Combinatorial Maps, a New Framework to Model Agroforestry Systems
Agroforestry systems are complex due to the diverse interactions between their elements, and they develop over several decades. Existing numerical models focus either on the structure or on the functions of agroforestry systems. However, both of these aspects are necessary, as function influences st...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
American Association for the Advancement of Science (AAAS)
2023-01-01
|
| Series: | Plant Phenomics |
| Online Access: | https://spj.science.org/doi/10.34133/plantphenomics.0120 |
| _version_ | 1797389769460678656 |
|---|---|
| author | Laëtitia Lemiere Marc Jaeger Marie Gosme Gérard Subsol |
| author_facet | Laëtitia Lemiere Marc Jaeger Marie Gosme Gérard Subsol |
| author_sort | Laëtitia Lemiere |
| collection | DOAJ |
| description | Agroforestry systems are complex due to the diverse interactions between their elements, and they develop over several decades. Existing numerical models focus either on the structure or on the functions of agroforestry systems. However, both of these aspects are necessary, as function influences structure and vice versa. Here, we present a representation of agroforestry systems based on combinatorial maps (which are a type of multidimensional graphs), that allows conceptualizing the structure–function relationship at the agroecosystem scale. We show that such a model can represent the structure of agroforestry systems at multiple scales and its evolution through time. We propose an implementation of this framework, coded in Python, which is available on GitHub. In the future, this framework could be coupled with knowledge based or with biophysical simulation models to predict the production of ecosystem services. The code can also be integrated into visualization tools. Combinatorial maps seem promising to provide a unifying and generic description of agroforestry systems, including their structure, functions, and dynamics, with the possibility to translate to and from other representations. |
| first_indexed | 2024-03-08T23:01:47Z |
| format | Article |
| id | doaj.art-c2315afefb8049bbbaa46c7298c6578c |
| institution | Directory Open Access Journal |
| issn | 2643-6515 |
| language | English |
| last_indexed | 2024-03-08T23:01:47Z |
| publishDate | 2023-01-01 |
| publisher | American Association for the Advancement of Science (AAAS) |
| record_format | Article |
| series | Plant Phenomics |
| spelling | doaj.art-c2315afefb8049bbbaa46c7298c6578c2023-12-15T19:21:55ZengAmerican Association for the Advancement of Science (AAAS)Plant Phenomics2643-65152023-01-01510.34133/plantphenomics.0120Combinatorial Maps, a New Framework to Model Agroforestry SystemsLaëtitia Lemiere0Marc Jaeger1Marie Gosme2Gérard Subsol3ABSys, Univ Montpellier, CIHEAM-IAMM, CIRAD, INRAE, Institut Agro, Montpellier, France.CIRAD, UMR AMAP, F-34398 Montpellier, France.ABSys, Univ Montpellier, CIHEAM-IAMM, CIRAD, INRAE, Institut Agro, Montpellier, France.Research-Team ICAR, LIRMM, Univ Montpellier, CNRS, Montpellier, France.Agroforestry systems are complex due to the diverse interactions between their elements, and they develop over several decades. Existing numerical models focus either on the structure or on the functions of agroforestry systems. However, both of these aspects are necessary, as function influences structure and vice versa. Here, we present a representation of agroforestry systems based on combinatorial maps (which are a type of multidimensional graphs), that allows conceptualizing the structure–function relationship at the agroecosystem scale. We show that such a model can represent the structure of agroforestry systems at multiple scales and its evolution through time. We propose an implementation of this framework, coded in Python, which is available on GitHub. In the future, this framework could be coupled with knowledge based or with biophysical simulation models to predict the production of ecosystem services. The code can also be integrated into visualization tools. Combinatorial maps seem promising to provide a unifying and generic description of agroforestry systems, including their structure, functions, and dynamics, with the possibility to translate to and from other representations.https://spj.science.org/doi/10.34133/plantphenomics.0120 |
| spellingShingle | Laëtitia Lemiere Marc Jaeger Marie Gosme Gérard Subsol Combinatorial Maps, a New Framework to Model Agroforestry Systems Plant Phenomics |
| title | Combinatorial Maps, a New Framework to Model Agroforestry Systems |
| title_full | Combinatorial Maps, a New Framework to Model Agroforestry Systems |
| title_fullStr | Combinatorial Maps, a New Framework to Model Agroforestry Systems |
| title_full_unstemmed | Combinatorial Maps, a New Framework to Model Agroforestry Systems |
| title_short | Combinatorial Maps, a New Framework to Model Agroforestry Systems |
| title_sort | combinatorial maps a new framework to model agroforestry systems |
| url | https://spj.science.org/doi/10.34133/plantphenomics.0120 |
| work_keys_str_mv | AT laetitialemiere combinatorialmapsanewframeworktomodelagroforestrysystems AT marcjaeger combinatorialmapsanewframeworktomodelagroforestrysystems AT mariegosme combinatorialmapsanewframeworktomodelagroforestrysystems AT gerardsubsol combinatorialmapsanewframeworktomodelagroforestrysystems |