Carbon Stocks and Sequestration Potentials in Managed Mangrove Plantations of Gazi Bay, Kenya

Abstract

Mangroves forests are important ecosystems found along the coastlines throughout the tropical coast. They provide goods and services that are of ecological, environmental and cultural importance to society. Mangroves store exceptionally large quantities of carbon stocks. This carbon is bound to be emitted when mangroves are degraded. The objective of this study was to quantify total ecosystem carbon stocks for mangroves forest at Gazi Bay, Kenya. Three categories were selected for this study; 13 year old El Niño plantation, 19 year old Kinondo plantation and a Natural stand of R. mucronata. Plots of 10×10 m2 were selected in each study site. Four carbon pools were investigated; above and belowground vegetation carbon, dead wood and soil carbon. Additionally, Nitrates, Ammonium and Phosphates from the soil were also measured. Twenty five trees were harvested and used to develop biomass and volume equations of the form y = ax2 + bx +c, and Y = aXb respectively for the 19 year old Kinondo plantation. Biomass for carbon determination in Natural and El Niño stands was estimated using a general equation. Mean total C stocks in El Niño and Kinondo plantations was 914.5±237.3 and 812.6±186.5 Mg C ha-1 respectively, while the Natural stand contained significantly lower mean total C stocks of 692.9±142.9 Mg C/ha. (ANOVA, F; 2, 6 = 28.91, P < 0.05). Ammonium was the most abundant nutrient in the three sites. Belowground biomass was generally found to correlate negatively with the soil nutrients. This study show reforestation influences structural development of replanted mangroves and that replanted mangrove are significant carbon stores. Soil organic matter was signicantly high in plantations than in the Natural stand (F; 2, 92 = 8.89, P < 0.05). Proper monitoring is essential for continued verification of stored carbon stocks and improvement of data quality. Development of local allometric equations for all mangrove species can be useful estimating aboveground biomass carbon.