Response of gross primary productivity of vegetation to meteorological drought in the Yellow River Basin

Asymmetric response of vegetation GPP to impervious surface expansion: Case studies in the Yellow and Yangtze River Basins

China’s karst areas play an important role in regulating the global carbon dynamic and mitigating atmospheric CO2 concentration. Yet, extreme drought events have occurred frequently in recent years over China’s karst areas, which have a negative effect on the gross primary productivity (GPP) in the region. It is unclear whether gross primary productivity gains in the wet years can compensate for its losses in the dry years over the karst areas. In this study, we selected the asymmetry indices to assess the potential asymmetric response of gross primary productivity to the change in precipitation over China’s karst areas during the 2003 to 2018 period, using the gross primary productivity and precipitation dataset. Our results show that the gross primary productivity exhibits a positive asymmetry in response to precipitation changes, namely, the gains caused by increased precipitation in the wet years overcompensate the losses caused by decreased precipitation in the dry years. In addition, the gross primary productivity asymmetry shows an increasing trend over the study period despite extreme drought events occurring frequently, which is due to the response of gross primary productivity to drought has significantly decreased over the study period. For each biome, grasslands show the highest positive gross primary productivity asymmetry, indicating that the grassland biomes have a stronger capacity to utilize the increased precipitation during the wet years to increase gross primary productivity compared to other biomes. Furthermore, the gross primary productivity asymmetry over China’s karst areas can be effected by the precipitation asymmetry as well as mean annual precipitation. Our results will contribute to our knowledge of the response of gross primary productivity to precipitation changes in the karst areas of China.

The frequency and severity of wildfire events have increased significantly due to global warming, further disturbing the terrestrial ecosystem carbon cycle. Observations over the past several decades have shown that wildfires cause a dramatic decline in vegetation productivity. However, the biome‐specific responses of gross primary productivity (GPP) to wildfires remain uncleared. Here, structural equation modeling was employed to analyze the mechanisms underlying wildfires on GPP using moderate resolution imaging spectroradiometer (MODIS) satellite data along with climatic and vegetation information in South America over a 20‐year period from 2001 to 2020. We observed the biome‐specific responses in GPP to wildfires among vegetation types. In forest ecosystems, increased burning severity led to substantial reductions in GPP directly, whereas in savanna ecosystems, wildfires indirectly regulated GPP by altering soil moisture. In grasslands, burned area rather than wildfire severity dominated the decrease in GPP. These findings emphasize the crucial role of vegetation types in exploring the effects of wildfires on the terrestrial ecosystem carbon cycle.

The desert steppe ecosystem at the Northern Foothills of the Yinshan Mountains (NFYS) is characterized by its fragility and heightened sensitivity to global climate change. Understanding the response and lag effects of Gross Primary Productivity (GPP) to climate change is imperative for advancing ecological management and fostering sustainable development. The spatiotemporal dynamics of chlorophyll fluorescence-based GPP data and its responses to precipitation, temperature, and extreme climate from 2001 to 2023 were analyzed. The random forest model and the partial least squares regression model were employed to further elucidate the response mechanisms of GPP to extreme climate, with a specific focus on the lag effect. The findings revealed that the GPP in the NFYS exhibited distinct regional characteristics, demonstrating a predominantly increasing trend over the past 23 years. The region has experienced a warming and drying trend, marked by a decrease in the intensity and frequency of extreme precipitation events, and an increase in extremely high temperatures and consecutive hot days, except a slight, albeit insignificant, increase in precipitation in the northeastern part. GPP exhibits varying degrees of lag, ranging from one to three months, in response to both normal and extreme climatic conditions, with a more immediate response to extreme temperatures than to precipitation. The influence of different climatic conditions on the lag effects of GPP can amplify the negative effects of extreme temperatures and the positive impact of extreme precipitation. The anticipated trend towards a warmer and more humid climate is projected to foster an increase in GPP. This research is of great theoretical and practical significance for deeply understanding the adaptation mechanisms of ecosystems under the context of climate change, optimizing desertification control strategies, and enhancing regional ecological resilience.

Changes in the sizes of precipitation events in the context of global climate change may have profound impacts on ecosystem productivity in arid and semiarid grasslands. However, we still have little knowledge about to what extent grassland productivity will respond to an individual precipitation event. In this study, we quantified the duration, the maximum, and the time-integrated amount of the response of daily gross primary productivity (GPP) to an individual precipitation event and their variations with different sizes of precipitation events in a typical temperate steppe in Inner Mongolia, China. Results showed that the duration of GPP-response (tau(R)) and the maximum absolute GPP-response (GPP(max)) increased linearly with the sizes of precipitation events (P-es), driving a corresponding increase in time-integrated amount of the GPP-response (GPP(total)) because variations of GPPtotal were largely explained by tau (R) and GPP(max). The relative contributions of these two parameters to GPP(total) were strongly P-es-dependent. The GPP(max) contributed more to the variations of GPP(total) when P-es was relatively small (< 20 mm), whereas tau (R) was the main driver to the variations of GPP(total) when P-es was relatively large. In addition, a threshold size of at least 5 mm of precipitation was required to induce a GPP-response for the temperate steppe in this study. Our work has important implications for the modeling community to obtain an advanced understanding of productivity-response of grassland ecosystems to altered precipitation regimes.

The strong correlation between gross primary production (GPP) and sun-induced chlorophyll fluorescence (SIF) has been reported in many studies and is the basis of the SIF-based GPP estimation. However, GPP and SIF are not fully synchronous under various environmental conditions, which may destroy a stable GPP–SIF relationship. Therefore, exploring the difference between responses of GPP and SIF to the environment is essential to correctly understand the GPP–SIF relationship. As the common driver of GPP and SIF, the incident radiation could cause GPP and SIF to have similar responses to the environment, which may obscure the discrepancies in the responses of GPP and SIF to the other environmental variables, and further result in the ambiguity of the GPP–SIF relationship and uncertainties in the application of SIF. Therefore, we tried to exclude the dominant role of radiation in the responses of GPP and SIF to the environment based on the binning method, in which continuous tower-based SIF, satellite SIF, and eddy covariance GPP data from two growing seasons were used to investigate the differences in the responses of GPP and SIF to radiation, air temperature (Ta), and evaporation fraction (EF). We found that the following: (1) At both the site and satellite scales, there were divergences in the light response speeds between GPP and SIF which were affected by Ta and EF. (2) SIF and its light response curves were insensitive to EF and Ta compared to GPP, and the consistency in GPP and SIF light responses was gradually improved with the improvement of Ta and EF. (3) The dynamic slope values of the GPP–SIF relationship were mostly caused by the different sensitivities of GPP and SIF to EF and Ta. Our results highlighted that GPP and SIF were not highly consistent, having differences in environmental responses that further confused the GPP–SIF relationship, leading to complex SIF application.

Wildfire smoke covers entire continents, depositing aerosols and reducing solar radiation fluxes to millions of freshwater ecosystems, yet little is known about impacts on lakes. Here, we quantified trends in the spatial extent of smoke cover in California, USA, and assessed responses of gross primary production and ecosystem respiration to smoke in 10 lakes spanning a gradient in water clarity and nutrient concentrations. From 2006 − 2022, the maximum extent of medium or high-density smoke occurring between June-October increased by 300,000 km2. In the three smokiest years (2018, 2020, 2021), lakes experienced 23 − 45 medium or high-density smoke days, characterized by 20% lower shortwave radiation fluxes and five-fold higher atmospheric fine particulate matter concentrations. Ecosystem respiration generally declined during smoke cover, especially in low-nutrient, cold lakes, whereas responses of primary production were more variable. Lake attributes and seasonal timing of wildfires will mediate the effects of smoke on lakes.

The response of vegetation productivity to water availability provides a key link between the carbon and water cycles. Correctly representing this response in Earth System Models (ESMs) is essential for accurate modelling of the terrestrial carbon cycle and the evolution of the climate system. To investigate how well models capture this relationship at intraseasonal timescales, we use global datasets based on satellite observations to assess the land surface response to intraseasonal precipitation events, and evaluate the performance of CMIP6 ESMs in representing this response in the recent historical period. Whereas models are able to capture the observed surface soil moisture (SSM) response with reasonable agreement, there are large inter-model discrepancies in the response of Gross Primary Productivity (GPP), both in magnitude and timing, even in regions where land cover is similar between models. In particular, ACCESS-ESM and NorESM produce much lower-amplitude GPP responses to rainfall than UKESM and CNRM-ESM. All the models studied are able to represent that the regional amplitude of the GPP response is positively correlated with the amplitude of the SSM response, and negatively correlated with the amplitude of the vapour pressure deficit (VPD) response. All models except NorESM also capture that stronger SSM responses are associated with faster GPP responses. However, the models differ in their sensitivity to these drivers, and can produce very different GPP responses from similar variations in SSM and VPD, particularly in climatologically dry regions. This highlights the need for a better understanding of the uncertainties in the representation of water-vegetation relationships in ESMs, such as the effect of atmospheric vapour pressure deficit on stomatal conductance and the control of soil moisture stress on GPP.

Based on daily meteorological data at 43 gauging stations in the Pearl River basin and 65 gauging stations in the Yellow River basin, we analyze changing properties of actual evapotranspiration (ETa), reference evapotranspiration (ETref) and precipitation in these two river basins. In our study, Pearl River basin is taken as the ‘energy-limited’ system and the Yellow River basin as the ‘water-limited’ system. The results indicate decreasing ETa in the Pearl River and Yellow River basin. However, different changing properties are detected for ETref when compared to ETa. The middle and upper Yellow River basin are characterized by increasing ETref values, whereas the Pearl River basin is dominated by decreasing ETref values. This result demonstrates enhancing drying force in the Yellow River basin. ETa depends mainly on the changes of precipitation amount in the Yellow River basin. In the Pearl River basin, however, ETa changes are similar to those of ETref, i.e. both are in decreasing trend and which may imply weakening hydrological cycle in the Pearl River basin. Different influencing factors are identified behind the ETa and ETref in the Pearl River and Yellow River basin: In the Pearl River basin, intensifying urbanization and increasing aerosol may contribute much to the evapotranspiration changes. Variations of precipitation amount may largely impact the spatial and temporal patterns of ETa in the Yellow River basin. The current study is practically and scientifically significant for regional assessment of water resource in the arid and humid regions of China under the changing climate.

Disentangling climate effects of greenhouse gas emissions and land cover change on future gross primary productivity in the Yellow River basin, China.

The global hydrological cycle is predicted to be intensified under the warming climate, with more extreme precipitation events and longer dry spell in between. Here, we evaluated how extreme precipitation events (EPEs) with antecedent dry (dry-EPEs) and wet (wet-EPEs) water conditions influence carbon exchange along gradient of arid, semi-arid, and sub-humid ecosystems based on eddy covariance datasets. After EPEs, ecosystem respiration and gross primary productivity (GPP) were stimulated by pulses of soil moisture in arid and semi-arid regions, but suppressed by decreased soil temperature in sub-humid region. Antecedent water condition determined asynchronous response of ecosystem respiration and GPP to EPEs, and therefore fluctuations in net carbon balance. Net carbon uptake capacity was enhanced immediately following wet-EPEs because of more rapid and greater response of GPP than respiration. However, after dry-EPEs, net carbon uptake capacity decreased immediately and increased thereafter because the response of GPP to dry-EPEs lagged behind ecosystem respiration. More antecedent precipitation further stimulated accumulative net carbon uptake. In general, the accumulated net carbon uptake within 3 weeks after wet-EPEs was two times and seven times of that after dry-EPEs in arid and semi-arid region, respectively. In sub-humid region, ecosystems acted as a carbon sink after wet-EPEs, but as a carbon source after dry-EPEs. We conclude that antecedent water conditions and local climate regimes need to be considered when interpreting the response of carbon exchange to EPEs in dryland ecosystems.

Runoffs in the Yellow River and Yangtze River basins, China, have been changing constantly during the last half century. In this paper, data from eight river gauging stations and 529 meteorological stations, inside and adjacent to the study basins, were analyzed and compared to quantify the hydrological processes involved, and to evaluate the role of human activities in changing river discharges. The Inverse Distance Weighted (IDW) interpolation method was used to obtain climatic data coverage from station observations. According to the runoff coefficient equation, the effect of human activities and climate can be expressed by changes in runoff coefficients and changes in precipitation, respectively. Annual runoff coefficients were calculated for the period 1950–2008, according to the correlation between respective hydrological series and regional precipitation. Annual precipitation showed no obvious trend in the upper reaches of the Yellow River but a marked downward trend in the middle and downstream reaches, with declines of 8.8 and 9.8 mm/10 a, respectively. All annual runoff series for the Yellow River basin showed a significant downward trend. Runoff declined by about 7.8 mm/10 a at Sanmenxia and 10.8 mm/10 a at Lijin. The series results indicated that an abrupt change occurred in the late 1980s to early 1990s. The trend of correlations between annual runoff and precipitation decreased significantly at the Yellow River stations, with rates ranging from 0.013/10 a to 0.019/10 a. For the hydrologic series, all precipitation series showed a downward trend in the Yangtze River basin with declines ranging from about 24.7 mm/10 a at Cuntan to 18.2 mm/10 a at Datong. Annual runoff series for the upper reaches of the Yangtze River decreased significantly, at rates ranging from 9.9 to 7.2 mm/10 a. In the middle and lower reaches, the runoff series showed no significant trend, with rates of change ranging from 2.1 to 2.9 mm/10 a. Human activities had the greatest influence on changes in the hydrological series of runoff, regardless of whether the effect was negative or positive. During 1970–2008, human activities contributed to 83% of the reduction in runoff in the Yellow River basin, and to 71% of the increase in runoff in the Yangtze River basin. Moreover, the impacts of human activities across the entire basin increased over time. In the 2000s, the impact of human activities exceeded that of climate change and was responsible for 84% of the decrease and 73% of the increase in runoff in the Yellow River and Yangtze River basins, respectively. The average annual runoff from 1980 to 2008 fell by about 97%, 83%, 83%, and 91%, compared with 1951–1969, at the Yellow River stations Lanzhou, Sanmenxia, Huayuankou and Lijin, respectively. Most of the reduction in runoff was caused by human activities. Changes in precipitation also caused reductions in runoff of about 3%, 17%, 17%, and 9% at these four stations, respectively. Falling precipitation rates were the main explanation for runoff changes at the Yangtze River stations Cuntan, Yichang, Hankou, and Datong, causing reductions in runoff of 89%, 74%, 43%, and 35%, respectively. Underlying surface changes caused decreases in runoff in the Yellow River basin and increases in runoff in the Yangtze River basin. Runoff decreased in arid areas as a result of increased water usage, but increased in humid and sub-humid areas as a result of land reclamation and mass urbanization leading to decreases in evaporation and infiltration.

It is generally agreed that El Nino can be classified into East Pacific (EP) and Central Pacific (CP) types. Nevertheless, little is known about the relationship between these two types of El Nino and land surface climate elements. This study investigates the linkage between EP/CP El Nino and summer streamflow over the Yellow and Yangtze River basins and their possible mechanisms. Over the Yellow River basin, the anomalous streamflow always manifests as positive (negative) in EP (CP) years, with a correlation coefficient of 0.39 (−0.37); while over the Yangtze River basin, the anomalous streamflow shows as positive in both EP and CP years, with correlation coefficients of 0.72 and 0.48, respectively. Analyses of the surface hydrological cycle indicate that the streamflow is more influenced by local evapotranspiration (ET) than precipitation over the Yellow River basin, while it is dominantly affected by precipitation over the Yangtze River basin. The different features over these two river basins can be explained by the anomalous atmospheric circulation, which is cyclonic (anticyclonic) north (south) of 30°N over East Asia. EP years are dominated by two anticyclones, which bring strong water vapor convergence and induce more precipitation but less ET, and subsequently increase streamflow and flooding risks. In CP years, especially over the Yellow River basin, two cyclones dominate and lead to water vapor divergence and reduce moisture arriving. Meanwhile, the ET enhances mainly due to local high surface air temperature, which further evaporates water from the soil. As a result, the streamflow decreases, which will then increase the drought risk.

The Yellow and Yangtze River basins are the most important basins in China due to their environment and natural and socioeconomic conditions, and they are highly sensitive to extreme climate events. In this study, we used daily maximum and minimum temperature data gathered from 892 meteorological stations to analyse the spatiotemporal variations in temperature extremes in the Yellow and Yangtze River basins during 1961–2014 and identified correlations with the geographic location and atmospheric circulation patterns. The results indicated that annual mean maximum and minimum temperatures (TXmandTNm), most warm extremes and some cold extremes (minimum of the minimum temperature and maximum temperature,TNnandTXn) generally showed low values in the northwestern region of the Yellow and Yangtze basins, while the diurnal temperature range (DTR) and some cold extremes (ice days,ID0and frost days,FD0) were generally higher in the northwest of the two basins.TXm,TNm, all warm extremes and some cold extremes (TNnandTXn) showed significant increasing trends in both basins. The increase in the extreme temperature was between 0.17–0.38°C/decade in the Yellow basin, while the interval was 0.15–0.38°C/decade in the Yangtze basin. DTR decreased by −0.07 days/decade in the former and −0.05 days/decade in the latter. Furthermore, warm event days increased by 1.38–3.52 and 1.42–2.65 days/decade in the Yellow and Yangtze basins, respectively. At the same time, the cold event days decreased by −1.90 to −3.47 and −0.20 to −2.70 days/decade in the respective basins. In terms of the spatial patterns, most stations that displayed significant trends were located over the Loess Plateau in the Yellow River basins; Sichuan basin and the lower reaches of the Yangtze River basins. Moreover, almost all of the temperature extremes exhibited the largest trends in spring and winter in the two basins. Most temperature extremes showed strong correlations with longitude and altitude and the Atlantic Multidecadal Oscillation (AMO) displayed significant correlations with almost all of the temperature extremes, except DTR,TNnandTXn; the East Atlantic/Western Russia (EA/WR) was also related to many temperature extremes. Finally, most temperature observations showed abrupt changes in the 1990s, and the timing in the Yangtze River basin was generally later than that in the Yellow River basin.

Precipitation and other hydrologic variables play important roles in river basins. In this study, summer precipitation, evaporation, and water vapor transport from 16 models that have participated in Coupled Model Intercomparison Project Phase 5 (CMIP5) for the Yellow River basin (a water-limited basin) and the Yangtze River basin (an energy-limited basin) over the period 1986–2005 are analyzed and evaluated. The results suggest that most models tend to overestimate precipitation in the Yellow River basin, whereas precipitation in the Yangtze River basin is generally well simulated. Models that overestimate precipitation in the Yellow River basin also simulate evaporation with large positive biases. For water vapor transport, models and reanalysis data concur that both basins are moisture sinks in summer. In addition, models that strongly overestimate precipitation in the Yellow River basin tend to produce strong water vapor convergence in that region, which is likely to be related to the situation that the western Pacific subtropical high (WPSH) simulated by these models strengthens and advances further westward and northward, resulting in stronger water vapor convergence in the Yellow River basin. Moreover, convective precipitation biases simulated by the models are also partially responsible for their total precipitation biases. Finally, summer precipitation and evaporation are negatively correlated in the Yangtze River basin, whereas the relation between these variables is weak in the Yellow River basin. In both basins, precipitation and water vapor convergence are positively correlated, which is well simulated by all models.