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<jats:title>Abstract</jats:title><jats:p>The integration of trees within agricultural systems delivers the opportunity to provide multiple benefits over those afforded by agriculture without trees. The use of windbreaks as a form of agroforestry, in water scarce environments, is primarily used to reduce windspeeds in order to decrease evapotranspiration. Quick growing poplar species such as <jats:italic>Populus simonii</jats:italic> ((Carrière) Wesm.) are frequently utilised within windbreak structures, but to date, few allometric equations are available to quantify biomass production and to make inferences about carbon storage potential of this species, and none outside the forest. To fill this knowledge gap, we destructively sampled 17 <jats:italic>P. simonii</jats:italic> growing within a windbreak on a wine estate in the Western Cape Provence, South Africa. Power functions were constructed to explain tree height, whole tree aboveground woody biomass, stem and branch biomass as a function of stem diameter at 1.3 m. Additional functions were developed to predict individual branch length and biomass based on branch stub diameter. The presented models explained each variable with high significance. The models could be used to estimate carbon stock per km of windbreak for the given example. Furthermore, bark percentage predicted by stem sectional diameter was modelled to provide a function that can separate wood and bark fractions as a further outlook for the species’ utilisation.</jats:p>

<jats:title>Abstract</jats:title><jats:p>Forest landscape restoration through agroforestry has been implemented as a Nature-based Solution to deforestation in the Global South with varied outcomes. The Modified Taungya System (MTS) is one of such programmes introduced in Ghana to address socio-economically-induced degradation of forest reserves. For two decades since its establishment, there has not been any examination of  a synthesised findings on the MTS and their implication for the prospects of the programme. Using the PRISMA method to select empirical studies, this article examines the state of reforestation under the MTS by reflecting on the conditions of success and failures of the programme. In doing so, two interrelated arguments are advanced. First, the MTS seems to be successful when farmers are well-educated about the programme and their future benefits in the reserves that they enrich. Second, the MTS has largely failed to achieve its full potentials for forest recovery due to bribery, corruption and nepotism that have bedevilled land demarcation to, and delays in signing benefit sharing agreement with, farmers. There is a need for a thorough sensitisation on the MTS to enhance its transparency. Besides, the MTS needs to be remodified if it would be one of the strategies to contribute to the Bonn Challenge and for a durable climate mitigation.</jats:p>

<jats:title>Abstract</jats:title><jats:p>Allometric equations were developed for estimating aboveground biomass carbon (AGBC) in five tree species grown in a tree-based intercropping system at the University of Guelph Agroforestry Research Station, Guelph, Ontario, Canada. A total of 66 representative trees from five species: red oak (<jats:italic>Quercus rubra</jats:italic>) [n = 12], black walnut (<jats:italic>Juglans nigra</jats:italic>) [n = 16], black locust (<jats:italic>Robinia pseudoacacia</jats:italic>) [n = 10], white ash (<jats:italic>Fraxinus americana</jats:italic>) [n = 15], Norway spruce (<jats:italic>Picea abies</jats:italic>) [n = 13] were selected, harvested and their aboveground biomass and carbon content were quantified. Three commonly used allometric models were used to develop predictive equations. Regression models were developed and parameterized for each tree species and the best are presented based on information criteria (AIC, AICc, and BIC), mean absolute percentage error (MAPE), over/under estimation (MOUE), root mean square error (RMSE), R<jats:sup>2</jats:sup>, and regression coefficients (a, b) of the observed/predicted (OP) linear regression analysis. All equations with diameter at breast height (D) only and D and tree height (H) as the predictor variables fitted the AGBC data well, with R<jats:sup>2</jats:sup> &gt; 97% and RMSE &lt; 40. However, a power model using D as the only predictor is recommended as the best model for black walnut, black locust, white ash, and Norway spruce. The models presented are the best fitted allometric equations for the indicated species and are recommended for these species, growing on similar soils under the same temperate conditions at densities of &lt; 125 tree per hectare.</jats:p>