Biology subjects

Rosbakh, S.

Publications and source records attributed to Rosbakh, S..

3 recordsLinked to original sources

bioRxiv2022

The role of floral traits in community assembly process at high elevations in Lesser Himalaya

O_LIEcological theory postulates that plant trait research should consider multiple traits related to different organs and/or ontogenetic stages as such traits represent different ecological niche axes. Particularly, floral traits have been suggested to play an important role in assembling plant communities along environmental gradients as they determine the reproductive success, one of the key functions in plants. Yet, the predictive power of floral traits in community assembly research remains largely unverified empirically. C_LIO_LIWe analyzed the predictive power of six floral traits of 139 herbaceous species for inferring community assembly process in twenty-one sites located along an elevation gradient in Lesser Himalaya ranging from 2,000 to 4,000 meters above sea level. The floral trait variability along the gradient was analyzed using community-weighted trait mean (CWM) values and functional diversities (FD) calculated for each of the study communities. C_LIO_LIThe CWM values for onset of flowering and flower display area increased significantly with increasing elevation, whereas specific flower area showed an opposite pattern. In combination with convergence in onset of flowering and specific area (i.e., lower FD values in high elevation sites), these patterns suggest that abiotic filtering and plant-pollinator interactions affected the floral trait composition of the communities studied. Increasing low-temperature stress towards high-elevation sites selected for late-flowering species that produce resource-intensive flowers with larger display areas. C_LIO_LILow pollinator abundancy and activity in high elevation, could also explain why these traits were selected in the study communities. Delayed flowering with increasing elevations might facilitate the phenological overlap of plants and their pollinators, as pollinator activity at higher elevation peaks in the second half of the vegetation period. The dominance of species with low specific flower area and larger display area in high elevation communities were attributed to the increased flower longevity and attraction of pollinators, respectively, to maximize pollination success under pollinator scarcity. C_LIO_LISynthesis. Our study provides empirical support of the recent argument that floral traits contribute considerably to the assembly of plant communities along environmental gradients. Thus, such traits should be included into community assembly research agenda as they represent key growth and survival ecological functions. C_LI

ecology↗

bioRxiv2022

Machine learning algorithms predict soil seed bank persistence from easily available traits

QuestionSoil seed banks (SSB), i.e., pools of viable seeds in the soil and its surface, play a crucial role in plant biology and ecology. Information on seed persistence in soil is of great importance for fundamental and applied research, yet compiling datasets on this trait still requires enormous efforts. We asked whether the machine learning (ML) approach could be used to infer and predict SSB properties of a regional flora based on easily available data. LocationEighteen calcareous grasslands located along an elevational gradient of almost 2000 m in the Bavarian Alps, Germany. MethodsWe compared a commonly used ML model (random forest) with a conventional model (linear regression model) as to their ability to predict SSB presence/absence and density using empirical data on SSB characteristics (environmental, seed traits and phylogenetic predictors). Further, we identified the most important determinants of seed persistence in soil for predicting qualitative and quantitative SSB characteristics using the ML approach. ResultsWe demonstrated that the ML model predicts SSB characteristics significantly better than the linear regression model. A single set of predictors (either environment, or seed traits, or phylogenetic eigenvectors) was sufficient for the ML model to achieve high performance in predicting SSB characteristics. Importantly, we established that a few widely available SSB predictors can achieve high predictive power in the ML approach, suggesting a high flexibility of the developed approach for use in various study systems. ConclusionsOur study provides a novel methodological approach that combines empirical knowledge on the determinants of SSB characteristics with a modern, flexible statistical approach based on ML. It clearly demonstrates that ML can be developed into a key tool to facilitate labor-intensive, costly and time-consuming functional trait research.

ecology↗

bioRxiv2021

Inferring community assembly processes from functional seed trait variation along temperature gradient

O_LIAssembly of plant communities has long been scrutinized through the lens of trait-based ecology. Studies generally analyze functional traits related to the vegetative growth, survival and resource acquisition and thus ignore how ecological processes may affect plants at other stages of their lifecycle, particularly when seeds disperse, persist in soil and germinate. C_LIO_LIHere, we analyzed an extensive data set of 16 traits for 167 species measured in-situ in 36 grasslands located along an elevational gradient and compared the impact of abiotic filtering, biotic interactions and dispersal on traits reflecting different trait categories: plant vegetative growth, germination, dispersal, and seed morphology. For each community, we quantified community weighted mean (CWM) and functional diversity (FD) for all traits and established their relationships to mean annual temperature. C_LIO_LIThe seed traits were weakly correlated to vegetative traits and thus constituted independent axes of plant phenotypical variation that were affected differently by the ecological processes considered. Abiotic filtering impacted mostly the vegetative traits and to a lesser extent on seed germination and morphological traits. Increasing low-temperature stress towards colder sites selected for short-stature, slow-growing and frost-tolerant species that produce small quantity of smaller seeds with higher degree of dormancy, high temperature requirements for germination and comparatively low germination speed. C_LIO_LIBiotic interactions, specifically competition in the lowlands and facilitation in uplands, also filtered certain functional traits in the study communities. The benign climate in lowlands promoted plant with competitive strategies including fast growth and resource acquisition (vegetative growth traits) and early and fast germination (germination traits), whereas the effects of facilitation on the vegetative and germination traits were cancelled out by the strong abiotic filtering. C_LIO_LIThe changes in the main dispersal vector from zoochory to anemochory along the gradient strongly affected the dispersal and the seed morphological trait structure of the communities. Specifically, stronger vertical turbulence and moderate warm-upwinds combined with low grazing intensity selected for light and non-round shaped seeds with lower terminal velocity and endozoochorous potential. C_LIO_LISynthesis. We clearly demonstrate that, in addition to vegetation traits, seed traits can substantially contribute to functional structuring of plant communities along environmental gradients. Thus, the, hard seed traits related to germination and dispersal are critical to detect multiple, complex community assembly rules. Consequently, such traits should be included in core lists of plant traits and, when applicable, be incorporated into analysis of community assembly. C_LI

ecology↗