Carbonate chemistry, community metabolism, PAR, temperature and salinity of One Tree Island reef

There are few in situ studies showing how net community calcification (Gnet) of coral reefs is related to carbonate chemistry, and the studies to date have demonstrated different predicted rates of change. In this study, we measured net community production (Pnet), Gnet, and carbonate chemistry of a reef flat at One Tree Island, Great Barrier Reef. Diurnal pCO2 variability of 289-724 µatm was driven primarily by photosynthesis and respiration. The reef flat was found to be net autotrophic, with daily production of ? 35 mmol C/m**2/d and net calcification of ? 33 mmol C/m**2/d . Gnet was strongly related to Pnet, which drove a hysteresis pattern in the relationship between Gnet and aragonite saturation state (Omega ar). Although Pnet was the main driver of Gnet, Omega ar was still an important factor, where 95% of the variance in Gnet could be described by Pnet and Omega ar. Based on the observed in situ relationship, Gnet would be expected to reach zero when Omega ar is 2.5. It is unknown what proportion of a decline in Gnet would be through reduced calcification and what would occur through increased dissolution, but the results here support predictions that overall calcium carbonate production will decline in coral reefs as a result of ocean acidification.

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.