Regional Vegetation Research Articles

Modern pollen and non-pollen palynomorphs from sub-tropical central India: discerning anthropogenic signal in surface pollen assemblages

Interpretation of past vegetation using pollen analysis depends on our understanding about the relationship between the modern vegetation and surface pollen assemblages. In the present study, we sampled the modern pollen-rain in a mixed environment of cultivated land and dry and wet tropical forests in central India. We established to which extent modern vegetation types are reflected in the pollen-rain and explained biases in the modern pollen spectra. Our study revealed that the modern pollen assemblages do not fully represent the extant regional vegetation, as many of the forest components, especially trees and shrubs, are either under-represented or remained palynologically silent in the pollen records. Low pollen productivity of most of the tropical deciduous taxa, owing to entomophily, as well as low preservation potential of some tree pollen are primarily responsible for this irregularity in their representation in the pollen spectra. Moreover, Shorea robusta and Tectona grandis pollen, despite being high pollen producers, are not encountered in any sample, which could be further attributed to their poor preservation in surface soil samples, as well as to their low (pollen) dispersal efficiency. Cerealia, Amaranthaceae, Caryophyllaceae, Brassicaceae, Cannabis sativa, Artemisia spp. and Alternanthera spp. indicate agricultural practices and other human activities around the respective study areas. Moreover, the consistent presence of Asteroideae pollen indicates pastoral activities, whereas Sporormiella spp., Sordaria spp., Podosora spp., Delitschia spp., and Cercophora spp. indicate local grazing and herbivory.

Impacts of Water Diversion Projects on Vegetation Coverage in Central Yunnan Province, China (2017–2022)

The water diversion project in Central Yunnan Province (WDP-YN) is the largest water diversion project under construction in China. However, the ecological effects of this water diversion project are still unclear. This study utilized Sentinel-2 remote sensing data to estimate fractional vegetation cover (FVC), maps spatiotemporal variations of FVC in construction areas from 2017 to 2022, and evaluates the impact of the WDP-YN on regional vegetation coverage using buffer analysis and vegetation type transition matrix methods. The study led to the following findings: (1) From 2017 to 2022, FVC within 10 km of the tunnel construction route showed a slightly downward trend or remained relatively stable with no significant changes in the spatial pattern of FVC. (2) Before and after the construction of WDP-YN, over 60% of the area within 10 km of the tunnel construction route showed no change in FVC. On Construction Route Section I (CRS-I), vegetation improved and/or degraded within 12.90% (14.10%) of the area and the regions with degraded FVC concentrated in the northern CRS-I. For Construction Route Section II (CRS-II), 11.96% and 27.51% of the regions were dominated by improved and/or degraded FVC. Vegetation changes near Groundwater Monitoring Point a (GMPa) were relatively stable. (3) The WDP-YN degraded vegetation within 2 km of both sides of CRS-I, slowing down the increase in FVC, while the WDP-YN improved vegetation within 2–6 km of both sides of CRS-II, the closer the distance to CRS-II, the faster the increase in FVC and the decrease in FVC slowed down within 0–2 km of both sides of CRS-II. This study sheds light on the impacts of water diversion infrastructure on vegetation coverage and provides practical guidance and reference for eco-environment protection and ecological restoration given water conservancy projects in China and other regions of the world.

Restoration of vegetation in the Yellow River Basin of Inner Mongolia is limited by geographic factors

Studying the relationships between vegetation cover and geography in the Mongolian region of the Yellow River Basin will help to optimize local vegetation recovery strategies and achieve harmonious human relations. Based on MOD13Q1 data, the spatial and temporal variations in fractional vegetation cover (FVC) in the Mongolian Yellow River Basin during 2000–2020 were investigated via trend and correlative analysis. The results are as follows: (1) From 2000 to 2020, the vegetation cover in the Mongolian section of the Yellow River Basin recovered well, the mean increase in the FVC was 0.001/a, the distribution of vegetation showed high coverage in the southeast and low coverage in the northwest, and 31.19% of the total area showed an extremely significant and significant increase in vegetation cover. (2) The explanatory power of each geographic factor significantly differed. Precipitation, soil type, air temperature, land use type and slope were the main driving factors influencing the spatial distribution of the vegetation cover, and for each factor, the explanatory power of its interaction with other factors was greater than that of the single factor. (3) The correlation coefficients between FVC and temperature and precipitation are mainly positive. The mean value of the FVC and its variation trend are characterized by differences in terrain and soil characteristics, population density and land use. Land use conversion can reflect the characteristics of human activities, and positive effects, such as returning farmland to forest and grassland and afforestation of unused land, promote the significant improvement of regional vegetation, while negative effects, such as urban expansion, inhibit the growth of vegetation.

Soil properties override climatic factors to shape soil nematode diversity in the eastern forest transect of China

Soil nematodes are among the most significant soil-dwelling organisms in forest ecosystems. However, the factors that shape the distribution of soil nematodes are still not well explored. Therefore, we collected soil samples from 20 forest sites along the eastern transect of China and sequenced 18S rRNA V9 region to reveal the biodiversity of soil nematodes. Our study found that soil nematode richness is higher in temperate mixed needleleaf and broadleaf forests compared with the other four vegetation regions. Soil physiochemical properties overrode climatic factors to be the primary drivers of soil nematode richness and community composition. Importantly, the soil nematode richness significantly enhanced ecosystem multifunctionality, especially bacterial biomass and enzyme activities, with a determination coefficient (r2) of 0.23, suggesting that soil nematodes played essential roles in the forest ecosystem.

Vegetation response to large-scale mountain excavation and city construction projects on the Loess Plateau of China

Since 2012, the “Mountain Excavation and City Construction” (MECC) project has been implemented extensively on the Loess Plateau of China, transforming gullies into flat land for urban sprawl by leveling loess hilltops to fill in valleys. However, this unprecedented human activity has caused widespread controversy over its unknown potential ecological impacts. Quantitative assessment of the impacts of the MECC project on the vegetation is key to ecological management and restoration. Taking the largest MECC project area on the Loess Plateau, Yan'an New District (YND), as the study area, this study investigated the spatiotemporal pattern of vegetation dynamics before and after the implementation of the MECC project using a multitemporal normalized difference vegetation index (NDVI) time series from 2009 to 2023 and explored the response of vegetation dynamics to the large-scale MECC project. The results showed that the vegetation dynamics in the YND exhibited significant spatial and temporal heterogeneity due to the MECC project, with the vegetation in the project-affected areas showing rapid damage followed by slow recovery. Vegetation damage occurred only in the project-affected area, and 84 % of these areas began recovery within 10 years, indicating the limited impact of the large-scale MECC project on the regional vegetation. The strong correlation between vegetation dynamics and the MECC project suggested that the destruction and recovery of vegetation in the project-affected areas was mainly under anthropogenic control, which highlights the importance of targeted ecological policies. Specifically, the MECC project induced local anthropogenic damage to the plant population structure during the land creation period, but regeneration and rational allocation of the vegetation were achieved through urbanization, gradually forming a new balanced ecological environment. These findings will contribute to a full understanding of the response of vegetation to such large-scale engineering activities and help local governments adopt projects or policies that facilitate vegetation recovery.

Response of Vegetation Coverage to Climate Drivers in the Min-Jiang River Basin along the Eastern Margin of the Tibetan Plat-Eau, 2000–2022

Ecological zonation research is typically conducted in the eastern margin of the Tibetan Plateau. In order to enhance the structure and function of regional ecosystems and monitor their quality, it is crucial to investigate shifts in the coverage of vegetation and the factors that contribute to these shifts. The goal of this study is to assess the spatial and temporal variations in vegetation covering and the partitioning of its drivers in the Minjiang River Basin on the eastern edge of the Tibetan Plateau between 2000 and 2022. The Mann-Kendall test, Hurst index, Theil-Sen median trend analysis, and other techniques were used to look at the features of temporal and geographical changes in regional vegetation coverage as well as potential development trends. The climatic influences leading to the spatial differentiation of vegetation NDVI (Normalized Difference Vegetation Index) were quantified through partial and complex correlation analyses of NDVI with temperature and precipitation. The results of the study showed that (1) the NDVI of the watershed performed well with a stable upward trend, indicating that the vegetation growth was generally good; (2) the spatial analysis showed that the coefficient of variation of the NDVI reached 0.092, which highlighted the stability of the vegetation change in the region; (3) the future development trend of the vegetation coverage in the watershed is low, and there is a certain degree of ecological risk; and (4) the main driver of the vegetation coverage is the non-climate factor, distributed in most parts of the watershed; (5) the climate driver shows localized influence, especially concentrated in the southwest, downstream and part of the upstream areas of the watershed.

Advanced precipitation enhances vegetation primary productivity in Central Asia

Climate change is reshaping the seasonal distribution of precipitation patterns across Central Asia, affecting not only the total accumulation but also the timing of precipitation events. However, how seasonal precipitation timing (i.e., precipitation seasonality) shift and may influence dryland ecosystem responses have rarely been considered. Here we utilized gross primary productivity (GPP) data derived from satellite observations over 2001–2022 and a proxy of precipitation timing (precipitation center time index, PCT) to elucidate changes in precipitation timing and assess its impact on vegetation productivity along bioclimate gradients in Central Asia. Our findings revealed that, from southwest to northeast, the precipitation season gradually extended from spring (PCT ≤ 5.0) to summer (PCT ≥ 6.0). Notably, approximately 74.4 % of the study area exhibited a trend of advanced precipitation, particularly evident in regions characterized by earlier precipitation onset. Changes in precipitation timing were found to induce variations in vegetation productivity, albeit with spatial heterogeneity. About 82.0 % of the vegetated areas showed positive GPP anomalies with advanced precipitation, especially in the eastern drylands, while delayed precipitation depressed productivity, leading to negative GPP anomalies in nearly 65.9 % of the vegetation zones. Vegetation in arid regions demonstrated heightened susceptibility to altered precipitation timing, whereas this sensitivity diminished in humid regions characterized by greater moisture availability. More precipitation distributed in early growing season would be more favorable to increase GPP, especially in xeric sparse vegetation, grassland, rained cropland, and shrubland. Our study highlight that it is necessary to pay more attention to the effects of altered precipitation timing on changes in terrestrial ecosystem productivity related to carbon cycle, especially in dryland.

Plant species diversity and functional diversity relations in the degradation process of desert steppe in an arid area of northwest China

Species and functional diversity play a major role in the stability and sustainability of grassland ecosystems. However, changes in species and functional diversity during grassland degradation in arid areas as well as the underlying mechanisms remain unclear. In this study, we surveyed the vegetation and soil properties of arid regions across a degradation gradient to explore the shifts in species and functional diversity in plant communities, their relationships and key determinants during desert steppe degradation. Our results found significant variability in species diversity and functional diversity across degradation stages. Species diversity (Shannon-Wiener index (H), and Pielou index) and functional diversity (functional evenness (FEve) index, and Rao's quadratic entropy (RaoQ) index) tended to increase initially and then decrease with increasing grassland degradation. The Patrick index, Simpson index, functional richness (FRic) index, functional divergence (FDiv) index, and functional dispersion (FDis) index declined as grassland degradation increased. The relationships between species diversity and functional diversity indices at different stages of degradation in the desert steppe were inconsistent. From no to heavy degradation grasslands, the correlation between species diversity and functional diversity gradually weakened. Specifically, there was a significant correlation between Patrick (R) and FRic indices (R2 > 0.7) on both non-degraded and light degraded grasslands, but there was no significant correlation between R and FRic indices in moderately and heavily degraded grasslands (R2 < 0.7), and R2 gradually decreased. Redundancy analysis and partial least squares path modeling showed that grassland degradation has a significant direct effect on the species diversity and functional diversity. In addition grassland degradation has direct and indirect effects on the species diversity through soil available nitrogen, organic matter and total nitrogen. Functional diversity is directly or indirectly affected by species diversity, soil available nitrogen, organic matter and total nitrogen, soil moisture content, soil bulk density, and pH value. In summary, the relationship between species and functional diversity indices gradually weakened from areas with no degradation to heavy degradation in arid desert grasslands. Our study reveals the patterns and relationships between species diversity and functional diversity throughout the process of grassland degradation, demonstrating a gradual decrease in ecosystem stability and sustainability as degradation advances. Our results have significant implications for the restoration of grassland degradation and the management of ecosystem services in arid steppe regions.

Dynamic Integrated Ecological Assessment along the Corridor of the Sichuan–Tibet Railway

Engineering activities along the Sichuan–Tibet Railway (STR) could cause land degradation and threaten the surrounding ecological security. It is crucial to evaluate the integrated land ecology during and after the construction of this project. This study assesses the land ecology along the STR corridor from 2000 to 2022 using a transfer matrix, the analytic hierarchy process (AHP), and the PSR-TOPSIS model. The main results are as follows: (1) The novel comprehensive ecological assessment process including nine indicators is feasible. (2) The high-quality land ecological, surface vegetation, and environmental regions were concentrated in Ya’an and Nyingchi, whereas the low-quality regions were situated in Qamdo and Garze Tibetan Autonomous Prefecture. (3) There was an overall decline in the integrated land ecological quality along the STR from 2000 to 2022. While it steadily improved in the Ya’an and Nyingchi regions from 2010 to 2022, it continued to decline around the Qamdo region. (4) The most degraded land-use type during the 22 years was grassland, and farmland was the most secure land-use type. Overall, spatial analyses and examinations of residue disposal sites suggested that these locations have negatively impacted integrated land ecology since the beginning of the STR construction project. Our findings have implications for preserving the ecological ecosystem and ensuring the sustainability of the STR construction project.

The Response of Soil Respiration to Temperature and Humidity in the Thermokarst Depression Zone of the Headwater Wetlands of Qinghai Lake.

As the climate warms, the thickening of the active layer of permafrost has led to permafrost melting and surface collapse, forming thermokarst landforms. These changes significantly impact regional vegetation, soil physicochemical properties, and hydrological processes, thereby exacerbating regional carbon cycling. This study analyzed the relationship between soil respiration rate (Rs), soil temperature (T), and volumetric water content (VWC) in the thermokarst depression zone of the headwater wetlands of Qinghai Lake, revealing their influence on these soil parameters. Results showed a significant positive correlation between soil temperature and Rs (p < 0.001), and a significant negative correlation between VWC and Rs (p < 0.001). The inhibitory effect of VWC on Rs in the thermokarst depression zone was stronger than under natural conditions (p < 0.05). Single-factor models indicated that the temperature-driven model had higher explanatory power for Rs variation in both the thermokarst depression zone (R2 = 0.509) and under natural conditions (R2 = 0.414), while the humidity-driven model had lower explanatory power. Dual-factor models further improved explanatory power, slightly more so in the thermokarst depression zone. This indicates that temperature and humidity jointly drive Rs. Additionally, during the daytime, temperature had a more significant impact on Rs under natural conditions, while increased VWC inhibited Rs. At night, the positive correlation between Rs and temperature in the thermokarst depression zone increased significantly. The temperature sensitivity (Q10) values of Rs were 3.32 and 1.80 for the thermokarst depression zone and natural conditions, respectively, indicating higher sensitivity to temperature changes at night in the thermokarst depression zone. This study highlights the complexity of soil respiration responses to temperature and humidity in the thermokarst depression zone of Qinghai Lake's headwater wetlands, contributing to understanding carbon cycling in wetland ecosystems and predicting wetland carbon emissions under climate change.

The Disparity in Normalized Difference Vegetarian Index Response to Climate Warming and Humidification in the Tibetan Plateau before and after 1998

The Tibetan Plateau (TP) serves as a crucial ecological barrier in Asia, with vegetation playing a pivotal role in the terrestrial ecosystem by facilitating energy exchange between the land and atmosphere, regulating climate, and participating in the carbon cycle. In this study, we analyze the characteristics of surface vegetation on the TP in the growing season during 1982–2018 using satellite remote sensing data obtained from the National Oceanic and Atmospheric Administration (NOAA) and China Meteorological Forcing Dataset (CMFD). We investigate how these characteristics respond to climate change under different warming and humidification conditions across the TP. The main conclusions are as follows. (1) The normalized difference vegetation index (NDVI) values on the TP exhibit a gradual decrease from southeast to northwest during the growing season. There is a significant overall increasing trend at a climate tendency rate of 0.01·decade−1 (p &lt; 0.01) from 1982 to 2018, characterized by a notable mutation of around 1998. Over the past 37 years, a polarized trend of vegetation was observed on the TP, with notable improvement in its central and eastern regions. However, there has been noticeable degradation in northwestern TP, specifically within the Kunlun Mountains and Qaidam Basin. (2) The climate of the TP demonstrates distinct regional disparities in terms of warming and humidification characteristics before and after 1998. During the period of 1982–1998 (1998–2018), the temperature increase is primarily concentrated in the northern (southern) TP, while precipitation increase is mainly observed in the southern and northwestern (northeastern and western) regions of the TP. (3) The responses of surface vegetation to climate factors exhibit significant variations across diverse climatic backgrounds. It is noteworthy that moisture conditions have a substantial impact on the response of vegetation to air temperature on the TP. During the period of 1982–1998, under relatively insufficient moisture conditions, a positive correlation was observed between air temperature and surface vegetation in the humid and semi-humid regions of the southeastern TP, while a negative correlation was found in the semi-arid regions of northeastern TP. During 1998–2018, as moisture conditions became relatively sufficient, surface vegetation in the semi-arid regions showed positive correlations with both temperature and precipitation. However, surface vegetation in the humid and semi-humid regions exhibited a significant negative correlation with precipitation. During this period, the synergistic effects between warm and humid climates in the semi-arid regions of northeastern TP and warm and dry climates in humid and semi-humid regions of southeastern TP substantially enhanced surface vegetation on the TP. Furthermore, our results indicate that thermal factors (air temperature) primarily influence variations in surface vegetation within the high-altitude arid region of the TP. During 1998–2018, a significant cooling trend was observed in the northwestern TP, which could potentially account for the degradation of surface vegetation in the Kunlun Mountains. The findings of this study establish a scientific basis for the sustainable development of grassland ecosystems on the TP.

Exploring local and regional vegetation compositional changes during the Neolithic (5th–3rd millennium BC): A case study on the forager impact on vegetation in north-east Europe

This research explores the vegetation compositional changes between the fifth and third millennium BC on the Karelian Isthmus (north-west Russia). Special emphasis is placed on studying the timing and magnitude of the impact of hunter-fisher-gatherers on the vegetation. First, we reconstruct the local vegetation around Lake Bolshoye Zavetnoye by using the Landscape Reconstruction Algorithm modelling. The application of different scenarios to the relevant source area of pollen is used to assess the local vegetation around Lake Bolshoye Zavetnoye (BZL) at specific distances from 500 to 3000 m. The regional vegetation reconstruction is assessed by using the REVEALS model. Second, we present new pollen and charcoal data from adjacent Lake Ikmenlampi (LI). Third, we calculate indices of vegetation change for BZL, LI and the region. We further explore the potential causes for these differences between the spatial scales and compare all these outcomes with local and regional archaeological data. The results show that foragers actively manipulated their environment. A shift towards more heliophilous conditions is shown by ca 4800 BC. Between 4000 and 3000 BC, an increase in archaeological material suggests intensive resource procurement and landscape management activities, particularly near settlements. Around the BZL site a local decrease in birch is observed from 4100 BC, coinciding with an increase in the rate of vegetation changes. Additionally, a decline in tree species (spruce, hazel, Alder) from 3500 to 3300 BC suggests human activities. The high fire frequency recorded between 4090 and 3150 BC further supports the presence of local human disturbances by the deliberate use of fire to create favourable living conditions. The results from the LI site go in the same direction with fluctuating abundances of spruce and the presence of pollen from Cannabis, Hordeum, Urtica and Plantago lanceolata from ca 4000 to 3600 BC, indicating the use of spruce-dominated forests and an early, incipient cultivation.

Spatial patterns and variations in leaf traits of alpine plants on the interior Tibetan Plateau

Spatial patterns and environmental gradients in plant traits can elucidate the relationships between plant characteristics, environmental factors, and ecosystem functions and can be used to develop the next generation of vegetation models for predicting vegetation distribution and functions. Studies of Plant traits across spatial scales have advanced significantly worldwide, including on the Tibetan Plateau (TP), the highest and largest plateau globally. Previous research on plant traits on the TP has been limited to specific areas, leaving the overall trend across the plateau unclear. In this study, we examined seven leaf traits—leaf thickness (LT), leaf dry matter content (LDMC), leaf area (LA), specific leaf area (SLA), and leaf carbon (LCC), nitrogen (LNC), and phosphorus (LPC) contents—in 1314 individuals at 237 sites within the alpine vegetation region above 3000 m on the TP to determine their distribution patterns across three spatial dimensions and their relationships with environmental factors. Our results indicated that, compared with Chinese plants, TP plants exhibited significantly greater LT, LDMC, and LNC but lower LA, LCC, and LPC. Except for SLA and LCC, most leaf traits showed significant spatial variability. Climate and soil explained 29.23 % of the total variations in traits. Radiation had the most pronounced effect on LDMC, LA, LNC, and LPC, whereas soil pH primarily constrained LT and LCC. Precipitation influenced most traits both directly and indirectly, with substantial overall effects. Temperature and soil nutrient had minimal influence on the regulation of leaf traits across most of the TP. Our findings suggest that alpine plants typically employ a conservative strategy to cope with the harsh conditions on the TP, but this strategy varies at broader spatial scales and longer environmental gradients, particularly in extreme environments such as the highest alpine regions.

Validation of beyond visual-line-of-sight drone photogrammetry for terrain and canopy height applications

Aerial drones enable detailed three-dimensional terrain and vegetation canopy reconstructions supporting a diverse set of environmental monitoring applications. Small drone-derived photogrammetric datasets (<5 km2) often extend field-scale observations and enable calibration and validation for satellite-based mapping. Applications usually require data over much larger areas or in remote areas such as the Arctic, yet large-area drone datasets are rare due to aviation regulations usually stipulating that missions adhere to within-visual-line-of-sight (VLOS) conditions. Terrain and vegetation canopy reconstruction based on longer-range drone missions requires evaluation to justify future beyond-visual-line-of-sight (BVLOS) data initiatives. This work analyzed BVLOS drone photogrammetric datasets for terrain and vegetation height applications along a forest-tundra ecotone (FTE) spanning 396 km in northern Canada. Specifically, we: 1) performed validation assessments of derived terrain models and canopy height models, and 2) investigated remote sensing applications supported by BVLOS data in a FTE experiencing the effects of climate change. The BVLOS data covered in excess of 550 km2, increasing conventional drone data coverage by two orders of magnitude. Elevation validation indicated that strong agreement with GNSS benchmarks, Airborne Laser Scanning (ALS) and VLOS drone data (0.15–0.19 m RMSE) is possible, and that vertical RMSEs <2x the image spatial resolution is achievable. To validate vegetation canopy height modelling capabilities, comparisons with NASA's Land, Vegetation, and Ice Sensor (LVIS) full-waveform ALS observations indicated satisfactory agreement for height metrics (R2 = 0.7 to 0.8, RMSEs <1.0 m). Canopies were reconstructed at fine spatial scales, which in turn supported a unique comparison of vegetation height distributions between six land-cover classes and ecoregions along the FTE, and identified discrepancies in how national and international canopy height models represented the FTE. Detected terrain subsidence, including retrogressive thaw slumping and ice-wedge degradation, illustrated how climate-driven permafrost thaw is modifying landscapes and placing infrastructure at increased risk, which requires intensive monitoring. These applications demonstrated how BVLOS-derived data enables broader scale assessments of regional vegetation structure and terrain changes across larger spatial extents than previously possible with VLOS drones. Mapping opportunities will arise in the environmental remote sensing discipline as drone systems are increasingly operated beyond visual range.

Supervised NDVI Composite Thresholding for Arid Region Vegetation Mapping

Supervised NDVI Composite Thresholding for Arid Region Vegetation Mapping

Response of soil inorganic nitrogen dynamics to planting age and vegetation type in artificial sand‐fixing land

AbstractVegetation restoration in dryland regions may be a powerful way to control desertification and promote local habitat recovery. In these artificial revegetation systems, ecosystem processes and functioning are strongly determined by nitrogen (N) availability, while soil inorganic N (SIN) is the major available N form and is absorbed as a main N source for plants. However, SIN dynamics, their influencing factors, and their relative importance to the ecosystem of these N‐limited systems are not well understood. A field investigation was conducted to examine the monthly variations in SIN and its response to planting age and vegetation type in a typical artificial sand‐fixing system in northwestern China. The SIN content in topsoil (0–20 cm) during the growing season ranged from 7.10 to 95.65 mg kg−1, with a mean value of 27.14 mg kg−1. Soil nitrate N had a dominant role in determining SIN monthly dynamics, which showed a fluctuating trend with two peak values in early July and late August. SIN showed a significant increasing trend with the planting age of sand‐fixing vegetation, and it was highest for Nitraria sphaerocarpa (55.66 ± 5.76 mg kg−1), followed by Haloxylon ammodendron (29.81 ± 3.47 mg kg−1) and interspace (11.39 ± 1.13 mg kg−1). SIN displayed a hump‐shaped relationship with air temperature (R2 = 0.96, p &lt; 0.01) and had a maximum at 19.88°C. The change rate of SIN was positively correlated with accumulated precipitation (R2 = 0.99, p &lt; 0.05). SIN was correlated significantly with soil organic carbon (SOC), total nitrogen (TN), and soil clay content. Our results revealed that climatic (air temperature and precipitation), abiotic (soil texture), plant (planting age and vegetation type), and nutrient‐related (SOC and TN) factors regulate SIN dynamics in artificial sand‐fixing vegetation systems. Climate was the predominant factor affecting soil ammonium N, and soil nutrients (SOC and TN) were the predominant factor affecting soil nitrate N. Therefore, these factors should be integrated into optimizing regional vegetation establishment and improving ecosystem management practices in sand‐fixing lands.

Holocene Vegetation Dynamics Revealed by a High-Resolution Pollen Record from Lake Yangzonghai in Central Yunnan, SW China

Long-term regional vegetation dynamics is essential for the understanding of past land cover changes. High-resolution pollen analysis of a 1020 cm core from a large lake, Lake Yangzonghai (YZH), in central Yunnan, SW China, was conducted to reveal regional vegetation dynamics in the lake catchment over the past 13,400 years. Pollen record, principal component analysis (PCA) of pollen percentages of major arboreal taxa, and plant abundances estimated from the “Regional Estimates of VEgetation Abundance from Large Sites” (REVEALS) model show five successional stages of vegetation dynamics since 13,400 cal. a BP: regional vegetation with high coverages in the lateglacial (13,400–11,400 cal. a BP) was dominated by evergreen broadleaved forest (EBF) and deciduous broadleaved forest (DBF), together with some grass meadows and marshes; pine forest and alder forest expanded in the early Holocene (11,400–9000 cal. a BP) when vegetation coverages were still high; regional vegetation with low coverages was dominated by sweetgum forest, together with some pine forest during the mid-Holocene (9000–4200 cal. a BP); more pine forest, grass meadows and marshes occupied the lake catchment during the late Holocene (4200–800 cal. a BP), when vegetation coverages were higher than the average of the past 13,400 years; regional vegetation with low coverage was dominated by grass meadows and marshes, great deforestation happened in the last 800 years. Regional vegetation dynamics over the past 13,400 years in the Lake YZH catchment was the result of regional vegetation response to climate changes during the lateglacial and early–mid Holocene, and to human activities mainly during the late Holocene.

Coupling the PROSAIL Model and Machine Learning Approach for Canopy Parameter Estimation of Moso Bamboo Forests from UAV Hyperspectral Data

Parameters such as the leaf area index (LAI), canopy chlorophyll content (CCH), and canopy carotenoid content (CCA) are important indicators for evaluating the ecological functions of forests. Currently, rapidly developing unmanned aerial vehicles (UAV) equipped with hyperspectral technology provide advanced technical means for the real-time dynamic acquisition of regional vegetation canopy parameters. In this study, a hyperspectral sensor mounted on a UAV was used to acquire the data in the study area, and the canopy parameter estimation model of moso bamboo forests (MBF) was developed by combining the PROSAIL radiative transfer model and the machine learning regression algorithm (MLRA), inverted the canopy parameters such as LAI, CCH, and CCA. The method first utilized the extended Fourier amplitude sensitivity test (EFAST) method to optimize the global sensitivity analysis and parameters of the PROSAIL model, and the successive projections algorithm (SPA) was used to screen the characteristic wavebands for the inversion of MBF canopy parameter inversion. Then, the optimized PROSAIL model was used to construct the ‘LAI-CCH-CCA-canopy reflectance’ simulation dataset for the MBF; multilayer perceptron regressor (MLPR), extra tree regressor (ETR), and extreme gradient boosting regressor (XGBR) employed used to construct PROSAIL_MLPR, PROSAIL_ETR, and PROSAIL_XGBR, respectively, as the three hybrid models. Finally, the best hybrid model was selected and used to invert the spatial distribution of the MBF canopy parameters. The following results were obtained: Waveband sensitivity analysis reveals 400–490 and 710–1000 nm as critical for LAI, 540–650 nm for chlorophyll, and 490–540 nm for carotenoids. SPA narrows down the feature bands to 43 for LAI, 19 for CCH, and 9 for CCA. The three constructed hybrid models were able to achieve high-precision inversion of the three parameters of the MBF, the model fitting accuracy of PROSAIL_MLRA reached more than 95%, with lower RMSE values, and the PROSAIL_XGBR model yielded the best fitting results. Our study provides a novel method for the inversion of forest canopy parameters based on UAV hyperspectral data.

Global Overview of the Application of the Braun-Blanquet Approach in Research

Environmental classifications are of paramount importance for assessing the impacts of land-use changes, for prioritizing conservation efforts, and for developing effective management strategies to mitigate the negative impacts of human activities. The aim of our research was to provide as complete an analysis as possible of the studies that have been carried out using the Braun-Blanquet approach. The global review of studies based on the Braun-Blanquet approach includes 1168 papers and was conducted using the PRISMA 2009 methodological recommendations, strict criteria for the selection/quality of papers, and modern methods of data analysis and visualization using VOSviewer software developed by Nees Jan van Eck and Ludo Waltman (Centre for Science and Technology Studies (CWTS) of Leiden University in the Netherlands) (version 1.6.18), which ensures a representative sample, minimization of subjective judgements, and reliability of conclusions. It was noted that the number of publications on Braun-Blanquet is growing exponentially. This is an indication of the scientific interest in this methodology and its continuous further development. Based on a detailed analysis of the keywords, the main research directions and challenges are identified. These include improving the conceptual and methodological foundations of the Braun-Blanquet approach; improvement in regional vegetation classifications, synthesizing them and producing a comprehensive classification for large areas as a basis for biodiversity conservation and sustainable land use; expansion of the geography; compilation and updating of databases of phytosociological data; management of dynamics and vegetation; discussion of the important problem of continuity and discreteness of vegetation in the context of ecological classifications; and vegetation mapping. The top 20 journals publishing the most cited articles were identified, as well as the top 20 most cited journals whose high citation rate is due to the large number of high-quality articles. The analysis of the bibliographic network of papers in dynamics has shown that the structure of relationships is not constant and has changed significantly. The analysis of the authors’ publication activity showed that the vast majority of researchers have a low publication activity and have published only one to three papers. A peculiarity also emerges: if all the most cited authors are concentrated in Eurasia, then most of the most actively published authors are outside Eurasia. The importance of the Braun-Blanquet approach for the study and classification of forest vegetation should be emphasized. In this case, the Braun-Blanquet approach is integrated into forest typologies, increasing their ecological validity and environmental relevance.

Vegetation response in NW Mediterranean borderlands to the millennial-scale climate variability of the last glacial period

Deep-sea pollen records from the Western European margin show that during the Last Glacial period (115-27 ka), regional vegetation oscillated between steppe and open forest in response to the millennial scale climate variability, Dansgaard-Oeschger (D-O) cycles and Heinrich events (HE), and that the magnitude of the forest expansions during D-O warming events was modulated by orbital parameters. However, little is known about the vegetation response in the northwestern Mediterranean region. Here, we present a new well-chronologically constrained high-resolution marine pollen record from the Gulf of Lion documenting the NW Mediterranean vegetation response during Marine Isotope Stages (MIS) 4 and 3. The pollen record highlights the strongest forest expansions during D-O 17-16 and D-O 8 in NW Mediterranean borderlands, likely driven by minima in precession. In this region, Heinrich Stadials (HS) 5 and 4 are marked by steppe landscapes while temperate forest surprisingly characterized HS 6. We hypothesize that the combination of minima in precession and local atmospheric and marine processes allows the development of the temperate forest in NW Mediterranean while the expansion of open environments occurred in other areas of Western Europe. In addition, our results support the hypothesis of Picea survival in NW Mediterranean during MIS 4 to 3.