Quantification of Above-Ground Biomass and Carbon Sequestration Potential of Roadside Trees in the Plateau Department of Benin Republic

Roadside trees are effective natural solutions for mitigating climate change. Despite the usefulness of trees to carbon sequestration, there is a dearth of information on the estimation of biomass and carbon stock for roadside trees in the study area. This study aimed to estimate the carbon stock and carbon dioxide equivalent of roadside trees. A complete enumeration of trees was carried out in Kétou, Pobè and Sakété within the communes of the Plateau Department, Bénin Republic. Total height and diameter at breast height were measured from trees along the roads while individual wood density value was obtained from wood density database. The allometric method of biomass estimation was adopted for the research. The results showed that the total estimations for above-ground biomass, carbon stock and carbon equivalent from all the enumerated roadside trees were 154.53 mt, 72.63 mt and 266.55 mt, respectively. The results imply that the roadside trees contain a substantial amount of carbon stock that can contribute to climate change mitigation through carbon sequestration.

Resilience-Driven Road Network Retrofit Optimization Subject to Tropical Cyclones Induced Roadside Tree Blowdown

This article focuses on decision making for retrofit investment of road networks in order to alleviate severe consequences of roadside tree blowdown during tropical cyclones.The consequences include both the physical damage associated with roadside trees and the functional degradation associated with road networks.A trilevel,two-stage,and multiobjective stochastic mathematical model was developed to dispatch limited resources to retrofit the roadside trees of a road network.In the model,a new metric was designed to evaluate the performance of a road network;resilience was considered from robustness and recovery efficiency of a road network.The proposed model is at least a nondeterministic polynomialtime hardness(NP-hard)problem,which is unlikely to be solved by a polynomial time algorithm.Pareto-optimal solutions for this problem can be obtained by a proposed trilevel algorithm.The random forest method was employed to transform the trilevel algorithm into a singlelevel algorithm in order to decrease the computation burden.Roadside tree retrofit of a provincial highway network on Hainan Island,China was selected as a case area because it suffers severely from tropical cyclones every year,where there is an urgency to upgrade roadside trees against tropical cyclones.We found that roadside tree retrofit investment significantly alleviates the expected economic losses of roadside tree blowdown,at the same time that it promotes robustness and expected recovery efficiency of the road network.

Structure and species composition of tree stands on verges and slopes along a major highway in Hong Kong

Arboricultural research focusing on transport land use was lacking in Hong Kong.Some highway slopes were registered in the Systematic Identification of Maintenance Responsibility of Slopes in the Territory(SIMAR),abbreviated as SIMAR slopes.We aimed to analyze patterns in the structure and species composition of the tree stock along a highway in Hong Kong and examined how a slope registration system could help explain the characteristics of urban forests.The 53 slopes and 52 verges along San Tin Highway,Hong Kong were randomly selected.The trees on each slope and verge were collectively sampled as a tree stand.Six variables,namely tree abundance,species richness,maximum tree height,Shannon-Wiener diversity,Simpson's dominance,and Pielou's evenness were measured for each stand.In addition,a limited visual tree risk assessment was performed.The 7,209 trees in 23 species were recorded.Species richness was low,ranging from one to eight species per stand.SIMAR and non-SIMAR slopes were compared.SIMAR slopes had significantly higher species richness,diversity,evenness but lower dominance,with mean difference of 1.41 species,0.17,0.17 and-0.28respectively.SIMAR slopes were associated with lower tree risk rating.When training regression models,boosting as an ensemble method arbitrarily raised the explanatory power and the predictive accuracy of some models.Slope height,length,angle and area could be significant predictors of the biodiversity-related variables.Future research can sample more habitat characteristics related to the structure and species composition of slopes and verges which were important components of urban forestry.