Zhang Shengwei, Zhang Rui, Liu Tingxi, Song Xin, A Adams Mark
College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot, China.
Centre for Carbon, Water and Food, University of Sydney, Sydney, Australia.
PLoS One. 2017 Nov 7;12(11):e0187678. doi: 10.1371/journal.pone.0187678. eCollection 2017.
Spatiotemporal variations in net primary productivity (NPP) reflect the dynamics of water and carbon in the biosphere, and are often closely related to temperature and precipitation. We used the ecosystem model known as the Carnegie-Ames-Stanford Approach (CASA) to estimate NPP of semiarid grassland in northern China counties between 2001 and 2013. Model estimates were strongly linearly correlated with observed values from different counties (slope = 0.76 (p < 0.001), intercept = 34.7 (p < 0.01), R2 = 0.67, RMSE = 35 g C·m-2·year-1, bias = -0.11 g C·m-2·year-1). We also quantified inter-annual changes in NPP over the 13-year study period. NPP varied between 141 and 313 g C·m-2·year-1, with a mean of 240 g C·m-2·year-1. NPP increased from west to east each year, and mean precipitation in each county was significantly positively correlated with NPP-annually, and in summer and autumn. Mean precipitation was positively related to NPP in spring, but not significantly so. Annual and summer temperatures were mostly negatively correlated with NPP, but temperature was positively correlated with spring and autumn NPP. Spatial correlation and partial correlation analyses at the pixel scale confirmed precipitation is a major driver of NPP. Temperature was negatively correlated with NPP in 99% of the regions at the annual scale, but after removing the effect of precipitation, temperature was positively correlated with the NPP in 77% of the regions. Our data show that temperature effects on production depend heavily on recent precipitation. Results reported here have significant and far-reaching implications for natural resource management, given the enormous size of these grasslands and the numbers of people dependent on them.
净初级生产力（NPP）的时空变化反映了生物圈中水分和碳的动态变化，且通常与温度和降水密切相关。我们使用了名为卡内基-埃姆斯-斯坦福方法（CASA）的生态系统模型，来估算2001年至2013年中国北方半干旱草原县域的NPP。模型估算值与不同县域的观测值呈强线性相关（斜率 = 0.76（p < 0.001），截距 = 34.7（p < 0.01），R2 = 0.67，均方根误差 = 35 g C·m-2·年-1，偏差 = -0.11 g C·m-2·年-1）。我们还量化了13年研究期内NPP的年际变化。NPP在141至313 g C·m-2·年-1之间变化，平均值为240 g C·m-2·年-1。NPP每年从西向东增加，每个县域的年平均降水量与NPP呈显著正相关，在夏季和秋季也是如此。春季平均降水量与NPP呈正相关，但不显著。年平均温度和夏季温度大多与NPP呈负相关，但温度与春季和秋季NPP呈正相关。像素尺度的空间相关性和偏相关性分析证实，降水是NPP的主要驱动因素。在年尺度上，99%的区域温度与NPP呈负相关，但去除降水影响后，77%的区域温度与NPP呈正相关。我们的数据表明，温度对生产力的影响在很大程度上取决于近期的降水量。鉴于这些草原面积巨大以及依赖它们的人口数量众多，本文报道的结果对自然资源管理具有重大且深远的意义。
