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Plot-based monitoring has yielded much information on the taxonomic diversity and carbon (C) storage in tropical lowland forests of the Amazon basin. This has resulted in an improved understanding of the relationship between lowland forest biomass dynamics and global change drivers, such as climate change and atmospheric CO2 concentration. Much less attention has been paid to the mountain ecosystems of South America that comprise montane forests and alpine vegetation (páramo, puna, high Andean grasslands, wetlands, and alpine heath). This vegetation complex provides a variety of ecosystem services and forms a natural laboratory along various physiographic, geological and evolutionary history/biogeography, and land use history gradients. Here, we review existing empirical understanding and model-based approaches to quantify the contribution of mountain ecosystems to ecosystem service provision in the rapidly changing socioecological setting of the South American mountains. The objective of this paper is to outline a broad road map for the implementation of mountain vegetation into dynamic global vegetation models (DGVM) for use in Earth System Models (ESM), based on our current understanding of their structure and function and of their responsiveness to global change drivers. We also identify treeline processes, critical in mountain ecosystems, as key missing elements in DGVMs/ESMs, and thus explore in addition a treeline model. Stocktaking of the availability of empirical data was undertaken from eight research sites along the Andes and in south-eastern Brazil. Out of eight sites, two (one each in Venezuela and Brazil) had some climate, ecological and ecophysiological data potentially suitable to parametrise a DGVM. Tree biomass data were available for six sites. A preliminary assessment of the Joint UK Land Environment Simulator (JULES) DGVM was made to identify gaps in available data and their impacts on model parametrisation and calibration. Additionally, the potential climate-determined elevation of the treeline was modelled to check the DGVM for its ability to identify the transition between the montane forest and alpine vegetation. Outcomes of the evaluation of the JULES land surface model identified the following key processes in montane forests: temperature-related decrease in net primary production, respiration, and allocation to above-ground biomass and increase in soil C stocks with elevation. There was a variable agreement between simulated biomass and those derived from field measurements via allometric equations. We identified major gaps between data availability and the needs for process-based modelling of South American mountain vegetation and its dynamics in DGVMs. To bridge this gap, we propose a transdisciplinary network, composed of members of the theoretical/modelling and empirical scientific communities, to study the natural dynamics of mountain ecosystems and their responses to global change drivers locally, regionally and at the continental scale, within a social-ecological system framework. The work presented here forms the basis for the design of data collection from field measurements and instrumental monitoring stations to parametrise and verify DGVMs. The network is designed to collaborate with and complement existing long-term research initiatives in the region and will adopt existing standard field protocols. Complementary protocols will ensure compatibility between field data collection and data needed for process-based and empirical models. [ABSTRACT FROM AUTHOR]

Many issues involving leaf areas (LA) allometry, such as the possibility of adjusting morphometric models based on the leaves of different species and the influence model performance on intraspecific variability, are still unclear. In this work, we described allometric equations for 14 different woody tropical species. This study's novelty is to show how a generalised allometric equation accurately estimates LAs of different species with similar leaf morphologies [oblong: Ŷ = 0.6356(LW)1.0260, and elliptical: Ŷ = 0.6552(LW)1.0094]. Natural variation that occurs in the leaf development does not represent an obstacle to the implementation of generalised models. In general, simple linear models are considered ineffective to describe the full range of leaf variation. Extrapolation of these equations to other woody species of similar leaf morphology can be compared with models developed for oblong and elliptical leaves, based on the principle that in potential models, the variation of the intercept coefficient (β0) tended to 0.5 for leaves more elongated to 0.7 in less elongated leaves. While the angular coefficient (β1) tended to vary from 0.97 for less elongated leaves, up to 1 when the relationship between LA is remarkably close to a rectangle. [ABSTRACT FROM AUTHOR]

Coastal ecosystems are considered environments with great potential for carbon storage. Given the difficulties in quantifying biomass, allometric equations and remote sensing have become fundamental tools in the studies of quantification of vegetation biomass and carbon stocks. Thus, the objective of this study is to quantify and estimate the spatial distribution of vegetation biomass and to quantify the carbon stock of the Parnaíba River Delta vegetation. The study was carried out in part of the Parnaíba River Delta Environmental Protection Area and in the Parnaíba River Delta Marine Extractive Reserve, in NE Brazil, in five spots within distinct vegetation types: psammophile pioneer vegetation, dune subevergreen vegetation, mangrove evergreen vegetation, floodplain vegetation and vegetation associated with carnaubals. At 26 collection points, 10 × 20 m plots were marked, in which the diameter at breast height and height of all individuals were measured. The collected data were used in allometric equations for vegetation biomass estimates and these values were converted into carbon stocks. The spatial distribution of aboveground vegetation biomass (AGB) was also estimated by remote sensing, where we extracted and selected spectral variables obtained from Landsat-8 OLI sensor images, on three different dates. Prediction models were calculated by multiple linear regression analysis. It was observed that the mangrove evergreen vegetation obtained higher vegetation biomass and carbon stock than the others. The models obtained through remote sensing that provided the best estimates of AGB were those of November 12th, 2016 (EAM = 6.84; RMSE = 47.89 Mg ha−1; R2 = 0.72) and November 28th, 2016 (EAM = 9.63; RMSE = 34.67 Mg ha−1; R2 = 0.58). [ABSTRACT FROM AUTHOR]

Forests in the southwestern Amazon are rich, diverse, and dense. The region is of high ecological importance, is crucial for conservation and management of natural resources, and contains substantial carbon and biodiversity stocks. Nevertheless, few studies have developed allometric equations for this part of the Amazon, which differs ecologically from the parts of Amazonia where most allometric studies have been done. To fill this gap, we developed allometric equations to estimate the volume, biomass, and carbon in commercial trees with diameter at breast height (DBH) ≥ 50 cm in an area under forest management in the southeastern portion of Brazil's state of Acre. We applied the Smalian formula to data collected from 223 felled trees in 20 species, and compared multiple linear and nonlinear models. The models used diameter (DBH) measured at 1.30 m height (d), length of the commercial stem (l), basic wood density (p), and carbon content (t), as independent variables. For each dependent variable (volume, biomass, or carbon) we compared models using multiple measures of goodness-of-fit, as well as graphically analyzing residuals. The best fit for estimating aboveground volume of individual stems using diameter (d) and length (l) as variables was obtained with the Spurr model (1952; logarithmic) (root mean square error (RMSE) = 1.637, R² = 0.833, mean absolute deviation (MAD) = 1.059). The best-fit equation for biomass, considering d, l, and p as the explanatory variables, was the Loetsch et al. (1973; logarithmic) model (RMSE = 1.047, R² = 0.855, MAD = 0.609). The best fit equation for carbon was the Loetsch et al. (1973; modified) model, using the explanatory variables d, l, p, and t (RMSE = 0.530, R² = 0.85, MAD = 0.304). Existing allometric equations applied to our study trees performed poorly. We showed that the use of linear and nonlinear allometric equations for volume, biomass, and carbon can reduce the errors and improve the estimation of these metrics for the harvested stems of commercial species in the southwestern Amazon. [ABSTRACT FROM AUTHOR]

Necromass has a relevant role to play in the carbon stock of forest ecosystems, especially with the increase of tree mortality due to climate change. Despite this importance, its quantification is often neglected in tropical forests. The objective of this study was to quantify the carbon storage in a secondary Atlantic Forest fragment in Viçosa, Minas Gerais, Brazil. Coarse Woody Debris (CWD), standing dead trees (snags), and litter were quantified in twenty 10 m x 50 m plots randomly positioned throughout the forest area (simple random sampling). Data were collected during 2015, from July to December. The CWD and snags volumes were determined by the Smalian method and by allometric equations, respectively. The necromass of these components was estimated by multiplying the volume by the apparent density at each decomposition classes. The litter necromass was estimated by the proportionality method and the average of the extrapolated estimates per hectare. The carbon stock of the three components was quantified by multiplying the necromass and the carbon wood content. The total volume of dead wood, including CWD and snag, was 23.6 ± 0.9 m3 ha−1, being produced mainly by the competition for resources, senescence, and anthropic and climatic disturbances. The total necromass was 16.3 ± 0.4 Mg ha−1. The total carbon stock in necromass was 7.3 ± 0.2 MgC ha−1. The CWD, snag and litter stocked 3.0 ± 0.1, 1.8 ± 0.1, and 2.5 ± 0.1 MgC ha−1, respectively. These results demonstrate that although necromass has a lower carbon stock compared to biomass, neglecting its quantification may lead to underestimation of the carbon balance of forest ecosystems and their potential to mitigate climate change. [ABSTRACT FROM AUTHOR]

Hybrid eucalypt clones are grown for fiber production worldwide and to provide an ecosystem service that can store atmospheric carbon at a very fast rate. This study assessed the carbon stocks in the soil and various tree fractions in a 10-year-old plantation of Eucalyptus urophylla S.T. Blake × Eucalyptus globulus Labill. in Southern Brazil. Four experimental plots were established, and an inventory of Eucalyptus trees was conducted by considering five diametric classes. Three trees in each diametric class were harvested for biomass and carbon quantification. The understory biomass of native trees was quantified in five subplots and the litter was quantified in 16 subplots. Organic C was quantified in the soil (SOC) and roots (diameter ≤ 0.5 cm) to a depth of 100 cm. The C concentration in the different biomass fractions of the eucalyptus trees were 55.7% (±0.6), 50.4% (±0.4), 49.5% (±0.6) and 45.4 % (±0.9) for leaves, branches, wood and bark, respectively. The C concentrations in the understory fractions were 51.4% (±1.0) for the canopy and 50.0% (±0.9) for the stem. The carbon concentration in the fine root biomass was 45.7% (±1.4). Soil C concentrations were 1.23% (±0.32), 0.97% (±0.10), 0.45% (±0.14), and 0.24% (±0.10) for depths of 0–25, 25–50, 50–75, and 75–100 cm. C was allocated in: (a) the trees (aboveground fraction = 118.45 Mg ha−1 and belowground fraction = 30.06 Mg ha−1), (b) the understory = 1.44 Mg ha−1, (c) the litter = 8.34 Mg ha−1, and (d) the soil (without roots) = 99.7 Mg ha−1. The share of total C stock (a + b + c + d = 258.0 Mg ha−1) was similar in the aboveground (49.7%) and belowground (50.3%) fractions, thus indicating a very high rate of C sequestration in the biomass. Eucalyptus plantations in Brazil are fast growing (for this study = 36.7 m³ ha−1 year−1) and contribute to intense carbon sequestration in above and belowground biomass (14.8 Mg ha−1 year−1). [ABSTRACT FROM AUTHOR]

Background: The Cerrado is the second largest biome in Brazil and the most biodiverse tropical savannah in the world and acts as a great sequester of atmospheric carbon. The lack of studies related to the quantification of its total biomass compromises the understanding of the dynamics of CO2 in this biome. Thus, it is relevant to develop studies aiming at obtaining accurate estimates of the carbon stock in the different phytophysiognomies that make the Cerrado, to include them in appropriate forest management models. Based on the hypothesis that the amount of carbon stored can vary according to the vegetation typology and vegetation compartments, the aerial stock of dry biomass and carbon were estimated in different compartments (arboreal, herbaceous-shrub and litter). The study was developed in open Brazilian savannah and soils on the sandstone and discussed the effect of fire on this phytophysiognomy. For the arboreal compartment were adjusted mathematical models to fit the biomass equations to estimate the individual stock of the trees in this compartment. The results of the stocks were discussed considering the effect of fire on the phytophysiognomy. Results: Based on the precision and extra distribution measures, the Schumacher-Hall (non-logarithmic) equation presented better results to estimate the individual biomass and carbon stocks of the open Brazilian savannah trees. The aboveground biomass was 12.88 Mg ha−1, corresponding to a total carbon stock of 5.91 Mg ha−1, where most of the stocks are in the herbaceous-shrub compartment (44%). The arboreal compartment accounts for the smallest part of the stocks, followed by the litter. Conclusions: The observed values are in the interval verified for other areas of savannah studied in Brazil. The values verified for the open Brazilian savannah in sandy soils are at the lower limit of this range, due to the nutrient-poor nature of this type of soil. The distribution of stocks in the different compartments above the ground points to the fragility of this environment to the random fire effect, common in the region. That shows the need for conservation measures for vegetation maintenance and soil protection to preserve adequate nutrient cycling in the ecosystem. [ABSTRACT FROM AUTHOR]