Cristine L. S. Morgan

Soil Security: Solving the Global Soil Crisis

Soil degradation is a critical and growing global problem. As the world population increases, pressure on soil also increases and the natural capital of soil faces continuing decline. International policy makers have recognized this and a range of initiatives to address it have emerged over recent years. However, a gap remains between what the science tells us about soil and its role in underpinning ecological and human sustainable development, and existing policy instruments for sustainable development. Functioning soil is necessary for ecosystem service delivery, climate change abatement, food and fiber production and fresh water storage. Yet key policy instruments and initiatives for sustainable development have under-recognized the role of soil in addressing major challenges including food and water security, biodiversity loss, climate change and energy sustainability. Soil science has not been sufficiently translated to policy for sustainable development. Two underlying reasons for this are explored and the new concept of soil security is proposed to bridge the science–policy divide. Soil security is explored as a conceptual framework that could be used as the basis for a soil policy framework with soil carbon as an exemplar indicator.

Unmanned Aerial Vehicles for High-Throughput Phenotyping and Agronomic Research

Advances in automation and data science have led agriculturists to seek real-time, high-quality, high-volume crop data to accelerate crop improvement through breeding and to optimize agronomic practices. Breeders have recently gained massive data-collection capability in genome sequencing of plants. Faster phenotypic trait data collection and analysis relative to genetic data leads to faster and better selections in crop improvement. Furthermore, faster and higher-resolution crop data collection leads to greater capability for scientists and growers to improve precision-agriculture practices on increasingly larger farms; e.g., site-specific application of water and nutrients. Unmanned aerial vehicles (UAVs) have recently gained traction as agricultural data collection systems. Using UAVs for agricultural remote sensing is an innovative technology that differs from traditional remote sensing in more ways than strictly higher-resolution images; it provides many new and unique possibilities, as well as new and unique challenges. Herein we report on processes and lessons learned from year 1—the summer 2015 and winter 2016 growing seasons–of a large multidisciplinary project evaluating UAV images across a range of breeding and agronomic research trials on a large research farm. Included are team and project planning, UAV and sensor selection and integration, and data collection and analysis workflow. The study involved many crops and both breeding plots and agronomic fields. The project’s goal was to develop methods for UAVs to collect high-quality, high-volume crop data with fast turnaround time to field scientists. The project included five teams: Administration, Flight Operations, Sensors, Data Management, and Field Research. Four case studies involving multiple crops in breeding and agronomic applications add practical descriptive detail. Lessons learned include critical information on sensors, air vehicles, and configuration parameters for both. As the first and most comprehensive project of its kind to date, these lessons are particularly salient to researchers embarking on agricultural research with UAVs.

Modeling Forest Aboveground Biomass and Volume Using Airborne LiDAR Metrics and Forest Inventory and Analysis Data in the Pacific Northwest

The United States Forest Service Forest Inventory and Analysis (FIA) Program provides a diverse selection of data used to assess the status of the nation’s forests using sample locations dispersed throughout the country. Airborne laser scanning (ALS) systems are capable of producing accurate measurements of individual tree dimensions and also possess the ability to characterize forest structure in three dimensions. This study investigates the potential of discrete return ALS data for modeling forest aboveground biomass (AGBM) and gross volume (gV) at FIA plot locations in the Malheur National Forest, eastern Oregon utilizing three analysis levels: (1) individual subplot (r = 7.32 m); (2) plot, comprising four clustered subplots; and (3) hectare plot (r = 56.42 m). A methodology for the creation of three point cloud-based airborne LiDAR metric sets is presented. Models for estimating AGBM and gV based on LiDAR-derived height metrics were built and validated utilizing FIA estimates of AGBM and gV derived using regional allometric equations. Simple linear regression models based on the plot-level analysis out performed subplot-level and hectare-level models, producing R2 values of 0.83 and 0.81 for AGBM and gV, utilizing mean height and the 90th height percentile as predictors, respectively. Similar results were found for multiple regression models, where plot-level analysis produced models with R2 values of 0.87 and 0.88 for AGBM and gV, utilizing multiple height percentile metrics as predictor variables. Results suggest that the current FIA plot design can be used with dense airborne LiDAR data to produce area-based estimates of AGBM and gV, and that the increased spatial scale of hectare plots may be inappropriate for modeling AGBM of gV unless exhaustive tree tallies are available. Overall, this study demonstrates that ALS data can be used to create models that describe the AGBM and gV of Pacific Northwest FIA plots and highlights the potential of estimates derived from ALS data to augment current FIA data collection procedures by providing a temporary intermediate estimation of AGBM and gV for plots with outdated field measurements.

Scale-Dependent Correspondence of Floristic and Edaphic Gradients across Salt Marsh Creeks

Biogeographers emphasize the presence of scale-dependence in vegetation–environment relationships. This research addresses the issue of scale-dependence, focusing on spatial correspondence of floristic and edaphic gradients across salt marsh creeks at Skallingen, Denmark. We employed a hierarchical approach, which compared vegetation and soil gradients at both fine and coarse scales. At the fine scale, we used ordination techniques to identify the gradient structure of vegetation and soil data acquired in 1-m2 plots along transects across creeks. For the coarse-scale comparison, we systematically aggregated the fine-scale information (i.e., gradient structure) into larger blocks, or topographic zones such as point bar, cutbank edge, and marsh interiors. We found poor correlations between vegetation and soil at the fine scale but an improved correspondence at the coarse scale. The poor correspondence was caused by differential spatial extents that the vegetation and soil factors exhibited responding to environmental variations. At the fine scale, modes of plant–plant interactions were the key determinant of species composition and varied significantly across tidal creeks. Soil properties responded less sensitively to topographic and hydrologic changes than vegetation did, however. As the scale of our analysis increased, the fine-scale floristic variation averaged out, and the overall compositional patterns were then governed by broader variations in environmental (edaphic) constraints. Our research accommodates the importance of both biological and environmental components by explicitly emphasizing their simultaneous significance, each perceived at different spatial scales. We conclude that the concept of scale-dependence might serve as an efficient conceptual framework in salt marsh biogeography.

Combined mapping of soil properties using a multi-scale tree-structured spatial model

Accurate maps of various key soil properties on fine spatial resolutions play an important role in precision modeling of agricultural systems. Recent development of alternatives to soil coring enables us to collect multiple sources of data, but data quality and spatial resolutions may differ greatly from one source to another. In this article, we use a multi-scale model for combining all data sources, despite varying resolutions and accuracies, to produce soil maps. We demonstrate that the method gives accurate results via computer simulations. Using the multi-scale method, we combine soil coring, penetrometer, and topographic data to map the depth-to-till on a 10-m resolution in an Arlington, Wisconsin field, and combine soil coring and soil electrical conductivity measurements to map field capacity on a 20-m resolution in a Waunakee, Wisconsin field. The proposed mapping technique has several advantages: (1) it is computationally fast and hence is well suited for landscape modeling; (2) it provides a means to combine more than two sources of data; and (3) it provides a way to accommodate prior knowledge of spatial dependencies associated with various data sources.

Hydrological responses of land use change from cotton (Gossypium hirsutum L.) to cellulosic bioenergy crops in the Southern High Plains of Texas, USA

The Southern High Plains (SHP) region of Texas in the United States, where cotton is grown in a vast acreage, has the potential to grow cellulosic bioenergy crops such as perennial grasses and biomass sorghum (Sorghum bicolor). Evaluation of hydrological responses and biofuel production potential of hypothetical land use change from cotton (Gossypium hirsutum L.) to cellulosic bioenergy crops enables better understanding of the associated key agroecosystem processes and provides for the feasibility assessment of the targeted land use change in the SHP. The Soil and Water Assessment Tool (SWAT) was used to assess the impacts of replacing cotton with perennial Alamo switchgrass (Panicum virgatum L.), Miscanthus × giganteus (Miscanthus sinensis Anderss. [Poaceae]), big bluestem (Andropogon gerardii) and annual biomass sorghum on water balances, water use efficiency and biofuel production potential in the Double Mountain Fork Brazos watershed. Under perennial grass scenarios, the average (1994–2009) annual surface runoff from the entire watershed decreased by 6–8% relative to the baseline cotton scenario. In contrast, surface runoff increased by about 5% under the biomass sorghum scenario. Perennial grass land use change scenarios suggested an increase in average annual percolation within a range of 3–22% and maintenance of a higher soil water content during August to April compared to the baseline cotton scenario. About 19.1, 11.1, 3.2 and 8.8 Mg ha−1 of biomass could potentially be produced if cotton area in the watershed would hypothetically be replaced by Miscanthus, switchgrass, big bluestem and biomass sorghum, respectively. Finally, Miscanthus and switchgrass were found to be ideal bioenergy crops for the dryland and irrigated systems, respectively, in the study watershed due to their higher water use efficiency, better water conservation effects, greater biomass and biofuel production potential, and minimum crop management requirements.

Micro Side-Viewing Optical Probe for VNIR-DRS Soil Measurement

In this paper, we present the design, fabrication and testing of a new micro optical sensor probe with side-viewing function to enable in-field visible-near infrared diffuse reflectance spectroscopy (VNIR-DRS) for soil. The optical probe consists of two microfabricated source chips and two collection chips. The source chips are used to deliver oblique (45°) light incidence onto the soil surface, while the diffuse reflectance is received from the normal direction through the collector chips. Several design and fabrication considerations have been made to optimize the optical transmission efficiency of the probe and the signal-to-noise ratio (SNR) of the collected diffuse reflectance signal. The probe has a small outer dimension of 6 mm × 15 mm × 6 mm and thus can be easily fit into a typical soil penetrometer for in-filed VNIR-DRS measurements. Using the new optical probe, VNIR-DRS measurements have been successfully conducted on a number of soil samples, which shows the new optical probe offers better performance than the existing commercial ASD® 135680 bifurcated reflectance soil probe.

Effect of diet composition on the determination of ash and moisture content in solid cattle manure using visible and near-infrared spectroscopy.

Visible and near-infrared (Vis-NIR, 350–2500 nm) diffuse reflection spectroscopy (DRS) models built from “as-collected” samples of solid cattle manure accurately predict concentrations of moisture and crude ash. Because different organic molecules emit different spectral signatures, variations in livestock diet composition may affect the predictive accuracy of these models. This study investigates how differences in livestock diet composition affect Vis-NIR DRS prediction of moisture and crude ash. Spectral signatures of solid manure samples (n = 216) from eighteen groups of cattle on six different diets were used to calibrate and validate partial least squares (PLS) regression models. Seven groups of PLS models were created and validated. In the first group, two-thirds of all samples were randomly selected as the calibration set and the remaining one-third were used for the validation set. In the remaining six groups, samples were grouped by livestock diet (ration). Each ration in turn was held out of calibrations and then used as a validation set. When predicting crude ash, the fully random calibration model produced a root mean square deviation (RMSD) of 2.5% on a dry basis (db), ratio of standard error of prediction to the root mean squared deviation (RPD) of 3.1, bias of 0.14% (db), and correlation coefficient r2 of 0.90., When predicting moisture, an RMSD of 1.5% on a wet basis (wb), RPD of 4.3, bias of −0.09% (wb), and r2 of 0.95 was achieved. Model accuracy and precision were not impaired by exclusion of any single ration from model calibration.

VIBRATION-INDUCED CONDUCTIVITY FLUCTUATION MEASUREMENT FOR SOIL BULK DENSITY ANALYSIS

Soil bulk density is a physical property of soils that affects water storage, water and nutrient movement, and plant root activity in the soil profile. The ability to quantify soil bulk density using vibration-induced conductivity fluctuation was investigated with possible field applications in the future. The AC electrical conductance of soil was measured using a pair of blade-like electrodes while exposing to periodic vibration. The blades were positioned longitudinally and transversally to the direction of the induced vibration to enable the calculation of a normalized index. This normalized index was expected to provide data independent from the vibration strength, and to reduce the effect of soil salinity and water content. Simulations on a simplified resistor lattice indicate that the ratio of transversal and longitudinal fluctuation decreases as soil bulk density increases. The experiment was conducted on natural and salinized fine sand at two moisture conditions and four compaction levels. The blade-shaped electrodes improved electrode-soil contact compared to cylindrical electrodes, and thereby, reduced measurement noise. Dry sand measurements showed an inverse correlation between the normalized conductivity fluctuation and soil bulk density for both longitudinal and transversal fluctuation. The wet natural and salinized soils performed very similarly as hypothesized, but their normalized VICOF response was not associated with bulk density changes. This lack of sensitivity might be attributed to the heavy electrodes and/or the specific vibration method used. The effects of electrode material, vibration method and soil properties on the experiment need further study.

THEORY AND TECHNIQUES FOR VIBRATION-INDUCED CONDUCTIVITY FLUCTUATION TESTING OF SOILS

First we present and theoretically analyze the phenomenological physical picture behind Vibration-Induced Conductivity Fluctuations. We identify the relevant tensors characterizing the electromechanical response against the vibrations for both longitudinal and transversal responses. We analyze the conductivity response with acceleration type vibrations and a new scheme, measurements with more advantageous compression type vibrations that are first introduced here. Compression vibrations provide sideband spectral lines shifted by the frequency of the vibration instead of its second harmonics; moreover the application of this method is less problematic with loose electrodes. Concerning geometry and electrodes, the large measurement errors in earlier experiment indicated electrode effects which justify using four-electrode type measurements. We propose and analyze new arrangements for the longitudinal and transversal measurements with both compression vibration and acceleration vibration for laboratory and field conditions.