Published November 2021 | Version v1
Journal article

Abundance of Ganoderma sp. in Europe and SW Asia: modelling the pathogen infection levels in local trees using the proxy of airborne fungal spore concentrations

  • 1. Institute of Biology, University of Szczecin, 13 Wąska Street, 71-415 Szczecin (Poland)
  • 2. Department of Systematic and Environmental Botany, Laboratory of Biological Spatial Information, Faculty of Biology, Adam Mickiewicz University, Uniwersytetu Poznańskiego 6, 61-614 Poznań (Poland)
  • 3. Institute of Marine and Environmental Sciences, University of Szczecin, 70-383 Szczecin (Poland)
  • 4. Institute of Geoecology and Geoinformation, Adam Mickiewicz University, 10 Krygowskiego Street, 61-680 Poznań (Poland)
  • 5. Madeira University, Faculty of Life Sciences, Campus Universitário da Penteada, 9020-105 Funchal (Portugal)

Description

Highlights: • The locations of potential pathogen host areas were identified for each study site. • A new Pathogen Infection Level Index is developed to assess relative pathogen abundance. • Local thermal variables were most important to predict airborne Ganoderma spore concentrations. • Whilst local sources of Ganoderma spores are a major source, long-distance transport is also a factor at some sites. • UK woodlands were more severely infected with Ganoderma species than the other sites investigated. Ganoderma comprises a common bracket fungal genus that causes basal stem rot in deciduous and coniferous trees and palms, thus having a large economic impact on forestry production. We estimated pathogen abundance using long-term, daily spore concentration data collected in five biogeographic regions in Europe and SW Asia. We hypothesized that pathogen abundance in the air depends on the density of potential hosts (trees) in the surrounding area, and that its spores originate locally. We tested this hypothesis by (1) calculating tree cover density, (2) assessing the impact of local meteorological variables on spore concentration, (3) computing back trajectories, (4) developing random forest models predicting daily spore concentration. The area covered by trees was calculated based on Tree Density Datasets within a 30 km radius from sampling sites. Variations in daily and seasonal spore concentrations were cross-examined between sites using a selection of statistical tools including HYSPLIT and random forest models. Our results showed that spore concentrations were higher in Northern and Central Europe than in South Europe and SW Asia. High and unusually high spore concentrations (> 90th and > 98th percentile, respectively) were partially associated with long distance transported spores: at least 33% of Ganoderma spores recorded in Madeira during days with high concentrations originated from the Iberian Peninsula located >900 km away. Random forest models developed on local meteorological data performed better in sites where the contribution of long distance transported spores was lower. We found that high concentrations were recorded in sites with low host density (Leicester, Worcester), and low concentrations in Kastamonu with high host density. This suggests that south European and SW Asian forests may be less severely affected by Ganoderma. This study highlights the effectiveness of monitoring airborne Ganoderma spore concentrations as a tool for assessing local Ganoderma pathogen infection levels.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.scitotenv.2021.148509

Additional details

Identifiers

DOI
10.1016/j.scitotenv.2021.148509;
PII
S0048969721035816;

Publishing Information

Journal Title
Science of the Total Environment
Journal Volume
793
Journal Page Range
vp.
ISSN
0048-9697
CODEN
STENDL

INIS

Country of Publication
Netherlands
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
54058517
Subject category
S54: ENVIRONMENTAL SCIENCES;
Descriptors DEI
COMPUTERIZED SIMULATION; ECOLOGICAL CONCENTRATION; FORESTRY; FORESTS; SAMPLING; SPORES
Descriptors DEC
SIMULATION

Optional Information

Copyright
Copyright (c) 2021 Elsevier B.V. All rights reserved.