Appendix B. A figure showing the relationships between change in Dryas octopetala cover and change in community diversity parameters from 2000 to 2003 in climate change simulation plots in alpine Norway.

A figure showing the relationships between change in Dryas octopetala cover and change in community diversity parameters from 2000 to 2003 in climate change simulation plots in alpine Norway

Appendix C. A table of simple linear regressions between change in Dryas octopetala cover and changes in community diversity parameters in climate change simulation plots from 2000 to 2003 in alpine Norway.

A table of simple linear regressions between change in Dryas octopetala cover and changes in community diversity parameters in climate change simulation plots from 2000 to 2003 in alpine Norway

Appendix A. A table of community parameter values before (2000) and after (2003) climate change simulations in alpine Norway.

A table of community parameter values before (2000) and after (2003) climate change simulations in alpine Norway

Eldegard et al env data

Eldegard et al environmental data raw site plo

Eldegard et al community data

Eldegard et al community matrix vascular plant data to GNMDS raw&weighe

Comparison of stand structural and environmental variables (mean ± SE) measured in moist forest and miombo woodland of Hanang district in Tanzania.

<p>* Corresponding Wilcoxon Mann-Whitney test showing the differences in median of the measured parameters between moist forest (N = 60) and miombo woodland (N = 40).</p><p>Comparison of stand structural and environmental variables (mean ± SE) measured in moist forest and miombo woodland of Hanang district in Tanzania.</p

Relationships between leaf area index (LAI), stand structural and environmental variables in moist forest and miombo woodland of Hanang district in Tanzania.

<p>(A) LAI shows a non-linear relationship with predominant height, (B) linear relationship with tree species richness, (C) soil nitrogen, (D) soil pH under high disturbance levels, (E) stem density and (F) tree species evenness when all other variables are set to their mean values (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0142784#pone.0142784.s004" target="_blank">S2 Table</a>, combined models). Solid lines plot fitted partial regressions from generalized linear models, with standard errors of the mean in dotted lines.</p

Relationships between leaf area index (LAI) and, stand structural and environmental variables in miombo woodland of Hanang district in Tanzania.

<p>(A) LAI shows linear relationships with tree species richness at high soil phosphorous, (B) with tree species richness at high soil potassium, (C) with tree species richness at high soil pH, and (D) with predominant height at low and high soil potassium, when all other variables are set to their mean values (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0142784#pone.0142784.s004" target="_blank">S2 Table</a>, combined model). The solid lines are the fitted partial regression lines from generalized linear models of the relationships between LAI and labeled variables (Low and High levels of P = phosphorous, K = potassium and pH, respectively), with standard errors of the mean in dotted lines.</p

Relationships between aboveground herbaceous biomass (AGB_H), stand structural and environmental variables in moist forest and miombo woodland of Hanang district in Tanzania.

<p>(A) AGB_H show a non-linear relationship with leaf area index, (B) linear relationship with tree species richness, (C) a non-linear relationship with LAI at high elevation in moist forest, and (D) linear relationship with LAI in miombo woodland at high levels of disturbance, when all other variables are set to their mean values (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0142784#pone.0142784.s005" target="_blank">S3 Table</a>, combined models). The solid lines are the fitted partial regression lines from generalized linear models of the relationships between AGB_H and labeled variables (Low-Elv, High-Elv, and Low-Stump and High-Stump are low and high levels of elevation and disturbance gradients, respectively), with standard errors of the mean in dotted lines.</p

Comparison of alternative models for predicting LAI in moist forest and miombo woodland of Hanang District in Tanzania.

<p>Predictor sets include: structural variables only; environmental variables only; structural and environmental variables combined (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0142784#pone.0142784.t001" target="_blank">Table 1</a>). Results are for models reduced by stepwise selection (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0142784#pone.0142784.s003" target="_blank">S1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0142784#pone.0142784.s004" target="_blank">S2</a> Tables for details on global models and covariate estimates, respectively). Statistics: D², percent deviance explained; ΔAIC, change in Akaike Information Criterion compared with null model; LRT, likelihood ratio test comparing final models with their respective global models at P ≤ 0.05; MSEP, mean square error of prediction; W, Wilcoxon Mann-Whitney statistic used to estimate prediction bias.</p><p>Comparison of alternative models for predicting LAI in moist forest and miombo woodland of Hanang District in Tanzania.</p