Parus major and blue tits Cyanistes caeruleus occupying three sites in habitats with contrasting urbanization level in central Poland. We found low but significant divergence of urban park population with both suburban and non-urban forest great tit populations, while no differentiation was found between suburban forest and non-urban forest populations. In contrast, no evidence for genetic differentiation was found between blue tit populations from the urban park, suburban forest and non-urban forest sites. We conclude that great tits and blue tits respond to urbanization-related changes in a different way, which may be a result of different rates of migration and/or dispersal, likely higher in blue tits. Some impact may be also induced by interspecific competition. We suggest that changing the focus of urban genetic research from single to multiple species may provide novel insights into how natural populations respond to the processes of urbanization.Landscape conversions induced by human activities can affect dispersal patterns of various bird species and, as a result, affect genetic structure of their populations. Genetic differentiation of bird populations may be enhanced by habitat variation, especially in urban-non-urban systems. The majority of population genetic studies focus on single species, which inflicts limitations for direct comparisons of genetic responses of avian populations to urbanization. Here, we used a set of microsatellite markers to examine genetic diversity, gene flow and population structure in two common parid species, great tits  Particularly, urbanization processes constitute relatively rapid and long-lasting alterations in the environment, triggering a major threat to wildlife5. Primarily, modern management of urban areas exerts a great impact on habitats, consequently leading to their loss, rearrangement and/or fragmentation7. Moreover, the great majority of urbanized areas have strongly altered energy flux, nutrient cycles, hydrology and temperature balance as well as increased levels of chemical, noise and light pollutions9. It is thought, that such habitat conversions affect population genetic diversity and structure of many terrestrial species. Even for highly-mobile organisms such as birds, which can easily avoid isolated and unfavorable habitats and fly over “city barriers”, this kind of genetic effects can also be found17. The greater landscape modification occurs, including mainly roads, housing, commercial property development and other anthropogenic pressures, the greater are limitations in movements of organisms and interactions between them, which ultimately can contribute to genetic isolation19. Hence, this factor can usually strongly impede gene flow and change allele frequencies, mainly leading to genetic diversity loss within isolated populations and increase of genetic differentiation between isolated populations21.The natural environment has been extensively modified by humans22. On the other hand, little or no genetic divergence of wild bird populations in human-altered habitats has also been reported26. Thus, it seems that the patterns of genetic diversity and genetic structure across urban and non-urban bird populations are heterogeneous and possibly species- or location-specific27, although urbanization is often evoked as a crucial trigger in the processes of diversification. To get more comprehensive understanding of these mechanisms, factors such as life history of the species and its dispersal capability, as well as the size, spatial layout and age of habitat patches, and intensity of environmental conversions made by humans should be taken into consideration in further genetic studies on avian populations19.There is an increasing body of research on how landscape conversions made by humans affect population genetics of different species. So far, evidence for urbanization-driven genetic divergence across metapopulations was found for various bird species from different phylogenetic lineagesParus major and blue tit Cyanistes caeruleus. Both are widespread in the Western Palearctic and, although evolved as woodland species, they nowadays abundantly inhabit various types of environments, from natural deciduous and/or mixed forests to heavily urbanized cities30. Having high dispersal potential and ability to colonize and adapt to new habitats, both the great tit and blue tit are considered as model organisms used to examine adaptation to environmental heterogeneity32. However, genetic studies on dispersion, migration and connectivity between populations of tits from various habitats and across a gradient of urbanization (urban and forest) are scarce and apparently inconsistent30. While a recent large-scale study reported that great tits form a single patchy metapopulation across Europe32, some other presented subtle genetic differentiation among examined populations at a fine-scale5. The results for the blue tit seem to be more consistent and usually provide support for a weak genetic differentiation among neighboring populations of blue tits in deciduous and evergreen habitats35. Surprisingly, overwhelming majority of population genetic studies of birds are conducted on a single species12, which does not allow for direct comparisons of genetic processes at the inter-specific level. Thus, here we applied a set of microsatellite markers to examine and compare genetic diversity and population genetic structure of great tits and blue tits occupying study sites located in habitats of varying urbanization level in central Poland. We considered isolation by distance as our primary hypothesis, where geographically closer populations of both species would be genetically more similar compared to those located farther apart. Alternatively, we hypothesized that genetic differentiation and population genetic structure may be produced by isolation due to landscape (urbanization) variation, where the strongest differentiation would be expected between urban and non-urban populations irrespectively of geographical distances between them, while suburban populations are expected to intermediately differentiate from the others.In this study we aimed to investigate population genetic patterns in two small passerine species, great tit All ten microsatellite loci analyzed showed a moderate to high level of polymorphism in both tit species, with the number of alleles ranging from 8 to 18 for great tits and from 5 to 32 for blue tits. The observed heterozygosity values were similar for great tits and blue tits and ranged from 0.60 to 0.94 and from 0.52 to 0.92, respectively  and pairwise Nei’s genetic distance  were genetically diverse and distant than those from both sub- and non-urban forest sites. At the same time, both forest populations of the great tit were not genetically different from each other. The lack of genetic divergence between two distant forest (sub-urban and non-urban) populations in great and blue tits indicates that both species maintain high dispersal potential and population connectivity within study sites representing similar types of habitat. On the other hand, the gene flow between study sites located in contrasting habitats was apparently reduced in the great tit (significant divergence between urban and forest populations), when compared with the blue tit (no divergence between urban and forest populations), suggesting that the population structure of the latter species may be less responsive to the level of landscape urbanization. At the same time, for neither of the species we found evidence for isolation by distance, which suggests that, particularly in the case of great tits, genetic differentiation recorded among the study sites could not be primarily attributed to their geographical location (and distances between them), but was likely produced by variation in the landscape characteristics, e.g. the level of urbanization.Our analysis of microsatellite data in two species of tits revealed that while there was no clear evidence for genetic differentiation between urban and non-urban blue tit populations, low but significant divergence was found in the great tit, as shown by F5, using microsatellite markers, found stronger significant genetic differentiation among great tits sampled at 12 parks in central Barcelona (Spain) and in an oak forest nearby the city. The average value of FST = 0.067 recorded in the Barcelona meta-population was much higher than values in our study . Notably, this differentiation was higher in south-western European great tits in comparison to northern parts of the continent, suggesting an effect of geographic location and important role of various environmental factors . According to Lemoine et al.32, south-western populations could be more isolated and could experience stronger genetic drift and/or selective pressure effects compared to the northern populations that considered as more homogenous. In this latter case, it was supposed that gene flow determined demographic and evolutionary aspects. Specifically, habitat selection and assortative mating system may play a crucial role in the local adaptation. Therefore, it seems that conclusions presented by Lemoine et al.32 to some extent explain the differences found between our study (more northern population) and the study by Björklund et al.5 on a southern Spanish population.Low but significant genetic differentiation between urban and forest populations of great tits recorded in this study may seem to be inconsistent when compared to some other studies analyzing the pattern of genetic differentiation of this species in urbanization gradients. For example, Björklund et al.36. Again, similarly to our findings, the authors recorded low but statistically significant genetic differentiation between populations breeding in the eastern and western part of the island (FST = 0.011), despite the relatively short distance among the sites (a few kilometers away). Surprisingly, no difference was noted between the western part of Vlieland and the mainland population, while the eastern part and mainland differed significantly (FST = 0.0084). These genetic differences among both parts of the island possibly reflected an effect of unequal proportion of gene flow from mainland population. Presumably, in that case the differences in immigration rate among sites play more important role rather than differences in adaptation mechanisms36. In another study, conducted by Perrier et al.2, it was found that the urbanization induced low but significant effects on great tit genetic structure along an urban–rural gradient . Once more, it was consistent with our findings, however in this particular case it was demonstrated by applying RAD sequencing techniques.Microsatellite differentiation was also analyzed in a small, structured population of great tits from Vlieland Island and a large mainland population located in the central Netherlands37, where genomic responses of great tits to urbanization were examined at the broad geographical scale. An analysis of genome-wide SNP data revealed relatively low genetic differentiation between paired urban–rural populations, with values of FST ranging between 0.004 and 0.050, although this differentiation was associated with repeated polygenic responses to urban habitats that mostly included polymorphisms at genes related to neural function and development37.Finally, similar conclusions were also presented in the latest study by Salmón et al.38, blue tits are a weaker competitor during the breeding season than great tits, but they are also more sensitive to biotic and abiotic factors compared to great tits. Therefore, we assume that migration could be more frequent in blue tits, which has already been recorded as a partial migrant species in both central and northern Europe40, triggering more gene flow and, consequently, less pronounced genetic differentiation between populations, as we found in our study. Perhaps, it may also be important that blue tits are thought to be more sensitive to human alterations in the structure of habitats compared to great tits, at least in central Europe42. Another thing worth considering is that great and blue tits also compete for roosting site during wintering. Dhondt and Eyckerman43 found that great tits exclude blue tits from these sites, thus probably reducing their survival rates. Therefore, we suspect that such an effect also occurs in our study system. During winter periods between 2013 and 2016, we found that recoveries of banded individuals were more frequent in great tits than in the case of blue tits, with frequencies being 20% and 8%, respectively(unpublished data). This suggests that more blue tits winter outside the breeding grounds, perhaps resulting in more opportunity to mix with other populations. We suppose that a weaker tendency of southern tit populations to migrate during the non-breeding season may support local population differentiation.The lack of clear evidence for any genetic differentiation among blue tit populations in our study system stands in some contrast to our findings on great tits. In our study system, extensive dispersal movements among both habitats were more likely in the blue tit, in particular from urban site, which could contribute to increased gene flow and observed homogenization of gene pools across all study populations. We suppose that interspecific competition between great and blue tits could contribute to variation in dispersal among our study sites. According to Dhondt33, demonstrated a significant level of genetic differentiation among populations sampled in Corsica and in southern continental France. Pairwise estimates of FST ranged from 0.003 to 0.049 for all pairwise comparisons between these populations. According to Porlier et al.33, neither geographic distance nor physical barriers were the reason, but habitat type (deciduous or evergreen) and, presumably, habitat quality were identified as crucial factors. Porlier et al.33 concluded that their results suggest an importance of local adaptation in shaping the genetic structure of blue tits from Corsica. Low but significant genetic differentiation among blue tit populations from fragmented habitats (ca. 20 km distant) was also found in Spain, with values of FST ranging from 0.005 to 0.00843. According to Ortego et al.44, there was some evidence that habitat fragmentation may be responsible for weak dispersal movements between habitat patches, which reduced gene flow between populations.Other microsatellite-based studies of blue tit populations from various habitats found more genetic differentiation. Porlier et al.12, showed that progressing urbanization in southern California significantly reduced gene flow in the wrentit Chanaea fasciata, leading to a decrease in genetic diversity and significant genetic divergence among isolated groups . Similar patterns were found in song sparrows Melospiza melodia inhabiting metropolitan Seattle, where urban development limited connectivity between sub-populations13. This was manifested in overall low but significant genetic divergence among study sites, with pairwise FST values ranging from 0.001 to 0.028.Evidence for various effects of urbanization on population genetic structure is rapidly accumulating for an increasing number of bird taxa. Deleney et al.Passer domesticus22 and blackbirds Turdus merula4. The first study showed genetic differences among urban and rural populations of house sparrow around Ghent (Belgium) and demonstrated that average relatedness was higher among urban birds compared to those from rural habitats22. In contrast, urban populations of blackbirds were characterized by the lower genetic diversity compared to paired rural populations. At the same time, differentiation among urban blackbird populations proved to be greater than that between urban and rural populations4. In turn, analyzes of microsatellite data conducted by Brewer et al.19 revealed that the level of urbanization did not affect genetic diversity and genetic structure of song sparrows inhabiting patches in a gradient of urbanization around Blacksburg (USA), where pairwise FST values ranged from 0.011 to 0.023. Similar conclusion was provided by studies on black headed gulls Chroicocephalus ridibundus in northern Poland15 and on common kestrels Falco tinnuculus in Czech Republic24, where urban and rural populations did not differ genetically.Similar conclusions can be drawn from studies conducted on house sparrows 5, and small panels of microsatellite markers have been reported to produce highly consistent results with genomic approaches based on thousands of SNP loci47. Nonetheless, we acknowledge that further research should incorporate more comprehensive sampling  and more robust genotyping approaches (possibly combining genetic and genomic methodology) to overcome the limitations of the current study and provide more general insights into urbanization processes of the two most common European parid species.In summary, to our best knowledge this study is the first attempt to examine the genetic diversity and population genetic structure of both great tits and blue tits co-occupying contrastingly different yet spatially close habitats. Our data indicate that there was a contrasting pattern of the genetic structure among the two parid species. This can suggest, that both great and blue tits respond differently to urbanization factors, presumably due to a different level of migration and/or dispersal capability of urban populations. We suppose that in our study system these discrepancies in movements may be in some part related to interspecific competition between great and blue tits, which could already start during winter time preceding the breeding season. It is necessary to emphasize that our conclusions were based on data from three particular study sites located in a single geographical region . Although we think that our results can possibly reflect more general patterns of great tit and blue tit responses to urbanization, it cannot be directly inferred from our data. We are also aware that our study could have suffered from relatively low sample sizes and from relatively few genetic markers used in our analyses. Despite these methodological limitations, we consider our analyses and conclusions reliable, as our sample sizes were actually comparable (or even more extensive) to other genetic studies on titsThis study was conducted as part of a long term project (initiated in 1999) on the breeding biology of hole-nesting passerines in central Poland. The study was carried out in compliance with the ARRIVE guidelines. All procedures were performed in accordance with Polish legislation and approved by the Local Bioethical Commission for Experiments on Animals, Medical University in Łódź (No. 70/ŁB07/2015) and the Regional Directorate for Environmental Protection (WPN-II.6401.13.2016.MS).48. This area has highly fragmented arrangement of tree cover, formed artificially. The forest site encompasses ca. 140 ha, situated in the interior of the Łagiewniki Forest , bordering to the northeast part of the suburbia of the city of Łódź. This study site consists of tree stands mainly based on mature deciduous trees, with oaks Quercus robur and Quercus petraea being dominant species49. The third study site was established in the Spała Forest District located within the Pilica valley, which is situated ca. 50 km apart from Łódź  with marginal participation of old oaks (2.3%) which can be mainly found in one of nature reserves (Spała), within the Spała Landscape Park50. Referring to the data collected and presented in some of the our previous studies52, we emphasize that both the study sites located in Łódź (urban parkland and suburban forest) differed distinctly not only in habitat structure but also in the level of anthropogenic pressure. This was mainly manifested by apparent differences in a variety of measures of human presence and activity in these areas, with much higher human attendance being recorded in the urban parkland site . Additionally, the urban parkland site was situated relatively close to the city center (ca. 3 km) and surrounded by roads with intense traffic as well as city buildings, whereas the study site located in the Łagiewniki Forest was characterized by a lower number of roads with many traffic restrictions52. At the same time, the study site in the Spała Forest District is remote from dense human settlements and is surrounded by a landscape protection area. As a consequence, human presence at the site is highly limited, both in terms of their abundance and disturbance to breeding birds50 own.obs.During the 2018 breeding season, a total of 85 and 48 individuals of great and blue tit, respectively, were sampled at three study sites  and great tits . DNA extraction was performed using GeneMATRIX Bio-Trance DNA Purification Kit. A part of every dried blood sample (approx. 2 mm2) was cut away from each FTA MiniCard, with the use of sterile cutter. Subsequently, DNA isolation was performed in accordance with the manufacturer’s protocol guidelines. In the next step, polymerase chain reaction was conducted using the final volume of 20 µl containing 10 µl of DreamTaq PCR MasterMix (Thermo Fisher Scientific) and 0.5 µl of primer and 1 µl of extracted DNA. The amplification steps and conditions followed the protocols developed by Dawson et al.55 and Saladin et al.54. One exception was applied to the annealing temperature for PmaTAGAn86 primers, which finally was set to 61 °C. Forward primers were labeled with 6-FAM fluorescent dye and PCR amplifications were performed separately for each locus. Microsatellite genotyping was carried out in a commercial laboratory . Allele sizes were determined against an internal lane size standard (Henescan TM 600 LIZ) using Geneious software.From each sampled bird, a sample of ca. 10 µl of blood was collected from the ulnar vein on FTA MiniCards and, after drying, stored at room temperature for the purpose of genetic analyses. Population genetic structure of great and blue tits was examined using microsatellite markers, which are recognized as a relevant tool, traditionally used in population genetic and evolutionary studies56 was used to check for any mistyped allele sizes and scoring errors due to large allele dropout or stuttering. Deviation from Hardy–Weinberg equilibrium (HWE) was tested for each locus in each population with the Markov-chain algorithm  implemented in the exact tests57 available in Arlequin 3.5.1.258. Linkage disequilibrium between all pairs of loci was tested in FSTAT 2.9.3.259. The results of these analyses were adjusted for multiple testing with Bonferroni correction60. The expected and observed heterozygosity , allelic richness (Na) and the frequency of null alleles were computed for each locus using Cervus 3.0.3 software60, while inbreeding coefficients (FIS) were estimated using GeneAlEx 6.5 software62. To examine differences in genetic diversity measures  between species, permutation procedure  was applied by using FSTAT software.The Micro-Checker 2.2.3 softwareST. This is a classic measure of population divergence, although it is known to diminish the role of mutations in inducing genetic variation within populations63. Therefore, an alternative statistic RST63 was introduced based on the stepwise mutation model, which can more accurately reflect changes in microsatellite allele sizes21. However, under certain scenarios, RST can be less accurate in reflecting population divergence than FST due to high sampling variance21. Taking all this into consideration, to check whether microsatellite allele sizes provide information on population differentiation within our dataset, we applied the allele size permutation tests64, using SPAGeDi 1.5 software65. The tests were run under the null hypothesis (Ho) that variation in allele sizes does not affect population differentiation 64. The results did not allow to reject the null hypothesis both for the great tit (P = 0.41) and blue tit (P = 0.82). Hence, we used FST statistic as a measure of genetic differentiation for both species and pairwise FST’s were computed with 100,000 permutations in Arlequin 3.5.1.2 software. Additionally, standardized FST values (F′ST) were calculated as the original FST divided by the maximum possible FST value in respect to the intra-population genetic variation. These computations followed recommendations by Hedrick66 and were performed using RecodeData 0.1 software67. To measure the genetic distance between the populations we also calculated pairwise Nei’s unbiased genetic distances68, using GeneAlEx 6.5 software. We also checked whether any differences in the genetic structure between great and blue tits were related to inequality in sample sizes. For this purpose, we re-computed FST statistics and pairwise Nei’s unbiased genetic distances for great tits, randomly limiting their sample sizes for each population to match them with those available for blue tits. To examine the effects of geographical distance on genetic structure we conducted Mantel test between all pairwise FST and the corresponding pairwise geographical distances, with 10,000 permutations using the package ade469 developed for R statistical environment. Finally, we conducted the Discriminant Analysis of Principal Components (DAPC) to infer the number of genetic clusters within our data and to assign individuals to these clusters. The analysis was run in the adegenet70 R package. The number of genetic clusters (1 ≤ k ≤ 3) were identified based on the minimum Bayesian Information Criterion (BIC) using the same number of principal components (PCs) for each species (n = 40). In the case of k > 1 we performed the discriminant analysis an posterior assignment of individuals to cluster using dapc function.Evaluation of genetic divergence between populations of each species was conducted by calculation of Wright’s fixation index FSupplementary Information.


The highest NO2 emission reduction (~ 50%) was recorded in Wuhan city during the lockdown of 2020. AOD was highest in Beijing and lowest in Colombo (< 10%). Overall, 90% movement was reduced till mid-April, 2020. A 98% reduction in mobility was recorded in Delhi, Seoul, and Wuhan. This analysis suggests that smart mobility and partial shutdown policies could be developed to reduce environmental pollutions in the region. Wuhan city is one of the benchmarks and can be replicated for the rest of the Asian cities wherever applicable.This study investigated the environmental spatial heterogeneity of novel coronavirus (COVID-19) and spatial and temporal changes among the top-20 metropolitan cities of the Asia-Pacific. Remote sensing-based assessment is performed to analyze before and during the lockdown amid COVID-19 lockdown in the cities. Air pollution and mobility data of each city  have been collected and analyzed for 2019 and 2020. Results indicated that almost every city was impacted positively regarding environmental emissions and visible reduction were found in Aerosol Optical Depth (AOD), sulfur dioxide (SO According to the latest statistics by the World Health Organization4, over 200 million people have been affected and the death toll rises to almost 4.6 million by September 20214. And this trend of the outbreak from epidemic to pandemic is continued and all efforts have been mobilized to flatten the curve. This led to various lockdown implementations in different countries and cities , starting from Wuhan, China on January 21, 20205. Since then, lockdown is being implemented in most of the Asia-Pacific countries such as partial lockdown in Bangladesh, China, India, Japan, Pakistan, South Korea, and Thailand. Asia-Pacific region includes most of the countries in East, West, South Asia, and Oceania with proximity to Western Pacific Ocean6. Besides its negative impacts on daily life in terms of social, economic, health, environmental, and development forms, few co-benefits on our natural environment may also be observed. It is hard to grasp the notion of co-benefits of COVID-19; however, changes are actual and evident.Novel coronavirus 2019 commonly known as COVID-19 has become the additive factor of everyday life across the globe. A lot of reporting, analysis, and suggestions are being available and published recently10, some investigated its correlation with weather12; likewise, an interesting study compiled the information released by National Aeronautics and Space Administration (NASA) on pollution across the globe13 based on the maps released by the NASA and European Space Agency (ESA). Another study analyzed the situation in Wuhan and other 122 cities of China5, and global bird eye-view14. Nonetheless, some original analysis of temporal change in the natural environment with a comparative breakdown of the pollutants is still missing, especially, in many highly polluted metropolitan cities of the Asia-Pacific. As we know that, 99 out of the 100 world’s most polluted cities are present in the Asian region15, therefore, it is necessary to understand the environmental dynamics of such metropolitan cities relating to COVID-19. Moreover, this wave of lockdown following pandemic is interlinked with the mobility feature. Restriction on mobility resulted in unprecedented reductions in deadly air pollution around the world16. Quantifying the changes in air pollution during the lockdown period may provide a unique opportunity to understand the types, patterns, and origins of air pollution by comparing pre-lockdown with lockdown and/or post-lockdown conditions17. Keeping in view all these facts and research gap, this study investigated the environmental spatial heterogeneity of COVID-19 and spatial and/or temporal changes among the top-20 (now onwards T20) metropolitan cities of the Asia-Pacific.Having said that, some studies have reported the air quality correlated with COVID-19To the best of our knowledge, no such study has been conducted thus far that analyses the environmental changes and spatial heterogeneity of COVID-19 in the T20metropolitan cities of the Asia-Pacific. Moreover, this study explains the comparative assessment of important yet selected greenhouse gases (GHGs) emissions before and during lockdown amidst COVID-19. The novelty of the research lies in analyzing the big data, linking environmental changes with COVID-19, and connecting mobility data before and during the lockdown. Therefore, the results reported here are novel, timely, and may help policymakers to understand the lockdown policies accordingly to understand co-benefits and heterogeneity of COVID-19.18. The first COVID-19 lockdown in the world was imposed in Wuhan city on 21st January 2020 and the latest was in Singapore, on 7th April 202019. Keeping that in view and spatial heterogeneity, we have selected the metropolitan cities of the Asia-Pacific especially from middle- and low-income countries. These cities are listed as top metropolitan cities16 and most of them are among top in the list of most polluted cities. “Spatial heterogeneity is defined either as the variation in space in distribution of a point pattern, or variation of a qualitative or quantitative value of a surface pattern”20. Table Metropolitan status is achieved by any city if its agglomeration index and core population exceed 50,000 or aboveThe lowest levels were observed in Ho Chi Minh, Delhi, Taipei, and Wuhan cities in 2019. On the contrary, Ho Chi Minh, Tehran, Bangkok, and Shanghai were the top among lowest level cities respectively, from January to May 2020. Busan, Calcutta, and Tokyo cities were positively impacted during the lockdown and reaped more environmental benefits than other metropolitan cities , on 17th March 2019 whereas the minimum level of NO2 was recorded in Calcutta (5.06 µmol/m2), on 2nd May 2019. Moreover, the maximum level of NO2 was observed in Beijing city (20%), on 17th January 2020, as compared to 2019, which then decreased to almost 95% during the lockdown period. The minimum level in Kathmandu, Nepal showed a change of almost 85%, on 9th May 2020 as compared to the 2019. The topmost NO2 emitting cities in 2019 were Beijing, Wuhan, Shanghai, and Delhi; whereas during the lockdown of 2020 top cities were Beijing, Shanghai, Tokyo, and Seoul  made to the list of lowest levels. Almost 50% NO2 emission reduction was observed in Wuhan city  recorded on 2nd January 2019. Given the results of this analysis, CO emissions were rather increased in Beijing (10%) as per observations made on 28th January 2020 which decreased to almost 65% during March, 2020 (lockdown period). Furthermore, the lowest CO emissions remained in Tehran with (21% change) on 22nd March 2020 as compared to the previous year. The top most CO emitting city in 2019 was Beijing followed by Wuhan, Shanghai, and Delhi, and during the lockdown of 2020 Beijing was followed by Wuhan, Shanghai, and Calcutta  on 12th April 2019, and the minimum level was observed in Beijing (124.12 × 103 µmol/m2) on 23rd January 2019. Similarly, the maximum level of SO2 was recorded in Dhaka and Bangladesh (with a 42% increase) on 22nd April 2020, and the minimum level of SO2 in Seoul which was (87% decrease), on 17th January 2020. During 2019, the highest levels of SO2 were in Kathmandu, followed by Calcutta, Dhaka, and Singapore, and during the lockdown of 2020 was Dhaka (42%), followed by Calcutta (23%), Hong Kong (21%), and Beijing(19%) cities  in Seoul was observed on 25th February 2020, however, mobility in the parks reached its maximum (158%) on 30th April 2020. While minimum mobility in parks was noted in Delhi on 16th April 2020 (-98%). In the residential sector, maximum mobility was recorded in Singapore on 1st May 2020 (55%) and minimum mobility in the residential sector was documented in Calcutta on 11th March 2020 (-3%). In the transit sector, maximum mobility was observed in Colombo on 10th March 2020 (12%). And minimum mobility was recorded in Manila on 10th April, 2020 (-90%). According to Google mobility data, 90% movement was reduced till mid-April, 2020 in the Asia-Pacific region and it is worth to note that most of the populated cities of the world are in Asia-Pacific.Air pollution is robustly interconnected with the mobility of people and other modes of transportationace Fig. . Accordi24, we, however, used a time bracket and studied that time frame to observe and analyze the changes compared to the reference year (2019). Specifically, the changes in the air quality during the lockdown period can be classified into three types of changes . Firstly, cities such as Colombo, Dhaka, Singapore, Taipei, and Tehran showed less than 10% change in NO2 emissions  during the lockdown compared to the reference year, 2019. Secondly, Bangkok, Busan, Delhi, Kathmandu, Karachi, Mumbai, PRD Hong Kong, Seoul, Shanghai, and Tokyo showed changes between 10 and 25% during the studied period. Only Beijing, Manila, and Wuhan were the cities that portrayed significant changes in the air quality as compared to the reference year. Wuhan remained at the top among all the metropolitan cities studied. Wuhan was under complete lockdown unlike Seoul and Shanghai, which is the reason why it reaped plenty of environmental benefits in the form of air pollution reduction. Our results are also similar to those studied by25 in different cities of China. Another study was conducted at the global level and found the same results of CO reduction27.Main purpose of this study was to investigate the spatio-temporal heterogeneity of environmental changes due to COVID-19 lockdowns among the top-20 selected metropolitan cities of the Asia-Pacific. Different cities experienced lockdown phases from time to time28 carried out to investigate air quality impacts during the lockdown in the Middle East metropolitan cities. Dhaka is one of the most densely populated and economically vibrant metropolitan cities; however, it did not show significant changes as per our analysis, and the results are in line with this study conducted in Bangladesh29. This study also found that in Bangladesh, lockdown is linked to the reduction in air pollution specifically, in Dhaka city of Bangladesh, but insignificantly30. Comparative analytical results showed that Wuhan and Shanghai cities especially made significant improvements in terms of AOD, NO2, and CO emission reductions during the lockdown31. Wuhan made it to the lowest emissions list of 2020 from the top as in 2019. Beijing and Wuhan again showed a variant environmental spatial heterogeneity during the lockdown period which indicate the positive impacts of COVID-19 lockdown. Moreover, it helps to understand the environmental conglomeration in different cities of Asia. It is important to note that the changes in concentrations of the pollutants and their response to lockdown implementation may vary as a function of characteristics of the city including population, urbanization or industrialization, growth rate as well as local meteorological conditions.Our study highlighted an interesting finding that small metropolitan cities such as Colombo and Taipei were not significantly influenced by the lockdown considering air quality changes as compared to the large metropolitan cities , and this result is contradictory to a study2 emission reduction is observed in Wuhan in 2020 compared to 2019. Moreover, Beijing, Wuhan, Calcutta, and Seoul showed a significant reduction in emissions levels during the lockdown period. Dhaka, Tehran, and Colombo remained in the lowest levels of change regarding overall air pollution before and during the lockdown. The rest of the metropolitan cities remained mid-level emission emitters. Therefore, a visible pattern of environmental spatial heterogeneity was found in the Asian metropolitan cities before and during the lockdown. However, the COVID-19 lockdown made it further visible than before. This portrays that reducing few activities in the largest metropolitan cities of Asia may help to gain sufficient environmental benefits, and then some action plans should be crafted. COVID-19 lockdown economically proved to be negative but environmentally positive for almost all of the studied cities. This co-benefit analysis suggests that smart mobility and temporal shutdown policies could be developed to reduce environmental pollutions. Wuhan city is one of the benchmarks and can be replicated for the other Asian cities wherever applicable. Further studies may include/exclude other cities of Asia-Pacific to study the changes. Such impacts using new methods can also be tested to observe the changes.The purpose of this study was to highlight that COVID-19 had many adverse impacts on different sectors of the economies, but environmental benefits were also reaped in the form of air pollution reduction knowingly or unknowingly. Reduction in the pollutant from east to west with time since the outbreak indicates a clear pattern and lack of timely actions. Moreover, response actions of different governments and response of residents portray sequential patterns of priorities. It is interesting to conclude that almost 50% NO34. The study area map indicating locations and geographic coverage of the study sites can be consulted in Fig. The impact of lockdown varied from east to west with different lockdown periods and relevant policies in the Asia-Pacific region. Apart from a wall-to-wall assessment of air quality of the whole region, we also analyzed the patterns of changes in 20 metropolitan cities of the region including Bangkok, Beijing, Busan, Calcutta, Columbo, Delhi, Dhaka, Ho Chi Minh, Karachi, Kathmandu, Manila, Mumbai, Pearl River Delta, Seoul, Shanghai, Singapore, Taipei, Tehran, Tokyo, and Wuhan. The city-specific assessment aimed to reveal the geographic spread of the pandemic and response of governments regarding lockdown initiatives. Earth Observation-based monitoring systems are being very efficiently used to understand the impact of the COVID-19 spread on the environment in the short- and long-runs2), sulphur dioxide (SO2), and Aerosol Optical Depth at 550 nm (AOD), and mobility before and during COVID-19 lockdown. The environmental datasets were processed and obtained using the cloud computing platform, Google Earth Engine, mobility data was acquired from Google, and the analysis was performed in R.We analyzed carbon monoxide (CO), nitrogen dioxide  onboard Sentinel 5P. Sentinel 5P enables a new era of satellite-based mapping and monitoring of atmospheric pollutants and gasses at global and regional scale. We used the level 3 products, available in the Google Earth Engine, which were subsequently masked for good quality pixel by using the relevant quality control tags of the data . These datasets were converted into measurement units of µmol/m2 before exporting the results at ~ 1 km spatial resolution. The AOD measurements used in this study were derived from the MODIS product (MCD19A2-V6)35 which is a combined product of MODIS sensors onboard Terra and Aqua satellite. It is based on the MAIAC (Multi-angle Implementation of Atmospheric Correction) algorithm and provide daily global coverage of AOD at 1 km spatial resolution. The data was screened for good quality pixels and the pixel tagged with poor quality indicators were masked out. It is important to note that the products have been spatially averaged over the hot spot region of the corresponding cities for time series assessment. Therefore, an underlying limitation of the datasets and the analysis could be the coarse spatial resolution of the imagery and spatial averaging which must be considered while assessing the pollutant concentration at local scale.The NO2 in 2019 to demarcate the hotspot areas by drawing a confounding rectangle around the high concertation pixels  in the environmental pollutants were calculated by normalizing the difference between the control period (P1) and the other post-pandemic or periods associated with lockdown implementation or relaxations . Positive values show normal or high concentration conditions while negative values indicate a decline in the pollutants.The google community mobility data calculated the changes in mobility patterns with reference to the baseline median value for each weekday obtained during the five weeks period . All the processed and raw datasets can be obtained from the supplementary materials.Supplementary Information 1.Supplementary Information 2.


Finally, we provided prospects concerning how our introduced approaches of landscape genomics can assist policymaking and improve the existing conservation strategies for tree species under the ongoing global changes.Understanding the genetic basis of how species respond to changing environments is essential to the conservation of species. However, the molecular mechanisms of adaptation remain largely unknown for long-lived tree species which always have large population sizes, long generation time, and extensive gene flow. Recent advances in landscape genomics can reveal the signals of adaptive selection linking genetic variations and landscape characteristics and therefore have created novel insights into tree conservation strategies. In this review article, we first summarized the methods of landscape genomics used in tree conservation and elucidated the advantages and disadvantages of these methods. We then highlighted the newly developed method “Risk of Non-adaptedness,” which can predict the genetic offset or genomic vulnerability of species  However, pre- and post-processing of data will be labor-intensive when using the SAMβADA. In view of these facts, The SAM is developed to assess putative associations between molecular markers and environmental variables using multiple univariate logistic regressions . It deteThe multivariate statistical analysis usually integrates environmental variables and spatial genetic structure into the analytical framework to detect the adaptive variation. Traditionally, isolation by environment (IBE) is commonly used to detect selection signatures . HoweverThe CCA aimed to find a linear relationship between multiple loci and environmental factors. The loadings consist of loci and environmental variables indicate which loci respond to which environmental factors. However, we need caution to infer the outcomes if strong patterns of multicollinearity exist within datasets . RDA is via RDA and LFMM, the former has the advantage to identify the main selective gradients as a combination of environmental variables  or LFMM . Even thariables . Additioariables .Traditionally, the vulnerability of species mainly relied on the prediction of species distribution models (SDMs)  or its ePopulus balsamifera, and they concluded that the changes of genetic composition are required if it tries to mitigate maladaptation and maintain genetic diversity in the future. GDM accounts for spatial patterns in genetic data caused by demographic processes, accommodates varied factors  as predictors, and also enables to deal with numerous SNP loci  means managed translocation of individuals within the current species range to mitigate local maladaptation . AGF is ong time . Additioong time .Eucalyptus microcarpa, and 62 of which are associated with mean annual temperature by a combination of four FST outlier tests and one EAA  as the general framework of landscape genomics  associated with plant circadian clock and light perception pathways in balsam poplar is similar, although slight differences existed in its marginal area, both methods predict the range core of balsam poplar likely suffered minimal disruption of the existing GEAs. In the future, efforts by a combination of simulations, genomic data, and common garden experiments might be applied to demonstrate the high effectivity and accuracy of genomic offset under alternative climates  and restriction-site associated DNA sequencing (RADseq)] and RNA sequencing. However, the number of SNPs obtained and the ability to detect genes underlying local adaptation from the abovementioned methods may be influenced due to the differences in library preparation, SNP densities, and the bioinformatics parameters applied to SNP filtering . As moreUnderstanding the genetic mechanism of adaptation is the key issue for molecular ecology and evolutionary biology. We reviewed the existing theories and methods that belong to landscape genomics for detecting adaptive evolution in species and advocated utilizing an integrated analytical framework to illuminate the GEAs between genetic and environmental data. We particularly emphasized the effectivity and necessity of multiple methods for detecting signatures of local adaptation combined with models for predicting adaptation potential in tree conservation. With the low sequencing cost, ease availability of high-solution environmental data, and newly developed genomic tools in the near future, we believe that the conservation efforts and management interventions for forest trees will benefit from advancing studies of landscape genomics.LF and FD conceived the study and wrote the manuscript. Both authors designed the focus, structure and content of the review.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.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.


Fermented feed has been of wide concern in livestock and poultry production because of its many advantages. In this study, the nutritional quality of the feed before and after fermentation was assessed, and four supplemental levels of fermented feed were used to replace unfermented feed to study the influence of fermented feed on the gut health of the laying hens during the laying peak period. The results suggest that fermented feed can improve the intestinal morphology and barrier functions of laying hens, possibly by altering the cecal microbiome.p < 0.05). Moreover, fermentation in the feed significantly increased the crude protein content (p < 0.05). Supplementation with fermented feed significantly reduced the crypt depth and increased the villi height:crypt depth ratio of duodenum and jejunum (p < 0.05). Meanwhile, fermented feed increased the secretory immunoglobulin A content and MUC2 mRNA expression of jejunum (p < 0.05). These beneficial effects were exhibited at the addition level ≥6% and microbial composition of caeca in the control, and so 6% fermented feed groups were analyzed. The structure of the gut microbiota was remarkably altered by additions, characterized by increased abundances of some health-promoting bacteria, such as Parasutterella, Butyricicoccus and Erysipelotrichaceae (p < 0.05). In summary, fermented mixed feed modulated cecal flora, subsequently contributing to improvements in intestinal morphology and barrier functions in laying hens.This study aimed to evaluate the effects of fermented corn–soybean meal mixed feed on intestinal barrier function and cecal microbiota in laying hens. A total of 360 Jingfen No.6 laying hens (22 wk-old) were assigned to 4 dietary treatments, which were offered basal diets (without antibiotics) containing 0, 4, 6 and 8% of fermented mixed feed respectively. The results showed that the pH value and anti-nutritional factor concentrations in fermented mixed feed were lower than those in unfermented feed ( To achieve resistance-free breeding, a growing number of studies has been conducted to evaluate non-antibiotic alternatives and their effects on the health and production performance of animals . FermentGut integrity and function are essential factors in maintaining animal health and production performance. Intestinal morphology is an important criterion for evaluating intestinal health of animals. Villus height and crypt depth were related to nutrient digestion and poultry performance . The comIn China, fermented feed mainly refers to the fermented single feed material, such as soybean meal , rapeseeBacillus 2 × 109 CFU/g, Lactobacillus 3 × 109 CFU/g, Saccharomyces cerevisiae 5 × 108 CFU/g. The probiotic powder was dissolved in 1 L sterile water at 37 °C, and stirred evenly to make a probiotic solution. The basal substrate (12 kg) included 60% corn, 20% soybean meal and 20% wheat bran, which was mixed and inoculated in probiotics with probiotic solution. The fermentation process according to the method of Shi et al. [The probiotic purchased from Baide Biotechnology Co., Ltd. , was a lyophilized powder containing i et al. , with apn = 3) were tested to determine their crude fiber , crude protein  and ether extract  contents according to AOAC International guidelines [g for 5 min, the supernatant pH was tested using a probe style-pH meter . Protein extraction and SDS-polyacrylamide gel electrophoresis (PAGE) of the feed samples were performed according to the method described in reference [Fermented and unfermented feed were collected and dried at 65 °C for 48 h. Feed samples . A total of 360 Jingfen No.6 layers aged 22 weeks were randomly assigned to four numerically equal groups, with 6 replicates per treatment and 15 birds per replicate. The layers had a similar body weight and good health. The feeding period lasted 10 weeks, commencing when the layers were 25 weeks of age and ending when they were 35 weeks of age, with an addition of 3 weeks for feed adaptation. During the experiment, three laying hens were kept in each cage and had ad libitum access to feed and water. Proper indoor temperature (15~22 °C) and humidity (30%~50%) were maintained.According to the NRC (1994) layer feeding standard, the corn–soybean meal basal diet (antibiotic-free) was designed based on the actual situation of layer feeding in the experimental chicken farm. Unfermented corn, soybean meal, and wheat bran were replaced in the basic diet with increasing levels of fermented mixed feed . The ingredients were mixed in a mixer for 15 min. Feed composition and nutrient content of the experimental diets are shown in At 35 wk, 24 chickens (one with an average body weight from each replicate pen) were selected to collect samples. All birds were killed by cervical dislocation and small intestinal  mucosa was scraped off at the forepart of individual small intestinal segments with a glass microscope slide on ice and frozen and stored immediately at −80 °C liquid nitrogen tanks for further analysis. About 3 cm of the mid-portion of the small intestines were excised carefully and washed in saline solution before storing in formalin (10%). The cecal contents were gathered using sterile spatulas into sterile plastic tubes, immediately refrigerated (maximum 2 h) and stored at −80 °C refrigeration until the DNA extraction. Three-centimeter lengths from the medial portions of duodenum, jejunum and ileum from chickens were fixed with 10% formalin for 24 h. Tissues were later embedded in paraffin wax blocks, mounted onto glass slides, and then stained with Haematoxylin & Eosin (H&E). The fixed segments were sectioned and observed under the light microscope, and the villus height VD, crypt depth CD and the ratio of VD and CD evaluated.Secretory immunoglobulin A (sIgA) content of mucous membrane samples of the duodenum, jejunum, and ileum were measured by ELISA kits  according to the kit instructions. Total RNA was extracted from the snap-frozen jejunal tissue samples with a RNeasy mini kit , following the instructions. Complementary DNA (cDNA) was synthesized from 1 μg of total RNA using MMLV reverse transcriptase . Then, the transcriptional changes were identified by quantitative PCR using Premix Ex TaqTM with SYBR Green  and the Bio-Rad CFX 96™ Real-Time Detection System . The thermocycle protocol lasted for 30 s at 94 °C, followed by 40 cycles of 5 s denaturation at 94 °C, 34 s annealing/extension at 60 °C, and then a final melting curve analysis to monitor the purity of the PCR product. The 2−ΔΔCt method was used to estimate mRNA abundance . Relative gene expression levels were normalized using β-actin as an internal control. The primers were synthesized by the Xi’an Qingke Biological Company, and the sequences are shown in ® High-Fidelity PCR Master Mix  and primers F341 and R806. The 30 μL reaction system was used in PCR reactions with 15 μL Mix, 0.2 M of forward and reverse primers, and about 10 ng template DNA. Thermal cycling consisted of initial denaturation at 98 °C for 1 min, followed by 30 cycles of denaturation at 98 °C for 10 s, annealing at 50 °C for 30 s, elongation at 72 °C for 30 s and a final elongation at 72 °C for 5 min. The amplicons were examined using 2% agarose gel electrophoresis, and then the GeneJET Gel Extraction Kit was used  to purify the excised target fragments. Finally, 16S rRNA gene sequencing was performed using the Illumina NovaSeq 6000 PE250  with the MiSeq Reagent Kit from Novogene Bioinformatics Technology Co., Ltd., Beijing, China.Total genomic DNA was extracted from samples using the CTAB/SDS method and then stored at −80 °C until sequencing analysis. The V3 + V4 fragments of the 16S rRNA gene were amplified using the Phusionhttp://qiime.org/index.html). Data regarding alpha diversity indices, intestinal morphology, total sIgA concentration and relative mRNA expression levels among all treatments in this study were analyzed by one-way ANOVA with SPSS 22.0. Differences among groups means were determined by Duncan’s multiple comparison test. The significance of differentiations in microbial structure among groups was assessed by ANOSIM using R package “vegan”. t-test was used to compare the chemical composition of feed and cecal microflora at the phylum and genus level. The correlations between the cecal microbial composition and gut health were assessed by Spearman’s correlation analysis using GraphPad Prism version 8.00. p < 0.05 was considered statistically significant and 0.05 < p ≤ 0.10 a trend.Alpha diversity (Shannon and Simpson indices) and abundance (Chao1 and ACE indices) were analyzed withQiime v.1.7.1. , crypt depth (CD) and the villi height:crypt depth ratio (VH/CD) are displayed in Secretory IgA (sIgA) acts as the first immune defense for intestinal epithelium and maintains the homeostasis of the gut. Therefore, we assessed the intestinal immune function by measuring the intestinal sIgA contents. As shown in p > 0.05; p < 0.05) to the control group and were larger than those of the inner-group (R > 0.05). Hence, to illuminate how fermented mixed feed served to improve the gut health of laying hens, the 6% group was selected as the representative group among the 3 treated groups to identify the roles of fermented mixed feed in regulating the cecal microbiota.As the microbial community plays an important role in the intestinal health and barrier function of laying hens, the composition of the cecal microbial community was analyzed using the 16S rRNA gene amplicon sequence. After filtering, an average of 60,788 ± 6481 reads were obtained for each sample. In the 16S amplicon data analysis, the Shannon and Simpson indices were used to assess the community diversity, and the ACE and Chao1 indices reflected the community richness. Therefore, alpha diversity was measured using these four indices, and there were no significant differences in cecal feces microbiome taxon abundance and diversity  on the phylum and genus  and Enterococcus were significantly decreased in the 6% fermentation group when compared with the 0% control group (p < 0.05).Since pairwise comparisons (0 and 6%) and the data were in accordance with normal distribution, nd genus . Compareunidentified_Lachnospiraceae, unidentified_Spirochaetaceae, Barnesiella Helicobacter, Parasutterella and Synergistes. In contrast, the intestinal morphology was negatively correlated with Bacteroides, Megamonas, Desulfovibrio, Alistipes, Tyzzerella, Fournierella Succinatimonas, Gallibacterium and Elusimicrobium significantly. In addition, the abundance of genus Faecalibacterium and Desulfovibrio were negatively correlated with the jejunal sIgA contents, and the abundance of genus Sutterella and Lachnoclostridium were negatively correlated with the duodenal sIgA content. Moreover, Fournierella was positively correlated with ileal sIgA contents. In order to explore the specific bacteria related to gut health, the Spearman correlation coefficient  was usedThe corn–soybean meal diet is the most widely applied in poultry production in China. However, ordinary corn–soybean meal diets contain some anti-nutritional factors, for instance, phytic acid, soybean antigenic protein and soy oligosaccharides, which may compromise the nutrient bioavailability and exhibit negative effects on animal health . Solid-sAmong a variety of parameters, pH is an important reference to estimate the quality of fermented feed, because lower pH may favor the digestion of intestinal nutrients and inhibit the growth of pathogenic microorganisms in feed . Our resThis study found that fermented mixed feed could partially improve the intestinal morphology of laying hens. This was consistent with the past study of Missotten et al. , who notThe gut barrier can prevent the intestinal tract from the colonization of pathogens, and sIgA is the critical component of the immune barrier, limiting epithelial contact with pathogens and other antigens . In thisParasutterella, Butyricicoccus, unidentified_Erysipelotrichaceae and Mailhella were identified as the main microbes with increased abundances in response to the addition of fermented feed. The increased proportion of Parasutterella has been reported to be beneficial to intestinal mucosal homeostasis [Parasutterella abundance and villus height VH and VH/CD ratio. Butyricicoccus, as butyrate producers, are assumed to improve growth performance, inhibit the proliferation of pathogens and relieve intestinal inflammation in broilers [Erysipelotrichaceae may be associated with the degradation of feed ingredients and the production of short-chain fatty acids [Alloprevotella, Gallibacterium, Romboutsia and Enterococcus were observed in 6% fermented feed group compared to the control. Gallibacterium has been recognized as a main cause of peritonitis and salpingitis in laying hens [Alloprevotella is known as an opportunistic pathogen; however, previous studies have noted that the increased abundance of Alloprevotella genera was linked to better intestinal health [Romboutsia is a valuable intestinal biomarker maintaining host health, and Enterococcus with natural antimicrobial probiotic properties could prevent diarrhea in animal production [Gallibacterium is directly associated with poultry intestinal disease, which was also confirmed in this study by a negative relationship between abundance and villus height [To further explore the underlying mechanism of its modulation on gut health, we have used Illumina MiSeq sequencing to analyze the cecal microbiota. The present study revealed no significant effect on the α-diversity of the cecal microbiota, whereas the β-diversity analysis showed significant clustering between the 6% and 8% groups and controls, indicating that the cecal microorganism community profiles in the 6% and 8% fermented groups could be altered following fermented feed addition. This was in line with the results on the intestinal morphology and the barrier-related gene expression, indicating that the 6% and 8% fermented feed could significantly improve intestinal health with no remarkable difference between the two groups. It was possible that fermented mixed feed at levels above a certain threshold (which was 6% in this study) could result in changes of the gut microflora and subsequently improve intestinal morphology and barrier functions. Therefore, control and 6% groups were selected for further analysis. At the genus level, eostasis . Similarbroilers . Erysipety acids . On the ing hens , which ll health . Besidesoduction . Howevers height . TherefoIn conclusion, fermented mixed feed could improve the morphology and barrier functions of the intestine, and alter the cecal microflora. This study demonstrated that fermented mixed feed could be used as a novel feed ingredient for laying hens, and that their favorable effects could be exhibited at addition levels of ≥6%. The specific mechanism of fermented feed-changing of cecal microflora of laying hens needs further study.


Fermentation is an important process that can provide new flavors and nutritional and functional foods, to deal with changing consumer preferences. Fermented foods have complex chemical components that can modulate unique qualitative properties. Consequently, monitoring the small molecular metabolites in fermented food is critical to clarify its qualitative properties and help deliver personalized nutrition. In recent years, the application of metabolomics to nutrition research of fermented foods has expanded. In this review, we examine the application of metabolomics technologies in food, with a primary focus on the different analytical approaches suitable for food metabolomics and discuss the advantages and disadvantages of these approaches. In addition, we summarize emerging studies applying metabolomics in the comprehensive analysis of the flavor, nutrition, function, and safety of fermented foods, as well as emphasize the applicability of metabolomics in characterizing the qualitative properties of fermented foods. Fermented foods have been produced and consumed since around the Neolithic period and have been embedded in dietary cultural norms around the world ,2. FermeSaccharomyces spp., Mucor spp., and Rhizopus spp.) and bacteria  [Fermentation is a metabolic process wherein microorganisms enzymatically convert substrates in raw materials into new products, which results in the unique final flavor, nutritional, functional, and safety characteristics of fermented foods ,11. The um spp.) ,13. Fermum spp.) ,15,16,17um spp.) . TherefoCurrently, metabolomics is an emerging field but is also considered an established but evolving analytical technology widely involved in many fields such as food science, food quality, and food safety ,20. WithMetabolomics allows for the collection of all metabolites in cells, tissues, or organisms under specific physiological periods or conditions . MetabolIn this review, we assess the latest applications of metabolomics in fermented food research. We discuss several metabolomics approaches and outline the perspectives on the current trends toward applying metabolomics to probe the flavor, nutrition, function, and safety properties of fermented foods. Further, this review provides a reference for quality control and identification associated with fermented foods.Studies describing food metabolomics have been published in many journals in the same field. Multiple databases were used to conduct a comprehensive search on related topics, such as Science Direct, National Center for Biotechnology Information, Web of science, and Google Scholar. The keywords included metabolomics, food, fermentation, detection methods, flavor, nutrition, function, safety, research, and were combined in different ways to effectively search relevant and up-to-date literature.http://www.google.com, accessed on 30 June 2021) [The basic metabolomics workflow was gradually standardized during application development . It compne 2021) ,34. Effene 2021) . The metne 2021) . Metabolne 2021) . MetabolNMR is one of the most frequently used analytical tools in metabolomic fingerprinting and profiling . SeveralInfrared (IR) spectroscopy is considered an effective tool for classifying, characterizing, and identifying small molecules, and FT-IR spectroscopy has rapidly become a valuable metabolic fingerprinting tool ,53,54. FOver the past decades, MS-based chromatographic systems (GC or LC) have rapidly developed into the most commonly used analytical approaches in metabolomic studies, partly because they yield higher sensitivity than the previously discussed techniques ,65,66. TGC-MS is the preferred analytical technique for the study of volatile compounds and is mainly employed for evaluating primary metabolites such as amino acids, fatty acids, organic acids, alcohols, and sugars or sugar alcohols ,69. GC-MCE-MS, another approach in metabolomics, is now a widely used analytical separation technique, notable for the separation of highly polar and charged metabolites, based on varying mass-to-charge ratios, such as amino acids, organic acids, and nucleotides ,81. The Another important detector with applications in metabolomics research is the electronic nose (E-nose), which deploys electronic sensors to mimic the biological olfactory mechanism to obtain the overall odor of products ,87. The Metabolomics generates extensive datasets that require effective data processing methods to successively interpret their biological implications. Bioinformatics and multifunctional tools for performing compound identification, statistics, enrichment, pathway prediction, and visualization provide high-quality and comprehensive metabolomics information .https://www.hmdb.ca, accessed on 30 June 2021; METLIN Database, https://metlin.scripps.edu/, accessed on 30 June 2021) [Before pattern recognition analysis , raw metabolomics data must be pre-processed, and a series of adjustments such as baseline correction, peak recognition, peak alignment, and normalization must be performed using the appropriate software, such as MestreNova  and Progenesis QI  ,98. Subshttps://www.genome.jp/kegg/, accessed on 30 June 2021) database or MetaboAnalyst , which helps understand the mechanisms of metabolic pathway changes in a sample [In addition, the application of multivariate statistical analysis can effectively reduce the complexity of a reliable metabolomics dataset containing qualitative and quantitative information in interpreting complex biological systems or related biological processes ,100. To a sample . Therefoa sample ,105.With increased consumption and a societal increase in health consciousness, the general population is more concerned about whether food and nutrition play an important role in maintaining health and reducing the risk of various diseases. The rise in health awareness has driven tremendous public interest in fermented foods, which have multiple health benefits, including antioxidant, anti-cancer, anti-inflammatory, and cardioprotective properties ,107. FerThe flavor of fermented foods is mostly generated through microbial metabolism and enzymatic biochemical reactions . It is abaijiu, huangjiu, beer, and red wine, which are all commonly consumed in Chinese society. Yang et al. [baijiu made from yellow, white, and black daqu, and captured 401 volatile compounds, mainly aromatic compounds and pyrazines. Among them, white daqu has the most types of esters and alcohols, but the levels of esters and alcohols in yellow and black daqu were higher than in white daqu, which may be related to microbial metabolism during fermentation. The flavor of Chinese huangjiu from Shanxi, a yellow rice wine with zao-aroma, was also analyzed based on GC-MS and GC-olfactometry (GC-O) techniques, and ethyl cinnamate and ethyl 3-phenylpropionate were demonstrated to be key aroma compounds, which indicated differences from others such as Zhejiang Shaoxing and Fujian Hongqu huangjiu [Monascus tea, and the understanding of the formation and evolution mechanism of its flavor-active compounds can improve its quality. Deng et al. [B. subtilis, are usually undesirable to the Chinese population, whereas natto is very popular in Japan where it is an important side dish. The volatile metabolite composition of natto products has been investigated through GC-MS and NMR, and it has been shown that ammonia, 2,5-dimethylpyrazine, isovalerate, isobutyrate, and 2-methylbutyrate are increased in amount and proportion in natto, which may explain the undesirable flavor [B. subtilis through NMR and not only found undesirable flavor compounds but also explained the changes in nutrients and functional components in fermented soymilk. In addition, metabolomics has played a key role in determining the maturity of cheese and other dairy products [Distinctive flavors are essential factors in alcoholic beverages, including g et al.  applied huangjiu ,115. Pu-g et al.  summarizg et al. . Wangzhig et al. . The mose flavor ,121,122.products , the anaproducts , and theproducts ,125.Consumer interest “beyond nutrition” and “functional” foods has surged dramatically, and fermented foods occupy a significant space in the functional foods market ,127. ConFermented soy products, including miso, meju, soybean paste, tempeh, and natto, are a staple in daily cuisine in East Asian countries. Based on metabolic characterization, it was found that during fermentation, formation and abundance of small peptides, amino acids, and fatty acids through the degradation of macromolecular substances such as protein and fat have an important influence on the nutritional quality of fermented soy foods ,133. WitLactobacillus bulgaricus and Streptococcus thermophilus [Fermented dairy products in the market are mainly yogurt and cheese, both of which are fermented by lactic acid bacteria, such as mophilus ,138. Themophilus . The ripmophilus . As the mophilus . Metabolmophilus ,141,142.Alcoholic beverages are prepared from plant sources such as grapes and cereals, the characteristics are mainly affected by yeast fermentation. Sugars represent the main groups of metabolites in wines, while organic acids, amino acids, and phenolic compounds represent other minor metabolites, which together constitute the basic nutritional quality of wines fermented with yeast strains . Grapes In addition, metabolomics has been applied to cabbage vinegar , ChineseConsumers not only pay attention to the sensory and nutritional value of food but now also have an increasing awareness of food safety, encouraging the food industry to establish and maintain product characteristics . Highly The improvement in food safety is mainly reflected in the changes in the nonnutritive factors or toxic compounds of the raw materials  before and after fermentation, which improve digestion and absorption. Seo et al.  performeAs the population and health awareness continue to increase, there will be an increasing need for functional as well as nutritious, safe, and palatable foods to meet changing consumer preferences. Fermentation technology can become a source of such functional foods, including the industrial production of traditional fermented foods, the development of fermented foods based on new raw materials, and the improvement of existing food fermentation technologies. Currently, fermented foods usually contain one or more probiotics beneficial to health. Fermentation is a highly complex biological process, which is essential for imparting new flavor characteristics to fermented foods, improving the nutritional and functional properties of raw materials, and improving the biological safety of fermented products. The industrial production and promotion of fermented foods is dependent on understanding its qualitative properties, which may require the introduction of new application technologies for characterization.The characterization should mainly include the main metabolites and secondary metabolites in the fermented foods, which directly reflect the quality characteristics, such as flavor and nutrition. Based on the established analytical techniques and knowledge of systems biology, metabolomics may prove to be an indispensable technique as it allows simultaneous qualitative and quantitative analysis of all low-molecular-weight metabolites in a certain organism or cell during a specific physiological period, it is also a manifestation of protein and gene level results. Thus, it can help consumers have more direct access to products with dietary nutrients that they desire. Thus, the application of metabolomics combined with multivariate statistical analysis has evolved into a useful tool in food science.This review shows the importance of applying metabolomic analysis to identify the quality characteristics of fermented foods. It was possible to perceive from the latest research in this field that the existing techniques used in metabolomic studies for investigating the molecular fingerprints of fermented foods include NMR, FT-IR, LC-MS, GC-MS, CE-MS, and E-nose. Each technique has its advantages and disadvantages in terms of sensitivity, reliability, and sample preparation; therefore, the use of a combined method is recommended to provide a more comprehensive understanding of the metabolomes of fermented foods. The application of metabolomics in characterizing the qualitative properties of fermented foods, specifically flavor, nutrition, function, and safety was also summarized in this review, and may assist in the discovery of biomarkers that discriminate maturity, variety, region, and promotion of value-added fermented foods. Nevertheless, considering the complexity of fermented foods and metabolomics, the verification of functional biomarker compounds in fermented foods, development of metabolomics technology for rapid and accurate detection, and integration with different techniques will be required in further research. Moreover, the development and improvement of a reliable database of fermented food metabolites is necessary for practical and industrial applications.


Phragmites australis (common reed) together with high genetic diversity and remarkable adaptability has been suggested as a model for responses to global change and indicators of environmental fluctuations. We found high levels of genetic and epigenetic diversity and significant genetic/epigenetic structure within each of 12 studied populations sampled from four natural habitats of P. australis. Possible adaptive epigenetic variation was suggested by significant correlations between DNA methylation‐based epigenetic differentiation and adaptive genetic divergence in populations across the habitats. Meanwhile, various AMOVAs indicated that some epigenetic differences may respond to various local habitats. A partial Mantel test was used to tease out the correlations between genetic/epigenetic variation and habitat after controlling for the correlation between genetic and epigenetic variations. We found that epigenetic diversity was affected mostly by soil nutrient availability, suggesting that at least some epigenetic differentiation occurred independently of genetic variation. We also found stronger correlations between epigenetic variation and phenotypic traits than between genetic variation and such traits. Overall, our findings indicate that genetically based differentiation correlates with heterogeneous habitats, while epigenetic variation plays an important role in ecological differentiation in natural populations of P. australis. In addition, our results suggest that when assessing global change responses of plant species, intraspecific variation needs to be considered.The mechanisms underlying heritable phenotypic divergence associated with adaptation in response to environmental stresses may involve both genetic and epigenetic variations. Several prior studies have revealed even higher levels of epigenetic variation than genetic variation. However, few population‐level studies have explored the effects of epigenetic variation on species with high levels of genetic diversity distributed across different habitats. Using AFLP and methylation‐sensitive AFLP markers, we tested the hypothesis that epigenetic variation may contribute to differences in plants occupying different habitats when genetic variation alone cannot fully explain adaptation. As a cosmopolitan invasive species,  Phragmites australis differ significantly among four habitat types with markedly different edaphic characteristics, including moisture, pH, and ions in the Songnen Prairie in Northeast China. Our findings indicate that genetically based differentiation correlates with heterogeneous habitats, while epigenetic variation plays an important role in ecological differentiation in natural populations of P. australis.Various morphological traits of native  Changes of P. australis may have strong socioeconomic impacts that indicate and provide feedback on changing environmental conditions. P. australis can reproduce both sexually and asexually and is an invasive plant in North America, which makes it a particularly good model for understanding adaptation and invasion . The area is influenced by a temperate, semiarid, and semiwet continental monsoon climate. The mean annual precipitation is 313–581 mm, most of which falls between June and August  The alkali‐saline patches lack accumulated rainwater and have a pH greater than 10 . The coverage of the monodominant P. australis community is 20%‐40%. The intrinsic soil has been severely destructed. However, after the rainy season, annual halophytes, including Kochia scoparia, Suaeda heteroptera, Suaeda corniculata, Suaeda glauca, and Chloris virgata, become dominant species at the end of the growing season. (c) The Leymus chinensis + Phragmites australis community  is the typical community of meadow steppe, with coverage greater than 90%. There is no accumulated rainwater or extremely short‐term accumulation throughout the year. (d) In the sandy soil habitat  with a pH of 8–8.5 and good soil aeration, the community coverage is 75%–80%. In addition to P. australis, Cleistogenes squarrosa, Trigonella ruthenica, Lespedeza daurica, Setaria viridis, and other species also occur in the community , total phosphorus, total nitrogen, organic matter, NO2.3EcoRI + 3/MseI + 3 primer pairs  that provided the most reliable, consistently scorable bands were chosen after screening (Table MseI enzyme with MspI or HpaII at the same concentration and chose 10 primers. GeneMapper v.4.1 software (Applied Biosystems) was utilized to analyze the raw data.Genomic DNA was extracted using a modified cetyltrimethylammonium bromide (CTAB) method  absent from both EcoRI/HpaII and EcoRI/MspI products, or (3) present in only the EcoRI/HpaII or the EcoRI/MspI product. Condition (1) corresponds to a nonmethylated state, condition (3) indicates a methylated state, and condition (2) was treated as a missing score because it could result from either fragment absence or hypermethylation. Loci were individually classified as either “methylation‐susceptible loci (MSL)” or “nonmethylated loci (NML)” according to whether the observed proportion of discordant MspI/HpaII scores exceeded a given threshold that was set equal to the expected per‐individual probability of obtaining a mismatch of MspI and HpaII scores due to errors  present in both 2.42.4.1α = 0.05). The patterns of variation in plant characteristics among habitats and locations were analyzed with habitat as a fixed factor and location nested within habitat as a random factor. The relationships of different soil and plant characteristics among the 4 habitats were investigated using a principal coordinate analysis (PCA) program . When the overall variation in the analysis of variation (ANOVA) was significant, post hoc comparisons among means of soil characteristics were performed (Tukey's honest significant difference (HSD) test, 2.4.2AN), the effective allele number per locus (EN), the percentage of polymorphic loci (P), Nei's gene diversity index (EH), the Shannon information index (I), and gene flow (mN). The percentage of polymorphic bands at the 5% level was calculated by AFLPSURV 1.0  analysis was used to build a dendrogram of the relationships among individuals from the 4 habitats by PAUP4b10 with 1,000 bootstrap replicates , represented “unmethylated”; type 2, with , represented “hemimethylated”; type 3, with , represented “internal cytosine methylation”; and type 4, with , represented “full methylation or absence of target.” AMOVAs in MSL and NML and a comparison of Shannon's diversity index were performed, and the proportions of the four methylation states in the habitats were also calculated.Principal coordinate analysis (PCoA) based on AFLP and MSAP‐MSL loci was conducted with the package “msap” in R  iterations , ΔK, an ad hoc quantity related to the second‐order rate of change of the log probability was calculated using the Evanno method , to identify candidate loci   are regressed against multivariate predictors . The RDA was performed to quantify the effects of 14 soil variables on genetic variations of A genetic/epigenetic distance matrix was used to calculate pairwise population PhiPT values and thus to analyze the correlations between genetic variation, epigenetic variation. and habitat by ZT software  and accounted for the 25.27% variance. The biplot showed the distribution of the 80 samples, demonstrating no major effect of location and separation among habitats , NO3‐nitrogen, Na+, K+, and pH  , and within populations  Table . The pai1) Table .3.3FST values than expected under neutrality at the 99.5% probability level  corresponding to loci potentially influenced by directional selection or linked to a locus under selection. According to modified FDIST, 24 outliers (0.97%) showed higher l Figure . BayeScal Figure . Three ll Figure . Accordil Figure . The mosdf = 1, p = 1.261e−05)   were identified by these 3 approaches. The loci identified with Samβada were the same as those identified with BayeScan, with the exception of 1 locus. Most of the outliers identified by BayeScan were consistent with those identified using these two methods Figure . One loc5) Table . Individ8) Table . All the3.4R2 = 0.716, p < .001). We also detected a significant correlation between the matrices of MSL‐based distances and NML‐based distances . A significant correlation between genetic variation and epigenetic variation was revealed by the Mantel test .AFLP pairwise Phi_ST had a positive correlation with MSAP‐MSL pairwise Phi_ST  for the polymorphic MSL (M ± SD = 0.514 ± 0.159) was significantly higher than the corresponding value for the NML (M ± SD = 0.244 ± 0.139) . Therefore, it was apparent that methylation‐based epigenetic diversity exceeded genetic diversity when the two magnitudes were compared using the same index. H1, H2, and H3 displayed a higher value of all diversity indices for genetic compared with epigenetic variation, in contrast to H4, which showed a higher level of epigenetic diversity than genetic diversity. There was more epigenetic variance than genetic variance within habitats  but nonsignificant genetic differentiation  between 9 individuals from H1 and 9 individuals from H3  but nonsignificant genetic differentiation  was found between 7 individuals from H2 and 15 individuals from H3, and 23 loci were significantly differentiated, indicating that the methylation patterns at these loci were different between habitats.The analysis of individuals with nonsignificant genetic differentiation more clearly suggested the potential contribution of epigenetic variation to plant ecological differentiation in response to different habitats. AMOVA revealed significant epigenetic differentiation  was found. Both epigenetic variation and genetic variation were significantly correlated with most soil variables. The values of correlation coefficients between epigenetic and environmental distances, with variables including soil moisture, total phosphorus (P), total nitrogen (N), organic matter, Ca2+, and Mg2+, were greater than the values of those between genetic and those environmental distances when we controlled for the correlation between genetic and epigenetic variations. However, the correlation values between genetic and environmental distances such as soil pH, conductivity, NO3‐N, NH4‐N, Cl−, SO42−, K+, and Na+ were greater than those between epigenetic and environmental distances. Thus, our data suggest epigenetic variation was more affected by soil nutrient availability than was genetic variation.To test for independent epigenetic variation, the correlations between genetic variation, epigenetic variation, and habitat for all individuals across all sites in H1, H2, and H3 were analyzed Table . A signieH and I . These results may explain why the growth parameters in H4 were always higher than those in H2 and H3, thereby indicating that the soil desertification in H4 was not very serious. Therefore, the variation in many traits in this set of P. australis variants from 4 habitats reflects the ability to acquire light resources and functionally accommodate alkaline–saline conditions; thus, they are putatively adaptive traits.In 3 of the 4 habitats, traits were significantly correlated with almost all the soil environmental factors Table . Biomass4.2p = 55.615, EH =0.202) with those of P. australis in the eastern half of the United States  model, global change driver affects lineages composed of different genotypes or ecotypes  will be important next steps in exploring the functional significance of epigenetic variation, allowing the direct comparison of genetic and epigenetic variations, and in turn, allowing the differentiation of “facilitated” and “pure” epigenetic variation. Then, carefully designed experiments, such as targeted bisulfite sequencing or expression of candidate loci in knockouts or transgenic manipulations, can be used to investigate the autonomy and importance of epigenetic effects.Together, our results suggest that epigenetic variation is correlated with genetic variation, and both may contribute to adaptation to stressful environments in the cosmopolitan grass, The authors have no conflict of interest to declare.Tian Qiu: Investigation ; Writing‐original draft . Zhiyuan Liu: Investigation ; Software . Yunfei Yang: Conceptualization ; Supervision . Bao Liu: Supervision ; Writing‐review & editing .Appendix S1Click here for additional data file.