Productivity-Based Land Suitability and Management Sensitivity Analysis: The Eucalyptus <i>E. urophylla</i> × <i>E. grandis</i> Case
Eucalyptus plantations are productive and short rotation forests prevalent in tropical areas that experience fast expansion and face controversies in ecological issues. In this study, we perform a systematic analysis of factors influencing eucalyptus growth through plot records from the National For...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-02-01
|
| Series: | Forests |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-4907/13/2/340 |
| _version_ | 1797480166763528192 |
|---|---|
| author | Miaoying Shi Jintao Xu Shilei Liu Zhenci Xu |
| author_facet | Miaoying Shi Jintao Xu Shilei Liu Zhenci Xu |
| author_sort | Miaoying Shi |
| collection | DOAJ |
| description | Eucalyptus plantations are productive and short rotation forests prevalent in tropical areas that experience fast expansion and face controversies in ecological issues. In this study, we perform a systematic analysis of factors influencing eucalyptus growth through plot records from the National Forest Inventories and satellite images. We find primary restricting factors for eucalyptus growth via machine learning algorithms with random forests and accumulated local effects plots, as conventional forest growth models are inadequate to calculate the causal effect with the large number of environmental and socioeconomic factors. As a result, despite common belief that temperature affects eucalyptus growth the most, we find that precipitation is the most evident restricting factor for eucalyptus growth. We then identify and rank key factors that affect timber growth, such as tree density, rotation period, and wood ownership. Finally, we suggest optimal management and planting strategies for local farmers and policymakers to facilitate eucalyptus growth. |
| first_indexed | 2024-03-09T21:56:07Z |
| format | Article |
| id | doaj.art-c9b474cf329b4232bcc092c39be26802 |
| institution | Directory Open Access Journal |
| issn | 1999-4907 |
| language | English |
| last_indexed | 2024-03-09T21:56:07Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Forests |
| spelling | doaj.art-c9b474cf329b4232bcc092c39be268022023-11-23T19:58:00ZengMDPI AGForests1999-49072022-02-0113234010.3390/f13020340Productivity-Based Land Suitability and Management Sensitivity Analysis: The Eucalyptus <i>E. urophylla</i> × <i>E. grandis</i> CaseMiaoying Shi0Jintao Xu1Shilei Liu2Zhenci Xu3School of Social and Public Administration, East China University of Science and Technology, Xuhui District, Shanghai 200237, ChinaNational School of Development, Peking University, Beijing 100871, ChinaSchool of Environment & Natural Resources, Renmin University of China, Beijing 100872, ChinaDepartment of Geography, The University of Hong Kong (HKU), Hong Kong 999077, ChinaEucalyptus plantations are productive and short rotation forests prevalent in tropical areas that experience fast expansion and face controversies in ecological issues. In this study, we perform a systematic analysis of factors influencing eucalyptus growth through plot records from the National Forest Inventories and satellite images. We find primary restricting factors for eucalyptus growth via machine learning algorithms with random forests and accumulated local effects plots, as conventional forest growth models are inadequate to calculate the causal effect with the large number of environmental and socioeconomic factors. As a result, despite common belief that temperature affects eucalyptus growth the most, we find that precipitation is the most evident restricting factor for eucalyptus growth. We then identify and rank key factors that affect timber growth, such as tree density, rotation period, and wood ownership. Finally, we suggest optimal management and planting strategies for local farmers and policymakers to facilitate eucalyptus growth.https://www.mdpi.com/1999-4907/13/2/340land suitabilitymanagement sensitivityforest plantationtimber volumemachine learning |
| spellingShingle | Miaoying Shi Jintao Xu Shilei Liu Zhenci Xu Productivity-Based Land Suitability and Management Sensitivity Analysis: The Eucalyptus <i>E. urophylla</i> × <i>E. grandis</i> Case Forests land suitability management sensitivity forest plantation timber volume machine learning |
| title | Productivity-Based Land Suitability and Management Sensitivity Analysis: The Eucalyptus <i>E. urophylla</i> × <i>E. grandis</i> Case |
| title_full | Productivity-Based Land Suitability and Management Sensitivity Analysis: The Eucalyptus <i>E. urophylla</i> × <i>E. grandis</i> Case |
| title_fullStr | Productivity-Based Land Suitability and Management Sensitivity Analysis: The Eucalyptus <i>E. urophylla</i> × <i>E. grandis</i> Case |
| title_full_unstemmed | Productivity-Based Land Suitability and Management Sensitivity Analysis: The Eucalyptus <i>E. urophylla</i> × <i>E. grandis</i> Case |
| title_short | Productivity-Based Land Suitability and Management Sensitivity Analysis: The Eucalyptus <i>E. urophylla</i> × <i>E. grandis</i> Case |
| title_sort | productivity based land suitability and management sensitivity analysis the eucalyptus i e urophylla i i e grandis i case |
| topic | land suitability management sensitivity forest plantation timber volume machine learning |
| url | https://www.mdpi.com/1999-4907/13/2/340 |
| work_keys_str_mv | AT miaoyingshi productivitybasedlandsuitabilityandmanagementsensitivityanalysistheeucalyptusieurophyllaiiegrandisicase AT jintaoxu productivitybasedlandsuitabilityandmanagementsensitivityanalysistheeucalyptusieurophyllaiiegrandisicase AT shileiliu productivitybasedlandsuitabilityandmanagementsensitivityanalysistheeucalyptusieurophyllaiiegrandisicase AT zhencixu productivitybasedlandsuitabilityandmanagementsensitivityanalysistheeucalyptusieurophyllaiiegrandisicase |