Abstract
As part of Blue Carbon ecosystems (BCEs), detached macrophytes can be transported to the coast due to current and wave actions, and then deposited on the shore as beach wrack. To date, the role of beach wrack in the material cycle in BCEs is still unclear. In order to track the fate of beach wrack, this study conducted a monitoring survey on a semi-sheltered beach in Odense Fjord (Denmark) using camera trap data. Deep learning with a VGG network architecture was used to classify the image dataset acquired by the camera trap. The VGG network demonstrated the capability to identify beach wrack from different beach scenes, and the method can provide results on large datasets within a short time (187 images analyzed within 5 min) compared to manual identification of images. By combining the VGG detection with color-based segmentation, beach wrack coverage was determined. To evaluate the impact of ambient conditions on wrack deposition on the shore and relocation back to the sea, wind (including speed and direction), water temperature, and tidal amplitude were analyzed as environmental variables. Partial least squares regression (PLSR) analysis revealed that micro-tidal action with an average amplitude of 0.41 m accelerated the movement of floating macrophytes between the shore and the sea. Despite being exposed to the prevailing southwesterly winds (average speed of 11 m/s), the beach was sheltered due to the location in the inner part of Odense Fjord, limiting the transport of drifting macrophytes from sea to the shore. By using the camera trap to conduct continuous monitoring, this study presents a labor-saving and practical approach to track the dynamics of detached macrophytes deposited on the shore. Furthermore, the application of deep learning in image identification provides a study case for using a large image dataset to assist in ecological studies of dynamic environments.
Highlights
Detached seagrasses and drifting macroalgae are transported to the shore by currents and waves and deposited as beach wrack (Rodil et al, 2008; Macreadie et al, 2017)
After detecting the region of interest (ROI), wrack on the shore was identified by the proposed VGG network, and beach wrack coverage was estimated (Figure 2)
The proposed algorithm demonstrated the ability to identify beach wrack in different beach scenes recorded by a camera trap
Summary
Detached seagrasses and drifting macroalgae are transported to the shore by currents and waves and deposited as beach wrack (Rodil et al, 2008; Macreadie et al, 2017). Beach Wrack Dynamics With Camera-Trap macrophytes in BCEs in addition to deeper-sea transfer (Duarte, 2017; Duarte and Krause-Jensen, 2017). Compared to the investigation of carbon buried in habitat sediments, exploring the exported part from BCEs is still a challenge, including the part transferred to deeper sea and the part deposited on the shore (Duarte, 2017). Investigating the deposition pattern of detached macrophytes on the shore is a priority to track the exported part from BCEs, which can assist in thoroughly exploring the fate of this part of exported carbon. Monitoring of beach wrack is of significance for the exploration of the carbon cycle in BCEs
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