Forest diversity plays a key role in determining the stand carbon stocks of Mexican forests

Defining the most important factors related with forest carbon (C) stocks in different forest types is still a controversial topic. In this study we used data from 10,500 plots from The National Forest Inventory of Mexico encompassing the six main forest types in Mexico (conifer, broadleaf, mixed, evergreen and semi-deciduous, dry and semiarid forests) in order to identify the main factors related to the spatial pattern of C stocks, including climate (temperature and rainfall), forest diversity (structural and species richness), topographic and soil characteristics (soil depth, slope and land tenure) and disturbance factors (fires, pests and tree felling). We built two different types of models, one taking all plots into account (global model, R2 = 0.54, P < 0.001) and others for each forest type separately. Overall, structural richness was the most important variable related to C stock both in the global model and in each forest type model. Tree richness had a strong relationship in tropical forests (both dry and evergreen) but not in temperate forests (conifer, broadleaf and mixed forests), where slope and climate variables had greater effects on C stocks. C stock was strongly and positively correlated with precipitation in almost all forest types, while it was strongly and negatively correlated with temperature in broadleaf and mixed forests. Surprisingly, slope was the second most important factor positively correlated with C stock in broadleaf and mixed forests. Surprisingly, soil depth, land tenure and disturbance variables had a negligible effect in almost all models, partially due to the poor quality of disturbance and soil depth data available from INFyS. The results suggest that, in order to enhance C stock in Mexican forests, management techniques should encourage increases of the number of tree species and, especially, tree size inequality, since both these factors were shown to have a key role in C stock.

---

• View from publisher

---

DOI:

https://doi.org/10.1016/j.foreco.2018.02.023

---

Altmetric score:

Dimensions Citation Count: