scholarly journals National Forest Inventory Data to Evaluate Climate-Smart Forestry

2021 ◽  
pp. 107-139
Author(s):  
Christian Temperli ◽  
Giovanni Santopuoli ◽  
Alessandra Bottero ◽  
Ignacio Barbeito ◽  
Iciar Alberdi ◽  
...  
Keyword(s):  
Forest Inventory ◽  
Sustainable Forest Management ◽  
National Forest Inventory ◽  
National Forest ◽  
Management Scenarios ◽  
Mountainous Regions ◽  
Mitigation And Adaptation ◽  
Composite Indices ◽  
Indicator Approach ◽  
Business As Usual

AbstractNational Forest Inventory (NFI) data are the main source of information on forest resources at country and subcountry levels. This chapter explores the strengths and limitations of NFI-derived indicators to assess forest development with respect to adaptation to and mitigation of climate change, that is, the criteria of Climate-Smart Forestry (CSF). We reflect on harmonizing NFI-based indicators across Europe, use literature to scrutinize available indicators to evaluate CSF, and apply them in 1) Switzerland, where CSF is evaluated for NFI records and simulation model projections with four management scenarios; 2) 43 selected European countries, for which the indicators for Sustainable Forest Management (SFM) are used. The indicators were aggregated to composite indices for adaptation and mitigation and to an overall CSF rating. The Swiss NFI records showed increased CSF ratings in mountainous regions, where growing stocks increased. Simulations under business-as-usual management led to a positive CSF rating, whereas scenarios of increased harvesting decreased either only adaptation or both mitigation and adaptation. European-level results showed increases in CSF ratings for most countries. Negative adaptation ratings were mostly due to forest damages. We discuss the limitations of the indicator approach, consider the broader context of international greenhouse gas reporting, and conclude with policy recommendations.

scholarly journals A multi-purpose National Forest Inventory in Bangladesh: design, operationalisation and key results

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Matieu Henry ◽  
Zaheer Iqbal ◽  
Kristofer Johnson ◽  
Mariam Akhter ◽  
Liam Costello ◽  
...  
Keyword(s):  
Climate Change ◽  
Forest Management ◽  
Data Collection ◽  
Land Cover ◽  
Forest Inventory ◽  
Sustainable Forest Management ◽  
National Forest Inventory ◽  
Forest Resources ◽  
National Forest ◽  
Land Cover Map

Abstract Background National forest inventory and forest monitoring systems are more important than ever considering continued global degradation of trees and forests. These systems are especially important in a country like Bangladesh, which is characterised by a large population density, climate change vulnerability and dependence on natural resources. With the aim of supporting the Government’s actions towards sustainable forest management through reliable information, the Bangladesh Forest Inventory (BFI) was designed and implemented through three components: biophysical inventory, socio-economic survey and remote sensing-based land cover mapping. This article documents the approach undertaken by the Forest Department under the Ministry of Environment, Forests and Climate Change to establish the BFI as a multipurpose, efficient, accurate and replicable national forest assessment. The design, operationalization and some key results of the process are presented. Methods The BFI takes advantage of the latest and most well-accepted technological and methodological approaches. Importantly, it was designed through a collaborative process which drew from the experience and knowledge of multiple national and international entities. Overall, 1781 field plots were visited, 6400 households were surveyed, and a national land cover map for the year 2015 was produced. Innovative technological enhancements include a semi-automated segmentation approach for developing the wall-to-wall land cover map, an object-based national land characterisation system, consistent estimates between sample-based and mapped land cover areas, use of mobile apps for tree species identification and data collection, and use of differential global positioning system for referencing plot centres. Results Seven criteria, and multiple associated indicators, were developed for monitoring progress towards sustainable forest management goals, informing management decisions, and national and international reporting needs. A wide range of biophysical and socioeconomic data were collected, and in some cases integrated, for estimating the indicators. Conclusions The BFI is a new information source tool for helping guide Bangladesh towards a sustainable future. Reliable information on the status of tree and forest resources, as well as land use, empowers evidence-based decision making across multiple stakeholders and at different levels for protecting natural resources. The integrated socio-economic data collected provides information about the interactions between people and their tree and forest resources, and the valuation of ecosystem services. The BFI is designed to be a permanent assessment of these resources, and future data collection will enable monitoring of trends against the current baseline. However, additional institutional support as well as continuation of collaboration among national partners is crucial for sustaining the BFI process in future.

Monitoring Canada's forests: The National Forest Inventory

2005 ◽  
Vol 81 (2) ◽  
pp. 214-221 ◽  
Author(s):  
M D Gillis ◽  
A Y Omule ◽  
T. Brierley
Keyword(s):  
Remote Sensing ◽  
Sustainable Development ◽  
Forest Inventory ◽  
Forest Cover ◽  
Sustainable Forest Management ◽  
Remote Sensing Data ◽  
National Forest Inventory ◽  
National Forest ◽  
Inventory Data ◽  
International Reporting

A new national forest inventory is being installed in Canada. For the last 20 years, Canada's forest inventory has been a compilation of inventory data from across the country. Although this method has a number of advantages, it lacks information about the nature and rate of changes to the resource, and does not permit projections or forecasts. To address these limitations a new National Forest Inventory (NFI) was developed to monitor Canada's progress in meeting a commitment towards sustainable forest management, and to satisfy requirements for national and international reporting. The purpose of the new inventory is to "assess and monitor the extent, state and sustainable development of Canada's forests in a timely and accurate manner." The NFI consists of a plot-based system of permanent observational units located on a national grid. A combination of ground plot, photo plot and remote sensing data are used to capture a set of basic attributes that are used to derive indicators of sustainability. To meet the monitoring needs a re-measurement strategy and framework to guide the development of change estimation procedures has been worked out. A plan for implementation has been drafted. The proposed plan is presented and discussed in this paper. Key words: Canada, forest cover, inventory, monitoring, National Forest Inventory, re-measurement, panel

scholarly journals Historical avenues of research in Russian forest typology: ecological, phytocoenotic, genetic, and dynamic classifications

2017 ◽  
Vol 47 (7) ◽  
pp. 849-860 ◽  
Author(s):  
V.V. Fomin ◽  
S.V. Zalesov ◽  
A.S. Popov ◽  
A.P. Mikhailovich
Keyword(s):  
Russian Federation ◽  
Forest Inventory ◽  
Sustainable Forest Management ◽  
Forest Type ◽  
National Forest Inventory ◽  
Montreal Protocol ◽  
Inventory Systems ◽  
National Forest ◽  
The Russian Federation ◽  
Forest Typology

The Russian Federation is one of many countries that have signed the Montreal Protocol and Pan-European Forest Process. These initiatives are aimed at harmonizing national forest inventory systems with criteria and indicators for sustainable forest management. In Russia, the classification of forest type is at the heart of national forest inventory systems. For various historical reasons, Russian scientific advancements in the field of forest typology remain little known in the rest of the world. This paper is aimed at addressing this deficiency. Here, we provide an overview of the main trends in the field of forest typology studies in the previous political states of the Russian Empire, the Soviet Union, and the Russian Federation from the end of the nineteenth century to the beginning of the twenty-first century. We detail the principles that formed the basis of the most significant forest type classifications. We also perform similarity and differences analyses comparing approaches used by members of different scientific schools in the field of forest typology. The historical relationship between ecological, phytocoenotic, genetic, and dynamic forest type classifications are discussed as well as the reasons for the prevalence of certain forest type classifications in different regions of Russia.

Multipurpose National Forest Inventory in Mongolia, 2014-2017 -A tool to support sustainable forest management

2019 ◽  
Vol 12 (3) ◽  
pp. 167-183 ◽  
Author(s):  
Dan Altrell
Keyword(s):  
Forest Management ◽  
Boreal Forest ◽  
Forest Inventory ◽  
Dead Wood ◽  
Sustainable Forest Management ◽  
National Forest Inventory ◽  
National Forest ◽  
Green Wood ◽  
Growing Stock ◽  
Stock Volume

Mongolia’s first Multipurpose National Forest Inventory, 2014-2017, was implemented by the Forest Research and Development Centre, in collaboration with international expertise and the country’s main forestry institutions, universities and research organisations.The long-term objective of the multipurpose NFI is to promote sustainable management of forestry resources in Mongolia, to enhance their social, economic and environmental functions.The NFI findings show that there are 11.3 million hectares of Boreal Forest in Mongolia. 9.5 million hectares are Stocked Boreal Forest Area, of which 69 percent is located outside of protected areas, 4 percent are designated for green-wood utilisation through forest enterprise concessions, and another 16 percent designated for fallen dead-wood collection through forest user group concessions. The non-protected stocked forests (i.e. production forest) have an average growing stock volume of 115 m3 per hectare, compared with an optimal growing stock volume of 237 m3 per hectare, and there is an additional 46.5 m3 of dead wood per hectare. The growing stock age distribution shows that 24 m3 per hectare are over 200 years (i.e. economically over-aged). The main tree species in stocked forest are Larix sibirica (81%), Pinus sibirica (7%), Betula platyphylla (6%) and Pinus sylvestris (5%), of which all, except for P. sibirica, are classified as legally harvestable tree species. Wild fire is the current main environmental factor decreasing the forest tree biomass.The NFI helped identifying priority areas for the forestry sector, and to guide the implementation of sustainable forest management at the local level. The main forest management challenges of Mongolia’s boreal forest will be to address that they are a) under-stocked (less than 50% of production potential), b) over-aged (31% of growing stock volume in stocked production forest is above optimal production age), and c) under-utilised (4% of forest area designated to green-wood utilisation). 

scholarly journals The State of British Columbia’s Forests: A Global Comparison

Forests ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 316
Author(s):  
Haris R. Gilani ◽  
John L. Innes
Keyword(s):  
British Columbia ◽  
Forest Management ◽  
Forest Inventory ◽  
Sustainable Forest Management ◽  
National Forest Inventory ◽  
Forest Resources ◽  
National Forest ◽  
Production Volume ◽  
Global Comparison ◽  
Resources Assessment

The Forest Resources Assessment 2015 is a comprehensive dataset from the Food and Agriculture Organization of the United Nations (FAO), which provides the opportunity to explore some of the emerging topics related to sustainable forest management. This paper assesses how forests in British Columbia, Canada, compare globally on several key sustainable forest management parameters in four domains—biophysical indicators and legal framework, management plans, data management, and stakeholder involvement. The comparison was done against eight jurisdictions, namely Australia, China, Japan, the European Union, New Zealand, the Russian Federation and the USA. To accomplish our objectives, country-specific data on sustainable forest management parameters were extracted from the 2015 FAO’s Global Forest Resources Assessment (FRA). Data specific to B.C. were sourced from Canada’s National Forest Inventory, and National Forest Database. Our results showed that British Columbia (B.C.) has one of the highest proportions of land covered with forests (57%) among all jurisdictions. The total forest area in B.C. has remained stable at around 55 million ha. The current rate of deforestation (6200 ha per year) is among the lowest in all jurisdictions. Data on the extent of primary forests in B.C. is unavailable. However, 22.6 million ha (41% of B.C.′s forests) have been classified as old growth forests (using a definition unique to B.C.). B.C. is the leading provincial forest producer by volume, and produced 67.97 million m3 of roundwood in 2015. With approximately 11 billion m3 of standing timber, roundwood production volume has held steady since 1990. In British Columbia, the National Forest Inventory—British Columbia Program (NFI-B.C.) is used to track and monitor the current status of the forests. It involves both ground plots and remote sensing. The most recent B.C. State of the Forests is one of the most comprehensive reports among all jurisdictions, using 24 topic areas, with each topic comprising several indicators of sustainable forest management. We conclude that British Columbia ranks high among other jurisdictions on several key sustainable forest management parameters with legislation and forest management regimes aiming to meet the environmental, social and economic needs of current and future generations.

Steigende Bestandszahlen bei Spechten und anderen Vogelarten dank Zunahme von Totholz? | An increase in the population of woodpeckers and other bird species thanks to an increase in the quantities of deadwood?

2009 ◽  
Vol 160 (11) ◽  
pp. 334-340 ◽  
Author(s):  
Pierre Mollet ◽  
Niklaus Zbinden ◽  
Hans Schmid
Keyword(s):  
Forest Inventory ◽  
Bird Species ◽  
National Forest Inventory ◽  
Population Increase ◽  
National Forest ◽  
Forest Species ◽  
Breeding Populations ◽  
Willow Tit ◽  
Middle Spotted Woodpecker ◽  
Important Habitat

Results from the monitoring programs of the Swiss Ornithological Institute show that the breeding populations of several forest species for which deadwood is an important habitat element (black woodpecker, great spotted woodpecker, middle spotted woodpecker, lesser spotted woodpecker, green woodpecker, three-toed woodpecker as well as crested tit, willow tit and Eurasian tree creeper) have increased in the period 1990 to 2008, although not to the same extent in all species. At the same time the white-backed woodpecker extended its range in eastern Switzerland. The Swiss National Forest Inventory shows an increase in the amount of deadwood in forests for the same period. For all the mentioned species, with the exception of green and middle spotted woodpecker, the growing availability of deadwood is likely to be the most important factor explaining this population increase.

scholarly journals Mapping forest age using National Forest Inventory, airborne laser scanning, and Sentinel-2 data

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Johannes Schumacher ◽  
Marius Hauglin ◽  
Rasmus Astrup ◽  
Johannes Breidenbach
Keyword(s):  
Forest Inventory ◽  
Regression Models ◽  
Laser Scanning ◽  
Site Index ◽  
National Forest Inventory ◽  
Airborne Laser Scanning ◽  
National Forest ◽  
Practical Applications ◽  
Airborne Laser ◽  
Sentinel 2

Abstract Background The age of forest stands is critical information for forest management and conservation, for example for growth modelling, timing of management activities and harvesting, or decisions about protection areas. However, area-wide information about forest stand age often does not exist. In this study, we developed regression models for large-scale area-wide prediction of age in Norwegian forests. For model development we used more than 4800 plots of the Norwegian National Forest Inventory (NFI) distributed over Norway between latitudes 58° and 65° N in an 18.2 Mha study area. Predictor variables were based on airborne laser scanning (ALS), Sentinel-2, and existing public map data. We performed model validation on an independent data set consisting of 63 spruce stands with known age. Results The best modelling strategy was to fit independent linear regression models to each observed site index (SI) level and using a SI prediction map in the application of the models. The most important predictor variable was an upper percentile of the ALS heights, and root mean squared errors (RMSEs) ranged between 3 and 31 years (6% to 26%) for SI-specific models, and 21 years (25%) on average. Mean deviance (MD) ranged between − 1 and 3 years. The models improved with increasing SI and the RMSEs were largest for low SI stands older than 100 years. Using a mapped SI, which is required for practical applications, RMSE and MD on plot level ranged from 19 to 56 years (29% to 53%), and 5 to 37 years (5% to 31%), respectively. For the validation stands, the RMSE and MD were 12 (22%) and 2 years (3%), respectively. Conclusions Tree height estimated from airborne laser scanning and predicted site index were the most important variables in the models describing age. Overall, we obtained good results, especially for stands with high SI. The models could be considered for practical applications, although we see considerable potential for improvements if better SI maps were available.

scholarly journals Classifying Forest Type in the National Forest Inventory Context with Airborne Hyperspectral and Lidar Data

2021 ◽  
Vol 13 (10) ◽  
pp. 1863
Author(s):  
Caileigh Shoot ◽  
Hans-Erik Andersen ◽  
L. Monika Moskal ◽  
Chad Babcock ◽  
Bruce D. Cook ◽  
...  
Keyword(s):  
Random Forest ◽  
Forest Inventory ◽  
Forest Type ◽  
Vegetation Indices ◽  
National Forest Inventory ◽  
Classification Algorithm ◽  
Lidar Data ◽  
National Forest ◽  
Interior Alaska ◽  
Type Information

Forest structure and composition regulate a range of ecosystem services, including biodiversity, water and nutrient cycling, and wood volume for resource extraction. Forest type is an important metric measured in the US Forest Service Forest Inventory and Analysis (FIA) program, the national forest inventory of the USA. Forest type information can be used to quantify carbon and other forest resources within specific domains to support ecological analysis and forest management decisions, such as managing for disease and pests. In this study, we developed a methodology that uses a combination of airborne hyperspectral and lidar data to map FIA-defined forest type between sparsely sampled FIA plot data collected in interior Alaska. To determine the best classification algorithm and remote sensing data for this task, five classification algorithms were tested with six different combinations of raw hyperspectral data, hyperspectral vegetation indices, and lidar-derived canopy and topography metrics. Models were trained using forest type information from 632 FIA subplots collected in interior Alaska. Of the thirty model and input combinations tested, the random forest classification algorithm with hyperspectral vegetation indices and lidar-derived topography and canopy height metrics had the highest accuracy (78% overall accuracy). This study supports random forest as a powerful classifier for natural resource data. It also demonstrates the benefits from combining both structural (lidar) and spectral (imagery) data for forest type classification.

Assessing forest resource damage following natural disasters using national forest inventory plots

2022 ◽  
Author(s):  
Tom Brandeis ◽  
Jeffery Turner ◽  
Andrés Baeza Motes ◽  
Mark Brown ◽  
Samuel Lambert
Keyword(s):  
Natural Disasters ◽  
Forest Inventory ◽  
National Forest Inventory ◽  
National Forest ◽  
Forest Resource
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