This HTML5 document contains 62 embedded RDF statements represented using HTML+Microdata notation.

The embedded RDF content will be recognized by any processor of HTML5 Microdata.

Namespace Prefixes

PrefixIRI
n11http://linked.opendata.cz/resource/domain/vavai/vysledek/RIV%2F00027073%3A_____%2F13%3A%230001515%21RIV14-MZP-00027073/
dctermshttp://purl.org/dc/terms/
n19http://linked.opendata.cz/resource/domain/vavai/projekt/
n5http://linked.opendata.cz/resource/domain/vavai/riv/tvurce/
n10http://linked.opendata.cz/resource/domain/vavai/subjekt/
n9http://linked.opendata.cz/ontology/domain/vavai/
n21http://linked.opendata.cz/resource/domain/vavai/zamer/
shttp://schema.org/
rdfshttp://www.w3.org/2000/01/rdf-schema#
skoshttp://www.w3.org/2004/02/skos/core#
n3http://linked.opendata.cz/ontology/domain/vavai/riv/
n20http://bibframe.org/vocab/
n2http://linked.opendata.cz/resource/domain/vavai/vysledek/
rdfhttp://www.w3.org/1999/02/22-rdf-syntax-ns#
n7http://linked.opendata.cz/ontology/domain/vavai/riv/klicoveSlovo/
n16http://linked.opendata.cz/ontology/domain/vavai/riv/duvernostUdaju/
xsdhhttp://www.w3.org/2001/XMLSchema#
n17http://linked.opendata.cz/ontology/domain/vavai/riv/aktivita/
n4http://linked.opendata.cz/ontology/domain/vavai/riv/jazykVysledku/
n18http://linked.opendata.cz/ontology/domain/vavai/riv/druhVysledku/
n15http://linked.opendata.cz/ontology/domain/vavai/riv/obor/
n8http://reference.data.gov.uk/id/gregorian-year/

Statements

Subject Item
n2:RIV%2F00027073%3A_____%2F13%3A%230001515%21RIV14-MZP-00027073
rdf:type
n9:Vysledek skos:Concept
rdfs:seeAlso
http://onlinelibrary.wiley.com/doi/10.1111/jvs.12018/full
dcterms:description
Questions: What are the differences between the tree spatial patterns (TSP) of various recruit and mortality waves in alluvial hardwood forests and mountain fir–beech forests? Are there any statistically significant differences between the mean TSP of these forest types? Are these differences stable over time? Location: Alluvial floodplain forests at the confluence of the Morava and Dyje rivers, and mountain fir–beech forests in the OuterWestern Carpathians, Czech Republic. Methods: In both forest types, seven 2-ha rectangular plots were analysed. The pair correlation function g(r) was used to describe tree density variability of trees with DBH>=10 cm. The analyses were carried out for data sets fromthe 1970s, 1990s and 2000s. A bootstrap method was used to test for significant differences between themean values of g(r) fromalluvial forests and fromfir–beech forests. Results: Recruits inmountain fir–beech forests revealed consistent clustering to at least 5 m. In alluvial hardwood forests, recruits also showed random distribution as well as occasional regular distribution at distances over 20 m. Bootstrap significance tests revealed significant differences between the mean values of g (r) for alluvial forests and fir–beech forests. Alluvial floodplain forests showed statistically significant stronger clustering up to a distance of 4 m in all study periods. At distances over 20 m,mountain fir–beech forests demonstrated stronger clustering. In the 1970s, this was statistically significant only at a distance of 32 m, but in the 2000s, itwas at intervals of 22–30 and 34–38 m. Conclusions: The methods of data analysis in this study enabled us to find significant features of TSP at finer resolution than the common resulting trichotomy of univariate analysis: clustering, randomness and regularity. We believe that, on the basis of detailed spatial analyses, it is possible to create a TSP model that reflects the typical features of particular forest types. Questions: What are the differences between the tree spatial patterns (TSP) of various recruit and mortality waves in alluvial hardwood forests and mountain fir–beech forests? Are there any statistically significant differences between the mean TSP of these forest types? Are these differences stable over time? Location: Alluvial floodplain forests at the confluence of the Morava and Dyje rivers, and mountain fir–beech forests in the OuterWestern Carpathians, Czech Republic. Methods: In both forest types, seven 2-ha rectangular plots were analysed. The pair correlation function g(r) was used to describe tree density variability of trees with DBH>=10 cm. The analyses were carried out for data sets fromthe 1970s, 1990s and 2000s. A bootstrap method was used to test for significant differences between themean values of g(r) fromalluvial forests and fromfir–beech forests. Results: Recruits inmountain fir–beech forests revealed consistent clustering to at least 5 m. In alluvial hardwood forests, recruits also showed random distribution as well as occasional regular distribution at distances over 20 m. Bootstrap significance tests revealed significant differences between the mean values of g (r) for alluvial forests and fir–beech forests. Alluvial floodplain forests showed statistically significant stronger clustering up to a distance of 4 m in all study periods. At distances over 20 m,mountain fir–beech forests demonstrated stronger clustering. In the 1970s, this was statistically significant only at a distance of 32 m, but in the 2000s, itwas at intervals of 22–30 and 34–38 m. Conclusions: The methods of data analysis in this study enabled us to find significant features of TSP at finer resolution than the common resulting trichotomy of univariate analysis: clustering, randomness and regularity. We believe that, on the basis of detailed spatial analyses, it is possible to create a TSP model that reflects the typical features of particular forest types.
dcterms:title
Spatiotemporal differences in tree spatial patterns between alluvial hardwood and mountain fir–beech forests: do characteristic patterns exist? Spatiotemporal differences in tree spatial patterns between alluvial hardwood and mountain fir–beech forests: do characteristic patterns exist?
skos:prefLabel
Spatiotemporal differences in tree spatial patterns between alluvial hardwood and mountain fir–beech forests: do characteristic patterns exist? Spatiotemporal differences in tree spatial patterns between alluvial hardwood and mountain fir–beech forests: do characteristic patterns exist?
skos:notation
RIV/00027073:_____/13:#0001515!RIV14-MZP-00027073
n9:predkladatel
n10:ico%3A00027073
n3:aktivita
n17:Z n17:P
n3:aktivity
P(GAP504/11/2301), Z(MSM6293359101)
n3:cisloPeriodika
6
n3:dodaniDat
n8:2014
n3:domaciTvurceVysledku
n5:3600416 n5:5253950 n5:6810578 n5:8885540 n5:9534482 n5:3675572 n5:8749051 n5:2524651
n3:druhVysledku
n18:J
n3:duvernostUdaju
n16:S
n3:entitaPredkladatele
n11:predkladatel
n3:idSjednocenehoVysledku
106816
n3:idVysledku
RIV/00027073:_____/13:#0001515
n3:jazykVysledku
n4:eng
n3:klicovaSlova
Bootstrap method; Forest type; Long-term study; Mortality; Natural forest; Pair correlation function; Recruits; Spatial point processes; Trees
n3:klicoveSlovo
n7:Recruits n7:Spatial%20point%20processes n7:Mortality n7:Long-term%20study n7:Forest%20type n7:Trees n7:Bootstrap%20method n7:Natural%20forest n7:Pair%20correlation%20function
n3:kodStatuVydavatele
US - Spojené státy americké
n3:kontrolniKodProRIV
[53D432585D24]
n3:nazevZdroje
Journal of Vegetation Science
n3:obor
n15:GK
n3:pocetDomacichTvurcuVysledku
8
n3:pocetTvurcuVysledku
8
n3:projekt
n19:GAP504%2F11%2F2301
n3:rokUplatneniVysledku
n8:2013
n3:svazekPeriodika
24
n3:tvurceVysledku
Unar, Pavel Král, Kamil Adam, Dušan Janík, David Šamonil, Pavel Horal, David Vrška, Tomáš Hort, Libor
n3:wos
000325370200018
n3:zamer
n21:MSM6293359101
s:issn
1100-9233
s:numberOfPages
13
n20:doi
10.1111/jvs.12018