Deciphering global patterns of forest canopy rainfall interception (FCRI): A synthesis of geographical, forest species, and methodological influences.

Forest canopy rainfall interception (FRCI) is an essential hydrological process that governs water and biogeochemical cycles in forest ecosystems. Identifying patterns and relationships of FCRI using a systematic review is key to improving our knowledge supporting new experiment research, modeling, and application. In this meta-analysis, we aimed to delineate the canopy interception (CI), throughfall (TF), and stemflow (SF) concerning geographical and forest variables and experimental methodologies. We leveraged peer-reviewed 170 articles across 234 sites globally, extracting TF, CI, SF, geographical, forest, and experimental aspects. We applied multivariate statistical procedures to discern the principal influences on TF, CI, and SF and examined their multicollinearity. In addition, we developed Generalized Linear Models (GLM) for CI and TF. Global TF experiments indicate that the predominant rainfall devices, number of sample trees, number of events, and monitoring length are 10-20 devices (81% fixed), 3-6 trees, 30-50 events, and 10-30 months. Predominant global values of TF, CI, and SF are 70-80% (median = 73%), 20%-30% (median = 23.9%), and <1.0% (median = 1.87%), respectively. Global models of CI and TF were responsive to T, LAI, and D (respectively, R2adj of 0.196** and 0.206**). Temperate forests mirrored the global model (R2adj of 0.274** and 0.31**, respectively). The Subtropical CI model was fitted based on P and DBH (R2adj = 0.245*), and the TF model was based on E, D, and LAI (R2adj = 0.532**); the Mediterranean CI model was based on T, Basal, and LAI (R2adj = 0.45*), while TF was based on P, Basal, and LAI (R2adj = 0.671**). The Tropical CI model was based on T and H (R2adj = 0.396*), and the TF model, LAI, and P (R2adj = 0.35*). This meta-analysis underscores the importance of comprehending the hydrological processes in forested areas as they are pivotal in mitigating climate change impacts.

The inverted forest: Aboveground and notably large belowground carbon stocks and their drivers in Brazilian savannas.

Savannas contribute to ca. 30 % of the total terrestrial net primary productivity and are responsible for significant carbon storage. Savannas in South America are mostly found within the Cerrado Domain, which is very threatened and presents remarkable carbon pools. Herein, we used a unique dataset of 21 Cerrado sites spanning 144 permanent field plots in Southeastern Brazil to assess the general patterns of above and belowground carbon stocks. We identified the main environmental and tree diversity drivers of aboveground wood carbon and productivity, belowground carbon stocks (roots and soil), carbon ratios (root:shoot and above:below) and total carbon stocks in the Cerrado through a combination of climatic estimates, fire frequency data, field measurements of vegetation, roots, soil carbon, nutrients and texture, and assessment of different components of diversity (species, functional and phylogenetic). Our findings reveal average aboveground, root, and soil carbon stocks of 20.4, 14.24, and 123.13 Mg.ha-1, respectively. Average Root:Shoot and Above:Below confirm the "inverted forest" concept with values of 1.58 and 0.21, respectively. Total carbon was 145.62 Mg.ha-1, reinforcing the great amount of carbon storage in the Cerrado and its role in the carbon cycle and dynamics. Tree diversity variables (mainly species diversity and functional composition variables) had more significant effects over aboveground variables, whereas environmental variables had more significant effects over belowground variables. Ratios and total carbon mixed up these effects. The impressive values of carbon storage, especially belowground, point out the need to better manage and protect the Cerrado. Moreover, our findings might be particularly relevant for discussions on restoration programs focused on the trees-for­carbon idea that do not consider species diversity and belowground carbon stocks.

Spatial distribution of wood volume in Brazilian savannas.

Here we model and describe the wood volume of Cerrado Sensu Stricto, a highly heterogeneous vegetation type in the Savanna biome, in the state of Minas Gerais, Brazil, integrating forest inventory data with spatial-environmental variables, multivariate regression, and regression kriging. Our study contributes to a better understanding of the factors that affect the spatial distribution of the wood volume of this vegetation type as well as allowing better representation of the spatial heterogeneity of this biome. Wood volume estimates were obtained through regression models using different environmental variables as independent variables. Using the best fitted model, spatial analysis of the residuals was carried out by selecting a semivariogram model for generating an ordinary kriging map, which in turn was used with the fitted regression model in the regression kriging technique. Seasonality of both temperature and precipitation, along with the density of deforestation, explained the variations of wood volume throughout Minas Gerais. The spatial distribution of predicted wood volume of Cerrado Sensu Stricto in Minas Gerais revealed the high variability of this variable (15.32 to 98.38 m3 ha-1) and the decreasing gradient in the southeast-northwest direction.