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A total number of 3189 lakes have been spatially delimited and analyzed. The delimitation and spatial distribution of the lakes revealed their uneven distribution within the Romanian territory. The largest share of lakes, (41.5%) are distributed within the low plains, located mainly in the South and West of the country. About 36% of the identified lakes are located in the hilly and plateau units, while 11.5% are in the mountain areas and about 11% in the Danube Delta.
The assessment of the state of degradation of the lentic ecosystems by the GIS based extended WRASTIC model revealed that more than half (57%) of the analyzed lakes are classified as semi-degraded. These are mostly distributed in the plains (46%) and in the plateau areas (33%) (Fig. 1).
Figure 1

Distribution of lentic ecosystems in Romania according to the major topography units (this map was created with Arc GIS 10.5 software).

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The lakes classified as degraded represent 31% of the total, mostly located in the plains (48%) and plateau (36.5%), the least part being located in the Danube Delta (about 0.5%). The lakes in the natural state represent a small share, respectively about 13%, generally located in the Danube Delta (72%) and the mountain areas (21%) (Supplementary Table 1).
Altitudinal stages represent a restrictive factor in the spatial distribution of lakes throughout the country. Most lakes, about 76%, are located at low altitudes, respectively below an altitude of 200 m. The number of lakes identified at higher altitudes, over 800 m, is reduced, representing about 8% of the total number of analyzed lakes (Fig. 2).
Figure 2

Distribution of lentic ecosystems on the Romanian territory according to the altitudinal stages (this map was created with Arc GIS 10.5 software).

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Regarding the natural lakes, the largest part of them is represented by natural lakes located at altitudes less than 200 m (about 83%). In the same time, about 75% of the lakes evaluated as degraded are located at altitudes less than 200 m.
About 98.5% of the 412 lakes in the natural state are located, partially or totally, in protected areas of national or international interest, such as national and natural parks, Ramsar sites, Biosphere reserves, UNESCO World heritage sites and Natura 2000 sites (Sites of Community Importance and Special Protection Areas) (Fig. 3.).
Figure 3

Distribution of lake categories according to the state of degradation and the relationship with protected areas of national and international interest in Romania (this map was created with Arc GIS 10.5 software).

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The percentage of semi-degraded and degraded lakes located in protected areas is lower (about 38% of the semi-degraded lakes, respectively 32.5% of the degraded) (Supplementary Table 2). The other lakes are not included in protected areas and do not own any special protection regime.
As a result of applying the methodology based on WRASTIC-HI index, only 9 lakes out of the total of 412 natural lakes are associated with industrial activities and different forms of small-scale exploitation within their hydrographic basins, while the rest of 98% do not present such activities.
The hydrographic basins of the natural lakes do not cover very large areas, 83% of them stretching on area of less than 39 square km, each. In about 97% of cases, agricultural activities in the reception basin represent below 20% of the economic activity, the irrigation percentage being low and the degree of vegetation cover being high.
Considering the degraded lakes, for a large share of them (87%) of them industrial and exploitation activities, such as mines, quarries or dumps are present within the river basin. A high percentage, about 98%, include treatment plants with different types of processing (primary or secondary) within the reception hydrographic basins. For 96% of the degraded lakes, agricultural activities and permanent irrigation activities are covering over 40% of the related basins area.
Spearman correlation showed that there is a good correlation between the degradation state and several components of the WRASTIC-HI index such as Industrial activities, Recreational activities, Wastewater, Ways of transportation, Irrigation and Agricultural activities (Table 1).
Table 1 Correlation between Degradation state and component indices of the WRASTIC-HI index.
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Between the state of degradation, on the one hand, and the permeability of the soil, the slope and the vegetation cover of the water lily, on the other hand, the analysis showed that there is no correlation. However, there is a weak correlation between the degradation state and Exposition (Table 2).
Table 2 Correlation between degradation state and the HI index variables, which belong to the WRASTIC-HI index.
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The computational results indicate a negative correlation between the state of degradation, the percentage of the basin included in the protected areas and the percentage of the basin included in the protected areas of the Natura 2000 network (the probability level of 0.0001, being less than 0.05, indicates that there is a statistical significance) (Table 3).
Table 3 The results of the statistical analysis regarding the relationship between the state of degradation and variables within the river basin.
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The statistical analysis performed shows that there is no correlation between the Degradation State and Altitude, while between the Degradation state and the Relief units there is a weak negative correlation.
The results indicate also a direct correlation between the state of degradation, the number of inhabitants without access to the sewerage and the population density in the lake basin, the correlation coefficient being 0.024, and respectively 0.235.
It is important to study of the state of the lentic ecosystems both regarding the pressures coming from human activity and the ones originating from climatic changes or other natural phenomena. However, the development of an assessment model that can be applied to all aquatic ecosystems, and lentic ecosystem in particular, is a challenge, because available data are not homogenous, each region and lake having its own particularities. Choosing the proper set of indicators that can be useful for the overall characterization of the quality of lentic ecosystems, will lead to a coherent implementation of biodiversity strategies.
To the best of our knowledge, this is the first evaluation of the quality of lentic ecosystems in Romania by multi-criteria analysis. This assessment is part of a national project for implementation of a national policy on biodiversity, as a response to EU requirements.
Over the time, the scientific literature identified various methodologies for the evaluation of the quality of water resources. Such methods include DRASTIC20,21, and methods derived from DRASTIC22,23,24. Other authors used digital surface model (DSM) and a point dataset as the sources of observation and target locations for Geospatial analysis of lake scenery25.
For integrative water quality management, Feng et al.26, proposed a model-based method. Their method integrated three indices derived from three models for assessment of the risk due to nutrient dynamics26.
A multi-attribute value theory to formulate an integrated water quality assessment method was used by Schuwirth27, for aggregation over multiple pollutants and time.
Another category of indexes that are used in evaluating the state of degradation of lacustrine ecosystems aim at analysis of the presence of degradation sources in supplying basin. For example, Mirzaei et al19 calculated WRASTIC index for assessment of pollution risk, respectively degradation sources, from the watershed that feeds a water body. Potential pollutant load index (PPL) was employed by Romanelli et al18 for analyzing the presence and intensity of potential pollution sources from the drainage area of several lakes, with the purpose of establishing degradation classes of the water body. In the same study, the Lake Vulnerability Index highlighted the capacity of the water body to handle the impact generated by degradation sources, taking into account parameters like slope, soil permeability or aspect of slopes18.
According to the characteristics of the study area, modified versions of WRASTIC index are to be found in the literature, and were implemented by using additional criteria or eliminating some parameters28.
Rahimi et al29 used WRASTIC Index for evaluation of wetland water quality. Their results revealed that the activity in adjacent wetland areas exert a large impact on wetland integrity29.
In another study, aquatic ecosystems pollution risk was evaluated by a combined Fuzzy-WRASTIC method. The model was validated by comparison with samples collected from the case study area. The authors concluded that the method has advantages over other methods, as it includes a wide range of drivers and parameters that influence the water quality. The results obtained pointed that areas with high contamination risk are due to the unbalanced arrangement and compact of land uses in the neighborhood of the aquatic ecosystems30. Using analytical survey and experimental studies Mirzaei et al19 investigated the pollution risk for Zayandehrud river, Iran. Agricultural, industrial activities and population centers were the main causes of pollution in the study case area19.
In Romania, the evaluation of aquatic ecosystems was performed by various researchers, either for a specific area or for a hydrographic basin.
For example, Rosca et al31 studied the impact of anthropogenic activity on water quality parameters of glacial lakes from Rodnei mountains. The factors taken in consideration were tourism and livestock. The pollution index was calculated based on three indices, targeted on heavy metal influences, namely, the heavy metal pollution index (indicating the quality of waters related to the heavy metals content), the heavy metal evaluation index (assessment of the quality of water with respect to heavy metals) and the degree of contamination (used to quantify the contamination level with the heavy metal). The physico-chemical parameters pointed a good quality of the study case lakes. The conclusion of the authors was that minor anthropic alteration and a low anthropogenic impact is exerted in these areas. The only anthropic pressure on the aquatic systems in Rodnei Mountains was reported as being exerted by grazing activities31.
Another paper described the assessment of actual water quality and sedimentological conditions of the Corbu lake, Western Black Sea coast. The ecological status of this lake was found to be from good to weak classes for nitrites, ammonium and phosphates, moderate for sulphates and weak for detergents32.
The impact of human interventions and climate changes on the hydro-chemical composition of Techirghiol lake (Romania) was recently investigated by Maftei et al33. The study identified a degradation of this ecosystem between 1970–1998, due to extensive irrigation in the lake region, followed by a major decrease of the lake’s salinity33. Physico-chemical water quality parameters of lake Brăneşti was investigated by Benciu et al34. The water quality parameters for the last 50 years were correlated with the anthropogenic pressure in the region. Analysis of water and soil samples in the vicinity of this lake, revealed that parameters were within legal norms for both water and soil34.
Another study presented by Dumitran et al35 proposed an eutrophication model for describing the ecological behavior of a eutrophic lake. The physical model was mathematically transposed to a set of equations for analysing the selected parameters linked to eutrophication state. The resulted model showed a good correlation with the measured data35.
It is to be noted that most of the available literature is based on the assessment of the water quality, by measurements of physico-chemical parameters, and calculation of pollution indexes. To our knowledge no extensive studies involved the study of the lentic ecosystems with respect to vulnerability and risk of pollution by using multicriterial analysis.
Generally, the precautionary approach is applied by identifying and analyzing the categories of drivers that influence the degradation of lentic ecosystems, especially in the protected areas36,37,38. Three main categories of activities that generate environmental issues have been identified within protected areas included within the Natura 2000 Sites as follows: (a) agricultural activities and forestry practice; (b) sectoral activities (industrial, commercial and tourism sectors); (c) conservation policies (management of protected areas, protection of different species, etc.)39. A cross-sectoral approach is needed in order to resolve medium-term environmental conflicts, thus being be able to extend the assessment towards various categories of protected areas and generating efficient policies for the management of resources40,41.
Identifying and analyzing the categories of conflicts that may be associated with lentic ecosystems provide the possibility of an efficient ecosystem management22,23.
The lakes from this case study comprise both natural lakes (glacial, karst, karst-saline, ponds, lagoons), as well as ponds accumulation lakes, with an important role in ensuring the resources of water for the population and economic activities, as well as the development and maintenance of habitats and species of community interest (birds, amphibians, reptiles, fish, etc.).
Most of the lakes resulting from the analysis as being degraded and semi-degraded are located in the plains, at low altitudes, within areas covered with agricultural lands, industrial facilities and dense transportation routes.
The lentic ecosystems characterized as being in a natural state resulting from the proposed methodology are mainly distributed in the high mountain areas and in the Danube Delta area. Thus, altitude, fragmentation of the relief and accessibility are favorable factors regarding the natural state of water bodies, including lentic ecosystems. The high number of lakes characterized as degraded or semi-degraded compared to that of natural lakes is justified by the existence of a small number of lakes located at high altitudes, over 800 m.
It is to be taken into account that the degradation state classification is directly influenced by the data used in defining WRASTIC indicators, being generally derived data, which may explain the limitation of the method from this point of view.
The lack of correlation or poor correlation resulting from the statistical analysis between the degradation state and the indicators defining the HI index (component part of the WRASTIC-HI index), respectively the permeability, the exposure and the slope, highlight the insignificant role of these parameters in determining the state of lake degradation. However, the processes of erosion and sediment transport on the surface of the basins and their accumulation in lakes can influence the water quality of the lakes, their clogging, their functionality and the services offered, which are important factors in improving the management of the analyzed lakes42.
The status of protected areas offers a high degree of protection by diminishing the anthropic activities and the negative effects on the lakes, being recommended that all economic activities be located outside these protected areas43 the basins being vulnerable to human activities. This aspect is also highlighted by the correlation between the state of degradation obtained and the percentage of the hydrographic basin existing in different categories of protected areas, between which there is a good correlation, as well as by the high number of natural lakes that are included in protected areas (~ 98%), located especially in the Danube Delta Biosphere Reserve.
The local public administrations are directly interested in the management and protection of lentic ecosystems, many lakes being included in different categories of protected areas. Increasing the number of lakes in the natural state involves identifying degraded or semi-degraded lentic ecosystems outside protected areas and carrying out ecological reconstruction activities or diminishing agricultural and industrial activities in their vicinity.
The state of the lakes may also depend on the dynamics of the hydrophilic and hydrophilic vegetation, respectively on the hedge with vegetation cover of the water lily. In our study, the statistical analysis showed that there is no correlation between the state of degradation and the Coverage with vegetation of the water lily. Thus, in this case, the state of degradation of the lentic ecosystems is not influenced by this parameter, although, in some cases, remote sensing analysis revealed the presence of excess algae and aquatic plants in both natural and semi-degraded lakes44.
The lakes located in the low plain areas are also affected by the eutrophication process, amplified by the reduced depth (which ensures the rapid development of algae during the summer), the contribution of nutrients due to the agricultural activities in the vicinity and the development of recreational activities. More

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Comparison of sampling methods for microbes on the surface of tobacco leaves
According to previous research, two sampling methods for microbes on the surface of tobaccos were selected to separately perform extraction and amplification of genome DNAs after sampling the microbes. As shown in Table 1, as for the first sampling method, the DNAs extracted from two tobacco leaf samples (fresh tobacco leaves and tobacco leaves in the later yellowing period) were both unqualified after subjected to amplification. Therefore, the first method was not suitable for extracting the microbes on the surface of tobacco leaves. The two tobacco samples extracted by using the second method both allowed favorably amplification and their amplification results were both proper. Thus, the second method was applied to sample the microbes on the surface of tobacco leaves subsequently.
Table 1 Comparison of effects of the two methods for sampling microbes on the surface of tobaccos.
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OTU clustering analysis
To explore the species compositions of various samples, OTUs clustering was carried out on effective Tags of all samples based on 97% of identity; afterwards, species annotation was performed on the OTUs sequences. According to OTUs results obtained through clustering and research requirements, the common and specific OTUs among different samples (groups) were analyzed.
OTU clustering analysis of bacteria in tobacco leaves
The result is shown in Fig. 3. Each petal in the petal diagram represents a group (sample) and different colors mean diverse samples (groups); the number at the core stands for the total number of OTUs in all samples; the number in each petal denotes the number of OTUs specific in the sample (group). It can be seen from the figure that the numbers of the core microbial communities subjected to conventional flue-curing procedure and dry-ball temperature set and wet-ball temperature degradation flue-curing procedure were basically consistent, showing no great change.
Figure 3

Petal diagrams of OTUs in samples flue-cured through conventional procedure and temperature- and humidity-controlled procedure under different sampling stages (SB: the surface bacteria of fresh tobacco leaves; EB: endophytic bacteria of fresh tobacco leaves; CSB: the surface bacteria of tobacco leaves flue-cured using conventional procedure; CEB: endophytic bacteria of tobacco leaves flue-cured using conventional procedure; SSB: the surface bacteria of tobacco leaves flue-cured using temperature- and humidity-controlled procedure; SEB: endophytic bacteria of tobacco leaves flue-cured using temperature- and humidity-controlled procedure; 2–6 represent different sampling stages).

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OTU clustering analysis of fungi in tobacco leaves
The result is displayed in Fig. 4. As shown in the figure, the core microbial communities flue-cured by conventional procedure and temperature- and humidity-controlled procedure showed basically coincident numbers. The latter was only 5–10 core microbial communities more than the former. Similar to the core bacterial communities, the number of core fungal communities presented no great difference in the flue-curing process.
Figure 4

Petal diagrams of OTUs of fungi in samples flue-cured by using conventional procedure and temperature- and humidity-controlled procedure in different sampling stages (SB: the surface fungi of fresh tobacco leaves; EB: endophytic fungi of fresh tobacco leaves; CSB: the surface fungi of tobacco leaves flue-cured using conventional procedure; CEB: endophytic fungi of tobacco leaves flue-cured using conventional procedure; SSB: the surface fungi of tobacco leaves flue-cured using temperature- and humidity-controlled procedure; SEB: endophytic fungi of tobacco leaves flue-cured using temperature and humidity-controlled procedure; 2–6 denote different sampling stages.

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Analysis of relative abundances of species
According to the results of species annotations, the species of each sample or group with the maximum abundance ranking the top 10–30 at various classification levels were selected to generate the cumulative histogram of relative abundances of species. The species with a high relative abundance in various samples at different classification levels and their proportions can be intuitively found.
Analysis of relative abundances of bacteria in tobaccos
Based on the results of species annotations, the species of each sample or group with the maximum abundance ranking the top 10–30 at various classification levels were selected to generate the cumulative histogram of relative abundances of species. The species with a high relative abundance in various samples at different classification levels and their proportions can be visualized.
As shown in Fig. 5, at the level of phylum, the bacteria in tobaccos mainly contained Proteobacteria, Actinobacteria, Bacteroidetes, Firmicutes, Planctomycetes, Acidobacteria, Chloroflexi, unidentified bacteria, Thaumarchaeota and Gemmatimonadetes. It can be seen that the surface and endophytic bacterial communities of fresh tobacco leaves slightly differed at the level of phylum. Proteobacteria showed the largest content, followed by Actinobacteria and Bacteroidetes, and the contents of the other bacterial phyla were relatively low. By using conventional flue-curing procedure, the bacterial diversity on the surface of tobacco leaves progressively declined as the flue-curing continued, and the relative content of Proteobacteria rose at first and then reduced; the reduction amplitude of Actinobacteria was relatively stable in the flue-curing process while that of Bacteroidetes was relatively large. For the dry-ball temperature set and wet-ball temperature degradation flue-curing procedure, as the flue-curing proceeded, the relative content of Proteobacteria gradually increased and it did not greatly reduce until reaching the last flue-curing stage. However, its relative content was not significantly different from that in fresh tobacco leaves; similar to Proteobacteria, the relative contents of both Actinobacteria and Bacteroidetes also grew at first and then decreased; in terms of endophytic bacteria of tobaccos, as the flue-curing process continued, the relative contents of Proteobacteria and the other main bacterial communities rapidly dropped while those of the other communities sharply increased.
Figure 5

Histogram of relative abundances of species at the level of phylum.

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As shown in Fig. 6, at the level of genus, the main dominant bacterial communities in endophytic bacteria of fresh tobacco leaves included Pseudomonas, Sphingomonas, Ralstonia, Methylobacterium, Massilia, Sphingobacterium, Rhizobium, Halomonas, Serratia and Rickettsia.
Figure 6

Column chart of species relative abundance at genus level.

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When employing conventional flue-curing procedure, the bacterial communities on the surface of tobaccos were relatively marginally changed at the level of genus while the endophytic bacteria varied remarkably. As the flue-curing process proceeded, the relative content of 30 main endophytic bacterial communities found before the flue-curing had dropped to 2% even in the early flue-curing stage (35 ℃). In comparison, the relative content of the bacterial communities in the first two flue-curing stages under dry-ball temperature set and wet-ball temperature degradation flue-curing procedure was higher.
Under conventional procedure, the relative abundance of Pseudomonas on the surface of tobacco leaves increased at first and then decreased, so did that of Sphingomonas. Although no signs of Ralstonia solanacearum were visualized on the surface of the sampled tobacco leaf samples, Ralstonia was found in the analysis of bacterial communities. With the ongoing flue-curing process, the relative content of Ralstonia rapidly reduced; the relative content of Methylobacterium on the surface of fresh tobacco leaves declined to some extent in the flue-curing process, and accounted for a large proportion in bacterial communities on the surface of flue-cured tobacco leaves. The relative contents of the other main bacterial communities were all progressively lowered basically.
When implementing dry-ball temperature set and wet-ball temperature degradation flue-curing procedure, the relative contents of the main bacterial communities in the early flue-curing stage were higher than those in fresh tobacco leaves. The relative contents of them marginally differed from those in fresh tobacco leaves even though flue-curing process was ended; the relative content of Pseudomonas gradually increased in the flue-curing process. By contrast, the relative contents of Sphingomonas and Methylobacterium both grew at first and then declined. The relative contents of the other main bacterial communities relatively slowly varied in the flue-curing process and they did not greatly decrease until the flue-curing process was ended. Moreover, the relative contents of some bacterial genera, including Sphingobacterium and Rickettsia, had remarkably dropped in the early flue-curing stage.
Analysis of relative abundances of fungi in tobaccos
As shown in Fig. 7, at the level of phylum, fungi in tobaccos mainly covered Ascomycota, Basidiomycota, Mortierellomycota, Rozellomycota, Glomeromycota, Chytridiomycota, Kickxellomycota, Mucoromycota and Olpidiomycota. It can be seen from the figure that fungi in tobaccos mainly included Ascomycota and Basidiomycota; the other fungi (phylum) took up a relatively low proportion.
Figure 7

Histogram of relative abundances of species at the level of phylum.

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When being flue-cured by using conventional procedure, the relative abundance of Ascomycota on the surface of tobacco leaves gradually increased while those of Basidiomycotaand the other fungal phyla gradually decreased with the ongoing flue-curing process; under temperature- and humidity-controlled flue-curing, the evolution law of fungal communities was similar to that using conventional procedure at the level of phylum. To be specific, a trend was shown that the relative abundance of Ascomycota gradually rose while those of Basidiomycota and the other fungal phyla were lowered, which was basically similar to that under conventional flue-curing procedure.
Their proportions were higher than those on the surface of tobacco leaves.The change amplitude of the endophytic fungi of tobacco leaves was less significant than that of fungi on the surface of tobacco leaves. Either under conventional flue-curing or temperature- and humidity-controlled flue-curing, the relative abundance of Ascomycota basically increased at first and then declined while that of Basidiomycota reduced at first, then grew and finally dropped.
As shown in Fig. 8, the change trends of community compositions under conventional flue-curing and temperature- and humidity-controlled flue-curing at the level of genus were similar to those at the level of phylum. There was a great difference only in the relative contents of fungal communities. In terms of fungi on the surface of tobacco leaves, the relative content of Alternaria under conventional flue-curing greatly increased at 38.5 ℃ and 54 ℃, with increases at the same time points under temperature- and humidity-controlled flue-curing; however, the growth amplitude of the relative content was less significant than that under conventional flue-curing. Cladosporium was another main fungal community and its relative content slowly decreased in the later stage of temperature- and humidity-controlled flue-curing. The relative content of Symmetrospora progressively decreased when using conventional flue-curing procedure while its reduction rate slowed down under temperature- and humidity-controlled flue-curing. The relative content of Ophiocordyceps on the surface of tobacco leaves was relatively low and it both gradually reduced when using the two flue-curing technologies. Moreover, the relative contents of the other fungal genera also progressively declined as the flue-curing proceeded.
Figure 8

Histogram of relative abundances of species at the level of genus.

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As for changes of endophytic fungi of tobaccos when using the two flue-curing technologies, the relative content of Alternaria under conventional flue-curing was higher than that under temperature- and humidity-controlled flue-curing. The result can be found even though the flue-curing process was ended. The relative content of Cladosporium marginally varied under conventional flue-curing and greatly increased at 35 ℃. After completing the flue-curing process, the relative content did not significantly differ from the value in fresh tobacco leaves. However, for dry-ball temperature set and wet-ball temperature degradation flue-curing procedure, the relative content of Cladosporium progressively reduced on the whole and the value after ending the flue-curing process was only about half of that in fresh tobacco leaves. The relative content of Symmetrospora showed a same change trend with Cladosporium under conventional flue-curing and temperature- and humidity-controlled flue-curing. Additionally, the reduction rate of the relative content of Symmetrospora was higher than that of Cladosporium under temperature- and humidity-controlled flue-curing. Relative to fungal communities on the surface of tobaccos, although the relative contents of the other endophytic fungal genera gradually dropped with the flue-curing.
Clustered heat maps of species abundances
According to species annotations and abundances of all samples at the level of genus, genera whose abundances ranked the top 35 were selected. Subsequently, based on the abundances of these genera in each sample, a heat map is drawn by conducting clustering from the two aspects: i.e. species and samples. By doing so, it is convenient to ascertain a species with a high abundance or low content and the sample from which it is found.
Clustered heat map of species abundances of bacteria in tobaccos
The result is displayed in Fig. 9. It can be seen from the clustered heat map that bacterial communities mainly reside on the surface and in the interior of the fresh tobacco leaves at first. As the flue-curing proceeded, the contents of the main bacterial communities were changed to some extent: the main bacterial communities reduced in the content and the tobacco leaves became light in color.
Figure 9

Clustered heat map of species abundances at the level of genus.

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Clustered heat map of species abundance of fungi in tobaccos
According to species annotations and abundances of all samples at the level of genus, the genera whose abundances ranked the top 35 were selected. Based on the abundances of these genera in each sample, a heat map is drawn by conducting clustering from the two aspects, i.e. species and samples. It can be found from Fig. 10 that the distribution of fungi on the surface of tobaccos greatly differed from that of endophytic fungi. Moreover, the distribution of materials also presented a great difference when using the two flue-curing technologies.
Figure 10

Clustered heat map of species abundances at the level of genus.

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Correlation with environmental factors
Correlation of bacteria with environmental factors
Temperature and humidity were mainly controlled in the flue-curing process of tobacco leaves; and the main environmental factors involved dry- and wet-bulb temperatures. It can be seen from Fig. 11 that Pantoea, Nesterenkonia, Staphylococcus, Variovorax, Chryseomonas, Rhodococcus, Paracoccus, Massilia, Serratia, Ralstonia and Pseudomonas were more likely to be affected by temperature and humidity. Pantoea and Variovorax exhibited a positive correlation with temperature and humidity; Nesterenkonia, Staphylococcus, Chryseomonas, Rhodococcus, Paracoccus, Serratia and Ralstonia presented a negative correlation with temperature and humidity. Actinomycetospora were negatively correlated with the dry-bulb temperature while positively correlated with the wet-bulb temperature; Stenotrophomonas, Cutibacterium and Sediminibacterium were all negatively correlated with both dry- and wet-bulb temperatures while they presented a higher negative correlation with the dry-bulb temperature.
Figure 11

Heat map of correlation with environmental factors at the level of genus.

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Correlation of fungi with environmental factors
Similar to the analysis method of environmental factors of bacteria, the correlation between the fungi in tobaccos and environmental factors is displayed in Fig. 12. Temperature and humidity were mainly controlled in the flue-curing process of tobacco leaves; the main environmental factors were dry- and wet-bulb temperatures. As shown in the figure, different from the correlation of bacterial communities in tobaccos with environmental factors, the majority of fungal genera in tobaccos presented a negative correlation with temperature and humidity, for example, Rachicladosporium, Vishniacozyma, Symmetrospora, Sarocladium, Ascochyta, Wallemia, Colletotrichum, Fusarium, Claviceps, Cladosporium, etc. A small number of fungal genera (such as Ustilaginoidea, Septoriella and Alternaria) were positively correlated with temperature and humidity.
Figure 12

Heat map of correlation with environmental factors at the level of genus.

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Function prediction of bacterial communities in tobaccos
According to the annotation result in the database, the functions with the maximum abundance ranking the top 10 in each sample or group at various layers of annotations were selected to generate the cumulative histogram of relative abundances of functions. Thus, it is convenient to check the functions with a high relative abundance in various samples at different layers of annotations and their proportions.
As shown in Fig. 13, bacterial communities with a half of relative abundances participated in the metabolism and a quarter of bacterial communities took part in the genetic information processing; the rest was engaged in the cellular processes and organismal systems and some bacterial communities were implicated to human diseases.
Figure 13

Relative abundances of function annotations of bacterial communities in tobaccos.

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Function prediction of fungal communities in tobaccos
Based on amplificon analysis of 16S or ITS, the species classification and abundances of fungi present in the environment can be attained. In many cases, people will also concern what role these species found in the environment play in the ecological environment. By applying FunGuild tool, it is feasible to attain the ecological functions of corresponding fungi based on the species classification of fungi. It can be seen from the Fig. 14 that the fungal communities in tobaccos delivered relatively abundant functions, in which the three fungal communities with the highest relative abundances separately showed the following functions: plant saprophytes, plant pathogens and undefined functional fungal communities; the rest of fungal communities participated in plant parasitism,soil-borne plant pathogen, lichenization, dung saprotroph, etc.
Figure 14

Relative abundances of function annotations of fungal communities in tobaccos.

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All procedures were approved by the Animal and Environment Ethics Committees of the University of São Paulo, College of Agriculture “Luiz de Queiroz” (USP/ESALQ). All applicable international, national, and/or institutional guidelines for the care and use of animals were followed.
Experimental site
Two experiments were carried out at Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, SP, Brazil (22° 42′ S, 47° 38′ W and 546 a.s.l.), during the summer 2017 (January to March). Napier elephant grass (Pennisetum purpureum Schum. cv. Napier) was used as model plant because of its large size, ease of vegetative propagation and the nature of the study. The soil was a high fertility Eutric Kandiudalf with the following chemical characteristics for the 0–20 cm layer: Experiment 1—pH CaCl2 = 5.9; OM = 46.0 g dm−3; P (ion-exchange resin extraction method) = 257.0 mg dm−3; Ca = 148.1 mmolc dm−3, Mg = 80.0 mmolc dm−3; K = 9.1 mmolc dm−3; H + Al = 15.0 mmolc dm−3; sum of bases = 237.1 mmolc dm−3; cation exchange capacity = 252.1 mmolc dm−3; base saturation = 94%; Experiment 2—pH CaCl2 = 5.8; OM = 39.3 g dm−3; P (ion-exchange resin extraction method) = 54.0 mg dm−3; Ca = 62.0 mmolc dm−3, Mg = 22.3 mmolc dm−3; K = 8.6 mmolc dm−3; H + Al = 29.0 mmolc dm−3; sum of bases = 93.1 mmolc dm−3; cation exchange capacity = 122.0 mmolc dm−3; base saturation = 76%. These were considered adequate for the forage species used, with no need for additional fertilisation.
The climate, according to Köppen classification, is Cfa, humid subtropical climate with wet summer40 and an average annual rainfall of 1,328 mm. The average air temperature during the experimental period was 24.2 °C and total precipitation 753.85 mm, from which 424.4 mm corresponded to total precipitation for Experiment 1 (Dec 27, 2016 to Feb 21, 2017) and 502.14.5 mm for Experiment 2 (Dec 09, 2016 to Mar 14, 2017). The greatest precipitation was recorded in January 2017 (336.55 mm).
To avoid soil water deficits, a drip irrigation system was installed in the area used for Experiment 1 and a sprinkler irrigation system was available in the area for Experiment 2. Irrigation in both areas was carried out according to records of precipitation, average air temperature and evapotranspiration. On rainy days, precipitation was recorded and taken into account in calculations for irrigation as a means of ensuring that plants were not submitted to either deficit or excessive soil moisture.
Experiment 1 (leaf morphology and anatomy): establishment and experimental control
Preparation of the experimental area (290 m2) started with the desiccation of previous vegetation (Cynodon dactylon (L.) Pers.) using the broad-spectrum herbicides Glyphosate (N-phosphonomethyl-glycine) and 2.4-D (2.4-Dichlorophenoxyacetic acid) in Sept 09 and Nov 15, 2016, and Paraquat (1.1′-dimethyl-4.4′-bipyridinium dichloride) in Dec 11, 16 days before planting on Dec 27, 2016.
One day before planting of the experimental area (290 m2), planting pits were opened and the desiccated vegetation around them removed. Planting material (stem cuttings with viable lateral buds) was harvested at an 850 m2 pasture of well-established Napier elephant grass41. Stems were fractioned in one-node pieces (one single axillary bud) discarding the basal and the apical portions of the stems to ensure vigorous sprouting from the planting material. Ten buds were placed in each pit at 5 cm depth, covered with soil and gently compressed by hand. The distance between pits in lines was 1.5 m and between planting lines was 2 m, in order to obtain the desired spaced-plant layout. Two weeks after planting, plants were thinned leaving one plant per pit.
Treatments corresponded to phytomer order along the tiller axis and the experimental design was a randomised complete block, with four replications. Plants within blocks were randomised using the statistical package SAS (Statistical Analysis System, v. 9.0).
Weed control during the experiment was carried out manually. Pest (Mocis sp.) and disease (Bipolaris sp.) control was carried out using the water-soluble insecticide Resolva (Lambda-Cyhalothrin) in Jan 07 and 22, 2017 (5 g L−1) and the fungicide Nativo (Trifloxistrobina + Tebuconazol) in Feb 05, 2017 (0.6 L ha−1), respectively.
Sampling followed the ontogenetic programme of plants, beginning with tiller 1, which corresponded to the anatomical evaluation of the 8th leaf (phytomer 8); tiller 2, which corresponded to the anatomical evaluation of the 9th leaf (phytomer 9) and the morphological evaluation of the 8th leaf; tiller 3, which corresponded to the anatomical evaluation of the 10th leaf (phytomer 10) and the morphological evaluation of the 9th leaf in this sequence until full expansion of the 16th leaf (phytomer 16) for morphological evaluation (tiller 10), totalling 40 tillers (4 tillers for anatomical characterisation of the 8th expanded leaf + 32 tillers for anatomical (9th to 16th leaf) and morphological (8th to 15th expanded leaf) evaluations + 4 tillers for morphological characterisation of the 16th expanded leaf). At each harvest, leaves were carefully removed from the tillers, identified and preserved with ice until processing in the laboratory. Sampled tillers were removed from the experimental area. In order to evaluate the effect of leaf age on the deposition of support tissues, all leaves from 8 tillers (4 for anatomical evaluations (tiller 11) and 4 for morphological evaluations (tiller 12)) were collected at a single harvest when the 16th leaf completed expansion following the same procedure described for each leaf separately. Twenty additional plants were grown (five per block) to ensure that all leaves would be harvested as planned, but they were not necessary.
Leaf anatomy
In the laboratory, the leaf blade was cut at the ligule, its length was measured (distance between the tip of the leaf and the ligule) and fractionated in five segments of similar length designated as: (1) basal—closest portion to the insertion on the tiller; (2) mid-basal—middle portion closest to the basal; (3) middle—middle portion of the blade; (4) mid-apical—middle portion closest to the apical; (5) apical—portion closest to the tip of the leaf. Each of the five segments were fragmented in 1-cm cuts and stored according to methodology described by Johansen42. Sample dehydration was carried out using a progressive alcoholic series with tertiary butyl alcohol43, and fragments infiltrated with paraffin and subsequently with paraplast. In sequence, fragments were sectioned (12-µm width) with a Leica Biosystems manual rotary microtome, followed by a triarch quadruple staining of tissues before permanent blade mounting, following the methodology proposed by Hagquist44. Images were captured using the AxioVision Program (V2.05, Carl Zeiss Vision) attached to a Zeiss Axioskop 2 binocular optical microscope and a Zeiss AxioCam MRc (1.388 × 1.040 pixels) digital camera. Images were captured using 20× objective lens from the first large vascular bundle after the central rib as a means of standardising readings. Estimates of the percentage of each anatomical tissue on the samples were made using the AxioVision software (AxioVs40, release 4.8.2.0, Carl Zeiss Micro Imaging GmbH, Germany). Initially, the whole cross-section area projected on the video was measured (STotal). Next in the measurement sequence were the areas of adaxial (EPIada) and abaxial (EPIaba) epidermis, parenchymatic sheath of vascular bundles (PSV), vascular tissue (VT—including xylem, phloem, mestome sheath and pericyclic fibers27) and sclerenchyma (SCL). The mesophyll area was calculated as the difference between STotal and that of all the other tissues, therefore including airspace. Measurements were made in µm2 and the results expressed as percentage of total area.
Leaf morphology
For the morphology measurements the leaf was cut at the ligule, its length was measured (distance between the tip of the leaf and the ligule) and fractionated in ten segments of similar length. At the mid portion of each segment the fragment width (distance between the opposite borders) was measured in millimetres. In the sequence, the central rib from each segment was removed using a scalpel and its width and length were also measured. The fragment parts (central rib and blade tissue) were passed through a LAI-3100 leaf area integrating device (LI-COR) and put to dry in a forced draught oven at 55 °C until constant weight. The results were used to calculated whole segment mass (mg) and specific leaf area (SLA—cm2.mg−1).
Experiment 2 (nutritive value): establishment and experimental control
Preparation of the experimental area (3,000 m2) started with the desiccation of previous vegetation (Arachis pintoi cv. Belmonte) using the broad-spectrum herbicides Glyphosate (N-phosphonomethyl-glycine) and 2.4-D (2.4-Dichlorophenoxyacetic acid) in Sept 08, Oct 01 and Nov 15, 2016. On Nov 30 the whole area was mowed and a final application of Paraquat (1.1′-dimethyl-4.4′-bipyridinium dichloride) was carried out in Dec 06 (blocks 2 and 3) and Dec 11, 2016 (block 1). The next steps followed the same protocol used in Experiment 1. Six buds were placed in each pit at 5 cm depth, covered with soil and gently compressed by hand. The distance between pits in lines and between lines was 1.0 m (Fig. 8).
Figure 8

General view of the experimental site during the establishment phase showing the layout and distribution of elephant grass plants on the area: (a) Pit opening and (b) planting of the stem cuttings.

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A total of 1,320 plants were cultivated. These were divided in three homogeneous blocks with 440 plants each. The number of plants per block was dimensioned to provide the necessary amount of dried and ground samples for the nutritive value analysis. Twenty days after planting, plants were thinned leaving one plant per pit.
Treatments corresponded to phytomer order along the tiller axis and the experimental design was a randomised complete block, with three replications. Plants within blocks were randomised using the statistical package SAS (Statistical Analysis System, v. 9.0). Weed, pest and disease control was the same as for Experiment 1.
Sampling was carried out when the 16th leaf (phytomer 16) complete its expansion and exposed the ligule. Main tillers had all their leaves identified with permanent marker before harvest. The leaves were stored in ice and taken to the laboratory. Processing involved removal of the sheaths and blades stored in freezer for future segmentation. Leaves 5, 6 and 7 were discarded because they were in advanced stage of senescence and decay, leaving leaves 8 to 16 for the analysis.
Nutritive value
After all field work was finished, leaf blades had their length measured (distance between the tip of the leaf and the ligule) and were fractionated in five segments of similar length, as described for leaf anatomy measurements in Experiment 1 (i.e. chemical analyses included all tissues of the leaf blade). These were pooled into a composite sample per leaf hierarchical order, totalling 135 samples (9 leaves × 5 segments × 3 blocks). These were put to dry into forced draught oven at 55 °C until constant weight.
After drying, because the apical portion of the leaves was too delicate, the dried material was ground in a micro mill with a 1 mm sieve (Wiley Mill, Thomas Scientific, Philadelphia, PA, USA) as a means of reducing dry matter losses. Ground samples were subjected to the following chemical analysis: in vtiro dry matter digestibility (IVDMD), using the artificial rumen fermentation device DAISYII from ANKOM Technology Corporation45; total nitrogen (Ntotal), determined by the Dumas combustion method using the Leco FP 528 System (Leco Instruments Inc., St. Joseph, MI, USA); and ashes (ASH) determined according to Silva & Queiroz46. Crude protein (CP) was calculated as Ntotal × 6.25. For the in vitro trial, rumen liquid was collected from one rumen-cannulated Nellore steer fed only with Tifton-85 (Cynodon dactylon spp.) haylage.
Statistical analysis
Leaf blade morphology and anatomy data were initially analysed using descriptive statistical analysis (means and standard error of the mean). Leaf blade total mass and central rib total mass were obtained by adding values for all ten segments from each leaf and were subjected to a regression analysis as a means of identifying the correlation between these two variables. Regression was performed using the procedure PROC REG of SAS (Statistical Analysis System, v. 9.0).
Nutritive value data were subjected to ANOVA using the procedure PROC GLM of SAS (Statistical Analysis System, v. 9.0), and means compared by Tukey test (P  More

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