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Project properties |
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| Title | Tree species’ distributions - Understanding the Who Where What Why? |
| Group | Plant Ecology and Nature Conservation Group |
| Project type | thesis |
| Credits | 36 |
| Supervisor(s) | Coline Boonman |
| Examiner(s) | Coline Boonman |
| Contact info | coline.boonman@wur.nl |
| Begin date | 2024/01/01 |
| End date | 2025/12/31 |
| Description | Trees are pivotal to global biodiversity, acting as ecosystem engineers and generating habitat to half the world’s known terrestrial flora and fauna. Accelerating global changes are threatening these tree species, where widespread species tend to be less vulnerable than local, rare species. Using the TREECHANGE database, which includes 8,408,454 occurrence records of 41,835 tree species (72.2% of all tree species worldwide), you will be able to address various research questions. Thus, when you are interested to do a macroecological study on tree species’ distribution, come see me!
The project can be approached from different angles, depending on your own interest. The scale you will work on depends on the topic you are interested in; from few to many species and from regional to global. Potential research topics may be related, but are not restricted, to: - Why are some tree species more widespread than others? One potential hypothesis is that more widespread species are better able to adapt to different environments via trait plasticity and greater intra-specific functional diversity. - Some tree species are only found in deserts. How are they able to survive there? Do they have specific traits, or are they strategically distributed in the landscape? - Threatened species are placed on the IUCN Red List, but assessments require a lot of data. Can changes in global anthropogenic pressures explain the upgrading or downgrading of tree species’ extinction risk (i.e. changes in IUCN status)? - Prolonged periods of drought are getting more and more common. What effect will this have on tree communities? Staring date is open for discussion, as no fieldwork is included! |
| Used skills | Data analysis, Spatial analysis, Empirical/Statistical Modelling, R (and/or GoogleEarthEngine/GIS) |
| Requirements | Experience in R and affinity with large datasets and modelling |