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. 2022 Jun 21:13:920086.
doi: 10.3389/fpls.2022.920086. eCollection 2022.

Spatiotemporal Variation in Aboveground Biomass and Its Response to Climate Change in the Marsh of Sanjiang Plain

Yiwen Liu  1   2 , Xiangjin Shen  1 , Yanji Wang  1   2 , Jiaqi Zhang  1 , Rong Ma  1   3 , Xianguo Lu  1 , Ming Jiang  1
Affiliations

Spatiotemporal Variation in Aboveground Biomass and Its Response to Climate Change in the Marsh of Sanjiang Plain

Yiwen Liu et al. Front Plant Sci. .

Abstract

The Sanjiang Plain has the greatest concentration of freshwater marshes in China. Marshes in this area play a key role in adjusting the regional carbon cycle. As an important quality parameter of marsh ecosystems, vegetation aboveground biomass (AGB) is an important index for evaluating carbon stocks and carbon sequestration function. Due to a lack of in situ and long-term AGB records, the temporal and spatial changes in AGB and their contributing factors in the marsh of Sanjiang Plain remain unclear. Based on the measured AGB, normalized difference vegetation index (NDVI), and climate data, this study investigated the spatiotemporal changes in marsh AGB and the effects of climate variation on marsh AGB in the Sanjiang Plain from 2000 to 2020. Results showed that the marsh AGB density and annual maximum NDVI (NDVImax) had a strong correlation, and the AGB density could be accurately calculated from a power function equation between NDVImax and AGB density (AGB density = 643.57 × NDVI max 4 . 2474 ). According to the function equation, we found that the AGB density significantly increased at a rate of 2.47 g·C/m2/a during 2000-2020 in marshes of Sanjiang Plain, with the long-term average AGB density of about 282.05 g·C/m2. Spatially, the largest increasing trends of AGB were located in the north of the Sanjiang Plain, and decreasing trends were mainly found in the southeast of the study area. Regarding climate impacts, the increase in precipitation in winter could decrease the marsh AGB, and increased temperatures in July contributed to the increase in the marsh AGB in the Sanjiang Plain. This study demonstrated an effective approach for accurately estimating the marsh AGB in the Sanjiang Plain using ground-measured AGB and NDVI data. Moreover, our results highlight the importance of including monthly climate properties in modeling AGB in the marshes of the Sanjiang Plain.

Keywords: NDVI; Sanjiang Plain; biomass; climatic change; marsh wetland.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Distributions of the marsh, meteorological stations, and sample sites of aboveground biomass (ABG) at the Sanjiang Plain.
Figure 2
Figure 2
Equation between maximum normalized difference vegetation index (NDVImax) and observed AGB density (A), and comparison between estimated AGB density and observed AGB density (B) in the marsh of the Sanjiang Plain.
Figure 3
Figure 3
Distributions of long-term average AGB density (g·C/m2) (A) and change trends of AGB density (g·C/m2/a) (B) in the marsh of the Sanjiang Plain from 2000 to 2020.
Figure 4
Figure 4
Temporal variation of AGB density in Sanjiang Plain's marshes during 2000–2020.
Figure 5
Figure 5
Spatial patterns in relationships of marsh AGB with annual precipitation (A), Tmean (B), Tmax (C) and Tmin (D) on the Sanjiang Plain marshes from 2000 to 2020.
Figure 6
Figure 6
Spatial patterns in relationships of AGB with precipitation (A), Tmean (B), Tmax (C), and Tmin (D) in January on the Sanjiang Plain marshes from 2000 to 2020.
Figure 7
Figure 7
Spatial patterns in relationships of AGB with precipitation (A), mean temperature (Tmean) (B), maximum temperature (Tmax) (C), and minimum temperature (Tmin) (D) in July on the Sanjiang Plain marshes from 2000 to 2020.
Figure 8
Figure 8
Correlation coefficients between marsh AGB and precipitation in January and mean temperature in July in two different regions of the Sanjiang Plain, south of 47°N ( ≤ 47°N) and north of 47°N (>47°N). ** and * mean significantly at the levels of p < 0.01 and p < 0.05, respectively.
Figure 9
Figure 9
Change trends in annual precipitation (mm/a) (A), Tmean (°C/a) (B), Tmax (°C/a) (C), and Tmin (°C/a) (D) in marshes of the Sanjiang Plain from 2000 to 2020.
Figure 10
Figure 10
Change trends in precipitation (mm/a) (A), Tmean (°C/a) (B), Tmax (°C/a) (C), and Tmin (°C/a) (D) in January in marshes of the Sanjiang Plain from 2000 to 2020.
Figure 11
Figure 11
Change trends in precipitation (mm/a) (A), Tmean (°C/a) (B), Tmax (°C/a) (C), and Tmin (°C/a) (D) in July in marshes of the Sanjiang Plain from 2000 to 2020.
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