Abstract
Habitat modifications driven by human impact and climate change may influence species distribution, particularly in aquatic environments. Niche-based models are commonly used to evaluate the availability and suitability of habitat and assess the consequences of future climate scenarios on a species range and shifting edges of its distribution. Together with knowledge on biology and ecology, niche models also allow evaluating the potential of species to react to expected changes. The availability of projections of future climate scenarios allows comparing current and future niche distributions, assessing a species’ habitat suitability modification and shift, and consequently estimating potential species’ reaction. In this study, differences between the distribution maps of 406 marine species, which were produced by the AquaMaps niche models on current and future (year 2050) scenarios, were estimated and evaluated. Discrepancy measurements were used to identify a discrete number of categories, which represent different responses to climate change. Clustering analysis was then used to automatically detect these categories, demonstrating their reliability compared to human supervised classification. Finally, the distribution of characteristics like extinction risk (based on IUCN categories), taxonomic groups, population trends and habitat suitability change over the clustering categories was evaluated. In this assessment, direct human impact was neglected, in order to focus only on the consequences of environmental changes. Furthermore, in the comparison between two climate snapshots, the intermediate phases were assumed to be implicitly included into the model of the 2050 climate scenario.
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References
Anthony K, Maynard JA, Diaz-Pulido G, Mumby PJ, Marshall PA, Cao L, Hoegh-Guldberg O (2011) Ocean acidification and warming will lower coral reef resilience. Glob Change Biol 17(5):1798–1808
Araujo MB, Guisan A (2006) Five (or so) challenges for species distribution modelling. J Biogeogr 33(10):1677–1688
Araújo MB, Pearson RG, Thuiller W, Erhard M (2005) Validation of species-climate impact models under climate change. Glob Change Biol 11(9):1504–1513
Arrigo KR, van Dijken GL, Bushinsky S (2008) Primary production in the Southern Ocean, 1997–2006. J Geophys Res Oceans (1978–2012) 113(C8):15587–15600
Assunçaoa MD, Calheirosb RN, Bianchia S, Nettoa MA, Buyyab R (2013) Big Data computing and clouds: challenges, solutions, and future directions. arXiv:1312.4722
Barratt P, Cavanagh RD (2015) Heterodontus zebra in the IUCN red list of threatened species. Version 2014.3, www.iucnredlist.org
Bellwood D, Hughes T, Folke C, Nyström M (2004) Confronting the coral reef crisis. Nature 429(6994):827–833
Bentley JL (1975) Multidimensional binary search trees used for associative searching. Commun ACM 18(9):509–517
Berry P, Dawson T, Harrison P, Pearson R (2002) Modelling potential impacts of climate change on the bioclimatic envelope of species in Britain and Ireland. Glob Ecol Biogeogr 11(6):453–462
BEST Commission (2003) The national invasive species strategy for the Bahamas. BEST, Nassau, The Bahamas 40
Botkin DB, Saxe H, Araujo MB, Betts R, Bradshaw RH, Cedhagen T, Chesson P, Dawson TP, Etterson JR, Faith DP, Ferrier S, Guisan A, Skjoldborg Hansen A, Hilbert DW, Loehle C, Margules C, New M, Sobel MJ, Stockwell DRB (2007) Forecasting the effects of global warming on biodiversity. Bioscience 57(3):227–236
Brierley AS, Kingsford MJ (2009) Impacts of climate change on marine organisms and ecosystems. Curr Biol 19(14):R602–R614
Campbell P (2008) Editorial on special issue on big data: community cleverness required. Nature 455(7209):1
Candela L, Castelli D, Coro G, Lelii L, Mangiacrapa F, Marioli V, Pagano P (2014) An infrastructure-oriented approach for supporting biodiversity research. Ecol Inform 26:162–172. doi:10.1016/j.ecoinf.2014.07.006
Cao D, Song L, Zhang Y, Lv K, Hu Z (2011) Environmental preferences of Alopias superciliosus and Alopias vulpinus in waters near Marshall Islands. N Z J Mar Freshw Res 45(1):103–119
Carlens H, Lydersen C, Krafft BA, Kovacs KM (2006) Spring haul-out behavior of ringed seals (Pusa hispida) in Kongsfjorden. Svalbard. Mar Mamm Sci 22(2):379–393
Castelli D, Michel J (2011) D4SCIENCE-II—data infrastructures ecosystem for science. Project final report. Data Infrastructures Ecosystem for Science. Deliverable DNA1.7
Castelli D, Taconet M, Garavelli S, Parker S (2013) iMarine infrastructure for data driven decision making and research: position paper. Presentation at the iMarine e-infrastructure Workshop for data-driven decision making and research, 14–15 May, Brussels, Belgium
Cheung WW, Lam VW, Sarmiento JL, Kearney K, Watson R, Pauly D (2009) Projecting global marine biodiversity impacts under climate change scenarios. Fish Fish 10(3):235–251
Cheung WW, Lam VW, Sarmiento JL, Kearney K, Watson R, Zeller D, Pauly D (2010) Large-scale redistribution of maximum fisheries catch potential in the global ocean under climate change. Glob Change Biol 16(1):24–35
Cheung WWL, Dunne J, Sarmiento JL, Pauly D (2011) Integrating ecophysiology and plankton dynamics into projected maximum fisheries catch potential under climate change in the Northeast Atlantic. ICES J Mar Sci 68(6):1008–1018
Chin A, Kyne PM, Walker TI, McAULEY R (2010) An integrated risk assessment for climate change: analysing the vulnerability of sharks and rays on Australia’s Great Barrier Reef. Glob Change Biol 16(7):1936–1953
Chuine I, Beaubien EG (2001) Phenology is a major determinant of tree species range. Ecol Lett 4(5):500–510
CNR T (2015) The gCube GeoExplorer. https://gcube.wiki.gcube-system.org/gcube/index.php/GeoExplorer
Cohen J et al (1960) A coefficient of agreement for nominal scales. Educ Psychol Meas 20(1):37–46
Coro G, Gioia A, Pagano P, Candela L (2013) A service for statistical analysis of marine data in a distributed e-infrastructure. Boll di Geofis Teorica e Appl 54(1):68–70
Coro G, Pagano P, Ellenbroek A (2014) Comparing heterogeneous distribution maps for marine species. GISci Remote Sens 51(5):593–611
Coro G, Candela L, Pagano P, Italiano A, Liccardo L (2015) Parallelizing the execution of native data mining algorithms for computational biology. Concurr Comput Pract Exp 27(17):4630–4644. doi:10.1002/cpe.3435
Corsi F, de Leeuw J, Skidmore A (2000) Modeling species distribution with GIS. Research Techniques in Animal Ecology, Columbia University Press, New York, pp 389–434
Costa GC, Nogueira C, Machado RB, Colli GR (2010) Sampling bias and the use of ecological niche modeling in conservation planning: a field evaluation in a biodiversity hotspot. Biodivers Conserv 19(3):883–899
Dawson TP, Jackson ST, House JI, Prentice IC, Mace GM (2011) Beyond predictions: biodiversity conservation in a changing climate. Science 332(6025):53–58
de La Beaujardière J (2004) OGC Web Map Service Interface, version 1.3.0. Open Geospatial Consortium
Dulvy NK, Rogers SI, Jennings S, Stelzenmüller V, Dye SR, Skjoldal HR (2008) Climate change and deepening of the North Sea fish assemblage: a biotic indicator of warming seas. J Appl Ecol 45(4):1029–1039
Erez J, Reynaud S, Silverman J, Schneider K, Allemand D (2011) Coral calcification under ocean acidification and global change. In: Dubinsky Z, Stambler N (eds) Coral reefs: an ecosystem in transition. Springer, Netherlands, pp 151–176
Ester M, Kriegel HP, Sander J, Xu X (1996) A density-based algorithm for discovering clusters in large spatial databases with noise. In: Kdd, vol 96, pp 226–231
FAO (2015) Fact sheets. http://www.fao.org/newsroom/en/facts/index.html
Fleiss JL (1971) Measuring nominal scale agreement among many raters. Psychol Bull 76(5):378
GCube (2015) The GCube Featherweight Stack. http://gcube.wiki.gcube-system.org/gcube/index.php/Featherweight_Stack
Genner MJ, Sims DW, Wearmouth VJ, Southall EJ, Southward AJ, Henderson PA, Hawkins SJ (2004) Regional climatic warming drives long-term community changes of British marine fish. Proc R Soc Lond Ser B Biol Sci 271(1539):655–661
Hare JA, Alexander MA, Fogarty MJ, Williams EH, Scott JD (2010) Forecasting the dynamics of a coastal fishery species using a coupled climate-population model. Ecol Appl 20(2):452–464
Heino M, Engelhard GH, Godo OR (2008) Migrations and hydrography determine the abundance fluctuations of blue whiting (Micromesistius poutassou) in the Barents Sea. Fish Oceanogr 17(2):153–163
Hey AJ, Tansley S, Tolle KM et al (2009) The fourth paradigm: data-intensive scientific discovery, vol 1. Microsoft Research Redmond, WA
Hiddink J, Ter Hofstede R (2008) Climate induced increases in species richness of marine fishes. Glob Change Biol 14(3):453–460
Hsieh CH, Kim HJ, Watson W, Di Lorenzo E, Sugihara G (2009) Climate-driven changes in abundance and distribution of larvae of oceanic fishes in the southern California region. Glob Change Biol 15(9):2137–2152
Hughes TP, Bellwood DR, Folke C, Steneck RS, Wilson J (2005) New paradigms for supporting the resilience of marine ecosystems. Trends Ecol Evolut 20(7):380–386
Hyrenbach KD, Veit RR (2003) Ocean warming and seabird communities of the southern California Current System (1987–98): response at multiple temporal scales. Deep Sea Res Part II Top Stud Oceanogr 50(14):2537–2565
IUCN (2015) The IUCN Red List of species. www.iucnredlist.org
Jordà G, Marbà N, Duarte CM (2012) Mediterranean seagrass vulnerable to regional climate warming. Nat Clim Change 2(11):821–824
Kaschner K, Watson R, Trites A, Pauly D (2006) Mapping world-wide distributions of marine mammal species using a relative environmental suitability (RES) model. Mar Ecol Prog Ser 316:285–310
Knights B (2003) A review of the possible impacts of long-term oceanic and climate changes and fishing mortality on recruitment of anguillid eels of the Northern Hemisphere. Sci Total Environ 310(1):237–244
Koch M, Bowes G, Ross C, Zhang XH (2013) Climate change and ocean acidification effects on seagrasses and marine macroalgae. Glob Change Biol 19(1):103–132
Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 1:159–174
Lassalle G, Rochard E (2009) Impact of twenty-first century climate change on diadromous fish spread over europe, north africa and the middle east. Glob Change Biol 15(5):1072–1089
Lawler IR, Parra G, Noad M (2007) Vulnerability of marine mammals in the Great Barrier Reef to climate change. http://hdl.handle.net/11017/548
Levin SA, Lubchenco J (2008) Resilience, robustness, and marine ecosystem-based management. Bioscience 58(1):27–32
MacLeod CD (2009) Global climate change, range changes and potential implications for the conservation of marine cetaceans: a review and synthesis. Endanger Species Res 7(2):125–136
MacQueen J (1967) Some methods for classification and analysis of multivariate observations. In: Proceedings of the fifth Berkeley symposium on mathematical statistics and probability, vol 14. California, USA, pp 281–297
Marzec RJ, Kim Y, Powell EN (2010) Geographical trends in weight and condition index of surfclams (Spisula solidissima) in the Mid-Atlantic Bight. J Shellfish Res 29(1):117–128
Mueter FJ, Litzow MA (2008) Sea ice retreat alters the biogeography of the Bering Sea continental shelf. Ecol Appl 18(2):309–320
Nakicenovic N, Swart R (2000) Special report on emissions scenarios. Special report on emissions scenarios, In: Nakicenovic N, Swart R (ed) pp 612 ISBN 0521804930, Cambridge University Press, Cambridge, UK, 1 July 2000
Nye JA, Link JS, Hare JA, Overholtz WJ (2009) Changing spatial distribution of fish stocks in relation to climate and population size on the Northeast United States continental shelf. Mar Ecol Prog Ser 393:111–129
Parmesan C (2006) Ecological and evolutionary responses to recent climate change. Annu Rev Ecol Evolut Syst 1:637–669
Pearson RG (2012) Species distribution modeling for conservation educators and practitioners. Synthesis. American Museum of Natural History. http://ncep.amnh.org
Pearson RG, Dawson TP (2003) Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Glob Ecol Biogeogr 12(5):361–371
Pelleg D, Moore AW (2000) X-means: extending K-means with efficient estimation of the number of clusters. In: ICML, pp 727–734
Pellissier L, Bråthen KA, Vittoz P, Yoccoz NG, Dubuis A, Meier ES, Zimmermann NE, Randin CF, Thuiller W, Garraud L, Van Es J, Guisan A (2013) Thermal niches are more conserved at cold than warm limits in arctic-alpine plant species. Glob Ecol Biogeogr 22(8):933–941
Perry AL, Low PJ, Ellis JR, Reynolds JD (2005) Climate change and distribution shifts in marine fishes. Science 308(5730):1912–1915
Ready J, Kaschner K, South AB, Eastwood PD, Rees T, Rius J, Agbayani E, Kullander S, Froese R (2010) Predicting the distributions of marine organisms at the global scale. Ecol Model 221(3):467–478. doi:10.1016/j.ecolmodel.2009.10.025
Reyes K (2015) AquaMaps: algorithm and data sources for aquatic organisms. http://www.aquamaps.org/main/FB_Book_KReyes_AquaMaps_JG.pdf
Roeckner E, Arpe K, Bengtsson L, Brinkop S, Dümenil L, Esch M, Kirk E, Lunkeit F, Ponater M, Rockel B et al (1992) Simulation of the present-day climate with the ECHAM model: impact of model physics and resolution. Max-Planck-Institut für Meteorologie, Hamburg
Sardella BA, Sanmarti E, Kültz D (2008) The acute temperature tolerance of green sturgeon (Acipenser medirostris) and the effect of environmental salinity. J Exp Zool Part A Ecol Genet Physiol 309(8):477–483
Schwartz MW (2012) Using niche models with climate projections to inform conservation management decisions. Biol Conserv 155:149–156
Schwarz G (1978) Estimating the dimension of a model. Ann Stat 6(2):461–464
Somero GN (2012) The physiology of global change: linking patterns to mechanisms. Ann Rev Mar Sci 4:39–61
Sorvari S, Brus M (2012) ENVRI—overcoming the environmental challenges with common solutions. EPOS newsletter, February
Sunday JM, Bates AE, Dulvy NK (2012) Thermal tolerance and the global redistribution of animals. Nat Clim Change 2(9):686–690
Sydeman W, García-Reyes M, Schoeman D, Rykaczewski R, Thompson S, Black B, Bograd S (2014) Climate change and wind intensification in coastal upwelling ecosystems. Science 345(6192):77–80
Thompson KF, Millar CD, Baker CS, Dalebout M, Steel D, van Helden AL, Constantine R (2013) A novel conservation approach provides insights into the management of rare cetaceans. Biol Conserv 157:331–340
Thuiller W (2004) Patterns and uncertainties of species’ range shifts under climate change. Glob Change Biol 10(12):2020–2027
Thuiller W, Lavorel S, Araújo MB, Sykes MT, Prentice IC (2005) Climate change threats to plant diversity in Europe. Proc Natl Acad Sci USA 102(23):8245–8250
Tzeng WN, Tseng YH, Han YS, Hsu CC, Chang CW, Di Lorenzo E, Hsieh Ch (2012) Evaluation of multi-scale climate effects on annual recruitment levels of the Japanese eel, Anguilla japonica, to Taiwan. PLoS One 7(2):e30,805
Waldrop MM (2008) Science 2.0. Sci Am 298(5):68–73
Wassmann P, Duarte CM, Agusti S, Sejr MK (2011) Footprints of climate change in the Arctic marine ecosystem. Glob Change Biol 17(2):1235–1249
Wootton JT, Pfister CA, Forester JD (2008) Dynamic patterns and ecological impacts of declining ocean pH in a high-resolution multi-year dataset. Proc Natl Acad Sci 105(48):18,848–18,853
Acknowledgments
The reported work has been partially supported by the i-Marine project (FP7 of the European Commission, INFRASTRUCTURES-2011-2, Contract No. 283644) and by the Giovanisi project of the Presidency of the Tuscan Regional Government.
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Coro, G., Magliozzi, C., Ellenbroek, A. et al. Automatic classification of climate change effects on marine species distributions in 2050 using the AquaMaps model. Environ Ecol Stat 23, 155–180 (2016). https://doi.org/10.1007/s10651-015-0333-8
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DOI: https://doi.org/10.1007/s10651-015-0333-8