Philippa Kaur

Kazarov, E. The Role of Zoos in Creating a Conservation Ethic in Visitors. SIT Digital Collections (2022). at https://digitalcollections.sit.edu/isp_collection/584.Hosey, G. How does the zoo environment affect the behaviour of captive primates?. Appl. Anim. Behav. Sci. 90, 107–129 (2005).
Google Scholar 
Morgan, K. & Tromborg, C. Sources of stress in captivity. Appl. Anim. Behav. Sci. 102, 262–302 (2007).
Google Scholar 
Sherwen, S. & Hemsworth, P. The visitor effect on zoo animals: Implications and opportunities for zoo animal welfare. Animals 9, 366 (2019).PubMed Central 

Google Scholar 
Chamove, A., Hosey, G. & Schaetzel, P. Visitors excite primates in zoos. Zoo Biol. 7, 359–369 (1988).
Google Scholar 
Tetley, C. L. & O’Hara, S. J. Ratings of animal personality as a tool for improving the breeding, management and welfare of zoo mammals. Anim. Welf. UFAW J. 21(4), 463 (2012).CAS 

Google Scholar 
Stoinski, T. S., Jaicks, H. F. & Drayton, L. A. Visitor effects on the behavior of captive western lowland gorillas: The importance of individual differences in examining welfare. Zoo Biol. 31(5), 586–599 (2012).PubMed 

Google Scholar 
Queiroz, M. B. & Young, R. J. The different physical and behavioural characteristics of zoo mammals that influence their response to visitors. Animals 8(8), 139 (2018).PubMed Central 

Google Scholar 
Fanson, K. V. & Wielebnowski, N. C. Effect of housing and husbandry practices on adrenocortical activity in captive Canada lynx (Lynx canadensis). Anim. Welf. 22, 159–165 (2013).CAS 

Google Scholar 
Pirovino, M. et al. Fecal glucocorticoid measurements and their relation to rearing, behavior, and environmental factors in the population of pileated gibbons (Hylobates pileatus) held in European zoos. Int. J. Primatol. 32(5), 1161–1178 (2011).
Google Scholar 
Williams, I., Hoppitt, W. & Grant, R. The effect of auditory enrichment, rearing method and social environment on the behavior of zoo-housed psittacines (Aves: Psittaciformes); implications for welfare. Appl. Anim. Behav. Sci. 186, 85–92 (2017).
Google Scholar 
Fernandez, E., Tamborski, M., Pickens, S. & Timberlake, W. Animal–visitor interactions in the modern zoo: Conflicts and interventions. Appl. Anim. Behav. Sci. 120, 1–8 (2009).
Google Scholar 
Hosey, G. & Skyner, L. Self-injurious behavior in zoo primates. Int. J. Primatol. 28, 1431–1437 (2007).
Google Scholar 
Mallapur, A., Sinha, A. & Waran, N. Influence of visitor presence on the behaviour of captive lion-tailed macaques (Macaca silenus) housed in Indian zoos. Appl. Anim. Behav. Sci. 94, 341–352 (2005).
Google Scholar 
Davey, G. Visitors’ Effects on the Welfare of Animals in the Zoo: A Review. J. Appl. Anim. Welf. Sci. 10, 169–183 (2007).CAS 
PubMed 

Google Scholar 
Jones, H., McGregor, P., Farmer, H. & Baker, K. The influence of visitor interaction on the behavior of captive crowned lemurs (Eulemur coronatus) and implications for welfare. Zoo Biol. 35, 222–227 (2016).CAS 
PubMed 

Google Scholar 
Cook, S. & Hosey, G. R. Interaction sequences between chimpanzees and human visitors at the zoo. Zoo Biol. 14(5), 431–440 (1995).
Google Scholar 
Baker, K. C. Benefits of positive human interaction for socially-housed chimpanzees. Anim. Welf. (South Mimms, Engl.nd) 13(2), 239 (2004).CAS 

Google Scholar 
Carder, G. & Semple, S. Visitor effects on anxiety in two captive groups of western lowland gorillas. Appl. Anim. Behav. Sci. 115, 211–220 (2008).
Google Scholar 
Wood, W. Interactions among environmental enrichment, viewing crowds, and zoo chimpanzees (Pantroglodytes). Zoo Biol. 17, 211–230 (1998).
Google Scholar 
Todd, P., Macdonald, C. & Coleman, D. Visitor-associated variation in captive Diana monkey (Cercopithecus diana diana) behaviour. Appl. Anim. Behav. Sci. 107, 162–165 (2007).
Google Scholar 
Davis, N., Schaffner, C. & Smith, T. Evidence that zoo visitors influence HPA activity in spider monkeys (Ateles geoffroyii rufiventris). Appl. Anim. Behav. Sci. 90, 131–141 (2005).
Google Scholar 
Sherwen, S. L. et al. Effects of visual contact with zoo visitors on black-capped capuchin welfare. Appl. Anim. Behav. Sci. 167, 65–73 (2015).
Google Scholar 
Choo, Y., Todd, P. & Li, D. Visitor effects on zoo orangutans in two novel, naturalistic enclosures. Appl. Anim. Behav. Sci. 133, 78–86 (2011).
Google Scholar 
Sherwen, S., Magrath, M., Butler, K., Phillips, C. & Hemsworth, P. A multi-enclosure study investigating the behavioural response of meerkats to zoo visitors. Appl. Anim. Behav. Sci. 156, 70–77 (2014).
Google Scholar 
Hosey, G. & Druck, P. The influence of zoo visitors on the behaviour of captive primates. Appl. Anim. Behav. Sci. 18, 19–29 (1987).
Google Scholar 
Mitchell, G. et al. More on the ‘influence’of zoo visitors on the behaviour of captive primates. Appl. Anim. Behav. Sci. 35(2), 189–198 (1992).
Google Scholar 
Sellinger, R. & Ha, J. The effects of visitor density and intensity on the behavior of two captive jaguars (Panthera onca). J. Appl. Anim. Welfare Sci. 8, 233–244 (2005).CAS 

Google Scholar 
Azevedo, C., Lima, M., Silva, V., Young, R. & Rodrigues, M. Visitor Influence on the Behavior of Captive Greater Rheas (Rhea americana, Rheidae Aves). J. Appl. Anim. Welfare Sci. 15, 113–125 (2012).
Google Scholar 
Das Gupta, M., Das, A., Sumy, M. C. & Islam, M. M. An explorative study on visitor’s behaviour and their effect on the behaviour of primates at Chittagong zoo. Bangladesh J. Vet. Anim. Sci. 5(2), 24–32 (2017).
Google Scholar 
Hemsworth, P. Human–animal interactions in livestock production. Appl. Anim. Behav. Sci. 81, 185–198 (2003).
Google Scholar 
Stoinski, T., Czekala, N., Lukas, K. & Maple, T. Urinary androgen and corticoid levels in captive, male Western lowland gorillas (Gorilla g. gorilla): Age- and social group-related differences. Am. J. Primatol. 56, 73–87 (2002).CAS 
PubMed 

Google Scholar 
Stoinski, T., Lukas, K., Kuhar, C. & Maple, T. Factors influencing the formation and maintenance of all-male gorilla groups in captivity. Zoo Biol. 23, 189–203 (2004).
Google Scholar 
Olsson, I. & Westlund, K. More than numbers matter: The effect of social factors on behaviour and welfare of laboratory rodents and non-human primates. Appl. Anim. Behav. Sci. 103, 229–254 (2007).
Google Scholar 
Martin, J. E. Early life experiences: Activity levels and abnormal behaviours in resocialised chimpanzees. Anim Welf. 11(4), 419–436 (2002).CAS 

Google Scholar 
Birkett, L. P. & Newton-Fisher, N. E. How abnormal is the behaviour of captive, zoo-living chimpanzees?. PLoS ONE 6(6), e20101 (2011).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Ballen, C., Shine, R. & Olsson, M. Effects of early social isolation on the behaviour and performance of juvenile lizards Chamaeleo calyptratus. Anim. Behav. 88, 1–6 (2014).
Google Scholar 
Coe, C., Mendoza, S., Smotherman, W. & Levine, S. Mother-infant attachment in the squirrel monkey: Adrenal response to separation. Behav. Biol. 22, 256–263 (1978).CAS 
PubMed 

Google Scholar 
Mendoza, S., Smotherman, W., Miner, M., Kaplan, J. & Levine, S. Pituitary-adrenal response to separation in mother and infant squirrel monkeys. Dev. Psychobiol. 11, 169–175 (1978).CAS 
PubMed 

Google Scholar 
Gilbert, M. & Baker, K. Social buffering in adult male rhesus macaques (Macaca mulatta): Effects of stressful events in single vs. pair housing. J. Med. Primatol. 40, 71–78 (2010).PubMed 
PubMed Central 

Google Scholar 
Schapiro, S. Effects of social manipulations and environmental enrichment on behavior and cell-mediated immune responses in rhesus macaques. Pharmacol. Biochem. Behav. 73, 271–278 (2002).CAS 
PubMed 

Google Scholar 
Chen, W. et al. Effects of social isolation and re-socialization on cognition and ADAR1 (p110) expression in mice. PeerJ 4, e2306 (2016).PubMed 
PubMed Central 

Google Scholar 
Glatston, A., Geilvoet-Soeteman, E., Hora-Pecek, E. & Van Hooff, J. The influence of the zoo environment on social behavior of groups of cotton-topped tamarins Saguinus oedipus oedipus. Zoo Biol. 3, 241–253 (1984).
Google Scholar 
Mitchell, G. et al. Effects of visitors and cage changes on the behaviors of mangabeys. Zoo Biol. 10, 417–423 (1991).
Google Scholar 
Geissmann, T. & Orgeldinger, M. The relationship between duet songs and pair bonds in siamangs Hylobates syndactylus. Anim. Behav. 60, 805–809 (2000).CAS 
PubMed 

Google Scholar 
Palombit, R. Pair bonds in monogamous apes: A comparison of the siamang hylobates syndactylus and the white-handed gibbon hylobates lar. Behaviour 133, 321–356 (1996).
Google Scholar 
Rutberg, A. The evolution of monogamy in primates. J. Theor. Biol. 104, 93–112 (1983).ADS 
CAS 
PubMed 

Google Scholar 
Giorgi, A., Montebovi, G., Vitale, A. & Alleva, E. A behavioural case study of early social isolation of a subadult white-handed gibbon (Hylobates lar). Folia Primatol. 89, 287–294 (2018).
Google Scholar 
Skynner, L. A., Amory, J. R. & Hosey, G. The effect of visitors on the self-injurious behaviour of a male pileated gibbon (Hylobates pileatus). Zool. Garten 74(1), 38–41 (2004).
Google Scholar 
Smith, K. & Kuhar, C. Siamangs (Hylobates syndactylus) and white-cheeked gibbons (Hylobates leucogenys) show few behavioral differences related to zoo attendance. J. Appl. Anim. Welfare Sci. 13, 154–163 (2010).CAS 

Google Scholar 
Lukas, K. E. et al. Longitudinal study of delayed reproductive success in a pair of white-cheeked gibbons (Hylobates leucogenys). Zoo Biol. 21, 413–434 (2002).
Google Scholar 
Cooke, C. & Schillaci, M. Behavioral responses to the zoo environment by white handed gibbons. Appl. Anim. Behav. Sci. 106, 125–133 (2007).
Google Scholar 
Mootnick, A. & Baker, E. Masturbation in captiveHylobates (gibbons). Zoo Biol. 13, 345–353 (1994).
Google Scholar 
Geissmann, T. Reassessment of age of sexual maturity in gibbons (hylobates spp.). American Journal of Primatology 23, 11–22 (1991).Altmann, J. Observational study of behavior: Sampling methods. Behaviour 49(3–4), 227–266 (1974).CAS 
PubMed 

Google Scholar 
Pomerantz, O. & Terkel, J. Effects of positive reinforcement training techniques on the psychological welfare of zoo-housed chimpanzees (Pan troglodytes). Am. J. Primatol. 71, 687–695 (2009).PubMed 

Google Scholar 
Orgeldinger, M. Protective and territorial behavior in captive siamangs (Hylobates syndactylus). Zoo Biol. 16, 309–325 (1997).
Google Scholar 
Fox, J. et al. Package ‘car’. Vienna: R Foundation for Statistical Computing, 16 https://cran.uni-muenster.de/web/packages/car/car.pdf (2012).Magnusson, A., Skaug, H., Nielsen, A., Berg, C., Kristensen, K., Maechler, M., van Bentham, K., Bolker, B., Brooks, M. & Brooks, M. M. Package ‘glmmtmb’. R Package Version 0.2. 0 (2017).Hartig, F., & Hartig, M. F. Package ‘DHARMa’. Vienna, Austria: R Development Core Team (2017).Troisi, A. Displacement activities as a behavioral measure of stress in nonhuman primates and human subjects. Stress 5, 47–54 (2002).PubMed 

Google Scholar 
Baker, K. & Aureli, F. Behavioural indicators of anxiety: An empirical test in chimpanzees. Behaviour 134, 1031–1050 (1997).
Google Scholar 
Vick, S. J. & Paukner, A. Variation and context of yawns in captive chimpanzees (Pan troglodytes). Am. J. Primatol. Off. J. Am. Soc. Primatol. 72(3), 262–269 (2010).
Google Scholar 
Norscia, I. & Palagi, E. When play is a family business: Adult play, hierarchy, and possible stress reduction in common marmosets. Primates 52, 101–104 (2010).PubMed 

Google Scholar 
Held, S. & Špinka, M. Animal play and animal welfare. Anim. Behav. 81, 891–899 (2011).
Google Scholar 
Davey, G. Visitor behavior in zoos: A review. Anthrozoös 19, 143–157 (2006).
Google Scholar 
Nimon, A. & Dalziel, F. Cross-species interaction and communication: a study method applied to captive siamang (Hylobates syndactylus) and long-billed corella (Cacatua tenuirostris) contacts with humans. Appl. Anim. Behav. Sci. 33, 261–272 (1992).
Google Scholar 
Suomi, S. Early determinants of behaviour: Evidence from primate studies. Br. Med. Bull. 53, 170–184 (1997).CAS 
PubMed 

Google Scholar 
Anderson, J. & Chamove, A. Self-aggression and social aggression in laboratory-reared macaques. J. Abnorm. Psychol. 89, 539–550 (1980).CAS 
PubMed 

Google Scholar 
Mallapur, A. & Choudhury, B. Behavioral abnormalities in captive nonhuman primates. J. Appl. Anim. Welfare Sci. 6, 275–284 (2003).CAS 

Google Scholar 
Barlow, C., Caldwell, C. & Lee, P. Individual differences and response to visitors in zoo-housed diana monkeys (Cercopithecus diana diana). Cabdirect.org (2022). at https://www.cabdirect.org/cabdirect/abstract/20123180753.Gartner, M. & Weiss, A. Studying primate personality in zoos: Implications for the management, welfare and conservation of great apes. International Zoo Yearbook 52, 79–91 (2018).
Google Scholar 
Mitchell, G., Raymond, E., Ruppenthal, G. & Harlow, H. Long-term effects of total social isolation upon behavior of rhesus monkeys. Psychol. Rep. 18, 567–580 (1966).
Google Scholar 
Martín, O., Vinyoles, D., García-Galea, E. & Maté, C. Improving the welfare of a zoo-housed male drill (Mandrillus leucophaeus poensis) aggressive toward visitors. J. Appl. Anim. Welfare Sci. 19, 323–334 (2016).
Google Scholar 
Ross, S., Melber, L., Gillespie, K. & Lukas, K. The impact of a modern, naturalistic exhibit design on visitor behavior: A cross-facility comparison. Visitor Stud. 15, 3–15 (2012).
Google Scholar 
Quadros, S., Goulart, V., Passos, L., Vecci, M. & Young, R. Zoo visitor effect on mammal behaviour: Does noise matter?. Appl. Anim. Behav. Sci. 156, 78–84 (2014).
Google Scholar 
Bonnie, K., Ang, M. & Ross, S. Effects of crowd size on exhibit use by and behavior of chimpanzees (Pan troglodytes) and Western lowland gorillas (Gorilla gorilla) at a zoo. Appl. Anim. Behav. Sci. 178, 102–110 (2016).
Google Scholar  More

Model validationBased on the time-series validations of water temperature and DO concentration, model accuracy improved gradually, despite several discrepancies at the beginning of the simulation (Supplementary Fig. S1). The model is primarily driven by a set of boundary data, including wind speed, solar radiation, and precipitation data24,25. From this perspective, more high-quality boundary data promotes better numerical reproducibility. However, meteorological data collection was challenging due to the early observation equipment limitations and low observational accuracy compared to current data. The temporal inconsistency of accuracy in observational data has been eliminated to a large extent by fitting a regression curve24. Spatial resolution is the other issue. Possessing spatially constant values for all boundary conditions complicates the numerical reproducibility of variations on finer scales.The relationship between turnovers and the curve shape of water temperature versus DO concentration is theoretically sound27,28. In the last stage of stratification in the lake, water temperature and DO concentration near the bottom are more likely to slightly increase due to thermal diffusion and DO supplies from the upper water. If a turnover occurs, the whole column of water is mixed strongly (Supplementary Fig. S3). Bottom water temperature decreases due to surface water cooling, and DO concentration increases, due to surface water replenishment and increased oxygen solubility. If the turnover fails, only the partial column of water is mixed, causing a delay in the timing of deep-water renewal (Supplementary Fig. S3). However, the upper water in later months, like that in March, has been rapidly warmed, resulting in an increase in the bottom water temperature. For example, in 2007 and 2016, the simulated water temperature and DO concentration fluctuated within a limited range in February and then skyrocketed in March, after mixing with the warmed surface water (blue points in Supplementary Fig. S4). On the other hand, explicit definitions of turnover timing are challenging. The threshold used to judge turnover timing is reliable because the results matched the observation. The turnover timing varied by 36 days in Lake Biwa during the simulation period, which is comparable to that observed in other lakes, such as approximately 21 days in Heiligensee, Germany over a 17-year timespan29, 16 days in Lake Washington over a 40-year timespan30, and 28 days in Blelham Tarn over a 41-year timespan31.Variables affecting the mixing regimeDetermining variables that affect the mixing regime is essential to improve understanding and enable future projections16,17,18. Air temperature, wind speed, cloud cover, precipitation, water density, and lake transparency are all potential variables. We, here, compared the above variables to the turnover timing in Lake Biwa. The meteorological inputs in this study provided data for air temperature, wind speed, cloud cover, and precipitation. Water density and particulate organic carbon (POC) concentration representing lake transparency were the model’s outputs. The annual averages and cold season (November–April) values of the above variables were calculated over the simulation period (Supplementary Fig. S6). Annual averages illustrate general long-term warming trends18, while cold season values particularly determine the timing of turnover17. However, in Lake Biwa, air temperature during the cold season fluctuated greatly compared to the annual averages. A random forest analysis17 has been conducted between the turnover timing and the above two variable sets (cold season values versus annual averages) in Lake Biwa, and the cold season values better explained the turnover timing (35.39% versus 18.48%). The results agree with the conclusion drawn from the previous sensitivity tests, which indicated the relative importance of air temperature and solar radiation during winter based on 40 scenarios32.The importance of variables was estimated based on the random forest analysis using the cold season data (Fig. 4a). Wind speed dominates the timing of turnover, which is consistent with the previous studies17,25. The POC concentration, the difference in water density between the surface and bottom, and cloud cover have moderate effects on the timing of turnover. However, air temperature is less important, which is contrary to the turnover mechanism17,24,32. A re-confirmation was conducted of the relationship between turnover timing and air temperature (Fig. 4b and Supplementary Fig. S7). The cool air generally encourages an early turnover, albeit with several anomalies. The turnover timing between 1976 and 1990 remained constant independent of climate change, and the period coincidently had a substantial nutrient fluctuation (Fig. 3). As a result, it is essential to investigate the nutrient status further.Figure 4Analysis results of the relationship between potential variables and turnover timing: (a) the importance of variables importance using a random forest analysis, and (b) the relationship between the cold season air temperature and the timing of turnover. Variable importance is calculated using the percentage increase in mean square error (MSE) and the increase in node purity. Higher values illustrate the greater importance of the variable. Variables include air temperature (AT), precipitation (pptn.), cloud cover (CC), the difference in density (DD), POC, and wind speed (WS).Full size imageLake nutrient concentrationsBecause phosphorus is the limiting nutrient in Lake Biwa and DIP concentrations can be effectively limited by regulating external loadings as practiced (Fig. 3), DIP concentrations become the focus of this discussion for nutrient status. However, the DIP concentrations disproportionately responded to the external loadings of total phosphorus (TP) in Lake Biwa. Although external TP loading itself fails to determine lake phosphorus concentrations due to the hydrodynamics of lakes33, Lake Biwa exhibited insignificant changes in the inflow rate or the retention time (and see an example of the surface flow in Supplementary Fig. S8). Therefore, it can be assumed that the hydraulic loading remained constant, and the input nutrient concentrations were proportionate to the external nutrient loadings in Lake Biwa. This finding contradicts a recent meta-analysis that highlighted a deterministic relationship between input nutrient concentrations and lake nutrient concentrations, based on steady-state mass balance models6. The possible reason is the dynamics of the lake’s ecosystem22, which have been considered in this study. For example, the surface DIP concentrations were almost nonexistent regardless of the external TP loadings in Lake Biwa, supporting that phosphorus is the limiting nutrient in Lake Biwa34,35. The low DIP concentrations at the surface may be caused by the rapid recycling of phosphorus because the amount of phosphorus available for phytoplankton is easily affected by the feedback mechanism between phytoplankton photosynthesis and the phosphorus released from the water35,36.Hypoxia and strategiesThe variations in DO concentration are the public’s top concern as it relates to hypoxia, a key indicator of water quality. Lake bottom, among all water depths, is more sensitive to small changes in oxygen conditions12. In Lake Biwa, the annual minimum DO concentrations ranged from 2 to 5.5 mg/L over the last 60 years (Supplementary Fig. S9). The decrease in DO concentrations in the early period, typically till the 1980s, was mainly caused by nutrient enrichments (Fig. 3). The nutrient enrichment-induced heavy eutrophication eventually accelerates the rate of DO depletion2. After eutrophication was controlled in the 1980s, climate change became the dominant stressor23. There remains much uncertainty surrounding the relationship between climatic variables-related turnover timing and hypoxia in Lake Biwa12. We, therefore, first investigate the relationship between hypoxia and turnover timing, and then concentrate on nutrients to alleviate hypoxia.Although the relationship between turnover timing and DO concentrations is quite weak (R2 = 0.10), there is a general decrease in DO concentrations with increasing turnover timing (Fig. 5a). On the other hand, a linear relationship has been found between DIP concentrations and DO concentrations, with an R2 of 0.67 (Fig. 5b). The slope of –0.841 μgP/mgDO means an increase in DIP concentrations by approximately 0.841 μgP/L causes a decrease in DO concentrations by 1 mg/L. Note that the simulation results were compared over the whole period, and eutrophication-induced hypoxia differs theoretically from climate-induced hypoxia. Additional testing has been conducted to distinguish the effects of two stressors (eutrophication- and climate-induced hypoxia; Supplementary Fig. S10). Before 1980 when eutrophication progressed, the annual minimum DO concentrations and the DIP concentrations had a stronger linear relationship (R2 = 0.89). Although waste-water treatment has improved conditions in the lake, climate change induced alteration of turnover timing may adversely influence water quality. However, the relationship weakened dramatically with an R2 of 0.10 after 1980, when climate change dominated hypoxia. The lower R2 value indicates that climate-related hypoxia is more complex as concluded previously37,38. The two possibilities are as follows. First, there can be a legacy of hypoxia related to eutrophication. The DO recovery at the bottom of Lake Biwa was complicated by the low DO concentration in 1980 and the delayed timing of turnover; similar phenomena have been observed in the Lake of Zurich22. Second, ecosystem dynamics could help explain the difficulty in predicting hypoxia at the bottom. Phytoplankton fully exploits phosphorus at the surface, as explained above, then the death and sinking of the surface phytoplankton are accompanied by the sedimentation of phosphorus to the bottom as modeled. Bacteria break down the sinking phytoplankton, releasing phosphorus and consuming DO in the process. Additional DO consumption lowers the bottom DO concentration, which in turn encourages phosphorus release from the sediment in a low DO environment22. Such unfavorable feedback between DIP and DO concentrations are strengthened by prolonged stratification and eventually accelerates the development of hypoxia. However, future research is necessary because this numerical model simplified the relationship between water and sediment. The sinking of organic carbon into sediment is integrated in the model, and due to the decomposition of organic carbon in the sediment, nutrients are released into and oxygen is depleted in the water. Despite that, the trends between DO and DIP concentrations stay the same under climate change (Fig. 5b), and thus controlling lake phosphorus is beneficial to the Lake Biwa hypoxia.Figure 5The linear regression results of the relationship: (a) between turnover timing and annual minimum concentration of DO, (b) between the annual minimum concentration of DO and annual average concentration of DIP. The simulation results at the monitoring station were used for analysis.Full size image More

During recent decades, pathogens that originated in bats have become an increasing public health concern. A major challenge is to identify how those pathogens spill over into human populations to generate a pandemic threat1. Many correlational studies associate spillover with changes in land use or other anthropogenic stressors2,3, although the mechanisms underlying the observed correlations have not been identified4. One limitation is the lack of spatially and temporally explicit data on multiple spillovers, and on the connections among spillovers, reservoir host ecology and behavior, and viral dynamics. We present 25 years of data on land-use change, bat behavior, and spillover of Hendra virus from Pteropodid bats to horses in subtropical Australia. These data show that bats are responding to environmental change by persistently adopting behaviors that were previously transient responses to nutritional stress. Interactions between land-use change and climate now lead to persistent bat residency in agricultural areas, where periodic food shortages drive clusters of spillovers. Pulses of winter flowering of trees in remnant forests appeared to prevent spillover. We developed integrative Bayesian network models based on these phenomena that accurately predicted the presence or absence of clusters of spillovers in each of 25 years. Our long-term study identifies the mechanistic connections among habitat loss, climate, and increased spillover risk. It provides a framework for examining causes of bat virus spillover and for developing ecological countermeasures to prevent pandemics. More

Ringø, E. et al. Probiotics, lactic acid bacteria and bacilli: Interesting supplementation for aquaculture. J. Appl. Microbiol. 129, 116–136 (2020).PubMed 

Google Scholar 
Borges, N. et al. Bacteriome structure, function, and probiotics in fish larviculture: The good, the bad, and the gaps. Annu. Rev. Anim. Biosci. 9, 423–452 (2021).CAS 
PubMed 

Google Scholar 
Aguilar-Toalá, J. E. et al. Postbiotics: An evolving term within the functional foods field. Trends Food Sci. Technol. 75, 105–114 (2018).
Google Scholar 
Salminen, S. et al. The International Scientific Association of Probiotics and Prebiotics (ISAPP) consensus statement on the definition and scope of postbiotics. Nat. Rev. Gastroenterol. Hepatol. 18, 649–667 (2021).PubMed 
PubMed Central 

Google Scholar 
Dash, G. et al. Evaluation of paraprobiotic applicability of Lactobacillus plantarum in improving the immune response and disease protection in giant freshwater prawn, Macrobrachium rosenbergii (de Man, 1879). Fish Shellf. Immunol. 43, 167–174 (2015).CAS 

Google Scholar 
Dawood, M. A. O., Koshio, S., Ishikawa, M. & Yokoyama, S. Effects of partial substitution of fish meal by soybean meal with or without heat-killed Lactobacillus plantarum (LP20) on growth performance, digestibility, and immune response of Amberjack, Seriola dumerili Juveniles. Biomed. Res. Int. 2015, 514196 (2015).PubMed 
PubMed Central 

Google Scholar 
Dawood, M. A. O., Koshio, S., Ishikawa, M. & Yokoyama, S. Immune responses and stress resistance in red sea bream, Pagrus major, after oral administration of heat-killed Lactobacillus plantarum and vitamin C. Fish Shellf. Immunol. 54, 266–275 (2016).CAS 

Google Scholar 
Dawood, M. A. O., Koshio, S., Ishikawa, M. & Yokoyama, S. Interaction effects of dietary supplementation of heat-killed Lactobacillus plantarum and β-glucan on growth performance, digestibility and immune response of juvenile red sea bream, Pagrus major. Fish Shellf. Immunol. 45, 33–42 (2015).CAS 

Google Scholar 
Tung, H. T. et al. Effects of heat-killed Lactobacillus plantarum supplemental diets on growth performance, stress resistance and immune response of juvenile Kuruma shrimp Marsupenaeus japonicus bate. Aquac. Sci. 57, 175–184 (2009).CAS 

Google Scholar 
Van Nguyen, N. et al. Evaluation of dietary heat-killed Lactobacillus plantarum strain L-137 supplementation on growth performance, immunity and stress resistance of Nile tilapia (Oreochromis niloticus). Aquaculture 498, 371–379 (2019).
Google Scholar 
Yang, H. et al. Effects of dietary heat-killed Lactobacillus plantarum L-137 (HK L-137) on the growth performance, digestive enzymes and selected non-specific immune responses in sea cucumber, Apostichopus japonicus Selenka. Aquac. Res. 47, 2814–2824 (2016).CAS 

Google Scholar 
Singh, S. T., Kamilya, D., Kheti, B., Bordoloi, B. & Parhi, J. Paraprobiotic preparation from Bacillus amyloliquefaciens FPTB16 modulates immune response and immune relevant gene expression in Catla catla (Hamilton, 1822). Fish Shelf. Immunol. 66, 35–42 (2017).CAS 

Google Scholar 
Kamilya, D., Baruah, A., Sangma, T., Chowdhury, S. & Pal, P. Inactivated probiotic bacteria stimulate cellular immune responses of catla, Catla catla (Hamilton) in vitro. Probiot. Antimicrob. Proteins 7, 101–106 (2015).CAS 

Google Scholar 
Wang, J. et al. Supplementation of heat-inactivated Bacillus clausii DE 5 in diets for grouper, Epinephelus coioides, improves feed utilization, intestinal and systemic immune responses and not growth performance. Aquac. Nutr. 24, 821–831 (2018).CAS 

Google Scholar 
Giri, S. S. et al. Effects of dietary heat-killed Pseudomonas aeruginosa strain VSG2 on immune functions, antioxidant efficacy, and disease resistance in Cyprinus carpio. Aquaculture 514, 734489 (2020).CAS 

Google Scholar 
Shabanzadeh, S. et al. Growth performance, intestinal histology, and biochemical parameters of rainbow trout (Oncorhynchus mykiss) in response to dietary inclusion of heat-killed Gordonia bronchialis. Fish Physiol. Biochem. 42, 65–71 (2016).CAS 
PubMed 

Google Scholar 
Wu, X. et al. Use of a paraprobiotic and postbiotic feed supplement (HWF™) improves the growth performance, composition and function of gut microbiota in hybrid sturgeon (Acipenser baerii × Acipenser schrenckii). Fish Shelf. Immunol. 104, 36–45 (2020).CAS 

Google Scholar 
Mora-Sánchez, B., Balcázar, J. L. & Pérez-Sánchez, T. Effect of a novel postbiotic containing lactic acid bacteria on the intestinal microbiota and disease resistance of rainbow trout (Oncorhynchus mykiss). Biotechnol. Lett. 42, 1957–1962 (2020).PubMed 

Google Scholar 
Xiong, J. et al. The temporal scaling of bacterioplankton composition: High turnover and predictability during shrimp cultivation. Microb. Ecol. 67, 256–264 (2014).PubMed 

Google Scholar 
Martins, P. et al. Seasonal patterns of bacterioplankton composition in a semi-intensive European seabass (Dicentrarchus labrax) aquaculture system. Aquaculture 490, 240–250 (2018).
Google Scholar 
Offret, C. et al. Protective efficacy of a Pseudoalteromonas strain in European abalone, Haliotis tuberculata, infected with Vibrio harveyi ORM4. Probiot. Antimicrob. Proteins 11, 239–247 (2019).
Google Scholar 
Richards, G. P. et al. Mechanisms for Pseudoalteromonas piscicida-induced killing of vibrios and other bacterial pathogens. Appl. Environ. Microbiol. 83, e00175-e217 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
Lin, S.-R., Chen, Y.-H., Tseng, F.-J. & Weng, C.-F. The production and bioactivity of prodigiosin: Quo vadis?. Drug Discov. Today 25, 828–836 (2020).CAS 
PubMed 

Google Scholar 
Vynne, N. G., Månsson, M., Nielsen, K. F. & Gram, L. Bioactivity, chemical profiling, and 16S rRNA-based phylogeny of Pseudoalteromonas strains collected on a global research cruise. Mar. Biotechnol. 13, 1062–1073 (2011).CAS 

Google Scholar 
Lovejoy, C., Bowman, J. P. & Hallegraeff, G. M. Algicidal effects of a novel marine Pseudoalteromonas isolate (class Proteobacteria, gamma subdivision) on harmful algal bloom species of the genera Chattonella, Gymnodinium, and Heterosigma. Appl. Environ. Microbiol. 64, 2806–2813 (1998).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Franks, A. et al. Inhibition of fungal colonization by Pseudoalteromonas tunicata provides a competitive advantage during surface colonization. Appl. Environ. Microbiol. 72, 6079–6087 (2006).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Hjelm, M. et al. Selection and identification of autochthonous potential probiotic bacteria from turbot larvae (Scophthalmus maximus) rearing units. Syst. Appl. Microbiol. 27, 360–371 (2004).PubMed 

Google Scholar 
Sorieul, L. et al. Survival improvement conferred by the Pseudoalteromonas sp. NC201 probiotic in Litopenaeus stylirostris exposed to Vibrio nigripulchritudo infection and salinity stress. Aquaculture 495, 888–898 (2018).
Google Scholar 
Pruitt, K. D., Tatusova, T. & Maglott, D. R. NCBI reference sequence (RefSeq): A curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic Acids Res. 33, D501–D504 (2005).CAS 
PubMed 

Google Scholar 
Yan, Y.-Y., Xia, H.-Q., Yang, H.-L., Hoseinifar, S. H. & Sun, Y.-Z. Effects of dietary live or heat-inactivated autochthonous Bacillus pumilus SE5 on growth performance, immune responses and immune gene expression in grouper Epinephelus coioides. Aquac. Nutr. 22, 698–707 (2016).CAS 

Google Scholar 
Louvado, A. et al. Humic substances modulate fish bacterial communities in a marine recirculating aquaculture system. Aquaculture 544, 737121 (2021).CAS 

Google Scholar 
Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 1, 5 (2019).
Google Scholar 
Callahan, B. J. et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
Bokulich, N. A. et al. Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome 6, 1–17 (2018).
Google Scholar 
Oksanen, J. et al. vegan: Community Ecology Package. R package version 2.5-6. 2019. (2020).R. Core Team. R: A Language and Environment for Statistical Computing (Version 2120) (R Foundation for Statistical Computing, 2012).
Google Scholar 
McMurdie, P. J. & Holmes, S. phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One 8, e61217 (2013).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Wemheuer, F. et al. Tax4Fun2: Prediction of habitat-specific functional profiles and functional redundancy based on 16S rRNA gene sequences. Environ. Microbiome 15, 11 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
Setiyono, E. et al. An Indonesian marine bacterium, Pseudoalteromonas rubra, produces antimicrobial prodiginine pigments. ACS Omega 5, 4626–4635 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
Buchan, A., LeCleir, G. R., Gulvik, C. A. & González, J. M. Master recyclers: Features and functions of bacteria associated with phytoplankton blooms. Nat. Rev. Microbiol. 12, 686–698 (2014).CAS 
PubMed 

Google Scholar 
Bakenhus, I. et al. Composition of total and cell-proliferating bacterioplankton community in early summer in the North Sea—roseobacters are the most active component. Front. Microbiol. 8, 1771 (2017).PubMed 
PubMed Central 

Google Scholar 
Sieber, C. M. K. et al. Unusual metabolism and hypervariation in the genome of a gracilibacterium (BD1-5) from an oil-degrading community. MBio 10, e02128-e2219 (2022).
Google Scholar 
Jaffe, A. L., Castelle, C. J., Matheus Carnevali, P. B., Gribaldo, S. & Banfield, J. F. The rise of diversity in metabolic platforms across the Candidate Phyla Radiation. BMC Biol. 18, 69 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
Williams, H. N. & Piñeiro, S. Ecology of the predatory Bdellovibrio and like organisms. In Predatory Prokaryotes 213–248 (Springer, 2006).
Google Scholar 
Johnke, J. et al. Multiple micro-predators controlling bacterial communities in the environment. Curr. Opin. Biotechnol. 27, 185–190 (2014).CAS 
PubMed 

Google Scholar 
Rice, T. D., Williams, H. N. & Turng, B.-F. Susceptibility of bacteria in estuarine environments to autochthonous bdellovibrios. Microb. Ecol. 35, 256–264 (1998).CAS 
PubMed 

Google Scholar 
Feng, S. et al. Predation by Bdellovibrio bacteriovorus significantly reduces viability and alters the microbial community composition of activated sludge flocs and granules. FEMS Microbiol. Ecol. 93, fix020 (2017).
Google Scholar 
Duarte, L. N. et al. Bacterial and microeukaryotic plankton communities in a semi-intensive aquaculture system of sea bass (Dicentrarchus labrax): A seasonal survey. Aquaculture 503, 59–69 (2019).
Google Scholar 
Hu, L. et al. Reclassification of the taxonomic framework of orders cellvibrionales, oceanospirillales, pseudomonadales, and alteromonadales in class gammaproteobacteria through phylogenomic tree analysis. mSystems 5, e00543-e620 (2021).
Google Scholar 
Garrity, G. M., Bell, J. A. & Lilburn, T. Oceanospirillalesord. Nov. in Bergey’s Manual® of Systematic Bacteriology 270–323 (Springer, 2005).
Google Scholar 
Thomas, F., Hehemann, J.-H., Rebuffet, E., Czjzek, M. & Michel, G. Environmental and gut bacteroidetes: The food connection. Front. Microbiol. 2, 93 (2011).PubMed 
PubMed Central 

Google Scholar 
Rajilić-Stojanović, M. & De Vos, W. M. The first 1000 cultured species of the human gastrointestinal microbiota. FEMS Microbiol. Rev. 38, 996–1047 (2014).PubMed 

Google Scholar 
Rosenberg, E. The family Chitinophagaceae. In The Prokaryotes: Other Major Lineages of Bacteria and The Archaea (eds Rosenberg, E. et al.) (Springer, 2014).
Google Scholar 
Beckmann, A., Hüttel, S., Schmitt, V., Müller, R. & Stadler, M. Optimization of the biotechnological production of a novel class of anti-MRSA antibiotics from Chitinophaga sancti. Microb. Cell Fact. 16, 1–10 (2017).
Google Scholar 
Loudon, A. H. et al. Interactions between amphibians’ symbiotic bacteria cause the production of emergent anti-fungal metabolites. Front. Microbiol. 5, 441 (2014).PubMed 
PubMed Central 

Google Scholar 
Taylor, J. D. & Cunliffe, M. Coastal bacterioplankton community response to diatom-derived polysaccharide microgels. Environ. Microbiol. Rep. 9, 151–157 (2017).CAS 
PubMed 

Google Scholar 
González, J. M. & Whitman, W. B. Oceanospirillum and related genera. In The Prokaryotes: A Handbook on the Biology of Bacteria Volume 6: Proteobacteria: Gamma Subclass (eds Dworkin, M. et al.) 887–915 (Springer, 2006).
Google Scholar 
Kleindienst, S., Paul, J. H. & Joye, S. B. Using dispersants after oil spills: Impacts on the composition and activity of microbial communities. Nat. Rev. Microbiol. 13, 388–396 (2015).CAS 
PubMed 

Google Scholar 
Williams, T. J. et al. The role of planktonic Flavobacteria in processing algal organic matter in coastal East Antarctica revealed using metagenomics and metaproteomics. Environ. Microbiol. 15, 1302–1317 (2013).CAS 
PubMed 

Google Scholar 
Gobet, A. et al. Evolutionary evidence of algal polysaccharide degradation acquisition by Pseudoalteromonas carrageenovora 9T to adapt to macroalgal niches. Front. Microbiol. 10, 2740 (2018).
Google Scholar 
Beier, S., Rivers, A. R., Moran, M. A. & Obernosterer, I. The transcriptional response of prokaryotes to phytoplankton-derived dissolved organic matter in seawater. Environ. Microbiol. 17, 3466–3480 (2015).CAS 
PubMed 

Google Scholar 
Müller, O., Seuthe, L., Bratbak, G. & Paulsen, M. L. Bacterial response to permafrost derived organic matter input in an Arctic fjord. Front. Mar. Sci. 5, 263 (2018).
Google Scholar 
Fernández-Álvarez, C. & Santos, Y. Identification and typing of fish pathogenic species of the genus Tenacibaculum. Appl. Microbiol. Biotechnol. 102, 9973–9989 (2018).PubMed 

Google Scholar 
Wirth, J. S. & Whitman, W. B. Phylogenomic analyses of a clade within the roseobacter group suggest taxonomic reassignments of species of the genera Aestuariivita, Citreicella, Loktanella, Nautella, Pelagibaca, Ruegeria, Thalassobius, Thiobacimonas and Tropicibacter, and the proposal. Int. J. Syst. Evol. Microbiol. 68, 2393–2411 (2018).CAS 
PubMed 

Google Scholar 
Luo, H. & Moran, M. A. Evolutionary ecology of the marine Roseobacter clade. Microbiol. Mol. Biol. Rev. 78, 573–587 (2014).PubMed 
PubMed Central 

Google Scholar 
Shahina, M. et al. Luteibaculum oceani gen. nov., sp. Nov., a carotenoid-producing, lipolytic bacterium isolated from surface seawater, and emended description of the genus Owenweeksia Lau et al. 2005. Int. J. Syst. Evol. Microbiol. 63, 4765–4770 (2013).CAS 
PubMed 

Google Scholar 
Davidov, Y. & Jurkevitch, E. Diversity and evolution of Bdellovibrio-and-like organisms (BALOs), reclassification of Bacteriovorax starrii as Peredibacter starrii gen. nov., comb. nov., and description of the Bacteriovorax–Peredibacter clade as Bacteriovoracaceae fam. nov. Int. J. Syst. Evol. Microbiol. 54, 1439–1452 (2004).CAS 
PubMed 

Google Scholar 
Müller, F. D., Beck, S., Strauch, E. & Linscheid, M. W. Bacterial predators possess unique membrane lipid structures. Lipids 46, 1129–1140 (2011).PubMed 

Google Scholar 
Kandel, P. P., Pasternak, Z., van Rijn, J., Nahum, O. & Jurkevitch, E. Abundance, diversity and seasonal dynamics of predatory bacteria in aquaculture zero discharge systems. FEMS Microbiol. Ecol. 89, 149–161 (2014).CAS 
PubMed 

Google Scholar 
Cao, H., Wang, H., Yu, J., An, J. & Chen, J. Encapsulated bdellovibrio powder as a potential bio-disinfectant against whiteleg shrimp-pathogenic vibrios. Microorganisms 7, 25 (2019).
Google Scholar 
Jafarian, N., Sepahi, A. A., Naghavi, N. S., Hosseini, F. & Nowroozi, J. Using autochthonous Bdellovibrio as a predatory bacterium for reduction of Gram-negative pathogenic bacteria in urban wastewater and reuse it. Iran. J. Microbiol. 12, 556–564 (2020).PubMed 
PubMed Central 

Google Scholar 
Cosgrove, L., McGeechan, P. L., Handley, P. S. & Robson, G. D. Effect of biostimulation and bioaugmentation on degradation of polyurethane buried in soil. Appl. Environ. Microbiol. 76, 810–819 (2010).ADS 
CAS 
PubMed 

Google Scholar 
Cruz, A. et al. Microbial remediation of organometals and oil hydrocarbons in the marine environment. In Marine Pollution and Microbial Remediation 41–66 (Springer, 2017).
Google Scholar 
Zhao, J., Chen, M., Quan, C. S. & Fan, S. D. Mechanisms of quorum sensing and strategies for quorum sensing disruption in aquaculture pathogens. J. Fish Dis. 38, 771–786 (2015).CAS 
PubMed 

Google Scholar 
Tyc, O., Song, C., Dickschat, J. S., Vos, M. & Garbeva, P. The ecological role of volatile and soluble secondary metabolites produced by soil bacteria. Trends Microbiol. 25, 280–292 (2017).CAS 
PubMed 

Google Scholar  More

These authors contributed equally: Yannick Garcin, Enno Schefuß, Greta C. Dargie, Simon L. LewisAix Marseille University, CNRS, IRD, INRAE, CEREGE, Aix-en-Provence, FranceYannick Garcin & Ghislain GassierInstitute of Geosciences, University of Potsdam, Potsdam, GermanyYannick GarcinMARUM—Center for Marine Environmental Sciences, University of Bremen, Bremen, GermanyEnno SchefußSchool of Geography, University of Leeds, Leeds, UKGreta C. Dargie, Bart Crezee, Dylan M. Young, Andy J. Baird, Paul J. Morris & Simon L. LewisSchool of Geography and Sustainable Development, University of St Andrews, St Andrews, UKDonna Hawthorne, Ian T. Lawson & George E. BiddulphIFP Energies Nouvelles, Earth Sciences and Environmental Technologies Division, Rueil-Malmaison, FranceDavid SebagInstitute of Earth Surface Dynamics, Geopolis, University of Lausanne, Lausanne, SwitzerlandDavid SebagFaculté des Sciences et Techniques, Université Marien Ngouabi, Brazzaville, Republic of the CongoYannick E. Bocko & Y. Emmanuel Mampouya WeninaÉcole Normale Supérieure, Université Marien Ngouabi, Brazzaville, Republic of the CongoSuspense A. IfoÉcole Normale Supérieure d’Agronomie et de Foresterie, Université Marien Ngouabi, Brazzaville, Republic of the CongoMackline MbembaFaculté de Gestion des Ressources Naturelles Renouvelables, Université de Kisangani, Kisangani, Democratic Republic of the CongoCorneille E. N. Ewango & Joseph Kanyama TabuFaculté des Sciences, Université de Kisangani, Kisangani, Democratic Republic of the CongoCorneille E. N. EwangoInstitut Supérieur Pédagogique de Mbandaka, Mbandaka, Democratic Republic of the CongoOvide Emba & Pierre BolaSchool of Geography, Geology and the Environment, University of Leicester, Leicester, UKGenevieve Tyrrell, Arnoud Boom & Susan E. PageSchool of Water, Energy and Environment, Cranfield University, Bedford, UKNicholas T. GirkinBritish Geological Survey, Centre for Environmental Geochemistry, Keyworth, UKChristopher H. VaneInstitute of Earth Sciences, University of Lausanne, Lausanne, SwitzerlandThierry AdatteNEIF Radiocarbon Laboratory, Scottish Universities Environmental Research Centre (SUERC), Glasgow, UKPauline GulliverSchool of Biosciences, University of Nottingham, Nottingham, UKSofie SjögerstenDepartment of Geography, University College London, London, UKSimon L. Lewis More

We aimed to understand the impact of changing pCO2 (400 vs. 800 ppm, representing current and projected year 2100 concentrations) on Prochlorococcus and Synechococcus and its effects on their interactions with the co-cultured heterotrophic “helper” bacterium Alteromonas sp. EZ55. Consistent with our previous research [7], EZ55 was more strongly affected by year 2100 pCO2 than any of the photoautotrophs in our study despite the primary dependence of the latter organisms’ metabolism on CO2. Strikingly, elevated pCO2 tended to reduce or eliminate the effect of co-culture on EZ55, with far fewer genes being significantly differentially transcribed relative to axenic EZ55 at the same pCO2. Thus, pCO2 strongly impacted the metabolic conversation between cyanobacteria and EZ55. Our detailed analysis of differentially regulated metabolic pathways suggested three mutually reinforcing mechanisms underlying this dynamic interaction: (i) pCO2 impacts on the release of ‘leaky’ cyanobacteria-derived metabolites, (ii) alteration of the dynamics of competition over inorganic nutrients between the co-cultured organisms, and (iii) modulation of bacterial and phytoplankton stress states. We explore each of these mechanisms in further detail below.Carbon cycling of “leaky” metabolites in co-cultureThe media we used for coculturing phytoplankton and bacteria contained no exogenous carbon sources; therefore, EZ55 was dependent on cyanobacterial exudates to grow, and it is likely that much of its changed transcription reflected changing availability of extracellular metabolites in the medium. The significant upregulation of carbon catabolism and transport genes as well as chemotaxis genes in co-cultures relative to axenic EZ55 supports the view that bacterial remineralization of cyanobacteria-secreted organic compounds is a driving force in these simple ecosystems. Additionally, changes in transcription of carbohydrate catabolism and transport genes provide clues as to which metabolites were being secreted under different experimental conditions (Fig. 5).Fig. 5: Proposed reconstruction of Alteromonas EZ55 ecophysiology.Reconstructions are shown for four different community contexts (axenic culture, or co-culture with Prochlorococcus MIT9312, Synechococcus WH8102, or Synechococcus CC9311) at 400 or 800 ppm pCO2, reflecting possible changes in the availability of C compounds, growth limiting factors, and stress conditions consistent with differential gene transcription observations. EZ55 image was obtained by cryoelectron microscopy from the sessions reported in Hennon et al. [7]. Background colors for each partner correspond to the bar colors in Fig. 3.Full size imageLike all oxygenic phototrophs, the cyanobacteria studied here fix carbon using the enzyme rubisco, which also catalyzes the undesirable photorespiration reaction leading to the production of 2PG instead of photosynthate. Phytoplankton in the field and in culture have been observed to excrete low molecular weight carboxylic acids including glycolate [39,40,41]. Photorespiratory glycolate is one of the most abundant sources of carbon in the oceans [38] and a preferred growth substrate for some marine heterotrophic bacteria [42]. Moreover the bacterial glcD gene for converting glycolate to glyoxylate is ubiquitously transcribed in the ocean [41, 43]. Although EZ55 lacks a specific transporter for glycolate, it can be taken up by the cell using the same transporters used for acetate and lactate uptake [44, 45], both of which were upregulated in co-culture conditions at 400 ppm (Fig. 3). Our data also showed differential regulation of enzymes involved in glycolate catabolism pathways, with at least one pathway upregulated in co-culture with each cyanobacterial strain (Fig. 3). We further demonstrated that EZ55 cultures were capable of growth on glycolate as a sole source of carbon, possibly using a novel GlcDF fusion protein (Fig. S11) and/or a plant-like LOX/GOX enzyme (Fig. 4). Thus, photorespiratory byproducts are likely a source of carbon for EZ55 in these cultures, particularly in the presence of MIT9312, which has no detectable enzymes for reclaiming 2PG on its own.There was also evidence that EZ55 utilized amino acids, organic acids, and fatty acids produced by phytoplankton under certain conditions in these cultures (Fig. S9). Lactate, acetate, and propanoate transporters and catabolism pathways were upregulated in co-culture with all cyanobacteria, as was pyruvate dehydrogenase with MIT9312, but only at 400 ppm. Both valine and glycine catabolism were also upregulated at 400 ppm in co-culture with the two Synechococcus strains, and fatty acid catabolism was upregulated in co-culture with MIT9312 and CC9311 at 400 ppm pCO2. Most of these substances have been directly or indirectly observed in cyanobacterial cultures in previous studies. For example, glycolate, lactate, acetate, and pyruvate have been directly measured in Prochlorococcus spent media [39], and co-culture with Prochlorococcus can fulfill the SAR11 growth requirement for glycine and pyruvate [46]. Fatty acid catabolism genes may have targeted membrane vesicles which are abundantly released by Prochlorococcus and other marine bacteria and may be a significant source of carbon for heterotrophs in the ocean [47, 48]; if so, future studies should investigate if WH8102 produces fewer vesicles than the other two cyanobacteria, explaining the differential transcription of beta-oxidation genes observed here.Valine, fatty acid, and propanoate catabolic pathways intersect with the formation of propanoyl-coA which in bacteria is generally fed into the TCA cycle through the methylcitrate pathway [49], which was significantly downregulated at 400 ppm in co-culture with all cyanobacteria even though other genes in these pathways were upregulated. Therefore, it is not clear what the ultimate fate of carbon from these sources is, although it is possible that EZ55 may be able to convert propanoyl-coA into a TCA cycle intermediate through another alternative pathway (e.g. as has been described in Mycobacterium tuberculosis via the methylmalonyl pathway [50]).Notably, gene transcription related to the utilization of all these products declined at 800 ppm pCO2 (Figs. 3, S8, S9). This was not unexpected for enzymes in the glycolate utilization pathways, as the increased CO2/O2 ratio at 800 ppm should decrease the rate of photorespiration relative to carbon fixation and therefore the availability of photorespiratory metabolites like glycolate [51, 52]. It is not clear, however, why organic and fatty acids would be less abundant in cyanobacterial exudates at 800 ppm. One possibility is that cyanobacteria release fewer of these compounds into the medium at high pCO2 because of a change in their internal redox state under these conditions favoring full oxidation of photosynthate. If future pCO2 conditions fundamentally alter the character of phytoplankton exudates, this could have profound implications for evolution and ecosystem functioning in future oceans.Evidence for inorganic nutrient limitation and competitionAutotrophic cyanobacteria and heterotrophic EZ55 were unlikely to compete over carbon under our experimental conditions, but we observed evidence of competition over inorganic nutrients such as N, P, and Fe. EZ55 phosphate, ammonium, and iron transporters, nitrogen regulatory protein P-II, and glutamine synthetase (the primary gateway for N assimilation in bacteria) were all more highly transcribed for all co-cultures compared to axenic cultures at 400 ppm pCO2 (Fig. S6), suggesting a switch from axenic carbon limitation to nutrient limitation in the presence of a continual supply of photosynthetically derived carbon (Fig. 5). On the other hand, few nutrient transporters were upregulated compared to axenic under 800 ppm pCO2. Although gene transcription data alone is not sufficient to conclude whether Alteromonas is limited by inorganic or organic nutrients, the reduced importance of nutrient acquisition suggests that EZ55 is carbon limited under these conditions just as it is in the absence of cyanobacteria.There were comparatively few species-specific changes in EZ55 nutrient transporter gene transcription. One example was an ammonium transporter, which was strongly upregulated in co-culture with both open ocean cyanobacteria (MIT9312 and WH8102) at 400 ppm pCO2. This may reflect a response to a comparatively high affinity for N in cyanobacteria adapted to the permanently oligotrophic open ocean, making them much stronger competitors for limiting N than coastal CC9311. N competition with EZ55 has been observed to increase the relative competitive fitness of Prochlorococcus vs. Synechococcus (coastal strain WH7803) in 3-way co-cultures [53]. In contrast, WH8102 appears to have higher N demand under 800 ppm pCO2, significantly upregulating a nitrate transporter and several genes related to urea utilization (Fig. S2). This may be explained by the enhanced transcription of carbon fixation genes and faster exponential growth rates observed in WH8102 at elevated pCO2, increasing N demand, and may indicate that WH8102 was C limited at 400 ppm.It is important to note that different N sources were provided in PEv medium (in which axenic EZ55 and MIT9312 co-cultures were grown) and SEv medium (in which CC9311 and WH8102 co-cultures were grown), with NH4+ in the former and NO3- in the latter. However, we do not think this difference can explain the observed changes in gene regulation, since EZ55 is capable of growth using either N source. It is interesting to note, however, that EZ55’s ammonium transporter was upregulated in both media types (Fig. S6), suggesting it may be benefitting from ammonium excreted by Synechococcus in SEv co-cultures.Impacts of co-culture and pCO2 on stress conditionsEZ55 showed less transcription of stress-related genes at 400 than 800 ppm pCO2, and also less evidence of stress in co-culture with any cyanobacterium than in axenic culture by itself. Nearly every gene in the EZ55 genome related to protection from H2O2 was downregulated in co-culture at 400 ppm, as were a suite of other stress-related genes (Fig. 2); on the other hand, many of these genes were significantly upregulated relative to axenic conditions at 800 ppm. Additionally, at 800 ppm there was a pronounced difference in EZ55 H2O2 defense gene transcription between cyanobacterial partners. As we described previously [7], both monofunctional catalases were downregulated at 800 ppm in co-culture with MIT9312, as were 2 of 3 alkylhydroperoxide reductase genes (although the third was significantly upregulated). In contrast, the monofunctional catalase genes were significantly upregulated in co-culture with WH8102 at 800 ppm. Elevated transcription of genes involved in the biosynthesis of glycine betaine, an osmoprotectant which has also been shown to function as an antioxidant [54, 55], provides further evidence for increased oxidative stress in co-culture with Synechococcus at 800 ppm in EZ55.Some indication of the mechanism behind EZ55’s changing stress level under co-culture and elevated pCO2 can be seen in the dynamics of three stress-related RNA polymerase sigma factors. Both rpoE and rpoH, responsible for controlling envelope and heat stress regulons, respectively, were downregulated at 400 ppm in co-culture relative to axenic and 800 ppm conditions; rpoE was significantly upregulated at 800 ppm pCO2. These trends are consistent with starvation-induced oxidative stress under both axenic and 800 ppm conditions, as discussed above. In contrast, rpoS was upregulated at 400 ppm pCO2, strongly so in co-culture with MIT9312. RpoS is a specialized sigma factor that accumulates under conditions of nutrient deprivation or as cells enter the stationary phase and serves to increase general stress resistance [56, 57]. For example, in Escherichia coli RpoS was shown to play a crucial role for survival during nitrogen deprivation [58]. While the decoupling of the transcription of oxidative stress genes like catalase from rpoS transcription was unexpected, rpoS trends are consistent with EZ55 being nutrient limited at 400 ppm pCO2 (Fig. S6) and with the upregulation of catalase in co-culture with MIT9312, but not WH8102 or CC9311, at 400 ppm (Fig. 2).In contrast to EZ55, differentially transcribed genes related to stress responses were rare in cyanobacteria at 800 ppm. While both MIT9312 and WH8102 had significant growth impairments at 800 ppm (Fig. S1), there was little evidence of a stress-specific gene transcription response in either strain. DNA mismatch repair genes were enriched as a group at 800 ppm in Prochlorococcus, although the only individual stress-related protein that was differentially transcribed was a HLI protein that was strongly downregulated at 800 ppm. No stress-related genes or gene sets were enriched in WH8102, and the small number of differentially transcribed stress genes in CC9311 (e.g., heat-shock and HLI proteins) were all downregulated at 800 ppm. This could indicate a dependence of both MIT9312 and WH8102 on their co-cultured EZ55 partner for protection, as neither of these cyanobacterial genomes contains catalase or several other stress-response genes common in heterotrophic bacteria. It could also indicate that they have different stress response mechanisms than those that have been characterized in heterotrophic bacteria; for instance, several hypothetical proteins of unknown function were differentially regulated in each cyanobacterium between the pCO2 conditions. Finally, it is possible that the stresses experienced by MIT9312 and WH8102 occurred in the initial days after transfer into fresh media (i.e., the significantly extended lag period observed for both), and were alleviated by the late log phase when the cultures were sampled for RNA sequencing.Summary overview of metabolic responsesWe have shown that the response to elevated pCO2 in our algal:bacterial co-cultures was driven more by interspecies interactions than by CO2-specific responses themselves. While it is important to note that we do not have direct culture-based evidence for some of these claims, we feel that gene transcription evidence is strong for several conclusions regarding the interactions in our cultures (Fig. 5).First, increased pCO2 appears to have fundamentally altered the amount and/or types of carbon compounds secreted by all three cyanobacterial strains examined, placing EZ55 into a stationary-phase metabolic state nearly indistinguishable to being in culture media with no added carbon source at all. We suggest that this is driven directly by the higher CO2:O2 ratio, which lowered the rate of photorespiration and subsequent release of 2PG and/or glycolate and indirectly may have reduced the amount of incompletely oxidized carbon released by cyanobacteria by changing the intracellular redox state [59]. Possibly because of the changing supply of carbon, EZ55 also appeared to transition away from a state of nutrient competition with its cyanobacterial partners, exemplified by decreased transcription of nutrient transporters at elevated pCO2 (Fig. S6).Second, co-culture at 400 ppm clearly reduced stress on EZ55 relative to either axenic growth or co-culture growth at 800 ppm, possibly due to the provision of a more reliable source of C as described above by the cyanobacterial partner under these conditions. In contrast, both MIT9312 and WH8102 clearly experienced elevated stress, potentially related to the changes in EZ55’s metabolism under these conditions. One of the major conclusions from our previous work [7] was the finding that EZ55 reduced catalase transcription at 800 ppm pCO2, eliminating the “helper” effect that Prochlorococcus depends on to grow in culture [13, 14]. In this work we see that the catalase response in co-culture with MIT9312 was opposite that in co-culture with the two Synechococcus strains. One possible explanation for this lies in the fact that MIT9312, unlike the other three strains in this study, did not possess a complete 2PG catabolism pathway and therefore likely excreted this product where it was subsequently catabolized by EZ55. We confirmed by genomic analysis (Figs. S10–S13) and culture experiments (Fig. 4) that EZ55 was able to grow on glycolate as a sole carbon source, and that its intracellular H2O2 concentration was elevated compared to growth on glucose. We suggest that more 2PG was secreted by MIT9312 at 400 ppm pCO2 due to the lower CO2:O2 ratio, and that growth on this carbon source increased EZ55’s internal oxidative stress load, resulting in higher transcription of H2O2 defenses such as catalase (Fig. 2). If true, this provides one possible explanation of why the “helper” relationship broke down at elevated pCO2 – by leaking 2PG as a readily available growth substrate for EZ55 at 400 ppm, MIT9312 forced EZ55 to maintain a high degree of intracellular ROS defense, leading to the well-characterized ability of EZ55 to cross-protect Prochlorococcus strains from the relatively lower H2O2 concentrations in the bulk environment, and allowing MIT9312 to eliminate two energetically costly enzymatic pathways. When higher pCO2 reduced the rate of photorespiration, EZ55’s need to produce excess catalase decreased, resulting in lower levels of protection, and concomitant growth impairments, for MIT9312.This is an example of how leaky Black Queen functions allow organisms like Prochlorococcus to streamline their metabolism while simultaneously creating stable interdependencies within their communities. However, it also shows how Black Queen-stabilized exchanges can break down. If our hypothesized relationship between pCO2 and catalase production is correct, then this system depends on the passive release of a metabolic by-product that evolved under a set of atmospheric pCO2 conditions that have been largely stable for thousands of years – but this leaves the system particularly vulnerable to the rapid changes in pCO2 currently taking place and may leave Prochlorococcus with no protection at all in the future ocean. If Prochlorococcus is outcompeted by less-streamlined competitors, this could reduce the overall efficiency of primary production in the open ocean gyres with possible positive feedbacks on CO2 accumulation in the atmosphere. Subsequent experiments should examine whether Prochlorococcus can overcome this imbalance through adaptive evolution quickly enough to avoid serious disruptions of its current niche.In conclusion, these results provide further support for the observation that axenic cultures do not provide a good window into the behavior of natural communities. The metabolism of Alteromonas sp. EZ55, a ubiquitous consumer in the ocean, was strongly dependent on its community context, and relatively subtle shifts in the chemical environment induced by elevated pCO2 were sufficient to significantly remodel its physiology. Moreover, the transcriptional response of EZ55 to changing pCO2 was much greater than that of any of the photoautotrophs examined, suggesting that more work is needed to understand the often-ignored heterotrophic bacteria associated with marine primary producers and how they will respond to global ocean change. Thus, further research is indicated on some of our core findings and hypotheses (e.g., the role of 2PG, and the nature of the carbon exchanged between the cyanobacteria and Alteromonas) via metabolomics or direct substrate measurements. These results further highlight the importance of laboratory experiments using co-cultures as an experimentally tractable intermediate between oversimplified axenic cultures and overly complicated natural communities. They also highlight the dominant role that primary producers play in determining the metabolism and interactions of the organisms that depend on them for sustenance. More

Randolph, S. E. & Rogers, D. J. The arrival, establishment and spread of exotic diseases: Patterns and predictions. Nat. Rev. Microbiol. 8, 361–371 (2010).Article 
PubMed 

Google Scholar 
Boussès, P., Dehecq, J. S., Brengues, C. & Fontenille, D. Inventaire actualisé des moustiques (Diptera : Culicidae) de l’île de La Réunion, océan Indien. Bulletin de la Société de pathologie exotique 106, 113–125 (2013).Article 
PubMed 

Google Scholar 
Delatte, H. et al. Geographic distribution and developmental sites of Aedes albopictus (Diptera: Culicidae) during a Chikungunya epidemic event. Vector-Borne Zoonotic Dis. 8, 25–34 (2008).Article 
PubMed 

Google Scholar 
Gomard, Y., Lebon, C., Mavingui, P. & Atyame, C. M. Contrasted transmission efficiency of Zika virus strains by mosquito species Aedes aegypti, Aedes albopictus and Culex quinquefasciatus from Reunion Island. Parasites Vectors https://doi.org/10.1186/s13071-020-04267-z (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Vazeille, M., Dehecq, J.-S. & Failloux, A.-B. Vectorial status of the Asian tiger mosquito Aedes albopictus of La Réunion Island for Zika virus: Ae. Albopictus of la réunion island. Med. Vet. Entomol. 32, 251–254 (2018).Article 
PubMed 

Google Scholar 
Youssouf, H. et al. Rift valley fever outbreak, Mayotte, France, 2018–2019. Emerg. Infect. Dis. 26, 769–772 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Sang, R. et al. Rift valley fever virus epidemic in Kenya, 2006/2007: The entomologic investigations. Am. J. Trop. Med. Hyg. 83, 28–37 (2010).Article 
PubMed 
PubMed Central 

Google Scholar 
Cardinale, E. et al. West Nile virus infection in horses, Indian ocean. Comp. Immunol. Microbiol. Infect. Dis. 53, 45–49 (2017).Article 
PubMed 

Google Scholar 
Bouyer, J., Yamada, H., Pereira, R., Bourtzis, K. & Vreysen, M. J. B. Phased conditional approach for mosquito management using sterile insect technique. Trends Parasitol. 36, 325–336 (2020).Article 
PubMed 

Google Scholar 
Lees, R. S., Carvalho, D. O. & Bouyer, J. Potential Impact of Integrating the Sterile Insect Technique into the Fight against Disease-Transmitting Mosquitoes 1081–1118 (CRC Press, 2021). https://doi.org/10.1201/9781003035572-33.Book 

Google Scholar 
Gouagna, L. C. et al. Strategic approach, advances, and challenges in the development and application of the SIT for area-wide control of Aedes albopictus mosquitoes in Reunion Island. Insects 11, 770 (2020).Article 
PubMed Central 

Google Scholar 
Bouyer, J. & Lefrançois, T. Boosting the sterile insect technique to control mosquitoes. Trends Parasitol. 30, 271–273 (2014).Article 
PubMed 

Google Scholar 
Soghigian, J. et al. Genetic evidence for the origin of Aedes aegypti, the yellow fever mosquito, in the southwestern Indian Ocean. Mol. Ecol. 29, 3593–3606 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Bouyer, J. & Vreysen, M. J. B. Yes, irradiated sterile male mosquitoes can be sexually competitive!. Trends Parasitol. 36, 877–880 (2020).Article 
PubMed 

Google Scholar 
Owino, E. A. et al. Field evaluation of natural human odours and the biogent-synthetic lure in trapping Aedes aegypti, vector of dengue and chikungunya viruses in Kenya. Parasites Vectors 7, 451 (2014).
Article 
PubMed 
PubMed Central 

Google Scholar 
Kröckel, U., Andreas, R., Eiras, Á. & Geier, M. New tools for surveillance of adult yellow fever mosquitoes: Comparison of trap catches with human landing rates in an urban environment. J. Am. Mosq. Control Assoc. 22, 229–238 (2006).Article 
PubMed 

Google Scholar 
Haramboure, M. et al. Modelling the control of Aedes albopictus mosquitoes based on sterile males release techniques in a tropical environment. Ecol. Model. 424, 109002 (2020).Article 

Google Scholar 
Farajollahi, A. et al. Field efficacy of BG-sentinel and industry-standard traps for Aedes albopictus (Diptera: Culicidae) and West Nile Virus Surveillance. J. Med. Entomol. 46, 919–925 (2009).Article 
PubMed 

Google Scholar 
Roiz, D. et al. Trapping the Tiger: Efficacy of the novel BG-sentinel 2 with several attractants and carbon dioxide for collecting Aedes albopictus (Diptera: Culicidae) in Southern France. J. Med. Entomol. 53, 460–465 (2016).Article 
PubMed 

Google Scholar 
Wilke, A. B. B. et al. Assessment of the effectiveness of BG-sentinel traps baited with CO2 and BG-Lure for the surveillance of vector mosquitoes in miami-dade County Florida. PLoS ONE 14, e0212688 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Staunton, K. M. et al. Effect of BG-lures on the male aedes (Diptera: Culicidae) sound trap capture rates. J. Med. Entomol. 58, 2425–2431 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Visser, T. M. et al. Optimisation and field validation of odour-baited traps for surveillance of Aedes aegypti adults in Paramaribo Suriname. Parasites Vectors 13, 121 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Owino, E. A. et al. An improved odor bait for monitoring populations of Aedes aegypti-vectors of dengue and chikungunya viruses in Kenya. Parasites Vectors 8, 253 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
Le Goff, G. et al. Comparison of efficiency of BG-sentinel traps baited with mice, mouse-litter, and CO2 lures for field sampling of male and female aedes albopictus mosquitoes. Insects 8, 95 (2017).Article 
PubMed Central 

Google Scholar 
Nielsen, G. D., Petersen, S. H., Vinggaard, A. M., Hansen, L. F. & Wolkoff, P. Ventilation, CO2 production, and CO2 exposure effects in conscious, restrained CF-1 mice. Pharmacol. Toxicol. 72, 163–168 (1993).
Article 
PubMed 

Google Scholar 
Gouagna, L. C., Dehecq, J.-S., Fontenille, D., Dumont, Y. & Boyer, S. Seasonal variation in size estimates of Aedes albopictus population based on standard mark–release–recapture experiments in an urban area on Reunion Island. Acta Trop. 143, 89–96 (2015).Article 
PubMed 

Google Scholar 
Dekker, T., Geier, M. & Cardé, R. T. Carbon dioxide instantly sensitizes female yellow fever mosquitoes to human skin odours. J. Exp. Biol. 208, 2963–2972 (2005).Article 
PubMed 

Google Scholar 
Grant, A. J. & O’Connell, R. J. Age-related changes in female mosquito carbon dioxide detection. J. Med. Entomol. 44, 617–623 (2007).Article 
PubMed 

Google Scholar 
Bohbot, J. & Vogt, R. G. Antennal expressed genes of the yellow fever mosquito (Aedes aegypti L.); characterization of odorant-binding protein 10 and takeout. Insect Biochem. Mol. Biol. 35, 961–979 (2005).Article 
PubMed 

Google Scholar 
Hartberg, W. K. Observations on the mating behaviour of Aedes aegypti in nature. Bull. World Health Organ. 45, 847 (1971).PubMed 
PubMed Central 

Google Scholar 
Cator, L. J., Arthur, B. J., Ponlawat, A. & Harrington, L. C. Behavioral observations and sound recordings of free-flight mating swarms of Ae. aegypti (Diptera: Culicidae) in Thailand. J. Med. Entomol. 48, 941–946 (2011).Article 
PubMed 

Google Scholar 
Lacroix, R., Delatte, H., Hue, T. & Reiter, P. Dispersal and survival of male and female Aedes albopictus(Diptera: Culicidae) on Réunion Island. J. Med. Entomol. 46, 1117–1124 (2009).Article 
PubMed 

Google Scholar 
Pombi, M. et al. Field evaluation of a novel synthetic odour blend and of the synergistic role of carbon dioxide for sampling host-seeking Aedes albopictus adults in Rome, Italy. Parasites Vectors 7, 580 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
Cilek, J. E., Hallmon, C. F. & Johnson, R. Semi-field comparison of the Bg Lure, nonanal, and 1-Octen-3-OL to attract adult mosquitoes in northwestern Florida. J. Am. Mosq. Control Assoc. 27, 393–397 (2011).Article 
PubMed 

Google Scholar 
Bagny Beilhe, L., Delatte, H., Juliano, S. A., Fontenille, D. & Quilici, S. Ecological interactions in Aedes species on Reunion Island. Med. Vet. Entomol. 27, 387–397 (2013).Article 
PubMed 

Google Scholar 
Golstein, C., Boireau, P. & Pagès, J.-C. Benefits and limitations of emerging techniques for mosquito vector control. Comptes Rendus Biol. 342, 270–272 (2019).Article 

Google Scholar 
Maïga, H., Gilles, J. R. L., Lees, R. S., Yamada, H. & Bouyer, J. Demonstration of resistance to satyrization behavior in Aedes aegypti from La Réunion island. Parasite 27, 22 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Zeileis, A., Kleiber, C. & Jackman, S. Regression models for count data in R. J. Stat. Soft. https://doi.org/10.18637/jss.v027.i08 (2008).Article 

Google Scholar 
Fawaz, E. Y., Allan, S. A., Bernier, U. R., Obenauer, P. J. & Diclaro, J. W. Swarming mechanisms in the yellow fever mosquito: Aggregation pheromones are involved in the mating behavior of Aedes aegypti. J. Vector Ecol. 39, 347–354 (2014).Article 
PubMed 

Google Scholar 
Guthery, F. S., Burnham, K. P. & Anderson, D. R. Model selection and multimodel inference: A practical information-theoretic approach. J. Wildl. Manag. 67, 655 (2003).Article 

Google Scholar 
Manly, B. F. J. Randomization, Bootstrap and Monte Carlo Methods in Biology 399 (CRC Press/Chapman & Hall, 2006). https://doi.org/10.1201/9781315273075.Book 
MATH 

Google Scholar 
R Core Team. R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, 2022).Barton, K. MuMIn: Multi-Model Inference. (R-Forge, 2022).
Google Scholar 
Burnham, K. P. & Anderson, D. R. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach 496 (Springer-Verlag, 2002).MATH 

Google Scholar 
Xie, Y., Dervieux, C. & Riederer, E. R Markdown Cookbook (Chapman; Hall/CRC, 2020). https://doi.org/10.1201/9781003097471.Book 

Google Scholar  More

Survey sites and data collectionBenthic and fish surveys were conducted at randomly stratified sites throughout the entirety of the FRT by NOAA’s National Coral Reef Monitoring Program (NCRMP). Sites were categorized into three biogeographic regions, including Dry Tortugas (DRTO, n = 228), Florida Keys (FLKs, n = 322), and Southeast Florida (SEFL, n = 173) (Fig. 1). The Florida Keys were further classified into the following four sub-regions: Lower Keys (LK, n = 103), Middle Keys (MK, n = 46), Upper Keys (UK, n = 140), Biscayne (BISC, n = 33). Within each region/sub-region (except for SEFL), reefs were categorized according to reef types. For DRTO, this included bank, forereef, and lagoon reef sites. For the LK, MK, UK, and BISC, reef types were categorized as inshore, mid-channel, and offshore. Data were collected throughout the region in 2014, 2016, and 2018.Fish and benthic surveys were conducted in accordance with NCRMP methodologies34 (Table S2). The protocol used for the fish surveys was developed from a modified Reef Visual Census (RVC) method35 and was performed using a stratified random sampling design. Divers surveyed two 15 m diameter cylinders, spaced 15 m apart. Fish species were identified to the lowest taxonomic level for a period of five minutes. This was followed by an additional five minutes dedicated to recording species abundances and sizes (10 cm bins).Surveys were used to quantify the benthic cover at each site. The protocol for these surveys followed a standard line point-intercept sampling design. At each site, a 15 m weighted transect was draped along the reef surface. Surveyors recorded benthic composition at 15 cm intervals along the transect (i.e., 100 equidistant points). The benthic composition from these 100 points was then transformed to percent cover of ecologically important functional groups (scleractinian coral [species-specific], gorgonians, hydrocoral, CCA, macroalgae, turf algae, sponges, bare/dead substrate, sand/sediment).Carbonate budget analysisPlanar benthic surveys were adjusted to account for the three-dimensional complexity (i.e., rugosity) of each site using light detection and ranging (LiDAR) data (1 m horizontal resolution; 15 cm vertical resolution) from topobathymetric mapping surveys of the South Florida eastern coastline conducted by NOAA’s National Geodetic Survey. A 15 m x 15 m region of interest (ROI) was placed around the GPS coordinates of each site using ArcGIS Pro with 3D and Spatial Analyst extensions (ESRI). The ROI was then overlaid with existing multibeam echosounder (MBES) and LiDAR bathymetry data. Within the ROI, LiDAR was extracted using the Clip Raster function from ArcPy (ArcGIS’s python coding interface), and the Surface Volume tool was used to calculate the 3D surface area. Rugosity was calculated by dividing the 3D surface area by the 2D surface area of the ROI.The methodology for standardizing reef carbonate budgets to topographic complexity (i.e., rugosity) diverged from that of the ReefBudget approach by using site-specific rugosity rather than species-specific rugosity17. This was a necessary limitation of this analysis as transect rugosity at 1 m increments was not measured using the NCRMP benthic survey protocol. To ensure that reef topographic complexity was still accounted for, however, rugosity of the entire reef site, calculated from LiDAR bathymetry data, was used in this analysis. While rugosity of the site rather than of each benthic component, specifically for corals, can lead to an under or overestimation of carbonate production rates, we note that site and species rugosity (i.e., encrusting and massive coral morphologies) was low for the vast majority of sites and species surveyed, thereby reducing the probability of an under or overestimation.Reef carbonate budget analysis was performed following a modified version of the ReefBudget approach17. Coral carbonate production was derived from species-specific linear extension rates (cm year−1), skeletal density (g cm−3), coral morphology (branching, massive, sub-massive, encrusting/plating), and percent cover. Carbonate production by CCA and other calcareous encrusters was similarly calculated as a function of surface area, literature reported linear extension rates, and skeletal density17. Gross carbonate production at each survey site was measured as the sum total of carbonate production by all calcareous organisms found at each site and was standardized to site-specific reef rugosity.Gross carbonate erosion for each survey-site was calculated as the sum total of erosion by four bioeroding groups: parrotfish, microborers, macroborers, and urchins. The calculations roughly followed the ReefBudget methodologies17 (Table 1). Parrotfish size frequency distributions from NCRMP surveys were multiplied by size and species-specific bite rates (bites min−1), volume removed per bite (cm3), and proportion of bites leaving scars to calculate total parrotfish erosion17. The substrate density (1.72 g cm−3) used in these calculations followed that of the ReefBudget protocol17. Microbioerosion was calculated from the percent cover of dead coral substrate, which was multiplied by a literature-derived rate17 of − 0.240 kg CaCO3 m−2 year−1. Macroboring was calculated as the percent cover of clionid sponges multiplied by the average erosion rate of all Caribbean/Atlantic clionid sponges17 (-6.05 kg CaCO3 m−2 year−1). External bioerosion by urchins was calculated using Diadema urchin abundance collected from the benthic surveys. Due to the lack of test size data from the NCRMP benthic surveys, urchin abundance was multiplied by the bioerosion rate of an average test sized36 (66 mm) Caribbean/Atlantic Diadema urchin (-0.003 kg CaCO3 m-2 year−1). While using an average test sized Diadema urchin for this analysis may have led to an under or overestimation of urchin erosion, the abundance of Diadema urchins measured in the surveys was minimal, as they appeared to be functionally irrelevant across the FRT.Model validationAs the survey methodologies and data sources employed in this analysis were modified from that of the standard ReefBudget approach17, we chose to validate our model through a fine scale temporal comparison of annual ReefBudget surveys conducted by NOAA at Cheeca Rocks (UK) to three nearby NCRMP sites used in our analysis. Since the NCRMP surveys were performed in 2014, 2016, and 2018, this study focused exclusively on these three survey years from the NOAA Cheeca Rocks dataset. Temporal trends related to reef growth/erosion were visually compared to see if survey types provided comparable results (SI Figure S6).Statistical analysisAll model calculations and statistical analyses were performed using R37 with the R Studio extension38. Generalized linear models (GLMs) were run on response variables involved in habitat production (i.e., net carbonate production, gross carbonate production, and gross carbonate erosion) to evaluate spatial trends related to reef development across sub-regions and reef types. Each GLM was performed with reef type being nested within sub-region. The best fit distribution for each variable was determined using the fitdistrplus R package39. Linear regression analysis was used to evaluate the relationship between net carbonate production and both live coral cover and parrotfish biomass. All plots were created using ggplot2 R package40 and edited for style with Adobe Illustrator41. More