Spatiotemporal Change of Net Primary Productivity and Its Response to Climate Change in Temperate Grasslands of China

Warming suppresses grassland recovery in biomass but not in community composition after grazing exclusion in a Mongolian grassland

We conducted a 4-year temperature manipulation experiment in a Mongolian grassland to examine the effect of daytime and nighttime warming on grassland recovery after grazing exclusion. After constructing a livestock exclusion fence in the grassland, we established daytime and daytime-and-nighttime warming treatments within the fenced area by a combination of open-top chambers (OTC) and electric heaters. We measured the numbers of plants and aboveground biomass by species after recording percentage vegetation cover every summer for three warming treatments inside the fence-non-warming, daytime warming, and daytime-and-nighttime warming-and for the grassland outside of the fence. OTCs increased daytime temperature by about 2.0 °C, and heaters increased nighttime temperature by 0.9 °C during the growing period. Grazing exclusion had little effect on grassland biomass but reduced the abundance of poorly palatable species and modified plant community composition. Daytime warming decreased soil moisture and lowered aboveground biomass within the fenced grassland but had little effect on plant community composition. Nighttime warming lowered soil moisture further but its effects on grassland biomass and community composition were undetectable. We concluded that recovery of plant biomass in grasslands degraded by grazing would be lowered by future climate warming through soil drying. Because warming had little effect on the recovery of community composition, adverse effects of warming on grassland recovery might be offset by improving plant productivity through mitigation of soil drying by watering. Soil drying due to nighttime warming might have detectable effects on vegetation when warming persists for a long time.

Climate change and Land Use/Land Cover Change (LUCC) leading to spatial shifts in net primary productivity in Anhui Province, China

As an important part of terrestrial carbon cycle research, net primary productivity is an important parameter to evaluate the quality of terrestrial ecosystem and plays an important role in the analysis of global climate change and carbon balance. Anhui Province is in the Yangtze River Delta region in eastern China. Based on the theoretical basis of CASA model, this paper uses MODIS NDVI, vegetation type data, meteorological data, and LUCC to estimate the NPP of Anhui Province during 2001-2020 and analyzes its spatial-temporal pattern. The results showed that the average NPP in Anhui province was 508.95 gC· (m2 ·a) -1, and the spatial heterogeneity of NPP was strong, and the high value areas were mainly distributed in the Jiangnan Mountains and Dabie Mountains. NPP increased in most areas of Anhui Province, but decreased significantly in 17.60% of the area, mainly in the central area affected by urban and rural expansion and the transformation of the Yangtze River. The dynamic change of NPP in Anhui province is the result of climate change and land use change. Meteorological data are positively correlated with NPP. Among them, the correlation between temperature and solar radiation is higher, and the correlation between NPP and precipitation is the lowest among the three. The NPP of all land cover types was more affected by temperature than precipitation, especially forest land and grassland. The decrease of cultivated land and the increase of Artificial Surfaces (AS) may have contributed to the decrease of NPP in Anhui Province. Human activities have weakened the increase in NPP caused by climate change. In conclusion, this study refined the drivers of spatial heterogeneity of NPP changes in Anhui province, which is conducive to rational planning of terrestrial ecosystems and carbon balance measures.

Interannual Variations in Terrestrial Net Ecosystem Productivity and Climate Attribution in the Southern Hilly Region of China

The vegetation ecosystem in the southern hilly region of China (SHRC) plays a crucial role in the country's carbon reservoir. Clarifying the dynamics of net primary productivity (NPP) in this area and its response to climate factors in the context of climate change is important for national forest ecology, management, and carbon neutrality efforts. This study, based on remote sensing and meteorological data spanning the period 2001 to 2021, aims to unveil the spatiotemporal patterns of vegetation productivity and climate factors in the southern hilly region, explore interannual variation characteristics of vegetation productivity with altitude, and investigate the response characteristics of NPP to various climate factors. The results indicate that from 2001 to 2021, the annual average NPP in the southern hilly region had a significant increasing trend of 2.13 ± 0.78 g m-2 a-1. The trend of NPP varies significantly with altitude. Despite a general substantial upward trend in vegetation NPP, regions at lower elevations exhibit a faster rate of increase, suggesting a diminishing difference in the NPP of different elevation ranges. The overall rise in average temperature has positive implications for the southern hilly region, while the impact of precipitation on vegetation NPP demonstrates noticeable spatial heterogeneity. Regions in which vegetation NPP is significantly negatively correlated with precipitation are mainly concentrated in the southern areas of Guangdong, Fujian, and Jiangxi provinces. In contrast, other regions further away from the southeastern coast tend to exhibit a positive correlation. Over the past two decades, there has been an asymmetry in the diurnal temperature variation in the SHRC, with the nighttime warming rate being 1.8 times that of the daytime warming rate. The positive impact of daytime warming on NPP of vegetation is more pronounced than the impact of nighttime temperature changes. Understanding the spatiotemporal patterns of NPP in the SHRC and the characteristics of its response to climate factors contributes to enhancing our ability to protect and manage vegetation resources amidst the challenges of global climate change.

Change and relationship between growing season metrics and net primary productivity in forestland and grassland in China

BACKGROUND

Vegetation phenology can characterize ecosystem functions and plays a key role in the dynamics of plant productivity. Here we investigated the changes in growing season metrics (start of growing season, SOS; end of growing season, EOS; length of growing season, LOS) and their relationships with net primary productivity (NPP) in forestland and grassland in China during 1981-2016.

RESULTS

SOS advanced, EOS delayed, LOS prolonged and NPP increased significantly in 23.7%, 21.0%, 40.5% and 19.9% of the study areas, with an average rate of 3.9 days decade-1, 3.3 days·decade-1, 6.7 days·decade-1 and 10.7 gC m-2·decade-1, respectively. The changes in growing season metrics were obvious in Northwest China (NWC) and North China (NC), but the least in Northeast China (NEC). NPP was negatively correlated with SOS and positively correlated with EOS and LOS in 22.0%, 16.3% and 22.8% of the study areas, respectively, and the correlation between NPP and growing season metrics was strong in NWC, NC and Southwest China (SWC), but weak in NEC and South China (SC).

CONCLUSION

The advanced SOS, delayed EOS and prolonged LOS all contribute to the increased NPP in forestland and grassland in China, especially in NWC, NC and SWC. This study also highlights the need to further study the response of NPP to growing season changes in different regions and under the influence of multiple factors.

Should time-lag and time-accumulation effects of climate be considered in attribution of vegetation dynamics? Case study of China's temperate grassland region

Although the time-lag and time-accumulation effects (TLTAEs) of climatic factors on vegetation growth have been investigated extensively, the uncertainties caused by disregarding TLTAEs in the attribution analysis of long-term changes in vegetation remain unclear. This hinders our understanding of the associated changes in ecosystems and the effects of climate change. In this study, using multiple methods, we evaluate the biases of attribution analyses of vegetation dynamics caused by the non-consideration of TLTAEs in the temperate grassland region (TGR) of China from 2000 to 2019. Based on the datasets of the normalized difference vegetation index (NDVI), temperature (TMP), precipitation (PRE), and solar radiation (SR), the temporal reaction patterns of vegetation are analyzed, and the relationships among these variables under two scenarios (considering and disregarding TLTAEs) are compared. The results indicate that most areas of the TGR show a greening trend. A time-lag or time-accumulation effect of the three climatic variables is observed in most areas with significant spatial differences. The lagged times of the vegetation response to PRE are particularly prominent, with an average of 2.12 months in the TGR. When the TLTAE is considered, the areas where changes in the NDVI are affected by climatic factors expanded significantly, whereas the explanatory power of climate change on NDVI change increased by an average of 9.3% in the TGR; these improvements are more prominent in relatively arid areas. This study highlights the importance of including TLTAEs in the attribution of vegetation dynamics and the assessment of climatic effects on ecosystems.

Spatiotemporal dynamics of net primary productivity and its influencing factors in the middle reaches of the Yellow River from 2000 to 2020

Introduction

Net primary productivity (NPP) is an important indicator used to characterize the productivity of terrestrial ecosystems. The spatial distribution and dynamic change in NPP are closely related to regional climate, vegetation growth and human activities. Studying the spatiotemporal dynamics of NPP and its influencing factors plays a vital role in understanding ecosystem carbon sink capacity.

Methods

Based on MODIS-NPP data, meteorological data, and land use data from 2000 to 2020, we analyzed the spatiotemporal variation characteristics and influencing factors of NPP in the middle reaches of the Yellow River (MRYR) by using unary linear regression analysis, third-order partial correlation analysis, and Sen+Mann-Kendall trend analysis.

Results

The results showed that the annual average NPP of the MRYR was 319.24 gCm-2a-1 with a spatially decreasing trend from the southern part to the northern part. From 2000 to 2020, the annual average NPP experienced a fluctuating upward trend at a rate of 2.83 gCm-2a-1, and the area with a significant upward trend accounted for 87.68%. The NPP of different land use types differed greatly, in which forest had the greatest increase in NPP. Temperature had a negative correlation with NPP in most parts of the MRYR. Water vapor pressure promoted the accumulation of NPP in the northwestern MRYR. The areas with a positive correlation between NPP and water vapor pressure accounted for 87.6%, and 20.43% of the MRYR area passed the significance test of P< 0.05.

Conclusion

The results of the study highlight the impact of climate factors and land-use changes on NPP and provide theoretical guidance for high-quality sustainable development in the MRYR.

Spatiotemporal variation in vegetation phenology and its response to climate change in marshes of Sanjiang Plain, China

Sanjiang Plain is the largest marsh distribution area of China, and marshes in this region significantly affect regional carbon cycle and biodiversity protection. The vegetation phenology of marsh significantly affects the energy exchange and carbon cycle in that region. Under the influence of global climatic change, identifying the changes in phenology and their responses to climatic variation in marshes of Sanjiang Plain is essential for predicting the carbon stocks of marsh ecosystem in that region. Using climate and NDVI data, this paper analyzed the spatiotemporal variations in the start (SOS), end (EOS), and length (LOS) of vegetation growing season and explored the impacts of climatic variation on vegetation phenology in marshes of Sanjiang Plain. Results showed that the SOS advanced by 0.30 days/a, and EOS delayed by 0.23 days/a, causing LOS to increase significantly (p < .05) by 0.53 days/a over marshes of Sanjiang Plain. Spatially, the large SOS advance and EOS delay resulted in an obvious increasing trend for LOS in northern Sanjiang Plain. The rise of spring and winter temperatures advanced the SOS and increased the LOS, and the rise in temperature in autumn delayed the EOS in marshes of Sanjiang Plain. Our findings highlight the necessity of considering seasonal climatic conditions in simulating marsh vegetation phenology and indicate that the different influences of climatic variation on marsh vegetation phenology in different regions should be fully considered to assess the marsh ecosystem response to climatic change in Sanjiang Plain.