Hostname: page-component-78c5997874-j824f Total loading time: 0 Render date: 2024-11-02T19:53:20.317Z Has data issue: false hasContentIssue false
  • English
  • Français

The relationships between land cover, climate and cave copepod spatial distribution and suitability along the Carpathians

Published online by Cambridge University Press:  15 November 2013

IOANA NICOLETA MELEG ,
MAGDALENA NĂPĂRUŞ ,
FRANK FIERS ,
IONUŢ HOREA MELEG ,
MARIUS VLAICU  and
OANA TEODORA MOLDOVAN
IOANA NICOLETA MELEG*
Affiliation:
Emil Racoviţă Institute of Speleology, Romanian Academy, Clinicilor 5, PO BOX 58, 400006, Cluj-Napoca, Romania
MAGDALENA NĂPĂRUŞ
Affiliation:
Tular Cave Laboratory, Kranj, Slovenia Transdisciplinary Center Landscape-Territory-Information Systems, University of Bucharest, Faculty of Geography, 1, N. Balcescu Bd, 010041 Bucureşti, Romania
FRANK FIERS
Affiliation:
Royal Belgian Institute of Natural Sciences, Vautierstraat 29, B-1000 Bruxelles, Belgium
IONUŢ HOREA MELEG
Affiliation:
Babeş-Bolyai University, Faculty of Geography, Clinicilor 5–7, 400006 Cluj-Napoca, Romania
MARIUS VLAICU
Affiliation:
Emil Racoviţă Institute of Speleology, Romanian Academy, Calea 13 Septembrie 13, Bucureşti, Romania
OANA TEODORA MOLDOVAN
Affiliation:
Emil Racoviţă Institute of Speleology, Romanian Academy, Clinicilor 5, PO BOX 58, 400006, Cluj-Napoca, Romania
*
*Correspondence: Dr Ioana Nicoleta Meleg e-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Summary

The distribution of subterranean copepods may reflect the persistence of cave assemblages in relation to the environmental health of the overlying landscape. Areas supporting groundwater fauna were established by modelling the persistence of seven copepod species using a geographical information system (GIS). Environmental drivers were found to influence subterranean copepod distribution in the caves of the Romanian Carpathians. Habitat-based modelling, using ordinary least squares regression and geographically-weighted regression to identify the significant predictors explaining copepod habitat suitability, predicted suitable areas for the selected taxa. The most constant predictor was land cover, a measure of human impact and climate change, followed by precipitation and altitude. The model performed well for the majority of analysed taxa, and the areas predicted as suitable for narrowly distributed taxa overlapped with observed distributions. GIS facilitated the prediction of suitable habitat, and also enabled spatial autocorrelation to be tested. The results of this study demonstrate the importance of sustainable management of the terrestrial surface in limestone areas in conserving copepod biodiversity.

Keywords

conservationcopepodsenvironmental driversgeographically-weighted regressionhabitat suitability modelssubterranean habitats
Type
THEMATIC SECTION: Spatial Simulation Models in Planning for Resilience
Information
Environmental Conservation , Volume 41 , Issue 2 , June 2014 , pp. 206 - 216
Copyright
Copyright © Foundation for Environmental Conservation 2013 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Akaike, H. (1974) A new look at the statistical model identification. IEEE Transactions on Automatic Control 19: 716–723.Google Scholar
Bacaro, G., Santi, E., Rocchini, D., Pezzo, F., Puglisi, L. & Chiarucci, A. (2011) Geostatistical modelling of regional bird species richness: exploring environmental proxies for conservation purpose. Biodiversity and Conservation 20: 1677–1694.Google Scholar
Bio, A.M.F., De Becker, P., De Bie, E., Huybrechts, W. & Wassen, M. (2002) Prediction of plant species distribution in lowland river valleys in Belgium: modelling species response to site conditions. Biodiversity and Conservation 11: 2189–2216.Google Scholar
Bennett, G. (2002) Ecoregion-Based Conservation: The Carpathians: Final Reconnaissance Report. Vienna, Austria: WWF-International Danube–Carpathian Programme.Google Scholar
Boulton, A.J., Fenwick, G.D., Hancock, P.J. & Harvey, M.S. (2008) Biodiversity, functional roles and ecosystem services of groundwater invertebrates. Invertebrate Systematics 22: 103–116.CrossRefGoogle Scholar
Brotons, L., Mañosa, S. & Estrada, J. (2004) Modelling the effects of irrigation schemes on the distribution of steppe birds in Mediterranean farmland. Biodiversity and Conservation 13: 1039–1058.Google Scholar
Cardoso, P., Borges, P.A.V., Triantis, K.A., Ferrández, M.A. & Martín, H.L. (2010) Adapting the IUCN Red List criteria for invertebrates. Biological Conservation 144: 2432–2440.Google Scholar
Castany, G. (1982) Principes et méthodes de l'hydrogéologie. Paris, France: Dunod Université. Ed. Bordas.Google Scholar
Castellarini, F., Malard, F., Dole-Olivier, M.-J. & Gibert, J. (2007) Modelling the distribution of stygobionts in the Jura Mountains (eastern France). Implications for the protection of ground waters. Diversity and Distributions 13: 213–224.Google Scholar
Costa, G.C., Wolfe, C., Shepard, D.B., Caldwell, J.P. & Vitt, L.J. (2008) Detecting the influence of climatic variables on species distributions: a test using GIS niche-based model along a steep longitudinal environmental gradient. Journal of Biogeography 35: 637–646.Google Scholar
Damian-Georgescu, A. (1963) Copepoda. Fam. Cyclopidae (forme de apă dulce). Fauna Republicii Populare Romîne. Crustacea 4(6). Bucureşti, Romînia: Academia Republicii Populare Romînia.Google Scholar
Damian-Georgescu, A. (1970) Copepoda. Harpacticoida (forme de apă dulce). Fauna Republicii Populare Romîne. Crustacea 4(11). Bucureşti, Romînia: Academia Republicii Populare Romînia.Google Scholar
Danielopol, D.L., Artheau, M. & Marmonier, P. (2009) Site prioritisation for the protection of rare subterranean species: the cases of two ostracods from south-western France. Freshwater Biology 54: 877–884.Google Scholar
Danielopol, D.L., Pospisil, P. & Rouch, R. (2000) Biodiversity in groundwater: a large-scale view. Trends in Ecology and Evolution 15: 223–224.CrossRefGoogle ScholarPubMed
Davin, E.L. & de Noblet-Ducoudré, N. (2010) Climatic Impact of Global-Scale Deforestation: Radiative versus Nonradiative Processes. Journal of Climate 23: 97–112.Google Scholar
Deharveng, L., Stoch, F., Gibert, J., Bedos, A., Galassi, D., Zagmajster, M., Brancelj, A., Camacho, A., Fiers, F., Martin, P., Giani, N., Magniez, G. & Marmonier, P. (2009) Groundwater biodiversity in Europe. Freshwater Biology 54: 709–726.CrossRefGoogle Scholar
Di Lorenzo, T., Stoch, F., Fiasca, B., Gattone, E., De Laurentiis, P., Ranalli, F. & Galassi, D.M.P. (2005) Environmental quality of the groundwater in the Lessinian Massif (Italy): signposts for sustainability. In: Proceedings of an International Symposium on World Subterranean Biodiversity, ed. Gibert, J., pp. 115–124. Villeurbanne, France: University of Lyon.Google Scholar
Dole-Olivier, M.-J., Marmonier, P., Creuzé des Châtelliers, M. & Martin, D. (1994) Interstitial fauna associated with the alluvial floodplains of the Rhône river (France). In: Groundwater Ecology, ed. Gibert, J., Danielopol, D.L. & Stanford, J.A., pp. 313–346. San Diego, CA, USA: Academic Press.Google Scholar
Dussart, B. & Defaye, D. (2006) World Directory of Crustacea Copepoda of Inland Waters. II - Cyclopiformes. Leiden, the Netherlands: Backhuys Publishers.Google Scholar
Elith, J., Graham, C.H., Anderson, R.P., Dudik, M., Ferrier, S., Guisan, A., Hijmans, R.J., Huettmann, H., Leathwick, J.R., Lehmann, A., Li, J., Lohmann, L.G., Loiselle, B.A., Manion, G., Moritz, C., Nakamura, M., Nakazawa, Y., Overton, J.C., Peterson, A.T., Phillips, S.J., Richardson, K., Scachetti-Pereira, R., Schapire, R.E., Soberón, J., Williams, S., Wisz, M.S. & Zimmermann, N.E. (2006) Novel methods improve prediction of species’ distributions from occurrence data. Ecography 29: 129–151.Google Scholar
Elith, J., Phillips, S.J., Hastie, T., Dudik, M., Chee, Y.E. & Yates, C.J. (2011) A statistical explanation of MaxEnt for ecologists. Diversity and Distributions 17: 43–57.Google Scholar
ESRI (2010) ArcGIS 9.3.1. Environmental Systems Research Institute, Inc., USA.Google Scholar
European Commission (2013) The Habitats Directive [www document]. URL http://ec.europa.eu/environment/nature/legislation/habitatsdirective/ Google Scholar
European Council (1980) Council Directive 80/68/EEC of 17 December 1979 on the protection of groundwater against pollution caused by certain dangerous substances as amended by Council Directive 91/692/EEC (further amended by Council Regulation 1882/2003/EC) [www document]. URL http://eur-lex.europa.eu/LexUriServ/site/en/consleg/1980/L/01980L0068–19911223-en.pdf Google Scholar
European Council (2006) Directive 2006/118/EC of the European Parliament and of the Council of 12 December 2006 on the protection of groundwater against pollution and deterioration [www document]. URL http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2006:372:0019:0019:EN:PDF Google Scholar
Fiers, F. & Moldovan, O.T. (2008) Redescription of Spelaeocamptus spelaeus (Chappuis 1925), a subterranean copepod endemic to the Apuseni Mountains in Romania (Copepoda Harpacticoida). Subterranean Biology 6: 51–64.Google Scholar
Finch, J.M., Samways, M.J., Hill, T.R., Piper, S.E. & Taylor, S. (2006) Application of predictive distribution modelling to invertebrates: Odonata in South Africa. Biodiversity and Conservation 15: 4239–4251.Google Scholar
Fotheringham, A., Brunsdon, C. & Charlton, M. (2002) Geographically weighted regression: the analysis of spatially varying relationships. Chichester, England: John Wiley & Sons Ltd.Google Scholar
Galassi, D.M.P., Huys, R. & Reid, J. (2009). Diversity, ecology and evolution of groundwater copepods. Freshwater Biology 54: 691–708.Google Scholar
Gibert, J., ed. (2005) World Subterranean Biodiversity. Proceedings of an International Symposium. Lyon, France: Université Claude Bernard.Google Scholar
Gibert, J. & Deharveng, L. (2002) Subterranean ecosystems: a truncated functional biodiversity. BioScience 52: 473–481.Google Scholar
Gibert, J., Culver, D.C., Dole-Olivier, M.-J., Malard, F., Christman, M.C. & Deharveng, L. (2009) Assessing and conserving groundwater biodiversity: synthesis and perspectives. Freshwater Biology 54: 930–941.Google Scholar
Goodchild, F.M. (1986) Spatial Autocorrelation. Norwich, UK: Geo Books: 57 pp.Google Scholar
Griebler, C., Stein, H., Kellermann, C., Berkhoff, S., Brielmann, H., Schmidt, S., Selesi, D., Steube, C., Fuchs, A & Hahn, H.J. (2010) Ecological assessment of groundwater ecosystems. Vision or illusion? Ecological Engineering 36: 1174–1190.Google Scholar
Guisan, A. & Thuiller, W. (2005) Predicting species distribution: offering more than simple habitat models. Ecology Letters 8: 993–1009.Google Scholar
Hancock, P.J., Boulton, A.J. & Humphreys, W.F. (2005) Aquifers and hyporheic zones: towards an ecological understanding of groundwater. Hydrogeology Journal 13: 98–111.Google Scholar
Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G. & Jarvis, A. (2005) Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965–1978 [www document]. URL http://www.worldclim.org/ Google Scholar
Iepure, S. & Defaye, D. (2008) The Acanthocyclops kieferi complex (Copepoda, Cyclopoida) from south-eastern Europe, with description of a new species. Crustaceana 81: 611–630.Google Scholar
Kenneth, R.S., Strager, M.P. & Welsh, S.A. (2013) Advantages of geographically weighted regression for modeling benthic substrate in two Greater Yellowstone ecosystem streams. Environmental Modeling and Assessment 18: 209–219.Google Scholar
Kopp, D., Santoul, F., Poulet, N., Compin, A. & Céréghino, R. (2010) Patterning the distribution of threatened crayfish and their exotic analogues using self-organizing maps. Environmental Conservation 37: 147–154.Google Scholar
Lefébure, T., Douady, C.J., Gouy, M., Trontelj, P., Briolay, J. & Gibert, J. (2006) Phylogeography of a subterranean amphipod reveals cryptic diversity and dynamic evolution in extreme environments. Molecular Ecology 15: 1797–1806.Google Scholar
Linkie, M., Chapron, G., Martyr, D.J., Holden, J. & Leader-Williams, N. (2006) Assessing the viability of tiger subpopulations in a fragmented landscape. Journal of Applied Ecology 43: 576–586.Google Scholar
Malard, F., Reygrobellet, J.-L. & Laurent, R. (1998) Spatial distribution of epigean invertebrates in an alluvial aquifer polluted by iron and manganese, Rhône River, France. Verhandlungen der Internationalen Vereinigung für Limnologie 26: 1590–1594.Google Scholar
Malard, F., Reygrobellet, J.-L., Mathieu, J. & Lafont, M. (1994) The use of invertebrate communities to describe groundwater flow and contaminant transport in a fractured rock aquifer. Archiv für Hydrobiologie 131: 93–110.Google Scholar
Martínez-Freiría, F., Sillero, N., Lizana, M. & Brito, J.C. (2008) GIS-based niche models identify environmental correlates sustaining a contact zone between three species of European vipers. Diversity and Distributions 14: 452–461.Google Scholar
Meleg, I.N., Moldovan, O.T., Iepure, S., Fiers, F. & Brad, T. (2011) Diversity patterns of fauna in dripping water of caves from Transylvania. Annales de Limnologie - International Journal of Limnology 47: 185–197.Google Scholar
Meleg, I.N., Fiers, F., Robu, M. & Moldovan, O.T. (2012) Distribution patterns pf subsurface copepods and the impact of environmental parameters. Limnologica 42: 156–164.Google Scholar
Mitchell, A. (2005) The ESRI guide to GIS analysis: spatial measurements and statistics. Redlands, CA, USA: ESRI Press.Google Scholar
Moldovan, O.T., Iepure, S. & Perşoiu, A. (2005) Biodiversity and protection of Romanian karst areas: the example of interstitial fauna. In: Water Resources and Environmental Problems in Karst. Proceedings International Conference and Field Seminary, ed. Stevanoviæ, Z. & Milanoviæ, P., pp. 831–836. Belgrade, Serbia & Montenegro: Belgrade & Kotor.Google Scholar
Moldovan, O.T., Pipan, T., Iepure, S., Mihevc, A. & Mulec, J. (2007) Biodiversity and ecology of fauna in percolating water in selected Slovenian and Romanian caves. Acta Carsologica 36: 493–501.Google Scholar
Moldovan, O.T., Levei, E., Banciu, M., Banciu, H.L., Marin, C., Pavelescu, C., Brad, T., Cîmpean, M., Meleg, I., Iepure, S. & Povară, I. (2011) Spatial distribution patterns of the hyporheic invertebrate communities in a polluted river in Romania. Hydrobiologia 669: 63–82.Google Scholar
Moldovan, O.T., Meleg, I.N. & Perşoiu, A. (2012) Habitat fragmentation and its effects on groundwater populations. Ecohydrology 5: 445–452.Google Scholar
Moldova, O.T., Meleg, I.N., Levei, E. & Terente, M. (2013) A simple method for assessing biotic indicators and predicting biodiversity in the hyporheic zone of a river polluted with metals. Ecological Indicators 24: 412–420.CrossRefGoogle Scholar
Mösslacher, F. & Notenboom, J. (1999) Groundwater biomonitoring. In: Biomonitoring of Polluted Water, ed. Gerhardt, A., pp. 119–140. Zürich, Switzerland: Trans Tech Publications.Google Scholar
Năpăruş, M. & Kuntner, M. (2012) A GIS model predicting global distributions of a lineage: a test case on hermit spiders (Nephilidae: Nephilengys). PLoS ONE 7: e30047. doi:10.1371 /journal.pone.0030047 Google Scholar
Neilson, R.P. (1995) A model for predicting continental-scale vegetation distribution and water balance. Ecological Applications 5: 362–385.Google Scholar
Osborne, P.E., Foody, G.M. & Suárez-Seoane, S. (2007) Non-stationarity and local approaches to modeling the distributions of wildlife. Diversity and Distributions 13: 313–323.Google Scholar
Paran, F., Malard, F., Mathieu, J., Lafont, M., Galassi, D.M.P. & Marmonier, P. (2005) Distribution of groundwater invertebrates along an environmental gradient in a shallow water-table aquifer. In: World Subterranean Biodiversity, Proceedings of an International Symposium, ed. Gibert, J., pp. 99–105. Lyon, France: Université Claude Bernard.Google Scholar
Pipan, T., Blejec, A. & Brancelj, A. (2006) Multivariate analysis of copepod assemblages in epikarstic waters of some Slovenian caves. Hydrobiologia 559: 213–223.Google Scholar
Rodríguez, J.P., Brotons, L., Bustamante, J. & Seoane, J. (2007) The application of predictive modelling of species distribution to biodiversity conservation. Diversity and Distributions 13: 243–251.Google Scholar
Schmidt, S.I. & Hahn, H.S. (2012) What is groundwater and what does this mean to fauna? An opinion. Limnologica 42: 1–6.Google Scholar
Schmitt, T. & Rákosy, L. (2007) Changes of traditional agrarian landscapes and their conservation implications: a case study of butterflies in Romania. Diversity and Distributions 13: 855–862.Google Scholar
Segurado, P. & Araújo, M. (2004) An evaluation of methods for modelling species distributions. Journal of Biogeography 31: 1555–1568.Google Scholar
Simpson, M. & Prots, B. (2013) Predicting the distribution of invasive plants in the Ukrainian Carpathians under climatic change and intensification of anthropogenic disturbances: implications for biodiversity conservation. Environmental Conservation 40: 167–181.Google Scholar
Stein, H., Kellermann, C., Schmidt, S.I., Brielmann, H., Steube, C., Berkhoff, S.E., Fuchs, A., Hahn, H.J., Thulin, B. & Griebler, C. (2010) The potential use of fauna and bacteria as ecological indicators for the assessment of groundwater quality. Journal of Environmental Monitoring 12: 242–254.Google Scholar
Stoch, F. & Galassi, D.M.P. (2010) Stygobiotic crustacean species richness: a question of numbers, a matter of scale. Hydrobiologia 653: 217–234.CrossRefGoogle Scholar
United Nations Environment Programme (2007) Carpathians Environment Outlook. Bielsko-Biala, Poland: Dimograf Printing House.Google Scholar
Vandewalle, M., de Bello, F., Berg, M.P., Bolger, T., Dolédec, S., Duds, F., Feld, C.K., Harrington, R., Harrison, P.A., Lavorel, S., da Silva, P.M., Moretti, M., Niemelä, J., Santos, P., Sattler, T., Sousa, J.P., Sykes, M.T., Vanbergen, A.J. & Woodcock, B.A. (2010) Functional traits as indicators of biodiversity response to land use changes across ecosystems and organisms. Biodiversity and Conservation 19: 2921–2947.CrossRefGoogle Scholar
Wells, J.B.J. (2007) An annotated checklist and keys to the species of Copepoda Harpacticoida (Crustacea). Zootaxa 1568: 1–872.Google Scholar
Williams, P.W. (2004) The epikarst: evolution of understanding. In: Proceedings of the Symposium on Epikarst, ed. Jones, W.K., Culver, D.C. & Herman, J.S., pp. 8–15. Charles Town, WV, USA: Karst Waters Institute Special Publication 9.Google Scholar
Whittaker, R.H., Araújo, M.B., Jepson, P., Ladle, R.J., Watson, J.E.M. & Willis, K.J. (2005) Conservation Biogeography: assessment and prospect. Diversity and Distributions 11: 3–23.Google Scholar
Yates, C.J., Elith, J., Latimer, A.M., Le Maitre, D., Midgley, G.F., Schurr, F.M. & West, A.G. (2010) Projecting climate change impacts on species distributions in megadiverse South African Cape and Southwest Australian Floristic Regions: opportunities and challenges. Austral Ecology 35: 374–391.Google Scholar
Supplementary material: File

Meleg et al. Supplementary Material

Appendix

Download Meleg et al. Supplementary Material(File)
File 2 MB
Supplementary material: Image

Meleg et al. Supplementary Material

Figure

Download Meleg et al. Supplementary Material(Image)
Image 409.8 KB
Supplementary material: Image

Meleg et al. Supplementary Material

Figure

Download Meleg et al. Supplementary Material(Image)
Image 680.9 KB
Supplementary material: Image

Meleg et al. Supplementary Material

Figure

Download Meleg et al. Supplementary Material(Image)
Image 444.9 KB
Supplementary material: Image

Meleg et al. Supplementary Material

Figure

Download Meleg et al. Supplementary Material(Image)
Image 405.9 KB
Supplementary material: Image

Meleg et al. Supplementary Material

Figure

Download Meleg et al. Supplementary Material(Image)
Image 452.1 KB
Supplementary material: File

Meleg et al. Supplementary Material

Data

Download Meleg et al. Supplementary Material(File)
File 80.9 KB
Supplementary material: File

Meleg et al. Supplementary Material

Data

Download Meleg et al. Supplementary Material(File)
File 27.1 KB