Analysis measures above-ground biomass and production across mangrove age zones, highlighting relationships with tidal position and sea-level rise implications.
Above‐ground biomass contributes a large proportion of mangrove carbon stock; however, spatio‐temporal dynamics of biomass are poorly understood in carbonate settings of the Southern Hemisphere. This influences the capacity to accurately project the effects of accelerating sea‐level rise on this important carbon store. Here, above‐ground biomass and productivity dynamics were quantified across mangrove age zones dominated by Rhizophora stylosa , spanning a tidal gradient atop a reef platform at Low Isles, Great Barrier Reef, Australia. Above‐ground biomass was extrapolated across the forest using field plot data, allometry, a canopy height model derived from remotely piloted aircraft (RPA) LiDAR, and regression analyses. Above‐ground biomass production was calculated as mean annual biomass increments, and canopy production was determined using RPA‐derived multispectral imagery and a Normalized Difference Vegetation Index. Mangrove above‐ground biomass was estimated at 519.7 ± 3.11 t ha −1 and increased with age up to the oldest forest (812.0 ± 12.9 t ha −1 ), believed to be ~135 ± 40 years old. Above‐ground biomass was explained by age and tidal position ( r 2 > 0.8), with a positive association between the two predictor variables. Above‐ground biomass production peaked at the lowest intertidal position in the youngest forest aged < 11 years at 36.3 t ha −1 yr. −1 , steadying thereafter, with a mean of 12.5 ± 5.4 t ha −1 yr. −1 across the island. Production in the canopy remained high until the oldest forest and was negatively associated with age and tidal position ( r 2 > 0.9). Declining production in the older zones corresponded to forest aging, tidal positions becoming suboptimal for growth, and increased exposure to prevailing winds and cyclones. By developing relationships between above‐ground biomass accumulation and age and tidal position, this study informs parameterization of models of the response of biomass to sea‐level rise but requires additional information about relationships between substrate evolution, forest development, and age.
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Conroy et al. (2025) studied this question.
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