Pelagic-benthic coupling of the microbial food web modifies nutrient cycles along a cascade-dammed river

Highlights

• Structure of multi-trophic microbial groups were analyzed using DNA metabarcoding.

• Discontinuity and trophic interactions were observed along the dam-fragmented river.

• C, N and P cycles are driven by top-down and bottom-up forces of microbial food web.

• Pelagic-benthic coupling may intensify nutrient accumulation in the river system.

Abstract

Cascade dams disrupt the river continuum, altering hydrology, biodiversity and nutrient flux. Describing the diversity of multi-trophic microbiota and assessing microbial contributions to the ecosystem processes are prerequisites for the restoration of these aquatic systems. This study investigated the microbial food web structure along a cascade-dammed river, paying special attention to the multi-trophic relationships and the potential role of pelagic-benthic coupling in nutrient cycles. Our results revealed the discontinuity in bacterial and eukaryotic community composition, functional group proportion, as well as α-diversity due to fragmentation by damming. The high microbial dissimilarity along the river, with the total multi-trophic β-diversity was 0.84, was almost completely caused by species replacement. Synchronization among trophic levels suggests potential interactions of the pelagic and the benthic groups, of which the β-diversities were primarily influenced by geographic and environmental factors, respectively. Dam-induced environmental variations, especially hydrological and nutrient variables, potentially influence the microbial food web via both top-down and bottom-up forces. We proposed that the cycles of carbon, nitrogen and phosphorus are influenced by multi-trophic groups through autotrophic and heterotrophic processes, predator–prey relationships, as well as the release of nutrients mainly by microfauna. Our results advance the notion that pelagic-benthic trophic coupling may intensify the accumulation of organic carbon, ammonium and inorganic phosphorus, thereby changing the biogeochemical patterns along river systems. As a consequence, researchers should pay more attention to the multi-trophic studies when assessing the environmental impacts, and to provide the necessary guidance for the ecological conservation and restoration of the dam-regulated systems.

Graphical abstract

Keywords

Reservoir / Multi-trophic / Beta diversity / Predator-prey / Nutrient accumulation

References

[1] Antiqueira P A P, Petchey O L, Dos Santos V P, De Oliveira Valéria m, Romero G Q (2018). Environmental change and predator diversity drive alpha and beta diversity in freshwater macro and microorganisms. Global Change Biology, 24(8): 3715–3728

[2] Baselga A (2010). Partitioning the turnover and nestedness components of beta diversity. Global Ecology and Biogeography, 19(1): 134–143

[3] Baselga A, Orme C D L (2012). betapart: an R package for the study of beta diversity. Methods in Ecology and Evolution, 3(5): 808–812

[4] Bista I, Carvalho G R, Walsh K, Seymour M, Hajibabaei M, Lallias D, Christmas M, Creer S (2017). Annual time-series analysis of aqueous eDNA reveals ecologically relevant dynamics of lake ecosystem biodiversity. Nature Communications, 8: 14087

[5] Bonaglia S, Nascimento F J A, Bartoli M, Klawonn I, Brüchert V (2014). Meiofauna increases bacterial denitrification in marine sediments. Nature Communications, 5: 5133

[6] Caporaso J G, Kuczynski J, Stombaugh J, Bittinger K, Bushman F D, Costello E K, Fierer N, Peña A G, Goodrich J K, Gordon J I, Huttley G A, Kelley S T, Knights D, Koenig J E, Ley R E, Lozupone C A, McDonald D, Muegge B D, Pirrung M, Reeder J, Sevinsky J R, Turnbaugh P J, Walters W A, Widmann J, Yatsunenko T, Zaneveld J, Knight R (2010). QIIME allows analysis of high-throughput community sequencing data. Nature Methods, 7(5): 335–336

[7] Chen J, Wang P, Wang C, Wang X, Miao L, Liu S, Yuan Q (2018). Bacterial communities in riparian sediments: A large-scale longitudinal distribution pattern and response to dam construction. Frontiers in Microbiology, 9: 999

[8] Chen M, Chen F, Zhao B, Wu Q L, Kong F (2010). Seasonal variation of microbial eukaryotic community composition in the large, shallow, subtropical Taihu Lake, China. Aquatic Ecology, 44: 1–12

[9] Chen Q, Shi W, Huisman J, Maberly S C, Zhang J, Yu J, Chen Y, Tonina D, Yi Q (2020). Hydropower reservoirs on the upper Mekong River modify nutrient bioavailability downstream. National Science Review, 7(9): 1449–1457

[10] Domingues C D, da Silva L H S, Rangel L M, de Magalhães L, de Melo Rocha A, Lobão L M, Paiva R, Roland F, Sarmento H (2017). Microbial food-web drivers in tropical reservoirs. Microbial Ecology, 73: 505–520

[11] dos N C L Santos E, García-Berthou J D, Dias T M, Lopes I D P, Affonso W, Severi L C, Gomes A, Agostinho A (2018). Cumulative ecological effects of a Neotropical reservoir cascade across multiple assemblages. Hydrobiologia, 819: 77–91

[12] Edgar R C (2010). Search and clustering orders of magnitude faster than BLAST. Bioinformatics (Oxford, England), 26(19): 2460–2461

[13] Gao Q, Tao Z, Shen C, Sun Y, Yi W, Xing C (2002). Riverine organic carbon in the Xijiang River (South China): seasonal variation in content and flux budget. Environmental Geology, 41: 826–832

[14] Grenouillet G, Brosse S, Tudesque L, Lek S, Baraille Y, Loot G (2008). Concordance among stream assemblages and spatial autocorrelation along a fragmented gradient. Diversity & Distributions, 14(4): 592–603

[15] Handley K M (2019). Determining microbial roles in ecosystem function: Redefining microbial food webs and transcending kingdom barriers. mSystems, 4(3): e00153–19

[16] Jamoneau A, Passy S I, Soininen J, Leboucher T, Tison-Rosebery J (2018). Beta diversity of diatom species and ecological guilds: Response to environmental and spatial mechanisms along the stream watercourse. Freshwater Biology, 63: 62–73

[17] Kathol M, Fischer H, Weitere M (2011). Contribution of biofilm-dwelling consumers to pelagic-benthic coupling in a large river. Freshwater Biology, 56(6): 1160–1172

[18] Kavazos C R J, Huggett M J, Mueller U, Horwitz P (2018). Bacterial and ciliate biofilm community structure at different spatial levels of a salt lake meta-community. FEMS Microbiology Ecology, 94(10): fiy148

[19] Keeley N, Wood S A, Pochon X (2018). Development and preliminary validation of a multi-trophic metabarcoding biotic index for monitoring benthic organic enrichment. Ecological Indicators, 85: 1044–1057

[20] Kiljunen M, Peltonen H, Lehtiniemi M, Uusitalo L, Sinisalo T, Norkko J, Kunnasranta M, Torniainen J, Rissanen A J, Karjalainen J (2020). Benthic-pelagic coupling and trophic relationships in northern Baltic Sea food webs. Limnology and Oceanography, 65(8): 1706–1722

[21] Li J, Dong S, Yang Z, Peng M, Liu S, Li X (2012). Effects of cascade hydropower dams on the structure and distribution of riparian and upland vegetation along the middle-lower Lancang-Mekong River. Forest Ecology and Management, 284: 251–259

[22] Li Y, Gal G, Makler-Pick V, Waite A M, Bruce L C, Hipsey M R (2014). Examination of the role of the microbial loop in regulating lake nutrient stoichiometry and phytoplankton dynamics. Biogeosciences, 11(11): 2939–2960

[23] Lischke B, Mehner T, Hilt S, Attermeyer K, Brauns M, Brothers S, Grossart H P, Köhler J, Scharnweber K, Gaedke U (2017). Benthic carbon is inefficiently transferred in the food webs of two eutrophic shallow lakes. Freshwater Biology, 62(10): 1693–1706

[24] Maavara T, Chen Q, Van Meter K, Brown L E, Zhang J, Ni J, Zarfl C (2020). River dam impacts on biogeochemical cycling. Nature Reviews Earth & Environment, 1: 103–116

[25] Martinez-Almoyna C, Thuiller W, Chalmandrier L, Ohlmann M, Foulquier A, Clément J C, Zinger L, Münkemüller T (2019). Multi-trophic β-diversity mediates the effect of environmental gradients on the turnover of multiple ecosystem functions. Functional Ecology, 33(10): 2053–2064

[26] Middelburg J J (2018). Reviews and syntheses: to the bottom of carbon processing at the seafloor. Biogeosciences, 15: 413–427

[27] Moitra M, Leff L (2015). Bacterial community composition and function along a river to reservoir transition. Hydrobiologia, 747: 201–215

[28] Molina V, Morales C E, Farías L, Cornejo M, Graco M, Eissler Y, Cuevas L A (2012). Potential contribution of planktonic components to ammonium cycling in the coastal area off central-southern Chile during non-upwelling conditions. Progress in Oceanography, 92–95: 43–49

[29] Montagna M, Berruti A, Bianciotto V, Cremonesi P, Giannico R, Gusmeroli F, Lumini E, Pierce S, Pizzi F, Turri F, Gandini G (2018). Differential biodiversity responses between kingdoms (plants, fungi, bacteria and metazoa) along an Alpine succession gradient. Molecular Ecology, 27(18): 3671–3685

[30] Mor J R, Ruhí A, Tornés E, Valcárcel H, Muñoz I, Sabater S (2018). Dam regulation and riverine food-web structure in a Mediterranean river. Science of the Total Environment, 625: 301–310

[31] Mori A S, Isbell F, Seidl R (2018). β-Diversity, community assembly, and ecosystem functioning. Trends in Ecology & Evolution, 33(7): 549–564

[32] Oliverio A M, Power J F, Washburne A, Cary S C, Stott M B, Fierer N (2018). The ecology and diversity of microbial eukaryotes in geothermal springs. The ISME journal, 12(8): 1918–1928

[33] Özen A, Tavşanoğlu Ü N, Çakıroğlu A İ, Levi E E, Jeppesen E, Beklioğlu M (2018). Patterns of microbial food webs in Mediterranean shallow lakes with contrasting nutrient levels and predation pressures. Hydrobiologia, 806: 13–27

[34] Palmer M, Ruhi A (2019). Linkages between flow regime, biota, and ecosystem processes: Implications for river restoration. Science, 365(6459): eaaw2087

[35] Pusceddu A, Fiordelmondo C, Danovaro R (2005). Sediment resuspension effects on the benthic microbial loop in experimental microcosms. Microbial Ecology, 50(4): 602–613

[36] Ritz S, Eßer M, Arndt H, Weitere M (2017). Large-scale patterns of biofilm-dwelling ciliate communities in a river network: Only small effects of stream order. International Review of Hydrobiology, 102(5–6): 114–124

[37] Rognes T, Flouri T, Nichols B, Quince C, Mahé F (2016). VSEARCH: A versatile open source tool for metagenomics. PeerJ, 4: e2584

[38] Schmidt R, Ulanova D, Wick L Y, Bode H B, Garbeva P (2019). Microbe-driven chemical ecology: Past, present and future. The ISME journal, 13(11): 2656–2663

[39] Schratzberger M, Ingels J (2018). Meiofauna matters: The roles of meiofauna in benthic ecosystems. Journal of Experimental Marine Biology and Ecology, 502: 12–25

[40] Singh D, Slik J W F, Jeon Y S, Tomlinson K W, Yang X, Wang J, Kerfahi D, Porazinska D L, Adams J M (2019). Tropical forest conversion to rubber plantation affects soil micro- & mesofaunal community & diversity. Scientific Reports, 9: 5893

[41] Socolar J B, Gilroy J J, Kunin W E, Edwards D P (2016). How should beta-diversity inform biodiversity conservation? Trends in Ecology & Evolution, 31(1): 67–80

[42] Šolić M, Šantić D, Šestanović S, Bojanić N, Jozić S, Ordulj M, Vrdoljak Tomaš A, Kušpilić G (2020). Changes in the trophic pathways within the microbial food web in the global warming scenario: an experimental study in the Adriatic Sea. Microorganisms, 8(4): 510

[43] Stoeck T, Bass D, Nebel M, Christen R, Jones M D M, Breiner H W, Richards T A (2010). Multiple marker parallel tag environmental DNA sequencing reveals a highly complex eukaryotic community in marine anoxic water. Molecular Ecology, 19(s1): 21–31

[44] Thingstad T F, Bellerby R G J, Bratbak G, Børsheim K Y, Egge J K, Heldal M, Larsen A, Neill C, Nejstgaard J, Norland S, Sandaa R A, Skjoldal E F, Tanaka T, Thyrhaug R, Töpper B (2008). Counterintuitive carbon-to-nutrient coupling in an Arctic pelagic ecosystem. Nature, 455(7211): 387–390

[45] Timpe K, Kaplan D (2017). The changing hydrology of a dammed Amazon. Science Advances, 3(11): e1700611

[46] van Dael T, De Cooman T, Verbeeck M, Smolders E (2020). Sediment respiration contributes to phosphate release in lowland surface waters. Water Research, 168: 115168

[47] Volvoikar S P, Nayak G N, Mazumdar A, Peketi A (2014). Reconstruction of depositional environment of a tropical estuary and response of δ¹³Corg and TOC/TN signatures to changing environmental conditions. Estuarine, Coastal and Shelf Science, 139: 137–147

[48] Wang X, Wang P, Wang C, Chen J, Miao L, Yuan Q, Liu S, Feng T (2020). Do bacterioplankton respond equally to different river regulations? A quantitative study in the single-dammed Yarlung Tsangpo River and the cascade-dammed Lancang River. Environmental Research, 191: 110194

[49] Weitere M, Erken M, Majdi N, Arndt H, Norf H, Reinshagen M, Traunspurger W, Walterscheid A, Wey J K (2018). The food web perspective on aquatic biofilms. Ecological Monographs, 88(4): 543–559

[50] Worden A Z, Follows M J, Giovannoni S J, Wilken S, Zimmerman A E, Keeling P J (2015). Rethinking the marine carbon cycle: Factoring in the multifarious lifestyles of microbes. Science, 347(6223): 1257594

[51] Wu B, Tian J, Bai C, Xiang M, Sun J, Liu X (2013). The biogeography of fungal communities in wetland sediments along the Changjiang River and other sites in China. The ISME journal, 7(7): 1299–1309

[52] Yang N, Li Y, Zhang W, Lin L, Qian B, Wang L, Niu L, Zhang H (2020). Cascade dam impoundments restrain the trophic transfer efficiencies in benthic microbial food web. Water Research, 170: 115351

[53] Yu Y, Lee C, Kim J, Hwang S (2005). Group-specific primer and probe sets to detect methanogenic communities using quantitative real-time polymerase chain reaction. Biotechnology and Bioengineering, 89(6): 670–679

[54] Zhang F, Zhang H, Yuan Y, Liu D, Zhu C, Zheng D, Li G, Wei Y, Sun D (2020a). Different response of bacterial community to the changes of nutrients and pollutants in sediments from an urban river network. Frontiers of Environmental Science & Engineering, 14: 2810.1007/s11783-019-1207-3

[55] Zhang Y, Pavlovska M, Stoica E, Prekrasna I, Yang J, Slobodnik J, Zhang X, Dykyi E (2020b). Holistic pelagic biodiversity monitoring of the Black Sea via eDNA metabarcoding approach: From bacteria to marine mammals. Environment International, 135: 105307

[56] Zou K, Thébault E, Lacroix G, Barot S (2016). Interactions between the green and brown food web determine ecosystem functioning. Functional Ecology, 30(8): 1454–1465

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Nos. 51779076 and 51879079).

Electronic Supplementary material

Supplementary material is available in the online version of this article at https://doi.org/10.1007/s11783-021-1484-5 and is accessible for authorized users.

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