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Improving conservation outcomes for Insects

Insect conservation has many challenges, particularly because many species are data sparse, many species need assessments, and we need to better translate data to decisions. 


At the EDS lab we are addressing all of these gaps, while working with government, non-governmental organizations, and private companies.  We are working on or leading the following initiatives:

  • Jayme is incorporating the use of occupancy models in the assessment process done by the Committee on the Status of Endangered Wildlife in Canada (COSEWIC). Our goal is to expedite the process of assessments for insects by using multi-species occupancy models.

  • Teagan is using multi-species occupancy models to model the changes in distribution of Suckley's cuckoo bumblebee.

  • Melissa is co-leading the Morpho NCEAS working group to synthesize data on plant-pollinator interactions to develop a conservation tool to guide the planting of native plants for insect habitat restoration. This work is partly inspired by her previous development of a shiny app for British Columbia. 

  • Vaughn is working with Xerces and IUCN to provide data on western skippers. 

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Engagement with policy

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In the EDS lab we aim to make our science relevant for policy makers.


Melissa participated as a panelist in the 50th anniversary celebration of the Endangered Species Act. Where she discussed the challenges in the biodiversity crisis with Members of Congress, administration officials, tribal members, and policy experts. Also, Melissa participated in a workshop to co-create a multispecies constitution, organized by the Berggruen Institute. This event drew from an interdisciplinary group of scholars where she was the only ecologist.


Melissa currently serves in the executive committee of the group 50 Voices for Endangered Species. Our mission is to expand access to the breadth and depth of rigorous research across disciplines in defense of biodiversity and the people who depend on it. 


Research on teaching statistics and R programming

We are recognizing the value of teaching statistics simultaneously with the programs that will provide plentiful opportunities to our students. However, programs such as R require basic levels of programming that most life science undergraduates do not have. Both statistics and programming are hard subjects that present a high intrinsic cognitive load. 

I used the framework for instructional design provided by cognitive load theory to design a series of homework assignments to teach R in statistics courses. I tested the effectiveness of these assignments using student grades and surveys.

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This research was supported by the Public Scholar Initiative at UBC and the CIRTL network

You can find our event on engaging education for the public good here.

Relevant publications: 

Successful integration of data science in undergraduate biostatistics courses using cognitive load theory.

Guzman, L. M., Pennell, M.W., Nikelski, E., Srivastava, D.S.

CBE-Life Science Education. 18(4), ar48-es5.



Teaching conservation data science in Colombia

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Through my training I have developed and taught courses in data science and statistics. I have now partnered with Ecodiversa Tropical, an non-profit organization devoted to the conservation of biodiversity in Colombia, to develop training modules on conservation data science for undergraduate students. Our first set of workshops can be found here. We were recently funded by the Experiment Foundation.

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