. . "http://onlinelibrary.wiley.com/doi/10.1111/jvs.12018/full" . "Unar, Pavel" . "RIV/00027073:_____/13:#0001515" . "8"^^ . "US - Spojen\u00E9 st\u00E1ty americk\u00E9" . . . . . "Kr\u00E1l, Kamil" . . . "8"^^ . "Spatiotemporal differences in tree spatial patterns between alluvial hardwood and mountain fir\u2013beech forests: do characteristic patterns exist?"@en . . "Adam, Du\u0161an" . "Spatiotemporal differences in tree spatial patterns between alluvial hardwood and mountain fir\u2013beech forests: do characteristic patterns exist?" . "13"^^ . "Jan\u00EDk, David" . . "[53D432585D24]" . . "Spatiotemporal differences in tree spatial patterns between alluvial hardwood and mountain fir\u2013beech forests: do characteristic patterns exist?" . "6" . "1100-9233" . . "\u0160amonil, Pavel" . "Horal, David" . "Questions: What are the differences between the tree spatial patterns (TSP) of various recruit and mortality waves in alluvial hardwood forests and mountain fir\u2013beech 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\u2013beech 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\u2013beech forests. Results: Recruits inmountain fir\u2013beech 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\u2013beech 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\u2013beech 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\u201330 and 34\u201338 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."@en . "24" . . . "Vr\u0161ka, Tom\u00E1\u0161" . . "P(GAP504/11/2301), Z(MSM6293359101)" . . "Questions: What are the differences between the tree spatial patterns (TSP) of various recruit and mortality waves in alluvial hardwood forests and mountain fir\u2013beech 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\u2013beech 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\u2013beech forests. Results: Recruits inmountain fir\u2013beech 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\u2013beech 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\u2013beech 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\u201330 and 34\u201338 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." . "Journal of Vegetation Science" . . . . "106816" . "10.1111/jvs.12018" . . . "Spatiotemporal differences in tree spatial patterns between alluvial hardwood and mountain fir\u2013beech forests: do characteristic patterns exist?"@en . . . . . . "000325370200018" . "RIV/00027073:_____/13:#0001515!RIV14-MZP-00027073" . . . "Hort, Libor" . . . "Bootstrap method; Forest type; Long-term study; Mortality; Natural forest; Pair correlation function; Recruits; Spatial point processes; Trees"@en . .