Journal Paper Digests 2020 #1 (part 3)
- Soil health assessment: Past accomplishments, current activities, and future opportunities
- Development of soil spectral allocation models considering the effect of soil moisture
- Evolutionary Pathways in Soil-Geomorphic Systems
- Australian hot and dry extremes induced by weakenings of the stratospheric polar vortex
- Exogenous and endogenous controls on the development of soil structure
Soil health assessment: Past accomplishments, current activities, and future opportunities
By: Karlen, Douglas; Veum, Kristen S.; Sudduth, Kenneth A.; et al.
SOIL & TILLAGE RESEARCH Volume: 195 Pages: 4365-4365 Published: DEC 2019
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Global interest in soil health has increased exponentially during the past decade, with many different government, non-government, and private sector groups striving to develop monitoring and assessment protocols. This brief review focuses on developments in the United States (U.S.) with some references to activities in other countries. It also documents how the soil health concept evolved and projects what is needed to scientifically advance monitoring and assessment with a particular focus on activities in the U.S. Recommendations emphasize improving the Soil Management Assessment Framework (SMAF) and/or Comprehensive Assessment of Soil Health (CASH) assessment tools, developing protocols for national soil health monitoring, identifying and calibrating better indicators of soil biological, chemical, and physical health, and developing sensors and other tools for more rapid and in-situ assessments. Collectively, these and other research and technology transfer activities will help achieve what we suggest should be a universal goal - striving for healthy soils, healthy landscapes, and vibrant economies.
Development of soil spectral allocation models considering the effect of soil moisture
By: Wang, Xiang; Dou, Xin; Zhang, Xinle; et al.
SOIL & TILLAGE RESEARCH Volume: 195 Pages: 4374-4374 Published: DEC 2019
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Soil spectral allocation or classification is usually conducted on air-dried soils. However, the field soils are not all air-dried, and the change of soil moisture will affect soil reflectance. We introduce a soil allocation model that considers the effect of soil moisture for the purpose of eliminating the effect of soil moisture. The topsoil spectral curves of four typical soils from the Songnen Plain in Northeast China were re-sampled to 10-nm intervals and converted to first-derivative spectral curves and continuum removal curves. The spectral feature parameters were extracted from continuum removal curves in the visible-near infrared (VNIR) range (350-2500 nm), and the range of 430-2400 nm was used to build soil allocation models for reducing the effect of noise. Samples with different soil moisture were mixed into air-dried soils and we calculated the coefficient of variation (CV) of different inputs to assess the effect of soil moisture and to find allocation indices that were not affected by soil moisture. We used allocation indices of Zhang et al. (2018) because of the high accuracy of their DT (Decision Tree) model to allocate mixed-soil samples. We also used allocation indices that were not affected by soil moisture to allocate mixed-soil samples with decision tree (DT), multinomial logistic regression (MLR) and multi-layer perception neural network (MLPNN), and compared the results of the two methods. The results show the following: 1) As SFPs were built with shorter bands, SFP was less sensitive to soil moisture than PCR and PCFD and thus SFP is more suitable to build soil allocation models that consider the effect of soil moisture as input than PCR and PCFD. 2) Differences in soil moisture had little effect on absorption valley shoulders, symmetry and absorption positions, moderate effect on absorption area and depth, and a major effect on the slope of different bands. 3) The effect of soil moisture on continuum removal curves of different soil classes was variable. There was little effect on Arenosols, a moderate effect on Chernozems and Cambisols, and a large effect on Phaeozems. 4) The accuracy of the DT model using allocation indices that were not affected by soil moisture was 91.892% with a Kappa coefficient of 0.888. Our results suggest that it is feasible to build soil spectral allocation models that are not affected by soil moisture, and this improves the universality of soil spectral allocation, especially to field soils, which can be of considerable help in soil classification.
Evolutionary Pathways in Soil-Geomorphic Systems
By: Phillips, Jonathan D.
SOIL SCIENCE Volume: 184 Issue: 1 Pages: 1-12 Published: FEB 2019
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Understanding evolution of soils and landforms (and other Earth surface systems) has itself evolved from concepts of single-path, single-outcome development to those that recognize multiple possible developmental trajectories and different maturely developed stales. Soil geomorphology and pedology should now move beyond showing that multiple trajectories are possible to investigating why some evolutionary pathways (EPs) are common and persistent, whereas others are rare and transient. A typology of EPs is developed and applied to soil formation in the North Carolina coastal plain. Some EN are impossible because of violation of generally applicable laws or absence of necessary conditions; others are currently impossible, having occurred in the past but requiring conditions that no longer exist. Improbable paths are possible but rare, because necessary circumstances involve rare events or boundary conditions. Inhibited EPs are also possible but rare because of resistance factors or feedbacks that prevent or inhibit them. Transient paths may be common but are not long-lived or well preserved and are thus rarely observed. Recurring but nonrepeating EPs occur in different locations but are irreversible in any given location and cannot recur except in the case of system-resetting disturbance or new inputs. Recurring EPs are riot inhibited or self-limited, occur in different locations, and may be repeated because of ongoing or recurrent processes or conditions. Selected path types occur in multiple situations, but with increased probability due to feedbacks or responses that encourage or enhance recurrence and/or persistence. The case study shows examples of all possible EP types.
Australian hot and dry extremes induced by weakenings of the stratospheric polar vortex
By: Lim, Eun-Pa; Hendon, Harry H.; Boschat, Ghyslaine; et al.
NATURE GEOSCIENCE Volume: 12 Issue: 11 Pages: 896-+ Published: NOV 2019
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The occurrence of extreme hot and dry conditions in warm seasons can have large impacts on human health, energy and water supplies, agriculture and wildfires. Australian hot and dry extremes have been known to be associated with the occurrence of El Nino and other variations of tropospheric circulation. Here we identify an additional driver: variability of the stratospheric Antarctic polar vortex. On the basis of statistical analyses using observational data covering the past 40 yr, we show that weakenings and warmings of the stratospheric polar vortex, which episodically occur during austral spring, substantially increase the chances of hot and dry extremes and of associated fire-conducive weather across subtropical eastern Australia from austral spring to early summer. The promotion of these Australian climate extremes results from the downward coupling of the weakened polar vortex to tropospheric levels, where it is linked to the low-index polarity of the Southern Annular Mode, an equatorward shift of the mid-latitude westerly jet stream and subsidence and warming in the subtropics. Because of the long timescale of the polar vortex variations, the enhanced likelihood of early-summertime hot and dry extremes and wildfire risks across eastern Australia may be predictable a season in advance during years of vortex weakenings.
Boundary line models for soil nutrient concentrations and wheat yield in national-scale datasets
By: Lark, Richard M.; Gillingham, Vincent; Langton, David; et al.
EUROPEAN JOURNAL OF SOIL SCIENCE Pages: NIL_1-NIL_18 Published: NOV 15 2019
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In boundary line analysis a biological response (e.g., crop yield) is assumed to be a function of a variable (e.g., soil nutrient concentration), which limits the response in only some subset of observations because other limiting factors also apply. The response function is therefore expressed by an upper boundary of the plot of the response against the variable. This model has been used in various branches of soil science. In this paper we apply it to the analysis of some large datasets, originating from commercial farms in England and Wales, on the recorded yield of wheat and measured concentrations of soil nutrients in within-field soil management zones. We considered boundary line models for the effects of potassium (K), phosphorus (P) and magnesium (Mg) on yield, comparing the model with a simple bivariate normal distribution or a bivariate normal censored at a constant maximum yield. We were able to show, using likelihood-based methods, that the boundary line model was preferable in most cases. The boundary line model suggested that the standard RB209 soil nutrient index values (Agriculture and Horticulture Development Board, nutrient management guide (RB209), 2017) are robust and apply at the within-field scale. However, there was evidence that wheat yield could respond to additional Mg at concentrations above index 0, contrary to RB209 guidelines. Furthermore, there was evidence that the boundary line model for yield and P differs between soils at different pH and depth intervals, suggesting that shallow soils with larger pH require a larger target P index than others. Highlights Boundary line analysis is one way to examine how soil variables influence crop yield in large datasets. We showed that boundary line models could be applied to large datasets on soil nutrients and crop yield. The resulting models are consistent with current practice for P and K, but not for Mg. Models suggest that more refined recommendations for P requirement could be based on soil pH and depth.
Exogenous and endogenous controls on the development of soil structure
By: Mohammed, Aoesta K.; Hirmas, Daniel R.; Nemes, Attila; et al.
GEODERMA Volume: 357 Pages: 13945-13945 Published: JAN 1 2020
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The categorical and qualitative nature of currently available soil structural data along with the lack of a geographically broad dataset have impeded progress in understanding the development of soil structure. In this study, we assembled a soil, climate, and ecological dataset for the USA, and used it to analyze relationships between soil structure (ped type, shape, size, and grade) and exogenous and endogenous variables influencing the development of soil structure. We analyzed a subset of the National Cooperative Soil Survey (NCSS) Soil Characterization database after merging this information with climatological and ecological data. The merged and cleaned dataset contains > 4400 observations from approximately 1600 pedons. We found that climate, as an exogenous factor was the most important predictor of ped shape and size. Cold and/or dry climates promoted the development of larger anisotropic peds with rougher surfaces whereas warmer and more humid climates promoted the development of finer equidimensional peds with smoother surfaces. Based on these findings, we argue that climate promotes the development of soil structure along either fragmentation or aggregation pathways. The former pathway is characterized by largely mechanical processes in cold and dry environments, whereas aggregation is promoted by predominately biological and chemical mechanisms found in warmer and wet environments. This connection between climate and the development of soil structure represents a potentially important effect of climate on a morphological property strongly linked to soil hydrology that warrants further investigation with continental-scale soil data.