Classifying forest stands according to spatial species mingling
Legislature and international treaties increasingly underline the importance of biodiversity and sustainability, hence the need for accurate measurements, regarding the aforementioned concepts. Biodiversity is a comprehensive term, which can be very difficult/costly to measure directly. Therefore, s...
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| Formato: | Second cycle, A2E |
| Lenguaje: | Inglés Inglés |
| Publicado: |
2019
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| Acceso en línea: | https://stud.epsilon.slu.se/14204/ |
| Sumario: | Legislature and international treaties increasingly underline the importance of biodiversity and sustainability, hence the need for accurate measurements, regarding the aforementioned concepts. Biodiversity is a comprehensive term, which can be very difficult/costly to measure directly. Therefore, surrogate measures can be used to quantify different aspects of biodiversity. An indicator closely linked to biodiversity in forest ecosystems is forest structure.
To quantify different aspects of forest structure metrices from the field of point process statistics can be used. In this study we introduce the new function J(̅r) and evaluate its ability to describe species mingling in forest stands. This is done by incorporating data from 20 fully inventoried stands from different parts of the world. Producing curves from J(̅r) and from the mark mingling function, v(r) which is arguably the most similar established function. The curves are classified in groups based on characteristics. This is done separately for each function to be able to investigate how the groups differ between J(̅r) and v(r) and to see what new information J(̅r) could provide, additional to v(r).
This study suggests that the new function of J(̅r) provides additional information to the mark mingling function, mostly related to J(̅r) being based on the nearest neighbour (NN) concept and thus providing more information on local neighbourhoods. This research also points to the value of J(̅r) being potentially more suitable to use on smaller plots, such as those commonly used in forest inventories. |
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