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Plant and Soil

Resumen/Descripción – provisto por la editorial en inglés
Plant and Soil publishes original papers and review articles exploring the interface of plant biology and soil sciences, and offering a clear mechanistic component. This includes both fundamental and applied aspects of mineral nutrition, plant-water relations, symbiotic and pathogenic plant-microbe interactions, root anatomy and morphology, soil biology, ecology, agrochemistry and agrophysics. Articles discussing a major molecular or mathematical component also fall within the scope of the journal. All contributions appear in the English language.
Palabras clave – provistas por la editorial

No disponibles.

Disponibilidad
Institución detectada Período Navegá Descargá Solicitá
No detectada desde ene. 1997 / hasta dic. 2023 SpringerLink

Información

Tipo de recurso:

revistas

ISSN impreso

0032-079X

ISSN electrónico

1573-5036

Editor responsable

Springer Nature

País de edición

Reino Unido

Fecha de publicación

Cobertura temática

Tabla de contenidos

Effect of water exchange rate on interspecies competition between submerged macrophytes: functional trait hierarchy drives competition

Ying Pan; Duanyang Yuan; Qihang Wu; Ling Jin; Mingli Xie; Yang Gu; Changqun DuanORCID

Palabras clave: Plant Science; Soil Science.

Pp. 631-647

Nitrogen and phosphorus cycling in an ombrotrophic peatland: a benchmark for assessing change

Verity G. SalmonORCID; Deanne J. Brice; Scott Bridgham; Joanne Childs; Jake Graham; Natalie A. Griffiths; Kirsten Hofmockel; Colleen M. Iversen; Terri M. Jicha; Randy K. Kolka; Joel E. Kostka; Avni Malhotra; Richard J. Norby; Jana R. Phillips; Daniel Ricciuto; Christopher W. Schadt; Stephen D. Sebestyen; Xiaoying Shi; Anthony P. Walker; Jeffrey M. Warren; David J. Weston; Xiaojuan Yang; Paul J. Hanson

Palabras clave: Plant Science; Soil Science.

Pp. 649-674

Correction to: Seed and leaf-spray inoculation of PGPR in brachiarias (Urochloa spp.) as an economic and environmental opportunity to improve plant growth, forage yield and nutrient status

Mariangela Hungria; Artur Berbel Lirio Rondina; Amanda Letícia Pit Nunes; Ricardo Silva Araujo; Marco Antonio Nogueira

Palabras clave: Plant Science; Soil Science.

Pp. 675-675

Correction to: Does the short-term fluctuation of mineral element concentrations in the closed hydroponic experimental facilities affect the mineral concentrations in cucumber plants exposed to elevated CO2?

Xun Li; Jinlong Dong; Nazim Gruda; Wenying Chu; Zengqiang Duan

Palabras clave: Plant Science; Soil Science.

Pp. 677-677

Correction to: The role of plants in the formation of the topsoil chemical composition in different climatic conditions of steppe landscape

Irina Yu. Kudrevatykh; Pavel I. Kalinin; Gennady V. Mitenko; Andrey O. Alekseev

Palabras clave: Plant Science; Soil Science.

Pp. 679-679

Silicon dynamics through the lens of soil-plant-animal interactions: perspectives for agricultural practices

Félix de Tombeur; Philippe RouxORCID; Jean-Thomas CornelisORCID

Palabras clave: Plant Science; Soil Science.

Pp. 1-28

Introduction of broadleaf species into monospecific Cunninghamia lanceolata plantations changed the soil Acidobacteria subgroups composition and nitrogen-cycling gene abundances

Yuting Zhang; Kai Ding; Kim Yrjälä; Haiyan Liu; Zaikang Tong; Junhong Zhang

Palabras clave: Plant Science; Soil Science.

Pp. 29-46

Novel plant-soil feedbacks drive adaption of invasive plants to soil legacies of native plants under nitrogen deposition

Zhenwei Xu; Xiao GuoORCID; Joshua S. CaplanORCID; Mingyan Li; Weihua GuoORCID

Palabras clave: Plant Science; Soil Science.

Pp. 47-65

Bayesian inference of root architectural model parameters from synthetic field data

Shehan MorandageORCID; Eric Laloy; Andrea Schnepf; Harry Vereecken; Jan Vanderborght

<jats:title>Abstract</jats:title><jats:sec> <jats:title>Background and aims</jats:title> <jats:p>Characterizing root system architectures of field-grown crops is challenging as root systems are hidden in the soil. We investigate the possibility of estimating root architecture model parameters from soil core data in a Bayesian framework.</jats:p> </jats:sec><jats:sec> <jats:title>Methods</jats:title> <jats:p>In a synthetic experiment, we simulated wheat root systems in a virtual field plot with the stochastic CRootBox model. We virtually sampled soil cores from this plot to create synthetic measurement data. We used the Markov chain Monte Carlo (MCMC) DREAM<jats:sub>(ZS)</jats:sub> sampler to estimate the most sensitive root system architecture parameters. To deal with the CRootBox model stochasticity and limited computational resources, we essentially added a stochastic component to the likelihood function, thereby turning the MCMC sampling into a form of approximate Bayesian computation (ABC).</jats:p> </jats:sec><jats:sec> <jats:title>Results</jats:title> <jats:p>A few zero-order root parameters: maximum length, elongation rate, insertion angles, and numbers of zero-order roots, with narrow posterior distributions centered around true parameter values were identifiable from soil core data. Yet other zero-order and higher-order root parameters were not identifiable showing a sizeable posterior uncertainty.</jats:p> </jats:sec><jats:sec> <jats:title>Conclusions</jats:title> <jats:p>Bayesian inference of root architecture parameters from root density profiles is an effective method to extract information about sensitive parameters hidden in these profiles. Equally important, this method also identifies which information about root architecture is lost when root architecture is aggregated in root density profiles.</jats:p> </jats:sec>

Palabras clave: Plant Science; Soil Science.

Pp. 67-89

Accumulation, translocation, and toxicity of arsenic in barley grown in contaminated soil

Marina BurachevskayaORCID; Tatiana MinkinaORCID; Alexey FedorenkoORCID; Grigory FedorenkoORCID; Natalia ChernikovaORCID; Vishnu D. RajputORCID; Saglara MandzhievaORCID; Tatiana BauerORCID

Palabras clave: Plant Science; Soil Science.

Pp. 91-106