Vegetation Types Research Articles

Relationships between pollen assemblages and modern vegetation of the southern Gaoligong Mountains region, southwest China

Comprehensive understanding of the modern pollen–vegetation relationship is crucial for utilizing fossil pollen to reconstruct palaeovegetation, especially in mountainous areas of southwestern China. In this study, we present forty-five modern surface samples collected from five different vegetation communities of the southern Gaoligong Mountains region, and the vegetation composition was investigated at each sample site. The modern pollen assemblages were analyzed through multivariate analysis to evaluate the relationships between vegetation types and pollen assemblages, and to investigate the representation of major pollen types in different vegetation types. The results indicate that the surface pollen assemblages of different vegetation types reliably represent the modern vegetation. The median R-values of dominant pollen taxa in the Gaoligong Mountains region can be ordered as follows: Pinus > Alnus > Poaceae > evergreen Quercus. The over-representation of Pinus pollen, attributed to its high productivity and strong dispersal ability, makes it the dominant component of exotic pollen. Conversely, the under-representation of evergreen Quercus suggests that the presence of its pollen within a sample might indicate the growth of the local parent plant in the study area. The human activities in the region have a recognizable effect on the surface pollen spectra and also exert a significant negative impact on pollen diversity. Our study supplements the modern pollen database of the mountain regions in southwestern China, and provides representative modern pollen analogues to interpret fossil pollen records from southwestern China and similar regions.

Extrinsic and intrinsic drivers of prevalence and abundance of hard-bodied ticks (Acari: Ixodidae) in one-humped camel (Camelus dromedarius)

BackgroundTicks are ectoparasites and can be vectors of a wide range of pathogens, posing significant health risks to livestock. In the Sahara Desert of Algeria, particularly among one-humped camels (Camelus dromedarius), there is a need to better understand the factors influencing tick infestation patterns to improve livestock management and health outcomes. ObjectivesThis study aimed to investigate the prevalence, intensity, and abundance of hard-bodied ticks (Acari: Ixodidae) among dromedaries, examining both intrinsic factors (sex, age, coat color) and extrinsic variables (farming systems, vegetation types, climate zones, and elevation) that might influence tick infestation in this region. MethodsTicks were collected from 286 dromedaries across nine sites in the pre-Saharan regions of Algeria, with elevations ranging from 736 m to 980 m. The sampled camels, which ranged in age from 6 days to 21 years, were examined for tick infestations. The ticks were identified through macroscopic and microscopic methods, and their abundance was analyzed in relation to the camels' characteristics and environmental factors. Three breeding systems were recognized: extensive, intensive, and mixed. ResultsA total of 980 ticks were collected, with Hyalomma dromedarii Koch, 1844 being the most abundant species (553 specimens), followed by Hyalomma impeltatum Schulze & Schlottke, 1930 (393 specimens), and Hyalomma excavatum Koch, 1844 (34 specimens). H. dromedarii showed a preference for parasitizing brown-coated dromedaries and exhibited significantly higher infestation levels during spring (p < 0.001). No significant association was observed between tick infestation and the camels' age or sex (p > 0.05). However, the farming system had a significant impact on tick abundance, with extensive and mixed systems showing higher tick burdens compared to intensive systems (p < 0.01). Additionally, the vegetation type, climate zone, and foraging habitat elevation were found to significantly influence tick densities and prevalence. ConclusionThis study provides essential insights into the tick infestation dynamics in dromedaries in drylands of Algeria. It highlights the influence of coat color, seasonality, and farming practices on tick burden, with brown-coated camels being more susceptible during the spring. The findings underline the importance of considering both intrinsic and extrinsic factors when developing effective tick control strategies, especially for camels raised in extensive or mixed farming systems in diverse arid rangelands. Future research should expand the scope to cover other arid regions in North Africa for a comprehensive understanding of tick-host dynamics.

Diversity of ecological functions of the insect families found in Citalahab Area of Mount Halimun Salak National Park (TNGHS)

The Citalahab area of ​​Mount Halimun Salak National Park (TNGHS) contains a diversity of insects with different ecological roles. In each type of habitat there was a composition of insect ecological roles. The study aimed to determine the diversity of ecological roles of insects in forest and plantation vegetation types in the Citalahab Area of ​​the Mount Halimun Salak National Park (TNGHS). This research uses the Simple Random Sampling method using pitfall traps in randomly determined plots measuring 20 x 20 meters (5 pit fall traps) in forests and plantations, with a total of 2 plots. There were 8 orders, 36 families with ecological roles such as: disease vectors, saprophages, pollinators, pests, predators, parasitoids, fungus eaters and decomposers. Insect families that act as parasitoids and disease vectors were only found in forest vegetation types. The richness of resources found in a habitat influences the diversity of the ecological roles of the insects found in it.

Urban greenery distribution and its link to social vulnerability

Urban greenery plays a pivotal role in urban environments, impacting the environmental well-being and people’s comfort. Several studies have demonstrated a strong link between urban greenery and socioeconomic status but still lack an analysis of greenery on uneven distribution in social vulnerability. This study assesses how multi-level greenery rates distribute and associate the social vulnerability of people in 429 census tracts in the Seattle metropolitan area. It integrates multi-source urban informatics data, including remote sensing data and street view imagery, to identify various vegetation types. Then, it uses the interpretable machine learning model to explore the relationship between street-level green space distribution and community vulnerability. The results show a serious problem of uneven distribution of green spaces in urban centers since urban areas are built up and fragmented the landscape. Areas with low urban greening in the Seattle area have higher rates of poverty, unemployment, racial segregation, and housing overcrowding. Besides, greening features like street green views, which are more related to human perception, have a great association with social vulnerability. These findings contribute to the urban green spaces to better promote community equity and vulnerability.

Evaluation of Leaf Phenology of Different Vegetation Types From Local to Hemispheric Scale in CLM

AbstractAccurate simulation of plant phenology is important in Earth system models as phenology modulates land‐atmosphere coupling and the carbon cycle. Evaluations based on grid cell average leaf area index (LAI) can be misleading because multiple plant functional types (PFTs) may be present in one model grid cell and PFTs with different phenology schemes have different LAI seasonal cycles. Here we examined PFT‐specific LAI magnitudes and seasonal cycles in the Community Land Model versions 5.0 and 4.5 (CLM5.0 and CLM4.5) and their relationship with the onset of growing season triggers in the Northern Hemisphere. LAI seasonal cycle and spring onset in CLM show the best agreement with Moderate Resolution Imaging Spectroradiometer (MODIS) for temperature‐dominated deciduous PFTs. Although the agreement in LAI magnitude between CLM5.0 and MODIS is better than CLM4.5, the agreement in seasonal cycles is worse in CLM5.0. Agreements between CLM and MODIS leaf phenology are primarily determined by the PFT and phenology scheme. While productivity depends on the environmental factors to which the plant is exposed during any given growing season, differences in phenology sensitivity to its environment necessitate a decoupling between the seasonality of LAI and GPP, which in turn could lead to biases in the carbon cycle as well as surface energy balance and hence land‐atmosphere interactions. Because the discrepancy not only depends on parameterizing phenology but phenology‐environment relationship, future improvements to other model components (e.g., soil moisture) could better align the seasonal cycle of LAI and GPP.

The Characteristics of Soil Microbial Community Structure, Soil Microbial Respiration and their Influencing Factors of Three Vegetation Types in Alpine Wetland Ecosystem

The Characteristics of Soil Microbial Community Structure, Soil Microbial Respiration and their Influencing Factors of Three Vegetation Types in Alpine Wetland Ecosystem

Drought Timing Differentiates the Drought Responses of Vegetation Growth on the Tibetan Plateau

AbstractThe Tibetan Plateau, with its great hydrothermal gradients and diverse ecosystems, is considered vulnerable to climate change. Extreme drought can have detrimental effects on carbon sequestration in terrestrial ecosystems by disrupting plant eco‐hydrological processes. Such effects are presumed to vary and depend on the vegetation types, environmental factors and drought properties. The drought timing has been widely highlighted in drought studies at both regional and site scales. However, the systematic insight into the impact of drought timing on the ecosystem functioning over the Tibetan Plateau remains unclear. In this study, we investigated the responses of vegetation greenness to meteorological drought and attributed them to the drought properties, climatic and edaphic factors. We found that the timing of drought plays a predominant role in regulating vegetation drought responses on the Tibetan Plateau. Notably, we observed significant differences in vegetation responses between late growing season drought and non‐late growing season drought. In addition to drought timing, soil moisture and long‐term hydrothermal conditions also played a significant role. Furthermore, our study revealed that alpine grassland was more sensitive to the drought timing, soil moisture and sand content than woody plants. We discovered a significant interplay between rainfall at hottest quarter and drought timing, with the role of drought timing weakening as the rainfall at hottest quarter increases. These findings underscore the crucial role of drought timing in shaping ecosystem functioning in response to the changing climate regime over the Tibetan Plateau and provide crucial insights into the improvement of land surface models.

GIS and remote sensing-based wildlife habitat suitability analysis for mountain nyala (Tragelaphus buxtoni) species mapping at Bale Mountains National Park, Ethiopia

Ethiopia's Bale Mountains National Park protects the continent's largest remaining alpine environments. This park was first suggested in 1973 to safeguard its great biodiversity, including the endangered Mountain Nyala (Tragelaphus buxtoni) and Red Foxes. Despite these conservation measures, the lack of infrastructure and the enormous area projected have resulted in significant wildlife habitat fragmentation. The purpose of this study is to analyse the habitat appropriateness of the Mountain Nyala in Bale Mountains National Park using GIS and remote sensing technologies in order to inform conservation efforts and assist park managers in making decisions. To identify potential habitats for the Mountain Nyala, the study employed GIS spatial analyst techniques such as the Digital Elevation Model (DEM) and Landsat 9 (OLI/TIRS) data, as well as key environmental factors such as vegetation types, soil types, topographic factors (elevation and slope), climate factors (temperature), and proximity factors (distance to settlements, roads, and rivers). The Weights of these factors was calculated using IDRISI32 Multi-Criteria Evaluation (MCE) with the pair-wise comparison method. These weighted factor maps were then integrated through weighted overlay analysis to model wildlife habitat suitability. The analysis revealed five classes of habitat suitability; of the total land area studied, 1326.7 km2 (60%) was deemed suitable for the Mountain Nyala while 881.3 km2 (40%) was unsuitable. Specifically, 327.4 km2 (15%) was classified as highly suitable, 240.7 km2 (11%) as moderately suitable, 758.6 km2 (34%) as marginally suitable, 352.4 km2 (16%) as currently not suitable, and 528.9 km2 (24%) as permanently not suitable. The majority of suitable habitats are concentrated in the northern part of the park, along the western border, and in the Harrena forest area. This study provides vital insights into habitat suitability that are crucial for the conservation of the Mountain Nyala and the overall management of the park.

Extracting Vegetation Phenology in Heterogeneous Drylands Using LiDAR and Landsat Temporal Decomposition: A Latitudinal Assessment of Waterholes Within the Cooper Creek, Australia

AbstractLand surface phenology (LSP) is useful to understand patterns of terrestrial ecosystems. Detecting LSP in drylands is more challenging when compared to agricultural and mesic environments due to vegetation heterogeneity, the presence of evergreen and seasonal species, and the dominant role of water (which is often received episodically with variable timing) in determining vegetation growth. In this study, LiDAR‐derived vegetation classes are defined to guide and improve the interpretation of LSP metrics extracted using temporally decomposed Landsat fPAR time series. This method was applied to waterholes within the Cooper Creek floodplain, in dryland Australia, which are important for ecological conservation. Results showed that phenology is mostly associated with the recurrent vegetation (approximately 80% of all identified phenological events) in all waterholes. However, during high streamflow periods, the number of phenological events associated with the persistent vegetation greatly increased (up to 40% of the identified events). Non‐annual phenology was also identified, with more than one phenological event occurring across a water year during high streamflow periods. The duration of the phenological events of the persistent vegetation exceeded one water year during periods of high streamflow. Phenological differences of the LiDAR‐derived vegetation classes occupying the riparian zone of the waterholes were also identified. Streamflow movement across the floodplain exerts an important influence on the vegetation phenology, as suggested by a lag in the phenology when comparing southern and northern waterholes. The method developed herein can be applied to other highly spatially heterogeneous ecosystems where vegetation species simultaneously present permanent and seasonal patterns.

Crops Feed Rain to Drylands in Northwest China

AbstractAs a key region supplementing China's limited croplands, Northwest China has undergone rapid cropland expansion over the past decades to satisfy rising food demand from population growth and socio‐economic development. Although cropland expansion may overconsume local water resources in general, in Northwest China, increased precipitation and enhanced glacier melt have increased the water available for croplands. Counterintuitively, the enhanced evapotranspiration (ET) resulting from this cropland expansion could benefit remote ecologically vulnerable natural vegetation through atmospheric moisture recycling. In this study, we used a moisture tracking model to quantify contributions of croplands and cropland expansion to local precipitation and the consequent precipitation supply to natural vegetation in Northwest China. We found that the croplands contributed 27.69 billion m3/year (2.13%) of regional total precipitation and supplied 17.30 billion m3/year (2.39%) of precipitation over natural vegetation, and the cropland expansion resulted in a net increase of 80.25 million m3/year (1.07% of the total increase) in regional precipitation and 36.23 million m3/year (4.56% of the total increase) in precipitation supply for natural vegetation. Among different types of natural vegetation, grasslands received the most precipitation supply due to its vast area, followed by forests and shrublands. The more arid regions experienced not only faster rates of cropland expansion but also obtained a greater increase in regional precipitation and precipitation supply to natural vegetation. Our study quantifies the ecological impacts of cropland expansion through moisture recycling in Northwest China. This shows the complexities of water competition between agricultural development and ecological conservation in drylands and elsewhere.

Multi-temporal assessment of a wildfire chronosequence by remote sensing

The study aimed to develop a methodological framework to identify forest ecosystems affected by wildfires and evaluate their recovery chronologically. To do this remote sensing analysis, sites with burn scars were selected based on various criteria (fire severity, affected area, vegetation and soil type, slope, aspect, and one-time occurrence of wildfire in the last 23 years). Spectral vegetation indices (VIs) from satellite imagery were used to estimate burn severity and vegetation cover changes. Images of surface reflectance were obtained from the collection of Landsat 5 ETM, Landsat 7 ETM+, and Landsat 8 OLI/TIRS, available and processed on the Google Earth Engine Platform (GEE). Indices VIs (i) the normalized difference vegetation index (NDVI), (ii) the normalized burn ratio (NBR), and (iii) the differenced normalized burn ratio (dNBR) were calculated to classify burn severity. The one-time occurrence selection was performed using the LandTrendr algorithm to monitor changes in land cover and burned areas. To validate the selection, the chosen sites within the chronosequence were clustered on 4 seasons of soil properties and litter accumulation recovery. Our result can guide methodological comparisons and forest management practices on large surfaces by comparing parches of different time-affected ecosystems. Validation sites of the cluster chronosequence shows consistent recovery of soil properties as soil carbon, bulk density and litter accumulation through the studied years•The study developed a framework to identify wildfire-affected forest ecosystems and evaluate their recovery using remote sensing and local data.•Vegetation indices (NDVI, NBR, dNBR) from Landsat satellite imagery processed on the Google Earth Engine were used to assess burn severity and vegetation changes over time.•Selected sites were validated using the LandTrendr algorithm and monitored for seasonal changes in soil properties and litter accumulation.

Reduced ligninase‐cellulase ratio enhances soil carbon sequestration following afforestation of agricultural land

AbstractIntroductionAfforestation of agricultural land is one of the most essential approaches to mitigate climate change by enhancing the sequestration of atmospheric carbon (C) into the soil. C‐degrading extracellular enzymes produced by soil microbes regulated the decomposition and fate of sequestrated soil organic carbon (SOC), with potential divergent variations following afforestation across different ecosystem scales. However, the feedbacks of different C‐degrading enzymes and their relationships with SOC following afforestation of agricultural land remain unclear.Materials and MethodsWe investigated the changes in enzyme activity and their relationships with SOC in soil aggregates across two typical climatic vegetation restoration regions in China, and explored the mechanisms through which changes in enzyme activity contribute to SOC sequestration following afforestation of agricultural land.ResultsAfforestation of agricultural land generally decreased ligninase activity and increased cellulase activity across various aggregate fractions, compared to the adjacent croplands in both subtropic (Danjiangkou Reservoir, DJK) and temperate (Maoershan, MES) region. Additionally, the ratio of ligninase to cellulase (L:C) was lower in afforested lands than in the croplands, with L:C as the major factor explaining the variations of SOC sequestration following afforestation. Specifically, ligninase and L:C were negatively correlated with SOC, whereas cellulase showed positive correlations with SOC. Further analyses suggested that microbial biomass C and nitrogen (MBC and MBN) and the ratio of SOC and total nitrogen (SOC:TN) were important factors influencing L:C and subsequently regulating SOC. These results suggest that shifts in microbial enzyme production from ligninase to cellulase following afforestation, reduced the decomposition of recalcitrant C, thus contributing to SOC sequestration.ConclusionOur work underscores the critical role of reduced L:C in enhancing SOC sequestration following the restoration of croplands to afforested lands. These findings advance the understanding of the influence of microbial community physiological adaptations on C sequestration across different land use types.

Spatial distribution and risk assessment of mercury in soils over the Tibetan Plateau

The Tibetan Plateau is one of the highest and most pristine plateaus in the world, and its ecological environment has a significant impact on global climate and the distribution of water resources. Mercury (Hg), as a toxic metal pollutant, can have a severe impact on the health of living organisms and the ecosystem due to its presence in the environment. This study collected 336 soil samples from 28 sites across four typical surface vegetation landscapes (meadow, grassland, desert, and forest) on the Tibetan Plateau to measure soil THg (Total Hg) concentrations. The research aimed to explore the factors influencing soil THg levels, analyze pollution and environmental risks of THg in the surface soil, and evaluate the associated health risks to the local population. The results indicate that the mean soil THg concentration (31.84 ± 32.58 ng·g−1) of this study is compared to the background value of THg in Tibetan Plateau soils (37.0 ng·g−1), but there are significant differences in THg concentration among soils with different surface vegetation landscapes. The mean THg concentration in soils of forest vegetation types (74.42 ± 41.19 ng·g−1) is approximately twice the background value of Tibetan Plateau soils. In the forested regions of the southeastern, eastern, and southern Tibetan Plateau, soil concentrations of total mercury are relatively high, whereas in the desert areas of the northern, northwestern, and northeastern Tibetan Plateau, the concentrations are lower. Organic matter (soil organic carbon) being an important factor influencing the soil THg. Based on existing surface soil THg data from this and previous research in Tibetan Plateau (n = 477), 34.2 % of the samples show Hg pollution and potential ecological risks. However, the health risks of soil Hg to both adults and children are not significant.

Optimization of vegetation carbon content parameters and their application in carbon storage estimation in China

As a key parameter for C pool and flux assessments, vegetation carbon (C) content can be used in ecological models to predict climate-induced changes in the C sequestration capacity of vegetation. However, the differences in methods for upscaling C content from the organ to the community scale and their impact on regional C stock estimates have been ignored. Based on a comprehensive community structure survey of 72 typical natural ecosystems in China and 27,905 measured samples of plant organs (leaves, twigs, trunks, and roots), we first quantified the differences among scaling-up methods for vegetation C content. These methods included the community or dominant species-weighted mean, geometric mean, arithmetic mean, and traditional empirical coefficients (45 % and 50 %), and their impact on C storage estimation at the regional scale. Comparing the accuracy, variability, and response patterns of the different scaling-up methods, the dominant C species biomass-weighted mean (CDWM) method had the highest similarity to the community-weighted C mean (CCWM) method. Concerning vegetation C storage estimation in China's natural terrestrial ecosystems, the relative errors of the other methods ranged from −2.6 % to 8.22 % compared with that of the CCWM method (18.39 Pg C). The empirical coefficients had the highest uncertainty, with a 45 % empirical coefficient underestimating the vegetation C stock by 2.60 %, and a 50 % empirical coefficient overestimating it by 8.22 %. The CDWM method proposed here has high reliability for C storage estimation (overestimated by only 0.44 %), making it a preferable sampling and scaling-up method for regional C content and stock assessment. Additionally, our study provided the C content of plant organs for China's provinces and typical vegetation types based on the CCWM, which could be used for regional C stock assessment and C cycle models.

Independent and interactive effects of N and P additions on foliar P fractions in evergreen forests of southern China

Fertilization or atmospheric deposition of nitrogen (N) and phosphorus (P) to terrestrial ecosystems can alter soil N (P) availability and the nature of nutrient limitation for plant growth. Changing the allocation of leaf P fractions is potentially an adaptive strategy for plants to cope with soil N (P) availability and nutrient-limiting conditions. However, the impact of the interactions between imbalanced anthropogenic N and P inputs on the concentrations and allocation proportions of leaf P fractions in forest woody plants remains elusive. We conducted a meta-analysis of data about the concentrations and allocation proportions of leaf P fractions, specifically associated with individual and combined additions of N and P in evergreen forests, the dominant vegetation type in southern China where the primary productivity is usually considered limited by P. This assessment allowed us to quantitatively evaluate the effects of N and P additions alone and interactively on leaf P allocation and use strategies. Nitrogen addition (exacerbating P limitation) reduced the concentrations of leaf total P and of different leaf P fractions. Nitrogen addition reduced the allocation to leaf metabolic P but increased the allocation to other fractions, while P addition showed opposite trends. The simultaneous additions of N and P showed an antagonistic (mutual suppression) effect on the concentrations of leaf P fractions, but an additive (summary) effect on the allocation proportions of leaf P fractions. These results highlight the importance of strategies of leaf P fraction allocation in forest plants under changes in environmental nutrient availability. Importantly, our study identified critical interactions associated with combined N and P inputs that affect leaf P fractions, thus aiding in predicting plant acclimation strategies in the context of intensifying and imbalanced anthropogenic nutrient inputs.

Effects of the types and ages of vegetation restoration on land surface roughness in the Eastern Hobq Desert, Northern China

Vegetation restoration has an important remodelling effect on near-surface characteristics, and consequent changes in land surface roughness (LSR) are key influences on soil wind erosion processes. However, the effects of vegetation restoration types and ages on LSR and the underlying mechanisms are not fully understood. In this study, the sand-fixing vegetation restoration area of the Hobq Desert was examined in comparison to a bare sand control area. The LSR of four artificial vegetation types (Salix psammophila, Caragana korshinskii, Artemisia ordosica, and Populus simonii) with restoration age of 36 years, and Salix psammophila and Caragana korshinskii after different periods of restoration (20, 28, 36 and 45 years) were measured using Structure-from-Motion (SfM) photogrammetry. Near-surface characteristics that may affect LSR were also measured. The results showed that vegetation restoration was associated with a 230–409 % higher LSR compared to the control site (1.74 mm). LSR in the different vegetation restoration areas were ranked, from high to low, as follows: AO (8.85 mm) > CK (7.89 mm) > SP (6.70 mm) > PS (6.61 mm). LSR also increased with time since restoration, with the greatest rate of increase during the first 20 years. The change of LSR is mainly affected by the change of near-surface characteristics, with the direct effects of biological crust thickness (0.331), litter thickness (0.289), soil bulk density (−0.239), and clay content (0.171) being significant. Stem diameter, litter density, biological crust coverage, and soil organic matter affected LSR indirectly, mainly through acting on the above factors. Finally, LSR was effectively estimated based on biological crust thickness, litter thickness, and soil bulk density (R2 = 0.904). The research results will help to further deepen the understanding of the influence mechanism of vegetation restoration on LSR, and provide scientific basis and practical reference for vegetation ecological restoration in similar areas.

Impact of invasive alien plants on the resident floral diversity in Koshi Tappu Wildlife Reserve, Nepal.

Invasive alien plant species (IAPS) pose a serious threat to overall plant biodiversity across the globe. Nepal's national parks and protected areas are not devoid of the impact of IAPS. Unfortunately, there is a substantial gap in knowledge regarding the extent and impact of invasion in protected areas of Nepal. This study assessed the impact of invasive alien plant species on the resident plant species of the Koshi Tapu wildlife reserve. After a preliminary field observation, we selected five major IAPS in the area, Mesosphaerum suaveolens, Chromolaena odorata, Ipomoea carnea, Lantana camara, and Mikania micrantha for this study. Ten pairs of adjacent plots sized 4 m × 4 m were surveyed for each invasive species, comprising diverse vegetation types. Each pair consisted of one "invaded plot" where the invasive species was dominant with cover greater than 50%, and another "uninvaded plot" laid out in an adjacent area with similar site conditions but without the invasive species. We calculated the Sørensen Index of Similarity for each paired plot. Wilcoxon rank-sum test was employed to compare ecological parameters between invaded and uninvaded plots for various plant species. Similarly, the difference in impact between each of the five invasive species was assessed using the Kruskal-Wallis test. Species richness varied significantly between invaded and uninvaded plots for C. odorata and I. carnea. The most significant impact on species composition of invaded communities (39.6%) was observed for C. odorata. The cover of the other dominant species varied significantly between invaded and uninvaded plots for all five species studied. The Kruskal-Wallis test showed no significant difference in the impact caused by the five studied invasive species on Species richness, Shannon-Wiener diversity index, species evenness, and height of dominant species. However, a significant difference was observed between the impacts of five studied invasive species and the cover of other dominant species. The crown cover of dominant species decreased much more in the invaded plots of L. camara and M. micrantha than in other species. Specialized management efforts are required to control highly invasive species, such as C. odorata and I. carnea, alongside proactive measures to prevent further spread in ecologically sensitive areas.

Influence of soil organic carbon fractions on the soil priming effect under different vegetation restoration modes

AbstractThe soil priming effect is a key mechanism influencing carbon (C) cycling processes between the forest soil organic carbon (SOC) pool and the atmosphere. Different vegetation restoration modes have different SOC pool compositions, and it is not clear whether such differences affect the soil priming effect. Therefore, we selected soil from six typical vegetation restoration modes Platycladus orientalis (PO), Pinus sylvestris (PS), Quercus acutissima (QA), shrub (SH) and wasteland (WL) in the soil and rocky mountainous areas of northern China and measured the soil properties, microbial communities, microbial necromass carbon (MNC), SOC fractions and the soil priming effect. The SOC content decreased in the order of PO (21.33 g kg−1), PS (22.00 g kg−1), QA (13.67 g kg−1), SH (13.33 g kg−1) and WL (10.33 g kg−1), and the trends of the mineral‐associated organic carbon (MAOC) and fungal necromass carbon (FNC) content were the same as those of the SOC content. The soil priming effect was greater in both forests and shrublands than in wastelands, with the greatest effect occurring in PO forests, where the soil priming effect reached 159.91 mg CO2‐C kg−1 soil after 30 days of incubation, which was 1.4 times greater than that in WL. The soil priming effect was mainly determined by the difference in MAOC content. In addition, the soil C/N ratio and bacterial community diversity also indirectly affected the soil priming effect by influencing the soil MNC and SOC fractions. Overall, afforestation increased the SOC content, fungal necromass contribution and mineral conservation, increasing the soil priming effect. This theoretical foundation supports the enhancement of SOC sequestration capacity by implementing various modes of vegetation restoration in the future.

Multi-spatial Resolution Imagery to Estimate Above-Ground Carbon Stocks in Mangrove Forests

Mangroves are a type of vegetation that can absorb carbon and have an essential role in controlling CO2 levels in the atmosphere. Mangroves can absorb carbon better than terrestrial ecosystems because of their ability to bury carbon in sediment. This research aims to compare and measure the carbon stock content above the surface of mangroves in the field using multi-spatial resolution imagery, namely, Landsat 8 OLI, Sentinel 2A, and Planetscope. Field carbon calculations were carried out using the allometric method based on mangrove species. The calculation results are then linked through regression analysis with the vegetation index Difference Vegetation Index (DVI) results. The total carbon obtained from PlanetScope imagery was 535.27 tons, Sentinel 2A imagery was 549.23 tons, and Landsat 8 OLI imagery was 533.57 tons. Among the three images used, based on Sentinel 2A statistical analysis reflects the possibility of overfitting or the best with higher r and R2 values in the calculations. However, based on SE accuracy tests, PlanetScope has better accuracy than the other two images. Apart from that, the accuracy test results using a 1:1 goodness of fit plot for each image, the distribution pattern of mangrove carbon stock estimates shows that the entire model in mapping mangrove carbon stocks is over-estimated. The overestimated results are possible because more objects around the mangrove, especially canopy density, are recorded by remote sensing sensors compared to tree diameter as input for field carbon results.

Deep Learning-Based Leafy Vegetable Image Classification for Smart Farm Automation

Deep Learning-Based Leafy Vegetable Image Classification for Smart Farm Automation