中国沙漠 ›› 2026, Vol. 46 ›› Issue (5): 300-313.DOI: 10.7522/j.issn.1000-694X.2026.00148
• • 上一篇
收稿日期:2026-06-22
修回日期:2026-08-15
出版日期:2026-09-20
发布日期:2026-11-02
通讯作者:
贾冬梅
作者简介:张雅梅(1975—),女,内蒙古赤峰人,硕士,高级实验师,主要从事植物保护与宏观生理生态交叉研究。E-mail: yameizhang@jlu.edu.cn
Yamei Zhang1(
), Meiyao Song2, Dongmei Jia1(
)
Received:2026-06-22
Revised:2026-08-15
Online:2026-09-20
Published:2026-11-02
Contact:
Dongmei Jia
摘要:
在全球气候变化加剧的背景下,探明植被光合生理信号与总初级生产力的时空分异特征及其水热驱动机制,是准确评估全球碳汇潜力的关键。本研究基于2002—2024年全球LHSIF和TRAX GPP数据,分析了全球植被日光诱导叶绿素荧光(SIF)和总初级生产力(GPP,以C计量)的时空变化及其关键水热驱动因素。结果表明:全球植被SIF和GPP的年际变化速率中位数分别为5.48×10⁻⁴ mW·m⁻²·sr⁻¹·nm⁻¹·a⁻¹和7.5×10⁻3 g·m⁻²·d⁻¹·a⁻¹;变化趋势整体以稳定和上升为主,SIF显著上升和下降区域分别占29.88%和8.64%,GPP分别占31.07%和21.56%,部分区域的光合生理信号未能同步转化为生态系统碳固定能力;SIF主要受热量或辐射因子驱动(相对贡献为57.87%),GPP则更受水分因子驱动(相对贡献为55.95%),SIF与GPP的主导驱动因子在不同植被类型和气候类型下发生系统性转变,光合生理信号向碳固定结果的转化受区域水热条件、气候背景和植被功能属性共同控制;总蒸散发、总降水量及地表向下热辐射等关键水热因子对植被光合与生产力的驱动作用呈现出非线性特征与阈值效应,且在不同的长期变化趋势下表现出非对称性。
中图分类号:
张雅梅, 宋美垚, 贾冬梅. 全球植被光合生理与总初级生产力的时空特征及其关键水热驱动因素[J]. 中国沙漠, 2026, 46(5): 300-313.
Yamei Zhang, Meiyao Song, Dongmei Jia. Spatiotemporal characteristics and key hydrothermal driving factors of global vegetation photosynthetic physiology and gross primary productivity[J]. Journal of Desert Research, 2026, 46(5): 300-313.
| 水热驱动因子 | 类别 | 单位 | ERA5-Land变量名 |
|---|---|---|---|
| 总降水量(tp) | 水 | m | Total precipitation |
| 地下径流(ssro) | 水 | m | Sub-surface runoff |
| 地表径流(sro) | 水 | m | Surface runoff |
| 植被蒸腾蒸发(evavt) | 水 | m(水当量) | Evaporation from vegetation transpiration |
| 潜在蒸散发(pev) | 水 | m | Potential evaporation |
| 总蒸散发(e) | 水 | m(水当量) | Total evaporation |
| 地表储水量(src) | 水 | m(水当量) | Skin reservoir content |
| 土壤体积含水量1(swvl1) | 水 | m3·m-3 | Volumetric soil water (layer 1) |
| 土壤体积含水量2(swvl2) | 水 | m3·m-3 | Volumetric soil water (layer 2) |
| 土壤体积含水量3(swvl3) | 水 | m3·m-3 | Volumetric soil water (layer 3) |
| 土壤体积含水量4(swvl4) | 水 | m3·m-3 | Volumetric soil water (layer 4) |
| 气温(t2m) | 热 | K | 2 metre temperature |
| 土壤温度1(stl1) | 热 | K | Soil temperature (layer 1) |
| 土壤温度2(stl2) | 热 | K | Soil temperature (layer 2) |
| 土壤温度3(stl3) | 热 | K | Soil temperature (layer 3) |
| 土壤温度4(stl4) | 热 | K | Soil temperature (layer 4) |
| 地表净太阳辐射(ssr) | 热 | J·m-2 | Surface net solar radiation |
| 地表向下太阳辐射(ssrd) | 热 | J·m-2 | Surface solar radiation downwards |
| 地表净热辐射(str) | 热 | J·m-2 | Surface net thermal radiation |
| 地表向下热辐射(strd) | 热 | J·m-2 | Surface thermal radiation downwards |
| 地表潜热通量(slhf) | 热 | J·m-2 | Surface latent heat flux |
| 地表感热通量(sshf) | 热 | J·m-2 | Surface sensible heat flux |
表1 水热驱动因子变量
Table 1 Hydrothermal driving factor variables
| 水热驱动因子 | 类别 | 单位 | ERA5-Land变量名 |
|---|---|---|---|
| 总降水量(tp) | 水 | m | Total precipitation |
| 地下径流(ssro) | 水 | m | Sub-surface runoff |
| 地表径流(sro) | 水 | m | Surface runoff |
| 植被蒸腾蒸发(evavt) | 水 | m(水当量) | Evaporation from vegetation transpiration |
| 潜在蒸散发(pev) | 水 | m | Potential evaporation |
| 总蒸散发(e) | 水 | m(水当量) | Total evaporation |
| 地表储水量(src) | 水 | m(水当量) | Skin reservoir content |
| 土壤体积含水量1(swvl1) | 水 | m3·m-3 | Volumetric soil water (layer 1) |
| 土壤体积含水量2(swvl2) | 水 | m3·m-3 | Volumetric soil water (layer 2) |
| 土壤体积含水量3(swvl3) | 水 | m3·m-3 | Volumetric soil water (layer 3) |
| 土壤体积含水量4(swvl4) | 水 | m3·m-3 | Volumetric soil water (layer 4) |
| 气温(t2m) | 热 | K | 2 metre temperature |
| 土壤温度1(stl1) | 热 | K | Soil temperature (layer 1) |
| 土壤温度2(stl2) | 热 | K | Soil temperature (layer 2) |
| 土壤温度3(stl3) | 热 | K | Soil temperature (layer 3) |
| 土壤温度4(stl4) | 热 | K | Soil temperature (layer 4) |
| 地表净太阳辐射(ssr) | 热 | J·m-2 | Surface net solar radiation |
| 地表向下太阳辐射(ssrd) | 热 | J·m-2 | Surface solar radiation downwards |
| 地表净热辐射(str) | 热 | J·m-2 | Surface net thermal radiation |
| 地表向下热辐射(strd) | 热 | J·m-2 | Surface thermal radiation downwards |
| 地表潜热通量(slhf) | 热 | J·m-2 | Surface latent heat flux |
| 地表感热通量(sshf) | 热 | J·m-2 | Surface sensible heat flux |
图1 2002—2024年 SIF和GPP年际变化速率的空间分布注:基于自然资源部标准地图服务网站审图号GS(2016)1665号标准地图制作,底图边界无修改
Fig.1 Spatial distribution of interannual change in SIF and GPP from 2002 to 2024
图2 不同植被类型和气候类型下SIF和GPP的年际变化速率注:不同植被类型、不同气候类型之间的SIF与GPP年际变化速率均存在显著性差异(P<0.05)。为保证图面清晰整洁,图中省略了显著性星号标记
Fig.2 Rates of interannual change in SIF and GPP across different vegetation types and climate zones
| 气候类型 | 占比 | 气候类型 | 占比 | 气候类型 | 占比 |
|---|---|---|---|---|---|
| 热带雨林气候 | 21.61% | 常湿冷温气候 | 7.17% | 热带草原气候 | 2.87% |
| 苔原气候 | 18.27% | 冬干冷温气候 | 6.65% | 冬干暖温气候 | 2.01% |
| 热带季风气候 | 17.12% | 沙漠气候 | 5.55% | 常湿暖温气候 | 1.81% |
| 夏干冷温气候 | 13.11% | 夏干暖温气候 | 3.19% | 草原气候 | 0.64% |
表2 不同气候类型下 SIF 显著上升且 GPP 显著下降区域的占比
Table 2 Proportions of regions with significant SIF increase and GPP decrease across different climate zones
| 气候类型 | 占比 | 气候类型 | 占比 | 气候类型 | 占比 |
|---|---|---|---|---|---|
| 热带雨林气候 | 21.61% | 常湿冷温气候 | 7.17% | 热带草原气候 | 2.87% |
| 苔原气候 | 18.27% | 冬干冷温气候 | 6.65% | 冬干暖温气候 | 2.01% |
| 热带季风气候 | 17.12% | 沙漠气候 | 5.55% | 常湿暖温气候 | 1.81% |
| 夏干冷温气候 | 13.11% | 夏干暖温气候 | 3.19% | 草原气候 | 0.64% |
图4 水热驱动因子对SIF和GPP空间异质性的相对贡献注:条形图内部镶嵌的黑色曲线表示该特征的真实值与SHAP值的依赖关系
Fig.4 Relative contributions of hydrothermal driving factors to the spatial heterogeneity of SIF and GPP
| 气候类型 | 有效像元数(n) | SIF | GPP | ||||||
|---|---|---|---|---|---|---|---|---|---|
| 主导因子 | 主导因子的贡献度 | R2 | CVR2 | 主导因子 | 主导因子的贡献度 | R2 | CV R2 | ||
| 冬干冷温气候 | 52 982 | 地表向下热辐射(strd) | 32.44% | 0.95 | 0.76 | 地下径流(ssro) | 20.64% | 0.92 | 0.78 |
| 冬干暖温气候 | 43 405 | 地表净热辐射(str) | 17.32% | 0.90 | 0.68 | 地表储水量(src) | 40.79% | 0.90 | 0.75 |
| 夏干冷温气候 | 13 510 | 地表向下热辐射(strd) | 27.79% | 0.94 | 0.76 | 地表向下太阳辐射(ssrd) | 33.38% | 0.94 | 0.72 |
| 夏干暖温气候 | 11 606 | 地表净热辐射(str) | 20.72% | 0.89 | 0.62 | 地表储水量(src) | 23.38% | 0.89 | 0.53 |
| 常湿冷温气候 | 219 662 | 总蒸散发(e) | 31.46% | 0.96 | 0.89 | 地表向下热辐射(strd) | 17.22% | 0.87 | 0.66 |
| 常湿暖温气候 | 51 824 | 地表感热通量(sshf) | 19.51% | 0.87 | 0.58 | 地表储水量(src) | 35.06% | 0.90 | 0.66 |
| 沙漠气候 | 22 836 | 地表向下热辐射(strd) | 23.78% | 0.96 | 0.69 | 地表向下热辐射(strd) | 17.07% | 0.92 | 0.28 |
| 热带季风气候 | 32 953 | 地表储水量(src) | 26.23% | 0.82 | 0.34 | 地表储水量(src) | 44.23% | 0.85 | 0.54 |
| 热带草原气候 | 117 187 | 地表储水量(src) | 37.35% | 0.88 | 0.69 | 地表储水量(src) | 43.10% | 0.88 | 0.74 |
| 热带雨林气候 | 43 951 | 地表感热通量(sshf) | 10.86% | 0.65 | 0.09 | 地表储水量(src) | 29.45% | 0.70 | 0.37 |
| 苔原气候 | 27 811 | 总降水量(tp) | 28.93% | 0.95 | 0.87 | 地表向下热辐射(strd) | 24.66% | 0.92 | 0.78 |
| 草原气候 | 105 007 | 地表向下热辐射(strd) | 28.26% | 0.94 | 0.80 | 总蒸散发(e) | 21.95% | 0.90 | 0.67 |
表3 不同气候类型下 SIF 和 GPP 的主导驱动因子及其贡献度
Table 3 Dominant driving factors and their contributions to SIF and GPP across different climate zones
| 气候类型 | 有效像元数(n) | SIF | GPP | ||||||
|---|---|---|---|---|---|---|---|---|---|
| 主导因子 | 主导因子的贡献度 | R2 | CVR2 | 主导因子 | 主导因子的贡献度 | R2 | CV R2 | ||
| 冬干冷温气候 | 52 982 | 地表向下热辐射(strd) | 32.44% | 0.95 | 0.76 | 地下径流(ssro) | 20.64% | 0.92 | 0.78 |
| 冬干暖温气候 | 43 405 | 地表净热辐射(str) | 17.32% | 0.90 | 0.68 | 地表储水量(src) | 40.79% | 0.90 | 0.75 |
| 夏干冷温气候 | 13 510 | 地表向下热辐射(strd) | 27.79% | 0.94 | 0.76 | 地表向下太阳辐射(ssrd) | 33.38% | 0.94 | 0.72 |
| 夏干暖温气候 | 11 606 | 地表净热辐射(str) | 20.72% | 0.89 | 0.62 | 地表储水量(src) | 23.38% | 0.89 | 0.53 |
| 常湿冷温气候 | 219 662 | 总蒸散发(e) | 31.46% | 0.96 | 0.89 | 地表向下热辐射(strd) | 17.22% | 0.87 | 0.66 |
| 常湿暖温气候 | 51 824 | 地表感热通量(sshf) | 19.51% | 0.87 | 0.58 | 地表储水量(src) | 35.06% | 0.90 | 0.66 |
| 沙漠气候 | 22 836 | 地表向下热辐射(strd) | 23.78% | 0.96 | 0.69 | 地表向下热辐射(strd) | 17.07% | 0.92 | 0.28 |
| 热带季风气候 | 32 953 | 地表储水量(src) | 26.23% | 0.82 | 0.34 | 地表储水量(src) | 44.23% | 0.85 | 0.54 |
| 热带草原气候 | 117 187 | 地表储水量(src) | 37.35% | 0.88 | 0.69 | 地表储水量(src) | 43.10% | 0.88 | 0.74 |
| 热带雨林气候 | 43 951 | 地表感热通量(sshf) | 10.86% | 0.65 | 0.09 | 地表储水量(src) | 29.45% | 0.70 | 0.37 |
| 苔原气候 | 27 811 | 总降水量(tp) | 28.93% | 0.95 | 0.87 | 地表向下热辐射(strd) | 24.66% | 0.92 | 0.78 |
| 草原气候 | 105 007 | 地表向下热辐射(strd) | 28.26% | 0.94 | 0.80 | 总蒸散发(e) | 21.95% | 0.90 | 0.67 |
| 植被类型 | 有效像 元数(n) | SIF | GPP | ||||||
|---|---|---|---|---|---|---|---|---|---|
| 主导因子 | 主导因子的贡献度 | R2 | CVR2 | 主导因子 | 主导因子的贡献度 | R2 | CV R2 | ||
| 林地 | 194 593 | 总蒸散发(e) | 39.58% | 0.96 | 0.90 | 总蒸散发(e) | 40.18% | 0.97 | 0.95 |
| 湿地 | 5 621 | 地表向下热辐射(strd) | 35.04% | 0.96 | 0.71 | 地表向下热辐射(strd) | 27.36% | 0.90 | 0.71 |
| 耕地 | 99 638 | 总降水量(tp) | 23.66% | 0.92 | 0.76 | 总降水量(tp) | 25.54% | 0.88 | 0.69 |
| 草地 | 442 882 | 总蒸散发(e) | 37.82% | 0.95 | 0.91 | 地表潜热通量(slhf) | 27.43% | 0.93 | 0.86 |
表4 不同植被类型下 SIF 和 GPP 的主导驱动因子及其贡献度
Table 4 Dominant driving factors and their contributions to SIF and GPP across different vegetation types
| 植被类型 | 有效像 元数(n) | SIF | GPP | ||||||
|---|---|---|---|---|---|---|---|---|---|
| 主导因子 | 主导因子的贡献度 | R2 | CVR2 | 主导因子 | 主导因子的贡献度 | R2 | CV R2 | ||
| 林地 | 194 593 | 总蒸散发(e) | 39.58% | 0.96 | 0.90 | 总蒸散发(e) | 40.18% | 0.97 | 0.95 |
| 湿地 | 5 621 | 地表向下热辐射(strd) | 35.04% | 0.96 | 0.71 | 地表向下热辐射(strd) | 27.36% | 0.90 | 0.71 |
| 耕地 | 99 638 | 总降水量(tp) | 23.66% | 0.92 | 0.76 | 总降水量(tp) | 25.54% | 0.88 | 0.69 |
| 草地 | 442 882 | 总蒸散发(e) | 37.82% | 0.95 | 0.91 | 地表潜热通量(slhf) | 27.43% | 0.93 | 0.86 |
图5 不同变化趋势下关键水热驱动因子对SIF和GPP的局部依赖关系注:第一、二、三列分别为相对贡献排名前三的关键水热驱动因子的SHAP依赖图;横坐标为经过标准化处理后的驱动因子数值;黑色实线为基于GAM拟合的平滑趋势线
Fig.5 Partial dependence of SIF and GPP on key hydrothermal driving factors under different variation trends
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