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Feeding of detritivores in freshwater sediments
Vos, J.H.
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Vos, J. H. (2001). Feeding of detritivores in freshwater sediments Amsterdam
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Download date: 16 Jun 2017
CHAPTERR 3
GROWTHH RESPONSE OF A BENTHIC DETRITIVORE TO ORGANIC
MATTERR COMPOSITION OF SEDIMENTS
J.H.. Vos1,, P.J. van den Brink2, F.P. van den Ende, M.A.G. Ooijevaar, A.J.P. Oosthoek,
J.F.. Postma3, and W. Admiraal
Departmentt of Aquatic Ecology and Ecotoxicology, Institute for Biodiversity and
Ecosystemm Dynamics, University of Amsterdam, Kruislaan 320, 1098 SM Amsterdam,
Thee Netherlands, '[email protected],
2
ALTERRA Green World Research,
Departmentt of Water and the Environment, P.O. Box 47, 6700 AA, Wageningen, The
Netherlands,, [email protected], 3present address: AquaSense Consultants, P.O. Box
95125,, 1090 HC Amsterdam, The Netherlands, [email protected]
Submittedd for publication
41 1
ChapterChapter 3
Abstract t
Thee biochemical composition of lake and stream sediments were analyzed and
comparedd to detritivore growth and survival to determine which biochemical parameters
correlatedd most strongly with sediment food quality. Sediments were collected from soft
bottomss of 41 sites and fed to the midge larvae of Chironomus riparius. These
sedimentss were analyzed for organic matter (OM) content, C, N, P, carbohydrates,
protein,, fatty acids, pigments, and grain size distribution. A microbial assay was used as
indicatorr of the fraction easily biodegradable OM. Data were analyzed by means of
univariatee and multivariate analyses. Positive correlations of growth or survival with
polyunsaturatedd fatty acids (PUFAs), pigments, and labile OM were found when
standardizedd on dry weight. When variables were standardized based on mass of OM,
additionall significant positive correlations with P, carbohydrates, proteins, and fatty
acidss of bacterial origin were detected. Similarly, multivariate analyses revealed
strongerr correlations between larval growth and survival and biochemical variables
standardizedd on OM compared to those standardized on dry weight. It was postulated
thatt dilution of OM by mineral particles caused the difference between the
standardizationn methods. Organic matter composition constituted an important factor
influencingg detritivore growth. Labile OM was found to support the highest larval
growth. .
42 2
ChironomidChironomid larvae growth on sediments
Introduction n
Detritivorouss animals feed on particles that vary through time in abundance and
inn state of decomposition. Consequently, food resources available to detritivores differ
inn nutritional quality during the course of the year (e.g. Hill et al. 1992, Canuel and
Martenss 1993, Ahlgren et al. 1997, Cavaletto and Gardner 1999). The strong positive
responsee of deposit feeders to seasonal inputs of newly produced organic matter (OM)
suggestss that food abundance is a limiting factor much of the year (Lopez and Levinton
1987,, Goedkoop and Johnson 1996). Indeed the species composition of algal blooms
hass also been recognized as a factor regulating the population dynamics of benthic
faunaa (Marsh and Tenore 1990, Cheng et al. 1993). Such factors may be entirely
explainedd through the varying quality of OM in sediments. Food quality of the pelagic
inputt to the benthic pool of detritus is dependent on the species that comprise the algae
blooms.. For instance, diatoms and flagellates form a high quality food due to their high
polyunsaturatedd fatty acid (PUFA) content, whereas the low PUFA content of cyanobacteriaa make their quality as food for detritivores poor (Ahlgren et al. 1997, Brett and
Müller-Navarraa 1997, review Napolitano 1999). During sedimentation, the biochemical
contentt of algae changes due to chemical oxidation, bacterial decomposition, cell
leaching,, and stripping by zooplankters prior to settling on to the substrate. The more
labilee components degrade first, leaving less easily digested compounds. This process
continuess after sedimentation and is promoted by bioturbation. As a consequence, sedimentss typically contain less digestible OM compared to other food sources consumed
byy aquatic animals (Bowen 1987, Fry 1987, Meyers and Ishiwatari 1995). Ahlgren et al.
(1997)) found distinct differences in chemical composition between plankton samples
takenn in the photic zone and sedimentation samples collected in the aphotic zone of a
largee mesotrophic lake. C/N ratios of sedimentation samples were mostly higher than
thosee of plankton, but the greatest differences between plankton and sedimentation
sampless were found for PUF As. Thus, ongoing degradation leads to a lower food qualityy to which benthic invertebrates have access compared to that accessible to pelagic
zooplankters. .
Planktonicc algae are not the sole sources of OM in sediments. Macrophytes, OM
off animal origin, and litter from terrestrial vegetation also add to sediment organic
43 3
ChapterChapter 3
material.. The diverse sources of OM and degradation histories are expected to result in
highlyy different food sources for the detritivorous component of benthos inhabiting
substratess of water systems that differ in primary and secondary production, current
regime,, and terrestrial vegetation type. This study explored differences in food
compositionn and nutritional state between individual sediments from various sites as
regulatingg factors of detritivore growth. Field samples of unpolluted sediments of
streamss and lakes in the Netherlands and the Pripyat basin (Republic of Belorussia)
weree taken to the laboratory where growth of the detritivorous Chironomus riparius
Meigenn larvae on the individual substrates was determined. In conjunction, the sedimentss were characterized with respect to a large number of chemical and physical parameterss to identify the main factors regulating growth of the invertebrates. Growth and
survivall of the larvae were correlated to these sediment parameters by means of univariateriate and multivariate analyses.
Methods s
SedimentSediment sampling
AA total of 41 freshwater sediment samples taken from habitats ranging from
smalll streams to large lakes were obtained using an Eckman-Birdge grab which was
adjustedd to sample the upper 4 cm surface layer. All sediments were analyzed by the
analyticall laboratory AlControl, Hoogvliet, the Netherlands, for metals, PAHs, PCBs,
andd pesticides. The sediments contained the sum of PCBs (PCB-28, -52, -101, -118, 138,, -153, and -180) 7 < ug kg"1, sum of pesticides (aldrin, dieldrin, endrin, DDT, endosulfan,, HCHs, heptachlor, and heptachlorepoxide) < 13 ug kg"1, sum of chloride benzeness (di-, tri-, tetra-, penta-, and hexachloride benzenes) < 1 ug kg"1, sum of PAKs
(naftalene,, benzo(a)antracene, benzo(ghi)perylene, benzo(a)pyrene, fenanthene, indeno(1,2,, 3-cd)pyrene, anthacene, benzo(k)fluoranthene, chrysene, fluoranthene) < 0.55 mg
kg*1,, EOX < 0.31 mg kg"1, mineral oil 47 < mg kg"1, and Cd < 0.4 mg kg"1, Hg < 0.05
mgg kg"1, Cu < 5 mg kg"1, Ni < 8 mg kg"1, Pd < 13 mg kg"1, Zn < 16 mg kg"1, Cr < 15 mg
kg*1,, and As < 4 mg kg"1 dry mass. According to the Dutch regulations (Evaluatienota
Waterr 1994) all 41 sediments were clean.
Thee sediment samples were collected between March 1997 and October 1998
44 4
ChironomidChironomid larvae growth on sediments
fromfrom 38 sites throughout the Netherlands and from 3 sites in the Republic of Belorussia
(Pripyatt basin). Of the 41 samples, 20 were taken from large and shallow lakes, 6 from
smalll lakes, 6 from large rivers (width > 5m), and 9 from small streams. Riparian vegetationn ranging from woods to meadows. All sediments were frozen at -20°C within 6 h
afterr sampling. After thawing the sediments were sieved through a 1000 um mesh to
removee larger particles such as pebbles, leaves, and twigs. The sediments were frozen a
secondd time to ensure the removal of all indigenous animals.
GrowthGrowth experiments with chironomid larvae
Growthh experiments were conducted at 20°C
1°C and a 16:8 hour light:dark
regime.. Experiments were carried out in polyethylene containers (10 x 10 x 6.5 cm).
1000 ml of homogenized sediment and 200 ml of artificial freshwater (Dutch Standard
Water,, pH 8.2, 210 mg CaC0 3 l') were added to each container and the water was
continuouslyy gently aerated. The sediments were allowed to settle and stabilize for 24 h,
andd pH and oxygen saturation of the overlying water were measured at the beginning of
thee experiment.
Att the start of each experiment, larvae originating from at least 10 egg masses of
ChironomusChironomus riparius (Meigen), a detritivorous (Rasmussen 1984, 1985) laboratory
culturedd midge, were used. Experiments were started by randomly adding 20 I s instar
larvaee less than 24 h old to each container. An additional group of 20 larvae was
randomlyy collected to determine initial larval length by means of a binocular microscope.. During the experiment, oxygen levels and pH were checked every 2-3 d. In
addition,, ammonium, nitrite, and nitrate concentrations in the overlying water were
measuredd at the start of the experiment using Quantofix® test sticks (SE = 5 mg N 1" for
NH4+)) and TetraTest Nitrite® test kit (SE - 0.05 mg N l"1 for N02" and N03"). After 14
d,, the lengths of surviving larvae were measured with a binocular microscope. Since
larvaee decrease in length during the prepupal stage it was decided to give these larvae
thee greatest length found in the reference containers of growth experiments that were
startedd at the same day. Growth experiments on each sediment sampled in 1997 were
replicatedd 4 times while the growth experiments sampled on sediments sampled in 1998
weree replicated 3 times. To test for food limitation, larval growth on the 1997 sediments
wass also tested 4 times with additions of 100 mg of the fishfood mixture each week.
45 5
ChapterChapter 3
Thee condition of 1st instar larvae used in the growth experiments was monitored by
takingg along 3 control units each day growth experiments were started. Controls consistedd of containers with 50 g of combusted Litofix® sand (<500 urn, heated at 550°C for 6
h),, 200 ml of Dutch Standard Water and 100 mg of a mixture of the commercial
availablee fishfoods Trouvit® and Tetraphyll® (95:5 m:m) each week. Replicates of each
sedimentt were started at different days to ensure complete statistical independence.
ChemicalChemical
analyses
Sedimentt samples for chemical analyses were collected in containers similar to
thosee used for growth experiments, and were treated identically as sediment used for the
growthh experiments. These sediments were frozen directly after starting the growth
experiments.. The resulting 3 or 4 subsamples per sediment were mixed quantitatively,
thann freeze-dried and stored at -20°C. Grain size distribution was determined by sieving
andd the pipet method descibed in ISO 11277 (1998). Water content was determined by
freezee drying a preweighted sediment sample in triplicate.
Thee OM content was determined as loss-on-ignition by combusting the material
att 550°C for 6 h (Luczak et al. 1997) in triplicate. Total C was measured in duplicate
withh a Carbo-Erba Element Analyser. N was measured according to Kjeldahl (ISO
112611 1995).
Totall P was determined according to Murphy and Riley (1962) and protein
accordingg to Rice (1982), with both analyses conducted in duplicate. For analyzing
carbohydrates,, a modified method based on the phenol-sulphuric acid-method of Dubois
ett al. (1956) was used. It was noted that the baseline of the photometric spectra between
4000 and 600 nm of the phenol-sulphuric acid solution of the individual sediments
differedd in intercept. It was decided to correct absorption at 485 nm with additional
spectrophotometricc measurements at 440 and 550 nm according to the following
calculationn for both sediment samples and calibration curve: Abs 485 n m , = Abs 4g5 nm ((Abss 550 nm + ((Abs 440 nm - Abs 550nm)*65/l 10)), in which Abs = absorption and Abs 485
nm'== Abs at 485 nm corrected for intercept of the baseline.
Chlorophyll-^^ and pheaophytin were measured according to Nusch and Palme
(1975)) in duplicate sediment samples. The ethanol solution was centrifuged in closed
test-tubess to avoid optical disturbance by suspended sediment. Chlorophyll-a and
46 6
ChironomidChironomid larvae growth on sediments
pheaophytinn contents were summed because during the analytical procedure chlorophyll-aa was found to partly degrade into pheaophytin indicated by a large standard error
off chlorophyll:pheaophytin ratio among replicates.
Lipidss were extracted with a 1:1:0.9 v/v/v chloroform:methanol:water mixture
followingg the Bligh and Dyer (1959) procedure. Prior to the extraction, preweighed
sedimentt samples of 5 - 10 g together with 8 ml double destilled water were sonificated
forr at least 5 minutes in a -4°C water bath. The resulting collected chloroform was
evaporatedd with nitrogen gas. For analyses of fatty acid composition the lipid samples
weree diluted again in an appropriate volume of hexane containing heneicosaenoic acid
(21:0,, 838.75 mg ml"1) as an internal standard and BHT (2,6-di-tert-butyl-p-cresol, 50
mgg ml"1) as an antioxidant with nitrogen as the overstanding gas and were stored at
-20°CC until transesterification. Fatty acid methyl esters (FAME) were obtained by mild
alcanolicc methanolic transesterification as described in Guckert et al. (1985). The
FAMEE samples were stored at -20°C with overstanding nitrogen gas for no longer than
22 months before Gas Chromatographic analysis took place. GC separation of the FAME
wass performed by injecting a 1 \il aliquot in a very polar 50 m CP-Sil 88 column (ID
0.255 mm, film thickness 0.20 mm) with a splitflow of 1:40. Optimal separation of
FAMEE peaks was obtained with a temperature program that began at injection with an
initiall column temperature of 180°C for 10 minutes followed by a rise of 3°C min"1 to a
finall temperature of 225°C, where it was held for 10 minutes. Fatty acid nomenclature
usedd in this study conforms to the A:BcoC model where A designates the number of
carbonn atoms in the fatty acid methyl ether, B the number of double bonds, and C the
distancee of the closest double bond from the aliphatic (co) end of the molecule. The fatty
acidss (FAs) mentioned in this study and used for further calculation and statistical
analysess were all cw-isomers.
Tentativee identification of FAME peaks was based on co-elution with the 21:0
standardd and by comparison of relative retention times, calculated as the retention time
(RT)) of the peak minus the time at which the solvent peak appeared divided by the
retentionn time of 16:0 or 21:0 minus the RT of the solvent peak. Final identification was
basedd on Mass Spectrometry analyses of 4 sediment FA samples performed by dr. Eric
Boschker,, NIOO, Yerseke, The Netherlands. A PUFA variable was obtained by
summingg up the peak areas of 16:2co4, 16:3co4, 18:2co6, 18:3<o3, and 18:3co6. Peak
47 7
ChapterChapter 3
areass of FAMEs of bacterial origin (i.e. Z14:0, i\5:0, al5:0, 15:1, /16:0, z'16:l, il7:0, and
«17:0;«17:0; Parkes 1987; Napolitano 1999) were added to obtain a bacterial FA variable. A
measuree for total FA was calculated by adding all fatty acid peaks from 12:0 up to the
lastt peak appearing in the chromatogram before the 21:0 internal standard peak
(18:3co3).. Only FAME peaks which appeared before the internal standard in the
chromatogramm were used for further calculations because the peaks appearing later in
thee chromatogram showed irregular retention times.
Energyy content (E-content) was calculated by assuming that 1 g of fat releases
38.99 kj, 1 g of protein releases 17.3 kJ, and 1 g of carbohydrate yields 16.9 kJ.
AssessmentAssessment of the most labile fraction of the organic matter
AA microbial assay was used to obtain a measure of the labile, i.e. easily
degradable,, fraction of the sediment organic matter. Microbial mineralization was
measuredd as CO2 production. Wet sediments were used that had been kept frozen until
analysis.. A bacteria inoculum was prepared from the surface layer of a sediment
containingg a decaying cyanobacterial mat (Oscillatoria sp). Bacteria were detached by
ultrasonicc treatment and particles were removed by centrifugation (5 min 50 g). In a 77
mll gas-tight bottle 4 ml of sediment was suspended in 11 ml of a 55 mM phosphate
bufferr (pH 7.1) and 1 ml of the bacteria inoculum was added. After 30 min of aeration
pHH was measured and the bottles were capped gas-tight. The bottles were placed on a
rotaryy shaker at 20°C in the dark and after allowing one hour equilibration the C0 2
concentrationn in the headspace was measured gaschromatographically. After 48 hours
incubationn the C0 2 concentration was measured again and the pH was measured. The
headspacee contained sufficient oxygen to maintain oxic conditions throughout the
experiments.. Gas in the headspace was assumed to remain at atmospheric pressure and
thee CO2 concentration in equilibrium with the aqueous phase. Total CO2 in carbonic
acid,, bicarbonate and carbonate in the aqueous phase was calculated according to
Stummm and Morgan (1981). Due to the large size of the headspace (61 ml) around half
thee total C0 2 was in the gas-phase thus ensuring accuracy of the measurement. C0 2
productionn was calculated by subtracting the total concentration in water and headspace
att the start from the total concentration after 48 h. Blancs showed that CO2 produced
fromm organic matter in the inoculum was negligible. Controls with yeast extract (2 mg
48 8
ChironomidChironomid larvae growth on
sediments
perr bottle) in stead of sediment were used to check for reproducibility during the
measurementss and to allow comparison with future experiments. None of the sediments
wass rich in inorganic carbonates so no attempt was made to remove these. During the
incubationn the pH declined less that 0.25 units, thus limiting possible interference of
carbonates. .
UnivariateUnivariate statistical analyses
Correlationss between larval growth, survival and chemical variables were
determinedd with Pearson correlation using the average larval survival and growth per
sedimentt and the mean of repeated analyses for the different sediment variables.
Correlationss were performed with variables standardized on both dry weight (DW) and
OM.. Growth and survival on sediments collected in 1997, with and without surplus of
foodd were compared with a two-way ANOVA.
MultivariateMultivariate analyses
Multivariatee analyses were performed using Principal Component Analysis to
obtainn a graphical summary of the data set and an overview of mutual relationships
betweenn sediment variables on the one hand and larval growth and survival as
determinedd in the laboratory tests on the other hand (ter Braak 1995). PCA was chosen
forr final ordination because the length of gradient was < 2.0 as was determined with
Detrendedd Corresponce Analysis (DCA). PCA is an ordination method which uses a
Tablee 1. Summary of variables found in the 41 substrates. Averages are calculated from the
averagee values of each indiviual sediment. CV = coefficient of variance. Min = minimum and
maxx = maximum value as found in the dataset. SWC = sediment water content (% of wet
weight),, OM = organic matter (% of dry weight), %<63 urn = percentage of volume particles <
633 (im, and %<210 urn = percentage of volume particles 0-210 urn.
average e
min n
max x
CV V
SWC C
32.9 9
14.1 1
90.6 6
24 4
OM M
2.3 3
0.2 2
8.8 8
121 1
C/N N
24.2 2
3.0 0
107 7
91 1
%<633 urn
20.8 8
0.7 7
79 9
126 6
%<210um m 60.9 9
5.1 1
96 6
50 0
49 9
ChapterChapter 3
Tablee 2. Overview of variables expressed as portion of dry weight or of organic matter
measuredd in the 41 sediments. Averages are calculated from the average values of the
individuall sediments. CV = coefficient of variance. Minimum (min) and maximum (min) value as
foundd in the dataset.
CO O
CD D
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oo
CD D
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CM M
CM M
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CM M
CM M
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CM M
CD D
a: :
co o
>>
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TS TS
V) V)
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m m CD
T_ _
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linearr model for dimension reduction. In PCA, imaginary, latent explanatory variables
(principall components) are calculated from the data set which best explain the variation
inn sediment parameter composition between sites. The first principle component is
constructedd in such a way that it explains the largest part of the total variance possible,
50 0
ChironomidChironomid larvae growth on sediments
thee second one the largest part of the remaining variance, etc. The first two principle
componentss were used as axes to construct an ordination diagram and the weights of the
parameterss and sites with these variables are plotted in the diagram represented by
points.. After the construction of the diagram, the larval performance parameters (growth
andd survival) were superposed on the diagram, i.e. they were regressed on the axes
usingg the site points. Within PCA, all sediment characteristics were standardized and
centeredd to make them mathematically equally important. This is necessary because all
characteristicss were measured or expressed in different units. Two analyses were performed,, 1 on the sediment data with biochemical variables standardized on DW, and 1
onn data with biochemical variables standardized on OM. Permutation tests were performedd on whether larval growth and survival have a significant relation with the variation
inn sediment characteristics among sites, using the constrained version of PCA, Redundancyy Analysis (ter Braak and Smilauer 1998). All multivariate analyses were performedd with the CANOCO for Windows software package (ter Braak and Smilauer 1998).
Results s
CompositionComposition of the sediments
Grainn size distribution of sediments samples ranged from silty to sandy (Table
1).. Sediment water content ranged from 14.1 to 90.6 % of wet weight, but the coefficientt of variation among samples was relatively low (CV = 24%). The variation in
organicc matter (OM) content was well spread over the samples (CV = 121%). All
biochemicall variables showed a high CV when standardized on dry weight (DW) (Table
2).. Standardization on OM content resulted in lower variation for most of the biochemicall variables. Only XFA, PUF As, and labile OM had slightly higher CVs when standardizedd on OM.
Iff the variables were standardized on DW many significant correlations were
foundd among the biochemical variables (Table 3). Most biochemical variables standardizedd on DW were also found to be significantly correlated with OM content. This may
bee expected, since the biochemical variables are all considered to represent part of the
OMM fraction. Levels of biochemical variables expressed as proportion of DW may
thereforee be expected to follow the level of OM. Only IFA and PUF As were found to
51 1
ChapterChapter 3
Tablee 3. Correlations of sediment parameters with the biochemical variables standardized on
totall fatty acids, PUFAs = polyunsaturated fatty acids, bac. FAs = fatty acids of bacterial origin,
%<633 um = percentage of volume particles smaller than 63 urn, %<210 urn = percentage of
CC
NN
NN
+0.81** *
PP
+0.70** * +0.52" "
PP
carbohydrates protein I F A
PUFAs s bac.. FAs
carbohydrates s + 0 . 7 7 " " +0.83" " +0.37" "
protein n
+0.51** * + 0 . 5 7 " " +0.67" " ++ 0.45"
IFA A
+0.17 7 +0.12 2 +0.26 6
++ 0.10
+0.18 8
PUFAs s
+0.26 6 +0.06 6 +0.55** * ++ 0.05
+0.266
bacteriall FAs
+0.70" " +0.44" " +0.86** * ++ 0.37" +0.54"" +0.20 ++ 0 . 7 1 "
pigments s
+0.51** * +0.35* * +0.44** * +0.33" " +0.34**
E-content t
+0.64** * +0.70" " +0.68" " +0.64" " +0.96"" +0.33* ++ 0.26 ++ 0.57"
C0 22 production + 0 . 5 1 " " +0.38" " +0.64** * +0.33* *
+0.21
+0.06 ++ 0.29* ++ 0.50"
+0.52"" +0.10 ++ 0.43" ++ 0.68"
havee a low number of significant correlations with the other chemical variables if
expressedd as portion of DW. Standardization on OM content decreased the number of
correlationss between biochemical variables, thus indicating a diverse composition of
OMM (Table 4). OM was strongly correlated to particle sizes < 63 um (R2 = 0.92, P <
0.01)) and less strong to particle sizes < 210 um (R2 = 0.31, P < 0.05).
Tablee 4. Correlations of sediment parameters with the biochemical variables standardized on
totall fatty acids, PUFAs = polyunsaturated fatty acids, bac. FAs = fatty acids of bacterial origin,
%<63umm = percentage of volume particles smaller than 63 um, %<210 um = percentage of
CC
NN
NN
+0.23 3
PP
+0.67" " +0.09 9
carbohydrates s -0.00 0
PP
carbohydrates protein I F A
PUFAs s bac.. FAs
+0.10 0 +0.08 8
protein n
+0.11 1 +0.07 7 +0.33* * +0.08 8
IFA A
+0.21 1 -0.02 2 +0.29* * +0.05 5
+0.05 5
PUFAs s
+0.54" " +0.20 0 +0.78** * +0.19 9
+0.34* * +0.20 0
bacteriall FAs
+0.36* * +0.06 6 +0.58** * +0.12 2
+0.28* * +0.09 9 +0.83** *
pigments s
+0.11 1 +0.18 8 +0.21 1
+0.04 4 +0.05 5 +0.55" " +0.49" "
E-content t
+0.18 8 +0.07 7 +0.42** * +0.29* *
C 0 22 production +0.03 3 +0.07 7 +0.16 6
52 2
+0.31* *
+0.17 7
+0.87" " +0.49** *+ 0 . 4 1 " " +0.29* *
+0.24 4 +0.16 6 +0.47" " +0.58" "
ChironomidChironomid larvae growth on
sediments
dryy weight. Pearson coefficient R2 and significance level. * = P < 0.05, ** = P < 0.01. I F A =
E-contentt = energy content, SWC = sediment water content, OM = organic matter,
volumee particles smaller than 210 um.
pigments s E-content t SWC C
+0.35* *
+0.64** *
OM M
C/N N
%<633 um %<2100 um
++ 0.89** ++ 0.83**
-0.20 0 ++ 0.77** +0.26* *
++ 0.63" ++ 0.74**
+0.09 9 ++ 0.81** +0.41** *
++ 0.84** ++ 0.79**
+0.07 7 ++ 0.63** +0.29* *
++ 0.54** ++ 0.57**
-0.12 2 ++ 0.56** +0.34* *
++ 0.14
++ 0.12
+0.04 4 ++ 0.20
+0.07 7
++ 0.25
++ 0.16
+0.11 1 ++ 0.25
+0.49** *
++ 0.63** ++ 0.69**
+0.09 9 ++ 0.73** +0.49** *
++ 0.44** ++ 0.52**
+0.08 8 ++ 0.40** +0.37** *
++ 0.68** ++ 0.69**
-0.07 7 ++ 0.65** +0.36** *
+0.52** * ++ 0.50** ++ 0.53**
-0.08 8 ++ 0.52** +0.56** *
GrowthGrowth and survival of midge larvae
Lengthh of the larvae at the start of the experiments averaged 0.89 mm (SE =
0.02).. After 14 d larvae in the controls averaged 12.5 mm (SE = 0.28) in length and
>70%% were in their 4th instar. After 14 days larval survival exceeded 80% in all controls.
Survivall per experimental unit with sampled sediment ranged between 0 and 100% and
organicc matter. Pearson coefficient R2 and significance level. * = P < 0.05, ** = P < 0.01. I F A =
E-contentt = energy content, SWC = sediment water content, OM = organic matter,
volumee particles smaller than 210 um.
pigmentss
E-content SWC
OM
C/N
%<63 um %<210um
-0.08 8
-0.45** * -0.04 4
-0.11 1
-0.22 2
+0.11 1
-0.14 4
+0.29* *
+0.10 0
+0.02 2
-0.08 8
-0.04 4
+0.31* *
-0.09 9
-0.17 7
-0.16 6
-0.16 6
+0.34* *
-0.25 5
-0.30* *
+0.02 2
-0.25 5
-0.19 9
-0.14 4
-0.30* *
+0.00 0
-0.26 6
+0.23 3
-0.14 4
-0.26 6
-0.07 7
-0.22 2
+0.15 5
-0.25 5
-0.35* *
-0.17 7
-0.37** * +0.15 5
-0.17 7
-0.27* *
-0.14 4
-0.25 5
-0.32* *
-0.43** *
-0.24 4
-0.43** * +0.05 5
+0.06 6
+0.01 1
+0.27* *
53 3
ChapterChapter 3
Fig.. 1. Larval growth (mm) and survival (%) after 14 days on sediments provided with and
withoutt surplus of food. White bars represent sediments supplemented with 100 mg of fish food
perr week, black bars represent sediments without additional food. Errors bars = SE.
M— —
cc
oo
C C 1— —
X. X. CD D CD D CO O
CD D C C o o
JZ JZ
(1) )
CD D C
O O
1_ _
^ ^
m m
n n oo X X
o o
CD D
"O O
<D D
-L L
CD D
CD D
m m CD D
EE
v v
C/) )
CD D
E E
CO O
CD D
m m b b5 5
c c b b _CO O
CD D
OO
OO
growthh between 0.8 and 11.0 mm. Growth was highly significantly correlated with
survivall in sediments not augmented with fish food (R2 = 0.69; P < 0.01).
Larvall growth and survival on sediments that were provided with fish food
(thosee collected in 1997) were similar to growth in the controls (Fig. 1). Survival was
>80%% in all experimental units provided with fish food. Growth and survival were significantlyy lower (P < 0.05) on the sediments not provided with fish food compared to
thee sediments provided with excess of food.
54 4
ChironomidChironomid larvae growth on sediments
Tablee 5. Correlations of growth and survival of C. riparius larvae after 14 days with sediment
parameters.. Pearson coefficient R2 and significance level. * = P < 0.05, ** = P < 0.01. SWC =
sedimentt water content, OM = organic matter, %<63 urn = percentage of volume particles
smallerr than 63 urn, %<210 urn = percentage of volume particles between 0 and 210 urn.
growth h
survival l
survival l
+0.69** *
SWC C
-0.01 1
-0.15 5
OM M
-0.14 4
-0.25 5
C/N N
-0.24 4
-0.33* *
%<633 nm
-0.15 5
-0.19 9
%<2100 urn
+0.51** *
+0.34 4
Duringg the growth experiments, the oxygen saturation level did not fall below
60%% in any of the experimental units of the 41 sediments. All N02" concentrations were
<11 mg l"1, the N t V concentrations <10 mg l"1, and the pH in the overlying water varied
betweenn 7.1 and 8.5 during the experimental period.
CorrelationsCorrelations of larval growth and survival with sediment parameters
Larvall growth and survival in non-augmented sediments were significantly correlatedd (P < 0.01, Table 5). Growth was positivily correlated with the particle size fractionn < 210 urn.
Whenn biochemical variables were expressed on the basis of DW, correlations of
growthh and survival were found with PUF As, pigments, and labile OM (P < 0.05, Table
6).. When sediment variables were standardized on OM content, the strength and number
off correlations increased, with additional significant correlations (P < 0.05) found with
P,, carbohydrates, protein, F As of bacterial origin, and energy-content.
MultivariateMultivariate analyses
Thee first 2 axes of the PC A plot based on biochemical variables expressed on a
DWW basis display 62% of the total variance among sediment variable (Fig. 2, Table 7).
Alll of the sediment characteristics are displayed on the right side of the diagram, indicatingg that they are all, to some extent, positively correlated with each other (see also
Tablee 3). Larval growth and survival correlated most strongly with sediment PUFA
content.. The results of the Monte Carlo permutation tests also show a significant corre-
55 5
ChapterChapter 3
Tablee 6. Correlations of growth and survival of C. riparius larvae after 14 days with the
biochemicall variables expressed per unit of dry weight or organic matter weight. Pearson
coefficientt F? and significance level. * = P < 0.05, ** = P < 0.01. I F A = total fatty acids, PUFAs
== polyunsaturated fatty acids, E-content = energy content.
variabless standardized on
dryy weight
growth h
survival l
cc
-0.10 0
NN
-0.06 6
organicc matter
growth h
survival l
-0.27* *
+0.24 4
+0.02 2
-0.20 0
+0.21 1
+0.12 2
PP
+0.12 2
+0.06 6
+0.45** *
+0.31* *
carbohydrates s
-0.01 1
-0.22 2
+0.41** *
+0.20 0
protein n
+0.21 1
+0.13 3
+0.32* *
+0.29* *
EFA A
-0.05 5
-0.01 1
-0.03 3
+0.08 8
PUFAs s
+0.51" "
+0.39** *
+0.58** *
+0.49** *
bacteriall FAs
+0.25 5
+0.21 1
+0.49** *
+0.50** *
pigments s
+0.39** *
+0.11 1
+0.70** *
+0.51** *
E-content t
+0.15 5
+0.04 4
+0.33* *
+0.32* *
C 0 22 production
+0.56** *
+0.41** *
+0.54** *
+0.59** *
lationn between the larval performance parameters and the sediment characteristics
(Tablee 7).
Thee biplot of the sediment characteristics with biochemical variables expressed
onn an OM basis explained 43% of the total variance, while larval performance explained
20%% of the total variance (Fig. 3, Table 7). Again all sediment characteristics are
displayedd on the right in the diagram, with the exception of water content. The setting of
thee biplot indicates a positive correlation with most of the sediment characteristics, and
especiallyy with CO2 production, pigments, fatty acids of bacterial origin, energycontent,, protein, carbohydrates, and N. A very strong correlation between the larval
performancee parameters and the sediment characteristics is indicated by the Monte
Carloo permutation tests (Table 7).
Strongerr correlation of larval performance and sediment characteristics (lower
P-values)) are found if the biochemical variables are standardized on OM content
comparedd to standardization of the biochemical variables on DW (Table 7). Moreover, a
higherr % of variance used to explain larval growth and survival is displayed in the
biplott with the standardization on OM whereas the total variance expressed of the sedi-
56 6
ChironomidChironomid larvae growth on sediments
mentt characteristics is lower. This means that a lower % of variance is used to explain a
higherr % of variance of larval growth and survival in the data set with the biochemical
variabless standardized on OM content compared to the data set with the biochemical
variabless standardized on DW.
Discussion n
Duringg this study, sediments were sampled in several different water systems
rangingg from large lakes to small streams and from silty to sandy sediments. The origin
off the organic matter (OM) presumably varied between predominantly algal in some
systemss to being largely land-derived in others. In spite of the broad variation in the
substratess used in this study, growth and survival of Chironomus ripctrius larvae were
welll correlated to chemical characteristics of these sediments. Evidently, the nutritional
valuee of ingested matter is highly limiting for larval growth and survival in many
sediments,, since supplementation with high quality fish food stimulated larval growth in
sedimentss from all 41 sites, simultaneously showing that physical characteristics of the
sedimentss did not influence larval growth of C. riparius. This finding supports the
hypothesiss posed by a few field studies that OM limits and regulates population dynamicss of benthic macrofauna (Lopez and Levinton 1987; Goedkoop and Johnson 1996).
Thee degree of food limitation that we demonstrate may partly be affected by the use of
C.C. riparius as a test species. C, riparius is known to abound in organically enriched
waters.. The very low survival and growth rates in the poorest sediments may have been
causedd by relatively high food demands of this species.
Besidess growth limitation caused by food supply, specific biochemical componentss were found to correlate with larval growth and survival. Standardization of these
variabless on the basis of sediment OM content resulted in more and stronger
correlationss with growth and survival of midge larvae than did standardization on basis
off dry weight (DW). The PCA analyses also showed more variance of larval performancee was explained when sediment characteristics were expressed on the basis of OM
content.. OM content of the sediments was strongly correlated with the small particulate
fractionn (< 63 urn). C. riparius larvae are mainly deposit feeders that eat whole sedimentss with a particle size limit determined by the mentum width (for instance, between
57 7
ChapterChapter 3
Fig.. 2. PCA biplot showing characteristics of 41 unpolluted sediments with the (bio)chemical
variabless standardized on dry weight. Open circles represent sediments, black dots sediments
parameters,, and arrows larval performance parameters. For percentages of total variance and
resultss of additional Monte Carlo permutation tests see Table 7.
+1.0 0
OO
carbohydratess
OO
organicc matter
oo
C
cPP
OO
€© ©
c
N
E-content
proteins s
w owo
OO
E/N N totall FA
OO
pigments s
PP
C0 22 production
%>210pm m
survivalsurvival\ \
bacterial FA
O O growthgrowth
OO \
1
PUFA A
-1.0 0
-1.0 0
Axiss 1, eigenvalue 0.49
+1.0 0
422 and 65 urn for 2" instar larvae, Chapter 4). The strong correlation of OM content
withh the small particle fraction of the sediments secures that standardization of variables
onn an OM basis includes the part of the sediments that potentially can be used as food
sourcee by the chironomid larvae. The small particle fraction probably not only containedd OM, but also mineral particles. The midge larvae used in our experiments inevitablybly ingested different quantities of small mineral particles along with the OM during
feedingg trials. Consequently, growth may have been limited to varying extents by dilutionn effects, associated with the portion of small mineral particles ingested (Chapter 4).
Differencess in mineral constituents and thus in the quantity of ingested OM among the
58 8
ChironomidChironomid larvae growth on sediments
Fig.. 3. PCA biplot showing characteristics of 41 sediments with the biochemical variables
standardizedd on organic matter content. Open circles represent sediments, black dots
sedimentss parameters, and arrows larval performance parameters. For displayed percentages
off total variance and results of additional Monte Carlo permutation tests is referred to Table 7.
+1.0 0
oo
OO
oo
oo
swc c
o
OO O
o
%>210um m
carbohydratess C0 2 production
NN
proteins growth
88
^w^w
^ ^^
^
cc
^^
O
E-content
survival
pigments
nn
0) )
O) )
UU
bacteriall
JJ
o
© OO o
p
oo
totall FA u
oo
F ^ ^
O
CC
oo )c)
OO
oo
C/N N
-1.0 0
-1.0 0
Axiss 1, eigenvalue 0.30
+1.0 0
individuall sediments may have disguished the influence of a set of biochemical constituentss of OM present in the sediments on the life history parameters of C. riparius when
thesee biochemical constituents were expressed on a DW basis. However, correlating
larvall growth to biochemical variables standardized based on OM content revealed the
influencee of organic matter composition directly. The effect of organic matter compositionn is independent of organic matter abundance and consequently is not influenced by
overalll food ingestion rate of the chironomid larvae.
Inn most studies, chemical parameters of sediments are expressed as portion of
DW.. If sedimentation traps are used to examine food sources of detritivorous inver-
59 9
ChapterChapter 3
tebrates,, the two different standardization procedures will likely not lead to the differencess found during the present study because organic content of the sedimented matter
iss expected to be high. However, as in the present study, sampled sediments often containn a broad range of mineral contents, potentially obfuscating a number of relationships
iff biochemical variables are standardized based on DW alone.
Growthh and survival of Chironomus riparius larvae did correlate with a few
variabless standardized based on DW, e.g. CO2 production as indicator of labile OM,
PUFF As, and pigments. The strong correlation between larval growth and PUF As may
havee arisen from the inability of animals to synthesize essential fatty acids (especially
co33 and co6 fatty acids; Brett and Miiller-Navarra 1997, Napolitano 1999). Therefore,
PUFAss have to be obtained from the diet, for instance from algae with high PUFA
contents.. Fatty acids in the sediments sampled during this study represented only a
smalll portion of the total amount of OM and, as such, PUFAs were a minor portion of
thee total fatty acids in the substrates. Consequently, it is probable that PUFAs were a
limitingg factor for larval growth in most of the sediments tested during this study. Labile
OMM was assessed with a microbial degradation assay. Microorganisms were chosen in
orderr to obtain a measure of overall digestibility of OM. Enzymatic assays are used to
Tablee 7. Summary of the PCA analyses. Percentage of total variance displayed on the first and
secondd axis and percentage of the total variance explained by larval performance (growth and
survival).. P-values of permutation tests.
biochemicall variables
standardizedd on
dryy weight
organic matter
49
30
%% of total variance
off sediment characteristics displayed on axis 1
off sediment characteristics displayed on axis 2
13
13
off sediment characteristics explaining larval performance
11
20
explainingg larval performance displayed on axis 1
28
76
explainingg larval performance displayed on axis 2
41
8
PP -value growth
0.035
<0.005
PP -value survival
0.050
<0.005
Permutationn test
60 0
ChironomidChironomid larvae growth on sediments
establishh the digestable fraction of specific components such as proteins (Dauwe et al.
I999a,b),I999a,b), but comparable assays that cover all food components are not available.
Judgedd from the good correlation between larval performance and labile OM the microbiall assay was adequate to determine the digestible fraction of OM. Similar to shortchainn PUF As, pigments may be considered as indicators of fresh algal material (Napolitanoo 1999), while CO2 production is an overall assessment of digestibility of OM.
Together,, correlations of PUFAs, pigments, and labile OM with chironomid larvae
growthh suggest that the nutritious and relatively easy digestible OM of algal origin was
ann important factor regulating growth of chironomid larvae in the field.
Organicc matter composition of sediments appeared to constitute a major factor
influencingg the growth and survival of Chironomus riparius larvae, in spite of the
complexx nature of this material. We base this conclusion on the high number of correlationss between the food quality parameters standardized on OM with larval growth and
survival,, and the high percentage of variance explained by ordination. For instance, P
wass found to be positively correlated with growth and survival. In an extensive number
off studies on daphnid crustaceans, both P and PUFAs have been identified as good
predictorss of food quality of living phytoplankton (e.g., Brett and Müller-Navarra 1997,
Gulatii and DeMott 1997). Carbohydrates were also found to be positively correlated
withh larval growth in spite of the diversity of polymeric sugars. The presently used
carbohydratee analysis not only measures simple sugars, but also complex sugars such as
cellulosee which are hardly digestible. At low food levels, carbohydrates are preferentiallyy used for maintenance of the body structures, leaving essential nutrients for
buildingg of new tissue (Roman 1983, Vos et al. 2000). A similar mechanism may have
aidedd the chironomid larvae to survive in the low nutritional conditions of some of the
sedimentss sampled during this study. Proteins are also a heterogeneous group, consistingg of a range of amino acids, some of which are essential and others non-essential
nutrients.. The chironomid larvae may have used proteins as source of essential amino
acidss (Cowey and Forster 1971, Cowie and Hedges 1996), of nitrogen, or of amino N
(Kreegerr et al. 1996).
Inn conclusion, the composition of OM in sediments strongly influences growth
andd survival of chironomid larvae. The presence of newly produced and labile OM,
indicatedd by pigments, PUFAs, and microbial mineralization rate, was strongly
61 1
ChapterChapter 3
correlatedd with larval growth. That population dynamics of benthic invertebrates in lake
sedimentss follow seasonal inputs from the pelagic zone, and that the response to algal
inputss varies with the species composition of algal blooms, has been previously
establishedd (Marsh and Tenore 1990, Goedkoop and Johnson 1996, Goedkoop et al.
1998).. Here, we stress the importance of the variable organic matter composition as a
keyy factor regulating the growth of detritivorous invertebrates. This study gives solid
evidencee that spatial and temporal differences in detritus quality are a major factor
regulatingg the growth dynamics of detritivores in soft bottoms.
Acknowledgements s
Partt of the project was financed by the Institute for Inland Water Management
andd Waste Water Treatment (RIZA), Lelystad, The Netherlands. We thank Ronald
Gylstraa and Edwin Peeters (Wageningen University) for their valuable comments on
thiss paper. Steven Arisz (UvA, Amsterdam, The Netherlands) greatly helped with the
fattyy acid analyses, by improving the GC analysis and with theoretical support. We are
endebtedd to Eric Boschker (NIOO, Yerseke, The Netherlands) who identified fatty acid
peakss with the MS. Joke Westerveld (UvA, Amsterdam, The Netherlands) supported the
CO22 analysis.
62 2