Effects of Habitat Structural Complexity on Diversity Patterns of Neotropical Fish Assemblages in the Bita River Basin, Colombia

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Biodiversity International Journal

Research Article Open Access Effects of habitat structural complexity on diversity patterns of neotropical fish assemblages in the Bita river basin, Colombia

Abstract Volume 3 Issue 6 - 2019

Several studies have shown that fish assemblages are structured by habitat features, most 1 of them have proposed that there is a positive relationship between habitat structural Diana Carolina Montoya Ospina, Edwin 1,2 3 complexity and species diversity. In this study, we aimed to test this positive-relationship Orlando López Delgado, Violeta Hevia, idea in three habitats (creeks, oxbow lakes and river sandbanks) distributed along the Francisco Antonio Villa Navarro1,3 Bita River Basin Colombia, South America. Standardized surveys were conducted during 1Grupo de Investigación en Zoología, Facultad de Ciencias, January and February of 2016 (low water period) at 30 sites distributed along the entire basin. Universidad del Tolima, Barrio Santa Helena parte alta, Ibagué, We recorded 23,092 individuals representing 191 species of fish. To investigate possible Tolima, Colombia 2 relationships between habitat structural complexity and species diversity, we calculated the Department of Wildlife and Fisheries Sciences, and Biodiversity first three Hill’s numbers, and performed a Non-metric Multidimensional Scaling (NMDS), Research and Teaching Collections, Texas A&M University, USA 3Department of Ecology, Universidad Autónoma de Madrid, a Principal Component Analysis (PCA) and a Canonical Correspondence Analysis (CCA). Spain Our results showed that river sandbanks and creeks harbored the highest species richness. Results from the NMDS analysis (stress=0.19) showed that fish community composition Correspondence: Diana Carolina Montoya Ospina, Grupo de was different in the assessed habitats (ANOSIM < p=0.001). According to the results of Investigación en Zoología, Facultad de Ciencias, Universidad del the principal component analysis, sand percentage, dissolved oxygen, and vegetation width Tolima, Barrio Santa Helena parte alta, Ibagué, Tolima, Colombia, separated the river sandbanks from the other habitats. Results from the Hill’s numbers, Tel (+57) 312 312 2878, Email forward selection procedure, and canonical correspondence analysis suggested that species composition and diversity were significantly influenced by the habitat structural complexity Received: November 06, 2019 | Published: November 26, index and conductivity. 2019

Keywords: biodiversity, structural complexity, orinoco river basin, Colombia

Introduction Habitat structural complexity influences fish assemblages in many ways. Several freshwater studies have found significant relationships The Neotropical region is the most biodiverse area in the world. between species richness and habitat complexity.6,9–11 Loss of habitat Regarding fish species, in this region has been described more than complexity affects diversity and distribution of fish assemblages by 1 6,000 species and the number increases by day. In the South American decreasing the diversity of native species, which results in biotic part of the Neotropical area, the Amazonas and Orinoco river basins homogenization of fish communities.2,12–20 are the largest and most biodiverse. The Orinoco River Basin extends to Colombia and Venezuela harboring roughly 1,000 fish species,2 Previous ichthyological research in the Bita River basin aimed just in the Colombian part, there are more than 663 species which to describe and characterize fish communities.21,22 Recently López- represents 45% of the Colombian fish diversity.3 Delgado et al.,11 evaluated fish metacommunity in the Bita River along the longitudinal gradient and found that species sorting and Given the current crisis of biodiversity loss due to anthropogenic environmental filtering were the principal structuring forces in this 4 impacts, it is crucial to study diversity patterns in these mega diverse system. Our study aimed to identify the effects of habitat structural regions. In the Orinoco river basin, the major threats are deforestation, complexity on the richness and diversity patterns of fish communities 2 land use change, damming, mining and overfishing. These affect in the Bita River drainage (Vichada, Colombia). We proposed that biodiversity in different ways. For instance, Montag found that land habitat structural complexity is related to fish richness and diversity, use change is an important driver of biodiversity in Neotropical and hypothesized that as habitat structural complexity increases, fish freshwater systems. Another important driver of biodiversity is habitat diversity will increase too. heterogeneity, in a Neotropical river of South America Willis et al.,6 found that fish assemblages were positive associated with habitat Materials and methods structural complexity. They found that species richness and evenness in structural complex habitats were related with niche partitioning. Study area The influence of habitat heterogeneity on fish species composition The Bita River drainage is located in the eastern plains of the is a well-known phenomenon.5 Habitat heterogeneity is related to Colombian Llanos in the Vichada department (Colombia), draining different ecological processes such as species richness, abundance, directly to the Orinoco River, with a water course distance of competition and many more.6 Some studies have found that high 700km approximately, and a total area of 812,312 ha. This region is 23 spatial heterogeneity often results in different microhabitats which characterized by an unimodal pluviometric regimen. The main river increase biotic diversity.7,8 and streams contain multiple habitats that vary mainly in substrate composition, riparian vegetation and depth, average air temperature in

Submit Manuscript | http://medcraveonline.com Biodiversity Int J. 2019;3(6):267‒274. 267 ©2019 Ospina et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and build upon your work non-commercially. Copyright: Effects of habitat structural complexity on diversity patterns of neotropical fish assemblages in the Bita 268 river basin, Colombia ©2019 Ospina et al. the region is 27°C, and average annual precipitation is 2,300 mm with After catch, fishes were removed from the nets, anesthetized most rainfall from May to August.11,22 and euthanized by immersion in tricaine methane sulfonate (MS- 222), then fixed in 10% formalin. In the laboratory, they were Sampling transferred to 70% ethanol for final preservation and were identified 24–48 The sampling campaign was carried out during the low water period using specialized taxonomic literature. Finally, specimens were (January, February 2016, dry season) when sampling efficiency is deposited in the ichthyological collections of the Universidad del higher and the relationship between fish species and habitat should be Tolima, Colombia (CZUT-IC) and Instituto Alexander von Humboldt, higher. Standardized surveys were performed using a seine net (10m Colombia (IAvH-P). x 2m; 3 mm mesh) and three gillnets (30m x 2m; 5cm mesh) at 30 Prior to the surveys, at each sampling site we measured sites distributed along the entire Bita River basin. Sampling sites were environmental variables following the methodology proposed by distributed in 11 river sandbanks, 10 creeks locally named “caños” Pease et al.9 Variables were divided into four categories: water and nine oxbow lakes “madreviejas” (Figure 1, Supplementary parameters, channel morphology, instream cover, and riparian cover. material Table 1). At each site we conducted six seine hauls in a 200 m Water parameters such as pH, conductivity, dissolved oxygen and reach and deployed the gillnets for 2 hours, checking them every hour. water temperature were measured using a multiparameter meter (YSI model 85). Channel width (m), width of the riparian vegetation, and depth (superficial <1m, moderate between 1-3m, deep > 3m), were measured using a metric tape, and the water flow was visually categorized as high, medium, and low. To characterize instream cover we visually estimated the percentage of mud (<0.06mm), sand (0.06–2mm), pebbles (6–25cm), filamentous algae, large trunks, small trunks, branches, roots, leaf litter, and riparian vegetation cover along the 200 m reach (Table 1). Structure and composition We calculated the relative abundance using the number of specimens collected from each species divided by the total number of specimens in the sample. Fish diversity was calculated using the first three Hill’s numbers q= 0 (species richness), q=1 (the exponential of Shannon’s index), and q=2 (the inverse of Simpson’s index) following the equation proposed by Jost49 q 1/(1− q) DS= ()q ∑i=1 P i Figure 1 Location of the sampling sites in the Bita river basin, Vichada, Where qD is the diversity. The exponent q determines the sensitivity Colombia. of the index to the relative abundances of the species.50 Additionally, Table 1 Contribution of environmental variables to the first three factors for to identify if diversity was different among the habitats, we applied the bootstrap method to construct confidence intervals around the habitats in the Bita river basin interpolated and extrapolated Hill’s numbers as proposed by Chao et 51 52 Variables Factor 1 Factor 2 al., using the R library iNEXT. Water pH 0.12103 -0.2879 To establish if community structure was similar in each habitat, parameters a Non-metric Multidimensional Scaling analysis (NMDS) was Water temperature (°C) 0.02394 -0.9045 performed, using the Bray-Curtis distance. NMDS was considered Electrical conductivity (μS -0.36653 -0.7472 robust when the stress value was less than 0.2. Additionally, we cm–1) performed a non-parametric Similarity Analysis (ANOSIM) 53 to Dissolved oxygen (mgO2 L–1) 0.53332 1.6E-05 determine if there were statistically significant differences between Instream groups (habitats). Statistical analyses were carried out using the R %Sand 0.76481 0.1369 cover variables library Vegan and the functions metaMDS and anosim. %Mud -1.02215 -0.0876 Habitat complexity %Cobble 0.22983 0.2619 %Algae -0.30023 0.2476 Habitat complexity was estimated using the habitat structural 54 % Big trunks -0.83098 -0.0358 complexity index (S) proposed by Winemiller et al. % Small trunks -0.90249 0.1392 ∑ i S = x %Roots -0.79517 -0.1787 N

%Leaf litter -0.37085 -0.3266 Where S is the structural complexity index, xi represents each % Riparian vegetation width component of the instream cover in each sampling site, and N is the -1.03458 0.9301 (m) number of joint components of the instream cover observed at the %riparian vegetation cover -0.07621 0.2822 sampling sites. Values close to zero indicate low complexity and close Forest cover -0.64825 -0.2923 to one, high complexity. Channel Width 0.70905 -0.5521 morphology

Environmental factors oxbow lakes obtained the highest effective number of species, and the lowest were observed in the river sandbanks (Figure 2). To reduce the dimensionality of the environmental variables and to identify if the habitats were separated based on instream cover Table 2 Physical, physicochemical and structural Variables of the habitats of and habitat features, we performed a Principal Components Analysis the Bita river basin. Mean ± standard error (PCA) on the correlation matrix with the data previously log(x+1) River’s transformed. Variables Creek Oxbow lake sandbanks The components retained for interpretation were chosen according to the broken stick model55 in which a pattern of expected eigenvalues pH 7.92±1.25 7.2±0.75 8.03±1.30 is estimated and only those components that exceed these values Water will be considered significant. These analyses were performed using temperature 28.9±1.39 29.63±1.72 29.1±1.25 the PCA function from the R library “FactoMineR” and the PCA (°C) significance function from the R package “BiodiversityR”.52 Electrical Water To determine if environmental variables were related to fish conductivity 5.85±2.84 44.47±48.97 5.02±1.25 parameters community structure, we performed a Canonical Correspondence (μS cm–1) Analysis (CCA) followed by a forward selection procedure with 999 permutations and a significance level of p=0.05. To perform Dissolved the CCA, we used the Hellinger-transformed species matrix and the oxygen 9.06±2.44 8.49±1.54 10.38±1.41 environmental variables log(x+1) transformed. For the environmental (mgO2 L–1) matrix we removed all the instream cover variables because they were used to calculated the structural complexity index, which could result %Pebble 0 0 14.55±32.67 in multicollinearity that could affect the performance of the analyses. These were conducted using the function cca from the “vegan” library %Sand 15.5±21.92 28.89±31.4 85.45±32.57 and the function forward.sel from the R library “adespatial”. %Mud 77±29.83 50±32.02 0 Results %Algae 5±9.72 1.11±3.33 0.91±3.02 Structure and composition Instream %Large We collected 23,092 specimens distributed in 10 orders, 39 cover 11±8.76 11.11±10.54 3.64±8.09 trunks families, 125 genera and 191 species. Characiforms was the most variables abundant order (79.34%), followed by Clupeiformes (9.99%) and % Small 25±10.8 16.67±6.61 4.55±6.88 Cichliformes (5.24%), while the others had an abundance lower trunks than 4%. Characidae was the most abundant family (70.39%), and the most abundant species were Hemigrammus elegans (12.38%), %Roots 7±9.49 7.78±7.12 2.73±9.05 Hemigrammus geisleri (11.46%), Amazonsprattus scintilla (9.50%), %Leaf litter 48±17.51 47.22±16.41 8.64±5.52 Hyphessobrycon diancistrus (7.26%), Hemigrammus analis (6.14%), Microschemobrycon casiquiare (4.62%) and Hemigrammus newboldi % Riparian (4.31%). vegetation 6±6.99 10±11.46 0.91±3.02 Regarding habitats, 47.67% (10,085) of the individuals were width (m) collected in the river sandbanks belonging to nine orders, 33 families, 80 genera and 122 species. The most abundant species were H. Riparian 20±29.81 8.11±9.13 14±16.56 geisleri (25.9%), A. scintilla (20.5%), M. casiquiare (9.1%) and vegetation Knodus cinarucoense (7.83%). In the creeks, 29.91% (6909) of the individuals were collected, belonging to nine orders, 33 families, 90 %Riparian genera, and 122 species. The most abundant species were H. elegans vegetation 50±24.61 21.67±13.69 2.27±4.10 (27.6%), H. newboldi (9.36%), H. analis (8.16%) and Tyttobrycon cover xeruini. (7.5%). Finally, in the oxbow lakes we collected 26.40% (6098) of the total number of individuals, belonging to 9 orders, 33 Structural families, 78 genera, and 108 species. The most abundant species were complexity 0.65±0.12 0.63±0.16 0.31±0.17 Hyphessobrycon diancistrus (24.65%), H. elegans (15.02%) and H. (S) analis (8.23%) (Table 2). With respect to the effective number of species, results from the Width 13.4±9.19 61.11±90.41 73.64±55.19 order q=0 showed that the river sandbanks (122 spp.) and creeks (122 spp.) had the greatest species richness and the oxbow lakes the lower Channel Depth 2.5±0.53 2.11±0.78 2.36±0.5 (Figure 2). However, when checking the confidence intervals, we did morphology not observe significant differences among habitats. In contrast, orders q=1 and q=2 showed significant differences between the evaluated Water flow 1.1±0.32 1±0 1.91±0.70 habitats (Figure 2). The order q=1 and q=2 showed that creeks and

Habitat complexity The S index showed that the sampling sites located in the creeks, and oxbow lakes had the highest values of habitat structural complexity. On the contrary, sampling sites located at the river sandbanks (E7, E20, E30, and E33) had the lowest values (Table 2). Environmental factors Using the broken stick model, we selected the first two components of the PCA. These two modeled 44.5% of the total variation (Figure 1). The first axis (modeling 30.1% variation) was positively associated with percentage of sand, width, and dissolved oxygen, and negatively with riparian cover and instream cover variables such as; percentage of leafpacks, mud, roots, and small and large woody debris (Table 1) separating creeks and oxbow lakes from river sandbanks (Figure 4). The second axis (modeling 14.4% variation) was negatively associated with water temperature and conductivity and positively with vegetation wide (Table 1). This axis described a physical gradient that separated some oxbow lakes, river sandbanks and creeks (Figure 4, Table 1).

Figure 2 Extrapolation and interpolation of the effective numbers of species of the orders q=0, q=1 and q=2 in the habitats of the Bita river basin (Vichada, Colombia). Results of the NMDS analysis (stress=0.19) showed that fish community composition differed in all the assessed habitats (ANOSIM, P <0.001) (Figure 3). Creeks and oxbow lakes were close to each other in the ordination diagram, because they share about 70% of the species. River sandbanks were the most isolated habitat in the ordination space, due to its particular composition, characterized by species such as: Serrasalmus irritans, Bivibranchia fowleri, Bivibranchia velox, Boulengerella lateristriga, Brycon pesu, Acestrorhynchus falcatus, Loncogenys ilisha, Acestrocephalus sardine, Astyanax bimaculatus, Creagrutus phasma, Microschemobrycon callops, Knodus cinarucoense, Roeboides affiis, Leptodoras linnelli, Phenacogaster prolatus, Mastiglanis asopos, Haemomaster venezuelae, Eigenmannia macrops, Cichla temensis, Panaqolus maccus and Paratocinclus eppleyi. Figure 4 Principal Component analysis (PCA) of the habitats evaluated in the Bita river basin (Vichada, Colombia), based on habitat and environmental variables. In general, environmental variables explained 34% of species variation in the assessed habitats. Species such as: Leporinus fasciatus, Hemigrammus elegans, Batrochoglanis villosus, Dicrossus filamentosus and Curimatopsis evelynae, were associated to creeks and oxbow lakes. These species were also related to the structural complexity index, conductivity and forest cover (Figure 5). In river sandbanks, we found species such as: Leporinus friederichi, Limatulichthys griseus, Knodus cinarucoensis, Moenkhausia copei, Amozonpratus scintilla, Aphyochrax alburnus, Bivibranchia fowleri, Creagrutus phasma and Eigenmannia macrops, which were associated with dissolved oxygen and river width (Figure 4). According to the results of the forward selection procedure, only structural complexity (p= <0.001) and conductivity (p= 0.02) were significantly correlated with species distribution. Ordination diagrams (Figures 4&5) showed that creeks and oxbow lakes were similar in terms of species composition and environmental variables. These two habitats shared Figure 3 Non-metric multidimensional scaling, of the fish fauna composition many species that inhabit sites with high structural complexity and in the habitats evaluated along the Bita river basin. forest cover.

debris contribute to habitat diversification,56 favoring the formation of microhabitats by increasing the spatial heterogeneity at the bottom of the river.57,58 For instance, species such as Tatia marthae, Tatia nigra, Batrochoglanis villosus, Ochmacanthus alternus, Amblydoras bolivarensis, Acanthodoras cataphractus among others, inhabit inside trunks for protection and foraging on invertebrates.6 In addition, these structures provide surfaces that favor the presence of invertebrates that are a food source of other fish species,59 and refuge for different life stages of fish fauna.14 Studies in the Cinaruco River (Venezuela), a similar system to ours have reported that structural complexity in creeks and oxbow lakes is strongly related to fish diversity, where the niche packing and habitat segregation seem to be responsible for the high diversity.6 Riparian cover was one of the variables that separated creeks and oxbow lakes from river sandbanks, studies in the Neotropics have shown that a better vegetal cover is related to a better water quality, that increase the number of native species and decrease the number of dominant and invasive species.60 The vegetal cover is also important because it is a source of allochthonous material, which is used as food and shelter for aquatic species.14,16,59–61 Leaflitter, roots and submerged branches support a higher primary and secondary productivity providing more foraging sites with diverse substrates for fish species.6 This could explain the presence of invertivores species such as Copella nattereri, Anostomus ternetzi, Acaronia vultuosa and Figure 5 Canonical Correspondence Analysis (CCA), relating fish community Geophagus abalios among others. structure with environmental variables and sampling sites in the Bita River Basin (Vichada, Colombia). Only the species well characterized by the first two Submerged vegetation produces an increase in shade, lower water CCA components are shown. temperature, and different types of microhabitats that fish species can exploit.62 This habitat feature traps detritus in its leaves and roots,63 Discussion which is used by detritivores species such as Cyphocharax spilurus. In this study, we investigated if there was a positive relationship Additionally, submerged vegetation provides camouflage and refuge between habitat structural complexity and fish diversity in a to some species (Dicrossus filamentosus, Elachocharax pulcher, Neotropical river basin. To do that, we evaluated three habitat types Apistogramma honsloi, physopysix lyra) to hide from predators such (creeks, oxbow lakes and river sandbanks) along the longitudinal as carnivorous species (Hoplerythrinus unitaeniatus, Crenicichla wallacii, Acestrorhyncus microlepis), and it is used for some species gradient of the Bita river basin as a mean to compare habitats with 64,65 different structural complexity. Our results suggest that environmental as spawning areas. variables such as habitat structural, complexity index and conductivity In southeastern Brazil, Gerhard et al.,66 identified patterns of were significantly associated with species abundance and distribution. association between fish communities and habitat variables. Their In general, it was observed that as the structural complexity index results suggested that species exchange in the lower parts of rivers is increased fish diversity increased too, supporting in part our initial due to an increase in the ecosystem productivity and greater habitat prediction. We expected that survey sites with low habitat structural complexity. Our results suggested that fish assembly in the different complexity index will show low species richness. However, in river habitats of the Bita River drainage respond to habitat structural sandbanks were the values of structural complexity index were low complexity, as well as to the influence of conductivity. we found a high species richness. Contrary to our prediction and contradicting most of the literature Results of the first three orders of Hill’s numbers revealed different on fish diversity and habitat structural complexity, we registered a diversity patterns. According to the order q=0 which measures species high species richness and the greatest abundance in river sandbanks. richness without taking in to account abundance, we did not find This habitat registered the lower values of the structural complexity significant difference among the evaluated habitats, rejecting our index and was characterized by a homogeneous sand substrate, greater working hypothesis. However, when evaluating the others two orders channel width, and high dissolved oxygen. High values of abundance which take into account rare and common species, river sandbanks and species richness could be related to the fact that fish species use registered low values of effective number of species supporting our this habitat as a refuge from the predation during certain periods hypothesis. These results showed the importance of using diversity of their life history.6 In a Neotropical river similar to our system, measures that go beyond the number of species. As proposed by Chao Echevarría, et al.,10 found that areas with open sand and low habitat et al.,51 it is crucial to consider evenness and inequality when studying structural complexity had higher species richness and trait diversity. biodiversity. They argued that despite habitats with submerged vegetation are more The highest values of the habitat structural complexity index complex that open sand areas, they tend to last less preventing fish were registered in creeks and oxbow lakes, these habitats were communities to reach higher species richness. characterized by higher percentages of tree branches, trunks, roots, We are aware that there could be certain limitations due to sampling leaves and lower water flow. The high diversity and richness of bias related to the gears used, especially in littoral areas of the creeks these habitats could be related to the fact that the trunks and woody and oxbow lakes. However, we performed a standardized sampling,

Citation: Ospina DCM, Delgado EOL, Hevia V, et al. Effects of habitat structural complexity on diversity patterns of neotropical fish assemblages in the Bita river basin, Colombia. Biodiversity Int J. 2019;3(6):267‒274. DOI: 10.15406/bij.2019.03.00154 Copyright: Effects of habitat structural complexity on diversity patterns of neotropical fish assemblages in the Bita 272 river basin, Colombia ©2019 Ospina et al. that yielded a high number of small species which are representative 10. Echeverría G, González N. Fish trait diversity in littorals of two floodplain to evaluate the species-habitat associations. De Bie et al.,67 compare lakes of the highly biodiverse Caura River, Venezuela. Ecology of aquatic communities of different taxa and found that small freshwater freshwater fish. 2018;27(1):158–159. organisms represent strongly habitat-associations due to their dispersal 11. López Delgado EO, Winemiller KO, Villa Navarro FA. Do meta limitation, short generation timer and rapid population growth. community theories explain spatial variation in fish assemblage structure in a pristine tropical river? Freshwater Biology. 2019;64(2):367–379. Species composition in the assessed habitats agrees with different studies performed in the Orinoco River Basin, where the orders 12. Fischer JR, Paukert CP. Habitat relationships with fish assemblages in Characiformes and Cichliformes are the most diverse at family minimally disturbed Great Plains regions. Ecology of Freshwater Fish. level.68–73 The Bita River basin was characterized for its high species 2008;17(4):597–609. richness, the collected species represented 20% (191 spp.) of the 13. Karr JR. Ecological perspective on water quality goals. Environmental total reported for the Orinoco River Basin (958 spp.) and 50% for management. 1981;5(1):55–68. 75,75 the Meta River (380 spp.). These results position this basin as one 14. Angermeier PL, Karr JR. 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