Please wait a minute...
Shopping Cart Email List Chinese
Advanced Search Fig/Tab
Frontiers of Earth Science

ISSN 2095-0195

ISSN 2095-0209(Online)

CN 11-5982/P

Postal Subscription Code 80-963

2018 Impact Factor: 1.205

Featured Articles  |  Most Downloaded  |  Most Reading
Online Submission Subscribe to Our RSS Content Feed
Front. Earth Sci.    2015, Vol. 9 Issue (1) : 137-151    https://doi.org/10.1007/s11707-014-0369-3
RESEARCH ARTICLE
Comparison of the spatial and temporal variability of macroinvertebrate and periphyton-based metrics in a macrophyte-dominated shallow lake
Lulu ZHANG,Jingling LIU(),Yi LI
State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
 Download: PDF(719 KB)   HTML
 Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks
Abstract

The influence of spatial differences, which are caused by different anthropogenic disturbances, and temporal changes, which are caused by natural conditions, on macroinvertebrates with periphyton communities in Baiyangdian Lake was compared. Periphyton and macrobenthos assemblage samples were simultaneously collected on four occasions during 2009 and 2010. Based on the physical and chemical attributes in the water and sediment, the 8 sampling sites can be divided into 5 habitat types by using cluster analysis. According to coefficients variation analysis (CV), three primary conclusions can be drawn : (1) the metrics of Hilsenhoff Biotic Index (HBI), Percent Tolerant Taxa (PTT), Percent dominant taxon (PDT), and community loss index (CLI), based on macroinvertebrates, and the metrics of algal density (AD), the proportion of chlorophyta (CHL), and the proportion of cyanophyta (CYA), based on periphytons, were mostly constant throughout our study; (2) in terms of spatial variation, the CV values in the macroinvertebrate-based metrics were lower than the CV values in the periphyton-based metrics, and these findings may be caused by the effects of changes in environmental factors; whereas, the CV values in the macroinvertebrate-based metrics were higher than those in the periphyton-based metrics, and these results may be linked to the influences of phenology and life history patterns of the macroinvertebrate individuals; and (3) the CV values for the functional-based metrics were higher than those for the structural-based metrics. Therefore, spatial and temporal variation for metrics should be considered when assessing applying the biometrics.
Keywords Baiyangdian Lake      biomonitoring      coefficient variation      structural metrics      functional metrics     
Corresponding Author(s): Jingling LIU   
Online First Date: 12 June 2014    Issue Date: 04 February 2015
 Cite this article:   
Lulu ZHANG,Jingling LIU,Yi LI. Comparison of the spatial and temporal variability of macroinvertebrate and periphyton-based metrics in a macrophyte-dominated shallow lake[J]. Front. Earth Sci., 2015, 9(1): 137-151.
 URL:  
https://academic.hep.com.cn/fesci/EN/10.1007/s11707-014-0369-3
https://academic.hep.com.cn/fesci/EN/Y2015/V9/I1/137
Sample site Coordinates Land-use characteristics
S1 N38.9044° E115.9238° Greatly influenced by wastewater inflow from Baoding City
S2 N38.9045° E115.9348° Greatly influenced by wastewater inflow from the Fu River, minor aquaculture, small village
S3 N38.9177° E116.0114° Major aquaculture, dense village
S4 N38.9407° E115.9997° Minor aquaculture
S5 N38.9021° E116.0804° The outlet of the Baiyangdian, minor human disturbances
S6 N38.8604° E116.0282° Major aquaculture, near to village
S7 N38.8249° E116.0102° Minor aquaculture, small village
S8 N38.8470° E115.9506° Major aquaculture, dense village
Tab.1  The anthropogenic disturbance levels of the sampling sites
Sample site T/°C pH DO/(mg·L–1) N O 3 - /(mg·L–1) N O 2 - /(mg/L) N H 4 + –N/(mg·L–1) TN/(mg·L–1) P O 4 3 - –P/(mg·L–1) TP/(mg·L–1) S O 4 2 - /(mg·L–1) Cl–/(mg·L–1) TOC/(mg·L–1)
S1 20.75 7.90 4.15 2.14 0.24 7.59 10.80? 0.60 0.41 169.93? 160.85 5.35
S2 19.88 7.90 4.75 2.02 0.21 6.69 9.05 0.27 0.22 152.26? 143.96 6.35
S3 20.63 8.13 6.95 0.69 0.13 2.55 5.76 0.42 0.19 142.67? 163.70 9.58
S4 22.80 8.05 8.93 0.20 ND 1.54 2.51 0.03 0.07 99.64 135.21 10.85?
S5 21.18 8.13 7.10 0.67 0.05 1.34 1.28 0.02 0.03 78.20 118.08 8.20
S6 20.70 8.10 8.63 0.73 ND 1.67 1.94 0.03 0.06 88.27 141.23 8.85
S7 20.40 8.33 7.93 0.24 ND 1.51 1.92 0.02 0.04 90.51 125.71 10.45?
S8 21.13 8.13 7.35 0.67 0.05 2.62 3.68 0.23 0.16 156.355 148.06 8.95
Tab.2  General water quality characteristics at the 8 sampling sites
Sample site Grain size (Gr)/% TOCs DOC TNs TPs
Gr<2 μm 2 μm<Gr<50 μm Gr>50 μm /(mg·kg–1) /(mg·kg–1) /(mg·kg–1) /(mg·kg–1)
S1 0.39 64.85 34.76 7.45 0.19 3.20 2.69
S2 0.27 60.83 38.90 9.47 0.35 1.81 1.75
S3 0.64 54.23 45.13 9.16 0.16 1.71 2.28
S4 0.08 42.78 57.14 37.80 0.27 1.83 1.38
S5 0.04 41.95 58.01 13.70 0.30 1.32 1.29
S6 0.00 27.48 72.52 25.60 0.15 2.14 1.12
S7 0.00 24.62 75.38 52.10 0.34 1.92 1.44
S8 0.70 56.28 43.02 27.05 0.24 2.20 1.64
Tab.3  Physical-chemical variables of the sediment at the 8 sampling sites
Metric type Metric Definition References
Structural Metrics (10) Tolerance metrics Hilsenhoff biotic index (HBI) ∑ i p i t i , where pi is the proportion of individuals in taxon i and ti is the PTV for taxon i Hilsenhoff, 1987; Plafkin et al., 1989
Percent tolerant taxa (PTT) (Number of tolerant taxa/all taxa) *100 Blocksom et al., 2002
Percent intolerant taxa (PIT) (Number of intolerant taxa/all taxa) *100 Lewis et al., 2001;
Richness metrics Taxa richness (TR) Total number of distinct taxa in the sample Barbour et al., 1996
Number of Diptera taxa (NDT) Number of Diptera taxa Blocksom et al., 2002
Composition metrics Percent non-insects (PNI) (Number of non-insects taxa/all taxa) *100 Mason et al., 1971;Lewis et al., 2001;Blocksom et al., 2002
Percent chironomidae (PC) (Number of chironomidae taxa/all taxa) *100 Brinkhurst et al., 1968;Trigal et al., 2006
Percent dominant taxon (PDT) (Number of individuals in the dominant taxon / total individuals in the sample) *100 Plafkin et al., 1989; Trigal et al., 2006
Community loss index (CLI) C L I = d - a e , where a is the number of taxa common to both stations; d is the total number of taxa percent at a reference station; and e is the total number of taxa percent at the station of comparison Plafkin et al., 1989;Lewis et al., 2001
Community similarity index (CSI) C S I = 2 C A + B , where A is the total number of taxa at reference station; B is the total number of taxa at comparison station; and C is the number of taxa common to both stations Plafkin et al., 1989;Lewis et al., 2001
Functional metrics (2) Trophic metrics Percent collector-gatherer taxa (PCGT) (Number of collector-gatherers taxa/all taxa)*100 Blocksom et al., 2002;Trigal et al., 2006
Percent predators (PP) (Number of predators taxa/all taxa)*100 Blocksom et al., 2002;Trigal et al., 2006
Tab.4  The 12 metrics in the macroinvertebrate community of Baiyangdian Lake
Metrics type Metrics Metrics References
Structural metrics (9) Algal density (AD)/(104 cells·cm-2) Sierra and Gomez, 2007
Chlorophyll a (Chl a)/(μg·cm-2) Ma et al., 2011
Chlorophyll b (Chl b)/(μg·cm-2) Ma et al., 2011
Chlorophyll c (Chl c)/(μg·cm-2) Ma et al., 2011
Chlorophyll b/ Chlorophyll a (Chl b/a) Ma et al., 2011
Chlorophyll c/ Chlorophyll a (Chl c/a) Ma et al., 2011
The proportion of bacillariophyta (BAC)/% Ma et al., 2011
The proportion of chlorophyta (CHL)/% Ma et al., 2011
The proportion of cyanophyta (CYA)/% Ma et al., 2011
Functional metrics (5) Alkaline phosphatase (APA)/(nmol·cm-2·h-1) Findlay and Sinsabaugh, 2006
β- Glucose Glycosidase (GLU)/(nmol·cm-2·h-1) Findlay and Sinsabaugh, 2006
Leucine amino peptide enzymes (LEU) /(nmol·cm-2·h-1) Findlay and Sinsabaugh, 2006
Polysaccharide content (PSC)/(mg·cm-2) Ma et al., 2011
Ash-free dry weight (AFDW)/(μg·cm-2) Fellows et al., 2006
Tab.5  The 14 metrics in the periphyton community of Baiyangdian Lake
Fig.1  The cluster results of sampling sites based on physical and chemical parameters of water and sediment.
Fig.2  Among-habitat and temporal variations of the relative abundance of macroinvertebrate taxa collected from 5 habitats on each sampling occasion (PTT= percent tolerant taxa; PIT=percent intolerant taxa; PFT=percent facultative taxa).
Phylum Scientific name Kinds of taxa Habitat 1 Habitat 2 Habitat 3 Habitat 4 Habitat 5
S1 S2 S8 S3 S5 S4 S6 S7
Annelida Whitmania pigra Facultative taxa o
Mollusca Cipangopaludia chinensis Facultative taxa X X X X X X
Cipangopaludina cathayensis Facultative taxa o + o
Bellamya purificata Facultative taxa X X X XX O
Radix sp. Tolerant taxa o o o
Bithynia sp. Tolerant taxa X X X + O
Arthropoda Caridina denticulata Intolerant taxa o O o
Eriocheir sinensis Tolerant taxa o
Tokunagayusurika akamushi Tolerant taxa O + O X XX
Tendipes insolita Tolerant taxa + O
Chironomus plumosus Tolerant taxa XX XX X
Glyptotendipes sp. Tolerant taxa X O
Pantala flarescens Tolerant taxa o
Tab.6  Benthic macroinvertebrate composition of Baiyangdian Lake
Metrics Coefficients of among-habitat variability/%
CV(h)m Jun 09 CV(h)m Aug 09 CV(h)m Nov 09 CV(h)m Apr 10 CVh-month
HBI 23.7 29.5 26.5 27.4 26.7
PTT 29.1 63.9 30.3 36.0 39.8
PIT 120.2 223.6 120.1 114.1 144.5
TR 95.8 28.1 70.8 54.3 62.2
NDT 81.4 68.2 60.1 53.4 65.7
PNI 59.5 97.9 104.0 102.5 90.9
PC 90.7 99.9 59.4 72.7 80.6
PDT 29.3 30.1 31.4 25.2 29.0
CLI 23.1 49.4 61.2 62.2 48.9
CSI 46.3 92.7 64.9 83.9 71.9
PCGT 65.9 73.2 71.9 81.4 73.1
PPT 56.7 69.8 72.4 76.9 69.0
Tab.7  Coefficients of variation expressed as percentages for the 12 selected biologic metrics in the macroinvertebrate community
Fig.3  Among-habitat and temporal changes of the algal composition in the periphyton community and in 5 habitats investigated.
Metrics Among-habitat variability
CV(h)m Jun 09 CV(h)m Aug 09 CV(h)m Nov 09 CV(h)m Apr 10 CVh-month
AD 47.8 49.5 36.7 26.7 40.2
Chl a 74.5 57.7 48.3 43.1 55.9
Chl b 96.4 76.4 72.7 79.7 81.3
Chl c 44.7 65.6 46.4 20.2 44.2
Chl b/a 37.7 50.1 37.9 48.5 43.6
Chl c/a 66.9 74.6 85.5 48.5 68.9
BAC 29.0 25.1 60.5 35.4 37.5
CHL 4.0 6.0 7.1 14.1 7.8
CYA 11.3 21.3 45.5 22.9 25.3
APA 73.3 66.2 55.9 39.3 58.7
GLU 71.8 64.3 91 40 66.8
LEU 26.7 53.9 77 64 55.4
PSC 31.0 91.2 93.2 88.4 76.0
AFDW 82.4 33.6 62.2 36.9 53.8
Tab.8  Coefficients of variation expressed as percentages for the 14 selected biologic metrics of the periphyton community
Fig.4  Seasonal variations in the total number and total density (individuals/m2) of the macroinvertebrate taxa in the lake.
Metrics Seasonal temporal variability
CV(m)h Habitat 1 CV(m)h Habitat 2 CV(m)h Habitat 3 CV(m)h Habitat 4 CV(m)h Habitat 5 CVs
HBI 5.8 6.6 5.6 3.8 2.9 4.9
PTT 16.2 7.9 5.4 37.9 15.2 16.5
PIT – – 67.8 30.6 67.2 55.2
TR 127.7 81.6 8.9 11.8 23.5 50.7
NDT 22.2 15.4 27.2 40.0 71.9 35.3
PNI 200.0 200.0 63.4 25.8 44.7 106.8
PC 18.0 22.2 45.0 87.4 87.4 52.0
PDT 3.1 2.9 6.1 4.6 5.8 4.5
CLI 36.0 30.6 24.6 15.6 26.0 26.6
CSI 200.0 84.4 18.7 15.9 17.3 67.3
PCGT 200.0 19.7 27.2 17.0 32.6 59.3
PPT 200.0 42.8 35.9 27.6 41.2 69.5
Tab.9  Coefficients of variation expressed as percentages for the 12 selected biologic metrics of the macroinvertebrate community
Fig.5  Seasonal variations of the algae composition and algae density of the periphyton community in the lake.
Metrics Seasonal temporal variability
CV(m)h Habitat 1 CV(m)h Habitat 2 CV(m)h Habitat 3 CV(m)h Habitat 4 CV(m)h Habitat 5 CVs
AD 45.5 34.4 29.4 26.9 42.3 35.7
Chl a 117.7 114.2 135.7 120.7 136.2 124.9
Chl b 119.0 118.3 132.3 156.9 135.7 132.4
Chl c 77.6 129.9 109 99.3 121.6 107.5
Chl b/a 39.4 50.3 52.7 72.3 55.1 54.0
Chl c/a 68.6 65.7 27.9 23.5 37.6 44.7
BAC 31.9 70.1 59.2 60.8 49.5 54.3
CHL 7.0 4.8 4.3 13.4 5.9 7.1
CYA 28.8 35.1 35.6 64.7 38.7 40.6
APA 56.4 80.0 50.3 59.5 47.7 58.8
GLU 104.6 112.1 98.4 116.2 75.3 101.3
LEU 58.0 72.8 40 105.5 65.0 68.3
PSC 148.3 56.3 48.9 53.9 77.4 77.0
AFDW 69.2 73.5 46.6 58.6 39.8 57.5
Tab.10  Coefficients of variation expressed as percentages for the 14 selected biologic metrics of the periphyton community
1 An K G, Park S S, Shin J Y (2002). An evaluation of a river health using the index of biological integrity along with relations to chemical and habitat conditions. Environ Int, 28(5): 411–420
pmid: 12437291
2 Angermeier P L, Smogor R A, Stauffer J R (2000). Regional frameworks and candidate metrics for assessing biotic integrity in mid-Atlantic highland streams. T Am Fish Soc, 129(4): 962–981
3 Barbour M T, Gerritsen J, Griffith G E, Frydenborg R, McCarron E, White J S, Bastian M L (1996). A framework for biological criteria for Florida streams using benthic macroinvertebrates. J N Am Benthol Soc, 15: 185–211
4 Barbour M T, Gerritsen J, Snyder B D, Stribling J B (1999). Rapid Bioassessment Protocols for Use in Streams and Rivers: Periphyton, Benthic Macroinvertebrates, and Fish (2nd ed). EPA 841/B-99/002. US Environmental Protection Agency, Washington, D.C.
5 Bazzanti M, Seminara M (1995). Eutrophication in a deep, meromictic lake (Lake Albano, Central Italy): spatial-temporal patterns of profundal benthic community as a tool for assessing environmental stress in the hypolimnion. Limnologica Jena, 25(11): 21–31
6 Beck M W, Hatch L K (2009). A review of research on the development of lake indices of biotic integrity. Environ Rev, 17: 21–44
7 Beck M W, Hatch L K, Vondracek B, Valley R D (2010). Development of a macrophyte-based index of biotoc integrity for Minnesota Lakes. Ecol Indic, 10(5): 968–979
8 Berkman H E, Rabeni C F (1987). Effects of siltation on stream fish communities. Environ Biol Fishes, 18: 285–294
9 Biggs J, Williams P, Whitfield M, Nicolet P, Weatherby A (2005). 15 years of ponds assessment in Britain: results and lessons learned from the work of Pond Conservation. Aquat Conserv: Mar Freshw Ecosyst, 15(6): 693–714
10 Blocksom K A, Kurtenbach J P, Klemm D J, Fulk F A, Cormier S M (2002). Development and evaluation of the Lake Macroinvertebrate Integrity Index (LMII) for New Jersey lakes and reservoirs. Environ Monit Assess, 77(3): 311–333
pmid: 12194418
11 Borja á (2005). The European Water Framework Directive: a challenge for nearshore, coastal and continental shelf research. Cont Shelf Res, 25(14): 1768–1783
12 Borja A, Franco J, Pérez V (2000). A marine biotic index to eatablish the ecological quality of soft-bottom benthos within European estuarine and coastal environments. Mar Pollut Bull, 40(12): 1100–1114
13 Brinkhurst R O, Hamilton A L, Herrington H B (1968). Components of the bottom fauna of the St. Lawrence, Great Lakes. No. PR33, Great Lakes Institute, University of Toronto, Toronto, ON, Canada, 50
14 Brodersen K P, Dall P C, Lindegaard C (2008). The fauna in the upper stony littoral of Danish lakes: macroinvertebrates as trophic indicators. Freshw Biol, 39: 577–592
15 Cheruvelil K S, Sorano P A, Madsen J D, Roberson M J (2002). Plant architecture and epiphytic macroinvertebrate communities: the role of an exotic dissected macrophyte. J N Am Benthol Soc, 21: 261–277
16 China Bureau of Environmental Protection (CBEP) (2002). Methods for monitoring and analysis of water and wastewater (4th ed). Beijing: China Environmental Science Press, 246–248 (in Chinese)
17 Chinese Academy of Sciences (CAS) (1978). Soil map of China (edited by the Nanjing Institute of Soil Science, Chinese Academy of Sciences). Beijing: Cartographic Publishing House (digital version published 1996 by State Key Laboratory of Resources and Environment Information System, Chinese Academy of Sciences, Beijing)
18 Costanza R, d’Arge R, De Groot R, Farber S, Grasso M, Hannon B, Limburg K, Naeem S, O'Neill R V, Paruelo J, Raskin R G, Sutton P, van den Belt M (1998). The value of the world’s ecosystem services and natural capital. Ecol Econ, 25(1): 3–15
19 Cyr H, Downing J A (1988). Empirical relationships of phytomacrofaunal abundance to plant biomass and macrophyte bed characteristics. Can J Fish Aquat Sci, 45: 976–984
20 De Lange H J, De Haas E M, Maas H, Peeters E T H M (2005). Contaminated sediments and bioassay responses of three macroinvertebrates, the midge larva Chironomus riparius, the water louse Asellus aquaticus and the mayfly nymph Ephoron virgo. Chemosphere, 61(11): 1700–1709
pmid: 15885739
21 De Szalay F A, Resh V H (2000). Factors influencing macroinvertebrate colonization of seasonal wetlands: responses to emergent plant cover. Freshw Biol, 45(3): 295–308
22 Diehl S (1992). Fish predation and benthic community structure: the role of omnivory and habitat complexity. Ecology, 73(5): 1646–1661
23 Fano E A, Mistri M, Rossi R (2003). The ecofunctional quality index (EQI): a new tool for assessing lagoonal ecosystem impairment. Estuar Coast Shelf S, 56(3–4): 709–716
24 Fellows C, Clapcott J, Udy J, Bunn S, Harch B, Smith M, Davies P (2006). Benthic metabolism as an indicator of stream ecosystem health. Hydrobiologia, 572(1): 71–87
25 Findlay S, Sinsabaugh R L (2006). Large-scale variation in subsurface stream biofilms: a cross-regional comparison of metabolic function and community similarity. Microb Ecol, 52(3): 491–500
pmid: 16909347
26 Gabriels W, Lock K, De Pauw N, Goethals P L M (2010). Multimetric Macroinvertebrate Index Flanders (MMIF) for biological assessment of rivers and lakes in Flanders (Belgium). Limnologica-Ecology Management of Inl Waters, 40(3): 199–207
27 Gérard C (2000). Dynamics and structure of a benthic macroinvertebrate community in a lake after drought. J Freshwat Ecol, 15: 65–69
28 Gilinsky E (1984). The role of fish predation and spatial heterogeneity in determining benthic community structure. Ecology, 65(2): 455–468
29 Gold C, Feurtet-Mazel A, Coste M, Boudou A (2002). Field transfer of periphytic diatom communities to assess short-term structural effects of metals (Cd, Zn) in rivers. Water Res, 36(14): 3654–3664
pmid: 12230212
30 Griffith M B, Hill B H, McCormick F H, Kaufmann P R, Herlihy A T, Selle A R (2005). Comparative application of indices of biotic integrity based on periphyton, macroinvertebrates, and fish to southern Rocky Mountain streams. Ecol Indic, 5(2): 117–136
31 Hamalainen H, Luotonen H, Koskenniemi E, Liljaniem P (2003). Inter-annual variation in macroinvertebrate communities in a shallow forest lake in eastern Finland during 1990–2001. Hydrobiologia, 506/509: 389–397
32 Heino J (2000). Lentic macroinvertebrate assemblage structure along gradients in spatial heterogeneity, habitat size and water chemistry. Hydrobiologia, 418: 229–242
33 Hill B H, Herlihy A T, Kaufmann P R, Stevenson J R, Mccormick F H, Johnson C B (2000). Use of periphyton assemblage data as an index of biotic integrity. J N Am Benthol Soc, 19: 50–67
34 Hilsenhoff W L (1987). An improved biotic index of organic stream pollution. Great Lakes Entomol, 30: 31–39
35 Hornung J P, Foote A L (2006). Aquatic invertebrate responses to fish presence and vegetation complexity in western boreal wetlands with implications for waterbird productivity. Wetlands, 26: 1–12
36 Institute of Soil Science, Chinese Academy of Sciences (1978). Physical and Chemical Analysis of Soil. Shanghai: Shanghai Science and Technology Press, 132–136 (In Chinese)
37 Iwaniec D M, Childers D L, Rondeau D, Madden C J, Saunders C (2006). Effects of hydrologic and water quality drivers on periphyton dynamics in the southern Everglades. Hydrobiologia, 569: 223–235
38 Johnson R K (1998). Spatiotemporal variability of temperate lake macroinvertebrate communities: detection of impact. Ecol Appl, 8(1): 61–70
39 Jongman R H, Ter Braak C J F, Van Tongeren O F R (1987). Data analysis in community and landscape ecology, Pudoc, Wageningen, 91–173
40 Karr J R (1981). Assessment of biotic integrity using fish communities. Fisheries (Bethesda, Md), 6: 21–27
41 Kashian D R, Burton T M (2000). A comparison of macroinvertebrates of two Great Lakes coastal wetlands: testing potential metrics for and index of ecological integrity. J Great Lakes Res, 26(4): 460–481
42 Kelly M, Bennion H, Burgess A, Ellis J, Juggins S, Guthrie R, Jamieson J, Adriaenssens V, Yallop M (2009). Uncertainty in ecological status assessments of lakes and rivers using diatoms. Hydrobiologia, 633: 5–15
43 Kireta A R, Reavie E D, Sgro G V, Angradi T R, Bolgrien D W, Hill B H, Jicha T M (2012). Planktonic and periphytic diatoms as indicators of stress on great rivers of the United States: testing water quality and disturbance models. Ecol Indic, 13(1): 222–231
44 Kornijów R (1989). Seasonal changes in the macrofauna living on submerged plants in two lakes of different trophy. Arch Hydrobiol, 117: 49–61
45 Kr?ncke I, Reiss H (2010). Influence of macrofauna long-term natural variability on benthic indices used in ecological quality assessment. Mar Pollut Bull, 60(1): 58–68
pmid: 19796775
46 Ledger M E, Hildrew A G (1998). Temporal and spatial variation in the epilithic biofilm of an acid stream. Freshwater Biol, 40(4): 655–670
47 Lewis P A, Klemm D J, Thoeny W T (2001). Perspectives on use of a multimetric lake bioassessment integrity index using benthic macroinvertebrates. Northeastern Naturalist, 8(2): 233–246
48 Lu R K (2000). Methods for Soil Agricultural Chemistry Analysis. Beijing: Chinese Agricultural Science and Technology Press
49 Lunde K B, Resh V H (2012). Development and validation of a macroinvertebrate index of biotic integrity (IBI) for assessing urban impacts to Northern California freshwater wetlands. Environ Monit Assess, 184(6): 3653–3674
pmid: 21823050
50 Ma M Y, Liu J L, Wang X M (2011). Biofilms as potential indicators of macrophyte-dominated lake health. Ecotoxicology, 20(5): 982–992
pmid: 21503613
51 Mason W T, Lewis P A Jr, Anderson J B (1971). Maconinvertebrate collections and water quality in the Ohio River Basin, 1963–1967. Office of Technical Programs, AQC Laboratory, Water Quality Office, US Environmental Protection Agency, Cincinnati, OH. 52 pp., Appendix A–1 to A–65
52 Melaas C L, Zimmer K D, Butler M G, Hanson M A (2001). Effects of rotenone on aquatic invertebrate communities in prairie wetlands. Hydrobiologia, 459(1–3): 177–186
53 Moore M J C, Langrehr H A, Angradi T R (2012). A submersed macrophyte index of condition for the Upper Mississippi River. Ecol Indic, 13(1): 196–205
54 O’Connor R J, Walls T E, Hughes R M (1998). Using multiple taxonomic groups to index the ecological condition of lakes. Environ Monit Assess, 61: 207–228
55 Plafkin J L, Barbour M T, Porter K D, Gross S K, Hughes R M (1989). Rapid bioassessment protocols for use in streams and rivers: benthic macroinvertebrates and fish. EPS/440/4–89/001. US Environmental Protection Agency, Washington, DC. 1–1 to 8–19 pp., Appendices A–1 to 1–42
56 Rennie M D, Jackson L J (2005). The influence of habitat complexity on littoral invertebrate distributions: pattern differs in shallow prairie lakes with and without fish. Can J Fish Aquat Sci, 62: 2088–2099
57 Rothrock P E, Simon T P, Stewart P M (2008). Development, calibration, and validation of a littoral zone plant index of biotic integrity (PIBI) for lacustrine wetlands. Ecol Indic, 8(1): 79–88
58 Seele J, Mayr M, Staab F, Raeder U (2000). Combination of two indication systems in pre-alpine lakes-diatom index and macrophyte index. Ecol Model, 130(1–3): 145–149
59 Sierra M V, Gomez N (2007). Structual characteristics and oxygen consumption of the epipelic biofilm in three lowland streams exposed to different land uses. Water Air Soil Pollut, 186(1): 115–127
60 Sorace A, Formichetti P, Boano A, Andreani P, Gramegna C, Mancini L (2002). The presence of a river bird, the dipper, in relation to water quality and biotic indices in central Italy. Environ Pollut, 118(1): 89–96
pmid: 11996386
61 Tangen B A, Bulter M G, Michael J E (2003). Weak correspondence between macroinvertebrate assemblages and land use in Prairie Pothole Region wetlands. USA. Wetlands, 23: 104–115
62 Tipping B, Bass J A B, Hardie D, Haworth E Y, Hurley M A, Wills G (2002). Biological responses to the reversal of acidification in surface waters of the English Lake District. Environ Pollut, 116(1): 137–146
pmid: 11817360
63 Tolonen K T, H?m?l?inen H, Holopainen I J, Karjalainen J (2001). Influences of habitat type and environmental variables on littoral macroinvertebrate communities in a large lake system. Arch Hydrobiol, 152: 39–67
64 Tolonen K T, H?m?l?inen H, Holopainen I J, Mikkonen K, Karjalainen J (2003). Body size and substrate association of littoral insects in relation to vegetation structure. Hydrobiologia, 499(1–3): 179–190
65 Townsend C R, Hildrew A G (1994). Species traits in relation to a habitat templet for river systems. Freshw Biol, 31(3): 265–275
66 Trigal C, García-Criado F, Fernández-Aláez C (2006). Among-habitat and temporal variability of selected macroinvertebrate based metrics in a Mediterranean shallow lake (NW Spain). Hydrobiologia, 563(1): 371–384
67 Trigal C, García-Criado F, Fernández-Aláez C (2007). Macroinvertebrate communities of mediterranean ponds (North Iberian Plateau): importance of natural and human-induced variability. Freshw Biol, 52(10): 2042–2055
68 USEPA (1998a). Environmental monitoring and assessment program-surface waters: field operations and methods for measuring the ecological conditions of wadeable streams, EPA/620/R-94/004F, U.S.EPA, Research Triangle Park, North Carolina
69 USEPA (1998b). Lake and reservoir bioassessment and biocriteria: Technical Guidance Document, EPA 841-B-98–007, USEPA, Washington, D.C.
70 USEPA (1999). Rapid bioassessment protocols for use in wadeable streams and rivers, EPA 841-B-99–002, U.S.EPA, Washington, D.C.
71 Wallace J B, Anderson N H (1996). Habitat, life history, and behavioral adaptations of aquatic insects. In: Merritt RW, Cummins KW, eds. An Introduction to the Aquatic Insects of North America(3rd ed). Dubuque: Kendall/Hunt Publishing Co., 41–73
72 Wefering F M, Danielson L E, White N M (2000). Using the AMOEBA approach to measure progress toward ecosystem sustainability within a shellfish restoration project in North Carolina. Ecol Model, 130(1–3): 157–166
73 White J, Irvine K (2003). The use of littoral mesohabitats and their macroinvertebrate assemblages in the ecological assessment of lakes. Aquat Conserv, 13(4): 331–351
74 Xu F L, Tao S, Dawson R W, Li P G, Cao J (2001). Lake ecosystem health assessment: indicators and methods. Water Res, 35(13): 3157–3167
pmid: 11487113
75 Zhang L L, Liu J L, Yang Z F, Li Y, Yang Y (2013). Integrated ecosystem health assessment of a macrophyte-dominated lake. Ecol Model, 242: 141–152
76 Zhou Q F, Zhang J B, Fu J J, Shi J B, Jiang G B (2008). Biomonitoring: an appealing tool for assessment of metal pollution in the aquatic ecosystem. Anal Chim Acta, 606(2): 135–150
pmid: 18082645
77 Zimmer K D, Hanson M A, Butler M G, Duffy W G (2001). Size distribution of aquatic invertebrates in two prairie wetlands, with and without fish, with implications for community production. Freshw Biol, 46(10): 1373–1386
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed