Espacios. Vol. 37 (Nº 02) Año 2016. Pág. 6
Rafael Alves ESTEVES 1
Recibido: 01/09/15 • Aprobado: 01/10/2015
2. Zoobenthos as bioindicators
3. Biomonitoring of freshwater ecosystems
ABSTRACT: The zoobenthos has shown excellent living resources in the systemic monitoring of aquatic ecosystems to assess the changes in the environment, usually caused by human action. This article presents the fundamentals of biological monitoring of aquatic environments and the methodological aspects of BMWP Index as a resource evaluation studies of the environmental health. Aiming to cooperate with the decision-making processes of water managers, applying this method of assessment of aquatic environments contributes to obtain fast results, with low cost and high efficiency, which fosters a participatory approach in water resources management in the national territory. |
RESUMO: Os zoobentos tem se mostrado excelentes recursos vivos no monitoramento sistêmico de ecossistemas aquáticos para avaliar as mudanças ocorridas no ambiente, geralmente causadas pela ação humana. Neste artigo são apresentados os fundamentos do monitoramento biológico de ambientes aquáticos e os aspectos metodológicos do Índice BMWP como subsídio a estudos de avaliação da saúde ambiental de corpos hídricos. Visando colaborar com os processos decisórios dos gestores de recursos hídricos, a aplicação desse método de avaliação de ambientes aquáticos contribui para obtenção de resultados rápidos, com baixo custo e alta eficiência, o que fomenta uma abordagem participativa na gestão dos recursos hídricos no território Nacional. |
The assessment of water quality is the subject of undeniable importance and priority. This good is essential to life and may be responsible for killing in mass when contaminated, both animals and humans and also of complete water systems. According Bilich and Lacerda (2005), changes in water cause as much environmental damage as economic, such as reducing fishing activity or increasing the cost of acquisition and treatment of water.
The start to attempt to mitigate the environmental problems caused by human activities and derived from mismanagement of water resources permeates the development of efficient methodologies of environmental diagnosis, able to measure the environmental health of the system being studied. According to a document of the United Nations (UN), Agenda 21 (CNUMAD, 1992), "water use should have as a priority the satisfaction of basic needs and the preservation of ecosystems". In chapter 18 of this document it is suggested that quality protection and supply of water resources to be made from the application of integrated criteria for the development, management and use of water resources.
Buss et al. (2003) says that the discussion about the importance of using integrated criteria for assessing water quality is not recent. Since the 1970s, researchers and water managers in Western Europe and North America (ARMITAGE, 1995; CAIRNS and PRATT, 1993; PRATT and COLER, 1976) argue that traditional methods of water classification, based in physical, chemical and bacteriological characteristics were not sufficient to meet the multiple uses of water, being particularly deficient in the evaluation of aesthetic quality, recreation and ecological environment.
The conclusion of the discussion is that an assessment only shows effective if conducted in the form of integrated water quality analysis, that is, considering not only the traditional valuation methodologies, but the biological system (BARBOSA, 1994; METCALFE, 1989; RESH and ROSENBERG, 1993).
According to Buss et al. (2003), to analyze the biological aspects of ecosystems, two methods have been used. Methods "bottom-up" fundamentally utilize laboratory data through experimentation in simple systems with subsequent extrapolation to more complex systems. The methodology "top-down" rating, at the macro level, the environmental impacts by changing the measurement of structural and functional organization of biological or ecosystem communities.
In the bottom-up methodology the tests are performed, in general, based on the responses of aquatic organisms to specific stressors. In such cases, they are used as indicators of chemical changes (enzymatic or genetic for example), physiological (ionic regulation), behavioral, metabolic and life cycle (BOUDOU and RIBEYRE, 1997; BUIKEMA and VOSHELL, 1993; CALOW, 1993; PIVETA et al., 2001; RESH and ROSENBERG, 1993).
The use of physiological responses in laboratory assessments is generically known as toxicology tests. Among them we highlight the acute reaction of bioassays, specialized in the determination of lethal and sublethal pollution of synthetic or natural substances of mineral, animal or vegetable (EWELL et al., 1986).
The laboratory evaluation also involves the analysis of chronic exposure, giving the deleterious effects as genotoxicity, carcinogenicity and mutagenicity (REYNOLDSON and METCALFE, 1992).
In turn, the top-down methodologies have proven viable in many cases and represent the fastest and practical for ecosystem management. With these methods you gain control and speed the reaction of toxicity tests, but you lose touch with reality and applicability to the environment (MOULTON, 1998).
Thus, for the analysis of water quality is advantageous to use topdown tools for efficiently assess: i) the actual loss of species diversity, rather than assess the indirect effects of stressors; ii) the synergistic effect of anthropogenic changes in the catchment area (eg, the sum of the effects of deforestation, the input of pesticides and domestic effluents); iii) water quality by relatively simple methods and inexpensive; iv) the impact of alien species on local flora and fauna; and v) the ecological integrity of aquatic ecosystems.
The purpose of this article is to present the methodological aspects of the use of zoobenthos in order to assess the environmental health of aquatic ecosystems by using Index Biological Monitoring Working Party System - BMWP Index, providing support for an integrated analysis of water quality.
According Brandimarte et al. (2004), the community of benthic invertebrates is one of the most widely used to assess water quality among all aquatic biota. This is because, due to their restricted mobility, the structure of this community is strongly influenced by environmental factors, reflecting the retrospective quality of the environment and highlighting changes that cannot always be revealed through costly physical and chemical monitoring of water (BASSET et al. 2004).
Also other characteristics of zoobenthos enable them as environmental indicators, such as large number of species, with a wide variety of functional groups even within the taxonomic level of family or genus (EPA-OHIO, 1987), relatively long life cycle, rapid response to environmental stress, ubiquity, addition of suitable size for sampling and handling (RESH and ROSENBERG, 1993; JUNQUEIRA et al., 2000; KUHLMANN et al., 2001; BASSET et al., 2004).
Several factors, however, can cause some difficulties to the use of zoobentos as bioindicators, such as the difficulty of taxonomic identification and a clustering distribution pattern, which requires a large number of replicas to the sample to be considered significant, which implies long for the screening of the higher costs and financial organizations (RESH and ROSENBERG, 1993; RESH, 1995).
According Kuhlmann et al. (2001), part of the problem related to sampling and identification can be reduced with the adoption of rapid assessment techniques which generally are inexpensive and have reliable results that can support control decisions. One of the techniques cited by the author is the taxonomic identification up to the family level. Even with a certain risk of underestimating some metrics, as warned by Guerold (2000), this level of identification has been used and recommended by many researchers in the evaluation of water quality (CHESSMAN, 1995;. BARBOUR et al, 1999; JUNQUEIRA et al., 2000; IMBIMBO, 2006). This technique is simple, fast and cost-effective in relation to the identification to genus or species and is suitable for the application of reliable metrics that reflect environmental degradation, and reduce the interference of spatial heterogeneity and stochastic events in routine monitoring (THORNE and WILLIAMS, 1997).
In short, Resh says (1995), that the use of benthic invertebrates in environmental assessments, as well as rapid assessment techniques, has proven advantageous because it is inexpensive and very informative, and suitable for application in water management research in developing countries.
Regarding to the diversity of zoobenthos community generally tends to be lower in small headboards, even in pristine water due to lower the diversity of habitat and chances of colonization by drift, poverty nutrients and food and consequently lower yield (CUMMINS, 1994). Similar effects are observed in impacted environments, due to elimination of the susceptible taxon and dominance tolerant forms (HELLAWELL, 1989). Thus, in line with the discussion said by Fidalgo (2006), it is expected to occur in a river a smaller amount of wealth and diversity of families in points headboards, and in the farthest reaches of them representing a sum of impacts. The highest values obtained are expected at the point of intermediate location, reflecting an environmental gradient.
In this sense, the benthic community is presented as an important resource for assessing the quality of aquatic ecosystems in environments subject to anthropogenic impacts and at the same time, they are configured as basic systems for development.
In order to monitor the water quality, during long time the academic community developed physical, chemical and biological parameters. Thus, very common now a days the usage of this parameters to characterize the quality of water. These parameters represent impurities when they reach values higher than those established for a certain application. There are several ways to consider these parameters, one of these is the Water Quality Index, which establishes levels and patterns of some physical, chemical and bacteriological, targeting the framework of bodies of water quality classes (BILICH and LACERDA, 2005). In Brazil the framework of water resources for each specific use is defined in CONAMA Resolution No. 357/2005 (Brazilian Environmental Agency responsible for environment-related legislation).
The monitoring of these variables provides some advantages in the assessment of environmental impacts on aquatic ecosystems as the immediate identification of changes in physical and chemical properties of water, accurate detection of the modified variable and determination of these altered concentrations. However they have some disadvantages, such as the temporal and spatial discontinuity of sampling. Sampling of physical and chemical variables provides only a picture of a situation that can present highly dynamic characteristics. (WHITFIELD, 2001)
The use of physical, chemical and bacteriological parameters to evaluate the water has been considered insufficient. Currently experts argue the importance of using multiple criteria for evaluation of water, and for such an integrated analysis is necessary, beyond the traditional methods using the biological system. These are based on the response of organisms and communities in relation to the environment where they live, so because biological communities reflect the overall ecological integrity of ecosystems, integrating the effects of different impactful agents and providing an aggregate measure of the impacts (BARBOUR et al., 1999 ).
The biological communities in aquatic ecosystems are formed by organisms that have developed several adaptations throughout evolution to certain environmental conditions and have different tolerances and responses to environmental changes. And it is these responses of biological communities to changes in the original environmental conditions that are used to analyze the quality of their environment (ALBA-TERCEDOR, 1996).
In this context, the bioindicators are widely used, these in turn are species chosen for their sensitivity or tolerance to various parameters such as organic pollution or other types of pollutants (BUSS et al., 2003). When the conditions of a habitat change, organisms sensitive to such changes tend to decline in number or even be locally extinct, since those tolerant tend to increase their number by decreased competition. So unexpected changes in the distribution of species in the community may be interpreted as signs of some kind of contamination (ALBA-TERCEDOR, 1996).
Among the various organisms used as bioindicators, those most tested and used among researchers are the benthic macroinvertebrates. This is due to the fact that these organisms are ubiquitous, so they can respond to disturbances in all aquatic environments and in all periods and quickly; They have large number of species, which offers a wide spectrum of responses; even in small water bodies, fauna can be extremely rich; They are relatively sedentary, allowing for more efficient analysis of the effects of disturbances, and moreover, this is a simple collection method and low cost that does not cause large effects to the environment, and the bodies are relatively easy to identify (BUSS et al ., 2003).
Also according to Buss et al. (2003), these organisms inhabit the bottom of aquatic ecosystems for at least part of their life cycle and are associated with various types of substrates, both organic (leaf litter, aquatic weeds) and inorganic (gravel, sand, rocks etc. ).
In this sense, it is clearly important that the sediment has to benthic organisms. Buss et al. (2003) states that the pellet can be considered as the resultant slot integration of all processes that occur in an aquatic ecosystem.
For Jesus et al. (2004) sediment, due to its high absorption capacity and accumulation, has greater concentrations of pollutants such as heavy metals, from the column of water. Various biotic and abiotic processes can also remobilize these pollutants substrate, thus becoming secondary sources of pollution affecting water quality and leading to bioaccumulation in the food chain. Consequently, contamination of sediment is a significant environmental problem worldwide. For these reasons the organisms that live in the feelings turn out to be most affected by environmental degradation, and being in the early part of bioaccumulation chain.
The benthic macroinvertebrates receive great influence of some physicochemical characteristics of aquatic environments, among these, we highlight the chain speed, quality and availability of food, type of substrate, water temperature and concentration of gases such as oxygen. These variables have a strong influence on the composition of these bodies, and their changes can be detected by the change in the amount and dominance among them (SILVA, 2007).
According the statements of Buss et al. (2003), in the late 1960s started up joint efforts in Europe to test the applicability of biomonitoring system. Most countries, except Germany and the Netherlands, decided to reject these methods and started using valuation methodologies represented by biotic indices of benthic macroinvertebrates, which consisted of assigning a "value" (score) for each species based on their tolerance to impact (METCALFE, 1989). Various biotic indices have emerged and have been tested since then, but a special index gained prominence, the Biological Monitoring Working Party Index - BMWP Index.
In 1976, it was created in Britain a working group to discuss and synthesize knowledge about the contents, causing the system known as Biological Monitoring Working Party score system (BMWP). In subsequent years, the BMWP Index has been tested and revised and currently considers macroinvertebrates identified to the taxonomic level of family, with values between 1 and 10 assigned based on their sensitivity to organic pollutants.
Families sensitive to high levels of pollutants are given higher values, while tolerant families receive lower values. After the case record of the taxon in one location, it add up the figures for each family, giving a final value for the location. The higher this value, the entire locality.
The application of the index created by Balloch et al. (1976) called Avarege Score Per Taxon - ASPT, which is the average of values each found family, this index became more efficient (ARMITAGE et al, 1983; WALLEY and FONTANA, 1998; HAWKES and WALLEY, 1997).
4.2. Methodological Aspects
As mentioned above, the original methodology of BMWP Index is based on the sum of values that are assigned to each macroinvertebrate group by their ability to survive in different levels of water quality in aquatic ecosystems.
This index ordered the families of aquatic macroinvertebrates in 9 groups, following a smaller gradient greater tolerance of the organisms on the organic pollution. Each family did match a score, which ranges 10-1, and households more sensitive to contamination receiving the highest scores, coming in descending order by 1, which are those more tolerant. Table 1 shows the values of the original scoring method.
Because it is a methodology developed in Britain, resulting in the determination of specific agencies for the region, it was necessary adjustments for application of the methodology in regions with other features. As stated by Junqueira and Campos (1998), it was the case of the Alba-Tercedor researchers and Sánchez-Ortega (1998) who needed to adapt the study and made a first modification of the index for the Iberian Peninsula, and it added new families to the original table and changed the score of some. Therefore correlated values BMWP' with five degrees of contamination by flagging them with the quality of the water as shown in Table 2.
Table 1. Score by family.
FAMILIES |
SCORE |
Siphlonuridae, Heptageniidae, Leptophlebiidae, Potamanthidae, Ephemeridae Taeniopterygidae, Leuctridae, Capniidae, Perlodidae, Perlidae, Chloroperlidae |
10 |
Aphelocheiridae Phryganeidae, Molannidae, Beraeidae, Odontoceridae, Leptoceridae, Goeridae Lepidostomatidae, Brachycentridae, Sericostomatidae, Calamoceratidae , Helicopsychidae, Megapodagrionidae Athericidae, Blephariceridae, Astacidae, Lestidae, Calopterygidae, Gomphidae, Cordulegastridae, Aeshnidae |
8 |
Corduliidae, Libellulidae, Psychomyiidae, Philopotamidae, Glossosomatidae Ephemerellidae , Prosopistomatidae, Nemouridae, Gripopterygidae |
7 |
Rhyacophilidae, Polycentropodidae, Limnephelidae, Ecnomidae, Hydrobiosidae, Pyralidae, Psephenidae, Neritidae, Viviparidae, Ancylidae, Thiaridae, Hydroptilidae, Unionidae, Mycetopodidae , Hyriidae |
6 |
Corophilidae, Gammaridae, Hyalellidae , Atyidae , Palaemonidae , Trichodactylidae, Platycnemididae, Coenagrionidae, Leptohyphidae, Oligoneuridae, Polymitarcyidae, Dryopidae, Elmidae, Helophoridae, Hydrochidae, Hydraenidae , Clambidae, Hydropsychidae |
5 |
Tipulidae, Simuliidae, Planariidae, Dendrocoelidae, Dugesiidae, Aeglidae Baetidae, Caenidae, Haliplidae, Curculionidae, Chrysomelidae, Tabanidae, Stratyiomyidae, Empididae, Dolichopodidae, Dixidae, Ceratopogonidae |
4 |
Anthomyidae, Limoniidae, Psychodidae, Sciomyzidae, Rhagionidae, Sialidae, Corydalidae, Piscicolidae, Hydracarina, Mesoveliidae, Hydrometridae, Gerridae, Nepidae, Naucoridae ( Limnocoridae ), Pleidae, Notonectidae, Corixidae, Veliidae, lodidae, Hydrophilidae, Hygrobiidae, Dytiscidae, Gyrinidae, Valvatidae, Hydrobiidae, Lymnaeidae, Physidae, Planorbidae |
3 |
Bithyniidae, Bythinellidae, Sphaeridae, Glossiphonidae, Hirudidae, Erpobdellidae, Asellidae, Ostracoda (all class), Chironomidae, Culicidae, Ephydridae, Thaumaleidae |
2 |
Oligochaeta (all class), Syrphidae |
1 |
Source: Modified from Junqueira and Campos (1998).
For the application of the above table, it is necessary to carry out the collection and removal of the macroinvertebrate community of a given ecosystem you want to study, exploring the various niches therein. A table with the families that was collected on site is elaborated with their respective scores. With this sum score is necessary to correlate the values obtained with the characteristics shown in Table 2 (below) for the evaluation of environmental health of the analyzed system.
Table 2. Values for interpreting the results of BMWP Index.
CLASS |
QUALITY |
VALUE |
MEAN |
COLOR |
I |
GOOD |
> 120
101 – 120 |
Very clean (pristine waters)
Unpolluted waters or system noticeably unchanged |
BLUE |
II |
ACCEPTABLE |
61 – 100 |
Are evident moderate pollution effects |
GREEN |
III |
DOUBTFUL |
36 – 60 |
Polluted waters (modified system) |
YELLOW |
IV |
CRITICAL |
16 – 35 |
Very polluted waters (much altered system) |
ORANGE |
V |
VERY CRITICAL |
< 16 |
Heavily polluted water (seriously affects system) |
RED |
Source: Modified from Junqueira and Campos (1998).
It is noteworthy that the BMWP Index has gained notoriety between the academic community in Brazil, as has been applied in national environmental prediction programs. This fact confirms the efficacy of the method and contributes to the promotion of research with the aim of continuous improvement in the way the method is conducted, applied to the national reality.
To monitor water quality is very important for society, but traditional methods are expensive and inadequate, not considering the complexity of aquatic systems.
To do this it uses changes in biotic communities to assess the impacts of anthropogenic changes in their habitats. A great group of organisms for this function are the benthic macroinvertebrates, this partly because they live at least a portion of their life in the substrate, which is greatly affected by environmental change, and records the concentrations of pollutants. Moreover, these organisms possess some intrinsic characteristics such as low mobility, a large diversity of species and reset wide range of environmental changes.
There are many researches on benthic macroinvertebrates and their use as bioindicators as well as several methods developed to assess water quality from your survey, as BMWP.
The Index BMWP features quickly, practical and inexpensive an assessment of the environmental health of aquatic ecosystems and can be widely used as a tool for the management of water resources. Can also assist in conducting environmental solutions for freshwater ecosystem recovery acting directly on the sensitivity of the issue, because the results fall perpendicularly on the cause of the problem in a dynamic way. It helps to comprehend the complete metabolism of the ecosystem studied.
However, it is observed that there are still further research on how the composition of the community of these organisms are affected by several factors such as the type of substrate and how pollutants interact with those communities.
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1. Mestrando no Programa de Pós-Graduação de Engenharia de Biossistemas da Universidade Federal Fluminense, Niterói – Rio de Janeiro (rafael-esteves@hotmail.com)