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Macrophytes are considered key components of aquatic ecosystems and they also provide multiple benefits for humans. In this review, I identified and exemplified 26 types of ecosystem services provided by macrophytes. The most important supporting services provided by these plants are related to nutrient cycling and provisioning of habitat, but macrophytes also participate in water cycling and gases production. The presence of macrophytes and their activity enhance water purification and disease control which are important regulating services. Provisioning services are provided in the form of food at the local and global scale (e.g., rice), fiber, biochemicals, natural medicine and ornamental resources. Cultural services are provided in the form of spiritual and religious artifacts and local knowledge systems of communities which depend on macrophytes for surviving. Other cultural services are associated with educational activities, art inspiration, esthetic values in aquatic gardens and ponds, uses for leisure, recreation and ecotourism. There is evidence that the efficiency of ecosystem functioning, the provision of ecosystem services and ecosystem stability is enhanced by macrophyte diversity. Because macrophyte communities provide important benefits for humans, their conservation and restoration, where necessary, are important for human well-being.

The drivers underlying the development of deep root systems, whether genetic or environmental, are poorly understood but evidence has accumulated that deep rooting could be a more widespread and important trait among plants than commonly anticipated from their share of root biomass. Even though a distinct classification of \"deep roots\" is missing to date, deep roots provide important functions for individual plants such as nutrient and water uptake but can also shape plant communities by hydraulic lift (HL). Subterranean fauna and microbial communities are highly influenced by resources provided in the deep rhizosphere and deep roots can influence soil pedogenesis and carbon storage.Despite recent technological advances, the study of deep roots and their rhizosphere remains inherently time-consuming, technically demanding and costly, which explains why deep roots have yet to be given the attention they deserve. While state-of-the-art technologies are promising for laboratory studies involving relatively small soil volumes, they remain of limited use for the in situ observation of deep roots. Thus, basic techniques such as destructive sampling or observations at transparent interfaces with the soil (e.g., root windows) which have been known and used for decades to observe roots near the soil surface, must be adapted to the specific requirements of deep root observation. In this review, we successively address major physical, biogeochemical and ecological functions of deep roots to emphasize the significance of deep roots and to illustrate the yet limited knowledge. In the second part we describe the main methodological options to observe and measure deep roots, providing researchers interested in the field of deep root/rhizosphere studies with a comprehensive overview. Addressed methodologies are: excavations, trenches and soil coring approaches, minirhizotrons (MR), access shafts, caves and mines, and indirect approaches such as tracer-based techniques.

Faced with huge environmental problems of ecosystem degradation, “Ecological Redline Policy (ERP)” in China is a new key national-level policy to manage different land use functions in accordance with development and environmental limits. As the water–land complex ecosystem with the largest freshwater lake, wetland natural reserves and ecological importance in China, Poyang Lake Region (PLR) is selected to quantify and map multiple ecosystem services, investigate the ecological function zoning as part of research on ecological zoning control and major ecological source areas to illustrate and address the implementation of this strategy based on the importance and vulnerability analysis of ecosystem services. According to ecological function zoning results, extremely important, highly important, medium important and important zones respectively account for 26.1%, 28.1%, 17.4% and 28.4% of the total area. With an area of 5422.2 km 2 , the extremely important zone is 1010.6 km 2 larger than the ERP. Moreover, 81.6% of the ERP is located in the extremely important zone. By discussing the implications and applications of ecological management, this study contributes to the ecological protection of Poyang Lake and provides a foundation for research on ecological function zoning at the regional scale.

As a critical component of the geographical divide between the northern and southern regions of China, the ecological stability of the Qinling region has profound implications for ecological balance within China and across East Asia. However, the degradation risk areas of the Qinling region remain unclear, and there are gaps in the delineation of key ecological protection areas. This study examines the improvement and decline in the Qinling region from 2000 to 2023 in terms of ecosystem patterns, quality, and functions. Moreover, key ecological function and degradation risk zones were identified, and future development paths were proposed for the Qinling region. The findings indicate that: (1) Urban area expansion was the most rapid, increasing by about 1800 km², with an average yearly growth rate of 2.43%. Ecosystem quality increased in 48.07% of the Qinling region. The degradation risk zones of ecosystem quality and function were primarily located in the Sanjiangyuan, the Minshan-Qinghai-Tibet Plateau, and the Loess Plateau in Shaanxi, Henan, and Gansu. The core areas for water and soil conservation only accounted for 17.92% and 10.47%, respectively, mainly distributed across the Qinling-Daba Mountains. Based on ecological patterns, quality, functions, and ecological protection and restoration projects, the Qinling region has been divided into two majority categories and 16 subcategories: 7 ecologically key functional areas and 9 degradation risk areas. This study offers recommendations for formulating ecological protection and restoration policies, thereby promoting the sustainable development of the region’s ecology and economy.

Microbial ecological functions are an emergent property of community composition. For some ecological functions, this link is strong enough that community composition can be used to estimate the quantity of an ecological function. Here, we apply random forest regression models to compare the predictive performance of community composition and environmental data for bacterial production (BP). Using data from two independent long-term ecological research sites—Palmer LTER in Antarctica and Station SPOT in California—we found that community composition was a strong predictor of BP. The top performing model achieved an R2 of 0.84 and RMSE of 20.2 pmol L−1 hr−1 on independent validation data, outperforming a model based solely on environmental data (R2 = 0.32, RMSE = 51.4 pmol L−1 hr−1). We then operationalized our top performing model, estimating BP for 346 Antarctic samples from 2015 to 2020 for which only community composition data were available. Our predictions resolved spatial trends in BP with significance in the Antarctic (P value = 1 × 10−4) and highlighted important taxa for BP across ocean basins. Our results demonstrate a strong link between microbial community composition and microbial ecosystem function and begin to leverage long-term datasets to construct models of BP based on microbial community composition.

Forest ecological function is one of the key indicators reflecting the quality of forest resources. The traditional weighting method to assess forest ecological function is based on a large amount of ground survey data; it is accurate but costly and time-consuming. This study utilized three machine learning algorithms to estimate forest ecological function levels based on multi-source data, including Sentinel-2 optical remote sensing images and digital elevation model (DEM) and forest resource planning and design survey data. The experimental results showed that Random Forest (RF) was the optimal model, with overall accuracy of 0.82, recall of 0.66, and F1 of 0.62, followed by CatBoost (overall accuracy = 0.82, recall = 0.62, F1 = 0.58) and LightGBM (overall accuracy = 0.76, recall = 0.61, F1 = 0.58). Except for the indicators from remote sensing images and DEM data, the five ground survey indicators of forest origin (QI_YUAN), tree age group (LING_ZU), forest category (LIN_ZHONG), dominant species (YOU_SHI_SZ), and tree age (NL) were used in the modeling and prediction. Compared to the traditional methods, the proposed algorithm has lower cost and stronger timeliness.

Sundarban is the world’s largest contiguous mangrove forest but is under threat from anthropogenic interventions. Plantations are the favored method to restore degraded mudflats. In this study, ecological functional soil indicators (available N, soil organic C, available P, salinity) and service (Blue carbon pool) of the iteroparous tree Avicennia marina (Forssk.) Vierh. (Acanthaceae family), plantation has been compared with a natural mudflat dominated by mangrove semelparous grass Proteresia coarctata (Roxb.) Tateoka (Poacease family). Both sites were under anthropogenic pressure. It was observed that the P. coarctata dominated natural site has gone through fluctuations in species population between 2012 and 2016 with higher Simpson’s dominance, and lower value of the Shannon–Weiner Index. A one-way Analysis of Variance (ANOVA), Principal Component Analysis (PCA), indicated that soil indicators have significantly varied and linearly increased across the years at the A. marina plantation site. Blue carbon pool increased by four times (10 cm soil depth) at the plantation site since 2012 compared to only one time in the mangrove grass dominated community within the study period (2012–2016). This study concludes that plantation with iteroparous mangrove species can improve ecosystem function and services at degraded mudflats dominated by semelparous grass and aid in achieving the Sustainable Development Goal 13 (Climate action).

Ecological function zoning is an essential means of scientific management of ecosystems. According to the characteristics of ecological function zoning, implementing zoning control is conducive to the governance and protection of the ecological environment and the maintenance of ecological sustainability. This study was conducted with the Nansi Lake Basin as the cross-section for 2018. The Integrated Valuation of Ecosystem Services and Trade-offs model was adopted to assess and measure five ecosystem services, including water yield, crop production, soil conservation, carbon storage and carbon sequestration, and habitat quality. The Self-Organizing Feature Maps neural network was applied to obtain the ecosystem service bundles, and then, the ecological function zones were divided. The results indicated that the overall spatial pattern of ecosystem services in the study zone showed a decreasing schema from east to west; There was a trade-off between supply services and support services and a synergy between supply services and regulatory services; according to the bundling results, the Nansi Lake Basin was divided into four ecological functional zones: the eastern ecological surplus zone, the central crop supply zone, the western ecological balance zone, and the lake habitat protection zone. The results showed that (1) the spatial distribution of various ecosystem services in the Nansi Lake Basin showed spatial heterogeneity and specific regional laws, showing a decreasing pattern from the east to the west as a whole, especially in soil conservation, carbon sequestration, and habitat quality. (2) According to the supply and spatial distribution of each ecosystem service, the Nansi Lake Basin was divided into four ecological functional zones: the eastern ecological surplus zone, the central crop supply zone, the western ecological balance zone, and the lake habitat protection zone. (3) For zone I, provisioning services and regulation services were in synergy. For zone II and zone III, the provisioning service had a trade-off relationship with the regulation service and the supporting service. For zone IV, supporting services were trade-offs not only with provisioning services but also with regulating services. In general, the trade-offs between ecosystem service in the Nansi Lake Basin were stronger than the synergies, and the overall benefits of ecosystem services were smaller. Relying on the perspective of the ecosystem service bundles, at the county level, this study provided an analysis of the trade-offs and synergies among ecosystem services in the Nansi Lake Basin, which helped formulate the management plan for the corresponding region and provided the appropriate recommendations for regional habitat conservation and restoration. Graphical Abstract

Revealing the dependence and uniqueness of microbial communities on microplastics could help us better understand the assembly of the microplastic microbial community in river ecosystems. In this study, we investigated the composition and ecological functions of the bacterial community on microplastics from the Three Gorges Reservoir area compared with those in water, sediment, and soil at species-level via full-length 16S rRNA gene sequencing. The results showed that the full-length 16S rRNA sequencing provided more detail and accurate taxa resolution of the bacterial community in microplastics (100%), water (99.90%), sediment (99.95%), and soil (100%). Betaproteobacteriales were the most abundant bacteria in microplastics (14.1%), water (32.3%), sediments (27.2%), and soil (21.0%). Unexpectedly, oligotrophic SAR11 clade was the third abundant bacteria (8.51%) and dominated the ecological functions of the bacterial community in water, but it was less observed on microplastics, with a relative abundance of 2.73×10-5. However, four opportunistic pathogens identified at the species level were selectively enriched on microplastics. Stenotrophomonas maltophilia was the main opportunistic pathogen on microplastics (0.29%). Sediment rather than soil and water may be contributed mostly to pathogens on microplastics. Moreover, some bacteria species with the biodegradation function of microplastics were enriched on microplastics, such as bacteria Rhodobacter sp., and endemic bacteria Luteimonas sp. The distinct bacteria composition on microplastics enhanced several ecological functions, such as xenobiotics biodegradation, which allows screening the bacteria with the biodegradation function of microplastics through long-term exposure.

The imbalance in the “production–living–ecology” function (PLEF) has become a major issue for global cities due to the rapid advancement of urbanization and industrialization worldwide. The realization of PLEF coupling and coordination is crucial for a region’s sustainable development. Existing research has defined the concept of PLEF from the perspective of land function and measured its coupling coordination level using relevant models. However, there is still room for improvement in the indicator system, research methods, and other aspects. This work builds a PLEF coupling coordination evaluation-index system based on the perspective of human habitat using multi-source data in order to examine the spatial differences in PLEF coupling coordination level and the influencing factors in the Yellow River Basin (YRB). Using the modified coupling coordination model, the Moran index, spatial Markov chain model, and geographically weighted random forest model were introduced to analyze its spatial and temporal differentiation and influencing factors. The results found that (a) the level of PLEF coupling coordination in the YRB from 2010 to 2022 has been improving, and the number of severely imbalanced cities has been reduced from 23 to 15, but the level of downstream cities’ coupling coordination is significantly higher than that of upstream cities. The probability of cities maintaining their own level is greater than 50%, and there is basically no cross-level transfer. (b) The Moran index of the PLEF coupling coordination level has risen from 0.137 to 0.229, which shows a significant positive clustering phenomenon and is continually strengthening. The intercity polarization effect is being continually enhanced as seen in the LISA clustering diagram. (c) There is significant heterogeneity between the influencing factors in time and space. In terms of importance level, the series is per capita disposable income (0.416) > nighttime lighting index (0.370) > local general public budget expenditure (0.332) > number of beds per 1000 people (0.191) > NO2 content in the air (0.110). This study systematically investigates the dynamic evolution of the coupled coordination level of PLEF in the YRB and its influencing mechanism, which is of great practical use.