Sources of error in the estimation of aboveground biomass carbon stocks in mangrove ecosystems
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- Mangroves, Carbon, Blue carbon, Allometry
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Abstract
Mangrove forests are a type of wetland ecosystem found along subtropical and tropical coasts around the world. True mangrove species are specially adapted to the environments they grow in with a range of features such as salt glands for salt-excretion and aerial roots for respiration in the tidal systems. Whilst it has been known for many years that mangroves serve vital functions as nurseries for commercially important fish as well as providing protection from extreme weather events, in more recent decades focus has turned to the amount of carbon stored in these habitats, particularly as solid aboveground biomass (AGB). However, mangroves are difficult to work in and generalised allometric equations for AGB and carbon content values for aboveground biomass carbon (AGBC) have been developed to help produce estimates. But the accuracy of the estimates produced using generalised values when compared to site and species-specific data has been questioned, particularly where the values have been developed in different parts of the world. In chapter 1, a systematic evidence map was designed to assess whether there was geographical bias in the current literature on mangrove carbon and if helicopter research potentially influenced the locations of studies. It was found that only 51.6% of countries that contain mangrove ecosystems were represented in the map, however, 5 countries represented 53.6% of the total study locations showing that the current mangrove carbon research is skewed towards certain locations with African and Island countries noticeably less represented. But the map also showed that the current research has mostly been conducted by researchers based at institutions in the country they studied, suggested that helicopter research does not heavily influence the field. Chapter 2 reviewed the current literature about calculation of AGBC estimates using 13 generalised values found in the literature compared to site-specific data from 6 papers. It was found that the use of generalised values with site-specific AGB data created significant differences in the estimates of AGBC produced using site-specific carbon values, with the largest value of underestimation at 20.20% of the original AGBC estimate and the largest value of overestimation at 16.76%. In chapter 3, three generalised common equations for calculating mangrove AGB were tested against equations designed for use on 3 species in Florida where diameter at breast height (dbh) and tree height were measured at the Vester Field Station in South-West Florida. Tree height was measured using 2 different methods, a telescopic pole and a clinometer, to test for significant differences in height values produced. The use of the common equations for estimating AGB produced 2 significantly different estimates, although the last equation did not, potentially due to roughly equal distribution of individual tree AGB estimations. The site-specific AGB values were the smallest overall which suggests that the use of generalised equations results in overestimation of mangrove AGB. It was also found that the tree height measurements made using the clinometer were significantly different than those taken with the telescopic pole. Chapter 4 used the site-specific AGB measurements from Florida combined with site-specific carbon content data, also collected from the Vester Field Station, to test the use of generalised carbon content values in situ, where it was found that all of the generalised carbon content values, apart from 49% (closest to the site-specific carbon value), produced significantly different estimates for AGBC. In Summary, the use of generalised AGB equations and carbon content values has been shown to produce significantly different AGBC estimates. This requires more testing, particularly in currently understudied regions, to assess whether there should be continued use of these equations and values in the production of AGBC estimates.
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Original language | English |
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Award date | 27 Oct 2023 |