Vegetation Height Research Articles

Prescribed burning effectively maintains threatened species in semi‐natural grasslands on lava flows

Societal Impact StatementPrescribed burning shows promise for managing certain grassland types, but relying solely on it often reduces plant diversity, including threatened species. In Japanese dry grasslands established on volcanic ejecta, we explored conditions under which burning maintains high diversity. Lava grasslands, especially those on young lava flows with hard, shallow, and acidic soil and high rock and stone cover, harbored the most diverse plants, including threatened species. Burning helps prevent forest encroachment, efficiently maintaining species‐rich grasslands on lava flows. We recommend this approach to land managers for maintaining grasslands and conserving threatened plants, particularly in shallow, acidic soil conditions.Summary Prescribed burning can be an effective and efficient method for managing large areas of grasslands, particularly in face of global increases in grassland abandonment. However, relying solely on regular burning often leads to declines in diversity of grassland plants including threatened species in Eurasian countries. Therefore, investigating conditions under which prescribed burning effectively conserves threatened species is highly important. We hypothesized that under specific soil physicochemical conditions, even burning‐only management can maintain high threatened species diversity. To test the hypothesis, we compared soil physicochemical properties and vegetation among burning‐managed grasslands on different volcanic bedrocks (young/old lava and scoria) in Nashigahara, Yamanashi, Japan. We quantitatively investigated how bedrock, soil, and vegetation properties affected diversity of plants, including threatened species. We found the highest plant diversity in young lava grasslands, which were characterized by hard and shallow soil and high rock and stone cover, than old lava and young/old scoria grasslands. Meanwhile, soil nutrients (N, P, K, Ca, and Mg) did not vary among bedrock types and had no significant effects on plant diversity. In young lava grasslands, shallow soil, low soil pH, and resulting low vegetation height caused high threatened species diversity, supporting the hypothesis. Mature vegetation on lava flows often comprises forests worldwide. Nonetheless, our findings suggest that prescribed burning successfully suppresses tree dominance and promotes the establishment of highly species‐rich grasslands on lava flows. We propose that prescribed burning can effectively conserve threatened species in semi‐natural grasslands established under specific soil environments, such as those on lava flows.

Monitoring changes of forest height in California

Forests of California are undergoing large-scale disturbances from wildfire and tree mortality, caused by frequent droughts, insect infestations, and human activities. Mapping and monitoring the structure of these forests at high spatial resolution provides the necessary data to better manage forest health, mitigate wildfire risks, and improve carbon sequestration. Here, we use LiDAR measurements of top of canopy height metric (RH98) from NASA’s Global Ecosystem Dynamics Investigation (GEDI) mission to map vegetation height across the entire California for two different time periods (2019–2020 and 2021–2022) and explore the impact of disturbance. Exploring the reliability of machine learning methods for temporal monitoring of forest is still a developing field. We train a deep neural network to predict forest height metrics at 10-m resolution from radar and optical satellite imagery. Model validation against independent airborne LiDAR data showed a R2≥0.65 for the top of canopy height outperforming existing GEDI-based height maps and with improved sensitivity for mapping tall trees (RH98 ≥ 50 m) across California. Height showed distinct spatial variations across forest types offering quantitative and spatial information to evaluate forest conditions. The model, trained on data from 2019 to 2020, showed a similar accuracy when applied to satellite imagery acquired in 2021–2022 allowing a robust detection of changes caused by natural and man-made disturbances of forest. Changes of height captured impacts of tree mortality and fire intensity, pointing to the influence of wildfire across landscapes. Fires caused more than 60% of the large forest disturbances between the two time periods. This study demonstrates the benefits of using locally trained ML models to rapidly modernize forest management techniques in the age of increasing climate risks.

Mechanical management decreases arthropod biomass by changing vegetation structure in fallow fields of high conservation value

Abstract Arthropods play key roles in ecosystems as pollinators or as food resources for many birds. The decline in arthropods in farmland due to agricultural intensification is related to negative population trends in farmland birds. Semi‐natural areas such as fallow land are valuable habitats for arthropod communities in farmland, but the potential of these areas to boost biodiversity greatly depends on their management. We used a field experiment to explore the mechanisms behind the effects of mechanical management on arthropod communities in high conservation value fallow land. We used GLMMs to explore changes in arthropod abundance after treatment application, and pSEM to discriminate direct effects of treatments from indirect effects mediated by changes in vegetation structure. Tillage had stronger negative effects than vegetation shredding on total arthropod, spider and bee abundance, which were mediated by a reduction in vegetation height, green cover and flowering. Coleoptera biomass did not vary between treatments. The differences between treatments disappeared from 2 to 3 months after treatment application for total arthropod and spider biomass, but not for Orthoptera and bees. Synthesis and applications. Low‐intensity mechanical management of fallows has short‐term negative effects on arthropod abundance. For conservation purposes, fallow management should combine untreated fallow fields (or strips within fields) to boost arthropod communities, with low‐intensity management to create suitable breeding habitats for steppe birds.

Exploring the impacts of land titling on eco-environment: A case of livestock farming system in Inner Mongolia, China.

Livestock farming system (LFS) is an important pillar of the agri-food system. With global environmental problems severer, exploring how to improve the eco-environment of LFS through institutional change is receiving increasingly concern. Based on macro and micro data from Inner Mongolia, this study examines the impacts of land titling on the eco-environment of LFS, explores the potential mechanisms, and analyzes the heterogeneity in terms of farm size by applying GIS spatial analysis and time-varying difference-in-difference (TV-DID) model. Main results showed that overall land titling significantly improved the eco-environment represented by GVC. (1) The GIS spatial analysis indicated that land titling considerably increased GVC. The TV-DID model results further verified that land titling increased the GVC by 0.306 grade, and increased vegetation height by 1.27cm on average; (2) The effects varied across farm sizes, with the GVC increased by 0.745 grade on farms larger than 373ha and 0.230 grade otherwise; (3) The effects were mainly induced by the enhancement of farmers' attitudes, management capacities and land use behaviors after land titling. These three effects indicate the net effect, scale effect and security effect of land titling on the eco-environment of LFS, respectively. The study highlights that appropriate institutions are conducive to the sustainable management of livestock farming system, and beneficial for the natural resource-based poor worldwide.

Vegetation height estimation based on machine learning model driven by multi-source data in Eurasian temperate grassland

Vegetation height estimation based on machine learning model driven by multi-source data in Eurasian temperate grassland

Functional responses of Mediterranean flora to fire: A community‐scale perspective

Abstract Fire regime is predicted to change, particularly in Mediterranean climate regions, towards more severe and frequent fire events. From a predictive perspective, trait‐based ecology offers a comprehensive framework to characterize vegetation responses to fire. Since fires induce erosion and decrease soil nutrients, species' functional traits and their distribution at community level should reflect these changes. Despite a vast literature focused on plant traits involved in resistance to fire, quantification of community trait responses to fire is lacking, particularly for traits that are linked to resource strategies. Here, we emphasis on plant traits related to morphology (height, specific leaf area, stem and wood density) and resource acquisition strategies (leaf nitrogen, leaf dry mass, seed dry mass). We compiled three different databases compiling vegetation, fire and functional traits for the flora of Southern France. We analysed the relationships between these three components at both species and community levels. Fire numbers and area burnt did not impact species trait distributions. At community level, a clear pattern emerged between the number of fires and the distribution of different traits considered, with two main axes: on the positive PC2 axis vegetative height and seed mass; and on negative PC1 axis leaf carbon and positive PC1 axis nitrogen content and leaf area. We also showed that vegetative height is positively correlated to the aridity index distribution in the region studied. Synthesis: We analysed the relationships among fire, vegetation and functional traits, at both species and community levels. Altogether, there are highly significant direct relationships between the number of fires and leaf area (negatively) as well as seed mass (positively). For woody communities, wood density is also highly positively significant related to the number of fires. Overall, these findings suggest that fire may have an important impact on the functional response of plant communities, while not apparent when looking at individual species. Further, this research paves new ground to better understand the mechanisms behind trait convergence and the way plant communities respond to different environmental pressures.

The effect of land use intensity and habitat characteristics on butterfly community composition within the Southern Great Plains of the United States

AbstractBackgroundAs grasslands decline, grassland‐dependent species such as grassland butterflies have experienced widespread population losses. To manage remaining grasslands, prescribed fire, grazing, and haying are common management practices across the Southern Great Plains of the United States. However, the impacts of management and land use intensity (LUI) on butterfly community composition and butterfly community traits are not well understood. Additionally, local habitat characteristics such as vegetation height and cover, as well as broader landscape categorization, including how much agriculture or urbanization is occurring around the habitat, can alter butterfly communities.MethodsWe conducted standardized butterfly and flowering forb surveys at grassland sites across north‐central Oklahoma.ResultsLUI influenced overall butterfly community composition with sites managed only with fire having the most dissimilar butterfly community compared to three other management regimens. The amount of agriculture, urbanization, and wetlands surrounding study sites also influenced butterfly community composition. Flowering forb community measures differed by site with sites managed by fire alone having lower blooming forbs species richness, diversity, and abundance than sites with other management regimens.ConclusionsSites managed with only prescribed fire had the most disparate butterfly community in comparison to other management methods, suggesting that specialist butterfly species may be sensitive to increasing disturbance.

Impacts of phosphate-solubilizing bacterium strain MWP-1 on vegetation growth, soil characteristics, and microbial communities in the Muli coal mining area, China.

Due to the cold climate and low soil nutrient content, high-altitude mining areas are challenging to restore ecologically. Their poor nutrient content may be ameliorated by introducing specific microorganisms into the soil. This study aims to evaluate the effects of a highly efficient phosphate solubilizing bacterium MWP-1, Pseudomonas poae, on plant growth, soil nutrients in remedying the soil of the high-altitude Muli mining area in Qinghai Province, and analyze its impact on microbial communities through high-throughput sequencing soil microbial communities. The results showed that MWP-1 significantly increased the content of soil available phosphorus by >50%, soil organic matter and total nitrogen by >10%, and significantly increased the height, coverage, and aboveground biomass of vegetation by >40% in comparison with the control (p < 0.05). MWP-1 mainly affected the composition of the soil bacterial communities at the taxonomic level below the phylum. Its impact on soil fungal communities occurred at the phylum and below taxonomic levels. In addition, MWP-1 also significantly improved the diversity of soil bacterial and fungal communities (p < 0.05), and changed their functions. It also significantly altered the relative abundance of genes regulating phosphorus absorption and transport, inorganic phosphorus dissolution and organic phosphorus mineralization in the bacterial community (p < 0.05). It caused a significant increase in the relative abundance of the genes regulating nitrogen fixation and nitrification in nitrogen cycling (p < 0.05), but a significant decrease in the genes regulating phospholipase (p < 0.05). Although sequencing results indicated that Pseudomonas poae did not become the dominant species, its dissolved phosphorus elements can promote plant growth and development, enrich soil nutrient content, and affect the succession of microbial communities, enhance ecosystem stability, with an overall positive effect on soil remediation in the mining area.

Meadow Degradation Affects Microbial Community Structure and Vegetation Characteristics by Increasing Soil pH

ABSTRACTSoil is the natural habitat for microorganisms, providing water and nutrients for vegetation, but the influence of meadow degradation on the “vegetation‐soil‐microorganism” system is still controversial, and the drivers of soil microbial and vegetation characteristics change are still unclear. This study explores in‐depth the vegetation and soil changes in four different degradation levels, that is, non‐degraded (ND), lightly degraded (LD), moderately degraded (MD), and severely degraded (SD), in the northeastern region of the Qinghai‐Tibetan Plateau. Soil metagenomic sequencing methods were employed to understand the soil microbial and functional diversity and the factors that influence them. The findings indicated that alpine meadow degradation decreased the vegetation height, coverage, and above‐ground biomass (AGB), but increased the vegetation diversity index. In addition, meadow degradation reduces soil properties (organic carbon, total nitrogen and phosphorus, available nitrogen and phosphorus) and enzyme activities (sucrase, cellulase, urease, and catalase) but increases soil pH. The copiotrophic groups (Actinobacteria, Ascomycota) decreased while oligotrophic groups (Acidobacteria, Glomeromycota) increased with meadow degradation. In particular, changes in vegetation characteristics and microbial community structure in alpine meadows are strongly influenced by changes in soil pH. In conclusion, the degradation of alpine meadows leads to the growth of some barren‐tolerant species and deviation of soil pH from neutrality, which increases vegetation diversity but surface exposure reduces the vegetation richness, affects the type and amount of root secretions and changes in soil microbial communities, which reduce the fixation and release of soil nutrients. This study provides the theoretical basis for further analyzing the inner mechanism of alpine meadow degradation.

Monitoring Fritillaria meleagris (Liliaceae) na nowym stanowisku w Zaleskiej Woli (województwo podkarpackie)

The paper presents a new locality of Fritillaria meleagris L. in Zaleska Wola (Podkarpackie Province). The observations were conducted on a wet hay meadow with an area of about 1 ha. The study, conducted in 2023–2024, focused on the analysis of habitat conditions and plant cover, as well as the determination of the number of generative F. meleagris individuals. The species was found in an area of 1784 m2 in the central part of the meadow. The soil was slightly acidic (pH 5.9) with an average moisture content of 12.1%. The average height of the herbaceous vegetation was 70.4 cm. A total of 81 vascular plant species were recorded, of which three were classified as invasive kenophytes (Rudbeckia laciniata, Rumex confertus and Solidago gigantea). There were four species included in the list of protected species and the Polish red list of pteridophytes and flowering plants (F. meleagris, Dactylorhiza incarnata subsp. incarnata, Ophioglossum vulgatum, and Dactylorhiza majalis). The phytocenoses were classified into the Cirsietum rivularis association. The well-developed moist meadow showed a high species richness (on average 38 species recorded in the phytosociological relevé), with a high proportion of characteristic species (including Cirsium rivulare, F. meleagris, Myosotis palustris, and D. majalis). The population size of F. meleagris was 247 and 383 generative individuals in 2023 and 2024, respectively. The new locality is currently being used properly (mown only once in July, together with biomass collection), but it may be threatened by habitat drying and invasive species encroachment.

Communal nesting ecology of Little Tern (Sternula albifrons) and Small Pratincole (Glareola lactea) in two seasonally emerged riverine islands in Bangladesh

Abstract The nesting ecology of two wetland-dependent bird species, the Little Tern (Sternula albifrons) and the Small Pratincole (Glareola lactea) were studied in two seasonally emerged riverine islands, locally named as charlands in Padma River of Bangladesh. A total of 269 and 299 nests of Little Tern and Small Pratincole were found in the breeding season of 2022. We monitored 70 nests of the two species from two charlands, and the nesting success was 74.28% and 78.57%, respectively. No correlation was found between nesting success of both species in relation to clutch size, nest height, nest depth and presence of vegetation near nest. We found strong positive correlation between nesting success and nest distance to river for Little Tern. Nesting success was higher if the Little Tern’s nests were located far from the river channel. However, no such trends were observed for Small Pratincole in the study area. The main factor affecting Little Tern nesting success was nest predation by avian predator (n = 6) and tropical storms (n = 3). On the contrary, eight Small Pratincole nests were predated by avian predators and four nests were lost due to storm. However, in case of 12 deserted nests (with unhatched eggs) of both species, no apparent reasons were identified. The study suggests that these charlands, if protected from human interferences, can provide great breeding support for colonial ground nesting waterbirds.

Ecological benefits of artificial vegetation restoration on local climate condition in abandoned mining area

The abandoned mining area in Hami, Xinjiang, suffers from severe ecological degradation, necessitating urgent vegetation restoration to improve local climate conditions. This study examines the ecological benefits of artificial re-vegetation conducted by our team since 2021. Using the Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) backward trajectory model and Global Data Assimilation System (GDAS) meteorological data, the long-range movement paths of air masses reaching the study area were identified. Simultaneously, on-site monitoring of meteorological factors (air temperature and humidity) was conducted to compare differences between the control point (non-vegetated area) and the artificially vegetated area. Additionally, wind speeds were monitored on both the windward and leeward sides of the vegetation restoration area for 66 days. Wind directions perpendicular to vegetation, to assess windbreak efficiency. The results indicated that the HYSPLIT model and the K-means clustering technique classified air masses’ long-range transportation into three categories: NW, N, and ES clusters. This classification illustrated the impact of regional climatic systems on local conditions. It showed cooler and more humid air masses from the northwest contributing significantly to local climate improvements. In the restored areas, high vegetation coverage and height significantly reduced air temperature by up to 1.5 °C and increased humidity by 2.7 % compared to the control area. Windbreak efficiency was notably enhanced, with wind speeds at 0.5 to 1 m heights on the leeward side reduced by approximately 1.2–1.7 m/s. This study underscores the critical role of artificial vegetation restoration in mitigating mining activities’ adverse effects, improving local climatic conditions, and promoting sustainable ecological rehabilitation in arid regions. The findings provide valuable insights for future ecological restoration projects and sustainable environmental management in similar degraded landscapes.

Effects of Fire and Cutting on Vegetation Physical Properties and Herbivorous Foraging Behavior in the Grassland of Bardia National Park, Nepal

Grasslands are critical ecosystems providing habitats and resources for wildlife. This study investigates the effects of grassland management practices, burning and cutting, on grass species composition and physical properties i.e., height and biomass in burned and cut grassland patches in the Bardia National Park (BNP). The study was carried out at Bagaura Phata of BNP. Vegetation assessment was carried out using point intercept method, with 1m2 quadrant and vegetation samples were hand separated into different parts (green leaf, green stem, dry leaf and dry stem) to compare the physical properties between burnt and cut plots. Likewise, grazing intensity and pattern was quantified by visual inspection of grazing, pellet group count and direct observation. Species diversity index for herbivores was estimated using Shannon’s diversity index. Our findings indicate significant differences in vegetation height between fire-treated and cutting-treated plots. Fire treatment significantly increased grass height, with a mean height of approximately 27.35 cm compared to 23.03 cm in cutting-treated plots. However, no significant disparities were observed in aboveground biomass between the two treatments. Additionally, distinct significant differences were found in the proportion of green leaf and dry leaf between fire-treated and cutting-treated plots, with the proportion of dry leaf being notably lower in fire-treated plots. Correlation analysis showed a negative relationship between grass height and grazing intensity, and between grass height and pellet group counts in both treatment types, indicating that grazing intensity decreases as vegetation height increases. No significant disparities were observed in grazing intensity between cutting and fire treatments. BNP contains more than 60 grass species of different families. There was no difference in the presence of individual grass species but difference between the plots receiving cutting and fire as a treatment- high presence of forbs species in the fire treatment. Desmostachya bipinnata, Narega prophyrocoma and Imperata cylindrica were dominant species in fire treatment plots whereas Vetivera zizanoides was dominant in cutting treatment plots. The study recommend for operations that a combination of burning and cutting to maintain biodiversity and optimize habitat conditions for various herbivores.

A Pseudo-Waveform-Based Method for Grading ICESat-2 ATL08 Terrain Estimates in Forested Areas

The ICESat-2 Land and Vegetation Height (ATL08) product is a new control point dataset for large-scale topographic mapping and geodetic surveying. However, its elevation accuracy is typically affected by multiple factors. The study aims to propose a new approach to classify ATL08 terrain estimates into different accuracy levels and extract reliable ground control points (GCPs) from ICESat-2 ATL08. Specifically, the methodology is divided into three stages. First, the ATL08 terrain estimates are matched with the raw ATL03 photon cloud data, and the ATL08 terrain estimates are used to fit a continuous terrain curve. Then, using the fitted continuous terrain curve and raw ATL03 photon cloud data, a pseudo-waveform is generated for grading the ATL08 terrain estimates. Finally, all the ATL08 terrain estimates are graded based on the peak characteristics of the generated pseudo-waveform. To validate the feasibility of the proposed method, four study areas from the National Ecological Observatory Network (NEON), characterized by various terrain features and forest types were selected. High-accuracy airborne lidar data were used to evaluate the accuracy of graded ICESat-2 terrain estimates. The results demonstrate that the method effectively classified all ATL08 terrain estimates into different accuracy levels and successfully extracted high-accuracy GCPs. The root mean square errors (RMSEs) of the first accuracy level in the four selected study areas were 0.99 m, 0.51 m, 1.88 m, and 0.65 m, representing accuracy improvement of 51.7%, 58.2%, 83.1%, and 68.8%, respectively, compared to the original ATL08 terrain estimates before classifying. Additionally, a comparison with the conventional threshold-based GCP extraction method demonstrated the superior performance of our proposed approach. This study introduces a new approach to extract high-quality elevation control points from ICESat-2 ATL08 data, particularly in forested areas.

Butterfly community dynamics in a monoculture‐dominated agricultural landscape

Abstract Understanding biodiversity dynamics in agricultural landscapes is essential for promoting sustainable land use and conserving wildlife. We examined butterfly communities in a monoculture‐dominated landscape, comparing remnant grassland sites surrounded by agricultural land (AGR), grasslands (GR), and forests (FOR). Data were collected from 30 sites across these three categories. We used non‐metric multidimensional scaling (NMDS) to assess community composition, rank abundance curves for community structure, and Hill numbers for alpha diversity. Generalised additive models (GAMs) identified key drivers of rare species richness and the abundance of the most common species, Coenonympha pamphilus. Results showed a few dominant species, with most having low abundances. Species richness was similar across all site categories, but differences in evenness and species dominance highlighted variations in community structure. GR and FOR sites had higher numbers of both rare and abundant species, indicating a more balanced distribution compared to AGR sites. NMDS revealed significant differences in composition, especially between FOR and AGR. The GAM results showed that the combination of agricultural land and forest cover enhances rare species richness, while agricultural cover alone had a negative impact. Even for the most common species C. pamphilus, high agricultural cover negatively impacts its population but shifts positively when combined with greater vegetation height in adjacent grasslands. These findings highlight the critical role of forest habitats within monoculture‐dominated landscapes in enhancing butterfly community diversity and stability. The adaptability of butterfly species to agricultural landscapes is limited to a small number of species and only up to a certain extent.

Comprehensively assessing seasonal variations in the impact of urban greenspace morphology on urban heat island effects: A multidimensional analysis

The urban heat island (UHI) effect poses an increasingly essential challenge in urban areas. Investigating the seasonal variations in how the two-dimensional (2D) and three-dimensional (3D) spatial morphology of urban greenspace (UGS) contributes to mitigating UHI effect in different seasons, which can significantly enhance UGS performance and support urban renewal planning. While previous studies have established the significant influence of urban morphology on UHI effect, there remains a lack of clarity regarding the intricate interplay and combined impacts of UGS landscape patterns (2D), morphological spatial patterns (also 2D in this context), and vegetation height characteristics (3D) on mitigating or exacerbating UHI effect. Therefore, this study develops predictive models to explore the intricate relationships between different modes of UGS spatial morphology—including 2D landscape pattern benchmarks, 2D spatial pattern combinations, and a fusion of 2D and 3D spatial morphology—and surface urban heat island intensity (UHII) across different seasons employing the XGBoost regression model in a case study of the highly urbanized districts of Guangzhou, China. Additionally, a SHapley Additive exPlanations (SHAP) algorithm for comprehensive analysis was employed to gain insights into the nonlinear effects of different metrics on surface UHII within these diverse modes. The results revealed that: (1) In the benchmark mode, G_LPI and G_PD had a positive impact on mitigating surface UHII across all seasons. The G_COHESION in summer and G_LSI in spring, autumn, and winter also demonstrated significant cooling effects. (2) In the 2D spatial pattern combination mode, CORE, EDGE, BRANCH, and G_PD significantly affected surface UHII. Increasing the number of UGS spatial pattern metrics did not correspondingly increase the number of main metrics influencing surface UHII, indicating that 2D UGS spatial pattern had limited effectiveness in mitigating surface UHII. (3) In the 2D and 3D spatial morphology combination mode, the marginal impact of main metrics on surface UHII is particularly significant across seasons. TGI, CORE, MVH, G_PD, and EDGE generally demonstrated strong cooling effects. During summer and autumn, 3D metrics had a more pronounced impact on reducing surface heat accumulation, while in spring and winter, 2D metrics played the most critical role in mitigating the spread of local heat sources. (4) Even after controlling for urban morphology, UGS spatial morphology still significantly influenced the urban thermal environment across different seasons. When developing urban renewal strategies, it is essential to prioritize the impact of main UGS spatial morphology metrics and focus on diversification of marginal effects of these metrics. This approach will help ensure that UGS can provide more stable and enduring regulation of the local microclimate. Overall, this study comprehensively reveals the complex interactions between UGS spatial morphology and surface UHII, providing theoretical support for urban renewal planners and policymakers in shaping effective urban renewal strategies.

Numerical analysis of solute transport and longitudinal dispersion coefficients in vegetated flow

Reasonable estimates of longitudinal dispersion coefficients are essential for predicting solute dispersion processes. However, the current knowledge of solute dispersion processes in vegetated waters is limited. In this work, we coupled a refined hydrodynamic model with scalar transport equations to simulate the flow field and dispersion process of solutes in water under the effect of vegetation. First, the proposed numerical model was verified using laboratory experiments, revealing the excellent performance of the coupled model in complex conditions. Eight different cases were subsequently simulated to analyse the effects of the upstream flow rate and vegetation height on the streamwise velocity, solute concentration, and longitudinal dispersion coefficients. The simulation results show that the upstream flow variation exerts a marked effect on the streamwise velocity and flow field within the vegetation zone, with a velocity difference within the shear layer reaching 54.7 % for an upstream flow of 0.018 m3·s-1. The height of the vegetation affects both the velocity profile and solute dispersion. Placing emergent vegetation upstream can enhance solute dispersion in the longitudinal direction. The correlation analysis reveals that the longitudinal dispersion coefficients obtained using the routing producer are close to those determined using the theoretical method, with correlation coefficients reaching 0.75. This work presents the appropriate application range and parameters that must be considered in deriving formulas for longitudinal dispersion coefficients.

Habitat management interventions for a specialist mid- successional grassland butterfly, the Lulworth Skipper

Evidence-based management is needed to reverse declines in insect abundance. The Lulworth Skipper Thymelicus acteon is a range-restricted and declining species in the UK and northern Europe associated with mid-successional grassland, which presents management challenges because interventions are necessary to prevent long-term habitat deterioration but can result in short-term reductions in quality. In addition, site management should be compatible for the focal species and for wider plant and insect diversity. We conducted factorial experimental management trials to understand effects of cutting and rotovation on the height and structure of vegetation containing the larval host plant Tor-grass Brachypodium rupestre. We monitored vegetation height, B. rupestre cover and plant diversity, and T. acteon larval presence over four years. Rotovation and cutting differed in their effects on habitat structure and larval occupancy relative to controls. Vegetation height and host plant cover, the most important components of habitat quality for T. acteon, were faster to recover to suitable levels on cut plots. However, larval occupancy increased more quickly on rotovated plots, where plant species diversity was also higher. Results suggest that due to initial negative impacts of interventions on T. acteon occupancy, low frequency or low-intensity management, such as managing sections of a site every three years, is advisable. Our results show that rotovation or cutting the sward can be suitable for mid-successional grassland species such as Lulworth Skipper on sites where grazing might be problematic. Rotational grazing or rotovation can maintain suitable conditions for habitat specialist insects requiring a range of different grassland conditions, serving wider conservation goals.

Integration of UAV LiDAR and WorldView-2 images for modeling mangrove aboveground biomass with GA-ANN wrapper

BackgroundIntegrating optical and LiDAR data is crucial for accurately predicting aboveground biomass (AGB) due to their complementarily essential characteristics. It can be anticipated that this integration approach needs to deal with an expanded set of variables and scale-related challenges. To achieve satisfactory accuracy in real-world applications, further exploration is needed to optimize AGB models by selecting appropriate scales and variables.MethodsThis study examined the impact of LiDAR point cloud-derived metrics on estimation accuracies at different scales, ranging from 2 to 16 m cell sizes. We integrated WorldView-2 imagery with LiDAR data to construct biomass models and developed a genetic algorithm-based wrapper for variable selection and parameter tuning in artificial neural networks (GA-ANN wrapper).ResultsOur findings indicated that the highest accuracies in estimating AGB were yielded by 4 m and 6 m cell sizes, followed by 8 m and 10 m, associated with the dimensions of vegetation canopies and sampling plots. Models integrating WorldView-2 and LiDAR data outperformed those using each data source individually, reducing RMSEr by 5.80% and 3.89%, respectively. Combining these data sources can capture the canopy spectral responses and vertical vegetation structure. The GA-ANN wrapper model decreased RMSEr by 1.69% over the ANN model and dwindled the number of variables from 38 to 9. The selected variables included vegetation density, height, species, and vegetation indices.ConclusionsThe appropriate cell size for AGB estimation should consider the sizes of vegetation canopies, tree densities, and sampling plots. The GA-ANN wrapper effectively reduced variables and achieved the highest accuracy. Additionally, canopy spectral and vertical structure information are vital for accurate AGB estimation. Our study offered insights into optimizing mangrove AGB models by integrating optical and LiDAR data. The approach, data, model, and indices employed in this research can effectively predict AGB estimates of any other forest types or vegetation cover types in different climate regions.

Investigating the Influence of Vegetation Height on the Air Concentration of Supercritical Aerated Flows

Investigating the Influence of Vegetation Height on the Air Concentration of Supercritical Aerated Flows