Use of Bayesian analysis with individual‐based modeling to project outcomes of coral restoration

Various approaches to coral restoration have been developed to help increase rate of reef recovery from perturbations, among the most common of which is coral transplantation. Success is often evaluated based on short‐term observations that capture only the initial phase of space colonization by coral transplants. Here, an individual‐based model is developed to quantify uncertainty in future trajectories in experimental plots given past observations. Empirical data were used to estimate probabilistic growth, survival, and fission rates of Acropora pulchra and A. intermedia (order Scleractinia) in a sandy reef flat (Bolinao, Philippines). Simulations were initialized with different densities (25 or 50 transplants per species per 16 m²) to forecast possible coral cover trajectories over a 5‐year period. Given current conditions, there is risk of local extinction which is higher in low‐density plots for both species, and higher for A. intermedia compared to A. pulchra regardless of density. While total coral cover is projected to increase, species composition in the future is more likely to be highly uneven. The model was used to quantify effect on recovery rate of protection from pulse anthropogenic disturbances, given different initial transplantation densities. When monitoring data are limited in time, stochastic models may be used to assess whether the restoration trajectory is heading toward the desired state and at what rate, and foresee system response to various adaptive interventions.     

Dealing with uncertainty in landscape genetic resistance models: a case of three co‐occurring marsupials

Landscape genetics lacks explicit methods for dealing with the uncertainty in landscape resistance estimation, which is particularly problematic when sample sizes of individuals are small. Unless uncertainty can be quantified, valuable but small data sets may be rendered unusable for conservation purposes. We offer a method to quantify uncertainty in landscape resistance estimates using multimodel inference as an improvement over single model‐based inference. We illustrate the approach empirically using co‐occurring, woodland‐preferring Australian marsupials within a common study area: two arboreal gliders (Petaurus breviceps, and Petaurus norfolcensis) and one ground‐dwelling antechinus (Antechinus flavipes). First, we use maximum‐likelihood and a bootstrap procedure to identify the best‐supported isolation‐by‐resistance model out of 56 models defined by linear and non‐linear resistance functions. We then quantify uncertainty in resistance estimates by examining parameter selection probabilities from the bootstrapped data. The selection probabilities provide estimates of uncertainty in the parameters that drive the relationships between landscape features and resistance. We then validate our method for quantifying uncertainty using simulated genetic and landscape data showing that for most parameter combinations it provides sensible estimates of uncertainty. We conclude that small data sets can be informative in landscape genetic analyses provided uncertainty can be explicitly quantified. Being explicit about uncertainty in landscape genetic models will make results more interpretable and useful for conservation decision‐making, where dealing with uncertainty is critical.     

Effects of re‐breeding rates on population size estimation of biennial breeders: results from a model based on albatrosses

Estimating total breeding populations (I) for species that exhibit biennial breeding is generally done from counts of individuals that breed in each year (N), but can be complicated by the fact that the proportion of individuals breeding varies from year to year. Partly, this reflects the proportion of individuals that re‐breed in successive years (re‐breeding rate, p), which is largely, although not exclusively, governed by reproductive failure. Here we show that variation in counts of breeding individuals not only reflects changes in total breeding population but can be sensitive to and powerfully driven by variation in p. A simulation of annual field counts of a bird exhibiting biennial breeding was constructed to explore the effect of re‐breeding attempts on estimations of the total breeding population. The model was used to simulate the consequences of adult mortality and different annual patterns of nesting failures on total breeding population estimates, and to explore the consequences of variation in p on N, when total breeding population remains constant. N is shown to be very sensitive to variations in p, so that even short‐term fluctuations in p can cause changes in N that oscillate for many years ahead. We compare our modelled results with real data for Grey‐headed Albatrosses Thalassarche chrysostoma and demonstrate that, when I is held constant in the model, actual counts may be simulated by variations in p only. Normally, I is unknown and is extrapolated from N on the assumption that N mirrors changes in the size of the total population. Consequently, applying average values of p can result in misleading estimates of total breeding population. We recommend that annual counts of breeding individuals are supplemented with annual estimates of p. Field protocols that aim to estimate annual breeding population size from counts of breeding individuals should be complemented by independent measures of rates of re‐breeding and nest failure.     

A PCR assay for the quantification of growth of the oomycete pathogen Hyaloperonospora arabidopsidis in Arabidopsis thaliana

The accurate quantification of disease severity is important for the assessment of host–pathogen interactions in laboratory or field settings. The interaction between Arabidopsis thaliana and its naturally occurring downy mildew pathogen, Hyaloperonospora arabidopsidis (Hpa), is a widely used reference pathosystem for plant–oomycete interactions. Current methods for the assessment of disease severity in the Arabidopsis–Hpa interaction rely on measurements at the terminal stage of pathogen development; namely, visual counts of spore‐producing structures or the quantification of spore production with a haemocytometer. These assays are useful, but do not offer sensitivity for the robust quantification of small changes in virulence or the accurate quantification of pathogen growth prior to the reproductive stage. Here, we describe a quantitative real‐time polymerase chain reaction (qPCR) assay for the monitoring of Hpa growth in planta. The protocol is rapid, inexpensive and can robustly distinguish small changes in virulence. We used this assay to investigate the dynamics of early Hpa mycelial growth and to demonstrate the proof of concept that this assay could be used in screens for novel oomycete growth inhibitors.     

Quantification of Survival of Escherichia coli O157:H7 on Plants Affected by Contaminated Irrigation Water

Enterohemorrhagic E. coli O157: H7 (EHEC) is a major foodborne pathogen capable of causing diarrhea and vomiting, with further complications such as hemolytic‐uremic syndrome (HUS). The aim of this study was to use the real‐time PCR method to quantify the survival of Escherichia coli O157:H7/pGFP in phyllosphere (leaf surface), rhizosphere (volume of soil tightly held by plant roots), and non‐rhizosphere soils (sand and clay) irrigated with contaminated water and compare the results obtained between real‐time PCR method and conventional plate counts. The real‐time PCR probe was designed to hybridize with the (eae) gene of E. coli O157:H7. The probe was incorporated into real‐time PCR containing DNA extracted from the phyllosphere, rhizosphere, and non‐rhizosphere soils irrigated with water artificially contaminated with E. coli O157:H7. The detection limit for E. coli O157:H7 quantification by real‐time PCR was 2.3 × 10³ in the rhizosphere and phyllosphere samples. E. coli O157:H7 survived longer in rhizosphere soil than the non‐rhizosphere soil. The concentration of E. coli O157:H7/pGFP in rhizosphere soils was ≥ 10⁴ CFU/g in both soils at day 12 based on both plate count and real time PCR, with the clay soil significantly (P = 0.05) higher than the sandy soil. This data showed that E. coli O157H:7 can persist in the environment for more than 50 d, and this may pose some risk for both animal and human infection and provides a very significant pathway for pathogen recontamination in the environment.     

Combining flow cytometry and gfp reporter gene for quantitative evaluation of Pectpbacterium carotovorum ssp. carotovorum in Ornithogalum dubium plantlets

Aims: Ornithogalum dubium is a natural host of the soft rot pathogen Pectobacterium carotovorum ssp. carotovorum (Pcc). The present study was aimed to develop a quantification system for Pcc expressing a gfp reporter gene, using fluorescent activated cell sorter (FACS) in planta. Methods and Results: Several calibration steps were required to distinctly gate the GFP‐labelled bacteria at FL1 mode and count the bacteria. To validate the bacterial counts obtained by FACS analysis, an internal standard of polystyrene green fluorescent microsphere beads was employed, resulting in high correlation with serial dilutions and plate counting. This allowed quantification of the bacteria, with no further need to culture, dilute or plate the cells. Micropropagation tools were developed to produce uniform plantlets of O. dubium, which were either inoculated with increasing concentrations of Pcc or elicited for resistance towards Pcc using methyl jasmonate. The rapid counting procedure allowed recovering, gating and counting the bacterial population in planta, separately from the plant cells background and from the microsphere beads. Conclusions: The FACS based quantification approach of Pcc was found accurate, reproducible and time saving, thus useful for counting bacteria in planta. Significance and Impact of the Study: The combination of time‐ and cost‐saving approach for Pcc quantification with efficient screening tools during early stages of micropropagation may facilitate the preliminary process of selection for resistant cultivars.     

Zero‐inflated Poisson factor model with application to microbiome read counts

Dimension reduction of high‐dimensional microbiome data facilitates subsequent analysis such as regression and clustering. Most existing reduction methods cannot fully accommodate the special features of the data such as count‐valued and excessive zero reads. We propose a zero‐inflated Poisson factor analysis model in this paper. The model assumes that microbiome read counts follow zero‐inflated Poisson distributions with library size as offset and Poisson rates negatively related to the inflated zero occurrences. The latent parameters of the model form a low‐rank matrix consisting of interpretable loadings and low‐dimensional scores that can be used for further analyses. We develop an efficient and robust expectation‐maximization algorithm for parameter estimation. We demonstrate the efficacy of the proposed method using comprehensive simulation studies. The application to the Oral Infections, Glucose Intolerance, and Insulin Resistance Study provides valuable insights into the relation between subgingival microbiome and periodontal disease.     

Validation and calibration of an accelerometer in preschool children

Objective: Obesity rates in young children are increasing, and decreased physical activity is likely to be a major contributor to this trend. Studies of physical activity in young children are limited by the lack of valid and acceptable measures. The purpose of this study was to calibrate and validate the ActiGraph accelerometer for use with 3‐ to 5‐year‐old children. Research Methods and Procedures: Thirty preschool children wore an ActiGraph accelerometer (ActiGraph, Fort Walton Beach, FL) and a Cosmed portable metabolic system (Cosmed, Rome, Italy) during a period of rest and while performing three structured physical activities in a laboratory setting. Expired respiratory gases were collected, and oxygen consumption was measured on a breath‐by‐breath basis. Accelerometer data were collected at 15‐second intervals. For cross‐validation, the same children wore the same instruments while participating in unstructured indoor and outdoor activities for 20 minutes each at their preschool. Results: In calibrating the accelerometer, the correlation between V?o ₂ (ml/kg per min) and counts was r = 0.82 across all activities. The only significant variable in the prediction equation was accelerometer counts (R² = 0.90, standard error of the estimate = 4.70). In the cross‐validation, the intraclass correlation coefficient between measured and predicted V?o ₂ was R = 0.57 and the Spearman correlation coefficient was R = 0.66 (p < 0.001). Cut‐off points for moderate‐ and vigorous‐intensity physical activity were identified at 420 counts/15 s (V?o ₂ = 20 mL/kg per min) and 842 counts/15 s (V?o ₂ = 30 mL/kg per min), respectively. When these cutpoints were applied to the cross‐validation data, percentage agreement, kappa, and modified kappa for moderate activity were 0.69, 0.36, and 0.38, respectively. For vigorous activity, the same measures were 0.81, 0.13, and 0.62. Discussion: Accelerometer counts were highly correlated with V?o ₂ in young children. Accelerometers can be appropriately used as a measure of physical activity in this population.     

Reactivation of latent tuberculosis in rhesus macaques by coinfection with simian immunodeficiency virus

Background Tuberculosis (TB) and AIDS together present a devastating public health challenge. Over 3 million deaths every year are attributed to these twin epidemics. Annually, ～11 million people are coinfected with HIV and Mycobacterium tuberculosis (Mtb). AIDS is thought to alter the spontaneous rate of latent TB reactivation. Methodology Macaques are excellent models of both TB and AIDS. Therefore, it is conceivable that they can also be used to model coinfection. Using clinical, pathological, and microbiological data, we addressed whether latent TB infection in rhesus macaques can be reactivated by infection with simian immunodeficiency virus (SIV). Results A low‐dose aerosol infection of rhesus macaques with Mtb caused latent, asymptomatic TB infection. Infection of macaques exhibiting latent TB with a rhesus‐specific strain of SIV significantly reactivated TB. Conclusions Rhesus macaques are excellent model of TB/AIDS coinfection and can be used to study the phenomena of TB latency and reactivation.     

Regional material flow behaviors of agro‐food processing craft villages in Red River Delta,Vietnam

The economic reform “??i M?i” in 1986 has rapidly increased the number of craft villages in Vietnam, especially in the Red River Delta (RRD) leading to environmental degradation. This article presents an assessment of environmental and resource issues of agro‐Food Processing Craft Villages (FPCVs) in RRD using a refined approach to material flow analysis focusing on consistent quantification of uncertainty with particular attention to secondary and empirical data that are often faced in material flow analyses in transition economies. Material flows of agro‐Food Processing including eight types of production were examined and linked to activities of private Households, Rice Cultivation, and Pig Farming in a model called Red River Delta. Materials investigated were Goods (i.e., total materials), organic carbon (org.C), nitrogen (N), and phosphorus (P). The findings reveal material cycles are almost entirely open, that is, the materials used in FPCVs do not recycle within the region. From ～10.5 million tons/year of imported Goods used for agro‐Food Processing, final products and utilized materials account for minor fractions (～5%, by weight). Conversely, the majority (88%) is directly discharged. Materials accumulated as stocks represent 1% of Goods (100,000 tons/year), 21% of org.C (～34,000 tons/year), 42% of N (～1,300 tons/year), and 57% of P (～300 tons/year), whose substance concentrations vastly exceed natural resilience capacities. Although agro‐Food Processing accounts for negligible material shares in Red River Delta, FPCVs pollution is severe at local levels due to the location of home‐based production. Several options for closing material loops at various system scales are recommended for environmental and resource management of FPCVs. The material flow analysis results provide a database that may be used as a decision support tool for production establishments in craft villages and relevant authorities in setting priorities on environmental planning and resource management. This article met the requirements for a gold – silver JIE data openness badge described at http://jie.click/badges .     

Euschistus conspersus female morphology and attraction to methyl (2E,4Z)-decadienoate pheromone–baited traps in processing tomatoes

Previous work documented seasonal field response dynamics of Euschistus conspersus Uhler (Heteroptera: Pentatomidae) to Euschistus spp. pheromone [methyl (2E,4Z)‐decadienoate]‐baited traps in California processing tomatoes, Lycopersicon esculentum (Miller) (Solanaceae). A laboratory phenology model has been reported for E. conspersus egg incubation to adult emergence. In the present work, reproductive and thoracic dissections were performed on female E. conspersus collected year‐round from seasonal habitats in California's Central Valley. We used these dissection data to establish relationships between the morphology of E. conspersus and time of year, habitat, sample recovery method, and female attraction to pheromone traps in commercial tomato fields. All ovariole categories, sexually immature through postreproductive, were recorded for females collected from tomatoes by plant‐beating sample throughout the growing season. Conversely, pheromone trap captures in tomatoes over the same period revealed that females entering the traps were exclusively reproductively active with matured eggs. We conclude that early season female‐biased E. conspersus pheromone trap catch can be used to establish a ‘biofix’ from which to accumulate degree days and forecast nymphal development in the field. Focusing control efforts on the more susceptible nymph stages may improve efficacy of reduced‐risk insecticides such as the neonicotinoids. Thoracic dissection results, with no significant difference in flight muscle size or color by ovariole condition, failed to support our hypothesis of a life history trade‐off between female reproductive activity and flight capability to explain a decline in female pheromone trap response during the mid‐summer tomato‐fruiting stages. The adaptive value of the observed retention of E. conspersus flight capability over the calendar year, and across reproductive stages, is discussed.     

Modeling daily flowering probabilities: expected impact of climate change on Japanese cherry phenology

Understanding the drivers of phenological events is vital for forecasting species’ responses to climate change. We developed flexible Bayesian survival regression models to assess a 29‐year, individual‐level time series of flowering phenology from four taxa of Japanese cherry trees (Prunus spachiana, Prunus × yedoensis, Prunus jamasakura, and Prunus lannesiana), from the Tama Forest Cherry Preservation Garden in Hachioji, Japan. Our modeling framework used time‐varying (chill and heat units) and time‐invariant (slope, aspect, and elevation) factors. We found limited differences among taxa in sensitivity to chill, but earlier flowering taxa, such as P. spachiana, were more sensitive to heat than later flowering taxa, such as P. lannesiana. Using an ensemble of three downscaled regional climate models under the A1B emissions scenario, we projected shifts in flowering timing by 2100. Projections suggest that each taxa will flower about 30 days earlier on average by 2100 with 2–6 days greater uncertainty around the species mean flowering date. Dramatic shifts in the flowering times of cherry trees may have implications for economically important cultural festivals in Japan and East Asia. The survival models used here provide a mechanistic modeling approach and are broadly applicable to any time‐to‐event phenological data, such as plant leafing, bird arrival time, and insect emergence. The ability to explicitly quantify uncertainty, examine phenological responses on a fine time scale, and incorporate conditions leading up to an event may provide future insight into phenologically driven changes in carbon balance and ecological mismatches of plants and pollinators in natural populations and horticultural crops.     

Occurrence of thermotolerant Campylobacter species in surface waters of a Mediterranean area and in its prevailing pollution sources

Aims: To determine the prevalence of Campylobacter in surface waters of a highly populated Mediterranean area. Methods and Results: Surface water and wastewater samples were collected from an area in the north‐east of Spain during a 2‐year study. All the samples were analysed using the MPN method and Multiplex PCR to quantify and identify Campylobacter. It was detected in 82% of the samples from the Llobregat River with a mean of 1·3 MPN 100 ml^?1. The lowest counts were obtained in summer. Campylobacter coli was the predominant species in this river. The bacteria were isolated from marsh water but not from seawater samples. The highest counts of campylobacters were found in poultry wastewater where Camp. jejuni was the predominant species, as in urban sewage. In pig slurry, Camp. coli was the only species detected. Conclusions: Campylobacter jejuni and Camp. coli are present and widely distributed in the surface water of the studied area. The two species co‐exist, with Camp. coli being predominant. In river water, campylobacter counts presented a seasonal distribution. No relationship with faecal indicators was found. Significance and Impact of the Study: This study provides the first data on the occurrence and concentrations of thermotolerant campylobacter species in surface water in a Mediterranean area.     

Reduced generation time of apple seedlings to within a year by means of a plant virus vector: a new plant‐breeding technique with no transmission of genetic modification to the next generation

Fruit trees have a long juvenile phase. For example, the juvenile phase of apple (Malus × domestica) generally lasts for 5–12 years and is a serious constraint for genetic analysis and for creating new apple cultivars through cross‐breeding. If modification of the genes involved in the transition from the juvenile phase to the adult phase can enable apple to complete its life cycle within 1 year, as seen in herbaceous plants, a significant enhancement in apple breeding will be realized. Here, we report a novel technology that simultaneously promotes expression of Arabidopsis FLOWERING LOCUS T gene (AtFT) and silencing of apple TERMINAL FLOWER 1 gene (MdTFL1‐1) using an Apple latent spherical virus (ALSV) vector (ALSV‐AtFT/MdTFL1) to accelerate flowering time and life cycle in apple seedlings. When apple cotyledons were inoculated with ALSV‐AtFT/MdTFL1 immediately after germination, more than 90% of infected seedlings started flowering within 1.5–3 months, and almost all early‐flowering seedlings continuously produced flower buds on the lateral and axillary shoots. Cross‐pollination between early‐flowering apple plants produced fruits with seeds, indicating that ALSV‐AtFT/MdTFL1 inoculation successfully reduced the time required for completion of the apple life cycle to 1 year or less. Apple latent spherical virus was not transmitted via seeds to successive progenies in most cases, and thus, this method will serve as a new breeding technique that does not pass genetic modification to the next generation.     

Accounting for uncertainty in dormant life stages in stochastic demographic models

Dormant life stages are often critical for population viability in stochastic environments, but accurate field data characterizing them are difficult to collect. Such limitations may translate into uncertainties in demographic parameters describing these stages, which then may propagate errors in the examination of population‐level responses to environmental variation. Expanding on current methods, we 1) apply data‐driven approaches to estimate parameter uncertainty in vital rates of dormant life stages and 2) test whether such estimates provide more robust inferences about population dynamics. We built integral projection models (IPMs) for a fire‐adapted, carnivorous plant species using a Bayesian framework to estimate uncertainty in parameters of three vital rates of dormant seeds – seed‐bank ingression, stasis and egression. We used stochastic population projections and elasticity analyses to quantify the relative sensitivity of the stochastic population growth rate (log λs) to changes in these vital rates at different fire return intervals. We then ran stochastic projections of log λs for 1000 posterior samples of the three seed‐bank vital rates and assessed how strongly their parameter uncertainty propagated into uncertainty in estimates of log λs and the probability of quasi‐extinction, P_q(t). Elasticity analyses indicated that changes in seed‐bank stasis and egression had large effects on log λs across fire return intervals. In turn, uncertainty in the estimates of these two vital rates explained > 50% of the variation in log λs estimates at several fire‐return intervals. Inferences about population viability became less certain as the time between fires widened, with estimates of P_q(t) potentially > 20% higher when considering parameter uncertainty. Our results suggest that, for species with dormant stages, where data is often limited, failing to account for parameter uncertainty in population models may result in incorrect interpretations of population viability.     

Age and growth of the spotted goatfish, Pseudupeneus maculatus (Bloch, 1793) in Brazil, validated through marginal increment and oxytetracycline dyes in the sagittae

A sample composed of 4973 specimens of the spotted goatfish, Pseudupeneus maculatus (4.5–29.2 cm fork length) was collected off northeastern Brazil from 1999 to 2002. Sagittae (398) were analyzed for age and growth estimation using both annuli and microincrements. For the first approach, the mean monthly marginal increment ratio analysis suggested that one band is formed annually from May to June. With the microincrements analysis, 15 specimens were reared (3–71 days) for validation of periodicity using oxytetracycline. Fluorescent dyes were observed in 10 specimens (7.5–16.9 cm). After testing, one microincrement was found to form daily. Otolith sections were polished and analyzed using a light microscope (100–1200× magnifications). Individuals larger than 22.6 cm (4 years) showed heavily overlaid increments on the otolith edge, which hampered the counts. There was agreement on the size from counts on an annual and daily basis. The von Bertalanffy function provided the following parameters: L_∞ = 33.23 cm; K = 0.265; t₀ = 0.0883 year. The sample was composed of 0⁺ to >5‐year‐old specimens. Age at first maturity was 3.6 years (20 cm), whereas the recruitment age for fisheries was 3.9 years. Juveniles represented about half of the catch (48.7%), which may have implications for population equilibrium.     

When mechanism matters: Bayesian forecasting using models of ecological diffusion

Ecological diffusion is a theory that can be used to understand and forecast spatio‐temporal processes such as dispersal, invasion, and the spread of disease. Hierarchical Bayesian modelling provides a framework to make statistical inference and probabilistic forecasts, using mechanistic ecological models. To illustrate, we show how hierarchical Bayesian models of ecological diffusion can be implemented for large data sets that are distributed densely across space and time. The hierarchical Bayesian approach is used to understand and forecast the growth and geographic spread in the prevalence of chronic wasting disease in white‐tailed deer (Odocoileus virginianus). We compare statistical inference and forecasts from our hierarchical Bayesian model to phenomenological regression‐based methods that are commonly used to analyse spatial occurrence data. The mechanistic statistical model based on ecological diffusion led to important ecological insights, obviated a commonly ignored type of collinearity, and was the most accurate method for forecasting.     

Selectivity and competitive interactions between two benthic invertebrate grazers (Asellus aquaticus and Potamopyrgus antipodarum): an experimental study using 13C- and 15N-labelled diatoms

1. Tracer experiments with two diatoms labelled with ¹³C (Nitzschia palea) and ¹⁵N (Fragilaria crotonensis), were conducted to investigate feeding selectivity and interspecific competition between the grazers Asellus aquaticus (Isopoda, Crustacea) and Potamopyrgus antipodarum (Hydrobiidae, Gastropoda). Conventional methods, such as cell counts and estimated biovolume, were used first to detect feeding preferences within the different grazer treatments. 2. The results revealed a significant decline in algal biovolume in all grazer treatments and no indications of active selectivity were observed. In contrast to conventional methods, measurements based on isotope signatures showed strong differences in tracer uptake, thus indicating different degrees of assimilation and digestion by the two grazers. 3. The selectivity index Q, which provides information on the uptake ratio of ¹³C to ¹⁵N, showed a significant time effect for both grazer species and a significant difference between single‐ and mixed‐grazer treatments for P. antipodarum. Thus, this technique enabled the direct quantification of the uptake by grazers and, therefore, served as an ideal tool for the detection of passive selectivity. 4. Our results indicate a shift in feeding preferences related to between‐species competition and a potential divergence of trophic niches when species coexist.     

The use of egg counts and suction trap samples to forecast the infestation of spring-sown field beans, Vicia faba, by the black bean aphid, Aphis fabae

Daily suction trap samples at a height of 12·2 m collected throughout the year, winter egg and ‘spring’ population counts on the spindle tree, Euonymus europaeus, and initial infestations of the black bean aphid, Aphis fabae, on field bean, Vicia faba, crops are available from Southern England since 1970. In different areas, estimates of the sizes of the autumn migrations, the over-wintering egg populations, the spring fundatrigeniae and the spring migrations, have been used to forecast field bean crop infestation levels which, in turn, project subsequent trap catches of alatae. The forecasts of crop infestation become progressively more accurate from the autumn migration to the following spring migration, accounting for 28%, 54%, 54% and 64% of the variance respectively. In areas where traps are sited, the spring migration trap samples give the most accurate estimate of the size and timing of crop infestation. Autumn trap catches are particularly useful as very early forecasts of likely very large or very small populations on field beans about 8 months later, but otherwise they lack precision. Egg sampling in winter provides a considerably more accurate forecast approximately 5 months before crop infestations. In spring (May), fundatrigeniae sampled on spindle are most useful for predicting time of migration, and provide approximately 2 weeks' warning for insecticide application, if needed. Finally, trap sampling of the spring migration provides the latest estimate of both the sizes of crop infestations and the timing of insecticide treatment. The E. europaeus and aerial sampling systems are complementary, the traps providing systematic, continuous information and the E. europaeus samples greater detail. Combined, they can provide excellent long-term fore-warning of the need for chemical control and short-term warning of control timing. Forecasts have been 90% correct in eight years out of nine. The error in the ninth year may be due to immigration from the European mainland.     

Detecting and quantifying introgression in hybridized populations: simplifying assumptions yield overconfidence and uncertainty

A growing threat to the conservation of many native species worldwide is genetic introgression from non‐native species. Although improved molecular genetic techniques are increasing the availability of species‐diagnostic markers for many species, efficient field sampling design and reliable data interpretation require accurate estimates of uncertainty associated with the detection of non‐native alleles and the quantification of introgression in native populations. Using fish populations as examples, we developed a simulation model of an age‐structured population that tracks the introduction and inheritance of non‐native alleles across generations by simulating stochastic mating and survival of individual fish and the resulting transmission of diagnostic markers. To simulate detection and quantification of introgression, we sampled varying combinations of n fish and m diagnostic markers to detect and quantify introgression from thousands of virtual, independent fish populations for a wide range of hybridization scenarios. Using the results of simulated sampling, we quantified the extent to which common simplifying assumptions regarding population structure and inheritance mechanisms can lead to the following: (i) overconfidence in our ability to detect non‐native alleles and (ii) unrealistically narrow confidence intervals for estimates of the proportion of non‐native alleles present. Under many circumstances, commonly used simplifying assumptions underestimate the probability of failing to detect ongoing introgression and the uncertainty associated with estimates of introgression by orders of magnitude. Such overconfidence in our ability to detect and quantify introgression can affect critical conservation and management decisions regarding native species undergoing or at risk of introgression from non‐native species.