I have led or helped perform greenhouse, field, and analytical/simulation experiments. I hold a MSc in Ecology and Evolutionary Biology and a BSc in Environmental Biology and Psychology (double major).

Research highlights

How can we predict soil variation across forested landscapes?

Machine learning models combine soil (response) and environmental (predictor) data to predict continuous soil variation across space

Soils are important to consider in forestry for many reasons. For example, soils modulate the types of trees and other biota that can survive in an area; soils signal the presence of important ecosites; soils modulate nutrient and carbon cycling; and soils determine the type of development that can occur on a given unit of land. However, detailed soils information are often neglected in forestry management because high resolution soil maps are unavailable.

I am using machine learning models to formalize the relationship between soil attributes and environmental data in Ontario forests in an effort to generate digital soil maps1 that can be integrated into sustainable forestry management programs.


Publication: Blackford C, Heung B, Baldwin K, Fleming RL, Hazlett PW, Morris DM, Uhlig P, Webster K. 2020. Digital Soil Mapping workflow for forest resource applications: A case study in the Hearst Forest, Ontario. Canadian Journal of Forest Research. doi: 10.1139/cjfr-2020-0066


Past research

Do phenological differences facilitate or inhibit coexistence between competitors?

Ecological theory has contrasting predictions surrounding if species with similar phenologies are more, or less likely to coexist with each other2, 3. On one hand, phenological differences could reduce competition for resources between species. On the other hand, a species with an early phenology could reduce resources available to later species and thus limit coexistence. In a greenhouse experiment, I manipulated germination timing of two competing grass species and quantified how this phenological separation affected their ability to co-exist with each other.

Publication: Blackford, C., Germain, R.M., and Gilbert, B. 2020. Species differences in phenology shape coexistence. The American Naturalist. doi: 10.1086/708719

Greenhouse design (Vulpia microstachys and Vulpia octoflora competing within pots)


How can we incorporate connectivity in Marine Protected Area design?

Canada has committed to protecting their marine and terrestrial ecosystems in an effort to conserve biodiversity4 . The effectiveness of these protected areas depends their design and implementation5. Specifically, these protected areas should be connected such that species can move between them safely.

In my MSc, I used the Canadian Pacific Ocean as a study system to understand how Marine Protected Areas should be configured to ensure connectivity exists for multiple species in the present, and under scenarios of climate change in the future.

Publication: Blackford, C., Krkošek, M., and Fortin, M.J. 2021. A data-limited modeling approach for conserving connectivity in Marine Protected Area Networks. doi: 10.1007/s00227-021-03890-3

Conservation prioritization model of the British Columbia coast based on connectivity analysis.


How will climate change impact species ranges?

A common prediction is that climate change will result in a contracted southern range and extended northern range for species above the equator 6, 7. As an undergraduate, I ran species distribution models to test if climate change is likely to shift Boreal tree ranges north and if tree species south of Ontario are likely to expand north into the Boreal forest.

Tree project pic
Climate suitability maps created in Maxent for Black Spruce (Picea mariana) for current climate (2000s) and projected future climate (2050s). Map extent shows western Ontario, Minnesota, Wisconsin, Michigan, Iowa, and Illinois.


1. McBratney, A.B., Mendonça Santos, M.L., and Minasny, B. 2003. On digital soil mapping. Geoderma 117: 3-52.
2. Chesson, P. 2000. Mechanisms of Maintenance of Species Diversity. Annual Review of Ecology and Systematics 31: 343-366.
3. Godoy, O., and Levine, J.M. 2014. Phenology effects on invasion success: insights from coupling field experiments to coexistence theory. Ecology 95: 726-736.
4. Convention on Biological Diversity. 2010. Tenth meeting of the Conference of the Parties to the Convention on Biological Diversity, Decision X/2. Nagoya, Japan. 18 – 29, October 2010.
5. Gaines, S.D., Lester, S.E., Grorud-Colvert, K., Costello, C., and Pollnac, R. 2010. Evolving science of marine reserves: New developments and emerging research frontiers. PNAS 107: 18251-18255.
6. Parmesan, C., and Yohe, G. 2003. A globally coherent fingerprint of climate change impacts across natural systems. Nature 421: 37-42.
7. Davis, M.B., and Shaw, R.G. 2001. Range shifts and adaptive responses to Quaternary climate change. Science 292: 673-679.

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