Search results for "FORESTS"

Structural variables drive the distribution of the sensitive lichen Lobaria pulmonaria in Mediterranean old-growth forests

2015

a b s t r a c t We tested the hypothesis that structural variables related to old-growth features affect the distribution of Lobaria pulmonaria in a Mediterranean National Park of Italy. A total of 36 plots, with old-growth characteristics and representing overall three forest types (beech- oak- and mixed- forests) were studied. The lichen was absent in about half of the sites, suggesting that the selection of old-growth forests based solely on structural features is not sufficient to predict the presence of this species, which therefore proves to be rather sensitive and selective. Its abundance was related to high tree circumference and basal area, and to availability of deadwood, confirmi…

From the forest to the plate – Hemicelluloses, galactoglucomannan, glucuronoxylan, and phenolic-rich extracts from unconventional sources as function…

2021

This study aimed to characterise pressurised hot water (PHW) extracts from nonconventional sources of functional carbohydrates and phenolic compounds in terms of antioxidant capacity, antiviral activity, toxicity, and human erythrocytes’ protection antidiabetic potential. PHW extracts of Norway spruce bark (E1 + E2) and Birch sawdust (E3 + E4) contained mostly galactoglucomannan and glucuronoxylan. In contrast, samples E5 to E9 PHW extracted from Norway spruce, and Scots pine bark are rich sources of phenolic compounds. Overall, phenolic-rich extracts presented the highest inhibition of α-amylase and α-glucosidase and protection against stable non-enveloped enteroviruses. Additionally, all …

Forest structural elements and bryophyte species richness in managed forest landscape

2013

Elektroniskā versija nesatur pielikumus

Dark matters : contrasting responses of stream biofilm to browning and loss of riparian shading

2022

Concentrations of terrestrial-derived dissolved organic carbon (DOC) in freshwater ecosystems have increased consistently, causing freshwater browning. The mechanisms behind browning are complex, but in forestry-intensive regions browning is accelerated by land drainage. Forestry actions in streamside riparian forests alter canopy shading, which together with browning is expected to exert a complex and largely unpredictable control over key ecosystem functions. We conducted a stream mesocosm experiment with three levels of browning (ambient vs. moderate vs. high, with 2.7 and 5.5-fold increase, respectively, in absorbance) crossed with two levels of riparian shading (70% light reduction vs.…

Adaptive Management as a Vehicle to Achieve Sustainability of Boreal Forests : A Historical Review from Fennoscandia to Minnesota

2021

Located solely in the northern hemisphere, boreal forests contain an estimated one-third of Earth’s forested land. The purpose of this work aimed at reviewing the evolution of approaches in land planning and management of boreal forests in Finland and Northern Sweden, while comparing these to those developed in Minnesota. The nature of this work is historical research of forests use and management during the last 200 years. The knowledge from past histories is valuable to improve management approaches that aim at retaining the economic viability of logging, without jeopardizing the regenerative capabilities of forest ecosystems. Various methods and restoration efforts aimed at recovering fr…

Developing tools for biodiversity surveys : studies with wood-inhabiting fungi

2010

Global Estimation of Biophysical Variables from Google Earth Engine Platform

2018

This paper proposes a processing chain for the derivation of global Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fraction Vegetation Cover (FVC), and Canopy water content (CWC) maps from 15-years of MODIS data exploiting the capabilities of the Google Earth Engine (GEE) cloud platform. The retrieval chain is based on a hybrid method inverting the PROSAIL radiative transfer model (RTM) with Random forests (RF) regression. A major feature of this work is the implementation of a retrieval chain exploiting the GEE capabilities using global and climate data records (CDR) of both MODIS surface reflectance and LAI/FAPAR datasets allowing the global estim…

Performance Dissimilarities in European Union Manufacturing: The Effect of Ownership and Technological Intensity

2021

Our paper addresses the relevance of a set of continuous and categorical variables that describe industry characteristics to differences in performance between foreign versus locally owned companies in industries with dissimilar levels of technological intensity. Including data on manufacturing sector performance from 20 European Union member countries and covering the 2009–2016 period, we used the random forests methodology to identify the best predictors of EU manufacturing industries’ a priori classification based on two main attributes: ownership (foreign versus local) and technological intensity. We found that EU foreign-owned businesses dominate locally owned ones in terms of size, wh…

Application of selected methods of black box for modelling the settleability process in wastewater treatment plant

2017

The paper described how the results of measurement s of inflow wastewater temperature in the chamber, a degree of external and internal recirculation in the biological-mechanical wastewater treatment plan t (WWTP) in Cedzyna near Kielce, Poland, were used to make predictions of settleability of activated sludge. Three methods,namely: multivariate adaptive regression splines (MARS), random forests (RF) and modified random forests (RF+ SOM) were employed to compute activated sludge settleability. The results of analysis indicate that modified random forests demonstrate the best predictive abilities.

Application of selected supervised classification methods to bank marketing campaign

2016

Supervised classification covers a number of data mining methods based on training data. These methods have been successfully applied to solve multi-criteria complex classification problems in many domains, including economical issues. In this paper we discuss features of some supervised classification methods based on decision trees and apply them to the direct marketing campaigns data of a Portuguese banking institution. We discuss and compare the following classification methods: decision trees, bagging, boosting, and random forests. A classification problem in our approach is defined in a scenario where a bank’s clients make decisions about the activation of their deposits. The obtained…