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.

Raster maps for 29 environmental variables in three geographical regions

Aim: Greater understanding of the processes underlying biological invasions is required to determine and predict invasion risk. Two subspecies of olive (Olea europaea subsp. europaea and Olea europaea subsp. cuspidata) have been introduced into Australia from the Mediterranean Basin and southern Africa during the 19th century. Our aim was to determine to what extent the native environmental niches of these two olive subspecies explain the current spatial segregation of the subspecies in their non-native range. We also assessed whether niche shifts had occurred in the non-native range, and examined whether invasion was associated with increased or decreased occupancy of niche space in the non-native range relative to the native range. Location: South-eastern Australia, Mediterranean Basin and southern Africa. Methods: Ecological niche models (ENMs) were used to quantify the similarity of native and non-native realized niches. Niche shifts were characterized by the relative contribution of niche expansion, stability and contraction based on the relative occupancy of environmental space by the native and non-native populations. Results: Native ENMs indicated that the spatial segregation of the two subspecies in their non-native range was partly determined by differences in their native niches. However, we found that environmentally suitable niches were less occupied in the non-native range relative to the native range, indicating that niche shifts had occurred through a contraction of the native niches after invasion, for both subspecies. Main conclusions: The mapping of environmental factors associated with niche expansion, stability or contraction allowed us to identify areas of greater invasion risk. This study provides an example of successful invasions that are associated with niche shifts, illustrating that introduced plant species are sometimes readily able to establish in novel environments. In these situations the assumption of niche stasis during invasion, which is implicitly assumed by ENMs, may be unreasonable.

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.

Cacao trees in tropical agroforestry landscapes of the Napu Valley in Central Sulawesi, Indonesia

All sample sites were situated at the northern tip of Napu Valley in Central Sulawesi, Indonesia. After an initial mapping of the study area, we selected 15 smallholder cacao plantations as sites for bird and bat exclosure experiments in March 2010. On each study site, we established 4 treatments for these exclosure experiments (bird exclosure - closed during daytime and open during night; bat exclosure - closed overnight and opened during daytime; full exclosure of both birds and bats - always closed and unmanipulated/open control treatments - always open). In each treatment, there were 2 cacao trees (total of 8 cacao trees per study site), surrounded by nylon filament (2x2 cm mesh size) that was opened and closed according to the activity period of day and night active flying vertebrates (05:00-06:00 am and 17:00-18:00 pm) on a daily basis. The mean tree height and diameter at breast height (dbh) result from two measures of all study trees at the beginning of the exclosure experiment (June 2010) and 6 months later (February 2011).

Maps and acoustic profiles of free gas distribution, Western Baltic Sea and Kattgat-Skagerrak area

A shallow gas depth-contour map covering the Skagerrak-western Baltic Sea region has been constructed using a relatively dense grid of existing shallow seismic lines. The digital map is stored as an ESRI shape file in order to facilitate comparison with other data from the region. Free gas usually occurs in mud and sandy mud but is observed only when sediment thickness exceeds a certain threshold value, depending on the water depth of the area in question. Gassy sediments exist at all water depths from approx. 20 m in the coastal waters of the Kattegat to 360 m in the Skagerrak. In spite of the large difference in water depths, the depth of free gas below seabed varies only little within the region, indicating a relatively fast movement of methane in the gas phase towards the seabed compared to the rate of diffusion of dissolved methane. Seeps of old microbial methane occur in the northern Kattegat where a relatively thin cover of sandy sediments exists over shallow, glacially deformed Pleistocene marine sediments. Previous estimates of total methane escape from the area may be correct but the extrapolation of local methane seepage rate data to much larger areas on the continental shelf is probably not justified. Preliminary data on porewater chemistry were compared with the free gas depth contours in the Aarhus Bay area, which occasionally suffers from oxygen deficiency, in order to examine if acoustic gas mapping may be used for monitoring the condition of the bay.

Global Ocean Biomes: Mean and time-varying maps (NetCDF 7.8 MB)

Large-scale studies of ocean biogeochemistry and carbon cycling have often partitioned the ocean into regions along lines of latitude and longitude despite the fact that spatially more complex boundaries would be closer to the true biogeography of the ocean. Herein, we define 17 open-ocean biomes classified from four observational data sets: sea surface temperature (SST), spring/summer chlorophyll a concentrations (Chl a), ice fraction, and maximum mixed layer depth (maxMLD) on a 1° × 1° grid. By considering interannual variability for each input, we create dynamic ocean biome boundaries that shift annually between 1998 and 2010. Additionally we create a core biome map, which includes only the grid cells that do not change biome assignment across the 13 years of the time-varying biomes. These biomes can be used in future studies to distinguish large-scale ocean regions based on biogeochemical function.