Sediment loading and siltation affect seagrasses directly by burying shoots, and indirectly by attenuating light through resuspension. In the Indo-Pacific tropical region, Cymodocea serrulata is considered to be one of the species most tolerant to burial and light attenuation, because it is able to form its canopy in a higher position above the bottom, due to the presence of a long vertical rhizome. To test whether C. serrulata survives in shaded environments by forming a tall canopy (through elongation of the vertical rhizome), we compared variability of this species in vertical rhizome length among sites with different levels of siltation and sedimentation with morphological variability in C. rotundata, which is less tolerant to the stresses. Monitoring of environmental conditions, seagrass collection and morphological measurements of seagrasses were carried out in a meadow in Japan and three meadows in Thailand. C. serrulata and C. rotundata showed different types of among-site variation. To produce a tall canopy, C. serrulata elongated vertical rhizomes, whereas C. rotundata extended blades. Upward elongation of the vertical rhizome or blade was not observed in either species in sites with heavier siltation, suggesting upward elongation is not related to low light stress or sedimental burial. As a conspicuous morphological trait, roots on vertical rhizomes of C. serrulata were abundant at sites where sediment deposition and erosion occur frequently. Having abundant roots on vertical rhizomes is considered to be adaptive for stabilizing unsettled sediment.
Seasonal variations in vegetative growth and production of two seagrass species, Zostera asiatica and Z. marina, were investigated in Akkeshi Bay, northern Japan. Z. asiatica, a threatened species in Japan, was dominant, occurring from the intertidal zone to the deepest edge of the seagrass bed (5 m deep), whereas Z. marina was restricted to the shallower edge of the bed (<2 m). Above ground biomass and above ground net production per shoot were greater for Z. asiatica than for Z. marina. In contrast, shoot density was 3- to 4-fold higher for Z. marina. Biomass and production were minimum in winter to early spring (January to March), and maximum in summer (June to July) for both species. Annual production per unit area of Z. asiatica was larger than that of Z. marina (2033 and 1354 g DW m-2 y-1, respectively). Our findings reveal contrasting growth patterns for the two species: Z. asiatica allocates more resources to enlarging shoot size, whereas Z. marina allocates more to increasing shoot density by clonal propagation of rhizomes. Seagrass beds consisting of Z. asiatica contributed importantly to coastal ecosystems in Akkeshi Bay area because of high productivity.
Few studies have investigated the long-term temporal dynamics of seagrass beds, especially in Southeast Asia. Remote sensing is one of the best methods for observing these dynamic patterns, and the advent of deep learning technology has led to recent advances in this method. This study examined the feasibility of applying image classification methods to supervised classification and deep learning methods for monitoring seagrass beds. The study site was a relatively natural seagrass bed in Hat Chao Mai National Park, Trang Province, Thailand, for which aerial photographs from the 1970s were available. Although we achieved low accuracy in differentiating among various densities of vegetation coverage, classification related to the presence of seagrass was possible with an accuracy of 80% or more using both classification methods. Automatic classification of benthic cover using deep learning provided similar or better accuracy than that of the other methods even when grayscale images were used. The results also demonstrate that it is possible to monitor the temporal dynamics of an entire seagrass area, as well as variations within sub-regions, located in close proximity to a river mouth.