The total dispersal kernel: a review and future directions

Rogers, Haldre S.; Beckman, Noelle G.; Hartig, Florian; Johnson, Jeremy S.; Pufal, Gesine; Shea, Katriona; Zurell, Damaris; Bullock, James M. ORCID: https://orcid.org/0000-0003-0529-4020; Cantrell, Robert Stephen; Loiselle, Bette; Pejchar, Liba; Razafindratsima, Onja H.; Sandor, Manette E.; Schupp, Eugene W.; Strickland, W. Christopher; Zambrano, Jenny. 2019 The total dispersal kernel: a review and future directions [in special issue: The role of seed dispersal in plant populations: perspectives and advances in a changing world] AoB Plants, 11 (5), plz042. 13, pp. 10.1093/aobpla/plz042

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Official URL: http://dx.doi.org/10.1093/aobpla/plz042

Abstract/Summary

The distribution and abundance of plants across the world depends in part on their ability to move, which is commonly characterized by a dispersal kernel. For seeds, the total dispersal kernel (TDK) describes the combined influence of all primary, secondary and higher-order dispersal vectors on the overall dispersal kernel for a plant individual, population, species or community. Understanding the role of each vector within the TDK, and their combined influence on the TDK, is critically important for being able to predict plant responses to a changing biotic or abiotic environment. In addition, fully characterizing the TDK by including all vectors may affect predictions of population spread. Here, we review existing research on the TDK and discuss advances in empirical, conceptual modelling and statistical approaches that will facilitate broader application. The concept is simple, but few examples of well-characterized TDKs exist. We find that significant empirical challenges exist, as many studies do not account for all dispersal vectors (e.g. gravity, higher-order dispersal vectors), inadequately measure or estimate long-distance dispersal resulting from multiple vectors and/or neglect spatial heterogeneity and context dependence. Existing mathematical and conceptual modelling approaches and statistical methods allow fitting individual dispersal kernels and combining them to form a TDK; these will perform best if robust prior information is available. We recommend a modelling cycle to parameterize TDKs, where empirical data inform models, which in turn inform additional data collection. Finally, we recommend that the TDK concept be extended to account for not only where seeds land, but also how that location affects the likelihood of establishing and producing a reproductive adult, i.e. the total effective dispersal kernel.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.1093/aobpla/plz042
UKCEH and CEH Sections/Science Areas:	Biodiversity (Science Area 2017-)
ISSN:	2041-2851
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
Additional Keywords:	defaunation, dispersal vector, frugivore, mathematical modeling, seed dispersal, seed dispersal effectiveness, total dispersal kernel, total effective dispersal kernel, wind
NORA Subject Terms:	Ecology and Environment Botany
Date made live:	28 Oct 2019 16:11 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/525264

Item Type:

Publication - Article

Digital Object Identifier (DOI):

10.1093/aobpla/plz042

UKCEH and CEH Sections/Science Areas:

Biodiversity (Science Area 2017-)

ISSN:

2041-2851

Additional Information. Not used in RCUK Gateway to Research.:

Open Access paper - full text available via Official URL link.

Additional Keywords:

defaunation, dispersal vector, frugivore, mathematical modeling, seed dispersal, seed dispersal effectiveness, total dispersal kernel, total effective dispersal kernel, wind

NORA Subject Terms:

Ecology and Environment
Botany

Date made live:

28 Oct 2019 16:11 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/525264