Ecology

Morphology and phenotypic plasticity
The morphological features of the investigated colepid strains differed from those described for C. hirtus, C. spetai and even for N. nolandi1 (Fig. 1). Characteristics that matched the descriptions were the ciliate cell length and width, the barrel-shaped cell (except for strain CIL-2017/7, which was pear-shaped and strain CCAP 1613/15 that had a cylindrical shape), a number of six armor tiers, the structure of the armor tiers (hirtus-type or nolandia-type, respectively), and one caudal cilium (Table S2). Variations (CV > 20%) were found (i) in the number of plate windows in the posterior/anterior main plates even within individual cells, and (ii) in the presence/absence of anterior and posterior spines (Tables 1 + S2, Fig. 1). This phenotypic plasticity of the ciliate could also be observed in freshly collected Coleps specimens and was therefore not an artifact resulting from cultivation conditions (Fig. 1A). Wickham and Gugenberger43 hypothesized that the formation of the spines was a response to grazing pressure on C. hirtus; however, this could not be confirmed by respective experiments. Nevertheless, spineless specimens of C. hirtus have obviously been found before44,45,46,47. Luckily, we were able to investigate two strains (CCAP 1613/1 and CCAP 1613/2) that had been kept in the CCAP culture collection since the 1950ies and the 1960ies and which did not bear any spines or symbionts and could be clearly assigned to C. hirtus (Fig. 1T–V). These observations suggest that without predation pressure, colepid ciliates probably do not need to synthesize spines avoiding ingestion by a predator.
The presence/absence of green algal endosymbionts, one of the diagnostic features for the discrimination among C. hirtus subspecies and C. spetai, was also not a stable feature (Table S2). Under culture conditions, some strains lost their endosymbionts completely, other strains consisted of symbiotic and aposymbiotic individuals, and some strains showed only symbiont-bearing individuals (e.g., CCAP 1613/5 and CIL-2017/6). This indicates that the symbiosis is facultative and might be probably influenced by cultivation or environmental conditions (presumably, though not tested, food availability). Consequently, the morphological separation of C. hirtus into the two subspecies may no longer be valid. We clearly demonstrated that the morphological features used for species descriptions can vary and have severe consequences for colepid species identification. Moreover, even the strains belonging to the groups 1 and 2 discovered by the phylogenetic analyses (Fig. 2) cannot discriminate morphotypes because they can neither be assigned to a certain cell morphology nor to the possession of algal endosymbionts. This questions the traditional morphology-based taxonomy. The separation of Coleps hirtus hirtus, C. hirtus viridis and C. spetai, which Foissner et al.1 differentiated by the presence of zoochlorellae in the latter two species and the number of windows in the armor plates, could not be supported by our analyses. C. hirtus viridis was originally described by Ehrenberg48,49 as C. viridis and later transferred as synonym of C. hirtus by Kahl50 based on almost identical morphological features. However, Foissner22 described C. spetai for the green Coleps because of the morphological discrepancies to the Ehrenberg’s C. viridis (presence of only 11 windows per plate row and smaller cell size in C. viridis; see Table 1 for comparison). Our study has clearly demonstrated that most of the morphological features are variable and the limits for species separation were too narrow. Therefore, we propose the re-establishment of C. viridis for group 1 and C. hirtus for group 2, both with emended descriptions as follows. Considering our findings, the morphological descriptions of C. spetai, C. hirtus viridis and C. hirtus hirtus cannot be applied for (sub-) species separation any more. Consequently, we deal with a cryptic species complex, i.e., two genetically different groups that are fused in a highly variable morphotype including features of all three (sub-) species. To solve this taxonomic problem, two possible scenarios can be proposed: (1) We merge the three morphotypes under C. hirtus, the type species of Coleps. As a consequence, two new species needed to be proposed for both groups 1 and 2, which could be done following the suggestion of Sonneborn51 for the P. aurelia-complex. However, Sonneborn based his new descriptions on results of mating experiments, which are not applicable for Coleps here because conjugations have not been reported and the conditions for the induction of sexual reproduction are unknown. (2) To avoid confusion by introducing new species names, we propose keeping the already existing names, i.e., C. viridis for group 1 and C. hirtus for group 2 including the synonyms (see below).
Clonal cultures of both genetically varying Coleps groups have been deposited in the CCAP culture collection. Future studies may therefore be able to investigate, for example, sibling among strains or predator-prey experiments revealing spine- or wing-formation.
Coleps viridis Ehrenberg 1831 (printed 1832), Abh. Königl. Akad. Wiss. Berlin 1832: 101.
Synonym: Coleps spetai Foissner 1984, Stapfia 12: 21-22, Fig. 7, SP: 1984/10 and 1984/11 (lectotype designated here deposited in LI, see Aescht 2008: Denisia 23: 179), Coleps hirtus sensu Kahl 1930, Tierwelt Deutschlands 18: 134.
Diagnosis: Differed from other colepid ciliates by their SSU and ITS rDNA sequences (MT253680).
Lectotype (designated here): Fig. II, Tab. XXXIII, 3 in Ehrenberg 1838, Infusionsthierchen als vollkommene Organismen, p. 314.
Improved Description (specifications in brackets apply to our reference strain CCAP 1613/7): Coleps with conspicuous armor composed of six tiers with plate windows of the hirtus-type. With or without green algal endosymbionts. Cell size 44–63 × 21–35 μm (52–54 × 35–36 μm). Total number of windows in length rows 12–16 (14–16), number of windows of anterior primary plates 3–6 (4–6), number of windows of anterior secondary plates 2–3 (2), number of windows of posterior primary plates 4–5 (4–5), number of windows of posterior secondary plates 2–3 (2–3). One caudal cilium (1). With 0-2 anterior (0–1) and 0–5 posterior (1–4) spines, respectively.
Reference material (designated here for HTS approaches): The reference strain CCAP 1613/7 permanently cryopreserved at CCAP in a metabolically inactive stage.
Locality of reference strain: Plankton of Lake Mondsee, Upper Austria, Austria (47° 50′ N, 13° 23′ E).
Coleps hirtus (O.F. Müller) Nitzsch ex Ersch & Gruber 1827, Allgemeine Encyclopädie der Wissenschaften und Künste 16: 69, NT (proposed by Foissner 1984, Stapfia 12: 22, fig. 8): 1984/12 and 1984/13 (LI, in Aescht 2008: Denisia 23: 159).
Protonym: Cercaria hirta O.F. Müller 1786, Animalcula Infusoria: 128, tab. XIX, fig. 17, 18 (lectotype designated here).
Diagnosis: Differed from other colepid ciliates by their SSU and ITS rDNA sequences (MT253687).
Improved Description: Coleps with spiny armor composed of six tiers with plates of the hirtus-type. Without green algal endosymbionts. Cell size 42–52 × 23–28 μm. Total number of windows in length rows 12-13, number of windows of anterior primary plates 3-5, number of windows of anterior secondary plates 2, number of windows of posterior primary plates 4-5, number of windows of posterior secondary plates 2. One caudal cilium. Without anterior and 1-4 posterior spines, respectively.
Reference strain (designated here for HTS approaches): The strain CCAP 1613/14 permanently cryopreserved at CCAP in a metabolically inactive stage.
Locality of reference strain: Plankton of Lake Piburg, Tyrol, Austria (47° 11′ N, 10° 53′ E).
Molecular phylogeny of the Colepidae (Prostomatea)
The colepids belonging to the Prostomatea form a monophyletic lineage in the phylogenetic analyses of SSU rDNA sequences (Fig. 2). Mixotrophic as well as heterotrophic Coleps strains that resembled C. hirtus and C. spetai clustered in group 1 whereas group 2 included only two specimens which were identified as C. hirtus. These findings confirm the results of Barth et al.29 with one exception. The authors found a clear separation into mixotrophic and heterotrophic species, which were therefore assigned to a C. spetai-(with endosymbionts) and a C. hirtus-group (without endosymbionts), respectively. Despite the difficulties of identifying these species by morphology, both groups clearly differed in their SSU and ITS rDNA sequences (Fig. 3). The ITS-2/CBC approach introduced for green algae (details in Darienko et al.52) clearly demonstrated that both groups represented two separate ciliate species from a molecular point of view, which was also confirmed by analyses of the V9 region of the SSU, a region commonly used for metabarcoding (Figs. 4 and 5).
Our study also confirmed the findings of Chen et al.7, Lu et al.9, and Moon et al.28, showing that the generic concept of colepid ciliates needs to be revised. None of the genera represented by more than one species is monophyletic. For example, the three species of Nolandia belonged to separate lineages. Nolandia nolandi was a sister to our studied strains, whereas both other species were closely related to taxa of Apocoleps, Pinacocoleps, and Tiarina (Fig. 2). The genus Levicoleps and Coleps amphacanthus formed a monophyletic clade representing another example that the generic conception is artificial and needs to be revised. However, to provide a new generic concept of colepid ciliates, it is necessary to study more of the described species by using an integrative approach including experimental approaches on, e.g., the formation of spines. For example, we clearly demonstrated that one key feature, which is the presence/absence of anterior/posterior spines, is highly variable and can therefore not be used to separate colepid genera as indicated by Foissner et al.12 (Fig. 1). There is a need for more experimental studies with colepids belonging to the Cyclidium viridis and C. hirtus morphotype. Therefore, we deposited all clones used in this study in the CCAP culture collection. One option would be to incorporate all species into one genus, i.e., Coleps in revised form.
Endosymbiosis in Coleps
Some strains of Coleps are known to bear green algal endosymbionts1. These green algae have Chlorella-like morphology (Fig. 6) and were identified as Micractinium conductrix (Fig. 7). So far, this alga was only known as endosymbiont of the ciliate Paramecium bursaria34. All green algal endosymbionts of Coleps harbored this Micractinium species. In contrast, Pröschold et al.34 found that one ciliate strain identified as C. hirtus viridis had Chlorella vulgaris as endosymbiont (the algae has been deposited in the Culture Collection of Algae and Protozoa under the number CCAP 211/111). Unfortunately, this ciliate strain is not available anymore53.
Ecology and distribution
For limnological studies, the preservation with Bouin’s solution and QPS is an appropriate method for quantifying and identifying ciliate species in environmental samples54. However, the quality in characterization of ciliates at the species level is sometimes limited as, in case of Coleps, the characteristic armored calcium carbonate plates are dissolved by the acidified fixation solution. Therefore, in our study, we could only distinguish between algal-bearing (mixotrophic) and non-algal-bearing (heterotrophic) Coleps. Despite that limitation, we could clearly see that the heterotrophic ones were only found in the deepest zones of both lakes (Fig. 8A). Not surprisingly, Coleps is often observed in nutrient- and ion-rich and also oxygen-depleted freshwater habitats or areas, e.g., sulfurous and crater lakes1,5,6,27,55,56 or even in the sludge of wastewater treatment plants57. Mixotrophic individuals of Coleps were mainly found in the upper layers of both lakes, whereas in Lake Mondsee we could also detect specimens down to 40 m depth (Fig. 8). In contrast to the mero- and monomictic Lake Zurich4,10,58,59, Lake Mondsee is holo- and dimictic60. During mixis events, algal-bearing Coleps specimens can be transferred passively from the upper layers into the deeper zones and vice versa. Although morphotype countings and HTS analyses reads matched quite well, we found discrepancies that have already been discussed before10,61 (Fig. S2).
Biogeographic aspects (haplotype network)
Our metabarcoding approach showed that C. viridis was found in both lakes as a common ciliate (Fig. S2). In contrast, C. hirtus could not be detected during the sampling period. To obtain more information about the distribution of both species, we used the BLASTn search algorithm62 (100 coverage, >97% identity) for the V4 and the V9 regions of the SSU and the ITS-2 sequences. No records using the V9 and the ITS-2 approaches could be discovered in GenBank, but 25 reference sequences using the V4 (Table S3). Together with the newly sequenced strains, we therefore constructed a V4 haplotype network (Fig. 10). Both groups are obviously widely distributed and subdivided into five (group 1) and four (group 2) haplotypes, respectively. All reference sequences were collected from freshwater habitats except for two marine records63 (EU446361 and EU446396; Mediterranean Sea) and showed no geographical preferences.
Figure 10

TCS haplotype network inferred from V4 sequences of Coleps viridis and C. hirtus. This network was inferred using the algorithm described by Clement et al.64,65. Sequence nodes corresponding to samples collected from different geographical regions and from different habitats.

Full size image

Co-occurrence networks
In the sub-networks of C. viridis in both lakes, we found several significant correlations that pointed to either potential prey items, e.g., diverse flagellated autotrophic or heterotrophic protists or co-occurring ciliates (Fig. 9). Also, the smaller ciliates such as Cinetochilum margaritaceum or Cyclidium glaucoma may as well be considered as food for the omnivorous C. viridis (for a compilation of the food spectrum; see Foissner et al.1). However, we identified the endosymbiont M. conductrix and its host C. viridis from both sub-networks of Lake Mondsee but not of Lake Zurich (Fig. 9). Despite this result, we want to point out that we may probably not find M. conductrix free-living in a water body because outside their ciliate host the algae were immediately attacked and killed by so-called Chlorella-viruses66. Therefore, the HTS-detection of M. conductrix was probably only together with a host ciliate. This might further explain why the green algae were detected in Lake Mondsee even in the aphotic 40 m zone where photosynthesis was impossible and individuals probably passively transferred into the deeper area by lake mixis.
Outlook
As demonstrated in our study, the combination of traditional morphological investigations, which includes the phenotypic plasticity of the cloned strains, and modern molecular analyses using both SSU and ITS sequencing as well as HTS approaches advise a taxonomic revision of the genus Coleps. This comprehensive and integrative approach is also applicable for other ciliate species and genera and will provide new insights into the ecology and evolution of this important group of protists.
Experimental procedures
Study sites, lake sampling and origin of the Coleps strains
Our main study sites were Lake Mondsee (Austria) and Lake Zurich (Switzerland), two pre-alpine oligo-mesotrophic lakes that were sampled at the deepest point of each lake (Table S4). Water samples were taken monthly from June 2016 through May 2017 over the whole water column and additionally biweekly at two main depths, i.e., 5 m in both lakes, 40 m in Lake Mondsee, and 120 m in Lake Zurich, respectively. A 5-L-Ruttner water sampler was used for Lake Zurich and a 10-L-Schindler-Patalas sampler (both from Uwitec, Austria) for Lake Mondsee. Twelve Coleps strains were isolated from Lake Mondsee and one from Lake Zurich. Another six clones could be obtained either from already successfully cultivated own strains, fresh isolates or from culture collections. Detailed information about sampling sites, dates and strain numbers is given in Table S2.
Seasonal and spatial distribution and abundance
For quantification, subsamples (200-300 mL) were preserved with Bouin’s solution (5% f.c.) containing 15 parts of picric acid, 5 parts of formaldehyde (37%) and 1 part of glacial acetic acid54. The samples were filtered through 0.8 μm cellulose nitrate filters (Sartorius, Germany) equipped with counting grids. The ciliates were stained following the protocol of the quantitative protargol staining (QPS) method after Skibbe54 with slight modifications after Pfister et al.67. The permanent slides were analyzed by light microscopy up to 1600x magnification with a Zeiss Axio Imager.M1 and an Olympus BX51 microscope. For identification of Coleps and Nolandia cells, the identification key of Foissner et al.1 was used. Microphotographs were taken with a ProgRes C14 plus camera using the ProgRes Capture Pro imaging system (version 2.9.0.1, Jenoptik, Jena, Germany).
Cloning, identification and cultivation of ciliates and endosymbionts
Single cells of Coleps were isolated and washed using the Pasteur pipette method68. The isolated strains were cultivated in 400 μl modified Woods Hole medium69 (MWC; modified) and Volvic mineral water in a mixture of 5:1 and with the addition of 10 μl of an algal culture (Cryptomonas sp., strain SAG 26.80) as food in microtiter plates. These clonal cultures were transferred into larger volumes after successful enrichment. All cultures were maintained at 15–21 °C under a light: dark cycle of 12:12 h (photon flux rate up 50 mol m−2 s−1).
For the isolation of their green algal endosymbionts, single ciliates were washed again and transferred into fresh MWC medium. After starvation and digestion of any food, after approx. 24 hrs, cells were washed again and the ciliates transferred onto agar plates containing Basal Medium with Beef Extract (ESFl; medium 1a in Schlösser70). Before placement of the ciliates onto agar plates, 50 μm of an antibiotic mix (mixture of 1% penicillin G, 0.25% streptomycin, and 0.25% chloramphenicol) were added to prevent bacterial growth. The agar plates were kept under the same conditions as described. After growth (6–8 weeks), the algal colonies were transferred onto agar slopes (1.5%) containing ESFl medium and kept under the described culture conditions.
For light microscopic investigations of the algae, Olympus BX51 and BX60 microscopes (equipped with Nomarski DIC optics) were used. Microphotographs were taken with a ProgRes C14 plus camera using the ProgRes Capture Pro imaging system (version 2.9.0.1, Jenoptik, Jena, Germany).
PCR, sequencing and phylogenetic methods
Single-cell PCR was used to obtain the sequences of the Coleps strains. Before PCR amplification, single cells of Coleps were washed as described above. After starvation followed by additional washing steps, cells were transferred into 5 μm sterile water in PCR tubes and the prepared PCR mastermix containing the primers EAF3 and ITS055R71 was added. After this primary PCR amplification and subsequent PCR purification, a nested PCR was conducted using the primer combinations EAF3/N1400R and N920F/ITS055R71.
The sequences of the Coleps strains were aligned according to their secondary structures of the SSU and ITS rDNA (see detailed folding protocol described in Darienko et al.52) and included into two data sets: (i) 34 SSU rDNA sequences (1,750 bp) of representatives of all members of the Prostomatea and (ii) 19 ITS rDNA sequences (538 bp) of the investigated strains. Genomic DNA of the green algae was extracted using the DNeasy Plant Mini Kit (Qiagen GmbH, Hilden, Germany). The SSU and ITS rDNA were amplified using the Taq PCR Mastermix Kit (Qiagen GmbH, Hilden, Germany) with the primers EAF3 and ITS055R. The SSU and ITS rDNA sequences of the isolated green algae (aligned according to the secondary structures) were included into a data set of 31 sequences (2,604 bp) of representatives of the Chlorellaceae (Trebouxiophyceae).
GenBank accession numbers of all newly deposited sequences can be found in Table S2 and in Fig. 7, respectively. For the phylogenetic analyses, the datasets with unambiguously aligned base positions were used. To test which evolutionary model fit best for both data sets, we calculated the log-likelihood values of 56 models using Modeltest 3.772 and the best models according to the Akaike criterion by Modeltest were chosen for the analyses. The settings of the best models are given in the figure legends. The following methods were used for the phylogenetic analyses: distance, maximum parsimony, maximum likelihood, and Bayesian inference. Programs used included PAUP version 4.0b16473, and MrBayes version 3.2.374.
The secondary structures were folded using the software mfold42, which uses the thermodynamic model (minimal energy) for RNA folding.
Haplotype networks
The haplotypes of the V4 region were identified among the groups of Coleps (see Fig. S1). The present haplotypes and the metadata (geographical origin and habitat) of each strain belonging to the different haplotypes are given in Table S3. To establish an overview on the distribution of the Coleps groups, the V4 haplotypes were used for a BLASTn search62 (100% coverage, >97% identity). To construct the haplotype networks, we used the TCS network tool64,65 implemented in PopART75.
High-throughput sequencing of the V9 18S rDNA region and subsequent bioinformatic analyses
On each sampling date, water samples for a high-throughput sequencing approach (HTS) were taken in depths of 5 m and 40 m at Lake Mondsee and 5 m and 120 m depths in Lake Zurich. DNA extraction, amplification of the V9 SSU rDNA, HTS and quality filtering of the obtained raw reads was conducted as described in Pitsch et al.10. After quality filtering, all remaining reads were subjected to a two-level clustering strategy76. In the first level, replicated reads were clustered in SWARM version 2.2.2 using d=177. In the second level, the representative sequences of all SWARM OTUs were subjected to pairwise sequence alignments in VSEARCH version 2.11.078 to construct sequence similarity networks at 97% sequence similarity. The network sequence clusters (NSCs) resulting from the second level of clustering were then taxonomically assigned by running BLASTn analyses against NCBI’s GenBank flat-file release version 230.0 and the Coleps SSU sequences obtained from single-cell sequencing. Network sequence clusters were assigned to Coleps, if the closest BLAST hit of the NSC representative sequence was a Coleps reference sequence. Furthermore, the NSC representative sequence had to share a fragment of at least 48 consecutive nucleotides and at least 90% sequence similarity to a reference sequence in order to be assigned to Coleps.
Co-occurrence networks
With the protist community data matrix resulting from HTS, we further conducted co-occurrence network analyses to assess biotic and abiotic interactions of Coleps. For each lake and depth, we ran network analyses with NetworkNullHPC (https://github.com/lentendu/NetworkNullHPC) following the null model strategy developed by Connor et al.79. This strategy was especially designed for dealing with HTS datasets and allows for inferring statistically significant correlations between NSCs while minimizing false positive correlation signals. We screened the resulting networks for Coleps nodes and extracted their subnetworks including all directly neighbouring co-occurrence partners as well as all edges between Coleps and its neighbours and the neighbours themselves. More

1.Huss, M. et al. Towards mountains without permanent snow and ice. Earth’s Future 5, 418–435 (2017).Article 

Google Scholar 
2.Zemp, M. et al. Global glacier mass changes and their contributions to sea-level rise from 1961 to 2016. Nature 568, 382–386 (2019).CAS 
Article 

Google Scholar 
3.Brown, L. E. et al. Functional diversity and community assembly of river invertebrates show globally consistent responses to decreasing glacier cover. Nat. Ecol. Evol. 2, 325–333 (2018).Article 

Google Scholar 
4.Cauvy-Fraunié, S. & Dangles, O. A global synthesis of biodiversity responses to glacier retreat. Nat. Ecol. Evol. 3, 1675–1685 (2019).Article 

Google Scholar 
5.Milner, A. M. et al. Glacier shrinkage driving global changes in downstream systems. Proc. Natl Acad. Sci. USA 114, 9770–9778 (2017).CAS 
Article 

Google Scholar 
6.Huss, M. & Hock, R. Global-scale hydrological response to future glacier mass loss. Nat. Clim. Change 8, 135–140 (2018).Article 

Google Scholar 
7.Ren, Z., Gao, H., Elser, J. J. & Zhao, Q. Microbial functional genes elucidate environmental drivers of biofilm metabolism in glacier-fed streams. Sci. Rep. 7, 12668 (2017).Article 
CAS 

Google Scholar 
8.Zhou, L. et al. Microbial production and consumption of dissolved organic matter in glacial ecosystems on the Tibetan Plateau. Water Res. 160, 18–28 (2019).CAS 
Article 

Google Scholar 
9.Cavicchioli, R. et al. Scientists’ warning to humanity: microorganisms and climate change. Nat. Rev. Microbiol. 17, 569–586 (2019).CAS 
Article 

Google Scholar 
10.Timmis, K. et al. The urgent need for microbiology literacy in society. Environ. Microbiol. 21, 1513–1528 (2019).Article 

Google Scholar 
11.Hotaling, S., Hood, E. & Hamilton, T. L. Microbial ecology of mountain glacier ecosystems: biodiversity, ecological connections and implications of a warming climate. Environ. Microbiol. 19, 2935–2948 (2017).Article 

Google Scholar 
12.Aufdenkampe, A. K. et al. Riverine coupling of biogeochemical cycles between lands, oceans, and atmosphere. Front. Ecol. Environ. 9, 53–60 (2011).Article 

Google Scholar 
13.Raymond, P. et al. Global carbon dioxide emissions from inland waters. Nature 503, 355–359 (2013).CAS 
Article 

Google Scholar 
14.Clark, D. R. et al. Streams of data from drops of water: 21st century molecular microbial ecology. WIREs Water 5, e1280 (2018).Article 

Google Scholar 
15.Zah, R. & Uehlinger, U. Particulate organic matter inputs to a glacial stream ecosystem in the Swiss Alps. Freshw. Biol. 46, 1597–1608 (2001).CAS 
Article 

Google Scholar 
16.Singer, G. A. et al. Biogeochemically diverse organic matter in alpine glaciers and its downstream fate. Nat. Geosci. 5, 710–714 (2012).CAS 
Article 

Google Scholar 
17.Uehlinger, U., Robinson, C. T., Hieber, M. & Zah, R. The physico-chemical habitat template for periphyton in alpine glacial streams under a changing climate. Hydrobiologia 657, 107–121 (2010).CAS 
Article 

Google Scholar 
18.Robinson, C. T. & Gessner, M. O. Nutrient addition accelerates leaf breakdown in an alpine springbrook. Oecologia 122, 258–263 (2000).CAS 
Article 

Google Scholar 
19.Robinson, C. T. & Jolidon, C. Leaf breakdown and the ecosystem functioning of alpine streams. J. North Am. Benthol. Soc. 24, 495–508 (2005).Article 

Google Scholar 
20.McKernan, C., Cooper, D. J. & Schweiger, E. W. Glacial loss and its effect on riparian vegetation of alpine streams. Freshw. Biol. 63, 518–529 (2018).Article 

Google Scholar 
21.Fellman, J. B. et al. Stream temperature response to variable glacier coverage in coastal watersheds of southeast Alaska. Hydrol. Process. 28, 2062–2073 (2014).Article 

Google Scholar 
22.Gessner, M. O. & Robinson, C. T. in Aquatic Ecology Series: Ecology of a Glacial Floodplain Vol. 1 (eds Ward, J. V. & Uehlinger, U.) 123–127 (Springer, 2003).23.Tiegs, S. D., Clapcott, J. E., Griffiths, N. A. & Boulton, A. J. A standardized cotton-strip assay for measuring organic-matter decomposition in streams. Ecol. Indic. 32, 131–139 (2013).CAS 
Article 

Google Scholar 
24.Tiegs, S. D. et al. Global patterns and drivers of ecosystem functioning in rivers and riparian zones. Sci. Adv. 5, eaav0486 (2019).Article 
CAS 

Google Scholar 
25.Ward, N. D. et al. Degradation of terrestrially derived macromolecules in the Amazon River. Nat. Geosci. 6, 530–533 (2013).CAS 
Article 

Google Scholar 
26.Colas, F. et al. Towards a simple global-standard bioassay for a key ecosystem process: organic-matter decomposition using cotton strips. Ecol. Indic. 106, 105466 (2019).CAS 
Article 

Google Scholar 
27.Bayer, E. A., Shoham, Y. & Lamed, R. Cellulose-decomposing bacteria and their enzyme systems. Prokaryotes 2, 578–617 (2006).Article 

Google Scholar 
28.Lindahl, B. D. et al. Fungal community analysis by high-throughput sequencing of amplified markers—a user’s guide. N. Phytol. Trust 199, 288–299 (2013).CAS 
Article 

Google Scholar 
29.Nguyen, N. H. et al. FUNGuild: an open annotation tool for parsing fungal community datasets by ecological guild. Fungal Ecol. 20, 241–248 (2016).Article 

Google Scholar 
30.Wang, M. et al. Psychrophilic fungi from the world’s roof. Persoonia 34, 100–112 (2015).CAS 
Article 

Google Scholar 
31.Zang, T. et al. Diversity and distribution of aquatic fungal communities in the Ny-Ålesund region, Svalbard (High Arctic). Microb. Ecol. 71, 543–554 (2016).Article 

Google Scholar 
32.Wilhelm, L., Singer, G. A., Fashing, C., Battin, T. J. & Besemer, K. Microbial biodiversity in glacier-fed streams. ISME J. 7, 1651–1660 (2013).CAS 
Article 

Google Scholar 
33.Hotaling, S. et al. Microbial assemblages reflect environmental heterogeneity in alpine streams. Glob. Change Biol. 25, 2576–2590 (2019).Article 

Google Scholar 
34.Jacobsen, D. & Dangles, O. Environmental harshness and global richness patterns in glacier-fed streams. Glob. Ecol. Biogeogr. 21, 647–656 (2012).Article 

Google Scholar 
35.Green, J. L., Bohannan, B. J. M. & Whitaker, R. J. Microbial biogeography: from taxonomy to traits. Science 320, 1039–1042 (2008).CAS 
Article 

Google Scholar 
36.Robinson, C. T., Gessner, M. O., Callies, K. A., Jolidon, C. & Ward, J. V. Larch needle breakdown in contrasting streams of an alpine glacial floodplain. J. North Am. Benthol. Soc. 19, 250–262 (2000).Article 

Google Scholar 
37.Ferreira, V., Graça, M., Pedroso de Lima, J. L. M. & Gomes, R. Role of physical fragmentation and invertebrate activity in the breakdown rate of leaves. Arch. fur Hydrobiol. 165, 493–513 (2006).CAS 
Article 

Google Scholar 
38.Besemer, K., Singer, G., Hödl, I. & Battin, T. J. Bacterial community composition of stream biofilms in spatially variable-flow environments. Appl. Environ. Microbiol. 75, 7189–7195 (2009).CAS 
Article 

Google Scholar 
39.Battin, T. J., Kaplan, L. A., Newbold, J. D., Cheng, X. & Hansen, C. Effects of current velocity on the nascent architecture of stream microbial biofilms. Appl. Environ. Microbiol. 9, 5443–5452 (2003).Article 
CAS 

Google Scholar 
40.Fell, S. C., Carrivick, J. L. & Brown, L. E. The multitrophic effects of climate change and glacier retreat in mountain rivers. BioScience 67, 897–911 (2017).Article 

Google Scholar 
41.Cristiano, G., Cicolani, B., Miccoli, F. P. & Di Sabatino, A. A modification of the leaf-bags method to assess spring ecosystem functioning: benthic invertebrates and leaf-litter breakdown in Vera Spring (central Italy). PeerJ 7, e6250 (2019).Article 

Google Scholar 
42.Greenwood, S. & Jump, A. S. Consequences of treeline shifts for the diversity and function of high altitude ecosystems. Arct. Antarct. Alp. Res. 46, 829–840 (2014).Article 

Google Scholar 
43.Hood, E. & Berner, L. Effects of changing glacial coverage on the physical and biogeochemical properties of coastal streams in southeastern Alaska. J. Geophys. Res. Biogeosci. 114, G03001 (2009).Article 
CAS 

Google Scholar 
44.Boix Canadell, M., Escoffier, N., Ulseth, A. J., Lane, S. N. & Battin, T. J. Alpine glacier shrinkage drives shifts in dissolved organic carbon export from quasi-chemostasis to transport limitation. Geophys. Res. Lett. 46, 8872–8881 (2019).CAS 
Article 

Google Scholar 
45.Jacobsen, D., Milner, A. M., Brown, L. E. & Dangles, O. Biodiversity under threat in glacier-fed river systems. Nat. Clim. Change 2, 361–364 (2012).Article 

Google Scholar 
46.GLIMS Glacier Viewer (Global Land Ice Measurements from Space (GLIMS), 2018); http://www.glims.org/maps/glims47.Robinson, C. T., Gessner, M. O. & Ward, J. V. Leaf breakdown and associated macroinvertebrates in alpine glacial streams. Freshw. Biol. 40, 215–228 (1998).Article 

Google Scholar 
48.Goodman, K. J., Baker, M. & Wurtsbaugh, W. Mountain lakes increase organic matter decomposition rates in streams. J. North Am. Benthol. Soc. 29, 521–529 (2010).Article 

Google Scholar 
49.Pfankuch, D. J. Stream Reach Inventory and Channel Stability Evaluation (Northern Region, Montana, US Department Forest Service, 1975).50.Vizza, C., Zwart, J. A., Jones, S. E., Tiegs, S. D. & Lamberti, G. A. Landscape patterns shape wetland pond ecosystem function from glacial headwaters to ocean. Limnol. Oceanogr. 62, S207–S221 (2017).CAS 
Article 

Google Scholar 
51.Tiegs, S. D. CELLDEX Protocol Part 1 https://www.researchgate.net/publication/281243407_CELLDEX_Protocol_Part_1 (2015).52.Tiegs, S. D. Protocol for Microbial DNA/RNA Sampling—CELLDEX Protocol https://www.researchgate.net/publication/281245895_Protocol_for_microbial_DNARNA_sampling_-_CELLDEX_Project (2015).53.Tiegs, S. D., Langhans, S. D., Tockner, K. & Gessner, M. O. Cotton strips as a leaf surrogate to measure decomposition in river floodplain habitats. J. North Am. Benthol. Soc. 26, 70–77 (2007).Article 

Google Scholar 
54.Tiegs, S. D. CELLDEX Protocol Part 2 https://www.researchgate.net/publication/283645782_CELLDEX_Protocol_Part_2 (2015).55.Griffiths, R. I., Whiteley, A. S., O’Donnell, A. G. & Bailey, M. J. Rapid method for coextraction of DNA and RNA from natural environments for analysis of ribosomal DNA- and rRNA-based microbial community composition. Appl. Environ. Microbiol. 66, 5488–5491 (2000).CAS 
Article 

Google Scholar 
56.Toju, H., Tanabe, A. S., Yamamoto, S. & Sato, H. High-coverage ITS primers for the DNA-based identification of ascomycetes and basidiomycetes in environmental samples. PLoS ONE 7, e40863 (2012).CAS 
Article 

Google Scholar 
57.Edwards, I. P., Upchurch, R. A. & Zak, D. R. Isolation of fungal Cellobiohydrolase I genes from sporocarps and forest soils by PCR. Appl. Environ. Microbiol. 74, 3481–3489 (2008).CAS 
Article 

Google Scholar 
58.McKew, B. A. & Smith, C. J. in Hydrocarbon and Lipid Microbiology Protocols (eds McGenity, T. J. et al.) 45–64 (Springer, 2017).59.Gardes, M. & Bruns, T. D. ITS primers with enhanced specificity for basidiomycetes—application to the identification of mycorrhizae and rusts. Mol. Ecol. 2, 113–118 (1993).CAS 
Article 

Google Scholar 
60.Nilsson, R. H. et al. Variability in the kingdom fungi as expressed in the international sequence databases and its implications for molecular species identification. Evol. Bioinform. Online 4, 193–201 (2008).Article 

Google Scholar 
61.Nilsson, R. H., Ryberg, M., Abarenkov, K., Sjökvist, E. & Kristiansson, E. The ITS region as a target for characterization of fungal communities using emerging sequencing technologies. FEMS Microbiol. Lett. 296, 97–111 (2009).CAS 
Article 

Google Scholar 
62.16S Metagenomic Sequencing Library Preparation (Illumina, 2013); https://ww.illumina.com/content/dam/illumina-support/documents/documentation/chemistry_documentation/16s/16s-metagenomic-library-prep-guide-15044223-b.pdf63.Kreader, C. A. Relief of amplification inhibition in PCR with bovine serum albumin or T4 gene 32 protein. Appl. Environ. Microbiol. 62, 1102–1106 (1995).Article 

Google Scholar 
64.Dumbrell, A. J., Ferguson, R. M. W. & Clark, D. R. in Hydrocarbon and Lipid Microbiology Protocols (eds McGenity, T. J. et al.) 155–206 (Springer, 2017).65.Maček, I. et al. Impacts of long-term elevated atmospheric CO2 concentrations on communities of arbuscular mycorrhizal fungi. Mol. Ecol. 28, 3445–3458 (2019).Article 
CAS 

Google Scholar 
66.Nilsson, R. H. et al. UNITE Community: Communication and Identification of DNA Based Fungal Species (UNITE, 2018); https://unite.ut.ee/search.php#fndtn-panel167.Nilsson, R. H. et al. The UNITE database for molecular identification of fungi: handling dark taxa and parallel taxonomic classifications. Nucleic Acids Res. 47, D259–D264 (2018).Article 
CAS 

Google Scholar 
68.Weiss, S. et al. Normalization and microbial differential abundance strategies depend upon data characteristics. Microbiome 5, 2–18 (2017).Article 

Google Scholar 
69.McKnight, D. T. et al. Methods for normalizing microbiome data: an ecological perspective. Methods Ecol. Evol. 10, 389–400 (2019).Article 

Google Scholar 
70.Wood, S. N. Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. J. R. Stat. Soc. B 73, 3–36 (2011).Article 

Google Scholar 
71.Wood, S. N. Stable and efficient multiple smoothing parameter estimation for generalized additive models. J. Am. Stat. Assoc. 99, 673–686 (2004).Article 

Google Scholar 
72.Wang, Y., Maumann, U., Wright, S. & Warton, D. mvabund: Statistical methods for analysing multivariate abundance data. R package https://cran.r-project.org/package=mvabund (2018). More

1.Andersson, M. B. Sexual Selection (Princeton Univ. Press, 1994).2.Clark, C. J. The role of power versus energy in courtship: what is the ‘energetic cost’of a courtship display? Anim. Behav. 84, 269–277 (2012).Article 

Google Scholar 
3.Vehrencamp, S. L., Bradbury, J. W. & Gibson, R. M. The energetic cost of display in male sage grouse. Anim. Behav. 38, 885–896 (1989).Article 

Google Scholar 
4.Kotiaho, J. S. Costs of sexual traits: a mismatch between theoretical considerations and empirical evidence. Biol. Rev. 76, 365–376 (2001).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
5.Mappes, J., Alatalo, R. V., Kotiaho, J. & Parri, S. Viability costs of condition-dependent sexual male display in a drumming wolf spider. Proc. R. Soc. Lond. B 263, 785–789 (1996).Article 

Google Scholar 
6.Zuk, M. & Kolluru, G. R. Exploitation of sexual signals by predators and parasitoids. Q. Rev. Biol. 73, 415–438 (1998).Article 

Google Scholar 
7.Woods, W. A. Jr, Hendrickson, H., Mason, J. & Lewis, S. M. Energy and predation costs of firefly courtship signals. Am. Nat.170, 702–708 (2007).PubMed 
Article 
PubMed Central 

Google Scholar 
8.Lande, R. Models of speciation by sexual selection on polygenic traits. Proc. Natl Acad. Sci. USA 78, 3721–3725 (1981).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
9.Cotton, S., Fowler, K. & Pomiankowski, A. Do sexual ornaments demonstrate heightened condition-dependent expression as predicted by the handicap hypothesis? Proc. R. Soc. Lond. B 271, 771–783 (2004).Article 

Google Scholar 
10.Tomkins, J. L., Radwan, J., Kotiaho, J. S. & Tregenza, T. Genic capture and resolving the lek paradox. Trends Ecol. Evol. 19, 323–328 (2004).PubMed 
Article 

Google Scholar 
11.Grafen, A. Biological signals as handicaps. J. Theor. Biol. 144, 517–546 (1990).CAS 
PubMed 
Article 

Google Scholar 
12.Johnstone, R. A. Sexual selection, honest advertisement and the handicap principle: reviewing the evidence. Biol. Rev. 70, 1–65 (1995).CAS 
PubMed 
Article 

Google Scholar 
13.Seymour, R. M. & Sozou, P. D. Duration of courtship effort as a costly signal. J. Theor. Biol. 256, 1–13 (2009).PubMed 
Article 

Google Scholar 
14.Byers, J., Hebets, E. & Podos, J. Female mate choice based upon male motor performance. Anim. Behav. 79, 771–778 (2010).Article 

Google Scholar 
15.Moran, N. P., Sánchez-Tójar, A., Schielzeth, H. & Reinhold, K. Poor nutritional condition promotes high-risk behaviours: a systematic review and meta-analysis. Biol. Rev. https://doi.org/10.1111/brv.12655 (2020).16.Cotton, S., Small, J. & Pomiankowski, A. Sexual selection and condition-dependent mate preferences. Curr. Biol. 16, R755–R765 (2006).CAS 
PubMed 
Article 

Google Scholar 
17.Kokko, H. Evolutionarily stable strategies of age-dependent sexual advertisement. Behav. Ecol. Sociobiol. 41, 99–107 (1997).Article 

Google Scholar 
18.Moore, F. R., Shuker, D. M. & Dougherty, L. Stress and sexual signaling: a systematic review and meta-analysis. Behav. Ecol. 27, 363–371 (2016).Article 

Google Scholar 
19.Dougherty, L. R. Meta-analysis shows the evidence for context-dependent mating behaviour is inconsistent or weak across animals. Ecol. Lett. https://doi.org/10.1111/ele.13679 (2021).20.Umbers, K. D., Symonds, M. R. & Kokko, H. The mathematics of female pheromone signaling: strategies for aging virgins. Am. Nat. 185, 417–432 (2015).PubMed 
Article 

Google Scholar 
21.Simmons, L. W. Sexual signalling by females: do unmated females increase their signalling effort? Biol. Lett. https://doi.org/10.1098/rsbl.2015.0298 (2015).22.Reynolds, J. D. Should attractive individuals court more? Theory and a test. Am. Nat. 141, 914–927 (1993).CAS 
PubMed 
Article 

Google Scholar 
23.Jennions, M. D. & Backwell, P. R. Variation in courtship rate in the fiddler crab Uca annulipes: is it related to male attractiveness? Behav. Ecol. 9, 605–611 (1998).Article 

Google Scholar 
24.Candolin, U. The relationship between signal quality and physical condition: is sexual signalling honest in the three-spined stickleback? Anim. Behav. 58, 1261–1267 (1999).CAS 
PubMed 
Article 

Google Scholar 
25.Clutton-Brock, T. H. Reproductive effort and terminal investment in iteroparous animals. Am. Nat. 123, 212–229 (1984).Article 

Google Scholar 
26.Duffield, K. R., Bowers, E. K., Sakaluk, S. K. & Sadd, B. M. A dynamic threshold model for terminal investment. Behav. Ecol. Sociobiol. 71, 185 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
27.Buchanan, K. L., Spencer, K. A., Goldsmith, A. & Catchpole, C. Song as an honest signal of past developmental stress in the European starling (Sturnus vulgaris). Proc. R. Soc. Lond. B 270, 1149–1156 (2003).CAS 
Article 

Google Scholar 
28.Chemnitz, J., Jentschke, P. C., Ayasse, M. & Steiger, S. Beyond species recognition: somatic state affects long-distance sex pheromone communication. Proc. R. Soc. B 282, 20150832 (2015).PubMed 
Article 
CAS 

Google Scholar 
29.Richardson, J. & Smiseth, P. T. Nutrition during sexual maturation and at the time of mating affects mating behaviour in both sexes of a burying beetle. Anim. Behav. 151, 77–85 (2019).Article 

Google Scholar 
30.Balsby, T. J. Song activity and variability in relation to male quality and female choice in whitethroats Sylvia communis. J. Avian Biol. 31, 56–62 (2000).Article 

Google Scholar 
31.Nickley, B., Saintignon, D. & Roberts, J. A. Influence of predator cues on terminal investment in courtship by male Schizocosa ocreata (Hentz, 1844) wolf spiders (Araneae: Lycosidae). J. Arachnol. 44, 176–181 (2016).Article 

Google Scholar 
32.Kehl, T. et al. Pheromone blend does not explain old male mating advantage in a butterfly. Ethology 120, 1137–1145 (2014).Article 

Google Scholar 
33.Houslay, T. M., Houslay, K. F., Rapkin, J., Hunt, J. & Bussiere, L. F. Mating opportunities and energetic constraints drive variation in age-dependent sexual signalling. Funct. Ecol. 31, 728–741 (2017).Article 

Google Scholar 
34.Smith, M. J. & Roberts, J. D. Call structure may affect male mating success in the quacking frog Crinia georgiana (Anura: Myobatrachidae). Behav. Ecol. Sociobiol. 53, 221–226 (2003).Article 

Google Scholar 
35.Lehtonen, T. K. Signal value of male courtship effort in a fish with paternal care. Anim. Behav. 83, 1153–1161 (2012).Article 

Google Scholar 
36.Bertram, S. M., Harrison, S. J., Thomson, I. R. & Fitzsimmons, L. P. Adaptive plasticity in wild field cricket’s acoustic signaling. PLoS ONE 8, e69247 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
37.Rundus, A. S., Biemuller, R., DeLong, K., Fitzgerald, T. & Nyandwi, S. Age-related plasticity in male mate choice decisions by Schizocosa retrorsa wolf spiders. Anim. Behav. 107, 233–238 (2015).Article 

Google Scholar 
38.Koricheva, J., Gurevitch, J. & Mengeresen, K. Handbook of Meta-analysis in Ecology and Evolution (Princeton Univ. Press, 2013).39.Harts, A. M., Booksmythe, I. & Jennions, M. D. Mate guarding and frequent copulation in birds: a meta‐analysis of their relationship to paternity and male phenotype. Evolution 70, 2789–2808 (2016).PubMed 
Article 

Google Scholar 
40.Partridge, C., Boettcher, A. & Jones, A. G. The role of courtship behavior and size in mate preference in the sex-role-reversed gulf pipefish, Syngnathus scovelli. Ethology 119, 692–701 (2013).Article 

Google Scholar 
41.Anderson, A. P. & Jones, A. G. Choosy Gulf pipefish males ignore age but prefer active females with deeply keeled bodies. Anim. Behav. 155, 37–44 (2019).Article 

Google Scholar 
42.Sundin, J., Rosenqvist, G. & Berglund, A. Hypoxia delays mating in the broad-nosed pipefish. Mar. Biol. Res. 11, 747–754 (2015).Article 

Google Scholar 
43.McLennan, D. A. & Shires, V. L. Correlation between the level of infection with Bunodera inconstans and Neoechinorhynchus rutili and behavioral intensity in female brook sticklebacks. J. Parasitol. 81, 675–682 (1995).CAS 
PubMed 
Article 

Google Scholar 
44.Simmons, L. W. Courtship role reversal in bush-crickets—another role for parasites. Behav. Ecol. 5, 259–266 (1994).Article 

Google Scholar 
45.Schatral, A. Diet influences male–female interactions in the bush-cricket Requena verticalis (Orthoptera, Tettigoniidae). J. Insect Behav. 6, 379–388 (1993).Article 

Google Scholar 
46.Serrano, J. M. & Penna, M. Sexual monomorphism in the advertisement calls of a neotropical frog. Biol. J. Linn. Soc. 123, 388–401 (2018).Article 

Google Scholar 
47.Yamane, T. & Yasuda, T. The effects of mating status and time since mating on female sex pheromone levels in the rice leaf bug, Trigonotylus caelestialium. Naturwissenschaften 101, 153–156 (2014).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
48.Cohen, J. A power primer. Psychol. Bull. 112, 155–159 (1992).CAS 
PubMed 
Article 

Google Scholar 
49.Klein, S. L. Parasite manipulation of the proximate mechanisms that mediate social behavior in vertebrates. Physiol. Behav. 79, 441–449 (2003).CAS 
PubMed 
Article 

Google Scholar 
50.Poulin, R. in Advances in the Study of Behavior Vol. 41 (eds Mitani, J. et al.) 151–186 (Elsevier, 2010).51.Clancey, E. & Byers, J. A. The definition and measurement of individual condition in evolutionary studies. Ethology 120, 845–854 (2014).Article 

Google Scholar 
52.Wilgers, D. J. & Hebets, E. A. in Animal Signaling and Function: An Integrative Approach (eds Irschick, D. J. et al.) 229–252 (John Wiley & Sons, 2015).53.Řežucha, R. & Reichard, M. Strategic exploitation of fluctuating asymmetry in male Endler’s guppy courtship displays is modulated by social environment. J. Evol. Biol. 28, 356–367 (2015).PubMed 
Article 

Google Scholar 
54.Oliveira, R. F., Taborsky, M. & Brockmann, H. J. Alternative Reproductive Tactics: An Integrative Approach (Cambridge Univ. Press, 2008).55.Gray, D. A. Female house crickets, Acheta domesticus, prefer the chirps of large males. Anim. Behav. 54, 1553–1562 (1997).CAS 
PubMed 
Article 

Google Scholar 
56.Lubanga, U., Peters, R. & Steinbauer, M. Substrate-borne vibrations of male psyllids vary with body size and age but females are indifferent. Anim. Behav. 120, 173–182 (2016).Article 

Google Scholar 
57.Ah‐King, M. & Gowaty, P. A. A conceptual review of mate choice: stochastic demography, within‐sex phenotypic plasticity, and individual flexibility. Ecol. Evol. 6, 4607–4642 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
58.Ouzzani, M., Hammady, H., Fedorowicz, Z. & Elmagarmid, A. Rayyan—a web and mobile app for systematic reviews. Syst. Rev. 5, 210 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
59.Adamo, S. A., Kovalko, I., Easy, R. H. & Stoltz, D. A viral aphrodisiac in the cricket Gryllus texensis. J. Exp. Biol. 217, 1970–1976 (2014).PubMed 
Article 

Google Scholar 
60.Aguilar, T. M., Maia, R., Santos, E. S. A. & Macedo, R. H. Parasite levels in blue-black grassquits correlate with male displays but not female mate preference. Behav. Ecol. 19, 292–301 (2008).Article 

Google Scholar 
61.Ahtiainen, J. J., Alataio, R. V., Mappes, J. & Vertainen, L. Fluctuating asymmetry and sexual performance in the drumming wolf spider Hygrolycosa rubrofasciata. Ann. Zool. Fenn. 40, 281–292 (2003).
Google Scholar 
62.Ahtiainen, J. J., Alatalo, R. V., Kortet, R. & Rantala, M. J. Immune function, dominance and mating success in drumming male wolf spiders Hygrolycosa rubrofasciata. Behav. Ecol. Sociobiol. 60, 826–832 (2006).Article 

Google Scholar 
63.Alonso, J. C., Magana, M., Martin, C. A. & Palacin, C. Sexual traits as quality indicators in lekking male great bustards. Ethology 116, 1084–1098 (2010).Article 

Google Scholar 
64.Alonso, J. C., Magana, M., Palacin, C. & Martin, C. A. Correlates of male mating success in great bustard leks: the effects of age, weight, and display effort. Behav. Ecol. Sociobiol. 64, 1589–1600 (2010).Article 

Google Scholar 
65.Amorim, M. C. P. & Almada, V. C. The outcome of male–male encounters affects subsequent sound production during courtship in the cichlid fish Oreochromis mossambicus. Anim. Behav. 69, 595–601 (2005).Article 

Google Scholar 
66.Amorim, M. C. P. & Neves, A. S. M. Acoustic signalling during courtship in the painted goby, Pomatoschistus pictus. J. Mar. Biol. Assoc. UK 87, 1017–1023 (2007).Article 

Google Scholar 
67.Amorim, M. C. P. et al. Painted gobies sing their quality out loud: acoustic rather than visual signals advertise male quality and contribute to mating success. Funct. Ecol. 27, 289–298 (2013).Article 

Google Scholar 
68.Amorim, M. C. P. et al. Lusitanian toadfish song reflects male quality. J. Exp. Biol. 213, 2997–3004 (2010).PubMed 
Article 

Google Scholar 
69.Amundsen, T. & Forsgren, E. Male preference for colourful females affected by male size in a marine fish. Behav. Ecol. Sociobiol. 54, 55–64 (2003).Article 

Google Scholar 
70.An, D. & Waldman, B. Enhanced call effort in Japanese tree frogs infected by amphibian chytrid fungus. Biol. Lett. https://doi.org/10.1098/rsbl.2016.0018 (2016).71.Andersson, S. Costs of sexual advertising in the lekking Jackson’s Widowbird. Condor 96, 1–10 (1994).Article 

Google Scholar 
72.Andrade, M. C. B. & Mason, A. C. Male condition, female choice, and extreme variation in repeated mating in a scaly cricket, Ornebius aperta (Orthoptera: Gryllidae: Mogoplistinae). J. Insect Behav. 13, 483–497 (2000).Article 

Google Scholar 
73.Anichini, M., Frommolt, K. H. & Lehmann, G. U. C. To compete or not to compete: bushcricket song plasticity reveals male body condition and rival distance. Anim. Behav. 142, 59–68 (2018).Article 

Google Scholar 
74.Arak, A. Female mate selection in the natterjack toad: active choice or passive atraction? Behav. Ecol. Sociobiol. 22, 317–327 (1988).
Google Scholar 
75.Arvidsson, B. L. & Neergaard, R. Mate choice in the willow warbler—a field experiment. Behav. Ecol. Sociobiol. 29, 225–229 (1991).Article 

Google Scholar 
76.Atagan, Y. & Forstmeier, W. Protein supplementation decreases courtship rate in the zebra finch. Anim. Behav. 83, 69–74 (2012).Article 

Google Scholar 
77.Backwell, P. R. Y., Jennions, M. D., Christy, J. H. & Schober, U. Pillar building in the fiddler-crab Uca beebei—evidence for a condition dependent ornament. Behav. Ecol. Sociobiol. 36, 185–192 (1995).Article 

Google Scholar 
78.Bakker, T. C. M. & Milinski, M. Sequential female choice and the previous male effect in sticklebacks. Behav. Ecol. Sociobiol. 29, 205–210 (1991).Article 

Google Scholar 
79.Becker, L. J. S., Aspbury, A. S. & Gabor, C. R. Body size dependent male sexual behavior in a natural population of sailfin mollies (Poecilia latipinna). Am. Midl. Nat. 167, 366–372 (2012).Article 

Google Scholar 
80.Bee, M. A. et al. Assessing acoustic signal variability and the potential for sexual selection and social recognition in boreal chorus frogs (Pseudacris maculata). Ethology 116, 564–576 (2010).Article 

Google Scholar 
81.Beeler, A. E., Rauter, C. M. & Moore, A. J. Pheromonally mediated mate attraction by males of the burying beetle Nicrophorus orbicollis: alternative calling tactics conditional on both intrinsic and extrinsic factors. Behav. Ecol. 10, 578–584 (1999).Article 

Google Scholar 
82.Bertram, S. M. & Bowen, M. Field cricket species differences in the temporal patterns of long-distance mate attraction signals. Ethology 112, 850–857 (2006).Article 

Google Scholar 
83.Bertram, S. M., Whattam, E. M., Visanuvimol, L., Bennett, R. & Lauzon, C. Phosphorus availability influences cricket mate attraction displays. Anim. Behav. 77, 525–530 (2009).Article 

Google Scholar 
84.Birkhead, T. R., Fletcher, F. & Pellatt, E. J. Sexual selection in the zebra finch Taeniopygia guttata: condition, sex traits and immune capacity. Behav. Ecol. Sociobiol. 44, 179–191 (1998).Article 

Google Scholar 
85.Biro, P. A., Fanson, K. V. & Santostefano, F. Stress-induced peak (but not resting) metabolism correlates with mating display intensity in male guppies. Ecol. Evol. 6, 6537–6545 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
86.Bolund, E., Martin, K., Kempenaers, B. & Forstmeier, W. Inbreeding depression of sexually selected traits and attractiveness in the zebra finch. Anim. Behav. 79, 947–955 (2010).Article 

Google Scholar 
87.Bolund, E., Schielzeth, H. & Forstmeier, W. No heightened condition dependence of zebra finch ornaments—a quantitative genetic approach. J. Evol. Biol. 23, 586–597 (2010).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
88.Bosholn, M., Fecchio, A., Silveira, P., Braga, E. M. & Anciaes, M. Effects of avian malaria on male behaviour and female visitation in lekking blue-crowned manakins. J. Avian Biol. 47, 457–465 (2016).Article 

Google Scholar 
89.Brandt, L. S. E., Ludwar, B. C. & Greenfield, M. D. Co-occurrence of preference functions and acceptance thresholds in female choice: mate discrimination in the lesser wax moth. Ethology 111, 609–625 (2005).Article 

Google Scholar 
90.Briggs, V. S. Call trait variation in Morelett’s tree frog, Agalychnis moreletii, of Belize. Herpetologica 66, 241–249 (2010).Article 

Google Scholar 
91.Buchanan, K. L., Catchpole, C. K., Lewis, J. W. & Lodge, A. Song as an indicator of parasitism in the sedge warbler. Anim. Behav. 57, 307–314 (1999).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
92.Buchinger, T. J. et al. Increased pheromone signaling by small male sea lamprey has distinct effects on female mate search and courtship. Behav. Ecol. Sociobiol. 71, 155 (2017).93.Callander, S., Jennions, M. D. & Backwell, P. R. Y. The effect of claw size and wave rate on female choice in a fiddler crab. J. Ethol. 30, 151–155 (2012).Article 

Google Scholar 
94.Candolin, U. & Salesto, T. Does competition allow male mate choosiness in threespine sticklebacks? Am. Nat. 173, 273–277 (2009).PubMed 
Article 
PubMed Central 

Google Scholar 
95.Castellano, S., Rosso, A., Doglio, S. & Giacoma, C. Body size and calling variation in the green toad (Bufo viridis). J. Zool. 248, 83–90 (1999).Article 

Google Scholar 
96.Chiswell, R., Girard, M., Fricke, C. & Kasumovic, M. M. Prior mating success can affect allocation towards future sexual signaling in crickets. PeerJ 2, e657 (2014).PubMed 
PubMed Central 
Article 

Google Scholar 
97.Churchill, E. R., Dytham, C. & Thom, M. D. F. Differing effects of age and starvation on reproductive performance in Drosophila melanogaster. Sci. Rep. 9, 2167 (2019).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
98.Clark, D. C., DeBano, S. J. & Moore, A. J. The influence of environmental quality on sexual selection in Nauphoeta cinerea (Dictyoptera: Blaberidae). Behav. Ecol. 8, 46–53 (1997).Article 

Google Scholar 
99.Clark, D. C. & Moore, A. J. Social communication in the Madagascar hissing cockroach—features of male courtship hisses and a comparison of courtship and agonistic hisses. Behaviour 132, 401–417 (1995).Article 

Google Scholar 
100.Clayton, D. H. Mate choice in experimentally parasitized rock doves: lousy males lose. Am. Zool. 30, 251–262 (1990).Article 

Google Scholar 
101.Cobb, M., Connolly, K. & Burnet, B. The relationship between locomotor activity and courtship in the melanogaster species sub-group of Drosophila. Anim. Behav. 35, 705–713 (1987).Article 

Google Scholar 
102.Cordes, N. et al. Larval food composition affects courtship song and sperm expenditure in a lekking moth. Ecol. Entomol. 40, 34–41 (2015).Article 

Google Scholar 
103.Cornuau, J. H., Schmeller, D. S., Courtois, E. A., Jolly, T. & Loyau, A. It takes two to tango: relative influence of male and female identity and morphology on complex courtship display in a newt species. Ethology 121, 218–226 (2015).Article 

Google Scholar 
104.Costa, F. J. V. & Macedo, R. H. Coccidian oocyst parasitism in the blue-black grassquit: influence on secondary sex ornaments and body condition. Anim. Behav. 70, 1401–1409 (2005).Article 

Google Scholar 
105.Crocker-Buta, S. P. & Leary, C. J. Hormonal and social correlates of courtship signal quality and behaviour in male green treefrogs. Anim. Behav. 146, 13–22 (2018).Article 

Google Scholar 
106.da Rocha, S. M. C., Lima, A. P. & Kaefer, I. L. Territory size as a main driver of male-mating success in an Amazonian nurse frog (Allobates paleovarzensis, Dendrobatoidea). Acta Ethol. 21, 51–57 (2018).Article 

Google Scholar 
107.David, M., Auclair, Y., Dall, S. R. X. & Cezilly, F. Pairing context determines condition-dependence of song rate in a monogamous passerine bird. Proc. R. Soc. B 280, 20122177 (2013).PubMed 
Article 

Google Scholar 
108.Deb, R., Bhattacharya, M. & Balakrishnan, R. Females of a tree cricket prefer larger males but not the lower frequency male calls that indicate large body size. Anim. Behav. 84, 137–149 (2012).Article 

Google Scholar 
109.Devigili, A., Kelley, J. L., Pilastro, A. & Evans, J. P. Expression of pre- and postcopulatory traits under different dietary conditions in guppies. Behav. Ecol. 24, 740–749 (2013).Article 

Google Scholar 
110.Drayton, J. M., Hunt, J., Brooks, R. & Jennions, M. D. Sounds different: inbreeding depression in sexually selected traits in the cricket Teleogryllus commodus. J. Evol. Biol. 20, 1138–1147 (2007).CAS 
PubMed 
Article 

Google Scholar 
111.Drayton, J. M., Milner, R. N. C., Hunt, J. & Jennions, M. D. Inbreeding and advertisement calling in the cricket Teleogryllus commodus: laboratory and field experiments. Evolution 64, 3069–3083 (2010).PubMed 

Google Scholar 
112.Droney, D. C. Environmental influences on male courtship and implications for female choice in a lekking Hawaiian Drosophila. Anim. Behav. 51, 821–830 (1996).Article 

Google Scholar 
113.Droney, D. C. The influence of the nutritional content of the adult male diet on testis mass, body condition and courtship vigour in a Hawaiian Drosophila. Funct. Ecol. 12, 920–928 (1998).Article 

Google Scholar 
114.Duffield, K. R. et al. Age-dependent variation in the terminal investment threshold in male crickets. Evolution 72, 578–589 (2018).Article 

Google Scholar 
115.Eastwood, L. & Burnet, B. Courtship latency in male Drosophila melanogaster. Behav. Genet. 7, 359–372 (1977).CAS 
PubMed 
Article 

Google Scholar 
116.Engqvist, L. & Sauer, K. P. Influence of nutrition on courtship and mating in the scorpionfly Panorpa cognata (Mecoptera, insecta). Ethology 109, 911–928 (2003).Article 

Google Scholar 
117.Forrest, T. G. et al. Mate choice in ground crickets (Gryllidae, Nemoiinae). Fla. Entomol. 74, 74–80 (1991).Article 

Google Scholar 
118.Galeotti, P. et al. Courtship displays and mounting calls are honest, condition-dependent signals that influence mounting success in Hermann’s tortoises. Can. J. Zool. 83, 1306–1313 (2005).Article 

Google Scholar 
119.Gibson, J. S. & Uetz, G. W. Effect of rearing environment and food availability on seismic signalling in male wolf spiders (Araneae: Lycosidae). Anim. Behav. 84, 85–92 (2012).Article 

Google Scholar 
120.Gibson, R. M. Relationships between blood parasites, mating success and phenotypic cues in male sage grouse Centrocercus urophasianus. Am. Zool. 30, 271–278 (1990).Article 

Google Scholar 
121.Gilbert, R., Karp, R. D. & Uetz, G. W. Effects of juvenile infection on adult immunity and secondary sexual characters in a wolf spider. Behav. Ecol. 27, 946–954 (2016).Article 

Google Scholar 
122.Gilbert, R. & Uetz, G. W. Courtship and male ornaments as honest indicators of immune function. Anim. Behav. 117, 97–103 (2016).Article 

Google Scholar 
123.Given, M. Interrelationships among calling effort, growth rate, and chorus tenure in Bufo fowleri. Copeia 2002, 979–987 (2002).Article 

Google Scholar 
124.Greenspan, S. E., Roznik, E. A., Schwarzkopf, L., Alford, R. A. & Pike, D. A. Robust calling performance in frogs infected by a deadly fungal pathogen. Ecol. Evol. 6, 5964–5972 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
125.Gumulka, M. & Rozenboim, I. Effect of the age of ganders on reproductive behavior and fertility in a competitive mating structure. Ann. Anim. Sci. 17, 733–746 (2017).Article 

Google Scholar 
126.Hankison, S. J. & Ptacek, M. B. Within and between species variation in male mating behaviors in the Mexican sailfin mollies Poecilia velifera and P. petenensis. Ethology 113, 802–812 (2007).Article 

Google Scholar 
127.Harrison, S. J., Thomson, I. R., Grant, C. M. & Bertram, S. M. Calling, courtship, and condition in the fall field cricket, Gryllus pennsylvanicus. PLoS ONE 8, e60356 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
128.Hausfater, G., Gerhardt, H. C. & Klump, G. M. Parasites and mate choice in gray treefrogs, Hyla versicolor. Am. Zool. 30, 299–311 (1990).Article 

Google Scholar 
129.Hay, D. E. & McPhail, J. D. Courtship behaviour of male threespine sticklebacks (Gasterosteus aculeatus) from old and new hybrid zones. Behaviour 137, 1047–1063 (2000).Article 

Google Scholar 
130.Head, M. L., Fox, R. J. & Barber, I. Environmental change mediates mate choice for an extended phenotype, but not for mate quality. Evolution 71, 135–144 (2017).PubMed 
Article 

Google Scholar 
131.Hegde, S. N. & Krishna, M. S. Size-assortative mating in Drosophila malerkotliana. Anim. Behav. 54, 419–426 (1997).CAS 
PubMed 
Article 

Google Scholar 
132.Hegyi, G. et al. Nutritional correlates and mate acquisition role of multiple sexual traits in male collared flycatchers. Naturwissenschaften 97, 567–576 (2010).CAS 
PubMed 
Article 

Google Scholar 
133.Henderson, L. J., Brazeal, K. R. & Hahn, T. P. Plumage coloration and social context influence male investment in song. Biol. Lett. 14, 20180300 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
134.Hermann, C. M., Brudermann, V., Zimmermann, H., Vollmann, J. & Sefc, K. M. Female preferences for male traits and territory characteristics in the cichlid fish Tropheus moorii. Hydrobiologia 748, 61–74 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
135.Hoefler, C. D., Carlascio, A. L., Persons, M. H. & Rypstra, A. L. Male courtship repeatability and potential indirect genetic benefits in a wolf spider. Anim. Behav. 78, 183–188 (2009).Article 

Google Scholar 
136.Hoefler, C. D., Moore, J. A., Reynolds, K. T. & Rypstra, A. L. The effect of experience on male courtship and mating behaviors in a cellar spider. Am. Midl. Nat. 163, 255–268 (2010).Article 

Google Scholar 
137.Hoefler, C. D., Persons, M. H. & Rypstra, A. L. Evolutionarily costly courtship displays in a wolf spider: a test of viability indicator theory. Behav. Ecol. 19, 974–979 (2008).Article 

Google Scholar 
138.Hoileitner, M., Nechtelberger, H. & Hoi, H. Song rate as a signal for nest-site quality in blackcaps (Sylvia atricapilla). Behav. Ecol. Sociobiol. 37, 399–405 (1995).Article 

Google Scholar 
139.Holzer, B., Jacot, A. & Brinkhof, M. W. G. Condition-dependent signaling affects male sexual attractiveness in field crickets, Gryllus campestris. Behav. Ecol. 14, 353–359 (2003).Article 

Google Scholar 
140.Honarmand, M., Riebel, K. & Naguib, M. Nutrition and peer group composition in early adolescence: impacts on male song and female preference in zebra finches. Anim. Behav. 107, 147–158 (2015).Article 

Google Scholar 
141.Houde, A. E. & Torio, A. J. Effect of parasitic infection on male color pattern and female choice in guppies. Behav. Ecol. 3, 346–351 (1992).Article 

Google Scholar 
142.Howard, R. D. & Young, J. R. Individual variation in male vocal traits and female mating preferences in Bufo americanus. Anim. Behav. 55, 1165–1179 (1998).CAS 
PubMed 
Article 

Google Scholar 
143.Hughes, A. L. Male size, mating success, and mating strategy in the mosquitofish Gambusia affinis (Poeciliidae). Behav. Ecol. Sociobiol. 17, 271–278 (1985).Article 

Google Scholar 
144.Humfeld, S. C. Condition-dependent signaling and adoption of mating tactics in an amphibian with energetic displays. Behav. Ecol. 24, 859–870 (2013).Article 

Google Scholar 
145.Jacot, A., Scheuber, H. & Brinkhof, M. W. G. Costs of an induced immune response on sexual display and longevity in field crickets. Evolution 58, 2280–2286 (2004).PubMed 
Article 

Google Scholar 
146.Jacot, A., Scheuber, H., Holzer, B., Otti, O. & Brinkhof, M. W. G. Diel variation in a dynamic sexual display and its association with female mate-searching behaviour. Proc. R. Soc. B 275, 579–585 (2008).PubMed 
Article 

Google Scholar 
147.Jennions, M. D. Tibial coloration, fluctuating asymmetry and female choice behaviour in the damselfly Platycypha caligata. Anim. Behav. 55, 1517–1528 (1998).CAS 
PubMed 
Article 

Google Scholar 
148.Jha, N. A. & Kumar, V. Protein-rich food does not affect singing behaviour and song quality in adult zebra finches, Taeniopygia guttata. Curr. Sci. 111, 1693–1696 (2016).Article 

Google Scholar 
149.Jiguet, F. & Bretagnolle, V. Sexy males and choosy females on exploded leks: correlates of male attractiveness in the Little Bustard. Behav. Process. 103, 246–255 (2014).Article 

Google Scholar 
150.Jones, K. M., Monaghan, P. & Nager, R. G. Male mate choice and female fecundity in zebra finches. Anim. Behav. 62, 1021–1026 (2001).Article 

Google Scholar 
151.Joshi, A. M., Narayan, E. J. & Gramapurohit, N. P. Interrelationship among steroid hormones, energetics and vocalisation in the Bombay night frog (Nyctibatrachus humayuni). Gen. Comp. Endocrinol. 246, 142–149 (2017).CAS 
PubMed 
Article 

Google Scholar 
152.Joyce, A. L., Bernal, J. S., Vinson, S. B. & Lomeli-Flores, R. Influence of adult size on mate choice in the solitary and gregarious parasitoids, Cotesia marginiventris and Cotesia flavipes. J. Insect Behav. 22, 12–28 (2009).Article 

Google Scholar 
153.Junca, F. A. et al. Advertisement call of species of the genus Frostius Cannatella 1986 (Anura: Bufonidae). Acta Herpetol. 7, 189–201 (2012).
Google Scholar 
154.Kaefer, I. L. & Lima, A. P. Sexual signals of the Amazonian frog Allobates paleovarzensis: geographic variation and stereotypy of acoustic traits. Behaviour 149, 15–33 (2012).Article 

Google Scholar 
155.Kahn, A. T., Dolstra, T., Jennions, M. D. & Backwell, P. R. Y. Strategic male courtship effort varies in concert with adaptive shifts in female mating preferences. Behav. Ecol. 24, 906–913 (2013).Article 

Google Scholar 
156.Karl, I., Heuskin, S. & Fischer, K. Dissecting the mechanisms underlying old male mating advantage in a butterfly. Behav. Ecol. Sociobiol. 67, 837–849 (2013).Article 

Google Scholar 
157.Kaspi, R., Taylor, P. W. & Yuval, B. Diet and size influence sexual advertisement and copulatory success of males in Mediterranean fruit fly leks. Ecol. Entomol. 25, 279–284 (2000).Article 

Google Scholar 
158.Kennedy, C. E. J., Endler, J. A., Poynton, S. L. & McMinn, H. Parasite load predicts mate choice in guppies. Behav. Ecol. Sociobiol. 21, 291–295 (1987).Article 

Google Scholar 
159.Ketola, T., Kortet, R. & Kotiaho, J. S. Endurance in exercise is associated with courtship call rate in decorated crickets, Gryllodes sigillatus. Evol. Ecol. Res. 11, 1131–1139 (2009).
Google Scholar 
160.Ketola, T. & Kotiaho, J. S. Inbreeding, energy use and sexual signaling. Evol. Ecol. 24, 761–772 (2010).Article 

Google Scholar 
161.Kim, T. W. & Choe, J. C. The effect of food availability on the semilunar courtship rhythm in the fiddler crab Uca lactea (de Haan) (Brachyura: Ocypodidae). Behav. Ecol. Sociobiol. 54, 210–217 (2003).Article 

Google Scholar 
162.Kim, T. W., Sakamoto, K., Henmi, Y. & Choe, J. C. To court or not to court: reproductive decisions by male fiddler crabs in response to fluctuating food availability. Behav. Ecol. Sociobiol. 62, 1139–1147 (2008).Article 

Google Scholar 
163.King, B. H., Saporito, K. B., Ellison, J. H. & Bratzke, R. M. Unattractiveness of mated females to males in the parasitoid wasp Spalangia endius. Behav. Ecol. Sociobiol. 57, 350–356 (2005).Article 

Google Scholar 
164.Kitsunezuka, K., Okutani-Akamatsu, Y., Watanabe, T. & Oku, K. Effects of male age on the mating behavior of both sexes in the sorghum plant bug, Stenotus rubrovittatus (Hemiptera: Miridae). Appl. Entomol. Zool. 48, 73–77 (2013).Article 

Google Scholar 
165.Knapp, R. A. Influence of energy reserves on the expression of a secondary sexual trait in male bicolor damselfish, Stegastes partitus. Bull. Mar. Sci. 57, 672–681 (1995).
Google Scholar 
166.Kodric-Brown, A. Dietary carotenoids and male mating success in the guppy: an environmental component to female choice. Behav. Ecol. Sociobiol. 25, 393–401 (1989).Article 

Google Scholar 
167.Kolluru, G. R., Bertram, S. M., China, E. H., Dunmeyer, C. V. & Graves, J. S. Mating behavior and its morphological correlates in two color morphs of Girardinus metallicus (Pisces: Poeciliidae), a species previously thought not to exhibit courtship display. Behav. Process. 106, 44–52 (2014).Article 

Google Scholar 
168.Kotiaho, J. S. Testing the assumptions of conditional handicap theory: costs and condition dependence of a sexually selected trait. Behav. Ecol. Sociobiol. 48, 188–194 (2000).Article 

Google Scholar 
169.Kotiaho, J. S. Sexual selection and condition dependence of courtship display in three species of horned dung beetles. Behav. Ecol. 13, 791–799 (2002).Article 

Google Scholar 
170.Kotiaho, J. S., Alatalo, R. V., Mappes, J. & Parri, S. Sexual signalling and viability in a wolf spider (Hygrolycosa rubrofasciata): measurements under laboratory and field conditions. Behav. Ecol. Sociobiol. 46, 123–128 (1999).Article 

Google Scholar 
171.Kotiaho, J. S., Simmons, L. W. & Tomkins, J. L. Towards a resolution of the lek paradox. Nature 410, 684–686 (2001).CAS 
PubMed 
Article 

Google Scholar 
172.Krishna, M. S. & Hegde, S. N. Influence of body size in mating success in three sympatric species of Drosophila. Ital. J. Zool. 70, 47–52 (2003).Article 

Google Scholar 
173.Kuczynski, M. C., Bello-DeOcampo, D. & Getty, T. No evidence of terminal investment in the gray treefrog (Hyla versicolor): older males do not signal at greater effort. Copeia 103, 530–535 (2015).Article 

Google Scholar 
174.Kuczynski, M. C., Storks, L., Gering, E. & Getty, T. Male treefrogs in low condition resume signaling faster following simulated predator attack. Behav. Ecol. Sociobiol. 70, 347–355 (2016).Article 

Google Scholar 
175.Kuriwada, T. Horn length is not correlated with calling efforts in the horn-headed cricket Loxoblemmus doenitzi (Orthoptera: Gryllidae). Entomol. Sci. 19, 228–232 (2016).Article 

Google Scholar 
176.Kuriwada, T. & Kasuya, E. Age-dependent changes in calling effort in the bell cricket Meloimorpha japonica. J. Ethol. 29, 99–105 (2011).Article 

Google Scholar 
177.Leary, C. J., Lippincott, J., Harris, S. & Hawkins, D. L. A test of the energetics-hormone vocalization model in the green treefrog. Gen. Comp. Endocrinol. 213, 32–39 (2015).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
178.Lehtonen, T. K., Svensson, P. A. & Wong, B. B. M. The influence of recent social experience and physical environment on courtship and male aggression. BMC Evol. Biol. 16, 18 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
179.Lehtonen, T. K., Svensson, P. A. & Wong, B. B. M. Aggressive desert goby males also court more, independent of the physiological demands of salinity. Sci. Rep. 8, 9352 (2018).180.Lode, T. & Le Jacques, D. Influence of advertisement calls on reproductive success in the male midwife toad Alytes obstetricans. Behaviour 140, 885–898 (2003).Article 

Google Scholar 
181.Lomborg, J. P. & Toft, S. Nutritional enrichment increases courtship intensity and improves mating success in male spiders. Behav. Ecol. 20, 700–708 (2009).Article 

Google Scholar 
182.Lopez, P. T. & Narins, P. M. Mate choice in the neotropical frog, Eleutherodactylus coqui. Anim. Behav. 41, 757–772 (1991).Article 

Google Scholar 
183.Lynn, S. E., Stamplis, T. B., Barrington, W. T., Weida, N. & Hudak, C. A. Food, stress, and reproduction: short-term fasting alters endocrine physiology and reproductive behavior in the zebra finch. Horm. Behav. 58, 214–222 (2010).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
184.Magellan, K., Pettersson, L. B. & Magurran, A. E. Quantifying male attractiveness and mating behaviour through phenotypic size manipulation in the Trinidadian guppy, Poecilia reticulata. Behav. Ecol. Sociobiol. 58, 366–374 (2005).Article 

Google Scholar 
185.Magoolagan, L., Mawby, P. J., Whitehead, F. A. & Sharp, S. P. The effect of early life conditions on song traits in male dippers (Cinclus cinclus). PLoS ONE 13, e0205101 (2018).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
186.Manica, L. T., Maia, R., Dias, A., Podos, J. & Macedoc, R. H. Vocal output predicts territory quality in a neotropical songbird. Behav. Process. 109, 21–26 (2014).Article 

Google Scholar 
187.Mariette, M., Kelley, J. L., Brooks, R. & Evans, J. P. The effects of inbreeding on male courtship behaviour and coloration in guppies. Ethology 112, 807–814 (2006).Article 

Google Scholar 
188.Mateos, C. & Carranza, J. Effects of male dominance and courtship display on female choice in the ring-necked pheasant. Behav. Ecol. Sociobiol. 45, 235–244 (1999).Article 

Google Scholar 
189.Matsuo, T. Effect of social condition on behavioral development during early adult phase in Drosophila prolongata. J. Ethol. 36, 15–22 (2018).PubMed 
Article 
PubMed Central 

Google Scholar 
190.McAuley, E. M. & Bertram, S. M. Field crickets compensate for unattractive static long-distance call components by increasing dynamic signalling effort. PLoS ONE 11, e0167311 (2016).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
191.McCullough, E. L. & Simmons, L. W. Selection on male physical performance during male–male competition and female choice. Behav. Ecol. 27, 1288–1295 (2016).Article 

Google Scholar 
192.McLean, M. J., Bishop, P. J., Hero, J. M. & Nakagawa, S. Assessing the information content of calls of Litoria chloris: quality signalling versus individual recognition. Aust. J. Zool. 60, 120–126 (2012).Article 

Google Scholar 
193.McNeil, G. V., Friesen, C. N., Gray, S. M., Aldredge, A. & Chapman, L. J. Male colour variation in a eurytopic African cichlid: the role of diet and hypoxia. Biol. J. Linn. Soc. 118, 551–568 (2016).Article 

Google Scholar 
194.Memmott, R. & Briffa, M. Exaggerated displays do not improve mounting success in male seaweed flies Fucellia tergina (Diptera: Anthomyiidae). Behav. Process. 120, 73–79 (2015).Article 

Google Scholar 
195.Milazzo, M. et al. Ocean acidification affects fish spawning but not paternity at CO2 seeps. Proc. R. Soc. B 283, 20161021 (2016).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
196.Morales, M. B., Alonso, J. C., Martin, C., Martin, E. & Alonso, J. Male sexual display and attractiveness in the great bustard Otis tarda: the role of body condition. J. Ethol. 21, 51–56 (2003).Article 

Google Scholar 
197.Morris, M. R. Female choice of large males in the treefrog Hyla ebraccata. J. Zool. 223, 371–378 (1991).Article 

Google Scholar 
198.Morris, M. R., Rios-Cardenas, O. & Darrah, A. Male mating tactics in the northern mountain swordtail fish (Xiphophorus nezahualcoyotl): coaxing and coercing females to mate. Ethology 114, 977–988 (2008).Article 

Google Scholar 
199.Muramatsu, D. The function of the four types of waving display in Uca lactea: effects of audience, sand structure, and body size. Ethology 117, 408–415 (2011).Article 

Google Scholar 
200.Murphy, C. G. Nightly timing of chorusing by male barking treefrogs (Hyla gratiosa): the influence of female arrival and energy. Copeia 1999, 333–347 (1999).Article 

Google Scholar 
201.Naguib, M., Heim, C. & Gil, D. Early developmental conditions and male attractiveness in zebra finches. Ethology 114, 255–261 (2008).Article 

Google Scholar 
202.O’Hanlon, J. C., Wignall, A. E. & Herberstein, M. E. Short and fast vs long and slow: age changes courtship in male orb-web spiders (Argiope keyserlingi). Sci. Nat. 105, 3 (2018).Article 
CAS 

Google Scholar 
203.Ohata, M., Wada, K. & Koga, T. Waving display by male Scopimera globosa (Brachyura: Ocypodoidea) as courtship behavior. J. Crustac. Biol. 25, 637–639 (2005).Article 

Google Scholar 
204.Olsson, K. H., Kvarnemo, C. & Svensson, O. Relative costs of courtship behaviours in nest-building sand gobies. Anim. Behav. 77, 541–546 (2009).Article 

Google Scholar 
205.Ortiz-Santaliestra, M. E., Marco, A., Fernández-Benéitez, M. J. & Lizana, M. Alteration of courtship behavior because of water acidification and minor effect of ammonium nitrate in the Iberian newt (Lissotriton boscai). Environ. Toxicol. Chem. 28, 1500–1505 (2009).CAS 
PubMed 
Article 

Google Scholar 
206.Papadopoulos, N. T., Katsoyannos, B. I., Kouloussis, N. A., Economopoulos, A. P. & Carrey, J. R. Effect of adult age, food, and time of day on sexual calling incidence of wild and mass-reared Ceratitis capitata males. Entomol. Exp. Appl. 89, 175–182 (1998).Article 

Google Scholar 
207.Pariser, E. C., Mariette, M. M. & Griffith, S. C. Artificial ornaments manipulate intrinsic male quality in wild-caught zebra finches (Taeniopygia guttata). Behav. Ecol. 21, 264–269 (2010).Article 

Google Scholar 
208.Partridge, L., Ewing, A. & Chandler, A. Male size and mating success in Drosophila melanogaster: the roles of male and female behaviour. Anim. Behav. 35, 555–562 (1987).Article 

Google Scholar 
209.Passmore, N. I., Bishop, P. J. & Caithness, N. Calling behavior influences mating success in male painted reed frogs, Hyperolius marmoratus. Ethology 92, 227–241 (1992).Article 

Google Scholar 
210.Pedroso, S. S., Barber, I., Svensson, O., Fonseca, P. J. & Amorim, M. C. P. Courtship sounds advertise species identity and male quality in sympatric Pomatoschistus spp. gobies. PLoS ONE 8, e64620 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
211.Pelabon, C. et al. Do microsporidian parasites affect courtship in two-spotted gobies? Mar. Biol. 148, 189–196 (2005).Article 

Google Scholar 
212.Pellitteri-Rosa, D., Sacchi, R., Galeotti, P., Marchesi, M. & Fasola, M. Courtship displays are condition-dependent signals that reliably reflect male quality in Greek tortoises, Testudo graeca. Chelonian Conserv. Biol. 10, 10–17 (2011).Article 

Google Scholar 
213.Perezlachaud, G. & Campan, M. Influence of previous sexual experience and postemergence rearing conditions on the mating-behavior of Chryseida bennetti. Entomol. Exp. Appl. 76, 163–170 (1995).Article 

Google Scholar 
214.Poole, K. G. & Murphy, C. G. Preferences of female barking treefrogs, Hyla gratiosa, for larger males: univariate and composite tests. Anim. Behav. 73, 513–524 (2007).Article 

Google Scholar 
215.Prathibha, M., Krishna, M. S. & Jayaramu, S. C. Male age influence on male reproductive success in Drosophila ananassae (Diptera: Drosophilidae). Ital. J. Zool. 78, 168–173 (2011).Article 

Google Scholar 
216.Pruett-jones, S. G., Pruett-jones, M. A. & Jones, H. I. Parasites and sexual selection in birds of paradise. Am. Zool. 30, 287–298 (1990).Article 

Google Scholar 
217.Pryke, S. R. & Andersson, S. Experimental evidence for female choice and energetic costs of male tail elongation in red-collared widowbirds. Biol. J. Linn. Soc. 86, 35–43 (2005).Article 

Google Scholar 
218.Ptacek, M. B. & Travis, J. Inter-population variation in male mating behaviours in the sailfin mollie, Poecilia latipinna. Anim. Behav. 52, 59–71 (1996).Article 

Google Scholar 
219.Ptacek, M. B. & Travis, J. Mate choice in the sailfin molly, Poecilia latipinna. Evolution 51, 1217–1231 (1997).PubMed 
Article 

Google Scholar 
220.Rahman, M. M., Kelley, J. L. & Evans, J. P. Condition-dependent expression of pre- and postcopulatory sexual traits in guppies. Ecol. Evol. 3, 2197–2213 (2013).PubMed 
PubMed Central 
Article 

Google Scholar 
221.Rahman, M. M., Turchini, G. M., Gasparini, C., Norambuena, F. & Evans, J. P. The expression of pre- and postcopulatory sexually selected traits reflects levels of dietary stress in guppies. PLoS ONE 9, e105856 (2014).PubMed 
PubMed Central 
Article 

Google Scholar 
222.Reifer, M. L., Harrison, S. J. & Bertram, S. M. How dietary protein and carbohydrate influence field cricket development, size and mate attraction signalling. Anim. Behav. 139, 137–146 (2018).Article 

Google Scholar 
223.Rezaei, A., Krishna, M. S. & Santhosh, H. T. Male age affects female mate preference, quantity of accessory gland proteins, and sperm traits and female fitness in D. melanogaster. Zool. Sci. 32, 16–24 (2015).Article 

Google Scholar 
224.Ritchie, M. G., Sunter, D. & Hockham, L. R. Behavioral components of sex role reversal in the tettigoniid bushcricket Ephippiger ephippiger. J. Insect Behav. 11, 481–491 (1998).Article 

Google Scholar 
225.Ritschard, M. & Brumm, H. Zebra finch song reflects current food availability. Evol. Ecol. 26, 801–812 (2012).Article 

Google Scholar 
226.Rodd, F. H. & Sokolowski, M. B. Complex origins of variation in the sexual-behavior of male Trinidadian guppies, Poecilia reticulata—interactions between social-environment, heredity, body-size and age. Anim. Behav. 49, 1139–1159 (1995).Article 

Google Scholar 
227.Rosenthal, M. F. & Hebets, E. A. Temporal patterns of nutrition dependence in secondary sexual traits and their varying impacts on male mating success. Anim. Behav. 103, 75–82 (2015).Article 

Google Scholar 
228.Sadowski, J. A., Grace, J. L. & Moore, A. J. Complex courtship behavior in the striped ground cricket, Allonemobius socius (Orthoptera: Gryllidae): does social environment affect male and female behavior? J. Insect Behav. 15, 69–84 (2002).Article 

Google Scholar 
229.Scheuber, H., Jacot, A. & Brinkhof, M. W. G. Condition dependence of a multicomponent sexual signal in the field cricket Gryllus campestris. Anim. Behav. 65, 721–727 (2003).Article 

Google Scholar 
230.Shakeel, M., He, X. Z., Martin, N. A., Hanan, A. & Wang, Q. Mating behaviour of the European leafminer Scaptomyza flava (Diptera: Drosophilidae). NZ Plant Prot. 63, 108–112 (2010).
Google Scholar 
231.Shelly, T. E., Edu, J. & Pahio, E. Female medflies mate selectively with young males but gain no apparent fitness benefits. J. Insect Behav. 24, 55–66 (2011).Article 

Google Scholar 
232.Shelly, T. E. & Kennelly, S. S. Starvation and the mating success of wild male Mediterranean fruit flies (Diptera: Tephritidae). J. Insect Behav. 16, 171–179 (2003).Article 

Google Scholar 
233.Shuker, D. et al. Mating behavior, sexual selection, and copulatory courtship in a promiscuous beetle. J. Insect Behav. 15, 617–631 (2002).Article 

Google Scholar 
234.Sikkel, P. C. Effects of nest quality on male courtship and female spawning-site choice in an algal-nesting damselfish. Bull. Mar. Sci. 57, 682–689 (1995).
Google Scholar 
235.Sisodia, S. & Singh, B. N. Size dependent sexual selection in Drosophila ananassae. Genetica 121, 207–217 (2004).PubMed 
Article 

Google Scholar 
236.Smit, J. A. H., Loning, H., Ryan, M. J. & Halfwerk, W. Environmental constraints on size-dependent signaling affects mating and rival interactions. Behav. Ecol. 30, 724–732 (2019).Article 

Google Scholar 
237.Snekser, J. L., Leese, J., Ganim, A. & Itzkowitz, M. Caribbean damselfish with varying territory quality: correlated behaviors but not a syndrome. Behav. Ecol. 20, 124–130 (2009).Article 

Google Scholar 
238.Spencer, K. A., Buchanan, K. L., Goldsmith, A. R. & Catchpole, C. K. Song as an honest signal of developmental stress in the zebra finch (Taeniopygia guttata). Horm. Behav. 44, 132–139 (2003).CAS 
PubMed 
Article 

Google Scholar 
239.Spencer, K. A. et al. Developmental stress affects the attractiveness of male song and female choice in the zebra finch (Taeniopygia guttata). Behav. Ecol. Sociobiol. 58, 423–428 (2005).Article 

Google Scholar 
240.Sundin, J., Vossen, L. E., Nilsson-Sköld, H. & Jutfelt, F. No effect of elevated carbon dioxide on reproductive behaviors in the three-spined stickleback. Behav. Ecol. 28, 1482–1491 (2017).Article 

Google Scholar 
241.Suzaki, Y., Katsuki, M., Miyatake, T. & Okada, Y. Relationships among male sexually selected traits in the bean bug, Riptortus pedestris (Heteroptera: Alydidae). Entomol. Sci. 18, 278–282 (2015).Article 

Google Scholar 
242.Takeshita, F., Murai, M., Matsumasa, M. & Henmi, Y. Multimodal signaling in fiddler crab: waving to attract mates is condition-dependent but other sexual signals are not. Behav. Ecol. Sociobiol. 72, 140 (2018).243.Tarano, Z. Variation in male advertisement calls in the neotropical frog Physalaemus enesefae. Copeia 2001, 1064–1072 (2001).Article 

Google Scholar 
244.Taylor, M. I., Turner, G. F., Robinson, R. L. & Stauffer, J. R. Sexual selection, parasites and bower height skew in a bower-building cichlid fish. Anim. Behav. 56, 379–384 (1998).CAS 
PubMed 
Article 

Google Scholar 
245.Tejedo, M. Large male mating advantage in natterjack toads, Bufo calamita: sexual selection or energetic constraints? Anim. Behav. 44, 557–569 (1992).Article 

Google Scholar 
246.Tolle, A. E. & Wagner, W. E. Costly signals in a field cricket can indicate high- or low-quality direct benefits depending upon the environment. Evolution 65, 283–294 (2011).PubMed 
Article 

Google Scholar 
247.Toth, C. A., Santure, A. W., Holwell, G. I., Pattemore, D. E. & Parsons, S. Courtship behaviour and display-site sharing appears conditional on body size in a lekking bat. Anim. Behav. 136, 13–19 (2018).Article 

Google Scholar 
248.Turiegano, E., Monedero, I., Pita, M., Torroja, L. & Canal, I. Effect of Drosophila melanogaster female size on male mating success. J. Insect Behav. 26, 89–100 (2013).Article 

Google Scholar 
249.Van Hout, A. J. M., Pinxten, R., Geens, A. & Eens, M. Non-breeding song rate reflects nutritional condition rather than body condition. PLoS ONE 7, e36547 (2012).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
250.Villarreal, A. E., Godin, J. G. J. & Bertram, S. M. Influence of the operational sex ratio on mutual mate choice in the Jamaican field cricket (Gryllus assimilis): testing the predictions of the switch point theorem. Ethology 124, 816–828 (2018).Article 

Google Scholar 
251.Wacker, S., de Jong, K., Forsgren, E. & Amundsen, T. Large males fight and court more across a range of social environments: an experiment on the two spotted goby Gobiusculus flavescens. J. Fish. Biol. 81, 21–34 (2012).CAS 
PubMed 
Article 

Google Scholar 
252.Wagner, W. E. & Hoback, W. W. Nutritional effects on male calling behaviour in the variable field cricket. Anim. Behav. 57, 89–95 (1999).CAS 
PubMed 
Article 

Google Scholar 
253.Walling, C. A., Stamper, C. E., Salisbury, C. L. & Moore, A. J. Experience does not alter alternative mating tactics in the burying beetle Nicrophorus vespilloides. Behav. Ecol. 20, 153–159 (2009).Article 

Google Scholar 
254.Watson, N. L. & Simmons, L. W. Mate choice in the dung beetle Onthophagus sagittarius: are female horns ornaments? Behav. Ecol. 21, 424–430 (2010).Article 

Google Scholar 
255.Whattam, E. M. & Bertram, S. M. Effects of juvenile and adult condition on long-distance call components in the Jamaican field cricket, Gryllus assimilis. Anim. Behav. 81, 135–144 (2011).Article 

Google Scholar 
256.Wilgers, D. J. & Hebets, E. A. Complex courtship displays facilitate male reproductive success and plasticity in signaling across variable environments. Curr. Zool. 57, 175–186 (2011).Article 

Google Scholar 
257.Wilgers, D. J. & Hebets, E. A. Age-related female mating decisions are condition dependent in wolf spiders. Behav. Ecol. Sociobiol. 66, 29–38 (2012).Article 

Google Scholar 
258.Wilson, A. D. M. et al. Behavioral correlations across activity, mating, exploration, aggression, and antipredator contexts in the European house cricket, Acheta domesticus. Behav. Ecol. Sociobiol. 64, 703–715 (2010).Article 

Google Scholar 
259.Win, A. T., Kojima, W. & Ishikawa, Y. Age-related male reproductive investment in courtship display and nuptial gifts in a moth, Ostrinia scapulalis. Ethology 119, 325–334 (2013).Article 

Google Scholar 
260.Woodhead, A. P. Male age: effect on mating behaviour and success in the cockroach Diploptera punctata. Anim. Behav. 34, 1874–1879 (1986).Article 

Google Scholar 
261.Yamada, K. & Soma, M. Diet and birdsong: short-term nutritional enrichment improves songs of adult Bengalese finch males. J. Avian Biol. 47, 865–870 (2016).Article 

Google Scholar 
262.Yuval, B., Kaspi, R., Shloush, S. & Warburg, M. S. Nutritional reserves regulate male participation in Mediterranean fruit fly leks. Ecol. Entomol. 23, 211–215 (1998).Article 

Google Scholar 
263.Zuk, M. et al. The role of male ornaments and courtship behavior in female mate choice of red jungle fowl. Am. Nat. 136, 459–473 (1990).Article 

Google Scholar 
264.Chargé, R., Saint Jalme, M., Lacroix, F., Cadet, A. & Sorci, G. Male health status, signalled by courtship display, reveals ejaculate quality and hatching success in a lekking species. J. Anim. Ecol. 79, 843–850 (2010).PubMed 

Google Scholar 
265.Lipsey, M. & Wilson, D. Practical Meta-analysis (Sage Publications, 2001).266.Hedges, L. V. & Olkin, I. Statistical Methods for Meta-analysis (Academic Press, 1985).267.Hinchliff, C. E. et al. Synthesis of phylogeny and taxonomy into a comprehensive tree of life. Proc. Natl Acad. Sci. USA 112, 12764–12769 (2015).CAS 
PubMed 
Article 

Google Scholar 
268.R Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020).269.Michonneau, F., Brown, J. W. & Winter, D. J. rotl: an R package to interact with the Open Tree of Life data. Methods Ecol. Evol. 7, 1476–1481 (2016).Article 

Google Scholar 
270.Paradis, E., Claude, J. & Strimmer, K. APE: analyses of phylogenetics and evolution in R language. Bioinformatics 20, 289–290 (2004).CAS 
PubMed 
Article 

Google Scholar 
271.Grafen, A. The phylogenetic regression. Philos. Trans. R. Soc. Lond. B 326, 119–157 (1989).CAS 
Article 

Google Scholar 
272.Tacutu, R. et al. Human Ageing Genomic Resources: integrated databases and tools for the biology and genetics of ageing. Nucleic Acids Res. 41, D1027–D1033 (2012).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
273.Carey, J. & Judge, D. Longevity Records: Life Spans of Mammals, Birds, Amphibians, Reptiles, and Fish (Odense Univ. Press, 2000).274.Höglund, J. & Alatalo, R. V. Leks (Princeton Univ. Press, 2005).275.Viechtbauer, W. Conducting meta-analyses in R with the metafor package. J. Stat. Softw. 36, 1–48 (2010).Article 

Google Scholar 
276.Noble, D. W., Lagisz, M., O’dea, R. E. & Nakagawa, S. Nonindependence and sensitivity analyses in ecological and evolutionary meta‐analyses. Mol. Ecol. 26, 2410–2425 (2017).PubMed 
Article 

Google Scholar 
277.Borenstein, M., Hedges, L. V., Higgins, J. P. & Rothstein, H. Introduction to Meta-analysis (John Wiley, 2009).278.Higgins, J., Thompson, S. G., Deeks, J. J. & Altman, D. G. Measuring inconsistency in meta-analyses. Br. Med. J. 327, 557–560 (2003).Article 

Google Scholar 
279.Nakagawa, S. & Santos, E. S. Methodological issues and advances in biological meta-analysis. Evol. Ecol. 26, 1253–1274 (2012).Article 

Google Scholar 
280.Hothorn, T., Bretz, F. & Westfall, P. Simultaneous inference in general parametric models. Biom. J. 50, 346–363 (2008).PubMed 
Article 

Google Scholar 
281.Nakagawa, S. & Schielzeth, H. A general and simple method for obtaining R2 from generalized linear mixed‐effects models. Methods Ecol. Evol. 4, 133–142 (2013).Article 

Google Scholar 
282.Duval, S. & Tweedie, R. Trim and fill: a simple funnel-plot–based method of testing and adjusting for publication bias in meta-analysis. Biometrics 56, 455–463 (2000).CAS 
PubMed 
Article 

Google Scholar 
283.Egger, M., Smith, G. D., Schneider, M. & Minder, C. Bias in meta-analysis detected by a simple, graphical test. Br. Med. J. 315, 629–634 (1997).CAS 
Article 

Google Scholar  More

1.
McFall-Ngai M, Hadfield MG, Bosch TCG, Carey HV, Domazet-Lošo T, Douglas AE, et al. Animals in a bacterial world, a new imperative for the life sciences. Proc Natl Acad Sci. 2013;110:3229–36.
CAS  PubMed  Article  Google Scholar 
2.
Thompson LR, Sanders JG, McDonald D, Amir A, Ladau J, Locey KJ, et al. A communal catalogue reveals Earth’s multiscale microbial diversity. Nature. 2017;551:457–63.
CAS  PubMed  PubMed Central  Article  Google Scholar 

3.
Feldhaar H, Gross R. Insects as hosts for mutualistic bacteria. Int J Med Microbiol. 2009;299:1–8.
PubMed  Article  Google Scholar 

4.
Hosokawa T, Ishii Y, Nikoh N, Fujie M, Satoh N, Fukatsu T. Obligate bacterial mutualists evolving from environmental bacteria in natural insect populations. Nat Microbiol. 2016;1:15011.
CAS  PubMed  PubMed Central  Article  Google Scholar 

5.
de Bekker C, Merrow M, Hughes DP. From behavior to mechanisms: an integrative approach to the manipulation by a parasitic fungus (Ophiocordyceps unilateralis s.l.) of its host ants (Camponotus spp.). Integr Comp Biol. 2014;54:166–76.
PubMed  Article  Google Scholar 

6.
Koskella B, Meaden S, Crowther WJ, Leimu R, Metcalf CJE. A signature of tree health? Shifts in the microbiome and the ecological drivers of horse chestnut bleeding canker disease. N. Phytol. 2017;215:737–46.
CAS  Article  Google Scholar 

7.
Smee MR, Baltrus DA, Hendry TA. Entomopathogenicity to two Hemipteran insects is common but variable across epiphytic Pseudomonas syringae strains. Front Plant Sci. 2017;8:2149.
PubMed  PubMed Central  Article  Google Scholar 

8.
Oliver KM, Degnan PH, Burke GR, Moran NA. Facultative symbionts in aphids and the horizontal transfer of ecologically important traits. Annu Rev Entomol. 2010;55:247–66.
CAS  PubMed  Article  Google Scholar 

9.
McLean AH. Cascading effects of defensive endosymbionts. Curr Opin Insect Sci. 2019;32:42–46.
PubMed  Article  Google Scholar 

10.
Adair KL, Douglas AE. Making a microbiome: the many determinants of host-associated microbial community composition. Curr Opin Microbiol. 2017;35:23–29.
PubMed  Article  Google Scholar 

11.
Wedin M, Maier S, Fernandez-Brime S, Cronholm B, Westberg M, Grube M. Microbiome change by symbiotic invasion in lichens. Environ Microbiol. 2015;18:1428–39.
PubMed  Article  CAS  Google Scholar 

12.
King KC, Brockhurst MA, Vasieva O, Paterson S, Betts A, Ford SA, et al. Rapid evolution of microbe-mediated protection against pathogens in a worm host. ISME J. 2016;10:1915–24.
CAS  PubMed  PubMed Central  Article  Google Scholar 

13.
Ford SA, Williams D, Paterson S, King KC. Co-evolutionary dynamics between a defensive microbe and a pathogen driven by fluctuating selection. Mol Ecol. 2017;26:1778–89.
CAS  PubMed  Article  Google Scholar 

14.
Weldon SR, Russell JA, Oliver KM. More is not always better: coinfections with defensive symbionts generate highly variable outcomes. Appl Environ Microbiol. 2020;86:e02537-19.
CAS  PubMed  PubMed Central  Google Scholar 

15.
Bongrand C, Ruby EG. Achieving a multi-strain symbiosis: strain behavior and infection dynamics. ISME J 2019;13:698-706.
PubMed  Article  Google Scholar 

16.
Doremus MR, Oliver KM. Aphid heritable symbiont exploits defensive mutualism. Appl Environ Microbiol. 2017;83:e03276–16.
CAS  PubMed  PubMed Central  Article  Google Scholar 

17.
McLean AHC, Parker BJ, Hrček J, Kavanagh JC, Wellham PAD, Godfray HCJ. Consequences of symbiont co-infections for insect host phenotypes. J Anim Ecol 2018;87:478-488.
PubMed  Article  Google Scholar 

18.
Oliver KM, Moran NA, Hunter MS. Costs and benefits of a superinfection of facultative symbionts in aphids. Proc R Soc B-Biol Sci. 2006;273:1273–80.
Article  Google Scholar 

19.
Greenblum S, Carr R, Borenstein E. Extensive strain-level copy-number variation across human gut microbiome species. Cell. 2015;160:583–94.
CAS  PubMed  PubMed Central  Article  Google Scholar 

20.
Lloyd-Price J, Mahurkar A, Rahnavard G, Crabtree J, Orvis J, Hall AB, et al. Strains, functions and dynamics in the expanded human microbiome project. Nature. 2017;550:61–66.
CAS  PubMed  PubMed Central  Article  Google Scholar 

21.
Des Roches S, Post DM, Turley NE, Bailey JK, Hendry AP, Kinnison MT, et al. The ecological importance of intraspecific variation. Nat Ecol Evol. 2018;2:57–64.
PubMed  Article  Google Scholar 

22.
Barbour MA, Fortuna MA, Bascompte J, Nicholson JR, Julkunen-Tiitto R, Jules ES, et al. Genetic specificity of a plant–insect food web: implications for linking genetic variation to network complexity. Proc Natl Acad Sci. 2016;113:2128–33.
CAS  PubMed  Article  Google Scholar 

23.
Reznick DN, Losos J, Travis J. From low to high gear: there has been a paradigm shift in our understanding of evolution. Ecol Lett. 2019;22:233–44.
PubMed  Article  Google Scholar 

24.
Koskella B, Bergelson J. The study of host–microbiome (co)evolution across levels of selection. Philos Trans R Soc B Biol Sci. 2020;375:20190604.
Article  Google Scholar 

25.
Whitham TG, Allan GJ, Cooper HF, Shuster SM. Intraspecific Genetic Variation and Species Interactions Contribute to Community Evolution. Annu Rev Ecol Evol Syst. 2020;51:587–612.
Article  Google Scholar 

26.
Ferrari J, West JA, Via S, Godfray HCJ. Population genetic structure and secondary symbionts in host-associated populations of the pea aphid complex. Evolution. 2012;66:375–90.
PubMed  Article  Google Scholar 

27.
Henry LM, Peccoud J, Simon J-C, Hadfield JD, Maiden MJC, Ferrari J, et al. Horizontally transmitted symbionts and host colonization of ecological niches. Curr Biol. 2013;23:1713–7.
CAS  PubMed  PubMed Central  Article  Google Scholar 

28.
Reuter M, Keller L. High levels of multiple Wolbachia infection and recombination in the ant Formica exsecta. Mol Biol Evol. 2003;20:748–53.
CAS  PubMed  Article  Google Scholar 

29.
Gauthier J-P, Outreman Y, Mieuzet L, Simon J-C. Bacterial communities associated with host-adapted populations of pea aphids revealed by deep sequencing of 16S ribosomal DNA. PloS One. 2015;10:e0120664.
PubMed  PubMed Central  Article  CAS  Google Scholar 

30.
Douglas AE. Nutritional interactions in insect-microbial symbioses: aphids and their symbiotic bacteria Buchnera. Annu Rev Entomol. 1998;43:17–37.
CAS  PubMed  PubMed Central  Article  Google Scholar 

31.
Douglas AE. The nutritional physiology of aphids. Advances in Insect Physiology. Oxford, UK: Academic Press; 2003. pp 73–140.

32.
Zytynska SE, Weisser WW. The natural occurrence of secondary bacterial symbionts in aphids. Ecol Entomol. 2016;41:13–26.
Article  Google Scholar 

33.
Smith AH, Łukasik P, O’Connor MP, Lee A, Mayo G, Drott MT, et al. Patterns, causes, and consequences of defensive microbiome dynamics across multiple scales. Mol Ecol. 2015;24:1135–49.
PubMed  Article  Google Scholar 

34.
Oliver KM, Russell JA, Moran NA, Hunter MS. Facultative bacterial symbionts in aphids confer resistance to parasitic wasps. Proc Natl Acad Sci USA. 2003;100:1803–7.
CAS  PubMed  Article  Google Scholar 

35.
Scarborough CL, Ferrari J, Godfray HCJ. Aphid protected from pathogen by endosymbiont. Science. 2005;310:1781–1781.
CAS  PubMed  Article  Google Scholar 

36.
Montllor CB, Maxmen A, Purcell AH. Facultative bacterial endosymbionts benefit pea aphids Acyrthosiphon pisum under heat stress. Ecol Entomol. 2002;27:189–95.
Article  Google Scholar 

37.
Hrček J, McLean AHC, Godfray HCJ. Symbionts modify interactions between insects and natural enemies in the field. J Anim Ecol. 2016;85:1605–12.
PubMed  PubMed Central  Article  Google Scholar 

38.
Rock DI, Smith AH, Joffe J, Albertus A, Wong N, O’Connor M, et al. Context-dependent vertical transmission shapes strong endosymbiont community structure in the pea aphid, Acyrthosiphon pisum. Mol Ecol. 2018;27:2039–56.
PubMed  Article  PubMed Central  Google Scholar 

39.
Moran NA, Russell JA, Koga R, Fukatsu T. Evolutionary relationships of three new species of Enterobacteriaceae living as symbionts of aphids and other insects. Appl Environ Microbiol. 2005;71:3302–10.
CAS  PubMed  PubMed Central  Article  Google Scholar 

40.
Manzano-Marín A, Szabó G, Simon J-C, Horn M, Latorre A. Happens in the best of subfamilies: establishment and repeated replacements of co-obligate secondary endosymbionts within Lachninae aphids. Environ Microbiol. 2017;19:393–408.
PubMed  Article  CAS  Google Scholar 

41.
Henry LM, Maiden MCJ, Ferrari J, Godfray HCJ. Insect life history and the evolution of bacterial mutualism. Ecol Lett. 2015;18:516–25.
PubMed  Article  Google Scholar 

42.
Oliver KM, Moran NA, Hunter MS. Variation in resistance to parasitism in aphids is due to symbionts not host genotype. Proc Natl Acad Sci USA. 2005;102:12795–12800.
CAS  PubMed  Article  Google Scholar 

43.
Oliver KM, Degnan PH, Hunter MS, Moran NA. Bacteriophages encode factors required for protection in a symbiotic mutualism. Science. 2009;325:992–4.
CAS  PubMed  PubMed Central  Article  Google Scholar 

44.
Degnan PH, Moran NA. Evolutionary genetics of a defensive facultative symbiont of insects: exchange of toxin-encoding bacteriophage. Mol Ecol. 2008;17:916–29.
CAS  PubMed  Article  Google Scholar 

45.
Chevignon G, Boyd BM, Brandt JW, Oliver KM, Strand MR. Culture-facilitated comparative genomics of the facultative symbiont Hamiltonella defensa. Genome Biol Evol. 2018;10:786–802.
CAS  PubMed  PubMed Central  Article  Google Scholar 

46.
Heyworth ER, Ferrari J. A facultative endosymbiont in aphids can provide diverse ecological benefits. J Evol Biol. 2015;28:1753–60.
CAS  PubMed  PubMed Central  Article  Google Scholar 

47.
Moran NA, Degnan PH, Santos SR, Dunbar HE, Ochman H. The players in a mutualistic symbiosis: Insects, bacteria, viruses, and virulence genes. Proc Natl Acad Sci USA. 2005;102:16919–26.
CAS  PubMed  Article  Google Scholar 

48.
Oliver KM, Higashi CH. Variations on a protective theme: Hamiltonella defensa infections in aphids variably impact parasitoid success. Curr Opin Insect Sci. 2019;32:1–7.
PubMed  Article  Google Scholar 

49.
Martinez AJ, Doremus MR, Kraft LJ, Kim KL, Oliver KM. Multi-modal defences in aphids offer redundant protection and increased costs likely impeding a protective mutualism. J Anim Ecol. 2018;87:464–77.
PubMed  Article  Google Scholar 

50.
Łukasik P, van Asch M, Guo H, Ferrari J, Charles J, Godfray H. Unrelated facultative endosymbionts protect aphids against a fungal pathogen. Ecol Lett. 2013;16:214–8.
PubMed  Article  Google Scholar 

51.
Parker BJ, Hrček J, McLean AHC, Godfray HCJ. Genotype specificity among hosts, pathogens, and beneficial microbes influences the strength of symbiont-mediated protection. Evolution. 2017;71:1222–31.
PubMed  PubMed Central  Article  Google Scholar 

52.
Vorburger C. The evolutionary ecology of symbiont-conferred resistance to parasitoids in aphids. Insect Sci. 2014;21:251–64.
PubMed  Google Scholar 

53.
Ferrari J, Via S, Godfray HCJ. Population differentiation and genetic variation in performance on eight hosts in the pea aphid complex. Evolution. 2008;62:2508–24.
PubMed  Article  Google Scholar 

54.
McLean AHC, van Asch M, Ferrari J, Godfray HCJ. Effects of bacterial secondary symbionts on host plant use in pea aphids. Proc R Soc B-Biol Sci. 2011;278:760–6.
CAS  Article  Google Scholar 

55.
R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/.

56.
Bates D, Maechler M, Bolker B, Walker S. Fitting linear mixed-effects models using lme4. J Stat Softw. 2015;67:1–48.
Article  Google Scholar 

57.
Russell JA, Weldon S, Smith AH, Kim KL, Hu Y, Łukasik P, et al. Uncovering symbiont-driven genetic diversity across North American pea aphids. Mol Ecol. 2013;22:2045–59.
PubMed  Article  Google Scholar 

58.
Jayakar SD. A mathematical model for interaction of gene frequencies in a parasite and its host. Theor Popul Biol. 1970;1:140–64.
CAS  PubMed  Article  Google Scholar 

59.
Tellier A, Brown JKM. Stability of genetic polymorphism in host–parasite interactions. Proc R Soc B Biol Sci. 2007;274:809–17.
Article  Google Scholar 

60.
Eren AM, Sogin ML, Morrison HG, Vineis JH, Fisher JC, Newton RJ, et al. A single genus in the gut microbiome reflects host preference and specificity. ISME J. 2015;9:90–100.
CAS  PubMed  Article  Google Scholar 

61.
Yin Y, Wang Y, Zhu L, Liu W, Liao N, Jiang M, et al. Comparative analysis of the distribution of segmented filamentous bacteria in humans, mice and chickens. ISME J. 2013;7:615–21.
CAS  PubMed  Article  Google Scholar 

62.
Parker BJ, McLean AHC, Hrček J, Gerardo NM, Godfray HCJ. Establishment and maintenance of aphid endosymbionts after horizontal transfer is dependent on host genotype. Biol Lett. 2017;13:20170016.
PubMed  PubMed Central  Article  Google Scholar 

63.
Nyabuga FN, Outreman Y, Simon J-C, Heckel DG, Weisser WW. Effects of pea aphid secondary endosymbionts on aphid resistance and development of the aphid parasitoid Aphidius ervi: a correlative study. Entomol Exp Appl. 2010;136:243–53.
Google Scholar 

64.
Leclair M, Polin S, Jousseaume T, Simon J-C, Sugio A, Morlière S, et al. Consequences of coinfection with protective symbionts on the host phenotype and symbiont titres in the pea aphid system. Insect Sci. 2016;24:798–808.
PubMed  Article  Google Scholar 

65.
Zhao D, Hoffmann AA, Zhang Z, Niu H, Guo H. Interactions between facultative symbionts Hamiltonella and Cardinium in Bemisia tabaci (Hemiptera: Aleyrodoidea): cooperation or conflict? J Econ Entomol. 2018;111:2660-2666.
PubMed  Article  CAS  Google Scholar 

66.
Vorburger C, Gehrer L, Rodriguez P. A strain of the bacterial symbiont Regiella insecticola protects aphids against parasitoids. Biol Lett. 2010;6:109–11.
PubMed  Article  Google Scholar 

67.
McLean AHC, Godfray HCJ. Evidence for specificity in symbiont-conferred protection against parasitoids. Proc R Soc B. 2015;282:20150977.
Article  Google Scholar 

68.
Patel V, Chevignon G, Manzano-Marín A, Brandt JW, Strand MR, Russell JA, et al. Cultivation-assisted genome of Candidatus Fukatsuia symbiotica; the enigmatic ‘X-type’ symbiont of aphids. Genome Biol Evol. 2019;11:3510-3522.
CAS  PubMed  PubMed Central  Google Scholar 

69.
Rouchet R, Vorburger C. Strong specificity in the interaction between parasitoids and symbiont-protected hosts. J Evol Biol. 2012;25:2369–75.
PubMed  Article  Google Scholar 

70.
Sanders D, Kehoe R, Veen FF, van, McLean A, Godfray HCJ, Dicke M, et al. Defensive insect symbiont leads to cascading extinctions and community collapse. Ecol Lett. 2016;19:789–99.
PubMed  PubMed Central  Article  Google Scholar  More

Fin and sperm whales residing or circulating in the Mediterranean Sea are exposed to biological and chemical hazard due to the increasing anthropogenic impact. In particular, most of the coastal areas bordering with the Sanctuary is heavily populated and full of commercial, touristic and military ports and industrial areas. As a consequence, a range of diverse human activities exerts several actual and potential threats to cetacean populations in the Sanctuary, including habitat degradation, urban, tourist, industrial, and agricultural development, intense maritime traffic, military exercises and oil and gas exploration, just to mention the most important ones.
This study provides background information on the occurrence and concentration of parasites and bacterial infections/communities as well a first investigation of heavy metals and organic pollutants in faecal samples from fin and sperm whale Mediterranean subpopulations within the Pelagos Sanctuary.
Here, a modified MINI-FLOTAC technique in combination with FILL-FLOTAC were used for parasitological detection of the cysts in the faecal samples of fin and sperm whales. Although this technique has never been used before for whale faecal samples, it has successfully been used in previous coprological surveys for the detection of gastrointestinal parasites in other marine animals as the loggerhead sea turtles (Caretta caretta)23,24. The MINI-FLOTAC can be considered as one of the most accurate methods for coprological diagnosis of endoparasite infections and cysts/eggs counting nowadays available in veterinary medicine25. It allowed an accurate and reliable detection of Blastocystis cysts in both fin and sperm faecal samples. Molecular analysis, sequencing and phylogenetic analysis confirmed the obtained results.
Blastocystis is a common intestinal protozoan parasite reported in several animals, e.g., humans, livestock, dogs, amphibians, reptiles, birds and even insects26,27,28. Although it possesses pathogenic potential, its virulence mechanisms in humans are still not well understood29. Blastocystis seems to be linked to Irritable Bowel Syndrome, i.e., a functional disorder mainly consisting in chronic or recurrent abdominal pain due to altered intestinal habits30. Studying the small subunit ribosomal RNA (SSU-rDNA) gene, several authors identified at least 22 different Blastocystis subtypes (ST) in a variety of animals, humans included, i.e., from ST1 to ST17, ST21, and ST23 to ST26 (Ref.26). To date, human Blastocystis isolates are classified into 10 ST (i.e., ST1-ST9 and ST12) that, with the only exception of ST9, have been identified also in other animals31. According to Parkar et al.32, Blastocystis has the potential to spread through human-to-human, animal-to-human, and human-to-animal contact.
Few similar parasitological investigations have been conducted in the past and are currently available in the literature. Hermosilla et al.33 detected three protozoan parasites (i.e., Giardia sp., Balantidium sp., Entamoeba sp.) and helminth parasites in individual faecal samples from wild fin (n. 10), sperm (n. 4), blue (Balaenoptera musculus; n. 2) and sei (Balaenoptera borealis; n. 1) Atlantic whale subpopulations from the Azores Islands, Portugal. Protozoan parasites (Giardia sp., Balantidium sp., Cistoisospora-like indet.) and helminth parasites were also found in individual faecal samples of wild sperm whales inhabiting Mediterranean Sea waters surrounding the Balearic Archipelago, Spain34. Out of these, three of herein detected parasites clearly bear anthropozoonotic potential, i.e., Anisakis, Balantidium and Giardia34.
In the present work, Blastocystis has been found in fin and sperm whale samples and, to the best of our knowledge, this is the first time that this protozoan genus is reported for any cetacean species. Therefore, this finding represents the first new host record for fin and sperm whales. Blastocystis ST3 was the only subtype found in fin and sperm whales. Molecular studies in human samples showed the occurrence of ST1–ST9, with ST3 as the most prevalent subtype35,36. Indeed, ST3 is the Blastocystis subtype with the highest prevalence in humans worldwide and probably represents the human species-specific ST (Ref.37). Consequently, animals harbouring ST3 may thus mirror environmental contamination by humans, confirming the zoonotic potential of animals for Blastocystis human infections. Unlike33,34, no eggs of helminths were found in our faecal samples.
Variations in parasites composition and prevalence might be related to several factors such as dietary differences, the parasite life cycle, the availability of hosts necessary to complete their life cycle, the interactions between parasite species, the host immune response, and the host population density23. Moreover, parasites can also spread in different way in animal populations in the wild, particularly when they act together with ecological, biological, and anthropogenic factors38.
The occurrence in whales of parasites with a zoonotic potential like Giardia or Balantidium, most probably due to coastal waters contaminated by sewage, agricultural and urban run-off, has been already reported elsewhere39,40,41,42,43. Furthermore, human excretions from increasing number of pleasure boats, fishing and whale watching boats could be an additional form of contamination. Finally, the intense maritime traffic in the Mediterranean Sea, the percentage of which is higher than in other oceans44, represents another source of contamination. In all cases, results highlight that human activities play an important role for the widespread of these pathogens.
No bacterial pathogen of human or terrestrial animal origin has been detected both by targeted PCR and by Illumina high throughput sequencing. This difference could be due to the lower survival rate of bacteria in the sea environment, compared to protozoan parasites45.
Previous works reported the occurrence of human pathogens in stranded common minke whale (Balaenoptera acutorostrata) from Philippines46 and killer whale respiratory microbiome in North Pacific47. Although the relatively low number of samples cannot exclude potential risk of transmission of human and zoonotic pathogenic bacteria to cetaceans in the surveyed area, our results suggest to focus on microbiological analyses to track potential internal waterborne pathogens to the ones able to form cysts (like parasites) or other forms of resistance (like spore-forming bacteria) that are more likely to survive for longer period in the seawater.
The dominance of Bacterioidetes and Firmicutes (common with other terrestrial mammals), the baleen-specific higher number of Spirochaetes and the lower of Proteobacteria characterized both species, as also reported elsewhere21. Moreover, differences of some taxa related with the diverse diet were confirmed: in the case of sperm whale, whose nutrition is based on cephalopods, a higher proportion of Synergistetes was observed in faecal samples, whereas faecal samples from fin whales had a higher level of Spirochaetes compared those from sperm whales. These findings are in agreement with Erwin et al.13. The Synergistetes phylum includes gram negative, anaerobic, rod-shaped bacteria, widely distributed in terrestrial and aquatic environments, including host-associated with mammals48. Within this phylum, Synergistaceae family and Pyramidobacter genus OTUs were particularly dominant among sperm whale microbiome (Fig. 4). However, no correlation with potential pathogenicity could be drawn from the presence of these specific OTUs, considering their ubiquity in oral and gut mucosa of marine and terrestrial animals, despite some of the genus belonging to Synergistaceae family (e.g. Cloacibacillus spp.) are considered opportunistic pathogens49. About potential health implication of Spirochaetes, similar conclusion than for Synergistetes could be drawn: Treponema sp., found as dominant genus in fin whales, were found in healthy baleen whales by Sanders et al.21 so as among more dynamical OTU in stranded right whales50Sphaerochaeta spp. associated with healthy cetacean monitored oral cavity microbiome14. Moreover, fin whale faeces also showed a higher proportion of taxa that are also enriched in terrestrial herbivores, like Lentisphaere, Verrucomicrobia, Actinobacteria and Tenericutes, as also reported elsewhere21. Although differences in species sampled and habitats compared to previous studies, we found confirmation of both species and diet-influenced gut microbiota composition. Notably Akkermansia (one of the dominant Verrucomicrobia OTUs) and Coriobacteriaceae (dominant family among Actinobacteria phylum) includes typical holobiont of terrestrial and marine mammals, but also some pathobiont, so far confirmed only for humans51. Due to the wide distribution of some of Synergistetes and Spirochaetes phyla, it is not possible to establish if their presence could be ascribed exclusively to an anthropogenic impact; however, it is worth of interest that some of the genus found in both whale species and belonging to these phyla include opportunistic pathogens whose virulence for marine mammals still need to be confirmed. Interestingly, some archaeal sequences related to the Thermoplasmatales order were also found. This confirms what already reported by Sanders et al.21, i.e., that archaea belonging to this order may have a role as methane producer from methylated amines in baleen gut, differently from methanogenic archaea belonging to other orders that typically colonize the gut of terrestrial mammals, including humans.
Therefore, the two sampled species harboured typical gut microbiome belonging to fin whale and sperm whale groups. These data extend the spectrum of surveyed whales gut microbiome to previously unsampled species and confirms that NGS analyses could be a useful tool to retrieve information on the health status of wild whales.
While the concentration of 16 U.S. EPA priority PAHs and of 29 PCBs, being always  More

1.
Sakschewski B, von Bloh W, Boit A, Poorter L, Peña-Claros M, Heinke J, et al. Resilience of Amazon forests emerges from plant trait diversity. Nat Clim Change. 2016;6:1032–6.
Article  Google Scholar 
2.
Gruber N, Galloway JN. An Earth-system perspective of the global nitrogen cycle. Nature. 2008;451:293–6.
CAS  PubMed  Article  Google Scholar 

3.
Kicklighter DW, Melillo JM, Monier E, Sokolov AP, Zhuang Q. Future nitrogen availability and its effect on carbon sequestration in Northern Eurasia. Nat Commun. 2019;10:1–19.
CAS  Article  Google Scholar 

4.
Liu L, Greaver TL. A global perspective on belowground carbon dynamics under nitrogen enrichment. Ecol Lett. 2010;13:819–28.
PubMed  Article  Google Scholar 

5.
Maaroufi NI, Nordin A, Hasselquist NJ, Bach LH, Palmqvist K, Gundale MJ. Anthropogenic nitrogen deposition enhances carbon sequestration in boreal soils. Glob Chang. Glob Change Biol. 2015;21:3169–80.
Article  Google Scholar 

6.
Lu M, Zhou X, Luo Y, Yang Y, Fang C, Chen J, et al. Minor stimulation of soil carbon storage by nitrogen addition: a meta-analysis. Agr Ecosyst Environ. 2011;140:234–44.
CAS  Article  Google Scholar 

7.
Chen J, Luo Y, van Groenigen KJ, Hungate BA, Cao J, Zhou X, et al. A keystone microbial enzyme for nitrogen control of soil carbon storage. Sci Adv. 2018;4:q1689.
Article  CAS  Google Scholar 

8.
Cusack DF, Torn MS, Mcdowell WH, Silver WL. The response of heterotrophic activity and carbon cycling to nitrogen additions and warming in two tropical soils. Glob Change Biol. 2010;16:2555–72.
Google Scholar 

9.
Zhang J, Balkovic J, Azevedo LB, Skalsky R, Bouwman AF, Xu G, et al. Analyzing and modelling the effect of long-term fertilizer management on crop yield and soil organic carbon in China. Sci Total Environ. 2018;627:361–72.
CAS  PubMed  Article  Google Scholar 

10.
Bending GD, Putland C, Rayns F. Changes in microbial community metabolism and labile organic matter fractions as early indicators of the impact of management on soil biological quality. Biol Fertil Soils. 2000;31:78–84.
CAS  Article  Google Scholar 

11.
Kallenbach CM, Frey SD, Grandy AS. Direct evidence for microbial-derived soil organic matter formation and its ecophysiological controls. Nat Commun. 2016;7:13630.
CAS  PubMed  PubMed Central  Article  Google Scholar 

12.
Leinweber P, Jandl G, Baum C, Eckhardt K, Kandeler E. Stability and composition of soil organic matter control respiration and soil enzyme activities. Soil Biol Biochem. 2008;40:1496–505.
CAS  Article  Google Scholar 

13.
Roth V, Lange M, Simon C, Hertkorn N, Bucher S, Goodall T, et al. Persistence of dissolved organic matter explained by molecular changes during its passage through soil. Nat Geosci. 2019;12:755–61.
CAS  Article  Google Scholar 

14.
Kallenbach CM, Grandy AS, Frey SD, Diefendorf AF. Microbial physiology and necromass regulate agricultural soil carbon accumulation. Soil Biol Biochem. 2015;91:279–90.
CAS  Article  Google Scholar 

15.
Chen L, Liu L, Qin S, Yang G, Fang K, Zhu B, et al. Regulation of priming effect by soil organic matter stability over a broad geographic scale. Nat Commun. 2019;10:5112.
PubMed  PubMed Central  Article  CAS  Google Scholar 

16.
Sollins P, Kramer MG, Swanston C, Lajtha K, Filley T, Aufdenkampe AK, et al. Sequential density fractionation across soils of contrasting mineralogy: evidence for both microbial- and mineral-controlled soil organic matter stabilization. Biogeochemistry. 2009;96:209–31.
CAS  Article  Google Scholar 

17.
Liang C, Schimel JP, Jastrow JD. The importance of anabolism in microbial control over soil carbon storage. Nat Microbiol. 2017;2:17105.
CAS  PubMed  Article  Google Scholar 

18.
Ding X, Chen S, Zhang B, Liang C, He H, Horwath WR. Warming increases microbial residue contribution to soil organic carbon in an alpine meadow. Soil Biol Biochem. 2019;135:13–9.
CAS  Article  Google Scholar 

19.
Ni X, Liao S, Tan S, Peng Y, Wang D, Yue K, et al. The vertical distribution and control of microbial necromass carbon in forest soils. Glob Ecol Biogeogr. 2020;29:1829–39.
Article  Google Scholar 

20.
Shao P, Lynch L, Xie H, Bao X, Liang C. Tradeoffs among microbial life history strategies influence the fate of microbial residues in subtropical forest soils. Soil Biol Biochem. 2021;153:108112.
CAS  Article  Google Scholar 

21.
Ma T, Zhu S, Wang Z, Chen D, Dai G, Feng B, et al. Divergent accumulation of microbial necromass and plant lignin components in grassland soils. Nat Commun. 2018;9:3480.
PubMed  PubMed Central  Article  CAS  Google Scholar 

22.
Malik AA, Puissant J, Buckeridge KM, Goodall T, Jehmlich N, Chowdhury S, et al. Land use driven change in soil pH affects microbial carbon cycling processes. Nat Commun. 2018;9:3591.
PubMed  PubMed Central  Article  CAS  Google Scholar 

23.
Nocker A, Sossa-Fernandez P, Burr MD, Camper AK. Use of propidium monoazide for live/dead distinction in microbial ecology. Appl Environ Microbiol. 2007;73:5111–7.
CAS  PubMed  PubMed Central  Article  Google Scholar 

24.
Castro HF, Classen AT, Austin EE, Norby RJ, Schadt CW. Soil microbial community responses to multiple experimental climate change drivers. Appl Environ Microbiol. 2010;76:999–1007.
CAS  PubMed  Article  Google Scholar 

25.
Rinnan R, MichelsenI A, Bååth E, Jonasson S. Fifteen years of climate change manipulations alter soil microbial communities in a subarctic heath ecosystem. Glob Change Biol. 2007;13:28–39.
Article  Google Scholar 

26.
Liang Y, Xiao X, Nuccio EE, Yuan M, Zhang N, Xue K, et al. Differentiation strategies of soil rare and abundant microbial taxa in response to changing climatic regimes. Environ Microbiol. 2020;22:1327–40.
CAS  PubMed  Article  Google Scholar 

27.
Wang M, Ding J, Sun B, Zhang J, Wyckoff KN, Yue H, et al. Microbial responses to inorganic nutrient amendment overridden by warming: consequences on soil carbon stability. Environ Microbiol. 2018;20:2509–22.
CAS  PubMed  Article  Google Scholar 

28.
Zhao M, Xue K, Wang F, Liu S, Bai S, Sun B, et al. Microbial mediation of biogeochemical cycles revealed by simulation of global changes with soil transplant and cropping. ISME J. 2014;8:2045–55.
CAS  PubMed  PubMed Central  Article  Google Scholar 

29.
Liang Y, Jiang Y, Wang F, Wen C, Deng Y, Xue K, et al. Long-term soil transplant simulating climate change with latitude significantly alters microbial temporal turnover. ISME J. 2015;9:2561–72.
PubMed  PubMed Central  Article  Google Scholar 

30.
Sun B, Wang F, Jiang Y, Li Y, Dong Z, Li Z, et al. A long-term field experiment of soil transplantation demonstrating the role of contemporary geographic separation in shaping soil microbial community structure. Ecol Evol. 2014;4:1073–87.
PubMed  PubMed Central  Article  Google Scholar 

31.
Fernandez I, Álvarez-González JG, Carrasco B, Ruíz-González AD, Cabaneiro A. Post-thinning soil organic matter evolution and soil CO2 effluxes in temperate radiata pine plantations: impacts of moderate thinning regimes on the forest C cycle. Can J Res. 2012;42:1953–64.
CAS  Article  Google Scholar 

32.
Baldock JA, Oades JM, Waters AG, Peng X, Vassallo AM, Wilson MA. Aspects of the chemical structure of soil organic materials as revealed by solid-state 13C NMR spectroscopy. Biogeochemistry. 1992;16:1–42.
CAS  Article  Google Scholar 

33.
Coxall HK, Wilson PA, Pälike H, Lear CH, Backman J. Rapid stepwise onset of Antarctic glaciation and deeper calcite compensation in the Pacific Ocean. Nature. 2005;433:53–7.
CAS  PubMed  Article  Google Scholar 

34.
Carini P, Marsden PJ, Leff JW, Morgan EE, Strickland MS, Fierer N, et al. is abundant in soil and obscures estimates of soil microbial diversity. Nat Microbiol. 2016;2:16242.
PubMed  Article  CAS  Google Scholar 

35.
Li H, Bi Q, Yang K, Zheng B, Pu Q, Cui L. D2O-isotope-labeling approach to probing phosphate-solubilizing bacteria in complex soil communities by single-cell raman spectroscopy. Anal Chem. 2019;91:2239–46.
CAS  PubMed  Article  Google Scholar 

36.
Cui L, Butler HJ, Martin-Hirsch PL, Martin FL. Aluminium foil as a potential substrate for ATR-FTIR, transflection FTIR or Raman spectrochemical analysis of biological specimens. Anal Methods. 2016;8:481–7.
CAS  Article  Google Scholar 

37.
Bååth E, Pettersson M, Söderberg KH. Adaptation of a rapid and economical microcentrifugation method to measure thymidine and leucine incorporation by soil bacteria. Soil Biol Biochem. 2001;33:1571–4.
Article  Google Scholar 

38.
Trivedi P, Delgado-Baquerizo M, Trivedi C, Hu H, Anderson IC, Jeffries TC, et al. Microbial regulation of the soil carbon cycle: evidence from gene-enzyme relationships. ISME J. 2016;10:2593–604.
CAS  PubMed  PubMed Central  Article  Google Scholar 

39.
Zhang X, Amelung W. Gas chromatographic determination of muramic acid, glucosamine, mannosamine, and galactosamine in soils. Soil Biol Biochem. 1996;28:1201–6.
CAS  Article  Google Scholar 

40.
Schermelleh-Engel K, Moosbrugger H. Evaluating the fit of structural equation models: tests of significance and descriptive goodness-of-fit measures. Methods Psychological Res Online. 2003;8:23–74.
Google Scholar 

41.
Clarke KR. Non-parametric multivariate analyses of changes in community structure. Austral Ecol. 1993;18:117–43.
Article  Google Scholar 

42.
Kruskal JB. Nonmetric multidimensional scaling: a numerical method. Psychometrika. 1964;29:115–29.
Article  Google Scholar 

43.
Legendre P, Legendre L. Numerical Ecology, 3rd English Edition. Oxford, UK: Elsevier; 2012.

44.
Liaw A, Wiener M. Classification and regression by randomForest. R N. 2002;2:18–22.
Google Scholar 

45.
Faust K, Sathirapongsasuti JF, Izard J, Segata N, Gevers D, Raes J, et al. Microbial co-occurrence relationships in the human microbiome. PLoS Comput Biol. 2012;8:e1002606.
CAS  PubMed  PubMed Central  Article  Google Scholar 

46.
Wu L, Ning D, Zhang B, Li Y, Zhang P, Shan X, et al. Global diversity and biogeography of bacterial communities in wastewater treatment plants. Nat Microbiol. 2019;4:1183–95.
CAS  PubMed  Article  Google Scholar 

47.
Crowther TW, Todd-Brown KEO, Rowe CW, Wieder WR, Carey JC, Machmuller MB, et al. Quantifying global soil carbon losses in response to warming. Nature. 2016;540:104–8.
CAS  PubMed  Article  Google Scholar 

48.
Hicks Pries CE, Castanha C, Porras RC, Torn MS. The whole-soil carbon flux in response to warming. Science. 2017;355:1420–3.
CAS  PubMed  Article  Google Scholar 

49.
Peñuelas J, Ciais P, Canadell JG, Janssens IA, Fernández-Martínez M, Carnicer J, et al. Shifting from a fertilization-dominated to a warming-dominated period. Nat Ecol Evol. 2017;1:1438–45.
PubMed  Article  Google Scholar 

50.
Sokol NW, Bradford MA. Microbial formation of stable soil carbon is more efficient from belowground than aboveground input. Nat Geosci. 2019;12:46–53.
CAS  Article  Google Scholar 

51.
Trumbore SE, Chadwick OA, Amundson R. Rapid exchange between soil carbon and atmospheric carbon dioxide driven by temperature change. Science. 1996;272:393–6.
CAS  Article  Google Scholar 

52.
Liang C, Cheng G, Wixon DL, Balser TC. An Absorbing Markov Chain approach to understanding the microbial role in soil carbon stabilization. Biogeochemistry. 2011;106:303–9.
Article  Google Scholar 

53.
Liang C, Amelung W, Lehmann J, Kästner M. Quantitative assessment of microbial necromass contribution to soil organic matter. Glob Change Biol. 2019;00:1–13.
Google Scholar 

54.
Tian J, Zong N, Hartley IP. Microbial metabolic response to winter warming stabilizes soil carbon. Glob Change Biol. 2021;00:1–18.
Google Scholar 

55.
Coxall HK, Wilson PA, Pälike H, Lear CH, Backman J. Rapid stepwise onset of Antarctic glaciation and deeper calcite compensation in the Pacific Ocean. Nature. 2005;433:53–7.
CAS  PubMed  Article  Google Scholar 

56.
Ding X, Chen S, Zhang B, He H, Filley TR, Horwath WR. Warming yields distinct accumulation patterns of microbial residues in dry and wet alpine grasslands on the Qinghai-Tibetan Plateau. Biol Fertil Soils. 2020;56:881–92.
CAS  Article  Google Scholar 

57.
Jia J, Feng X, He J, He H, Lin L, Liu Z. Comparing microbial carbon sequestration and priming in the subsoil versus topsoil of a Qinghai-Tibetan alpine grassland. Soil Biol Biochem. 2017;104:141–51.
CAS  Article  Google Scholar 

58.
Zhou X, Chen C, Wang Y, Xu Z, Duan J, Hao Y, et al. Soil extractable carbon and nitrogen, microbial biomass and microbial metabolic activity in response to warming and increased precipitation in a semiarid Inner Mongolian grassland. Geoderma. 2013;206:24–31.
CAS  Article  Google Scholar 

59.
Chen J, Ji C, Fang J, He H, Zhu B. Dynamics of microbial residues control the responses of mineral-associated soil organic carbon to N addition in two temperate forests. Sci Total Environ. 2020;748:141318.
CAS  PubMed  Article  Google Scholar 

60.
Fontaine S, Barot S, Barré P, Bdioui N, Mary B, Rumpel C. Stability of organic carbon in deep soil layers controlled by fresh carbon supply. Nature. 2007;450:277–80.
CAS  PubMed  Article  Google Scholar 

61.
Wang C, Wang X, Pei G, Xia Z, Peng B, Sun L, et al. Stabilization of microbial residues in soil organic matter after two years of decomposition. Soil Biol Biochem. 2020;141:107687.
CAS  Article  Google Scholar 

62.
Zhou J, Xue K, Xie J, Deng Y, Wu L, Cheng X, et al. Microbial mediation of carbon-cycle feedbacks to climate warming. Nat Clim Change. 2011;2:106–10.
Article  CAS  Google Scholar 

63.
Chen R, Senbayram M, Blagodatsky S, Myachina O, Dittert K, Lin X, et al. Soil C and N availability determine the priming effect: microbial N mining and stoichiometric decomposition theories. Glob Change Biol. 2014;20:2356–67.
Article  Google Scholar 

64.
Fontaine S, Henault C, Aamor A, Bdioui N, Bloor JMG, Maire V, et al. Fungi mediate long term sequestration of carbon and nitrogen in soil through their priming effect. Soil Biol Biochem. 2011;43:86–96.
CAS  Article  Google Scholar 

65.
Jones DL, Nguyen C, Finlay RD. Carbon flow in the rhizosphere: carbon trading at the soil–root interface. Plant Soil. 2009;321:5–33.
CAS  Article  Google Scholar 

66.
Zang H, Wang J, Kuzyakov Y. N fertilization decreases soil organic matter decomposition in the rhizosphere. Appl Soil Ecol. 2016;108:47–53.
Article  Google Scholar 

67.
Mason-Jones K, Schmücker N, Kuzyakov Y. Contrasting effects of organic and mineral nitrogen challenge the N-Mining Hypothesis for soil organic matter priming. Soil Biol Biochem. 2018;124:38–46.
CAS  Article  Google Scholar 

68.
Carreiro MM, Sinsabaugh RL, Repert DA, Parkhurst DF. Microbial enzyme shifts explain litter decay responses to simulated nitrogen deposition. Ecology. 2000;81:2359–65.
Article  Google Scholar 

69.
Sinsabaugh RL, Hill BH, Follstad Shah JJ. Ecoenzymatic stoichiometry of microbial organic nutrient acquisition in soil and sediment. Nature. 2009;462:795–98.
CAS  PubMed  Article  Google Scholar 

70.
Burns RG, DeForest JL, Marxsen J, Sinsabaugh RL, Stromberger ME, Wallenstein MD, et al. Soil enzymes in a changing environment: current knowledge and future directions. Soil Biol Biochem. 2013;58:216–34.
CAS  Article  Google Scholar 

71.
Tian D, Niu S. A global analysis of soil acidification caused by nitrogen addition. Environ Res Lett. 2015;10:24019.
Article  CAS  Google Scholar 

72.
Zhou Z, Wang C, Zheng M, Jiang L, Luo Y. Patterns and mechanisms of responses by soil microbial communities to nitrogen addition. Soil Biol Biochem. 2017;115:433–41.
CAS  Article  Google Scholar  More

Spatial map of Chinese protected areas
The database of protected areas (PA) distribution in China and a digitized spatial map thereof were compiled from Zhao et al.40 and Zhang et al.41. In total, we obtained the information of 2622 protected areas in China, which also included marine reserves. In order to evaluate the representation of terrestrial protected areas, we excluded marine reserves from our analyses. We also excluded Taiwan because we did not have the spatial distribution data for nature reserves in Taiwan. Finally, we had the boundary information of 2572 protected areas covering about 15.2% land area in China.
Species’ range maps
Range maps of threatened vertebrates (birds, mammals, amphibians and reptiles) were obtained from the IUCN’s Red List42. Distribution data of threatened plants were compiled from Flora of China, Atlas of woody plants in China, provincial and local floras, checklists of nature reserves, various inventory reports across China and peer-reviewed papers. We obtained the information for critically endangered (CR), endangered (EN) and vulnerable (VU) species. The conservation status of vertebrates was obtained from IUCN Red List42, while that of plants was obtained from Qin et al.43. In total, we obtained the distribution information of 103 birds, 86 mammals, 134 amphibians, 50 reptiles, and 2983 plants in China (see Supplementary Data 1). We estimated the number of species in each PA by overlaying the map of PA with the species’ range maps in ArcGIS 10.2 (ESRI, Redlands, CA). In order to validate the distribution of species, we further verified the presence of species in respective PA by checking their inventory reports.
Human footprint data
In order to measure the extent of human pressure on the protected areas, we obtained the most comprehensive global map of human pressure i.e., human footprint (HFP) from https://wcshumanfootprint.org. The human footprint measures the cumulative impact of direct pressures on environment from human activities and is based on data from built environments, agricultural lands, pasture lands, human population density, night-time lights, railways, roads and navigable waterways44. It is one of the most complete and finest terrestrial datasets on cumulative human pressure on the environment. The human footprint maps of two time periods (1993 and 2009) are available at present. We downloaded the maps of both time periods at the spatial resolution of 1 km × 1 km to quantify the change in human pressure within Chinese protected areas over a 16-year period. It should, however, be noted that any point estimate of the change in HFP might include errors due to the resolution and reliability of the component layers. For example, one of the components of HFP is the night-time lights, which changed over time from incandescent to mercury vapor to light emitting diode. This means that the change in night light is due to more than development. As a result, the systemic bias in regional economy could likely cause low HFP in wealthy as compared to rural areas. While this issue does not invalidate our analyses, such comparisons should be applied with caution.
Climate data
In order to represent the climatic conditions of the past and the present, we obtained 20 years climate data comprising monthly minimum temperature, monthly maximum temperature and monthly precipitation for two time periods (past: 1961–1970 and present: 2010–2019). We used 10 years window for each time period to capture the variability in climatic conditions in order to prevent over- or underestimation of the past and present climate. In total, we obtained 12 months × 10 years × 3 variables × 2 time periods = 720 global raster layers from the Climate Research Unit (CRU TS v. 4.04) database (http://www.cru.uea.ac.uk/data) at the spatial resolution of 0.5° × 0.5°45. We then calculated the monthly mean values for the three variables for each time period separately. From these monthly mean values, we estimated mean annual temperature (MAT), mean temperature of warmest quarter (MTWQ), mean temperature of coldest quarter (MTCQ), mean annual precipitation (MAP), precipitation of driest quarter (PDQ) and precipitation of wettest quarter (PWQ) for each time period using biovars function in the R package ‘dismo’46. We then estimated the average value of climate variables in each PA using zonal.stats function in the R package ‘spatialEco’47. In order to reduce dimensionality and collinearity of the 6 climate variables, we performed principal component analysis (PCA) using prcomp function in R v4.0.248. Following Carroll et al.37, we used climate data for both past and present based on the first 2 PCA axes, which explained 89.4–89.8 % of the variance (Supplementary Tables 1-2). Additionally, we also estimated the change in mean annual temperature to identify PAs that have experienced climate warming higher than the Paris Agreement threshold of 1.5 °C. All the analyses were performed in R version 4.0.248.
Vulnerability mapping
We calculated three indices of vulnerability within each protected area: (i) species vulnerability, (ii) anthropogenic vulnerability, and (iii) climate vulnerability. In order to measure species vulnerability, we first assigned numerical value to each IUCN threat category using a geometric progression49,50. We gave scores of 2, 4, and 8 to species belonging to categories VU, EN, and CR, respectively. We, then, summed the score of all species in each PA and standardized the value to the range of 0–1 using minimum–maximum normalization. We performed these steps separately for birds, mammals, amphibians, reptiles and plants to calculate the vulnerability score of each group. We also calculated the cumulative score by combining the total scores of all five groups. Values close to 0 indicated low species vulnerability and values close to 1 indicated high species vulnerability. Although species diversity is highly correlated with the species vulnerability metric used herein (Pearson’s correlation coefficient = 0.94 − 0.99, p  More

1.
Blair JMA, Webber MA, Baylay AJ, Ogbolu DO, Piddock LJV. Molecular mechanisms of antibiotic resistance. Nat Rev Microbiol. 2015;13:42–51.
CAS  Article  Google Scholar 
2.
Palmer AC, Kishony R. Understanding, predicting and manipulating the genotypic evolution of antibiotic resistance. Nat Rev Genet. 2013;14:243–8.
CAS  Article  Google Scholar 

3.
Blaser MJ. Antibiotic use and its consequences for the normal microbiome. Science. 2016;352:544–5.
CAS  Article  Google Scholar 

4.
Modi SR, Collins JJ, Relman DA. Antibiotics and the gut microbiota. J Clin Investig. 2014;124:4212–8.
Article  Google Scholar 

5.
Lawley TD, Walker AW. Intestinal colonization resistance. Immunology. 2013;138:1–11.
CAS  Article  Google Scholar 

6.
Libertucci J, Young VB. The role of the microbiota in infectious diseases. Nat Microbiol. 2019;4:35–45.
CAS  Article  Google Scholar 

7.
Bhalodi AA, Engelen TSR, van, Virk HS, Wiersinga WJ. Impact of antimicrobial therapy on the gut microbiome. J Antimicrobial Chemother. 2019;74:i6–i15.
CAS  Article  Google Scholar 

8.
Klümper U, Recker M, Zhang L, Yin X, Zhang T, Buckling A, et al. Selection for antimicrobial resistance is reduced when embedded in a natural microbial community. ISME J. 2019;13, 2927–37.
Article  Google Scholar 

9.
Baumgartner M, Bayer F, Pfrunder-Cardozo KR, Buckling A, Hall AR. Resident microbial communities inhibit growth and antibiotic-resistance evolution of Escherichia coli in human gut microbiome samples. PLOS Biol. 2020;18:e3000465.
CAS  Article  Google Scholar 

10.
Ianiro G, Tilg H, Gasbarrini A. Antibiotics as deep modulators of gut microbiota: between good and evil. Gut. 2016;65:1906–15.
CAS  Article  Google Scholar 

11.
Spaulding CN, Klein RD, Schreiber HL, Janetka JW, Hultgren SJ. Precision antimicrobial therapeutics: The path of least resistance? npj Biofilms Microbiomes. 2018;4:1–7.
Article  Google Scholar 

12.
Moya A, Ferrer M. Functional redundancy-induced stability of gut microbiota subjected to disturbance. Trends Microbiol. 2016;24:402–13.
CAS  Article  Google Scholar 

13.
Jernberg C, Löfmark S, Edlund C, Jansson JK. Long-term impacts of antibiotic exposure on the human intestinal microbiota. Microbiology. 2010;156:3216–23.
CAS  Article  Google Scholar 

14.
Stecher B, Chaffron S, Käppeli R, Hapfelmeier S, Freedrich S, Weber TC, et al. Like will to like: abundances of closely related species can predict susceptibility to intestinal colonization by pathogenic and commensal bacteria. PLoS Pathog. 2010;6:e1000711.
Article  Google Scholar 

15.
Van Der Waaij D, Berghuis-de Vries JM, Lekkerkerk-Van Der Wees JEC. Colonization resistance of the digestive tract in conventional and antibiotic-treated mice. J Hyg. 1971;69:405–11.
Article  Google Scholar 

16.
Kim S, Covington A, Pamer EG. The intestinal microbiota: antibiotics, colonization resistance, and enteric pathogens. Immunological Rev. 2017;279:90–105.
CAS  Article  Google Scholar 

17.
Mathieu A, Fleurier S, Frénoy A, Dairou J, Bredeche MF, Sanchez-Vizuete P, et al. Discovery and function of a general core hormetic stress response in E. coli induced by sublethal concentrations of antibiotics. Cell Rep. 2016;17:46–57.
CAS  Article  Google Scholar 

18.
Pamer EG. Resurrecting the intestinal microbiota to combat antibiotic-resistant pathogens. Science. 2016;352:535–8.
CAS  Article  Google Scholar 

19.
Louca S, Polz MF, Mazel F, Albright MBN, Huber JA, O’Connor MI, et al. Function and functional redundancy in microbial systems. Nat Ecol Evolution. 2018;2:936–43.
Article  Google Scholar  More