Vegetation Types Research Articles

Evaluating the Impact of Diverse Types of Green Vegetables on Snakehead Fish (Channa Striata) Nursery through an Eco-Friendly Aquaponic Approach

Evaluating the Impact of Diverse Types of Green Vegetables on Snakehead Fish (Channa Striata) Nursery through an Eco-Friendly Aquaponic Approach

The Combined Effect of Taproot and Fibrous Roots of Herbaceous Plants and Shrubs on the Distribution of Soil Water-Stable Aggregates

Soil aggregation, an important indicator of soil restoration in degraded ecosystems, is a fundamental unit of soil structure. However, research on the influence of grass–shrub composites on the distribution of >0.25 mm soil water-stable aggregates (macroaggregates) is scarce. Therefore, this study focuses on the hill and gully region of the Loess Plateau, where vegetation has been well restored since the return of farmland to forests and grasslands. The study investigated the root and macroaggregate distribution characteristics and interrelationships of three widely distributed mixed vegetation types of Caragana korshinskii and Agropyron cristatum (C-AC), C. korshinskii and Bothriochloa ischaemum (C-BI), and C. korshinskii and Artemisia gmelinii (C-AG) in this area. The results indicate that soil macroaggregates decrease with increasing depth. Due to the spatial differences in the distribution of shrub root, the content of macroaggregates at 50 cm from the shrub base was higher than that at the shrub base, with an increase of 25.98%–34.27% in different vegetation associations. In this study, the root length density and root diameter better reflected the influence of roots on the distribution of macroaggregates, and the product of the two had a good power function relationship with the content of macroaggregates (R2 ≥ 0.82, p < 0.01). Grey correlation analysis showed that the influence of root length density on the distribution of large aggregates was greater than that of root diameter. The content of macroaggregates in the vegetation association of taproot herbaceous plants and shrubs was higher than that of fibrous root herbaceous plants. The average soil macroaggregate content in the C-AG was 15.79%–248.6% higher than that in the C-BI and C-AC. In this study, the spatial distribution differences in root caused by shrub growth were the main reason for the spatial heterogeneity of soil macroaggregate content distribution. The improvement ability of soil macroaggregates was higher in the combination of taproot herbaceous plants and shrubs than in the combination of fibrous root herbaceous plants and shrubs. The results of this study can, to some extent, reveal the influence and mechanisms of plant roots on soil aggregates in grass–shrub vegetation association.

Assessing the change in soil water deficit characteristics from grassland to forestland on the Loess Plateau

Soil moisture is an important factor that affects terrestrial ecosystems and biological growth and development, and water deficit is one of the major environmental factors threatening vegetation restoration on the Loess Plateau. The purpose was to identify the change in the soil water deficit characteristics from grassland to forestland on the Loess Plateau. In this study, we measured the soil water storage and deficit in abandoned grassland, shrubland, pioneer forestland and climax forestland along with vegetation succession in situ monitor. The results showed that the soil water content and the soil water storage with natural vegetation recovery from the abandoned grassland to shrubland and forestland showed a gradual declining trend. While on the contrary, the soil water deficit was increasing during succession, it was more severe in the deep soil than in the shallow soil layers. And the soil water deficit in July and September of the rainy season as well as that the vigorous growing period of plants was more serious than that in May and November, which are in the non-rainy season on the Chinese Loess Plateau. The vegetation types and soil depth were the key factors affecting the soil water deficiency status in the process of vegetation succession. Water-saving measures should be taken during the vigorous growing period of plants especially for those forest with natural restoration ages >50a on the Loess Plateau. The results could have great potential in the sustainable development of forestry and provide a theoretical basis for effective water management and reasonable vegetation restoration in semiarid loess regions.

Spatial Distribution of Thaw Depth in Palsas Estimated From Optical Unoccupied Aerial Systems Data

ABSTRACTMaximum seasonal thaw depth, referred to as active layer thickness (ALT), is one of the key parameters used to monitor permafrost conditions. ALT maps based on interpolation of point measurements or derived from coarse or moderate spatial resolution satellite data often hide small‐scale spatial variations in thaw depth resulting from differences in surface characteristics and microtopography. To model and predict changes in hydrological and biogeochemical processes in permafrost areas accurately, high‐resolution remote sensing‐based estimations of ALT are needed. Therefore, we applied random forest (RF) regression on a set of topographical and spectral vegetation indices derived from optical unoccupied aerial systems data, Landsat 8 land surface temperature (LST) data, and field measurements to estimate thaw depths in palsas at three mires in north‐west Finland. We also analyzed differences in thaw depths between mires located at different elevations, between dome and plateau‐shaped palsas, and between different vegetation and surface cover classes. The RF models resulted in root mean square errors from 2.4 to 5.7 cm between predicted and observed thaw depths and the R2 values of 0.57–0.96. Height from the surrounding fen surface and LST were the most important variables in thaw depth models, although high‐accuracy results were also achieved without LST. The mean thaw depths did not differ between the sites with lowest and highest elevation, whereas the thaw depths were significantly deeper in dome‐shaped palsas compared to plateaus. The thaw depths were significantly different between vegetation cover classes only on plateau‐shaped palsas. The results indicate the high impact of the topography on the palsa thaw depth, thus highlighting the importance of accurate elevation models in spatial modeling of palsa ALT. The methodology presented in this study can be applied to other permafrost regions where field measurements of ALT are accompanied with high‐resolution topographical and multispectral data.

HARVESTMEN (ARACHNIDA: OPILIONES) RECORDS IN ATLANTIC FOREST REMNANTS OF MINAS GERAIS STATE, BRAZIL

Although the Atlantic Forest harbors the world’s greatest diversity of harvestmen (Arachnida: Opiliones), many forest areas remain undersampled or lack comprehensive data. Given the significant degradation experienced by the biome, it becomes crucial to perform faunal inventories of this group across different regions. This study aimed to conduct a survey of harvestmen by rapid sampling forest fragments of a Semideciduous Forest, a type of Atlantic Forest vegetation, in Ouro Fino and Itatiaiuçu, Minas Gerais, Brazil. Harvestmen were collected at night using the active search method. A total of 140 individuals from six species and seven morphospecies were collected, revealing the importance of protecting forest fragments of deforestation. Moreover, the findings indicate that more extensive sampling efforts are needed to accurately assess harvestman richness in these forest fragments, which may be under anthropogenic pressure. Additionally, there is a need for further inventories to better understand the conservation status of harvestmen in Brazil, and further contribute for biodiversity management and conservation.

Biomass burning CO emissions: exploring insights through TROPOMI-derived emissions and emission coefficients

Abstract. Emissions from biomass burning are a significant source of air pollution, which can adversely impact air quality and ecosystems thousands of kilometres downwind. These emissions can be estimated by a bottom-up approach that relies on fuel consumed and standardized emission factors. Emissions are also commonly derived with a top-down approach, using satellite-observed fire radiative power (FRP) as a proxy for fuel consumption. Biomass burning emissions can also be estimated directly from satellite trace gas observations, including carbon monoxide (CO). Here, we explore the potential of satellite-derived CO emission rates from biomass burning and provide new insights into the understanding of satellite-derived fire CO emissions globally, with respect to differences in regions and vegetation type. Specifically, we use the TROPOMI (Tropospheric Monitoring Instrument) high-spatial-resolution satellite datasets to derive burning CO emissions directly for individual fires between 2019 and 2021 globally. Using synthetic data (with known emissions), we show that the direct emission estimate methodology has a 34 % uncertainty for deriving CO emissions (and a total uncertainty of 44 % including wind and CO column uncertainty). From the TROPOMI-derived CO emissions, we derive biome-specific emission coefficients (emissions relative to FRP) by combining the direct emission estimates and the satellite-observed FRP from the Moderate Resolution Imaging Spectrometer (MODIS). These emission coefficients are used to establish annual top-down CO emission inventories from biomass burning, showing that Southern Hemisphere Africa has the highest CO biomass burning emissions (over 25 % of global total of 300–390 Mt(CO) yr−1 between 2003–2021), and almost 25 % of global CO biomass burning emissions are from broadleaved evergreen tree fires. A comprehensive comparison between direct estimates, top-down and bottom-up approaches, provides insight into the strengths and weaknesses of each method: FINN2.5 has higher CO emissions, by a factor between 2 and 5, than all other inventories assessed in this study. Trends over the past 2 decades are examined for different regions around the globe, showing that global CO biomass burning emissions have, on the whole, decreased (by 5.1 to 8.7 Mt(CO) yr−1), where some regions experience increased and others decreased emissions.

Characterization and depositional pattern of the modern pollen and non-pollen palynomorphs in Pobitora Wildlife Sanctuary, India and its implications to palaeoecology and palaeoherbivory analysis

ABSTRACT This study documents the depositional pattern of modern pollen and fungal spores in relation to the different vegetation types and wildlife activities in Pobitora Wildlife Sanctuary located in northeast India. The pollen data accurately matches the extant vegetation types and provides additional evidence on the representation and relative abundance of the major pollen taxa in the pollen assemblages. Forest habitat is characterized by the abundance of Bombax, Lagerstroemia, Barringtonia, and Albizia pollen in the pollen assemblage. The swamp habitat is characterized by a Cyperaceae, Onagraceae, Nymphaea, and Potamogeton the grassland habitat characterized by the dominance of non-cereal (Poaceae), Asteroideae, Cyperaceae, and Bombax pollen in the pollen assemblage. Among fungal spores, coprophilous fungal spores were observed and identified. Their presence varies in relation to the different vegetation types and level of wildlife activity in each habitat in the wildlife sanctuary. Rhododendron pollen in the palynoassemblages is indicative of seasonal flooding during periods of high rainfall in and around the study areas. Principal Component Analysis (PCA) applied to the quantified data obtained from the pollen frequency analyses revealed a significant variation that distinguished the three different vegetation types in the Pobitora Wildlife Sanctuary. This modern pollen and fungal spore data serves as a reliable baseline for the reconstruction of the palaeoecology and palaeoherbivory in the Pobitora Wildlife Sanctuary and to correlate the types of vegetation present in other parts of the tropical region of Indo-Burma.

Untangling the environmental drivers of gross primary productivity in African rangelands

Precipitation variability is forecast to increase under climate change but its impacts on vegetation productivity are complex. Here, we use generalised additive models and remote sensing-derived datasets to quantify the effect of precipitation amount, distribution, and intensity on the gross primary productivity of dry rangelands across sub-Saharan Africa from 2000 to 2019 and differentiate these effects from other variables. We find that total precipitation is the primary driver of productivity, but that more variable rainfall has a small negative effect across vegetation types and rainfall regimes. Temperature and soil nitrogen also have strong effects, especially in drier rangelands. Shrublands and grasslands are more sensitive to environmental variability than savannas. Our findings support a model in which the main constraints on productivity are maintenance of soil moisture and minimisation of plant water stress. This highlights the risks of climate warming and increasing variability for productivity in water-limited grass and shrublands but suggests savannas may have greater resilience in Africa.

Monitoring native, non-native, and restored tropical dry forest with Landsat: A case study from the Hawaiian Islands

Tropical dry forests are highly threatened at a global scale. Long-term monitoring of remaining stands is needed to assess forest health, efficacy of management practices, and potential impacts of climate change. Using a multi-seasonal Landsat time series, we examined Normalized Difference Vegetation Index (NDVI) patterns in native dry forest, non-native vegetation types, and dry forest restoration sites from 1999 to 2022 in the Hawaiian Islands. We calculated trends in median NDVI and robust coefficient of variation of NDVI for dry and wet seasons, and used Breaks for Additive Seasonal and Trend analysis to detect trend departures. To assess the impact of regional drying trends, NDVI trends were compared to the seasonal long-term precipitation anomaly and cumulative precipitation anomaly. We found that native dry forest was less green than non-native forest, particularly during the dry season, and that median NDVI increased in both native and non-native dry forests over the study period despite negative precipitation anomaly trends. This result differs from coarser-scale studies in Hawaii, but is supported by trends in other dry forest regions. Greening was also observed in restoration study sites, especially larger sites where native species establishment and recruitment has been reported. Non-native grassland NDVI exhibited a strong positive link to precipitation anomalies, suggesting that drier climate scenarios may exacerbate the invasive grass-wildfire cycle that threatens native dry forest. These results demonstrate that Landsat time series may be used to detect seasonal variation in dry forest plots and to support restoration site monitoring in a highly fragmented ecosystem.

The threat from ozone to vegetation in Ireland

Ozone is the most damaging air pollutant to vegetation globally. Metrics of accumulated ozone above a concentration threshold (e.g. AOT40, ppb·h) have been widely used to assess ozone risk. However, there is growing consensus that accumulated Phytotoxic Ozone Dose (POD) above a receptor-specific critical stomatal flux threshold (y; nmol O3 m–2 s–1), expressed per unit of projected leaf area, provides a more reliable risk assessment, as it considers ozone entering the leaf (PODy, mmol m–2 leaf area). Few studies have assessed both concentration- and flux-based metrics using site-specific observations of ozone and meteorology. In this study we assessed the risk that ozone poses to five vegetation types across eight sites in Ireland during 2005–2021, using AOT40 and PODy risk metrics, and we predicted impacts using dose–response relationships. Long-term trends in both metrics were also assessed. The PODy critical level for vegetation protection was exceeded for all vegetation types, with exceedances most common at Atlantic coastal sites, and for tree species (beech POD1 15.7–25.7 mmol/m2 PLA). When PODy and AOT40 results were normalised based on their respective critical levels, predicted impacts were higher for PODy. There were significant increases in PODy for three vegetation types at rural sites during the study period, which also experienced increases in temperature and global solar radiation. The long-term trends were consistent with other European studies that show decreases in AOT40 and increases in PODy. While ozone concentrations in Ireland are relatively low (39–75 μg/m3 five-year average range), the humid climate and longer growing season may lead to elevated stomatal ozone uptake and thereby a risk to vegetation.

The application of unsupervised machine learning for the elucidation of the burial effect of lignin in peatland: Case of TMAH thermochemolysis

Lignin is one of the major components of organic macromolecules in peatland. Analysis of lignin in sediments is considered as a valuable tool for understanding peat vegetation as well as carbon cycle. It provides valuable perspectives on different sides such as occurrence of various vegetation types and the extent of decay in terrestrial organic material. Thermochemolysis technique using tetramethyl ammonium hydroxide (TMAH) was used for lignin analysis, in an ombrotrophic peatland. It specifically breaks of O-aryl bonds followed by methylation of the lignin components yielding phenolic subunits. Several discrepancies exist between TMAH thermochemolysis findings and those obtained from previous investigations with CuO oxidation. This could be explained by the specific pool of aryl ether, specifically targeted by the thermochemolysis, with discarding of C-C bonds. Hence, this would show the capacity of TMAH thermochemolysis to cleave oxidised lignin leaving lignin of fresh and preserved organic matter intact. The TMAH thermochemolysis method's efficiency in molecular characterization and lignin degradation was evaluated using principal component analysis (PCA). PCA reduced dimensionality and redundancy of component contributions, with the first two principal components accounting for 70.33 % of the total variance. PCA has reinforced the selectively of the thermochemolytic approach in targeting O-aryl bonds while maintaining C-C bonding of polyphenolic sub-units. Hence, two distinct oxidation phases: recent (acrotelm and mesotelm) and older (catotelm) have been revealed. PCA was applied to diagenetic and source vegetation proxies, revealing strong agreement among variables which is supported by the use of molecular ratios as indicators of organic matter source and dynamics in a peat core.

Soil labile organic carbon and nitrate nitrogen are the main factors driving carbon-fixing pathways during vegetation restoration in the Loess Plateau, China

Although the microbial fixation of CO2 is a key process in regulating soil carbon cycling, the effects of vegetation type on microbial carbon-fixing pathways and their driving factors in soils have yet to be sufficiently established. In this study, based on macro-genome sequencing and other analytical methods, we sought to determine the soil physicochemical properties, soil organic carbon contents, carbon-fixing microorganisms, and carbon-fixing genes in areas of farmland (FL), grassland (GL). Robinia pseudoacacia (RP), Caragana korshinskii (CAK), and Prunus sibirica (PS) in the Wuliwan watershed of the Loess Plateau region of China. Our findings revealed that the organic carbon contents of the assessed soils increased in the following order: FL < GL∼PS < CAK < RP (P < 0.05). Re-vegetation-based restoration was found to enhance soil organic carbon pool stability. Compared with farmland soil, the proportions of recalcitrant organic carbon had increased by 6 % and 9 % in the soil at sites that had undergone restoration with C. korshinskii and R. pseudoacacia respectively. Among the identified carbon fixation pathways, the DC/4-HB cycle had the highest relative abundance of 25.10–25.52 %. The dominant groups of carbon-fixing microorganisms were identified as Actinobacteria and Proteobacteria, accounting for over 60 % of the total abundance. Furthermore, analysis based on a partial least squares path model revealed labile organic carbon and soil nitrate nitrogen as the primary drivers of carbon fixation pathways. Collectively, our findings in this study provide evidence to indicate that restoration of vegetation on the Loess Plateau can contribute to increases in soil organic carbon content and stability and the abundance of carbon-fixing microorganisms, with R. pseudoacacia and C. korshinskii having the most significant effects in this regard. These findings have important implications for restorative vegetation carbon pool management and provide additional perspectives for understanding global carbon cycling.

Enhancing fruit and vegetable detection in unconstrained environment with a novel dataset

Automating the detection of fruits and vegetables using computer vision is essential for modernizing agriculture, improving efficiency, ensuring food quality, and contributing to sustainable and technologically advanced farming practices. This paper presents an end-to-end pipeline for detecting and localizing fruits and vegetables in real-world scenarios. To achieve this, a dataset named FRUVEG67 was curated that includes images of 67 classes of fruits and vegetables captured in unconstrained scenarios, with only a few manually annotated samples per class. A semi-supervised data annotation algorithm (SSDA) was developed that generates bounding boxes for objects to label the remaining nonannotated images. For detection, Fruit and Vegetable Detection Network (FVDNet) was proposed, an ensemble version of YOLOv8n featuring three distinct grid configurations. In addition, an averaging approach for the prediction of the bounding box and a voting mechanism for the prediction of the classes was implemented. Finally Jensen–Shannon Divergence (JSD) in conjunction with focal loss was integrated as the overall loss function for better detection of smaller objects. Experimental results highlight the superiority of FVDNet compared to recent versions of YOLO, showcasing remarkable improvements in detection and localization performance. An impressive mean average precision (mAP) score of 0.82 across all classes was achieved. Furthermore, the efficacy of FVDNet on open-category refrigerator images were evaluated, where it demonstrates promising results.

Contribution of Climatic Change and Human Activities to Vegetation Dynamics over Southwest China during 2000–2020

Southwest China is an important carbon sink area in China. It is critical to track and assess how human activity (HA) and climate change (CC) affect plant alterations in order to create effective and sustainable vegetation restoration techniques. This study used MODIS NDVI data, vegetation type data, and meteorological data to examine the regional and temporal variations in the normalized difference vegetation index (NDVI) in Southwest China from 2000 to 2020. Using trend analysis, the study looks at the temporal and geographical variability in the NDVI. Partial correlation analysis was also used to assess the effects of precipitation, extreme climate indicators, and mean temperature on the dynamics of the vegetation. A new residual analysis technique was created to categorize the effects of CC and HA on NDVI changes while taking extreme climate into consideration. The findings showed that the NDVI in Southwest China grew at a rate of 0.02 per decade between 2000 and 2020. According to the annual NDVI, there was a regional rise in around 85.59% of the vegetative areas, with notable increases in 36.34% of these regions. Temperature had a major influence on the northern half of the research region, but precipitation and extreme climate had a notable effect on the southern half. The rates at which climatic variables and human activity contributed to changes in the NDVI were 0.0008/10a and 0.0034/10a, respectively. These rates accounted for 19.1% and 80.9% of the variances, respectively. The findings demonstrate that most areas displayed greater HA-induced NDVI increases, with the exception of the western Sichuan Plateau. This result suggests that when formulating vegetation restoration and conservation strategies, special attention should be paid to the impact of human activities on vegetation to ensure the sustainable development of ecosystems.

Variation in soil water content and groundwater levels across three land cover types in a floodplain of the Kromme catchment, South Africa

AbstractInvasions of floodplains and riparian areas by alien woody species replacing predominantly herbaceous indigenous vegetation have altered the hydrological and ecosystem functioning in catchments. Although existing studies have examined changes in river flows following the establishment or clearing of alien woody vegetation, our understanding of impacts on soil water content and groundwater remains poor. Limited process knowledge restricts our capacity to reliably model and predict the impacts of land cover changes. As such, this work compared temporal variations in soil water content (SWC) and groundwater levels at three locations with different vegetation types: black wattle (Acacia mearnsii) trees, palmiet (Prionium serratum), and grass (dominated by Pennisetum clandestinum spp), within a floodplain site in the Kromme Catchment in the Eastern Cape Province of South Africa. Soil water content and shallow groundwater levels (&lt; 4 m below ground) were monitored from August 2017 to December 2019 using soil moisture probes and piezometers. Rainfall, vegetation type and antecedent conditions were identified as the major factors controlling observed responses. On average, soil water content and water retention were significantly higher (p &lt; 0.05) at the palmiet site, whilst the wattle site had the lowest SWC among the three sites. Shallow groundwater levels were also higher at the palmiet and grass sites and lowest at the wattle site. Results showed the negative impacts of black wattle trees on SWC and groundwater levels. These results are crucial for improved quantitative predictive capacity which would allow for better catchment management, for example, informing water supply planning and guiding restoration programs focusing on alien plant clearing.

Spatiotemporal Variations in MODIS EVI and MODIS LAI and the Responses to Meteorological Drought across Different Slope Conditions in Karst Mountain Regions

Based on monthly MODIS EVI and LAI data from 2001 to 2020, combined with the Standardized Precipitation Evapotranspiration Index (SPEI), this study employs Theil–Sen trend analysis, Mann–Kendall (MK) test, Hurst index analysis, and correlation analysis to comparatively analyze the overall vegetation trends, spatial distribution characteristics, and future trends of different vegetation types in Guizhou Province under varying slope conditions. The study also explores the response of vegetation to SPEI at different time scales across different slopes. The results indicate the following: (1) From 2001 to 2020, the average values of EVI (0.34%/a) and LAI (1.4%/a) during the growing season exhibited an increasing trend, with the improved vegetation areas primarily concentrated in the western region of Guizhou, while the degradation areas were mainly located in the central and eastern regions. (2) Under different slope conditions, EVI generally showed slight improvement, while LAI exhibited significant improvement, with dry-lands experiencing the largest changes. Future trends indicate continuous improvement, but the proportion of vegetation improvement area decreases with increasing slope. When the slope is less than 5°, the proportion of vegetation improvement area is the highest. (3) The positive correlation between EVI, LAI, and SPEI at different time scales is stronger than the negative correlation, with the strongest correlations observed when the slope is less than 5°. When the slope exceeds 35°, the relationship between vegetation and drought response is almost unaffected by the slope. These findings provide a scientific basis for vegetation growth monitoring and the study of climate change and vegetation interactions in Guizhou Province.

Landscape patterns of carbon fluxes in natural and disturbed ice-wedge-polygon tundra

ABSTRACT The degradation of ice-rich permafrost ecosystems due to climate change and infrastructure development strongly impacts carbon exchange dynamics in tundra landscapes. This study investigates the effects of surficial geology and infrastructure disturbances from road dust and flooding on vegetation and trace gas fluxes in polygonal ice-wedge tundra in arctic Alaska. We compared CO2 and CH4 fluxes from closed-chamber measurements at common landform elements (polygon centers, troughs, and rims) at a natural site and a disturbed site within the Prudhoe Bay Oil Field. Relationships among environmental parameters, plant species composition, and trace gas fluxes were assessed through nonmetric multidimensional scaling. Map extrapolations showed spatial variations in midsummer landscape-level ecosystem productivity and CH4 efflux at the various geologic landforms. Highest carbon uptake occurred in ice-rich drained thaw lake basins with aquatic, graminoid-dominated polygon troughs. In contrast, wet, featureless areas associated with more recently drained, ice-poor thaw lake basins showed a net carbon loss even during summer. The damming effect of road infrastructure led to deeply flooded, minimally vegetated troughs with low ecosystem respiration and high CH4 fluxes close to the road. This work highlights the importance of the complex interactions among surficial geology, landform elements, vegetation type, and disturbance factors in understanding carbon exchange dynamics in ice-rich permafrost environments.

Evidence for a floristically diverse rainforest on the Falkland archipelago in the remote South Atlantic during the mid- to late Cenozoic

Abstract We report the discovery of an ancient forest bed near Stanley, on the Falkland Islands, the second such ancient deposit identified on the South Atlantic island archipelago that is today marked by the absence of native tree species. Fossil pollen, spores and wood fragments preserved in this buried deposit at Tussac House show that the source vegetation was characterized by a floristically diverse rainforest dominated by Nothofagus-Podocarpaceae communities, similar to cool temperate Nothofagus forests/woodlands and Magellanic evergreen Nothofagus rainforests. The age limit of the deposit is inferred from the stratigraphic distribution of fossil pollen species transported by wind, birds or ocean currents from southern Patagonia, as well as similar vegetation types observed across the broader region. The deposit is suggested to be between Late Oligocene and Early Miocene, making it slightly older than the previously analysed Neogene West Point Island forest bed (200 km west of Tussac House). The combined evidence adds to our current knowledge of the role of climate change and transoceanic dispersal of plant propagules in shaping high-latitude ecosystems in the Southern Hemisphere during the late Palaeogene and Neogene.

Physicochemical, Nutritional, and Antioxidant Properties of Traditionally Fermented Thai Vegetables: A Promising Functional Plant-Based Food.

Fermented plant-based products were gathered from various regions in Thailand and categorized into 10 types of traditional commercial vegetables. Different vegetable materials and natural fermentation methods influence the diverse physical, chemical, nutritional, and functional attributes of the products. All the traditionally fermented Thai vegetable samples collected showed physicochemical properties associated with the fermentation process, contributing to the nutritional and functional quality of the final products. Achieving consistent research results is challenging due to the intricate nature of food matrices and biochemical processes during fermentation. The roles of microorganisms, especially probiotics, are crucial in delivering health benefits through fermented foods. Traditionally fermented Thai vegetable foods contain high levels of total soluble solids, titratable acidity, and salinity in pickled shallot and ginger as a result of the natural fermentation process and the ingredients used. The research findings were confirmed using a hierarchical cluster analysis (HCA)-derived dendrogram pattern. The nutritional compositions, total phenolic contents, and antioxidant activities varied among the different types of vegetables. The correlations among lipid, protein, fiber, total soluble solid (TSSs), total titratable acidity (TTA), and salinity as potential biomarkers in fermented vegetable products were examined. The results suggest that traditionally fermented Thai vegetable products significantly impacted food research by enhancing the quality and preserving the authenticity of traditionally fermented Thai vegetables.

Multi-factor coupled forest fire model based on cellular automata

The risk of forest fires is substantial due to uneven precipitation distributions and abnormal climate change. This study employs cellular automata principles to analyze forest fire behavior, taking into account meteorological elements, combustible material types, and terrain slopes. The Wang Zhengfei model is utilized to compute fire spread speed, and a multifactor coupled forest fire model is developed. Comparisons with experimental data show a mean calculated fire spread speed of 0.69 m/min, which is consistent with the experimental results. Using the forest fire in Anning city, Yunnan Province, as a case study with a mean burned area of 2281 ha, the burned area, rate of change in burned area, and burning area demonstrated an increasing trend, with fluctuating states in the rate of change of the burning area. Employing the controlled variable method to examine forest fire spreading patterns under varying factors such as wind speed, vegetation type, and maximum slope reveals that under wind influence, the fire site adopts an elliptical shape with the downwind direction as the major axis. Quantitatively, when the wind speed increases from 2 m/s to 10 m/s, the burned area expands by a factor of 1.37. The ratio of the combustible material configuration coefficient to the burned area remains consistent across the different vegetation types, and the burned area increases by a factor of 1.92 when the maximum slope increases from 5° to 25°.