Point transect sampling of deadwood: a comparison with well-established sampling techniques for the estimation of volume and carbon storage in managed forests

Ritter, Tim; Saborowski, Joachim

doi:10.1007/s10342-012-0637-2

Cited by 17 publications

(11 citation statements)

References 23 publications

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“…For volume estimation, the height and dbh of all standing dead tree and the dbh of logs were measured. The volume of standing and fallen entire deadwoods was estimated by using Huber's (Ritter and Saborowski 2012), and the volume of living trees measured by using regional tariffs based on dbh and height measurements. Then, developmental stages were determined based on ecological consideration and using results of other researchers (e.g., Mataji 1999;Sagheb-Talebi et al 2003), and then, map of stages of the mosaic cycle was created.…”

Section: Methodsmentioning

confidence: 99%

“…Deadwood and its biodiversity play an important role for sustaining forest management and environmental services such as stabilizing forest, soil protection and storing carbon (Ritter and Saborowski 2012). Despite its importance, deadwood is now at a critically low level in many temperate forests, mainly due to inappropriate management practices.…”

Section: Introductionmentioning

confidence: 99%

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Deadwood assessment in different developmental stages of beech (Fagus orientalis Lipsky) stands in Caspian forest ecosystems

Mataji

Sagheb-Talebi

Eshaghirad

2014

Int. J. Environ. Sci. Technol.

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Deadwood is an indicator that addresses many parameters of naturalness and is becoming a general reference for natural forests. If there are enough of the different kinds of deadwood in a forest, then it is likely to be properly natural. Also, it is a practical indicator, representing the health and biodiversity of forests. The aim of this research was to find out how much deadwood should be present in different developmental stages in a natural forest as a reference. For this purpose, a natural forest ecosystem in Mazandaran province, north of Iran, which is located in Noshahr, was selected. Species, diameter and height of all (living and dead) trees in each area were assessed. Then, developmental stages were determined, and their map was produced. The amount of deadwood was determined in different stages. Results showed that all three stages (initial, optimal and decay stage) could be recognized in the studied beech stands. Deadwood rate varied and greatest volume and number of it occurred in decay and initial stages, respectively. The frequency and volume of deadwood depend on the pattern of natural disturbance, developmental stages and stand structure. The amount of deadwood within managed forests is open to debate and requires detailed knowledge about beech stands in local conditions. So, based on these results in natural forests of beech in north of Iran, deadwood volume between 4.9 and 54.3 m 3 ha -1 or 1.1-9.6 % of total volume of wood could be considered as a reasonable amount and each developmental stage must be different.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Deadwood assessment in different developmental stages of beech (Fagus orientalis Lipsky) stands in Caspian forest ecosystems

Mataji

Sagheb-Talebi

Eshaghirad

2014

Int. J. Environ. Sci. Technol.

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“…The low scores of deadwood-related variables of the FSI for Baden-Württemberg (deadwood standing, deadwood downed and deadwood decay classes, see Fig. 3) may be explained through the sampling of this attribute, which has a rare occurrence, on relatively small plots of 5 m radius (Meyer 1999;Ritter and Saborowski 2012). However, large amounts of deadwood, when scaled up to a hectare, can be recorded at individual plots (for example the highest value of downed deadwood (1713 m 3 •ha − 1 ) was the result of only two large trees sampled within the 5 m plot).…”

Section: Assessment Of Absolute Fsi-scoresmentioning

confidence: 99%

Quantifying forest structural diversity based on large-scale inventory data: a new approach to support biodiversity monitoring

2018

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Background: The importance of structurally diverse forests for the conservation of biodiversity and provision of a wide range of ecosystem services has been widely recognised. However, tools to quantify structural diversity of forests in an objective and quantitative way across many forest types and sites are still needed, for example to support biodiversity monitoring. The existing approaches to quantify forest structural diversity are based on small geographical regions or single forest types, typically using only small data sets. Results: Here we developed an index of structural diversity based on National Forest Inventory (NFI) data of Baden-Württemberg, Germany, a state with 1.3 million ha of diverse forest types in different ownerships. Based on a literature review, 11 aspects of structural diversity were identified a priori as crucially important to describe structural diversity. An initial comprehensive list of 52 variables derived from National Forest Inventory (NFI) data related to structural diversity was reduced by applying five selection criteria to arrive at one variable for each aspect of structural diversity. These variables comprise 1) quadratic mean diameter at breast height (DBH), 2) standard deviation of DBH, 3) standard deviation of stand height, 4) number of decay classes, 5) bark-diversity index, 6) trees with DBH ≥ 40 cm, 7) diversity of flowering and fructification, 8) average mean diameter of downed deadwood, 9) mean DBH of standing deadwood, 10) tree species richness and 11) tree species richness in the regeneration layer. These variables were combined into a simple, additive index to quantify the level of structural diversity, which assumes values between 0 and 1. We applied this index in an exemplary way to broad forest categories and ownerships to assess its feasibility to analyse structural diversity in large-scale forest inventories. Conclusions: The forest structure index presented here can be derived in a similar way from standard inventory variables for most other large-scale forest inventories to provide important information about biodiversity relevant forest conditions and thus provide an evidence-base for forest management and planning as well as reporting.

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“…For sampling downed deadwood, FAS and line intersect sampling (LIS) are the most popular methods (Woodall et al 2009a(Woodall et al , 2009b. However, as the occurrence of deadwood in managed forests can be regarded as a stochastically rare event with strong clumping and high local variability (Meyer 1999), FAS is a very inefficient sampling technique for deadwood (Ritter and Saborowski 2012), as well as for other objects having similar characteristics.…”

Section: Introductionmentioning

confidence: 99%

Correcting the nondetection bias of angle count sampling

2013

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The well-known angle count sampling (ACS) has proved to be an efficient sampling technique and has been applied in forest inventories for many decades. However, ACS assumes total visibility of objects; any violation of this assumption leads to a nondetection bias. We present a novel approach, in which the theory of distance sampling is adapted to traditional ACS to correct for the nondetection bias. Two new estimators were developed based on expanding design-based inclusion probabilities by model-based estimates of the detection probabilities. The new estimators were evaluated in a simulation study as well as in a real forest inventory. It is shown that the nondetection bias of the traditional estimator is up to −52.5%, whereas the new estimators are approximately unbiased.Résumé : L'échantillonnage par balayage sous angle constant (EAC) est une technique d'échantillonnage bien connue qui s'est avérée efficace et qui a été appliquée dans les inventaires forestiers pendant de nombreuses décennies. Toutefois, l'EAC assume que tous les objets sont visibles et toute violation de cette hypothèse entraîne un biais de non-détection. Nous présentons une nouvelle approche qui consiste à adapter la théorie de l'échantillonnage selon la distance à l'EAC traditionnel pour corriger le biais de non-détection. Deux nouveaux estimateurs ont été créés en complétant les probabilités d'inclusion basées sur le plan de sondage par les probabilités de détection basées sur un modèle. Les nouveaux estimateurs ont été évalués par une étude de simulation ainsi que par un inventaire forestier réel. Les résultats montrent que le biais de non-détection de l'estimateur traditionnel peut atteindre −52,5 %, alors que les nouveaux estimateurs sont presque exempts de biais. [Traduit par la Rédaction]

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Point transect sampling of deadwood: a comparison with well-established sampling techniques for the estimation of volume and carbon storage in managed forests

Abstract: In managed forests, the occurrence of deadwood (DW) can be regarded as a stochastically rare event with strong clumping and high local variability (Meyer in

Cited by 17 publications

References 23 publications

Deadwood assessment in different developmental stages of beech (Fagus orientalis Lipsky) stands in Caspian forest ecosystems

Deadwood assessment in different developmental stages of beech (Fagus orientalis Lipsky) stands in Caspian forest ecosystems

Quantifying forest structural diversity based on large-scale inventory data: a new approach to support biodiversity monitoring

Correcting the nondetection bias of angle count sampling

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