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Atkins JW, Costanza J, Dahlin KM, Dannenberg MP, Elmore AJ, Fitzpatrick MC, Hakkenberg CR, Hardiman BS, Kamoske A, LaRue EA, Silva CA, Stovall AEL, Tielens EK. Scale dependency of lidar‐derived forest structural diversity. Methods Ecol Evol 2023. [DOI: 10.1111/2041-210x.14040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Affiliation(s)
- Jeff W. Atkins
- Southern Research Station USDA Forest Service New Ellenton South Carolina USA
| | - Jennifer Costanza
- Southern Research Station USDA Forest Service Research Triangle Park North Carolina USA
| | - Kyla M. Dahlin
- Department of Geography, Environment & Spatial Sciences Michigan State University East Lansing Michigan USA
| | - Matthew P. Dannenberg
- Department of Geographical and Sustainability Sciences University of Iowa Iowa City Iowa USA
| | - Andrew J. Elmore
- National Socio‐Environmental Synthesis Center Annapolis Maryland USA
- Appalachian Laboratory University of Maryland Center for Environmental Science Frostburg Maryland USA
| | - Matthew C. Fitzpatrick
- Appalachian Laboratory University of Maryland Center for Environmental Science Frostburg Maryland USA
| | | | - Brady S. Hardiman
- Department of Forestry and Natural Resources Purdue University West Lafayette Indiana USA
- Department of Civil and Environmental Engineering Purdue University West Lafayette Indiana USA
| | - Aaron Kamoske
- Ecosystem Management Coordination USDA Forest Service Saint Paul Minnesota USA
| | - Elizabeth A. LaRue
- Department of Biological Sciences The University of Texas at El Paso El Paso Texas USA
| | - Carlos Alberto Silva
- Forest Biometrics and Remote Sensing Lab, School of Forest, Fisheries, and Geomatics University of Florida Gainesville Florida USA
| | - Atticus E. L. Stovall
- Department of Geographical Sciences University of Maryland College Park Maryland USA
- NASA Goddard Space Flight Center Greenbelt Maryland USA
| | - Elske K. Tielens
- Corix Plains Institute University of Oklahoma Norman Oklahoma USA
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2
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Martinuzzi S, Cook BD, Helmer EH, Keller M, Locke DH, Marcano‐Vega H, Uriarte M, Morton DC. Patterns and controls on island‐wide aboveground biomass accumulation in second‐growth forests of Puerto Rico. Biotropica 2022. [DOI: 10.1111/btp.13122] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Affiliation(s)
- Sebastián Martinuzzi
- SILVIS Lab Department of Forest and Wildlife Ecology University of Wisconsin‐Madison Madison Wisconsin USA
- Biospheric Sciences Laboratory NASA Goddard Space Flight Center Greenbelt Maryland USA
| | - Bruce D. Cook
- Biospheric Sciences Laboratory NASA Goddard Space Flight Center Greenbelt Maryland USA
| | - Eileen H. Helmer
- USDA Forest Service International Institute of Tropical Forestry San Juan Puerto Rico USA
| | - Michael Keller
- USDA Forest Service International Institute of Tropical Forestry San Juan Puerto Rico USA
- Jet Propulsion Laboratory California Institute of Technology Pasadena California USA
| | - Dexter H. Locke
- USDA Forest Service Northern Research Station Baltimore Field Station Baltimore Maryland USA
| | | | - María Uriarte
- Department of Ecology, Evolution & Environmental Biology Columbia University New York New York USA
| | - Douglas C. Morton
- Biospheric Sciences Laboratory NASA Goddard Space Flight Center Greenbelt Maryland USA
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Lourençoni T, da Silva Junior CA, Lima M, Teodoro PE, Pelissari TD, Dos Santos RG, Teodoro LPR, Luz IM, Rossi FS. Advance of soy commodity in the southern Amazonia with deforestation via PRODES and ImazonGeo: a moratorium-based approach. Sci Rep 2021; 11:21792. [PMID: 34750464 PMCID: PMC8576044 DOI: 10.1038/s41598-021-01350-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 10/27/2021] [Indexed: 11/09/2022] Open
Abstract
The guidance on decision-making regarding deforestation in Amazonia has been efficient as a result of monitoring programs using remote sensing techniques. Thus, the objective of this study was to identify the expansion of soybean farming in disagreement with the Soy Moratorium (SoyM) in the Amazonia biome of Mato Grosso from 2008 to 2019. Deforestation data provided by two Amazonia monitoring programs were used: PRODES (Program for Calculating Deforestation in Amazonia) and ImazonGeo (Geoinformation Program on Amazonia). For the identification of soybean areas, the Perpendicular Crop Enhancement Index (PCEI) spectral model was calculated using a cloud platform. To verify areas (polygons) of largest converted forest-soybean occurrences, the Kernel Density (KD) estimator was applied. Mann-Kendall and Pettitt tests were used to identify trends over the time series. Our findings reveal that 1,387,288 ha were deforested from August 2008 to October 2019 according to PRODES data, of which 108,411 ha (7.81%) were converted into soybean. The ImazonGeo data showed 729,204 hectares deforested and 46,182 hectares (6.33%) converted into soybean areas. Based on the deforestation polygons of the two databases, the KD estimator indicated that the municipalities of Feliz Natal, Tabaporã, Nova Ubiratã, and União do Sul presented higher occurrences of soybean fields in disagreement with the SoyM. The results indicate that the PRODES system presents higher data variability and means statistically superior to ImazonGeo.
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Affiliation(s)
- Thais Lourençoni
- State University of Mato Grosso (UNEMAT), Alta Floresta, MT, Brazil
| | | | - Mendelson Lima
- State University of Mato Grosso (UNEMAT), Alta Floresta, MT, Brazil
| | - Paulo Eduardo Teodoro
- Department of Crop Science, Department of Agronomy, Federal University of Mato Grosso Do Sul (UFMS), Chapadão Do Sul, MS, Brazil.
| | | | - Regimar Garcia Dos Santos
- Department of Crop Science, Department of Agronomy, Federal University of Mato Grosso Do Sul (UFMS), Chapadão Do Sul, MS, Brazil
| | - Larissa Pereira Ribeiro Teodoro
- Department of Crop Science, Department of Agronomy, Federal University of Mato Grosso Do Sul (UFMS), Chapadão Do Sul, MS, Brazil
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Modeling and Spatialization of Biomass and Carbon Stock Using LiDAR Metrics in Tropical Dry Forest, Brazil. FORESTS 2021. [DOI: 10.3390/f12040473] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
In recent years, with the growing environmental concern regarding climate change, there has been a search for efficient alternatives in indirect methods for the quantification of biomass and forest carbon stock. In this article, we seek to obtain pioneering results of biomass and carbon estimates from forest inventory data and LiDAR technology in a dry tropical forest in Brazil. We use forest inventory data in two areas together with data from the LiDAR flyby, generating estimates of local biomass and carbon levels obtained from local species. We approach three types of models for data analysis: Multiple linear regression with principal components (PCA), conventional multiple linear regression and stepwise multiple linear regression. The best fit total above ground biomass (TAGB) and total above ground carbon (TAGC) model was the stepwise multiple linear regression, concluding, then, that LiDAR data can be used to estimate biomass and total carbon in dry tropical forest, proven by an adjustment considered in the models employed, with a significant correlation between the LiDAR metrics. Our finding provides important information about the spatial distribution of TAGB and TAGC in the study area, which can be used to manage the reserve for optimal carbon sequestration.
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César RG, Moreno VDS, Coletta GD, Schweizer D, Chazdon RL, Barlow J, Ferraz SFB, Crouzeilles R, Brancalion PHS. It is not just about time: Agricultural practices and surrounding forest cover affect secondary forest recovery in agricultural landscapes. Biotropica 2021. [DOI: 10.1111/btp.12893] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Affiliation(s)
- Ricardo G. César
- Department of Forest Sciences, “Luiz de Queiroz” College of Agriculture University of São Paulo Piracicaba Brazil
| | - Vanessa de S. Moreno
- Department of Forest Sciences, “Luiz de Queiroz” College of Agriculture University of São Paulo Piracicaba Brazil
| | - Gabriel D. Coletta
- Plant Biology Graduate Program, Biology Institute University of Campinas Campinas Brazil
| | - Daniella Schweizer
- Department of Forest Sciences, “Luiz de Queiroz” College of Agriculture University of São Paulo Piracicaba Brazil
| | - Robin L. Chazdon
- Department of Forest Sciences, “Luiz de Queiroz” College of Agriculture University of São Paulo Piracicaba Brazil
- Department of Ecology and Evolutionary Biology University of Connecticut Storrs CT USA
| | - Jos Barlow
- Lancaster Environment Centre Lancaster University Lancaster UK
| | - Silvio F. B. Ferraz
- Department of Forest Sciences, “Luiz de Queiroz” College of Agriculture University of São Paulo Piracicaba Brazil
| | - Renato Crouzeilles
- International Institute for Sustainability Rio de Janeiro Brazil
- International Institute for Sustainability Australia Canberra ACT Australia
- Mestrado Profissional em Ciências do Meio Ambiente Universidade Veiga de Almeida Rio de Janeiro Brazil
| | - Pedro H. S. Brancalion
- Department of Forest Sciences, “Luiz de Queiroz” College of Agriculture University of São Paulo Piracicaba Brazil
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Estimating Structure and Biomass of a Secondary Atlantic Forest in Brazil Using Fourier Transforms of Vertical Profiles Derived from UAV Photogrammetry Point Clouds. REMOTE SENSING 2020. [DOI: 10.3390/rs12213560] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Knowing the aboveground biomass (AGB) stock of tropical forests is one of the main requirements to guide programs for reducing emissions from deforestation and forest degradation (REDD+). Traditional 3D products generated with digital aerial photogrammetry (DAP) have shown great potential in estimating AGB, tree density, diameter at breast height, height, and basal area in forest ecosystems. However, these traditional products explore only a small part of the structural information contained in the 3D data, thus not leveraging the full potential of the data for inventory purposes. In this study, we tested the performance of 3D products derived from DAP and a technique based on Fourier transforms of vertical profiles of vegetation to estimate AGB, tree density, diameter at breast height, height, and basal area in a secondary fragment of Atlantic Forest located in northeast Brazil. Field measurements were taken in 30 permanent plots (0.25 ha each) to estimate AGB. At the time of the inventory, we also performed a digital aerial mapping of the entire forest fragment with an unmanned aerial vehicle (UAV). Based on the 3D point clouds and the digital terrain model (DTM) obtained by DAP, vertical vegetation profiles were produced for each plot. Using traditional structure metrics and metrics derived from Fourier transforms of profiles, regression models were fit to estimate AGB, tree density, diameter at breast height, height, and basal area. The 3D DAP point clouds represented the forest canopy with a high level of detail, regardless of the vegetation density. The metrics based on the Fourier transform of profiles were selected as predictors in all models produced. The best model for AGB explained 93% (R2 = 0.93) of the biomass variation at the plot level, with an RMS error of 9.3 Mg ha−1 (22.5%). Similar results were obtained in the models fit for the tree density, diameter at breast height, height, and basal area, with R2 values above 0.90 and RMS errors of less than 18%. The use of Fourier transforms of profiles with 3D products obtained by DAP demonstrated a high potential for estimating AGB and other forest variables of interest in secondary tropical forests, highlighting the value of UAV as a low-cost tool to assist the implementation of REDD+ projects in developing countries like Brazil.
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How Can Remote Sensing Help Monitor Tropical Moist Forest Degradation?—A Systematic Review. REMOTE SENSING 2020. [DOI: 10.3390/rs12071087] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
In the context of the climate and biodiversity crisis facing our planet, tropical forests playing a key role in global carbon flux and containing over half of Earth’s species are important to preserve. They are today threatened by deforestation but also by forest degradation, which is more difficult to study. Here, we performed a systematic review of studies on moist tropical forest degradation using remote sensing and fitting indicators of forest resilience to perturbations. Geographical repartition, spatial extent and temporal evolution were analyzed. Indicators of compositional, structural and regeneration criteria were noted as well as remote sensing indices and metrics used. Tropical moist forest degradation is not extensively studied especially in the Congo basin and in southeast Asia. Forest structure (i.e., canopy gaps, fragmentation and biomass) is the most widely and easily measured criteria with remote sensing, while composition and regeneration are more difficult to characterize. Mixing LiDAR/Radar and optical data shows good potential as well as very high-resolution satellite data. The awaited GEDI and BIOMASS satellites data will fill the actual gap to a large extent and provide accurate structural information. LiDAR and unmanned aerial vehicles (UAVs) form a good bridge between field and satellite data. While the performance of the LiDAR is no longer to be demonstrated, particular attention should be brought to the UAV that shows great potential and could be more easily used by local communities and stakeholders.
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Chave J, Piponiot C, Maréchaux I, de Foresta H, Larpin D, Fischer FJ, Derroire G, Vincent G, Hérault B. Slow rate of secondary forest carbon accumulation in the Guianas compared with the rest of the Neotropics. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2020; 30:e02004. [PMID: 31520573 DOI: 10.1002/eap.2004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2019] [Revised: 06/18/2019] [Accepted: 08/02/2019] [Indexed: 06/10/2023]
Abstract
Secondary forests are a prominent component of tropical landscapes, and they constitute a major atmospheric carbon sink. Rates of carbon accumulation are usually inferred from chronosequence studies, but direct estimates of carbon accumulation based on long-term monitoring of stands are rarely reported. Recent compilations on secondary forest carbon accumulation in the Neotropics are heavily biased geographically as they do not include estimates from the Guiana Shield. We analysed the temporal trajectory of aboveground carbon accumulation and floristic composition at one 25-ha secondary forest site in French Guiana. The site was clear-cut in 1976, abandoned thereafter, and one large plot (6.25 ha) has been monitored continuously since. We used Bayesian modeling to assimilate inventory data and simulate the long-term carbon accumulation trajectory. Canopy change was monitored using two aerial lidar surveys conducted in 2009 and 2017. We compared the dynamics of this site with that of a surrounding old-growth forest. Finally, we compared our results with that from secondary forests in Costa Rica, which is one of the rare long-term monitoring programs reaching a duration comparable to our study. Twenty years after abandonment, aboveground carbon stock was 64.2 (95% credibility interval 46.4, 89.0) Mg C/ha, and this stock increased to 101.3 (78.7, 128.5) Mg C/ha 20 yr later. The time to accumulate one-half of the mean aboveground carbon stored in the nearby old-growth forest (185.6 [155.9, 200.2] Mg C/ha) was estimated at 35.0 [20.9, 55.9] yr. During the first 40 yr, the contribution of the long-lived pioneer species Xylopia nitida, Goupia glabra, and Laetia procera to the aboveground carbon stock increased continuously. Secondary forest mean-canopy height measured by lidar increased by 1.14 m in 8 yr, a canopy-height increase consistent with an aboveground carbon accumulation of 7.1 Mg C/ha (or 0.89 Mg C·ha-1 ·yr-1 ) during this period. Long-term AGC accumulation rate in Costa Rica was almost twice as fast as at our site in French Guiana. This may reflect higher fertility of Central American forest communities or a better adaptation of the forest tree community to intense and frequent disturbances. This finding may have important consequences for scaling-up carbon uptake estimates to continental scales.
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Affiliation(s)
- Jérôme Chave
- Laboratoire Evolution et Diversité Biologique, UMR5174, CNRS-Université Paul Sabatier-IRD, Bâtiment 4R1, 118 route de Narbonne, F-31062, Toulouse Cedex 9, France
| | - Camille Piponiot
- Cirad, UMR 'Ecologie des Forêts de Guyane' (AgroparisTech, CNRS, Inra, Université des Antilles, Université de la Guyane), F-97379, Kourou Cedex, French Guiana
| | - Isabelle Maréchaux
- Laboratoire Evolution et Diversité Biologique, UMR5174, CNRS-Université Paul Sabatier-IRD, Bâtiment 4R1, 118 route de Narbonne, F-31062, Toulouse Cedex 9, France
- AgroParisTech-ENGREF, 19 Avenue du Maine, F-75015, Paris, France
- AMAP, Univ Montpellier, IRD, CIRAD, CNRS, INRA, F-34000, Montpellier, France
| | - Hubert de Foresta
- AMAP, Univ Montpellier, IRD, CIRAD, CNRS, INRA, F-34000, Montpellier, France
| | - Denis Larpin
- Direction Générale Déléguée aux Musées, Jardins et Zoos, Muséum National d'Histoire Naturelle, 57 rue Cuvier, F-75005, Paris, France
| | - Fabian Jörg Fischer
- Laboratoire Evolution et Diversité Biologique, UMR5174, CNRS-Université Paul Sabatier-IRD, Bâtiment 4R1, 118 route de Narbonne, F-31062, Toulouse Cedex 9, France
| | - Géraldine Derroire
- Cirad, UMR 'Ecologie des Forêts de Guyane' (AgroparisTech, CNRS, Inra, Université des Antilles, Université de la Guyane), F-97379, Kourou Cedex, French Guiana
| | - Grégoire Vincent
- AMAP, Univ Montpellier, IRD, CIRAD, CNRS, INRA, F-34000, Montpellier, France
| | - Bruno Hérault
- Cirad, Univ Montpellier, UR Forests & Societies, F-34000, Montpellier, France
- INPHB, Institut National Polytechnique Félix Houphouët-Boigny, Yamoussoukro, Ivory Coast
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Winbourne JB, Feng A, Reynolds L, Piotto D, Hastings MG, Porder S. Nitrogen cycling during secondary succession in Atlantic Forest of Bahia, Brazil. Sci Rep 2018; 8:1377. [PMID: 29358584 PMCID: PMC5778002 DOI: 10.1038/s41598-018-19403-0] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2017] [Accepted: 12/21/2017] [Indexed: 11/08/2022] Open
Abstract
Carbon accumulation in tropical secondary forests may be limited in part by nitrogen (N) availability, but changes in N during tropical forest succession have rarely been quantified. We explored N cycle dynamics across a chronosequence of secondary tropical forests in the Mata Atlântica of Bahia, Brazil in order to understand how quickly the N cycle recuperates. We hypothesized that N fixation would decline over the course of succession as N availability and N gaseous losses increased. We measured N fixation, KCl-extractable N, net mineralization and nitrification, resin-strip sorbed N, gaseous N emissions and the soil δ15N in stands that were 20, 35, 50, and > 50 years old. Contrary to our initial hypothesis, we found no significant differences between stand ages in any measured variable. Our findings suggest that secondary forests in this region of the Atlantic forest reached pre-disturbance N cycling dynamics after just 20 years of succession. This result contrasts with previous study in the Amazon, where the N cycle recovered slowly after abandonment from pasture reaching pre-disturbance N cycling levels after ~50 years of succession. Our results suggest the pace of the N cycle, and perhaps tropical secondary forest, recovery, may vary regionally.
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Affiliation(s)
- Joy B Winbourne
- The Institute at Brown for Environment and Society, Brown University, Box 1951, Providence, RI, 02912, USA.
| | - Aida Feng
- The Institute at Brown for Environment and Society, Brown University, Box 1951, Providence, RI, 02912, USA
| | - Lovinia Reynolds
- The Institute at Brown for Environment and Society, Brown University, Box 1951, Providence, RI, 02912, USA
| | - Daniel Piotto
- Centro de Formação em Ciências Agroflorestais, Universidade Federal do Sul da Bahia, Ilhéus-BA, Brazil
| | - Meredith G Hastings
- The Institute at Brown for Environment and Society, Brown University, Box 1951, Providence, RI, 02912, USA
- Department of Earth, Environmental, and Planetary Sciences, Brown University, Box 1846, Providence, RI, 02912, USA
| | - Stephen Porder
- The Institute at Brown for Environment and Society, Brown University, Box 1951, Providence, RI, 02912, USA
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