A soil nutrient regime index for forest practitioner decisions in Hesse, Germany: spatial explicit modelling of soil chemistry and integration by fuzzy-logic

2020 ◽  
Author(s):  
Felix Heitkamp ◽  
Bernd Ahrends ◽  
Jan Evers ◽  
Henning Meesenburg
Keyword(s):  
Fuzzy Logic ◽  
Soil Nutrient ◽  
Parent Material ◽  
Additive Models ◽  
Ground Vegetation ◽  
Organic Layer ◽  
Forest Site ◽  
Nutrient Regime ◽  
Soil Map ◽  
Informed Decisions

<p>Forests face considerable pressure from climate change, while demand of provided ecosystem services is high. Managing and planting forests need well informed decisions by practitioners, to fulfill the goal of sustainability. In Germany, informed decisions are derived from forest site evaluation maps, integrating biogeoecolocigal conditions (climate, soil water, nutrients). Here, we focus on mapping of nutrients in the federal state Hesse, Germany. For Hesse, a forest site map exists, which indicates a soil nutrient regime (SNR) index (classes very poor, poor, medium, rich, very rich). Site mapping was done in the field by experts, considering ground vegetation and soil morphology. Guidelines exist for choosing management options (i.e. suitable species composition, harvest restrictions, etc.), but if spatial information is not accurate, management decisions will be misguided.</p><p>Three major challenges regarding the currently available site information exist: (1) the spatial proportion of “medium” sites is exceptionally high (65% of mapped forest area) and while there is differentiation between parent materials, topography is neglected. (2) Whereas 80% of Hesse’s forests were mapped, there is need to fill the gaps. (3) The existing SNR index does not take analytical measurements of soil nutrients into account. Objectives were (1) to refine and expand the existing map of SNR by (2) including soil chemical properties from the second National Forest Soil Inventory (NFSI), (3) which have to be regionalised beforehand.</p><p>Stocks of Ca, Mg and K, base saturation, effective cation exchange capacity (90cm depth and organic layer), and C/N ratio (organic layer or 0-5 cm) of 380 profiles from the NFSI were chosen to characterise the SNR. Regionalisation was performed with generalised additive models (GAM) by using environmental relationships of the target variables with variables of climate, vegetation, parent material and soil properties (soil map 1:50,000). Ten-fold cross validation revealed R² values from 0.54 to 0.79, with low relative root mean square deviation (5 to 17%) and slopes not significantly different from 1. From the six successfully modelled target variables, we inferred a single SNR for each soil map polygon. This was challenging, because variables provided contrasting information regarding the SNR. We addressed this by using the Soil Inference Engine (SIE), which bases on fuzzy logic. Each variable received an optimality value for each SNR class. Using an expert-driven weighting system a SNR membership was inferred, whereas highest membership defined the SNR class. The result was highly sensitive towards parent material and topography. For instance, acidic parent material had lower SNR classes compared to base rich parent material. Within a given parent material, ridges where judged less nutrient rich compared to planes and topographic positions, where material is accumulated.</p><p>The results provide a much more differentiated and complete map for SNR, which mirror actual expectations of nutrient distribution across Hesse’s landscape units. The approach is transparent and inter-subjectively reproducible. The new map will be used to guide reforestation activities in Hesse after the severe forest disturbances by recent climatic extremes (e.g. drought, storms) and the approach can be transferred to other regions.</p>

scholarly journals Prediction of soil nutrient regime based on a model of DEM-generated clay content for the province of Nova Scotia, Canada

2013 ◽  
Vol 93 (2) ◽  
pp. 193-203 ◽  
Author(s):  
Zhengyong Zhao ◽  
M. Irfan Ashraf ◽  
Kevin S. Keys ◽  
Fan-Rui Meng
Keyword(s):  
Nova Scotia ◽  
High Resolution ◽  
Soil Nutrient ◽  
Clay Content ◽  
Parent Material ◽  
Forest Growth ◽  
Soil Maps ◽  
Large Area ◽  
Nutrient Regime ◽  
Coarse Resolution

Zhao, Z., Ashraf, M. I., Keys, K. S. and Meng, F-R. 2013. Prediction of soil nutrient regime based on a model of DEM-generated clay content for the province of Nova Scotia, Canada. Can. J. Soil Sci. 93: 193–203. Soil nutrient regime (SNR) maps are widely required by ecological studies as well as forest growth and yield assessment. Traditionally, SNR is assessed in the field using vegetation indicators, topography and soil properties. However, field assessments are expensive, time consuming and not suitable for producing high-resolution SNR maps over a large area. The objective of this research was to develop a new model for producing high-resolution SNR maps over a large area (in this case, the province of Nova Scotia). The model used 10-m resolution clay content maps generated from digital elevation model data to capture local SNR variability (associated with topography) along with coarse-resolution soil maps to capture regional SNR variability (associated with differences in landform/parent material types). Field data from 1385 forest plots were used to calibrate the model and another 125 independent plots were used for model validation. Results showed field-identified SNRs were positively correlated with predicted clay content, with some variability associated with different landform/parent material types. Accuracy assessment showed that 63.7% of model-predicted SNRs were the same as field assessment, with 96.5% within ±1 class compared with field-identified SNRs. The predicted high-resolution SNR map was also able to capture the influence of topography on SNR which was not possible when predicting SNR from coarse-resolution soil maps alone.

scholarly journals Assessing Leaf Biomass of Agave sisalana Using Sentinel-2 Vegetation Indices

2021 ◽  
Vol 13 (2) ◽  
pp. 233
Author(s):  
Ilja Vuorinne ◽  
Janne Heiskanen ◽  
Petri K. E. Pellikka
Keyword(s):  
Near Infrared ◽  
Vegetation Indices ◽  
Fibre Production ◽  
Additive Models ◽  
Leaf Biomass ◽  
Ground Vegetation ◽  
Perennial Crop ◽  
Red Edge ◽  
Agave Sisalana ◽  
Sentinel 2

Biomass is a principal variable in crop monitoring and management and in assessing carbon cycling. Remote sensing combined with field measurements can be used to estimate biomass over large areas. This study assessed leaf biomass of Agave sisalana (sisal), a perennial crop whose leaves are grown for fibre production in tropical and subtropical regions. Furthermore, the residue from fibre production can be used to produce bioenergy through anaerobic digestion. First, biomass was estimated for 58 field plots using an allometric approach. Then, Sentinel-2 multispectral satellite imagery was used to model biomass in an 8851-ha plantation in semi-arid south-eastern Kenya. Generalised Additive Models were employed to explore how well biomass was explained by various spectral vegetation indices (VIs). The highest performance (explained deviance = 76%, RMSE = 5.15 Mg ha−1) was achieved with ratio and normalised difference VIs based on the green (R560), red-edge (R740 and R783), and near-infrared (R865) spectral bands. Heterogeneity of ground vegetation and resulting background effects seemed to limit model performance. The best performing VI (R740/R783) was used to predict plantation biomass that ranged from 0 to 46.7 Mg ha−1 (mean biomass 10.6 Mg ha−1). The modelling showed that multispectral data are suitable for assessing sisal leaf biomass at the plantation level and in individual blocks. Although these results demonstrate the value of Sentinel-2 red-edge bands at 20-m resolution, the difference from the best model based on green and near-infrared bands at 10-m resolution was rather small.

The influence of forest site on rate and extent of soil compaction and profile disturbance of skid trails during ground-based harvesting

2000 ◽  
Vol 30 (8) ◽  
pp. 1196-1205 ◽  
Author(s):  
J R Williamson ◽  
W A Neilsen
Keyword(s):  
Root Growth ◽  
Soil Compaction ◽  
Forest Type ◽  
Soil Bulk Density ◽  
Parent Material ◽  
Forest Site ◽  
Undisturbed Soil ◽  
Soil Parent Material ◽  
Wet Forests

Soil compaction has been considered a principal form of damage associated with logging, restricting root growth and reducing productivity. The rate and extent of soil compaction on skid trails was measured at six field locations covering a range of dry and wet forests. Data was collected for up to 21 passes of a laden logging machine. A similar extent of compaction, averaging 0.17 g·cm-3 increase in total soil bulk density (BD), was recorded for all field sites despite substantial site and soil differences. On average, 62% of the compaction in the top 10 cm of the soil occurred after only one pass of a laden logging machine. The environment under which soils had formed played a major role in determining the BD of the undisturbed soil. Compaction was strongly related to the original BD, forest type, and soil parent material. Soil strengths obtained in the field fell below levels found to restrict root growth. However, reduction in macropores, and the effect of that on aeration and drainage could reduce tree growth. On the wettest soils logged, machine forces displaced topsoils rather than causing compaction in situ. Recommended logging methods and implications for the development of sustainability indices are discussed.

Spatial Patterns and Drivers of Soil Chemical Properties in a Typical Hickory Plantation

2021 ◽  
Author(s):  
Mengjiao Sun ◽  
Enqing Hou ◽  
Jiasen Wu ◽  
Jianqin Huang ◽  
Xingzhao Huang
Keyword(s):  
Random Forest ◽  
Soil Nutrients ◽  
Spatial Patterns ◽  
Abiotic Factors ◽  
Soil Nutrient ◽  
Parent Material ◽  
Mean Annual Precipitation ◽  
Nutrient Concentrations ◽  
Available Phosphorus ◽  
Mean Annual Temperature

Abstract Background: Soil nutrients play critical roles in regulating and improving the sustainable development of economic forests. Consequently, an elucidation of the spatial patterns and drivers of soil nutrients in these forests is fundamental to their management. For this study, we collected 314 composite soils at a 0-30 cm depth from a typical hickory plantation in Lin 'an, Zhejiang Province, China. We determined the concentrations of macronutrients (i.e., soil organic carbon, hydrolyzed nitrogen, available phosphorus, and available potassium) and micronutrients (i.e., iron, manganese, zinc, and copper.) of the soils. We employed random forest analysis to quantify the relative importance of soil-forming factors to predict the soil nutrient concentrations, which could then be extrapolated to the entire hickory region. Results: Random forest models explained 61%–88% of the variations in soil nutrient concentrations. The mean annual temperature and mean annual precipitation were the most important predictor of soil macronutrient and micronutrient concentrations. Moreover, parent material was another key predictor of soil available phosphorus and micronutrient concentrations. Mapping results demonstrated the importance of climate in controlling the spatial distribution of soil nutrient concentrations at finer scales, as well as the effect of parent material, topography, stand structure, and management measures of hickory plantations. Conclusions: Our study highlights the biotic factors, abiotic factors, and management factors control over soil macronutrient and micronutrient concentrations, which have significant implications for the sustainability of soil nutrients in forest plantations.

scholarly journals Nutritional regime of gray forest soil аt different anthropogenic loads

2020 ◽  
pp. 16-26
Author(s):  
N. Borys ◽  
L. Krasjuk
Keyword(s):  
Forest Soil ◽  
Crop Rotation ◽  
Main Product ◽  
Gray Forest Soil ◽  
Organic Fertilizer ◽  
Soil Layer ◽  
Soil Nutrient ◽  
Mineral Fertilizers ◽  
Nutrient Regime ◽  
By Products

The aim of the research is to establish the peculiarities of the formation of the nutrient regime of gray forest soil with different systems of basic cultivation, fertilization and sealing of by-products of crops in short-rotation 4-field grain crop rotation – winter wheat–corn for grain–barley–soybean. Evaluate the quantitative inflow of biomass, participation in the formation of the nutrient regime of gray forest soil, especially the differentiation of 0–40 cm of soil layer depending on the distribution of nutrients in different tillage soil systems. The studies were carried out in a long-term stationary experiment of the department of soil cultivation and weed control of the NSC «Institute of Agriculture of the NAAS», founded in 1969. The fertilization system consisted of the application of mineral fertilizers N65Р58К68 kg acting things per 1 ha of crop rotation area. As an organic fertilizer, we used by-products of crop rotation, where during 2009–2013 received an average of 5,17–5,50 t/ha, and 2014–2017 – 6,65–7,76 t/ha of crop rotation. The existing yield of the main product significantly influenced the volume of the non-commodity part, with the growth of the main product, the growth of by-products also took place in direct proportion. Nitrogen removal averaged 105 kg/ha, and with biomass it returned on average 55,4 kg/ ha, nitrogen with a full mineralization cycle, in general, this corresponds to 45–47 % of the share of costs. In general, the return of phosphorus from by-products for the rotation of 5 received an average of 12,0–16,7 kg/ha and 4-field crop 26 rotation 19,5–22,0 kg/ha, which was 35–40 % of the total removal harvest. The soil received many times more potassium from the biomass of agricultural crops than part of the cost of the main product, due to the attraction of the maize leaf mass, from which an average of 177–253 kg/ha enters the soil, and for crop rotation – 61,4–95,4 kg/ha per hectare of sown area. Key words: gray forest soil, soil nutrient regime, recycling of nutrients, main and by-products of crops.

Impact of Soil Nutrient Contents and Spatial Variability in Different Sampling Schemes under the Conservation Tillage

2013 ◽  
Vol 718-720 ◽  
pp. 316-320
Author(s):  
Si Jia Li ◽  
Yan Nan Sun ◽  
Hong Bin Wang ◽  
Zhi Wen Chen
Keyword(s):  
Conservation Tillage ◽  
Cropping System ◽  
Soil Nutrient ◽  
Parent Material ◽  
Available P ◽  
Moderate Intensity ◽  
Structural Factors ◽  
Available N ◽  
Nutrient Contents ◽  
Sampling Schemes

According to the 40×40m mesh, taking the 180 soil samples in both strains and ridges of the demonstration fields under the stalk mulching conservation tillage for 5 consecutive years in Gaojia country, which the area covers 15 hm2 in Li Shu town, Jilin Province. The available N, available P, available K and other nutrition of soil in different sampling schemes have been tested. Based on the platform of GIS and the method of geostatistical analyst, the space distribution's characteristics of the three kinds of soil's nutrients have been researched, which demonstrate each variable corresponds normal distribution, the contents of available N and available K in different sampling schemes vary so much, but the content of available P has shown much more similarity than difference. Through the analysis of semivariogram, the soil nutrients in every different sampling schemes have revealed a moderate intensity autocorrelation and a relative strong spatial heterogeneity, which are affected by structural factors such as soil types, parent material, terrain, climate, hydrological conditions and so on, and they are also affected by random factors, for example, fertilization, cropping system, tillage operation and management. Analyzing the three nutrients in different sampling schemes, which are affected by random factors. Through applying the semivariogram and kriging to analyze the impacts factors of spatial variable in the soil, there are the differences between the two methods.

scholarly journals Experimental micropedology—A technique for investigating soil carbonate biogenesis along a desert-grassland-forest transect, New Mexico, USA .

2014 ◽  
Vol 4 ◽  
Author(s):  
Farhad Khormali ◽  
Y. Feng ◽  
Curtis Monger
Keyword(s):  
New Mexico ◽  
Growth Medium ◽  
Parent Material ◽  
Forest Site ◽  
Desert Grassland ◽  
X Ray ◽  
Carbonate Formation ◽  
Microscope Slides ◽  
Liquid Growth Medium

Manipulative experiments—characterized by the comparing treatments to controls—are widespread in scientific investigations. This study uses experimental micropedology to investigate whether soil microbes precipitate carbonate if a liquid growth-medium is applied to soil in situ. This was undertaken using apparatuses designed to (1) obtain micromorphological images of biogenic carbonate on microscope slides, (2) to quantify carbonate formation in fiberglass cloths, and (3) to measure associated carbon-isotope fractionations. The apparatuses were buried and harvested at monthly intervals from December 2010 to June 2011. The study was conducted along an ecological transect in New Mexico, USA, at three sites: a low-elevation desert (C3 shrubs), an intermediate-elevation steppe (C4 grasses), and a high-elevation forest (C3 conifers). In addition to comparing bioclimatic zones, the effect of parent material was also tested using paired limestone and igneous soils at each site. Microscope slides were analyzed with binocular, petrographic, and scanning electron microscopy equipped with an x-ray microanalyser (EDS), and the fiberglass traps were analyzed with x-ray diffraction and a mass spectrometer for carbon concentrations and isotope ratios. Naturally occurring calcified microbes were found at each site in the form of calcified hyphae, needle fiber, and calcified root hairs, with the exception of the forest site on igneous parent material. Liquid growth medium induced microbial calcification regardless of whether the vegetation was desert shrubs, grassland, or forest, and regardless of whether the parent material was igneous or limestone. Thus, the ability of soil microorganisms to biomineralize carbonate when supplied with liquid growth medium in situ is a phenomenon that crosses biomes and is not limited to microbes endemic to either limestone or igneous parent material.

scholarly journals DIGITAL SOIL MAPPING USING GEOMORPHOMETRIC ANALYSIS AND CASE-BASED FUZZY LOGIC APPROACH

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 863-866
Author(s):  
A. Rahmani ◽  
F. Sarmadian ◽  
S. R. Mousavi ◽  
S. E. Khamoshi
Keyword(s):  
Fuzzy Logic ◽  
Soil Mapping ◽  
Digital Soil Mapping ◽  
Kappa Index ◽  
Valley Bottom ◽  
Error Matrix ◽  
Soil Map ◽  
Expert’S Opinion ◽  
Fuzzy Logic Approach ◽  
Landscape Units

Abstract. In low relief region such as plains, applied digital soil mapping has a controvertible issue, therefore, this study was aimed to digital mapping of soil classes at family levels by appropriate Geomorphometric variables along with fuzzy logic with area of 16,600 hectares in Qazvin Plain. Based on the geomorphologic map, the plain and pen plain are dominant landscape units. In this regards, 61 soil profiles were dogged. According to the expert’s opinion, covariates including diffuse insolation, standardized height, catchment area, valley depth and multiresolution valley bottom flatness (MrVBF) had the most important in order to generating soil map. Also, 19 fuzzy soil class maps were generated through using sample-based in ArcSIE software. Validation were carried out using achieved overall accuracy (OA) and Kappa index through error matrix. Subsequently, both ignorance and exaggerating uncertainty of hardened soil map were also done. The results showed that 19 soil families class were found. Accordingly, OA and the Kappa index were 54% and 46% respectively. The uncertainty of ignorance and exaggeration were obtained from 0 to 0.64 and 0 to 1, respectively. Moreover, the results indicated that exaggerated uncertainty was the highest in the northern and the lowest in the southern regions. Generally, applied geomorphometric parameters had the specific importance in the low relief areas for mapping of soils that have not been assessed properly so far.

Development of Podzols in relation to Jenny's soil formation factors

2020 ◽  
Author(s):  
Tiina Törmänen ◽  
Antti-Jussi Lindroos ◽  
Hannu Ilvesniemi ◽  
Mike Starr
Keyword(s):  
Soil Formation ◽  
Parent Material ◽  
Environmental Research ◽  
National Database ◽  
Soil Profiles ◽  
Forest Site ◽  
Least Squares Regression ◽  
Reference Base ◽  
Soil Variables ◽  
Soil Formation Factors

<p>Podzols are considered to be the most common upland forest soil type in Finland. However, there have only been a few studies that have examined the degree of podsolization in Finnish soils. More detailed information about this dominating process in our soils can be utilized in other kinds of environmental research such as the impacts of climate change, carbon and nutrient cycling, and the degradation of soil and water systems.</p><p>We studied how the intensity of podsolization is related to Jenny’s classic five soil formation factors: climate, parent material, topography, biotic and time. The degree of podzolization of 86 soil profiles distributed over the whole of Finland was described using four podzolization indices: E-horizon thickness, B-horizon rubification, profile Al+Fe oxide eluviation-illuviation, and their sum (Podzolization Development Index, PDI). The soil profiles, selected out of over 600 soil profiles in a national database, met the World Reference Base for Soil Resources (WRB) criteria for them to be classified as Podzols. The relationship between the podzolization indices and a number of site and soil variables (continuous and categorical) describing Jenny’s soil formation factors were then evaluated. While podzolization intensity was found to be related to soil profile age, elevation, longitude, forest site type, aspect, Sphagnum moss cover and B-horizon texture, the individual relationships were weak. However, looking at the combined effect of all the variables using Partial Least Squares regression analysis, which is unaffected by multicollinearity among the predictor variables, nearly 70% of the measured PDI index could be explained.</p>

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