Maps (pdf) and raster images (tif) of predicted rural land cover suitability under current (2010) conditions and future climate scenarios

This study projects land cover probabilities under climate change for corn (maize), soybeans, spring and winter wheat, winter wheat-soybean double cropping, cotton, grassland and forest across 16 central U.S. states at a high spatial resolution, while also taking into account the influence of soil characteristics and topography. The scenarios span three oceanic-atmospheric global circulation models, three Representative Concentration Pathways, and three time periods (2040, 2070, 2100). As climate change intensifies, the suitable area for all six crops display large northward shifts. Total suitable area for spring wheat, followed by corn and soybeans, diminish. Suitable area for winter wheat and for winter wheat-soybean double-cropping expand northward, while cotton suitability migrates to new, more northerly, locations. Suitability for forest intensifies in the south while yielding to crops in the north; grassland intensifies in the western Great Plains as crop suitability diminishes. To maintain current broad geographic patterns of land use, large changes in the thermal response of crops such as corn would be required. A transition from corn-soybean to winter wheat-soybean doubling cropping is an alternative adaptation.

Bulk sediment element analysis of sediment cores GeoB10065-9 and GeoB10065-7, offshore northwest Sumba Island, Indonesia

The Australian-Indonesian monsoon has a governing influence on the agricultural practices and livelihood in the highly populated islands of Indonesia. However, little is known about the factors that have influenced past monsoon activity in southern Indonesia. Here, we present a ~6000 years high-resolution record of Australian-Indonesian summer monsoon (AISM) rainfall variations based on bulk sediment element analysis in a sediment archive retrieved offshore northwest Sumba Island (Indonesia). The record suggests lower riverine detrital supply and hence weaker AISM rainfall between 6000 yr BP and ~3000 yr BP compared to the Late Holocene. We find a distinct shift in terrigenous sediment supply at around 2800 yr BP indicating a reorganization of the AISM from a drier Mid Holocene to a wetter Late Holocene in southern Indonesia. The abrupt increase in rainfall at around 2800 yr BP coincides with a grand solar minimum. An increase in southern Indonesian rainfall in response to a solar minimum is consistent with climate model simulations that provide a possible explanation of the underlying mechanism responsible for the monsoonal shift. We conclude that variations in solar activity play a significant role in monsoonal rainfall variability at multi-decadal and longer timescales. The combined effect of orbital and solar forcing explains important details in the temporal evolution of AISM rainfall during the last 6000 years. By contrast, we find neither evidence for volcanic forcing of AISM variability nor for a control by long-term variations in the El Niño-Southern Oscillation (ENSO).

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.