Ecology

Morphology and light-emitting behavior of the undescribed Japanese Terebellidae wormIn 2016, some of the present authors were exploring shallow coastal waters (depth less than 1 m) to observe the ecological behaviors of marine animals in the Noto Peninsula, when they discovered unknown violet-light-emitting worms. At the sampling point, the worms were living in small holes (a few centimeters in diameter) or in cracks in rocks covered by sand at the shallow sea bottom (Supplementary Fig. S1). We successfully video-recorded their emission of violet light from the whole tentacle stretching into sea water when stimulated by air bubbling at night (Fig. 1A–C; Supplementary Videos S1 and S2). The violet-light emission consisted of rapid flashes with variable duration in the order of milliseconds (Supplementary Video S3), as observed for the worm P. perplexus in response to stimulation17. From our morphological observation, we identified the violet-light-emitting worm as a member of Polycirrus on the basis of the following characteristics18: (1) a sheetlike prostomium covering the upper lip; (2) avicular unicini on some neuropodia; (3) no branchiae. The specimens also have the following characteristics: (1) neurochaetae beginning on last notochaetigerous segment, chaetiger 14; (2) uncini with a long neck and concave base; (3) notopodial pre- and post-chaetal lobes both similar shape. These characters are also found in Polycirrus disjunctus Hutchings and Glasby18; however some of the characters in parapodial lobes and chaetae have differentiation. Thus, we concluded that this species should be treated as an undescribed species. Further comparative observation is needed to describe the species. At this time we treated the Polycirrus species observed in this study as Polycirrus sp. ISK. Application of an electric pulse also caused clear light emission from the tentacles of the living worm (Fig. 1D; Supplementary Video S3), and the luminescence spectrum showed that its λmax was 444 nm or slightly longer, depending on the individual (Fig. 2A). We also found that light emission was efficiently induced by the addition of KCl solution and observed the time course of light emission with rapid fluctuations with variable duration in the order of milliseconds for up to 30 s (Fig. 2B). The flash pattern was similar to that observed in a study of P. perplexus17. In the genus Polycirrus, P. medius and P. nervosus in Japan have been described18,19. However, the morphological features of the species in the present study differed from these species on the basis of our observations described above.Figure 1Photographs of Polycirrus sp. ISK. (A) Polycirrus sp. ISK in its natural habitat with bright-field illumination. (B) Bioluminescence of Polycirrus sp. ISK in its natural habitat without bright-field illumination. The worms were stimulated by air bubbling from SCUBA gear. (C) A single worm with stretched tentacles. Tentacles are indicated by white arrows. (D) The worm with light emission at the tentacles. This worm was stimulated by an electric shock. Scale bars = 100 mm for A and B, 10 mm for C and D. Each photograph was extracted from the videos recorded with the following settings: sensitivity, ISO 51200 or 11 lx; white balance, 4300 K or 5800 K; shutter speed, 1/30 s or 1/60 s; iris, F1.8-3.5; frame rate, 29.97 fps or 60 i; frame size, 1920 × 1080 pixels. Original high quality videos are available at https://youtu.be/KEsU0kWAEfg and https://youtu.be/24dxvPlBDB0Full size imageFigure 2Luminescence spectra and KCl-induced light emission of Polycirrus sp. ISK. (A) Spectrum analysis of Polycirrus sp. ISK using a living worm stimulated by an electric shock. The luminescence spectra were obtained from two different individuals. The λmax represented in closed circles and open circles were 444 nm and 446 nm, respectively. (B) Typical light-emission signal of a living worm soaked in 667 mM KCl. The black line indicates luminescence intensity after adding KCl solution, and the gray line indicates luminescence intensity before adding KCl solution.Full size imageJapanese Polycirrus spp. have not been described as luminous worms according to our review of the literature and web pages. In addition, the number of reports for new Polycirrus spp. from all over the world has been increasing, but a limited number of species are known to emit light13,17,18. Our finding of KCl-induced light emission from Polycirrus sp. ISK suggested that we can easily test the light-emitting ability of Polycirrus spp. by luminescence measurement just after adding KCl solution. A spectrum pattern has been reported for only one species, P. perplexus collected in California17, and it would be necessary for further understanding of these species to examine the light-emitting abilities and to compare light-emitting behaviors and spectrum patterns. The color of bioluminescence is often related to habitat, and light in the blue range is typical for pelagic species20. Thus, one of the points to be focused on is the ecological function of the violet-light emission of this worm inhabiting in a shallow coastal water environment. In P. perplexus, deterring predation is a possible function of luminescence based on that species’ habitat and its violet-light emission17,21. As shown in Supplementary Videos S1, S2, which are the first video records of in situ light emission of a Polycirrus species, the air bubble-stimulated luminescence of Polycirrus sp. ISK in its natural habitat also seemed to deter predation, but this explanation is still speculative.Differentially expressing genes between the tentacles and the rest of bodyA few years after discovering this worm, we found it difficult to collect enough of them to conduct common biochemical and chemical analyses because we did not find a place densely inhabited by hundreds of the worms whose wet weight was a few tens of milligrams (e.g. 16.5, 29.8, or 31.8 mg). Next, we conducted RNA-Seq analysis. In luminous animals with strong light emission, such as firefly or syllid polychaetes (Syllidae), luciferase expression is high especially at the luminous organ or in the whole body22,23. On the other hand, the light emission of Polycirrus sp. ISK was not so strong compared to that of fireflies, and the light-emitting area was limited to the tentacles. In addition, the genetic information related to the tentacles responsible for various ecological functions is still limited. Thus, in the present study we decided to purify RNA from the tentacles and the rest of body separately (Fig. 1C) and performed RNA-Seq analysis followed by a computational analysis using the MASER pipeline24. By de novo assembly, 110,775 contigs were predicted; 26.1% of them showed more than twice the expression level in the tentacles than in the rest of body, whereas 20.8% showed more than twice the expression in the rest of body than in the tentacles. When we performed a blastX search to the NCBI nr database for the contigs longer than 300 bp, 35.6% showed significant homology with registered genes with e-values of less than 1e−10. The average length for these contigs was 1384 bp, and half of them were in the range of 463–1863 bp (Supplementary Fig. S2). In the assembled sequence, we found the cytochrome oxidase subunit I (COI) gene and tried to construct a phylogenetic tree. However, the obtained phylogenetic tree was unreliable due to the low bootstrap values as shown in Supplementary Fig. S3.To focus on the tissue-specific genes, we first picked up genes with high expression levels based on high fpkm values (over 1000) and then ranked these genes based on the tissue-specificity judged by the comparison of fpkm values in tentacles and the rest of body. In tentacle-specific genes, we found that some genes coding for lectin(-like) domains were ranked in the top eight as shown in Supplementary Table S1. Of the top eight genes in the rest of body-specific genes (Supplementary Table S2), seven exhibited no similarity to any genes, and the remaining gene exhibited significant similarity to a hypothetical protein of Capitella teleta, which is a Polychaetes species with whole-genome information available25. Recently, TPM is preferably used to normalize expression level, and the value is used for statistical differential expression analysis26, and we also calculated TPM for tissue-specific genes (Supplementary Table S3).As we were unable to conduct statistical differential expression analysis due to no biological/technical replication resulted from difficulties in the sample collection, we simply compared TPM value between the tentacle and the rest of body samples. The ratio of TPM (tentacle/rest of body) was calculated, and then top 100 genes (Fig. 3A), which were highly expressing in the tentacle, were selected. Similarly, top 100 genes highly expressing in the rest of body were selected using the ratio of TPM (rest of body/tentacle) (Fig. 3B). These gene lists were annotated by gene ontology (GO) terms and analyzed using WEGO program27. WEGO results showed different expression patterns for the tentacle and the rest of body. In the tentacle, GO terms including cell adhesion, biological adhesion, small molecular binding, positive regulation of biological process, regulation of response to stimulus, carbohydrate binding, and immune response were significantly higher (Fig. 3C, D). In the rest of body, GO terms including hydrolase activity, catalytic activity, localization, and establishment of localization were significantly higher. In the top 100 genes highly expressing in the tentacle, we found 21 genes annotated as a gene coding for fucolectin by blast search (Supplementary Table S4). Fucolectin is a fucose-binding lectin involved in the innate immunity of diverse invertebrate species28. However, its function in invertebrates remains unclear, and no information is available for Terebellidae, including sequence information. Fucolectin was first identified in eel with mRNA distribution mainly in liver and gill28. In sea cucumber, expression of the fucolectin gene is confirmed in respiratory trees, muscle, and tentacle29. We were not able to see whether this gene was expressed in the respiratory organ of Polycirrus sp. ISK because a characteristic of the genus Polycirrus is the absence of branchiae18. Nevertheless, the tentacle-specific expression of fucolectin was consistent with the observation in sea cucumber, and the high expression of such proteins involved in innate immunity seemed reasonable because tentacles stretching out of their bodies can be damaged by attack of predators and thus are threatened by infectious bacteria and other pathogens11, as is the respiratory organ. In addition, localization of antimicrobial compounds in Terebellidae worms is suggested to be of antiseptic importance in damage by predation14. This study would provide indispensable information about the ecological meaning of Polycirrus sp. ISK’s life in future genetic studies.Figure 3WEGO analysis of highly expressing genes in the tentacle and the rest of body. (A) Box plot graph for the distribution of TPM value for top 100 genes highly expressing in the tentacle. Corresponding genes in each part are colored in the same gradation color according to the TPM value (red to blue form higher to lower value). (B) Box plot graph for the distribution of TPM value for top 100 genes highly expressing in the rest of body. Each gene is colored as in (A). (C) WEGO analysis of top 100 genes highly expressing in the tentacle (orange bar) and the rest of the body (blue bar). (D) P-values from Chi-square tests obtained by WEGO analysis. CC cellular component, MF molecular function, BP biological process.Full size imageTranscripts coding for luciferase-like genes in the wormTo find genes similar to the known luciferase, which is an enzyme oxidizing a specific compound called luciferin to emit light, from related species in polychaetes, we performed a blastX analysis against the Odontosyllis luciferase sequence using our RNA-Seq data. We found a gene coding for a protein that exhibited similarity to Odontosyllis luciferase, but the e-value was more than 1e−10 (Supplementary Fig. S4). In addition, the top hit for this gene analyzed by blastX was annotated to code an uncharacterized protein of Saccoglossus kowalevskii (Hemichordata), and its specific function was not predicted. Other hits were for genes from Chordata, Mollusca, and other phyla but there was no hit from Annelida. This result would suggest that the light-emission system of Polycirrus sp. ISK differs from that of the genus Odontosyllis, although further experiments using high purity Odontosyllis luciferase and the substrate will be necessary to confirm this. In further blastX analyses of representative luciferases, photoproteins, and a putative luciferase [luciferases from the ostracod Cypridina noctiluca (Accession number: BAD08210.1), the copepod Gaussia princeps (AAG54095.1), the deep-sea shrimp Oplophorus gracilirostris (BAB13775.1 and BAB13776.1), the firefly Photinus pyralis (AAA29795.1), the sea pansy Renilla reniformis (AAA29804.1); photoproteins from the hydrozoan jellyfish Aequorea victoria (AAA27720.1), the hydroid Clytia gregaria (CAA49754.1), the hydroid Obelia geniculate (AAL86372.1); a putative luciferase from the tunicate Pyrosoma atlanticum30 sequences using our RNA-Seq data], we found some tissue-nonspecific genes whose sequences exhibited similarity to firefly luciferase (FLuc) or Renilla luciferase-like protein (RLuc-like) sequences with an e-values of less than 1e−10 and percent identity of more than 50%. FLuc is a member of the acyl-adenylate-forming superfamily of enzymes responsible for firefly luciferin-dependent bioluminescence, which is found in terrestrial luminous beetles emitting light ranging from green to red31. Previously, a putative acyl-CoA synthetase protein was found in the luminous organ of firefly squid emitting blue light32, but there is no clear biochemical evidence that such protein is responsible for firefly squid’s bioluminescence. On the other hand, RLuc is responsible for coelenterazine-dependent bioluminescence, which is found in marine luminous organisms belonging to various taxa. An RLuc-like protein is found to be localized in luminous organs of the brittle star Amphiura filiformis, as revealed by taking advantage of the cross reactivity of anti-RLuc antibody to A. filiformis RLuc-like protein33. A recent study reported that recombinant RLuc-like protein found in P. atlanticum exhibited luciferase activity to coelenterazine30. However, an RLuc-like protein from sea urchin Strongylocentroutus purpuratus is confirmed to exhibit dehalogenase activity to various substrates but no luciferase activity to coelenterazine34. Therefore, it is suspected that Polycirrus sp. ISK possesses a luminescence system using an RLuc-like enzyme.Coelenterazine content in the wormTo investigate whether Polycirrus sp. ISK possesses not only a Renilla luciferase homologous gene but also coelenterazine, we analyzed an ethanolic extract of Polycirrus sp. ISK by UPLC with a UV–visible detector (Fig. 4). The obtained UPLC chromatogram did not show a peak corresponding to that of authentic coelenterazine. When further checking the chromatogram, we found the peak at a retention time similar to those of authentic coelenteramide and coelenteramine, which can be formed from coelenterazine. However, the absorption spectrum obtained by UPLC analysis and the mass spectrum obtained by MS/MS analysis were not identical to those of authentic coelenteramide or coelenteramine (Fig. 4 and Supplementary Figs. S5 and S6). In addition, when the worm extract was mixed with a recombinant RLuc, we did not detect luminescence using a luminometer. These results suggested that the luminescence system in the worm was independent of coelenterazine, although a RLuc homologous gene was found. Similarly, the existence of an RLuc homologous gene was reported in P. atlanticum, which has been suggested to use a coelenterazine-independent luminescence system relying on bacterial bioluminescent symbionts30,35. We also mixed the worm extract with a recombinant cypridinid luciferase, but we did not detect luminescence using a luminometer. This result was consistent with Harvey’s observation for P. caliendrum16. To examine whether the luminescence system is based on luciferin–luciferase reaction, which is found in various luminous animals including some syllid Odontosyllis spp.23,36,37,38,39, we prepared two different extracts of the worm using 100 mM HEPES–NaOH buffer (pH 7.4) and methanol, and subsequently subjected a mixture of the two to luminescent measurement. As a result, no light emission was detected from the mixture of the buffer and methanolic extracts of the worm. This result was also consistent with Harvey’s observation for P. caliendrum16. However, there is still a possibility that the light emission is based on luciferin–luciferase reaction, because luciferin–luciferase reaction found in fireflies or luminous mushrooms requires a cofactor such as ATP or NADPH, and we did not test all possible conditions due to the limitation of the number of collected specimens. In addition, extraction of luciferin and luciferase in the active form is sometimes difficult, as shown in previous studies37. Further studies using hundreds or more of the specimens must be performed to elucidate the mechanism underlying the violet-light emission.Figure 4Comparison of the ethanolic extract of Polycirrus sp. ISK with CTZ, CTMD, and CTM. (A) UPLC analysis of (a) the extract, (b) authentic CTZ, (c) authentic CTMD, and (d) authentic CTM using a multiwavelength detector. The black solid line indicates detection at 333 nm, and the blue solid line indicates detection at 435 nm. The compound between the red vertical dashed lines was collected for MS/MS analysis. (B) Absorption spectra of the compound from the extract, CTZ, CTMD, and CTM obtained at retention times of (a) 9.65, (b) 10.89, (c) 9.47, and (d) 9.27 shown in (A). CTZ coelenterazine, CTMD coelenteramide, CTM coelenteramine. These chemical structures are shown in Supplementary Fig. S5.Full size image More

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Water useMany potato physiological features (photosynthesis intensity, leaf water potential) morphological and agronomic features as the Soil Plant Analysis Development (SPAD) and dry matter content can be used as indicators of potato water stress. In this result water consumption and the average daily amount of water used for irrigation differed over the growing season, but differences also occurred between varieties and the humidity level (Table 1). When irrigating the Julinka variety at all stages of the growing season, regardless of the established pF values, water consumption per pot was higher. The average dose of water supplied per pot was 9.7%, 30.7% and 26.6% greater than for the Denar variety, at humidity levels 1, 2 and 3, respectively. The highest water consumption was observed during the potato growth period from BBCH 40/400 to 69/609 and ranged from 0.39 l/pot /day (level 1) to 0.99 l/ pot/day (level 3).Table 1 Water consumption per pot within potato growing stages (in liters) and average consumption of water per pot (in brackets).Full size tableThe highest water consumption in both potato varieties occurred in July (11–18 July). Analyzing the remaining two months of the irrigation period, it can be seen that in June the plants used less water than in July. Seasonal irrigation doses in mid-early potato of studies of Rolbiecki et al. (2015)9 ranged from 40 to 170 mm, and the highest daily values of field water consumption (over 3 mm) occurred in July, similar to the results in this research.Depending on the irrigation system, water consumption efficiency in potato varies from 5.4 to 12 kg m−316,24. Drip irrigation is one of the most effective methods and ranged from 6.3 to 8.6 kg m−3 (Sharma 2007)25. Different values for average WUE index’ in potato cultivation were obtained by Ati et al. (2012)26, and indicated value ranged from 5.9 to 12.2 kg m−3. In present research, average WUE index’ for the Denar variety was from 0.00 l day−1 in the 1st period to 0.79 l day−1 in the 5th harvest period, while for the Julinka it was from 0.49 to 0.92 l day−1, respectively.In the research by Zin El Abedin et al. (2019)27 the amount of water used for irrigating potato amounted to 1505 mm and 1062 mm for FI (full irrigation) and PRD (partial root zone drying) variants, respectively. The use of 50% of water consumption in the PRD reduced water productivity (WP), as compared to water stress in the form of excess FI and deficit irrigation (DI). A large amount of water in conditions of water deficit causes losses due to evaporation and leads to degradation of the soil environment. In turn, in this research the highest water consumption in both varieties was found at level 3, 39.60 l for the Denar variety and 50.15 l for the Julinka variety.Pszczółkowski et al. (2009)28 showed that early potato varieties water requirements in the period from May 1 to August 31 amounted to 336.4 mm, with greatest requirements in July (108—119.6 mm). In our research, the amount of water used depended on the assumed humidity level and amounted from 19.60 × 103 to 39.60 × 103 cm3 for the Denar variety and between 21.50×103 to 50.15 × 103 cm3 for the Julinka (Table 1).Total potato and tuber massThe total weight of plants aboveground—(stems with leaves) and underground (tubers, stolons and roots) was greater in water humidity level 1 than in humidity levels 2 and 3 (Table 2). Administration of increased amounts of water in the later stages of potato growth resulted in inhibition of biomass growth, mainly for the Julinka variety. At the 5th harvest time, at humidity level 3, the total weight and the weight of tubers were 59.2% and 54.7% lower than those obtained at level 1, respectively. At the same time, the difference for Denar was 11.9% and 18.8%, respectively. Begum et al. (2015, 2018)16,22 and Reyes-Cabrera et al. (2016)5 showed that the production of total and commercial tuber yield was strongly dependent on the total biomass production and its structure.Table 2 Potato total biomass and tuber increase depending on water humidity level (g per plant).Full size tableA three-factor analysis of variance showed that the total weight as well as the weight of potato tubers differed significantly by the humidity level and the variety. A significant effect was found for humidity level on the total weight and tuber weight for the Denar variety and tuber weight for the Julinka variety (Table 3).Table 3 Variance analysis for total biomass and tuber of potato depending on factors (significance verified by the Fisher test).Full size tableAnalysis of variance showed a significant impact of the variety on potato plant weight, while it did not show significant interaction of weight and weight of tubers between measurement dates. No significant effect was obtained for interaction between the factors studied (Table 3).Wang et al. (2009)29, concluded that the use of irrigation significantly contributed to an increase total and commercial tubers of medium-early Folva variety yield and its quality. Ossowski et al. (2013)30, shown that irrigation had a significant effect on medium-early potato varieties: Barycz, Mors, Triada tuber yield. When using drip irrigation, yield increased by 26%. In turn, Mazurczyk et al. (2007)31 showed that drip irrigation increased the tuber yield from 29.4–37.5 to 45.1–54.4 t·ha−1.Over the period from the 1st to the 5th harvest date, the total plant biomass increased from 3.5-fold (Julinka—level 3) to 7.2-fold (Julinka—level 1). On the first harvest, Denar did not produce tubers at levels 1 and 3, and for level 2 its weight was the lowest (6 g from a pot). The increase in tuber weight to the last harvest date was the highest for level 2: 23.9- and 22.9-fold, in Denar and Julinka varieties, respectively. At level 3, the growth dynamics of tubers was the lowest: 11.7 times for the Julinka and 9.1 times for the Denar variety (measured from the second harvest date). The highest total biomass increases and tuber weight was found between the 3rd, 4th and 5th dates when humidity was at levels 1 and 2, and between the 3rd and 4th dates at level 3.Kumari et al. (2011, 2018)1,2 concluded that drip irrigation significantly contributed to an increase in potato tuber yield 18% greater than with other irrigation methods. Xu et al. (2010)32 achieved higher yields using the same irrigation system (40–48 t ha−1), and potato tuber weight was reduced under the slight water stress. Potato reacts to stress when soil water tension exceeds 20 kPa24. In a study by Amer et al. (2016)33 potato tuber yield also decreased with the application of excessive irrigation, resulting in greater stress, increased vegetative growth and potential leaching of nutrients from the root zone.Changes also occur in the quality of potato tubers, such as the shape, skin smoothness and chemical composition34.In the research carried out by Zin El-Abedin et al. (2019)27 differences were found in potato tuber yield depending on the irrigation variant. At FI, the highest tuber yields of 31.77–35.91 Mg ha−1 were obtained. Water deficiency reduced tuber yield, in DI variants, by 53.24–65.15% as compared to the FI. Similar results were obtained by Kumari et al. (2011)1. In the present research, the tuber weight of the Denar variety in the fifth term in level 1, increased by 26% compared to the irrigation at level 2 and was a 24% increase for the Julinka variety under similar conditions. At humidity level 3 there was a decrease in total biomass by 12% and 59% (for Denar and Julinka, respectively) in comparison obtained at level 1. In the research Liu et al. (2006)35 the aboveground biomass reached the highest values in excess water conditions.Potato varieties react differently to the humidity of the soil. Mahmood et al. (2016)36 response of potato varieties diversity to soil water deficit, also Hassanapanah (2010)17 showed the reaction of potato varieties to stress conditions. In our study, a higher total and tubers weight was found for the Julinka variety than for the Denar variety.Regardless of the humidity level and variety, the trends in the biomass yield structure were similar (Fig. 3). A downward trend from the 1st to 5th harvest period was shown for roots and stolons. This varied from 5 to 18% at the beginning of the study to 2–5% by the 5th period. It should be noted that under level 3, especially for the Denar variety, the percentage of roots and stolons was at a constant, low level. The percentage of stems with leaves decreased from 68–90% at the first harvest time to 40–55% at 5th. The dynamics of the decline in the share of stems and leaves was highest at humidity level 3. The tuber percentage was from 0 to 20% for the 1st period to 40–60% for the 5th period.Figure 3Potato biomass structure changes depending on humidity level and tuber harvest term (percentage).Full size imageThe Denar variety, regardless of the humidity level, was characterized by a greater share of stems and leaves. For the Julinka, the tuber percentage at the last harvest was at the same or higher than in the case of stems and leaves. At humidity levels 2 and 3, tubers accounted up to 60% of the harvested biomass.The growth of stem and stolon biomass was noticeable at all stages of potato development (Table 2); greater dynamics were found in the growth of tuber mass (Fig. 3). Under level 3, the growth of the biomass of stems with leaves and stolons was slower than in level 2 of water was used.Water use efficiencyAverage daily doses of water used for the Denar and Julinka varieties in potato harvesting periods are shown in Fig. 4. The volume of water was determined each time for the corresponding level of humidity (1, 2 and 3). Based on the data obtained, a proportional increase in water consumption was found for both potato varieties. The most intensive increase in water consumption was noted at humidity level 3. The W index corresponding to the average daily dose of water calculated for the Denar variety varied from 0.40 l day−1 in the 1st period (O1) to 0.79 l day−1 in the 5th harvest period (O5), whereas for the Julinka it was from 0.49 l day−1 (O1) to 0.92 l day−1 (O5). The W values for the level 3 changed for the Denar variety from 0.23 l day−1 in (O1) to 0.38 l day−1 (O5), while for the Julinka from 0.28 l day-1 (O1) to 0.28 l day-1, respectively (O5). The difference in the intensity of water consumption increase for humidity levels was expressed by varying the values of simple directional coefficients approximating empirical data. The highest values of these coefficients were obtained for the humidity level 1. The directional coefficient for the Denar was 0.0077 day−1, and for the Julinka variety 0.009 day−1. For humidity level 3, these values are 4 and 6 times lower: 0.002 day−1 (Denar) and 0.0014 day−1 (Julinka), respectively.Figure 4Average daily water consumption for potato varieties, at three soil humidity levels (1, 2, 3) and in each of five growing stages (O1), (O2), (O3), (O4), (O5).Full size imageThe average daily water consumption throughout the growing season calculated from potato planting is shown in Fig. 5. The average daily water use was the highest for both varieties at humidity level 3. Index W1 for the Denar was 0.53 l day−1, while for Julinka was higher—0.70 l day−1. The water consumption for the humidity level 1 was about 2 times lower: for the Denar—0.27 l day−1 and for Julinka—0.29 l day−1.Figure 5Average daily water consumption for potato varieties, at three soil humidity levels (1, 2, 3), cumulative calculation from potato planting.Full size imageAhmadi et al. (2017)37 used various irrigation schedule strategies for water demand measurements at evapotranspiration. Water demand has been fully or partially satisfied in static and dynamic modes. The research presents dynamics of vapor pressure deficit (VPD) throughout the growing season. The value of VPD in the first days after planting the potato was about 0.5 kPa while in 70 days maximum value was noted (2.5 kPa), and at the end of the growing season (after 150 days) about 1.5 kPa. Due to the shorter potato growing season in present research, no decrease in water demand was noticed up to about 70 days and, as in the results of the research presented by Ahmadi et al. (2017)37, a steady increase in water demand was noted. Similar results were obtained by King et al. (2020)38 and the largest water deficit was found in the middle of vegetation, after 70–80 days after planting35,39.Values for average daily increase in potato tuber weight (index W2) in individual vegetation periods are presented below (Fig. 6). No approximation of functional models to empirical data is possible; hence, the conclusions are based on a description. In the 1st period, i.e. until day 24 (O1), tuber weight gains were smaller than in the other periods. Depending on the humidity level, these amounted to 2.0 to 3.5 g day−1 for the Denar variety, and 2.7 to 3.9 g day−1 for the Julinka. The differences for Denar were 1.5 g day−1 and for Julinka 1.2 g day−1. In the 2nd irrigation period (O2), average daily increase in potato tuber weight was the highest, from 5.9 g day−1 for level 2 to 7.9 g day−1 for level 3. Average daily tuber weight gain was 13% higher for level 1 than for level 2.Figure 6Average daily potato varieties tuber increase, at three soil humidity levels (1, 2, 3), in each of five potato growing stages (O1), (O2), (O3), (O4), (O5).Full size imageThe average daily weight gain of tubers of potato varieties (W3), calculated incrementally from the beginning of the experiment (Fig. 7). For the entire growing season, this indicator for the Denar variety was the highest for the humidity level 1st (5.7 g day−1), at the level 3rd (5.1 g day−1) and the lowest at the level 2nd (4.3 g day−1). The average daily weight gain of potato tubers of the Julinka was definitely highest for the first humidity level (8.1 g day−1).Figure 7Average daily potato varieties tuber increase, at three soil humidity levels (1, 2, 3), cumulative calculation from potato planting.Full size imageThe ratio of the average daily water consumption to the average weight gain of potato tuber (W4) for individual periods is given in Fig. 8. For humidity level 1 for Denar and Julinka varieties, the values decreased with the growing period of vegetation. In the period (O1), 0.079 l of water was used for the Denar variety and 0.075 l for the Julinka for an increase in potato tuber weight of 1 g. In the next stages of the growing season, this index ranged from 0.35 to 0.45 l g−1 for the Denar variety, for the Julinka it was definitely smaller and range from 0.25 to 0.34 l g−1. At humidity level 1, Julinka used less water than Denar to produce the same weight of tubers. At humidity level 2, the volume of water used at the beginning of growth was also the largest for the Denar variety (0.159 l g−1). This amount was two times higher than the volume at level 1. In subsequent periods, the indicator changed and ranged from 0.059 to 0.105 l g−1. For the Julinka variety, water consumption varied in individual periods from 0.085 to 0.113 l g−1 and showed no trend. At humidity level 3, Denar used the greatest amount of water, as compared to levels 1 and 2, and showing no trend. The Julinka variety used even more water at the same humidity level. This amount ranged from 0.164 to 0.298 l g−1 and, unlike in previous cases, it showed an upward trend with plant development.Figure 8Ratio of average daily water consumption to average daily tuber mass increase dependent on three soil humidity levels (1), (2), (3), in each of five potato growing stages (O1), (O2), (O3), (O4), (O5).Full size imageJovanovic et al. (2010)40 divided the potato growing season into five stages related to growth phases. There were no increases in the weight of leaves and stems, while the tuber weight, regardless of the irrigation method (PRD and FI), increased steadily. The weight of tubers in the last harvest, as compared to the first, increased five-fold. A similar relationship was obtained in the work of Shahnazari et al. (2007)41. This research also took account of different levels of humidity using the strategies of PRD and FI, also considering soil retention characteristics (pF curve). The research showed a clear steady increase in potato tuber weight in each harvest.The ratio of the average daily water consumption to the average weight gain of potato tuber varieties calculated cumulatively from the planting (Fig. 9). The W5 value (0.114 l g−1) for the Denar variety at the end of the growing season was the highest for the 3rd humidity level and was about two times higher than at level 1. Water consumption efficiency for the Denar variety was the highest at humidity level 1. The sequence of W5 values is similar for the Julinka, with the difference that for the 3rd level it was 0.205 l g−1; i.e. six times higher than the indicator for level 1. Water consumption efficiency for the Julinka variety was definitely highest at humidity level 1.Figure 9Ratio of average daily water consumption to average daily tuber mass increase dependent on three soil humidity levels (1), (2), (3), cumulative calculation from potato planting.Full size imageBadr et al. (2010)42 analyzed the tuber yield, using two irrigation systems: surface and subsurface drip line. The total volume of water applied during the growing season was the differentiating factor. Results showed that as the volume of water applied during the growing season increased, the yield increased. When the subsurface line was used, applying 75 mm of water during the growing season, the total yield was approx. 27.5 t ha−1, and 32.5 t ha−1 for 325 mm. The effect of water amount on increase in yield was greater for the surface drip line. After applying 75 mm, the yield was 17.5 t ha−1, and 40 t ha−1 (for 325 mm). Similar results were obtained in the work of Linker et al. (2016)43. Regardless of the frequency, amount and total size of irrigation treatments, a proportional increase in the size of crops was observed with increasing doses of water.Shahnazari et al. (2007)41 planned several harvest dates (H0–H4) throughout the entire growing season, analyzing the irrigation efficiency indicator (average WUE index’). Regardless of the irrigation technique, and taking into account, above all, the amount of water administered, the value of the average WUE index’ indicator was the highest in the period H2–H3, similar results were found in our own research. More

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All experimental procedures were permitted by the Institutional Animal Care and Usage Committees of the Grassland Science College of Gansu Agricultural University (GSC-IACUC-2015-0011). Our experiments were conducted according to their guidelines, which are in accordance with the Guide for the Care and Use of Laboratory Animals (the Constitution of Experimental Animal Ethics Committee of Gansu Agricultural University). All experiments were performed in accordance with ARRIVE guidelines.Animals and laboratory conditionsAdults of both sexes (three males and three females) were captured in April 2015. Specifically, the animals were captured in Mayin Tan (37°12′N, 102°46′E; Tianzhu Tibetan Autonomous County, China) using live traps25 set at fresh surface mounds. The individuals were then transported to the laboratory and housed in an acrylic box with a pipeline covered with soil. The box and pipeline were covered by black cloth to simulate the dark environment of plateau zokors. The temperature in the room was maintained between 20 and 25 °C. Food was supplied daily and consisted of potatoes, lettuce and carrot. After three days of acclimatization to the laboratory the animals were used in the different experiments. Our laboratory is located 2 km away from the field site. At the end of the experiments all animals were returned to the capture site in good health.Laboratory testing arenaThe experimental setup for the laboratory experiments was as follows (Fig. 1): A transparent Perspex tube (8 cm × 8 cm × 80 cm) was joined to the side of the dark acrylic box (40 cm × 40 cm × 40 cm). A rubber stopper was inserted into one end of the tube to avoid effects from the external environment. Treatment apparatus was placed into the rubber stopper (see “Laboratory treatment apparatus” section, below), and, to avoid the apparatus being damaged by the animals, wire mesh (8 cm × 8 cm × 0.5 cm) was placed about 15 cm from one end of the tube. A mercury thermometer was inserted into the tube in the middle to monitor the tube’s temperature. Between experiments with different animals, the box and tube were wiped with 95% alcohol and then with distilled water.Figure 1Schematic drawing of the setup used to test burrow-sealing behavior in plateau zokors in the laboratory. (1) acrylic box covered with soil 30 cm in depth; (2) experimental animal; (3) mercury thermometer; (4) transparent Perspex tube; (5) the pipe’s support clip; (6) wire mesh (8 cm × 8 cm × 0.5 cm); (7) rubber stopper (8 cm × 8 cm × 5 cm).Full size imageLaboratory treatment apparatusA rubber stopper with seven holes was used for plugging one end of the tube (Fig. 2). The oxygen concentration, light, temperature, sound and gas flow were considered in this design.Figure 2Schematic diagram of the rubber stopper used to simulate the entrance plug of the burrow. (1) power supply; (2) light bulb switch; (3) electric wire switch; (4) oxygen cylinder; (5) in situ three-parameter soil gas analyzer; (6) voice recorder; (7) negative pressure drainage device; (8) rubber plug; (9) LED bulb; (10) the iron rod; (11) heating cord; (12) AVOXIVY speaker with 5 cm diameter.Full size imageOxygen treatmentTo avoid the oxygen that was delivered into the tube causing the gas to flow too strongly, become drier, and create a sound, a steel oxygen cylinder and thin hose (0.3 cm in diameter) were selected, and one end of the hose was connected directly to the oxygen cylinder with a humidifier bottle, while the opposite end was inserted into the rubber stopper (Fig. 2). Before beginning the experiment, we allowed the oxygen cylinder to sit for two hours at laboratory temperature to remove any temperature effects. A three-parameter soil gas analyzer (13.05.03Pro, Shanghai SAFE Biotech Co., Ltd, China) was used to monitor the oxygen concentration in the tube (Fig. 2).Light treatmentThe average light intensity—that is, 360 Lux from 8:00 am to 8:00 pm—was measured in the field. One end of a wire was connected to an LED light (1 Watt), and the other end to the power supply (Fig. 2).Temperature treatmentThe temperature in the burrow entrance in the field was about 3 °C warmer than that at a tunnel depth of 10 cm. As such, one end of a wire was connected to a heater strip and the other end to the electrical power supply (Fig. 2). A thermometer was inserted into the tube to monitor the temperature inside the tube (Fig.1). During the experiment period in the laboratory, we switched on or off to make sure the relatively constant temperature inside the tube. The temperature range inside the tube was 3.2 ± 0.27 °C .Sound treatmentWhen a burrow is opened, wind whistle can be produced around the burrow entrance. Accordingly, a voice recorder (PCM-D50, frequency response 50 Hz–40 kHz, Sony, Japan) was placed at the burrow entrance in the field to record the burrow-entrance sound, the duration of which was 30 min. In the laboratory, the two ends of a wire were connected to an AVOXIVY loudspeaker (diameter: 5 cm; impedance: 4 Ω; 50 Hz–20 kHz) and a voice recorder, respectively (Fig. 2). The recorded sound was played back with a 60 dB sound pressure level, as measured at the burrow entrance in the field (XL2 sound level meter, Nti Audion, Switzerland). The sound was repeatedly played within one hour.Gas flow treatmentTo avoid ambient atmosphere entering the tube, a negative pressure drainage ball with plastic tube (12 cm long, 2 cm in diameter) connected the tube through a rubber stopper (Fig. 2). The tunnel gas was inhaled by the ball, then we pinched the ball to blow the gas into the tunnel as gas flow treatment.Field treatment apparatusFor the field experiment, the apparatus consisted of a tube (40 cm long, 8 cm in diameter) and an alarm device. The alarm device was made up of a loudspeaker, two slide rails (15 cm long), two metal plates (approximately 7 cm in length and 3 cm in width), and three coiled metal springs (5 cm long, 2 cm in diameter). The three springs were joined to one of the metal plates, while the other metal plate was fixed on the slide rails. The two metal plates were touched by the plateau zokor when it was plugging, which triggered the alarm device, thus enabling us to know whether or not burrow-sealing behavior was occurring (Fig. 3). The aluminum tube with an oxygen device was embedded into the burrow. The soil covering the tube served as an excellent insulator, buffering the tube from the aboveground temperature (Fig. 4A). A steel oxygen cylinder and thin hose (0.3 cm in diameter) were applied by connecting one end of the hose directly to the oxygen cylinder with a humidifier bottle, and then the opposite end of the hose was inserted into the tube (Fig. 4A). A three-parameter soil gas analyzer (13.05.03Pro, Shanghai SAFE Biotech Co., Ltd, China) was used to monitor the oxygen concentration in the tube (Fig. 4A). Allowing sunlight to enter the burrow, a glass bottle, open at one end but closed at the other, was embedded into the burrow. We also used soil to cover the bottle, and there was a 5 cm gap at the surface (Fig. 4B). The aluminum tube with high thermal conductivity was embedded into the burrow. Again, we used soil to cover the bottle and retained a 20 cm gap (Fig. 4B).Figure 3Schematic drawing of the apparatus used to test the burrow-sealing behavior of plateau zokor in the field. (1) tube; (2) loudspeaker; (3) slide rail; (4) metal plate; (5) coiled metal springs.Full size imageFigure 4(A) Schematic drawing of the apparatus used in the oxygen treatment placed in the tunnel of the plateau zokor. (B) Schematic drawing of the apparatus used for the temperature and light treatments placed in the tunnel of the plateau zokor. (1) tunnel of the plateau zokor; (2) oxygen cylinder; (3) three-parameter soil gas analyzer; (4) plateau zokor.Full size imageProcedureIn the laboratory experiment, we tested three males and three females for their responses to each treatment. To avoid generating stress and habituation to treatments, zokors were tested for 12 h each day and there was one hour interval between treatments, and five days interval between round of testing for the same individual (Table 1). We performed a control experiment in which a rod was inserted into the burrow but no further treatment was applied, which allowed us to evaluate whether it was the treatment that was causing the burrow-sealing behavior. Before beginning treatment experiment, each zokor was tested 24 times (12 h × 2 days) under the control experiment. We determined the rod movement as occurrence of burrow-sealing behavior.Table 1 Times of the experiments for each treatment in the laboratory simulation.Full size tableIn the field experiment, we tested three zokors (one male, two females), and six zokors were caught in the cold season and warm season (three males and three females, respectively). We then fastened radio collars (Ag357, Biotrack, Ltd., UK) to each captured individual to allow us to track the position in foraging tunnels of each zokor. Each zokor was used three times in the experiments under each treatment, and, after finishing each experiment, we changed the position of the foraging tunnel to ensure the test tunnel was not an abandoned tunnel. According to radio-tracking data, the straight-line distance between the test tunnel and the nest for each treatment was about 5 m. We conducted a control experiment that whether plateau zokor move to the test tunnel or not during the time between treatments. In the cold season, from 4 October 2015 to 2 November 2015, the burrow-sealing behavior of each zokor was tested under different treatments during their active time (12:00–18:00) and inactive time (09:00–11:00) for a total of 27 days (Table 2). The same was done in the warm season but for a total of 18 days from 15 May 2016 to 5 June 2016, in which the active time was 14:00–20:00 and the inactive time was 08:00–13:00 (Table 2).Table 2 Times of the experiments for each treatment in the active and inactive periods of plateau zokors during the warm and cold season.Full size tableData analysisThe occurrence of burrow-sealing was recorded as “1”, and non-sealing was recorded as “0”. The frequency of burrow-sealing was the number of times the burrow was sealed divided by the total number of experiments for each treatment26, and we considered the frequency for each individual as a replicate. The latency to reseal the burrow was the period from the start of the treatment to the sealing of the burrow, and we considered each instance of latency to reseal the burrow as a repeat. The latency to reseal the burrow for non-sealing under each treatment was unavailable data and was therefore removed. The presence of a normal distribution in the initial data was determined using the Kolmogorov–Smirnov test. All data followed a normal distribution. A comparison of males and females in their frequency of sealing the burrow and in their latency to reseal the burrow under each treatment was performed with an independent-samples T-test. Multiple comparisons were made for the frequency of burrow-sealing and the latency to reseal the burrow under different treatments by using the least significant difference method at the significance level of P = 0.05. In the field experiment, the number of replicates was fewer than three for frequency and the latency to reseal the burrow, we did not conduct multiple comparisons.Preliminary statistical analysis of the data was performed using Excel 2013 and SPSS 19.0. All the figures and tables were produced in GraphPad Prism 8.0 and Excel 2013. More

Site, meadow, and fertilisationThe grassland utilized in this study was located in Sedico (BL: 420 m a.s.l., eastern Italian Pre-Alps), where the annual mean temperature is 10.6 °C and the annual rainfall is approximately 1366 mm (389, 326, 401, and 250 mm in spring, summer, autumn, and winter, respectively). The site was level and had an alluvial calcareous substratum. The soil was sandy-loam textured with 12.2% gravel content, 14.6% total carbonate content, and a pH of 7.5. Since 1977, a section of the meadow has been used for a fertilisation trial organised as three completely randomized blocks with 24 m2 plots and twenty-seven treatments obtained by combining three levels of yearly N, P, and K applications per ha: 0, 96, and 192 kg N as ammonium nitrate; 0, 54, and 108 kg P2O5 as triple superphosphate; and 0, 108, and 216 kg K2O as K sulphate. Since 2010, the grassland has been cut twice per year and surveyed for seed production in three treatments: no fertilisation (000), fertilization with no N and intermediate levels of P and K (011), and fertilisation with the highest nutrient rates (222).The vegetation of the three treatments (Annex 1) corresponded to the following meadow types: type 000, vegetation intermediate between a poor-soil form of the Arrhenatherum elatius meadow (Ar0) and a Bromus erectus meadow (Br), with high species richness and low legume abundance; type 011, an Ar0 meadow with high species richness and legume abundance; and type 222, a grass-rich form of the Arrhenatherum elatius meadow with low species richness and legume abundance.Plant sampling and laboratory analysisDuring the two growth periods within each of the years from 2012 to 2017, fertile shoots were sampled from the three fertilization treatments. 15–30 shoots (5–10 in each plot) from each flowering species were collected at the optimal seed maturation stage (most fruits/inflorescences still intact, i.e., no seed shedding). At the sub-plot level, all fertile shoots were collected at the time of meadow mowing on one 1-m2 sub-plot per plot. Collected shoots were put separately per species into porous paper bags, dried, and preserved in a refrigerator until laboratory analysis.During the autumn and winter after collection, the 15–30 shoots of each species were analysed for the number of compound and/or simple inflorescences and the flowers per simple inflorescence or shoot. For species with flowers or inflorescences too numerous to be rapidly counted, an inflorescence length or diameter which could be related to the number of flowers was also measured (e.g., the panicle length in grasses). In sample flowers, intact fruits, or simple inflorescences, the number of ovules per flower and the number of ovules transformed to seed were observed under a binocular microscope. Mature seeds were weighed and tested for germinability and viability according to ISTA19. Germination trials were performed with three seed samples per species, which were placed on filter paper in petri-dishes and moved to a germinator for 4 weeks (8 h light/25 °C and 16 h darkness/15 °C) with weekly observation and extraction of germinated seeds. At the end of the germination test, seeds that had not germinated were checked for viability with the tetrazolium test. Total viability was calculated as the sum of germinability and viability of non-germinated seeds.All shoots collected on the sub-plots were counted and measured for the number of inflorescences and flowers. When inflorescences and flowers were too numerous to be counted rapidly (e.g., in all grasses), only the same length/diameter measured on the 15–30 shoot samples was recorded.A more detailed description of the laboratory analyses is available in Scotton20.Data analysisThe value of each reproductive trait was calculated for each year and growth period at the plot level for each species. The values of the traits describing the size of the reproductive system were obtained from the shoots collected on the sub-plots. However, for species with too many flowers per shoot, a relation was calculated between the flowers per shoot and the length/diameter of the inflorescences measured on the 15–30 shoot samples. This relationship was then used to calculate the flower number for each shoot. The number of ovules per flower, the portion of ovules transformed to seed (ovule site utilisation, i.e. the filled seed/ovule ratio), the 1000-seed weight, germinability, and viability were calculated from the results of lab analyses of the 15–30 shoot samples.Because all the species collected were not always present in the six study years, only the thirty-two species (fifteen grasses and seventeen forbs: Table 1) found in at least three of the study years were considered in this paper to obtain enough reliable results. For all grasses, data were available only for the first growth period. For four forbs (see Annex 3) data were available for the first and second growth periods: in these cases, the average values of the two periods were used in the analyses.Table 1 Species studied for reproductive traits in a grassland fertilisation trial in the Italian eastern Alps.Full size tableThe statistical analyses were performed at the levels of individual species and the two grassland functional groups (grasses and forbs). Nine main reproductive traits describing the whole process of gamic reproduction were considered: number of simple inflorescences per shoot, flowers per simple inflorescence, ovules per flower, ovules and viable seeds per shoot, OSU (ovule site utilization), percent viability, germinability, and seed weight. Percent dormancy (the difference between percent viability and germinability) and the shoot density recorded in the subplots were also considered in some analyses.Only sixteen species were present in all of the fertilisation treatments, presenting a challenge in the tests that included all of the species together because a balanced among-treatments comparison was only possible by discarding the data from species not present in all of the treatments. To overcome this issue, we assumed that due to symbiotic N-fixation, the high presence of legumes in the 011 treatment (fertilization with P and K) was equivalent to a yearly N fertilisation of about 3.5 kg/ha per percent point of legume abundance in the species composition21,22. Therefore, treatment 011 (30% more legume abundance than in treatment 222: Annex 1) was regarded as an intermediate N addition of 105 kg per ha per year (from 3.5 kg N × 30% legume abundance). The values of the reproductive traits were then calculated for two fertilisation levels, low (LowFert) and high (HighFert). For species present in 000 and 011, LowFert was 000 and HighFert was 011. For species present in 011 and 222, LowFert was 011 and HighFert was 222. For species present in three fertilisation treatments, LowFert was 000 and HighFert was the average between 011 and 222. Statistical analysis considering only the species present in all fertilisation treatments yielded a similar pattern of fertilisation effects to those found in analysis of the two separate fertilisation levels. The analysis of the two fertilisation levels was therefore utilized because it was representative of a larger number of species.Statistical analyses (see summary in Annex 2) were conducted with three main aims: 1. studying the fertilisation effect on the reproductive behaviour of individual species and the two species groups of grasses and forbs; 2. finding species biological and ecological traits explaining their response to fertilisation; and 3. identifying multispecies correlations among reproductive traits and the possible effects of fertilisation on their patterns.For the first aim, the fertilisation effect was tested for the reproductive traits of each individual species through application of a mixed linear model under a repeated measure approach. In the model, fertilisation treatment, year, and block were input as class factors, and a plot identifier was used as a random factor. In case of significant fertilisation effects, the among-treatment differences were tested using the Tukey multiple comparison adjustment. Prior to performing the mixed model, data were checked for homoscedasticity and normality and, if necessary, log-transformed.From the individual species mixed models, a table was calculated containing the frequency of cases with fertilisation effects (three levels: no, positive, or negative) for each reproductive trait and species group. To check if grasses and forbs differed for the obtained frequencies, for each trait a chi-square test on the frequency table “fertilisation effect x species group” was performed.In a following set of analyses, the effect of the grassland functional group (grasses or forbs) on the multi-year means of each reproductive trait was tested with general linear models (GLM). Prior to the analysis, the data were sometimes log-transformed to mitigate homoscedasticity and normality problems. In these analyses, species were considered as replicates within the species group (therefore not included as a class factor) and the fertilisation level was input as a class factor. The effect of the fertilisation level on each reproductive trait was tested separately for the two species groups. In this case, the GLM included both fertilisation level and species as class factors.For the second aim, possible biological and ecological traits explaining the species response to fertilisation were investigated by relating the percent variation due to fertilisation in two important size traits (ovule and viable seed number per shoot: variables Y) to the following explanatory (X) variables: average values of the nine reproductive traits, the seven Ellenberg bioindicator values23, and the percent variation of shoot density. The relationships were fitted according to a linear regression approach for grasses and forbs together or separately and checked for the parametric assumptions of residual normality and homoscedasticity. For the percent variation due to fertilisation of individual species of OSU, seed germinability, viability and weight, one-way analyses of variance were performed where three traits of the species reproductive biology (type of reproduction, breeding system and pollen vector4: Annex 1) were used as categorical factors. A GLM approach was also used in this case.For the third aim, multispecies correlations were analysed by in-pairs relating the reproductive trait values of individual species averaged across fertilisation treatments and years. Fertile shoot density recorded in the subplots. was used as a supplementary characteristic. Nonlinear relationships were made linear with a log-transformation. Because the purpose of the analysis was not to predict one trait from the other but to efficiently summarise the relationships between traits, the standardised major axis (SMA) approach was used instead of the linear regression method24. The analyses were performed for grasses and forbs both together and separately. In order to verify if fertilisation could affect the characteristics of the evaluated relationships, a second set of SMA analyses were performed by separating the two fertilisation levels and the lines obtained were tested for common slope and elevation according to Warton et al.24.The year effect will be reported in a forthcoming paper and is therefore not discussed here, despite its inclusion in the statistical analyses.We used SAS/STAT software 12.325 with procedures MIXED, GLM, REG, and UNIVARIATE, and R 3.0.026 with package SMATR.Additional statementsThe experimental research and the collection of plant material was done according to relevant institutional, national, and international guidelines and legislation. No grassland species considered in the research is included in the list of endangered species according to the IUCN, European Union, Italian national and regional classifications. The collection of plant specimen was done with permission of the grassland owner during the hay-making operations for forage production which do not need a special permission from the concerned local authorities. The plant species were identified by the first author, Michele Scotton. A voucher specimen of each plant species considered in the research was stored in the laboratory of the authors’ Department (DAFNAE) and the authors have provided an ID number for each voucher specimen. More

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Summary of sequencing dataWe obtained 168 million and 180 million 250 bp reads from Asian Badger and Northern Hog Badger, respectively. After removing transcripts and unigenes below 200 bp, we obtained 335,772 transcripts and 285,159 unigenes belonging to Asian Badger and 413,917 transcripts and 362,075 unigenes belonging to Northern Hog Badger (Table 1). Next, we analysed the length distribution of the unigenes and transcripts in these two species (Fig. 1). Their N50 of transcript length is longer than 1000 bp, and their N50 of unigene length is longer than 600 bp. The average GC content of the transcriptome data of Asian Badge was 52.71%, a value slightly higher than that of the Northern Hog Badger, which was 52.12% (Table 1).Table 1 Summary of the transcriptome of Asian Badgers and Northern Hog Badgers.Full size tableFigure 1Length and quantity distribution of transcripts and unigenes.Full size imageFunctional annotation and classification of the assembled unigenesThe success rate of annotation of these research data in the seven databases is shown in Table 2. In total, 34,150 (ZH) and 31,632 (GH) unigenes had GO terms (Table 2). Among them, there were three GO items related to digestion: positive regulation of the digestive system process (GH and ZH both have one gene), digestive tract development (GH and ZH both have four genes), and digestion (GH has five genes, ZH has three). Next, we compared the GO terms of Asian Badger and Northern Hog Badger transcriptomes and found that the distributions pattern of gene functions from these two species were particularly similar (Fig. 2). This predictable result indicates that there is no bias in the construction of the libraries from the Asian Badger and Northern Hog Badger. For both species, in the three main partitions (cellular component, molecular function, and biological process) of the GO classification, ‘Cellular process’, ‘Binding’ and ‘Metabolic process’, terms were principal individually (Fig. 2). In total, 8915 (ZH) and 10,203 (GH) unigenes had KOG terms (Table 2). In addition, 15,667 (ZH) and 17,823 (GH) were mapped to the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways (Table 2) and grouped into 32 subclasses. Interestingly, the digestive system subcategory contains 695 and 611 unigenes in Asian Badger and Northern Hog Badger, respectively, involving 9 pathways, namely, bile, gastric acid, pancreatic, salivary secretion, carbohydrate, protein, vitamin, fat digestion and absorption, and mineral absorption.Table 2 Gene annotation success rate statistics.Full size tableFigure 2GO term Top20 for GH and ZH.Full size imageAnalysis of orthologous genesThe transcriptome evolution of different species can be understood by comparing transcriptome data. We analysed the possible orthologous genes between the transcriptome of Asian Badger and Northern Hog Badger obtained in this study. We selected a total of 5227 homologous gene pairs from these four species. After 5227 pairs of homologous genes were optimized and screened, 943 orthologous gene pairs were obtained (Supplementary Table S1).To explore whether the genes related to small intestinal digestion in Asian Badger and Northern Hog Badger have undergone adaptive evolution. We can predict the genes that affect the evolution of the two species through selection pressure on orthologous genes12. We selected 473 orthologous gene pairs with Ka/Ks  > 1 called divergent orthologous genes from the Ka/ks analysis results. We obtained 1263 orthologous gene pairs with Ka/Ks  More