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

• Main Authors: Jerosch, Kerstin, Scharf, Frauke Katharina, Deregibus, Dolores, Campana, Gabriela L, Zacher-Aued, Katharina, Pehlke, Hendrik, Abele, Doris, Quartino, Maria Liliana
• Format: Article in Journal/Newspaper
• Language: English
• Published: PANGAEA 2015
• Subjects: Impact of climate induced glacier melt on marine coastal systems, Antarctica IMCOAST/IMCONet; Priority Programme 1158 Antarctic Research with Comparable Investigations in Arctic Sea Ice Areas SPP1158; Arctic; Antarctic; King George Island; Potter Cove; 25 de Mayo; isla 25 de Mayo; Antarc*; Antarctica; Climate change; Isla 25 de Mayo; Sea ice
• Online Access: https://dx.doi.org/10.1594/pangaea.854410; https://doi.pangaea.de/10.1594/PANGAEA.854410

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 ... : Subproject: JE 680/1-1 ...