# Aquatic ecosystem indices, linking ecosystem health to human health risks

Fanny de Carvalho, Adeline Loyau, Michelle Kelly-Irving, Dirk S Schmeller

► To cite this version:

Fanny de Carvalho, Adeline Loyau, Michelle Kelly-Irving, Dirk S Schmeller. Aquatic ecosystem indices, linking ecosystem health to human health risks. Biodiversity and Conservation, 2025, 34 (3), pp.723-767. 10.1007/s10531-025-03010-3. hal-05353960

HAL Id: hal-05353960

https://hal.science/hal-05353960v1

Submitted on 13 Nov 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# Aquatic ecosystem indices, linking ecosystem health to human health risks

Fanny G. De Carvalho<fnref n="1" /> · Adeline Loyau<fnref n="1" /> · Michelle Kelly-Irving<fnref n="2" /> · Dirk S. Schmeller<fnref n="1" />

Received: 19 July 2024 / Revised: 18 December 2024 / Accepted: 3 January 2025 /

Published online: 16 January 2025

© The Author(s) 2025, corrected publication 2025

## Abstract

The good functioning of aquatic ecosystems is essential for providing diverse ecosystem services that benefit humans. The degradation of ecosystem health due to continuous stressors, such as climate change or water pollution, is leading to an increase in human health risks and well-being. Indicators have been developed to determine human health risks from recreational and drinking water. Still, a general application to aquatic ecosystems linking ecosystem health and human health risks has not been done. We here reviewed indicators and indices applied to assess the health of aquatic ecosystems and their links with human health risk and well-being. We evaluated the extent to which indicators can witness a risk to human health and well-being. A total of 245 articles were reviewed, consisting of 185 on the assessment of aquatic ecosystem health and 60 linking ecosystem health and human health or well-being. Out of the 65 indices described, we evaluated the use of several parameters and their relevance to evaluate human health risks, including physico-chemical parameters, bioindicators, contaminants, and pathogens, therefore covering the various sources of ecosystem disturbance. Based on our assessment, we propose a set of indicators that would allow for the inclusion of risks for human health and well-being in the assessment of ecosystem health (e.g. coliforms, algae, pH, nutrients, chemical compounds, and ecosystem services). Measuring these parameters should be incorporated into future studies to allow an understanding of the linkage of ecosystem and human health.

**Keywords** Aquatic freshwater ecosystems · Health assessment · Health indicators · Human health

Communicated by Michael Joy.

<figure><img src="image_2.png" /></figure>

<footnote>Fanny G. De Carvalho
fanny.decarvalho@toulouse-inp.fr</footnote>

<footnote n="1">¹ Centre de Recherche sur la Biodiversité et l'Environnement (CRBE, UMR 5300), CNRS, IRD, Toulouse INP, Université de Toulouse, Toulouse, France</footnote>

<footnote n="2">² CERPOP UMR1295, Inserm-Université de Toulouse, Toulouse, France</footnote>
Introduction

Humanity is an integral part of the global life-support system. This system provides many
different resources and services, named ecosystem services, without which the existence
of any life would be impossible. Ecosystem services represent all outputs or processes pro-
vided by an ecosystem that directly or indirectly benefit humans, most prominently clean
air and drinking water (Millenium Ecosystem Assessment 2005). They are classified into
four categories: provisioning, regulating, supporting, and cultural ecosystem services.
These ecosystem services depend on the good functioning of ecosystems, which in turn
is the result of the rich interactions between species, as well as between species and their
environments. Simply said, ecosystem functioning and the resulting ecosystem services
depend primarily on biodiversity (Hooper et al. 2005; Le Provost et al. 2023). The differ-
ent health concepts EcoHealth, OneHealth, and Planetary Health (Lerner and Berg 2017),
all suggest that biodiversity loss will lead to a degradation in ecosystem services which in
turn will lead to increased health risks for humans, livestock, and wildlife (Schmeller et al.
2020).

Pressures on ecosystems from stressors such as chemical pollution, habitat destruction, climate change, and introduced harmful species have constantly increased over the past decades. The series of Scientists’ Warnings all outline the consequences of those pressures on the global life-support system (Cavicchioli et al. 2019; Ripple et al. 2017; 2021; Schmeller et al. 2022). Some studies reported on the effects of water pollution on human health and well-being. One such study, assessing the health of people living close to a polluted river in Bangladesh, demonstrated that water pollution incurs skin disease, diarrhea, gastric problems, and respiratory illness (Halder and Islam 2015). As the last decades have seen ever-increasing water contamination and pollution, even in remote areas (Machate et al. 2022, 2023), the degradation of water quality and aquatic ecosystems has become a threat to human society. These degradations can have severe impacts on ecosystems, including lower resilience to dealing with pressures and stresses, as well as increased loss of biodiversity. Above a certain threshold, ecosystem functioning and the resulting ecosystem services will lose the capacity to support human society (Reader et al. 2023). The ecosystem then has entered an unhealthy state with numerous direct and indirect impacts on the human nervous, respiratory, digestive, and other systems of the human body, leading to the degradation of human well-being and health (Cairns 1995). These impacts also have the potential to reduce not only the physical but also the mental health of humans (Fig. 1). The manifold health consequences, particularly disruption of social interactions and cohesion, emergence of infectious diseases and disease vectors, as well as intoxication events, have been widely studied to understand the evolution of the quality of life in human societies (e.g. Martinez-Juarez et al. 2015; Summers et al. 2012; Sandifer et al. 2015; Karr 2011).

Despite the rich literature on the consequences of degraded or unhealthy ecosystems for human health, there is no consensus on a final definition of ecosystem health. Definitions of a healthy ecosystem range from a sustainable ecosystem, modified and impacted by human intervention, that uses its vital functions to prosper and is resilient to stress (Costanza and Mageau 1999) to definitions revolving around human health analogies, or ecological integrity (Lackey 2001; Scrimgeour and Wicklum 1996). The notion of ecosystem health is often used as a synonym of ecological integrity, despite their obvious differences (Karr and Chu 1995; Karr et al. 2020). Ecological integrity was described as the ability of an ecosystem to support and maintain diverse, balanced, integrated, and adaptive biological
<figure><img src="image_3.png" /><figcaption>**Fig. 1** Impacts of the aquatic ecosystem on human health and well-being. Direct and indirect consequences of the health of aquatic ecosystems found in the included literature were compiled. The indicators that can be used to assess the risk of direct impacts have been listed</figcaption></figure>

communities and ecological processes in a stable state, combining physical, chemical, and biological integrity (Karr and Chu 1995). Ecological integrity is considered to be measurable by comparing composition, structure, and function to natural or historic ranges of variation (Bridgewater et al. 2014). However, in the Anthropocene, it appears to be difficult to define a natural state or a historical reference state of an ecosystem due to the dominance of human activities and the high degree of environmental alteration (Hansen et al. 2021). The concept of ecosystem health does evaluate the condition of ecosystems, using diverse indicators of habitats, species, and resources, as well as indicators of function, allowing to assess if an ecosystem is able to retain natural functions and the capacity to deliver ecosystem services (Burkhard et al. 2008). The ecosystem health concept, in a decisive difference to ecological integrity, integrates environmental conditions with anthropogenic impacts to inform about the sustainable use and management of natural resources. Understanding both concepts, ecological integrity and ecosystem health, ask for a large amount of data on abiotic and biotic variables, which are often only available on local scales, but not at larger scales, an issue also addressed with the concepts of Essential Biodiversity Variables (Haase et al. 2018; Schmeller et al. 2018) or Essential Climate Variables (Thornton et al. 2021). Those data needs are further exacerbated by system variability and system complexity (Schmeller et al. 2018). For a better understanding of the state and trends of ecosystems, independent if we want to look at ecological integrity or ecosystem health, a common measurement approach is urgently needed. As drinking water is a particularly precious natural resource, we here focus on aquatic ecosystems.

Water is a key element and an important resource for all living organisms, as it supplies adequate and rich environments for wildlife (Karr 2011). A plethora of parameters can be analyzed in water that allows the assessment of the status of the aquatic ecosystem by looking at species abundance, chemical composition, and water body condition (Burkhard et al. 2008). As ecosystems are spatially heterogeneous and vary over time, indicators or indices of ecosystem health need to take this variability into account. Modifications of aquatic
ecosystems will create stress and pressure on their biodiversity and ecosystem health, reducing at best the benefits of ecosystem services and at worst render them disservices (Grizzetti et al. 2016; Pongsiri and Roman 2007). These changes may affect economic activities, hydrological structures, and human well-being. As human well-being is composed of four principal elements: physiological and safety needs (which are the primary needs), economic needs including social requirements, environmental needs, and subjective happiness (Summers et al. 2012). The impacts of aquatic ecosystem degradation on humans differ depending on social and economic groups and their dependence on aquatic ecosystems (Horwitz and Finlayson 2011). Therefore, the link between green/blue environments and human well-being is not always obvious and depends on contextual determinants such as socio-economic, demographic, and climatic factors (Martinez-Juarez et al. 2015), a notion that is corroborated by the World Bank, recommending that the assessment of human well-being should consider the quality of life, security, health, freedom, and social connections (Narayan et al. 2000). As there is an interdependence between economics, human health, and ecosystem health (Boischio et al. 2009; Webb et al. 2010; Jax and Heink 2016), linking ecosystem health and human health and well-being is a complex task.

In many parts of the world, human health issues are visible, such as increasing allergies, anxiety, depression, obesity, and immune system disorders, impacting physical and mental health (Sandifer et al. 2015). Cohort studies have outlined a range of socio-economic factors contributing to degrading human health (Stringhini et al. 2017). However, only a few studies also take into consideration ecosystem health and environmental variations, particularly in aquatic ecosystems. Two threats to human health are particularly related to aquatic ecosystems, vector-borne diseases where vectors are closely linked to water bodies, and waterborne pathogens. In 2019, about 1.4 million people died worldwide due to the lack of safe drinking water, sanitation, and waterborne pathogens (Wolf et al. 2023). The number of people falling ill every year due to waterborne pathogens accounts for several million (Wolf et al. 2023). Waterborne pathogens can be present in various types of water due to contaminated fecal matter from the discharge of contaminated wastewater and partly from problems with water treatment (Gibson 2014). In addition, a large diversity of parasites can be found in aquatic ecosystems, even in ecosystems considered healthy (Adlard et al. 2015). These parasites are sensitive to climate change such as changes in temperature, which can influence their life cycle, transmission, geographical distribution, biodiversity, or else their interaction with hosts.

By weakening aquatic ecosystems, humans are creating more suitable environments for new pathogens, particularly for non-specific host pathogens (Boesch and Paul 2001; Newman and Reantaso 2010). These pathogens create a risk for aquatic wildlife and humans (Johnson and Paul 2011), leading to multiple ways of spreading infectious diseases. Climate change and modifications of the ecosystem increase the number of infectious diseases and the spread of aquatic invasive species, modifying parasite load, and the transmission rate and pathways of other aquatic pathogens (Conn 2014). Johnson showed in an experiment that eutrophication of an aquatic environment increases the density of infected snail hosts and stimulates per-snail production of the parasite *Ribeiroia ondatra* (Johnson et al. 2007). The *Anopheles* fly (*Anopheles gambiae*), the vector responsible for Malaria spread, has seen its niche and number increase due to climate change, deforestation, and modifications of human behavior, leading to a change in its behavior (Grieco et al. 2006). Habitat deterioration alters the communities, decreases predators, and increases invasive species, reducing competition and increasing the competent host population (Sandifer et al. 2015). Aquatic ecosystems provide fundamental ecosystem services, such as purification of water, regulation of eutrophication by recycling nutrients, support of food storage, and
balancing energies. They can further play a role in the prevention of disease outbreaks, control processes, and species, and avoid natural disasters by regulating climatic conditions. The establishment of indices capable of determining the presence of waterborne pathogens, and preventing their emergence is important for preventing health risks for ecosystems, wildlife, and humans (Stewart et al. 2008).

Aquatic ecosystems have also beneficial effects on human well-being, concerning social life, and physical and psychological well-being (Fig. 1). In healthy ecosystems, contact with nature may have positive impacts on physical and psychological health and can contribute to improving physical health, moods, and behavior (Sandifer et al. 2015; Moore et al. 2007). Bergou et al. (2022) showed that contact with canals and rivers is associated with mental well-being. Additional cultural services such as the attractiveness of sceneries, recreational activities, spiritual and moral utilities, and cultural and scientific interests are also beneficial (Limburg 2009). The reduction of recreational activities, social and economic isolation, psychological decline, loss of culture and environmental knowledge, and environmental injustice can therefore impact human mental health if cultural services of aquatic ecosystems are reduced or absent (Sandifer et al. 2015; Moore et al. 2007; Bergou et al. 2022). Aquatic ecosystems are the focus of the European Water Framework Directive (WFD, Directive 2000/60/EC), the main law for water protection in Europe. This directive aims to ensure that there is enough water of sufficiently good quality to support wildlife as well as human needs. The aim is to provide an integrated approach to water management, focusing on the integrity of aquatic ecosystems by regulating pollution and setting regulatory standards in regard to good chemical and ecological status. The different national water agencies are therefore monitoring aquatic environments and producing a large amount of data, allowing to assess ecosystem status. The Water Framework Directive, directed by the European Commission, has helped to advance a common assessment methodology, but, apart from drinking water and recreational water specific indices were not developed to assess the linkage of human health and ecosystem health.

While interest in assessing ecosystem health is growing, more work is needed to discern a robust set of aquatic ecosystem health indicators. Therefore, in our literature review, we provide an overview of currently available and applied biological, chemical, and physical indicators and indices that provide information on aquatic ecosystem health. We specifically aim to provide an overview of which ecosystem health indicators might be closely linked to human health risks and human well-being. To improve knowledge on the links between aquatic ecosystem health and human well-being, we evaluated the applicability across environments, ease of use, and identification of the source of disruption, in currently used aquatic ecosystem indicators and indices. We also provide an overview of available studies linking aquatic ecosystem health to human well-being. Based on our analysis, we recommend a set of aquatic ecosystem health indicators and indices that should be prioritized to improve knowledge on the link between ecosystem and human health. We here address an important gap in the literature by summarizing the relationship between indicators of aquatic ecosystem health and human health risk.

## Materials and methods

Firstly, we identified articles dealing with the assessment of aquatic ecosystem health and articles about the link between ecosystem health and human health and well-being. We aimed to gather the main aquatic ecosystem indices used to analyze their link with human
health risks. The articles were searched for in Web of Science, Science Direct, Springer, PubMed, and Google Scholar databases. Articles cited by selected articles were also analyzed and included if they were dealing with aquatic ecosystem health assessment. To find articles about aquatic ecosystem health several keywords and combinations of them were used (Table 1). The aim was to identify broad indices containing indicators usable in the context of a wide variety aquatic environments. The keywords used were then selected to provide access to the main articles dealing with and linking ecosystem health and human health in a wide variety of aquatic ecosystems. Our review did not examine the contents of the grey literature, which may contain important information about the implementation of certain indicators. Examining this literature was not within the scope of our review, which focused on the peer-reviewed scientific literature.

We yielded a total of 245 articles, published between 1963 and 2023, of those 185 articles focused on the assessment of aquatic ecosystem health, and 60 articles made the link between ecosystem health and human health and well-being. We then extracted 65 indices that we categorized into four groups depending on what they evaluate: habitat quality, water quality, biological communities, and/or overall ecosystem health. Indices per definition comprise several indicators, i.e. parameters measured to assess the quality or the health of the ecosystem, such as abiotic factors (e.g. pH, temperature, oxygen concentration) and ecological components (e.g. number of species, relative proportions of taxa). For each index, we listed the indicators that compose them and the ecosystem type to which it has been applied. We also assessed the frequency of use of 50 headline indicators among the 65 indices to identify the most frequently used indicators. We evaluated the applicability of each index, using information about the types of water bodies in which the index can be applied (lake, river, stream), the practical ease for non-experts to measure abiotic factors and to easily identify organisms down to species level without expert training (e.g. fish, plants). For example, some organisms like diatoms, even if they are starting to be increasingly documented and used (Bere et al. 2014), as well as some species of macroinvertebrates, may require experts to be identified. Fish may be easier to identify but are not found in all aquatic ecosystems, and in others such as e.g. mountain lakes where fish are non-native, they have low diversity rates (Allardi 1994; Herman and Nejadhashemi 2015) and rather witness the degradation of an ecosystem (Miró et al. 2019). We also considered if the index can discriminate or not the stressor(s) which can trigger an ecosystem-wide stress response. For that, we identified 10 such stressors to aquatic ecosystems (i.e. degradation of the water quality, variation of the pH, rise of temperature, eutrophication, increase bacterial load, increase solids materials, increase pollution, modification of the habitat, cyanobacterial bloom and anthropogenic activities and stress).

We used the 60 articles dealing with the link between human health and well-being and ecosystem health to evaluate the link between indicators/indices, and human health deterioration, defining a 'human health deterioration score'. This score varied from 0 to 3. Zero corresponded to no direct impact on human health. A value of 1 was assigned to behavioral or psychological impacts via visual modification of the ecosystem or modification of human activities. The presence of a pathogen or pollutant that could cause slight impacts or lead to temporary illness development was categorized as deterioration score 2. The final category, 3, corresponds to the presence of pathogens or pollutants that may cause a chronic pathology, disruption of body function, or even mortal risk.

Based on the 12 most used indicators (e.g. diatoms, macroinvertebrates, pH, nutrients, coliforms) we assessed from the literature if and how they vary depending on the 10 stressors previously identified. We considered that there was an impact of the stressor when there was a covariation (an increase, a decrease or change in both parameters) between

<figure><img src="image_4.png" /></figure>
<table><caption>**Table 1** Selection criteria and keywords for articles on aquatic ecosystem health and links to human well-being</caption><thead><tr><th></th><th>Aquatic ecosystem health</th><th>Human well-being</th></tr></thead><tbody><tr><td>Keywords</td><td>- aquatic ecosystem health<br>- aquatic health<br>- aquatic ecosystem OR ecosystem health<br>- water quality</td><td>- ecosystem health AND human health OR well-being<br>- aquatic environment AND human health OR well-being<br>- aquatic ecosystem AND human health OR well-being</td></tr><tr><td>Exclusion criteria</td><td>Articles dealing with green space only.<br>Repetitive articles with the same index or no specific index used, derived indices too similar or too specific for one place.<br>Indices with too little information on its applicability.</td><td>Articles focusing only on green space and human health.</td></tr><tr><td>Inclusion criteria</td><td>Assessment of aquatic ecosystem health, review on aquatic indices, development of new or derived index.</td><td>Description of the impacts on human well-being or health linked to ecosystems health and aquatic ecosystems.<br>Link to human health and perturbations of aquatic ecosystems.</td></tr><tr><td>Number of articles included</td><td>185</td><td>60</td></tr></tbody></table>
the stressor and the ecosystem indicator or human health simultaneously over time. These variations made it possible to assess the extent to which these indicators can witness envi- ronmental change and be applied in the assessment of ecosystem health. The levels of community sensitivity to disturbances have been described in the literature, and compared between communities with a short or long-life cycle. We considered a community to be of high sensitivity, when the literature suggested a rapid and significant change in community composition. We assume a moderate sensitivity, where the literature suggests less rapid and moderate changes in the community composition. In cases, for which the literature reported slow and small changes, we classified the community sensitivity as low.

Finally, to understand the direct and indirect impacts of aquatic ecosystems on human well-being, we compiled and categorized the potential effects of aquatic ecosystems on human well-being.

## Results

We extracted a non-exhaustive but representative list of 65 main indices applied in the assessment of aquatic ecosystem health (Table 2). Among these indices, the majority focused on biological communities (n=39), on water quality (n=22), and on habitat struc- ture (n=2). The direct integration of indicators from at least two categories in one index was rare (n=2). Only the Spatial Ecosystem Health Index and the Ecosystem Health index directly use water quality and biological community parameters into the calculation of the index. On average, 8.71 indicators were applied per index ranging from 1 to 39 indicators (Fig. 2). Among biological indices, the Index of Biological Integrity (IBI, Karr 1981), was the most cited and used one (n=11/65). Biological indices were mainly represented by dia- tom communities (n=15) and macroinvertebrates (n=11). Studies applying a biological index often added physicochemical indicators to estimate the overall ecosystem state. The most frequent physicochemical indicators, among water quality indices, were Dissolved Oxygen (DO) (n=20), pH (n=16), Biological Oxygen Demand (BOD) (n=15), Sus- pended Solids (SS) (n=14), and ammonia (n=12) followed by 7 others (Tables 2 and 3). Of the 65 indices, no index scored in all three categories (applicability to multiple environ- ments, ease of application, and discrimination of sources of disruption), 53 were applicable to multiple environments, 37 were easy to use, and 10 indices were described as being able to discriminate between the stress factors for which the index was developed and other ecosystems in the same geographical region. 31 indices scored in two categories, of which 21 were easy to use and applicable to different environments, 2 were applicable to multiple environments and able to discriminate stress sources. Finally, 8 indices were easy to use and discriminated between sources of stress that impact indicator variations (Tables 2 and 3). Most indices are specific to certain aquatic ecosystems due to the difference in the flow regime and species diversity (Table 2). Moreover, the ease of application depends on the cost and the facility of collection, the difficulty of identification of biological organisms, and the complexity of the index calculation.

All indices allow different assessments of aquatic ecosystem health, however, most of them could not evaluate directly the link between ecosystem health and human health or well-being (n=42) based on our human health deterioration score (Table 2). Only a few indices could identify a risk of chronic pathology, body function, or mortal risk on health (n=5) through the analysis of the presence of pathogens or pollutants known to cause harm to humans. The remaining indices assessed impacts on psychological well-being (n=3), or
<table><caption>**Table 2** List of indices and their ability to assess aquatic ecosystem health</caption><thead><tr><th rowspan="2">Categories</th><th rowspan="2">Index</th><th rowspan="2">Derived from the index</th><th rowspan="2">Indicators measured</th><th rowspan="2">Environment</th><th colspan="2">Applicability index</th><th rowspan="2">Human health deterioration score</th><th rowspan="2">References</th></tr><tr><th>App</th><th>Ease</th><th>DoS</th></tr></thead><tbody><tr><td rowspan="2">Habitat quality</td><td rowspan="2">River habitat quality index</td><td rowspan="2">Habitat quality index (HQI)</td><td>Substrate, habitat complexity, velocity-depth, bank stability and conservation, channel alteration, stream conditions, water quality, vegetation cover and diversity, and human activities</td><td>River, stream</td><td>-</td><td>+</td><td>-</td><td>1</td><td>Texas Commission on Environmental Quality (1999), Chen et al. (2019), Chen et al. (2022)</td></tr><tr><td>Substrate, embeddedness, velocity-depth regime, canopy cover, channel alteration, bottom, deposition, pool run/bend ratios, (habitat complexity and channel alteration)</td><td>River</td><td>+</td><td>+</td><td>-</td><td>1</td><td>An et al. (2002)</td></tr><tr><td rowspan="2">Water quality</td><td rowspan="2">Qualitative habitat evaluation index (QHEI)</td><td rowspan="2">Original</td><td>pH, DO, conductivity, alkalinity, chloride, fecal coliforms, sewage treatment and carbon chloroforms extract</td><td>River</td><td>+</td><td>+</td><td>/</td><td>3</td><td>Horton (1965), Gupta et al. (2017)</td></tr><tr><td>Original (1960)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
<figure><img src="image_5.png" /><figcaption>**Table 2 (continued)**</figcaption></figure>

<table><thead><tr><th rowspan="2">Categories</th><th rowspan="2">Index</th><th rowspan="2">Derived from the index</th><th rowspan="2">Indicators measured</th><th rowspan="2">Environment</th><th colspan="2">Applicability index</th><th rowspan="2">Human health deterioration score</th><th rowspan="2">References</th></tr><tr><th>App</th><th>Ease</th><th>DoS</th></tr></thead><tbody><tr><td></td><td>The national sanitation foundation WQI (NSF)</td><td>Horton index</td><td>Water temperature, total solids, pH, DO, BOD, fecal coliforms, total phosphorus, nitrates, turbidity, pesticides and toxic components</td><td>Lake, river, stream, marine water</td><td>-</td><td>+</td><td>/</td><td>3</td><td>Brown et al. (1970), Brown et al. (1973), Gupta et al. (2017)</td></tr><tr><td></td><td>Dinius index</td><td>The National Sanitation Foundation (NSF) WQI</td><td>Water temperature, color, pH, DO, BOD, conductivity, alkalinity, chloride, fecal coliforms, total coliforms and hardness</td><td>River</td><td>+</td><td>+</td><td>-</td><td>2</td><td>Dinius (1987)</td></tr><tr><td></td><td>Oregon index</td><td>NSF WQI</td><td>Water temperature, suspended solids, pH, DO, BOD, ammonia, fecal coliforms, total phosphorus, nitrates and total nitrogen</td><td>River</td><td>-</td><td>+</td><td>-</td><td>2</td><td>Dunnette (1979), Cude (2001)</td></tr></tbody></table>
<table><caption>**Table 2 (continued)**</caption><thead><tr><th rowspan="2">Categories</th><th rowspan="2">Index</th><th rowspan="2">Derived from the index</th><th rowspan="2">Indicators measured</th><th rowspan="2">Environment</th><th colspan="3">Applicability index</th><th rowspan="2">Human health deterioration score</th><th rowspan="2">References</th></tr><tr><th>App</th><th>Ease</th><th>DoS</th></tr></thead><tbody><tr><td></td><td>Scottish research development department (SRDD-WQI)</td><td>Original (1970)</td><td>Water temperature, suspended solids, pH, DO, BOD, conductivity, ammonia, fecal coliforms, total phosphorus and total nitrogen</td><td>River</td><td>+</td><td>+</td><td>-</td><td>2</td><td>Bordalo (2001)</td></tr><tr><td></td><td>The bascaron index</td><td>SRDD WQI</td><td>Water temperature, color, turbidity, pH, DO, BOD, conductivity, ammonia, total coliforms, total sulfate, nitrates, total hardness, detergent, permeation reduction, pesticides, oil and grease, CN<sup>-</sup>, Na<sup>+</sup>, free CO<sub>2</sub>, Mg<sub>2+</sub>, P, NO<sub>2</sub>, Ca<sub>2+</sub>, and visual appearance</td><td>River, marine water</td><td>+</td><td>+</td><td>/</td><td>3</td><td>Abrahão et al. (2010)</td></tr></tbody></table>
<table><caption>**Table 2 (continued)**</caption><thead><tr><th rowspan="2">Categories</th><th rowspan="2">Index</th><th rowspan="2">Derived from the index</th><th rowspan="2">Indicators measured</th><th rowspan="2">Environment</th><th colspan="2">Applicability index</th><th rowspan="2">Human health deterioration score</th><th rowspan="2">References</th></tr><tr><th>App</th><th>Ease</th><th>DoS</th></tr></thead><tbody><tr><td></td><td>House index</td><td>SRDD WQI</td><td>Water temperature, suspended solids, pH, DO, BOD, chloride, ammonia, total coliforms and nitrates</td><td>River</td><td>-</td><td>+</td><td>-</td><td>2</td><td>House (1989)</td></tr><tr><td></td><td>Dalmatian index</td><td>SRDD WQI</td><td>Water temperature, mineralization, corrosion coefficient, DO, BOD, total nitrogen, protein nitrogen, total phosphorus and total coliforms</td><td>Marine water</td><td>+</td><td>+</td><td>-</td><td>2</td><td>Stambuk-Giljanovic (1999)</td></tr><tr><td></td><td>Ross index or Fuzzy interface system (FIS)</td><td>Original (1977)</td><td>Suspended solids, DO, BOD, ammonia</td><td>River, lake, marine water</td><td>+</td><td>+</td><td>-</td><td>0</td><td>Ross (1995)</td></tr><tr><td></td><td>Environmental quality index (EQI)</td><td>Original (1982)</td><td>Suspended solids, specific conductance, chloride, fecal coliforms, total phosphorus, chlorophyll a, obvious pollution, toxic inorganic contaminants, toxic organic contaminants</td><td>River, lake</td><td>+</td><td>+</td><td>/</td><td>3</td><td>Steinhart et al. (1982)</td></tr></tbody></table>

<figure><img src="image_6.png" /></figure>
<table><caption>**Table 2 (continued)**</caption><thead><tr><th rowspan="2">Categories</th><th rowspan="2">Index</th><th rowspan="2">Derived from the index</th><th rowspan="2">Indicators measured</th><th rowspan="2">Environment</th><th colspan="2">Applicability index</th><th colspan="2">Human health deterioration score</th><th rowspan="2">References</th></tr><tr><th>App</th><th>Ease</th><th>DoS</th></tr></thead><tbody><tr><td></td><td>Smith index</td><td>Original (1990)</td><td>Water temperature, temperature difference, pH, turbidity, suspended solids, DO, BOD, ammonia, fecal coliforms</td><td>River</td><td>+</td><td>+</td><td>/</td><td>2</td><td>Smith (1990)</td></tr><tr><td></td><td>Dojido index</td><td>Original (1994)</td><td>Suspended solids, pH, DO, BOD, Chemical Oxygen Demand (COD), chloride, ammonia, total phosphorus, total sulfate, nitrates, total hardness, total nitrogen, cadmium, manganese, zinc, copper, mercury, lead, nickel, chrome, iron, etc</td><td>River</td><td>+</td><td>+</td><td>/</td><td>3</td><td>Dojido et al. (1994)</td></tr><tr><td></td><td>British Columbia WQI (BCWQI)</td><td>Original (1995)</td><td>DO, pH, turbidity, total suspended solids, ammonia, copper, lead, zinc, etc</td><td>River</td><td>+</td><td>-</td><td>/</td><td>2</td><td>Dunn (1995), Zand-bergen and Hall (1998)</td></tr></tbody></table>
<table><caption>**Table 2 (continued)**</caption><thead><tr><th rowspan="2">Categories</th><th rowspan="2">Index</th><th rowspan="2">Derived from the index</th><th rowspan="2">Indicators measured</th><th rowspan="2">Environment</th><th colspan="2">Applicability index</th><th colspan="2">Human health deterioration score</th><th rowspan="2">References</th></tr><tr><th>App</th><th>Ease</th><th>DoS</th></tr></thead><tbody><tr><td></td><td>Canadian council of ministers of the environment (CCME)</td><td>BCWQI</td><td>Water quality indicators of choice, no recommendations were made</td><td>Coastal water, river, lake, marine water</td><td>+</td><td>+</td><td>/</td><td>0</td><td>Canadian Council of Ministers of the Environment (2001). Gupta et al. (2017)</td></tr><tr><td></td><td>Liou index</td><td>Original (2003)</td><td>Water temperature, turbidity, suspended solids, pH, DO, BOD, chloride, ammonia, cadmium, zinc, copper, lead and chrome</td><td>River</td><td>+</td><td>+</td><td>/</td><td>2</td><td>Liou et al. (2004)</td></tr><tr><td></td><td>Said index</td><td>Original (2004)</td><td>Turbidity, DO, conductivity, total coliforms and total phosphorus</td><td>Marine water</td><td>-</td><td>+</td><td>-</td><td>2</td><td>Said et al. (2004)</td></tr><tr><td></td><td>Hanh index</td><td>Said index</td><td>Orthophosphate, turbidity, suspended solids, DO, BOD, COD, ammonia, and total coliforms</td><td>River</td><td>+</td><td>+</td><td>-</td><td>2</td><td>Hanh et al. (2011)</td></tr><tr><td></td><td>Malaysian index</td><td>Original (2007)</td><td>Suspended solids, pH, DO, BOD, COD and ammonia</td><td>River</td><td>+</td><td>+</td><td>-</td><td>0</td><td>Gazzaz et al. (2012)</td></tr></tbody></table>

<figure><img src="image_7.png" /></figure>
<table><caption>**Table 2 (continued)**</caption><thead><tr><th rowspan="2">Categories</th><th rowspan="2">Index</th><th rowspan="2">Derived from the index</th><th rowspan="2">Indicators measured</th><th rowspan="2">Environment</th><th colspan="3">Applicability index</th><th rowspan="2">Human health deterioration score</th><th rowspan="2">References</th></tr><tr><th>App</th><th>Ease</th><th>DoS</th></tr></thead><tbody><tr><td></td><td>Almedia index or recreational water quality index</td><td>Original (2012)</td><td>pH, turbidity, detergents, total coliforms, fecal coliforms, <i>E. coli</i>, Enterococci, nitrate, orthophosphate- and COD</td><td>River</td><td>+</td><td>+</td><td>-</td><td>2</td><td>Almeida et al. (2012)</td></tr><tr><td></td><td>Aquatic Health Index (AHI)</td><td>Aquatic Health Index (AHI)</td><td>Salinity, pH, water temperature, transparency, DO, nitrate, phosphate, silicate, oil and grease, lead, zinc, copper, fecal coliforms, BOD</td><td>Coastal water, estuaries</td><td>-</td><td>+</td><td>/</td><td>2</td><td>Barua and Rahman (2020), Saha et al. (2017)</td></tr><tr><td></td><td>Coastal Water Quality</td><td>Coastal Water Quality</td><td>Total suspended solids, oil and grease, COD, total nitrogen, ammonia, total phosphorus, phosphate, chlorophyll a, total coliforms, fecal coliforms, DO and total organic carbon</td><td>Coastal water</td><td>-</td><td>+</td><td>-</td><td>2</td><td>Nguyen and Sevando (2019)</td></tr></tbody></table>
<figure><img src="image_8.png" /><figcaption>**Table 2 (continued)**</figcaption></figure>

<table><thead><tr><th rowspan="2">Categories</th><th rowspan="2">Index</th><th rowspan="2">Derived from the index</th><th rowspan="2">Indicators measured</th><th rowspan="2">Environment</th><th colspan="2">Applicability index</th><th rowspan="2">Human health deterioration score</th><th rowspan="2">References</th></tr><tr><th>App</th><th>Ease</th><th>DoS</th></tr></thead><tbody><tr><td rowspan="2">Biological communities<br>Fauna</td><td>Fuzzy Comprehensive Evaluation Method</td><td>Fuzzy Comprehensive Evaluation Method</td><td>DO, pH, water temperature, ammonium, water color and taste, and floating object</td><td>Aquaculture water, pond</td><td>+</td><td>+</td><td>-</td><td>1</td><td>You et al. (2021)</td></tr><tr><td>Shannon-Wiener biodiversity index</td><td>Shannon-Wiener index</td><td>Number of species, and proportion of individuals per species</td><td>River</td><td>+</td><td>+</td><td>-</td><td>0</td><td>Shannon (1963), Zhao et al. (2017), Zhao et al. (2019), Scotti et al. (2022)</td></tr><tr><td>Diatoms</td><td>Sladecek index (SLA)</td><td>Original (1984)</td><td>Species, saprobic valence, weight of species and individual saprobic index</td><td>River, lake, stream</td><td>+</td><td>-</td><td>-</td><td>0</td><td>Sládeček (1986)</td></tr><tr><td rowspan="2">Leclercq and Maquet index (ILM)<br>Diatom index (DI)</td><td>Saprobi indices</td><td>Saprobi indices</td><td>Indicators value and saprobic valence for diatom</td><td>River</td><td>+</td><td>-</td><td>+</td><td>0</td><td>Leclercq and Maquet (1987)</td></tr><tr><td>Saprobi indices</td><td>Saprobi indices</td><td>Diatom species, relative abundance, sensitivity index and indicating value</td><td>Marshe, river</td><td>+</td><td>-</td><td>/</td><td>0</td><td>Naqeeb et al. 2020</td></tr><tr><td>Generic Diatom Index (GDI)</td><td>Diatom index (DI)</td><td>Diatom index (DI)</td><td>Number of diatom taxa, taxa abundance, global sensitivity and stenoeocia degree</td><td>Marshe, river</td><td>+</td><td>-</td><td>/</td><td>0</td><td>Rumeau and Coste (1988), Naqeeb et al. (2020)</td></tr></tbody></table>
<table><caption>**Table 2 (continued)**</caption><thead><tr><th rowspan="2">Categories</th><th rowspan="2">Index</th><th rowspan="2">Derived from the index</th><th rowspan="2">Indicators measured</th><th rowspan="2">Environment</th><th colspan="2">Applicability index</th><th rowspan="2">Human health deterioration score</th><th rowspan="2">References</th></tr><tr><th>App</th><th>Ease</th><th>DoS</th></tr></thead><tbody><tr><td></td><td>Generic index (GI) / Generic diatom index</td><td>Generic Diatom Index (GDI)</td><td>Ratio of individual abundance</td><td>River</td><td>+</td><td>-</td><td>0</td><td>Wu (1999)</td></tr><tr><td></td><td>Specific Pollution Sensitivity Index (IPS)</td><td>Diatom index (DI)</td><td>Diatoms species and sensitivity/tolerance to pollutants</td><td>River, lake</td><td>+</td><td>-</td><td>0</td><td>CEMAGREF, AERM C (1982), Prygiel and Coste (1993), Descy and Coste (1991), Stenger-Kovács et al. (2013)</td></tr><tr><td></td><td>Indice Diatomique Pratique (IDP)</td><td>IDG and IPS</td><td>Diatom species, sensitivity to pollution and indicator value</td><td>River</td><td>+</td><td>-</td><td>0</td><td>Prygiel et al. (1996)</td></tr><tr><td></td><td>Diatom Assemblage Index (DAI ou DAlpo) or Watanabe's index</td><td>Diatom Community index (1982)</td><td>Diatom taxa, relative abundance of taxa, sensitivity to organic pollution</td><td>River, lake</td><td>+</td><td>-</td><td>0</td><td>Watanabe et al. (1986)</td></tr><tr><td></td><td>Commission for Economical Community / European index (CEE ou CEC)</td><td>Original (1991)</td><td>Relative abundance of taxa, taxa species, tolerance and indicator value</td><td>River</td><td>+</td><td>-</td><td>0</td><td>Descy and Coste (1991)</td></tr><tr><td></td><td>Schiefele & Schreiner index (SHE)</td><td>Original (1991)</td><td>Relative abundance of taxa, diatom species, sensitivity/tolerance to pollutants and indicator value</td><td>River, lake</td><td>+</td><td>-</td><td>0</td><td>Schiefele and Schreiner (1991)</td></tr></tbody></table>
<table><caption>**Table 2 (continued)**</caption><thead><tr><th rowspan="2">Categories</th><th rowspan="2">Index</th><th rowspan="2">Derived from the index</th><th rowspan="2">Indicators measured</th><th rowspan="2">Environment</th><th colspan="2">Applicability index</th><th rowspan="2">Human health deterioration score</th><th rowspan="2">References</th></tr><tr><th>App</th><th>Ease</th><th>DoS</th></tr></thead><tbody><tr><td></td><td>Trophic Diatom Index (TDI)</td><td>Original (1995)</td><td>Relatives proportion of taxa and species, sensitivity of species and indicator value of species</td><td>River, stream</td><td>+</td><td>-</td><td>/</td><td>0</td><td>Kelly and Whitton (1995), Naqeeb et al. (2020), Stenger-Kovács et al. (2013)</td></tr><tr><td></td><td>Diatom-based Eutrophication/ Pollution Index (EPI-D)</td><td>Original (1996)</td><td>Species abundance, sensitivity to organic load, mineralization degree and nutrients load</td><td>River</td><td>+</td><td>-</td><td>+</td><td>0</td><td>Dell’Uomo et al. (2004)</td></tr><tr><td></td><td>IBD</td><td>Biological Diatom Index (IBD)</td><td>Diatoms taxa and relative abundance</td><td>River, lake, stream</td><td>+</td><td>-</td><td>+</td><td>0</td><td>Prygiel and Coste (2000), Stenger-Kovács et al. (2013)</td></tr><tr><td></td><td>Benthic Diatom Index of Biotic Integrity (BD-IBI)</td><td>Index of Biological Integrity (IBI)</td><td>Percentage of prostrate individuals, percentage of Amphora individuals, Diatom-based Eutrophication/ Pollution Index, and percentage of polysaprobiotic species</td><td>River</td><td>+</td><td>-</td><td>+</td><td>0</td><td>Tan et al. (2015)</td></tr></tbody></table>

<figure><img src="image_9.png" /></figure>
<table><caption>**Table 2 (continued)**</caption><thead><tr><th rowspan="2">Categories</th><th rowspan="2">Index</th><th rowspan="2">Derived from the index</th><th rowspan="2">Indicators measured</th><th rowspan="2">Environment</th><th colspan="2">Applicability index</th><th rowspan="2">Human health deterioration score</th><th rowspan="2">References</th></tr><tr><th>App</th><th>Ease</th><th>DoS</th></tr></thead><tbody><tr><td rowspan="2">Algae and diatoms</td><td>Algae-IBI</td><td>Index of Biological Integrity (IBI)</td><td>Number of heterotroph diatom, diatom sedimentation, haplobiontic diatom, etc</td><td>Stream</td><td>+</td><td>-</td><td>/</td><td>0</td><td>Fetscher et al. (2013)</td></tr><tr><td>Hilsenhoff Biotic Index (HBI)</td><td>Original (1977)</td><td>Tolerance/sensitivity to pollutants and number of individuals per species</td><td>Stream</td><td>+</td><td>-</td><td>-</td><td>0</td><td>Hilsenhoff (1982), Bennett et al. (2004)</td></tr><tr><td rowspan="2">Macroinvertebrates</td><td>Family Biotic index (FBI)</td><td>Hilsenhoff Biotic Index (HBI)</td><td>Number of individuals within a taxon, tolerance value to organic pollutants and total number of organisms</td><td>Streams</td><td>+</td><td>-</td><td>/</td><td>0</td><td>Chen et al. (2019), Bennett et al. (2004)</td></tr><tr><td>Biological Monitoring Working Party (BMWP)</td><td>Original (1980)</td><td>Pollution tolerance value to organic pollution</td><td>Stream, river</td><td>+</td><td>-</td><td>/</td><td>0</td><td>Chesters (1980)</td></tr><tr><td></td><td>Ephemeroptera, Plecoptera and Trichoptera (EPT)</td><td>Original (1988)</td><td>Ephemeroptera, Plecoptera and Trichoptera populations richness and percentage abundance</td><td>Stream, river</td><td>+</td><td>-</td><td>-</td><td>0</td><td>Barbour et al. (1999), Liu et al. (2017)</td></tr></tbody></table>
<table><caption>**Table 2 (continued)**</caption><thead><tr><th rowspan="2">Categories</th><th rowspan="2">Index</th><th rowspan="2">Derived from the index</th><th rowspan="2">Indicators measured</th><th rowspan="2">Environment</th><th colspan="3">Applicability index</th><th rowspan="2">Human health deterioration score</th><th rowspan="2">References</th></tr><tr><th>App</th><th>Ease</th><th>DoS</th></tr></thead><tbody><tr><td></td><td>Benthic-IBI</td><td>Index of Biological Integrity (IBI)</td><td>Community richness, proportion of species, nutritional structure, tolerance and habitat quality</td><td>River, stream</td><td>+</td><td>-</td><td>-</td><td>0</td><td>Kerans and Karr (1994)</td></tr><tr><td></td><td>Basin-wide Index of Benthic Integrity (B-IBI)</td><td>Index of Biological Integrity (IBI)</td><td>Ephemeroptera/ Plecoptera/ Trichoptera taxonomic richness, Hilsenhoff Family Biotic Index, proportion of clingers, proportion of collectors, percent contribution of the dominant taxon, proportion of EPT individuals, total taxonomic richness</td><td>Basin</td><td>+</td><td>-</td><td>+</td><td>0</td><td>Astin (2007)</td></tr></tbody></table>

<figure><img src="image_10.png" /></figure>
<table><caption>**Table 2 (continued)**</caption><thead><tr><th rowspan="2">Categories</th><th rowspan="2">Index</th><th rowspan="2">Derived from the index</th><th rowspan="2">Indicators measured</th><th rowspan="2">Environment</th><th colspan="2">Applicability index</th><th rowspan="2">Human health deterioration score</th><th rowspan="2">References</th></tr><tr><th>App</th><th>Ease</th><th>DoS</th></tr></thead><tbody><tr><td></td><td>Invertebrate Community Index (ICI)</td><td>IBI and EPT</td><td>Total number of taxa, total number of mayfly taxa, total number of caddisfly taxa, total number of dipteran taxa, percent of mayflies, percent of caddisflies</td><td>River, stream, coastal water</td><td>+</td><td>-</td><td>/</td><td>0</td><td>DeShon (1995), Bennett et al. (2004)</td></tr><tr><td></td><td>The Global Biological Normalized index (GBNI)</td><td>Original (2004)</td><td>Sensitivity, class variety, number of indicators faunistic group and taxonomic richness</td><td>River</td><td>+</td><td>-</td><td>-</td><td>0</td><td>Archaimbault and Dumont (2010)</td></tr><tr><td></td><td>Urban Stream Multimetric Index (USMI)</td><td>Original (2017)</td><td>The number of taxa, Hill diversity, the percentage of Ephemeroptera, Odonata and Trichoptera and the percentage of collector-filterer</td><td>Stream</td><td>+</td><td>-</td><td>-</td><td>0</td><td>Liu et al. (2017)</td></tr><tr><td></td><td>Benthic Macroinvertebrate Index (BMI)</td><td>Original</td><td>Contamination index species, number of species and weight index species</td><td>Stream</td><td>+</td><td>-</td><td>-</td><td>0</td><td>Kang et al. (2022)</td></tr></tbody></table>
<figure><img src="image_11.png" /><figcaption>**Table 2 (continued)**</figcaption></figure>

<table><thead><tr><th rowspan="2">Categories</th><th rowspan="2">Index</th><th rowspan="2">Derived from the index</th><th rowspan="2">Indicators measured</th><th rowspan="2">Environment</th><th colspan="2">Applicability index</th><th rowspan="2">Human health deterioration score</th><th rowspan="2">References</th></tr><tr><th>App</th><th>Ease</th><th>DoS</th></tr></thead><tbody><tr><td></td><td>River Invertebrate Prediction and Classification System (RIVPACS)</td><td>Original</td><td>Altitude at site, distance from source, slope, mean width, mean depth, discharge category of the site, date of sampling, maximum surface velocity, pH, DO, chloride, alkalinity, total nitrogen, mean percentage macrophyte cover</td><td>River, streams</td><td>+</td><td>-</td><td>/</td><td>0</td><td>Wright (2000)</td></tr><tr><td rowspan="3">Fish</td><td>Fish Community Index</td><td>Original</td><td>Number of species, species abundance, trophic index</td><td>Stream</td><td>+</td><td>-</td><td>/</td><td>0</td><td>Jordan et al. (2010)</td></tr><tr><td>Fish Assessment Index (FAI)</td><td>Original</td><td>Native fish species, rifflie-benthic species, sensitive species, tolerant species, nutritional structure</td><td>River, stream</td><td>-</td><td>+</td><td>+</td><td>0</td><td>Klemm et al. (1993), Kang et al. (2022)</td></tr><tr><td>Fish-IBI</td><td>Index of Biological Integrity (IBI)</td><td>Species composition and abundance, nutritional structure, reproduction, tolerance and distribution</td><td>River, stream</td><td>-</td><td>+</td><td>/</td><td>0</td><td>Karr (1981), Karr et al. (1986), Wu et al. (2020), Zhao et al. (2019)</td></tr></tbody></table>
<table><caption>**Table 2 (continued)**</caption><thead><tr><th rowspan="2">Categories</th><th rowspan="2">Index</th><th rowspan="2">Derived from the index</th><th rowspan="2">Indicators measured</th><th rowspan="2">Environment</th><th colspan="3">Applicability index</th><th rowspan="2">Human health deterioration score</th><th rowspan="2">References</th></tr><tr><th>App</th><th>Ease</th><th>DoS</th></tr></thead><tbody><tr><td></td><td>European Fish Index (EFI)</td><td>Index of Biological Integrity (IBI)</td><td>Trophic structure, benthic species, rheophilic species, tolerant and intolerant species</td><td>River</td><td>-</td><td>+</td><td>+</td><td>0</td><td>Pont et al. (2007)</td></tr><tr><td></td><td>Aquatic Ecosystem Health Index (AEHI)</td><td>Original</td><td>Ethoxyresorufin-O-Deethylase, creatinine, alanine aminotransferase, triglyceride, condition factor, liver-somatic index, spleno-somatic index, viseral-somatic index, gonado-somatic index, fecundity, atretic oocyte and size</td><td>River</td><td>-</td><td>-</td><td>/</td><td>0</td><td>Yeom and Adams (2007)</td></tr></tbody></table>
<table><caption>**Table 2 (continued)**</caption><thead><tr><th rowspan="2">Categories</th><th rowspan="2">Index</th><th rowspan="2">Derived from the index</th><th rowspan="2">Indicators measured</th><th rowspan="2">Environment</th><th colspan="2">Applicability index</th><th rowspan="2">Human health deterioration score</th><th rowspan="2">References</th></tr><tr><th>App</th><th>Ease</th><th>DoS</th></tr></thead><tbody><tr><td>Fauna</td><td>Index of Biological Integrity (IBI)</td><td>Original (1981)</td><td>Fish assemblages: native fish species, benthic species, sensitive species, proportion of tolerant species, nutritional structure, number of individuals, proportion of exotics individuals and proportion of individuals with anomalies</td><td>Stream, river</td><td>-</td><td>+</td><td>/</td><td>0</td><td>Karr (1981), An et al. (2002), Kim et al. (2007), Roley et al. (2014), Hoyle et al. (2018), Xu and Zhang (2020)</td></tr><tr><td>Zooplankton</td><td>Zooplankton-IBI</td><td>Index of Biological Integrity (IBI)</td><td>Species density, species richness, species biomass</td><td>River</td><td>+</td><td>-</td><td>+</td><td>0</td><td>Yao et al. (2021)</td></tr><tr><td></td><td>Freshwater Ecosystem Health Index (FEHI)</td><td>Based on Z-IBI</td><td>Taxonomic composition, individual abundance, body size, biodiversity of zooplankton</td><td>River, lake</td><td>+</td><td>-</td><td>/</td><td>0</td><td>Cai et al. (2020)</td></tr></tbody></table>

<figure><img src="image_12.png" /></figure>
<table><caption>**Table 2 (continued)**</caption><thead><tr><th rowspan="2">Categories</th><th rowspan="2">Index</th><th rowspan="2">Derived from the index</th><th rowspan="2">Indicators measured</th><th rowspan="2">Environment</th><th colspan="2">Applicability index</th><th rowspan="2">Human health deterioration score</th><th rowspan="2">References</th></tr><tr><th>App</th><th>Ease</th><th>DoS</th></tr></thead><tbody><tr><td rowspan="2">Plankton</td><td rowspan="2">Plankton-IBI</td><td rowspan="2">Index of Biological Integrity (IBI)</td><td>Crustacean zooplankton biomass, percentage of the species biomass on the total biomass, biomass of edible algae taxa, zoo-plankton ratio, L. macturus density</td><td>Lake</td><td>+</td><td>-</td><td>/</td><td>0</td><td>Kane et al. (2009)</td></tr><tr><td>Species richness, Shannon index, exotic species, number of individuals per species, dominant species, tolerance to pollutants, percentage of individuals per species</td><td>Wetland</td><td>+</td><td>+</td><td>/</td><td>0</td><td>Miller et al. (2006)</td></tr><tr><td>Algae</td><td>TSI</td><td>Trophic State Index (TSI)</td><td>Chlorophyll a, Secchi disk depth, total phosphorus</td><td>Lake</td><td>+</td><td>+</td><td>/</td><td>0</td><td>Carlson and Simpson (1996), Carlson (1977), Devic et al. (2014), Roley et al. (2014)</td></tr><tr><td>Dragonfly</td><td>DBI</td><td>Dragonfly Biotic Index (DBI)</td><td>Species distribution, threat status, and the tolerance of a species</td><td>All waterbodies</td><td>+</td><td>-</td><td>-</td><td>0</td><td>Samways and Simaika (2008), Moor (2017)</td></tr></tbody></table>
<figure><img src="image_13.png" /><figcaption>**Table 2** (continued)</figcaption></figure>

<table><thead><tr><th rowspan="2">Categories</th><th rowspan="2">Index</th><th rowspan="2">Derived from the index</th><th rowspan="2">Indicators measured</th><th rowspan="2">Environment</th><th colspan="2">Applicability index</th><th rowspan="2">Human health deterioration score</th><th rowspan="2">References</th></tr><tr><th>App</th><th>Ease</th><th>DoS</th></tr></thead><tbody><tr><td rowspan="2">Ecosystem health</td><td rowspan="2">Spatial ecosystem health index (EHI)</td><td rowspan="2">Ecosystem health index</td><td>Secchi depth, seagrass loss, total phosphate, concentration in nitrogen-stable isotope, percentage of <i>Lyngebya majus</i>-cule presence, and chlorophyll a</td><td>River, bay</td><td>+</td><td>+</td><td>/</td><td>0</td><td>Pantus and Dennison (2005)</td></tr><tr><td>Water temperature, pH, turbidity, salinity, DO, BOD, ammonia, orthophosphorus, silicate, nitrite, nitrate, total suspended solids, COD, chlorophyll a, diatoms</td><td>Lake, coastal water</td><td>+</td><td>+</td><td>/</td><td>2</td><td>Padua et al. (2023), Simčič and Brancelj (2009), Flint et al. (2017)</td></tr><tr><td>Ecosystem health index (various derived)</td><td>Ecosystem health index (EHI)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

Applicable to multiple environments, *Ease* of application, *DoS* Discrimination of the stressors, +: yes, -: no, /: unknown. *DO* Dissolved Oxygen, *BOD* Biochemical Oxygen Demand

Human health deterioration score (0=no direct impact on human health, 1=behavioral or psychological impacts, 2=slight impacts or risk of temporary illness development, 3=risk of development of a chronic pathology, disruption of body function, or mortal risk)
Number of indicators per index

<figure><img src="image_14.png" /><figcaption>**Fig. 2** Distribution of the number of indicators per index</figcaption></figure>

slight impacts on physical health, or development of temporary illness (n = 14). These latter indices make it possible to fully or partially assess the impact of the state of the ecosystem on human health and well-being (Table 2).

When investigating indicators, we found that the 12 most used physicochemical and biological indicators were able to evaluate 10 environmental stressors which comprise e.g. bacterial load, eutrophication, and organic pollution (Table 3). The degradation and change in water quality, anthropogenic stress, the rise of temperature, eutrophication, the increase of pollution, and cyanobacteria bloom have strong impacts on seven physicochemical metrics and five bioindicators (phytoplankton, diatoms, macroinvertebrates, zooplankton, fish), and make these parameters good indicators of environmental change. The species richness, the diversity and the composition of these aquatic communities vary according to the presence of stressors and environmental parameters (Dey et al. 2023). For example, the distribution of zooplankton species will be most affected by temperature and electrical conductivity, but also by pollution. Machate (Machate et al. 2022) demonstrated the impact of pollution by showing that certain zooplankton species were absent or had low abundance in the most polluted environments. In addition to zooplankton, macroinvertebrates and fish respond strongly to degraded water quality (Marzin et al. 2012). These changes, such as acidification, oxygen depletion or the presence of pollution, will create selection pressure and lead to a loss of biodiversity and/or a change in the most sensitive communities.

Examining the external stressors for aquatic systems in terms of indicators of aquatic ecosystem health revealed that six of the 10 stressors can be directly linked to human health (Fig. 3). Those include a reduction in general water quality, which can have an impact on the taste of drinking water, the increase of pollution and bacterial load, and cyanobacteria bloom, which can cause fever, skin irritation, and increased cancer risks.

Human health impacts measured by aquatic ecosystem indicators included impacts on mental, neurological, and physical health issues (Table 4).

Aquatic ecosystems can also impact human well-being regarding socio-cultural and psychological effects (Table 4). Within these impacts, we can find the reduction of recreational
<table><caption>**Table 3** Indicators linking stressors of ecosystem health to responses to environmental change</caption><thead><tr><th>Indicators</th><th>Potential responses to change</th><th>Sources of disruption of ecosystem health</th><th>References</th></tr></thead><tbody><tr><td>Dissolved Oxygen (DO)</td><td>- Oxygen depletion can increase nitrate and decrease nitrite concentrations<br>- Extremely low and high oxygen concentration impact aquatic organisms<br>- Eutrophication can lead to oxygen depletion, and induce hypoxia or anoxia</td><td>Bacterial load, extreme water temperature, high chemical and biological treatments, and eutrophication</td><td>Rabalais and Nixon (2002), Rose et al. (2019), Karr et al. (2020), Trbojevic et al. (2021), Rose et al. (2023)</td></tr><tr><td>pH</td><td>- High water temperature can decrease pH<br>- Extremely high and low pH values can increase risks of eutrophication, or acidification, and can create a toxic environment for aquatic organisms</td><td>Rise of water temperature (higher than 25 °C)</td><td>Häder et al. (2014), WHO (2017)</td></tr><tr><td>Biochemical Oxygen Demand (BOD) and Chemical Oxygen Demand (COD)</td><td>- High water temperature and low level of dissolved oxygen increase the BOD and COD.<br>- High BOD and COD levels can lead to increased mortality of aquatic life</td><td>Dissolved oxygen level, high water temperature and organic pollution</td><td>Wu et al. (2016), Tampo et al. (2021), Cai et al. (2018)</td></tr><tr><td>Suspended Solids and dissolved solids</td><td>- Pollution increase levels of suspended and dissolved solids, inducing a decrease of phytoplankton biomass, diversity, and can impact the growth of some aquatic organisms</td><td>Quantity of suspended solids, and pollution</td><td>WHO (2017), Madhav et al. (2020), Silwal et al. (2021)</td></tr><tr><td>Ammonia, nitrate, nitrite</td><td>- Pollution leads to nutrient enrichment<br>- High concentration can be toxic for the aquatic organisms<br>- It can lead to eutrophication, algae bloom, perturbation of the nitrogen cycle, acidulation water, and reduction of dissolved oxygen</td><td>Pollution, eutrophication, algal bloom</td><td>Rabalais and Nixon (2002), Camargo and Alonso (2006), Estevez et al. (2017), Scholz-Starke et al. (2018), Karr et al. (2020)</td></tr></tbody></table>

<figure><img src="image_15.png" /></figure>
<table><caption>**Table 3 (continued)**</caption><thead><tr><th>Indicators</th><th>Potential responses to change</th><th>Sources of disruption of ecosystem health</th><th>References</th></tr></thead><tbody><tr><td>Phosphate, phosphorus, orthophosphorus</td><td>- Pollution leads to nutrient enrichment<br/>- High concentration can be toxic for the aquatic organisms<br/>- It can lead to eutrophication, algae bloom</td><td>Pollution, eutrophication, algal bloom</td><td>Rabalais and Nixon (2002), Estevez et al. (2017), Scholz-Starke et al. (2018), Karr et al. (2020)</td></tr><tr><td>Coliforms</td><td>- High coliform concentrations increase bacterial load, and impact aquatic organism health</td><td>Increased bacterial load, domestic sewage, pollution, anthropic activities</td><td>Almeida et al. (2012), Tampo et al. (2021), Wolf et al. (2023)</td></tr><tr><td>Diatoms</td><td>- High sensitivity to environmental changes, organic pollution, and eutrophication<br/>- Induce selection pressure, change in abundances, diversity loss, and increase mortality rate in diatoms community</td><td>Water quality, pH change, extreme nutrient concentrations, organic matters and pollution, extreme levels of dissolved oxygen</td><td>Dixit et al. (1992), Brown et al. (2004)</td></tr><tr><td>Macroinvertebrates</td><td>- Moderate sensitivity to environmental changes, sensitivity to pollution vary depending on the pollutants, and the species<br/>- Induce selection pressure, change in abundances, diversity loss, increase mortality rate, and induce physiological stress</td><td>Water quality (dissolved oxygen, pH...), extreme water temperature, change in conductivity, modification of the habitat, pollution and nutrients enrichment</td><td>Wilhm and Dorris (1968), Reyneldson and Metcalfe-Smith (1992), Verneaux (1994), Brenaman et al. 2000, Barbosa et al. (2001), Lalonde et al. (2016), Wu et al. (2020), Tampo et al. (2021)</td></tr></tbody></table>
<table><caption>**Table 3 (continued)**</caption><thead><tr><th>Indicators</th><th>Potential responses to change</th><th>Sources of disruption of ecosystem health</th><th>References</th></tr></thead><tbody><tr><td>Fish</td><td><ul><li>Moderate sensitivity to environmental changes, sensitivity to pollution vary depending on the pollutants, and the species</li><li>Sensitive to habitat changes and environmental contamination</li><li>Induce selection pressure, modifications of the diversity, increase mortality rate, and induce modifications of the behavior</li></ul></td><td>Water quality (dissolved oxygen, pH...), high chloride and metal concentrations, extreme water temperature, hydrological perturbations</td><td>Moiseenko (2008), Marzin et al. (2012), Karr et al. (2020), Wu et al. (2020), Biswas et al. (2023)</td></tr><tr><td>Zooplankton</td><td><ul><li>High sensitivity to environmental disruption but can vary depending on the species</li><li>Induce selection pressure, diversity loss, increase mortality rate and induce physiological stress</li></ul></td><td>Water quality, extreme water temperature, change in salinity, food availability, pollutant concentration, high pollutant toxicity, and eutrophication</td><td>Karr et al. (2020), Padovesi-Fonseca (2020), Dey et al. (2023), Machate et al. (2022)</td></tr><tr><td>Phytoplankton</td><td><ul><li>High sensitivity to change in water quality and nutrient concentrations can change environment resilience, stress resistance, and sustainability</li><li>Induce selection pressure, diversity loss, and increase mortality rate</li></ul></td><td>Water quality, extreme water temperature, change in water conductivity and channel stability, high biochemical and chemical oxygen demand, and extreme nutrients concentrations</td><td>Prygiel (1994), Brown et al. (2004), Moiseenko (2008), Meng et al. (2009), Zhang (2019), Karr et al. (2020)</td></tr></tbody></table>

<figure><img src="image_16.png" /></figure>
<figure><img src="image_17.png" /><figcaption>**Fig. 3** Crossing external stressors on aquatic ecosystems with their impact indicators and human health. Orange cells indicate a proven positive or negative correlation between the sources of stress and the indicator, based on the literature reviewed. Empty cells indicate an absence of information and verified direct relationship in the reviewed literature (e.g. water temperature only has an indirect impact by changing the visual aspect of the environment or the organisms living in it). Red arrows indicate potentially negative impacts on human health from the changes the indicators are measuring in aquatic ecosystems (see also Table 4)</figcaption></figure>

activities, social and economic isolation, declines in psychological wellbeing, loss of culture and environmental knowledge, and environmental injustice. Other direct impacts are related to damage to human health, such as diseases, allergies, stress, depression, obesity, and immune disorders (Table 4). Based on our assessment, the principal indicators that can have repercussions on human health and well-being are pollutants (e.g. potentially harmful trace elements, microplastics), nutrients (e.g. nitrite), pathogens (e.g. coliforms, cyanotoxins), pathological risk, health of aquatic organisms (e.g. macroinvertebrates, diatoms), and ecosystem services (Table 4).

## Discussion

Here, we reviewed indicators and indices used in the assessment of aquatic ecosystem health and assessed their potential to evaluate human health risks and their well-being. We found that only a few studies approached the notion of ecosystem health in relation to human health (Angermeier et al. 2021), despite the known diverse direct and indirect impacts aquatic ecosystems have on human well-being. None of the studies and indices listed in this review use or include parasites or vectors of infectious diseases in the assessment of ecosystems, even though they can be sources of risk for human health. Those impacts can involve physical, psychological, or socio-cultural elements of human health
<table><caption>**Table 4** Impacts of aquatic ecosystem parameters on human well-being and health</caption><thead><tr><th>Source of modification of aquatic ecosystems</th><th>Impact on human health and well-being</th><th>References</th></tr></thead><tbody><tr><td>Alkalinity and Hardness</td><td>- Impacts the taste of drinking water</td><td>Silwal et al. 2021</td></tr><tr><td>High chloride concentration in ingested water</td><td>- Risk of asthma, hypertension, renal stones, or gastroin- testinal disorders</td><td>Silwal et al. 2021</td></tr><tr><td>Coliforms, waterborne pathogens, toxic aquatic fungi and parasites</td><td>- Increase of the risk of infections and gastroenteritis</td><td>Gibson 2014, Conn 2014, Adlard et al. 2015, Magwaza et al. 2017, McNinch et al. 2009</td></tr><tr><td>Cyanobacteria and cyanotoxins</td><td>- Change in water color, taste and smell<br/>Neurotoxins: interruption of respiratory functions or death<br/>- Microcystins: fever, gastroenteritis, dysfunctions of the liver or liver cancer<br/>- Hapatoxins: risk of cancers<br/>- Dermatotoxines: skin irritation</td><td>Mez et al. 1998, Zanchette and Oliveira-Filho 2013, Codd et al. 1999</td></tr><tr><td>Environmental microbiome</td><td>- Can impact the human respiratory microbiome, inte- tinal microbiome, skin microbiome and the immune system</td><td>Sandifer et al. 2015, Adamovsky et al. 2018</td></tr><tr><td>Potentially harmful trace elements (mercury, arsenic, lead...)</td><td>- Risk of abortion, congenital malformation, gastro- intestinal disorders, dysfunctions of organs, chronic diseases, or cancers</td><td>Mouly et al. 2012, Wu et al. 2013, McNinch et al. 2009, Singh and Kalamdhad 2011</td></tr><tr><td>Microplastics</td><td>- Can impact the nervous system, the respiratory system, digestive system, and can be responsible for infertility, obesity or cancers</td><td>Sharma and Chatterjee 2017, Elizalde-Velasquez and Gómez-Oliván 2021</td></tr><tr><td>Micropollutants (Persistent Organic Pollutants (POPs), Polycyclic Aromatic Hydrocarbons (PAHs), pesti- cides, herbicides, biocides...)</td><td>- Potential disruption of the endocrine functions, the immune system or the nervous system, or risk of cancers</td><td>Kim and Zoh 2016, Knap et al. 2002</td></tr><tr><td>Increase of nitrate or nitrite</td><td>- Impact oxygen transport and can induce Methaemo- globinaemia or impact respiratory functions</td><td>Gupta et al. 2017, Silwal et al. 2021</td></tr><tr><td>Total dissolved solids</td><td>- Impact nervous system, and induce gastrointestinal irritations</td><td>Gupta et al. 2017</td></tr><tr><td>“bad” overall water quality</td><td>- Can lead to skin disease, diarrhea, gastric problems, or respiratory illness</td><td>Halder and Islam 2015</td></tr></tbody></table>

<figure><img src="image_18.png" /></figure>
<table><caption>**Table 4 (continued)**</caption><thead><tr><th>Source of modification of aquatic ecosystems</th><th>Impact on human health and well-being</th><th>References</th></tr></thead><tbody><tr><td>Ecosystem services</td><td><ul><li>Provision of resources, water, food...</li><li>Provide cultural services, recreational activities, cultural and scientific development, improve psychological and physiological health, social interactions, moods and behavior</li></ul></td><td>Limburg 2009, Sandifer et al. 2015</td></tr><tr><td>Biodiversity of the ecosystem</td><td><ul><li>Prevention and reduction of diseases outbreaks, and control of infectious diseases</li></ul></td><td>Sandifer et al. 2015, Grizetti et al. 2016, Pongsiri and Roman 2007</td></tr></tbody></table>

(POPs Persistent Organic Pollutants, PAHs Polycyclic Aromatic Hydrocarbons, pesticides, herbicides, biocides...)

Some stress factors have not been shown to have a direct impact on human health. For example, the pH and alkalinity of water has no direct impact on human health, but may impact human well-being through the taste. Only repeated and excessive consumption of water with a very acid or very alkaline pH may have an impact on human health (Sil-wal et al. 2021)
and well-being. Moreover, only a few studies, mainly in North America, have examined the cumulative effects of various stressors on aquatic ecosystem health (Dube et al. 2006; Crain et al. 2008). Based on our review, we suggest that an adaptation of bioindicators (e.g. phytoplankton, macroinvertebrates), physicochemical parameters, and chemical compounds already in use is needed to widen their application to the assessment of the impact of ecosystems on human well-being.

The main indicators used in biological indices and physicochemical indices found in the literature have been described through the few indices cited. For example, in biological indices, indicators are mainly based on taxonomic metrics such as the richness, abundance or taxonomic composition, or on parameters of sensitivity or tolerance to disturbance, or the presence and ratio of native and non-native species (Birk et al. 2012, Poikane et al. 2015, Poikane et al. 2020). These parameters used in the different available indices are largely overlapping. The main physicochemical indicators used to assess aquatic ecosystems, either via an index or calculated separately, were also analyzed here.

The most suitable and pertinent bioindicators are the ones with a sensitive and fast response to environmental modifications to evaluate the state of the ecosystem over the long term (Adams and Greeley 2000, Roley et al. 2014). Among sensitive bioindicators, diatoms and other phytoplankton species (e.g. cyanobacteria, Sentenac et al. 2023) appear highly suitable, owing to their short development cycle, sensitivity to environmental conditions, organic pollution, and eutrophication, and their rapid response rate (Brown et al. 2004). Monitoring cyanobacteria, indicators of ecosystem degradation (Mateo et al. 2015), has the additional advantage, that they can also inform about the potential presence of potentially harmful cyanotoxins (Sentenac et al. 2023). Toxins can affect humans through oral infection, skin or inhalation during recreational activities, or ingestion of contaminated water or organisms. The human morbidities associated with cyanotoxins are varied including fever, skin irritation, disruption of the gastrointestinal system, and in very rare and severe cases increased risk of cancer (Dash et al. 2015; Christensen and Khan 2020). Their impacts are multiple from disruptions of ecosystem services like water treatment, recreational activities, or economic loss, to the production of hazardous toxins for animals and humans (Mez et al. 1998; Zanchett and Oliveira-Filho 2013). However, there is a lack of standardized methods and experts for phytoplankton identification which makes such indices difficult to use and not always suitable. A metataxiconomic approach targeting diatoms and cyanobacteria might be an advance, but currently available 16S and 18S primers have limited taxonomic resolution (Sentenac et al. 2023) and call for new targeted primer development.

Phytoplankton monitoring indicators should be supplemented by data on macroinvertebrates and fish. They are less sensitive to environmental changes, but easier to identify, while time-consuming to collect (Verneaux 1994, Barbosa et al. 2001). Macroinvertebrate and fish indices can be useful to study the long-term evolution of ecosystems and constitute stable communities and are hence complementary to phytoplankton and zooplankton approaches. Both species groups indicate degradation of water quality, eutrophication, increase in bacterial load and pollution and cyanobacteria blooms, all impacting negatively on human health.

Physico-chemical metrics are easy to use and interpret, and can easily be comparable from different environments if there is a reference state. We identified dissolved oxygen, pH, biochemical oxygen demand, suspended solids, and nutrients as the most useful metrics of aquatic ecosystem health linked to human health risks. They indicate degradation of water quality, eutrophication, and human-induced stress, increasing the risk for human health.
Finally, organic and inorganic contaminants, such as pesticides and heavy metals, are an ever-increasing health issue, even in remote areas (Machate et al. 2022, 2023). Only eight indices in our review used data on organic and inorganic pollution. The quantitative assessment of the concentrations and the presence of organic molecules and of inorganic heavy metal trace elements is generally costly and many molecules are not readily detectable with current sampling and analytical techniques. A broad assessment of environmental contamination would ask for a consequent budget, while more sporadic assessments would not allow to analyze background contamination levels. For example, even in low concentrations of ng/l, two molecules, diazinon and permethrin, crustacean species are affected in remote mountain lakes due to their high toxicity (Machate et al. 2022). In those lakes, the period of exposure to the pesticides and their peak concentrations remain unknown and would not have been detected with sporadic sampling. A broad environmental contaminant monitoring would be needed to allow for a robust analysis of health risks for wildlife, animals, and humans. For the moment, there is a lack of studies on the combined impact of organic and inorganic micropollutants on the health of aquatic ecosystems.

Various indices have been developed to assess the health of aquatic ecosystems over the past decades, but linking them up to human health risks has been insufficient done. Setting up an integrative method with several indices is important. We here have outlined that biodiversity monitoring of diatoms, cyanobacteria, macroinvertebrates and fish, needs to be complemented by environmental monitoring of physicochemical parameters, including nutrients, organic and inorganic pollutants, and pathogens to assess ecosystem health and resulting benefits and risks for human health (Fig. 3). While the water framework directive (WFD, Directive 2000/60/EC) is an important policy tool, which provided a unified set of EU-wide applicable indicators on drinking water, a set of more specified indices and indicators for assessing aquatic ecosystem health, such as the one proposed here, are needed for the assessment of existing and emerging human health risks across the European continent.

**Acknowledgements** We acknowledge this work has been supported and financed by the Interdisciplinary Doctoral Grants fellowship from Toulouse Midi-Pyrénées, the European OneAquaHealth project. D.S.S. holds the AXA Chair for Functional Mountain Ecology funded by the AXA Research Fund through the project GloMEc.

**Author contributions** The idea for the article came from Schmeller Dirk. De Carvalho Fanny and Schmeller Dirk contributed to the conception and design of the study. The literature search, data collection, data analysis, and visualization were performed by De Carvalho Fanny. The supervision and validation were done by Schmeller Dirk, Kelly-Irving Michelle, and Loyau Adeline. The first draft of the manuscript was written by De Carvalho Fanny, and all authors commented and revised on previous versions. All authors read and approved the final manuscript.

**Funding** Open access funding provided by Institut National Polytechnique de Toulouse. This work was supported by the Interdisciplinary Doctoral Grants fellowship from Toulouse Midi-Pyrénées and the AXA Research Fund.

**Data availability** No datasets were generated or analysed during the current study.

## Declarations

**Conflict of interest** The authors have no relevant financial or non-financial interests to disclose.

**Open Access** This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

## References

Abrahão R, Carvalho M, Da Silva W, Machado T, Gadelha C, Hernandez M (2010) Use of index analysis to evaluate the water quality of a stream receiving industrial effluents. Water SA. https://doi.org/10.4314/wsa.v33i4.52940

Adamovsky O, Buerger AN, Wormington AM, Ector N, Griffitt RJ, Bisesi JH, Martyniuk CJ (2018) The gut microbiome and aquatic toxicology: an emerging concept for environmental health: the microbiome and aquatic toxicology. Environ Toxicol Chem 37:2758–2775. https://doi.org/10.1002/etc.4249

Adams SM, Greeley MS (2000) Ecotoxicological indicators of water quality using multi-response indicators to assess the health of aquatic ecosystems. In: Belkin S (ed) Environmental Challenges. Springer, Dordrecht, pp 103–115. https://doi.org/10.1007/978-94-011-4369-1_10

Adlard RD, Miller TL, Smit NJ (2015) The butterfly effect: parasite diversity, environment, and emerging disease in aquatic wildlife. Trends Parasitol 31:160–166. https://doi.org/10.1016/j.pt.2014.11.001

Allardi J (1994) Les poissons comme "indicateur biologique" de l'état des écosystèmes aquatiques Sémi-naire national Hydrosystèmes: état de santé des écosystèmes aquatiques - les variables biologiques comme indicateurs. Paris, 2–3 novembre 1994, 1997, Paris, p 229–241

Almeida C, González SO, Mallea M, González P (2012) A recreational water quality index using chemical, physical and microbiological parameters. Environ Sci Pollu Res 19:3400–3411. https://doi.org/10.1007/s11356-012-0865-5

An K-G, Park SS, Shin J-Y (2002) An evaluation of a river health using the index of biological integrity along with relations to chemical and habitat conditions. Environ Int 28:411–420. https://doi.org/10.1016/S0160-4120(02)00066-1

Angermeier PL, Krometis LA, Stern MJ, Hemby TL (2021) Exploring relationships among stream health, human well-being, and demographics in Virginia, USA. Ecol Indic 121:107194. https://doi.org/10.1016/j.ecolind.2020.107194

Archaimbault V, Dumont B (2010) L'indice biologique global normalisé (IBGN), principes et évolution dans le cadre de la directive cadre européenne sur l'eau. Sciences Eaux & Territoires Numéro 1:36. https://doi.org/10.3917/set.001.0036

Astin LE (2007) Developing biological indicators from diverse data: the potomac basin-wide index of benthic integrity (B-IBI). Ecol Indic 7:895–908. https://doi.org/10.1016/j.ecolind.2006.09.004

Barbosa FAR, Callisto M, Galdean N (2001) The diversity of benthic macroinvertebrates as an indicator of water quality and ecosystem health: a case study for Brazil. Aquat Ecosyst Health Manage 4:51–59. https://doi.org/10.1080/146349801753569270

Barbour MT, Gerritsen J, Snyder BD, & Stribling JB (1999) Rapid Bioassessment Protocols for Use in Streams and Wadeable Rivers: Periphyton, Benthic Macroinvertebrates and Fish, Second Edition EPA 841-B-99-002 US Environmental Protection Agency; Office of Water; Washington

Barua P, Rahman SH (2020) Aquatic health index of coastal aquaculture activities at south-eastern coast of Bangladesh. Water Conserv Manag 4:61–67. https://doi.org/10.26480/wcm.02.2020.61.67

Bennett HH, Mullen MW, Stewart PM, Sawyer JA, Webber EC (2004) Development of an invertebrate community index for an Alabama coastal plain watershed. J Am Water Resour Assoc 40:43–51. https://doi.org/10.1111/j.1752-1688.2004.tb01008.x

Bere T, Mangadze T, Mwedzi T (2014) The application and testing of diatom-based indices of stream water quality in Chinhoyi Town, Zimbabwe. Water SA 40(3):503. https://doi.org/10.4314/wsa.v40i3.14

Bergou N, Hammoud R, Smythe M, Gibbons J, Davidson N, Tognin S, Reeves G, Shepherd J, Mechelli A (2022) The mental health benefits of visiting canals and rivers: an ecological momentary assessment study. PLoS ONE 17(8):e0271306. https://doi.org/10.1371/journal.pone.0271306

Birk S, Bonne W, Borja A, Brucet S, Courrat A, Poikane S, Solimini A, Van De Bund W, Zampoukas N, Hering D (2012) Three hundred ways to assess Europe's surface waters: an almost complete overview of biological methods to implement the water framework directive. Ecol Ind 18:31–41
Biswas JK, Pramanik S, Kuma M (2023) Fish parasites as proxy bioindicators of degraded water quality of River Saraswati. India Environ Monit Assess 195:818. https://doi.org/10.1007/s10661-023-11411-6

Boesch DF, Paul JF (2001) An overview of coastal environmental health indicators. Hum Ecol Risk Assess 7:1409–1417. https://doi.org/10.1080/20018091095096

Boischio A, Sánchez A, Orosz Z, Charron D (2009) Health and sustainable development: challenges and opportunities of ecosystem approaches in the prevention and control of dengue and Chagas disease. Cad Saude Publica 25(Suppl 1):S149–S154. https://doi.org/10.1590/s0102-311x2009001300014

Bordalo A (2001) Water quality and uses of the Bangpakong River (Eastern Thailand). Water Res 35:3635–3642. https://doi.org/10.1016/S0043-1354(01)00079-3

Breneman D, Richards C, Lozano S (2000) Environmental influences on benthic community structure in a Great Lakes embayment. J Great Lakes Res 26:287–304. https://doi.org/10.1016/S0380-1330(00)70693-9

Bridgewater P, Kim RE, Bosselmann K (2014) Ecological integrity: a relevant concept for international environmental law in the anthropocene? Yearb Int Environ Law 25(1):61–78. https://doi.org/10.1093/yiel/yv059

Brown RM, McClelland NI, Deininger RA, Tozer RG (1970) A water quality index: do we dare? Water Sewage Works 117(10):339–343

Brown R, McClelland RM, Deininger NI, Tozer RA (1973) Validating the WQI. Presented at the National Meeting on Water Resources Engineering of the American Society for Civil Engineers, Environmental Indices Theory and Practice, Washington

Brown LE, Sherlock C, Milner AM, Hannah DM, Ledger M (2004) The influence of environmental variables on the distribution of diatom communities in an alpine proglacial stream, Taillon-Babiétous catchment, French Pyrénées. Pirineos 158–159:73–86. https://doi.org/10.3989/pirineos.2004.v158-159.50

Burkhard B, Müller F, Lill A (2008) Ecosystem health indicators. Encyclopedia of ecology. Academic Press, Oxford, pp 1132–1138

Cai Y, Fu X, Gao X, Li L (2018) Research progress of on-line automatic monitoring of chemical oxygen demand (COD) of water. IOP Conf. Ser. Earth Environ. Sci. 121:022039. https://doi.org/10.1088/1755-1315/121/2/022039

Cai W, Xia J, Yang M, Wang W, Dou C, Zeng Z, Dong S, Sheng L (2020) Cross-basin analysis of freshwater ecosystem health based on a zooplankton-based Index of Biotic Integrity: models and application. Ecol Indic 114:106333. https://doi.org/10.1016/j.ecolind.2020.106333

Cairns J (1995) Ecological integrity of aquatic systems. Regul Rivers Res Manage 11:313–323. https://doi.org/10.1002/rrr.3450110307

Camargo JA, Alonso Á (2006) Ecological and toxicological effects of inorganic nitrogen pollution in aquatic ecosystems: a global assessment. Environ Int 32:831–849. https://doi.org/10.1016/j.envint.2006.05.002

Canadian Council of Ministers of the Environment (2001) Canadian Water Quality Guidelines for the Protection of Aquatic Life: CCME Water Quality Index 1.0, User's Manual. Canadian Environmental Quality Guidelines 1999, Canadian Council of Ministers of the Environment, Winnipeg

Carlson RE (1977) A trophic state index for lakes. Limnol Oceanogr 22:361–369. https://doi.org/10.4319/lo.1977.22.2.0361

Carlson RE, Simpson J (1996) A coordinator's guide to volunteer lake monitoring methods. North Am Lake Manage Soc 96:305

Cavicchioli R, Ripple WJ, Timmis KN, Azam F, Bakken LR, Baylis M, Behrenfeld MJ, Boetius A, Boyd PW, Classen AT, Crowther TW, Danovaro R, Foreman CM, Huisman J, Hutchins DA, Jansson JK, Karl DM, Koskella B, Mark Welch DB, Martiny JBH, Moran MA, Orphan VJ, Reay DS, Remais JV, Rich VI, Singh BK, Stein LY, Stewart FJ, Sullivan MB, van Oppen MJH, Weaver SC, Webb EA, Webster NS (2019) Scientists' warning to humanity: microorganisms and climate change. Nat Rev Microbiol. https://doi.org/10.1038/s41579-019-0222-5

CEMAGREF, AERMC (1982) Etude des méthodes biologiques d'appréciation quantitative de la qualité des eaux. Agence de l'eau Rhône Méditerranée Corse. https://www/documentation.eauetbiodiverse.fr/notice/etude-des-méthodes-biologiques-d-appréciation-quantitative-de-la-qualité-des-eaux0

Chen J, Wang Y, Li F, Liu Z (2019) Aquatic ecosystem health assessment of a typical sub-basin of the Liao River based on entropy weights and a fuzzy comprehensive evaluation method. Sci Rep 9:14045. https://doi.org/10.1038/s41598-019-50499-0

Chen H, Li W, Zuo Q, Zhang Y, Liang S (2022) Evaluation of aquatic ecological health of sluice-controlled rivers in Huai River Basin (China) using evaluation index system. Environ Sci Pollut Res 29:65128–65143. https://doi.org/10.1007/s11356-022-20252-8
Chesters RK (1980) Biological monitoring working party: the 1978 national testing exercise. Department of the Environment, Water Data Unit

Christensen VG, Khan E (2020) Freshwater neurotoxins and concerns for human, animal, and ecosystem health: a review of anatoxin-a and saxitoxin. Sci Total Environ 736:139515. https://doi.org/10.1016/j.scitotenv.2020.139515

Codd G, Bell S, Kaya K, Ward C, Beattie K, Metcalf J (1999) Cyanobacterial toxins, exposure routes and human health. Eur J Phycol 34:405–415. https://doi.org/10.1080/09670269910001736462

Conn DB (2014) Aquatic invasive species and emerging infectious disease threats: a one health perspective. Aquat Invasions 9:383–390. https://doi.org/10.3391/ai.2014.9.3.12

Costanza R, Mageau M (1999) What is a healthy ecosystem? Aquat Ecol 33:105–115. https://doi.org/10.1023/A:1009930313242

Crain CM, Kroeker K, Halpern BS (2008) Interactive and cumulative effects of multiple human stressors in marine systems. Ecol Lett 11:1304–1315. https://doi.org/10.1111/j.1461-0248.2008.01253.x

Cude CG (2001) Oregon water quality index a tool for evaluating water quality management effectiveness. J Am Water Resour Assoc 37:125–137. https://doi.org/10.1111/j.1752-1688.2001.tb05480.x

Dash P, Silwal S, Ikenga J, Pinckney J, Arslan Z, Lizotte R (2015) Water quality of four major lakes in Mississippi, USA: impacts on human and aquatic ecosystem health. Water 7:4999–5030. https://doi.org/10.3390/w7094999

De Moor FC (2017) Dragonflies as indicators of aquatic ecosystem health. S Afr J Sci. https://doi.org/10.17159/sajs.2017/a0199

Dell’Uomo A, Torrisi M, Corsini A, Cavalieri S (2004) L’indice diatomico di eutrofizzazione/pol-luzione (EPI-D) nel monitoraggio delle acque correnti: linee guida. Agenzia per la protezione dell’ambiente e per i servizi tecnici.

Descy JP, Coste M (1991) A test of methods for assessing water quality based on diatoms. SIL Proc 24:2112–2116. https://doi.org/10.1080/03680770.1989.11899905

DeShon JE (1995) Development and application of the invertebrate community index (ICI). In: Davis WS, Simon TP (eds) Biological assessment and criteria—tools for water resource planning and decision making. Lewis Publishers, Boca Raton, pp 217–244

Devic G, Ørdevic D, Sakan S (2014) Freshwater environmental quality parameters of man-made lakes of Serbia. Environ Monit Assess 186:5221–5234. https://doi.org/10.1007/s10661-014-3771-0

Dey S, Samanta P, Ratan Ghosh A (2023) Assessment of aquatic ecological health: a comparative study between cistern-made and ‘Natural’ earthen-made waterbody. Watershed Ecol Environ 5:88–99. https://doi.org/10.1016/j.wsee.2023.02.001

Dinius SH (1987) Design of an index of water quality. J Am Water Resour Assoc 23:833–843. https://doi.org/10.1111/j.1752-1688.1987.tb02959.x

Dixit SS, Smol JP, Kingston JC, Charles DF (1992) Diatoms: powerful indicators of environmental change. Environ Sci Technol 26:22–33. https://doi.org/10.1021/es00025a002

Dojlido JAN, Raniszewski J, Woyciechowska J (1994) Water quality index applied to rivers in the Vis-tula river basin in Poland. Environ Monit Assess 33:33–42. https://doi.org/10.1007/BF00546659.

Dubé M, Johnson B, Dunn G, Culp J, Cash K, Munkittrick K, Wong I, Hedley K, Booty W, Lam D, Resler O, Storey A (2006) Development of a new approach to cumulative effects assessment: a northern river ecosystem example. Environ Monit Assess 113:87–115. https://doi.org/10.1007/s10661-005-9098-0

Dunn GW (1995) Trends in water quality variables at the Alberta/Saskatchewan Boundary. Prepared For The Committee On Water Quality.

Dunnette DA (1979) A geographically variable water quality index used in Oregon. Water Pollut Control Fed 51:53–61

Elizalde-Velázquez GA, Gómez-Oliván LM (2021) Microplastics in aquatic environments: a review on occurrence, distribution, toxic effects, and implications for human health. Sci Total Environ 780:146551. https://doi.org/10.1016/j.scitotenv.2021.146551

Estevez E, Rodríguez-Castillo T, Álvarez-Cabria M, Peñas FJ, González-Ferreras AM, Lezcano M, Barquín J (2017) Analysis of structural and functional indicators for assessing the health state of mountain streams. Ecol Indic 72:553–564. https://doi.org/10.1016/j.ecolind.2016.08.052

European Parliament, Council of the European Union, 23 October 2000, European WaterFramework Directive, EU directive 2000/60/EC

Fetscher AE, Sutula MA, Busse LB, Stein ED (2013) Condition of California perennial, wadeable streams based on algal indicators. Final Technical Report 2007–11 prepared for the California State Water Board. Southern California Coastal Water Research Project and San Diego Regional Water Quality Control Board, Costa Mesa, California
Flint N, Rolfe J, Jones CE, Sellens C, Johnston ND, Ukkola L (2017) An ecosystem health index for a large and variable river basin: methodology, challenges and continuous improvement in Queensland's Fitzroy Basin. Ecol Indic 73:626–636. https://doi.org/10.1016/j.ecolind.2016.10.007

Gazzaz NM, Yusoff MK, Aris AZ, Juahir H, Ramli MF (2012) Artificial neural network modeling of the water quality index for Kinta River (Malaysia) using water quality variables as predictors. Mar Pollut Bull 64:2409–2420. https://doi.org/10.1016/j.marpolbul.2012.08.005

Gibson KE (2014) Viral pathogens in water: occurrence, public health impact, and available control strategies. Curr Opin Virol 4:50–57. https://doi.org/10.1016/j.coviro.2013.12.005

Grieco JP, Johnson S, Achee NL, Masuoka P, Pope K, Rejmánková E, Vanzie E, Andre R, Roberts D (2006) Distribution of *Anopheles albimanus*, *Anopheles vestitipennis*, and *Anopheles crucians* associated with land use in northern Belize. J Med Entomol 43(3):614–622. https://doi.org/10.1603/0022-2585(2006)43[614:doaaav]2.0.co;2

Grizzetti B, Lanzanova D, Liquete C, Reynaud A, Cardoso AC (2016) Assessing water ecosystem services for water resource management. Environ Sci Policy 61:194–203. https://doi.org/10.1016/j.envsci.2016.04.008

Gupta N, Pandey P, Hussain J (2017) Effect of physicochemical and biological parameters on the quality of river water of Narmada, Madhya Pradesh, India. Water Sci 31:11–23. https://doi.org/10.1016/j.wsj.2017.03.002

Haase P, Tonkin JD, Stoll S, Burkhard B, Frenzel M, Geijzendorffer IR, Häusser C, Klotz S, Kühn I, McDowell WH, Mirtl M, Müller F, Musche M, Penner J, Zacharias S, Schmeller DS (2018) The next generation of site-based long-term ecological monitoring: linking essential biodiversity variables and ecosystem integrity. Sci Total Environ 613–614:1376–1384. https://doi.org/10.1016/j.scitotenv.2017.08.111

Häder DP, Villafañe VE, Helbling EW (2014) Productivity of aquatic primary producers under global climate change. Photochem Photobiol Sci 13:1370–1392. https://doi.org/10.1039/c3pp50418b

Halder J, Islam N (2015) Water pollution and its impact on the human health. J Environ Hum 2:36–46. https://doi.org/10.15764/EH.2015.01005

Hanh TMP, Sthiannopkao S, The Ba D, Kim KW (2011) Development of water quality indexes to identify pollutants in Vietnam's surface water. J Environ Eng 137:273–283. https://doi.org/10.1061/(ASCE)EE.1943-7870.0000314

Hansen AJ, Noble BP, Veneros J, East A, Goetz SJ, Supples C, Watson JEM, Jantz PA, Pillay R, Jetz W, Ferrier S, Grantham HS, Evans TD, Ervin J, Venter O, Virnig ALS (2021) Toward monitoring forest ecosystem integrity within the post-2020 global biodiversity framework. Conserv Lett. https://doi.org/10.1111/conl.12822

Herman MR, Nejadhashemi AP (2015) A review of macroinvertebrate- and fish-based stream health indices. Ecohydrol Hydrobiol 15:53–67. https://doi.org/10.1016/j.ecohyd.2015.04.001

Hilsenhoff WL (1982) Using a biotic index to evaluate water quality in streams. Madison, Wisconsin: Wisconsin Department of Natural Resources. Tech Bull 132:1982

Hooper DU, Chapin Iii FS, Ewel JJ, Hector A, Schmid B, Inchausti P, Lavorel S, Lawton JH, Lodge DM, Loreau M, Naeem S, Setäla H, Symstad AJ, Vandermeer J, Wardle DA (2005) Effects of biodiversity on ecosystem functioning: a consensus of current knowledge. Ecol Monogr 75:3–35. https://doi.org/10.1890/04-0922

Horton RK (1965) An index number system for rating water quality. J Water Pollut Control Fed 37:300–306

Horwitz P, Finlayson CM (2011) Wetlands as settings for human health: incorporating ecosystem services and health impact assessment into water resource management. Bioscience 61:678–688. https://doi.org/10.1525/bio.2011.61.9.6

House MA (1989) A water quality index for river management. Water Environ J 3:336–344. https://doi.org/10.1111/j.1747-6593.1989.tb01538.x

Hoyle JA, Boston CM, Chu C, Yuille MJ, Portiss R, Randall RG (2018) Fish community indices of ecosystem health: how does Toronto Harbour compare to other Lake Ontario nearshore areas? Aquat Ecosystem Health Manage 21:306–317. https://doi.org/10.1080/14634988.2018.1502562

Jax K, Heink U (2016) Human Well-Being: In: Potschin M, Jax K (eds) OpenNESS Ecosystem Services Reference Book. EC FP7 Grant Agreement no. 308428. Available via: www.opennessproject.eu/libra ry/reference-book

Johnson PTJ, Paull SH (2011) The ecology and emergence of diseases in fresh waters: freshwater diseases. Freshw Biol 56:638–657. https://doi.org/10.1111/j.1365-2427.2010.02546.x

Johnson PTJ, Chase JM, Dosch KL, Hartson RB, Gross JA, Larson DJ, Sutherland DR, Carpenter SR (2007). Aquatic eutrophication promotes pathogenic infection in amphibians. The Proceedings of the National Academy of Sciences USA. 104, 15781–15786. https://doi.org/10.1073/pnas.0707763104
Jordan SJ, Lewis MA, Harwell LM, Goodman LR (2010) Summer fish communities in northern Gulf of Mexico estuaries: indices of ecological condition. Ecol Indic 10(2):504–515. https://doi.org/10.1016/j.ecolind.2009.09.003

Kane DD, Gordon SI, Munawar M, Charlton MN, Culver DA (2009) The planktonic index of biotic integrity (P-IBI): an approach for assessing lake ecosystem health. Ecol Indic 9:1234–1247. https://doi.org/10.1016/j.ecolind.2009.03.014

Kang H, Jin Jeon D, Kim S, Jung K (2022) Estimation of fish assessment index based on ensemble artificial neural network for aquatic ecosystem in South Korea. Ecol Indic 136:108708. https://doi.org/10.1016/j.ecolind.2022.108708

Karr JR (1981) Assessment of biotic integrity using fish communities. Fisheries 6:21–27. https://doi.org/10.1577/1548-8446(1981)006%3c0021:AOBIUF%3e2.0.CO;2

Karr J (2011) Ecological integrity: an essential ingredient for humans’ long-term success. In: Westra L, Bosselmann K, Soskolne CL (eds) Globalisation and ecological integrity in science and international law. Cambridge Scholars, Newcastle upon Tyne, pp 8–25

Karr JR, Chu EW (1995) Ecological integrity: reclaiming lost connections. In: Westra L, Lemons J (eds) Perspectives on ecological integrity, environmental science and technology library. Springer, Dordrecht, pp 34–48

Karr JR, Fausch KD, Angermeier PL, Yant PR, Schlosser IJ (1986) Assessing biological integrity in running waters: a method and its rationale. Illinois Natural History Survey Special Publication 5. 28

Karr JR, Chu EW, Yoder CO (2020) Biological integrity and ecological health: making the most of lessons from systematic biomonitoring. In: Newman MC (ed) Fundamentals of ecotoxicology: the science of pollution, 5th edn. CRC Press, Boca Raton, pp 373–383

Kelly MG, Whitton BA (1995) The trophic diatom index: a new index for monitoring eutrophication in rivers. J Appl Phycol 7:433–444. https://doi.org/10.1007/BF00003802

Kerans BL, Karr JR (1994) A benthic index of biotic integrity (B-IBI) for rivers of the Tennessee Valley. Ecol Appl 4:768–785. https://doi.org/10.2307/1942007

Kim MK, Zoh KD (2016) Occurrence and removals of micropollutants in water environment. Environ Eng Res 21:319–332. https://doi.org/10.4491/eer.2016.115

Kim J-Y, Lee BT, Shin KH, Lee KY, Kim KW, An KG, Park YS, Kim JY, Kwon YH (2007) Ecological health assessment and remediation of the stream impacted by acid mine drainage of the Gwangyang mine area. Environ Monit Assess 129:79–85. https://doi.org/10.1007/s10661-006-9429-9

Klemm DJ, Stober QJ, Lazorchak JM (1993) Fish field and laboratory methods for evaluating the biological integrity of surface waters. Cincinnati, Ohio: Environmental Monitoring Systems Laboratory-Cincinnati, Office of Modeling, Monitoring Systems, and Quality Assurance, Office of Research and Development, U.S. Environmental Protection Agency

Knap A, Dewailly E, Furgal C, Galvin J, Baden D, Bowen RE, Depledge M, Duguay L, Fleming LE, Ford T, Moser F, Owen R, Suk WA, Unluata U (2002) Indicators of ocean health and human health: developing a research and monitoring framework. Environ Health Perspect 110:839–845. https://doi.org/10.1289/ehp.02110839

Lackey RT (2001) Values, policy, and ecosystem health. Bioscience 51:437–443. https://doi.org/10.1641/0006-3568(2001)051[0437:VPAEH]2.0.CO;2

Lalonde BA, Garron C, Mercier V (2016) Analysis of benthic invertebrate communities downstream of land-based aquaculture facilities in Nova Scotia, Canada. Cogent Environ Sci 2:1136099. https://doi.org/10.1080/23311843.2015.1136099

Le Provost G, Schenk NV, Penone C, Thiele J, Westphal C, Allan E, Ayasse M, Blüthgen N, Boeddinghaus RS, Boesing AL (2023) The supply of multiple ecosystem services requires biodiversity across spatial scales. Nat Ecol Evol 7:236–249. https://doi.org/10.1038/s41559-022-01918-5

Leclercq L, Maquet B (1987) Deux nouveaux indices diatomiques et de qualité chimique des eaux couvrantes. Comparaison avec différents indices existants. Cah Biol Mar 28:303–310

Lerner H, Berg C (2017) A comparison of three holistic approaches to health: one health, ecohealth, and planetary health. Front Vet Sci. https://doi.org/10.3389/fvets.2017.00163

Limburg KE (2009) Aquatic ecosystem services. Encyclopedia of inland waters. Elsevier, Amsterdam, pp 25–30

Liou SM, Lo SL, Wang SH (2004) A generalized water quality index for Taiwan. Environ Monit Assess 96:35–52. https://doi.org/10.1023/B:EMAS.0000031715.83752.al

Liu L, Xu Z, Yin X, Li F, Dou T (2017) Development of a multimetric index based on benthic macroinvertebrates for the assessment of urban stream health in Jinan City. China Environ Monit Assess 189:205. https://doi.org/10.1007/s10661-017-5920-8

Machate O, Schmeller DS, Loyau A, Paschke A, Krauss M, Carmona E, Schulze T, Moyer A, Lutz K, Brack W (2022) Complex chemical cocktail, containing insecticides diazinon and permethrin, drives acute
toxicity to crustaceans in mountain lakes. Sci Total Environ. https://doi.org/10.1016/j.scitotenv.2022.154456

Machate O, Schmeller DS, Schulze T, Brack W (2023) Review: mountain lakes as freshwater resources at risk from chemical pollution. Environ Sci Eur 35:3. https://doi.org/10.1186/s12302-022-00710-3

Madhav S, Ahamad A, Singh AK, Kushawaha J, Chauhan JS, Sharma S, Singh P (2020) Water pollutants: sources and impact on the environment and human health. In: Pooja D, Kumar P, Singh P, Patil S (eds) Sensors in water pollutants monitoring: role of material, advanced functional materials and sensors. Springer, Singapore, pp 43–62

Magwaza N, Nxumalo E, Mamba B, Msagati T (2017) The occurrence and diversity of waterborne fungi in African aquatic systems: their impact on water quality and human health. Int J Environ Res Public Health 14:546. https://doi.org/10.3390/ijerph14050546

Martinez-Juarez P, Chiabai A, Taylor T, Quiroga Gómez S (2015) The impact of ecosystems on human health and well-being: a critical review. J Outdoor Recreat Tour 10:63–69. https://doi.org/10.1016/j.jort.2015.06.008

Marzin A, Archaimbault V, Belliard J, Chauvin C, Delmas F, Pont D (2012) Ecological assessment of running waters: do macrophytes, macroinvertebrates, diatoms and fish show similar responses to human pressures? Ecol Indic Vol 23:56–65. https://doi.org/10.1016/j.ecolind.2012.03.010

Mateo P, Leganés F, Perona E, Loza V, Fernandez-Pinas F (2015) Cyanobacteria as bioindicators and bioreporters of environmental analysis in aquatic ecosystems. Biodiversity Conserv 24:909–948. https://doi.org/10.1007/s10531-015-0903-y

McNinch RM, Rose JB, Dreelin EA (2009) Aquatic ecosystems and human health. Encyclopedia of inland waters. Elsevier, Amsterdam, pp 13–20

Meng W, Zhang N, Zhang Y, Zheng B (2009) Integrated assessment of river health based on water quality, aquatic life and physical habitat. J Environ Sci 21:1017–1027. https://doi.org/10.1016/S1001-0742(08)62377-3

Mez K, Hanselmann K, Preisig HR (1998) Environmental conditions in high mountain lakes containing toxic benthic cyanobacteria. Hydrobiologia 368:1–15. https://doi.org/10.1023/A:1003224032079

Millennium Ecosystem Assessment (2005) Ecosystems and human well-being: wetlands and water. World Resources Institute, Washington

Miller SJ, Wardrop DH, Mahaney WM, Brooks RP (2006) A plant-based index of biological integrity (IBI) for headwater wetlands in central Pennsylvania. Ecol Indic 6:290–312. https://doi.org/10.1016/j.ecolind.2005.03.011

Miró A, O’Brien D, Tomàs J, Buchaca T, Sabàs I, Osorio V, Lucati F, Pou-Rovira Q, Ventura M (2019) Rapid amphibian community recovery following removal of non-native fish from high mountain lakes. Biol Conserv. https://doi.org/10.1016/j.biocon.2020.108783

Moiseenko TI (2008) The concept of ecosystem health in water quality assessment and rating of anthropogenic loads. Russ J Ecol 39:390–397. https://doi.org/10.1134/S1067413608060027

Moore M, Townsend M, Oldroyd J (2007) Linking human and ecosystem health: the benefits of community involvement in conservation groups. EcoHealth 3:255–261. https://doi.org/10.1007/s10393-006-0070-4

Mouly D, Jusot JF, Bérat B, Goria S, Stempfelet M, Beau DU P (2012) Étude de la relation entre l'exposition chronique à l'arsenic hydrique d'origine naturelle et la survenue de cancers en Auvergne. Environ Risques Sante. https://doi.org/10.1684/ers.2012.0548

Naqeeb NAA, Hassany JSA, Mashi FK (2020) Assessment of the water quality of Um El-Naaj Marshes by Diatoms. Ecol Environ Conserv Paper 26(1):405–410

Narayan D, Chambers R, Shah MK, Petesch P (2000) Crying out for change: voices of the poor. World Bank. https://doi.org/10.1596/0-1952-1602-4

Newman S, Reantaso MB (2010) One health – integrating aquatic biosecurity into the way forward - a natural progression. Environ Sci 45:42–45

Nguyen N, Sevando M (2019) Assessing coastal water quality through an overall index. Polish J Environ Stud 28:2321–2330. https://doi.org/10.15244/pjoes/90836

Padovesi-Fonseca C (2020) Potential use of zooplankton as ecological quality indicator according to water framework directive (WFD) in central Brazilian reservoir. Ocean Fish Open Access J. https://doi.org/10.19080/OFOAJ.2020.11.555814

Padua S, Kripa V, Prema D, Mohamed KS, Jeyabaskaran R, Kaladharan P, Ratheesh L, Jenny B, Shylaja G, Joseph RV, Shyamala MP, Vysakhan P, John S, Babu A (2023) Assessment of ecosystem health of a micro-level Ramsar coastal zone in the Vembanad Lake, Kerala, India. Environ Monit Assess 195:95. https://doi.org/10.1007/s10661-022-10692-7

Pantus FJ, Dennison WC (2005) Quantifying and evaluating ecosystem health: a case study from Moreton Bay, Australia. Environ Manage 36:757–771. https://doi.org/10.1007/s00267-003-0110-6
Poikane S, Birk S, Böhmer J, Carvalho L, De Hoyos C, Gassner H, Hellsten S, Kelly M, Solheim AL, Olin M, Pall K (2015) A hitchhiker's guide to European lake ecological assessment and intercalibration. Ecol Indic 52:533–544

Poikane S, Herrero FS, Kelly MG, Borja A, Birk S, van de Bund W (2020) European aquatic ecological assessment methods: a critical review of their sensitivity to key pressures. Sci Total Environ 740:140075

Pongsiri MJ, Roman J (2007) Examining the links between biodiversity and human health: an inter-disciplinary research initiative at the U.S. Environmental Protection Agency. EcoHealth 4:82–85. https://doi.org/10.1007/s10393-007-0087-3

Pont D, Hugueny B, Rogers C (2007) Development of a fish-based index for the assessment of river health in Europe: the European fish index. Fish Manage Ecol 14(6):427–439. https://doi.org/10.1111/j.1365-2400.2007.00577.x

Prygiel J (1994) Comparaison de six indices diatomiques et deux indices invertébrés pour l'estimation de la qualité de l'eau de la rivière Sensée (France). Ecologia Mediterranea 20:121–133. https://doi.org/10.3406/ecmed.1994.1736

Prygiel J, Coste M (1993) The assessment of water quality in the Artois-Picardie water basin (France) by the use of diatom indices. Hydrobiologia 269–270:343–349. https://doi.org/10.1007/BF00028033

Prygiel J, Coste M (2000) Guide méthodologique pour la mise en œuvre de l'Indice Biologique Diatomées NF T 90-354. Agence de l'eau Artois Picardie, pp 340

Prygiel J, Lévêque L, Iserentant R (1996) Un nouvel Indice Diatomique Pratique pour l'évaluation de la qualité des eaux en réseau de surveillance. Revue des Sciences De L'eau / J Water Sci 9(1):97–113. https://doi.org/10.7202/705244ar

Rabalais NN, Nixon SW (2002) Nutrient over-enrichment in coastal waters: global patterns of cause and effect. Estuarine Research Federation

Reader MO, Eppinga MB, De Boer HJ, Damm A, Petchey OL, Santos MJ (2023) Biodiversity mediates relationships between anthropogenic drivers and ecosystem services across global mountain, island and delta systems. Global Environ Change 78:102612. https://doi.org/10.1016/j.gloenvcha.2022.102612

Reynoldson TB, Metcalfe-Smith JL (1992) An overview of the assessment of aquatic ecosystem health using benthic invertebrates. J Aquat Ecosystem Health 1:295–308. https://doi.org/10.1007/BF00044171

Ripple WJ, Wolf C, Newsome TM, Galetti M, Alamgir M, Crist E, Mahmoud MI, Laurance WF (2017) World scientists' warning to humanity: a second notice. Bioscience 67:1026–1028. https://doi.org/10.1093/biosci/bix125

Ripple WJ, Wolf C, Newsome TM, Gregg JW, Lenton TM, Palomo I, Eikelboom JAJ, Law BE, Huq S, Duffy PB, Rockström J (2021) World scientists' warning of a climate emergency 2021. Bioscience 71:894–898. https://doi.org/10.1093/biosci/biab079

Roley SS, Griffiths JR, Levi PS, Patrick CJ, Sadro S, Zarnetske JP (2014) Taking the pulse of the ecosystem: progress in quantifying aquatic ecosystem health. Limnol Oceanogr, Eco-DAS X symposium, p 88–105. https://doi.org/10.4319/ecodas.2014.978-0-9845591-4-5-88

Rose KA, Gutiérrez D, Breitburg D, Conley D, Craig JK, Jeyabaskaran R, Kripa V, Mbaye BC, Mohamed KS, Padua S, Prema D (2019) Impacts of ocean deoxygenation on fisheries. Ocean deoxygenation: Everyone's problem - Causes, impacts, consequences and solutions. Gland

Rose KC, Bierwagen B, Bridgham SD, Carlisle DM, Hawkins CP, Poff NL, Read JS, Rohr JR, Saros JE, Williamson CE (2023) Indicators of the effects of climate change on freshwater ecosystems. Clim Change 176:23. https://doi.org/10.1007/s10584-022-03457-1

Ross TJ (1995) Fuzzy logic with engineering applications, 1st edn. Wiley, Hoboken

Rumeau A, Coste M (1988) Initiation à la systématique des diatomées d'eau douce. Pour l'utilisation pratique d'un indice diatomique générique. Knowledge & Management of Aquatic Ecosystems. Issue "Bull Fr Pêche Piscic", p 1–69. https://doi.org/10.1051/kmae:1988009

Saha A, Zaman S, Mitra A (2017) Assessment of coastal water quality using aquatic health index (AHI). Parana J Sci Edu (PJSE) 3(6):34–41. https://doi.org/10.5281/zenodo.3818507

Said A, Stevens DK, Sehlk G (2004) An innovative index for evaluating water quality in streams. Environ Manage 34:406–414. https://doi.org/10.1007/s00267-004-0210-y

Samways MJ, Simaika JP (2008) Manual of freshwater assessment for South Africa: dragonfly biotic index. J Insect Conserv 21:581–582. https://doi.org/10.1007/s10841-017-9984-0

Sandifer PA, Sutton-Grier AE, Ward BP (2015) Exploring connections among nature, biodiversity, ecosystem services, and human health and well-being: opportunities to enhance health and biodiversity conservation. Ecosyst Ser 12:1–15. https://doi.org/10.1016/j.ecoser.2014.12.007
Schiefele S, Schreiner C (1991) Use of diatoms for monitoring nutrient enrichment, acidification and impact of salt in rivers in Germany and Austria. In: Whitton BA, Rott E, Friedrich G (eds) Use of algae for monitoring rivers. Institut für Botanik Universität Innsbruck, Innsbruck, pp 103–110

Schmeller DS, Weatherdon LV, Loyau A, Bondeau A, Brotons L, Brummitt N, Geijzendorffer IR, Haase P, Kuemmerlen M, Martin CS, Mihoub JB, Rocchini D, Saarenmaa H, Stoll S, Regan EC (2018) A suite of essential biodiversity variables for detecting critical biodiversity change. *Biol Rev* 93:55–71. https://doi.org/10.1111/brv.12332

Schmeller DS, Courchamp F, Killeen G (2020) Biodiversity loss, emerging pathogens and human health risks. *Biodivers Conserv* 29:3095–3102. https://doi.org/10.1007/s10531-020-02021-6

Schmeller DS, Urbach D, Bates K, Catalan J, Cogălniceanu D, Fisher MC, Friesen J, Füreder L, Gaube V, Haver M, Jacobsen D, Le Roux G, Lin Y-P, Loyau A, Machate O, Mayer A, Palomo I, Plutzar C, Sentenac H, Sommaruga R, Tiberti R, Ripple WJ (2022) Scientists’ warning of threats to mountains. *Sci Total Environ*. https://doi.org/10.1016/j.scitotenv.2022.158611

Scholz-Starke B, Bo L, Holbach A, Norra S, Floehr T, Hollert H, Roß-Nickoll M, Schäffer A, Ottermanns R (2018) Simulation-based assessment of the impact of fertiliser and herbicide application on freshwater ecosystems at the Three Gorges Reservoir in China. *Sci Total Environ* 639:286–303. https://doi.org/10.1016/j.scitotenv.2018.05.057

Scotti M, Bondavalli C, Rossetti G, Bodini A (2022) Flow network indices signal a directional change in ecosystems: evidence from a small mountain lake (Lake Santo, northern Italy). *Ecol Indic* 139:108896. https://doi.org/10.1016/j.ecolind.2022.108896

Scrimgeour GJ, Wicklum D (1996) Aquatic ecosystem health and integrity: problems and potential solutions. *J N Am Benthol Soc* 15:254–261. https://doi.org/10.2307/1467951

Sentenac H, Loyau A, Zoccarato L, Jassey VEJ, Grossart HP, Schmeller DS (2023) Biofilm community composition is changing in remote mountain lakes with a relative increase in potentially toxigenic algae. *Water Res* 245:120547. https://doi.org/10.1016/j.watres.2023.120547

Shannon CE (1963) A mathematical theory of communication. *Bell Syst Tech J* 27:379–423

Sharma S, Chatterjee S (2017) Microplastic pollution, a threat to marine ecosystem and human health: a short review. *Environ Sci Pollut Res* 24:21530–21547. https://doi.org/10.1007/s11356-017-9910-8

Silwal P, Prajapati R, Thapa BR, Talchabhadel R, Kafle AS, Davids JC (2021) Assessment of groundwater quality by using water quality index (WQI): a case study of Bhaktapur municipality. *Bull Nepal Hydrogeol Assoc* 6:43

Simčič T, Brancelj A (2009) Ecosystem health index (EHI) and electron transport system (ETS) activity of plankton and sediment in two lakes differing in trophic status. *Fundam Appl Limnol* 175(4):317–326. https://doi.org/10.1127/1863-9135/2009/0175-0317

Singh J, Kalamdhad AS (2011) Effects of heavy metals on soil, plants, human health and aquatic life. *Int J Res Chem Environ* 1(2):15–21

Sládeček V (1986) Diatoms as indicators of organic pollution. *Acta Hydrochim Et Hydrobiol* 14:555–566. https://doi.org/10.1002/aheh.19860140519

Smith DG (1990) A better water quality indexing system for rivers and streams. *Water Res* 24:1237–1244. https://doi.org/10.1016/0043-1354(90)90047-A

Stambuk-Giljanovic N (1999) Water quality evaluation by index in Dalmatia. *Water Res* 33:3423–3440. https://doi.org/10.1016/S0043-1354(99)00063-9

Steinhart CE, Schierow LJ, Sonzogni WC (1982) An environmental quality index for the Great Lakes. *J Am Water Resour Assoc* 18:1025–1031. https://doi.org/10.1111/j.1752-1688.1982.tb00110.x

Stenger-Kovács C, Lengyel E, Crossetti LO, Üveges V, Padisák J (2013) Diatom ecological guilds as indicators of temporally changing stressors and disturbances in the small Torna-stream, Hungary. *Ecol Indic* 24:138–147. https://doi.org/10.1016/j.ecolind.2012.06.003

Stewart JR, Gast RJ, Fujioka RS, Solo-Gabriele HM, Meschke JS, Amaral-Zettler LA, Del Castillo E, Polz MF, Collier TK, Strom MS, Sinigalliano CD, Moeller PD, Holland AF (2008) The coastal environment and human health: microbial indicators, pathogens, sentinels and reservoirs. *Environ Health* 7:S3. https://doi.org/10.1186/1476-069X-7-S2-S3

Stringhini S, Carmeli C, Jokela M, Avendaño M, Muennig P, Guida F, Ricceri F, d'Errico A, Barros H, Bochud M, Chadeau-Hyam M, Clavel-Chapelon F, Costa G, Delpierre C, Fraga S, Goldberg M, Giles GG, Krogh V, Kelly-Irving M, Layte R, Lasserre AM, Marmot MG, Preisig M, Shipley MJ, Vollenweider P, Zins M, Kawachi I, Steptoe A, Mackenbach JP, Vineis P, Kivimäki M, Alenius H, Avendano M, Barros H, Bochud M, Carmeli C, Carra L, Castagné R, Chadeau-Hyam M, Clavel-Chapelon F, Costa G, Courtin E, Delpierre C, D'Errico A, Dugué PA, Elliott P, Fraga S, Gares V, Giles G, Goldberg M, Greco D, Hodge A, Irving MK, Karisola P, Kivimäki M, Krogh V, Lang T, Layte R, Lepage B, Mackenbach J, Marmot M, McCrory C, Milne R, Muennig P, Nusselder W, Panico S, Petrovic D, Polidoro S, Preisig M, Raitakari O, Ribeiro AI, Ribeiro AI, Ricceri F,
Robinson O, Valverde JR, Sacerdote C, Satolli R, Severi G, Shipley MJ, Stringhini S, Tumino R, Vineis P, Vollenweider P, Zins M (2017) Socioeconomic status and the risk factors as determinants of premature mortality: a multicohort study and meta-analysis of 17;7 million men and women. Lancet 389:1229–1237. https://doi.org/10.1016/S0140-6736(16)32380-7

Summers JK, Smith LM, Case JL, Linthurst RA (2012) A review of the elements of human well-being with an emphasis on the contribution of ecosystem services. Ambio 41:327–340. https://doi.org/10.1007/s13280-012-0256-7

Tampo L, Kaboré I, Alhassan EH, Ouéda A, Bawa LM, Djaneye-Boundjou G (2021) Benthic macroinvertebrates as ecological indicators: their sensitivity to the water quality and human disturbances in a tropical river. Front Water 3:662765. https://doi.org/10.3389/frwa.2021.662765

Tan X, Ma P, Bunn SE, Zhang Q (2015) Development of a benthic diatom index of biotic integrity (BD-IBI) for ecosystem health assessment of human dominant subtropical rivers, China. J Environ Manage 151:286–294. https://doi.org/10.1016/j.jenvman.2014.12.048

Texas Commission on Environmental Quality (1999) Surface Water Quality Monitoring Procedures, Volume 1: Physical and Chemical Monitoring Methods. TCEQ. Monitoring and Assessment Section

Thornton JM, Palazzi E, Pepin NC, Cristofanelli P, Essery R, Kotlarski S, Giuliani G, Guigoz Y, Kulonen A, Pritchard D, Li X, Fowler HJ, Randin CF, Shahgedanova M, Steinbacher M, Zebisch M, Adler C (2021) Toward a definition of essential mountain climate variables. One Earth 4:805–827. https://doi.org/10.1016/j.oneear.2021.05.005

Trbojević IS, Popović SS, Milovanović VV, Predojević DD, Subakov Simić GV, Jakovljević OS, Krizmanić JŽ (2021) Substrate type selection in diatom-based lake water quality assessment. Knowl Manag Aquat Ecosyst. https://doi.org/10.1051/kmae/2021022

Verneaux J (1994) Macrobenthos et l''état de santé'' des eaux douces. Fondements, contraintes et perspectives. In, Etat de santé des écosystèmes aquatiques. Les variables biologiques comme indicateurs- Acte du séminaire national- Cemagref editions.

Watanabe T, Asai K, Houki A (1986) Numerical estimation to organic pollution of flowing water by using the epilithic diatom assemblage—diatom assemblage index (DAIpo). Sci Total Environ 55:209–218. https://doi.org/10.1016/0048-9697(86)90180-4

Webb JC, Mergler D, Parkes MW, Saint-Charles J, Spiegel J, Waltner-Toews D, Yassi A, Woollard RF (2010) Tools for thoughtful action: the role of ecosystem approaches to health in enhancing public health. Can J Public Health 101:439–441. https://doi.org/10.1007/BF03403959

Wilhm JL, Dorris TC (1968) Biological parameters for water quality criteria. Bioscience 18:477–481. https://doi.org/10.2307/1294272

Wolf J, Johnston RB, Ambelu A, Arnold BF, Bain R, Brauer M, Brown J, Caruso BA, Clasen T, Colford JM Jr, Mills JE, Evans B, Freeman MC, Gordon B, Kang G, Lanata CF, Medlicott KO, Prüss-Ustün A, Troeger C, Boisson S, Cumming O (2023) Burden of disease attributable to unsafe drinking water, sanitation, and hygiene in domestic settings: a global analysis for selected adverse health outcomes. Lancet 401:2060–2071. https://doi.org/10.1016/S0140-6736(23)00458-0

World Health Organization (2017) Guidelines for drinking-water quality: fourth edition incorporating first addendum, 4th edn. World Health Organization, Geneva

Wright JF (2000). Assessing the biological quality of fresh waters: RIVPACS and other techniques. Invited contributions from an international workshop held in Oxford, UK. Freshwater Biological Association, AMBLESIDE, CUMBRIA, UK. http://hdl.handle.net/1834/22844

Wu JT (1999) A generic index of diatom assemblages as bioindicator of pollution in the Keelung River of Taiwan. Hydrobiologia 397:79–87. https://doi.org/10.1023/A:1003694414751

Wu L, Pan X, Chen L, Huang Y, Teng Y, Luo Y, Christie P (2013) Occurrence and distribution of heavy metals and tetracyclines in agricultural soils after typical land use change in east China. Environ Sci Pollut Res 20:8342–8354. https://doi.org/10.1007/s11356-013-1532-1

Wu Q, Zhou H, Tam NFY, Tian Y, Tan Y, Zhou S, Li Q, Chen Y, Leung JYS (2016) Contamination, toxicity and speciation of heavy metals in an industrialized urban river: Implications for the dispersal of heavy metals. Mar Pollut Bull 104:153–161. https://doi.org/10.1016/j.marpolbul.2016.01.043

Wu J, Mao R, Li M, Xia J, Song J, Cheng D, Sun H (2020) Assessment of aquatic ecological health based on determination of biological community variability of fish and macroinvertebrates in the Weihe River Basin, China. J Environ Manage 267:110651. https://doi.org/10.1016/j.jenvman.2020.110651

Xu Y, Zhang H (2020) Index of biological integrity and its research progress in aquatic ecosystem health. Int J Eng Res Appl 10(8):53–56
Yao N, Feng B, Zhang M, He L, Zhang H, Liu Z (2021) Impact of Industrial production, dam construc-
tion, and agriculture on the Z-IBI in river ecosystems: a case study of the Wanan River Basin in
China. Water 13:123. https://doi.org/10.3390/w13020123

Yeom DH, Adams SM (2007) Assessing effects of stress across levels of biological organization using an aquatic ecosystem health index. Ecotoxicol Environ Saf 67:286–295. https://doi.org/10.1016/j.ecoenv.2006.07.006

You G, Xu B, Su H, Zhang S, Pan J, Hou X, Li J, Ding R (2021) Evaluation of aquaculture water quality based on improved Fuzzy comprehensive evaluation method. Water 13:1019. https://doi.org/10.3390/w13081019

Zanchett G, Oliveira-Filho E (2013) Cyanobacteria and cyanotoxins: from impacts on aquatic ecosystems and human health to anticarcinogenic effects. Toxins 5:1896–1917. https://doi.org/10.3390/toxins5101896

Zandbergen PA, Hall KJ (1998) Analysis of the British Columbia water quality index for watershed manag-
ers: a case study of two small watersheds. Water Qual Res J 33:519–550. https://doi.org/10.2166/wqrj.1998.030

Zhang YH (2019) Research on ecosystem health assessment indices and thresholds of a large Yangtze-con-
nected lake, Poyang lake. App Ecol Environ Res 17(5):11701–11716. https://doi.org/10.15666/aeer/1705_1170111716

Zhao K, Song K, Pan Y, Wang L, Da L, Wang Q (2017) Metacommunity structure of zooplankton in river networks: roles of environmental and spatial factors. Ecol Indic 73:96–104. https://doi.org/10.1016/j.ecolind.2016.07.026

Zhao C, Shao N, Yang S, Ren H, Ge Y, Zhang Z, Zhao Y, Yin X (2019) Integrated assessment of ecosystem health using multiple indicator species. Ecol Eng 130:157–168. https://doi.org/10.1016/j.ecoleng.2019.02.016

**Publisher’s Note** Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.