Robert A. Monserud

TL;DR: A model to predict global patterns in vegetation physiognomy was developed from physiological considera- tions influencing the distributions of different functional types of plant in a given environment, and selected the potentially dominant types from among them as discussed by the authors.

TL;DR: The Kappa statistic as mentioned in this paper is presented as an objective tool for comparing global vegetation maps, which can result from either compilations of observed spatial patterns or from simulations from models that are global in scope.

TL;DR: In this paper, a basal area increment model is developed for all the main forest species in Austria: spruce (Picea abies), fir (Abies alba), larch (Larix decidua), Scots pine (Pinus sylvestris), black pine (Pus nigra), stone pine (pinus cembra), beech (Fagus silvatica), oak (Quercus robur, Quercus petraea and Quercius cerris), and for all other broadleaf species combined.

TL;DR: A modified Budyko global vegetation model is used to predict changes in global vegetation patterns resulting from climate change (CO2 doubling). Vegetation patterns are predicted using a model based on a dryness index and potential evaporation determined by solving radiation balance equations as mentioned in this paper.

TL;DR: Combining the genetic index and simple environmental variables accounted for nearly half the variation in site index, and a strong correlation between genotype and environment, reflecting the steep adaptive clines that are well known for this species.