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Summary: A long‐standing debate looks at whether air or soil dryness is more limiting to vegetation water use and productivity. The answer has large implications for future ecosystem functioning, as atmospheric dryness is predicted to increase globally while changes in soil moisture are predicted to be far more variable. Here, I review the complexities that contribute to this debate, including the strong coupling between atmospheric and soil dryness, and the widespread heterogeneity in vegetation hydraulic traits, acclimations, and adaptations to water stress. I discuss solutions to improve understanding and modeling of vegetation sensitivity to dryness, including how different types of observational data can be used together to gain insight into vegetation response to water stress across spatial and temporal scales. [ABSTRACT FROM AUTHOR]

[Display omitted] Automatic co-registration of multi-epoch Unmanned Aerial Vehicle (UAV) image sets remains challenging due to the radiometric differences in complex dynamic scenes. Specifically, illumination changes and vegetation variations usually lead to insufficient and spatially unevenly distributed common tie points (CTPs), resulting in under-fitting of co-registration near the areas without CTPs. In this paper, we propose a novel Common-Feature-Track-Matching (CFTM) approach for UAV image sets co-registration, to alleviate the shortage of CTPs in complex dynamic scenes. Instead of matching features between multi-epoch images, we first search correspondences between multi-epoch feature tracks (i.e., groups of features corresponding to the same 3D points), which avoids the removal of matches due to unreliable estimation of the relative pose between inter-epoch image pairs. Then, the CTPs are triangulated from the successfully matched track pairs. Since an even distribution of CTPs is crucial for robust co-registration, a block-based strategy is designed, as well as enabling parallel computation. Finally, an iterative optimization algorithm is developed to gradually select the best CTPs to refine the poses of multi-epoch images. We assess the performance of our method on two challenging datasets. The results show that CFTM can automatically acquire adequate and evenly distributed CTPs in complex dynamic scenes, achieving a high co-registration accuracy approximately four times higher than the state-of-the-art in challenging scenario. Our code is available at https://github.com/lixinlong1998/CoSfM. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim Location Taxon Methods Results Main Conclusions Tropical peatlands are globally significant carbon stores, increasingly threatened by human activities and climate change. However, their ecohydrological responses to shifting water availability remain poorly understood. In this study, we investigate the connections between climate change, hydrology and vegetation dynamics in a coastal tropical peatland in Panama, aiming to understand the effects of future drying on peatland dynamics.Bocas del Toro, Panama (9°22′54″N, 82°21′59″W).Angiosperms.High‐resolution multiproxy palaeoecological data, including pollen and plant macrofossils (vegetation), testate amoebae (water‐table depth) and physical peat properties, are used to explore the relationships between climate change, hydrology and vegetation in a coastal tropical peatland over the past 700 years. Downscaled climate simulations are integrated with this process‐based understanding to project the likely future responses of this coastal peatland to climate change.We identify a clear connection between precipitation variability, driven by shifts in the Intertropical Convergence Zone and water‐table dynamics, which subsequently influence changes in the peatland vegetation mosaic. Historical drier periods are marked by the expansion of shrub communities into the open peatland plain.Palaeoecological studies incorporating climate and hydrological proxies are essential for understanding both recent and future ecohydrological dynamics of tropical peatlands. Our findings suggest that in response to future climate change, water tables will lower and shrub communities will expand due to rising temperatures and reduced precipitation. Additionally, future sea‐level rise, combined with declining rainfall, may result in seawater intrusion and significant vegetation shifts in coastal tropical peatlands. [ABSTRACT FROM AUTHOR]

Armed conflicts are acknowledged for their effects on the environment, including ecosystem degradation and biodiversity loss, but also ecological restoration. Both processes impact post-conflict opportunities for peace and development. The armed conflict in Northern Uganda (1986–2008) profoundly affected local communities and their natural environment. While some areas suffered environmental degradation others underwent ecological restoration. Understanding this historical pattern is crucial for post-conflict natural resource management and peace and development prospects. This article aims to analyse vegetation changes in Northern Uganda during and after the conflict, exploring potential drivers of such changes and their implications for sustainable peace and development. Utilising remote sensing analysis and literature review, we observe a post-conflict 'greening' trend alongside a more equal vegetation deterioration and restoration spatial distribution. We propose that if these trends are driven by agriculture expansion, the way this is organised and articulated with natural vegetation will be central for peace and development. [ABSTRACT FROM AUTHOR]

Understanding the influence of climatic factors on vegetation dynamics and cumulative effects is critical for global sustainable development. However, the response of vegetation to climate and the underlying mechanisms in different climatic zones remains unclear. In this study, we analyzed the response of vegetation gross primary productivity (GPP) to climatic factors and the cumulative effects across various vegetation types and climatic zones, utilizing data on precipitation (Pr), temperature (Ta), and the standardized precipitation evapotranspiration index (SPEI). The results showed that: (1) GPP showed significant differences among the seven climatic zones, with the highest value observed in zone VII, reaching 1860.07 gC·m− 2, and the lowest in zone I, at 126.03 gC·m− 2. (2) GPP was significantly and positively correlated with temperature in climatic zones I, IV, V, and VI and with precipitation in climatic zones I, II, and IV. Additionally, a significant positive correlated was found between SPEI and GPP in climatic zones I, II, and IV. (3) Drought exerted a cumulative effect on GPP in 45.10% of the regions within China, with an average cumulative duration of 5 months. These effects persisted for 6–8 months in zones I, II, and VII, and for 2–4 months in zones III, IV and VI. Among different vegetation types, forests experienced longest cumulative effect time of 6 months, followed by grasslands (5 months), croplands (4 months), and shrublands (4 months). The cumulative time scale decreased with increasing annual SPEI. The varying responses and accumulation of GPP to drought among different vegetation types in various climatic zones underscore the complexity of vegetation-climate interactions the response and accumulation of GPP to drought. [ABSTRACT FROM AUTHOR]

Wood density (WD) is an important quality and functional trait of wood. However, despite the relationships between WD and abiotic factors being important to model or predict spatial distributions of functional traits, as well as responses of vegetation to climate changes, in current Earth system models or dynamic global vegetation models (ESMs/DGVMs), WD is often oversimplified, being defined as a globally uniform constant either for all plant functional types (PFTs) or for each individual PFT. Such oversimplifications may lead to simulation biases in the morphology of woody PFTs, as well as ecosystem transition and vegetation–atmosphere interactions. Moreover, existing conclusions about the relationships between WD and abiotic factors drawn from field observations remain mixed, making model parameterization improvements difficult. This study systematically investigated the influences of climate and soil factors on WD across various PFTs. Optimal fitting models for predicting WD within each PFT were then constructed by utilizing our collated global database of 138 604 observations. For WDs of tree PFTs, climate emerges as a more influential factor than soil characteristics, whereas for shrub PFTs the effects of climate and soil are of equivalent significance. Across all six PFTs, correlation coefficients between predictions by fitting models and observed WD range from 0.49 to 0.93. The predicted and observed WD exhibit good agreement across climate space. It is expected that the incorporation of our research findings into DGVMs will improve the simulation of tree height and forest fractional coverage, particularly in the central forest areas and forest transition zones. [ABSTRACT FROM AUTHOR]

Increases in shrub height, biomass and canopy cover are key whole‐plant features of warming‐induced vegetation change in tundra. We investigated leaf functional traits underlying photosynthetic capacity of Arctic shrub species, particularly its main limiting processes such as mesophyll conductance. In this nutrient‐limited ecosystem, we expect leaf nitrogen concentration to be the main limiting factor for photosynthesis. We measured the net photosynthetic rate at saturated light (Asat) in three Salix species throughout a glacial valley in High‐Arctic tundra and used a causal approach to test relationships between leaf stomatal and mesophyll conductances (gsc, gm), carboxylation capacity (Vcmax), nitrogen and phosphorus concentration (Narea, Parea) and leaf mass ratio (LMA). Arctic Salix species showed no difference in Asat compared to a global data set, while being characterized by higher Narea, Parea and LMA. Vcmax, gsc and gm independently increased Asat, with Vcmax as its main limitation. We highlighted a nitrogen‐influenced pathway for increasing photosynthesis in the two prostrate mesic habitat species. In contrast, the erect wetland habitat Salix richardsonii mainly increased Asat with increasing gsc. Overall, our study revealed high photosynthetic capacities of Arctic Salix species but contrasting regulatory pathways that may influence shrub ability to respond to environmental changes in High Arctic tundra. Summary statement: The photosynthetic capacity and limitations in Arctic shrubs revealing contrasting adaptations among Salix species that may influence their ability to provide negative carbon feedback to the atmosphere in high‐Arctic tundra, despite their similar photosynthetic rate compared to a global data set. [ABSTRACT FROM AUTHOR]

For the last seven years, PlanetScope satellites have started near-daily imaging of parts of the Earth's surface, making high-density multitemporal, multispectral, 3-m pixel imagery accessible to researchers. Multitemporal satellite data enables landscape archaeologists to examine changes in environmental conditions at time scales ranging from daily to decadal. This kind of temporal resolution can accentuate landscape features on the ground by de-emphasizing non-permanent signatures caused by seasonal or even daily changes in vegetation. We argue that the availability of high spatial and temporal resolution multispectral imagery from Planet Inc. will enable new approaches to studying archaeological visibility in landscapes. While palimpsests are discrete overlapping layers of material accumulation, multitemporal composites capture cyclical and seasonal time and can be used to interpret past landscape histories at multiple scales. To illustrate this perspective, we present three case studies using PlanetScope imagery in tropical environments on the Indian Ocean islands of Madagascar, Mauritius, and Zanzibar. [ABSTRACT FROM AUTHOR]

Climate change has emerged as a major concern at both regional and global scales in recent decades. Northwestern Algeria is particularly vulnerable as a semi-arid zone, where changes in climate and land cover (LC) will have a significant impact on vegetation in the long term. This study analyses, through a multidimensional approach, the influence of climate change and LC on vegetation dynamics. Hierarchical partitioning (HP) analysis was conducted to determine the most influential climatic variables (precipitation, temperature) on the dynamics of NDVI. The results show that the annual NDVI shows a fluctuating spatial trend between decrease and increase in different regions. Trends in seasonal NDVI are spatially varied and less uniform. Variations in precipitation are stable, while temperatures show clear and consistent significant increases across the region, with a general tendency to increase (p<0.01) in spring and summer. In mountainous areas, NDVI shows an increasing trend both annually and seasonally. The correlation (r²) between NDVI, temperature and precipitation (0.75–1.0) over the different seasons reveals significant seasonal and regional variability. LC transition patterns also influence spatio-temporal trends in vegetation cover. They reveal that the rate of change of NDVI varies between LC types and regions, with resilience in forests and grasslands. These variations have significant implications for vegetation dynamics, as observed by NDVI. [ABSTRACT FROM AUTHOR]

Salt marshes exist at the terrestrial-marine interface, providing important ecosystem services such as nutrient cycling and carbon sequestration. Tidal inputs play a dominant role in salt marsh porewater mixing, and terrestrially derived freshwater inputs are increasingly recognized as important sources of water and solutes to intertidal wetlands. However, there remains a critical gap in understanding the role of freshwater inputs on salt marsh hydrology, and how this may impact marsh subsurface salinity and plant productivity. Here, we address this knowledge gap by examining the hydrologic behavior, porewater salinity, and pickleweed (Sarcocornia pacifica also known as Salicornia pacifica) plant productivity along a salt marsh transect in an estuary along the central coast of California. Through the installation of a suite of hydrometric sensors and routine porewater sampling and vegetation surveys, we sought to understand how seasonal changes in terrestrial freshwater inputs impact salt marsh ecohydrologic processes. We found that salt marsh porewater salinity, shallow subsurface saturation, and pickleweed productivity are closely coupled with elevated upland water level during the winter and spring, and more influenced by tidal inputs during the summer and fall. This seasonal response indicates a switch in salt marsh hydrologic connectivity with the terrestrial upland that impacts ecosystem functioning. Through elucidating the interannual impacts of drought on salt marsh hydrology, we found that the severity of drought and historical precipitation can impact contemporary hydrologic behavior and the duration and timing of the upland-marsh hydrologic connectivity. This implies that the sensitivity of salt marshes to climate change involves a complex interaction between sea level rise and freshwater inputs that vary at seasonal to interannual timescales. [ABSTRACT FROM AUTHOR]

China's Losses Plateau (LP) is one of the ecologically vulnerable and the most severe soil erosion regions. Thus, knowing spatiotemporal changes in evapotranspiration (ET) and its components (soil evaporation, E; transpiration, T; and vegetation interception evaporation, EI) and revealing the underlying mechanisms are vital for ecosystem and water resources sustainability for this region. Here, we investigate the spatiotemporal changes in ET and its components and then quantify the impacts of climate variables (i.e., precipitation, radiation, temperature, and relative humidity) and vegetation dynamics (e.g., land use/cover changes [LUCC] and changes in leaf area index [LAI]) on their annual trends, by using a process‐based terrestrial ecosystem model and a joint‐solution method with multiple sensitivity numerical experiments. Results show that over 67% of the study region experienced significant (p < 0.05) increases in annual ET, T, and EI, with regional average rises of 4.05, 3.67, and 0.74 mm·year−1, respectively. However, there are significant (p < 0.05) decreases in regional mean E of 0.38 mm·year−1, and the negative trend covers 35.8% of the study area. E, T, and EI changes dominate the annual ET trends over 11.8%, 87.3%, and 0.9% of the study area, respectively. Attribution analyses highlight the increased LAI as the critical factor governing these trends across most of the LP (>58%). At the same time, precipitation and LUCC play a more dominant role in the remaining areas. This study emphasizes the spatial heterogeneity in the drivers of changes in ET and its components and highlights the critical role of vegetation dynamics. These findings provide valuable insights for understanding the ET processes and guiding sustainable water resource management in the LP. [ABSTRACT FROM AUTHOR]

The Gobi Desert is a prominent dust source in Asia, where the dust storm is severe and features great interannual and seasonal variability. Previous studies have found land surface variation plausibly plays an important role in the occurrence and intensity of dust storms. However, the quantitative estimation and numerical description in current models are still limited. Here, a comprehensive study utilizing multiple observations and modeling methods to assess the influence of vegetation and snow on dust was conducted. We found that Gobi deserts exhibit substantial monthly and interannual variability in dust storms, which shows a close connection with vegetation and snow. To quantitatively understand the impact of vegetation and snow cover on dust emissions and also to better characterize such effects in numerical models, we introduced a high‐resolution dynamic dust source function that incorporates the effects of vegetation and snow on erodibility. The new parameterization noticeably improved dust‐related simulations, including aerosol optical thickness and PM10 concentrations, and provided insights into the distinct effects of vegetation and snow on dust emissions. This study sheds light on the effects of vegetation and snow on dust storms over the Gobi Desert, highlighting the importance of dynamic representation of time‐varying surface properties in dust simulation. Plain Language Summary: In Asia, the Gobi Desert is an important source of dust storms, and severe ones frequently engulf densely populated eastern China. The dust storms feature great seasonal and spatial variations. By combining multiple observations and numerical simulations, we found that vegetation, snow and dust storms in the Gobi Desert show synchronous monthly and interannual variations. Sparse vegetation and rapid snowmelt could greatly facilitate dust occurrence and intensity. To quantitatively understand the impacts of changing vegetation and snow cover on dust emissions, we develop a new parametrization to characterize dynamic dust sources. This new modeling method is capable of better representing Gobi dust storms and demonstrating how plants and snow affect dust storms. Key Points: Ground‐based observations and satellite products are combined to indicate the correlation between dust storms and vegetation and snow coverA high‐resolution dynamic dust source function, incorporating vegetation and snow factors, is developed for the GOCART‐WRF dust schemeThe dynamic dust source function improves model performance and demonstrates the vegetation and snow effects on dust over the Gobi region [ABSTRACT FROM AUTHOR]

ABSTRACT Actions for ecological restoration under the Great Green Wall (GGW) initiative in the northern Sahel have been plant focused, paying scant attention to plant–animal interactions that are essential to ecosystem functioning. Calls to accelerate implementation of the GGW make it timely to develop a more solid conceptual foundation for restoration actions. As a step towards this goal, we review what is known in this region about an important class of plant–animal interactions, those between plants and flower‐visiting insects. Essential for pollination, floral resources also support insects that play important roles in many other ecosystem processes. Extensive pastoralism is the principal subsistence mode in the region, and while recent analyses downplay the impact of livestock on vegetation dynamics compared to climatic factors, they focus primarily on rangeland productivity, neglecting biodiversity, which is critical for long‐term sustainability. We summarise current knowledge on insect–flower interactions, identify information gaps, and suggest research priorities. Most insect‐pollinated plants in the region have open‐access flowers exploitable by diverse insects, an advantageous strategy in environments with low productivity and seasonal and highly variable rainfall. Other plant species have diverse traits that constrain the range of visitors, and several distinct flower types are represented, some of which have been postulated to match classical “pollination syndromes”. As in most ecosystems, bees are among the most important pollinators. The bee fauna is dominated by ground‐nesting solitary bees, almost all of which are polylectic. Many non‐bee flower visitors also perform various ecosystem services such as decomposition and pest control. Many floral visitors occupy high trophic levels, and are indicators of continued functioning of the food webs on which they depend. The resilience of insect–flower networks in this region largely depends on trees, which flower year‐round and are less affected by drought than forbs. However, the limited number of abundant tree species presents a potential fragility. Flowering failure of a crucial “hub” species during exceptionally dry years could jeopardise populations of some flower‐visiting insects. Furthermore, across Sahelian drylands, browsers are increasingly predominant over grazers. Although better suited to changing climates, browsers exert more pressure on trees, potentially weakening insect–flower interaction networks. Understanding the separate and combined effects of climate change and land‐use change on biotic interactions will be key to building a solid foundation to facilitate effective restoration of Sahelian ecosystems. [ABSTRACT FROM AUTHOR]

Monitoring vegetation response to valley‐scale floodplain restoration to evaluate effectiveness can be costly and time‐consuming. We used publicly available National Agriculture Imagery Program (NAIP) data and commonly used ArcGIS software to assess land cover change over time at five study sites located in semi‐arid environments of eastern Oregon and north‐central California. Accuracy assessments of our unsupervised classifications were used to evaluate effectiveness. Overall accuracy across sites and years ranged from 64.2% to 89.2% with mean and median accuracy of 79.1% and 80.6%, respectively. Further, we compared our classifications with high‐resolution uncrewed aerial systems (UAS)‐based data collected in the same timeframe. Restored areas classified as dense vegetation were within 4% of the UAS study, water was within 6%, and post‐restoration classifications of sparse vegetation and bare ground classes were within 6% and 4% of the UAS study, respectively. This comparison demonstrates that our unsupervised NAIP data classification of land cover change across entire valley‐scale restoration projects can be used to monitor riparian vegetation change over time as accurately as UAS‐based methods, but at lower cost. Additionally, our methods leverage existing fine‐resolution, pre‐restoration vegetation density data that were not collected as part of project planning. [ABSTRACT FROM AUTHOR]

Based on reasonable management of vegetation in arid area, we consider the effect of artificial irrigation and proposed a vegetation management model with seasonal rainfall and groundwater diffusion. In this work, we describe the relationship between vegetation and groundwater by impulsive differential equation. Sufficient conditions are derived to ensure global asymptotic stability of the vegetation-extinction boundary periodic solution. Sufficient conditions are also derived to examine the permanence of the investigated system. Besides, the correctness of our results is further verified through numerical simulations. These results show that artificial irrigation and groundwater diffusion have a positive effect on the survival of vegetation in arid area. [ABSTRACT FROM AUTHOR]

Introduction: Vegetation plays a crucial role in terrestrial ecosystems, acting as a vital link connecting the lithosphere, hydrosphere, and atmosphere in terms of energy flow and material cycling. Changes in surface vegetation significantly regulate the water cycle, energy flow within terrestrial surfaces, and global carbon balance. Methods: This study focuses on nine major river basins in China to quantitatively investigate the impacts of climate factors, vegetation dynamics, and land use changes on carbon use efficiency (CUE) and water use efficiency (WUE). Results: The primary controlling factors of WUE trends are NDVI (average contribution: 33.75% ± 6.90%) and VPD (average contribution: 28.04% ± 3.98%). NDVI predominates in the Haihe, Yellow River, Yangtze River, Pearl River, and Songliao River basins, while shortwave radiation (Srad) dominates in the southeastern rivers and inland river areas, and humidity (Shum) in the southwestern river basins. For CUE trends, the main controlling factors are Srad (average contribution: 36.46% ± 3.40%) and precipitation (Pre) (average contribution: 26.72% ± 5.20%). NDVI negatively influences the Huaihe River and southeastern river basins, while Pre negatively influences the Songliao River and Yellow River basins, and Srad negatively influences the Huaihe and southwestern river basins. Pre predominates in the Huaihe, Songliao, Haihe, southwestern river basins, and inland river areas, while Srad predominates in the Pearl River, Yangtze River, and Yellow River basins. Discussion: Climate factors and vegetation dynamics have significant regional impacts on WUE and CUE across different river basins, especially the roles of NDVI and VPD on WUE, and Srad and precipitation on CUE. These differences underscore the importance of developing region-specific management strategies to optimize ecosystem services in each basin. [ABSTRACT FROM AUTHOR]

Shifting cultivation, an age-old agricultural practice, is a major factor in forest cover change across Southeast Asia, where repeated cycles of vegetation disturbance and regrowth lead to far-reaching environmental and socio-economic impacts. The present study aims to assess the spatio-temporal patterns of vegetation disturbance and regrowth caused by shifting cultivation in Tripura state of India, over the past three decades, utilizing temporal segmentation of time-series Landsat data. The study analyzed vegetation disturbance and regrowth patterns in a shifting cultivation landscape from 1991 to 2020 using normalized burn ratio trends through LandTrendr, validated by the TimeSync tool. Six land use and land cover classes, viz., forests and trees outside forests, rubber plantation, shifting cultivation, water bodies, agriculture, and settlements, were mapped with an accuracy of 83.08% using a random forest classifier. This classification enabled the identification of the effective study area, which included forest areas with shifting cultivation patches. The analysis revealed that 2533.96 km2 of the study area remained undisturbed, 568.43 km2 experienced low-magnitude disturbance, 1501.11 km2 were moderately disturbed, and 184.82 km2 were highly disturbed. The shifting cultivation cycles in the study area show considerable variation. Low-magnitude disturbance indicates a single slash-and-burn event in the past three decades, moderate-magnitude disturbance involves fallow periods of over 10 years, and high-magnitude disturbance occurs with fallow periods of less than 8 years. The study revealed a shift from traditional shifting cultivation to more permanent agricultural practices in parts of Tripura. In response to incentives for commercial crops, cultivators are increasingly adopting long-term cultivation, including the growing of pineapple, areca nut, and rubber, as well as intercropping with papaya, banana, lemon, tapioca, pepper, and ginger. These plots are, however, abandoned if the yields become economically unviable. The expansion of monoculture cultivation significantly reduces the available area for shifting cultivation, thereby compelling jhum cultivators to revisit their jhum patches more frequently. This study is a first-of-its-kind attempt in the Indian context and sheds light on changing patterns in an age-old agricultural practice. [ABSTRACT FROM AUTHOR]

Vegetation serves as a crucial indicator of ecological environment and plays a vital role in preserving ecosystem stability. However, as urbanization escalates rapidly, natural vegetation landscapes are undergoing continuous transformation. Paradoxically, vegetation is pivotal in mitigating the ecological and environmental challenges posed by urban sprawl. The middle and lower Yangtze River Basin (MLYRB) in China, particularly its economically thriving lower reaches, has witnessed a surge in urbanization. Consequently, this study explored the spatiotemporal variations of normalized difference vegetation index (NDVI) in the MLYRB, with an emphasis on elucidating the impact of climate change and urbanization on vegetation dynamics. The results indicate that a significant increasing trend in NDVI across the MLYRB from 2000 to 2020, a pattern that is expected to persist. An improvement in vegetation was observed in 94.12% of the prefecture-level cities in the study area, predominantly in the western and southern regions. Temperature and wind speed stand out as dominant contributors to this improvement. Nevertheless, significant vegetation degradation was detected in some highly urbanized cities in the central and eastern parts of the study area, mainly attributed to the negative effects of escalating urbanization. Interestingly, a positive correlation between NDVI and the urbanization rate was observed, which may be largely related to proactive ecological preservation policies. Additionally, global climatic oscillations were identified as a key force driving periodic NDVI variations. These findings hold significant importance in promoting harmonious urbanization and ecological preservation, thereby providing invaluable insights for future urban ecological planning efforts. [ABSTRACT FROM AUTHOR]

It is anticipated that global warming will modify precipitation and evapotranspiration patterns, consequently affecting water availability. Changes in water availability pose challenges to freshwater supply, food security, and ecosystem sustainability. However, the variations and driving mechanisms of water availability in the arid and semiarid regions of Northern China remain unclear. This study evaluates the accuracy of three evapotranspiration products and analyzes the changes in water availability in the arid and semiarid regions of Northern China over the past 39 years (1982–2020) along with their driving factors. The results indicate that during this period, precipitation increased at a rate of 7.5 mm/decade, while evapotranspiration rose at a higher rate of 13 mm/decade, resulting in a decline in water availability of 5.5 mm/decade. Spatially, approximately 30.17% of the area exhibited a significant downward trend in water availability, while 65.65% remained relatively stable. Evapotranspiration is the dominant factor leading to the decrease in water availability, with a contribution rate of 63.41%. The increase in evapotranspiration was primarily driven by temperature (32.53% contribution) and the saturation vapor pressure deficit (24.72% contribution). The decline in water availability may further exacerbate drought risks in arid and semiarid regions. The research results can provide a scientific basis for developing water resource management strategies and ecological restoration strategies under environmental change. [ABSTRACT FROM AUTHOR]

The ecosystem's gross primary productivity (GPP) and greenness, as indicated by the normalized difference vegetation index (NDVI), are both essential ecological indicators used to evaluate how ecosystems responded to climate variability. However, the relationships between NDVI and GPP under the influence of drying and wetting and its characteristics along aridity (AI) gradients were not yet fully understood. In this study, we investigated the relationships of the NDVI-GPP (i.e., the strength of the coupling and the sensitivity, as quantified by the coefficient of determination (R2) and slope of the linear regression, respectively) along the aridity gradients during the growing season from 1982 to 2018 in China. The results show that the coupling between NDVI and GPP was stronger (i.e., high R2) in semi-arid regions (0.24) compared to humid and hyper-humid regions (R2 values were 0.11). For different plant functional types (PFTs), decoupling occurred in ENF with a determination coefficient value (R2) of 0.04, whereas GRA shows a higher coupling with an R2 of 0.20. The coupling trend experienced a shift in semi-arid regions, characterized by an aridity index (AI) ranging from 0.20 to 0.50. Additionally, the sensitivity of GPP to NDVI also decreased with increasing aridity. The slope values were 0.19, 0.21, 0.24, 0.20, 0.11, and 0.11 in hyper-arid, arid, semi-arid, dry sub-humid, humid, and hyper-humid, respectively. What is more, asynchronous changes in vegetation productivity and greenness can be detected by capturing the inter-annual variability (IAV) of NDVI and GPP. The IAV of GPP steadily decreased with the aridity gradients, while the IAV of NDVI present fluctuated, suggesting that NDVI was more variable than GPP under the influence of drying and wetting conditions. Our study suggests that there may be a stronger trade-off between ecosystem greenness and photosynthesis in more humid areas. [ABSTRACT FROM AUTHOR]

Recent research has demonstrated that global warming significantly enhances peak vegetation growth on the Tibetan Plateau (TP), underscoring the influence of climatic factors on vegetation dynamics. Nevertheless, the effects of different drought types on peak vegetation growth remain underexplored. This study utilized satellite-derived gross primary productivity (GPP) and the normalized difference vegetation index (NDVI) to assess the impacts of soil moisture (SM) and vapor pressure deficit (VPD) on peak vegetation growth (GPPmax and NDVImax) across the TP from 2001 to 2022. Our findings indicate that NDVImax and GPPmax exhibited increasing trends in most regions, displaying similar spatial patterns, with 65.28% of pixels showing an increase in NDVImax and 72.98% in GPPmax. In contrast, the trend for SM primarily showed a decrease (80.86%), while VPD showed an increasing trend (74.75%). Through partial correlation analysis and ridge regression, we found that peak vegetation growth was significantly affected by SM or VPD in nearly 20% of the study areas, although the magnitude of these effects varied considerably. Furthermore, we revealed that hydrothermal conditions modulated the responses of peak vegetation growth to SM and VPD. In regions with annual precipitation less than 650 mm and an annual mean temperature below 10 °C, decreased SM and increased VPD generally inhibited peak vegetation growth. Conversely, in warm and humid areas, lower SM and higher VPD promoted peak vegetation growth. These findings are crucial for deepening our understanding of vegetation phenology and its future responses to climate change. [ABSTRACT FROM AUTHOR]

Summary Direct human activity and global climatic changes are threatening the existence of many vegetated habitats. Seedling establishment, one of the riskiest plant life stages, must be successful for such habitats to persist. The establishment of seedlings is known to be enhanced by nurse effects, but most studies to date have looked at the nursing effects of plants while sidelining inanimate objects. Nevertheless, nurse objects can support seedling establishment via diverse mechanisms such as moderating abiotic stresses like extreme temperatures and drought, reducing negative biological interactions such as herbivory while enhancing positive processes like seed dispersal, and providing protection from physical disturbances such as trampling and fire. The robust nature of nurse objects highlights their potential in habitat restoration. The addition of nurse objects allows a simple, single‐effort rehabilitation strategy that can later draw on natural seed dispersal and establishment. By achieving a better understanding of the processes in which nurse objects are involved we should be able to better predict vegetation dynamics and manipulate them to minimize adverse processes and support regeneration in natural habitats. [ABSTRACT FROM AUTHOR]

We argue that the spatial discretization of the strongly nonlinear Lefever–Lejeune partial differential equation defines a nonlinear lattice that is physically relevant in the context of the nonlinear physics of ecosystems, modelling the dynamics of vegetation densities in dry lands. We study the system in the lattice ℤ2$$ {\mathrm{\mathbb{Z}}}&#x0005E;2 $$, which is especially relevant because of its natural dimension for the emergence of pattern formation. Theoretical results identify parametric regimes for the system that distinguish between extinction and potential convergence to nontrivial states. Importantly, we analytically identify conditions for Turing instability, detecting thresholds on the discretization parameter for the manifestation of this mechanism. Numerical simulations reveal the sharpness of the analytical conditions for instability and illustrate the rich potential for pattern formation even in the strongly discrete regime, emphasizing the importance of the interplay between higher dimensionality and discreteness. [ABSTRACT FROM AUTHOR]

Limestone pavements contain a unique flora, dominated by ferns with a mix of herbaceous species more often found in woodlands, heathlands and grasslands. The crevices between the rocks are known as grikes, they provide a shaded habitat which, depending on pavement structure, can protect plants from grazing. Despite being of conservation importance and supporting a number of rare and scarce plant species there has been very little research into vegetation change in limestone pavements. This study repeated a survey originally conducted between 1972 and 1975. The Ward and Evans survey visited 535 limestone pavement units spread across England, Scotland and Wales and recorded grike vegetation. This study was able to resurvey 516 of those pavements and repeat the survey using the original methods. Expansion of tree and shrub cover has been observed in some pavements but not previously quantified so tree cover was assessed using historic aerial photographs and satellite imagery. On average species richness per pavement increased but there was a very wide range of change in species richness across individual pavement units ranging from a loss of 56 species to an increase of 38. Dissimilarity averaged 0.41. The area of pavement covered by trees or large shrubs increased by 62% between the two surveys but the number of pavements with zero tree cover also increased. Breaking down pavement units into those with low (<5%), medium (5%–30%) and high (>30%) current tree cover shows that species richness increased in open pavements but was reduced in pavements with high tree cover. Pavement units with high tree cover also showed higher dissimilarity and lower levels of indicators of disturbance. In pavements with high tree cover Ellenberg light (L) values were significantly lower than in open pavements. Open pavements showed higher levels of competitive species (based on Grime CSR values) but no change difference in Ellenberg nutrient (N) values. Vegetation in limestone pavements has changed considerably in the period between the two surveys with negative effects of high tree and shrub cover particularly problematic. There is an urgent need for investigation to support management decisions in this habitat. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Analyzing vegetation coverage and land-use and land cover (LULC) characteristics helps to understand the interaction between human activities and the natural environment. The coastal regions of the Guangdong Province are economically active areas with frequent human activities, located in the advantageous natural environment of South China. This study analyzed the spatiotemporal characteristics of the normalized difference vegetation index (NDVI) and LULC from 2000 to 2020, to explore the response of NDVI changes to LULC changes. The results show that (1) the overall NDVI is relatively high, with a proportion of 85.37% to 89.48% of areas with higher coverage and above categories, mainly distributed in the east and west. Vegetation coverage showed an increasing trend. (2) The LULC in this area is mainly composed of forest land (46.5% to 47.5%) and cultivated land (30.7% to 33.4%), with forest land mainly distributed in relatively high-altitude regions and cultivated land mainly distributed in the plains. The changes in LULC from 2015 to 2020 were relatively significant, mainly due to the mutual transfer of cultivated land and forest land. In addition, built-up land continued to expand from 2000 to 2020, mainly in the Pearl River Delta. (3) The NDVI decreases come from the transfer of various types of land to built-up land, mainly in the Pearl River Delta region, while the NDVI increase comes from the stability and mutual transfer of cultivated land. The net contribution rate of forest land change to vegetation cover change is the most significant (−38.903% to 23.144%). This study has reference significance for the spatiotemporal characteristics of vegetation cover changes in coastal areas and their response to land-use changes, as well as coastal management and sustainable development. [ABSTRACT FROM AUTHOR]

We argue that the spatial discretization of the strongly nonlinear Lefever–Lejeune partial differential equation defines a nonlinear lattice that is physically relevant in the context of the nonlinear physics of ecosystems, modelling the dynamics of vegetation densities in dry lands. We study the system in the lattice ℤ2$$ {\mathrm{\mathbb{Z}}}&#x0005E;2 $$, which is especially relevant because of its natural dimension for the emergence of pattern formation. Theoretical results identify parametric regimes for the system that distinguish between extinction and potential convergence to nontrivial states. Importantly, we analytically identify conditions for Turing instability, detecting thresholds on the discretization parameter for the manifestation of this mechanism. Numerical simulations reveal the sharpness of the analytical conditions for instability and illustrate the rich potential for pattern formation even in the strongly discrete regime, emphasizing the importance of the interplay between higher dimensionality and discreteness. [ABSTRACT FROM AUTHOR]

Many hydrological models incorporate vegetation-related parameters to describe hydrological processes more precisely. These parameters should adjust dynamically in response to seasonal changes in vegetation. However, due to limited information or methodological constraints, vegetation-related parameters in hydrological models are often treated as fixed values, which restricts model performance and hinders the accurate representation of hydrological responses to vegetation changes. To address this issue, a vegetation-related dynamic-parameter framework is applied on the Xinanjiang (XAJ) model, which is noted as Eco-XAJ. The dynamic-parameter framework establishes the regression between the Normalized Difference Vegetation Index (NDVI) and the evapotranspiration parameter K. Two routing methods are used in the models, i.e., the unit hydrograph (XAJ-UH and Eco-XAJ-UH) and the Linear Reservoir (XAJ-LR and Eco-XAJ-LR). The original XAJ model and the modified Eco-XAJ model are applied to the Ou River Basin, with detailed comparisons and analyses conducted under various scenarios. The results indicate that the Eco-XAJ model outperforms the original model in long-term discharge simulations, with the NSE increasing from 0.635 of XAJ-UH to 0.647 of Eco-XAJ-UH. The Eco-XAJ model also reduces overestimation and incorrect peak flow simulations during dry seasons, especially in the year 1991. In drought events, the modified model significantly enhances water balance performance. The Eco-XAJ-UH outperforms the XAJ-UH in 9 out of 16 drought events, while the Eco-XAJ-LR outperforms the XAJ-LR in 14 out of 16 drought events. The results demonstrate that the dynamic-parameter model, in regard to vegetation changes, offers more accurate simulations of hydrological processes across different scenarios, and its parameters have reasonable physical interpretations. [ABSTRACT FROM AUTHOR]

The fossil record of the U.S. Pacific Northwest preserves many Middle Miocene floras with potential for revealing long-term climate-vegetation dynamics during the Miocene Climatic Optimum. However, the possibility of strong, eccentricity-paced climate oscillations and concurrent, intense volcanism may obscure the signature of prevailing, long-term Miocene climate change. To test the hypothesis that volcanic disturbance drove Middle Miocene vegetation dynamics, high-resolution, stratigraphic pollen records and other paleobotanical data from nine localities of the Sucker Creek Formation were combined with sedimentological and geochemical evidence of disturbance within an updated chronostratigraphic framework based on new U-Pb zircon ages from tuffs. The new ages establish a refined, minimum temporal extent of the Sucker Creek Formation, ~15.8 to ~14.8 Ma, and greatly revise the local and regional chronostratigraphic correlations of its dispersed outcrop belt. Our paleoecological analysis at one ~15.52 Ma locality reveals two abrupt shifts in pollen spectra coinciding with the deposition of thick ash-flow tuffs, wherein vegetation dominated by Cupressaceae/Taxaceae, probably representing a Glyptostrobus oregonensis swamp, and upland conifers was supplanted by early-successional forests with abundant Alnus and Betula. Another ephemeral shift from Cupressaceae/Taxaceae swamp taxa in favor of upland conifers Pinus and Tsuga correlates with a shift from low-Ti shale to high-Ti claystone, suggesting a link between altered surface hydrology and vegetation. In total, three rapid vegetation shifts coincide with ash-flow tuffs and are attributed to volcanic disturbance. Longer-term variability between localities, spanning ~1 Myr of the Miocene Climatic Optimum, is chiefly attributed to eccentricity-paced climate change. Overall, Succor Creek plant associations changed frequently over ≤105 years timespans, reminiscent of Quaternary vegetation records. Succor Creek stratigraphic palynology suggests that numerous and extensive collection of stratigraphically controlled samples is necessary to understand broader vegetation trends through time. [ABSTRACT FROM AUTHOR]

Cave pearls are spherical concentric speleothems growing radially around nuclei in shallow pools saturated with calcite. They are very rare in the Southern Levant. We present a unique assemblage of 50 cave pearls found in the Iron Age Joweizeh artificial spring tunnel in the Jerusalem Hills of Israel. Some of these deposits represent the first global evidence of formation on archaeological artefacts: pottery sherds and ancient plaster. Multi‐analyses were conducted to date and characterize the different nuclei and pearls. Charcoal samples extracted from the plaster nuclei of two pearls were 14C dated to the Hellenistic period. Two pearls were formed on sherds of Hellenistic lamps. XPS found Co colour remains, suggesting both had been imported. The Hellenistic date is also supported by archaeomagnetic dates of seven other pottery nuclei. Most Hellenistic remains are probably the outcome of a renovation campaign in the tunnel. Four pearls were sampled for stable isotopes (δ13C and δ18O). The range of δ18O values from the Joweizeh pearls is compatible with the Holocene Soreq and Jerusalem caves’ records. The δ13C differences between Joweizeh and Soreq indicate local changes in the overlying vegetation throughout history. The various lines of evidence enabled us to characterize the pearls’ formation process, reconstruct the Joweizeh spring tunnel's hydraulic environment and detect changes that occurred in its water flow regime throughout history. [ABSTRACT FROM AUTHOR]

As the main component of terrestrial ecosystem, vegetation plays a very important role in regional ecosystem environmental change, global carbon cycle and climate regulation. The Lower Mekong region (LMR) is at the core of Southeast Asia, its vegetation changes will affect the regional ecosystem and climate. Five countries of LMR were selected as the study area, based on MODIS (Moderate-Resolution Imaging Spectroradiometer) NDVI(Normal Difference Vegetation Index) data from 2000 to 2022, using the Sen's slope estimator, Mann–Kendall trend test and geographic detector to study the spatial and temporal variation trends and driving forces of vegetation coverage. The results showed that:(1) From 2000 to 2022,the vegetation coverage in the LMR showed an overall fluctuating upward trend, the annual average Fractional Vegetation Cover(FVC) value was 0.70, mainly with high vegetation coverage and relatively high vegetation coverage. Vegetation distribution had obviously spatial heterogeneity, and the vegetation of Myanmar, Laos and Vietnam was significantly larger than Thailand and Cambodia.(2) The variation trend analysis of Sen_MK showed that the proportion of improved and degraded vegetation coverage areas in the LMR were 56.33% and 37.55% respectively. The vegetation improvement area was much larger than the vegetation degradation area during 2000–2022. According to the variation trend analysis of different countries, the vegetation coverage improvement area in Vietnam, Myanmar and Thailand were larger than the degraded , the overall vegetation coverage variation trend were good. However, in Laos and Cambodia, the degraded areas were larger than the improved, the overall variation trends of coverage were not good.(3) The results of geographic detector showed that the Land Use and Land Cover(LULC) had the greatest influence on vegetation coverage in the study area.The influencing factors of vegetation coverage were different in the LMR. For Vietnam, Thailand and Laos,elevation and slope factors were second only to LULC, for Myanmar and Cambodia, the influence of precipitation factor was second only to LULC. The results provide scientific data support for understanding the ecological environment status and future changes in the research area. [ABSTRACT FROM AUTHOR]

Grazing is a major ecological driver that influences vegetation dynamics globally. We investigated the long‐term effects of different grazing regimes on the vegetation structure of the Central Anatolian steppes, a region characterized by its unique convergence of biogeographical influences and historical land use. We employed the spatially explicit FATELAND model to simulate vegetation dynamics over a 50‐year period under three distinct grazing scenarios: no grazing, moderate grazing, and overgrazing. Our simulations incorporated a range of plant functional traits to predict changes across five different vegetation types in Central Anatolia, including woodland steppes and treeless steppes. The simulations revealed that moderate grazing supports the diversity and abundance of various plant functional groups, excluding resprouter trees, which flourish under no grazing conditions. In contrast, overgrazing leads to significant reductions in the abundance of perennial forbs and both spiny and non‐spiny subshrubs, often resulting in a shift toward grassland dominated by resprouter gramineae or an annual herb‐dominated grassland, depending on the initial abundance of gramineae. Our findings highlight the critical role of grazing management in maintaining biodiversity and ecological stability in steppe ecosystems. While moderate grazing can enhance plant functional group diversity, overgrazing significantly threatens the ecological integrity of the Central Anatolian steppes. In conclusion, our modeling approach reveals that the grazing regime is a major driver in shaping the vegetation structure of Central Anatolian steppes. Grazing management strategies that are adjusted to the ecological characteristics and historical context of specific regions are required to prevent degradation and promote sustainable grassland vegetation. [ABSTRACT FROM AUTHOR]

The maximum seasonal vegetation photosynthesis (Phomax) is crucial to regulating the global carbon dynamics. Of particular importance are the seasonal increments in vegetation photosynthesis (ΔPho), which provide key insights into understanding Phomax. However, the interannual variability of ΔPho within the photosynthesis‐up period (PUP) and its influencing factors remain unclear. To address this gap, we identified PUP and quantified the multi‐year characteristics of ΔPho using satellite‐derived solar‐induced chlorophyll fluorescence. We further investigated the response of ΔPho in northern ecosystems to climate change and vegetation greening by integrating climate data and the normalized difference vegetation index. In the northern ecosystems, longer PUP often spatially correlated with a higher ΔPho. An increasing trend was evident regarding the multi‐year variations in ΔPho, suggesting enhanced vegetation photosynthesis within the PUP. This phenomenon is primarily driven by increased solar radiation and intensified vegetation greening. Additionally, based on the results derived from satellite data, we found three pieces of evidence for the decoupling trend between vegetation photosynthesis and greening under the influence of climate change: first, the inconsistent trends between ΔPho and greening; second, the declining moving trend in the correlation coefficient between ΔPho and greening, approximately 9.17 × 10−4; and third, the weakened dominant role of greening on ΔPho. These findings were further supported by results from ecosystem model simulations. In summary, this study provides insights into the interannual variability of ΔPho and its influencing factors and indicates that vegetation dynamics and terrestrial carbon cycle are likely to become more complex under future climate change scenarios. [ABSTRACT FROM AUTHOR]

This study presents an innovative investigation into the spatiotemporal dynamics of vegetation growth and its response to both individual and composite climatic factors. The Normalized Difference Vegetation Index (NDVI), derived from SPOT satellite remote sensing data, was employed as a proxy for vegetation growth. Multiple analytical methods, including the coefficient of variation, Mann–Kendall trend analysis, and Hurst index, were applied to characterize the spatiotemporal patterns of the NDVI in Sichuan Province from 2000 to 2020. The Standardized Precipitation Evapotranspiration Index (SPEI) was calculated using monthly precipitation and temperature data from 45 meteorological stations to examine the influence of composite climatic factors on vegetation growth, while the time lag effects between the NDVI and various climatic variables were also explored. Our findings unveil three key insights: (1) Vegetation coverage in Sichuan Province exhibited an overall increasing trend, with the highest NDVI values in summer and the lowest in winter. Significant NDVI fluctuations were observed in spring in the western Sichuan plateau and in winter in northern, eastern, and southern Sichuan. (2) A significant upward trend in the NDVI was detected across Sichuan Province, except for Chengdu Plain, where a downward trend prevailed outside the summer season. (3) On shorter time scales, the NDVI was positively correlated with precipitation, temperature, and the SPEI, with a one-month lag. The response of the NDVI to sunlight duration showed a two-month lag, with the weakest correlation and a five-month lag in western Sichuan. This research advances our understanding of the complex interactions between vegetation dynamics and climatic factors in Sichuan Province and provides valuable insights for predicting future vegetation growth trends. [ABSTRACT FROM AUTHOR]

The quantitative assessment of the impact of vegetation restoration on evapotranspiration and its components is of great significance in developing sustainable ecological restoration strategies for water resources in a given region. In this study, we used the Priestley-Taylor Jet Pro-pulsion Laboratory (PT-JPL) to simulate the ET components in the Helong section (HLS) of the Yellow River basin. The effects of vegetation restoration on ET and its components, vegetation transpiration (Et), soil evaporation (Es), and canopy interception evaporation (Ei) were separated by manipulating model variables. Our findings are as follows: (1) The simulation results are compared with the ET calculated by water balance and the annual average ET of MODIS products. The R2 of the validation results are 0.61 and 0.78, respectively. The results show that the PT-JPL model tracks the change in ET in the HLS well. During 2000–2018, the ET, Ei, and Es increased at a rate of 1.33, 0.87, and 2.99 mm/a, respectively, while the Et decreased at a rate of 2.52 mm/a. (2) Vegetation restoration increased the annual ET in the region from 331.26 mm (vegetation-unchanged scenario) to 338.85 mm (vegetation change scenario) during the study period, an increase of 2.3%. (3) TMP (temperature) and VPD (vapor pressure deficit) were the dominant factors affecting ET changes in most areas of the HLS. In more than 37.2% of the HLS, TMP dominated the change affecting ET, and vapor pressure difference (VPD) dominated the area affecting ET in 30.5% of the HLS. Overall, the precipitation (PRE) and VPD were the main factors affecting ET changes. Compared with previous studies that directly explore the relationship between many influencing factors and ET results through correlation research methods, our study uses control variables to obtain results under two different scenarios and then performs difference analysis. This method can reduce the excessive interference of influencing factors other than vegetation changes on the research results. Our findings can provide strategic support for future water resource management and sustainable vegetation restoration in the HLS region. [ABSTRACT FROM AUTHOR]

With global climate change, linking vegetation phenology with net ecosystem productivity (NEP) is crucial for assessing vegetation carbon storage capacity and predicting terrestrial ecosystem changes. However, there have been few studies investigating the relationship between vegetation phenology and NEP in the middle and high latitudes of the Northern Hemisphere. This study comprehensively analyzed vegetation phenological changes and their climate drivers using satellite data. It also investigated the spatial distribution and climate drivers of NEP and further analyzed the sensitivity of NEP to vegetation phenology. The results indicated that the average land surface phenology (LSP) was dominated by a monotonic trend in the study area. LSP derived from different satellite products and retrieval methods exhibited relatively consistent responses to climate. The average SOS and POS for different retrieval methods showed a higher negative correlation with nighttime temperatures compared to daytime temperatures. The average EOS exhibited a higher negative correlation with daytime temperatures than a positive correlation. The correlations between VPD and the average SOS, POS, and EOS showed that the proportion of negative correlations was higher than that of positive correlations. The average annual NEP ranged from 0 to 1000 gC·m−2. The cumulative trends of NEP were mainly monotonically increasing, accounting for 61.04%, followed by monotonically decreasing trends, which accounted for 17.95%. In high-latitude regions, the proportion of positive correlation between VPD and NEP was predominant, while the proportion of negative correlation was predominant in middle-latitude regions. The positive and negative correlations between soil moisture and NEP (48.08% vs. 51.92%) were basically consistent in the study area. The correlation between SOS and POS with NEP was predominantly negative. The correlation between EOS and NEP was overall characterized by a greater proportion of negative correlations than positive correlations. The correlation between LOS and NEP exhibited a positive relationship in most areas. The sensitivity of NEP to vegetation phenological parameters (SOS, POS, and EOS) was negative, while the sensitivity of NEP to LOS was positive (0.75 gC·m−2/d for EVI vs. 0.63 gC·m−2/d for LAI vs. 0.30 gC·m−2/d for SIF). This study provides new insights and a theoretical basis for exploring the relationship between vegetation phenology and NEP under global climate change. [ABSTRACT FROM AUTHOR]

Droughts in the Weihe River Basin are occurring more frequently and are becoming more intense. These events negatively affect industrial production, economic development, and ecosystems. Studying how vegetation changes in response to them is of practical significance. We report temporal and spatial trends in vegetation cover, use a copula function to analyze relationships between drought and vegetation cover, and assess the probability of vegetation loss in different drought scenarios. A vegetation index trends upwards from north to south in this basin; from 2001 to 2017, vegetation cover also trends upward in most areas, although it decreases in areas with high vegetation cover. An escalated susceptibility to drought has been observed in the southern and eastern sectors, where proximity to the riverbank correlates with heightened drought sensitivity, particularly in zones of intensified vegetation density. The probability of vegetation loss at the same vegetation loss preset point gradually increases with increased drought severity. These results will facilitate the formulation of countermeasures to prevent and combat the effects of drought on vegetation and land management. [ABSTRACT FROM AUTHOR]

Accurate burn severity mapping is essential for understanding the impacts of wildfires on vegetation dynamics in arid savannas. The frequent wildfires in these biomes often cause topkill, where the vegetation experiences above-ground combustion but the below-ground root structures survive, allowing for subsequent regrowth post-burn. Investigating post-fire regrowth is crucial for maintaining ecological balance, elucidating fire regimes, and enhancing the knowledge base of land managers regarding vegetation response. This study examined the relationship between bush burn severity and woody vegetation post-burn coppicing/regeneration events in the Kalahari Desert of Botswana. Utilizing UAV-derived RGB imagery combined with a Random Forest (RF) classification algorithm, we aimed to enhance the precision of burn severity mapping at a fine spatial resolution. Our research focused on a 1 km2 plot within the Modisa Wildlife Reserve, extensively burnt by the Kgalagadi Transfrontier Fire of 2021. The UAV imagery, captured at various intervals post-burn, provided detailed orthomosaics and canopy height models, facilitating precise land cover classification and burn severity assessment. The RF model achieved an overall accuracy of 79.71% and effectively identified key burn severity indicators, including green vegetation, charred grass, and ash deposits. Our analysis revealed a >50% probability of woody vegetation regrowth in high-severity burn areas six months post-burn, highlighting the resilience of these ecosystems. This study demonstrates the efficacy of low-cost UAV photogrammetry for fine-scale burn severity assessment and provides valuable insights into post-fire vegetation recovery, thereby aiding land management and conservation efforts in savannas. [ABSTRACT FROM AUTHOR]

This study provides a comprehensive analysis of the dynamics of a three-level vertical food chain model, specifically focusing on the interactions between vegetation, herbivores, and predators in a Snowshoe hare-Canadian lynx system. By simplifying the model through dimensional analysis, we determine conditions for equilibrium existence and identify various types of bifurcations, including Saddle-Node and Hopf bifurcations. Additionally, the study explores codimension-two bifurcations such as Bogdanov–Takens (BT) and zero-Hopf bifurcations. Coefficient formulas of normal forms are derived through the use of center manifold reduction and normal form theory. The study also presents an approximation of homoclinic orbits near a BT bifurcation of the system by computing explicit asymptotics based on regular perturbation methods. Utilizing the MATLAB package MATCONT, a family of limit cycles and their associated bifurcations are computed, including limit point cycles, period-doubling bifurcations, cusp points of cycles, fold-flip bifurcations, and various resonance bifurcations (R1, R2, R3, and R4). The biological implications of the findings are discussed in detail, highlighting how the identified bifurcations and dynamics can impact the population dynamics of vegetation, herbivores, and predators in real-world ecosystems. Numerical experiments validate the theoretical results and provide further support for the conclusions. [ABSTRACT FROM AUTHOR]

Herbivores drive shifts in plant species composition by interacting with vegetation through defoliation, trampling and nutrient addition: urine and faeces. As herbivore effects on vegetation accumulate over time, they might spillover to other trophic levels, but how and when this happens is poorly understood. Since it is methodologically demanding to measure biodiversity across spatial gradients, an alternative approach is to assess it through biodiversity indices of vascular plants. We employed the Index of biodiversity relevance developed for Swedish flora which provides an estimated number of organisms associated with a plant species, allowing the quantification of trophic community size. Values from this index were coupled with vegetation data from a network of 96 fenced and paired grazed plots across Fennoscandia. We analysed the role herbivory has on plant richness and diversity, and on the number of organisms that interact with the vegetation according to the index values. We also explored how herbivores influence the competitive effects of tall shrubs on other plants since the dominance of a vegetation type links directly to biodiversity. Plant diversity had no clear response to grazing. Overall vegetation and the vegetation subgroups herbs and non‐fruit shrubs had higher biodiversity index values in fenced plots, indicating a higher number of plant–host interactions. Herb cover was negatively related to shrubs in both treatments but with a faster decline in the absence of herbivores. This study highlights the importance of maintaining herbivore populations in the Arctic to conserve the vegetation structure and biodiversity of the tundra. This method of coupling biodiversity indexes with vegetation data provides complementary information to the plant diversity, especially when methodological or time constraints prevent complete field inventories. [ABSTRACT FROM AUTHOR]

We analysed ground vegetation in 250 plots in 2018 in the old‐growth Picea abies‐dominated forest Säby Västerskog, south‐east Sweden as a follow‐up of studies in 1946 and 1998 with the same layout of plots. The vegetation changes were not clearly directional: the species composition in 2018 was intermediate between that of 1946 and 1998, whereas in 1998 species richness was higher and with the unique presence of a number of species indicating small‐scale disturbances. Vaccinium myrtillus increased in cover since 1946 and Avenella flexuosa decreased. This goes against regional trends that have been attributed to nitrogen deposition. Regional changes are overshadowed by local dynamics. [ABSTRACT FROM AUTHOR]

In semi-arid northeastern Brazil, where water is scarce, rainforest refugia can be seen along the coastal relief, where the trade winds bring in humidity from the Atlantic Ocean, or further inland, at the Araripe plateau where water comes from aquifer resurgence. In order to reconstruct past changes in water resurgence and in their associated vegetation types, we analyzed pollen, charcoal, and trace elements from sediment cores collected in the permanent swamps created by the resurgences. Our high temporal resolution analyses show that the vegetation was more sparse and drier than today until 2700 cal yr BP. Between 2700 and 2000 cal yr BP, palm swamp and evergreen forest tree taxa started to expand, suggesting an increase in water resurgence. At 2000 cal yr BP, the moist forest with Mauritia expanded and fire activity changed from mixed to woody fuel particles. During the last 200 cal yr BP, a decrease in the palm tree Mauritia flexuosa, an expansion of Poaceae and an increase in macrocharcoal particles are attributed to an increase in anthropogenic activities in the Araripe Basin. The Late-Holocene climatic trend seen at Araripe mirrors that of eastern Brazil and has controlled the aquifer activity, including during the major droughts that affected the region. This is highly relevant for the application of public policies that rely on the aquifers of Araripe for the 21st century. [ABSTRACT FROM AUTHOR]

AMS radiocarbon-dated palynological evidence from Embilikala Lagoon in Bundala National Park (one of the Ramsar wetland sites) on the southeast coast of Sri Lanka indicates palaeoenvironmental changes during the last 2,700 years. The persistence of fewer mangroves (eg Rhizophoraceae taxa) suggests that sea level low stands occurred between 2,700 and 1750 cal yr BP. From the later age, the relative sea level rose, and reached the present sea level at 950 cal yr BP as indicated by the mangrove maximum. At 2,250, 700–400 and 200–150 cal yr BP, the sudden increase in marine dinoflagellate cysts (eg Spiniferites mirabilis) and foraminifera (Globigerinoides ruber) suggests increased marine influence. This is consistent with a decrease in mangrove habitats. Between 2,700 and 950 cal yr BP, severely degraded dry monsoon forests and minimal levels mangrove suggest human and marine influences were the critical drivers for changing the major vegetation types along the southeastern coast. Vegetation changes have been drastic over the last millennia. [ABSTRACT FROM AUTHOR]

The quantification of carbon stocks has emerged as a critical global issue due to its vital role in ecosystem services amid increasing urbanization and the impacts of global climate change. This study assesses carbon stocks in urban green space (UGS) ecosystems using time-series remote sensing data from 2014 to 2022. Carbon stock computation was derived from vegetation indices obtained from Landsat 8 satellite sensors, specifically the red and near infrared (NIR) bands with central wavelengths of 0.665 µm and 0.705 µm, respectively. The results, based on nine years of annual data, indicate a 24% increase in carbon stocks within UGS ecosystems. However, year-to-year transitions showed significant fluctuations, with a 19% decrease in carbon stocks from 2017 to 2019, and notable increases of 25% and 40% during the 2015-2016 and 2019-2020 periods, respectively. Spatially, carbon stock fluctuations were most pronounced in agricultural ecosystems, which are vulnerable to climate change, especially during El Niño-Southern Oscillation (ENSO) and positive Indian Ocean Dipole (IOD) events that influenced vegetation dynamics, particularly in low-density areas. The most substantial contributors to carbon stocks, exhibiting relatively stable and adaptive patterns to climate change, were mangrove and urban forest ecosystems. From a state-of-the-art perspective, this research addresses a gap in the literature where previous studies focused on calculating carbon for specific periods using various model approaches. Our implementation of a new time series analysis demonstrates that carbon stocks are dynamic, as evidenced by our findings. The results underscore the importance of preserving urban forest ecosystems, which play a significant role in climate change mitigation and the reduction of urban greenhouse gas emissions. [ABSTRACT FROM AUTHOR]

Accurate assessment of crop vegetative state is crucial for agricultural management, particularly under environmental stress, and detailed field experiments face logistical and cost challenges. This study addresses two key gaps: (1) limited research on the effects of biostimulants, specifically L-alpha amino acids, on sugarcane's metabolism, yield, and quality; and (2) the need for robust, non-invasive methods to evaluate crop performance. A novel approach is proposed using the Vegetation Activity Index (VAI), derived from integrated NDVI data, as an effective tool for assessing vegetation dynamics over the crop cycle. There was no significant difference in VAI between treated and untreated areas during the plant development cycle (p = 0.342), but a significant increase in VAI was observed in treated areas post-treatment (p = 0.009). Polynomial regression models (R2: 0.921–0.959) effectively explained vegetation variability. VAI and Total Recoverable Sugars per Hectare (STH) data followed a normal distribution, with no significant difference in VAI during the plant development cycle (p = 0.342) and no significant impact on STH (p = 0.492). A strong correlation between VAI and STH for treated areas (r = 0.966, p = 0.034) was observed. The L-alpha biostimulant increased vegetation activity during critical growth periods but did not affect sugar yield. Return on investment analysis indicated high profitability for the treatment. [ABSTRACT FROM AUTHOR]

The Indo–Pacific Pollen Database (IPPD) is the brainchild of the late professor Geoffrey Hope, who gathered pollen records from across the region to ensure their preservation for future generations of palaeoecologists. This noble aim is now being fulfilled by integrating the IPPD into the online Neotoma Paleoecology Database, making this compilation available for public use. Here we explore the database in depth and suggest directions for future research. The IPPD comprises 226 fossil pollen records, most postdating 20 ka but with some extending as far back as 50 ka or further. Over 80 % of the records are Australian, with a fairly even distribution between the different Australian geographical regions, with the notable exception being Western Australia, which is only represented by three records. The records are also well distributed in the modern climate space, with the largest gap being in drier regions due to preservation issues. However, many of the records contain few samples or have fewer than five chronology control points, such as radiocarbon, luminescence or Pb-210, for the younger sequences. Average deposition time for the whole database, counted as years per centimetre, is 64.8 yrcm-1 , with 61 % of the records having a deposition time shorter than 50 yrcm-1. The slowest deposition time by geographical region occurs on Australia's east coast, while the fastest times are from the western Pacific. Overall, Australia has a slower deposition time than the rest of the Indo–Pacific region. The IPPD offers many exciting research opportunities to investigate past regional vegetation changes and associated drivers, including contrasting the impact of the first human arrival and European colonisation on vegetation. Examining spatiotemporal patterns of diversity and compositional turnover/rate of change, land cover reconstructions, and plant functional or trait diversity are other avenues of potential research, amongst many others. Merging the IPPD into Neotoma also facilitates inclusion of data from the Indo–Pacific region into global syntheses. [ABSTRACT FROM AUTHOR]

The absence of spatial and temporal cropping information in semi-arid regions poses a significant challenge in assessing the dynamics of agricultural systems at river basin scales. Satellite remote sensing provides qualitative and quantitative information to derive vegetation dynamics over extensive areas of inherent complexities due to limitations in the availability of field data and the diverse nature of agricultural cropping practices. Utilizing phenological information derived from MODIS Normalized Difference Vegetation Index (NDVI) time series data from 2003–2004 to 2021–2022, this study derives major crop types, and cropping calendar (sowing, maturity, and harvest dates) for each season and year at 250-m resolution. This study introduces an integrated function-fitting model based on the Fast Fourier Transform (FFT) and a Lagrangian 3-point derivative-based approach to extract phenological events from the NDVI time series automatically. The derived phenological information is used in a hybrid crop classification algorithm that combines a rule-based decision tree approach (using the phenological events/dates) and a random forest classifier (using the phenological metrics) to generate the classified crop map at a river basin scale for multiple seasons and years. The implemented approach successfully captured sowing and harvesting dates for every crop growing season over 19 years, with an RMSE of 9 days, as observed with the available field survey data from 2015 to 2021. The classification results from this hybrid approach demonstrate an overall 82% accuracy. The proposed method shows a substantial improvement in cropping area estimation with a 60% reduction in MAE and RMSE compared to the existing algorithm. From the long time series of derived seasonal crop data (19-year analysis period), the influence of monsoonal activities and shifts on the spatial and temporal dynamics of sowing time and cropping patterns are assessed for a large river basin, demonstrating the utility of this continuous crop calendar. Further, an extensive analysis of results highlights farmers' adaptive strategies in response to dry and wet years, providing foundational insights for future studies on assessing the impacts of climate change. Hence, the hybrid framework adopted in this study for deriving a continuous crop calendar holds immense relevance for parameterizing and utilizing such information for developing river basin scale hydrologic and crop growth models for water resources planning and assessment. [ABSTRACT FROM AUTHOR]

Vegetation is one of the important components of ecosystems that usually changes seasonally. An accurate parameterization of vegetation cover dynamics by developing time series models can strengthen our understanding of vegetation change. This research aims to investigate and model the temporal changes of net primary production (NPP) and normalized difference vegetation index (NDVI) across bioclimatic regions of Iran, including the Khazari, Baluchi, semi-desert, steppe, semi-steppe, and arid forests. We used Moderate Resolution Imaging Spectroradiometer (MODIS) sensor products for NPP and NDVI time series (MOD17A2 and MOD13Q1, respectively). The SARIMA (Seasonal Autoregressive Integrated Moving Average) time series model is developed for NPP and NDVI time series. The investigation of autocorrelation functions (ACF) showed a strong seasonality in NPP and NDVI at the 12-month lag time. Comparing the lag times from 1 to 24 month for different regions shows that the NPP variable has a stronger seasonality. The evaluation of error criteria which showed NPP time series models based on RMSE, R2, MRE, and CE criteria was better, while based on the ME criteria, the models perform better for NDVI time series (for example, in Khazari region for NPP and NDVI time series, respectively, ME = 3.67, 0.05, RMSE = 0.12, 0.18, R2 = 0.87, 0.63, MRE = 0.02, 0.12, and CE = 0.84, 0.12). The selected models provided a short-term forecasting of the NPP and NDVI index for study regions at 24-month time, which is useful for the planning and management to reduce vegetation degradation and preserve ecosystem and biodiversity. [ABSTRACT FROM AUTHOR]

To evaluate the quantitative impacts of land cover change on vegetation greenness in the significantly human-impacted subtropical region, the characteristics of land cover change were explored by land use dynamic degree, transition matrix and normalized entropy. Various methods including Standardized coefficient, LMG (Lindeman-Merenda-Gold), GEN (Genizi measure) and CAR (Correlation-Adjusted Marginal Correlation) were employed to estimate the contributions of land cover changes on vegetation greenness using MODIS data during 2001–2022 in Guangdong. The conclusions revealed that land cover changes exhibited obvious temporal characteristics in Guangdong with a significantly increasing trend of normalized entropy indicating a more balanced distribution of land cover types under human intervention. NDVI (Normalized Difference Vegetation Index) tended to increase likely due to the large-scale increase in evergreen forest. With regard to the contributions of impact factors on vegetation greenness, the contributions evaluated by LMG, GEN and CAR showed that the natural variation of NDVI accounted for the major contribution (> 33%), while the changes of evergreen forest and grassland had the highest contribution (> 37%) according to Standardized coefficient. These differences were mainly due to the characteristics of land cover changes in Guangdong, the correlations among impact factors and the inherent attributions of the methods. Moreover, the expansions of evergreen forest and urban at the expense of the reductions of grassland and cropland also had significant impacts on NDVI (> 10%) according to LMG, GEN and CAR indicating that human-induced land cover changes had remarkable influences on NDVI. [ABSTRACT FROM AUTHOR]

Ecological sluices were constructed along the Tarim River to supplement the ecosystem's water supply. However, the impact of water regulation by these sluices on the surface water area (SWA) and its relationship with the vegetation response remain unclear. To increase the efficiency of ecological water use, it is crucial to study the response of SWA to water control by the ecological gates and its relationship with vegetation restoration. We utilized the Google Earth Engine (GEE) cloud platform, which integrates Landsat-5/7/8 satellite imagery and employs methods such as automated waterbody extraction via mixed index rule sets, field investigation data, Sen + MK trend analysis, mutation analysis, and correlation analysis. Through these techniques, the spatiotemporal variations in SWA in the middle reaches of the Tarim River (MROTR) from 1990–2022 were analyzed, along with the relationships between these variations and vegetation restoration. From 1990–2022, the SWA in the MROTR showed an increasing trend, with an average annual growth rate of 12.47 km2 per year. After the implementation of ecological gates water regulations, the SWA significantly increased, with an average annual growth rate of 28.8 km2 per year, while the ineffective overflow within 8 km of the riverbank notably decreased. The NDVI in the MROTR exhibited an upward trend, with a significant increase in vegetation on the northern bank after ecological sluice water regulation. This intervention also mitigated the downward trend of the medium and high vegetation coverage types. The SWA showed a highly significant negative correlation with low-coverage vegetation within a 5-km range of the river channel in the same year and a significant positive correlation with high-coverage vegetation within a 15-km range. The lag effect of SWA influenced the growth of medium- and high-coverage vegetation. These findings demonstrated that the large increase in SWA induced by ecological gate water regulation positively impacted vegetation restoration. This study provides a scientific basis for water resource regulation and vegetation restoration in arid regions globally. [ABSTRACT FROM AUTHOR]

Active vegetation restoration plays an important role in the improvement in soil organic matter (SOM), including the carbon (C), nitrogen (N) and phosphorus (P) sequestration of degraded mining ecosystems. However, there is still a lack of understanding of the key drivers of SOM pool size and dynamics in active vegetation restoration. For this study, soil was collected from five different sites (Xiaoxian, Dingyuan, Chaohu, Tongling and Dongzhi), four habitats (platforms, slopes, steps and native areas) and two soil layers (0–20 cm and 20–40 cm) in limestone mines of Anhui province to quantify the spatial distribution of SOM contents and their stoichiometric characteristics and influential factors. It was found that the top soil in Chaohu had the highest significant C, N and P contents in the ranges of 14.95–17.97, 1.74–2.21 and 0.80–1.24 g/kg, respectively. Comparing the stoichiometric ratios of the different sites revealed significant differences in C:N and N:P ratios, but C:P ratios were relatively consistent. In particular, the C:N and C:P ratios in deep soil were higher than those in top soil, whereas the N:P ratio in deep soil was lower than that in top soil, suggesting that soil N is a major limiting factor in the top soil. The SOM content did not differ significantly between the three reclaimed habitats, but was significantly higher than that in the native habitat, suggesting that mine restoration has significantly enhanced SOM accumulation. Further analysis showed that nutrient availability and enzyme activity are important factors affecting soil C, N and P content in top soil, while the relationship gradually weakens in deep soil. This was attributed to active anthropogenic management and conservation measures during the early stages of reclamation. This study shows that the ecological recovery of the mining area can be enhanced by implementing differentiated vegetation planting strategies and anthropogenic management on different habitats in the mining area. [ABSTRACT FROM AUTHOR]