Spatial analysis of marine categorical information using indicator kriging applied to georeferenced video mosaics of the deep-sea Håkon Mosby Mud Volcano

Default versus Configured-Geostatistical Modeling of Suspended Particulate Matter in Potter Cove, West Antarctic Peninsula

The glacier retreat observed during the last decades at Potter Cove (PC) causes an increasing amount of suspended particulate matter (SPM) in the water column, which has a high impact on sessile filter feeder’ species at PC located at the West Antarctic Peninsula. SPM presents a highly-fluctuating dynamic pattern on a daily, monthly, seasonal, and interannual basis. Geostatistical interpolation techniques are widely used by default to generate reliable spatial information and thereby to improve the ecological understanding of environmental variables, which is often fundamental for guiding decision-makers and scientists. In this study, we compared the results of default and configured settings of three geostatistical algorithms (Simple Kriging, Ordinary Kriging, and Empirical Bayesian) and developed a performance index. In order to interpolate SPM data from the summer season 2010/2011 at PC, the best performance was obtained with Empirical Bayesian Kriging (standard mean = −0.001 and root mean square standardized = 0.995). It showed an excellent performance (performance index = 0.004), improving both evaluation parameters when radio and neighborhood were configured. About 69% of the models showed improved standard means when configured compared to the default settings following a here proposed guideline.

Assessing the impact of fishing in shallow rocky reefs: a multivariate approach to ecosystem management

In this paper we develop a tool to assess the impact of fishing on ecosystem functioning in shallow rocky reefs. The relationships between biological parameters (fishes, sea urchins, seaweeds), and fishing activities (fish traps, boats, land-based fishing, spearfishing) were tested in La Palma island (Canary Islands). Data from fishing activities and biological parameters were analyzed using principal component analyses. We produced two models using the first component of these analyses. This component was interpreted as a new variable that described the fishing pressure and the conservation status at each studied site. Subsequently the scores on the first axis were mapped using universal kriging methods and the models obtained were extrapolated across the whole island to display the expected fishing pressure and conservation status more widely. The fishing pressure and conservation status models were spatially related; zones where fishing pressure was high coincided with zones in the unhealthiest ecological state.

Using decision trees to predict benthic communities within and near the German Exclusive Economic Zone (EEZ) of the North Sea

In this article a concept is described in order to predict and map the occurrence of benthic communities within and near the German Exclusive Economic Zone (EEZ) of the North Sea. The approach consists of two work steps: (1) geostatistical analysis of abiotic measurement data and (2) calculation of benthic provinces by means of Classification and Regression Trees (CART) and GIS-techniques. From bottom water measurements on salinity, temperature, silicate and nutrients as well as from punctual data on grain size ranges (0-20, 20-63, 63-2,000 mu) raster maps were calculated by use of geostatistical methods. At first the autocorrelation structure was examined and modelled with help of variogram analysis. The resulting variogram models were then used to calculate raster maps by applying ordinary kriging procedures. After intersecting these raster maps with punctual data on eight benthic communities a decision tree was derived to predict the occurrence of these communities within the study area. Since such a CART tree corresponds to a hierarchically ordered set of decision rules it was applied to the geostatistically estimated raster data to predict benthic habitats within and near the EEZ.