0.89). On the contrary, the GCC of shrubs (Cistus salviifolius and Ulex airensis) showed a better fit with NDWI (r2 = 0.78 and 0.55, respectively) than with NDVI (r2 = 0.60 and 0.30). Models show that grouping shrub species together improves the predictive results obtained with ulex but not with cistus. Concerning the relationship with climatic factors, all vegetation types showed a response to rainfall and temperature. Grasses and cistus showed similar responses to meteorological drivers, particularly mean maximum temperature (r = −0.66 and −0.63, respectively). The use of digital repeat photography to track vegetation phenology was found to be very suitable for understory vegetation with the exception of one shrub species. Thus, this method proves to have the potential to monitor a wide spectrum of understory vegetation at a much lower cost than FS.
Highlights
Tracking seasonal patterns in vegetation dates back centuries [1] and was traditionally conducted through human observation of the most common metrics of plant structural change, for example, leaf unfolding—the time of year when leaves begin to sprout—and senescence—the time when they dry at the end of the growing season [2]
Understanding phenology is relevant in the context of process-based forest models, since it determines how ecosystems respond to different climate scenarios that are used to predict the impact of climate change [4]
This difference extends further into how data should be organized since our results show that separating by plant functional types (PFTs) is essential when using green chromatic coordinates (GCC) as a proxy for normalized difference vegetation index (NDVI)
Summary
Tracking seasonal patterns in vegetation dates back centuries [1] and was traditionally conducted through human observation of the most common metrics of plant structural change, for example, leaf unfolding—the time of year when leaves begin to sprout—and senescence—the time when they dry at the end of the growing season [2]. The timing of these events has tremendous implications on ecosystems, since plants are the base of the food chain. Sensors are at a great distance from the target of interest, producing several
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
