Ecology

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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Nicholas School of the Environment, Duke University, Durham, NC, USA
James S. Clark, Christopher L. Kilner, Jordan Luongo, Renata Poulton-Kamakura, Ethan Ready, Chantal D. Reid, C. Lane Scher, William H. Schlesinger, Shubhi Sharma, Samantha Sutton, Jennifer J. Swenson & Margaret Swift

INRAE, LESSEM, University Grenoble Alpes, Saint-Martin-d’Heres, France
James S. Clark, Benoit Courbaud, Georges Kunstler, Kyle C. Rodman & Thomas T. Veblen

Department of Geography, University of Colorado Boulder, Boulder, CO, USA
Robert Andrus & Emily Moran

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Melaine Aubry-Kientz

Forest Research Institute, University of Quebec in Abitibi-Temiscamingue, Rouyn-Noranda, QC, Canada
Yves Bergeron

Department of Systematic Zoology, Faculty of Biology, Adam Mickiewicz University, Poznan, Poland
Michal Bogdziewicz

USDA Forest Service, Southern Research Station, Monticello, AR, USA
Don C. Bragg

USDA Forest Service Southern Research Station, Auburn, AL, USA
Dale Brockway & Timothy J. Fahey

Natural Resources, Cornell University, Ithaca, NY, USA
Natalie L. Cleavitt

Institute for the Environment, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Susan Cohen

Greater Yellowstone Network, National Park Service, Bozeman, MT, USA
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USGS Western Ecological Research Center, Three Rivers, CA, USA
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Earth and Environment, Boston University, Boston, MA, USA
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Finnish Meteorological Institute, Helsinki, Finland
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Forest Resources, University of Washington, Seattle, WA, USA
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Department of Biological Science, Northern Arizona University, Flagstaff, AZ, USA
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University of California, Santa Cruz, Santa Cruz, CA, USA
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USDA Forest Service, Bent Creek Experimental Forest, Asheville, NC, USA
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USDA Forest Service Southern Research Station, Eastern Forest Environmental Threat Assessment Center, Research Triangle Park, NC, USA
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Department of Biology, University of Washington, Seattle, WA, USA
Janneke HilleRisLambers

School for Environment and Sustainability, University of Michigan, Ann Arbor, MI, USA
Ines Ibanez

Department of Biology, University of Saskatchewan, Saskatoon, SK, Canada
Jill Johnstone

Health and Environmental Sciences Department, Xian Jiaotong-Liverpool University, Suzhou, China
Johannes Knops

Hastings Reservation, University of California Berkeley, Carmel Valley, CA, USA
Walter D. Koenig

Department of Biological Sciences, DePaul University, Chicago, IL, USA
Jalene M. LaMontagne

Department of Wildland Resources, Utah State University Ecology Center, Logan, UT, USA
James A. Lutz

Department of Biology, University of New Mexico, Albuquerque, NM, USA
Diana Macias

Pacific Forestry Centre, Victoria, BC, Canada
Eliot J. B. McIntire

Université du Québec en Abitibi-Témiscamingue, Rouyn-Noranda, Quebec, Canada
Yassine Messaoud

Department of Biology, Colby College, Waterville, ME, USA
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Department of Biology, Washington University in St. Louis, St. Louis, MO, USA
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University of New Mexico, Albuquerque, NM, USA
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Fort Collins Science Center, Fort Collins, CO, USA
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