Browse > Article
http://dx.doi.org/10.1186/s41610-021-00196-9

Major environmental factors and traits of invasive alien plants determining their spatial distribution  

Oh, Minwoo (School of Biological Sciences, Seoul National University)
Heo, Yoonjeong (School of Biological Sciences, Seoul National University)
Lee, Eun Ju (School of Biological Sciences, Seoul National University)
Lee, Hyohyemi (National Institute of Ecology)
Publication Information
Journal of Ecology and Environment / v.45, no.4, 2021 , pp. 277-286 More about this Journal
Abstract
Background: As trade increases, the influx of various alien species and their spread to new regions are prevalent and no longer a special problem. Anthropogenic activities and climate changes have made the distribution of alien species out of their native range common. As a result, alien species can be easily found anywhere, and they have nothing but only a few differences in intensity. The prevalent distribution of alien species adversely affects the ecosystem, and a strategic management plan must be established to control them effectively. To this end, hot spots and cold spots were analyzed according to the degree of distribution of invasive alien plants, and major environmental factors related to hot spots were found. We analyzed the 10,287 distribution points of 126 species of alien plants collected through the national survey of alien species by the hierarchical model of species communities (HMSC) framework. Results: The explanatory and fourfold cross-validation predictive power of the model were 0.91 and 0.75 as AUC values, respectively. The hot spots of invasive plants were found in the Seoul metropolitan area, Daegu metropolitan city, Chungcheongbuk-do Province, southwest shore, and Jeju island. Generally, the hot spots were found where the higher maximum temperature of summer, precipitation of winter, and road density are observed, but temperature seasonality, annual temperature range, precipitation of the summer, and distance to river and sea were negatively related to the hot spots. According to the model, the functional traits accounted for 55% of the variance explained by the environmental factors. The species with higher specific leaf areas were more found where temperature seasonality was low. Taller species preferred the bigger annual temperature range. The heavier seed mass was only preferred when the max temperature of summer exceeded 29 ℃. Conclusions: In this study, hot spots were places where 2.1 times more alien plants were distributed on average than non-hot spots (33.5 vs 15.7 species). The hot spots of invasive plants were expected to appear in less stressful climate conditions, such as low fluctuation of temperature and precipitation. Also, the disturbance by anthropogenic factors or water flow had positive influences on the hot spots. These results were consistent with the previous reports about the ruderal or competitive strategies of invasive plants instead of the stress-tolerant strategy. The functional traits are closely related to the ecological strategies of plants by shaping the response of species to various environmental filters, and our result confirmed this. Therefore, in order to effectively control alien plants, it is judged that the occurrence of disturbed sites in which alien plants can grow in large quantities is minimized, and the river management of waterfronts is required.
Keywords
Invasive alien plants; Functional traits; Habitat suitability; Hot spot; Species distribution model;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Naimi B, Hamm NAS, Groen TA, Skidmore AK, Toxopeus AG. Where is positional uncertainty a problem for species distribution modelling. Ecography. 2014;37(2):191-203. https://doi.org/10.1111/j.1600-0587.2013.00205.x.   DOI
2 Grime JP. The role of plasticity in exploiting environmental heterogeneity. Exploitation of environmental heterogeneity by plants: ecophysiological processes above-and belowground, vol. 19. New York: Academic Press; 1994.
3 R Core Team. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical. Computing. 2020. https://www.R-project.org.
4 Aan A, Hallik LEA, Kull O, et al. J Ecol. 2006:1143-55.   DOI
5 Abrego N, Norberg A, Ovaskainen O. Measuring and predicting the influence of traits on the assembly processes of wood-inhabiting fungi. J Ecol. 2017;105(4):1070-81. https://doi.org/10.1111/1365-2745.12722.   DOI
6 Anselin L. Local indicators of spatial association-LISA. Geogr Anal. 1995;27(2):93-115. https://doi.org/10.1111/j.1538-4632.1995.tb00338.x.   DOI
7 Hood WG, Naiman RJ. Vulnerability of riparian zones to invasion by exotic vascular plants. Plant Ecol. 2000;148(1):105-14. https://doi.org/10.1023/A:1009800327334.   DOI
8 Falster DS, Westoby M. Plant height and evolutionary games. Trends in Ecology & Evolution. 2003;18(7):337-43. https://doi.org/10.1016/S0169-5347(03)00061-2.   DOI
9 Guo W-Y, van Kleunen M, Winter M, Weigelt P, Stein A, Pierce S, et al. The role of adaptive strategies in plant naturalization. Ecol Lett. 2018;21(9):1380-9. https://doi.org/10.1111/ele.13104.   DOI
10 Harper JL, Lovell PH, Moore KG. The shapes and sizes of seeds. Annu Rev Ecol Syst. 1970;1(1):327-56. https://doi.org/10.1146/annurev.es.01.110170.001551.   DOI
11 Hosmer DW Jr, Lemeshow S, Sturdivant RX. Applied logistic regression. 3rd ed. Hoboken: Wiley; 2013.
12 Hulme PE. Trade, transport and trouble: managing invasive species pathways in an era of globalization. J Appl Ecol. 2009;46(1):10-8. https://doi.org/10.1111/j.1365-2664.2008.01600.x.   DOI
13 Jin Y, Qian H. V.PhyloMaker: an R package that can generate very large phylogenies for vascular plants. Ecography. 2019;42(8):1353-9. https://doi.org/10.1111/ecog.04434.   DOI
14 Lobell DB, Field CB. Global scale climate-crop yield relationships and the impacts of recent warming. Environ Res Lett. 2007;2(1):014002. https://doi.org/10.1088/1748-9326/2/1/014002.   DOI
15 Joly M, Bertrand P, Gbangou RY, White M-C, Dube J, Lavoie C. Paving the way for invasive species: road type and the spread of common ragweed (Ambrosia artemisiifolia). Environ Manag. 2011;48(3):514-22. https://doi.org/10.1007/s00267-011-9711-7.   DOI
16 Lambers HANS, Poorter H. Inherent variation in growth rate between higher plants: a search for physiological causes and ecological consequences. Adv Ecol Res. 1992;23:187-261. https://doi.org/10.1016/S0065-2504(08)60148-8.   DOI
17 Lobell DB, Asner GP. Climate and management contributions to recent trends in U.S. agricultural yields. Science. 2003;299(5609):1032.   DOI
18 Reich PB, Walters MB, Ellsworth DS. Leaf life span in relation to leaf, plant, and stand characteristics among diverse ecosystems. Ecol Monogr. 1992;62(3):365-92. https://doi.org/10.2307/2937116.   DOI
19 Kattge J, Bonisch G, Diaz S, Lavorel S, Prentice IC, Leadley P, et al. TRY plant trait database - enhanced coverage and open access. Glob Chang Biol. 2020;26(1):119-88. https://doi.org/10.1111/gcb.14904.   DOI
20 Regos A, Gagne L, Alcaraz-Segura D, Honrado JP, Dominguez J. Effects of species traits and environmental predictors on performance and transferability of ecological niche models. Sci Rep. 2019;9(1).
21 Reich PB, Walters MB, Ellsworth DS. From tropics to tundra: global convergence in plant functioning. Proc Natl Acad Sci. 1997;94(25):13730-4. https://doi.org/10.1073/pnas.94.25.13730.   DOI
22 Pysek PETR, Prach K. How important are rivers for supporting plant invasions. Ecol Manag Invasive Riverside Plants. 1994:19-26.
23 Diagne C, Leroy B, Vaissiere AC, Gozlan RE, Roiz D, Jaric I, et al. High and rising economic costs of biological invasions worldwide. Nature. 2021;592(7855):571-6. https://doi.org/10.1038/s41586-021-03405-6.   DOI
24 Moles AT, Warton DI, Warman L, Swenson NG, Laffan SW, Zanne AE, et al. Global patterns in plant height. J Ecol. 2009;97(5):923-32. https://doi.org/10.1111/j.1365-2745.2009.01526.x.   DOI
25 Kaluza P, Kolzsch A, Gastner MT, Blasius B. The complex network of global cargo ship movements. J R Soc Interface. 2010;7(48):1093-103. https://doi.org/10.1098/rsif.2009.0495.   DOI
26 Moravcova L, Pysek P, Jarosik V, Pergl J. Getting the right traits: reproductive and dispersal characteristics predict the invasiveness of herbaceous plant species. PLoS ONE. 2015;10(4):e0123634. https://doi.org/10.1371/journal.pone.0123634.   DOI
27 Ovaskainen O, Tikhonov G, Dunson D, Grotan V, Engen S, Saether BE, et al. How are species interactions structured in species-rich communities? A new method for analysing time-series data. Proc Biol Sci. 2017;284(1855):20170768.
28 Pearson DE, Ortega YK, Eren O, Hierro JL. Community assembly theory as a framework for biological invasions. Trends Ecol Evol. 2018;33(5):313-25. https://doi.org/10.1016/j.tree.2018.03.002.   DOI
29 Pierce S, Brusa G, Vagge I, Cerabolini BEL. Allocating CSR plant functional types: the use of leaf economics and size traits to classify woody and herbaceous vascular plants. Funct Ecol. 2013;27(4):1002-10. https://doi.org/10.1111/1365-2435.12095.   DOI
30 Cadotte MW, Arnillas CA, Livingstone SW, Yasui SL. Predicting communities from functional traits. Trends Ecol Evol (Amst). 2015;30(9):510-1. https://doi.org/10.1016/j.tree.2015.07.001.   DOI
31 Tjur T. Coefficients of determination in logistic regression models-a new proposal: the coefficient of discrimination. Am Stat. 2009;63(4):366-72. https://doi.org/10.1198/tast.2009.08210.   DOI
32 Smith CC, Fretwell SD. The optimal balance between size and number of offspring. Am Nat. 1974;108(962):499-506. https://doi.org/10.1086/282929.   DOI
33 Tikhonov G, Duan L, Abrego N, Newell G, White M, Dunson D, et al. Computationally efficient joint species distribution modeling of big spatial data. Ecology. 2019:e02929.
34 Tikhonov G, Opedal OH, Abrego N, Lehikoinen A, Jonge MMJ, Oksanen J, et al. Joint species distribution modelling with the r -package H msc. Methods Ecol Evol. 2020;11(3):442-7. https://doi.org/10.1111/2041-210X.13345.   DOI
35 Westoby M. A leaf-height-seed (LHS) plant ecology strategy scheme. Plant Soil. 1998;199(2):213-27. https://doi.org/10.1023/A:1004327224729.   DOI
36 Diaz S, Kattge J, Cornelissen JH, Wright IJ, Lavorel S, Dray S, et al. The global spectrum of plant form and function. Nature. 2016;529(7585):167-71. https://doi.org/10.1038/nature16489.   DOI
37 Fick SE, Hijmans RJ. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int J Climatol. 2017;37:4302-15. https://doi.org/10.1002/joc.5086.   DOI
38 Vesk PA, Morris WK, Neal WC, Mokany K, Pollock LJ. Transferability of trait-based species distribution models. Ecography. 2021;44(1):134-47. https://doi.org/10.1111/ecog.05179.   DOI
39 Vojtech E, Loreau M, Yachi S, Spehn EM, Hector A. Light partitioning in experimental grass communities. Oikos. 2008;117(9):1351-61. https://doi.org/10.1111/j.0030-1299.2008.16700.x.   DOI
40 Warton DI, Blanchet FG, O'Hara RB, Ovaskainen O, Taskinen S, Walker SC, et al. So many variables: joint modeling in community ecology. Trends Ecol Evol (Amst). 2015;30(12):766-79. https://doi.org/10.1016/j.tree.2015.09.007.   DOI
41 Wright IJ, Reich PB, Westoby M, Ackerly DD, Baruch Z, Bongers F, et al. The worldwide leaf economics spectrum. Nature. 2004;428(6985):821-7. https://doi.org/10.1038/nature02403.   DOI
42 Belluau M, Shipley B. Linking hard and soft traits: Physiology, morphology and anatomy interact to determine habitat affinities to soil water availability in herbaceous dicots. PLOS ONE. 2018;13(3):e0193130. https://doi.org/10.1371/journal.pone.0193130.   DOI
43 Benedetti Y, Morelli F. Spatial mismatch analysis among hotspots of alien plant species, road and railway networks in Germany and Austria. PLoS ONE. 2017;12(8):e0183691. https://doi.org/10.1371/journal.pone.0183691.   DOI
44 Bivand RS, Wong DWS. Comparing implementations of global and local indicators of spatial association. Test. 2018;27(3):716-48. https://doi.org/10.1007/s11749-018-0599-x.   DOI
45 Mouillot D, Graham NA, Villeger S, Mason NW, Bellwood DR. A functional approach reveals community responses to disturbances. Trends Ecol Evol. 2013;28(3):167-77. https://doi.org/10.1016/j.tree.2012.10.004.   DOI
46 Brisson J, de Blois S, Lavoie C. Roadside as invasion pathway for common reed (Phragmites australis). Invasive Plant Sci Manag. 2010;3(4):506-14. https://doi.org/10.1614/IPSM-09-050.1.   DOI
47 Dawson W, Moser D, van Kleunen M, Kreft H, Pergl J, Pysek P, et al. Global hotspots and correlates of alien species richness across taxonomic groups. Nat Ecol Evol. 2017;1(7).
48 Meunier G, Lavoie C. Roads as corridors for invasive plant species: new evidence from smooth bedstraw (Galium mollugo). Invasive Plant Sci Manag. 2012;5(1):92-100. https://doi.org/10.1614/IPSM-D-11-00049.1.   DOI
49 NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team. ASTER Global Digital Elevation Model V003. NASA EOSDIS Land Processes DAAC; 2019. https://doi.org/10.5067/ASTER/ASTGTM.003. Accessed 07 Sept. 2020   DOI
50 Novoa A, Richardson DM, Pysek P, Meyerson LA, Bacher S, Canavan S, et al. Invasion syndromes: a systematic approach for predicting biological invasions and facilitating effective management. Biol Invasions. 2020;22(5):1801-20. https://doi.org/10.1007/s10530-020-02220-w.   DOI
51 Pluess AR, Schutz W, Stocklin J. Seed weight increases with altitude in the Swiss Alps between related species but not among populations of individual species. Oecologia. 2005;144(1):55-61. https://doi.org/10.1007/s00442-005-0047-y.   DOI