Relationship between rhizosphere soil fungi and plant aboveground biomass in the meadow steppe of Saihanba, Hebei, China

doi:10.17521/cjpe.2024.0458

Abstract

Abstract:

Aims Plant growth is influenced by a combination of their own characteristics and soil microbial communities. However, it remains unclear how plant resource acquisition strategies affect their own biomass through the diversity of rhizosphere soil fungi in natural communities.
Methods In this study, we selected 12 dominant and common plant species from the meadow steppe of Saihanba in Hebei Province, and performed high-throughput sequencing on their rhizosphere soil fungi, and simultaneously measured the functional traits of these plants’ leaves and roots, as well as aboveground biomass. The aim was to delve into the relationship between rhizosphere soil fungal diversity and aboveground biomass under different resource acquisition strategies.
Important findings The study found that: 1) in terms of resources acquisition strategies, leguminous plants belonged to the “fast-growing” strategy species, while Cyperaceae and Poaceae plants belonged to “slow-growing” strategy species. Cyperaceae plants exhibited a “do-it-yourself” strategy, and most non-leguminous forbs tended to be “outsourcing” strategy. 2) Plants with “slow-growing” and “do-it-yourself” strategies increased the overall rhizosphere fungal and saprotrophic fungal diversity, and the above-ground biomass of plants with these strategies dominated the community. 3) Rhizosphere soil fungal diversity was positively correlated with plant above-ground biomass, with the diversity of saprotrophic and pathogenic fungi playing particularly crucial roles. 4) The differences in above-ground biomass within the community were mainly directly influenced by the “fast-slow” economic spectrum of plants. These findings not only reveal the regulatory effect of plant resource acquisition strategies on rhizosphere soil fungal communities, but also highlight the key role of the “fast-slow” economic spectrum and rhizosphere soil fungal diversity in driving above-ground biomass accumulation. This study provides a theoretical basis for understanding the impact of plant-microbe interactions on the functions of grassland ecosystems.

Key words: “fast-slow” economic spectrum, collaborative dimension, aboveground biomass, rhizosphere fungi, meadow steppe

SONG Shan-Shan, TANG Zhi-Yao. Relationship between rhizosphere soil fungi and plant aboveground biomass in the meadow steppe of Saihanba, Hebei, China[J]. Chin J Plant Ecol, 2025, 49(9): 1461-1471.

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URL: https://www.plant-ecology.com/EN/10.17521/cjpe.2024.0458

https://www.plant-ecology.com/EN/Y2025/V49/I9/1461

Figures/Tables 7

Fig. 1 Principal component analysis (PCA) of soil properties. AP, available phosphorus content; NH4+-N, ammonium nitrogen content; NO3--N, nitrate nitrogen content; SOC, soil organic carbon content; SWC, soil water content; TN, total nitrogen content; TP, total phosphorus content.

Fig. 2 Principal component analysis (PCA) of traits related to the “fast-slow” economic spectrum (A) and the collaboration dimension (B). LDMC, leaf dry matter content; LMA, specific leaf mass; LN, leaf nitrogen content; LP, leaf phosphorus content; RD, root diameter; RN, root nitrogen content; RP, root phosphorus content; SLA, specific leaf area; SRA, specific root area; SRL, specific root length; SRTA, specific root tip abundance.

Fig. 3 Community composition (A) and diversity (B) of plant rhizosphere soil fungi. A, Bromus inermis; B, Elymus dahuricus; C, Leymus chinensis; D, Medicago ruthenica; E, Carex korshinskyi; F, Artemisia tanacetifolia; G, Plantago asiatica; H, Sanguisorba officinalis; I, Geum aleppicum; J, Thalictrum petaloideum; K, Potentilla longifolia; L, Achillea asiatica. OTU, operational taxonomic unit.

Table 1 Effect of plant functional traits (PFT) and soil properties on rhizosphere soil fungal diversity and aboveground biomass

因子 Factor	df	Fungi_Total		Fungi_Sap		Fungi_Path				生物量 Biomass
因子 Factor	df	Est.	SE	Est.	SE	Est.	SE	Est.	SE	Est.	SE
SLA	62	-24.16^†	12.26	-4.61^*	2.21	-0.72	0.52	-2.60	2.51	-14.36^***	2.94
LN	62	-23.64^†	12.22	-3.72	2.23	-0.95^†	0.51	-1.30	2.50	-8.18^*	3.27
LP	62	-8.63	12.59	-0.99	2.30	-0.15	0.53	-1.14	2.54	-11.41^***	3.12
LDMC	62	12.06	12.53	1.49	2.29	0.52	0.52	1.68	2.54	13.27^***	3.01
LMA	62	19.31	12.41	4.03	2.23	0.68	0.52	1.27	2.52	16.02^***	2.81
RN	62	-37.90^**	11.64	-5.64^*	2.16	-0.90^†	0.51	-4.01	2.47	-9.26^**	3.23
RP	62	-17.05	12.47	-1.79	2.29	-0.53	0.52	-2.95	2.53	-9.08^**	3.24
RD	62	-22.42	12.28	-3.55	2.25	-0.69	0.52	-0.43	2.55	-9.33^**	3.23
SRA	62	25.08^*	12.22	4.10	2.23	1.08^*	0.51	2.70	2.52	7.80^*	3.29
SRL	62	28.00^*	12.09	4.82^*	2.20	1.16^*	0.50	0.74	2.52	10.41^**	3.18
SRTA	62	32.52^**	11.86	5.74^**	2.15	0.98^†	0.51	-2.17	2.49	15.81^***	2.82
SWC	67	-17.90	12.48	-1.50	2.36	-0.22	0.53	-6.83^*	2.60	-0.33	3.42
pH	67	12.970	12.57	3.78	2.33	0.01	0.54	-2.74	2.71	-1.97	3.41
TN	67	-23.24^†	12.35	-3.14	2.34	-0.52	0.53	-5.08^†	2.66	-0.28	3.42
NH₄⁺-N	67	7.33	12.64	5.49^*	2.27	0.57	0.53	-9.53^***	2.47	0.34	3.42
NO₃^--N	67	-5.03	12.65	1.49	2.36	0.62	0.53	-7.87^**	2.55	1.83	3.41
TP	67	-24.11^†	12.32	-4.94^*	2.29	-0.66	0.53	-0.74	2.73	-0.28	3.42
AP	67	-21.66^†	12.39	-5.12^*	2.28	-0.67	0.53	1.17	2.73	-0.64	3.42
SOC	67	-28.70^*	12.17	-5.36^*	2.28	-0.90^†	0.52	-2.60	2.71	-0.65	3.42

Fig. 4 Linear mixed-effects modelling of the effect of plant resource acquisition strategies on operational taxonomic units (OTU) richness of rhizosphere soil fungi. FungiTotal, OTU richness of overall fungi; FungiSap, OTU richness of saprophytic fungi; FungiPath, OTU richness of pathogenic fungi; FungiAMF, OTU richness of arbuscular mycorrhizal fungi. PCA1Col, scores on the first axis of principal component analysis for traits related to the collaboration dimension; PCA1Con, scores on the first axis of principal component analysis for traits related to the “fast-slow” economic spectrum. The solid line represents the significant slope value (p < 0.05 or p ≈ 0.05) for the linear mixed-effects model, and the corresponding shaded area represents the fitted 95% confidence interval.

Fig. 5 Linear mixed-effects modelling of the effect of plant resource acquisition strategies and rhizosphere soil fungal diversity on aboveground biomass. FungiTotal, operational taxonomic units (OTU) richness of overall fungi; FungiSap, OTU richness of saprophytic fungi; FungiPath, OTU richness of pathogenic fungi; FungiAMF, OTU richness of arbuscular mycorrhizal fungi. PCA1Col, scores on the first axis of principal component analysis for traits related to the collaboration dimension; PCA1Con, scores on the first axis of principal component analysis for traits related to the “fast-slow” economic spectrum.

Fig. 6 Structural equation modelling (SEM) of the direct and indirect effect of plant resource acquisition strategies and rhizosphere soil fungal diversity on aboveground biomass. Red and black arrows represent positive and negative effects, respectively, and the numbers on the arrows represent standardized path coefficients. The arrow thickness is proportional to the magnitude of these path coefficients. FungiTotal, operational taxonomic units (OTU) richness of overall fungi; FungiSap, OTU richness of saprophytic fungi; FungiPath, OTU richness of pathogenic fungi; FungiAMF, OTU richness of arbuscular mycorrhizal fungi; PCA1Col, scores on the first axis of principal component analysis for traits related to the collaboration dimension; PCA1Con, scores on the first axis of principal component analysis for traits related to the “fast-slow” economic spectrum; PCA2Env, scores on the second axis of principal component analysis for soil properties. The significance levels are denoted as follows: †, p ≈ 0.05; *, p < 0.05; **, p < 0.01; ***, p < 0.001. Two-way arrows indicate significant correlations between variables. The R2 of each dependent variable in the model are expressed as percentages.

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