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

What is new in the intrval R package?

An update (v 0.1-1) of the intrval package was recently published on CRAN. The package simplifies interval related logical operations (read more about the motivation in this post). So what is new in this version? Some of the inconsistencies in the 1st CRAN release have been cleaned up, and I have been pushed hard (see GitHub issue to implement all the 16 interval-to-interval operators. These operators define the open/closed nature of the lower/upper limits of the intervals on the left and right hand side of the o in the middle as in c(a1, b1) %[]o[]% c(a2, b2).

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