海河流域植被净初级生产力时空变化及驱动因素分析

Spatio-temporal variation of vegetation net primary productivity and its driving factors in the Haihe River Basin

关键词:  净初级生产力, MOD17A3HGF, 时空变化, 驱动因素, 海河流域

Key words:  net primary productivity(NPP), MOD17A3HGF, spatio-temporal variation, driving factors, the Haihe River Basin

摘要:

为揭示海河流域植被净初级生产力(net primary productivity,NPP)时空变化特征及其时空异质性驱动机制,该文基于MOD17A3HGF数据集,综合自然和人为两方面的影响因素,利用变异系数、趋势分析、相关分析、Hurst指数以及地理探测器等,分析2000—2020年海河流域植被NPP时空格局演变特征和定量识别驱动因素及其影响力。结果表明:(1)时间上,2000—2020年海河流域植被NPP整体呈显著上升趋势,增速为1.73 Tg C·a^-1,年均NPP为326.75 g C·m^-2·a^-1,其中针叶林、阔叶林、灌丛、草地和农用地的NPP多年均值分别为313.59、385.28、353.03、320.12、295.22 g C·m^-2·a^-1。(2)空间上,植被NPP高值区集中于西北部山区,低值区集中于东南部平原区; NPP整体情况稳定,变异系数均值为0.17; 未来变化趋势呈反持续性,植被NPP可能下降。(3)植被NPP与气温呈负相关,与降水呈正相关,降水为主要气象因素; NPP随着高程和坡度增加均呈“增加—减少”的变化趋势; 耕地转草地使植被NPP增量最大,为732.22×10^-3 Tg C。(4)2000—2020年期间,不同驱动因素影响力均值为0.2,排序依次为降水>高程>坡度>湿度>气温>日照时数>土地利用>风速。综上表明,研究期内海河流域植被NPP整体呈好转趋势; 不同植被类型生产力存在差异,最强为阔叶林和灌丛; 影响植被NPP空间分布的主导因素为降水、高程和坡度,人为因素的影响力低于自然因素。该研究结果为海河流域水土流失、植被退化等生态环境治理提供了科学参考和决策依据。

Abstract:

To reveal the spatio-temporal variation characteristics of vegetation net primary productivity(NPP)in the Haihe River Basin and the driving mechanisms of its spatio-temporal heterogeneity, we studied the spatio-temporal pattern evolution characteristics of vegetation NPP in the Haihe River Basin from 2000 to 2020 using coefficient of variation, trend analysis, and Hurst index, based on MOD17A3HGF dataset. Driving factors from natural and human aspects and their influence were also quantitatively explored for vegetation NPP variations using correlation analysis and the Geodetector model. The results were as follows:(1)The temporal variation of vegetation NPP in the Haihe River Basin presented a significant growth trend form 2000 to 2020, with a rate of 1.73 Tg C·a^-1, and the annual average NPP was 326.75 g C·m^-2·a^-1; the average NPP of coniferous forests, broad-leaved forest, shrub, grassland and farmland were 313.59, 385.28, 353.03, 320.12, 295.22 g C·m^-2·a^-1.(2)In terms of spatial distribution, the high-value areas of vegetation NPP were mainly located in the northwest mountains, and the low-value areas were mainly located in the southeast plain; the overall situation of vegetation NPP was relatively stable, with an average coefficient of variation of 0.17; the future trend of NPP was anti-continuity and might decrease.(3)The correlation analysis showed that vegetation NPP was negatively correlated with temperature, and positively correlated with precipitation that was the main climate factor; NPP showed an “increase-decrease” trend with elevation and slope increasing; the conversion of farmland to grassland resulted in the largest increment of NPP at 732.22×10^-3 Tg C.(4)From 2000 to 2020, the average influence value of different drivers was 0.2, and the order was precipitation > elevation > slope > humidity > temperature > sunshine duration > land use > wind speed. Overall, the results indicated that vegetation NPP in the Haihe River Basin was improving during the study period; productivity varied among different vegetation types, with the strongest being broad-leaved forest and shrubland; the dominant factors affecting the spatial distribution of vegetation NPP were precipitation, elevation and slope, and the influence of human factors was lower than that of natural factors. The results of this study provide some scientific reference and decision basis for the treatment of ecological environment such as soil erosion and vegetation degradation in the Haihe River Basin.