IntroductionUnderstanding the elevational patterns of intrinsic water-use efficiency (iWUE) and their drivers is crucial for predicting plant adaptation and ecosystem responses to climate change. However, how iWUE in different photosynthetic pathways (C3 vs C4) varies with elevation, which is interactively shaped by climate and nutrient constraints remains unclear.MethodsHere, we integrated stable carbon (δ13C) and oxygen (δ18O) isotopes with plant-soil stoichiometry across a grassland elevation transect to interpret these mechanisms.ResultsOur results reveal a fundamental divergence in the response of iWUE to elevation: iWUE increased significantly in C₃ grasses but decreased slightly in C4 grasses. Using a machine learning approach, we identified vapor pressure deficit (VPD) and leaf stoichiometry (C:P and N:P ratios) as key drivers to shape the altitudinal patterns of iWUE. However, these factors exhibited opposing effects: VPD was negatively correlated with iWUE in C3 species but positively correlated in C4 species.DiscussionThese contrasting patterns reflect distinct eco-physiological strategies. C3 plants improve iWUE under the cooler, potentially nutrient-limited in high-elevation conditions through conservative resource-use traits. In contrast, the CO2-concentrating mechanism of C4 plants appears constrained at lower temperatures, limiting their iWUE. Our findings demonstrate that iWUE patterns are not simply climate-driven but emerge from pathway-specific interactions between climatic gradients and nutrient availabilities. This study provides a mechanistic framework for forecasting shifts in grassland community structure and carbon-water fluxes under future climate change.

The precise identification of pollution sources constitutes a cornerstone for effective water environment management in mountainous watersheds. This study employed principal component analysis-absolute principal component scores-multiple linear regression (PCA-APCS-MLR) receptor modeling to analyze monthly water quality indicators across the Longxi River Basin. Results revealed comparable water quality between the main stream and its tributaries, with no statistically significant differences identified. Water quality exhibited a distinct spatial pattern, with superior conditions in the upstream and downstream segments compared to the middle reaches. Water quality parameters exhibited significant seasonal variations. During the wet period, the degradation of water quality was primarily driven by diffuse agricultural sources, contributing 42.9%, followed by watershed background levels and surface runoff. In the dry season, rural domestic wastewater (39.3%) was the leading pollution source. For Permanganate index (CODMn) exceedance, basin background and agricultural non-point sources in the wet season were the main contributors (46.8% and 44.7%, respectively). For ammonium nitrogen (NH3-N), wet season agricultural non-point sources (44.4%) and dry season rural domestic pollution (71.8%) were key contributors. Agricultural non-point sources were the dominant pollution source for total nitrogen (TN) in the wet season (84.2%). Effective water quality improvement in the Longxi River Basin hinges on targeted strategies-to mitigate diffuse agricultural sources through optimized fertilization, and to enhance the collection and treatment of rural domestic sewage. This study not only enhances the understanding of pollution source distribution and quantification in mountainous watersheds, but also serves as a vital reference for formulating targeted water environment management strategies.

During August to September 2024, the Sichuan Basin in Southwest China experienced a record-breaking compound heatwave and drought event (CHDE)—the most severe since 1980. This event was characterized by unprecedented high temperatures and extreme drought. Using the latest daily observations from 121 meteorological stations, this study investigated the intensity, duration, and spatial extent of this CHDE. The regional mean daily temperature reached 29.17°C, a positive anomaly of 4.73°C relative to the climatological mean. The event featured 45 heatwave days, about 10 times higher than the climatological mean, and over 99% of stations recorded their highest temperatures since 1980. Concurrently, the averaged SPEI (standardized precipitation evapotranspiration index) declined to −1.74, indicating the most severe drought since 1980. The key driver of this CHDE was the strongest anomalous descent over the Sichuan Basin, which was closely linked to the unprecedented intensification and westward extension of the western Pacific subtropical high since 1980. This anomalous descent over this concave basin induced warming temperatures and decreasing precipitation, providing favorable conditions for the extreme heatwave and drought conditions of the record-breaking CHDE. The study highlights an escalating and severe threat of CHDEs in the Sichuan Basin, which increases the challenges for disaster prevention and mitigation.

Quantitative and integrative assessment of ecological benefits is essential for evaluating conservation effectiveness and supporting management decisions in national parks. However, existing approaches often struggle to capture complex interactions among ecological conditions, socioeconomic factors, and governance contexts. In this study, a Bayesian network-based indicator framework was developed to assess ecological benefits and their socio-economic drivers in national parks. Fractional vegetation cover (FVC), dynamic habitat index (DHI), and carbon sequestration (CS) were selected as core ecological indicators and while incorporating social, economic, and perception-related variables as influencing factors. Using Nanshan National Park, China, as a case study, spatiotemporal changes in ecological benefits from 2016 to 2024 were quantified, and probabilistic relationships among key influencing factors were explored through sensitivity and scenario analyses. The research findings were as follows: (1) the core protection zone of Nanshan National Park was found to demonstrate markedly superior performance, relative to the general controlled zone, in the maintenance and enhancement of ecological benefits. (2) an evaluation index system that integrated natural, social, and economic factors-Together with residents' perceptions and participation-Was developed in this study. The analysis revealed that education level, the proportion of non-agricultural income, willingness to participate in national park development, and actual participation levels were all positively correlated with ecological benefits (p < 0.05). In contrast, the Gini coefficient, livelihood types, and household annual income exhibited strongly negative correlations with ecological benefits (p < 0.01). (3) multi-scenario simulation based on Bayesian network analysis indicated that a spatial mismatch existed between ecological benefits and socioeconomic development levels. This study provides a robust indicator-based assessment framework for evaluating conservation performance and supports evidence-based zoning management in national parks. The proposed approach is transferable to other protected areas and offers practical implications for sustainable environmental governance

ABSTRACT Grassland ecosystems provide substantial social and cultural value but are vulnerable to climate change and human activities. Large‐scale evidence on how climate and disturbance jointly affect above‐ground biomass (AGB), species richness, and their relationship remains limited. We conducted a meta‐analysis by compiling and standardizing plot‐level observations from 226 studies of Chinese grasslands. The final database contained 1192 records from 378 sites surveyed between 1982 and 2019, with matched climatic variables (mean annual temperature, annual precipitation, and radiation) and disturbance categories (grazing, mowing, and fencing). Random‐forest models identified disturbance, precipitation, and radiation as the strongest predictors of AGB, whereas temperature was the strongest predictor of species richness. AGB was higher under mowing and fencing than under grazing and declined with increasing grazing intensity; it also increased with local precipitation. Species richness was highest under mowing, followed by fencing and grazing, and was greatest under wetter conditions and moderate temperatures. Across the national dataset, AGB and species richness were linearly and positively related overall, although several plant formations showed a unimodal pattern. Heavy grazing weakened the linear relationship, whereas moderate grazing strengthened it. Our study provides a scientific basis for the management of grassland ecosystems under the influence of climate change and human activities.

Biodiversity is undergoing continuous and rapid loss under ongoing climate change, but where those costeffective protected lands (CPLs) are theoretically best located under different future climatic scenarios remains poorly understood, which is particularly important for timely biodiversity conservation strategies. Here, we developed a comprehensive framework based on the "30 x 30" target to identify CPLs for terrestrial vertebrates focusing on future climate refugia in China. Under the SSP245 and SSP585 scenarios, we identified a total of 31.19 % and 30.55 % of China's terrestrial area as proposed CPLs by 2030, which significantly enhance the representativeness for safeguarding terrestrial vertebrates, particularly through the high and medium-level proposed CPLs. However, only 20.26 % and 20.90 % of these CPLs are covered by existing protected areas (PAs), respectively. Our findings suggest optimization strategies for PAs and other effective area-based conservation measures (OECMs) to better conserve biodiversity in response to the sustained climate change.

Global ecosystems, particularly in biodiversity-rich tropical rainforests, are increasingly under pressure from human activities. As socio-economic development continues and populations steadily grow, the effective planning of areas surrounding national parks has become a global challenge. This study, based on remote sensing data and utilizing landscape ecology tools, such as ArcGIS 10.8, GeoDa 1.20, and Fragstats 4.2, combines spatial statistical methods, trend analysis, and the Hurst index to conduct a long-term analysis and forecast future trends in vegetation ecological quality indicators (VEQI) and landscape pattern changes within and around the Hainan Tropical Rainforest National Park. VEQI changes across various buffer zones were also assessed. Our results show that both arable and built-up land increased, especially from 2002 to 2022. Arable land decreased from 5566.8 km2 to 4796.8 km2, then increased to 5904.6 km2; built-up land expanded from 163.97 km2 to 314.59 km2, reflecting urbanization. Spatiotemporal analysis revealed that 42.54% of the study area experienced significant VEQI changes, with a 24.05% increase (mainly in the northwest) and an 18.49% decrease (mainly in the southeast). The VEQI improvements were consistent across all buffer zones, with the most significant growth in the 7.5 km zone. Landscape indices indicated high fragmentation in coastal areas, while inland areas remained stable, reflecting the tension between conservation and urbanization. These findings provide a theoretical basis for future ecological development and buffer zone policies in the park.

Effective conservation of core habitats for terrestrial vertebrates is critical to their survival, while the rapid increase in human pressure has become a major driver of habitat degradation, loss, and fragmentation. Currently, challenges remain in the quantitative identification of species’ priority core habitats (PCHs) and the dynamic assessment of their responses to human pressure. To address this, we developed an integrated framework for assessing the impact of human pressure on PCHs of rare and endangered species. Taking the Three Parallel Rivers Region of China as a case study, we identified PCHs of 48 rare and endangered terrestrial vertebrates based on habitat suitability maps, and applied a random forest model to reveal the driving factors and mechanisms underlying human footprint trends within PCHs. The results showed that 36.75 % of PCHs exhibited a significant decreasing trend in human footprint from 2001 to 2020 (p < 0.05, slope < 0), while 29.42 % of the areas showed a significant increasing trend (p < 0.05, slope > 0). The slope of human footprint change inside protected areas (median = 0.018) within PCHs was significantly higher than outside protected areas (median = -0.020) (p < 0.05), suggesting that protected areas have not effectively mitigated the rising human pressure. Nighttime light intensity was identified as the most important driver of human footprint changes within PCHs, whereas management intensity contributed the least explanatory power. This study provides a scientific basis and technical support for the identification and dynamic management of species’ PCHs under human pressure, offering valuable insights for optimizing biodiversity conservation strategies.

Understanding the spatial association network structure and carbon balance zoning of land-use carbon emissions (LUCEs) is essential for guiding regional environmental management. This study constructs a LUCE spatial association network for Hubei Province using a modified gravity model to uncover the spatial linkages in carbon emissions. Carbon balance zones are delineated by integrating LUCE network characteristics with economic and ecological indicators. To further examine the network dynamics, link prediction algorithms are employed to anticipate potential emission connections, while quadratic assignment procedure (QAP) regression analyzes how intercity differences in socioeconomic, ecological, and land-use attributes influence LUCE connectivity. The results reveal a pronounced core–periphery structure, with potential carbon spillover pathways extending toward both eastern and western cities. Based on the carbon balance analysis, six functional zones are identified, each aligned with targeted collaborative mitigation strategies. The QAP results indicate that intercity differences in innovation capacity, industrial structure, and economic development are positively associated with the formation of LUCE spatial networks, whereas disparities in urbanization level, government expenditure, and construction land use are negatively associated with LUCE connectivity. This study provides a differentiated governance framework to address the dual challenges of carbon emissions and land-use transformation in agro-urban regions.

Protected areas (PAs) play a critical role in conserving natural ecosystems. Understanding ecosystem changes within PAs and their driving factors is essential for evaluating their effectiveness and optimizing management strategies. However, large-scale studies often fail to account for variability among individual PAs, thereby limiting their applicability. Here, we utilized continuous land cover data from 2011 to 2020 to analyze changes in the areas of four terrestrial ecosystems-forest, grassland, wetland, and desert-within China's National Nature Reserves (NNRs). Random forest regression models were employed to identify the drivers of ecosystem changes at different levels: all NNRs, NNRs within different climatic zones, and individual NNR. The results revealed that from 2011 to 2020, the areas of grasslands, wetlands, and deserts across all NNRs significantly increased (P < 0.05), while forest areas remained stable (P > 0.05). At the individual NNR level, 63.16 % NNRs exhibited stable desert ecosystem areas, whereas 40.80 %, 62.00 %, and 38.71 % of NNRs experienced net declines in forest, grassland, and wetland areas, respectively. Overall, topographic factors (elevation and slope) were the primary drivers of ecosystem changes across all NNRs, while cropland area changes played a dominant role in driving ecosystem changes at the individual NNR level. Additionally, ecosystem changes in the humid and semi-humid eastern regions were mainly driven by cropland, whereas those in the arid and semi-arid northwestern regions were mainly driven by elevation and climate factors. These findings highlight the importance developing region-specific conservation strategies for NNRs, particularly by strengthening cropland management to balance ecological protection and sustainable agricultural development. This study can provide a scientific basis and technical reference for the management and conservation strategies of PAs at global or national scales.

Anthropogenic activities and climate change have significantly altered runoff generation in the upper Han River basin, posing a challenge to the water supply sustainability for the Middle Route of the South-to-North Water Diversion Project. Land use/cover changes (LUCCs) affect hydrological processes by modifying evapotranspiration, infiltration and soil moisture content. Based on hydro-meteorological data from 1961 to 2023 and LUCC data series from 1985 to 2023, this study aimed to identify the temporal trend in hydro-meteorological variables, to quantify the impacts of underlying land surface and climate factors at different time scales and to clarify the effects of LUCCs and basin greening on the runoff generation process. The results showed that (1) inflow runoff declined at a rate of −1.71 mm/year from 1961 to 2023, with a marked shift around 1985, while potential evapotranspiration increased at a rate of 2.06 mm/year within the same time frame. (2) Annual climate factors accounted for 61.01% of the runoff reduction, while underlying land surface contributed 38.99%. Effective precipitation was the dominant climatic factor during the flood season, whereas potential evapotranspiration had a greater influence during the dry season. (3) From 1985 to 2023, the LUCC changed significantly, mainly manifested by the increasing forest area and decreasing crop land area. The NDVI also showed an upward trend over the years; the actual evapotranspiration increased by 1.163 billion m3 due to the LUCC. This study addresses the climate-driven and human-induced hydrological changes in the Danjiangkou Reservoir and provides an important reference for water resource management.

Small and micro wetlands exhibit enduring ecological dynamics that critically inform urban development planning and biodiversity conservation strategies. Focusing on Wuxi City (a representative area under high-intensity anthropogenic pressure in China’s Yangtze River Delta urban agglomeration), we employ the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. By integrating multi-temporal remote sensing imagery (1980–2020) with field surveys, we quantitatively assess spatiotemporal variations in habitat quality, with particular emphasis on their enhancement effects. The key findings were as follows. (1) The overall habitat quality in Wuxi City declined significantly during the period of 1980–2020 based on 30 m resolution land-use/land cover (LULC) data. The area of “good” habitat increased marginally by 1.02%, while “fair” and “excellent” habitats decreased by 19.4% and 1.64%, respectively. Conversely, the area of “poor” habitat rose markedly by 28.71%. (2) Small and micro wetlands were identified using Support Vector Machine (SVM) classification on Landsat imagery, showing a transformation from abundance to scarcity and then back to abundance. Before 2000, these areas grew rapidly, reaching a peak of 4.04 × 104 hm2 in 2000. Afterward, there was a sharp decline from 2000 to 2005, followed by stabilization. (3) A comparison of two land-use scenarios revealed that incorporating small and micro wetlands significantly expanded high-quality habitat areas and reduced low-quality areas. The most notable expansion occurred in 2000, with high-quality habitat areas increasing by 12.30%. This study demonstrates that directly using existing land-use data for habitat quality simulation overlooks the influence of small and micro wetlands. It is recommended that habitat quality simulations include extracted small and micro wetland data to ensure accurate assessments.

The widespread abandonment of croplands poses a severe threat to China's food security. However, the existing knowledge regarding the potential for recultivating abandoned croplands is limited. Previous studies have generally overestimated this potential due to inadequate assessments of their suitability for recultivation. In the present study, an optimized machine learning approach was introduced to assess, for the first time, the suitability of abandoned croplands for recultivation in China. In 2022, the total abandoned croplands in China covered 31.2 million hectares, of which 82.54 % was deemed suitable for recultivation. Recultivating abandoned croplands in China could substantially enhance food security, potentially yielding around 162 million tons annually. Moreover, crop switching can further increase the yield rate by up to 24.95 % or energy supply by up to 43.14 %. The present study offers valuable insights to policymakers in determining cropping strategies, establishing strategic grain reserves, and managing international food trade.

Mammal suitable habitats are increasingly threatened by human disturbance, yet quantifying the performance of protected areas (PAs) in conserving these habitats remains challenging. Additionally, research on the relationship between the representativeness of PAs and their effectiveness in conserving mammal suitable habitats remains limited. To address this gap, we predicted the potential suitable habitats (PSHs) of terrestrial mammals across China using species distribution models. We then developed a rapid assessment method to evaluate the effectiveness of PAs in mitigating human footprints (HFP) within the mammal PSHs. Locally Weighted Scatterplot Smoothing (Lowess) was applied to identify the optimal proportion of mammal PSHs represented by PAs that maximizes conservation effectiveness. Our analysis revealed that 99.6 % of mammal PSHs experienced a significant increase in HFP from 2011 to 2020, with narrow-range species showing the most rapid growth. Despite these pressures, PAs effectively mitigated HFP within the PSHs of 92 % of species. For mammal species with varying PSH sizes, the highest effectiveness in PA representativeness was observed at 29 % for species with PSH < 100,000 km2, 19 % for species with 100,000 km2 ≤ PSH ≤ 250,000 km2, and 17 % for species with PSH > 250,000 km2. Our findings emphasize the need to enhance the representativeness of PAs for mammal suitable habitats, particularly for narrow-range species. This study will provide scientific guidance for the conservation of suitable habitats for terrestrial mammals in China and globally, as well as for the strategic planning of PAs.

National parks play a crucial role in promoting the achievement of the Sustainable Development Goals (SDGs) and have become one of the key topics of global concern and discussion. However, it is still unclear whether national park development can effectively enhance the level of sustainable development in local communities related to social and economic dimensions of SDGs. In this study, we constructed an evaluation system based on the SDG assessment indicator framework, to evaluate the sustainable development level of local communities within Hunan Nanshan National Park (NSNP), China. We assessed the development level of various SDG indicators through field visits and structured surveys of local communities inside and around HNNP. We used the entropy method to determine the weight of each indicator and calculated the integrated development index of different communities within and around NSNP. The results indicate the following: (1) The integrated development index of communities within NSNP is generally lower than that of the surrounding communities, but it scores higher in the dimensions of SDG1 and SDG10. (2) The integrated development index within NSNP shows the highest in communities within original natural park, but the lowest in communities within original nature reserve. (3) The structured questionnaire surveys reveal that the primary cause of income decline of residents within NSNP is the restriction on land-use and resource exploitation, while ecological compensation and employment opportunities related to national park management can help improve local livelihoods and thereby promote development level of local communities. This study provides a technical framework for assessing the sustainable development of local communities in Chinese national parks and supports regional planning. It also offers a scientific basis for balancing national park conservation with local community development.

(1) Background: Ecological restoration is crucial to improve ecological functions and optimize its security patterns. The Zhangbei of Zhangjiakou, a typical agro-pastoral transition zone, was studied as an example to conduct ecological restoration suitability evaluation in northern China. (2) Methods: suitability of ecological restoration in Zhangbei was assessed by both single factor analysis and comprehensive factor analysis, which were based on the data of regional water resources, ecosystem service function, and ecosystem sensitivity obtained from a high-precision environmental survey. (3) Results and conclusions: The results show that in Zhangbei County, areas classified as important and extremely important for ecosystem service functions account for 50.32%, ecologically sensitive and highly sensitive areas represent 5.95%, and regions designated as important and extremely important for ecological protection cover 52.70%. Furthermore, ecological restoration of Zhangbei was divided into four ecological restoration zones: agro-forest–wetland ecological restoration and soil erosion control zone, agro-forest–wetland ecological restoration and water conservation zone, forest–grassland soil erosion and soil–water conservation zone, and mountain forest conservation and biodiversity maintenance zone. The study can be a scientific case study for local ecosystem restoration and conservation. In the future, this study will further explore multi-source data fusion, the establishment of a multi-scale evaluation system, and the trade-off analysis between conservation and development.

Protected areas (PAs) are critical for safeguarding biodiversity and maintaining ecosystem services. Assessing the conservation effectiveness of PAs in preserving forest ecosystem is of considerable significance in promoting management and policy recommendations of PAs. However, studies on the integrated effectiveness of PAs in enhancing forest coverage, improving forest ecosystem services, and mitigating forest fragmentation remains relatively limited. In this study, we chose three indicators include fraction vegetation coverage (FVC), forest fragmentation index (FFI), and ecosystem services (ESs, including water retention, soil conservation, carbon sequestration, and habitat quality) to investigate the conservation effectiveness of PAs in preserving forest ecosystems within the Three Parallel Rivers Region (TPRR), China. The results indicated that during the past two decades (2001–2020), 48.81%, 52.11%, and 59.82% of the areas within PAs showed positive or stable trends in FVC, FFI, and ESs, respectively. The integrated assessment revealed mixed results: 33.03% of the area within PAs achieved high conservation effectiveness, while 60.73% showed medium effectiveness. Overall, while 93.76% of the area showed a positive trend in at least one of the three indicators, this highlights the complex trade-offs in conservation outcomes. Moreover, the influencing factors of integrated conservation effectiveness were analyzed using the random forest model, revealing that natural factors and the size of protected areas had the greatest impact. To further enhance overall conservation effectiveness, more stringent management measures should be implemented at the local level nature reserves in this region. This multi-indicator assessment reveals the complexity of forest ecosystems across different regions, which facilitates the incorporation of additional indicators and provides guidance for a more comprehensive evaluation of the conservation effectiveness of diverse natural ecosystems in future research.

Establishing protected areas (PAs) is a major measure of biodiversity conservation, and various methods have been explored to assess PAs’ effectiveness. However, those methods mainly compared the relative changes in land cover between treated samples inside the PAs and their matched samples outside the PAs, which would produce misjudgments, especially in some climax communities with a relatively steady state. Thus, in this study, we constructed an integrated framework through a series of assessments according to the state, trend, and relative change of each PA to explore the conservation effectiveness of PAs in the Three Parallel Rivers Region in China from 2000 to 2020. Here, “state” refers to the difference among samples from within and outside the PA, assessed through yearly sample mean comparison. “Trend” means linear regression of mean forest area of each PA throughout the assessment period. “Relative change” means the difference in the mean value of the slope of forest changes between the treated samples inside each PA and their matched control samples outside of PAs. The entire forest area within all PAs in the Three Parallel Rivers Region showed a significant increasing trend from 2000 to 2020 (R2 = 0.919, P<0.05). Among all the PAs, twelve (86%) had a positive effect on protecting the forest ecosystem, and two had a nonsignificant effect. Among the factors affecting the state and relative change in PAs’ forests, the annual total precipitation was the most important, followed by distance to the nearest road. Moreover, the management-level variable was an essential factor in the state of PAs’ forest ecosystems, which indicated that national PAs (nature reserves and natural parks) were in a better state than local (provincial- and county-level) nature reserves. Overall, the conservation effectiveness of forests in PAs was assessed at a regional scale in the Three Parallel Rivers Region, implying that our framework would be additional useful in regions with high biodiversity and steady ecosystems. This framework better avoids underestimating conservation effectiveness assessment tasks than traditional methods do. Thus, we posit that this framework is suitable for future global or country-level assessments.

Submerged macrophytes play an important role in maintaining the structure and function of shallow lakes. Under eutrophication, the community of submerged macrophytes shows a shift of growth forms from rosette-like to canopy-forming macrophytes and a further decline due to the increasing shading from epiphyton and phytoplankton. However, at the early phase of eutrophication, the population of submerged macrophytes may increase due to increased nutrient availability, and the responses of submerged macrophytes to eutrophication are expected to be growth-form dependent. To explore the direct effects of nutrient enrichment on the submerged macrophytes of both growth forms, we constructed a mesocosm study with rosette-like macrophytes (Vallisneria denseserrulata and V. spinulosa) and canopy-forming macrophytes (Potamogeton lucens and P. wrightii) under two nutrient levels but maintained low phytoplankton and epiphyton biomass. Nutrient enrichment had a positive effect on the plant size for both macrophyte growth forms under low algal shading. Based on the 21 plant traits determined, the same growth form responded similarly to the increase in nutrient availability with few exceptions. Interestingly, increased nutrient levels induced different allocation strategies between canopy-forming (especially for ‘magnopotamid’) and rosette-like submerged macrophytes. The increased nutrients promoted leaf growth in rosette-like macrophytes and ramet production in canopy-forming macrophytes. These results provide a case study on the direct effects of increased nutrient levels on submerged macrophytes during the early phase of eutrophication in shallow lakes.