Dissertation Defence: Pattern, Function, and Planning: Modelling Ecosystem Service Dynamics for Sustainable Multifunctional Landscapes in the Canadian Prairies

Ehsan Pashanejad, supervised by Dr. Lael Parrott, will defend their dissertation titled “Pattern, Function, and Planning: Modelling Ecosystem Service Dynamics for Sustainable Multifunctional Landscapes in the Canadian Prairies” in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Earth and Environmental Sciences.

An abstract for Ehsan Pashanejad’s dissertation is included below.

Examinations are open to all members of the campus community as well as the general public. Registration is not required for in-person exams.

---

Abstract

Multifunctional landscapes are essential for sustaining ecosystem services (ES) and agricultural productivity, yet land-use and management practices often create complex trade-offs and synergies. In the Canadian prairies, one of the intensively modified agricultural landscapes, the spatial dynamics of ES interactions remain inadequately understood, limiting their long-term resilience and sustainability. This dissertation addresses this gap by developing and operationalizing a novel “Pattern-Function-Planning” framework, which systematically explores how landscape patterns govern ES flows and their implications for sustainable land management. The research first uses mechanistic modelling to understand pollination dynamics, then employs network analysis to map the functional connectivity of multiple interacting ES. It subsequently explores how these landscape patterns and ES flows mediate agricultural crop yield. Finally, it identifies spatial patterns of trade-offs and synergies among conservation, production, and climate resilience objectives to inform targeted planning. These questions are addressed through a multi-faceted approach integrating spatial ES modelling (ARIES, InVEST, GIS), ecological network analysis, non-linear statistical modelling (GAMs), and multi-objective optimization. Key findings reveal that: over 45% of pollination-dependent croplands in the study area lack sufficient wild pollination; approximately 29% of the selected landscape functions as critical ES interaction hotspots, with natural habitats like wetlands and grasslands serving as vital mediators of ES connectivity; landscape configuration (e.g., connectivity) often exerts greater influence on crop yield than the mere amount of natural habitat; and, while an area covering 27.33% of the landscape faces significant production-conservation trade-offs, only 9.11% currently supports synergistic, resilient production systems. This research demonstrates that landscape pattern is a fundamental driver of the ecological and regional functions that dictate ES flows and bundling. The findings underscore that agricultural output is not just a function of field-level inputs but is deeply embedded within, and responsive to, the broader landscape matrix and the ecological processes it supports. A crucial insight is that strategic management of landscape configuration—such as enhancing connectivity and crop diversity—can offer greater returns for both agricultural performance and ES multifunctionality than focusing merely on the quantity of natural habitat. The empirically grounded “Pattern-Function-Planning” framework, culminating in the spatial optimization analysis, offers a novel and applied approach to explore ES spatial dynamics and reconcile conflicting objectives. This research thus provides pragmatic decision pathways and a spatially explicit basis for policy and land-use planning aimed at fostering sustainable, multifunctional agricultural landscapes where single-priority management is no longer a viable solution.