The population-dynamic functions of seed dispersal

We summarize some of the population-dynamic consequences of the mosaic structure of plant populations for the evolution of seed dispersal. A fairly elaborated set of theoretical ideas exist regarding the evolution of dispersal and we have synthesized some of them in an attempt to make them more accessible to field ecologists. We consider the relationship of these general theoretical ideas to our understanding of fruit and seed dispersal.We develop three related models to describe the similarities and differences in how dispersal functions for risk reduction (bet hedging), escaping the negative consequences of crowding, and escaping high concentrations of relatives. We also briefly discuss directed dispersal as a fourth population-dynamic aspect of dispersal. Dispersal can have a risk-reducing function only when there is global (metapopulation) temporal variance in success. Dispersal to escape the negative consequences of crowding requires only spatial and local temporal environmental variation. Dispersal for escaping high concentrations of relatives requires no environmental variation, but does require genetic population structure. Directed dispersal, defined as non-random into particular patch types contingent on the expectation of local success, is always valuable when possible and represents an advantage independent the others which can occur with random dispersal.In an effort to accommodate for the differences between simple mathematical models and the behavior of complex natural fruit and seed dispersal systems we have discussed the following issues: actual patterns of patch structure and dispersal distance; the implications of plant cosexuality, perenniality, and allocation costs of dispersal structures; and the impact of the detailed nature of density dependence, breeding systems, and genetic structure. We briefly compare the population-dynamic functions of dispersal presented here with the widely cited functions of colonization, escape, and directed dispersal. Finally, we suggest how the theoretical models can be used with field data to estimate the fitness consequences of dispersal.     

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.     

De-normalizing smoking in urban areas: Public smoking bans and smoking prevalence

The effectiveness of command-and-control policies related to tobacco use has been studied in high-income countries. Still, there is limited evidence of their effects in low and middle-income countries. We explore the case of Colombia, a country that introduced a business-supported smoking ban in bars and restaurants and all public indoor spaces in 2010. This paper investigates the effect of smoking bans in bars and restaurants on smoking prevalence in Bogotá, Colombia. In this paper, we use the matching with triple-differences technique in analyzing household consumption data from the 2007 and 2011 quality of life surveys. This is done by exploiting their geographical proximity and variation in the density of commercial areas. We found that after the smoking ban implementation, smoking prevalence reduced in households near high-density commercial blocks compared to households near low-density commercial blocks (−10.8 pp.). The impact is larger for households with children and older household heads. Since households near high-density commercial blocks are more frequently exposed to smoking than households near low-density commercial blocks, the former would be more willing to internalize the smoking de-normalization process.     

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.     

偏头痛患者体感刺激下脑电信号的功能连接（英文）

目的 偏头痛是一种复杂的脑功能障碍性疾病,全球范围内患病率为14.4%。功能连接测量两个神经信号之间的统计学相互依赖性,不同的功能连接反映了大脑区域协同工作的不同模式。因此,研究不同脑区的功能连接对于理解偏头痛的病理生理机制具有十分重要的意义。以往基于脑电图对偏头痛患者脑功能连接的分析主要集中在视觉和疼痛刺激。本文尝试研究偏头痛患者在发作间期对体感刺激的皮质反应,以进一步了解偏头痛的神经功能障碍,为偏头痛的预防和治疗提供线索。方法 招募23例无先兆偏头痛患者,10例有先兆偏头痛患者,28名健康对照者。所有受试者均进行详细的基本资料和病史采集,完善量表评估,在正中神经体感刺激下进行脑电图记录。计算68个脑区的相干性作为功能连接,并评估功能连接与临床参数的相关性。结果 在正中神经体感刺激下,无先兆偏头痛和有先兆偏头痛患者的脑电功能连接与对照组相比存在差异,异常的脑电功能连接主要位于感觉辨别、疼痛调节、情绪认知和视觉处理等区域。无先兆偏头痛和有先兆偏头痛患者的大脑皮层对体感刺激可能具有相同的反应方式。偏头痛患者的功能连接异常与临床特征之间存在相关性,可以部分反映偏头痛的严重程度。结论 本研究...     

寄主植物对桑寄生植物叶片功能性状的影响

为了解寄生植物叶片功能性状的差异及其影响因素,研究了西双版纳地区寄主植物对3种桑寄生植物叶片功能性状的影响,并分析了桑寄生植物与寄主植物叶片功能性状的相关性。结果表明,不同寄主植物的相同寄生植物叶片功能性状存在显著差异,来自7种寄主植物的五蕊寄生(Dendrophthoe pentandra)的叶片含水量(61.2%～70.1%)、氮含量(9.6～16.0 g/kg)、碳氮比(30.8～48.5)以及缩合单宁含量(3.3%～11.0%)等性状的差异较大;从4种寄主植物上获取的澜沧江寄生(Scurrula chingii var.yunnanensis)的叶片含水量(60.0%～71.7%)、碳含量(431.3～502.3 g/kg)和缩合单宁含量(3.8%～9.9%)等性状也呈现较大种间差异,而在2种寄主植物上的离瓣寄生(Helixanthera parasitica)的叶片功能性状没有显著差异。桑寄生植物与寄主植物的叶片含水量、总碳含量、总氮含量、碳氮比和缩合单宁含量呈显著的正相关。寄主植物作为桑寄生植物营养物质的主要来源,会影响桑寄生植物叶片的相应功能性状。桑寄生植物能从寄主植物获...