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.

(Figure 2) Mean discharge per day (total and baseflow part) of the San Francisco River and daily precipitation at station ECPL (Planta), in 2007

We investigated controls on the water chemistry of a South Ecuadorian cloud forest catchment which is partly pristine, and partly converted to extensive pasture. From April 2007 to May 2008 water samples were taken weekly to biweekly at nine different subcatchments, and were screened for differences in electric conductivity, pH, anion, as well as element composition. A principal component analysis was conducted to reduce dimensionality of the data set and define major factors explaining variation in the data. Three main factors were isolated by a subset of 10 elements (Ca2+, Ce, Gd, K+, Mg2+, Na+, Nd, Rb, Sr, Y), explaining around 90% of the data variation. Land-use was the major factor controlling and changing water chemistry of the subcatchments. A second factor was associated with the concentration of rare earth elements in water, presumably highlighting other anthropogenic influences such as gravel excavation or road construction. Around 12% of the variation was explained by the third component, which was defined by the occurrence of Rb and K and represents the influence of vegetation dynamics on element accumulation and wash-out. Comparison of base- and fast flow concentrations led to the assumption that a significant portion of soil water from around 30 cm depth contributes to storm flow, as revealed by increased rare earth element concentrations in fast flow samples. Our findings demonstrate the utility of multi-tracer principal component analysis to study tropical headwater streams, and emphasize the need for effective land management in cloud forest catchments.

(Tables 1-3) Water chemistry of cloud forest streams at baseflow conditions, Rio San Francisco, Ecuador

We investigated controls on the water chemistry of a South Ecuadorian cloud forest catchment which is partly pristine, and partly converted to extensive pasture. From April 2007 to May 2008 water samples were taken weekly to biweekly at nine different subcatchments, and were screened for differences in electric conductivity, pH, anion, as well as element composition. A principal component analysis was conducted to reduce dimensionality of the data set and define major factors explaining variation in the data. Three main factors were isolated by a subset of 10 elements (Ca2+, Ce, Gd, K+, Mg2+, Na+, Nd, Rb, Sr, Y), explaining around 90% of the data variation. Land-use was the major factor controlling and changing water chemistry of the subcatchments. A second factor was associated with the concentration of rare earth elements in water, presumably highlighting other anthropogenic influences such as gravel excavation or road construction. Around 12% of the variation was explained by the third component, which was defined by the occurrence of Rb and K and represents the influence of vegetation dynamics on element accumulation and wash-out. Comparison of base- and fast flow concentrations led to the assumption that a significant portion of soil water from around 30 cm depth contributes to storm flow, as revealed by increased rare earth element concentrations in fast flow samples. Our findings demonstrate the utility of multi-tracer principal component analysis to study tropical headwater streams, and emphasize the need for effective land management in cloud forest catchments.

Half-degree gridded nitrogen and phosphorus fertilizer use for global agriculture production during 1900-2013

In addition to enhance agricultural productivity, synthetic nitrogen (N) and phosphorous (P) fertilizer application in croplands dramatically altered global nutrient budget, water quality, greenhouse gas balance, and their feedbacks to the climate system. However, due to the lack of geospatial fertilizer input data, current Earth system/land surface modeling studies have to ignore or use over-simplified data (e.g., static, spatially uniform fertilizer use) to characterize agricultural N and P input over decadal or century-long period. We therefore develop a global time-series gridded data of annual synthetic N and P fertilizer use rate in croplands, matched with HYDE 3,2 historical land use maps, at a resolution of 0.5º latitude by longitude during 1900-2013. Our data indicate N and P fertilizer use rates increased by approximately 8 times and 3 times, respectively, since the year 1961, when IFA (International Fertilizer Industry Association) and FAO (Food and Agricultural Organization) survey of country-level fertilizer input were available. Considering cropland expansion, increase of total fertilizer consumption amount is even larger. Hotspots of agricultural N fertilizer use shifted from the U.S. and Western Europe in the 1960s to East Asia in the early 21st century. P fertilizer input show the similar pattern with additional hotspot in Brazil. We find a global increase of fertilizer N/P ratio by 0.8 g N/g P per decade (p< 0.05) during 1961-2013, which may have important global implication of human impacts on agroecosystem functions in the long run. Our data can serve as one of critical input drivers for regional and global assessment on agricultural productivity, crop yield, agriculture-derived greenhouse gas balance, global nutrient budget, land-to-aquatic nutrient loss, and ecosystem feedback to the climate system.

Towards convection-resolving, global atmospheric simulations with the Model for Prediction Across Scales (MPAS) v3.1: an extreme scaling experiment, links to sourcecode of model and grides

The Model for Prediction Across Scales (MPAS) is a novel set of Earth system simulation components and consists of an atmospheric model, an ocean model and a land-ice model. Its distinct features are the use of unstructured Voronoi meshes and C-grid discretisation to address shortcomings of global models on regular grids and the use of limited area models nested in a forcing data set, with respect to parallel scalability, numerical accuracy and physical consistency. This concept allows one to include the feedback of regional land use information on weather and climate at local and global scales in a consistent way, which is impossible to achieve with traditional limited area modelling approaches. Here, we present an in-depth evaluation of MPAS with regards to technical aspects of performing model runs and scalability for three medium-size meshes on four different high-performance computing (HPC) sites with different architectures and compilers. We uncover model limitations and identify new aspects for the model optimisation that are introduced by the use of unstructured Voronoi meshes. We further demonstrate the model performance of MPAS in terms of its capability to reproduce the dynamics of the West African monsoon (WAM) and its associated precipitation in a pilot study. Constrained by available computational resources, we compare 11-month runs for two meshes with observations and a reference simulation from the Weather Research and Forecasting (WRF) model. We show that MPAS can reproduce the atmospheric dynamics on global and local scales in this experiment, but identify a precipitation excess for the West African region. Finally, we conduct extreme scaling tests on a global 3?km mesh with more than 65 million horizontal grid cells on up to half a million cores. We discuss necessary modifications of the model code to improve its parallel performance in general and specific to the HPC environment. We confirm good scaling (70?% parallel efficiency or better) of the MPAS model and provide numbers on the computational requirements for experiments with the 3?km mesh. In doing so, we show that global, convection-resolving atmospheric simulations with MPAS are within reach of current and next generations of high-end computing facilities.

Interpolated maps of pollen percentages in Europe over the last 15,000 years

Aim Palaeoecological reconstructions document past vegetation change with estimates of rapid rates of changing species distribution limits that are often not matched by model simulations of climate-driven vegetation dynamics. Genetic surveys of extant plant populations have yielded new insight into continental vegetation histories, challenging traditional interpretations that had been based on pollen data. Our aim is to examine an updated continental pollen data set from Europe in the light of the new ideas about vegetation dynamics emerging from genetic research and vegetation modelling studies. Location Europe Methods: We use pollen data from the European Pollen Database (EPD) to construct interpolated maps of pollen percentages documenting change in distribution and abundance of major plant genera and the grass family in Europe over the last 15,000 years. Results: Our analyses confirm high rates of postglacial spread with at least 1000 metres per year for Corylus, Ulmus and Alnus and average rates of 400 metres per year for Tilia, Quercus, Fagus and Carpinus. The late Holocene expansions of Picea and Fagus populations in many European regions cannot be explained by migrational lag. Both taxa shift their population centres towards the Atlantic coast suggesting that climate may have played a role in the timing of their expansions. The slowest rates of spread were reconstructed for Abies. Main conclusions: The calculated rates of postglacial plant spread are higher in Europe than those from North America, which may be due to more rapid shifts in climate mediated by the Gulf Stream and westerly winds. Late Holocene anthropogenic land use practices in Europe had major effects on individual taxa, which in combination with climate change contributed to shifts in areas of abundance and dominance. The high rates of spread calculated from the European pollen data are consistent with the common tree species rapidly tracking early Holocene climate change and contribute to the debate on the consequences of global warming for plant distributions.