Concept and Methodology of the National Forest Soil Inventory

Wellbrock, Nicole; Ahrends, Bernd; Bögelein, Rebekka; Bolte, Andreas; Eickenscheidt, Nadine; Grüneberg, Erik; König, Nils; Schmitz, Andreas; Fleck, Stefan; Ziche, Daniel

doi:10.1007/978-3-030-15734-0_1

Cited by 11 publications

(15 citation statements)

References 32 publications

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“…Samples in this data set originate from all over Saxony (18.400 km

). More information on the methodology of the periodic BZE sampling can be found in [ 30 ]. From all 727 available retained samples, we selected a subsample that represents abundant vegetation types and parent materials in Saxony.…”

Section: Methodsmentioning

confidence: 99%

Application of Low-Cost MEMS Spectrometers for Forest Topsoil Properties Prediction

Thomas

Petzold²,

Becker³

et al. 2021

Sensors

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Increasing temperatures and drought occurrences recently led to soil moisture depletion and increasing tree mortality. In the interest of sustainable forest management, the monitoring of forest soil properties will be of increasing importance in the future. Vis-NIR spectroscopy can be used as fast, non-destructive and cost-efficient method for soil parameter estimations. Microelectromechanical system devices (MEMS) have become available that are suitable for many application fields due to their low cost as well as their small size and weight. We investigated the performance of MEMS spectrometers in the visual and NIR range to estimate forest soil samples total C and N content of Ah and Oh horizons at the lab. The results were compared to a full-range device using PLSR and Cubist regression models at local (2.3 ha, n: Ah = 60, Oh = 50) and regional scale (State of Saxony, Germany, 184,000 km2, n: Ah = 186 and Oh = 176). For each sample, spectral reflectance was collected using MEMS spectrometer in the visual (Hamamatsu C12880MA) and NIR (NeoSpetrac SWS62231) range and using a conventional full range device (Veris Spectrophotometer). Both data sets were split into a calibration (70%) and a validation set (30%) to evaluate prediction power. Models were calibrated for Oh and Ah horizon separately for both data sets. Using the regional data, we also used a combination of both horizons. Our results show that MEMS devices are suitable for C and N prediction of forest topsoil on regional scale. On local scale, only models for the Ah horizon yielded sufficient results. We found moderate and good model results using MEMS devices for Ah horizons at local scale (R2≥ 0.71, RPIQ ≥ 2.41) using Cubist regression. At regional scale, we achieved moderate results for C and N content using data from MEMS devices in Oh (R2≥ 0.57, RPIQ ≥ 2.42) and Ah horizon (R2≥ 0.54, RPIQ ≥2.15). When combining Oh and Ah horizons, we achieved good prediction results using the MEMS sensors and Cubist (R2≥ 0.85, RPIQ ≥ 4.69). For the regional data, models using data derived by the Hamamatsu device in the visual range only were least precise. Combining visual and NIR data derived from MEMS spectrometers did in most cases improve the prediction accuracy. We directly compared our results to models based on data from a conventional full range device. Our results showed that the combination of both MEMS devices can compete with models based on full range spectrometers. MEMS approaches reached between 68% and 105% of the corresponding full ranges devices R2 values. Local models tended to be more accurate than regional approaches for the Ah horizon. Our results suggest that MEMS spectrometers are suitable for forest soil C and N content estimation. They can contribute to improved monitoring in the future as their small size and weight could make in situ measurements feasible.

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“…Samples in this data set originate from all over Saxony (18.400 km

Section: Methodsmentioning

confidence: 99%

Application of Low-Cost MEMS Spectrometers for Forest Topsoil Properties Prediction

Thomas

Petzold²,

Becker³

et al. 2021

Sensors

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“…The NFSI I was carried out according to a common sample plot protocol [55] based on the German manual of soil mapping [56]. Soils in the NFSI I grid plots were sampled at eight satellite points around a central soil profile.…”

Section: Organic Layer Mineral Soil and Foliar Samplingmentioning

confidence: 99%

“…Total P concentrations were measured in aqua regia extracts for the organic layer and for the soil depths 0-5 and 5-10 cm. Details regarding soil sampling and analytical methods can be found in [38,41,55,[57][58][59].…”

Section: Organic Layer Mineral Soil and Foliar Samplingmentioning

confidence: 99%

“…After drying, leaves were separated from shoots and samples from the three trees were combined into one composite sample. Samples were prepared (HNO 3 microwave digestion) and P concentrations were measured (using, e.g., ICP, ICP-MS, and AAS) according to the recommended pre-treatment and analysis given in the ICP Forest manual (for more details, see [38,41,55,59,60]). The entire NFSI data set used in this study is available online at https://link.springer.com/book/10.1007/978-3-030-15734-0 [61] and at https://www.thuenen.de/de/wo/arbeitsbereiche/waldmonitoring/bodenzustandserhebung/.…”

Section: Organic Layer Mineral Soil and Foliar Samplingmentioning

confidence: 99%

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Linkages between Phosphorus and Plant Diversity in Central European Forest Ecosystems—Complementarity or Competition?

Rieger

Kowarik

Ziche

et al. 2019

Forests

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The phosphorus nutrition status of European forests has decreased significantly in recent decades. For a deeper understanding of complementarity and competition in terms of P acquisition in temperate forests, we have analyzed α-diversity, organic layer and mineral soil P, P nutrition status, and different concepts of P use efficiency (PUE) in Fagus sylvatica L. (European beech) and Picea abies (L.) H. Karst. (Norway spruce). Using a subset of the Second National Soil Survey in Germany, we correlated available data on P in the organic layer and soil with α-diversity indices for beech and spruce forests overall and for individual vegetation layers (tree, shrub, herb, and moss layers). Moreover, we investigated α-diversity feedbacks on P nutrition status and PUE of both tree species. The overall diversity of both forest ecosystems was largely positively related to P content in the organic layer and soil, but there were differences among the vegetation layers. Diversity in the tree layer of both forest ecosystems was negatively related to the organic layer and soil P. By contrast, shrub diversity showed no correlation to P, while herb layer diversity was negatively related to P in the organic layer but positively to P in soil. A higher tree layer diversity was slightly related to increased P recycling efficiency (PPlant/Porganic layer) in European beech and P uptake efficiency (PPlant/Psoil) in Norway spruce. The diversity in the herb layer was negatively related to P recycling and uptake efficiency in European beech and slightly related to P uptake efficiency in Norway spruce. In spruce forests, overall and herb species richness led to significantly improved tree nutrition status. Our results confirm significant, non-universal relationships between P and diversity in temperate forests with variations among forest ecosystems, vegetation layers, and P in the organic layer or soil. In particular, tree species diversity may enhance complementarity and hence also P nutrition of dominant forest trees through higher PUE, whereas moss and herb layers seemed to show competitive relationships among each other in nutrient cycling.

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“…There is a great effort in monitoring of FFC and SOC stocks through space and time, such as the International Co‐operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests Level II) or extensive national forest soil inventories (NFSI; de Vos et al., 2015; Fleck et al., 2016; Wellbrock et al., 2019). The grid‐based sampling approach in extensive monitoring gives by design representative values for larger areas (Webster and Oliver, 2007).…”

Section: Introductionmentioning

confidence: 99%

Spatial 3D mapping of forest soil carbon stocks in Hesse, Germany

Heitkamp

Ahrends

Evers

et al. 2021

J. Plant Nutr. Soil Sci.

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Background Forest soils are an important reservoir of organic carbon (OC) and a potential source or sink for atmospheric CO2. Prediction of OC stock changes under ongoing climatic and management changes requires a spatial explicit base. Knowledge of the vertical distribution of OC stocks is very important, since varying soil layers may be affected differently by environmental change. Aim Three‐dimensional regionalization of OC stocks of the forest floor (FFC) and 5 cm depth increments of the mineral soil (SOC) of Hesse, Germany. Methods Datasets of the second National Forest Soil Inventory (NFSI II) were used for parametrization of hierarchical generalized additive models (hGAM). Validation was performed by a 10 times repeated 10‐fold cross‐validation, and spatial model uncertainty was assessed. Results Depth‐dependent validation indicated that model performance was best between 15 and 60 cm (amount of variance explained ≈ 0.5). All covariates showed plausible partial effects. FFC stocks were predicted to be highest under coniferous forest with a high influence of N deposition. Climate and potential cation exchange capacity affected SOC stocks markedly, whereas soil class and parent material were most important for the depth distribution. Overall, average predicted OC stocks were between 78.0 and 92.5 t ha−1, amounting to 67.6 to 80.1 Mt for all forest soils of Hesse. Between 16% and 24% were stored in the forest floor. Sixty‐eight percent to 69% of predicted SOC stocks were stored in the upper 30 cm. Model uncertainty was highest at locations with high elevation or ground water influence. Conclusions This work provides the first spatial explicit database for OC stocks of forest soils in Hesse at an intermediate scale. Stocks can be assessed flexibly for varying depth from the forest floor down to 100 cm. Uncertainty analysis informs about locations, where the model results have to be handled with care.

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Concept and Methodology of the National Forest Soil Inventory

Cited by 11 publications

References 32 publications

Application of Low-Cost MEMS Spectrometers for Forest Topsoil Properties Prediction

Application of Low-Cost MEMS Spectrometers for Forest Topsoil Properties Prediction

Linkages between Phosphorus and Plant Diversity in Central European Forest Ecosystems—Complementarity or Competition?

Spatial 3D mapping of forest soil carbon stocks in Hesse, Germany

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