Sensitivity analysis of the pond heating and temperature regulation (PHATR) model

Lamoureux, Jonathan; Tiersch, Terrence R.; Hall, Steven G.

doi:10.1016/j.aquaeng.2005.06.003

Cited by 9 publications

(4 citation statements)

References 6 publications

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“…The sensitivity analysis of energy inputs on crop production is essential because it can reveal what changes in energy inputs cause greater impacts on the output. Furthermore, it is of especial importance for policy-makers to frame suitable policies for improving energy use efficiency (Lamoureux et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Energy flow modeling and sensitivity analysis of inputs for canola production in Iran

Mousavi‐Avval

Rafiee

Jafari

et al. 2011

Journal of Cleaner Production

114

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Section: Introductionmentioning

confidence: 99%

Energy flow modeling and sensitivity analysis of inputs for canola production in Iran

Mousavi‐Avval

Rafiee

Jafari

et al. 2011

Journal of Cleaner Production

114

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“…Wind speed was also negatively correlated with knockdown times. Higher wind speeds are capable of decreasing surface temperatures of both marine (Qu et al, 2012) and freshwater water bodies (Ptak et al, 2019), particularly in smaller pools of water (Lamoureux et al, 2006). Consequently, increased wind speeds may lead to a lower ambient thermal environment, and the correlated reduction in relative thermal tolerances as a result.…”

Section: Discussionmentioning

confidence: 99%

Anticipating change: The impact of simulated seasonal heterogeneity on heat tolerances along a latitudinal cline

Lush,

Sgrò,

Hall

2024

Ecology

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An understanding of thermal limits and variation across geographic regions is central to predicting how any population may respond to global change. Latitudinal clines, in particular, have been used to demonstrate that populations can be locally adapted to their own thermal environment and, as a result, not all populations will be equally impacted by an increase in temperature. But how robust are these signals of thermal adaptation to the other ecological challenges that animals commonly face in the wild? Seasonal changes in population density, food availability, or photoperiod are common ecological challenges that could disrupt patterns of thermal tolerance along a cline if each population differentially used these signals to anticipate future temperatures and adjust their thermal tolerances accordingly. In this study, we aimed to test the robustness of a cline in thermal tolerance to simulated signals of seasonal heterogeneity. Experimental animals were derived from clones of the Australian water flea, Daphnia carinata, sampled from nine distinct populations along a latitudinal transect in Eastern Australia. We then factorially combined summer (18 h light, 6 h dark) and winter (6 h light, 18 h dark) photoperiods with high (5 million algal cells individual−1 day−1) and low (1 million algal cells individual−1 day−1) food availabilities, before performing static heat shock assays to measure thermal tolerance. We found that the thermal tolerances of the clonal populations were sensitive to both measures of seasonal change. In general, higher food availability led to an increase in thermal tolerances, with the magnitude of the increase varying by clone. In contrast, a switch in photoperiod led to rank‐order changes in thermal tolerances, with heat resistance increasing for some clones, and decreasing for others. Heat resistance, however, still declined with increasing latitude, irrespective of the manipulation of seasonal signals, with clones from northern populations always showing greater thermal resistance, most likely driven by adaptation to winter thermal conditions. While photoperiod and food availability can clearly shape thermal tolerances for specific populations, they are unlikely to overwhelm overarching signals of thermal adaptation, and thus, observed clines in heat resistance will likely have remained robust to these forms of seasonal heterogeneity.

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“…Nagai (2002) per formed SA of a new atmo sphere-soil-veg e ta tion model set ting on sur face fluxes. Lamoureux et al (2006) used SA to iden tify which fac tors had a greater ef fect on pond tem per a ture. These ef fec tive ap pli ca tions of SA sparked our in ter est in adopt ing the SA method for our wave model para met ric test in or der to increase the ac cu racy of our model.…”

Section: Introductionmentioning

confidence: 99%

Parametric Sensitivity Analysis of the WAVEWATCH III Model

Lee¹,

Yang²,

Chuang³

et al. 2009

Terr. Atmos. Ocean. Sci.

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AB STRACTThe pa ram e ters in nu mer i cal wave mod els need to be cal i brated be fore a model can be ap plied to a spe cific re gion. In this study, we se lected the 8 most im por tant pa ram e ters from the source term of the WAVEWATCH III model and sub jected them to sen si tiv ity anal y sis to eval u ate the sen si tiv ity of the WAVEWATCH III model to the se lected pa ram e ters to de ter mine how many of these pa ram e ters should be con sid ered for fur ther dis cus sion, and to jus tify the sig nif i cance pri or ity of each pa ram e ter. Af ter rank ing each pa ram e ter by sen si tiv ity and as sess ing their cu mu la tive im pact, we adopted the ARS method to search for the op ti mal val ues of those pa ram e ters to which the WAVEWATCH III model is most sen si tive by com par ing mod el ing re sults with ob served data at two data buoys off the coast of north east ern Tai wan; the goal be ing to find op ti mal pa ram e ter val ues for im proved mod el ing of wave de vel op ment. The pro ce dure adopt ing op ti mal pa ram e ters in wave sim u la tions did im prove the accuracy of the WAVEWATCH III model in comparison to default runs based on field observations at two buoys. Ocean. Sci., 20, 425-432, doi: 10.3319/TAO.2008.04.25.01(Oc) IN TRO DUC TIONFor sev eral de cades, nu mer i cal wave mod els have been an in te gral part of weather pre dic tion at weather fore cast cen ters around the world. Ma jor me te o ro log i cal agen cies now rely on so-called third-gen er a tion wave mod els such as WAM or WAVEWATCH III (WW3). In these mod els, all phys i cal pro cesses de scrib ing wave growth and de cay are parameterized ex plic itly. There fore, there are many em pir ical or tun ing pa ram e ters in the for mu las of mod els, and the set ting of these pa ram e ters greatly in flu ences the re sults of model sim u la tion. Con se quently, it is im por tant to first deter mine the most in flu en tial pa ram e ters and then find their optimal values so as to improve model outcomes.Sen si tiv ity anal y sis (SA) (Saltelli et al. 2000) was created to deal sim ply with un cer tain ties in model pa ram e ters. Since its de vel op ment, SA has been used widely in many fields. Gu and Li (2002) adopted SA to eval u ate river temper a ture vari a tions in re sponse to changes in hy drau lic and me te o ro log i cal con di tions. Vachaud and Chen (2002) analyzed a large-scale hydrologic mod el ing prob lem us ing sensitivity the ory. Nagai (2002) per formed SA of a new atmo sphere-soil-veg e ta tion model set ting on sur face fluxes. Lamoureux et al. (2006) used SA to iden tify which fac tors had a greater ef fect on pond tem per a ture. These ef fec tive ap pli ca tions of SA sparked our in ter est in adopt ing the SA method for our wave model para met ric test in or der to increase the ac cu racy of our model.In this pa per, we first an a lyze the WW3 to de ter mine which of the model's many pa ram e ters most in flu ence the model. We then con duct sen si tiv ity anal y sis on these parameters to rank th...

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Sensitivity analysis of the pond heating and temperature regulation (PHATR) model

Cited by 9 publications

References 6 publications

Energy flow modeling and sensitivity analysis of inputs for canola production in Iran

Energy flow modeling and sensitivity analysis of inputs for canola production in Iran

Anticipating change: The impact of simulated seasonal heterogeneity on heat tolerances along a latitudinal cline

Parametric Sensitivity Analysis of the WAVEWATCH III Model

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