Critical thresholds of adult patch density and spacing during coral fertilisation

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Ricardo, Christopher Doropoulos, Russell C. Babcock, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5405858/v2 This work is licensed under a CC BY 4.0 License Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Abstract Extreme climate events have severe impacts on the ecological functioning of marine ecosystems by causing wide-spread declines in population sizes and, for surviving individuals, limiting the capacity for population recovery through sexual reproduction. Ecological theory suggests that impacted populations can suffer local extinction due to Allee effects that occur during reproduction 1-3 : large distances between corals prevents gamete encounters, resulting in reproductive failure 4-6 . Corals are particularly vulnerable to climate impacts; however, without understanding the relationship between the spacing of spawning individuals and fertilisation success, reefs may pass a critical population threshold before effective conservation measures can be implemented. To assess the influence of adult patch characteristics on fertilisation success, we conducted a series of manipulative field experiments using three common broadcast-spawning Acropora species in two countries (One Tree Island, GBR; and Nikko Bay, Palau). Experimental coral populations ranged in mean intercolonial distance from 1 to 2 m and resulted in low but notable fertilisation success, ranging from 1.2 to 8.7%. We developed an independent mechanistic coral fertilisation model whose predictions closely aligned with the empirical data. The model predicts that in absence of strong convergence zones, adult coral densities need to exceed 13 – 50 colonies per 100 square meters for reefs to remain 10% reproductively functional. Marine and Freshwater Ecology Ecological Modeling Population Biology Allee effects Coral reproduction Population thresholds Fertilisation model Figures Figure 1 Figure 2 Figure 3 Main Text Allee effects describe the decline in individual fitness and population growth rates as population density or size decreases 1 . At low population sizes or densities, inverse density dependence can occur whereby the per capita growth rate of the population remains negative and local extinctions can occur if the population is not supplemented with new members 1 . In coral reef ecosystems suffering widespread, climate-driven losses 7 , populations falling below critical demographic and fecundity thresholds may entirely fail to reproduce 8,9 . 1,2 . One of the most significant Allee effects in corals occurs during external fertilisation in broadcast-spawning species, where reproductive success is highly dependent on gamete production and concentration 10-12 . Fertilisation success depends on population size, the number of adult spawning colonies, their proximity to one another, and individual colony size, as larger colonies contribute disproportionately to reproductive output 13 . During spawning events, gametes aggregate in surface slicks for a brief fertilisation period before wind, waves, and currents dilute them to low concentrations. Specifically, small population sizes not only reduce the total potential reproductive output (number of eggs) but also the proportion of those fertilising, owing to largely to low sperm concentrations under local dilutive forces. Fertilisation failure may result in a full year's recruitment failure, impacting long-term resilience to ongoing ocean warming threats 14 . For the majority of reef coral species, spawning events occur just one or two consecutive nights over a period that may last only minutes 15 .This limited window for reproduction heightens the vulnerability of coral populations and presents significant challenges in characterising these events. During spawning, most gamete encounters occur within a brief 2–3 hr period before the coral spawn slick becomes too diluted for further fertilisation 4,5,16 . While laboratory studies provide insights into species-specific fertilisation responses, they neglect the hydrodynamic processes that strongly influence slick formation and persistence in the field. However, collecting empirical data during annual coral spawning events is a challenging task owing to the ephemeral nature of these events, their occurrence at night, variability in predictability, and the complexity of heterospecific spawning that co-occurs 5,15,17 . Here, we conducted three manipulated experiments in the natural environment across two countries marking the first investigation, to our knowledge, to experimentally test how adult coral population densities affect fertilisation success. We utilised spatial and physical isolation of the experimental corals (herein: patches) from natural spawning populations in the main lagoon at One Tree Island, southern Great Barrier Reef, and the southern channel of Nikko Bay (Ngermid), Palau. These locales were chosen for their distinct hydrological and geographical features conducive to isolating outplanted coral patches from potential interspecific and conspecific contamination. We focused on the genus Acropora , a key framework builder and rapid recoloniser, selecting A. cf . tenuis and A. cf. digitifera at One Tree Island, and A. cf. hyacinthus in Palau. In a manipulated patch of eight smaller-sized A. cf. tenuis colonies with 2.1 m mean spacing (0.14 colonies m -2 ) in the lagoon of One Tree Island, the mean fertilisation success was 1.2% [Fig. 1; 95% CI: 0.2–8.2%; n = 6]. A larger patch of 15 A. cf. digitifera colonies with a tighter 1.1 m mean spacing (0.25 colonies m -2 ) achieved a slightly higher fertilisation success of 7.0% in [95% CI: 2.6–17.3%; n = 6]. In Palau, a larger patch of 20 larger-sized colonies of the table coral A. hyacinthus , spaced 1 m apart (0.69 colonies m -2 ), achieved a mean fertilisation rate of 8.7% [95% CI: 4.6–15.8%; n = 13].. These experiments demonstrate clear evidence of Allee effects in small populations, with none achieving more than 10% fertilisation success on average. Heterogeneity among replicates of the egg containers and the in-situ sperm concentrations indicates high spatial variability of the manipulated spawn slick, similar to observations in coral spawn slicks from wild populations in previous studies 4,5 . For example, fertilisation in A . cf. tenuis was primarily attributed to a single replicate (~25% fertilisation), the only sample exceeding the contamination and self-fertilisation controls of ~2% (Fig. 1 d). Successful outcross fertilisation was observed in over 50% of A. cf. digitifera samples , and 86% of A. cf. hyacinthus samples (Fig. 1 d). In situ sperm concentrations measured by flow cytometry ranged from 0 to 2.2 × 10 3 sperm mL -1 for A. tenuis , 9.6 × 10 1 to 1.3 × 10 3 sperm mL -1 for A. digitifera , and 0 to 9.4 × 10 3 sperm mL -1 for A. hyacinthus (Fig. 1 c, e). The highest sperm concentrations recorded in field samples corresponded to levels sufficient for fertilisation success reported in laboratory experiments of the same species i.e. >10 3 sperm mL -1 10,18,19 , but were markedly lower than those considered as ‘optimal’ or saturating sperm concentrations’ 4,12 . To understand the potential for Allee effects, we created a spatially explicit coral fertilisation model independent of our field experiments. For model parameterisation, we conducted a suite of biological and hydrodynamic experiments (see Methods; Extended Data Figure 1–2), in addition to using values reported in the literature. Instantaneous release of gametes into a turbulent flow was modelled as an advection-diffusion problem in a scalar field using an explicit finite difference method, with this approach differing from traditional steady-state assumptions found in previous fertilisation models 20-22 (Fig. 2a). The grid was initialised using the predicted gamete production (fecundity) based on colony size, polyps per area, gametes per bundle, and the proportion of the colony that is fertile (fertile zone). Gametes (bundle, eggs, sperm) were subject to different turbulent diffusion forces depending on their position in the water column and the gamete type. Upon bundle dissociation, fertilisation success for each time step was calculated using a polyspermy-block fertilisation kinetics model for marine invertebrates 23 . All input and derived parameters are detailed in Extended Data Table 1 and 2. The fertilisation model predicted fertilisation success within a close percentage of the field experiments, predicting fertilisation success with an absolute difference of 0.15% for A. cf. tenuis . For A. cf. digitifera , the model's predictions differed from the experimental data by 1.3%. Although a slightly larger difference of 6.9% between the model predictions and experimental data existed for A. cf. hyacinthus (Fig. 2b), uncertainty analyses using random parameter combinations for those parameters with a higher level of uncertainty revealed substantial alignment between the model and the empirical data for all species, as indicated by the overlap between the model results and the 95% confidence intervals of the field experimental data (Fig. 2b). Using the patch characteristics of A. cf. hyacinthus in Palau as a representative example, there was a strong effect of intercolonial distance and colony size, with fertilisation success decreasing rapidly with greater spacing between individuals and smaller size classes (Fig. 2c). For example, a 30 cm diameter colony at 1 m intercolonial distance would result in 22.7% fertilisation success, whereas the same sized colony at 5 m intercolonial distance would result in 10.7%. Further, at a fixed intercolonial distance of 1 m, a large colony of 40 cm diameter would result in 12-fold greater fertilisation success than a smaller 10 cm colony (Fig. 2c). Sensitivity analysis for several auxiliary input parameters revealed the ‘egg fertilisation efficiency’, ‘current velocities, and ‘longitudinal dispersion constant’ had the greatest influence on model predictions (Fig. 2d), and further studies on these variables to reduce their uncertainty could lead to more precise model outcomes. The model did not capture the variability observed in the container or in situ water samples, however, the alignment of the model predictions and the overall measured fertilisation success observed in the experiment suggests that our heuristic model performs well through spatial averaging of fertilisation within the slick. These findings could assist restoration practitioners in evaluating the trade-offs between outplanting fewer, larger colonies at lower density versus a greater number of smaller colonies at high densities to reduce the risk of fertilisation failure and thus ensure ongoing persistence of their restored sites through multiple generations. To estimate the influence of reef degradation on the likelihood of coral fertilisation failure, a series of simulations were run by sequentially and randomly removing individuals from virtual reef patches. To initialise colony positions on our virtual grid, we used field survey data of A. hyacinthus collected from three 10 m × 5 m belt transects on the reef crest and a single 50 m × 5 m belt transect on the slope of an offshore reef in Palau (Extended Data Figure 3). A mean colony diameter was 0.27 m used to match the mean size used in the Palau experiment, and a Monte Carlo simulation was run to evaluate how mean inter-colony spacing increases – and density and species-specific coral cover decreases – as coral colonies are lost (n=1000). Each level of colony spacing, and corresponding density, were then represented in the coral fertilisation model as a uniform square patch. Many ecological and evolutionary models ignore fertilisation Allee effects, assuming 100% fertilisation success 24 , and we see that such approaches massively overestimate embryo output particularly as coral populations begin to decline (Fig. 3a). Indeed, fertilisation decreased non-linearly as species-specific coral cover declined from a natural level of ~3% (Fig. 3b). Using a fertilisation success threshold of 10%, our model indicates that patches require at least 13 adult colonies for Acropora hyacinthus , 24 for Acropora digitifera , and 50 for Acropora tenuis within 100 m 2 to ensure fertilisation success (Fig. 3c). Allee effects during coral spawning events clearly have the potential to lead to population-level fertilisation failure. As population densities decline owing to climate change and other threats 25,26 , critical populations densities are needed to sustain reef functions into the future. Here, we show that minimal density thresholds of 13 – 50 colonies per 100 m 2 are required to sustain even modest reproductive success. In contrast to other marine invertebrates that may aggregate and thus enhance conspecific proximity 27 , the sessile nature of broadcast spawning corals markedly heightens their susceptibility to adverse consequences of Allee effects during fertilisation 28 . Further, lower gamete concentrations increase their susceptibility to environmental stressors and pollutants 18,29-31 . Across three manipulative field experiments, our findings show that while small coral patches can achieve fertilisation, the overall success is relatively low. The results from our manipulations are consistent with observations from a natural reef setting in the Caribbean where species-specific fertilisation success was low and increased with the number of spawning colonies in visual sight per diver 5 . Other studies have reported variable but sometimes higher levels of fertilisation success, yet details on adult patch population size, densities or site characterisation are often not reported, making comparisons difficult 4,32 . Overall, we model the density-dependent thresholds required to overcome Allee effects during fertilisation in coral populations. Fertilisation in Acropora is most likely to occur in the general proximity of the release site, highlighting the importance of patch-scale coral population densities rather than larger-distance dispersal prior to mixing and fertilisation. We conclude this because of several properties of coral gametes. Fertilisation typically occurs within 30 minute of egg-sperm contact 10,12,33 , the gamete immaturity phase appears non-existent (Extended Figure 1d), and egg-sperm bundles under agitation likely dissociate within 30 minutes of release 34 , and field observations report fertilisation constrained to just a few hours 4,5,16 . Moreover, our experimental container releases shows that the spawn slicks travel at 0.1–0.15 m s -1 ; typical of current velocities found during tracer dye releases, flow meter measurements, and reported for coral reefs 5,35 . These current velocities result in the fertilising slick travelling approximately 360–540 m in the first hour of spawning, and modelled fertilisation typically occurred within the first 40 min of spawning. For many areas of a typical coral reef, this raises questions about the extent to which their gametes would arrive at larger scale convergence zones such as topographically controlled fronts during the fertilisation period, as suggested elsewhere 36 . As coral reefs degrade, the diminishing numbers of colonies increases intercolonial distances, and consequently impacts fertilisation success of external spawners. Recently, Mumby et al. 37 found evidence of Allee effects during fertilisation along a natural, unmanipulated population of A. hyacinthus in Palau with nearest-neighbour intercolonial distance emerging as the most parsimonious predictor . In this study, natural adult populations of A. hyacinthus were observed at mean intercolonial distances of 0.63 m on the reef flat and 0.71 m on the reef slope, over 2-fold higher than in our experiments. Simulations of colony densities reveal a highly non-linear trend with intercolonial distances, indicating that only a few colonies within an area can markedly reduce intercolonial distances. However, approximately 26 colonies are required to reduce intercolonial distances to within 1 m, and more than 60 colonies to reduce them within 0.5 m (Extended Data Figure 4), indicating that while fertilisation success would rapidly decline as reefs degrade, it would still be maintained at a minimum level for some time, even as colonies become increasingly sparse. The thresholds presented here can be used to assess areas of reefs that require intervention, and the level of intervention needed. Population models that do not consider Allee effects on fertilisation success in broadcast spawners would overestimate larval production and supply, leading to unrealistic estimates of metapopulation recovery and resilience. Declarations Data availability statement The datasets generated and analysed during this study are deposited in the CSIRO Data Access Portal and will be made publicly available at the following link: https://data.csiro.au/. Data will be accessible upon publication of the manuscript. No clinical datasets or third-party data were used in this study. Code availability statement The code used to implement the model described in this study is available on GitHub at https://github.com/gerard-ricardo/fert-model . Acknowledgments The authors would like to acknowledge the Traditional Owners of the Great Barrier Reef, particularly the Byelle, Gooreng Gooreng, Gurang and Taribelang Bunda First Nations people of the Port Curtis Coral Coast, and the Manbarra First Nations people of the Palm Islands, for permission to work in their Sea Country with free prior and informed consent. We pay our respects to their Elders, past, present, and emerging, and acknowledge their continuing spiritual connection to their Sea Country. Work on the Great Barrier Reef was conducted under GBRMPA permits G21/44774.1 and G22/46963.1, and work in Palau under Marine Research Permit RE-22-11. We thank S. Blanchfield, J. Goldman, M. Tonks, and staff from One Tree Island Research Station, Heron Island Research Station, Orpheus Island Research Station, the National Sea Simulator at AIMS, and the Palau International Coral Research Center for assistance during the field work. J. Crosswell, T. Malthus and S. Noonan kindly provided equipment. We’d like to thank A. Wuppukondur and D. Callaghan for their advice on hydrodynamic modelling options. The authors acknowledge the facilities and technical assistance of the Centre for Microscopy and Microanalysis, UQ. This work was supported by the EcoRRAP subprogram (https://gbrrestoration.org/program/ecorrap/) that is part of the Reef Restoration and Adaptation Program (RRAP, https://gbrrestoration.org/). RRAP is funded by the partnership between the Australian Governments Reef Trust and the Great Barrier Reef Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. CRediT author statement Conceptualization: Christopher Doropoulos, Peter Mumby, Gerard Ricardo Methodology: Gerard Ricardo, Peter Mumby, Christopher Doropoulos, Russell Babcock, Elisabeth Buccheri Formal analysis: Gerard Ricardo Investigation: Gerard Ricardo, Peter Mumby, Russell Babcock, Andrew Khalil Writing - Original Draft: Gerard Ricardo Writing - Review & Editing: All authors Visualization: Gerard Ricardo Supervision: Peter Mumby, Christopher Doropoulos Funding acquisition: Christopher Doropoulos, Peter Mumby References 1 Courchamp, F., Clutton-Brock, T. & Grenfell, B. Inverse density dependence and the Allee effect. Trends Ecol. Evol. 14 , 405-410 (1999). 2 Allee, W. Animal Aggregations: A Study in General Sociology. Chicago: Chicago Univ. Press. (1931). 3 Lamont, B. B., Klinkhamer, P. G. & Witkowski, E. Population fragmentation may reduce fertility to zero in Banksia goodii—a demonstration of the Allee effect. Oecologia 94 , 446-450 (1993). 4 Oliver, J. K. & Babcock, R. C. 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R. & Hughes, T. P. The population sizes and global extinction risk of reef-building coral species at biogeographic scales. Nature Ecology & Evolution 5 , 663-669 (2021). 27 Levitan, D. R., Sewell, M. A. & Chia, F.-S. How distribution and abundance influence fertilization success in the sea urchin Strongylocentotus franciscanus . Ecology 73 , 248-254 (1992). 28 Knowlton, N. The future of coral reefs. Proceedings of the National Academy of Sciences 98 , 5419-5425 (2001). 29 Nordborg, F. M., Brinkman, D. L., Ricardo, G. F., Agustí, S. & Negri, A. P. Comparative sensitivity of the early life stages of a coral to heavy fuel oil and UV radiation. Sci. Total Environ. 781 , 146676 (2021). 30 Albright, R. & Mason, B. Projected near-future levels of temperature and pCO 2 reduce coral fertilization success. PLoS One 8 , e56468 (2013). https://doi.org:https://doi.org/10.1371/journal.pone.0056468 31 Lam, E. et al. High levels of inorganic nutrients affect fertilization kinetics, early development and settlement of the scleractinian coral Platygyra acuta . Coral Reefs 34 , 837-848 (2015). 32 Coma, R. & Lasker, H. R. Effects of spatial distribution and reproductive biology on in situ fertilization rates of a broadcast-spawning invertebrate. The Biological Bulletin 193 , 20-29 (1997). 33 Iguchi, A., Morita, M., Nakajima, Y., Nishikawa, A. & Miller, D. In vitro fertilization efficiency in coral Acropora digitifera. Zygote 17 , 225-227 (2009). 34 Wolstenholme, J. K. Temporal reproductive isolation and gametic compatibility are evolutionary mechanisms in the Acropora humilis species group (Cnidaria; Scleractinia). Mar. Biol. 144 , 567-582 (2004). 35 Panero, M., Galbraith, G., Srinivasan, M. & Jones, G. Roles of depth, current speed, and benthic cover in shaping gorgonian assemblages at the Palm Islands (Great Barrier Reef). Coral Reefs , 1-13 (2023). 36 Wolanski, E. & Hamner, W. M. Topographically controlled fronts in the ocean and their biological influence. Science 241 , 177-181 (1988). 37 Mumby, P. J. et al. Allee effects limit coral fertilization success. P Natl Acad Sci USA 121 (2024). https://doi.org:ARTN e241831412110.1073/pnas.2418314121 Additional Declarations The authors declare no competing interests. Supplementary Files 20250222AlleemsletterMethodsandExtendedData.docx Cite Share Download PDF Status: Posted Version 2 posted You are reading this latest preprint version Show more versions 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-5405858","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":375569951,"identity":"0790b54a-1602-4add-996f-2e4e425d1850","order_by":0,"name":"Gerard F. 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Mumby","email":"","orcid":"","institution":"The University of Queensland","correspondingAuthor":false,"prefix":"","firstName":"Peter","middleName":"J.","lastName":"Mumby","suffix":""}],"badges":[],"createdAt":"2024-11-07 01:31:00","currentVersionCode":2,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-5405858/v2","doiUrl":"https://doi.org/10.21203/rs.3.rs-5405858/v2","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":78549698,"identity":"7a204d7f-deb7-45fb-a872-d38ef0cdad17","added_by":"auto","created_at":"2025-03-14 19:02:32","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":882326,"visible":true,"origin":"","legend":"\u003cp\u003eField sites and fertilisation success of three \u003cem\u003eAcropora\u003c/em\u003e species. (a) Satellite imagery of One Tree Island Reef, Great Barrier Reef, Australia. Inset: a map of Australia with the study area denoted in black. (b) Satellite imagery of Koror Island, Republic of Palau. Inset: a map of the main Palauan Island group with the study area denoted in black. (c) Locations of \u003cem\u003ein situ\u003c/em\u003e sperm samples (10\u003csup\u003ex \u003c/sup\u003esperm mL\u003csup\u003e-1\u003c/sup\u003e) collected within the One Tree Island lagoon. Above: \u003cem\u003eAcropora cf. tenuis\u003c/em\u003e. Below: \u003cem\u003eAcropora \u003c/em\u003ecf. \u003cem\u003edigitifera\u003c/em\u003e. (d) Half-violin and mean plots of fertilisation success across the three species. Blue points denote individual observations (\u003cem\u003eA. cf. tenuis\u003c/em\u003e: n = 6 mesh containers, \u003cem\u003eA. digitifera\u003c/em\u003e: n = 6, \u003cem\u003eA. hyacinthus\u003c/em\u003e: n = 13). Dark-grey points denote mean and 95% CI fits of the GLMM (e) Locations of \u003cem\u003ein situ \u003c/em\u003esperm samples (10\u003csup\u003ex \u003c/sup\u003esperm mL\u003csup\u003e-1\u003c/sup\u003e) of \u003cem\u003eA. \u003c/em\u003ecf. \u003cem\u003ehyacinthus\u003c/em\u003e collected within Nikko Bay, Palau. In the sperm concentration maps (c, e) the black circles denote the release point of the mesh containers, and white crosses denotes the collection point of the mesh containers.\u003c/p\u003e","description":"","filename":"f1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5405858/v2/d16b032d0054251fea4df2f8.jpg"},{"id":78549699,"identity":"5397fa2f-47fa-4629-bec5-727c0fbc933d","added_by":"auto","created_at":"2025-03-14 19:02:33","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":557370,"visible":true,"origin":"","legend":"\u003cp\u003eFertilisation model overview, predictions, and sensitivity analysis (a) Schematic representation of the key processes in the fertilisation model. Species-specific parameters are inputted into the model in addition to the colony size, which determines the total reproductive output of the patch. The patch characteristics are then configured to closely match the manipulative field experiment. Egg-sperm bundles are released at time_step = 1, and the bundles then dispersed, advected, and ascended in a loop for each time step. Bundles dissociate conditionally (bundle loop) following truncated normal distribution, and released eggs and sperm are dispersed and advected. Eggs and sperm occurring in the same cells fertilise according to fertilisation kinetics models conditionally (gamete loop), and the resulting number of embryos are then removed from the pool. (b) Model reference prediction and uncertainty analysis (n = 20 runs) compared against the manipulative field experiments. Model reference prediction used best-estimates across model inputs, whereas the model uncertainty predictions used random combinations of inputs derived from the range of values reported in the literature. (c) Modelled fertilisation success (prop.) of colonies following the Palau 4 × 5 experimental patch arrangement and \u003cem\u003eAcropora hyacinthus\u003c/em\u003e as a test species, at various intercolonial distances and colony diameters. Red lines correspond to the proportion of fertilisation success. (d) A sensitivity test, keeping all parameters constant except the one of interest, following the Palau experimental adult patch as a reference. The red line corresponds to the best estimate of parameters.\u003c/p\u003e","description":"","filename":"f2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5405858/v2/f1798564a550923c71078347.jpg"},{"id":78549700,"identity":"247bf3ab-4cc3-42ed-9bbe-8f3fdfa9e1de","added_by":"auto","created_at":"2025-03-14 19:02:33","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":222850,"visible":true,"origin":"","legend":"\u003cp\u003eRelationships between simulated patch (10 × 10 m) characteristics and fertilisation success. (a) Embryo output and (b) fertilisation success predictions with changes in coral cover compared against 100% fertilised eggs, as is assumed in models that do not consider Allee effects. (c) The relationship between adult colony density and fertilisation successes. Colony image size is relative to difference in mean colony diameter (m); \u003cem\u003eA. cf. tenuis\u003c/em\u003e = 0.17, \u003cem\u003eA. cf. digitifera\u003c/em\u003e= 0.20, \u003cem\u003eA. cf. hyacinthus\u003c/em\u003e = 0.27. Red dashed line indicates a 10% fertilisation success threshold.\u003c/p\u003e","description":"","filename":"f3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5405858/v2/39eff5344804d12837f1e1b3.jpg"},{"id":78550966,"identity":"3ec8cb29-75cd-48b4-ae6d-2d03e155e69b","added_by":"auto","created_at":"2025-03-14 19:34:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2730228,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5405858/v2/39a5ff22-e344-46ac-8645-1f69400f1181.pdf"},{"id":78549706,"identity":"18960116-964a-497e-b842-da2ee5d86cec","added_by":"auto","created_at":"2025-03-14 19:02:33","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2479983,"visible":true,"origin":"","legend":"","description":"","filename":"20250222AlleemsletterMethodsandExtendedData.docx","url":"https://assets-eu.researchsquare.com/files/rs-5405858/v2/3589a84c4f2587d534f5995d.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eCritical thresholds of adult patch density and spacing during coral fertilisation\u003c/p\u003e","fulltext":[{"header":"Main Text","content":"\u003cp\u003eAllee effects describe the decline in individual fitness and population growth rates as population density or size decreases\u003csup\u003e1\u003c/sup\u003e. At low population sizes or densities, inverse density dependence can occur whereby the per capita growth rate of the population remains negative and local extinctions can occur if the population is not supplemented with new members \u003csup\u003e1\u003c/sup\u003e.\u0026nbsp;In coral reef ecosystems suffering widespread, climate-driven losses\u0026nbsp;\u003csup\u003e7\u003c/sup\u003e, populations falling below critical demographic and fecundity thresholds may entirely fail to reproduce\u0026nbsp;\u003csup\u003e8,9\u003c/sup\u003e.\u003csup\u003e1,2\u003c/sup\u003e.\u0026nbsp;One of the most significant Allee effects in corals occurs during external fertilisation in broadcast-spawning species, where reproductive success is highly dependent on gamete production and concentration\u0026nbsp;\u003csup\u003e10-12\u003c/sup\u003e. Fertilisation success depends on population size, the number of adult spawning colonies, their proximity to one another, and individual colony size, as larger colonies contribute disproportionately to reproductive output\u0026nbsp;\u003csup\u003e13\u003c/sup\u003e. During spawning events, gametes aggregate in surface slicks for a brief fertilisation period before wind, waves, and currents dilute them to low concentrations.\u0026nbsp;Specifically, small population sizes not only reduce the total potential reproductive output (number of eggs) but also the proportion of those fertilising, owing to largely to low sperm concentrations under local dilutive forces.\u0026nbsp;Fertilisation failure may result in a full year\u0026apos;s recruitment failure, impacting long-term resilience to ongoing ocean warming threats\u0026nbsp;\u003csup\u003e14\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor the majority of reef coral species, spawning events occur just one or two consecutive nights over a period that may last only minutes \u003csup\u003e15\u003c/sup\u003e.This limited window for reproduction heightens the vulnerability of coral populations and presents significant challenges in characterising these events. During spawning, most gamete encounters occur within a brief 2\u0026ndash;3 hr period before the coral spawn slick becomes too diluted for further fertilisation \u003csup\u003e4,5,16\u003c/sup\u003e. While laboratory studies provide insights into species-specific fertilisation responses, they neglect the hydrodynamic processes that strongly influence slick formation and persistence in the field. However, collecting empirical data during annual coral spawning events is a challenging task owing to the ephemeral nature of these events, their occurrence at night, variability in predictability, and the complexity of heterospecific spawning that co-occurs\u0026nbsp;\u003csup\u003e5,15,17\u003c/sup\u003e. Here, we conducted three manipulated experiments in the natural environment across two countries marking the first investigation, to our knowledge, to experimentally test how adult coral population densities affect fertilisation success. We utilised spatial and physical isolation of the experimental corals (herein: patches) from natural spawning populations in the main lagoon at One Tree Island, southern Great Barrier Reef, and the southern channel of Nikko Bay (Ngermid), Palau. These locales were chosen for their distinct hydrological and geographical features conducive to isolating outplanted coral patches from potential interspecific and conspecific contamination. We focused on the genus \u003cem\u003eAcropora\u003c/em\u003e, a key framework builder and rapid recoloniser, selecting \u003cem\u003eA.\u0026nbsp;\u003c/em\u003ecf\u003cem\u003e. tenuis\u003c/em\u003e and \u003cem\u003eA.\u0026nbsp;\u003c/em\u003ecf.\u003cem\u003e\u0026nbsp;digitifera\u003c/em\u003e at One Tree Island, and \u003cem\u003eA.\u0026nbsp;\u003c/em\u003ecf.\u003cem\u003e\u0026nbsp; hyacinthus\u0026nbsp;\u003c/em\u003ein Palau.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn a manipulated patch of eight smaller-sized \u003cem\u003eA.\u0026nbsp;\u003c/em\u003ecf.\u003cem\u003e\u0026nbsp;tenuis\u003c/em\u003e colonies with 2.1 m mean spacing (0.14 colonies m\u003csup\u003e-2\u003c/sup\u003e) in the lagoon of One Tree Island, the mean fertilisation success was 1.2% [Fig. 1; 95% CI: 0.2\u0026ndash;8.2%; n = 6]. A larger patch of 15 \u003cem\u003eA.\u0026nbsp;\u003c/em\u003ecf.\u003cem\u003e\u0026nbsp;digitifera\u0026nbsp;\u003c/em\u003ecolonies with a tighter 1.1 m mean spacing (0.25 colonies m\u003csup\u003e-2\u003c/sup\u003e) achieved a slightly higher fertilisation success of 7.0% in [95% CI: 2.6\u0026ndash;17.3%; n = 6]. In Palau, a larger patch of 20 larger-sized colonies of the table coral \u003cem\u003eA. hyacinthus\u003c/em\u003e, spaced 1 m apart (0.69 colonies m\u003csup\u003e-2\u003c/sup\u003e), achieved a mean fertilisation rate of 8.7% [95% CI: 4.6\u0026ndash;15.8%; n = 13].. These experiments demonstrate clear evidence of Allee effects in small populations, with none achieving more than 10% fertilisation success on average. Heterogeneity among replicates of the egg containers and the \u003cem\u003ein-situ\u003c/em\u003e sperm concentrations indicates high spatial variability of the manipulated spawn slick, similar to observations in coral spawn slicks from wild populations in previous studies \u003csup\u003e4,5\u003c/sup\u003e. For example, fertilisation in \u003cem\u003eA\u003c/em\u003e. cf.\u003cem\u003e\u0026nbsp;tenuis\u003c/em\u003e was primarily attributed to a single replicate (~25% fertilisation), the only sample exceeding the contamination and self-fertilisation controls of ~2% (Fig. 1 d). Successful outcross fertilisation was observed in over 50% of \u003cem\u003eA. cf. digitifera\u003c/em\u003e samples , and 86% of \u003cem\u003eA.\u0026nbsp;\u003c/em\u003ecf.\u003cem\u003e\u0026nbsp;hyacinthus\u003c/em\u003e samples (Fig. 1 d). \u003cem\u003eIn situ\u003c/em\u003e sperm concentrations measured by flow cytometry ranged from 0 to 2.2 \u0026times; 10\u003csup\u003e3\u003c/sup\u003e sperm mL\u003csup\u003e-1\u003c/sup\u003e for \u003cem\u003eA. tenuis\u003c/em\u003e, 9.6\u0026nbsp;\u0026times;\u0026nbsp;10\u003csup\u003e1\u003c/sup\u003e to 1.3 \u0026times; 10\u003csup\u003e3\u003c/sup\u003e sperm mL\u003csup\u003e-1\u003c/sup\u003e for \u003cem\u003eA. digitifera\u003c/em\u003e, and 0 to 9.4\u0026nbsp;\u0026times;\u0026nbsp;10\u003csup\u003e3\u003c/sup\u003e sperm mL\u003csup\u003e-1\u003c/sup\u003e for \u003cem\u003eA. hyacinthus\u003c/em\u003e (Fig. 1 c, e). The highest sperm concentrations recorded in field samples corresponded to levels sufficient for fertilisation success reported in laboratory experiments of the same species i.e. \u0026gt;10\u003csup\u003e3\u003c/sup\u003e sperm mL\u003csup\u003e-1\u003c/sup\u003e \u003csup\u003e10,18,19\u003c/sup\u003e, but were markedly lower than those considered as \u0026lsquo;optimal\u0026rsquo; or saturating sperm concentrations\u0026rsquo; \u003csup\u003e4,12\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo understand the potential for Allee effects, we created a spatially explicit coral fertilisation model independent of our field experiments. For model parameterisation, we conducted a suite of biological and hydrodynamic experiments (see Methods; Extended Data Figure 1\u0026ndash;2), in addition to using values reported in the literature. Instantaneous release of gametes into a turbulent flow was modelled as an advection-diffusion problem in a scalar field\u0026nbsp;using an explicit finite difference method, with this approach differing from traditional steady-state assumptions found in previous fertilisation models \u003csup\u003e20-22\u003c/sup\u003e (Fig. 2a). The grid was initialised using the predicted gamete production (fecundity) based on colony size, polyps per area, gametes per bundle, and the proportion of the colony that is fertile (fertile zone). Gametes (bundle, eggs, sperm) were subject to different turbulent diffusion forces depending on their position in the water column and the gamete type. Upon bundle dissociation, fertilisation success for each time step was calculated using a polyspermy-block fertilisation kinetics model for marine invertebrates \u003csup\u003e23\u003c/sup\u003e. All input and derived parameters are detailed in Extended Data Table 1 and 2.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe fertilisation model predicted fertilisation success within a close percentage of the field experiments, predicting fertilisation success with an absolute difference of 0.15% for \u003cem\u003eA.\u0026nbsp;\u003c/em\u003ecf.\u003cem\u003e\u0026nbsp;tenuis\u003c/em\u003e. For \u003cem\u003eA.\u0026nbsp;\u003c/em\u003ecf.\u003cem\u003e\u0026nbsp;digitifera\u003c/em\u003e, the model\u0026apos;s predictions differed from the experimental data by 1.3%. Although a slightly larger difference of 6.9% between the model predictions and experimental data existed for \u003cem\u003eA.\u0026nbsp;\u003c/em\u003ecf. \u003cem\u003ehyacinthus\u0026nbsp;\u003c/em\u003e(Fig. 2b), uncertainty analyses using random parameter combinations for those parameters with a higher level of uncertainty revealed substantial alignment between the model and the empirical data for all species, as indicated by the overlap between the model results and the 95% confidence intervals of the field experimental data (Fig. 2b). Using the\u003cem\u003e\u0026nbsp;\u003c/em\u003epatch characteristics of \u003cem\u003eA. cf. hyacinthus\u003c/em\u003e in Palau as a representative example, there was a strong effect of intercolonial distance and colony size, with fertilisation success decreasing rapidly with greater spacing between individuals and smaller size classes (Fig. 2c). For example, a 30 cm diameter colony at 1 m intercolonial distance would result in 22.7% fertilisation success, whereas the same sized colony at 5 m intercolonial distance would result in 10.7%. Further, at a fixed intercolonial distance of 1 m, a large colony of 40 cm diameter would result in 12-fold greater fertilisation success than a smaller 10 cm colony (Fig. 2c). Sensitivity analysis for several auxiliary input parameters revealed the \u0026lsquo;egg fertilisation efficiency\u0026rsquo;, \u0026lsquo;current velocities, and \u0026lsquo;longitudinal dispersion constant\u0026rsquo; had the greatest influence on model predictions (Fig. 2d), and further studies on these variables to reduce their uncertainty could lead to more precise model outcomes. The model did not capture the variability observed in the container or \u003cem\u003ein situ\u003c/em\u003e water samples, however, the alignment of the model predictions and the overall measured fertilisation success observed in the experiment suggests that our heuristic model performs well through spatial averaging of fertilisation within the slick. These findings could assist restoration practitioners in evaluating the trade-offs between outplanting fewer, larger colonies at lower density versus a greater number of smaller colonies at high densities to reduce the risk of fertilisation failure and thus ensure ongoing persistence of their restored sites through multiple generations. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo estimate the influence of reef degradation on the likelihood of coral fertilisation failure, a series of simulations were run by sequentially and randomly removing individuals from virtual reef patches. To initialise colony positions on our virtual grid, we used field survey data of \u003cem\u003eA. hyacinthus\u003c/em\u003e collected from three 10 m \u0026times; 5 m belt transects on the reef crest and a single 50 m \u0026times; 5 m belt transect on the slope of an offshore reef in Palau (Extended Data Figure 3). A mean colony diameter was 0.27 m used to match the mean size used in the Palau experiment, and a Monte Carlo simulation was run to evaluate how mean inter-colony spacing increases \u0026ndash; and density and species-specific coral cover decreases \u0026ndash; as coral colonies are lost (n=1000). Each level of colony spacing, and corresponding density, were then represented in the coral fertilisation model as a uniform square patch. Many ecological and evolutionary models ignore fertilisation Allee effects, assuming 100% fertilisation success\u003csup\u003e24\u003c/sup\u003e, and we see that such approaches massively overestimate embryo output particularly as coral populations begin to decline (Fig. 3a). Indeed, fertilisation decreased non-linearly as species-specific coral cover declined from a natural level of ~3% (Fig. 3b). Using a fertilisation success threshold of 10%, our model indicates that patches require at least 13 adult colonies for \u003cem\u003eAcropora hyacinthus\u003c/em\u003e, 24 for \u003cem\u003eAcropora digitifera\u003c/em\u003e, and 50 for \u003cem\u003eAcropora tenuis\u003c/em\u003e within 100 m\u003csup\u003e2\u003c/sup\u003e to ensure fertilisation success (Fig. 3c).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAllee effects during coral spawning events clearly have the potential to lead to population-level fertilisation failure. As population densities decline owing to climate change and other threats \u003csup\u003e25,26\u003c/sup\u003e, critical populations densities are needed to sustain reef functions into the future. Here, we show that minimal density thresholds of 13 \u0026ndash; 50 colonies per 100 m\u003csup\u003e2\u003c/sup\u003e are required to sustain even modest reproductive success. In contrast to other marine invertebrates that may aggregate and thus enhance conspecific proximity \u003csup\u003e27\u003c/sup\u003e, the sessile nature of broadcast spawning corals markedly heightens their susceptibility to adverse consequences of Allee effects during fertilisation \u003csup\u003e28\u003c/sup\u003e.\u0026nbsp;Further, lower gamete concentrations increase their susceptibility to environmental stressors and pollutants\u0026nbsp;\u003csup\u003e18,29-31\u003c/sup\u003e.\u0026nbsp;Across three manipulative field experiments, our findings show that while small coral patches can achieve fertilisation, the overall success is relatively low. The results from our manipulations are consistent with observations from a natural reef setting in the Caribbean where species-specific fertilisation success was low and increased with the number of spawning colonies in visual sight per diver\u0026nbsp;\u003csup\u003e5\u003c/sup\u003e. Other studies have reported variable but sometimes higher levels of fertilisation success, yet details on adult patch population size, densities or site characterisation are often not reported, making comparisons difficult\u003csup\u003e4,32\u003c/sup\u003e. Overall, we model the density-dependent thresholds required to overcome Allee effects during fertilisation in coral populations.\u003c/p\u003e\n\u003cp\u003eFertilisation in \u003cem\u003eAcropora\u003c/em\u003e is most likely to occur in the general proximity of the release site, highlighting the importance of patch-scale coral population densities rather than larger-distance dispersal prior to mixing and fertilisation. We conclude this because of several properties of coral gametes. \u0026nbsp;Fertilisation typically occurs within 30 minute of egg-sperm contact \u003csup\u003e10,12,33\u003c/sup\u003e, the gamete immaturity phase appears non-existent (Extended Figure 1d), and egg-sperm bundles under agitation likely dissociate within 30 minutes of release\u003csup\u003e34\u003c/sup\u003e, and field observations report fertilisation constrained to just a few hours \u003csup\u003e4,5,16\u003c/sup\u003e. Moreover, our experimental container releases shows that the spawn slicks travel at 0.1\u0026ndash;0.15 m s\u003csup\u003e-1\u003c/sup\u003e; typical of current velocities found during tracer dye releases, flow meter measurements, and reported for coral reefs \u003csup\u003e5,35\u003c/sup\u003e. These current velocities result in the fertilising slick travelling approximately 360\u0026ndash;540 m in the first hour of spawning, and modelled fertilisation typically occurred within the first 40 min of spawning. For many areas of a typical coral reef, this raises questions about the extent to which their gametes would arrive at larger scale convergence zones such as topographically controlled fronts during the fertilisation period, as suggested elsewhere \u003csup\u003e36\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAs coral reefs degrade, the diminishing numbers of colonies increases intercolonial distances, and consequently impacts fertilisation success of external spawners. Recently, Mumby et al. \u003csup\u003e37\u003c/sup\u003e found evidence of Allee effects during fertilisation along a natural, unmanipulated population of \u003cem\u003eA. hyacinthus\u0026nbsp;\u003c/em\u003ein Palau with nearest-neighbour intercolonial distance emerging as the most parsimonious predictor\u003cem\u003e.\u003c/em\u003e In this study, natural adult populations of \u003cem\u003eA. hyacinthus\u003c/em\u003e were observed at mean intercolonial distances of 0.63 m on the reef flat and 0.71 m on the reef slope, over 2-fold higher than in our experiments. Simulations of colony densities reveal a highly non-linear trend with intercolonial distances, indicating that only a few colonies within an area can markedly reduce intercolonial distances. However, approximately 26 colonies are required to reduce intercolonial distances to within 1 m, and more than 60 colonies to reduce them within 0.5 m (Extended Data Figure 4), indicating that while fertilisation success would rapidly decline as reefs degrade, it would still be maintained at a minimum level for some time, even as colonies become increasingly sparse. The thresholds presented here can be used to assess areas of reefs that require intervention, and the level of intervention needed. Population models that do not consider Allee effects on fertilisation success in broadcast spawners would overestimate larval production and supply, leading to unrealistic estimates of metapopulation recovery and resilience.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch1\u003eData availability statement\u003c/h1\u003e\n\u003cp\u003eThe datasets generated and analysed during this study are deposited in the CSIRO Data Access Portal and will be made publicly available at the following link: https://data.csiro.au/. Data will be accessible upon publication of the manuscript. No clinical datasets or third-party data were used in this study.\u003c/p\u003e\n\u003ch1\u003eCode availability statement\u003c/h1\u003e\n\u003cp\u003eThe code used to implement the model described in this study is available on GitHub at \u003ca href=\"https://github.com/gerard-ricardo/fert-model\" target=\"_blank\" title=\"https://github.com/gerard-ricardo/fert-model\"\u003ehttps://github.com/gerard-ricardo/fert-model\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch1\u003eAcknowledgments\u003c/h1\u003e\n\u003cp\u003eThe authors would like to acknowledge the Traditional Owners of the Great Barrier Reef, particularly the Byelle, Gooreng Gooreng, Gurang and Taribelang Bunda First Nations people of the Port Curtis Coral Coast,\u0026nbsp;and the Manbarra First Nations people of the Palm Islands, for permission to work in their Sea Country with free prior and informed consent. We pay our respects to their Elders, past, present, and emerging, and acknowledge their continuing spiritual connection to their Sea Country. Work on the Great Barrier\u0026nbsp;Reef was conducted under GBRMPA permits G21/44774.1 and G22/46963.1, and work in Palau under Marine Research Permit RE-22-11. We thank S. Blanchfield, J. Goldman, M. Tonks, and staff from One Tree Island Research Station, Heron Island Research Station, Orpheus Island Research Station, the National Sea Simulator at AIMS, and the Palau International Coral Research Center for assistance during the field work. J. Crosswell, T. Malthus and S. Noonan kindly provided equipment. We\u0026rsquo;d like to thank A. Wuppukondur and D. Callaghan for their advice on hydrodynamic modelling options. The authors acknowledge the facilities and technical assistance of the Centre for Microscopy and Microanalysis, UQ. This work was supported by the EcoRRAP subprogram (https://gbrrestoration.org/program/ecorrap/) that is part of the Reef Restoration and Adaptation Program (RRAP, https://gbrrestoration.org/). RRAP is funded by the partnership between the Australian Governments Reef Trust and the Great Barrier Reef Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003ch1\u003eCRediT author statement\u003c/h1\u003e\n\u003cp\u003eConceptualization: Christopher Doropoulos, Peter Mumby, Gerard Ricardo\u003c/p\u003e\n\u003cp\u003eMethodology: Gerard Ricardo, Peter Mumby, Christopher Doropoulos, Russell Babcock, Elisabeth Buccheri\u003c/p\u003e\n\u003cp\u003eFormal analysis: Gerard Ricardo\u003c/p\u003e\n\u003cp\u003eInvestigation: Gerard Ricardo, Peter Mumby, Russell Babcock, Andrew Khalil\u003c/p\u003e\n\u003cp\u003eWriting - Original Draft: Gerard Ricardo\u003c/p\u003e\n\u003cp\u003eWriting - Review \u0026amp; Editing: All authors\u003c/p\u003e\n\u003cp\u003eVisualization: Gerard Ricardo\u003c/p\u003e\n\u003cp\u003eSupervision: Peter Mumby, Christopher Doropoulos\u003c/p\u003e\n\u003cp\u003eFunding acquisition: Christopher Doropoulos, Peter Mumby\u003c/p\u003e"},{"header":"References","content":"\u003cp\u003e1\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Courchamp, F., Clutton-Brock, T. \u0026amp; Grenfell, B. 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J.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Allee effects limit coral fertilization success. \u003cem\u003eP Natl Acad Sci USA\u003c/em\u003e \u003cstrong\u003e121\u003c/strong\u003e (2024). \u003ca href=\"https://doi.org:ARTN\"\u003ehttps://doi.org:ARTN\u003c/a\u003e e241831412110.1073/pnas.2418314121\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Queensland","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Allee effects, Coral reproduction, Population thresholds, Fertilisation model","lastPublishedDoi":"10.21203/rs.3.rs-5405858/v2","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5405858/v2","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eExtreme climate events have severe impacts on the ecological functioning of marine ecosystems by causing wide-spread declines in population sizes and, for surviving individuals, limiting the capacity for population recovery through sexual reproduction. Ecological theory suggests that impacted populations can suffer local extinction due to Allee effects that occur during reproduction \u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e1-3\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e: large distances between corals prevents gamete encounters, resulting in reproductive failure \u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e4-6\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e. Corals are particularly vulnerable to climate impacts; however, without understanding the relationship between the spacing of spawning individuals and fertilisation success, reefs may pass a critical population threshold before effective conservation measures can be implemented. To assess the influence of adult patch characteristics on fertilisation success, we conducted a series of manipulative field experiments using three common broadcast-spawning \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eAcropora\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e species in two countries (One Tree Island, GBR; and Nikko Bay, Palau). Experimental coral populations ranged in mean intercolonial distance from 1 to 2 m and resulted in low but notable fertilisation success, ranging from 1.2 to 8.7%. We developed an independent mechanistic coral fertilisation model whose predictions closely aligned with the empirical data. The model predicts that in absence of strong convergence zones, adult coral densities need to exceed 13 – 50 colonies per 100 square meters for reefs to remain 10% reproductively functional.\u003c/strong\u003e\u003c/p\u003e","manuscriptTitle":"Critical thresholds of adult patch density and spacing during coral fertilisation","msid":"","msnumber":"","nonDraftVersions":[{"code":2,"date":"2025-03-14 19:02:28","doi":"10.21203/rs.3.rs-5405858/v2","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}},{"code":1,"date":"2024-11-08 05:06:14","doi":"10.21203/rs.3.rs-5405858/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"05a725d1-eb98-4ea6-8841-f3ace86802c9","owner":[],"postedDate":"March 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":44718220,"name":"Marine and Freshwater Ecology"},{"id":44718221,"name":"Ecological Modeling"},{"id":44718222,"name":"Population Biology"}],"tags":[],"updatedAt":"2024-11-08T05:06:14+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-14 19:02:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v2","identity":"rs-5405858","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5405858","identity":"rs-5405858","version":["v2"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}