Statistical computing meets biodiversity conservation and natural resource management

Introducing the bSims R package for simulating bird point counts

The bSims R package is a highly scientific and utterly addictive bird point count simulator. Highly scientific, because it implements a spatially explicit mechanistic simulation that is based on statistical models widely used in bird point count analysis (i.e. removal models, distance sampling), and utterly addictive because the implementation is designed to allow rapid interactive exploration (via shiny apps) and efficient simulation (supporting various parallel backends), thus elevating the user experience.

Fitting removal models with the detect R package

In a paper recently published in the Condor, titled Evaluating time-removal models for estimating availability of boreal birds during point-count surveys: sample size requirements and model complexity, we assessed different ways of controlling for point-count duration in bird counts using data from the Boreal Avian Modelling Project. As the title indicates, the paper describes a cost-benefit analysis to make recommendations about when to use different types of the removal model. The paper is open access, so feel free to read the whole paper here.

Shiny slider examples with the intrval R package

The intrval R package is lightweight (~11K), standalone (apart from importing from graphics, has exactly 0 non-base dependency), and it has a very narrow scope: it implements relational operators for intervals — very well aligned with the tiny manifesto. In this post we will explore the use of the package in two shiny apps with sliders.

Phylogeny and species traits predict bird detectability

It all started with this paper in Methods in Ecol. Evol. where we looked at detectability of many species. So we wanted to use life history traits to validate our results. But we had to cut the manuscript, and there was this leftover with some neat patterns, but without much focus. It took a few years, and the most positive peer-review experience ever, and the paper is now early view in Ecography. This post is a quick summary of the goodies stuffed inside the lhreg R package that makes the whole analysis reproducible, and provides some functions for similar PGLMM models.

PVA: Publication Viability Analysis, round 3

A friend and colleague of mine, Péter Batáry has circulated news from Nature magazine about the EU freezing innovation funds to Bulgaria. The article had a figure about publication trends for Bulgaria, compared with Romania and Hungary. As I have blogged about such trends in ecology before (here and here), I felt the need to update my PVA models with two years worth of data from WoS.

The progress bar just got a lot cheaper

The pbapply R package that adds progress bar to vectorized functions has been know to accumulate overhead when calling parallel::mclapply with forking (see this post for more background on the issue). Strangely enough, a GitHub issue held the key to the solution that I am going to outline below. Long story short: forking is no longer expensive with pbapply, and as it turns out, it never was.

Publications

Knight, E. C, Sólymos, P., Scott, C., and Bayne, E. M., 2020. Validation prediction: a flexible protocol to increase efficiency of automated acoustic processing for wildlife research. Ecological Applications, xx: xx–xx..

Sólymos, P., Toms, J. D., Matsuoka, S. M., Cumming, S. G., Barker, N. K. S., Thogmartin, W. E., Stralberg, D., Crosby, A. D., Dénes, F. V., Haché, S., Mahon, C. L., Schmiegelow, F. K. A., and Bayne, E. M., 2020. Lessons learned from comparing spatially explicit models and the Partners in Flight approach to estimate population sizes of boreal birds in Alberta, Canada. Condor, xx: xx–xx. —  journal website fulltext PDF supporting material.

Cadieux, P., Boulanger, Y., Cyr, D., Taylor, A. R., Price, D. T., Sólymos, P., Stralberg, D., Chen, H. Y. H., Brecka, A., and Tremblay, J. A., 2020. Projected effects of climate change on boreal bird community accentuated by anthropogenic disturbances in western boreal forest, Canada. Diversity and Distributions, 26: 668–682. —  journal website fulltext PDF.

Roy, C., Michel, N., Handel, C., Van Wilgenburg, S., Burkhalter, J., Gurney, K., Messmer, D., Princé, K., Rushing, C., Saracco, J., Schuster, R., Smith, A. C., Smith, P. A., Sólymos, P., Venier, L., and Zuckerberg, B., 2019. Monitoring boreal avian populations: how can we estimate trends and trajectories from noisy data? Avian Conservation and Ecology, 14(2): 8. —  journal website fulltext PDF.

Yip, D. A., Knight, E. C., Haave-Audet, E., Wilson, S. J., Charchuk, C., Scott, C. D., Sólymos, P., and Bayne, E. M., 2019. Sound level measurements from audio recordings provide objective distance estimates for distance sampling wildlife populations. Remote Sensing in Ecology and Conservation, xx: xx–xx. —  journal website fulltext PDF.