[Company Logo Image] 

2

Up Home Feedback Links Search

 

 

 

 

SPATIO-TEMPORAL PREDICTIVE MODELS OF MEDITERRANEAN VEGETATION DYNAMICS

Yohay Carmel(1), Ronen Kadmon(1), and Ronit Nirel(2)

(1)Department of Evolution, Systematics and Ecology
(2)Department of Statistics
The Hebrew University of Jerusalem
Jerusalem 91904, Israel

November 1998

ABSTRACT

Empirical modeling of vegetation dynamics can be used for predictive purposes. The goal of the present study is to construct and evaluate possible
approaches for empirical modeling of vegetation dynamics, and investigate
their potential use in planning and management. Specifically we studied three major issues: 1. Finding an optimal spatial resolution for a vegetation change database, that would maximize both positional accuracy and resolution; 2. Assessing the performance of logistic vs.
linear models, and the performance of stochastic vs. deterministic realizations of a logistic model; and 3. Evaluating two different approaches to cope with spatial autocorrelation, namely the use of a small sample of the database and the introduction of autocovariates.
An empirical model of Mediterranean vegetation dynamics was constructed using a case study of vegetation change in an area in the Galilee mountains, northern Israel, over 28 years. Present vegetation in any location was modeled as a function of past vegetation and environmental factors (e.g. topography, and various disturbances); future vegetation pattern was then modeled as a function of current vegetation and effects of environmental factors. In order to assess
model performance, the actual vegetation map was compared with maps
representing model realizations, for the study area and for an external validation area. Three types of measures were used to compare the predicted and actual vegetation maps: overall vegetation composition, pattern indices and cell-by-cell match.
Our results indicate that landscape-scale vegetation dynamics can be fairly well modeled, using few biologically important variables. The logistic and linear models had similar performance, in spite of the reduced information on which the logistic models were based. The use of only a 4% sample of the database resulted in a negligible reduction in model performance. Model performance was reduced - but was still fair - when applied to an external area.

KEYWORDS:
Vegetation Dynamics, Predictive modeling, Empirical models, GIS,
Mediterranean vegetation, Aerial photographs, Succession,
Polychotomous logistic model, Autocovariate.


CORRESPONDENCE:
Yohay Carmel
Department of Forest Sciences
Colorado State University
Fort Collins, CO 80523
Phone: (970) 491-3650
Fax: (970) 491-6754

E-mail: yohay@techunix.technion.ac.il

[ To Publications ]

 

Send mail to msnardi@mscc.huji.ac.il with questions or comments about this web site.
Last modified: 28/02/01