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.

Data compilation on the biological response to ocean acidification: environmental and experimental context of data sets and related literature

The exponential growth of studies on the biological response to ocean acidification over the last few decades has generated a large amount of data. To facilitate data comparison, a data compilation hosted at the data publisher PANGAEA was initiated in 2008 and is updated on a regular basis (doi:10.1594/PANGAEA.149999). By January 2015, a total of 581 data sets (over 4 000 000 data points) from 539 papers had been archived. Here we present the developments of this data compilation five years since its first description by Nisumaa et al. (2010). Most of study sites from which data archived are still in the Northern Hemisphere and the number of archived data from studies from the Southern Hemisphere and polar oceans are still relatively low. Data from 60 studies that investigated the response of a mix of organisms or natural communities were all added after 2010, indicating a welcomed shift from the study of individual organisms to communities and ecosystems. The initial imbalance of considerably more data archived on calcification and primary production than on other processes has improved. There is also a clear tendency towards more data archived from multifactorial studies after 2010. For easier and more effective access to ocean acidification data, the ocean acidification community is strongly encouraged to contribute to the data archiving effort, and help develop standard vocabularies describing the variables and define best practices for archiving ocean acidification data.

Organic nitrogen and organic phosphorus concentrations bays of the White Sea

Concentrations of organic and mineral nitrogen and phosphorus in waters from different types of bays were determined during summer of 1987. Content of organic nitrogen in surface waters reached 80-97% of total; content of mineral phosphorus was 60-100%. Concentrations of N_org and P_org in deep waters decreased to 70 and 40%, respectively. Distribution of organic matter in the bays was controlled by river run-off.