Essays about: "LPJ-GUESS"

Showing result 11 - 15 of 34 essays containing the word LPJ-GUESS.

  1. 11. A detailed study on Amazon Forest structure and mortality rates through LPJ-GUESS vegetation model

    University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Author : Sara Mazzuoli; [2021]
    Keywords : Amazon s Forest; LPJ-GUESS; simulation; TEAM-NETWORK; dynamic vegetation model; observation; mortality; allometry; tree stand structure; biomass; cohort; PFTs; plant functional types; NPP; Earth and Environmental Sciences;

    Abstract : Nowadays it has become relevant for scientists to understand the impact of tropical forest structure on the Global Carbon Cycle. Dynamic vegetation models have been developed to pursue this issue, specifically by improving algorithms that could analyze the allometry, biomass content and mortality rate of each singular simulated plant individual and how this responds to climate change, management and rising CO2 concentrations. READ MORE

  2. 12. Evaluation of estate level forest management strategies in terms of ecosystem services and biodiversity aspects

    University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Author : Jon Gant; [2021]
    Keywords : Forest management; Ecosystem services; EQOs; LPJ-GUESS; Earth and Environmental Sciences;

    Abstract : Ecosystem services from forests provide society with a multitude of benefits. However, current research shows that in Swedish forests aspects of ecosystem services have a status ranging from “moderate” to “inadequate”. READ MORE

  3. 13. 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. 14. Increasing forest mortality and its drivers: Simulating central European forests under climate change

    University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Author : Marieke Scheel; [2021]
    Keywords : forest mortality; central Europe; competition; CO2; temperature; precipitation; DVM; LPJ-GUESS; simulation; reproducing data; Earth and Environmental Sciences;

    Abstract : Increasing tree growth and mortality rates in Europe are still poorly understood and have been attributed to a variety of drivers. This study aimed to relate increasing forest mortality rates in six central European countries to climate drivers (CO2 concentration, temperature and precipitation) from 1985-2015, using a process-based vegetation model. READ MORE

  5. 15. Multitask Convolutional Neural Network Emulators for Global Crop Models - Supervised Deep Learning in Large Hypercubes of Non-IID Data

    University essay from Lunds universitet/Matematisk statistik

    Author : Amanda Nilsson; [2020]
    Keywords : Multitask Learning; Convolutional Neural Network CNN ; Branched Neural Network; Dynamic Global Vegetation Models DGVM ; Automated Feature Extraction; Feature Importance; Supervised Machine Learning; Emulator; Surrogate Model; Response Surface Model; Approximation Model; Metamodeling; Model Composition; Regularization; Robustness; Hyperparameter Optimization; Mathematics and Statistics;

    Abstract : The aim of this thesis is to establish whether a neural network (NN) can be used for emulation of simulated global crop production - retrieved from the computationally demanding dynamic global vegetation model (DGVM) Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS). It has been devoted to elaboration with various types of neural network architectures: Branched NNs capable of processing inputs of mixed data types; Convolutional Neural Network (CNN) architectures able to perform automated temporal feature extraction of the given weather time series; simpler fully connected (FC) structures as well as Multitask NNs. READ MORE