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Environmental thresholds and predictors of macrophyte species richness in aquatic habitats in central Europe

Abstract

The degradation of habitats and species loss in freshwaters is far greater than in any other ecosystem. The decline in biodiversity has a strong potential to alter the functioning of the ecosystem and the services they provide to human society. Therefore, there is an urgent need for accurate information on patterns and drivers of diversity that could be used in the management of freshwater ecosystems. We present the results of an analysis of the relationships between macrophyte species richness and environmental characteristics using an extensive dataset collected from 160 sites in two central-European bioregions. We modelled macrophyte species richness using recursive partitioning methods to assess the diversity-environmental relationships and to estimate the environmental thresholds of species richness in rivers, streams, ditches and ponds. Several hydrological and chemical variables were identified as significant predictors of macrophyte richness. Among them, pH, conductivity, turbidity and substrate composition appeared as the most important. There is also evidence that natural ponds support a greater number of plant species than man-made ponds. Based on the detected environmental thresholds, we offer a series of simple rules for maintaining higher macrophyte species richness, which is potentially useful in the conservation and management of aquatic habitats in central Europe.

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References

  • Akasaka M, Takamura N, Mitsuhashi H, Kadono Y (2009) Effects of land use on aquatic macrophyte diversity and water quality of ponds. Freshw Biol 55:909–922

    Article  Google Scholar 

  • Bakker ES, Sarneel JM, Gulati RD, Liu Z, Donk E van (2013) Restoring macrophyte diversity in shallow temperate lakes: biotic versus abiotic constraints. Hydrobiologia 710:23–37

  • Barko JW, James WF (1998) Effects of submerged aquatic macrophytes on nutrient dynamics, sedimentation, and resuspension. In Jeppesen E, Sondergaard M, Sondergaard M, Christofferson K (eds) The Structuring Role of Submerged Macrophytes in Lakes, Springer, New York, pp 197–214

    Chapter  Google Scholar 

  • Bornette G, Puijalon S (2011) Response of aquatic plants to abiotic factors: a review. Aquatic Sciences 73:1–14

    CAS  Article  Google Scholar 

  • Breiman L (2001) Random forests. Mach learn 45:5–32

    Article  Google Scholar 

  • Broyer J, Curtet L (2012) Biodiversity and fish farming intensification in French fishpond systems. Hydrobiologia 694:205–218

    Article  Google Scholar 

  • Brylinsky M, Mann K (1973) An analysis of factors governing productivity in lakes and reservoirs. Limnol Oceanogr 18:1–14

    CAS  Article  Google Scholar 

  • Capers RS, Selsky R, Bugbee GJ, White JC (2009) Species richness of both native and invasive aquatic plants influenced by environmental conditions and human activity. Botany 87:306–314

    CAS  Article  Google Scholar 

  • Canfield DE, Langeland KA, Linda SB, Haller WT (1985) Relations between water transparency and maximum depth of macrophyte colonization in lakes. J Aquat Plant Manage 23:25–28

    Google Scholar 

  • Chambers PA, Lacoul P, Murphy KJ, Thomaz SM (2008) Global diversity of aquatic macrophytes in freshwater. Hydrobiologia 595:9–26

    Article  Google Scholar 

  • Chappuis E, Ballesteros E, Gacia E (2012) Distribution and richness of aquatic plants across Europe and Mediterranean countries: patterns, environmental driving factors and comparison with total plant richness. J Veg Sci 23:985–997

    Article  Google Scholar 

  • De'ath G, Fabricius KE (2000) Classification and regression trees: a powerful yet simple technique for ecological data analysis. Ecology 81:3178–3192

    Article  Google Scholar 

  • Downing AL, Leibold MA (2002) Ecosystem consequences of species richness and composition in pond food webs. Nature 416:837–841

    CAS  Article  PubMed  Google Scholar 

  • Dudgeon D, Arthington AH, Gessner MO, Kawabata ZI, Knowler DJ, Lévêque C, Naiman RJ, Prieur-Richard AH, Soto D, Stiassny MLJ, Sullivan CA (2006) Freshwater biodiversity: importance, threats status and conservation challenges. Biol Rev 81:163–182

    Article  PubMed  Google Scholar 

  • Edvardsen A, Økland RH (2006) Variation in plant species composition in and adjacent to 64 ponds in SE Norwegian agricultural landscapes. Aquat bot 85:92–102

    Article  Google Scholar 

  • Engelhardt KA, Ritchie ME (2001) Effects of macrophyte species richness on wetland ecosystem functioning and services. Nature 411:687–689

    CAS  Article  PubMed  Google Scholar 

  • Futák J (1966) Fytogeografické členenie (Phytogeographical classification). In Futák J (ed) Flóra Slovenska I. Vydavateľstvo Slovenskej akadémie vied, Bratislava, pp 533–538

    Google Scholar 

  • Hastie T, Tibshirani R, Friedman J (2009) The elements of statistical learning (Second edition). Springer, New York, 745 pp

  • Heino J, Mykrä H, Rintala J (2010) Assessing patterns of nestedness in stream insect assemblages along environmental gradients. Ecoscience 17:345–355

    Article  Google Scholar 

  • Hooper DU, Chapin III FS, Ewel JJ, Hector A, Inchausti P, Lavorel S, Lawton JH, Lodge DM, Loreau M, Naeem S, Schmid B, Setälä H, Symstad AJ, Vandermeer J, Wardle DA (2005).Effects of biodiversity on ecosystem functioning: a consensus of current knowledge. Ecological monographs 75:3–35

    Article  Google Scholar 

  • Hothorn T, Hornik K, Zeileis A (2006) Unbiased recursive partitioning: a conditional inference framework. J Comp Graph Stat 15:651–674

    Article  Google Scholar 

  • Houlahan JE, Keddy PA, Makkay K, Findlay CS (2006) The effects of adjacent land use on wetland species richness and community composition. Wetlands 26:79–96

    Article  Google Scholar 

  • Hrivnák R, Oťaheľová H, Valachovič M, Paľove-Balang P, Kubinská A (2010) Effect of environmental variables on the aquatic macrophyte composition pattern in streams: a case study from Slovakia. Fundam Appl Limnol 177:115–124

    Article  Google Scholar 

  • Hrivnák R, Oťaheľová H, Kochjarová J, Paľove-Balang P (2013) Effect of environmental conditions on species composition of macrophytes – study from two distinct biogeographical regions of Central Europe. Knowl Managt Aquatic Ecosyst 411:09

  • Janauer GA (2003) Methods. In Janauer GA, Hale P, Sweeting R (eds) Macrophyte inventory of the river Danube: A pilot study. Arch Hydrobiol, Large Rivers 14:9–16

  • Janauer GA, Dokulil M (2006) Macrophytes and algae in running waters. In Ziglio G, Siligardi M, Flaim G (eds) Biological monitoring of rivers. John Wiley & Sons, Chichester, pp 89–109

    Chapter  Google Scholar 

  • Jones JI, Collins AL, Naden PS, Sear DA (2012) The relationship between fine sediment and macrophytes in rivers. River Res Appl 28:1006–1018

    Article  Google Scholar 

  • Karatayev AY, Burlakova LE, Dodson SI (2008) Community analysis of Belarusian lakes: correlations of species diversity with hydrochemistry. Hydrobiologia 605:99–112

    CAS  Article  Google Scholar 

  • Lacoul P, Freedman B (2006) Environmental influences on aquatic plants in freshwater ecosystems. Environ Rev 14:89–136

    Article  Google Scholar 

  • Liaw A, Wiener M (2002) Classification and regression by randomForest. R News 2:18–22

  • Linton S, Goulder R (2000) Botanical conservation value related to origin and management of ponds. Aquatic Conserv Mar Freshw Ecosyst 10:77–91

    Article  Google Scholar 

  • Manolaki P, Papastergiadou E (2013) The impact of environmental factors on the distribution pattern of aquatic macrophytes in a middle-sized Mediterranean stream. Aquatic Bot 104: 34–46

    Article  Google Scholar 

  • Marhold K, Hindák F (1998) Zoznam nižších a vyšších rastlín flóry Slovenska (Checklist of nonvascular and vascular plants of Slovakia). Veda, Bratislava

  • Miklós L (2002) Atlas krajiny Slovenskej republiky. 1 vydanie (Landscape atlas of Slovakia. First edition). Ministerstvo životného prostredia Slovenskej republiky, Bratislava & Slovenská agentúra životného prostredia, Banská Bystrica

  • Murphy KJ (2002) Plant communities and plant diversity in softwater lakes of northern Europe. Aquatic Bot 73:287–324

    Article  Google Scholar 

  • Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O’Hara RB, Simpson GL, Solymos P, Stevens MHH, Wagner H (2013) Vegan: Community ecology package. R package Version 2.0–6

  • Prasad AM, Iverson LR, Liaw A (2006) Newer classification and regression tree techniques: bagging and random forests for ecological prediction. Ecosystems 9:181–199

    Article  Google Scholar 

  • Ricciardi A, Rasmussen JB (1999) Extinction rates of North American freshwater fauna. Conserv Biol 13:1220–1222

    Article  Google Scholar 

  • R Core Team (2013) A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria

    Google Scholar 

  • Rørslett B (1991) Principal determinants of aquatic macrophyte richness in northern European lakes. Aquatic Bot 39:173–193

    Article  Google Scholar 

  • Sand-Jensen K (1998) Influence of submerged macrophytes on sediment composition and near-bed flow in lowland streams. Freshw Biol 39:663–679

    Article  Google Scholar 

  • Sand-Jensen K, Borum J (1991) Interactions among phytoplankton, periphyton, and macrophytes in temperate freshwaters and estuaries. Aquatic Bot 41:137–175

    Article  Google Scholar 

  • Sand-Jensen K, Pedersen NL, Thorsgaard I, Moeslund B, Borum J, Brodersen KP (2008) 100 years of vegetation decline and recovery in Lake Fure, Denmark. J Ecol 96: 260–271

    Article  Google Scholar 

  • Strobl C, Boulesteix AL, Zeileis A, Hothorn T (2007) Bias in random forest variable importance measures: illustrations, sources and a solution. BMC bioinformatics 8:25

    Article  PubMed  PubMed Central  Google Scholar 

  • Strobl C, Malley J, Tutz G (2009) An introduction to recursive partitioning: rationale, application, and characteristics of classification and regression trees, bagging, and random forests. Psychological Methods 14:323–348

    Article  PubMed  PubMed Central  Google Scholar 

  • Vestergaard O, Sand-Jensen K (2000) Aquatic macrophyte richness in Danish lakes in relation to alkalinity, transparency, and lake area. Can J Fish Aquatic Sci 57:2022–2031

    Article  Google Scholar 

  • Willby NJ, Abernethy VJ, Demars BOL (2000) Attribute-based classification of European hydrophytes and its relationship to habitat utilization. Freshwater Biol 43:43–74

    Article  Google Scholar 

  • Williams P, Whitfield M, Biggs J, Bray S, Fox G, Nicolet P, Sear D (2003) Comparative biodiversity of rivers, streams, ditches and ponds in an agricultural landscape in Southern England. Biol Conserv 115:329–341

    Article  Google Scholar 

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Acknowledgements

This work was supported by the Slovak Research and Development Agency under contract No. APVV-0059-11. This study was also partially funded by the Slovak Scientific Grant Agency (VEGA, project No. 2/0004/11). We are grateful to Ivana Svitková for language editing and comments on an early version of the manuscript.

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Correspondence to Richard Hrivnák.

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Plant nomenclature Marhold and Hindák (1998)

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Svitok, M., Hrivnák, R., Kochjarová, J. et al. Environmental thresholds and predictors of macrophyte species richness in aquatic habitats in central Europe. Folia Geobot 51, 227–238 (2016). https://doi.org/10.1007/s12224-015-9211-2

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  • DOI: https://doi.org/10.1007/s12224-015-9211-2

Keywords

  • aquatic plants
  • diversity
  • random forests
  • regression trees
  • Slovakia