Abstract
Early detection and management of aquatic invasive species requires identification of those areas most at risk of invasion (i.e., hotspots). Here we identify present-day and future hotspots of invasion risk for marine invertebrates and algae in nearshore habitats of the northwest Atlantic and northeast Pacific using more than 12 years of monitoring data in conjunction with other occurrence data and stacked species distribution models. The stacked species distribution models predicted the general patterns of observed invasive species richness in both study areas (Atlantic: r2 = 0.52, Pacific: r2 = 0.42). In the northwest Atlantic, we identified hotspots through much of Massachusetts, New Hampshire and southern Maine, and in several bays in southwestern New Brunswick and Nova Scotia. In the northeast Pacific, much of the southern Salish Sea was identified as a hotspot, as were a few areas along the outer coast of Washington and Oregon. Projecting our species distribution modelling results to 2075 (climate scenario RCP 8.5), we found that existing hotspots are likely to expand slightly in the Atlantic, while in the Pacific existing hotspots are predicted to shift or expand, new hotspots are likely to appear, and areas with few invasive species attaining moderate invasive species richness. Our results suggest that climate change will have larger effects on the distributions of our focal invasive species on the Pacific coast compared to the Atlantic. Resultant hotspot maps provide an integrated perspective and guidance to managers tasked with prioritizing locations for monitoring and implementing policy related to marine invasive species, with projected hotspots making planning for future changes in invasion risk possible.
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References
Aarts G, Fieberg J, Matthiopoulos J (2012) Comparative interpretation of count, presence-absence and point methods for species distribution models. Methods Ecol Evol 3:177–187. https://doi.org/10.1111/j.2041-210X.2011.00141.x
Arenas F, Bishop JDD, Carlton JT et al (2006) Alien species and other notable records from a rapid assessment survey of marinas on the south coast of England. J Mar Biol Assoc UK 86:1329–1337. https://doi.org/10.1017/S0025315406014354
Assis J, Tyberghein L, Bosch S et al (2018) Bio-ORACLE v2.0: extending marine data layers for bioclimatic modelling. Glob Ecol Biogeogr 27:227–284. https://doi.org/10.1111/geb.12693
Ball IR, Possingham HP, Watts ME (2009) Marxan and relatives: software for spatial conservation prioritization. In: Moilanen A, Wilson KA, Possingham HP (eds) Spatial conservation prioritisation: quantitative methods and computational tools. Oxford University Press, Oxford, pp 185–195
Barry S, Elith J (2006) Error and uncertainty in habitat models. J Appl Ecol 43:413–423. https://doi.org/10.1111/j.1365-2664.2006.01136.x
Baxter PWJ, Possingham HP (2011) Optimizing search strategies for invasive pests: learn before you leap. J Appl Ecol 48:86–95. https://doi.org/10.1111/j.1365-2664.2010.01893.x
Bayliss H, Stewart G, Wilcox A, Randall N (2013) A perceived gap between invasive species research and stakeholder priorities. NeoBiota 19:67–82. https://doi.org/10.3897/neobiota.19.4897
Beal BF, Kraus MG (2002) Interactive effects of initial size, stocking density, and type of predator deterrent netting on survival and growth of cultured juveniles of the soft-shell clam, Mya arenaria L., in eastern Maine. Aquaculture 208:81–111. https://doi.org/10.1016/S0044-8486(01)00900-0
Bellard C, Leclerc C, Leroy B et al (2014) Vulnerability of biodiversity hotspots to global change. Glob Ecol Biogeogr 23:1376–1386. https://doi.org/10.1111/geb.12228
Bellard C, Jeschke JM, Leroy B, Mace GM (2018) Insights from modeling studies on how climate change affects invasive alien species geography. Ecol Evol 8:5688–5700. https://doi.org/10.1002/ece3.4098
Brickman D, Wang Z, DeTracey B (2016) High resolution future climate ocean model simulations for the northwest Atlantic shelf region. Can Tech Rep Hydrogr Ocean Sci 315:1–143
Brown JL, Bennett JR, French C (2017) SDMtoolbox 2.0: the next generation Python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses. PeerJ. https://doi.org/10.7717/peerj.4095
Burrows MT, Harvey R, Robb L (2008) Wave exposure indices from digital coastlines and the prediction of rocky shore community structure. Mar Ecol Prog Ser 353:1–12. https://doi.org/10.3354/meps07284
Calabrese JM, Certain G, Kraan C, Dormann CF (2014) Stacking species distribution models and adjusting bias by linking them to macroecological models. Glob Ecol Biogeogr 23:99–112. https://doi.org/10.1111/geb.12102
Carman MR, Morris JA, Karney RC, Grunden DW (2010) An initial assessment of native and invasive tunicates in shellfish aquaculture of the North American east coast. J Appl Ichthyol 26:8–11. https://doi.org/10.1111/j.1439-0426.2010.01495.x
Carver CE, Chisholm A, Mallet AL (2003) Strategies to mitigate the impact of Ciona intestinalis (L.) biofouling on shellfish production. J Shellfish Res 22:621–631
Castro MCT, Hall-Spencer JM, Poggian CF, Fileman TW (2018) Ten years of Brazilian ballast water management. J Sea Res 133:36–42. https://doi.org/10.1016/j.seares.2017.02.003
Cheng L, Abraham J, Hausfather Z, Trenberth KE (2019) How fast are the oceans warming? Science 363:128–129. https://doi.org/10.1126/science.aav7619
Cheung WWL (2019) Predicting the future ocean: pathways to global ocean sustainability. In: Cisneros-Montemayor AM, Cheung WWL, Ota Y (eds) Predicting future oceans: sustainability of ocean and human systems amidst global environmental change. Elsevier, Amsterdam, pp 3–15
Clarke Murray C, Pakhomov EA, Therriault TW (2011) Recreational boating: a large unregulated vector transporting marine invasive species. Divers Distrib 17:1161–1172. https://doi.org/10.1111/j.1472-4642.2011.00798.x
Cohen AN, Carlton JT (1998) Accelerating invasion rate in a highly invaded estuary. Science (80-) 279:555–558. https://doi.org/10.1126/science.279.5350.555
Davis AJ, Jenkinson LS, Lawton JH et al (1998) Making mistakes when predicting shifts in species range in response to global warming. Nature 391:783–786. https://doi.org/10.1038/35842
De Rivera CE, Steves BP, Fofonoff PW et al (2011) Potential for high-latitude marine invasions along western North America. Divers Distrib 17:1198–1209. https://doi.org/10.1111/j.1472-4642.2011.00790.x
Drake JM, Lodge DM (2004) Global hot spots of biological invasions: evaluating options for ballast-water management. Proc R Soc B Biol Sci 271:575–580. https://doi.org/10.1098/rspb.2003.2629
Drolet D, DiBacco C, Locke A et al (2016) Evaluation of a new screening-level risk assessment tool applied to non-indigenous marine invertebrates in Canadian coastal waters. Biol Invasions 18:279–294. https://doi.org/10.1007/s10530-015-1008-y
Elith J, Leathwick JR (2009) Species distribution models: ecological explanation and prediction across space and time. Annu Rev Ecol Evol Syst 40:677–697. https://doi.org/10.1146/annurev.ecolsys.110308.120159
Elith J, Phillips SJ, Hastie T et al (2011) A statistical explanation of MaxEnt for ecologists. Divers Distrib 17:43–57. https://doi.org/10.1111/j.1472-4642.2010.00725.x
Esler KJ, Prozesky H, Sharma GP, McGeoch M (2010) How wide is the “knowing-doing” gap in invasion biology? Biol Invasions 12:4065–4075. https://doi.org/10.1007/s10530-010-9812-x
Fofonoff PW, Ruiz GM, Steves B, Simkanin C, Carlton J (2018) National exotic marine and estuarine species information system. https://invasions.si.edu/nemesis/. Accessed 14 Mar 2018
Franklin J (2010) Mapping species distributions: spatial inference and prediction ecology, biodiversity and conservation ecology, biodiversity and conservation. Cambridge University Press, Cambridge
Fridley JD, Stachowicz JJ, Naeem S et al (2007) The invasion paradox: reconciling pattern and process in species invasions. Ecology 88:3–17. https://doi.org/10.1890/0012-9658(2007)88[3:TIPRPA]2.0.CO;2
Getis A, Ord JK (1992) The analysis of spatial association by use of distance statistics. Geogr Anal 24:189–206. https://doi.org/10.1111/j.1538-4632.1992.tb00261.x
Giakoumi S, Guilhaumon F, Kark S et al (2016) Space invaders; biological invasions in marine conservation planning. Divers Distrib 22:1220–1231. https://doi.org/10.1111/ddi.12491
Gormley AM, Forsyth DM, Griffioen P et al (2011) Using presence-only and presence-absence data to estimate the current and potential distributions of established invasive species. J Appl Ecol 48:25–34. https://doi.org/10.1111/j.1365-2664.2010.01911.x
Guisan A, Tingley R, Baumgartner JB et al (2013) Predicting species distributions for conservation decisions. Ecol Lett 16:1424–1435. https://doi.org/10.1111/ele.12189
Guo L, Sheng J (2017) Impacts of climate changes on ocean surface gravity waves over the eastern Canadian shelf. Ocean Dyn 67:621–637. https://doi.org/10.1007/s10236-017-1046-3
Hällfors MH, Liao J, Dzurisin J et al (2016) Addressing potential local adaptation in species distribution models: implications for conservation under climate change. Ecol Appl 26:1154–1169. https://doi.org/10.1890/15-0926
Honrado JP, Pereira HM, Guisan A (2016) Fostering integration between biodiversity monitoring and modelling. J Appl Ecol 53:1299–1304. https://doi.org/10.1111/1365-2664.12777
International Council for the Exploration of the Sea (2005) ICES code of practice on the introductions and transfers of marine organisms 2005
Jeschke JM, Strayer DL (2008) Usefulness of bioclimatic models for studying climate change and invasive species. Ann NY Acad Sci 1134:1–24
Johnson LE, Bossenbroek JM, Kraft CE (2006) Patterns and pathways in the post-establishment spread of non-indigenous aquatic species: the slowing invasion of North American inland lakes by the zebra mussel. Biol Invasions 8:475–489. https://doi.org/10.1007/s10530-005-6412-2
Kramer-Schadt S, Niedballa J, Pilgrim JD et al (2013) The importance of correcting for sampling bias in MaxEnt species distribution models. Divers Distrib 19:1366–1379. https://doi.org/10.1111/ddi.12096
Kulhanek SA, Leung B, Ricciardi A (2011) Using ecological niche models to predict the abundance and impact of invasive species: application to the common carp. Ecol Appl 21:203–213. https://doi.org/10.1890/09-1639.1
Li H, Wu J (2006) Uncertainty analysis in ecological studies: an overview. In: Wu J, Jones KB, Li H, Loucks OL (eds) Scaling and uncertainty analysis in ecology: methods and applications. Springer, Dordrecht, pp 45–66
Li X, Liu X, Kraus F et al (2016) Risk of biological invasions is concentrated in biodiversity hotspots. Front Ecol Environ 14:411–417. https://doi.org/10.1002/fee.1321
Locke A, Doe KG, Fairchild WL et al (2009) Preliminary evaluation of effects of invasive tunicate management with acetic acid and calcium hydroxide on non-target marine organisms in Prince Edward Island, Canada. Aquat Invasions 4:221–236. https://doi.org/10.3391/ai.2009.4.1.23
Lockwood JL, Cassey P, Blackburn T (2005) The role of propagule pressure in explaining species invasions. Trends Ecol Evol 20:223–228. https://doi.org/10.1016/j.tree.2005.02.004
Lowen JB, McKindsey CW, Therriault TW, DiBacco C (2016) Effects of spatial resolution on predicting the distribution of aquatic invasive species in nearshore marine environments. Mar Ecol Prog Ser 556:17–30. https://doi.org/10.3354/meps11765
Lowen JB, DiBacco C, Lowen JB et al (2017) Distributional changes in a guild of non-indigenous tunicates in the NW Atlantic under high-resolution climate projections. Mar Ecol Prog Ser 570:173–186. https://doi.org/10.3354/meps12077
Lowen JB, Hart DR, Stanley RRE et al (2019) Assessing effects of genetic, environmental, and biotic gradients in species distribution modelling. ICES J Mar Sci. https://doi.org/10.1093/icesjms/fsz049
Mačić V, Albano PG, Almpanidou V et al (2018) Biological invasions in conservation planning: a global systematic review. Front Mar Sci. https://doi.org/10.3389/fmars.2018.00178
Marchini A, Ferrario J, Sfriso A, Occhipinti-Ambrogi A (2015) Current status and trends of biological invasions in the Lagoon of Venice, a hotspot of marine NIS introductions in the Mediterranean Sea. Biol Invasions 17:2943–2962. https://doi.org/10.1007/s10530-015-0922-3
Matzek V, Covino J, Funk JL, Saunders M (2014) Closing the knowing-doing gap in invasive plant management: accessibility and interdisciplinarity of scientific research. Conserv Lett 7:208–215. https://doi.org/10.1111/conl.12042
Mesgaran MB, Cousens RD, Webber BL (2014) Here be dragons: a tool for quantifying novelty due to covariate range and correlation change when projecting species distribution models. Divers Distrib 20:1147–1159. https://doi.org/10.1111/ddi.12209
Muscarella R, Galante PJ, Soley-Guardia M et al (2014) ENMeval: an R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models. Methods Ecol Evol 5:1198–1205. https://doi.org/10.1111/2041-210x.12261
Naylor RL, Williams SL, Strong DR (2001) Aquaculture—a gateway for exotic species. Science 294:1655–1656. https://doi.org/10.1126/science.1064875
O’Donnell J, Gallagher RV, Wilson PD et al (2012) Invasion hotspots for non-native plants in Australia under current and future climates. Glob Chang Biol 18:617–629. https://doi.org/10.1111/j.1365-2486.2011.02537.x
OBIS (2018) Ocean biogeographic information system. Intergovernmental Oceanographic Commission of UNESCO. www.iobis.org. Accessed 17 Mar 2017
Pajuelo JG, González JA, Triay-Portella R et al (2016) Introduction of non-native marine fish species to the Canary Islands waters through oil platforms as vectors. J Mar Syst 163:23–30. https://doi.org/10.1016/j.jmarsys.2016.06.008
Pejchar L, Mooney HA (2009) Invasive species, ecosystem services and human well-being. Trends Ecol Evol 24:497–504
Peña A, Fine I, Masson D (2018) Towards climate change projections of biogeochemical conditions along the British Columbia coast. In: Jang CJ, Curchitser E (eds) Report of working group 29 on regional climate modeling. PICES scientific report No. 54, pp 114–124
Peña MA, Fine I, Callendar W (2019) Interannual variability in primary production and shelf-offshore transport of nutrients along the northeast Pacific Ocean margin. Deep Sea Res Part II Top Stud Oceanogr. https://doi.org/10.1016/j.dsr2.2019.104637
Phillips SJ, Dudík M, Elith J et al (2009) Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data. Ecol Appl 19:181–197. https://doi.org/10.1890/07-2153.1
Phillips SJ, Anderson RP, Dudík M et al (2017) Opening the black box: an open-source release of Maxent. Ecography (Cop) 40:887–893. https://doi.org/10.1111/ecog.03049
Pinsky ML, Worm B, Fogarty MJ et al (2013) Marine taxa track local climate velocities. Science (80-) 341:1239LP–1242LP. https://doi.org/10.1126/science.1239352
Pyšek P, Richardson DM (2010) Invasive species, environmental change and management, and health. Annu Rev Environ Resour 35:25–55. https://doi.org/10.1146/annurev-environ-033009-095548
R Development Core Team (2018) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna
Rascle N, Ardhuin F (2013) A global wave parameter database for geophysical applications. Part 2: model validation with improved source term parameterization. Ocean Model 70:174–188. https://doi.org/10.1016/j.ocemod.2012.12.001
Renner IW, Warton DI (2013) Equivalence of MAXENT and poisson point process models for species distribution modeling in ecology. Biometrics 69:274–281. https://doi.org/10.1111/j.1541-0420.2012.01824.x
Rondinini C, Wilson KA, Boitani L et al (2006) Tradeoffs of different types of species occurrence data for use in systematic conservation planning. Ecol Lett 9:1136–1145. https://doi.org/10.1111/j.1461-0248.2006.00970.x
Ruiz GM, Fofonoff PW, Steves B et al (2011) Marine invasion history and vector analysis of California: a hotspot for western North America. Divers Distrib 17:362–373. https://doi.org/10.1111/j.1472-4642.2011.00742.x
Sax DF (2001) Latitudinal gradients and geographic ranges of exotic species: implications for biogeography. J Biogeogr 28:139–150. https://doi.org/10.1046/j.1365-2699.2001.00536.x
Sbrocco EJ, Barber PH (2013) MARSPEC: ocean climate layers for marine spatial ecology. Ecology 94:979. https://doi.org/10.1890/12-1358.1
Scriven DR, DiBacco C, Locke A, Therriault TW (2015) Ballast water management in Canada: a historical perspective and implications for the future. Mar Policy 59:121–133. https://doi.org/10.1016/j.marpol.2015.05.014
Seebens H, Gastner MT, Blasius B (2013) The risk of marine bioinvasion caused by global shipping – Supplementary information. Ecol Lett 16:782–790. https://doi.org/10.1111/ele.12111
Seebens H, Schwartz N, Schupp PJ, Blasius B (2016) Predicting the spread of marine species introduced by global shipping. Proc Natl Acad Sci 113:5646–5651. https://doi.org/10.1073/pnas.1524427113
Soontiens N, Allen SE (2017) Modelling sensitivities to mixing and advection in a sill-basin estuarine system. Ocean Model 112:17–32. https://doi.org/10.1016/j.ocemod.2017.02.008
Soontiens N, Allen SE, Latornell D et al (2016) Storm surges in the Strait of Georgia simulated with a regional model. Atmos Ocean 54:1–21. https://doi.org/10.1080/07055900.2015.1108899
Stachowicz JJ, Terwin JR, Whitlatch RB, Osman RW (2002) Linking climate change and biological invasions: ocean warming facilitates nonindigenous species invasions. Proc Natl Acad Sci USA 99:15497–15500. https://doi.org/10.1073/pnas.242437499
Sylvester F, Kalaci O, Leung B et al (2011) Hull fouling as an invasion vector: can simple models explain a complex problem? J Appl Ecol 48:415–423. https://doi.org/10.1111/j.1365-2664.2011.01957.x
Tidbury HJ, Taylor NGH, Copp GH et al (2016) Predicting and mapping the risk of introduction of marine non-indigenous species into Great Britain and Ireland. Biol Invasions. https://doi.org/10.1007/s10530-016-1219-x
Tyberghein L, Verbruggen H, Pauly K et al (2012) Bio-ORACLE: a global environmental dataset for marine species distribution modelling. Glob Ecol Biogeogr 21:272–281. https://doi.org/10.1111/j.1466-8238.2011.00656.x
Venette RC, Kriticos DJ, Magarey RD et al (2010) Pest risk maps for invasive alien species: a roadmap for improvement. Bioscience 60:349–362. https://doi.org/10.1525/bio.2010.60.5.5
Vitousek PM, D’Antonio CM, Loope LL et al (1997) Introduced species: a significant component of human-caused global change. N Z J Ecol 21:1–16
Weigle SM, Smith LD, Carlton JT, Pederson J (2005) Assessing the risk of introducing exotic species via the live marine species trade. Conserv Biol 19:213–223. https://doi.org/10.1111/j.1523-1739.2005.00412.x
Worm B, Tittensor DP (2018) A theory of global diversity. Princeton University Press, Princeton
Acknowledgements
We thank the editor, two anonymous reviewers, P. L. Thompson and A. M. Gehman for comments on a previous version of this manuscript. We also thank M. Sizer for help with occurrence data, and M. E. Auger-Méthé and R. R. E. Stanley for coding tips. This research was research was supported by funding from Fisheries and Oceans Canada’s Strategic Program for Ecosystem-Based Research and Advice (SPERA).
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Lyons, D.A., Lowen, J.B., Therriault, T.W. et al. Identifying marine invasion hotspots using stacked species distribution models. Biol Invasions 22, 3403–3423 (2020). https://doi.org/10.1007/s10530-020-02332-3
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DOI: https://doi.org/10.1007/s10530-020-02332-3