A repository with the original data, code and results of: Silviculture alternatives evaluation for managing complex Quercus pyrenaica stands
📜 Manuscript DOI:
Pyrenean oak (Quercus pyrenaica Willd.) is a Mediterranean forest species endemic to the Iberian Peninsula and is highly expanded in the Castilla and León region (Spain). Despite its potential in the wood industry, traditional uses and the lack of profitable management guidelines deteriorated its stands status, reducing the attention of owners and managers towards this species. This study explores the effects of different silvicultural scenarios on Pyrenean oak stands in transforming regular coppice stands into irregular high forests and in managing irregular stands based on a sustainable approach. Considering different criteria to ensure satisfactory forest conditions, predictions about key forest characteristics and various wood products were estimated to attract industry attention to the species’ potential. A clear need to adapt thinning periodicity, intensity, and criteria according to the local conditions of the stand was identified, requiring managers with expertise in irregular forest management. While numerical predictions may be biased, the trends observed under different management styles allow us to rank them according to the management objectives. Future work should aim to increase knowledge of irregular stand management and develop accurate tools to support managers on decision-making processes.
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💾 1_data:
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☀️ climate data obtained from WorldClim data
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🌳 tree and plot inventory data used on each case study is available in .xlsx format
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🌱 2_simanfor contains inputs and outputs (Spanish and English) for all the simulations developed with SIMANFOR. Check out them! There are a lot of metrics unexplored in this paper 🪵 🍁
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💻 3_code:
Script Name | Purpose | Input | Output |
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0_dbh_distribution_inventory.R |
Uses the original inventories to graph its diameter classes distribution | 1_data, WorldClim data | 0_dbh_distribution_inventory |
1_dbh_distribution_simulation.R |
Uses the SIMANFOR simulation results to graph its diameter classes distribution | 2_simanfor/output | 1_dbh_distribution_simulation_1 1_dbh_distribution_simulation_2 |
2.0_group_simanfor_data.R |
Functions created to group SIMANFOR results in a format to graph them | - | - |
2.1_graph_templates.R |
Functions created with templates to graph SIMANFOR results | - | - |
2.2_graph_results.R |
Code that uses both previous scripts to manage and graph SIMANFOR results | 2_simanfor/output | SG02, SO02, SG02*, SO02*, andgrouped_figures graphs |
3_summary_scenarios.R |
Code to summarize SIMANFOR silvicultural paths used in this study | 2_simanfor/output | 3_summary_scenarios |
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📊 4_figures: graphs and figures used on the article
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📚 5_bibliography: recopilation of all the references used on the article
To gain a better understanding of how SIMANFOR works, you can explore its website, GitHub repository, manual, YouTube playlist or even the last paper.
The content of this repository is under the MIT license.
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\ ORCID \ Researchgate \ LinkedIn \ Twitter \ UVa