Fehrmann, Lutz

[["dc.bibliographiccitation.issue","13"],["dc.bibliographiccitation.journal","AFZ, der Wald"],["dc.bibliographiccitation.volume","68"],["dc.contributor.author","Stangler, D."],["dc.contributor.author","Schreiner, S."],["dc.contributor.author","Lu, Y."],["dc.contributor.author","Hoffmann, S."],["dc.contributor.author","Fehrmann, Lutz"],["dc.contributor.author","Makeschin, F."],["dc.contributor.author","Spieker, H."],["dc.contributor.author","Kleinn, Christoph"],["dc.date.accessioned","2017-09-07T11:49:03Z"],["dc.date.available","2017-09-07T11:49:03Z"],["dc.date.issued","2013"],["dc.identifier.gro","3149588"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/6271"],["dc.notes.status","public"],["dc.notes.submitter","chake"],["dc.title","Chinas Forstwirtschaft vor großen Herausforderungen"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","319"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","New Forests"],["dc.bibliographiccitation.lastpage","332"],["dc.bibliographiccitation.volume","47"],["dc.contributor.author","Tang, Xiaolu"],["dc.contributor.author","Lu, Yuanchang"],["dc.contributor.author","Fehrmann, Lutz"],["dc.contributor.author","Forrester, David I."],["dc.contributor.author","Guisasola-Rodríguez, Rubén"],["dc.contributor.author","Pérez-Cruzado, César"],["dc.contributor.author","Kleinn, Christoph"],["dc.date.accessioned","2017-11-28T09:52:29Z"],["dc.date.available","2017-11-28T09:52:29Z"],["dc.date.issued","2015"],["dc.description.abstract","Chinese fir [(Cunninghamia lanceolata (Lamb.) Hook] is one of the most important plantation tree species in subtropical China, accounting for about 21 % of China’s total forest plantation area. Although many studies have been conducted in Chinese fir plantations, uncertainties remain regarding its potential and dynamics to sequestrate carbon as a function of stand type, stand age and management. In this study, we applied tree ring analysis as a retrospective tool to study tree- and stand-level aboveground biomass (AGB) dynamics in a 17-year old Chinese fir plantation in Shitai County, Anhui Province, China. A total of 18 trees from different dominance classes were felled for the stem analyses: 6 dominant, 6 co-dominant and 6 suppressed trees. The stem analyses showed that as expected the annual increments of dbh and AGB were significantly higher for dominant trees than those for co-dominant and suppressed trees. Total stand-level AGB increased from 1.85 t ha−1 at age 3 years to 108.12 t ha−1 at age 17 years. Splitting the stand into dominance classes, tree analysis was useful to explain variation of the stand-level AGB and provided more detailed information about the growth dynamics of the stands. Tree ring analyses offer a viable and efficient approach to retrospectively study tree growth and AGB accumulation dynamics in Chinese fir plantations. In the studied stand under the given management regime, a rotation period of 17 years would optizimise AGB productivity."],["dc.identifier.doi","10.1007/s11056-015-9518-0"],["dc.identifier.fs","622632"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/10568"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.relation.eissn","1573-5095"],["dc.relation.issn","0169-4286"],["dc.title","Estimation of stand-level aboveground biomass dynamics using tree ring analysis in a Chinese fir plantation in Shitai County, Anhui Province, China"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","366"],["dc.bibliographiccitation.journal","Forest Ecology and Management"],["dc.bibliographiccitation.lastpage","374"],["dc.bibliographiccitation.volume","310"],["dc.contributor.author","Seidel, Dominik"],["dc.contributor.author","Leuschner, Christoph"],["dc.contributor.author","Scherber, Christoph"],["dc.contributor.author","Beyer, Friderike"],["dc.contributor.author","Wommelsdorf, Tobias"],["dc.contributor.author","Cashman, Matthew Joseph"],["dc.contributor.author","Fehrmann, Lutz"],["dc.date.accessioned","2018-08-09T16:03:40Z"],["dc.date.available","2018-08-09T16:03:40Z"],["dc.date.issued","2013"],["dc.description.abstract","The relationship between tree species richness and forest productivity is not well understood. We used ground-based laser scanning for analyzing the canopy structure and three-dimensional space filling by foliage and twigs in a species-rich temperate old-growth forest to test the hypotheses that (i) canopy space filling increases with tree species richness, and (ii) a higher degree of canopy space filling in diverse stands is linked to higher aboveground productivity (NPPa). Space filling was quantified in 80 plots with variable species composition (five species) and species richness (1–3 species) and related to stem wood and litter production. Neither space filling nor NPPa were higher in more diverse than monospecific plots, while species identity had a significant effect on the patterns of space occupation in the sun and shade crown. We conclude that increased complementarity in canopy space filling among the species is not an important productivity-determining factor in this temperate mixed forest."],["dc.identifier.doi","10.1016/j.foreco.2013.08.058"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/15244"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.title","The relationship between tree species richness, canopy space exploration and productivity in a temperate broad-leaf mixed forest"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","iForest - Biogeosciences and Forestry"],["dc.bibliographiccitation.lastpage","11"],["dc.bibliographiccitation.volume","7"],["dc.contributor.author","Beckschäfer, Philip"],["dc.contributor.author","Fehrmann, Lutz"],["dc.contributor.author","Harrison, Rhett D."],["dc.contributor.author","Xu, Jianchu"],["dc.contributor.author","Kleinn, Christoph"],["dc.date.accessioned","2017-09-07T11:47:03Z"],["dc.date.available","2017-09-07T11:47:03Z"],["dc.date.issued","2013"],["dc.description.abstract","Canopy leaf area, frequently quantified by the Leaf Area Index (LAI), serves as the dominant control over primary production, energy exchange, transpiration, and other physiological attributes related to ecosystem processes. Maps depicting the spatial distribution of LAI across the landscape are of particularly high value for a better understanding of ecosystem dynamics and processes, especially over large and remote areas. Moreover, LAI maps have the potential to be used by process models describing energy and mass exchanges in the biosphere/atmosphere system. In this article we assess the applicability of the RapidEye satellite system, whose sensor is optimized towards vegetation analyses, for mapping LAI along a disturbance gradient, ranging from heavily disturbed shrub land to mature mountain rainforest. By incorporating image texture features into the analysis, we aim at assessing the potential quality improvement of LAI maps and the reduction of uncertainties associated with LAI maps compared to maps based on Vegetation Indexes (VI) solely. We identified 22 out of the 59 image features as being relevant for predicting LAI. Among these, especially VIs were ranked high. In particular, the two VIs using RapidEye’s RED-EDGE band stand out as the top two predictor variables. Nevertheless, map accuracy as quantified by the mean absolute error obtained from a 10-fold cross validation (MAE_CV) increased significantly if VIs and texture features are combined (MAE_CV = 0.56), compared to maps based on VIs only (MAE_CV = 0.62). We placed special emphasis on the uncertainties associated with the resulting map addressing that map users often treat uncertainty statements only in a pro-forma manner. Therefore, the LAI map was complemented with a map depicting the spatial distribution of the goodness-of-fit of the model, quantified by the mean absolute error (MAE), used for predictive mapping. From this an area weighted MAE (= 0.35) was calculated and compared to the unweighted MAE of 0.29. Mapping was done using randomForest, a widely used statistical modeling technique for predictive biological mapping."],["dc.identifier.doi","10.3832/ifor0968-006"],["dc.identifier.gro","3149244"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/5900"],["dc.language.iso","en"],["dc.notes.intern","Kleinn Crossref Import"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation.issn","1971-7458"],["dc.title","Mapping Leaf Area Index in subtropical upland ecosystems using RapidEye imagery and the randomForest algorithm"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","412"],["dc.bibliographiccitation.issue","2-3"],["dc.bibliographiccitation.journal","Forest Ecology and Management"],["dc.bibliographiccitation.lastpage","421"],["dc.bibliographiccitation.volume","236"],["dc.contributor.author","Fehrmann, Lutz"],["dc.contributor.author","Kleinn, Christoph"],["dc.date.accessioned","2017-09-07T11:47:11Z"],["dc.date.available","2017-09-07T11:47:11Z"],["dc.date.issued","2006"],["dc.description.abstract","Allometric relations for tree growth modelling have been subject to research for decades, partly as empirical models, and partly as process models such as the pipe model, hydraulic architecture, mechanical approaches or the fractal-like nature of plant architecture. Unlike empirical studies, process models aim at explaining the scaling within tree architecture as a function of biological, physical or mechanical factors and at modelling their effect on functionality and growth of different parts of an individual tree. The goal of the underlying study is to link theoretical explanation to empirical approaches of tree biomass estimation by the example of Norway spruce (Picea abies [L.] Karst.). Decisively, this article tries to take allometry out of the purely curve-fitting exercise common in literature and derives implications for the use of allometric biomass functions. Our results demonstrate that the dbh as independent variable might be misleading for the comparison of universal scaling laws with empirical studies. We were able to show, that the use of a recalculated diameter in relative stem height by means of a taper form model confirms general biological implications better than the dbh measured at a fixed tree height. We used a compiled dataset of altogether 245 trees that were measured on different sites in central Europe to proof our consideration. As one result we estimated a scaling factor b of 2.65 for the allometric relation (agb = aAllometric relations for tree growth modelling have been subject to research for decades, partly as empirical models, and partly as process models such as the pipe model, hydraulic architecture, mechanical approaches or the fractal-like nature of plant architecture. Unlike empirical studies, process models aim at explaining the scaling within tree architecture as a function of biological, physical or mechanical factors and at modelling their effect on functionality and growth of different parts of an individual tree. The goal of the underlying study is to link theoretical explanation to empirical approaches of tree biomass estimation by the example of Norway spruce (Picea abies [L.] Karst.). Decisively, this article tries to take allometry out of the purely curve-fitting exercise common in literature and derives implications for the use of allometric biomass functions. Our results demonstrate that the dbh as independent variable might be misleading for the comparison of universal scaling laws with empirical studies. We were able to show, that the use of a recalculated diameter in relative stem height by means of a taper form model confirms general biological implications better than the dbh measured at a fixed tree height. We used a compiled dataset of altogether 245 trees that were measured on different sites in central Europe to proof our consideration. As one result we estimated a scaling factor b of 2.65 for the allometric relation (agb = aAllometric relations for tree growth modelling have been subject to research for decades, partly as empirical models, and partly as process models such as the pipe model, hydraulic architecture, mechanical approaches or the fractal-like nature of plant architecture. Unlike empirical studies, process models aim at explaining the scaling within tree architecture as a function of biological, physical or mechanical factors and at modelling their effect on functionality and growth of different parts of an individual tree. The goal of the underlying study is to link theoretical explanation to empirical approaches of tree biomass estimation by the example of Norway spruce (Picea abies [L.] Karst.). Decisively, this article tries to take allometry out of the purely curve-fitting exercise common in literature and derives implications for the use of allometric biomass functions. Our results demonstrate that the dbh as independent variable might be misleading for the comparison of universal scaling laws with empirical studies. We were able to show, that the use of a recalculated diameter in relative stem height by means of a taper form model confirms general biological implications better than the dbh measured at a fixed tree height. We used a compiled dataset of altogether 245 trees that were measured on different sites in central Europe to proof our consideration. As one result we estimated a scaling factor b of 2.65 for the allometric relation (agb = aAllometric relations for tree growth modelling have been subject to research for decades, partly as empirical models, and partly as process models such as the pipe model, hydraulic architecture, mechanical approaches or the fractal-like nature of plant architecture. Unlike empirical studies, process models aim at explaining the scaling within tree architecture as a function of biological, physical or mechanical factors and at modelling their effect on functionality and growth of different parts of an individual tree. The goal of the underlying study is to link theoretical explanation to empirical approaches of tree biomass estimation by the example of Norway spruce (Picea abies [L.] Karst.). Decisively, this article tries to take allometry out of the purely curve-fitting exercise common in literature and derives implications for the use of allometric biomass functions. Our results demonstrate that the dbh as independent variable might be misleading for the comparison of universal scaling laws with empirical studies. We were able to show, that the use of a recalculated diameter in relative stem height by means of a taper form model confirms general biological implications better than the dbh measured at a fixed tree height. We used a compiled dataset of altogether 245 trees that were measured on different sites in central Europe to proof our consideration. As one result we estimated a scaling factor b of 2.65 for the allometric relation (agb = aD) between a diameter in relative stem height (D0.1) and aboveground biomass (agb), which is close to scaling relations predicted by process models. The standard error of a linear regression model based on the log-transformed variables could be slightly reduced to 0.21 (R2 = 0.98) when we used the diameter in relative tree height.) between a diameter in relative stem height (D0.1) and aboveground biomass (agb), which is close to scaling relations predicted by process models. The standard error of a linear regression model based on the log-transformed variables could be slightly reduced to 0.21 (R2 = 0.98) when we used the diameter in relative tree height.) between a diameter in relative stem height (D0.1) and aboveground biomass (agb), which is close to scaling relations predicted by process models. The standard error of a linear regression model based on the log-transformed variables could be slightly reduced to 0.21 (R2 = 0.98) when we used the diameter in relative tree height.) between a diameter in relative stem height (D0.1) and aboveground biomass (agb), which is close to scaling relations predicted by process models. The standard error of a linear regression model based on the log-transformed variables could be slightly reduced to 0.21 (R2 = 0.98) when we used the diameter in relative tree height."],["dc.identifier.doi","10.1016/j.foreco.2006.09.026"],["dc.identifier.gro","3149273"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/5931"],["dc.language.iso","en"],["dc.notes.intern","Kleinn Crossref Import"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation.issn","0378-1127"],["dc.title","General considerations about the use of allometric equations for biomass estimation on the example of Norway spruce in central Europe"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","20"],["dc.bibliographiccitation.journal","Biomass and Bioenergy"],["dc.bibliographiccitation.lastpage","25"],["dc.bibliographiccitation.volume","47"],["dc.contributor.author","Seidel, D."],["dc.contributor.author","Albert, Katja"],["dc.contributor.author","Fehrmann, L."],["dc.contributor.author","Ammer, C."],["dc.date.accessioned","2017-09-07T11:47:48Z"],["dc.date.available","2017-09-07T11:47:48Z"],["dc.date.issued","2012"],["dc.description.abstract","Methods for estimating the biomass potential of dense coppice in coppice-with-standard forests in a fast and objective way are currently rare. We adapted existing methodical approaches for biomass estimations from terrestrial laser scanning developed for mature stands in order to perform single scan measurements of diameter at breast height in extremely dense coppice with a stem density of 30,000 ha−1. Diameter was then used as input for allometric regression models for estimations of the dry weights. As a tribute to the dense stocking on the investigated stands study plots were smaller than in previous studies focusing on mature forests. Results were found to be sound with a mean absolute error of about 6.9 kg which is equal to a relative error of 11.1%. With respect to the strongly reduced amount of field work the method is therefore of high efficiency. With the new approach reliable assessments of the bioenergy potentials become possible for coppice stands, which might play an important role in future tasks of mitigating climate change."],["dc.identifier.doi","10.1016/j.biombioe.2012.10.009"],["dc.identifier.gro","3146769"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/4570"],["dc.language.iso","en"],["dc.notes.status","zu prüfen"],["dc.relation.issn","0961-9534"],["dc.title","The potential of terrestrial laser scanning for the estimation of understory biomass in coppice-with-standard systems"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","223"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Environmental and Ecological Statistics"],["dc.bibliographiccitation.lastpage","237"],["dc.bibliographiccitation.volume","18"],["dc.contributor.author","Yang, Haijun"],["dc.contributor.author","Kleinn, Christoph"],["dc.contributor.author","Fehrmann, Lutz"],["dc.contributor.author","Tang, Shouzheng"],["dc.contributor.author","Magnussen, Steen"],["dc.date.accessioned","2017-09-07T11:47:09Z"],["dc.date.available","2017-09-07T11:47:09Z"],["dc.date.issued","2009"],["dc.description.abstract","Adaptive cluster sampling (ACS) is a sampling technique for sampling rare and geographically clustered populations. Aiming to enhance the practicability of ACS while maintaining some of its major characteristics, an adaptive sample plot design is introduced in this study which facilitates field work compared to “standard” ACS. The plot design is based on a conditional plot expansion: a larger plot (by a pre-defined plot size factor) is installed at a sample point instead of the smaller initial plot if a pre-defined condition is fulfilled. This study provides insight to the statistical performance of the proposed adaptive plot design. A design-unbiased estimator is presented and used on six artificial and one real tree position maps to estimate density (number of objects per ha). The performance in terms of coefficient of variation is compared to the non-adaptive alternative without a conditional expansion of plot size. The adaptive plot design was superior in all cases but the improvement depends on (1) the structure of the sampled population, (2) the plot size factor and (3) the critical value (the minimum number of objects triggering an expansion). For some spatial arrangements the improvement is relatively small. The adaptive design may be particularly attractive for sampling in rare and compactly clustered populations with an appropriately chosen plot size factor."],["dc.identifier.doi","10.1007/s10651-009-0129-9"],["dc.identifier.gro","3149274"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/6653"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/5933"],["dc.language.iso","en"],["dc.notes.intern","Kleinn Crossref Import"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation.issn","1352-8505"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","A new design for sampling with adaptive sample plots"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","no"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1041"],["dc.bibliographiccitation.issue","5"],["dc.bibliographiccitation.journal","Remote Sensing"],["dc.bibliographiccitation.volume","13"],["dc.contributor.author","Pérez-Cruzado, César"],["dc.contributor.author","Kleinn, Christoph"],["dc.contributor.author","Magdon, Paul"],["dc.contributor.author","Álvarez-González, Juan Gabriel"],["dc.contributor.author","Magnussen, Steen"],["dc.contributor.author","Fehrmann, Lutz"],["dc.contributor.author","Nölke, Nils"],["dc.date.accessioned","2021-04-14T08:27:52Z"],["dc.date.available","2021-04-14T08:27:52Z"],["dc.date.issued","2021"],["dc.description.sponsorship","Forest Research Institute of the German Federal State of Rheinland-Pfalz (FAWF) in Trippstadt"],["dc.identifier.doi","10.3390/rs13051041"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/82431"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.publisher","MDPI"],["dc.relation.eissn","2072-4292"],["dc.rights","https://creativecommons.org/licenses/by/4.0/"],["dc.title","The Horizontal Distribution of Branch Biomass in European Beech: A Model Based on Measurements and TLS Based Proxies"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","107"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Environmental and Ecological Statistics"],["dc.bibliographiccitation.lastpage","123"],["dc.bibliographiccitation.volume","19"],["dc.contributor.author","Fehrmann, Lutz"],["dc.contributor.author","Gregoire, Timothy G."],["dc.contributor.author","Kleinn, Christoph"],["dc.date.accessioned","2017-09-07T11:47:09Z"],["dc.date.available","2017-09-07T11:47:09Z"],["dc.date.issued","2011"],["dc.identifier.doi","10.1007/s10651-011-0177-9"],["dc.identifier.gro","3149278"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/7540"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/5937"],["dc.notes.intern","Kleinn Crossref Import"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","public"],["dc.notes.submitter","chake"],["dc.publisher","Springer Nature"],["dc.relation.issn","1352-8505"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","Triangulation based inclusion probabilities: a design-unbiased sampling approach"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","300"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","Scandinavian Journal of Forest Research"],["dc.bibliographiccitation.lastpage","312"],["dc.bibliographiccitation.volume","34"],["dc.contributor.author","Magnussen, Steen"],["dc.contributor.author","Fehrmann, Lutz"],["dc.date.accessioned","2020-12-10T18:14:50Z"],["dc.date.available","2020-12-10T18:14:50Z"],["dc.date.issued","2019"],["dc.identifier.doi","10.1080/02827581.2019.1599063"],["dc.identifier.eissn","1651-1891"],["dc.identifier.issn","0282-7581"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/74634"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","In search of a variance estimator for systematic sampling"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]