Early response of herbaceous vegetation to Rhododendron ponticum subsp. baeticum invasion in European Atlantic forests

Questions

Rhododendron ponticum subsp. baeticum is an invasive shrub of growing concern in continental Europe, but little is known about its impact on native plant communities. Here we ask: do environmental conditions differ between forest stands invaded by it and uninvaded stands? Do these differences correlate with R. ponticum's cover? Are these differences associated with differences in taxonomic and functional diversity of vascular plant species of the herb layer? Can these vegetation changes be explained by the sorting of certain life-history traits by R. ponticum-induced environmental changes?

Location

Several forests invaded by R. ponticum in the French Atlantic domain.

Methods

We recorded vegetation composition and a number of environmental variables in 400-m² plots that were established in 64 paired forest stands (32 invaded vs 32 uninvaded). We compiled traits from existing databases. We computed several metrics of taxonomic and functional diversity. We compared environmental variables and diversity metrics between invaded and uninvaded stands. We used correlation and regression analyses to relate them with R. ponticum's cover. We ran RLQ and fourth-corner analyses to explore the relationships between R. ponticum invasion, environmental variables, species traits, and vegetation composition.

Results

Independent of its abundance, R. ponticum invasion was associated with lower light arrival at the forest floor and increased litter thickness. Concomitantly, species richness and diversity and trait diversity were reduced. The major driver of species assemblages was soil pH, which strongly interacted with the invasion gradient. R. ponticum did not sort species according to traits associated with shade tolerance and thick-litter tolerance. However, tree and shrub saplings were more abundant in invaded than uninvaded stands, at the expense of graminoid and fern species.

Conclusions

As R. ponticum becomes the dominant shrub, it exerts new selection forces on life-history traits of extant species, mostly via reduced light availability, increased litter thickness, and physical competition, thereby reducing taxonomic and functional diversity of the herb layer, without impeding tree and shrub self-regeneration, at least in the short term.     

A trait-based approach to assess niche overlap and functional distinctiveness between non-indigenous and native species

Our understanding of the community assembly processes acting on non-indigenous species (NIS), as well as the relationship with native species is limited, especially in marine ecosystems. To overcome this knowledge gap we here develop a trait-based approach based on the functional distinctiveness metric to assess niche overlap between NIS and native species, using high-resolution data on benthic invertebrate communities in the Baltic Sea. Our results show that NIS retain a certain degree of similarity with native species, but display one or a few singular unique traits (e.g., bioturbation ability). Furthermore, we demonstrate that community assembly processes, including both environmental filtering and limiting similarity affect NIS establishment, but that their effects may be highly context dependent, as illustrated by pronounced spatial patterns in distinctiveness. Finally, our trait-based approach provides a generic framework applicable to other areas and organisms, to better understand and address biological invasions.     

绿色木霉组蛋白去乙酰化酶编码基因TvRpd3在木霉生物防治作用中的功能分析

【目的】本文借助基因编辑技术在具有生物防治潜力的绿色木霉(Trichoderma viride)中敲除组蛋白去乙酰化酶编码基因TvRpd3,来研究TvRpd3基因及其编码蛋白在提高木霉病原菌拮抗能力中的作用。【方法】利用融合PCR和同源重组策略构建了TvRpd3基因缺失的突变菌株,通过对峙培养、表型观察、免疫组化检测、代谢组学分析等系统比较TvRpd3基因敲除前后菌株的组蛋白乙酰化修饰水平、次级代谢产物合成、病原菌拮抗能力以及田间防治效果等。【结果】与野生型菌株相比,缺失TvRpd3基因的木霉工程菌(?TvRpd3)对多种病原菌表现出了更强的对峙抑制效果,其所产的发酵液对小麦白粉病、烟草黑胫病和番茄枯萎病的防治效果分别提高了62.27%、57.45%和70.71%。同时,敲除TvRpd3基因也显著改变了木霉工程菌所产次级代谢产物的种类和产量,抗生性物质的产量大幅提高。【结论】绿色木霉TvRpd3基因及其介导的组蛋白乙酰化修饰在提高绿色木霉生物防治中起着重要作用。     

Trade-offs and synergies between ecosystem productivity and stability in temperate grasslands

Aim

It is crucial to monitor how the productivity of grasslands varies with its temporal stability for management of these ecosystems. However, identifying the direction of the productivity–stability relationship remains challenging because ecological stability has multiple components that can display neutral, positive or negative covariations. Furthermore, evidence suggests that the direction of the productivity–stability relationship depends on the biotic interactions and abiotic conditions that underlie ecosystem productivity and stability. We decipher the relationships between grassland productivity and two components of its stability in four habitat types with contrasting environments and flora.

Location

France.

Time period

2000–2020.

Major taxa

Grassland plant species.

Methods

We used c. 20,000 vegetation plots spread across French permanent grasslands and remotely sensed vegetation indices to quantify grassland productivity and temporal stability. We decomposed stability into constancy (i.e., temporal invariability) and resistance (i.e., maximum deviation from average) and deciphered the direct and indirect effects of abiotic (namely growing season length and nitrogen input) and biotic (namely plant taxonomic diversity, trait diversity and community-weighted mean traits) factors on productivity–stability relationships using structural equation models.

Results

We found a positive relationship between productivity and constancy and a negative relationship between productivity and resistance in all habitats. Abiotic factors had stronger effects on productivity and stability compared with biotic factors. A longer growing season enhanced grassland productivity and constancy. Nitrogen input had positive and negative effects on grassland productivity and resistance, respectively. Trait values affected the constancy and resistance of grassland more than taxonomic and trait diversity, with effects varying from one habitat to another. Productivity was not related to any biotic factor.

Main conclusions

Our findings reveal how vital it is to consider both the multiple components of stability and the interaction between environment and biodiversity to gain an understanding of the relationships between productivity and stability in real-world ecosystems, which is a crucial step for sustainable grassland management.     

Selective incorporation of 5-hydroxytryptophan blocks long range electron transfer in oxalate decarboxylase

Oxalate decarboxylase from Bacillus subtilis is a binuclear Mn-dependent acid stress response enzyme that converts the mono-anion of oxalic acid into formate and carbon dioxide in a redox neutral unimolecular disproportionation reaction. A π-stacked tryptophan dimer, W96 and W274, at the interface between two monomer subunits facilitates long-range electron transfer between the two Mn ions and plays an important role in the catalytic mechanism. Substitution of W96 with the unnatural amino acid 5-hydroxytryptophan leads to a persistent EPR signal which can be traced back to the neutral radical of 5-hydroxytryptophan with its hydroxyl proton removed. 5-Hydroxytryptophan acts as a hole sink preventing the formation of Mn(III) at the N-terminal active site and strongly suppresses enzymatic activity. The lower boundary of the standard reduction potential for the active site Mn(II)/Mn(III) couple can therefore be estimated as 740 mV against the normal hydrogen electrode at pH 4, the pH of maximum catalytic efficiency. Our results support the catalytic importance of long-range electron transfer in oxalate decarboxylase while at the same time highlighting the utility of unnatural amino acid incorporation and specifically the use of 5-hydroxytryptophan as an energetic sink for hole hopping to probe electron transfer in redox proteins.     

Latent group detection in functional partially linear regression models

In this paper, we propose a functional partially linear regression model with latent group structures to accommodate the heterogeneous relationship between a scalar response and functional covariates. The proposed model is motivated by a salinity tolerance study of barley families, whose main objective is to detect salinity tolerant barley plants. Our model is flexible, allowing for heterogeneous functional coefficients while being efficient by pooling information within a group for estimation. We develop an algorithm in the spirit of the K-means clustering to identify latent groups of the subjects under study. We establish the consistency of the proposed estimator, derive the convergence rate and the asymptotic distribution, and develop inference procedures. We show by simulation studies that the proposed method has higher accuracy for recovering latent groups and for estimating the functional coefficients than existing methods. The analysis of the barley data shows that the proposed method can help identify groups of barley families with different salinity tolerant abilities.     

Variable selection in nonlinear function-on-scalar regression

We develop a new method for variable selection in a nonlinear additive function-on-scalar regression (FOSR) model. Existing methods for variable selection in FOSR have focused on the linear effects of scalar predictors, which can be a restrictive assumption in the presence of multiple continuously measured covariates. We propose a computationally efficient approach for variable selection in existing linear FOSR using functional principal component scores of the functional response and extend this framework to a nonlinear additive function-on-scalar model. The proposed method provides a unified and flexible framework for variable selection in FOSR, allowing nonlinear effects of the covariates. Numerical analysis using simulation study illustrates the advantages of the proposed method over existing variable selection methods in FOSR even when the underlying covariate effects are all linear. The proposed procedure is demonstrated on accelerometer data from the 2003–2004 cohorts of the National Health and Nutrition Examination Survey (NHANES) in understanding the association between diurnal patterns of physical activity and demographic, lifestyle, and health characteristics of the participants.     

Functional data analysis with covariate-dependent mean and covariance structures

Functional data analysis has emerged as a powerful tool in response to the ever-increasing resources and efforts devoted to collecting information about response curves or anything that varies over a continuum. However, limited progress has been made with regard to linking the covariance structures of response curves to external covariates, as most functional models assume a common covariance structure. We propose a new functional regression model with covariate-dependent mean and covariance structures. Particularly, by allowing variances of random scores to be covariate-dependent, we identify eigenfunctions for each individual from the set of eigenfunctions that govern the variation patterns across all individuals, resulting in high interpretability and prediction power. We further propose a new penalized quasi-likelihood procedure that combines regularization and B-spline smoothing for model selection and estimation and establish the convergence rate and asymptotic normality of the proposed estimators. The utility of the developed method is demonstrated via simulations, as well as an analysis of the Avon Longitudinal Study of Parents and Children concerning parental effects on the growth curves of their offspring, which yields biologically interesting results.     

A meta-analysis on morphological,physiological and biochemical responses of plants with PGPR inoculation under drought stress

Plant growth-promoting rhizobacteria (PGPR) can help plants to resist drought stress. However, the mechanisms of how PGPR inoculation affect plant status under drought remain incompletely understood. We performed a meta-analysis of plant response to PGPR inoculation by compiling data from 57 PGPR-inoculation studies, including 2, 387 paired observations on morphological, physiological and biochemical parameters under drought and well-watered conditions. We compare the PGPR effect on plants performances among different groups of controls and treatments. Our results reveal that PGPR enables plants to restore themselves from drought-stressed to near a well-watered state, and that C4 plants recover better from drought stress than C3 plants. Furthermore, PGPR is more effective underdrought than well-watered conditions in increasing plant biomass, enhancing photosynthesis and inhibiting oxidant damage, and the responses of C4 plants to the PGPR effect was stronger than that of C3 plants under drought conditions. Additionally, PGPR belonging to different taxa and PGPR with different functional traits have varying degrees of drought-resistance effects on plants. These results are important to improve our understanding of the PGPR beneficial effects on enhanced drought-resistance of plants.