Global data compilation across climate gradients supports the use of
common allometric equations for mangrove species Avicennia germinans,
Laguncularia racemosa, and Rhizophora mangle
Abstract
1. Predicting the distribution, structure and biomass of mangrove
forests is an area of high research interest. Across the Atlantic East
Pacific biogeographic region, three species are common and abundant
members of local mangrove communities; Rhizophora mangle, Avicennia
germinans and Laguncularia racemosa. 2. Biomass prediction for these
species has relied on two approaches: site-specific allometries based on
the idea that environmental/climatic differences between sites drive
growth differences, or the use of common allometric equations based on
the idea that site driven differences are minimal. Meta-analyses of
global compilations of interspecific plot level data (e.g. mean canopy
height, stand basal area) show trends in size and structure with
climatic variables, however this has not been critically evaluated
across these species using empirical allometric growth functions. 3. We
compared allometric equations derived from 590 individuals within and
across nine broadly distributed sites at interspecific and intraspecific
levels and explored the influence of climatic variables on allometric
slopes and intercepts. 4. Assessing variables that can be used to
predict biomass in the field (height, DBH, canopy spread), we find
interspecific root mean squared errors similar to or smaller than
intraspecific or site-specific equations for tree height. We also find
significant effects of several climatic variables on growth allometries
with the strongest effects from minimum temperature followed by
precipitation seasonality. 5. Our results suggest that while climate has
a clear influence on mangrove allometric growth, common equations,
particularly using interspecific height to predict biomass, may have
utility in biomass prediction. Future methodological improvements
combined with data from a broader range of growth conditions will
further inform which allometric relationships exhibit the most
variability within and across sites and which variables best predict
mangrove biomass.