Mullastiku ja taimestiku seosed Laeva piirkonna metsa kasvukäigu püsiproovitükkidel
Laen...
Kuupäev
2016
Kättesaadav alates
Autorid
Ajakirja pealkiri
Ajakirja ISSN
Köite pealkiri
Kirjastaja
Abstrakt
1995. aastal hakati rajama Eesti metsa kasvukäigu püsiproovitükke. 2012. aastal tehti
esmakordselt ka alustaimestiku ja muldade uuringuid. Kaks aastat hiljem, 2014. aastal viidi
sellised uuringud läbi naadi kasvukohatüübi puistutes ning 2015. aastal Laeva piirkonnas,
endises Pikknurme metskonnas.
Kuna loodus on väga muutlik, siis kasvukohatüüpe võib olla raske määrata. Käesoleva töö
eesmärgiks on vaadata ühe piirkonna proovitükke mõõdetud puistu- ja mullaandmete põhjal
ning uurida, kas on ka mingeid muid viise kuidas jagada erinevaid püsiproovitükke.
Puistu takseerandmete saamiseks kasutati ringproovitükkide meetodit, samadel aladel viidi
läbi alustaimestiku inventuur ja koostati mullakirjeldused. Andmete töötlemiseks kasutasin
MS Exceli keskkonnas olevat regressioonanalüüsi. Erinevate keskkonnatunnuste,
alustaimestiku, mullanäitajate ja takseerandmete analüüsimiseks kasutasin erinevaid PC-ORD
6 analüüsipakette.
Analüüside käigus selgus, et Laeva piirkonna proovitükid jagunesid mulla- ning
puistuandmete järgi kahte gruppi, mis erinesid varem üles märgitud kasvukohatüübist.
Tulemuse põhjal ei taheta ümber lükata ühtegi klassifikatsiooni meetodit, aga tulemuse põhjal
saab öelda, et ühtegi täpset tulemust ei ole võimalik saada lihtsalt visuaalse määramise teel.
Looduse kiire muutumise tõttu, tuleb õige tulemuse saamiseks teha rohkem tööd, kui lihtsalt
paljas vaatlus.
In 1996, the first forest site sample plots were created in Estonia to researching their growth. The first ground vegetation and soil analyses were carried out in 2012. Two years later, in 2014, similar research was conducted at the forest stands of the Aegopodium forest site type and in 2015, at the former Pikknurme forest district. As nature is constantly changing, classifying forest site types is difficult. The purpose of this thesis is to study permanent sample plots of a single area based on data other than already determined forest site types and to examine other possibilities for classifying permanent sample plots. To acquire the taxation data of the forest stand, a circular systematic method of drawing samples was used, during which an inventory of ground vegetation was conducted and soil excavation performed in order to provide soil descriptions. MS Excel’s regression analysis was used to process the data. Different environmental features, ground vegetation, soil indicators, and taxation data was analysed using different PC-ORD 6 analysis packages. The analyses revealed that many of the sample plots that had been classified as similar forest site types might in fact have been classified incorrectly. Therefore, we decided to analyse and research the continuous data. The conclusion of this thesis does not aim to discredit any method of classification; however, the results revealed that merely visual examination is not sufficient for achieving accurate results. As nature is highly changeable, more research must be done for accurate results and mere visual examination is not enough.
In 1996, the first forest site sample plots were created in Estonia to researching their growth. The first ground vegetation and soil analyses were carried out in 2012. Two years later, in 2014, similar research was conducted at the forest stands of the Aegopodium forest site type and in 2015, at the former Pikknurme forest district. As nature is constantly changing, classifying forest site types is difficult. The purpose of this thesis is to study permanent sample plots of a single area based on data other than already determined forest site types and to examine other possibilities for classifying permanent sample plots. To acquire the taxation data of the forest stand, a circular systematic method of drawing samples was used, during which an inventory of ground vegetation was conducted and soil excavation performed in order to provide soil descriptions. MS Excel’s regression analysis was used to process the data. Different environmental features, ground vegetation, soil indicators, and taxation data was analysed using different PC-ORD 6 analysis packages. The analyses revealed that many of the sample plots that had been classified as similar forest site types might in fact have been classified incorrectly. Therefore, we decided to analyse and research the continuous data. The conclusion of this thesis does not aim to discredit any method of classification; however, the results revealed that merely visual examination is not sufficient for achieving accurate results. As nature is highly changeable, more research must be done for accurate results and mere visual examination is not enough.
Kirjeldus
Märksõnad
puistud, alustaimestu, mullad, kasvukohatüübid, naat, bakalaureusetööd