@article{fdi:010054202,
  title = {{M}odeling invasive species spread in complex landscapes : the case of potato moth in {E}cuador},
  author = {{C}respo-{P}erez, {V}. and {R}ebaudo, {F}. and {S}ilvain, {J}ean-{F}ran{\c{c}}ois and {D}angles, {O}livier},
  editor = {},
  language = {{ENG}},
  abstract = {{T}ropical mountains have a long history of human occupation, and although vulnerable to biological invasions, have received minimal attention in the literature. {U}nderstanding invasive pest dynamics in socio-ecological, agricultural landscapes, like the tropical {A}ndes, is a challenging but timely issue for ecologists as it may provide developing countries with new tools to face increasing threats posed by these organisms. {I}n this work, road rehabilitation into a remote valley of the {E}cuadorian {A}ndes constituted a natural experiment to study the spatial propagation of an invasive potato tuber moth into a previously non-infested agricultural landscape. {W}e used a cellular automaton to model moth spatio-temporal dynamics. {I}ntegrating real-world variables in the model allowed us to examine the relative influence of environmental versus social landscape heterogeneity on moth propagation. {W}e focused on two types of anthropogenic activities: (1) the presence and spatial distribution of traditional crop storage structures that modify local microclimate, and (2) long-distance dispersal ({LDD}) of moths by human-induced transportation. {D}ata from participatory monitoring of pest invasion into the valley and from a larger-scale field survey on the {E}cuadorian {A}ndes allowed us to validate our model against actual presence/absence records. {O}ur simulations revealed that high density and a clumped distribution of storage structures had a positive effect on moth invasion by modifying the temperature of the landscape, and that passive, {LDD} enhanced moth invasion. {M}odel validation showed that including human influence produced more precise and realistic simulations. {W}e provide a powerful and widely applicable methodological framework that stresses the crucial importance of integrating the social landscape to develop accurate invasion models of pest dynamics in complex, agricultural systems.},
  keywords = {{B}oosted regression tree ; {C}ellular automata ; {C}rop storage structures ; {G}ravity model ; {I}nvasive species ; {L}ong-distance dispersal ; {M}ountainous ; landscapes ; {T}ecia solanivora ; {T}ropical {A}ndes},
  booktitle = {},
  journal = {{L}andscape {E}cology},
  volume = {26},
  numero = {10},
  pages = {1447--1461},
  ISSN = {0921-2973},
  year = {2011},
  DOI = {10.1007/s10980-011-9649-4},
  URL = {https://www.documentation.ird.fr/hor/fdi:010054202},
}