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Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e2025233, enero-diciembre 2025 (Publicado Set. 18, 2025)
Spatial variability and trophic structure of aquatic macroinvertebrate
communities in the semi-arid Quilca-Chili basin, Peru
Pastor Coayla-Peñaloza1*; https://orcid.org/0000-0002-2317-7154
André Cheneaux-Díaz1; https://orcid.org/0000-0002-7148-0174
Ingrid Caceres-Benavente1; https://orcid.org/0009-0007-7098-7479
Mauro Caceres-Olcon1; https://orcid.org/0009-0005-6728-0443
Maritza Maquera-Ccahua1; https://orcid.org/0009-0008-9343-4815
Fernando Cobo2; https://orcid.org/0000-0001-5684-266X
Cristina Damborenea3; https://orcid.org/0000-0002-6411-1282
1. Universidad Nacional de San Agustín de Arequipa, Av. Alcides Carrión s/n, Arequipa, Perú; pcoaylap@unsa.edu.pe*
(Correspondence), acheneaux@unsa.edu.pe, icaceresbe@unsa.edu.pe, mcacereso@unsa.edu.pe, mmaquerac@unsa.
edu.pe
2. Departamento de Zoología, Genética y Antropología Física, Facultad de Biología, Universidad de Santiago de
Compostela, 15 782 Santiago de Compostela, España; ernando.cobo@usc.es
3. Consejo Nacional de Investigaciones Científicas y Técnicas, División de Zoología de Invertebrados, Facultad de
Ciencias Naturales y Museo (FCNyM), Universidad Nacional de La Plata, Paseo del Bosque s/n -B1900FWA, La Plata,
Argentina; cdambor@fcnym.unlp.edu.ar
Received 08-IV-2025. Corrected 16-VI-2025. Accepted 02-IX-2025.
ABSTRACT
Introduction: The trophic structure of macroinvertebrate communities is of particular interest for understand-
ing the functioning of the river ecosystems.
Objective: To determine the community structure and functional feeding groups of aquatic macroinvertebrates
in the Quilca-Chili basin.
Methods: Two sampling campaigns were conducted at 26 stations, distributed across six sectors, from June to
October 2022. The community structure was analyzed based on basic ecological parameters, including taxonom-
ic richness, dominance, evenness, and diversity. Spatial variability was assessed through a similarity percentage
analysis and non-metric multidimensional scaling using the Bray-Curtis distance index. The relationship with
physicochemical variables was determined through canonical correlation analysis.
Results: A total of 51 families were identified and assigned to functional feeding groups: predator, shredder,
collector-gatherer, scraper, and filterer. The highest and lowest diversity was observed in the Sihuas sector and
the Chili and Lluta sectors, respectively. Differences in community structure indices were found between the six
sectors of the basin. The most abundant functional feeding groups were scrapers, while shredders and predators
were the least abundant.
Conclusion: The spatial distribution reflects the complexity and variability among physicochemical parameters
and functional feeding groups in this basin.
Key words: functional feeding groups; macroinvertebrates; desert; high Andean; rivers.
https://doi.org/10.15517/pw9gjn97
AQUATIC ECOLOGY
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INTRODUCTION
The study of the trophic structure of mac-
roinvertebrate communities is of particular
interest for understanding the functioning of
river ecosystems. By assigning these organisms
to different functional feeding groups, accord-
ing to the general classification established by
Cummins (1973), we can simplify the taxo-
nomic complexity of the community for each
sector of the basin’s watercourses and deter-
mine the basic functioning in relation to the
relative importance of exogenous and endog-
enous materials. This also helps us understand
potential disruptions in the normal flow of
energy caused by external inputs (Cummins,
1995; Statzner et al., 2001; Vannote et al., 1980).
In general, the trophic strategies and dis-
tribution patterns of macroinvertebrate groups
are well known in temperate regions of the
globe (Cummins et al., 2008). However, in
semi-arid and arid regions, they have been
studied little, despite their importance for
understanding the behavior of climate variabil-
ity (Vidal-Abarca et al., 2004).
The arid and semi-arid regions of Peru are
characterized by unique geological, geographic,
and climatic conditions, subject to highly vari-
able large-scale climatic events such as “El Niño”
and “La Niña” (Arana-Maestre et al., 2021). The
extreme spatial and temporal variability of cli-
matic conditions in the region results in scarce
rainfall that is highly variable in both space and
time, which can lead to intense floods and per-
sistent droughts in the rivers. The Quilca-Chili
basin is located in the western part of the Andes
Mountain range and is the most important in
the Arequipa Region of Peru (Autoridad Nacio-
nal del Agua [ANA], 2013).
The spatial and temporal heterogeneity of
river ecosystems in arid and semi-arid regions
suggests that there may be significant differ-
ences in the organization of river ecosystems,
presenting a scientific challenge to understand
the keys to their structure and functioning
(Gómez et al., 2001; Likens, 1999; Vidal-Abarca
et al., 2004). The aim of this study was to deter-
mine the community structure and functional
feeding groups of aquatic macroinvertebrates
in the Quilca-Chili basin, with the aim of
RESUMEN
Variabilidad espacial y estructura trófica de las comunidades de macroinvertebrados acuáticos
de la cuenca semiárida Quilca-Chili, Perú
Introducción: La estructura trófica de las comunidades de macroinvertebrados tiene un interés especial para
comprender el funcionamiento del ecosistema fluvial.
Objetivo: Determinar la estructura de la comunidad y los grupos funcionales de alimentación de los macroinver-
tebrados acuáticos de la cuenca Quilca-Chili.
Métodos: Se realizaron dos muestreos en 26 estaciones, distribuidas en seis sectores, de junio a octubre del 2022.
La estructura de la comunidad se analizó según los parámetros ecológicos básicos de riqueza taxonómica, domi-
nancia, equidad y diversidad. La variabilidad espacial se valoró en función de un análisis de similitud porcentual
y otro mediante el método no paramétrico de escalamiento multidimensional empleando el índice de distancia
de Bray-Curtis. La relación con las variables fisicoquímicas se determinó con un análisis de correlación canónica.
Resultados: Se reconocieron 51 familias que se asignaron a los grupos funcionales de alimentación depredador,
desmenuzador, recolector de depósito, raspador y filtrador. La mayor y menor diversidad se presentó en el sector
de Sihuas y en los sectores de Chili y Lluta respectivamente. Existieron diferencias de los índices de estructura
comunitaria entre los seis sectores de la cuenca. El grupo funcional de alimentación más abundante fue el de los
raspadores y los menos abundantes desmenuzadores y depredadores.
Conclusión: La distribución espacial refleja la complejidad y variabilidad entre los parámetros fisicoquímicos y
grupos funcionales de alimentación de esta cuenca.
Palabras clave: grupos funcionales de alimentación; macroinvertebrados; desierto; alto andino; ríos.
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understanding the role of these organisms in
rivers within arid ecosystems of Peru. This
valuable information will contribute to improv-
ing the integrated management of the basin.
MATERIAL AND METHODS
Study area: The Quilca-Chili basin admin-
istratively comprises the provinces of Areq-
uipa, Caylloma, and Camaná in the Arequipa
Region. It is located on the Southwestern coast
of Peru, between Lat. 15º37’50’’ S & 16º47’10’’
S and Long. 70º49’15’’ W & 72º26’35’’ W. The
basin covers an area of 13 457.01 km², repre-
senting 21.24 % of the total area of the region
(63 418.34 km²) (ANA, 2023). The Quilca-
Chili basin (Fig. 1) has most of its extension
in the Province of Arequipa. Geographically,
it is characterized by deep, rugged terrain with
moderate slopes and narrow canyons, where
the land shows a continuous and rapid descent
from the summits toward the Pacific Ocean
(ANA, 2023).
The main course of the basin takes differ-
ent names depending on the sector considered
(ANA, 2023). From its source in the districts of
San Juan de Tarucani (Arequipa Province) and
San Antonio de Chuca (Caylloma Province) to
the confluence with the Blanco River, it is called
the Sumbay River, with a length of 133.7 km.
From the confluence with the Blanco River to
the confluence with the Yura River in Palca, it is
called the Chili River, with a length of 88.20 km.
After this confluence, the Chili River changes
its name to the Vítor River, with a length of
80.70 km. Further downstream, it receives the
waters of the Sihuas River, and again changes
its name to the Quilca River, with a length of
23.50 km, which empties into the Pacific Ocean
(Carpio-Fernández et al., 2022).
Along this basin, 26 sampling stations were
established (Fig. 1). Three stations were located
in the Sumbay sector (E24, E25, E26), semi-
arid, higher altitude zone, four stations in the
Chili sector (E17, E18, E19, E20), which crosses
the city of Arequipa, six stations in the Vítor
sector (E01, E02, E03, E04, E05, E06), seven
stations in the Sihuas sector (E07, E08, E09,
E10, E11, E12, E13), three in the Lluta sector
(E21, E22, E23), arid zone, and three stations in
Fig. 1. Location of sampling sectors in the Quilca-Chili Basin of the Arequipa region, Perú.
4Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e2025233, enero-diciembre 2025 (Publicado Set. 18, 2025)
the Quilca sector (E14, E15, E16), lower part of
the river. The sampling method was stratified
by sectors, and within the stations, a targeted
random sampling was conducted (Maroñas et
al., 2010), considering the location and 0.
Sampling and data processing: Biological
sampling and physicochemical data collection
were conducted between June and October
2022. At each sampling station, three replicates
were taken using a Surber net (0.09 m²) with
a 500 µm mesh size. The samples were fixed
with 4 % formaldehyde and transported to the
laboratory for separation and identification
under a stereomicroscope, using the taxonomic
keys and descriptions of Cummins et al. (2008);
Domínguez & Fernández (2009); Huamantinco
& Ortiz (2010); Thorp & Rogers (2014). Simul-
taneously, physicochemical parameters were
measured at each sampling site using a Hanna
HI 9 829 multiparameter probe. In situ mea-
surements included water temperature (T °),
dissolved oxygen (DO), electrical conductivity
(EC), pH, salinity (Sal), total dissolved solids
(TDS), and turbidity (Turb). Water velocity
and depth were measured using a Global Water
FP111 flowmeter to calculate the flow rate (Q)
in cubic meters per second.
Macroinvertebrates were grouped into five
functional feeding groups: collector-gatherers
(DF), predators (P), shredders (SH), scrapers
(SC), and filterers (FF), according to Cum-
mins (1973); Baptista et al. (2006); Tomanova
et al. (2006); Domínguez & Fernández (2009);
Chará-Serna et al. (2010); Rodríguez-Barrios
et al. (2011); and Chará-Serna et al. (2012).
For specimens with poor information for the
Neotropics areas, they were assigned to a func-
tional feeding group based on the classifica-
tion proposed by Cummins et al. (2008) for
North America.
Data analysis: Average abundances per
taxon were used to normalize the data and
standardize the variance. The number of indi-
viduals per taxon was transformed using the
square root to reduce the effects of domi-
nant taxa, allowing intermediate and rare taxa
to contribute to potential differences between
sampling stations before conducting tests. To
determine the differences in community com-
position between sampling sectors, an analysis
of similarity (ANOSIM) was performed (p <
0.05), creating a matrix using the Bray-Curtis
index, which was complemented by a similarity
percentage analysis (SIMPER) to identify the
taxa that most influence community patterns.
To analyze spatial distribution patterns among
the sampling stations, the non-parametric Mul-
tidimensional Scaling (nMDS) method was
applied. These analyses were conducted using
the statistical software PRIMER v7 (Clarke &
Gorley, 2006).
The evaluation of community structure
was carried out using ecological indices ana-
lyzed with the software PAST 4.03 (Hammer et
al., 2001). Macroinvertebrate abundance data
were not standardized before analysis. The
indices included species richness (S), Pielou’s
evenness (J’), Shannon-Wiener diversity index
(H’), Simpson’s dominance index (D), and were
subjected to an ANOVA test to identify signifi-
cant differences (p < 0.05) between sectors.
Canonical Correspondence Analysis
(CCA) was applied to establish the relationship
between physicochemical parameters and func-
tional feeding groups. Previously, functional
feeding groups data were transformed using the
square root. This process was carried out using
the software PAST 4.03 (Hammer et al., 2001).
The relative abundance of functional feed-
ing groups was also subjected to an ANOVA
test to identify significant differences between
sectors (p < 0.05).
RESULTS
Aquatic macroinvertebrates: A total of
20 450 aquatic macroinvertebrate individuals
belonging to 79 taxa, distributed across five
phylum, 21 orders, and 51 families were collect-
ed (Table 1). The highest diversity and abun-
dance corresponded to the class Insecta, with
the orders Diptera (37.97 %), Coleoptera (13.92
%), Hemiptera (6.33 %), Trichoptera (6.33 %),
Ephemeroptera (6.33 %), and Odonata (5.06 %)
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Table 1
Average abundance of aquatic macroinvertebrates by sampling sector in the Quilca-Chili watershed.
Orden Familia Taxa GF Vitor Sihuas Quilca Chili Lluta Sumbay
Tricladida Dugesiidae Girardia P 28.5 2.83 0 119.33 3.33 12
Triplonchida TripylidaeTripyla P 1.67 1.67 0 0.67 1 6
Rhynchobdellida Glossiphoniidae Helobdella SH 1.83 3.5 0 36 0 0.33
Arhynchobdellida Erpobdellidae Nephelopsis P10000 0
Haplotaxida Naididae Pristina CG 9 4.67 4 3 0.67 15
Lumbriculida Lumbriculidae Lumbriculus CG 3.17 11.67 1.83 72 117 20.67
Basommatophora Planorbidae Acrorbis S20110 1
Physidae Physa S 43.17 195 2.33 22.33 0 2
Littorinimorpha Hydrobiidae Heleobia S 10.33 6 2.17 3 983.67 2.33 1.33
Veneroida Sphaeriidae Pisidium F 0 0 0 0.33 0 0
Amphipoda Hyalellidae Hyalella CG 4.5 5.5 3 4.67 330 33.33
Podocopida Cyprididae Isocypris F 23 197.83 3.33 4.667 5 2.33
SarcoptiformesLimnozetidae Limnozetes P 1.17 1 0 0 0 0
Trombidiformes LimnesiidaeTyrrellia P 32.83 148.33 2 5.33 1 19.33
Hygrobatoidea Hygrobatoidea1 P 0 0.83 0 0 0 0
Ephemeroptera Leptohyphidae Thicorythodes SH 0.17 0.17 0 0 0 0
Baetidae Callibaetis CG 0.83 1.17 1.17 0 0 0
Cryptonympha CG 23.5 211.33 1.17 115.67 1 638.67 22
Camelobaetidius CG 2.33 509.17 0.5 0 0 0
Oligoneuriidae Lachlania F 0 8.5 0 0 0 0
Plecoptera Gripopterygidae Falklandoperla SH 0 0.67 0 0 5.33 74.33
Notoperla CG 00001 3
Odonata Aeshnidae Aeshna P 3 4.67 1 0 2 1
Libellulidae Sympetrum P 1.17 4.83 0 0 0 1
Coenagrionidae Argia P 3.17 6.17 1 0 0 0
Ischnura P 2.17 5 2.5 0 0 0
Trichoptera Glossosomatidae Glossosomatidae1 S 0 0.17 0 0 0 0
Hydrobiosidae Cailloma P 0 6 0 1 5.67 1.33
Hydroptilidae Metrichia S 223.33 442.17 7.17 411 349.33 492
Neotrichia S 0 4.17 0 0 0 0
Leptoceridae Nectopsyche SH 2.33 0.33 0 1.67 0 0
Leptoceridae1 CG 10000 0
Lepidoptera Crambidae Crambidae1 SH 10001 0
Hemiptera Mesoveliidae Mesovelia P01000 0
Veliidae Microvelia P 2.67 4.67 2.17 1.33 0 0.67
Rhagovelia P12000 0
Notonectidae Notonecta P01000 0
Corixidae Trichocorixa P 0 1 0 0 0 4.67
Coleoptera Dytiscidae Meridiorhantus P 0 1.17 1 0 0 0
Leuronectes P 0 3.5 0 0 0.33 0
Hydrophilidae Tropisternus SH 1 4.67 2 1 0 1
Staphylinidae Thinobius P 2.17 2.17 1 0 0.33 0
Elmidae Austrelmis P 53.5 166 0.5 1 87 22
Microcylloepus S 829.33 679.83 35.83 1.67 7 33.33
Heterelmis S01000 0
6Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e2025233, enero-diciembre 2025 (Publicado Set. 18, 2025)
of the total taxa. Twenty-one taxa were shared
among the studied sectors of the basin, with the
most abundant families being Chironomidae
(26.49 %), Cochliopidae (19.59 %), Simuliidae
(12.36 %), Baetidae (12.36 %), Hydroptilidae
(9.43 %), and Elmidae (9.38 %) of the total
number of individuals. The most abundant
taxa were Polypedilum in the Quilca and Sihuas
sectors; meanwhile Microcylloepus, Heleobia,
Simulium, Cryptonympha, and Metrichia in the
Vítor, Chili, Lluta, and Sumbay sectors, respec-
tively. SIMPER analysis indicated a global dis-
similarity of 60.7 % between all sectors of the
basin regarding macroinvertebrate composi-
tion, with 16 macroinvertebrate taxa being the
most influential in this dissimilarity (Table 2).
The nMDS analysis showed four groups
with a 40 % similarity and a stress factor of 0.14
(Fig. 2). The first group consisted of stations
in the Quilca sector, located in the lower part
Orden Familia Taxa GF Vitor Sihuas Quilca Chili Lluta Sumbay
Luchoelmis S00100 0
Limnichidae Limnichidae1 CG 03300 0
Chrysomelidae Chrysomelidae1 S 0 0.17 0 0 0 0
Curculionidae Curculionidae1 SH 01000 0
Diptera Blephariceridae Paltostoma S 1.17 12.17 0 5.67 0.33 0
Psychodidae Pericoma CG 1 4.17 3 1 1 1
Culicidae Anopheles F02100 0
Aedes CG 11000 0
Simuliidae Simulium F 29.67 473.17 0 836 1 142.33 46.33
Ceratopogonidae Culicoides CG 2.33 20 1.17 1.33 1.33 4.33
Bezzia P 0 15 0 0 5.33 0
Forcipomyia P 3 0 0.33 0 0 0
Chironomidae Podonomus S 0 2 0 0 0.67 5.33
Tanytarsus F 34.17 70 1.67 968.67 3.67 8.33
Aedokritus CG 44.17 127.17 5.5 88.67 2.67 7.67
Polypedilum SH 688.5 147.5 111 55 19.67 7.33
Larsia P 5.83 9.5 0 0 9.33 1.33
Alotanypus P 16 36 0.5 3.67 3.33 2.67
Onconeura F 91.33 251.67 12.83 339.33 1 0
Cricotopus CG 60 183.67 1.67 493 194.67 263.33
Paratrichocladius CG 51 44.83 10.17 304 537 90
Corynoneura F00010 0
Tabanidae Tabanus F 0 3.67 0 0 1 2.67
Stratiomyidae Stratiomys CG 22000 0
Nemotelus CG 1 1.33 0 0 0 0
Dolichopodidae Dolichopodidae1 P 4.17 31.83 1.33 26.33 4 2.67
Dolichopodidae2 P 1 2.17 0 0 1 0
Dolichopodidae3 P 1 1.5 1 0 0 0.33
Tipulidae Holorusia CG 02001 0
Empididae Neoplasta P 3.83 79.83 1.17 2.67 5.33 0.67
Ephydridae Brachydeutera CG 0 1.33 0 0 0 2.67
Ephydra CG 1 2 0 0 4.67 2
Scatella CG 13100 1
Muscidae Limnophora P 6.17 14.83 1 5.33 10.33 2
Functional feeding group al (FG): P = Predator; SH= Shredder; CG= Collector-gatherer; S= Scraper; F= Filterer.
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of the basin (E14, E15, E16), where the most
abundant taxa were Polypedilum (47.23 %),
Microcylloepus (15.25 %), and Onconeura (5.46
%). The second group included stations from
the Vítor and Sihuas sectors (E01 to E13) and
two stations from the Lluta and Sumbay sectors
(E23, E25), where the most abundant taxa were
Simulium (16.88 %), Cryptonympha (16.17 %),
and Microcylloepus (15.34 %). The third group
comprised stations from the Chili sector (E17,
Table 2
SIMPER Analysis of benthic macroinvertebrates in comparing the six sectors.
Sector Overall average dissimilarity (%) Taxa Contribution (%) Cumulate (%)
Vitor 60.71% Simulium 6.95 6.95
Sihuas Heleobia 6.84 13.79
Quilca Microcylloepus 6.31 20.09
Chili Cryptonympha 6.01 26.10
Lluta Metrichia 5.78 31.88
Sumbay Cricotopus 5.17 37.05
Polypedilum 4.81 41.87
Paratrichocladius 4.81 46.68
Tanytarsus 4.07 50.75
Onconeura 3.88 54.63
Camelobaetidius 3.20 57.83
Austrelmis 2.67 60.50
Hyalella 2.58 63.08
Physa 2.41 65.49
Lumbriculus 2.34 67.83
Aedokritus 2.28 70.12
Fig. 2. nMDS of aquatic macroinvertebrate abundances by sampling station.
8Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e2025233, enero-diciembre 2025 (Publicado Set. 18, 2025)
E18, E19), where the most abundant taxa were
Heleobia (55.13 %), Tanytarsus (13.40 %), and
Simulium (11.48 %). The fourth group was
formed by the station located upstream from
the city of Arequipa, in the Chili sector (E20),
and stations from the Lluta and Sumbay sectors
(E21, E22, E24, E26), which are at higher alti-
tudes. The most abundant taxa in these stations
were Metrichia (31.97 %), Paratrichocladius
(22.71 %), and Cryptonympha (13.24 %). ANO-
SIM indicated that these groups were statisti-
cally significant (R = 0.7621, p = 0.0001).
Species richness (40 taxa) (Fig. 3A),
Pielou’s evenness (J’ = 0.63) and Shannon-
Wiener diversity index values (H’ = 2.32) (Fig.
3B, Fig. 3C) were highest in the Sihuas sector.
Dominance index values (Fig. 3D) were low
across all sectors (D < 0.5). Significant differ-
ences were found in species richness and diver-
sity, across the river sectors (Table 3).
Functional feeding groups: Of the 79
identified taxa, 29 were predators, 21 collector-
gatherers, 12 scrapers, nine filterers, and eight
shredders. Scrapers were the most abundant
Fig. 3. Macroinvertebrate community structure in the Quilca-Chili watershed. A. Number of taxa (S). B. Pielou’s equity (J’).
C. Shannon-Wiener diversity (H’). D. Simpson dominance (D).
Table 3
ANOVA test for community structure indices among zones
of the watershed. Significant values are highlighted in bold.
DF Fp
Richness (S) 5 7.548 0.0004001
Shannon Diversity Index (H’) 5 4.607 0.0058610
Pielou’s Evenness Index (J’) 5 2.299 0.0835900
Simpson’s Dominance Index (D) 5 2.199 0.0949500
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functional feeding group, accounting for 38 %
(7 821 individuals), followed by collector-gath-
erers with 28 % (5 764) and filterers with 22 %
(4 567). Shredders represented 6 % of the total
(1 179 individuals), while predators accounted
for 6 % as well (1 119 individuals).
Fig. 4 shows the variation in the relative
abundance of aquatic macroinvertebrates by
functional feeding group. Collector-gatherers
increase upstream, while predators decrease.
Shredders increase downstream, being under-
represented in the Chili, Lluta, and Sumbay
sectors. Filterers had the highest number of
individuals in the middle part of the basin,
especially in the Sihuas and Chili sectors. The
most abundant filterers families were Simuli-
idae (12.36 %), Chironomidae (8.72 %), and
Cyprididae (1.15 %). Scrapers showed fluctuat-
ing values throughout the basin (3.15 to 79.39
%), with the most abundant representatives
being the families Cochliopidae (19.59 %),
Hydroptilidae (9.43 %), and Elmidae (7.77 %).
Significant differences were found between the
abundance of functional feeding groups (F =
3.413, p = 0.00594).
The first two components of the CCA
together explained 90.48 % of the accumulated
variance in the association between physico-
chemical variables (Table 4) and functional
feeding groups composition. Shredders and col-
lector-gatherers were associated with high dis-
solved oxygen values, with the highest values
in the Quilca sector (E15 and E16). Predators
were associated with high total dissolved sol-
ids (TDS) values, and scrapers were related to
pH, with both groups prevalent at stations E07
and E08. Meanwhile, filterers were associated
with lower pH, electrical conductivity, salinity,
TDS, and temperature values. High flow rates
were inversely associated with filterers and
collector-gatherers. In general, stations in the
Chili, Sihuas, Lluta, and Sumbay sectors had
lower values for the studied physicochemical
variables, while the Vítor and Quilca sectors
recorded the highest values for these param-
eters (Fig. 5).
DISCUSSION
The results confirm the presence of a
diverse and abundant aquatic macroinverte-
brate fauna in the Quilca-Chili basin in the
department of Arequipa, which is characterized
by arid and semi-arid conditions. In this study,
Fig. 4. Relative abundance of aquatic macroinvertebrates by functional feeding groups in the Quilca-Chili basin. The
numbers on the x-axis correspond to altitudinal levels.
10 Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e2025233, enero-diciembre 2025 (Publicado Set. 18, 2025)
79 taxa conformed the diversity in these basins.
These results are similar to those reported (77
taxa) for the Damas River watershed (Figueroa
et al., 2003) as well as for the Lluta River (Ferru
& Fierro, 2015) in Chile. This similarity most
likely due to these are desert ecosystem riv-
ers, which exhibit similar characteristics. How-
ever, the diversity found in this study is lower
than reported for the Burkina Faso basin in
West Africa (Kabore et al., 2016), which shows
variability determined by fluvial factors and
human activity.
It has been reported that aquatic macro-
invertebrate communities are primarily com-
posed of Diptera (Ferru & Fierro, 2015; Hankel
et al., 2018; Kabore et al., 2016; Leal-Bastidas
et al., 2021), Plecoptera (Figueroa et al., 2003),
and Coleoptera (Nieto et al., 2016). Also, a
greater richness of families from the order
Diptera was found, followed by Coleoptera
and Ephemeroptera. This responds by the wide
distribution and adaptability of Diptera to dif-
ferent environmental conditions (Gutiérrez-
Garaviz et al., 2014), even in areas with varying
levels of disturbance. This is the case with many
members of the family Chironomidae, known
for their high tolerance to pollution, which
were found to be most abundant in the Quilca
sector (the lower part of the basin), where an
increase in mud or fine particulate matter likely
promotes their development.
The differences in groupings between
zones found in the multidimensional scaling
analysis (nMDS) can be attributed to local
Table 4
Physicochemical parameters recorded in the sectors of the Quilca-Chili basin during the study period.
Est. Sector Temp.[°C] pH EC[µS/cm] TDS [mg/L] Sal. [psu] D.O.[mg/L] Turb.FNU
E01 Vitor 25.72 ± 0 8.45 ± 0 2231.5 ± 266.64 1 120 ± 1.87 1.14 ± 0 8.23 ± 0.02 6.52 ± 0.5
E02 Vitor 22.71 ± 0 8.16 ± 0 3 873 ± 832.67 1 194 ± 1.91 2.05 ± 0 7.26 ± 0.03 11.02 ± 1.21
E03 Vitor 23.86 ± 0 8.65 ± 0 1 579.67 ± 844 790 ± 1.67 0.8 ± 0 9.82 ± 0.13 3.45 ± 0.4
E04 Vitor 23.89 ± 0 8.64 ± 0 1 254 ± 120.28 630 ± 1.57 0.62 ± 0.01 11.1 ± 0.15 4.22 ± 0.32
E05 Vitor 20.44 ± 0.01 8.51 ± 0.01 1 327.33 ± 237.16 660 ± 1.59 0.67 ± 0 9.18 ± 0.26 6.05 ± 1.45
E06 Vitor 16.64 ± 0.12 8.29 ± 0.01 878.33 ± 67.19 440 ± 1.46 0.43 ± 0 7.71 ± 0.03 0.2 ± 0
E07 Sihuas 15.5 ± 0 8.82 ± 0 6 796 ± 4.05 4 417 ± 2.68 3.71 ± 0 9.2 ± 0.03 0 ± 0
E08 Sihuas 18.6 ± 0 8.67 ± 0.01 5 207.83 ± 7.08 3 384.5 ± 4.59 2.79 ± 0.01 8.48 ± 0.01 1.3 ± 1.31
E09 Sihuas 25.8 ± 0 8.36 ± 0 1 482.13 ± 4.97 962.88 ± 3.09 0.7 ± 0 8.8 ± 0.52 1.8 ± 0.29
E10 Sihuas 25.5 ± 0 8.37 ± 0 1 326.2 ± 1.92 861.4 ± 1.14 0.63 ± 0 10.39 ± 0.01 51.79 ± 0.63
E11 Sihuas 26.34 ± 0.05 8.32 ± 0.01 1 112.43 ± 3.26 722.57 ± 2.23 0.53 ± 0 7.47 ± 0.02 0.63 ± 0.17
E12 Sihuas 20.8 ± 0 8.58 ± 0 803.83 ± 1.17 522 ± 0.89 0.34 ± 0 7.69 ± 0.01 15.8 ± 1.66
E13 Sihuas 15.3 ± 0 8.84 ± 0 670.5 ± 0.84 435.33 ± 0.52 0.28 ± 0 8.2 ± 0.01 10.3 ± 1.92
E14 Quilca 25.28 ± 0.01 8.73 ± 0 4 226.5 ± 173.25 2 110 ± 86.84 2.24 ± 0.1 14.2 ± 0.05 7.2 ± 0.49
E15 Quilca 20.32 ± 0.01 8.45 ± 0.01 3 967 ± 167.36 1 980 ± 83.61 2.11 ± 0.09 13.41 ± 0.05 8.6 ± 2.25
E16 Quilca 22.28 ± 0.01 8.78 ± 0 1 928.17 ± 130.02 960 ± 65.11 0.98 ± 0.07 13.45 ± 0.06 9.37 ± 1.52
E17 Chili 9.42 ± 0 8.14 ± 0 754.25 ± 0.5 377 ± 0 0.37 ± 0 7.38 ± 0.02 6.9 ± 0.12
E18 Chili 11.37 ± 0.01 8.09 ± 0 685.5 ± 0.58 343 ± 0 0.34 ± 0 7.09 ± 0.11 5.35 ± 1.17
E19 Chili 10.72 ± 0.01 7.61 ± 0.01 526.25 ± 0.5 263 ± 0 0.26 ± 0 7.1 ± 0.03 1.7 ± 0.22
E20 Chili 8.13 ± 0.01 8.41 ± 0.01 325 ± 0 162.4 ± 0.11 0.16 ± 0 11.14 ± 0.66 58.1 ± 7.62
E21 Lluta 13.59 ± 0.024 8.93 ± 0 1 051.29 ± 1.7 682.71 ± 0.95 0.5 ± 0 7.3 ± 0.01 ND
E22 Lluta 15.56 ± 0.04 8.83 ± 0.01 580.13 ± 1.89 376.63 ± 1.06 0.24 ± 0 7.42 ± 0.01 ND
E23 Lluta 15.55 ± 0.051 8.84 ± 0 1 251.87 ± 1.55 813.25 ± 1.16 0.59 ± 0 7.6 ± 0.02 ND
E24 Sumbay 13.89 ± 0.02 8.83 ± 0 234 ± 0 120 ± 1.05 0.11 ± 0 1.26 ± 0.1 2.97 ± 0.3
E25 Sumbay 11.04 ± 0.01 8.06 ± 0.02 122.83 ± 0.02 60 ± 0.9 0.06 ± 0.1 2.32 ± 0.05 11.08 ± 1.5
E26 Sumbay 9.23 ± 0.07 8.34 ± 0.01 506.67 ± 0.01 250 ± 1.02 0.25 ± 0 1.96 ± 0.1 18.9 ± 1.76
11
Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e2025233, enero-diciembre 2025 (Publicado Set. 18, 2025)
factors such as the presence of urban areas
(Carrasco-Badajoz et al., 2022) and intense
agricultural activity, particularly in the middle
and lower parts of the basin. These factors
influence the distribution and composition of
aquatic macroinvertebrates.
Species richness is influenced by both local
and regional factors, such as dispersal and
historical events (Rodrigues-Capítulo et al.,
2020). Phenomena such as “El Niño” and “La
Niña” are of great importance in the basin, as
they affect climate variability and the annual
rainfall pattern, ultimately determining water
availability. These events shape the environ-
mental and substrate characteristics of all rivers
in the region, which are important factors in
species distribution (Schenková et al., 2016), as
well as in the development of aquatic vegeta-
tion (Lin & Yo, 2008). Macroinvertebrates have
been reported to be associated with specific
substrates; for example, collectors prefer gravel
sediments, while predators favor macrophytes
(Rodrigues-Capítulo et al., 2020). This likely
occurs in all sectors of the basin.
Significant differences in species rich-
ness and diversity were found among the river
sectors in this study. Richness and diversity
were highest in the Sihuas sector, which may
be related to specific factors such as reduced
flow and the presence of emergent plants. These
macrophytes provide a stable habitat (Habib &
Yousuf, 2015), offering shelter and protection
from predation (Bendary et al., 2023; Gallardo
et al., 2017). Diversity indices have also been
used to assess rivers with declining water qual-
ity (Zhang et al., 2021), where lower values are
linked to human-induced disturbances. It is
likely that the low values found in the Chili sec-
tor are due to it being the most populated area
of the basin. In contrast, the low diversity values
found in the Lluta sector may be related to the
shape of the river, which is canyon-like, torren-
tial, and lacks vegetation, along with other geo-
logical factors (Rodríguez-Barrios et al., 2011).
In this study, the most abundant func-
tional feeding groups was the scrapers, followed
by collector-gatherers, filterers, shredders,
and predators. These results differ from those
reported for regions with similar character-
istics, where collector-gatherers are the most
abundant functional feeding groups (Ferru
& Fierro, 2015; Mangadze et al., 2019). The
Fig. 5. Canonical Correspondence Analysis (CCA) between trophic functional groups and physicochemical variables.
12 Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e2025233, enero-diciembre 2025 (Publicado Set. 18, 2025)
abundance of scrapers is related to the type of
substrate, such as stones, wood, or submerged
macrophytes in aquatic environments (Li et al.,
2023), where they find their food. These char-
acteristics are present throughout the basin,
suggesting a greater availability of periphyton,
which promotes the growth of organisms that
feed on this resource.
Differences were found in the abundance
of functional feeding groups across the sec-
tors of the basin. The most abundant groups
throughout the basin were scrapers and collec-
tor-gatherers, which replace the dominance that
shredders would typically have in tropical rivers
(Chará-Serna et al., 2010; Rodríguez-Barrios
et al., 2011), as arid and semi-arid basins lack
significant amounts of coarse organic matter,
which is the primary food source for shredders
(Shredder). The feeding habits of scrapers are
related to the availability of periphyton (Moyo
& Richoux, 2017), while the abundance of col-
lector-gatherers is associated with their ability
to acquire any food in the form of fine organic
matter (Demars et al., 2021).
Filterers are more abundant in lotic sys-
tems (Hanson et al., 2010) due to their unique
adaptation to environmental conditions, an
adaptive advantage that other groups. In
this study, filterers were abundant in sectors
with strong currents and higher flow rates,
such as in the Sihuas, Chili, and Lluta sec-
tors. Additionally, the presence of filterers is
associated with an increase in fine particulate
organic matter (FPOM) transport, a common
phenomenon during the rainy seasons in such
systems (Cummins, 2021; Tamaris-Turizo &
Rodríguez-Barrios, 2015; Uieda & Motta, 2007;
Wantzen et al., 2008).
Shredders were found to be less abundant
in this study, especially in Quilca sector, which
is consistent with findings from other rivers in
arid zones (Ferru & Fierro, 2015). This is likely
due to the scarcity of coarse allochthonous
organic matter, as riparian vegetation is sparse
or absent in many parts of the basin.
The abundance of predators in the differ-
ent sectors did not show significant differences
and remained constant throughout the basin.
Predator abundance depends on the abundance
of other functional feeding groups that serve as
their prey (Moyo & Richoux, 2017) and remains
constant due to their ability to switch prey
based on availability (Vannote et al., 1980). This
would explain the distribution pattern of preda-
tors recorded in the different sectors of this
study (Fig. 4), in which functional feeding such
as scrapers, collector-gatherers, and shredders
are well represented across the basin. A similar
pattern was observed by Carrasco-Badajoz et al.
(2022) in the Alameda River (Ayacucho, Peru),
where predator abundance remained relatively
stable along an urban gradient despite marked
changes in environmental quality. This suggests
that trophic dynamics of predator groups can
be resilient to certain types of disturbance, as
long as prey availability remains sufficient.
The CCA analysis revealed associations
between functional feeding groups and physi-
cochemical variables that were not particularly
strong. We found that pH values were associ-
ated with scrapers, consistent with reports for
Andean zones (Carrasco-Badajoz et al., 2022),
where a strong association between pH and this
functional feeding groups. Also, we found that
predators were associated with high dissolved
oxygen levels, as also reported in the works of
Moyo & Richoux (2017) and Mangadze et al.
(2019), where a positive relationship was found
between these functional feeding groups and
dissolved oxygen. Additionally, the proportion
of predators and collector-gatherers was related
to total dissolved solids, consistent with find-
ings from other studies (Mangadze et al., 2019;
Moyo & Richoux, 2017).
These findings highlight the complexity
and variability of relationships between physi-
cochemical parameters and functional feeding
groups in aquatic ecosystems. It is essential
to consider these relationships when design-
ing management and conservation strate-
gies for aquatic resources in the Quilca-Chili
basin, underscoring the importance of specific
research in this region for effective resource
management and biodiversity conservation.
13
Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e2025233, enero-diciembre 2025 (Publicado Set. 18, 2025)
Ethical statement: The authors declare
that they all agree with this publication and
made significant contributions; that there is no
conflict of interest of any kind; and that we fol-
lowed all pertinent ethical and legal procedures
and requirements. All financial sources are fully
and clearly stated in the acknowledgments sec-
tion. A signed document has been filed in the
journal archives.
ACKNOWLEDGMENTS
We thank the Universidad Nacional de San
Agustín for financing the research, through
the UNSA - INVESTIGA funds. Contract
N°IAI-006-2018-UNAS.
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