A synthesis of empirical plant dispersal kernels

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985939%3A_____%2F17%3A00478128" target="_blank" >RIV/67985939:_____/17:00478128 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1111/1365-2745.12666" target="_blank" >http://dx.doi.org/10.1111/1365-2745.12666</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1111/1365-2745.12666" target="_blank" >10.1111/1365-2745.12666</a>

Result language

angličtina

Original language name

A synthesis of empirical plant dispersal kernels

Original language description

We synthesized empirical data describing seed dispersal and fitting general dispersal kernels representing major plant types and dispersal modes. * A comprehensive literature search resulted in 107 papers describing 168 dispersal kernels for 144 vascular plant species. The data covered 63 families, all the continents except Antarctica, and the broad vegetation types of forest, grassland, shrubland and more open habitats (e.g. deserts). We classified kernels in terms of dispersal mode (ant, ballistic, rodent, vertebrates other than rodents, vehicle or wind), plant growth form (climber, graminoid, herb, shrub or tree), seed mass and plant height. We fitted 11 widely used probability density functions to each of the 168 data sets to provide a statistical description of the dispersal kernel. The exponential power (ExP) and log-sech (LogS) functions performed best. Other 2-parameter functions varied in performance. For example, the log-normal and Weibull performed poorly, while the 2Dt and power law performed moderately well. Of the single-parameter functions, the Gaussian performed very poorly, while the exponential performed better. No function was among the best-fitting for all data sets. * For 10 plant growth form/dispersal mode combinations for which we had >3 data sets, we fitted ExP and LogS functions across multiple data sets to provide generalized dispersal kernels. We also fitted these functions to subdivisions of these growth form/dispersal mode combinations in terms of seed mass (for animal-dispersed seeds) or plant height (wind-dispersed) classes. These functions provided generally good fits to the grouped data sets, despite variation in empirical methods, local conditions, vegetation type and the exact dispersal process. Potential uses of our synthesis include the following: (i) choosing appropriate dispersal functions in mathematical models, (ii) selecting informative dispersal kernels for one's empirical study system, and (iii) using representative disper

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10618 - Ecology

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2017

Confidentiality

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

Name of the periodical

Journal of Ecology

ISSN

0022-0477

e-ISSN

—

Volume of the periodical

105

Issue of the periodical within the volume

1

Country of publishing house

GB - UNITED KINGDOM

Number of pages

14

Pages from-to

6-19

UT code for WoS article

000390331000002

EID of the result in the Scopus database

2-s2.0-85006173289