Secchi depth maps for the Baltic Sea, 2003-2012, with links to GeoTIFs

Secchi depth is a measure of water transparency. In the Baltic Sea region, Secchi depth maps are used to assess eutrophication and as input for habitat models. Due to their spatial and temporal coverage, satellite data would be the most suitable data source for such maps. But the Baltic Sea's optical properties are so different from the open ocean that globally calibrated standard models suffer from large errors. Regional predictive models that take the Baltic Sea's special optical properties into account are thus needed. This paper tests how accurately generalized linear models (GLMs) and generalized additive models (GAMs) with MODIS/Aqua and auxiliary data as inputs can predict Secchi depth at a regional scale. It uses cross-validation to test the prediction accuracy of hundreds of GAMs and GLMs with up to 5 input variables. A GAM with 3 input variables (chlorophyll a, remote sensing reflectance at 678 nm, and long-term mean salinity) made the most accurate predictions. Tested against field observations not used for model selection and calibration, the best model's mean absolute error (MAE) for daily predictions was 1.07 m (22%), more than 50% lower than for other publicly available Baltic Sea Secchi depth maps. The MAE for predicting monthly averages was 0.86 m (15%). Thus, the proposed model selection process was able to find a regional model with good prediction accuracy. It could be useful to find predictive models for environmental variables other than Secchi depth, using data from other satellite sensors, and for other regions where non-standard remote sensing models are needed for prediction and mapping. Annual and monthly mean Secchi depth maps for 2003-2012 come with this paper as Supplementary materials.

Habitat characteristics and energy budget of the ocean quahog (Arctica islandica)

We compared lifetime and population energy budgets of the extraordinary long-lived ocean quahog Arctica islandica from 6 different sites - the Norwegian coast, Kattegat, Kiel Bay, White Sea, German Bight, and off northeast Iceland - covering a temperature and salinity gradient of 4-10°C (annual mean) and 25-34, respectively. Based on von Bertalanffy growth models and size-mass relationships, we computed organic matter production of body (PSB) and of shell (PSS), whereas gonad production (PG) was estimated from the seasonal cycle in mass. Respiration (R) was computed by a model driven by body mass, temperature, and site. A. islandica populations differed distinctly in maximum life span (40 y in Kiel Bay to 197 y in Iceland), but less in growth performance (phi' ranged from 2.41 in the White Sea to 2.65 in Kattegat). Individual lifetime energy throughput, as approximated by assimilation, was highest in Iceland (43,730 kJ) and lowest in the White Sea (313 kJ). Net growth efficiency ranged between 0.251 and 0.348, whereas lifetime energy investment distinctly shifted from somatic to gonad production with increasing life span; PS/PG decreased from 0.362 (Kiel Bay, 40 y) to 0.031 (Iceland, 197 y). Population annual energy budgets were derived from individual budgets and estimates of population mortality rate (0.035/y in Iceland to 0.173/y in Kiel Bay). Relationships between budget ratios were similar on the population level, albeit with more emphasis on somatic production; PS/ PG ranged from 0.196 (Iceland) to 2.728 (White Sea), and P/B ranged from 0.203-0.285/y. Life span is the principal determinant of the relationship between budget parameters, whereas temperature affects net growth efficiency only. In the White Sea population, both growth performance and net growth efficiency of A. islandica were lowest. We presume that low temperature combined with low salinity represent a particularly stressful environment for this species.

Mapped cetacean habitat suitability and richness in the Azores, links to ArcGIS files

Marine spatial planning and ecological research call for high-resolution species distribution data. However, those data are still not available for most marine large vertebrates. The dynamic nature of oceanographic processes and the wide-ranging behavior of many marine vertebrates create further difficulties, as distribution data must incorporate both the spatial and temporal dimensions. Cetaceans play an essential role in structuring and maintaining marine ecosystems and face increasing threats from human activities. The Azores holds a high diversity of cetaceans but the information about spatial and temporal patterns of distribution for this marine megafauna group in the region is still very limited. To tackle this issue, we created monthly predictive cetacean distribution maps for spring and summer months, using data collected by the Azores Fisheries Observer Programme between 2004 and 2009. We then combined the individual predictive maps to obtain species richness maps for the same period. Our results reflect a great heterogeneity in distribution among species and within species among different months. This heterogeneity reflects a contrasting influence of oceanographic processes on the distribution of cetacean species. However, some persistent areas of increased species richness could also be identified from our results. We argue that policies aimed at effectively protecting cetaceans and their habitats must include the principle of dynamic ocean management coupled with other area-based management such as marine spatial planning.