Assessment of pristine vegetation structure in semiarid shrublands based on spatial explicit modeling

BISIGATO, A.J.; ARES, J.O.; BERTILLER, M.B

PHYTOCOENOLOGIA

GEBRUDER BORNTRAEGER

Año: 2002 vol. 32 p. 581 - 594

0340-269X

In the Argentinean southern Monte, the vegetation has been extensively altered and fragmented as a consequence of the introduction of sheep grazing during the last century. Activities leading to restoration of land condition and conservation of the shrubland ecosystems would be facilitated if relict areas that had not been impacted by sheep were available for reference. Such areas have not been maintained but there are some others that remained exclosed from sheep during the last 1- 3 decades where qualitative trends of restoration are already observable. We hypothesised that information on the vegetation structure from these areas and analytical modeling of plant growth and competition-facilitation processes would allow reconstructing the basic characteristics of the pristine vegetation. This would serve as benchmark for restoration activities. We selected short-term exclosure plots (5- 25 years) and measured structural vegetation parameters related to the shrub-grass partition of aboveground biomass and the spatial distribution of plants. We also conducted observations on seedling establishment, growth and lateral diffusion of shrubs and grasses in newly denuded plots. We built a spatial explicit simulation model of establishment, growth and lateral diffusion of the main plant components with parameters derived from our experimental plots. We validated the model with observations in non-grazed areas (not used to derive model parameters) and extrapolated the model behaviour until a stable distribution of shrubs and grasses was attained. The stationary state produced by the model shows most of the characteristics observable during vegetation restoration in exclosures, and provides an estimate of main vegetation traits in the Monte under pre-domestic-herbivore conditions which incorporates most of the quantitative knowledge available.