Assessing the quality of offshore Binomial sampling biosecurity inspections using onshore inspections.

Introduction of pests and diseases through trade is one of the main socio-ecological challenges worldwide. Although Binomial sampling inspection at the border can reduce pest entry risk, it is common for consignments to fail inspection, wasting resources for both exporter and importer. Outsourcing the inspection to the exporting country could reduce the cost of inspection for both parties. However, there is then a need to assess the quality of the offshore inspection. In this paper, we develop an inverse method combining past inspection data on the pathway, an onshore inspection sample, and the Beta-Binomial model to infer the sample size of the offshore inspection. We illustrate the method on two case studies: the importation of live plants through germplasm into Australia and the importation of pelleted seeds in New Zealand. In these case studies, we found that detecting four to five infested units in a single onshore inspection was typically sufficient to significantly doubt the presence of a compliant offshore inspection. We also ran a simulation experiment to quantify the statistical power to reject or accept the presence of compliant offshore inspection in practice: In highly infested pathways, we could detect the absence of offshore inspections after inspecting five consignments onshore. Less infested pathways required inspecting 20 to 60 consignments onshore. Our study demonstrates that Binomial sampling onshore can be used to assess the quality of offshore inspections.

Multiple ecological processes underpin the eruptive dynamics of small mammals: House mice in a semi-arid agricultural environment.

Mouse plagues are a regular feature of grain-growing regions, particularly in southern and eastern Australia, yet it is not clear what role various ecological processes play in the eruptive dynamics generating these outbreaks.This research was designed to assess the impact of adding food, water, and cover in all combinations on breeding performance, abundance, and survival of mouse populations on a typical cereal growing farm in northwestern Victoria.Supplementary food, water, and cover were applied in a 2 × 2 × 2 factorial design to 240 m sections of internal fence lines between wheat or barley crops and stubble/pasture fields over an 11-month period to assess the impact on mouse populations.We confirmed that mice were eating the additional food and were accessing the water provided. We did not generate an outbreak of mice, but there were some significant effects from the experimental treatments. Additional food increased population size twofold and improved apparent survival. Both water and cover improved breeding performance. Food and cover increased apparent survival.Our findings confirm that access to food, water, and cover are necessary for outbreaks, but are not sufficient. There remain additional factors that are important in generating mouse plagues, particularly in a climatically variable agricultural environment.

When Does Poor Governance Presage Biosecurity Risk?

Border inspection, and the challenge of deciding which of the tens of millions of consignments that arrive should be inspected, is a perennial problem for regulatory authorities. The objective of these inspections is to minimize the risk of contraband entering the country. As an example, for regulatory authorities in charge of biosecurity material, consignments of goods are classified before arrival according to their economic tariff number. This classification, perhaps along with other information, is used as a screening step to determine whether further biosecurity intervention, such as inspection, is necessary. Other information associated with consignments includes details such as the country of origin, supplier, and importer, for example. The choice of which consignments to inspect has typically been informed by historical records of intercepted material. Fortunately for regulators, interception is a rare event; however, this sparsity undermines the utility of historical records for deciding which containers to inspect. In this article, we report on an analysis that uses more detailed information to inform inspection. Using quarantine biosecurity as a case study, we create statistical profiles using generalized linear mixed models and compare different model specifications with historical information alone, demonstrating the utility of a statistical modeling approach. We also demonstrate some graphical model summaries that provide managers with insight into pathway governance.

Non-bee insects are important contributors to global crop pollination.

Wild and managed bees are well documented as effective pollinators of global crops of economic importance. However, the contributions by pollinators other than bees have been little explored despite their potential to contribute to crop production and stability in the face of environmental change. Non-bee pollinators include flies, beetles, moths, butterflies, wasps, ants, birds, and bats, among others. Here we focus on non-bee insects and synthesize 39 field studies from five continents that directly measured the crop pollination services provided by non-bees, honey bees, and other bees to compare the relative contributions of these taxa. Non-bees performed 25-50% of the total number of flower visits. Although non-bees were less effective pollinators than bees per flower visit, they made more visits; thus these two factors compensated for each other, resulting in pollination services rendered by non-bees that were similar to those provided by bees. In the subset of studies that measured fruit set, fruit set increased with non-bee insect visits independently of bee visitation rates, indicating that non-bee insects provide a unique benefit that is not provided by bees. We also show that non-bee insects are not as reliant as bees on the presence of remnant natural or seminatural habitat in the surrounding landscape. These results strongly suggest that non-bee insect pollinators play a significant role in global crop production and respond differently than bees to landscape structure, probably making their crop pollination services more robust to changes in land use. Non-bee insects provide a valuable service and provide potential insurance against bee population declines.

Estimating the abundance of mouse populations of known size: promises and pitfalls of new methods.

Knowledge of animal abundance is fundamental to many ecological studies. Frequently, researchers cannot determine true abundance, and so must estimate it using a method such as mark-recapture or distance sampling. Recent advances in abundance estimation allow one to model heterogeneity with individual covariates or mixture distributions and to derive multimodel abundance estimators that explicitly address uncertainty about which model parameterization best represents truth. Further, it is possible to borrow information on detection probability across several populations when data are sparse. While promising, these methods have not been evaluated using mark-recapture data from populations of known abundance, and thus far have largely been overlooked by ecologists. In this paper, we explored the utility of newly developed mark-recapture methods for estimating the abundance of 12 captive populations of wild house mice (Mus musculus). We found that mark-recapture methods employing individual covariates yielded satisfactory abundance estimates for most populations. In contrast, model sets with heterogeneity formulations consisting solely of mixture distributions did not perform well for several of the populations. We show through simulation that a higher number of trapping occasions would have been necessary to achieve good estimator performance in this case. Finally, we show that simultaneous analysis of data from low abundance populations can yield viable abundance estimates.