Integration of ecosystem science into radioecology: A consensus perspective
Autor: | James C. Beasley, Cara N. Love, Garth Gladfelder, Nicole E. Martinez, Austin Coleman, Teresa J. Mathews, E. A. Pryakhin, Travis C. Glenn, Arthur McKee, Steve Mihok, David S. White, François Bréchignac, Amelia K. Ward, Gary L. Mills, Jess K. Zimmerman, Caitlin Condon, Olin E. Rhodes, Ben Parrott, Robert A. Kennamer, William J. McShea, Lawrence W. Barnthouse, Dean E. Fletcher, Bernard Clément, Maryna Shkvyria, Carmel Mothersill, David E. Scott, John A. Arnone, Susan P. Hendricks, Michael Wood, Timothy A. DeVol, Ulrik Kautsky, Stacey L. Lance, Doug P. Aubrey, Lindsay R. Boring, Krista A. Capps, Clare Bradshaw, Albert L. Bryan, Ken Ishida, Thomas G. Hinton, Lisa Manglass, Colin Seymour, Gennadiy Laptyev, Tim Jannik, John C. Seaman, Brian A. Powell, Wendy W. Kuhne, Wes Flynn, Fanny Coutelot, Larry Kapustka, Guha Dharmarajan, Andrea Bonisoli-Alquati, Ann L. Rypstra |
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Přispěvatelé: | Savannah River Ecology Laboratory (SREL), University of Georgia [USA], Södertörn University College, University College Cork (UCC), Laboratoire d'Ecologie des Hydrosystèmes Naturels et Anthropisés (LEHNA), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE)-Centre National de la Recherche Scientifique (CNRS), Géoressources et environnement, Institut Polytechnique de Bordeaux (Bordeaux INP)-Université Bordeaux Montaigne, McMaster Univ, Med Phys & Appl Radiat Sci Dept, Hamilton, ON, Canada |
Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
Ecosystem health
medicine.medical_specialty Environmental Engineering 010504 meteorology & atmospheric sciences Ecosystem ecology Ecosystem health Ecotoxicology Radioecology Radionuclides Risk assessment Inference 010501 environmental sciences 15. Life on land 16. Peace & justice 01 natural sciences Pollution Radioecology 13. Climate action Radiological weapon Causal inference medicine Environmental Chemistry Ecosystem [SDE.BE]Environmental Sciences/Biodiversity and Ecology Ecosystem ecology Risk assessment Psychology Waste Management and Disposal Environmental planning 0105 earth and related environmental sciences |
Zdroj: | Science of the Total Environment Science of the Total Environment, Elsevier, 2020, 740, pp.140031. ⟨10.1016/j.scitotenv.2020.140031⟩ |
ISSN: | 0048-9697 1879-1026 |
Popis: | International audience; In the Fall of 2016 a workshop was held which brought together over 50 scientists from the ecological and radio- logical fields to discuss feasibility and challenges of reintegrating ecosystem science into radioecology. There is a growing desire to incorporate attributes of ecosystem science into radiological risk assessment and radioecological research more generally, fueled by recent advances in quantification of emergent ecosystem at- tributes and the desire to accurately reflect impacts of radiological stressors upon ecosystem function. This paper is a synthesis of the discussions and consensus of the workshop participant's responses to three primary questions, which were: 1) How can ecosystem science support radiological risk assessment? 2) What ecosystem level endpoints potentially could be used for radiological risk assessment? and 3) What inference strategies and associated methods would be most appropriate to assess the effects of radionuclides on ecosystem structure and function? The consensus of the participants was that ecosystem science can and should support radiological risk assessment through the incorporation of quantitative metrics that reflect ecosystem functions which are sensi- tive to radiological contaminants. The participants also agreed that many such endpoints exit or are thought to exit and while many are used in ecological risk assessment currently, additional data need to be collected that link the causal mechanisms of radiological exposure to these endpoints. Finally, the participants agreed that ra- diological risk assessments must be designed and informed by rigorous statistical frameworks capable of reveal- ing the causal inference tying radiological exposure to the endpoints selected for measurement. |
Databáze: | OpenAIRE |
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