Asynchronous local dynamics contributes to stability of a seagrass bed in Tokyo Bay

Abstract

Abstract:It is known that asynchronous temporal variations in local populations can contribute to the stability of metapopulations. However, studies evaluating the hierarchical organization of multiple spatial scales are rare for continuous marine landscapes, especially for marine vegetation such as seagrass beds. In this study, long-term observation (26 years) of temporal changes and nested spatial analyses were combined for an extensive seagrass meadow in Tokyo Bay, Japan, using remote sensing and geographic information system technologies. We examined how the dynamics at the whole-bed scale (~1 km 2 ) are related to those at a local scale (0.04 km 2 ), and investigated the relationship between the seagrass dynamics and long-term changes in environmental conditions using data on oceanography, water quality, and sediment dynamics. The seagrass bed size fluctuated between a maximum of 1.28 km 2 (in 1987) and a minimum of 0.39 km 2 (in 2001), with an average of 0.90 km 2 . The temporal variation in seagrass bed size at the whole-bed scale correlated with sand movement within the seagrass bed related to changes in the position of a sandbar. Seagrass bed size fluctuated asynchronously at a local scale. Multivariate analyses recognized clusters of local areas showing similar patterns of fluctuation. Temporal patterns in the various clusters responded differently to changes in environmental factors, e.g., the position of the sandbar was highly correlated with seagrass bed size in shallow habitats but not in deeper areas. The magnitudes of the temporal variations for the local clusters were greater than that of the entire bed, suggesting that asynchronous fluctuation in different areas of the bed plays an important role in the overall stability of the seagrass bed. The results of the present study also highlight the importance of physical processes in regulating the temporal dynamics of seagrass beds in shallow sedimentary landscapes.

Environmental and spatial controls of macroinvertebrate functional assemblages in seagrass ecosystems along the Pacific coast of northern Japan

“…Reed and Hovel, 2006;Yamada et al, 2007a). These findings suggest that the existence and/or dynamics of patches of seagrass (e.g., Vellend and Geber, 2005;Phinn et al, 2008;Yamakita et al, 2011;Chust et al, 2013a) may affect the variation of functional groups, that is, patch dynamics may ensure the variation of ecosystem functions provided by macroinvertebrate communities. In support of this idea, Yamada et al (2011) concluded that the functional diversity of the macrocrustacean community in seagrass ecosystems is the variable at the local patch scale, but homogeneous (i.e., occurrence of functional redundancy) at the regional scale (e.g.…”

“…Vellend and Geber, 2005;Phinn et al, 2008;Yamakita et al, 2011). The presence of seagrass increases habitat complexity and provides living space, shelter, and feeding and nursery grounds for a greater variety and abundance of faunal species than in adjacent unvegetated habitats (Connolly and Hindell, 2006;Horinouchi, 2007).…”

More than the sum of the parts: annual partitioning within spatial guilds underpins community regulation

“…One reason for this could be that aggregate communities are typically probed in metanalyses of large databases. However, evidence for compensation appears strongest when assemblages are decomposed, for example, by taking account of variation in ecophysiology [33] or habitat heterogeneity [34]. Detailed local knowledge of taxa thus remains an essential part of community ecology alongside broad brush macroecological analyses.…”

Estimating the change in regional scale distribution of seagrass and macroalgal beds using discrete local distribution data analyzed from aerial images

“…However, the classification accuracy of the images without the water column correction was better than that of the images with the water column correction. To our knowledge, however, some recent studies without water column correction for analysis of submerged vegetation have been reported (e.g., Pasqualini et al, 2005, Gullstrom et al, 2006, Phinn et al, 2008, Wabnitz et al, 2008, Yamakita et al, 2011, Roelfsema et al, 2013, and these studies without the correction were mostly done in shallow water (<10 m). The result of this study was also considered to be scientifically sufficient in terms of the reliability of the data, even though we did not use the most suitable method for the analysis of aerial images.…”