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Predicting Distributions of Invasive Species

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Elith, Jane·2017·Invasive Species
DOI 10.1017/9781139019606.006
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Abstract

This chapter aims to inform a practitioner about current methods for predicting potential distributions of invasive species. It mostly addresses single species models, covering the conceptual bases, touching on mechanistic models, and then focusing on methods using species distribution records and environmental data to predict distributions. The commentary in this last section is oriented towards key issues that arise in fitting, and predicting with, these models (which include CLIMEX, MaxEnt and other regression methods). In other words, it is more about the process of thinking about the data and the modelling problem (which is a challenging one) than it is about one technique versus another. The discussion helps clarify the necessary steps and expertise for predicting distributions. Some researchers are optimistic that correlative models will predict with high precision; while that may be true for some species at some scales of evaluation, I believe that the issues discussed in this chapter show that substantial errors are reasonably likely. I am hopeful that ongoing developments will produce models better suited to the task and tools to help practitioners to better understand predictions and their uncertainties.

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  • There is still much uncertainty in predictions of which species will colonize new regions and habitats and what their impacts will be.

    “Despite intensive research directed at modelling potential changes in the distribution of terrestrial, freshwater, and marine species owing to climate and land‐use change, there is still much uncertainty in predictions of which species will colonize new regions and habitats and what their impacts will be (Elith, 2017; Capinha et al., 2018; Rocchini et al., 2019).”

    From Scientists' warning on invasive alien species (2020) · cites this paper as Elith, 2017

    Section 5.5.7 describes multiple sources of uncertainty in predictions of invasive-species distributions, and the Conclusions (§5.6) say substantial prediction errors are reasonably likely. The chapter addresses where invasive species may find suitable conditions, but these passages do not establish uncertainty about which species will colonize or what their impacts will be. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

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Research works printed but not linked: 176

  1. 10.1890/07-0868.1 · DOI
  2. Elith, 2009, Spatial conservation prioritization: Quantitative methods and computational tools, 70, 10.1093/oso/9780199547760.003.0006 · DOI · Paper page
  3. 10.1111/j.1365-2664.2008.01524.x · DOI
  4. 10.1111/j.1469-8137.2006.01811.x · DOI
  5. Moisen, G. G. , & Frescino, T. S. (2002). Comparing five modeling techniques for predicting forest characteristics. Ecological Modelling, 157(2–3), 209–25. · DOI
  6. 10.1016/S0167-8809(00)00216-4 · DOI
  7. 10.1111/j.1472-4642.2008.00472.x · DOI
  8. 10.1111/j.0021-8901.2004.00881.x · DOI
  9. 10.1016/j.landurbplan.2006.04.002 · DOI
  10. 10.1111/j.1365-2699.2007.01716.x · DOI
  11. 10.1094/PDIS-91-4-0336 · DOI
  12. Huey, 2005, Species invasions: Insights into ecology, evolution and biogeography, 139
  13. 10.1046/j.1365-2699.2003.00861.x · DOI
  14. 10.1111/j.1570-7458.2006.00445.x · DOI
  15. 10.1111/j.1654-1103.2006.tb02505.x · DOI
  16. 10.1007/s13313-012-0178-7 · DOI
  17. 10.1890/07-2153.1 · DOI · Paper page
  18. 10.1080/10635150252899789 · DOI
  19. 10.1890/03-0820 · DOI
  20. 10.1111/j.1600-0587.2008.05505.x · DOI
  21. 10.1098/rsbl.2008.0254 · DOI
  22. 10.1111/j.1472-4642.2010.00727.x · DOI
  23. 10.1046/j.1365-2486.2003.00666.x · DOI
  24. 10.1016/j.ecolmodel.2006.05.021 · DOI
  25. 10.1371/journal.pone.0014670 · DOI
  26. 10.1016/j.ecolmodel.2006.05.025 · DOI
  27. 10.1073/pnas.0901637106 · DOI
  28. 10.1111/j.1600-0706.2009.17977.x · DOI
  29. 10.1016/j.ecolmodel.2006.07.005 · DOI
  30. 10.1111/j.1472-4642.2010.00725.x · DOI · Paper page
  31. 10.1046/j.1461-0248.2001.00261.x · DOI
  32. 10.1111/2041-210X.12180 · DOI
  33. 10.1666/0094-8373(2000)26[194:ROPPAC]2.0.CO;2 · DOI
  34. 10.1073/pnas.0901650106 · DOI · Paper page
  35. 10.1111/j.1472-4642.2007.00337.x · DOI
  36. 10.1111/j.1600-0587.2009.06042.x · DOI
  37. 10.1086/379204 · DOI
  38. 10.1111/j.1365-2664.2006.01136.x · DOI
  39. 10.1093/icesjms/fsn021 · DOI
  40. 10.1371/journal.pone.0040969 · DOI
  41. 10.1016/j.ecolmodel.2011.02.011 · DOI
  42. 10.1111/j.1472-4642.2008.00496.x · DOI
  43. 10.3354/meps225079 · DOI
  44. 10.1111/j.1600-0587.2009.06039.x · DOI · Paper page
  45. 10.1098/rsbl.2008.0181 · DOI
  46. 10.1111/j.1654-1103.2011.01274.x · DOI
  47. 10.1111/j.1541-0420.2008.01116.x · DOI
  48. 10.17161/bi.v3i0.29 · DOI
  49. 10.1017/CBO9780511810602 · DOI
  50. 10.1111/j.1654-1103.2011.01294.x · DOI
  51. 10.2307/1939924 · DOI
  52. 10.1111/j.1461-0248.2005.00792.x · DOI
  53. 10.1890/08-0134.1 · DOI
  54. 10.2193/0022-541X(2004)068[0774:UAIOLR]2.0.CO;2 · DOI
  55. Nix, 1986, Atlas of elapid snakes of Australia, 4
  56. 10.1111/j.2041-210X.2011.00134.x · DOI
  57. 10.1111/j.1365-2338.2010.02423.x · DOI
  58. 10.1038/sdata.2014.6 · DOI
  59. 10.1111/j.1523-1739.2008.00999.x · DOI
  60. 10.1111/j.1467-9671.2005.00220.x · DOI
  61. 10.1111/j.1461-0248.2007.01060.x · DOI
  62. 10.1016/S0304-3800(00)00354-9 · DOI · Paper page
  63. 10.1023/A:1021346712677 · DOI
  64. 10.1111/j.1365-2699.2006.01466.x · DOI
  65. 10.1111/j.1466-822X.2006.00237.x · DOI
  66. 10.1016/S1389-9341(02)00083-7 · DOI
  67. 10.1111/j.1466-8238.2009.00483.x · DOI
  68. 10.1111/j.1472-4642.2012.00887.x · DOI
  69. 10.1111/j.2006.0906-7590.04596.x · DOI · Paper page
  70. 10.1111/j.1472-4642.2010.00652.x · DOI
  71. 10.1016/j.ecolmodel.2008.07.015 · DOI
  72. 10.1111/j.2006.0030-1299.14908.x · DOI
  73. Gutzwiller, 2001, Bird-landscape relations in the Chihuahuan Desert: Coping with uncertainties about predictive models, Ecological Applications, 11, 1517
  74. 10.1111/j.1472-4642.2010.00639.x · DOI
  75. 10.1111/j.1365-2699.2010.02325.x · DOI
  76. 10.1016/j.ecolmodel.2006.05.023 · DOI
  77. 10.1016/j.ecolmodel.2007.11.013 · DOI
  78. 10.1046/j.1461-0248.2000.00143.x · DOI
  79. 10.1111/j.0906-7590.2008.05457.x · DOI
  80. 10.1525/bio.2010.60.5.5 · DOI
  81. 10.1016/S0304-3800(02)00202-8 · DOI
  82. 10.1016/j.ecolmodel.2005.03.026 · DOI · Paper page
  83. 10.1371/journal.pone.0079168 · DOI
  84. Thomas, 2010, Bioinvasions and globalization: Ecology, economics, management and policy, 19
  85. 122 Fensterer, V. (2010) Statistical methods in niche modelling for the spatial prediction of forest tree species. Diploma thesis, Ludwig-Maximilians-University Munich. www.osti.gov/eprints/topicpages/documents/record/277/2903664.html
  86. Busby, 1991, Nature conservation: Cost effective biological surveys and data analysis, 64
  87. 10.1007/s10530-011-9963-4 · DOI
  88. 10.1111/j.1365-3180.2010.00827.x · DOI
  89. 10.1007/s10530-009-9665-3 · DOI
  90. Hirzel, A. H. , Hausser, J. , Chessel, D. , & Perrin, N. (2002). Ecological-Niche factor analysis: how to compute habitat-suitability maps without absence data? Ecology, 83(7), 2027–2036. · DOI
  91. 10.1890/1051-0761(2007)017[0266:PVMFCI]2.0.CO;2 · DOI
  92. 10.1111/j.1365-2664.2007.01348.x · DOI
  93. 10.1046/j.1523-1739.2001.00053.x · DOI
  94. 10.1002/jpln.200700027 · DOI
  95. 10.1890/1051-0761(2001)011[0070:SRBOHS]2.0.CO;2 · DOI
  96. 10.1111/j.1365-2699.2006.01460.x · DOI
  97. 10.1016/0167-8809(85)90016-7 · DOI
  98. 10.2307/25065311 · DOI
  99. Harrell, 2006, Regression modeling strategies: With applications to linear models, logistic regression, and survival analysis,
  100. Peterson, 2011, Ecological niches and geographic distributions, 10.23943/princeton/9780691136868.001.0001 · DOI
  101. 10.1007/s10651-005-6816-2 · DOI
  102. 10.1890/07-1772.1 · DOI
  103. Phillips, 2011, Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 1384
  104. 10.1007/s10530-008-9228-z · DOI
  105. Peterson, 2008, Environmental data sets matter in ecological niche modelling: An example with Solenopsis invicta and Solenopsis richteri, Global Ecology and Biogeography, 17, 135, 10.1111/j.1466-8238.2007.00347.x · DOI
  106. 10.1007/978-0-387-84858-7 · DOI · Paper page
  107. Manly, 2002, Resource selection by animals: Statistical design and analysis for field studies
  108. 10.1111/j.1365-2486.2005.001018.x · DOI
  109. 10.1007/s00114-010-0694-7 · DOI
  110. 10.1111/j.1365-2699.2010.02416.x · DOI
  111. 10.1093/icb/42.3.431 · DOI
  112. 10.1016/j.ecolmodel.2009.08.013 · DOI
  113. 10.1111/j.1523-1739.2006.00560.x · DOI
  114. 10.1111/j.1365-2486.2006.01256.x · DOI
  115. 10.1890/02-5166 · DOI
  116. 10.1890/10-0173.1 · DOI
  117. 10.1111/j.1539-6924.2009.01284.x · DOI
  118. 10.1017/S003060530300036X · DOI
  119. 10.1111/j.1365-2699.2008.01887.x · DOI
  120. 10.1111/j.1365-2699.2011.02659.x · DOI
  121. 10.1111/j.1365-2699.2006.01673.x · DOI
  122. 10.1111/j.2007.0906-7590.05171.x · DOI · Paper page
  123. 10.1214/10-AOAS331 · DOI
  124. 10.1111/j.1541-0420.2006.00725.x · DOI
  125. Buckley, 2010, Can mechanism inform species’ distribution models?, Ecology Letters, 13, 1041, 10.1111/j.1461-0248.2010.01479.x · DOI
  126. 10.1111/2041-210X.12242 · DOI
  127. 10.1111/geb.12216 · DOI
  128. 10.1111/j.1472-4642.2011.00800.x · DOI
  129. 10.1086/368401 · DOI
  130. 10.1017/S0376892997000088 · DOI · Paper page
  131. 10.1890/1051-0761(2006)016[1377:UHSIAP]2.0.CO;2 · DOI
  132. 10.1016/j.ecolmodel.2004.07.012 · DOI
  133. 10.1111/j.1539-6924.2009.01343.x · DOI
  134. 10.1016/j.biocontrol.2009.10.001 · DOI
  135. 10.1214/13-AOAS667 · DOI
  136. 10.1111/j.1461-0248.2008.01277.x · DOI
  137. 10.1016/S0304-3800(00)00322-7 · DOI
  138. 10.1111/j.1466-8238.2011.00656.x · DOI
  139. 10.1016/j.tree.2004.07.006 · DOI
  140. 10.1111/j.1466-822X.2005.00182.x · DOI
  141. 10.1111/1365-2664.12234 · DOI
  142. 10.1007/s12080-009-0050-8 · DOI
  143. 10.1111/ecog.00845 · DOI
  144. 10.1111/j.1600-0587.2012.07348.x · DOI · Paper page
  145. Herborg, 2009, Bioeconomics of invasive species: Integrating ecology, economics, policy and management, 63, 10.1093/oso/9780195367980.003.0004 · DOI
  146. 10.1111/j.0030-1299.2008.16434.x · DOI
  147. 10.1016/j.ppees.2007.09.004 · DOI
  148. 10.1111/j.1749-6632.2011.06440.x · DOI
  149. 10.1023/A:1021302930424 · DOI
  150. 10.1111/j.1365-2699.2010.02329.x · DOI
  151. 10.1111/j.1755-263X.2010.00097.x · DOI
  152. 10.1016/0304-3800(95)00152-2 · DOI
  153. Cook, 1925, The distribution of the alfalfa weevil (Phytonomus posticus Gyll.). A study in physical ecology, Journal of Agricultural Research, 30, 479
  154. 10.1046/j.1365-2699.2003.00946.x · DOI
  155. 10.1111/ddi.12209 · DOI
  156. 10.1073/pnas.0901643106 · DOI
  157. 10.1086/378926 · DOI
  158. 10.1073/pnas.0606292104 · DOI
  159. 10.1016/j.tree.2006.09.010 · DOI · Paper page
  160. 10.1016/S0304-3800(02)00205-3 · DOI
  161. 10.1016/j.ecolmodel.2005.11.039 · DOI
  162. 10.1111/j.1654-1103.2010.01250.x · DOI
  163. 10.1016/0378-1127(88)90013-8 · DOI
  164. 10.1093/jee/99.3.979 · DOI
  165. 10.1890/0012-9658(2000)081[3178:CARTAP]2.0.CO;2 · DOI
  166. 10.1007/s10530-008-9313-3 · DOI
  167. 10.1002/joc.1276 · DOI
  168. 10.1890/06-1632.1 · DOI
  169. 10.1111/ele.12003 · DOI
  170. 10.1111/2041-210X.12352 · DOI
  171. 10.1111/j.1461-0248.2006.00954.x · DOI
  172. 10.1111/j.1466-8238.2008.00407.x · DOI
  173. Pearson, 2007, Species’ distribution modeling for conservation educators and practitioners
  174. 10.1146/annurev.ecolsys.110308.120159 · DOI · Paper page
  175. 10.2307/1943043 · DOI
  176. Sutherst, 2007, Climex version 3: User’s guide

Cited by

Sorted by citations

  • Scientists' warning on invasive alien species

    Pyšek, P., Hulme, P. E., Simberloff, D., Bacher, S., Blackburn, T. M., Carlton, J. T., Dawson, W., Essl, F., Foxcroft, L. C., Genovesi, P., et al. (2020) · Biological Reviews · doi:10.1111/brv.12627 · Cited by 2,234

    “Despite intensive research directed at modelling potential changes in the distribution of terrestrial, freshwater, and marine species owing to climate and land-use change, there is still much uncertainty in predictions of which species will colonize new regions and habitats and what their impacts will be (Elith, 2017;…”
    Background

Metadata

Authors
Elith, J.
Affiliations
The University of Melbourne (AU)
Corresponding author
Elith, Jane
ORCID
Elith, Jane
Venue
Invasive Species
Publisher
Cambridge University Press
Published
2017-06-08
Pages
93-129
DOI
10.1017/9781139019606.006
OpenAlex
W1815427854
Cited by
106
References
4
Citations by year
2026: 3 · 2025: 16 · 2024: 11 · 2023: 8 · 2022: 10 · 2021: 11 · 2020: 8 · 2019: 17 · 2018: 4 · 2017: 8
FWCI
18.30
Type
book chapter
Language
en
Open access
Licence
www.cambridge.org/core/terms (unspecified, 25 d)
Locations
  • Cambridge University Press eBooks (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • arXiv (Cornell University)
Topics
  • Physical Sciences › Environmental Science › Ecological Modeling › Species Distribution and Climate Change
  • Physical Sciences › Environmental Science › Nature and Landscape Conservation › Ecology and Vegetation Dynamics Studies
  • Life Sciences › Agricultural and Biological Sciences › Plant Science › Botany and Plant Ecology Studies
Keywords
invasive species, species distribution prediction, mechanistic model, correlation model, CLIMEX, MaxEnt, species distribution records, environmental data, model fitting, forecast uncertainty, single-species model

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