scholarly journals Isoscapes resolve species-specific spatial patterns in plant–plant interactions in an invaded Mediterranean dune ecosystem

2016 ◽  
Vol 36 (12) ◽  
pp. 1460-1470 ◽  
Author(s):  
Christine Hellmann ◽  
Katherine G. Rascher ◽  
Jens Oldeland ◽  
Christiane Werner
Keyword(s):  
Spatial Patterns ◽  
Plant Interactions ◽  
Species Specific ◽  
Plant Plant

scholarly journals Plant-plant interactions scale up to produce vegetation spatial patterns: the influence of long- and short-term process

Ecosphere ◽  
2017 ◽  
Vol 8 (8) ◽  
pp. e01915 ◽  
Author(s):  
Concepción L. Alados ◽  
Hugo Saiz ◽  
Maite Gartzia ◽  
Paloma Nuche ◽  
Juan Escós ◽  
...  
Keyword(s):  
Spatial Patterns ◽  
Scale Up ◽  
Plant Interactions ◽  
Short Term ◽  
Plant Plant

ALLELOPATHIC EFFECTS OF PARTHENIUM HYSTEROPHORUS ON GERMINATION OF SORGHUM SEEDS

2018 ◽  
Vol 6 (26) ◽  
Author(s):  
Jitendra Rajpoot
Keyword(s):  
Biological System ◽  
Growth And Development ◽  
Plant Virus ◽  
Evolutionary Origin ◽  
Plant Interactions ◽  
Biological Organization ◽  
Plant Soil ◽  
System A ◽  
Allelopathic Effects ◽  
Plant Plant

International Allelopathy Society has redefined Allelopathy as any process involving secondary metabolities produced by plants, algae, bacteria, fungi and viruses that influences the growth and development of agricultural and biological system; a study of the functions of secondary metabolities, their significance in biological organization, their evolutionary origin and elucidation of the mechanisms involving plant-plant, plant-microorganisms, plant-virus, plant-insect, plant-soil-plant interactions.

scholarly journals Competition-free gaps are essential for the germination and recruitment of alpine species along an elevation gradient in the European Alps

Alpine Botany ◽  
2021 ◽  
Author(s):  
Vera Margreiter ◽  
Janette Walde ◽  
Brigitta Erschbamer
Keyword(s):  
Vegetation Cover ◽  
Seedling Recruitment ◽  
Environmental Control ◽  
Elevation Gradient ◽  
European Alps ◽  
Plant Interactions ◽  
Experimental Conditions ◽  
Positive Effects ◽  
Seed Sowing ◽  
Plant Plant

AbstractSeed germination and seedling recruitment are key processes in the life cycle of plants. They enable populations to grow, migrate, or persist. Both processes are under environmental control and influenced by site conditions and plant–plant interactions. Here, we present the results of a seed-sowing experiment performed along an elevation gradient (2000–2900 m a.s.l.) in the European eastern Alps. We monitored the germination of seeds and seedling recruitment for 2 years. Three effects were investigated: effects of sites and home sites (seed origin), effects of gaps, and plant–plant interactions. Seeds of eight species originating from two home sites were transplanted to four sites (home site and ± in elevation). Seed sowing was performed in experimentally created gaps. These gap types (‘gap + roots’, ‘neighbor + roots’, and ‘no-comp’) provided different plant–plant interactions and competition intensities. We observed decreasing germination with increasing elevation, independent of the species home sites. Competition-released gaps favored recruitment, pointing out the important role of belowground competition and soil components in recruitment. In gaps with one neighboring species, neutral plant–plant interactions occurred (with one exception). However, considering the relative vegetation cover of each experimental site, high vegetation cover resulted in positive effects on recruitment at higher sites and neutral effects at lower sites. All tested species showed intraspecific variability when responding to the experimental conditions. We discuss our findings considering novel site and climatic conditions.

scholarly journals Trichoderma Strains and Metabolites Selectively Increase the Production of Volatile Organic Compounds (VOCs) in Olive Trees

Metabolites ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 213
Author(s):  
Irene Dini ◽  
Roberta Marra ◽  
Pierpaolo Cavallo ◽  
Angela Pironti ◽  
Immacolata Sepe ◽  
...  
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Gas Chromatography Mass Spectrometry ◽  
Lipid Signaling ◽  
Plant Interactions ◽  
Growth Promoters ◽  
Volatile Organic ◽  
Trichoderma Fungi ◽  
Olive Trees ◽  
Plant Plant

Plants emit volatile organic compounds (VOCs) that induce metabolomic, transcriptomic, and behavioral reactions in receiver organisms, including insect pollinators and herbivores. VOCs’ composition and concentration may influence plant-insect or plant-plant interactions and affect soil microbes that may interfere in plant-plant communication. Many Trichoderma fungi act as biocontrol agents of phytopathogens and plant growth promoters. Moreover, they can stimulate plant defense mechanisms against insect pests. This study evaluated VOCs’ emission by olive trees (Olea europaea L.) when selected Trichoderma fungi or metabolites were used as soil treatments. Trichoderma harzianum strains M10, T22, and TH1, T. asperellum strain KV906, T. virens strain GV41, and their secondary metabolites harzianic acid (HA), and 6-pentyl-α-pyrone (6PP) were applied to olive trees. Charcoal cartridges were employed to adsorb olive VOCs, and gas chromatography mass spectrometry (GC-MS) analysis allowed their identification and quantification. A total of 45 volatile compounds were detected, and among these, twenty-five represented environmental pollutants and nineteen compounds were related to olive plant emission. Trichoderma strains and metabolites differentially enhanced VOCs production, affecting three biosynthetic pathways: methylerythritol 1-phosphate (MEP), lipid-signaling, and shikimate pathways. Multivariate analysis models showed a characteristic fingerprint of each plant-fungus/metabolite relationship, reflecting a different emission of VOCs by the treated plants. Specifically, strain M10 and the metabolites 6PP and HA enhanced the monoterpene syntheses by controlling the MEP pathway. Strains GV41, KV906, and the metabolite HA stimulated the hydrocarbon aldehyde formation (nonanal) by regulating the lipid-signaling pathway. Finally, Trichoderma strains GV41, M10, T22, TH1, and the metabolites HA and 6PP improve aromatic syntheses at different steps of the shikimate pathway.

Mycorrhizosphere bacteria and plant-plant interactions facilitate maize P acquisition in an intercropping system

2021 ◽  
pp. 127993
Author(s):  
Chun Song ◽  
Clement Kyei Sarpong ◽  
Xiaofeng Zhang ◽  
Wenjing Wang ◽  
Lingfeng Wang ◽  
...  
Keyword(s):  
Plant Interactions ◽  
P Acquisition ◽  
Plant Plant

Ecological field theory model: a mechanistic approach to simulate plant–plant interactions in southeastern forest ecosystems

1993 ◽  
Vol 23 (10) ◽  
pp. 2180-2193 ◽  
Author(s):  
Pu Mou ◽  
Robert J. Mitchell ◽  
Robert H. Jones
Keyword(s):  
Field Theory ◽  
Loblolly Pine ◽  
Vegetation Dynamics ◽  
Plant Size ◽  
Theory Model ◽  
Plant Interactions ◽  
Simulation Accuracy ◽  
Individual Level ◽  
The Individual ◽  
Plant Plant

Ecological field theory, unlike many other vegetation modeling approaches, provides a basis to construct an individually based, spatially explicit, and resource-mediated model for mechanistic simulation of plant–plant interactions and vegetation dynamics. The model REGROW has been developed, based on ecological field theory principles, to simulate vegetation dynamics for northern hardwood forests. Using data from a current study of a southern pine system to calibrate a modified version of this model, SPGROW, we simulated growth of individuals for the first growing season in stands of loblolly pine (Pinustaeda L.) and sweetgum (Liquidambarstyraciflua L.) seedlings and loblolly pine seedling–sweetgum sprout mixtures. SPGROW accurately simulated stand development at population and stand levels. However, less agreement occurred at the individual level between simulated and field survey values, possibly owing to lack of data on site heterogeneity and genetic variation. Plant interactions, which altered resource availability (light, water, and nutrients) to individual plants, played a major role in differentiating plant size in the model. Given its unique model structure and simulation accuracy, SPGROW has the potential to provide very detailed insight into the mechanisms of plant–plant interactions.

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