Biological Invasions

, Volume 16, Issue 3, pp 677–690 | Cite as

Cross-scale management strategies for optimal control of trees invading from source plantations

Original Paper


Biological invasion by non-native tree species can transform landscapes, and as a consequence, has received growing attention from researchers and managers alike. This problem is driven primarily by the naturalisation and invasion of tree species escaping from cultivation or forestry plantations. Furthermore, these invasions can be strongly influenced by the land-use matrix of the surrounding region, specific management of the source populations, and environmental conditions that influence seed dispersal or habitat quality for the invader. A major unresolved challenge for managing tree invasions in landscapes is how management should be deployed to contain or slow the spread of invading populations from one or more sources (e.g. plantations). We develop a spatial simulation model to test: (1) how to best prioritise the control of invasive tree populations spatially to slow or contain the biological invader when habitat quality varies in the landscape, and (2) how to allocate control effort among different management units when trees spread from many source populations. We first show that to slow down spread effectively, management strategy is less important than management effort. We then identify the conditions affecting the relative performance of different management strategies. At the landscape scale, targeting peripheral stands consistently yielded the best results whereas at the regional scale, management strategies needed to account for both habitat quality and tree life-history. Overall, our findings demonstrate that knowledge of how habitat affects tree life-history stages can improve management to contain or slow tree invasions by improving the spatial match between management effort and efficacy.


Biological invasions Cohort model Spatial spread Tree invasions Weed management scenarios 



PC was supported by the weed impacts in ecosystems research programme from the New Zealand Ministry of Business, Innovation and Employment (MBIE), CH by the Incentive Programme 76912 and the Competitive Programme 81825 of the National Research Foundation (NRF), DP by Core funding for Crown Research Institutes from MBIE’s Science and Innovation Group, and BDM was funded by NSF- WildFIRE PIRE, OISE 09667472.

Supplementary material

10530_2013_608_MOESM1_ESM.doc (28 kb)
Supplementary material 1 (DOC 28 kb)


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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • P. Caplat
    • 1
  • C. Hui
    • 2
  • B. D. Maxwell
    • 3
  • D. A. Peltzer
    • 4
  1. 1.Department of Physical Geography and Ecosystem ScienceUniversity of LundLundSweden
  2. 2.Department of Botany and Zoology, Centre for Invasion BiologyStellenbosch UniversityMatielandSouth Africa
  3. 3.Department of Land Resources and Environmental ScienceMontana State UniversityBozemanUSA
  4. 4.Landcare ResearchLincolnNew Zealand

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