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Environmental Niche Modelling Predicts a Contraction in the Potential Distribution of Two Boreal Owl Species under Different Climate Scenarios

. 2022 Nov 21 ; 12 (22) : . [epub] 20221121

Status PubMed-not-MEDLINE Language English Country Switzerland Media electronic

Document type Journal Article

Studying current and future geographic distribution is essential for conserving endangered species such as the Boreal Owl and Eurasian Pygmy Owl. The main aim of this study was to determine the potential distribution of both species in the Balkan Peninsula by using spatial distribution models (SDMs) in MaxEnt. We used data from field surveys, the scientific and grey literature, and an online database. We considered the current time and two future periods, 2041-2060 and 2061-2080. For future periods, we included different climate scenarios (SSP 126, 245, 370, and 585) in studying the potential geographic distribution of both species. We identified two types of potential future refugia for species: in situ and ex situ. Our study shows the highly suitable area for the Boreal Owl increased during the 2041-2060 period compared with the current area in all scenarios, except in SSP 585. However, during the 2061-2080 period, the highly suitable areas contracted. For the Eurasian Pygmy Owl, highly suitable areas decreased during 2041-2060, but during the 2061-2080 period, it was larger than the current area. Our study is of importance for conservation and preserving areas of potential distribution and refugia for Boreal and Eurasian Pygmy Owls in the face of climate change.

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MEA—Millennium Ecosystem Assessment . Ecosystems and Human Well-Being: Synthesis. Island Press; Washington, DC, USA: [(accessed on 28 September 2022)]. p. 7815. Available online: www.islandpress.org.

Michael R.W.R., William M.A., Bennun L., Stuart H.M.B., Clements A., Coomes D., Entwistle A., Hodge I., Kapos V., Jörn P.W.S., et al. Biodiversity Conservation: Challenges Beyond 2010. Science. 2010;329:1298–1303. PubMed

Mace G.M., Norris K., Fitter A.H. Biodiversity and ecosystem services: A multilayered relationship. Trends Ecol. Evol. 2011;27:19–26. doi: 10.1016/j.tree.2011.08.006. PubMed DOI

Ceballos G., Ehrlich P.R., Barnosky A.D., García A., Pringle R.M., Palmer T.M. Accelerated modern human–induced species losses: Entering the sixth mass extinction. Environ. Sci. 2015;1:1–5. doi: 10.1126/sciadv.1400253. PubMed DOI PMC

De Vos J.M., Joppa L.N., Gittleman J.L., Stephens P.R., Pimm S.L. Estimating the normal background rate of species extinction. Conserv. Biol. 2015;29:452–462. doi: 10.1111/cobi.12380. PubMed DOI

Pimm S.L., Jenkins C.N., Abell R., Brooks T.M., Gittleman J.L., Joppa L.N., Raven P.H., Roberts C.M., Sexton J.O. The biodiversity of species and their rates of extinction, distribution, and protection. Science. 2014;34:1–10. doi: 10.1126/science.1246752. PubMed DOI

IPBES The Global Assessment Report on Biodiversity and Ecoystem Services, Summary for Policymakers. [(accessed on 28 September 2022)]. Published online 2019. Available online: www.ipbes.net.

Skea J., Sjukla P., Reisinger A., Slade R., Pathak M., Some P., Vyas P., Fradera R., Belkacemi M., Hasija A., et al. IPCC Climate Change 2022—Mitigation of Climate Change—Working Group III. Cambridge Univ. Press; Cambridge, UK: 2022. p. 1454.

Loarie S.R., Carter B.E., Hayhoe K., McMahon S., Moe R., Knight C.A., Ackerly D.D. Climate change and the future of California’s endemic flora. PLoS ONE. 2008;3:1–10. doi: 10.1371/journal.pone.0002502. PubMed DOI PMC

Lehikoinen A., Johnston A., Massimino D. Climate and land use changes: Similarity in range and abundance changes of birds in Finland and Great Britain. Ornis Fernica. 2021;98:1–15.

Pélissié M., Johansson F., Hyseni C. Pushed Northward by Climate Change: Range Shifts With a Chance of Co-occurrence Reshuffling in the Forecast for Northern European Odonates. Environ. Entomol. 2022;51:910–921. doi: 10.1093/ee/nvac056. PubMed DOI PMC

Workie T.G., Debella H.J. Climate change and its effects on vegetation phenology across ecoregions of Ethiopia. Glob. Ecol. Conserv. 2018;13:e00366. doi: 10.1016/j.gecco.2017.e00366. DOI

Diele-Viegas L.M., Werneck F.P., Rocha C.F.D. Climate change effects on population dynamics of three species of Amazonian lizards. Comp. Biochem. Physiol. -Part A Mol. Integr. Physiol. 2019;236:110530. doi: 10.1016/j.cbpa.2019.110530. PubMed DOI

Van De Pol M., Vindenes Y., Sæther B.E., Engen S., Ens B.J., Oosterbeek K., Tinbergen J.M. Effects of climate change and variability on population dynamics in a long-lived shorebird. Ecology. 2010;91:1192–1204. doi: 10.1890/09-0410.1. PubMed DOI

Yang H., Wu M., Liu W., Zhang Z., Zhang N., Wan S. Community structure and composition in response to climate change in a temperate steppe. Glob. Chang. Biol. 2011;17:452–465. doi: 10.1111/j.1365-2486.2010.02253.x. DOI

Heidari H., Arabi M., Warziniack T. Effects of climate change on natural-caused fire activity in western U.S. national forests. Atmosphere. 2021;12:981. doi: 10.3390/atmos12080981. DOI

Grimm N.B., Chapin F.S., Bierwagen B., Gonzalez P., Groffman P.M., Luo Y., Melton F., Nadelhoffer K., Pairis A., Raymond P.A., et al. The impacts of climate change on ecosystem structure and function. Front. Ecol. Environ. 2013;11:474–482. doi: 10.1890/120282. DOI

Peh K.S.H. Potential effects of climate change on elevational distributions of tropical birds in Southeast Asia. Condor. 2007;109:437–441. doi: 10.1093/condor/109.2.437. DOI

Freeman B.G., Class Freeman A.M. Rapid upslope shifts in New Guinean birds illustrate strong distributional responses of tropical montane species to global warming. Proc. Natl. Acad. Sci. USA. 2014;111:4490–4494. doi: 10.1073/pnas.1318190111. PubMed DOI PMC

Couet J., Marjakangas E.L., Santangeli A., Kålås J.A., Lindström Å., Lehikoinen A. Short-lived species move uphill faster under climate change. Oecologia. 2022;198:877–888. doi: 10.1007/s00442-021-05094-4. PubMed DOI PMC

Levinsky I., Skov F., Svenning J.C., Rahbek C. Potential impacts of climate change on the distributions and diversity patterns of European mammals. Biodivers. Conserv. 2007;16:3803–3816. doi: 10.1007/s10531-007-9181-7. DOI

Dullinger S., Gattringer A., Thuiller W., Moser D., Zimmermann N.E., Guisan A., Willner W., Plutzar C., Leitner M., Mang T., et al. Extinction debt of high-mountain plants under twenty-first-century climate change. Nat. Clim. Chang. 2012;2:619–622. doi: 10.1038/nclimate1514. DOI

Jiguet F., Gregory R.D., Devictor V., Green R.E., Vořšek P., Van Strien A., Couvet D. Population trends of European common birds are predicted by characteristics of their climatic niche. Glob. Chang. Biol. 2010;16:497–505. doi: 10.1111/j.1365-2486.2009.01963.x. DOI

Koh L.P., Sodhi N.S., Brook B.W. Ecological correlates of extinction proneness in tropical butterflies. Conserv. Biol. 2004;18:1571–1578. doi: 10.1111/j.1523-1739.2004.00468.x. DOI

Manes S., Costello M.J., Beckett H., Debnath A., Devenish-Nelson E., Grey K.A., Jenkins R., Khan T.M., Kiessling W., Krause C., et al. Endemism increases species’ climate change risk in areas of global biodiversity importance. Biol. Conserv. 2021;257:109070. doi: 10.1016/j.biocon.2021.109070. DOI

Trew B.T., Maclean I.M.D. Vulnerability of global biodiversity hotspots to climate change. Glob. Ecol. Biogeogr. 2021;30:768–783. doi: 10.1111/geb.13272. DOI

Guisan A., Zimmermann N.E. Predictive habitat distribution models in ecology. Ecol. Modell. 2000;135:147–186. doi: 10.1016/S0304-3800(00)00354-9. DOI

Warren D.L., Glor R.E., Turelli M. Environmental Niche Versus Conservatism: Quantitative Approaches to Niche Evolution. Evolution. 2008;62:2868–2883. doi: 10.1111/j.1558-5646.2008.00482.x. PubMed DOI

Elith J., Leathwick J.R. Species distribution models: Ecological explanation and prediction across space and time. Annu. Rev. Ecol. Evol. Syst. 2009;40:677–697. doi: 10.1146/annurev.ecolsys.110308.120159. DOI

Booth T.H., Nix H.A., Busby J.R., Hutchinson M.F. Bioclim: The first species distribution modelling package, its early applications and relevance to most current MaxEnt studies. Divers. Distrib. 2014;20:1–9. doi: 10.1111/ddi.12144. DOI

Phillips S.J., Anderson R.P., Schapire R.E. Maximum entropy modeling of species geographic distributions. Ecol. Modell. 2006;190:231–259. doi: 10.1016/j.ecolmodel.2005.03.026. DOI

Brambilla M., Rubolini D., Appukuttan O., Calvi G., Karger D.N., Kmecl P., Mihelič T., Sattler T., Seaman B., Teufelbauer N., et al. Identifying climate refugia for high-elevation Alpine birds under current climate warming predictions. Glob. Chang. Biol. 2022;28:4276–4291. doi: 10.1111/gcb.16187. PubMed DOI PMC

Araújo M.B., Williams P.H. Selecting areas for species persistence using occurrence data. Biol. Conserv. 2000;96:331–345. doi: 10.1016/S0006-3207(00)00074-4. DOI

Sun X., Long Z., Jia J. A multi-scale Maxent approach to model habitat suitability for the giant pandas in the Qionglai mountain, China. Glob. Ecol. Conserv. 2021;30:e01766. doi: 10.1016/j.gecco.2021.e01766. DOI

Spiers J.A., Oatham M.P., Rostant L.V., Farrell A.D. Applying species distribution modelling to improving conservation based decisions: A gap analysis of trinidad and tobago’s endemic vascular plants. Biodivers. Conserv. 2018;27:2931–2949. doi: 10.1007/s10531-018-1578-y. DOI

Warren D.L., Wright A.N., Seifert S.N., Shaffer H.B. Incorporating model complexity and spatial sampling bias into ecological niche models of climate change risks faced by 90 California vertebrate species of concern. Divers. Distrib. 2014;20:334–343. doi: 10.1111/ddi.12160. DOI

Phillips S.B., Aneja V.P., Kang D., Arya S.P. Modelling and analysis of the atmospheric nitrogen deposition in North Carolina. Int. J. Glob. Environ. Issues. 2006;6:231–252. doi: 10.1504/IJGENVI.2006.010156. DOI

Phillips S.J., Dudik M., Schapire R.E. Maxent Software for Modeling Species Niches and Distributions (Version 3.4.1) [(accessed on 18 September 2022)]. Available online: http://biodiversityinformatics.amnh.org/open_source/maxent/

Elith J., Phillips S.J., Hastie T., Dudík M., Chee Y.E., Yates C.J. A statistical explanation of MaxEnt for ecologists. Divers. Distrib. 2011;17:43–57. doi: 10.1111/j.1472-4642.2010.00725.x. DOI

Merow C., Smith M.J., Silander J.A. A practical guide to MaxEnt for modeling species’ distributions: What it does, and why inputs and settings matter. Ecography. 2013;36:1058–1069. doi: 10.1111/j.1600-0587.2013.07872.x. DOI

Elith J., H. Graham C.P., Anderson R., Dudík M., Ferrier S., Guisan A., J. Hijmans R., Huettmann F., R. Leathwick J., Lehmann A., et al. Novel methods improve prediction of species’ distributions from occurrence data. Ecography. 2006;29:129–151. doi: 10.1111/j.2006.0906-7590.04596.x. DOI

Wisz M.S., Hijmans R.J., Li J., Peterson A.T., Graham C.H., Guisan A., Elith J., Dudík M., Ferrier S., Huettmann F., et al. Effects of sample size on the performance of species distribution models. Divers. Distrib. 2008;14:763–773. doi: 10.1111/j.1472-4642.2008.00482.x. DOI

Aguirre-Gutiérrez J., Carvalheiro L.G., Polce C., van Loon E.E., Raes N., Reemer M., Biesmeijer J.C. Fit-for-Purpose: Species Distribution Model Performance Depends on Evaluation Criteria—Dutch Hoverflies as a Case Study. PLoS ONE. 2013;8:1–11. doi: 10.1371/journal.pone.0063708. PubMed DOI PMC

Mikkola H. Owls of Europe. T & AD Poyser Ltd. (A & C Black); London, UK: 1983.

Korpimäki E., Hakkarainen H. The Boreal Owl: Ecology, Behaviour and Conservation of a Forest-Dwelling Predator. Cambridge University Press; Cambridge, UK: 2012.

Vrezec A., Davorin T., Vrezec A., Tome D. Habitat selection and patterns of distribution in a hierarchic forest owl guild. Ornis Fenn. 2004;81:109–118.

Rajković D., Grujić D., Novčić R., Mirić R. Population of Tengmalm’s Owl Aegolius funereus in Kopaonik National Park (Central Serbia) Acrocephalus. 2013;34:27–32. doi: 10.2478/acro-2013-0003. DOI

Shurulinkov P., Stoyanov G., Komitov E., Daskalova G., Ralev A. Contribution to the Knowledge on Distribution, Number and Habitat Preferences of Rare and Endangered Birds in Western Rhodopes Mts, Southern Bulgaria. Strigiformes and Piciformes. [(accessed on 28 September 2022)];Acta Zool. Bulg. 2012 64:43–56. Available online: https://www.researchgate.net/publication/232712650.

BirdLife International Glaucidium passerinum. [(accessed on 6 September 2022)];IUCN Red List Threat. Species. 2016 82:1–8. Available online: https://www.iucnredlist.org/species/22689194/86868363.

BirdLife International Boreal Owl (Aegolius funereus) [(accessed on 6 September 2022)];IUCN Red List Threat. Species. 2021 8235:1–8. Available online: https://www.iucnredlist.org/species/22689362/166227347.

Rajković D., Puzović S., Raković M., Grubač B., Simović A., Đorđević V.M. Records of Boreal Owl Aegolius funereus in Serbia. Ciconia. 2010;19:131–140.

Shurulinkov P., Ralev A., Daskalova G., Chakarov N. Distribution, numbers and habitat of Pigmy Owl Glaucidium passerinum in Rhodopes Mts (S Bulgaria) Acrocephalus. 2007;135:161–165.

Obratov-Petković D., Beloica J., Čavlović D., Djurdjević V., Simić S.B., Bjedov I. Modelling Response of Norway Spruce Forest Vegetation to Projected Climate and Environmental Changes in Central Balkans Using Different Sets of Species. Forests. 2022;13:566. doi: 10.3390/f13050666. DOI

Cvijić J. Balkansko Poluostrvo i Južnoslovenske Zemlje. SANU: Književne novine: Zavod za udžbenike i nastavna sredstva; Belgrade, Serbia: 1987. pp. 12–25.

Reed J.M., Kryštufek B., Eastwood W.J. Balkan Biodiversity. Kluwer Academic Publishers; Dordrecht, The Netherlands: 2004. The Physical Geography of The Balkans and Nomenclature of Place Names; pp. 9–22. DOI

Furlan D. Climates of Central and Southern Europe. World Survey of Climatology. Volume 6. Elsevier; Amsterdam, The Netherlands: 1977. The Climate of Southeast Europe; pp. 185–235.

Griffiths H.I., Kryštufek B., Reed J.M. Balkan Biodiversity. Springer Science + Business Media; Berlin/Heidelberg, Germany: 2004.

Global Biodiversity Information Facility—GBIF. [(accessed on 7 September 2022)]. Available online: https://www.gbif.org/

ESRI ArcGIS desktop: Release 10. 2011. [(accessed on 6 September 2022)]. Available online: https://www.esri.com/en-us/home.

Pačenovský S., Shurulinkov P. Latest data on distribution of the Pygmy Owl (Glaucidium passerinum) in Bulgaria and Slovakia including population density comparison. Slovak Raptor J. 2008;2:91–106. doi: 10.2478/v10262-012-0023-5. DOI

Sorbi S. Size and use of Tengmalm’s Owl Aegolius funereus home range in the high Belgian Ardennes: Results from radio-tracking. Alauda. 2003;71:215–220.

Santangeli A., Hakkarainen H., Laaksonen T., Korpimäki E. Home range size is determined by habitat composition but feeding rate by food availability in male Tengmalm’s owls. Anim. Behav. 2012;83:1115–1123. doi: 10.1016/j.anbehav.2012.02.002. DOI

Moran P.A.P. The Interpretation of Statistical Maps. J. R. Stat. Soc. Ser. B. 1948;2:243–251. doi: 10.1111/j.2517-6161.1948.tb00012.x. DOI

Kissling W.D., Carl G. Spatial autocorrelation and the selection of simultaneous autoregressive models. Glob. Ecol. Biogeogr. 2008;17:59–71. doi: 10.1111/j.1466-8238.2007.00334.x. DOI

Valcu M., Kempenaers B. Spatial autocorrelation: An overlooked concept in behavioral ecology. Behav. Ecol. 2010;21:902–905. doi: 10.1093/beheco/arq107. PubMed DOI PMC

Beaumont L., Hughes L., Poulsen M. Predicting species distributions: Use of climatic parameters in BIOCLIM and its impact on predictions of species’ current and future distributions. Ecol. Modell. 2005;2:251–270. doi: 10.1016/j.ecolmodel.2005.01.030. DOI

Zhao Y., Cao H., Xu W., Chen G., Lian J., Du Y., Ma K. Contributions of precipitation and temperature to the large scale geographic distribution of fleshy-fruited plant species: Growth form matters. Sci. Rep. 2018;8:1–9. doi: 10.1038/s41598-018-35436-x. PubMed DOI PMC

WorldClim [(accessed on 1 October 2021)]. Published 2022. Available online: https://www.worldclim.org/

Wei B., Wang R., Hou K., Wang X., Wu W. Predicting the current and future cultivation regions of Carthamus tinctorius L. using MaxEnt model under climate change in China. Glob. Ecol. Conserv. 2018;16:e00477. doi: 10.1016/j.gecco.2018.e00477. DOI

Nikolov B.P., Zlatanov T., Groen T., Stoyanov S., Hristova-Nikolova I., Lexer M.J. Habitat requirements of Boreal Owl (Aegolius funereus) and Pygmy Owl (Glaucidium passerinum) in rear edge montane populations on the Balkan Peninsula. Avian Res. 2022;13:100020. doi: 10.1016/j.avrs.2022.100020. DOI

Elith J., Kearney M., Phillips S. The art of modelling range-shifting species. Methods Ecol. Evol. 2010;1:330–342. doi: 10.1111/j.2041-210X.2010.00036.x. DOI

Syfert M.M., Smith M.J., Coomes D.A. The Effects of Sampling Bias and Model Complexity on the Predictive Performance of MaxEnt Species Distribution Models. PLoS ONE. 2013;8:e55158. doi: 10.1371/annotation/35be5dff-7709-4029-8cfa-f1357e5001f5. PubMed DOI PMC

Radosavljevic A., Anderson R.P. Making better Maxent models of species distributions: Complexity, overfitting and evaluation. J. Biogeogr. 2013;41:629–643. doi: 10.1111/jbi.12227. DOI

Morales N.S., Fernández I.C., Baca-González V. MaxEnt’s parameter configuration and small samples: Are we paying attention to recommendations? A systematic review. PeerJ. 2017;2017:e3093. doi: 10.7717/peerj.3093. PubMed DOI PMC

Akaike H. A new look at the statistical model identification. IEEE Trans Automat Contr. 1974;19:716–723. doi: 10.1109/TAC.1974.1100705. DOI

Burnham K.P., Anderson D.R. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach. 2nd ed. Springer-Verlag; Berlin/Heidelberg, Germany: 2002.

Kline R.B. Principles and Practice of Structural Equation Modeling. The Guilford Press; New York, NY, USA: 1998.

Grimmett L., Whitsed R., Horta A. Presence-only species distribution models are sensitive to sample prevalence: Evaluating models using spatial prediction stability and accuracy metrics. Ecol. Modell. 2020;431:109194. doi: 10.1016/j.ecolmodel.2020.109194. DOI

Quinn G., Keough M. Experimental Design and Data Analysis for Biologists. Cambridge University Press; Cambridge, UK: 2002. DOI

Liu C., White M., Newell G. Selecting thresholds for the prediction of species occurrence with presence-only data. J. Biogeogr. 2013;40:778–789.8. doi: 10.1111/jbi.12058. DOI

rStudio Team rStudio: Integrated Development Environment for R. rStudio. 2021. [(accessed on 3 September 2022)]. Available online: https://posit.co/download/rstudio-desktop/

Zhu B., Wang B., Zou B., Xu Y., Yang B., Yang N., Ran J. Assessment of habitat suitability of a high-mountain Galliform species, buff-throated partridge (Tetraophasis szechenyii) Glob. Ecol. Conserv. 2020;24:e01230. doi: 10.1016/j.gecco.2020.e01230. DOI

Zhang J., Jiang F., Li G., Qin W., Li S., Gao H., Cai Z., Lin G., Zhang T. Maxent modeling for predicting the spatial distribution of three raptors in the Sanjiangyuan National Park, China. Ecol. Evol. 2019;9:6643–6654. doi: 10.1002/ece3.5243. PubMed DOI PMC

Obunga G., Siljander M., Maghenda M., Pellikka P.K.E. Habitat suitability modelling to improve conservation status of two critically endangered endemic Afromontane forest bird species in Taita Hills, Kenya. J. Nat. Conserv. 2022;65:126111. doi: 10.1016/j.jnc.2021.126111. DOI

Meza Mori G., Rojas-Briceño N.B., Cotrina Sánchez A., Oliva-Cruz M., Olivera Tarifeño C.M., Hoyos Cerna M.Y., Ramos Sandoval J.D., Torres Guzmán C. Potential Current and Future Distribution of the Long-Whiskered Owlet (Xenoglaux loweryi) in Amazonas and San Martin, NW Peru. Animals. 2022;12:1794. doi: 10.3390/ani12141794. PubMed DOI PMC

Ševčík R., Riegert J., Šťastný K., Zárybnický J., Zárybnická M. The effect of environmental variables on owl distribution in Central Europe: A case study from the Czech Republic. Ecol. Inform. 2021;64:101375. doi: 10.1016/j.ecoinf.2021.101375. DOI

Flousek J., Telenský T., Hanzelka J., Reif J. Population trends of central European montane birds provide evidence for adverse impacts of climate change on high-altitude species. PLoS ONE. 2015;10:1–14. doi: 10.1371/journal.pone.0139465. PubMed DOI PMC

Alba R., Kasoar T., Chamberlain D., Buchanan G., Thompson D., Pearce-Higgins J.W. Drivers of change in mountain and upland bird populations in Europe. Ibis. 2022;164:635–648. doi: 10.1111/ibi.13043. DOI

Reif J., Flousek J. The role of species’ ecological traits in climatically driven altitudinal range shifts of central European birds. Oikos. 2012;121:1053–1060. doi: 10.1111/j.1600-0706.2011.20008.x. DOI

Tellería J.L. Long-term altitudinal change in bird richness in a Mediterranean mountain range: Habitat shifts explain the trends. Reg. Environ. Chang. 2020;20:9. doi: 10.1007/s10113-020-01657-y. DOI

Chamberlain D., Arlettaz R., Caprio E., Maggini R., Pedrini P., Rolando A., Zbinden N. The altitudinal frontier in avian climate impact research. Ibis. 2012;154:205–209. doi: 10.1111/j.1474-919X.2011.01196.x. DOI

Brambilla M., Caprio E., Assandri G., Scridel D., Bassi E., Bionda R., Celada C., Falco R., Bogliani G., Pedrini P., et al. A spatially explicit definition of conservation priorities according to population resistance and resilience, species importance and level of threat in a changing climate. Divers. Distrib. 2017;23:727–738. doi: 10.1111/ddi.12572. DOI

Puzović S., Radišić D., Ružić M., Rajković D., Radaković M., Pantović U., Janković M., Stojnić N., Šćiban M., Tucakov M., et al. Birds of Serbia: Breeding Population Estimates and Trend for the period 2008–2013. Department of Biology and Ecology, Faculty of Sciences, University of Novi Sad; Novi Sad, Serbia: 2015.

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