Predicting plant species richness in forested landslide zones using geostatistical methods

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Predicting plant species richness in forested landslide zones using geostatistical methods

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Predicting plant species richness in forested landslide zones using geostatistical methods

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10511 - Environmental sciences (social aspects to be 5.7)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název periodika

Ecological Indicators

ISSN

1470-160X

e-ISSN

—

Svazek periodika

132

Číslo periodika v rámci svazku

DEC

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

11

Strana od-do

"108297-1"-"108297-11"

Kód UT WoS článku

000710621100007

EID výsledku v databázi Scopus

2-s2.0-85117391050