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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

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
Vertebrate species worldwide are currently facing significant declines in many populations. Although we have gained substantial knowledge ab… (see more)out the direct threats that affect individual species, these threats only represent a fraction of the broader vertebrate threat profile, which is also shaped by species interactions. For example, threats faced by prey species can jeopardize the survival of their predators due to food resource scarcity. Yet, indirect threats arising from species interactions have received limited investigation thus far. In this study, we investigate the indirect consequences of anthropogenic threats on biodiversity in the context of European vertebrate food webs. We integrated data on trophic interactions among over 800 terrestrial vertebrates, along with their associated human‐induced threats. We quantified and mapped the vulnerability of various components of the food web, including species, interactions, and trophic groups to six major threats: pollution, agricultural intensification, climate change, direct exploitation, urbanization, and invasive alien species and diseases. Direct exploitation and agricultural intensification were two major threats for terrestrial vertebrate food webs: affecting 34% and 31% of species, respectively, they threaten 85% and 69% of interactions in Europe. By integrating network ecology with threat impact assessments, our study contributes to a better understanding of the magnitude of anthropogenic impacts on biodiversity.
2024-03-01
Global Change Biology (published)
doi.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
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
Food webs are essential for understanding how ecosystems function, but empirical data on the interactions that make up these ecological netw… (see more)orks are lacking for most taxa in most ecosystems. Trait‐based models can fill these data gaps, but their ability to do so has not been widely tested. We test how well these models can extrapolate to new ecological communities both in terms of pairwise predator–prey interactions and higher level food web attributes (i.e. species position, food web‐level properties).Canada, Europe, Tanzania.Current.Terrestrial vertebrates.We train trait‐based models of pairwise trophic interactions on four independent vertebrate food webs (Canadian tundra, Serengeti, alpine south‐eastern Pyrenees and Europe) and evaluate how well these models predict pairwise interactions and network properties of each food web.We find that, overall, trait‐based models predict most interactions and their absence correctly. Performance was best for training and testing on the same food web (AUC > 0.90) and declined with environmental and phylogenetic distances with the strongest loss of performance for the tundra‐Serengeti ecosystems (AUC > 0.75). Network metrics were less well‐predicted than single interactions by our models with predicted food webs being more connected, less modular, and with higher mean trophic levels than observed.Theory predicts that the variability observed in food webs can be explained by differences in trait distributions and trait‐matching relationships. Our finding that trait‐based models can predict many trophic interactions, even in contrasting environments, adds to the growing body of evidence that there are general constraints on interactions and that trait‐based methods can serve as a useful first approximation of food webs in unknown areas. However, food webs are more than the sum of their parts, and predicting network attributes will likely require models that simultaneously predict individual interactions and community constraints.
2024-01-29
Global Ecology and Biogeography (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
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
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