Socioeconomic deprivation modifies green space and mental health associations: A within person study.

Living in an area with good availability and accessibility of residential green spaces such as parks, woodlands, and residential gardens can improve mental health and reduce the global disease burden. Unlike for physical health, it is not well understood if mental health and green space associations might be modified by local area deprivation. Existing evidence for this association comes from cross-sectional studies, widely considered vulnerable to confounding and bias. Individual time-invariant mental health status, personality, and other factors may result in positive effect modification on green space and mental health associations in more deprived areas. We use fixed-effects models that remove time-invariant confounding by calculating differences within-persons to eliminate this bias and add to the existing evidence. We modelled changes in mental health status, green space, and deprivation (relative to the within-person mean) within 54,666 individuals with a combined total of 300,710 mental health scores from one of the world's largest panel surveys: "Understanding Society" in the UK. We found a positive effect of increasing residential green space on mental health and this was positively modified and intensified by area deprivation before and after adjusting for confounding. Our results support providing green space to protect against the negative impact of socioeconomic deprivation on health, particularly for those moving from a less deprived to a more deprived area.

Incorporating biotic interactions to better model current and future vegetation of the maritime Antarctic.

Maritime Antarctica's harsh abiotic conditions forged simple terrestrial ecosystems, mostly constituted of bryophytes, lichens, and vascular plants. Though biotic interactions are, together with abiotic factors, thought to help shape this ecosystem, influencing species' distribution and, indirectly, mediating their response to climate, the importance of these interactions is still fairly unknown. We modeled current and future abundance patterns of bryophytes, lichens, and vascular plants, accounting for biotic interactions and abiotic drivers, along a climatic gradient in maritime Antarctica. The influence of regional climate and other drivers was modeled using structural equation models, with and without biotic interactions. Models with biotic interactions performed better; the one offering higher ecological support was used to estimate current and future spatial distributions of vegetation. Results suggest that plants are confined to lower elevations, negatively impacting bryophytes and lichens, whereas at higher elevations both climate and other drivers influence bryophytes and lichens. Our findings strongly support the use of biotic interactions to predict the spatial distribution of Antarctic vegetation.

An integrated fast-slow plant and nematode economics spectrum predicts soil organic carbon dynamics during natural restoration.

Aboveground and belowground attributes of terrestrial ecosystems interact to shape carbon (C) cycling. However, plants and soil organisms are usually studied separately, leading to a knowledge gap regarding their coordinated contributions to ecosystem C cycling. We explored whether integrated consideration of plant and nematode traits better explained soil organic C (SOC) dynamics than plant or nematode traits considered separately. Our study system was a space-for-time natural restoration chronosequence following agricultural abandonment in a subtropical region, with pioneer, early, mid and climax stages. We identified an integrated fast-slow trait spectrum encompassing plants and nematodes, demonstrating coordinated shifts from fast strategies in the pioneer stage to slow strategies in the climax stage, corresponding to enhanced SOC dynamics. Joint consideration of plant and nematode traits explained more variation in SOC than by either group alone. Structural equation modeling revealed that the integrated fast-slow trait spectrum influenced SOC through its regulation of microbial traits, including microbial C use efficiency and microbial biomass. Our findings confirm the pivotal role of plant-nematode trait coordination in modulating ecosystem C cycling and highlight the value of incorporating belowground traits into biogeochemical cycling under global change scenarios.

Land use, land cover changes and expansion of artificial reservoirs in Eastern Thailand: implications for agriculture and vegetation drought reduction.

Eastern Thailand and Rayong province face perennial drought and water scarcity due to natural characteristics of climate and geology. Therefore, increasing water surface by man-made reservoirs is one of the priorities in the regional development plan to provide water adequately for industrial purposes, domestic consumption, and agriculture. The large reservoir constructions may induce land use, land cover changes (LULCC), yet it also is expected to alleviate the drought harshness in the region. By delineating Landsat satellite images and spatial analysis, this study revealed the LULCC in Rayong from 1990 to 2020. The most prominent LULCC was surface water expansion, about 10.9% per year, yet the increase was the most substantial in the first decade rather than the last two decades. Vegetation expansion was observed, contributing to an increase in forests/plantations and intensified agriculture by 39.19% and 25.54%, respectively. The LULCC corresponded to a 3.64% increase in ecosystem service values (ESV), implying positive benefits from the LULCC. Vegetation drought conditions monitored by the vegetation health index (VHI) exhibited an improvement trend, especially in the eastern basins. The development of artificial reservoirs was proven to stimulate the expansion of intensive agriculture and vegetation drought mitigation with spatial heterogeneity, spreading mainly across areas of the basins rather than remote areas. The research findings inform the efficiency of the reservoirs and irrigation systems regarding the beneficial effects on drought mitigation and water scarcity for agricultural cultivation. They also provide spatial information on areas still hindered by water problems that should be addressed in future strategies.

Precision estimation of winter wheat crop height and above-ground biomass using unmanned aerial vehicle imagery and oblique photoghraphy point cloud data.

Introduction: Crop height and above-ground biomass (AGB) serve as crucial indicators for monitoring crop growth and estimating grain yield. Timely and accurate acquisition of wheat crop height and AGB data is paramount for guiding agricultural production. However, traditional data acquisition methods suffer from drawbacks such as time-consuming, laborious and destructive sampling. Methods: The current approach to estimating AGB using unmanned aerial vehicles (UAVs) remote sensing relies solely on spectral data, resulting in low accuracy in estimation. This method fails to address the ill-posed inverse problem of mapping from two-dimensional to three-dimensional and issues related to spectral saturation. To overcome these challenges, RGB and multispectral sensors mounted on UAVs were employed to acquire spectral image data. The five-directional oblique photography technique was utilized to construct the three-dimensional point cloud for extracting crop height. Results and Discussion: This study comparatively analyzed the potential of the mean method and the Accumulated Incremental Height (AIH) method in crop height extraction. Utilizing Vegetation Indices (VIs), AIH and their feature combinations, models including Random Forest Regression (RFR), eXtreme Gradient Boosting (XGBoost), Gradient Boosting Regression Trees (GBRT), Support Vector Regression (SVR) and Ridge Regression (RR) were constructed to estimate winter wheat AGB. The research results indicated that the AIH method performed well in crop height extraction, with minimal differences between 95% AIH and measured crop height values were observed across various growth stages of wheat, yielding R2 ranging from 0.768 to 0.784. Compared to individual features, the combination of multiple features significantly improved the model's estimate accuracy. The incorporation of AIH features helps alleviate the effects of spectral saturation. Coupling VIs with AIH features, the model's R2 increases from 0.694-0.885 with only VIs features to 0.728-0.925. In comparing the performance of five machine learning algorithms, it was discovered that models constructed based on decision trees were superior to other machine learning algorithms. Among them, the RFR algorithm performed optimally, with R2 ranging from 0.9 to 0.93. Conclusion: In conclusion, leveraging multi-source remote sensing data from UAVs with machine learning algorithms overcomes the limitations of traditional crop monitoring methods, offering a technological reference for precision agriculture management and decision-making.

[Spatial and Temporal Characteristics of Fractional Vegetation Cover and Its Response to Urbanization in Beijing].

Exploration of the spatiotemporal changes in fractional vegetation cover （FVC） and its response characteristics to urbanization is of great significance for urban ecological protection and planning in Beijing. This study analyzed the spatiotemporal characteristics of vegetation cover changes in Beijing from 2000 to 2020 using the Theil-Sen Median and Mann-Kendall methods based on a long-term time series vegetation cover dataset. Then, this study used the urbanization index as a key indicator of spatial urbanization and utilized the transect line and global grid analysis methods to investigate the response characteristics of FVC to different urbanization gradients. The results indicated that： ① FVC changes showed spatial and temporal heterogeneity. From 2000 to 2020, Beijing was predominantly covered by high vegetation, accounting for 65.22% of the total area, which was mainly distributed in ecological conservation areas consistent with the Jundu, Xishan, and Yaji Mountain ranges. The FVC presented an overall positive development trend, with a decreasing trend of areas with low FVC. The increase in FVC was significant （by 28.68%）, mainly distributed in ecological conservation areas and within a range of 10-12 km in concentric circles centered around Tiananmen Square. The urbanization index and FVC change rate were relatively high in Haidian District, Chaoyang District, Fengtai District, Shijingshan District, and Changping District. ② The artificial land surface in 2000, 2010, and 2020 was 9.69%, 13.64%, and 21.19%, respectively, with significant spatial agglomeration and strong spatial heterogeneity. During the urbanization process in Beijing, the increase in artificial land surface reached 11.5%, with the conversion from arable land to artificial land surface accounting for 53.83% of the total land use conversion area. ③ There was a significant negative correlation between FVC and the urbanization index, indicating that urbanization had a negative impact on regional FVC. However, as the urbanization process stabilized, this negative correlation tended to gradually weaken. Although the central urban areas were mainly characterized by low FVC, there was a significant increasing trend in the FVC, indicating a positive development in the FVC and an improvement in regional ecological quality, which was closely related to the governance of the mountain-water-forest-field-lake-grass-sand system. The results of the study can provide a basis for the development of vegetation restoration programs and ecological management measures in Beijing.

[NDVI Changes and Influencing Factors of Different Soil and Water Conservation Zones in Shandong Province].

Exploring the characteristics of vegetation change and its influencing factors is essential to construct an ecological environment. Based on the NDVI dataset from 2000 to 2020, this study analyzed the spatial temporal attributes of NDVI changes in Shandong Province using the Sen trend analysis and the gravity center migration model. Furthermore, the spatial heterogeneity of NDVI and its influencing factors within the whole study area and different soil and water conservation zones were investigated using a Geo-detector model, considering population, hydrological, topographic, soil types, and vegetation types. The results were as follows： ① The NDVI in Shandong Province from 2000 to 2020 showed a fluctuating upward trend with significant seasonal characteristics that varied from different zones. The annual NDVI change showed a trend of single-peak in the Ⅲ-4-2t, Ⅲ-4-1xt, and Ⅲ-5-2w but showed a trend of double-peak in the Ⅲ-5-3fn. ② Regarding the spatial distribution, the NDVI was higher in the west-north and west-south areas and lower in the north and coastal areas. During the 21 years, the primary type of NDVI change was "medium-high coverage → high coverage," especially in the northeastern part of the soil conservation area of the Ⅲ-4-2t, the western part of the Ⅲ-4-1xt, and the ecological maintenance area of the Ⅲ-5-2w. Overall, 61.47% of the area had a positive trend of NDVI change with the gravity center of high coverage mitigating to the northeast, and the ecological environment was improved. ③ Soil types and population density were the dominant factors affecting NDVI in Shandong Province, with q values of 0.174 and 0.130, respectively. The chief factor in the Ⅲ-5-3fn, Ⅲ-4-2t, and Ⅲ-4-1xt was population density, with q values higher than 0.22, and the dominant factors in the Ⅲ-5-2w were soil types and vegetation types, with q values of 0.326 and 0.227, respectively. The interaction of the two factors enhanced the influence of the single factor, and the relationship between the influencing factors showed two-factor enhancement and nonlinear enhancement. The q-value of population density ∩ relative humidity was the highest, with a value of 0.257 in the Ⅲ-5-3fn. The q-value of population density ∩ soil types was the highest in the Ⅲ-4-2t and Ⅲ-4-1xt, reaching 0.297 and 0.378, respectively. The q-value of soil types ∩ vegetation types was the highest, with a value of 0.444 in the Ⅲ-5-2w. The results are expected to provide valuable references for improving the ecological environment of Shandong Province and lay a scientific foundation to make different conservation strategies for the individual soil and water conservation zones.

[Characteristics of Vegetation and Soil of Degraded Grasslands and Their Relationships in Xizang].

To investigate the characteristics of grassland degradation on a regional scale in Xizang, data on grassland degradation from the second grassland survey of Xizang and 12 vegetation and soil indicators from the National Tibetan Plateau Data Center were collected. Using ArcMap, 10 000 random sample points were selected on raster data （excluding non-grassland, desertification, and salinization data, leaving 7 949 valid sample points）. The multi-value extraction to-point method was applied to extract degradation and indicator data for each sample point. The characteristics of degraded grassland vegetation and soil and their relationships were analyzed in Xizang. Moreover, random forest modeling was conducted to predict the trend of grassland ecosystem changes. The results indicated that： ① The grasslands in Xizang were primarily composed of alpine steppe and alpine meadow types, accounting for 45.83% and 41.15% of the valid sample points, respectively. ② With the intensification of grassland degradation, the number of steppe-type species among the 17 grassland types gradually decreased, and the proportion of steppe dominated by species such as Stipa purpurea and Carex moorcroftii decreased, whereas the proportion of miscellaneous grasses and Dasiphora fruticosa increased. ③ As the degree of degradation increased, vegetation indicators generally showed a declining trend, with soil total nitrogen, total phosphorus, total potassium, and organic carbon decreasing, whereas soil pH and bulk density increased, and soil moisture content was not significant. ④ A positive correlation exists between soil moisture content, total nitrogen, total phosphorus, total potassium, organic carbon, vegetation cover, net primary productivity of vegetation, normalized difference vegetation index, aboveground biomass, and habitat quality. However, there was a negative correlation between pH and soil bulk density, and the correlation coefficients among various indicators decreased with the intensification of degradation. ⑤ The random forest simulation results showed that during the degradation process, the contribution rates of soil bulk density and habitat quality both exceeded 12%, with the model prediction accuracy reaching 78%. The study revealed that grassland degradation in Xizang was closely related to soil bulk density and habitat quality, indicating that higher soil bulk density or lower habitat quality may correspond to more severe grassland degradation. This provides a scientific basis for future grassland conservation and management.

[Effects of Grazing on Plant Diversity and Their Carbon Stocks in Different Types of Grasslands].

With the drying and warming of the climate and irrational grazing, various types of grasslands in Inner Mongolia have been degraded to different degrees, and different management modes will inevitably affect the plant diversity and vegetation carbon stock of soil grasslands. To clarify the changes and influencing factors of plant diversity and carbon stock in different types of grasslands under different management modes, plant species composition, aboveground biomass, and vegetation carbon were analyzed based on 18 sentinel monitoring stations across three different types of grasslands in Inner Mongolia. The results showed that grazing increased the dominance of typical grassland and desert grassland, whereas meadow grassland decreased, and the evenness index and Shannon Wiener diversity index increased less in meadow grassland and desert grassland. Grazing decreased graminaceous biomass in meadow grassland and typical grassland, whereas it increased in desert grassland. Above-ground vegetation and below-ground root carbon stocks were much higher than those in grazing areas, 1.5 and 1.2 higher, respectively, but vegetation carbon stocks in long-term grazing sites were significantly lower than those in short-term grazing. Further, the structural equations showed that the effects of geographic location, climatic factors, and soil factors on the biomass and vegetation carbon stocks of the three grassland types differed significantly. The results can provide a reference for the ecologically sustainable development of grassland and the optimization of management mode.

Deciphering the role of rodents in grassland degradation; A review.

Grasslands are vital ecosystems that play a crucial role in providing numerous services to both humans and the environment. Healthy grasslands are characterized by diverse vegetation, efficient soil, and abundant microbial communities, which enable them to function effectively. However, these ecosystems are at risk of degradation due to various factors, such as overgrazing, land conversion for agriculture, climate change, and rodent activities. Rodents, in particular, are known to have a significant impact on grassland ecosystems. Moderate and low rodent density can be beneficial for grassland dynamics by acting as ecological engineers, and playing a role in the food chain, while heavy rodent density and outbreaks can have detrimental effects. The rodent's activities are associated with and influenced by other driving factors of grassland degradation. Depending on their density and habitat, rodents can have either beneficial or detrimental effects on the dynamics of grasslands by altering the microbial communities, edaphic factors, and vegetation. This review focuses on rodent activities as one of the potential drivers of grassland degradation on vegetation, soil physicochemical dynamics, and microbial communities. This work also deciphers the interplay between rodent activities and other driving factors of grassland degradation. It also discusses potential strategies for mitigating the impact of rodent disturbance on degraded grasslands. Additionally, suggestions for future research directions are provided to explore the role of rodent activities in shaping the structure and functions of grassland ecosystems. The exact influence of rodent activities on grasslands is still not fully understood, and further manipulative research is needed to determine its impact on grassland dynamics.

Drone and ground-truth data collection, image annotation and machine learning: A protocol for coastal habitat mapping and classification.

Aerial drone imaging is an efficient tool for mapping and monitoring of coastal habitats at high spatial and temporal resolution. Specifically, drone imaging allows for time- and cost-efficient mapping covering larger areas than traditional mapping and monitoring techniques, while also providing more detailed information than those from airplanes and satellites, enabling for example to differentiate various types of coastal vegetation. Here, we present a systematic method for shallow water habitat classification based on drone imagery. The method includes:•Collection of drone images and creation of orthomosaics.•Gathering ground-truth data in the field to guide the image annotation and to validate the final map product.•Annotation of drone images into - potentially hierarchical - habitat classes and training of machine learning algorithms for habitat classification.As a case study, we present a field campaign that employed these methods to map a coastal site dominated by seagrass, seaweed and kelp, in addition to sediments and rock. Such detailed but efficient mapping and classification can aid to understand and sustainably manage ecologically and valuable marine ecosystems.

A detailed simulation study on radionuclide dispersion under spent fuel road transportation conditions: Effects of vessel type and coniferous vegetation growth.

Vegetation barriers are an important environmental characteristic of spent fuel road transportation accidents. Spent fuel vessels may be affected by force majeure factors during transportation, which leads to damage to spent fuel assemblies and containers and can cause radionuclides to gradually release from assemblies to vessels to the external environment. In this work, considering the growth periods of coniferous vegetation barriers and vessel type, a radionuclide dispersion model based on computational fluid dynamics (CFD) was established by adding a decay term and a pressure loss term. The simulations showed that, first, compared to the small (Type-II) vessel, the effects of fluid flow around the large vessel (Type-I) have a more significant impact on radionuclide dispersion. The backflow around the Type-I vessel causes leaked radionuclides to disperse towards the vessel, and the larger the vessel is, the more significant the rise of the leaked radionuclide plume tail will be due to the increased negative pressure gradient area. Moreover, the area contaminated exceeding the maximum allowable concentration by radioactivity for the Type-I vessel is reduced gradually with the growth of coniferous vegetation barriers due to the weakening of the backflow effect by growing vegetation. Second, compared to vegetation barriers of 15 years and 23 years, the horizontal distance exceeding the maximum allowable concentration of the leaked 131I dispersion from Type II vessels near vegetation barriers for 12 years is the longest. The older the vegetation barrier is, the shorter the horizontal dispersion range, and the shape of radionuclide dispersion gradually transforms from flat to semicircular with vegetation barrier growth, but this could cause a greater radioactive accumulation effect near the leakage point, and the maximum concentration of leaked 131I reached 0.54 kBq·m-3 for leaked radionuclides from the Type II vessel under vegetation barriers of 23 years. In addition, improvement suggestions based on the proposed method are presented, which will enable the Standards Institutes to apply the research methodologies described herein across various scenarios. ENVIRONMENTAL IMPLICATION: Compared to nonradioative pollutants, radioactive pollutants are intercepted by vegetation barriers and then migrate to the soil through leaves, stems, and roots, which can contaminate the surrounding environment. Considering the effects of vessel type and coniferous vegetation growth, a radionuclide dispersion model based on CFD was established. Suggestions for decontaminating radioactive pollution areas have been proposed based on the simulation results of hypothetical scenarios. The scenario applicability improvements based on the proposed model could assist relevant Standards Institutes to making improving measures.

The impact of predators and vegetation on shoaling in wild zebrafish.

In their natural habitats, animals experience multiple ecological factors and regulate their social responses accordingly. To unravel the impact of two ecological factors on the immediate behavioural response of groups, we conducted experiments on wild zebrafish shoals in arenas with vegetation, predator cues, and both factors simultaneously or neither (control treatments). Analysis of 297 trials revealed that while shoals formed significantly larger subgroups in the presence of predator cues, their subgroup size was comparable to control treatments when they faced predator cues and vegetation. Shoals were highly polarized in open arenas, in the absence of either ecological factors and in the presence of predator cues (with/without vegetation). The presence of vegetation alone, however, significantly reduced shoal polarization. Furthermore, food intake was significantly reduced when predator cues and/or vegetation were present. Tracking individuals revealed that (i) individuals within shoals receiving predator cues had a significantly higher probability to continue being in a group compared with control treatments and (ii) individuals occupying the front positions deviated less from their median position within a shoal as compared with other individuals regardless of predator cues. The adaptability of animals depends on behavioural responses to changing environments, making this study significant in the context of environmental changes.

Uncovering the impact of climate and vegetation changes on runoff in karstic regions of southwest China.

The vegetation-runoff relationship remains unclear in karstic regions. The karst landform in southwest China is a focal area where significant changes in vegetation have occurred in the past few decades, which may substantially impact water resources. To date, the effects of these changes on runoff remain uncertain. This study employed statistical analysis, numerical simulation, and scenario analysis to investigate the temporal and spatial patterns of runoff, climate, and vegetation in 20 typical catchments. The study also evaluated the response of runoff to vegetation and climate changes and the underlying factors. The findings revealed precipitation changes dominated changes in runoff in these catchments (mean contribution of 53.03%), whereas the contributions of vegetation and potential evapotranspiration changes were 23.16% and 23.82%, respectively. The study also revealed that the impacts of vegetation changes on runoff were significantly dependent on vegetation and climate factors (R2 = 0.60, P < 0.01). Furthermore, under the same climate change conditions, a higher distribution of natural vegetation (such as forest) in the catchment resulted in a larger decreasing trend in runoff. The results provide guidelines for the prediction of runoff variation in southwest China, and benefits to decision-making on ecological restoration and water resources development.

Compound hot-dry events greatly prolong the recovery time of dryland ecosystems.

Compound hot-dry events cause more severe impacts on terrestrial ecosystems than dry events, while the differences in recovery time (ΔRT) between hot-dry and dry events and their contributing factors remain unclear. Both remote sensing observations and eddy covariance measurements reveal that hot-dry events prolong the recovery time compared with dry events, with greater prolongation of recovery time in drylands than in humid regions. Random forest regression modeling demonstrates that the difference in vapor pressure deficit between hot-dry and dry events, with an importance score of 35%, is the major factor contributing to ΔRT. The severity of stomatal restriction exceeds that of non-stomatal limitation, which restricts the vegetation productivity that is necessary for the recovery process. These results emphasize the negative effect of vapor pressure deficit on vegetation recovery during hot-dry events and project an extension of drought recovery time considering elevated vapor pressure deficit in a warming world.

Effects of modified sediments on the growth of submerged macrophyte Vallisneria natans under low light conditions.

Submerged plants are an important part of aquatic ecosystems, and the restoration of submerged plants is a key step in the reconstruction of aquatic ecosystems. However, little is known about the role of modified sediments in helping submerged plants recover under low light. In this study, we set up four sediment types and two light intensities to explore the effects of modified sediments on the growth of Vallisneria natans under two low light conditions. The results showed that the independent and interactive effects of light intensity and sediment type significantly affected the biomass, morphology, photosynthetic pigment content and antioxidant enzyme activity of V. natans. At 5% and 20% natural light intensity, the sediment modified with 40% peat soil had a larger root biomass and the highest leaf and root C/N ratio, the sediment modified with 40% vermiculite had a longer root length and more ramets. At 5% natural light intensity, the sediments modified with fly ash had shorter root length and smaller leaf biomass. The sediments modified with fly ash had the greatest chlorophyll content at 20% natural light intensity. It can be concluded that the addition of 40% peat soil or 40% vermiculite in sediment is conducive to the growth of V. natans under low light conditions. Our study indicates the positive effects of the modified sediment on the growth of V. natans under low light conditions, and our study will provide a reference for the restoration of submerged plants in aquatic ecosystems.

Hyperspectral imaging for chloroplast movement detection.

We employed hyperspectral imaging to detect chloroplast positioning and assess its influence on common vegetation indices. In low blue light, chloroplasts move to cell walls perpendicular to the direction of the incident light. In high blue light, chloroplasts exhibit the avoidance response, moving to cell walls parallel to the light direction. Irradiation with high light results in significant changes in leaf reflectance and the shape of the reflectance spectrum. Using mutants with disrupted chloroplast movements, we found that blue-light-induced changes in the reflectance spectrum are mostly due to chloroplast relocations. We trained machine learning methods in the classification of leaves according to the chloroplast positioning, based on the reflectance spectra. The convolutional network showed low levels of misclassification of leaves irradiated with high light even when different species were used for training and testing, suggesting that reflectance spectra may be used to detect chloroplast avoidance in heterogeneous vegetation. We also examined the correlation between chloroplast positioning and values of indices of normalized-difference type for various combinations of wavelengths and identified an index sensitive to chloroplast positioning. We found that values of some of the vegetation indices, including those sensitive to the carotenoid levels, may be altered due to chloroplast rearrangements.

Widespread homogenization in vegetation activities along the elevational gradients across the Himalaya over the past 40 years.

Mountainous regions are vital biodiversity hotspots with high heterogeneity, providing essential refugia for vegetation. However, climate change threatens this diversity with the potential homogenization of the distinct environmental conditions at different elevations. Here, we used a time-series (1985-2023) of Normalized Difference Vegetation Index (NDVI) from Landsat archives (30 m) to quantify vegetation changes across an elevation gradient on Himalaya Mountain. Our analysis revealed that over the past 40 years, the Himalayas have experienced widespread greening, accompanied by homogenization of vegetation across elevations. This homogenization, characterized by a reduction in the differences between high and low elevations, can be attributed to two main factors: (1) increased warming and a higher snowmelt rate at high elevations, facilitating rapid changes in high-elevation vegetation activities; and (2) higher anthropogenic disturbance at low and mid elevations, thus inhibiting low-elevation vegetation. These factors have resulted in a reduction of habitat differentiation along the mountain slopes, homogenizing vegetation and potentially threatening the unique biodiversity adapted to specific elevational zones. Our findings emphasize the urgent need for conservation strategies that prioritize the protection of heterogeneous mountain habitats to preserve their rich biodiversity in the face of climate change.

Dissecting the characteristics and driver factors of potential vegetation water use efficiency in China.

While large-scale vegetation greening in China has substantially influenced global vegetation dynamics, the specific impact of this restoration on water use efficiency (WUE) remained inadequately understood. This study employed both the Geodetector and structural equation modeling (SEM) methods, utilizing the Lund-Potsdam-Jena (LPJ) Global Dynamic Vegetation Model, to explore the contributions of various driving factors to China's potential vegetation WUE from 1982 to 2019. The results indicated: (1) there existed considerable further potential for vegetation recovery nationwide. Among them, the Loess Plateau, Inner Mongolia Plateau, and northern Xinjiang had relatively high potential for vegetation recovery. This potential was further amplified by the significant prospects for enhancing WUE in these areas; (2) The application of the Geodetector method revealed that the normalized difference vegetation index (NDVI) explained over 40 % of the variation in potential vegetation WUE in China, exerting a greater influence than climatic factors. In arid/semi-arid regions, precipitation (PRE), NDVI, and vapor pressure deficit (VPD) significantly influenced WUE. Temperature (TEM) was the dominant factor affecting WUE in humid and humid/semi-humid regions; (3) Utilizing the SEM analysis method, it was evident that NDVI exerted the most substantial direct positive influence on potential vegetation WUE in China, whereas VPD and PRE had notable negative impacts. In arid/semi-arid regions, PRE emerged as the primary determinant of WUE. Conversely, in regions where water resources were not limiting, TEM and VPD exerted a more pronounced influence on potential vegetation WUE. This indicated that while vegetation restoration generally enhanced potential vegetation WUE, other factors such as PRE, TEM, and VPD played critical roles in different climatic zones, shaping the regional variations in WUE.

Delayed loss of stability of periodic travelling waves: Insights from the analysis of essential spectra.

Periodic travelling waves (PTW) are a common solution type of partial differential equations. Such models exhibit multistability of PTWs, typically visualised through the Busse balloon, and parameter changes typically lead to a cascade of wavelength changes through the Busse balloon. In the past, the stability boundaries of the Busse balloon have been used to predict such wavelength changes. Here, motivated by anecdotal evidence from previous work, we provide compelling evidence that the Busse balloon provides insufficient information to predict wavelength changes due to a delayed loss of stability phenomenon. Using two different reaction-advection-diffusion systems, we relate the delay that occurs between the crossing of a stability boundary in the Busse balloon and the occurrence of a wavelength change to features of the essential spectrum of the destabilised PTW. This leads to a predictive framework that can estimate the order of magnitude of such a time delay, which provides a novel "early warning sign" for pattern destabilisation. We illustrate the implementation of the predictive framework to predict under what conditions a wavelength change of a PTW occurs.