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Wall-to-Wall Mapping of Forest Biomass and Wood Volume Increment in Italy
Giannetti , Francesca , Chirici , Gherardo , Vangi , Elia , Corona , P. , Maselli , Fabio , Chiesi , Marta , D'Amico , Giovanni , Puletti , Nicola
remote sensing forest biomass forest increment mediterranean forest national forest inventories
Mostra abstract
Several political initiatives aim to achieve net-zero emissions by the middle of the twenty-first century. In this context, forests are crucial as a carbon sink to store unavoidable emissions. Assessing the carbon sequestration potential of forest ecosystems is pivotal to the availability of accurate forest variable estimates for supporting international reporting and appropriate forest management strategies. Spatially explicit estimates are even more important for Mediterranean countries such as Italy, where the capacity of forests to act as sinks is decreasing due to climate change. This study aimed to develop a spatial approach to obtain high-resolution maps of Italian forest above-ground biomass (ITA-BIO) and current annual volume increment (ITA-CAI), based on remotely sensed and meteorological data. The ITA-BIO estimates were compared with those obtained with two available biomass maps developed in the framework of two international projects (i.e., the Joint Research Center and the European Space Agency biomass maps, namely, JRC-BIO and ESA-BIO). The estimates from ITA-BIO, JRC-BIO, ESA-BIO, and ITA-CAI were compared with the 2nd Italian NFI (INFC) official estimates at regional level (NUT2). The estimates from ITA-BIO are in good agreement with the INFC estimates (R<sup>2</sup> = 0.95, mean difference = 3.8 t ha<sup>−1</sup>), while for JRC-BIO and ESA-BIO, the estimates show R<sup>2</sup> of 0.90 and 0.70, respectively, and mean differences of 13.5 and of 21.8 t ha<sup>−1</sup> with respect to the INFC estimates. ITA-CAI estimates are also in good agreement with the INFC estimates (R<sup>2</sup> = 0.93), even if they tend to be slightly biased. The produced maps are hosted on a web-based forest resources management Decision Support System developed under the project AGRIDIGIT (ForestView) and represent a key element in supporting the new Green Deal in Italy, the European Forest Strategy 2030 and the Italian Forest Strategy. © 2022 by the authors.
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2022
Rivista
Forests
Dettagli
Vol. 13 (12)
DOI
From model selection to maps: A completely design-based data-driven inference for mapping forest resources
Di Biase , Rosa Maria , Fattorini , Lorenzo , Franceschi , Sara , Grotti , Mirko , Puletti , Nicola , Corona , P.
density estimation harmonization model selection predictions pseudopopulation bootstrap regression estimator residuals smoothing parameter spatial interpolation
Mostra abstract
A completely data-driven, design-based sampling strategy is proposed for mapping a forest attribute within the spatial units tessellating a survey region. Based on sample data, a model is selected, and model parameters are estimated using least-squares criteria for predicting the attribute of interest within units as a linear function of a set of auxiliary variables. The spatial interpolation of residuals arising from model predictions is performed by inverse distance weighting. The leave-one-out cross validation procedure is adopted for selecting the smoothing parameter used for interpolation. The densities of the attributes of interest within units are estimated by summing predictions and interpolated residuals. Finally, density estimates are rescaled to match the total estimate over the survey region obtained by the traditional regression estimator with the total estimate obtained from the map as the sum of the density estimates within units. A bootstrap procedure accounts for the uncertainty. The consistency of the strategy is proven by incorporating previous results. A simulation study is performed and an application for mapping wood volume densities in the forest estate of Rincine (Central Italy) is described. © 2022 John Wiley & Sons Ltd.
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2022
Rivista
Environmetrics
Dettagli
Vol. 33 (7)
DOI
MASTREE+: Time-series of plant reproductive effort from six continents
Hacket-Pain , Andrew J. , Foest , Jessie J. , Pearse , Ian S. , LaMontagne , Jalene M. , Koenig , Walter D. , Vacchiano , Giorgio , Bogdziewicz , Michał , Caignard , Thomas , Celebias , Paulina , van Dormolen , Joep , Fernández-Martínez , Marcos , Moris , Jose V. , Palaghianu , Ciprian , Pesendorfer , Mario B. , Satake , Akiko , Schermer , Éliane , Tanentzap , Andrew J. , Thomas , Peter A. , Vecchio , Davide , Wion , Andreas P. , Wohlgemuth , Thomas , Xue , Tingting , Abernethy , Katharine A. , Aravena Acuña , Marie Claire , Barrera , Marcelo Daniel , Barton , Jessica H. , Boutin , Stan A. , Bush , Emma R. , Donoso Calderón , Sergio R. , Carevic , Felipe S. , Castilho , Carolina V. , Manuel Cellini , Juan , Chapman , Colin A. , Chapman , H. M. , Chianucci , Francesco , Costa , Patricia Da , Croisé , Luc , Cutini , Andrea , Dantzer , Ben J. , DeRose , Robert Justin , Dikangadissi , Jean Thoussaint , Dimoto , Edmond , da Fonseca , Fernanda Lopes , Gallo , Leonardo Ariel , Gratzer , Georg , Greene , David F. , Hadad , Martín Ariel , Huertas Herrera , Alejandro , Jeffery , Kathryn J. , Johnstone , Jill F. , Kalbitzer , Urs , Kantorowicz , Władysław , Klimas , Christie Ann , Lageard , Jonathan G.A. , Lane , Jeffrey E. , Lapin , Katharina , Ledwoń , Mateusz , Leeper , Abigail C. , Lencinas , María Vanessa , Lira-Guedes , Ana Cláudia , Lordon , Michael C. , Marchelli , Paula , Marino , Shealyn , Schmidt van Marle , Harald , McAdam , Andrew G. , Momont , Ludovic R.W. , Nicolas , Manuel , de Oliveira Wadt , Lúcia Helena , Panahi , Parisa , Martínez Pastur , Guillermo J. , Patterson , Thomas W. , Luis Peri , Pablo , Piechnik , Łukasz , Pourhashemi , Mehdi , Espinoza Quezada , Claudia , Roig , Fidel Alejandro , Peña-Rojas , Karen A. , Rosas , Yamina Micaela , Schueler , Silvio , Seget , Barbara , Soler , Rosina M. , Steele , Michael A. , Toro Manríquez , Mónica Del Rosario , Tutin , Caroline E.G. , Ukizintambara , Tharcisse , White , Lee J.T. , Yadok , Biplang Godwill , Willis , John L. , Zolles , Anita , Żywiec , Magdalena , Ascoli , Davide
plant reproduction masting demography flowering general flowering recruitment regeneration
Mostra abstract
Significant gaps remain in understanding the response of plant reproduction to environmental change. This is partly because measuring reproduction in long-lived plants requires direct observation over many years and such datasets have rarely been made publicly available. Here we introduce MASTREE+, a data set that collates reproductive time-series data from across the globe and makes these data freely available to the community. MASTREE+ includes 73,828 georeferenced observations of annual reproduction (e.g. seed and fruit counts) in perennial plant populations worldwide. These observations consist of 5971 population-level time-series from 974 species in 66 countries. The mean and median time-series length is 12.4 and 10 years respectively, and the data set includes 1122 series that extend over at least two decades (≥20 years of observations). For a subset of well-studied species, MASTREE+ includes extensive replication of time-series across geographical and climatic gradients. Here we describe the open-access data set, available as a.csv file, and we introduce an associated web-based app for data exploration. MASTREE+ will provide the basis for improved understanding of the response of long-lived plant reproduction to environmental change. Additionally, MASTREE+ will enable investigation of the ecology and evolution of reproductive strategies in perennial plants, and the role of plant reproduction as a driver of ecosystem dynamics. © 2022 The Authors. Global Change Biology published by John Wiley & Sons Ltd.
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2022
Rivista
Global Change Biology
Dettagli
Vol. 28 (9) pp. 3066 - 3082
DOI