Next Article in Journal
Field-Based Analysis of Runoff Generation Processes in Humid Lowlands of the Taihu Basin, China
Next Article in Special Issue
The Urgent Need for River Health Biomonitoring Tools for Large Tropical Rivers in Developing Countries: Preliminary Development of a River Health Monitoring Tool for Myanmar Rivers
Previous Article in Journal
Systems Approach to Management of Water Resources—Toward Performance Based Water Resources Engineering
Previous Article in Special Issue
The Macrophyte Index for Rivers (MIR) as an Advantageous Approach to Running Water Assessment in Local Geographical Conditions
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Water
Volume 12
Issue 4
10.3390/w12041215
water-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

A Fish-Based Index of Biotic Integrity for Neotropical Rainforest Sandy Soil Streams—Southern Brazil

by
Gabriel Gonino
1,2,*,
Evanilde Benedito
2,
Vivian de Mello Cionek
3,
Maria Teresa Ferreira
4 and
João Manuel Oliveira
4,5
1
Instituto Federal Catarinense (IFC-Campus Ibirama), Ibirama 89140-000, Brazil
2
PGB/PEA/NUPELIA, State University of Maringá, Maringá 87020-900, Brazil
3
Departamento de Ensino Científico e Tecnológico, Universidade do Estado de Santa Catarina, Florianópolis 88035-901, Brazil
4
Forest Research Centre (CEF), School of Agriculture, University of Lisbon, Tapada da Ajuda, 1349-017 Lisbon, Portugal
5
Centre for Ecology, Evolution and Environmental Changes (cE3c), Faculty of Sciences, University of Lisbon, 1749-016 Lisbon, Portugal
*
Author to whom correspondence should be addressed.
Water 2020, 12(4), 1215; https://doi.org/10.3390/w12041215
Submission received: 28 February 2020 / Revised: 7 April 2020 / Accepted: 20 April 2020 / Published: 24 April 2020
(This article belongs to the Special Issue Use of Aquatic Biota to Detect Ecological Changes in Freshwater: Current Status and Future Directions)
Browse Figures
Versions Notes

Abstract

:
Multimetric indices are considered a low-cost and rapid means of assessing ecological integrity in streams. This study aimed to develop a fish-based Index of Biotic Integrity (N3S-IBI) in an agricultural region within the domains of the Atlantic rainforest in Brazil. We sampled 23 first-order streams and used large-scale land use and a local physical condition index to choose reference sites and to classify sites according to the disturbance level. N3S-IBI resulted in six metrics (Simpson’s dominance; the numbers of Characiformes and non-native individuals (Poecilia reticulata); and the percentages of Characidae species, intolerant insectivorous individuals, and tolerant species), contemplating tolerance, composition, abundance, richness, trophic habits, and origin. The low number of metrics contributes to a quick and easy biomonitoring process. N3S-IBI showed an excellent performance to separate least and most disturbed sites in our study area and can provide additional knowledge about anthropogenic effects within this impacted region. In fact, this tool could be utilized by managers to direct restoration actions for the most disturbed sites and to strengthen the preservation of the least disturbed sites.

1. Introduction

Surface freshwaters are among the most disturbed ecosystems on the planet and in recent decades have suffered faster rates of decline in biodiversity than those observed in terrestrial ecosystems [1,2]. The conversion of natural landscapes for human use is among the main drivers of the impact on these systems [3,4,5,6]. In fact, agricultural practices are the most widespread cause of stream degradation, degrading riparian areas, decreasing bank stability, modifying natural hydrological patterns, increasing chemical and sediments inputs (including pesticides, heavy metals, and herbicides), and altering natural habitats and biological communities [1,3,7,8,9,10,11,12]. Indeed, many studies have shown that agriculture and the alterations derived from its practices present strong influence on the integrity of fish communities, affecting ecological traits related to feeding and reproduction and promoting the increase in the abundance of non-native and tolerant species [10,12,13,14,15].
The Southern region of Brazil has also experienced an increase in crop areas in the last decades, mainly sugarcane, corn, wheat, and soybean plantations, with direct impacts on the watersheds [16,17]. Common endpoints are the replacement of fish species that are habitat and feeding specialists by widespread generalists and the increasing of species that are tolerant to a wide range of physicochemical conditions [10,18,19]. The predominance of Characiformes and Siluriformes species in preserved streams of the Neotropical region is well known, being constantly near to 80% in headwaters [20,21,22,23]. However, in disturbed conditions there may be changes in this composition, including the increase of more tolerant species of Perciformes and Cyprinodontiformes [24,25,26]. For example, the high representativeness of non-native Poecilia reticulata Peters, 1859, and native Phalloceros harpagos Lucinda, 2008, both Cyprinodontiformes, seems to be common in disturbed first-order streams of the upper Paraná river basin [20,27,28,29].
Given the degradation that aquatic resources in these regions are experiencing, the development of tools to assess their ecological status is a major challenge in the management of freshwater ecosystems. One of the most used methods for assessing the ecological integrity of streams and rivers is the Index of Biotic Integrity (IBI). This method was first presented by Karr [30] and was later adapted to a wide range of conditions worldwide including Temperate [31,32], Mediterranean [33,34], and Neotropical streams [10,18,35,36]. The IBI is based on the principle that biological communities respond to human changes in a predictable and quantifiable manner, representing an integration of the physical, chemical, and biological conditions of the system [37]. This type of tools is composed by a set of metrics related to the species composition and functional attributes of biological assemblages, such as taxa richness, trophic and habitat niche, and abundance. Application of this multimetric approach often involves the adaptation of metrics for each river type, i.e., to the specific biota and environmental conditions under study, and the subsequent use of specific methods for their selection [38]. The selected metrics should be sensitive to different types of degradation and respond in a predictive way to the pressure gradients. The value of the index at a site is compared with the expected value on the same river type representing the least disturbed conditions (reference conditions), with the stream biotic integrity varying according to the degree of this deviation. Neotropical streams encompass a variety of reference conditions, fish communities, and types of pressures that need to be addressed on a regional basis.
Giving the challenges of using biotic indicators in environmental management and regulations in Brazil [39], there is an urgent need to provide managers and decision makers with user-friendly tools based on the biotic component of the aquatic systems. In this paper, our goal was to develop a fish-based IBI for an agricultural dominated Neotropical region within the Atlantic rainforest domain, being the first one focused only on sandy soil first-order streams. Thus, we expected to detect changes in fish assemblages according to the environmental conditions of these types of streams. This sandstone region has peculiar drainage characteristics regarding soil and sediment transport—for example, removal of forests to give place to other land use types increases siltation in a more pronounced manner than in other nearby areas [40]. Headwater streams represent the maximum interface with the landscape [41] and therefore are extremely vulnerable to human pressures, including the ecological effects on its native fish assemblages [42,43]. Although research has highlighted the consequences of anthropic impacts on stream biotic integrity on some agricultural areas of the Atlantic rainforest region [10,19,26,35], no studies were conducted to exclusively reveal those effects on fish assemblages in headwater streams of a single geomorphological unit. Moreover, our work presents an unusually large number of statistically tested metrics, aiming at greater robustness of the IBI, including testing with combined guilds.

2. Materials and Methods

2.1. Study Area and Site Selection

We selected 23 streams that drain small catchments in four sub-basins of the upper Paraná river basin (Ivaí, Paraná, Paranapanema, and Pirapó) (Figure 1). The study reaches were similar in catchment size and channel dimensions and represented small headwater streams. The upper Paraná river region is mainly comprised of sandy soils with homogeneous grain sizes, originated from Caiuá Sandstone geological formation, and within the domains of the semi-deciduous forest, originating from the Atlantic rainforest [44,45,46,47]. This biome is characterized by a tropical climate with an average annual rainfall of 1626 mm year−1. The average annual temperature and relative humidity are 27.9 °C and 68.8%, respectively [48]. Although study sites presented differences in land use at the catchment scale, the land cover of the region is dominated by agricultural uses (e.g., sugarcane, corn, peanut, orange, and soy). The selection of the study sites followed Cionek [49] and was primarily based on land-use at the catchment level in order to provide a wide range of environmental conditions that could represent distinct degradation status of the streams. The selection was conducted in ArcGis software® (ESRI, Redlands, CA, USA) through the delimitation of headwater watersheds. We used SRTM images to create and Landsat 8 OLI images to verify the stream basins. For each first order watershed, we calculated land-use percentage of agriculture (e.g., sugarcane, corn, peanut, orange, soy), pasture (grassland without use or used for extensive livestock), forest (natural forest, excluding eucalypt plantation), urban and exposed soil areas (usually temporarily exposed, before the next plantation—Table S1). All classifications were confirmed in the field. We included in our study the streams that were in watersheds with the largest proportion of each land use typology. In-stream and riparian environmental conditions were assessed by means of both a Rapid Assessment Protocol (described below) and limnological parameters (i.e., conductivity, pH, water temperature, turbidity, water velocity—Table S2).

2.2. Measuring Anthropogenic Disturbance at Local-Scale

A Rapid Assessment Protocol (RAP) especially designed for the study region [50], based on that proposed by Barbour et al. [51], was used to quantify local effects of anthropogenic disturbance at the sites during sampling visits (Table S3). RAP consists of nine parameters that are visually evaluated and scored as poor (scores 0 to 5), regular (scores 6 to 10), good (scores 11 to 15), and optimal (scores 16 to 20). The mean value of all parameters is used to determinate the stream physical condition. RAP cannot be applied without previous training, in order to properly identify natural features and provide an accurate evaluation. We always evaluate 30 m stretches—a feasible length to be visually assessed. RAP quantifies the underwater available cover, underwater habitat complexity, velocity/depth combinations, channel sinuosity, water level amplitude, channel integrity, bank stability, bank vegetative protection, and vegetation conservation on the riparian area.

2.3. Reference Conditions and Site Classification

The reference conditions were defined as the best conditions given today’s state of the landscape, i.e., the least disturbed sites [50,52]. Based on the criteria used by other authors for the selection of reference sites [53,54,55] and considering the particular conditions of our sandy soil streams, we proposed pressure variables at two spatial scales. Regarding the catchment level, we considered the following land cover classes (see description of each type of land-use in Section 2.1): agriculture, urban (these two types of land-use are by far the most impactful in our study area) [56]; pasture (mostly, significantly less impacted areas than those in the previously two land uses), and forests. Thus, according to the RAP scores (i.e., local characterization) and predominant land use type (i.e., catchment characterization), and following the procedures proposed by Whittier et al. [31], we used assessment scores as least disturbed sites (LD), intermediate sites (ID) and most disturbed sites (MD). We defined LD sites as those meeting three criteria: (i) to feature the lowest percentage of agriculture at the catchment level (less than 35%, including sugarcane crops); (ii) absence of urbanized areas in the watershed; and (iii) classified as excellent or good, according the RAP. The MD sites were defined as those (i) presenting the highest percentage of agriculture + urban at the catchment level (more than 35%) and (ii) classified as poor or regular, according the RAP. The ID sites were those presenting (i) low agricultural + urban land use at the catchment level but degraded local habitat conditions (poor or regular) or (ii) low disturbed habitats (excellent or good) but high agricultural + urban land use. Similarly to Santos and Esteves [10], in a highly agricultural area in southern Brazil, we could expect non-pristine reference sites (including areas with low natural forest cover). However, we believe that these criteria assured us the selection of a group of sites that were significantly less altered than those clearly impacted by agriculture and urban land use.

2.4. Fish Sampling

Fish assemblages were sampled in April 2015, which represents the beginning of the drought period, to minimize the effect of rainfall on the habitat structure. The streams do not dry out completely in the low water season. We used daytime electrofishing with three consecutive efforts applied to each 80-m stream reach [57]; the sites were seine-blocked to prevent fishes from escaping. All individuals were counted and screened on the field. Up to 10 individuals of each morphospecies (whenever possible) were anesthetized with benzocaine [58] and fixed in 10% formalin, while the remainder were returned alive to nature. From each individual, we obtained total weight (g), standard length (cm), and identification based on specialized literature [59,60]. Specimens from all species were deposited in the Ichthyology Collection of NUPELIA (Nucleus of Research in Limnology, Ichthyology and Aquaculture) from the State University of Maringá (UEM), Brazil.

2.5. Metrics Evaluation and IBI Construction

Biological characteristics of fish species were determined from the literature and according to Pereira [61] (Table S4). The Index of Biotic Integrity for Neotropical Sandy Soil Streams (N3S-IBI) was developed following Whittier et al. and Krause et al. [31,55]. First, a list of 227 candidate metrics (Table S5) were compiled from the literature and organized into the following groups: diversity/abundance, composition (individuals), composition (family/order), origin (native/non-native), habitat guilds, reproductive guilds, tolerance, and trophic guilds. Metrics were calculated using standardized measures (1000 m2 for every candidate metric) of number, biomass and proportion of taxa or individuals. The candidate metrics that passed the following four criteria were selected: (a) range of homogeneity test, that checks the distribution of metric values across all of the available data and allows for the elimination of those with very small ranges; (b) responsiveness to disturbances, performed with a Kruskal–Wallis test (p < 0.1) to verify the capacity of the metrics to distinguish between the least and most disturbed sites; (c) redundancy, performed with a Spearman correlation test to choose metrics without redundant information with other metrics (r > 0.70), and (d) range test for metric values, based on the analyses of box plots of the metric scores (medians) for the LD and MD sites, to check if there was no overlap between most values of the two groups.
For metric scoring and calculation of final N3S-IBI, we used the 75th percentile of metric values of the LD sites for each positive metric (i.e., those that are highest in the least disturbed sites) as the scoring ceiling, to reduce the restriction of LD, and the 5th percentile of the distribution of values at all sites as the scoring floor (score = 0). Metric scores between the 5th and 75th percentile were interpolated linearly [31]. For negative metrics, we reversed the floor and ceiling values. The scored metrics were summed and divided by the number of metrics, and the index was scaled to a range of 0 to 1, where 0 corresponds to the worst and 1 to the best quality of each stream [62]. The quality is expressed within one of five quality classes (excellent, good, regular, poor, and very poor), thereby facilitating the communication of results to non-specialists.
A comparison between the disturbance categories of sites (i.e., least, intermediate, and most disturbed) was made using the Kruskal–Wallis test (p < 0.05) to verify the ability of IBI to classify environmental quality. In addition, we checked the correlation between the final index scores of the N3S-IBI and RAP and land use values for all sites using Spearman’s test. We used R software for all statistical analysis [63].

3. Results

3.1. Fish Assemblages

The selected method for establishing reference conditions returned to us 7 LD, 9 ID, and 7 MD sites where we collected 5166 individuals comprised of 32 fish species, 13 families, and 6 orders (Table S4). For all sites combined, Cyprinodontiformes was the most abundant order (63.3%), followed by Siluriformes (26.7%) and Characiformes (8.7%) (Table 1). The Cyprinodontiform non-native species P. reticulata (Poeciliidae) was the most abundant species (58.0%), especially in MD sites where it represented 70.7% of the captures, while the native P. harpagos (Poeciliidae) was the most captured Cyprinodontiform species in the LD sites (27.0%). The Siluriform Hypostomus ancistroides (Ihering, 1911) (Loricariidae) presented the highest frequency of occurrence, being captured in 16 out of 23 streams.

3.2. N3S-IBI Data Development

Of all candidate metrics, only 6 metrics were approved in all tests to compose the final N3S-IBI (Table 2). Most of the metrics (119) were eliminated during the responsiveness test, and only six out of 13 metrics passed the final range test (Figure 2). The chosen metrics were Simpson’s dominance (diversity), number of Characiformes individuals (composition (individuals)), percentage of Characidae species (composition (family/order)), number of non-native individuals (origin), percentage of tolerant species (tolerance), and percentage of intolerant insectivorous (individuals) (trophic guild).
Final scores of the N3S-IBI, RAP values (see also Tables S6 and S7), and land use are shown in Table 3. Positive Spearman’s correlation between N3S-IBI and RAP for all sites was marginally significant (ρ = 0.41; p = 0.055), while the negative correlation between N3S-IBI and agricultural + urban land use (ρ = −0.31, p = 0.15) was not statistically significant although it was ecologically relevant [64]. There was a significant difference in N3S-IBI values between LD and MD sites (Kruskal–Wallis test: H = 9.52; p = 0.009; n = 23) (Figure 3).
The three streams from Paraná River basin presented IBI values between good and excellent (Table 3). These sites occur within or nearby an Environmental Protection Area (in Portuguese: Área de Proteção Ambiental das Ilhas e Várzeas do Rio Paraná). Streams from the Paranapanema river basin presented regular to excellent local habitat (RAP scores > 79) but only one showed an excellent biotic integrity, while the others were scored as poor or very poor. On the other hand, the streams of the Ivaí River basin presented a wide range of IBI values, across the gradient of very poor to excellent.

4. Discussion

The IBI for Neotropical sandy soil streams was composed of six metrics: Simpson’s dominance, number of Characiformes individuals, percentage of Characidae species, percentage of intolerant insectivorous individuals, number of non-native individuals, and percentage of tolerant species. Our hypothesis was not rejected, and the N3S-IBI showed an excellent performance to separate least and most disturbed sites in our study area. We agree with Karr and Chu [65] that the selection of appropriate metrics is the key step in the proper functioning of this type of index. In fact, appropriate statistical criteria and sufficient expertise about the studied region are essential to the choice of metrics, and we believe that those selected for our N3S-IBI were properly representative of the sandy bottom streams of the upper Paraná river basin.
Some characteristics of our metrics were: (i) Simpson’s dominance: it is a metric used in some IBIs, in which disturbed streams tend to show dominance of few species and present low overall species richness, whereas more preserved streams exhibit few dominant species and more rare species [10,66,67]; (ii) number of Characiformes individuals: the abundance of individuals from this order tends to decrease in disturbed streams, giving place to the occupancy of more disturbance-tolerant species, such as P. reticulata [66]; this same pattern may also be expected for the (iii) percentage of Characidae species, although both metrics were not redundant; (iv) percentage of intolerant insectivorous individuals, which tend to be replaced in disturbed sites by tolerant species showing generalist feeding behaviors [30,37]; (v) percentage of tolerant species: tolerance is a frequent metric for biomonitoring tools and was also important for distinguishing our streams [18,26,66]; (vi) number of non-native individuals: some authors have pointed out the relevance of non-native fishes as indicators of disturbance intensity [68,69,70], and in our study sites the non-native species are represented by P. reticulata, a very tolerant species to environmental degradation [71].
The low abundances and/or the absence of Characiformes/Characidae in the most degraded streams represent a good predicting metric for the studied systems. We found a strong relationship between stream degradation and the decrease of both Characiform and Characid species and individuals. Our degraded sites were frequently depleted of riparian vegetation, and their streams presented eroded channels, low potential cover for fish, high habitat homogeneity, and substrates revealing a negligible presence of elements other than sand. Although these species represent a large range of trophic guilds, most of them are water column feeders and intolerant to habitat destruction and persistent water quality degradation [35]. Other Neotropical IBIs, that somehow followed robust metric selection processes, have found this relation [35,39], although Santos and Esteves [10] had not selected these metrics for an agricultural dominated region of São Paulo state. We believe that the higher number of Characid species in our study, all intolerant to degradation, could have strengthened the response of this metric.
A decrease of insectivores typically reflects a degradation of the invertebrate food base of lotic systems and turned out to be a good predictor of stream integrity [37]. In our study, the impoverishment of the invertebrate fauna might be directly associated to the absence of riparian protection in the most disturbed sites. In fact, the prevalence of a few riparian plant species, with dominant grass species along the immediate margin of streams, tends to homogenize the invertebrate community, which represents an essential food resource to intolerant insectivorous fish [35,72,73,74]. Additionally, land-use and water quality degradation (including substances as pesticides and heavy metals) may have reduced the diversity and richness of macroinvertebrates in the most disturbed sites, decreasing the food availability for these species [52,75,76].
The occurrence of Cyprinodontiformes is quite common in tropical streams [8,27,28,29,77,78], especially because they present ovoviviparity as a reproductive strategy and a wide variety of feeding habits [29,79,80,81], characteristics only common to these species in the sampled sites. Our results showed that the native Cyprinodontiform (P. harpagos) is more abundant in the least-disturbed sites, while in the most-disturbed sites it was replaced by the non-native P. reticulata. Such a change in the identity of the Cyprinodontiform species occurrence between LD and MD sites contributed to the good performance of the N3S-IBI for stream quality assessment. The ability of non-native fishes to thrive in degraded conditions and consequently to impact natural fish assemblages has also been detected worldwide [68,69,70] and represents one of the main causes of decline in biotic integrity. Moreover, while studying Neotropical streams, Ferreira and Casatti [66] used the percentage of P. reticulata as a metric, since the presence of this species is one of the most prominent indicators of degraded condition to streams on the South of Brazil. However, P. harpagos was also used as an indicator of stream degradation on another IBI for Neotropical streams [10], although it was not statistically significant for this approach in our study. This is an example of the importance of developing different IBIs of regional scale in multi-diverse regions. Ruaro et al. [71] proposed a multimetric index to another Neotropical basin and analyzed the influence of non-native species on the loss of ecological integrity. Our study brings new outcomes for Neotropical streams from a nearby region that drains through Caiuá Sandstone geological formation, helping to fill a knowledge gap in one of the most impacted regions by monocultures, providing more information about these anthropogenic impacts.
Biotic indices can be developed with distinct biotic communities, such as periphyton, macroinvertebrates, and fishes. Each presents particular pros and cons regarding its application [82]. However, larger-sized organisms (like fish) are readily identified and sorted in the field, compared to the time required for screening and identification of macroinvertebrates [37]. This is particularly relevant for the IBIs, which intend to be expeditious tools of environmental quality assessment. Moreover, within our study region, fishes are amongst the most popular and easily recognizable organisms to raise awareness about results provided by the N3S-IBI. This index was composed of six metrics, which makes a quick and easy biomonitoring tool. Therefore, like Ruaro and Gubiani [83], we also believe that a simple and fast index is efficient for monitoring aquatic environments. It is practically impossible to apply a single monitoring tool to an entire country when it has the continental proportions and the heterogeneity of biomes of Brazil. However, we support proposals such as that of Stoddard et al. [84], with the development of local and regional tools, interconnected in a single monitoring system. Although there is no standardization in the collection methodologies for studies of fish-based IBIs in Brazil, there are some papers developing this tool in many states, especially in the South-Central region [10,35,39,85,86,87]. However, we suggest the adoption of an electrofishing protocol as an initial step for a single regional tool that would facilitate the use of fish data collected by colleagues throughout all localities, similar to the one used by Oliveira et al. [88] in Portugal.
The establishment of reference sites is one of the first steps in assessing the ecological status of streams using IBIs [78,89] and defined as being those with least anthropic influence. Our reference and disturbed sites did not overlap in the results. In fact, the MD and LD sites were totally separated by the IBI values, and the ID sites were equally distributed among them. We understand that the same did not occur with the RAP classification because it is a specific habitat tool, and the visual evaluation does not allow for the identification of larger-scale and limnological influences; however, it was useful to determine our reference sites, and this should be applied as a complementary tool. Although some authors did not find a relation between land use and biotic integrity [90,91], we also believe that N3S-IBI was significantly affected by land use at a larger scale, which proved to be a useful tool to classify our reference sites, clearly identifying the degree of disturbance in the sampled streams. Fish assemblages supply an integrated response to environmental changes that can be accounted for by means of community composition alterations. Variation of physical or chemical indices can be temporary or not large enough to allow the proper detection of the multiple human impacts on freshwater ecosystems [37]. In fact, the biological indices represent an integration of the physical, chemical, hydrological, and biological conditions of the system; ultimately, it is not possible to measure all factors that impact biotic integrity [37]. However, the characterization of any environmental factor affecting the aquatic biota, as the habitat quality (e.g., provided by the RAP) can provide an initial profiling of the ecosystems and improve our ability to interpret biological responses [92]. Additionally, it can show us that biological responses may not vary until a sufficient alteration has occurred within the systems (i.e., resilience) [93].
Often public management agencies collect information restricted only to monitoring fluviometric levels, physical and chemical parameters, and quantification of specific bacteria [94,95], possibly due to the volume of work and costs. Water is a vital resource for all living beings, so it is understood that its monitoring must go beyond these parameters and include the biotic integrity of the aquatic communities. Initiatives to conserve freshwater systems in a large country such as Brazil go through the development of regional tools. In this way, although it needs to be validated, N3S-IBI is a well-developed tool for freshwater systems in a region of approximately 3 million ha [95]. On the other hand, it is imperative to improve the monitoring system. Thus, all actions concerning the collection of biological integrity data from aquatic systems are more than welcome, whether if they are from a public institution or non-governmental groups. Environmental researchers have been neglected in Brazil over the years, but the political role of their contributions [85] becomes clearer when tools like N3S-IBI are an accessible facilitator in the engagement of people inside and outside the control agencies and the academic environment. In fact, this tool could be utilized by managers to direct restoration actions for the most disturbed sites and to strengthen the preservation of the least disturbed ones.

Supplementary Materials

The following are available online at https://www.mdpi.com/2073-4441/12/4/1215/s1, Table S1: Abiotic variables at the catchment scale., Table S2: Local abiotic variables., Table S3: Rapid Assessment Protocol adapted to the study region., Table S4: Classification of sampled species according to their biological characteristics., Table S5: Candidate metrics for the N3S-IBI., Table S6: RAP metrics., Table S7: Rapid Assessment Protocol—Field Spreadsheet.

Author Contributions

G.G. designed the sample collection, conducted the field work, wrote the manuscript draft, and led the manuscript revision. E.B. and V.d.M.C. contributed to the design of the sample collection and revised the manuscript. M.T.F. contributed to the revision of the manuscript. J.M.O. contributed to the statistical analysis and supervised all manuscript preparation steps. G.G., E.B., V.d.M.C., M.T.F and J.M.O. commented on the manuscript. G.G., E.B., V.d.M.C., M.T.F and J.M.O. have read and agreed to the published version of the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES)—Finance Code 001, grant number PDSE 88881.135421/2016-01, by a CNPq grant number 303556/2017-0 and by an IFC–Ibirama grant number 23474.000039/2015-41.

Acknowledgments

The authors acknowledge all of field work personnel, the team of the Ecologia Energética Lab.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

References

  1. Carpenter, S.R.; Cole, J.J.; Pace, M.L.; Batt, R.; Brock, W.A.; Cline, T.; Coloso, J.; Hodgson, J.R.; Kitchell, J.F.; Seekell, D.A.; et al. Early warnings of regime shifts: A whole-ecosystem experiment. Science 2011, 332, 1079–1082. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Saunders, D.L.; Meeuwig, J.J.; Vincent, A.C.J. Freshwater protected areas: Strategies for conservation. Conserv. Biol. 2002, 16, 30–41. [Google Scholar] [CrossRef] [Green Version]
  3. Allan, J.D. Landscapes and Riverscapes: The influence of land use on stream ecosystems. Annu. Rev. Ecol. Evol. Syst. 2004, 35, 257–284. [Google Scholar] [CrossRef] [Green Version]
  4. Sabater, S.; Elosegi, A. River Conservation: Challenges and Opportunities Concluding Remarks on River Conservation; Rubes Editorial.; BVA: Bilbao, Spain, 2013; ISBN 978-84-92937-47-9. [Google Scholar]
  5. Ferreira, I.J.M.; Bragion, G.R.; Ferreira, J.H.D.; Benedito, E.; Couto, E.V. Landscape pattern changes over 25 years across a hotspot zone in southern Brazil. South. For. 2019, 81, 175–184. [Google Scholar] [CrossRef]
  6. Alves, G.H.Z.; Santos, R.S.; Figueiredo, B.R.S.; Manetta, G.I.; Message, H.J.; Pazianoto, L.H.R.; Guimarães, G.B.; Benedito, E.; Couto, E.V. Misguided policy may jeopardize a diverse South Brazilian environmental protection area. Biota Neotrop. 2019, 19, e20180574. [Google Scholar] [CrossRef]
  7. Barletta, M.; Jaureguizar, A.J.; Baigun, C.; Fontoura, N.F.; Agostinho, A.A.; Almeida-Val, V.M.F.; Val, A.L.; Torres, R.A.; Jimenes-Segura, L.F.; Giarrizzo, T.; et al. Fish and aquatic habitat conservation in South America: A continental overview with emphasis on Neotropical systems. J. Fish Biol. 2010, 76, 2118–2176. [Google Scholar] [CrossRef]
  8. Winemiller, K.O.; Agostinho, A.A.; Caramaschi, É.P. Fish ecology in Tropical streams. In Tropical Stream Ecology; Dudgeon, D., Ed.; Elsevier: Amsterdam, The Netherlands, 2008; pp. 107–146. ISBN 9780120884490. [Google Scholar]
  9. Hepp, L.U.; Santos, S. Benthic communities of streams related to different land uses in a hydrographic basin in southern Brazil. Environ. Monit. Assess. 2009, 157, 305–318. [Google Scholar] [CrossRef] [PubMed]
  10. Santos, F.B.; Esteves, K.E. A fish-based index of biotic integrity for the assessment of streams located in a sugarcane-dominated landscape in southeastern Brazil. Environ. Manag. 2015, 56, 532–548. [Google Scholar] [CrossRef]
  11. Henley, W.F.; Patterson, M.A.; Neves, R.J.; Lemly, A.D. Effects of sedimentation and turbidity on lotic food webs: A concise review for natural resource managers. Rev. Fish. Sci. 2000, 8, 125–139. [Google Scholar] [CrossRef] [Green Version]
  12. Wang, L.; Lyons, J.; Kanehl, P.; Gatti, R. Influences of watershed land use on habitat quality and biotic integrity in Wisconsin streams. Fisheries 1997, 22, 6–12. [Google Scholar] [CrossRef]
  13. Bramblett, R.G.; Johnson, T.R.; Zale, A.V.; Heggem, D.T. Development and evaluation of a fish assemblage index of biotic integrity for northwestern Great Plains streams. Trans. Am. Fish. Soc. 2005, 134, 624–640. [Google Scholar] [CrossRef]
  14. Feld, C.K. Response of three lotic assemblages to riparian and catchment-scale land use: Implications for designing catchment monitoring programmes. Freshw. Biol. 2013, 58, 715–729. [Google Scholar] [CrossRef]
  15. Meador, M.R.; Goldstein, R.M. Assessing water quality at large geographic scales: Relations among land use, water physicochemistry, riparian condition, and fish community structure. Environ. Manag. 2003, 31, 504–517. [Google Scholar] [CrossRef] [PubMed]
  16. IBGE Censo Agro 2017. Home. Available online: https://censos.ibge.gov.br/agro/2017/ (accessed on 24 February 2020).
  17. Gonino, G.M.R.; Figueiredo, B.R.S.; Manetta, G.I.; Zaia-Alves, G.H.; Benedito, E. Fire increases the productivity of sugarcane, but it also generates ashes that negatively affect native fish species in aquatic systems. Sci. Total Environ. 2019, 664, 215–221. [Google Scholar] [CrossRef]
  18. Bozzetti, M.; Schulz, U.H. An index of biotic integrity based on fish assemblages for subtropical streams in southern Brazil. Hydrobiologia 2004, 529, 133–144. [Google Scholar] [CrossRef]
  19. Esteves, K.E.; Alexandre, C.V. Development of an index of biotic integrity based on fish communities to assess the effects of rural and urban land use on a stream in southeastern . Braz. Int. Rev. Hydrobiol. 2011, 96, 296–317. [Google Scholar] [CrossRef]
  20. Frota, A.; Message, H.J.; Oliveira, R.C.; Benedito, E.; Graça, W.J. Ichthyofauna of headwater streams from the rio Ribeira de Iguape basin, at the boundaries of the Ponta Grossa arch, Paraná, Brazil. Biota Neotrop. 2019, 19, 20180666. [Google Scholar] [CrossRef]
  21. Castro, R.M.C.; Casatti, L.; Santos, H.F.; Melo, A.L.A.; Martins, L.S.F.; Ferreira, K.M.; Gibran, F.Z.; Benine, R.C.; Carvalho, M.; Ribeiro, A.C.; et al. Estrutura e composição da ictiofauna de riachos da bacia do Rio Grande no estado de São Paulo, Sudeste do Brasil. Biota Neotrop. 2004, 4, 1–39. [Google Scholar] [CrossRef] [Green Version]
  22. Cetra, M.; Mattox, G.M.T.; Ferreira, F.C.; Guinato, R.B.; Silva, F.V.; Pedrosa, M. Headwater stream fish fauna from the Upper Paranapanema River basin. Biota Neotrop. 2016, 16, e20150145. [Google Scholar] [CrossRef] [Green Version]
  23. Lowe-McConnell, R.H. Ecological Studies in Tropical Fish Communities; Cambridge University Press: Cambridge, UK, 1987; ISBN 9780511721892. [Google Scholar]
  24. Alves, G.H.Z.; Tófoli, R.M.; Ganassin, M.J.M.; Hahn, N.S. Diet of Poecilia reticulata Peters, 1959 in streams from Paraná River basin: Influence of the urbanization. Acta Sci. Biol. Sci. 2016, 38, 313–318. [Google Scholar] [CrossRef] [Green Version]
  25. Caetano, D.L.F.; Oliveira, E.F.; Zawadzki, C.H. Fish species indicators of environmental variables of Neotropical streams in southern Brazil, upper Paraná River basin. Acta Ichthyol. Piscat. 2016, 46, 87–96. [Google Scholar] [CrossRef] [Green Version]
  26. Casatti, L.; Ferreira, C.P.; Langeani, F. A fish-based biotic integrity index for assessment of lowland streams in southeastern Brazil. Hydrobiologia 2009, 623, 173–189. [Google Scholar] [CrossRef]
  27. Casatti, L. Fish assemblage structure in a first order stream, southeastern Brazil: Longitudinal distribution, seasonality, and microhabitat diversity. Biota Neotrop. 2005, 5, 75–83. [Google Scholar] [CrossRef]
  28. Cetra, M.; Barrella, W.; Neto, F.L.; Martins, A.G.; Mello, B.J.; Almeida, R.S. Fish fauna of headwater streams that cross the Atlantic Forest of south São Paulo state. Check List 2012, 8, 421–425. [Google Scholar] [CrossRef] [Green Version]
  29. Cionek, V.D.M.; Sacramento, P.A.; Zanatta, N.; Ota, R.P.; Corbetta, D.D.F.; Benedito, E. Fishes from first order streams of lower Paranapanema and Ivaí rivers, upper Paraná River basin, Paraná, Brazil. Check List 2012, 8, 1158–1162. [Google Scholar] [CrossRef] [Green Version]
  30. Karr, J. Assessment of biotic integrity using fish communities. Fisheries 1981, 6, 21–27. [Google Scholar] [CrossRef]
  31. Whittier, T.R.; Hughes, R.M.; Stoddard, J.L.; Lomnicky, G.A.; Peck, D.V.; Herlihy, A.T. A structured approach for developing indices of biotic integrity: Three examples from streams and rivers in the western USA. Trans. Am. Fish. Soc. 2007, 136, 718–735. [Google Scholar] [CrossRef]
  32. Pont, D.; Hugueny, B.; Beier, U.; Goffaux, D.; Melcher, A.; Noble, R.; Rogers, C.; Roset, N.; Schmutz, S. Assessing river biotic condition at a continental scale: A European approach using functional metrics and fish assemblages. J. Appl. Ecol. 2006, 43, 70–80. [Google Scholar] [CrossRef]
  33. Magalhães, M.F.; Ramalho, C.E.; Collares-Pereira, M.J. Assessing biotic integrity in a Mediterranean watershed: Development and evaluation of a fish-based index. Fish. Manag. Ecol. 2008, 15, 273–289. [Google Scholar] [CrossRef]
  34. Hermoso, V.; Clavero, M.; Blanco-Garrido, F.; Prenda, J. Assessing the ecological status in species-poor systems: A fish-based index for Mediterranean Rivers (Guadiana River, SW Spain). Ecol. Indic. 2010, 10, 1152–1161. [Google Scholar] [CrossRef] [Green Version]
  35. Terra, B.F.; Hughes, R.M.; Francelino, M.R.; Araújo, F.G. Assessment of biotic condition of Atlantic Rain Forest streams: A fish-based multimetric approach. Ecol. Indic. 2013, 34, 136–148. [Google Scholar] [CrossRef]
  36. Van Oosterhout, M.P.; van der Velde, G. An advanced index of biotic integrity for use in tropical shallow lowland streams in Costa Rica: Fish assemblages as indicators of stream ecosystem health. Ecol. Indic. 2015, 48, 687–698. [Google Scholar] [CrossRef]
  37. Karr, J.R.; Fausch, K.D.; Angermeier, P.L.; Yant, P.R.; Schlosser, I.J. Assessing Biological Integrity in Running Waters. A Method and Its Rationale; Illinois Natural History Survey: Champaign, IL, USA, 1986. [Google Scholar]
  38. Pont, D.; Hughes, R.M.; Whittier, T.R.; Schmutz, S. A predictive index of biotic integrity model for aquatic-vertebrate assemblages of western U.S. streams. Trans. Am. Fish. Soc. 2009, 138, 292–305. [Google Scholar] [CrossRef]
  39. Carvalho, D.R.; Leal, C.G.; Junqueira, N.T.; Castro, M.A.; Fagundes, D.C.; Alves, C.B.M.; Hughes, R.M.; Pompeu, P.S. A fish-based multimetric index for Brazilian savanna streams. Ecol. Indic. 2017, 77, 386–396. [Google Scholar] [CrossRef]
  40. Castro, S.S.; Neto, J.P.Q. Soil erosion in Brazil from coffee to the present-day soy bean production. Dev. Earth Surf. Process. 2009, 13, 195–221. [Google Scholar]
  41. Vannote, R.L.; Minshall, G.W.; Cummins, K.W.; Sedell, J.R.; Cushing, C.E. The river continuum concept. Can. J. Fish. Aquat. Sci. 1980, 37, 130–137. [Google Scholar] [CrossRef]
  42. Böhlke, J.E.; Weitzman, S.H.; Menezes, N.A. Estado atual da sistemática dos peixes de água doce da América do Sul. Acta Amaz. 1978, 8, 657–677. [Google Scholar] [CrossRef]
  43. Castro, R.M.C. Evolução da ictiofauna de riachos sul-americanos: Padrões gerais e possíveis processos causais. Oecologia Aust. 1999, 06, 139–155. [Google Scholar] [CrossRef]
  44. Campos, J.B.; Romagnolo, M.B.; Souza, M.C. Structure, composition and spatial distribution of tree species in a remnant of the semideciduous seasonal Alluvial Forest of the upper Paraná River Floodplain. Braz. Arch. Biol. Technol. 2000, 43, 185–194. [Google Scholar] [CrossRef] [Green Version]
  45. EMBRAPA. Levantamento de Reconhecimento dos Solos do Estado do Paraná; EMBRAPA: Brasília, Brazil, 1984. [Google Scholar]
  46. Fernandes, L.A.; Magalhães-Ribeiro, C.M. Evolution and palaeoenvironment of the Bauru Basin (Upper Cretaceous, Brazil). J. South Am. Earth Sci. 2015, 61, 71–90. [Google Scholar] [CrossRef]
  47. Torres, E. As Transformações Históricas e a Dinâmica Atual da Paisagem nas Microbacias dos Ribeirões: Santo Antonio-SP, São Francisco-PR e Três Barras-MS; Universidade Estadual Paulista (UNESP): São Paulo, Brazil, 2003. [Google Scholar]
  48. IAPAR, Instituto Agronômico do Paraná. Médias Históricas em Estações do IAPAR. Available online: http://www.iapar.br/pagina-668.html (accessed on 27 December 2018).
  49. Cionek, V.M. Estrutura Trófica e Processamento Foliar em Riachos sob Influência do Uso do Solo. Ph.D. Thesis, Universidade Estadual de Maringá, Maringá, Brazil, 2016. [Google Scholar]
  50. Cionek, V.; Benedito, E.; Beaumord, A. Protocolo de Avaliação Rápida do Ambiente Para Riachos Inseridos da Região do Arenito Caiuá—Noroeste do Paraná, 1st ed.; EDUEM: Maringá, Brazil, 2011. [Google Scholar]
  51. Barbour, M.T.; Gerritsen, J.; Snyder, B.D.; Stribling, J.B. Rapid Bioassessment Protocols for Use in Streams and Wadeable Rivers: Periphyton, Benthic Macroinvertebrates and Fish, 2nd ed.; EPA/841-B-99-002. U.S. EPA; Office of Water: Washington, DC, USA, 1999. [Google Scholar]
  52. Cionek, V.M.; Fogaça, F.N.O.; Moulton, T.P.; Pazianoto, L.H.R.; Landgraf, G.O.; Benedito, E. Environmental degradation effects on headwater stream functioning: Responses of leaf litter breakdown and microbial communities. Hydrobiologia 2020. under review. [Google Scholar]
  53. Degerman, E.; Beier, U.; Breine, J.; Melcher, A.; Quataert, P.; Rogers, C.; Roset, N.; Simoens, I. Classification and assessment of degradation in European running waters. Fish. Manag. Ecol. 2007, 14, 417–426. [Google Scholar] [CrossRef]
  54. Sánchez-Montoya, M.M.; Vidal-Abarca, M.R.; Puntí, T.; Poquet, J.M.; Prat, N.; Rieradevall, M.; Alba-Tercedor, J.; Zamora-Muñoz, C.; Toro, M.; Robles, S.; et al. Defining criteria to select reference sites in Mediterranean streams. Hydrobiologia 2009, 619, 39–54. [Google Scholar] [CrossRef] [Green Version]
  55. Krause, J.R.; Bertrand, K.N.; Kafle, A.; Troelstrup, N.H. A fish index of biotic integrity for South Dakota’s Northern Glaciated Plains Ecoregion. Ecol. Indic. 2013, 34, 313–322. [Google Scholar] [CrossRef]
  56. Agostinho, A.A.; Thomaz, S.M.; Gomes, L.C. Conservation of the biodiversity of Brazil’s inland waters. Conserv. Biol. 2005, 19, 646–652. [Google Scholar] [CrossRef]
  57. Reynolds, L.; Herlihy, A.T.; Kaufmann, P.R.; Gregory, S.V.; Hughes, R.M. Electrofishing effort requirements for assessing species richness and biotic integrity in western Oregon streams. N. Am. J. Fish. Manag. 2003, 23, 450–461. [Google Scholar] [CrossRef]
  58. AVMA, (American Veterinary Medical Association). Guidelines for the Euthanasia of Animals; AVMA: Schaumburg, IL, USA, 2013. [Google Scholar]
  59. Graça, W.; Pavanelli, C.S. Peixes da Planície de Inundação do Alto Rio Paraná e Áreas Adjacentes; EDUEM: Maringá, Brazil, 2007. [Google Scholar]
  60. Ota, R.R.; Deprá, G.C.; Graça, W.J.; Pavanelli, C.S. Peixes da planície de inundação do alto rio Paraná e áreas adjacentes: Revised, annotated and updated. Neotrop. Ichthyol. 2018, 16, e170094. [Google Scholar] [CrossRef]
  61. Pereira, L.M. Impactos Antropogênicos Definem Traços Funcionais da Ictiofauna em Riachos Neotropicais de Primeira Ordem. Master’s Thesis, Universidade Estadual de Maringá, Maringá, Brazil, 2016. [Google Scholar]
  62. Hering, D.; Feld, C.K.; Moog, O.; Ofenböck, T. Cook book for the development of a Multimetric Index for biological condition of aquatic ecosystems: Experiences from the European AQEM and STAR projects and related initiatives. Hydrobiologia 2006, 566, 311–324. [Google Scholar] [CrossRef]
  63. R Core Team R. A Language and Environment for Statistical Computing. R Foundation for Statistical Computing: Vienna, Austria, 2018. [Google Scholar]
  64. Amrhein, V.; Greenland, S.; McShane, B. Retire statistical significance. Nature 2019, 567, 305–307. [Google Scholar] [CrossRef] [Green Version]
  65. Karr, J.R.; Chu, E.W. Sustaining living rivers. Hydrobiologia 2000, 422/423, 1–14. [Google Scholar] [CrossRef]
  66. Ferreira, C.P.; Casatti, L. Stream biotic integrity assessed by fish assemblages in the Upper Rio Paraná basin. Biota Neotrop. 2006, 6, 1–25. [Google Scholar]
  67. Hughes, R.; Oberdorff, T. Applications of IBI Concepts and Metrics to Waters Outside the Unites State and Canada. In Assessing the Sustainability and Biological Integrity of Water Resources Using Fish Communities; Simon, T., Ed.; CRC Press: Boca Raton, FL, USA, 1999; pp. 79–93. [Google Scholar]
  68. Brown, L.R. Fish communities and their associations with environmental variables, lower San Joaquin River drainage, California. Environ. Biol. Fishes 2000, 57, 251–269. [Google Scholar] [CrossRef]
  69. Kennard, M.J.; Arthington, A.H.; Pusey, B.J.; Harch, B.D. Are alien fish a reliable indicator of river health? Freshw. Biol. 2005, 50, 174–193. [Google Scholar] [CrossRef] [Green Version]
  70. Ferreira, T.; Caiola, N.; Casals, F.; Oliveira, J.M.; Sostoa, A. Assessing perturbation of river fish communities in the Iberian Ecoregion. Fish. Manag. Ecol. 2007, 14, 519–530. [Google Scholar] [CrossRef]
  71. Ruaro, R.; Mormul, R.P.; Gubiani, É.A.; Piana, P.A.; Cunico, A.M.; Graça, W.J. Non-native fish species are related to the loss of ecological integrity in Neotropical streams: A multimetric approach. Hydrobiologia 2018, 817, 413–430. [Google Scholar] [CrossRef]
  72. Zeni, J.O.; Casatti, L. The influence of habitat homogenization on the trophic structure of fish fauna in tropical streams. Hydrobiologia 2014, 726, 259–270. [Google Scholar] [CrossRef]
  73. Oliveira, J.M.; Fernandes, F.; Ferreira, M.T. Effects of forest management on physical habitats and fish assemblages in Iberian eucalypt streams. For. Ecol. Manag. 2016, 363, 1–10. [Google Scholar] [CrossRef]
  74. Costa, I.D.; Petry, A.C.; Mazzoni, R. Fish assemblages respond to forest cover in small Amazonian basins. Limnologica 2020, 81, 125757. [Google Scholar] [CrossRef]
  75. Egler, M.; Buss, D.F.; Moreira, J.C.; Baptista, D.F. Influence of agricultural land-use and pesticides on benthic macroinvertebrate assemblages in an agricultural river basin in southeast Brazil. Braz. J. Biol. 2012, 72, 437–443. [Google Scholar] [CrossRef] [Green Version]
  76. Thiere, G.; Schulz, R. Runoff-related agricultural impact in relation to macroinvertebrate communities of the Lourens River, South Africa. Water Res. 2004, 38, 3092–3102. [Google Scholar] [CrossRef]
  77. Teshima, F.A.; Ferreira, F.C.; Cetra, M. Rarity status of endemic and vulnerable fish species in a Brazilian Atlantic Forest protected area. Nat. Conserv. 2015, 13, 67–73. [Google Scholar] [CrossRef] [Green Version]
  78. Casatti, L. Ichthyofauna of two streams (silted and reference) in the Upper Paraná river basin, Southeastern Brazil. Braz. J. Biol. 2004, 64, 757–765. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  79. Aranha, J.M.R.; Caramaschi, É.P. Estrutura populacional, aspectos da reprodução e alimentação dos Cyprinodontiformes (Osteichthyes) de um riacho do sudeste do Brasil. Rev. Bras. Zool. 1999, 16, 637–651. [Google Scholar] [CrossRef] [Green Version]
  80. Langeani, F.; Castro, R.M.C.; Oyakawa, O.T.; Shibatta, O.A.; Pavanelli, C.S.; Casatti, L. Diversidade da ictiofauna do Alto Rio Paraná: Composição atual e perspectivas futuras. Biota Neotrop. 2007, 7, 182–196. [Google Scholar] [CrossRef]
  81. Rocha, F.; Casatti, L.; Pereira, D. Structure and feeding of a stream fish assemblage in Southeastern Brazil: Evidence of low seasonal influences. Acta Limnol. Bras 2009, 21, 123–134. [Google Scholar]
  82. Resh, V.H. Which group is best? Attributes of different biological assemblages used in freshwater biomonitoring programs. Environ. Monit. Assess. 2008, 138, 131–138. [Google Scholar] [PubMed]
  83. Ruaro, R.; Gubiani, É.A. A scientometric assessment of 30 years of the Index of Biotic Integrity in aquatic ecosystems: Applications and main flaws. Ecol. Indic. 2013, 29, 105–110. [Google Scholar] [CrossRef]
  84. Stoddard, J.L.; Herlihy, A.T.; Peck, D.V.; Hughes, R.M.; Whittier, T.R.; Tarquinio, E. A process for creating multimetric indices for large-scale aquatic surveys. J. N. Am. Benthol. Soc. 2008, 27, 878–891. [Google Scholar] [CrossRef]
  85. Costa, P.F.; Schulz, U.H. The fish community as an indicator of biotic integrity of the streams in the Sinos River basin, Brazil. Braz. J. Biol. 2010, 70, 1195–1205. [Google Scholar] [CrossRef]
  86. Pinto, B.C.T.; Araujo, F.G.; Hughes, R.M. Effects of landscape and riparian condition on a fish index of biotic integrity in a large southeastern Brazil river. Hydrobiologia 2006, 556, 69–83. [Google Scholar] [CrossRef]
  87. Polaz, C.N.M.; Ferreira, F.C.; Petrere Júnior, M. The protected areas system in Brazil as a baseline condition for wetlands management and fish conservancy: The example of the Pantanal National Park. Neotrop. Ichthyol. 2017, 15, e170041. [Google Scholar] [CrossRef] [Green Version]
  88. Oliveira, J.M.; Ferreira, M.T.; Morgado, P.; Hughes, R.M.; Teixeira, A.; Cortes, R.M.; Bochechas, J.H. A preliminary fishery quality index for portuguese streams. N. Am. J. Fish. Manag. 2009, 29, 1466–1478. [Google Scholar] [CrossRef]
  89. Hughes, R.M. Defining Acceptable Biological Status by Comparing with Reference Conditions; Lewis Publishers: Boca Raton, FL, USA, 1995. [Google Scholar]
  90. Li, H.-Y.; Ruby Leung, L.; Tesfa, T.; Voisin, N.; Hejazi, M.; Liu, L.; Liu, Y.; Rice, J.; Wu, H.; Yang, X. Modeling stream temperature in the Anthropocene: An earth system modeling approach. J. Adv. Model. Earth Syst. 2015, 7, 1661–1679. [Google Scholar] [CrossRef]
  91. Machado, N.; Venticinque, E.; Penha, J. Effect of environmental quality and mesohabitat structure on a Biotic Integrity Index based on fish assemblages of Cerrado streams from Rio Cuiabá basin, Brazil. Braz. J. Biol. 2011, 71, 577–586. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  92. Ward, T.A.; Tate, K.W.; Atwill, E.R.; Lile, D.F.; Lancaster, D.L.; McDougald, N.; Barry, S.; Ingram, R.S.; George, H.A.; Jensen, W.; et al. A comparison of three visual assessments for riparian and stream health. J. Soil Water Conserv. 2003, 58, 83–88. [Google Scholar]
  93. McCallum, E.S.; Nikel, K.E.; Mehdi, H.; Du, S.N.N.; Bowman, J.E.; Midwood, J.D.; Kidd, K.A.; Scott, G.R.; Balshine, S. Municipal wastewater effluent affects fish communities: A multi-year study involving two wastewater treatment plants. Environ. Pollut. 2019, 252, 1730–1741. [Google Scholar] [CrossRef]
  94. IPARDES. Indicadores de Desenvolvimento Sustentável Por Bacias Hidrográficas do Estado do Paraná; IPARDES: Curitiba, Brazil, 2013. [Google Scholar]
  95. SEMA, Secretaria de Estado do Meio Ambiente e Recursos Hídricos. Bacias Hidrográficas do Paraná; SEMA: Curitiba, Brazil, 2010. [Google Scholar]
Water 12 01215 g001 550
Figure 1. Location of the sampled stream sites.
Figure 1. Location of the sampled stream sites.
Water 12 01215 g001
Water 12 01215 g002 550
Figure 2. Distribution of metric values from the final range test for the least disturbed (LD) and most disturbed (MD) sites, and results from the Kruskal–Wallis test (n = 14; p < 0.05). Metrics passed this final range test if a majority of the sites did not have the same metric score regardless of disturbance class.
Figure 2. Distribution of metric values from the final range test for the least disturbed (LD) and most disturbed (MD) sites, and results from the Kruskal–Wallis test (n = 14; p < 0.05). Metrics passed this final range test if a majority of the sites did not have the same metric score regardless of disturbance class.
Water 12 01215 g002
Water 12 01215 g003 550
Figure 3. Distribution of N3S-IBI scores across disturbance classes; LD = least disturbed; ID = intermediate; MD = most disturbed. * represents significant difference (Kruskal–Wallis: H = 9.52; p = 0.009; n = 23).
Figure 3. Distribution of N3S-IBI scores across disturbance classes; LD = least disturbed; ID = intermediate; MD = most disturbed. * represents significant difference (Kruskal–Wallis: H = 9.52; p = 0.009; n = 23).
Water 12 01215 g003
Table
Table 1. Abundance of sampled fish orders (%) according to the disturbance class. LD = least disturbed sites, ID = intermediate sites, and MD = most disturbed sites.
Table 1. Abundance of sampled fish orders (%) according to the disturbance class. LD = least disturbed sites, ID = intermediate sites, and MD = most disturbed sites.
OrderAbundance at Sites (%)
LDIDMDTOTAL
Siluriformes30.226.426.426.7
Characiformes39.045.80.38.7
Cyprinodontiformes27.520.073.163.3
 Native (P. harpagos)27.08.02.35.4
 Non-native (P. reticulata)0.612.070.758.0
Table
Table 2. Metrics evaluation test by class and number of remaining metrics to build the Index of Biotic Integrity (N3S-IBI).
Table 2. Metrics evaluation test by class and number of remaining metrics to build the Index of Biotic Integrity (N3S-IBI).
Metric ClassStartMetric Evaluation Test
RangeResponsivenessRedundancyFinal Range Test
Diversity/Abundance55511
Composition (individuals)1261261851
Composition (family/order)279211
Origin66421
Habitat guild1212300
Reproductive guild1515620
Tolerance1210311
Trophic guild2424511
TOTAL227207108136
Table
Table 3. N3S-IBI scores, RAP values, land use, and disturbance for the twenty-three Neotropical sandy soil streams; ALU = agricultural land use; ULU = urban land use; LD = least disturbed; ID = intermediate; MD = most disturbed.
Table 3. N3S-IBI scores, RAP values, land use, and disturbance for the twenty-three Neotropical sandy soil streams; ALU = agricultural land use; ULU = urban land use; LD = least disturbed; ID = intermediate; MD = most disturbed.
StreamIBIRAPLand UseDisturbanceWatershed River
s201.00
(Excellent)		160
(Excellent)		33% ALU
<3% ULU		LDParanapanema
s040.99
(Excellent)		150
(Excellent)		60% ALU
<3% ULU		IDIvaí
s230.97
(Excellent)		91
(Good)		73% ALU
<3% ULU		IDPirapó
s150.84
(Excellent)		86
(Good)		5% ALU
<3% ULU		LDIvaí
s080.83
(Excellent)		97
(Good)		62% ALU
<3% ULU		IDIvaí
s270.82
(Excellent)		117
(Good)		12% ALU
<3% ULU		LDParaná
s250.76
(Good)		86
(Good)		33% ALU
<3% ULU		LDParaná
s050.74
(Good)		108
(Good)		24% ALU
<3% ULU		LDIvaí
s020.72
(Good)		135
(Excellent)		67% ALU
<3% ULU		IDIvaí
s240.70
(Good)		86
(Good)		11% ALU
<3% ULU		LDParaná
s140.54
(Regular)		115
(Good)		17% ALU
<3% ULU		LDIvaí
s030.54
(Regular)		61
(Regular)		26% ALU
3% ULU		MDIvaí
s130.54
(Regular)		148
(Excellent)		77% ALU
<3% ULU		IDIvaí
s090.40
(Poor)		37
(Regular)		69% ALU
4% ULU		MDIvaí
s220.36
(Poor)		116
(Good)		90% ALU
<3% ULU		IDPirapó
s110.36
(Poor)		79
(Regular)		77% ALU
<3% ULU		MDParanapanema
s100.30
(Poor)		115
(Good)		62% ALU
<3% ULU		IDParanapanema
s170.27
(Poor)		59
(Regular)		20% ALU
18% ULU		MDIvaí
s120.17
(Very Poor)		58
(Regular)		71% ALU
<3% ULU		MDIvaí
s210.17
(Very Poor)		162
(Excellent)		22% ALU
<3% ULU		IDParanapanema
s010.16
(Very Poor)		94
(Good)		39% ALU
<3% ULU		IDParanapanema
s070.09
(Very Poor)		76
(Regular)		26% ALU
14% ULU		MDIvaí
s180.00
(Very Poor)		60
(Regular)		9% ALU
87% ULU		MDIvaí

Share and Cite

MDPI and ACS Style

Gonino, G.; Benedito, E.; Cionek, V.d.M.; Ferreira, M.T.; Oliveira, J.M. A Fish-Based Index of Biotic Integrity for Neotropical Rainforest Sandy Soil Streams—Southern Brazil. Water 2020, 12, 1215. https://doi.org/10.3390/w12041215

AMA Style

Gonino G, Benedito E, Cionek VdM, Ferreira MT, Oliveira JM. A Fish-Based Index of Biotic Integrity for Neotropical Rainforest Sandy Soil Streams—Southern Brazil. Water. 2020; 12(4):1215. https://doi.org/10.3390/w12041215

Chicago/Turabian Style

Gonino, Gabriel, Evanilde Benedito, Vivian de Mello Cionek, Maria Teresa Ferreira, and João Manuel Oliveira. 2020. "A Fish-Based Index of Biotic Integrity for Neotropical Rainforest Sandy Soil Streams—Southern Brazil" Water 12, no. 4: 1215. https://doi.org/10.3390/w12041215

APA Style

Gonino, G., Benedito, E., Cionek, V. d. M., Ferreira, M. T., & Oliveira, J. M. (2020). A Fish-Based Index of Biotic Integrity for Neotropical Rainforest Sandy Soil Streams—Southern Brazil. Water, 12(4), 1215. https://doi.org/10.3390/w12041215

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop