Predicting plant species richness in forested landslide zones using geostatistical methods
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F21%3A73608838" target="_blank" >RIV/61989592:15310/21:73608838 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S1470160X21009626" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1470160X21009626</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ecolind.2021.108297" target="_blank" >10.1016/j.ecolind.2021.108297</a>
Alternative languages
Result language
angličtina
Original language name
Predicting plant species richness in forested landslide zones using geostatistical methods
Original language description
andslides, like most natural disturbances, facilitate the evolution of new plant species. Hence, a detail characterization of topographic conditions can improve the prediction and mapping of species in such complex terrains. Within the Outer (Flysch) Upper Carpathian region, south Poland, we analyze the role of convergence points prepared in a previous study from slope and slope exposition (aspect) data, derived from a 1 m digital elevation model. Convergence points reflected microscale variability in topographic conditions and were analyzed in this study as convergence point density (CPD). Our objective was to use CPD to predict species richness on forested landslides using three geostatistical methods; Ordinary kriging (OK), Ordinary cokriging (OCK), and regression kriging (RK). Our results showed a relatively high correlation (r similar to 0.65) between species richness and CPD compared to slope or slope exposition or with both. OCK and RK generally improved prediction. However, the application of cokriging in such terrains remains challenging and will not be appropriate, particularly if species richness has a small sample size. RK outperformed OK and OCK, decreasing the root mean square error (RMSE) by 33% and 10%, respectively. RK was also more robust to topographic heterogeneity and the limited number of observations than OCK. We conclude that a denser sampling of species composition or a more robust indicator is needed to improve these results. Notwithstanding these limitations, our results can be used as the first step to support short-term conservation efforts, especially when time-dependent changes in species composition are unimportant.
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
10511 - Environmental sciences (social aspects to be 5.7)
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
Ecological Indicators
ISSN
1470-160X
e-ISSN
—
Volume of the periodical
132
Issue of the periodical within the volume
DEC
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
11
Pages from-to
"108297-1"-"108297-11"
UT code for WoS article
000710621100007
EID of the result in the Scopus database
2-s2.0-85117391050