PCA and RDA analysis data sheet

The data were collected in the field. Excel was used to create the data. Gram+-gram positive bacteria, Gram--gram negative bacteria, AMF- arbuscular mycorrhizal fungi, B/F-bacteria to fungi ratio, SOC- soil organic carbon, TN- soil total nitrogen, C/N-soil organic carbon to total nitrogen ratio. Treatment: C- control,DU-dung and urine return; M-mowing; T-trampling; DU+M-mowing combined with the addition of dung and urine; M+T-mowing combined with trampling; DU+T-trampling combined with the addition of dung and urine; DU+M+T-mowing combined with trampling and the addition of dung and urin

Soil parameters

The data were collected in the field. Excel was used to create the data. SE-standard error, MBC-soil microbial biomass carbon, MBN- soil microbial biomass nitrogen. Treatment: C- control,DU-dung and urine return; M-mowing; T-trampling; DU+M-mowing combined with the addition of dung and urine; M+T-mowing combined with trampling; DU+T-trampling combined with the addition of dung and urine; DU+M+T-mowing combined with trampling and the addition of dung and urin

Soil microbes' parameters

The data were collected in the field. Excel was used to create the data. SE-standard error, Gram+-gram positive bacteria, Gram--gram negative bacteria, AMF- arbuscular mycorrhizal fungi, B/F-bacteria to fungi ratio. Treatment: C- control,DU-dung and urine return; M-mowing; T-trampling; DU+M-mowing combined with the addition of dung and urine; M+T-mowing combined with trampling; DU+T-trampling combined with the addition of dung and urine; DU+M+T-mowing combined with trampling and the addition of dung and urin

Effects of alkalinity stress, rhizome connection and data on the tiller number and height of subsequent ramets.

<p>Solid lines with 0C, 60C, 180C and 300C represented 0/0, 0/60, 0/180 and 0/300 mmol L^-1 alkalinity levels in the rhizome-connected treatments, respectively; Dash lines with 0S, 60S, 180S and 300S represented 0/0, 0/60, 0/180 and 0/300 mmol L^-1 alkalinity levels in the rhizome-severed treatments, respectively.</p

Analysis of variance for the effects of alkalinity stress (A) and rhizome connection (C) on the biomass of original and subsequent ramets and cost-benefit analysis.

<p>Note: <i>F</i>-values are shown for each variable followed by their respective significance levels.</p><p>*<i>P</i> < 0.05;</p><p>**<i>P</i> < 0.01;</p><p>***<i>P</i> <0.001;</p><p>^ns, <i>P</i> > 0.05.</p><p>Analysis of variance for the effects of alkalinity stress (A) and rhizome connection (C) on the biomass of original and subsequent ramets and cost-benefit analysis.</p

Analysis of variance for the effects of alkalinity stress (A) and rhizome connection (C) on the photosynthetic rate, water potential, root weight, rhizome length and rhizome buds of subsequent ramets.

<p>Note: <i>F</i>-values are shown for each variable followed by their respective significance levels.</p><p>*<i>P</i> < 0.05;</p><p>**<i>P</i> < 0.01;</p><p>***<i>P</i> <0.001;</p><p>^ns, <i>P</i> > 0.05.</p><p>Analysis of variance for the effects of alkalinity stress (A) and rhizome connection (C) on the photosynthetic rate, water potential, root weight, rhizome length and rhizome buds of subsequent ramets.</p

Analysis of variance for the effects of alkalinity stress (A), rhizome connection (C) and data (D) on the tiller number and height of subsequent ramets.

<p>Note: <i>F</i>-values are shown for each variable followed by their respective significance levels.</p><p>*<i>P</i> < 0.05;</p><p>**<i>P</i> < 0.01;</p><p>***<i>P</i> <0.001;</p><p>^ns, <i>P</i> > 0.05.</p><p>Analysis of variance for the effects of alkalinity stress (A), rhizome connection (C) and data (D) on the tiller number and height of subsequent ramets.</p

Effects of alkalinity stress and rhizome connection on a) the biomass of daughter and b) mother ramets, c) the total biomass of clonal organs and d) cost-benefits of clonal integration.

<p>Bar groups with different capital letters indicate significant differences (<i>P</i> < 0.05) between the four levels of alkalinity in the rhizome-connected treatment. Bar groups with different lowercase letters indicate significant differences (<i>P</i> < 0.05) between the four levels of alkalinity in the rhizome-severed treatment. Asterisks indicate significant differences (<i>P</i> < 0.05) between rhizome-connected and rhizome-severed treatments.</p

Effects of alkalinity stress and rhizome connection on a) root weight, b) rhizome length, c) bud number, d) photosynthetic rate and e) water potential of subsequent ramets.

<p>Bar groups with different capital letters indicate significant differences (<i>P</i> < 0.05) between the four levels of alkalinity in the rhizome-connected treatment. Bar groups with different lowercase letters indicate significant differences (<i>P</i> < 0.05) between the four levels of alkalinity in the rhizome-severed treatment. Asterisks indicate significant differences (<i>P</i> < 0.05) between rhizome-connected and rhizome-severed treatments.</p

Data_Sheet_1_Trichoderma Biofertilizer Links to Altered Soil Chemistry, Altered Microbial Communities, and Improved Grassland Biomass.docx

In grasslands, forage and livestock production results in soil nutrient deficits as grasslands typically receive no nutrient inputs, leading to a loss of grassland biomass. The application of mature compost has been shown to effectively increase grassland nutrient availability. However, research on fertilization regime influence and potential microbial ecological regulation mechanisms are rarely conducted in grassland soil. We conducted a two-year experiment in meadow steppe grasslands, focusing on above- and belowground consequences of organic or Trichoderma biofertilizer applications and potential soil microbial ecological mechanisms underlying soil chemistry and microbial community responses. Grassland biomass significantly (p = 0.019) increased following amendment with 9,000 kg ha−1 of Trichoderma biofertilizer (composted cattle manure + inoculum) compared with other assessed organic or biofertilizer rates, except for BOF3000 (fertilized with 3,000 kg ha−1 biofertilizer). This rate of Trichoderma biofertilizer treatment increased soil antifungal compounds that may suppress pathogenic fungi, potentially partially responsible for improved grassland biomass. Nonmetric multidimensional scaling (NMDS) revealed soil chemistry and fungal communities were all separated by different fertilization regime. Trichoderma biofertilizer (9,000 kg ha−1) increased relative abundances of Archaeorhizomyces and Trichoderma while decreasing Ophiosphaerella. Trichoderma can improve grassland biomass, while Ophiosphaerella has the opposite effect as it may secrete metabolites causing grass necrosis. Correlations between soil properties and microbial genera showed plant-available phosphorus may influence grassland biomass by increasing Archaeorhizomyces and Trichoderma while reducing Ophiosphaerella. According to our structural equation modeling (SEM), Trichoderma abundance was the primary contributor to aboveground grassland biomass. Our results suggest Trichoderma biofertilizer could be an important tool for management of soils and ultimately grassland plant biomass.</p