Bio
Veronica is a quantitative ecologist and science communicator focused on understanding biodiversity-human relationships within the contexts of conservation, sustainability, and ecological theory. She advances methods in ecological and synthesis research by creating innovative, open-source databases, modeling tools, and frameworks that have been widely adopted for conservation and industrial applications. Her award-winning research has been published in leading journals such as Methods in Ecology & Evolution and Nature Ecology & Evolution, and has consistently gained global media attention, being featured in The New York Times, The Washington Post, CNN, and Smithsonian Magazine.
Veronica earned a dual Ph.D. in Fisheries & Wildlife and Ecology, Evolution, & Behavior from Michigan State University in 2024. She also holds a dual M.Sc. in International Nature Conservation from Göttingen University (Germany) and Lincoln University (New Zealand). She has studied and worked in many places around the world—from as far north as Alaska’s Bering Sea, to as far south as the Falkland Islands. Speaking six languages, her international experiences and relationships with diverse communities inform her research on coupled human-natural systems at local to global scales.
Veronica is a Stanford Science Fellow and National Science Foundation Postdoctoral Research Fellow in Biology at Hopkins Marine Station (Doerr School of Sustainability). Her faculty host is Fiorenza Micheli, the David and Lucile Packard Professor of Marine Science, Chair of the Oceans Department, and Co-Director of the Stanford Center for Ocean Solutions. For her postdoctoral research, Veronica is developing a novel framework for predicting human-wildlife relationships under global change.
Honors & Awards
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NSF Postdoctoral Research Fellowship in Biology (PRFB), National Science Foundation (2024-2027)
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Stanford Science Fellowship, Stanford University (2024-2027)
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Jianguo (Jack) Liu Graduate Award in Sustainability, Michigan State University (2024)
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Outstanding Publication in Environmental Science and Policy, Michigan State University (2022)
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Outstanding Publication on New Zealand Ecology, New Zealand Ecological Society (2022)
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Harvey Fellowship, The 28twelve Foundation (2022-2024)
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University Enrichment Fellowship, Michigan State University (2018-2024)
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NSF Graduate Research Fellowship (GRFP), National Science Foundation (2018-2023)
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Modelling Complex Ecological Dynamics (MCED) Award, GfÖ, The Ecological Society of Germany, Austria and Switzerland (2017)
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NASA-MSU Professional Enhancement Award, US International Association of Landscape Ecology (2016)
Professional Education
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Doctor of Philosophy, Michigan State University, Fisheries & Wildlife + Ecology, Evolution, & Behavior (2024)
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Master of Science, University of Göttingen (Germany), International Nature Conservation (2015)
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Master of Science, Lincoln University (New Zealand), International Nature Conservation (2015)
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Bachelor of Science, Messiah University, Environmental Science (2007)
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Bachelor of Arts, Messiah University, French (2007)
All Publications
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Gaps and opportunities in modelling human influence on species distributions in the Anthropocene.
Nature ecology & evolution
2024; 8 (7): 1365-1377
Abstract
Understanding species distributions is a global priority for mitigating environmental pressures from human activities. Ample studies have identified key environmental (climate and habitat) predictors and the spatial scales at which they influence species distributions. However, regarding human influence, such understandings are largely lacking. Here, to advance knowledge concerning human influence on species distributions, we systematically reviewed species distribution modelling (SDM) articles and assessed current modelling efforts. We searched 12,854 articles and found only 1,429 articles using human predictors within SDMs. Collectively, these studies of >58,000 species used 2,307 unique human predictors, suggesting that in contrast to environmental predictors, there is no 'rule of thumb' for human predictor selection in SDMs. The number of human predictors used across studies also varied (usually one to four per study). Moreover, nearly half the articles projecting to future climates held human predictors constant over time, risking false optimism about the effects of human activities compared with climate change. Advances in using human predictors in SDMs are paramount for accurately informing and advancing policy, conservation, management and ecology. We show considerable gaps in including human predictors to understand current and future species distributions in the Anthropocene, opening opportunities for new inquiries. We pose 15 questions to advance ecological theory, methods and real-world applications.
View details for DOI 10.1038/s41559-024-02435-3
View details for PubMedID 38867092
View details for PubMedCentralID PMC11239511
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Integrated SDM database: Enhancing the relevance and utility of species distribution models in conservation management
METHODS IN ECOLOGY AND EVOLUTION
2022; 13 (1): 243-261
View details for DOI 10.1111/2041-210X.13736
View details for Web of Science ID 000715140300001
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Quantifying apart what belongs together: A multi-state species distribution modelling framework for species using distinct habitats
METHODS IN ECOLOGY AND EVOLUTION
2018; 9 (1): 98-108
View details for DOI 10.1111/2041-210X.12847
View details for Web of Science ID 000419821200011
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Use of local ecological knowledge to investigate endangered baleen whale recovery in the Falkland Islands
BIOLOGICAL CONSERVATION
2016; 202: 127-137
View details for DOI 10.1016/j.biocon.2016.08.017
View details for Web of Science ID 000386318400014
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Reciprocal inhibition and competitive hierarchy cause negative biodiversity-ecosystem function relationships.
Ecology letters
2024; 27 (1): e14356
Abstract
The relationship between biodiversity and ecosystem function (BEF) captivates ecologists, but the factors responsible for the direction of this relationship remain unclear. While higher ecosystem functioning at higher biodiversity levels ('positive BEF') is not universal in nature, negative BEF relationships seem puzzlingly rare. Here, we develop a dynamical consumer-resource model inspired by microbial decomposer communities in pitcher plant leaves to investigate BEF. We manipulate microbial diversity via controlled colonization and measure their function as total ammonia production. We test how niche partitioning among bacteria and other ecological processes influence BEF in the leaves. We find that a negative BEF can emerge from reciprocal interspecific inhibition in ammonia production causing a negative complementarity effect, or from competitive hierarchies causing a negative selection effect. Absent these factors, a positive BEF was the typical outcome. Our findings provide a potential explanation for the rarity of negative BEF in empirical data.
View details for DOI 10.1111/ele.14356
View details for PubMedID 38193391
- It takes a village to raise a science communicator Journal of Higher Education Outreach and Engagement 2024; 28 (3): 140-156
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seesus: a social, environmental, and economic sustainability classifier for Python
Journal of Open Source Software
2024; 9 (96): 6244
View details for DOI 10.21105/joss.06244
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SDGdetector: an R-based text mining tool for quantifying efforts toward Sustainable Development Goals
Journal of Open Source Software
2023; 8 (84): 5124
View details for DOI 10.21105/joss.05124
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The metacoupled Arctic: Human-nature interactions across local to global scales as drivers of sustainability.
Ambio
2022; 51 (10): 2061-2078
Abstract
The Arctic is an epicenter of complex environmental and socioeconomic change. Strengthened connections between Arctic and non-Arctic systems could threaten or enhance Arctic sustainability, but studies of external influences on the Arctic are scattered and fragmented in academic literature. Here, we review and synthesize how external influences have been analyzed in Arctic-coupled human and natural systems (CHANS) literature. Results show that the Arctic is affected by numerous external influences nearby and faraway, including global markets, climate change, governance, military security, and tourism. However, apart from climate change, these connections are infrequently the focus of Arctic CHANS analyses. We demonstrate how Arctic CHANS research could be enhanced and research gaps could be filled using the holistic framework of metacoupling (human-nature interactions within as well as between adjacent and distant systems). Our perspectives provide new approaches to enhance the sustainability of Arctic systems in an interconnected world.
View details for DOI 10.1007/s13280-022-01729-9
View details for PubMedID 35353295
View details for PubMedCentralID PMC9378800
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A network perspective for mapping freshwater service flows at the watershed scale
ECOSYSTEM SERVICES
2020; 45
View details for DOI 10.1016/j.ecoser.2020.101129
View details for Web of Science ID 000577345300001
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Assessing the water and carbon footprint of hydropower stations at a national scale.
The Science of the total environment
2019; 676: 595-612
Abstract
Hydropower is among the most widely-adopted renewable energy sources worldwide. Its development has, however, led to environmental impacts such as carbon emissions and water loss. To date, the water footprint (WF) and carbon footprint (CF) of hydropower stations have been assessed, but not simultaneously or at a large scale such as national scale. Previous WF and CF studies rarely assessed all life-cycle stages of a hydropower station, calling for a more holistic understanding of the environmental impacts of hydropower. We developed a complete WF and CF assessment method and applied it to a case study on 50 of China's most influential hydropower stations, representing over 80% of the country's total hydropower. The total annual WF of these hydropower stations was 5.50 × 1011 m3, equal to 18.9% of Yellow River's annual runoff. The total CF of these stations was 1.06 × 107 tCO2e, with extremely large variations found, ranging from 1850 to 1.56 × 106 tCO2e. This study provides the first environmental impact assessment to simultaneously include the WF and CF of multiple influential hydropower stations at a national scale. We were able to show spatial variations in their environmental impacts from different life-cycle stages of the hydropower station. Most of the WF was due to surface water loss from reservoirs, while most of the CF was derived from the operational and maintenance stage of these stations. This initial WF and CF assessment of hydropower at a national scale provides insights for water resource management and carbon reduction during hydropower development.
View details for DOI 10.1016/j.scitotenv.2019.04.148
View details for PubMedID 31051366
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Spatial distribution of cetacean strandings in the Falkland Islands to define monitoring opportunities
Journal of Cetacean Research and Management
2018; 19: 1-7
View details for DOI 10.47536/jcrm.v19i1.410