Pierre Glynn, Ph.D. (Former Employee)
Science and Products
Filter Total Items: 39
The natural capital accounting opportunity: Let's really do the numbers
The nation’s economic accounts provide objective, regular, and standardized information routinely relied upon by public and private decision makers. But they are incomplete. The U.S. and many other nations currently do not account for the natural capital — such as the wildlife, forests, grasslands, soils, and water bodies—upon which all other economic activity rests. By creating formal...
Authors
James W. Boyd, Kenneth J. Bagstad, Jane Carter Ingram, Carl D. Shapiro, Jeffery Adkins, C. Frank Casey, Clifford S. Duke, Pierre D. Glynn, Erica Goldman, Monica Grasso, Julie L. Hass, Justin C. Johnson, Glenn-Marie Lange, John Matuszak, Ann Miller, Kirsten L. L. Oleson, Stephen M. Posner, Charles Rhodes, Francois Soulard, Michael Vardon, Ferdinando Villa, Brian Voigt, Scott A. Wentland
Twelve questions for the participatory modeling community
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...
Authors
Rebecca Jordan, Steven Gray, Moira L. Zellner, Pierre D. Glynn, Alexey A. Voinov, Beatrice Hedelin, Eleanor J. Sterling, Kirsten M. Leong, Laura Schmitt Olabisi, Klaus Hubacek, Pierre Bommel, Todd K. BenDor, Antonie J. Jetter, Bethany K. Laursen, Alison Singer, Philippe J. Giabbanelli, Nagesh Kolagani, Laura Basco Carrera, Karen Elizabeth Jenni, Christina Prell
Tools and methods in participatory modeling: Selecting the right tool for the job
Various tools and methods are used in participatory modelling, at different stages of the process and for different purposes. The diversity of tools and methods can create challenges for stakeholders and modelers when selecting the ones most appropriate for their projects. We offer a systematic overview, assessment, and categorization of methods to assist modelers and stakeholders with...
Authors
Alexey A. Voinov, Karen Jenni, Steven Gray, Nagesh Kolagani, Pierre D. Glynn, Pierre Bommel, Christina Prell, Moira L. Zellner, Michael Paolisso, Rebecca Jordan, Eleanor J. Sterling, Laura Schmitt Olabasi, Philippe J. Giabbanelli, Zhanli Sun, Christophe Le Page, Sondoss Elsawah, Todd K. BenDor, Klaus Hubacek, Bethany K. Laursen, Antonie J. Jetter, Laura Basco Carrera, Alison Singer, Laura G. Young, Jessica Brunacini, Alex Smajgl
Response to comment by Walker et al. on “From data to decisions: Processing information, biases, and beliefs for improved management of natural resources and environments”
Our different kinds of minds and types of thinking affect the ways we decide, take action, and cooperate (or not). The comment by Walker et al. (2018, https://doi.org/10.1002/2017EF000750) illustrates several points made by Glynn et al. (2017, https://doi.org/10.1002/2016EF000487) and many other articles. Namely, biases and beliefs often drive scientific reasoning, and scientists, just...
Authors
Pierre D. Glynn, Alexey A. Voinov, Carl D. Shapiro, Paul M. White
Purpose, processes, partnerships, and products: four Ps to advance participatory socio-environmental modeling
Including stakeholders in environmental model building and analysis is an increasingly popular approach to understanding ecological change. This is because stakeholders often hold valuable knowledge about socio-environmental dynamics and collaborative forms of modeling produce important boundary objects used to collectively reason about environmental problems. Although the number of...
Authors
Steven Gray, Alexey A. Voinov, Michael Paolisso, Rebecca Jordan, Todd K. BenDor, Pierre Bommel, Pierre D. Glynn, Beatrice Hedelin, Klaus Hubacek, Josh Introne, Nagesh Kolagani, Bethany K. Laursen, Christina Prell, Laura Schmitt-Olabisi, Alison Singer, Eleanor J. Sterling, Moira L. Zellner
From data to decisions: Processing information, biases, and beliefs for improved management of natural resources and environments
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...
Authors
Pierre D. Glynn, Alexey A. Voinov, Carl D. Shapiro, Paul M. White
Modelling with stakeholders - Next generation
This paper updates and builds on ‘Modelling with Stakeholders’ Voinov and Bousquet, 2010 which demonstrated the importance of, and demand for, stakeholder participation in resource and environmental modelling. This position paper returns to the concepts of that publication and reviews the progress made since 2010. A new development is the wide introduction and acceptance of social media...
Authors
Alexey A. Voinov, Nagesh Kolagani, Michael K McCall, Pierre D. Glynn, Marit E Kragt, Frank O Ostermann, Suzanne A Pierce, Palaniappan Ramu
Review of the USA National Phenology Network
In January 2014, leadership from the U.S. Geological Survey (USGS) Ecosystems Mission Area commissioned a review of the USA National Phenology Network (USA–NPN) Program. The Ecosystems Mission Area has a key stake in the USA–NPN, providing both supervision of its Director and most of the appropriated funds. The products and objectives of the program are relevant to six of the seven USGS...
Integrated Environmental Modelling: Human decisions, human challenges
Integrated Environmental Modelling (IEM) is an invaluable tool for understanding the complex, dynamic ecosystems that house our natural resources and control our environments. Human behaviour affects the ways in which the science of IEM is assembled and used for meaningful societal applications. In particular, human biases and heuristics reflect adaptation and experiential learning to...
Authors
Pierre D. Glynn
W(h)ither the Oracle? Cognitive biases and other human challenges of integrated environmental modeling
Integrated environmental modeling (IEM) can organize and increase our knowledge of the complex, dynamic ecosystems that house our natural resources and control the quality of our environments. Human behavior, however, must be taken into account. Human biases/heuristics reflect adaptation over our evolutionary past to frequently experienced situations that affected our survival and that...
Authors
Pierre D. Glynn
Integrated environmental modeling: a vision and roadmap for the future
Integrated environmental modeling (IEM) is inspired by modern environmental problems, decisions, and policies and enabled by transdisciplinary science and computer capabilities that allow the environment to be considered in a holistic way. The problems are characterized by the extent of the environmental system involved, dynamic and interdependent nature of stressors and their impacts...
Authors
Gerard F. Laniak, Gabriel Olchin, Jonathan L. Goodall, Alexey A. Voinov, Mary C. Hill, Pierre D. Glynn, Gene Whelan, Gary N. Geller, Nigel W. T. Quinn, Michiel Blind, Scott D Peckham, Sim Reaney, Noha Gaber, Philip R. Kennedy, Andrew Hughes
Modeling groundwater flow and quality
In most areas, rocks in the subsurface are saturated with water at relatively shallow depths. The top of the saturated zone—the water table—typically occurs anywhere from just below land surface to hundreds of feet below the land surface. Groundwater generally fills all pore spaces below the water table and is part of a continuous dynamic flow system, in which the fluid is moving at...
Authors
Leonard F. Konikow, Pierre D. Glynn
Science and Products
Filter Total Items: 39
The natural capital accounting opportunity: Let's really do the numbers
The nation’s economic accounts provide objective, regular, and standardized information routinely relied upon by public and private decision makers. But they are incomplete. The U.S. and many other nations currently do not account for the natural capital — such as the wildlife, forests, grasslands, soils, and water bodies—upon which all other economic activity rests. By creating formal...
Authors
James W. Boyd, Kenneth J. Bagstad, Jane Carter Ingram, Carl D. Shapiro, Jeffery Adkins, C. Frank Casey, Clifford S. Duke, Pierre D. Glynn, Erica Goldman, Monica Grasso, Julie L. Hass, Justin C. Johnson, Glenn-Marie Lange, John Matuszak, Ann Miller, Kirsten L. L. Oleson, Stephen M. Posner, Charles Rhodes, Francois Soulard, Michael Vardon, Ferdinando Villa, Brian Voigt, Scott A. Wentland
Twelve questions for the participatory modeling community
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...
Authors
Rebecca Jordan, Steven Gray, Moira L. Zellner, Pierre D. Glynn, Alexey A. Voinov, Beatrice Hedelin, Eleanor J. Sterling, Kirsten M. Leong, Laura Schmitt Olabisi, Klaus Hubacek, Pierre Bommel, Todd K. BenDor, Antonie J. Jetter, Bethany K. Laursen, Alison Singer, Philippe J. Giabbanelli, Nagesh Kolagani, Laura Basco Carrera, Karen Elizabeth Jenni, Christina Prell
Tools and methods in participatory modeling: Selecting the right tool for the job
Various tools and methods are used in participatory modelling, at different stages of the process and for different purposes. The diversity of tools and methods can create challenges for stakeholders and modelers when selecting the ones most appropriate for their projects. We offer a systematic overview, assessment, and categorization of methods to assist modelers and stakeholders with...
Authors
Alexey A. Voinov, Karen Jenni, Steven Gray, Nagesh Kolagani, Pierre D. Glynn, Pierre Bommel, Christina Prell, Moira L. Zellner, Michael Paolisso, Rebecca Jordan, Eleanor J. Sterling, Laura Schmitt Olabasi, Philippe J. Giabbanelli, Zhanli Sun, Christophe Le Page, Sondoss Elsawah, Todd K. BenDor, Klaus Hubacek, Bethany K. Laursen, Antonie J. Jetter, Laura Basco Carrera, Alison Singer, Laura G. Young, Jessica Brunacini, Alex Smajgl
Response to comment by Walker et al. on “From data to decisions: Processing information, biases, and beliefs for improved management of natural resources and environments”
Our different kinds of minds and types of thinking affect the ways we decide, take action, and cooperate (or not). The comment by Walker et al. (2018, https://doi.org/10.1002/2017EF000750) illustrates several points made by Glynn et al. (2017, https://doi.org/10.1002/2016EF000487) and many other articles. Namely, biases and beliefs often drive scientific reasoning, and scientists, just...
Authors
Pierre D. Glynn, Alexey A. Voinov, Carl D. Shapiro, Paul M. White
Purpose, processes, partnerships, and products: four Ps to advance participatory socio-environmental modeling
Including stakeholders in environmental model building and analysis is an increasingly popular approach to understanding ecological change. This is because stakeholders often hold valuable knowledge about socio-environmental dynamics and collaborative forms of modeling produce important boundary objects used to collectively reason about environmental problems. Although the number of...
Authors
Steven Gray, Alexey A. Voinov, Michael Paolisso, Rebecca Jordan, Todd K. BenDor, Pierre Bommel, Pierre D. Glynn, Beatrice Hedelin, Klaus Hubacek, Josh Introne, Nagesh Kolagani, Bethany K. Laursen, Christina Prell, Laura Schmitt-Olabisi, Alison Singer, Eleanor J. Sterling, Moira L. Zellner
From data to decisions: Processing information, biases, and beliefs for improved management of natural resources and environments
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...
Authors
Pierre D. Glynn, Alexey A. Voinov, Carl D. Shapiro, Paul M. White
Modelling with stakeholders - Next generation
This paper updates and builds on ‘Modelling with Stakeholders’ Voinov and Bousquet, 2010 which demonstrated the importance of, and demand for, stakeholder participation in resource and environmental modelling. This position paper returns to the concepts of that publication and reviews the progress made since 2010. A new development is the wide introduction and acceptance of social media...
Authors
Alexey A. Voinov, Nagesh Kolagani, Michael K McCall, Pierre D. Glynn, Marit E Kragt, Frank O Ostermann, Suzanne A Pierce, Palaniappan Ramu
Review of the USA National Phenology Network
In January 2014, leadership from the U.S. Geological Survey (USGS) Ecosystems Mission Area commissioned a review of the USA National Phenology Network (USA–NPN) Program. The Ecosystems Mission Area has a key stake in the USA–NPN, providing both supervision of its Director and most of the appropriated funds. The products and objectives of the program are relevant to six of the seven USGS...
Integrated Environmental Modelling: Human decisions, human challenges
Integrated Environmental Modelling (IEM) is an invaluable tool for understanding the complex, dynamic ecosystems that house our natural resources and control our environments. Human behaviour affects the ways in which the science of IEM is assembled and used for meaningful societal applications. In particular, human biases and heuristics reflect adaptation and experiential learning to...
Authors
Pierre D. Glynn
W(h)ither the Oracle? Cognitive biases and other human challenges of integrated environmental modeling
Integrated environmental modeling (IEM) can organize and increase our knowledge of the complex, dynamic ecosystems that house our natural resources and control the quality of our environments. Human behavior, however, must be taken into account. Human biases/heuristics reflect adaptation over our evolutionary past to frequently experienced situations that affected our survival and that...
Authors
Pierre D. Glynn
Integrated environmental modeling: a vision and roadmap for the future
Integrated environmental modeling (IEM) is inspired by modern environmental problems, decisions, and policies and enabled by transdisciplinary science and computer capabilities that allow the environment to be considered in a holistic way. The problems are characterized by the extent of the environmental system involved, dynamic and interdependent nature of stressors and their impacts...
Authors
Gerard F. Laniak, Gabriel Olchin, Jonathan L. Goodall, Alexey A. Voinov, Mary C. Hill, Pierre D. Glynn, Gene Whelan, Gary N. Geller, Nigel W. T. Quinn, Michiel Blind, Scott D Peckham, Sim Reaney, Noha Gaber, Philip R. Kennedy, Andrew Hughes
Modeling groundwater flow and quality
In most areas, rocks in the subsurface are saturated with water at relatively shallow depths. The top of the saturated zone—the water table—typically occurs anywhere from just below land surface to hundreds of feet below the land surface. Groundwater generally fills all pore spaces below the water table and is part of a continuous dynamic flow system, in which the fluid is moving at...
Authors
Leonard F. Konikow, Pierre D. Glynn