Abstract:

Net ecosystem productivity (NEP) measures the carbon sequestration capacity of regional ecosystems. Based on MODIS NPP data, the spatiotemporal dynamics of vegetation NEP in the Tianshan region from 2001 to 2024 were analyzed using a soil microbial respiration model. The ridge regression model combined with residual analysis was used to quantitatively assess the contributions of different climatic factors and human activities to NEP. The results indicate that: 1) The NEP in the Tianshan region showed a spatial distribution characteristic of high in the west and low in the east, with a mean value of C 200 g·m⁻²; NEP overall showed a fluctuating but increasing trend, growing at a rate of C 0.73 g·m⁻²·a⁻¹, and in the future, NEP in most areas of the Tianshan region will also show an increasing trend. 2) Swamps, broad-leaved forests, and grasslands had higher NEP, with mean values of C 284, 247 and 244 g·m⁻², respectively; swamps, and cultivated vegetation had higher growth rates (C 1.58 and 0.97 g·m⁻²·a⁻¹, respectively), and in the future, NEP for each vegetation type will predominantly show an increasing trend. 3) The average contributions of precipitation, soil moisture, solar radiation, and air temperature to NEP were 22.0%, 34.8%, 17.8%, and 25.4%, respectively. Precipitation change had an overall negative contribution to NEP, whereas changes in soil moisture, solar radiation, and air temperature had overall positive contributions. 4) Meadows, grasslands, alpine vegetation, shrubs, deserts, broad-leaved forests, and coniferous forests were soil moisture-driven; swamps and other vegetation types were temperature-driven; and cultivated vegetation was precipitation driven. 5) Changes in NEP in the Tianshan region were jointly influenced by climate and human activities, with relative contributions of 61.6% and 38.4%, respectively. Grasslands and swamps were most affected by climate change, whereas alpine vegetation and other plant types were most affected by human activities.

Key words: net ecosystem productivity (NEP), spatiotemporal dynamics, ridge regression, driving factors, Tianshan region

摘要：

净生态系统生产力（Net ecosystem productivity，NEP）能够衡量区域生态系统的固碳能力。基于MODIS NPP数据，利用土壤微生物呼吸模型分析出2001－2024年天山地区植被NEP时空动态。然后采用岭回归模型结合残差分析的方法，定量评估出不同气候因子和人类活动对NEP的贡献。结果表明，1）天山地区NEP呈西高东低的空间分布特征，均值为C 200 g·m⁻²。NEP整体呈波动上升趋势且以C 0.73 g·m⁻²·a⁻¹的速率增长，未来天山大部分区域的NEP也将呈现上升趋势。2）沼泽、阔叶林和草原的NEP较高，均值为C 284、247和244 g·m⁻²；沼泽和栽培植的增长速率较高（分别为C 1.58和0.97 g·m⁻²·a⁻¹），并且未来各植被类型NEP以上升趋势为主体。3）降水、土壤湿度、太阳辐射和气温对NEP的平均贡献分别为22.0%、34.8%、17.8%和25.4%。降水变化对NEP整体呈负贡献，土壤湿度、太阳辐射和气温变化对NEP整体呈正贡献。4）草甸、草原、高山植物、灌丛、荒漠、阔叶林和针叶林为土壤湿度驱动类型，沼泽和其他为气温驱动型植被，栽培植为降水驱动型植被。5）天山地区NEP变化受到气候和人类活动的共同作用，相对贡献分别为61.6%和38.4%。草原和沼泽受气候变化的影响最多，高山植物和其他植物类型受人类活动的影响最多。

关键词: 净生态系统生产力（NEP）, 时空动态, 岭回归, 驱动因素, 天山地区