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    Inferring the ecological niche of bat viruses closely related to SARS-CoV-2 using phylogeographic analyses of Rhinolophus species

    Genetic analyses of Rhinolophus species identified as reservoirs of viruses closely related to SARS-CoV-2Until now, SCoV2rCs have been found in four bat species of the genus Rhinolophus: R. acuminatus, R. affinis, R. malayanus, and R. shameli. The haplotype networks constructed using CO1 sequences of these four species are shown in Fig. 3. A star-like genetic pattern, characterized by one dominant haplotype and several satellite haplotypes was found for the two bat species endemic to Southeast Asia, i.e. R. acuminatus and R. shameli.Figure 3Haplotype networks based on CO1 sequences of the four Rhinolophus species found positive for viruses closely related to SARS-CoV-2 (SCoV2rCs). The networks were constructed with the median joining method available in PopART 1.513 and modified under Adobe Illustrator CS6 (version 16.0). The codes used for the countries are the following: B (Myanmar), C (Cambodia), Ch (China), I (Indonesia), L (Laos), M (Malaysia), T (Thailand), and V (Vietnam). Colours indicate the geographic origin of haplotypes according to Fig. 2 (see online supplementary Table S1). The circles indicate haplotypes separated by at least one mutation. The black lines on the branches show the number of mutations ≥ 2. Black circles represent missing haplotypes. Circle size is proportional to the number of haplotypes. Haplogroups separated by more than seven mutations (pairwise nucleotide distances  > 1%) are highlighted by dotted lines. The red arrows show the positions of the nine bats found positive for SCoV2rCs.Full size imageIn the network of R. acuminatus, the most common haplotype (named Rac1 in online supplementary Table S1) was found in northern Cambodia, southern Laos, eastern Thailand and southern Vietnam, indicating recent gene flow among these populations. Since a virus related to SARS-CoV-2 (91.8% of genome identity), named RacCS203, was detected in five R. acuminatus bats caught in eastern Thailand in June 20206, the genetic pattern obtained for this species suggests that viruses closely related to RacCS203 may have circulated in most southern regions of mainland Southeast Asia. In contrast, R. acuminatus bats collected in Borneo (M5) showed a divergent haplotype (separated by 12 mutations; haplogroup II), suggesting that the South China Sea between mainland Southeast Asia and Borneo constitutes a barrier to gene flow. Isolated populations of R. acuminatus described in northern Myanmar, Indonesia (Java and Sumatra) and the Philippines14 should be further studied.The network of R. shameli shows a typical star-like pattern, the most common haplotype (named Rsh1 in online supplementary Table S1) being detected in northern Cambodia and Laos. Since a virus related to SARS-CoV-2 (93.1% of genome identity), named RshSTT200, was recently discovered in two R. shameli bats collected in northern Cambodia in December 20107, the genetic pattern obtained for this species suggests that viruses closely related to RshSTT200 may have circulated, at least in the zone between northern Cambodia and central Laos. The bats sampled south to the Tonle Sap lake (n = 4; southern Cambodia and Vietnamese island of Phu Quoc) were found to be genetically isolated from northern populations (four mutations). However, further sampling in the south is required to confirm this result, as it may reveal CO1 sequences identical to the haplotypes detected in the north.For the two species distributed in both China and Southeast Asia, i.e. R. affinis and R. malayanus, the genetic patterns are more complex with different haplogroups showing more than 1% of nucleotide divergence. In the network of R. affinis, there are three major haplogroups (named I, II and III in Fig. 3) separated by a minimum of seven mutations. The results are therefore in agreement with those previously published using CO1 and D-loop mitochondrial sequences15. The CO1 haplotypes detected in the localities sampled in southern China (ch1, ch4, ch5) are distantly related to the single haplotype available for central China (ch6), but they are also found in Laos, northern and central Vietnam, northern Thailand and northeastern Myanmar. This result suggests recent gene flow between populations from southern Yunnan and those from northern mainland Southeast Asia. Since a virus related to SARS-CoV-2 (96.2% of genome identity), named RaTG13, was detected in one R. affinis bat captured in southern Yunnan in 20131, the genetic pattern obtained for this species suggests that viruses closely related to RaTG13 may have circulated in the zone comprising southern Yunnan and northern mainland Southeast Asia.In the network of R. malayanus, there are four major haplogroups (named I, II, III and IV in Fig. 3) separated by a minimum of seven mutations. The CO1 haplotypes detected in the localities sampled in southern China (ch2 and ch3) were also found in northern Laos (L1 and L3), suggesting recent gene flow between populations from these two countries. Since a virus related to SARS-CoV-2 (93.7% of genome identity), named RmYN02, was recently isolated from one R. malayanus bat collected in southern Yunnan in June 20195, the genetic pattern obtained for this species suggests that viruses closely related to RmYN02 may have circulated, at least between southern Yunnan and northern Laos. In contrast, the bats sampled in Myanmar were found to be genetically isolated from other geographic populations (haplogroup II in Fig. 3).Two different ecological niches for bat viruses related to either SARS-CoV or SARS-CoV-2In the wild, sarbecoviruses were generally detected after examining fecal samples collected on dozens of bats. For instance, two sarbecoviruses were found7 among the total 59 bats collected at the same cave entrance in northern Cambodia in 2010 (unpublished data). However, this does not mean necessarily that sarbecoviruses were absent in negative samples, as degradation of RNA molecules and very low viral concentrations may prevent the detection of RNA viruses. Despite these difficulties, full genomes of Sarbecovirus have been sequenced from a wide diversity of horseshoe bat species collected in Asia, Africa and Europe5,6,7,8,9,10. Therefore, there is no doubt that Rhinolophus species constitute the natural reservoir host of all sarbecoviruses3,8. The genus Rhinolophus currently includes between 9211 and 10916 insectivorous species that inhabit temperate and tropical regions of the Old World, with a higher biodiversity in Asia (63–68 out of the 92–109 described species) than in Africa (34–38 species), Europe (5 species) and Oceania (5 species). Although some Rhinolophus species are solitary, most of them are gregarious and live in large colonies or small groups generally in caves and hollow trees, but also in burrows, tunnels, abandonned mines, and old buildings11,16. However, they prefer large caves with total darkness, where temperatures are stable and less affected by diurnal and seasonal climatic variations. Importantly, all Rhinolophus species in which sarbecoviruses were detected in previous studies1,5,6,7,8,9,17 are cave species that form small groups or colonies (up to several hundreds)11,18,19.In China, many SCoVrCs were previously detected in several horseshoe bat species, including Rhinolophus sinicus, Rhinolophus ferrumequinum (currently R. nippon)16, Rhinolophus macrotis (currently R. episcopus)16, Rhinolophus pearsoni, and Rhinolophus pusillus, and it has been shown that they circulate not only among conspecific bats from the same colony, but also between bat species inhabiting the same caves17,20,21. The ecological niche predicted for bat SCoVrCs using a data set of 19 points (see online supplementary Table S2) is shown in Fig. 4. The AUC was 0.81. The value was  > 95% CI null-model’s AUCs (0.68), indicating that the model performs significantly better than a random model (see online supplementary Fig. S1). The highest probabilities of occurrence (highlighted in green in Fig. 4) were found in Nepal, Bhutan, Bangladesh, northeastern India, northern Myanmar, northern Vietnam, most regions of China south of the Yellow River, Taiwan, North and South Korea, and southern Japan.Figure 4Ecological niche of bat viruses related to SARS-CoV (SCoVrCs). The geographic distribution of suitable environments was predicted using the Maxent algorithm in ENMTools (see “Methods” section for details). AUC = 0.81. Black circles indicate localities used to build the distribution model (see geographic coordinates in online supplementary Table S2).Full size imageIn Southeast Asia and southern China, SCoV2rCs have currently been found in four Rhinolophus species (R. acuminatus, R. affinis, R. malayanus and R. shameli)1,6,7,8, but the greatest diversity of horseshoe bat species in mainland Southeast Asia (between 28 and 36 species)11,16 suggests that many sarbecoviruses will be discovered soon. Despite the limited data currently available on SCoV2rCs, several arguments support that bat intraspecific and interspecific transmissions also occur with SCoV2rCs. Firslty, recent genomic studies have revealed that SCoV2rCs circulate and evolve among horseshoe bats of the same colony, as five very similar genomes (nucleotide distances between 0.03% and 0.10%) were sequenced from five R. acuminatus bats collected from the same colony in eastern Thailand6, and as two genomes differing at only three nucleotide positions (distance = 0.01%) were sequenced from two R. shameli bats collected at the same cave entrance on the same night7. Secondly, the discovery of four viruses closely related to SARS-CoV-2 (between 96.2 and 91.8% of genome identity) in four different species of Rhinolophus is a strong evidence that interspecific transmission occurred several times in the past. As detailed in online supplementary Table S1, these species were collected together in several localities of Cambodia (three species in C1, C2, and C5; two species in C8), Laos (four species in L10; three species in L9; two species in L1, L5, L8, L11), and Vietnam (two speciess in V10, V9, V17, V18). These data corroborate previous studies suggesting that sarbecoviruses can be transmitted, at least occasionally, between Rhinolophus species sharing the same caves.The ecological niche of bat SCoV2rCs was firstly predicted using the four localities where bat viruses were previously detected1,6,7,8 (Fig. 5a). The highest probabilities of occurrence (highlighted in green in Fig. 5a) were found in Southeast Asia rather than in China. However, the AUC was only 0.58, and the value was  95% CI null-model’s AUCs (0.81), indicating that the model performs significantly better than a random model (see online supplementary Fig. S3). The areas showing the highest probabilities of occurrence (highlighted in green in Fig. 5b) include four main geographic areas: (i) southern Yunnan, northern Laos and bordering regions in northern Thailand and northwestern Vietnam; (ii) southern Laos, southwestern Vietnam, and northeastern Cambodia; (iii) the Cardamom Mountains in southwestern Cambodia and the East region of Thailand; and (iv) the Dawna Range in central Thailand and southeastern Myanmar.Figure 5Ecological niches of bat viruses closely related to SARS-CoV-2 (SCoV2rCs) predicted using 4 points (a) (AUC = 0.58) and 21 points (b) (AUC = 0.96). The geographic distributions of suitable environments were predicted using the Maxent algorithm in ENMTools (see “Methods” section for details). Black circles indicate localities used to build the distribution model (see geographic coordinates in online supplementary Table S1).Full size imageOur results show that bat SCoVrCs and SCoV2rCs have different ecological niches: that of SCoVrCs covers mainly China and several adjacent countries and extends to latitudes between 18° and 43°N, whereas that of SCoV2rCs covers northern mainland Southeast Asia and extends to latitudes between 10° and 24°N. Most Rhinolophus species involved in the ecological niche of SCoVrCs have to hibernate in winter when insect populations become significantly less abundant. This may be different for most Rhinolophus species involved in the ecological niche of SCoVrC2s. Since this ecological difference may be crucial for the dynamics of viral transmission among bat populations, it needs to be further studied through comparative field surveys in different regions of China and Southeast Asia. The ecological niches of SCoVrCs and SCoV2rCs slightly overlap in the zone including southern Yunnan, northern Laos, and northern Vietnam (Figs. 4, 5b). This zone corresponds to the northern edge of tropical monsoon climate23. Highly divergent sarbecoviruses of the two main lineages SCoVrCs and SCoV2rCs are expected to be found in sympatry in this area. This is confirmed by the discovery of both SCoVrCs and SCoV2rCs in horseshoe bats collected in southern Yunnan1,6,21. Collectively, these data suggest that genomic recombination between viruses of the two divergent lineages are more likely to occur in bats roosting, at least seasonally, in the caves of these regions. Since highly recombinant viruses can threaten the benefit of vaccination campaigns, southern Yunnan, northern Laos, and northern Vietnam should be the targets of closer surveillance.Mainland Southeast Asia is the cradle of diversification of bat SCoV2rCsChinese researchers have actively sought sarbecoviruses in all Chinese provinces after the 2002–2004 SARS outbreak. They found many bat SCoVrCs16,20,21 but only two SCoV2rCs1,5 and both of them were discovered in southern Yunnan, the Chinese province bordering Southeast Asia. The ecological niches predicted herein for bat sarbecoviruses suggest that SCoVrCs are dominant in China (Fig. 4) while SCoV2rCs are present mostly in Southeast Asia (Fig. 5). This means that viruses similar to SARS-CoV-2 have been circulating for several decades throughout Southeast Asia, and that different species of bats have exchanged these viruses in the caves they inhabit. The data available on human cases and deaths caused by the COVID-19 pandemic2 indirectly support the hypothesis that the cradle of diversification of bat SCoV2rCs is mainland Southeast Asia, and in particular the areas highlighted in green in Fig. 5b. Indeed, human populations in Cambodia, Laos, Thailand, and Vietnam appear to be much less affected by the COVID-19 pandemic than other countries of the region, such as Indonesia, Malaysia, Myanmar, and the Philippines (Fig. 6). This suggests that some human populations of Cambodia, Laos, Thailand, and Vietnam, in particular rural populations living in contact with wild animals for several generations, have a better immunity against SCoV2rCs because they have been regularly contaminated by bats and/or infected secondary hosts such as pangolins.Figure 6Number of COVID-19 patients per million inhabitants (in blue) and deaths per million inhabitants (in red) for the different countries of Southeast Asia. Data extracted from the Worldometers website2 on June 08, 2021. The figure was drawn in Microsoft Excel and PowerPoint (version 16.16.27).Full size imagePangolins contaminated by bats in Southeast AsiaApart from bats, the Sunda pangolin (Manis javanica) and Chinese pangolin (Manis pentadactyla) are the only wild animals in which viruses related to SARS-CoV-2 have been found so far. However, these discoveries were made in a rather special context, that of pangolin trafficking. Several sick pangolins were seized by Chinese customs in Yunnan province in 2017 (unpublished data), in Guangxi province in 2017–201824 and in Guangdong province in 201925. Even if the viruses sequenced in pangolins are not that close to SARS-CoV-2 (one was 85% identical and the other 90%), they indicate that at least two sarbecoviruses could have been imported into China well before the emergence of COVID-19 epidemic. Indeed, it has been shown that Sunda pangolins collected from different Southeast Asian regions have contaminated each other while in captivity on Chinese territory3. It has been estimated that 43% of seized pangolins were infected by at least one SARS-CoV-2-like virus3. Such a high level of viral prevalence and the symptoms of acute interstitial pneumonia detected in most dead pangolins24 indicate that captive pangolins are highly permissive to infection by SARS-CoV-2-like viruses. The question remained on how the Sunda pangolins became infected initially. Could it have been in their natural Southeast Asian environment, before being captured? The discovery of two new viruses close to SARS-CoV-2 in bats from Cambodia and Thailand7,8 supports this hypothesis, as Rhinolophus bats and pangolins can meet, at least occasionally, in forests of Southeast Asia, possibly in caves, tree hollows or burrows. Further substantiating this hypothesis, the geographic distribution of Manis javanica26 overlaps the ecological niche here predicted for bat SCoV2rCs (Fig. 5), and SARS-CoV-2 neutralizing antibodies have been recently detected in one of the ten pangolin sera sampled from February to July 2020 from three wildlife checkpoint stations in Thailand6. Collectively, these data strengthen the hypothesis that pangolin trafficking is responsible for multiple exports of viruses related to SARS-CoV-2 to China3. More

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    Gene body DNA methylation in seagrasses: inter- and intraspecific differences and interaction with transcriptome plasticity under heat stress

    1.Merilä, J. & Hendry, A. P. Climate change, adaptation, and phenotypic plasticity: the problem and the evidence. Evol. Appl. 7, 1–14. https://doi.org/10.1111/eva.12137 (2014).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    2.Reusch, T. B. Climate change in the oceans: evolutionary versus phenotypically plastic responses of marine animals and plants. Evol. Appl. 7, 104–122. https://doi.org/10.1111/eva.12109 (2014).Article 
    PubMed 

    Google Scholar 
    3.Pazzaglia, J., Reusch, T. B., Terlizzi, A., Marín‐Guirao, L. & Procaccini, G. Phenotypic plasticity under rapid global changes: the intrinsic force for future seagrasses survival. Evol. Appl. (2021).4.Lopez-Maury, L., Marguerat, S. & Baehler, J. Tuning gene expression to changing environments: from rapid responses to evolutionary adaptation. Nat. Rev. Genet. 9, 583–593 (2008).CAS 
    PubMed 
    Article 

    Google Scholar 
    5.Mäkinen, H., Papakostas, S., Vøllestad, L. A., Leder, E. H. & Primmer, C. R. Plastic and evolutionary gene expression responses are correlated in European grayling (Thymallus thymallus) subpopulations adapted to different thermal environments. J. Hered. 107, 82–89 (2016).PubMed 
    Article 
    CAS 

    Google Scholar 
    6.Alonso, C., Pérez, R., Bazaga, P., Medrano, M. & Herrera, C. M. MSAP markers and global cytosine methylation in plants: a literature survey and comparative analysis for a wild-growing species. Mol. Ecol. Resour. 16, 80–90 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    7.Jeremias, G. et al. Synthesizing the role of epigenetics in the response and adaptation of species to climate change in freshwater ecosystems. Mol. Ecol. 27, 2790–2806 (2018).PubMed 
    Article 

    Google Scholar 
    8.Nicotra, A. B. et al. Adaptive plasticity and epigenetic variation in response to warming in an Alpine plant. Ecol. Evol. 5, 634–647 (2015).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    9.Kelly, S., Panhuis, T. & Stoehr, A. (2012).10.Thorson, J. L. et al. Epigenetics and adaptive phenotypic variation between habitats in an asexual snail. Sci. Rep. 7, 1–11 (2017).CAS 
    Article 

    Google Scholar 
    11.Rey, O., Danchin, E., Mirouze, M., Loot, C. & Blanchet, S. Adaptation to global change: a transposable element–epigenetics perspective. Trends Ecol. Evol. 31, 514–526. https://doi.org/10.1016/j.tree.2016.03.013 (2016).Article 
    PubMed 

    Google Scholar 
    12.Law, J. A. & Jacobsen, S. E. Establishing, maintaining and modifying DNA methylation patterns in plants and animals. Nat. Rev. Genet. 11, 204–220 (2010).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    13.Zemach, A., McDaniel, I. E., Silva, P. & Zilberman, D. Genome-wide evolutionary analysis of eukaryotic DNA methylation. Science 328, 916–919 (2010).CAS 
    PubMed 
    Article 
    ADS 

    Google Scholar 
    14.Niederhuth, C. E. et al. Widespread natural variation of DNA methylation within angiosperms. Genome Biol. 17, 1–19 (2016).Article 
    CAS 

    Google Scholar 
    15.Zhang, X. et al. Genome-wide high-resolution mapping and functional analysis of DNA methylation in Arabidopsis. Cell 126, 1189–1201 (2006).CAS 
    Article 

    Google Scholar 
    16.Bewick, A. J. et al. On the origin and evolutionary consequences of gene body DNA methylation. Proc. Natl. Acad. Sci. 113, 9111–9116 (2016).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    17.Bewick, A. J. & Schmitz, R. J. Gene body DNA methylation in plants. Curr. Opin. Plant Biol. 36, 103–110 (2017).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    18.Sarda, S., Zeng, J., Hunt, B. G. & Yi, S. V. The evolution of invertebrate gene body methylation. Mol. Biol. Evol. 29, 1907–1916 (2012).CAS 
    PubMed 
    Article 

    Google Scholar 
    19.Takuno, S. & Gaut, B. S. Body-methylated genes in Arabidopsis thaliana are functionally important and evolve slowly. Mol. Biol. Evol. 29, 219–227 (2012).CAS 
    PubMed 
    Article 

    Google Scholar 
    20.Takuno, S. & Gaut, B. S. Gene body methylation is conserved between plant orthologs and is of evolutionary consequence. Proc. Natl. Acad. Sci. 110, 1797–1802 (2013).CAS 
    PubMed 
    PubMed Central 
    Article 
    ADS 

    Google Scholar 
    21.Takuno, S., Ran, J.-H. & Gaut, B. S. Evolutionary patterns of genic DNA methylation vary across land plants. Nat. Plants 2, 1–7 (2016).Article 
    CAS 

    Google Scholar 
    22.Wendte, J. M. et al. Epimutations are associated with CHROMOMETHYLASE 3-induced de novo DNA methylation. Elife 8, e47891 (2019).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    23.Aceituno, F. F., Moseyko, N., Rhee, S. Y. & Gutiérrez, R. A. The rules of gene expression in plants: organ identity and gene body methylation are key factors for regulation of gene expression in Arabidopsis thaliana. BMC Genomics 9, 438 (2008).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    24.Elango, N., Hunt, B. G., Goodisman, M. A. & Soojin, V. Y. DNA methylation is widespread and associated with differential gene expression in castes of the honeybee, Apis mellifera. Proc. Natl. Acad. Sci. 106, 11206–11211 (2009).CAS 
    PubMed 
    PubMed Central 
    Article 
    ADS 

    Google Scholar 
    25.Gavery, M. R. & Roberts, S. B. DNA methylation patterns provide insight into epigenetic regulation in the Pacific oyster (Crassostrea gigas). BMC Genomics 11, 1–9 (2010).Article 
    CAS 

    Google Scholar 
    26.Zilberman, D., Gehring, M., Tran, R. K., Ballinger, T. & Henikoff, S. Genome-wide analysis of Arabidopsis thaliana DNA methylation uncovers an interdependence between methylation and transcription. Nat. Genet. 39, 61–69 (2007).CAS 
    PubMed 
    Article 

    Google Scholar 
    27.Coleman-Derr, D. & Zilberman, D. in Cold Spring Harbor symposia on quantitative biology. 147–154 (Cold Spring Harbor Laboratory Press).28.Kim, M. Y. & Zilberman, D. DNA methylation as a system of plant genomic immunity. Trends Plant Sci. 19, 320–326 (2014).CAS 
    PubMed 
    Article 

    Google Scholar 
    29.Muyle, A. & Gaut, B. S. Loss of gene body methylation in Eutrema salsugineum is associated with reduced gene expression. Mol. Biol. Evol. 36, 155–158 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    30.Roberts, S. B. & Gavery, M. R. Is there a relationship between DNA methylation and phenotypic plasticity in invertebrates?. Front. Physiol. 2, 116 (2012).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    31.Dimond, J. L. & Roberts, S. B. Germline DNA methylation in reef corals: patterns and potential roles in response to environmental change. Mol. Ecol. 25, 1895–1904 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    32.Dixon, G. B., Bay, L. K. & Matz, M. V. Bimodal signatures of germline methylation are linked with gene expression plasticity in the coral Acropora millepora. BMC Genomics 15, 1–11 (2014).Article 
    CAS 

    Google Scholar 
    33.Bird, A. P. DNA methylation and the frequency of CpG in animal DNA. Nucleic Acids Res. 8, 1499–1504 (1980).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    34.Sved, J. & Bird, A. The expected equilibrium of the CpG dinucleotide in vertebrate genomes under a mutation model. Proc. Natl. Acad. Sci. 87, 4692–4696 (1990).CAS 
    PubMed 
    PubMed Central 
    Article 
    ADS 

    Google Scholar 
    35.Suzuki, M. M., Kerr, A. R., De Sousa, D. & Bird, A. CpG methylation is targeted to transcription units in an invertebrate genome. Genome Res. 17, 625–631 (2007).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    36.Weber, M. et al. Distribution, silencing potential and evolutionary impact of promoter DNA methylation in the human genome. Nat. Genet. 39, 457–466 (2007).CAS 
    PubMed 
    Article 

    Google Scholar 
    37.Glastad, K., Hunt, B. G., Yi, S. & Goodisman, M. DNA methylation in insects: on the brink of the epigenomic era. Insect Mol. Biol. 20, 553–565 (2011).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    38.Aliaga, B., Bulla, I., Mouahid, G., Duval, D. & Grunau, C. Universality of the DNA methylation codes in Eucaryotes. Sci. Rep. 9, 1–11 (2019).CAS 
    Article 

    Google Scholar 
    39.Asselman, J., De Coninck, D. I., Pfrender, M. E. & De Schamphelaere, K. A. Gene body methylation patterns in Daphnia are associated with gene family size. Genome Biol Evol 8, 1185–1196 (2016).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    40.Park, J. et al. Comparative analyses of DNA methylation and sequence evolution using Nasonia genomes. Mol. Biol. Evol. 28, 3345–3354 (2011).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    41.Olsen, J. L. et al. The genome of the seagrass Zostera marina reveals angiosperm adaptation to the sea. Nature 530, 331–335. https://doi.org/10.1038/nature16548 (2016).CAS 
    Article 
    PubMed 
    ADS 

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

    Google Scholar 
    43.Nordlund, L. M., Koch, E. W., Barbier, E. B. & Creed, J. C. Correction: Seagrass ecosystem services and their variability across genera and geographical regions. PLoS ONE 12, e0169942 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    44.Orth, R. J. et al. A global crisis for seagrass ecosystems. Bioscience 56, 987–996. https://doi.org/10.1641/0006-3568(2006)56[987:agcfse]2.0.co;2 (2006).Article 

    Google Scholar 
    45.Waycott, M. et al. Accelerating loss of seagrasses across the globe threatens coastal ecosystems. Proc. Natl. Acad. Sci. 106, 12377–12381. https://doi.org/10.1073/pnas.0905620106 (2009).Article 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 
    46.Koch, M., Bowes, G., Ross, C. & Zhang, X. H. Climate change and ocean acidification effects on seagrasses and marine macroalgae. Glob. Change Biol. 19, 103–132. https://doi.org/10.1111/j.1365-2486.2012.02791.x (2013).Article 
    ADS 

    Google Scholar 
    47.Marbà, N. & Duarte, C. M. Mediterranean warming triggers seagrass (Posidonia oceanica) shoot mortality. Glob. Change Biol. 16, 2366–2375. https://doi.org/10.1111/j.1365-2486.2009.02130.x (2010).Article 
    ADS 

    Google Scholar 
    48.Thomson, J. A. et al. Extreme temperatures, foundation species, and abrupt ecosystem change: an example from an iconic seagrass ecosystem. Glob. Change Biol. 21, 1463–1474. https://doi.org/10.1111/gcb.12694 (2014).Article 
    ADS 

    Google Scholar 
    49.Maxwell, P. S. et al. Phenotypic plasticity promotes persistence following severe events: physiological and morphological responses of seagrass to flooding. J. Ecol. 102, 54–64 (2014).Article 

    Google Scholar 
    50.Marín-Guirao, L., Ruiz, J. M., Dattolo, E., Garcia-Munoz, R. & Procaccini, G. Physiological and molecular evidence of differential short-term heat tolerance in Mediterranean seagrasses. Sci. Rep. 6, 28615. https://doi.org/10.1038/srep28615 (2016).CAS 
    Article 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 
    51.Sandoval-Gil, J. M., Ruiz, J. M., Marin-Guirao, L., Bernardeau-Esteller, J. & Sanchez-Lizaso, J. L. Ecophysiological plasticity of shallow and deep populations of the Mediterranean seagrasses Posidonia oceanica and Cymodocea nodosa in response to hypersaline stress. Mar. Environ. Res. 95, 39–61. https://doi.org/10.1016/j.marenvres.2013.12.011 (2014).CAS 
    Article 
    PubMed 

    Google Scholar 
    52.Franssen, S. et al. Transcriptomic resilience to global warming in the seagrass Zostera marina, a marine foundation species. Proc. Natl. Acad. Sci. USA 108, 19276–19281 (2011).CAS 
    PubMed 
    PubMed Central 
    Article 
    ADS 

    Google Scholar 
    53.Jueterbock, A. et al. Phylogeographic differentiation versus transcriptomic adaptation to warm temperatures in Zostera marina, a globally important seagrass. Mol. Ecol. 25, 5396–5411 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    54.Marín-Guirao, L., Entrambasaguas, L., Dattolo, E., Ruiz, J. M. & Procaccini, G. Molecular mechanisms behind the physiological resistance to intense transient warming in an iconic marine plant. Front. Plant Sci. https://doi.org/10.3389/fpls.2017.01142 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    55.Lee, H. et al. The genome of a southern hemisphere seagrass species (Zostera muelleri). Plant Physiol. (2016).56.Greco, M., Chiappetta, A., Bruno, L. & Bitonti, M. B. Effects of light deficiency on genome methylation in Posidonia oceanica. Mar. Ecol. Prog. Ser. 473, 103–114 (2013).CAS 
    Article 
    ADS 

    Google Scholar 
    57.Greco, M., Chiappetta, A., Bruno, L. & Bitonti, M. B. In Posidonia oceanica cadmium induces changes in DNA methylation and chromatin patterning. J. Exp. Bot. 63, 695–709. https://doi.org/10.1093/jxb/err313 (2012).CAS 
    Article 
    PubMed 

    Google Scholar 
    58.Ruocco, M., De Luca, P., Marín-Guirao, L. & Procaccini, G. Differential leaf age-dependent thermal plasticity in the keystone seagrass Posidonia oceanica. Front. Plant Sci. https://doi.org/10.3389/fpls.2019.01556 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    59.Ruocco, M., Marín-Guirao, L. & Procaccini, G. Within- and among-leaf variations in photo-physiological functions, gene expression and DNA methylation patterns in the large-sized seagrass Posidonia oceanica. Mar. Biol. 166, 24. https://doi.org/10.1007/s00227-019-3482-8 (2019).CAS 
    Article 

    Google Scholar 
    60.Ruocco, M. et al. A king and vassals’ tale: Molecular signatures of clonal integration in Posidonia oceanica under chronic light shortage. J. Ecol. (2020).61.Jueterbock, A. et al. The seagrass methylome is associated with variation in photosynthetic performance among clonal shoots. Front. Plant Sci. 11 (2020).62.Marín-Guirao, L. et al. Carbon economy of Mediterranean seagrasses in response to thermal stress. Mar. Pollut. Bull. 135, 617–629 (2018).PubMed 
    Article 
    CAS 

    Google Scholar 
    63.Beca-Carretero, P. et al. Effects of an experimental heat wave on fatty acid composition in two Mediterranean seagrass species. Mar. Pollut. Bull. 134, 27–37 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    64.Angers, B., Castonguay, E. & Massicotte, R. Environmentally induced phenotypes and DNA methylation: how to deal with unpredictable conditions until the next generation and after. Mol. Ecol. 19, 1283–1295 (2010).CAS 
    PubMed 
    Article 

    Google Scholar 
    65.Dubin, M. J. et al. DNA methylation in Arabidopsis has a genetic basis and shows evidence of local adaptation. Elife 4, e05255 (2015).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    66.Kawakatsu, T. et al. Epigenomic diversity in a global collection of Arabidopsis thaliana accessions. Cell 166, 492–505 (2016).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    67.Smith, Z. D. & Meissner, A. DNA methylation: roles in mammalian development. Nat. Rev. Genet. 14, 204–220 (2013).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    68.Serres-Giardi, L., Belkhir, K., David, J. & Glémin, S. Patterns and evolution of nucleotide landscapes in seed plants. Plant Cell 24, 1379–1397 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    69.Tatarinova, T., Elhaik, E. & Pellegrini, M. Cross-species analysis of genic GC3 content and DNA methylation patterns. Genome Biol. Evol. 5, 1443–1456 (2013).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    70.Vining, K. J. et al. Dynamic DNA cytosine methylation in the Populus trichocarpa genome: tissue-level variation and relationship to gene expression. BMC Genomics 13, 27 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    71.Lyko, F. et al. The honey bee epigenomes: differential methylation of brain DNA in queens and workers. PLoS Biol 8, 1506 (2010).Article 
    CAS 

    Google Scholar 
    72.Cortijo, S., Aydin, Z., Ahnert, S. & Locke, J. C. Widespread inter-individual gene expression variability in Arabidopsis thaliana. Mol. Syst. Biol. 15, e8591 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    73.Procaccini, G., Olsen, J. L. & Reusch, T. B. H. Contribution of genetics and genomics to seagrass biology and conservation. J. Exp. Mar. Biol. Ecol. 350, 234–259. https://doi.org/10.1016/j.jembe.2007.05.035 (2007).CAS 
    Article 

    Google Scholar 
    74.Alberto, F. et al. Genetic differentiation and secondary contact zone in the seagrass Cymodocea nodosa across the Mediterranean-Atlantic transition region. J. Biogeogr. 35, 1279–1294 (2008).Article 

    Google Scholar 
    75.Becker, C. et al. Spontaneous epigenetic variation in the Arabidopsis thaliana methylome. Nature 480, 245–249 (2011).CAS 
    PubMed 
    PubMed Central 
    Article 
    ADS 

    Google Scholar 
    76.Schmitz, R. J. et al. Patterns of population epigenomic diversity. Nature 495, 193–198 (2013).CAS 
    PubMed 
    PubMed Central 
    Article 
    ADS 

    Google Scholar 
    77.Yi, S. V. Insights into epigenome evolution from animal and plant methylomes. Genome Biol. Evol. 9, 3189–3201 (2017).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    78.Jahnke, M. et al. Adaptive responses along a depth and a latitudinal gradient in the endemic seagrass Posidonia oceanica. Heredity https://doi.org/10.1038/s41437-018-0103-0 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    79.Tuya, F. et al. Biogeographical scenarios modulate seagrass resistance to small-scale perturbations. J. Ecol. 107, 1263–1275 (2019).Article 

    Google Scholar 
    80.Gao, G. et al. Comparison of the heat stress induced variations in DNA methylation between heat-tolerant and heat-sensitive rapeseed seedlings. Breed. Sci. 64, 125–133 (2014).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    81.Dowen, R. H. et al. Widespread dynamic DNA methylation in response to biotic stress. Proc. Natl. Acad. Sci. 109, E2183–E2191 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    82.Wada, Y., Miyamoto, K., Kusano, T. & Sano, H. Association between up-regulation of stress-responsive genes and hypomethylation of genomic DNA in tobacco plants. Mol. Genet. Genomics 271, 658–666 (2004).CAS 
    PubMed 
    Article 

    Google Scholar 
    83.Yaish, M. W., Colasanti, J. & Rothstein, S. J. The role of epigenetic processes in controlling flowering time in plants exposed to stress. J. Exp. Bot. 62, 3727–3735 (2011).CAS 
    PubMed 
    Article 

    Google Scholar 
    84.Secco, D. et al. Stress induced gene expression drives transient DNA methylation changes at adjacent repetitive elements. Elife 4, e09343 (2015).PubMed Central 
    Article 
    PubMed 

    Google Scholar 
    85.Marín-Guirao, L., Entrambasaguas, L., Ruiz, J. M. & Procaccini, G. Heat-stress induced flowering can be a potential adaptive response to ocean warming for the iconic seagrass Posidonia oceanica. Mol. Ecol. 28, 2486–2501. https://doi.org/10.1111/mec.15089 (2019).Article 
    PubMed 

    Google Scholar 
    86.Nguyen, H. M. et al. Stress memory in seagrasses: first insight into the effects of thermal priming and the role of epigenetic modifications. Front. Plant Sci. 11, 494 (2020).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    87.Pikaard, C. S. & Scheid, O. M. Epigenetic regulation in plants. Cold Spring Harbor Perspect. Biol. 6, a019315 (2014).Article 
    CAS 

    Google Scholar 
    88.Yu, Y. et al. Cytosine methylation alteration in natural populations of Leymus chinensis induced by multiple abiotic stresses. PLoS ONE 8, e55772 (2013).CAS 
    PubMed 
    PubMed Central 
    Article 
    ADS 

    Google Scholar 
    89.Liu, R. & Lang, Z. The mechanism and function of active DNA demethylation in plants. J. Integr. Plant. Biol. 62, 148–159 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    90.Xu, X. et al. A CRISPR-based approach for targeted DNA demethylation. Cell Discovery 2, 1–12 (2016).
    Google Scholar 
    91.Arnaud-Haond, S. et al. Implications of extreme life span in clonal organisms: millenary clones in meadows of the threatened seagrass Posidonia oceanica. PLoS ONE 7, e30454. https://doi.org/10.1371/journal.pone.0030454 (2012).CAS 
    Article 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 
    92.Mascaró, O., Romero, J. & Pérez, M. Seasonal uncoupling of demographic processes in a marine clonal plant. Estuar. Coast. Shelf Sci. 142, 23–31 (2014).Article 
    ADS 

    Google Scholar 
    93.Olesen, B., Enríquez, S., Duarte, C. M. & Sand-Jensen, K. Depth-acclimation of photosynthesis, morphology and demography of Posidonia oceanica and Cymodocea nodosa in the Spanish Mediterranean Sea. Mar. Ecol. Prog. Ser. 236, 89–97. https://doi.org/10.3354/meps236089 (2002).Article 
    ADS 

    Google Scholar 
    94.Ruocco, M. et al. Genomewide transcriptional reprogramming in the seagrass Cymodocea nodosa under experimental ocean acidification. Mol. Ecol. 26, 4241–4259. https://doi.org/10.1111/mec.14204 (2017).CAS 
    Article 
    PubMed 

    Google Scholar 
    95.Fraley, C. & Raftery, A. E. Model-based methods of classification: using the mclust software in chemometrics. J. Stat. Softw. 18, 1–13 (2007).Article 

    Google Scholar 
    96.R Core Team (ISBN 3-900051-07-0, 2012).97.Benaglia, T., Chauveau, D., Hunter, D., Young, D. mixtools: an R package for analyzing finite mixture models (2009).98.Langmead, B., Trapnell, C., Pop, M. & Salzberg, S. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10, R25 (2009).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    99.Li, B. & Dewey, C. N. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformat. 12, 323 (2011).CAS 
    Article 

    Google Scholar 
    100.Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: a bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140. https://doi.org/10.1093/bioinformatics/btp616 (2010).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar  More

  • in

    The energy allocation trade-offs underlying life history traits in hypometabolic strepsirhines and other primates

    1.van Schaik, C. P. & Isler, K. Life-history evolution. In The Evolution of Primate Societies (eds Mitani, J., Call, J., Kappeler, P. M. et al.) 220–244 (Chicago University Press, 2012).
    Google Scholar 
    2.Pontzer, H. et al. Primate energetics and life history. Proc. Natl. Acad. Sci. USA 111, 1433–1437. https://doi.org/10.1073/pnas.1316940111 (2014).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    3.Burger, J. R., Hou, C. & Brown, J. H. Toward a metabolic theory of life history. Proc. Natl. Acad. Sci. USA 116, 26653–26661. https://doi.org/10.1073/pnas.1907702116 (2019).CAS 
    Article 
    PubMed Central 

    Google Scholar 
    4.Charnov, E. L. & Berrigan, D. Why do female primates have such long lifespans and so few babies? Or life in the slow lane. Evol. Anthropol. 1, 191–194. https://doi.org/10.1002/evan.1360010604 (1993).Article 

    Google Scholar 
    5.Jones, J. H. Primates and the evolution of long, slow life histories. Curr. Biol. 21, R708–R717. https://doi.org/10.1016/j.cub.2011.08.025 (2011).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    6.Speakman, J. R. Body size, energy metabolism and lifespan. J. Exp. Biol. 208, 1717–1730. https://doi.org/10.1242/jeb.01556 (2005).Article 
    PubMed 

    Google Scholar 
    7.Martin, R. D. Relative brain size and basal metabolic rate in terrestrial vertebrates. Nature 293, 57–60. https://doi.org/10.1038/293057a0 (1981).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    8.Read, A. F. & Harvey, P. H. Life history differences among the eutherian radiations. J. Zool. 219, 329–353. https://doi.org/10.1111/j.1469-7998.1989.tb02584.x (1989).Article 

    Google Scholar 
    9.Harvey, P. H., Pagel, M. D. & Rees, J. A. Mammalian metabolism and life histories. Am. Nat. 137, 556–566 (1991).Article 

    Google Scholar 
    10.Kappeler, P. Causes and consequences of life-history variation among strepsirhine primates. Am. Nat. 148, 868–891 (1996).Article 

    Google Scholar 
    11.Dausmann, K.H. Flexible patterns in energy savings: heterothermy in primates. J. Zool. 292, 101–111, https://doi.org/10.1111/jzo.12104 (2014)12.Richard, A. F., Dewar, R. E., Schwartz, M. & Ratsirarson, J. Mass change, environmental variability and female fertility in wild Propithecus verreauxi. J. Hum. Evol. 39, 381–391. https://doi.org/10.1006/jhev.2000.0427 (2000).CAS 
    Article 
    PubMed 

    Google Scholar 
    13.Richard, A. F., Dewar, R. E., Schwartz, M. & Ratsirarson, J. Life in the slow lane? Demography and life histories of male and female sifaka (Propithecus verreauxi verreauxi). J. Zool. (London) 256, 421–436. https://doi.org/10.1017/S0952836902000468 (2002).Article 

    Google Scholar 
    14.Kappeler, P. K. & Fichtel, C. Eco-evo-devo of the lemur syndrome: did adaptive behavioral plasticity get canalized in a large primate radiation? Front. Zool. 12, S15. https://doi.org/10.1186/1742-9994-12-S1-S15 (2015).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    15.Dewar, R. E. & Richard, A. F. Evolution in the hypervariable environment of Madagascar. Proc. Natl. Acad. Sci. USA 104, 13723–13727. https://doi.org/10.1073/pnas.0704346104 (2007).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    16.Wright, P. C. Lemur traits and Madagascar ecology: coping with an island environment. Yearb. Phys. Anthropol. 42, 31–72. (1999).Article 

    Google Scholar 
    17.Ganzhorn, J. U. et al. Possible fruit protein effects on primate communities in Madagascar and the Neotropics. PLoS ONE 4, e8253. https://doi.org/10.1371/journal.pone.0008253 (2009).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    18.Pontzer, H., Raichlen, D. A., Shumaker, R. W., Ocobock, C. & Wich, S. A. Metabolic adaptation for low energy throughput in orangutans. Proc. Natl. Acad. Sci. USA 107, 14048–14052. https://doi.org/10.1073/pnas.1001031107 (2010).ADS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    19.Simmen, B., Darlu, P., Hladik, C. M. & Pasquet, P. Scaling of free-ranging primate energetics with body mass predicts low energy expenditure in humans. Physiol. Behav. 138, 193–199. https://doi.org/10.1016/j.physbeh.2014.10.018 (2015).CAS 
    Article 
    PubMed 

    Google Scholar 
    20.Pontzer, H. et al. Metabolic acceleration and the evolution of human brain size and life history. Nature 533, 390–392. https://doi.org/10.1038/nature17654 (2016).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    21.Chevillard, M.-C. Capacités thermorégulatrices d’un lémurien malgache, Microcebus murinus. Ph.D. Thesis, University Paris VII, Paris (1976).22.Genoud, M., Martin, R. D. & Glaser, D. Rate of metabolism in the smallest simian primate, the pygmy marmoset (Cebuella pygmaea). Am. J. Primatol. 41, 229–245. (1997).CAS 
    Article 

    Google Scholar 
    23.Snodgrass, J. J., Leonard, W. R. & Robertson, M. L. Primate bioenergetics: An evolutionary perspective. In Primate Origins: Adaptations and Evolution (eds Ravosa, M. J. & Dagosto, M.) 703–737 (Springer, Boston, 2007). https://doi.org/10.1007/978-0-387-33507-0_20.24.Kurland, J. A. & Pearson, J. D. Ecological significance of hypometabolism in nonhuman primates: allometry, adaptation, and deviant diets. Am. J. Phys. Anthropol. 71, 445–457. https://doi.org/10.1002/ajpa.1330710408 (1986).CAS 
    Article 
    PubMed 

    Google Scholar 
    25.Harvey, P. H., Martin, R. D. & Clutton- Brock, T. H. Life histories in a comparative perspective. In Primate Societies (eds Smuts, B. B., Cheney, D. L., Seyfarth, R. M., Wrangham, R. W. & Struhsaker, T. T.) 181– 196 (University of Chicago Press, Chicago, 1987).26.Isler, K. et al. Endocranial volumes of primate species: scaling analyses using a comprehensive and reliable data set. J. Hum. Evol. 55, 967–978. https://doi.org/10.1016/j.jhevol.2008.08.004 (2008).Article 
    PubMed 

    Google Scholar 
    27.Simmen, B., Tarnaud, L., Marez, A. & Hladik, A. Leaf chemistry as a predictor of primate biomass and the mediating role of food selection: A case study in a folivorous lemur (Propithecus verreauxi). Am. J. Primatol. 76, 563–575. https://doi.org/10.1002/ajp.22249 (2014).CAS 
    Article 
    PubMed 

    Google Scholar 
    28.Lewis, R. J. & Kappeler, P. M. Seasonality, body condition, and timing of reproduction in Propithecus verreauxi verreauxi. Am. J. Primatol. 66, 1–18. https://doi.org/10.1002/ajp.20187 (2005).Article 

    Google Scholar 
    29.Donati, D., Ricci, E., Baldi, N., Morelli, V. & Borgognini-Tarli, S. M. Behavioral thermoregulation in a gregarious lemur, Eulemur collaris: Effects of climatic and dietary-related factors. Am. J. Phys. Anthrop. 144, 355–364. https://doi.org/10.1002/ajpa.21415 (2011).Article 
    PubMed 

    Google Scholar 
    30.Simmen, B. & Rasamimanana, H. Energy (im-)balance in frugivorous lemurs in southern Madagascar: a preliminary study in Lemur catta and Eulemur rufifrons x collaris. Folia Primatol. 89, 382–396. https://hal.archives-ouvertes.fr/hal-02349627/(2018).31.Simmen, B. et al. Total energy expenditure and body composition in two free-living sympatric lemurs. PLoS ONE 5, e9860. https://doi.org/10.1371/journal.pone.0009860 (2010).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    32.Rasamimanana, H. R., Andrianome, V. N., Rambeloarivony, H. & Pasquet, P. Male and female ringtailed lemurs’ energetic strategy does not explain female dominance. In Ringtailed Lemur Biology: Lemur catta in Madagascar (eds Jolly, A., Sussman, R. W., Koyama, N. & Rasamimanana, H.) 271–95 (Springer, Chicago, 2006). https://doi.org/10.1007/978-0-387-34126-2_1633.Irwin, M. T. Ecologically enigmatic lemurs: The sifakas of the eastern forests (Propithecus candidus, P. diadema, P. edwardsi, P. perrieri, and P. tattersalli). In Lemurs: Ecology and Adaptation (eds Gould, L. & Sauther, M.L.) 305–326 (Springer, New York, 2006). https://doi.org/10.1007/978-0-387-34586-4_1434.Vuarin, P. et al. When to initiate torpor use? Food availability times the transition to winter phenotype in a tropical heterotherm. Oecologia 179, 43–53. https://doi.org/10.1007/s00442-015-3328-0 (2015).ADS 
    Article 
    PubMed 

    Google Scholar 
    35.Nagy, K. A., Girard, I. A. & Brown, T. K. Energetics of free-ranging mammals, reptiles, and birds. Annu. Rev. Nutr. 19, 247–277. https://doi.org/10.1146/annurev.nutr.19.1.247 (1999).CAS 
    Article 
    PubMed 

    Google Scholar 
    36.Pontzer, H. Energy expenditure in humans and other primates: A new synthesis. Annu. Rev. Anthropol. 44, 169–187. https://doi.org/10.1146/annurev-anthro-102214-013925 (2015).Article 

    Google Scholar 
    37.Schmid, J. & Speakman, J. R. Daily energy expenditure of the grey mouse lemur (Microcebus murinus): A small primate that uses torpor. J. Comp. Physiol. B 170, 633–641. https://doi.org/10.1007/s003600000146 (2000).CAS 
    Article 
    PubMed 

    Google Scholar 
    38.Stalenberg E. Biophysical ecology of the white-footed sportive lemur (Lepilemur leucopus) of southern Madagascar, Ph.D. Thesis, The Australian National University, Canberra (2019).39.Schmid, J. & Speakman, J. Torpor and energetic consequences in free-ranging grey mouse lemurs (Microcebus murinus): A comparison of dry and wet forests. Naturwissenschaften 96, 609–620. https://doi.org/10.1007/s00114-009-0515-z (2009).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    40.Westerterp, K. & Speakman, J. R. Physical activity energy expenditure has not declined since the 1980s and matches energy expenditures of wild mammals. Int. J. Obes. (London) 32, 1256–1263. https://doi.org/10.1038/ijo.2008.74 (2008).CAS 
    Article 

    Google Scholar 
    41.Muchlinski, M. N., Snodgrass, J. J. & Terranova, C. J. Muscle mass scaling in primates: An energetic and ecological perspective. Am. J. Primatol. 74, 395–407. https://doi.org/10.1002/ajp.21990 (2012).Article 
    PubMed 

    Google Scholar 
    42.Thompson, S. D., MacMillen, R. E., Burke, E. M. & Taylor, C. R. The energetic cost of bipedal hopping in small mammals. Nature 287, 223–224. https://doi.org/10.1038/287223a0 (1980).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    43.Demes, B., Jungers, W. L., Gross, T. S. & Fleagle, J. G. Kinetics of leaping primates: Influence of substrate orientation and compliance. Am. J. Phys. Anthropol. 96, 419–429. https://doi.org/10.1002/ajpa.1330960407 (1995).CAS 
    Article 
    PubMed 

    Google Scholar 
    44.Webster, K. N. & Dawson, T. J. Locomotion energetics and gait characteristics of a rat-kangaroo, Bettongia penicillata, have some kangaroo-like features. J. Comp. Physiol. B 173, 549–557. https://doi.org/10.1007/s00360-003-0364-6 (2003).CAS 
    Article 
    PubMed 

    Google Scholar 
    45.Pontzer, H., Raichlen, D. A. & Sockol, M. D. From treadmill to tropics: Calculating ranging cost in chimpanzees. In Primate Locomotion: Linking Field and Laboratory Research, Developments in Primatology: Progress and Prospects (eds D’Août, K., Vereecke & E. E.) 289–309 (Springer, New York, 2011). https://doi.org/10.1007/978-1-4419-1420-0_1546.Hladik, C. M. Diet and the evolution of feeding strategies among forest primates. In Omnivorous Primates. Gathering and Hunting in Human Evolution (eds Harding, R. S. O. & Teleki, G.) 215–254 (Columbia University Press, New York, 1981). https://hal.archives-ouvertes.fr/hal-0057868747.Oates, J. F. (1987) Food distribution and foraging behavior. In Primate Societies (eds Smuts, B. B. et al.) 197–209 (University of Chicago Press, 1987).
    Google Scholar 
    48.Clutton-Brock, T. H. & Harvey, P. H. Primate ecology and social organization. J. Zool., (London) 183, 1–39, https://doi.org/10.1111/j.1469-7998.1977.tb04171.x (1977).49.Harvey, P. & Bennett, P. Evolutionary biology: Brain size, energetics, ecology and life history patterns. Nature 306, 314–315. https://doi.org/10.1038/306314a0 (1983).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    50.Milton, K. & May, M. L. Body weight, diet and home range area in primates. Nature 259, 459–462. https://doi.org/10.1038/259459a0 (1976).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    51.Snaith, T. V. & Chapman, C. A. Primate group size and interpreting socioecological models: Do folivores really play by different rules?. Evol. Anthropol. 16, 94–106. https://doi.org/10.1002/evan.20132 (2007).Article 

    Google Scholar 
    52.Tecot, S. R. It’s all in the timing: Birth seasonality and infant survival in Eulemur rubriventer. Int. J. Primatol. 31, 715–735. https://doi.org/10.1007/s10764-010-9423-5 (2010).Article 

    Google Scholar 
    53.van Woerden, J. T., van Schaik, C. P. & Isler, K. Effects of seasonality on brain size evolution: Evidence from strepsirhine primates. Am. Nat. 176, 758–776. https://doi.org/10.1086/657045 (2010).Article 
    PubMed 

    Google Scholar 
    54.Edwards, W., Lonsdorf, E. V. & Pontzer, H. Total energy expenditure in captive capuchins (Sapajus apella). Am. J. Primatol. 79, e22638. https://doi.org/10.1002/ajp.22638 (2017).CAS 
    Article 

    Google Scholar 
    55.Dugas, L. R. et al. Energy expenditure in adults living in developing compared with industrialized countries: A meta-analysis of doubly labeled water studies. Am. J. Clin. Nutr. 93, 427–441. https://doi.org/10.3945/ajcn.110.007278 (2011).CAS 
    Article 
    PubMed 

    Google Scholar 
    56.Barrickman, N. L. & Lin, M. J. Encephalization, expensive tissues, and energetics: An examination of the relative costs of brain size in strepsirhines added with new data. Am. J. Phys. Anthropol. 143, 579–590. https://doi.org/10.1002/ajpa.21354 (2010).Article 
    PubMed 

    Google Scholar 
    57.Benedict, F. G. Vital Energetics: A Study in Comparative Basal Metabolism, Carnegie Institution, Washington, 1938), Publication No 503.58.Schoeller, D. A. et al. Energy expenditure by the doubly labeled water: validation in humans and proposed calculations. Am. J. Physiol. 250, R823–R830. https://doi.org/10.1152/ajpregu.1986.250.5.R823 (1986).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    59.Speakman, J. R. Doubly Labelled Water: Theory and Practice (Chapman, Hall, London, 1997). https://doi.org/10.1046/j.1365-2656.2001.00515-4.x60.Chery, I., Zahariev, A., Simon, C. & Blanc, S. Analytical aspects of measuring (2)H/(1)H and (18)O/(16)O ratios in urine from doubly labelled water studies by high-temperature conversion elemental analyser-isotope-ratio mass spectrometry. Rapid Commun. Mass Spectrom. 29, 562–572. https://doi.org/10.1002/rcm.7135 (2015).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    61.Drack, S. et al. Field metabolic rate and the cost of ranging of the red-tailed sportive lemur (Lepilemur ruficaudatus). In New Directions in Lemur Studies (eds Rakotosamimanana B. et al) 83–91 (Kluwer Academic/Plenum Publishers, 1999). https://doi.org/10.1007/978-1-4615-4705-1_562.Pagel, M., Meade, A. & Barker, D. Bayesian estimation of ancestral character states on phylogenies. Syst. Biol. 53, 673–684. https://doi.org/10.1080/10635150490522232 (2004).Article 
    PubMed 

    Google Scholar 
    63.Arnold, C., Matthews, L. J. & Nunn, C. L. The 10kTrees website: A new online resource for primate phylogeny. Evol. Anthropol. 19, 114–118 (2010).Article 

    Google Scholar 
    64.R Core Team. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, https://www.r-project.org/ (2020).65.RStudio Team (2020). RStudio: Integrated Development for R. RStudio, PBC, Boston, MA URL https://www.rstudio.com/. More

  • in

    Metabolic flexibility of aerobic methanotrophs under anoxic conditions in Arctic lake sediments

    1.Saunois M, Stavert AR, Poulter B, Bousquet P, Canadell JG, Jackson RB, et al. The global methane budget 2000-2017. Earth Syst Sci Data. 2020;12:1561–623.Article 

    Google Scholar 
    2.Reeburgh WS. Oceanic methane biogeochemistry. Chem Rev. 2007;107:486–513.CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    3.Weber T, Wiseman NA, Kock A. Global ocean methane emissions dominated by shallow coastal waters. Nat Commun. 2019;10:4584.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    4.He R, Wooller MJ, Pohlman JW, Quensen J, Tiedje JM, Leigh MB. Shifts in identity and activity of methanotrophs in arctic lake sediments in response to temperature changes. Appl Environ Microb. 2012;78:4715–23.CAS 
    Article 

    Google Scholar 
    5.Phelps AR, Peterson KM, Jeffries MO. Methane efflux from high-latitude lakes during spring ice melt. J Geophys Res Atmos. 1998;103:29029–36.CAS 
    Article 

    Google Scholar 
    6.Walter KM, Smith LC, Chapin FS. Methane bubbling from northern lakes: present and future contributions to the global methane budget. Philos Trans A Math Phys Eng Sci. 2007;365:1657–76.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    7.Wik M, Varner RK, Anthony KW, MacIntyre S, Bastviken D. Climate-sensitive northern lakes and ponds are critical components of methane release. Nat Geosci. 2016;9:99–105.CAS 
    Article 

    Google Scholar 
    8.Knittel K, Boetius A. Anaerobic oxidation of methane: progress with an unknown process. Annu Rev Microbiol. 2009;63:311–34.CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    9.Timmers PHA, Welte CU, Koehorst JJ, Plugge CM, Jetten MSM, Stams AJM. Reverse methanogenesis and respiration in methanotrophic archaea. Archaea. 2017;2017:1654237.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    10.Shen LD, Ouyang L, Zhu Y, Trimmer M. Active pathways of anaerobic methane oxidation across contrasting riverbeds. ISME J. 2019;13:752–66.CAS 
    PubMed 
    Article 

    Google Scholar 
    11.Valenzuela EI, Cervantes FJ. The role of humic substances in mitigating greenhouse gases emissions: Current knowledge and research gaps. Sci Total Environ. 2021;750:141677.CAS 
    PubMed 
    Article 

    Google Scholar 
    12.Orphan VJ, House CH, Hinrichs KU, McKeegan KD, DeLong EF. Multiple archaeal groups mediate methane oxidation in anoxic cold seep sediments. Proc Natl Acad Sci USA. 2002;99:7663–8.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    13.Orphan VJ, House CH, Hinrichs KU, McKeegan KD, DeLong EF. Methane-consuming archaea revealed by directly coupled isotopic and phylogenetic analysis. Science. 2001;293:484–7.CAS 
    PubMed 
    Article 

    Google Scholar 
    14.Haroon MF, Hu S, Shi Y, Imelfort M, Keller J, Hugenholtz P, et al. Anaerobic oxidation of methane coupled to nitrate reduction in a novel archaeal lineage. Nature. 2013;500:567–70.CAS 
    PubMed 
    Article 

    Google Scholar 
    15.Cai C, Leu AO, Xie GJ, Guo JH, Feng YX, Zhao JX, et al. A methanotrophic archaeon couples anaerobic oxidation of methane to Fe(III) reduction. ISME J. 2018;12:1929–39.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    16.Ettwig KF, Zhu B, Speth D, Keltjens JT, Jetten MSM, Kartal B. Archaea catalyze iron-dependent anaerobic oxidation of methane. Proc Natl Acad Sci USA. 2016;113:12792–6.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    17.Leu AO, Cai C, Mcllroy SJ, Southam G, Orphan VJ, Yuan ZG, et al. Anaerobic methane oxidation coupled to manganese reduction by members of the Methanoperedenaceae. ISME J. 2020;14:1030–41.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    18.Ettwig KF, Butler MK, Le Paslier D, Pelletier E, Mangenot S, Kuypers MMM, et al. Nitrite-driven anaerobic methane oxidation by oxygenic bacteria. Nature. 2010;464:543–8.CAS 
    PubMed 
    Article 

    Google Scholar 
    19.Martinez-Cruz K, Leewis MC, Herriott IC, Sepulveda-Jauregui A, Anthony KW, Thalasso F, et al. Anaerobic oxidation of methane by aerobic methanotrophs in sub-Arctic lake sediments. Sci Total Environ. 2017;607:23–31.PubMed 
    Article 
    CAS 

    Google Scholar 
    20.He R, Wooller MJ, Pohlman JW, Quensen J, Tiedje JM, Leigh MB. Diversity of active aerobic methanotrophs along depth profiles of arctic and subarctic lake water column and sediments. ISME J. 2012;6:1937–48.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    21.Bowman JP, Sly LI, Nichols PD, Hayward AC. Revised taxonomy of the methanotrophs: description of Methylobacter gen. nov., validation of Methylosinus and Methylocystis species, and a proposal that the family Methylococcaceae includes only the group I methanotrophs. Int J Syst Bacteriol. 1993;43:735–53.Article 

    Google Scholar 
    22.Oswald K, Milucka J, Brand A, Hach P, Littmann S, Wehrli B, et al. Aerobic gammaproteobacterial methanotrophs mitigate methane emissions from oxic and anoxic lake waters. Limnol Oceanogr. 2016;61:S101–18.Article 

    Google Scholar 
    23.Cabrol L, Thalasso F, Gandois L, Sepulveda-Jauregui A, Martinez-Cruz K, Teisserenc R, et al. Anaerobic oxidation of methane and associated microbiome in anoxic water of Northwestern Siberian lakes. Sci Total Environ. 2020;736:139588.CAS 
    PubMed 
    Article 

    Google Scholar 
    24.Milucka J, Kirf M, Lu L, Krupke A, Lam P, Littmann S, et al. Methane oxidation coupled to oxygenic photosynthesis in anoxic waters. ISME J. 2015;9:1991–2002.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    25.Kalyuzhnaya MG, Yang S, Rozova ON, Smalley NE, Clubb J, Lamb A, et al. Highly efficient methane biocatalysis revealed in a methanotrophic bacterium. Nat Commun. 2013;4:2785.CAS 
    PubMed 
    Article 

    Google Scholar 
    26.Kits KD, Klotz MG, Stein LY. Methane oxidation coupled to nitrate reduction under hypoxia by the Gammaproteobacterium Methylomonas denitrificans, sp. nov. type strain FJG1. Environ Microbiol. 2015;17:3219–32.CAS 
    PubMed 
    Article 

    Google Scholar 
    27.Eberl DD. Quantitative mineralogy of the Yukon River system: variations with reach and season, and determining sediment provenance. Am Mineral. 2004;89:1784–94.CAS 
    Article 

    Google Scholar 
    28.Lipson DA, Raab TK, Goria D, Zlamal J. The contribution of Fe(III) and humic acid reduction to ecosystem respiration in drained thaw lake basins of the Arctic Coastal Plain. Glob Biogeochem Cycles 2013;27:399–409.CAS 
    Article 

    Google Scholar 
    29.Li WB, Yao J, Tao PP, Guo MT, Feng XY, He YN, et al. A comparative study on two extraction procedures in speciation of iron in municipal solid waste. J Hazard Mater. 2010;182:640–8.CAS 
    PubMed 
    Article 

    Google Scholar 
    30.Oremland RS, Taylor BF. Sulfate reduction and methanogenesis in marine sediments. Geochim Cosmochim Acta. 1978;42:209–14.CAS 
    Article 

    Google Scholar 
    31.Glassburn CL, Potter BA, Clark JL, Reuther JD, Bruning DL, Wooller MJ. Strontium and oxygen isotope profiles of sequentially sampled modern bison (bison bison bison) teeth from interior Alaska as proxies of seasonal mobility. Arctic. 2018;71:183–200.Article 

    Google Scholar 
    32.He R, Wooller MJ, Pohlman JW, Catranis C, Quensen J, Tiedje JM, et al. Identification of functionally active aerobic methanotrophs in sediments from an arctic lake using stable isotope probing. Environ Microbiol. 2012;14:1403–19.CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    33.Leigh MB, Pellizari VH, Uhlik O, Sutka R, Rodrigues J, Ostrom NE, et al. Biphenyl-utilizing bacteria and their functional genes in a pine root zone contaminated with polychlorinated biphenyls (PCBs). ISME J. 2007;1:134–48.CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    34.Swan BK, Ehrhardt CJ, Reifel KM, Moreno LI, Valentine DL. Archaeal and bacterial communities respond differently to environmental gradients in anoxic sediments of a California hypersaline lake, the salton sea. Appl Environ Microb. 2010;76:757–68.CAS 
    Article 

    Google Scholar 
    35.Dedysh SN, Liesack W, Khmelenina VN, Suzina NE, Trotsenko YA, Semrau JD, et al. Methylocella palustris gen. nov., sp. nov., a new methane-oxidizing acidophilic bacterium from peat bogs, representing a novel subtype of serine-pathway methanotrophs. Int J Syst Evol Microbiol. 2000;50:955–69.CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    36.Vorobev AV, Baani M, Doronina NV, Brady AL, Liesack W, Dunfield PF, et al. Methyloferula stellata gen. nov. sp. nov. an acidophilic, obligately methanotrophic bacterium that possesses only a soluble methane monooxygenase. Int J Syst Evol Microbiol. 2011;61:2456–63.CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    37.Kolb S, Knief C, Stubner S, Conrad R. Quantitative detection of methanotrophs in soil by novel pmoA-targeted real-time PCR assays. Appl Environ Microbiol. 2003;69:2423–9.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    38.Fierer N, Schimel JP, Holden PA. Influence of drying–rewetting frequency on soil bacterial community structure. Micro Ecol. 2003;45:63–71.CAS 
    Article 

    Google Scholar 
    39.Fierer N, Jackson RB. The diversity and biogeography of soil bacterial communities. Proc Natl Acad Sci USA. 2006;103:626–31.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    40.Huang XQ, Madan A. CAP3: a DNA sequence assembly program. Genome Res. 1999;9:868–77.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    41.Ma RC, Chu YX, Wang J, Wang C, Leigh MB, Chen Y, et al. Stable-isotopic and metagenomic analyses reveal metabolic and microbial link of aerobic methane oxidation coupled to denitrification at different O2 levels. Sci Total Environ. 2020;764:142901.PubMed 
    Article 
    CAS 

    Google Scholar 
    42.Luo RB, Liu BH, Xie YL, Li ZY, Huang WH, Yuan JY, et al. SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. GigaScience. 2012;1:18.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    43.You MS, Yue Z, He WY, Yang XH, Yang G, Xie M, et al. A heterozygous moth genome provides insights into herbivory and detoxification. Nat Genet. 2013;45:220–5.CAS 
    PubMed 
    Article 

    Google Scholar 
    44.Zhu WH, Lomsadze A, Borodovsky M. Ab initio gene identification in metagenomic sequences. Nucleic Acids Res. 2010;38:e132.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    45.Guo JH, Peng YZ, Fan L, Zhang L, Ni BJ, Kartal B, et al. Metagenomic analysis of anammox communities in three different microbial aggregates. Environ Microbiol. 2016;18:2979–93.CAS 
    PubMed 
    Article 

    Google Scholar 
    46.Li WZ, Godzik A. Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics. 2006;22:1658–9.CAS 
    PubMed 
    Article 

    Google Scholar 
    47.Liu SP, Chen QL, Zou HJ, Yu YJ, Zhou ZL, Mao J, et al. A metagenomic analysis of the relationship between microorganisms and flavor development in Shaoxing mechanized huangjiu fermentation mashes. Int J Food Microbiol. 2019;303:9–18.CAS 
    PubMed 
    Article 

    Google Scholar 
    48.Francis OE, Bendall M, Manimaran S, Hong CJ, Clement NL, Castro-Nallar E, et al. Pathoscope: Species identification and strain attribution with unassembled sequencing data. Genome Res. 2013;23:1721–9.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    49.He Y, Feng XY, Fang J, Zhang Y, Xiao X. Metagenome and metatranscriptome revealed a highly active and intensive sulfur cycle in an oil-immersed hydrothermal chimney in Guaymas basin. Front Microbiol. 2015;6:1236.PubMed 
    PubMed Central 

    Google Scholar 
    50.Schubert CJ, Vazquez F, Losekann-Behrens T, Knittel K, Tonolla M, Boetius A. Evidence for anaerobic oxidation of methane in sediments of a freshwater system (Lago di Cadagno). FEMS Microbiol Ecol. 2011;76:26–38.CAS 
    PubMed 
    Article 

    Google Scholar 
    51.He R, Wooller MJ, Pohlman JW, Tiedje JM, Leigh MB. Methane-derived carbon flow through microbial communities in arctic lake sediments. Environ Microbiol. 2015;17:3233–50.CAS 
    PubMed 
    Article 

    Google Scholar 
    52.Vorholt JA. Cofactor-dependent formaldehyde oxidation in methylotrophic bacteria. Arch Microbiol. 2002;178:239–49.CAS 
    PubMed 
    Article 

    Google Scholar 
    53.Garber AI, Nealson KH, Okamoto A, McAllister SM, Chan CS, Barco RA, et al. FeGenie: a comprehensive tool for the identification of iron genes and iron gene neighborhoods in genome and metagenome assemblies. Front Microbiol. 2020;11:37.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    54.Barco A, Emerson D, Sylvan JB, Orcutt BN, Meyers MEJ, Ramírez GA, et al. New insight into microbial iron oxidation as revealed by the proteomic profile of an obligate iron-oxidizing chemolithoautotroph roman. Appl Environ Microbiol. 2015;81:5927–37.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    55.De Beer D, Sauter E, Niemann H, Kaul N, Foucher JP, Witte U, et al. In situ fluxes and zonation of microbial activity in surface sediments of the Hakon Mosby Mud Volcano. Limnol Oceanogr. 2006;51:1315–31.Article 

    Google Scholar 
    56.Lösekann T, Knittel K, Nadalig T, Fuchs B, Niemann H, Boetius A, et al. Diversity and abundance of aerobic and anaerobic methane oxidizers at the Haakon Mosby mud volcano, Barents Sea. Appl Environ Microb. 2007;73:3348–62.Article 
    CAS 

    Google Scholar 
    57.Blees J, Niemann H, Wenk CB, Zopfi J, Schubert CJ, Kirf MK, et al. Micro-aerobic bacterial methane oxidation in the chemocline and anoxic water column of deep south-Alpine Lake Lugano (Switzerland). Limnol Oceanogr. 2014;59:311–24.CAS 
    Article 

    Google Scholar 
    58.Reid T, Chaganti SR, Droppo IG, Weisener CG. Novel insights into freshwater hydrocarbon-rich sediments using metatranscriptomics: opening the black box. Water Res. 2018;136:1–11.CAS 
    PubMed 
    Article 

    Google Scholar 
    59.Weber KA, Achenbach LA, Coates JD. Microorganisms pumping iron: anaerobic microbial iron oxidation and reduction. Nat Rev Microbiol. 2006;4:752–64.CAS 
    PubMed 
    Article 

    Google Scholar 
    60.Ward N, Larsen Ø, Sakwa J, Bruseth L, Khouri H, Durkin AS, et al. Genomic insights into methanotrophy: the complete genome sequence of Methylococcus capsulatus (Bath). PLoS Biol. 2004;2:1616–28.CAS 

    Google Scholar 
    61.Versantvoort W, Pol A, Jetten MSM, van Niftrik L, Reimann J, Kartal B, et al. Multiheme hydroxylamine oxidoreductases produce NO during ammonia oxidation in methanotrophs. Prot Natl Acad Sci USA. 2020;117:24459–63.CAS 
    Article 

    Google Scholar 
    62.Richardson DJ, Berks BC, Russell DA, Spiro S, Taylor CJ. Functional, biochemical and genetic diversity of prokaryotic nitrate reductases. Cell Mol Life Sci. 2001;58:165–78.CAS 
    PubMed 
    Article 

    Google Scholar 
    63.Carere CR, McDonald B, Peach HA, Greening C, Gapes DJ, Collet C, et al. Hydrogen oxidation influences glycogen accumulation in a verrucomicrobial methanotroph. Front Microbiol. 2019;10:1873.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    64.Hanczár T, Csáki R, Bodrossy L, Murrell JC, Kovács KL. Detection and localization of two hydrogenases in Methylococcus capsulatus (Bath) and their potential role in methane metabolism. Arch Microbiol. 2002;177:167–72.PubMed 
    Article 
    CAS 

    Google Scholar 
    65.Shah NN, Hanna ML, Jackson KJ, Taylor RT. Batch cultivation of Methylosinus trichosporium OB3b. 4: production of hydrogen-driven soluble or particulate methane monooxygenase activity. Biotechnol Bioeng. 1995;45:229–38.CAS 
    PubMed 
    Article 

    Google Scholar 
    66.Mohammadi S, Pol A, van Alen TA, Jetten MSM, Op den Camp HJM. Methylacidiphilum fumariolicum SolV, a thermoacidophilic ‘Knallgas’ methanotroph with both an oxygen-sensitive and -insensitive hydrogenase. ISME J. 2017;11:945–58.CAS 
    PubMed 
    Article 

    Google Scholar 
    67.Carere CR, Hards K, Houghton KM, Power JF, McDonald B, Collet C, et al. Mixotrophy drives niche expansion of Verrucomicrobial methanotrophs. ISME J. 2017;11:2599–610.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    68.Orata FD, Meier-Kolthoff JP, Sauvageau D, Stein LY. Phylogenomic analysis of the Gammaproteobacterial methanotrophs (Order Methylococcales) calls for the reclassification of members at the genus and species levels. Front Microbiol. 2018;9:3162.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    69.Kucera J, Sedo O, Potesil D, Janiczek O, Zdrahal Z, Mandl M. Comparative proteomic analysis of sulfur-oxidizing Acidithiobacillus ferrooxidans CCM 4253 cultures having lost the ability to couple anaerobic elemental sulfur oxidation with ferric iron reduction. Res Microbiol. 2016;167:587–94.CAS 
    PubMed 
    Article 

    Google Scholar 
    70.Kucera J, Zeman J, Mandl M, Cerna H. Stoichiometry of bacterial anaerobic oxidation of elemental sulfur by ferric iron. Antonie van Leeuwenhoek. 2012;101:919–22.PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    71.He QX, Yu LP, Li JB, He D, Cai XX, Zhou SG. Electron shuttles enhance anaerobic oxidation of methane coupled to iron (III) reduction. Sci Total Environ. 2019;688:664–72.CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    72.Jing XX, Wu YC, Shi L, Peacock CL, Ashry NM, Gao CH, et al. Outer membrane c-type cytochromes OmcA and MtrC play distinct roles in enhancing the attachment of Shewanella oneidensis MR-1 cells to goethite. Appl Environ Microbiol. 2020;86:e01941–20.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    73.Tanaka K, Vokoe S, Igarashi K, Takashino M, Ishikawa M, Hori K, et al. Extracellular electron transfer via outer membrane cytochromes in a methanotrophic bacterium Methylococcus capsulatus (Bath). Front Microbiol. 2018;9:2905.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    74.Kamalanathan M, Dao LHT, Chaisutyakorna P, Gleadow R, Beardall J. Photosynthetic physiology of Scenedesmus sp (Chlorophyceae) under photoautotrophic and molasses-based heterotrophic and mixotrophic conditions. Phycologia. 2017;56:666–74.CAS 
    Article 

    Google Scholar 
    75.Qu LR, Wang C, Bai E. Evaluation of the 18O-H2O incubation method for measurement of soil microbial carbon use efficiency. Soil Biol Biochem. 2020;145:107802.CAS 
    Article 

    Google Scholar 
    76.Kapiluto Y, Yakir D, Tans P, Berkowitz B. Experimental and numerical studies of the 18O exchange between CO2 and water in the atmosphere–soil invasion flux. Geochim Cosmochim Acta. 2007;71:2657–71.CAS 
    Article 

    Google Scholar 
    77.Zeebe RE. Kinetic fractionation of carbon and oxygen isotopes during hydration of carbon dioxide. Geochim Cosmochim Acta. 2014;139:540–52.CAS 
    Article 

    Google Scholar  More

  • in

    Stratigraphy of stable isotope ratios and leaf structure within an African rainforest canopy with implications for primate isotope ecology

    1.Vogel, J. Recyling of carbon in a forest environment. Oecol. Plant. 13, 89–94 (1978).
    Google Scholar 
    2.Medina, E. & Minchin, P. Stratification of δ 13C values of leaves in Amazonian rain forests. Oecologia 45, 377–378 (1980).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    3.Ehleringer, J. R., Field, C. B., Lin, Z. & Kuo, C. Leaf carbon isotope and mineral composition in subtropical plants along an irradiance cline. Oecologia 70, 520–526 (1986).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    4.Medina, E., Sternberg, L. & Cuevas, E. Vertical stratification of δ13C values in closed natural and plantation forests in the Luquillo mountains, Puerto Rico. Oecologia 87, 369–372 (1991).ADS 
    PubMed 
    Article 

    Google Scholar 
    5.Graham, H. V. et al. Isotopic characteristics of canopies in simulated leaf assemblages. Geochim. Cosmochim. Acta 144, 82–95 (2014).ADS 
    CAS 
    Article 

    Google Scholar 
    6.Buchmann, N., Kao, W.-Y. & Ehleringer, J. Influence of stand structure on carbon-13 of vegetation, soils, and canopy air within deciduous and evergreen forests in Utah, United States. Oecologia 110, 109–119 (1997).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    7.Sternberg, L. D. S. L., Mulkey, S. S. & Wright, S. J. Oxygen isotope ratio stratification in a tropical moist forest. Oecologia 81, 51–56 (1989).ADS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    8.Ometto, J. P. H. B. et al. The stable carbon and nitrogen isotopic composition of vegetation in tropical forests of the Amazon Basin, Brazil. Biogeochemistry 79, 251–274 (2006).CAS 
    Article 

    Google Scholar 
    9.van der Merwe, N. J. & Medina, E. The canopy effect, carbon isotope ratios and foodwebs in Amazonia. J. Archaeol. Sci. 18, 249–259 (1991).Article 

    Google Scholar 
    10.Houle, A. & Wrangham, R. W. Contest competition for fruit and space among wild chimpanzees in relation to the vertical stratification of metabolizable energy. Anim. Behav. 175, 231–246 (2021).Article 

    Google Scholar 
    11.Roberts, P., Blumenthal, S. A., Dittus, W., Wedage, O. & Lee-Thorp, J. A. Stable carbon, oxygen, and nitrogen, isotope analysis of plants from a South Asian tropical forest: Implications for primatology. Am. J. Primatol. 79, e22656 (2017).Article 
    CAS 

    Google Scholar 
    12.Barbour, M. M. Stable oxygen isotope composition of plant tissue: A review. Funct. Plant Biol. 34, 83–94 (2007).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    13.Cernusak, L. A. et al. Stable isotopes in leaf water of terrestrial plants. Plant Cell Environ. 39, 1087–1102 (2016).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    14.Ometto, J. P. H., Flanagan, L. B., Martinelli, L. A. & Ehleringer, J. R. Oxygen isotope ratios of waters and respired CO2 in Amazonian forest and pasture ecosystems. Ecol. Appl. 15, 58–70 (2005).Article 

    Google Scholar 
    15.Yakir, D. Variations in the natural abundance of oxygen-18 and deuterium in plant carbohydrates. Plant Cell Environ. 15, 1005–1020 (1992).CAS 
    Article 

    Google Scholar 
    16.Wania, R., Hietz, P. & Wanek, W. Natural 15N abundance of epiphytes depends on the position within the forest canopy: Source signals and isotope fractionation. Plant Cell Environ. 25, 581–589 (2002).CAS 
    Article 

    Google Scholar 
    17.Blumenthal, S. A., Rothman, J. M., Chritz, K. L. & Cerling, T. E. Stable isotopic variation in tropical forest plants for applications in primatology. Am. J. Primatol. 78, 1041–1054 (2016).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    18.Schleser, G. H. & Jayasekera, R. 13C-variations of leaves in forests as an indication of reassimilated CO2 from the soil. Oecologia 65, 536–542 (1985).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    19.van der Merwe, N. J. & Medina, E. Photosynthesis and 13C12C ratios in Amazonian rain forests. Geochim. Cosmochim. Acta 53, 1091–1094 (1989).ADS 
    Article 

    Google Scholar 
    20.Chazdon, R. L. & Pearcy, R. W. The importance of sunflecks for forest understory plants. Bioscience 41, 760–766 (1991).Article 

    Google Scholar 
    21.Lambers, H., Chapin, F. S. & Pons, T. L. Plant Physiological Ecology (Springer New York, 2008) https://doi.org/10.1007/978-0-387-78341-3.Book 

    Google Scholar 
    22.Hellkvist, J., Richards, G. P. & Jarvis, P. G. Vertical gradients of water potential and tissue water relations in sitka spruce trees measured with the pressure chamber. J. Appl. Ecol. 11, 637–667 (1974).Article 

    Google Scholar 
    23.Ambrose, A. R., Sillett, S. C. & Dawson, T. E. Effects of tree height on branch hydraulics, leaf structure and gas exchange in California redwoods. Plant Cell Environ. 32, 743–757 (2009).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    24.Peltoniemi, M. S., Duursma, R. A. & Medlyn, B. E. Co-optimal distribution of leaf nitrogen and hydraulic conductance in plant canopies. Tree Physiol. 32, 510–519 (2012).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    25.Araguás-Araguás, L., Froehlich, K. & Rozanski, K. Deuterium and oxygen-18 isotope composition of precipitation and atmospheric moisture. Hydrol. Process. 14, 1341–1355 (2000).ADS 
    Article 

    Google Scholar 
    26.Gonfiantini, R., Roche, M.-A., Olivry, J.-C., Fontes, J.-C. & Zuppi, G. M. The altitude effect on the isotopic composition of tropical rains. Chem. Geol. 181, 147–167 (2001).ADS 
    CAS 
    Article 

    Google Scholar 
    27.Craine, J. M. et al. Global patterns of foliar nitrogen isotopes and their relationships with climate, mycorrhizal fungi, foliar nutrient concentrations, and nitrogen availability. New Phytol. 183, 980–992 (2009).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    28.Guenni, O., Romero, E., Guédez, Y., Bravo de Guenni, L. & Pittermann, J. Influence of low light intensity on growth and biomass allocation, leaf photosynthesis and canopy radiation interception and use in two forage species of Centrosema (DC.) Benth. Grass Forage Sci. 73, 967–978 (2018).CAS 
    Article 

    Google Scholar 
    29.Ryan, M. G. & Yoder, B. J. Hydraulic limits to tree height and tree growth. Bioscience 47, 235–242 (1997).Article 

    Google Scholar 
    30.Dunham, N. T. & Lambert, A. L. The role of leaf toughness on foraging efficiency in Angola black and white colobus monkeys (Colobus angolensis palliatus). Am. J. Phys. Anthropol. 161, 343–354 (2016).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    31.Poorter, L., van de Plassche, M., Willems, S. & Boot, R. G. A. Leaf traits and herbivory rates of tropical tree species differing in successional status. Plant Biol. 6, 746–754 (2004).CAS 
    PubMed 
    Article 

    Google Scholar 
    32.Sponheimer, M. et al. Using carbon isotopes to track dietary change in modern, historical, and ancient primates. Am. J. Phys. Anthropol. 140, 661–670 (2009).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    33.Nelson, S. V. Chimpanzee fauna isotopes provide new interpretations of fossil ape and hominin ecologies. Proc. R. Soc. B 280, 20132324 (2013).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    34.Krigbaum, J., Berger, M. H., Daegling, D. J. & McGraw, W. S. Stable isotope canopy effects for sympatric monkeys at Taï Forest, Côte d’Ivoire. Biol. Lett. 9, 20130466 (2013).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    35.Oelze, V. M., Head, J. S., Robbins, M. M., Richards, M. & Boesch, C. Niche differentiation and dietary seasonality among sympatric gorillas and chimpanzees in Loango National Park (Gabon) revealed by stable isotope analysis. J. Hum. Evol. 66, 95–106 (2014).PubMed 
    Article 

    Google Scholar 
    36.McGraw, W. S. Positional behavior of Cercopithecus petaurista. Int. J. Primatol. 21, 157–182 (2000).Article 

    Google Scholar 
    37.McGraw, W. S. Comparative locomotion and habitat use of six monkeys in the Tai Forest, Ivory Coast. Am. J. Primatol. 105, 493–510 (1998).CAS 

    Google Scholar 
    38.Carter, M. L. & Bradbury, M. W. Oxygen isotope ratios in primate bone carbonate reflect amount of leaves and vertical stratification in the diet. Am. J. Primatol. 78, 1086–1097 (2016).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    39.Bryant, J. D. & Froelich, P. N. A model of oxygen isotope fractionation in body water of large mammals. Geochim. Cosmochim. Acta 59, 4523–4537 (1995).ADS 
    CAS 
    Article 

    Google Scholar 
    40.Sharma, N. et al. Watering holes: The use of arboreal sources of drinking water by Old World monkeys and apes. Behav. Proc. 129, 18–26 (2016).Article 

    Google Scholar 
    41.Wittig, R. M. Taï chimpanzees. In Encyclopedia of Animal Cognition and Behavior (eds Vonk, J. & Shackelford, T.) 1–7 (Springer International Publishing, 2017) https://doi.org/10.1007/978-3-319-47829-6_1564-1.Chapter 

    Google Scholar 
    42.Nelson, S. V. & Rook, L. Isotopic reconstructions of habitat change surrounding the extinction of Oreopithecus, the last European ape. Am. J. Phys. Anthropol. 160, 254–271 (2016).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    43.Ryan, M. G., Phillips, N. & Bond, B. J. The hydraulic limitation hypothesis revisited. Plant Cell Environ. 29, 367–381 (2006).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    44.Bachofen, C., D’Odorico, P. & Buchmann, N. Light and VPD gradients drive foliar nitrogen partitioning and photosynthesis in the canopy of European beech and silver fir. Oecologia 192, 323–339 (2020).ADS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    45.Chazdon, R. L., Williams, K. & Field, C. B. Interactions between crown structure and light environment in five rain forest piper species. Am. J. Bot. 75, 1459–1471 (1988).Article 

    Google Scholar 
    46.Ambrose, A. R. et al. Hydraulic constraints modify optimal photosynthetic profiles in giant sequoia trees. Oecologia 182, 713–730 (2016).ADS 
    PubMed 
    Article 

    Google Scholar 
    47.Voigt, C. C. Insights into strata use of forest animals using the ‘canopy effect’. Biotropica 42, 634–637 (2010).Article 

    Google Scholar 
    48.Ometto, J. P. H. B. et al. Carbon isotope discrimination in forest and pasture ecosystems of the Amazon Basin. Brazil. Glob. Biogeochem. Cycles 16, 56-1-56–10 (2002).
    Google Scholar 
    49.Loudon, J. E. et al. Stable isotope data from bonobo (Pan paniscus) faecal samples from the Lomako Forest Reserve, Democratic Republic of the Congo. Afr. J. Ecol. 57, 437–442 (2019).Article 

    Google Scholar 
    50.Medina, E., Klinge, H., Jordan, C. & Herrera, R. Soil respiration in Amazonian rain forests in the Rio Negro Basin. Flora 170, 240–250 (1980).Article 

    Google Scholar 
    51.Craine, J. M. et al. Ecological interpretations of nitrogen isotope ratios of terrestrial plants and soils. Plant Soil 396, 1–26 (2015).CAS 
    Article 

    Google Scholar 
    52.Niinemets, Ü. & Tenhunen, J. D. A model separating leaf structural and physiological effects on carbon gain along light gradients for the shade-tolerant species Acer saccharum. Plant Cell Environ. 20, 845–866 (1997).Article 

    Google Scholar 
    53.Schoener, T. W. Theory of feeding strategies. Annu. Rev. Ecol. Syst. 2, 369–404 (1971).Article 

    Google Scholar 
    54.Onoda, Y., Schieving, F. & Anten, N. P. R. Effects of light and nutrient availability on leaf mechanical properties of plantago major: A conceptual approach. Ann. Bot. 101, 727–736 (2008).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    55.Dasilva, G. L. Diet of Colobus polykomos on Tiwai Island: Selection of food in relation to its seasonal abundance and nutritional quality. Int. J. Primatol. 15, 655–680 (1994).Article 

    Google Scholar 
    56.Rothman, J. M., Chapman, C. A. & Pell, A. N. Fiber-bound nitrogen in gorilla diets: Implications for estimating dietary protein intake of primates. Am. J. Primatol. 70, 690–694 (2008).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    57.Ganzhorn, J. U. et al. The importance of protein in leaf selection of folivorous primates. Am. J. Primatol. 79, e22550 (2017).Article 
    CAS 

    Google Scholar 
    58.Tejada, J. V. et al. Comparative isotope ecology of western Amazonian rainforest mammals. Proc. Natl. Acad. Sci. USA 117, 26263–26272 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    59.Cernusak, L. A. et al. Why are non-photosynthetic tissues generally 13C enriched compared with leaves in C3 plants? Review and synthesis of current hypotheses. Funct. Plant Biol. 36, 199–213 (2009).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    60.Fannin, L. D. & McGraw, W. S. Does oxygen stable isotope composition in primates vary as a function of vertical stratification or folivorous behaviour?. Folia Primatol. 91, 219–227 (2020).Article 

    Google Scholar 
    61.Crowley, B. E., Melin, A. D., Yeakel, J. D. & Dominy, N. J. Do oxygen isotope values in collagen reflect the ecology and physiology of neotropical mammals?. Front. Ecol. Evol. 3, 127 (2015).Article 

    Google Scholar 
    62.DeNiro, M. J. & Epstein, S. Influence of diet on the distribution of nitrogen isotopes in animals. Geochim. Cosmochim. Acta 45, 341–351 (1981).ADS 
    CAS 
    Article 

    Google Scholar 
    63.Lemoine, R. et al. Source-to-sink transport of sugar and regulation by environmental factors. Front. Plant Sci. 4, 272 (2013).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    64.Anderson, D. L., Koomjian, W., French, B., Altenhoff, S. R. & Luce, J. Review of rope-based access methods for the forest canopy: Safe and unsafe practices in published information sources and a summary of current methods. Methods Ecol. Evol. 6, 865–872 (2015).Article 

    Google Scholar  More

  • in

    Natal origin and age-specific egress of Pacific bluefin tuna from coastal nurseries revealed with geochemical markers

    1.Duffy, L. M. et al. Global trophic ecology of yellowfin, bigeye, and albacore tunas: Understanding predation on micronekton communities at ocean-basin scales. Deep Sea Res. Part II Top. Stud. Oceanogr. 140, 55–73 (2017).ADS 
    Article 

    Google Scholar 
    2.Mariani, P., Andersen, K. H., Lindegren, M. & MacKenzie, B. Trophic impact of Atlantic bluefin tuna migrations in the North Sea. ICES J. Mar. Sci. 74, 1552–1560 (2017).Article 

    Google Scholar 
    3.Block, B. A. et al. Tracking apex marine predator movements in a dynamic ocean. Nature 475, 86–90 (2011).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    4.Arrizabalaga, H. et al. Chapter 3. Life history and migrations of Mediterranean bluefin tuna. In The Future Of Bluefin Tuna: Ecology, Fisheries Management, and Conservation (ed. Block, B. A.) 67–93 (Johns Hopkins University Press, 2019).
    Google Scholar 
    5.Rooker, J. R. et al. Population connectivity of pelagic megafauna in the Cuba–Mexico–United States triangle. Sci. Rep. 9, 1663 (2019).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    6.Sun, J., Hinton, M. G. & Webster, D. G. Modeling the spatial dynamics of international tuna fleets. PLoS ONE 11, e0159626 (2016).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    7.Collette, B. B. et al. Conservation: High value and long life-double jeopardy for tunas and billfishes. Science 333, 291–292 (2011).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    8.Kerr, L. A., Cadrin, S. X., Secor, D. H. & Taylor, N. G. Modeling the implications of stock mixing and life history uncertainty of Atlantic bluefin tuna. Can. J. Fish. Aquat. Sci. 74, 1990–2004 (2017).Article 

    Google Scholar 
    9.Fromentin, J. M. & Lopuszanski, D. Migration, residency, and homing of bluefin tuna in the western Mediterranean Sea. ICES J. Mar. Sci. 71, 510–518 (2014).Article 

    Google Scholar 
    10.Lam, C. H., Galuardi, B. & Lutcavage, M. E. Movements and oceanographic associations of bigeye tuna (Thunnus obesus) in the Northwest Atlantic. Can. J. Fish. Aquat. Sci. 71, 1529–1543 (2014).Article 

    Google Scholar 
    11.Rooker, J. R. et al. Wide-ranging temporal variation in transoceanic movement and population mixing of bluefin tuna in the North Atlantic Ocean. Front. Mar. Sci. 6, 398 (2019).Article 

    Google Scholar 
    12.Bayliff, W. H. A review of the biology and fisheries for northern bluefin tuna, Thunnus thynnus, in the Pacific Ocean. FAO Fish. Tech. Pap. 336, 244–295 (1994).
    Google Scholar 
    13.Collette, B. & Graves, J. Tunas and Billfishes of the World (Johns Hopkins University Press, 2019).
    Google Scholar 
    14.Madigan, D. J., Baumann, Z. & Fisher, N. S. Pacific bluefin tuna transport Fukushima-derived radionuclides from Japan to California. Proc. Natl. Acad. Sci. U. S. A. 109, 9483–9486 (2012).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    15.Fujioka, K. et al. Spatial and temporal variability in the trans-Pacific migration of Pacific bluefin tuna (Thunnus orientalis) revealed by archival tags. Prog. Oceanogr. 162, 52–65 (2018).ADS 
    Article 

    Google Scholar 
    16.Fujioka, K., Masujima, M., Boustany, A. M. & Kitagawa, T. Horizontal movements of Pacific bluefin tuna. In Biology and Ecology of Bluefin Tuna (eds Kitagawa, T. & Kimura, S.) 101–122 (CRC Press, 2015).
    Google Scholar 
    17.Fujioka, K. et al. Habitat use and movement patterns of small (age-0) juvenile Pacific bluefin tuna (Thunnus orientalis) relative to the Kuroshio. Fish. Oceanogr. 27, 185–198 (2018).Article 

    Google Scholar 
    18.Kitagawa, T., Kimura, S., Nakata, H. & Yamada, H. Diving behavior of immature, feeding Pacific bluefin tuna (Thunnus thynnus orientalis) in relation to season and area: The East China Sea and the Kuroshio–Oyashio transition region. Fish. Oceanogr. 13, 161–180 (2004).Article 

    Google Scholar 
    19.Rooker, J. R. et al. Natal homing and connectivity in Atlantic bluefin tuna populations. Science 322, 742–744 (2008).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    20.Wells, R. J. D., Rooker, J. R. & Itano, D. G. Nursery origin of yellowfin tuna in the Hawaiian Islands. Mar. Ecol. Prog. Ser. 461, 187–196 (2012).ADS 
    CAS 
    Article 

    Google Scholar 
    21.Wells, R. J. D. et al. Natal origin of Pacific bluefin tuna from the California current large marine ecosystem. Biol. Lett. 16, 20190878 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    22.Baumann, H. et al. Combining otolith microstructure and trace elemental analyses to infer the arrival of juvenile Pacific bluefin tuna in the California current ecosystem. ICES J. Mar. Sci. 72, 2128–2138 (2015).Article 

    Google Scholar 
    23.Rooker, J. R. & Secor, D. H. Otolith microchemistry: Migration and ecology of Atlantic bluefin tuna. In The Future of Bluefin Tuna: Ecology, Fisheries Management, and Conservation (ed. Block, B. A.) 45–66 (Johns Hopkins University Press, 2019).
    Google Scholar 
    24.Kitchens, L. L. et al. Discriminating among yellowfin tuna Thunnus albacares nursery areas in the Atlantic Ocean using otolith chemistry. Mar. Ecol. Prog. Ser. 603, 201–213 (2018).ADS 
    CAS 
    Article 

    Google Scholar 
    25.Reeves, J., Chen, J., Wang, X. L., Lund, R. & Lu, Q. A review and comparison of changepoint detection techniques for climate data. J. Appl. Meteorol. Climatol. 46, 900–915 (2007).ADS 
    Article 

    Google Scholar 
    26.Killick, R. & Eckley, I. A. Changepoint: An R package for changepoint analysis. J. Stat. Softw. 58, 1–19 (2014).Article 

    Google Scholar 
    27.Liu, H., Gilmartin, J., Li, C. & Li, K. Detection of time-varying pulsed event effects on estuarine pelagic communities with ecological indicators after catastrophic hurricanes. Ecol. Indic. 123, 107327 (2021).Article 

    Google Scholar 
    28.Millar, R. B. Comparison of methods for estimating mixed stock fishery composition. Can. J. Fish. Aquat. Sci. 47, 2235–2241 (1990).Article 

    Google Scholar 
    29.Rooker, J. R., Secor, D. H., Zdanowicz, V. S. & Itoh, T. Discrimination of northern bluefin tuna from nursery areas in the Pacific Ocean using otolith chemistry. Mar. Ecol. Prog. Ser. 218, 275–282 (2001).ADS 
    CAS 
    Article 

    Google Scholar 
    30.Wells, R. J. D. et al. Natural tracers reveal population structure of albacore (Thunnus alalunga) in the eastern North Pacific Ocean. ICES J. Mar. Sci. 72, 2118–2127 (2015).Article 

    Google Scholar 
    31.Elsdon, T. S. et al. Otolith chemistry to describe movements and life history parameters of fishes: Hypotheses, assumptions, limitations and inferences. Oceanogr. Mar. Biol. Annu. Rev. 46, 297–330 (2008).
    Google Scholar 
    32.Secor, D. H. Migration Ecology of Marine Fishes (Johns Hopkins University Press, 2015).
    Google Scholar 
    33.Chen, C. T. A., Ruo, R., Pai, S. C., Liu, C. T. & Wong, G. T. F. Exchange of water masses between East China Sea and the Kuroshio off northeastern Taiwan. Cont. Shelf Res. 15, 19–39 (1995).ADS 
    Article 

    Google Scholar 
    34.Sasaki, Y. N., Minobe, S., Asai, T. & Inatsu, M. Influence of the Kuroshio in the East China Sea on the early summer (Baiu) rain. J. Climate 25, 6627–6645 (2012).ADS 
    Article 

    Google Scholar 
    35.Sturrock, A. M., Trueman, C. N., Darnaude, A. M. & Hunter, E. Can otololith elemental chemistry retrospectively track migrations in marine fishes. J. Fish. Biol. 81, 766–795 (2012).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    36.Lebrato, M. et al. Global variability in seawater Mg:Ca and Sr:Ca ratios in the modern ocean. Proc. Nat. Acad. Sci. 117, 22281–22292 (2020).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    37.Rooker, J. R., Wells, R. J. D., Itano, D. G., Thorrold, S. R. & Lee, J. M. Natal origin and population connectivity of bigeye and yellowfin tuna in the Pacific Ocean. Fish. Oceanogr. 25, 277–291 (2016).Article 

    Google Scholar 
    38.Liao, W. H. & Ho, T. Y. Particulate trace metal composition and sources in the Kuroshio adjacent to the East China Sea: The importance of aerosol deposition. J. Geophys. Res. Oceans 123, 6207–6223 (2018).ADS 
    CAS 
    Article 

    Google Scholar 
    39.Campana, S. E. Chemistry and composition of fish otoliths: Pathways, mechanisms and applications. Mar. Ecol. Prog. Ser. 188, 263–297 (1999).ADS 
    CAS 
    Article 

    Google Scholar 
    40.Elsdon, T. S. & Gillanders, B. M. Relationship between water and otolith elemental concentrations in juvenile black bream Acanthopagrus butcheri. Mar. Ecol. Prog. Ser. 260, 263–272 (2003).ADS 
    CAS 
    Article 

    Google Scholar 
    41.Elsdon, T. S. & Gillanders, B. M. Interactive effects of temperature and salinity on otolith chemistry: Challenges for determining environmental histories of fish. Can. J. Fish. Aquat. Sci. 59, 1796–1808 (2002).CAS 
    Article 

    Google Scholar 
    42.Stanley, R. R. E. et al. Environmentally mediated trends in otolith composition of juvenile Atlantic cod (Gadus morhua). ICES J. Mar. Sci. 72, 2350–2363 (2015).Article 

    Google Scholar 
    43.Macdonald, J. I. & Crook, D. A. Variability in Sr:Ca and Ba:Ca ratios in water and fish otoliths across an estuarine salinity gradient. Mar. Ecol. Prog. Ser. 413, 147–161 (2010).ADS 
    CAS 
    Article 

    Google Scholar 
    44.Reis-Santos, P., Tanner, S. E., Elsdon, T. S., Cabral, H. N. & Gillanders, B. M. Effects of temperature, salinity and water composition on otolith elemental incorporation of Dicentrarchus labrax. J. Exp. Mar. Biol. Ecol. 446, 245–252 (2013).CAS 
    Article 

    Google Scholar 
    45.Rooker, J. R., Kraus, R. T. & Secor, D. H. Dispersive behaviors of black drum and red drum: Is otolith Sr:Ca a reliable indicator of salinity history?. Estuaries 27, 334–441 (2004).Article 

    Google Scholar 
    46.Hüssy, K. et al. Trace element patterns in otoliths: The role of biomineralization. Rev. Fish. Sci. Aquacult. https://doi.org/10.1080/23308249.2020.1760204 (2020).Article 

    Google Scholar 
    47.Thorrold, S. R., Jones, C. M. & Campana, S. E. Response of otolith microchemistry to environmental variations experienced by larval and juvenile Atlantic croaker (Micropogonias undulatus). Limnol. Oceanogr. 42, 102–111 (1997).ADS 
    CAS 
    Article 

    Google Scholar 
    48.Secor, D. H. & Rooker, J. R. Is otolith strontium a useful scalar of life-cycles in estuarine fishes?. Fish. Res. 1032, 1–14 (2000).
    Google Scholar 
    49.Izzo, C., Reis-Santos, P. & Gillanders, B. M. Otolith chemistry does not just reflect environmental conditions: A meta-analytic evaluation. Fish Fish. 19, 441–454 (2018).Article 

    Google Scholar 
    50.Sturrock, A. M. et al. Quantifying physiological influences on otolith chemistry. Methods Ecol. Evol. 6, 806–816 (2015).Article 

    Google Scholar 
    51.Bath, G. E. et al. Strontium and barium uptake in aragonitic otoliths of marine fish. Geochim. Cosmochim. Acta 64, 1705–1714 (2000).ADS 
    CAS 
    Article 

    Google Scholar 
    52.Arai, T., Kotake, A., Kayama, S., Ogura, M. & Watanabe, Y. Movements and life history patterns of the skipjack tuna Katsuwonus pelamis in the western Pacific, as revealed by otolith Sr:Ca ratios. J. Mar. Biol. Assoc. U. K. 85, 1211–1271 (2005).Article 

    Google Scholar 
    53.Shiozaki, T., Kondo, Y., Yuasa, D. & Takeda, S. Distribution of major diazotrophs in the surface water of the Kuroshio from northeastern Taiwan to south of mainland Japan. J. Plankton Res. 40, 407–419 (2018).CAS 
    Article 

    Google Scholar 
    54.Nakata, K., Hada, A. & Masukawa, Y. Variation in food abundance for Japanese sardine larvae related to Kuroshio meander. Fish. Oceanogr. 3, 39–49 (1994).Article 

    Google Scholar 
    55.Kitagawa, T. et al. Horizontal and vertical movements of juvenile bluefin tuna (Thunnus orientalis) in relation to seasons and oceanographic conditions in the eastern Pacific Ocean. Fish. Oceanogr. 16, 409–421 (2007).Article 

    Google Scholar 
    56.Ichinokawa, M., Okamura, H., Oshima, K., Yokawa, K. & Takeuchi, Y. Spatiotemporal catch distribution of age-0 Pacific bluefin tuna Thunnus orientalis caught by the Japanese troll fishery in relation to surface sea temperature and seasonal migration. Fish. Sci. 80, 1181–1191 (2014).CAS 
    Article 

    Google Scholar 
    57.Shimose, T., Tanabe, T., Chen, K. S. & Hsu, C. C. Age determination and growth of Pacific bluefin tuna, Thunnus orientalis, off Japan and Taiwan. Fish. Res. 100, 134–139 (2009).Article 

    Google Scholar 
    58.Chiba, S. et al. Large-scale climate control of zooplankton transport and biogeography in the Kuroshio–Oyashio extension region. Geophys. Res. Lett. 40, 5182–5187 (2013).ADS 
    Article 

    Google Scholar 
    59.Hiraoka, Y., Fujioka, K., Fukuda, H., Watai, M. & Ohshimo, S. Interannual variation of the diet shifts and their effects on the fatness and growth of age-0 Pacific bluefin tuna (Thunnus orientalis) off the southwestern Pacific coast of Japan. Fish. Oceanogr. 28, 419–433 (2019).Article 

    Google Scholar 
    60.Inagake, D. et al. Migration of young bluefin tuna, Thunnus orientalis Temminck et Schlegel, through archival tagging experiments and its relation with oceanographic conditions in the western north Pacific. Bull. Natl Res. Inst. Far Seas Fish. 38, 53–81 (2001).
    Google Scholar 
    61.Mohan, J. A. et al. Elements of time and place: Manganese and barium in shark vertebrae reflect age and upwelling histories. Proc. R. Soc. B Biol. Sci. 285, 20181760 (2018).Article 

    Google Scholar 
    62.Hsieh, Y. T. & Henderson, G. M. Barium stable isotopes in the global ocean: Tracer of Ba inputs and utilization. Earth Planet. Sci. Lett. 473, 269–278 (2017).ADS 
    CAS 
    Article 

    Google Scholar 
    63.Kimura, S. et al. Biological productivity of meso-scale eddies caused by front disturbances in the Kuroshio. ICES J. Mar. Sci. 54, 179–192 (1997).Article 

    Google Scholar 
    64.Tanaka, Y. et al. Occurrence of Pacific bluefin tuna (Thunnus orientalis) larvae off the Pacific coast of Tohoku area, northeastern Japan: Possibility of the discovery of the third spawning ground. Fish. Oceanogr. 29, 46–51 (2019).Article 

    Google Scholar 
    65.Shiao, J. C. et al. Contribution rates of different spawning and feeding grounds to adult Pacific bluefin tuna (Thunnus orientalis) in the northwestern Pacific Ocean. Deep Sea Res. Part I Oceanogr. Res. Pap. https://doi.org/10.1016/j.dsr.2020.103453 (2020).Article 

    Google Scholar 
    66.Uematsu, Y., Ishihara, T., Hiraoka, Y., Shimose, T. & Ohshimo, S. Natal origin identification of Pacific bluefin tuna (Thunnus orientalis) by vertebral first annulus. Fish. Res. 199, 26–31 (2018).Article 

    Google Scholar 
    67.Kitagawa, T., Fujioka, K. & Suzuki, N. Migrations of Pacific bluefin tuna in the western Pacific Ocean. In The Future of Bluefin Tuna: Ecology, Fisheries Management, and Conservation (ed. Block, B. A.) 147–164 (Johns Hopkins University Press, 2019).
    Google Scholar  More

  • in

    Recent expansion of marine protected areas matches with home range of grey reef sharks

    1.Rasher, D. B., Hoey, A. S. & Hay, M. E. Cascading predator effects in a Fijian coral reef ecosystem. Sci. Rep. 7, 1–10 (2017).CAS 
    Article 

    Google Scholar 
    2.Roff, G. et al. The ecological role of sharks on coral reefs. Trends Ecol. Evol. 31, 395–407 (2016).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    3.Ruppert, J. L. W., Travers, M. J., Smith, L. L., Fortin, M.-J. & Meekan, M. G. Caught in the middle: Combined impacts of shark removal and coral loss on the fish communities of coral reefs. PLoS ONE 8, e74648 (2013).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    4.Dulvy, N. K. et al. Extinction risk and conservation of the world’s sharks and rays. Elife 3, e00590 (2014).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    5.Field, I. C., Meekan, M. G., Buckworth, R. C. & Bradshaw, C. J. A. Chapter 4 susceptibility of sharks, rays and chimaeras to global extinction. In Advances in Marine Biology vol. 56 275–363 (Elsevier, 2009).6.MacNeil, M. A. et al. Global status and conservation potential of reef sharks. Nature 583, 801–806 (2020).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    7.Ward-Paige, C. A. et al. Large-scale absence of sharks on reefs in the Greater-Caribbean: A footprint of human pressures. PLoS ONE 5(8), e11968 (2010).8.Robbins, W. D., Hisano, M., Connolly, S. R. & Choat, J. H. Ongoing collapse of coral-reef shark populations. Curr. Biol. 16, 2314–2319 (2006).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    9.Juhel, J.-B. et al. Reef accessibility impairs the protection of sharks. J. Appl. Ecol. https://doi.org/10.1111/1365-2664.13007 (2017).Article 

    Google Scholar 
    10.Nadon, M. O. et al. Re-creating missing population baselines for pacific reef sharks. Conserv. Biol. 26, 493–503 (2012).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    11.Ferretti, F., Curnick, D., Liu, K., Romanov, E. V. & Block, B. A. Shark baselines and the conservation role of remote coral reef ecosystems. Sci. Adv. 4, eaaq0333 (2018).12.Ferretti, F., Worm, B., Britten, G. L., Heithaus, M. R. & Lotze, H. K. Patterns and ecosystem consequences of shark declines in the ocean: Ecosystem consequences of shark declines. Ecol. Lett. 13, 1055–1071 (2010).PubMed 
    PubMed Central 

    Google Scholar 
    13.Cinner, J. E. et al. Gravity of human impacts mediates coral reef conservation gains. Proc. Natl. Acad. Sci. 115, E6116–E6125 (2018).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    14.Davidson, L. N. K. & Dulvy, N. K. Global marine protected areas to prevent extinctions. Nat. Ecol. Evol. 1, 0040 (2017).Article 

    Google Scholar 
    15.O’Leary, B. C. et al. Effective coverage targets for ocean protection: Effective targets for ocean protection. Conserv. Lett. 9, 398–404 (2016).Article 

    Google Scholar 
    16.Sala, E. et al. Assessing real progress towards effective ocean protection. Mar. Policy 91, 11–13 (2018).Article 

    Google Scholar 
    17.D’agata, S. et al. Marine reserves lag behind wilderness in the conservation of key functional roles. Nat. Commun. 7, 12000 (2016).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    18.MacKeracher, T., Diedrich, A. & Simpfendorfer, C. A. Sharks, rays and marine protected areas: A critical evaluation of current perspectives. Fish Fish. 20, 255–267 (2019).Article 

    Google Scholar 
    19.Juhel, J.-B. et al. Isolation and no-entry marine reserves mitigate anthropogenic impacts on grey reef shark behavior. Sci. Rep. 9, 2897 (2019).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    20.Robbins, W. D. Abundance, demography and population structure of the grey reef shark (Carcharhinus amblyrhynchos) and the white tip reef shark (Triaenodon obesus) (Fam. Charcharhinidae). (James Cook University, 2006).21.Kellner, J. B., Tetreault, I., Gaines, S. D. & Nisbet, R. M. Fishing the line near marine reserves in single and multispecies fisheries. Ecol. Appl. 17, 1039–1054 (2007).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    22.Nillos Kleiven, P. J. et al. Fishing pressure impacts the abundance gradient of European lobsters across the borders of a newly established marine protected area. Proc. R. Soc. B Biol. Sci. 286, 20182455 (2019).Article 

    Google Scholar 
    23.Gerber, L. R. et al. Population models for marine reserve design: A retrospective and prospective synthesis. Ecol. Appl. 13, 47–64 (2003).Article 

    Google Scholar 
    24.Grüss, A., Kaplan, D. M., Guénette, S., Roberts, C. M. & Botsford, L. W. Consequences of adult and juvenile movement for marine protected areas. Biol. Conserv. 144, 692–702 (2011).Article 

    Google Scholar 
    25.Edgar, G. J. et al. Global conservation outcomes depend on marine protected areas with five key features. Nature 506, 216–220 (2014).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    26.Abecasis, D., Afonso, P. & Erzini, K. Combining multispecies home range and distribution models aids assessment of MPA effectiveness. Mar. Ecol. Prog. Ser. 513, 155–169 (2014).ADS 
    Article 

    Google Scholar 
    27.Di Franco, A. et al. Linking home ranges to protected area size: The case study of the Mediterranean Sea. Biol. Conserv. 221, 175–181 (2018).Article 

    Google Scholar 
    28.Krueck, N. C. et al. Reserve sizes needed to protect coral reef fishes: reserve sizes to protect coral reef fishes. Conserv. Lett. 11, e12415 (2018).29.Pittman, S. J. et al. Fish with chips: Tracking reef fish movements to evaluate size and connectivity of Caribbean marine protected areas. PLoS ONE 9, e96028 (2014).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    30.Weeks, R., Green, A. L., Joseph, E., Peterson, N. & Terk, E. Using reef fish movement to inform marine reserve design. J. Appl. Ecol. 54, 145–152 (2017).Article 

    Google Scholar 
    31.Dwyer, R. G. et al. Individual and population benefits of marine reserves for reef sharks. Curr. Biol. 30, 117–118 (2020).32.Friedlander, A., Sandin, S., DeMartini, E. & Sala, E. Spatial patterns of the structure of reef fish assemblages at a pristine atoll in the central Pacific. Mar. Ecol. Prog. Ser. 410, 219–231 (2010).ADS 
    Article 

    Google Scholar 
    33.Clarke, C., Lea, J. & Ormond, R. Comparative abundance of reef sharks in the Western Indian Ocean. In Proceedings of the 12th International Coral Reef Symposium, Cairns, Australia, 9-13 July 2012 (2012).34.Bonnin, L. et al. Repeated long-range migrations of adult males in a common Indo-Pacific reef shark. Coral Reefs https://doi.org/10.1007/s00338-019-01858-w (2019).Article 

    Google Scholar 
    35.Speed, C. W. et al. Reef shark movements relative to a coastal marine protected area. Reg. Stud. Mar. Sci. 3, 58–66 (2016).Article 

    Google Scholar 
    36.Udyawer, V. et al. A standardised framework for analysing animal detections from automated tracking arrays. Anim. Biotelem. 6, 17 (2018).Article 

    Google Scholar 
    37.Brodie, S. et al. Continental-scale animal tracking reveals functional movement classes across marine taxa. Sci. Rep. 8, 3717 (2018).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    38.Espinoza, M., Heupel, M. R., Tobin, A. J. & Simpfendorfer, C. A. Residency patterns and movements of grey reef sharks (Carcharhinus amblyrhynchos) in semi-isolated coral reef habitats. Mar. Biol. 162, 343–358 (2015).CAS 
    Article 

    Google Scholar 
    39.Vianna, G. M. S., Meekan, M. G., Meeuwig, J. J. & Speed, C. W. Environmental influences on patterns of vertical movement and site fidelity of grey reef sharks (Carcharhinus amblyrhynchos) at aggregation sites. PLoS ONE 8, e60331 (2013).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    40.Barnett, A., Abrantes, K. G., Seymour, J. & Fitzpatrick, R. Residency and spatial use by reef sharks of an isolated seamount and its implications for conservation. PLoS ONE 7, e36574 (2012).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    41.Field, I. C., Meekan, M. G., Speed, C. W., White, W. & Bradshaw, C. J. A. Quantifying movement patterns for shark conservation at remote coral atolls in the Indian Ocean. Coral Reefs 30, 61–71 (2010).ADS 
    Article 

    Google Scholar 
    42.Heupel, M. R. & Simpfendorfer, C. A. Long-term movement patterns of a coral reef predator. Coral Reefs 34, 679–691 (2015).ADS 
    Article 

    Google Scholar 
    43.Andréfouët, S., Torres-Pulliza, D., Dosdane, M., Kranenburg, C. & Murch, B. Atlas des récifs coralliens de Nouvelle-Calédonie. IFRECOR Nouv.-Caléd. IRD Nouméa 26 (2004).44.Lea, J. S. E., Humphries, N. E., von Brandis, R. G., Clarke, C. R. & Sims, D. W. Acoustic telemetry and network analysis reveal the space use of multiple reef predators and enhance marine protected area design. Proc. R. Soc. B Biol. Sci. 283, 20160717 (2016).Article 

    Google Scholar 
    45.Benhamou, S. & Cornélis, D. Incorporating movement behavior and barriers to improve kernel home range space use estimates. J. Wildl. Manag. 74, 1353–1360 (2010).Article 

    Google Scholar 
    46.Fieberg, J. & Börger, L. Could you please phrase “home range” as a question?. J. Mammal. 93, 890–902 (2012).Article 

    Google Scholar 
    47.Heupel, M. R. & Simpfendorfer, C. A. Importance of environmental and biological drivers in the presence and space use of a reef-associated shark. Mar. Ecol. Prog. Ser. 496, 47–57 (2014).ADS 
    Article 

    Google Scholar 
    48.Dwyer, R. G. et al. Using individual-based movement information to identify spatial conservation priorities for mobile species. Conserv. Biol. 33, 1426–1437 (2019).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    49.IUCN, UNEP-WCMC. The World Database on Protected Areas (WDPA). [01/2019]. (UNEP World Conservation Monitoring Centre, Cambridge (UK), 2014). Available at: https://www.protectedplanet.net.50.UNEP-WCMC. Global Distribution of Warm-Water Coral Reefs, Compiled from Multiple Sources Including the Millennium Coral Reef Mapping Project. Version 4.0. (WorldFish Centre, WRI, TNC, 2018).51.Graham, N. A. J., Spalding, M. D. & Sheppard, C. R. C. Reef shark declines in remote atolls highlight the need for multi-faceted conservation action. Aquat. Conserv. Mar. Freshw. Ecosyst. 20, 543–548 (2010).Article 

    Google Scholar 
    52.Davis, K. L. F., Russ, G. R., Williamson, D. H. & Evans, R. D. Surveillance and poaching on inshore reefs of the Great Barrier Reef marine park. Coast. Manag. 32, 373–387 (2004).Article 

    Google Scholar 
    53.D’agata, S. et al. Human-mediated loss of phylogenetic and functional diversity in coral reef fishes. Curr. Biol. 24, 555–560 (2014).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    54.Gaines, S. D., White, C., Carr, M. H. & Palumbi, S. R. Designing marine reserve networks for both conservation and fisheries management. Proc. Natl. Acad. Sci. 107, 18286–18293 (2010).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    55.Bessa-Gomes, C., Legendre, S. & Clobert, J. Allee effects, mating systems and the extinction risk in populations with two sexes. Ecol. Lett. 7, 802–812 (2004).Article 

    Google Scholar 
    56.Rankin, D. J. & Kokko, H. Do males matter? The role of males in population dynamics. Oikos 116, 335–348 (2007).Article 

    Google Scholar 
    57.Pratt, H. L. & Carrier, J. C. A review of elasmobranch reproductive behavior with a case study on the nurse shark, Ginglymostoma cirratum. Environ. Biol. Fish. 60, 157–188 (2001).Article 

    Google Scholar 
    58.Momigliano, P., Harcourt, R., Robbins, W. D. & Stow, A. Connectivity in grey reef sharks (Carcharhinus amblyrhynchos) determined using empirical and simulated genetic data. Sci. Rep. 5, 13229 (2015).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    59.Momigliano, P. et al. Genetic structure and signatures of selection in grey reef sharks (Carcharhinus amblyrhynchos). Heredity 119(3), 142–153 (2017).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    60.Bradley, D. et al. Resetting predator baselines in coral reef ecosystems. Sci. Rep. 5, 43131 (2017).61.Williams, J. J., Papastamatiou, Y. P., Caselle, J. E., Bradley, D. & Jacoby, D. M. P. Mobile marine predators: An understudied source of nutrients to coral reefs in an unfished atoll. Proc. R. Soc. B 285, 20172456 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    62.Mourier, J., Vercelloni, J. & Planes, S. Evidence of social communities in a spatially structured network of a free-ranging shark species. Anim. Behav. 83, 389–401 (2012).Article 

    Google Scholar 
    63.Mourier, J. et al. Extreme inverted trophic pyramid of reef sharks supported by spawning groupers. Curr. Biol. 26, 2011–2016 (2016).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    64.Robbins, W. D. & Renaud, P. Foraging mode of the grey reef shark, Carcharhinus amblyrhynchos, under two different scenarios. Coral Reefs 35, 253–260 (2015).ADS 
    Article 

    Google Scholar 
    65.Devillers, R. et al. Reinventing residual reserves in the sea: Are we favouring ease of establishment over need for protection?. Aquat. Conserv. Mar. Freshw. Ecosyst. 25, 480–504 (2015).Article 

    Google Scholar 
    66.Boerder, K., Miller, N. A. & Worm, B. Global hot spots of transshipment of fish catch at sea. Sci. Adv. 4, eaat7159 (2018).67.Kroodsma, D. A. et al. Tracking the global footprint of fisheries. Science 359, 904–908 (2018).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    68.Watson, R. A. et al. Marine foods sourced from farther as their use of global ocean primary production increases. Nat. Commun. 6, 7365 (2015).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    69.Januchowski-Hartley, F. A., Vigliola, L., Maire, E., Kulbicki, M. & Mouillot, D. Low fuel cost and rising fish price threaten coral reef wilderness. Conserv. Lett. 13, e12706 (2020).Article 

    Google Scholar 
    70.Dent, F. & Clarke, S. State of the global market for shark products. FAO Fish. Aquac. Tech. Pap. 590, 37 (2015).
    Google Scholar 
    71.Schofield, G. et al. Evidence-based marine protected area planning for a highly mobile endangered marine vertebrate. Biol. Conserv. 161, 101–109 (2013).72.Botsford, L. W., Micheli, F. & Hastings, A. Principles for the design of marine reserves. Ecol. Appl. 13, 25–31 (2003).Article 

    Google Scholar 
    73.Hastings, A. & Botsford, L. W. Comparing designs of marine reserves for fisheries and for biodiversity. Ecol. Appl. 13, 65–70 (2003).Article 

    Google Scholar 
    74.Green, A. L. et al. Larval dispersal and movement patterns of coral reef fishes, and implications for marine reserve network design. Biol. Rev. 90, 1215–1247 (2015).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    75.CBD. Decisions Adopted by the Conference of the Parties to the Convention on Biological Diversity at its Eighth Meeting (Decision VIII/15, Annex IV). (2006).76.Giakoumi, S. et al. Revisiting “success” and “failure” of marine protected areas: A conservation scientist perspective. Front. Mar. Sci. 5, 223 (2018).Article 

    Google Scholar 
    77.Gill, D. A. et al. Capacity shortfalls hinder the performance of marine protected areas globally. Nature 543, 665–669 (2017).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    78.Rife, A. N., Erisman, B., Sanchez, A. & Aburto-Oropeza, O. When good intentions are not enough … Insights on networks of “paper park” marine protected areas. Conserv. Lett. 6, 200–212 (2013).Article 

    Google Scholar 
    79.Heupel, M. R., Simpfendorfer, C. A. & Fitzpatrick, R. Large-scale movement and reef fidelity of grey reef sharks. PLoS ONE 5, e9650 (2010). ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    80.Heupel, M. R., Reiss, K. L., Yeiser, B. G. & Simpfendorfer, C. A. Effects of biofouling on performance of moored data logging acoustic receivers. Limnol. Oceanogr. Methods 6, 327–335 (2008).Article 

    Google Scholar  More

  • in

    Heterodissemination: precision insecticide delivery to mosquito larval habitats by cohabiting vertebrates

    1.Gubler, D. J. Prevention and control of Aedes aegypti-borne diseases: lesson learned from past successes and failures. AsPac. J. Mol. Biol. Biotechnol. 19, 111–114 (2011).
    Google Scholar 
    2.Gratz, N. G. Critical review of the vector status of Aedes albopictus. Med. Vet. Entomol. 18, 215–227. https://doi.org/10.1111/j.0269-283X.2004.00513.x (2004).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    3.Unlu, I. Aedes albopictus in America: current perspectives and future challenges. CAB Rev. 14, 1–22 (2019).Article 

    Google Scholar 
    4.Schoof, H. Dispersal of Aedes taeniorhynchus Wiede-mann near Savannah. Georgia. Mosq. News 23, 1–10 (1963).
    Google Scholar 
    5.Fonseca, D. M. et al. Area-wide management of Aedes albopictus. Part 2: gauging the efficacy of traditional integrated pest control measures against urban container mosquitoes. Pest Manag. Sci. 69, 1351–1361 (2013).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    6.YiBin, Z., TongYan, Z. & PeiEn, L. Evaluation on the control efficacy of source reduction to Aedes albopictus in Shanghai, China. Chin. J. Vector Biol. Control 20, 3–6 (2009).
    Google Scholar 
    7.Rochlin, I., Ninivaggi, D. V., Hutchinson, M. L. & Farajollahi, A. Climate change and range expansion of the Asian tiger mosquito (Aedes albopictus) in Northeastern USA: implications for public health practitioners. PLoS ONE 8, e60874. https://doi.org/10.1371/journal.pone.0060874 (2013).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    8.Hawley, W. A. The biology of Aedes albopictus. J. Am. Mosq. Control Assoc. Suppl. 1, 1–39 (1988).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    9.Richards, S. L., Ghosh, S. K., Zeichner, B. C. & Apperson, C. S. Impact of source reduction on the spatial distribution of larvae and pupae of Aedes albopictus (Diptera: Culicidae) in suburban neighborhoods of a Piedmont community in North Carolina. J. Med. Entomol. 45, 617–628 (2008).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    10.Unlu, I., Farajollahi, A., Strickman, D. & Fonseca, D. M. Crouching tiger, hidden trouble: Urban sources of Aedes albopictus (Diptera: Culicidae) refractory to source-reduction. PLoS ONE 8, e77999 (2013).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    11.Lam, P. H. Y., Boon, C. S., Yng, N. Y. & Benjamin, S. Aedes albopictus control with spray application of Bacillus thuringiensis israelensis, strain AM 65-52. Southeast Asian J. Trop. Med. Public Health 41, 1071 (2010).PubMed 
    PubMed Central 

    Google Scholar 
    12.Seleena, P., Lee, H. L., Nazni, W., Rohani, A. & Kadri, M. Microdroplet application of mosquitocidal Bacillus thuringiensis using ultra-low-volume generator for the control of mosquitos. Southeast Asian. J. Trop. Med. Public Health 27, 628–632 (1996).CAS 

    Google Scholar 
    13.Chandel, K. et al. Targeting a hidden enemy: Pyriproxyfen autodissemination strategy for the control of the container mosquito Aedes albopictus in cryptic habitats. PLoS Negl. Trop. Dis. 10, e0005235 (2016).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    14.Pruszynski, C. A., Hribar, L. J., Mickle, R. & Leal, A. L. A large scale biorational approach using Bacillus thuringiensis israeliensis (strain AM65-52) for managing Aedes aegypti populations to prevent dengue, chikungunya and Zika transmission. PLoS ONE 12, e0170079 (2017).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    15.Unlu, I., Faraji, A., Indelicato, N. & Fonseca, D. M. The hidden world of Asian tiger mosquitoes: immature Aedes albopictus (Skuse) dominate in rainwater corrugated extension spouts. Trans. R. Soc. Trop. Med. Hyg. 108, 699–705. https://doi.org/10.1093/trstmh/tru1139 (2014).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    16.Itoh, T. Utilization of blood fed females of Aedes aegypti as a vehicle for the transfer of the insect growth regulator, pyriproxyfen, to larval habitats. Trop. Med. 36, 243–248 (1995).
    Google Scholar 
    17.Gaugler, R., Suman, D. & Wang, Y. An autodissemination station for the transfer of an insect growth regulator to mosquito oviposition sites. Med. Vet. Entomol. 26, 37–45 (2012).CAS 
    PubMed 
    Article 

    Google Scholar 
    18.Mbare, O., Lindsay, S. W. & Fillinger, U. Testing a pyriproxyfen auto-dissemination station attractive to gravid Anopheles gambiae sensu stricto for the development of a novel attract-release-and-kill strategy for malaria vector control. BMC Infect. Dis. 19, 1–12 (2019).CAS 
    Article 

    Google Scholar 
    19.Devine, G. J. et al. Using adult mosquitoes to transfer insecticides to Aedes aegypti larval habitats. Proc. Natl. Acad. Sci. 106, 11530–11534 (2009).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    20.Caputo, B. et al. The “auto-dissemination” approach: a novel concept to fight Aedes albopictus in urban areas. PLoS Negl. Trop. Dis. 6, e1793 (2012).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    21.Lwetoijera, D., Kiware, S., Okumu, F., Devine, G. J. & Majambere, S. Autodissemination of pyriproxyfen suppresses stable populations of Anopheles arabiensis under semi-controlled settings. Malar. J. 18, 1–10 (2019).Article 

    Google Scholar 
    22.Unlu, I. et al. Large-scale operational pyriproxyfen autodissemination deployment to suppress the immature Asian Tiger Mosquito (Diptera: Culicidae) populations. J. Med. Entomol. 57, 1120–1130 (2020).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    23.Mains, J. W., Brelsfoard, C. L. & Dobson, S. L. Male mosquitoes as vehicles for insecticide. PLoS Negl. Trop. Dis. 9, e0003406–e0003406 (2015).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    24.Bibbs, C. S., Anderson, C. S., Smith, M. L. & Xue, R.-D. Direct and indirect efficacy of truck-mounted applications of s-methoprene against Aedes albopictus (Diptera: Culicidae). Int. J. Pest Manag. 64, 19–26 (2018).CAS 
    Article 

    Google Scholar 
    25.Wang, Y. et al. Heterodissemination: precision targeting container Aedes mosquitoes with a cohabiting midge species carrying insect growth regulator. Pest Manag. Sci. 76, 2105–2112 (2020).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    26.Lopez, L. C. S., Filizola, B., Deiss, I. & Rios, R. I. Phoretic behaviour of bromeliad annelids (Dero) and ostracods (Elpidium) using frogs and lizards as dispersal vectors. Hydrobiologia 549, 15–22 (2005).Article 

    Google Scholar 
    27.Torresdal, J. D., Farrell, A. D. & Goldberg, C. S. Environmental DNA detection of the golden tree frog (Phytotriades auratus) in bromeliads. PLoS ONE 12, e0168787 (2017).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    28.Wilke, A. B., Vasquez, C., Mauriello, P. J. & Beier, J. C. Ornamental bromeliads of Miami-Dade County, Florida are important breeding sites for Aedes aegypti (Diptera: Culicidae). Parasit. Vectors 11, 1–7 (2018).Article 

    Google Scholar 
    29.Council, N. R. Guide for the Care and Use of Laboratory Animals (National Academies Press, Washington, 2010).
    Google Scholar 
    30.Unlu, I. et al. Effectiveness of autodissemination stations containing pyriproxyfen in reducing immature Aedes albopictus populations. Parasit. Vectors 10, 1–10 (2017).Article 
    CAS 

    Google Scholar 
    31.Unlu, I. et al. Effects of a red marker dye on Aedes and Culex larvae: are there implications for operational mosquito control?. J. Am. Mosq. Control Assoc. 31, 375–379 (2015).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    32.Development, R. & Team, C. A language and environment for statistical computing. R Foundation for Statistical Computing. Vienna, Austria ( https://www.R-project.org/ ) (2019).33.Bates, D., Maechler, M., Bolker, B. & Walker, S. lme4: Linear mixed-effects models using Eigen and S4. R package version 1 (2014).34.Crawley, M. J. The R Book (Wiley, Chichester, 2012).MATH 
    Book 

    Google Scholar 
    35.Lenth, R. V. Using lsmeans. J. Stat. Softw. 69, 1–33 (2017).
    Google Scholar 
    36.Plummer, M. in Proceedings of the 3rd international workshop on distributed statistical computing. 1–10 (Vienna, Austria.).37.Kellner, K. jagsUI: a wrapper around rjags to streamline JAGS analyses. R Package Vers. 1, 2015 (2015).
    Google Scholar 
    38.Khan, G. Z., Khan, I., Khan, I. A., Salman, M. & Ullah, K. Evaluation of different formulations of IGRs against Aedes albopictus and Culex quinquefasciatus (Diptera: Culicidae). Asian. Pac. J. Trop. Biomed. 6, 485–491 (2016).CAS 
    Article 

    Google Scholar 
    39.Bury, R. B. & Whelan, J. A. Ecology and Management of the Bullfrog Vol. 155 (Fish and Wildlife Service, Washington, 1985).
    Google Scholar 
    40.WHO. Review of the insect growth regulator pyriproxyfen GR, pp. 50–67. InReport of the 4th WHOPES Working Group Meeting, 2000 December 4–5, Geneva Switzerland Geneva. WHO/CDS, WHOPES/2001. (2001).41.Devillers, J. Fate and ecotoxicological effects of pyriproxyfen in aquatic ecosystems. Environ. Sci. Pollut. Res. 1–17 (2020).42.Schaefer, C. & Miura, T. Chemical persistence and effects of S-31183, 2-[1-methyl-2-(4-phenoxyphenoxy) ethoxy] pyridine, on aquatic organisms in field tests. J. Econ. Entomol. 83, 1768–1776 (1990).CAS 
    Article 

    Google Scholar 
    43.Ose, K., Miyamoto, M., Fujisawa, T. & Katagi, T. Bioconcentration and metabolism of pyriproxyfen in tadpoles of African clawed frogs, Xenopus laevis. J. Agric. Food Chem. 65, 9980–9986 (2017).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    44.Lajmanovich, R. C. et al. Insecticide pyriproxyfen (Dragón®) damage biotransformation, thyroid hormones, heart rate, and swimming performance of Odontophrynus americanus tadpoles. Chemosphere 220, 714–722 (2019).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    45.https://edis.ifas.ufl.edu/uw259. The Cuban Treefrog (Osteopilus septentrionalis) in Florida. This document is WEC218, one of a series of the Department of Wildlife Ecology and Conservation, UF/IFAS Extension. (2017).46.Glorioso, B. M. et al. Osteopilus septentrionalis (Cuban treefrog). Herpetol. Rev. 49, 70–71 (2018).
    Google Scholar 
    47.Wermelinger, E. D. & Carvalho, RWd. Methods and procedures used in Aedes aegypti control in the successful campaign for yellow fever prophylaxis in Rio de Janeiro, Brazil, in 1928 and 1929. Epidemiol. Serv. Saude. 25, 837–844 (2016).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    48.Santos França, L. et al. Challanges for the control and prevention of the Aedes aegypti mosquito. Rev. Enferm. UFPE. 11, 4913 (2017).Article 

    Google Scholar 
    49.Minakawa, N., Mutero, C. M., Githure, J. I., Beier, J. C. & Yan, G. Spatial distribution and habitat characterization of anopheline mosquito larvae in western Kenya. Am. J. Trop. Med. Hyg. 61, 1010–1016 (1999).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    50.Mutuku, F. M. et al. Pupal habitat productivity of Anopheles gambiae complex mosquitoes in a rural village in western Kenya. Am. J. Trop. Med. Hyg. 74, 54–61 (2006).PubMed 
    Article 
    PubMed Central 

    Google Scholar  More