Open AccessEstimating global cropland production from 1961 to 2010
Author(s) -
Pengfei Han,
Ning Zeng,
Fang Zhao,
Xiangui Lin
Publication year - 2017
Publication title -
earth system dynamics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.807
H-Index - 39
eISSN - 2190-4979
pISSN - 2190-4987
DOI - 10.5194/esd-8-875-2017
Subject(s) - primary production , environmental science , las vegas , global change , agriculture , climatology , china , vegetation (pathology) , scale (ratio) , physical geography , geography , climate change , ecosystem , geology , oceanography , ecology , cartography , medicine , archaeology , metropolitan area , pathology , biology
Global cropland net primary production (NPP) has tripled over the\udlast 50 years, contributing 17–45 % to the increase in global\udatmospheric CO2 seasonal amplitude. Although many regional-scale\udcomparisons have been made between statistical data and modeling results,\udlong-term national comparisons across global croplands are scarce due to the\udlack of detailed spatiotemporal management data. Here, we conducted a\udsimulation study of global cropland NPP from 1961 to 2010 using a\udprocess-based model called Vegetation–Global Atmosphere–Soil (VEGAS) and compared the results with Food and\udAgriculture Organization of the United Nations (FAO) statistical data on both\udcontinental and country scales. According to the FAO data, the global\udcropland NPP was 1.3, 1.8, 2.2, 2.6, 3.0, and 3.6 PgC yr−1 in the\ud1960s, 1970s, 1980s, 1990s, 2000s, and 2010s, respectively. The VEGAS model\udcaptured these major trends on global and continental scales. The NPP\udincreased most notably in the US Midwest, western Europe, and the North\udChina Plain and increased modestly in Africa and Oceania. However,\udsignificant biases remained in some regions such as Africa and Oceania,\udespecially in temporal evolution. This finding is not surprising as VEGAS is\udthe first global carbon cycle model with full parameterization representing\udthe Green Revolution. To improve model performance for different major\udregions, we modified the default values of management intensity associated\udwith the agricultural Green Revolution differences across various regions to\udbetter match the FAO statistical data at the continental level and for\udselected countries. Across all the selected countries, the updated results\udreduced the RMSE from 19.0 to 10.5 TgC yr−1\ud(∼ 45 % decrease). The results suggest that these regional\uddifferences in model parameterization are due to differences in\udsocioeconomic development. To better explain the past changes and predict\udthe future trends, it is important to calibrate key parameters on regional\udscales and develop data sets for land management history