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Optimal surveillance strategy for invasive species management when surveys stop after detection.

ABSTRACT: Invasive species are a cause for concern in natural and economic systems and require both monitoring and management. There is a trade-off between the amount of resources spent on surveying for the species and conducting early management of occupied sites, and the resources that are ultimately spent in delayed management at sites where the species was present but undetected. Previous work addressed this optimal resource allocation problem assuming that surveys continue despite detection until the initially planned survey effort is consumed. However, a more realistic scenario is often that surveys stop after detection (i.e., follow a "removal" sampling design) and then management begins. Such an approach will indicate a different optimal survey design and can be expected to be more efficient. We analyze this case and compare the expected efficiency of invasive species management programs under both survey methods. We also evaluate the impact of mis-specifying the type of sampling approach during the program design phase. We derive analytical expressions that optimize resource allocation between monitoring and management in surveillance programs when surveys stop after detection. We do this under a scenario of unconstrained resources and scenarios where survey budget is constrained. The efficiency of surveillance programs is greater if a "removal survey" design is used, with larger gains obtained when savings from early detection are high, occupancy is high, and survey costs are not much lower than early management costs at a site. Designing a surveillance program disregarding that surveys stop after detection can result in an efficiency loss. Our results help guide the design of future surveillance programs for invasive species. Addressing program design within a decision-theoretic framework can lead to a better use of available resources. We show how species prevalence, its detectability, and the benefits derived from early detection can be considered.

SUBMITTER: Guillera-Arroita G

PROVIDER: S-EPMC4063473 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature

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Optimal surveillance strategy for invasive species management when surveys stop after detection.

Guillera-Arroita Gurutzeta G Hauser Cindy E CE McCarthy Michael A MA

Ecology and evolution 20140411 10

Invasive species are a cause for concern in natural and economic systems and require both monitoring and management. There is a trade-off between the amount of resources spent on surveying for the species and conducting early management of occupied sites, and the resources that are ultimately spent in delayed management at sites where the species was present but undetected. Previous work addressed this optimal resource allocation problem assuming that surveys continue despite detection until the ...[more]

PMID: 24963374

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Project description:BACKGROUND: Invasive aedine mosquito species have become a major issue in many parts of the world as most of them are recognised vectors or potentially involved in transmission of pathogens. Surveillance of these mosquitoes (e.g. Ae. aegypti, Yellow fever mosquito, Aedes albopictus, Asian tiger mosquito) is mainly done by collecting eggs using ovitraps and by identification of the larvae hatched in the laboratory. In order to replace this challenging and laborious procedure, we have evaluated matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) for easy and rapid species identification. METHODS: Individual protein profiles were generated using five eggs each of nine aedine species (Ae. aegypti, Ae. albopictus, Ae. atropalpus, Ae. cretinus, Ae. geniculatus, Ae. japonicus, Ae. koreicus, Ae. phoeniciae, Ae. triseriatus) from various geographical origins, and species-specific biomarker mass sets could be generated. A blinded validation using our reference data base for automated egg identification was performed. In addition, pools of 10 aedine eggs (132 two-species and 18 three-species pools) in different ratios were evaluated. RESULTS: Specific biomarker mass sets comprising 18 marker masses could be generated for eggs of nine container-inhabiting aedine species, including all the major invasive and indigenous species of Europe and North America. Two additional masses shared by all investigated aedine species are used as internal calibrators. Identification of single eggs was highly accurate (100% specificity, 98.75% sensitivity), and this method is also of value for the identification of species in pools of ten eggs. When mixing two or three species, all were identified in all pools in at least 2 or 1 of the 4 loaded replicates, respectively, if the "lesser abundant" species in the pool accounted for three or more eggs. CONCLUSIONS: MALDI-TOF MS, which is widely applied for routine identification of microorganisms in clinical microbiology laboratories, is also suited for robust, low-cost and high throughput identification of mosquito vectors in surveillance programmes. This tool can further be developed to include a wide spectrum of arthropods but also other Metazoa for which surveillance is required, and might become the method of choice for their centralised identification via online platforms.

Project description:Biological invasions are not only a major threat to biodiversity, they also have major impacts on local economies and agricultural production systems. Once established, the connection of local populations into metapopulation networks facilitates dispersal at landscape scales, generating spatial dynamics that can impact the outcome of pest-management actions. Much planning goes into landscape-scale invasive species management. However, effective management requires knowledge on the interplay between metapopulation network topology and management actions. We address this knowledge gap using simulation models to explore the effectiveness of two common management strategies, applied across different extents and according to different rules for selecting target localities in metapopulations with different network topologies. These management actions are: (i) general population reduction, and (ii) reduction of an obligate resource. The reduction of an obligate resource was generally more efficient than population reduction for depleting populations at landscape scales. However, the way in which local populations are selected for management is important when the topology of the metapopulation is heterogeneous in terms of the distribution of connections among local populations. We tested these broad findings using real-world scenarios of European rabbits (Oryctolagus cuniculus) infesting agricultural landscapes in Western Australia. Although management strategies targeting central populations were more effective in simulated heterogeneous metapopulation structures, no difference was observed in real-world metapopulation structures that are highly homogeneous. In large metapopulations with high proximity and connectivity of neighbouring populations, different spatial management strategies yield similar outcomes. Directly considering spatial attributes in pest-management actions will be most important for metapopulation networks with heterogeneously distributed links. Our modelling framework provides a simple approach for identifying the best possible management strategy for invasive species based on metapopulation structure and control capacity. This information can be used by managers trying to devise efficient landscape-oriented management strategies for invasive species and can also generate insights for conservation purposes.

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Optimal surveillance strategy for invasive species management when surveys stop after detection.

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Optimal surveillance strategy for invasive species management when surveys stop after detection.

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