Ecology

This is the first study analyzing mandible shape in both mink species and, together with a previous study on their cranial shape38, it has revealed how small morphological differences in highly similar species can lead to substantial biomechanical differences (see breakdown below). As with cranial shape, mandible shape in minks is influenced by the complex interaction of size and sexual dimorphism both at the inter- and intraspecific levels. However, while in cranial shape both species had divergent shape allometries and parallel interspecific sexual allometries, the opposite was true for mandible shape.Differences in mandible shape between European and American mink were summarized by PC1 (Fig. 2, Fig. S1) and can be mainly related to muscle size and jaw biomechanics (i.e., in-levers and out-levers). The relatively taller and slightly wider coronoid process of European minks suggests a relatively larger temporalis muscle, while the anteriorly expanded masseteric fossa of American mink is indicative of a relatively larger masseter complex17,22,25. The relatively enlarged angular process of European mink provides a larger attachment area for the superficial masseter, with both mink species having a distinctive fossa on the lateral side of the angular process where this muscle attaches. This angular fossa is not present in European polecats (Gálvez-López, pers. obs.), part of the sister clade to European mink41.Regarding jaw biomechanics, the particular morphology of the American mink illustrates the compromise between maximizing both bite force efficiency and increased gape. The MAs for all masticatory muscles were higher in European mink due to their relatively longer in-levers (and also shorter out-levers if measured on PC1 configurations), with the exception of the MA of the deep masseter which was considerably higher in American mink (Table S2; Fig. 1D). These findings indicate that American mink exhibit features that allow them to produce larger forces at wide gape, which is particularly useful for holding and killing terrestrial vertebrates22,42. In agreement with this, a short moment arm of the superficial masseter (as observed in American mink) has been associated with increased gape in other mammals43. It is also worth noting that low MAs for the posterior temporalis and superficial masseter have also been associated with fish capture, as they indicate a relatively longer mandible relative to the muscle in-levers, which in turn allows the mouth to close faster when trying to catch elusive prey underwater21. In contrast, the characteristic features of European mink are indicative of stronger bites at the carnassials, which would allow them to cut through relatively tougher tissues and also to crush harder objects (e.g. shells of aquatic prey). Favoring carnassial over anterior bites could also be advantageous to feeding on fish. Mink catch fish underwater by grabbing them by the fins or back with their anterior teeth, and then dragging them to the surface where they are processed using cheek (carnassial) bites (Gálvez-López, pers. obs.).In our previous study on cranial shape in mink38, morphological differences between both species indicated relatively larger muscle volumes overall in the American mink (temporalis: more developed sagittal and nuchal crests, narrower braincase; masseter: longer and more curved zygomatic arches, larger infratemporal fossa), which suggested that bite forces both at the anterior dentition and at the carnassials were larger in this species. However, when combined with the MA results from this study on mandible shape, the relationship between muscle volume and force production becomes less straightforward. In the case of the European mink, the relatively smaller temporalis has a larger attachment site on the mandible (i.e., a broader and taller coronoid) and becomes more efficient (i.e., has higher MAs) due to the relatively longer in-lever. Similarly, in the American mink the effective length of the superficial masseter is increased by the marked curvature of the zygomatic arches, which mitigates the dorsal displacement of the angular process. However, the efficiency of the relatively larger temporalis is diminished by a smaller coronoid (i.e., reduced attachment area and shorter in-levers). The remaining differences in cranial morphology align with differences in mandible shape. Namely, the relatively broader zygomatic arches of the European mink support a strong superficial masseter, while the larger infratemporal fossae of American mink account for their enlarged deep masseter. On a final note, another finding common to both cranial and mandible shape was the relatively larger crushing dentition of American mink.Thus, after combining the results of cranial and mandible shape, it appears that, while the characteristic features of European mink indeed allow stronger carnassial bites, American mink present morphological indicators of both strong killing bites at wide gapes and powerful carnassial bites with a marked crushing component.The allometric effect on mandible size common to both species was represented by PC2 (Fig. 2, Fig. S3), which complements the common allometric trend recovered for both mink species in cranial shape38. The relative expansion of the masseteric fossa and the angular process with increasing size suggests that larger mink present a larger masseter complex. However, most of the allometric shape changes are related to muscle in-levers and out-levers. With increasing size, the length of both the out-lever at the anterior teeth and the in-levers of its related muscles (anterior temporalis, deep masseter) increases (Table S2), but the in-levers scale faster than the out-lever (Table S2). Thus, the mechanical advantages of both muscles at the anterior teeth also increase with size (Table S2), indicating that larger mink have markedly stronger and more efficient killing bites (particularly true for the deep masseter, which also becomes larger with size). This, together with their relatively larger anterior dentition (both in the mandible and the cranium) and taller anterior corpus, can be related to feeding on larger prey as size increases (i.e., stronger bites to perforate tougher skulls and hold onto stronger struggling prey, which would also require more robust teeth and corpora to resist the stresses placed on them). Similar features have been described for felids18, which also kill prey in this way22,32.Note, however, that one of the shape changes along PC2 does not accurately reflect the common allometric pattern: the lever arm of the superficial masseter, which slightly decreases along PC2 (Fig. 2; Table S2) and results in a decrease of the mechanical advantage of the superficial masseter and hence bite force at the carnassials along this axis (Table S2). In contrast, this lever arm significantly increases with size in the original specimens (Table S2), in agreement with the common allometric trend in cranial shape suggesting stronger bites at all teeth with increasing size38. A likely explanation for this phenomenon is that the common allometric trend is being confounded with interspecific shape differences, as American mink have significantly shorter superficial masseter in-levers than European mink (Fig. 1F; Table S2) yet their males are significantly larger than all other specimens (Fig. 1A). As mentioned above, the relative decrease in MA might reflect the trade-off between producing strong bite forces at the anterior teeth and having a wider gape to capture larger prey43, both of which are heavily supported by other morphological features in this common allometric trend.Sexual dimorphism in mandible shape was significant both within each species, and when grouping sexes from both species together. In her study of Palearctic mustelids, Romaniuk28 also found evidence for interspecific sexual dimorphism in mandible shape, but within species it was only significant for the Siberian weasel (Mustela sibirica). The different results for the European mink in that study might be related to its smaller sample. Note, however, that Hernández-Romero et al.40 did not find evidence for sexual dimorphism in mandible shape within Neotropical otters (Lontra longicaudis) even though their sample sizes were equivalent to those in the present study.Overall, the results of the present study reveal that mandible shape differences between males and females are the consequence of a complex interaction between sex and size at both inter- and intraspecific levels. For instance, each sex in each species has a mandible shape significantly different from each other (Table 1), but allometric shape changes within each of them are similar (except maybe female American mink; Fig. S5A). Additionally, while trajectory analysis indicates that the degree of sexual dimorphism in mandible shape is similar within each species, the specific differences between sexes are different in each species (i.e., same magnitude, different orientation; Table 2, Fig. S5B). While at the interspecific level, male and female mandible shapes change differently with increasing size even though the change per unit size is similar in both sexes (Tables 1, 2; Fig. S5C,D), and some of the allometric changes are common to both species and sexes (see section above; PC2 in Fig. 2). Finally, another set of shape changes related to sexual dimorphism and common to both species are those related to sexual dimorphism in mandible size, illustrated by PC3 (Figs. 2, Fig. S4).Shape changes related to sexual dimorphism in size are represented along PC3 and can be related to an overall increase in bite force (i.e., at all teeth), as higher scores on this axis correspond to increased muscle attachment areas and longer in-levers (taller and wider coronoid, anteriorly expanded masseteric fossa, ventrally expanded angular process), shorter out-levers (particularly at the anterior teeth), and a more robust corpus (dorsoventrally and mediolaterally expanded). This interpretation of shape changes along PC3 is supported by the results of the ANOVAs on the lever arms and MAs measured on the PC3 configurations (Table S2). These variables were only related to sex and size, with female mink having longer out-levers and male mink presenting longer in-levers and higher MAs, while out-levers decreased with increasing size and in-levers and MAs increased in both sexes (no significant interaction between sex and size indicates parallel allometric trajectories in both sexes). This trend is consistent with the common sexual allometry described for cranial shape, which suggested that larger males have bigger masticatory muscles than smaller females and thus produce higher bite forces38. Additionally, even though the relative length of the toothrow decreases, the size of the canine markedly increases and there is no change in molar size or the relative proportions in its shearing and crushing regions. Although this might be interpreted as reinforcing the canines to cope with killing larger prey while maintaining an otherwise similar dietary regime20, it is worth noting that larger canines have been long described as a feature of sexual size dimorphism in mustelids19,44,45.In terms of interspecific differences in sexual allometry, with increasing size the following shape changes were observed in females but not in males (Fig. S5C): a dorsoventrally more robust corpus, a ventral expansion of the angular process, longer in-levers for all masticatory muscles, larger incisors, and an increase in the shearing portion of m1 relative to the crushing portion. Most of these shape changes are similar to those described for PC3, which suggests that the female interspecific allometry bridges the bite force gap caused by sexual dimorphism in size. The changes to the female dentition suggest a shift in diet from crushing tough food items (e.g. aquatic invertebrates) towards slicing meat, which makes sense since these changes occur simultaneously with the common allometric trend (related to improved capabilities for killing larger vertebrate prey). However, as noted earlier, the increased shearing component is also advantageous for a piscivorous diet. Shape changes in male mandibles not observed in females seem to emphasize the common allometric trend (i.e., stronger killing bite at larger gapes) (Fig. S5D): a wider coronoid process for more muscle attachment, a dorsally displaced angular process to allow wider gapes, and mediolateral expansion of the corpus to increase its strength. Regarding their dentition, the opposite trend to females was observed (i.e., slightly smaller anterior teeth and a longer crushing molar portion), suggesting a larger durophagous component in the diet of larger males.As expected, variation in mandible shape could be linked to potential dietary differences between European and American mink, and also between sexes. In summary, the results of the present study show that:

American mink are better equipped for preying on terrestrial vertebrates, as they can achieve relatively larger gapes and their mandibles are able to produce larger forces during the killing bite (i.e., at the anterior teeth and with an open mouth).

European mink, on the other hand, can produce relatively stronger bites at the carnassials, suggesting that they rely more on tougher prey and/or fish.

Regardless of species and sex, morphological features in larger mink demonstrate increased capabilities for feeding on larger terrestrial prey (stronger killing bites and more robust anterior teeth and corpora to resist the stresses caused by struggling prey).

Due to their larger size, male mink of both species have stronger bites than females at both the anterior teeth and the carnassials. However, with increasing size, females bridge the gap by developing relatively stronger bites overall while shifting their diet from tougher or harder prey (probably aquatic invertebrates) towards less mechanically demanding food items (e.g. terrestrial vertebrates and/or fish). In contrast, increasing size in males leads to even more specialization towards feeding on larger terrestrial prey while tough items become more relevant in their diets (probably crushing bones of small prey).

These findings confirm our original predictions based on previous results on cranial shape differences, but do they agree with observed dietary preferences in minks? Diet studies in American mink are numerous, and provide a wide picture of seasonal and regional variation8,11 as well as intraspecific dietary competition6,7,12. However, studies on European mink diet are scarcer9,14, particularly those comparing the sexes13. Additionally, a few studies have compared diets of sympatric European and American mink10,15. All these studies can be summarized as: A, male American mink favor medium-sized mammals and birds usually heavier than themselves; B, female American mink favor aquatic prey, but are displaced towards small mammals and birds when seasonal changes in prey availability shift the males’ diet towards aquatic prey; C, European mink favor aquatic prey, particularly fish and crayfish; but D, they are displaced towards amphibians and small mammals when sympatric with American mink. From these, our results on mandible shape variation support A and somewhat B and C, but provide no information on the interspecific competition scenario or on potential seasonal or local dietary differences. Additionally, there is no information on size-related dietary changes in either species that could validate our findings on sexual allometry in mandible shape. Thus, while mandible shape is very useful for identifying broad dietary indicators even between highly similar species, its ability to provide accurate information on their potential prey is limited.As a final note on mink diets, our previous study on cranial shape38, suggested a gradient in muscle force (and potential dietary range) from female European mink to male American mink. Based on those results and studies on social interactions between and within species35,46, we hypothesized that competition between both mink species could be displacing female European mink towards narrower and poorer diets, which could affect their survivability and ability to successfully reproduce. Fortunately, the results of the present study not only propose that there might be less overlap in diets between species and sexes than suggested by dietary studies7,10,13,15, but also indicate that dietary competition seems to be higher for small terrestrial vertebrates, not aquatic prey (on which female European mink are particularly well equipped to feed). More

Lees, A. C., Attwood, S., Barlow, J. & Phalan, B. Biodiversity scientists must fight the creeping rise of extinction denial. Nat. Ecol. Evol. 4, 1440–1443 (2020).PubMed 

Google Scholar 
Díaz, S. et al. Pervasive human-driven decline of life on Earth points to the need for transformative change. Science 366, eaax3100 (2019).
Google Scholar 
Driscoll, D. A. et al. A biodiversity-crisis hierarchy to evaluate and refine conservation indicators. Nat. Ecol. Evol. 2, 775–781 (2018).PubMed 

Google Scholar 
Jackson, J. B. et al. Historical overfishing and the recent collapse of coastal ecosystems. Science 293, 629–637 (2001).CAS 
PubMed 

Google Scholar 
McCauley, D. J. et al. Marine defaunation: Animal loss in the global ocean. Science 347, 6219 (2015).
Google Scholar 
Sala, E. & Knowlton, N. Global marine biodiversity trends. Annu. Rev. Environ. Resour. 31, 93–122 (2006).
Google Scholar 
Worm, B. et al. Impacts of biodiversity loss on ocean ecosystem services. Science 314, 787–790 (2006).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Beaumont, N. et al. Identification, definition and quantification of goods and services provided by marine biodiversity: Implications for the ecosystem approach. Mar. Pollut. Bull. 54, 253–265 (2007).CAS 
PubMed 

Google Scholar 
Hooper, D. U. et al. Effects of biodiversity on ecosystem functioning: A consensus of current knowledge. Ecol. Monogr. 75, 3–35 (2005).
Google Scholar 
Turpie, J. K. The existence value of biodiversity in South Africa: How interest, experience, knowledge, income and perceived level of threat influence local willingness to pay. Ecol. Econ. 46, 199–216 (2003).
Google Scholar 
Ruiz-Frau, A., Hinz, H., Edwards-Jones, G. & Kaiser, M. Spatially explicit economic assessment of cultural ecosystem services: Non-extractive recreational uses of the coastal environment related to marine biodiversity. Mar. Policy 38, 90–98 (2013).
Google Scholar 
Thrush, S. F., Gray, J. S., Hewitt, J. E. & Ugland, K. I. Predicting the effects of habitat homogenization on marine biodiversity. Ecol. Appl. 16, 1636–1642 (2006).PubMed 

Google Scholar 
Gillies, C. L. et al. Australian shellfish ecosystems: Past distribution, current status and future direction. PLoS ONE 13, e0190914 (2018).PubMed 
PubMed Central 

Google Scholar 
Commito, J. A., Como, S., Grupe, B. M. & Dow, W. E. Species diversity in the soft-bottom intertidal zone: Biogenic structure, sediment, and macrofauna across mussel bed spatial scales. J. Exp. Mar. Biol. Ecol. 366, 70–81 (2008).
Google Scholar 
Tokeshi, M. Species Coexistence: Ecological and Evolutionary Perspectives (Wiley, Hoboken, 2009).
Google Scholar 
Paul, L. J. A history of the Firth of Thames dredge fishrey for mussels: Use and abuse of a coastal resource. Report No. 94, (Wellington, New Zealand, 2012).Enderlein, P. & Wahl, M. Dominance of blue mussels versus consumer-mediated enhancement of benthic diversity. J. Sea Res. 51, 145–155 (2004).ADS 

Google Scholar 
Lejart, M. & Hily, C. Differential response of benthic macrofauna to the formation of novel oyster reefs (Crassostrea gigas, Thunberg) on soft and rocky substrate in the intertidal of the Bay of Brest, France. J. Sea Res. 65, 84–93 (2011).ADS 

Google Scholar 
Norling, P. & Kautsky, N. Patches of the mussel Mytilus sp. are islands of high biodiversity in subtidal sediment habitats in the Baltic Sea. Aquat. Biol. 4, 75–87 (2008).
Google Scholar 
Norling, P., Lindegarth, M., Lindegarth, S. & Strand, Å. Effects of live and post-mortem shell structures of invasive Pacific oysters and native blue mussels on macrofauna and fish. Mar. Ecol. Prog. Ser. 518, 123–138 (2015).ADS 

Google Scholar 
McLeod, I., Parsons, D., Morrison, M., Van Dijken, S. & Taylor, R. Mussel reefs on soft sediments: A severely reduced but important habitat for macroinvertebrates and fishes in New Zealand. N. Z. J. Mar. Freshw. Res. 48, 48–59 (2014).CAS 

Google Scholar 
Seitz, R. D., Wennhage, H., Bergström, U., Lipcius, R. N. & Ysebaert, T. Ecological value of coastal habitats for commercially and ecologically important species. ICES J. Mar. Sci. 71, 648–665 (2014).
Google Scholar 
zu Ermgassen, P. S., Grabowski, J. H., Gair, J. R. & Powers, S. P. Quantifying fish and mobile invertebrate production from a threatened nursery habitat. J. Appl. Ecol. 53, 596–606 (2016).
Google Scholar 
Grabowski, J. H. The influence of trophic interactions, habitat complexity, and landscape setting on community dynamics and restoration of oyster reefs. Ph.D., The University of North Carolina at Chapel Hill (2002).Harding, J. M., Allen, D. M., Haffey, E. R. & Hoffman, K. M. Site fidelity of oyster reef blennies and gobies in saltmarsh tidal creeks. Estuaries Coasts 43, 409–423 (2020).CAS 

Google Scholar 
Parsons, D. et al. Snapper (Chrysophrys auratus): A review of life history and key vulnerabilities in New Zealand. N. Z. J. Mar. Freshw. Res. 48, 256–283 (2014).
Google Scholar 
Callier, M. D., Richard, M., McKindsey, C. W., Archambault, P. & Desrosiers, G. Responses of benthic macrofauna and biogeochemical fluxes to various levels of mussel biodeposition: An in situ “benthocosm” experiment. Mar. Pollut. Bull. 58, 1544–1553. https://doi.org/10.1016/j.marpolbul.2009.05.010 (2009).CAS 
Article 
PubMed 

Google Scholar 
Ysebaert, T., Hart, M. & Herman, P. M. Impacts of bottom and suspended cultures of mussels Mytilus spp. on the surrounding sedimentary environment and macrobenthic biodiversity. Helgol. Mar. Res. 63, 59–74 (2009).ADS 

Google Scholar 
Sea, M. A., Thrush, S. F. & Hillman, J. R. Environmental predictors of sediment denitrification rates within restored green-lipped mussel (Perna canaliculus) beds. Mar. Ecol. Prog. Ser. 667, 1–13 (2021).ADS 
CAS 

Google Scholar 
Hillman, J. R., O’Meara, T. A., Lohrer, A. M., & Thrush, S. F. Influence of restored mussel reefs on denitrification in
marine sediments. J. Sea Res. 175, 102099 (2021).
Google Scholar 
Bacheler, N. M. et al. Comparison of trap and underwater video gears for indexing reef fish presence and abundance in the southeast United States. Fish. Res. 143, 81–88 (2013).
Google Scholar 
Wells, R. D., Boswell, K. M., Cowan, J. H. Jr. & Patterson, W. F. III. Size selectivity of sampling gears targeting red snapper in the northern Gulf of Mexico. Fish. Res. 89, 294–299 (2008).
Google Scholar 
Emslie, M. J., Cheal, A. J., MacNeil, M. A., Miller, I. R. & Sweatman, H. P. Reef fish communities are spooked by scuba surveys and may take hours to recover. PeerJ 6, e4886 (2018).PubMed 
PubMed Central 

Google Scholar 
Piggott, C. V., Depczynski, M., Gagliano, M. & Langlois, T. J. Remote video methods for studying juvenile fish populations in challenging environments. J. Exp. Mar. Biol. Ecol. 532, 151454 (2020).
Google Scholar 
Dean, W. E. Determination of carbonate and organic matter in calcareous sediments and sedimentary rocks by loss on ignition: Comparison with other methods. J. Sediment. Res. 44, 242–248 (1974).CAS 

Google Scholar 
Lorenzen, C. J. Determination of chlorophyll and pheo-pigments: Spectrophotometric equations. Limnol. Oceanogr. 12, 343–346 (1967).ADS 
CAS 

Google Scholar 
Anderson, M. J. A new method for non-parametric multivariate analysis of variance. Austral Ecol. 26, 32–46 (2001).
Google Scholar 
McArdle, B. H. & Anderson, M. J. Fitting multivariate models to community data: A comment on distance-based redundancy analysis. Ecology 82, 290–297 (2001).
Google Scholar 
Clarke, K. R. & Gorley, R. N. PRIMER v7: User Manual/Tutorial (2015).Anderson, M. J., Gorley, R. N. & Clarke, K. R. PERMANOVA+ for PRIMER: Guide to software and statistical methods (2008).R: A language and environment for statistical computing (R Foundation for Statistical Computing, Vienna, Austria, 2021).Saier, B. Subtidal and intertidal mussel beds (Mytilus edulis L.) in the Wadden Sea: Diversity differences of associated epifauna. Helgol. Mar. Res. 56, 44–50 (2002).ADS 

Google Scholar 
Peterson, C. H., Grabowski, J. H. & Powers, S. P. Estimated enhancement of fish production resulting from restoring oyster reef habitat: Quantitative valuation. Mar. Ecol. Prog. Ser. 264, 249–264 (2003).ADS 

Google Scholar 
Gutiérrez, J. L., Jones, C. G., Strayer, D. L. & Iribarne, O. O. Mollusks as ecosystem engineers: The role of shell production in aquatic habitats. Oikos 101, 79–90 (2003).
Google Scholar 
Norkko, A., Hewitt, J. E., Thrush, S. F. & Funnell, T. Benthic-pelagic coupling and suspension-feeding bivalves: Linking site-specific sediment flux and biodeposition to benthic community structure. Limnol. Oceanogr. 46, 2067–2072 (2001).ADS 

Google Scholar 
Russell, B. The food and feeding habits of rocky reef fish of north-eastern New Zealand. N. Z. J. Mar. Freshw. Res. 17, 121–145 (1983).
Google Scholar 
Gillies, C., Creighton, C. & McLeod, I. Shellfish reef habitats: A synopsis to underpin the repair and conservation of Australia’s environmentally, socially and economically important bays and estuaries. Report to the National Environmental Science Programme, Marine Biodiversity Hub, Centre for Tropical Water and Aquatic Ecosystem Research (TropWATER) Publication, James Cook University, Townsville, Qld, Australia (2015).Lenihan, H. S. et al. Cascading of habitat degradation: Oyster reefs invaded by refugee fishes escaping stress. Ecol. Appl. 11, 764–782 (2001).
Google Scholar 
Connell, S. & Jones, G. The influence of habitat complexity on postrecruitment processes in a temperate reef fish population. J. Exp. Mar. Biol. Ecol. 151, 271–294 (1991).
Google Scholar 
Usmar, N. Ontogeny and Ecology of Snapper (Pagrus auratus) in an estuary, the Mahurangi Harbour (University of Auckland, 2009).
Google Scholar 
Willis, T. J. & Anderson, M. J. Structure of cryptic reef fish assemblages: Relationships with habitat characteristics and predator density. Mar. Ecol. Prog. Ser. 257, 209–221 (2003).ADS 

Google Scholar 
Thompson, S. Homing in a territorial reef fish. Copeia 1983, 832–834 (1983).
Google Scholar 
Thrush, S. F., Schultz, D., Hewitt, J. E. & Talley, D. Habitat structure in soft-sediment environments and abundance of juvenile snapper Pagrus auratus. Mar. Ecol. Prog. Ser. 245, 273–280 (2002).ADS 

Google Scholar 
Pickering, H. & Whitmarsh, D. Artificial reefs and fisheries exploitation: A review of the ‘attraction versus production’debate, the influence of design and its significance for policy. Fish. Res. 31, 39–59 (1997).
Google Scholar 
Karp, M. A., Seitz, R. D. & Fabrizio, M. C. Faunal communities on restored oyster reefs: Effects of habitat complexity and environmental conditions. Mar. Ecol. Prog. Ser. 590, 35–51 (2018).ADS 

Google Scholar 
Hanke, M. H., Posey, M. H. & Alphin, T. D. The effects of intertidal oyster reef habitat characteristics on faunal utilization. Mar. Ecol. Prog. Ser. 581, 57–70 (2017).ADS 

Google Scholar 
Cranfield, H., Rowden, A., Smith, D., Gordon, D. & Michael, K. Macrofaunal assemblages of benthic habitat of different complexity and the proposition of a model of biogenic reef habitat regeneration in Foveaux Strait, New Zealand. J. Sea Res. 52, 109–125 (2004).ADS 

Google Scholar 
Norling, P. & Kautsky, N. Structural and functional effects of Mytilus edulis on diversity of associated species and ecosystem functioning. Mar. Ecol. Prog. Ser. 351, 163–175 (2007).ADS 

Google Scholar 
Jaunatre, R. et al. New synthetic indicators to assess community resilience and restoration success. Ecol. Indicators 29, 468–477 (2013).
Google Scholar 
O’Meara, T. A., Hewitt, J. E., Thrush, S. F., Douglas, E. J. & Lohrer, A. M. Denitrification and the role of macrofauna across estuarine gradients in nutrient and sediment loading. Estuaries Coasts 43, 1394–1405. https://doi.org/10.1007/s12237-020-00728-x (2020).CAS 
Article 

Google Scholar 
McCann, L. D. Oligochaete influence on settlement, growth and reproduction in a surface-deposit-feeding polychaete. J. Exp. Mar. Biol. Ecol. 131, 233–253 (1989).
Google Scholar 
Hope, J. A., Paterson, D. M. & Thrush, S. F. The role of microphytobenthos in soft-sediment ecological networks and their contribution to the delivery of multiple ecosystem services. J. Ecol. 108, 815–830 (2020).
Google Scholar 
Christianen, M. J. et al. Benthic primary producers are key to sustain the Wadden Sea food web: Stable carbon isotope analysis at landscape scale. Ecology 98, 1498–1512 (2017).CAS 
PubMed 

Google Scholar 
Commito, J. A. & Dankers, N. M. Dynamics of spatial and temporal complexity in European and North American soft-bottom mussel beds. In Ecological Comparisons of Sedimentary Shores, 39–59 (Springer, Berlin, 2001).Arribas, L. P., Donnarumma, L., Palomo, M. G. & Scrosati, R. A. Intertidal mussels as ecosystem engineers: Their associated invertebrate biodiversity under contrasting wave exposures. Mar. Biodivers. 44, 203–211 (2014).
Google Scholar 
Walles, B., Salvador de Paiva, J., van Prooijen, B. C., Ysebaert, T. & Smaal, A. C. The ecosystem engineer Crassostrea gigas affects tidal flat morphology beyond the boundary of their reef structures. Estuaries Coasts 38, 941–950 (2015).
Google Scholar 
Tsuchiya, M. & Nishihira, M. Islands of Mytilus edulis as a habitat for small intertidal animals: Effect of Mytilus age structure on the species composition of the associated fauna and community organization. Mar. Ecol. Prog. Ser. 31, 171–178 (1986).ADS 

Google Scholar 
Craeymeersch, J. A. & Jansen, H. M. Bivalve assemblages as hotspots for biodiversity. In Goods and Services of Marine Bivalves, 275–294 (Springer, Cham, 2019).Buschbaum, C. et al. Mytilid mussels: Global habitat engineers in coastal sediments. Helgol. Mar. Res. 63, 47–58 (2009).ADS 

Google Scholar  More

Wernberg, T., Krumhansl, K. A., Filbee-Dexter, K. & Pedersen, M. Status and trends for the world’s kelp forests. In World Seas: An Environmental Evaluation (ed. Sheppard, C.) 57–78 (Elsevier, 2019).Chapter 

Google Scholar 
Smale, D. A. et al. Marine heatwaves threaten global biodiversity and the provision of ecosystem services. Nat. Clim. Change 9, 306–312. https://doi.org/10.1038/s41558-019-0412-1 (2019).ADS 
Article 

Google Scholar 
Wernberg, T. et al. Climate-driven regime shift of a temperate marine ecosystem. Science 353, 169–172. https://doi.org/10.1126/science.aad8745 (2016).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Coleman, M. A., Minne, A. J. P., Vranken, S. & Wernberg, T. Genetic tropicalisation following a marine heatwave. Sci. Rep. UK 10, 12726. https://doi.org/10.1038/s41598-020-69665-w (2020).ADS 
CAS 
Article 

Google Scholar 
Krumhansl, K. A. et al. Global patterns of kelp forest change over the past half-century. Proc. Natl. Acad. Sci. 113, 13785–13790. https://doi.org/10.1073/pnas.1606102113 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Arafeh-Dalmau, N. et al. Extreme marine heatwaves alter kelp forest community near its equatorward distribution limit. Front. Mar. Sci. https://doi.org/10.3389/fmars.2019.00499 (2019).Article 

Google Scholar 
Tanaka, K., Taino, S., Haraguchi, H., Prendergast, G. & Hiraoka, M. Warming off southwestern Japan linked to distributional shifts of subtidal canopy-forming seaweeds. Ecol. Evol. 2, 2854–2865. https://doi.org/10.1002/ece3.391 (2012).Article 
PubMed 
PubMed Central 

Google Scholar 
Wernberg, T. et al. Genetic diversity and kelp forest vulnerability to climatic stress. Sci. Rep. UK 8, 1851. https://doi.org/10.1038/s41598-018-20009-9 (2018).ADS 
CAS 
Article 

Google Scholar 
Graham, M. H., Kinlan, B. P., Druehl, L. D., Garske, L. E. & Banks, S. Deep-water kelp refugia as potential hotspots of tropical marine diversity and productivity. Proc. Natl. Acad. Sci. 104, 16576. https://doi.org/10.1073/pnas.0704778104 (2007).ADS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Marzinelli, E. M. et al. Large-scale geographic variation in distribution and abundance of Australian deep-water kelp forests. PLoS ONE 10, e0118390. https://doi.org/10.1371/journal.pone.0118390 (2015).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Varela, R., Rodríguez-Díaz, L., de Castro, M. & Gómez-Gesteira, M. Influence of Eastern Upwelling systems on marine heatwaves occurrence. Glob. Planet Change 196, 103379. https://doi.org/10.1016/j.gloplacha.2020.103379 (2021).Article 

Google Scholar 
Assis, J. et al. Deep reefs are climatic refugia for genetic diversity of marine forests. J. Biogeogr. 43, 833–844. https://doi.org/10.1111/jbi.12677 (2016).Article 

Google Scholar 
Lourenço, C. R. et al. Upwelling areas as climate change refugia for the distribution and genetic diversity of a marine macroalga. J. Biogeogr. 43, 1595–1607. https://doi.org/10.1111/jbi.12744 (2016).Article 

Google Scholar 
Vranken, S. et al. Genotype-environment mismatch of kelp forests under climate change. Mol. Ecol. 30, 3730–3746. https://doi.org/10.1111/mec.15993 (2021).Article 
PubMed 

Google Scholar 
Wood, G. et al. Genomic vulnerability of a dominant seaweed points to future-proofing pathways for Australia’s underwater forests. Glob. Change Biol. 27, 2200–2212. https://doi.org/10.1111/gcb.15534 (2021).ADS 
Article 

Google Scholar 
Wernberg, T. et al. Biology and ecology of the globally significant kelp Ecklonia radiata. Oceanogr. Mar. Biol.: An Annu. Rev. 57, 265–324 (2019).Article 

Google Scholar 
Durrant, H. M. S., Barrett, N. S., Edgar, G. J., Coleman, M. A. & Burridge, C. P. Shallow phylogeographic histories of key species in a biodiversity hotspot. Phycologia 54, 556–565. https://doi.org/10.2216/15-24.1 (2015).Article 

Google Scholar 
Rothman, M. D. et al. A molecular investigation of the genus Ecklonia (Phaeophyceae, Laminariales) with special focus on the southern hemisphere. J. Phycol. 51, 236–246. https://doi.org/10.1111/jpy.12264 (2015).CAS 
Article 
PubMed 

Google Scholar 
Starko, S. et al. A comprehensive kelp phylogeny sheds light on the evolution of an ecosystem. Mol. Phylogenetics Evol. 136, 138–150. https://doi.org/10.1016/j.ympev.2019.04.012 (2019).Article 

Google Scholar 
Shepherd, S. A. & Edgar, G. J. In (eds Shepherd, S. A. & Edgar, G. J.) (CSIRO Publishing, 2013).Guiry, M. D. et al. AlgaeBase: An on-line resource for algae. Cryptogam. Algol. 35, 105–115, 111 (2014).Barratt, L., Ormond, R. F. G. & Wrathall, T. J. Ecological studies of southern Oman kelp communities. Part 1. Ecology and productivity of the sublittoral algae Ecklonia radiata and Sargassopsis zanardinii (Council for the conservation of the environment and water resources, and regional organisation for the protection of the marine environment, Muscat and Kuwait, 1986).Barratt, L. et al. An ecological study of the rocky shores on the south coast of Oman. Report of IUCN to UNEP’s regional seas programme, Vol. 104 (Tropical Marine Research Unit, York, 1984).Klaus, R. & Turner, J. R. The marine biotopes of the Socotra Archipelago. Fauna Arab. 20, 45–116 (2004).
Google Scholar 
Claereboudt, M. R. Oman. In World Seas: An Environmental Evaluation, (ed. Sheppard, C.) 25–47 (Academic Press, 2019).Savidge, G., Lennon, H. J. & Matthews, A. D. A shore based survey of oceanographic variables in the Dhofar region of southern Oman, August–October 1985. In Ecological Studies of Southern Oman Kelp Communities. Summary Report, 4–21. ROPME/GC-6/001 (1988).Hatcher, B. G., Kirkman, H. & Wood, W. F. Growth of the kelp Ecklonia-radiata near the northern limit of its range in Western-Australia. Mar. Biol. 95, 63–73. https://doi.org/10.1007/Bf00447486 (1987).Article 

Google Scholar 
Veenhof, R. et al. Kelp gametophytes in changing oceans. Oceanogr. Mar. Biol. Annu. Rev. 60 (in press).Goes, J. I., Thoppil, P. G., Gomes, H. D. R. & Fasullo, J. T. Warming of the Eurasian landmass is making the Arabian sea more productive. Science 308, 545. https://doi.org/10.1126/science.1106610 (2005).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Roxy, M. K. et al. A reduction in marine primary productivity driven by rapid warming over the tropical Indian Ocean. Geophys. Res. Lett. 43, 826–833. https://doi.org/10.1002/2015GL066979 (2016).ADS 
Article 

Google Scholar 
Watanabe, T. K., Watanabe, T., Yamazaki, A., Pfeiffer, M. & Claereboudt, M. R. Oman coral δ18O seawater record suggests that Western Indian Ocean upwelling uncouples from the Indian Ocean Dipole during the global-warming hiatus. Sci. Rep. UK 9, 1887. https://doi.org/10.1038/s41598-018-38429-y (2019).ADS 
CAS 
Article 

Google Scholar 
Watanabe, T. K. et al. Past summer upwelling events in the Gulf of Oman derived from a coral geochemical record. Sci. Rep. UK 7, 4568. https://doi.org/10.1038/s41598-017-04865-5 (2017).ADS 
CAS 
Article 

Google Scholar 
Edwards, M. & Estes, J. A. Catastrophe, recovery and range limitation in NE Pacific kelp forests: a large-scale perspective. Mar. Ecol. Prog. Ser. 320, 79–87 (2006).ADS 
Article 

Google Scholar 
Glynn, P. W. Monsoonal upwelling and episodic Acanthaster predation as probable controls of coral reef distribution and community structure in Oman, Indian Ocean. Atoll Res. Bull. 379, 1–66 (1993).Article 

Google Scholar 
Hiscock, S., Barratt, L. & Ormond, R. The marine algae of Dhofar, Oman-an upwelling system in the Arabian Sea. Br. Phycol. J. 19, 194 (1984).Article 

Google Scholar 
Kirkman, H. The 1st year in the life-history and the survival of the juvenile marine macrophyte, Ecklonia-radiata (Turn) J Agardh. J. Exp. Mar. Biol. Ecol. 55, 243–254. https://doi.org/10.1016/0022-0981(81)90115-5 (1981).Article 

Google Scholar 
Maeda, T., Kawai, T., Nakaoka, M. & Yotsukura, N. Effective DNA extraction method for fragment analysis using capillary sequencer of the kelp, Saccharina. J. Appl. Phycol. 25, 337–347 (2013).CAS 
Article 

Google Scholar 
Voisin, M., Engel, C. R. & Viard, F. Differential shuffling of native genetic diversity across introduced regions in a brown alga: Aquaculture vs. maritime traffic effects. Proc. Natl. Acad. Sci. USA 102, 5432. https://doi.org/10.1073/pnas.0501754102 (2005).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Lane, C. E., Lindstrom, S. C. & Saunders, G. W. A molecular assessment of northeast Pacific Alaria species (Laminariales, Phaeophyceae) with reference to the utility of DNA barcoding. Mol. Phylogenetics Evol. 44, 634–648 (2007).CAS 
Article 

Google Scholar 
Kearse, M. et al. Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics 28, 1647–1649. https://doi.org/10.1093/bioinformatics/bts199 (2012).Article 
PubMed 
PubMed Central 

Google Scholar 
Johnson, M. et al. NCBI BLAST: A better web interface. Nucl. Acids Res. 36, W5–W9 (2008).CAS 
Article 

Google Scholar 
Trifinopoulos, J., Nguyen, L.-T., von Haeseler, A. & Minh, B. Q. W-IQ-TREE: A fast online phylogenetic tool for maximum likelihood analysis. Nucl. Acids Res. 44, W232–W235 (2016).CAS 
Article 

Google Scholar 
Kalyaanamoorthy, S., Minh, B. Q., Wong, T. K., Von Haeseler, A. & Jermiin, L. S. ModelFinder: Fast model selection for accurate phylogenetic estimates. Nat. Methods 14, 587–589 (2017).CAS 
Article 

Google Scholar 
Chernomor, O., von Haeseler, A. & Minh, B. Q. Terrace aware data structure for phylogenomic inference from supermatrices. Syst. Biol. 65, 997–1008. https://doi.org/10.1093/sysbio/syw037 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Hoang, D. T., Chernomor, O., Von Haeseler, A., Minh, B. Q. & Vinh, L. S. UFBoot2: Improving the ultrafast bootstrap approximation. Mol. Biol. Evol. 35, 518–522 (2018).CAS 
Article 

Google Scholar 
Rambaut, A. & Drummond, A. FigTree: Tree Figure Drawing Tool, Version 1.2. 2 (Institute of Evolutionary Biology, University of Edinburgh, 2008).
Google Scholar 
Rozas, J. et al. DnaSP 6: DNA sequence polymorphism analysis of large data sets. Mol. Biol. Evol. 34, 3299–3302. https://doi.org/10.1093/molbev/msx248 (2017).CAS 
Article 
PubMed 

Google Scholar 
Clement, M., Posada, D. & Crandall, K. A. TCS: A computer program to estimate gene genealogies. Mol. Ecol. 9, 1657–1659. https://doi.org/10.1046/j.1365-294x.2000.01020.x (2000).CAS 
Article 
PubMed 

Google Scholar 
Leigh, J. W. & Bryant, D. popart: Full-feature software for haplotype network construction. Methods Ecol. Evol. 6, 1110–1116 (2015).Article 

Google Scholar 
Team, R. C. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2019).Vergés, A. et al. Long-term empirical evidence of ocean warming leading to tropicalization of fish communities, increased herbivory, and loss of kelp. Proc. Natl. Acad. Sci. 113, 13791–13796. https://doi.org/10.1073/pnas.1610725113 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Wood, G. et al. Using genetics to test provenance effects and to optimise seaweed restoration. J. Appl. Ecol. https://doi.org/10.1111/1365-2664.13707 (2020).Article 

Google Scholar 
Wynne, M. J. A checklist of the benthic marine algae of the Northern Arabian Sea coast of the Sultanate of Oman. Bot. Mar. 61, 481–498. https://doi.org/10.1515/bot-2018-0035 (2018).Richards, G. & Wynne, M. J. 57 (2003).Schils, T. Marine Plant Communities of Upwelling Areas Within the Arabian Sea: A Taxonomic, Ecological ABD Biogeographic Case Study on the Marine Flora of the Socotra Archipelago (Yemen) and Masirah Island (Oman). PhD thesis (2002).Schils, T. & Coppejans, E. Phytogeography of upwelling areas in the Arabian Sea. J. Biogeogr. 30, 1339–1356. https://doi.org/10.1046/j.1365-2699.2003.00933.x (2003).Article 

Google Scholar 
Schils, T. & Wilson, S. C. temperature threshold as a biogeographic barrier in northern Indian Ocean Macroalgae. J. Phycol. 42, 749–756. https://doi.org/10.1111/j.1529-8817.2006.00242.x (2006).Article 

Google Scholar 
Wiggert, J. D., Hood, R. R., Banse, K. & Kindle, J. C. Monsoon-driven biogeochemical processes in the Arabian Sea. Prog. Oceanogr. 65, 176–213. https://doi.org/10.1016/j.pocean.2005.03.008 (2005).ADS 
Article 

Google Scholar 
Serisawa, Y., Imoto, Z., Ishikawa, T. & Ohno, M. Decline of the Ecklonia cava population associated with increased seawater temperatures in Tosa Bay, southern Japan. Fish. Sci. 70, 189–191. https://doi.org/10.1111/j.0919-9268.2004.00788.x (2004).CAS 
Article 

Google Scholar 
Nelson, W., Duffy, C., Trnski, T. & Stewart, R. Mesophotic Ecklonia radiata (Laminariales) at Rangitāhua, Kermadec Islands, New Zealand. Phycologia 57, 534–538. https://doi.org/10.2216/18-9.1 (2018).Article 

Google Scholar 
Richmond, S. & Stevens, T. Classifying benthic biotopes on sub-tropical continental shelf reefs: How useful are abiotic surrogates?. Estuar. Coast. Shelf Sci. 138, 79–89. https://doi.org/10.1016/j.ecss.2013.12.012 (2014).ADS 
Article 

Google Scholar 
Davis, T. R., Champion, C. & Coleman, M. A. Climate refugia for kelp within an ocean warming hotspot revealed by stacked species distribution modelling. Mar. Environ. Res. 166, 105267. https://doi.org/10.1016/j.marenvres.2021.105267 (2021).CAS 
Article 
PubMed 

Google Scholar 
Jooste, C. M., Oliver, J., Emami-Khoyi, A. & Teske, P. R. Is the Wild Coast in eastern South Africa a distinct marine bioregion?. Helgol. Mar. Res. 72, 6. https://doi.org/10.1186/s10152-018-0509-3 (2018).Article 

Google Scholar 
Bolton, J. J. et al. Where is the western limit of the tropical Indian Ocean seaweed flora? An analysis of intertidal seaweed biogeography on the east coast of South Africa. Mar. Biol. 144, 51–59. https://doi.org/10.1007/s00227-003-1182-9 (2004).Article 

Google Scholar 
Bolton, J. J. The biogeography of kelps (Laminariales, Phaeophyceae): A global analysis with new insights from recent advances in molecular phylogenetics. Helgol. Mar. Res. 64, 263–279. https://doi.org/10.1007/s10152-010-0211-6 (2010).ADS 
Article 

Google Scholar 
Bolton JJ, De Clerck O, John DM (2003). Seaweed diversity patterns in Sub-Saharan Africa. In Proceedings of the Marine Biodiversity in Sub-Saharan Africa: The Known and the Unknown. (eds. Decker, C. et al. ) Cape Town, South Africa, pp. 229–241 (2003).Wood, M. et al. Zanzibar and Indian Ocean trade in the first millennium CE: The glass bead evidence. Archaeol. Anthropol. Sci. 9, 879–901. https://doi.org/10.1007/s12520-015-0310-z (2017).Article 

Google Scholar 
Pollard, E., Bates, R., Ichumbaki, E. B. & Bita, C. Shipwreck evidence from Kilwa, Tanzania. Int. J. Naut. Archaeol. 45, 352–369. https://doi.org/10.1111/1095-9270.12185 (2016).Article 

Google Scholar 
Staples, M. In Oman. A Maritime History (eds Al Salimi, A. & Staples, E.) Chap. 4, 81–116 (Georg Olms Verlag, 2017).Assis, J. et al. Past climate changes and strong oceanographic barriers structured low-latitude genetic relics for the golden kelp Laminaria ochroleuca. J. Biogeogr. 45, 2326–2336. https://doi.org/10.1111/jbi.13425 (2018).Article 

Google Scholar 
Wade, R. et al. Macroalgal germplasm banking for conservation, food security, and industry. PLoS Biol. 18, e3000641. https://doi.org/10.1371/journal.pbio.3000641 (2020).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Coleman, M. A. et al. Restore or redefine: Future trajectories for restoration. Front. Mar. Sci. https://doi.org/10.3389/fmars.2020.00237 (2020).Article 

Google Scholar  More

The Willmott similarity indices, over the first 4 months, for outside and inside temperatures, in sunny and shaded environments, with values close to 1, confirm that A. sexdens colonies were exposed to significantly different temperatures. The lowest values of this index for irradiance, differing between the sunny and shaded environments for internal temperature (in the initial chamber), indicates variation in this parameter between environments. Irradiance values close to 0 between environments represent differences between sunny and shaded areas, but the temperature of the initial chamber did not vary. The selection pressure from irradiance and, consequently, temperature, defines the ideal depth of the initial chamber for the founding queens16 to keep this parameter at values adequate for the fungus garden and the offspring8 in the field. The similar temperature, in the nests in the shaded environment, agrees with that reported for this leaf-cutting ant, of 24°C3, but this varies between species of these insects, being 25–28 °C for A. sexdens17, 27.5 °C for A. vollenweideri18 and 27 °C for A. heyeri19. This adaptation of an ideal depth to construct the initial chamber allows A. sexdens to adapt to different habitats in full sun and shade. The nesting process, habits and foraging strategies differ between A. bisphaerica and A. sexdens, with the former normally establishing their nests in full sun in areas with predominantly grass forages and the latter in shaded areas where it cuts dicot leaves14. Furthermore, differences in nest depth between these species may be related to soil temperature, which is lower in shaded areas7. For this reason, fungal chambers in exposed nests in pastures are deeper than in shaded areas in forests, as soil temperature is negatively correlated with depth7. Soil humidity and temperature act simultaneously due to the thermo preference of workers, resulting in the construction of shallower nests in cold soils and deeper nests in warmer ones7. Soil moisture also varies according to depth, affecting the nest-digging behavior of leaf-cutting ants7,15.The temperature in the shaded environment was higher than that reported for A. sexdens rubropilosa, from 24.82 ± 3.14 to 24.11 ± 1.30 °C at a depth of 5–25 cm underground, for optimal offspring development and, consequently, reduction in the lipid content of queens at high temperatures, without affecting their survival20. This is because the depth of the initial chamber excavated by the queen is adequate for colony success8,16.The different habitats occupied by the ant A. sexdens21, from dense forests to cerrado and caatinga may explain the greater depth and volume of the initial chamber of the nests in shaded than in sunny environments. However, the depth of the initial nests varies between Atta species with 7.5–12 cm, 6.5–13 cm, 15–25 cm, 10–30 cm, 10–15 cm, 11–34 cm, and 9–15 cm for A. colombica, A. cephalotes, A. texana, A. sexdens rubropilosa, A bisphaerica, A capiguara, and A. insulares, respectively1,13,15,22,23,24. The initial chamber volume is within the expected range for A. sexdens1,13 in both environments, with a chamber volume of 24.88 cm3 in a shaded area with eucalyptus plantation13. Different excavation efforts with the removal of small soil particles by the founding queen using her jaws in repeated biting motions25, subsequently discarded outside the nest8,16,26 may explain the greater volume of the initial chamber in the shaded area. The greater solar irradiation in sunny areas increases the temperature, with the higher soil temperature generating greater excavation effort and oxidative damage27,28, in addition to water loss, as described for seed-collecting ants29,30. Further, humid soils are easier to dig, which explains the greater volume of the initial chamber in the shaded area as found for the excavation behavior by Atta spp. in soils with different densities and moistures15,16,31.The higher mass of A. sexdens queens in the first month of the claustral phase than in the fourth, in both sunny and shaded environments, stems from a reduction in their body mass, due to the metabolism of the lipid content during the first 6 months following the flight, but with recovery in the subsequent months1. The mass loss is due to the use of body reserves by the queens to prepare and maintain the colony in the claustral phase, as stored lipids are important in the evolutionary history of the Attini tribe, from semi-claustral to claustral foundation32. The queen, with a claustral foundation, does not feed, remaining enclosed in the nest and rearing her initial offspring by metabolizing her own body reserves33, as reported for this ant species1. The selection pressure on the evolution of claustral foundation tends to minimize risk during foraging33 with a more viable adaptation being the storing of reserves in the body, as observed in our study. The greater biomass of the fungus garden in the fourth month is due to growth, but its values were lower than those reported for 4-month-old A. sexdens nests, from 2000 to 3000 mg1.The lower number of A. sexdens eggs in the first than in the third month is similar to that observed in laboratory colonies of this ant8. The irregularity in the egg production by the queen is due to hormone fluctuations regulated by the endocrine system, and is correlated with the activity cycle of the corpora allata during the 3 or 4 months of colony life34. This gland synthesizes the juvenile hormone, which acts in the oviposition of founding queens, as verified for females that underwent alatectomy34. This hormone acts in the fat body, initiating the synthesis of vitellogenin (glycolipophosphoproteins, with lipids and carbohydrates in its composition) to be deposited in the oocyte35. Thus, the production of offspring depends on body reserves (fatty body lipids and muscle mass protein), as the queen does not feed during the foundation period (claustral foundation). The lower production of small and medium workers in the first month than in the second, third or fourth months, agrees with that reported in A. sexdens nests1. The similar number of larvae over the 4 months is due to the duration of the larval period of A. sexdens, of around 25 days8, with new immature individuals produced monthly with overlapping generations, common in social insects. This overlap begins with larvae in the first month of nests and pupae, usually in the second month of ant nests in the laboratory8.The lower values of fungus biomass and number of eggs, larvae, pupae and small and medium workers of A. sexdens in nests in the sunny environment may be due to a higher incidence of solar irradiance increasing the variation in the internal temperature of the initial chamber. This agrees with reports that a lower incidence of solar irradiance improved the stability of the internal temperature of the initial chamber, favoring A. sexdens with narrow thermal tolerance range as it is a thermally protected underground species11. However, frequent heat peaks, with habitat-specific physiological consequences for subterranean ectothermic animals, are common in sunny areas11. The queen’s body mass, similar between environments, indicates a similar reduction of this parameter between them and their tolerance to temperature variations in this type of foundation. A reduction in the mass of A. sexdens queens is expected from the nuptial flight to the end of the claustral phase. The energy expenditure of A. sexdens queens, in carbohydrates and body lipids for the nuptial flight and nest excavation, was estimated at 0.58 J36 and during the claustral phase, they metabolize body lipids and proteins to survive and form the initial colony26,37.The higher mortality of A. sexdens nests in the sunny environment, during the claustral foundation, is due to a higher incidence of solar irradiance, increasing the variation in the internal temperature of the initial chamber and, consequently, the excavation effort and oxidative damage to the founding queens27,28, in addition to water losses as reported for seed-collecting ants29,30. This mortality may also be related to entomopathogens, unsuccessful symbiotic fungus regurgitation, excavation effort, density and soil moisture1,9,38,39.Atta sexdens founder queens were exposed to sunny and shaded environments with greater solar irradiance and, consequently, a greater variation range in the internal temperature of the initial chamber in the first environment. The shaded environment, with lower incidence of solar irradiance and greater stability of the internal temperature of the initial chamber, was more favorable for colony development, as confirmed by the biological parameters and greater survival of A. sexdens queens.
Atta sexdens female collection methods- after the nuptial flightAtta sexdens queens were collected at the Experimental Farm Lageado in Botucatu, Brazil in 2019 (22°50′37.3″S 48°25′38.3″W) on sunny days after heavy rains from late October to early November. Two hundred queens were collected using tweezers. They were stored separately in 250 ml pots with 1 cm wet plaster for 60 min prior to use. We had permission to collect Atta sexdens queen specimens.Experimental areasThe A. sexdens queens were individualized in two experimental areas: sunny—an open area exposed to Global Horizontal Irradiation with exclusive coverage of Paspalum notatum Flügge grass (N = 100) and shaded – an area exposed to Diffuse Horizontal Irradiation (50% shade screen—1.50 × 50 MT), in a plowed environment (N = 100). The soil is a superficial horizon of oxisols.The founding A. sexdens queens were individualized in the center of a square of land (50 × 50 cm) covered with a transparent bottle measuring 20 cm in diameter by 12 cm in height, delimiting the space to be drilled in the soil by the ant queens per experimental area of 25 m2 (Fig. S1).Development of early nests during the claustral phaseAtta sexdens queens were evaluated over 4 months following nest foundation, to monitor its development. A total of 25% of the successfully established nests were excavated per month by removing the colony with a gardening shovel. The number of eggs, larvae, pupae and adults was counted and the mass of the queen and the biomass of the fungus garden determined. The depth, width, length, and height of each nest were measured with the aid of a caliper. The estimated volume of each fungus chamber was based on a cylinder. A correction factor was used to calculate the volume of the chamber because they are rounded: V = πr2 (ch + r0.67), in which ‘r’ is the chamber base radius and ‘ch’ the cylinder height, measured by subtracting the maximum height of the chamber from its radius, ch = h − r40. Queen mortality was evaluated during the excavation of their nests.Temperature and radiation measurementThe temperatures of the external and internal environments (15 cm deep), in each area, were measured for 4 months, with Data loggers (Testo), after the foundation of the nest by the leaf-cutting ant. Global Horizontal Irradiation (GHI) was measured using an Eppley PSP Pyranometer and Diffuse Horizontal Irradiation by a Kipp & Zonen CM3 Pyranometer (Table 3). Solar measurements were obtained over a five-minute time scale (mean of 60 readings with scanning time every five seconds) in W/m2 by a CR300041 model data logger and stored in an ASCII file.Table 3 Instruments used to measure solar irradiance in nests of Atta sexdens (Hymenoptera: Formicidae) in sunny and shaded environments.Full size tableThe measurements were submitted to a quality control procedure to verify if their values were in accordance with pre-defined solar irradiance thresholds. This procedure consists of a series of checks on physically possible limits per component measured (Table 4). These checks were carried out according to the process created by the International Commission on Illumination (CIE) discarding erroneous measures to avoid compromising the processes of numerical integration or data processing.Table 4 Physically possible minimum and maximum values for each measurement of solar irradiance.Full size tableMeasures accepted as possible were those above 0 W/m2 and lower than the maximum stipulated limit, per component, according to the extraterrestrial solar irradiance (IE) (Eq. 1). This represents the maximum value reaching the top of the atmosphere, without attenuation by atmospheric elements (clouds, particles, among others). Values measured at the earth’s surface are lower than those at the top of the atmosphere. However, the phenomenon of multireflection when scattered clouds near the apparent location of the sun reflect part of the solar irradiance onto the sensor, increase the value measured even higher than the extraterrestrial irradiance over short periods45. For this reason, the global irradiance value can be up to 20% higher than that of the extraterrestrial one.The 1361 of Eq. (1), to calculate the extraterrestrial irradiance, represents the solar constant in W/m246, R the relation of the average dimensionless distance between the Earth and the Sun (Eq. 2) and Z the zenithal angle of the Sun (Eq. 3) in degrees47.$${text{I}}_{{text{E}}} = {1361}left( {text{1/R}} right) ,{{cos}}, left( {text{Z}} right)$$
(1)
$$begin{aligned} {text{R}} & = {1} – 0.000{9467};{text{sen}} left( {text{F}} right) – 0.0{1671};{text{cos}},left( {text{F}} right) – 0.000{1489}left( {{text{2F}}} right) \ & quad – 0.0000{2917};{text{sen}}left( {{text{3F}}} right) – 0.000{3438};{text{cos}},left( {{text{4F}}} right) \ end{aligned}$$
(2)
$${text{Z}} = {text{sen}} ,left(updelta right);{text{sen}}left(upphi right) + cos left(updelta right);cos left(upphi right);cos left(upomega right)$$
(3)
F, in Eq. (4), is the angular fraction of the date of interest in degrees, δ, at 5, the solar declination in degrees, Φ, at 6, the geographic latitude of the location in degrees (22.85) and ω, at 6, the clockwise angle in degrees.$${mathbf{F}} = {36}0^circ ;{text{D/365}}$$
(4)
$$begin{aligned} {{varvec{updelta}}} & = 0.{3964} + {3}.{631};{text{sen}}left( {text{F}} right) – {22}.{97};{text{cos}}left( {text{F}} right) + 0.0{3838};{text{sen}}left( {{text{2F}}} right) – 0.{3885};{text{cos}};left( {{text{2F}}} right) \ & quad + 0.0{7659};{text{sen}};left( {{text{3F}}} right) – 0.{1587};{text{cos}}left( {{text{3F}}} right) – 0.0{1}0{21};{text{cos}}left( {{text{4F}}} right) \ end{aligned}$$
(5)
$${{varvec{upomega}}} = left( {{12} – {text{Hd}}} right){15}$$
(6)
The d, in the previous expression, represents the day of the year, from 1 to 365 and the Hd, the hour and the tenth of an hour in degrees of the moment of interest.The values were numerically integrated, after applying the measurement quality control procedure, obtaining a solar irradiation value for the day in MJ/m2 representing the total energy received daily, on a horizontal surface of 1 m2.Statistical analysisThe null hypothesis that the mortality proportions (probabilities of success) of the founding queens of both groups are the same was submitted to the test of equal proportions.The null hypothesis that a data sample came from a normally distributed population was submitted to the Shapiro–Wilk test.Data structure fitting the ANOVA (completely randomized factorial scheme) assumptions were submitted to this analysis and to Tukey’s test for multiple comparisons of means. The Scheirer Ray Hare test is a nonparametric test used for a two-way completely randomized factorial design49. This procedure is an extension of the Kruskal–Wallis rank test allowing for calculation of the interaction effects and linear contrasts and were used for data structure that did not fit the ANOVA assumptions. Dunn’s test50 of multiple median comparisons was performed with a correction (the false discovery rate method) to control the experiment-wise error rate.The Willmott’s Index of Similarity (d) is a standardized measure of the degree of similarity between two data series ranging from 0.0 to 1.0 with the value 1.0 indicating a perfect match (two identical data sets), and 0 no agreement at all51. As an example, in the sunny environment, the indoor and outdoor temperature data were identical, which results in 1.0. The more identical, close, and concordant two data sets are, the closer to 1.0 they will be. The calculation of the index is presented with A and B representing two data sets whose agreement is to be evaluated.$$begin{aligned} A^{prime}_{i} & = A_{i} – overline{B} \ B^{prime}_{i} & = B_{i} – overline{B} \ d & = 1 – frac{{sumnolimits_{i = 1}^{N} {left( {A_{i} – B_{i} } right)^{2} } }}{{sumnolimits_{i = 1}^{N} {left[ {left| {A_{i} } right| – left| {B_{i} } right|} right]^{2} } }} \ end{aligned}$$The R companion package, ggplot252, FSA53, tidyverse54, and hydroGOF55 used is a free software environment for statistical computing and graphics R version 4.0.456. More

Study area and dateIn the north-west of France, the macrotidal Bourgneuf Bay (1°-2° W, 46°-47° N; total area ~340 km2; Fig. 1) has an intertidal zone largely dominated by mudflats (exposed surface area ~100 km2). Bourgneuf Bay is situated south of the Loire estuary and is open to the sea along 12 km from the west to the north-west. C. gigas aquaculture here is of national importance and wild C. gigas reefs can account for over double the biomass of their farmed conspecifics65. Analysis of satellite observations covering 30 years of MPB biomass in the bay confirmed the co-occurrence of high MPB biomass with wild oyster reefs and cultivated stocks16 (Supplementary Methods: Wider Situation of the Reefs). Two small (each  > 750 m2) wild C. gigas reefs and their immediate surroundings (10–100 m) in the north of Bourgneuf Bay were deemed suitable for experimental manipulation (yellow and orange regions in Fig. 1). Méléder et al.18 described MPB biomass as mostly concentrating around the 2 m isobath, the Falleron river channel (closest point ~400 m NNE from the eastern reef), and oyster farms. Covering this isobath, we superimposed a 350 * 350 m grid (12.25 hectares) to cover the two wild oyster reefs, orientated so that the ‘Y’ axis runs parallel to the slope of bathymetry (Fig. 1). The grid was split regularly into 49 ‘grand-cells’ of 50 * 50 m (i.e., n = 49) and each of those split into 25 cells of 10 * 10 m (i.e., n = 1225; Fig. 1). Four cells per grand-cell were chosen randomly for the sampling of meiofauna, granulometry, OM (see Table 3 for specific methodology), and macrofauna. Of these cells, only every second cell was processed for meiofauna because of time constraints in assessing their abundance.Table 3 Summary of study variables and their sampling methodologies.Full size tableAlthough there were only two oyster reef complexes (‘reefs’, hereon) in this study, multiple sampling cells fell on, or in close proximity to, each reef, so that each reef had many potential (though not independent) distance decay transects running from it capturing natural variation in spatial structure66. Comparing the ecological change following the experimental burning of oyster reefs (described below) against ecological change occurring at these two reefs over the previous 25 years16 also allowed us greater confidence to disentangle the treatment effects from typical variation. Through the centres of five grand-cells to the south of the extent, a transect forming an ‘L’ shape (Fig. 1) was sampled every 10 m for in situ MPB pigment composition and biomass. We used these data to complete the remote sensing approach for MPB biomass estimation (see below, Microphytobenthos). The western reef was slightly larger than the eastern reef and contained a large rock, ‘Roche Bonnet’, rising 0.5–1 m from the sediment. Outside the grid, another larger (200 * 80 m) wild oyster reef lies WSW at ~260 m distance from the western reef. The grid was sampled for the variables listed in Table 3 during the winter MPB low and early autumn peak seasons (see also ground-truthing in16), on the dates 18-19th September 2013 and 17-18th March 2014, before treatment, and on 7-8th October 2014 after treatment.MicrophytobenthosWe mapped MPB biomass by satellite remote sensing, following the method described in detail in Echappé et al. (2018). We used the same long-term record of high-resolution satellite images to analyse the spatial distribution of the normalised difference vegetation index (NDVI), a proxy of MPB chlorophyll a concentration at the sediment’s surface18,67, before and after treatment (individual image details in captions of Fig. 2 and Supplementary Figs. S4–S7). After atmospheric correction (FLASH and US40 aerosol model), the satellite-derived NDVI was validated against associated field measurements (r2 = 0.85, root-mean-square deviation, RMSE = 0.04, n = 57, P 20°) was limited (Supplementary Results: Additional MPB Images). An optimal image was chosen as representative of MPB biomass patterns per season16. The study area would ideally be tidally uncovered for ~2 h before the image was taken, whereupon MPB biomass is concentrated at the sediment surface. The optimal images met this condition (i.e., Fig. 2).To complete NDVI maps, in situ MPB pigment composition and biomass were retrieved by HPLC analysis from the 25 triplicates of sediment. These had been sampled using contact-cores to freeze the top 2 mm of sediment in situ with liquid nitrogen, with a metal surface 56 mm in diameter. Biomass was expressed by Chl a concentration (mg m−2), and dominance of MPB taxa was broadly assessed by ratio of pigment sources to Chl a: Fucoxanthin (Fuco), Diadinoxanthin (DD), Diatoxanthin (DT) and Chl c for diatoms. The ratio of unknown carotenoids (interpreted as by-products due to the low resolution of their absorption spectra) to Chl a was also analysed for ecological purposes (dominant taxa), whereas grazing pressure was investigated using the ratio of pheophorbid a to Chl a (methodological discussion in28).Sediment variablesFor laser granulometry, we sampled two depths, 0–5 cm and 5–10 cm, in triplicate at each cell. Each of the triplicate samples was put in a vial with water and sonicated. The particle size distribution was determined on a Mastersizer 3000 with a reporting range 50 nm to 3 mm. We also determined sediment percentage OM at two depths by mass loss on ignition in comparison to the oven-dried original (procedure as described for Macrofauna, also Table 3).MacrofaunaWe sampled macrofauna by a single 200 * 200 mm (depth * diameter) core per cell. Contents were placed into labelled buckets and sieved onshore (1 mm mesh). Soft-bodied polychaetes were picked out with forceps and preserved in buffered formalin during sieving. All material left on the sieve was bagged and preserved in formalin at the laboratory. Individuals were counted and measured by the longest axis (accuracy 0.1 mm, calipers); the deep-burrowing polychaete Diopatra biscayensis was counted by the presence of visible tubes above the sediment. Calibration curves from length to mass per species per season were built by identifying size classes by Sturges rule. Multiple individuals per size class (ideally n = 100) were measured to estimate mean organic mass per individual of each size class. Shell matter was physically separated from tissue, before both being dried in aluminium foil cups for 48 h at 60 °C and weighed (g) for tissue dry mass using a mass balance. Dry mass was then incinerated for four hours at 450 °C and reweighed (g; decrease in mass of the aluminium cup was also accounted for), the difference giving the organic matter mass (including residue in the shell matter), or ash free dry weight (AFDW). This number was divided by number of individuals. Calibration curves per species used first order polynomial curves for bivalves, unless numbers of size classes and individuals were small (1% of the total abundance. All mapping and analyses were performed in the statistical computing environment R (v4.0.2)73.Reporting summaryFurther information on research design is available in the Nature Research Reporting Summary linked to this article. More

Xu, L., Saatchi, S.S., Yang, Y., Yu, Y., Pongratz, J., Bloom, A.A., Bowman, K., Worden, J., Liu, J., Yin, Y. & Domke, G. Changes in global terrestrial live biomass over the 21st century. Sci. Adv. 7(27), p.eabe9829 (2001).Hoecker, T. J., Higuera, P. E., Kelly, R. & Hu, F. S. Arctic & boreal paleofire records reveal drivers of fire activity & departures from Holocene variability. Ecology 101(9), e03096 (2020).Article 

Google Scholar 
Bradshaw, C. J. & Warkentin, I. G. Global estimates of boreal forest carbon stocks & flux. Global Planet. Change 128, 24–30 (2015).Article 

Google Scholar 
Kuhry, P. & Turunen, J. The postglacial development of boreal and subarctic peatlands in Boreal Peatland Ecosystems, 25–46 (Springer, 2006).Walker, X. J. et al. Increasing wildfires threaten historic carbon sink of boreal forest soils. Nature 572(7770), 520–523 (2019).CAS 
Article 

Google Scholar 
Gauthier, S., Bernier, P., Kuuluvainen, T., Shvidenko, A. Z. & Schepaschenko, D. G. Boreal forest health & global change. Science 349(6250), 819–822 (2015).CAS 
Article 

Google Scholar 
Walker, X. J. et al. Cross-scale controls on carbon emissions from boreal forest megafires. Global Change Biol. 24(9), 4251–4265 (2018).Article 

Google Scholar 
Flannigan, M. D., Logan, K. A., Amiro, B. D., Skinner, W. R. & Stocks, B. J. Future area burned in Canada. Clim. Change 72(1), 1–16 (2005).CAS 
Article 

Google Scholar 
Balshi, M. S. et al. Assessing the response of area burned to changing climate in western boreal North America using a Multivariate Adaptive Regression Splines (MARS) approach. Global Change Biol. 15(3), 578–600 (2009).Article 

Google Scholar 
Johnstone, J. F. & Chapin, F. S. Fire interval effects on successional trajectory in boreal forests of northwest Canada. Ecosystems 9(2), 268–277 (2006).Article 

Google Scholar 
Viereck, L.A. & Little, E.L. Alaska trees & shrubs. US Forest Service 410, (1972).Paine, R. T., Tegner, M. J. & Johnson, E. A. Compounded perturbations yield ecological surprises. Ecosystems 1(6), 535–545 (1998).Article 

Google Scholar 
Buma, B. Disturbance interactions: characterization, prediction, & the potential for cascading effects. Ecosphere 6(4), 1–15 (2015).Article 

Google Scholar 
Burton, P. J., Jentsch, A. & Walker, L. R. The ecology of disturbance interactions. Bioscience 70(10), 854–870 (2020).Article 

Google Scholar 
Brown, C. D. & Johnstone, J. F. Once burned, twice shy: Repeat fires reduce seed availability & alter substrate constraints on Picea mariana regeneration. Forest Ecol. Manage. 266, 34–41 (2012).Article 

Google Scholar 
Buma, B., Brown, C. D., Donato, D. C., Fontaine, J. B. & Johnstone, J. F. The impacts of changing disturbance regimes on serotinous plant populations & communities. Bioscience 63(11), 866–876 (2013).Article 

Google Scholar 
Coop, J. D. et al. Wildfire-driven forest conversion in western North American landscapes. Bioscience 70(8), 659–673 (2020).Article 

Google Scholar 
Enright, N. J., Fontaine, J. B., Bowman, D. M., Bradstock, R. A. & Williams, R. J. Interval squeeze: altered fire regimes & demographic responses interact to threaten woody species persistence as climate changes. Front. Ecol. Enviro 13(5), 265–272 (2015).Article 

Google Scholar 
Burns, R.M., & Honkala B.H. Silvics of North America US Department of Agriculture, Forest Service, Ag. Handbook 654, (1990).Hayes, K. & Buma, B. Effects of short-interval disturbances continue to accumulate, overwhelming variability in local resilience. Ecosphere 12(3), 03379 (2021).Article 

Google Scholar 
Mack, M. C. et al. Carbon loss from boreal forest wildfires offset by increased dominance of deciduous trees. Science 372(6539), 280–283 (2021).CAS 
Article 

Google Scholar 
Viereck, L. A., Dyrness, C. T. & Foote, M. J. An overview of the vegetation & soils of the floodplain ecosystems of the Tanana River, interior Alaska. Can. J. For. Res. 23(5), 889–898 (1993).Article 

Google Scholar 
Hoy, E. E., Turetsky, M. R. & Kasischke, E. S. More frequent burning increases vulnerability of Alaskan boreal black spruce forests. Enviro. Res. Lett. 11(9), 095001 (2016).Article 

Google Scholar 
Whitman, E., Parisien, M. A., Thompson, D. K. & Flannigan, M. D. Short-interval wildfire & drought overwhelm boreal forest resilience. Sci. Rep. 9(1), 1–12 (2019).Article 

Google Scholar 
Greene, D. F. et al. The reduction of organic-layer depth by wildfire in the North American boreal forest & its effect on tree recruitment by seed. Can. J. For. Res. 37(6), 1012–1023 (2007).Article 

Google Scholar 
Héon, J., Arseneault, D. & Parisien, M. A. Resistance of the boreal forest to high burn rates. PNAS 111(38), 13888–13893 (2014).Article 

Google Scholar 
Buma, B., Weiss, S., Hayes, K. & Lucash, M. Wildland fire reburning trends across the US West suggest only short-term negative feedback & differing climatic effects. Enviro. Res. Lett. 15(3), 034026 (2020).Article 

Google Scholar 
Thompson, D. K. et al. Fuel accumulation in a high-frequency boreal wildfire regime: from wetland to upland. Can. J. For. Res. 47(7), 957–964 (2017).Article 

Google Scholar 
Kasischke, E. S. et al. Alaska’s changing fire regime—implications for the vulnerability of its boreal forests. Can. J. For. Res. 40(7), 1313–1324 (2010).Article 

Google Scholar 
Kelly, R. et al. Recent burning of boreal forests exceeds fire regime limits of the past 10,000 years. PNAS 110(32), 13055–13060 (2013).CAS 
Article 

Google Scholar 
Gaboriau, D. M. et al. Temperature & fuel availability control fire size/severity in the boreal forest of central Northwest Territories, Canada. Quat. Sci. Rev. 250, 106697 (2020).Article 

Google Scholar 
Johnstone, J. F., Rupp, T. S., Olson, M. & Verbyla, D. Modeling impacts of fire severity on successional trajectories & future fire behavior in Alaskan boreal forests. Landscape Ecol. 26(4), 487–500 (2011).Article 

Google Scholar 
Hess, K. A. et al. Satellite-based assessment of grassland conversion & related fire disturbance in the Kenai Peninsula, Alaska. Rem. Sens. 11(3), 283 (2019).Article 

Google Scholar 
Hollingsworth, T. N., Breen, A. L., Hewitt, R. E. & Mack, M. C. Does fire always accelerate shrub expansion in Arctic tundra? Examining a novel grass-dominated successional trajectory on the Seward Peninsula. A. A. A. Res. 53(1), 93–109 (2021).
Google Scholar 
Turner, M. G., Romme, W. H. & Tinker, D. B. Surprises & lessons from the 1988 Yellowstone fires. Frontiers Ecol. Environ. 1(7), 351–358 (2003).Article 

Google Scholar 
Shvidenko, A. Z. et al. Impact of wildfire in Russia between 1998–2010 on ecosystems & the global carbon budget. Dokl. Earth Sci. 441(2), 1678–1682 (2011).CAS 
Article 

Google Scholar 
Alaska Fire Service 2021. Alaska Interagency Coordination Center, Bureau of L& Management, Alaska Fire Service. https://fire.ak.blm.gov/arcgis/rest/services/Map&FeatureServices/FireHistory/MapServer/1French, N. H. et al. Using Landsat data to assess fire & burn severity in the North American boreal forest region: an overview and summary of results. Int. J. Wildland Fire 17(4), 443–462 (2008).Article 

Google Scholar 
Morimoto, M. & Juday, G. Perspectives on Sustainable Forest Management in Interior Alaska Boreal Forest: Recent History and Challenges. Forests 10(6), 484 (2019).Article 

Google Scholar 
NASA/METI/AIST/Japan Spacesystems, & U.S./Japan ASTER Science Team. ASTER Global Digital Elevation Model V003. distributed by NASA EOSDIS L& Processes DAAC, https://doi.org/10.5067/ASTER/ASTGTM.003 (2018)Fick, S. E. & Hijmans, R. J. WorldClim 2: New 1-km spatial resolution climate surfaces for global land areas. Int. J. Clim 37(12), 4302–4315 (2017).Article 

Google Scholar 
US Environmental Protection Agency, Level III Ecoregions of the Continental United States, Corvallis, Oregon: U.S. EPA— National Health & Environmental Effects Research Laboratory https://epa.gov/eco-research/level-iii-&-ivecoregions-continental-united-states (2013)Wang, J.A., et al. ABoVE: Landsat-derived Annual Dominant Land Cover Across ABoVE Core Domain, 1984-2014. ORNL DAAC, Oak Ridge, Tennessee, USA (2019).. https://doi.org/10.3334/ORNLDAAC/1691Debeer, D. & Strobl, C. Conditional permutation importance revisited. BMC Bioinform. 21(1), 1–30 (2020).Article 

Google Scholar 
Strobl, C., Boulesteix, A. L., Kneib, T., Augustin, T. & Zeileis, A. Conditional variable importance for r&om forests. BMC Bioinform. 9(1), 1–11 (2008).Article 

Google Scholar 
Moisen, G. & Frescino, T. Comparing five modelling techniques for predicting forest characteristics. Ecol. Mod. 157, 209–225 (2002).Article 

Google Scholar 
R Core Team R: A language & environment for statistical computing (2021).Pebesma, E.J. & Bivand, R.S. Classes and methods for spatial data in R. R News 5 (2), https://cran.r-project.org/doc/Rnews/. (2005)Hijmans, R.J. raster: Geographic Data Analysis and Modeling. R package version 3.4–5. (2020) https://CRAN.R-project.org/package=rasterStrobl, C., Boulesteix, A.-L., Kneib, T., Augustin, T. & Zeileis, A. Conditional variable importance for random forests. BMC Bioinform. 9, 307 (2008).Article 

Google Scholar 
Debeer, D., Hothorn, T. & Strobl, C permimp: Conditional Permutation Importance. R package version 1.0–1. https://CRAN.R-project.org/package=permimp (2021)Schneider, G., Chicken, E., & Becvarik, R. NSM3:Functions and Datasets to Accompany Hollander, Wolfe, and Chicken – Nonparametric Statistical Methods, Third Edition. R package version 1.16. https://CRAN.R-project.org/package=NSM3 (2021) More

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doi: https://doi.org/10.1038/d41586-022-00832-x

ReferencesLiu, J. et al. Conserv. Biol. https://doi.org/10.1111/cobi.13907 (2022).Article 

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Siver et al.19 identified three categories of fossil Mallomonas species uncovered in the extensive Giraffe Pipe locality. One group of species had scales with morphological characteristics similar to, and difficult to separate from, modern congeners. Based on a morphological species concept, these could be viewed as representing the same species. A second group had morphologically different scales, but ones that could be linked to one or more modern species. The third group possessed scales that could not be directly linked to any modern species. The majority of the species contained in the latter group lacked a V-rib and well developed dome, and were considered as stem organisms within the broad section Planae. Siver et al.19 further reported that the mean size of scales in the group containing the extinct stem taxa was larger than those fossil taxa grouped with modern congeners.The current study adds additional modern and fossil species to the database used by Siver et al.19, including the oldest known taxon from the Cretaceous Wombat locality, and provides the first attempt to reconstruct cell size for fossil Mallomonas species. Based on the expanded database, several trends with respect to the evolution of scale and cell size of Mallomonas taxa can be made. First, there is a strong relationship between scale width and scale length that was similar for both fossil and modern forms. Second, as a group, fossil taxa had scales that are significantly larger than those produced by modern species, especially with respect to surface area. The five species with the largest scales belong to extinct fossil species, four of which belong to the group of stem taxa within section Planae. These scales are massive compared with modern forms, and support the concept of scale gigantism for early members of the Mallomonas clade containing species with scales that lack a V-rib and dome (Fig. 1; subclade A2). Third, assuming the model relating scale and cell size can be applied to the geologic record, fossil species produced significantly larger cells than modern forms.Because the models relating scale length to scale width were similar for modern and fossil species, the assumption is that the models developed relating scale size to cell size are appropriate for fossil taxa. In addition, the precise overlapping pattern of scales comprising the cell covering on modern species has recently been documented for Eocene fossil species22, indicating that this architectural design was well evolved by at least the early Eocene. Thus, making the assumption that other fossil taxa had similarly constructed cell coverings is reasonable, and further supports the application of the models relating scale and cell size to these fossil forms.Based on the model estimates, the mean cell size of the fossil species is approximately twice as large as the average cell produced by modern organisms. This doubling of cell size was also observed for the smallest species. The mean size of the five smallest modern species (M. canina, M. mangofera, M. dickii, M. madagascariensis, and M. gutata) was 9.3 × 5 µm, compared to the mean cell size estimated for the five smallest fossil taxa (M. pseudohamata, M. preisigii, M. dispar, M. bakeri and M. GP4) of 18 × 8.7 µm. The cell size discrepancy is even greater for fossil species that lack modern congeners, and especially for the extinct stem species within section Planae that possessed an average cell size of 69.2 × 20.8 µm, with a maximum cell size of 81.7 × 22.7 µm for M. GP13. The scales produced by these large fossil cells were not only massive in size, but also robust and heavily silicified. It is likely that these large cells covered with large, heavy and cumbersome scales would have been slow swimmers that expended significantly more energy to maintain their position in the water column than modern species. Perhaps these cells were also more prone to predation by larger zooplankton, and a combination of decreased motility and greater predation provided the evolutionary pressure for smaller and faster cells with less dense siliceous components, and ultimately caused the demise of the large-celled fossil species. In contrast, it is also possible that the stimulus initially resulting in the evolution of the larger species was the fact that they were too big to be preyed upon by smaller invertebrates.Several points regarding the models used to estimate cell size are warranted. First, it is important to note that because the scale sizes used to estimate cell sizes for the larger fossil taxa are at the end of the range used to produce the model, caution needs to be exercised. The assumption is being made that the linear relationship of the model holds for the larger scales, and that the linear relationship does not begin to flatten and reach a maximum cell size. However, there is no indication that the relationship is reaching an asymptote, nor reason to assume that the model would not hold for organisms that produce larger siliceous components. Second, the scale and cell size data used to produce the models consisted of the midpoint values of the ranges given in the literature. Thus, the cell sizes inferred from the models represent a midpoint estimate of the range for each species, and not an upper size limit. Third, there is more data available in the literature documenting scale size than there is for cell size for most modern Mallomonas species. Additional data on cell size, especially inclusion of mean values, may help to further fine-tune the models. Lastly, the formula of an ellipse was used to estimate scale surface area for the few species with “square-shaped” scales. Although this may slightly underestimate the surface area, using a formula for a square or rectangle would have resulted in an overestimation. Because the few species with square-shaped scales were primarily the extinct fossil taxa lacking modern congeners, their cell size may actually have been slightly larger than estimated in this study.Interestingly, fossil scales that have morphologically similar (identical) modern counterparts were not significantly different in size from each other, implying that their corresponding cells were also of similar size. These taxa have significantly smaller scales compared to those species with gigantic scales, and closer to the mean of modern species. Perhaps, this is why the lineages of these morphologically-identical species have survived for tens of millions of years. Despite maintaining virtually identical scale types, the degree of genetic difference from a physiological or reproductive perspective between taxa with virtually identical siliceous components remains unknown19,23.The extinct scale types are not only significantly larger than those of species with modern congeners, but some have a tendency of being more rectangular to square-shaped. In contrast, fossil scale types that can be linked to modern species, along with their contemporary counterparts, tend to have elliptical-shaped scales. This is especially true of body scales15,16,19. Although a few smaller species of Mallomonas form spherical cells, the vast majority of species produce ellipsoidal-shaped cells, and this is especially true of species forming larger cells15,16. Smaller elliptical-shaped scales would be more efficient in covering a curving ellipsoidal cell surface than larger and square-shaped scales, and allow for a closer fitting cell covering. Jadrná et al.26 recently reported that scales of the closely related synurophyte genus, Synura, have also become smaller and more elongate over geologic time, complementing the observations for Mallomonas. Taken together, these findings support the idea that the evolutionary trend for synurophyte organisms has been towards smaller, elliptical scales.Cyanobacteria, a prokaryotic group of organisms estimated to have evolved by 3.5–3.4 Ga, represent one of the earliest known and smallest life forms on Earth27. Since the evolution of these early prokaryotes, Smith et al.28 estimated that the maximum body size of subsequent life forms has increased approximately 18-fold, with large jumps occurring with the evolution of eukaryote cells, and another concurrent with the advent of multicellularity. In contrast, shifts in the sizes of siliceous scales and corresponding cells of Mallomonas species are small in comparison, within an order of magnitude, and similar to changes observed for prokaryote organisms and other unicellular protists over the Geozoic28,29.Despite the overall lack of historical information on cell size for the majority of unicellular eukaryote lineages, there are data for some organisms that build resistant cell walls or coverings that are taxonomically diagnostic and become incorporated into the fossil record. Diatoms produce a siliceous cell wall known as the frustule, a structure composed of top and bottom pieces called valves that are held together with additional structures called girdle bands. Frustules, or their valve components, can be uncovered from the fossil record and used to provide a direct measure of cell size. Using this technique, Finkel et al.29 reported that the size of planktic marine diatoms declined over the Cenozoic, and correlated the shift with abiotic forcing factors, including a rise in sea surface temperature and water column stratification. Foraminifera are heterotrophic marine protists that build shells out of calcium carbonate, the latter of which can also become part of the fossil record. Changes in the size of foraminifera shells over the Cenozoic have also been correlated with shifts in the intensity of water column stratification30. At this time, it is not known if the decline in cell size for Mallomonas species in the section Planae lineage recorded in the current study was the result of abiotic variables (e.g. energy expenditure or temperature), biotic factors (e.g. predation), or a combination of forcing variables.The current study has provided a means to link scale size to cell size for Mallomonas that, in turn, can be used to trace shifts in cell size over geologic time. As additional scales of Mallomonas species are uncovered from the fossil record, the scale-to-cell size model will be a valuable tool for continuing to unravel the evolutionary history of cell size for this important photosynthetic organism. Other groups of unicellular protists, including euglyphids, heliozoids and rotosphaerids, are similar to synurophytes in that they build cell coverings using numerous overlapping siliceous scales or plates that can become fossilize. Perhaps the same technique of relating scale size to cell size could be used to develop models for these protist organisms, and similarly applied to the fossil record.It is interesting to note that most modern Mallomonas species with large body scales are found in warm tropical regions, including M. bronchartiana Compère, M. pseudobronchartiana Gusev, Siver & Shin, M. velari Gusev, Siver & Shin31, M. vietnamica Gusev, Kezlya & Trans32, M. gusakovii33 and several varieties of M. matvienkoae16. In addition, the modern tropical taxa M. neoampla Gusev & Siver and M. vietnamica share several rare features of their scales and bristles with fossil species recorded from the Giraffe locality, suggesting a possible link between the modern tropical and fossil floras. During the early to middle Eocene, the Earth experienced warm greenhouse conditions and lacked a cryosphere34. The Giraffe locality, positioned near the Arctic Circle, had an estimated mean annual temperature 17 °C warmer, and a mean annual precipitation over four times higher, than present conditions35. In fact, the assemblage of plants and animals in the Eocene Arctic has been described as analogous to those found today in eastern Asia36. Perhaps tropical regions, especially in southeastern Asia, offered refugia for some of the ancient Mallomonas lineages.In summary, multiple extinct fossil species of the diverse and common synurophyte genus, Mallomonas, are reported here to have possessed gigantic scales that are significantly larger than those found on modern species. Based on a model relating scale to cell size, cells of fossil Mallomonas species were estimated to be, on average, twice as large as modern species. A combination of larger cells with heavy siliceous scales that fit less effectively around the cell may have resulted in slower cells more prone to predation, heavier cells requiring more energy resources to maintain their position in the water column, and ultimately their demise. Additional fossil species, especially representing other localities and time periods, will ultimately strengthen our understanding of the evolution of scale and cell size in synurophyte algae. More