Multi-scale remote sensing of coral reef community dynamics
Date
2026
Authors
Harrison, Dominica Elaine
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Abstract
Ecological patterns and processes are inherently scale-dependent, yet our ability to observe and quantify how community structures vary across space and time remains a central challenge in ecology. This dissertation develops a multi-scale framework to understand how coral reef benthic communities and compositions assemble across spatial gradients and reorganize through time. Focusing on reef-building corals as marine foundation species, I integrate imaging spectroscopy, spatial modeling, and three-dimensional (3D) structural mapping to bridge organismal scales; embayment (1–3 km) and regional spatial scales (~32 km); and multiyear temporal scales spanning an acute disturbance event (a 10-month El Niño–induced marine heatwave) and a prolonged disturbance gradient (a chronic anthropogenic gradient). By linking ecological theory with remote-sensing technologies, this work addresses long-standing technological limitations in coral reef mapping, in which classifications have historically been limited to coarse benthic categories or geomorphic proxies.
Using coral reefs across southwest Hawaiʻi Island, USA, as a case study, my second chapter demonstrates that fine-scale biological and morphological variation in corals can be detected and scaled using high-resolution imaging spectroscopy. Through a sensitivity analysis that combines in-situ spectral libraries, endmember modeling, simulated ocean optical properties, and Global Airborne Observatory (GAO) data, I quantify how organismal and benthic signals propagate through the water column to produce detectable airborne spectral signals. In my third chapter, I demonstrate that spectral decomposition isolates higher-order principal components that retain benthic signal, enabling their delineation, classification, and ecological attribution to benthic compositional assemblages, which I term “spectral communities.” Scaling from individual embayments to a 32-km regional coastline in chapter four, I demonstrate that spectrally derived classes, identified through spatial clustering and k-means classification of higher-order principal components, are organized along continuous benthic compositional gradients shaped by interacting, scale-dependent processes. Broad-scale patterns reflect the combined influence of environmental filtering and dispersal limitation; mesoscale structure emerges from dispersal and neighborhood effects; and fine-scale heterogeneity is driven primarily by local environmental filtering.
In chapter 5, focusing on temporal coral reef dynamics in Kiritimati, Republic of Kiribati, I integrate structure-from-motion (SfM) photogrammetry and a convolutional neural network to automate benthic classification and quantify reef structural complexity, seven years after the 2015–2016 marine heatwave and across a persistent human disturbance gradient. In my final chapter, I show that acute thermal stress and chronic human disturbance interact, leading to the reassembly of coral cover, taxonomic morphology, and structural complexity. Although reefs exhibited partial recovery seven years post-disturbance, chronic human pressure constrained recovery trajectories and altered morphological composition, revealing scale-dependent resilience and functional reassembly.
Overall, this dissertation develops a scalable and repeatable approach for detecting, modeling, and interpreting coral reef dynamics across space and time, providing critical tools for monitoring and conservation in a rapidly changing climate. This dissertation also demonstrates how integrating imaging spectroscopy, spatial modeling, and 3D structural mapping can address fundamental ecological questions about scale dependence, community assembly, and the processes that structure benthic composition in coral reef ecosystems.
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Keywords
Coral reefs, Imaging spectroscopy, Remote sensing, Spatial ecology