Large-Scale Analysis of the Spatiotemporal Changes of Net Ecosystem Production in Hindu Kush Himalayan Region

Terrestrial vegetation carbon sink analysis and driving mechanism identification in the Qinghai-Tibet Plateau

The estimation of terrestrial carbon sinks in the Qinghai-Tibet Plateau (QTP) still faces significant uncertainties, and the spatiotemporal dynamics of terrestrial carbon sinks along altitudinal gradients remain unexplored. Moreover, the driving mechanisms of terrestrial carbon sinks at the watershed scale in the QTP continue to be lacking. To address these research gaps, based on multi-source remote sensing data and meteorological data, this study calculated the Net Ecosystem Productivity (NEP) in the QTP from 2000 to 2020 using the Modis NPP-soil respiration model. Through the coefficient of variation (CV), the Mann-Kendall test (MK), and the spatial autocorrelation methods, the spatial distribution pattern and spatiotemporal trends of NEP were investigated. Employing a pixel accumulation method, the variation of NEP along altitudinal gradients was explored. Grey relation analysis, Pearson correlation analysis, and Geographical detector (GD) were used to investigate the driving mechanisms of NEP at the watershed scale. Results showed that: (1) the terrestrial ecosystem in the QTP served as a carbon sink, which produced a total of 2.04 Pg C from 2000 to 2020, and the multi-year average of total carbon sinks was 96.92 Tg C; (2) the spatial distribution of NEP shows a decreasing change from southeast to northwest, and the clustering characteristic of NEP is significant at the watershed scale; (3) the elevation of 4507 m we proposed is likely to be a key threshold for biophysical processes of the terrestrial ecosystems in the QTP; (4) the fluctuation and change trend of carbon sources and carbon sinks show significant differences between the East and West; (5) at the watershed scale, precipitation and temperature play a dominant role in the variation of NEP, while the impact of human activities on NEP variation is weak. Our study aims to address the existing knowledge gaps and provide valuable insights into the management of terrestrial carbon sinks in QTP.

The fusion of multiple scale data indicates that the carbon sink function of the Qinghai-Tibet Plateau is substantial

BACKGROUND

The Qinghai-Tibet Plateau is the "sensitive area" of climate change, and also the "driver" and "amplifier" of global change. The response and feedback of its carbon dynamics to climate change will significantly affect the content of greenhouse gases in the atmosphere. However, due to the unique geographical environment characteristics of the Qinghai-Tibet Plateau, there is still much controversy about its carbon source and sink estimation results. This study designed a new algorithm based on machine learning to improve the accuracy of carbon source and sink estimation by integrating multiple scale carbon input (net primary productivity, NPP) and output (soil heterotrophic respiration, Rh) information from remote sensing and ground observations. Then, we compared spatial patterns of NPP and Rh derived from the fusion of multiple scale data with other widely used products and tried to quantify the differences and uncertainties of carbon sink simulation at a regional scale.

RESULTS

Our results indicate that although global warming has potentially increased the Rh of the Qinghai-Tibet Plateau, it will also increase its NPP, and its current performance is a net carbon sink area (carbon sink amount is 22.3 Tg C/year). Comparative analysis with other data products shows that CASA, GLOPEM, and MODIS products based on remote sensing underestimate the carbon input of the Qinghai-Tibet Plateau (30-70%), which is the main reason for the severe underestimation of the carbon sink level of the Qinghai-Tibet Plateau (even considered as a carbon source).

CONCLUSIONS

The estimation of the carbon sink in the Qinghai-Tibet Plateau is of great significance for ensuring its ecological barrier function. It can deepen the community's understanding of the response to climate change in sensitive areas of the plateau. This study can provide an essential basis for assessing the uncertainty of carbon sources and sinks in the Qinghai-Tibet Plateau, and also provide a scientific reference for helping China achieve "carbon neutrality" by 2060.

Spatial and temporal variations of net ecosystem productivity in Xinjiang Autonomous Region, China based on remote sensing

Net ecosystem productivity (NEP), which plays a key role in the carbon cycle, is an important indicator of the ecosystem's carbon budget. In this paper, the spatial and temporal variations of NEP over Xinjiang Autonomous Region, China from 2001 to 2020 were studied based on remote sensing and climate re-analysis data. The modified Carnegie Ames Stanford Approach (CASA) model was employed to estimate net primary productivity (NPP), and the soil heterotrophic respiration model was used to calculate soil heterotrophic respiration. Then NEP was obtained by calculating the difference between NPP and heterotrophic respiration. The annual mean NEP of the study area was high in the east and low in the west, high in the north and low in the south. The 20-year mean vegetation NEP of the study area is 128.54 gC·m^-2, indicating that the study area is a carbon sink on the whole. From 2001 to 2020, the annual mean vegetation NEP ranged between 93.12 and 158.05 gC·m^-2, and exhibited an increasing trend in general. 71.46% of the vegetation area showed increasing trends of NEP. NEP exhibited a positive relationship with precipitation and a negative relationship with air temperature, and the correlation with air temperature was more significant. The work reveals the spatio-temporal dynamics of NEP in Xinjiang Autonomous Region and can provide a valuable reference for assessing regional carbon sequestration capacity.

Temperature Mediates the Dynamic of MODIS NPP in Alpine Grassland on the Tibetan Plateau, 2001–2019

Although alpine grassland net primary productivity (NPP) plays an important role in balancing the carbon cycle and is extremely vulnerable to climate factors, on the Tibetan Plateau, the generalized effect of climate factors on the NPP in areas with humid and arid conditions is still unknown. Hence, we determined the effects of precipitation and temperature on the MODIS NPP in alpine grassland areas from 2001 to 2019 according to information from humid and arid climatic regions. On a spatial scale, we found that temperature generated a larger effect on the NPP than precipitation did in humid regions, but as a primary factor, precipitation had an impact on the NPP in arid regions. These results suggest that temperature and precipitation are the primary limiting factors for plant growth in humid and arid regions. We also found that temperature produced a greater effect on the NPP in humid regions than in arid regions, but no significant differences were observed in the effects of precipitation on the NPP in humid and arid regions. In a time series (2001–2019), the effects of precipitation and temperature on the NPP presented fluctuating decrease (R2 = 0.28, p < 0.05) and increase (R2 = 0.24, p < 0.05) trends in arid regions. However, the effect of the climate on the NPP remained stable in humid regions. In both humid and arid regions, the dynamics of the NPP from 2001 to 2019 were mediated by an increase in temperature. Specifically, 35.9% and 2.57% of the dynamic NPP in humid regions and 45.1 and 7.53% of the dynamic NPP in arid regions were explained by variations in the temperature and precipitation, respectively. Our findings highlighted that grassland areas in humid regions can adapt to dynamic climates, but plants in arid regions are sensitive to changes in the climate. These findings can increase our understanding of climate and ecological responses and provide a framework for adapting management practices.