Calculated sea surface temperatures of two sediment cores

The reconstruction of ocean history employs a large variety of methods with origins in the biological, chemical, and physical sciences, and uses modern statistical techniques for the interpretation of extensive and complex data sets. Various sediment properties deliver useful information for reconstructing environmental parameters. Those properties that have a close relationship to environmental parameters are called ''proxy variables'' (''proxies'' for short). Proxies are measurable descriptors for desired (but unobservable) variables. Surface water temperature is probably the most important parameter for describing the conditions of past oceans and is crucial for climate modelling. Proxies for temperature are: abundance of microfossils dwelling in surface waters, oxygen isotope composition of planktic foraminifers, the ratio of magnesium or strontium to calcium in calcareous shells or the ratio of certain organic molecules (e.g. alkenones produced by coccolithophorids). Surface water salinity, which is important in modelling of ocean circulation, is much more difficult to reconstruct. At present there is no established method for a direct determination of this parameter. Measurements associated with the paleochemistry of bottom waters to reconstruct bottom water age and flow are made on benthic foraminifers, ostracodes, and deep-sea corals. Important geochemical tracers are d13C and Cd/Ca ratios. When using benthic foraminifers, knowledge of the sediment depth habitat of species is crucial. Reconstructions of productivity patterns are of great interest because of important links to current patterns, mixing of water masses, wind, the global carbon cycle, and biogeography. Productivity is reflected in the flux of carbon into the sediment. There are a number of fluxes other than those of organic carbon that can be useful in assessing productivity fluctuations. Among others, carbonate and opal flux have been used, as well as particulate barite. Furthermore, microfossil assemblages contain clues to the intensity of production as some species occur preferentially in high-productivity regions while others avoid these. One marker for the fertility of sub-surface waters (that is, nutrient availability) is the carbon isotope ratio within that water (13C/12C, expressed as d13C). Carbon isotope ratios in today's ocean are negatively correlated with nitrate and phosphate contents. Another tracer of phosphate content in ocean waters is the Cd/Ca ratio. The correlation between this ratio and phosphate concentrations is quite well documented. A rather new development to obtain clues on ocean fertility (nitrate utilization) is the analysis of the 15N/14N ratio in organic matter. The fractionation dynamics are analogous to those of carbon isotopes. These various ratios are captured within the organisms growing within the tagged water. A number of reconstructions of the partial pressure of CO2 have been attempted using d13C differences between planktic and benthic foraminifers and d13C values of bulk organic material or individual organic components. To define the carbon system in sea water, two elements of the system have to be known in addition to temperature. These can be any combination of total CO2 , alkalinity, or pH. To reconstruct pH, the boron isotope composition of carbonates has been used. Ba patterns have been used to infer the distribution of alkalinity in past oceans. Information relating to atmospheric circulationand climate is transported to the ocean by wind or rivers, in the form of minerals or as plant andanimal remains. The most useful tracers in this respect are silt-sized particles and pollen.

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.

Land cover classification of Samoylov Island and Landsat subpixel water cover of Lena River Delta, Siberia, with links to ESRI grid files

Ignoring small-scale heterogeneities in Arctic land cover may bias estimates of water, heat and carbon fluxes in large-scale climate and ecosystem models. We investigated subpixel-scale heterogeneity in CHRIS/PROBA and Landsat-7 ETM+ satellite imagery over ice-wedge polygonal tundra in the Lena Delta of Siberia, and the associated implications for evapotranspiration (ET) estimation. Field measurements were combined with aerial and satellite data to link fine-scale (0.3 m resolution) with coarse-scale (upto 30 m resolution) land cover data. A large portion of the total wet tundra (80%) and water body area (30%) appeared in the form of patches less than 0.1 ha in size, which could not be resolved with satellite data. Wet tundra and small water bodies represented about half of the total ET in summer. Their contribution was reduced to 20% in fall, during which ET rates from dry tundra were highest instead. Inclusion of subpixel-scale water bodies increased the total water surface area of the Lena Delta from 13% to 20%. The actual land/water proportions within each composite satellite pixel was best captured with Landsat data using a statistical downscaling approach, which is recommended for reliable large-scale modelling of water, heat and carbon exchange from permafrost landscapes.