ISSN:
1572-9761
Keywords:
Markov chain
;
cellular automata
;
Lymantria dispar
;
Lepidoptera: Lymantriidae
Source:
Springer Online Journal Archives 1860-2000
Topics:
Biology
Notes:
Abstract A series of cellular transition probability models that predict the spatial dynamics of gypsy moth (Lymantria dispar L.) defoliation were developed. The models consisted of four classes: Simple Markov chains, Rook's and Queen's move neighborhood models, and distance weighted neighborhood models. Historical maps of gypsy moth defoliation across Massachusetts from 1961 to 1991 were digitized into a binary raster matrix and used to estimate transition probabilities. Results indicated that the distance weighted neighborhood model performed better then the other neighborhood models and the simple Markov chain. Incorporation of interpolated counts of overwintering egg mass counts taken throughout the state and incorporation of historical defoliation frequencies increased the performance of the transition models.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF00133030
