Table 1.
Linking the salient features of biodiversity modelling and scenarios with principles of applied ethics
| Salient features | Technical issue | Consideration of ethical principle |
|---|---|---|
| Collective endeavour | There is no one-to-one correspondence between individual modeller’s action or decision and impacts associated with model uses. | Collective responsible and accountable behaviour. |
| Participation | Not only scientists but also stakeholders, ethicists and policy-makers should be involved at the various stages of platform conception, development and use. | Promote a pluralistic approach. |
| Knowledge integration | A common framework for sharing and producing knowledge must be developed, adopted and used in a consensual manner. | Implement fairness and openness. |
| Reduction | Explain and disseminate the knowledge representation processes that include knowledge reduction, the enforcement of coherence between representations and the use of integrity constraints. | Strengthen the transparency and legitimacy of knowledge. |
| Categorisation | The model ontology is not a passive representation of some system. It also frames—and possibly reifies—social and ecological segmentation and categorisations. | Foster disclosure. |
| Scenario valuation | The definition of a scenario explicitly or latently expresses the interests and values of the group that conceives it. Obligations to involve the public in decision-making about these technical matters. | Assume accountability, foster comprehension and social acceptability of scenarios. |
| Differentiation of impacts | Scenarios are not only used to improve knowledge but also to take decisions that have differentiated impacts on different segments of society, biodiversity and ecosystems. | Integrate values of equity and justice. |
| Knowledge use | Simulation results can be used by policy-makers, governmental and non-governmental organisations, civil society, etc. | Strengthen the independence of end users and promote benefit-sharing. |
| Capacity | Obligation to promote public education regarding the most relevant aspects of model and scenario building and use for supporting policy and regulation. | Adhere to the transparency of modelling and scenario uses. |
| Data sharing | Make all data open access and available on public repositories | Build public trust and inclusivity. |
See, e.g. CBD 2011