Dear friends,
I would like to exchange some ideas about the issue I am dealing with
currently.
I would like to cluster data on forest structure (basal area, height,
diameter, species composition, richness and evenness) according with forest
successional/conservation status. This aims at testing hypothesis on tree
population size structure, in the end. Data consists in nearly one hundred
areas each one 0,1-ha in size, sampled throughout hundreds of kilometers in
Southern South America, covering two types of subtropical forest: semideciduous
forests and mixed conifer-hardwood forests.
The real problem is that, if I disregard species composition, I can end
with a group of well-conserved or developed forests that have a species
composition still very distinctive from mature forests, according with current
successional theory (this states that the strucutre of a community recovers
much faster than its species composition). However, since there are no forest
tracks in untouched state to compare with, I think I am in a circle.
Furthermore, I think multivariate analysis available in common softwares
do not allow for the inclusion of compositional information along with
structural information in a single analysis. And at least, maybe all this is
senseless in the absence of sound biogeographical theory that could make
quantitative predictions against which to test the community parameters of the
data!
What do you think?
Thanks in advance for sharing your points of view.
Best whishes,
Alexandre
Dr. Alexandre F. Souza
Programa de Pós-Graduação em Biologia: Diversidade e Manejo da Vida Silvestre
Universidade do Vale do Rio dos Sinos
Av. UNISINOS 950 - C.P. 275
São Leopoldo 93022-000
RS - Brasil
Telefone: (051)3590-8477 ramal 1263
Skype: alexfadigas
[EMAIL PROTECTED]
http://www.unisinos.br/laboratorios/lecopop
