Understanding Informed Design through Trade-Off Decisions With an Empirically-Based Protocol for Students and Design Educators

Trade-off decisions, which necessitate striking a balance between two or more desirable but competing features, are a crucial part of design practice. However, they are known to be difficult for student designers to make. While designers, educators, and researchers have numerous methods to assess the quality of design artifacts, these methods are not necessarily easy to use, nor do they indicate design competency. Moreover, they are not grounded in a definition of engineering design. The objectives of this study were twofold. First, we developed a protocol to depict design artifact quality through the lens of design trade-off decisions. We aimed to produce a protocol that:(1) encompasses multiple complementary and competing dimensions, (2) can be applied consistently and systematically, and (3) indicates design competency. We conceptualized a quantitative representation of the degree to which a design artifact addresses human, technical, and economic requirements called the Trade-off Value Protocol. Second, we tested the Trade-off Value Protocol by applying it to 398 middle school students’ design artifacts of energy-efficient homes. We used an etic approach of thematic analysis to identify the patterns of variation therein. We found five distinct patterns of variation in the set of student design artifacts, which suggested certain trends in the way that students address design dimensions and demonstrate varying levels of design competency. The Trade-off Value Protocol isolates an important feature of design competency with which beginning designers often struggle and could be a tool for educators to help students become more informed designers

Drought Monitoring and Assessment: Remote Sensing and Modeling Approaches for the Famine Early Warning Systems Network

Drought monitoring is an essential component of drought risk management. It is usually carried out using drought indices/indicators that are continuous functions of rainfall and other hydrometeorological variables. This chapter presents a few examples of how remote sensing and hydrologic modeling techniques are being used to generate a suite of drought monitoring indicators at dekadal (10-day), monthly, seasonal, and annual time scales for several selected regions around the world. Satellite-based rainfall estimates are being used to produce drought indicators such as standardized precipitation index, dryness indicators, and start of season analysis. The Normalized Difference Vegetation Index is being used to monitor vegetation condition. Several satellite data products are combined using agrohydrologic models to produce multiple short- and long-term indicators of droughts. All the data sets are being produced and updated in near-real time to provide information about the onset, progression, extent, and intensity of drought conditions. The data and products produced are available for download from the Famine Early Warning Systems Network (FEWS NET) data portal at http:// earlywarning.usgs.gov. The availability of timely information and products support the decision-making processes in drought-related hazard assessment, monitoring, and management with the FEWS NET. The drought-hazard monitoring approach perfected by the U.S. Geological Survey for FEWS NET through the integration of satellite data and hydrologic modeling can form the basis for similar decision support systems. Such systems can operationally produce reliable and useful regional information that is relevant for local, district-level decision making

Water-Use Data in the United States: Challenges and Future Directions

In the United States, greater attention has been given to developing water supplies and quantifying available waters than determining who uses water, how much they withdraw and consume, and how and where water use occurs. As water supplies are stressed due to an increasingly variable climate, changing land-use, and growing water needs, greater consideration of the demand side of the water balance equation is essential. Data about the spatial and temporal aspects of water use for different purposes are now critical to long-term water supply planning and resource management. We detail the current state of water-use data, the major stakeholders involved in their collection and applications, and the challenges in obtaining high-quality nationally consistent data applicable to a range of scales and purposes. Opportunities to improve access, use, and sharing of water-use data are outlined. We cast a vision for a world-class national water-use data product that is accessible, timely, and spatially detailed. Our vision will leverage the strengths of existing local, state, and federal agencies to facilitate rapid and informed decision-making, modeling, and science for water resources. To inform future decision-making regarding water supplies and uses, we must coordinate efforts to substantially improve our capacity to collect, model, and disseminate water-use data

A New Approach to Evaluate and Reduce Uncertainty of Model-Based Biodiversity Projections for Conservation Policy Formulation

Biodiversity projections with uncertainty estimates under different climate, land-use, and policy scenarios are essential to setting and achieving international targets to mitigate biodiversity loss. Evaluating and improving biodiversity predictions to better inform policy decisions remains a central conservation goal and challenge. A comprehensive strategy to evaluate and reduce uncertainty of model outputs against observed measurements and multiple models would help to produce more robust biodiversity predictions. We propose an approach that integrates biodiversity models and emerging remote sensing and in-situ data streams to evaluate and reduce uncertainty with the goal of improving policy-relevant biodiversity predictions. In this article, we describe a multivariate approach to directly and indirectly evaluate and constrain model uncertainty, demonstrate a proof of concept of this approach, embed the concept within the broader context of model evaluation and scenario analysis for conservation policy, and highlight lessons from other modeling communities

Development of a Benchmark Eddy Flux Evapotranspiration Dataset for Evaluation of Satellite-Driven Evapotranspiration Models Over the CONUS

A large sample of ground-based evapotranspiration (ET) measurements made in the United States, primarily from eddy covariance systems, were post-processed to produce a benchmark ET dataset. The dataset was produced primarily to support the intercomparison and evaluation of the OpenET satellite-based remote sensing ET (RSET) models and could also be used to evaluate ET data from other models and approaches. OpenET is a web-based service that makes field-delineated and pixel-level ET estimates from well-established RSET models readily available to water managers, agricultural producers, and the public. The benchmark dataset is composed of flux and meteorological data from a variety of providers covering native vegetation and agricultural settings. Flux footprint predictions were developed for each station and included static flux footprints developed based on average wind direction and speed, as well as dynamic hourly footprints that were generated with a physically based model of upwind source area. The two footprint prediction methods were rigorously compared to evaluate their relative spatial coverage. Data from all sources were post-processed in a consistent and reproducible manner including data handling, gap-filling, temporal aggregation, and energy balance closure correction. The resulting dataset included 243,048 daily and 5,284 monthly ET values from 194 stations, with all data falling between 1995 and 2021. We assessed average daily energy imbalance using 172 flux sites with a total of 193,021 days of data, finding that overall turbulent fluxes were understated by about 12% on average relative to available energy. Multiple linear regression analyses indicated that daily average latent energy flux may be typically understated slightly more than sensible heat flux. This dataset was developed to provide a consistent reference to support evaluation of RSET data being developed for a wide range of applications related to water accounting and water resources management at field to watershed scales

Genome-Wide Association Mapping for Yield and Related Traits Under Drought Stressed and Non-stressed Environments in Wheat

Understanding the genetics of drought tolerance in hard red spring wheat (HRSW) in northern USA is a prerequisite for developing drought-tolerant cultivars for this region. An association mapping (AM) study for drought tolerance in spring wheat in northern USA was undertaken using 361 wheat genotypes and Infinium 90K single-nucleotide polymorphism (SNP) assay. The genotypes were evaluated in nine different locations of North Dakota (ND) for plant height (PH), days to heading (DH), yield (YLD), test weight (TW), and thousand kernel weight (TKW) under rain-fed conditions. Rainfall data and soil type of the locations were used to assess drought conditions. A mixed linear model (MLM), which accounts for population structure and kinship (PC+K), was used for marker–trait association. A total of 69 consistent QTL involved with drought tolerance-related traits were identified, with p ≤ 0.001. Chromosomes 1A, 3A, 3B, 4B, 4D, 5B, 6A, and 6B were identified to harbor major QTL for drought tolerance. Six potential novel QTL were identified on chromosomes 3D, 4A, 5B, 7A, and 7B. The novel QTL were identified for DH, PH, and TKW. The findings of this study can be used in marker-assisted selection (MAS) for drought-tolerance breeding in spring wheat

Characterization of a membrane-bound C-glucosyltransferase responsible for carminic acid biosynthesis in Dactylopius coccus Costa

Carminic acid is a widely applied red colorant that is still harvested from insects because its biosynthesis is not fully understood. Here, the authors identify and characterize a membrane-bound C-glucosyltransferase catalyzing the final step during carminic acid biosynthesis

Challenges and Future Directions in Quantifying Terrestrial Evapotranspiration

Abstract: Terrestrial evapotranspiration is the second‐largest component of the land water cycle, linking the water, energy, and carbon cycles and influencing the productivity and health of ecosystems. The dynamics of ET across a spectrum of spatiotemporal scales and their controls remain an active focus of research across different science disciplines. Here, we provide an overview of the current state of ET science across in situ measurements, partitioning of ET, and remote sensing, and discuss how different approaches complement one another based on their advantages and shortcomings. We aim to facilitate collaboration among a cross‐disciplinary group of ET scientists to overcome the challenges identified in this paper and ultimately advance our integrated understanding of ET

Rate-Induced Transitions in Networked Complex Adaptive Systems: Exploring Dynamics and Management Implications Across Ecological, Social, and Socioecological Systems

Complex adaptive systems (CASs), from ecosystems to economies, are open systems and inherently dependent on external conditions. While a system can transition from one state to another based on the magnitude of change in external conditions, the rate of change -- irrespective of magnitude -- may also lead to system state changes due to a phenomenon known as a rate-induced transition (RIT). This study presents a novel framework that captures RITs in CASs through a local model and a network extension where each node contributes to the structural adaptability of others. Our findings reveal how RITs occur at a critical environmental change rate, with lower-degree nodes tipping first due to fewer connections and reduced adaptive capacity. High-degree nodes tip later as their adaptability sources (lower-degree nodes) collapse. This pattern persists across various network structures. Our study calls for an extended perspective when managing CASs, emphasizing the need to focus not only on thresholds of external conditions but also the rate at which those conditions change, particularly in the context of the collapse of surrounding systems that contribute to the focal system's resilience. Our analytical method opens a path to designing management policies that mitigate RIT impacts and enhance resilience in ecological, social, and socioecological systems. These policies could include controlling environmental change rates, fostering system adaptability, implementing adaptive management strategies, and building capacity and knowledge exchange. Our study contributes to the understanding of RIT dynamics and informs effective management strategies for complex adaptive systems in the face of rapid environmental change.Comment: 25 pages, 4 figures, 1 box, supplementary informatio

Deriving Hourly Evapotranspiration Rates with SEBS: A Lysimetric Evaluation

Numerous energy balance (EB) algorithms have been developed to use remote sensing data for mapping evapotranspiration (ET) on a regional basis. Adopting any single or combination of these models for an operational ET remote sensing program requires a thorough evaluation. The Surface Energy Balance System (SEBS) was evaluated for its ability to estimate hourly ET rates of summer tall and short crops grown in the Texas High Plains by using 15 Landsat 5 Thematic Mapper scenes acquired during 2006 to 2009. Performance of SEBS was evaluated by comparing estimated hourly ET values with measured ET data from four large weighing lysimeters, each located at the center of a 4.3 ha field in the USDA-ARS Conservation and Production Research Laboratory in Bushland, TX. The performance of SEBS in estimating hourly ET was good for crops under both irrigated and dryland conditions. A locally derived, surface albedo-based soil heat flux (G) model further improved the G estimates. Root mean square error and mean bias error were 0.11 and −0.005 mm h−1, respectively, and the Nash–Sutcliff model efficiency was 0.85 between the measured and calculated hourly ET. Considering the equal or better performance with a minimal amount of ancillary data as compared to with other EB algorithms, SEBS is a promising tool for use in an operational ET remote sensing program in the semiarid Texas High Plains. However, thorough sensitivity and error propagation analyses of input variables to quantify their impact on ET estimations for the major crops in the Texas High Plains under different agroclimatological conditions are needed before adopting the SEBS into operational ET remote sensing programs for irrigation scheduling or other purposes