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      20th‐Century hurricanes leave long‐lasting legacies on tropical forest height and the abundance of a dominant wind‐resistant palm

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          Abstract

          Projected increases in hurricane intensity under a warming climate will have profound effects on many forest ecosystems. One key challenge is to disentangle the effects of wind damage from the myriad factors that influence forest structure and species distributions over large spatial scales. Here, we employ a novel machine learning framework with high‐resolution aerial photos, and LiDAR collected over 115 km 2 of El Yunque National Forest in Puerto Rico to examine the effects of topographic exposure to two hurricanes, Hugo (1989) and Georges (1998), and several landscape‐scale environmental factors on the current forest height and abundance of a dominant, wind‐resistant species, the palm Prestoea acuminata var. montana. Model predictions show that the average density of the palm was 32% greater while the canopy height was 20% shorter in forests exposed to the two storms relative to unexposed areas. Our results demonstrate that hurricanes have lasting effects on forest canopy height and composition, suggesting the expected increase in hurricane severity with a warming climate will alter coastal forests in the North Atlantic.

          Abstract

          Projected increases in hurricane intensity under a warming climate will have profound effects on many forests. We employ a novel machine learning framework with high‐resolution aerial photos and LiDAR collected over El Yunque National Forest in Puerto Rico to examine the effects of hurricanes on the current canopy height and density of Prestoea acuminate, a wind‐resistant palm. Model predictions show that the average density of the palm was 32% greater while the canopy height was 20% shorter in forests exposed to the two storms relative to unexposed areas.

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          The use of the area under the ROC curve in the evaluation of machine learning algorithms

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            R: A Language and Evnironment for Statistical Computing

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              THE DISTRIBUTION OF THE FLORA IN THE ALPINE ZONE.1

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                Author and article information

                Contributors
                mu2126@columbia.edu
                Journal
                Ecol Evol
                Ecol Evol
                10.1002/(ISSN)2045-7758
                ECE3
                Ecology and Evolution
                John Wiley and Sons Inc. (Hoboken )
                2045-7758
                27 November 2023
                November 2023
                : 13
                : 11 ( doiID: 10.1002/ece3.v13.11 )
                : e10776
                Affiliations
                [ 1 ] Department of Ecology Evolution & Environmental Biology Columbia University New York New York USA
                [ 2 ] Department of Statistics Columbia University New York New York USA
                [ 3 ] Biospheric Sciences Laboratory NASA Goddard Space Flight Center Greenbelt Maryland USA
                [ 4 ] Department of Environmental Sciences Universidad de Puerto Rico San Juan Puerto Rico USA
                Author notes
                [*] [* ] Correspondence

                María Uriarte, Department of Ecology Evolution & Environmental Biology, Columbia University, New York, NY 10027, USA.

                Email: mu2126@ 123456columbia.edu

                Author information
                https://orcid.org/0000-0002-0484-0758
                Article
                ECE310776 ECE-2023-06-01009.R2
                10.1002/ece3.10776
                10680431
                38020686
                f7131058-0724-434b-a8d1-43732b9a5da3
                © 2023 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 08 November 2023
                : 04 May 2023
                : 13 November 2023
                Page count
                Figures: 6, Tables: 4, Pages: 11, Words: 7059
                Funding
                Funded by: Division of Environmental Biology , doi 10.13039/100000155;
                Award ID: 0620910
                Funded by: Microsoft , doi 10.13039/100004318;
                Categories
                Ecosystem Ecology
                Global Change Ecology
                Landscape Ecology
                Population Ecology
                Research Article
                Research Articles
                Custom metadata
                2.0
                November 2023
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.3.5 mode:remove_FC converted:27.11.2023

                Evolutionary Biology
                canopy height,machine learning,tropical cyclones
                Evolutionary Biology
                canopy height, machine learning, tropical cyclones

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