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2022 ◽  
Vol 505 ◽  
pp. 119868
Author(s):  
Thomas Gschwantner ◽  
Iciar Alberdi ◽  
Sébastien Bauwens ◽  
Susann Bender ◽  
Dragan Borota ◽  
...  

2022 ◽  
Vol 14 (2) ◽  
pp. 36
Author(s):  
Emanuel Arnoni Costa ◽  
Cristine Tagliapietra Schons ◽  
César Augusto Guimarães Finger ◽  
André Felipe Hess

Improving volumetric quantification of Parana pine (Araucaria angustifolia) in Mixed Ombrophilous Forest is a constant need in order to provide accurate and timely information on current and future growing stock to ensure forest management. Thus, the present study aimed to evaluate and compare the volume estimates obtained through Nonlinear Regression (NR), Genetic Algorithm (GA) and Simulated Annealing (SA) in order to generate accurate volume estimates. Volumetric equations were developed including the independent variables diameter at breast height (dbh), total height (h) and crown rate (cr) and from the fit through the NR, GA and SA approaches. The GA and SA approaches evaluated proved to be a reliable optimization strategy for parameter estimation in Parana pine volumetric modelling, however, no significant differences were found in comparison with the NR approach. This study therefore contributes through the generation of robust equations that could be used for accurate estimates of the volume of the Parana pine in southern Brazil, thus supporting the planning and establishment of management and conservation actions.


Author(s):  
М.О. Гурьянов ◽  
Д.Э. Раупова

Взаимосвязи между высотами деревьев и диаметрами на высоте груди широко применяются при определении запасов и сортиментной структуры древостоев. Для их описания применяются многочисленные математические модели. Сравнительный анализ точности шести моделей на примере древостоев сосны обыкновенной Учебно-опытного лесничества Ленинградской области показал близкую точность каждой из них. При этом для разных пробных площадей наибольшую точность показывали разные модели. Это обуславливает необходимость дальнейших исследований по данной тематике с целью выявления наиболее применимых для различных древесных пород, возрастов и условий местопроизрастаний математических моделей. В практической деятельности часто используются таблицы, составленные с учетом соотношений высот и диаметров на высоте груди в древостоях, основными из которых являются таблицы объемов стволов по разрядам высот и сортиментные таблицы. В рамках исследования было установлено, что фактические зависимости высот деревьев от диаметров на высоте груди отличаются от приведенных в таблицах, что обусловлено индивидуальными особенностями структуры и условий местопроизрастания древостоев. По этой причине разряды высот, определенные для отдельных ступеней толщины, зачастую отличаются от найденных по средним для древостоя высоте и диаметру на высоте груди. Это приводит к расхождениям в найденных с учетом данных двух подходов запасах древостоев, а также выхода и стоимости сортиментов в них. Несмотря на незначительность различий, их наличие свидетельствует о необходимости дальнейших исследований с целью повышения точности определения таксационных показателей древостоев. The relationships between heights and diameters at breast height of trees are widely used in determining of growing stock and assortment structure of stands. Numerous mathematical models are used to describe them. A comparative analysis of the accuracy of six models on the example of tree stands of Scots pine in the Training and Experimental Forestry of the Leningrad region showed the close accuracy of each of them. For different sample plots, however, the highest accuracy was showed by different models. This necessitates further research on this topic in order to identify the most applicable mathematical models for different tree species, ages and habitat conditions. In practice are often used the tables, compiled taking into account the ratios of heights and diameters at breast height in tree stands, the main of which are tables of volumes of trees by height ranks and assortment tables. Within the framework of the study, it was found that the actual relationships between tree heights and diameters at breast height differ from those given in the tables, which is due to the individual features of the stand structure and habitat conditions. For this reason, the height ranks, determined for individual diameter classes often differ from those found for the average tree stand height and diameter at breast height. This leads to discrepancies in the growing stocks of tree stands, found taking into account these two approaches, as well as the yield and cost of assortments in them. Although the differences are insignificant, they highlight the need for further research in order to improve the accuracy of determining the inventory parameters of tree stands


2021 ◽  
Vol 13 (23) ◽  
pp. 4924
Author(s):  
Gaia Vaglio Laurin ◽  
Nicola Puletti ◽  
Clara Tattoni ◽  
Carlotta Ferrara ◽  
Francesco Pirotti

Windstorms are a major disturbance factor for European forests. The 2018 Vaia storm, felled large volumes of timber in Italy causing serious ecological and financial losses. Remote sensing is fundamental for primary assessment of damages and post-emergency phase. An explicit estimation of the timber loss caused by Vaia using satellite remote sensing was not yet undertaken. In this investigation, three different estimates of timber loss were compared in two study sites in the Alpine area: pre-existing local growing stock volume maps based on lidar data, a recent national-level forest volume map, and an novel estimation of AGB values based on active and passive remote sensing. The compared datasets resemble the type of information that a forest manager might potentially find or produce. The results show a significant disagreement in the different biomass estimates, related to the methods used to produce them, the study areas characteristics, and the size of the damaged areas. These sources of uncertainty highlight the difficulty of estimating timber loss, unless a unified national or regional European strategy to improve preparedness to forest hazards is defined. Considering the frequent impacts on forest resources that occurred in the last years in the European Union, remote sensing-based surveys targeting forests is urgent, particularly for the many European countries that still lack reliable forest stocks data.


Forests ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1682
Author(s):  
Ewa Referowska-Chodak ◽  
Bożena Kornatowska

At all times, historical, political, economic, and social factors have affected the management of forests, with direct and indirect effects on the landscape. This study aimed to trace the impact of Poland’s forestry evolution over the last 75 years (1945–2020) on forest biodiversity at the landscape level. Five indicators were selected (forest area, forest fragmentation, protected forests, protective forests, harvesting intensity) to identify directions and dynamics of changes of the forest landscape and their determinants and repercussions. In addition, there were determined forest landscapes threats and recommendations for further action and intervention were formulated. The study period embraced two eras of widely divergent political-economic conditions in Poland (socialism and democracy). In the socialism era (1945–1989), there promptly increased total forest cover, wood resources (total growing stock) and the total area of protective forests (essential for safeguarding biodiversity, including the landscape level). In the era of democracy (1990–2020), average growing stock density increased intensely, and at the same time, a greater emphasis was put on reducing forest fragmentation and clear-cut logging. The results obtained showed equal average increase in the area of protected forests in both eras under the study (most intense at their crossing point). In view of the protection of biodiversity at the forest landscape level, the changes throughout the study period were considered positive, although not without problems and challenging consequences for foresters. The determined pressures to the forest landscapes, requiring legal, political, or financial solutions, include a risk of alteration of the ownership structure of Poland’s forests or possibility of operational changes in the State Forests National Forest Holding; outdated forest policies; organizational difficulties in the forest landscape protection; insufficient conservation funding; uneven distribution and further fragmentation of forests; and—last but not least—climate change impacts, including extreme weather events and droughts.


2021 ◽  
pp. 399-433
Author(s):  
Chiara Torresan ◽  
Sebastiaan Luyssaert ◽  
Gianluca Filippa ◽  
Mohammad Imangholiloo ◽  
Rachel Gaulton

AbstractMonitoring forest responses to climate-smart forestry (CSF) is necessary to determine whether forest management is on track to contribute to the reduction and/or removal of greenhouse gas emissions and the development of resilient mountain forests. A set of indicators to assess “the smartness” of forests has been previously identified by combining indicators for sustainable forest management with the ecosystem services. Here, we discuss the remote sensing technologies suitable to assess those indicators grouped in forest resources, health and vitality, productivity, biological diversity, and protective functions criteria. Forest cover, growing stock, abiotic, biotic, and human-induced forest damage, and tree composition indicators can be readily assessed by using established remote sensing techniques. The emerging areas of phenotyping will help track genetic resource indicators. No single existing sensor or platform is sufficient on its own to assess all the individual CSF indicators, due to the need to balance fine-scale monitoring and satisfactory coverage at broad scales. The challenge of being successful in assessing the largest number and type of indicators (e.g., soil conditions) is likely to be best tackled through multimode and multifunctional sensors, increasingly coupled with new computational and analytical approaches, such as cloud computing, machine learning, and deep learning.


PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0259795
Author(s):  
Jean-Daniel Bontemps

The current increase in European forest resources forms a singularity across the globe. Whether this trend will persist, and how biological and economic trends feature it form crucial issues to green economy challenges and C sequestration. The present screening of Forest Europe 2015 statistics explored the features, inertia and limits of this expansion, and its relationships with countries’ development, forest management and trade, intense in this area of the world. Persisting footprint of past demographic pressure on forests was identified, with opposed traces on their area and growing stock density. Steady growing stock (GS) increases, proportional to GS, not density-limited, and sustained by forest area increases, supported the view of an inflationary forest dynamic. Economic development and liberalism fostered both forest exploitation and production, yielding no significant impact on GS changes. Wood exports exerted a tension on forest exploitation and GS changes, thus lowering GS inflation but providing a resource security margin in the face of expected climate threats. Conflicting a common view, GS inflation and moderate felling-to-increment ratios make increased use of wood resources and C sequestration reconcilable, and GS expansion timely for ongoing EU forest policy processes. Anticipated adverse impacts of ongoing climate change were not clearly identified in these statistics.


2021 ◽  
Vol 2 (2) ◽  
pp. 257-267
Author(s):  
Syed Usman Qadri ◽  
Naveed Iqbal ◽  
Syeda Shamaila Zareen

The purpose of this study is to determine the predictability of the Pakistani stock market's one-day forward returns by utilizing lagged daily returns for Pakistan, India, and Malaysia from 2006 to 2016. The findings indicate that lagged Pakistani market returns significantly predict Pakistani one-day ahead market returns. However, the other two growing stock markets, India and Malaysia, show no association with one-day ahead market returns. Mostly, stock market behavior in the pre-2008 and post-2008 eras was the same, although industry return behaviour was different due to the economic crisis of 2008. However, the Pakistani stock market one-day ahead returns predict the own Pakistani lag returns due to an inefficient market and prices do not follow a random walk. As a result, investors and financial analysts can foresee and generate anomalous returns by using previous data and information. Key words: Stock Market Returns Predictability, Stock Market crash, Market efficiency


2021 ◽  
pp. 1-11
Author(s):  
Shannon White ◽  
Xinbiao Zhu ◽  
Fanrui Meng ◽  
Scott Taylor ◽  
Charles P.-A. Bourque

Moose (Alces alces L.) browsing in Gros Morne National Park has damaged its balsam fir (Abies balsamea (L.) Mill.)dominated forest. A forest estate model was used to evaluate (i) the impacts of moose browsing and woodcutting on forest succession and (ii) strategies of forest restoration through planting and moose population management. The simulation results show that under current heavy browsing pressure growing stock of balsam fir decreases by 38%, but the area of spruce (Picea mariana (Mill.) BSP and P. glauca (Moench) Voss) increases by 32% over a 100-year planning horizon, compared to that under light browsing scenario which is assumed to be similar to the forest outside the Park due to moose population management. Annual allowable cut (AAC) for the Park’s 19 400 ha domestic harvest area is estimated to be around 120 979 m3 in a light browsing scenario, 21% higher than the sustainable harvest level in a heavy browsing scenario. The model forecasts a 97% reforestation of the Park’s 7 194 ha disturbed area by planting in the heavy browsing scenario, leading to an increase in total forest growing stock by 22% and AAC by 12%. Integration of planting with moose population management could be a more efficient way of restoring forest under high browsing pressure in GMNP.


2021 ◽  
Vol 13 (21) ◽  
pp. 4483
Author(s):  
W. Gareth Rees ◽  
Jack Tomaney ◽  
Olga Tutubalina ◽  
Vasily Zharko ◽  
Sergey Bartalev

Growing stock volume (GSV) is a fundamental parameter of forests, closely related to the above-ground biomass and hence to carbon storage. Estimation of GSV at regional to global scales depends on the use of satellite remote sensing data, although accuracies are generally lower over the sparse boreal forest. This is especially true of boreal forest in Russia, for which knowledge of GSV is currently poor despite its global importance. Here we develop a new empirical method in which the primary remote sensing data source is a single summer Sentinel-2 MSI image, augmented by land-cover classification based on the same MSI image trained using MODIS-derived data. In our work the method is calibrated and validated using an extensive set of field measurements from two contrasting regions of the Russian arctic. Results show that GSV can be estimated with an RMS uncertainty of approximately 35–55%, comparable to other spaceborne estimates of low-GSV forest areas, with 70% spatial correspondence between our GSV maps and existing products derived from MODIS data. Our empirical approach requires somewhat laborious data collection when used for upscaling from field data, but could also be used to downscale global data.


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