1982-2020年安徽省净生态系统生产力时空格局变化及其成因

净生态系统生产力（NEP）是定量描述陆地生态系统与大气之间碳交换的重要指标。明确区域尺度NEP的时空格局及主导因子，有助于增强对区域碳循环变化机制的认知。基于BEPS （Boreal Ecosystem Productivity Simulator）模型模拟结果，评估了安徽省1982-2020年NEP时空格局，分析了安徽省NEP对主要环境植被因子的敏感性，并借助通径分析和贡献率分析探究了影响安徽省NEP时空变化的驱动因子。结果表明：（1）1982-2020年，安徽省多年年均NEP为651.14 gC/m²，线性趋势变化率为1.10 gC m^-2 a^-1，总体呈显著增加趋势（P<0.01）。在空间上，NEP表现为"南北部较高、中部较低"的分布，显著增加（P<0.05）的区域占52.77%，主要分布在北部和南部，显著减小（P<0.05）的区域占7.11%，主要分布在西部和东南部。NEP重心有显著的北移趋势（P<0.01）。（2） NEP对大气CO₂浓度变化最为敏感，对降水变化最不敏感。时间上，NEP对叶面积指数（LAI）（P<0.01）、CO₂（P<0.01）和饱和水汽压差（VPD）（P<0.05）的敏感性变化显著增强，对总辐射的敏感性变化显著减弱（P<0.01），对气温和降水的敏感性变化不显著（P>0.05）。空间上，NEP对各因子的敏感性有地区差异性。（3）所选环境植被因子综合解释了NEP 79%的时空变化。LAI与CO₂是安徽省NEP时空变化的主导因子，为正贡献，气候因子为次主导因子，为负贡献。空间上，LAI为主导因子的地区主要分布在安徽省北部、中西部的大部分地区，占49.65%，CO₂为主导因子的地区主要分布在安徽省西北部与东南部的大部分地区，占44.54%。

Spatio-temporal pattern changes and attribution analysis of net ecosystem productivity in Anhui Province from 1982 to 2020

Net ecosystem productivity (NEP) is an important indicator to quantitatively describe the carbon exchange between terrestrial ecosystems and the atmosphere. Clarifying the temporal and spatial patterns of NEP at the regional scale and its dominant factors is helpful to enhance the understanding of the mechanism of regional carbon cycling. Based on the simulation of BEPS model, this paper evaluated the spatio-temporal pattern of NEP in Anhui Province from 1982 to 2020, analyzed the sensitivity of NEP to major environmental and vegetation factors, and explored the driving factors affecting the spatio-temporal change of NEP with the help of path analysis and contribution analysis. The results showed that:(1) the annual average NEP in Anhui Province was 651.14 gC/m², and NEP overall showed a significant increasing trend with the linear trend change rate of 1.10 gC m^-2 a^-1 (P<0.01) from 1982 to 2020. Spatially, NEP showed the distribution of "higher in the north and south and lower in the middle". The areas with significant increase accounted for 52.77% (P<0.05), mainly in the north and south regions, while the areas with significant decrease accounted for 7.11% (P<0.05), mainly in the west and southeast regions. The center of gravity of NEP had a significant northward shift trend (P<0.01). (2) NEP was the most sensitive to changes in atmospheric CO₂ concentration and the least sensitive to changes in precipitation. In terms of time, the sensitivity changes of NEP to leaf area index (LAI) (P<0.01), CO₂(P<0.01), and vapor pressure deficit (VPD) (P<0.05) were significantly enhanced, but the sensitivity change to total radiation (Rad) was significantly weakened (P<0.01) and the sensitivity change to air temperature and precipitation did not change significantly (P>0.05). The sensitivity of NEP to each factor varied with region on the spatial scale. (3) The selected environment and vegetation factors comprehensively explained 79% of the temporal and spatial variations of NEP. LAI and CO₂ were the dominant factors of NEP variations, and showed the positive contributions to NEP changes, while climate factors had negative contributions to NEP changes. LAI and CO₂ were the dominant factors of spatio-temporal variation of NEP in Anhui Province, with positive contributions, while climate factors as the secondary dominant factors had negative contributions. Spatially, the LAI as the dominant factor determined NEP changes in 49.65% of the Province that mainly distributed in northern, central and western Anhui province; CO₂ as the dominant factor played a leading role in 44.54% of the Province that mainly distributed in northwest and southeast Anhui Province.