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Beta-diversity reflects the spatial changes in community species composition which helps to understand how communities are assembled and biodiversity is formed and maintained. Larch (Larix) forests, which are coniferous forests widely distributed in the mountainous and plateau areas in North and Southwest China, are critical for maintaining the environmental conditions and species diversity. Few studies of larch forests have examined the beta-diversity and its constituent components (species turnover and nestedness-resultant components). Here, we used 483 larch forest plots to determine the total beta-diversity and its components in different life forms (i.e., tree, shrub, and herb) of larch forests in China and to evaluate the main drivers that underlie this beta-diversity. We found that total beta-diversity of larch forests was mainly dependent on the species turnover component. In all life forms, total beta-diversity and the species turnover component increased with increasing geographic, elevational, current climatic, and paleoclimatic distances. In contrast, the nestedness-resultant component decreased across these same distances. Geographic and environmental factors explained 20%–25% of total beta-diversity, 18%–27% of species turnover component, and 4%–16% of nestedness-resultant component. Larch forest types significantly affected total beta-diversity and species turnover component. Taken together, our results indicate that life forms affect beta-diversity patterns of larch forests in China, and that beta-diversity is driven by both niche differentiation and dispersal limitation. Our findings help to greatly understand the mechanisms of community assemblies of larch forests in China.

ABSTRACTSatellite datasets have revealed significant greening and soil drying in arid Central Asia. However, the influence mechanism of vegetation and climate on soil moisture dynamics is still unclear. In this study, we investigated the spatiotemporal consistency of vegetation and soil moisture changes, examined the controlling factors of soil moisture under different vegetation indices (normalized differential vegetation index, NDVI; leaf area index, LAI), and explored the time lag and accumulation effects of vegetation greening on the soil moisture in arid Central Asia in the period of 1985 to 2020. The results showed that the co-occurrence of vegetation greening and soil drying in 30.4% (NDVI) and 19.4% (LAI) of the study area spatially. Temporally, the soil moisture increased from 1985 to 1989, but decreased from 1989 or 1990 to 2020. In contrast, vegetation activity increased continuously during 1985–2020. Precipitation accounted for the most variance of the soil moisture. The vegetation greenness demonstrated positive correlations with soil moisture, representing 20.7% (for NDVI) and 39.3% (for LAI) of vegetated areas (areas with long-term mean NDVI ≥ 0.1 and LAI > 0), while negative correlations were observed in only 5.4% (for NDVI) and 3.3% (for LAI) of vegetated areas, respectively. Soil moisture exhibited varying time lag and accumulation effects in response to different vegetation indices, precipitation, and temperature. The main temporal effects of NDVI and temperature were simultaneous changes with no time lag or accumulation effects on soil moisture. In contrast, the main temporal effects of LAI and precipitation included 1-month lag in their influence on soil moisture. Considering the inconsistencies in spatiotemporal patterns between vegetation and soil moisture, as well as the dominance and time lag effects of precipitation on soil moisture variations, we concluded that climate, especially precipitation, rather than vegetation greening, regulates soil moisture in Central Asia. These findings provide a scientific basis for vegetation restoration or regional water resource management in drylands.

Knowing how functional diversity varies across environmental gradients is crucial in investigating biodiversity formation and community assembly processes. The majority of studies concerning functional diversity are based on one fixed plot size, resulting in weakened sensitivity of the spatial patterns to sampling resolution. This weakness may obscure the true mechanisms behind community assemblage. In this study, we utilized hyperspectral imagery collected by Orbita hyperspectral satellites (OHS) to explore the spatial distribution patterns of functional traits and diversity in alpine meadows at four sampling radii (25 m, 50 m, 100 m, 200 m). We examined how functional traits and their diversity responded to variations in climatic and soil conditions at different sampling resolutions. Our findings revealed a significant influence of solar radiation and soil depth on the patterns of functional traits in alpine meadows. Scale dependency was evident in the functional richness (FRic), functional evenness (FEve), and functional dispersion (FDis) of different traits, indicated by a notable difference from the null model. In the presence of stronger soil nutrient and water limitation, chlorophyll a content (CAC), specific leaf area (SLA), leaf thickness (LT), and plant height (Height) exhibited increased clustering and convergence at larger sampling resolutions, illustrating environmental filtering in habitat patch assembly in the alpine meadow. For the first time, this study explores scale dependency in functional diversity patterns in alpine meadows using satellite-based hyperspectral imagery. It unveils the environmental filtering effect of soil nutrient limitation on shaping vegetation patch structures at a landscape level from a remote sensing perspective. The study underscores the significance of accounting for sampling resolution in future related research.

Climate variability is an important factor leading to spatial and temporal changes in structure and functions of plant communities. Exploring the temporal stability of communities in response to climate variability is essential for further evaluating the impacts of climate change to ecosystem functions and services. Current research on climate variability mainly focuses on plot-scale experiments (alpha scale), while how it impacts the long-term stability of a metacommunity (gamma scale) still needs further study. We analyzed the effects of climate variability on the temporal stability of plant communities at alpha and gamma scales based on a long-term observation of plant cover from 1938 to 1968 in a mixed-grass prairie in Kansas, western United States. The results demonstrated that precipitation variability strengthened alpha and gamma stability of plant cover, while the temporal mean of temperature has opposite effects on them. Precipitation variability enhanced alpha stability directly and indirectly by increasing species asynchrony, though its positive effects were weak. Alpha stability combined with spatial asynchrony further promoted gamma stability. We therefore concluded that precipitation variability had a weak but significant stabilizing effect on community structure. These findings reveal the role of precipitation variability in temporal stability of community structure at alpha and gamma scales over decades, which could contribute to a more comprehensive understanding of the conservation of biodiversity and ecosystem functioning under the future climate change. Our study emphasized that both temporal mean and standard variation of climate should be considered when exploring the effects of climate change on ecosystem functions.

The structure, thermal stability and elastic modulus of MgO-Al₂O₃-SiO₂ glasses doped with Y₂O₃ were studied by using XRD, FT-IR, density, DSC, and elastic modulus tests. The results showed that the glass samples remained amorphous with the addition of Y₂O₃. Moreover, the FT-IR results indicated that with an increase in the Y₂O₃ content, the overall change in the degree of polymerisation of the glass network structure showed an increasing trend. The Tg and first crystallisation peak Tp1 of the glasses significantly increased, and the thermal stability was enhanced. As the Y₂O₃ content increased, the densities of the glasses increased from 2.59g/cm³ to 2.88g/cm³. At the same time, the elastic modulus of glasses increased from 98.06 GPa to 107.77 GPa.

Long-term and large scale spatiotemporal patterns of planted forests are essential for evaluating local plantation effectiveness and to promote sustainable afforestation. Satellite remote sensing data provide broad spatial coverage and increasingly long-term and large scale records for spatiotemporal analysis of planted forests. In this study, we developed a dynamic and conversion extraction (DCE) framework by combining the similarity of Landsat normalized difference vegetation index (NDVI) time-series with a change detection algorithm. This framework allows the analysis of spatiotemporal dynamics of planted forests. The proposed framework can be used to extract the planting year and conversion patterns of planted forests by performing the Mann-Kendall (MK) statistic test on the inter-annual Landsat NDVI time-series and measuring the similarity of the intra-annual time-series, respectively. Therefore, it can be applied to addressing the key questions on where, when, and how planted forests conversions have occurred. Took the Loess Plateau in China as an example, we applied the DCE framework to illustrate how planted forests have changed over time and space and have been converted from other land cover types from 1986 to 2021. The producer and user accuracies for the mapping of planted forests were 88.22% and 87.11% in 2021, respectively, and the accuracy of identifying planted forests conversions was 80.25%. The results showed that the newly planted forests experienced four phases: a slow rise from 1986 to 2000, a sharp increase during 2001–2004, a fluctuating pattern from 2005 to 2013, and a reduction until 2020, resulting in a total planted forest area of 7.13 Mha in 2021. In addition, 83.51% of the planted forest pixels underwent conversion from grasslands (58.19% or 4.15 Mha) or croplands (25.32% or 1.81 Mha) during 1986–2021. These results indicate the capability of the DCE framework to capture essential information (planting year and conversion patterns) to support the spatiotemporal analysis of planted forests at large scales.

ObjectiveTo systematically compare and rank the accuracy of AI-based intraocular lens (IOL) power calculation formulas and traditional IOL formulas in highly myopic eyes.MethodsWe screened PubMed, Web of Science, Embase, and Cochrane Library databases for studies published from inception to April 2023. The following outcome data were collected: mean absolute error (MAE), percentage of eyes with a refractive prediction error (PE) within ±0.25, ±0.50, and ±1.00 diopters (D), and median absolute error (MedAE). The network meta-analysis was conducted by R 4.3.0 and STATA 17.0.ResultsTwelve studies involving 2,430 adult myopic eyes (with axial lengths >26.0 mm) that underwent uncomplicated cataract surgery with mono-focal IOL implantation were included. The network meta-analysis of 21 formulas showed that the top three AI-based formulas, as per the surface under the cumulative ranking curve (SUCRA) values, were XGBoost, Hill-RBF, and Kane. The three formulas had the lowest MedAE and were more accurate than traditional vergence formulas, such as SRK/T, Holladay 1, Holladay 2, Haigis, and Hoffer Q regarding MAE, percentage of eyes with PE within ±0.25, ±0.50, and ±1.00 D.ConclusionsThe top AI-based formulas for calculating IOL power in highly myopic eyes were XGBoost, Hill-RBF, and Kane. They were significantly more accurate than traditional vergence formulas and ranked better than formulas with Wang–Koch AL modifications or newer generations of formulas such as Barrett and Olsen.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42022335969.

The family Lauraceae is characterized by numerous species and is an important element in tropical and subtropical forests in China. Altogether 99 species of the family have been considered as threatened, caused mainly by over exploitation and habitat loss, and 13 were listed in the National Key Protected Wild Plants (NKPWP, vers. 2021). However, the distribution characteristics and conservation status of these threatened species in China have not been established. Here we assemble a new distribution database of Lauraceae species in China, then analyze the geographic pattern of Lauraceae richness and the underlying environmental determinants, and further investigate the conservation status of these species. In total, our database contains 36,479 distribution records of 510 native species (including infraspecific taxa), including 2233 records of the 99 threatened species and 1066 records of the 13 NKPWP species. The results indicate that overall species richness of Lauraceae decreases with latitude, and is positively correlated with aridity index (AI), precipitation of warmest quarter (PWQ) and precipitation of coldest quarter (PCQ) while richness of threatened species is mainly influenced by isothermality (ISN) and temperature seasonality (TSN), slightly increases along ISN but decreases with TSN. Eighty-eight of the 99 endangered species (88.9% of the total) are protected in nature reserves. Eleven of the 13 NKPWP species (84.6% of the total) are distributed in different nature reserves, but two species (Cinnamomum chago and Sinopora hongkongensis) are not included in any nature reserves. The richness of NKPWP is positively correlated with the AI, but slowly decreasing with the increasing of precipitation seasonality (PSN) and PWQ. We found that 413 species (85.9% of the total) are distributed in nature reserves and the protection effectiveness of the family is high, but nine threatened species and two NKPWP species have not been conserved in any nature reserves. We propose taking in situ conservation actions urgently, especially for those species with extremely small populations including Machilus longipes, Cinnamomum chago and Sinopora hongkongensis. We reveal the distribution characteristics and identify conservation gaps of overall, threatened and NKPWP species of Lauraceae in China, and propose targeted strategies for further conservation, which is important for the conservation of Lauraceae in China.

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Global patterns of regional plant diversity are relatively well known, but whether they hold for local communities is debated. This study created multi-grain global maps of alpha diversity for vascular plants to provide a nuanced understanding of plant diversity hotspots and improve predictions of global change effects on biodiversity.

Shifts in tree species and their mycorrhizal associations driven by global change play key roles in biogeochemical cycles. In this paper, we proposed a framework of the mycorrhizal-associated nutrient economy (MANE), and tested it using nutrient addition experiments conducted in two tropical rainforests. We selected two tropical rainforests dominated by arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) trees, and established eighteen 20 ​m ​× ​20 ​m plots in each rainforest. Six nitrogen (N) and phosphorus (P) addition treatments were randomly distributed in each rainforest with three replicates. We examined the differences in soil carbon (C) and nutrient cycling, plant and litter productivity between the two rainforests and their responses to 10-year inorganic N and P additions. We also quantified the P pools of plants, roots, litter, soil and microbes in the two rainforests. Overall, distinct MANE frameworks were applicable for tropical rainforests, in which soil C, N and P were cycled primarily in an inorganic form in the AM-dominated rainforest, whereas they were cycled in an organic form in the ECM-dominated rainforest. Notably, the effects of mycorrhizal types on soil P cycling were stronger than those on C and N cycling. The intensified N and P deposition benefited the growth of AM-dominated rainforests instead of ECM-dominated rainforests. Our findings underpin the key role of mycorrhizal types in regulating biogeochemical processes, and have important implications for predicting the ecological consequences of global changes.

Investigating how the productivity dynamics of planted forests vary over time is important for understanding the resilience of forests against disturbance and for maximizing ecological restoration and replanting efforts. In this study, the patterns of interannual variability in net primary production (NPP) were analyzed for planted forests as indicated by the inverse of the coefficient of variation (ICV) time series at a ten-year moving window on the Loess Plateau, China, from 2000 to 2021. The spatial–temporal patterns were defined based on the increase or decrease trend obtained using the ordinary least squares method between abrupt change points performed by a Mann–Kendall test in an ICV time series, as follows: only one linear trend, increase (LI), and decrease (LD); at least two trends, increase firstly and decrease lastly (ID) and decrease firstly and increase lastly (DI); and other trends. The results showed that 82.74% of the ICV on the Loess Plateau displayed LD and ID patterns, indicating an increasing variability of forest productivity in this region. Overall, 73.83% of the ICV had a lower degree of rate decrease in the last phase than during the initial increase. Thus, the variability was in an early stage of increasing degree. The ICV time series showed an LI pattern in the eastern Gansu and the southern Shanxi, indicating a decreased variability, due partly to the improved forest restoration. When the plantation age was considered, the newly planted forests (less than 19 a) exhibited a decreasing variability, indicating the proactive role of forest management and restoration in averting environmental disruptions in dry environments.

Abstract Vegetation community complexity is a critical factor influencing terrestrial ecosystem stability. China, the country leading the world in vegetation greening resulting from human activities, has experienced dramatic changes in vegetation community composition during the past 30 years. However, how China's vegetation community complexity varies spatially and temporally remains unclear. Here, we examined the spatial pattern of China's vegetation community complexity and its temporal changes from the 1980s to 2015 using two vegetation maps of China as well as more than half a million field samples. Spatially, China's vegetation community complexity distribution is primarily dominated by elevation, although temperature and precipitation can be locally more influential than elevation when they become the factors limiting plant growth. Temporally, China's vegetation community complexity shows a significant decreasing trend during the past 30 years, despite the observed vegetation greening trend. Prevailing climate warming across China exhibits a significant negative correlation with the decrease in vegetation community complexity, but this correlation varies with biogeographical regions. The intensity of human activities have an overall negative influence on vegetation community complexity, but vegetation conservation and restoration efforts can have a positive effect on maintaining vegetation composition complexity, informing the critical role of vegetation management policies in achieving the sustainable development goal.

Increasing evidence shows that both abiotic and biotic factors affect species richness and stand biomass in forests, yet the relative and interactive impacts of these factors remain debated in different forest ecosystems. We sampled 55 forest plots (600 m2 per plot) on two subtropical mountains with distinct diversity levels in China to explore the elevational patterns of tree species richness and stand biomass and examined how they were affected by climate, stand structure, and dominance of mycorrhizal types. The tree species richness of both mountains decreased with elevation, while the stand biomass exhibited unimodal or no apparent trends. On both mountains, the tree species richness was strongly shaped by climatic factors, especially the mean annual temperature, whereas the stand biomass was mainly affected by the stand structure. Specifically, on the mountain with higher species richness, both the tree height variation and maximum tree size were strongly correlated with the stand biomass. Meanwhile, on the species-poor mountain with higher elevations, only the maximum tree size correlated with the stand biomass. The dominance of ectomycorrhizal trees also had positive effects on the stand biomass of both mountains. These results suggest that climate, stand structure, and mycorrhizal dominance may jointly drive the decoupling between tree species richness and stand biomass, which should be given more attention in further research and forest management to achieve the climate change mitigation goals.

Abstract Atmospheric nitrogen (N) deposition has significantly altered nutrient availability in most terrestrial ecosystems, which may affect plant nutrient resorption and hence change nutrient cycling and community composition. Although studies on the effects of changed soil nutrients on leaf nutrient resorption have been extensively reported in forests and grasslands, much less known about how plants in temperate shrublands respond to nitrogen deposition across the world. A 4‐year N addition experiment in Vitex negundo and Spiraea trilobata shrublands was conducted to investigate the potential impacts of N deposition on nutrient resorption in two life forms. The green and senesced leaf N ([N]g and [N]s) and phosphorus ([P]g and [P]s) concentrations were measured in four shrubs and two graminoids to calculate N (NRE) and P (PRE) resorption efficiency. We found markedly lower NRE and PRE in shrubs than in graminoids, implying that shrubs probably have a higher capability of acquiring nutrients from soil, whereas graminoids rely on acquiring more nutrients via resorption. N addition increased the [N]g, [N]s, and N:P ratios ([N:P]) and decreased the [P]g of shrubs and all species, whereas it only increased [N]s but had negligible effects on the [N]g, [P]g, and [N:P] of graminoids. The [P]s, NRE, and PRE did not change in either life form or all species combined after N fertilization. Our results suggest that shrubs increase N uptake but do not alter internal N cycling (i.e., nutrient resorption), whereas graminoids do not change N acquisition strategies, in response to increased N supply from the soil. Continuous N addition exacerbated the P limitation of the shrub plants. Both shrubs and graminoids were more likely to adopt nearly complete utilization of P from the soil and senesced leaves under P deficiency, leading to a noneffect of N addition on leaf PRE. Our findings also suggest that the [N]g and [P]g responses to N addition are life‐form specific, implying that N addition may affect ecosystem carbon (C) and nutrient cycles by altering the dominance values of the two life forms and community composition.

Abstract Background Larch (Larix Mill.) forests are widely distributed in the upper parts of mountainous areas in China, playing vital roles in constructing mountain landscapes and maintaining mountain environments. Despite their importance, our knowledges on the large-scale patterns of structure characteristics and the relationships between different structure variables are unclear. In this paper, we investigated 155 plots from 11 natural larch forest types across the country to explore the biogeographic patterns of the structure characteristics and the allometric relationships between different structure variables for Chinese larch forests. Results The structure characteristics were significantly different among larch forest types. For different larch forest types, the power function fits the relationships between tree height and diameter at breast height (DBH), average DBH and stem density, and taper and stem density well, but with different exponents among larch forest types. The power exponents of the allometric relationships between tree height and DBH for different larch forest types varied from 0.61 to 0.93 (mean = 0.86) by standard major axis regression (SMA), and from 0.51 to 0.78 (mean = 0.56) by ordinary least square regression (OLS). The 50%, 75% and 95% quantile regression (QR) and OLS indicated that the average DBH and taper of the L. gmelinii forests, L. gmelinii var. principis-rupprechtii forests, and L. sibirica forests were significantly correlated with stem density. Conclusions The relationship between tree height and DBH showed a power function relationship for all larch forest types in China, but with different exponents. Overall, stem density was negatively correlated with average DBH and taper. The Sect. Larix forests exhibited stand density effect. Our findings provide an important basis for recognizing the biogeographic patterns of structure factors and for the management of larch forests in China.

AimWuling Mountains range from the northeast to southwest in Central China, a region with high habitat complexity and diversity that supports substantial plant species diversity. Connecting the northern subtropics to the mid-subtropics, Wuling Mountains also link the floras of Eastern and South-Western China. Despite a long-standing interest in how important role Wuling Mountains play in species exchange, patterns of plant species diversity in Wuling and their underlying drivers are still not well characterized. Here, the spatial distribution of woody plant species in this region is described and the role the Wuling Mountains play in structuring biodiversity in surrounding areas is explored.LocationWuling Mountains and adjacent regions, China.MethodsDetailed distribution data for woody plant species in China were collected and mapped onto a raster grid of the Wuling Mountains and adjacent regions (a total of 820,000 km2) to analyze spatial patterns in species diversity, including α-diversity (species richness) and β-diversity (βsor). Unweighted pair-group method using arithmetic averages (UPGMA) clustering was used to divide the study region based on species composition. Canonical redundancy analysis was used to illustrate spatial patterns and species-environment relationships.ResultsMountainous areas in the study region have high species richness as compared to other areas. Species exchanges occurred at a greater rate latitudinally vs. longitudinally, especially in Wuling Mountains. This suggests that Wuling Mountains may be an important ecological corridor for woody species, linking Northern and Southern Chinese floras. The study region was divided into six bioregions based on species composition: the Wuling Mountains Region, Nanling-Xuefengshan Mountains Region, Qinling-Dabashan Mountains Region, Sichuan Basin Region, Yangtze Plain Region and Yungui Plateau Region.Main ConclusionsThe Wuling Mountains Region acts as an ecological corridor for woody species, linking Northern and Southern China, and fostering biodiversity exchange and conservation in Central China.

Abstract Aim Dryland ecosystems are exceedingly sensitive to climate change. Desertification induced by both climate changes and human activities seriously threatens dryland vegetation. However, the impact of climate change on distribution of dryland plant species has not been well documented. Here, we studied the potential distribution of four representative dryland plant species (Haloxylon ammodendron, Anabasis aphylla, Calligonum mongolicum, and Populus euphratica) under current and future climate scenarios in a temperate desert region, aiming to improve our understanding of the responses of dryland plant species to climate change and provide guidance for dryland conservation and afforestation. Location Junggar Basin, a large desert region in northwestern China. Methods Occurrence data of the studied species were collected from an extensive field investigation of 2,516 sampling sites in the Junggar Basin. Ensemble species distribution models using 10 algorithms were developed and used to predict the potential distribution of each studied species under current and future climate scenarios. Result Haloxylon ammodendron and A. aphylla were likely to lose most of their current suitable habitats under future climate scenarios, while C. mongolicum and P. euphratica were likely to expand their ranges or remain relatively stationary. Variable importance evaluation showed that the most important climate variables influencing species distribution differed across the studied species. These results may be explained by the different ecophysiological characteristics and adaptation strategies to the environment of the four studied species. Main conclusions We explored the responses of the representative dryland plant species to climate change in the Junggar Basin in northwestern China. The different changes in suitability of different species imply that policymakers may need to reconsider the selection and combination of the afforestation species used in this area. This study can provide valuable reference for the management and conservation of dryland ecosystems under future climate change scenarios.

Given the important role of protected areas (PAs) in biological conservation and the huge investment required to establish and manage them, it is essential to accurately assess the effectiveness of PAs. Previous studies typically used the difference between the PA and a non-protected area to measure the effectiveness and presented many space constraints to enhance the comparability between treatment and control groups. In contrast, however, researchers have given less consideration to time constraints, and there is still no consensus on the choice of period for assessing the effectiveness. Here, we explored this issue and assessed the effectiveness of 2,975 PAs worldwide using the difference in differences (DID) model. We found that 56.2% of PAs were effective in maintaining plant productivity, and PAs in forests were more effective than those in non-forests. However, the effectiveness of PAs in improving ecological stability was limited. The stability rose only in the regions where PAs could effectively maintain plant productivity (e.g., needleleaf forest, woodland or Central Europe). Further, an event-study analysis showed that global PAs had been playing a positive and persistent role in maintaining plant productivity. In addition to providing these new assessment results, we compared the assessment results derived from different methods and confirmed that the impact of not using the DID model was greater than that of not using the propensity score matching (PSM) method. We therefore recommend the use of the DID model in future effectiveness assessments.

Elevational gradients strongly affect the spatial distribution and structure of soil bacterial communities. However, our understanding of the effects and determining factors is still limited, especially in the deep soil layer. Here, we investigated the diversity and composition of soil bacterial communities in different soil layers along a 1,500-m elevational gradient in the Taibai Mountain. The variables associated with climate conditions, plant communities, and soil properties were analyzed to assess their contributions to the variations in bacterial communities. Soil bacterial richness and α-diversity showed a hump-shaped trend with elevation in both surface and deep layers. In the surface layer, pH was the main factor driving the elevational pattern in bacterial diversity, while in the deep layer, pH and soil carbon (C) availability were the two main predictors. Bacterial community composition differed significantly along the elevational gradient in all soil layers. In the surface layer, Acidobacteria, Delta-proteobacteria, and Planctomycetes were significantly more abundant in the lower elevation sites than in the higher elevation sites; and Gemmatimonadetes, Chloroflexi, and Beta-proteobacteria were more abundant in the higher elevation sites. In the deep layer, AD3 was most abundant in the highest elevation site. The elevational pattern of community composition co-varied with mean annual temperature, mean annual precipitation, diversity and basal area of trees, pH, soil C availability, and soil C fractions. Statistical results showed that pH was the main driver of the elevational pattern of the bacterial community composition in the surface soil layer, while soil C fractions contributed more to the variance of the bacterial composition in the deep soil layer. These results indicated that changes in soil bacterial communities along the elevational gradient were driven by soil properties in both surface and deep soil layers, which are critical for predicting ecosystem functions under future climate change scenarios.

Plant functional traits at the community level (plant community traits hereafter) are commonly used in trait-based ecology for the study of vegetation–environment relationships. Previous studies have shown that a variety of plant functional traits at the species or community level can be successfully retrieved by airborne or spaceborne imaging spectrometer in homogeneous, species-poor ecosystems. However, findings from these studies may not apply to heterogeneous, species-rich ecosystems. Here, we aim to determine whether unmanned aerial vehicle (UAV)-based hyperspectral imaging could adequately estimate plant community traits in a species-rich alpine meadow ecosystem on the Qinghai–Tibet Plateau. To achieve this, we compared the performance of four non-parametric regression models, i.e., partial least square regression (PLSR), the generic algorithm integrated with the PLSR (GA-PLSR), random forest (RF) and extreme gradient boosting (XGBoost) for the retrieval of 10 plant community traits using visible and near-infrared (450–950 nm) UAV hyperspectral imaging. Our results show that chlorophyll a, chlorophyll b, carotenoid content, starch content, specific leaf area and leaf thickness were estimated with good accuracies, with the highest R2 values between 0.64 (nRMSE = 0.16) and 0.83 (nRMSE = 0.11). Meanwhile, the estimation accuracies for nitrogen content, phosphorus content, plant height and leaf dry matter content were relatively low, with the highest R2 varying from 0.3 (nRMSE = 0.24) to 0.54 (nRMSE = 0.20). Among the four tested algorithms, the GA-PLSR produced the highest accuracy, followed by PLSR and XGBoost, and RF showed the poorest performance. Overall, our study demonstrates that UAV-based visible and near-infrared hyperspectral imaging has the potential to accurately estimate multiple plant community traits for the natural grassland ecosystem at a fine scale.

Plant litter decomposition is a crucial ecosystem process that regulates nutrient cycling, soil fertility, and plant productivity and is strongly influenced by increased nitrogen (N) deposition. However, the effects of exogenous N input on litter decomposition are still poorly understood, especially in temperate shrublands, which hinders predictions of soil C and nutrient dynamics under the context of global change. Temperate shrub ecosystems are usually N-limited and particularly sensitive to changes in exogenous N input. To investigate the responses of Vitex negundo and Spiraea trilobata litter decomposition to N addition, we conducted a field experiment in Vitex- and Spiraea-dominated shrublands located on Mt. Dongling in Beijing, North China. Four N treatment levels were applied: control (N0; no N addition), low N (N1; 20 kg⋅N⋅ha–1⋅year–1), moderate N (N2; 50 kg⋅N⋅ha–1⋅year–1), and high N (N3; 100 kg⋅N⋅ha–1⋅year–1). The litter decomposition in V. negundo was faster than that in S. trilobata, which may be due to the differences in their nutrient content and C/N ratio. N addition increased the amount of remaining N in the two litter types but had no effect on the remaining mass, C, or P. Nitrogen treatment did not affect the litter decomposition rates (k) of either litter type; i.e., N addition had no effect on litter decomposition in temperate shrublands. The neutral effect of N addition on litter decomposition may be primarily explained by the low temperatures and P limitation at the site as well as the opposing effects of the exogenous inorganic N, whereby exogenous N inhibits lignin degradation but promotes the decomposition of readily decomposed litter components. These results suggest that short-term N deposition may have a significant impact on N cycling but not C or P cycling in such shrub ecosystems.

Planted forests provide a variety of meaningful ecological functions and services, which is a major approach for ecological restoration, especially in arid areas. However, mapping planted forests with remote-sensed data remains challenging due to the similarities in canopy spectral and structure characteristics and associated phenology features between planted forests and other vegetation types. In this study, taking advantage of the Google Earth Engine (GEE) platform and taking the Ningxia Hui Autonomous Region in northwestern China as an example, we developed an approach to map planted forests in an arid region by applying long-term features of the NDVI derived from dense Landsat time series. Our land cover map achieved a satisfactory accuracy and relatively low uncertainty, with an overall accuracy of 93.65% and a kappa value of 0.92. Specifically, the producer (PA) and user accuracies (UA) were 92.48% and 91.79% for the planted forest class, and 93.88% and 95.83% for the natural forest class, respectively. The total planted forest area was estimated as 3608.72 km2 in 2020, accounting for 20.60% of the study area. The proposed mapping approach can facilitate assessment of the restoration effects of ecological engineering and research on ecosystem services and stability of planted forests.

Lakes play a key role in the global water cycle, providing essential water resources and ecosystem services for humans and wildlife. Quantifying long-term changes in lake volume at a global scale is therefore important to the sustainability of humanity and natural ecosystems. Yet, such an estimate is still unavailable because, unlike lake area, lake volume is three-dimensional, challenging to be estimated consistently across space and time. Here, taking advantage of recent advances in remote sensing technology, especially NASA’s ICESat-2 satellite laser altimeter launched in 2018, we generated monthly volume series from 2003 to 2020 for 9065 lakes worldwide with an area ≥ 10 km2. We found that the total volume of the 9065 lakes increased by 597 km3 (90% confidence interval 239–2618 km3). Validation against in situ measurements showed a correlation coefficient of 0.98, an RMSE (i.e., root mean square error) of 0.57 km3 and a normalized RMSE of 2.6%. In addition, 6753 (74.5%) of the lakes showed an increasing trend in lake volume and were spatially clustered into nine hot spots, most of which are located in sparsely populated high latitudes and the Tibetan Plateau; 2323 (25.5%) of the lakes showed a decreasing trend in lake volume and were clustered into six hot spots—most located in the world’s arid/semi-arid regions where lakes are scarce, but population density is high. Our results uncovered, from a three-dimensional volumetric perspective, spatially uneven lake changes that aggravate the conflict between human demands and lake resources. The situation is likely to intensify given projected higher temperatures in glacier-covered regions and drier climates in arid/semi-arid areas. The 15 hot spots could serve as a blueprint for prioritizing future lake research and conservation efforts.

Extensive grazing activity is threatening the alpine grassland of the Qinghai-Tibetan Plateau. Evidence has shown that grazing exclusion may change the composition, structure, and functions of grassland ecosystems. However, such effects depend on the intensity and duration of exclusion. We explored the effects of short-term (2 and 4 years) and long-term (9 and 11 years) grazing exclusion on plant height, coverage, and diversity and community heterogeneity in the alpine grassland of the Qinghai-Tibetan Plateau. We found no difference in plant diversity between short-term grazing exclusion and control. However, long-term grazing exclusion reduced species richness and increased the Simpson dominance index. This decrease in plant species richness was mainly attributable to the decrease in common species richness (defined as species with a relative coverage of 1∼5%). In addition, community heterogeneity (coefficient of variation, CV) was significantly higher in long-term grazing exclusion than in controlled plots. Structural equation modeling (SEM) demonstrated that long-term grazing exclusion increased the community heterogeneity mainly by reducing species diversity. These results suggest that the effects of grazing exclusion on the composition, structure, and community spatial heterogeneity of the alpine grassland ecosystem are dependent on exclusion duration. Grazing activity may maintain the high biodiversity and community stability of the alpine grassland in the harsh environment of the Qinghai-Tibetan Plateau.

Biodiversity change can impact ecosystem functioning, though this is primarily studied at lower trophic levels. Here, Schuldt et al. find that biodiversity components other than tree species richness are particularly important, and higher trophic level diversity plays a role in multifunctionality.

Reliable estimates of the total forest carbon (C) pool are lacking due to insufficient information on dead organic matter (DOM). Here, the authors estimate that the current DOM C stock in China is 925 ± 54 Tg and that it grew by 6.7 ± 2.2 Tg C/yr over the past two decades primarily due to increasing forest area

Legumes are characterized as keeping stable nutrient supply under nutrient-limited conditions. However, few studies examined the legumes' stoichiometric advantages over other plants across various taxa in natural ecosystems. We explored differences in nitrogen (N) and phosphorus (P) stoichiometry of different tissue types (leaf, stem, and root) between N2-fixing legume shrubs and non-N2-fixing shrubs from 299 broadleaved deciduous shrubland sites in northern China. After excluding effects of taxonomy and environmental variables, these two functional groups differed considerably in nutrient regulation. N concentrations and N:P ratios were higher in legume shrubs than in non-N2-fixing shrubs. N concentrations were positively correlated between the plants and soil for non-N2-fixing shrubs, but not for legume shrubs, indicating a stronger stoichiometric homeostasis in legume shrubs than in non-N2-fixing shrubs. N concentrations were positively correlated among three tissue types for non-N2-fixing shrubs, but not between leaves and non-leaf tissues for legume shrubs, demonstrating that N concentrations were more dependent among tissues for non-N2-fixing shrubs than for legume shrubs. N and P concentrations were correlated within all tissues for both functional groups, but the regression slopes were flatter for legume shrubs than non-N2-fixing shrubs, implying that legume shrubs were more P limited than non-N2-fixing shrubs. These results address significant differences in stoichiometry between legume shrubs and non-N2-fixing shrubs, and indicate the influence of symbiotic nitrogen fixation (SNF) on plant stoichiometry. Overall, N2-fixing legume shrubs are higher and more stoichiometrically homeostatic in N concentrations. However, due to excess uptake of N, legumes may suffer from potential P limitation. With their N advantage, legume shrubs could be good nurse plants in restoration sites with degraded soil, but their P supply should be taken care of during management according to our results.

Analyzing how climate change affects vegetation distribution is one of the central issues of global change ecology as this has important implications for the carbon budget of terrestrial vegetation. Mapping vegetation distribution under historical climate scenarios is essential for understanding the response of vegetation distribution to future climatic changes. The reconstructions of palaeovegetation based on pollen data provide a useful method to understand the relationship between climate and vegetation distribution. However, this method is limited in time and space. Here, using species distribution model (SDM) approaches, we explored the climatic determinants of contemporary vegetation distribution and reconstructed the distribution of Chinese vegetation during the Last Glacial Maximum (LGM, 18,000 14C yr BP) and Middle-Holocene (MH, 6000 14C yr BP). The dynamics of vegetation distribution since the LGM reconstructed by SDMs were largely consistent with those based on pollen data, suggesting that the SDM approach is a useful tool for studying historical vegetation dynamics and its response to climate change across time and space. Comparison between the modeled contemporary potential natural vegetation distribution and the observed contemporary distribution suggests that temperate deciduous forests, subtropical evergreen broadleaf forests, temperate deciduous shrublands and temperate steppe have low range fillings and are strongly influenced by human activities. In general, the Tibetan Plateau, North and Northeast China, and the areas near the 30°N in Central and Southeast China appeared to have experienced the highest turnover in vegetation due to climate change from the LGM to the present.

Accurate mapping of vegetation is a premise for conserving, managing, and sustainably using vegetation resources, especially in conditions of intensive human activities and accelerating global changes. However, it is still challenging to produce high-resolution multiclass vegetation map in high accuracy, due to the incapacity of traditional mapping techniques in distinguishing mosaic vegetation classes with subtle differences and the paucity of fieldwork data. This study created a workflow by adopting a promising classifier, extreme gradient boosting (XGBoost), to produce accurate vegetation maps of two strikingly different cases (the Dzungarian Basin in China and New Zealand) based on extensive features and abundant vegetation data. For the Dzungarian Basin, a vegetation map with seven vegetation types, 17 subtypes, and 43 associations was produced with an overall accuracy of 0.907, 0.801, and 0.748, respectively. For New Zealand, a map of 10 habitats and a map of 41 vegetation classes were produced with 0.946, and 0.703 overall accuracy, respectively. The workflow incorporating simplified field survey procedures outperformed conventional field survey and remote sensing based methods in terms of accuracy and efficiency. In addition, it opens a possibility of building large-scale, high-resolution, and timely vegetation monitoring platforms for most terrestrial ecosystems worldwide with the aid of Google Earth Engine and citizen science programs.

China has been experiencing significant climate and land use changes over the past decades. The way in which these changes, particularly a warming hiatus and national ecological restoration projects that occurred almost concurrently in the late 1990s, have influenced vegetation net primary productivity (NPP), is not well documented. Here, we estimated annual and seasonal changes in China’s NPP between 1982 and 2015 using the Carnegie-Ames-Stanford Approach model and examined their shifting years (SHYs) caused by the switch in climatic factors and the restoration projects. Our analyses revealed that the growth of annual, spring and summer NPP stalled in 1997 or 1998, while the trend of autumn NPP increased in 1992 at the national scale. We also showed that the changes in the NPP trends were more sensitive to the warming hiatus in spring and autumn, as well as in the temperate monsoonal region and the Tibetan Plateau, while the larger trend of autumn NPP in eastern China after the SHY was strongly coupled with increased monsoonal precipitation. Although the starting years of the restoration projects were partially consistent with the SHYs of the NPP trends, the projects were likely playing minor roles in enhancing NPP increase. Our findings can be applied for ecological risk assessment and future management of ecological restoration projects in the context of global change.

Research about biodiversity-productivity relationships has focused on herbaceous ecosystems, with results from tree field studies only recently beginning to emerge. Also, the latter are concentrated largely in the temperate zone. Tree species diversity generally is much higher in subtropical and tropical than in temperate or boreal forests, with reasons not fully understood. Niche overlap and thus complementarity in the use of resources that support productivity may be lower in forests than in herbaceous ecosystems, suggesting weaker productivity responses to diversity change in forests. We studied stand basal area, vertical structure, leaf area, and their relationship with tree species richness in a subtropical forest in south-east China. Permanent forest plots of 30 x 30 m were selected to span largely independent gradients in tree species richness and secondary successional age. Plots with higher tree species richness had a higher stand basal area. Also, stand basal area increases over a 4-year census interval were larger at high than at low diversity. These effects translated into increased carbon stocks in aboveground phytomass (estimated using allometric equations). A higher variability in tree height in more diverse plots suggested that these effects were facilitated by denser canopy packing due to architectural complementarity between species. In contrast, leaf area was not or even negatively affected by tree diversity, indicating a decoupling of carbon accumulation from leaf area. Alternatively, the same community leaf area might have assimilated more C per time interval in more than in less diverse plots because of differences in leaf turnover and productivity or because of differences in the display of leaves in vertical and horizontal space. Overall, our study suggests that in species-rich forests niche-based processes support a positive diversity-productivity relationship and that this translates into increased carbon storage in long-lived woody structures. Given the high growth rates of these forests during secondary succession, our results further indicate that a forest management promoting tree diversity after disturbance may accelerate CO2 sequestration from the atmosphere and thus be relevant in a climate-change context.

Nutrient resorption from senescing leaves is a key mechanism of nutrient conservation for plants. The nutrient resorption efficiency is highly dependent on leaf nutrient status, species identity and soil nutrient availability. Nitrogen is a limiting nutrient in most ecosystems, it is widely reported that nitrogen resorption efficiency (NRE) was highly dependent on the soil nitrogen availability and vary with N deposition. The effects of nitrogen deposition on NRE and nitrogen concentration in green and senescing leaves have been well established for forests and grasslands; in contrast, little is known on how plants in shrublands respond to nitrogen deposition across the world. In this study, we conducted a two-year nitrogen addition manipulation experiment to explore the responses of nitrogen concentration in green and senescing leaves, and NRE of seven dominant species, namely, Vitex negundo, Wikstroemia chamaedaphne, Carex rigescens and Cleistogenes chinensis from the Vitex negundo community, and Spirea trilobata, Armeniaca sibirica, V. negundo, C. rigescens and Spodiopogon sibiricus from the Spirea trilobata community, to nitrogen deposition in two typical shrub communities of Mt. Dongling in northern China. Results showed that NRE varied remarkably among different life forms, which was lowest in shrubs, highest in grasses, and intermediate in forbs, implying that shrubs may be most capable of obtaining nitrogen from soil, grasses may conserve more nitrogen by absorption from senescing leaves, whereas forbs may adopt both mechanisms to compete for limited nitrogen supply from the habitats. As the N addition rate increases, N concentration in senescing leaves ([N]s) increased consistent from all species from both communities, that in green leaves ([N]g) increased for all species from the Vitex negundo community, while no significant responses were found for all species from the Spirea trilobata community; NRE decreased for all species except A. sibirica from the Vitex community and W. chamaedaphn from the Spirea community. Given the substantial interspecific variations in nutrient concentration, resorption and the potentially changing community composition, and the increased soil nutrient availability due to fertilization may indirectly impact nutrient cycling in this region.

Losses of plant species diversity can affect ecosystem functioning, with decreased primary productivity being the most frequently reported effect in experimental plant assemblages, including tree plantations. Less is known about the role of biodiversity in natural ecosystems, including forests, despite their importance for global biogeochemical cycling and climate. In general, experimental manipulations of tree diversity will take decades to yield final results. To date, biodiversity effects in natural forests therefore have only been reported from sample surveys or meta-analyses with plots not initially selected for diversity. We studied biomass and growth of subtropical forests stands in southeastern China. Taking advantage of variation in species recruitment during secondary succession, we adopted a comparative study design selecting forest plots to span a gradient in species richness. We repeatedly censored the stem diameter of two tree size cohorts, comprising 93 species belonging to 57 genera and 33 families. Tree size and growth were analyzed in dependence of species richness, the functional diversity of growth-related traits, and phylogenetic diversity, using both general linear and structural equation modeling. Successional age covaried with diversity, but differently so in the two size cohorts. Plot-level stem basal area and growth were positively related with species richness, while growth was negatively related to successional age. The productivity increase in species-rich, functionally and phylogenetically diverse plots was driven by both larger mean sizes and larger numbers of trees. The biodiversity effects we report exceed those from experimental studies, sample surveys and meta-analyses, suggesting that subtropical tree diversity is an important driver of forest productivity and re-growth after disturbance that supports the provision of ecological services by these ecosystems.

Dryland ecosystems are highly vulnerable to climatic and land-use changes, while the mechanisms underlying patterns of dryland species richness are still elusive. With distributions of 3637 native vascular plants, 154 mammals, and 425 birds in Xinjiang, China, we tested the water-energy dynamics hypothesis for species richness patterns in Central Asian drylands. Our results supported the water-energy dynamics hypothesis. We found that species richness of all three groups was a hump-shaped function of energy availability, but a linear function of water availability. We further found that water availability had stronger effects on plant richness, but weaker effects on vertebrate richness than energy availability. We conducted piecewise linear regressions to detect the breakpoints in the relationship between species richness and potential evapotranspiration which divided Xinjiang into low and high energy regions. The concordance between mammal and plant richness was stronger in high than in low energy regions, which was opposite to that between birds and plants. Plant richness had stronger effects than climate on mammal richness regardless of energy levels, but on bird richness only in high energy regions. The changes in the concordance between vertebrate and plant richness along the climatic gradient suggest that cautions are needed when using concordance between taxa in conservation planning.

Changes in forest carbon stocks are a determinant of the regional carbon budget. In the past several decades, China has experienced a pronounced increase in forest area and density. However, few comprehensive analyses have been conducted. In this study, we employed the Forest Identity concept to evaluate the changing status of China's forests over the past three decades, using national forest inventory data of five periods (1977-1981, 1984-1988, 1989-1993, 1994-1998, and 1999-2003). The results showed that forest area and growing stock density increased by 0.51% and 0.44% annually over the past three decades, while the conversion ratio of forest biomass to growing stock declined by 0.10% annually. These developments resulted in a net annual increase of 0.85% in forest carbon sequestration, which is equivalent to a net biomass carbon uptake of 43.8 Tg per year (1 Tg = 10(12) g). This increase can be attributed to the national reforestation/afforestation programs, environmentally enhanced forest growth and economic development as indicated by the average gross domestic product.

Given the central importance of protected area systems in local, regional and global conservation strategies, it is vital that there is a good understanding of their effectiveness in maintaining ecological functioning. Here, we provide, to our knowledge, the first such global analysis, focusing on plant production, a "supporting" ecosystem function necessary for multiple other ecosystem services. We use data on the normalized difference vegetation index (NDVI) as a measure of variation in plant production in the core, boundary and surroundings of more than 1000 large protected areas over a 25 year period. Forested protected areas were higher (or similar), and those non-forested were lower (or similar), in NDVI than their surrounding areas, and these differences have been sustained. The differences from surrounding areas have increased for evergreen broadleaf forests and barren grounds, decreased for grasslands, and remained similar for deciduous forests, woodlands, and shrublands, reflecting different pressures on those surroundings. These results are consistent with protected areas being effective both in the representation and maintenance of plant production. However, widespread overall increases in NDVI during the study period suggest that plant production within the core of non-forested protected areas has become higher than it was in the surroundings of those areas in 1982, highlighting that whilst the distinctiveness of protected areas from their surroundings has persisted the nature of that difference has changed.