Research Article |
Corresponding author: Demetrio Mora ( demetriomora@gmail.com ) Academic editor: Kalina Manoylov
© 2017 Demetrio Mora, Javier Carmona, Regine Jahn, Jonas Zimmermann, Nélida Abarca.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Mora D, Carmona J, Jahn R, Zimmermann J, Abarca N (2017) Epilithic diatom communities of selected streams from the Lerma-Chapala Basin, Central Mexico, with the description of two new species. PhytoKeys 88: 39-69. https://doi.org/10.3897/phytokeys.88.14612
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The Lerma-Chapala Basin, in Central Mexico, is geologically heterogeneous, climatically diverse and boasts high biodiversity, lying within two Biodiversity Hotspots, namely Mesoamerica and the Madrean Pine–Oak Woodlands. Epilithon and water samples were collected in the basin from 14 sampling sites three times each, two sampling campaigns during the rainy season and one in the dry season. A total of 274 infrageneric taxa in 48 genera were recorded. The taxonomic composition observed was dominated by taxa from the genera Nitzschia, Gomphonema, Pinnularia, Navicula, Sellaphora and Eunotia. About a third of the taxa found could not be identified to the species level. From those unidentified morphodemes, two are described as new species, namely Brachysira altepetlensis and Sellaphora queretana. Furthermore, Eolimna rhombica is transferred to Sellaphora. Canonical Correspondence Analysis (CCA) revealed that specific conductivity and pH were the main environmental factors driving the community composition observed. Three groups of samples were identified after the CCA: 1) characterized by acidic waters and low conductivity; 2) with circumneutral waters, low specific conductivity and high temperature and phosphorous concentrations; and 3) characterized by circumneutral waters, high conductivity and low nitrogen concentrations. The indicator value method (IndVal), based on the relative abundance and relative frequency of the most abundant taxa was calculated based on the groups observed in the CCA, identifying the characteristic taxa for each of the three groups.
Central Mexico, diatom communities, epilithon, indicator species, Lerma-Chapala Basin, mountain streams, new species
Lotic environments, i.e. streams, are unidirectional flows of water. They are characterized by a broad spatial (i.e. substrate, slope, vegetation) and temporal (i.e. water velocity, light) heterogeneity, which determines the specialized biota that inhabit them (
Even though there is mounting evidence of the applied use of diatoms as indicators of environmental change in lotic environments (
Diatom studies of lotic environments from Mexico have been mostly focused on the center of the country: Antigua River Basin (
The studies conducted in the Lerma-Chapala Basin have been focused on the polluted Lerma River and some of its main tributaries (Abarca-Mejía 2010,
In order to contribute to the studies done in the Lerma-Chapala Basin, one of the most important basins of the country regarding population and trade, the aims of this study are: to document the epilithic diatom diversity from selected headwater and midland streams from the Lerma-Chapala Basin, Central Mexico; to illustrate the most abundant taxa; and to identify the environmental factors that determine the variation observed in diatom composition.
Study area. The Lerma-Chapala Basin is located in Central Mexico, covering an area of 53,591.3 km2 (Fig.
Location of the area of study. A Map of Mexico, showing the location of the Lerma-Chapala Basin in the center of the country. B Location of the 14 sampling sites in the Lerma-Chapala Basin, indicated by red dots. The numbers next to the red dots refer to the name of the sampling site in Table
This basin is one of the most important centers in the country for agriculture and industry, and has a population of more than 15 million inhabitants (
The 14 sampling sites selected for this study are located in the north and central–east sections of the Lerma-Chapala Basin at elevations ranging from 2,000 to 2,400 meters above sea level. Of those 14 sites, one is a perennial spring–fed creek and 13 correspond to streams that have water during most part of the year (Fig.
Sampling sites in the Lerma-Chapala Basin, including site number and name, type of water body, geographical coordinates and elevation.
Site | Water body | Latitude (N) / Longitude (W) | Elevation (m a.s.l) | ||
---|---|---|---|---|---|
1 | La Mesa | Stream | 21°05'28.69"N, 101°08'18.98"W | 2215 | |
2 | Calvillo | Stream | 21°06'50.40"N, 101°08'04.10"W | 2138 | |
3 | Ojo de Agua de Calvillo | Stream | 21°07'41.80"N, 101°07'04.50"W | 2102 | |
4 | Peña Colorada | Stream | 21°09'03.84"N, 101°05'58.96"W | 2110 | |
5 | San Martín | Stream | 21°09'24.50"N, 101°03'11.30"W | 2017 | |
6 | Paredones | Stream | 21°11'20.60"N, 101°06'53.40"W | 2089 | |
7 | La Laborcilla 1 | Stream | 21°11'04.70"N, 101°06'14.60"W | 2076 | |
8 | La Laborcilla 2 | Stream | 21°11'20.10"N, 101°05'37.90"W | 2065 | |
9 | El Membrillo | Stream | 20°50'21.22"N, 100°38'43.46"W | 2114 | |
10 | Guanajuatito | Spring fed-creek | 20°53'23.98"N, 100°32'30.72"W | 2120 | |
11 | Los Ailes 1 | Stream | 20°19'58.72"N, 100°15'17.09"W | 2358 | |
12 | Laguna de Servín 1 | Stream | 20°18'18.10"N, 100°17'38.10"W | 2409 | |
13 | Laguna de Servín 2 | Stream | 20°18'45.20"N, 100°17'25.60"W | 2409 | |
14 | Los Ailes 2 | Stream | 20°20'50.20"N, 100°16'45.50"W | 2317 |
Sampling. Water and epilithon samples were collected three times from each sampling site in: September/October 2013, rainy season (sampling campaign I); February 2014, dry season (sampling campaign II); and September 2014, rainy season (sampling campaign III); resulting in 42 water and epilithon samples. Each epilithon sample was collected from five cobbles across a transversal section of the stream, brushing with a disposable toothbrush ten square centimeters of epilithic growth from each of the five cobbles to make a composite sample, fixed in 70% alcohol. In situ measurements of pH, water temperature, specific conductivity and total dissolved solids were recorded using a Hanna multi–sensor (HI 991300, California, USA). Dissolved oxygen was recorded with an YSI–85 oxygen meter (YSI, Ohio, USA). Dissolved oxygen saturation percentages were calculated from dissolved oxygen data according to correcting factors for elevation and water temperature. Specific conductivity values were corrected to 25°C. Water velocity was recorded with a Global Water FP111 velocity meter (Texas, USA). At each sampling site, a 500 ml sample of water was filtered through 0.22 μm and 0.45 μm filter membranes (Millipore, Massachusetts, USA) and collected in sterile polypropylene bottles for chemical analysis. Samples were kept cold and in the dark before laboratory analysis. The subsequent chemical laboratory analyses were adapted from Standard Methods for the Examination of Water and Wastewater and analyzed using a DR 3900 laboratory Spectrophotometer (Hach Company, Loveland, Colorado) (
The Riparian Forest Quality index (QBR from its Catalan abbreviation) was calculated in order to evaluate the riparian habitat quality (
Diatom analysis. Fractions of the diatom samples were cleaned by adding aliquots of 35% hydrogen peroxide and heating at 80°C until no bubbling was observed. After the digestion was completed, peroxide remnants were removed by rinsing at least three times with distilled water. Samples were finally diluted with distilled water in order to avoid high concentrations of valves and sediment. Three permanent slides per sample were made using the high refraction index mounting medium Naphrax®. The slides were scanned and the diatoms photographed under the light microscope (LM) in order to account for diatom diversity, using a Zeiss Axioscope microscope with Differential Interference Contrast equipped with an AXIOAM MRc camera. In order to estimate the relative abundance of the taxa, a minimum of 500 valves per sample were counted and identified with the 100x immersion oil objective. Aliquots of cleaned sample material for scanning electron microscopy observations were mounted on stubs, sputter-coated with gold-palladium and observed under a Hitachi FE 8010 scanning electron microscope (SEM) operated at 1.0 kV. Samples and slides are stored at the Diatom Collection of the Botanical Garden and Botanical Museum Berlin–Dahlem, Freie Universität Berlin. Diatoms were identified to the lowest taxonomical level possible using monographs as well as papers for particular taxa (Suppl. material
Data analysis. Only taxa with relative abundance ≥1% were included in the statistical analyses, resulting in 105 diatom taxa. Diatom abundances were transformed using Hellinger’s transformation, which is suited to large abundance datasets with lots of low counts and zeros (
From the initial dataset composed of 42 samples, only 39 were used for the analysis of running waters, i.e. those streams with water velocity records in at least one of the sampling campaigns; the three samples of site 10 were omitted since no water velocity was recorded in this spring-fed creek at any of the three sampling campaigns, with 10 cm/s being the detection limit of the water velocity meter. All the environmental variables, except for temperature, pH and water velocity were transformed using log10 (x+1) because they had skew distributions. Distribution tests were run in Statistica 8.0.
Multivariate analyses were performed to explore gradients in diatom composition and its relation to environmental factors. Detrended Correspondence Analysis (DCA) was used to estimate gradient lengths. The first four axes showed lengths of 5.7, 3, 2.3 and 2.2, suggesting a strong unimodal response, meaning that a method based on unimodal models like Canonical Correspondence Analysis (CCA) would be appropriate for subsequent ordination. CCA was run to identify variation in species composition that can be determined by environmental variables. Since not all the environmental variables influence diatom distributions independently, CCA with forward selection and unrestricted Montecarlo permutation tests was used (999 permutations, p<0.05). All ordinations were done using CANOCO 4.5 for Windows (ter Braak and Ṧmilauer 2002), with downweighting of rare species in all cases.
The indicator value method (IndVal) (
Species composition and taxonomy. A total of 196 taxa (species and varieties) were found while performing the counts to determine relative abundances. Seventy-eight additional taxa were observed by scanning the whole slides looking for rare taxa, bringing the total diversity to 274 taxa belonging to 48 genera (Suppl. material
Overview of the most abundant taxa (≥ 1% relative abundance in at least one sample). 2 Cyclotella meneghiniana 3Eunotia cf. meridiana4 Eunotia sp. 1 5 Eunotia sp. 3 6 Eunotia sp. 2 7 Eunotia minor 8 Fragilaria pectinalis 9 Fragilaria austriaca 10 Fragilaria bidens 11 Fragilaria tenera 12–13 Achnanthidium sp. 5 14–15Achnanthidium aff. catenatum16–17 Achnanthidium sp. 1 18–19 Achnanthidium minutissimum 20–21 Achnanthidium sp. 4 22–23 Planothidium rostratum 24–25 Planothidium victori 26–27 Planothidium incuriatum 28–29 Planothidium cryptolanceolatum 30–31 Cocconeis pediculus 32–33 Cocconeis sp. 2 34 Ulnaria ulna. Scale bar 10 μm.
Overview of the most abundant taxa (≥ 1% relative abundance in at least one sample). 35 Fistulifera saprophila 36 Craticula subminuscula 37 Craticula sp. 2 38 Craticula molestiformis 39Craticula cf. pumilio40 Sellaphora cosmopolitana 41 Sellaphora sp. 3 42 Eolimna sp. 1 43 Sellaphora nigri 44 Sellaphora madida 45 Sellaphora queretana 46 Sellaphora atomoides 47 Sellaphora saugerresii 48 Sellaphora pupula 49 Mayamaea permitis 50 Reimeria sinuata 51 Diadesmis confervacea 52 Nupela wellneri 53 Geissleria decussis 54 Navicula veneta 55 Navicula erifuga 56 Navicula libonensis 57 Navicula capitatoradiata 58 Navicula symmetrica 59 Navicula notha 60Navicula cf. cryptocephala61Encyonopsis cf. thienemannii62 Navicula gregaria 63 Navicula cryptocephala 64 Navicula reichardtiana 65 Brachysira altepetlensis 66 Encyonema minutum 67 Halamphora montana 68 Amphora pediculus 69 Navicula trivialis 70 Navicula rostellata 71 Frustulia crassinervia 72 Encyonema brevicapitatum 73 Encyonema minutiforme 74Encyonema cf. minutiforme75Encyonema cf. hebridiforme76 Encyonema jemtlandicum 77 Encyonema pergracile. Scale bar 10 μm.
Overview of the most abundant taxa (≥ 1% relative abundance in at least one sample). 78 Gomphonema exilissimum 79 Gomphonema parvuliforme 80Gomphonema cf. parvuliforme81 Gomphonema parvulum 82 Gomphonema lagenula 83Gomphonema cf. lagenula84Gomphonema aff. sarcophagus85Gomphonema aff. mariovense86 Gomphonema subclavatum 87 Gomphonema stonei 88 Gomphonema pumilum 89 Gomphonema graciledictum 90 Gomphonema naviculoides 91 Gomphonema minusculum 92 Gomphonema sp. 4 93 Gomphonema sp. 2 94 Gomphonema innocens 95Gomphonema aff. parvulius96 Nitzschia desertorum 97 Nitzschia semirobusta 98 Nitzschia inconspicua 99 Nitzschia sp. 1 100 Nitzschia supralitorea 101Nitzschia cf. hantzschiana102 Nitzschia fonticola 103 Nitzschia perminuta 104 Surirella angusta 105 Nitzschia acicularis 106 Nitzschia amphibia 107 Nitzschia communis 108 Nitzschia gracilis 109 Nitzschia paleacea 110 Nitzschia intermedia 111 Nitzschia palea 112Nitzschia palea var. tenuirostris113Nitzschia palea var. debilis114 Nitzschia balcanica 115 Nitzschia linearis 116 Epithemia sorex 117 Epithemia adnata. Scale bar 10 μm.
A high specific taxa richness was found among the genera Nitzschia (35 taxa), Gomphonema (26 taxa), Pinnularia (21 taxa), Navicula (19 taxa), Sellaphora (18 taxa) and Eunotia (16 taxa). About a third of the diversity found, 94 taxa, did not fit completely into already described species. Most of the taxa were found in relatively low abundances while further scanning the slides under the LM after the enumeration of 500 valves; when scanning samples under the SEM, some of those rare unidentified taxa were found but in several cases not. When the taxa were found under the SEM, not enough valves were observed for reliable identification. This is why only two new species from those 94 unidentified taxa are here described as new, one belonging to the genus Brachysira and the other to Sellaphora. Furthermore, one Eolimna species is transferred to Sellaphora, this species sharing the same morphology of areolae as the Sellaphora species here described as new.
B 40 0042006; Figure
B 40 0042007 (SEM stub), QMEX DIAT0001 (Slide).
Cleaned unmounted material is available under the numbers B 40 0042008 and QMEX DIAT0002.
Paredones stream, on the outskirts of Paredones village, Dolores Hidalgo, Guanajuato, Mexico (21°11'20.60"N; 101°06'53.40"W; 2089 m a.s.l). Collected by Demetrio Mora on 07.09.2014.
the valves are lanceolate to linear–lanceolate with rostrate apices. The axial area is narrow–linear throughout the valve and the central area round to elliptical (Figs
Brachysira altepetlensis D. Mora, R. Jahn & N. Abarca, sp. nov. LM (118–128) and SEM (129–132). 118–123 type material, from Paredones stream, Guanajuato, Mexico, collected on 07.09.2014 121 designated as holotype 124–125 collected from type location but on 06.10.2013 126–128 collected from type location but on 09.02.2014 129–132 from type material: 129–130 external view of entire valves 131 external view of an entire valve showing elongated areolae in the valve mantle 132 internal view of entire valve, showing occlusion of the areolae by hymens. The arrow points at Voigt discontinuity. Scale bars 10 μm (118–128); 5 μm (129–132).
Brachysira procera Lange-Bertalot & Gerd Moser is the species which most closely resembles B. altepetlensis in valve outline but is larger (25–60 µm), wider at valve center (4.5–6 µm) and has less striae in 10 µm (27–30) (
The valve dimensions as well as the striae density of the new species fall within the range of the Brachysira neoexilis Lange-Bertalot species complex, but the type population of B. neoexilis has clear capitate apices and the larger specimens have a very slightly triundulate valve margins (
this new Brachysira species takes the name from the word “āltepētl” which means “water mountain” in Náhuatl language, that is how the surrounding mountains were used to be named by native people 500 years ago, at the time Spaniards first came to the region.
apart from the type locality, this species was also found in four streams sampled for this study, namely Peña Colorada (site 4), San Martín (site 5), La Laborcilla 1 (site 7) and La Laborcilla 2 (site 8), all of these sites were characterized by low specific conductivity (≤ 100 μS/cm) and pH values going from acidic to slightly alcaline (5.1–7.9). But B. altepetlensis only reached high relative abundances (>10%) in acidic waters (pH= 5.1–5.8) with low specific conductivity (42–53 μS/cm).
B 40 0042009; Figure
B 40 0042010 (SEM stub), QMEX DIAT0003 (Slide).
Cleaned unmounted material is available under the numbers B 40 0042011 and QMEX DIAT0004.
stream Los Ailes 1, close to the town San Pedro, Huimilpan, Querétaro, Mexico (20°19'58.72"N; 100°15'17.09"W; 2358 m a.s.l). Collected by Demetrio Mora on 18.09.2013.
the valves are linear–elliptical with broadly rounded apices (Figs
Sellaphora queretana D. Mora, N. Abarca & J. Carmona, sp. nov. LM (133–140) and SEM (141–144). 133–137 type material, from stream Los Ailes 1, Querétaro, Mexico, collected on 18.09.2013 137 designated as holotype 138–140 population from stream Laguna de Servín 2, collected on 29.09.2013 141–144 from type material: 141, 142, 144 external views of entire valves 143 internal view of an entire valve. Scale bars 5 μm (133–140); 1 μm (141–144).
there are no known taxa with the same combination of valve outline and areola type. The outline of S. queretana resembles that of Sellaphora chistiakovae (Kulikovskiy & Lange–Bertalot) C.E. Wetzel, Ector, Van de Vijver, Compère & D.G. Mann; the linear–elliptical forms of Sellaphora crassulexigua (E. Reichardt) C.E. Wetzel & Ector; and that of Sellaphora nigri (De Notaris) C.E. Wetzel & Ector. But S. chistiakovae has uniseriate to irregularly biseriate striae (
this new Sellaphora species takes its name from the demonym of the Mexican state Querétaro, from where it was collected.
so far only known from the type locality (sampling site 11 in this study) and from stream Laguna de Servín 2 (site 13) located 4 km away from the type location, in acidic waters (pH 5.9–6.2) with low conductivity (77–88 μS/cm).
Based on morphological similarities with other small Sellaphora species, Eolimna rhombica Gerd Moser, Lange–Bertalot & Metzeltin is transferred to Sellaphora:
Eolimna rhombica Gerd Moser, Lange-Bertalot & Metzeltin, 1998, Bibliotheca Diatomologica, vol. 38, p. 156, pl. 23, figs 11–20.
The physical and chemical composition of the water from the sampling sites, as well as QBR values are enlisted in Table
Physical and chemical composition of the water from the sampling sites in the Lerma‒Chapala Basin. Samples were taken in September/October 2013 for sampling campaign I, in February 2014 for the campaign II and in September 2014 for campaign III. T= temperature in °C; Cond= specific conductivity corrected at 25°C (μS/cm); TDS= total dissolved solids as particles per million (ppm); TA= total alkalinity mg/L of CaCO3; v= water velocity (cm/s); DO= dissolved oxygen (mg/L); DOS= dissolved oxygen saturation percentage; SRP = soluble reactive phosphorous (mg/L); NO2‒‒N = nitrite nitrogen (mg/L); NO3‒‒N = nitrate nitrogen (mg/L); NH4+‒N= ammonium nitrogen (mg/L); DIN= dissolved inorganic nitrogen (mg/L); QBR = Riparian Forest Quality Index.
Sampling campaign | Site | T | pH | Cond | TDS | TA | v | DO | DOS | SRP | NO2‒‒N | NO3‒‒N | NH4+‒N | DIN | QBR |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
I Rainy season | 1 | 14.5 | 6.7 | 114 | 45 | 30 | 29 | 6.5 | 84 | 1.09 | 0.005 | 0.010 | 0.005 | 0.02 | 85 |
2 | 16.1 | 7.5 | 417 | 173 | 91 | 33 | 8.2 | 107 | 0.92 | 0.005 | 0.010 | 0.050 | 0.06 | 75 | |
3 | 17.8 | 7.7 | 422 | 182 | 93 | 39 | 7.2 | 98 | 0.59 | 0.004 | 0.015 | 0.025 | 0.04 | 75 | |
4 | 26.3 | 7.4 | 59 | 30 | 12 | 11 | 6.5 | 103 | 0.59 | 0.004 | 0.010 | 0.020 | 0.03 | 55 | |
5 | 25.8 | 7.1 | 100 | 51 | 13 | 24 | 6.8 | 105 | 0.57 | 0.003 | 0.010 | 0.005 | 0.02 | 70 | |
6 | 20.0 | 5.8 | 48 | 21 | 9 | 15 | 6.7 | 94 | 0.49 | 0.002 | 0.010 | 0.000 | 0.01 | 75 | |
7 | 23.5 | 6.1 | 84 | 41 | 23 | 32 | 7.2 | 108 | 0.68 | 0.003 | 0.020 | 0.000 | 0.02 | 50 | |
8 | 25.4 | 6.3 | 70 | 35 | 18 | 38 | 5.9 | 91 | 0.50 | 0.004 | 0.020 | 0.010 | 0.03 | 75 | |
9 | 23.2 | 7.2 | 134 | 65 | 38 | 22 | 9.7 | 146 | 0.67 | 0.009 | 1.200 | 0.055 | 1.26 | 30 | |
10 | 20.7 | 7.6 | 777 | 357 | 369 | 0 | 16.2 | 233 | 0.55 | 0.176 | 8.800 | 0.140 | 9.12 | 35 | |
11 | 15.9 | 6.2 | 88 | 36 | 20 | 24 | 7.1 | 96 | 0.30 | 0.010 | 1.250 | 0.065 | 1.33 | 75 | |
12 | 16.3 | 5.8 | 58 | 24 | 10 | 9 | 7.2 | 98 | 0.36 | 0.005 | 0.750 | 0.000 | 0.76 | 60 | |
13 | 18.5 | 5.9 | 77 | 34 | 9 | 37 | 7.0 | 99 | 0.84 | 0.015 | 0.050 | 0.060 | 0.12 | 70 | |
14 | 16.4 | 6.5 | 96 | 40 | 26 | 38 | 7.3 | 99 | 0.83 | 0.018 | 0.140 | 0.105 | 0.26 | 65 | |
II Dry season | 1 | 13.8 | 7.5 | 432 | 170 | 152 | 18 | 8.3 | 105 | 0.24 | 0.015 | 0.025 | 0.010 | 0.05 | 85 |
2 | 17.4 | 7.5 | 878 | 375 | 168 | 24 | 8.5 | 115 | 0.30 | 0.015 | 0.030 | 0.000 | 0.04 | 75 | |
3 | 18.5 | 7.7 | 857 | 376 | 168 | 13 | 8.7 | 119 | 0.23 | 0.016 | 0.025 | 0.000 | 0.04 | 75 | |
4 | 18.5 | 7.2 | 61 | 27 | 14 | 25 | 8.3 | 114 | 0.25 | 0.015 | 0.020 | 0.000 | 0.04 | 65 | |
5 | 20.5 | 6.8 | 79 | 36 | 16 | 19 | 9.3 | 131 | 0.28 | 0.016 | 0.020 | 0.015 | 0.05 | 70 | |
6 | 17.4 | 5.8 | 42 | 18 | 7 | 16 | 7.9 | 106 | 0.29 | 0.014 | 0.020 | 0.010 | 0.04 | 65 | |
7 | 25.6 | 7.4 | 71 | 36 | 21 | 14 | 9.2 | 144 | 0.26 | 0.016 | 0.030 | 0.035 | 0.08 | 50 | |
8 | 22.7 | 5.5 | 53 | 25 | 14 | 17 | 8.3 | 123 | 0.28 | 0.017 | 0.030 | 0.000 | 0.05 | 65 | |
9 | 14.7 | 6.1 | 283 | 113 | 83 | 0 | 4.2 | 54 | 0.32 | 0.016 | 0.030 | 0.000 | 0.05 | 30 | |
II Dry season | 10 | 18.8 | 7.4 | 969 | 427 | 461 | 0 | 9.7 | 134 | 0.83 | 0.018 | 0.030 | 0.015 | 0.06 | 35 |
11 | 9.9 | 6.4 | 279 | 99 | 91 | 0 | 6.1 | 71 | 0.28 | 0.015 | 0.025 | 0.000 | 0.04 | 75 | |
12 | 13.8 | 5.8 | 94 | 37 | 17 | 0 | 6.2 | 81 | 0.26 | 0.016 | 0.030 | 0.025 | 0.07 | 60 | |
13 | 12.0 | 6.3 | 129 | 48 | 22 | 0 | 6.4 | 80 | 0.26 | 0.017 | 0.030 | 0.015 | 0.06 | 60 | |
14 | 19.5 | 6.9 | 172 | 77 | 65 | 23 | 6.9 | 99 | 0.24 | 0.014 | 0.020 | 0.010 | 0.04 | 75 | |
III Rainy season | 1 | 16.5 | 7.7 | 125 | 53 | 41 | 32 | 5.3 | 71 | 0.38 | 0.007 | 0.015 | 0.040 | 0.06 | 75 |
2 | 16.0 | 7.2 | 306 | 127 | 66 | 43 | 6.1 | 80 | 0.29 | 0.025 | 0.040 | 0.145 | 0.21 | 65 | |
3 | 18.0 | 7.7 | 313 | 136 | 72 | 68 | 6.1 | 82 | 0.29 | 0.017 | 0.025 | 0.115 | 0.16 | 75 | |
4 | 23.9 | 6.8 | 40 | 20 | 10 | 31 | 5.2 | 79 | 0.29 | 0.006 | 0.010 | 0.010 | 0.03 | 65 | |
5 | 26.1 | 7.9 | 65 | 33 | 19 | 27 | 5.5 | 86 | 0.31 | 0.005 | 0.010 | 0.005 | 0.02 | 70 | |
6 | 17.1 | 5.1 | 42 | 18 | 4 | 80 | 5.9 | 79 | 0.36 | 0.006 | 0.010 | 0.010 | 0.03 | 75 | |
7 | 19.9 | 5.3 | 55 | 25 | 16 | 62 | 5.2 | 73 | 0.27 | 0.011 | 0.020 | 0.055 | 0.09 | 50 | |
8 | 22.1 | 5.5 | 48 | 22 | 12 | 51 | 5.1 | 75 | 0.13 | 0.008 | 0.020 | 0.030 | 0.06 | 65 | |
9 | 24.2 | 6.8 | 138 | 68 | 56 | 36 | 5.1 | 77 | 0.50 | 0.005 | 0.010 | 0.015 | 0.03 | 30 | |
10 | 20.8 | 7.1 | 850 | 391 | 430 | 0 | 4.7 | 67 | 0.47 | 0.051 | 0.165 | 0.040 | 0.26 | 35 | |
11 | 15.2 | 6.8 | 91 | 37 | 34 | 18 | 5.0 | 66 | 0.71 | 0.010 | 0.030 | 0.140 | 0.18 | 65 | |
12 | 15.7 | 5.4 | 54 | 22 | 8 | 32 | 5.6 | 75 | 0.43 | 0.005 | 0.005 | 0.020 | 0.03 | 60 | |
13 | 15.8 | 5.9 | 78 | 32 | 15 | 45 | 5.9 | 80 | 0.55 | 0.010 | 0.030 | 0.015 | 0.05 | 70 | |
14 | 17.6 | 6.5 | 99 | 42 | 32 | 50 | 5.3 | 73 | 0.46 | 0.008 | 0.010 | 0.020 | 0.04 | 65 |
On the CCA biplot three groups of samples were visualized (Fig.
Diversity indices and physical and chemical composition of the three groups visualized after the CCA. The mean value and standard deviation is provided for each variable. S= species richness; H’= Shannon-Wiener diversity index; J’ = Pielou evenness index. For abbreviations and units of the physical and chemical variables refer to Table
Group 1 | Group 2 | Group 3 | |
---|---|---|---|
S | 16±5 | 21±6 | 17±4 |
H’ | 2.43±0.33 | 2.75±0.40 | 2.53±0.30 |
J’ | 0.61±0.12 | 0.63±0.16 | 0.56±0.17 |
T | 18.2 ± 3.5 | 21 ± 4.8 | 16 ± 2.9 |
pH | 5.9 ± 0.5 | 7 ± 0.5 | 7.3 ± 0.5 |
Cond | 70 ± 24 | 104 ± 59 | 453 ± 249 |
TDS | 30 ± 9 | 47 ± 23 | 191 ± 110 |
TA | 14 ± 7 | 30 ± 20 | 107 ± 43 |
v | 31 ± 23 | 24 ± 11 | 29 ± 20 |
DO | 6.6 ± 1.2 | 6.6 ± 1.7 | 7.3 ± 1.1 |
DOS | 91 ± 18 | 95 ± 27 | 97 ± 16 |
SRP | 0.38 ± 0.17 | 0.5 ± 0.25 | 0.37 ± 0.23 |
NO2‒‒N | 0.010 ± 0.005 | 0.008 ± 0.005 | 0.014 ± 0.006 |
NO3‒‒N | 0.14 ± 0.35 | 0.11 ± 0.32 | 0.02 ± 0.01 |
NH4+‒N | 0.022 ± 0.021 | 0.031 ± 0.043 | 0.039 ± 0.054 |
DIN | 0.18 ± 0.35 | 0.15 ± 0.33 | 0.08 ± 0.06 |
QBR | 66 ± 7 | 58 ± 18 | 75 ± 5 |
Indicator taxa from the three groups visualized after the CCA. The indicator value of the taxa is accompanied by their relative abundance (RA) and relative frequency (RF) values. Significant IndVals (p< 0.05) are indicated in bold.
Taxa | Group 1 | Group 2 | Group 3 | |||||||
---|---|---|---|---|---|---|---|---|---|---|
RA | RF | IndVal | RA | RF | IndVal | RA | RF | IndVal | ||
1 | Achnanthidium sp. 1 | 99 | 69 | 68 | 0 | 7 | 2 | 1 | 11 | 0 |
2 | Achnanthidium aff. catenatum | 77 | 63 | 48 | 22 | 29 | 6 | 1 | 11 | 0 |
3 | Brachysira altepetlensis | 96 | 44 | 42 | 4 | 36 | 1 | 0 | 0 | 0 |
4 | Eunotia sp. 3 | 99 | 31 | 31 | 1 | 7 | 0 | 0 | 0 | 0 |
5 | Fragilaria austriaca | 71 | 56 | 40 | 29 | 7 | 2 | 0 | 0 | 0 |
6 | Frustulia crassinervia | 100 | 31 | 31 | 0 | 0 | 0 | 0 | 0 | 0 |
7 | Gomphonema exilissimum | 64 | 75 | 47 | 31 | 43 | 13 | 5 | 22 | 1 |
8 | Craticula molestiformis | 16 | 31 | 5 | 74 | 79 | 58 | 10 | 33 | 3 |
9 | Craticula subminuscula | 3 | 6 | 0 | 84 | 57 | 48 | 13 | 56 | 7 |
10 | Cyclotella meneghiniana | 0 | 0 | 0 | 100 | 21 | 21 | 0 | 0 | 0 |
11 | Encyonema minutum | 11 | 13 | 1 | 85 | 64 | 54 | 4 | 11 | 0 |
12 | Eolimna sp. 1 | 12 | 13 | 2 | 88 | 36 | 31 | 0 | 0 | 0 |
13 | Fistulifera saprophila | 4 | 6 | 0 | 79 | 57 | 45 | 17 | 22 | 4 |
14 | Gomphonema aff. sarcophagus | 3 | 13 | 0 | 96 | 43 | 41 | 1 | 11 | 0 |
15 | Mayamaea permitis | 9 | 31 | 3 | 69 | 86 | 59 | 22 | 67 | 15 |
16 | Navicula rostellata | 2 | 6 | 0 | 87 | 57 | 50 | 11 | 11 | 1 |
17 | Nitzschia gracilis | 0 | 0 | 0 | 100 | 29 | 29 | 0 | 0 | 0 |
18 | Nitzschia palea var. debilis | 8 | 25 | 2 | 91 | 50 | 45 | 1 | 11 | 0 |
19 | Nitzschia palea var. tenuirostris | 9 | 38 | 4 | 91 | 64 | 58 | 0 | 0 | 0 |
20 | Amphora pediculus | 0 | 0 | 0 | 3 | 7 | 0 | 97 | 44 | 43 |
21 | Cocconeis sp. 2 | 0 | 0 | 0 | 2 | 14 | 0 | 98 | 67 | 66 |
22 | Cocconeis pediculus | 0 | 0 | 0 | 0 | 0 | 0 | 100 | 22 | 22 |
23 | Epithemia adnata | 0 | 0 | 0 | 0 | 0 | 0 | 100 | 33 | 33 |
24 | Epithemia sorex | 0 | 0 | 0 | 4 | 7 | 0 | 96 | 44 | 43 |
25 | Gomphonema pumilum | 0 | 6 | 0 | 28 | 21 | 6 | 72 | 67 | 48 |
26 | Gomphonema minusculum | 0 | 0 | 0 | 0 | 0 | 0 | 100 | 33 | 33 |
27 | Halamphora montana | 0 | 0 | 0 | 16 | 14 | 2 | 84 | 56 | 46 |
28 | Navicula reichardtiana | 0 | 0 | 0 | 0 | 0 | 0 | 100 | 56 | 56 |
29 | Navicula gregaria | 0 | 0 | 0 | 13 | 14 | 2 | 87 | 56 | 48 |
30 | Nitzschia inconspicua | 1 | 13 | 0 | 0 | 0 | 0 | 99 | 56 | 55 |
31 | Planothidium victori | 0 | 6 | 0 | 12 | 29 | 3 | 88 | 78 | 69 |
32 | Reimeria sinuata | 0 | 0 | 0 | 0 | 0 | 0 | 100 | 67 | 67 |
33 | Sellaphora atomoides | 10 | 31 | 3 | 20 | 29 | 6 | 70 | 78 | 54 |
The second group, found on the upper middle side of the plot contains samples with circumneutral waters, low in specific conductivity and the highest mean temperature and soluble reactive phosphorous concentrations. The mean number of species was 17 (Table
Samples from the third group correspond to well mineralized waters with the highest pH values on average, and also the lowest nitrogen concentrations. The sites in this group scored the higher values for the QBR on average. The mean species richness was 17 (Table
The three sampling campaigns of eight sites are within the same groups of the CCA plot (Fig.
Canonical Correspondence Analysis (CCA) ordination plot. Distribution of sampling sites based on diatom abundance data in relation to statistically significant environmental variables. Three groups of samples are depicted within ovals. For visualization purposes, only species with significant IndVals (p< 0.05) are included in the plot. Black squares correspond to species; numbers within the black squares refer to taxa names in Table
In contrast, in 5 sites there were changes of the samples among the three groups. For site 7, one sample from the rainy season is together with the sample from the dry season in group 2, whereas the other rainy season sample is in group 1. The three samples of sites 11 and 14 are one in each of the three different groups observed in the CCA plot (Fig.
Species composition and taxonomy. The species richness found, 274 taxa, was relatively high compared to previous studies on the basin: 209 taxa were found by Abarca-Mejía (2010) from 59 samples analyzed from three substrates; 178 taxa by Segura-García (2012) from 66 epilithon samples analyzed; 173 taxa by
The resulting high diversity found in our study can be explained by the detail at which samples were analyzed under both LM and SEM, which resulted in the separation of several morphodemes instead of lumping them into species complexes. The fact that a third of the flora, 94 morphodemes, could not be assigned to described species is not surprising due to the nature of the samples, coming from within the tropics, for which no extensive identification floras have been produced yet, compared to northern temperate regions. Furthermore, it is encouraging to have such a big number of unidentified morphodemes, because they could be helpful in the quest of unravelling if the freshwater diatom floras of Mexico have certain biogeographical affinities, as it would be expected due to the fact that the country lies within the so called Mexican Transition Zone, a complex area in which Neotropical and Nearctic biotic elements converge (
In most of the freshwater diatom floras generated for Mexico, there seems to be a high intrinsic cosmopolitism, with a large proportion of taxa from north temperate waters. Nowadays it seems unlikely to find large amounts of shared species with north temperate regions due to mounting evidence that even microorganisms like diatoms have biogeography (
On the other hand, finding a large proportion of cosmopolitan taxa should not be that surprising since isolated areas such the Andes have shown to have as much as 42% cosmopolitan taxa, but also a considerable proportion of newly described taxa (9.5%) plus seemingly endemic regionals (
Another hypothesis that could explain the high species richness found in our study is the heterogeneity of environmental conditions of the study areas: a) the sampling campaigns were done in both rainy and dry seasons; b) varied geomorphologies of the streams from headwaters to the midlands and also from the plains, resulting in different riparian communities, reflected in the QBR index values obtained; c) streams ranging from perennial to temporary; d) heterogeneity of physical and chemical composition of the water. Environmental heterogeneity of habitats has been proposed in other studies as a determinant of species richness and distribution (Petrov and Nevrova, 2014).
An additional indicator of the heterogeneity of the studied sites is the fact that no single taxon was found in all samples, which contrast with previous findings on the Lerma-Chapala Basin, where the following taxa were found in all sites and seasons Craticula subminuscula, Gomphonema parvulum, Navicula veneta, Nitzschia amphibia, N. capitellata, N. palea and Sellaphora pupula (Segura-García 2012,
When looking at the macroalgae of the studied streams, it is worth mentioning that sampling sites 11–14 host red algae like Batrachospermum gelatinosum (Linnaeus) De Candolle, Paralemanea mexicana (Kützing) Vis & Sheath and Sirodotia suecica Kylin, species typically found in headwater mountain streams of temperate regions (
Diatom communities. The different diatom compositions found in the Lerma-Chapala Basin were mainly driven by specific conductivity and pH. Temperature, soluble reactive phosphorous and the Riparian Forest Quality Index were statistically significant but when analyzing the mean values and their standard deviations, the border between each group was not distinct.
For both specific conductivity and pH, the lowest values were recorded in the streams located in the headwaters, which is logical since water there has not gone deep into the geological matrix and therefore is not well mineralized. On the other hand, the higher values for both specific conductivity and pH were recorded on the midland and plains, where the streams received more contributions of well mineralized waters, for example from springs. There is no better example of this than what was recorded at sampling site 10, where pH values were high and specific conductivity values were the highest recorded for this study. This phenomenon is shown by
No clear seasonal effect (rainy and dry seasons) was observed on the three groups of sampling sites observed after the CCA because in every group there are samples from both rainy seasons together with the dry season. Even though there were seasonal variations in physical and chemical factors such as specific conductivity, pH and water velocity, the community composition (species richness and abundance) apparently did not respond to those seasonal fluctuations (
Regarding the characteristic species of the three groups visualized after the CCA, there are several similarities with previous reports on the ecological preferences of these taxa. Some species were found in all three groups but with varying relative abundances, so only those with the largest abundances were taken as the representative for a group.
For group 1, species from genera such as Brachysira, Eunotia and Frustulia are well regarded as characteristic from acidic and electrolyte poor waters (
The representative species from group 2 were taxa well regarded as indicators of circumneutral and eutrophic waters with varying degrees of perturbation such as Craticula molestiformis, Mayamaea permitis and N. palea var. tenuirostris (
Regarding group 3, its characteristic species also confirm the meso-eutrophic, mineralized and alkaliphilous nature of its waters, with taxa such a Cocconeis sp. 2 (C. placentula Ehrenberg sensu lato based only on LM observations), Navicula reichardtiana, Nitzschia inconspicua, Planothidium victori (formerly within Planothidium frequentissimum (Lange-Bertalot) Lange-Bertalot sensu lato), Reimeria sinuata and Sellaphora atomoides (former Eolimna tantula (Hustedt) Lange-Bertalot) (
This work contributed to increase the knowledge of the diatom flora from the Lerma-Chapala Basin, Central Mexico, providing a diversity baseline and evidence of its distinctiveness from the floras of other areas in Mexico, with a large proportion of unidentified taxa to be described as new. The studied diatom communities are subjected to moderate environmental disturbance, representing a transition between warm and cold waters, with ionic composition, temperature and the quality of the riparian forest being the main factors defining the community composition observed. The next approach to investigate the diatom diversity of the region would be by means of environmental DNA metabarcoding in combination with the development of a taxonomic reference database, in order to highlight the complementary aspect of classical taxonomy and eDNA metabarcoding, i.e. the importance of the reciprocal illumination (
The work of DM was funded by the Mexican Government through doctoral grants from CONACYT, CONCYTEQ and DGRI–SEP. Samples were taken under permit CONAPESCA PPF/DGOPA–149/14. The Deutsche Forschungsgemeinschaft is thanked for Grant INST 130/839–1 FUGG concerning SEM funding. We gratefully acknowledge Carlos E. Wetzel who provided advice on the taxonomy of small Sellaphora species. Loren Bahls kindly adviced on the identification of some Stauroneis species. Wolf–Henning Kusber is thanked for his advice on nomenclature. Monika Lüchow and Kim Govers kindly assisted at the SEM. We thank Verónica Aguilar Zamora for creating the map. Martin Jagodzinski kindly advised on figure plate preparation. Mahinda Martínez is thanked for her assistance with vascular plant identifications.
Diatom taxa list from the Lerma-Chapala Basin, Central Mexico and identification references
Data type: species data
Explanation note: Diatom taxa list from the Lerma‒Chapala Basin, Central Mexico