Supporting resilience-based coral reef management using broadscale threshold approaches

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Burt, Anna Koester, Nancy Bunbury, Philip Haupt, Rowana Walton, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4867751/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 16 Jul, 2025 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract Managing coral reefs to maintain ecosystem function and maximise resilience requires identification of resilience indicators and clear ecological reference thresholds for reef managers to maintain or aim for. In the absence of local resilience-based targets, reef managers can conduct local-scale resilience assessments by collecting data on resilience indicators and comparing them to recently established broadscale thresholds which have been defined by incorporating large spatial variability. This study documents the application of these broadscale threshold approaches to kick-start resilience-based management at Aldabra Atoll UNESCO Marine World Heritage Site. Aldabra’s seaward coral reefs conformed to the expected resilience of a well-managed and remote marine reserve. All but one reef met or exceeded thresholds for each of the five assessed resilience indicators and fell within the ‘recover’ strategy of the management strategy analysis. Combining the individual indices into a synthetic index of resilience gave an atoll-level estimate of reefs having an 87.5% ‘chance of recovery’ post-disturbance. Reef resilience predictions largely aligned with our data on post-bleaching coral trajectories. We recommend additional broadscale threshold categories that could be defined and included in future assessments, and suggest local factors that need to be considered to fine-tune the assessments at site-level. Earth and environmental sciences/Ecology/Ecosystem ecology Biological sciences/Ecology/Ecosystem ecology Earth and environmental sciences/Environmental sciences/Environmental impact Earth and environmental sciences/Ocean sciences/Marine biology Earth and environmental sciences/Climate sciences/Climate change/Climate change impacts/Environmental health Earth and environmental sciences/Climate sciences/Ocean sciences/Marine biology Earth and environmental sciences/Environmental sciences ecological thresholds resilience indicators coral reef conservation coral bleaching coral reef recovery UNESCO World Heritage Figures Figure 1 Figure 2 Figure 3 Introduction In the face of climate change and lagging political responses to reducing greenhouse gas emissions, even the best protected coral reefs are transforming rapidly 1–3 . Coral reef conservation and management goals therefore need to shift focus from maintaining intact systems to preserving ecosystem functions 4,5 . Managing reefs to maintain ecosystem function and maximise resilience—the ability to resist and recover from disturbances 6 —is complex and requires clear articulation of management aims (i.e., to maximise resilience of what to what?), identification of resilience indicators and clear reference thresholds for reef managers to maintain or aim for 4,5,7 . Shifting to resilience-based reef management requires that targets be defined a priori , but defining resilience-based targets depends on availability of historical local or regional data about marine communities and natural variability 8,9 . Reef management authorities often lack these data, or the capacity and resources to identify localised targets 10,11 . It is feasible, however, for reef managers with reef monitoring capacity to conduct local-scale resilience assessments by collecting data on resilience indicators and comparing them to recently established broadscale thresholds which have been defined by incorporating large spatial variability. Although there are inherent problems in applying general values to a particular reef site, managers can adopt them as temporary ‘thresholds of potential concern’ until more site-specific data can be acquired 12,13 . Broadscale parameters established for predicting the recovery potential of live coral cover include thresholds for reef depth, structural complexity, herbivore biomass, juvenile coral density 14 , and have also been developed to define minimum resident reef fish biomass in no-take zones 15 . Another approach is to investigate the composition and organisation of reef communities which can explain energy flows through the ecosystem and therefore be used to evaluate ecological condition and expected vulnerability to climate change. For example, Graham et al. 16 quantified the expected fish trophic distributions across a gradient of human disturbance. This provided specific predictions of biomass distributions between trophic levels defined for different levels of human disturbance, from which managers can compare their own local distributions 16–18 . Darling et al. 19 produced one of several recent guides for reef conservation management under climate change (see also reviews by Boon and Baxter 20 , Harvey et al. 21 and McLeod et al. 4,22 ), but it is the only approach that provides meta-analysis derived indicator thresholds that can readily be applied by managers at the local scale. The metrics of this assessment (percent cover of framework corals, prior heat stress, and magnitude of heat stress) combine information on key ecological processes: structural complexity, carbonate production, reef growth and past thermal stress to allocate reefs to one of three reef management strategies, i.e., protect, recover or transform. Despite reef resilience assessments becoming more common, they rarely present structured processes to guide and justify indicator selection 23 , and there are – to our knowledge – no published examples of the use of the above broad-scale thresholds being used by reef managers to assess site-level resilience and guide management. This study trials the application of these broadscale threshold approaches for resilience-based management at Aldabra Atoll, in the small island large ocean state of Seychelles. We use reef data collected in 2014 and 2015 (prior to bleaching at Aldabra in 2016) to: ( 1 ) assess relative resilience of Aldabra’s seaward coral reef sites by evaluating the position of the atoll's seaward reefs in broadscale analyses as described in Graham et al. 14 and MacNeil et al., and along known disturbance gradients as in Graham et al. 16 ; ( 2 ) combine the different scores for the resilience indicators in relation to the thresholds into a 'unique status assessment' for each site; and ( 3 ) classify Aldabra's seaward coral reefs into management strategies according to Darling et al.’s 19 portfolio. We discuss the resilience assessments in the context of the 2014–2017 global bleaching event on Aldabra’s live coral cover and coral recovery trajectories between 2016 and 2022, and how these assessments/indicators can be applied elsewhere. Methods Study site Aldabra, a UNESCO Marine World Heritage Site, is a remote atoll in the Western Indian Ocean within the Republic of Seychelles, located ca. 400 km northwest of Madagascar (Fig. 1 ). Aldabra hosts the largest reef system in Seychelles, which, due to its protection and remoteness, has limited local stressors. The atoll has been managed by a public trust, the Seychelles Islands Foundation (SIF) since 1979 and was designated as Special Reserve in 1981. Aldabra is uninhabited except for 10–20 SIF staff based at the research station, who monitor the atoll's ecosystems and biodiversity year-round. Ongoing management efforts on Aldabra include maintenance of the no-take protected area (2559 km 2 since 2018; formerly 439 km 2 ) while allowing limited tourism and a small-scale subsistence fishery (only for SIF staff), and restoring ecosystems (e.g. invasive alien species eradications 24 ; native species re-introductions 25 ; marine debris removal 26 ). Due to Aldabra’s remoteness and history of protection, its coral reefs are thought to be relatively resilient, with potential to advance knowledge of natural ecosystem variation in the absence of significant direct stressors 27 . Data collection and processing Coral reef monitoring projects have been conducted sporadically at Aldabra since the 1960s with varied methodologies 28–33 but a long-term annual reef monitoring programme was established by SIF in 2014. The 12 permanently fixed Aldabra Reef Monitoring (ARM) sites represent each of Aldabra’s coastlines with varying oceanographic conditions (Fig. 1 ) and data on fish (a subset of species) and benthic communities is collected along permanent transects annually 1,27,34,35 (Table S1 ). In December 2015, additional surveys were conducted to obtain data on reef structural complexity, coral recruit density, total fish biomass and total herbivore biomass to supplement existing data (Table S1 ). We assessed reef resilience and future management strategies for the Aldabra reef monitoring sites using data collected in 2014 (percent framework corals) and 2015 (structural complexity, total fish biomass, total herbivore biomass, coral recruit density; Table S1 ). At each of the eight sites, perpendicular to the reef slope, three 50-m long transects were laid at 5 m depth and one 50-m long transect at 15 m depth. On each transect, data on fish community, structural complexity and coral juvenile density were collected. The fish community was surveyed by recording number, identity (to species) and size (to nearest cm) of all fish > 8 cm by a single observer along the entire 50-m transects with a transect width of 4 m. At the start of every survey day, fish size estimation was calibrated using PVC pipes of known lengths. Count data was converted to biomass (kg/ha) using published length-weight relationships 36–42 . Structural complexity was visually estimated using the 6-point scale of Wilson et al. 43 at the start of each transect. The number, identity and size of juvenile coral colonies (< 5 cm diameter) was recorded in five replicate 0.25-m 2 quadrats per transect. Benthic photoquadrat surveys were conducted at each site along the permanent transect on two 10-m long sub-transects (10 m gap between sub-transects) on both sides of the tape measure as described in Koester et al. 27 . The benthic photos were analysed using Coral Point Count with Excel extensions 44 by identifying the benthos at 16 randomly assigned points per image as described by Cerutti et al. 1 . Study approach and data analysis All statistical analyses were conducted using R (version 4.1.2 45 ). Whilst acknowledging that depth is an important factor influencing reef communities, particularly fish assemblages 46 , data from the three 5 m and one 15 m transects were pooled as only one transect was surveyed at 15 m depth at each site (see ‘Data collection and processing’). 1. Comparisons with published recommended thresholds Values of four reef characteristics (total reef fish biomass [including only reef fish following MacNeil et al. 15 ], herbivorous fish biomass, coral juvenile density and structural complexity) were compared against reference thresholds from MacNeil et al. 15 and Graham et al. 14 with two-tailed one sample t-tests (Table 1 ). Table 1 Components of the resilience and future management assessment showing corresponding ecosystem processes and functions. Approach Method Metric & year of data collection Process of interest a Indicative of a References Analysis Resilience Assessment Comparison with published recommended reference thresholds Total fish biomass (1013 kg ha − 1 of diurnally active, non-cryptic resident reef fish fish > 10 cm of 20 families); data collected in 2015 Productivity Community functions MacNeil et al. 15 Two-tailed one-sample t-tests against reference thresholds Scoring of t-test outcomes Scores used in 'one out, all out' method and synthetic index Herbivore biomass (177 kg ha − 1 ); data collected in 2015 Herbivory Primary production, community functions Graham et al. 14 Coral juvenile abundance (>6.2 per m 2 ); data collected in 2015 Coral recruitment Reef recovery (gain of primary habitat) Graham et al. 14 Structural complexity (> 3.1); data collected in 2015 Productivity, active reef growth Habitat availability, benthic community landscape, enhanced coral settlement Graham et al. 14 Comparisons based on trophic pyramids distributions Trophic levels of diurnally active, non-cryptic, reef-associated fish; data collected in 2015 Productivity Human impact (cf. unexploited systems) Graham et al. 16 Comparison of trophic pyramids with those of “fished” and “unfished” seascapes as per Graham et al. 16 and the classic trophic pyramid as per Trebilco et al. 18 Management Assessment Comparison to established threshold values of heat stress Water temperature (satellite derived 53 ) Physiological stress Significant thermal stress Darling et al. 19 Assessing local DHW value during the 2014–2017 global bleaching event against 4 DHW threshold Classification of sites into management strategy portfolio of Darling et al. 19 : protect, recover or transform. Comparison against the recommended minimum reference value (10%) Percent cover of competitive and stress-tolerant corals (framework corals); data collected in 2014 Coral calcification Active reef growth (gain of primary habitat) Darling et al. 19 T-test against reference threshold a also with reference to Brandl et al.’s 76 eight core ecosystem processes T-test outcomes for each reef characteristic were scored for Aldabra overall and for each site. A score of 1 was given if the observed mean was significantly higher than the reference threshold; zero if the observed mean was not statistically different from the reference threshold; and − 1 if the observed mean was significantly lower than the reference threshold (i.e., target was not met). To combine the different reef characteristics into a 'unique status assessment', two methods were used: the 'one out, all out' method and calculation of a 'synthetic index' (see also Halpern et al. 48 ) that we developed to incorporate responsiveness to data quality and real differences in coral reef health. The 'one out, all out' method was used against all four characteristics whereby if any characteristics scored − 1, the area did not meet the target 47 . The synthetic index attempted a more nuanced investigation into the data and was calculated by normalising the scores ( u ) for all four characteristics ( tfb : total fish biomass, hbm : herbivorous fish biomass, juv : coral juvenile abundance, rug : rugosity): $$\:I=\left(\frac{\sum\:\left({u}_{tfb},{u}_{hbm},{u}_{juv},{u}_{rug}\right)+4)\:}{4+4}\right)\times\:100$$ The synthetic index therefore provides us with a score out of 100 that reflects the level of resilience based on all four characteristics. 2. Trophic pyramid structure comparisons Following the method outlined by Graham et al. 16 and using fish biomass data (kg/ha) we: ( 1 ) assigned trophic levels at the species level using Fishbase 41,49 ; ( 2 ) calculated relative distribution of biomass among five trophic levels to create trophic pyramids for Aldabra overall and each site individually; and ( 3 ) compared these trophic pyramids to the ‘fished’ and ‘unfished’ seascapes of Graham et al. 16 and the classical trophic pyramid (see Trebilco et al. 18 ). The five trophic levels, as suggested by Graham et al. 16 , are: 1: 2.0–2.5, 2: 2.5–3.0, 3: 3.0–3.5, 4: 3.5–4.0 and 5: 4.0–4.5. To enable direct comparison with Graham et al. 16 , we excluded any fish families that are not part of the 17 target families listed by Graham et al. 16 . 3. Management strategy classification We used coral community data (pre-bleaching percent coral cover) and degree heating weeks (DHW) data accessed from the National Oceanic and Atmospheric Administration 50 to evaluate the ecological condition of Aldabra’s reef sites and their exposure to climate change following Darling et al. 19 (Table 1 ). We then classified Aldabra’s reef sites based on the ‘protect’, ‘recover’ and ‘transform’ management strategies outlined by Darling et al. 19 . These strategies were to: ( 1 ) ‘protect’ functioning reefs that were associated with limited exposure to recent bleaching-level thermal stress (DHW < 4°C-weeks) and maintained coral cover above 10%; ( 2 ) ‘recover’ reefs that have recently maintained cover above 10% but were exposed to severe potential bleaching stress in 2014–2017; and ( 3 ) for reefs with coral cover below net-positive carbonate budgets (< 10% hard coral cover), societies may ultimately need to ‘transform’ away from reef-dependent livelihoods 19 . Ecological condition was represented by the potential for a net-positive carbonate budget before the 2014–2017 bleaching event 19 . To assess ecological condition we: ( 1 ) assigned life history strategies (‘competitive’, ‘generalist’, ‘stress-tolerant’, ‘weedy’) at the genera and growth form level following Darling et al. 51 , using the Coral Traits Database 52 ( https://coraltraits.org/ ); ( 2 ) calculated percent cover of (summed) competitive and stress-tolerant corals (hereafter, ‘framework’ corals); and ( 3 ) compared Aldabra data against the threshold value (10% cover 19 ) using two-tailed one-sample t-tests. Climate change exposure was represented by thermal stress during the 2014–2017 bleaching event 19 . To assess climate change exposure we: ( 1 ) extracted daily DHW data available from NOAA Coral Reef Watch 53 between two coordinates at Aldabra (coordinate one: -9.575; 46.075, coordinate two: -9.225; 46.675) for the period January 2014 to December 2017 through the ERDDAP data server via the Pacific Islands Ocean Observing System (PacIOOS) website ( https://pae-paha.pacioos.hawaii.edu/erddap/griddap/dhw_5km.html ); ( 2 ) calculated maximum DHW estimated for each year; and ( 3 ) compared these Aldabra data against the established threshold for thermal stress exposure (4 DHW °C-weeks 19 ). The two indices (ecological condition and climate change exposure) were then placed into Darling et al.’s 19 management strategy portfolio, which recommends a ‘protect’ strategy if reefs were exposed to thermal stress below DHW 4°C-weeks during 2014–2017 and had > 10% cover of framework corals, a ‘recover’ strategy if reefs were exposed to severe bleaching-level stress (DHW > 4°C-weeks during 2014–2017) and had > 10% cover of framework corals, and a ‘transform’ strategy if reefs were exposed to severe bleaching-level stress and had < 10% cover of framework corals. Results Recommended threshold comparisons Comparing the observed values versus recommended thresholds for four reef characteristics across all eight sites indicated high likelihood of resilience on the seaward forereef slopes of Aldabra using both the ‘one out, all out’ method, and the synthetic index (Table 2 ). Reef characteristics met recommended thresholds — structural complexity was not significantly different from the recommended threshold ( t = -0.13125, df = 31, p > 0.05; Table S2), while total and herbivorous fish biomass and juvenile coral colony density were significantly greater than recommended ( t = 3.3138, df = 31, p < 0.01; t = 3.8482, df = 31, p < 0.01, t = 5.5305, df = 30, p < 0.001, respectively; Table S2). Combining the individual indices into a synthetic index of resilience gave an atoll-level estimate of reefs having an 87.5% chance of recovery post-disturbance (Table 2 ). Table 2 Unique status assessments considering four reef characteristics (total fish biomass; herbivorous fish biomass; juvenile coral density; structural complexity) overall and at each site. Numbers represent outcomes from the two-tailed one-sample t-tests (pooling three ‘5 m depth’ and one ’15 m depth’ transects: df = 3 at the site-level; df = 31 overall); observed mean was significantly higher ( 1 ), lower (-1) or not statistically different (0) from the recommended threshold. Columns represent assessment outcomes using the 'one out, all out' method (Pass/Fail based on all characteristics) and the 'synthetic index' expressed on a scale of 0–100%. Site Total fish biomass Herbivorous fish biomass Juvenile coral density Structural complexity One-out, all-out Synthetic Index score (%) Overall 1 1 1 0 Pass 87.5 ARM01 0 0 1 1 Pass 75 ARM02 0 0 1 1 Pass 75 ARM03 0 0 0 0 Pass 50 ARM04 0 0 0 0 Pass 50 ARM05 0 0 0 0 Pass 50 ARM06 1 0 1 0 Pass 75 ARM08 0 0 0 0 Pass 50 ARM12 0 0 0 -1 Fail 37.5 Investigating individual sites showed similar patterns to the overall assessment (Table 2 ). Seven (of the eight) sites displayed high likelihood of resilience using the ‘one out, all out’ method and the synthetic index (i.e., index score ≥ 50%). For the three reefs (ARM01, ARM02, ARM06) with an index score of 75% we can be confident that they would be likely to recover following a disturbance. Site ARM12 met thresholds for three of the four reef characteristics: total reef fish biomass, herbivorous fish biomass and juvenile coral density ( t = 1.2099, df = 3, p > 0.05; t = 1.6439, df = 3, p > 0.05; t = 0.55641, df = 3, p > 0.05, respectively; Table S2). However, the structural complexity threshold was not met ( t = -9.3531, df = 3, p < 0.01; Table S2), resulting in failure using the ‘one out, all out’ method. Combining the individual indices into a synthetic index of resilience gave a site-level estimate of 37.5% chance of reef recovery post-disturbance (Table 2 ). Trophic pyramid structure comparisons The overall trophic pyramid of the reef fish community compared favourably to Graham et al.’s 16 concave unfished pyramid shape (Fig. 2 , Figure S1 ). At the site-scale, seven of the eight pyramids showed higher proportions of upper trophic level biomass than expected based on a classic biomass pyramid 18 , approaching Graham et al.’s 16 concave shape. Community biomass was greater than the recommended 650 kg/ha at the atoll-level (mean biomass = 1846 ± 255 SE kg/ha) and for all sites (mean biomass ranged from 986 ± 157 kg/ha at ARM01 to 4267 ± 756 kg/ha at ARM06; Table S2). Management strategy classification All but one of Aldabra’s seaward coral reefs fell within the ‘recover’ strategy of Darling et al.’s 19 management portfolio: predicted maximum heat stress was at > 6 DHW in April 2016 (Figure S2) and the cover of competitive and stress-tolerant coral species did not differ from the 10% threshold at all sites except ARM05 (Table S3). Site ARM05 therefore fell within the ‘transform’ strategy, whilst all other sites fell within the ‘recover’ strategy. Discussion By using multiple approaches to evaluate site-level resilience, we were able to establish that in 2015 (pre-bleaching) Aldabra’s seaward coral reefs conformed to the expected resilience of a well-managed and remote marine reserve. For each of the assessed resilience indicators (total and herbivorous fish biomass, trophic fish biomass distributions, coral juvenile density, and structural complexity), the reefs met or exceeded multiple thresholds. Combining the individual indices into a synthetic index of resilience gave an atoll-level estimate of reefs having an 87.5% ‘chance of recovery’ post-disturbance. In addition, within Darling et al.’s 19 management strategy analysis, all but one of Aldabra’s seaward coral reefs fell within the recover strategy, meaning they are predicted to recover despite exposure to severe bleaching stress. Crucially, the resilience predictions mostly align with post-bleaching data on Aldabra’s reef dynamics (Table S4; Figure S3), validating the application of these approaches. Resilience assessment In 2015, both total (986–4267 kg/ha) and herbivore (264–958 kg/ha) fish biomass at all seaward coral reefs sites on Aldabra met or exceeded recommended thresholds (total fish biomass: 1000 kg/ha 15 ; herbivore biomass: 177 kg/ha 14 ; Fig. 3 ). These biomass figures are equivalent to other remote and protected sites, like the Chagos Archipelago 54 , but align more closely with the biomass recorded around the inhabited atoll of Diego Garcia, where subsistence fishing occurs, than the uninhabited and unfished Northern Atolls 55 . This could indicate that even a population of < 1 person/km 2 on Aldabra may have an impact on resident fish biomass via the Aldabra subsistence fishery, as also suggested by Fournier-Carnoy 56 . Despite this, we found that Aldabra’s fish biomass trophic pyramids have a concave structure (except ARM08), where most of the biomass is located in the top (predator) and bottom (herbivores) trophic levels. This indicates energy-balanced communities 16 and is similar to other remote and protected locations (e.g. Mexico 57 ). Aside from the threat of climate driven changes in fish community structure and biomass 58–60 , the present state of relative health in fish biomass and trophic structure at Aldabra is threatened by increasing poaching (SIF, unpubl. data). With fishers travelling longer distances 61 and dwindling stocks elsewhere, Aldabra’s fish biomass is highly attractive, so greater surveillance and enforcement of the reserve will be a key management strategy to continue to meet these resilience thresholds. The Aldabra subsistence fishery could also shift efforts from predominantly bottom fishing which targets reef fish, to trolling for pelagic species. The high herbivorous fish biomass found across Aldabra’s reef sites promotes the availability of suitable coral larvae settlement substrates 14 . As such, coral juvenile density at all reef sites in this study (7.0–25.8 coral juveniles/m 2 ) met or exceeded the recommended resilience indicator threshold 14 of 6.2 coral juveniles/m 2 . All sites also met or exceeded the recommended threshold for structural complexity, except ARM12. This site is located in the south-east of the atoll and exposed to high and persistent wave energy 62 . Reefs in such conditions naturally consist of more stable coral growth forms (e.g. encrusting and massive 63 ), impacting the structural complexity score of the reef. The site met all other thresholds, highlighting site-specific factors that can now be considered and incorporated when defining (or refining) the local thresholds used for local resilience-based management. Predicted resilience vs post-disturbance trajectories Our research presents a snapshot of one point in time, but studies of Aldabra’s reefs from as early as the 1960s align with our findings. The north-west reef front of Aldabra was described as having the most ‘luxuriant coral growth’ 28,29,32 . This corresponds with our findings of high structural complexity and a net positive carbonate budget at all sites except ARM12 and ARM05 in the south-east and east, and the high resilience index scores at sites on the north-west coast. The south to south-east reef fronts (sites ARM08, ARM12), were assumed to have undergone catastrophic cyclone damage in the years preceding the 1960s surveys 28,29,32 , and both sites are naturally exposed to stronger waves than the northern coast, shaping benthic community composition 62 . The fact that our 2015 surveys show similar patterns to those described 50 years ago, despite the impacts of the 1998 global coral bleaching event 64 , demonstrates the long-term resilience of several areas of reef and supports the accuracy of both the assessment methods and resulting resilience scores. Contemporary data, collected annually at Aldabra since 2014, allow preliminary checks of our predicted resilience from this study against observed changes in ecosystem community and processes following the 2016 bleaching event, which peaked at Aldabra in April 2016. Overall, this event caused a reduction of relative hard coral cover of 54% 1,27 , with substantial variation across sites (14–73% reduction; Table S4, Figure S3). By early 2022, six years post-bleaching, relative hard coral cover at these sites reached 43–107% of the pre-bleaching cover in 2014 (Table S4). This highlights that live coral recovery potential (one component of ecosystem resilience) varied across sites, and in some cases was surprising compared to our estimates of predicted resilience. For example, our 2015 resilience assessment highlighted ARM12 as potentially less resilient than the other reefs, but this was one of the two sites that reached or exceeded pre-bleaching hard coral cover values by 2022 (Table S4, Figure S3). Conversely, site ARM05, which met all resilience indicator thresholds, experienced relatively low hard coral recovery, only reaching 43% of the pre-bleaching cover by 2022. This lower recovery trajectory was attributed to rapid expansion of the calcareous green algae Halimeda spp., which is more abundant on the eastern seaward reefs of Aldabra 27 , attributed to an increase in hydrodynamic energy from west to east 32,65 . Potentially we need to consider some additional indicators such as Halimeda specific thresholds within future resilience assessments for Aldabra. Overall, while trends in live coral cover followed expectations, we can now describe additional site-specific characteristics likely affecting resilience/recovery potential. For example, at Aldabra, we can be less concerned by lower complexity scores in areas exposed to high and persistent wave energy but consider additional indicators to track the extent of Halimeda spp., especially on eastern reefs. Aldabra’s daily temperature regimes are known to influence fine-scale resilience patterns, especially when comparing the lagoonal vs. seaward coral reefs. Aldabra’s lagoon, which has a much greater daily temperature fluctuation saw less mortality and faster recovery from the 2016 bleaching event 27 . Localised nutrient input from seabird colonies via guano deposits may also influence the resilience potential of adjacent reefs around islands 66 . At Aldabra these inputs are patchy 67 due to tidal changes, strong currents and because seabird colonies (Fig. 1 ) are restricted by the presence of invasive mammals. Both of these factors (temperature regimes and levels of seabird-derived nutrients) should be considered as additional broadscale resilience indicators to future assessments for resilience-based management, although these proposed indicators require more resources to acquire site-level data than the indicators used in this study. Management assessment All but one of Aldabra’s seaward reef sites in this study fell within the recover strategy under Darling et al.’s 19 approach. The management goal in this strategy is to move reefs back above the 10% threshold of framework coral cover as quickly as possible following climate impacts. Active management strategies to achieve this include minimising local stressors (e.g., invasive species control on islands, pollution control, reduced tourism activities, reduced fishing pressure) and conducting active restoration (e.g., coral gardening or other reef restoration techniques, coastal habitat restoration). Two Aldabra reef monitoring sites with high synthetic index scores (ARM01, ARM06) – our proxy for resilience – are located closest to local human activity and potential stressors: the research station, the food security and the tourism zones (Fig. 1 ). These findings suggest that the current level of human activity in the vicinity of these sites has minimal impact on site-level reef resilience. Other local stressors identified by managers include plastic pollution and invasive alien mammals. An estimated 500 tonnes of plastic pollution have accumulated along Aldabra’s coastline 26 . Evidence suggests that plastic could impact coral health and subsequent resilience 68 . SIF already undertakes active management of this issue through regular clean-ups, although limited resources hinder removal at scale 26 . Invasive alien mammals are known to suppress seabirds and their nutrient inputs on islands 69 . Eradicating introduced rats and cats from Aldabra would kickstart restoration of a more diverse breeding seabird community across the atoll. This in turn is expected to substantially increase the quantity and distribution of seabird-derived nutrient subsidies entering near-shore reef systems. These nutrient subsidies are now understood to enhance reef resilience through faster coral growth, higher recruitment rates and higher reef fish biomass 66,69–72 . As a strategy to enhance coral resilience at Aldabra, a rat and cat eradication is therefore of highest priority and an eradication feasibility assessment for the atoll is currently underway. Usefulness of the approaches used Despite efforts to make the concept of resilience-based management operational to reef managers and conservationists (e.g. Graham et al. 14 , Maynard et al. 73 ), uptake has been slow. The application of several approaches to assess coral reef resilience at Aldabra has been largely successful, with reef resilience predictions mostly aligning with observed post-bleaching coral trajectories. As reef managers, we found the exercise highly valuable for Aldabra—the largest reef system in Seychelles and an important coral larvae source for the region 74,75 . Combining resilience indicators into the synthetic index was an effective way of summarising multiple results at monitoring site level, but the variability of index scores between sites meant an island-level score was less valuable from a site management perspective. It would be a valuable exercise to conduct similar resilience-based management assessments across Seychelles and other island groups where data is available. Such reef resilience mapping could be combined with recent coral reef connectivity data 74,75 to strengthen and inform reef system management strategies, define national-level resource and conservation priorities and feed into monitoring national contributions to meeting the Kunming-Montreal Global Biodiversity Framework objectives. With the development of appropriate tools, such as analysis and tracking tools via an open access app, resilience-based management approaches are likely to be extremely important for identifying and protecting the reefs most likely to survive repeated bleaching events. With bleaching events becoming more frequent and intense, applying these broadscale thresholds can provide reef managers with tangible resilience targets to maintain, improve or aim for, and help guide and implement adaptive resilience-based management actions for coral reefs. Declarations Competing interests The authors declare no competing interests. Funding The development and set-up of the Aldabra Reef Monitoring (ARM) programme was funded by the Global Environmental Facility (GEF Project ID 3925). The annual ARM surveys were funded by the Seychelles Islands Foundation. Open Access publishing of this article was funded by the University of Bremen. Author Contribution AJB and AK contributed equally to this work and are joint first authors. AJB: Conceptualization, Methodology, Validation, Investigation, Data Curation, Writing - Original Draft, Writing - Review & Editing, Visualization, Project administration. AK: Methodology, Validation, Formal analysis, Investigation, Data Curation, Writing - Original Draft, Writing - Review & Editing, Visualization, Funding acquisition. NB: Conceptualization, Writing - Original Draft, Writing - Review & Editing, Supervision, Project administration, Funding acquisition. PH: Methodology, Investigation, Data Curation, Writing - Review & Editing, Funding acquisition. RW: Formal analysis, Data Curation, Writing - Review & Editing. FFD: Writing - Review & Editing, Supervision, Project administration, Funding acquisition. KCS: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Data Curation, Writing - Original Draft, Writing - Review & Editing, Visualization, Project administration. Acknowledgement We thank the Seychelles Islands Foundation (SIF) and their current and former staff members for their work and support. Specifically, we extend our appreciation to the many Aldabra staff who over the years have contributed to marine data collection and planning. We are grateful to M. Pratchett, K. Nash and N. Graham who provided valuable comments on earlier versions of this manuscript. Data Availability The data on fish diversity, abundance, and biomass utilised in this research is accessible on Figshare (DOI: https://doi.org/10. 6084/m9.figshare.22792580.v1). The data on coral juvenile abundance and diversity is available in the supplementary files of Koester et al. 2021 (PLOS ONE 16(12): e0260516. https://doi.org/10.1371/journal.pone.0260516). All other data used for this research is available from the corresponding author on reasonable request. References Cerutti, J. M. B. et al. Impacts of the 2014–2017 global bleaching event on a protected remote atoll in the Western Indian Ocean. Coral Reefs 39, 15–26 (2020). Head, C. E. I. et al. 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Effects of climate-induced coral bleaching on coral-reef fishes - ecological and economic consequences. in Oceanography and Marine Biology - An Annual Review (eds. Gibson, R., Atkinson, R. & Gordon, J.) vol. 20081322 251–296 (CRC Press, Boca Raton, USA, 2008). Pratchett, M. S., Hoey, A. S. & Wilson, S. K. Reef degradation and the loss of critical ecosystem goods and services provided by coral reef fishes. Curr. Opin. Environ. Sustain. 7, 37–43 (2014). Januchowski-Hartley, F. A., Vigliola, L., Maire, E., Kulbicki, M. & Mouillot, D. Low fuel cost and rising fish price threaten coral reef wilderness. Conserv. Lett. 13, e12706 (2020). Haupt, P. Reef fish associations with benthic habitats at a remote protected coral reef ecosystem in the Western Indian Ocean ~ Aldabra Atoll, Seychelles. (Rhodes University, 2019). Robinson, J. P. W., Wilson, S. K. & Graham, N. A. J. Abiotic and biotic controls on coral recovery 16 years after mass bleaching. Coral Reefs 38, 1255–1265 (2019). Spencer, T., Teleki, K. A., Bradshaw, C. & Spalding, M. D. Coral Bleaching in the Southern Seychelles During the 1997–1998 Indian Ocean Warm Event. Mar. Pollut. Bull. 40, 569–586 (2000). Stobart, B. et al. Aldabra: Monitoring the Path to Recovery. in Coral Degradation in the Indian Ocean: Status Report 2002 (eds. Lindén, O., Souter, D., Wilhelmson, D. & Obura, D.) 232–247 (CORDIO, Department of Biology and Environmental Science, University of Kalmar, 2002). Benkwitt, C. E. et al. Seabirds boost coral reef resilience. Sci. Adv. 9, eadj0390 (2023). Appoo, J., Bunbury, N., Jaquemet, S. & Graham, N. A. J. Seabird nutrient subsidies enrich mangrove ecosystems and are exported to nearby coastal habitats. iScience 27, 109404 (2024). Lamb, J. B. et al. Plastic waste associated with disease on coral reefs. Science 359, 460–462 (2018). Graham, N. A. J. et al. Seabirds enhance coral reef productivity and functioning in the absence of invasive rats. Nature 559, 250–253 (2018). Benkwitt, C. E., Wilson, S. K. & Graham, N. A. J. Seabird nutrient subsidies alter patterns of algal abundance and fish biomass on coral reefs following a bleaching event. Glob. Change Biol. 25, 2619–2632 (2019). Benkwitt, C. E., Gunn, R. L., Le Corre, M., Carr, P. & Graham, N. A. J. Rat eradication restores nutrient subsidies from seabirds across terrestrial and marine ecosystems. Curr. Biol. 31, 2704–2711.e4 (2021). Benkwitt, C. E., Carr, P., Wilson, S. K. & Graham, N. A. J. Seabird diversity and biomass enhance cross-ecosystem nutrient subsidies. Proc. R. Soc. B Biol. Sci. 289, 20220195 (2022). Maynard, J. A. et al. Assessing relative resilience potential of coral reefs to inform management. Biol. Conserv. 192, 109–119 (2015). Burt, A. J. et al. Integration of population genetics with oceanographic models reveals strong connectivity among coral reefs across Seychelles. Sci. Rep. 14, 4936 (2024). Vogt-Vincent, N. S., Burt, A. J., Van Der Ven, R. M. & Johnson, H. L. Coral reef potential connectivity in the southwest Indian Ocean. Coral Reefs (2024) doi: 10.1007/s00338-024-02521-9 . Brandl, S. J. et al. Coral reef ecosystem functioning: eight core processes and the role of biodiversity. Front. Ecol. Environ. 17, 445–454 (2019). Additional Declarations No competing interests reported. Supplementary Files AldabraResilienceMSSupplementaryMaterial.pdf Cite Share Download PDF Status: Published Journal Publication published 16 Jul, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 21 Mar, 2025 Reviews received at journal 13 Mar, 2025 Reviewers agreed at journal 06 Mar, 2025 Reviewers agreed at journal 06 Jan, 2025 Reviews received at journal 10 Oct, 2024 Reviewers agreed at journal 17 Sep, 2024 Reviewers invited by journal 30 Aug, 2024 Editor assigned by journal 30 Aug, 2024 Editor invited by journal 19 Aug, 2024 Submission checks completed at journal 14 Aug, 2024 First submitted to journal 06 Aug, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4867751","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":349662326,"identity":"56eb53df-fab2-4eb1-9980-eb5dbd8d9f22","order_by":0,"name":"April J. 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Chong-Seng","email":"","orcid":"","institution":"Seychelles Islands Foundation, PO Box 853 Victoria Seychelles","correspondingAuthor":false,"prefix":"","firstName":"Karen","middleName":"M.","lastName":"Chong-Seng","suffix":""}],"badges":[],"createdAt":"2024-08-06 10:31:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4867751/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4867751/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-09531-9","type":"published","date":"2025-07-16T16:05:37+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":64286295,"identity":"5dfcca75-7b96-4f48-8662-414e4033ea4b","added_by":"auto","created_at":"2024-09-11 08:50:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1307706,"visible":true,"origin":"","legend":"\u003cp\u003eLocation of Aldabra Atoll in the Indian Ocean and within Seychelles. The twelve Aldabra Reef Monitoring (ARM) sites are located on the seaward reef (nine) and inside the lagoon (three) and data from sites 1–6 and 8 is included in the analysis. Blue polygons on the seaward reefs demark zones within which SIF permits handline bottom fishing of its subsistence fishery; yellow zones demark areas within which tourism activities are allowed (snorkeling, diving, boating). Figure modified after Koester et al.\u003csup\u003e34\u003c/sup\u003e with the map layout adapted from J. Letori’s original design.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4867751/v1/29040aac91be13006deed4cc.png"},{"id":64286293,"identity":"71a7698e-ce2c-4b62-9d2d-a73b1248ad85","added_by":"auto","created_at":"2024-09-11 08:50:33","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2175565,"visible":true,"origin":"","legend":"\u003cp\u003eRelative biomass distribution among trophic positions based on species from 14 families of non-cryptic, diurnal, reef-associated fishes. Plots on the left represent results of Aldabra overall and individual sites, plots on the right show comparative pyramids based on the “Classical” expectation\u003csup\u003e18\u003c/sup\u003e, and the expected biomass of fished and unfished locations of Graham et al.\u003csup\u003e16\u003c/sup\u003e for areas where total biomass is between 665–4915 kg/ha (log biomass 6.5 to 8.5; reproduction of their Figure S2). Colours represent trophic levels: 1: 2.0–2.5 (dark green), 2: 2.5–3.0 (yellow), 3: 3.0–3.5\u003c/p\u003e","description":"","filename":"Figure2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4867751/v1/4f6d68380c8f3a9898a65986.jpeg"},{"id":64287225,"identity":"d51a77d4-63ac-434b-9358-9b43dd512ed3","added_by":"auto","created_at":"2024-09-11 08:58:33","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":161208,"visible":true,"origin":"","legend":"\u003cp\u003eVisualisation of results from the resilience assessment and future management assessment overall (inset) and at each site. Green assessment cards indicate all thresholds were met or exceeded; yellow assessment cards show that at least one threshold was not met.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4867751/v1/f861b5385aede416cb9e0cb0.png"},{"id":87220620,"identity":"6b3e0b59-a33f-4250-99ce-2c239816116b","added_by":"auto","created_at":"2025-07-21 16:12:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2802569,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4867751/v1/8f8f46d6-9b36-44e3-91ef-f47f18646f9f.pdf"},{"id":64287226,"identity":"9c2b8ee0-fbdc-43f1-b2c6-5fa000b0a7e0","added_by":"auto","created_at":"2024-09-11 08:58:33","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":598780,"visible":true,"origin":"","legend":"","description":"","filename":"AldabraResilienceMSSupplementaryMaterial.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4867751/v1/ece3583227fceefe04dcfc7a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Supporting resilience-based coral reef management using broadscale threshold approaches","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn the face of climate change and lagging political responses to reducing greenhouse gas emissions, even the best protected coral reefs are transforming rapidly\u003csup\u003e1\u0026ndash;3\u003c/sup\u003e. Coral reef conservation and management goals therefore need to shift focus from maintaining intact systems to preserving ecosystem functions\u003csup\u003e4,5\u003c/sup\u003e. Managing reefs to maintain ecosystem function and maximise resilience\u0026mdash;the ability to resist and recover from disturbances\u003csup\u003e6\u003c/sup\u003e\u0026mdash;is complex and requires clear articulation of management aims (i.e., to maximise resilience of what to what?), identification of resilience indicators and clear reference thresholds for reef managers to maintain or aim for\u003csup\u003e4,5,7\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eShifting to resilience-based reef management requires that targets be defined \u003cem\u003ea priori\u003c/em\u003e, but defining resilience-based targets depends on availability of historical local or regional data about marine communities and natural variability\u003csup\u003e8,9\u003c/sup\u003e. Reef management authorities often lack these data, or the capacity and resources to identify localised targets\u003csup\u003e10,11\u003c/sup\u003e. It is feasible, however, for reef managers with reef monitoring capacity to conduct local-scale resilience assessments by collecting data on resilience indicators and comparing them to recently established broadscale thresholds which have been defined by incorporating large spatial variability. Although there are inherent problems in applying general values to a particular reef site, managers can adopt them as temporary \u0026lsquo;thresholds of potential concern\u0026rsquo; until more site-specific data can be acquired\u003csup\u003e12,13\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBroadscale parameters established for predicting the recovery potential of live coral cover include thresholds for reef depth, structural complexity, herbivore biomass, juvenile coral density\u003csup\u003e14\u003c/sup\u003e, and have also been developed to define minimum resident reef fish biomass in no-take zones\u003csup\u003e15\u003c/sup\u003e. Another approach is to investigate the composition and organisation of reef communities which can explain energy flows through the ecosystem and therefore be used to evaluate ecological condition and expected vulnerability to climate change. For example, Graham et al.\u003csup\u003e16\u003c/sup\u003e quantified the expected fish trophic distributions across a gradient of human disturbance. This provided specific predictions of biomass distributions between trophic levels defined for different levels of human disturbance, from which managers can compare their own local distributions\u003csup\u003e16\u0026ndash;18\u003c/sup\u003e. Darling et al.\u003csup\u003e19\u003c/sup\u003e produced one of several recent guides for reef conservation management under climate change (see also reviews by Boon and Baxter\u003csup\u003e20\u003c/sup\u003e, Harvey et al.\u003csup\u003e21\u003c/sup\u003e and McLeod et al.\u003csup\u003e4,22\u003c/sup\u003e), but it is the only approach that provides meta-analysis derived indicator thresholds that can readily be applied by managers at the local scale. The metrics of this assessment (percent cover of framework corals, prior heat stress, and magnitude of heat stress) combine information on key ecological processes: structural complexity, carbonate production, reef growth and past thermal stress to allocate reefs to one of three reef management strategies, i.e., protect, recover or transform.\u003c/p\u003e \u003cp\u003eDespite reef resilience assessments becoming more common, they rarely present structured processes to guide and justify indicator selection\u003csup\u003e23\u003c/sup\u003e, and there are \u0026ndash; to our knowledge \u0026ndash; no published examples of the use of the above broad-scale thresholds being used by reef managers to assess site-level resilience and guide management. This study trials the application of these broadscale threshold approaches for resilience-based management at Aldabra Atoll, in the small island large ocean state of Seychelles. We use reef data collected in 2014 and 2015 (prior to bleaching at Aldabra in 2016) to: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) assess relative resilience of Aldabra\u0026rsquo;s seaward coral reef sites by evaluating the position of the atoll's seaward reefs in broadscale analyses as described in Graham et al.\u003csup\u003e14\u003c/sup\u003e and MacNeil et al., and along known disturbance gradients as in Graham et al.\u003csup\u003e16\u003c/sup\u003e; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) combine the different scores for the resilience indicators in relation to the thresholds into a 'unique status assessment' for each site; and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) classify Aldabra's seaward coral reefs into management strategies according to Darling et al.\u0026rsquo;s\u003csup\u003e19\u003c/sup\u003e portfolio. We discuss the resilience assessments in the context of the 2014\u0026ndash;2017 global bleaching event on Aldabra\u0026rsquo;s live coral cover and coral recovery trajectories between 2016 and 2022, and how these assessments/indicators can be applied elsewhere.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eStudy site\u003c/p\u003e \u003cp\u003eAldabra, a UNESCO Marine World Heritage Site, is a remote atoll in the Western Indian Ocean within the Republic of Seychelles, located ca. 400 km northwest of Madagascar (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Aldabra hosts the largest reef system in Seychelles, which, due to its protection and remoteness, has limited local stressors. The atoll has been managed by a public trust, the Seychelles Islands Foundation (SIF) since 1979 and was designated as Special Reserve in 1981. Aldabra is uninhabited except for 10\u0026ndash;20 SIF staff based at the research station, who monitor the atoll's ecosystems and biodiversity year-round. Ongoing management efforts on Aldabra include maintenance of the no-take protected area (2559 km\u003csup\u003e2\u003c/sup\u003e since 2018; formerly 439 km\u003csup\u003e2\u003c/sup\u003e) while allowing limited tourism and a small-scale subsistence fishery (only for SIF staff), and restoring ecosystems (e.g. invasive alien species eradications\u003csup\u003e24\u003c/sup\u003e; native species re-introductions\u003csup\u003e25\u003c/sup\u003e; marine debris removal\u003csup\u003e26\u003c/sup\u003e). Due to Aldabra\u0026rsquo;s remoteness and history of protection, its coral reefs are thought to be relatively resilient, with potential to advance knowledge of natural ecosystem variation in the absence of significant direct stressors\u003csup\u003e27\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eData collection and processing\u003c/p\u003e \u003cp\u003eCoral reef monitoring projects have been conducted sporadically at Aldabra since the 1960s with varied methodologies\u003csup\u003e28\u0026ndash;33\u003c/sup\u003e but a long-term annual reef monitoring programme was established by SIF in 2014. The 12 permanently fixed Aldabra Reef Monitoring (ARM) sites represent each of Aldabra\u0026rsquo;s coastlines with varying oceanographic conditions (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and data on fish (a subset of species) and benthic communities is collected along permanent transects annually\u003csup\u003e1,27,34,35\u003c/sup\u003e (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn December 2015, additional surveys were conducted to obtain data on reef structural complexity, coral recruit density, total fish biomass and total herbivore biomass to supplement existing data (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). We assessed reef resilience and future management strategies for the Aldabra reef monitoring sites using data collected in 2014 (percent framework corals) and 2015 (structural complexity, total fish biomass, total herbivore biomass, coral recruit density; Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAt each of the eight sites, perpendicular to the reef slope, three 50-m long transects were laid at 5 m depth and one 50-m long transect at 15 m depth. On each transect, data on fish community, structural complexity and coral juvenile density were collected.\u003c/p\u003e \u003cp\u003eThe fish community was surveyed by recording number, identity (to species) and size (to nearest cm) of all fish\u0026thinsp;\u0026gt;\u0026thinsp;8 cm by a single observer along the entire 50-m transects with a transect width of 4 m. At the start of every survey day, fish size estimation was calibrated using PVC pipes of known lengths. Count data was converted to biomass (kg/ha) using published length-weight relationships\u003csup\u003e36\u0026ndash;42\u003c/sup\u003e. Structural complexity was visually estimated using the 6-point scale of Wilson et al.\u003csup\u003e43\u003c/sup\u003e at the start of each transect. The number, identity and size of juvenile coral colonies (\u0026lt;\u0026thinsp;5 cm diameter) was recorded in five replicate 0.25-m\u003csup\u003e2\u003c/sup\u003e quadrats per transect.\u003c/p\u003e \u003cp\u003eBenthic photoquadrat surveys were conducted at each site along the permanent transect on two 10-m long sub-transects (10 m gap between sub-transects) on both sides of the tape measure as described in Koester et al.\u003csup\u003e27\u003c/sup\u003e. The benthic photos were analysed using Coral Point Count with Excel extensions\u003csup\u003e44\u003c/sup\u003e by identifying the benthos at 16 randomly assigned points per image as described by Cerutti et al.\u003csup\u003e1\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eStudy approach and data analysis\u003c/p\u003e \u003cp\u003eAll statistical analyses were conducted using R (version 4.1.2\u003csup\u003e45\u003c/sup\u003e). Whilst acknowledging that depth is an important factor influencing reef communities, particularly fish assemblages\u003csup\u003e46\u003c/sup\u003e, data from the three 5 m and one 15 m transects were pooled as only one transect was surveyed at 15 m depth at each site (see \u0026lsquo;Data collection and processing\u0026rsquo;).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1. Comparisons with published recommended thresholds\u003c/h2\u003e \u003cp\u003eValues of four reef characteristics (total reef fish biomass [including only reef fish following MacNeil et al.\u003csup\u003e15\u003c/sup\u003e], herbivorous fish biomass, coral juvenile density and structural complexity) were compared against reference thresholds from MacNeil et al.\u003csup\u003e15\u003c/sup\u003e and Graham et al.\u003csup\u003e14\u003c/sup\u003e with two-tailed one sample t-tests (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComponents of the resilience and future management assessment showing corresponding ecosystem processes and functions.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApproach\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMethod\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMetric \u0026amp; year of data collection\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProcess of interest\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIndicative of\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eReferences\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eAnalysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eResilience Assessment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eComparison with published recommended reference thresholds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal fish biomass (1013 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of diurnally active, non-cryptic resident reef fish fish\u0026thinsp;\u0026gt;\u0026thinsp;10 cm of 20 families); data collected in 2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProductivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCommunity functions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMacNeil et al.\u003csup\u003e15\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"3\" nameend=\"c8\" namest=\"c7\" rowspan=\"4\"\u003e \u003cp\u003eTwo-tailed one-sample t-tests against reference thresholds\u003c/p\u003e \u003cp\u003eScoring of t-test outcomes\u003c/p\u003e \u003cp\u003eScores used in 'one out, all out' method and synthetic index\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHerbivore biomass (177 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e); data collected in 2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHerbivory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePrimary production, community functions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGraham et al.\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCoral juvenile abundance (\u0026gt;6.2 per m\u003csup\u003e2\u003c/sup\u003e); data collected in 2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCoral recruitment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReef recovery (gain of primary habitat)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGraham et al.\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStructural complexity (\u0026gt;\u0026thinsp;3.1); data collected in 2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProductivity, active reef growth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHabitat availability, benthic community landscape, enhanced coral settlement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGraham et al.\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComparisons based on trophic pyramids distributions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTrophic levels of diurnally active, non-cryptic, reef-associated fish; data collected in 2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProductivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHuman impact (cf. unexploited systems)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGraham et al.\u003csup\u003e16\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eComparison of trophic pyramids with those of \u0026ldquo;fished\u0026rdquo; and \u0026ldquo;unfished\u0026rdquo; seascapes as per Graham et al.\u003csup\u003e16\u003c/sup\u003e and the classic trophic pyramid as per Trebilco et al.\u003csup\u003e18\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eManagement Assessment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComparison to established threshold values of heat stress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWater temperature (satellite derived\u003csup\u003e53\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePhysiological stress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSignificant thermal stress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDarling et al.\u003csup\u003e19\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAssessing local DHW value during the 2014\u0026ndash;2017 global bleaching event against 4 DHW threshold\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eClassification of sites into management strategy portfolio of Darling et al.\u003csup\u003e19\u003c/sup\u003e: protect, recover or transform.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComparison against the recommended minimum reference value (10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercent cover of competitive and stress-tolerant corals (framework corals); data collected in 2014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCoral calcification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eActive reef growth (gain of primary habitat)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDarling et al.\u003csup\u003e19\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eT-test against reference threshold\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e also with reference to Brandl et al.\u0026rsquo;s\u003csup\u003e76\u003c/sup\u003e eight core ecosystem processes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eT-test outcomes for each reef characteristic were scored for Aldabra overall and for each site. A score of 1 was given if the observed mean was significantly higher than the reference threshold; zero if the observed mean was not statistically different from the reference threshold; and \u0026minus;\u0026thinsp;1 if the observed mean was significantly lower than the reference threshold (i.e., target was not met).\u003c/p\u003e \u003cp\u003eTo combine the different reef characteristics into a 'unique status assessment', two methods were used: the 'one out, all out' method and calculation of a 'synthetic index' (see also Halpern et al.\u003csup\u003e48\u003c/sup\u003e) that we developed to incorporate responsiveness to data quality and real differences in coral reef health. The 'one out, all out' method was used against all four characteristics whereby if any characteristics scored \u0026minus;\u0026thinsp;1, the area did not meet the target\u003csup\u003e47\u003c/sup\u003e. The synthetic index attempted a more nuanced investigation into the data and was calculated by normalising the scores (\u003cem\u003eu\u003c/em\u003e) for all four characteristics (\u003cem\u003etfb\u003c/em\u003e: total fish biomass, \u003cem\u003ehbm\u003c/em\u003e: herbivorous fish biomass, \u003cem\u003ejuv\u003c/em\u003e: coral juvenile abundance, \u003cem\u003erug\u003c/em\u003e: rugosity):\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:I=\\left(\\frac{\\sum\\:\\left({u}_{tfb},{u}_{hbm},{u}_{juv},{u}_{rug}\\right)+4)\\:}{4+4}\\right)\\times\\:100$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe synthetic index therefore provides us with a score out of 100 that reflects the level of resilience based on all four characteristics.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2. Trophic pyramid structure comparisons\u003c/h2\u003e \u003cp\u003eFollowing the method outlined by Graham et al.\u003csup\u003e16\u003c/sup\u003e and using fish biomass data (kg/ha) we: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) assigned trophic levels at the species level using Fishbase\u003csup\u003e41,49\u003c/sup\u003e; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) calculated relative distribution of biomass among five trophic levels to create trophic pyramids for Aldabra overall and each site individually; and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) compared these trophic pyramids to the \u0026lsquo;fished\u0026rsquo; and \u0026lsquo;unfished\u0026rsquo; seascapes of Graham et al.\u003csup\u003e16\u003c/sup\u003e and the classical trophic pyramid (see Trebilco et al.\u003csup\u003e18\u003c/sup\u003e). The five trophic levels, as suggested by Graham et al.\u003csup\u003e16\u003c/sup\u003e, are: 1: 2.0\u0026ndash;2.5, 2: 2.5\u0026ndash;3.0, 3: 3.0\u0026ndash;3.5, 4: 3.5\u0026ndash;4.0 and 5: 4.0\u0026ndash;4.5. To enable direct comparison with Graham et al.\u003csup\u003e16\u003c/sup\u003e, we excluded any fish families that are not part of the 17 target families listed by Graham et al.\u003csup\u003e16\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e3. Management strategy classification\u003c/h2\u003e \u003cp\u003eWe used coral community data (pre-bleaching percent coral cover) and degree heating weeks (DHW) data accessed from the National Oceanic and Atmospheric Administration\u003csup\u003e50\u003c/sup\u003e to evaluate the ecological condition of Aldabra\u0026rsquo;s reef sites and their exposure to climate change following Darling et al.\u003csup\u003e19\u003c/sup\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). We then classified Aldabra\u0026rsquo;s reef sites based on the \u0026lsquo;protect\u0026rsquo;, \u0026lsquo;recover\u0026rsquo; and \u0026lsquo;transform\u0026rsquo; management strategies outlined by Darling et al.\u003csup\u003e19\u003c/sup\u003e. These strategies were to: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) \u0026lsquo;protect\u0026rsquo; functioning reefs that were associated with limited exposure to recent bleaching-level thermal stress (DHW\u0026thinsp;\u0026lt;\u0026thinsp;4\u0026deg;C-weeks) and maintained coral cover above 10%; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) \u0026lsquo;recover\u0026rsquo; reefs that have recently maintained cover above 10% but were exposed to severe potential bleaching stress in 2014\u0026ndash;2017; and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) for reefs with coral cover below net-positive carbonate budgets (\u0026lt;\u0026thinsp;10% hard coral cover), societies may ultimately need to \u0026lsquo;transform\u0026rsquo; away from reef-dependent livelihoods\u003csup\u003e19\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eEcological condition was represented by the potential for a net-positive carbonate budget before the 2014\u0026ndash;2017 bleaching event\u003csup\u003e19\u003c/sup\u003e. To assess ecological condition we: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) assigned life history strategies (\u0026lsquo;competitive\u0026rsquo;, \u0026lsquo;generalist\u0026rsquo;, \u0026lsquo;stress-tolerant\u0026rsquo;, \u0026lsquo;weedy\u0026rsquo;) at the genera and growth form level following Darling et al.\u003csup\u003e51\u003c/sup\u003e, using the Coral Traits Database\u003csup\u003e52\u003c/sup\u003e (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://coraltraits.org/\u003c/span\u003e\u003cspan address=\"https://coraltraits.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e); (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) calculated percent cover of (summed) competitive and stress-tolerant corals (hereafter, \u0026lsquo;framework\u0026rsquo; corals); and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) compared Aldabra data against the threshold value (10% cover\u003csup\u003e19\u003c/sup\u003e) using two-tailed one-sample t-tests.\u003c/p\u003e \u003cp\u003eClimate change exposure was represented by thermal stress during the 2014\u0026ndash;2017 bleaching event\u003csup\u003e19\u003c/sup\u003e. To assess climate change exposure we: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) extracted daily DHW data available from NOAA Coral Reef Watch\u003csup\u003e53\u003c/sup\u003e between two coordinates at Aldabra (coordinate one: -9.575; 46.075, coordinate two: -9.225; 46.675) for the period January 2014 to December 2017 through the ERDDAP data server via the Pacific Islands Ocean Observing System (PacIOOS) website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pae-paha.pacioos.hawaii.edu/erddap/griddap/dhw_5km.html\u003c/span\u003e\u003cspan address=\"https://pae-paha.pacioos.hawaii.edu/erddap/griddap/dhw_5km.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e); (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) calculated maximum DHW estimated for each year; and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) compared these Aldabra data against the established threshold for thermal stress exposure (4 DHW \u0026deg;C-weeks\u003csup\u003e19\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eThe two indices (ecological condition and climate change exposure) were then placed into Darling et al.\u0026rsquo;s \u003csup\u003e19\u003c/sup\u003e management strategy portfolio, which recommends a \u0026lsquo;protect\u0026rsquo; strategy if reefs were exposed to thermal stress below DHW 4\u0026deg;C-weeks during 2014\u0026ndash;2017 and had\u0026thinsp;\u0026gt;\u0026thinsp;10% cover of framework corals, a \u0026lsquo;recover\u0026rsquo; strategy if reefs were exposed to severe bleaching-level stress (DHW\u0026thinsp;\u0026gt;\u0026thinsp;4\u0026deg;C-weeks during 2014\u0026ndash;2017) and had\u0026thinsp;\u0026gt;\u0026thinsp;10% cover of framework corals, and a \u0026lsquo;transform\u0026rsquo; strategy if reefs were exposed to severe bleaching-level stress and had\u0026thinsp;\u0026lt;\u0026thinsp;10% cover of framework corals.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eRecommended threshold comparisons\u003c/p\u003e \u003cp\u003eComparing the observed values versus recommended thresholds for four reef characteristics across all eight sites indicated high likelihood of resilience on the seaward forereef slopes of Aldabra using both the \u0026lsquo;one out, all out\u0026rsquo; method, and the synthetic index (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Reef characteristics met recommended thresholds \u0026mdash; structural complexity was not significantly different from the recommended threshold (\u003cem\u003et\u003c/em\u003e = -0.13125, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;31, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Table S2), while total and herbivorous fish biomass and juvenile coral colony density were significantly greater than recommended (\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.3138, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;31, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01; \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.8482, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;31, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.5305, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;30, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, respectively; Table S2). Combining the individual indices into a synthetic index of resilience gave an atoll-level estimate of reefs having an 87.5% chance of recovery post-disturbance (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnique status assessments considering four reef characteristics (total fish biomass; herbivorous fish biomass; juvenile coral density; structural complexity) overall and at each site. Numbers represent outcomes from the two-tailed one-sample t-tests (pooling three \u0026lsquo;5 m depth\u0026rsquo; and one \u0026rsquo;15 m depth\u0026rsquo; transects: df\u0026thinsp;=\u0026thinsp;3 at the site-level; df\u0026thinsp;=\u0026thinsp;31 overall); observed mean was significantly higher (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), lower (-1) or not statistically different (0) from the recommended threshold. Columns represent assessment outcomes using the 'one out, all out' method (Pass/Fail based on all characteristics) and the 'synthetic index' expressed on a scale of 0\u0026ndash;100%.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal fish biomass\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHerbivorous fish biomass\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eJuvenile coral density\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStructural complexity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOne-out, all-out\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSynthetic Index score (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e87.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARM01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARM02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARM03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARM04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARM05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARM06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARM08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARM12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFail\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e37.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eInvestigating individual sites showed similar patterns to the overall assessment (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Seven (of the eight) sites displayed high likelihood of resilience using the \u0026lsquo;one out, all out\u0026rsquo; method and the synthetic index (i.e., index score\u0026thinsp;\u0026ge;\u0026thinsp;50%). For the three reefs (ARM01, ARM02, ARM06) with an index score of 75% we can be confident that they would be likely to recover following a disturbance.\u003c/p\u003e \u003cp\u003eSite ARM12 met thresholds for three of the four reef characteristics: total reef fish biomass, herbivorous fish biomass and juvenile coral density (\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.2099, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05; \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.6439, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05; \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.55641, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05, respectively; Table S2). However, the structural complexity threshold was not met (\u003cem\u003et\u003c/em\u003e = -9.3531, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01; Table S2), resulting in failure using the \u0026lsquo;one out, all out\u0026rsquo; method. Combining the individual indices into a synthetic index of resilience gave a site-level estimate of 37.5% chance of reef recovery post-disturbance (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTrophic pyramid structure comparisons\u003c/p\u003e \u003cp\u003eThe overall trophic pyramid of the reef fish community compared favourably to Graham et al.\u0026rsquo;s \u003csup\u003e16\u003c/sup\u003e concave unfished pyramid shape (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). At the site-scale, seven of the eight pyramids showed higher proportions of upper trophic level biomass than expected based on a classic biomass pyramid \u003csup\u003e18\u003c/sup\u003e, approaching Graham et al.\u0026rsquo;s\u003csup\u003e16\u003c/sup\u003e concave shape. Community biomass was greater than the recommended 650 kg/ha at the atoll-level (mean biomass\u0026thinsp;=\u0026thinsp;1846\u0026thinsp;\u0026plusmn;\u0026thinsp;255 SE kg/ha) and for all sites (mean biomass ranged from 986\u0026thinsp;\u0026plusmn;\u0026thinsp;157 kg/ha at ARM01 to 4267\u0026thinsp;\u0026plusmn;\u0026thinsp;756 kg/ha at ARM06; Table S2).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eManagement strategy classification\u003c/p\u003e \u003cp\u003eAll but one of Aldabra\u0026rsquo;s seaward coral reefs fell within the \u0026lsquo;recover\u0026rsquo; strategy of Darling et al.\u0026rsquo;s\u003csup\u003e19\u003c/sup\u003e management portfolio: predicted maximum heat stress was at \u0026gt;\u0026thinsp;6 DHW in April 2016 (Figure S2) and the cover of competitive and stress-tolerant coral species did not differ from the 10% threshold at all sites except ARM05 (Table S3). Site ARM05 therefore fell within the \u0026lsquo;transform\u0026rsquo; strategy, whilst all other sites fell within the \u0026lsquo;recover\u0026rsquo; strategy.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eBy using multiple approaches to evaluate site-level resilience, we were able to establish that in 2015 (pre-bleaching) Aldabra\u0026rsquo;s seaward coral reefs conformed to the expected resilience of a well-managed and remote marine reserve. For each of the assessed resilience indicators (total and herbivorous fish biomass, trophic fish biomass distributions, coral juvenile density, and structural complexity), the reefs met or exceeded multiple thresholds. Combining the individual indices into a synthetic index of resilience gave an atoll-level estimate of reefs having an 87.5% \u0026lsquo;chance of recovery\u0026rsquo; post-disturbance. In addition, within Darling et al.\u0026rsquo;s\u003csup\u003e19\u003c/sup\u003e management strategy analysis, all but one of Aldabra\u0026rsquo;s seaward coral reefs fell within the recover strategy, meaning they are predicted to recover despite exposure to severe bleaching stress. Crucially, the resilience predictions mostly align with post-bleaching data on Aldabra\u0026rsquo;s reef dynamics (Table S4; Figure S3), validating the application of these approaches.\u003c/p\u003e \u003cp\u003eResilience assessment\u003c/p\u003e \u003cp\u003eIn 2015, both total (986\u0026ndash;4267 kg/ha) and herbivore (264\u0026ndash;958 kg/ha) fish biomass at all seaward coral reefs sites on Aldabra met or exceeded recommended thresholds (total fish biomass: 1000 kg/ha\u003csup\u003e15\u003c/sup\u003e; herbivore biomass: 177 kg/ha\u003csup\u003e14\u003c/sup\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These biomass figures are equivalent to other remote and protected sites, like the Chagos Archipelago\u003csup\u003e54\u003c/sup\u003e, but align more closely with the biomass recorded around the inhabited atoll of Diego Garcia, where subsistence fishing occurs, than the uninhabited and unfished Northern Atolls\u003csup\u003e55\u003c/sup\u003e. This could indicate that even a population of \u0026lt;\u0026thinsp;1 person/km\u003csup\u003e2\u003c/sup\u003e on Aldabra may have an impact on resident fish biomass via the Aldabra subsistence fishery, as also suggested by Fournier-Carnoy\u003csup\u003e56\u003c/sup\u003e. Despite this, we found that Aldabra\u0026rsquo;s fish biomass trophic pyramids have a concave structure (except ARM08), where most of the biomass is located in the top (predator) and bottom (herbivores) trophic levels. This indicates energy-balanced communities\u003csup\u003e16\u003c/sup\u003e and is similar to other remote and protected locations (e.g. Mexico\u003csup\u003e57\u003c/sup\u003e). Aside from the threat of climate driven changes in fish community structure and biomass\u003csup\u003e58\u0026ndash;60\u003c/sup\u003e, the present state of relative health in fish biomass and trophic structure at Aldabra is threatened by increasing poaching (SIF, unpubl. data). With fishers travelling longer distances\u003csup\u003e61\u003c/sup\u003e and dwindling stocks elsewhere, Aldabra\u0026rsquo;s fish biomass is highly attractive, so greater surveillance and enforcement of the reserve will be a key management strategy to continue to meet these resilience thresholds. The Aldabra subsistence fishery could also shift efforts from predominantly bottom fishing which targets reef fish, to trolling for pelagic species.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe high herbivorous fish biomass found across Aldabra\u0026rsquo;s reef sites promotes the availability of suitable coral larvae settlement substrates\u003csup\u003e14\u003c/sup\u003e. As such, coral juvenile density at all reef sites in this study (7.0\u0026ndash;25.8 coral juveniles/m\u003csup\u003e2\u003c/sup\u003e) met or exceeded the recommended resilience indicator threshold\u003csup\u003e14\u003c/sup\u003e of 6.2 coral juveniles/m\u003csup\u003e2\u003c/sup\u003e. All sites also met or exceeded the recommended threshold for structural complexity, except ARM12. This site is located in the south-east of the atoll and exposed to high and persistent wave energy\u003csup\u003e62\u003c/sup\u003e. Reefs in such conditions naturally consist of more stable coral growth forms (e.g. encrusting and massive\u003csup\u003e63\u003c/sup\u003e), impacting the structural complexity score of the reef. The site met all other thresholds, highlighting site-specific factors that can now be considered and incorporated when defining (or refining) the local thresholds used for local resilience-based management.\u003c/p\u003e \u003cp\u003ePredicted resilience vs post-disturbance trajectories\u003c/p\u003e \u003cp\u003eOur research presents a snapshot of one point in time, but studies of Aldabra\u0026rsquo;s reefs from as early as the 1960s align with our findings. The north-west reef front of Aldabra was described as having the most \u0026lsquo;luxuriant coral growth\u0026rsquo;\u003csup\u003e28,29,32\u003c/sup\u003e. This corresponds with our findings of high structural complexity and a net positive carbonate budget at all sites except ARM12 and ARM05 in the south-east and east, and the high resilience index scores at sites on the north-west coast. The south to south-east reef fronts (sites ARM08, ARM12), were assumed to have undergone catastrophic cyclone damage in the years preceding the 1960s surveys\u003csup\u003e28,29,32\u003c/sup\u003e, and both sites are naturally exposed to stronger waves than the northern coast, shaping benthic community composition\u003csup\u003e62\u003c/sup\u003e. The fact that our 2015 surveys show similar patterns to those described 50 years ago, despite the impacts of the 1998 global coral bleaching event\u003csup\u003e64\u003c/sup\u003e, demonstrates the long-term resilience of several areas of reef and supports the accuracy of both the assessment methods and resulting resilience scores.\u003c/p\u003e \u003cp\u003eContemporary data, collected annually at Aldabra since 2014, allow preliminary checks of our predicted resilience from this study against observed changes in ecosystem community and processes following the 2016 bleaching event, which peaked at Aldabra in April 2016. Overall, this event caused a reduction of relative hard coral cover of 54%\u003csup\u003e1,27\u003c/sup\u003e, with substantial variation across sites (14\u0026ndash;73% reduction; Table S4, Figure S3). By early 2022, six years post-bleaching, relative hard coral cover at these sites reached 43\u0026ndash;107% of the pre-bleaching cover in 2014 (Table S4). This highlights that live coral recovery potential (one component of ecosystem resilience) varied across sites, and in some cases was surprising compared to our estimates of predicted resilience. For example, our 2015 resilience assessment highlighted ARM12 as potentially less resilient than the other reefs, but this was one of the two sites that reached or exceeded pre-bleaching hard coral cover values by 2022 (Table S4, Figure S3). Conversely, site ARM05, which met all resilience indicator thresholds, experienced relatively low hard coral recovery, only reaching 43% of the pre-bleaching cover by 2022. This lower recovery trajectory was attributed to rapid expansion of the calcareous green algae \u003cem\u003eHalimeda\u003c/em\u003e spp., which is more abundant on the eastern seaward reefs of Aldabra\u003csup\u003e27\u003c/sup\u003e, attributed to an increase in hydrodynamic energy from west to east\u003csup\u003e32,65\u003c/sup\u003e. Potentially we need to consider some additional indicators such as \u003cem\u003eHalimeda\u003c/em\u003e specific thresholds within future resilience assessments for Aldabra.\u003c/p\u003e \u003cp\u003eOverall, while trends in live coral cover followed expectations, we can now describe additional site-specific characteristics likely affecting resilience/recovery potential. For example, at Aldabra, we can be less concerned by lower complexity scores in areas exposed to high and persistent wave energy but consider additional indicators to track the extent of \u003cem\u003eHalimeda\u003c/em\u003e spp., especially on eastern reefs. Aldabra\u0026rsquo;s daily temperature regimes are known to influence fine-scale resilience patterns, especially when comparing the lagoonal vs. seaward coral reefs. Aldabra\u0026rsquo;s lagoon, which has a much greater daily temperature fluctuation saw less mortality and faster recovery from the 2016 bleaching event\u003csup\u003e27\u003c/sup\u003e. Localised nutrient input from seabird colonies via guano deposits may also influence the resilience potential of adjacent reefs around islands\u003csup\u003e66\u003c/sup\u003e. At Aldabra these inputs are patchy\u003csup\u003e67\u003c/sup\u003e due to tidal changes, strong currents and because seabird colonies (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) are restricted by the presence of invasive mammals. Both of these factors (temperature regimes and levels of seabird-derived nutrients) should be considered as additional broadscale resilience indicators to future assessments for resilience-based management, although these proposed indicators require more resources to acquire site-level data than the indicators used in this study.\u003c/p\u003e \u003cp\u003eManagement assessment\u003c/p\u003e \u003cp\u003eAll but one of Aldabra\u0026rsquo;s seaward reef sites in this study fell within the recover strategy under Darling et al.\u0026rsquo;s\u003csup\u003e19\u003c/sup\u003e approach. The management goal in this strategy is to move reefs back above the 10% threshold of framework coral cover as quickly as possible following climate impacts. Active management strategies to achieve this include minimising local stressors (e.g., invasive species control on islands, pollution control, reduced tourism activities, reduced fishing pressure) and conducting active restoration (e.g., coral gardening or other reef restoration techniques, coastal habitat restoration). Two Aldabra reef monitoring sites with high synthetic index scores (ARM01, ARM06) \u0026ndash; our proxy for resilience \u0026ndash; are located closest to local human activity and potential stressors: the research station, the food security and the tourism zones (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). These findings suggest that the current level of human activity in the vicinity of these sites has minimal impact on site-level reef resilience.\u003c/p\u003e \u003cp\u003eOther local stressors identified by managers include plastic pollution and invasive alien mammals. An estimated 500 tonnes of plastic pollution have accumulated along Aldabra\u0026rsquo;s coastline\u003csup\u003e26\u003c/sup\u003e. Evidence suggests that plastic could impact coral health and subsequent resilience\u003csup\u003e68\u003c/sup\u003e. SIF already undertakes active management of this issue through regular clean-ups, although limited resources hinder removal at scale\u003csup\u003e26\u003c/sup\u003e. Invasive alien mammals are known to suppress seabirds and their nutrient inputs on islands\u003csup\u003e69\u003c/sup\u003e. Eradicating introduced rats and cats from Aldabra would kickstart restoration of a more diverse breeding seabird community across the atoll. This in turn is expected to substantially increase the quantity and distribution of seabird-derived nutrient subsidies entering near-shore reef systems. These nutrient subsidies are now understood to enhance reef resilience through faster coral growth, higher recruitment rates and higher reef fish biomass\u003csup\u003e66,69\u0026ndash;72\u003c/sup\u003e. As a strategy to enhance coral resilience at Aldabra, a rat and cat eradication is therefore of highest priority and an eradication feasibility assessment for the atoll is currently underway.\u003c/p\u003e \u003cp\u003eUsefulness of the approaches used\u003c/p\u003e \u003cp\u003eDespite efforts to make the concept of resilience-based management operational to reef managers and conservationists (e.g. Graham et al.\u003csup\u003e14\u003c/sup\u003e, Maynard et al.\u003csup\u003e73\u003c/sup\u003e), uptake has been slow. The application of several approaches to assess coral reef resilience at Aldabra has been largely successful, with reef resilience predictions mostly aligning with observed post-bleaching coral trajectories. As reef managers, we found the exercise highly valuable for Aldabra\u0026mdash;the largest reef system in Seychelles and an important coral larvae source for the region\u003csup\u003e74,75\u003c/sup\u003e. Combining resilience indicators into the synthetic index was an effective way of summarising multiple results at monitoring site level, but the variability of index scores between sites meant an island-level score was less valuable from a site management perspective.\u003c/p\u003e \u003cp\u003eIt would be a valuable exercise to conduct similar resilience-based management assessments across Seychelles and other island groups where data is available. Such reef resilience mapping could be combined with recent coral reef connectivity data\u003csup\u003e74,75\u003c/sup\u003e to strengthen and inform reef system management strategies, define national-level resource and conservation priorities and feed into monitoring national contributions to meeting the Kunming-Montreal Global Biodiversity Framework objectives. With the development of appropriate tools, such as analysis and tracking tools via an open access app, resilience-based management approaches are likely to be extremely important for identifying and protecting the reefs most likely to survive repeated bleaching events. With bleaching events becoming more frequent and intense, applying these broadscale thresholds can provide reef managers with tangible resilience targets to maintain, improve or aim for, and help guide and implement adaptive resilience-based management actions for coral reefs.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe development and set-up of the Aldabra Reef Monitoring (ARM) programme was funded by the Global Environmental Facility (GEF Project ID 3925). The annual ARM surveys were funded by the Seychelles Islands Foundation. Open Access publishing of this article was funded by the University of Bremen.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAJB and AK contributed equally to this work and are joint first authors. AJB: Conceptualization, Methodology, Validation, Investigation, Data Curation, Writing - Original Draft, Writing - Review \u0026amp; Editing, Visualization, Project administration. AK: Methodology, Validation, Formal analysis, Investigation, Data Curation, Writing - Original Draft, Writing - Review \u0026amp; Editing, Visualization, Funding acquisition. NB: Conceptualization, Writing - Original Draft, Writing - Review \u0026amp; Editing, Supervision, Project administration, Funding acquisition. PH: Methodology, Investigation, Data Curation, Writing - Review \u0026amp; Editing, Funding acquisition. RW: Formal analysis, Data Curation, Writing - Review \u0026amp; Editing. FFD: Writing - Review \u0026amp; Editing, Supervision, Project administration, Funding acquisition. KCS: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Data Curation, Writing - Original Draft, Writing - Review \u0026amp; Editing, Visualization, Project administration.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe thank the Seychelles Islands Foundation (SIF) and their current and former staff members for their work and support. Specifically, we extend our appreciation to the many Aldabra staff who over the years have contributed to marine data collection and planning. We are grateful to M. Pratchett, K. Nash and N. Graham who provided valuable comments on earlier versions of this manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data on fish diversity, abundance, and biomass utilised in this research is accessible on Figshare (DOI: https://doi.org/10. 6084/m9.figshare.22792580.v1). The data on coral juvenile abundance and diversity is available in the supplementary files of Koester et al. 2021 (PLOS ONE 16(12): e0260516. https://doi.org/10.1371/journal.pone.0260516). All other data used for this research is available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCerutti, J. M. B. \u003cem\u003eet al.\u003c/em\u003e Impacts of the 2014\u0026ndash;2017 global bleaching event on a protected remote atoll in the Western Indian Ocean. Coral Reefs 39, 15\u0026ndash;26 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHead, C. E. I. \u003cem\u003eet al.\u003c/em\u003e Coral bleaching impacts from back-to-back 2015\u0026ndash;2016 thermal anomalies in the remote central Indian Ocean. 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Coral reef potential connectivity in the southwest Indian Ocean. Coral Reefs (2024) doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00338-024-02521-9\u003c/span\u003e\u003cspan address=\"10.1007/s00338-024-02521-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrandl, S. J. \u003cem\u003eet al.\u003c/em\u003e Coral reef ecosystem functioning: eight core processes and the role of biodiversity. Front. Ecol. Environ. 17, 445\u0026ndash;454 (2019).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"ecological thresholds, resilience indicators, coral reef conservation, coral bleaching, coral reef recovery, UNESCO World Heritage","lastPublishedDoi":"10.21203/rs.3.rs-4867751/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4867751/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eManaging coral reefs to maintain ecosystem function and maximise resilience requires identification of resilience indicators and clear ecological reference thresholds for reef managers to maintain or aim for. In the absence of local resilience-based targets, reef managers can conduct local-scale resilience assessments by collecting data on resilience indicators and comparing them to recently established broadscale thresholds which have been defined by incorporating large spatial variability. This study documents the application of these broadscale threshold approaches to kick-start resilience-based management at Aldabra Atoll UNESCO Marine World Heritage Site. Aldabra\u0026rsquo;s seaward coral reefs conformed to the expected resilience of a well-managed and remote marine reserve. All but one reef met or exceeded thresholds for each of the five assessed resilience indicators and fell within the \u0026lsquo;recover\u0026rsquo; strategy of the management strategy analysis. Combining the individual indices into a synthetic index of resilience gave an atoll-level estimate of reefs having an 87.5% \u0026lsquo;chance of recovery\u0026rsquo; post-disturbance. Reef resilience predictions largely aligned with our data on post-bleaching coral trajectories. We recommend additional broadscale threshold categories that could be defined and included in future assessments, and suggest local factors that need to be considered to fine-tune the assessments at site-level.\u003c/p\u003e","manuscriptTitle":"Supporting resilience-based coral reef management using broadscale threshold approaches","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-11 08:50:28","doi":"10.21203/rs.3.rs-4867751/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-03-21T16:31:31+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-13T19:58:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"311192864607236142655352711285114260369","date":"2025-03-06T13:45:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"262921314970201299441465074293438850890","date":"2025-01-06T19:25:14+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-10T09:33:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"31866900139695547683668760294685142062","date":"2024-09-17T08:10:36+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-30T19:09:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-30T19:08:16+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-08-19T08:21:53+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-14T11:37:34+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-08-06T10:29:49+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bc54c98a-540c-4e23-b9d2-895faa036525","owner":[],"postedDate":"September 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":37114866,"name":"Earth and environmental sciences/Ecology/Ecosystem ecology"},{"id":37114867,"name":"Biological sciences/Ecology/Ecosystem ecology"},{"id":37114868,"name":"Earth and environmental sciences/Environmental sciences/Environmental impact"},{"id":37114869,"name":"Earth and environmental sciences/Ocean sciences/Marine biology"},{"id":37114870,"name":"Earth and environmental sciences/Climate sciences/Climate change/Climate change impacts/Environmental health"},{"id":37114871,"name":"Earth and environmental sciences/Climate sciences/Ocean sciences/Marine biology"},{"id":37114872,"name":"Earth and environmental sciences/Environmental sciences"}],"tags":[],"updatedAt":"2025-07-21T16:11:04+00:00","versionOfRecord":{"articleIdentity":"rs-4867751","link":"https://doi.org/10.1038/s41598-025-09531-9","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-07-16 16:05:37","publishedOnDateReadable":"July 16th, 2025"},"versionCreatedAt":"2024-09-11 08:50:28","video":"","vorDoi":"10.1038/s41598-025-09531-9","vorDoiUrl":"https://doi.org/10.1038/s41598-025-09531-9","workflowStages":[]},"version":"v1","identity":"rs-4867751","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4867751","identity":"rs-4867751","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}