Can leaf area index and biomass be estimated from Braun‐Blanquet cover scores in tropical forests?
2015
Döbert, Timm F. | Webber, Bruce L. | Sugau, John B. | Dickinson, Katharine J.M. | Didham, R. K. (Raphael K.) | Foster, Bryan
QUESTIONS: The loss and degradation of tropical forests is having severe impacts on the dynamics of understorey plant communities. Understanding these impacts requires efficient ways to measure vegetation change over broad spatial and temporal scales. Leaf area index (LAI) and above‐ground biomass are preferred quantitative measures of variation in plant community structure. However, their accurate measurement requires destructive sampling, which can be impractical or inappropriate. Here we test whether semi‐quantitative assessment of Braun‐Blanquet vegetation cover scores is a reliable proxy for direct quantitative measures of LAI and above‐ground biomass of differing plant growth forms (PGF) within tropical forests. LOCATION: Six hundred square kilometre area of tropical lowland rain forest in Sabah, Malaysia. METHODS: We sampled understorey rain forest plant communities across a disturbance gradient in 2 × 2 m plots at 301 locations. We used a modified Braun‐Blanquet scale to estimate plant cover, destructively harvested all live above‐ground biomass up to a height of 2 m, calculated the above‐ground biomass of each species from separately processed stem and leaf fractions in each plot, and then calculated LAI using reference measures of specific leaf area for each species. For each of nine PGFs, we regressed LAI and biomass against the nine‐point Braun‐Blanquet ordinal transform scale (OTS) using linear mixed effects models. RESULTS: We found a simple, uniform logarithmic scaling of LAI with increasing Braun‐Blanquet cover classes that was consistent across most PGFs, and with slope estimates close to 1.0. By contrast, no simple scaling relationship was found for above‐ground biomass, with most PGFs exhibiting an asymptotic relationship in which the Braun‐Blanquet estimates across high cover scores provided almost no resolution of observed variation in empirical biomass measures. CONCLUSIONS: We found that the Braun‐Blanquet OTS provides a remarkably simple and accurate logarithmic scaling of LAI, but care should be taken in applying scaling rules uniformly across PGFs. In contrast, the Braun‐Blanquet OTS shows a more complex relationship with plant above‐ground biomass and we caution against its unconditional use for biomass estimation. The findings of this study should be broadly applicable to other ecosystems due to the heterogeneity of plant communities included in this work.
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