Journal Paper Digests 2022 #10
- A global 1-km downscaled SMAP soil moisture product based on thermal inertia theory
- A device to simulate contaminant transfer and surface and subsurface flow through intact soil monoliths
- Lasting Effects of Soil Compaction on Soil Water Regime Confirmed by Geoelectrical Monitoring
- Writing Accessible Theory in Ecology and Evolution: Insights from Cognitive Load Theory
- Confronting the water potential information gap
Confronting the water potential information gap
Water potential directly controls the function of leaves, roots and microbes, and gradients in water potential drive water flows throughout the soil-plant-atmosphere continuum. Notwithstanding its clear relevance for many ecosystem processes, soil water potential is rarely measured in situ, and plant water potential observations are generally discrete, sparse, and not yet aggregated into accessible databases. These gaps limit our conceptual understanding of biophysical responses to moisture stress and inject large uncertainty into hydrologic and land-surface models. Here, we outline the conceptual and predictive gains that could be made with more continuous and discoverable observations of water potential in soils and plants. We discuss improvements to sensor technologies that facilitate in situ characterization of water potential, as well as strategies for building new networks that aggregate water potential data across sites. We end by highlighting novel opportunities for linking more representative site-level observations of water potential to remotely sensed proxies. Together, these considerations offer a road map for clearer links between ecohydrological processes and the water potential gradients that have the ‘potential’ to substantially reduce conceptual and modelling uncertainties.
Continuous and discoverable observations of water potential could vastly improve understanding of biophysical processes throughout the soil-plant-atmosphere continuum and are achievable thanks to recent technological advances.
Writing Accessible Theory in Ecology and Evolution: Insights from Cognitive Load Theory
Theories underpin science. In biology, theories are often formalized in the form of mathematical models, which may render them inaccessible to those lacking mathematical training. In the present article, we consider how theories could be presented to better aid understanding. We provide concrete recommendations inspired by cognitive load theory, a branch of psychology that addresses impediments to knowledge acquisition. We classify these recommendations into two classes: those that increase the links between new and existing information and those that reduce unnecessary or irrelevant complexities. For each, we provide concrete examples to illustrate the scenarios in which they apply. By enhancing a reader’s familiarity with the material, these recommendations lower the mental capacity required to learn new information. Our hope is that these recommendations can provide a pathway for theoreticians to increase the accessibility of their work and for empiricists to engage with theory, strengthening the feedback between theory and experimentation.
Lasting Effects of Soil Compaction on Soil Water Regime Confirmed by Geoelectrical Monitoring
Despite its importance for hydrological and ecological soil functioning, characterizing, and quantifying soil structure in the field remains a challenge. Traditional characterization of soil structure often relies on point measurements, more recently, we advanced the use of minimally invasive geophysical methods that operate at plot-field scales and provide information under natural conditions. In this study, we expand the application using geoelectrical and time-domain reflectometry (TDR) monitoring of soil water dynamics to infer impacts of compaction on soil structure and function. We developed a modeling scheme combining a new pedophysical model of soil electrical conductivity and a soil-structure-informed one-dimensional water flow and heat-transfer model. The model was used to interpret Direct Current (DC)-resistivity and TDR monitoring data in compacted soils at the Soil Structure Observatory (SSO) located in the vicinity of Zurich, Switzerland. We find that (1) soil compaction leads to a persistent decrease in soil electrical resistivity and (2) that compacted soils are typically drier than non-compacted soils during long drying events. The main decrease in electrical resistivity is attributed to decreasing macroporosity and increasing connectivity of soil aggregates due to compaction. Higher water losses in compacted soils are explained in terms of enhanced evaporation. Our work advances characterization of soil structure at the field scale with electrical methods by offering a physically based explanation of the impact of soil compaction on electrical properties and by interpreting DC-resistivity data in terms of soil water dynamics.
A device to simulate contaminant transfer and surface and subsurface flow through intact soil monoliths
Many contaminants of agricultural origin are released into rural environments, particularly at the soil surface. Their fate has been extensively investigated in repacked soils, but only few studies have addressed their transport in structurally preserved natural soils. Much remains unknown about their fate and transfer within and between environmental compartments, while the susceptibility of these compartments to the contaminants adverse effects can vary considerably. The lack of studies regarding surface and subsurface transfer of contaminants through intact soil compared with studies on repacked soil led us to propose a device and protocol for sampling intact soil monoliths (60 x 30 x 22 cm(3), length, width, depth [LWD]) without heavy machinery. This is achieved by a modular design with removable top and bottom lid and a protocol of cutting the soil and replacing the affected bottom soil with a drainage layer of glass beads. The device allows the application of artificial rainfall events with simultaneous highly resolved quantification of infiltration excess overland flow and drainage discharge. It is designed to facilitate the collection of samples for physical, biological, and chemical analyses that fulfill cleanliness standards for organic contaminant analysis at trace levels using only poorly reactive stainless steel and glass materials. Testing of the device was performed by measuring the transfer of the antiparasitic drug ivermectin (IVM) through and over a silt-loam pasture soil. This test case illustrates how the device can be used to gain valuable information on the transfer of trace organic contaminants through topsoils.
A global 1-km downscaled SMAP soil moisture product based on thermal inertia theory
Microwave remote sensing technology has been applied to produce soil moisture (SM) retrievals on a global scale for various studies and applications. However, due to the limitations of current technology, the native spatial resolution of currently available passive microwave SM products is on the order of tens of kilometers, and this resolution cannot be used to characterize SM variability on a regional scale. To overcome this limitation, a downscaling algorithm based on the thermal inertia theory-derived relationship between SM and temperature difference was developed using outputs from the Global Land Data Assimilation System-Noah Land Surface Model and the land long-term data record-Advanced Very High Resolution Radiometer normalized difference vegetation index (NDVI) dataset and applied to the Aqua Moderate Resolution Imaging Spectroradiometer land surface temperature/NDVI data to produce a downscaled 1-km Soil Moisture Active Passive (SMAP) radiometer daily SM product, respectively, at 6:00 a.m. and 6:00 p.m. on a global scale from 2015 to 2020. The evaluation results reveal that the downscaling model performs better in the middle or low latitudes than in high latitudes. It also performs better in warm months than in cold months. The in situ SM observations from dense networks around the world were used to validate the 1-km and enhanced 9-km SMAP SM data. The validation metrics indicated that both the 1-km and 9-km SM data have overall overestimation trends, and the unbiased RMSE (0.063 m(3) m(-3) on average), mean absolute error (0.052 m(3) m(-3) on average), and spatial standard deviation (0.025 m(3) m(-3) on average) of the 1 km data are generally more accurate than the metrics of the 9-km SM data, which indicates that the downscaled data provide reliable observed SM information.