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Laura J. Pollock

Associate Academic Member
Assistant Professor, McGill University, Department of Biology
Research Topics
Computational Biology
Probabilistic Models

Biography

I am an assistant professor of conservation, ecology, evolution and behaviour in the Biology Department at McGill University.

As a quantitative ecologist, I am interested in large-scale patterns of biodiversity at regional, continental or global scales. My research focuses on the effects of climate change on biodiversity, which combines many biodiversity data inputs with predictive models. The second part of my research is focused on optimizations for identifying key biodiversity areas and efficient conservation solutions.

Publications

Advancing EDGE Zones to identify spatial conservation priorities of tetrapod evolutionary history
Sebastian Pipins
Jonathan E. M. Baillie
Alex Bowmer
Laura J. Pollock
Nisha Owen
Rikki Gumbs
2024-09-03
Nature Communications (published)
doi.org
Herbarium collections remain essential in the age of community science
Isaac Eckert
Anne Bruneau
D. Metsger
Simon Joly
T. Dickinson
Laura J. Pollock
2024-08-31
Nature Communications (published)
doi.org
Vulnerability of terrestrial vertebrate food webs to anthropogenic threats in Europe
Louise M. J. O'Connor
Francesca Cosentino
Michael B. J. Harfoot
Luigi Maiorano
Chiara Mancino
Laura J. Pollock
Wilfried Thuiller
2024-03-22
Global Change Biology (published)
doi.org
Plant invasion in Mediterranean Europe: current hotspots and future scenarios
Luigi Cao Pinna
Laure Gallien
Laura J. Pollock
Irena Axmanová
Milan Chytrý
Marco Malavasi
Alicia T. R. Acosta
Juan Antonio Campos
Marta Carboni
The Mediterranean Basin has historically been subject to alien plant invasions that threaten its unique biodiversity. This seasonally dry an… (see more)d densely populated region is undergoing severe climatic and socioeconomic changes, and it is unclear whether these changes will worsen or mitigate plant invasions. Predictions are often biased, as species may not be in equilibrium in the invaded environment, depending on their invasion stage and ecological characteristics. To address future predictions uncertainty, we identified invasion hotspots across multiple biased modelling scenarios and ecological characteristics of successful invaders. We selected 92 alien plant species widespread in Mediterranean Europe and compiled data on their distribution in the Mediterranean and worldwide. We combined these data with environmental and propagule pressure variables to model global and regional species niches, and map their current and future habitat suitability. We identified invasion hotspots, examined their potential future shifts, and compared the results of different modelling strategies. Finally, we generalised our findings by using linear models to determine the traits and biogeographic features of invaders most likely to benefit from global change. Currently, invasion hotspots are found near ports and coastlines throughout Mediterranean Europe. However, many species occupy only a small portion of the environmental conditions to which they are preadapted, suggesting that their invasion is still an ongoing process. Future conditions will lead to declines in many currently widespread aliens, which will tend to move to higher elevations and latitudes. Our trait models indicate that future climates will generally favour species with conservative ecological strategies that can cope with reduced water availability, such as those with short stature and low specific leaf area. Taken together, our results suggest that in future environments, these conservative aliens will move farther from the introduction areas and upslope, threatening mountain ecosystems that have been spared from invasions so far.
2024-03-05
Ecography (published)
doi.org
Novel community data in ecology-properties and prospects.
Florian Hartig
Nerea Abrego
Alex Bush
Jonathan M. Chase
G. Guillera‐Arroita
M. Leibold
Otso T. Ovaskainen
Loïc Pellissier
Maximilian Pichler
Giovanni Poggiato
Laura J. Pollock
Sara Si-moussi
Wilfried Thuiller
Duarte S Viana
D. Warton
Damaris Zurell
Douglas W. Yu
2024-03-01
Trends in Ecology & Evolution (published)
doi.org
arxiv.org
Linking biodiversity, ecosystem function, and Nature’s contributions to people: a macroecological energy flux perspective
Ana Carolina Antunes
Emilio Berti
Ulrich Brose
Myriam R. Hirt
Dirk N. Karger
Louise M. J. O'Connor
Laura J. Pollock
Wilfried Thuiller
Benoit Gauzens
2024-02-01
Trends in Ecology & Evolution (published)
doi.org
Trait‐matching models predict pairwise interactions across regions, not food web properties
Dominique Caron
Ulrich Brose
Miguel Lurgi
F. Guillaume Blanchet
Dominique Gravel
Laura J. Pollock
2024-01-29
Global Ecology and Biogeography (published)
doi.org
Transnational conservation to anticipate future plant shifts in Europe
Yohann Chauvier-Mendes
Laura J. Pollock
Peter H. Verburg
Dirk N. Karger
Loïc Pellissier
Sébastien Lavergne
Niklaus E. Zimmermann
Wilfried Thuiller
2024-01-22
Nature Ecology & Evolution (published)
doi.org
Author Correction: 30×30 biodiversity gains rely on national coordination
Isaac Eckert
Andrea Brown
Dominique Caron
Federico Riva
Laura J. Pollock
2023-11-27
Nature Communications (published)
doi.org
30×30 biodiversity gains rely on national coordination
Isaac Eckert
Andrea Brown
Dominique Caron
Federico Riva
Laura J. Pollock
2023-11-06
Nature Communications (published)
doi.org
Graph embedding and transfer learning can help predict potential species interaction networks despite data limitations
Tanya Strydom
Salomé Bouskila
Francis Banville
Ceres Barros
Dominique Caron
Maxwell J. Farrell
Marie‐Josée Fortin
Benjamin Mercier
Laura J. Pollock
Rogini Runghen
Giulio V. Dalla Riva
Timothée Poisot
Metawebs (networks of potential interactions within a species pool) are a powerful abstraction to understand how large‐scale species inter… (see more)action networks are structured. Because metawebs are typically expressed at large spatial and taxonomic scales, assembling them is a tedious and costly process; predictive methods can help circumvent the limitations in data deficiencies, by providing a first approximation of metawebs. One way to improve our ability to predict metawebs is to maximize available information by using graph embeddings, as opposed to an exhaustive list of species interactions. Graph embedding is an emerging field in machine learning that holds great potential for ecological problems. Here, we outline how the challenges associated with inferring metawebs line‐up with the advantages of graph embeddings; followed by a discussion as to how the choice of the species pool has consequences on the reconstructed network, specifically as to the role of human‐made (or arbitrarily assigned) boundaries and how these may influence ecological hypotheses.
2023-10-19
Methods in Ecology and Evolution (published)
doi.org
Conserving avian evolutionary history can effectively safeguard future benefits for people
Rikki Gumbs
Claudia L. Gray
Michael Hoffmann
Rafael Molina-Venegas
Nisha Owen
Laura J. Pollock
Phylogenetic diversity (PD)—the evolutionary history of a set of species—is conceptually linked to the maintenance of yet-to-be-discover… (see more)ed benefits from biodiversity or “option value.” We used global phylogenetic and utilization data for birds to test the PD option value link, under the assumption that the performance of sets of PD-maximizing species at capturing known benefits is analogous to selecting the same species at a point in human history before these benefits were realized. PD performed better than random at capturing utilized bird species across 60% of tests, with performance linked to the phylogenetic dispersion and prevalence of each utilization category. Prioritizing threatened species for conservation by the PD they encapsulate performs comparably to prioritizing by their functional distinctiveness. However, species selected by each metric show low overlap, indicating that we should conserve both components of biodiversity to effectively conserve a variety of uses. Our findings provide empirical support for the link between evolutionary history and benefits for future generations.
2023-09-20
Science Advances (published)
doi.org