Microbial Community Responses to Contaminants and the Use of Molecular Techniques



Human activities threaten global ecosystems through the introduction of a range of contaminants. The potential effects of contaminants are commonly tested on organisms, or cell lines, in separate tests: one toxicant and one species at a time. The results have limited predictive capacity in complex ecosystems, and when they are used to calculate guideline toxicity values, multiple safety factors must be applied to mitigate this uncertainty. Community responses can provide a more realistic assessment of contaminant effects but may be more difficult to detect and interpret. In recent years, advances in molecular approaches have significantly improved our ability to investigate community responses at the micro scale. Microbial groups represent a major source of biomass and chemical activity in many ecosystems and they include many of the most chemically sensitive organism groups. Traditional microbial ecotoxicological studies have either measured impacts on diversity or on ecosystem function, with very few attempting to quantify both diversity and function at the same time. Molecular approaches to microbial ecotoxicology have the potential to reveal novel elements of ecosystem change such as the mechanisms behind functional responses to contaminants. This is crucial to understand because structural changes do not necessarily translate to a change in function and vice versa. Increasing our understanding of stress-related structural and functional changes in microbial groups that drive global biogeochemical cycles will enable highly relevant and sensitive predictions of the impact of contaminants on ecosystem health.


Molecular methods Whole-community assessment Omics Contaminants Diversity Function 



The authors received funding from the Australian Research Council through LP130100364 awarded to ELJ. We thank two anonymous reviewers for their comments, which helped to improve this chapter.


  1. Allison SD, Martiny JBH (2008) Resistance, resilience, and redundancy in microbial communities. Proc Natl Acad Sci 105:11512–11519CrossRefPubMedPubMedCentralGoogle Scholar
  2. Ancion PY, Lear G, Lewis GD (2010) Three common metal contaminants of urban runoff (Zn, Cu & Pb) accumulate in freshwater biofilm and modify embedded bacterial communities. Environ Pollut 158:2738–2745. doi: 10.1016/j.envpol.2010.04.013 CrossRefPubMedGoogle Scholar
  3. Antizar-Ladislao B (2010) Bioremediation: working with bacteria. Elements 6:389–394. doi: 10.2113/gselements.6.6.389 CrossRefGoogle Scholar
  4. Araújo CVM, Tornero V, Lubián LM et al (2010) Ring test for whole-sediment toxicity assay with—a—benthic marine diatom. Sci Total Environ 408:822–828. doi: 10.1016/j.scitotenv.2009.10.018 CrossRefPubMedGoogle Scholar
  5. Arias-Estévez M, López-Periago E, Martínez-Carballo E et al (2008) The mobility and degradation of pesticides in soils and the pollution of groundwater resources. Agric Ecosyst Environ 123:247–260. doi: 10.1016/j.agee.2007.07.011 CrossRefGoogle Scholar
  6. Aylagas E, Borja Á, Rodríguez-Ezpeleta N (2014) Environmental status assessment using DNA metabarcoding: towards a genetics based marine biotic index (gAMBI). PLoS ONE 9:e90529. doi: 10.1371/journal.pone.0090529 CrossRefPubMedPubMedCentralGoogle Scholar
  7. Baird DJ, Hajibabaei M (2012) Biomonitoring 2.0: a new paradigm in ecosystem assessment made possible by next-generation DNA sequencing. Mol Ecol 21:2039–2044CrossRefPubMedGoogle Scholar
  8. Bier RL, Bernhardt ES, Boot CM et al (2015) Linking microbial community structure and microbial processes: an empirical and conceptual overview. FEMS Microbiol Ecol 91:1–11. doi: 10.1093/femsec/fiv113 CrossRefGoogle Scholar
  9. Birch GF (1996) Sediment-bound metallic contaminants in Sydney’s estuaries and adjacent offshore, Australia. Estuar Coast Shelf Sci 42:31–44. doi: 10.1006/ecss.1996.0003 CrossRefGoogle Scholar
  10. Birch GF, Eyre BD, Taylor SE (1999) The distribution of nutrients in bottom sediments of Port Jackson (Sydney Harbour), Australia. Mar Pollut Bull 38:1247–1251CrossRefGoogle Scholar
  11. Birch GF, Taylor SE (1999) Source of heavy metals in sediments of the Port Jackson estuary, Australia. Sci Total Environ 227:123–138. doi: 10.1016/S0048-9697(99)00007-8 CrossRefGoogle Scholar
  12. Bissett A, Burke C, Cook PLM, Bowman JP (2007) Bacterial community shifts in organically perturbed sediments. Environ Microbiol 9:46–60. doi: 10.1111/j.1462-2920.2006.01110.x CrossRefPubMedGoogle Scholar
  13. Bissett A, Richardson AE, Baker G et al (2010) Life history determines biogeographical patterns of soil bacterial communities over multiple spatial scales. Mol Ecol 19:4315–4327. doi: 10.1111/j.1365-294X.2010.04804.x CrossRefPubMedGoogle Scholar
  14. Blanck H, Dahl B (1996) Pollution-induced community tolerance (PICT) in marine periphyton in a gradient of tri-n-butyltin (TBT) contamination. Aquat Toxicol 35:59–77. doi: 10.1016/0166-445X(96)00007-0 CrossRefGoogle Scholar
  15. Blanck H, Wängberg S-Å (1988) Induced community tolerance in marine periphyton established under arsenate stress. Can J Fish Aquat Sci 45:1816–1819CrossRefGoogle Scholar
  16. Bourlat SJ, Borja Á, Gilbert JA et al (2013) Genomics in marine monitoring: new opportunities for assessing marine health status. Mar Pollut Bull 74:19–31. doi: 10.1016/j.marpolbul.2013.05.042 CrossRefPubMedGoogle Scholar
  17. Breitholtz M, Rudén C, Ove Hansson S, Bengtsson BE (2006) Ten challenges for improved ecotoxicological testing in environmental risk assessment. Ecotoxicol Environ Saf 63:324–335. doi: 10.1016/j.ecoenv.2005.12.009 CrossRefPubMedGoogle Scholar
  18. Browne MA, Crump P, Niven SJ et al (2011) Accumulation of microplastic on shorelines worldwide: sources and sinks. Environ Sci Technol 45:9175–9179. doi: 10.1021/es201811s CrossRefPubMedGoogle Scholar
  19. Bruins MR, Kapil S, Oehme FW (2000) Microbial resistance to metals in the environment. Ecotoxicol Environ Saf 45:198–207. doi: 10.1006/eesa.1999.1860 CrossRefPubMedGoogle Scholar
  20. Brunet RC, Garcia-Gil LJ (1996) Sulfide-induced dissimilatory nitrate reduction to ammonia in anaerobic freshwater sediments. FEMS Microbiol Ecol 21:131–138. doi: 10.1111/j.1574-6941.1996.tb00340.x CrossRefGoogle Scholar
  21. Buikema AL, Niederlehner BR, Cairns J (1982) Biological monitoring part IV-Toxicity testing. Water Res 16:239–262. doi: 10.1016/0043-1354(82)90188-9 CrossRefGoogle Scholar
  22. Chapman PM (2002) Integrating toxicology and ecology: putting the “eco” into ecotoxicology. Mar Pollut Bull 44:7–15. doi: 10.1016/S0025-326X(01)00253-3 CrossRefPubMedGoogle Scholar
  23. Chariton A, Simpson S, Roach A, Batley G (2010) The influence of environmental variable choice on interpreting the spatial patterns of sediment contaminants and their relationships with benthic communities. Mar Freshw Res 61:1109–1122CrossRefGoogle Scholar
  24. Clark GF, Kelaher BP, Dafforn KA et al (2015) What does impacted look like? High diversity and abundance of epibiota in modified estuaries. Environ Pollut 196:12–20. doi: 10.1016/j.envpol.2014.09.017 CrossRefPubMedGoogle Scholar
  25. Clements WH, Rohr JR (2009) Community responses to contaminants: using basic ecological principles to predict ecotoxicological effects. Environ Toxicol Chem 28:1789. doi: 10.1897/09-140.1 CrossRefPubMedGoogle Scholar
  26. Dafforn KA, Baird DJ, Chariton AA et al (2014) Faster, higher and stronger? The pros and cons of molecular faunal data for assessing ecosystem condition. Adv Ecol Res 51:1–40. doi: 10.1016/B978-0-08-099970-8.00003-8 CrossRefGoogle Scholar
  27. Dafforn KA, Johnston EL, Ferguson A et al (2016) Big data opportunities and challenges for assessing multiple stressors across scales in aquatic ecosystems. Mar Freshw Res 67:393–413. doi: 10.1071/MF15108 CrossRefGoogle Scholar
  28. Dafforn KA, Simpson SL, Kelaher BP et al (2012) The challenge of choosing environmental indicators of anthropogenic impacts in estuaries. Environ Pollut 163:207–217. doi: 10.1016/j.envpol.2011.12.029 CrossRefPubMedGoogle Scholar
  29. Davison J (1999) Genetic exchange between bacteria in the environment. Plasmid 42:73–91. doi: 10.1006/plas.1999.1421 CrossRefPubMedGoogle Scholar
  30. Dequiedt S, Saby NPA, Lelievre M et al (2011) Biogeographical patterns of soil molecular microbial biomass as influenced by soil characteristics and management. Glob Ecol Biogeogr 20:641–652. doi: 10.1111/j.1466-8238.2010.00628.x CrossRefGoogle Scholar
  31. Di HJ, Cameron KC, McLaren RG (2000) Isotopic dilution methods to determine the gross transformation rates of nitrogen, phosphorus, and sulfur in soil: a review of the theory, methodologies, and limitations. Soil Res 38:213–230. doi: 10.1071/SR99005 CrossRefGoogle Scholar
  32. Edge KJ, Dafforn KA, Simpson SL et al (2015) Resuspended contaminated sediments cause sublethal stress to oysters: a biomarker differentiates total suspended solids and contaminant effects. Environ Toxicol Chem 34:1345–1353. doi: 10.1002/etc.2929 CrossRefPubMedGoogle Scholar
  33. Edge KJ, Dafforn KA, Simpson SL et al (2014) A biomarker of contaminant exposure is effective in large scale assessment of ten estuaries. Chemosphere 100:16–26CrossRefPubMedGoogle Scholar
  34. Ellis RJ, Neish B, Trett MW et al (2001) Comparison of microbial and meiofaunal community analyses for determining impact of heavy metal contamination. J Microbiol Methods 45:171–185. doi: 10.1016/S0167-7012(01)00245-7 CrossRefPubMedGoogle Scholar
  35. Eyre BD, Ferguson AJP (2005) Benthic metabolism and nitrogen cycling in a subtropical east Australian estuary (Brunswick): temporal variability and controlling factors. Limnol Oceanogr 50:81–96. doi: 10.4319/lo.2005.50.1.0081 CrossRefGoogle Scholar
  36. Falkowski PG, Fenchel T, Delong EF (2008) The microbial engines that drive earth’s biogeochemical cycles. Science (80) 320:1034–1039. doi: 10.1126/science.1153213
  37. Finlay BJ, Maberly SC, Cooper JI (1997) Microbial diversity and ecosystem function. Oikos 80:209–213. doi: 10.2307/3546587 CrossRefGoogle Scholar
  38. Friberg N, Bonada N, Bradley DC et al (2011) Biomonitoring of human impacts in freshwater ecosystems: the good, the bad and the ugly. Elsevier Ltd., AmsterdamCrossRefGoogle Scholar
  39. Geets J, Borremans B, Diels L et al (2006) DsrB gene-based DGGE for community and diversity surveys of sulfate-reducing bacteria. J Microbiol Methods 66:194–205. doi: 10.1016/j.mimet.2005.11.002 CrossRefPubMedGoogle Scholar
  40. Gibson JF, Shokralla S, Curry C et al (2015) Large-scale biomonitoring of remote and threatened ecosystems via high-throughput sequencing. PLoS ONE 10:e0138432. doi: 10.5061/dryad.vm72v CrossRefPubMedPubMedCentralGoogle Scholar
  41. Gillan DC, Danis B, Pernet P et al (2005) Structure of sediment-associated microbial communities along a heavy-metal contamination gradient in the marine environment. Appl Environmantal Microbiol 71:679–690. doi: 10.1128/AEM.71.2.679 CrossRefGoogle Scholar
  42. Graham JE, Wantland NB, Campbell M, Klotz MG (2011) Characterizing bacterial gene expression in nitrogen cycle metabolism with RT-qPCR. Methods Enzymol 496:345–372. doi: 10.1016/B978-0-12-386489-5.00014-2 CrossRefPubMedGoogle Scholar
  43. Gray JS, Wu RS, Or YY (2002) Effects of hypoxia and organic enrichment on the coastal marine environment. Mar Ecol Prog Ser 238:249–279. doi: 10.3354/meps238249 CrossRefGoogle Scholar
  44. Haller L, Tonolla M, Zopfi J et al (2011) Composition of bacterial and archaeal communities in freshwater sediments with different contamination levels (Lake Geneva, Switzerland). Water Res 45:1213–1228. doi: 10.1016/j.watres.2010.11.018 CrossRefPubMedGoogle Scholar
  45. Hartl FU (1996) Molecular chaperones in cellular protein folding. Nature 381:571–579CrossRefPubMedGoogle Scholar
  46. He Z, Van Nostrand JD, Zhou J (Joe) (2013) GeoChip-based metagenomic technologies for analyzing microbial community functional structure and activities. pp 236–247Google Scholar
  47. Holt MS (2000) Sources of chemical contaminants and routes into the freshwater environment. Food Chem Toxicol 38:S21–S27. doi: 10.1016/S0278-6915(99)00136-2 CrossRefPubMedGoogle Scholar
  48. Horvath S, Dong J (2008) Geometric interpretation of gene coexpression network analysis. PLoS Comput Biol 4:e1000117. doi: 10.1371/journal.pcbi.1000117 CrossRefPubMedPubMedCentralGoogle Scholar
  49. Johnston EL, Mayer-Pinto M (2015) Pollution : effects of chemical contaminants and debris. Mar Ecosyst Hum impacts biodivers Funct Serv 244. doi: 10.1017/CBO9781139794763.009
  50. Johnston EL, Mayer-Pinto M, Crowe TP (2015) REVIEW: chemical contaminant effects on marine ecosystem functioning. J Appl Ecol 52:140–149. doi: 10.1111/1365-2664.12355 CrossRefGoogle Scholar
  51. Johnston EL, Roberts DA (2009) Contaminants reduce the richness and evenness of marine communities: a review and meta-analysis. Environ Pollut 157:1745–1752. doi: 10.1016/j.envpol.2009.02.017 CrossRefPubMedGoogle Scholar
  52. Jones SE, Lennon JT (2010) Dormancy contributes to the maintenance of microbial diversity. Proc Natl Acad Sci 107:5881–5886. doi: 10.1073/pnas.0912765107 CrossRefPubMedPubMedCentralGoogle Scholar
  53. Kelaher BP, Bishop MJ, Potts J et al (2013) Detrital diversity influences estuarine ecosystem performance. Glob Chang Biol 19:1909–1918. doi: 10.1111/gcb.12162 CrossRefPubMedGoogle Scholar
  54. Kelly J, Thornton I, Simpson PR (1996) Urban geochemistry: a study of the influence of anthropogenic activity on the heavy metal content of soils in traditionally industrial and non-industrial areas of Britain. Appl Geochemistry 11:363–370. doi: 10.1016/0883-2927(95)00084-4 CrossRefGoogle Scholar
  55. Kennish MJ (2002) Environmental threats and environmental future of estuaries. Environ Conserv 29:78–107CrossRefGoogle Scholar
  56. Kinsella CM, Crowe TP (2016) Separate and combined effects of copper and freshwater on the biodiversity and functioning of fouling assemblages. Mar Pollut Bull 107:136–143. doi: 10.1016/j.marpolbul.2016.04.008 CrossRefPubMedGoogle Scholar
  57. Kraft B, Tegetmeyer HE, Sharma R et al (2014) The environmental controls that govern the end product of bacterial nitrate respiration. Science (80) 345:676–679Google Scholar
  58. Lawes JC, Clark GF, Johnston EL (2016a) Contaminant cocktails: interactive effects of fertiliser and copper paint on marine invertebrate recruitment and mortality. Mar Pollut Bull 102:148–159. doi: 10.1016/j.marpolbul.2015.11.040 CrossRefPubMedGoogle Scholar
  59. Lawes JC, Neilan BA, Brown MV et al (2016b) Elevated nutrients change bacterial community composition and connectivity: high throughput sequencing of young marine biofilms. Biofouling 32:57–69. doi: 10.1080/08927014.2015.1126581 CrossRefPubMedGoogle Scholar
  60. Lejzerowicz F, Esling P, Pillet LL et al (2015) High-throughput sequencing and morphology perform equally well for benthic monitoring of marine ecosystems. Sci Rep 5:13932. doi: 10.1038/srep13932 CrossRefPubMedPubMedCentralGoogle Scholar
  61. Liikanen A, Martikainen PJ (2003) Effect of ammonium and oxygen on methane and nitrous oxide fluxes across sediment-water interface in a eutrophic lake. Chemosphere 52:1287–1293. doi: 10.1016/S0045-6535(03)00224-8 CrossRefPubMedGoogle Scholar
  62. Liu L, Li Y, Li S et al (2012) Comparison of next-generation sequencing systems. J Biomed Biotechnol. doi: 10.1155/2012/251364 Google Scholar
  63. Lohbeck KT, Riebesell U, Reusch TBH (2014) Gene expression changes in the coccolithophore Emiliania huxleyi after 500 generations of selection to ocean acidification. Proc R Soc B 281:1–7. doi: 10.1098/rspb.2014.0003 CrossRefGoogle Scholar
  64. Mayer-Pinto M, Johnston EL, Hutchings PA et al (2015) Sydney Harbour: a review of anthropogenic impacts on the biodiversity and ecosystem function of one of the world’s largest natural harbours. Mar Freshw Res 66:1088. doi: 10.1071/MF15157 CrossRefGoogle Scholar
  65. McKinley AC, Dafforn KA, Taylor MD, Johnston EL (2011) High levels of sediment contamination have little influence on estuarine beach fish communities. PLoS ONE 6:e26353. doi: 10.1371/journal.pone.0026353 CrossRefPubMedPubMedCentralGoogle Scholar
  66. Meyer-Reil L-A, Köster M (2000) Eutrophication of marine waters: effects on benthic microbial communities. Mar Pollut Bull 41:255–263CrossRefGoogle Scholar
  67. Nguyen TC, Loganathan P, Nguyen TV et al (2014) Polycyclic aromatic hydrocarbons in road-deposited sediments, water sediments, and soils in Sydney, Australia: comparisons of concentration distribution, sources and potential toxicity. Ecotoxicol Environ Saf 104:339–348. doi: 10.1016/j.ecoenv.2014.03.010 CrossRefPubMedGoogle Scholar
  68. Nicholson FA, Smith SR, Alloway BJ et al (2003) An inventory of heavy metals inputs to agricultural soils in England and Wales. Sci Total Environ 311:205–219. doi: 10.1016/S0048-9697(03)00139-6 CrossRefPubMedGoogle Scholar
  69. Nielsen UN, Ayres E, Wall DH, Bardgett RD (2011) Soil biodiversity and carbon cycling: a review and synthesis of studies examining diversity-function relationships. Eur J Soil Sci 62:105–116. doi: 10.1111/j.1365-2389.2010.01314.x CrossRefGoogle Scholar
  70. Nikolopoulou M, Pasadakis N, Kalogerakis N (2013) Evaluation of autochthonous bioaugmentation and biostimulation during microcosm-simulated oil spills. Mar Pollut Bull 72:165–173. doi: 10.1016/j.marpolbul.2013.04.007 CrossRefPubMedGoogle Scholar
  71. Noyer C, Abot A, Trouilh L et al (2015) Phytochip: development of a DNA-microarray for rapid and accurate identification of Pseudo-nitzschia spp. and other harmful algal species. J Microbiol Methods 112:55–66. doi: 10.1016/j.mimet.2015.03.002 CrossRefPubMedGoogle Scholar
  72. Oliver TH, Heard MS, Isaac NJB et al (2015) Biodiversity and resilience of ecosystem functions. Trends Ecol Evol xx:1–12. doi: 10.1016/j.tree.2015.08.009
  73. Pal A, Gin KYH, Lin AYC, Reinhard M (2010) Impacts of emerging organic contaminants on freshwater resources: review of recent occurrences, sources, fate and effects. Sci Total Environ 408:6062–6069. doi: 10.1016/j.scitotenv.2010.09.026 CrossRefPubMedGoogle Scholar
  74. Piola RF, Johnston EL (2008) Pollution reduces native diversity and increases invader dominance in marine hard-substrate communities. Divers Distrib 14:329–342. doi: 10.1111/j.1472-4642.2007.00430.x CrossRefGoogle Scholar
  75. Proulx SR, Promislow DEL, Phillips PC (2005) Network thinking in ecology and evolution. Trends Ecol Evol 20:345–353. doi: 10.1016/j.tree.2005.04.004 CrossRefPubMedGoogle Scholar
  76. Puckett LJ (1995) Identifying the major sources of nutrient water pollution. Environ Sci Technol 29:408A–414A. doi: 10.1021/es00009a001 CrossRefGoogle Scholar
  77. Radchuk V, De Laender F, Van den Brink PJ, Grimm V (2016) Biodiversity and ecosystem functioning decoupled: invariant ecosystem functioning despite non-random reductions in consumer diversity. Oikos 125:424–433. doi: 10.1111/oik.02220 CrossRefGoogle Scholar
  78. Reusch TBH, Boyd PW (2013) Experimental evolution meets marine phytoplankton. Evolution (N Y) 67:1849–1859. doi: 10.1111/evo.12035 Google Scholar
  79. Ross-Gillespie A, Kümmerli R (2014) Collective decision-making in microbes. Front Microbiol 5:54. doi: 10.3389/fmicb.2014.00054
  80. Santschi PH, Presley BJ, Wade TL et al (2001) Historical contamination of PAHs, PCBs, DDTs, and heavy metals in Mississippi River Delta, Galveston Bay and Tampa Bay sediment cores. Mar Environ Res 52:51–79. doi: 10.1016/S0141-1136(00)00260-9 CrossRefPubMedGoogle Scholar
  81. Scanes P, Coade G, Doherty M, Hill R (2007) Evaluation of the utility of water quality based indicators of estuarine lagoon condition in NSW, Australia. Estuar Coast Shelf Sci 74:306–319. doi: 10.1016/j.ecss.2007.04.021 CrossRefGoogle Scholar
  82. Schimel JP, Balser TC, Wallenstein M (2007) Microbial stress-response physiology and its implications for ecosystem function. Ecology 88:1386–1394. doi: 10.1890/06-0219 CrossRefPubMedGoogle Scholar
  83. Scholz-Starke B, Nikolakis A, Leicher T et al (2011) Outdoor terrestrial model ecosystems are suitable to detect pesticide effects on soil fauna: design and method development. Ecotoxicology 20:1932–1948. doi: 10.1007/s10646-011-0732-z CrossRefPubMedGoogle Scholar
  84. Shade A, Peter H, Allison SD et al (2012) Fundamentals of microbial community resistance and resilience. Front Microbiol 3:1–19. doi: 10.3389/fmicb.2012.00417 CrossRefGoogle Scholar
  85. Sims A, Zhang Y, Gajaraj S et al (2013) Toward the development of microbial indicators for wetland assessment. Water Res 47:1711–1725. doi: 10.1016/j.watres.2013.01.023 CrossRefPubMedGoogle Scholar
  86. Smith JG, Brandt CC, Christensen SW (2011) Long-term benthic macroinvertebrate community monitoring to assess pollution abatement effectiveness. Environ Manage 47:1077–1095. doi: 10.1007/s00267-010-9610-3 CrossRefPubMedGoogle Scholar
  87. Stewart FJ, Ulloa O, Delong EF (2012) Microbial metatranscriptomics in a permanent marine oxygen minimum zone. Environ Microbiol 14:23–40. doi: 10.1111/j.1462-2920.2010.02400.x CrossRefPubMedGoogle Scholar
  88. Strickland MS, Lauber CL, Fierer N, Bradford MA (2009) Testing the functional significance of microbial community composition. Ecology 90:441–451CrossRefPubMedGoogle Scholar
  89. Sun MY (2016) Impacts of anthropogenic modification on the taxonomic and functional structure of estuarine sediment communities. University of New South Wales, AustraliaGoogle Scholar
  90. Sun MY, Dafforn KA, Brown MV, Johnston EL (2012) Bacterial communities are sensitive indicators of contaminant stress. Mar Pollut Bull 64:1029–1038. doi: 10.1016/j.marpolbul.2012.01.035 CrossRefPubMedGoogle Scholar
  91. Sun MY, Dafforn KA, Johnston EL, Brown MV (2013) Core sediment bacteria drive community response to anthropogenic contamination over multiple environmental gradients. Environ Microbiol 15:2517–2531. doi: 10.1111/1462-2920.12133 CrossRefPubMedGoogle Scholar
  92. Thomas T, Rusch D, DeMaere MZ et al (2010) Functional genomic signatures of sponge bacteria reveal unique and shared features of symbiosis. ISME J 4:1557–1567. doi: 10.1038/ismej.2010.74 CrossRefPubMedGoogle Scholar
  93. Tlili A, Berard A, Blanck H et al (2015) Pollution-induced community tolerance (PICT): towards an ecologically relevant risk assessment of chemicals in aquatic systems. Freshw Biol 1–11. doi: 10.1111/fwb.12558
  94. Tlili A, Bérard A, Roulier JL et al (2010) PO43-dependence of the tolerance of autotrophic and heterotrophic biofilm communities to copper and diuron. Aquat Toxicol 98:165–177. doi: 10.1016/j.aquatox.2010.02.008 CrossRefPubMedGoogle Scholar
  95. van der Linden P, Borja Á, Rodríquez JG et al (2016) Spatial and temporal response of multiple trait-based indices to natural- and anthropogenic seafloor disturbance (effluents). Ecol Indic 69:617–628. doi: 10.1016/j.ecolind.2016.05.020 CrossRefGoogle Scholar
  96. Westerhoff HV, Brooks AN, Simeonidis E et al (2014) Macromolecular networks and intelligence in microorganisms. Front Microbiol 5:379. doi: 10.3389/fmicb.2014.00379
  97. Zaiko A, Schimanski K, Pochon X et al (2016) Metabarcoding improves detection of eukaryotes from early biofouling communities: implications for pest monitoring and pathway management. Biofouling 32:671–684. doi: 10.1080/08927014.2016.1186165 CrossRefPubMedGoogle Scholar
  98. Zhu W, Bian B, Li L (2008) Heavy metal contamination of road-deposited sediments in a medium size city of China. Environ Monit Assess 147:171–181. doi: 10.1007/s10661-007-0108-2 CrossRefPubMedGoogle Scholar
  99. Zimmerman N, Izard J, Klatt C et al (2014) The unseen world: environmental microbial sequencing and identification methods for ecologists. Front Ecol Environ 12:224–231. doi: 10.1890/130055 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Evolution and Ecology Research Centre, School of Biological, Earth and Environmental SciencesUniversity of New South WalesSydneyAustralia
  2. 2.The Sydney Institute of Marine ScienceMosmanAustralia

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