MICHAEL GAVIN, PHD
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For over two decades my research has focused on identifying emerging trends and major gaps for which innovative science can provide solutions. To advance this applied research I have developed partnerships with communities, government agencies, NGOs, companies, and scientists from diverse disciplines. My work is supported by funding from foundations, government agencies, and international research institutes. The research efforts I direct develop and use novel quantitative and qualitative research methods to produce results that help build resilience to complex environmental challenges. I then communicate the results in diverse ways to reach a wide audience.
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Biocultural conservation

I led an international working group linked to the Commission on Environmental, Economic and Social Policy of the International Union for the Conservation of Nature (IUCN). Our research developed and promoted biocultural approaches to environmental conservation, which are “conservation actions made in service of sustaining the biophysical and socio-cultural components of dynamic, interacting, and interdependent social-ecological systems”. Our foundational article, published in Trends in Ecology and Evolution, established a set of principles to guide conservation action in response to the simultaneous and rapid loss of biological and cultural diversity. My students and I have also conducted related research on biodiversity conservation and local and Indigenous resource management practices in more than a dozen countries, publishing in leading journals including Conservation Letters, Conservation Biology, Biological Conservation, and the Journal of Applied Ecology.

Examples of related projects include:
  • Participatory governance in shaping ecological impacts of protected areas in Peru and Mexico
  • Pathways for integration of cultural ecosystem services into federal environmental decision-making in the U.S.
  • Frameworks for ethical research practices with Indigenous and local communities
  • Supporting school education models that encourage transmission of Indigenous ecological knowledge in Vanuatu
  • Identifying factors shaping success or failure of protected areas in Peru, Mexico, and globally
  • Sustainability of hunting in the Amazon
  • Impacts of cattle ranching on avifauna in Argentina
  • Supporting Indigenous ecological knowledge systems in U.S., Peru, Amazonia, and globally

Understanding the Origins of Diversity

Since 2010, I have led interdisciplinary, international teams that have helped defined the frontier of human macroecology. This work began with support from the National Science Foundation’s National Evolutionary Synthesis Center, through which we built a large, open-access dataset now driving research across the field. We have applied diverse computational methods originally developed in ecology and evolutionary biology to study how the environment shapes patterns of human diversity, including natural resource management systems, linguistic diversity, and architecture.

Includes:
  • Database of Places, Language, Culture, and Environment
  • Exploring drivers of natural resource management strategies in 1000+ societies across the planet
  • Ecology of religious beliefs
  • Identifying mechanisms of language diversification in Australia and North America
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Sustainable Investing & the Environment

I collaborate with colleagues at the Wharton School's Impact, Value, and Sustainable Business Initiative at the University of Pennsylvania, where I serve as a  Senior Research Fellow. This research has been funded through partnerships with large institutional investment firms. We examine how a company's environmental impact may shape its financial outcomes, as well as how financial performance may influence a company’s environmental behavior. To address these questions, our team draws on a diverse computational toolkit, including machine learning, structural equation modeling, and fuzzy-set qualitative comparative analysis. This work has produced academic publications and conference proceedings, as well as reports for industry partners. The research has also spun off an early-stage startup that applies machine learning to design low-carbon stock portfolios designed to outperform the market.


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