Biome Types Research Articles

Disentangling the Effects of Atmospheric and Soil Dryness on Autumn Phenology across the Northern Hemisphere

In recent decades, drought has intensified along with continuous global warming, significantly impacting terrestrial vegetation. High atmospheric water demand, indicated by vapor pressure deficit (VPD), and insufficient soil moisture (SM) are considered the primary factors causing drought stress in vegetation. However, the influences of VPD and SM on the autumn phenology are still unknown. Using satellite observations and meteorological data, we examined the impacts of VPD and SM on the end of the growing season (EOS) across the Northern Hemisphere (>30°N) from 1982 to 2022. We found that VPD and SM were as important as temperature, precipitation, and radiation in controlling the variations in the EOS. Moreover, the EOS was predominantly influenced by VPD or SM in more than one-third (33.8%) of the study area. In particular, a ridge regression analysis indicated that the EOS was more sensitive to VPD than to SM and the other climatic factors, with 25% of the pixels showing the highest sensitivity to VPD. In addition, the effects of VPD and SM on the EOS varied among biome types and climate zones. VPD significantly advanced the EOS in 25.8% of temperate grasslands, while SM had the greatest impact on advancing the EOS in 17.7% of temperate coniferous forests. Additionally, 27.7% of the midlatitude steppe (BSk) exhibited a significant negative correlation between VPD and the EOS, while 19.4% of the marine west coast climate (Cfb) showed a positive correlation between SM and the EOS. We also demonstrated that the correlation between VPD and the EOS was linearly affected by VPD and the leaf area index, while the correlation between SM and the EOS was affected by SM, precipitation, and the leaf area index. Our study highlights the importance of VPD and SM in regulating autumn phenology and enhances our understanding of terrestrial ecosystem responses to climate change.

Was the steppe bison a grazing beast in Pleistocene landscapes?

The history and palaeoecology of the steppe bison (Bison priscus) remain incompletely understood despite its widespread distribution. Using dental microwear textural analysis (DMTA) and vegetation modelling, we reconstructed the diet and assessed the habitat of steppe bison inhabiting Eurasia and Alaska since the Middle Pleistocene. During the Late Pleistocene, steppe bison occupied a variety of biome types: from the mosaic of temperate summergreen forest and steppe/temperate grassland (Serbia) to the tundra biomes (Siberia and Alaska). Despite the differences in the identified biome types, the diet of steppe bison did not differ significantly among populations in Eurasia. DMTA classified it as a mixed forager in all populations studied. The DMTA of Bb1 bison-a recently identified genetically extinct sister-clade of Bison bonasus-was typical of a highly grazing bovid species and differed from all B. priscus populations. The results of the study temper the common perception that steppe bison were grazers in steppe habitats. The dietary plasticity of the steppe bison was lower when compared with modern European bison and may have played an important role in its extinction, even in the stable tundra biome of eastern Siberia, where it has survived the longest in all of Eurasia.

Impact of extreme seasonal drought on ecosystem carbon‒water coupling across China

Water use efficiency (WUE) is a critical evaluation indicator of ecosystem responses to climate change and its extremes. However, the influence of the timing of extreme drought on the variation of ecosystem WUE under severe water stress has not been studied extensively. In particular, the modulation of drought impacts on WUE under regional hydro-climatic conditions and biome types is poorly understood. Considering observation-based ecosystem flux and drought index datasets, this study examined the impact of extreme seasonal drought on WUE in China and attempted to reveal the underlying drivers of seasonal variations in drought impacts. Results showed that the direction and magnitude of drought impacts on WUE depend on the occurrence time of extreme drought and the seasonal dynamics of regional ecological and climatic conditions. Across the vegetated regions in China, the most widespread reduction in WUE under extreme drought conditions was observed in summer, whereas approximately 60% of the study area showed positive changes in WUE under extreme drought conditions in spring. Furthermore, the co-regulation of drought characteristics and background environmental conditions in determining the impacts of extreme seasonal drought on ecosystem WUE is highlighted. Classification and regression tree analysis results illustrate that leaf area index (LAI) and drought timing dominated ecosystem WUE variation in response to extreme drought in China. Regions with lower LAI experienced more serious reductions in WUE under extreme drought. These findings indicate the importance of accounting for the interaction between drought seasonality and biome features in assessing drought impacts, thus contributing to improving the modelling of terrestrial ecosystem responses to climate extremes under global warming.

Temperature, not net primary productivity, drives continental-scale variation in insect flight activity.

The amount of energy available in a system constrains large-scale patterns of abundance. Here, we test the role of temperature and net primary productivity as drivers of flying insect abundance using a novel continental-scale data source: weather surveillance radar. We use the United States NEXRAD weather radar network to generate a near-daily dataset of insect flight activity across a gradient of temperature and productivity. Insect flight activity was positively correlated with mean annual temperature, explaining 38% of variation across sites. By contrast, net primary productivity did not explain additional variation. Grassland, forest and arid-xeric shrubland biomes differed in their insect flight activity, with the greatest abundance in subtropical and temperate grasslands. The relationship between insect flight abundance and temperature varied across biome types. In arid-xeric shrublands and in forest biomes the temperature-abundance relationship was indirectly (through net primary productivity) or directly (in the form of precipitation) mediated by water availability. These results suggest that temperature constraints on metabolism, development, or flight activity shape macroecological patterns in ectotherm abundance. Assessing the drivers of continental-scale patterns in insect abundance and their variation across biomes is particularly important to predict insect community response to warming conditions. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Reconstructing monthly 0.25° terrestrial evapotranspiration data in a remote arid region using Bayesian-driven ensemble learning method

This study presents a Bayesian-driven ensemble learning framework to minimize errors in evapotranspiration (ET) data assimilation, thereby generating a continuous-scale ET estimation with improved accuracy for the data-scarce arid Central Asia (CA). Five state-of-the-art gridded ET products were extensively tested and utilized to reconstruct new long-term ET data at grid scale, including two Global Land Data Assimilation System (GLDAS)-Land Surface Models (LSM) (Catchment and NOAH), two reanalysis products (European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) and Modern-Era Retrospective Analysis for Research and Applications – ver. 2 (MERRA2)), along with the Global Land Evaporation Amsterdam (GLEAM) satellite ET product ver. 3.6b. Taylor Skill Score was employed to evaluate the input gridded ET datasets, using in situ measurements across four arid biomes — cropland, shrubland, farmland, and grassland —as benchmarks. Bayes-Markov Chain Monte Carlo (Bayes-MCMC)-derived logarithmically transformed predictors from the posterior ensemble anomalies were standardized to resolve the mismatches in the cumulative distribution functions of ET data relating to the in situ observations. We found that the constrained residual errors were more profound between 45th and 95th percentiles for the rescaled total ET anomalies across all the input ET datasets at 95 % confidence interval. Moreover, the weighted ensemble estimates derived from the Bayes-MCMC were instrumental in correcting ET anomalies, leading to the robust reconstruction of a more reliable ensemble mean ET data for Central Asia (CAETens) at monthly temporal and 0.25° spatial resolutions, spanning from 2003 to 2020. Overall, CAETens exhibited superior performance, achieving the highest averaged Kling-Gupta Efficiency of 0.75 and registering the lowest Root Mean Square Error of 6.85 mm/m compared to the standalone gridded ET products. Comparisons of spatial distributions of fine-scale features, and evaluations using standard metrics revealed that all ET products varied significantly (p < 0.05) by biome types. Remarkably, only CAETens exhibited a reasonable low positive bias and pronounced ability to resolve the complex spatiotemporal patterns associated with the input gridded ET products. The study bridges the gap in continuous ET monitoring for sustainable water resources management in CA.

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.

Linking African herbivore community enamel isotopes and environments: challenges, opportunities, and paleoecological implications.

Paleoenvironmental reconstructions of fossil sites based on isotopic analyses of enamel typically rely on data from multiple herbivore taxa, with the assumption that this dietary spectrum represents the community's isotopic range and provides insights into local or regional vegetation patterns. However, it remains unclear how representative the sampled taxa are of the broader herbivore community and how well these data correspond to specific ecosystems. Verifying these underlying assumptions is essential to refining the utility of enamel isotopic values for paleoenvironmental reconstructions. This study explores potential links between modern herbivore community carbon isotopic enamel spectra, biome types, and climate in sub-Saharan Africa. This region is one of the most comprehensively isotopically sampled areas globally and is of particular relevance to hominin evolution. Our extensive data compilation reveals that published enamel isotopic data from sub-Saharan Africa typically sample only a small percentage of the taxa documented at most localities and that some biome types (e.g., subtropical savannas) are dramatically overrepresented relative to others (e.g., forests) in these modern data sets. Multiple statistical analyses, including linear models and cluster analyses, revealed weak relationships of associated mammalian herbivore enamel isotopic values, biome type, and climate parameters. These results confound any simple assumptions about how community isotopic profiles map onto specific environments, highlighting the need for more precise strategic approaches in extending isotopic frameworks into the past for paleoecological reconstructions. Developing more refined modern analogs will ultimately allow us to more accurately characterize the isotopic spectra of paleo-communities and link isotopic dietary signatures to specific ecosystems.

Estimation of All-Sky High-Resolution Gross Primary Production Across Different Biome Types Using Active Microwave Satellite Images and Environmental Data

Estimation of All-Sky High-Resolution Gross Primary Production Across Different Biome Types Using Active Microwave Satellite Images and Environmental Data

Soil organic matter turnover: Global implications from δ13C and δ15N signatures

The turnover and residence time of carbon (C) and nitrogen (N) in soil is a fundamental parameter reflecting the rates of soil organic matter (SOM) transformation and the contribution of soils to greenhouse gases fluxes. Based on the global database of the stable isotope composition of C (δ13C) and N (δ15N) depending on soil depth (171 profiles), we assessed С and N turnover and related them to climate, biome types and soil properties. The 13C and 15N discrimination between the litter horizon and mineral soil was evaluated to explain the key processes of litter transformation. The 13C and 15N discrimination by microbial utilization of litter and SOM, as well as the continuous increase of δ13C and δ15N with depth, enabled to assess C and N turnover within SOM. N turnover was two times faster than that of C, which reflects i) repeated N recycling by microorganisms accelerating N turnover, ii) C loss as CO2 and input of new C atoms to cycling, which reduces the C turnover within soil, and iii) generally slower turnover of N free persistent organic compounds (e.g. lignin, suberin, cellulose) compared to the N containing compounds (e.g. amino acids, ribonucleic acids). An increase in temperature and precipitation accelerated C and N turnover because: i) higher microbial activity and SOM decomposition rate, ii) larger soil moisture and fast diffusion of dissolved organics towards exoenzymes, iii) downward transport of 13C-enriched organic matter (e.g. sugars, amino acids), and iii) leaching of 15N-depleted nitrates from the topsoil into subsoil and losses from the whole soil profile. Temperature accelerates SOM turnover stronger than precipitation. The temperature increase by 10 °C accelerates the C and N turnover for 40 %. SOM turnover is boosted by decreasing C/N ratio because: i) SOM with a high C/N ratio originated from litter is converted to microbially-derived SOM in mineral soil characterized by a low C/N ratio; ii) litter with a low C/N ratio is decomposed faster than litter with a high C/N; iii) microbial carbon-use efficiency increases with N availability. The biome type affects SOM decomposition by i) climate: slower turnover under wet and cold conditions, and ii) by litter quality: faster utilization of leaves than needles. Thus, the fastest C turnover is common under evergreen forests and the lowest under mixed and coniferous ones, whereas temperature and C/N ratio are the main factors controlling SOM turnover. Concluding, the assessment of SOM turnover by δ13C and δ15N approach showed two times faster N turnover compared to C, and specifics of SOM turnover depending on the biomes as well as climate conditions.

Predictive model of the outage of transmission lines exposed to wildfires

Transmission lines are essential for access to clean and affordable energy sources, Sustainable Development Goal 7. Wildfires are an important factor in the degradation of the quality of public transmission service provision. This work sought to build a model to predict the outage of a transmission line when exposed to a wildfire. The characteristics analysed of the spans exposed to fires of twelve transmission lines at a voltage level of 500 kV in Brazil totalled 3,998 km. The logistic regression technique was used for the study. It was possible to reach a model with a hit rate higher than 73% for the occurrence of transmission line outages. The quantity of fire outbreaks, the climatic variables, and the type of biome of the spans were observed to be the best predictive variables available. The temperature rise can potentially increase the number of outages caused by wildfires.

MATHEMATICAL MODELS OF METHANE CONSUMPTION BY SOILS: A REVIEW

MATHEMATICAL MODELS OF METHANE CONSUMPTION BY SOILS: A REVIEW

Plant functional composition as an effective surrogate for biodiversity conservation

In biodiversity conservation frameworks, determining surrogates for biodiversity is crucial for improving the effectiveness of biodiversity conservation and management. As plant functional composition can indicate variations in ecosystem functions and services, it could be used as an effective surrogate in biodiversity conservation planning. However, to the best of our knowledge, this metric has been rarely used in biodiversity conservation planning. To explore whether plant functional composition can be used as an effective surrogate for biodiversity conservation, we used a linear mixed regression model to investigate the relationships between plant functional composition (i.e., community-weighted means (CWMs) from the sPlot database) and the species richness of birds, mammals, and amphibians, and between plant functional composition and terrestrial conservation priority ranks (considering biodiversity conservation alone, or biodiversity, carbon, and water conservation together). Thereafter, we quantified the changing trends in these relationships across biomes using the least square method. We found that CWMs significantly affected species richness and terrestrial conservation priority ranks, based on the marginal R2 and conditional R2 values from the linear mixed regression model. Further, CWMs significantly affected species richness and terrestrial conservation priority ranks across different biomes of forests and shrublands. However, the nature of these effects (i.e., positive or negative) was dependent on biome type. These results suggest that functional composition can be considered as a biodiversity surrogate for conservation planning, and that biome-specific relationships should be considered.

Are multiple ecosystem stability metrics equally sensitive and consistent to environmental gradient? A test for African terrestrial biomes

It is necessary to find effective methods for quantifying ecosystem stability that can forewarn massive collapses of ecosystem structure and inform ecosystem management. Multiple ecosystem stability metrics (ESMs) have been proposed and are increasingly employed to quantify terrestrial ecosystem stability. However, their sensitivity and consistency in depicting stability changes in diverse terrestrial ecosystems have not been thoroughly examined. Here, we evaluated 11 commonly suggested ESMs using two vegetation indices (normalized difference vegetation index, NDVI, and enhanced vegetation index, EVI) and examined their responses to the climatic gradient in diverse African biomes. We found that ESMs exhibited unequal sensitivity as certain metrics showed insignificant trends with climatic drivers whereas others indicated significant changes in stability in the same case. Among the significant results, inconsistent trends indicated by different ESMs were prevalent. Moreover, diverse ESMs exhibited mostly weak correlations despite being based on the same theoretical deduction. The ESMs derived from NDVI and EVI exhibited inconsistencies in some cases, suggesting the influence of the adopted variables on ESM performance. Our study revealed that multiple ESMs were unequally sensitive and inconsistent in indicating ecosystem stability. ESM performance was synthetically influenced by the ESM algorithm (different metrics), the adopted variable for ESM calculation, and the target biome type. Improvements in ecosystem stability evaluation on broad scales, therefore, are needed through further exploration and verification of ESMs.

Biogeographic patterns and environmental drivers of species richness in the globally distributed Millettioid/Phaseoloid clade (Fabaceae, subfamily Papilionoideae)

IntroductionThe Millettioid/Phaseoloid (MP) clade of Fabaceae is globally distributed, economically important, and highly diverse, making it an attractive system for studying biogeographic and macroecological patterns at a global scale. We conducted the first global macroecological study to map and explore the environmental drivers of the MP clade's species richness patterns.MethodsWe compiled 116,212 species occurrences (161 genera) for the MP clade and 20 environmental variables (19 bioclimatic variables and elevation). Geospatial analyses were performed to estimate species richness patterns and biogeographic heterogeneity. The effects of environmental variables on the species richness of the MP clade were measured through multiple regression models.ResultsOur study identified the megathermal regions as hotspots of species richness for the MP clade. While species distributions and richness largely fit the latitudinal diversity gradient pattern, there was a significant negative relationship between the species richness of the MP clade along the latitude and longitude. The Afrotropic biogeographic realm had the highest alpha diversity (~36%); in terms of biome types, tropical and subtropical moist broadleaf forests had the highest alpha diversity (25%), while the beta diversity revealed a high dispersal rate and habitat tracking. Furthermore, the species richness was positively influenced by multiple climatic factors, with the mean diurnal range of temperatures and precipitation in the warmest quarter having strongest influence.DiscussionOverall, the staggering species richness patterns could be explained by multiple diversity gradient hypotheses. Particularly, colder climates play a crucial role in shaping the species richness pattern by limiting the ecological opportunities for MP clade species in the higher latitudes of the Northern Hemisphere. This suggests that the species richness patterns of the MP clade can be described as "when dispersal meets adaptation." Our study provides a new basis for identifying priority regions for conservation of legumes.

Evolutionary history of the Arctic flora

The Arctic tundra is a relatively young and new type of biome and is especially sensitive to the impacts of global warming. However, little is known about how the Arctic flora was shaped over time. Here we investigate the origin and evolutionary dynamics of the Arctic flora by sampling 32 angiosperm clades that together encompass 3626 species. We show that dispersal into the Arctic and in situ diversification within the Arctic have similar trends through time, initiating at approximately 10–9 Ma, increasing sharply around 2.6 Ma, and peaking around 1.0–0.7 Ma. Additionally, we discover the existence of a long-term dispersal corridor between the Arctic and western North America. Our results suggest that the initiation and diversification of the Arctic flora might have been jointly driven by progressive landscape and climate changes and sea-level fluctuations since the early Late Miocene. These findings have important conservation implications given rapidly changing climate conditions in the Arctic.

Mapping the Late Miocene Pyrenean Forests of the La Cerdanya Basin, Spain

The Late Miocene palaeofloras of the La Cerdanya Basin represent a unique look into the Pyrenean Miocene forested areas of the Iberian Peninsula at a time when the European warm and humid climate was experiencing progressive cooling and aridification. Macrofossils (leaves, seeds, fruits and cones) and miospores from several outcrops revealed the composition and abundances of the different plant species present in the area during the Tortonian and early Messinian geological stages (ca. 11.1–5.7 Ma). These fossils were found in the sediment deposits of an ancient lake system situated in the southwestern part of the basin. Previous studies indicated the presence of highly diversified mixed mesophytic forests with broadleaved evergreen and deciduous trees and conifers. However, the spatial structure and distribution of these forest types remains unknown. In the present work, the biomization method was used to infer the different late Miocene vegetation types from the basin. The extent of these vegetation types was calculated using a methodology for mapping vegetation units from fossil and biome data. While previous attempts at mapping Miocene vegetation units had a broad geographical scale, the present work aimed to map the extent of the vegetation units at a small scale, recreating local and specific vegetation changes in an abrupt basin. Results showed similarly high scores between for four biome types, which represent the different types of vegetation that coexisted in the basin during the Tortonian and the early Messinian: warm-temperate evergreen broadleaf and mixed woodlands (WTEM biome), temperate deciduous forests (TEDE) and cool conifer forests (COMX and COEG). Their extent was depicted in two vegetation maps, which account for differences in palaeoaltitude and palaeoclimate. These forests occupied different vegetation belts, which shifted upwards and downwards with climatic variations and the progressive uplift of the Pyrenees during the late Miocene. Azonal riparian forests and wetland vegetation occupied the more humid areas in the centre of the basin. Nonetheless, dry conditions during the early Messinian and decrease in the lake area degraded the wetland environments, which were partially replaced by broadleaved evergreen mixed woodlands.

Effects of Extreme Temperature and Precipitation Events on Daily CO2 Fluxes in the Tropics

The effects of anomalous weather conditions (such as extreme temperatures and precipitation) on CO2 flux variability in different tropical ecosystems were assessed using available reanalysis data, as well as information about daily net CO2 fluxes from the global FLUXNET database. A working hypothesis of the study suggests that the response of tropical vegetation can differ depending on local geographical conditions and intensity of temperature and precipitation anomalies. The results highlighted the large diversity of CO2 flux responses to the fluctuations of temperature and precipitation in tropical ecosystems that may differ significantly from some previously documented relationships (e.g., higher CO2 emission under the drier and hotter weather, higher CO2 uptake under colder and wetter weather conditions). They showed that heavy precipitation mainly leads to the strong intensification of mean daily CO2 release into the atmosphere at almost all stations and in all types of study biomes. For the majority of considered tropical ecosystems, the intensification of daily CO2 emission during cold and wet weather was found, whereas the ecosystems were predominantly served as CO2 sinks from the atmosphere under hot/dry conditions. Such disparate responses suggested that positive and negative temperature and precipitation anomalies influence Gross Primary Production (GPP) and Ecosystem Respiration (ER) rates differently that may result in various responses of Net Ecosystem Exchanges (NEE) of CO2 to external impacts. Their responses may also depend on various local biotic and abiotic factors, including plant canopy age and structure, plant biodiversity and plasticity, soil organic carbon and water availability, surface topography, solar radiation fluctuation, etc.

Retrieval and validation of vertical LAI profile derived from airborne and spaceborne LiDAR data at a deciduous needleleaf forest site

ABSTRACT Leaf area index (LAI) is defined as one half of the total green leaf area per unit ground surface area. Its vertical profile is critical for understanding the remote sensing radiative transfer processes. LAI profile has been derived from airborne and spaceborne LiDAR data, such as the Global Ecosystem Dynamics Investigation (GEDI) installed on the International Space Station. However, the capability of various algorithms for the LAI profile estimation with airborne LiDAR is not clearly evaluated, and the estimated LAI profiles, including the GEDI LAI products, are not been fully validated. This study conducted a quantitative retrieval and validation of the LAI profiles using terrestrial and airborne laser scanning (TLS and ALS) and spaceborne GEDI data over a deciduous needleleaf forest site in northern China. The vertical LAI profile was estimated in the field using an upward digital hemispherical photography (DHP) attached to a portable measurement system in 2020 and 2021. A suite of new LiDAR indices combining both LiDAR return number and return intensity was explored for the LAI profile estimation. All LAI profiles obtained from the DHP, TLS, ALS, and GEDI during the leaf-on season and leaf-off season were compared. The DHP shows a good agreement with the TLS LAI profiles (R2 = 0.97). The LAI profile derived from the ALS data using the combined light penetration index (LPIRI) agrees well (R2 ≥0.86) with the DHP, TLS, and GEDI estimates. In general, the LPIRI is advantageous for regional LAI profile mapping from ALS. The GEDI cumulative LAI corresponds well with the DHP during the leaf-on season (R2 = 0.90, RMSE = 0.23), but underestimates during the leaf-off season (R2 = 0.70, RMSE = 0.14, bias=−0.13). The underestimation is attributed to the higher canopy and ground reflectance ratio (ρv/ρg) assigned in the algorithm and the height discrepancy between the GEDI and field measurements. For the GEDI LAI profile product, further validation and improvement are necessary for other biome types and landscape conditions, especially during the leaf-off season.

Global vegetation greenness interannual variability and its evolvement in recent decades

The interannual variability (IAV) of global vegetation greenness needs careful assessment as it relates to the stability of the climate, conservation of biodiversity, sustainable ecosystem services, and global food security. Here, we investigated the spatial feature and temporal evolvement of global vegetation greenness interannual variability from 1982 to 2015 using the Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index third generation (NDVI3g) data. Generally, regions with herbaceous and short woody plants had larger IAV of vegetation greenness than those with tall woody biome types (7.9% versus 2.9%). On average, all the biomes displayed increasing IAV of vegetation greenness from 1982 to 2015, with notable increases over northern high latitudes (0.135%/year), Eastern Europe (0.037%//year), and Central Australia (0.231%/year). Croplands in China and India experienced decreasing IAV of vegetation greenness (–0.037%/year for China and –0.004%/year for India). The changing IAV of vegetation greenness had implications for climatic, environmental, and anthropogenic changes that influence vegetation dynamics. Some note-worthy factors include climate warming, the CO2 fertilization effect, agricultural practice improvement, cropland abandonment, and China’s Grain-for-Green Program.

Quantifying Mercury Distribution and Source Contribution in Surface Soil of Qinghai-Tibetan Plateau Using Mercury Isotopes.

Long-range transport and atmospheric deposition of gaseous mercury (Hg0) result in significant accumulation of Hg in the Qinghai-Tibetan Plateau (QTP). However, there are significant knowledge gaps in understanding the spatial distribution and source contribution of Hg in the surface soil of the QTP and factors influencing Hg accumulation. In this study, we comprehensively investigated Hg concentrations and isotopic signatures in the QTP to address these knowledge gaps. Results show that the average Hg concentration in the surface soil ranks as follows: forest (53.9 ± 36.9 ng g-1) > meadow (30.7 ± 14.3 ng g-1) > steppe (24.5 ± 16.1 ng g-1) > shrub (21.0 ± 11.6 ng g-1). Hg isotopic mass mixing and structural equation models demonstrate that vegetation-mediated atmospheric Hg0 deposition dominates the Hg source in the surface soil, with an average contribution of 62 ± 12% in forests, followed by 51 ± 10% in shrub, 50 ± 13% in steppe, and 45 ± 11% in meadow. Additionally, geogenic sources contribute 28-37% of surface soil Hg accumulation, and atmospheric Hg2+ inputs contribute 10-18% among the four types of biomes. The Hg pool in 0-10 cm surface soil over the QTP is estimated as 8200 ± 3292 Mg. Global warming, permafrost degradation, and anthropogenic influences have likely perturbed Hg accumulation in the soil of QTP.