Operating as ecological engineers, the increased distribution and abundance of wild hogs (Sus scrofa) has caused considerable socio-economic impacts. The international scope of economic research providing wild hog damage estimates are often confined to agricultural crops, while damage estimates among forest plantations are lacking. In Alabama, private landowners hold the majority of timberland acreage and are less equipped to absorb financial losses from wild hog damage than their industrial counterparts. A survey was conducted to estimate the economic impact of wild hogs, namely costs of damage and control, to privately owned forestlands. The survey was distributed in the summer of 2016 to a sample of 1160 private landowners across the State. A 35% response rate was achieved from the sampled group. Survey results indicated in 2013 to 2015 longleaf pine (Pinus palustris) and loblolly pine (Pinus taeda) were the only species damaged by wild hogs. Wild hogs caused damage to 34 and 13% of forest acres in longleaf and loblolly plantations, respectively. At $50.40 per acre, costs associated with replanting damaged longleaf acres were double those for loblolly. Survey results suggest the southern half of Alabama holds the largest wild hog populations and sustained the most damage to forest stands. Consequently, landowners in this region invested the most capital on control methods where the average cost per control technique ranged from $12–2750. Additionally, landowners who did not have wild hogs on their property were willing to pay around $14 per acre more for eradication than those with. We hope the findings from this survey will provide a better understanding of the economic impact of wild hogs in young forest plantations.

Objectives This study used computer simulation modeling to estimate and compare costs of different free-roaming cat (FRC) management options (lethal and non-lethal removal, trap–neuter–return, combinations of these options and no action) and their ability to reduce FRC population abundance in open demographic settings. The findings provide a resource for selecting management approaches that are well matched for specific communities, goals and timelines, and they represent use of best available science to address FRC issues. Methods Multiple FRC management approaches were simulated at varying intensities using a stochastic individual-based model in the software package Vortex. Itemized costs were obtained from published literature and expert feedback. Metrics generated to evaluate and compare management scenarios included final population size, total cost and a cost efficiency index, which was the ratio between total cost and population size reduction. Results Simulations suggested that cost-effective reduction of FRC numbers required sufficient management intensity, regardless of management approach, and greatly improved when cat abandonment was minimized. Removal yielded the fastest initial reduction in cat abundance, but trap–neuter–return was a viable and potentially more cost-effective approach if performed at higher intensities over a sufficient duration. Of five management scenarios that reduced the final population size by approximately 45%, the three scenarios that relied exclusively on removal were considerably more expensive than the two scenarios that relied exclusively or primarily on sterilization. Conclusions and relevance FRCs present a challenge in many municipalities, and stakeholders representing different perspectives may promote varying and sometimes incompatible population management policies and strategies. Although scientific research is often used to identify FRC impacts, its use to identify viable, cost-effective management solutions has been inadequate. The data provided by simulating different interventions, combined with community-specific goals, priorities and ethics, provide a framework for better-informed FRC policy and management outcomes.

Populations of invasive species often spread heterogeneously across a landscape, consisting of local populations that cluster in space but are connected by dispersal. A fundamental dilemma for invasive species control is how to optimally allocate limited fiscal resources across local populations. Theoretical work based on perfect knowledge of demographic connectivity suggests that targeting local populations from which migrants originate (sources) can be optimal. However, demographic processes such as abundance and dispersal can be highly uncertain, and the relationship between local population density and damage costs (damage function) is rarely known. We used a metapopulation model to understand how observational uncertainty in abundance and connectivity, and imperfect knowledge of the damage function, affect return on investment (ROI) for optimal control strategies. Budget, observational uncertainty, and the damage function had strong effects on the optimal resource allocation strategy. Uncertainty in dispersal probability was the least important determinant of ROI. The damage function determined which resource prioritization strategy was optimal when connectivity was symmetric but not when it was asymmetric. When connectivity was asymmetric, prioritizing source populations had a higher ROI than allocating effort equally across local populations, regardless of the damage function, but uncertainty in connectivity structure and abundance reduced ROI of the optimal prioritization strategy by 57% on average depending on the control budget. With low budgets (monthly removal rate of 6.7% of population), there was little advantage to prioritizing resources, especially when connectivity was high or symmetric, and observational uncertainty had only minor effects on ROI. Allotting funding for improved monitoring appeared to be most important when budgets were moderate (monthly removal of 13-20% of the population). Our result showed that multiple sources of observational uncertainty should be considered concurrently for optimizing ROI. Accurate estimates of connectivity direction and abundance were more important than accurate estimates of dispersal rates. Developing cost-effective surveillance methods to reduce observational uncertainties, and quantitative frameworks for determining how resources should be spatially apportioned to multiple monitoring and control activities are important and challenging future directions for optimizing ROI for invasive species control programs.

Invasive alien species are a significant threat to both economic and ecological systems. Identifying the processes that give rise to invasive populations is essential for implementing effective control strategies. We conducted an ancestry analysis of invasive feral swine ( Sus scrofa , Linnaeus, 1758), a highly destructive ungulate that is widely distributed throughout the contiguous United States, to describe introduction pathways, sources of newly emergent populations and processes contributing to an ongoing invasion. Comparisons of high‐density single nucleotide polymorphism genotypes for 6,566 invasive feral swine to a comprehensive reference set of S. scrofa revealed that the vast majority of feral swine were of mixed ancestry, with dominant genetic associations to Western heritage breeds of domestic pig and European populations of wild boar. Further, the rapid expansion of invasive feral swine over the past 30 years was attributable to secondary introductions from established populations of admixed ancestry as opposed to direct introductions of domestic breeds or wild boar. Spatially widespread genetic associations of invasive feral swine to European wild boar deviated strongly from historical S. scrofa introduction pressure, which was largely restricted to domestic pigs with infrequent, localized wild boar releases. The deviation between historical introduction pressure and contemporary genetic ancestry suggests wild boar‐hybridization may contribute to differential fitness in the environment and heightened invasive potential for individuals of admixed domestic pig–wild boar ancestry.

A critical element in effective wildlife management is monitoring the status of wildlife populations; however, resources to monitor wildlife populations are typically limited. We compared cost effectiveness of three common population estimation methods (i.e. non-invasive DNA sampling, camera sampling, and sampling from trapping) by applying them to wild pigs (Sus scrofa) across three habitats in South Carolina, U.S.A where they are invasive. We used mark-recapture analyses for fecal DNA sampling data, spatially-explicit capture-recapture analyses for camera sampling data, and a removal analysis for removal sampling from trap data. Density estimates were similar across methods. Camera sampling was the least expensive, but had large variances. Fecal DNA sampling was the most expensive, although this technique generally performed well. We examined how reductions in effort by method related to increases in relative bias or imprecision. For removal sampling, the largest cost savings while maintaining unbiased density estimates was from reducing the number of traps. For fecal DNA sampling, a reduction in effort only minimally reduced costs due to the need for increased lab replicates while maintaining high quality estimates. For camera sampling, effort could only be marginally reduced before inducing bias. We provide a decision tree for researchers to help make monitoring decisions.

We report the results of a survey on wild pigs (Sus scrofa) damage to livestock producers in 13 US states (Alabama, Arkansas, California, Florida, Georgia, Louisiana, Mississippi, Missouri, North Carolina, Oklahoma, South Carolina, Tennessee, Texas). The survey was distributed by the USDA National Agricultural Statistical Service in the summer of 2017 to a sample of livestock producers in the 13-state region. Findings indicate that predation and disease-related damage can be substantial in certain states and for certain types of livestock. In particular, damage to cattle operations in Texas and Arkansas was substantially higher than damage in other states and types of livestock operations. When extrapolated to livestock producers across the entire 13-state region, we estimated that damages sum to an annual cost of about $40 million. We hope findings from this survey will help guide control efforts and research, as well as serve as a benchmark against which the effectiveness of future control efforts can be measured.

We present a new modeling tool that can be used to maximize the impact of canine rabies management resources that are available at the local level. The model is accessible through a web-based interface that allows for flexibility in the management strategies that can be investigated. Rabies vaccination, sterilization, chemo-contraception, and euthanasia can be specified and limited to specific demographic groups. Additionally, we allowed for considerable complexity in the specification of management costs. In many areas, the costs of contacting additional dogs increases as management effort increases, and this can have important strategic implications. We illustrated the application of the model by examining several alternative management strategies in an area of Mpumalanga Province, South Africa. Our results based on this dog population suggested that puppies should be vaccinated and sterilization would not be optimal if the spatial extent of management is not large (and perhaps not even then). Furthermore, given a sufficient budget, it was evident that vaccination campaigns should be repeated annually.

Cross-species disease transmission between wildlife, domestic animals and humans is an increasing threat to public and veterinary health. Wild pigs are increasingly a potential veterinary and public health threat. Here we investigate 84 pathogens and the host species most at risk for transmission with wild pigs using a network approach. We assess the risk to agricultural and human health by evaluating the status of these pathogens and the co-occurrence of wild pigs, agriculture and humans. We identified 34 (87%) OIE listed swine pathogens that cause clinical disease in livestock, poultry, wildlife, and humans. On average 73% of bacterial, 39% of viral, and 63% of parasitic pathogens caused clinical disease in other species. Non-porcine livestock in the family Bovidae shared the most pathogens with swine (82%). Only 49% of currently listed OIE domestic swine diseases had published wild pig surveillance studies. The co-occurrence of wild pigs and farms increased annually at a rate of 1.2% with as much as 57% of all farms and 77% of all agricultural animals co-occurring with wild pigs. The increasing co-occurrence of wild pigs with livestock and humans along with the large number of pathogens shared is a growing risk for cross-species transmission.

We report the results of one of the most comprehensive surveys on feral swine (Sus scrofa) damage and control in 11 US states (Alabama, Arkansas, California, Florida, Georgia, Louisiana, Mississippi, Missouri, North Carolina, South Carolina and Texas). The survey was distributed by the USDA National Agricultural Statistical Service in the summer of 2015 to a sample of producers of corn (Zea mays), soybeans (Glycine max), wheat (Triticum), rice (Oryza sativa), peanuts (Arachis hypogaea), and sorghum (Sorghum bicolor) in the 11-state region. Producers that failed to respond to the initial mailing received multiple follow-up phone calls in an attempt to minimize non-response bias, and a total of 4377 responses were obtained. Findings indicate that damage can be substantial. The highest yield loss estimates occur in peanut and corn production in the Southeast and Texas. Control efforts are common, and producers incur considerable costs from shooting and trapping efforts. Extrapolating crop damage estimates to the state-level in 10 states with reportable damage yields an estimated crop loss of $190 million. Though large, this number likely represents only a small fraction of the total damage by feral swine in the 10 states because it only includes crop damage to six crops. We hope findings from this survey will help guide control efforts and research, as well as serve as a benchmark against which the effectiveness of future control efforts can be measured.

We report the results of one of the most comprehensive surveys on feral swine damage and control in 11 U.S. states (Alabama, Arkansas, California, Florida, Georgia, Louisiana, Mississippi, Missouri, North Carolina, South Carolina, and Texas). The survey was distributed by the USDA National Agricultural Statistical Service in the summer of 2015 to a sample of producers of corn, soybeans, wheat, rice, peanuts, and sorghum in the 11 states listed above. A total of 4,377 responses were obtained. Findings indicate that damage caused by feral swine can be substantial. The highest yield loss estimates occur in peanut and corn production in the Southeast U.S. and Texas. We hope findings from this survey will help guide control efforts and research, as well as serve as a benchmark against which the effectiveness of future control efforts can be measured.