thesis_access.pdf (8.5 MB)
Download file

Parameterising and Adapting Ecosystem Service Models in Data Sparse Regions: Gaps, Guidelines, and an Application in the Vietnamese Mekong Delta

Download (8.5 MB)
thesis
posted on 16.06.2022, 21:43 by Anh Nguyet Dang

Demand for applying ES models in decision-making has increased across the world. However, despite advances in modelling approaches for ES, adopting either discipline-specific models or more holistic multi-ES models is time and data intensive, especially in data sparse areas and areas where ES modelling has not been well established. Many of the main challenges are rooted in model parameters/assumptions and processes biased to specific ecosystem, policy, and data contexts for which ES models were initially developed or established. ES modelling, therefore, needs to be improved to cover wider ecosystem, policy, and data conditions, and fast enough for use during decision-making timeframes. The aim of this research is to facilitate ES model parameterisation and adaptation to enhance ES model applicability, especially in data sparse areas and areas where ES modelling has not been well established. It will ultimately reduce efforts required to produce ES modelling and assessments.

History

Copyright Date

17/06/2022

Date of Award

17/06/2022

Publisher

Te Herenga Waka—Victoria University of Wellington

Rights License

CC BY 4.0

Degree Discipline

Physical Geography

Degree Grantor

Te Herenga Waka—Victoria University of Wellington

Degree Level

Doctoral

Degree Name

Doctor of Philosophy

ANZSRC Type Of Activity code

1 Pure basic research

Victoria University of Wellington Item Type

Awarded Doctoral Thesis

Language

en_NZ

Victoria University of Wellington School

School of Geography, Environment and Earth Sciences

Advisors

Jackson, Bethanna; Tomscha, Stephanie