Environmental pressures resulting from intensified human activities severely threaten biodiversity and ecosystem structure, with freshwater ecosystems being particularly affected (Yi et al., 2014; Newbold et al., 2015; Zhao et al., 2019; Wang J. et al., 2021; Moi et al., 2022; Polazzo et al., 2022). One major threat is eutrophication (Rosset et al., 2014), which disrupts the natural balance of nutrients crucial for the stability of aquatic ecosystems (Huisman et al., 2018). Excessive nutrient inputs can trigger algal bloom outbreaks, reduce planktonic biodiversity (Wang et al., 2022), alter community structure (McQuatters-Gollop et al., 2009; Bužančić et al., 2016; Wang H. et al., 2021), reduce ecological niche differentiation, and intensify interspecific competition, thereby affecting ecosystem functions (Amorim and Moura, 2021). These blooms, often dominated by species such as Cyanobacteria, Chlorophyta, and Bacillariophyta, increase water turbidity and pH, resulting in anoxia and organism mortality (Visser et al., 2016). Furthermore, the intensity of the bloom also increases phytoplankton nutrient utilization but blocks the energy transfer from primary producers to zooplankton (Grey et al., 2000), which is not conducive to the acquisition of nutrients by zooplankton and negatively affects ecosystem functioning (Tian et al., 2017).

The relationship between biodiversity and ecosystem functioning (BEF) has long been a central theme in ecology. Considerable evidence suggests that biodiversity is critical for maintaining ecosystem functioning, and a loss of biodiversity reduces the capacity of ecosystems to provide multiple services (Cardinale et al., 2012; Naeem et al., 2012; Hagan et al., 2021; Mitchell et al., 2024), i.e., biodiversity positively influences ecosystem functioning (Cardinale et al., 2011; Tilman et al., 2014; Oliver et al., 2015; Soliveres et al., 2016; Slade et al., 2017). However, this relationship may also exhibit a non-linear pattern influenced by interspecific interactions and environmental heterogeneity (Cardinale et al., 2011; Thompson et al., 2017). Most of the early research on BEF relationships has focused on terrestrial ecosystems (Soliveres et al., 2016; Schuldt et al., 2018), particularly terrestrial plants, while aquatic ecosystems have received less attention (Daam et al., 2019). Globally, the biodiversity of freshwater systems is declining faster than that of terrestrial and marine systems (Vaughn, 2010; Zhang et al., 2019), and its loss will seriously threaten ecosystem stability and productivity.

The BEF relationship of phytoplankton was first proposed by Ptacnik et al. (2008), who used resource use efficiency (RUE) to indicate ecosystem functioning. RUE quantifies ecosystem functioning by measuring the ratio of resources acquired by organisms to the amount of biomass they transform and serves as a better indicator of the level of resource use by organisms (Hodapp et al., 2019). As one of the most important primary producers in river ecosystems (Varol, 2019), phytoplankton communities reflect their fundamental and critical role in material cycling, pollutant degradation, water self-purification, and ecosystem stability (Yang et al., 2022). Due to their tiny unicellular size and extreme sensitivity to environmental changes (Feio et al., 2009), phytoplankton are susceptible to both abiotic factors, such as nutrient salinity and water temperature, as well as biotic factors, such as grazing and interspecific competition. Consequently, they are considered ideal aquatic ecological indicator organisms (Wojciechowski et al., 2017). In the context of China’s rapid urbanization and industrialization, changes in phytoplankton diversity significantly reflect the response and adaptation of river ecosystems to environmental stress. In particular, increased nutrients from industrial wastewater and urban runoff cause eutrophication of water bodies, affecting phytoplankton community structure and function, reducing water quality, and threatening the overall aquatic biodiversity (Mustapha et al., 2013; Barakat et al., 2016). Therefore, monitoring and analyzing changes in phytoplankton diversity not only assesses the health of ecosystems but also provides a critical scientific basis for developing effective environmental management strategies.

While numerous studies have confirmed the overall positive correlation between BEF, most have focused solely on taxonomic diversity metrics such as species richness (Duffy et al., 2017; Amorim and Moura, 2021). In contrast, evenness metrics, which reflect the uniformity of species distribution within communities, and functional diversity metrics, which describe the functional traits of species, have received limited attention. Recent studies have concluded that the relationship between phytoplankton evenness and ecosystem functioning (measured by resource use efficiency) generally shows a negative effect in highly disturbed ecosystems, i.e., dominant species with superior resource utilization capabilities outcompete others (Filstrup et al., 2019; Otero et al., 2020). Furthermore, evenness is considered a sensitive indicator of changes in biodiversity, often reflecting the impacts of anthropogenic activities or environmental changes better than species richness and eliciting rapid responses in ecosystem functioning (Chapin III et al., 2000; Wilsey and Potvin, 2000; Filstrup et al., 2014; Hodapp et al., 2015). In contrast, species richness ignores the effects of differences in relative abundance among species on interspecific interactions and overemphasizes the importance of rare species (Zhang et al., 2012; Filstrup et al., 2014), which does not adequately represent the diversity associated with ecosystem functioning. In particular, changes in evenness often occur with little or no change in species richness, i.e., species tend to decline in number before going extinct, and evenness can capture such species declines (Wilsey and Potvin, 2000; Hillebrand et al., 2008). Consequently, the effects of evenness on ecosystem functioning warrant further in-depth investigation (Wilsey and Potvin, 2000).

Field and experimental studies have demonstrated that functional diversity is a highly effective predictor of ecosystem functioning, making it a critical aspect of contemporary biodiversity research (Griffin et al., 2009; Abonyi et al., 2017). In this context, the functional diversity indices proposed by Villéger et al. (2008), which comprehensively assess functional traits such as growth forms, habitat preferences, and resource use strategies, have received widespread recognition in the international scientific community (Eisenhauer et al., 2019). Compared to traditional research focused on taxonomic diversity, this species trait-based method of analysis more accurately reflects the actual functional roles of species within ecosystems. This approach highlights the functional differences among species and addresses the problem of traditional biodiversity indices that treat the contributions of each species equally (Cadotte et al., 2011), making it a promising tool for biological monitoring and ecosystem management. In particular, in the study of phytoplankton, by analyzing the relationship between their functional diversity and ecosystem functions, we can better understand the critical contributions of these microorganisms to primary productivity and nutrient cycling in water bodies. This will further elucidate the complex response mechanisms of aquatic ecosystems to environmental change, providing a solid foundation for the formulation of scientific ecological conservation and management strategies.

Currently, studies of aquatic biodiversity tend to focus on biodiversity effects within individual trophic levels, with less attention paid to vertical biodiversity effects across multiple trophic levels (Duffy et al., 2007). This approach may overlook potential trophic connectivity effects during urbanization, resulting in a lack of understanding of the role of individual taxa in food webs and their impact on ecosystem functioning (Eisenhauer et al., 2013; Li et al., 2021; Moi et al., 2021). Organisms drive ecosystem functioning at multiple trophic levels, and considering trophic complexity is critical to understanding the role of biodiversity at different trophic levels (Li et al., 2020). Primary producers can have different effects on ecosystem functioning within and across trophic levels (Filstrup et al., 2014). Results that consider only a single trophic group are likely to underestimate the importance of biodiversity and fail to effectively reflect the complexity of river and lake ecosystems (Weijters et al., 2009; Soliveres et al., 2016; Li et al., 2020). Therefore, it is necessary to integrate data from multiple trophic levels and horizontally explore the ecosystem functions of communities at different trophic levels to improve our understanding of the ecological health of rivers.

The Xiaoqing River, situated in northern China, is a highly urbanized area where intensive human activities have led to eutrophication of the water and the outbreaks of algal blooms. This makes it an ideal ecosystem to empirically test the relationship between biodiversity and river ecosystem functioning (Wang and Yin, 2023). We used phytoplankton taxonomic diversity (evenness) and functional diversity (functional divergence) as indicators of biodiversity, and resource use efficiency of phytoplankton (RUEpp) and zooplankton (RUEzp) communities as measures of ecosystem functioning. As one of the most important primary producers in river ecosystems, the diversity change of phytoplankton can reflect the response of rivers to environmental stress, while RUE can comprehensively reflect the level of resource utilization by biomes, and the correlation analysis between the two can help to elucidate the intrinsic mechanism underlying the biodiversity-ecosystem functioning relationship. We tested the following research hypotheses: (1) Phytoplankton evenness would be negatively correlated with RUEpp but positively correlated with RUEzp. (2) Functional divergence (FDiv) of the phytoplankton community would be negatively correlated with RUEpp but positively correlated with RUEzp. (3) The increase of dominant species caused by algal blooms would lead to an increase in RUEpp and a decrease in RUEzp.

Although most BEF-related studies have focused on single sampling and single taxa, our study investigated the BEF relationship across trophic levels under different seasons. Our results demonstrated that the increase in the relative abundance of dominant species caused by Bacillariophyta blooms significantly impacted the RUEpp and RUEzp. Meanwhile, phytoplankton evenness negatively affected RUEpp but positively affected RUEzp. Similar correlation trends were also reflected in the functional divergence index. We evaluated the roles of environmental factors and biodiversity in explaining variations in RUE, among which evenness emerged as the most significant contributor.

The results of the multiple linear regression modeling showed that evenness had a significant effect in both RUEpp and RUEzp models and was the main factor explaining the variation. This is in agreement with Hodapp et al. (2015) who found that evenness was a key driver of phytoplankton productivity and RUE compared to environmental factors such as temperature and light. In communities with lower evenness, a few dominant species have a competitive advantage and are able to use resources more efficiently due to their higher physiological or chemical adaptations (Hodapp et al., 2015). In contrast, higher phytoplankton evenness may mean that zooplankton have a more diverse food source, which not only provides richer nutrients, but also improves zooplankton growth and reproductive efficiency (Wang et al., 2024).

In the RUEpp model, NO₃ ⁻-N and COD_Mn had positive effects on resource use efficiency, while total phosphorus (TP), evenness, functional divergence and functional evenness all had negative effects. High phosphorus levels in eutrophic waters can make nitrate a limiting factor, and as nitrate levels increase, resource use efficiency can be improved by supporting more phytoplankton growth (He et al., 2021). Meanwhile, higher COD_Mn values indicate the presence of more biodegradable substances in the water body, which may release additional nutrients (e.g., nitrogen and phosphorus) during degradation that can be used by phytoplankton to further improve resource use efficiency (Reinl et al., 2022). The possible reason for the negative correlation of functional divergence is that under eutrophication conditions, functional convergence of algae reduces ecological niche occupancy and ecosystem resources cannot be fully utilized (Zhang et al., 2019; Dunck et al., 2019). In contrast, in the RUEzp model, NO₃ ⁻-N had a significant negative effect on RUEzp, except for phytoplankton evenness, which had a significant positive effect. We hypothesize that the possible reason is that elevated nitrate-nitrogen concentrations usually contribute to the occurrence of algal blooms, in which some harmful algal species bloom and may not be consumed by zooplankton. In addition, algal blooms can cause rapid changes in water quality (e.g., oxygen depletion and toxin release) that stress zooplankton populations and reduce their growth and reproductive success (He et al., 2021).

Principal coordinate analysis revealed significant seasonal variations in the composition of phytoplankton and zooplankton communities. This finding indicates that the structure of riverine organisms is largely influenced by seasonal differences, such as temperature and flow. The results of the one-way ANOVA showed that RUEpp and RUEzp also exhibited seasonal differences. Among the variables, RUEpp exhibited a significantly higher value in spring than in other seasons. This indicates that phytoplankton growth activity was higher in the spring, probably due to increased light and temperature, which significantly increased resource use efficiency. Furthermore, the higher RUEzp observed in summer may be attributed to the availability of phytoplankton as a food source, which in turn facilitates the growth and reproduction of zooplankton. For the study of algal bloom conditions in the Xiaoqing River, Bacillariophyta dominated the phytoplankton community during the sampling period and formed high-density algal blooms (density >5 × 10⁶ cells/L) several times. The strongest bloom was found in spring, which could reach up to class Ⅳ, followed by class Ⅲ in summer, and the weakest degree of bloom was found in autumn and winter. Compared with Chlorophyta and other higher aquatic plants, Bacillariophyta have a more efficient photosynthetic rate, faster exponential growth rate, and more robust salinity tolerance, which allows them to fully utilize water resources. In contrast, zooplankton feeding strategies favor algae such as Chlorophyta, which are more palatable, and avoid Bacillariophyta (Vincent and Bowler, 2020). Possible mechanisms include the release of substances by Bacillariophyta that can inhibit zooplankton predation (Malej and Harris, 1993), their hard siliceous shells, and the production of toxic aldehydes, which are also important predation avoidance mechanisms (Miralto et al., 1999). Furthermore, studies of eutrophic lakes have found that when blooms occur, RUEpp often increases while RUEzp decreases (Filstrup et al., 2014; Gao et al., 2022). If bloom algae with higher RUE and competitive advantages are well adapted to environmental conditions, they may produce greater RUEpp; simultaneously, zooplankton may reduce predation on these dominant species with lower nutrient quality (Hassett et al., 1997), thereby decreasing RUEzp.

The positive correlation between phytoplankton species richness and RUE has been widely demonstrated in the assessment of ecosystem functioning (Ptacnik et al., 2008; Striebel et al., 2009). However, evenness tends to have a better effect on ecosystem functioning than species richness, because it captures changes in the abundance of each species rather than just the loss and gain of species (Filstrup et al., 2019). Meanwhile, under dramatic environmental change, evenness can better reflect the rapid changes in the external environment, and higher evenness means that the abundance of species in the community tends to be more balanced and the whole tends to be more stable (Otero et al., 2020). Most current studies have focused more on the relationship between primary producer diversity and RUE and less on the RUE of herbivores and even higher trophic levels. Therefore, a comprehensive understanding of the effects of biodiversity requires the integration of both horizontal and vertical dimensions of biodiversity, especially when specific taxa with unique traits dominate primary producers (Duffy et al., 2007). Our results consistently showed that phytoplankton evenness is significantly correlated with RUEpp and RUEzp across seasons (although the strength of the correlation may be differ) and exhibits opposite trends, which is consistent with the findings of Filstrup et al. (2014) in eutrophic lakes. These findings can also be explained by ecological stoichiometry, i.e., when RUEpp is high, RUEzp decreases due to reduced trophic quality (Hassett et al., 1997). Notably, in contrast to other seasons, we found that the relationship between phytoplankton evenness and RUE was not significant in the autumn, speculating that this finding may be related to the large amount of tree litter input to the river from the riparian zone. As an essential source of carbon, nitrogen, and phosphorus, leaf litter can significantly increase phytoplankton biomass and chlorophyll content and promote photosynthesis (Zhang et al., 2018). However, large amounts of leaf litter can also form a cover on the water surface that reduces light transmittance, diminishes the amount of light available to phytoplankton in the water column, and reduces photosynthetic efficiency (Domingues et al., 2014). Some light-loving taxa, such as Microcystis and Scenedesmus, are reduced, while shade-tolerant species, such as Cryptomonas and Euglena, are benefitted (Reynolds et al., 2002; Padisák et al., 2009). Furthermore, leaf litter accumulation may lead to localized stagnation of the water column, affecting mobility, nutrient transport, and light distribution, disrupting vertical migration of phytoplankton, and ultimately limiting their distribution and growth (Li et al., 2013).

Individual ecology-based classification of phytoplankton functional groups can more accurately characterize habitats, reveal dynamic relationships between phytoplankton functional groups and the aquatic environment, and predict changes in ecosystem function (Abrantes et al., 2006; Borics et al., 2021). Our results are consistent with the hypothesis that FDiv has some explanatory power in predicting ecosystem functioning. Its response pattern is consistent with taxonomic diversity (evenness), i.e., FDiv has a negative correlation effect on RUEpp and a positive correlation on RUEzp, indicating that FDiv well reflects the distribution of species in the functional trait space and their effects on RUE. The higher the FDiv of phytoplankton, the weaker the competition for resources among species, the more fully utilized the ecological niche space, and the higher the primary productivity generated, so that RUEzp exhibited an upward trend (Ptacnik et al., 2010). Several studies have demonstrated that functional diversity can be a better predictor of ecosystem properties because adding or subtracting species with similar functions has little effect on ecosystem functioning (Carmona et al., 2016; Abonyi et al., 2017; Gross et al., 2017; Ye et al., 2019). Due to the heterogeneity of ecosystem habitats and resources, communities with similar functions cannot achieve maximum resource utilization. In contrast, communities with greater functional differences can improve RUE and enhance ecosystem functioning (Cadotte et al., 2011). Therefore, the functional characterization approach is considered a more promising tool in stream ecosystem biomonitoring and management (Abonyi et al., 2017; Breton et al., 2017; Leruste et al., 2018). The present study demonstrated that both taxonomic and functional diversity were significantly correlated with ecosystem functioning. However, the model fit for taxonomic diversity was slightly better than that for functional diversity. This observation contradicts the results of previous studies, and this discrepancy may stem from the fact that our ability to quantify traits remains limited, and the trait profiles covered need to adequately capture slight differences in species at specific ecological niches. For instance, differences in light requirements, which may be a key trait in determining species’ efficient use of heterogeneous resources within the environment, may need to be better captured, thus reducing the percentage of variance explained by functional diversity in RUE. Furthermore, trait-mediated effects due to interactions among taxa must be considered, which may limit the applicability of currently used traits (Klais et al., 2017).

Our study supports a bottom-up ecosystem regulatory mechanism in which resource use drives competition among species at the primary producer level, with more competitive populations gaining a resource advantage and dominating the community, i.e., selection effects. At the herbivore level, resource heterogeneity and differences in food selectivity drive changes in trophic transfer efficiency (Filstrup et al., 2019), and such interactions across trophic levels form a more complex and rich BEF relationship. In this study, only two groups of organisms were involved, and we should consider expanding the scope of the study based on field observations to investigate the BEF mechanism of organisms at higher trophic levels. Considering the advantages of studying BEF relationships based on functional traits, our results improve the quantitative description of phytoplankton functional traits in subsequent studies. This study contributes to a more comprehensive identification of various ecologically relevant traits for a more comprehensive assessment of river ecosystem functioning (Abonyi et al., 2017; Kremer et al., 2017). Furthermore, the findings of this study will provide theoretical guidance for the protection and management of eutrophic waters. Specifically, we propose the implementation of measures to control nutrient inputs, maintain the structural stability of phytoplankton communities, and strengthen ecosystem monitoring and assessment. These measures aim to slow down the eutrophication process, maintain the functional balance and diversity of primary producer communities, and thus improve the resource use efficiency and ecological service function of the whole ecosystem. These protection strategies should be further refined and a comprehensive eutrophication water management plan should be formulated and implemented with the ultimate goal of curbing eutrophication and realizing the improvement and restoration of the aquatic ecosystem.

In summary, this study has established the patterns and mechanisms between biodiversity and ecosystem function in natural phytoplankton communities under eutrophic conditions. The results verified our preliminary hypothesis that both phytoplankton evenness and FDiv significantly affect RUE and have opposite patterns at the different trophic levels. Due to the increase of dominant species caused by algal blooms, the abundance of each species tends to be unbalanced, the occupation of the trophic ecological niche decreases, and it becomes difficult to effectively transfer and utilize resources to the upper trophic level. When the dominant harmful algal blooms declined, a relative equilibrium state was reached among the species, the whole ecological niche was gradually utilized more comprehensively, and the ecosystem function was enhanced. Therefore, in order to effectively manage and protect the health of water bodies, we suggest controlling the input of nutrients and slowing down the eutrophication process; taking measures to restore and maintain an appropriate phytoplankton community structure and avoiding the absolute dominance of a single species; and strengthening the monitoring and assessment of the structural and functional indicators of phytoplankton communities and formulating corresponding protection management and strategies. This study provides important insights into the study of ecosystem functioning across trophic scales. It supports the view that increased ecological niche utilization can improve resource use efficiency, providing an important reference for subsequent studies of BEF mechanisms at higher trophic levels.