4.6 Article

Assessing the response of vegetation photosynthesis to meteorological drought across northern China

期刊

LAND DEGRADATION & DEVELOPMENT
卷 32, 期 1, 页码 20-34

出版社

WILEY
DOI: 10.1002/ldr.3701

关键词

chlorophyll fluorescence; drought indices; drought time-scales; drylands; vegetation vulnerability

资金

  1. Natural Science Foundation of Gansu Province [17JR5RA061]
  2. Qinghai Key R&D and Transformation Program [2020-SF-146]
  3. Fundamental Research Funds for the Central Universities [lzujbky-2020-21]
  4. National Natural Science Foundation of China [41901113]

向作者/读者索取更多资源

This study found that the sensitivity of satellite SIF signals to meteorological drought varies with different climatic conditions and biome types, with spatial variability of SIF constrained by wetness conditions and biome types. As aridity increases, drought-induced declines in vegetation photosynthesis will be quicker and more significant.
Satellite-based solar-induced chlorophyll fluorescence (SIF) has the potential to offer early detection and accurate impact assessment of meteorological drought on vegetation photosynthesis. However, how the response of satellite SIF to meteorological drought varies under different climatic conditions and biome types remains poorly understood. In this study, we determined the drought time-scale at which the vegetation photosynthesis response was highest based on the standardized precipitation evapotranspiration index (SPEI) and satellite SIF and examined how the sensitivity of SIF signals from different ecosystems to drought varied along an aridity gradient in northern China. The results showed that spatial variability of the annual maximum SIF was constrained by wetness conditions and biome types. Annual maximum SIF was positively correlated with SPEI in 57.9% of vegetated lands (p < .05). About 34.8% of humid ecosystems were characterized by a significant SIF-SPEI correlation (p < .05). This percentage reached 44, 71.4, and 86.2% for arid, subhumid, and semiarid ecosystems, respectively. The variation of SIF-SPEI correlations was a Gaussian function of the aridity index (AI), with the highest SIF-SPEI correlation appearing in the AI bin of 0.4 (0.37-0.46). The drivers for this pattern were vegetation composition and water availability. The variation of SIF time scales in response to SPEI was a linear function of the AI, but the slope varied among biomes. To summarize, with increasing aridity drought-induced declines in vegetation photosynthesis will be quicker and more significant.

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