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dc.contributor.author
Graham, Stuart I.
dc.contributor.author
Rokem, Ariel
dc.contributor.author
Ris Lambers, Janneke Hille
dc.date.accessioned
2022-10-05T06:32:14Z
dc.date.available
2022-07-28T03:20:58Z
dc.date.available
2022-08-10T09:25:14Z
dc.date.available
2022-10-05T06:32:14Z
dc.date.issued
2022-10
dc.identifier.issn
0906-7590
dc.identifier.issn
1600-0587
dc.identifier.other
10.1111/ecog.06223
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/560513
dc.identifier.doi
10.3929/ethz-b-000560513
dc.description.abstract
Stem-mapped forest stands offer important opportunities for investigating the fine-scale spatial processes occurring in forest ecosystems. These stands are areas of the forest where the precise locations and repeated size measurements of each tree are recorded, thereby enabling the calculation of spatially-explicit metrics of individual growth rates and of the entire tree community. The most common use of these datasets is to investigate the drivers of variation in forest processes by modeling tree growth rate or mortality as a function of these neighborhood metrics. However, neighborhood metrics could also serve as important covariates of many other spatially variable forest processes, including seedling recruitment, herbivory and soil microbial community composition. Widespread use of stem-mapped forest stand datasets is currently hampered by the lack of standardized, efficient and easy-to-use tools to calculate tree dynamics (e.g. growth, mortality) and the neighborhood metrics that impact them. We present the forestexplorR package that facilitates the munging, exploration, visualization and analysis of stem-mapped forest stands. By providing flexible, user-friendly functions that calculate neighborhood metrics and implement a recently-developed rapid-fitting tree growth and mortality model, forestexplorR broadens the accessibility of stem-mapped forest stand data. We demonstrate the functionality of forestexplorR by using it to investigate how the species identity of neighboring trees influences the growth rates of three common tree species in Mt Rainier National Park, WA, USA. forestexplorR is designed to facilitate researchers to incorporate spatially-explicit descriptions of tree communities in their studies and we expect this increased diversity of contributors to develop exciting new ways of using stem-mapped forest stand data.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Wiley
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/3.0/
dc.subject
forest stand
en_US
dc.subject
mortality
en_US
dc.subject
neighborhood model
en_US
dc.subject
tree density
en_US
dc.subject
tree growth
en_US
dc.subject
visualization
en_US
dc.title
forestexplorR: an R package for the exploration and analysis of stem-mapped forest stand data
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 3.0 Unported
dc.date.published
2022-07-20
ethz.journal.title
Ecography
ethz.journal.volume
2022
en_US
ethz.journal.issue
10
en_US
ethz.pages.start
e06223
en_US
ethz.size
10 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.publication.place
Hoboken, NJ
en_US
ethz.publication.status
published
en_US
ethz.date.deposited
2022-07-28T03:21:22Z
ethz.source
WOS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2022-10-05T06:32:15Z
ethz.rosetta.lastUpdated
2022-10-05T06:32:15Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
ethz.COinS
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