Discussion on "The central role of the identifying assumption in population size estimation" by Serge Aleshin-Guendel, Mauricio Sadinle, and Jon Wakefield.

In this discussion response, we consider some practical implications of the authors' consideration of the no-highest-order interaction (NHOI) model for multiple systems estimation, which permits the authors to derive the explicit (albeit untestable) identifying assumption related to the unobserved (or missing) individuals. In particular, we discuss several aspects, from the standard process of model selection to potential poor predictive performance due to over-fitting and the implications of data reduction. We discuss these aspects in relation to the case study presented by the authors relating to the number of civilian casualties within the Kosovo war, and conduct further preliminary simulations to investigate these issues further. The results suggest that the NHOI models considered, despite having a potentially useful theoretical result in relation to the underlying identifying assumption, may perform poorly in practice.

Latent multinomial models for extended batch-mark data.

Batch marking is common and useful for many capture-recapture studies where individual marks cannot be applied due to various constraints such as timing, cost, or marking difficulty. When batch marks are used, observed data are not individual capture histories but a set of counts including the numbers of individuals first marked, marked individuals that are recaptured, and individuals captured but released without being marked (applicable to some studies) on each capture occasion. Fitting traditional capture-recapture models to such data requires one to identify all possible sets of capture-recapture histories that may lead to the observed data, which is computationally infeasible even for a small number of capture occasions. In this paper, we propose a latent multinomial model to deal with such data, where the observed vector of counts is a non-invertible linear transformation of a latent vector that follows a multinomial distribution depending on model parameters. The latent multinomial model can be fitted efficiently through a saddlepoint approximation based maximum likelihood approach. The model framework is very flexible and can be applied to data collected with different study designs. Simulation studies indicate that reliable estimation results are obtained for all parameters of the proposed model. We apply the model to analysis of golden mantella data collected using batch marks in Central Madagascar.

Avoiding bias in estimates of population size for translocation management.

Mark-recapture surveys are commonly used to monitor translocated populations globally. Data gathered are then used to estimate demographic parameters, such as abundance and survival, using Jolly-Seber (JS) models. However, in translocated populations initial population size is known and failure to account for this may bias parameter estimates, which are important for informing conservation decisions during population establishment. Here, we provide methods to account for known initial population size in JS models by incorporating a separate component likelihood for translocated individuals, using a maximum-likelihood estimation, with models that can be fitted using either R or MATLAB. We use simulated data and a case study of a threatened lizard species with low capture probability to demonstrate that unconstrained JS models may overestimate the size of translocated populations, especially in the early stages of post-release monitoring. Our approach corrects this bias; we use our simulations to demonstrate that overestimates of population size between 78% and 130% can occur in the unconstrained JS models when the detection probability is below 0.3 compared to 1%-8.9% for our constrained model. Our case study did not show an overestimate; however accounting for the initial population size greatly reduced error in all parameter estimates and prevented boundary estimates. Adopting the corrected JS model for translocations will help managers to obtain more robust estimates of the population sizes of translocated animals, better informing future management including reinforcement decisions, and ultimately improving translocation success.

Removal models accounting for temporary emigration.

Removal of protected species from sites scheduled for development is often a legal requirement in order to minimize the loss of biodiversity. The assumption of closure in the classic removal model will be violated if individuals become temporarily undetectable, a phenomenon commonly exhibited by reptiles and amphibians. Temporary emigration can be modeled using a multievent framework with a partial hidden process, where the underlying state process describes the movement pattern of animals between the survey area and an area outside of the study. We present a multievent removal model within a robust design framework which allows for individuals becoming temporarily unavailable for detection. We demonstrate how to investigate parameter redundancy in the model. Results suggest the use of the robust design and certain forms of constraints overcome issues of parameter redundancy. We show which combinations of parameters are estimable when the robust design reduces to a single secondary capture occasion within each primary sampling period. Additionally, we explore the benefit of the robust design on the precision of parameters using simulation. We demonstrate that the use of the robust design is highly recommended when sampling removal data. We apply our model to removal data of common lizards, Zootoca vivipara, and for this application precision of parameter estimates is further improved using an integrated model.

Initiation and duration of selective serotonin reuptake inhibitor prescribing over time: UK cohort study.

BACKGROUND: Recent media reports have focused on the large increase in antidepressants dispensed in England. We investigated this, focusing on selective serotonin reuptake inhibitors (SSRIs). AIMS: To examine the rate of initiation of SSRIs over time and changes over time in the duration of prescribing episodes. METHOD: We estimated initiation and duration of SSRI prescribing from 7 025 802 individuals aged over 18 years and registered with a general practice that contributed data to The Health Improvement Network. RESULTS: Rates of SSRI initiation increased from 1.03 per 100 person-years in 1995 to 2.15 in 2001, but remained stable from then to 2012. The median duration of prescribing episodes increased from 112 to 169 days for episodes starting in 1995 to 2010. CONCLUSIONS: Despite media reports describing an increasing rate of antidepressant prescribing, SSRI initiation rates have stabilised since 2001. However, our results suggest that individuals who take SSRIs are receiving treatment for longer.

Parameter redundancy in discrete state-space and integrated models.

Discrete state-space models are used in ecology to describe the dynamics of wild animal populations, with parameters, such as the probability of survival, being of ecological interest. For a particular parametrization of a model it is not always clear which parameters can be estimated. This inability to estimate all parameters is known as parameter redundancy or a model is described as nonidentifiable. In this paper we develop methods that can be used to detect parameter redundancy in discrete state-space models. An exhaustive summary is a combination of parameters that fully specify a model. To use general methods for detecting parameter redundancy a suitable exhaustive summary is required. This paper proposes two methods for the derivation of an exhaustive summary for discrete state-space models using discrete analogues of methods for continuous state-space models. We also demonstrate that combining multiple data sets, through the use of an integrated population model, may result in a model in which all parameters are estimable, even though models fitted to the separate data sets may be parameter redundant.

Climate anomalies and competition reduce establishment success during island colonization.

Understanding the factors that facilitate or constrain establishment of populations in novel environments is crucial for conservation biology and the study of adaptive radiation. Important questions include: (1) Does the timing of colonization relative to stochastic events, such as climatic perturbations, impact the probability of successful establishment? (2) To what extent does community context (e.g., the presence of competitors) change the probability of establishment? (3) How do sources of intrapopulation variance, such as sex differences, affect success at an individual level during the process of establishment? Answers to these questions are rarely pursued in a field-experimental context or on the same time scales (months to years) as the processes of colonization and establishment. We introduced slender anole lizards (Anolis apletophallus) to eight islands in the Panama Canal and tracked them over multiple generations to investigate the factors that mediate establishment success. All islands were warmer than the mainland (ancestral) environment, and some islands had a native competitor. We transplanted half of these populations only 4 months before the onset of a severe regional drought and the other half 2 years (two generations) before the drought. We found that successful establishment depended on both the intensity of interspecific competition and the timing of colonization relative to the drought. The islands that were colonized shortly before the drought went functionally extinct by the second generation, and regardless of time before the drought, the populations on islands with interspecific competition declined continuously over the study period. Furthermore, the effect of the competitor interacted with sex, with males suffering, and females benefitting, from the presence of a native competitor. Our results reveal that community context and the timing of colonization relative to climactic events can combine to determine establishment success and that these factors can generate opposite effects on males and females.

Multistate mark-recapture model selection using score tests.

Although multistate mark-recapture models are recognized as important, they lack a simple model-selection procedure. This article proposes and evaluates a step-up approach to select appropriate models for multistate mark-recapture data using score tests. Only models supported by the data require fitting, so that over-complicated model structures with too many parameters do not need to be considered. Typically only a small number of models are fitted, and the procedure is also able to identify parameter-redundant and near-redundant models. The good performance of the technique is demonstrated using simulation, and the approach is illustrated on a three-region Canada goose data set. In this case, it identifies a new model that is much simpler than the best model previously considered for this application.

Removal modelling in ecology: A systematic review.

Removal models were proposed over 80 years ago as a tool to estimate unknown population size. More recently, they are used as an effective tool for management actions for the control of non desirable species, or for the evaluation of translocation management actions. Although the models have evolved over time, in essence, the protocol for data collection has remained similar: at each sampling occasion attempts are made to capture and remove individuals from the study area. Within this paper we review the literature of removal modelling and highlight the methodological developments for the analysis of removal data, in order to provide a unified resource for ecologists wishing to implement these approaches. Models for removal data have developed to better accommodate important features of the data and we discuss the shift in the required assumptions for the implementation of the models. The relative simplicity of this type of data and associated models mean that the method remains attractive and we discuss the potential future role of this technique.

A Test of Positive Association for Detecting Heterogeneity in Capture for Capture-Recapture Data.

The Cormack-Jolly-Seber (CJS) model assumes that all marked animals have equal recapture probabilities at each sampling occasion, but heterogeneity in capture often occurs and should be taken into account to avoid biases in parameter estimates. Although diagnostic tests are generally used to detect trap-dependence or transience and assess the overall fit of the model, heterogeneity in capture is not routinely tested for. In order to detect and identify this phenomenon in a CJS framework, we propose a test of positive association between previous and future encounters using Goodman-Kruskal's gamma. This test is based solely on the raw capture histories and makes no assumption on model structure. The development of the test is motivated by a dataset of Sandwich terns (Thalasseus sandvicensis), and we use the test to formally show that they exhibit heterogeneity in capture. We use simulation to assess the performance of the test in the detection of heterogeneity in capture, compared to existing and corrected diagnostic goodness-of-fit tests, Leslie's test of equal catchability and Carothers' extension of the Leslie test. The test of positive association is easy to use and produces good results, demonstrating high power to detect heterogeneity in capture. We recommend using this new test prior to model fitting as the outcome will guide the model-building process and help draw more accurate biological conclusions. Supplementary materials accompanying this paper appear online. ELECTRONIC SUPPLEMENTARY MATERIAL: Supplementary materials for this article are available at 10.1007/s13253-017-0315-4.

A novel application of mark-recapture to examine behaviour associated with the online trade in elephant ivory.

The illegal trade in elephant ivory is driving the unlawful killing of elephants such that populations are now suffering unsustainable reductions. The internet is increasingly being used as a platform to conduct illegal wildlife trade, including elephant ivory. As a globally accessible medium the internet is as highly attractive to those involved in the illegal trade as it is challenging to regulate. Characterising the online illegal wildlife (ivory) trade is complex, yet key to informing enforcement activities. We applied mark-recapture to investigate behaviour associated with the online trade in elephant ivory on eBay UK as a generalist online marketplace. Our results indicate that trade takes place via eBay UK, despite its policy prohibiting this, and that two distinct trading populations exist, characterised by the pattern of their ivory sales. We suggest these may represent a large number of occasional (or non-commercial) sellers and a smaller number of dedicated (or commercial) sellers. Directing resource towards reducing the volume of occasional sales, such as through education, would enable greater focus to be placed upon characterising the extent and value of the illegal, "commercial" online ivory trade. MRC has the potential to characterise the illegal trade in ivory and diverse wildlife commodities traded using various online platforms.

Antiepileptic drugs prescribed in pregnancy and prevalence of major congenital malformations: comparative prevalence studies.

OBJECTIVE: The aim of this study was to examine the prevalence of major congenital malformations associated with antiepileptic drug (AED) treatment in pregnancy. PATIENTS AND METHODS: Using data from The Health Improvement Network, we identified women who have given live birth and their offspring. Four subgroups were selected based on the AED treatment in early pregnancy, valproate, carbamazepine, lamotrigine and women not receiving AED treatment. We compared the prevalence of major congenital malformations within children of these four groups and estimated prevalence ratios (PRs) using Poisson regression adjusted for maternal age, sex of child, quintiles of Townsend deprivation score and indication for treatment. RESULTS: In total, 240,071 women were included in the study. A total of 229 women were prescribed valproate in pregnancy, 357 were prescribed lamotrigine and 334 were prescribed carbamazepine and 239,151 women were not prescribed AEDs. Fifteen out of 229 (6.6%) women prescribed valproate gave birth to a child with a major congenital malformation. The figures for lamotrigine, carbamazepine and women not prescribed AEDs were 2.7%, 3.3% and 2.2%, respectively. The prevalence of major congenital malformation was similar for women prescribed lamotrigine or carbamazepine compared to women with no AED treatment in pregnancy. For women prescribed valproate in polytherapy, the prevalence was fourfold higher. After adjustments, the effect of estimates attenuated, but the prevalence remained two- to threefold higher in women prescribed valproate. CONCLUSION: The results of our study suggest that lamotrigine and carbamazepine are safer treatment options than valproate in pregnancy and should be considered as alternative treatment options for women of childbearing potential and in pregnancy.

Risks associated with antipsychotic treatment in pregnancy: Comparative cohort studies based on electronic health records.

BACKGROUND: Limited information is available on whether antipsychotics prescribed in pregnancy are associated with increased risks of adverse outcomes. METHODS: We used electronic health records from pregnant women and their children to examine risks of adverse maternal and child outcomes in three cohorts of women who: (A) received antipsychotic treatment in pregnancy (n=416) (B) discontinued antipsychotic treatment before pregnancy (n=670), and (C) had no records of antipsychotic treatment before or during pregnancy (n=318,434). Absolute and risk ratios were estimated and adjusted for health and lifestyle and concomitant medications. RESULTS: Caesarean section was more common in cohort A (25%) than C (18%), but non-significant after adjustment for health and lifestyle factors (Risk Ratio (adj.) 1.09 (95% CI: 0.92, 1.30). Proportion of gestational diabetes was similar in cohort A (2.6%) and B (2.7%), but lower in A than B after adjustments (RRadj: 0.43 (0.20, 0.93). Premature birth/low birthweight were more common in cohort A (10%) than B (4.3%) and C (3.9%), A versus B (RRadj: 2.04 (1.13, 3.67), A versus C (RRadj: 1.43 (0.99, 2.05). Major congenital malformations were more common in A (3.4%), than B (2.2%) and C (2%). However no significant difference was observed (A versus B: RRadj: 1.79 (0.72, 4.47) A versus C RRadj: 1.59 (0.84, 3.00)). Risks estimates were similar for women prescribed atypical and typical antipsychotics. CONCLUSIONS: Antipsychotic treatment in pregnancy carries limited risks of adverse pregnancy and birth outcomes once adjustments have been made for health and lifestyle factors.

Risks and benefits of psychotropic medication in pregnancy: cohort studies based on UK electronic primary care health records.

BACKGROUND: Although many women treated with psychotropic medication become pregnant, no psychotropic medication has been licensed for use in pregnancy. This leaves women and their health-care professionals in a treatment dilemma, as they need to balance the health of the woman with that of the unborn child. The aim of this project was to investigate the risks and benefits of psychotropic medication in women treated for psychosis who become pregnant. OBJECTIVE(S): (1) To provide a descriptive account of psychotropic medication prescribed before pregnancy, during pregnancy and up to 15 months after delivery in UK primary care from 1995 to 2012; (2) to identify risk factors predictive of discontinuation and restarting of lithium (multiple manufacturers), anticonvulsant mood stabilisers and antipsychotic medication; (3) to examine the extent to which pregnancy is a determinant for discontinuation of psychotropic medication; (4) to examine prevalence of records suggestive of adverse mental health, deterioration or relapse 18 months before and during pregnancy, and up to 15 months after delivery; and (5) to estimate absolute and relative risks of adverse maternal and child outcomes of psychotropic treatment in pregnancy. DESIGN: Retrospective cohort studies. SETTING: Primary care. PARTICIPANTS: Women treated for psychosis who became pregnant, and their children. INTERVENTIONS: Treatment with antipsychotics, lithium or anticonvulsant mood stabilisers. MAIN OUTCOME MEASURES: Discontinuation and restarting of treatment; worsening of mental health; acute pre-eclampsia/gestational hypertension; gestational diabetes; caesarean section; perinatal death; major congenital malformations; poor birth outcome (low birthweight, preterm birth, small for gestational age, low Apgar score); transient poor birth outcomes (tremor, agitation, breathing and muscle tone problems); and neurodevelopmental and behavioural disorders. DATA SOURCES: Clinical Practice Research Datalink database and The Health Improvement Network primary care database. RESULTS: Prescribing of psychotropic medication was relatively constant before pregnancy, decreased sharply in early pregnancy and peaked after delivery. Antipsychotic and anticonvulsant treatment increased over the study period. The recording of markers of worsening mental health peaked after delivery. Pregnancy was a strong determinant for discontinuation of psychotropic medication. However, between 40% and 76% of women who discontinued psychotropic medication before or in early pregnancy restarted treatment by 15 months after delivery. The risk of major congenital malformations, and neurodevelopmental and behavioural outcomes in valproate (multiple manufacturers) users was twice that in users of other anticonvulsants. The risks of adverse maternal and child outcomes in women who continued antipsychotic use in pregnancy were not greater than in those who discontinued treatment before pregnancy. LIMITATIONS: A few women would have received parts of their care outside primary care, which may not be captured in this analysis. Likewise, the analyses were based on prescribing data, which may differ from usage. CONCLUSIONS: Psychotropic medication is prescribed before, during and after pregnancy. Many women discontinue treatment before or during early pregnancy and then restart again in late pregnancy or after delivery. Our results support previous associations between valproate and adverse child outcomes but we found no evidence of such an association for antipsychotics. FUTURE WORK: Future research should focus on (1) curtailing the use of sodium valproate; (2) estimating the benefits of psychotropic drug use in pregnancy; and (3) investigating the risks associated with lifestyle choices that are more prevalent among women using psychotropic drugs. FUNDING DETAILS: The National Institute for Health Research Health Technology Assessment programme.

Women's perception of risks of adverse fetal pregnancy outcomes: a large-scale multinational survey.

OBJECTIVE: To determine pregnant women and new mothers' perception of risks in pregnancy. DESIGN, SETTINGS AND PARTICIPANTS: This was a large-scale multinational survey including 9113 pregnant women and new mothers from 18 countries in Europe, North America and Australia. MAIN OUTCOMES: Risk perception scores (0-10) for harmful effects to the fetus were derived for: (1) medicines (over-the-counter medicine and prescribed medicine), (2) food substances (eggs and blue veined cheese), (3) herbal substances (ginger and cranberries) (4) alcohol and tobacco, and (5) thalidomide. RESULTS: Overall, 80% (6453/8131) of women perceived the risk of giving birth to a child with a birth defect to be ≤ 5 of 100 births. The women rated cranberries and ginger least harmful (mean risk perception scores 1.1 and 1.5 of 10, respectively) and antidepressants, alcohol, smoking and thalidomide as most harmful (7.6, 8.6, 9.2 and 9.4 out of 10, respectively). The perception varied with age, level of education, pregnancy status, profession and geographical region. Noticeably, 70% had not heard about thalidomide, but of those who had (2692/9113), the risk perception scores were 0.4-0.5 points lower in women below 25 years compared to women aged 26-30 years. CONCLUSIONS: In general, women perceived the risks of giving birth to a child with birth defects low, but there were substantial disparities between women's perceived risks and the actual risks when it comes to over-the-counter agents against nausea and prescribed medication. The study revealed that few women knew of thalidomide, suggesting that the general awareness among women of the teratogenic effects of thalidomide is declining, but it has left a general scepticism about safety of medication in pregnancy. This may have some severe consequences if women are left without medical treatments in pregnancy.

Lithium prescribing during pregnancy: a UK primary care database study.

BACKGROUND: Women taking lithium must decide whether to continue the medication if they conceive or plan to conceive. Little is known about the extent of prescribing of lithium during pregnancy. AIMS: To determine: 1) the prevalence of lithium prescribing during pregnancy and 2) to assess whether pregnancy is associated with discontinuation of lithium. METHOD: First, we identified women receiving any lithium prescriptions before and during pregnancy using The Health Improvement Network (THIN) primary care database. Subsequently, we used a Kaplan-Meier plot to compare time to last prescription in women prescribed lithium continuously three months before pregnancy and a comparison group of non-pregnant women. Finally, we described the characteristics of the women prescribed lithium in pregnancy. RESULTS: Very few women were prescribed lithium during pregnancy; out of 458,761 pregnancies, we identified 47 (0.01%) in which lithium was prescribed after the 6th week of pregnancy (when the pregnancy was likely to be known). In our study of discontinuation, we found pregnant women were more likely to stop lithium than those who were not pregnant. Of the 52 women who were being continuously prescribed lithium three months before pregnancy, only 17 (33%) continued receiving prescriptions beyond the 6th week of pregnancy. However, most of these 17 women continued treatment throughout pregnancy. CONCLUSIONS: Pregnancy was strongly associated with discontinuation of lithium. Further evidence on the risks of lithium is needed so that women can weight these against the risk of a deterioration in maternal mental health.

Does your species have memory? Analyzing capture-recapture data with memory models.

We examine memory models for multisite capture-recapture data. This is an important topic, as animals may exhibit behavior that is more complex than simple first-order Markov movement between sites, when it is necessary to devise and fit appropriate models to data. We consider the Arnason-Schwarz model for multisite capture-recapture data, which incorporates just first-order Markov movement, and also two alternative models that allow for memory, the Brownie model and the Pradel model. We use simulation to compare two alternative tests which may be undertaken to determine whether models for multisite capture-recapture data need to incorporate memory. Increasing the complexity of models runs the risk of introducing parameters that cannot be estimated, irrespective of how much data are collected, a feature which is known as parameter redundancy. Rouan et al. (JABES, 2009, pp 338-355) suggest a constraint that may be applied to overcome parameter redundancy when it is present in multisite memory models. For this case, we apply symbolic methods to derive a simpler constraint, which allows more parameters to be estimated, and give general results not limited to a particular configuration. We also consider the effect sparse data can have on parameter redundancy and recommend minimum sample sizes. Memory models for multisite capture-recapture data can be highly complex and difficult to fit to data. We emphasize the importance of a structured approach to modeling such data, by considering a priori which parameters can be estimated, which constraints are needed in order for estimation to take place, and how much data need to be collected. We also give guidance on the amount of data needed to use two alternative families of tests for whether models for multisite capture-recapture data need to incorporate memory.

Discontinuation of antipsychotic medication in pregnancy: a cohort study.

BACKGROUND: Women prescribed antipsychotics face the dilemma on whether to continue medication in pregnancy in terms of balancing risks and benefits. Previous research on other psychotropic medications suggests that many women discontinue treatment in early pregnancy. However, very limited evidence exists on discontinuation of antipsychotic medication. METHODS: We identified 495,953 pregnant women from THIN primary care database. Kaplan-Meier plots were used to examine time to last antipsychotic prescription. Poisson regression was used to examine characteristics of those who stopped treatment during pregnancy. RESULTS: There has been an overall increase in prevalence of antipsychotic prescribing since 2007. However, antipsychotics were more likely to be stopped in pregnant than non-pregnant women. Only 107/279 (38%) of women on atypical antipsychotics and 39/207 (19%) of women on typical antipsychotics before pregnancy still received treatment at the start of third trimester. Older women were more likely to continue typical antipsychotic treatment in pregnancy (35+ versus <25 years risk ratio: 3.09 [95% CI 1.76, 5.44]). Likewise, those who received typical antipsychotics for longer periods before were most likely to continue treatment in pregnancy (12+ versus <6 months: RR: 3.12 [95% CI 1.97, 4.95]). For atypical antipsychotics length and dose of prior prescribing were also associated with continuation in pregnancy. CONCLUSIONS: Pregnancy was a major determinant of cessation of antipsychotics. Only 38% of women on atypical and 19% on typical antipsychotics were still prescribed the drug in the third trimester. Duration of prior treatment, maternal age as well as dose was significantly associated with continued treatment of antipsychotics in pregnancy.

Demography of straw-colored fruit bats in Ghana.

Eidolon helvum is widely distributed across sub-Saharan Africa where it forms large, dense colonies. The species is migratory and satellite telemetry studies have demonstrated that individuals can migrate over 2,500 km. It is a common source of bush meat in West Africa and evidence of infection with potentially zoonotic viruses has been found in West African colonies. The species, therefore, is of interest to both ecologists and those interested in public health. Despite this, demographic parameters of the species are unknown. We focused our study primarily on a colony of up to 1,000,000 bats that roost in trees in Accra, Ghana to obtain estimates of birth rate and survival probability. Aging of bats by examination of tooth cementum annuli allowed use of life tables to indicate an annual survival probability for juveniles of 0.43 (95% confidence interval [CI] 0.16-0.77) and for adults of 0.83 (95% CI 0.73-0.93). Additionally, an annual adult survival probability of 0.63 (95% CI 0.27-0.88) was estimated by following 98 radiocollared bats over a year; capture-recapture data were analyzed using multistate models to address the confounding factor of emigration. True survival probabilities may be in between the 2 estimates, because permanent emigration may lead to underestimation in the capture-recapture study, and population decline may lead to overestimation in the life table analysis. Birth rates (0.96 young per female per year, 95% CI 0.92-0.98) and colony size changes were also estimated. Estimation of these key parameters will allow future analyses of both infection dynamics within, and harvest sustainability of, E. helvum populations.