Talks

I was invited to represent ABMI at the Multi-taxa Monitoring in North America symposium, North American Congress for Conservation Biology, Madison, Wisconsin, July 18, 2016. The symposium was organized by Michael Lucid (Idaho Department of Fish and Game). It was great to see all the good work happening in North America, and the commitment to push the agenda of multi-taxa monitoring against critics and scarce funding (of course Alberta ‘has all the oil money’).

We presented a poster at the ICCB/ECCB 2015 congress in Montpellier, France, that summarized our research on single visit methodology.

The ABMI hosted its 2nd annual Speakers’ Series ‘Better Environmental Management Through Monitoring 2015’ to understand distribution of biodiversity and to inform sustainable resource development and biological conservation in Alberta.

I presented a guest lecture ‘Data cloning: bridging the Bayesian and frequentist statistical paradigms’, at the Budapest R User Group meetup, Budapest, Hungary.

Discussing problems vs. finding solutions: an operational framework for dealing with imperfect detection in species distribution modelling, International Statistical Ecology Conference 2014, Montpellier, France.

Development of predictive models for migratory landbirds and estimation of cumulative effects of human development in the oil sands areas of Alberta, Joint Oil Sands Monitoring: Cause-Effects Assessment of Oil Sands Activity on Migratory Landbirds, Edmonton, AB, 2014.

Statistical computing meets biodiversity conservation and natural resource management

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.

ABMI (6) ARU (1) C (1) CRAN (1) Hungary (2) JOSM (2) PVA (2) PVAClone (1) QPAD (1) R (18) R packages (1) bioacoustics (1) biodiversity (1) birds (2) course (2) data (1) data cloning (4) dclone (3) dependencies (1) detect (2) detectability (1) footprint (3) forecasting (1) functions (3) intrval (3) lhreg (1) mefa4 (1) monitoring (2) pbapply (5) phylogeny (1) plyr (1) poster (2) processing time (2) progress bar (4) publications (2) report (1) sector effects (1) single visit (1) site (1) slides (2) special (3) species (1) trend (1) tutorials (2) video (4)