Species Ecological Envelopes under Climate Change Scenarios: A Case Study for the Main Two Wood-Production Forest Species in Portugal

Species ecological envelope maps were obtained for the two main Portuguese wood-production species (<i>Eucalyptus globulus</i> Labill. and <i>Pinus pinaster</i> Aiton) and projected future climate change scenarios. A machine learning approach was used to understand the most i...

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Main Authors: Cristina Alegria, Natália Roque, Teresa Albuquerque, Saki Gerassis, Paulo Fernandez, Maria Margarida Ribeiro
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Forests
Subjects:
Online Access:https://www.mdpi.com/1999-4907/11/8/880
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spelling doaj-c4e27a6c56254cefac7b668f395b3e492020-11-25T03:36:10ZengMDPI AGForests1999-49072020-08-011188088010.3390/f11080880Species Ecological Envelopes under Climate Change Scenarios: A Case Study for the Main Two Wood-Production Forest Species in PortugalCristina Alegria0Natália Roque1Teresa Albuquerque2Saki Gerassis3Paulo Fernandez4Maria Margarida Ribeiro5Instituto Politécnico de Castelo Branco, 6000-084 Castelo Branco, PortugalInstituto Politécnico de Castelo Branco, 6000-084 Castelo Branco, PortugalInstituto Politécnico de Castelo Branco, 6000-084 Castelo Branco, PortugalDepartment of Natural Resources and Environmental Engineering, University of Vigo, Lagoas Marcosende, 36310 Vigo, SpainInstituto Politécnico de Castelo Branco, 6000-084 Castelo Branco, PortugalInstituto Politécnico de Castelo Branco, 6000-084 Castelo Branco, PortugalSpecies ecological envelope maps were obtained for the two main Portuguese wood-production species (<i>Eucalyptus globulus</i> Labill. and <i>Pinus pinaster</i> Aiton) and projected future climate change scenarios. A machine learning approach was used to understand the most influential environmental variables that may explain current species distribution and productivity. <i>Background and Objectives: </i>The aims of the study were: (1) to map species potential suitability areas using ecological envelopes in the present and to project them in the future under climate change scenarios; (2) to map species current distributions; (3) to map species current productivity; and (4) to explore the most influential environmental variables on species current distribution and productivity. <i>Materials and Methods:</i> Climate, elevation data, and soil data sets were used to obtain present and future species ecological envelopes under two climate change scenarios. The official land cover maps were used to map species distributions. Forest inventory data were used to map the species productivity by geostatistical techniques. A Bayesian machine learning approach, supported by species distributions and productivity data, was used to explore the most influential environmental variables on species distribution and productivity and to validate species ecological envelopes. <i>Results:</i> The species ecological envelope methodology was found to be robust. Species’ ecological envelopes showed a high potential for both species’ afforestation. In the future, a decrease in the country’s area potentiality was forecasted for both species. The distribution of maritime pine was found to be mainly determined by precipitation-related variables, but the elevation and temperature-related variables were very important to differentiate species productivity. For eucalypts, species distribution was mainly explained by temperature-related variables, as well as the species productivity. <i>Conclusions:</i> These findings are key to support recommendations for future afforestation and will bring value to policy-makers and environmental authorities in policy formulation under climate change scenarios.https://www.mdpi.com/1999-4907/11/8/880ecological envelopesclimate change scenariosspecies distributionspecies productivitymachine learning
collection DOAJ
language English
format Article
sources DOAJ
author Cristina Alegria
Natália Roque
Teresa Albuquerque
Saki Gerassis
Paulo Fernandez
Maria Margarida Ribeiro
spellingShingle Cristina Alegria
Natália Roque
Teresa Albuquerque
Saki Gerassis
Paulo Fernandez
Maria Margarida Ribeiro
Species Ecological Envelopes under Climate Change Scenarios: A Case Study for the Main Two Wood-Production Forest Species in Portugal
Forests
ecological envelopes
climate change scenarios
species distribution
species productivity
machine learning
author_facet Cristina Alegria
Natália Roque
Teresa Albuquerque
Saki Gerassis
Paulo Fernandez
Maria Margarida Ribeiro
author_sort Cristina Alegria
title Species Ecological Envelopes under Climate Change Scenarios: A Case Study for the Main Two Wood-Production Forest Species in Portugal
title_short Species Ecological Envelopes under Climate Change Scenarios: A Case Study for the Main Two Wood-Production Forest Species in Portugal
title_full Species Ecological Envelopes under Climate Change Scenarios: A Case Study for the Main Two Wood-Production Forest Species in Portugal
title_fullStr Species Ecological Envelopes under Climate Change Scenarios: A Case Study for the Main Two Wood-Production Forest Species in Portugal
title_full_unstemmed Species Ecological Envelopes under Climate Change Scenarios: A Case Study for the Main Two Wood-Production Forest Species in Portugal
title_sort species ecological envelopes under climate change scenarios: a case study for the main two wood-production forest species in portugal
publisher MDPI AG
series Forests
issn 1999-4907
publishDate 2020-08-01
description Species ecological envelope maps were obtained for the two main Portuguese wood-production species (<i>Eucalyptus globulus</i> Labill. and <i>Pinus pinaster</i> Aiton) and projected future climate change scenarios. A machine learning approach was used to understand the most influential environmental variables that may explain current species distribution and productivity. <i>Background and Objectives: </i>The aims of the study were: (1) to map species potential suitability areas using ecological envelopes in the present and to project them in the future under climate change scenarios; (2) to map species current distributions; (3) to map species current productivity; and (4) to explore the most influential environmental variables on species current distribution and productivity. <i>Materials and Methods:</i> Climate, elevation data, and soil data sets were used to obtain present and future species ecological envelopes under two climate change scenarios. The official land cover maps were used to map species distributions. Forest inventory data were used to map the species productivity by geostatistical techniques. A Bayesian machine learning approach, supported by species distributions and productivity data, was used to explore the most influential environmental variables on species distribution and productivity and to validate species ecological envelopes. <i>Results:</i> The species ecological envelope methodology was found to be robust. Species’ ecological envelopes showed a high potential for both species’ afforestation. In the future, a decrease in the country’s area potentiality was forecasted for both species. The distribution of maritime pine was found to be mainly determined by precipitation-related variables, but the elevation and temperature-related variables were very important to differentiate species productivity. For eucalypts, species distribution was mainly explained by temperature-related variables, as well as the species productivity. <i>Conclusions:</i> These findings are key to support recommendations for future afforestation and will bring value to policy-makers and environmental authorities in policy formulation under climate change scenarios.
topic ecological envelopes
climate change scenarios
species distribution
species productivity
machine learning
url https://www.mdpi.com/1999-4907/11/8/880
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