A century of national forest inventories – informing past, present and future decisions

In 2019, 100 years had elapsed since the first National Forest Inventory (NFI) was established in Norway. Motivated by a fear of over-exploitation of timber resources, NFIs today enable informed policy making by providing data vital to decision support at international, national, regional, and local scales. This Collection of articles celebrates the 100th anniversary of NFIs with a description of past, present, and future research aiming at improving the monitoring of forest and other terrestrial ecosystems.

The Timber Footprint of the German Bioeconomy—State of the Art and Past Development

The article gives a comprehensive overview of the roundwood equivalents (RE) consumed in the German bioeconomy from Germany and abroad between 1995 and 2015, i.e., the Timber Footprint of final Consumption (TFPcon). The calculation is based on an adapted version of Exiobase 3.4. The sustainability of roundwood procurement for the TFPcon is assessed. A systematic embedding of the tree compartments considered in the TFP in the context of national forest inventories and material flow analysis is presented. The results show that, in 2015, the total volume of the TFPcon of Germany is 90 Mm3 (slightly above the 1995 level) and is composed of 61% coniferous and 39% non-coniferous wood. Germany is strongly dependent on roundwood sourced from abroad and thus was a net importer of RE in 2015. Among the 17 countries with the largest supply of RE for the TFPcon, around one third very likely include large shares of roundwood procured from deforestation or clear-cutting. The self-sufficiency rate in 2015 was only 76%. It would be possible to increase domestic roundwood production by 8–41% (mainly in the hardwood sector) without exceeding the sustainability limits as defined in the WEHAM scenarios.

No “Abrupt increase in harvested forest area over Europe after 2015” – How the misuse of a satellite-based map led to completely wrong conclusions

<p>In a recent <em>Nature </em>article, the satellite-based Global Forest Change (GFC) map was used to estimate the yearly harvest area in each of the EU26-states over the period 2004 to 2018 (Ceccherini et al. 2020). Finland and Sweden were identified as the countries with the largest harvest increases and the biggest effect on the EU’s climate policy strategy. Here, we employ more than 45,000 field observations from the Finnish and Swedish national forest inventories as reference observations to analyze the accuracy of GFC data. We find that harvested area increases only marginally, if at all, after 2015. What did increase abruptly after 2015, however, was GFC’s sensitivity to detect harvested areas and thinnings.</p><p>The results of the <em>Nature </em>article are therefore a consequence of an inconsistent time series in GFC due to a change in the mapping algorithm or the sensor system and are thus both incorrect and misleading. The article is thus a good example for how wrong results based on satellite data can be, if no adequate estimators utilizing reference data are used.</p><p> </p><p>References</p><p>Ceccherini, G. et al. Abrupt increase in harvested forest area over Europe after 2015. Nature 583, 72-77 (2020).</p>

Lessons learned from assessing the cover and yield of bilberry and lingonberry using the national forest inventories in Finland and Sweden

Bilberry ( L.) and lingonberry ( L.) can be a part of healthy diet and are important for many animals. Two approaches are described to assessing their vegetation cover and berry yield via national forest inventory (NFI) observations. The aim was to provide estimates and predictions of the abundance and yield of the species at regional and national levels in Finland and Sweden. In Finland, the model-based predictions are used in evaluating the impacts of cutting intensity on forest berries needed in forest-related decision making. In Sweden, seasonal inventory-based estimates are used to evaluate the annual national and regional berry yields, and in a forecasting system aimed at large public and berry enterprises. Based on the NFI sample plots measured between 2014 and 2018, the total annual yields are estimated to be 208 Mkg of bilberry and 246 Mkg of lingonberry on productive forest land (increment at least 1 m ha year) in Finland, and 336 and 382 Mkg respectively in Sweden (average of NFI inventories in 2015–2019). The predicted development of berry yields is related to the intensity of cuttings in alternative forest management scenarios: lower removals favoured bilberry, and higher removals lingonberry. The model-based method describes the effects of stand development and management on berry yields, whereas the inventory-based method can calibrate seasonal estimates through field observations. In providing spatially and timely more accurate information concerning seasonal berry yields, an assessment of berry yields should involve the elements of both inventory-based and model-based approaches described in this study.Vaccinium myrtillusV. vitis-idaea3–1–1

Use of Remote Sensing Data to Improve the Efficiency of National Forest Inventories: A Case Study from the United States National Forest Inventory

Globally, forests are a crucial natural resource, and their sound management is critical for human and ecosystem health and well-being. Efforts to manage forests depend upon reliable data on the status of and trends in forest resources. When these data come from well-designed natural resource monitoring (NRM) systems, decision makers can make science-informed decisions. National forest inventories (NFIs) are a cornerstone of NRM systems, but require capacity and skills to implement. Efficiencies can be gained by incorporating auxiliary information derived from remote sensing (RS) into ground-based forest inventories. However, it can be difficult for countries embarking on NFI development to choose among the various RS integration options, and to develop a harmonized vision of how NFI and RS data can work together to meet monitoring needs. The NFI of the United States, which has been conducted by the USDA Forest Service’s (USFS) Forest Inventory and Analysis (FIA) program for nearly a century, uses RS technology extensively. Here we review the history of the use of RS in FIA, beginning with general background on NFI, FIA, and sampling statistics, followed by a description of the evolution of RS technology usage, beginning with paper aerial photography and ending with present day applications and future directions. The goal of this review is to offer FIA’s experience with NFI-RS integration as a case study for other countries wishing to improve the efficiency of their NFI programs.

Characterisation of Woody Necromass in Beech Forests with Different Anthropic Accessibility: The Case of La Rioja (Spain)

In this study, a comprehensive analysis of deadwood was conducted in four macro-areas located in two beech forests of public utility in Enciso (La Rioja, Spain). Dendrometric data, as well as qualitative and quantitative characteristics of deadwood, were collected and analysed with respect to the degree of accessibility to the forest to determine the effect of different levels of forest accessibility on deadwood volume and carbon stocks. All decomposition classes were present except the first, highlighting the development of natural degradation dynamics. Deadwood stored 6.9 t/ha of C in the easy accessibility class, 5.7 t/ha of C in the medium accessibility class and 2.2 t/ha of C in the difficult accessibility class. The average volume of deadwood and carbon stored calculated in this study were higher than the values reported in the Spanish and Italian national forest inventories, including one developed for Riojan beech forests. Deadwood volume was on average 22.5 m3/ha, showing an unequal distribution, with the lowest values found far from the access roads, despite forest accessibility generally being considered a factor that facilitates the human collection of deadwood. The distribution patterns of deadwood in beech forests of La Rioja, apparently counterintuitive, were due to a combination of different factors, including slope, cattle grazing, and weather conditions which might have favoured downward movement of the deadwood.