Propagating uncertainty to estimates of above-ground biomass for Kenyan mangroves
A scaling procedure from tree to landscape level
Abstract
Mangroves are globally important carbon stores and as such have potential for inclusion in future forest-based climate change mitigation strategies such as Reduced Emissions from Deforestation and Degradation (REDD+). Participation in REDD+ will require developing countries to produce robust estimates of forest above-ground biomass (AGB) accompanied by an appropriate measure of uncertainty. Final estimates of AGB should account for known sources of uncertainty (measurement and predictive) particularly when estimating AGB at large spatial scales. In this study, mixed-effects models were used to account for variability in the allometric relationship of Kenyan mangroves due to species and site effects.
This research was supported by the Ecosystem Services for Poverty Alleviation (ESPA) programme
Citation
Cohen, R., Kaino, J., Okello, J.A., Bosire, J.O., Kairo, J.G., Huxham, M., Mencuccini, M., Propagating uncertainty to estimates of above-ground biomass for Kenyan mangroves: A scaling procedure from tree to landscape level, Forest Ecology and Management, vol.310, pp.968-982, Elsevier, 2013