Bio-economic optimisation of surveillance to confirm broadscale eradications of invasive pests and diseases

Eradicating an invasive mammal requires local elimination and reduced reinvasion from an urban source population

Invasive mammal eradications are increasingly attempted across large, complex landscapes. Sequentially controlled management zones can be at risk of reinvasion from adjacent uncontrolled areas, and managers must weigh the relative benefits of ensuring complete elimination from a zone or minimizing reinvasion risk. This is complicated in urban areas, where habitat heterogeneity and a lack of baseline ecological knowledge increase uncertainty. We applied a spatial agent-based model to predict the reinvasion of a well-studied species, the brushtail possum (Trichosurus vulpecula), across an urban area onto a peninsula that is the site of an elimination campaign in Aotearoa New Zealand. We represented fine-scale urban habitat heterogeneity in a land cover layer and tested management scenarios that varied four factors: the density of possums remaining following an elimination attempt, the maintenance trap density on the peninsula, and effort expended toward preventing reinvasion by means of a high-density trap buffer at the peninsula isthmus or control of the source population adjacent to the peninsula. We found that achieving complete elimination on the peninsula was crucial to avoid rapid repopulation. The urban isthmus was predicted to act as a landscape barrier and restrict immigration onto the peninsula, but reliance on this barrier alone would fail to prevent repopulation. In combination, complete elimination, buffer zone, and source population control could reduce the probability of possum repopulation to near zero. Our findings support urban landscape barriers as one tool for sequential invasive mammal elimination but reaffirm that novel methods to expose residual individuals to control will be necessary to secure elimination in management zones. Work to characterize the urban ecology of many invasive mammals is still needed.

Are predictions of bovine tuberculosis-infected herds unbiased and precise?

Bovine tuberculosis (bTB) is prevalent among livestock and wildlife in many countries including New Zealand (NZ), a country which aims to eradicate bTB by 2055. This study evaluates predictions related to the numbers of livestock herds with bTB in NZ from 2012 to 2021 inclusive using both statistical and mechanistic (causal) modelling. Additionally, this study made predictions for the numbers of infected herds between 2022 and 2059. This study introduces a new graphical method representing the causal criteria of strength of association, such as R2, and the consistency of predictions, such as mean squared error. Mechanistic modelling predictions were, on average, more frequently (3 of 4) unbiased than statistical modelling predictions (1 of 4). Additionally, power model predictions were, on average, more frequently (3 of 4) unbiased than exponential model predictions (1 of 4). The mechanistic power model, along with annual updating, had the highest R2 and the lowest mean squared error of predictions. It also exhibited the closest approximation to unbiased predictions. Notably, significantly biased predictions were all underestimates. Based on the mechanistic power model, the biological eradication of bTB from New Zealand is predicted to occur after 2055. Disease eradication planning will benefit from annual updating of future predictions.

Analytical Bayesian approach for the design of surveillance and control programs to assess pest-eradication success

Large invasive species eradication programs are undertaken to protect native biodiversity and agriculture. Programs are typically followed by a series of surveys to assess the likelihood of eradication success and, when residual pests are detected, small-scale control or 'mop-ups' are implemented to eliminate these infestations. Further surveys follow to confirm absence with 'freedom' declared when a target probability of absence is reached. Such biosecurity programs comprise many interacting processes - stochastic biological processes including growth, and response and control interventions - and are an important component of post-border biosecurity. Statistical frameworks formulated to contribute to the design and efficiency of these surveillance and control programs are few and, those available, rely on the simulation of the component processes. In this paper we formulate an analytical Bayesian framework for a general biosecurity program with multiple components to assess pest-eradication success. Our model incorporates stochastic growth and detection processes, and several pest control mechanisms. Survey results and economic considerations are also taken into account to support a range of biosecurity management decisions. Using a case study we demonstrate that solutions match published simulation results and extend the available analysis. Principally, we show how analytical solutions can offer a powerful tool to support the design of effective and cost-efficient biosecurity systems, and we establish some general principles that guide and contribute to robust design.

Quantifying the probability of detection of wild ungulates with the Judas technique

The Judas technique is often used in control or eradication of particular vertebrate pests. The technique exploits the tendency of individuals to form social groups. A radio collar is affixed to an individual and its subsequent monitoring facilitates the detection of other conspecifics. Efficacy of this technique would be improved if managers could estimate the probability that a Judas individual would detect conspecifics. To calculate this probability, we estimated association rates of Judas individuals with other Judas individuals, given the length of time the Judas has been deployed. We developed a simple model of space-use for individual Judas animals and constrained detection probabilities to those specific areas. We then combined estimates for individual Judas animals to infer the probability that a wild individual could be detected in an area of interest via Judas surveillance. We illustrated the method by using data from a feral goat eradication program on Isla Santiago, Galápagos, and a feral pig eradication program on Santa Cruz Island, California. Association probabilities declined as the proximity between individual areas of use of a Judas pair decreased. Unconditional probabilities of detection within individual areas of use averaged 0.09 per month for feral pigs and 0.11 per month for feral goats. Probabilities that eradication had been achieved, given no detections of wild conspecifics, and an uninformative prior probability of eradication were 0.79 (90% CI 0.22-0.99) for feral goats and 0.87 (90% CI 0.44-1.0) for feral pigs. We envisage several additions to the analyses used that could improve estimates of Judas detection probability. Analyses such as these can help managers increase the efficacy of eradication efforts, leading to more effective effects to restore native biodiversity.

Confirming the broadscale eradication success of nutria (Myocastor coypus) from the Delmarva Peninsula, USA

Nutria (Myocastor coypus) were introduced to the eastern shore of Chesapeake Bay, USA in the 1940s. They reached peak densities in the late 1990s, causing massive wetland loss. Beginning in 2002, a systematic plan to eradicate nutria from the 1.7M ha Delmarva Peninsula was implemented. Since that time the nutria population has been effectively reduced, and no nutria have been detected since May 2015. A lack of detection does not equate with complete absence. We address the following three questions. (1) What is the expected probability of nutria eradication from the Delmarva Peninsula as of the end of 2020? (2) If the probability of eradication is below the management target of 0.95, how much more surveillance is required? (3) How sensitive is the estimated probability of eradication to varying levels of public surveillance and modelled population growth rates? These questions were addressed by employing a stochastic spatially-explicit surveillance model that uses data in which no nutria were detected to quantify the probability of complete absence (PoA) over the entire Delmarva Peninsula. We applied an analytical framework that decomposes the spatial risk of survivors and data into management zones, and took advantage of low-cost public reporting of nutria sightings. Active surveillance by the eradication program included detector dog and tracker surveys, shoreline surveys, detection with ground and water platforms (with hair snares), and camera traps. Results showed that the PoA increased with time and surveillance from a beginning PoA in May 2015 of  0.01 to a mean of 0.75 at the end of 2020. This indicates that the PoA on the Delmarva was well below the target threshold of 0.95 for declaring eradication success. However, given continued surveillance without detection, a PoA of 0.95 would be achieved by June 2022. This analysis provides an objective mechanism to align the expectations of policy makers, managers and the public on when eradication of nutria from the entire Delmarva Peninsula should be declared successful.

Cost-effective surveillance of invasive species using info-gap theory

Invasive species can lead to community-level damage to the invaded ecosystem and extinction of native species. Most surveillance systems for the detection of invasive species are developed based on expert assessment, inherently coming with a level of uncertainty. In this research, info-gap decision theory (IGDT) is applied to model and manage such uncertainty. Surveillance of the Asian House Gecko, Hemidactylus frenatus Duméril and Bibron, 1836 on Barrow Island, is used as a case study. Our research provides a novel method for applying IGDT to determine the population threshold (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$K$$\end{document}K) so that the decision can be robust to the deep uncertainty present in model parameters. We further robust-optimize surveillance costs rather than minimize surveillance costs. We demonstrate that increasing the population threshold for detection increases both robustness to the errors in the model parameter estimates, and opportuneness to lower surveillance costs than the accepted maximum budget. This paper provides guidance for decision makers to balance robustness and required surveillance expenditure. IGDT offers a novel method to model and manage the uncertainty prevalent in biodiversity conservation practices and modelling. The method outlined here can be used to design robust surveillance systems for invasive species in a wider context, and to better tackle uncertainty in protection of biodiversity and native species in a cost-effective manner.

Analytical Bayesian models to quantify pest eradication success or species absence using zero-sighting records

It is not possible to establish the absence of a population with certainty using imperfect zero-sighting records, but absence can be inferred. In this paper we use Bayesian methods to formulate analytical inferred distributions and statistics. When such formulations are available, they offer a highly efficient and powerful means of analysis. Our purpose is to provide accessible and versatile formulations to support an assessment of population absence for management decisions, using data from a series of regular and targeted surveys with zero-sightings. The stochastic processes considered here are prior population size, growth and imperfect detection, which are combined into a single distribution with sufficient flexibility to accommodate alternative distributions for each of the driving processes. Analytical solutions formulated include the inferred mean and variance for population size or number of infested survey-units, the probability of absence, the probability of a series of negative surveys conditional on presence, and the probability a population is first detected in a given survey, although we also formulate other statistics and provide explicit thresholds designed to support management decisions. Our formulation and results are straightforward to apply and provide insight into the nonlinear interactions and general characteristics of such systems. Although motivated by an assessment of population absence following a pest eradication program, results are also relevant to the status of threatened species, to 'proof-of-freedom' requirements for trade, and for inferring population size when a population is first detected.

Risk-based surveillance of chronic wasting disease in semi-domestic reindeer

Reindeer pastoralism is a widespread practise across Fennoscandia and Russia. An outbreak of chronic wasting disease (CWD) among wild reindeer (Rangifer tarandus) poses a severe threat to the semi-domestic reindeer herding culture. Establishing surveillance is therefore key, but current models for surveillance of CWD are designed for wild cervids and rely on samples obtained from recreational hunters. Targeting animal groups with a higher infection probability is often used for more efficient disease surveillance. CWD has a long incubation period of 2-3 years, and the animals show clinical signs in the later stages of the infection i.e. 1-4 months prior to death. The semi-domestic reindeer are free-ranging most of the year, but during slaughtering in late fall, herders stress the animals in penned areas. This allows removal of animals with deviant behaviour or physical appearance, and such removals are likely to include animals in the clinical stages of CWD if the population is infected. In Norway, the semi-domestic reindeer in Filefjell is adjacent to a previously CWD infected wild population. We developed a risk-based surveillance method for this semi-domestic setting to establish the probability of freedom from infection over time, or enable early disease detection and mitigation. The surveillance scheme with a scenario tree using three risk categories (sample category, demographic group, and deviations in behaviour or physical appearance) was more effective and less invasive as compared to the surveillance method developed for wild reindeer. We also simulated how variation in susceptibility, incubation period and time for onset of clinical signs (linked to variation in the prion protein gene, PRNP) would potentially affect surveillance. Surveillance for CWD was mandatory within EU-member states with reindeer (2018-2020). The diversity of management systems and epidemiological settings will require the development of a set of surveillance systems suitable for each different context. Our surveillance model is designed for a population with a high risk of CWD introduction requiring massive sampling, while at the same time aiming to limit adverse effects to the populations in areas of surveillance.

The failure of success: cyclic recurrences of a globally invasive pest

In the six decades since 1960, the oriental fruit fly, Bactrocera dorsalis (Hendel), has been announced successfully eradicated in California by the U.S. Department of Agriculture a total of 564 times. This includes eradication declarations in one city a total of 25 different years, in 12 cities 8-19 different years, and in 101 cities 2-7 different years. We here show that the false negatives in declaring elimination success hinge on the easily achieved regulatory criteria, which have virtually guaranteed the failure of complete extirpation of this pest. Analyses of the time series of fly detection over California placed on a grid of 100-km² cells revealed (1) partial success of the eradication program in controlling the invasion of the oriental fruit fly; (2) low prevalence of the initial detection in these cells is often followed by high prevalence of recurrences; (3) progressively shorter intervals between years of consecutive detections; and (4) high likelihood of early-infested cells also experiencing the most frequent outbreaks. Facing the risk of recurrent invasions, such short-term eradication programs have only succeeded annually according to the current regulatory criteria but have failed to achieve the larger goal of complete extirpation of the oriental fruit fly. Based on the components and running costs of the current programs, we further estimated the efficiency of eradication programs with different combinations of eradication radius, duration, and edge impermeability in reducing invasion recurrences and slowing the spread of the oriental fruit fly. We end with policy implications including the need for agricultural agencies worldwide to revisit eradication protocols in which monitoring and treatments are terminated when the regulatory criteria for declaring eradication are met. Our results also have direct implications to invasion biologists and agriculture policy makers regarding long-term risks of short-term expediency.

Evaluating the effects of landscape structure on the recovery of an invasive vertebrate after population control

CONTEXT

Effective landscape control of invasive species is context-dependent due to the interplay between the landscape structure, local population dynamics, and metapopulation processes. We use a modelling approach incorporating these three elements to explore the drivers of recovery of populations of invasive species after control.

OBJECTIVES

We aim to improve our understanding of the factors influencing the landscape-level control of invasive species.

METHODS

We focus on the case study of invasive brushtail possum (Trichosurus vulpecula) control in New Zealand. We assess how 13 covariates describing the landscape, patch, and population features influence the time of population recovery to a management density threshold of two possums/ha. We demonstrate the effects of those covariates on population recovery under three scenarios of population growth: logistic growth, strong Allee effects, and weak Allee effects.

RESULTS

Recovery times were rapid regardless of the simulated population dynamics (average recovery time < 2 years), although populations experiencing Allee effects took longer to recover than those growing logistically. Our results indicate that habitat availability and patch area play a key role in reducing times to recovery after control, and this relationship is consistent across the three simulated scenarios.

CONCLUSIONS

The control of invasive possum populations in patchy landscapes would benefit from a patch-level management approach (considering each patch as an independent management unit), whereas simple landscapes would be better controlled by taking a landscape-level view (the landscape as the management unit). Future research should test the predictions of our models with empirical data to refine control operations.

Roll-Back Eradication of Bovine Tuberculosis (TB) From Wildlife in New Zealand: Concepts, Evolving Approaches, and Progress

The New Zealand government and agricultural industries recently jointly adopted the goal of nationally eradicating bovine tuberculosis (TB) from livestock and wildlife reservoirs by 2055. Only Australia has eradicated TB from a wildlife maintenance host. Elsewhere the disease is often self-sustaining in a variety of wildlife hosts, usually making eradication an intractable problem. The New Zealand strategy for eradicating TB from wildlife is based on quantitative assessment using a Bayesian “Proof of Freedom” framework. This is used to assess the probability that TB has been locally eradicated from a given area. Here we describe the framework (the concepts, methods and tools used to assess TB freedom and how they are being applied and updated). We then summarize recent decision theory research aimed at optimizing the balance between the risk of falsely declaring areas free and the risk of overspending on disease management when the disease is already locally extinct. We explore potential new approaches for further optimizing the allocation of management resources, especially for places where existing methods are impractical or expensive, including using livestock as sentinels. We also describe how the progressive roll-back of locally eradicated areas scales up operationally and quantitatively to achieve and confirm eradication success over the entire country. Lastly, we review the progress made since the framework was first formally adopted in 2011. We conclude that eradication of TB from New Zealand is feasible, and that we are well on the way to achieving this outcome.

Livestock as sentinels for an infectious disease in a sympatric or adjacent-living wildlife reservoir host

A central question to address in managing wildlife diseases is how much effort and resources are required to reduce infection prevalence to below a requisite threshold? This requires surveillance for infection in at least one species involved in the infection cycle, a process that is often expensive and time-consuming but one which could be enhanced using additional sources of readily-obtainable surveillance data. We demonstrate how surveillance data from ruminant livestock monitored for bovine tuberculosis (bTB) in New Zealand can be employed in spatially-explicit modelling to help predict the probability of freedom from Mycobacterium bovis infection in a sympatric wildlife reservoir species, the brushtail possum (Trichosurus vulpecula). We apply the model to a case study and compare resulting probabilities of freedom when utilizing (1) livestock data only, (2) wildlife data only, and (3) combined livestock-plus-wildlife surveillance data. Results indicated that the greatest probability of M. bovis eradication was achieved using wildlife monitoring data supplemented with livestock surveillance data. This combined approach lessened the time required for a confident (95% probability) declaration of regional eradication. However, the combined model was sensitive to the precision of the input parameters, and we describe ways to account for this. In a broad sense, this modelling approach is flexible in that any spatial arrangement of wildlife habitat and farms can be analysed, provided infection is readily detectable in both the wild and domestic animal(s) of interest. It is applicable to monitoring any communicable wildlife disease that affects regularly-tested livestock. The potential benefits to wildlife disease management include reduced surveillance costs and more rapid achievement of targeted reductions in disease prevalence.