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Učinek izbiralnega redčenja na prostorsko razmestitev dreves
ID Kokovnik, Gaber (Author), ID Ficko, Andrej (Mentor) More about this mentor... This link opens in a new window

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Abstract
V diplomski nalogi smo proučevali vzorce razmestitve dreves ter njihovo spreminjanje v redčenih in neredčenih sestojih. Želeli smo ugotoviti, v kolikšni meri z izbiralnimi redčenji pospešujemo enakomerno porazdelitev dreves in izbrancev. V raziskovalnem objektu Pišece smo analizirali začetno ter končno stanje ploskve, predvidene za izbiralno redčenje, njene koordinate so [N: 46° 00,311', E: 15° 36,048'], in ploskve, kjer ukrepanje ni bilo predvideno, njene koordinate so [N: 46° 00,282', E: 15° 35,814']. Prva meritev je bila opravljena leta 2009, druga leta 2021. Za analizo smo uporabili različne načine vizualizacije prostorske razmestitve dreves, centrografijo ter nekaj najpogosteje uporabljenih kazalnikov razmestitev in testov (npr. Ripleyeve funkcije, Clark-Evansov indeks). Analizo in vizualizacijo podatkov smo opravili s pomočjo programskega jezika Python. Obe ploskvi sta imeli na začetku nekoliko agregiran prostorski vzorec, ki pa je bil na redčeni ploskvi po izvedenem redčenju leta 2021 popolnoma odstranjen. Vzorec na redčeni ploskvi je postal popolnoma prostorsko naključen. Na kontrolni ploskvi pa je po 12 letih zaradi zelo majhne mortalitete vzorec ostal nespremenjen. Zaradi tega sklepamo, da redčenje pospešuje razvoj prostorske razmestitve, tako da zmanjšuje agregiranost in poveča razdalje med najbližjimi sosedi. Na ploskvi, na kateri je bilo opravljeno izbiralno redčenje, so bili do-ločeni tudi izbranci, tako za leto 2009 kot tudi 2021. Zanje smo ugotovili, da so bili 2009 razporejeni enakomerno, po redčenju je vzorec ostal bolj ali manj nespremenjen. To kaže na pomen redčenja za izkoriščenost rastiščnega potenciala.

Language:Slovenian
Keywords:prostorski vzorec točk, točkovni proces, prostorska razmestitev dreves, naključna razmestitev, gručasta razmestitev, enakomerna razmestitev
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:BF - Biotechnical Faculty
Publisher:[G. Kokovnik]
Year:2023
PID:20.500.12556/RUL-149256 This link opens in a new window
UDC:630*2:630*6(043.2)=163.6
COBISS.SI-ID:163431939 This link opens in a new window
Publication date in RUL:06.09.2023
Views:719
Downloads:85
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Secondary language

Language:English
Title:The effect of selective thinning on the spatial distribution of trees
Abstract:
The purpose of this thesis was to examine the spatial point pattern of trees in thinned and naturally developing stands and to test the effect of thinning on a regular spatial pattern. Two plots were analyzed, and two measurements were carried out for each of them, the first in 2009, showing the state of the plots before the thinning, and the second in 2021, showing the state of the plots after the thinning. On one of the plots selective thinning was to be carried out, the coordinates of which are [N: 46°00,311', E: 15°36,048'], and the other was meant as a control, with coordinates [N: 46°00,282', E: 15°35,814'], so no type of thinning was applied to it. The analysis and visualization were done with the programing language Python. We compared the state of the plots before and after the thinning and found that the two plots were somewhat aggregated in 2009. After the thinning on one of the plots in 2021, the signs of aggregation were removed, and the spatial pattern was now completely spatially random. On the other hand, the changes between the plot in 2009 and in 2021 for the control plot were basically nonexistent. This leads us to believe that thinning accelerates the development of a spatial pattern of trees in a stand, such that it decreases aggregation and increases nearest neighbor distances. On the plot where selective thinning was carried out, selected trees were also determined for both 2009 and 2023. We found they were evenly distributed, and after the thinning, the spatial pattern did not become more even, nor did it become more random but remained virtually unchanged.

Keywords:spatial point pattern, point process, spatial distribution of trees, random spatial distribution, clustered spatial distribution, even spatial distribution

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