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All issues Volume 58 (2022) Int. J. Lim., 58 (2022) 2 Full HTML
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Issue
Int. J. Lim.
Volume 58, 2022
Article Number 2
Number of page(s) 8
DOI https://doi.org/10.1051/limn/2022003
Published online 20 April 2022

© EDP Sciences, 2022

1 Introduction

Predicting changes in an ecosysteḿs functioning requires understanding the processes which define the diversity patterns of its biological communities (Ricklefs, 1987). The structure and diversity of species assemblages at the global level depend on historical processes which can constrain diversity patterns (Vyverman et al., 2007). At the regional scale, restrictions to dispersion and colonization can be determinant (Heino et al., 2015), and at the local level mostly biotic and abiotic factors can modulate them. Overall, biological assemblages are the product of interacting processes of colonization, dispersion, and environmental factors, such as hydrology and water chemistry (González-Trujillo et al., 2020a, Potapova and Charles, 2003).

River ecosystems in the Andean Mountains are important mediators between the region's terrestrial and aquatic ecosystems. Human settlement and activities are increasingly transforming river ecosystems in the Andean range (Donato-R and Sabater, 2014). These influences cause them to direct water pollution, basin deforestation, human water attribution, and the utilization and loss of soil (González-Trujillo et al., 2020b). The effects may be significant in tropical mountain fluvial systems, which may be then submitted to large water flow variations and the input of sediments and nutrients.

River flow dynamics in the Andes mostly depend on intense altitudinal gradients and not so much on the seasonal variations which is characteristic of temperate climates. Altitudinal gradients create steep slopes that regulate water volume and velocity, controlling sediment transportation, organic matter, nutrients, and biological assemblages composition (Donato and Galvis, 2008). However, due to the rapid warming of tropical Andean zones (Bradley et al., 2006) and the unpredictable interannual precipitation variability in Colombia (Arias et al., 2021), it is unknown how these elements will impact water fluxes and the biological assemblages associated with these rivers. Under this environment, contributing nutrients may be a predominant factor that alters the biomass and structure of biological communities and increase their autotrophic character, even under high water flow conditions (Artigas et al., 2013; Chaparro, 2010; Donato et al., 2010).

Eutrophication in tropical rivers is limited, and in the northern Andes, the information turns around the use of biotic index (Ríos-Touma et al., 2014). Studies on tropical streams in Africa indicated differences between conserved and disturbed catchments, being the diatom assemblages in the disturbed rivers more abundant in eutrophic tolerant species (Bellinger et al., 2006). Flushing rate and water level are determinants for algal development in polluted rivers; however, this is expected in rivers deep enough and with long hydraulic residence (Hilton et al., 2006). The altitudinal gradient is essential for the flow of mountain rivers in the Andes. This aspect, joined to the anthropogenic pressure in the area and uncertain precipitation and temperature of the Colombian Andes, limits the understanding of the response that the mountain rives in Colombia will experience. We used data from a previous experiment in a mountain river in the northern Andes in Colombia to examine the response of diatom assemblages to nutrient enrichment under different water level conditions to fill the gap about the response that Andean rivers will show to eutrophication in a scenario of fluctuating water level conditions, using a long-term on-site experiment. The experiment aimed to test the hypothesis that nutrient enrichment affects the local diversity of diatom assemblages in Andean streams under basal water flow conditions but not when the water regime shifts to high water flow conditions, when nutrient influence becomes irrelevant. High mountain tropical streams remain relatively under-researched, even though watercourses are essential in the context of watershed use and at the same time because they are strongly affected by anthropic activities. Understanding the relationship between biodiversity and environmental variability is of great importance to mitigate the deterioration of the structure and functioning of river ecosystems (Dudgeon et al., 2006), and how they can change is critical to managing them in the future (Tonkin et al., 2019).

2 Methods

2.1 Study area

The study was performed in the Tota River (Río Tota), a third-order river system located at 2540 m above-sea-level (05° 34′ 53.04″ N, 72° 59′10.9″ W) in the eastern Colombian mountain range in the province of Boyacá, Colombia. The stream drains a 140 km2 basin containing mainly shale and clay. Approximately 40% of the basin's surface area is used for agriculture, livestock, and pasture (Castro and Donato, 2008), the rest is covered by secondary forest and sparse vegetation (Artigas et al., 2013). The average multi-annual monthly temperature ranges from 10.5 to 11.8 °C, and the annual average rainfall is 730.5 mm. The area is subjected to a bimodal rainfall regime, higher precipitation occurring from April to May (97.6 to 87.4 mm per month) and from October to November (76.7 to 86.1 mm per month), while the period of lower precipitation is from December to February (26.2 to 26.5 mm per month) (data from El Túnel weather station, IDEAM). The average streamflow in the stream averages 670 L s−1, high water conditions occur between May to July and October to November, and minimum flows between December and March (Castro and Donato, 2008). Riparian vegetation mainly consists of willows (Salix nigra), alders (Alnus acuminata), eucalyptus (Eucalyptus globulus), and kikuyo grass (Pennisetum clandestinum).

2.2 Study design

Fertilization in the experimental section began in April 2008 and finish in January 2009. The upstream reach (05°34′53.04′′N, 72°59′10.9′′W) served as the control (CS) and was 2,500 m upstream of a second reach (05°35′13.6′′N, 72°59′2.54′′W), which served as the experimental section (ES). To ensure that both reaches had similar conditions, both sections of the river were monitored 6 months before the fertilization (October 2007 to March 2008). Physical, chemical, and hydraulic measurements and diatom community samples were collected in each of the two reaches, and incident radiation was measured with a PAR LiCor Li190S.

The ES continuously received assimilable P2O5 phosphate, N-NH4+ ammonia and N-NO3– nitrate. Nutrient solution was dissolved in river water in a 500 L tank and then released through a hose system into the ES at 0 m, 20 m, and 40 m. Nutrient fertilization was continuous with a constant rate of discharge, and the concentration of each nutrient was weekly adjusted according to the river concentration, so that the concentration of each nutrient in the ES was three times that in the CS (Chaparro, 2010).

2.3 Physical and chemical water analysis

In both ES and CS, monthly measurements were performed on hydraulic, physical, and chemical variables. River depth was measured at three points (located at 25%, 50%, and 75% of the channel width) in each of the two reaches, and from these three depths, the average water depth was estimated (Wetzel and Likens, 2000). Temperature (°C), conductivity (μS cm−1), oxygen (O2), and pH [H+] of the river water were measured simultaneously with a YSI sensor, Model 5563-10 MPS. Water velocity measurements (ms−1) were obtained using a digital Globalwater flowmeter. Water samples were collected in each of the sites and filtered (Whatman GF/C). Phosphate concentrations were determined using the molybdate method; ammonia was determined using the salicylate method. Nitrate concentrations were obtained by passing the water samples through a reduction column and then analyzing the nitrite using the sulfanilamide method (Butturini et al., 2009). We estimated a monthly nutrient quotient to determine the ratio of nutrient increase induced by fertilization:Qm=averagem[nutrientexp]/averagem[nutrientcontrol]

where Q is the nutrient quotient for a given month m, averagem [nutrientexp.] is the average nutrient concentration in the ES for that month, and averagem [nutrientcontrol] is the average nutrient concentration in the CS for the same month (Chaparro, 2010).

2.4 Diatom community analysis

Artificial ceramic substrata (1.2 × 1.2 cm) were colonized in the CS and ES for 4 weeks, and then collected to estimate both the richness and diversity of diatom communities. Substrata were attached to three different concrete slabs submerged in the river. We assumed four weeks as the time required for a benthic diatom community to reach a composition resembling natural assemblages; (Peterson, 1987). At the end of this period, substrata from each slab were randomly collected, and the biofilm cleaned and preserved in 4% formalin. Organic materials from the samples were oxidized using 30% Hydrogen Peroxide. The diatom frustules were mounted on slides using Naphrax® following the protocol described in Bellinger and Sigee (2015) and observed under an Olympus CX21 microscope at 1000x magnification. Diatoms identification used the manuals of Krammer (2002), Krammer and Lange-Bertalot (1986, 1991a, 1991b) and Lange-Bertalot (1993, 2001). At least 400 valves on each plate were counted and classified, and the number of individuals counted for each species was used to calculate the relative abundance.

2.5 Data analysis

The arithmetic means and coefficient of variations (CV) were used to estimate the measurements' central tendency and dispersion. The sampling effort effectivity was calculated with EstimateS Win 9.1 (Colwell et al., 2012), using a 1st-order Jackknife estimator, the Abundance Coverage Index (ACE), and Chao 1 estimator. The Shannon-Wiener (H') and the Simpson indices (S) for diatom diversity were calculated using PAST 3.14 (Øyvind et al., 2005). A one-factor ANOVA test was run to detect significant changes (p ≤ 0.05) in diversity between the reaches. We performed parametric correlations (Pearson correlation) among the environmental variables (except incident light) and diatom diversity of the two reaches. All analyses were performed with SPSS v20.

The diatom community statistics and environmental data, except for temperature and pH, were transformed using base-10 logarithms. Using Canoco 4.56, a Redundancy Analysis ('RDA,' Thompson, B. 1984) was performed to identify the relationship between the diatom taxa and environmental variables. Initially, we used the averages of all the environmental variables. Then, the Forward Selection procedure was applied to decrease the number of explanatory variables and obtain a more parsimonious model. Factors with variance inflation less than five were chosen to avoid multi-collinearity; model significance was tested through Monte Carlo simulation (999 permutations), and species with a representative percentage equal to or greater than 1% were chosen.

3 Results

3.1 Physical and chemical variables

The Control Section (CS) had flow rates ranging from 28 Ls−1 to a maximum of 1911 Ls−1. During The lowest flow rates (28–113 Ls−1) occurred in February and April 2008, while the highest rates (723–1911 Ls−1) occurred in October 2007 and May–July of 2008. For the experimental period, low waters occurred during December 2008 to January 2009, and the high flow season was observed from May to July 2008. Water conductivity ranged from 47 μS cm−1 during periods of high flow or rainfall to 134 μS cm−1 during low flow periods. Water temperature varied between 12.8 and 15.8 °C, dissolved O2 between 7 and 7.9 mg l−1, and pH between 5.8 and 8.0 (Fig. 1). Finally, incident light oscillated between 258 and 897 μmol photons s−1 m−2. The Experimental Section (ES) had flow rates between 21.5 and 1394 Ls−1, with maxima and minima occurring in the same periods as for the CS. Water conductivity ranged between 49 and 188 μS cm−1, temperature between 11.6 and 8.0 °C, pH between 6.6 and 7.9 (Fig. 1), and incident light 522 to 1290 μmol photons s−1 m−2. The one-factor ANOVA test indicated that there were no significant differences between these five environmental variables in the ES and those in the CS (p = 0.277, p = 0.375, p = 0.132, p = 0,857, and p = 0.195, respectively for water conductivity, temperature, dissolved O2, pH, and incident light). In both sections, the variations in conductivity with respect to time were negatively correlated with flow rate: r = –0.945, p = 3.631 × 10−6, for CS; r = –0.923, p = 3.421 × 10−7 for ES). The same was true of temperature (CS: r = –0.688, p = 0.013; ES: r = –0.841, p = 1.635 × 10−4).

Basal nutrient concentrations in the two reaches before the experimental nutrient addition ranged between 11.4 and 130.6 μg L−1 P-PO4; between 4.1 and 45.2 μg L−1 N-NH4; between 1.4 and 48.9 μg L−1 N-NO2; and between 0.2 and 196.1 μg L−1 N-NO3 (Fig. 2). The concentrations of ammonia in the two reaches were relatively higher during the low-water season (January 2009). Nutrient enrichment caused the nutrient concentrations to increase in ES (Fig. 2), where P ranged between 16.1 and 476.2 μg L−1; ammonia between 3.2 and 940 μg L−1; nitrite between 2.5 and 12.3 μg L−1 and nitrate between 1.3 and 3948 μg L−1. Nutrient increases therefore ranged 1.5–3 times, differences being significant for P, NH4, NO3 (p = 0.025, p = 0.017 and p = 0.020, respectively). Ammonia concentrations were negatively correlated with flow rate in both the CS and ES (r = –0.59, p = 0.005 and r = –0.728, p = 8.295 × 10−5, respectively) and, in the ES, there was a negative correlation between nitrate concentration and flow rate (r = –0.848, p = 4.968 × 10−4).

thumbnail Fig. 1

Records of the physical and chemical variables of the control and fertilized section during the sampling in the Tota stream. Start of fertilization in April 2008.
thumbnail Fig. 2

Nutrient records of the control and fertilized section during the sampling in the Tota stream. Start of fertilization April 2008.

3.2 Diatom community structure

118 diatom taxa were identified during the study. The rarefaction analysis (Fig. 3) indicated that the asymptote was not reached. The ACE varied between 50 and 68.9; Chao 1 between 46 and 64.3; and Jack1 between 70.5 and 73.4. The species with the highest relative abundances, i.e., the dominant and co-dominant species, were: Rhoicosphenia abbreviata (RABB), Nitzschia dissipata (NDIS), Cocconeis placentula (CPLA), Reimeria sinuata (RSIN), Achnanthidium minutissimum (AMIN), Nitzschia Sp2, (NSP2), Epithemia sorex (ESOR), Melosira varians (MVAR), and Nitzschia Sp1 (NSP1) (Fig. 4a,b).

The Shannon-Wiener index (H́) for diatom diversity ranged from 0.68 to 2.2, with relatively high values during high water time (October 2007 and May 2008) for CS and ES. Relatively low values occurred during February 2008 and October 2008. On average, the highest values of the Simpson index (S) occurred for the original condition (October 2007 (0.81) and February 2008 (0.76)) (Fig. 5), while the lowest values were observed in April 2008 (0.51) and January 2009 (0.48). Although diatom diversity in the ES initially increased with nutrient enrichment (Fig. 5), diversity was greater in the unfertilized CS by the end of the experiment.

There was a significant relationship in the CS between the diversity indices and phosphate concentration (H́: p = 0.004; S: p = 0.007, n = 27), as well as with nitrate concentration (S: p = 0.001, n = 27). H′ was significantly correlated with water flow (r = 0.578, p = 0.002, n = 27) and S was negatively correlated with phosphate concentration (r = –0.664, p = 0.009, n = 27). In the ES, H́ was significantly correlated with ammonia concentration (p = 0.03; F = 12,310, n = 27) and phosphate concentration (p = 0.01; F = 21,389, n = 27), while S was not significantly associated to the experimental variables.

Based on the previous correlation analysis, conductivity, phosphate concentration, nitrate concentration, and flow rate were selected for the RDA. The first two axes explained 83.3% of the data variation. Phosphate concentration (28%), nitrate concentration (22%), flow rate (18%), and conductivity (16%) contributed to the variance. The variables associated with the first axis were flow rate, nitrate concentration, and conductivity (negatively), while phosphates were associated with the second axis (Fig. 6). Higher phosphate concentrations, high flow rate, and low water conductivity were associated with the abundance of Epithemia adnata var. minor, (EMIN), Nitzschia dissipata (NDIS), and Reimeria sinuata (RSIN). Navicula rynchocephala (NGER), Gomphonema parvulum (GPAR), Navicula capitatoradiata (NCPR), and, to a lesser extent, Melosira varians (MVAR) were associated with higher phosphate concentrations. In contrast, Achnanthidium minutissimum (AMIN), Cocconeis placentula (CPLA), and Epithemia sorex (ESOR) were associated with lower phosphate concentrations.

thumbnail Fig. 3

Diatom accumulation curves in the Tota stream both in the control and fertilized section.
thumbnail Fig. 4

(a) Valves number with greater representativeness in the control section in Tota stream. Rhoicosphenia abbreviata (RABB), Nitzschia dissipata (NDIS), Cocconeis placentula (CPLA), Reimeria sinuata (RSIN), Achnanthidium minutissimum (AMIN), Nitzschia Sp2, (NSP2), Epithemia sorex (ESOR), Melosira varians (MVAR), and Nitzschia Sp1 (NSP1). b-. Valves number with greater representativeness in the fertilized section in Tota stream. Nitzschia Sp2, (NSP2), Navicula rynchocephala (NGER), Nitzschia Sp1 (NSP1), Nitzschia Sp (NSCH), Epithemia adnata var. minor, (EMIN), Gomphonema parvulum (GPAR), Navicula capitatoradiata (NCPR).
thumbnail Fig. 5

Shannon (H́) and Simpson's diversity values. The red line shows the start of fertilization in April 2008.
thumbnail Fig. 6

Redundancy analysis (RDA) for the significant environmental variables and the most representative diatom species.

4 Discussion

Our results agree with previous works in the Tota river (Rivera and Donato, 2008; Donato et al., 2010; Artigas et al., 2013; Donato, 2019), which emphasize the importance of nutrient concentrations of water and conductivity in the structuring of diatom communities (Potapova and Charles, 2003; Soininen et al., 2004).

Diatom diversity and composition did not significantly differ between the two reaches of the Andean stream before the long nutrient addition experiment. However, diatom diversity and composition significantly differed between the two sections once the in situ experiment progressed. Overall, the increased nutrient concentrations (and particularly phosphates and ammonia) were drivers for diatom diversity change. Therefore, our experiment showed that the nutrient addition to oligotrophic Andean rivers caused a shift in the diatom composition and diversity, as much as other studies have shown elsewhere (Donato, 2019; Biggs and Smith, 2002). However, this response was not maintained during the high-water flow season, when differences between the two reaches were minor. Consequently, for these results, diatoms can serve as a proxy of the degree of eutrophication in these mountain streams (Bellinger et al., 2006).

Our results support the hypothesis that, in addition to nutrients, other environmental characteristics (mainly water flow and conductivity) influence the diatom community structure (Stendera et al., 2012). A similar study conducted in the Tota River (Rivera and Donato, 2008) found no significant relationship between nutrients and community diversity. Our results partly coincide with those of Castellanos (2004), who found that diatom diversity in the Tota River was related to ammonia, silica, and phosphate concentrations.

The role of nutrients on diatom richness and diversity is prevalent to that of conductivity and pH, which usually are described as ecological factors playing an important role in the regional structure of diatom composition (Potapova and Charles, 2002; Dow and Zampella, 2000). This experiment shows that diatom diversity in Andean oligotrophic streams is mainly explained by nutrient availability and water flow. These changes in short-term explanatory factors point to a response of seasonal character (Artigas et al., 2013) in Andean tropical mountain streams. It is a special ecological feature that influences the response of species ranging from eutrophy (Melosira varians, Navicula rynchocephala y Navicula capitatoradiata) to oligotrophy (Achnanthidium minutissimum, Cocconeis placentula, Reimeria sinuata, and Nitzschia sp). This, together with the taxonomic species diversity reported (118), helps explain the relatively high values of diatom diversity in these streams and demonstrates the ecological significance of Andean Mountain streams and their contribution to biodiversity.

In conclusion, this study showed that phosphate, nitrate, and ammonia concentrations, as well as flow rate, are determinant for the response of diatom diversity in Andean rivers. Finally, these results may apply to other tropical mountain (oligotrophic) streams threatened by a wide range of anthropic activities. Andean mountain rivers and their basins represent a vast network with diverse geologic and geomorphologic patterns united by a surrounding environment of hydraulic and nutrient regimes, land-use, and altitudinal gradients with similar temperatures. This characteristic, along with the biodiversity of Andean fluvial systems, must be the basis for developing regional plans for identifying critical areas in need of conservation (Higgins et al., 2005) and for defining services essential for the well-being of freshwater ecosystems (Stendera et al., 2012).

Acknowledgments

This study was funded through the project Global changes in fluvial systems: effects on the trophic web biodiversity and the functional aspects (GLOBRIO) − Banco Bilbao Viscaya − Argentaria (BBVA) − Colciencias-Universidad Nacional de Colombia. Additional financing was obtained through project RC 204-2006, financed by Colciencias − Universidad Nacional de Colombia. José Alejandro Cuellar C helped perform the statistical analyses.

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Cite this article as: Donato-R JC, Mendivelso HA, Pedraza-Garzón EL, Sabater S. 2022. Drivers of the diversity of diatoms in an oligotrophic Andean stream. Int. J. Lim. 58: 2

All Figures

thumbnail Fig. 1

Records of the physical and chemical variables of the control and fertilized section during the sampling in the Tota stream. Start of fertilization in April 2008.
In the text
thumbnail Fig. 2

Nutrient records of the control and fertilized section during the sampling in the Tota stream. Start of fertilization April 2008.
In the text
thumbnail Fig. 3

Diatom accumulation curves in the Tota stream both in the control and fertilized section.
In the text
thumbnail Fig. 4

(a) Valves number with greater representativeness in the control section in Tota stream. Rhoicosphenia abbreviata (RABB), Nitzschia dissipata (NDIS), Cocconeis placentula (CPLA), Reimeria sinuata (RSIN), Achnanthidium minutissimum (AMIN), Nitzschia Sp2, (NSP2), Epithemia sorex (ESOR), Melosira varians (MVAR), and Nitzschia Sp1 (NSP1). b-. Valves number with greater representativeness in the fertilized section in Tota stream. Nitzschia Sp2, (NSP2), Navicula rynchocephala (NGER), Nitzschia Sp1 (NSP1), Nitzschia Sp (NSCH), Epithemia adnata var. minor, (EMIN), Gomphonema parvulum (GPAR), Navicula capitatoradiata (NCPR).
In the text
thumbnail Fig. 5

Shannon (H́) and Simpson's diversity values. The red line shows the start of fertilization in April 2008.
In the text
thumbnail Fig. 6

Redundancy analysis (RDA) for the significant environmental variables and the most representative diatom species.
In the text

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