Essays about: "tree size distributions"

Found 3 essays containing the words tree size distributions.

  1. 1. Changes in the oak (Quercus robur) population in Dalby Söderskog national park 2011–2020 : stem size distribution, spatial distributions, vitality and mortality

    University essay from SLU/Southern Swedish Forest Research Centre

    Author : Johan Larsson; [2021]
    Keywords : forest reserve; national park; long-term study; oak; oak regeneration; Quercus robur;

    Abstract : A recent oak (Quercus robur) decline has been noticed and studied in Europe during the last few decades. This decline in combination with failure in natural regeneration could threaten not only oak populations, but also oak-associated species. READ MORE

  3. 2. Evaluating the ability of LPJ-GUESS to simulate the tree size structures of tropical forests

    University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Author : Margot Jeanne Knapen; [2021]
    Keywords : tropical forests; tree size distributions; LPJ-GUESS; carbon; biomass; sensitivity analysis; Earth and Environmental Sciences;

    Abstract : Tropical forests are of great importance to all living-beings due to their high biodiversity and the valu-able resources, such as food and fuel, they provide. In addition, tropical trees sequester a high amount of carbon and consequently over half of the global forest carbon stock can be found in the tropics. READ MORE

  4. 3. Evaluating inventory methods for estimating stem diameter distributions in micro stands derived from airborn laser scanning

    University essay from SLU/Dept. of Forest Resource Management

    Author : Anders Lundholm; [2014]
    Keywords : kMSN; imputation; transect inventory; guided sampling; ALS;

    Abstract : A lot of research has focused on which laser metrics and which k-Nearest Neighbour (kNN) distances give the most accurate estimations. Most studies suggest that the kNN distance k-Most Similar Neighbour (kMSN) is the most accurate for estimating forest variables from local training data. READ MORE