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Brian Patrick Folt

Publications and source records attributed to Brian Patrick Folt.

3 recordsLinked to original sources

Effects of mountain lion predation on reducing feral horse population growth rates: Panacea or pipedream?

A goal of applied ecology is to evaluate how demographic rates contribute to population growth and how demography might be manipulated to achieve management objectives. In western North America, many feral horse ( Equus caballus ) populations occupying public lands are protected by federal law and managed for site-specific numerical targets. However, feral horses can exhibit population growth rates exceeding 20% per yr, which can lead to overpopulation, and therefore conflict with other permitted land uses. In response, some stakeholder groups have advocated for natural solutions to the problem of rapid growth and overabundance. Mountain lion ( Puma concolor ) predation has been hypothesized to have suppressive effects on horse population growth rates under some conditions. Here, we evaluated the degree to which this phenomenon might reduce feral horse growth rates using elasticity analysis, scenario analysis with simulations, and an empirical state-space model for a horse population in southeastern Nevada subject to chronic predation. Age-specific elasticities revealed that annual population growth rates (λ) were more sensitive to perturbations in foal and yearling survival rates than for older age-classes. This finding, in conjunction with empirical measures indicating that foals comprised approximately 60% of horses killed by mountain lions, suggests that predation may have greater potential to reduce horse population growth rates than previously recognized. Scenario analysis predicted that horse populations could decrease to target levels within 10 years if predation reduced: (1) annual foal survival by 80% each year, or (2) annual survival rates of foals, yearlings, and 2-year olds by >60%. The state-space model indicated that the heavily predated Nevada horse population experienced positive population growth during 2022 and 2023 (λ = 1.07, both years). Using information on known predation-caused mortalities from 2020–2021, our model predicted that population growth rate in the absence of predation (‘predicted λ’) would have been approximately twice as high (predicted λ 2020 = 1.14; predicted λ 2021 = 1.14 in 2021). Taken together, our results suggest that predation is unlikely to singularly induce stable or negative population growth of feral horses. That said, our findings suggest two aspects of predation that may benefit resource managers. First, chronic predation may reduce λ, thereby increasing the time required for populations to either recover from declines, or exceed management objectives; and second, predation may be most effective in achieving management objectives for horse populations when combined with other interventions, such as removals or fertility control treatments.

Nevada↗

PopEquus: a predictive modeling tool to support management decisions for free-roaming horse populations

Feral horse ( Equus caballus ) population management is a challenging problem around the world because populations often exhibit density-independent growth, can exert negative ecological effects on ecosystems, and require great cost to be managed. However, strong value-based connections between people and horses cause contention around management decisions. To help make informed decisions, natural resource managers might benefit from more detailed understanding of how horse management alternatives, including combinations of removals and fertility control methods, could achieve objectives of sustainable, multiple-use ecosystems while minimizing overall horse handling and fiscal costs. Here, we describe a modeling tool that simulates horse management alternatives and estimates trade-offs in predicted metrics related to population size, animal handling, and direct costs of management. The model considers six management actions for populations (removals for adoption or long-term holding; fertility control treatment with three vaccines, intrauterine devices, and mare sterilization), used alone or in combination. We simulated 19 alternative management scenarios at 2-, 3-, and 4-year management return intervals and identified efficiency frontiers among alternatives for trade-offs between predicted population size and six management metrics. Our analysis identified multiple alternatives that could maintain populations within target population size ranges, but some alternatives (e.g., removal and mare sterilization, removal and GonaCon treatment) performed better at minimizing overall animal handling requirements and management costs. Cost savings increased under alternatives with more effective, longer lasting fertility control techniques over longer management intervals compared with alternatives with less-effective, shorter lasting fertility control techniques. We built a user-friendly website application, PopEquus , that decision makers and interested individuals can use to simulate management alternatives and evaluate trade-offs among management and cost metrics. Our results and website application provide quantitative trade-off tools for horse population management decisions and can help support value-based management decisions for wild or feral horse populations and ecosystems at local and regional scales around the world.

Ecosphere↗

Multi-objective modeling as a decision-support tool for free-roaming horse management

Decisions related to controversial problems in natural resource management receive the greatest support when they account for multiple objectives of stakeholders in a structured and transparent fashion. In the United States, management of free-roaming horses ( Equus caballus ; horses) is a controversial multiple-objective problem because disparate stakeholder groups have varying objectives and opinions about how to manage fast-growing horse populations in ways that sustain both natural ecosystems and healthy horses. Despite much decision-support research on management alternatives that prevent excessive population size or cost, horse management decisions still receive resistance from a variety of stakeholder groups, potentially because decisions fail to explicitly or transparently account for multiple objectives of diverse stakeholders. Here, we used a predictive model for horse populations to evaluate the degree to which alternative management strategies involving removals and fertility control treatment with the immunocontraceptive vaccine PZP-22 maximize 4 objectives in horse management: maximize ecosystem health, maximize horse health, minimize effects on horse behavior, and minimize management cost. We simulated scenarios varying in management action, frequency, magnitude, and starting population size over a 10-year interval and evaluated scenario performance with a weighted multiple-objective utility reward function. Management involving high-magnitude removals along with PZP-22 treatment generally outperformed other alternatives by achieving higher reward relative to alternatives in 2 scenario analyses. Simulation of 1,372 scenarios at 5 starting population sizes generally found that management with biannual removals and 2 doses of PZP-22 treatment for half of eligible females during years 1 and 5 generated the most rewarding outcomes. However, a removal scenario with more frequent PZP-22 application generated the greatest reward when starting population size was already within target population size range. Our paper demonstrates how values and objectives of diverse stakeholders can be used to support management decisions in ways that might lead to greater acceptance of decisions by a broad array of stakeholder groups.

Human-Wildlife Interactions↗