Current issue: 56(1)
Under compilation: 56(2)
Currently, tools to predict the aboveground and belowground biomass (AGB and BGB) of woody species in Guinean savannas (and the data to calibrate them) are still lacking. Multispecies allometric equations calibrated from direct measurements can provide accurate estimates of plant biomass in local ecosystems and can be used to extrapolate local estimates of carbon stocks to the biome scale. We developed multispecies models to estimate AGB and BGB of trees and multi-stemmed shrubs in a Guinean savanna of Côte d’Ivoire. The five dominant species of the area were included in the study. We sampled a total of 100 trees and 90 shrubs destructively by harvesting their biometric data (basal stem diameter Db, total stem height H, stump area SS, as well as total number of stems n for shrubs), and then measured their dry AGB and BGB. We fitted log-log linear models to predict AGB and BGB from the biometric measurements. The most relevant model for predicting AGB in trees was fitted as follows: AGB = 0.0471 (ρDb2H)0.915 (with AGB in kg and ρDb2H in g cm–1 m). This model had a bias of 19%, while a reference model for comparison (fitted from tree measurements in a similar savanna ecosystem, Ifo et al. 2018) overestimated the AGB of trees of our test savannas by 132%. The BGB of trees was also better predicted from ρDb2H as follows: BGB = 0.0125 (ρDb2H)0.6899 (BGB in kg and ρDb2H in g cm–1 m), with 6% bias, while the reference model had about 3% bias. In shrubs, AGB and BGB were better predicted from ρDb2H together with the total number of stems (n). The best fitted allometric equation for predicting AGB in shrubs was as follows: AGB = 0.0191 (ρDb2H)0.6227 n0.9271. This model had about 1.5% bias, while the reference model overestimated the AGB of shrubs of Lamto savannas by about 79%. The equation for predicting BGB of shrubs is: BGB = 0.0228 (ρDb2H)0.7205 n0.992 that overestimated the BGB of the shrubs of Lamto savannas with about 3% bias, while the reference model underestimated the BGB by about 14%. The reference model misses an important feature of fire-prone savannas, namely the strong imbalance of the BGB/AGB ratio between trees and multi-stemmed shrubs, which our models predict. The allometric equations we developed here are therefore relevant for C stocks inventories in trees and shrubs communities of Guinean savannas.
The article considers the relation of shifting cultivation to deforestation and degradation, and hence its impacts in terms of carbon emissions and sequestration potential. There is a need to understand these relationships better in the context of international policy on Reduced Emissions from Deforestation and Forest Degradation (REDD+). The article reviews the way in which shifting cultivation has been incorporated in global and national estimations of carbon emissions, and assembles the available information on shifting cultivation in Tropical Dry Forests (TDF) in Mexico, where it is widely practiced. It then takes the case of two villages, Tonaya and El Temazcal, which lie within the basin of the River Ayuquila in Jalisco, Mexico. Field data for the typical carbon stocks and fluxes associated with shifting cultivation are compared with stocks and fluxes associated with more intensive agricultural production in the same dry tropical forest area to highlight the carbon sequestration dynamics associated with the shortening and potential lengthening of the fallow cycles. The biomass density in the shifting cultivation system observed can reach levels similar to that of old growth forests, with old fallows (>20 years) having higher carbon stocks than old growth forests. Per Mg of maize produced, the biomass-related emissions from shifting cultivation in the traditional 12 year cycle are about three times those from permanent cultivation. We did not, however, take into account the additional emissions from inputs that result from the use of fertilizers and pesticides in the case of permanent agriculture. Shortening of the fallow cycle, which is occurring in the study area as a result of government subsidies, results in higher remaining stocks of carbon and lower emissions at the landscape level.