Energy budgets reveal equal benefits of varied migration strategies in northern gannets

We investigated migration and wintering of adult northern gannets (Morus bassanus) breeding in east Scotland, North Sea, by deploying geolocation loggers over three winters. The wintering ranges of these birds varied from the North Sea to the Atlantic off West Africa. Flight time was taken as a proxy for migration and foraging effort. Gannets wintering off Africa had higher total flight times during migration than birds wintering further north. Total flight times in different wintering regions were generally low. Birds off West Africa consistently spent < 25 % of daylight hours in flight, but birds further north showed more variable values that may reflect more variable weather or food availability. Winter sea surface temperatures ranged from 9 °C (North Sea) to 16 °C (West Africa). Thermostatic costs in winter as estimated by measuring thermal conductance in carcasses in still air and water were 28 % higher in North Sea than off West Africa. This effect is aggravated by higher thermostatic costs caused by stronger wind chills in the North Sea compared to the conditions off West Africa. Birds wintering close to the UK arrived at the colony on average 12 days earlier than birds wintering off West Africa. We conclude that the net cost-benefit analysis may be similar for all wintering areas investigated.     

Inexpensive substrate sampler for macroinvertebrates

Assessment of aquatic macroinvertebrates is a critical component of many watershed monitoring programs and passive samplers are often used to collect long-term site data, especially in environments where active sampling is not possible. However, standard passive samplers can be expensive and lost in extreme conditions. We developed a sampler using plastic soda bottles (PSB) filled with river rock and compared its effectiveness with standard Hester-Dendy samplers in both lotic and lentic environments. Abundance, taxa richness, and macroinvertebrate composition showed no significant differences between sampler types in either habitat type. PSB samplers, which can be constructed for less than one dollar each, collected the same number of organisms and represented the same diversity as Hester-Dendy devices that cost around $38 each. In studies where funds are limited, PSB samplers appear to be suitable for passive monitoring.     

Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions

Deep learning (DL) models are increasingly used to make accurate hindcasts of management-relevant variables, but they are less commonly used in forecasting applications. Data assimilation (DA) can be used for forecasts to leverage real-time observations, where the difference between model predictions and observations today is used to adjust the model to make better predictions tomorrow. In this use case, we developed a process-guided DL and DA approach to make 7-day probabilistic forecasts of daily maximum water temperature in the Delaware River Basin in support of water management decisions. Our modeling system produced forecasts of daily maximum water temperature with an average root mean squared error (RMSE) from 1.1 to 1.4°C for 1-day-ahead and 1.4 to 1.9°C for 7-day-ahead forecasts across all sites. The DA algorithm marginally improved forecast performance when compared with forecasts produced using the process-guided DL model alone (0%–14% lower RMSE with the DA algorithm). Across all sites and lead times, 65%–82% of observations were within 90% forecast confidence intervals, which allowed managers to anticipate probability of exceedances of ecologically relevant thresholds and aid in decisions about releasing reservoir water downstream. The flexibility of DL models shows promise for forecasting other important environmental variables and aid in decision-making.     

A remote sensing tool for near real-time monitoring of harmful algal blooms and turbidity in reservoirs

Harmful algal blooms (HABs) diminish the utility of reservoirs for drinking water supply, irrigation, recreation, and ecosystem service provision. HABs decrease water quality and are a significant health concern in surface water bodies. Near real-time monitoring of HABs in reservoirs and small water bodies is essential to understand the dynamics of turbidity and HAB formation. This study uses satellite imagery to remotely sense chlorophyll-a concentrations (chl-a), phycocyanin concentrations, and turbidity in two reservoirs, the Grand Lake O′ the Cherokees and Hudson Reservoir, OK, USA, to develop a tool for near real-time monitoring of HABs. Landsat-8 and Sentinel-2 imagery from 2013 to 2017 and from 2015 to 2020 were used to train and test three different models that include multiple regression, support vector regression (SVR), and random forest regression (RFR). Performance was assessed by comparing the three models to estimate chl-a, phycocyanin, and turbidity. The results showed that RFR achieved the best performance, with R² values of 0.75, 0.82, and 0.79 for chl-a, turbidity, and phycocyanin, while multiple regression had R² values of 0.29, 0.51, and 0.46 and SVR had R² values of 0.58, 0.62, and 0.61 on the testing datasets, respectively. This paper examines the potential of the developed open-source satellite remote sensing tool for monitoring reservoirs in Oklahoma to assess spatial and temporal variations in surface water quality.     

Enhancing perspectives on lake impairments using satellite observations: A case study on High Rock Lake,North Carolina

Stakeholders developing water quality improvement plans for lakes and reservoirs are challenged by the sparsity of in-situ data and the uncertainty ingrained in management decisions. This study explores how satellite images can fill gaps in water quality databases and provide more holistic assessments of impairments. The study site is an impaired water body that is serving as a pilot for improving state-wide nutrient management planning processes. An existing in-situ database was used to calibrate semi-analytical models that relate satellite reflectance values to turbidity and total suspended solids (TSS). Landsat-7 images from 1999 to 2020 that overpass High Rock Lake, North Carolina were downloaded and processed, providing 42 turbidity and 39 TSS satellite and in-situ match-ups for model calibration and validation. Model r-squared values for the fitted turbidity and TSS models are 0.72 and 0.74, and the mean absolute errors are 14.6 NTU and 3.2 mg/L. The satellite estimates were compared to the in-situ data and simulated TSS values produced by a calibrated hydrologic-hydrodynamic model. The process-based model is considered less accurate than the satellite model based on statistical performance metrics. Comparisons between data sources are illustrated with time series plots, frequency curves, and aggregate decision metrics to highlight the dependence of lake impairment assessments on the spatial and temporal frequency of available data and model accuracy.     

Mentor–protege diversity and its impact on international internship experiences

This research examines demographic diversity between mentors and proteges on international internships. Using a sample of 138 interns on six‐month overseas assignments, the results indicate that interns who are different in nationality and gender from their mentors are much less likely to receive task‐related, social‐related, and career‐related support from them. Moreover, this deficit in mentoring is associated with poorer socialization to internship assignments, lower levels of learning about international business, lower likelihoods of receiving and accepting job offers from internship employers, and lower perceived career instrumentality of the internships. The implications of the results for future research on mentor–protege diversity and the design of international internships are discussed as well. Copyright © 1999 John Wiley & Sons, Ltd.     

The effect of different educational interventions on schoolchildren's knowledge of earthquake protective behaviour in Israel

Knowledge of appropriate behaviour during an earthquake is crucial for prevention of injury and loss of life. The Israeli Home Front Command conducts a yearly earthquake education programme in all Israeli schools, using three types of educational interventions: lectures, drills and a combination of the two. The aim of this study was to evaluate the effectiveness of these interventions in providing students with knowledge. We distributed a questionnaire to 2,648 children from the 5th and 6th grades in 120 schools nationwide. Knowledge scores for both 5th and 6th grades were increased, regardless of type of intervention, compared to the non-exposure group. A combined intervention of lectures and drills resulted in the highest knowledge scores. Our findings suggest that for the age group studied a combination of lectures and drills will likely prepare students best for how to behave in the event of an earthquake.     

Analysing spectroscopy data using two-step group penalized partial least squares regression

Environmental and Ecological Statistics - A statistical challenge to analyse hyperspectral data is the multicollinearity between spectral bands. Partial least squares (PLS) has been extensively...     

Modeling affective and cognitive responses to soft-target terrorism over time

Environment Systems and Decisions - There is great value in understanding the public’s reactions to terror attacks, though such reactions pose stark challenges for sound psychological...     

Systemic long-term impact of clinical pathways: UPMC experience with hysterectomy patients

Environment Systems and Decisions - Clinical pathways are defined as evidence-based, multidisciplinary care algorithms that outline essential steps in the management of patients. Pathway...