Wetland Vegetation Research Articles

Historical changes in bird communities at Quitobaquito Springs, Arizona and impacts of climate, spring flow, and shift from Indigenous to federal-agency management

For nearly a century, bird communities at the oasis of Quitobaquito Springs in the Sonoran Desert have attracted desert ecologists. This spring-fed oasis is among the most biologically and culturally significant sites in arid southwestern North America, but has experienced marked changes in management and is threatened by climate change, border, and other development. We assembled data on birds at Quitobaquito across 83 years (1939–2022) and evaluated the patterns and potential drivers of changes in communities. We found evidence of marked community shifts that included apparent loss and replacement of species dependent on riparian and wetland vegetation, mud flats, agricultural fields, and human settlements, to species that use deeper more open-water environments, generalists, and desertscrub. Strong associations between community composition and shift from Indigenous to federal-agency management, temperature, and spring flow suggest important drivers of change, but associations with precipitation and border development were weaker. Such patterns match those for bird communities at broader scales in nearby and other aridlands and indicate impacts of increasing aridification. Our work represents the first analysis of changes in faunal assemblages at Quitobaquito that quantitatively assesses potential drivers of change, and provides insights for management and conservation.

Delineating wetland vegetation species using a UAV-mounted multi-spectral camera and computer-aided classification

Agricultural runoff can be harmful to the environment by increasing soil erosion and flooding, while adding excess nutrients such as phosphorus to downstream waterways. Stormwater detention ponds are a common way to mitigate flood risk and improve water quality in urban areas. This concept has since been adapted to protect susceptible areas downstream of agriculture. Wetland vegetation can be planted around these ponds to uptake nutrients and slow water flow. Vegetation mapping is a frequent practice within land management to monitor health and species distribution. This process could be less labor-intensive if paired with the use of aerial imagery and computer-aided classification. Unmanned Aerial Vehicle (UAV) acquired imagery allows for high temporal and spatial resolutions that can map the environment in high detail and accuracy. Here we present a detailed workflow for species-level mapping from data acquisition in the field through image processing and analysis.

Dike risk evaluation incorporating the contribution of coastal wetlands: A case study on Chongming Island, China

Due to the increasing risk of coastal disasters and climate change, the traditional gray sea dikes may become unsustainable. Coastal wetlands provide natural protection for shoreline areas and have wave attenuation capacities as green dikes. In this study, we developed a new assessment approach to evaluate comprehensive dike risk for coastal gray-green defense systems, based on the dike characters and the wave attenuation capacity of coastal wetlands for the Chongming Island. The risk assessment system consists of nine indicators of dike constructure standards, dike-top height, land subsidence, wetland vegetation width, wave attenuation capacity of vegetation, mean high water level, storm frequency, rain intensity, and annual rainfall, to determine the dike risk index (RI). The information of dike and meteorological conditions were obtained by carrying out a field survey and referring to construction bulletins and domestic statistical yearbooks. The wave attenuation effect of wetland vegetation was characterized by plant morphology and seasonality. The results indicated that, without the coastal wetland indicators, the RI values of most parts of the dike ring of the island were high. The high-risk regions were mainly located in the south and north shores, consisting of several old dikes that did not meet the constructure standard. The risk level was higher in summer and autumn than in winter and spring, due to seasonal variations (typhoon or storm frequency and intensity). When the coastal wetland indicators were included, the presence of coastal wetland vegetation reduced the dike RI values by an average of 13.6% around the Chongming Island. During the flourishing periods of the vegetation, a high rate of wave attenuation reduced the RI levels considerably. We provide a reliable framework to carry out large-scale and high-resolution dike risk assessment to be applied for wetland vegetation restoration, green dike construction, and risk management in coastal areas.

Studies on genetic diversity, gene flow and landscape genetic in Avicennia marina: Spatial PCA, Random Forest, and phylogeography approaches

Mangrove forests grow in coastal areas, lagoons, estuaries, and deltas and form the main vegetation in tidal and saline wetlands. Due to the mankind activities and also changes in climate, these forests face degradations and probably extinction in some areas. Avicennia marina is one of the most distributed mangrove species throughout the world. The populations of A. marina occur in a limited region in southern parts of Iran. Very few genetic and spatial analyses are available on these plants from our country. Therefore, the present study was planned to provide detailed information on Avicennia marina populations with regard to genetic diversity, gene flow versus genetic isolation, effects of spatial variables on connectivity and structuring the genetic content of trees populations and also identifying adaptive genetic regions in respond too spatial variables. We used SCoT molecular markers for genetic analyses and utilized different computational approaches for population genetics and landscapes analyses. The results of present study showed a low to moderate genetic diversity in the studied populations and presence of significant Fst values among them. Genetic fragmentation was also observed within each province studied. A limited gene flow was noticed among neighboring populations within a particular province. One population was almost completely isolated from the gene flow with other populations and had peculiar genetic content.Spatial PCA analysis revealed both significant global and local genetic structuring in the studied populations. Spatial variables like humidity, longitude and altitude were the most important spatial features affecting genetic structure in these populations.

Identifying conservation and restoration priorities for degraded coastal wetland vegetations: Integrating species distribution model and GeoDetector

The ongoing degradation of seagrass and seaweed is of global concern. Comprehending the spatial distribution of these wetland vegetation types and the threats they face becomes critical for effective conservation and restoration efforts. In this study, we combined a species distribution model and geographical detector to propose a novel framework for mapping the distribution and disturbance of degraded coastal wetland vegetation in sparsely recorded areas and identifying conservation and restoration priorities. Guangxi is a province in China known for its extensive coastal wetland vegetation. In our study of Guangxi, habitats suitable for two degraded vegetation types, i.e., seagrass and seaweed, were mapped using the maximum entropy model; 669.44 km2 of seagrass habitat and 929.69 km2 of seaweed habitat were identified. The geographical detector model was used to analyze anthropogenic disturbance caused by four local disturbance factors: shoreline development, fisheries, waterways, and ports and anchorages. Shoreline development was identified as the disturbance factor with the strongest impact on potential habitats of both vegetation types. According to these findings, 48.40 %–64.23 % of the vegetation habitats suffered from high anthropogenic disturbance. Preexisting nature reserves had not effectively protected wetland vegetation from human disturbance. Based on the spatial pattern of vegetation habitat and comprehensive anthropogenic disturbance, conservation and restoration priorities for seagrasses and seaweeds covering an area of 302.26 km2 were further mapped. Our results thus help improve wetland vegetation conservation by providing basic information, and they provide a tool to support site planning for seagrass and seaweed conservation and restoration.

Dynamic changes in net primary productivity of marsh wetland vegetation in China from 2005 to 2015

Wetlands are one of the world's three major ecosystems. Marsh wetland vegetation, with its unique characteristics, is playing an increasingly prominent role in absorbing atmospheric carbon dioxide and mitigating climate warming. This study estimated the annual, seasonal, and monthly trends of marsh wetland vegetation net primary productivity (NPP) in China from 2005 to 2015 based on the Carnegie–Ames–Stanford approach (CASA) model. The temporal and spatial characteristics of NPP were analyzed and the driving factors were discussed. The results showed that the annual marsh wetland vegetation NPP had an increasing trend from 2005 to 2015 on national scale in China, with the lowest and highest values in 2005 (202.03 gCm−2a−1) and 2015 (222.58 gCm−2a−1), respectively. The monthly seasonal variations in marsh wetland vegetation NPP consistent with the typical growth pattern of vegetation observed in China. Monthly marsh wetland vegetation NPP showed a unimodal distribution, and May to September were the main months for NPP accumulation. The highest vegetation NPP values occurred during the summer season. Marsh wetland vegetation types did impact the NPP distribution, Gramineous marsh vegetation contributed most to the total NPP (29%). Spatially, the NPP was higher in east than in the west, and higher in the center than in the south and north. An overall positive impact of precipitation and temperature on the Chinese marsh wetland vegetation NPP was revealed. The study recommended to give greater attention the conservation of Gramineous vegetation alongside the overall protection of Chinese marsh wetlands. Our findings can offer important evaluation results and guidance for the future addressing climate change and conservation and maintenance of the carbon sink capacity of marsh wetland vegetation in China.

A Simulation Optimization Approach for Wetland Conservation and Management in an Agricultural Basin

Decreasing water quantity and growth in water demand have increased the competition between satisfying societal water needs and protecting ecosystem requirements. Wetlands are some of the most productive ecosystems on Earth. They provide various services to people’s livelihoods, in addition to being suitable habitats for many plant and wildlife species. However, wetlands are under threat of loss and degradation due to anthropogenic activities, particularly the diversion of water for irrigation. The flow regime is usually considered the most crucial ecological factor and a key component of wetland management. So, determining the allocation of environmental requirements is a main factor for managing, restoring, and protecting wetlands, and it is crucial to reach a compromise for optimal water allocation between different sectors. For this purpose, in this research, a new approach is developed to achieve the optimal environmental flow of the wetland in an agricultural-dominated basin using a combination of remote sensing and the simulation optimization method. Waterbirds and vegetation are used as bioindicators of wetland ecosystems. First, using remote sensing data and analyses, we obtained the interrelation between the wetland water regime, vegetation, and waterbird characteristics using different time series of Landsat spectral indices. Then, by employing the long-term simulation optimization (WEAP-MOPSO) model, the optimal e-flow of the wetland is evaluated in such a way that the suitable ecological condition of the wetland is achieved and the wetland is able to provide its functions and services.

Modern pollen- and phytolith-vegetation relationships at a wetland in northeastern South Africa

In palaeoenvironmental reconstructions, few studies have focused on comparing the presence of pollen and phytoliths in surface sediments to the local vegetation. Notwithstanding inherent differential pollen and phytolith preservation, production, and dispersal, which affect their recovery and interpretation in sediment archives, there remains a need to explore modern pollen-vegetation, phytolith-vegetation and pollen-phytolith relationships to improve palaeoenvironmental reconstructions. We carried out palynological and phytolith analysis on six surface sediment samples linked to the botanical survey of five vegetation survey plots at Gustav Klingbiel Nature Reserve, Mpumalanga province in northeastern South Africa, to understand the relationships between the modern pollen and phytolith assemblages in the surface sediments and the contemporary vegetation of the study area. Correspondence Analysis (CA) was undertaken to examine the fingerprint of the local vegetation in the modern pollen-phytolith assemblage and evaluate whether the phytolith and pollen assemblages were tracking each other. CA illustrated that pollen and phytolith proxies are not tracking the same primary vegetation signals; modern pollen assemblages best represent the components of forest and wetland vegetation. In contrast, modern phytolith assemblages best represent grassland vegetation. Our study shows that differential pollen and phytolith preservation, production and dispersal significantly affect sediment records more than anticipated, thus combining multi-proxies (e.g., phytoliths, pollen) provides a more accurate basis for the interpretation of fossil spectra in palaeoenvironmental reconstructions.

Impacts of sea-access roads on wetland landscape dynamics in the Yellow River Delta front

The coevolution between oilfield development and deltaic wetlands is critical for ensuring environmental sustainability in mega-deltas. In the Yellow River Delta (YRD), the construction of offshore artificial islands and their sea-access roads (SARs) in delta fronts, providing accommodation for oilfields development of oilfields influences the evolution of adjacent wetland landscapes. This study utilized the threshold segmentation method based on MNDWI and the object-oriented random forest algorithm to extract the shoreline and classify typical wetland vegetation in the study area. It also analysed the impact of SAR on the landscape dynamics of coastal wetlands from 2004 to 2020. The results show that the SAR significantly affected the local sediment transport and erosion and accretion patterns in its adjacent coast, which has gone through accretion-domination, erosion, and continuous accretion stages, with significant accretion and erosion on the north and south sides of the SAR, respectively. From 2004 to 2020, 13.74 km2 of new-born wetland was formed, and the vegetation dynamics in the study area transformed from primary succession to human-disturbed succession. Spartina alterniflora (S. alterniflora) grew rapidly from 4.15 km2 to 18.04 km2 during 2010–2016, showed an imbalanced distribution on both sides of the SAR. This research can provide references for the sustainable coevolution of offshore oilfields and coastal environments.

Improved understanding of vegetation dynamics and wetland ecohydrology via monthly UAV‐based classification

AbstractVegetation classification is an essential prerequisite for understanding vegetation‐water relations at a range of spatial scales. However, in site‐specific applications, such classifications were mostly based on a single Unmanned Aerial Vehicle (UAV) flight, which can be challenging in grasslands and/or herbaceous‐dominated systems, as those communities are small in size and highly mixed. Here, we conducted monthly UAV flights for two years in a riparian wetland in Germany, with acquired imagery used for vegetation classification on a monthly basis under different strategies (with or without auxiliary information from other flights) to increase understanding in ecohydrology. The results show that multi‐flight‐based classification outperformed single‐flight‐based classification due to the higher classification accuracy. Moreover, improved sensitivity of temporal changes in community distribution highlights the benefits of multi‐flight‐based classification ‐ providing a more comprehensive picture of community evolution. From reference to the monthly community distribution, we argue that a combination of two or three flights in early‐ and late‐summer is enough to achieve comparable results to monthly flights, while mid‐summer would be a better timing in case only one flight is scheduled. With such detailed vegetation mapping, we further interpreted the complex spatio‐temporal heterogeneity in NDVI and explored the dominant areas and developmental progress of each community. Impacts from management (mowing events) were also evaluated based on the different responses between communities in two years. Finally, we explored how such vegetation mapping could help understand landscape ecohydrology, and found that the spatio‐temporal distribution of minimal soil moisture was related to NDVI peaks of local community, while grass distribution was explained by both topography and low moisture conditions. Such bi‐directional relationships proved that apart from contributing to an evidence base for wetland management, multi‐flight UAV vegetation mapping could also provide fundamental insights into the ecohydrology of wetlands.

Prey availability and foraging activity by tundra-nesting sea ducks: Strong preference for specific wetland types.

Wetlands in Arctic tundra support abundant breeding waterbirds. Wetland types differing in area, depth, vegetation, and invertebrate biomass density may vary in importance to birds, and in vulnerability to climate change. We studied availability and use of different wetland types by prelaying females of four species of sea ducks (Mergini) breeding on the Arctic Coastal Plain of Alaska, USA: long-tailed ducks (Clangula hyemalis) and Steller's (Polysticta stelleri), spectacled (Somateria fischeri), and king eiders (Somateria spectabilis). All four species preferred shallow vegetated wetlands versus deeper lakes. The ducks spent almost all their active time feeding, but their occurrence in different wetland types was not affected by the relative biomass density of known prey or of all invertebrates that we sampled combined. Sea ducks strongly preferred wetlands dominated by emergent and submersed Arctophila fulva over those dominated by the sedge Carex aquatilis, despite the much greater number, total area, and invertebrate biomass density of Carex wetlands. The hens depend heavily on local invertebrate prey for protein to produce eggs; thus, their preference for Arctophila wetlands likely reflects greater accessibility of prey in the near-surface canopy and detritus of Arctophila. Such shallow wetlands decreased substantially in number (-17%) and area (-30%) over 62 years before 2013 and appear highly susceptible to further declines with climate warming. Impacts on sea ducks of climate-driven changes in availability of important wetland types will depend on their adaptability in exploiting alternative wetlands.

Genus Lindernia All. (Linderniaceae) in Bosnia and Herzegovina

Field research conducted in the Peripanonian part of Bosnia and Herzegovina resulted in new and noteworthy records for the genus Lindernia. For the first time, alien L. dubia was recorded in Bosnia and Herzegovina, and new localities of threatened L. procumbens were also discovered. Individuals of both species grew in wetland vegetation of the class Isoëto-Nanojuncetea. The paper presents data on the morphology, ecology and distribution of species of the genus Lindernia. The alien status of L. dubia in Bosnia and Herzegovina is determined as the initial phase of naturalisation. The threatened status of L. procumbens in Bosnia and Herzegovina is assessed as endangered. These results contribute to a better knowledge of the flora and vegetation of ephemeral wetlands in Bosnia and Herzegovina, as well as the Balkans, which are still not sufficiently explored.

Trajectories of plant communities in Massachusetts, USA cranberry farms discontinued from agriculture

Retirement of cultivated croplands creates potential for ecosystem and wetland restoration, but vegetation and soil legacies of cropping influence the development of post-agriculture vegetation. In low-lying coastal watersheds of southeastern Massachusetts, cranberries (Vaccinium macrocarpon Aiton) are cultivated in commercial farm units that are diked, leveled and sanded beds created from historic wetlands. Current low cranberry prices and expanding cranberry production elsewhere now increase the likelihood of cranberry farmland retirement. We quantified the trajectories of plant species richness and cover, and plant characteristics (life form, native or non-native, wetland or non-wetland) in a chronosequence of cranberry farm beds that ranged from cultivated units to those retired from cropping and revegetated for 90 years with no post-cropping management. Species richness increased from active beds to 10–20 year-old beds and subsequently decreased. Post-retirement species richness was overwhelmingly dominated by native species. Shrub and tree richness and cover increased steadily over time. The richness of wetland, upland and facultative species all increased quickly after retirement and then declined in the oldest retired beds. The basal area and canopy cover of red maple (Acer rubrum) and pitch pine (Pinus rigida) increased over time. Vegetation followed a relatively consistent successional trajectory and the plant community after five to nine decades was predominantly forest and dominated by non-wetland plants. Encouragement of long-term persistence of greater diversity and cover of wetland plant species on retired cranberry farms will likely require active hydrological and soil modifications that decrease sand depth and raise water tables.

Effects of Multi-Growth Periods UAV Images on Classifying Karst Wetland Vegetation Communities Using Object-Based Optimization Stacking Algorithm

Combining machine learning algorithms with multi-temporal remote sensing data for fine classification of wetland vegetation has received wide attention from researchers. However, wetland vegetation has different physiological characteristics and phenological information in different growth periods, so it is worth exploring how to use different growth period characteristics to achieve fine classification of vegetation communities. To resolve these issues, we developed an ensemble learning model by stacking Random Forest (RF), CatBoost, and XGBoost algorithms for karst wetland vegetation community mapping and evaluated its classification performance using three growth periods of UAV images. We constructed six classification scenarios to quantitatively evaluate the effects of combining multi-growth periods UAV images on identifying vegetation communities in the Huixian Karst Wetland of International Importance. Finally, we clarified the influence and contribution of different feature bands on vegetation communities’ classification from local and global perspectives based on the SHAP (Shapley Additive explanations) method. The results indicated that (1) the overall accuracies of the four algorithms ranged from 82.03% to 93.37%, and the classification performance was Stacking > CatBoost > RF > XGBoost in order. (2) The Stacking algorithm significantly improved the classification results of vegetation communities, especially Huakolasa, Reed-Imperate, Linden-Camphora, and Cephalanthus tetrandrus-Paliurus ramosissimus. Stacking had better classification performance and generalization ability than the other three machine learning algorithms. (3) Our study confirmed that the combination of spring, summer, and autumn growth periods of UAV images produced the highest classification accuracy (OA, 93.37%). In three growth periods, summer-based UAVs achieved the highest classification accuracy (OA, 85.94%), followed by spring (OA, 85.32%) and autumn (OA, 84.47%) growth period images. (4) The interpretation of black-box stacking model outputs found that vegetation indexes and texture features provided more significant contributions to classifying karst wetland vegetation communities than the original spectral bands, geometry features, and position features. The vegetation indexes (COM and NGBDI) and texture features (Homogeneity and Standard Deviation) were very sensitive when distinguishing Bermudagrass, Bamboo, and Linden-Camphora. These research findings provide a scientific basis for the protection, restoration, and sustainable development of karst wetlands.

Wetland vegetation cover changes and its response to climate changes across Heilongjiang-Amur River Basin.

The Heilongjiang-Amur River Basin is one of the largest and most complex aquatic systems in Asia, comprising diverse wetland resources. The wetland vegetation in mid-high latitude areas has high natural value and is sensitive to climate changes. In this study, we investigated the wetland vegetation cover changes and associated responses to climate change in the Heilongjiang-Amur River Basin from 2000 to 2018 based on the growing season (May to September) climate and LAI data. Our results indicated that the wetland LAI increased at 0.014 m2·m-2/yr across Heilongjiang-Amur River Basin with the regional climate showed wetting and warming trends. On a regional scale, wetland vegetation in China and Russia had positive partial correlation with solar radiation and minimum air temperature, with precipitation showing a slight lag effect. In contrast, wetland vegetation in Mongolia had positive partial correlation with precipitation. These correlations were further investigated at different climate intervals. We found the precipitation is positively correlated with LAI in the warm regions while is negatively correlated with LAI in the wet regions, indicating an increase in precipitation is beneficial for the growth of wetland vegetation in heat sufficient areas, and when precipitation exceeds a certain threshold, it will hinder the growth of wetland vegetation. In the cold regions, we found solar radiation and minimum air temperature are positively correlated with LAI, suggesting SR and minimum air temperature instead of mean air temperature and maximum air temperature play more important roles in affecting the wetland vegetation growth in the heat limited areas. The LAI was found to be negatively correlated with maximum air temperature in the arid areas, indicating excessive temperature would inhibit the wetland vegetation growth when the water is limited. Our investigation can provide a scientific foundation for the trilateral region in wetland ecosystem protection and is beneficial for a more comprehensive understanding of the responses of wetlands in the middle and high latitudes to climate change.

Mapping the Late Miocene Pyrenean Forests of the La Cerdanya Basin, Spain

The Late Miocene palaeofloras of the La Cerdanya Basin represent a unique look into the Pyrenean Miocene forested areas of the Iberian Peninsula at a time when the European warm and humid climate was experiencing progressive cooling and aridification. Macrofossils (leaves, seeds, fruits and cones) and miospores from several outcrops revealed the composition and abundances of the different plant species present in the area during the Tortonian and early Messinian geological stages (ca. 11.1–5.7 Ma). These fossils were found in the sediment deposits of an ancient lake system situated in the southwestern part of the basin. Previous studies indicated the presence of highly diversified mixed mesophytic forests with broadleaved evergreen and deciduous trees and conifers. However, the spatial structure and distribution of these forest types remains unknown. In the present work, the biomization method was used to infer the different late Miocene vegetation types from the basin. The extent of these vegetation types was calculated using a methodology for mapping vegetation units from fossil and biome data. While previous attempts at mapping Miocene vegetation units had a broad geographical scale, the present work aimed to map the extent of the vegetation units at a small scale, recreating local and specific vegetation changes in an abrupt basin. Results showed similarly high scores between for four biome types, which represent the different types of vegetation that coexisted in the basin during the Tortonian and the early Messinian: warm-temperate evergreen broadleaf and mixed woodlands (WTEM biome), temperate deciduous forests (TEDE) and cool conifer forests (COMX and COEG). Their extent was depicted in two vegetation maps, which account for differences in palaeoaltitude and palaeoclimate. These forests occupied different vegetation belts, which shifted upwards and downwards with climatic variations and the progressive uplift of the Pyrenees during the late Miocene. Azonal riparian forests and wetland vegetation occupied the more humid areas in the centre of the basin. Nonetheless, dry conditions during the early Messinian and decrease in the lake area degraded the wetland environments, which were partially replaced by broadleaved evergreen mixed woodlands.

Aboveground biomass estimation of wetland vegetation at the species level using unoccupied aerial vehicle RGB imagery.

Wetland vegetation biomass is an essential indicator of wetland health, and its estimation has become an active area of research. Zizania latifolia (Z. latifolia) is the dominant species of emergent vegetation in Honghu Wetland, and monitoring its aboveground biomass (AGB) can provide a scientific basis for the protection and restoration of this and other wetlands along the Yangtze River. This study aimed to develop a method for the AGB estimation of Z. latifolia in Honghu Wetland using high-resolution RGB imagery acquired from an unoccupied aerial vehicle (UAV). The spatial distribution of Z. latifolia was first extracted through an object-based classification method using the field survey data and UAV RGB imagery. Linear, quadratic, exponential and back propagation neural network (BPNN) models were constructed based on 17 vegetation indices calculated from RGB images to invert the AGB. The results showed that: (1) The visible vegetation indices were significantly correlated with the AGB of Z. latifolia. The absolute value of the correlation coefficient between the AGB and CIVE was 0.87, followed by ExG (0.866) and COM2 (0.837). (2) Among the linear, quadratic, and exponential models, the quadric model based on CIVE had the highest inversion accuracy, with a validation R2 of 0.37, RMSE and MAE of 853.76 g/m2 and 671.28 g/m2, respectively. (3) The BPNN model constructed with eight factors correlated with the AGB had the best inversion effect, with a validation R2 of 0.68, RMSE and MAE of 732.88 g/m2 and 583.18 g/m2, respectively. ​Compared to the quadratic model constructed by CIVE, the BPNN model achieved better results, with a reduction of 120.88 g/m2 in RMSE and 88.10 g/m2 in MAE. This study indicates that using UAV-based RGB images and the BPNN model provides an effective and accurate technique for the AGB estimation of dominant wetland species, making it possible to efficiently and dynamically monitor wetland vegetation cost-effectively.

Coupling of soil methane emissions at different depths under typical coastal wetland vegetation types

As an important source of atmospheric methane, methane emissions from coastal wetlands are affected by many factors. However, the methane emission process and interrelated coupling mechanisms in coastal wetland soils of a variety of environments remain unclear owing to complex interactions between intensified anthropogenic activities and climate change in recent years. In this study, we investigated methane cycling processes and the response mechanisms of environmental and microbial factors in soils at different depths under four typical coastal wetland vegetation types of the Yellow River Delta, China, using laboratory culture and molecular biology techniques. Our results show that methane generation pathways differed among the different soil layers, and that the methane emission process has a special response to soil N compounds (NO3−, NH4+). We found that nitrogen can indirectly affect methane emission by impacting key physicochemical properties (pH, oxidation reduction potential, etc.) and some functional communities (mcrA, ANME-2d, sulfate-reducing bacteria (SRB), narG, nosZII). Methane production processes in shallow soils compete closely with sulfate reduction processes, while methane emissions facilitated in deeper soils due to denitrification processes. We believe that our results provide a reference for future research and wetland management practices that seek to mitigate the global greenhouse effect and climate change.

Assessing Typhoon Soulik-induced morphodynamics over the Mokpo coastal region in South Korea based on a geospatial approach

Abstract. The inner shelf and coastal region of the Yellow Sea along the Korean Peninsula are frequently impacted by typhoons. The Mokpo coastal region in South Korea was significantly affected by Typhoon Soulik in 2018, the deadliest typhoon strike to the southwestern coast since Typhoon Maemi in 2003. Typhoon Soulik overran the region, causing extensive damage to the coast, shoreline, vegetation, and coastal geomorphology. Therefore, it is important to investigate its impact on the coastal ecology, landform, erosion/accretion, suspended-sediment concentration (SSC), and associated coastal changes along the Mokpo region. In this study, the net shoreline movement (NSM), normalized difference vegetation index (NDVI), fractional vegetation coverage (FVC), coastal-landform change model, normalized difference suspended-sediment index (NDSSI), and SSC–reflectance relation have been used to analyze the coastal morphodynamics over the typhoon periods. We used pre- and post-typhoon Sentinel-2 MultiSpectral Instrument (MSI) images for mapping and monitoring the typhoon effect and recovery status of the Mokpo coast through short- and medium-term coastal-change analysis. The findings highlighted the significant impacts of typhoons on coastal dynamics, wetland vegetation, and sediment resuspension along the Mokpo coast. It has been observed that typhoon-induced SSC influences shoreline and coastal morphology. The outcome of this research may provide databases to manage coastal environments and a long-term plan to restore valuable coastal habitats. In addition, the findings may be useful for post-typhoon emergency response, coastal planners, and administrators involved in the long-term development of human life.

Microbial community structural and functional differentiation in capped thickened oil sands tailings planted with native boreal species.

The oil sands mining operations in Alberta have produced billions of m3 of tailings which must be reclaimed and integrated into various mine closure landforms, including terrestrial landforms. Microorganisms play a central role in nutrient cycling during the reclamation of disturbed landscapes, contributing to successful vegetation restoration and long-term sustainability. However, microbial community succession and response in reconstructed and revegetated tailings remain largely unexplored. This study aimed to monitor the structural and functional responses of microbial communities in tailings subjected to different capping and vegetation strategies over two growing seasons (GS). To achieve this, a column-based greenhouse experiment was conducted to investigate microbial communities in tailings that were capped with a layer (10 or 30 cm) of peat-mineral mix (PMM) and planted with either upland or wetland communities. DNA metabarcoding analysis of the bacterial 16S rRNA gene and fungal ITS2 region as well as shotgun metagenomics were used to asses the impact of treatments on microbial taxonomy and functions, respectively. Results showed that tailings microbial diversity and community composition changed considerably after two GS compared to baseline samples, while communities in the PMM capping layer were much more stable. Likewise, several microbial functions were significantly enriched in tailings after two GS. Interestingly, the impact of capping on bacterial communities in tailings varied depending on the plant community, leading to a higher number of differentially abundant taxa and to a decrease in Shannon diversity and evenness in the upland treatment but not in the wetland treatment. Moreover, while capping in the presence of wetland vegetation increased the energy-related metabolic functions (carbon, nitrogen, and sulfur), these functions were depleted by capping in the upland treatment. Fungi represented a small proportion of the microbial community in tailings, but the relative abundance of several taxa changed over time, while the capping treatments favored the growth of some beneficial taxa, notably the root endophyte Serendipita, in both upland and wetland columns. The results suggest that selecting the right combination of capping material and vegetation type may contribute to improve below-ground microbial processes and sustain plant growth in harsh environments such as oil sands tailings.