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Lake sturgeon (Acipenser fulvescens) exhibit a complex life-history strategy where behaviour, including habitat selection, depends on ontogenetic stage. Protection or recovery efforts for one stage may not impact other stages. Stage-structured models have been used to explore the sensitivity of the population to changes in vital rates of individual stages. Recent research demonstrates that juvenile mortality may be lower than estimated in prior modelling efforts and density-dependent. We constructed a Lefkovitch matrix model to reflect an updated understanding of the prerecruitment stages of the lake sturgeon. We then compared the model to a population of lake sturgeon on the Ontario--Minnesota border. Our model predicts that population growth rate, time to equilibrium, and final population size were most sensitive to changes to the survival of early adults, followed by subadults and juveniles. Sensitivity to changes in age-0 survival was very low in contrast to earlier modelling efforts, while sensitivities to juvenile (ages 1-7 years) and subadult (ages 8-23 years) were higher than previously reported values. Key words: population structure, statistical analysis, matrix models, lake sturgeon, protected species Les esturgeons jaunes (Acipenserfulvescens) emploient une strategie de cycle biologique complexe dans laquelle les comportements, dont la selection d'habitats, dependent de l'etape de l'ontogenese. Les efforts de protection ou de retablissement pour une etape pourraient ne pas avoir d'incidence sur les autres etapes. Des modeles structures selon l'etape ont ete utilises pour explorer la sensibilite de la population a des variations de taux vitaux de differentes etapes. Des travaux recents demontrent que la mortalite des juveniles pourrait etre plus faible que les estimations issues d'efforts de modelisation passes et pourrait dependre de la densite. Nous avons construit un modele matriciel de Lefkovitch refletant une comprehension a jour des etapes pre-recrutement du cycle de vie de l'esturgeon jaune. Nous avons ensuite compare le modele a une population d'esturgeons jaunes chevauchant la frontiere de l'Ontario et du Minnesota. Notre modele predit que le taux de croissance de la population, le temps pour atteindre l'equilibre et la taille finale de la population sont les variables les plus sensibles aux variations de la survie des adultes precoces, suivis des subadultes et des juveniles. La sensibilite aux variations de la survie d'individus de moins d'un an est tres faible comparativement aux resultats d'efforts de modelisation anterieurs, alors que les sensibilites des juveniles (1-7 ans) et des subadultes (8-23 ans) sont plus elevees que les valeurs rapportees precedemment. [Traduit par la Redaction] Mots-cles : structure de la population, analyse statistique, modeles matriciels, esturgeon jaune, espece protegee, Introduction Restoring populations of lake sturgeon (Acipenser fulvescens) requires habitat protection and restoration across the species' North American range. Mathematical models are often employed in estimating recovery potential and determining [...]

In this paper, we propose unbiased sensitivity estimators of the expected functional of one-dimensional diffusion processes. Under general diffusion models, it is common to rely on discretization methods such as the Euler scheme for the generation of sample paths because of the lack of knowledge in the probability distributions associated with the diffusions. The Euler discretization method is easy to apply, but it is difficult to avoid discretization biases. As an alternative approach, we propose unbiased Monte Carlo estimators of sensitivities by taking advantage of the Beskos-Roberts method, which is an exact simulation algorithm for one-dimensional stochastic differential equations (SDEs), and applying the Poisson kernel method. The proposed estimators can be computed by discretely observed Brownian paths, and thus it is simple to implement our algorithms. We illustrate the ideas and algorithms with examples. Funding: This work was supported by the National Research Foundation of Korea (NRF) funded by the Korea government (MEST) [Grant NRF-2017R1A2B4011546]. Keywords: unbiased estimator * sensitivity estimation * derivative estimation * Greeks * Beskos-Roberts method * Poisson kernel method, 1. Introduction In this paper, we develop a method to estimate sensitivities of expected functionals of processes using Monte Carlo simulation under one-dimensional general diffusion models. The accurate estimation of [...]

BHP plans to enter the bulk fertilizer market by developing its first potash operation, the Jansen Potash Mine, in Saskatchewan, Canada. In conjunction with Amec Foster Wheeler, the Jansen project team developed a model of the Jansen production and logistics chain to understand the drivers of production capacity. The Detailed Integrated Capacity Estimate model (DICE) is a comprehensive discrete-event simulation model of Jansen's upstream production (mining, hoisting, and ore processing) and downstream logistics (rail, port, and marketing). DICE provides an unprecedented combination of complexity, granularity, and scalability, which informs ore storage capacities, product sizing infrastructure, critical-equipment redundancies, bypasses, and operational practices. The team used DICE during the prefeasibility study of the Jansen project. The model provided the justification for the removal of about $300 million in capital expenses to equip the second of two hoisting shafts, the reduction of planned maintenance, and the increase of the degree of mining automation. Throughout the prefeasibility study, Jansen's annual production in stage 1 of operations was estimated to increase by 15-20 percent, with two-thirds of this gain credited to DICE. This potential additional production added $500 million to the net present value of Jansen stage 1. In consideration of this, among other factors, the BHP board of directors approved the transition of the Jansen project from a prefeasibility to a feasibility study. Keywords: models * discrete time * capacity expansion * capital assets * investment * mining * sensitivity analysis * simulation, Introduction BHP, one of the world's largest producers of iron ore, copper, coal, and oil and gas, intends to build a potash business based on a series of large, long-life, [...]

In evaluating opportunities, investors wish to identify key sources of uncertainty. We propose a new way to 'measure how sensitive model outputs are to each probabilistic input (e.g., revenues, growth, [...]

In observational studies, subjects are not randomly assigned to treatment or control, so they may differ in their chances of receiving the treatment. A simple method is developed and demonstrated for displaying the sensitivity of conventional two-group permutation inferences to departures from random assignment of treatments. The unmatched case, discussed here, differs in certain technical and computational details from the matched case, discussed previously; however, the underlying model and the method lor quantifying departures from randomization are the same. The method may be applied to Wilcoxon's rank sum test, the Gehan and log-rank tests for censored outcomes, Mantel's test for scored categories, and Fisher's exact test for binary responses. The method embeds the usual randomization reference distribution in a one-parameter family of departures involving an unobserved covariate that would have been controlled by adjustments had it been observed. As this parameter is varied, the sensitivity of permutational significance levels and confidence intervals is displayed. Brief discussion of an example shows that comparisons vary considerably in their degree of sensitivity to unobserved biases. KEY WORDS: Rank tests; Sensitivity analysis., 1. INTRODUCTION AND NOTATION The use of permutation inferences in randomized experiments is sustained or warranted by the physical act of randomization, which creates the only probability distribution used in [...]