Valerio Avitabile

Dr. Valerio Avitabile

orcid

Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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13 November 2023 in Nature
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LMLidong Mo
Lidong Mo
CZConstantin M. Zohner
Constantin M. Zohner
PRPeter B. Reich
Peter B. Reich
JLJingjing Liang
Jingjing Liang
Sergio de MiguelSergio de Miguel
Sergio de Miguel
TCThomas W. Crowther
Thomas W. Crowther
Forests are a substantial terrestrial carbon sink, but anthropogenic changes in land use and climate have considerably reduced the scale of this system1. Remote-sensing estimates to quantify carbon losses from global forests2–5 are characterized by considerable uncertainty and we lack a comprehensive ground-sourced evaluation to benchmark these estimates. Here we combine several ground-sourced6 and satellite-derived approaches2,7,8 to evaluate the scale of the global forest carbon potential outside agricultural and urban lands. Despite regional variation, the predictions demonstrated remarkable consistency at a global scale, with only a 12% difference between the ground-sourced and satellite-derived estimates. At present, global forest carbon storage is markedly under the natural potential, with a total deficit of 226 Gt (model range = 151–363 Gt) in areas with low human footprint. Most (61%, 139 Gt C) of this potential is in areas with existing forests, in which ecosystem protection can allow forests to recover to maturity. The remaining 39% (87 Gt C) of potential lies in regions in which forests have been removed or fragmented. Although forests cannot be a substitute for emissions reductions, our results support the idea2,3,9 that the conservation, restoration and sustainable management of diverse forests offer valuable contributions to meeting global climate and biodiversity targets.

11 August 2021 in Earth System Science Data
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Journal Article
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MSMaurizio Santoro
Maurizio Santoro
OCOliver Cartus
Oliver Cartus
NCNuno Carvalhais
Nuno Carvalhais
DRDanaë M. A. Rozendaal
Danaë M. A. Rozendaal
VAValerio Avitabile
Valerio Avitabile
SWSimon Willcock
Simon Willcock
The terrestrial forest carbon pool is poorly quantified, in particular in regions with low forest inventory capacity. By combining multiple satellite observations of synthetic aperture radar (SAR) backscatter around the year 2010, we generated a global, spatially explicit dataset of above-ground live biomass (AGB; dry mass) stored in forests with a spatial resolution of 1 ha. Using an extensive database of 110 897 AGB measurements from field inventory plots, we show that the spatial patterns and magnitude of AGB are well captured in our map with the exception of regional uncertainties in high-carbon-stock forests with AGB >250 Mg ha−1, where the retrieval was effectively based on a single radar observation. With a total global AGB of 522 Pg, our estimate of the terrestrial biomass pool in forests is lower than most estimates published in the literature (426–571 Pg). Nonetheless, our dataset increases knowledge on the spatial distribution of AGB compared to the Global Forest Resources Assessment (FRA) by the Food and Agriculture Organization (FAO) and highlights the impact of a country's national inventory capacity on the accuracy of the biomass statistics reported to the FRA. We also reassessed previous remote sensing AGB maps and identified major biases compared to inventory data, up to 120 % of the inventory value in dry tropical forests, in the subtropics and temperate zone. Because of the high level of detail and the overall reliability of the AGB spatial patterns, our global dataset of AGB is likely to have significant impacts on climate, carbon, and socio-economic modelling schemes and provides a crucial baseline in future carbon stock change estimates. The dataset is available at https://doi.org/10.1594/PANGAEA.894711 (Santoro, 2018).

1 July 2020 in Nature
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GCGuido Ceccherini
Guido Ceccherini
GDGregory Duveiller
Gregory Duveiller
GGGiacomo Grassi
Giacomo Grassi
GLGuido Lemoine
Guido Lemoine
VAValerio Avitabile
Valerio Avitabile
ACAlessandro Cescatti
Alessandro Cescatti

25 August 2021 in Nature
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Journal Article
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ACAida Cuni-Sanchez
Aida Cuni-Sanchez
MSMartin Sullivan
Martin Sullivan
PPPhilip J. Platts
Philip J. Platts
SLSimon L. Lewis
Simon L. Lewis
RMRob Marchant
Rob Marchant
EZEtienne Zibera
Etienne Zibera

3 July 2024 in Nature
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Journal Article
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CBClement Bourgoin
Clement Bourgoin
GCGuido Ceccherini
Guido Ceccherini
MGMarco Girardello
Marco Girardello
CVC. Vancutsem
C. Vancutsem
VAValerio Avitabile
Valerio Avitabile
FAF. Achard
F. Achard
Tropical forest degradation from selective logging, fire and edge effects is a major driver of carbon and biodiversity loss1–3, with annual rates comparable to those of deforestation4. However, its actual extent and long-term impacts remain uncertain at global tropical scale5. Here we quantify the magnitude and persistence of multiple types of degradation on forest structure by combining satellite remote sensing data on pantropical moist forest cover changes4 with estimates of canopy height and biomass from spaceborne6 light detection and ranging (LiDAR). We estimate that forest height decreases owing to selective logging and fire by 15% and 50%, respectively, with low rates of recovery even after 20 years. Agriculture and road expansion trigger a 20% to 30% reduction in canopy height and biomass at the forest edge, with persistent effects being measurable up to 1.5 km inside the forest. Edge effects encroach on 18% (approximately 206 Mha) of the remaining tropical moist forests, an area more than 200% larger than previously estimated7. Finally, degraded forests with more than 50% canopy loss are significantly more vulnerable to subsequent deforestation. Collectively, our findings call for greater efforts to prevent degradation and protect already degraded forests to meet the conservation pledges made at recent United Nations Climate Change and Biodiversity conferences.

8 August 2022 in Nature Ecology & Evolution
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JLJingjing Liang
Jingjing Liang
JGJavier G. P. Gamarra
Javier G. P. Gamarra
NPNicolas Picard
Nicolas Picard
MZMo Zhou
Mo Zhou
BPBryan Pijanowski
Bryan Pijanowski
CHCang Hui
Cang Hui