Root Pathogens

Termorshuizen, A.J.

doi:10.1007/978-94-017-8890-8_6

Cited by 13 publications

(14 citation statements)

References 66 publications

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“…First, effective specialization can result from local adaptation of a pathogen or cryptic diversity, if a perceived pathogen species in fact constitutes multiple subpopulations or genotypes with preferences towards certain plant species or local plant populations (Konno et al ., 2011; Barrett & Heil, 2012; Eck et al ., 2019). Indeed, cryptic diversity within pathogenic species is well established, particularly in fungi where formae specialis , pathotypes and other intra‐specific categories have been historically used to delineate variations in host preference (Termorshuizen, 2014). Second, effective specialization may also be driven by context dependency of biotic interactions, including the regulatory effects of the abiotic environment, host phenology and age (Laine, 2007; Alvarez‐Loayza et al ., 2011; Grulke, 2011), and co‐infection by multiple pathogens.…”

Section: Redefining Specificity In Belowground Plant–microbial Associ...mentioning

confidence: 99%

Deciphering the role of specialist and generalist plant–microbial interactions as drivers of plant–soil feedback

et al. 2022

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Introduction: host specificity as the key assumption in plant-soil feedback research 1930 II. How prevalent is host specificity in belowground plant-microbial associations? 1932 III. Redefining specificity in belowground plant-microbial associations 1933 IV. Plant-pathogen interactions as drivers of PSF 1933 V. Mutualistic interactions as drivers of PSF 1935 VI. Soil microbial decomposers as drivers of PSF 1936 VII. Synthesis: mapping plant-microbial interactions and resulting PSFs onto major axes of variation in plant form and function 1937 VIII. Future directions 1939 Acknowledgements 1940 References 1940

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Section: Redefining Specificity In Belowground Plant–microbial Associ...mentioning

confidence: 99%

Deciphering the role of specialist and generalist plant–microbial interactions as drivers of plant–soil feedback

et al. 2022

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“…Soil-borne fungal diseases in natural grasslands are rarely observed, either because the disease incidence is low in higher diversity communities or other species replace the poorly performing species before they have a significant effect ( Gilbert, 2002 ; Burdon et al., 2006 ; Alexander, 2010 ). Soil-borne pathogens in grasslands are highly diverse due to the overall high species diversity and the genotype diversity for a given species ( Termorshuizen, 2014 ; Dassen et al., 2017 ; Yang et al., 2017 ; Bach et al., 2018 ). Although plant root systems in grasslands are colonized by a wide variety of fungi, only a few have been isolated and had their pathogenicity thoroughly examined through Koch’s postulates ( Vandenkoornhuyse et al., 2002 ).…”

Section: Soil-borne Fungal Pathogens In Grasslandsmentioning

confidence: 99%

Fungal Pathogens in Grasslands

Karunarathna

Tibpromma

Jayawardena

et al. 2021

Front. Cell. Infect. Microbiol.

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Grasslands are major primary producers and function as major components of important watersheds. Although a concise definition of grasslands cannot be given using a physiognomic or structural approach, grasslands can be described as vegetation communities experiencing periodical droughts and with canopies dominated by grasses and grass-like plants. Grasslands have a cosmopolitan distribution except for the Antarctic region. Fungal interactions with grasses can be pathogenic or symbiotic. Herbivorous mammals, insects, other grassland animals, and fungal pathogens are known to play important roles in maintaining the biomass and biodiversity of grasslands. Although most pathogenicity studies on the members of Poaceae have been focused on economically important crops, the plant-fungal pathogenic interactions involved can extend to the full range of ecological circumstances that exist in nature. Hence, it is important to delineate the fungal pathogen communities and their interactions in man-made monoculture systems and highly diverse natural ecosystems. A better understanding of the key fungal players can be achieved by combining modern techniques such as next-generation sequencing (NGS) together with studies involving classic phytopathology, taxonomy, and phylogeny. It is of utmost importance to develop experimental designs that account for the ecological complexity of the relationships between grasses and fungi, both above and below ground. In grasslands, loss in species diversity increases interactions such as herbivory, mutualism, predation or infectious disease transmission. Host species density and the presence of heterospecific host species, also affect the disease dynamics in grasslands. Many studies have shown that lower species diversity increases the severity as well as the transmission rate of fungal diseases. Moreover, communities that were once highly diverse but have experienced decreased species richness and dominancy have also shown higher pathogenicity load due to the relaxed competition, although this effect is lower in natural communities. This review addresses the taxonomy, phylogeny, and ecology of grassland fungal pathogens and their interactions in grassland ecosystems.

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“…Live soil contains a variety of organisms, large ones like earthworms, ants, and larvae and microbial ones like protozoa, bacteria, and fungi. Some of those organisms will affect plant chemical composition, either by mutualistic effects such as providing nutrients, producing growth hormones, suppressing diseases ( Hol et al, 2014 ) or by pathogenic interactions, which damage plant tissue and could trigger the plants’ defense system ( Termorshuizen, 2014 ). Variation in the plant’s chemical composition can be detected by high-resolution spectroscopy ( Asner and Martin, 2008 ; Ramoelo et al, 2012 ; Carvalho et al, 2013a , b ; Kokaly and Skidmore, 2015 ).…”

Section: Introductionmentioning

confidence: 99%

The Potential of Hyperspectral Patterns of Winter Wheat to Detect Changes in Soil Microbial Community Composition

2016

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Reliable information on soil status and crop health is crucial for detecting and mitigating disasters like pollution or minimizing impact from soil-borne diseases. While infestation with an aggressive soil pathogen can be detected via reflected light spectra, it is unknown to what extent hyperspectral reflectance could be used to detect overall changes in soil biodiversity. We tested the hypotheses that spectra can be used to (1) separate plants growing with microbial communities from different farms; (2) to separate plants growing in different microbial communities due to different land use; and (3) separate plants according to microbial species loss. We measured hyperspectral reflectance patterns of winter wheat plants growing in sterilized soils inoculated with microbial suspensions under controlled conditions. Microbial communities varied due to geographical distance, land use and microbial species loss caused by serial dilution. After 3 months of growth in the presence of microbes from the two different farms plant hyperspectral reflectance patterns differed significantly from each other, while within farms the effects of land use via microbes on plant reflectance spectra were weak. Species loss via dilution on the other hand affected a number of spectral indices for some of the soils. Spectral reflectance can be indicative of differences in microbial communities, with the Renormalized Difference Vegetation Index the most common responding index. Also, a positive correlation was found between the Normalized Difference Vegetation Index and the bacterial species richness, which suggests that plants perform better with higher microbial diversity. There is considerable variation between the soil origins and currently it is not possible yet to make sufficient reliable predictions about the soil microbial community based on the spectral reflectance. We conclude that measuring plant hyperspectral reflectance has potential for detecting changes in microbial communities yet due to its sensitivity high replication is necessary and a strict sampling design to exclude other ‘noise’ factors.

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Root Pathogens

Cited by 13 publications

References 66 publications

Deciphering the role of specialist and generalist plant–microbial interactions as drivers of plant–soil feedback

Deciphering the role of specialist and generalist plant–microbial interactions as drivers of plant–soil feedback

Fungal Pathogens in Grasslands

The Potential of Hyperspectral Patterns of Winter Wheat to Detect Changes in Soil Microbial Community Composition

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