Philippa Kaur

Smale, D. A. et al. Marine heatwaves threaten global biodiversity and the provision of ecosystem services. Nat. Clim. Change. 9, 306–312 (2019).Article 

Google Scholar 
Garrabou, J. et al. Mass mortality in Northwestern Mediterranean rocky benthic communities: Effects of the 2003 heat wave. Global Change Biol. 15, 1090–1103 (2009).Article 

Google Scholar 
Hoeksema, B. W. & Matthews, J. L. Contrasting bleaching patterns in mushroom coral assemblages at Koh Tao Gulf of Thailand. Coral Reefs 30, 95 (2011).Article 

Google Scholar 
Coleman, M. A., Minne, A. J. P., Vranken, S. & Wernberg, T. Genetic tropicalisation following a marine heatwave. Sci. Rep. 10, 12726 (2020).Article 

Google Scholar 
Hutchinson G. E. Concluding remarks. – Cold Spring Harb. Symp. Quant. Biol. 22: 415–427 (1957).Lavergne, S., Mouquet, N., Thuiller, W. & Ronce, O. Biodiversity and climate change: Integrating evolutionary and ecological responses of species and communities. Ann. Rev. Ecol. Evol. Syst. 41, 321–350 (2010).Article 

Google Scholar 
King, N. G., McKeown, N. J., Smale, D. A. & Moore, P. J. The importance of phenotypic plasticity and local adaptation in driving intraspecific variability in thermal niches of marine macrophytes. Ecography 41(9), 1469–1484 (2018).Article 

Google Scholar 
Thomas, L. et al. Mechanisms of thermal tolerance in reef-building corals across a fine-grained environmental mosaic: Lessons from Ofu American Samoa. Front. Mar. Sci. 4, 434 (2018).Article 

Google Scholar 
Fox, R. J., Donelson, J. M., Schunter, C., Ravasi, T. & Gaitán-Espitia, J. D. Beyond buying time: the role of plasticity in phenotypic adaptation to rapid environmental change. Phil. Trans. R. Soc. B. 37420180174 (2019).Howells, E. et al. Coral thermal tolerance shaped by local adaptation of photosymbionts. Nat. Clim. Change 2, 116–120 (2012).Article 

Google Scholar 
Haguenauer, A., Zuberer, F., Ledoux, J.-B. & Aurelle, D. Adaptive abilities of the Mediterranean red coral Corallium rubrum in a heterogeneous and changing environment: from population to functional genetics. J. Exp. Mar. Biol. Ecol. 449, 349–357 (2013).Article 

Google Scholar 
Linares, C., Cebrian, E., Kipson, S. & Garrabou, J. Does thermal history influence the tolerance of temperate gorgonians to future warming?. Mar. Environ. Res. 89, 45–52 (2013).Article 

Google Scholar 
Palumbi, S. R., Barshis, D. J., Traylor-Knowles, N. & Bay, R. Mechanisms of reef coral resistance to future climate change. Science 344, 895–898 (2014).Article 

Google Scholar 
Dixon, G. B. et al. Genomic determinants of coral heat tolerance across latitudes. Science 348, 1460–1462 (2015).Article 

Google Scholar 
Chakravarti, L. J., Beltran, V. H. & van Oppen, M. J. Rapid thermal adaptation in photosymbionts of reefbuilding corals. Glob. Chang. Biol. 23, 4675–4688 (2017).Article 

Google Scholar 
Krueger, T. et al. Common reef-building coral in the northern Red Sea resistant to elevated temperature and acidification. R. Soc. Open Sci. 4, 170038 (2017).Article 

Google Scholar 
Middlebrook, R., Hoegh-Guldberg, O. & Leggat, W. The effect of thermal history on the susceptibility of reef building corals to thermal stress. J. Exp. Biol. 211, 1050–1056 (2008).Article 

Google Scholar 
Bellantuono, A. J., Granados-Cifuentes, C., Miller, D. J., Hoegh-Guldberg, O. & Rodriguez-Lanetty, M. Coral thermal tolerance: Tuning gene expression to resist thermal stress. PLoS ONE 7, e50685 (2012).Article 

Google Scholar 
Hawkins, T. D. & Warner, M. E. Warm preconditioning protects against acute heat-induced respiratory dysfunction and delays bleaching in a symbiotic sea anemone. J. Exp. Biol. 220, 969–983 (2017).
Google Scholar 
Williams, D. E., Miller, M. W., Bright, A. J., Pausch, R. E. & Valdivia, A. Thermal stress exposure, bleaching response, and mortality in the threatened coral Acropora palmata. Bull. Mar. Poll. 124, 189–197 (2017).Article 

Google Scholar 
Hughes, T. P. et al. Ecological memory modifies the cumulative impact of recurrent climate extremes. Nat. Clim. Change 9, 40–43 (2019).Article 

Google Scholar 
Ferrier-Pagès, C. et al. Physiological response of the symbiotic gorgonian Eunicella singularis to a long-term temperature increase. J. Exp. Biol. 212, 3007–3015 (2009).Article 

Google Scholar 
Rodolfo-Metalpa, R. et al. Thermally tolerant corals have limited capacity to acclimatize to future warming. Global Change Biol. 20, 3036–3049 (2014).Article 

Google Scholar 
Ledoux, J-B., Aurelle, D., Bensoussan, N, Marschal, C., Feral & Garrabou, J. Potential for adaptive evolution at species range margins: contrasting interactions between red coral populations and their environment in a changing ocean. Ecol. Evol. 5, 1178–1192 (2015).Crisci, C. et al. Regional and local environmental conditions do not shape the response to warming of a marine habitat-forming species. Sci. Rep. 7, 5069 (2017).Article 

Google Scholar 
Jurriaans, S. & Hoogenboom M. O. Thermal performance of scleractinian corals along a latitudinal gradient on the Great Barrier Reef. Phil. Trans. R. Soc. B. 37420180546 (2019).Cerrano, C. et al. Catastrophic mass-mortality episode of gorgonians and other organisms in the Ligurian Sea (North-western Mediterranean), Summer 1999. Ecol. Lett. 3, 284–293 (2000).Article 

Google Scholar 
Garrabou, J., Gómez-Gras, D., Medrano, A., Cerrano, C., Ponti, M., et al. Marine heatwaves drive recurrent mass mortalities in the Mediterranean Sea. Global. Chang. Biol. (in press).Rossi, S. et al. Temporal variation in protein, carbohydrate, and lipid concentrations in Paramuricea clavata (Anthozoa, Octocorallia): evidence for summer–autumn feeding constraints. Mar Biol. 149, 643–651 (2006).Article 

Google Scholar 
Coma, R. et al. Global warming-enhanced stratification and mass mortality events in the Mediterranean. Proc. Natl. Acad. Sci. U.S.A. 106, 6176–6181 (2009).Article 

Google Scholar 
Kipson, S. Ecology of gorgonian dominated communities in the Eastern Adriatic Sea. PhD thesis. University of Zagreb, Zagreb, 160 pp. (2013).Bally, M. & Garrabou, J. Thermodependent bacterial pathogens and mass mortalities in temperate benthic communities: a new case of emerging disease linked to climate change. Global Change Biol. 13, 2078–2088 (2007).Article 

Google Scholar 
Vezzulli, L., Previati, M., Pruzzo, C., Marchese, A., Bourne. D. G. & Cerrano C. Vibrio infections triggering mass mortality events in a warming Mediterranean Sea. Environ. Microbiol. 12, 2007–2019 (2010).Corinaldesi, C. et al. Changes in coral forest microbiomes predict the impact of marine heatwaves on habitat-forming species down to mesophotic depths. Sci. Total Environ. 823, 153701 (2022).Article 

Google Scholar 
Tignat-Perrier, R. et al. The effect of thermal stress on the physiology and bacterial communities of two key Mediterranean gorgonians. Appl. Environ. Microbiol. 88(6), e0234021 (2022).Article 

Google Scholar 
Arizmendi-Mejía, R. et al. Demographic responses to warming: reproductive maturity and sex influence vulnerability in an octocoral. Coral Reefs 34, 1207–1216 (2015).Article 

Google Scholar 
Arizmendi-Mejía, R. et al. Combining genetic and demographic data for the conservation of a mediterranean marine habitat-forming species. PLoS ONE 10, e0119585 (2015).Article 

Google Scholar 
Ponti, M. et al. Ecological shifts in Mediterranean coralligenous assemblages related to gorgonian forest loss. PLoS ONE 9(7), e102782 (2014).Article 

Google Scholar 
Ponti, M., Turicchia, E., Ferro, F., Cerrano, C. & Abbiati, M. The understorey of gorgonian forests in mesophotic temperate reefs. Aquat. Conserv. Mar. Freshw. Ecosyst. 28(5), 1153–1166 (2018).Gómez-Gras, D. et al. Climate change transforms the functional identity of Mediterranean coralligenous assemblages. Ecol. Lett. 24(5), 1038–1051 (2021).Article 

Google Scholar 
Boavida, J., Assis, J., Silva, I., & Serrão, E. A. Overlooked habitat of a vulnerable gorgonian revealed in the Mediterranean and Eastern Atlantic by ecological niche modelling. Sci. Rep. 6(1) (2016).Linares, C., Doak, D., Coma, R., Diaz, D. & Zabala, M. Life history and viability of a long-lived marine invertebrate: The octocoral Paramuricea clavata. Ecology 88, 918–928 (2007).Article 

Google Scholar 
Coma, R., Ribes, M., Zabala, M. & Gili, J. M. Growth in a modular colonial marine invertebrates. Estuar. Coast. Shef Sci. 47, 459–470 (1998).Article 

Google Scholar 
Linares, C. et al. Early life history of the Mediterranean gorgonian Paramuricea clavata: Implication for population dynamics. Invertebr. Biol. 127, 1–11 (2008).Article 

Google Scholar 
Mokhtar-Jamaï, K. et al. From global to local genetic structuring in the red gorgonian Paramuricea clavata: The interplay between oceanographic conditions and limited larval dispersal. Mol. Ecol. 20, 3291–3305 (2011).Article 

Google Scholar 
Ledoux, J. et al. Postglacial range expansion shaped the spatial genetic structure in a marine habitat-forming species: Implications for conservation plans in the Eastern Adriatic Sea. J. Biogeogr. 45, 2645–2657 (2018).Article 

Google Scholar 
Dias, V. et al. High coral bycatch in bottom-set gillnet coastal fisheries reveals rich coral habitats in Southern Portugal. Front. Mar. Sci. 7, 1–16 (2020).Article 

Google Scholar 
Cebrian, E., Linares, C., Marshall, C. & Garrabou, J. Exploring the effects of invasive algae on the persistence of gorgonian populations. Biol. Invas. 14, 2647–2656 (2012).Article 

Google Scholar 
Mateos-Molina, D. et al. Assessing consequences of land cover changes on sediment deliveries to coastal waters at regional level over the last two decades in the northwestern Mediterranean Sea. Ocean Coast. Manag. 116, 435–442 (2015).Article 

Google Scholar 
Gómez-Gras, D. et al. Population collapse of habitat-forming species in the Mediterranean: a long-term study of gorgonian populations affected by recurrent marine heatwaves. Proc. R. Soc. B. 288, 20212384 (2021).Article 

Google Scholar 
Otero, M. M., Numa, C., Bo, M., Orejas, C., Garrabou, J. et al., Overview of the conservation status of Mediterranean anthozoans. IUCN, Malaga, Spain, 73 (2017).Bensoussan, N., Cebrian, E., Dominici, J. M., Kersting, D. K., Kipson, S., et al. Using CMEMS and the Mediterranean Marine protected Area sentinel network to track ocean warming effects in coastal areas. In: Copernicus Marine Service Ocean State Report. J. Oper. Oceanogr. 3 (2019).Garrabou, J. et al. Collaborative database to track mass mortality events in the Mediterranean Sea. Front. Mar. Sci. 6, 707 (2019).Article 

Google Scholar 
Gómez-Gras, D. et al. Response diversity in Mediterranean coralligenous assemblages facing climate change: insights from a multi-specific thermotolerance experiment. Ecol. Evol. 9(7), 4168–4180 (2019).Article 

Google Scholar 
Cox, D. R. Regression models and life tables (with discussion). J. R. Stat. Soc. Series B 34, 187–220 (1972).MATH 

Google Scholar 
Kaplan, E. L. & Meier, P. Nonparametric estimation from incomplete observations. J. Am. Stat. Assoc. 53, 457–481 (1958).Article 
MathSciNet 
MATH 

Google Scholar 
Mantel, N. Evaluation of survival data and two new rank order statistics arising in its consideration. C. Chemoth. Rep. 50(3), 163–170 (1966).
Google Scholar 
Galli, G., Solidoro, C. & Lovato, T. Marine heat waves hazard 3D maps and the risk for low motility organisms in a warming Mediterranean Sea. Fronts Mar. Sci. 4 (2017).Darmaraki, S. et al. Future evolution of marine heatwaves in the mediterranean sea. Clim. Dyn. 53, 1371–1392 (2019).Article 

Google Scholar 
Coles, S. L., Jokiel, P. L. & Lewis, C. R. Thermal tolerance in tropical versus subtropical Pacific reef corals. Pac. Sci. 30, 156–166 (1976).
Google Scholar 
Bay, R. A. & Palumbi, S. R. Rapid acclimation ability mediated by transcriptome changes in reef-building corals. Genome Biol. Evol. 7, 1602–1612 (2015).Article 

Google Scholar 
Fangue, N. A., Hofmeister, M. & Schulte, P. M. Intraspecific variation in thermal tolerance and heat shock protein gene expression in common killifish Fundulus heteroclitus. J. Exp. Biol. 209, 2859–2872 (2006).Article 

Google Scholar 
Jensen, L. F. et al. Local adaptation in brown trout early life-history traits: Implications for climate change adaptability. Proc. R. Soc. B Biol. Sci. 275, 2859–2868 (2008).Article 

Google Scholar 
Kuo, E. S. L. & Sanford, E. Geographic variation in the upper thermal limits of an intertidal snail: implications for climate envelope models. Mar. Ecol.: Prog. Ser. 388, 137–146 (2009).Safaie, A. et al. High frequency temperature variability reduces the risk of coral bleaching. Nat. Commun. 9, 1671 (2018).Article 

Google Scholar 
Thompson, D. M. & van Woesik, R. Corals escape bleaching in regions that recently and historically experienced frequent thermal stress. Proc. R. Soc. Biol. Sci. B 276, 2893–2901 (2009).Article 

Google Scholar 
Gates, R. D. & Edmunds, P. J. The physiological mechanisms of acclimatization in tropical reef corals. Am. Zool. 39, 30–43 (1999).Article 

Google Scholar 
West-Eberhard, M. J. Developmental plasticity and evolution (Oxford University Press, 2003).Book 

Google Scholar 
Brown, B. E., Dunne, R. P., Edwards, A. J., Sweet, M. J. & Phongsuwan, N. Decadal environmental ’memory’ in a reef coral?. Mar. Biol. 162, 479–483 (2015).Article 

Google Scholar 
Torda, G. et al. Rapid adaptive responses to climate change in corals. Nat. Clim. Change 7, 627 (2017).Article 

Google Scholar 
Liew, Y. J. et al. Intergenerational epigenetic inheritance in reef-building corals. Nat. Clim. Change 10, 254–259 (2020).Article 

Google Scholar 
Howells, E. J., Abrego, D., Liew, Y. J., Burt, J. A., Meyer, E. & Aranda, M. Enhancing the heat tolerance of reef-building corals to future warming. Sci. Adv. 7, eabg6070 (2021).Palstra, F. P. & Ruzzante, D. E. Genetic estimates of contemporary effective population size: What can they tell us about the importance of genetic stochasticity for wild population persistence?. Mol. Ecol. 17, 3428–3447 (2008).Article 

Google Scholar 
Hague, M. & Routman, E. Does population size affect genetic diversity? A test with sympatric lizard species. Heredity 116, 92–98 (2016).Article 

Google Scholar 
Gurgel, C. F. D., Camacho, O., Minne, A. J., Wernberg, T. & Coleman, M. A. Marine heatwave drives cryptic loss of genetic diversity in underwater forests. Curr. Biol. 30(7), 1199–1206 (2020).Article 

Google Scholar 
Ledoux, J.-B. et al. Assessing the impact of population decline on mating system in the overexploited Mediterranean red coral. Aquat. Conserv: Mar. Freshw. Ecosyst. 30(6), 1149–1159 (2020).Article 

Google Scholar 
Howells, E. J., Berkelmans, R., van Oppen, M. J. H., Willis, B. L. & Bay, L. K. Historical thermal regimes define limits to coral acclimatization. Ecology 94, 1078–1088 (2013).Article 

Google Scholar 
Spielman, D., Brook, B. W. & Frankham, R. Most species are not driven to extinction before genetic factors impact them. Proc. Nat. Acad. Sci. USA 101, 15261–15264 (2004).Article 

Google Scholar 
Frankham, R., Bradshaw, C. J. A. & Brook, B. W. Genetics in conservation management: Revised recommendations for the 50/500 rules, Red List criteria and population viability analyses. Biol. Cons. 170, 56–63 (2014).Article 

Google Scholar 
Gori, A. et al. Effects of food availability on the sexual reproduction and biochemical composition of the Mediterranean gorgonian Paramuricea clavata. J. Exp. Mar. Biol. Ecol. 444, 38–45 (2013).Article 

Google Scholar 
Darmaraki, S., Somot, S., Sevault, F. & Nabat, P. Past variability of Mediterranean Sea marine heatwaves. Geophys. Res. Lett. 46, 9813–9823 (2019).Article 

Google Scholar 
Bongaerts, P., Ridgway, T., Sampayo, E. M. & Hoegh-Guldberg, O. Assessing the ‘deep reef refugia’ hypothesis: Focus on Caribbean reefs. Coral Reefs 29, 309–327 (2010).Article 

Google Scholar 
Pilczynska, J. et al. Genetic diversity increases with depth in red gorgonian populations of the Mediterranean Sea and the Atlantic Ocean. Peer J 7, e6794 (2019).Article 

Google Scholar 
Gugliotti, E. F., DeLorenzo, M. E. & Etnoyer, P. J. Depth-dependent temperature variability in the Southern California bight with implications for the cold-water gorgonian octocoral Adelogorgia phyllosclera. J. Exp. Mar. Biol. Ecol. 514–515, 118–126 (2019).Article 

Google Scholar 
Aurelle, D. et al. Genetic insights into recolonization processes of Mediterranean octocorals. Mar. Biol. 167, 73 (2020).Article 

Google Scholar 
Morikawa, M. K., & Palumbi, S. R. Using naturally occurring climate resilient corals to construct bleaching-resistant nurseries. Proc. Nat. Acad. Sci. USA 116(21), 10586 LP–10591 (2019).Crisci, C., Bensoussan, N., Romano, J. C. & Garrabou, J. Temperature anomalies and mortality events in marine communities: Insights on factors behind differential mortality impacts in the NW Mediterranean. PLoS ONE 6, e23814 (2011).Article 

Google Scholar 
Brener-Raffalli, K., Vidal-Dupiol, J., Adjeroud, M., Rey, O., Romans, P., et al. Gene expression plasticity and frontloading promote thermotolerance in Pocilloporid corals. bioRxiv 398602 (2018).Ledoux, J. B. et al. The Genome Sequence of the Octocoral Paramuricea clavata – A Key resource to study the impact of climate change in the Mediterranean. G3 10(9), 2941–2952 (2020).Article 

Google Scholar  More

The rise of animals (metazoans) is a seminal event in the history of life. The Cambrian Radiation ~540 Ma marks the appearance of abundant and diverse metazoans and increasing ecosystem complexity in the fossil record1. A causal relationship between the redox and fossil records is proposed, where oxygen provision reached a threshold, or series of thresholds, which allowed for the diversification of metazoans with increasing metabolic demands2. Global geochemical data, however, suggest that oxygenation was not a simple, linear process, but rather occurred episodically via a series of short-lived pulses (1–3 Myr), or ‘oceanic oxygenation events’ (OOEs)3,4. Early and even later Cambrian seas likely had shallower, and more dynamic, oxygen minimum zones (OMZs) than modern oceans5,6. Such pulses of increased oxygenation (and related changes in productivity) are hypothesised to have increased the extent of shallow-ocean oxygenation and hence to have promoted diversification7. But what remains unquantified is the community-wide response of metazoans to such redox cycles, an insight into the evolutionary processes involved, and hence whether these pulses were indeed a driving force for the Cambrian Radiation.In order to test the hypothesis that oxic pulses led to diversification and potentially ecological development, a correlation between increased oxygenation, rates of origination, and metrics of metazoan ecosystem complexity needs to be demonstrated. Early Cambrian marine environments were heterogeneous with respect to oxygen provision and nutrient load at a regional scale, so in order to investigate potential correlations, we require the integration of global and local redox proxies, and biotic records in the same stratigraphically well-constrained geological successions.During the early Cambrian, the Siberian Platform was a vast isolated, tropical continent almost entirely covered by an epicontinental sea (Fig. 1a)8,9. The platform supported a single metacommunity, i.e. a species pool with many local, interacting communities e.g.10, representing a third of total early Cambrian metazoan benthic diversity with widespread metazoan (archaeocyath sponge) reefs that formed bioherms (Fig. 1b)7,11. Dynamic and synchronous changes of body size in archaeocyath sponges, hyoliths, and helcionelloid molluscs through the early Cambrian on the Siberian Platform have been quantified, which coincide with elevated biodiversity and rates of origination: these have been proposed to follow OOEs12. Here we consider temporal changes in both the position of archaeocyath sponge reefs as a function of relative water depth, and in individual reef size (diameter), as well as the ecological complexity of the reef-building and dwelling communities by quantification of changing reef community membership of sessile archaeocyath sponge, coralomorph, and cribricyath species, on the Siberian Platform.Fig. 1: Palaeogeographic and stratigraphic position of the early Cambrian archaeocyath reefs of the Lena-Aldan area on the Siberian Platform.a Early Cambrian palaeofacies zonation map of the Siberian Platform. b Cross section to show relative positions of sampled transects along the Lena River11,40,66,67,68. c Lithostratigraphy, biostratigraphy, carbon isotope (δ13C)29,31,32 and carbonate-associated sulfate sulfur isotope (δ34SCAS)7 data for sections from the middle Lena River (Isit’, Zhurinsky Mys, Achchagy-Kyyry-Taas, and Achchagy-Tuoydakh). S.E.—Sinsk Event; Tolb.—Tolba Formation; ATD., BOT., N.-D., TOM.—Atdabanian, Botoman, Nemakit-Daldynian, and Tommotian local stages, respectively.Full size imageTo quantify ecological complexity, we used metacommunity analyses, which compare the structure between communities in terms of taxa (generally species) compositions spatially and temporally10 (see Methods). The ‘Elements of Metacommunity Structure’ framework used here is a hierarchical analysis that identifies properties in site-by-species presence/absence matrices that are related to the underlying processes, such as species interactions, dispersal, and environmental filtering that shape species distributions10. Application to various marine and terrestrial palaeocommunities has demonstrated the robustness of these methods to fossil data and sample size variations13,14. There are fourteen different types of metacommunity structure which are determined by the calculation of three metacommunity metrics: Coherence, Turnover, and Boundary Clumping, which reveal different controlling processes of underlying metacommunity structure10,15,16,17,18.The most ecologically complex metacommunities are classified as Clementsian, and have positive coherence, turnover and boundary clumping16. Clementsian metacommunities contain groups of taxa with similar range boundaries that respond to the environment synchronously as taxa have physiological or evolutionary trade-offs within the communities associated with environmental thresholds19. By contrast, when taxa respond individualistically to the underlying environment, without accounting for other taxa within the community, the structure is Gleasonian, and is defined by positive coherence and turnover but no significant boundary clumping16. When coherence is positive, but turnover is not significantly different from random, then the resultant metacommunity structures are known as quasi-structures (e.g. quasi-Clementsian), which reflect weaker underlying structuring processes.We determined the metacommunity structure for archaeocyath sponge species on the Siberian Platform throughout their early Cambrian record using an entire previously published data set11 then on a sub-set of metacommunities which had a sufficient number of reef sites to be suitable for analyses, i.e. with a sufficient number of sites to be statistically significant. Further, to investigate the effects of water depth on metacommunity structure, we used Spearman rank correlations to test whether the metacommunity ranking (as determined by reciprocal averaging, a type of correspondence analysis which ordinates the sites based on their species composition17), is significantly correlated to water depth. Finally, to quantify how pairwise associations between taxa change between the three temporally different metacommunities, we determined which pairwise taxa co-occurrences are significantly non-random using a combinatorics approach, and whether any non-random co-occurrences are positive or negative20.Species richness estimates are highly sensitive to differences in sampling. When comparing species richness of assemblages from several time intervals, it is advisable to standardise sampling across those assemblages to ensure that changes in species richness are not attributable to sampling differences. One approach is to subsample each time interval down to a standardised number of individuals (size-based rarefaction), but this approach can underestimate changes in richness because it tends to sample low-richness assemblages more completely than high-richness ones21. Coverage-based rarefaction, where each sample is down-sampled to a standardised level of taxonomic completeness, avoids this potential issue. The coverage of a sample is the proportion of species in the assemblage which are represented in that sample, and it can be estimated by subtracting the proportion of singletons in a sample from 1 (e.g.22; see also21 for details). We used the estimateD function from R package iNEXT23 to produce coverage-standardised species richness estimates with 95% confidence intervals, by repeatedly down-sampling the sampled assemblage from each time interval to match the coverage of the lowest-coverage interval. We did this by setting datatype = “abundance”, base = “coverage” and leaving all other arguments as default.In sum, we test the biotic response to OOEs by compiling metrics of archaeocyath reef size, location, and metacommunity complexity, integrated with existing data on archaeocyath individual size, species richness and origination and extinction rates12 and high-resolution geochemistry4,7 recalculated to the same stratigraphic scale, on the Siberian Platform over 11 Myr through Cambrian stages 2–3 (mid-Tommotian to early Botoman on the Siberian stratigraphic scale; 525–514 Ma). These results are used to quantify the community-wide response of metazoans to extrinsic redox cycles, and hence gain insight into the evolutionary processes involved.Geological setting and evolution of redoxDuring the early Cambrian shallow marine carbonates associated with evaporites and siliciclastics dominated the inner Siberian Platform, passing to shallow marginal carbonates of transitional facies known as the transitional zone (or the Anabar-Sinsk), thence to deep ramp and slope settings that accumulated organic-rich limestone and shale (Fig. 1a)24,25,26. Archaeocyathan reefs or bioherms were almost entirely restricted to the transitional facies. Such reefs appeared and proliferated during Cambrian stages 2 and 3 (Tommotian, Atdabanian and earliest Botoman), disappeared at the beginning of Stage 4 (middle Botoman) and re-appeared briefly at the end of this stage (Toyonian).We integrate palaeontological (archaeocyath species number and individual size), palaeoecological (reef size and palaeodepth location) and chemostratigraphic information (carbon isotope cycles 5p, 6p, and II–VII) for sections of the Aldan, Selinde and Lena rivers with sub-metre-scale lithostratigraphic subdivisions27,28,29,30,31,32,33 (Figs. 1c, 2a–c, 3a). This results in negligible uncertainty associated with sample heights, which are fixed relative to a consistent datum within each section.Fig. 2: Lithostratigraphy, biostratigraphy and carbon isotope (δ13C) data for sections of the Aldan and Selinde rivers bearing the earlierst archaeocyath reef communities of the Siberian Platform.a Dvortsy27,28,30 b Ulakhan-Sulugur33,34, and c Selinde69,70.Full size imageFig. 3: Summary of geochemical and biotic changes through the early Cambrian, Siberian Platform, and uranium isotope data representing a global record.a International and Siberian timescale, within age model C of 57. ND—Nemakit-Daldynian regional stage; U’-Y—Ust’-Yudoma Formation. b Summary of carbon and sulphur isotopes (from the Lena River, Siberia7). c Uranium isotopes from Siberia (grey; Sukharikha and Bol’shaya Kuonamka rivers), South China (blue), and Morocco (orange) (all data points are larger than 2SE)4. d Archaeocyath sponge species diversity and maximum diameter12. Plotted richness values are the species richness estimator21 with accompanying 95% confidence interval, calculated using the estimated function from R package iNEXT62. e Rates of archaeocyath sponge species origination and extinction12. f Reef location as a function of relative water depth (Supplementary Table 1). FWWB—Fair weather wave base. SWB—Storm weather wave base. g Reef/bioherm diameter, coloured by relative water depth (see column f, and Supplementary Table 2). h Number of reef community types (Supplementary Table 3). i Archaeocyath reef ecosystem complexity, with percentage of species co-occurrence as changing proportions of total non-random and positive and negative. G = Gleasonian, QG = Quasi-Gleasonian, C = Clementsian.Full size imageThroughout Cambrian stages 2 and 3, high-amplitude positive δ13C carbon isotope excursions show a strong positive covariation with the sulphur isotope composition of carbonate-associated sulphate (δ34SCAS) in sections from the Lena River (Fig. 3b)7. The rising limbs of these excursions are interpreted as intervals of progressive burial of reductants under anoxic bottom water conditions, and a progressive increase in atmospheric oxygen7. Coincident δ13C and δ34SCAS peaks (numbered II–VII) correspond with a pulse of atmospheric oxygen into the shallow marine environment (creating an OOE), followed by a corresponding decrease in reductant burial under more widespread marine oxia (falling limbs of δ13C and δ34SCAS), and leading to gradual de-oxygenation over Myr7. In addition, phosphorous retention might have occurred under oxic shallow marine conditions, acting to reduce primary productivity and further oxygenate the shallow marine environment in the short-term ( More

SamplesWe examined 1,022 avian species (~ 10% recorded species) in this study, representing 418 genera, from 91 families (37% recorded families) and 29 orders (73% of all orders). Specimens were from the skin collection of the World Museum Liverpool, Tring Natural History Museum, Manchester Museum and Wollaton Hall Museum, all situated in the United Kingdom. All work was carried out in accordance with ethical regulations at Manchester Metropolitan University and with the permission of all aforementioned museums. Only the best-preserved adult specimens (no signs of cut off feathers or holes in the skin near the beak) were chosen for this study to ensure accurate measurements of bristle length, shape and presence, which should not be affected by the process of skin removal and specimen conservation. Species were randomly chosen, without targeting our sampling towards species known a priori to have bristles. Where possible, two specimens per species were measured (occurring in 82% of all species examined). Specimens of each sex were measured when present; however, this was not always possible since labelling was often inaccurate or missing. In total, the sample included 508 males, 412 females and 374 individuals of unknown sex. Both sexes were examined in 274 species and there was no difference whatsoever between the presence of bristles on male or female species (n = 97 with bristles present and n = 180 with bristles absent for both males and females). Length (Mann–Whitney U test, W = 37,962, N = 552, P = 0.94) and shape (Chi-square test, χ2 = 0, N = 552, df = 3, P = 1) of rictal bristles also did not significantly differ between males and females. Therefore, rictal bristles are likely to be sexually monomorphic and data for males and females was pooled for further analyses. Overall, rictal bristles were absent in 64% of species examined (n = 656) and just over a third of species (n = 366) had bristles present.Bristle descriptionsFacial bristles were initially identified by sight and touch in each specimen. Bristles were recorded as either present or absent from the upper rictal, lorial, lower rictal, narial and interramal regions (Fig. 1a). We use the term ‘rictal bristle’ here for bristles on both the upper rictal and/or the lorial region, since there was no clear differentiation and morphological differences between the bristles found in these regions forming a continuum of bristles above the edge of the beak. When present, rictal bristle shape was recorded as: (i) unbranched rictal bristles, (ii) rictal bristles with barbs only at the base (“Base”) and (iii) branched rictal bristles (“Branched”), i.e. barbs and barbules present along the bristle rachis (Fig. 1b). The three longest rictal bristles were measured on both sides of the head of each specimen using digital callipers, and these lengths were averaged to provide a mean length of rictal bristles per species. In species lacking rictal bristles, a length of “0” and a shape category of “Absent” was recorded.Ancestral reconstruction of facial bristle presenceFollowing Felice et al.19, a single consensus phylogenetic tree was generated from the Hackett posterior distribution of trees from Birdtree.org20 with a sample size of 10,000 post burn-in, using the TreeAnnotator utility in BEAST software21 with a burn-in of 0. Maximum Clade Credibility (MCC) with the option “-heights ca” was selected as the method of reconstruction. The common ancestor trees option (-heights ca) builds a consensus tree by summarising clade ages across all posterior trees. Both the consensus tree and posterior distribution of 10,000 trees were imported into RStudio v. 1.2.5 for R22,23 and pruned so that only species present in the dataset of this study remained in the phylogeny. Taxon names were modified where necessary to match those from the Birdtree.org (http://birdtree.org) species record. Negative terminal branches in our consensus tree were slightly lengthened to be positive using ‘edge.length[tree$edge.length  More

Global statistics on declining biodiversity can give the impression that every population of every species is in a downward spiral. In fact, many populations are stable or growing, while a small number of species faces truly existential challenges. These photos capture some specific crises. They are images of threats unfolding, of desperate attempts at species defence and of the beautiful living world that is at stake.
The 15th United Nations Biodiversity Conference, COP15, opens in Montreal, Canada, on 7 December. At the meeting, delegates will attempt to agree on goals for stabilizing species’ declines by 2030 and reverse them by mid-century. The current draft framework agreement promises nothing less than a “transformation in society’s relationship with biodiversity”.
Help for the kelp. Tasmania’s forests of giant kelp (Macrocystis pyrifera) are dying as climate change shifts ocean currents, bringing warm water to the east coast of the temperate Australian island. The kelp forests host an entire ecosystem, including abalone and crayfish — both economically important species and part of local food culture. Now, researchers at the Institute for Marine and Antarctic Studies in Hobart are breeding kelp plants that can tolerate warmer conditions, and replanting them along the coast — a trial for what they hope will become a landscape-scale restoration. More

Goulson, D., Nicholls, E., Botías, C. & Rotheray, E. L. Bee declines driven by combined stress from parasites, pesticides, and lack of flowers. Science 347, 1255957 (2015).Article 
PubMed 

Google Scholar 
– Potts, S. G., et al. Summary for Policymakers of the Assessment Report of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services on pollinators, pollination, and food production (eds. Potts, S. G. et al.). 36 pages. (Bonn, Germany, 2016).Dolezal, A. G. et al. Interacting stressors matter: Diet quality and virus infection in honeybee health. R. Soc. Open Sci. 6, 181803 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Annoscia, D. et al. Neonicotinoid Clothianidin reduces honeybee immune response and contributes to Varroa mite proliferation. Nat. Commun. 11, 1–7 (2020).Article 

Google Scholar 
Macías-Macías, J. O. et al. Nosema ceranae causes cellular immunosuppression and interacts with thiamethoxam to increase mortality in the stingless bee Melipona colimana. Sci. Rep. 10, 1–8 (2020).Article 

Google Scholar 
Michener, C. D. Pot-honey. In Pot-Honey: A Legacy of Stingless Bees (eds Vit, P. et al.) 3–17 (Springer, 2013).Chapter 

Google Scholar 
Rosa, C. A. et al. Yeast communities associated with stingless bees. FEMS Yeast Res. 4, 271–275 (2003).Article 
PubMed 

Google Scholar 
Menezes, C., Vollet-Neto, A. & Fonseca, V. L. I. An advance in the in vitro rearing of stingless bee queens. Apidologie 44, 491–500 (2013).Article 

Google Scholar 
Morais, P. B., Calaça, P. S. S. T. & Rosa, C. A. Microorganisms associated with stingless bees. In Pot-Honey Bees (eds Vit, P. et al.) 173–186 (Springer, 2013).Chapter 

Google Scholar 
Menegatti, C. et al. Paenibacillus polymyxa associated with the stingless bee Melipona scutellaris produces antimicrobial compounds against entomopathogens. J. Chem. Ecol. 44, 1158–1169 (2018).Article 
PubMed 

Google Scholar 
Paludo, C. R. et al. Stingless bee larvae require fungal steroid to pupate. Sci. Rep. 8, 1122321 (2018).Article 

Google Scholar 
Paludo, C. R. et al. Microbial community modulates growth of symbiotic fungus required for stingless bee metamorphosis. PLoS ONE 14, e0219696 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Hamzah, S. A., Zawawi, N. & Sabri, S. A review on the association of bacteria with stingless bees. Sains Malays. 49, 1853–1863 (2020).Article 

Google Scholar 
de Paula, G. T., Menezes, C., Pupo, M. T. & Rosa, C. A. Stingless bees and microbial interactions. Curr. Opin. Insect Sci. 44, 41–47 (2020).Article 
PubMed 

Google Scholar 
Menezes, C. et al. A Brazilian social bee must cultivate fungus to survive. Curr. Biol. 25, 2851–2855 (2015).Article 
PubMed 

Google Scholar 
– Flechtmann, C. H. W. & de Camargo, C. A. Acari associated with stingless bees (Meliponidae, Hymenoptera) from Brazil. in Proceedings of the 4th International Congress of Acarology, Saalfelden (Austria)/edited by Edward Piffl (Budapest, Akademiai Kiado,1979).Dorigo, A. S. et al. In vitro larval rearing protocol for the stingless bee species Melipona scutellaris for toxicological studies. PLoS ONE 14, e0213109 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Rosa-Fontana, A., Dorigo, A. S., Galaschi-Teixeira, J. S., Nocelli, R. C. F. & Malaspina, O. What is the most suitable native bee species from the neotropical region to be proposed as model-organism for toxicity tests during the larval phase?. Environ. Pollut. 265, 114849 (2020).Article 
PubMed 

Google Scholar 
Miotelo, L., Dos Reis, A. L. M., Malaquias, J. B., Malaspina, O. & Roat, T. C. Apis mellifera and Melipona scutellaris exhibit differential sensitivity to thiamethoxam. Environ. Pollut. 268, 115770 (2021).Article 
PubMed 

Google Scholar 
Rosa, A. E., André, H. & Flechtmann, C. H. W. Acari domun meliponirarum brasiliensium habitantes. Proctotydaeus alvearii 45(1–2), 79–83 (1985).
Google Scholar 
Da-Costa, T., dos Santos, C. F., Rodighero, L. F., Ferla, N. J. & Blochtein, B. Mite diversity is determined by the stingless bee host species. Apidologie 52(5), 950–959. https://doi.org/10.1007/s13592-021-00878-2 (2021).Article 

Google Scholar 
de Rosa, A. S. et al. Consumption of the neonicotinoid thiamethoxam during the larval stage affects the survival and development of the stingless bee Scaptotrigona aff. depilis. Apidologie 47, 729–738 (2016).Article 

Google Scholar 
Wu, J. Y., Anelli, C. M. & Sheppard, W. S. Sub-lethal effects of pesticide residues in brood comb on worker honeybee (Apis mellifera) development and longevity. PLoS One 6, e14720 (2011).Article 
PubMed 
PubMed Central 

Google Scholar 
Tavares, D. A., Roat, T. C., Carvalho, S. M., Silva-Zacarin, E. C. M. & Malaspina, O. In vitro effects of thiamethoxam on larvae of Africanized honeybee Apis mellifera (Hymenoptera: Apidae). Chemosphere 135, 370–378 (2015).Article 
PubMed 

Google Scholar 
Biani, N. B., Mueller, U. G. & Wcislo, W. T. Cleaner mites: sanitary mutualism in the miniature ecosystem of neotropical bee nests. Am. Nat. 173, 841–847 (2009).Article 
PubMed 

Google Scholar 
Gilliam, M., Roubik, D. W. & Lorenz, B. J. Microorganisms associated with pollen, honey, and brood provisions in the nest of a stingless bee Melipona fasciata. Apidologie 21, 89–97 (1990).Article 

Google Scholar 
Rebelo, K. S., Ferreira, A. G. & Carvalho-Zilse, G. A. Physicochemical characteristics of pollen collected by Amazonian stingless bees. Ciência Rural 46, 927–932 (2016).Article 

Google Scholar 
Mohammad, S. M., Mahmud-Ab-Rashid, N.-K. & Zawawi, N. Stingless bee-collected pollen (bee bread): Chemical and microbiology properties and health benefits. Molecules 26, 957 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
da Cruz Landim, C. (2009). Abelhas. Unesp.Rosa, A. S. et al. Quantification of larval food and its pollen content in the diet of stingless bees: Subsidies for toxicity bioassays studies. Braz. J. Biol. 75(3), 771–772. https://doi.org/10.1590/1519-6984.22314 (2015).Article 
PubMed 

Google Scholar 
Vollet-Neto, A., Maia-Silva, C., Menezes, C. & Imperatriz-Fonseca, V. L. Newly emerged workers of the stingless bee Scaptotrigona aff. depilis prefer stored pollen to fresh pollen. Apidologie 48, 204–210 (2017).Article 

Google Scholar 
Hartfelder, K. & Engels, W. The composition of larval food in stingless bees: evaluating nutritional balance by chemosystematic methods. Insect. Soc. 36, 1–14 (1989).Article 

Google Scholar 
Costa, R. A. C. & da Cruz-Landim, C. Distribution of acid phosphatases in the hypopharyngeal glands from workers, queens, and males of a Brazilian stingless bee Scaptotrigona postica Latreille: An ultrastructural cytochemical study. Histochem. J. 33, 653–662 (2001).Article 
PubMed 

Google Scholar 
de Moraes, R. L. M. S., Brochetto-Braga, M. R. & Azevedo, A. Electrophoretical studies of proteins of the hypopharyngeal glands and of the larval food of Melipona quadrifasciata anthidioides Lep. (Hymenoptera, Meliponinae). Insect. Soc. 43, 183–188 (1996).Article 

Google Scholar 
Fernandes-da-Silva, P. G., Muccillo, G. & Zucoloto, F. S. Determination of minimum quantity of pollen and nutritive value of different carbohydrates for Scaptotrigona depilis Moure (Hymenoptera, Apidae). Apidologie 24, 73–79 (1993).Article 

Google Scholar 
Fernandes-da-Silva, P. G. & Serrão, J. E. Nutritive value and apparent digestibility of bee-collected and bee-stored pollen in the stingless bee, Scaptotrigona postica Latr. (Hymenoptera, Apidae, Meliponini). Apidologie 31, 39–45 (2000).Article 

Google Scholar 
Crailsheim, K. & Stolberg, E. Influence of diet, age and colony condition upon intestinal proteolytic activity and size of the hypopharyngeal glands in the honeybee (Apis mellifera L.). J. Insect Physiol. 35, 595–602 (1989).Article 

Google Scholar 
Oliveira, R. A., Roat, T. C., Carvalho, S. M. & Malaspina, O. Side-effects of thiamethoxam on the brain and midgut of the africanized honeybee Apis mellifera (Hymenopptera: Apidae). Environ. Toxicol. 29, 1122–1133 (2014).Article 
PubMed 

Google Scholar 
Christen, V., Schirrmann, M., Frey, J. E. & Fent, K. Global transcriptomic effects of environmentally relevant concentrations of the neonicotinoids clothianidin, imidacloprid, and thiamethoxam in the brain of honeybees (Apis mellifera). Environ. Sci. Technol. 52, 7534–7544 (2018).Article 
PubMed 

Google Scholar 
Moreira, D. R. et al. Toxicity and effects of the neonicotinoid thiamethoxam on Scaptotrigona bipunctata Lepeletier, 1836 (Hymenoptera: Apidae). Environ. Toxicol. 33, 463–475 (2018).Article 
PubMed 

Google Scholar 
Tavares, D. A., Roat, T. C., Silva-Zacarin, E. C. M., Nocelli, R. C. F. & Malaspina, O. Exposure to thiamethoxam during the larval phase affects synapsin levels in the brain of the honeybee. Ecotoxicol. Environ. Saf. 169, 523–528 (2019).Article 
PubMed 

Google Scholar 
Roat, T. C. et al. Using a toxicoproteomic approach to investigate the effects of thiamethoxam into the brain of Apis mellifera. Chemosphere 258, 127362 (2020).Article 
PubMed 

Google Scholar 
Caesar, L. et al. The virome of an endangered stingless bee suffering from annual mortality in southern Brazil. J. Gen. Virol. 100, 1153–1164 (2019).Article 
PubMed 

Google Scholar 
Guimarães-Cestaro, L. et al. Occurrence of virus, microsporidia, and pesticide residues in three species of stingless bees (Apidae: Meliponini) in the field. Sci. Nat. 107, 1–14 (2020).Article 

Google Scholar 
Teixeira, É. W. et al. European Foulbrood in stingless bees (Apidae: Meliponini) in Brazil: Old disease, renewed threat. J. Invertebr. Pathol. 172, 107357 (2020).Article 
PubMed 

Google Scholar 
Alberoni, D., Gaggìa, F., Baffoni, L. & Di Gioia, D. Beneficial microorganisms for honeybees: problems and progresses. Appl. Microbiol. Biotechnol. 100, 9469–9482 (2016).Article 
PubMed 

Google Scholar 
Manley, R., Boots, M. & Wilfert, L. Emerging viral disease risk to pollinating insects: ecological, evolutionary, and anthropogenic factors. J. Appl. Ecol. 52, 331–340 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
Manley, R. et al. Knock- on community impacts of a novel vector: spillover of emerging DWV- B from Varroa- infested honeybees to wild bumblebees. Ecol. Lett. 22, 1306–1315 (2019).PubMed 
PubMed Central 

Google Scholar 
Graystock, P., Blane, E. J., McFrederick, Q. S., Goulson, D. & Hughes, W. O. H. Do managed bees drive parasite spread and emergence in wild bees?. Int. J. Parasitol. Parasit. Wildl. 5, 64–75 (2016).Article 

Google Scholar 
Requier, F. et al. The conservation of native honeybees is crucial. Trends Ecol. Evol. 34, 789–798 (2019).Article 
PubMed 

Google Scholar 
Test No. 237: Honey Bee (Apis Mellifera) Larval Toxicity Test, Single Exposure. (2013). OECD. https://doi.org/10.1787/9789264203723-enMoral, R. A., Hinde, J. & Demétrio, C. G. Half-normal plots and overdispersed models in R: the hnp package. J. Stat. Softw. 81(1), 1–23 (2017).
Google Scholar 
– Kassambara, A. Survminer. GitHub repository. https://github.com/kassambara/survminer (2020).- Therneau, T., Crowson, C., & Atkinson, E. Multi-state models and competing risks. CRAN-R https://cran.r-project.org/web/packages/survival/vignettes/compete (2020). More

Machado, D. et al. Polarization of microbial communities between competitive and cooperative metabolism. Nat. Ecol. Evol. 5, 195–203 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Thompson, L. R. et al. A communal catalogue reveals Earth’s multiscale microbial diversity. Nature 551, 457–463 (2017).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Price, M. Erroneous predictions of auxotrophies by CarveMe. https://doi.org/10.1038/s41559-022-01936-3 (2022).Machado, D., Andrejev, S., Tramontano, M. & Patil, K. R. Fast automated reconstruction of genome-scale metabolic models for microbial species and communities. Nucleic Acids Res. 46, 7542–7553 (2018).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Price, M. N., Deutschbauer, A. M. & Arkin, A. P. GapMind: automated annotation of amino acid biosynthesis. mSystems 5, e00291-20 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Mee, M. T., Collins, J. J., Church, G. M. & Wang, H. H. Syntrophic exchange in synthetic microbial communities. Proc. Natl. Acad. Sci. USA 111, E2149–E2156 (2014).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Ponomarova, O. et al. Yeast creates a niche for symbiotic lactic acid bacteria through nitrogen overflow. Cell Syst. 5, 345–357.e6 (2017).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Zengler, K. & Zaramela, L. S. The social network of microorganisms—how auxotrophies shape complex communities. Nat. Rev. Microbiol. 16, 383–390 (2018).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Giri, S. et al. Metabolic dissimilarity determines the establishment of cross-feeding interactions in bacteria. Curr. Biol. 31, 5547–5557.e6 (2021).Article 
CAS 
PubMed 

Google Scholar 
Morris, J. J., Lenski, R. E. & Zinser, E. R. The black queen hypothesis: evolution of dependencies through adaptive gene loss. mBio 3, e00036-12 (2012).Article 
PubMed 
PubMed Central 

Google Scholar 
Campbell, K. et al. Self-establishing communities enable cooperative metabolite exchange in a eukaryote. eLife 4, e09943 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
D’Souza, G. & Kost, C. Experimental evolution of metabolic dependency in bacteria. PLOS Genet. 12, e1006364 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Ziesack, M. et al. Engineered interspecies amino acid cross-feeding increases population evenness in a synthetic bacterial consortium. mSystems 4, e00352-19 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Ryback, B., Bortfeld-Miller, M. & Vorholt, J. A. Metabolic adaptation to vitamin auxotrophy by leaf-associated bacteria. ISME J. https://doi.org/10.1038/s41396-022-01303-x (2022). More

Whether land acts as a carbon sink or source depends largely on two opposite fluxes: carbon uptake through photosynthesis and carbon release through turnover. Turnover occurs through multiple processes, including but not limited to, leaf senescence, tree mortality, and respiration by plants, microbes, and animals. Each of these processes is sensitive to climate, and ecologists and climatologists have been working to figure out how temperature regulates biological activities and to what extent the carbon cycle responds to global warming. Previous theoretical and experimental studies have yielded conflicting relationships between temperature and carbon turnover, with large variations across ecosystems, climate and time-scale1,2,3,4. Writing in Nature Geoscience, Fan et al.5 find that hydrometeorological factors have an important influence on how the turnover time of land carbon responds to changes in temperature. More

Banerjee, A. K. et al. Setting the priorities straight-Species distribution models assist to prioritize conservation targets for the mangroves. Sci. Total Environ. 806, 150937 (2022).Article 
CAS 

Google Scholar 
Duke, N. C. et al. A world without mangroves?. Science 317(5834), 41–42 (2007).Article 
CAS 

Google Scholar 
Friess, D. A. Ecosystem services and disservices of mangrove forests: Insights from historical colonial observations. Forests 7(9), 183 (2016).Article 

Google Scholar 
Hu, W. et al. Mapping the potential of mangrove forest restoration based on species distribution models: A case study in China. Sci. Total Environ. 748, 142321 (2020).Article 
CAS 

Google Scholar 
Blankespoor, B., Dasgupta, S. & Lange, G. M. Mangroves as a protection from storm surges in a changing climate. Ambio 46(4), 478–491 (2017).Article 

Google Scholar 
FAO. TheWorld’s Mangroves 1980–2005. Food and Agriculture Organization of the United Nations, Rome. http://www.fao.org/3/a1427e/a1427e00.htm. (2007).Abd-El Monsef, H., Hassan, M. A. & Shata, S. Using spatial data analysis for delineating existing mangroves stands and siting suitable locations for mangroves plantation. Comput. Electron. Agric. 141, 310–326 (2017).Article 

Google Scholar 
Donato, D. C. et al. Mangroves among the most carbon-rich forests in the tropics. Nat. Geosci. 4, 293–297. https://doi.org/10.1038/ngeo1123 (2011).Article 
CAS 

Google Scholar 
Aheto, D. W. et al. Community-based mangrove forest management: Implications for local livelihoods and coastal resource conservation along the Volta estuary catchment area of Ghana. Ocean Coast. Manag. 127, 43–54 (2016).Article 

Google Scholar 
Costanza, R. et al. Changes in the global value of ecosystem services. Glob. Environ. Chang. 26, 152–158. https://doi.org/10.1016/j.gloenvcha.2014.04.002 (2014).Article 

Google Scholar 
Stephanie, S. R. et al. Conservation and restoration of mangroves: Global status, perspectives, and prognosis. Ocean Coast. Manag. 154, 72–82. https://doi.org/10.1016/j.ocecoaman.2018.01.009 (2018).Article 

Google Scholar 
Friess, D. A. et al. Mangroves give cause for conservation optimism, for now. Curr. Biol. 30, R153–R154 (2020).Article 
CAS 

Google Scholar 
Valiela, I., Bowen, J. L. & York, J. K. Mangrove forests: One of the world’s threatened major tropical environments: At least 35% of the area of mangrove forests has been lost in the past two decades, losses that exceed those for tropical rain forests and coral reefs, two other well-known threatened environments. Bioscience 51, 807–815. https://doi.org/10.1641/0006-3568(2001)051[0807:MFOOTW]2.0.CO;2 (2001).Article 

Google Scholar 
Feller, I. C. et al. Biocomplexity in mangrove ecosystems. Ann. Rev. Mar. Sci. 2, 395–417 (2010).Article 
CAS 

Google Scholar 
Polidoro, B. A. et al. The loss of species: Mangrove extinction risk and geographic areas of global concern. PLoS ONE 5, e10095 (2010).Article 

Google Scholar 
IUCN. Global Assessments of Mangrove Losses and Degradation, 2016; https://www.iucn.org/sites/dev/files/content/documents/mangroveloss-brief-4pp-19.10.low_.pdf.Sreelekshmi, S., Nandan, S. B., Kaimal, S. V., Radhakrishnan, C. K. & Suresh, V. R. Mangrove species diversity, stand structure and zonation pattern in relation to environmental factors—a case study at Sundarban delta, east coast of India. Reg. Stud. Mar. Sci. 35, 101111 (2020).
Google Scholar 
Sahana, M. et al. Assessing coastal island vulnerability in the Sundarban Biosphere Reserve, India, using geospatial technology. Environ. Earth Sci. 78(10), 1–22 (2019).Article 

Google Scholar 
FSI. India State of Forest Report. Forest Survey of India, Dehradun (2017).Ellison, A. M., Mukherjee, B. B. & Karim, A. Testing patterns of zonation in mangroves: Scale dependence and environmental correlates in the Sundarbans of Bangladesh. J. Ecol. 88(5), 813–824 (2000).Article 

Google Scholar 
Sahana, M., Rehman, S., Sajjad, H. & Hong, H. Exploring effectiveness of frequency ratio and support vector machine models in storm surge flood susceptibility assessment: A study of Sundarban Biosphere Reserve, India. CATENA 189, 104450 (2020).Article 

Google Scholar 
Sahana, M. & Sajjad, H. Vulnerability to storm surge flood using remote sensing and GIS techniques: A study on Sundarban Biosphere Reserve, India. Rem. Sens. Appl. Soc. Env. 13, 106–120 (2019).
Google Scholar 
Chowdhury, M. Q. et al. Nature and periodicity of growth rings in two Bangladeshi mangrove species. IAWA J. 29(3), 265–276 (2008).Article 

Google Scholar 
Sarker, S. K., Reeve, R., Thompson, J., Paul, N. K. & Matthiopoulos, J. Are we failing to protect threatened mangroves in the Sundarbans world heritage ecosystem?. Sci. Rep. 6(1), 1–12 (2016).Article 

Google Scholar 
Iftekhar, M. S. & Saenger, P. Vegetation dynamics in the Bangladesh Sundarbans mangroves: A review of forest inventories. Wetlands Ecol. Manage. 16(4), 291–312 (2008).Article 

Google Scholar 
Siddiqi, N. A. In Mangrove forestry in Bangladesh, Institute of Forestry and Environmental Sciences. University of Chittagong, Chittagong, Bangladesh 201 (2001).Lewis, R. R. III. Ecological engineering for successful management and restoration of mangrove forests. Ecol. Eng. 24(4), 403–418 (2005).Article 

Google Scholar 
Peterson, T. A., Papeş, M. & Eaton, M. Transferability and model evaluation in ecological niche modeling: A comparison of GARP and Maxent. Ecography 30, 550–560. https://doi.org/10.1111/j.0906-7590.2007.05102.x (2007).Article 

Google Scholar 
Stockwell, D. & Peters, D. The GARP modelling system: problems and solutions to automated spatial prediction. Int. J. Geogr. Inf. Sci. 13, 143–158. https://doi.org/10.1080/136588199241391 (1999).Article 

Google Scholar 
Guisan, A. & Thuiller, W. Predicting species distribution: Offering more than simple habitat models. Ecol. Lett. 8, 993–1009. https://doi.org/10.1111/j.1461-0248.2005.00792.x (2005).Article 

Google Scholar 
Phillips, S. J., Anderson, R. P. & Schapire, R. E. Maximum entropy modeling of species geographic distributions. Ecol. Model. 190, 231–259. https://doi.org/10.1016/j.ecolmodel.2005.03.026 (2006).Article 

Google Scholar 
Feng, Z. et al. Dynamics ofmangrove forests in Shenzhen Bay in response to natural and anthropogenic factors from 1988 to 2017. J. Hydrol. 591, 125271. https://doi.org/10.1016/j.jhydrol.2020.125271 (2020).Article 

Google Scholar 
Kaky, E. & Gilbert, F. Using species distribution models to assess the importance of Egypt’s protected areas for the conservation of medicinal plants. J. Arid Environ. 135, 140–146. https://doi.org/10.1016/j.jaridenv.2016.09.001 (2016).Article 

Google Scholar 
Pecchi, M. et al. Species distribution modelling to support forest management A literature review. Ecol. Model. 411, 108817 (2019).Article 

Google Scholar 
Spiers, J. A., Oatham, M. P., Rostant, L. V. & Farrell, A. D. Applying species distribution modelling to improving conservation-based decisions: A gap analysis of Trinidad and Tobago’s endemic vascular plants. Biodivers. Conserv. 27, 2931–2949 (2018).Article 

Google Scholar 
Elith, J. & Leathwick, J. R. Species distribution models: Ecological explanation and prediction across space and time. Annu. Rev. Ecol. Evol. Syst. 40, 677–697. https://doi.org/10.1146/annurev.ecolsys.110308.120159 (2009).Article 

Google Scholar 
Fois, M., Cuena-Lombraña, A., Fenu, G. & Bacchetta, G. Using species distribution models at local scale to guide the search of poorly known species: Review, methodological issues and future directions. Ecol. Model. 385, 124–132 (2018).Article 

Google Scholar 
Gilani, H., Goheer, M. A., Ahmad, H. & Hussain, K. Under predicted climate change: Distribution and ecological niche modelling of six native tree species in Gilgit-Baltistan, Pakistan. Ecol. Indic. 111, 106049 (2020).Article 

Google Scholar 
Ellison, A. M., Felson, A. J. & Friess, D. A. Mangrove rehabilitation and restoration as experimental adaptive management. Front. Mar. Sci. 7, 327. https://doi.org/10.3389/fmars.2020.00327 (2020).Article 

Google Scholar 
Ellison, A. M. Mangrove restoration: Do we know enough?. Restor. Ecol. 8(3), 219–229 (2000).Article 

Google Scholar 
Brown, B., Fadillah, R., Nurdin, Y., Soulsby, I., & Ahmad, R. CASE STUDY: Community Based Ecological Mangrove Rehabilitation (CBEMR) in Indonesia. In From small (12–33 ha) to medium scales (400 ha) with pathways for adoption at larger scales ( > 5000 ha). SAPI EN. S. Surveys and Perspectives Integrating Environment and Society 7.2 (2014).Rodríguez-Rodríguez, J. A., Mancera-Pineda, J. E. & Tavera, H. Mangrove restoration in Colombia: Trends and lessons learned. For. Ecol. Manage. 496, 119414 (2021).Article 

Google Scholar 
Romañach, S. S. et al. Conservation and restoration
of mangroves: Global status, perspectives, and prognosis. Ocean Coast Manag. 154, 72–82. https://doi.org/10.1016/j.ocecoaman.2018.01.009 (2018).Article 

Google Scholar 
Sulochanan, B. et al. Water and sediment quality parameters of the restored mangrove ecosystem of Gurupura River and natural mangrove ecosystem of Shambhavi River in Dakshina Kannada, India. Marine Pollution Bulletin 176, 113450. https://doi.org/10.1016/j.marpolbul.2022.113450 (2022).Lovelock, C. E., Barbier, E. & Duarte, C. M. Tackling the mangrove restoration challenge. PLoS Biol. 20(10), e3001836 (2022).Article 
CAS 

Google Scholar 
Lovelock, C. E. & Brown, B. M. Land tenure considerations are key to successful mangrove restoration. Nature Ecol. Evol. 3(8), 1135–1135 (2019).Article 

Google Scholar 
Su, J., Friess, D. A. & Gasparatos, A. A meta-analysis of the ecological and economic outcomes of mangrove restoration. Nat. Commun. 12(1), 1–13 (2021).Article 

Google Scholar 
Lee, S. Y., Hamilton, S., Barbier, E. B., Primavera, J. & Lewis, R. R. Better restoration policies are needed to conserve mangrove ecosystems. Nature Ecol. Evol. 3(6), 870–872 (2019).Article 

Google Scholar 
Chakraborty, S., Sahoo, S., Majumdar, D., Saha, S. & Roy, S. Future Mangrove suitability assessment of Andaman to strengthen sustainable development. J. Clean. Prod. 234, 597–614 (2019).Article 

Google Scholar 
Charrua, A. B., Bandeira, S. O., Catarino, S., Cabral, P. & Romeiras, M. M. Assessment of the vulnerability of coastal mangrove ecosystems in Mozambique. Ocean Coast. Manag. 189, 105145 (2020).Article 

Google Scholar 
Hu, W. et al. Predicting potential mangrove distributions at the global northern distribution margin using an ecological niche model: Determining conservation and reforestation involvement. For. Ecol. Manage. 478, 118517 (2020).Article 

Google Scholar 
Rodríguez-Medina, K., Yañez-Arenas, C., Peterson, A. T., Euán Ávila, J. & Herrera-Silveira, J. Evaluating the capacity of species distribution modeling to predict the geographic distribution of the mangrove community in Mexico. PLoS ONE 15(8), e0237701 (2020).Article 

Google Scholar 
Wang, Y. et al. Simulating spatial change of mangrove habitat under the impact of coastal land use: Coupling MaxEnt and Dyna-CLUE models. Sci. Total Environ. 788, 147914 (2021).Article 
CAS 

Google Scholar 
Gopal, B. & Chauhan, M. Biodiversity and its conservation in the Sundarban mangrove ecosystem. Aquat. Sci. 68(3), 338–354 (2006).Article 

Google Scholar 
Sahana, M., Rehman, S., Paul, A. K. & Sajjad, H. Assessing socio-economic vulnerability to climate change-induced disasters: Evidence from Sundarban Biosphere Reserve, India. Geol. Ecol. Landsc. 5(1), 40–52 (2021).Article 

Google Scholar 
Giri, C. et al. Mangrove forest distributions and dynamics (1975–2005) of the tsunami-affected region of Asia. J. Biogeogr. 35(3), 519–528 (2008).Article 

Google Scholar 
Giri, C., Pengra, B., Zhu, Z., Singh, A. & Tieszen, L. L. Monitoring mangrove forest dynamics of the Sundarbans in Bangladesh and India using multi-temporal satellite data from 1973 to 2000. Estuar. Coast. Shelf Sci. 73(1–2), 91–100 (2007).Article 

Google Scholar 
Islam, S. N. & Gnauck, A. Effects of salinity intrusion in mangrove wetlands ecosystems in the Sundarbans: An alternative approach for sustainable management. Wetlands Monitor. Modell. Manag. 2007, 315 (2007).
Google Scholar 
Hazra, S., Ghosh, T., DasGupta, R. & Sen, G. Sea level and associated changes in the Sundarbans. Sci. Cult. 68(9/12), 309–321 (2002).
Google Scholar 
Purkait, B. Coastal erosion in response to wave dynamics operative in Sagar Island, Sundarban delta, India. Front. Earth Sci. China 3(1), 21–33 (2009).Article 

Google Scholar 
World Bank (2014). Building resilience for sustainable development of the Sundarbans: Strategy report (No. 20116; World Bank Other Operational Studies). The World Bank Group. https://ideas.repec.org/p/wbk/wboper/20116.html.Das, M. A. H. U. A. Impact of commercial coastal fishing on the environment of Sundarbans for sustainable development. Asian Fish. Sci. 22(1), 157–167 (2009).
Google Scholar 
Hoq, M. E. An analysis of fisheries exploitation and management practices in Sundarbans mangrove ecosystem, Bangladesh. Ocean Coast. Manag. 50(5–6), 411–427 (2007).Article 

Google Scholar 
Census of India (2011). Primary census abstract, census of India. The government of India, Registrar General and Census Commissioner of India, Ministry of Home Affairs, New Delhi, India. https://censusindia.gov.in/nada/index.php/catalog/41021Chowdhury, A. & Maiti, S. K. Assessing the ecological health risk in a conserved mangrove ecosystem due to heavy metal pollution: A case study from Sundarbans Biosphere Reserve, India. Hum. Ecol. Risk Assess. Int. J. 22(7), 1519–1541 (2016).Article 
CAS 

Google Scholar 
Hajra, R. et al. Unravelling the association between the impact of natural hazards and household poverty: Evidence from the Indian Sundarban delta. Sustain. Sci. 12(3), 453–464 (2017).Article 

Google Scholar 
Sahana, M. & Sajjad, H. Assessing Influence of Erosion and Accretion on Landscape Diversity in Sundarban Biosphere Reserve, Lower Ganga Basin: A Geospatial Approach. In Quaternary Geomorphology in India, (eds Das, B. et al.) (Springer, Cham, 2019). https://doi.org/10.1007/978-3-319-90427-6_10 (2018).Chaudhuri, A. B., Choudhury, A., Hussain, Z., & Acharya, G. Mangroves of the Sundarbans. Vol. I. India, The IUCN Wetlands Programme 247 (IUCN, 1994).GBIF.org. GBIF Occurrence Download, 2018. https://www.gbif.org/. Avicennia marina: https://doi.org/10.15468/dl.vmlooq and R. mucronata: https://doi.org/10.15468/dl.ewnqnm (accessed March 2019).Mandal, R. N. & Naskar, K. R. Diversity and classification of Indian mangroves: A review. Trop. Ecol. 49(2), 131–146 (2008).
Google Scholar 
Mandal, A. K., & Nandi, N. C. Fauna of Sundarban mangrove ecosystem, west Bengal, India, Vol. 3 (Zoological Survey of India, 1989).Mitra, A. & Pal, S. The Oscillating Mangrove Ecosystem and the Indian Sundarbans (WWF-India-WBSO, 2002).Naskar, K., & Guha Bakshi, D. N. Mangrove Swamps of the Sundarbans (Naya Prokash, 1987).Barik, J. & Chowdhury, S. True mangrove species of Sundarbans delta, West Bengal, eastern India. Check list 10(2), 329–334. https://doi.org/10.15560/10.2.329 (2014).IUCN 2018. The IUCN Red List of Threatened Species. Version 2018. 2018. Electronic database accessible, accessed 15 Nov 2018; http://www.iucnredlist.org.Guyon, I. & Elisseeff, A. An introduction to variable and feature selection. J. Mach. Learn. Res. 3, 1157–1182 (2003).MATH 

Google Scholar 
Cavanaugh, K. C. et al. Climate-driven regime shifts in a mangrove–salt marsh ecotone over the past 250 years. Proc. Natl. Acad. Sci. 116(43), 21602–21608 (2019).Article 
CAS 

Google Scholar 
Naskar, K. & Mandal, R. Ecology and Biodiversity of Indian Mangroves, Vol. 1 (Daya Books, 1999).Figueiredo, F. O. et al. Beyond climate control on species range: The importance of soil data to predict distribution of Amazonian plant species. J. Biogeogr. 45(1), 190–200 (2018).Article 

Google Scholar 
Booth, T. H., Nix, H. A., Busby, J. R. & Hutchinson, M. F. BIOCLIM: The first species distribution modelling package, its early applications and relevance to most current MAXENT studies. Divers. Distrib. 20(1), 1–9 (2014).Article 

Google Scholar 
Asbridge, E., Lucas, R., Ticehurst, C. & Bunting, P. Mangrove response to environmental change in Australia’s Gulf of Carpentaria. Ecol. Evol. 6(11), 3523–3539 (2016).Article 

Google Scholar 
He, Q. & Silliman, B. R. Climate change, human impacts, and coastal ecosystems in the Anthropocene. Curr. Biol. 29(19), R1021–R1035. https://doi.org/10.1016/j.cub.2019.08.042 (2019).Beaumont, L. J., Hughes, L. & Poulsen, M. Predicting species distributions: Use of climatic parameters in BIOCLIM and its impact on predictions of species’ current and future distributions. Ecol. Model. 186(2), 251–270 (2005).Article 

Google Scholar 
Guisan, A., Thuiller, W. & Zimmermann, N. E. Habitat Suitability and Distribution Models: With Applications in R (Cambridge University Press, 2017).Book 

Google Scholar 
Boyce, M. S., Vernier, P. R., Nielsen, S. E. & Schmiegelow, F. K. A. Evaluating resource selection functions. Ecol. Model. 157, 281–300 (2002).Article 

Google Scholar 
STR Annual Report. In Conservator of Forest & Field Director, Sundarban Tiger Reserve. Canning, West Bengal, India: Directorate of Forests, Government of West Bengal (2013–2014).Segurado, P. & Araujo, M. B. An evaluation of methods for modelling species distributions. J. biogeogr. 31(10), 1555–1568. https://doi.org/10.1111/j.1365-2699.2004.01076.x (2004).Kadmon, R., Farber, O. & Danin, A. A systematic analysis of factors affecting the performance of climatic envelope models. Ecol. Appl. 13(3), 853–867. https://doi.org/10.1890/1051-0761(2003)013[0853:ASAOFA]2.0.CO;2 (2003).Wisz, M. S. et al. Effects of sample size on the performance of species distribution models. Divers. distribut. 14(5), 763–773. https://doi.org/10.1111/j.1472-4642.2008.00482.x (2008).Simard, M. et al. Mangrove canopy height globally related to precipitation, temperature and cyclone frequency. Nat. Geosci. 12(1), 40–45 (2019).Article 
CAS 

Google Scholar 
Hoguane, A. M., Hill, A. E., Simpson, J. H. & Bowers, D. G. Diurnal and tidal variation of temperature and salinity in the Ponta Rasa mangrove swamp, Mozambique. Estuar. Coast. Shelf S. 49(2), 251–264. https://doi.org/10.1006/ecss.1999.0499 (1999).  Article 
CAS 

Google Scholar 
Sanders, C. J. et al. Are global mangrove carbon stocks driven by rainfall? J. Geophys. Res. Biogeosci. 121(10), 2600–2609. https://doi.org/10.1002/2016JG003510 (2016).Srivastava, J., Farooqui, A. & Seth, P. Pollen-vegetation relationship in surface sediments, Coringa mangrove ecosystem, India: palaeoecological applications. Palynology 43(3), 451–466. https://doi.org/10.1080/01916122.2018.1458755 (2019).Nandy, P., Das, S., Ghose, M. & Spooner-Hart, R. Effects of salinity on photosynthesis, leaf anatomy, ion accumulation and photosynthetic nitrogen use efficiency in five Indian mangroves. Wetlands Ecol. Manage. 15(4), 347–357 (2007).Article 
CAS 

Google Scholar 
Washington, W., Kathiresan, K. & Bingham, B. L. Biology of mangroves and mangrove ecosystems. Adv. Mar. Biol. 2001, 40 (2001).
Google Scholar 
Blasco, F., Aizpuru, M. & Gers, C. Depletion of the mangroves of Continental Asia. Wetlands Ecol. Manage. 9(3), 255–266 (2001).Article 

Google Scholar 
Datta, D. & Deb, S. Forest structure and soil properties of mangrove ecosystems under management scenarios: Experiences from the intensely humanized landscape of Indian Sunderbans. Ocean Coast. Manag. 140, 22–33 (2017).Article 

Google Scholar 
Wahid, S. M., Babel, M. S. & Bhuiyan, A. R. Hydrologic monitoring and analysis in the Sundarbans mangrove ecosystem, Bangladesh. J. Hydrol. 332(3–4), 381–395 (2007).Article 

Google Scholar 
Iftekhar, M. S. & Islam, M. R. Degeneration of Bangladesh’s Sundarbans mangroves: A management issue. Int. For. Rev. 6(2), 123–135 (2004).
Google Scholar 
Saenger, P. Mangrove Ecology, Silviculture, and Conservation (Kluwer Academic Publishers, 2002).Book 

Google Scholar 
Feka, Z. N. Sustainable management of mangrove forests in West Africa: A new policy perspective?. Ocean Coast. Manag. 116, 341–352. https://doi.org/10.1016/j.ocecoaman.2015.08.006 (2015).Article 

Google Scholar 
Giri, S. et al. A study on abundance and distribution of mangrove species in Indian Sundarban using remote sensing technique. J. Coast Conserv. 18, 359–367. https://doi.org/10.1007/s11852-014-0322-3 (2014).Article 

Google Scholar 
Moschetto, F. A., Ribeiro, R. B. & De Freitasa, D. M. Urban expansion, regeneration and socioenvironmental vulnerability in a mangrove ecosystem at the southeast coastal of São Paulo, Brazil. Ocean Coast. Manag. 24, 105418. https://doi.org/10.1016/j.ocecoaman.2020.105418 (2020).Article 

Google Scholar 
Tuholskea, C., Tane, Z., López-Carra, D., Roberts, D. & Cassels, S. Thirty years of land use/cover change in the Caribbean: Assessing the relationship between urbanization and mangrove loss in Roatán, Honduras. Appl. Geogr. 88, 84–93. https://doi.org/10.1016/j.apgeog.2017.08.018 (2017).Article 

Google Scholar 
Kantharajan, G. et al. Vegetative structure and species composition of mangroves along the Mumbai coast, Maharashtra, India. Reg. Stud. Mar. Sci. 19, 1–8 (2018).
Google Scholar 
Marcinko, C. L. et al. The development of a framework for the integrated assessment of SDG trade-offs in the Sundarban Biosphere Reserve. Water 13(4), 528 (2021).Article 

Google Scholar 
Sahana, M. et al. Assessing Wetland ecosystem health in Sundarban Biosphere Reserve using pressure-state-response model and geospatial techniques. Remot. Sens. Appl. Soc. Environ. 26, 100754. https://doi.org/10.1016/j.rsase.2022.100754 (2022).Saha, S., & Choudhury, A. Vegetation Analysis of Restored And Natural Mangrove Forest In Sagar Island, Sundarbans, East Coast of India. Indian J. Mar. Sci. 24, 133–136. http://nopr.niscpr.res.in/bitstream/123456789/37297/1/IJMS%2024%283%29%20133-136.pdf (1995).Balke, T. & Friess, D. A. Geomorphic knowledge for mangrove restoration: A pantropical categorization. Earth Surf. Process. Landf. 41, 231–239. https://doi.org/10.1002/esp.3841 (2016).Article 

Google Scholar 
Alongi, D. M. Mangrove forests of timor-leste: Ecology, degradation and vulnerability to climate change. In Mangrove ecosystems of Asia 199–212 (Springer, 2014).Biswas, S. R., Mallik, A. U., Choudhury, J. K. & Nishat, A. A unified framework for the restoration of Southeast Asian mangroves—bridging ecology, society and economics. Wetlands Ecol. Manage. 17(4), 365–383 (2009).Article 

Google Scholar 
Dubey, S. K., Censkowsky, U., Roy, M., Chand, B. K., & Dey, A. Framework for rapid evaluation of a mangrove restoration site: A case study from Indian Sundarban. In Sabkha Ecosystems 363–378 (Springer, 2019).Islam, M. M. & Shamsuddoha, M. Coastal and marine conservation strategy for Bangladesh in the context of achieving blue growth and sustainable development goals (SDGs). Environ. Sci. Pol. 87, 45–54. https://doi.org/10.1016/j.envsci.2018.05.014 (2018).Article 

Google Scholar 
Bosire, J., Celliers, L., Groeneveld, J., Paula, J. & Schleyer, M.H. Regional State of the Coast Report-Western Indian Ocean. UNEP-Nairobi Convention and WIOMSA 546 (2015).Owuor, M. A., Mulwa, R., Otieno, R., Icely, J. & Newton, A. Valuing mangrove biodiversity and ecosystem services: A deliberative choice experiment in Mida Creek, Kenya. Ecosyst. Serv. 40, 101040. https://doi.org/10.1016/j.ecoser.2019.101040 (2019).Article 

Google Scholar 
Barwell, L. et al. (2018). Regional
State of the Coast Report Western Indian Ocean. The United Nations Environment
Programme/Nairobi Convention Secretariat. https://wedocs.unep.org/handle/20.500.11822/9700?show=fullde Jesús Arce-Mojica, T., Nehren, U., Sudmeier-Rieux, K., Miranda, P. J. & Anhuf, D. Nature-based solutions (NbS) for reducing the risk of shallow landslides: where do we stand? Int. J. disaster risk reduct. 41, 101293. https://doi.org/10.1016/j.ijdrr.2019.101293 (2019).Bardhan, M. An empirical study on mangrove restoration in Indian Sundarbans—a community-based environmental approach. In Modern Cartography Series, vol. 10 387–405 (Academic Press, 2021).Kumar, M. C., Bholanath, M. & Debashis, S. Study on utility and revival through community approach in sundarbans mangrove. Int. J. Soc. Sci. https://doi.org/10.5958/2321-5771.2014.00101.X (2014).Article 

Google Scholar 
Chakraborty, S. K., Giri, S., Chakravarty, G. & Bhattacharya, N. Impact of eco-restoration on the biodiversity of Sundarbans Mangrove Ecosystem, India. Water Air Soil Pollut. Focus 9(3), 303–320 (2009).Article 

Google Scholar 
Paulson Institute. Research report on mangrove protection and restoration strategy in China, 2020; https://paulsoninstitute.org.cn/wpcontent/uploads/2020/06/%E4%B8%AD%E5%9B%BD%E7%BA%A2%E6%A0%91%E6%9E%97%E4%BF%9D%E6%8A%A4%E4%B8%8E%E6%81%A2%E5%A4%8D%E6%88%98%E7%95%A5%E7%A0%94%E7%A9%B6%E6%8A%A5%E5%91%8A%E2%80%94%E6%91%98%E8%A6%81%E7%89%88.pdf.Fan, H. Q. & Wang, W. Q. Some thematic issues for mangrove conservation in China. J. Xiamen Univ. Nat. Sci 56, 323–330. https://doi.org/10.6043/j.issn.0438-0479.201612003 (2017).Article 

Google Scholar 
Wang, W., Fu, H., Lee, S. Y., Fan, H. & Wang, M. Can strict protection stop the decline of mangrove ecosystems in China? Fromrapid destruction to rampant degradation. Forests 11, 55. https://doi.org/10.3390/f11010055 (2020).Article 

Google Scholar 
Roy, A. K. D. & Alam, K. Participatory forest management for the sustainable management of the sundarbans mangrove forest. Am. J. Env. Sci. 8(5), 549–555. https://doi.org/10.3844/ajessp.2012.549.555 (2012).Article 

Google Scholar 
Selvam, V. et al. In Toolkit for establishing coastal bioshield. M. S. Swaminathan Research Foundation, Centre for Research on Sustainable Agriculture and Rural Development (2005).Raju, J. S. S. N. Xylocarpus (Meliaceae): A less-known mangrove taxon of the Godavari estuary, India. Curr. Sci. 84(7), 879–881. https://www.currentscience.ac.in/Volumes/84/07/0879.pdf (2003).
Google Scholar 
Siddiqui, A. H. & Khair, A. Infestation status of heart rot disease of pasur (Xylocarpus mekongensis), tree in the sundarbans. Indian For. 138(2), 165–168 (2012).
Google Scholar 
Iqbal, M. & Hossain, M. Tourists’ willingness to pay for restoration of Sundarbans Mangrove forest ecosystems: A contingent valuation modeling study. Env. Dev. Sustain. 2022, 1–22 (2022).
Google Scholar 
Ekka, A. & Pandit, A. Willingness to pay for restoration of natural ecosystem: A study of Sundarban mangroves by contingent valuation approach. Indian J. Agric. Econ. 67, 902 (2012).
Google Scholar 
Datta, D., Chattopadhyay, R. N. & Guha, P. Community based mangrove management: A review on status and sustainability. J. Env. Manag. 107, 84–95. https://doi.org/10.1016/j.jenvman.2012.04.013 (2012).Article 

Google Scholar 
Ghosh, A., Schmidt, S., Fickert, T. & Nusser, M. The Indian Sundarban mangrove forests: History, utilization, conservation strategies and local perception. Diversity 7(2), 149–169. https://doi.org/10.3390/d7020149 (2015).Article 
CAS 

Google Scholar 
Ranjan, R. Optimal mangrove restoration through community engagement on coastal lands facing climatic risks: The case of Sundarbans region in India. Land Use Policy 81, 736–749 (2019).Article 

Google Scholar 
Dutta, M., Roy, S. & Nibirh, S. Joint forest management and forest protection committees: Negotiation systems and the design of incentives—a case study of West Bengal. Electron. J. https://doi.org/10.2139/ssrn.2245965 (2001).Article 

Google Scholar 
McKee, K. L., Rooth, J. E. & Feller, I. C. Mangrove recruitment after forest disturbance is facilitated by herbaceous species in the Caribbean. Ecol. Appl. 17(6), 1678–1693 (2007).Article 

Google Scholar 
Begam, M. et al. Native salt-tolerant grass species for habitat restoration, their acclimation and contribution to improving edaphic conditions: A study from a degraded mangrove in the Indian Sundarbans. Hydrobiologia 803(1), 373–387 (2017).Article 
CAS 

Google Scholar 
Donnelly, M. & Walters, L. Trapping of Rhizophora mangle propagules by coexisting early successional species. Estuaries Coasts 37, 1562–1571 (2014).Article 

Google Scholar 
Ren, H. et al. Sonneratia apetala Buch. Ham in the mangrove ecosystems of China: An invasive species or restoration species?. Ecol. Eng. 35(8), 1243–1248 (2009).Article 

Google Scholar 
Cheong, S.-M. et al. Coastal adaptation with ecological engineering. Nature Clim. Change 3, 787–791. https://doi.org/10.1038/nclimate1854 (2013).Article 

Google Scholar  More