Jessica A. Benthuysen

Coral reef management under climate change is challenging due to data sparsity and high uncertainty, yet it is essential for informing conservation strategies. We present CoralBlox, a mechanistic discrete time coral ecology model with the explicit aim of supporting rapid scenario exploration and decision making. The model represents discretized distributions of five coral functional groups across configurable spatial scales while incorporating key ecological processes, including coral growth, reproduction, thermal adaptation, and responses to disturbances. Validation against observed data demonstrates that CoralBlox effectively captures major trends in coral cover dynamics across the Great Barrier Reef, particularly for bleaching-driven mortality and recovery patterns. While simplifying ecological complexities, the model maintains sufficient ecological realism to evaluate and compare the result of distinct management strategies. CoralBlox enables comprehensive assessment of potential management interventions with high computational efficiency and interoperability. The model’s flexible architecture makes it extensible to coral ecosystems worldwide, providing valuable exploratory capability for reef management. Teaser: CoralBlox is an efficient coral reef ecology model supporting rapid scenario testing and management decision making under climate change. Highlights: Marine ecosystems are characterized by high uncertainty and data sparsity. Management decisions still need to be made under these uncertain contexts. CoralBlox offers a conceptually simple yet credible representation of ecological processes. Comparatively fast runtimes across different spatial scales enable rapid exploration of plausible future states.

The full text of this preprint has been withdrawn by the authors while they make corrections to the work. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author.

In this study, we have analyzed 13+ years of moored observations of ocean current, temperature, and salinity on the Rottnest Shelf off southwest Australia, to describe the characteristics of the Leeuwin Current, the Capes Current, and associated seasonal variability. The observations capture the Leeuwin Current component anchored on the continental shelf and slope, which extends to ∼300 m, being stronger in the austral winter (peak in June) and weaker in summer (December/January), with an estimated annual mean, poleward volume transport of ∼1.8 Sv (10 ⁶ m ³ s ⁻¹ ). The estimated mean transport is 2.4 Sv when adjusted with a data assimilating model. The variations of the Leeuwin Current are closely associated with thermocline depth variability at the shelf break, with seasonal maximum subsurface temperatures leading the annual peak of the Leeuwin Current by 1–2 months. The 500 m mooring on the continental slope captures the Leeuwin Undercurrent in the 300–400 m depth range. The offshore volume flux in this depth range, likely linked to the offshore bottom Ekman flows on the shelf, is rather weak at this latitude. The Capes Current flows northward, mostly confined in the middle shelf (20–50 m), with a mean equatorward transport of 0.07 Sv from November to March, forced by strong southerly winds. The cross‐shelf flows associated with the Capes Current are weak on the middle shelf and appear strong off Rottnest Island on the edge between the outer and the middle shelf, where active upwelling tends to occur in the summer months.

As the ocean has warmed, in recent decades marine heatwaves (MHWs) have emerged as a major threat to marine ecosystems and ecosystem services, presenting challenges for management of marine fisheries, aquaculture, tourism, and conservation, including for marine protected areas (MPAs). An MHW is a period of unusually high ocean temperatures, often defined as ocean temperatures that are warmer than 90% of the previous observations for a given time of year. MHWs along Australia’s coastal regions have led to mass coral bleaching on the Great Barrier Reef, damage to kelp forests and seagrass meadows in Western Australia, shifts in species, and fish and invertebrate mortality, all creating pressures on fisheries management (as reviewed in Smith et al., 2023). Understanding how climate change influences ocean extremes and impacts societal and natural values is key for evaluating future risks. Growing concerns around the effects of MHWs on marine industries, food security, ecosystem dynamics, and conservation efforts led to the development of MHW response plans for Tasmania and New South Wales during the summer of 2023/24 (Hobday et al., 2024).

Marine heatwaves have profoundly impacted marine ecosystems over large areas of the world oceans, calling for improved understanding of their dynamics and predictability. Here, we critically review the recent substantial advances in this active area of research, including the exploration of the three-dimensional structure and evolution of these extremes, their drivers, their connection with other extremes in the ocean and over land, future projections, and assessment of their predictability and current prediction skill. To make progress on predicting and projecting marine heatwaves and their impacts, a more complete mechanistic understanding of these extremes over the full ocean depth and at the relevant spatial and temporal scales is needed, together with models that can realistically capture the leading mechanisms at those scales. Sustained observing systems, as well as measuring platforms that can be rapidly deployed, are essential to achieve comprehensive event characterizations while also chronicling the evolving nature of these extremes and their impacts in our changing climate.

An accurate representation of physical and biological processes is crucial to resolve larval dispersal pathways and characterize connectivity of coral reef ecosystems. We investigate how hydrodynamic forcings drive larval retention rates during the bi‐annual mass coral spawning of the coral genus Acropora within a coral reef atoll (Mermaid Reef), located off northwestern Australia. By analyzing hydrodynamic conditions during 41 yr of historical spring and autumn coral spawning events, we identify typical and extreme hydrodynamic forcing conditions. Particle tracking using the output from a fine‐scale coupled wave‐flow hydrodynamic model forced with typical hydrodynamic conditions during coral spawning, revealed a mean transport of larvae eastward across the atoll. Transport was mainly driven by a combination of wave and tidal currents, where the residual tidal flow and unidirectional wave flow increased the net export of particles, and the oscillatory tidal (non‐residual) flow reduced the net export of particles from the reef. Importantly, however, numerical simulations forced with extreme hydrodynamic conditions generated by episodic tropical cyclones (11 out of 41 yr) showed large deviations from the typical eastward flow during autumn spawning, generating different connectivity pathways within the reef. Considering the substantial time larvae can be retained within reef systems, overlooking fine‐scale hydrodynamic processes may greatly overestimate larval transport distances between adjacent coral reef atolls. As a result, we emphasize the need to consider fine‐scale hydrodynamic processes within regional connectivity predictions, which is generally not considered yet critical to understand the capacity of reefs to recover following disturbances.

Waves and tides are often the two primary forcing mechanisms responsible for driving hydrodynamic processes within coral reefs worldwide. Although wave‐ and tide‐driven flows are individually well understood, there remain considerable gaps in our understanding of how their interactions control the reef circulation, and consequently how they shape a range of ecological processes. During 11 months of hydrodynamic measurements across Mermaid Reef, a coral reef atoll off northwestern Australia, the atoll was regularly exposed to a range of wave and tidal conditions. Using a validated wave‐flow numerical model, we showed that wave‐ and tidally driven processes interacted to drive the reef's circulation through several mechanisms including wave‐current interactions and tidal water level modulation of wave‐driven flows. The atoll morphology, particularly the higher elevation of the western reef flat, was found to be a key factor controlling the relative importance of waves and tides. Wave‐driven processes dominated for tidal ranges smaller than required to expose the shallower western reef flat. In contrast, tidal processes dominated for larger tidal ranges, when the western reef flat temporarily acted as a physical barrier to incoming and outgoing flows. The residual (tidally averaged) circulation was consistently directed eastward across the atoll. Over time scales of several months to years, Mermaid Reef can be classified as a tide‐dominated reef. However, due to the incident wave energy and spring‐neap tidal range variability, the relative importance of the dominant hydrodynamic drivers can vary on time scales of hours to days allowing wave processes to episodically dominate the reef circulation.

The 2020 marine heatwave (MHW) in the Great Barrier Reef (GBR) and Coral Sea led to mass coral bleaching. Sea surface temperature anomalies reached +1.7 °C for the whole of the GBR and Coral Sea and exceeded +2 °C across broad regions (referenced to 1990–2012). The MHW reached Category 2 (Strong) and warm anomalies peaked between mid-February and mid-March 2020. The MHW’s peak intensity aligned with regions of reduced cloud cover and weak wind speeds. We used a MHW framework to assess the ability of an operational coupled ocean-atmosphere prediction system (Australian Community Climate and Earth System Simulator Seasonal version 1) to capture the MHW’s severity, duration, and spatial extent. For initial week predictions, the predicted MHW severity generally agreed with the magnitude and spatial extent of the observed severity for that week. The model ensemble mean did not capture the MHW’s development phase at lead times beyond the first week. The model underestimated the MHW’s spatial extent, which reached up to 95% of the study area with at least Moderate severity and up to 43% with at least Strong severity. However, most forecast ensemble members correctly predicted the period of Strong severity in the first week of the model forecast. The model correctly predicted MHW conditions to persist from mid-February to mid-March but did not capture the end of the MHW. The inability to predict the end of the event and other periods of less skilful prediction were related to subseasonal variability owing to weather systems, including the passage of tropical cyclones not simulated in the model. On subseasonal time scale, evaluating daily to weekly forecasts of ocean temperature extremes is an important step toward implementing methods for developing operational forecast extremes products for use in early warning systems.