The ADnet Bayesian belief network for alder decline: Integrating empirical data and expert knowledge

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43410%2F24%3A43925234" target="_blank" >RIV/62156489:43410/24:43925234 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1016/j.scitotenv.2024.173619" target="_blank" >https://doi.org/10.1016/j.scitotenv.2024.173619</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.scitotenv.2024.173619" target="_blank" >10.1016/j.scitotenv.2024.173619</a>

Jazyk výsledku

angličtina

Název v původním jazyce

The ADnet Bayesian belief network for alder decline: Integrating empirical data and expert knowledge

Popis výsledku v původním jazyce

The globalization in plant material trading has caused the emergence of invasive pests in many ecosystems, such as the alder pathogen Phytophthora xalni in European riparian forests. Due to the ecological importance of alder to the functioning of rivers and the increasing incidence of P. xalni-induced alder decline, effective and accessible decision tools are required to help managers and stakeholders control the disease. This study proposes a Bayesian belief network methodology to integrate diverse information on the factors affecting the survival and infection ability of P. xalni in riparian habitats to help predict and manage disease incidence. The resulting Alder Decline Network (ADnet) management tool integrates information about alder decline from scientific literature, expert knowledge and empirical data. Expert knowledge was gathered through elicitation techniques that included 19 experts from 12 institutions and 8 countries. An original dataset was created covering 1189 European locations, from which P. xalni occurrence was modeled based on bioclimatic variables. ADnet uncertainty was evaluated through its sensitivity to changes in states and three scenario analyses. The ADnet tool indicated that mild temperatures and high precipitation are key factors favoring pathogen survival. Flood timing, water velocity, and soil type have the strongest influence on disease incidence. ADnet can support ecosystem management decisions and knowledge transfer to address P. xalni-induced alder decline at local or regional levels across Europe. Management actions such as avoiding the planting of potentially infected trees or removing man-made structures that increase the flooding period in disease-affected sites could decrease the incidence of alder disease in riparian forests and limit its spread. The coverage of the ADnet tool can be expanded by updating data on the pathogen&apos;s occurrence, particularly from its distributional limits. Research on the role of genetic variability in alder susceptibility and pathogen virulence may also help improve future ADnet versions.

Název v anglickém jazyce

The ADnet Bayesian belief network for alder decline: Integrating empirical data and expert knowledge

Popis výsledku anglicky

The globalization in plant material trading has caused the emergence of invasive pests in many ecosystems, such as the alder pathogen Phytophthora xalni in European riparian forests. Due to the ecological importance of alder to the functioning of rivers and the increasing incidence of P. xalni-induced alder decline, effective and accessible decision tools are required to help managers and stakeholders control the disease. This study proposes a Bayesian belief network methodology to integrate diverse information on the factors affecting the survival and infection ability of P. xalni in riparian habitats to help predict and manage disease incidence. The resulting Alder Decline Network (ADnet) management tool integrates information about alder decline from scientific literature, expert knowledge and empirical data. Expert knowledge was gathered through elicitation techniques that included 19 experts from 12 institutions and 8 countries. An original dataset was created covering 1189 European locations, from which P. xalni occurrence was modeled based on bioclimatic variables. ADnet uncertainty was evaluated through its sensitivity to changes in states and three scenario analyses. The ADnet tool indicated that mild temperatures and high precipitation are key factors favoring pathogen survival. Flood timing, water velocity, and soil type have the strongest influence on disease incidence. ADnet can support ecosystem management decisions and knowledge transfer to address P. xalni-induced alder decline at local or regional levels across Europe. Management actions such as avoiding the planting of potentially infected trees or removing man-made structures that increase the flooding period in disease-affected sites could decrease the incidence of alder disease in riparian forests and limit its spread. The coverage of the ADnet tool can be expanded by updating data on the pathogen&apos;s occurrence, particularly from its distributional limits. Research on the role of genetic variability in alder susceptibility and pathogen virulence may also help improve future ADnet versions.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10612 - Mycology

Projekt

<a href="/cs/project/EF15_003%2F0000453" target="_blank" >EF15_003/0000453: Výzkumné centrum pro studium patogenů z rodu Phytophthora</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Science of the Total Environment

ISSN

0048-9697

e-ISSN

1879-1026

Svazek periodika

947

Číslo periodika v rámci svazku

15 October

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

15

Strana od-do

173619

Kód UT WoS článku

001270516700001

EID výsledku v databázi Scopus

2-s2.0-85198028751