Skip to main content

Analysis of the invasiveness of spotted wing Drosophila (Drosophila suzukii) in North America, Europe, and the Mediterranean Basin

Abstract

The polyphagous Asian vinegar fly Drosophila suzukii (spotted wing Drosophila) is a native of Eastern and Southeastern Asia. It emerged as an important invasive insect pest of berries and stone fruits in the Americas and Europe beginning in 2008. Species distribution models are commonly used for analyzing the extant and potential range expansion of invasive species. Previous modeling efforts for D. suzukii include a degree-day model, a MaxEnt ecological niche model, a demographic model incorporating the effects of temperature, and a preliminary mechanistic physiologically-based demographic model (PBDM). In the present analysis, we refine the PBDM for D. suzukii based on biological data reported in the literature. The PBDM is used to assess the effects of temperature and relative humidity from a recently published global climate dataset (AgMERRA) on the prospective geographic distribution and relative abundance of the pest in the USA and Mexico, and in Europe and the Mediterranean Basin. Our focus is on areas of recent invasion and of predicted higher invasiveness in these areas. Although the species is native to Asia and is of putative temperate origins, it has established in subtropical to north temperate zones worldwide where it infests a wide range of wild and domesticated berries and stone fruits. The model captures the observed phenology of D. suzukii at specific locations, as well as the potential geographic distribution and relative favorability across larger regions. The main limiting factor is cold winter temperature in northern areas, though high temperatures and low relative humidity may be limiting in arid areas. The effect of greater cold tolerance in winter morph adults is explored.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

References

  • Adrion JR, Kousathanas A, Pascual M, Burrack HJ, Haddad NM, Bergland AO, Machado H, Sackton TB, Schlenke TA, Watada M, Wegmann D, Singh ND (2014) Drosophila suzukii: the genetic footprint of a recent, worldwide invasion. Mol Biol Evol 31:3148–3163. doi:10.1093/molbev/msu246

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Asplen MK, Anfora G, Biondi A, Choi D-S, Chu D, Daane KM, Gibert P, Gutierrez AP, Hoelmer KA, Hutchinson WD, Isaacs R, Jiang Z-L, Kárpáti Z, Kimura MT, Pascual M, Philips CR, Plantamp C, Ponti L, Vétek G, Vogt H, Walton VM, Yu Y, Zappalà L, Desneux N (2015) Invasion biology of spotted wing Drosophila (Drosophila suzukii): a global perspective and future priorities. J Pest Sci 88:469–494. doi:10.1007/s10340-015-0681-z

    Article  Google Scholar 

  • Bieri M, Baumgärtner J, Bianchi G, Delucchi V, Von Arx R (1983) Development and fecundity of pea aphid (Acyrthosiphon pisum Harris) as affected by constant temperatures and pea varieties. Mitt Schweiz Ent Ges 56:163–171

    Google Scholar 

  • Brière JF, Pracros P, Le Roux AY, Pierre JS (1999) A novel rate model of temperature-dependent development for arthropods. Environ Entomol 28:22–29

    Article  Google Scholar 

  • CERIS, Center for Environmental and Regulatory Information Systems (2015) Survey status of spotted wing Drosophila—Drosophila suzukii. http://pest.ceris.purdue.edu/map.php?code=IOAPAUA#. Accessed 15 Oct 2015

  • Chabert S, Allemand R, Poyet M, Ris N, Gibert P (2013) Drosophila suzukii, vers une lutte biologique contre ce ravageur des fruits rouges. Phytoma 660:34–38

    Google Scholar 

  • Cini A, Anfora G, Escudero-Colomar LA, Grassi A, Santosuosso U, Seljak G, Papini A (2014) Tracking the invasion of the alien fruit pest Drosophila suzukii in Europe. J Pest Sci 87:559–566

    Article  Google Scholar 

  • Coop L (2010) Online phenology and degree-day model for agricultural and decision-making in the US. Integrated Plant Protection Center, Botany & Plant Pathology Dept. Oregon State University, Corvallis, Oregon. http://uspest.org/risk/models?spp=swd

  • Dalton DT, Walton VM, Shearer PW, Walsh DB, Caprile J, Isaacs R (2011) Laboratory survival of Drosophila suzukii under simulated winter conditions of the Pacific Northwest and seasonal field trapping in five primary regions of small and stone fruit production in the United States. Pest Manag Sci 67:368–1374

    Article  CAS  Google Scholar 

  • Damus M (2009) Some preliminary results from Climex and Maxent distribution modeling of Drosophila suzukii. Version 2. CFIA Plant Health Risk Assessment, Ottawa, Canada. http://extension.wsu.edu/swd/Documents/Damus%202009.%20Climate%20modeling%20D.%20suzukii.pdf. Accessed 28 Oct 2015

  • David JR, Clavel MF (1965) Interaction entre le génotype et le milieu d’élevage. Conséquences sur les caractéristiques du développement de la Drosophile. Bull Biol Fr Bel 99:369–378

    Google Scholar 

  • DiCola G, Gilioli G, Baumgärtner J (1999) Mathematical models for age-structured population dynamics. In: Huffaker CB, Gutierrez AP (eds) Ecological entomology, 2nd edn. Wiley, New York, pp 503–534

    Google Scholar 

  • Dingle H (1972) Migration strategies of insects. Science 175:1327–1334

    Article  CAS  PubMed  Google Scholar 

  • Emiljanowicz LM, Ryan GD, Langille A, Newman J (2014) Development, reproductive output and population growth of the fruit fly pest Drosophila suzukii (Diptera: Drosophilidae) on artificial diet. J Econ Entomol 107(4):1392–1398

    Article  PubMed  Google Scholar 

  • Gilioli G, Pasquali S, Marchesini E (2016) A modelling framework for pest population dynamics and management: an application to the grape berry moth. Ecol Model 320:348–357. doi:10.1016/j.ecolmodel.2015.10.018

    Article  Google Scholar 

  • GRASS Development Team (2014) Geographic Resources Analysis Support System (GRASS) software, version 6.4.4. Open Source Geospatial Foundation. http://grass.osgeo.org

  • Gutierrez AP (1996) Applied population ecology: a supply-demand approach. Wiley, New York, p 300

    Google Scholar 

  • Gutierrez AP, Baumgärtner JU (1984) Multitrophic level models of predator–prey energetics: II. A realistic model of plant–herbivore–parasitoid–predator interactions. Can Entomol 116:933–949

    Article  Google Scholar 

  • Gutierrez AP, Ponti L (2013) Eradication of invasive species: why the biology matters. Environ Entomol 42:395–411. doi:10.1603/EN12018

    Article  PubMed  Google Scholar 

  • Gutierrez AP, Ponti L (2014) The new world screwworm: prospective distribution and role of weather in eradication. Agric For Entomol 16:158–173

    Article  Google Scholar 

  • Gutierrez AP, Havenstein DE, Nix HA, Moore PA (1974) The ecology of Aphis craccivora Koch and subterranean clover stunt virus. III. A regional perspective of the phenology and migration of the cowpea aphid. J Appl Ecol 11:21–35

    Article  Google Scholar 

  • Gutierrez AP, Ponti L, Gilioli G (2010) Climate change effects on plant–pest–natural enemy interactions. In: Hillel D, Rosenzweig C (eds) Handbook of climate change and agroecosystems: impact, adaptation and mitigation. Imperial College Press, London

    Google Scholar 

  • Gutierrez AP, Ponti L, Gilioli G (2014) Comments on the concept of ultra-low cryptic tropical fruit fly populations. Proc R Soc B Biol Sci 281:20132825

    Article  Google Scholar 

  • Hamby KA, Bellamy DE, Chiu JC, Lee JC, Walton VM, Wiman NG, York RM, Biondi A (2016) Biotic and abiotic factors impacting development, behavior, phenology, and reproductive biology of Drosophila suzukii. J Pest Sci. doi:10.1007/s10340-016-0756-5

    Google Scholar 

  • Harris DW, Hamby KA, Wilson HE, Zalom FG (2014) Seasonal monitoring of Drosophila suzukii (Diptera: Drosophilidae) in a mixed fruit production system. J Asia-Pac Entomol 17:857–864

    Article  Google Scholar 

  • IPCC (2014) Reports ‘Impacts, Adaptation and Vulnerability’, fourth and fifth assessment reports of the intergovernmental panel on climate change. http://ipcc-wg2.gov/publications/Reports/

  • Izquierdo JI (1991) How does Drosophila melanogaster overwinter? Entomol Exp Appl 59:51–58

    Article  Google Scholar 

  • Jakobs R, Gariepy TD, Sinclair BJ (2015) Adult plasticity of cold tolerance in a continental-temperate population of Drosophila suzukii. J Insect Physiol 79:1–9

    Article  CAS  PubMed  Google Scholar 

  • Jaramillo SL, Mehlferber E, Moore PJ (2015) Life-history trade-offs under different larval diets in Drosophila suzukii (Diptera: Drosophilidae). Physiol Entomol 40:2–9. doi:10.1111/phen.12082

    Article  Google Scholar 

  • Kaçar G, Wang X, Stewart TJ, Daane KM (2015) Overwintering survival of Drosophila suzukii (Diptera: Drosophilidae) and the effect of food on adult survival in California’s San Joaquin Valley. Environ Entomol. doi:10.1093/ee/nvv182

    PubMed  Google Scholar 

  • Kaneshiro KY (1983) Drosophila (Sophophora) suzukii (Matsumura). Proc Hawaii Entomol Soc 24:179

    Google Scholar 

  • Kanzawa T (1939) Studies on Drosophila suzukii Mats. Rev Appl Entomol 29:622 (abstract)

    Google Scholar 

  • Kenis M, Tonina L, Eschen R, van der Sluis B, Sancassani M, Mori N, Haye T, Helsen H (2016) Non-crop plants used as hosts by Drosophila suzukii in Europe. J Pest Sci. doi:10.1007/s10340-016-0755-6

    Google Scholar 

  • Kimura M (2004) Cold and heat tolerance of drosophilid flies with reference to their latitudinal distributions. Oecologia 140:442–449

    Article  PubMed  Google Scholar 

  • Kinjo H, Kunimi Y, Nakai M (2014) Effects of temperature on the reproduction and development of Drosophila suzukii (Diptera: Drosophilidae). Appl Entomol Zool 49:297–304

    Article  Google Scholar 

  • Klick J, Yang WQ, Walton VM, Dalton DT, Hagler JR, Dreves AJ, Lee JC, Bruck DJ (2015) Distribution and activity of Drosophila suzukii in cultivated raspberry and surrounding vegetation. J Appl Entomol 140:37–46. doi:10.1111/jen.12234

    Article  Google Scholar 

  • Langille AB, Arteca EM, Ryan GD, Emiljanowicz LM, Newman JA (2016) North American invasion of Spotted-Wing Drosophila (Drosophila suzukii): a mechanistic model of population dynamics. Ecol Model. doi:10.1016/j.ecolmodel.2016.05.014

    Google Scholar 

  • Lee JC, Dreves AJ, Cave AM, Kawai S, Isaacs R, Miller JC, Bruck DJ (2015) Infestation of wild and ornamental noncrop fruits by Drosophila suzukii (Diptera: Drosophilidae). Ann Entomol Soc Amer 108(2):117–129. doi:10.1093/aesa/sau014

    Article  Google Scholar 

  • Manetsch TJ (1976) Time-varying distributed delays and their use in aggregate models of large systems. IEEE Trans Syst Man Cybern 6:547–553

    Article  Google Scholar 

  • Metz M, Rocchini D, Neteler M (2014) Surface temperatures at the continental scale: tracking changes with remote sensing at unprecedented detail. Remote Sens 6:3822–3840. doi:10.3390/rs6053822

    Article  Google Scholar 

  • NASA (National Aeronautics and Space Administration) (2015) AgMERRA and AgCFSR climate forcing datasets for agricultural modeling. Goddard Institute for Space Studies. http://data.giss.nasa.gov/impacts/agmipcf/. Accessed 28 Oct 2015

  • Ometto L, Cestaro A, Ramasamy S, Grassi A, Revadi S, Siozios S, Moretto M, Fontana P, Varotto C, Pisani D, Dekker T, Wrobel N, Viola R, Pertot I, Cavalieri D, Blaxter M, Anfora G, Rota-Stabelli O (2013) Linking genomics and ecology to investigate the complex evolution of an invasive Drosophila pest. Genome Biol Evol 5:745–757. doi:10.1093/gbe/evt034

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Pelton E, Gratton C, Isaacs R, Van Timmeren S, Blanton A, Guédot C (2016) Earlier activity of Drosophila suzukii in high woodland landscapes but relative abundance is unaffected. J Pest Sci. doi:10.1007/s10340-016-0733-z

    Google Scholar 

  • Plantamp C, Salort K, Gibert P, Dumet A, Mialdea G, Mondy N, Voituron Y (2016) All or nothing: Survival, reproduction and oxidative balance in Spotted Wing Drosophila (Drosophila suzukii) in response to cold. J Insect Physiol 89:28–36. doi:10.1016/j.jinsphys.2016.03.009

    Article  CAS  PubMed  Google Scholar 

  • Ponti L, Gilioli G, Biondi A, Desneux N, Gutierrez AP (2015a) Physiologically based demographic models streamline identification and collection of data in evidence-based pest risk assessment. EPPO Bull 45:317–322. doi:10.1111/epp.12224

    Article  Google Scholar 

  • Ponti L, Gutierrez AP, Altieri MA (2015b) Holistic approach in invasive species research: the case of the tomato leaf miner in the Mediterranean Basin. Agroecol Sust Food Syst 39:436–468. doi:10.1080/21683565.2014.990074

    Article  Google Scholar 

  • Potter KA, Arthur Woods H, Pincebourde S (2013) Microclimatic challenges in global change biology. Glob Change Biol 19(10):2932–2939

    Article  Google Scholar 

  • Poyet M, Le Roux V, Gibert P, Meirland A, Prévost G, Eslin P, Chabrerie O (2015) The wide potential trophic niche of the asiatic fruit fly Drosophila suzukii: the key of its invasion success in temperate Europe? PLoS One 10:e0142785. doi:10.1371/journal.pone.0142785

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Ruane AC, Goldberg R, Chryssanthacopoulos J (2015) Climate forcing datasets for agricultural modeling: merged products for gap-filling and historical climate series estimation. Agric For Meteorol 200:233–248. doi:10.1016/j.agrformet.2014.09.016

    Article  Google Scholar 

  • Ryan GD, Emiljanowicz L, Wilkinson F, Kornya M, Newman JA (2016) Thermal tolerances of the spotted-wing Drosophila Drosophila suzukii (Diptera: Drosophilidae). J Econ Entomol. doi:10.1093/jee/tow006

    PubMed  Google Scholar 

  • Shearer PW, West JD, Walton VM, Brown PH, Svetec N, Chiu JC (2016) Seasonal cues induce phenotypic plasticity of Drosophila suzukii to enhance winter survival. BMC Ecol 16:11. doi:10.1186/s12898-016-0070-3

    Article  PubMed  PubMed Central  Google Scholar 

  • Stephens AR, Asplen MK, Hutchison WD, Venette RC (2015) Cold hardiness of winter-acclimated Drosophila suzukii (Diptera: Drosophilidae) adults. Environ Entomol 44:1619–1626. doi:10.1093/ee/nvv134

    Article  CAS  PubMed  Google Scholar 

  • R Core Team (2015) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. http://www.R-project.org

  • Tochen S, Dalton DT, Wiman N, Hamm C, Shearer PW, Walton VM (2014) Temperature-related development and population parameters for Drosophila suzukii (Diptera: Drosophilidae) on cherry and blueberry. Environ Entomol 43(2):501–510. doi:10.1603/EN13200

    Article  PubMed  Google Scholar 

  • Tochen S, Woltz JM, Dalton DT, Lee JC, Wiman NG, Walton VM (2015) Humidity affects populations of Drosophila suzukii (Diptera: Drosophilidae) in blueberry. J Appl Entomol 140:47–57. doi:10.1111/jen12247

    Article  Google Scholar 

  • Tominski C, Fuchs G, Schumann H (2008) Task-driven color coding. Information visualisation, IV’08 12th international conference, London, UK, pp 373–380. doi:10.1109/IV.2008.24

  • Toxopeus J, Jakobs R, Ferguson LV, Gariepy TD, Sinclair BJ (2016) Reproductive arrest and stress resistance in winter-acclimated Drosophila suzukii. J Insect Physiol 89:37–51. doi:10.1016/j.jinsphys.2016.03.006

    Article  CAS  PubMed  Google Scholar 

  • Vansickle J (1977) Attrition in distributed delay models. IEEE Trans Syst Man Cybern 7:635–638

    Article  Google Scholar 

  • Walsh DB, Bolda MP, Goodhue RE, Dreves AJ, Lee J, Bruck DJ, Walton VM, O’Neal SD, Zalom FG (2011) Drosophila suzukii (Diptera: Drosophilidae): invasive pest of ripening soft fruit expanding its geographic range and damage potential. J Integr Pest Manag 2(1):1–7. doi:10.1603/IPM10010

    Article  Google Scholar 

  • Wang X-G, Stewart TJ, Biondi A, Chavez BA, Ingels C, Caprile J, Grant JA, Walton VM, Daane KM (2016) Population dynamics and ecology of Drosophila suzukii in Central California. J Pest Sci. doi:10.1007/s10340-016-0747-6

    Google Scholar 

  • Wiman NG, Walton VM, Dalton DT, Anfora G, Burrack HJ, Chiu JC, Daane KM, Grassi A, Ioriatti C, Miller B, Tochen S, Wang X, Ioriatti C (2014) Integrating temperature—dependent life table data into a matrix projection model for Drosophila suzukii population estimation. PLoS One 9(9):e106909

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Wiman NG, Dalton DT, Anfora G, Biondi A, Chiu JC, Daane KM, Gerdeman B, Gottardello A, Hamby KA, Isaacs R, Grassi A, Ioriatti C, Lee JC, Miller B, Stacconi MVR, Shearer PW, Tanigoshi L, Wang X, Walton VM (2016) Drosophila suzukii population response to environment and management strategies. J Pest Sci. doi:10.1007/s10340-016-0757-4

    Google Scholar 

  • Zerulla FN, Schmidt S, Streitberger M, Zebitz CPW, Zelger R (2015) On the overwintering ability of Drosophila suzukii in South Tyrol. J Berry Res 5:41–48. doi:10.3233/JBR-150089

    Google Scholar 

Download references

Acknowledgments

We (A.P.G. and L.P.) wish to thank Dr. Patricia Gibert and C. Plantamp for providing developmental data initially reported in Asplen et al. (2015). We are grateful to Dr. Markus Neteler of mundialis GmbH & Co. KG http://www.mundialis.de and the international network of co-developers for maintaining the Geographic Resources Analysis Support System (GRASS) software, and making it available to the scientific community. Funding for the modeling/GIS analysis was provided by the Center for the Analysis of Sustainable Agricultural Sytems (CASAS) and Agenzia nazionale per le nuove tecnologie, l’energia e lo sviluppo economico sostenibile (ENEA), Rome Italy. The experimental work on D. suzukii was supported at Oregon State University by the US Department of Agriculture National Institute of Food and Agriculture (USDA-NIFA) award #2010-51181-21167, the Oregon Blueberry Commission, and the Northwest Center for Small Fruit Research, and the Agricultural Research Foundation.

Author contributions

A.P.G. and L.P. conceived and developed the PBDM/GIS system. D.D. developed field and laboratory data used in the analysis. All authors read and approved the manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Andrew Paul Gutierrez.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 951 kb)

Appendix

Appendix

A review of physiologically based demographic model (PBDM)

Physiologically-based demographic system models (PBDMs) explicitly capture the mechanistic weather-driven biology and dynamics of species at all trophic levels to predict the weather driven phenology, dynamics and distribution of single and multiple species across wide geographic areas on a daily basis—a time step rarely used in macro-ecological modeling (see Gutierrez and Baumgärtner 1984; Gutierrez 1996; Gutierrez and Ponti 2013). For some applications, the time step could be smaller or larger (Gilioli et al. 2016). The model captures via sub-models the processes of resource acquisition and allocation, and the birth–death rates in great detail or using simple functions that capture the relevant biology (see Gutierrez 1996; Gutierrez and Ponti 2013; Gilioli et al. 2016). PBDMs are sufficiently detailed to be realistic, and yet complexity is kept to a minimum by applying the same dynamics model and process sub models to all trophic levels. The complexity enters the model at the conceptual level and running the model requires minimal computational capacity. These models have contributed to basic theory and helped solve many applied field problems because they bridge the gap between purely theoretical analytic models and overly complicated simulation models. Physiological analogy across trophic levels is a powerful conceptual tool and is used as a way to tackle the huge challenges facing global ecosystem modeling.

A demographic dynamics model with distributed maturation times

The biology of resource acquisition and allocation is embedded in a demographic model with distributed maturation times (Manetsch 1976; Vansickle 1977) and is used to simulate the dynamics of age (and mass) structured populations where time (t) is chronological time and age (a) is in physiological time units (e.g., proportional development, degree days). But other dynamics models could also be used (e.g., Gutierrez 1996; DiCola et al. 1999; Gilioli et al. 2016).

The general distributed maturation time model for the ith age class of a population as a rate (r i ) is

$$\frac{{dr_{i}}}{dt} = \frac{k\,\Delta x}{del}[r_{i - 1} (t) - r_{i} (t)] - \mu_{i} (t)r_{i} (t).$$
(11)

The density of the ith cohort is \(N_{i} (t) = \frac{del}{k}r_{i}\), where Erlang parameter k is the number of different age cohorts (stages), del is the expected mean developmental time, Δx is an increment in time varying physiological age, \(\frac{k\,\Delta x}{del}\) scales the time varying flow rate of individuals between age classes, and \(- \infty < \mu_{i} (t) < \infty\) is the proportional net loss rate that could include age-species death and net immigration and in mass dynamics model the age specific growth rate. Note that births enter the first age class with age zero. The density of all k cohorts is \(N(t) = \sum\nolimits_{i = 1}^{k} {N_{i}} (t)\), but the density can also be summed by life stage. The maturation across the k age classes is depicted in Fig. 8a, while the patterns of emergence times for different values of k are depicted in Fig. 8b (see Manetsch 1976; Vansickle 1977). Assuming k = 25 age classes, the standard deviation of developmental times for the immature and adult life stages (i.e., \(std = \sqrt {del^{2}/k}\)) is ~20 % of the mean. Similar schemes could be used for each life stages (Fig. 8c).

Fig. 8
figure 8

A distributed maturation time model: a the general model across all life stages including flow rates between stages (r), net mortality rates [i.e. μ i (t), i = 1, , k] due to biotic and abiotic factors where x 0(t) are births and y(t) is death at maximum age, b the stylized distribution of cohort maturation times given different values of the Erlang parameter k, and c the general model with the dynamics of a specified for each life stage (S) including stage specific flow rates between stages (y stage ), net mortality (i.e. μstage) due to biotic and abiotic factors (see text)

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gutierrez, A.P., Ponti, L. & Dalton, D.T. Analysis of the invasiveness of spotted wing Drosophila (Drosophila suzukii) in North America, Europe, and the Mediterranean Basin. Biol Invasions 18, 3647–3663 (2016). https://doi.org/10.1007/s10530-016-1255-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10530-016-1255-6

Keywords