Nocardiopsis halophila CGMCC 4.1195T in vitro and in vivo. The Rpf protein was expressed in the host Escherichia coli BL21 codon plus (DE3) and was confirmed to have a significant resuscitation effect on the viable but non-culturable (VBNC) N. halophila. Subsequently, the rpf gene of N. halophila was knocked out. We found that the growth rate of the mutant strain (Δrpf) was slower than that of the wild strain, and the former produced significantly shorter spores than the wild-type strain. Our results confirmed the activity of the Rpf protein in N. halophila to promote dormant bacteria resuscitation. This study will lay the foundation for the application of the Rpf protein from N. halophila to exploit actinomycetes resources.Resuscitation promoting factors (Rpf), a class of proteins secreted by gram-positive bacteria including actinobacteria, promote the resuscitation of dormant bacteria and spore germination. Here, we describe the reconstitution of the resuscitation promoting activity of the Rpf protein from  Micrococcus luteus [M. luteus [M. luteus was a member of a large family of the secreted bacterial Rpf-like proteins among the phylum Actinobacteria, including the representatives of Mycobacterium, Corynebacterium, Nocardia, Rhodococcus and Streptomyces genera. The number of the rpf gene orthologs for each species varies from 1 to 5 [M. luteus, Mycobacterium tuberculosis, Mycobacterium smegmatis and Mycobacterium bovis, have been used in vaccine development [M. luteus could promote the isolation and culture of actinomycetes [Rpf (resuscitation promoting factor) is a ≈16–17 kDa protein, first identified by Mukamolova et al. in 1998 in . luteus . The prom 1 to 5 ,4,5, andm 1 to 5 . To dateelopment ,12,13,14elopment ,16,17 anelopment ,25,26,27omycetes .Actinomycetes are microorganisms that have considerable importance in the production of antibiotics ; they arNocardiopsis halophila, a halophilic actinomycete isolated from a saline soil sample in Iraq [N. halophila CGMCC 4.1195T, and found a single copy rpf gene with a size of 1251 bp encoding a protein of 416 amino acids. In this study, we aimed to clone and express the Rpf protein from N. halophila CGMCC 4.1195T and verify its resuscitation function, laying the foundation for mining extreme environmental actinomycetes resources.Rpfs, acting as cell-wall-Lytic enzymes, have been implicated in the cleavage of dormant bacterial cell walls and the subsequent promotion of growth and metabolic reactivation in actinobacteria , which m in Iraq , is an ehttps://www.uniprot.org/) (accessed on 29 January 2023). Prediction of protein domain was carried out using HMMER (https://www.ebi.ac.uk/Tools/hmmer/) (accessed on 29 January 2023). Homology modeling was performed using Swiss-Model (https://swissmodel.expasy.org/interactive) (accessed on 29 January 2023) [Multiple sequence alignment was performed on the UniProt portal (ry 2023) . Alignmery 2023) . MEGA X ry 2023)  was usedThe test strains, recipient strains and vectors used in this study are shown in N. halophila CGMCC 4.1195T was cultured in Salt Tolerance Medium (STM) broth 2SO4, 1 g K2HPO4, 1 g MgSO4·7H2O, 1g NaCl, 2 g CaCO3, add an additional 100 g NaCl and 1000 mL deionized H2O, pH 7.2) at 28 °C, 180 r/min for 3–5 d. The cultures were centrifuged at 10,000 rpm for 10 min at 4 °C, and the pellets were washed with sterile water and stored at −20 °C. rpf gene from N. halophila CGMCC 4.1195T genomic DNA which was extracted using Bacterial Genome Small Quantity Extraction Kit , referencing manufacturer’s instructions. The amplification procedure were as follows: predenaturation at 95 °C for 5 min, denatured 15 s at 95 °C, annealing 15 s at 65 °C, extension at 72 °C for 30 s, 30 cycles. The resulting PCR products were purified using a MiniBEST agarose gel DNA extraction kit  and sequentially digested with EcoRI and XholI and ligated with pMD18-T vector , which had been digested with the EcoRI and XholI, using T4 DNA ligase . The resulting ligation mixture (pMD18-T:rpf) was used to transform E. coli DH5α chemically competent cells  referencing the manufacturer’s instructions and then plated on LB medium containing ampicillin (100 μg mL−1). A MiniBEST plasmid purification kit  was used to extract plasmid from transformants, and the predicted sequences confirmed by sequencing . The PCR primers in rpf and pET 28a(+) plasmid was all digested using the EcoRI and XholI, and both digested rpf gene insert and vector were cut from agarose gels and purified using a MiniBEST agarose gel DNA extraction kit (TaKaRa) and sequentially ligated using T4 DNA ligase (TaKaRa). The resulting ligation mix (pET 28a(+):rpf) was used to transform chemically competent cells of E. coli BL21 codon plus (DE3)(Sangon Biotech) and then plated on LB medium containing kanamycin (50 μg mL−1). The pET 28a(+):rpf plasmid extraction and the rpf gene sequences confirmation were as above.The purified pMD18-T:E. coli BL21 codon plus (DE3) colonies including pET 28a(+):rpf were inoculated in 10 mL cultures supplemented with kanamycin (as above) and chloramphenicol (25 μg mL−1) and grown at 37 °C overnight, and then the cultures were inoculated into 500 mL of LB medium containing kanamycin (as above) and chloramphenicol (as above) and grown at 37 °C until an optical density of 0.6 to 0.8 at 600 nm (OD600), followed by induction with 50 mM IPTG . Cells containing pET 28a(+):rpf were grown at 37 °C for a further 3 h before harvesting by centrifugation . The cell pellets were collected and resuspended in Native IMAC lysis buffer  containing lysozyme (1mg·mL−1). The mixture was then sonicated by Ultrasonic Process or inanicebath for 15 min with 5 s pulse and 5 s break, and centrifuged at 10,000 r/min for 20 min at 4 °C. Recombinant Rpf was purified with Ni2+ affinity chromatography Protein Purification Kit  with reference to the manufacturer’s instructions, and analyzed using SDS-PAGE. The protein was filtered and sterilized using a sterile 0.22 µm sterile millipore polytetrafluoroethylene membrane and finally stored in a refrigerator at −20 °C. The concentration of the recombinant Rpf protein was determined by the Lowry method [The positive clone of N. halophila CGMCC 4.1195T was inoculated in STM broth and cultured oscillatively at 200 r/min, 28 °C for 3-5 days. The cultures were collected and centrifuged at 4 °C at 6000 r/min for 10 min, and the cell pellets were washed using sterile saline solution (repeated three times). Finally, the cell pellets were re-suspended in sterile saline solution and stored in a refrigerator at 4 °C for at least three months (one year in this experiment) [eriment) . In the N. halophila was diluted 10-fold with STM broth before adding purified recombinant Rpf protein to a final concentration of 1, 0.1 and 0.01 mg/mL, respectively, and then incubated on a shaker at 28 °C. The group without recombinant Rpf protein was used as the control group. Each group was repeated 3 times. The staining of resuscitated bacteria was observed by Confocal laser scanning microscope  on days 3, 5 and 7, on which propidium iodide  and fluorescein diacetate  were used as fluorescent stains [To investigate the resuscitating ability of purified recombinant Rpf protein, a sample of VBNC t stains . In addiN. halophila CGMCC 4.1195T was extracted as outlined above and used to amplify the homologous arms of rpf with the primers shown in XbaI and BamHI sites to construct the recombinant plasmid pJTU1278: left. Similarly, the right arm was amplified using the primers R-F/R-R . The constructed knockout vector was transferred into E. coli ET12567 (pUZ8002) for later use.DNA genome of  R-F/R-R  and inseE. coli ET12567 (pUZ8002) with knockout vector was inoculated in LB liquid medium containing chloramphenicol (25 μg mL−1) and ampicillin (100 μg mL−1), and cultured overnight at 37 °C. On the second day, a small amount of culture was transferred to a fresh 50 mL LB medium containing chloramphenicol (as above) and ampicillin (as above), and cultured until an optical density of 0.5 to 0.6 at 600 nm (OD600). The cultures were centrifuged at 10,000 r/min for 10 min at 4 °C and the cell pellets were collected, washed with fresh LB medium 2–3 times, and then suspended with equal volume LB medium to be used as conjugation transfer donor. N. halophila CGMCC 4.1195T from fresh cultures grown on the slant of STM were gently scraped off and added into 5 mL sterile water, and the spores suspension was placed in a sterilized 100 mL triangular flask with several sterile glass beads. The flask was shaken thoroughly to disperse the spores, filtered with sterilized cotton, and washed using 0.9% NaCl saline. Finally, the spores were resuspended with 0.9% NaCl saline and divided into 100 μL portions in 1.5 mL Eppendorf tubes.Spores of 4~108 CFU  for 30 min. The mixtures were spread on STM plates without antibiotics, blow-dried, and incubated at 28 °C for 16~20 h. The surfaces of the plates were covered with l mL sterile water containing nalidixic acid (75 μg mL−1) and thiostrepton (37.5 μg mL−1), and the white zygotes were observed after being blow-dried and cultured at 28 °C for 3–5 days. Finally, the zygotes were verified by colony PCR and sequencing, and the zygote lacking the rpf gene was used as deletion mutant Δrpf strain. The spore suspension was put into a 50 °C water bath pot for heat shock treatment for 10 min, and then transferred to 37 °C water bath pot for 0.5–1 h culture (pre-germination). The pre-germinated spores were washed in LB medium three times, and suspended in 100 μL LB medium as recipients. It was mixed with donors of 10rpf strain were coated on STM agar plates, respectively. The growth of the strains were observed at days 3, 5, and 7. At the same time, the sporulation was observed with optical microscope and scanning electron microscopy. In addition, we observed and monitored the growth of wild-type and Δrpf strain in STM broth for 7 days using an automatic growth curve analyzer . The above experiments were repeated 3 times.The wild-type strain and Δp < 0.05).The GraphPad Prism (Version 9.4.1) was used for statistical analysis. Mean ± standard deviation (SD) for each parameter was calculated using the data of all three replicates. The unpaired T test was used to analyze the significance level  (accessed on 29 January 2023). The results showed that the Rpf coding chain has five domains as shown in M. tuberculosis, M. smegmatis, Streptomyces coelicolor, Rhodococcus erythropolis, Corynebacterium glutamicum, Mycobacterium ulcerans and M. luteus.Domains in the https://www.uniprot.org/align) (accessed on 29 January 2023) for the amino acid sequences of the Rpfs of N. halophila, M. luteus, S. coelicolor, M. tuberculosis, M. smegmatis, R. erythropolis, C. glutamicum and M. ulcerans. It was found that they had in common a conserved domain with a similar amino acid sequence (approximately 75 amino acid residues)  . This waN. halophila, M. luteus, M. tuberculosis, M. smegmatis, R. erythropolis, S. coelicolor C. glutamicum and M. ulcerans. The results showed that the Rpf protein of N. halophila and the Rpf B protein of S. coelicolor belong to the same branch of evolution  of the RpfB protein of M. tuberculosis were the most closely correlated, and the sequence identity between them was 28.22%. The alignment of the tertiary structures of the two Rpf proteins was assessed using PyMol Version 2.5.4 [http://wishart.biology.ualberta.ca/SuperPose/) (accessed on 29 January 2023). If all atoms are considered, the RMSD between the overall structure is 3.79 Å. If only the carbon skeleton is considered, the RMSD between the overall structure is 3.36 Å. From the RMSD value, we think that the two proteins are similar in structure.Homology modeling of the Rpf protein of on 2.5.4 . The terN. halophila CGMCC 4.1195T was used as a template to prepare rpf genes using primers in E. coli BL21 codon plus (DE3) from plasmid pET 28a(+): rpf, and was purified from the cell extract with Ni2+ affinity chromatography. The purified recombinant Rpf protein was filtered and sterilized through a 0.22 μm sterile filter and adjusted to 2 mg/mL and stored in a refrigerator at −20 °C.The genomic DNA of N. halophila CGMCC 4.1195T. The resuscitating effect of the Rpf on the bacteria was observed using Confocal laser scanning microscope  on days three, five and seven and is shown in N. halophila CGMCC 4.1195T was most evident when 0.1 mg/mL of the recombinant Rpf protein was added to the medium. In addition, the same results were obtained from the growth curves of VBNC N. halophila CGMCC 4.1195T at different Rpf protein concentrations  was slower than that of the wild strain in the early days. The wild-type strain had weak colonies at 3 days, however the Δrpf bacteria could not be observed. At 5 days, the wild-type had more colonies than the Δrpf group (rpf strain at 1–5 days (p < 0.05); at three days p = 0.0027, at five days p = 0.0007 (rpf) produced significantly shorter spores than the wild-type strain (p < 0.05)  A,B. WhetM. luteus, which could resuscitate VBNC bacteria [M. luteus was a member of a large family of the secreted bacterial Rpf-like proteins among many gram-positive (G+C)-rich bacteria belonging to the phylum Actinobacteria [M. tuberculosis and S. coelicolor could also reactivate VBNC bacteria or dormant spores [rpf gene, with a size of 1251 bp, encoding an Rpf-like protein in the genome of N. halophila. Bioinformatics analyses showed that the Rpf-like protein had approximately 75 conserved amino acid residues similar to the M. luteus Rpf protein [S. coelicolor [N. halophila and the template (5e27.1.A) of the RpfB protein of M. tuberculosis were the most closely correlated, and the RMSDs between the two proteins were 3.79 Å  and 3.36 Å (where only the carbon skeleton was considered), respectively. So, we speculate that the Rpf-like protein has a resuscitation function similar to the Rpf proteins of M. tuberculosis and M. luteus.Rpf was first found in the culture supernatant of bacteria . Subsequbacteria . Moreovet spores ,36. We p protein  . Different concentrations of Rpf protein were added to VBNC bacteria and observed with confocal fluorescence microscopy. The results showed that the recombinant Rpf-like protein from N. halophila had a significant resuscitation effect on the VBNC N. halophila, and the resuscitation effect was most obvious when 0.1 mg/mL of the recombinant Rpf protein was added  in the sporulating mother cell decreases germination efficiency. Eno is phosphorylated by the conserved Ser/Thr protein kinase PrkC which decreases the catalytic activity of Eno, and phosphorylation also regulates Eno expression and localization, thereby controlling the overall spore germination process [rpf null strain of Streptomyces [It was reported that loss of the mination . Howevermitation . These dmitation . The surrculosis ; they mirculosis  reported process . There wptomyces . HoweverN. halophila obtained in this study can be used to mine halophilic actinomycetes resources from extreme halophilic environment samples, and to improve the culturability of halophilic actinomycetes in the future. This will lay the foundation for further studying the function of Rpf proteins of different actinomycetes. Although this study did not focus on the relationship between the structure and function of Rpfs, nor the detailed mechanism of Rpf protein promoting spore germination, we plan to take them as the contents of further in-depth research in the future.In short, based on the resuscitation function, the Rpf protein of


The available ice out (the date of disappearance of ice from a water body) records were analyzed from four relatively closely spaced lakes in southwestern New Brunswick  and eastern Maine (West Grand Lake), with the longest set of available observations being for Oromocto Lake starting in 1876. Results of a coherence analysis carried out on the ice out data from the four lakes indicates that there is regional coherence and correspondingly, that regional drivers influence ice out. These results also indicate that ice out dates for lakes from the region where records have not been kept can also be interpolated from these results. As the ice out record was coherent, further analysis was done for only Oromocto Lake on the basis of it having the longest ice out record. Cross-wavelet analysis was carried out between the ice out record and a variety of cyclic climate teleconnections and the sunspot record to identify which phenomena best explain the observed ice out trends. The most important observed contributors to ice out were the North Atlantic Oscillation (NAO) and the El Niño Southern Oscillation (ENSO), with observed periodicities at the interannual scale. At the decadal scale the Pacific Decadal Oscillation (PDO) and the 11-year solar cycle were the only patterns observed to significantly contribute to ice out. Ice phenology data comprises a series of annual dates corresponding to when ice forms in the fall (ice in/on) and recedes in the spring (ice out/off) . Ice in/e.g., Quasi-Biennial Oscillation (QBO), North Atlantic Oscillation (NAO), El Niño Southern Oscillation (ENSO)) has been recognized  to its frequency-domain counterpart, revealing the cyclic components of a given signal. Spectral analysis techniques have been used in many climate and environmental studies to provide information on the periodic nature of various systems and improve the understanding of recurrent patterns. Recognizing periodic patterns in natural systems helps provide context for observed changes, particularly when assessing the impact of quasi-linear processes   determine the spatial coherence of lake ice out in four closely spaced inland lakes from southwestern New Brunswick, Canada and eastern Maine, USA; (2) provide a robust assessment of the periodic nature of the ice out records; and (3) assess and correlate potential drivers of the periodic changes in ice out dates. The trends and cycles documented for seven well-known climatic oscillations—the Schwabe Solar Cycle (SSC), Arctic Oscillation (AO), Atlantic Multidecadal Oscillation (AMO), Pacific Decadal Oscillation (PDO), Quasi-Biennial Oscillation (QBO), North Atlantic Oscillation (NAO), and El Niño Southern Oscillation (ENSO)—will be compared against year over year changes in lake ice out dates to assess their relationships. Each of these oscillations and their effects on the study region are described in  change) . FurtherIce out records from three southwest New Brunswick lakes (Oromocto Lake (1876–2021), Skiff Lake (1933–2021), and Harvey Lake (1975–2021)) and one inland eastern Maine lake , all located within 75 km of each other , were obAll data analysis was completed using Matlab. Each ice out record was checked for normality and detrended prior to applying any spectral analysis techniques. The Julian date of recorded ice out was used in each of the analyses completed. These dates are relative to each lake. As the patterns in the ice out records are the points of interest in this study, this relative data did not require standardization. The Harvey, Skiff, and West Grand lakes ice out records were each, in turn, compared to the Oromocto Lake record using wavelet coherence (WTC) and Pearson’s correlation coefficients to assess spatial relationships within the study region. Oromocto Lake was chosen for this role due to it having, by two years, the longest ice out record of the four lakes. WTC transformations were carried out as they have been demonstrated to reliably identify local correlations between oscillating time series . The useTo assess long-term trends and fluctuations, locally weighted linear regressions (LOWESS) was carried out for each of the four lake ice out records over 20-year periods . The 95%Due to strong correlation and coherence between each of West Grand, Harvey, and Skiff lakes to Oromocto Lake, only the ice out record for Oromocto Lake was assessed for its periodic components (for simplicity) using spectral and wavelet analysis. Thomson’s Multitaper Method MTM,  was usedThe mean spectral estimate was compared to 80, 90, 95, and 99% false alarm levels, calculated using chi-square confidence estimate, and the red noise (AR1) model, calculated using a Monte Carlo loop  .x-axis indicating the time, a y-axis indicating the frequency or period, and a colour axis representing the spectral power. The 95% confidence interval was calculated using the chi-square estimate (Continuous wavelet transforms (CWTs) were used in tandem with the MTM to assess the time-frequency variation of the time series. Similar to the MTM, CWTs compare a waveform to a time series, the results of which present the spectral information of a time series; this method differs from the MTM, as it does not provide discrete spectral peaks, though it does indicate the variation in these signals in time . This tiestimate  and is svia cross wavelet transforms (XWTs). XWTs are a type of spectral transform similar to a CWT, in that the time-varying frequency information of time series is computed. However, the purpose of an XWT is not to present only this time-frequency information, but rather to compare a reference signal with an analyte signal to assess the common time-frequency components to the two signals. The resulting XWT scalogram appears the same as that of a CWT, though only the common elements time-frequency spectrum is displayed  and each analyte signal .The Oromocto Lake ice out record was then compared to each of the SSC , PDO De, AMO Tr, AO NCA, NAO Hu, ENSO T, and QBOisplayed . Using tWhile ice out dates can fluctuate by as much as 20 + days year over year, long-term averages in lake ice phenology are generally more consistent, only varying up to 10 days decade over decade . On Westr2 = 0.355, p = 0.004, df = 62), but are strongly coherent and correlated afterwards  with coherence primarily at interdecadal scales but increased after 1960 . Harvey Lake has the shortest available ice out record and shows strong and significant coherence . While the relationship for AMO is less significant (<95% confidence), there nevertheless exists an area of high incidence between the AMO and the ice out time series from approximately 1920 and 1980, with oscillations of 23–30 years. Furthermore, the beginnings of a 45+ year oscillation related to the AMO is just visible at the bottom of the AMO—ice out scalogram, indicating that the longer band of the AMO may have a relationship with ice out dates.At the interdecadal to multidecadal scales, the PDO, SSC, and AMO are of particular interest. The PDO shows strong relationships with cycles within the 15–18-year band (most significantly from ∼1940–1960) as well as a 23–34-year oscillation from 1920–1965. The SSC is linked to ∼7–13-year oscillations in the ice out dates, most significantly from 1900–1980. Less significant relationships exist during times of weak quasi-decadal oscillations in ice out  from the mid 20th century until his recent passing. The reporting of ice out on Oromocto Lake is now carried out collaboratively by many members of the Oromocto Lake Association using the same criteria as used by Clayton Piercy, but now aided by real time simultaneous social media monitoring of the entire lake. Prior to the mid 20th century, reports were made by many people at different locations on the lake, where based on examination of the data, ice out may have been declared when ice disappeared from the main body of the lake, and not slightly later when it disappeared from coves . This unIce out in the study area is primarily dominated by interannual oscillations in the ∼2–8 year range  and 5. AThe AO exhibited a relationship to ice out similar to that of the ENSO and NAO, though it was generally weaker . The NAO is a geographically localized subset of the AO with both being products of oscillations in atmospheric pressure which, in turn, impact atmospheric circulation and the movement of airmasses . While tThe QBO exhibited a relationship to observed ∼2–3 year oscillations in ice out, which suggests that it plays a role in driving interannual ice out variability, albeit less importantly than for the ENSO and NAO though. The QBO has previously been attributed as the driver of ∼2-year variations in ice out along the east coast of North America , and hasInterdecadal oscillations in ice out in these lakes were primarily correlated to the SSC and the PDO. While the quasi-decadal signal in the ice out time series was generally weak, it has a strong relationship to the SSC. This result suggests that while quasi-decadal oscillations are not always prominent in the ice out record, in the instances when they are present, they are primarily driven by the SSC. A strong relationship between the SSC and quasi-decadal oscillations has been previously observed for both ice out records  and tempe.g., 1890, 1925, and 1947) are somewhat recognizable in the PDO–ice out relationships  may be distorted outside of the cone of influence . The CWTLastly, a brief instance of an interdecadal-scale relationship was depicted between ice out and the QBO between approximately 1953–1980. This result likely stems from a modulatory effect between the SSC and the QBO, reported in several studies , which hThis study examined four inland lakes, all within 75 km of each other in eastern Maine and southwest New Brunswick, to assess regional drivers of ice out variability. The ice out records of three of these lakes  were first compared to that of Oromocto Lake in New Brunswick, as it had the longest record, to assess the presence of regionally consistent patterns. The lakes in the region were strongly correlated and coherent with Oromocto Lake’s ice out record, particularly from the mid-20th century, suggesting regional consistency in ice out patterns and their drivers. Inconsistencies prior to the mid-20th century may be attributed to changes in data-gathering methodology and personnel, though this hypothesis has not been confirmed.via spectral, CWT, and XWT analysis. These time-series analysis techniques suggest that most ice out variation occurs primarily at the interannual scale. These variations are generally related to the ENSO and the NAO, particularly for periods of 4–8 years. Lower interannual oscillations (2–3 years), while less prominent in the ice out time series, are related to the QBO. Interdecadal to multidecadal variations form a secondary component of the ice out time series, and are most strongly driven by the SSC  and the PDO (15–25 year). A good understanding of the role of trends and cycles of regional climate drivers on ice out allows for the prediction of both future variation in regional lake ice out and regional climate. This is of importance as this data will inform policy makers and planners when considering future recreation, economic development, and environmental practices as they relate to adapting to changes in regional climate. Of particular environmental concern is that the length of the open water season is driven by ice out, which in turn significantly impacts lake ecosystems, particularly the significant emergent environmental threat to the region, cyanobacteria blooms.Oromocto Lake ice out was then compared to various climatic oscillations 10.7717/peerj.13741/supp-1Article S1Click here for additional data file.10.7717/peerj.13741/supp-2Data S1Click here for additional data file.10.7717/peerj.13741/supp-3Figure S1Cross wavelet transforms (XWTs) between lake ice out records and each of the SSC, PDO, AMO, ENSO, NAO, AO, and QBO. Time scales all span 1876–2020 for easy comparisons.Click here for additional data file.


Dehalococcoides) were measured at low abundances (101–102 cells/mL) within the TCE source and plume areas. In combination with geochemical analyses, these data suggested that intrinsic biodegradation  may be occurring, but activities were limited by electron donor availability. The framework was utilized to support development of a full-scale enhanced bioremediation design  and to monitor remedial performance. Additionally, the framework was applied at a second site with residual petroleum hydrocarbon (PHC) impacted soils and groundwater. MBTs, specifically qPCR and 16S gene amplicon rRNA sequencing, were used to characterize intrinsic bioremediation mechanisms. Functional genes associated with anaerobic biodegradation of diesel components  were measured to be 2–3 orders of magnitude greater than unimpacted, background samples. Intrinsic bioremediation mechanisms were determined to be sufficient to achieve groundwater remediation objectives. Nonetheless, the framework was further utilized to assess that an enhanced bioremediation could be a successful remedial alternative or complement to source area treatment. While bioremediation of chlorinated solvents, PHCs, and other contaminants has been demonstrated to successfully reduce environmental risk and reach site goals, the application of field-scale MBT data in combination with contaminant and geochemical data analyses to design, implement, and monitor a site-specific bioremediation approach can result in more consistent remedy effectiveness.Leveraging the capabilities of microorganisms to reduce (degrade or transform) concentrations of pollutants in soil and groundwater can be a cost-effective, natural remedial approach to manage contaminated sites. Traditional design and implementation of bioremediation strategies consist of lab-scale biodegradation studies or collection of field-scale geochemical data to infer associated biological processes. While both lab-scale biodegradation studies and field-scale geochemical data are useful for remedial decision-making, additional insights can be gained through the application of Molecular Biological Tools (MBTs) to directly measure contaminant-degrading microorganisms and associated bioremediation processes. Field-scale application of a standardized framework pairing MBTs with traditional contaminant and geochemical analyses was successfully performed at two contaminated sites. At a site with trichloroethene (TCE) impacted groundwater, framework application informed design of an enhanced bioremediation approach. Baseline abundances of 16S rRNA genes for a genus of obligate organohalide-respiring bacteria (i.e.,  Traditiotential . Additiootential .Over the past 20 years, MBTs have been increasingly utilized, due to scientific advancement and decreased analytical cost, to directly assess microbiological processes at contaminated sites . MBTs, sDehalococcoides) along with contaminant trends and geochemical data were utilized to develop a full-scale enhanced bioremediation design and to monitor remedial performance. At a second site with residual petroleum hydrocarbon (PHC) impacted soils and groundwater, MBTs, specifically qPCR and 16S rRNA gene amplicon sequencing (NGS), were used to identify and characterize contaminant-degrading microorganisms and associated biodegradation activities to assess the feasibility of a MNA approach within the downgradient plume and an enhanced bioremediation approach  within the source area.A framework was developed to demonstrate how MBTs could be consistently applied at the field-scale to reduce uncertainty of subsurface biological processes and support decision-making using site-specific biogeochemical data . This fr2.2.1.in situ biogeochemical processes, design a bioremediation approach, and measure bioremediation performance using field-scale MBT data. Many of the details applied through the framework at these two sites, such as tool selection and sampling plan development, were aligned with ASTM E3354 Standard Guide for Application of Molecular Biological Tools to Assess Biological Processes at Contaminated Sites  at locations across the area of interest and across intrinsic contaminant concentration or geochemical gradients. Spatial and temporal contaminant trends provide empirical evidence of attenuation and biodegradation, while geochemical results help to elucidate potential associated biodegradation mechanisms and potential electron acceptor/donor limitations to intrinsic biodegradation. MBTs are evaluated to determine the presence and abundance of contaminant-degrading microorganisms or enzymes, and the inferred extent of intrinsic biodegradation. When the results of the assessment stage suggest a bioremediation approach is feasible, the contaminant, geochemical, and MBTs results are evaluated during the Stage 2: Design to support determination and design a site-specific bioremediation strategy. For natural bioremediation strategies, these data should provide conclusive evidence to support occurrence of intrinsic bioremediation across the area of interest. Additionally, the contaminant, geochemical, and MBT data should guide the design of the natural bioremediation monitoring program. If the results of the Assessment Stage indicate enhanced bioremediation  is warranted to meet site goals, the contaminant, geochemical, and MBTs data can guide approaches to enhance attenuation by adding a site-specific amendment , and/or microbial cultures  to areas of residual impacts. Following implementation of the natural or enhanced bioremediation strategy, the Stage 3: Performance Monitoring includes generating and monitoring contaminant, geochemical, and MBT data to assess remedy progress toward objectives. Because spatiotemporal contaminant trends can be confounded by complex fate and transport processes that complicate biodegradation and remedy performance determinations, MBTs and geochemical data can be helpful to demonstrate biogeochemical effects of the remedy, and in some cases serve as a leading indicator of remedy performance.The framework staged process begins with the 2.2.The framework approach was applied and validated at a former manufacturing site where trichloroethene (TCE) was used during manufacturing activities that resulted in impacted soil and groundwater. Groundwater impacts extend across three general hydrostratigraphic depth zones  within the underlying eolian loess deposits. Hard-pan horizons characterized by comparatively lower hydraulic conductivity separate the hydrostratigraphic zones. Within each zone, groundwater generally flows to the south. Site investigation activities, primarily high-resolution site characterization using membrane interface probe (MIP) technology, identified the transport of TCE-impacted groundwater is controlled by lateral migration along the hard-pan layers until isolated areas of vertical fractures are encountered that facilitate downward transport into the underlying hydrostratigraphic zone. These transport mechanisms result in a stair-shaped plume, as shown by MIP results in 2.3.The field-scale framework was applied to a former PHC bulk storage terminal that operated from at least the 1920s to the 1990s. Soil and groundwater impacts have been investigated across the site and have observed free-phase, light non-aqueous phase liquid (LNAPL) in shallow soil and in the shallow water table zone which generally fluctuates one to five feet below the ground surface. Multiple source areas characterized by observations of LNAPL are present within the former site footprint . ShallowThe primary contaminants at the site are PHC, primarily diesel range organics (TPH-Dx) and gasoline range organics (TPH-Gx). TPH-Dx is detected most consistently above regulatory thresholds across the site in soil and groundwater and beyond the site within the shallow, dissolved-phase groundwater plume . TPH-Gx 2.4.Groundwater sampling was performed at Sites 1 and 2 during the field-scale framework stages in a systematic approach to characterize contaminant and geochemical conditions within impacted areas, including source and downgradient plume areas, and from background sample locations for comparative purposes. Groundwater samples were collected using low-flow groundwater sampling methods .Groundwater sampling at Site 1 was performed to establish contaminant concentrations and geochemical conditions across the lateral and vertical extent of the groundwater plume at groundwater monitoring wells during the Assessment Stage baseline characterization (nine monitoring wells), Design Stage pilot-scale implementation (four monitoring wells), and remedy Performance Monitoring Stage (nine monitoring wells). Contaminant analyses included volatile organic compounds  and ethene (US EPA Method RSK-175), a non-toxic reductive dechlorination end product. Geochemical analyses included general biogeochemical indicators , potential bacterial electron acceptors (nitrate and sulfate by US EPA Methods 353.3 and 300.0 respectively), potential by-products of anaerobic microbial respiration , and organic carbon growth substrate availability . Samples for contaminant and biogeochemical indicators were analyzed by a certified, commercial analytical laboratory .Groundwater samples were collected at Site 2 to supplement historical contaminant and biogeochemical indicator data from the background, source area, and downgradient plume monitoring wells during the Assessment Stage baseline characterization (seven monitoring wells) and from six pilot study monitoring wells during the Performance Monitoring Stage. Contaminant analyses included PHCs (TPH-Dx and TPH-Gx by NWTPH) and BTEX (US EPA Method 8260C). Biogeochemical indicator analyses included general biogeochemical indicators , potential bacterial electron acceptors (nitrate and sulfate by US EPA Method 300.0), and potential by-products of anaerobic microbial respiration . Samples for contaminant and biogeochemical indicators were analyzed by a certified, commercial analytical laboratory .2.5.Groundwater samples (500 mL to 1 L of groundwater) were collected from Sites 1 and 2 to supplement contaminant and geochemical data to characterize microbiological conditions and potential contaminant biodegradation processes. Groundwater samples for molecular analyses were collected concurrently with contaminant and geochemistry samples from monitoring wells within impacted areas, including source and downgradient plume areas, and from background monitoring well locations for comparison. Groundwater samples from Sites 1 and 2 were shipped overnight on ice to Microbial Insights, Inc. of Knoxville, TN (MI). MI personnel extracted DNA from the groundwater samples.Dehalococcoides (DHC) 16S rRNA gene, a genus capable of complete, sequential reductive dechlorination of TCE (and tetrachloroethene) to the non-toxic end product ethene (qPCR was performed on the Site 1 samples for PCR primers targeting the t ethene . DHC obtt ethene .bcrA) gene implicated in cleavage of the benzene ring structure under anaerobic conditions (bssA) gene implicated in anaerobic biodegradation of toluene and xylenes (mnssA) gene (assA) which is linked to anaerobic biodegradation of alkane PHCs. Further, the adenosine-5′-phosphosulfate reductase gene (APS) characteristic of sulfate-reducing bacteria  for which quantities are added as previously described , qPCR analysis was performed on the Site 2 samples to detect and quantify functional genes related to anaerobic PHC biodegradation mechanisms including the benzoyl coenzyme A reductase  gene , anaerobsA) gene , and alkria SRB; , which cria SRB; . MI perfescribed .All qPCR analyses were performed using TaqMan™ 2X Universal PCR Master Mix (Thermo Fisher Scientific™) and were run on the QuantStudio™ 12 K Flex (Thermo Fisher Scientific™) with a thermal cycling amplification profile for including a single cycle of 2 min at 50°C for uracil-N-glycosylase (UNG) enzyme activation, followed by a single cycle of 10 min at 95°C to inactivate UNG enzyme, template DNA denaturing, and AmpliTaq Gold polymerase activation, followed by 40 cycles of 15 s at 95°C and 1 min at 60.0°C for repeated denaturing, polymerase annealing, and extension . qPCR da®) and Nextera Index Kit V2 Set A (Illumina®) and were run on the MiSeq (Illumina®). Universal primers targeting the V3 and V4 regions of bacterial 16S rRNA genes were used as previously described (®).Additionally, taxonomic 16S rRNA gene sequencing  was performed to assess microbial community composition and potential phyla and genera linked to PHC biodegradation. MI performed NGS of the 16S rRNA gene utilizing MiSeq Reagent Kit V3 300 cycle  may have been useful to assess and demonstrate 3.3.1.in situ biostimulation strategy to treat TCE and lesser chlorinated daughter products.The field-scale framework was applied and SSBOs were established to assess the potential for natural or enhanced bioremediation of the primary contaminant, TCE. Baseline chemical characterization as part of the initial step of the framework process was performed and demonstrated that TCE and the first reductive dechlorination daughter product, cis-1,2-dichloroethene (cDCE), were the dominant contaminants present in saturated soil  and groundwater. Vinyl chloride  and non-toxic end products, ethene and ethane, were generally absent in groundwater suggesting that complete reductive dechlorination of TCE was not occurring . Since T3.1.1.1–103 cells per milliliter (cells/mL); detection limit of 10−1 cells/mL] that likely limited the rate of biodegradation. Therefore, while the requisite dechlorinating bacteria were present demonstrating that a bioremediation approach was feasible, the data indicated that biostimulation could be a useful strategy to increase the availability of fermentable substrates and promote geochemical conditions favorable for sustained in situ bioremediation through reductive dechlorination.Initial baseline geochemical characterization in November 2010 indicated that while plume conditions were anaerobic as shown by the absence of dissolved oxygen in groundwater monitoring wells, the geochemical conditions were not favorable for intrinsic reductive dechlorination . Detecti3.1.2.The contaminant, geochemical, and MBT data generated during the Assessment Stage provided MLOE that a biostimulation approach to enhance intrinsic bioremediation could be effective. The Assessment Stage results indicated that low levels of natural organic carbon in the source area and associated groundwater plume likely limited the intrinsic reductive dechlorination capacity of native dechlorinating microorganisms. Therefore, based on these data and hydrogeologic understanding, injection of a soluble organic carbon amendment (sodium lactate solution) was posited to be effective in enhancing intrinsic reductive dechlorination activities. During the Design Stage, the mass of lactate in the amendment solution  was calculated to provide the electron equivalents necessary to satisfy the demand for reductive dechlorination of chlorinated contaminants in aqueous and sorbed phases (assuming equilibrium partitioning to aquifer solids) and other competing electron acceptors in the system  over a period of four injection events .7 DHC cells/mL), which was added to the three pilot injection wells (2 L per well) during the fourth quarterly amendment injection event. DHC abundance increased by up to three orders of magnitude (OoM) after the fourth injection event (105–108 cells/mL) and cDCE concentrations decreased while the concentration of ethene increased  amendment injections  in three injection wells that targeted the shallow and intermediate portion of the plume nearest the source area between November 2010 and August 2011. Pilot performance groundwater samples for contaminant chemistry, geochemical indicator parameters, and MBTs  were collected from four groundwater monitoring wells  ~2 months after each injection. With the exception of Well #7, which was determined to be outside of the radius of influence of injections, TCE concentrations decreased following the first injection and remained <50 μg/L in pilot wells following the second and third injections . Conversncreased .The pilot test results during the Design Stage were used to conclude that (1) injection of a lactate amendment could favorably achieve biogeochemical conditions that promote reductive dechlorination, and (2) biostimulation was unlikely to stimulate growth of native DHC to support complete reductive dechlorination at the site and bioaugmentation was warranted following establishment of appropriate, reducing geochemical conditions.3.1.3.Following and informed by the pilot test, an expanded amendment injection program was designed, and implemented with 31 additional on-site and off-site injection wells in the shallow source area and the intermediate and deep hydrostratigraphic zones of the dissolved plume . AmendmeSimilar to the pilot test, groundwater samples were collected from nine on-site and off-site monitoring wells ~1 month prior to each amendment injection event for contaminant chemistry, geochemical indicator parameters, and MBT data (DHC abundances). Overall, the results of the full-scale amendment injection program mirrored the results of the pilot test. The amendment injections increased the availability of organic carbon (TOC concentrations >100 mg/L in remedy performance monitoring wells) and promoted geochemically reducing conditions favorable for reductive dechlorination. Following the first several on-site and off-site amendment injection events, TCE concentrations within the dissolved plume in the hydrostratigraphic zones decreased . Consist3–107 cells/mL in the intermediate zone and 103–106 cells/mL in the deep zone. cDCE levels generally decreased in the June 2013 groundwater sampling event in both intermediate and deep zones, while vinyl chloride and ethene also increased above baseline levels. Continued quarterly amendment injection continued until November 2014 and TCE, cDCE, and vinyl chloride levels decreased below baseline levels across the plume. Based on attainment of regulatory criteria across a substantial portion of the plume, the bioremediation strategy was shifted in March 2015 to a MNA strategy for a 3-year period to assess the long-term stability of the treatment area. The lack of plume rebound except for two isolated areas and the continued detection of DHC indicated that natural biodegradation capacity was sufficient to meet remedial and regulatory objectives and the site was transitioned to a long-term monitoring regulatory program.Bioaugmentation with the commercially available SDC-9™ DHC culture was added to the injection wells screened in the intermediate and deep treatment zones (2 L per injection well) during the April 2013 amendment injection event. Following bioaugmentation, abundances of DHC increased up to four and three OoM, respectively, to 103.1.4.Application of the field-scale framework at the Assessment Stage demonstrated that intrinsic reductive dechlorination was occurring at the site, but that the activities of native dechlorinating bacteria were limited by electron donor availability. Field pilot studies during the Design Stage demonstrated that injection of an organic carbon amendment could modify geochemical conditions to those that favor reductive dechlorination, but the MBT data  demonstrated that abundance of native populations of DHC did not substantially increase suggesting that bioaugmentation should be part of the remedial strategy at this site. Following full-scale implementation of the enhanced bioremediation strategy, groundwater monitoring during the Performance Monitoring Stage demonstrated remedy success through a MLOE approach, including decreasing plume contaminant concentrations (primary line of evidence), shift toward reducing geochemical conditions favorable for reductive dechlorination (secondary line of evidence), and increased DHC abundance following bioaugmentation and injections sufficient for enhanced bioremediation as determined by MBT analyses, specifically qPCR (tertiary line of evidence).3.2.The field-scale framework was applied to the Site and SSBOs were established to assess the potential intrinsic biodegradation capacity to assess whether bioremediation was applicable to mitigate Site contamination. As the initial step of the framework application, critical review of historical groundwater data collected between August 2010 and March 2018 demonstrated that plume contraction had occurred during this period within the source areas and in the downgradient plume . Due to 3.2.1.Analytical results of geochemical parameters indicated that anaerobic and strongly reducing biogeochemical conditions were present in the on-site source area, as monitored by W-1, W-15R, and MW-A1, and extend into the downgradient plume area, as monitored by MW-19, MW-A2, and MW-A4. Spatial distribution plots of key biogeochemical indicator parameters sulfate and dissolved methane are presented in bcrA) gene implicated in cleavage of the benzene ring structure under anaerobic conditions (bssA) gene implicated in anaerobic biodegradation of toluene and xylenes  and downgradient plume area monitoring wells , which were at higher abundances compared to the background area well . Abundances of functional genes associated with anaerobic biodegradation of TPH-Dx components, including naphthyl-2-methyl-succinate synthase (mnssA) gene  and downgradient plume monitoring wells  as compared to background (mnssA and ANC not detected above detection limits of 4.6 cells/mL). The abundance of alkylsuccinate synthase (assA) which is linked to anaerobic biodegradation of alkane PHCs was also elevated in the source area and plume samples (not detected to 5.2 × 102 cells/mL) as compared to background. Further, many SRB, detected and measured by APS  gene  and anaesA) gene  were alsd by APS , anaerobd by APS . The abuDechloromonas  was recommended for performance monitoring of MNA of the downgradient plume.Overall, the Assessment Stage data provide sufficient, strong evidence that supports occurrence of intrinsic bioremediation across the source area and downgradient groundwater plume. Given the collapse of the downgradient TPH-Dx plume to levels near regulatory criteria and demonstrated intrinsic biodegradation, a MNA approach was determined to be appropriate for the downgradient plume. A monitoring program developed during the Design Stage that includes continued sampling of downgradient plume monitoring wells  for analysis for contaminants, key geochemical indicator parameters , and key functional and taxonomic genes related to anaerobic biodegradation of PHCs  is potentially limiting the biodegradation capacity of the residual PHCs in the source areas . Therefo3.2.3.The sulfate amendment was initially injected in November 2020. One, two, and three months  after injection, performance groundwater samples were collected for analyses of contaminants (TPH-Dx and TPH-Gx), geochemical parameters, and MBTs  to assess the initial effects of the sulfate amendment on native microorganisms and associated anaerobic biodegradation of PHCs. As shown in the concentration trends presented in 4 cells/mL to 6.53 × 105 cells/mL), IW-2 (1.41 × 104 cells/mL to 2.09 × 105 cells/mL), OBS-2 (6.34 × 103 cells/mL to 2.23 × 105 cells/mL), and W-15R (5.59 × 104 cells/mL to 2.60 × 106 cells/mL) as shown in via qPCR, such as alkane succinate synthase (assA), or application of additional MBTs  may have provided further evidence to assess effectiveness of enhanced bioremediation of TPH constituents through biostimulation with sulfate.The sulfate dosage was subsequently increased to 30 kg of magnesium sulfate in 500 gallons of water for the second (February 2021) and third (May 2021) injection events. Owing to increased sulfate availability, abundance of SRBs (measured by APS) increased by more than one OoM in April 2021 as compared to February 2021 in IW-1  suggest that direct injection of a sulfate amendment could promote growth, increased abundance, and presumably activity of PHC-degrading SRBs. However, while SRB abundance did increase above pre-injection levels downgradient of the injection area suggesting increased biodegradation capacity, TPH-Dx and TPH-Gx concentration trends did not exhibit sustained decreasing concentration trends. These data suggest that a higher sulfate mass dosage and potentially a less soluble sulfate source, such as gypsum, to sustain elevated levels of sulfate for longer durations should be considered to enhance bioremediation capacity and activity at the site.3.2.4.Application of the field-scale framework at the Assessment Stage demonstrated that intrinsic biodegradation of the PHCs was occurring within the source and downgradient plume areas. MLOE including contaminant spatiotemporal trends, geochemical characterization, and abundance of functional genes and microorganism linked to anaerobic PHC biodegradation above background abundances provided strong evidence that groundwater remedial objectives could be achieved by natural intrinsic bioremediation. Yet, the data suggested that limited availability of electron acceptors may be restricting intrinsic bioremediation in the source area. The field pilot study developed during the Design Stage demonstrated during the Performance Monitoring Stage that a sulfate amendment could promote increased biodegradation by sulfate reduction mechanisms, but that substantial sulfate mass may be required to achieve success at full-scale implementation.4.Natural or enhanced bioremediation treatment strategies can be favorable approaches for contaminated site management as natural microorganisms present at impacted sites are capable of reducing (degrading or transforming) concentrations of a wide range of pollutants in soil and groundwater. Increasing application of MBTs to directly measure microbiological processes can reduce site uncertainties to better inform remedial decisions and increase the potential for success of bioremediation. Yet, while many publications and guidance documents extol the advantages of employing MBTs in concert with contaminant chemistry and geochemistry evaluations, MBTs application, implementation strategies, and data interpretation are inconsistent. To aid in demonstration of the utility of MBTs to increase knowledge of relevant subsurface microbiological processes, this study focuses on field-scale application of a standardized and systematic framework that pairs MBTs with traditional contaminant and geochemical analyses.The previously published framework describing a standardized approach to applying MBTs at the field-scale  was succIncreased application of a standardized approach that employs MBTs in concert with traditional analyses to assess physical, chemical, and biological processes has the potential to reduce site uncertainties, improve bioremediation effectiveness, and provide site managers and stakeholders greater confidence in contaminated site management. Further, it is hoped and anticipated that the associated framework applied and data herein to contextualize current field-scale use of MBTs, identify areas of improvement, and inform future targeted research. As example, potential areas for future research to further improve field-scale use of MBTs at contaminated sites include demonstrating comparative analysis of metabolomics or proteomics versus qPCR data at field-scale to improve or support bioremediation decision-making or conceptual site model development, and development of machine-learning algorithms to assist or automate data interpretation of field-scale MBT, contaminant, and geochemical data to decrease time between data generation and interpretation to support to more informed site decision-making.https://doi.org/10.6084/m9.figshare.21905697.v1.The original contributions presented in the study are publicly available. This data can be found here: AM and TK contributed to conception and design of this perspective. SS and YW refined and sharpened conceptual layout and messaging of content. AM and TK wrote sections of the manuscript. All authors contributed to manuscript review and read and approved the submitted manuscript.Funding and in-kind contributions were provided by ExxonMobil Environmental and Property Solutions Company, Golder Associates USA, Inc., and Imperial Oil Limited. The funder had the following involvement in the study: study design, interpretation of data, and the writing of this article.AM and SS were employed by Golder Associates USA Inc. YW was employed by Imperial Oil Limited. TK was employed by ExxonMobil Environmental and Property Solutions Company.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Uria aalge, an abundant and well‐studied colonially breeding seabird. Using time‐lapse photography, we recorded occupancy at breeding sites from October to March over three consecutive non‐breeding seasons. We then monitored the successive breeding timing (lay date) and breeding success at each site. On average, sites were first occupied on the 27th October ± 11.7 days (mean ± SD), subsequently occupied on 46 ± 18% of survey days and for 55 ± 15% of the time when at least one site was occupied. Higher‐quality sites, sites with higher average historic breeding success, were occupied earlier, more frequently and for longer daily durations thereafter. Laying was earlier at sites that were occupied more frequently and sites occupied earlier were more successful, supporting the site defense hypothesis. A path analysis showed that the return date had a greater or equal effect on breeding success as lay date. Pair level occupancy had no effect on breeding timing or success. The clear effect of non‐breeding occupancy of breeding sites on breeding timing and success highlights the benefits of this behavior on demography in this population and the importance of access to breeding sites outside the breeding season in systems where competition for high‐quality sites is intense.Competition for high‐quality breeding sites in colonial species is often intense, such that individuals may invest considerable time in site occupancy even outside the breeding season. The site defense hypothesis predicts that high‐quality sites will be occupied earlier and more frequently, consequently those sites will benefit from earlier and more successful breeding. However, few studies relate non‐breeding season occupancy to subsequent breeding performance limiting our understanding of the potential life‐history benefits of this behavior. Here, we test how site occupancy in the non‐breeding season related to site quality, breeding timing, and breeding success in a population of common guillemots  The relationship between occupancy of breeding sites in the non‐breeding season and subsequent breeding success is not well‐understood despite having likely impacts on population fitness. We used time‐lapse photography to record occupancy throughout the non‐breeding period, October–March, in a population of common guillemots to investigate how site occupancy related to site quality, timing of breeding, and breeding success. High‐quality sites were occupied earlier and more often with positive consequences for breeding timing and success and highlighting the benefits of this behavior on demography in this population and the importance of access to breeding sites outside of the breeding season in systems where competition for high‐quality sites is intense. Second, we tested whether sites that were occupied earlier, more frequently, and for longer were bred at earlier the following breeding season (hypothesis 2a), and had higher breeding success (hypothesis 2b). Third, we tested whether occupancy directly affected breeding success, or whether any effects were indirect and sequential such that site quality affected return date, then occupancy frequency, lay date, and ultimately breeding success (hypothesis 3). We investigated the three hypotheses in situations when only one individual, one or two individuals, or two individuals occupied a site to test whether any effects were dependent on the number of individuals present at the site.2The study was carried out on the Isle of May National Nature Reserve in the Firth of Forth, Scotland  from 2017 to 2020. We collected data on site occupancy during the non‐breeding season, timing of breeding, and breeding success in two areas (subcolony 1 and subcolony 2) of the large guillemot breeding colony on the island , we recorded breeding site occupancy in both subcolonies. We defined a breeding site as the small area of a cliff ledge, ~10 cm × 10 cm where a pair later incubated an egg. To ensure consistency when assigning birds to sites, we took images of both subcolonies during the preceding breeding season from the same vantage points and marked the locations of pairs to produce breeding site maps, assigning each a unique ID. We then recorded whether zero, one, or two birds were present at each of these sites for each time‐lapse image using the maps as a reference . In the vast majority of instances , birds were observed on their future breeding site. This supports earlier observations that in the non‐breeding season individuals only occupy the site where they subsequently breed  the ordinal first date on which one or two birds occupied a site (return date), (2) how frequently a site was occupied , and (3) the daily duration of time spent at a site relative to occupancy of other sites in the subcolony as indicated by the number of images on each day that a site was occupied divided by the number of images on each day where at least one bird was present in the subcolony (relative time investment).2.6We used general and generalized linear mixed‐models to test all hypotheses. All continuous explanatory variables were standardized for each subcolony and year prior to modeling by subtracting the mean and dividing by the standard deviation for each subcolony for each year. We included a random term of “Site ID” in all models to accommodate site level variation, not included in our covariates. Unless stated otherwise, we also included a random effect of “Subcolony Year”  to account for interannual and inter‐subcolony differences in occupancy, and/or breeding parameters that may arise from unmeasured environmental and individual factors.2.7Hypothesis 1Site quality and occupancy (site defense hypothesis).Prior to testing the effect of our three occupancy measures on timing of breeding and breeding success, we tested the associations between these measures. This was to establish whether sites occupied earlier were also those occupied more frequently during the non‐breeding season, and for longer each day, or whether these measures were independent of one another. To examine these relationships, we used two generalized linear mixed‐effects models with a binomial error structure and a logit link. In the first model, we tested whether those sites that were occupied earlier were occupied more frequently. The explanatory variable was return date, and our response variable was the occupancy frequency. In the second model, we tested whether sites that were occupied earlier and more frequently, were occupied for longer each day. Here, we included both the return date and the frequency with which a site was occupied as explanatory variables, and the relative time investment at a site each day as the response. We also included a two‐way interaction between return date and occupancy frequency to test whether the effect of occupancy frequency on the relative time investment at a site was intensified by returning earlier.n = 20 sites, 19 with three years and, one with one year of data). We tested each of these occupancy measures in three separate general linear mixed‐effects model, each with site quality as our explanatory variable and the occupancy measure as the response. For the model with return date as the response, we used a Gaussian error structure  and two‐sided Kolmogorov–Smirnov tests ). For the other two models, we used a binomial error distribution and a logit link. We included a fixed effect of “year” to test whether occupancy measures varied interannually.Hypothesis 2Occupancy and breeding.We tested for evidence of the site defense hypothesis that a key motivation for birds to occupy the breeding site in the non‐breeding season is to defend a high‐quality breeding site (hypothesis 1). We predicted that higher‐quality sites would have an earlier return date, be occupied more frequently, and for longer during the day. For this analysis, we used only data from subcolony 1 . Next, we tested our hypothesis 2b, that those sites that are occupied earlier, more frequently, and for longer had a higher likelihood of having a successful breeding attempt. Here, the breeding success of a site was our response variable, assuming a binomial error structure with a logit link . In both models, we included all two‐way and three‐way interactions to test whether any effect of occupying a site more frequently or for longer was intensified by occupying sites earlier than conspecifics.We then quantified the effects of the three occupancy measures on lay date (hypothesis 2a), and breeding success (hypothesis 2b). First, we tested our hypothesis 2a that those sites that are first occupied earlier, more frequently, and for longer had an earlier lay date in the following breeding season. Here, the ordinal lay date for a site was our response variable with a Gaussian error structure  all variables. For this analysis, we included only data from subcolony 1 as we did not have site quality measures for sites in subcolony 2.To test the support for each pathway, we used structural equation modeling in a Bayesian framework with three key model parts: data models which were the likelihood linking input data to the model parameters, process models linking the predictions from the model to the parameters and minimally informative prior distributions of parameters. For “Breeding success,” we assumed a Bernoulli probability, We ran the model with three chains, each with 200,000 iterations, a thinning interval of three and a burn in of 15,000. The model successfully converged under these parameters; the Gelman–Ruben statistics for all variables were between 1 and 1.05 . Following initial return to the colony, the proportion of sites occupied generally increased until plateauing in ~mid‐March when ~50% of sites were occupied each day Figure . There w3.2Overall, the mean date that a site was first occupied was October 27th ± 11.7 days (OD = 297). Sites were occupied for an average of 46 ± 18% of days during the non‐breeding period, and for 55 ± 15% of the time that a subcolony was occupied.R2 = .41, conditional R2 = .96). Return date alone explained a comparatively much smaller proportion of the variance in occupancy frequency . For both models, the most supported random effect structure contained a random intercept and slope for Subcolony year , but the relationship was weak, with a ten‐day difference in return rate resulting in a 2 ± 8% (±SE) increase in frequency. Those sites that were occupied earlier or more frequently were also occupied for longer on a given day . These two effects had a positive interaction with one another, such that sites occupied 10 days earlier were occupied 5.1 ± 17% (±SE) longer, and for an additional 6 ± 14% (±SE) longer for each 10% increase in how frequently sites were occupied  and vice versa. How early and frequently sites were occupied together explained almost half of model variance for how long sites were occupied  and “Site ID” (n = 58) contributed to a large part of model variance , reflecting the contributions of interannual and intersite variation in lay date.There was weak support for hypothesis 2a that sites that were occupied more frequently had an earlier lay date , and “Site ID” (n = 59) in the model explained a large proportion of model variance . This result likely reflects the susceptibility of breeding outcome to extrinsic factors between years untested here.Hypothesis 3Occupancy as a driver of breeding success.As with the tests on lay date, the random‐term component of “Subcolony Year” , 93.1% of posterior density greater than zero. The effect of return date on breeding success also had the most support of all pathway steps, such that 99.6% of the posterior was positive . Our results show that occupancy had important effects on breeding performance; sites occupied earlier were more successful, and sites occupied more frequently had an earlier lay date, so supporting our second hypothesis that occupancy will have benefits for breeding. Finally, we found support for a direct effect of occupancy on breeding success, as well as evidence for a separate indirect effect of occupancy affecting breeding success via timing of breeding. Both the direct and the indirect effects of non‐breeding site occupancy received equal or greater support compared with the direct effect of timing of breeding on breeding success. This is in broad agreement with our third hypothesis which predicted that the positive effects of occupancy would sequentially affect timing of breeding and in turn breeding success. Occupancy of sites in the non‐breeding season can hence have a central role in the well‐established relationship between breeding timing and success.Cinclus cinclus: Crowther et al., Milvus nigrans: Sergio & Newton, Fulmarus glacialis share these traits and, accordingly, a link between site quality and non‐breeding site occupancy has been well documented in the species ; data curation ; formal analysis (lead); investigation (lead); methodology ; project administration ; visualization (lead); writing – original draft (lead); writing – review and editing . Mike P. Harris: Conceptualization ; data curation ; investigation ; methodology ; validation ; writing – review and editing . Sarah Wanless: Conceptualization ; investigation ; methodology ; validation ; writing – review and editing . Jonathan A. Green: Conceptualization ; investigation ; methodology ; supervision ; validation ; writing – review and editing . Kate R. Searle: Formal analysis (supporting); investigation ; validation ; writing – review and editing . Mark A. Newell: Data curation . Francis Daunt: Conceptualization ; funding acquisition (lead); investigation ; methodology ; project administration ; resources (lead); supervision (lead); validation ; writing – review and editing .The authors declare no conflict of interests.