Predictive Quality of Pedotransfer Functions for Estimating Bulk Density of Forest Soils

Vos, Bruno De; Meirvenne, Marc Van; Quataert, Paul; Deckers, Jozef; Muys, Bart

doi:10.2136/sssaj2005.0500

Cited by 282 publications

(216 citation statements)

References 17 publications

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“…Some soil-derived properties are strongly dependent of soil texture, for example, soil porosity (Bruand and Cousin 1995), soil bulk density (De Vos et al 2005), and soil hydraulic characteristics (Saxton et al 1986;Wösten et al 2001;Toth et al 2015). Depending on the fixed depth layer, this information is available for 60-80 % of the plots.…”

Section: Texture Classmentioning

confidence: 99%

The Level II aggregated forest soil condition database links soil physicochemical and hydraulic properties with long-term observations of forest condition in Europe

Fleck

Cools

Vos

et al. 2016

Annals of Forest Science

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Key message Aggregated, consolidated, and derived soil physicochemical data of 286 ICP Forests Level II plots were completed with soil hydraulic properties for integrated use with forest monitoring data. Database access should be requested at http://icp-forests.net . Metadata associated available at https://metadata-afs.nancy.inra.fr/geonetwork/apps/georchestra/?uuid=153e599e-6624-4e2b-b862-8124386ea9cd&hl=eng Context The ICP Forests database is one of the most comprehensive forest ecosystem datasets in Europe and contains the accumulated results of more than two decades of harmonised forest monitoring all over Europe. Aims The aim of this paper is to share knowledge on the ICP Forests Level II soil data for broader use among forest scientists. Methods After standard analysis, quality checks, aggregation, and calculation of derived variables (e.g. nutrient stocks, base saturation, C:N ratio, and water retention parameters), data have been gathered into a static database (AFSCDB.LII.2.2), which will be updated to new versions as soon as new measurements become available. Results The database provides a basis for the combined evaluation of up to 130 unique soil variables of 286 plots with dynamic data on tree growth, ground vegetation, foliar chemistry, crown condition, tree phenology, leaf area index, ozone injury, litterfall, soil solution chemistry, deposition, ambient air quality, and meteorological data assessed on the same plots. Conclusion The unprecedented comprehensiveness and level of detail in this newly aggregated database may overcome existing restrictions so far impeding the realisation of large-scale forest ecosystem studies in Europe.

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Section: Texture Classmentioning

confidence: 99%

The Level II aggregated forest soil condition database links soil physicochemical and hydraulic properties with long-term observations of forest condition in Europe

Fleck

Cools

Vos

et al. 2016

Annals of Forest Science

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“…The soil physicochemical properties were analyzed at both elevations following standard procedures [20][21][22]. The population located at low elevation (36°43′18″ N, 4°57′53″ W, 1226 m a.s.l.)…”

Section: Study Site and Field Samplingmentioning

confidence: 99%

Regulation of Water Use in the Southernmost European Fir (Abies pinsapo Boiss.): Drought Avoidance Matters

Sánchez‐Salguero

Ortíz

Covelo

et al. 2015

Forests

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Abstract:The current scenario of global warming has resulted in considerable uncertainty regarding the capacity of forest trees to adapt to increasing drought. Detailed ecophysiological knowledge would provide a basis to forecast expected species dynamics in response to climate change. Here, we compare the water balance (stomatal conductance, xylem water potential, needle osmotic adjustment) of Abies pinsapo, a relict drought-sensitive Mediterranean fir, along an altitudinal gradient. We related these variables to soil water and nutrient availability, air temperature, atmospheric water potential, and vapour pressure deficit during two consecutive years. Our results indicate that A. pinsapo closed stomata rapidly over a very narrow range of soil water availability and atmospheric dryness. This isohydric response during water stress suggests that this relict conifer relied on the plant hormone abscisic acid to maintain closed stomata during sustained drought, instead of needle desiccation to passively drive stomatal closure, needle osmotic adjustment OPEN ACCESS Forests2015, 62242 or a plastic response of the xylem to different levels of water availability. Both the soil and foliar nutrient contents suggest that the studied populations are not limited by nutrient deficiencies, and drought was stronger in the warmer low-elevation areas.

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“…Many studies differentiate between topsoil and subsoil by depth (De Vos et al, 2005;Katterer et al, 2006). However, the lower depth of the topsoil layer can vary from 15 cm (Bellamy et al, 2005) to 30 cm (Martin et al, 2009).…”

Section: Data Preprocessingmentioning

confidence: 99%

Modelling soil bulk density at the landscape scale and its contributions to C stock uncertainty

et al. 2013

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Soil bulk density (D_b) is a major contributor to uncertainties in landscape-scale carbon and nutrient stock estimation. However, it is time consuming to measure and is, therefore, frequently predicted using surrogate variables, such as soil texture. Using this approach is of limited value for estimating landscape-scale inventories, as its accuracy beyond the sampling point at which texture is measured becomes highly uncertain. In this paper, we explore the ability of soil landscape models to predict soil D_b using a suite of landscape attributes and derivatives for both topsoil and subsoil. The models were constructed using random forests and artificial neural networks.

Using these statistical methods, we have produced a spatially distributed prediction of D_b on a 100 m × 100 m grid, which was shown to significantly improve topsoil carbon stock estimation. In comparison to using mean values from point measurements, stratified by soil class, we found that the gridded method predicted D_b more accurately, especially for higher and lower values within the range. Within our study area of the Midlands, UK, we found that the gridded prediction of D_b produced a stock inventory of over 1 million tonnes of carbon greater than the stratified mean method. Furthermore, the 95% confidence interval associated with total C stock prediction was almost halved by using the gridded method. The gridded approach was particularly useful in improving organic carbon (OC) stock estimation for fine-scale landscape units at which many landscape–atmosphere interaction models operate

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Predictive Quality of Pedotransfer Functions for Estimating Bulk Density of Forest Soils

Cited by 282 publications

References 17 publications

The Level II aggregated forest soil condition database links soil physicochemical and hydraulic properties with long-term observations of forest condition in Europe

The Level II aggregated forest soil condition database links soil physicochemical and hydraulic properties with long-term observations of forest condition in Europe

Regulation of Water Use in the Southernmost European Fir (Abies pinsapo Boiss.): Drought Avoidance Matters

Modelling soil bulk density at the landscape scale and its contributions to C stock uncertainty

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