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"Flower power": How flowering affects spectral diversity metrics and their relationship with plant diversity

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12310%2F24%3A43909508" target="_blank" >RIV/60076658:12310/24:43909508 - isvavai.cz</a>

  • Nalezeny alternativní kódy

    RIV/60460709:41330/24:98466

  • Výsledek na webu

    <a href="https://www.sciencedirect.com/science/article/pii/S1574954124001316?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1574954124001316?via%3Dihub</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.ecoinf.2024.102589" target="_blank" >10.1016/j.ecoinf.2024.102589</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    "Flower power": How flowering affects spectral diversity metrics and their relationship with plant diversity

  • Popis výsledku v původním jazyce

    Biodiversity monitoring is constrained by cost- and labour-intensive field sampling methods. Increasing evidence suggests that remotely sensed spectral diversity (SD) is linked to plant diversity, holding promise for monitoring applications. However, studies testing such a relationship reported conflicting findings, especially in challenging ecosystems such as grasslands, due to their variety and high temporal dynamism. It follows that a thorough investigation of the key factors influencing these relationships, such as the metrics applied (i.e., continuous, categorical) and phenology (e.g., flowering), is necessary. The present study aims to assess the effect of flowering on the applicability of six different SD metrics for plant diversity monitoring at the local scale and to investigate how spatial resolution affects the results. Taxonomic diversity was calculated based on data collected in 159 plots of 1.5 m x 1.5 m with experimental mesic grassland communities. Spectral information was collected using a UAV-borne sensor measuring reflectance across six bands in the visible and near-infrared range at similar to 2 cm spatial resolution. Our results showed that, in the presence of flowering, the relationship between SD and plant diversity is significant and positive only when SD is calculated using categorical metrics. Despite the observed significance, the variance explained by the models was very low, with no evident differences when resampling spectral data to coarser pixel sizes. Such findings suggest that new insights into the possible confounding effects on the SD-plant diversity relationship in grassland communities are needed to use SD for monitoring purposes.

  • Název v anglickém jazyce

    "Flower power": How flowering affects spectral diversity metrics and their relationship with plant diversity

  • Popis výsledku anglicky

    Biodiversity monitoring is constrained by cost- and labour-intensive field sampling methods. Increasing evidence suggests that remotely sensed spectral diversity (SD) is linked to plant diversity, holding promise for monitoring applications. However, studies testing such a relationship reported conflicting findings, especially in challenging ecosystems such as grasslands, due to their variety and high temporal dynamism. It follows that a thorough investigation of the key factors influencing these relationships, such as the metrics applied (i.e., continuous, categorical) and phenology (e.g., flowering), is necessary. The present study aims to assess the effect of flowering on the applicability of six different SD metrics for plant diversity monitoring at the local scale and to investigate how spatial resolution affects the results. Taxonomic diversity was calculated based on data collected in 159 plots of 1.5 m x 1.5 m with experimental mesic grassland communities. Spectral information was collected using a UAV-borne sensor measuring reflectance across six bands in the visible and near-infrared range at similar to 2 cm spatial resolution. Our results showed that, in the presence of flowering, the relationship between SD and plant diversity is significant and positive only when SD is calculated using categorical metrics. Despite the observed significance, the variance explained by the models was very low, with no evident differences when resampling spectral data to coarser pixel sizes. Such findings suggest that new insights into the possible confounding effects on the SD-plant diversity relationship in grassland communities are needed to use SD for monitoring purposes.

Klasifikace

  • Druh

    J<sub>imp</sub> - Článek v periodiku v databázi Web of Science

  • CEP obor

  • OECD FORD obor

    10618 - Ecology

Návaznosti výsledku

  • Projekt

  • Návaznosti

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Ostatní

  • Rok uplatnění

    2024

  • Kód důvěrnosti údajů

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

Údaje specifické pro druh výsledku

  • Název periodika

    Ecological Informatics

  • ISSN

    1574-9541

  • e-ISSN

    1878-0512

  • Svazek periodika

    81

  • Číslo periodika v rámci svazku

    JUL 2024

  • Stát vydavatele periodika

    NL - Nizozemsko

  • Počet stran výsledku

    9

  • Strana od-do

  • Kód UT WoS článku

    001229138200001

  • EID výsledku v databázi Scopus

    2-s2.0-85189919892