Reduction of sampling effort assessing macroinvertebrate assemblages for biomonitoring of rivers

Abstract

Biomonitoring methods based on macroinvertebrate assemblages are widely developed in streams and rivers. However, the use of invertebrates has been criticized due to the long time and expense of processing samples. Therefore, we evaluated the effectiveness of reducing the sampling effort from 20 to 5 samples to assess the stream macroinvertebrate community. In six streams in the Basque Country (North of Spain) 20 kick nets were collected following a multihabitat stratified sampling design. The macroinvertebrates were identified to family level and a smoothed family accumulation curve fitting the Clench function to the data was calculated for each stream. Richness was lower in 5 than in 20 samples. However, in general, the percentage of richness estimated with the subsampling may be considered representative of the existing taxa richness. Therefore, the study of five samples may be adequate for biomonitoring Basque streams, greatly minimizing time, effort and costs. RÉSUMÉ

Full text

Knowledge and Management of Aquatic Ecosystems (2015) 416, 08 http://www.kmae-journal.org
c
ONEMA, 2015
DOI: 10.1051/kmae/2015004
Reduction of sampling effort assessing macroinvertebrate
assemblages for biomonitoring of rivers
B. Gartzia De Bikuña(1),E.López
(1),J.M.Leonardo
(1), J. Arrate(1),
A. Martínez(1),(2),,A.Agirre
(1),A.Manzanos
(3)
Received October 2, 2014
Revised January 13, 2015
Accepted January 28, 2015
ABSTRACT
Key-words:
stream
invertebrates,
effort reduction,
biomonitoring
Biomonitoring methods based on macroinvertebrate assemblages are
widely developed in streams and rivers. However, the use of invertebrates
has been criticized due to the long time and expense of processing sam-
ples. Therefore, we evaluated the effectiveness of reducing the sampling
effort from 20 to 5 samples to assess the stream macroinvertebrate com-
munity. In six streams in the Basque Country (North of Spain) 20 kick
nets were collectedfollowing a multihabitat stratified sampling design.The
macroinvertebrates were identified to family level and a smoothed family
accumulation curve fitting the Clench function to the data was calculated
for each stream. Richness was lower in 5 than in 20 samples. However, in
general, the percentage of richness estimated with the subsampling may
be considered representative of the existing taxa richness. Therefore, the
study of five samples may be adequate for biomonitoring Basque streams,
greatly minimizing time, effort and costs.
RÉSUMÉ
Réduction de l’effort d’échantillonnage pour l’évaluation des assemblages de macroinver-
tébrés pour la biosurveillance des rivières
Mots-clés :
invertébrés,
cours d’eau,
réduction
de l’effort,
biosurveillance
Les méthodes de biosurveillance basées sur les assemblages de macroinverté-
brés sont largement développées dans les ruisseaux et rivières. Cependant, l’uti-
lisation d’invertébrés a été critiquée en raison du long temps de collecte et du
coût de traitement des échantillons. Par conséquent, nous avons évalué l’effica-
cité de la réduction de l’effort d’échantillonnage de 20 à 5 échantillons pour éva-
luer la communauté des macroinvertébrés d’une rivière. En six rivières du Pays
Basque (nord de l’Espagne) 20 filets à main Kicker ont été recueillis suivant un
plan d’échantillonnage stratifié multihabitat. Les macroinvertébrés ont été identi-
fiés au niveau de la famille et une courbe de cumul de famille lissée de la fonction
de Clench ajustée aux données a été calculée pour chaque rivière. La richesse
était plus faible dans 5 échantillons que dans 20. Cependant, en général, le pour-
centage de la richesse estimée avec le sous-échantillonnage peut être consi-
déré comme représentatif de la richesse des taxons existants. Par conséquent,
l’étude de cinq échantillonspeut être adéquate pour la biosurveillance des rivières
basques, minimisant considérablement les efforts de temps et les coûts.
(1) Anbiotek S.L. Axpe Industrialdea, Ribera de Axpe 11 B-201, 48950 Erandio, Spain
(2) Laboratory of Stream Ecology, Department of Plant Biology and Ecology, University of the Basque Country,
P.O. Box 644, 48080 Bilbao, Spain
(3) URA. Agencia Vasca del Agua. C/ Orio, 1-3, 01010 Vitoria-Gasteiz, Spain
Corresponding author: aingeru.martinez@ehu.es
Article published by EDP Sciences

B. Gartzia De Bikuña et al.: Knowl. Manag. Aquat. Ecosyst. (2015) 416, 08
INTRODUCTION
Streams and rivers are among the most threatened habitats in the world (Malmqvist and
Rundle, 2002). Since they provide important ecosystem services (Thorp et al.,2010), it is
crucial to understand the consequences of human perturbations on these ecosystems to
preserve or restore their integrity (Meybeck, 2003). Therefore, assessment and biomonitor-
ing programs are carried out widely by public authorities. In river biomonitoring, the aquatic
macroinvertebrates are the most commonly studied group (Bonada et al.,2006) since they
are sensitive to multiple ecological alterations (Johnson and Ringler, 2014). In particular, taxa
richness has been widely used because it is a key measurement to assess the structure of bi-
ological assemblages (Gotelli and Cowell, 2001). However, the use of invertebrates has been
criticized due to the long time and expensive costs of sampling, sorting, counting and identi-
fying them (Ciborowski, 1991). Therefore, since the effectiveness of biomonitoring protocols
depends mainly on the time required and on the overall costs, techniques that optimize the
cost-benefit have been developed (Marini et al., 2013; Pinna et al.,2013,2014). Neverthe-
less, caution is needed since the technique and the way in which samples are collected and
processed may influence the description of the studied community (Boonsoong et al.,2009;
Di Sabatino et al.,2014). In fact, reducing effort and costs is not the only aim of subsampling
methods, but also of paramount concern is the need to gain information not substantially bi-
ased by the procedure and capable of answering research questions (Barbour and Gerritsen
1996).
In Spain, as in other states in Europe, the methodology focused on benthic macroinverte-
brates established by the Water Framework Directive, WFD (EU, 2000), for river biomonitor-
ing is multihabitat stratified sampling (Barbour et al.,1999;AQEM,2002). However, the large
number of kick samples required in each stream increases the time, effort and costs, making
the application of this approach in programs with a great number of monitored systems nearly
impossible. Therefore, the goal of this work is to test if a significant reduction in the sampling
effort from 20 to 5 samples, that would minimize time, effort and costs, allows for the collec-
tion of representative information about the richness of macroinvertebrate communities for
biomonitoring.
MATERIALS AND METHODS
> STUDY SITE
The study was conducted in six streams in the Basque Country (North of Spain) flowing into
the Atlantic Ocean. The study sites differ in the basin area, but not in the water physico-
chemical characteristics. The main land uses of the catchments are native vegetation, conifer
plantations and farming, percentages varying among sites (Table I). The climate in this re-
gion is oceanic, with cool winters (mean winter temperature around 9 ◦C) and warm summers
(mean summer temperature around 21 ◦C), and with a mean annual rainfall of 1000−1200 mm,
evenly distributed throughout the year.
> FIELD PROCEDURES
Benthic macroinvertebrates were sampled in late spring 2012 in three of the six streams
(S1, S2, S3) and in late spring 2013 in the other three (S4, S5, S6). At each site, multihabitat,
stratified and semiquantitative sampling was carried out, collecting 20 kick nets (25 ×20.5 cm;
500 µm) within a 100-m-long reach (Barbour et al.,1999;AQEM,2002). With each kick an
estimated stream bottom area of 0.05 m2(semiquantitative) was sampled. The habitats that
represented 5% of the total surface were sampled (multihabitat). The number of samples
taken in each habitat depended on the percentage that each habitat represented of the total
study reach surface (stratified). The habitats considered included rocky substrates, cover
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Tab le I
Location, water physicochemical characteristics and basin land-use percentages of the studied streams.
S1 S2 S3 S4 S5 S6
Watershed name Barbadun Arratia Altube Oria Altzolaratz Urumea
UTMX 488 696 518 568 504 944 561 781 564 110 587 359
UTMY 4 790 874 4 783 160 4 776 385 4 763 504 4 788 455 4 786 268
Basin (km2)47.9 137.7 192.9 59.8 21.9 156.7
Water temperature (◦C) 14.3 14.3 14.5 13.8 14.3 13.2
pH 7.8 7.9 8.1 8.0 7.9 8.1
Conductivity (µS·cm−1)363.7 397.4 379.3 577.6 310.9 60.4
Total nitrogen (mg·L−1)1.97 2.26 1.39 1.61 2.07 1.00
Total phosphorous (mg·L−1)0.09 0.26 0.21 0.07 0.04 0.04
O2saturation (%) 86.7 91.1 92.9 94.3 93.1 111.9
Land use (%)
Native vegetation 36.9 24.1 50.8 46.2 55.8 77.0
Conifer plantations 20.9 57.5 31.9 29.6 10.6 18.4
Farming 40.2 17.4 16.1 23.4 33.3 4.6
Rocky 1.9 0.3 0.7 0.6 0 0
Urban 00.7 0.4 0.4 0.2 0
vegetation (aquatic bryophytes and algae), macrophytic vegetation (emerged, floating and
submerged macrophytes) and riparian vegetation (roots, vegetation over the channel and
vegetal detritus).
> LABORATORY PROCEDURES
The macroinvertebrates were preserved in 4% formaldehyde for subsequent processing. In
the laboratory, each sample was divided into multiple subsamples. The fauna was studied in
a subsample, identifying the individuals to family level (Oligochaeta and Ostracoda to class)
following Tachet et al. (2002). The size of the analyzed subsample depended on the sample
size (following AQEM, 2002). The total number of individuals in each sample was estimated
by multiplying the number of each taxon by the inverse of the portion. From the portion of the
sample not analyzed, taxa previously not encountered were extracted avisu.
> COST CALCULATIONS
The cost of 20 and 5 samples’ collection and processing was calculated both in terms of time
and money, considering a price of 12 eper hour spent doing the field and laboratory work.
> STATISTICAL ANALYSIS
For each study site, a smoothed family accumulation curve was calculated using Esti-
mateS (100 randomizations; Colwell, 2000). This program computes sample-based rarefac-
tion curves for family richness estimation, presenting the mean number of random sample
re-orderings, and thus removing the possible effects due to the order by which the samples
have been listed. Using STATISTICA, we fitted a Clench function to the data of each study
site to assess the precision of our estimates of family richness. The equation of the Clench
function is Sn=an/(1 + bn), where Snis the observed family number for a given number of
samples, nis the number of samples, ais the new families’ increase rate in the first stages
and bis a parameter related to the curve form.
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B. Gartzia De Bikuña et al.: Knowl. Manag. Aquat. Ecosyst. (2015) 416, 08
Tab le II
Values of the Clench function fitted to family accumulation curves for each stream and the representa-
tiveness of the estimated richness of the richness percentage collected with 20 and five kick samples.
Stream R2a b Final stage slope % taxa richness collected
20 kicks 5 kicks
S1 0.97 37.34 0.60 0.12 96.0 75.0
S2 0.98 15.88 0.35 0.24 91.5 64.0
S3 0.97 18.65 0.41 0.21 93.4 67.5
S4 0.98 24.15 0.75 0.09 96.5 79.0
S5 0.96 37.87 0.72 0.15 96.0 78.2
S6 0.99 42.41 0.99 0.01 97.0 83.3
Figure 1
Family accumulation curves for each stream. Black bars indicate the estimated family richness, taking
into account five samples.
RESULTS
The Clench function estimate of the number of families based on 20 samples represented
from 91.5% (S2) to 97.0% (S6) of the total estimated richness (Table II). In comparison, the
number of families estimated by collecting just five samples was lower (Figure 1), representing
from 64.0% in S2 to 83.3% in S6 of the total estimated richness (Table II).
From the practical viewpoint, the collection and processing of 5 samples is 3.3 times less
time-consuming and cheaper than for 20 samples (Table III).
DISCUSSION
Estimating lower taxa richness is common when attempting to minimize sampling efforts,
either when subsampling within the same technique or using simpler techniques. In this study,
reducing the sampling effort from 20 to 5 samples led to estimating lower taxa richness, but
the diminution was not significant. According to Moreno and Halffter (2000), the inventory of a
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B. Gartzia De Bikuña et al.: Knowl. Manag. Aquat. Ecosyst. (2015) 416, 08
Table III
Cost in terms of time and money required to collect and identify macroinvertebrate assemblages with 5
and 20 samples.
Person number 5 samples 20 samples
Habitat identification (h) 20.33 1.00
Sample collection (h) 20.42 0.75
Sample processing (h) 12.00 8.00
Total t i m e ( h·person−1)3.50 11.50
Total p r i ce (12 e·h−1·person−1)42 138
particular group is consideredrepresentativeof its existing species richness when the number
of sampled species reaches at least 70% of the estimated number of species present. In
this study, four of the six cases were over this threshold, and in the other two (S2 and S3)
the values were very close. Additionally, in these two streams, the percentages collected
from the estimated maximum family richness value with 20 samples were also lower than
those in the other four streams, the richness value not reaching the asymptote of the curve.
These lower values were attributed to the river bed substratum and not to differences in
water physicochemical properties, basin size or land uses. In fact, the river bed was covered
by boulders and bedrock in these two streams, which complicated the collection of samples
with the kick net.
Moreover, despite losing taxa richness, it has been shown that subsampling within the same
sampling technique allows obtaining a representative view of the structure of benthic macroin-
vertebrate communities and that the differences among systems remain, their application be-
ing acceptable in biomonitoring (Marini et al.,2013; Pinna et al.,2013,2014). In contrast, using
different techniques to minimize effort can lead to bias in the information on the structure of
biological communities (Di Sabatino et al.,2014).
In conclusion, the reduction of the sampling effort from 20 to 5 samples may provide a repre-
sentative view of the macroinvertebrate community composition in these streams. Therefore,
the collection of five samples may be sufficient for biomonitoring Basque streams, allowing
savings on time, human effort and costs. These savings, simplifying the spatial sampling ef-
fort, would provide greater temporal effort with a similar cost estimate. Thus, managers and
policy-makers could carry out more exhaustive monitoring in systems where steps to improve
the ecological status are being applied.
ACKNOWLEDGEMENTS
This study was supported by a contract undertaken with the Basque Water Agency (URA).
Data for this study were obtained from the project entitled “Monitoring network of the biolog-
ical status of rivers within the Basque Country” funded by URA and the Basque Government.
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Cite this article as: B. Gartzia De Bikuña, E. López, J.M. Leonardo, J. Arrate, A. Martínez, A. Agirre,
A. Manzanos, 2015. Reduction of sampling effort assessing macroinvertebrate assemblages for
biomonitoring of rivers. Knowl. Manag. Aquat. Ecosyst., 416, 08.
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