A Bayesian Modelling Framework for Integration of Ecosystem Services into Freshwater Resources Management.
Environ Manage
; 69(4): 781-800, 2022 04.
Article
em En
| MEDLINE
| ID: mdl-35171345
ABSTRACT
Models of ecological response to multiple stressors and of the consequences for ecosystem services (ES) delivery are scarce. This paper describes a methodology for constructing a BBN combining catchment and water quality model output, data, and expert knowledge that can support the integration of ES into water resources management. It proposes "small group" workshop methods for elucidating expert knowledge and analyses the areas of agreement and disagreement between experts. The model was developed for four selected ES and for assessing the consequences of management options relating to no-change, riparian management, and decreasing or increasing livestock numbers. Compared with no-change, riparian management and a decrease in livestock numbers improved the ES investigated to varying degrees. Sensitivity analysis of the expert information in the BBN showed the greatest disagreements between experts were mainly for low probability situations and thus had little impact on the results. Conversely, in our applications, the best agreement between experts tended to occur for the higher probability, more likely, situations. This has implications for the practical use of this type of model to support catchment management decisions. The complexity of the relationship between management measures, the water quality and ecological responses and resulting changes in ES must not be a barrier to making decisions in the present time. The interactions of multiple stressors further complicate the situation. However, management decisions typically relate to the overall character of solutions and not their detailed design, which can follow once the nature of the solution has been chosen, for example livestock management or riparian measures or both.
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Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Ecossistema
/
Conservação dos Recursos Naturais
Tipo de estudo:
Prognostic_studies
Limite:
Animals
Idioma:
En
Ano de publicação:
2022
Tipo de documento:
Article