Ensemble modellingmodeling of Antarctic macroalgal habitats exposed to glacial melt in a polar fjord

Macroalgae are the main primary producers in polar coastal regions and of major importance for the associated heterotrophic communities. On King George Island/Isla 25 de Mayo, West Antarctic Peninsula (WAP) several fjords undergo rapid glacial retreat in response to increasing atmospheric temperatures. Hence, extended meltwater plumes laden with suspended particulate matter (SPM) are generated that hamper primary production during the austral summer season. We used ensemble modeling to approximate changes in the benthic productivity of an Antarctic fjord as a function of SPM discharge. A set of environmental variables was statistically selected and an ensemble of correlative species-distribution models was devised to project scattered georeferenced observation data to a spatial distribution of macroalgae for a “time of measurement” (“tom”) scenario (2008-2015). The model achieved statistically reliable validation results (true scale statistics 0.833, relative operating characteristics 0.975) and explained more than 60% of the modeled macroalgae distribution with the variables “hard substrate” and “SPM”. This “tom” scenario depicts a macroalgae cover of approx. 8% (63 ha) for the total study area (8 km2) and a summer production of approximately 350 t dry weight. Assuming a linear increase of meltwater SPM load over time, two past (1991 and 1998) and two future (2019 and 2026) simulations with varying SPM intensities were applied. The simulation using only 50% of the “tom” scenario SPM amount (simulating 1991) resulted in increased macroalgal distribution (143 ha) and a higher summer production (792 t) compared to the “tom” status and could be validated using historical data. Forecasting the year 2019 from the “tom” status, an increase of 25% SPM results in a predicted reduction of macroalgae summer production to approximately 60% (141 t). We present a first quantitative model for changing fjordic macroalgal production under continued melt conditions at WAP. As meltwater influenced habitats are extending under climate change conditions, our approach can serve to approximate future productivity shifts for WAP fjord systems. The reduction of macroalgal productivity as predicted for Potter Cove may have significant consequences for polar coastal ecosystems under continuing climate change

What is available and who does it? Metadata available for German-Argentinian Cooperation compiled during IMCOAST/IMCONET Project: 25 Years of investigation in Potter Cove, Carlini Station, King George Island (Isla 25 de Mayo)

A meta data compilation available in Pangaea, papers or row data of main investigations during the IMCOAST\IMCONET Project (1991-2016) in Potter Cove, Carlini Station, King George Island (Isla 25 de Mayo). This includes environmental (metereology, geochemistry, chemistry, biogeochemistry, light (PAR,kd), webcam, suspended matter, CTD) and biological variables. Map picture available and Shapefile for ArcGis (Projection WGS 1984 UTM21S)

Sea surface and the sea floor regionalization of the Southern Ocean by multivariate cluster analysis, links to ArcGIS project files

This study subdivides the Weddell Sea, 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 uses 28 environmental variables for the sea surface, 25 variables for the seabed and 9 variables for the analysis between surface and bottom variables. The data were taken during the years 1983-2013. Some data were interpolated. The statistical errors of several interpolation methods (e.g. IDW, Indicator, Ordinary and Co-Kriging) with changing settings have been compared for the identification of the most reasonable method. 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. For the seabed 8 and 12 clusters were identified as reasonable numbers for clustering the Weddell Sea. For the sea surface the numbers 8 and 13 and for the top/bottom analysis 8 and 3 were identified, respectively. Additionally, the results of 20 clusters are presented for the three alternatives offering the first small scale environmental regionalization of the Weddell Sea. Especially the results of 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

A geomorphological seabed classification for the Weddell Sea, Antarctica, with links to ArcGIS project files

Sea floor morphology plays an important role in many scientific disciplines such as ecology, hydrology and sedimentology since geomorphic features can act as physical controls for e.g. species distribution, oceanographically flow-path estimations or sedimentation processes. In this study, we provide a terrain analysis of the Weddell Sea based on the 500 m × 500 m resolution bathymetry data provided by the mapping project IBCSO. Seventeen seabed classes are recognized at the sea floor based on a fine and broad scale Benthic Positioning Index calculation highlighting the diversity of the glacially carved shelf. Beside the morphology, slope, aspect, terrain rugosity and hillshade were calculated. Applying zonal statistics to the geomorphic features identified unambiguously the shelf edge of the Weddell Sea with a width of 45-70 km and a mean depth of about 1200 m ranging from 270 m to 4300 m. A complex morphology of troughs, flat ridges, pinnacles, steep slopes, seamounts, outcrops, and narrow ridges, structures with approx. 5-7 km width, build an approx. 40-70 km long swath along the shelf edge. The study shows where scarps and depressions control the connection between shelf and abyssal and where high and low declination within the scarps e.g. occur. For evaluation purpose, 428 grain size samples were added to the seabed class map. The mean values of mud, sand and gravel of those samples falling into a single seabed class was calculated, respectively, and assigned to a sediment texture class according to a common sediment classification scheme

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

High resolution bathymetric compilation for Potter Cove, WAP, Antarctica, with links to data in ArcGIS format

The bathymetry raster with a resolution of 5 m x 5 m was processed from unpublished single beam data from the Argentine Antarctica Institute (IAA, 2010) and multibeam data from the United Kingdom Hydrographic Office (UKHO, 2012) with a cell size of 5 m x 5 m. A coastline digitized from a satellite image (DigitalGlobe, 2014) supplemented the interpolation process. The 'Topo to Raster' tool in ArcMap 10.3 was used to merge the three data sets, while the coastline represented the 0-m-contour to the interpolation process ('contour type option')

Ensemble prediction distribution maps of macroalgae for current conditions and four climate change scenarios and high resultion bathymetry for Potter Cove, WAP, Antarctica

Species distribution models (SDM) predict species occurrence based on statistical relationships with environmental conditions. The R-package biomod2 which includes 10 different SDM techniques and 10 different evaluation methods was used in this study. Macroalgae are the main biomass producers in Potter Cove, King George Island (Isla 25 de Mayo), Antarctica, and they are sensitive to climate change factors such as suspended particulate matter (SPM). Macroalgae presence and absence data were used to test SDMs suitability and, simultaneously, to assess the environmental response of macroalgae as well as to model four scenarios of distribution shifts by varying SPM conditions due to climate change. According to the averaged evaluation scores of Relative Operating Characteristics (ROC) and True scale statistics (TSS) by models, those methods based on a multitude of decision trees such as Random Forest and Classification Tree Analysis, reached the highest predictive power followed by generalized boosted models (GBM) and maximum-entropy approaches (Maxent). The final ensemble model used 135 of 200 calculated models (TSS > 0.7) and identified hard substrate and SPM as the most influencing parameters followed by distance to glacier, total organic carbon (TOC), bathymetry and slope. The climate change scenarios show an invasive reaction of the macroalgae in case of less SPM and a retreat of the macroalgae in case of higher assumed SPM values

The potential macroalgae habitat shifts in an Antarctic Peninsula fjord due to climate change

The Western Antarctic Peninsula (WAP) region is one of the most rapidly warming on earth since the last 50 yr. The WAP glaciers currently contribute one third of the melt water to global sea level rise. Climate warming is supposed to induce important changes in polar ecosystems, from microbial communities to apex predators’ levels. Macroalgae are the main biomass producers in Potter Cove located at King George Island, the biggest island of the South Shetland Arc. They are sensitive to climate change factors such as suspended particulate matter (SPM). Macroalgae presence and absence data were used to test SDMs suitability and, simultaneously, to assess the environmental response of macroalgae as well as to model four scenarios of distribution shifts by varying SPM conditions due to climate change. Species distribution models (SDM) predict species occurrence based on statistical relationships with environmental conditions. The R-package ‘biomod2’ which includes 10 different SDM techniques and 10 different evaluation methods was used in this study. According to the averaged evaluation scores of Relative Operating Characteristics (ROC) and True scale statistics (TSS) by models, those methods based on a multitude of decision trees such as Random Forest and Classification Tree Analysis, reached the highest predictive power followed by generalized boosted models (GBM) and maximum-entropy approaches (Maxent). The final ensemble model (EM) used 135 of 200 calculated models (TSS > 0.7) and identified hard substrate and SPM as the most influencing parameters followed by distance to glacier, total organic carbon (TOC), bathymetry and slope. The modeled current status of macroalgae distribution results in only 18.25% of earlier estimated areas populated by macroalgae in Potter Cove. The climate change scenarios show an invasive reaction of the macroalgae in case of less SPM and a retreat of the macroalgae in case of higher assumed SPM values