Time-series of seagrass and land cover maps from 1972 to 2010, in South East Queensland, Australia, with links to GeoTIFFs

Long term global archives of high-moderate spatial resolution, multi-spectral satellite imagery are now readily accessible, but are not being fully utilised by management agencies due to the lack of appropriate methods to consistently produce accurate and timely management ready information. This work developed an object-based remote sensing approach to map land cover and seagrass distribution in an Australian coastal environment for a 38 year Landsat image time-series archive (1972-2010). Landsat Multi-Spectral Scanner (MSS), Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) imagery were used without in situ field data input (but still using field knowledge) to produce land and seagrass cover maps every year data were available, resulting in over 60 map products over the 38 year archive. Land cover was mapped annually using vegetation, bare ground, urban and agricultural classes. Seagrass distribution was also mapped annually, and in some years monthly, via horizontal projected foliage cover classes, sand and deep water. Land cover products were validated using aerial photography and seagrass maps were validated with field survey data, producing several measures of accuracy. An average overall accuracy of 65% and 80% was reported for seagrass and land cover products respectively, which is consistent with other studies in the area. This study is the first to show moderate spatial resolution, long term annual changes in land cover and seagrass in an Australian environment, created without the use of in situ data; and only one of a few similar studies globally. The land cover products identify several long term trends; such as significant increases in South East Queensland's urban density and extent, vegetation clearing in rural and rural-residential areas, and inter-annual variation in dry vegetation types in western South East Queensland. The seagrass cover products show that there has been a minimal overall change in seagrass extent, but that seagrass cover level distribution is extremely dynamic; evidenced by large scale migrations of higher seagrass cover levels and several sudden and significant changes in cover level. These mapping products will allow management agencies to build a baseline assessment of their resources, understand past changes and help inform implementation and planning of management policy to address potential future changes.

Experimental results for Ecklonia radiata growth and in situ incubation experiments and in situ measurements of pH within E. radiata beds in south eastern Tasmania

Ocean acidification (OA) is the reduction in seawater pH due to the absorption of human-released CO2 by the world's oceans. The average surface oceanic pH is predicted to decline by 0.4 units by 2100. However, kelp metabolically modifies seawater pH via photosynthesis and respiration in some temperate coastal systems, resulting in daily pH fluctuations of up to ±0.45 units. It is unknown how these fluctuations in pH influence the growth and physiology of the kelp, or how this might change with OA. In laboratory experiments that mimicked the most extreme pH fluctuations measured within beds of the canopy-forming kelp Ecklonia radiata in Tasmania, the growth and photosynthetic rates of juvenile E. radiata were greater under fluctuating pH (8.4 in the day, 7.8 at night) than in static pH treatments (8.4, 8.1, 7.8). However, pH fluctuations had no effect on growth rates and a negative effect on photosynthesis when the mean pH of each treatment was reduced by 0.3 units. Currently, pH fluctuations have a positive effect on E. radiata but this effect could be reversed in the future under OA, which is likely to impact the future ecological dynamics and productivity of habitats dominated by E. radiata.

Distribution of coccoliths in surface sediments of the south-eastern South Atlantic Ocean

Recent coccoliths from 52 surface sediment samples recovered from the south-eastern South Atlantic were examined qualitatively and quantitatively in order to assess the controlling mechanisms for their distribution patterns, such as ecological and preservational factors, and their role as carbonate producers. Total coccolith abundances range from 0.2 to 39.9 coccoliths*10**9/ g sediment. Four assemblages can be delineated by their coccolith content characterising the northern Benguela, the middle to southern Benguela, the Walvis Ridge and the deeper water. Distinctions are based on multivariate ordination techniques applied on the relative abundances of the most abundant taxa, Emiliania huxleyi, Calcidiscus leptoporus, Gephyrocapsa spp., Coccolithus pelagicus and subtropical to tropical species. The coccolith distribution seems to be temperature and nutrient controlled co-varying with the seaward extension of the upwelling filament zone in the Benguela. A preservation index (CEX') based on the differential dissolution behaviour of the delicate E. huxleyi and Gephyrocapsa ericsonii versus the robust C. leptoporus is applied in order to detect the position of the coccolith lysocline. Although some samples were recognised as dissolution-affected, the distribution of the coccoliths in the surface-sediments reflects the different oceanographic surface-water conditions. Mass estimations of the coccolith carbonate reveal coccoliths to be only minor contributors to the carbonate preserved in the surface sediments. The mean computed coccolith carbonate content is 17 wt.%, equivalent to a mean contribution of 23% to the bulk carbonate.

Multi-temporal mapping of seagrass cover, species and biomass of the Eastern Banks, Moreton Bay, Australia, with links to shapefiles

The spatial and temporal dynamics of seagrasses have been studied from the leaf to patch (100 m**2) scales. However, landscape scale (> 100 km**2) seagrass population dynamics are unresolved in seagrass ecology. Previous remote sensing approaches have lacked the temporal or spatial resolution, or ecologically appropriate mapping, to fully address this issue. This paper presents a robust, semi-automated object-based image analysis approach for mapping dominant seagrass species, percentage cover and above ground biomass using a time series of field data and coincident high spatial resolution satellite imagery. The study area was a 142 km**2 shallow, clear water seagrass habitat (the Eastern Banks, Moreton Bay, Australia). Nine data sets acquired between 2004 and 2013 were used to create seagrass species and percentage cover maps through the integration of seagrass photo transect field data, and atmospherically and geometrically corrected high spatial resolution satellite image data (WorldView-2, IKONOS and Quickbird-2) using an object based image analysis approach. Biomass maps were derived using empirical models trained with in-situ above ground biomass data per seagrass species. Maps and summary plots identified inter- and intra-annual variation of seagrass species composition, percentage cover level and above ground biomass. The methods provide a rigorous approach for field and image data collection and pre-processing, a semi-automated approach to extract seagrass species and cover maps and assess accuracy, and the subsequent empirical modelling of seagrass biomass. The resultant maps provide a fundamental data set for understanding landscape scale seagrass dynamics in a shallow water environment. Our findings provide proof of concept for the use of time-series analysis of remotely sensed seagrass products for use in seagrass ecology and management.