The environmental risks associated with genetically-engineered (GE) organisms have been controversial, and so have the models for the assessment of these risks. We propose an ecologically-based environmental risk assessment (ERA) model that follows the 1998 USEPA guidelines, focusing on potential adverse effects to biological diversity. The approach starts by (1) identifying the local environmental values so the ERA addresses specific concerns associated with local biological diversity. The model simplifies the indicator endpoint selection problem by (2) classifying biological diversity into ecological functional groups and selecting those that deliver the identified environmental values. (3) All of the species or ecosystem processes related to the selected functional groups are identified and (4) multi-criteria decision analysis (MCDA) is used to rank the indicator endpoint entities, which may be species or ecological processes. MCDA focuses on those species and processes that are critical for the identified ecological functions and are likely to be highly exposed to the GE organism. The highest ranked indicator entities are selected for the next step. (5) Relevant risk hypotheses are identified. Knowledge about the specific transgene and its possible environmental effects in other countries can be used to assist development of risk hypotheses. (6) The risk hypotheses are ranked using MCDA with criteria related to the severity of the potential risk. The model emphasizes transparent, expert-driven, ecologically-based decision-making and provides formal methods for completing a screening level-ERA that can focus ERA on the most significant concerns. The process requires substantial human input but the human capital is available in most countries and regions of the world.

An ecologically-based method for selecting ecological indicators for assessing risks to biological diversity from genetically-engineered plants

ARPAIA S;
2013-01-01

Abstract

The environmental risks associated with genetically-engineered (GE) organisms have been controversial, and so have the models for the assessment of these risks. We propose an ecologically-based environmental risk assessment (ERA) model that follows the 1998 USEPA guidelines, focusing on potential adverse effects to biological diversity. The approach starts by (1) identifying the local environmental values so the ERA addresses specific concerns associated with local biological diversity. The model simplifies the indicator endpoint selection problem by (2) classifying biological diversity into ecological functional groups and selecting those that deliver the identified environmental values. (3) All of the species or ecosystem processes related to the selected functional groups are identified and (4) multi-criteria decision analysis (MCDA) is used to rank the indicator endpoint entities, which may be species or ecological processes. MCDA focuses on those species and processes that are critical for the identified ecological functions and are likely to be highly exposed to the GE organism. The highest ranked indicator entities are selected for the next step. (5) Relevant risk hypotheses are identified. Knowledge about the specific transgene and its possible environmental effects in other countries can be used to assist development of risk hypotheses. (6) The risk hypotheses are ranked using MCDA with criteria related to the severity of the potential risk. The model emphasizes transparent, expert-driven, ecologically-based decision-making and provides formal methods for completing a screening level-ERA that can focus ERA on the most significant concerns. The process requires substantial human input but the human capital is available in most countries and regions of the world.
2013
genetically engineered orgnaism, environmental risk assessment, ecosystem serices
File in questo prodotto:
File Dimensione Formato  
Andow_et_al_2013_jbiosafety-andowal 2pdf.pdf

non disponibili

Tipologia: Versione Editoriale (PDF)
Licenza: Licenza per accesso riservato
Dimensione 785.4 kB
Formato Adobe PDF
785.4 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12079/71027
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
social impact