Journal Paper Digests 2019 #9
- Effect of Macroporosity on Pedotransfer Function Estimates at the Field Scale
- Combining Visible-Near-Infrared and Pedotransfer Functions for Parameterization of Tile Drain Flow Simulations
- Meteoric Beryllium-10 as a Tracer of Erosion Due to Postsettlement Land Use in West-Central Minnesota, USA
- Normalized difference vegetation change index: A technique for detecting vegetation changes using Landsat imagery
- Evaluating the utilization of the red edge and radar bands from sentinel sensors for wetland classification
- Extreme Pedology: Elements of Theory and Methodological Approaches
- Climate change does not alter land-use effects on soil fauna communities
- Global environmental changes impact soil hydraulic functions through biophysical feedbacks
- Spatial early warning signals for impending regime shifts: A practical framework for application in real-world landscapes
Effect of Macroporosity on Pedotransfer Function Estimates at the Field Scale
Authors: Zhang, X; Zhu, JF; Wendroth, O; Matocha, C; Edwards, D
Source: VADOSE ZONE JOURNAL, 18 (1):80151-80151; MAY 9 2019
Abstract: Saturated hydraulic conductivity (K-s) is one of the crucial hydraulic properties for assessing water and solute transport in soils. However, direct measurement of K-s is time consuming and arduous. Alternatively, pedotransfer functions (PTFs) have been developed to estimate K-s indirectly through more easily measurable soil properties that are part of regional, national, or international databases. These PTFs are usually based on datasets collected from large regions. However, their validity for a specific site remains unclear. The objectives of this study were to evaluate the performance of established PTFs in estimating K-s in a specific field and improve PTFs to arrive at a locally adapted estimation result for K-s. Forty-one soil samples were collected from 10 locations at five depths at a farmland in western Kentucky for hydraulic conductivity and physical property measurements. The performance of seven PTFs in estimating K-s was evaluated using the root mean square err or (RMSE), Nash-Sutcliffe efficiency (NSE), and the coefficient of determination (R-2). At this scale, all the selected PTFs exhibited unsatisfactory prediction of K-s (high RMSE, low NSE and R-2). In the field studied, approximately 60% of variance in K-s could be explained by soil texture and macropore components based on factor analysis. Clay content and macroporosity were identified as the most representative variables for each component. The performance of a PTF in estimating K-s for the field site investigated was significantly improved by including macroporosity (pores with diameter >75 mu m) as a predictor. The results confirmed that soil structure was crucial in characterizing soil hydraulic conductivity.
Combining Visible-Near-Infrared and Pedotransfer Functions for Parameterization of Tile Drain Flow Simulations
Authors: Varvaris, I; Pittaki-Chrysodonta, Z; Moldrup, P; de Jonge, LW; Iversen, BV
Source: VADOSE ZONE JOURNAL, 18 (1):80171-80171; MAY 3 2019
Abstract: Estimation of soil hydraulic parameters is essential when generating a hydrogeological model for simulating water flow dynamics in an agricultural field. However, estimation of the input parameters through direct measurements is time consuming and costly, and the spatial variability presents an uncertainty. Therefore, we proposed a rapid and inexpensive concept (integration of visible-near-infrared spectroscopy [vis-NIR] and a pedotransfer function [PTF]) to estimate hydraulic properties considering catchment scale. An existing vis-NIR-predicted Campbell retention function was used for estimating the Campbell b parameter and the water content at -1000 cm H2O soil-water matric potential (log vertical bar-1000 vertical bar = pF 3). A PTF was developed for predicting the saturated hydraulic conductivities using the vis-NIR-predicted Campbell b and the effective porosity, defined as the difference in volumetric water contents at pF 0.3 and 3. The concept was evaluated by developi ng a hydrogeological model in HYDRUS-2D software for simulating the tile drainage discharge from a clayey agricultural subcatchment in Denmark, using as input hydraulic parameters the output from the suggested approach. The suggested approach simulated the main attributes of the flow hydrograph with a reasonable degree of accuracy (R-2 and RMSE values of 0.86 and 1.25 L s(-1), respectively). A sensitivity analysis was performed to determine the response of the model to changes in values of predicted parameters when predicting the drainage discharge, and it showed that small variations (<10%) would not affect the predictive ability of the model.
Meteoric Beryllium-10 as a Tracer of Erosion Due to Postsettlement Land Use in West-Central Minnesota, USA
Authors: Jelinski, NA; Campforts, B; Willenbring, JK; Schumacher, TE; Li, S; Lobb, DA; Papiernik, SK; Yoo, K
Source: JOURNAL OF GEOPHYSICAL RESEARCH-EARTH SURFACE, 124 (4):874-901; APR 2019
Abstract: Meteoric beryllium-10 (Be-10(m), t(1/2)=1.4Myr) is a cosmogenic radionuclide that remains largely underutilized for deriving hillslope-scale estimates of erosion on uplands under conditions of land use change. We applied two different models for estimating erosion rates from observed Be-10(m) concentrations (a one-dimensional model predicting vertical profiles of Be-10(m) within hillslope soils [loss only, diffusion only, LODO] and a two-dimensional model predicting the concurrent evolution of hillslope topography and Be-10(m) distributions via bioturbation, chemical mobility, and surface erosion [Be2D]). Both models were used to derive pre-European and post-European settlement erosion rates (E-nat and E-post, respectively) across paired cultivated and uncultivated hillslopes in west-central Minnesota, USA. E-post estimates from Be-10(m) were compared to E-post estimates derived from Cs-137 inventories and the process-based Water and Tillage Erosion Model (WaTEM). The results from these models suggest that erosion rates from upper positions on the cultivated hillslope have increased from an average of 0.047mm/year under natural conditions to E-post values of 3.09mm/year. The Be2D and LODO models, on average, produced E-post estimates that were similar in magnitude to WaTEM and Cs-137 conversion models. This numerical convergence does not imply absolute Be-10(m) model accuracy, particularly when considering the uncertainties inherent in each approach, but it does suggest that the orders of magnitude increase in estimated erosion rates from E-nat to E-post is robust. Additionally, the pattern of E-post estimates produced using Be-10(m) conversion models is supported by the distribution of soil inorganic carbon at the study site. Our results demonstrate that Be-10(m) can provide reasonable estimates of both predisturbance and postdisturbance erosion rates in landscapes that have undergone extensive human modification.Plain Language Summary Agricult ural practices have substantially changed soil erosion rates! in the Midwestern United States. Although much work has been devoted to understanding the changes in soil erosion rates with land cover change, the ability to quantify those changes at discrete locations on the landscape over long periods of time has been limited. We use a set of tracers and models to estimate presettlement and postsettlement erosion rates on a hillslope in west-central Minnesota, USA, and show that soil erosion has increased by approximately 1 to 2 orders of magnitude over a period of approximately 110years. This has implications for how we view our current agricultural landscapes and how we think about soil sustainability in the future.
Normalized difference vegetation change index: A technique for detecting vegetation changes using Landsat imagery
Authors: Rokni, K; Musa, TA
Source: CATENA, 178 59-63; JUL 2019
Abstract: Vegetation indices have been developed to characterize and extract the Earth’s vegetation cover from space using satellite images. For detection of vegetation changes, temporal images are usually independently analyzed or vegetation index differencing is implemented. In this study, a vegetation change index, named normalized difference vegetation change index (NDVCI), was developed to directly detect vegetation changes between two different time images with improved accuracy. The effectiveness of the proposed method to detect vegetation changes was evaluated in comparison with that of enhanced vegetation index (EVI) differencing and normalized difference vegetation index (NDVI) differencing methods at seven test sites under different environmental conditions in Iran, Malaysia, and Italy. Landsat imagery as one of the most widely used sources of data in remote sensing was used for this purpose. Overall accuracy, kappa coefficient, and omission and commission errors were calcul ated to assess the accuracy of the resulting change maps. The results demonstrated superiority and higher performance of NDVCI compared to EVI and NDVI differencing for detection of vegetation changes. In five out of the seven test sites, the classification accuracy of NDVCI was higher compared to that of the other methods. In contrast, the results revealed lower accuracy of EVI differencing for vegetation change detection at all the test sites, while NDVI differencing was superior at two of the test sites. In conclusion, the study demonstrated great performance of NDVCI for monitoring vegetation changes at different environmental conditions. Accordingly, this technique may improve the vegetation change detection in future studies.
Evaluating the utilization of the red edge and radar bands from sentinel sensors for wetland classification
Authors: Kaplan, G; Avdan, U
Source: CATENA, 178 109-119; JUL 2019
Abstract: As one of the most important ecosystems, wetlands are threatened from both natural and anthropogenic activities. Mapping wetland is one of the curtail needs in order to prevent further loss. Since the beginning of the Remote Sensing revolution, different approaches using satellite images have been used for mapping and monitoring wetlands.In this paper we investigate the potential of the recently launched Sentinel satellites, both separate and in combination, for accurately mapping of different wetland classes using Support Vector Machines (SVMs) learning classifier. For investigating the influence of the Sentinel-2 red-edge bands, and the radar bands from Sentinel-1, three different datasets have been analyzed.The results showed that for more accurate mapping of different wetland classes, different datasets should be used. Thus, the red-edge bands have significant influence over the intensive vegetated wetland classes such as swamps, and the radar bands have significant influ ence over partially decayed vegetated wetland areas such as bogs. For future studies, in addition to the analyzed datasets, we recommend adding and investigating several vegetation indices for mapping and monitoring wetland areas.
Extreme Pedology: Elements of Theory and Methodological Approaches
Authors: Goryachkin, SV; Mergelov, NS; Targulian, VO
Source: EURASIAN SOIL SCIENCE, 52 (1):1-13; JAN 2019
Abstract: Extreme environmental conditions that occur in Arctic, Antarctic, high mountains, extremely arid regions, as well as in toxic or nutrient-poor substrates, shallow waters, under intense anthropogenic impact, and in specific atmosphere or its absence in extraterrestrial systems, lead to the formation of soils and soloids (soil-like bodies) that cannot be adequately described, and their genesis and geography cannot be satisfactorily explained within the framework of the traditional Dokuchaev’s pedology. A new scientific direction is proposedextreme pedology (genesis and geography of soils in extreme environments), which requires its own theory, conceptual apparatus, and methodological basis. It is based on the assumption that soils and soloids can develop in extreme conditions under the deficit or surplus of resources. In the first case, soloids are just few millimeters thick; in the second case, they have the profiles of multimeter scale. Various classes of soils and soloids ex tremeness are specified: factorial, regime-functional, and chorological (extra-areal). The behavior of extreme objects in time and the nature of their pedogenic records can have both specific and common features with normal soils. Morphological and analytical study of soils and soloids of extreme environments requires state-of-the-art methodological approaches and scientific equipment.
Climate change does not alter land-use effects on soil fauna communities
Authors: Yin, R; Eisenhauer, N; Schmidt, A; Gruss, I; Purahong, W; Siebert, J; Schadlera, M
Source: APPLIED SOIL ECOLOGY, 140 1-10; AUG 2019
Abstract: Soil organisms are important drivers of the functioning of terrestrial ecosystems and co-determine how these ecosystems respond to human-induced changes in climate and land use. In the present study, we assessed the interacting effects of these two global change drivers on soil faunal communities. We carried out an experimental field study within the framework of the Global Change Experimental Facility (GCEF) manipulating (1) two climatic conditions (ambient vs. future) and (2) five land-use regimes (with two croplands: conventional farming and organic farming; and three grasslands: intensively-used meadow, extensively-used meadow and extensivelyused pasture). The future climate treatment is characterized by a slight increase of soil temperature (similar to 0.5 degrees C), whereas precipitation was strongly decreased during the summer (by similar to 20%) but moderately increased during spring and autumn (by similar to 10%). Soil fauna was sampled in two consecutive years in s pring and autumn. Overall, future climate tented to have negative effects on soil fauna communities. For specific taxa, the detrimental effects of climate change were only evident for Isotomidae (Collembola) and Chilopoda. In general, soil faunal composition differed strongly between grasslands and croplands, with a higher number of macrofauna taxa and generally higher abundances of meso- and macrofauna in grasslands. However, land-use intensity within these land-use types had no further effect. Likewise, there were negligible interactive effects of climate and land use, and short-term effects of projected climate change on the community compositions of soil fauna were found to be more subtle than land-use effects. Land-use effects on soil fauna are therefore equally strong under ambient and future climatic conditions.
Global environmental changes impact soil hydraulic functions through biophysical feedbacks
Authors: Robinson, DA; Hopmans, JW; Filipovic, V; van der Ploeg, M; Lebron, I; Jones, SB; Reinsch, S; Jarvis, N; Tuller, M
Source: GLOBAL CHANGE BIOLOGY, 25 (6):1895-1904; JUN 2019
Abstract: Although only representing 0.05% of global freshwater, or 0.001% of all global water, soil water supports all terrestrial biological life. Soil moisture behaviour in most models is constrained by hydraulic parameters that do not change. Here we argue that biological feedbacks from plants, macro-fauna and the microbiome influence soil structure, and thus the soil hydraulic parameters and the soil water content signals we observe. Incorporating biological feedbacks into soil hydrological models is therefore important for understanding environmental change and its impacts on ecosystems. We anticipate that environmental change will accelerate and modify soil hydraulic function. Increasingly, we understand the vital role that soil moisture exerts on the carbon cycle and other environmental threats such as heatwaves, droughts and floods, wildfires, regional precipitation patterns, disease regulation and infrastructure stability, in addition to agricultural production. Biological fe edbacks may result in changes to soil hydraulic function that could be irreversible, resulting in alternative stable states (ASS) of soil moisture. To explore this, we need models that consider all the major feedbacks between soil properties and soil-plant-faunal-microbial-atmospheric processes, which is something we currently do not have. Therefore, a new direction is required to incorporate a dynamic description of soil structure and hydraulic property evolution into soil-plant-atmosphere, or land surface, models that consider feedbacks from land use and climate drivers of change, so as to better model ecosystem dynamics.
Spatial early warning signals for impending regime shifts: A practical framework for application in real-world landscapes
Authors: Nijp, JJ; Temme, AJAM; van Voorn, GAK; Kooistra, L; Hengeveld, GM; Soons, MB; Teuling, AJ; Wallinga, J
Source: GLOBAL CHANGE BIOLOGY, 25 (6):1905-1921; JUN 2019
Abstract: Prediction of ecosystem response to global environmental change is a pressing scientific challenge of major societal relevance. Many ecosystems display nonlinear responses to environmental change, and may even undergo practically irreversible ‘regime shifts’ that initiate ecosystem collapse. Recently, early warning signals based on spatiotemporal metrics have been proposed for the identification of impending regime shifts. The rapidly increasing availability of remotely sensed data provides excellent opportunities to apply such model-based spatial early warning signals in the real world, to assess ecosystem resilience and identify impending regime shifts induced by global change. Such information would allow land-managers and policy makers to interfere and avoid catastrophic shifts, but also to induce regime shifts that move ecosystems to a desired state. Here, we show that the application of spatial early warning signals in real-world landscapes presents unique and unexpecte d challenges, and may result in misleading conclusions when employed without careful consideration of the spatial data and processes at hand. We identify key practical and theoretical issues and provide guidelines for applying spatial early warning signals in heterogeneous, real-world landscapes based on literature review and examples from real-world data. Major identified issues include (1) spatial heterogeneity in real-world landscapes may enhance reversibility of regime shifts and boost landscape-level resilience to environmental change (2) ecosystem states are often difficult to define, while these definitions have great impact on spatial early warning signals and (3) spatial environmental variability and socio-economic factors may affect spatial patterns, spatial early warning signals and associated regime shift predictions. We propose a novel framework, shifting from an ecosystem perspective towards a landscape approach. The framework can be used to identify conditions under which resilience assessment with spatial remotely sen! sed data may be successful, to support well-informed application of spatial early warning signals, and to improve predictions of ecosystem responses to global environmental change.