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.

Genotypic data for nine microsatellite loci for the seagrass Zostera muelleri collections from Lake Macquarie, NSW, Australia

Seagrasses are ecosystem engineers that offer important habitat for a large number of species and provide a range of ecosystem services. Many seagrass ecosystems are dominated by a single species; with research showing that genotypic diversity at fine spatial scales plays an important role in maintaining a range of ecosystem functions. However, for most seagrass species, information on fine-scale patterns of genetic variation in natural populations is lacking. In this study we use a hierarchical sampling design to determine levels of genetic and genotypic diversity at different spatial scales (centimeters, meters, kilometers) in the Australian seagrass Zostera muelleri. Our analysis shows that at fine-spatial scales (< 1 m) levels of genotypic diversity are relatively low (R (Plots) = 0.37 ± 0.06 SE), although there is some intermingling of genotypes. At the site (10's m) and meadow location (km) scale we found higher levels of genotypic diversity (R (sites) = 0.79 ± 0.04 SE; R (Locations) = 0.78 ± 0.04 SE). We found some sharing of genotypes between sites within meadows, but no sharing of genotypes between meadow locations. We also detected a high level of genetic structuring between meadow locations (FST = 0.278). Taken together, our results indicate that both sexual and asexual reproduction are important in maintaining meadows of Z. muelleri. The dominant mechanism of asexual reproduction appears to occur via localised rhizome extension, although the sharing of a limited number of genotypes over the scale of 10's of metres could also result from the localised dispersal and recruitment of fragments. The large number of unique genotypes at the meadow scale indicates that sexual reproduction is important in maintaining these populations, while the high level of genetic structuring suggests little gene flow and connectivity between our study sites. These results imply that recovery from disturbances will occur through both sexual and asexual regeneration, but the limited connectivity at the landscape-scale implies that recovery at meadow-scale losses is likely to be limited.

Hydrochemistry, water level, and discharge of water from Samoylov Island, Lena Delta, northeastern Siberia, in 2008

Although ponds make up roughly half of the total area of surface water in permafrost landscapes, their relevance to carbon dioxide emissions on a landscape scale has, to date, remained largely unknown. We have therefore investigated the inflows and outflows of dissolved organic and inorganic carbon from lakes, ponds, and outlets on Samoylov Island, in the Lena Delta of northeastern Siberia in September 2008, together with their carbon dioxide emissions. Outgassing of carbon dioxide (CO2) from these ponds and lakes, which cover 25% of Samoylov Island, was found to account for between 74 and 81% of the calculated net landscape-scale CO2 emissions of 0.2-1.1 g C/m**2/d during September 2008, of which 28-43% was from ponds and 27-46% from lakes. The lateral export of dissolved carbon was negligible compared to the gaseous emissions due to the small volumes of runoff. The concentrations of dissolved inorganic carbon in the ponds were found to triple during freezeback, highlighting their importance for temporary carbon storage between the time of carbon production and its emission as CO2. If ponds are ignored the total summer emissions of CO2-C from water bodies of the islands within the entire Lena Delta (0.7-1.3 Tg) are underestimated by between 35 and 62%.

Drivers of multi-scale plant community structure in agricultural field margins of South Korea

This data set describes the distribution of a total of 90 plant species growing on field margins of an agricultural landscape in the Haean-myun catchment in South Korea. We conducted our survey between July and August 2011 in 100 sampling plots, covering the whole catchment. In each plot we measured three environmental variables: slope, width of the field margin, and management type (i.e. "managed" for field margins that had signs of management activities from the ongoing season such as cutting or spraying herbicides and "unmanaged" for field margins that had been left untouched in the season). For the botanical survey each plot was sampled using three subplots of one square meter per subplot; subplots were 4 m apart from each other. In each subplot, we estimated three different vegetation characteristics: vegetation cover (i.e. the percentage of ground covered by vegetation), species richness (i.e. the number of observed species) and species abundance (i.e. the number of observed individuals / species). We calculated the percentage of the non-farmed habitats by creating buffer zones of 100, 200, 300, 400 and 500 m radii around each plot using data provided by (Seo et al. 2014). Non-farmed habitats included field margins, fallows, forest, riparian areas, pasture and grassland.