Journal of Resources and Ecology >
Satellite-based Estimates of Canopy Photosynthetic Parameters for an Alpine Meadow in Northern
NIU Ben, E-mail: niub@igsnrr.ac.cn |
Received date: 2020-03-02
Accepted date: 2020-04-11
Online published: 2020-06-16
Supported by
The National Key Research and Development Program of China(2016YFC0502001)
The National Natural Science Foundation of China(41807331)
The West Light Foundation of the Chinese Academy of Sciences(2018)
Copyright
Plant photosynthesis is the fundamental driver of all the biospheric functions. Alpine meadow on the Tibetan Plateau is sensitive to rapid climate change, and thus can be considered an indicator for the response of terrestrial ecosystems to climate change. However, seasonal variations in photosynthetic parameters, including the fraction of photosynthetically active radiation by canopy (FPAR), the light extinction coefficient (k) through canopy, and the leaf area index (LAI) of plant communities, are not known for alpine meadows on the Tibetan Plateau. In this study, we used field measurements of radiation components and canopy structure from 2009 to 2011 at a typical alpine meadow on the northern Tibetan Plateau to calculate these three photosynthetic parameters. We developed a satellite-based (NDVI and EVI) method derived from the Beer-Lambert law to estimate the seasonal dynamics of FPAR, k ,and LAI, and we compared these estimates with the Moderate Resolution Imaging Spectroradiometer (MODIS) FPAR (FPAR_MOD) and LAI product (LAI_MOD). The results showed that the average daily FPAR was 0.33, 0.37 and 0.35, respectively, from 2009 to 2011, and that the temporal variations could be explained by all four satellite-based FPAR estimations, including FPAR_MOD, an FPAR estimation derived from the Beer-Lambert law with a constant k (FPAR_LAI), and two FPAR estimations from the nonlinear functions between the ground measurements of FPAR (FAPRg) and NDVI/EVI (FPAR_NDVI and FPAR_EVI). We found that FPAR_MOD seriously undervalued FPARg by over 40%. Tower-based FPAR_LAI also significantly underestimated FPARg by approximately 20% due to the constant k (0.5) throughout the whole growing seasons. This indicated that using FPAR_LAI to validate the FPAR_MOD was not an appropriate method in this alpine meadow because the seasonal variation of k ranged from 0.19 to 2.95 in this alpine meadow. Thus, if the seasonal variation of k was taken into consideration, both FPAR_NDVI and FPAR_EVI provided better descriptions, with negligible overestimates of less than 5% of FAPRg (RMSE=0.05), in FPARg estimations than FPAR_MOD and FPAR_LAI. Combining the satellite-based (NDVI and EVI) estimations of seasonal FPAR and k, LAI_NDVI and LAI_EVI derived from the Beer-Lambert law also provided better LAIg estimations than LAI_MOD (less than 30% of LAIg). Therefore, this study concluded that satellite-based models derived from the Beer-Lambert law were a simple and efficient method for estimating the seasonal dynamics of FPAR, k and LAI in this alpine meadow.
NIU Ben , HE Yongtao , ZHANG Xianzhou , SHI Peili , DU Mingyuan . Satellite-based Estimates of Canopy Photosynthetic Parameters for an Alpine Meadow in Northern[J]. Journal of Resources and Ecology, 2020 , 11(3) : 253 -262 . DOI: 10.5814/j.issn.1674-764X.2020.03.002
Fig. 1 The 8-day step radiation observations during the years 2009 to 2011. (a) Total radiation and net radiation. (b) Photosynthetically active radiation (PAR) and the absorbed PAR by canopy (APAR). |
Fig. 2 Seasonal patterns of FPAR observations (FPARg) and satellite-based FPAR estimations from 2009 to 2011 (a); and comparison with the FPARg from: 2009 (b); 2010 (c); and 2011 (d). Slope values (Slope) in (b-d) are the linear relationships between FAPRg and satellite-based FPAR estimations, and the dashed lines are the reference lines of 1:1. All linear |
Table 1 Satellite-based FPAR estimations and comparisons with tower-based FPAR observations during the growing seasons from 2009 to 2011. |
Method | Daily average FPAR estimations (n=21) | Mean FPAR (n=63) | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Mean of SD | RMSE | RPE (%) | ||||||||||
2009 | 2010 | 2011 | 2009 | 2010 | 2011 | Mean | 2009 | 2010 | 2011 | Mean | Mean (SD) | |
FPAR_MOD | 0.19 (0.08) | 0.21 (0.11) | 0.20 (0.09) | 0.16 | 0.19 | 0.16 | 0.17 | 43.1 | 43.0 | 41.9 | 42.7 | 0.20 (0.09) a |
FPAR_LAI | 0.26 (0.16) | 0.30 (0.21) | 0.30 (0.20) | 0.13 | 0.20 | 0.16 | 0.17 | 23.4 | 19.1 | 15.1 | 19.2 | 0.29 (0.19) b |
FPAR_NDVI | 0.34 (0.05) | 0.36 (0.05) | 0.36 (0.06) | 0.07 | 0.06 | 0.03 | 0.05 | -4.2 | 3.8 | -1.3 | -0.5 | 0.36 (0.05) c |
FPAR_EVI | 0.35 (0.05) | 0.36 (0.06) | 0.36 (0.05) | 0.07 | 0.06 | 0.03 | 0.05 | -4.1 | 4.5 | 1.2 | -0.3 | 0.35 (0.05) c |
FPARg | 0.33 (0.08) | 0.37 (0.10) | 0.35 (0.09) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.35 (0.08) c |
Note: *SD is the standard deviation of the average 8-day composite FPAR estimations. Negative RPE indicates that satellite-based FPAR estimations overestimate the FPAR observations. Columns with the different alphabets indicate that significant difference existed among diverse mean FPAR estimations (α=0.05, P<0.01). |
Fig. 3 Satellite-based estimations of the fractions of absorbed PAR by vegetation canopy (FPAR) and the extinction coefficient (kt) in the alpine meadow study area (n = 63) |
Fig. 4 Seasonal patterns of LAI observation (LAIg) and satellite-based LAI estimations derived from satellite-based PFAR and kt estimations (a); and comparison with the LAIg from 2009 to 2011 (b). Slope values and dashed lines in (b) are the linear slope between LAIg and satellite-based LAI estimations, and the reference lines of 1:1, respectively. All linear regressions are extremely significant (P < 0.0001). |
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