<b>Spatial structure of a soil-borne fungal plant pathogen in an untilled grassland: insights using new analytical tools</b>

Understanding the link between spatial patterns of soil-borne fungal plant pathogens (SFPP) and environmental conditions is an important first step to understanding how these organisms impact both agricultural and untilled systems. However, the vast majority of SFPP spatial patterns studies have occurred in agricultural systems and relied on basic statistical measures of variance. Recent statistical advancements in spatial analysis combined with resampling strategies allow increased insight into spatial patterns but require robust sampling designs. Here, we begin to address this knowledge gap for Macrophomina phaseolina by quantifying its spatial pattern at multiple spatial scales in an untilled grassland system in Riley County, Kansas, U.S.A, and relate these patterns to soil and plant variables. Using microsclerotia density as a measure of M. phaseolina abundance, we found considerable spatial variability in untilled soil, even at a scale much finer than historically sampled for M. phaseolina scales (7 cm). We utilized point pattern analysis to examine how densities are arranged in space, and we found no evidence of spatial aggregation. Rather, M. phaseolina density was randomly distributed and did not strongly associate with any measured soil or plant variables. Our findings contrast with previous work detecting aggregation of M. phaseolina likely due to our use of more robust, spatially explicit statistics that examine multiple scales as well as the ecological dichotomy between untilled grassland systems and row-crop agricultural systems. Additionally, the fact that high spatial variation of M. phaseolina over small scales was poorly explained by plant or soil variables suggests that a better understanding of temporal variation can aid in identifying factors that most influence M. phaseolina abundance.

Publication Details

Journal
Figshare
Published
2025-01-09
DOI
https://doi.org/10.6084/m9.figshare.28175510
Primary Topic
Plant Disease Management Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Spatial structure of a soil-borne fungal plant pathogen in an untilled grassland: insights using new analytical tools

Figshare
Plant Disease Management Techniques
article

Spatial structure of a soil-borne fungal plant pathogen in an untilled grassland: insights using new analytical tools

article en

Abstract

Understanding the link between spatial patterns of soil-borne fungal plant pathogens (SFPP) and environmental conditions is an important first step to understanding how these organisms impact both agricultural and untilled systems. However, the vast majority of SFPP spatial patterns studies have occurred in agricultural systems and relied on basic statistical measures of variance. Recent statistical advancements in spatial analysis combined with resampling strategies allow increased insight into spatial patterns but require robust sampling designs. Here, we begin to address this knowledge gap for Macrophomina phaseolina by quantifying its spatial pattern at multiple spatial scales in an untilled grassland system in Riley County, Kansas, U.S.A, and relate these patterns to soil and plant variables. Using microsclerotia density as a measure of M. phaseolina abundance, we found considerable spatial variability in untilled soil, even at a scale much finer than historically sampled for M. phaseolina scales (7 cm). We utilized point pattern analysis to examine how densities are arranged in space, and we found no evidence of spatial aggregation. Rather, M. phaseolina density was randomly distributed and did not strongly associate with any measured soil or plant variables. Our findings contrast with previous work detecting aggregation of M. phaseolina likely due to our use of more robust, spatially explicit statistics that examine multiple scales as well as the ecological dichotomy between untilled grassland systems and row-crop agricultural systems. Additionally, the fact that high spatial variation of M. phaseolina over small scales was poorly explained by plant or soil variables suggests that a better understanding of temporal variation can aid in identifying factors that most influence M. phaseolina abundance.

Figshare
Zero hunger
Openalex Percentile: Top 35%
Plant Disease Management Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.