A Framework for Integrated Ecosystem Service Valuation under Climate Uncertainty

Thesis Abstract

In the face of accelerating climate variability, ecosystems provide a diverse array of services whose valuatio n is shaped by uncertain future conditions, yet current valuation frameworks inadequately integrate ecological dynamics, risk, and adaptation potential. This study develops a framework for integrated ecosystem service valuation under climate uncertainty that consolidates biophysical, economic, and social dimensions to enhance decision making under deepening climate risks. The specific objectives are to (i) identify climate-driven drivers altering the supply and perception of ecosystem services in coastal-marine and peri-urban landscapes, (ii) construct a participatory valuation model combining physical biophysical outputs, contingent valuation, and ecosystem service transfer methods under multiple climate scenarios, (iii) quantify uncertainty propagation through a probabilistic Monte Carlo simulation linked to a Bayesian belief network to prioritize service endpoints and their trade-offs, and (iv) validate the framework through a pilot application in the Lagos Lagoon watershed, Nigeria, and a comparable case in the Netherlands' Delta region to demonstrate transferability. A mixed-methods design is employed. The study adopts a comparative case approach with two focal sites Lagos Lagoon (n=1,500 stakeholder respondents across households, fishers, and urban planners) and the Zeeland Delta (n=1,200 stakeholders). Data collection combines structured household surveys (n=800 per site), in-depth interviews with 60 experts (water managers, ecologists, and economists), and participatory workshops (four per site) to elicit service values, vulnerability perceptions, and adaptive capacity. Biophysical data are sourced from remote sensing products and local hydrological measurements spanning 15 years (2009–2023) to model service supply under Representative Concentration Pathways RCP4.5 and RCP8.5. Instruments include a standardized ecosystem service questionnaire, a stated-preference valuation module, and ecological indicators such as sediment retention, flood attenuation, nutrient cycling, and biodiversity indices. Validity is ensured via pilot testing (n=60) and triangulation across qualitative and quantitative instruments; reliability is assessed with Cronbach’s alpha (>0.7) and test-retest reliability. Methodologically, the framework integrates (i) ecosystem service modeling to derive a multi-criteria indicator set, (ii) value elicitation using revealed and stated preference methods, and (iii) uncertainty analysis employing Monte Carlo simulations (10,000 iterations) to propagate climate scenario uncertainties into service values. A Bayesian network model captures causal linkages among climate drivers, ecosystem structure, service supply, and user valuations, while regression analyses (bounded and Tobit models) identify determinants of willingness-to-pay and non-market values. The analytical pipeline is augmented by scenario analysis to compare baseline and climate-resilient management options, with sensitivity analyses to identify critical parameters. The theoretical underpinning integrates ecosystem services theory with resilience theory and prospect theory to account for risk preferences and adaptive behavior under uncertainty. Expected findings indicate that climate uncertainty substantially alters the marginal value and perceived reliability of provisioning services (e.g., fisheries yield, flood protection), while regulating and supporting services exhibit indirect valuation shifts mediated by governance and stakeholder risk perceptions. The framework is anticipated to demonstrate higher value stability when adaptive management and nature-based solutions are prioritized, and when participatory valuation processes are used to align preferences with ecological thresholds. The Lagos site is expected to reveal pronounced valuation of disaster risk reduction and water quality maintenance, whereas the Zeeland site may show stronger valuation of cultural and recreational services coupled with flood buffering under advanced early-warning systems. Cross-site synthesis will yield transferable insights for modular integration of valuation components, enabling policy makers to compare trade-offs under diverse climate pathways. The study contributes to knowledge by presenting a tractable, replicable framework that couples biophysical service supply, economic valuation, and uncertainty propagation within a single analytic platform, extending ecosystem service valuation to explicitly incorporate climate risk in heterogeneous socio-ecological contexts. It advances methodological integration by combining Bayesian networks, Monte Carlo simulation, and mixed-effects regression within a single framework, and provides practical guidelines for policy-relevant decision making under uncertainty. Policy implications include prioritizing climate-resilient, nature-based interventions, refining payment-for-services schemes under uncertainty, and informing spatial planning to maintain multi-service portfolios. The conclusion emphasizes the necessity of participatory, scenario-driven valuation for robust environmental governance and recommends extending the framework to additional regions with similar vulnerability profiles and data availability.