Biomass Estimation And Spatial Distribution Of Maize Root In China

Understanding the magnitude, spatial, and vertical patterns of crop roots and the underlying mechanisms are critical for estimating ecosystem functioning (e.g., water and nutrient fluxes), and addressing agricultural challenges of ensuring food security and mitigating the impacts of climate change, considering most soil carbon (C) is derived from root and strongly influenced by agricultural management practices. Maize (Zea mays L.) is the most geographically ubiquitous crop, playing a vital role in the world’s food security. With a large and extensive root system, maize can significantly contribute to C sequestration through its belowground inputs, including root biomass (RB) and rhizodeposition (e.g. mucilage, sloughed cells, and root exudates). China’s landscape is vast with distinct climate, soil, and vegetation etc. zonality, which may contribute to observably typical root distribution patterns. Moreover, maize root data at the national scale across China could be very useful in developing of ecosystem modeling, crop growth models, and climate models, considering limited root information globally, especially in agroecosystem. Here we compiled root data from 311 published references and 16 research trials conducted between 1986-2012, to analyze the spatial and vertical distribution of maize RB and its associated C deposition in soil across China. Descriptive statistical analysis and geostatistical analysis were used to analyze biomass and spatial distribution of maize root in China. The partial least-squares regression (PLS) models incorporating climatic, edaphic, topographical, and agronomic factors were used to explore biotic and abiotic factors determining maize RB, root depth (RD), and the spatial patterns. The main results are as follows:(1) The results showed that maize RB was 30.10 g plant-1 (8.20-88.90 g plant-1) or 0.18 kg m-2 (0.05-0.38 kg m-2), average across China. The magnitude and spatial pattern varied across five different agroecological zones. On a per plant basis, significantly higher RB was shown in North Spring Maize Zone (NS), while no distinct difference was found in the remaining zones. Variation of RB on a per square meter basis was more apparent. Root biomass in NS was significantly higher than those in the rest zones, and RB in Huanghuaihai Summer Maize Zone (HS) was significantly higher than that of South Hilly Maize Zone (SH). Interpolated RB density using inverse distance weighted (IDW) algorithm across China reflected a higher cultivation intensity in NS and HS zones. At last, the total biomass map showed a roughly declining trend from north to south, and from east to west of China, with the highest total RB appeared in NS and HS zones. On average, maize RB accounted for approximately 0.08 kg m-2 input of C to the soil at harvest. Based on the map of maize planting area, a total of 22.9 Tg C yr-1 inputs of maize RB carbon (RBC) was estimated to be added to the soil C pools.(2) The mean of extroplated D50 and D95 (soil depths containing 50% and 95% of RB, respectively was 11.3 cm (3.45-25.18 cm) and 94.3 cm (12.62-175.95cm). According to one-way analysis of variance (ANOAV), a significant difference in extroplated D50 was found among agroecological zones:NS> Northwest Inland Maize Zone (NI)> HS> Southwest Mountains and Hilly Maize Zone (SM). The order of extroplated D95 was different from that of extroplated D50:HS>NS>NI> SM. In general, in 0-80 cm depth, maize in NS rooted more deeply, and similar root profiles were found in HS and NI zones. However, HS had the deepest extroplated D95 values. And the shallowest extroplated D95 were found in SM zone. Interpolated RD density using IDW algorithm across China also reflected a roughly declining trend from north to south of China. Based on the logistic dose-response curve (LDR) model, approximately 71.53% of all maize roots located in top 0-20 cm soil depth, resulting in a total of 16.39 Tg C inputted in top soil through RB.(3) The PLS models incorporating climatic, edaphic, topographical, and agronomic factors explained 42.40% and 56.70% of the variation in RB and RD, respectively. Different biotic and abiotic factors determining maize RB and RD were observed. Maize RB was positively correlated with plant density, grain yield, mean annual precipitation, monthly mean precipitation in April, monthly mean sunshine duration in May, soil organic content and the percentage of sand in the soil, while negatively correlated with monthly mean precipitation in July and October, pH, and potassium content in the fertilizer. However, maize RD was positively correlated with the percentage of sand in the soil, pH, mean annual sunshine duration, monthly mean sunshine duration in September, and the cation exchange capacity, while negatively correlated with slope, elevation, the percentage of clay in the soil, soil bulk density, and monthly mean sunshine duration in July. Of the variables examined nationally, agronomic management (especially planting density) was the dominant factor affecting RB, whereas RD was mostly influenced by soil-related factors (especially the proportion of sand and soil pH). The climatic factors affecting RB and RD were also different. Results showed that RD was more sensitive to sunshine duration, while RB tended to have high association with hydrology. The trends of spatial patterns of RB and RD across China estimated by the PLS model were much similar with the results derived from IDW algorithm, however, the PLS model was considerend a better method of spatial prediction in our research.(4) Maize RB didn’t change significantly from 1986 to 2012 at the national scale. In recent decade (2002-2012), RB on a per plant basis didn’t change significantly, either. However, decrease in RB on a per square meter basis was observed at a national scale with a constant plant density.In NS zone, RB decreased significantly from 2002 to 2012, showing an opposite trend with aboveground grain yield. In addition, significantly deeper extroplated D50 and D95 were observed against years in NS. In HS zone, the adverse dynamics of RB and yield was also observed since 2009. However, dynamics of extroplated D95 were consistent with the trend of grain yield in the main districts of maize in China, indicating that the increasing of RD might be closely correlated the historical maize yield trends in China.