We offer external services on data/code management and statistical analyses. Your time can be better invested on you project's science, the generation of new ideas, and the writing of publications and proposals.


  • Automated harvesting of information from Tropicos.org, GBIF, GenBank, ... Using APIs or old-school web scraping.

  • LiDAR data processing. Generation of digital terrain models, digital surface models, and canopy height models. Growth estimates in tree height and crown size.

  • Image segmentation to semi-automate crown delineation using high spatial resolution imagery.

  • Spectral and spatial image analyses. Photogrammetry to estimate forest-level and tree-level properties.

  • Data quality control: we can check your data for outliers, missing data, inconsistencies, etc. We write reproducible code for data cleaning and imputation customized to your needs.

  • Meta-academic data. We have used the Microsoft Academic Graph to describe networks of co-authorships, obtain multiple metrics of academic impact, identify gender and age biases, group authors by topics, etc.


  • Null models. Patterns are often influenced by system properties that must be controlled to avoid spurious conclusions, such as species diversity, aggregation of habitat or individuals within species, or differences in body size or abundances. We can critically review your methods and help with the implementation and interpretation of null models to reach more robust conclusions.

  • Clustering and ordination of multidimensional data. From the standard tools in community ecology (PCA, PCoA, NMDS, PCNM) to more general and less used solutions for highly dimensional/disconnected data (curvilinear or non-linear component analysis, Sammon's mapping, LTSA, t-distributed stochastic neighbor embedding).

  • We have much experience with variation partitioning analyses, both using dissimilarity modeling and redundancy analyses. We designed a way to estimate adjusted R-squared in matrix regressions. We improved the stepping stone algorithm so dissimilarity modeling conforms to the standard assumptions of linear modeling. We have worked on the quantification of co-dominance-based community ecology (clustering and ordination).

  • Network analyses and related applications. Many types of ecological data can be expressed as networks, opening the door to using many concepts and algorithms from graph theory. We have worked on the description of food web topologies, detecting cyclic succession through time, description of spatial associations between species, 'death spirals' in trees through the accumulation of damage, ...

  • Structural Equation Modeling. We have worked in the translation between lavaan and sem R packages too.

  • If you are unsure of what you need, we can review your case for free.


  • We have organized introductory and specialized workshops on good practices in analytical workflows and R programming.

  • Review and packaging of R code: if your project has generated a useful body of R code, we can re-organize it, document it, and create a package. You can report it as a broader impact or byproduct of your project.

If you think we could help, just ask: data@oikobit.com.


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Oikobit LLC. 2105 Vista Oeste St NW, Suite E - 1154. Albuquerque, New Mexico 87120, U.S.A.