Abstract
A better knowledge of tree vegetative growth phenology and its relationship to environmental variables is crucial to understanding forest growth dynamics and how climate change may affect it. Less studied than reproductive structures, vegetative growth phenology focuses primarily on the analysis of growing shoots, from buds to leaf fall. In temperate regions, low winter temperatures impose a cessation of vegetative growth shoots and lead to a well-known annual growth cycle pattern for most species. The humid tropics, on the other hand, have less seasonality and contain many more tree species, leading to a diversity of patterns that is still poorly known and understood. The work in this study aims to advance knowledge in this area, focusing specifically on herbarium scans, as herbariums offer the promise of tracking phenology over long periods of time. However, such a study requires a large number of shoots to be able to draw statistically relevant conclusions. We propose to investigate the extent to which the use of deep learning can help detect and type-classify these relatively rare vegetative structures in herbarium collections. Our results demonstrate the relevance of using herbarium data in vegetative phenology research as well as the potential of deep learning approaches for growing shoot detection.
Highlights
The current challenges of climate change require a better understanding of plant growth dynamics, to better measure the evolution of the carbon sequestration capacity of forests [1]
We propose to evaluate the potential of deep learning approaches for the analysis of the vegetative axis extension pattern of tropical tree species based on the analysis of herbarium specimens
The third model that we evaluated is based on the Mask R-Convolutional Neural Network (CNN) architecture [65], which was chosen for its ability to perform an instance segmentation task by extending the Faster Region-Based Convolutional Neural Networks (R-CNN) approach to a pixel-level mask prediction task
Summary
The current challenges of climate change require a better understanding of plant growth dynamics, to better measure the evolution of the carbon sequestration capacity of forests [1]. Because carbohydrates are synthesized in leaves through photosynthesis, it is of primary importance to understand shoot extension dynamics (which include shoot leaf and internode extension), leaf functioning, and life span over time. This understanding must be achieved by integrating different scales such as the leaf organ, the crown of the tree, the populations of species, or the community of species that make up the forest canopy
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.
