Introduction

Freshwater ecosystems in the world are most vulnerable to a variety of anthropogenic impacts (Hellawell 2012). Physical habitat changes due to dam constructions, the input of agrochemicals from agricultural activities, urbanization (Kripa et al. 2013), and recreational activities have a profound impact on aquatic ecosystems (Allan 2004; Bae et al. 2005; Barletta et al. 2010). Agricultural pollutants have been identified as the major contributors to aquatic pollution, worldwide (Gunawardhana et al. 2016; Jayawardana et al. 2017). Excessive use of fertilizers, hormones and pesticides in crop production often leads to contamination of waterways with such chemicals (Cooper 1993; Hapeman et al. 2002; Kripa et al. 2013) and they are most noticeable when they produce immediate or delayed toxic effects on aquatic life (Brühl and Zaller 2019; Cooper 1993; Khan and Law 2005; Zacharia 2011). Consequently, these may cause the alteration of the species composition in aquatic systems (Brühl and Zaller 2019; Wang et al. 2007). In addition to that, Persistent Organic Pollutants and heavy metals can accumulate in the aquatic food chains causing impacts on nontarget species (Cui et al. 2015; Ribeiro et al. 2005).

A significant measure of a healthy freshwater ecosystem is the state of the physical-chemical environment and biological integrity (Bae and Park 2014; Butcher et al. 2003; Herman and Nejadhashemi 2015; Hughes et al. 2000). Traditional methods of measuring physical and chemical water quality parameters were found not accurately representing the status and disturbance events that took place in the freshwater systems over time. For example, most pesticide residues in the aquatic environment are not readily detectable as they often occur at low concentrations and due to their diffuse and transient nature (Beketov et al. 2009; Comoretto et al. 2008). Nonetheless, even at extremely low levels, such chemicals can cause physiological impairments in aquatic species that are often expressed at the level of the population. However, biological monitoring has proven to be most successful in capturing such transient impacts caused by toxicants at very low concentrations (Barr and Needham 2002; Sanders et al. 2009). This paper therefore reviews the literature on various approaches of biomonitoring currently being adopted in different regions of the world, with particular reference to macroinvertebrates and the pollution of pesticides. Given the inadequacy of biomonitoring information and the scarcity of biomonitoring-related data in some regions of the world, the review seeks to integrate biomonitoring concepts for environmental management in regions where they are not adequately recognized.

Bioindicators and Biomarkers

The environmental stressors can act on various hierarchical levels of biological organization and most ecologically relevant ones occur at higher levels, for example, population or community levels. Population responses to environmental stress are regarded as a primary caution of ecosystem changes due to the alteration of growth and reproduction of aquatic communities (Orfanidis et al. 2007). Also, aquatic organisms can respond to contamination at even very low levels when the contaminants are present in water or sediments (Wijeyaratne and Pathiratne 2006). The real bioavailable fraction of pollutants and pollution effects at low levels can be studied using bioindicators and validated under both field and laboratory conditions (Hamza-Chaffai 2014). Moreover, bioindicators reflect the present state and past trends of additional and accurate information concerning the environmental behavior (Oertel and Salánki 2003) since it reflects cumulative changes over time. Two main levels of organization of biomonitoring can be addressed as biomarkers and bioindicators (Adams and Greeley 2000; Van der Oost et al. 2003). In general, bioindicators have intermediate relevance of sensitivity, high ecological relevance and diagnostic utility (Adams and Greeley 2000), while biomarkers are pollutant sensitive and measure potentially much more diagnostically, but its ecological relevance is low (Van der Oost et al. 2003). Aquatic organisms are often used as bioindicators or biomarkers since they are exposed to widespread environmental variations during their life cycle. At first, limnologists used the presence or absence of selected indicator species for biomonitoring programs. However, with the development of quantitative analytical methods using computers and other sophisticated techniques, more advanced biomonitoring techniques have been developed. “Saprobic Index, Saprobic Valency, Indicative Weight, Trent Biotic Index (TBI), Score System, and Hilsenhoff Biotic Index” are some of these common biological indices that have been developed (Resh and Rosenberg 1993). These biological monitoring studies using macroinvertebrates include an understanding of indirect consequences, mechanisms of recovery and relative pollutant sensitivities.

Bio monitors or bioindicators are living organisms that can be used to measure contaminants or collect information on the impacts of contaminants on environmental spatial and temporal variance. These organisms reflect the bioavailable fraction of pollutants and interest for environmental managers because of their potential ecotoxicological significance (Hamza-Chaffai 2014). Compliance indicators, diagnostic indicators and early warning indicators are three classes of bioindicators that are classified based on the purpose of their use. Deviations from acceptable health limits of the aquatic ecosystem are revealed by the compliance indicators while diagnostic indicators express the causes for the deviations in the environment. The early warning indicators signify the impending decline of the health of the aquatic ecosystem. Although all three groups of indicators should be represented in an integrated assessment of ecosystem health, indicator selection is based on the purpose and objective of the specific assessment (Cairns and McCormick 1992; Hamza-Chaffai 2014).

Good bioindicator organisms possess several desirable characteristics such as clear taxonomy, cosmopolitan distribution, sufficient abundance, and wide distribution for replicate sampling. In addition, low genetic and ecological variability, suitable body size and ease of finding, low mobility (local indication), long life-span to the comparison between various ages, well-studied ecology, optimal for being “actively” monitored, bioaccumulation without death, higher sensitivity toward stressors to be monitored, the higher capability for quantification, and standardization are among the other characters (Füreder and Reynolds 2003; Hilty and Merenlender 2000; Resh and Rosenberg 1993; Zhou et al. 2008). However, it is too stringent to choose bioindicator species with all the characteristics, but it is more possible to select indicators with suitable characteristics that serve the purpose of biological evaluation (Zhou et al. 2008). Especially, the use of bioindicators are useful in situations in where the indicated environmental factor cannot be measured or difficult to interpret (Gerhardt 1999). The commonly used bioindicators for the assessment of aquatic environment are macroinvertebrates, bivalves, gastropods, fishes, zooplankton, phytoplanktons, and macrophytes (Hamza-Chaffai 2014; Marbà et al. 2006; Zhou et al. 2008).

In different levels of biological organization (i.e., molecular, cellular, or physiological levels), biomarkers are measurable parameters that affect or change the metabolic regulatory processes due to environmental stressors (Van der Oost et al. 2003). Another definition for biomarkers is a measurable biologic system or sample which can induce variation in cellular or biochemical structures or functions, components or processes, xenobiotically (Hamza-Chaffai 2014; Van der Oost et al. 2003). Biomarkers occur at a molecular level followed by cellular, tissue/organ, and whole-body levels. Higher levels of effects such as individual, population, and ecosystem-level are less irreversible, more detrimental and generally accepted to have ecological relevance. Hence, routine biomonitoring program needs to be focused towards on identifying and understanding the toxic effects which initiated at the sub-organism levels of molecular, biochemical, or physiological changes when developing biomonitoring programs.

Examples of biomarkers that are widely studied in laboratories are metallothioneins (MTs), malondialdehyde, acetylcholinesterase (AchE) glycogen, and stress on stress test (Hamza-Chaffai 2014). There are several applications of biomarkers for detecting the aquatic ecosystem health (De la Torre et al. 2002; Hamza-Chaffai et al. 2000). De la Torre et al. (2002) have assessed the effect of prolonged exposure of urban pollutants on brain AchE activity on caged Cyprinus carpio and field-captured Cnesterodon decemmaculatus and demonstrated high sensitivity of AChE activity as an exposure biomarker. The use of the marine bivalve Ruditapes decussatu to validate the relationship between MTs and metals (Cd, Cu, and Zn) under field conditions is another example of the use of biomarkers for detecting environmental pollutants. The study showed that MTs in the digestive gland of R. decussatus reacted to moderate rises in metal contamination and may be a promising biochemical metal exposure predictor (Hamza-Chaffai et al. 2000). A study investigating the activation of biochemical stress responses in Macrobrachium malcolmsonii in response to their exposure to endosulfan, demonstrated an elevated levels of glutathione S-transferase and a decreased content of AchE in test prawns. Also, phosphatases and lactate dehydrogenase levels alterations were also noted in tissues. This suggested the disruption of fundamental metabolic activities in research prawns due to the exposure to endosulfan pesticide (Bhavan and Geraldine 2001). Biomarkers may be used as an early warning system in environmental quality assessment to diagnose exposure to environmental pollution in the aquatic environment that has risen in recent decades (Hamza-Chaffai 2014).

Macroinvertebrates as Indicators

Organisms that live entirely or part of their life cycle in the bottom substrates such as sediments, debris, logs, etc. in aquatic ecosystems which are observed by naked eyes are regarded as benthic macroinvertebrates (Chessman 2003; Resh and Rosenberg 1993). In terms of species richness and individual abundance, ~95% of benthic macroinvertebrates comprise freshwater arthropods (Bae et al. 2005). Chukwu and Nwankwo (2003) and Roozbahani et al. (2010) showed that benthic macroinvertebrates diversity can be used as a good indicator for evaluating the ecological status of the aquatic system. The advantages of using benthic macroinvertebrates for biomonitoring are that they are universal thus can be used in many different types of aquatic systems, exhibit high species richness and abundance, respond to wide range of environmental stress. Also, their sedentary or benthic habitat and long-life cycle compared to other aquatic organisms such as algae and planktons in freshwater are useful effect-based indicators for assessing spatial and temporal analysis respectively and thus sampling may be less frequent (Bae et al. 2005; Borisko et al. 2007; Mathuriau et al. 2012). According to Voshell (2002), at least 60% of the biological indices that have been identified in running water over the past years, are macroinvertebrates. Macroinvertebrates are an essential part of the aquatic environment as they transfer the energy to other trophic levels in the aquatic food web (López-López and Sedeño-Díaz 2015) and their degree of sensitivity to environmental changes differ among various groups. Physico-chemical conditions of a given location can be predicted using the morphology, presence/absence, abundance, physiology, or behavior of these macroinvertebrates (Sharma et al. 2008). Factors regulating macroinvertebrates in freshwater habitats are food, current speed, the substratum, riffle depth, vegetation, water temperature and conductivity, shade, effects of altitude and season, liability to drought and floods, competition between species and zoogeography.

In this context, macroinvertebrates are ideal for determining site-specific impacts because they have restricted migration, differ in quantity and types of contaminants in their tolerance levels and are easy to recognize (Sharma et al. 2006). Further, macroinvertebrate communities contain board range of species which belong to various trophic levels and their life cycles generally limited to ~1 year of which most is spent in the water (Agouridis et al. 2015; Hauer and Lamberti 2011). They also exhibit pollution sensitivity (Compin and Céréghino 2003) and provide aggregate impact for different stressors in short term and long term (Girgin et al. 2003; Sharma and Rawat 2009). Also, suitable taxonomic keys are available to identify the specimens because of standardized field sampling methods and laboratory processing protocols (Chirhart 2003). Water quality degradation is demonstrated by the presence or absence of sensitive and tolerant organisms because different taxa have different habitat preferences and wide tolerances for pollutants (López-López and Sedeño-Díaz 2015).

Despite the relative advantages of using macroinvertebrates as indicators of water quality monitoring, it also has several limitations. Some of these limitations include the difficulty of quantitative sampling as their distribution is nonrandom in riverbed because some invertebrates life cycles are showing seasonality and the effects of natural and catastrophic drift (López-López and Sedeño-Díaz 2015). Another limitation is macroinvertebrates exhibit limited spatial dispersal ability in response to environmental changes or stresses frequently occurring in the aquatic environment. As a result, organisms located at the edge of their natural aquatic habitat are more vulnerable to environmental stress than those at the center of their distribution. It, therefore, limits the use of universal biological assessment based on the same species/taxa response.

“Hilsenhoff’s Biotic Index”, “Invertebrate Community Index”, “Biological Monitoring Working Party Score (BMWP)”, “Macroinvertebrate Water Quality Index”, “Average Score per Taxon”, “Percent Model Affinity”, and “EPT Richness Index” are few of the commonly used indices which integrated macroinvertebrates composition to assess the quality of aquatic environment in different regions of the world (Kripa et al. 2013). However, many of these protocols and biological monitoring methods are developed based on the taxa relevant to regions of northern hemisphere of the world including North America and Europe. However, few countries in Asian and African regions make use of such indices after modifications for biomonitoring. But these indexes with European threshold values did not well explain the stress on the aquatic system (Cornejo et al. 2019; Rasmussen et al. 2016). According to Morse et al. (2007) inadequate knowledge on macroinvertebrate fauna and their aquatic stages in most Asian countries, scarcity of necessary equipment, and lack of support and understanding of biomonitoring by the respective authorities are some of the challenges to the introduction of biomonitoring techniques for water quality monitoring. Though research on tropical streams has been increasing over the last two decades, there is still a lack of knowledge on aquatic fauna and ecological understanding (Al-Shami et al. 2011; Gopal 2005).

Different Approaches of Biomonitoring

There are many different biomonitoring techniques employed for biological monitoring of aquatic ecosystems addressing many different organizational levels (Bonada et al. 2006; Mandaville 2002). Available resources and the issue being addressed depend on the selection of suitable biomonitoring techniques. “The diversity indices, Biotic indices, Multimetric approaches, Multivariate approaches, Indices of Biological Integrity (IBI), Functional Approaches and macroinvertebrate trait-based approaches” are the approaches used for assessing the freshwater ecosystem using macroinvertebrates (Li et al. 2010).

Diversity Indices

Diversity indices reflect the combined effect of species richness (number of species), evenness (homogeneity of distribution abundances among species) and abundance (total number of species) of a community to environmental variations. Abundance indicators are used to provide information about the condition of a freshwater environment by evaluating key or sensitive macroinvertebrates such as the EPT index (Johnson et al. 2012). Stream health based on species distribution or qualitative measure of diversity found within the ecosystem is measured using species richness (Wan et al. 2010). High diversity, even distribution among species and the high number of individuals in a community represent undisturbed environments. Diversity indices that developed based on species richness, evenness, and abundance at the community level are Shannon-Wiener Index, Simpson Index, Margalef’s and Menhinick’s Indices, and Pielou evenness etc. (Andem et al. 2013; Roozbahani et al. 2010). These indexes can be used as an indicator of disturbed aquatic environment comparing with reference aquatic environments (Schäfer et al. 2011a).

There are also several limitations of the use of diversity indices in community ecology (Okpiliya 2012). In community ecology, the use of diversity indices has been highly criticized because diversity does not transmit any information on a community’s actual species composition (Rosenzweig 1995). Diversity of species is a population overview measure which does not take into account individual species’ uniqueness or possible ecological significance (Sanders 1968; Risser and Rice 1971; Whittaker 1972). A community can have a high diversity of species, but mainly common or undesirable species are included. A community, on the other hand, may have low species diversity, but it is composed of particular, uncommon, or highly desirable species. For instance, Sanders (1968), Risser and Rice (1971), and Whittaker (1972) stated that the Simpson index as a measure of diversity is that the abundance of the two or three most abundant species in a population is too heavily affected. So the Simpson index gives the uncommon species very less weight and the common species more weight.

Biotic Indices

Biotic indices evaluate river health based on certain taxonomic groups (Bioindicator) to sensitivity and tolerance for environmental variations of eutrophication, organic pollution, pesticides, heavy metals, and pH in the community through numerical scores or single index. According to Perry (2005), the abundance of pollution sensitive organisms indicates the stream healthiness as the sensitivity and tolerance of indicator assemblages are different according to the environmental characteristics. The advantages of this indices are used simple calculations and utilize only one stressor or metrics to evaluate stream health. The disadvantage is that biotic indices do not utilize the combined effects on multiple stressors within the aquatic ecosystem (Fierro et al. 2017; Herman and Nejadhashemi 2015). Several biotic indices have been developed for particular regions, but many of these indices can be used with modifications in other regions. Examples of region-specific indices are “Nepalese Biotic Score and National Sanitation Foundation Water Quality Index” in India (Sharma et al. 2008; Sharma et al. 2006) “Trent Biotic Index (TBI)” and the “Biological Monitoring Working Party (BMWP) score” for the UK (Hooda et al. 2000), the “Belgian Biotic Index” for Belgian rivers, the “South African Scoring System” for southern Africa, the “Zambian Invertebrate Scoring System” for Zambia, the “Namibian Scoring System” for Namibia, the “Okavango Assessment System” used in Okavango Delta, Botswana, and the “Tanzanian River Scoring System” for Tanzanian rivers (Shimba and Jonah 2016). BMWP score has been widely used in other regions in the world (Kumar et al. 2013; Romero et al. 2017; Uherek and Pinto Gouveia 2014; Varnosfaderany et al. 2010).

Multimeric Approaches

Multimetric indices (MMIs) have been used as standard tools for presenting single “Multimetric” value for the biological condition of water body of various structural and functional metrics of an ecosystem, describing a specific assemblage such as fish, macroinvertebrates, or periphyton (Blocksom 2003; Stoddard et al. 2008). MMIs are highly recommended since it provides robust, quantitative measures, and sensitive insights toward the responses to natural and human-induced stressors from regional to continental level (Stoddard et al. 2008; Zhou et al. 2016). Structural and functional metrics used in Multimetric approaches include “taxa richness, taxonomic composition, relative abundance, dominance, pollution tolerance, functional feeding groups, life history strategies, and behavioral habits” (Ferreira et al. 2011). Examples of MMIs are “Index of Biotic Integrity” and “Benthic Index of Biotic Integrity”. In the sense of natural variability, biotic integrity, and associated indices reflects aquatic system’s ability to sustain characteristic functional and structural populations, to resist loss of this function and structure due to disturbance, and to recover from such disturbance (Perera et al. 2012). The disadvantages associated with use of such indices are their complexity of calculations in determining the stream health (Fierro et al. 2017).

Multivariate Approaches

Multivariate approaches are effective for predicting the relationship between bioindicators (absence or presence of site-specific fauna patterns) and environmental characteristics using statistical analysis (Ordination analyses and cluster analyses or combination of these) under the major environmental stress to the reference site (López-López and Sedeño-Díaz 2015; Niemi and McDonald 2004). Predictive models are required in multivariate methods that relate the physicochemical properties of an aquatic ecosystem with bioindicator organisms, which are represented under reference conditions. Widely used such multivariate techniques are RIVPACS (River Invertebrate Prediction and Classification System) which was first implemented in the UK and its derivative models AusRivAS (Australian Rivers Assessment System), BEAST (BEnthic Assessment Sediment), and ANNA (Assessment by Nearest Neighbor Analysis) (Davies 2000; Li et al. 2010; López-López and Sedeño-Díaz 2015). Other similar approaches include LIMPACT (LIMnology and imPACT) in Germany, the integrated evaluation system SERCON in Scotland and the Rapid Bioassessment Protocols in the USA (Neumann et al. 2003). The advantages of this approach are the representativeness of the various stressors and can be used to evaluate the stream health beyond the sampling points. Disadvantages are the complexity of developing the approach, which require expert knowledge (Herman and Nejadhashemi 2015).

Functional Approaches

A functional approach is a proper approach for reflecting ecological integrity based on the information on both structure and function of the aquatic ecosystem. This approach is focused on similar biological characteristics (life cycle, reproductive characteristics, mobility, modes of resistance, food, feeding, and breathing habits) and ecological characteristics (temperature preferences, trophic stage, biogeographic distribution, longitudinal zoning, substratum, organic pollution tolerance, and current velocity) which are susceptible to the local environmental gradient (Charvet et al. 1998; Jayawardana and Westbrooke 2010; Menezes et al. 2010; Poff et al. 2006). Moreover, this approach better detects anthropogenic impacts than traditional methods such as diversity indices or chemical methods (Tomanova et al. 2008). The increased sensitivity and mechanistic linkage of biotic responses to environmental conditions are intrinsic feature of such indices and they aid in ecological risk assessment by providing useful information relevant changes of structure and function of the aquatic ecosystem (Culp et al. (2011). The disadvantages of this approach are less sensitivity to sampling effort, taxonomic resolution level, and large-scale spatial taxonomic differences (Bonada et al. 2006).

Indices of Biological Integrity (IBI)

Macroinvertebrates occupy the entire aquatic system of sediments, water columns and submerged substrates of streams, rivers, lakes and wetlands and may represent the biological integrity of the entire aquatic system (Chirhart 2003). IBI was first developed for communities then subsequently been modified for aquatic macroinvertebrates, terrestrial macroinvertebrates, and algae (Chirhart 2003). IBI developed using a combination of univariate and biotic indices to detect the impacts of anthropogenic disturbances on the aquatic environment. Metrics in IBI denote changes in a predictable way of quantifiable attributes which are the biological assemblage of different levels of anthropogenic stress on the ecosystem. The total number of taxa or the number of “EPT taxa” (Ephemeroptera, Plecoptera, and Trichoptera) is a typical example of the metrics used in IBI macroinvertebrates. Each metric value is based on a comparison of anthropogenic disturbances with little to no effect (Karr 1991). Attributes used to the development of IBI fall into four categories namely “Richness measures”, “Tolerance measures”, “Composition measures”, and “Trophic structure measure”. Inclusion of one or more metrics from each of these categories improves the predictability of IBI (Chirhart 2003; Karr and Chu 1998). A “RIVPACS (River Invertebrate Prediction and Classification System)” is an example of IBI, which is a particular case of IBI and multivariate approaches. The advantage of this approach is that it is proven to be very adaptable in different regions (Karr and Chu 1998).

Macroinvertebrate Traits Based Approaches

Trait-based macrobenthic indicators are being developed in recent years to overcome the problem of less sensitivity of taxonomy based indicators to specific stressors related to the aquatic ecological impairment (Knillmann et al. 2018; Liess et al. 2008; Reynoldson et al. 1997; Schäfer et al. 2007). Generally, taxonomy based indicators do not identify specific stressors responsible for impairment but respond to multiple stresses associated with such impairments (Schäfer et al. 2011a). In recent years Biotic indicators based on biological traits such as generation time, body size and mode of reproduction along with physiological traits such as physiological sensitivity have been developed to identify specific effects of identified stresses (Liess et al. 2008). SPEcies At Risk (SPEAR)pesticides approach is a recently developed trait-based approach which incorporate macroinvertebrate traits sensitive to pesticide contamination for monitoring pesticide contamination (Knillmann et al. 2018; Schäfer et al. 2007). SPEARsalinity is another trait-based indicator developed for South East Australia to assess the impacts of salinization of rivers (Schäfer et al. 2011a). SPEARorganic indicator is a trait-based indicators which was developed to assess the impact of organic toxicant on the trait composition of invertebrate communities in streams of Europe and Siberia (Beketov and Liess 2008).

In order to establish trait-based indicators in biomonitoring, it is important to compile the trait information for taxa present in the area under consideration. These data bases have been well developed in most of the Europe or North America regions. However, such data bases are not available for most regions of the Southern hemisphere and Asia (Schäfer et al. 2011a).

Pesticide Pollution Monitoring

Pesticides are widely used for securing agricultural production and has worldwide applications. However, impacts of the chemicals applied to crop fields may not only act on target pest populations but also have impacts on nontarget species. According to Kaoga et al. (2013), over 95% of applied insecticides and herbicides on the field end up in nontarget areas. Most frequently pesticides applied into crop fields may travel through the land as surface runoff or leach through soil and end up in aquatic systems (Mutuku et al. 2014). In the aquatic environment, pesticide residues accumulate and are found to affect aquatic species in various ways. Specifically, it has been found that pesticides may cause the decline of species in the aquatic environment (Schäfer et al. 2007; Schäfer et al. 2012). The use of pesticides is expected to increase due to climate change in the future and it is considered to be an important cause of the loss of biodiversity in the world (Beketov et al. 2013). Increase in temperature and change in precipitation patterns caused due to climate change can increase crop pests. As a consequence, increased use of pesticides is anticipated in the form of higher quantities, concentrations, frequencies and various varieties or forms of products used (Delcour et al. 2015; Schäfer et al. 2011a). Runoff, leaching, spray drift, preferential flow through soil macropores, or a combination of these processes from agricultural areas are regarded as a nonpoint source of aquatic pesticide contamination (Loewy et al. 2011; Phillips and Bode 2004). Among them, the main route by which pesticides are transported to the aquatic environment is runoff, but the rate depends on the types of soil, the physicochemical properties of the pesticides, the timing and rate of application, and the precipitation after application of the pesticide (Phillips and Bode 2004). Abiotic factors (photodecomposition by sunlight or hydrolysis by water) can lead to degradation of pesticides or adsorb to the sediments or organic matter whereas biotic factors of uptake, metabolization, and accumulation in organisms determine the fate of pesticides in the aquatic environment (Schäfer et al. 2011b). Exposure through contaminated food sources and uptake from overlying water through body walls or respiratory surfaces are the main routes of pesticide entry to bodies of aquatic species (Reynoldson 1987).

Pesticides can be classified as organochlorines (OCPs), organophosphates (OPPs), carbamates (CMs), pyrethroids, and inorganics according to their active ingredients and these synthetic pesticides have been used since the 1940s to control insects around the world. Low cost, broad-spectrum, and persistence nature are reasons for OCPs widely used in the past. The high lipophilic nature, and low biodegradability of OCPs facilitate them to bioaccumulate and biomagnifies in the aquatic food chains causing lethal or sub lethal effects. Most OCPs are banned in the world due to such harmful effects (Keithmaleesatti et al. 2009), however, OCPs residues are still detected in certain areas of the world due to its persistent nature as well as due to the continuation of application of such pesticides in some regions of the world (Rathore and Nollet 2012).

OPPs are the most widely used pesticide in agriculture worldwide and are considered by the WHO to be one of the most hazardous pesticides to vertebrate (Ross et al. 2013). OPPs are easily hydrolyzed and highly toxic to insects (Chambers et al. 2010). CMs are also commonly used in agricultural lands, but it is less toxic to insects and the mode of action is similar to OPPs (Gupta 2006). Pyrethroids are the most widely used group of synthetic pesticide and it is highly toxic to invertebrates and fish and capable of killing invertebrates at ppb levels (Shimba and Jonah 2016).

The bioavailability of pesticides is highly dependent on the pesticide sorption behavior in the aquatic environment. The toxicity of most agricultural chemicals is temperature-dependent (Rathore and Nollet 2012). At high temperatures, several OPP insecticides exhibit increased toxicity to invertebrates, whereas, at low temperatures, pyrethroid insecticides exposure shows increased toxicity. These temperature effects may alter contaminant uptake, or biotransformation rates which result in modification of an organism’s capacity to detoxify xenobiotics and ultimately influence the toxicity (Willming et al. 2013). Chemical stability and cation exchange capacity of organic matter and pH (Gunnarsson et al. 1999; Katagi 2006) are also found to determine the sorption characteristics of pesticides in the sediment layer.

The pesticide contamination is found to contribute to the loss of biodiversity in aquatic systems, but physiological acclimation or genetic adaptation increases the tolerance of aquatic biota to pesticides. Simple mutations at a single locus have been found to cause the development of resistance of invertebrates to toxicants (Becker and Liess 2015). Adaptation of nontarget aquatic species to insecticides is less known (Becker and Liess 2017; Liess and Ohe 2005; Muenze et al. 2015). Weston et al. (2013) disclosed that moderate levels of resistance to CMs and OPPs (<2-fold increase in LC50) have been developed by the water flea “Daphnia magna”. Crustacean “Hyalella Azteca” laboratory cultures and wild populations demonstrated 550-fold resistance to pyrethroid insecticides through mutations in the voltage-gated sodium channel at the target site for pyrethroid toxicity (Weston et al. 2013). In nontarget black flies, high levels of resistance to DDT, and pyrethroids were also observed (Montagna et al. 2003) in which 355-fold pyrethroid resistance was developed due to esterase enzyme activity (Montagna et al. 2012).

The most popular and widely used group of invertebrates which is used to assessing pesticide pollution of water is benthic macroinvertebrates. Benthic communities play an important role in transferring energy from one tropic level to another. Modern insecticides are found to have adverse impacts on nontarget aquatic invertebrates in the aquatic habitats (Friberg-Jensen et al. 2003; Schulz and Liess 2001; Wendt-Rasch et al. 2003). Benthic macroinvertebrates are well suited for estimating the toxicity of currently used pesticides because the detection of actual concentrations of pesticides in the environment is difficult and expensive due to their episodic and low- concentration levels and the existence of a multitude of substances (Castillo et al. 2006; Schäfer et al. 2011). For example, “invertebrates Daphnia magna, Hyalella azteca, and Chironomus tentans were about ≥200 times more sensitive than the fish fathead minnow (Pimephales promels) to the AChE inhibiting organophosphorus insecticide chlorpyrifos” (Moore et al. 1998). Macroinvertebrate groups of “Ephemeroptera, Plecoptera, and Trichoptera” (commonly known as EPT taxa) are very sensitive species to pollution while midge larva, pouch snails and rat-tailed maggots are tolerant to environmental contaminants (Agouridis et al. 2015). “Species-at-risk (SPEAR)” pesticides index is commonly used to indicate changes in the abundance of the taxa vulnerable to aquatic pesticide concentrations (Liess and Ohe 2005; Schäfer et al. 2007; Schäfer et al. 2011; Rasmussen et al. 2012).

Table 1 Examples of pesticide effects on macroinvertebrate community using biological indices on different regions of the world
Full size table

Monitoring of invertebrate community composition is highly ecologically relevant for detecting pesticide pollution of the aquatic environment because the pesticide exposure from agriculture and the macroinvertebrates establishment has shown a clear exposure effect relationship (Table 1). Studies comparing the variance of stream macrobenthic communities based on the pesticide exposure indicated that the benthic macroinvertebrate fauna in control sites of immediately upstream of an area of agricultural land and downstream sites are having a significant difference in sensitive and tolerant taxa where sensitive taxa showing declining trends in comparison to control sites (Neumann and Dudgeon 2002; Thiere and Schulz 2004). Another study by Macchi et al. (2018) indicated the dominance of a single taxon in places of pesticide application. However, these studies characteristically relied on the comparison of sensitive and tolerant taxa in sites located in proximity, to eliminate the other environmental variations such as stream size, discharge, substrate characteristics, and riparian vegetation. Hence these studies raise the question of representativeness because they were not adequately representing broader spatial scales.

The use of various macroinvertebrate-based indices to evaluate the levels of contamination of pesticides in streams is widely practiced in temperate regions. However, these are of limited use for assessing tropical streams and the sensitive species of macroinvertebrates in tropical regions are largely unknown. On the other hand, BMWP index which is one of the most often used biotic indices based on macroinvertebrates to measure organic pollution (nutrient enrichment) and association with oxygen depletion in streams, has been successfully used in tropical environments such as Ecuador, Brazil and Costa Rica with slight modification to the index although it was developed for the temperate regions (Damanik-Ambarita et al. 2016; Nascimento et al. 2018; Svensson et al. 2018). SPEAR pesticides index is a widely used index for pesticide monitoring which is a trait-based approach to assess responses of macroinvertebrate communities to pesticides. It has been developed and successfully applied in different biogeographical regions in Europe, however, additional researches are needed to the application of the SPEAR pesticides index through its development in other regions of the world that are having different climatic, geographic conditions and/or agricultural practices (Cornejo et al. 2019; Rasmussen et al. 2016; Schäfer et al. 2013). Many studies done in temperate countries have shown a strong negative correlation between pesticide concentrations in aquatic systems and the SPEAR index but shown poor correlations in tropical regions (Rasmussen et al. 2012; Schäfer et al. 2007; Schäfer et al. 2011). This weak associations recorded in tropical aquatic systems may have been attributed to the frequent exposure of invertebrates to high doses of pesticides during the crop cycles during the year that is released from the crop fields. In addition, the post-contamination recovery period for pesticides and the vulnerability of aquatic phases may differ in tropical taxa (Rasmussen et al. 2016). Among the other research gaps related to understanding of effects of pesticides and biomonitoring, a few studies are conducted to explore the synergistic effects of different pesticides on aquatic invertebrates (Shahid et al. 2019). Therefore, further research is needed to carryout to understand the synergistic effects of different pesticides on aquatic biota. In addition to that, lentic systems are highly vulnerable to pesticide accumulation, but very few studies were conducted in the lentic aquatic ecosystems to assess the applicability of these indices (Molozzi et al. 2012). However, some countries are widely using biological indices, for example, “SWAMPS index” in Australia (Chessman et al. 2002), a “Biological Integrity Index” developed for wetlands of the Missouri River (Haugerud 2003) and “Multimetric Index” for wetlands in southwest Ethiopia to assess the lentic systems (Mereta et al. 2013).

In conclusion, use of macroinvertebrates in biological monitoring is a powerful tool to study changes within the aquatic system more importantly to assess the effects of agricultural pesticides. they are an important group involved in the transfer of energy in the aquatic food chain to higher levels and are also a good indicator of pollution in the aquatic environment. although research on tropical streams has increased over the last two decades, there is still a knowledge gap on use of macroinvertebrate fauna for biomonitoring in tropical regions of the world. “biotic indices” and “multimetric approaches” are widely used to evaluate the health of aquatic ecosystems worldwide. review of literature on past studies suggested that bmwp and ept taxa richness do not correlate well with pesticide toxicity but largely sensitive to other environmental variables (Schäfer et al. 2011a). SPEAR pesticide index is successfully applied in temperate regions to monitor the effects of pesticides on aquatic ecosystems but with limited use in tropics. We suggest that future studies should focus on characterizing the sensitivity and vulnerability of tropical species and their response to multiple stressors for use in biomonitoring programs.