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Uncertainty in the detection of disturbance spatial patterns in temperate forests

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00027073%3A_____%2F16%3AN0000019" target="_blank" >RIV/00027073:_____/16:N0000019 - isvavai.cz</a>

  • Alternative codes found

    RIV/62156489:43410/16:43910762

  • Result on the web

    <a href="http://www.sciencedirect.com/science/article/pii/S1125786515000892" target="_blank" >http://www.sciencedirect.com/science/article/pii/S1125786515000892</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.dendro.2015.12.002" target="_blank" >10.1016/j.dendro.2015.12.002</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Uncertainty in the detection of disturbance spatial patterns in temperate forests

  • Original language description

    The use of individual-based models in the study of the spatial patterns of disturbances has opened new horizons in forest ecosystem research. However, no studies so far have addressed (i) the uncertainty in geostatistical modelling of the spatial relationships in dendrochronological data, (ii) the number of increment cores necessary to study disturbance spatial patterns, and (iii) the choice of an appropriate geostatistical model in relation to disturbance regime. In addressing these issues, we hope to contribute to advances in research methodology as well as to improve interpretations and generalizations from case studies. We used data from the beech-dominated Žofínský Prales forest reserve (Czech Republic), where we cored 3020 trees on 74 ha. Block bootstrap and geostatistics were applied to the data, which covered five decades with highly different disturbance histories. This allowed us to assess the general behavior of various mathematical models. Uncertainty in the spatial patterns and stability of the models was measured as the length of the 95% confidence interval (CI) of model parameters. The results suggest that with a sample size of 1000–1400 cores and a properly chosen model, one reaches a certain precision in estimation that does not increase significantly with growing sample size. It appears that in temperate old-growth forests controlled by fine-scale disturbances, it is necessary to have at least 500 cores to estimate sill, nugget and relative nugget, while to estimate practical range at least 1000 cores are needed. When choosing the best model, the stability of the model should be considered together with the value of AIC. Our results indicate the general limits of disturbance spatial pattern studies using dendrochronological and geostatistical methods, which can be only partially overcome by sample size or sampling design.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    GK - Forestry

  • OECD FORD branch

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2016

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    DENDROCHRONOLOGIA

  • ISSN

    1125-7865

  • e-ISSN

  • Volume of the periodical

    37

  • Issue of the periodical within the volume

    March 2016

  • Country of publishing house

    DE - GERMANY

  • Number of pages

    11

  • Pages from-to

    46-56

  • UT code for WoS article

    000386868300005

  • EID of the result in the Scopus database