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Henniger H, Huth A, Bohn FJ. A new approach to derive productivity of tropical forests using radar remote sensing measurements. R Soc Open Sci 2023; 10:231186. [PMID: 38026043 PMCID: PMC10663792 DOI: 10.1098/rsos.231186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 10/30/2023] [Indexed: 12/01/2023]
Abstract
Deriving gross & net primary productivity (GPP & NPP) and carbon turnover time of forests from remote sensing remains challenging. This study presents a novel approach to estimate forest productivity by combining radar remote sensing measurements, machine learning and an individual-based forest model. In this study, we analyse the role of different spatial resolutions on predictions in the context of the Radar BIOMASS mission (by ESA). In our analysis, we use the forest gap model FORMIND in combination with a boosted regression tree (BRT) to explore how spatial biomass distributions can be used to predict GPP, NPP and carbon turnover time (τ) at different resolutions. We simulate different spatial biomass resolutions (4 ha, 1 ha and 0.04 ha) in combination with different vertical resolutions (20, 10 and 2 m). Additionally, we analysed the robustness of this approach and applied it to disturbed and mature forests. Disturbed forests have a strong influence on the predictions which leads to high correlations (R2 > 0.8) at the spatial scale of 4 ha and 1 ha. Increased vertical resolution leads generally to better predictions for productivity (GPP & NPP). Increasing spatial resolution leads to better predictions for mature forests and lower correlations for disturbed forests. Our results emphasize the value of the forthcoming BIOMASS satellite mission and highlight the potential of deriving estimates for forest productivity from information on forest structure. If applied to more and larger areas, the approach might ultimately contribute to a better understanding of forest ecosystems.
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Affiliation(s)
- Hans Henniger
- Department of Ecological Modeling, Helmholtz Centre of Environmental Research (UFZ), Permoserstraße 15, Leipzig 04318, Germany
- Institute for Environmental Systems Research, University of Osnabrück, Barbara Straße 12, Osnabrück 49074, Germany
| | - Andreas Huth
- Department of Ecological Modeling, Helmholtz Centre of Environmental Research (UFZ), Permoserstraße 15, Leipzig 04318, Germany
- Institute for Environmental Systems Research, University of Osnabrück, Barbara Straße 12, Osnabrück 49074, Germany
- iDiv German Centre for Integrative Biodiversity Research Halle-Jena-Leipzig, Puschstraße 4, Leipzig 04103, Germany
| | - Friedrich J. Bohn
- Department of Computational Hydrosystems, Helmholtz Centre of Environmental Research (UFZ), Permoserstraße 15, Leipzig 04318, Germany
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Chuang HY, Kiang JF. High-Resolution L-Band TomoSAR Imaging on Forest Canopies with UAV Swarm to Detect Dielectric Constant Anomaly. Sensors (Basel) 2023; 23:8335. [PMID: 37837165 PMCID: PMC10575232 DOI: 10.3390/s23198335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 09/30/2023] [Accepted: 10/07/2023] [Indexed: 10/15/2023]
Abstract
A rigorous TomoSAR imaging procedure is proposed to acquire high-resolution L-band images of a forest in a local area of interest. A focusing function is derived to relate the backscattered signals to the reflectivity function of the forest canopies without resorting to calibration. A forest voxel model is compiled to simulate different tree species, with the dielectric constant modeled with the Maxwell-Garnett mixing formula. Five different inverse methods are applied on two forest scenarios under three signal-to-noise ratios in the simulations to validate the efficacy of the proposed procedure. The dielectric-constant profile of trees can be used to monitor the moisture content of the forest. The use of a swarm of unmanned aerial vehicles (UAVs) is feasible to carry out TomoSAR imaging over a specific area to pinpoint potential spots of wildfire hazards.
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Affiliation(s)
| | - Jean-Fu Kiang
- Graduate Institute of Communication Engineering, National Taiwan University, Taipei 10617, Taiwan
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Huber N, Bugmann H, Cailleret M, Bircher N, Lafond V. Stand-scale climate change impacts on forests over large areas: transient responses and projection uncertainties. Ecol Appl 2021; 31:e02313. [PMID: 33630399 PMCID: PMC8243936 DOI: 10.1002/eap.2313] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Revised: 10/08/2020] [Accepted: 11/30/2020] [Indexed: 06/12/2023]
Abstract
The increasing impacts of climate change on forest ecosystems have triggered multiple model-based impact assessments for the future, which typically focused either on a small number of stand-scale case studies or on large scale analyses (i.e., continental to global). Therefore, substantial uncertainty remains regarding the local impacts over large areas (i.e., regions to countries), which is particularly problematic for forest management. We provide a comprehensive, high-resolution assessment of the climate change sensitivity of managed Swiss forests (~10,000 km2 ), which cover a wide range of environmental conditions. We used a dynamic vegetation model to project the development of typical forest stands derived from a stratification of the Third National Forest Inventory until the end of the 22nd century. Two types of simulations were conducted: one limited to using the extant local species, the other enabling immigration of potentially more climate-adapted species. Moreover, to assess the robustness of our projections, we quantified and decomposed the uncertainty in model projections resulting from the following sources: (1) climate change scenarios, (2) local site conditions, and (3) the dynamic vegetation model itself (i.e., represented by a set of model versions), an aspect hitherto rarely taken into account. The simulations showed substantial changes in basal area and species composition, with dissimilar sensitivity to climate change across and within elevation zones. Higher-elevation stands generally profited from increased temperature, but soil conditions strongly modulated this response. Low-elevation stands were increasingly subject to drought, with strong negative impacts on forest growth. Furthermore, current stand structure had a strong effect on the simulated response. The admixture of drought-tolerant species was found advisable across all elevations to mitigate future adverse climate-induced effects. The largest uncertainty in model projections was associated with climate change scenarios. Uncertainty induced by the model version was generally largest where overall simulated climate change impacts were small, thus corroborating the utility of the model for making projections into the future. Yet, the large influence of both site conditions and the model version on some of the projections indicates that uncertainty sources other than climate change scenarios need to be considered in climate change impact assessments.
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Affiliation(s)
- Nica Huber
- Forest EcologyDepartment of Environmental Systems ScienceInstitute of Terrestrial EcosystemsETH ZurichUniversitätstrasse 16Zurich8092Switzerland
- Remote SensingSwiss Federal Research Institute WSLZürcherstrasse 111Birmensdorf8903Switzerland
| | - Harald Bugmann
- Forest EcologyDepartment of Environmental Systems ScienceInstitute of Terrestrial EcosystemsETH ZurichUniversitätstrasse 16Zurich8092Switzerland
| | - Maxime Cailleret
- Forest EcologyDepartment of Environmental Systems ScienceInstitute of Terrestrial EcosystemsETH ZurichUniversitätstrasse 16Zurich8092Switzerland
- INRAEUMR RECOVERAix‐Marseille University3275 route de CézanneAix‐en‐Provence cedex 5CS40061France
| | - Nicolas Bircher
- Forest EcologyDepartment of Environmental Systems ScienceInstitute of Terrestrial EcosystemsETH ZurichUniversitätstrasse 16Zurich8092Switzerland
| | - Valentine Lafond
- Forest EcologyDepartment of Environmental Systems ScienceInstitute of Terrestrial EcosystemsETH ZurichUniversitätstrasse 16Zurich8092Switzerland
- Department of Forest Resources ManagementFaculty of ForestryForest Sciences CentreUniversity of British Columbia2424 Main MallVancouverBritish ColumbiaV6T 1Z4Canada
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Pellegrini AFA, Hein AM, Cavender-Bares J, Montgomery RA, Staver AC, Silla F, Hobbie SE, Reich PB. Disease and fire interact to influence transitions between savanna-forest ecosystems over a multi-decadal experiment. Ecol Lett 2021; 24:1007-1017. [PMID: 33694319 DOI: 10.1111/ele.13719] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 02/05/2021] [Accepted: 02/11/2021] [Indexed: 11/27/2022]
Abstract
Global change is shifting disturbance regimes that may rapidly change ecosystems, sometimes causing ecosystems to shift between states. Interactions between disturbances such as fire and disease could have especially severe effects, but experimental tests of multi-decadal changes in disturbance regimes are rare. Here, we surveyed vegetation for 35 years in a 54-year fire frequency experiment in a temperate oak savanna-forest ecotone that experienced a recent outbreak of oak wilt. Different fire regimes determined whether plots were savanna or forest by regulating tree abundance (r2 = 0.70), but disease rapidly reversed the effect of fire exclusion, increasing mortality by 765% in unburned forests, but causing relatively minor changes in frequently burned savannas. Model simulations demonstrated that disease caused unburned forests to transition towards a unique woodland that was prone to transition to savanna if fire was reintroduced. Consequently, disease-fire interactions could shift ecosystem resilience and biome boundaries as pathogen distributions change.
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Affiliation(s)
- Adam F A Pellegrini
- Department of Plant Sciences, University of Cambridge, Cambridge, CB2 3EA, UK
| | - Andrew M Hein
- Institute of Marine Sciences, University of California, Santa Cruz, CA, 95060, USA
| | - Jeannine Cavender-Bares
- Department of Ecology, Evolution, and Behavior, University of Minnesota, St. Paul, MI, 55108, USA
| | - Rebecca A Montgomery
- Department of Forest Resources, University of Minnesota, St. Paul, MI, 55108, USA
| | - A Carla Staver
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, 06520, USA
| | - Fernando Silla
- Area of Ecology, Faculty of Biology, Universidad de Salamanca, Salamanca, 37071, Spain
| | - Sarah E Hobbie
- Department of Ecology, Evolution, and Behavior, University of Minnesota, St. Paul, MI, 55108, USA
| | - Peter B Reich
- Department of Forest Resources, University of Minnesota, St. Paul, MI, 55108, USA.,Hawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW, 2753, Australia
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Fischer FJ, Maréchaux I, Chave J. Improving plant allometry by fusing forest models and remote sensing. New Phytol 2019; 223:1159-1165. [PMID: 30897214 DOI: 10.1111/nph.15810] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2018] [Accepted: 03/05/2019] [Indexed: 06/09/2023]
Abstract
Allometry determines how tree shape and function scale with each other, related through size. Allometric relationships help scale processes from the individual to the global scale and constitute a core component of vegetation models. Allometric relationships have been expected to emerge from optimisation theory, yet this does not suitably predict empirical data. Here we argue that the fusion of high-resolution data, such as those derived from airborne laser scanning, with individual-based forest modelling offers insight into how plant size contributes to large-scale biogeochemical processes. We review the challenges in allometric scaling, how they can be tackled by advances in data-model fusion, and how individual-based models can serve as data integrators for dynamic global vegetation models.
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Affiliation(s)
- 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
| | - Isabelle Maréchaux
- AMAP, INRA, IRD, CIRAD, CNRS, University of Montpellier, F-34000, Montpellier, France
| | - 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
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Collalti A, Trotta C, Keenan TF, Ibrom A, Bond‐Lamberty B, Grote R, Vicca S, Reyer CPO, Migliavacca M, Veroustraete F, Anav A, Campioli M, Scoccimarro E, Šigut L, Grieco E, Cescatti A, Matteucci G. Thinning Can Reduce Losses in Carbon Use Efficiency and Carbon Stocks in Managed Forests Under Warmer Climate. J Adv Model Earth Syst 2018; 10:2427-2452. [PMID: 31007835 PMCID: PMC6472666 DOI: 10.1029/2018ms001275] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2018] [Revised: 09/10/2018] [Accepted: 09/16/2018] [Indexed: 05/10/2023]
Abstract
Forest carbon use efficiency (CUE, the ratio of net to gross primary productivity) represents the fraction of photosynthesis that is not used for plant respiration. Although important, it is often neglected in climate change impact analyses. Here we assess the potential impact of thinning on projected carbon cycle dynamics and implications for forest CUE and its components (i.e., gross and net primary productivity and plant respiration), as well as on forest biomass production. Using a detailed process-based forest ecosystem model forced by climate outputs of five Earth System Models under four representative climate scenarios, we investigate the sensitivity of the projected future changes in the autotrophic carbon budget of three representative European forests. We focus on changes in CUE and carbon stocks as a result of warming, rising atmospheric CO2 concentration, and forest thinning. Results show that autotrophic carbon sequestration decreases with forest development, and the decrease is faster with warming and in unthinned forests. This suggests that the combined impacts of climate change and changing CO2 concentrations lead the forests to grow faster, mature earlier, and also die younger. In addition, we show that under future climate conditions, forest thinning could mitigate the decrease in CUE, increase carbon allocation into more recalcitrant woody pools, and reduce physiological-climate-induced mortality risks. Altogether, our results show that thinning can improve the efficacy of forest-based mitigation strategies and should be carefully considered within a portfolio of mitigation options.
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Affiliation(s)
- Alessio Collalti
- Impacts on Agriculture, Forests and Ecosystem Services DivisionFoundation Euro‐Mediterranean Center on Climate Change (CMCC)ViterboItaly
- National Research Council of ItalyInstitute for Agriculture and Forestry Systems in the Mediterranean (CNR‐ISAFOM)RendeItaly
| | - Carlo Trotta
- Department for Innovation in Biological, Agro‐food and Forest SystemsUniversity of TusciaViterboItaly
| | - Trevor F. Keenan
- Earth Sciences DivisionLawrence Berkeley National LaboratoryBerkeleyCAUSA
- Department of Environmental Science Policy and ManagementUniversity of CaliforniaBerkeleyCAUSA
| | - Andreas Ibrom
- Department Environmental EngineeringTechnical University of Denmark (DTU)LyngbyDenmark
| | - Ben Bond‐Lamberty
- Pacific Northwest National LaboratoryJoint Global Change Research Institute at the University of Maryland‐College ParkCollege ParkMDUSA
| | - Ruediger Grote
- Institute of Meteorology and Climate Research (IMK‐IFU)Karlsruhe Institute of TechnologyKarlsruheGermany
| | - Sara Vicca
- Centre of Excellence PLECO (Pant and Vegetation Ecology), Department of BiologyUniversity of AntwerpAntwerpBelgium
| | | | | | | | - Alessandro Anav
- College of Engineering, Mathematics and Physical SciencesUniversity of ExeterExeterUK
| | - Matteo Campioli
- Department Environmental EngineeringTechnical University of Denmark (DTU)LyngbyDenmark
| | - Enrico Scoccimarro
- Climate Simulation and Prediction DivisionFoundation Euro‐Mediterranean Center on Climate Change (CMCC)BolognaItaly
| | - Ladislav Šigut
- Department of Matter and Energy FluxesGlobal Change Research Institute CASBrnoCzech Republic
| | - Elisa Grieco
- Impacts on Agriculture, Forests and Ecosystem Services DivisionFoundation Euro‐Mediterranean Center on Climate Change (CMCC)ViterboItaly
| | - Alessandro Cescatti
- Directorate for Sustainable ResourcesEuropean Commission, Joint Research CentreIspraItaly
| | - Giorgio Matteucci
- National Research Council of ItalyInstitute for Agriculture and Forestry Systems in the Mediterranean (CNR‐ISAFOM)RendeItaly
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