Range Of Plausible Parameter Values Research Articles

Bayesian History Matching Applied to the Calibration of a Gravity Wave Parameterization

AbstractBreaking atmospheric gravity waves (GWs) in the tropical stratosphere are essential in driving the roughly 2‐year oscillation of zonal winds in this region known as the Quasi‐Biennial Oscillation (QBO). As Global Climate Models (GCM)s are not typically able to directly resolve the spectrum of waves required to drive the QBO, parameterizations are necessary. Such parameterizations often require knowledge of poorly constrained physical parameters. In the case of the spectral gravity parameterization used in this work, these parameters are the total equatorial GW stress and the half width of phase speed distribution. Radiosonde observations are used to obtain the period and amplitude of the QBO, which are compared against values obtained from a GCM. We utilize two established calibration techniques to obtain estimates of the range of plausible parameter values: History matching & Ensemble Kalman Inversion (EKI). History matching is found to reduce the size of the initial range of plausible parameters by a factor of 98%, requiring only 60 model integrations. EKI cannot natively provide any uncertainty quantification but is able to produce a single best estimate of the calibrated values in 25 integrations. When directly comparing the approaches using the Calibrate, Emulate, Sample method to produce a posterior estimate from EKI, history matching produces more compact posteriors with fewer model integrations at lower ensemble sizes compared to EKI; however, these differences become less apparent at higher ensemble sizes.

Dynamics of a two-group model for assessing the impacts of pre-exposure prophylaxis, testing and risk behaviour change on the spread and control of HIV/AIDS in an MSM population

Although much progress has been made in reducing the public health burden of the human immunodeficiency virus (HIV), which causes acquired immunodeficiency syndrome (AIDS), since its emergence in the 1980s (largely due to the large-scale use and availability of potent antiviral therapy, improved diagnostic and intervention and mitigation measures), HIV remains an important public health challenge globally, including in the United States. This study is based on the use of mathematical modeling approaches to assess the population-level impact of pre-exposure prophylaxis (PrEP), voluntary testing (to detect undetected HIV-infected individuals), and changes in human behavior (with respect to risk structure), on the spread and control of HIV/AIDS in an MSM (men-who-have sex-with-men) population. Specifically, a novel two-group mathematical model, which stratifies the total MSM population based on risk (low or high) of acquisition of HIV infection, is formulated. The model undergoes a PrEP-induced backward bifurcation when the control reproduction number of the model is less than one if the efficacy of PrEP to prevent a high-risk susceptible MSM individual from acquiring HIV infection is not perfect (the consequence of which is that, while necessary, having the reproduction number of the model less than one is no longer sufficient for the elimination of the disease in the MSM population). For the case where the efficacy of PrEP is perfect, this study shows that the disease-free equilibrium of the two-group model is globally-asymptotically stable when the associated control reproduction number of the model is less than one. Global sensitivity analysis was carried out to identify the main parameters of the model that have the highest influence on the value of the control reproduction number of the model (thereby, having the highest influence on the disease burden in the MSM population). Numerical simulations of the model, using a plausible range of parameter values, show that if half of the MSM population considered adhere strictly to the specified PrEP regimen (while other interventions are maintained at their baseline values), a reduction of about 22% of the new yearly HIV cases recorded at the peak of the disease could be averted (compared to the worst-case scenario where PrEP-based intervention is not implemented in the MSM population). The yearly reduction at the peak increases to about 50% if the PrEP coverage in the MSM population increases to 80%. This study showed, based on the parameter values used in the simulations, that the prospects of elimination of HIV/AIDS in the MSM community are promising if high-risk susceptible individuals are no more than 15% more likely to acquire HIV infection, in comparison to their low-risk counterparts. Furthermore, these prospects are significantly improved if undetected HIV-infected individuals are detected within an optimal period of time.

High uncertainty in fish bioenergetics impedes precision of fish-mediated carbon transport estimates into the ocean’s twilight zone

Mesopelagic fishes may contribute substantially to marine carbon transport by consuming organic carbon near the surface at night and releasing it in the mesopelagic zone during the day. However, the magnitude and uncertainties associated with this transport are not well understood; fish-mediated carbon flux estimates range from less than 1 % to greater than 30 % of biologically-driven carbon export out of the epipelagic zone. While total mesopelagic fish biomass is an important source of uncertainty, information on fish bioenergetics and movement might also limit the precision of carbon transport estimates. Here, we ask how uncertainties in fish bioenergetics and behaviors affect carbon flux estimation, and which processes contribute most to uncertainty. We used sensitivity analyses to reveal that modeled carbon flux was most sensitive to respiration-related parameters, and per capita fish carbon flux estimates varied six-fold over the range of plausible parameter values. Biomass estimation can add at least ten-fold variation in ecosystem-scale carbon flux estimates. We conclude that it is not currently possible to estimate fish-mediated carbon flux precisely, but estimates may be constrained through future empirical work on the most influential parameters.

Time-lagged effects of habitat fragmentation on terrestrial mammals in Madagascar.

Biodiversity is severely threatened by habitat destruction. As a consequence of habitat destruction, the remaining habitat becomes more fragmented. This results in time-lagged population extirpations in remaining fragments when these are too small to support populations in the long term. If these time-lagged effects are ignored, the long-term impacts of habitat loss and fragmentation will be underestimated. We quantified the magnitude of time-lagged effects of habitat fragmentation for 157 nonvolant terrestrial mammal species in Madagascar, one of the biodiversity hotspots with the highest rates of habitat loss and fragmentation. We refined species' geographic ranges based on habitat preferences and elevation limits and then estimated which habitat fragments were too small to support a population for at least 100 years given stochastic population fluctuations. We also evaluated whether time-lagged effects would change the threat status of species according to the International Union for the Conservation of Nature (IUCN) Red List assessment framework. We used allometric relationships to obtain the population parameters required to simulate the population dynamics of each species, and we quantified the consequences of uncertainty in these parameter estimates by repeating the analyses with a range of plausible parameter values. Based on the median outcomes, we found that for 34 species (22% of the 157 species) at least 10% of their current habitat contained unviable populations. Eight species (5%) had a higher threat status when accounting for time-lagged effects. Based on 0.95-quantile values, following a precautionary principle, for 108 species (69%) at least 10% of their habitat contained unviable populations, and 51 species (32%) had a higher threat status. Our results highlight the need to preserve continuous habitat and improve connectivity between habitat fragments. Moreover, our findings may help to identify species for which time-lagged effects are most severe and which may thus benefit the most from conservation actions.

The epidemiological impact of the Canadian COVID Alert app

ObjectivesWe analyzed the effectiveness of the Canadian COVID Alert app on reducing COVID-19 infections and deaths due to the COVID-19 virus.MethodsTwo separate but complementary approaches were taken. First, we undertook a comparative study to assess how the adoption and usage of the COVID Alert app compared to those of similar apps deployed in other regions. Next, we used data from the COVID Alert server and a range of plausible parameter values to estimate the numbers of infections and deaths averted in Canada using a model that combines information on number of notifications, secondary attack rate, expected fraction of transmissions that could be prevented, quarantine effectiveness, and expected size of the full transmission chain in the absence of exposure notification.ResultsThe comparative analysis revealed that the COVID Alert app had among the lowest adoption levels among apps that reported usage. Our model indicates that use of the COVID Alert app averted between 6284 and 10,894 infections across the six Canadian provinces where app usage was highest during the March–July 2021 period. This range is equivalent to 1.6–2.9% of the total recorded infections across Canada in that time. Using province-specific case fatality rates, 57–101 deaths were averted during the same period. The number of cases and deaths averted was greatest in Ontario, whereas the proportion of cases and deaths averted was greatest in Newfoundland and Labrador. App impact measures were reported so rarely and so inconsistently by other regions that the relative assessment of impact is inconclusive.ConclusionWhile the nationwide rates are low, provinces with widespread adoption of the app showed high ratios of averted cases and deaths (upper bound was greater than 60% of averted cases). This finding suggests that the COVID Alert app, when adopted at sufficient levels, can be an effective public health tool for combatting a pandemic such as COVID-19.

Optimal experimental designs for ordinal models with mixed factors for industrial and healthcare applications

Models with ordinal outcomes are an important part of generalized linear models and design issues for them are less studied, especially when the model has discrete and continuous factors. We propose an effective and flexible Particle Swarm Optimization (PSO) algorithm for finding locally D-optimal approximate designs for experiments with ordinal outcomes modeled using the cumulative logit link. We apply our technique to obtain a locally D-optimal approximate design for an odor removal experiment with both discrete and continuous factors and show that this design is superior to the design obtained by discretizing the continuous factor. Additionally, we find a pseudo-Bayesian D-optimal approximate design for this problem and study the performance of both designs under a range of plausible parameter values. We also (i) demonstrate PSO’s versatility by finding locally D-optimal approximate designs for a manufacturing example with surface defects and multiple continuous factors, and (ii) use PSO to find other optimal designs for estimating percentiles in a dose-response study.

Mechanistic models can reveal infection pathways from prevalence data: the mysterious case of polar bears Ursus maritimus and Trichinella nativa

Parasites exhibit a diverse range of life history strategies. Transmission to a host is a key component of each life cycle but the difficulty of observing host–parasite contacts has often led to confusion surrounding transmission pathways. Given limited data on most host–parasite systems, flexible approaches are needed for disentangling the obscure transmission dynamics of these systems. Here, we develop a modelling framework for formally testing long‐standing hypotheses regarding how the parasitic nematode Trichinella nativa is maintained at high prevalences in polar bear populations. We evaluated transmission from marine prey, from scavenging terrestrial carrion, from cannibalism and from scavenging on dead infected bears as possible pathways, and assessed their respective importance by comparing model‐projected prevalences for each mechanism against observed total and age‐specific population prevalences in the Southern Beaufort Sea polar bear subpopulation. Cannibalism and the scavenging on conspecifics have previously been assumed to be critical transmission pathways, but despite data scarcity, our model exposes these mechanisms as ineffective across a wide range of plausible parameter values. Instead, our analyses suggest that transmission from the consumption of infected marine prey, and in particular seals, can explain observed prevalence levels by itself, with other transmission pathways likely playing varying small contributing roles. Furthermore, our model suggests that transmission declines with bear age, perhaps due to age‐dependent changes in diet or immunity. By formalising multiple transmission mechanisms in a unified, mathematical framework, we distilled several hypotheses to a likely main mode of T. nativa transmission to polar bears. The specifics of our model are tailored towards the T. nativa‐polar bear system, but the approach is easily generalized; it provides a powerful, quantitative means for ecologists to explore competing hypothesis for parasite transmission and other difficult‐to‐observe animal interactions even in data‐poor systems.

FMRI in Non-human Primate: A Review on Factors That Can Affect Interpretation and Dynamic Causal Modeling Application.

Dynamic causal modeling (DCM)—a framework for inferring hidden neuronal states from brain activity measurements (e. g., fMRI) and their context-dependent modulation—was developed for human neuroimaging, and has not been optimized for non-human primate (NHP) studies, which are usually done under anesthesia. Animal neuroimaging studies offer the potential to improve effective connectivity modeling using DCM through combining functional imaging with invasive procedures such as in vivo optogenetic or electrical stimulation. Employing a Bayesian approach, model parameters are estimated based on prior knowledge of conditions that might be related to neural and BOLD dynamics (e.g., requires empirical knowledge about the range of plausible parameter values). As such, we address the following questions in this review: What factors need to be considered when applying DCM to NHP data? What differences in functional networks, cerebrovascular architecture and physiology exist between human and NHPs that are relevant for DCM application? How do anesthetics affect vascular physiology, BOLD contrast, and neural dynamics—particularly, effective communication within, and between networks? Considering the factors that are relevant for DCM application to NHP neuroimaging, we propose a strategy for modeling effective connectivity under anesthesia using an integrated physiologic-stochastic DCM (IPS-DCM).

Surface Flux Equilibrium Theory Explains an Empirical Estimate of Water‐Limited Daily Evapotranspiration

AbstractEvapotranspiration (ET) plays a central role in the water, energy, and carbon cycles but is difficult to model and estimate due to its dependence on the heterogeneous land surface. Recent studies suggest that standard weather station atmospheric observations alone may be sufficient to estimate ET. This is surprising since ET over land is often strongly constrained by the land surface, for instance, by water limitation. While these studies have been empirically successful, a physical explanation for why this is possible has been lacking. Here, we provide a physical explanation for why one of these approaches—the ET from Relative Humidity at Equilibrium (ETRHEQ) method—works, using a simple model of a steady‐state idealized atmospheric boundary layer. We show that, across a wide range of plausible parameter values, this model reproduces ETRHEQ, suggesting that it contains the essential physics that lead to ETRHEQ. We derive a closed‐form expression for ETRHEQ at steady state and use it to show that ETRHEQ can be explained in terms of the near‐surface relative humidity (RH) budget of the idealized model: in particular, it is equivalent to assuming a balance between surface moistening and heating terms in the RH budget. Negative feedbacks between surface fluxes (constrained by the surface energy budget) and atmospheric temperature and humidity mean that these terms typically balance, explaining the empirical success of ETRHEQ over a wide range of conditions. We define this state—in which the moistening and heating terms balance in the RH budget—as “surface flux equilibrium.”

Decomposing the growth of the high-skilled wage premium in an advanced economy open to trade

We use a double-calibrated general equilibrium model to decompose the growth of the high-skilled wage premium in the UK from 1979 to 2000 into a range of potential contributory factors. This structural approach ensures that the model used is consistent with both price and quantity data simultaneously, and allows us to investigate a wide range of plausible parameter values. We find that the small observed rise in the skill premium is the net outcome of a set of opposing effects, some of which are large. In particular, the negative effect on the skill premium from the rising supply of skilled labour is mostly offset by the factor bias of technical change in favour of skilled labour. To this extent our work supports previous labour-market based studies, but is novel in showing that these are consistent with trade price and volume changes in a general equilibrium framework. If we assume a production technology dominated by capital-skill complementarity, the fall in capital prices (positive effect on the skill premium) and the sector bias of technical change in favour of unskilled-labour-intensive sectors (negative effect) also become quantitatively important. The impact of international trade and consumer preferences on the skill premium is mostly positive, and while not large compared to the role of factor bias, it is still significant as a proportion of to the net change in the wage premium. We conclude that a structural model such as ours provides robust insights into the processes that drive the skill premium. At the same time, while we treat the rise in the supply of skilled labour as exogenous, future research might usefully aim to endogenize skill acquisition decisions and labour market policies with a more fully dynamic modelling technique.

Dynamic Hydraulic Conductivity Reconciles Mismatch Between Modeled and Observed Winter Subglacial Water Pressure

The link between subglacial hydrology and basal sliding has prompted work on basal hydrology models with water pressure and drainage capacity as prognostic variables. We find that the Glacier Drainage System model, which belongs to a commonly used family of subglacial hydrology models that include both channelized and distributed drainage components, underpredicts winter water pressure when compared to borehole observations from western Greenland given a wide range of plausible parameter values and inputs. This problem, though previously noted by other modelers, has not been addressed. Possible causes for the discrepancy including idealized model inputs or unconstrained parameters are investigated through a series of modeling experiments on both synthetic and realistic ice sheet geometries. Numerical experiments reveal that englacial storage and hydraulic conductivity in the distributed system are the primary controls on winter water pressure in Glacier Drainage System model. Observations of temperate layer thickness and englacial water content from western Greenland imply an upper bound on englacial storage, suggesting that a reduction in hydraulic conductivity is the most plausible cause of high winter water pressure. We conclude that hydraulic conductivity acts as a proxy for the subgrid‐scale connectivity of the linked cavity system and should therefore change seasonally in correspondence with melt water availability.

The Relative Contribution of Direct and Environmental Transmission Routes in Stochastic Avian Flu Epidemic Recurrence: An Approximate Analysis.

We present an analysis of an avian flu model that yields insight into the roles of different transmission routes in the recurrence of avian influenza epidemics. Recent modelling work suggests that the outbreak periodicity of the disease is mainly determined by the environmental transmission rate. This conclusion, however, is based on a modelling study that only considers a weak between-host transmission rate. We develop an approximate model for stochastic avian flu epidemics, which allows us to determine the relative contribution of environmental and direct transmission routes to the periodicity and intensity of outbreaks over the full range of plausible parameter values for transmission. Our approximate model reveals that epidemic recurrence is chiefly governed by the product of a rotation and a slowly varying standard Ornstein-Uhlenbeck process (i.e. mean-reverting process). The intrinsic frequency of the damped deterministic version of the system predicts the dominant period of outbreaks. We show that the typical periodicity of major avian flu outbreaks can be explained in terms of either or both types of transmission and that the typical amplitude of epidemics is highly sensitive to the direct transmission rate.

Emissions leakage, environmental policy and trade frictions

We develop a two-good general equilibrium model of a small open economy to decompose the effect of a country's unilateral strengthening of environmental policy on pollution emissions in the rest of the world, known as emissions leakage. We show analytically and numerically that the level of emissions leakage depends on the level of trade friction in the service sector. In the model, production in the manufacturing sector is associated with pollution emissions, and production in the service sector is clean. In a special case with free trade in manufacturing and no trade in services, no leakage occurs. Allowing for trade in services, we solve for the relationship between trade frictions in the service sector and leakage. At lower levels of service sector's trade friction, leakage from a small strengthening of environmental regulation decreases (increases) if services are imported (exported). Finally, we simulate the model, calibrating the to the Canadian economy to compare these effects’ relative sizes over a range of plausible parameter values. Leakage is about 18% lower when using trade friction levels estimated from the literature rather than assuming no trade friction in services.

Managerial Risk Aversion and Accounting Conservatism

This paper investigates the delegation of financial reporting policy to a manager as a shareholder commitment device to achieve an ex-ante preferred level of conservatism. It especially explores how managerial traits – specifically the level of risk aversion and overconfidence – facilitate efficient implementation of the preferred level of conservatism. The potential benefit of a conservative reporting policy has been demonstrated in the literature, but if firms have some freedom to set the level of conservatism and it is not perfectly observable, the enforcement of a commitment to conservative reporting could be a concern (firms may claim to be conservative while in fact being aggressive). Therefore, the delegation of the reporting policy and the design of an appropriate incentive scheme could be a possible commitment device. We present a model in which to obtain better funding terms, a firm has an ex-ante preference for a given level of conservatism. Hiring a more risk-averse manager lowers the cost of implementing a conservative reporting policy, but increases the agency cost linked to the productive effort. We show that, for a plausible range of parameter values, the optimal level of managerial risk aversion which minimizes the overall agency cost is increasing with respect to the level of conservatism the firm wants to induce. Similar results hold for the degree of overconfidence – in the opposite direction: the optimal level of overconfidence is decreasing with respect to the desired level of conservatism. These results suggest an alternative explanation for recent empirical evidence linking CEO and CFO characteristics to the level of conservatism: firms deliberately choose managers with specific personality traits for efficient implementation of shareholders’ ex-ante preferred level of conservatism.

Rising Inequality, Demand, and Growth in the US Economy

We use consumption and balance sheet data disaggregated between the top 5% and the bottom 95% of US households by income to show that the bottom 95% went deeply into debt to mitigate the impact of their stagnant incomes on their consumption. We use micro data to calibrate an intrinsic Keynesian growth model and show that over a range of plausible parameter values, the rise in US household income inequality increased enough between the early 1980s and 2000s to cause the entire magnitude of the Great Recession and can explain the slow and prolonged recovery.

Trading green backs for green crabs: evaluating the commercial shellfish harvest at risk from European green crab invasion

Nonnative species pose a threat to native biodiversity and can have immense impacts on biological communities, altering the function of ecosystems. How much value is at risk from high-impact invasive species, and which parameters determine variation in that value, constitutes critical knowledge for directing both management and research, but it is rarely available. We evaluated the value of the commercial shellfish harvest that is at risk in nearshore ecosystems of Puget Sound, Washington State, USA, from the invasive European green crab,Carcinus maenas. We assessed this value using a simple static ecological model combined with an economic model using data from Puget Sound’s shellfish harvest and revenue and the relationship betweenC. maenasabundance and the consumption rate of shellfish. The model incorporates a range inC. maenasdiet preference, calories consumed per year, and crab densities.C. maenasis likely to prey on commercially harvested hardshell clams, oysters, and mussels, which would likely reduce additional revenue from processing and distribution, and the number of jobs associated with these fisheries.The model results suggest possible revenue losses of these shellfish ranging from $1.03-23.8 million USD year-1(2.8-64% losses), with additional processing and distribution losses up to $17.6 million USD and 442 job positions each year associated with a range of plausible parameter values. The broad range of values reflects the uncertainty in key factors underlying impacts, factors that are highly variable across invaded regions and so not knowablea priori. However, future research evaluating species invasions can reduce the uncertainty of impacts by characterizing several key parameters: density of individuals, number of arrivals, predation and competition interactions, and economic impacts. This study therefore provides direction for research to inform more accurate estimates of value-at-risk, and suggests substantial motivation for strong measures to prevent, monitor, and manage the possible invasion ofC. maenas.

Global warming and the evaluation of fuel substitution strategies: on why policy should be left to the politicians

It is often taken for granted that substituting natural gas for oil will serve to reduce the greenhouse emissions of the energy sector, and executing such substitution is thus seen as a coherent policy response to the problem of global warming. In this paper we argue that such a policy is ill–founded because the supposition on which it rests is based on an incomplete consideration of the comparative pollution characteristics of the two fuels. The consideration is incomplete in two senses: (i) authors focus on emissions of carbon dioxide to the virtual exclusion of the secondary greenhouse gases, and (ii) attention is paid only to those emissions which result from fuel combustion, rather than to emissions from the entire fuel cycle (including extraction, distribution and storage). In this paper we adopt a simple, empirical 'emissions–accounting' framework [28]. Using a range of plausible parameter values it is demonstrated that the 'greenhouse friendliness' ranking of natural gas and oil is highly ambiguous. We cite very recent engineering estimates of methane leakage associated with commercial natural gas distribution and go on to demonstrate that natural gas usage may result in the emission of more greenhouse gases than oil usage. The ambiguity in the ranking is driven by two major uncertainties, one technological and one political. The most significant implication is that the resolution of the technical uncertainty surrounding the greenhouse effect and man's impact upon global climate will not be sufficient to determine what constitutes an effective policy response. The determination of policy will be an essentially political problem. Policy formulation and determination should, as the title suggests, be left to the politicians.

Long-run investment under uncertain demand

In the literature investigating the impact of uncertainty on short-run and long-run investment, most authors have used a log linear profit function. This functional form has been generally considered a reasonable approximation for a more general one and has the advantage of providing closed form solutions for both short-run investment rule and long-run rate of capital accumulation. In this paper, we consider the profit function for the case of a monopolistic firm facing a linear demand function with additive shocks. Under this assumption, analytical solutions, for both short-run investment rule and long-run rate of capital accumulation, are not available. We then 1) propose an analytical approximation of the short-run investment rule and 2) show how such approximation can be used in order to derive the corresponding i) steady-state distribution of the optimal stock of capital and ii) the long-run average rate of capital accumulation. Finally, we compare the long-run rates of capital accumulation calculated under both profit function specifications. We find that, within a plausible range of parameter values, the two rates are significantly different. Hence, we conclude that the choice of a log linear functional form has a non-trivial impact on the magnitude of the long run rate of capital accumulation.

Trading green backs for green crabs: evaluating the commercial shellfish harvest at risk to European green crab invasion.

Nonnative species pose a threat to native biodiversity and can have immense impacts on biological communities, altering the function of ecosystems. How much value is at risk from high-impact invasive species, and which parameters determine variation in that value, constitutes critical knowledge for directing both management and research, but it is rarely available. We evaluated the value of the commercial shellfish harvest that is at risk in nearshore ecosystems of Puget Sound, Washington State, USA, from the invasive European green crab, Carcinus maenas. We assessed this value using a simple static ecological model combined with an economic model using data from Puget Sound's shellfish harvest and revenue and the relationship between C. maenas abundance and the consumption rate of shellfish. The model incorporates a range in C. maenas diet preference, calories consumed per year, and crab densities. C. maenas is likely to prey on commercially harvested hardshell clams, oysters, and mussels, which would likely reduce additional revenue from processing and distribution, and the number of jobs associated with these fisheries. The model results suggest possible revenue losses of these shellfish ranging from $1.03-23.8 million USD (2.8-64% losses), with additional processing and distrubution losses up to $17.6 million USD and 442 job positions each year associated with a range of plausible parameter values. The broad range of values reflects the uncertainty in key factors underlying impacts, factors that are highly variable across invaded regions and so not knowable a priori. However, future research evaluating species invasions can reduce the uncertainty of impacts by characterizing several key parameters: density of individuals, number of arrivals, predation and competition interactions, and economic impacts. This study therefore provides direction for research to inform more accurate estimates of value-at-risk, and suggests substantial motivation for strong measures to prevent, monitor, and manage the possible invasion of C. maenas.

Trading green backs for green crabs: evaluating the commercial shellfish harvest at risk from European green crab invasion

Nonnative species pose a threat to native biodiversity and can have immense impacts on biological communities, altering the function of ecosystems. How much value is at risk from high-impact invasive species, and which parameters determine variation in that value, constitutes critical knowledge for directing both management and research, but it is rarely available. We evaluated the value of the commercial shellfish harvest that is at risk in nearshore ecosystems of Puget Sound, Washington State, USA, from the invasive European green crab, Carcinus maenas. We assessed this value using a simple static ecological model combined with an economic model using data from Puget Sound’s shellfish harvest and revenue and the relationship between C. maenas abundance and the consumption rate of shellfish. The model incorporates a range in C. maenas diet preference, calories consumed per year, and crab densities. C. maenas is likely to prey on commercially harvested hardshell clams, oysters, and mussels, which would likely reduce additional revenue from processing and distribution, and the number of jobs associated with these fisheries.The model results suggest possible revenue losses of these shellfish ranging from $1.03-23.8 million USD year -1 (2.8-64% losses), with additional processing and distribution losses up to $17.6 million USD and 442 job positions each year associated with a range of plausible parameter values. The broad range of values reflects the uncertainty in key factors underlying impacts, factors that are highly variable across invaded regions and so not knowable a priori. However, future research evaluating species invasions can reduce the uncertainty of impacts by characterizing several key parameters: density of individuals, number of arrivals, predation and competition interactions, and economic impacts. This study therefore provides direction for research to inform more accurate estimates of value-at-risk, and suggests substantial motivation for strong measures to prevent, monitor, and manage the possible invasion of C. maenas.