"The value of a scientist lies more in their acquired skills and experiences than the facts in their heads." -- Bruno Sánchez-Andrade Nuño, https://book.impactscience.dev/

Data manipulation and analyses

As an R enthousiast, I mainly used this progamming language. I present some output examples below.

Statistical Modeling

Effect of mycorrhizal proportion on tree species diversity using a generalized linear mixed-effect model with a truncated Poisson distribution.

Estimation of the effect of time on diversity using Markov chain Monte Carlo method implemented in a Bayesian framework.

Path analysis linking soil chemistry with soil biota and plant diversity in primary succession

Multivariate approach Ordination using principal component analysis of the community structure of earthworms in four proglacial plains at two sampling depths.

Constrained ordination of a fungal community by soil chemistry variables using a distance-based redundancy analysis with Bray-Curtis dissimilarities.

Spatial visualization Ectomycorrhizal tree proportion across the globe (using publsihed data).

Large database management Tree richness at the community scale across the U.S. calculated for ~85,00 plots containing >2 million trees, retrieved from the FIA database (https://apps.fs.usda.gov/fia/datamart/).

Meta-analyses
I have followed several workshops given about meta-analysis and hope to put it in practice very soon!