Global patterns and climatic drivers of above- and belowground net primary productivity in grasslands

Opportunities for carbon sequestration from removing or intensifying pasture-based beef production

Pastures, on which ruminant livestock graze, occupy one third of the earth's surface. Removing livestock from pastures can support climate change mitigation through carbon sequestration in regrowing vegetation and recovering soils, particularly in potentially forested areas. However, this would also decrease food and fiber production, generating a tradeoff with pasture productivity and the ruminant meat production pastures support. We evaluate the magnitude and distribution of this tradeoff globally, called the "carbon opportunity intensity" of pastures, at a 5-arcminute resolution. We find that removing beef-producing cattle from high-carbon intensity pastures could sequester 34 (22 to 43) GtC i.e. 125 (80 to 158) GtCO2 into ecosystems, which is an amount greater than global fossil CO2 emissions from 2021-2023. This would lead to only a minor loss of 13 (9 to 18)% of the global total beef production on pastures, predominantly within high- and upper-middle-income countries. If areas with low-carbon intensity pastures and less efficient beef production simultaneously intensified their beef production to 47% of OECD levels, this could fully counterbalance the global loss of beef production. The carbon opportunity intensity can inform policy approaches to restore ecosystems while minimizing food losses. Future work should aim to provide higher-resolution estimates for use at local and farm scales, and to incorporate a wider set of environmental indicators of outcomes beyond carbon.

Global convergence in terrestrial gross primary production response to atmospheric vapor pressure deficit

Atmospheric vapor pressure deficit (VPD) increases with climate warming and may limit plant growth. However, gross primary production (GPP) responses to VPD remain a mystery, offering a significant source of uncertainty in the estimation of global terrestrial ecosystems carbon dynamics. In this study, in-situ measurements, satellite-derived data, and Earth System Models (ESMs) simulations were analysed to show that the GPP of most ecosystems has a similar threshold in response to VPD: first increasing and then declining. When VPD exceeds these thresholds, atmospheric drought stress reduces soil moisture and stomatal conductance, thereby decreasing the productivity of terrestrial ecosystems. Current ESMs underscore CO2 fertilization effects but predict significant GPP decline in low-latitude ecosystems when VPD exceeds the thresholds. These results emphasize the impacts of climate warming on VPD and propose limitations to future ecosystems productivity caused by increased atmospheric water demand. Incorporating VPD, soil moisture, and canopy conductance interactions into ESMs enhances the prediction of terrestrial ecosystem responses to climate change.

Geographical patterns and determinants of insect biodiversity in China

Insects play important roles in the maintenance of ecosystem functioning and the provision of livelihoods for millions of people. However, compared with terrestrial vertebrates and angiosperms, such as the giant panda, crested ibis, and the metasequoia, insect conservation has not attracted enough attention, and a basic understanding of the geographical biodiversity patterns for major components of insects in China is lacking. Herein, we investigated the geographical distribution of insect biodiversity across multiple dimensions (taxonomic, genetic, and phylogenetic diversity) based on the spatial distribution and molecular DNA sequencing data of insects. Our analysis included 18 orders, 360 families, 5,275 genera, and 14,115 species of insects. The results revealed that Southwestern and Southeastern China harbored higher insect biodiversity and numerous older lineages, representing a museum, whereas regions located in Northwestern China harbored lower insect biodiversity and younger lineages, serving as an evolutionary cradle. We also observed that mean annual temperature and precipitation had significantly positive effects, whereas altitude had significantly negative effects on insect biodiversity in most cases. Moreover, cultivated vegetation harbored the highest insect taxonomic and phylogenetic diversity, and needleleaf and broadleaf mixed forests harbored the highest insect genetic diversity. These results indicated that human activities may positively contribute to insect spatial diversity on a regional scale. Our study fills a knowledge gap in insect spatial diversity in China. These findings could help guide national-level conservation plans and the post-2020 biodiversity conservation framework.

Plant size traits are key contributors in the spatial variation of net primary productivity across terrestrial biomes in China

Understanding the spatial variability of ecosystem functions is an important step forward in predicting changes in ecosystems under global transformations. Plant functional traits are important drivers of ecosystem functions such as net primary productivity (NPP). Although trait-based approaches have advanced rapidly, the extent to which specific plant functional traits are linked to the spatial diversity of NPP at a regional scale remains uncertain. Here, we used structural equation models (SEMs) to disentangle the relative effects of abiotic variables (i.e., climate, soil, nitrogen deposition, and human footprint) and biotic variables (i.e., plant functional traits and community structure) on the spatial variation of NPP across China and its eight biomes. Additionally, we investigated the indirect influence of climate and soil on the spatial variation of NPP by directly affecting plant functional traits. Abiotic and biotic variables collectively explained 62.6 % of the spatial differences of NPP within China, and 28.0 %-69.4 % across the eight distinct biomes. The most important abiotic factors, temperature and precipitation, had positive effects for NPP spatial variation. Interestingly, plant functional traits associated with the size of plant organs (i.e., plant height, leaf area, seed mass, and wood density) were the primary biotic drivers, and their positive effects were independent of biome type. Incorporating plant functional traits improved predictions of NPP by 6.7 %-50.2 %, except for the alpine tundra on the Qinghai-Tibet Plateau. Our study identifies the principal factors regulating NPP spatial variation and highlights the importance of plant size traits in predictions of NPP variation at a large scale. These results provide new insights for involving plant size traits in carbon process models.

Root carbon and soil temperature may be key drivers of below-ground biomass in grassland following prescribed fires in autumn and spring

Under global warming, fire and the season in which the fire occurs both have important impacts on grassland plant biomass. Still, the effect of fire on below-ground biomass (BB) along a natural aridity gradient and the main impact factors remain unclear. Here, we conducted a fire manipulation experiment (including un-fired, autumn fire and spring fire treatments) to investigate the effects of prescribed fire on BB and its critical determinants along a transect of grassland in northern China. BB had different response strategies in different aridity regions and fire seasons, despite above-ground biomass (AB) and root-shoot ratio were not significantly affected by fire. General linear regression models revealed that the fire changed the trend of increasing BB to decreasing along increasing aridity (p ＜ 0.05). Random forest model (RFM) and partial correlations revealed that the BB was primarily influenced by aridity, followed by the nitrogen (N) and phosphorus (P) concentration ratio of AB under un-fired disturbance. For autumn fire, the BB was primarily influenced by below-ground biomass carbon concentration (BB c), followed by the C and N concentration ratio of BB. For spring fire, the BB was primarily influenced by soil temperature (ST), followed by aridity and soil total phosphorus concentration (Soil p). Furthermore, partial least squares path model (PLS-PM) revealed that autumn fires weakened the effects of environmental factors on BB, while spring fires enhanced the effects of soil nutrients on BB. These suggested that fire disrupted the original stable nutrient dynamics of BB. Our results suggested that fire promoted the growth of BB in relatively humid areas (aridity = 0.51-0.53) while inhibited the growth of BB in relatively arid areas (aridity = 0.68-0.74). BB c and ST may be key drivers of BB after prescribed fire in autumn and spring.

An evaluation of topsoil carbon storage in Chinese deserts

Deserts are important components of the terrestrial ecosystem, and significantly affect the terrestrial carbon cycle. However, their carbon storage is poorly understood. To evaluate the topsoil carbon storage in Chinese deserts, we systematically collected topsoil samples (to a depth of 10 cm) from 12 deserts in northern China and analyzed their organic carbon storage. We used partial correlation and boosted regression tree (BRT) analysis to analyze the factors influencing the spatial distribution of soil organic carbon density based on climate, vegetation, soil grain-size distribution, and element geochemistry. The total organic carbon pool of Chinese deserts was 4.83 × 10⁸ t, the mean soil organic carbon density was 1.37 ± 0.18 kg C m^-2, and the mean turnover time was 16.50 ± 2.66 yr. With the largest area, the Taklimakan Desert had the highest topsoil organic carbon storage (1.77 × 10⁸ t). The organic carbon density was high in the east and low in the west, whereas the turnover time showed the opposite trend. The soil organic carbon density was >2 kg C m^-2 in the four sandy lands in the eastern region, and was greater than the values for the eight deserts (0.72 to 1.22 kg C m^-2). Grain-size (i.e., the silt and clay contents) had the strongest influence on the organic carbon density in Chinese deserts, followed by element geochemistry. Precipitation was the main climatic factor that affected the distribution of organic carbon density in the deserts. Based on climate and vegetation cover trends during the past 20 years, Chinese deserts have a high potential for future organic carbon sequestration.

Time Effects of Global Change on Forest Productivity in China from 2001 to 2017

With global warming, the concentrations of fine particulate matter (PM_2.5) and greenhouse gases, such as CO₂, are increasing. However, it is still unknown whether these increases will affect vegetation productivity. Exploring the impacts of global warming on net primary productivity (NPP) will help us understand how ecosystem function responds to climate change in China. Using the Carnegie-Ames-Stanford Approach (CASA) ecosystem model based on remote sensing, we investigated the spatiotemporal changes in NPP across 1137 sites in China from 2001 to 2017. Our results revealed that: (1) Mean Annual Temperature (MAT) and Mean Annual Precipitation (MAP) were significantly positively correlated with NPP (p < 0.01), while PM_2.5 concentration and CO₂ emissions were significantly negatively correlated with NPP (p < 0.01). (2) The positive correlation between temperature, rainfall and NPP gradually weakened over time, while the negative correlation between PM_2.5 concentration, CO₂ emissions and NPP gradually strengthened over time. (3) High levels of PM_2.5 concentration and CO₂ emissions had negative effects on NPP, while high levels of MAT and MAP had positive effects on NPP.

The urgent need to develop a new grassland map in China: based on the consistency and accuracy of ten land cover products

Grasslands are the most dominant terrestrial ecosystem in China, but few national grassland maps have been generated. The grassland resource map produced in the 1980s is widely used as background data, but it has not been updated for almost 40 years. Therefore, a reliable map depicting the current spatial distribution of grasslands across the country is urgently needed. In this study, we evaluated the grassland consistency and accuracy of ten land cover datasets (GLC2000, GlobCover, CCI-LC, MCD12Q1, CLUD, GlobeLand30, GLC-FCS30, CGLS-LC100, CLCD, and FROM-GLC) for 2000, 2010, and 2020 based on extensive fieldwork. We concluded that the area of these ten grassland products ranges from 107.80×10⁴ to 332.46×10⁴ km², with CLCD and MCD12Q1 having the highest area consistency. The spatial and sample consistency is highest in the regions of east-central Inner Mongolia, the Qinghai-Tibet Plateau and northern Xinjiang, while the distribution of southern grasslands is scattered and differs considerably among the ten products. MCD12Q1 is significantly more accurate than the other nine products, with an overall accuracy (OA) reaching 77.51% and a kappa coefficient of 0.51; CLCD is slightly less accurate than MCD12Q1 (OA=73.02%, kappa coefficient=0.45) and is more conducive to the fine monitoring and management of grassland because of its 30-meter resolution. The highest accuracy of grassland was found in the Inner Mongolia-Ningxia region and Qinghai-Tibet Plateau, while the accuracy was worst in the southeastern region. In the future grassland mapping, cartographers should improve the accuracy of the grassland distribution in South China and regions where grassland is confused with forest, cropland and bare land. We specify the availability of valuable data in existing land cover datasets for China's grasslands and call for researchers and the government to actively produce a new generation of grassland maps.

Precipitation and soil nutrients determine the spatial variability of grassland productivity at large scales in China

Changes in net primary productivity (NPP) to global change have been studied, yet the relative impacts of global change on grassland productivity at large scales remain poorly understood. Using 182 grassland samples established in 17 alpine meadows (AM) and 21 desert steppes (DS) in China, we show that NPP of AM was significantly higher than that of DS. NPP increased significantly with increasing leaf nitrogen content (LN) and leaf phosphorus content (LP) but decreased significantly with increasing leaf dry matter content (LDMC). Among all abiotic factors, soil nutrient factor was the dominant factor affecting the variation of NPP of AM, while the NPP of DS was mainly influenced by the changing of precipitation. All abiotic factors accounted for 62.4% of the spatial variation in the NPP of AM, which was higher than the ability to explain the spatial variation in the NPP of DS (43.5%). Leaf traits together with soil nutrients and climatic factors determined the changes of the grassland productivity, but the relative contributions varied somewhat among different grassland types. We quantified the effects of biotic and abiotic factors on grassland NPP, and provided theoretical guidance for predicting the impacts of global change on the NPP of grasslands.

Terrestrial carbon sinks in China and around the world and their contribution to carbon neutrality

Enhancing the terrestrial ecosystem carbon sink (referred to as terrestrial C sink) is an important way to slow down the continuous increase in atmospheric carbon dioxide (CO₂) concentration and to achieve carbon neutrality target. To better understand the characteristics of terrestrial C sinks and their contribution to carbon neutrality, this review summarizes major progress in terrestrial C budget researches during the past decades, clarifies spatial patterns and drivers of terrestrial C sources and sinks in China and around the world, and examines the role of terrestrial C sinks in achieving carbon neutrality target. According to recent studies, the global terrestrial C sink has been increasing from a source of (-0.2±0.9) Pg C yr^-1 (1 Pg=10¹⁵ g) in the 1960s to a sink of (1.9±1.1) Pg C yr^-1 in the 2010s. By synthesizing the published data, we estimate terrestrial C sink of 0.20-0.25 Pg C yr^-1 in China during the past decades, and predict it to be 0.15-0.52 Pg C yr^-1 by 2060. The terrestrial C sinks are mainly located in the mid- and high latitudes of the Northern Hemisphere, while tropical regions act as a weak C sink or source. The C balance differs much among ecosystem types: forest is the major C sink; shrubland, wetland and farmland soil act as C sinks; and whether the grassland functions as C sink or source remains unclear. Desert might be a C sink, but the magnitude and the associated mechanisms are still controversial. Elevated atmospheric CO₂ concentration, nitrogen deposition, climate change, and land cover change are the main drivers of terrestrial C sinks, while other factors such as fires and aerosols would also affect ecosystem C balance. The driving factors of terrestrial C sink differ among regions. Elevated CO₂ concentration and climate change are major drivers of the C sinks in North America and Europe, while afforestation and ecological restoration are additionally important forcing factors of terrestrial C sinks in China. For future studies, we recommend the necessity for intensive and long term ecosystem C monitoring over broad geographic scale to improve terrestrial biosphere models for accurately evaluating terrestrial C budget and its dynamics under various climate change and policy scenarios.

Decoupled responses of above- and below-ground stability of productivity to nitrogen addition at the local and larger spatial scale

Temporal stability of net primary productivity (NPP) is important for predicting the reliable provisioning of ecosystem services under global changes. Although nitrogen (N) addition is known to affect the temporal stability of aboveground net primary productivity (ANPP), it is unclear how it impacts that of belowground net primary productivity (BNPP) and NPP, and whether such effects are scale dependent. Here, using experimental N addition in a grassland, we found different responses of ANPP and BNPP stability to N addition at the local scale and that these responses propagated to the larger spatial scale. That is, N addition significantly decreased the stability of ANPP but did not affect the stability of BNPP and NPP at the two scales investigated. Additionally, spatial asynchrony of both ANPP and BNPP among communities provided greater stability at the larger scale and was not affected by N addition. Our findings challenge the traditional view that N addition would reduce ecosystem stability based on results from aboveground dynamics, thus highlighting the importance of viewing ecosystem stability from a whole system perspective.

Above- and belowground biomass allocation and its regulation by plant density in six common grassland species in China

Above- and belowground biomass allocation is an essential plant functional trait that reflects plant survival strategies and affects belowground carbon pool estimation in grasslands. However, due to the difficulty of distinguishing living and dead roots, estimation of biomass allocation from field-based studies currently show large uncertainties. In addition, the dependence of biomass allocation on plant species, functional type as well as plant density remains poorly addressed. Here, we conducted greenhouse manipulation experiments to study above- and belowground biomass allocation and its density regulation for six common grassland species with different functional types (i.e., C₃ vs C₄; annuals vs perennials) from temperate China. To explore the density regulation on the biomass allocation, we used five density levels: 25, 100, 225, 400, and 625 plant m^-2. We found that mean root to shoot ratio (R/S) values ranged from 0.04 to 0.92 across the six species, much lower than those obtained in previous field studies. We also found much lower R/S values in annuals than in perennials (C. glaucum and S. viridis vs C. squarrosa, L. chinensis, M. sativa and S. grandis) and in C₄ plants than in C₃ plants (C. squarrosa vs L. chinensis, M. sativa and S. grandis). In addition to S. grandis, plant density had significant effects on the shoot and root biomass fraction and R/S for the other five species. Plant density also affected the allometric relationships between above- and belowground biomass significantly. Our results suggest that R/S values obtained from field investigations may be severely overestimated and that R/S values vary largely across species with different functional types. Our findings provide novel insights into approximating the difficult-to-measure belowground living biomass in grasslands, and highlight that species composition and intraspecific competition will regulate belowground carbon estimation.