Advertisement

Ambio

, Volume 45, Issue 8, pp 895–903 | Cite as

Generating an agricultural risk map based on limited ecological information: A case study using Sicyos angulatus

  • Takeshi Osawa
  • Shigenori Okawa
  • Shunji Kurokawa
  • Shinichiro Ando
Report

Abstract

In this study, we propose a method for estimating the risk of agricultural damage caused by an invasive species when species-specific information is lacking. We defined the “risk” as the product of the invasion probability and the area of potentially damaged crop for production. As a case study, we estimated the risk imposed by an invasive weed, Sicyos angulatus, based on simple cellular simulations and governmental data on the area of crop that could potentially be damaged in Miyagi Prefecture, Japan. Simulation results revealed that the current distribution range was sufficiently accurate for practical purposes. Using these results and records of crop areas, we present risk maps for S. angulatus in agricultural fields. Managers will be able to use these maps to rapidly establish a management plan with minimal cost. Our approach will be valuable for establishing a management plan before or during the early stages of invasion.

Keywords

Agricultural risk Alien invasive species Management strategy Risk mapping Risk management Virtual ecology 

Notes

Acknowledgments

We would like to thank Dr. M. Akasaka for giving us good suggestions. Two anonymous reviewers gave us many constructive suggestions. We also would like to thank Dr. D. Sprague for checking English.

References

  1. Akasaka, M., T. Osawa, and M. Ikegami. 2015. The role of roads and urban area in occurrence of an ornamental invasive weed: A case of Rudbeckia laciniata L. Urban Ecosystems 18: 1021–1030.CrossRefGoogle Scholar
  2. Akasaka, M., M. Takada, R. Kitagawa, and H. Igarashi. 2012. Invasive non-native species attributes and invasion extent: Examining the importance of grain size. Journal of Vegetation Science 23: 33–40.CrossRefGoogle Scholar
  3. Albert, C.H., F. Grassein, F.M. Schurr, G. Vieilledent, and C. Violle. 2011. When and how should intraspecific variability be considered in trait-based plant ecology? Perspectives in Plant Ecology, Evolution and Systematics 13: 217–225.CrossRefGoogle Scholar
  4. Millennium Ecosystem Assessment. 2005. Ecosystems and human well-being. Washington, DC: Island Press.Google Scholar
  5. Barney, J.N. 2006. North American history of two invasive plant species: Phytogeographic distribution, dispersal vectors, and multiple introductions. Biological Invasions 8: 703–717.CrossRefGoogle Scholar
  6. Berkes, F., J. Colding, and C. Folke. 2000. Rediscovery of traditional ecological knowledge as adaptive management. Ecological Applications 10: 1251–1262.CrossRefGoogle Scholar
  7. Cristescu, B., and M.S. Boyce. 2013. Focusing ecological research for conservation. Ambio 42: 805–815.CrossRefGoogle Scholar
  8. Davies, K.F., P. Chesson, S. Harrison, B.D. Inouye, B.A. Melbourne, and K.J. Rice. 2005. Spatial heterogeneity explains the scale dependence of the native-exotic diversity relationship. Ecology 86: 1602–1610.CrossRefGoogle Scholar
  9. Drolet, D., C. DiBacco, A. Locke, C.H. McKenzie, C.W. McKindsey, A.M. Moore, J.L. Webb, and T.W. Therriault. 2016. Evaluation of a new screening-level risk assessment tool applied to non-indigenous marine invertebrates in Canadian coastal waters. Biological Invasions 18: 279–294.CrossRefGoogle Scholar
  10. Engler, R., A. Guisan, and L. Rechsteiner. 2004. An improved approach for predicting the distribution of rare and endangered species from occurrence and pseudo-absence data. Journal of Applied Ecology 41: 263–274.CrossRefGoogle Scholar
  11. Foxcroft, L.C., D.M. Richardson, M. Rouget, and S. MacFadyen. 2009. Patterns of alien plant distribution at multiple spatial scales in a large national park: Implications for ecology, management and monitoring. Diversity and Distributions 15: 367–378.CrossRefGoogle Scholar
  12. Giljohann, K.M., C.E. Hauser, N.S.G. Williams, and J.L. Moore. 2011. Optimizing invasive species control across space: Willow invasion management in the Australian Alps. Journal of Applied Ecology 48: 1286–1294.CrossRefGoogle Scholar
  13. Guisan, A., and W. Thuiller. 2005. Predicting species distribution: Offering more than simple habitat models. Ecology Letters 8: 993–1009.CrossRefGoogle Scholar
  14. Holle, B.V., and D. Simberloff. 2005. Ecological resistance to biological invasion overwhelmed by propagule pressure. Ecology 86: 3212–3218.CrossRefGoogle Scholar
  15. Humston, R., D.A. Mortensen, and O.N. Bjoernstad. 2005. Anthropogenic forcing on the spatial dynamics of an agricultural weed: The case of the common sunflower. Journal of Applied Ecology 42: 863–872.CrossRefGoogle Scholar
  16. Januchowski-Hartley, S.R., P. Visconti, and R.L. Pressey. 2011. A systematic approach for prioritizing multiple management actions for invasive species. Biological Invasions 13: 1241–1253.CrossRefGoogle Scholar
  17. Kaplan, H., A. van Niekerk, J.J. Le Roux, D.M. Richardson, and J.R. Wilson. 2014. Incorporating risk mapping at multiple spatial scales into eradication management plans. Biological Invasions 16: 691–703.CrossRefGoogle Scholar
  18. Kobayashi, H., S. Kurokawa, and K. Ikeda. 2012. Dairyland populations of bur cucumber (Sicyos angulatus) as a possible seed source for riverbank populations along the Abukuma River, Japan. Weed Biology and Management 12: 147–155.CrossRefGoogle Scholar
  19. Koike, F. 2006. Prediction of range expansion and optimum strategy for spatial control of feral raccoon using a metapopulation model. Assessment and control of biological invasion risks, 148–156. Kyoto: Shoukadoh Book Sellers, IUCN, Gland.Google Scholar
  20. Koike, F., and K. Iwasaki. 2011. A simple range expansion model of multiple pathways: The case of nonindigenous green crab Carcinus aestuarii in Japanese waters. Biological Invasions 13: 459–470.CrossRefGoogle Scholar
  21. Kurokawa, S., H. Kobayashi, and T. Senda. 2009. Genetic diversity of Sicyos angulatus in central and northeastern Japan by inter-simple sequence repeat analysis. Weed Research 49: 365–372.CrossRefGoogle Scholar
  22. Leung, B., D.M. Lodge, D. Finnoff, J.F. Shogren, M.A. Lewis, and G. Lamberti. 2002. An ounce of prevention or a pound of cure: Bioeconomic risk analysis of invasive species. Proceedings of the Royal Society of London Series B: Biological Sciences 269: 2407–2413.CrossRefGoogle Scholar
  23. Leuven, R.S.E.W., G. van der Velde, I. Baijens, J. Snijders, C. van der Zwart, H.J.R. Lenders, and A. bij de Vaate. 2009. The river Rhine: A global highway for dispersal of aquatic invasive species. Biological Invasions 11: 1989–2008.CrossRefGoogle Scholar
  24. Lockwood, J.L., P. Cassey, and T. Blackburn. 2005. The role of propagule pressure in explaining species invasions. Trends in Ecology & Evolution 20: 223–228.CrossRefGoogle Scholar
  25. Moles, A.T., M.A.M. Gruber, and S.P. Bonser. 2008. A new framework for predicting invasive plant species. Journal of Ecology 96: 13–17.Google Scholar
  26. NARO. 2013. A report on invasive weed for forage crops in summer season. 1347–2712.Google Scholar
  27. Osawa, T., and K. Ito. 2015. A rapid method for constructing precaution maps based on a simple virtual ecology model: A case study on the range expansion of the invasive aquatic species Limnoperna fortunei. Population Ecology 57: 529–538.CrossRefGoogle Scholar
  28. Osawa, T., H. Mitsuhashi, and H. Niwa. 2013. Many alien invasive plants disperse against the direction of stream flow in riparian areas. Ecological Complexity 15: 26–32.CrossRefGoogle Scholar
  29. Osawa, T., H. Mitsuhashi, H. Niwa, and A. Ushimaru. 2011. The role of river confluences and meanderings in preserving local hot spots for threatened plant species in riparian ecosystems. Aquatic Conservation: Marine and Freshwater Ecosystems 21: 358–363.CrossRefGoogle Scholar
  30. Pagel, J., and F.M. Schurr. 2012. Forecasting species ranges by statistical estimation of ecological niches and spatial population dynamics. Global Ecology and Biogeography 21: 293–304.CrossRefGoogle Scholar
  31. Parendes, L.A., and J.A. Jones. 2000. Role of light availability and dispersal in exotic plant invasion along roads and streams in the HJ Andrews Experimental Forest, Oregon. Conservation Biology 14: 64–75.CrossRefGoogle Scholar
  32. Pichancourt, J.B., I. Chadès, J. Firn, R.D. van Klinken, and T.G. Martin. 2012. Simple rules to contain an invasive species with a complex life cycle and high dispersal capacity. Journal of Applied Ecology 49: 52–62.CrossRefGoogle Scholar
  33. Pimentel, D., S. McNair, J. Janecka, J. Wightman, C. Simmonds, C. O’connell, E. Wong, L. Russel, J. Zern, and T. Aquino. 2001. Economic and environmental threats of alien plant, animal, and microbe invasions. Agriculture, Ecosystems & Environment 84: 1–20.CrossRefGoogle Scholar
  34. Pimentel, D., R. Zuniga, and D. Morrison. 2005. Update on the environmental and economic costs associated with alien-invasive species in the United States. Ecological Economics 52: 273–288.CrossRefGoogle Scholar
  35. Pysek, P., V. Jarosik, P.E. Hulme, J. Pergl, M. Hejda, U. Schaffner, and M. Vila. 2012. A global assessment of invasive plant impacts on resident species, communities and ecosystems: The interaction of impact measures, invading species’ traits and environment. Global Change Biology 18: 1725–1737.CrossRefGoogle Scholar
  36. R Development Core Team. 2014. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Available at: http://developer.r-project.org/.
  37. Shaw, D.R. 2005. Remote sensing and site-specific weed management. Frontiers in Ecology and the Environment 3: 526–532.CrossRefGoogle Scholar
  38. Shimizu, N. 1999. The level of damage by the foreign weed Sicyos angulatus. Weed Science Society of Japan 2: 2–3.Google Scholar
  39. Simberloff, D. 2003. How much information on population biology is needed to manage introduced species? Conservation Biology 17: 83–92.CrossRefGoogle Scholar
  40. Suter II, G.W. 2006. Ecological risk assessment. Boca Raton: CRC Press.Google Scholar
  41. Watanabe, O., S. Kurokawa, H. Sasaki, T. Nishida, T. Onoue, and Y. Yoshimura. 2002. Geographic scale distribution and occurrence pattern of invasive weeds. Grassland Science 48: 440–450.Google Scholar

Web References

  1. CABI, Crop Protection Compendium. Retrieved February 20, 2016, from http://www.cabi.org/cpc.
  2. EPPO, EPPO Global Database. Retrieved February 20, 2016, from https://gd.eppo.int/.
  3. Japan Map Center. Retrieved February 20, 2016, from http://www.jmc.or.jp/ (in Japanese).
  4. Ministry of Agriculture, Forestry and Fisheries. Census for Agriculture, Forestry and Fisheries (CAFF) 2005. Retrieved February 20, 2016, from http://www.maff.go.jp/j/tokei/census/afc/2010/05houkokusyo.html (in Japanese).
  5. Ministry of Agriculture, Forestry and Fisheries. Caution invasive weeds. Retrieved February 20, 2016, from https://www.s.affrc.go.jp/docs/pdf/sicyos.pdf (in Japanese).
  6. Ministry of Land, Infrastructure, Transport and Tourism, Japan. National Land Numerical Information Download Service. Retrieved February 20, 2016, from http://nlftp.mlit.go.jp/ksj-e/.
  7. Ministry of Environment. Biodiversity Center of Japan (J-IBIS). Retrieved February 20, 2016, from http://www.biodic.go.jp/trialSystem/top_en.html.

Copyright information

© Royal Swedish Academy of Sciences 2016

Authors and Affiliations

  • Takeshi Osawa
    • 1
  • Shigenori Okawa
    • 2
  • Shunji Kurokawa
    • 3
  • Shinichiro Ando
    • 2
  1. 1.National Institute for Agro-environmental SciencesTsukubaJapan
  2. 2.Miyagi Prefectural Furukawa Agricultural Experiment StationFurukawaJapan
  3. 3.NARO Agricultural Research CenterTsukubaJapan

Personalised recommendations