Free Access
Issue
Ann. Limnol. - Int. J. Lim.
Volume 54, 2018
Article Number 37
Number of page(s) 6
DOI https://doi.org/10.1051/limn/2018028
Published online 28 November 2018

© EDP Sciences, 2018

1 Introduction

Aquatic systems are considered open ecosystems, with continuous longitudinal and temporal variations with respect to the import and export of nutrients and sunlight variations (Allan and Castillo, 2007). The trophic energy of the streams varies spatially, being at first mostly allochthonous (upstream) and gradually becoming autochthonous (downstream) (Vannote et al., 1980). On a temporal perspective, a prominent lateral contribution of nutrients is observed when the water level retracts after a flood pulse, importing organic particles into the streams (Junk et al., 1989). In both processes (longitudinal and temporal), abiotic dynamics modulate species diversity through time and space (Vannote et al., 1980; Junk et al., 1989; Brasil et al., 2017).

One of the most important predictors of variation in the aquatic communities is a set of climatic conditions (Allan, 2004). The central region of Brazil has well-defined dry and rainy seasons (Ratter et al., 1997). This climatic seasonality changes the water flow, dissolved oxygen rates, water temperature, and the litter contribution to the stream channel throughout the year (Giehl et al., 2015), and it leads to a greater habitat heterogeneity in the dry season. Therefore, the greatest diversity of aquatic insects occurs in the dry period (Bispo et al., 2006; Yokoyama et al., 2012). In addition, water quality is an important factor for the distribution of these organisms (Rosenberg and Resh, 1993). The Ephemeroptera Plecoptera and Thichoptera (EPT), for example, are sensitive to changes in water quality (Martins et al., 2017). This is because they lack the physiological plasticity to withstand sudden changes in pH, oxygen, and water temperature (Poff and Ward, 1990). Therefore, in places with changes in water quality, the individuals and/or species of these sensitive groups (EPT) are gradually replaced by more tolerant groups, for example, the Diptera (Martins et al., 2017).

The Trichoptera stand out among the various aquatic organisms for being sensitive to environmental changes (Morse, 2009). These insects are locally abundant, well distributed, and highly diverse in their trophic status and function, allowing them to inhabit tropical and subtropical watercourses, from their headwaters to their mouths, in many regions (Bispo et al., 2001). The key role of Trichopterans is in aquatic ecosystems as fundamental links in the trophic web, and their contribution to the processing of organic material in the ecosystem (Dos Santos and Rodrigues, 2015). In Cerrado streams, the distribution of Trichoptera is related to the natural variation in environmental conditions (throughout the year) (Yokoyama et al., 2012), and spatially the natural environmental variations and/or anthropogenic, for example, changes in land use (Nogueira et al., 2011). Both (temporal and spatial environmental variations) cause changes in the physico-chemical conditions of the water, but changes of anthropic origin may be more intense and/or more frequent, damaging the biotic integrity of the communities (Karr, 1991).

Our objective was to evaluate temporal (along 3 years) and longitudinal variations (along the stream) in the Thichoptera community of a Cerrado stream, Brazilian Midwest region. Our hypothesis is that there is an important interaction between spatial and temporal factors in determining community composition in these environments, given to the influence of climatic seasonality on the entrance of energy and microhabitat formation along the streams.

2 Material and methods

2.1 Study area

Bacaba stream is a second-order stream located in the municipality of Nova Xavantina southwestern of Mato Grosso, Brazil. This stream is part of the Tocantins basin, between the coordinates 14°36′ to 14°44′ S and 52°22′ to 52°17′ W (Fig. 1) with 5 km length, surround by natural vegetation (Marimon et al., 2002) and headwaters close to the Mario Viana Municipal Park (Bacaba Park) (Bleich et al., 2009). The Bacaba Park is composed by a mosaic of different Cerrado forms (grasslands, typical cerrado, cerrado sensu stricto, and cerrado woodlands) (Abad and Marimon, 2008) with predominance of livestock surrounding it (Bleich et al., 2009). There is a waterfall and rocks upstream of the site 1 (P1). In the streambed of the site 2 (P2) are large rocks interspersed with sand. Site 3 (P3) is located near the edge of the park with sandy streambed (Raimundi et al., 2017).

thumbnail Fig. 1

Sampling sites at the Bacaba Stream, Nova Xavantina, state of Mato Grosso, Brazil.

2.2 Data sampling

We analyzed the larvae of the order Trichoptera found in the Bacaba Stream, based on samples of the substrate of the margins. We collected specimens over a 3-year period, in a monthly frequency during the first year, and bimonthly during the following years, at three sites along the stream continuum (Fig. 1), in the upstream (P1), intermediate (P2), and downstream (P3) sectors. We demarcated a linear transect of 100 m, which was subdivided into 20 segments of 5 m at each site, establishing permanent plots with metallic stakes placed on the right margin of the stream. To collect specimens, we used a hand sieve with a diameter of 18 cm and mesh of 250 μm, which was passed three times along the margin of each segment, to provide a single subsample. At the end, the three subsamples collected in the 20 sequences amounted to 60 subsamples of substrate collected at each site, for each date.

The specimens collected were sorted and fixed in 85% alcohol in the field and were identified to the genus level in the laboratory using the keys of Angrisano (1995), Angrisano and Korob (2001), Pes et al. (2005), Wiggins (1996), and the morphospecies descriptions found in the “James A. Ratter” Collection and the Collection at the Nova Xavantina University of the State of Mato Grosso (UNEMAT), where the material is deposited.

The environmental variables were measured at 25 m intervals along with the biotic samples, either in situ or in the laboratory. Electrical conductivity, pH, and dissolved oxygen were measured with a Horiba multiparameter probe, water temperature with a digital thermometer, and turbidity, with a desktop turbidimeter.

2.3 Data analysis

A total of 63 sample units were used for all analyses, of which 36 were collected in the first year (monthly in P1, P2, and P3), 18 in the second year (bimonthly in P1, P2, and P3), and 9 in the third (quarterly in P1, P2, and P3) (Supplementary 1). We used a PERMANOVA with two factors to test our hypothesis that the spatiotemporal variation would explain the composition of Trichoptera species. The PERMANOVA tests differences based on randomization of test F (pseudo-F) models (Anderson and Walsh, 2013). With this approach, we partition the variation among time (throughout the years), longitudinal variation (along the stream), and the interaction between space and time (spatiotemporal variation). On the two factors of Permanova, the temporal factor was the season of the year: rainy (January, February, and March), ebb (April, May, and June), dry (July, August, and September), and early rainy (October, November, and December). The second factor (longitudinal) were the collection points: upstream (point 1), intermediate (point 2), and downstream (point 3).

We used a multivariate distance matrix regression (MDMR) (Anderson, 2001) using environmental and temporal predictors and the composition of Trichoptera species to verify the important mechanisms for spatiotemporal variation. The environmental variables were electrical conductivity, pH, dissolved oxygen, water temperature, and turbidity. The temporal variables were calculated using a principal coordinate analysis of neighbor matrices (PCNM) (Dray et al., 2006) as “temporal filters” to understand how much of the community variation was explained by the temporal distance among samples (temporal autocorrelation) (Brasil et al., 2017). We used the function “pcnm” of the package vegan (Oksanen et al., 2013) to calculate the PCNMs, where the vectors represented the sampling dates (month and year). Subsequently, we conducted a selection to use only the PCNMs needed to solve the temporal autocorrelation bias using the forward.sel of the package packfor (Blanchet et al., 2008).

3 Results

A total of 1202 Trichopteran larvae were collected, representing six families, 10 genera, and 42 morphotypes. The most abundant families were Hydropsychidae (n = 605 specimens) and Odontoceridae (n = 353), while the least abundant were Leptoceridae (n = 19) and Helicopsychidae (n = 3). The most abundant genera were Marilia (n = 354) and Leptonema (n = 320), and the least abundant were Macronema (n = 9), Helicopsyche (n = 3), and Oecetis (n = 2). The most abundant morphospecies were Marilia sp.1 (n = 353) and Phylloicus sp.1 (n = 151), while nine morphospecies showed only one specimen (Supplementary 2).

The longitudinal distribution (sites) along with the temporal variation (seasons) explained 41.2% of the spatiotemporal variation of the composition of Trichopera species, of which 21.4% was explained exclusively by longitudinal variation (pseudo-F = 10.945, R2 = 0.214, p = 0.001), 11.5% by temporal variation (pseudo-F = 3.927, R2 = 0.115, p = 0.001), and 8.3% by an interaction between spatial and temporal variation (pseudo-F = 1.418, R2 = 0.083, p = 0.046). Three environmental predictors and three important temporal predictors were observed when we evaluated the environmental and temporal mechanisms predictors of the variation of the Trichoptera species composition. The main environmental predictors were pH, total dissolved solids and dissolved oxygen, and the temporal predictors PCNMs 1, 2, and 5 (Tab. 1).

Table 1

Multivariate distance matrix regression between species composition and environmental and temporal variables.

4 Discussion

The longitudinal distribution of the sites as well as the temporal distribution of the samples were important for the distribution of Trichoptera species in the 3 years evaluated. This corroborates our hypothesis that there is an important interaction between spatial and temporal factors in determining community composition in these environments. Other studies carried out in the same stream but with other taxonomic groups have found similar results of the longitudinal distribution on the distribution of a Heteroptera population (Giehl et al., 2015), and of the temporal variation on rare and common Ephemeroptera communities (Brasil et al., 2017). In addition to a temporal evaluation of zooplankton of reservoirs in the Cerrado (Lodi et al., 2014), these previous evidences along with our results indicate a certain level of synchrony in the spatiotemporal distribution of aquatic species in the Cerrado.

The longitudinal variation occurs due to changes in environmental conditions along the stream. Site 3 (downstream) is environmentally more dissimilar than sites 1 and 2 (headwater and intermediate regions), where light input and depth are greater (Giehl et al., 2015). The river continuum concept theory (Vannote et al., 1980) posits that environments near the source and with great light input are trophically more heterogeneous and combine allochthonous energy derived from the stream banks, with autochthonous energy related to light input (algae and periphyton). It is expected that this point has differences in the Trichoptera community due to loss of environmental integrity and water quality (Pereira et al., 2012), which are common in environments with these characteristics of use of the land (livestock) (Brasil et al., 2014a; Leal et al., 2016).

Communities of aquatic insects from Cerrado streams have higher diversity values in the driest season (Bispo et al., 2001; Yokoyama et al., 2012). This is because the stream channel accumulates more leaf banks in this period, providing an increased heterogeneity (Baptista et al., 2001). Simultaneously, more rare species, which live for only few months of the year as immature individuals, are recorded in the driest season (Brasil et al., 2017). In this work and others (e.g., Bispo et al., 2006; Yokoyama et al., 2012; Brasil et al., 2017), the relation of communities with the variation in the physico-chemical conditions of water was evident, mainly between dry and rainy seasons (Bleich et al., 2009). In addition, there are also intrinsic factors of the species such as the eclosion time of eggs, larval births, and voltinism that are important for its distribution throughout the year (Cayrou and Céréghino, 2005). However, this intrinsic information is totally or partially nonexistent for aquatic insects in the Brazilian Cerrado.

The physical and chemical conditions of the water are very important to jointly evaluate this spatiotemporal variation, since they vary in both time and space (Bleich et al., 2009; Giehl et al., 2015) and are important conditions for the establishment of aquatic insect communities (Couceiro et al., 2012). This was clear in our study when we observed that both the physical and chemical variables of the water, and the temporal filters, were related to Trichoptera composition (Tab. 1). The relation of the communities with the variation of dissolved oxygen and pH is well known (Rosenberg and Resh, 1993). In general, it is expected that Trichoptera live in well-oxygenated water (Philipson, 1954). Naturally, dissolved oxygen and pH fluctuate throughout the year, especially during the dry season (Bleich et al., 2009; Giehl et al., 2015). In addition, spatially the oxygen in the water decreases and the pH increases in anthropogenic areas (Couceiro et al., 2007; Martins et al., 2017) as in point 3. The total dissolved solids tend to increase in the rainy period due to the entrance of sediments of the margins, and spatially increase in anthropic places where the margins are unprotected by the riparian forests (Johnson et al., 1997). All the mechanisms mentioned above are known to be important for the spatiotemporal distribution of Trichoptera communities.

Among the most abundant families of this work, Hydrosychidae and Odontoceridae, the first has the highest number of individuals and species richness in the study region (Nogueira et al., 2011) and is distributed in different habitat types throughout the neotropical region (Wiggins, 1996; Flint et al., 1999). In Cerrado streams, the family Hydrosychidae has taxa distributed in lentic and lotic environments, and even in anthropized streams (Nogueira et al., 2011), and are abundant during all seasons of the year (Bispo and Oliveira, 2007). The second most abundant family (Odontoceridae) was represented only by genera Marilia, which is common in streams with preserved riparian forest (Nogueira et al., 2011; Pereira et al., 2012). This is because they are shredders that depend on the leaves coming from the margins to feed themselves (Brasil et al., 2014b). Therefore, even though the second most abundant taxon in our work, Marilia almost did not occur in the anthropized point: abundance of Marilia point 1 (276 individuals or 78%), point 2 (73 individuals or 21%), and in point 3 only (5 individuals or 2%) (Supplementary 2).

Our results indicate that the composition of the Trichoptera communities has great spatiotemporal dynamics in the Cerrado streams. The variation of the environmental conditions of the water and the temporal autocorrelation were the most important factors to explain the spatiotemporal dynamics observed. From these indications, it is possible to suppose that seasonal variation throughout the year is also an important factor for these aquatic communities, in addition to their known importance in management of water quality (bioindicators). Therefore, if climate change predictions are correct, spatiotemporal patterns of Trichoptera communities of Cerrado streams will probably be affected, a result that can be extrapolated to other savanna regions with a marked seasonal climate.

Acknowledgments

We are grateful to Entomology Laboratory for field support. Brasil, L.S. acknowledge to the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for granting Ph.D scholarship (#140111/2015-8) and to PNPD/CAPES for post-doctorate grant linked to the PPG in Zoology (UFPA and MPEG). Santos, D.C. thanks FAPEMAT / UNEMAT for the Scientific Initiation Grant (#365804 / 2012). We thank PELD/MCT/CNPq I and II (#558069/2009-6 and 403725/2012-7) for financial support and PELD/CNPq II for the DTI-C stipend to N.F.S.G. (#384856/2013-6 and 385588/2014-3). Giehl, N.F.S. also thanks Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) for the doctorate scholarship.

References

  • Abad JCS, Marimon BS. 2008. Caracterização e diagnóstico ambiental do Parque Municipal do Bacaba, Nova Xavantina (MT), RiMa, São Carlos, 56 p. [Google Scholar]
  • Allan JD. 2004. Landscapes and river scapes: the influence of land-use on river ecosystems. Annu Rev Ecol Evol Syst 35: 257–284. [CrossRef] [Google Scholar]
  • Allan JD, Castillo MM. 2007. Stream Ecology: Structure and Function of Running Waters, Dordrecht, The Netherlands: Springer, 436 p. [Google Scholar]
  • Anderson MJ, Walsh DC. 2013. PERMANOVA, ANOSIM, and the Mantel test in the face of heterogeneous dispersions: what null hypothesis are you testing? Ecol Monogr 83, 557–574. [CrossRef] [Google Scholar]
  • Anderson MJ. 2001. A new method for non-parametric multivariate analysis of variance. Austral Ecol 26, 32–46. [Google Scholar]
  • Angrisano EB. 1995. Insecta Trichoptera. In: Lopretto EC, Tell G, eds. Ecossistemas de águas continentales, metodologia para su estudio, Ediciones Sul, La Plata, 1199–1227. [Google Scholar]
  • Angrisano EB, Korob P. 2001. Trichoptera. In: Fernández HR, Domínguez E, eds. Guía para La determinación de los artrópodos bentônicos sudamericanos, Editorial Universitaria de Tucumán, Tucumán, 55–92. [Google Scholar]
  • Baptista DF, Dorvillé LF, Buss DF, Nessimian JL. 2001. Spatial and temporal organization of aquatic insects assemblages in the longitudinal gradient of a tropical river. Braz J Biol 61, 295–304. [Google Scholar]
  • Bispo PC, Oliveira, LG. 2007. Diversity and structure of Ephemeroptera, Plecoptera and Trichoptera (Insecta) assemblages from riffles in mountain streams of Central Brazil. Rev Bras Zool 24, 283–293. [CrossRef] [Google Scholar]
  • Bispo PC, Oliveira LG, Crisci VL, Silva MM. 2001. A pluviosidade como fator de alteração da entomofauna bentônica (Ephemoropthera, Plecoptera e Tricoptera) em córregos do Planalto Central do Brasil. Acta Limnol Bras 13, 1–9. [Google Scholar]
  • Bispo PC, Oliveira LG, Bini LM, Sousa KG. 2006. Ephemeroptera, Plecoptera and Trichoptera from riffles in mountain streams of Central Brazil: environmental factors influencing the distribution and abundance of immatures. Braz J Biol 66, 611–622. [CrossRef] [PubMed] [Google Scholar]
  • Blanchet FG, Legendre P, Borcard D. 2008. Forward selection of explanatory variables. Ecology, 89: 2623–2632. [CrossRef] [PubMed] [Google Scholar]
  • Bleich ME, Silva CJ, Rossete AN. 2009. Variação temporal e espacial das características limnológicas de um ecossistema lótico no Cerrado do Mato Grosso. Biotemas 22, 161–171. [CrossRef] [Google Scholar]
  • Brasil LS, Juen L, Cabette HSR. 2014a. The effects of environmental integrity on the diversity of mayflies, Leptophlebiidae (Ephemeroptera), in tropical streams of the Brazilian Cerrado. Ann Limnol − Int J Lim 50, 325–334. [CrossRef] [Google Scholar]
  • Brasil LS, Juen L, Batista JD, Pavan MG, Cabette HSR. 2014b. Longitudinal distribution of the functional feeding groups of aquatic insects in streams of the Brazilian Cerrado Savanna. Neotrop Entomol 43, 421–428. [CrossRef] [PubMed] [Google Scholar]
  • Brasil LS, Juen L, Giehl NFS, Cabette HSR. 2017. Effect of environmental and temporal factors on patterns of rarity of Ephemeroptera in Stream of the Brazilian Cerrado. Neotrop Entomol 46, 29–35. [CrossRef] [PubMed] [Google Scholar]
  • Cayrou J, Céréghino R. 2005. Life cycle phenology of some aquatic insects: implications for pond conservation. Aquat Conserv 15, 559–571. [CrossRef] [Google Scholar]
  • Couceiro SR, Hamada N, Luz SL, Forsberg BR, Pimentel TP. 2007. Deforestation and sewage effects on aquatic macroinvertebrates in urban streams in Manaus, Amazonas, Brazil. Hydrobiologia 575, 271–284. [CrossRef] [Google Scholar]
  • Couceiro SR, Hamada N, Forsberg BR, Pimentel TP, Luz SL. 2012. A macroinvertebrate multimetric index to evaluate the biological condition of streams in the Central Amazon region of Brazil. Ecol Indic 18, 118–125. [CrossRef] [Google Scholar]
  • Dos Santos IGA, Rodrigues GG. 2015. Colonização de macroinvertebrados bentônicos em detritos foliares em um riacho de primeira ordem na Floresta Atlântica do nordeste brasileiro. Iheringia Sér Zool 105, 84–93. [CrossRef] [Google Scholar]
  • Dray S, Legendre P, Peres-Neto PR. 2006. Spatial modelling: a comprehensive frame-work for principal coordinate analysis of neighbor matrices (PCNM). Ecol Model 196, 483–493. [CrossRef] [Google Scholar]
  • Flint OS, Jr, Rosenthal RW, Harris SC. 1999. Catalog of the Neotropical Caddisflies (Insecta: Trichoptera), Ohio Biological Survey, Columbus, 239 p. [Google Scholar]
  • Giehl NFS, Fonseca PVB, Dias-Silva K, Brasil LS, Cabette HSR. 2015. Efeito de fatores abióticos sobre Brachymetra albinervis albinervis (Heteroptera: Gerridae). Iheringia Sér Zool 105, 411–415. [CrossRef] [Google Scholar]
  • Johnson LB, Richards C, Host GE, Arthur AW. 1997. Landscape influences on water chemistry in Midwestern stream ecosystems. Freshw Biol 37, 193–208. [CrossRef] [Google Scholar]
  • Junk WJ, Bayley PB, Sparks RE. 1989. The flood pulse concept in river-floodplain systems. Can Spec Publ Fish Aquat Sci 106, 110–127. [Google Scholar]
  • Karr JR. 1991. Biological integrity: a long-neglected aspect of water resource management. Ecol Appl 1, 66–84. [CrossRef] [PubMed] [Google Scholar]
  • Leal C, Pompeu PS, Gardner TA, Leitão RP, Hughes RM, Kaufmann PR, Zuanon J, Paula FR, Ferraz SFB, Thomson JR, Nally RM, Ferreira J, Barlow J. 2016. Multi-scale assessment of human-induced changes to Amazonian instream habitats. Landscape Ecol 31, 1725–1745. [CrossRef] [Google Scholar]
  • Lodi S, Velho LFM, Carvalho P, Bini LM. 2014. Patterns of zooplankton population synchrony in a tropical reservoir. J Plankton Res 36, 966–977. [CrossRef] [Google Scholar]
  • Marimon BS, Felfili JM, Lima ES. 2002. Floristics and pkytosociology of the gallery forest of the Bacaba stream, Nova Xavantina, Mato Grosso, Brazil. Edinb J Bot 59, 303–318. [CrossRef] [Google Scholar]
  • Martins RT, Couceiro SR, Melo AS, Moreira MP, Hamada N. 2017. Effects of urbanization on stream benthic invertebrate communities in Central Amazon. Ecol Indic 73, 480–491. [CrossRef] [Google Scholar]
  • Morse JC. 2009. Trichoptera (caddisflies). In: Resh VH, Cardé RT, eds. Encyclopedia of Insects, New York: Academic Press, pp. 1015–1020. [CrossRef] [Google Scholar]
  • Nogueira DS, Cabette HSR, Juen L. 2011. Estrutura e composição da comunidade de Trichoptera (Insecta) de rios e áreas alagadas da bacia do rio Suiá-Miçú, Mato Grosso, Brasil. Iheringia Sér Zool 101, 173–180. [Google Scholar]
  • Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O'hara, RB, Oksanen, MJ. 2013. Package vegan, Community Ecology Package, Version 2. https://CRAN.R-project.org/package=vegan (accessed 8 September 2016). [Google Scholar]
  • Pereira LR, Cabette HSR, Juen L. 2012. Trichoptera as bioindicators of habitat integrity in the Pindaíba river basin, Mato Grosso (Central Brazil). Ann Limnol − Int J Lim 48, 295–302. [CrossRef] [Google Scholar]
  • Pes AMO, Hamada N, Nessimian JL. 2005. Chaves de identificação de larvas para famílias e gêneros de Trichoptera (Insecta) da Amazônia Central, Brasil. Rev Bras Entomol 49, 181–204. [CrossRef] [Google Scholar]
  • Philipson GN. 1954. The effect of water flow and oxygen concentration on six species of caddis fly (Trichoptera) larvae. J Zool 123, 547–564. [Google Scholar]
  • Poff NL, Ward JV. 1990. Physical habitat template of lotic systems: recovery in the context of historical patterns of spatiotemporal heterogeneity. Environ Manag 14, 629–645. [CrossRef] [Google Scholar]
  • Raimundi EA, Cabette HS, Brasil LS, Salles FF. 2017. A new species of Miroculis Edmunds, 1963 (Ephemeroptera: Leptophlebiidae) from Cerrado-Amazonian forest transition zone, Brazil. Zootaxa 4299, 271–278. [CrossRef] [Google Scholar]
  • Ratter JA, Ribeiro JF, Bridgewater S. 1997. The Brazilian cerrado vegetation and threats to its biodiversity. Ann Bot 80, 223–230. [CrossRef] [Google Scholar]
  • Rosenberg, DM, Resh VH. 1993. Freshwater Biomonitoring and Benthic Macro Invertebrates, London: Chapman & Hall, 486 p. [Google Scholar]
  • Vannote RL, Minshall GW, Cummins KW, Sedell JR, Cushing CE. 1980. The river continuum concept. Can J Fish Aquat Sci 37, 130–137. [Google Scholar]
  • Wiggins GB. 1996. Larvae of the North American Caddisfly Genera (Trichoptera). Toronto: University of Toronto, 457 p. [Google Scholar]
  • Yokoyama E, Paciencia GP, Bispo PC, Oliveira LG. 2012. Sazonalidade ambiental afeta a composição faunística de Ephemeroptera e Trichoptera em riachos de Cerrado do Sudeste do Brasil? Ambiência 8, 73–84. [Google Scholar]

Cite this article as: Brasil LS, Santos DC, Vieira TB, Cabette HSR, Umetsu RK, da Silva Giehl NF. 2018. Spatiotemporal dynamics in caddisfly (Insecta: Trichoptera) of a Cerrado stream, Brazil. Ann. Limnol. - Int. J. Lim. 54: 37

All Tables

Table 1

Multivariate distance matrix regression between species composition and environmental and temporal variables.

All Figures

thumbnail Fig. 1

Sampling sites at the Bacaba Stream, Nova Xavantina, state of Mato Grosso, Brazil.

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