Comparing generalized and customized spread models for nonnative forest pests
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41320%2F20%3A84325" target="_blank" >RIV/60460709:41320/20:84325 - isvavai.cz</a>
Result on the web
<a href="https://esajournals.onlinelibrary.wiley.com/doi/abs/10.1002/eap.1988" target="_blank" >https://esajournals.onlinelibrary.wiley.com/doi/abs/10.1002/eap.1988</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1002/eap.1988" target="_blank" >10.1002/eap.1988</a>
Alternative languages
Result language
angličtina
Original language name
Comparing generalized and customized spread models for nonnative forest pests
Original language description
While generality is often desirable in ecology, customized models for individual species are thought to be more predictive by accounting for context specificity. However, fully customized models require more information for focal species. We focus on pest spread and ask: How much does predictive power differ between generalized and customized models? Further, we examine whether an intermediate semi-generalized model, combining elements of a general model with species-specific modifications, could yield predictive advantages. We compared predictive power of a generalized model applied to all forest pest species (the generalized dispersal kernel or GDK) to customized spread models for three invasive forest pests (beech bark disease Cryptococcus fagisuga, gypsy moth Lymantria dispar, and hemlock woolly adelgid Adelges tsugae), for which time-series data exist. We generated semi-generalized dispersal kernel models (SDK) through GDK correction factors based on additional species-specific information. We f
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10618 - Ecology
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
ECOLOGICAL APPLICATIONS
ISSN
1051-0761
e-ISSN
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Volume of the periodical
30
Issue of the periodical within the volume
1
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
13
Pages from-to
1-13
UT code for WoS article
000505549500024
EID of the result in the Scopus database
2-s2.0-85075423540