Publicações

2025

1. Ecol Indic

   Aboveground biomass and carbon stocks in subtropical forests

   Hiago Adamosky Machado, Adriane Avelhaneda Mallmann, Kauana Engel, and 8 more authors

   Ecological Indicators, Mar 2025

   Abs DOI

   Quantifying plant biomass in native forests is essential to understanding ecosystem health, primary productivity, biodiversity, and the carbon cycle, contributing to climate regulation. Therefore, the objective of this study was to establish biomass estimators and quantify biomass and carbon stocks in subtropical forests in Brazil. The study area can be considered one of the largest preserved areas of the Atlantic Forest biome, covering approximately 6,000 km2. Two procedures were used to quantify biomass and carbon: i) for trees with less than 50 cm of dbh, equations were established using allometric data collected; ii) for trees with more than 50 cm of dbh, the equations established by Trautenmüller et al. (2021) were used. These equations were biologically consistent and were corrected for heteroscedasticity, using the WNSUR procedure. These equations were later used to estimate the biomass of everyone in an inventory of subtropical forests in the state of Paraná, Brazil. A total of 456,302.00 ha of area with vegetation cover were found, with an average biomass stock of 117.26 Mg.ha−1. The total biomass stock for the entire area was 53,505.97 Gg, and the carbon equivalent was 92,208.63 Gg, highlighting the need to preserve this area with vegetation cover. One of the most immediate actions to mitigate the effects of climate change is to reduce deforestation, which can be the result of human activities or caused by mass movement. New studies should be carried out to assess the effects of climate extremes on carbon stocks and how these can affect the lives involved.

2. Forest Systems

   Carbon stock in the biomass of native urban fragments: A case study in an Atlantic Forest remnant in Brazil

   Carla T. Pertille, Ernandes Da Cunha-Neto, Carlos R. Sanquetta, and 2 more authors

   Forest Systems, Apr 2025

   Abs DOI

   Aim of study: In the face of global concern about climate change, urban forests have great potential in the scenario of mitigating climate change and reducing emissions by carbon dioxide. Thus, the objective of this work was to evaluate the potential for carbon and carbon dioxide (CO2) removal of a forest fragment. Area of study: A native urban Atlantic Forest fragment located in Curitiba, State of Paraná, Brazil. Material and methods: To do so, dendrometric data measured in the years 2006, 2009, 2012, 2015, 2018 and 2021 were used, totalling 77,016 individuals. From these data, the height, shoot and underground biomass were estimated based on allometric equations available in the literature. The growth dynamics and carbon stock were quantified by the difference in carbon stock at the beginning (2006) and at the end of the assessment (2021) in general, by genus and by diameter class. Main results: The results showed that around 156.56 t.ha-1 of biomass were accumulated in 15 years,resulting in 64.23 t.ha-1 of carbon, 235.51 t.ha-1 of carbon dioxide equivalent (CO2eq) and annual removal of4.06 t.ha-1.year-1. The genus Araucaria was predominant throughout the period in relation to the generafound, followed by Ocotea, Luehea and Casearia, while Gymmanthes, Clethra and Citronella were laterincluded in the evaluations. Araucaria individuals with a diameter class of 60 and 70 cm were responsiblefor the largest amount of carbon stored. The carbon stock concentration for the other genera was higher fordiameter classes smaller than 40 cm. Research highlights: Given the numbers found of annual carbon removal and biomass accumulation, it can be concluded that this native urban fragment positively contributed to the absorption and fixation of atmospheric carbon in forest biomass.

2024

1. CERNE

   Effects of flight and smoothing parameters of number of trees with aerial imagery in a native Brazilian atlantic forest remnant

   Carla Talita Pertille, Karla Mayara Almada Gomes, Darcy Maria da Conceição Laura dos Santos, and 5 more authors

   CERNE, Sep 2024

   Publisher: UFLA - Universidade Federal de Lavras

   Abs DOI

   Background:  The objective of this study was to detect native trees from different flight configurations and smoothing techniques in Canopy Height Models (CHMs) in a native remnant in the municipality of Curitiba, State of Paraná, Brazil. To do so, eight flights were carried out with a Phantom 4, with two flight planning applications (Litchi and Pix4Dcapture) and two flight arrangements (single and double), totaling four flights for each application. All flights were processed using the Pix4Dmapper program. The LiDAR database was obtained with a DJI Matrice 300 system and from this data, the Digital Terrain Model (DTM) of the area was extracted. From the UAV data, the Digital Surface Model (DSM) of each flight was obtained. Subtracting each DSM from the DTM resulted in the CHMs for each UAV flight flown. The CHMs were smoothed with the CHMsmoothing function and three search window sizes were tested (6.5 x 6.5, 8 x 8, and 10 x 10). Results:  The results of the ITD approach revealed that in unsmoothed and smoothed CHMs, the search window of size 8 resulted in the best precision metrics, with the highest recall, precision, and F-score values. In the smallest window size, there was the highest number of false positives while in the largest window size, the omitted trees were more representative. Conclusion:  The best combination between flight parameters and smoothing techniques was with the Litchi application, with a single flight and 80% lateral and longitudinal overlap, resulting in individuals detected with an F-score of 0.94. Keywords:Remote sensing; LM algorithm; canopy height model.

2022

1. Land

   Applying High-Resolution UAV-LiDAR and Quantitative Structure Modelling for Estimating Tree Attributes in a Crop-Livestock-Forest System

   Ana Paula Dalla Corte, Bruna Nascimento Vasconcellos, Franciel Eduardo Rex, and 15 more authors

   Land, Apr 2022

   Number: 4 Publisher: Multidisciplinary Digital Publishing Institute

   Abs DOI

   Individual tree attributes, such as stem volume and biomass, are usually predicted by using traditional field-derived allometric models. However, these models are derived from data collected from small areas and lack a level of detail of tree components (e.g., stem, branches, and leaves). Remote sensing techniques such as the Quantitative Structure Modelling (QSM) applied on high-density LiDAR data emerge as a promising solution for obtaining extensive and detailed tree attribute estimates. We used a high-density LiDAR data on board of a Unmanned Aerial Vehicle (UAV) to evaluate the performance of the QSM approach in estimating field-derived individual tree attributes such as the diameter at breast height (dbh), tree height (ht), and volume (v), as well as the stem (SAGB), branch (BAGB), and total (TAGB) aboveground biomass of eucalyptus trees. QSM was used in two different approaches: (i) using dbh and h derived from QSM and then applied into the field-based equations for estimation of volume and (ii) deriving tree volume directly from QSM. In general, all fitted models using the QSM approach were satisfactory, but with a slight tendency of over-estimation of dbh (9.33%), ht (12.40%), v-QSM1 (26.35%), v-QSM2 (26.66%), TAGB (27.08%), SAGB (25.57%), and BAGB (20.08%). Non-significant differences were noticed when estimating the dbh, tree volume, stem, and aboveground biomass. Despite the overestimation, this study indicates that using the QSM approach to estimate individual tree attributes from UAV-LiDAR is a promising alternative to support the decision-making process regarding forest management activities, especially when considering tree architecture and biomass components.