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Ecosystems worldwide are increasingly being invaded by multiple species, and the rate of biological invasion is accelerating, leading to more interactions among invasive species. One such interaction that has received little attention is the phenomenon of 'serial replacement' or 'over-invasion', where an established invasive species is supplanted by a second invasive species. Understanding this interaction is important as controlling the second species could inadvertently lead to an increase in the abundance of the first species. We used a hierarchical state-space model to analyse changes in annual abundances (commercial catch-per-unit-effort) of three invasive fish species, tench (Tinca tinca), common carp (Cyprinus carpio) and redfin perch (Perca fluviatilis), in the Murray-Darling River system (MDRS), Australia between 1954–2002. Tench were present at low abundances until the mid-1970 s, before declining to the point of no commercial catch post-1989. This rapid decline coincided with a significant increase in carp abundance, suggesting that carp may have driven the tench decline through habitat modification (particularly the destruction of aquatic plants), consistent with findings from European studies that show the disappearance of tench from ponds with intensive carp farming. Redfin perch populations, were inferred to be much less impacted by the invading carp population. While carp were present in the MDRS for the duration of the study, the rapid increase in carp abundance in the early 1970 s coincided with the introduction of a specific genetic lineage—the "Boolarra strain". Our analysis provides compelling evidence of serial replacement of long-established tench by invading common carp triggered by the introduction of a novel carp strain. [ABSTRACT FROM AUTHOR]

Monitoring waterbird populations in Australia is challenging for reasons of counting logistics, and because population aggregation and dispersion can shift rapidly in response to large spatio-temporal variations in resource availability. The East Australian Waterbird survey has conducted annual, aerial, systematic counts of waterbirds over eastern Australia for almost 40 years. It was designed to monitor waterbird populations using design-based inference though for many species this form of inference appears inadequate in the face of these challenges. Here we develop a state-space model-based Bayesian approach that, in addition to explicitly incorporating process noise and observation uncertainty, uses random effects and rainfall-derived covariates to model the year-to-year variation in the proportion of the total (super) population that is present on surveyed wetlands, and available to be counted. We use this model-based approach to estimate the superpopulation size of 45 waterbird species annually, and model the rate of population increase as a function of antecedent rainfall. The results confirm the strong positive effect of antecedent rainfall on population growth rates for nearly all species, and illustrate that species respond to rainfall differently in terms of habitat use, which influences whether they are present on surveyed wetlands. For many species, the year-to-year variation in the estimated proportion of the population on surveyed wetlands is very high. The results have implications for making inferences on population trends from these data, with the ability to model the year-to-year sampling variation a key requirement before the rate of population increase can be estimated with any precision. This study illustrates how to progress this approach, and infers that under average rainfall conditions, the general trend is for estimated superpopulation rates of increase to be negative, though for only a few species is this occurring with strong belief. [ABSTRACT FROM AUTHOR]

Decisions regarding invasive risk of exotic species are often based on species distribution models projected onto the recipient region of interest. Such projections are essentially a measure of prior belief in the ability of an organism to invade. Whilst many decisions are made on the basis of such projections, it is less clear how such prior belief may be empirically modified on the basis of data, in particular introduction events that haven't led to establishment. Here, using the Asian green mussel (Perna viridis) as an example, we illustrate how information on failed introduction attempts may be used to continually update our beliefs in the ability of an organism to invade per introduction, and the underlying habitat suitability for establishment. Our results show that the establishment probability of P. viridis per fouled ship visit in the supposedly favourable northern Australian waters are much lower than initially though, and are continuing to decline. A Bayesian interpretation of our results notes the dramatic reduction in our belief of the ability of P. viridis to invade in the light of what we estimate to be 100's of fouled vessels per year visiting ports without any persistent populations establishing. Under a hypothetico-deductive approach we would reject the null (prior) species distribution model as being useful, and seek to find a better one that can withstand the challenge of data. [ABSTRACT FROM AUTHOR]

Data streams arising from citizen reporting activities continue to grow, yet the information content within these streams remains unclear, and methods for addressing the inherent reporting biases little developed. Here, we quantify the major influence of physical insect features (colour, size, morphology, pattern) on the propensity of citizens to upload photographic sightings to online portals, and hence to contribute to biosecurity surveillance. After correcting for species availability, we show that physical features and pestiness are major predictors of reporting probability. The more distinctive the visual features, the higher the reporting probabilities—potentially providing useful surveillance should the species be an unwanted exotic. Conversely, the reporting probability for many small, nondescript high priority pest species is unlikely to be sufficient to contribute meaningfully to biosecurity surveillance, unless they are causing major harm. The lack of citizen reporting of recent incursions of small, nondescript exotic pests supports the model. By examining the types of insects of concern, industries or environmental managers can assess to what extent they can rely on citizen reporting for their surveillance needs. The citrus industry, for example, probably cannot rely on passive unstructured citizen data streams for surveillance of the Asian citrus psyllid (Diaphorina citri). In contrast, the forestry industry may consider that citizen detection and reporting of species of the large and colourful insects such as pine sawyers (Monochamus spp.) may be sufficient for their needs. Incorporating citizen surveillance into the general surveillance framework is an area for further research. [ABSTRACT FROM AUTHOR]

Citizen science and crowdsourcing have been emerging as methods to collect data for surveillance and/or monitoring activities. They could be gathered under the overarching term citizen surveillance. The discipline, however, still struggles to be widely accepted in the scientific community, mainly because these activities are not embedded in a quantitative framework. This results in an ongoing discussion on how to analyze and make useful inference from these data. When considering the data collection process, we illustrate how citizen surveillance can be classified according to the nature of the underlying observation process measured in two dimensions-the degree of observer reporting intention and the control in observer detection effort. By classifying the observation process in these dimensions we distinguish between crowdsourcing, unstructured citizen science and structured citizen science. This classification helps the determine data processing and statistical treatment of these data for making inference. Using our framework, it is apparent that published studies are overwhelmingly associated with structured citizen science, and there are well developed statistical methods for the resulting data. In contrast, methods for making useful inference from purely crowd-sourced data remain under development, with the challenges of accounting for the unknown observation process considerable. Our quantitative framework for citizen surveillance calls for an integration of citizen science and crowdsourcing and provides a way forward to solve the statistical challenges inherent to citizen-sourced data. [ABSTRACT FROM AUTHOR]

Container-inhabiting mosquitoes such as Aedes notoscriptus, Aedes aegypti, and Aedes albopictus are potential vectors of a number of arboviruses of significance to human health and domestic animals. To assess the risk of mosquito-borne viruses, residential properties were surveyed for mosquito larvae within the Brisbane area during 2010-2012. A two-stage modeling approach was used to model both the presence/absence of Ae. notoscriptus larvae and abundance of larvae when present. Results indicate the total number of wet containers found on a property is the main driving factor of both presence/absence and abundance of Ae. notoscriptus larvae. The generalized additive modeling approach used indicates more standard logistic regression and odds ratios may overestimate the importance of common covariates. The two-stage modeling also potentially allows for predictions of Ae. notoscriptus abundance and common risk indices that are not possible using traditional logistic regression. Factors influencing the number of wet containers are explored with a view toward risk mitigation. [ABSTRACT FROM AUTHOR]

Interception data collected at the Australian quarantine border on the orders Coleoptera, Hemiptera, Lepidoptera and Diptera during 1986-2005 were cross-referenced to incursion data. For insects from these four orders, detection at the quarantine border was a poor predictor of successful incursions over the corresponding period. Most species that successfully mounted an incursion during the 1986-2005 period were not recorded as being intercepted at the quarantine border over the same period. This may be due to either organisms arriving via pathways that are not subject to border inspection, or that the inspection sensitivity is low, or that species discovered are not reliably identified, recorded and reported. The end result is that the border inspection, at least during the period 1986-2005, would have been largely ineffective as an early warning system for a large proportion of incursions occurring over that period. This finding is contrary to the expectation that interception data is a useful tool for predicting future incursions and opens the question as to whether different approaches to collecting interception data might improve predictive power. That said, within those species that were intercepted, those with a higher interception rate had an increased probability of a recorded incursion, particularly for incursions before 1986, and so supports the argument that propagule pressure is a key factor in invasion establishment. [ABSTRACT FROM AUTHOR]