scholarly journals Dynamic-parameter movement models reveal drivers of migratory pace in a soaring bird

2018 ◽  
Author(s):  
Joseph M. Eisaguirre ◽  
Marie Auger-Méthé ◽  
Christopher P. Barger ◽  
Stephen B. Lewis ◽  
Travis L. Booms ◽  
...  

AstractLong distance migration can increase lifetime fitness, but can be costly, incurring increased energetic expenses and higher mortality risks. Stopover and other en route behaviors allow animals to rest and replenish energy stores and avoid or mitigate other hazards during migration. Some animals, such as soaring birds, can subsidize the energetic costs of migration by extracting energy from flowing air. However, it is unclear how these energy sources affect or interact with behavioral processes and stopover in long-distance soaring migrants. To understand these behaviors and the effects of processes that might enhance use of flight subsidies, we developed a flexible mechanistic model to predict how flight subsidies drive migrant behavior and movement processes. The novel modelling framework incorporated time-varying parameters informed by environmental covariates to characterize a continuous range of behaviors during migration. This model framework was fit to GPS satellite telemetry data collected from a large soaring and opportunist foraging bird, the golden eagle (Aquila chrysaetos), during migration in western North America. Fitted dynamic model parameters revealed a clear circadian rhythm in eagle movement and behavior, which was directly related to thermal uplift. Behavioral budgets were complex, however, with evidence for a joint migrating/foraging behavior, resembling a slower paced fly-and-forage migration, which could facilitate efficient refueling while still ensuring migration progress. In previous work, ecological and foraging conditions are normally considered to be the key aspects of stopover location quality, but taxa that can tap energy sources from moving fluids to drive migratory locomotion, such as the golden eagle, may pace migration based on both foraging opportunities and available flight subsidies.

1999 ◽  
Vol 39 (10-11) ◽  
pp. 193-196
Author(s):  
J. Petersen ◽  
J. G. Petrie

The release of heavy metal species from deposits of solid waste materials originating from minerals processing operations poses a serious environmental risk should such species migrate beyond the boundaries of the deposit into the surrounding environment. Legislation increasingly places the liability for wastes with the operators of the process that generates them. The costs for long-term monitoring and clean-up following a potential critical leakage have to be factored in the overall project plan from the outset. Thus assessment of the potential for a particular waste material to generate a harmful leachate is directly relevant for estimating the environmental risk associated with the planned disposal operation. A rigorous mechanistic model is proposed, which allows prediction of the time-dependent generation of a leachate from a solid mineral waste deposit. Model parameters are obtained from a suitably designed laboratory waste assessment methodology on a relatively small sample of the prospective waste material. The parameters are not specific to the laboratory environment in which they were obtained but are valid also for full-scale heap modelling. In this way the model, combined with the assessment methodology, becomes a powerful tool for meaningful assessment of the risks associated with solid waste disposal strategies.


Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 463
Author(s):  
Gopinathan R. Abhijith ◽  
Leonid Kadinski ◽  
Avi Ostfeld

The formation of bacterial regrowth and disinfection by-products is ubiquitous in chlorinated water distribution systems (WDSs) operated with organic loads. A generic, easy-to-use mechanistic model describing the fundamental processes governing the interrelationship between chlorine, total organic carbon (TOC), and bacteria to analyze the spatiotemporal water quality variations in WDSs was developed using EPANET-MSX. The representation of multispecies reactions was simplified to minimize the interdependent model parameters. The physicochemical/biological processes that cannot be experimentally determined were neglected. The effects of source water characteristics and water residence time on controlling bacterial regrowth and Trihalomethane (THM) formation in two well-tested systems under chlorinated and non-chlorinated conditions were analyzed by applying the model. The results established that a 100% increase in the free chlorine concentration and a 50% reduction in the TOC at the source effectuated a 5.87 log scale decrement in the bacteriological activity at the expense of a 60% increase in THM formation. The sensitivity study showed the impact of the operating conditions and the network characteristics in determining parameter sensitivities to model outputs. The maximum specific growth rate constant for bulk phase bacteria was found to be the most sensitive parameter to the predicted bacterial regrowth.


Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 317
Author(s):  
Fadhliani Umar ◽  
Zed Zulkafli ◽  
Badronnisa Yusuf ◽  
Siti Nurhidayu

Rainfall runoff modeling has been a subject of interest for decades due to a need to understand a catchment system for management, for example regarding extreme event occurrences such as flooding. Tropical catchments are particularly prone to the hazards of extreme precipitation and the internal drivers of change in the system, such as deforestation and land use change. A model framework of dynamic TOPMODEL, DECIPHeR v1—considering the flexibility, modularity, and portability—and Generalized Likelihood Uncertainty Estimation (GLUE) method are both used in this study. They reveal model performance for the streamflow simulation in a tropical catchment, i.e., the Kelantan River in Malaysia, that is prone to flooding and experiences high rates of land use change. Thirty-two years’ continuous simulation at a daily time scale simulation along with uncertainty analysis resulted in a Nash Sutcliffe Efficiency (NSE) score of 0.42 from the highest ranked parameter set, while 25.35% of the measurement falls within the uncertainty boundary based on a behavioral threshold NSE 0.3. The performance and behavior of the model in the continuous simulation suggests a limited ability of the model to represent the system, particularly along the low flow regime. In contrast, the simulation of eight peak flow events achieves moderate to good fit, with the four peak flow events simulation returning an NSE > 0.5. Nonetheless, the parameter scatter plot from both the continuous simulation and analyses of peak flow events indicate unidentifiability of all model parameters. This may be attributable to the catchment modeling scale. The results demand further investigation regarding the heterogeneity of parameters and calibration at multiple scales.


Author(s):  
J. Lizardo Cruz-Romo ◽  
Martin Sánchez-Vilchis ◽  
Víctor Sánchez-Cordero ◽  
Robert K. Murphy ◽  
Ismael Cruz-Molina ◽  
...  

ABSTRACT The southern limit of the Golden Eagle's (Aquila chrysaetos) breeding range in North America is Mexico, where the eagle is the national symbol yet designated as a threatened, high priority species for conservation action. Movement information needed for conserving Mexico's Golden Eagles is sparse; knowledge of dispersal from natal areas is essential to understand the eagle's ecology and help provide for its management. Using satellite telemetry data, we analyzed movements of three males and one female from central Mexico during their first year of life; we documented (1) timing and distance of initial dispersal movements, (2) total distance traveled and maximum distance from natal site by month of age following fledging, and (3) size of areas (based on 95% adaptive local convex hulls) across which eagles ranged following initial dispersal. Individual eagles dispersed from their natal areas between mid-September and mid-November, at 6–8 mo of age. Monthly total distance traveled by males reached approximately 350–1350 km at 8–11 mo; the female's peak monthly travel was 3000 km, at age 7 mo. Monthly proximity to natal sites by individuals at ages 8–12 mo was relatively constant, averaging 17.9 km (SD = 5.7) to 129.1 km (SD = 11.3). After dispersal, the monthly ranging areas overall increased during the first year of life for all eagles, especially the female, due mainly to multiple long-distance excursions. Our data suggest that movement behavior of juvenile Golden Eagles from Mexico is mostly similar to that of conspecifics from nonmigratory populations elsewhere. Our study may help serve as a foundation for future work to better understand movement dynamics and resource selection by Mexico's Golden Eagles.


2018 ◽  
Vol 40 ◽  
pp. 02046 ◽  
Author(s):  
Eric Gasser ◽  
Andrew Simon ◽  
Paolo Perona ◽  
Luuk Dorren ◽  
Johannes Hübl ◽  
...  

Large woody debris (LWD) exacerbates flood damages near civil structures and in urbanized areas and the awareness of LWD as a risk is becoming more and more relevant. The recruitment of “fresh” large woody debris has been documented to play a significant role of the total amount of wood transported during flood events in mountain catchments. Predominately, LWD recruitment due to hydraulic and geotechnical bank erosion and shallow landslides contribute to high volumes of wood during floods. Quantifying the effects of vegetation on channel and slope processes is extremely complex. This manuscript therefore presents the concepts that are being implemented in a new modelling framework that aims to improve the quantification of vegetation effects on LWD recruitment processes. One of the focuses of the model framework is the implementation of the effect of spatio-temporal distribution of root reinforcement in recruitment processes such as bank erosion and shallow landslides in mountain catchments. Further, spatio-temporal precipitation patterns will be considered using a probabilistic approach to account for the spatio-temporal precipitation variability to estimate a LWD recruitment correction coefficient. Preliminary results are herein presented and discussed in form of a case study in the Swiss Prealps.


Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 1948 ◽  
Author(s):  
Fu-Cheng Wang ◽  
Yi-Shao Hsiao ◽  
Yi-Zhe Yang

This paper discusses the optimization of hybrid power systems, which consist of solar cells, wind turbines, fuel cells, hydrogen electrolysis, chemical hydrogen generation, and batteries. Because hybrid power systems have multiple energy sources and utilize different types of storage, we first developed a general hybrid power model using the Matlab/SimPowerSystemTM, and then tuned model parameters based on the experimental results. This model was subsequently applied to predict the responses of four different hybrid power systems for three typical loads, without conducting individual experiments. Furthermore, cost and reliability indexes were defined to evaluate system performance and to derive optimal system layouts. Finally, the impacts of hydrogen costs on system optimization was discussed. In the future, the developed method could be applied to design customized hybrid power systems.


2017 ◽  
Vol 17 (6) ◽  
pp. 401-422 ◽  
Author(s):  
Buu-Chau Truong ◽  
Cathy WS Chen ◽  
Songsak Sriboonchitta

This study proposes a new model for integer-valued time series—the hysteretic Poisson integer-valued generalized autoregressive conditionally heteroskedastic (INGARCH) model—which has an integrated hysteresis zone in the switching mechanism of the conditional expectation. Our modelling framework provides a parsimonious representation of the salient features of integer-valued time series, such as discreteness, over-dispersion, asymmetry and structural change. We adopt Bayesian methods with a Markov chain Monte Carlo sampling scheme to estimate model parameters and utilize the Bayesian information criteria for model comparison. We then apply the proposed model to five real time series of criminal incidents recorded by the New South Wales Police Force in Australia. Simulation results and empirical analysis highlight the better performance of hysteresis in modelling the integer-valued time series.


2014 ◽  
Vol 14 (16) ◽  
pp. 8533-8557 ◽  
Author(s):  
M. Karl ◽  
N. Castell ◽  
D. Simpson ◽  
S. Solberg ◽  
J. Starrfelt ◽  
...  

Abstract. In this study, a new model framework that couples the atmospheric chemistry transport model system Weather Research and Forecasting–European Monitoring and Evaluation Programme (WRF-EMEP) and the multimedia fugacity level III model was used to assess the environmental impact of in-air amine emissions from post-combustion carbon dioxide capture. The modelling framework was applied to a typical carbon capture plant artificially placed at Mongstad, on the west coast of Norway. The study region is characterized by high precipitation amounts, relatively few sunshine hours, predominantly westerly winds from the North Atlantic and complex topography. Mongstad can be considered as moderately polluted due to refinery activities. WRF-EMEP enables a detailed treatment of amine chemistry in addition to atmospheric transport and deposition. Deposition fluxes of WRF-EMEP simulations were used as input to the fugacity model in order to derive concentrations of nitramines and nitrosamine in lake water. Predicted concentrations of nitramines and nitrosamines in ground-level air and drinking water were found to be highly sensitive to the description of amine chemistry, especially of the night-time chemistry with the nitrate (NO3) radical. Sensitivity analysis of the fugacity model indicates that catchment characteristics and chemical degradation rates in soil and water are among the important factors controlling the fate of these compounds in lake water. The study shows that realistic emission of commonly used amines result in levels of the sum of nitrosamines and nitramines in ground-level air (0.6–10 pg m−3) and drinking water (0.04–0.25 ng L−1) below the current safety guideline for human health that is enforced by the Norwegian Environment Agency. The modelling framework developed in this study can be used to evaluate possible environmental impacts of emissions of amines from post-combustion capture in other regions of the world.


2004 ◽  
Vol 4 (6) ◽  
pp. 8627-8676 ◽  
Author(s):  
D. O. Topping ◽  
G. B. McFiggans ◽  
H. Coe

Abstract. A thermodynamic modelling framework to predict the equilibrium behaviour of mixed inorganic salt aerosols is developed, and then coupled with a technique for finding a solution to the Köhler equation in order to create a diameter dependent hygroscopic aerosol model (Aerosol Diameter Dependent Equilibrium Model – ADDEM). The model described here provides a robust and accurate inorganic basis using a mole fraction based activity coefficient model and adjusted energies of formation for treating solid precipitation. The model framework can accommodate organic components, though this added complexity is considered in a companion paper, whereas this paper describes the development of the modelling architecture to be used and predictions of an inorganic model alone. The modelling framework has been developed to flexibly use a combination of mixing rules and other potentially more accurate techniques where available to calculate the water content. Comparisons with other state-of-the-art general equilibrium models and experimental data are presented and show excellent agreement. The Kelvin effect can be considered in this scheme using a variety of surface tension models. Comparison of predicted diameter dependent phenomena, such as the increased relative humidity for onset of deliquescence with decreasing diameter, with another diameter dependent model is very good despite the different approach used. The model is subject to various sensitivities. For the inorganic systems studied here, the model is sensitive to choice of surface tension scheme used, which decreases for larger aerosol. Large sensitivities are found for the value of dry density used. It is thus likely that the history of the aerosol studied in a hygroscopic tandem differential mobility analyser (HTDMA), specifically the nature of the drying process that will influence the final crystalline form, will create systematic uncertainties upon comparisons with theoretical predictions. However, the magnitudes of all of the above sensitivities are potentially less than those introduced when using a semi ideal growth factor analogue for certain conditions.


2020 ◽  
Author(s):  
Thijs Defraeye ◽  
Flora Bahrami ◽  
Rene M Rossi

Transdermal drug delivery systems are a key technology to administer drugs with a high first-pass effect in a non-invasive and controlled way. Physics-based modeling and simulation are on their way to become a cornerstone in the engineering of these healthcare devices since it provides a unique complementarity to experimental data and insights. Simulations enable to virtually probe the drug transport inside the skin at each point in time and space. However, the tedious experimental or numerical determination of material properties currently forms a bottleneck in the modeling workflow. We show that multiparameter inverse modeling to determine the drug diffusion and partition coefficients is a fast and reliable alternative. We demonstrate this strategy for transdermal delivery of fentanyl. We found that inverse modeling reduced the normalized root mean square deviation of the measured drug uptake flux from 26 to 9%, when compared to the experimental measurement of all skin properties. We found that this improved agreement with experiments was only possible if the diffusion in the reservoir holding the drug was smaller than the experimentally-measured diffusion coefficients suggested. For indirect inverse modeling, which systematically explores the entire parametric space, 30 000 simulations were required. By relying on direct inverse modeling, we reduced the number of simulations to be performed to only 300, so a factor 100 difference. The modeling approach's added value is that it can be calibrated once in-silico for all model parameters simultaneously by solely relying on a single measurement of the drug uptake flux evolution over time. We showed that this calibrated model could accurately be used to simulate transdermal patches with other drug doses. We showed that inverse modeling is a fast way to build up an accurate mechanistic model for drug delivery. This strategy opens the door to clinically-ready therapy that is tailored to patients.


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