Essays about: "explain the importance of forest"

Showing result 1 - 5 of 24 essays containing the words explain the importance of forest.

  1. 1. Influence of structural complexity of the Rumperöd forest on evapotranspiration

    University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Author : Madeleine Durdek; [2023]
    Keywords : Forest structural complexity; evapotranspiration; vapour pressure deficit; eddy covariance; Earth and Environmental Sciences;

    Abstract : The influence of Forest Structural Complexity (FSC) on evapotranspiration (ET) was investigated in a mixed forest of Southern Sweden where micrometeorological Eddy Covariance (EC) measurements were conducted for the years 2015 to 2022. For each year, the top 25% of Vapour Pressure Deficit (VPD) were selected to emphasize the response of ET to the driest atmospheric conditions. READ MORE

  3. 2. Legacy effects of temperature alterations on microbial resistance and resilience to drying and rewetting

    University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Author : Franklin Lee Harris; [2023]
    Keywords : microbial ecology; soil; carbon dynamics; high latitudes; climate change; moisture stress; isotopes; respiration; trait based ecology; soil microbes; Environmental Changes in High Latitudes EnCHIL ; Earth and Environmental Sciences; Biology and Life Sciences;

    Abstract : With warming in soils due to climate change, a series of secondary factors arise, which have multifaceted effects on soil microbial communities. Of these, alterations to soil moisture are among the most crucial to understanding how microbial functions will change in the face of climate change. READ MORE

  4. 3. Exploring the Dynamics of Damage Costs Inflation on Insurance Matters : An In-depth Regression Analysis on Macroeconomic Variables

    University essay from Umeå universitet/Institutionen för matematik och matematisk statistik

    Author : Jacob Liljestrand; Fredrik Nyberg; [2023]
    Keywords : Inflation; Time lag; Regression; Macroeconomic variables; Insurance;

    Abstract : The aim of this thesis consist of three parts. Firstly, the aim was to developan accurate historical inflation index suitable for the insurance business, usinginformation about insurance matters. The calculated inflation index was compared to an in-house benchmark at the insurance company Gjensidige, it wasfound to be a good match. READ MORE

  5. 4. What is the future of emission data? A study of environmental purchasing criteria in the heavy road freight transport industry in Sweden

    University essay from Lunds universitet/Produktionsekonomi

    Author : Måns Kvarnfors; Magnus Åström; [2022]
    Keywords : emission data; purchasing; GHG emissions; road transport; Sweden; environmental purchasing; Technology and Engineering;

    Abstract : Heavy road freight transports in Sweden are responsible for a significant portion of national greenhouse gas emissions. Earlier research has looked at the purchasing process of transports in a business-to-business context and established its importance for limiting environmental impact. READ MORE

  6. 5. Estimation of dissolved organic carbon from inland waters using remote sensing data and machine learning

    University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Author : Lasse Harkort; [2022]
    Keywords : dissolved organic carbon; machine learning; remote sensing; inland waters; water quality; open source data; Earth and Environmental Sciences;

    Abstract : This thesis presents the first attempt to estimate Dissolved Organic Carbon (DOC) in inland waters over a large-scale area using satellite data and machine learning (ML) methods. Four ML approaches, namely Random Forest Regression (RFR), Support Vector Regression (SVR), Gaussian Process Regression (GPR), and a Multilayer Backpropagation Neural Network (MBPNN) were tested to retrieve DOC using a filtered version of the recently published open source AquaSat dataset with more than 16 thousand samples across the continental US matched with satellite data from Landsat 5, 7 and 8 missions. READ MORE