Data underlying the publication: Unraveling drivers of local adaptation through Evolutionary Functional-Structural Plant modelling.
doi: 10.4121/a826cd0b-e818-451b-b005-3afa417fce41
This is a repository of the data presented in the paper entitled "Unraveling drivers of local adaptation through Evolutionary Functional-Structural Plant modelling" by de Vries et.al.. In this ecological study, we present and validate an evolutionary functional-structural plant model, which we use to disentangle the relative contribution of different abiotic and biotic selection pressures on local adaptation in an alpine carnation. The study contains data generated with the mechanistic modelling approach presented in the study, and empirical data collected from in situ populations of D. carthusianorum. This data repository contains the model code, model output, empirical data, and the R scripts used to analyse the data and produce the figures presented in the paper.
- 2024-09-06 first online, published, posted
- ETH Zürich Postdoctoral Fellowship (grant code 19-2 FEL-72) ETH Zürich
- European Union’s Horizon 2020 research and innovation programme under grant agreement No. 678841 (grant code 678841) European Union
- Swiss National Science Foundation (SNF) (grant code 31003A_182675) Swiss National Science Foundation (SNF)
Wageningen University and Research, Department Environmental Science, Wageningen
DATA
- 3,154 bytesMD5:
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README.txt - 1,295,508 bytesMD5:
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Benign Environment.txt - 4,188 bytesMD5:
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custom-functions.R - 120,633 bytesMD5:
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data_carth_s1_2016_NP.csv - 59,831 bytesMD5:
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Dianthus E-FSP.gsz - 31,909 bytesMD5:
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Dianthus Figures.R - 9,606 bytesMD5:
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Germination.csv - 7,705,908 bytesMD5:
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Home Environment.txt - 157,867 bytesMD5:
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In silico populations.zip - 50,646,845 bytesMD5:
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Transplant.txt -
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