Pierre D. Glynn

Dr. Pierre D. Glynn

orcid

Research Focus & Metrics

Academic Career Length

37Years (1990-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 March 2016 in Environmental Modelling & Software
Verified
Journal Article
Closed access
Alexey VoinovAlexey Voinov
Alexey Voinov
NKNagesh Kolagani
Nagesh Kolagani
MMMichael K. McCall
Michael K. McCall
PGPierre D. Glynn
Pierre D. Glynn
MKMarit E. Kragt
Marit E. Kragt
PRPalaniappan Ramu
Palaniappan Ramu

25 February 2005 in Hydrogeology Journal
Verified
Journal Article
Closed access
PDF file
PGPierre D. Glynn
Pierre D. Glynn
LPL. Niel Plummer
L. Niel Plummer

1 February 1990 in Geochimica et Cosmochimica Acta
Verified
Journal Article
Closed access
PGPierre D. Glynn
Pierre D. Glynn
EREric J Reardon
Eric J Reardon
LPL.NIel Plummer
L.NIel Plummer
EBEurybiades Busenberg
Eurybiades Busenberg

24 April 2017 in Earth's Future
Verified
Journal Article
Open access
PDF file
PGPierre D. Glynn
Pierre D. Glynn
Alexey VoinovAlexey Voinov
Alexey Voinov
CSCarl D. Shapiro
Carl D. Shapiro
PWPaul A. White
Paul A. White
Our different kinds of minds and types of thinking affect the ways we decide, take action, and cooperate (or not). Derived from these types of minds, innate biases, beliefs, heuristics, and values (BBHV) influence behaviors, often beneficially, when individuals or small groups face immediate, local, acute situations that they and their ancestors faced repeatedly in the past. BBHV, though, need to be recognized and possibly countered or used when facing new, complex issues or situations especially if they need to be managed for the benefit of a wider community, for the longer‐term and the larger‐scale. Taking BBHV into account, we explain and provide a cyclic science‐infused adaptive framework for (1) gaining knowledge of complex systems and (2) improving their management. We explore how this process and framework could improve the governance of science and policy for different types of systems and issues, providing examples in the area of natural resources, hazards, and the environment. Lastly, we suggest that an “Open Traceable Accountable Policy” initiative that followed our suggested adaptive framework could beneficially complement recent Open Data/Model science initiatives.Plain Language Summary: Our review paper suggests that society can improve the management of natural resources and environments by (1) recognizing the sources of human decisions and thinking and understanding their role in the scientific progression to knowledge; (2) considering innate human needs and biases, beliefs, heuristics, and values that may need to be countered or embraced; and (3) creating science and policy governance that is inclusive, integrated, considerate of diversity, explicit, and accountable. The paper presents a science‐infused adaptive framework for such governance, and discusses the types of issues and systems that it would be best suited to address.

3 August 2018 in Earth's Future
Verified
Journal Article
Open access
PDF file
RJRebecca Jordan
Rebecca Jordan
SGSteven Gray
Steven Gray
MZMoira Zellner
Moira Zellner
PGPierre D. Glynn
Pierre D. Glynn
Alexey VoinovAlexey Voinov
Alexey Voinov
NGNational Socio‐Environmental Synthesis Center Participatory Modeling Pursuit Working Group
National Socio‐Environmental Synthesis Center Participatory Modeling Pursuit Working Group
Participatory modeling engages the implicit and explicit knowledge of stakeholders to create formalized and shared representations of reality and has evolved into a field of study as well as a practice. Participatory modeling researchers and practitioners who focus specifically on environmental resources met at the National Socio‐Environmental Synthesis Center (SESYNC) in Annapolis, Maryland, over the course of 2 years to discuss the state of the field and future directions for participatory modeling. What follows is a description of 12 overarching groups of questions that could guide future inquiry.