Table 1. Modeling approaches associated with research themes. (See Fig. 2 for relationships between research themes and Appendix X for details of modeling approaches.)


Research theme Modeling approach References
Deforestation Statistical modeling (e.g., logistic regression) Echeverría et al. (2007a,b), Wilson et al. (2005), Cayuela et al. (2006a,c)
Forest fragmentation Statistical modeling (e.g., logistic regression) Echeverría et al. (2007a,b), Cayuela et al. (2006b,d)
Edge effects Statistical analysis, conceptual modeling López-Barrera et al. (2005, 2006, 2007a,b), Guzmán-Guzmán and Williams-Linera (2006).
Forest degradation Statistical modeling (regression) Newton et al. (2007), Echeverría et al. (2007a,b), Cayuela et al. (2006b,d)
Species diversity Statistical modeling, SPARs Echeverría et al. (2007a,b), Rey Benayas et al. (2007), Cayuela et al. (2006b,d)
Genetic diversity Statistical analysis and modeling Premoli et al. (2007)
Landscape dynamics (including land-use change and climate change impacts) LANDIS II, GEOMOD, DOMAIN, MaxEnt Echeverría et al. (2008), Newton (2008a)
Stand dynamics FORMIND, PINQUE, Markov model Golicher and Newton (2007), Rüger (2006), Rüger et al. (2007a,b), Zavala et al. (2007)
Forest restoration Statistical analysis, spatial MCA, LANDIS II, FORMIND, PINQUE Gonzalez-Espinosa et al. (2007), Golicher and Newton (2007), Rüger et al. (2007a,b), Newton (2008a)
Sustainable use PVA, FORMIND, PINQUE Bekessy et al. (2004), Golicher and Newton (2007), Rüger et al. (2007a, 2008), Newton (2008b)
Decision-support tools, management recommendations, policy options Scenarios, BBN, spatial MCA, outputs from other modeling activities Miles et al. (2007), Newton (2008a, 2009)