Probability inundation map for a scenario combining storm surge and sea-level rise

Coastal managers require reliable spatial data on the extent and timing of potential coastal inundation, particularly in a changing climate. Most sea level rise (SLR) vulnerability assessments are undertaken using the easily implemented bathtub approach, where areas adjacent to the sea and below a given elevation are mapped using a deterministic line dividing potentially inundated from dry areas. This method only requires elevation data usually in the form of a digital elevation model (DEM). However, inherent errors in the DEM and spatial analysis of the bathtub model propagate into the inundation mapping. The aim of this study was to assess the impacts of spatially variable and spatially correlated elevation errors in high-spatial resolution DEMs for mapping coastal inundation. Elevation errors were best modelled using regression-kriging. This geostatistical model takes the spatial correlation in elevation errors into account, which has a significant impact on analyses that include spatial interactions, such as inundation modelling. The spatial variability of elevation errors was partially explained by land cover and terrain variables. Elevation errors were simulated using sequential Gaussian simulation, a Monte Carlo probabilistic approach. 1,000 error simulations were added to the original DEM and reclassified using a hydrologically correct bathtub method. The probability of inundation to a scenario combining a 1 in 100 year storm event over a 1 m SLR was calculated by counting the proportion of times from the 1,000 simulations that a location was inundated. This probabilistic approach can be used in a risk-aversive decision making process by planning for scenarios with different probabilities of occurrence. For example, results showed that when considering a 1% probability exceedance, the inundated area was approximately 11% larger than mapped using the deterministic bathtub approach. The probabilistic approach provides visually intuitive maps that convey uncertainties inherent to spatial data and analysis.

Environmental variables and multivariate seabed classification maps via k means clustering of Potter Cove, Antarctica, link to input and result files in GeoTIFF format

This study subdivides the Potter Cove, King George Island, Antarctica, into seafloor regions using multivariate statistical methods. These regions are categories used for comparing, contrasting and quantifying biogeochemical processes and biodiversity between ocean regions geographically but also regions under development within the scope of global change. The division obtained is characterized by the dominating components and interpreted in terms of ruling environmental conditions. The analysis includes in total 42 different environmental variables, interpolated based on samples taken during Australian summer seasons 2010/2011 and 2011/2012. The statistical errors of several interpolation methods (e.g. IDW, Indicator, Ordinary and Co-Kriging) with changing settings have been compared and the most reasonable method has been applied. The multivariate mathematical procedures used are regionalized classification via k means cluster analysis, canonical-correlation analysis and multidimensional scaling. Canonical-correlation analysis identifies the influencing factors in the different parts of the cove. Several methods for the identification of the optimum number of clusters have been tested and 4, 7, 10 as well as 12 were identified as reasonable numbers for clustering the Potter Cove. Especially the results of 10 and 12 clusters identify marine-influenced regions which can be clearly separated from those determined by the geological catchment area and the ones dominated by river discharge.

Resilience to temperature and pH changes in a future climate change scenario in six strains of the polar diatom Fragilariopsis cylindrus

The effects of ocean acidification and increased temperature on physiology of six strains of the polar diatom Fragilariopsis cylindrus from Greenland were investigated. Experiments were performed under manipulated pH levels (8.0, 7.7, 7.4, and 7.1) and different temperatures (1, 5, and 8 °C) to simulate changes from present to plausible future levels. Each of the 12 scenarios was run for 7 days, and a significant interaction between temperature and pH on growth was detected. By combining increased temperature and acidification, the two factors counterbalanced each other, and therefore no effect on the growth rates was found. However, the growth rates increased with elevated temperatures by 20-50% depending on the strain. In addition, a general negative effect of increasing acidification on growth was observed. At pH 7.7 and 7.4, the growth response varied considerably among strains. However, a more uniform response was detected at pH 7.1 with most of the strains exhibiting reduced growth rates by 20-37% compared to pH 8.0. It should be emphasized that a significant interaction between temperature and pH was found, meaning that the combination of the two parameters affected growth differently than when considering one at a time. Based on these results, we anticipate that the polar diatom F. cylindrus will be unaffected by changes in temperature and pH within the range expected by the end of the century. In each simulated scenario, the variation in growth rates among the strains was larger than the variation observed due to the whole range of changes in either pH or temperature. Climate change may therefore not affect the species as such, but may lead to changes in the population structure of the species, with the strains exhibiting high phenotypic plasticity, in terms of temperature and pH tolerance towards future conditions, dominating the population.

Effects of ocean acidification on growth and physiology of Ulva lactuca (Chlorophyta) in a rockpool-scenario, link to supplementary data

Rising atmospheric CO2-concentrations will have severe consequences for a variety of biological processes. We investigated the responses of the green alga Ulva lactuca (Linnaeus) to rising CO2-concentrations in a rockpool scenario. U. lactuca was cultured under aeraton with air containing either preindustrial pCO2 (280µatm) or for the end of the 21st century predicted (700µatm) pCO2 for 31 days. We addressed the following question: Will elevated CO2-concentrations affect photosynthesis (net photosynthesis, rETR(max), Fv/Fm, pigment composition) and growth of U. lactuca in rockpools with limited water exchange? Two phases of the experiment were distinguished: In the initial phase (day 1-4) the Seawater Carbonate System (SWCS) of the culture medium could be adjusted to the selected atmospheric pCO2 condition by continuous aeration with target pCO2 values. In the second phase (day 4-31) the SWCS was largely determined by the metabolism of the growing U. lactuca biomass. In the initial phase, Fv/Fm and rETR(max) were only slightly elevated at high CO2-concentrations whereas growth was significantly enhanced. After 31 days the Chl a content of the thalli was significantly lower under future conditions and the photosynthesis of thalli grown under preindustrial conditions was not dependent on external carbonic anhydrase. Biomass increased significantly at high CO2-concentrations. At low CO2-concentrations most adult thalli disintegrated between day 14 and 21, whereas at high CO2-concentrations most thalli remained integer until day 31. Thallus disintegration at low CO2-concentrations was mirrored in a drastic decline in seawater DIC and HCO3-. Accordingly, the SWCS differed significantly between the treatments. Our results indicated a slight enhancement of photosynthetic performance and significantly elevated growth of U. lactuca at future CO2-concentrations. The accelerated thallus disintegration at high CO2-concentrations under conditions of limited water exchange indicates additional CO2 effects on the life cycle of U. lactuca when living in rockpools.