OPTIMISING LANDSCAPE-SCALE FOREST RESTORATION WITH SPECIES DISTRIBUTION MODELS, REGENERATION TRENDS, AND ECOSYSTEM SERVICE MODELLING

<p><strong>Abstract The urgency of restoring degraded ecosystems has never been more critical as global environmental challenges intensify. This PhD thesis explores landscape-scale ecological restoration, focusing on approaches that integrate future climate resilience, regeneration dynamics, and ecosystem service optimization. Addressing the need for practical and scalable solutions, the research emphasizes methodologies that enhance restoration outcomes while aligning with long-term ecological and socio-economic objectives. By leveraging modeling tools and statistical analyses, this thesis contributes to the growing body of knowledge on restoring complex landscapes effectively and sustainably.</strong></p><p>The degradation of ecosystems worldwide has been exacerbated by habitat loss, fragmentation, and the escalating impacts of climate change. In Aotearoa New Zealand (ANZ), deforestation during both pre- and post-European settlement periods has left extensive tracts of degraded land, providing opportunities for restoration at scale. However, achieving successful landscape-scale restoration requires careful planning and adaptive management, particularly under the pressures of climate change. This research addresses key questions for future-proofing restoration: (1) How will climate change affect the species distributions central to restoration efforts? (2) How do landscape-level factors influence natural regeneration at restoration sites? (3) What are the quantifiable ecosystem service benefits of restoration at a landscape scale?</p><p>This thesis employs a multi-method approach across three core studies to explore these questions, offering insights into how landscape-scale restoration can be planned, implemented, and sustained to meet future challenges.</p>