Software
Freely available tools developed by the Levi Lab to support quantitative ecology, wildlife management, and biodiversity science.
The Levi Lab develops and releases open-source software tools to support reproducible research in wildlife ecology and conservation. Our tools span web-based simulation platforms, statistical models, and AI-assisted image analysis.
In silico optimization of multiplex PCR primer panels for targeted sequencing. Given candidate primers for many loci, multiplex_wormhole predicts primer-dimer interactions and uses simulated annealing and iterative improvement to choose the combination that minimizes the overall dimer load, with tools for assessing how compatible a finished panel is.
Developed by Maggie Hallerud for noninvasive wildlife genetics, where fecal and hair DNA make efficient multiplexing essential, but applicable to any multiplex PCR targeted-sequencing assay. Available on PyPI as multiplex-wormhole, with a command-line interface and a Python API.
Turns consensus multilocus genotypes from noninvasive samples into unique individuals. Upload a genotype table (SNPs or microsatellites, any panel, any species) and genoID runs five identification methods side by side, from exact matching and mismatch thresholds to likelihood-ratio and Sethi et al. (2016) approaches with an explicit genotyping-error model, so you can see whether the answer comes from the data or from the settings.
It also covers data QC, panel power (P(ID) and P(ID)sib), per-sample confidence, an interactive map of scats coloured by individual, and an optional spatial likelihood that uses home-range size to resolve ambiguous pairs. The app is compiled to WebAssembly and runs entirely in the browser, so unpublished genotypes never leave your machine. Results download as CSV along with an R script that reproduces the run.
A web-based, user-friendly implementation of biodemographic models for assessing the long-term sustainability of subsistence hunting in tropical forests. Users can parameterize wildlife populations, hunting offtake rates, and landscape configurations to project long-term population trajectories.
Originally developed to support wildlife management planning for indigenous communities in Manu National Park, Peru, and subsequently applied across Amazonia and other tropical systems. The beta version was created by Tasman Thenell.
Levi, T., et al. (2009). Modeling the long-term sustainability of indigenous hunting in Manu National Park, Peru. Journal of Applied Ecology 46: 804–814.
Levi, T., et al. (2011). Spatial tools for modeling the sustainability of subsistence hunting in tropical forests. Ecological Applications 21: 1802–1818.
A simulation tool for modeling how forest exclusion zones around individual trees affect seed predation by host-specific enemies (pathogens and herbivores) and the maintenance of tropical tree diversity.
FEZ was developed to accompany our theoretical work demonstrating that tropical forests can maintain hyperdiversity through enemy-mediated mechanisms (Janzen-Connell effects). The simulator allows users to explore how zone size, enemy specificity, and dispersal interact to determine coexistence outcomes.
Levi, T., Barfield, M., Barrantes, S., et al. (2019). Tropical forests can maintain hyperdiversity because of enemies. Proceedings of the National Academy of Sciences.
An open-source platform for collaborative image labeling and the development and deployment of custom computer vision models for ecological research. Njobvu-AI allows research teams to collaboratively annotate camera trap images and train species detection models without requiring deep machine-learning expertise.
Developed by Cara Appel, Ashwin Subramanian, and collaborators, the platform is designed for wildlife ecologists who need scalable, user-friendly AI tools for processing large volumes of camera trap or passive acoustic data.
Appel, C.L., Subramanian, A., Koning, J.S., et al. (2025). Developing custom computer vision models with Njobvu-AI. Ecological Applications.
Koning, J.S., Subramanian, A., Alotaibi, M., et al. (2023). Njobvu-AI: An open-source tool for collaborative image labeling and implementation of computer vision models. ArXiv.
A highly sensitive, accurate, and affordable SNP genotyping method adapted from GT-seq for noninvasive genetic samples (hair, scat, environmental DNA). The approach uses high-throughput amplicon sequencing to genotype wildlife from field-collected samples with minimal DNA input.
This pipeline dramatically reduces the cost of noninvasive genetics studies, making population-level genetic monitoring feasible for a wider range of species and study systems. It has been applied to carnivores across the Pacific Northwest and Alaska.
Eriksson, C.E., Ruprecht, J., Levi, T. (2020). More affordable and effective noninvasive single nucleotide polymorphism genotyping using high-throughput amplicon sequencing. Molecular Ecology Resources 20(6): 1505–1516.