Key Thresholds Research Articles

Toward Near‐Field Tsunami Forecasting Along the Cascadia Subduction Zone Using Rapid GNSS Source Models

AbstractOver the past 15 years and through multiple large and devastating earthquakes, tsunami warning systems have grown considerably in their efficacy in providing timely and accurate forecasts to affected communities. However, one part of tsunami warning that still needs improvement is forecasts catered to local, near‐field communities in the time after an earthquake rupture but before coastal inundation. In this study, we test a rapid, Global Navigation Satellite Systems (GNSS)‐driven earthquake characterization model using a large data set of synthetic megathrust ruptures for its near‐field tsunami forecasting potential. We also provide a framework for tsunami forecasting that focuses on the likelihood of exceedance of user‐defined coastal amplitudes that may be of use in the first 15 min following an earthquake. Specifically, we can estimate the earthquake magnitude, without saturation, for 82% of tested ruptures. We can also identify test ruptures as dominantly thrust events, without analyst guidance for 92% of tested thrust ruptures. Finally, modeling the tsunami component of our rapidly estimated fault rupture leads to greater than 80% accuracy in identifying tsunami impact at key coastal amplitude thresholds. This is promising for near‐field warning when the time prior to inundation is limited to tens of minutes. We focus this study on large megathrust ruptures along the quiescent Cascadia subduction zone where there is already a dense GNSS network.

Sustainable Design of Diverging Diamond Interchange: Development of Warrants for Improving Operational Performance

Conventional diamond interchanges are facing ever-growing challenges related to traffic operations and safety risks due to increasing traffic volumes and worsening congestions. The agencies are well aware of the high socioeconomic (e.g., user delay cost, fuel cost, and high accident rates) and environmental losses (traffic emissions due to vehicles queuing) associated with the conventional interchange design. This paper provides insight into the different factors that affect the sustainability performance (operational and safety) of a conventional interchange through its redesign into the Diverging Diamond Interchange (DDI) with the increased left-turn demand. It also assesses the need to redesign an interchange to improve the efficiency. Two interchanges that have DDI designs were selected for investigations, and the required data were collected from the relevant agency. The average delay and the capacity were used as the Measures of Effectiveness (MOEs) for data analysis. Numerous factors, that affected these MOEs, were used to design an experiment. This experiment included different levels of volumes, geometric designs, and signal plans. The micro-simulation software (VISSIM 8.0) was employed to calibrate and validate the existing conditions through several steps, including signal optimization and driving behavior parameter optimization. The analysis of the results detected the key thresholds of switching from the conventional design to the innovative design under 90 different scenarios. Finally, the sustainability evaluation of DDI and Conventional Design Interchange was conducted based on their operation and safety performance comparison. The results and findings of this research will act as a guideline for decision-makers regarding when they should consider switching from the conventional interchange design to an innovative design.

Climate change impact assessment on grape and wine for Ontario, Canada’s appellations of origin

This paper assesses the impacts of observed (1981–2010) and projected (2011–2100) climate changes on key indicators and critical thresholds for grape growth and wine production across the three appellations of origin in Ontario (Canada). The historical analysis is based on local weather station data from Environment Canada and the projections are based on selective ensembles of seasonal global climate model projections, statistically downscaled to create local-daily climate change scenarios. Average growing season temperatures have already been warming and growing degree days are increasing, both at statistically significant rates, and are both projected to continue increasing over the course of the twenty-first century. For Niagara Peninsula and Lake Erie North Shore, these one-time cool climate wine regions have already evolved into intermediate climate wine regions and are projected to transition into warm or even hot climate regions by the 2080s. There is also evidence showing that heat stress has and will likely continue to increase, while freeze damage has and likely will continue to decrease. Pruning and shading are the key short-term adaptation strategies while varietal selection is the key long-term adaptation strategy to minimize risks and maximise opportunities in response to these observed and projected regional climate change impacts.

The scale of biodiversity impacts of the Belt and Road Initiative in Southeast Asia

The Belt and Road Initiative (BRI) is the largest infrastructure development in human history. Given its scale of influence and infrastructure undertakings, it is set to bring far-reaching environmental impacts to regions such as Southeast Asia, one of the biologically richest and most diverse regions in the world. Knowing where and what biodiversity BRI will potentially affect is crucial to plan and address its negative impacts. Using BRI transport infrastructure spatial data, we conducted a GIS analysis of the potential BRI impacts in Southeast Asia on terrestrial and marine biodiversity indicators, including protected areas (PAs), Key Biodiversity Areas (KBAs), terrestrial ecoregions, forest cover, threatened species, and fragile ecosystems such as seagrasses, mangroves, and coral reefs. We assessed the potential impacts across four key distance thresholds (1, 5, 25, and 50 km “impact zones”) on either side of the routes. For the terrestrial routes we assessed impacts for five different types of linear rail and road infrastructure development. Within 1 km of all routes 32 PAs, 40 KBAs and 29 ecoregions are intersected. While, 142 threatened species including 26 critically endangered species are within 5 km from new rail, which are also commonly found in frontier landscapes. In marine ecosystems 20 marine PAs and 16 KBAs are intersected by BRI marine routes. We conclude by discussing ways BRI could minimise its environmental impacts and utilise its political weight to advance conservation efforts in host nations.

Comparing key drivers of cyanobacteria biomass in temperate and tropical systems

There is growing evidence that cyanobacterial blooms are becoming more common in different parts of the world; within this context, predictive cyanobacteria models have an essential role in lake management. Several models have been successfully used in temperate systems to describe the main drivers of cyanobacterial blooms, but relatively less work has been conducted in the Tropics. We analyzed data from six Brazilian reservoirs and from five Canadian lakes using a combination of regression tree analyses and variation partitioning to evaluate the similarities and differences between regions. Our results, together with a synthesis of the literature from different latitudes, showed that trophic state (i.e. nutrients), climatic variables (e.g., temperature and/or precipitation) and hydrodynamic regimes (i.e. water residence time) are significant drivers of cyanobacteria biomass over several scales. Nutrients came out as the primary predictor in both regions, followed by climate, but when all systems were pooled together, water residence time came out as most important. The consistency in variables identified between regions suggests that these drivers are widely important and cyanobacteria responded quite similarly in different geographical settings and waterbody types (i.e. lakes or reservoirs). However, more work is needed to identify key thresholds across latitudinal gradients. Taken together, these results suggest that multi-region syntheses can help identify drivers that predict broad-scale patterns of cyanobacteria biomass.

Environmental sustainability of typical agro-food products: a scientifically sound and user friendly approach

The paper introduces an approach, developed in Agriculture & Quality programme, to evaluate the environmental sustainability of Apulian quality agro-food products that is integrated in the regional quality scheme “Quality Products”. It highlights the methodological approach adopted, the sustainability themes identified and the indicators selected. Indicators measurable at the farm/firm level were selected in relation to the following environmental themes: biodiversity, land use and management, energy use and climate change, use of chemical inputs, and responsible management of by-products and waste. A scoring scale was developed for each indicator; going from 0 (unsustainable) to 10 (very sustainable) with 5 corresponding to the sustainability threshold or reference value. The presented approach is both robust and user friendly and is in line with the principle entailing continuous improvement; the key sustainability thresholds will be periodically reviewed and updated. It represents a practical and innovative way to develop an information scheme for typical agri-food products and can be, with some refinement and contextualisation, easily scaled up to other territories.

A simplified math approach to predict ICU beds and mortality rate for hospital emergency planning under Covid-19 pandemic

The different stages of Covid-19 pandemic can be described by two key-variables: ICU patients and deaths in hospitals. We propose simple models that can be used by medical doctors and decision makers to predict the trends on both short-term and long-term horizons. Daily updates of the models with real data allow forecasting some key indicators for decision-making (an Excel file in the Supplemental material allows computing them). These are beds allocation, residence time, doubling time, rate of renewal, maximum daily rate of change (positive/negative), halfway points, maximum plateaus, asymptotic conditions, and dates and time intervals when some key thresholds are overtaken.Doubling time of ICU beds for Covid-19 emergency can be as low as 2–3 days at the outbreak of the pandemic. The models allow identifying the possible departure of the phenomenon from the predicted trend and thus can play the role of early warning systems and describe further outbreaks.

BMI mobility and obesity transitions among children in Ireland

This paper examines mobility and changes in Body Mass Index (BMI) for a sample of Irish children/adolescents across three waves of the longitudinal Growing Up in Ireland dataset. Particular attention is paid to transitions across the key BMI thresholds of overweight and obesity. Analysis is carried out by gender and by maternal education. In general, mobility is observed, with intra-generational rank-rank BMI coefficients of around 0.63 compared to coefficients of around 0.77 for the mothers of the children over the same time period. Across the distribution as a whole there is relatively little variation by gender and maternal education. However there a gender difference in terms of mobility out of obesity with the Shorrocks mobility index across categories of normal weight/overweight/obesity taking a value of 0.56 for females as opposed to 0.71 for males. This relative lack of mobility is more observed in later rather than earlier adolescence.

Twenty first century changes in Antarctic and Southern Ocean surface climate in CMIP6

AbstractTwo decades into the 21st century there is growing evidence for global impacts of Antarctic and Southern Ocean climate change. Reliable estimates of how the Antarctic climate system would behave under a range of scenarios of future external climate forcing are thus a high priority. Output from new model simulations coordinated as part of the Coupled Model Intercomparison Project Phase 6 (CMIP6) provides an opportunity for a comprehensive analysis of the latest generation of state‐of‐the‐art climate models following a wider range of experiment types and scenarios than previous CMIP phases. Here the main broad‐scale 21st century Antarctic projections provided by the CMIP6 models are shown across four forcing scenarios: SSP1‐2.6, SSP2‐4.5, SSP3‐7.0 and SSP5‐8.5. End‐of‐century Antarctic surface‐air temperature change across these scenarios (relative to 1995–2014) is 1.3, 2.5, 3.7 and 4.8°C. The corresponding proportional precipitation rate changes are 8, 16, 24 and 31%. In addition to these end‐of‐century changes, an assessment of scenario dependence of pathways of absolute and global‐relative 21st century projections is conducted. Potential differences in regional response are of particular relevance to coastal Antarctica, where, for example, ecosystems and ice shelves are highly sensitive to the timing of crossing of key thresholds in both atmospheric and oceanic conditions. Overall, it is found that the projected changes over coastal Antarctica do not scale linearly with global forcing. We identify two factors that appear to contribute: (a) a stronger global‐relative Southern Ocean warming in stabilisation (SSP2‐4.5) and aggressive mitigation (SSP1‐2.6) scenarios as the Southern Ocean continues to warm and (b) projected recovery of Southern Hemisphere stratospheric ozone and its effect on the mid‐latitude westerlies. The major implication is that over coastal Antarctica, the surface warming by 2100 is stronger relative to the global mean surface warming for the low forcing compared to high forcing future scenarios.

Successful Full Lactation Achieved by Mothers of Preterm Infants Using Exclusive Pumping.

Background: Some mothers of preterm infants suffer from difficulties in initiating and maintaining adequate milk production. This study was designed to investigate the milk production in mothers of preterm infants using hospital-grade breast pumps and to study the nutrient content of their milk.Methods: This was an observational prospective study. Mothers of preterm infants with gestational age < 32 weeks or birth weight < 1,500 g who were admitted to our hospital from August 2016 to December 2017 were recruited. A pumping diary and a questionnaire were completed by mothers (n = 30). Milk samples from before, during, and after each pumping session on days 7 and 14 postpartum were analyzed.Results: The median time to onset of lactogenesis II was 75.4 h. Mean milk output increased gradually, meeting key thresholds of 350 g/d on day 6, 500 g/d on day 8, and close to 750 g/d on day 14. Then, all mean milk outputs were over 750 g/d. The mean milk output exceeded the mean feeding volume on days 7, 14, 21, 28, 35, and 42. Mothers using hospital-grade breast pumps had more cumulative milk production compared with mothers using hand expression. The milk yield on days 7 and 14 were positively correlated to that on days 21, 28, 35, and 42. Milk outputs on days 7, 14, and 42 of mothers with a pumping frequency of ≥ 6 times/d were greater than mothers with a pumping frequency of < 6 times/d. Threshold values for milk output on day 7 (cut-off, 406.8 g/d; sensitivity, 68.2%; specificity, 100%) and day 14 (cut-off, 518.0 g/d; sensitivity, 81.8%; specificity, 100%) were identified as predicting a milk output of more than 750 g/d on day 42. Fat and energy levels were higher in hind-milk than fore- or mixed-milk on days 7 and 14. Those who pumped ≥ 6 times/d had higher levels of fat, carbohydrate, and energy in their milk on day 7.Conclusion: Most preterm infants' mothers using a hospital-grade pump with a pumping frequency of ≥ 6 times/d can reach full lactation successfully. Nutrient analysis of the human milk should be performed.

Geomechanical models for the quantitatively prediction of multi-scale fracture distribution in carbonate reservoirs

In order to predict the multi-scale fractures in carbonate, the geo-mechanical model need to be established. The key thresholds (0.82σc and σc) for the micro-fractures and macro-fractures according to the mass release of the elastic strain energy and bursting was confirmed, through CT scanning and some mechanics experiments. Then two physical models between strain energy density and fracture volume density were built based on the geomechanics theory. Combined with the Mohr-Coulomb and Griffith's criterion, the fracture parameters under the complex stress condition were modified and deduced. All geo-mechanical algorithms were written into the finite element platform, combined with the paleo-structural restoration of the Hetianhe anticline, the three-dimensional distribution of the multi-scale fracture density and aperture were quantitatively simulated. The prediction results are consistent with current in-situ core and FMI observations.

Redox classification and calibration of redox thresholds in sedimentary systems

Existing redox classifications and the calibrations of elemental proxies to modern environmental redox scales are in need of re-evaluation. Here, we review environmental redox classifications, commonly used elemental redox proxies, and their intercalibration, and we propose a novel approach to improve the calibration of such proxies, using datasets from the modern Black Sea, Saanich Inlet, and California Margin as examples. Our approach is based on recognition of compound covariation patterns among pairs of elemental redox proxies within a redox framework based on three key thresholds: (1) the Re4+/Re3− couple near the suboxidized/subreduced boundary of the suboxic zone, (2) the U6+/U4+ couple in the middle of the subreduced zone, and (3) the SO42−/H2S couple at the suboxic/euxinic boundary. Within this framework, it is possible to determine the relative timing of onset and the degree of enrichment of other elemental redox proxies. Our analysis demonstrates that, even though some elements exhibit limited enrichment within the suboxic zone, the bulk of authigenic enrichment of the redox-sensitive elements considered in this study occurs within the euxinic zone. One important finding of our study is that the threshold value associated with a given elemental proxy can vary considerably between depositional systems. For this reason, it is inadvisable to transfer published threshold values (i.e., from earlier paleoredox studies) to completely different formations, and redox proxies must be internally calibrated for each individual paleodepositional system under investigation.

Combination of a Big Data Analytics Resource System With an Artificial Intelligence Algorithm to Identify Clinically Actionable Radiation Dose Thresholds for Dysphagia in Head and Neck Patients

PurposeWe combined clinical practice changes, standardizations, and technology to automate aggregation, integration, and harmonization of comprehensive patient data from the multiple source systems used in clinical practice into a big data analytics resource system (BDARS). We then developed novel artificial intelligence algorithms, coupled with the BDARS, to identify structure dose volume histograms (DVH) metrics associated with dysphagia. Methods and MaterialsFrom the BDARS harmonized data of ≥22,000 patients, we identified 132 patients recently treated for head and neck cancer who also demonstrated dysphagia scores that worsened from base line to a maximum grade ≥2. We developed a method that used both physical and biologically corrected (α/β = 2.5) DVH curves to test both absolute and percentage volume based DVH metrics. Combining a statistical categorization algorithm with machine learning (SCA-ML) provided more extensive detailing of response threshold evidence than either approach alone. A sensitivity guided, minimum input, machine learning (ML) model was iteratively constructed to identify the key structure DVH metric thresholds. ResultsSeven swallowing structures producing 738 candidate DVH metrics were ranked for association with dysphagia using SCA-ML scoring. Structures included superior pharyngeal constrictor (SPC), inferior pharyngeal constrictor (IPC), larynx, and esophagus. Bilateral parotid and submandibular gland (SG) structures were categorized by relative mean dose (eg, SG_high, SG_low) as a dose versus tumor centric analog to contra and ipsilateral designations. Structure DVH metrics with high SCA-ML scores included the following: SPC: D20% (equivalent dose [EQD2] Gy) ≥47.7; SPC: D25% (Gy) ≥50.4; IPC: D35% (Gy) ≥61.7; parotid_low: D60% (Gy) ≥13.2; and SG_high: D35% (Gy) ≥61.7. Larynx: D25% (Gy) ≥21.2 and SG_low: D45% ≥28.2 had high SCA-ML scores but were segmented on less than 90% of plans. A model based on SPC: D20% (EQD2 Gy) alone had sensitivity and area under the curve of 0.88 ± 0.13 and 0.74 ± 0.17, respectively. ConclusionsThis study provides practical demonstration of combining big data with artificial intelligence to increase volume of evidence in clinical learning paradigms.

Research on Passenger Flow Early Warning of Urban Rail Transit Station Based on System Dynamics

Large-scale passenger flows occur frequently during the peak hours of urban rail transit stations and on holidays. Thus, the timely and accurate early warning of impending large-scale passenger flows can positively impact the operational safety of the entire station. By further deepening the definition of passenger flow warnings in stations, a new model of urban rail transit station passenger flow based on system dynamics is constructed. The method of determining the key area of passenger flows in the early warning stage based on streamlines is proposed; the key indicators and thresholds affecting early warnings are studied. Finally, taking a typical station as an example, a station model is built using Anylogic software. The parameter sensitivity analysis is used to determine the impact of each key indicator on the passenger flow in the key area of the station early warning, and the reference threshold of each indicator is determined.

Understanding and Modeling the Occurrence of E. coli Blooms in Drinking Water Reservoirs

AbstractCertain strains of Escherichia coli have been reported to bloom in the environment, resulting in high concentrations in waters in the absence of apparent fecal input or human pathogens, and in turn, undermining its reliability as an indicator of recent fecal contamination. Given the capacity of environmental strains of E. coli to replicate in the environment, the objective of this research work was to investigate whether any of the routinely measured parameters could predict the onset of an E. coli bloom in drinking water reservoirs. Information from historical catchment, weather, and water quality data were extracted for a number of Australian reservoirs that experienced E. coli blooms. Data were preprocessed and analyzed with time series analysis, linear and nonlinear regression, and self‐organizing maps. Findings suggest that warm water, dry catchments, algal blooms, and nutrient availability were important factors in increasing the propensity for a bloom. Nutrient availability can be affected by many extrinsic factors that are often not well characterized, such as bushfires and back burning, decomposition of aquatic species, and dust storms. Based on data analysis outputs, a data‐driven Bayesian Network model was developed, which, considering the paucity of data for some key input parameters, should only be used to trigger more intensive monitoring programs whenever the predicted risk of a bloom exceeds predetermined key thresholds. Such new data could be fed into the model to continuously improve its accuracy, and to eventually predict and proactively manage future blooms.

Beyond the low-carbon niche: Global tipping points in the rise of wind, solar, and electric vehicles to regime scale systems

Scholars are interested in the potential of positive feedbacks between market and political progress to accelerate a shift to low-carbon energy systems when new industries gain momentum and contest incumbents. However, the literatures on climate-policy feedbacks and sociotechnical transitions feature minimal consideration of the essential role of scaling processes and scalar differences (e.g. between photovoltaics and concentrating solar power). This article addresses the role of scaling processes by characterizing the tipping points (or key thresholds) involved in a shift from “niche scale” to “regime scale.” It introduces indicators of “regime scale” as applied to the global cases of wind, photovoltaics, and lithium-ion–based electric-vehicle (EV) industries. The indicators highlight “feedback-friendly” characteristics that help power transition-accelerating feedbacks. The results show the shift of photovoltaics and wind towards regime scale tipped circa 2008 and circa 2015 for EVs. The discussion considers the new social and political path-dependencies produced at regime scale and explains why political programs to accelerate energy transitions – like a Green New Deal – should consider technology scale and leverage technologies with “feedback-friendly” characteristics.

Research on the Impact of Electricity Price Fluctuation on Energy Management Strategy

Energy management strategy (EMS) is an effective measure to improve the energy economy, however, where fluctuant electricity and fuel prices were not taken into account. Since price fluctuations have an impact on rule-based energy management strategies, constant price energy management strategies are not optimal. This paper proposes a novel energy management strategy considering price fluctuation of electricity and fuel for plug-in electric vehicles (PHEVs). Firstly, the electricity price data of partial cities during peak and trough periods are counted. Secondly, a SA-PSO algorithm is used in the rule-based energy management strategy to optimize the key thresholds. The influence of electricity price fluctuation on energy management strategy has been analyzed.

Assessing status and trends of open ocean habitats: A regionally resolved approach and Southern Ocean application

Abstract Assessing the status and trends of habitats, species, and ecosystems in the vast, remote, and difficult to observe open oceans is a pressing challenge for conserving and managing marine species and ecosystems under a changing climate. Here, we present a framework for assessing the status and trends of key ocean habitat components using synoptic data sources. It aims to quantify ecosystem variability and long-term change, and to provide summaries and indicators of change at scales that are both ecologically meaningful and relevant for management. We illustrate our approach using the Southern Ocean as a case-study and assess habitat based on remotely-sensed sea ice concentration, sea surface temperature (SST) and chlorophyll-a. We use Antarctic krill Euphausia superba as an illustrative example of how thresholds and optimum ranges for key taxa (and the ranges they define) can be used to delimit areas that are likely to constitute “good” habitat. Availability of “good” habitat, in terms of area, provides a simple indicator for quantifying change through time, and for assessing regional differences. Our assessment of sea ice reveals that the absence of a strong trend in the mean annual duration of sea ice cover around Antarctica masks a loss of areas with the longest periods of cover. In the polar latitudinal zone of the East Pacific, the area with the longest ice coverage has declined by 123,533 km2 over the past four decades. Our assessment of chlorophyll-a and SST highlights that the area of “good” habitat for krill has increased in the high-latitude zone, but decreased in the polar zone close to the continent in all sectors other than the East Pacific, where the reverse has been true. These examples demonstrate how our general approach can visualise and identify (i) known trends in mean values but also diagnose where changes in the habitat area over time may not match the mean trend; (ii) key habitat thresholds across a range of variables and in different seasons; and (iii) changes in the degree of spatial overlap of areas with desirable ranges for different habitat components. Our approach provides a versatile method to generate summaries of status and trends of ocean habitats at scales meaningful to decision makers. It can readily be adapted to other habitat variables and for other areas, supporting ongoing efforts to assess status and trends of open ocean habitats worldwide.

Parameterizing and validating existing algorithms for identifying out-of-bed time using hip-worn accelerometer data from older women

Objective: To parameterize and validate two existing algorithms for identifying out-of-bed time using 24 h hip-worn accelerometer data from older women. Approach: Overall, 628 women (80 ± 6 years old) wore ActiGraph GT3X+ accelerometers 24 h d−1 for up to 7 d and concurrently completed sleep-logs. Trained staff used a validated visual analysis protocol to measure in-bed periods on accelerometer tracings (criterion). The Tracy and McVeigh algorithms were adapted for optimal use in older adults. A training set of 314 women was used to choose two key thresholds by maximizing the sum of sensitivity and specificity for each algorithm and data (vertical axis, VA, and vector magnitude [VM]) combination. Data from the remaining 314 women were then used to test agreement in waking wear time (i.e. out-of-bed time while wearing the accelerometer) by computing sensitivity, specificity, and kappa comparing the algorithm output with the criterion. Waking wear time-adjusted means of sedentary time, light-intensity physical activity (light PA) and moderate-to-vigorous-intensity physical activity (MVPA) were then estimated and compared. Main results: Waking wear time agreement with the criterion was high for Tracy_VA, Tracy_VM, McVeigh_VA, and highest for McVeigh_VM. Compared to the criterion, McVeigh_VM had mean sensitivity = 0.92, specificity = 0.87, kappa = 0.80, and overall mean difference (±SD) of −0.04 ± 2.5 h d−1. Minutes of sedentary time, light PA, and MVPA adjusted for waking wear time using the criterion measure and McVeigh_VM were not statistically different (p > 0.43|all). Significance: The McVeigh algorithm with optimal parameters using VM performed best compared to criterion sleep-log assisted visual analysis and is suitable for automated identification of waking wear time in older women when visual analysis is not feasible.

Identifying Environmental Cues for Atlantic Sturgeon and Shortnose Sturgeon Spawning Migrations in the Savannah River

AbstractWe investigated environmental cues for spawning migration behavior of Atlantic Sturgeon Acipenser oxyrinchus and Shortnose Sturgeon A. brevirostrum in the lower Savannah River, South Carolina and Georgia, from January 2013 to May 2018. Sturgeon were implanted with acoustic transmitters and detected on an array of 45 stationary receivers located every 5–10 km between Savannah Harbor and the upstream‐most barrier to movement (301 fluvial kilometers). Throughout the study period, we observed six Atlantic Sturgeon attempting nine fall migrations (n = 918 records), four Atlantic Sturgeon attempting eight spring migrations (n = 257 records), and 15 Shortnose Sturgeon attempting 29 spring migrations (n = 3,542 records). Cues for the initiation of migration and upriver movement were species‐specific. We observed significance in the main effects of water temperature, 3‐d lagged temperature, maximum discharge, and 3‐d lagged discharge, as well as in the interaction effect of 3‐d lagged temperature × 3‐d lagged discharge. Water temperature was the primary predictor of sturgeon migrations, which can be used to determine spawning season, but discharge also played a significant role in predicting upriver movement, particularly when high flows began to diminish. Directed flow regulation (e.g., intermittent flood pulsing) during key temperature thresholds may better facilitate the upriver movement of sturgeons and aid in the conservation of these imperiled species.