ORCID Profile
0000-0003-3714-8175
Current Organisation
Oregon State University
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Publisher: Copernicus GmbH
Date: 08-04-2019
DOI: 10.5194/BG-2019-75
Abstract: Abstract. Coarse dead wood is an important component of forest carbon stocks, but it is rarely measured in Amazon forests and is typically excluded from regional forest carbon budgets. Our study is based on line intercept s ling for fallen coarse dead wood conducted along 103 transects with a total length of 48 km matched with forest inventory plots where standing coarse dead wood was measured in the footprints of larger areas of airborne lidar acquisitions. We developed models to relate lidar metrics and Landsat time series variables to coarse dead wood stocks for intact, logged, and burned or logged and burned forests. Canopy characteristics such as gap area produced significant in idual relations for logged forests. For total fallen plus standing coarse dead wood (hereafter defined as total coarse dead wood), the relative root mean square error for models with only lidar metrics ranged from 33 % in logged forest to up to 36 % in burned forests. The addition of historical information improved model performance slightly for intact forests (31 % against 35 % relative root mean square error), not justifying the use of number of disturbances events from historical satellite images (Landsat) with airborne lidar data. Lidar-derived estimates of total coarse dead wood compared favorably to independent ground-based s ling for areas up to several hundred hectares. The relations found between total coarse dead wood and structural variables derived from airborne lidar highlight the opportunity to quantify this important, but rarely measured component of forest carbon over large areas in tropical forests.
Publisher: American Geophysical Union (AGU)
Date: 31-08-2023
DOI: 10.1029/2023JG007465
Abstract: The Brazilian Amazon has been a focus of land development with large swaths of forests converted to agriculture. Forest degradation by selective logging and fires has accompanied the agricultural frontier and has resulted in significant impacts on Amazonian ecosystems. Changes in forest structure resulting from forest disturbances have large impacts on the surface energy balance, including on land surface temperature (LST) and evapotranspiration (ET). This study's objective is to assess the effects of forest disturbances on water fluxes and forest structure in a transitional forest site in the Southern Amazon. We used ET and LST products from MODIS and Landsat 8 and GEDI‐derived forest structure data to address our research questions. We found that disturbances induced seasonal water stress, more pronounced in croplands astures than in forests (differences up to 20% in the dry season), and more pronounced in second‐growth and recently burned areas than in logged and intact forests (differences up to 12% in the dry season). Moreover, ET and LST were negatively related, with more consistent relationships across disturbance classes in the dry season ( R 2 : 0.41–0.87) than in the wet season ( R 2 : 0.18–0.49). Forest and cropland or pasture classes showed contrasting relationships in the dry season. Finally, we found that forest structure exhibited stronger relationships with ET and LST in the most disturbed forests ( R 2 : 0.01–0.43) than in the least disturbed forests ( R 2 0.05). Our findings help to elucidate degraded forests functioning under a changing climate and to improve estimates of water and energy fluxes in Amazonian degraded forests.
Publisher: Elsevier BV
Date: 11-2009
Publisher: Copernicus GmbH
Date: 13-09-2019
Abstract: Abstract. Coarse dead wood is an important component of forest carbon stocks, but it is rarely measured in Amazon forests and is typically excluded from regional forest carbon budgets. Our study is based on line intercept s ling for fallen coarse dead wood conducted along 103 transects with a total length of 48 km matched with forest inventory plots where standing coarse dead wood was measured in the footprints of larger areas of airborne lidar acquisitions. We developed models to relate lidar metrics and Landsat time series variables to coarse dead wood stocks for intact, logged, burned, or logged and burned forests. Canopy characteristics such as gap area produced significant in idual relations for logged forests. For total fallen plus standing coarse dead wood (hereafter defined as total coarse dead wood), the relative root mean square error for models with only lidar metrics ranged from 33 % in logged forest to up to 36 % in burned forests. The addition of historical information improved model performance slightly for intact forests (31 % against 35 % relative root mean square error), not justifying the use of a number of disturbance events from historical satellite images (Landsat) with airborne lidar data. Lidar-derived estimates of total coarse dead wood compared favorably with independent ground-based s ling for areas up to several hundred hectares. The relations found between total coarse dead wood and variables quantifying forest structure derived from airborne lidar highlight the opportunity to quantify this important but rarely measured component of forest carbon over large areas in tropical forests.
Publisher: Wiley
Date: 20-06-2019
Publisher: Copernicus GmbH
Date: 23-03-2020
DOI: 10.5194/EGUSPHERE-EGU2020-4801
Abstract: & & Tropical forest degradation through selective logging, fragmentation, and understory fires substantially changes forest structure and composition.& In the Amazon, degradation is as widespread as deforestation however, studies addressing the effects of forest degradation on tropical ecosystem functions are scarce. Here, we integrate small-footprint airborne lidar over the Brazilian Amazon (& 250,000 ha), collected between 2016& #8211 , with recent ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) land surface temperature and evapotranspiration products (70-m resolution, data acquired in 2018& #8211 ) to investigate the role of forest structure, forest fragmentation, and disturbance history on dry-season land surface temperature and evapotranspiration.& During the dry season, degraded forests, especially those affected by multiple degradation events, are significantly warmer (up to 9.3& #176 C) and show reduced evapotranspiration (10% less than intact forests). Likewise, forest near the edges (& 350m) experience the greatest warming (up to 6.5& #176 C) and the greatest reduction (9%) in evapotranspiration. We also used the airborne lidar dataset to initialize the Ecosystem Demography Model (ED-2.2) to investigate the impact of degradation on the gross primary production (GPP), evapotranspiration (ET), and sensible heat flux (H) under a broader range of climate conditions, including severe droughts. Consistent with ECOSTRESS, the simulations during the dry season in typical years showed that severely degraded forests experienced water-stress with declines in ET (34% reduction), GPP (35% reduction), and increases of H (43% increases) and daily mean ground temperatures (up to 6.5& #176 C) relative to intact forests.& In the model, the simulated changes are mostly driven by increased below-ground water stress, which can be attributed to the shallower rooting profile of degraded forests. However, relative to intact forest, the impact of degradation on energy, water, and carbon cycles markedly diminishes under extreme droughts such as 2015& #8211 , when all forests experience severe stress. Our results indicate the potentially important role of tropical forest degradation changing the carbon, water, and energy cycles in the Amazon, and consequently a much broader influence of land use activities on functioning of tropical ecosystems.& &
Publisher: American Geophysical Union (AGU)
Date: 11-2016
DOI: 10.1002/2016GB005465
Publisher: MDPI AG
Date: 24-03-2019
DOI: 10.3390/RS11060709
Abstract: Forest degradation is common in tropical landscapes, but estimates of the extent and duration of degradation impacts are highly uncertain. In particular, selective logging is a form of forest degradation that alters canopy structure and function, with persistent ecological impacts following forest harvest. In this study, we employed airborne laser scanning in 2012 and 2014 to estimate three-dimensional changes in the forest canopy and understory structure and aboveground biomass following reduced-impact selective logging in a site in Eastern Amazon. Also, we developed a binary classification model to distinguish intact versus logged forests. We found that canopy gap frequency was significantly higher in logged versus intact forests even after 8 years (the time span of our study). In contrast, the understory of logged areas could not be distinguished from the understory of intact forests after 6–7 years of logging activities. Measuring new gap formation between LiDAR acquisitions in 2012 and 2014, we showed rates 2 to 7 times higher in logged areas compared to intact forests. New gaps were spatially clumped with 76 to 89% of new gaps within 5 m of prior logging damage. The biomass dynamics in areas logged between the two LiDAR acquisitions was clearly detected with an average estimated loss of −4.14 ± 0.76 MgC ha−1 y−1. In areas recovering from logging prior to the first acquisition, we estimated biomass gains close to zero. Together, our findings unravel the magnitude and duration of delayed impacts of selective logging in forest structural attributes, confirm the high potential of airborne LiDAR multitemporal data to characterize forest degradation in the tropics, and present a novel approach to forest classification using LiDAR data.
Publisher: Authorea, Inc.
Date: 09-03-2023
DOI: 10.22541/ESSOAR.167839947.73218884/V1
Abstract: The Brazilian Amazon has been a focus of land development with large swaths of forests converted to agriculture. Forest degradation by selective logging and fires has accompanied the advance of the frontier and has resulted in significant impacts on Amazonian ecosystems. Changes in forest structure resulting from forest disturbances have large impacts on the surface energy balance, including on land surface temperature (LST) and evapotranspiration (ET). The objective of this study is to assess the effects of forest disturbances on water fluxes and canopy structural properties in a transitional forest site located in Mato Grosso State, Southern Amazon. We used ET and LST products from MODIS and Landsat 8 as well as GEDI-derived forest structure data to address our research questions. We found that disturbances induced seasonal water stress, more pronounced and earlier in croplands and pastures than in forests, and more pronounced in second-growth and recently burned areas than in logged and intact forests. Moreover, we found that ET and LST were negatively related, with a more consistent relationship across disturbance classes in the dry season than the wet season, and that forest and cropland and pasture classes showed contrasting relationships in the dry season. Finally, we found that canopy structural properties exhibited moderate relationships with ET and LST in the most disturbed forests, but negligible correlations in the least disturbed forests. Our findings help to elucidate degraded forests functioning under a changing climate and to improve estimates of water and energy fluxes in the Amazon degraded forests.
Publisher: Springer Science and Business Media LLC
Date: 11-01-2022
Publisher: Italian Society of Sivilculture and Forest Ecology (SISEF)
Date: 06-2016
DOI: 10.3832/IFOR1534-008
Publisher: MDPI AG
Date: 17-06-2018
DOI: 10.3390/RS10060970
Publisher: FapUNIFESP (SciELO)
Date: 09-2015
Abstract: RESUMOA infraestrutura para exploração florestal é fundamental nas atividades de exploração madeireira, mas responde por grande parte dos impactos ambientais dessa atividade. O presente estudo aplicou e testou cinco técnicas de processamento digital de imagens orbitais com três resoluções espaciais distintas para a detecção de estradas e pátios florestais construídos em áreas sob manejo florestal sustentável na Floresta Nacional do Jamari, estado de Rondônia. Os resultados mostraram que o NDVI e a Análise de componentes principais apresentaram a melhor acurácia global nas resoluções espaciais de 5 e 10 metros e na de 30 metros, respectivamente. De maneira geral, a acurácia do produtor para a classe de interesse não foi alta, alcançando no máximo 39,2%, e índice Kappa de 0,38. A baixa performance das técnicas de geoprocessamento utilizadas na detecção de florestas exploradas seletivamente está relacionada às alterações ocorridas no dossel da floresta manejada, pouco perceptíveis em imagens de satélite.
No related grants have been discovered for Ekena Rangel Pinagé.