Predicting non-native insect impact: focusing on the trees to see the forest
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41320%2F21%3A89578" target="_blank" >RIV/60460709:41320/21:89578 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/article/10.1007/s10530-021-02621-5" target="_blank" >https://link.springer.com/article/10.1007/s10530-021-02621-5</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10530-021-02621-5" target="_blank" >10.1007/s10530-021-02621-5</a>
Alternative languages
Result language
angličtina
Original language name
Predicting non-native insect impact: focusing on the trees to see the forest
Original language description
Non-native organisms have invaded novel ecosystems for centuries, yet we have only a limited understanding of why their impacts vary widely from minor to severe. Predicting the impact of non-established or newly detected species could help focus biosecurity measures on species with the highest potential to cause widespread damage. However, predictive models require an understanding of potential drivers of impact and the appropriate level at which these drivers should be evaluated. Here, we used non-native, specialist herbivorous insects of forest ecosystems to test which factors drive impact and if there were differences based on whether they used woody angiosperms or conifers as hosts. We identified convergent and divergent patterns between the two host types indicating fundamental similarities and differences in their interactions with non-native insects. Evolutionary divergence time between native and novel hosts was a significant driver of insect impact for both host types but was modulated by di
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10616 - Entomology
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Biological Invasions
ISSN
1387-3547
e-ISSN
—
Volume of the periodical
23
Issue of the periodical within the volume
12
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
16
Pages from-to
3921-3936
UT code for WoS article
000691636700002
EID of the result in the Scopus database
2-s2.0-85113928578