Introduction

Vidal, Claude; Sallnäs, Ola; Redmond, John; Alberdi, Iciar; Barreiro, Susana; Hernández, Laura; Schadauer, Klemens

doi:10.1007/978-3-319-44015-6_1

Cited by 11 publications

(8 citation statements)

References 14 publications

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“…For NFI purposes, Vidal et al (2016a) defined shrub cover as the "horizontal projection of the outermost crown limits of a shrub or a group of shrubs." When applied to a single species, the result it is called "species cover" and when applied without distinctions among species is called "total cover" (Wilson 2011).…”

Section: Introductionmentioning

confidence: 99%

Mean species cover: a harmonized indicator of shrub cover for forest inventories

et al. 2018

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Because shrub cover is related to many forest ecosystem functions, it is one of the most relevant variables for describing these communities. Nevertheless, a harmonized indicator of shrub cover for large-scale reporting is lacking. The aims of the study were threefold: to define a shrub indicator that can be used by European countries for harmonized shrub cover estimation using data from their respective national forest inventories (NFIs); to quantify the effects of using different NFI field cover scales; and to establish bridges to facilitate harmonized estimation. Data for shrub species cover from the Third Spanish NFI together with scales for cover assessment from 16 European NFIs were used. The indicator, mean species cover (MSC), was defined for each species and each European forest category. Estimates of MSC calculated using species covers recorded for field plots, with 1% interval widths (MSCobs), were compared with the MSC values that would be obtained for the same data with the different European cover scales (MSCpred). Residuals calculated as differences between MSCobs and MSCpred were analyzed, and a linear mixed model was used as bridging function to adjust predictions and thus further harmonize estimates. Scales with only two or three intervals produced the greatest residuals, while all the other analyzed scales had residuals less than 5%. Most scales, except those most similar to Braun-Blanquet, displayed a tendency to be unreliable for larger covers. The proposed mean species cover indicator provides comparable estimates for shrub communities at large scales. The linear models improved the harmonization of MSC for the scales having two and three intervals. Keywords Vegetation • National forest inventories • Braun-Blanquet cover scale • European forest categories • Bridge function • Linear mixed model Abbreviations EFC European forest categories SNFI-3 Third Spanish national forest inventory NFIs National forest inventories MSC Mean species cover ME Mean error MAE Mean absolute error RMSE Root mean square error

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Section: Introductionmentioning

confidence: 99%

Mean species cover: a harmonized indicator of shrub cover for forest inventories

et al. 2018

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“…This process was intended to ensure inclusiveness of the analysis and detect unanticipated relationships, meaningful to the issue of current forest inflation. Weighted correlations and weighted regression analyses were systematically computed, with countries’ forest area in 2015 as the weighting vector across countries most able to fulfil the requirements of the international UN/FAO forest definition owing to the increased implementation of NFI programs across Europe [ 97 ]. Weighted correlations and associated t-tests were computed with weights package of R. Weighted regressions and associated t-tests and R2 were computed with the standard lm function of R. P-values delivered all along the manuscript refer to these tests.…”

Section: Methodsmentioning

confidence: 99%

Inflation of wood resources in European forests: The footprints of a big-bang

Bontemps

2021

PLoS ONE

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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.

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“…Each cluster has 4 sample plots. They are situated on each 250 m length side of square 25 m from its angles [19]. At plot establishment, the following data were recorded for every sample tree: the species, the diameter over bark at 1.30 m high and measured to the nearest millimeter and the total height to the nearest quarter meter.…”

Section: Methodsmentioning

confidence: 99%

New Insights into Tree Height Distribution Based on Mixed Effects Univariate Diffusion Processes

Rupšys

2016

PLoS ONE

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The aim of this paper is twofold: to introduce the mathematics of stochastic differential equations (SDEs) for forest dynamics modeling and to describe how such a model can be applied to aid our understanding of tree height distribution corresponding to a given diameter using the large dataset provided by the Lithuanian National Forest Inventory (LNFI). Tree height-diameter dynamics was examined with Ornstein-Uhlenbeck family mixed effects SDEs. Dynamics of a tree height, volume and their coefficients of variation, quantile regression curves of the tree height, and height-diameter ratio were demonstrated using newly developed tree height distributions for a given diameter. The parameters were estimated by considering a discrete sample of the diameter and height and by using an approximated maximum likelihood procedure. All models were evaluated using a validation dataset. The dataset provided by the LNFI (2006–2010) of Scots pine trees is used in this study to estimate parameters and validate our modeling technique. The verification indicated that the newly developed models are able to accurately capture the behavior of tree height distribution corresponding to a given diameter. All of the results were implemented in a MAPLE symbolic algebra system.

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Introduction

Cited by 11 publications

References 14 publications

Mean species cover: a harmonized indicator of shrub cover for forest inventories

Mean species cover: a harmonized indicator of shrub cover for forest inventories

Inflation of wood resources in European forests: The footprints of a big-bang

New Insights into Tree Height Distribution Based on Mixed Effects Univariate Diffusion Processes

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