ALBERT

Description: Globally, seagrass habitats have experienced sharp declines over the past century, with an annual loss of seagrass cover of 7%yr-1 since 1990. Despite the attention to seagrass this decline has brought, little research has been directed towards trends of seagrass habitats in Singapore. The research presented here developed and applied remote sensing methods to partially fill this gap, provide tools for more extensive monitoring in the future, and contribute to the global body of seagrass research. Satellite images from four different satellite sensors were used to estimate seagrass bed extent in Singapore’s second largest seagrass meadow, at Pulau Semakau, from 2001 to 2013. Statistical estimates of image signal-to-noise ratios were used to screen images for quality. Validation data collected in 2013 were used to estimate error for supervised classifications produced from each sensor. A novel method was explored to account for macroalgae blooms in the study area, but the resulting correction could not be validated and did not affect the overall trends in seagrass bed extent. In addition to the classification analysis, an empirical model linking remote sensing reflectance to above-ground biomass was constructed to examine the distribution of seagrass within the meadow. Applied to WV2 images from 2011 and 2013, this model produced estimates of above-ground biomass with root mean squared error (RMSE) of 54 gm-2 and 44.7 gm-2, respectively, within ranges of 0-288 gm-2 and 0-229 gm-2, respectively. A novel index to measure seagrass density non-destructively was developed to help conservation and monitoring efforts. This index, normalized canopy index (NCI), was estimated from satellite imagery more precisely than above-ground biomass, producing estimates from the 2013 WV2 image corresponding to field data with an R2 of 0.71 relative to the R2 of 0.39 produced by the above-ground biomass model. This index may be a promising, non-destructive alternative to above-ground biomass for remote sensing studies and should be pursued further in future research. Based on the time-series classification analysis, seagrass bed extent at Pulau Semakau declined from over 44.6 ha in April 2002 to 25.3 ha in June 2013. This decline occurred at an average of 5.1%yr-1 from 2001 to 2013, although this rate of decline slowed to 3.7%yr-1 in 2012. These declines are likely representative of other seagrass habitats in Singapore. Broader monitoring is required to determine to what extent Singapore’s seagrasses are disappearing. Although seagrass bed extent declined by 17% from April 2011 to June 2013, over the same time period total above-ground biomass in the seagrass meadow declined only 5%, from 41.6 Mg to 39.6 Mg. Two acute sedimentation events recorded over this time period corresponded to a large and permanent decrease in bed extent captured by WV2 imagery and a small and temporary decrease in bed extent captured by ALI imagery. I hypothesize that the discrepancy in decreases in extent and biomass, coupled with an increase in median biomass, is attributable to preferential survival and recolonization of dense-biomass seagrass species during these sedimentation events. Measurements of seagrass species abundance during this time period provide support for this hypothesis. This exercise demonstrates the advantages and limitations of monitoring seagrass bed extent and above-ground biomass. Bed extent provides a measure of overall viability of a seagrass meadow, but above-ground biomass provides a better index of spatially variable health and internal change. Coupled, these two measurements provide greater insight into complex seagrass bed processes and seagrass response to disturbance.

Description: Masters