A repository with the original data, code and results of the poster titled: Mixed forest model parameterization and integration into simulation platforms as a tool for decision-making processes
Mixed forest model parameterization and integration into simulation platforms as a tool for decision-making processes
💡 Have a look at the original poster here.
🔖 Poster DOI: http://dx.doi.org/10.13140/RG.2.2.27865.94564
Mixed forests are crucial to climate resilience in Mediterranean ecosystems and show great potential for mitigating the effects of climate change. Proper parameterization and integration of mixed-forest models into simulation platforms open the possibility to explore and assess alternative silvicultural paths. In this study, a climate-sensitive growth model for mixed forests was implemented on SIMANFOR, offering parameterizations for 29 species mixtures including the most frequent in Spain. After describing the model implementation process and its potential applications, a case study is presented to show the mixed-model performance, thus using data from the Spanish Fourth National Forest Inventory (SNFI4) and previously developed silviculture scenarios for Castilla and Leon region (Spain). The case study analysed four different mixtures of Pinus sylvestris with Pinus nigra, Pinus pinaster, Fagus sylvatica, and Quercus pyrenaica, which were selected for their complementarity, productivity, and resource-use efficiency. The results show that thinned mixed stands exhibited higher quadratic mean diameter, biomass and carbon content compared to unthinned stands. The differences observed in biomass and carbon allocation among silvicultural scenarios were consistent in all mixtures. This case study shows how simulations can play a crucial role in understanding the potential of different silvicultural alternatives and in orientating forest management guidelines.
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💾 1_data:
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☀️ climate data obtained from WorldClim data
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🌳 tree and plot data obtained from SFNI4 data
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🌱 2_simanfor contains inputs and outputs for all the simulations developed with SIMANFOR. Check out them! There are a lot of metrics unexplored in this work 🪵 🍁
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💻 3_code:
Script Name | Purpose | Input | Output |
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0.0_SFNI4_data_curation.r 0.1_SFNI_functions code to extract data from WorldClim not attached |
Uses the original SFNI4 data to adapt them to the SIMANFOR requirements | SFNI4 data, WorldClim data, 1_data/IFN3_plots* |
1_data/IFN4_* data |
1.0_group_simanfor_results.r |
Reads all the SIMANFOR outputs, complete the calculations and organize them to be graph | 2_simanfor/output/* |
1_data/simulation_results.RData |
1.1_clean_plots_manually.r |
Function created to delete plots that cause noise on the final results | - | - |
1.2_graph_simanfor_results.r |
Code to make graphs of all the interesting variables | 1_data/simulation_results.RData |
4_figures/simulation_graphs/* |
2.0_data_summary.r |
Code to create a data summary of the principal variable with the used plots | 1_data/simulation_results.RData |
4_figures/summary_table.csv |
2.1_location_map.r |
Code to draw a map with the plot locations | 1_data/simulation_results.RData |
IFN4_plots_map_* |
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📊 4_figures: graphs and figures used in the article
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📚 5_bibliography: recompilation of all the references used in the article
The content of this repository is under the MIT license.
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