Abstract
The number of invasive species threatening freshwater habitats are increasing globally, and can be accelerated by climate change. Thus, risk assessments of potential invasive species are required for establishing prevention measures, in which quantitative risk assessments provide results objectively. In this study, the invasion risk of largemouth bass (Micropterus salmoides) in four major river basins (the Han, Nakdong, Geum, and Yeongsan) in South Korea was evaluated using an ensemble of species distribution models (SDMs). A weighted ensemble of the SDMs was developed to predict the probability of largemouth bass occurrence in the present (2011–2015) and two future periods: 2050 (2046–2055) and 2080 (2076–2085). The invasion risk of largemouth bass was evaluated using two approaches: relative and absolute risk assessments. Both approaches predicted an increase in Tier 1 (the highest risk) areas under representative concentration pathway (RCP) 4.5; however, a decrease in the areas of concern under RCP 8.5. In particular, the upper streams of the Nakdong and Han river basins are expected to be at risk in the future. In addition, Tier 1 risk areas are predicted to shift northward under both RCP 4.5 and 8.5 scenarios, especially in the Nakdong River Basin. This study provides a quantitative risk assessment tool based on the SDMs for the management of largemouth bass invasion under climate change.
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The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
References
Ahmed DA, Hudgins E, Cuthbert R, Kourantidou M, Diagne C, Haubrock PJ, Leung B, Liu C, Leroy B, Petrovskii S, Beidas A, Courchamp F (2022) Managing biological invasions: the cost of inaction. Biol Invasions 24:1927–1946. https://doi.org/10.1007/s10530-022-02755-0
Allouche O, Tsoar A, Kadmon R (2006) Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). J Appl Ecol 43(6):1223–1232. https://doi.org/10.1111/j.1365-2664.2006.01214.x
Andersen MC, Adams H, Hope B, Powell M (2004) Risk assessment for invasive species. Risk Anal Int J 24(4):787–793. https://doi.org/10.1111/j.0272-4332.2004.00478.x
Bae MJ, Murphy CA, García-Berthou E (2018) Temperature and hydrologic alteration predict the spread of invasive Largemouth Bass (Micropterus salmoides). Sci Total Environ 639:58–66. https://doi.org/10.1016/j.scitotenv.2018.05.001
Baker R, Cannon RAY, Bartlett P, Barker IAN (2005) Novel strategies for assessing and managing the risks posed by invasive alien species to global crop production and biodiversity. Ann Appl Biol 146(2):177–191. https://doi.org/10.1111/j.1744-7348.2005.040071.x
Baker RHA, Black R, Copp GH, Haysom KA, Hulme PE, Thomas MB, Brown A, Brown M, Cannon RJC, Ellis J, Ellis M, Ferris R, Glaves P, Gozlan RE, Holt J, Howe L, Knight JD, MacLeod A, Moore NP, Mumford JD, Murphy ST, Parrott D, Sansford CE, Smith GC, St-Hilaire S, Ward NL (2008) The UK risk assessment scheme for all non-native species. In: Rabitsch W, Essl F, Klingenstein F (eds) Biological invasions—from ecology to conservation, vol 7. NEOBIOTA, Berlin, pp 46–57
Barbet-Massin M, Jiguet F, Albert CH, Thuiller W (2012) Selecting pseudo-absences for species distribution models: how, where and how many? Methods Ecol Evol 3(2):327–338. https://doi.org/10.1111/j.2041-210X.2011.00172.x
Bellard C, Thuiller W, Leroy B, Genovesi P, Bakkenes M, Courchamp F (2013) Will climate change promote future invasions? Glob Change Biol 19(12):3740–3748. https://doi.org/10.1111/gcb.12344
Bernery C, Bellard CA, Courchamp F, Brosse S, Gozlan R, Jarić I, Teletchea F, Leroy B (2022) Freshwater fish invasions: a comprehensive review. Annu Rev Ecol Evol Syst 53:427–456. https://doi.org/10.1146/annurev-ecolsys-032522-015551
Bonar SA, Bolding BD, Divens M, Meyer W (2005) Effects of introduced fishes on wild juvenile coho salmon in three shallow Pacific Northwest lakes. Trans Am Fish Soc 134(3):641–652. https://doi.org/10.1577/T04-154.1
Bosch J, Bielby J, Matin-Beyer B, Rincón P, Correa-Araneda F, Boyero L (2019) Eradication of introduced fish allows successful recovery of a stream-dwelling amphibian. PLoS One 14(4):e0216204. https://doi.org/10.1371/journal.pone.0216204
Brown TG, Runciman B, Pollard S, Grant ADA (2009) Biological synopsis of largemouth bass (Micropterus salmoides). Can Manuscr Rep Fish Aquat Sci 2884:1–26
Buisson L, Thuiller W, Casajus N, Lek S, Grenouillet G (2010) Uncertainty in ensemble forecasting of species distribution. Glob Change Biol 16(4):1145–1157. https://doi.org/10.1111/j.1365-2486.2009.02000.x
Chernick MR (2011) Bootstrap methods: a guide for practitioners and researchers. Wiley, New York
Choi JW, An K-G (2016) Hydrodynamic fish modeling for potential-expansion evaluations of exotic species (largemouth bass) on waterway tunnel of Andong-Imha Reserv. J Ecol Environ 40(1):1–11. https://doi.org/10.1186/s41610-016-0014-z
Clarke SA, Vilizzi L, Lee L, Wood LE, Cowie WJ, Burt JA, Stebbing PD (2020) Identifying potentially invasive non-native marine and brackish water species for the Arabian Gulf and Sea of Oman. Glob Change Biol 26(4):2081–2092. https://doi.org/10.1111/gcb.14964
Compton TJ, De Winton M, Leathwick JR, Wadhwa S (2012) Predicting spread of invasive macrophytes in New Zealand lakes using indirect measures of human accessibility. Freshw Biol 57(5):938–948. https://doi.org/10.1111/j.1365-2427.2012.02754.x
Copp GH, Garthwaite R, Gozlan RE (2005) Risk identification and assessment of non-native freshwater fishes: a summary of concepts and perspectives on protocols for the UK. J Appl Ichthyol 21(4):371. https://doi.org/10.1111/j.1439-0426.2005.00692.x
Copp GH, Vilizzi L, Tidbury H, Stebbing PD, Tarkan AS, Miossec L, Goulletquer P (2016) Development of a generic decision-support tool for identifying potentially invasive aquatic taxa: AS-ISK. Manag Biol Invasions 7:343–350. https://doi.org/10.3391/mbi.2016.7.4.04
Dudgeon D, Arthington AH, Gessner MO, Kawabata ZI, Knowler DJ, Lévêque C, Sullivan CA (2006) Freshwater biodiversity: importance, threats, status and conservation challenges. Biol Rev 81(2):163–182. https://doi.org/10.1017/S1464793105006950
Ficetola GF, Thuiller W, Miaud C (2007) Prediction and validation of the potential global distribution of a problematic alien invasive species—the American bullfrog. Divers Distrib 13(4):476–485. https://doi.org/10.1111/j.1472-4642.2007.00377.x
Gallardo B, Aldridge DC (2013) Priority setting for invasive species management: risk assessment of Ponto-Caspian invasive species into Great Britain. Ecol Appl 23(2):352–364. https://doi.org/10.1890/12-1018.1
Gallardo B, Aldridge DC (2020) Priority setting for invasive species management by the water industry. Water Res 178:115771. https://doi.org/10.1016/j.watres.2020.115771
Gallardo B, Errea MP, Aldridge DC (2012) Application of bioclimatic models coupled with network analysis for risk assessment of the killer shrimp, Dikerogammarus villosus in Great Britain. Biol Invasions 14(6):1265–1278. https://doi.org/10.1007/s10530-011-0154-0
González-Ferreras AM, Barquín J, Peñas FJ (2016) Integration of habitat models to predict fish distributions in several watersheds of Northern Spain. J Appl Ichthyol 32(1):204–216. https://doi.org/10.1111/jai.13024
Grenouillet G, Buisson L, Casajus N, Lek S (2011) Ensemble modelling of species distribution: the effects of geographical and environmental ranges. Ecography 34(1):9–17. https://doi.org/10.1111/j.1600-0587.2010.06152.x
Guisan A, Tingley R, Baumgartner JB, Naujokaitis-Lewis I, Sutcliffe PR, Tulloch AI, Buckley YM (2013) Predicting species distributions for conservation decisions. Ecol Lett 16(12):1424–1435. https://doi.org/10.1111/ele.12189
Guo C, Lek S, Ye S, Li W, Liu J, Li Z (2015) Uncertainty in ensemble modelling of large-scale species distribution: effects from species characteristics and model techniques. Ecol Model 306:67–75. https://doi.org/10.1016/j.ecolmodel.2014.08.002
Hao T, Elith J, Lahoz-Monfort JJ, Guillera-Arroita G (2020) Testing whether ensemble modelling is advantageous for maximising predictive performance of species distribution models. Ecography 43(4):549–558. https://doi.org/10.1111/ecog.04890
Havel JE, Kovalenko KE, Thomaz SM, Amalfitano S, Kats LB (2015) Aquatic invasive species: challenges for the future. Hydrobiologia 750(1):147–170. https://doi.org/10.1007/s10750-014-2166-0
Hermoso V, Clavero M, Blanco-Garrido F, Prenda J (2011) Invasive species and habitat degradation in Iberian streams: an analysis of their role in freshwater fish diversity loss. Ecol Appl 21(1):175–188. https://doi.org/10.1890/09-2011.1
Hijmans RJ, Phillips S, Leathwick J, Elith J (2011) Package ‘dismo’. http://cran.r-project.org/web/packages/dismo/index.html. Accessed 23 Aug 2022
Hodgson JR, Hansen EM (2005) Terrestrial prey items in the diet of largemouth bass, Micropterus salmoides, in a small north temperate lake. J Fresh Ecol 20(4):2005. https://doi.org/10.1080/02705060.2005.9664809
Holt J, Leach AW, Schrader G, Petter F, MacLeod A, van der Gaag DJ, Mumford JD (2014) Eliciting and combining decision criteria using a limited palette of utility functions and uncertainty distributions: illustrated by application to pest risk analysis. Risk Anal 34(1):4–16. https://doi.org/10.1111/risa.12089
Hong S, Jang I, Kim D, Kim S, Park HS, Lee K (2022) Predicting potential habitat changes of two invasive alien fish species with climate change at a regional scale. Sustainability 14(10):6093. https://doi.org/10.3390/su14106093
IPCC (2013) Climate change 2013: the physical science basis. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge
Jang MH, Joo GJ, Lucas MC (2006) Diet of introduced largemouth bass in Korean rivers and potential interactions with native fishes. Ecol Freshw Fish 15(3):315–320. https://doi.org/10.1111/j.1600-0633.2006.00161.x
Jones PE, Tummers JS, Galib SM, Woodford DJ, Hume JB, Silva LGM, Braga RR, Leaniz CG, Vitule JRS, Herder JE, Lucas MC (2021) The use of barriers to limit the spread of aquatic invasive animal species: a global review. Front Ecol Evol. https://doi.org/10.3389/fevo.2021.611631
Jones-Farrand DT, Fearer TM, Thogmartin WE, Thompson FR III, Nelson MD, Tirpak JM (2011) Comparison of statistical and theoretical habitat models for conservation planning: the benefit of ensemble prediction. Ecol Appl 21(6):2269–2282. https://doi.org/10.1890/10-1047.1
Kamerath M, Chandra S, Allen BC (2008) Distribution and impacts of warm water invasive fish in Lake Tahoe, USA. Aquat Invasions 3(1):35–41. https://doi.org/10.3391/ai.2008.1.1.7
Keller RP, Zu Ermgassen PS, Aldridge DC (2009) Vectors and timing of freshwater invasions in Great Britain. Conserv Biol 23(6):1526–1534. https://doi.org/10.1111/j.1523-1739.2009.01249.x
Kernan M (2015) Climate change and the impact of invasion on aquatic ecosystems. Aquat Ecosyst Health Manag 18:321–333. https://doi.org/10.1080/14634988.2015.1027636
Kim JE, An K-G (2021) Long-term distribution trend analysis of largemouth bass (Micropterus salmoides), based on national fish database, and the ecological risk assessments. Korean J Environ Biol 39(2):207–217. https://doi.org/10.11626/KJEB.2021.39.2.207
Kim Z, Shim T, Ki SJ, Seo D, An K-G, Jung J (2021) Evaluation of classification algorithms to predict largemouth bass (Micropterus salmoides) occurrence. Sustainability 13(17):9507. https://doi.org/10.3390/su13179507
Kim Z, Shim T, Ki SJ, An K-G, Jung J (2022) Prediction of three-dimensional shift in the distribution of largemouth bass (Micropterus salmoides) under climate change in South Korea. Ecol Indic 137:108731. https://doi.org/10.1016/j.ecolind.2022.108731
Kolar CS, Lodge DM (2002) Ecological predictions and risk assessment for alien fishes in North America. Science 298(5596):1233–1236. https://doi.org/10.1126/science.1075753
Kutner MC, Nachtsheim C, Neter J (2008) Applied linear regression models, 4th edn. McGraw Hill, New York
Lawson LL Jr, Hill JE, Vilizzi L, Hardin S, Copp GH (2013) Revisions of the fish invasiveness screening kit (FISK) for its application in warmer climatic zones, with particular reference to peninsular Florida. Risk Anal 33(8):1414–1431. https://doi.org/10.1111/j.1539-6924.2012.01896.x
Lee D-S, Lee D-Y, Ji CW, Kwak I-S, Hwang S-J, Lee H-J, Park Y-S (2020) Impacts of introduced fishes (Carassius cuvieri, Micropterus salmoides, Lepomis macro macrochirus) on stream fish communities in South Korea. Korean Soc Limnol 53(3):241–254. https://doi.org/10.11614/KSL.2020.53.3.241
Lemmens P, Mergeay J, Vanhove T, De Meester L, Declerck SA (2014) Suppression of invasive topmouth gudgeon Pseudorasbora parva by native pike Esox lucius in ponds. Aquat Conserv Mar Freshw Ecosyst 25(1):41–48. https://doi.org/10.1002/aqc.2479
Lobo JM, Jiménez-Valverde A, Hortal J (2010) The uncertain nature of absences and their importance in species distribution modelling. Ecography 33(1):103–114. https://doi.org/10.1111/j.1600-0587.2009.06039.x
Lodge DM, Williams S, MacIsaac HJ, Hayes KR, Leung B, Reichard S, McMichael A (2006) Biological invasions: recommendations for US policy and management. Ecol Appl 16(6):2035–2054. https://doi.org/10.1890/1051-0761(2006)016[2035:BIRFUP]2.0.CO;2
Lodge DM, Simonin PW, Burgiel SW, Keller RP, Bossenbroek JM, Jerde CL, Zhang H (2016) Risk analysis and bioeconomics of invasive species to inform policy and management. Annu Review Environ Resour 41:453–488. https://doi.org/10.1146/annurev-environ-110615-085532
Maezono Y, Miyashita T (2003) Community-level impacts induced by introduced largemouth bass and bluegill in farm ponds in Japan. Biol Conserv 109(1):111–121. https://doi.org/10.1016/S0006-3207(02)00144-1
Mainali KP, Warren DL, Dhileepan K et al. (2015) Projecting future expansion of invasive species: comparing and improving methodologies for species distribution modeling. Glob Change Biol 21(12):4464–4480. https://doi.org/10.1111/gcb.13038
Mandrak NE, Cudmore B (2015) Risk assessment: cornerstone of an aquatic invasive species program. Aquat Ecosyst Health Manag 18(3):312–320. https://doi.org/10.1080/14634988.2015.1046357
Ministry of Environment (MOE) and National Institution of Ecology (NIE) (2021) Information for the field management of invasive alien species in Korea. National Institution of Ecology, Seocheon, Korea
Moghaddas SD, Abdoli A, Kiabi BH, Rahmani H, Vilizzi L, Copp GH (2021) Identifying invasive fish species threats to RAMSAR wetland sites in the Caspian Sea region—a case study of the Anzali Wetland Complex (Iran). Fish Manag Ecol 28(1):28–39. https://doi.org/10.1111/fme.12453
Mumford JD, Booy O, Baker RHA, Rees M, Copp GH, Black K, Hartley M (2010) Invasive non-native species risk assessment in Great Britain. Asp Appl Biol 104:49–54
Musil J, Adámek Z (2007) Piscivorous fishes diet dominated by the Asian cyprinid invader, topmouth gudgeon (Pseudorasbora parva). Biologia 62(4):488–490. https://doi.org/10.2478/s11756-007-0093-5
National Institute of Environmental Research (NIER) (2014) Survey and assessment of stream/river ecosystem health(VII). National Institute of Environmental Research, Incheon, Korea
Nienhuis S, Haxton T (2016) A Bayesian risk assessment tool to quantify the probability of aquatic invasions in Ontario-background documentation. Ontario Ministry of Natural Resources and Forestry, Science and Research Branch, Peterborough, ON
Oreska MP, Aldridge DC (2011) Estimating the financial costs of freshwater invasive species in Great Britain: a standardized approach to invasive species costing. Biol Invasions 13(2):305–319. https://doi.org/10.1007/s10530-010-9807-7
Page LM, Burr BM (1991) A field guide to freshwater fishes: North America north of Mexico. Houghton Mifflin Harcourt, Boston
Pineda E, Lobo JM (2009) Assessing the accuracy of species distribution models to predict amphibian species richness patterns. J Anim Ecol 78(1):182–190. https://doi.org/10.1111/j.1365-2656.2008.01471.x
Poulos HM, Chernoff B, Fuller PL, Butman D (2012) Ensemble forecasting of potential habitat for three invasive fishes. Aquat Invasions 7(1):59–72. https://doi.org/10.3391/ai.2012.7.1.007
R Core Team (2021) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org/. Accessed 28 Oct 2021
Rahel FJ, Olden JD (2008) Assessing the effects of climate change on aquatic invasive species. Conserv Biol 22:551–561. https://doi.org/10.1111/j.1523-1739.2008.00950.x
Rokach L (2010) Ensemble-based classifiers. Artif Intell Rev 33(1):1–39. https://doi.org/10.1007/s10462-009-9124-7
Rowe DK (2007) Exotic fish introductions and the decline of water clarity in small North Island, New Zealand lakes: a multi-species problem. Hydrobiologia 583(1):345–358. https://doi.org/10.1007/s10750-007-0646-1
Roy HE, Rabitsch W, Scalera R, Stewart A, Gallardo B, Genovesi P, Zenetos A (2018) Developing a framework of minimum standards for the risk assessment of alien species. J Appl Ecol 55(2):526–538. https://doi.org/10.1111/1365-2664.13025
Roy HE, Bacher S, Essl F, Adriaens T, Aldridge DC, Bishop JD, Rabitsch W (2019) Developing a list of invasive alien species likely to threaten biodiversity and ecosystems in the European Union. Glob Change Biol 25(3):1032–1048. https://doi.org/10.1111/gcb.14527
Seebens H, Blackburn TM, Dyer EE, Genovesi P, Hulme PE, Jeschke JM, Essl F (2017) No saturation in the accumulation of alien species worldwide. Nat Commun 8:14435. https://doi.org/10.1038/ncomms14435
Simberloff D, Von Holle B (1999) Positive interactions of nonindigenous species: invasional meltdown? Biol Invasions 1(1):21–32. https://doi.org/10.1023/A:1010086329619
Sor R, Park YS, Boets P, Goethals PL, Lek S (2017) Effects of species prevalence on the performance of predictive models. Ecol Model 354:11–19. https://doi.org/10.1016/j.ecolmodel.2017.03.006
Thuiller W, Lafourcade B, Engler R, Araújo MB (2009) BIOMOD—a platform for ensemble forecasting of species distributions. Ecography 32(3):369–373. https://doi.org/10.1111/j.1600-0587.2008.05742.x
Thuiller W, Georges D, Engler R, Breiner F, Georges MD, Thuiller CW (2016) Package ‘biomod2’. https://cran.r-project.org/web/packages/biomod2/. Accessed 28 Oct 2021
Turbelin AJ, Malamud BD, Francis RA (2017) Mapping the global state of invasive alien species: patterns of invasion and policy responses. Glob Ecol Biogeogr 26(1):78–92. https://doi.org/10.1111/geb.12517
UNEP (2014) Pathways of introduction of invasive species, their prioritization and management. UNEP/CBD/SBSTTA/18/9/Add.1, subsidiary body on scientific, technical and technological advice, eighteenth meeting, Montreal
Valavi R, Guillera-Arroita G, Lahoz-Monfort JJ, Elith J (2022) Predictive performance of presence-only species distribution models: a benchmark study with reproducible code. Ecol Monogr 92:e01486. https://doi.org/10.1002/ecm.1486
Van Kleef HH, Jongejans E (2014) Identifying drivers of pumpkinseed invasiveness using population models. Aquat Invasions 9(3):315–326. https://doi.org/10.3391/ai.2014.9.3.07
Van Rossum G, Drake FL (2009) Python 3 reference manual. CreateSpace, Scotts Valley
Vander Zanden MJ, Olden JD (2008) A management framework for preventing the secondary spread of aquatic invasive species. Can J Fish Aquat Sci 65(7):1512–1522. https://doi.org/10.1139/F08-099
Verhelst P, Boets P, Van Thuyne G, Verreycken H, Goethals PL, Mouton AM (2016) The distribution of an invasive fish species is highly affected by the presence of native fish species: evidence based on species distribution modelling. Biol Invasions 18(2):427–444. https://doi.org/10.1007/s10530-015-1016-y
Vilizzi L, Thwaites LA, Smith BB, Nicol JM, Madden CP (2014) Ecological effects of common carp (Cyprinus carpio) in a semi-arid floodplain wetland. Mar Freshw Res 65(9):802–817. https://doi.org/10.1071/MF13163
Zurell D, Franklin J, König C et al. (2020) A standard protocol for reporting species distribution models. Ecography 43(9):1261–1277. https://doi.org/10.1111/ecog.04960
Acknowledgements
This study was supported by the Korea Environment Industry & Technology Institute (KEITI) through the Exotic Invasive Species Management Program, funded by the Korea Ministry of Environment (MOE) [RE201807019].
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This study was supported by the Korea Environment Industry & Technology Institute through the Exotic Invasive Species Management Program, funded by the Korea Ministry of Environment [RE201807019].
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Conceptualization: ZK, JJ, EH; data curation: ZK, YC; funding acquisition: SJK, K-GA, JJ; methodology: ZK, YC, TS; visualization: ZK, TS; writing—original draft: ZK; writing—review and editing: JJ.
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Kim, Z., Cho, Y., Shim, T. et al. Quantitative risk assessment of largemouth bass (Micropterus salmoides) invasion in South Korea under different climate change scenarios. Aquat Sci 86, 3 (2024). https://doi.org/10.1007/s00027-023-01017-y
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DOI: https://doi.org/10.1007/s00027-023-01017-y