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    Droplet microfluidics-based high-throughput bacterial cultivation for validation of taxon pairs in microbial co-occurrence networks

    Conception of the workflow to demonstrate the microbial associations from co-occurrence networks with microbial cultivationMicrobial co-occurrence networks are composed of nodes and edges, which usually represent microbes and statistically significant associations between microbes, respectively. We hypothesized that the microbial associations could be validated if the topological properties of networks are simplified, and if the microbes representing the nodes can be cultivated. To test this hypothesis, we designed a workflow as shown in Fig. 1. A total of 12,096 wells from 126 96-well plates were inoculated with droplets of series diluted environmental samples, wells from each 96-well plate represented the same combination of given culture condition, sample type (plants, roots, and sediments) and dilution rate (from 10–1 to 10–7). After being cultivated at 30 °C for 10 days, 69 effective (Supplementary Table S3) plates with  > 30% wells showing microbial growth were retained for downstream microbial community analysis. Microbial DNA in each well was extracted, bar-coded, and sequenced for the inference of co-occurrence networks. The wells of plates showing high abundances of target Zotus were targeted for microbial isolations. Lastly, the cultivated microbial isolates were matched to Zotus in the network and used for demonstration of microbial interactions.Figure 1Overview of experimental demonstration of microbial interactions in co-occurrence networks. For detailed description, please refer to the method section.Full size imagePrevalent Zotu pairs in the co-occurrence networksDepending on the microbial density in samples, the 96-well plates harbored different numbers of wells with microbial growth. We obtained 65 96-well plates (6,091 wells) that were effective with microbial growth and data analysis for co-occurrence network reconstruction. After quality control and denoise, we obtained 130 Gbp sequence data. A total of 14,377 Zotus were annotated (Supplementary Table S4). There were 217 ± 94 (average ± standard deviation) prevalent Zotus, i.e., these Zotus appeared at frequencies ≥ 30% of wells in a given 96-well plate.Next, we analyzed Zotus compositions and abundances in each well of the 65 plates. Accordingly, we reconstructed 65 independent microbial co-occurrence networks and further retrieved the robust (Spearman’s |ρ| > 0.6 and P  More

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    Kinship dynamics may drive selection of age-related traits

    “This new study is inspired by some our earlier theoretical work applied to killer whales that suggests that age-related changes in relatedness are important for the evolution of menopause,” says Samuel Ellis, the first author of the study. “Reproduction can be thought of as a form of generalized harm as the birth of an offspring increases within-group competition for resources. Kinship dynamics — the ways in which local relatedness changes over an individual’s lifetime — are one way that menopause could be favored, because older females are more inclined to cease reproduction to not harm their group mates than younger females. Here we wanted to generalize this concept to both sexes, and to other species without menopause.” More

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    Viral metagenomics reveals persistent as well as dietary acquired viruses in Antarctic fur seals

    After massive parallel sequencing of the nucleic acids obtained from fur seal scats, a wide variety of invertebrate and vertebrate viral hosts assignations with low nucleotidic and amino-acidic identities were obtained, most of them corresponding to animal species not described before in Antarctica. These results make us reconsider the use of closed RefSeq databases for viral discovery, especially because the studied area was a remote geographical area where a high number of new viral species is expected to occur22.After repeating the analysis of the contigs obtained using BLASTn, a high number of miss-assignments was observed, corresponding almost entirely to contigs newly assigned as unclassified Eukaryotic Circular Rep-Encoding Single-Stranded DNA (CRESS-DNA) viral sequences. CRESS viruses have been detected ubiquitously in many different animals without any recognised role in the development of any disease23,24,25,26.These results are in accordance with the recent reporting of CRESS sequences also being ubiquitous in a wide variety of environments and at high proportions, including Antarctica, where they have been described to represent more than 50% of sequences obtained from glacier waters27.Viral-host distributionVirome studies in other Arctocephalus species from subantarctic and South American regions revealed a 5% of viral sequences with predominance of bacteriophages followed by viruses from the Parvoviridae family28. The methodology here applied provided an increase of 12–25% viral reads when probe-based Target Enrichment Sequencing (TES) was applied, that in comparison with Untargeted Viral Metagenomics (UVM) approaches conducted in these type of samples28 could be considered an optimal result.Most of the viral species detected in feces corresponded to unknown viruses, 83.59% from the total of sequences, followed by viruses that infect invertebrates, 8.75%, bacteriophages, 4.46%, and vertebrate viruses, 3.11% (Fig. 1).Figure 1Host distribution of viral assignations sequenced from fecal (A) and serum (B) samples collected from male A. gazella.Full size imageAs expected, when applying both targeted and untargeted sequencing methodologies, TES approach resulted in a recovery of many vertebrate viral assignations (Table 1) whereas untargeted sequencing enabled a better detection of viruses known to infect invertebrates (Table 2). To describe the complete A. gazella fecal virome, sequences obtained by both sequencing methodologies were considered all together, representing a total of 2.62 million reads.Table 1 Vertebrate viral assignations obtained from fecal samples sequencing from male A. gazella. Ranges of Genome coverage, nucleotide identity and aminoacidic identity are expressed in percentages.Full size tableTable 2 Invertebrate viral assignations obtained from fecal samples sequencing from male A. gazella. Colours represent the presence of each assignation in the processed pools. Ranges of Coverage, NT ID and AA ID are represented in percentages.Full size table
    A. gazella virusesFur seal picorna-like virusFur seal picorna-like virus was firstly described in a fecal sample obtained from A. gazella in King George Island in the South Shetland Islands, Antarctica by Krumbholz and co-workers16.In this study, we report a total of 19 contigs resulting after assembling 2671 reads obtained from 4/4 fecal pools analysed being the most prevalent virus described in this study. One of the contigs covered 96.91% of the fur seal picorna-like virus genome and presented a nucleotide homology of 99.38% with the reference strain described in 2017. The other contigs coverage ranged from 19.75 to 21.22% with a 45.92 to 90.5% nucleotide identity with reference strain NC_035110. Four contigs matching the ORF2 polyprotein are represented in Fig. 2 where differences among them and with the reference strain are showed.Figure 2Nucleotide alignment of ORF2 sequences from the A. gazella picorna-like contigs compared to the ORF2 from RefSeq NC_0351110. In consensus strain, position 1 represents position 6523 from RefSeqs genome.Full size imagePicornaviruses are known to cause a wide variety of diseases in vertebrate hosts, especially mammals29, but the role of Fur seal picorna-like virus in pathogenesis development is still unknown30. Many picornaviruses are transmitted horizontally via fecal–oral or airborne routes29. The fact that these sequences were detected in all the fecal pools obtained from animals with no evidence of disease may that suggest the virus may have a stable endemic relationship within that seal population.Torque teno pinniped virusLambdatorquevirus is a genus within the Anelloviridae family. The genus comprises 8 species named Torque teno pinniped virus 2 to 9 isolated from different pinniped species: A. gazella (Torque teno pinniped virus 6 and 7)17, Phoca vitulina (Torque teno pinniped virus 2, 3, 4)31, Zalophus californianus (Torque teno pinniped virus 5)32 and Leptonychotes weddellii (Torque teno pinniped 8 and 9)33.One contig with a nuleotide similarity of 95.12% against Torque teno pinniped virus 7 was obtained from one of the fecal pools. This virus had been described in these animals inhabiting Livingston Island in 2016, using rolling circle amplification and subsequent Sanger sequencing from buccal swabs17. However, sequences obtained in this study belong to partial ORF2 which is not the optimal genome region for typing purposes or phylogenetic analysis.These members of the Anelloviridae represent the more abundant viruses found in human, animals and environmental samples although their etiological role in any disease has not been clearly identified being considered a persistent virus ubiquitous to several different tissues34,35No Torque teno virus sequences were detected in serum samples which agree with what was observed for Zalophus californianus anellovirus prevalently detected in different tissues, like lung and liver, but not in blood samples. Interestingly, other known anelloviruses are typically found in blood or plasma samples32.MamastrovirusTwo of the fecal pools analyzed presented Mamastrovirus sequences. The presence of these viruses in humans and other mammals is widely known, as well as their involvement in gastroenteritis development36. The four contigs obtained (comprising 1008 sequences) showed homologies against reference genomes, ranging from 45.70% to 59.37% when compared at nucleotide level and 36.69% to 46.69% when compared at aminoacidic level. Phylogenetic analysis of partial OFR2 regions of these contigs indicate its closer similarity with sequences from California Sea Lion astroviruses, a virus that was determined as to be the most prevalent in fecal samples from these animals (Z. californianus)37. This finding suggests that these sequences may belong to a yet unknown virus like Z. californianus astrovirus and may indicate that such virus is prevalent in the sampled area (detected in 2/4 fecal pools studied) and the second more abundant virus (1008 reads) in the studied fecal samples (Fig. 3).Figure 3Phylogenetic consensus tree based on partial ORF2 sequences from the Mamastrovirus contigs sequenced from A. gazella scats (in bold). Bootstrap resampling with 1000 replicates.Full size imageAdeno associated virus 2Two of the studied fecal pools presented 138 sequences, forming 3 contigs with nucleotide identities ranging from 46.91 to 48.04% (Table 1), that matched adeno associated viruses previously described in Z. californianus, humans and other mammals with and unknow etiologic role (Fig. 4). The detected sequences probably correspond to fur seal adeno associated viruses never described before. The detection of these viruses is quite common in other mammals suggesting they could cause persistent infections in their hosts, but no etiological role has been attributed to them38.Figure 4Phylogenetic consensus tree of the Adeno-associated virus contigs sequenced from A. gazella scats (in bold). Bootstrap resampling with 1000 replicates.Full size imageNorovirusA norovirus contig was obtained in one of the four pools analyzed. Noroviruses are the most relevant non-bacterial gastroenteritis etiological agents in humans39, with its presence widely described in other mammals40. The contig detected in the fecal samples, represented the 4.43% of the viral genome, was in the VP1 region and comprised 56 reads with an identity  > 99% to California sea lion norovirus described by Teng and collaborators in 201841 (Fig. 5). Results obtained suggest these sequences belong to a putative new norovirus specie.Figure 5Phylogenetic consensus tree of the Norovirus contig sequenced from A. gazella scats (in bold). Bootstrap resampling with 1000 replicates.Full size imageViruses in serum samplesAll the viral sequences obtained from serum samples (970 reads) matched to CRESS-DNA viral sequences from unknown hosts.The fact that no other viruses were identified in serum samples suggests the animals tested were not under active viremia at the time of sample collection or it was not detectable by the applied methodology.Diet related virusesSeveral virus sequences similar to viruses known to have invertebrate animals as hosts were detected in fecal pools, mainly by UVM although some also by TES. These viruses are probably present in fur seal feces because of dietary habits although, since scats were collected from the ground nearby the animals, environmental cross-contamination should not be ruled out.Sequences with high coverage or similarities to any described virus are showed in Table 2.The high prevalence of virus sequences from crustaceans in the feces analyzed is hardly surprising because A. gazella inhabiting the Antarctic peninsula and the Atlantic sector of the Southern Ocean feed mostly on Antarctic krill Euphasia superba during the summer months42,43,44,45,46,47,48. Sequences from cephalopod viruses were also detected, although were much scarcer than those from crustaceans. This also agrees with current knowledge about the diet of A. gazella in the Atlantic sector of the Southern Ocean, where octopuses and squids are regularly consumed, although in low numbers44,45,46. It is worth noting than not cephalopod beak was recovered from the scats analyzed here48. Among all invertebrate viruses identified, some sequences present low identities with genomes from available databases, probably because Antarctica wildlife has been scarcely explored, forcing bioinformatic analysis to match them with the most similar viruses from these databases.No fish viruses were found in this study. Hard skeletal remains of fishes are often recovered from the scats of A. gazella from the Atlantic sector of the Southern Ocean42,43,44,45,46,47 and occurred indeed in the samples analysed here48, but stable isotope analysis of blood and whiskers revealed a negligible contribution of fish to the assimilate diet of juvenile and subadult male A. gazella49, which likely explain the absence of fish viruses in the samples analized here. Additionaly, no data on the virome present in the fish species regularly consumed by A. gazella has been published to our knowledge, with information limited to the bacteriome32, so even in case fish viruses were sequenced, it might not be correctly assigned to a fish host. Nevertheless, the methodology applied in this study had been successfully applied to the identification of the virome of Atlantic fishes50. Furthermore, Li and coworkers.37 and Wille and coworkers.22 also observed viral sequences probably corresponding to fish when analyzing the fecal virome of the California sea lions and Antarctic penguins.On the other hand, sequences highly similar to Coelho and Khabarov viral polymerases (greater than 98% of aminoacid identity), previously described in chinstrap penguins (Pygoscelis antarcticus) by Wille and coworkers22, were found in this study. The consumption of penguins by A. gazella during the summer months has been reported widely51,52,53,54,55, penguins feathers were reported from the scats analyzed in this study48 and stable isotope analysis of blood and whiskers revealed penguins as the second most relevant prey from juvenile and subadult male A. gazella in the population studied here49. This evidence is consistent with the presence of virus from chinstrap penguins in the samples analysed here. All in all, the study of fecal virome constitutes a very promising tool to explore the consumers’ diet. More

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    Presence of algal symbionts affects denitrifying bacterial communities in the sea anemone Aiptasia coral model

    Darwin C. The structure and distribution of coral reefs, 3rd edn. D. Appleton & Company: New York, NY, USA, 1889.Lajeunesse TC, Parkinson JE, Gabrielson PW, Jeong HJ, Reimer JD, Voolstra CR, et al. Systematic Revision of Symbiodiniaceae Highlights the Antiquity and Diversity of Coral Endosymbionts. Curr Biol. 2018;28:2570–80.e6.CAS 
    PubMed 

    Google Scholar 
    Muscatine L, Porter JW. Reef corals: mutualistic symbioses adapted to nutrient-poor environments. Bioscience. 1977;27:454–60.
    Google Scholar 
    Rohwer F, Seguritan V, Azam F, Knowlton N. Diversity and distribution of coral-associated bacteria. Mar Ecol Prog Ser. 2002;243:1–10.
    Google Scholar 
    Rosenberg E, Koren O, Reshef L, Efrony R, Zilber-Rosenberg I. The role of microorganisms in coral health, disease and evolution. Nat Rev Microbiol. 2007;5:355–62.CAS 
    PubMed 

    Google Scholar 
    Muscatine L. The role of symbiotic algae in carbon and energy flux in reef corals. Coral Reefs. 1990;25:75–87.
    Google Scholar 
    Falkowski PG, Dubinsky Z, Muscatine L, McCloskey L. Population control in symbiotic corals. Bioscience. 1993;43:606–11.
    Google Scholar 
    Baker DM, Freeman CJ, Wong JCY, Fogel ML, Knowlton N. Climate change promotes parasitism in a coral symbiosis. ISME J. 2018;12:921–30.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Rädecker N, Pogoreutz C, Gegner HM, Cárdenas A, Perna G, Geißler L, et al. Heat stress reduces the contribution of diazotrophs to coral holobiont nitrogen cycling. ISME J. 2022;16:1110–8.PubMed 

    Google Scholar 
    Rädecker N, Pogoreutz C, Voolstra CR, Wiedenmann J, Wild C. Nitrogen cycling in corals: the key to understanding holobiont functioning? Trends Microbiol. 2015;23:490–7.PubMed 

    Google Scholar 
    Bourne DG, Webster NS. Coral Reef Bacterial Communities. In: Rosenberg E, DeLong EF, editors. The Prokaryotes. Springer: Berlin Heidelberg; 2013. pp. 163–87.Ainsworth DT, Krause L, Bridge T, Torda G, Raina J-B, Zakrzewski M, et al. The coral core microbiome identifies rare bacterial taxa as ubiquitous endosymbionts. ISME J. 2015;9:2261–74.CAS 

    Google Scholar 
    Pernice M, Raina J-B, Rädecker N, Cárdenas A, Pogoreutz C, Voolstra CR. Down to the bone: the role of overlooked endolithic microbiomes in reef coral health. ISME J. 2020;14:325–34.PubMed 

    Google Scholar 
    Pogoreutz C, Oakley CA, Rädecker N, Cárdenas A, Perna G, Xiang N, et al. Coral holobiont cues prime Endozoicomonas for a symbiotic lifestyle. ISME J. 2022;16:1883–95.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Pogoreutz C, Voolstra CR, Rädecker N, Weis V. The coral holobiont highlights the dependence of cnidarian animal hosts on their associated microbes. In: Bosch TCG, Hadfield MG, editors. Cellular Dialogues in the Holobiont. Boca Raton: CRC Press; 2020. pp. 91–118.Babbin AR, Tamasi T, Dumit D, Weber L, Rodríguez MVI, Schwartz SL, et al. Discovery and quantification of anaerobic nitrogen metabolisms among oxygenated tropical Cuban stony corals. ISME J. 2021;15:1222–35.CAS 
    PubMed 

    Google Scholar 
    Glaze TD, Erler DV, Siljanen HMP. Microbially facilitated nitrogen cycling in tropical corals. ISME J. 2022;16:68–77.CAS 
    PubMed 

    Google Scholar 
    Lesser MP, Morrow KM, Pankey SM, Noonan SHC. Diazotroph diversity and nitrogen fixation in the coral Stylophora pistillata from the Great Barrier Reef. ISME J. 2018;12:813–24.CAS 
    PubMed 

    Google Scholar 
    Cardini U, Bednarz VN, Naumann MS, van Hoytema N, Rix L, Foster RA, et al. Functional significance of dinitrogen fixation in sustaining coral productivity under oligotrophic conditions. Proc R Soc B. 2015;282:20152257.PubMed 
    PubMed Central 

    Google Scholar 
    Pogoreutz C, Rädecker N, Cárdenas A, Gärdes A, Wild C, Voolstra CR. Nitrogen fixation aligns with nifH abundance and expression in two coral trophic functional groups. Front Microbiol. 2017;8:1187.PubMed 
    PubMed Central 

    Google Scholar 
    Pogoreutz C, Rädecker N, Cárdenas A, Gärdes A, Voolstra CR, Wild C. Sugar enrichment provides evidence for a role of nitrogen fixation in coral bleaching. Glob Chang Biol. 2017;23:3838–48.PubMed 

    Google Scholar 
    Bednarz VN, van de Water JA, Rabouille S, Maguer JF, Grover R, Ferrier‐Pagès C. Diazotrophic community and associated dinitrogen fixation within the temperate coral Oculina patagonica. Environ Microbiol. 2019;21:480–95.CAS 
    PubMed 

    Google Scholar 
    Lema KA, Willis BL, Bourne DG. Corals form characteristic associations with symbiotic nitrogen-fixing bacteria. Appl Environ Microbiol. 2012;78:3136–44.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lema KA, Clode PL, Kilburn MR, Thornton R, Willis BL, Bourne DG. Imaging the uptake of nitrogen-fixing bacteria into larvae of the coral Acropora millepora. ISME J. 2016;10:1804–8.CAS 
    PubMed 

    Google Scholar 
    Santos HF, Carmo FL, Duarte G, Dini-Andreote F, Castro CB, Rosado AS, et al. Climate change affects key nitrogen-fixing bacterial populations on coral reefs. ISME J. 2014;8:2272–9.PubMed 
    PubMed Central 

    Google Scholar 
    Rädecker N, Pogoreutz C, Gegner HM, Cárdenas A, Roth F, Bougoure J, et al. Heat stress destabilizes symbiotic nutrient cycling in corals. Proc Natl Acad Sci USA. 2021;118:e2022653118.PubMed 
    PubMed Central 

    Google Scholar 
    Braker G, Fesefeldt A, Witzel K-P. Development of PCR primer systems for amplification of nitrite reductase genes (nirK and nirS) to detect denitrifying bacteria in environmental samples. Appl Environ Microbiol. 1998;64:3769–75.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Tilstra A, El-Khaled YC, Roth F, Rädecker N, Pogoreutz C, Voolstra CR, et al. Denitrification aligns with N2 fixation in Red Sea corals. Sci Rep. 2019;9:1–9.Tilstra A, Roth F, El-Khaled YC, Pogoreutz C, Rädecker N, Voolstra CR, et al. Relative abundance of nitrogen cycling microbes in coral holobionts reflects environmental nitrate availability. R Soc Open Sci. 2021;8:201835.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Xiang N, Hassenrück C, Pogoreutz C, Rädecker N, Simancas-Giraldo SM, Voolstra CR, et al. Contrasting microbiome dynamics of putative denitrifying bacteria in two octocoral species exposed to dissolved organic carbon (DOC) and warming. Appl Environ Microbiol. 2022;88:e01886-21.El-Khaled YC, Roth F, Tilstra A, Rädecker N, Karcher DB, Kürten B, et al. In situ eutrophication stimulates dinitrogen fixation, denitrification, and productivity in Red Sea coral reefs. Mar Ecol Prog Ser. 2020;645:55–66.CAS 

    Google Scholar 
    Beauchamp EG, Trevors JT, Paul JW. Carbon sources for bacterial Denitrification. In: Stewart BA. Advances in Soil Science. Springer: New York, NY; 1989. pp. 113–42.Baker AC. Flexibility and Specificity in Coral-Algal Symbiosis: Diversity, Ecology, and Biogeography of Symbiodinium. Ann Rev Ecol Evol Syst. 2003;34:661–89.
    Google Scholar 
    Wang J-T, Chen Y-Y, Tew KS, Meng P-J, Chen CA. Physiological and Biochemical Performances of Menthol-Induced Aposymbiotic Corals. PLoS ONE. 2012;7:e46406.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Cui G, Liew YJ, Li Y, Kharbatia N, Zahran NI, Emwas A-H, et al. Host-dependent nitrogen recycling as a mechanism of symbiont control in Aiptasia. PLoS Genet. 2019;15:e1008189.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Rädecker N, Raina J-B, Pernice M, Perna G, Guagliardo P, Kilburn MR, et al. Using Aiptasia as a Model to Study Metabolic Interactions in Cnidarian-Symbiodinium Symbioses. Front Physiol. 2018;9:214.PubMed 
    PubMed Central 

    Google Scholar 
    Voolstra CR. A journey into the wild of the cnidarian model systemAiptasiaand its symbionts. Mol Ecol. 2013;22:4366–8.PubMed 

    Google Scholar 
    Sunagawa S, Wilson EC, Thaler M, Smith ML, Caruso C, Pringle JR, et al. Generation and analysis of transcriptomic resources for a model system on the rise: the sea anemone Aiptasia pallida and its dinoflagellate endosymbiont. BMC Genom. 2009;10:258.
    Google Scholar 
    Xiang T, Hambleton EA, DeNofrio JC, Pringle JR, Grossman AR. Isolation of clonal axenic strains of the symbiotic dinoflagellate Symbiodinium and their growth and host specificity1. J Phycol. 2013;49:447–58.CAS 
    PubMed 

    Google Scholar 
    Thornhill DJ, Lewis AM, Wham DC, Lajeunesse TC. Host‐specialist lineages dominate the adaptive radiation of reef coral endosymbionts. Evolution. 2014;68:352–67.CAS 
    PubMed 

    Google Scholar 
    Bieri T, Onishi M, Xiang T, Grossman AR, Pringle JR. Relative Contributions of Various Cellular Mechanisms to Loss of Algae during Cnidarian Bleaching. PLoS ONE. 2016;11:e0152693.PubMed 
    PubMed Central 

    Google Scholar 
    Baumgarten S, Simakov O, Esherick LY, Liew YJ, Lehnert EM, Michell CT, et al. The genome of Aiptasia, a sea anemone model for coral symbiosis. Proc Natl Acad Sci USA. 2015;112:11893–8.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Correa AMS, McDonald MD, Baker AC. Development of clade-specific Symbiodinium primers for quantitative PCR (qPCR) and their application to detecting clade D symbionts in Caribbean corals. Mar Biol. 2009;156:2403–11.CAS 

    Google Scholar 
    Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2− ΔΔCT method. Methods. 2001;25:402–8.CAS 
    PubMed 

    Google Scholar 
    Lee JA, Francis CA. DeepnirSamplicon sequencing of San Francisco Bay sediments enables prediction of geography and environmental conditions from denitrifying community composition. Environ Microbiol. 2017;19:4897–912.CAS 
    PubMed 

    Google Scholar 
    Huggett J, Dheda K, Bustin S, Zumla A. Real-time RT-PCR normalisation; strategies and considerations. Genes Immun. 2005;6:279–84.CAS 
    PubMed 

    Google Scholar 
    Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13:581–3.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBO J. 2011;17:10–2.
    Google Scholar 
    Boutet E, Lieberherr D, Tognolli M, Schneider M, Bairoch A. UniProtKB/Swiss-Prot: the manually annotated section of the UniProt KnowledgeBase. Methods Mol Biol. 2007;406:89–112.Abascal F, Zardoya R, Telford MJ. TranslatorX: multiple alignment of nucleotide sequences guided by amino acid translations. Nucleic Acids Res. 2010;38:7–13.
    Google Scholar 
    Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004;32:1792–7.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kearse M, Moir R, Wilson A, Stones-Havas S, Cheung M, Sturrock S, et al. Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics. 2012;28:1647–9.PubMed 
    PubMed Central 

    Google Scholar 
    Fish JA, Chai B, Wang Q, Sun Y, Brown CT, Tiedje JM, et al. FunGene: the functional gene pipeline and repository. Front Microbiol. 2013;4:291.PubMed 
    PubMed Central 

    Google Scholar 
    Wickham H. ggplot2. Wiley Interdiscip Rev Comput Stat. 2011;3:180–5.Oksanen J, Kindt R, Legendre P, O’Hara B, Stevens MHH, Oksanen MJ, et al. The vegan package. Commun Ecol Package. 2007;10:719.
    Google Scholar 
    McMurdie PJ, Holmes S. phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data. PLoS ONE. 2013;8:e61217.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lin H, Peddada SD. Analysis of compositions of microbiomes with bias correction. Nat Commun. 2020;11:1–11.CAS 

    Google Scholar 
    Meunier V, Geissler L, Bonnet S, Rädecker N, Perna G, Grosso O, et al. Microbes support enhanced nitrogen requirements of coral holobionts in a high CO 2 environment. Mol Ecol. 2021;30:5888–99.CAS 
    PubMed 

    Google Scholar 
    Geissler L, Meunier V, Rädecker N, Perna G, Rodolfo-Metalpa R, Houlbrèque F, et al. Highly Variable and Non-complex Diazotroph Communities in Corals From Ambient and High CO2 Environments. Front Mar Sci. 2021;8:754682.Thornhill DJ, Xiang Y, Pettay DT, Zhong M, Santos SR. Population genetic data of a model symbiotic cnidarian system reveal remarkable symbiotic specificity and vectored introductions across ocean basins. Mol Ecol. 2013;22:4499–515.CAS 
    PubMed 

    Google Scholar 
    Röthig T, Costa RM, Simona F, Baumgarten S, Torres AF, Radhakrishnan A, et al. Distinct bacterial communities associated with the coral model Aiptasia in aposymbiotic and symbiotic states with Symbiodinium. Front Mar Sci. 2016;3:234.
    Google Scholar 
    Hartman LM, Blackall LL, van Oppen MJH. Antibiotics reduce bacterial load in Exaiptasia diaphana, but biofilms hinder its development as a gnotobiotic coral model. Access Microbiol. 2022;4:000314.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lawson CA, Raina JB, Kahlke T, Seymour JR, Suggett DJ. Defining the core microbiome of the symbiotic dinoflagellate, Symbiodinium. Environ Microbiol Rep. 2018;10:7–11.CAS 
    PubMed 

    Google Scholar 
    Matthews JL, Raina JB, Kahlke T, Seymour JR, van Oppen MJ, Suggett DJ. Symbiodiniaceae‐bacteria interactions: rethinking metabolite exchange in reef‐building corals as multi‐partner metabolic networks. Environ Microbiol. 2020;22:1675–87.PubMed 

    Google Scholar 
    Costa RM, Cárdenas A, Loussert-Fonta C, Toullec G, Meibom A, Voolstra CR. Surface Topography, Bacterial Carrying Capacity, and the Prospect of Microbiome Manipulation in the Sea Anemone Coral Model Aiptasia. Front Microbiol. 2021;12:637834.Pelve EA, Fontanez KM, DeLong EF. Bacterial succession on sinking particles in the ocean’s interior. Front Microbiol. 2017;8:2269.PubMed 
    PubMed Central 

    Google Scholar 
    Welles L, Lopez-Vazquez CM, Hooijmans CM, Van Loosdrecht MCM, Brdjanovic D. Prevalence of ‘Candidatus Accumulibacter phosphatis’ type II under phosphate limiting conditions. AMB Express. 2016;6:1–12.Kaneko T. Complete Genomic Sequence of Nitrogen-fixing Symbiotic Bacterium Bradyrhizobium japonicum USDA110. DNA Res. 2002;9:189–97.PubMed 

    Google Scholar 
    Cziesielski MJ, Liew YJ, Cui G, Schmidt-Roach S, Campana S, Marondedze C, et al. Multi-omics analysis of thermal stress response in a zooxanthellate cnidarian reveals the importance of associating with thermotolerant symbionts. Proc R Soc B: Biol Sci. 2018;285:20172654.
    Google Scholar 
    Xiang T, Lehnert E, Jinkerson RE, Clowez S, Kim RG, Denofrio JC, et al. Symbiont population control by host-symbiont metabolic interaction in Symbiodiniaceae-cnidarian associations. Nat Commun. 2020;11:1–9.CAS 

    Google Scholar  More

  • in

    Estimates of regeneration potential in the Pannonian sand region help prioritize ecological restoration interventions

    Brondizio, E. S., Settele, J., Díaz, S. & Ngo, H. T. (eds). Global assessment report on biodiversity and ecosystem services of the intergovernmental science-policy platform on biodiversity and ecosystem services. https://doi.org/10.5281/zenodo.3831673 (IPBES Secretariat, 2019).UNEP/FAO. The UN Decade on Ecosystem Restoration 2021-2030 “Prevent, halt and reverse the degradation of ecosystems worldwide.” https://www.decadeonrestoration.org/ (2020).Fischer, J., Riechers, M., Loos, J., Martin-Lopez, B. & Temperton, V. M. Making the UN decade on ecosystem restoration a social-ecological endeavour. Trends Ecol. Evol. 36, 1 (2021).
    Google Scholar 
    Tolvanen, A. & Aronson, J. Ecological reastoration, ecosystem services, and land use: a European perspective. Ecol. Soc. 21, 47 (2016).
    Google Scholar 
    Strassburg, B. B. N. et al. Global priority areas for ecosystem restoration. Nature 586, 724–729 (2020).CAS 
    PubMed 

    Google Scholar 
    Temperton, V. M. et al. Step back from the forest and step up to the Bonn Challenge: how a broad ecological perspective can promote successful landscape restoration. Restor. Ecol. 27, 705–719 (2019).
    Google Scholar 
    Prach, K. & Hobbs, R. J. Spontaneous succession versus technical reclamation in the restoration of disturbed sites. Restor. Ecol. 16, 363–366 (2008).
    Google Scholar 
    Prach, K., Šebelíková, L., Řehounková, K. & del Moral, R. Possibilities and limitations of passive restoration of heavily disturbed sites. Landsc. Res. 45, 247–253 (2019).
    Google Scholar 
    Gilby, B. L. et al. Applying systematic conservation planning to improve the allocation of restoration actions at multiple spatial scales. Restor. Ecol. 29, e13403 (2021).
    Google Scholar 
    Erdős, L. et al. The edge of two worlds: a new review and synthesis on Eurasian forest-steppes. Appl. Veg. Sci. 21, 345–362 (2018).
    Google Scholar 
    Poschlod, P. & WallisDeVries, M. F. The historical and socioeconomic perspective of calcareous grasslands. Lessons learnt from the distant and recent past. Biol. Conserv. 104, 361–376 (2022).
    Google Scholar 
    Wesche, K. et al. The Palaearctic steppe biome: a new synthesis. Biodivers. Conserv. 25, 2197–2231 (2016).
    Google Scholar 
    Butaye, J., Dries, A. & Honnay, O. Conservation and restoration of calcareous grasslands: a concise review of the effects of fragmentation and management on plant species. Biotechnol. Agron. Soc. Environ. 9, 111–118 (2005).
    Google Scholar 
    Strassburg, B. B. N. et al. Strategic approaches to restoring ecosystems can triple conservation gains and halve costs. Nat. Ecol. Evol. 3, 62–70 (2019).PubMed 

    Google Scholar 
    Knight, M. L. & Overbeck, G. E. How much does is cost to restore a grassland? Restor. Ecol. 29, e13463 (2021).
    Google Scholar 
    Albert, Á.-J. et al. Trait-based analysis of spontaneous grassland recovery in sandy old-fields. Appl. Veg. Sci. 17, 214–224 (2014).
    Google Scholar 
    Crouzeilles, R. et al. Achieving cost-effective landscape-scale forest restoration through targeted natural regeneration. Conserv. Lett. 13, e12709 (2020).
    Google Scholar 
    Seregélyes, T., Molnár, Z. S., Csomós, Á. & Bölöni, J. Regeneration potential of the Hungarian (semi)-natural habitats I. Concepts and basic data of the MÉTA database. Acta Bot. Hung. 50, 229–248 (2008).
    Google Scholar 
    Käyhkö, N. & Skånes, H. Change trajectories and key biotopes – Assessing landscape dynamics and sustainability. Landsc. Urban Plan 75, 300–321 (2006).
    Google Scholar 
    Käyhkö, N. & Skånes, H. Retrospective land cover/land use change trajectories as drivers behind the local distribution and abundance patterns of oaks in south-western Finland. Landsc. Urban Plan 88, 12–22 (2008).
    Google Scholar 
    Swetnam, R. D. Rural land use in England and Wales between 1930 and 1998: Mapping trajectories of change with a high resolution spatio-temporal dataset. Landsc. Urban Plan 81, 91–103 (2007).
    Google Scholar 
    Ruiz, J. & Domon, G. 2009. Analysis of landscape pattern change trajectories within areas of intensive agricultural use: case study in a watershed of southern Québec, Canada. Landsc. Ecol. 24, 419–432 (2009).
    Google Scholar 
    Eremiášová, R. & Skokanová, H. Land use changes (recorded in old maps) and delimitation of the most stable areas from the perspective of land use in the Kašperské Hory region. Landsc. Ecol. 88, 20–34 (2009).
    Google Scholar 
    Frondoni, R. B. M. & Capotorti, G. A landscape analysis of land cover change in the Municipality of Rome (Italy): spatio-temporal characteristics and ecological implications of land cover transitions from 1954 to 2001. Landsc. Urban Plan 100, 117–128 (2011).
    Google Scholar 
    Biró, M., Szitár, K., Horváth, F., Bagi, I. & Molnár, Z. S. Detection of long-term landscape changes and trajectories in a Pannonian sand region: comparing land-cover and habitat-based approaches at two spatial scales. Community Ecol. 14, 219–230 (2013).
    Google Scholar 
    Molnár, Z. S, Biró, M., Bartha, S. & Fekete, G. in Eurasian Steppes. Ecological Problems and Livelihoods in a Changing World (eds Werger, M. J. A. & van Staalduinen, M. A.) Ch. 7 (Springer, 2012).Mezősi, G. in The Physical Geography of Hungary. Geography of the Physical Environment (ed. Mezősi, G) Ch. 11 (Springer, 2017).Biró, M., Bölöni, J. & Molnár, Z. Use of long-term data to evaluate loss and endangerment status of Natura 2000 habitats and effects of protected areas. Conserv. Biol. 32, 660–671 (2018).PubMed 

    Google Scholar 
    Pe’er, G. et al. Action needed for the EU Common Agricultural Policy to address sustainability challenges. People Nat. 2, 305–316 (2020).
    Google Scholar 
    Benton, T. G., Bieg, C., Harwatt, H., Pudasaini, R. & Wellesley, L. Food system impacts on biodiversity loss. Three levers for food system transformation in support of nature. Chatham House, the Royal Institute of International Affairs. ISBN: 978 1 78413 433 4 (2021).Kuemmerle, T. et al. Cross-border comparison of post-socialist farmland abandonment in the Carpathians. Ecosystems 11, 614 (2008).
    Google Scholar 
    Feranec, J. et al. Inventory of major landscape changes in the Czech Republic, Hungary, Romania and Slovak Republic 1970s – 1990s. Int. J. Appl. Earth Observ. Geoinf. 2, 129–139 (2000).
    Google Scholar 
    Pyšek, P. et al. Scientists’ warning on invasive alien species. Biol. Rev. 95, 1511–1534 (2020).PubMed 

    Google Scholar 
    Csákvári, E. et al. Conservation biology research priorities for 2050: a Central-Eastern European perspective. Biol. Conserv. 264, 109396 (2021).
    Google Scholar 
    Molnár, Z. S., Bölöni, J. & Horváth, F. Threatening factors encountered: actual endangerment of the Hungarian (semi-)natural habitats. Acta Bot. Hung. 50, 199–217 (2008).
    Google Scholar 
    Király, G., Molnár, ZS., Bölöni, J., Csiky, J. & Vojtkó, A. Magyarország földrajzi kistájainak növényzete (in Hungarian). MTA ÖBKI, Vácrátót, 248 (2008).Botta-Dukát, Z. Invasion of alien species to Hungarian (semi-)natural habitats. Acta Bot. Hung. 50, 219–227 (2008).
    Google Scholar 
    Csákvári, E., Bede-Fazekas, Á., Horváth, F., Molnár, Z. & Halassy, M. Do environmental predictors affect the regeneration capacity of sandy habitats? A country-wide survey from Hungary. Glob. Ecol. Conserv. 27, e01547 (2021).
    Google Scholar 
    Somodi, I. et al. Implementation and application of multiple potential natural vegetation models–a case study of Hungary. J. Veg. Sci. 28, 1260–1269 (2017).
    Google Scholar 
    Bölöni, J., Molnár, Zs. & Kun, A. (Eds.), Magyarország élőhelyei. A hazai vegetációtípusok leírása és határozója (in Hungarian) (Habitats – Description and Identification of Vegetation Types of Hungary, ÁNÉR 2011). MTA Ökológiai és Botanikai Kutatóintézet, Vácrátót, pp. 439. ISBN 978-963-8391-51 (2011).Choi, Y. D. et al. Ecological restoration for future sustainability in a changing environment. Ecoscience 15, 53–64 (2008).CAS 

    Google Scholar 
    Valkó, O. et al. Abandonment of croplands: problem or chance for grassland restoration? Case studies from Hungary. Ecosyst. Health Sustain. 2, e01208 (2016).
    Google Scholar 
    Csecserits, A. et al. Tree plantations are hot-spots of plant invasion in a landscape with heterogeneous land-use. Agric. Ecosyst. Environ. 226, 88–98 (2016).
    Google Scholar 
    Pyšek P. & Richardson D. M. in Biological Invasions. Ecological Studies (Analysis and Synthesis) (ed. Nentwig, W) Ch. 7 (Springer, 2008).Reis, B. P. et al. The long-term effect of initial restoration intervention, landscape composition, and time on the progress of Pannonic sand grassland restoration. Landsc. Ecol. Eng. https://doi.org/10.1007/s11355-022-00512-y (2022).Article 

    Google Scholar 
    Ruprecht, E. Successfully recovered grassland: a promising example from Romanian old‐fields. Restor. Ecol. 14, 473–480 (2006).
    Google Scholar 
    Török, P. et al. Restoring grassland biodiversity: sowing low-diversity seed mixtures can lead to rapid favourable changes. Biol. Conserv. 143, 3 (2010).
    Google Scholar 
    Török, P., Vida, E., Deák, B., Lengyel, S. & Tóthmérész, B. Grassland restoration on former croplands in Europe: an assessment of applicability of techniques and costs. Biodivers. Conserv. 20, 2311–2332 (2011).
    Google Scholar 
    Prach, K., Jongepierová, I., Řehounková, K. & Fajmon, K. Restoration of grasslands on ex-arable land using regional and commercial seed mixtures and spontaneous succession: successional trajectories and changes in species richness. Agric. Ecosyst. Environ. 182, 131–136 (2014).
    Google Scholar 
    Prach, K., Chenoweth, J. & del Moral, R. Spontaneous and assisted restoration of vegetation on the bottom of a former water reservoir, the Elwha River, Olympic National Park, WA, USA. Restor. Ecol. 27, 592–599 (2019).
    Google Scholar 
    Török, P., Helm, A., Kiehl, K., Buisson, E. & Valkó, O. Beyond the species pool: modification of species dispersal, establishment, and assembly by habitat restoration. Restor. Ecol. 26, S65–S72 (2018).
    Google Scholar 
    Török, P., Bullock James M, J. M., Jiménez‐Alfaro, B. & Sonkoly, J. The importance of dispersal and species establishment in vegetation dynamics and resilience. J. Veg. Sci. 31, 935–942 (2020).
    Google Scholar 
    Saura, S., Bodin, Ö. & Fortin, M. J. Stepping stones are crucial for species’ long-distance dispersal and range expansion through habitat networks. J. Appl. Ecol. 51, 171–182 (2014).
    Google Scholar 
    Kirmer, A., Baasch, A. & Tischew, S. Sowing of low and high diversity seed mixtures in ecological restoration of surface mined-land. Appl. Veg. Sci. 15, 198–207 (2012).
    Google Scholar 
    Llumiquinga, Y. B. et al. Long-term results of initial seeding, mowing and carbon amendment on the restoration of Pannonian sand grassland on old fields. Tuxenia 41, 361–379 (2021).
    Google Scholar 
    Edwards, A. R. et al. Hay strewing, brush harvesting of seed and soil disturbance as tools for the enhancement of botanical diversity in grasslands. Biol. Conserv. 134, 372–382 (2007).
    Google Scholar 
    Veldman, J. W. et al. Where tree planting and forest expansion are bad for biodiversity and ecosystem services. BioScience 65, 1011–1018 (2015).
    Google Scholar 
    Bussion, E., Archibald, S., Fidelis, A. & Sudling, K. N. Ancient grasslands guide ambitious goals in grassland restoration. Science 377, 594–598 (2022).
    Google Scholar 
    Csecserits, A. et al. Regeneration of sandy old-field in the forest steppe region of Hungary. Plant Biosyst. 145, 715–726 (2011).
    Google Scholar 
    Szitár, K. et al. Az országos zöldinfrastruktúrahálózat kijelölésének módszertana többszempontú állapotértékelés alapján. (in Hungarian) (Methodology for designating the national green infrastructure network based on multi-criteria assessment). Term.észetvédelmi K.özlemények 27, 145–157 (2021).
    Google Scholar 
    Szalai, S., Szinell, C. S. & Zoboki, J. Early warning systems for drought preparedness and drought management. In Proc. Expert Group Meeting (eds Wilhite, D. A., Sivakumar, M. V. K. & Wood, D. A.) (World Meteorological Organization, 2000).Szilassi, P. et al. The link between landscape pattern and vegetation naturalness on a regional scale. Ecol. Indic. 81, 252–259 (2017).
    Google Scholar 
    Demeter, I., Makádi, M., Végső, B., Aranyos, T. J. & Posta, K. The effect of recycled plant residues on the microbial activity of typical sandy soil of the Nyírség region. In Abstract Book, 18th Alps-Adria Scientific Workshop https://doi.org/10.34116/NTI.2019.AA.13 (2019).Borhidi, A. Social behaviour types, the naturalness and relative ecological indicator values of the higher plants in the Hungarian Flora. Acta Bot. Hung. 39, 97–181 (1995).
    Google Scholar 
    Horváth, F. et al. Flóra adatbázis 1.2. Taxonlista és attribútum-állomány (Flora database 1.2. Taxon list and attribute file). MTA Ökológiai és Botanikai Kutatóintézet, Vácrátót, ISBN 9638391197 (1995).Király, G. Új Magyar Füvészkönyv. Magyarország hajtásos növényei (New Herbal Guide to the Hungarian Flora). Aggteleki Nemzeti Park Igazgatóság, Jósvafő, Hungary, 628p. (2009).Máté, A. 6260 pannon homoki gyepek. In: Haraszthy, L. (Eds.), Natura 2000 fajok és élőhelyek Magyarországon. (in Hungarian) Pro Vértes Közalapítvány, Csákvár, Hungary, pp. 817-823. ISBN: 9789630888530 (2014).Molnár, Z. S. et al. Magyarországi Élőhelytérképezési Adatbázisának (MÉTA) térképezési módszertani és Adatlapkitöltési Útmutatója (AL-KÚ) 3.3 Kézirat, (Guide on the methods of MÉTA and on the completion of the MÉTA datasheets). MTA ÖBKI, Vácrátót, Hungary, 54 pp. (2003).Molnár, Z. S. et al. A grid-based, satellite-image supported multi-attributed vegetation mapping method (MÉTA). Folia Geobotanica 42, 225–247 (2007).
    Google Scholar 
    Horváth, F. et al. Fact sheet of the MÉTA database 1.2. Acta Bot. Hung. 50, 11–34 (2008).
    Google Scholar 
    Bölöni, J., Kun, A. & Molnár, Z. S. Élőhely-ismereti Útmutató (Habitat guide). MTA ÖBKI, Vácrátót, Hungary (2003).European Environment Agency. Corine Land Cover 2006 seamless vector data (Version 17). https://www.eea.europa.eu/data-and-maps/data/clc-2006-vector-data-version-3 (2013).European Environment Agency. CLC2006 Technical Guidelines. Report No. 17/2007, ISNN 1725-2237 (2017).ESRI ArcGIS Vers. 10.2. (Environmental System Research Institute Inc., 2013).Pásztor, L. et al. Compilation of novel and renewed, goal oriented digital soil maps using geostatistical and data mining tools. Hungarian Geogr. Bull. 64, 49–64 (2015).
    Google Scholar 
    Hijmans, R. J. raster: geographic data analysis and modeling. R package version 2.4-20, https://cran.r-project.org/web/packages/raster/index.html (2015).R Core Team. R: a language and environment for statistical computing. R Foundation for Statistical Computing. https://www.r-project.org/ (2019).USGS. Shuttle Radar Topography Mission, 3 Arc Second scene SRTM_u03_n045e016-SRTM_ff03_n048e022, Unfilled Unfinished 2.0, Global Land Cover Facility, February 2000. College Park, MD, USA, University of Maryland (2004).SRTM. SRTM Mission Summary. URL: lta.cr.usgs.gov/srtm/mission_summary (2015). [Last accesed: 2016.04.22.].Szalai, S. et al. Climate of the Greater Carpathian Region. Final Technical Report. http://www.carpatclim-eu.org/ (2013).Liaw, A. & Wiener, M. Classification and regression by randomForest. R. N. 2, 18–22, https://CRAN.R-project.org/doc/Rnews/ (2002).
    Google Scholar 
    Breiman, L., Friedman, J., Stone, C. J. & Olshen, R. A. Classification and Regression Trees (CRC Press, 1984).Sarica, A., Cerasa, A. & Quattrone, A. Random Forest algorithm for the classification of neuroimaging data in Alzheimer’s disease: a systematic review. Front. Aging Neurosci. 6, 329 (2017).
    Google Scholar 
    Hothorn, T., Hornik, K. & Zeileis, A. Unbiased recursive partitioning: a conditional inference framework. J. Comput. Graph Stat. 15, 651–674 (2006).
    Google Scholar 
    Pebesma, E. Simple features for R: standardized support for spatial vector. Data. R. J. 10, 439–446 (2018).
    Google Scholar 
    Bivand, R. S., Pebesma, E. & Gomez-Rubio, V. Applied Spatial Data Analysis with R 2nd ed. (Springer, 2013).Bivand, R. S. & Wong, D. W. S. Comparing implementations of global and local indicators of spatial association. TEST 27, 716–748 (2018).
    Google Scholar 
    Bölöni, J., Molnár, Z. S., Horváth, F. & Illyés, E. Naturalness-based habitat quality of the Hungarian (semi-)natural habitats. Acta Bot. Hung. 50, 149–159 (2008).
    Google Scholar 
    Czúcz, B., Molnár, Z. S., Horváth, F. & Botta-Dukát, Z. The natural capital index of Hungary. Acta Bot. Hung. 50, 161–177 (2008).
    Google Scholar  More

  • in

    Towards a unified theory of plant photosynthesis and hydraulics

    Raschke, K., Monteith, J. L. & Weatherley, P. E. How stomata resolve the dilemma of opposing priorities. Phil. Trans. R. Soc. Lond. B 273, 551–560 (1976).Article 
    CAS 

    Google Scholar 
    Brodribb, T. J. & Cochard, H. Hydraulic failure defines the recovery and point of death in water-stressed conifers. Plant Physiol. 149, 575–584 (2009).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Brodribb, T. J., Bowman, D. J. M. S., Nichols, S., Delzon, S. & Burlett, R. Xylem function and growth rate interact to determine recovery rates after exposure to extreme water deficit. New Phytol. 188, 533–542 (2010).Article 
    PubMed 

    Google Scholar 
    Choat, B. et al. Triggers of tree mortality under drought. Nature 558, 531–539 (2018).Article 
    CAS 
    PubMed 

    Google Scholar 
    Keeling, R. F. et al. Atmospheric evidence for a global secular increase in carbon isotopic discrimination of land photosynthesis. Proc. Natl Acad. Sci. USA https://doi.org/10.1073/pnas.1619240114 (2017).Guerrieri, R. et al. Disentangling the role of photosynthesis and stomatal conductance on rising forest water-use efficiency. Proc. Natl Acad. Sci. USA 116, 16909–16914 (2019).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Grossiord, C. et al. Plant responses to rising vapor pressure deficit. New Phytol. 226, 1550–1566 (2020).Article 
    PubMed 

    Google Scholar 
    McDowell, N. G. & Allen, C. D. Darcy’s law predicts widespread forest mortality under climate warming. Nat. Clim. Change 5, 669–672 (2015).Article 

    Google Scholar 
    Brienen, R. J. W. et al. Long-term decline of the Amazon carbon sink. Nature 519, 344–348 (2015).Article 
    CAS 
    PubMed 

    Google Scholar 
    McDowell, N. G. et al. Pervasive shifts in forest dynamics in a changing world. Science 368, eaaz9463 (2020).Article 
    CAS 
    PubMed 

    Google Scholar 
    Novick, K. A. et al. The increasing importance of atmospheric demand for ecosystem water and carbon fluxes. Nat. Clim. Change 6, 1023–1027 (2016).Article 
    CAS 

    Google Scholar 
    Damour, G., Simonneau, T., Cochard, H. & Urban, L. An overview of models of stomatal conductance at the leaf level. Plant Cell Environ. 33, 1419–1438 (2010).PubMed 

    Google Scholar 
    Wang, Y., Sperry, J. S., Anderegg, W. R. L., Venturas, M. D. & Trugman, A. T. A theoretical and empirical assessment of stomatal optimization modeling. New Phytol. 227, 311–325 (2020).Article 
    CAS 
    PubMed 

    Google Scholar 
    Anderegg, W. R. L. et al. Woody plants optimise stomatal behaviour relative to hydraulic risk. Ecol. Lett. 21, 968–977 (2018).Article 
    PubMed 

    Google Scholar 
    Venturas, M. D. et al. A stomatal control model based on optimization of carbon gain versus hydraulic risk predicts aspen sapling responses to drought. New Phytol. 220, 836–850 (2018).Article 
    CAS 
    PubMed 

    Google Scholar 
    Sabot, M. E. B. et al. Plant profit maximization improves predictions of European forest responses to drought. New Phytol. 226, 1638–1655 (2020).Article 
    PubMed 

    Google Scholar 
    Eller, C. B. et al. Stomatal optimization based on xylem hydraulics (SOX) improves land surface model simulation of vegetation responses to climate. New Phytol. 226, 1622–1637 (2020).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Hickler, T., Prentice, I. C., Smith, B., Sykes, M. T. & Zaehle, S. Implementing plant hydraulic architecture within the LPJ Dynamic Global Vegetation Model. Glob. Ecol. Biogeogr. 15, 567–577 (2006).Article 

    Google Scholar 
    Bonan, G. B., Williams, M., Fisher, R. A. & Oleson, K. W. Modeling stomatal conductance in the earth system: linking leaf water-use efficiency and water transport along the soil–plant–atmosphere continuum. Geosci. Model Dev. 7, 2193–2222 (2014).Article 

    Google Scholar 
    Christoffersen, B. O. et al. Linking hydraulic traits to tropical forest function in a size-structured and trait-driven model (TFS v.1-Hydro). Geosci. Model Dev. 9, 4227–4255 (2016).Article 

    Google Scholar 
    Kennedy, D. et al. Implementing plant hydraulics in the Community Land Model, Version 5. J. Adv. Model. Earth Syst. 11, 485–513 (2019).Article 

    Google Scholar 
    Cowan, I. R. & Farquhar, G. D. Stomatal function in relation to leaf metabolism and environment. Symp. Soc. Exp. Biol. 31, 471–505 (1977).CAS 
    PubMed 

    Google Scholar 
    Wolf, A., Anderegg, W. R. L. & Pacala, S. W. Optimal stomatal behavior with competition for water and risk of hydraulic impairment. Proc. Natl Acad. Sci. USA 113, E7222–E7230 (2016).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Sperry, J. S. et al. Predicting stomatal responses to the environment from the optimization of photosynthetic gain and hydraulic cost. Plant Cell Environ. 40, 816–830 (2017).Article 
    CAS 
    PubMed 

    Google Scholar 
    Bartlett, M. K., Detto, M. & Pacala, S. W. Predicting shifts in the functional composition of tropical forests under increased drought and CO2 from trade-offs among plant hydraulic traits. Ecol. Lett. 22, 67–77 (2019).Article 
    PubMed 

    Google Scholar 
    Prentice, I. C., Dong, N., Gleason, S. M., Maire, V. & Wright, I. J. Balancing the costs of carbon gain and water transport: testing a new theoretical framework for plant functional ecology. Ecol. Lett. 17, 82–91 (2014).Article 
    PubMed 

    Google Scholar 
    Wright, I. J., Reich, P. B. & Westoby, M. Least‐cost input mixtures of water and nitrogen for photosynthesis. Am. Nat.161, 98–111 (2003).Article 
    PubMed 

    Google Scholar 
    Wang, H. et al. Towards a universal model for carbon dioxide uptake by plants. Nat. Plants 3, 734–741 (2017).Article 
    CAS 
    PubMed 

    Google Scholar 
    Maire, V. et al. The coordination of leaf photosynthesis links C and N fluxes in C3 plant species. PLoS ONE 7, e38345 (2012).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Stocker, B. D. et al. Quantifying soil moisture impacts on light use efficiency across biomes. New Phytol. 218, 1430–1449 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Stocker, B. D. et al. P-model v1.0: an optimality-based light use efficiency model for simulating ecosystem gross primary production. Geosci. Model Dev. 13, 1545–1581 (2020).Article 

    Google Scholar 
    Lavergne, A. et al. Historical changes in the stomatal limitation of photosynthesis: empirical support for an optimality principle. New Phytol. 225, 2484–2497 (2020).Article 
    CAS 
    PubMed 

    Google Scholar 
    Sperry, J. S. & Love, D. M. What plant hydraulics can tell us about responses to climate-change droughts. New Phytol. 207, 14–27 (2015).Article 
    CAS 
    PubMed 

    Google Scholar 
    Farquhar, G. D., von Caemmerer, S. & Berry, J. A. A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species. Planta 149, 78–90 (1980).Article 
    CAS 
    PubMed 

    Google Scholar 
    Chen, J.-L., Reynolds, J. F., Harley, P. C. & Tenhunen, J. D. Coordination theory of leaf nitrogen distribution in a canopy. Oecologia 93, 63–69 (1993).Article 
    PubMed 

    Google Scholar 
    Buckley, T. N., John, G. P., Scoffoni, C. & Sack, L. How does leaf anatomy influence water transport outside the xylem? Plant Physiol. 168, 1616–1635 (2015).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Scoffoni, C. et al. Outside-xylem vulnerability, not xylem embolism, controls leaf hydraulic decline during dehydration. Plant Physiol. 173, 1197–1210 (2017).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Carminati, A. & Javaux, M. Soil rather than xylem vulnerability controls stomatal response to drought. Trends Plant Sci. 25, 868–880 (2020).Article 
    CAS 
    PubMed 

    Google Scholar 
    Klein, T. et al. Xylem embolism refilling and resilience against drought-induced mortality in woody plants: processes and trade-offs. Ecol. Res. 33, 839–855 (2018).CAS 

    Google Scholar 
    Rodriguez-Dominguez, C. M. & Brodribb, T. J. Declining root water transport drives stomatal closure in olive under moderate water stress. New Phytol. 225, 126–134 (2020).Article 
    CAS 
    PubMed 

    Google Scholar 
    Sack, L. & Holbrook, N. M. Leaf hydraulics. Annu. Rev. Plant Biol. 57, 361–381 (2006).Article 
    CAS 
    PubMed 

    Google Scholar 
    Bourbia, I., Pritzkow, C. & Brodribb, T. J. Herb and conifer roots show similar high sensitivity to water deficit. Plant Physiol. 186, 1908–1918 (2021).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Zhou, S., Duursma, R. A., Medlyn, B. E., Kelly, J. W. G. & Prentice, I. C. How should we model plant responses to drought? An analysis of stomatal and non-stomatal responses to water stress. Agric. Meteorol. 182–183, 204–214 (2013).Article 

    Google Scholar 
    Kanechi, M., Uchida, N., Yasuda, T. & Yamaguchi, T. Non-stomatal inhibition associated with inactivation of rubisco in dehydrated coffee leaves under unshaded and shaded conditions. Plant Cell Physiol. 37, 455–460 (1996).Article 
    CAS 

    Google Scholar 
    Salmon, Y. et al. Leaf carbon and water status control stomatal and nonstomatal limitations of photosynthesis in trees. New Phytol. 226, 690–703 (2020).Article 
    CAS 
    PubMed 

    Google Scholar 
    Dong, N. et al. Components of leaf-trait variation along environmental gradients. New Phytol. 228, 82–94 (2020).Article 
    CAS 
    PubMed 

    Google Scholar 
    Martínez‐Vilalta, J., Poyatos, R., Aguadé, D., Retana, J. & Mencuccini, M. A new look at water transport regulation in plants. New Phytol. 204, 105–115 (2014).Article 
    PubMed 

    Google Scholar 
    Bartlett, M. K., Klein, T., Jansen, S., Choat, B. & Sack, L. The correlations and sequence of plant stomatal, hydraulic, and wilting responses to drought. Proc. Natl Acad. Sci. USA 113, 13098–13103 (2016).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Brodribb, T. J., Holbrook, N. M., Edwards, E. J. & Gutiérrez, M. V. Relations between stomatal closure, leaf turgor and xylem vulnerability in eight tropical dry forest trees. Plant Cell Environ. 26, 443–450 (2003).Article 

    Google Scholar 
    Martin‐StPaul, N., Delzon, S. & Cochard, H. Plant resistance to drought depends on timely stomatal closure. Ecol. Lett. 20, 1437–1447 (2017).Article 
    PubMed 

    Google Scholar 
    Skelton, R. P. et al. Low vulnerability to xylem embolism in leaves and stems of North American oaks. Plant Physiol. 177, 1066–1077 (2018).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Choat, B. et al. Global convergence in the vulnerability of forests to drought. Nature 491, 752–755 (2012).Article 
    CAS 
    PubMed 

    Google Scholar 
    Dewar, R. et al. New insights into the covariation of stomatal, mesophyll and hydraulic conductances from optimization models incorporating nonstomatal limitations to photosynthesis. New Phytol. 217, 571–585 (2018).Article 
    CAS 
    PubMed 

    Google Scholar 
    Hölttä, T., Lintunen, A., Chan, T., Mäkelä, A. & Nikinmaa, E. A steady-state stomatal model of balanced leaf gas exchange, hydraulics and maximal source–sink flux. Tree Physiol. 37, 851–868 (2017).Article 
    PubMed 

    Google Scholar 
    Pivovaroff, A. L., Sack, L. & Santiago, L. S. Coordination of stem and leaf hydraulic conductance in southern California shrubs: a test of the hydraulic segmentation hypothesis. New Phytol. 203, 842–850 (2014).Article 
    PubMed 

    Google Scholar 
    Boyer, J. S., Wong, S. C. & Farquhar, G. D. CO2 and water vapor exchange across leaf cuticle (epidermis) at various water potentials. Plant Physiol. 114, 185–191 (1997).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Deans, R. M., Brodribb, T. J., Busch, F. A. & Farquhar, G. D. Optimization can provide the fundamental link between leaf photosynthesis, gas exchange and water relations. Nat. Plants 6, 1116–1125 (2020).Article 
    CAS 
    PubMed 

    Google Scholar 
    Zhou, S.-X., Medlyn, B. E. & Prentice, I. C. Long-term water stress leads to acclimation of drought sensitivity of photosynthetic capacity in xeric but not riparian Eucalyptus species. Ann. Bot. 117, 133–144 (2016).Article 
    CAS 
    PubMed 

    Google Scholar 
    Rungwattana, K. et al. Trait evolution in tropical rubber (Hevea brasiliensis) trees is related to dry season intensity. Funct. Ecol. 32, 2638–2651 (2018).Article 

    Google Scholar 
    Dybzinski, R., Farrior, C., Wolf, A., Reich, P. B. & Pacala, S. W. Evolutionarily stable strategy carbon allocation to foliage, wood, and fine roots in trees competing for light and nitrogen: an analytically tractable, individual-based model and quantitative comparisons to data. Am. Nat. 177, 153–166 (2011).Article 
    PubMed 

    Google Scholar 
    Hikosaka, K. & Anten, N. P. R. An evolutionary game of leaf dynamics and its consequences for canopy structure. Funct. Ecol. 26, 1024–1032 (2012).Article 

    Google Scholar 
    Franklin, O. et al. Organizing principles for vegetation dynamics. Nat. Plants 6, 444–453 (2020).Article 
    PubMed 

    Google Scholar 
    Le Quéré, C. et al. Global carbon budget 2017. Earth Syst. Sci. Data 10, 405–448 (2018).Article 

    Google Scholar 
    Jasechko, S. et al. Terrestrial water fluxes dominated by transpiration. Nature 496, 347–350 (2013).Article 
    CAS 
    PubMed 

    Google Scholar 
    Xu, X., Medvigy, D., Powers, J. S., Becknell, J. M. & Guan, K. Diversity in plant hydraulic traits explains seasonal and inter-annual variations of vegetation dynamics in seasonally dry tropical forests. New Phytol. 212, 80–95 (2016).Article 
    PubMed 

    Google Scholar 
    Wang, H. et al. Acclimation of leaf respiration consistent with optimal photosynthetic capacity. Glob. Change Biol. 26, 2573–2583 (2020).Article 

    Google Scholar 
    Papastefanou, P. et al. A dynamic model for strategies and dynamics of plant water-potential regulation under drought conditions. Front. Plant Sci. 11, 373 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Grieu, P., Guehl, J. M. & Aussenac, G. The effects of soil and atmospheric drought on photosynthesis and stomatal control of gas exchange in three coniferous species. Physiol. Plant. 73, 97–104 (1988).Article 

    Google Scholar 
    Liu, F., Andersen, M. N., Jacobsen, S.-E. & Jensen, C. R. Stomatal control and water use efficiency of soybean (Glycine max L. Merr.) during progressive soil drying. Environ. Exp. Bot. 54, 33–40 (2005).Article 
    CAS 

    Google Scholar 
    Tezara, W., Driscoll, S. & Lawlor, D. W. Partitioning of photosynthetic electron flow between CO2 assimilation and O2 reduction in sunflower plants under water deficit. Photosynthetica 46, 127–134 (2008).Article 
    CAS 

    Google Scholar 
    Liu, C.-C. et al. Influence of drought intensity on the response of six woody karst species subjected to successive cycles of drought and rewatering. Physiol. Plant. 139, 39–54 (2010).Article 
    CAS 
    PubMed 

    Google Scholar 
    Posch, S. & Bennett, L. T. Photosynthesis, photochemistry and antioxidative defence in response to two drought severities and with re-watering in Allocasuarina luehmannii. Plant Biol. 11, 83–93 (2009).Article 
    CAS 
    PubMed 

    Google Scholar 
    Jiang, M., Kelly, J. W. G., Atwell, B. J., Tissue, D. T. & Medlyn, B. E. Drought by CO2 interactions in trees: a test of the water savings mechanism. New Phytol. 230, 1421–1434 (2021).Article 
    CAS 
    PubMed 

    Google Scholar 
    Ennajeh, M., Tounekti, T., Vadel, A. M., Khemira, H. & Cochard, H. Water relations and drought-induced embolism in olive (Olea europaea) varieties ‘Meski’ and ‘Chemlali’ during severe drought. Tree Physiol. 28, 971–976 (2008).Article 
    PubMed 

    Google Scholar 
    Peguero-Pina, J. J., Sancho-Knapik, D., Morales, F., Flexas, J. & Gil-Pelegrín, E. Differential photosynthetic performance and photoprotection mechanisms of three Mediterranean evergreen oaks under severe drought stress. Funct. Plant Biol. 36, 453–462 (2009).Article 
    PubMed 

    Google Scholar 
    Liu, C.-C. et al. Exploitation of patchy soil water resources by the clonal vine Ficus tikoua in karst habitats of southwestern China. Acta Physiol. Plant. 33, 93–102 (2011).Article 

    Google Scholar 
    Leuning, R. A critical appraisal of a combined stomatal-photosynthesis model for C3 plants. Plant Cell Environ. 18, 339–355 (1995).Article 
    CAS 

    Google Scholar 
    Medlyn, B. E. et al. Reconciling the optimal and empirical approaches to modelling stomatal conductance. Glob. Change Biol. 17, 2134–2144 (2011).Article 

    Google Scholar 
    Brodribb, T. et al. Linking xylem network failure with leaf tissue death. New Phytol. 232, 68–79 (2021).Article 
    PubMed 

    Google Scholar 
    Klein, T. The variability of stomatal sensitivity to leaf water potential across tree species indicates a continuum between isohydric and anisohydric behaviours. Funct. Ecol. 28, 1313–1320 (2014).Article 

    Google Scholar  More

  • in

    The point of no return for species facing heatwaves

    Seneviratne, S. I. et al. in Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (eds Masson-Delmotte, V. et al.) 1513–1766 (Cambridge Univ. Press, 2021).
    Google Scholar 
    Hesketh, A. V. & Harley, C. D. G. Glob. Change Biol. https://doi.org/10.1111/gcb.16390 (2022).Article 

    Google Scholar 
    Jørgensen, L. B., Ørsted, M., Malte, H., Wang, T. & Overgaard, J. Nature https://doi.org/10.1038/s41586-022-05334-4 (2022).Article 

    Google Scholar 
    Sunday, J. M., Bates, A. E. & Dulvy, N. K. Nature Clim. Change 2, 686–690 (2012).Article 

    Google Scholar 
    Cossins, A. R. & Bowler, K. Temperature Biology of Animals (Chapman & Hall, 1987).
    Google Scholar 
    Dell, A. I., Pawar, S. & Savage, V. M. Proc. Natl Acad. Sci. USA 108, 10591–10596 (2011).Article 
    PubMed 

    Google Scholar 
    Dillon, M. E. et al. Integr. Comp. Biol. 56, 14–30 (2016).Article 
    PubMed 

    Google Scholar 
    Stillman, J. H. Physiology 34, 86–100 (2019).Article 
    PubMed 

    Google Scholar 
    MacMillan, H. A. J. Exp. Biol. 222, jeb191593 (2019).Article 
    PubMed 

    Google Scholar 
    Kingsolver, J. G. & Umbanhowar, J. J. Exp. Biol. 221, jeb167858 (2018).Article 
    PubMed 

    Google Scholar  More

  • in

    Temporal change in plant communities and its relationship to soil salinity and microtopography on the Caspian Sea coast

    Shomurodov, K. F. & Adilov, B. A. Current state of the flora of Vozrozhdeniya Island (Uzbekistan). Arid Ecosyst. 9, 97–103 (2019).
    Google Scholar 
    Adilov, B. et al. Transformation of vegetative cover on the Ustyurt Plateau of Central Asia as a consequence of the Aral Sea shrinkage. J. Arid Land 13, 71–87 (2020).
    Google Scholar 
    Kuz’mina, Z. V. & Treshkin, S. E. Soil salinization and dynamics of Tugai vegetation in the southeastern Caspian Sea region and in the Aral Sea coastal region. Eurasian Soil Sci. 30, 642–649 (1997).
    Google Scholar 
    Kuz’mina, Z. V., Shinkarenko, S. S. & Solodovnikov, D. A. Main tendencies in the dynamics of floodplain ecosystems and landscapes of the lower reaches of the Syr Darya river under modern changing conditions. Arid Ecosyst. 9, 226–236 (2019).
    Google Scholar 
    Dimeyeva, L. A. Phytogeography of the northeastern coast of the Caspian Sea: Native flora and recent colonizations. J. Arid Land 5, 439–451 (2013).
    Google Scholar 
    Goryaev, I. A. & Korablev, A. P. Halophytic vegetation in the west caspian lowland. Contemp. Probl. Ecol. 13, 514–521 (2020).
    Google Scholar 
    Novikova, N. M., Volkova, N. A., Ulanova, S. S. & Chemidov, M. M. Change in vegetation on meliorated solonetcic soils of the Peri-Yergenian plain over 10 years (Republic of Kalmykia). Arid Ecosyst. 10, 194–202 (2020).
    Google Scholar 
    Ravanbakhsh, M., Amini, T. & Hosseini, S. M. N. Plant species diversity among ecological species groups in the Caspian Sea coastal sand dune; Case study: Guilan Province, North of Iran. Biodiversitas 16, 16–21 (2015).
    Google Scholar 
    Yan, S., Mu, G., Xu, Y. & Zhao, Z. Quarternary environmental evolution of the Lop Nur region, China. Dili Xuebao/Acta Geogr. Sin. 53, 332–340 (1998).
    Google Scholar 
    Hao, H., Ferguson, D. K., Chang, H. & Li, C. S. Vegetation and climate of the Lop Nur area, China, during the past 7 million years. Clim. Change 113, 323–338 (2012).ADS 

    Google Scholar 
    Li, C. et al. Growth and sustainability of Suaeda salsa in the Lop Nur, China. J. Arid Land 10, 429–440 (2018).
    Google Scholar 
    Barrett, G. Vegetation communities on the shores of a salt lake in semi-arid Western Australia. J. Arid Environ. 67, 77–89 (2006).ADS 

    Google Scholar 
    Neffar, S., Chenchouni, H. & Si Bachir, A. Floristic composition and analysis of spontaneous vegetation of Sabkha Djendli in north-east Algeria. Plant Biosyst. 150, 396–403 (2016).
    Google Scholar 
    Yanina, T. A. The Ponto-Caspian region: Environmental consequences of climate change during the Late Pleistocene. Quat. Int. 345, 88–99 (2014).
    Google Scholar 
    Rychagov, G. I. Pleistocene History of the Caspian Sea (Moscow State University, 1977).
    Google Scholar 
    Rychagov, G. I. The level mode of the Caspian Sea during the last 10000. Vestn. Mosk. Univ. Seriya 5 Geogr. 2, 38–49 (1993).
    Google Scholar 
    Kroonenberg, S. B. et al. Solar-forced 2600 BP and Little Ice Age highstands of the Caspian Sea. Quat. Int. 173–174, 137–143 (2007).
    Google Scholar 
    Kasimov, N. S., Lychagin, M. Y. & Kroonenberg, S. B. Geochemical indication of cyclic fluctuations of the caspian sea level. Vestn. Mosk. Univ. Seriya Geogr. 2, 72–77 (2011).
    Google Scholar 
    Kroonenberg, S. B., Badyukova, E. N., Storms, J. E. A., Ignatov, E. I. & Kasimov, N. S. A full sea-level cycle in 65 years: Barrier dynamics along Caspian shores. Sediment. Geol. 134, 257–274 (2000).ADS 

    Google Scholar 
    Bolikhovskaya, N. & Kasimov, N. The evolution of climate and landscapes of the Lower Volga region during the Holocene. Geogr. Environ. Sustain. 3, 78–97 (2010).
    Google Scholar 
    Magomedov, M.M.-R. & Gasanov, S. M. Features of soil changes under crowns of the shrubberies tamarisk (Tamarix meyeri boiss, T. ramosissima zedeb). South Russ. Ecol. Dev. 6, 12–21 (2014).
    Google Scholar 
    Du, N. et al. Facilitation or competition? The effects of the shrub species tamarix chinensis on herbaceous communities are dependent on the successional stage in an impacted coastal wetland of North China. Wetlands 37, 899–911 (2017).
    Google Scholar 
    Jiang, L., Jiapaer, G., Bao, A., Guo, H. & Ndayisaba, F. Vegetation dynamics and responses to climate change and human activities in Central Asia. Sci. Total Environ. 599–600, 967–980 (2017).ADS 
    PubMed 

    Google Scholar 
    Burke, I. C. et al. Plant–soil interactions in temperate grasslands. In Plant-Induced Soil Changes: Processes and Feedbacks (ed. van Breemen, N.) 121–143 (Springer, 1998). https://doi.org/10.1007/978-94-017-2691-7_7.Chapter 

    Google Scholar 
    Webb, C. O., Ackerly, D. D., McPeek, M. A. & Donoghue, M. J. Phylogenies and community ecology. Annu. Rev. Ecol. Syst. 33, 475–505 (2002).
    Google Scholar 
    Abaturov, B. D. Microdepression microrelief of Caspian Lowland and mechanisms of its formation. Arid. Ecosistemy 16, 31–45 (2010).
    Google Scholar 
    Sapanov, M. K. The results of soil water investigations in Djanybek stationary. Dokuchaev Soil Bull. 83, 22–40 (2016).
    Google Scholar 
    Bolshakov, A. F. & Bazykina, G. S. Natural biogeocenoses and the conditions of their existence. In Biogeocenotic Basis of the Reclamation of Semidesert in the Northern Caspain Lowland (ed. Rode, A. A.) 6–34 (Nauka, 1974).
    Google Scholar 
    Konyushkova, M. V., Nukhimovskaya, Y. D., Gasanova, Z. U. & Stepanova, N. Y. The temporal change in variability of soil salinity and phytodiversity at the coastal plain of the Caspian Sea. Arid Ecosyst. 10, 312–321 (2020).
    Google Scholar 
    Semenkov, I., Konyushkova, M., Heidari, A., Nukhimovskaya, Y. & Klink, G. Data on the soilscape and vegetation properties at the key site in the NW Caspian Sea coast, Russia. Data Br. 31, 105972 (2020).
    Google Scholar 
    Konyushkova, M. V. et al. Spatial and seasonal salt translocation in the young soils at the coastal plains of the Caspian Sea. Quat. Int. 590, 15–25 (2021).
    Google Scholar 
    Semenkov, I., Konyushkova, M., Heidari, A. & Nikolaev, E. Chemical differentiation of recent fine-textured soils on the Caspian Sea coast: A case study in Golestan (Iran) and Dagestan (Russia). Quat. Int. 590, 48–55 (2021).
    Google Scholar 
    Haghani, S. et al. An early ‘Little Ice Age’ brackish water invasion along the south coast of the Caspian Sea (sediment of Langarud wetland) and its wider impacts on environment and people. Holocene 26, 3–16 (2016).ADS 

    Google Scholar 
    Panin, G. N., Mamedov, R. M. & Mitrofanov, I. V. Present State of the Caspian Sea (Nauka, 2005).
    Google Scholar 
    Konyushkova, M. V. et al. The spatial differentiation of soil salinity at the young saline coastal plain of the Caspian region. Dokuchaev Soil Bull. 95, 41–57 (2018).
    Google Scholar 
    Cherepanov, S. K. Vascular Plants of Russia and Adjacent States (Within the Former USSR) (Cambridge University Press, 1995).
    Google Scholar 
    Takhtajan, A. Flowering Plants (Springer Science+Business Media B.V, 2009). https://doi.org/10.1007/978-1-4020-9609-9.Book 

    Google Scholar 
    Govaerts, R., Nic Lughadha, E., Black, N., Turner, R. & Paton, A. The World Checklist of Vascular Plants, a continuously updated resource for exploring global plant diversity. Sci. Data 8, 215 (2021).PubMed 
    PubMed Central 

    Google Scholar 
    POWO. Plants of the World Online. Facilitated by the Royal Botanic Gardens, Kew (Board of Trustees of the Royal Botanic Gardens, 2022).Chase, M. W. et al. An update of the Angiosperm Phylogeny Group classification for the orders and families of flowering plants: APG IV. Bot. J. Linn. Soc. 181, 1–20 (2016).
    Google Scholar 
    Qian, H. & Jin, Y. An updated megaphylogeny of plants, a tool for generating plant phylogenies and an analysis of phylogenetic community structure. J. Plant Ecol. 9, 233–239 (2016).
    Google Scholar 
    Clarke, K. R. & Warwick, R. M. A taxonomic distinctness index and its statistical properties. J. Appl. Ecol. 35, 523–531 (1998).
    Google Scholar 
    Semenkov, I. N. et al. The variability of soils and vegetation of hydrothermal fields in the Valley of Geysers at Kamchatka Peninsula. Sci. Rep. 11, 11077 (2021).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020).Wickham, H. & Henry, L. tidyr: Tidy Messy Data. R Packag. version 1.0.0 (2019).Goryaev, I. A. Regularities of distribution of halophytic vegetation on the Caspian Lowland. Bot. Zhurnal 104, 1072–1089 (2019).
    Google Scholar 
    Soltanmuradova, Z. I. & Teimurov, A. A. Taxonomic structure of the flora of the Primorskaya Lowland of the Republic of Dagestan. South Russ. Ecol. Dev. 3, 38 (2010).
    Google Scholar 
    Zörb, C., Sümer, A., Sungur, A., Flowers, T. J. & Özcan, H. Ranking of 11 coastal halophytes from salt marshes in northwest Turkey according their salt tolerance. Turk. J. Botany 37, 1125–1133 (2013).
    Google Scholar 
    Zhao, Y., Yu, H., Zhang, T. & Guo, J. Mycorrhizal colonization of chenopods and its influencing factors in different saline habitats, China. J. Arid Land 9, 143–152 (2017).
    Google Scholar 
    Podar, D. et al. Morphological, physiological and biochemical aspects of salt tolerance of halophyte Petrosimonia triandra grown in natural habitat. Physiol. Mol. Biol. Plants 25, 1335–1347 (2019).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Nayyar, H. & Gupta, D. Differential sensitivity of C3 and C4 plants to water deficit stress: Association with oxidative stress and antioxidants. Environ. Exp. Bot. 58, 106–113 (2006).CAS 

    Google Scholar 
    Way, D. A., Katul, G. G., Manzoni, S. & Vico, G. Increasing water use efficiency along the C3 to C4 evolutionary pathway: A stomatal optimization perspective. J. Exp. Bot. 65, 3683–3693 (2014).PubMed 
    PubMed Central 

    Google Scholar 
    Atia, A. et al. Ecophysiological aspects in 105 plants species of saline and arid environments in Tunisia. J. Arid Land 6, 762–770 (2014).
    Google Scholar 
    Pickett, S. T. A. Space-for-time substitution as an alternative to long-term studies. In Long-Term Studies in Ecology 110–135 (1989) https://doi.org/10.1007/978-1-4615-7358-6_5.Walker, L. R., Wardle, D. A., Bardgett, R. D. & Clarkson, B. D. The use of chronosequences in studies of ecological succession and soil development. J. Ecol. 98, 725–736 (2010).
    Google Scholar 
    Dimeeva, L. A. Dynamics of vegetation in deserts of Aral and Caspian regions. (2011).Yu, K. et al. Late quaternary environments in the Gobi Desert of Mongolia: Vegetation, hydrological, and palaeoclimate evolution. Palaeogeogr. Palaeoclimatol. Palaeoecol. 514, 77–91 (2019).
    Google Scholar 
    Cao, X., Tian, F., Dallmeyer, A. & Herzschuh, U. Northern Hemisphere biome changes ( >30°N) since 40 cal ka BP and their driving factors inferred from model-data comparisons. Quat. Sci. Rev. 220, 291–309 (2019).ADS 

    Google Scholar 
    Zhang, D. et al. Response of vegetation to Holocene evolution of westerlies in the Asian Central Arid Zone. Quat. Sci. Rev. 229, 106138 (2020).
    Google Scholar 
    Lu, K. Q. et al. A new approach to interpret vegetation and ecosystem changes through time by establishing a correlation between surface pollen and vegetation types in the eastern central Asian desert. Palaeogeogr. Palaeoclimatol. Palaeoecol. 551, 109762 (2020).
    Google Scholar 
    He, Q., Bertness, M. D. & Altieri, A. H. Global shifts towards positive species interactions with increasing environmental stress. Ecol. Lett. 16, 695–706 (2013).PubMed 

    Google Scholar 
    Ziffer-Berger, J., Weisberg, P. J., Cablk, M. E. & Osem, Y. Spatial patterns provide support for the stress-gradient hypothesis over a range-wide aridity gradient. J. Arid Environ. 102, 27–33 (2014).ADS 

    Google Scholar 
    Vinogradov, B. V. Plant Indicators and Their Use in the Study of Natural Resources (Visshaya shkola, 1964).
    Google Scholar 
    Luo, C. et al. Characteristics of the modern pollen distribution and their relationship to vegetation in the Xinjiang region, northwestern China. Rev. Palaeobot. Palynol. 153, 282–295 (2009).
    Google Scholar 
    Zhao, Y. & Herzschuh, U. Modern pollen representation of source vegetation in the Qaidam Basin and surrounding mountains, north-eastern Tibetan Plateau. Veg. Hist. Archaeobot. 18, 245–260 (2009).
    Google Scholar  More