A hierarchical framework for estimating abundance and population growth from imperfectly observed removals

Stevens, Bryan S.; Bence, James R.; Luukkonen, David R.; Porter, William F.

doi:10.1002/ecs2.3131

Cited by 3 publications

(4 citation statements)

References 52 publications

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“…In addition to incorporating multiple removal methods, our approach allows for abundance to vary with open population demographics (i.e., births, deaths, immigration, and emigration), and for population estimation at discrete periods across time, in line with how invasive species management is often conducted. This advance, similar to Link et al (2018) and Stevens et al (2020), lets us match the monitoring method with the management method, and continually track population changes in time. The standard removal model would need to be run separately for different removal periods that do not have demographic closure.…”

Section: Discussionmentioning

confidence: 99%

An efficient method of evaluating multiple concurrent management actions on invasive populations

Davis

Farrar

Jump

et al. 2022

Ecological Applications

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Evaluating the efficacy of management actions to control invasive species is crucial for maintaining funding and to provide feedback for the continual improvement of management efforts. However, it is often difficult to assess the efficacy of control methods due to limited resources for monitoring. Managers may view effort on monitoring as effort taken away from performing management actions. We developed a method to estimate invasive species abundance, evaluate management effectiveness, and evaluate population growth over time from a combination of removal activities (e.g., trapping, ground shooting) using only data collected during removal efforts (method of removal, date, location, number of animals removed, and effort). This dynamic approach allows for abundance estimation at discrete time points and the estimation of population growth between removal periods. To test this approach, we simulated over 1 million conditions, including varying the length of the study, the size of the area examined, the number of removal events, the capture rates, and the area impacted by removal efforts. Our estimates were unbiased (within 10% of truth) 81% of the time and were correlated with truth 91% of the time. This method performs well overall and, in particular, at monitoring trends in abundances over time. We applied this method to removal data from Mingo National Wildlife Refuge in Missouri from December 2015 to September 2019, where the management objective is elimination. Populations of feral swine on Mingo NWR have fluctuated over time but showed marked declines in the last 3–6 months of the time series corresponding to increased removal pressure. Our approach allows for the estimation of population growth across time (from both births and immigration) and therefore, provides a target removal rate (above that of the population growth) to ensure the population will decline. In Mingo NWR, the target monthly removal rate is 18% to cause a population decline. Our method provides advancement over traditional removal modeling approaches because it can be applied to evaluate management programs that use a broad range of removal techniques concurrently and whose management effort and spatial coverage vary across time.

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Section: Discussionmentioning

confidence: 99%

An efficient method of evaluating multiple concurrent management actions on invasive populations

Davis

Farrar

Jump

et al. 2022

Ecological Applications

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“…In either case, mean CPUE of the more avid hunters who remain may be bolstered. Spring, male‐only turkey hunting potentially fits both scenarios given male turkeys are likely to be clumped across the landscape during spring (Pollentier et al 2019) and harvests tend to be concentrated amongst a small percentage of overall turkey hunters (Godwin et al 1997) who may not necessarily be distributed in patterns corresponding to turkey abundance (Clawson et al 2015, Stevens et al 2020). Given male turkeys proclivity to vocalize, even in sparse, low‐density populations skilled hunters can target the limited individual male turkeys available, thereby reinforcing CPUE even as the overall availability of males drops.…”

Section: Discussionmentioning

confidence: 99%

“…The relationship between CPUE and turkey population abundance has been established from band‐recovery modeling (Lint et al 1995), and variations in CPUE can be predicted by recruitment surveys (Butler et al 2015). In addition, catch‐per‐unit‐effort has been used in the development of turkey abundance estimates (Clawson et al 2015, Stevens et al 2020) and to demonstrate synchrony across metapopulations (Wang 2018). Moreover, collection of turkey hunter CPUE has been recommended to state wildlife agencies to ensure harvest trends provide reasonable inference about population status (Byrne et al 2015).…”

mentioning

confidence: 99%

Connecting hunt outcomes to the demographics, behaviors, and experiences of wild turkey hunters in Mississippi

Butler

Wang

2022

Wildlife Society Bulletin

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The ability to evaluate population trends through time is essential to successful conservation of wildlife. Directly estimating abundance of eastern wild turkeys (Meleagris gallopavo silvestris) is difficult, with few practical options for wide-scale population monitoring. As a result, managers often rely on abundance indices derived from hunter harvest. Catchper-unit-effort (CPUE) is a commonly used metric which standardizes harvest totals and has been shown to track turkey abundance, but its use is predicated on an assumption of spatially and temporally consistent hunter efficiency. From 2015-2018, we surveyed avid turkey hunters in Mississippi to evaluate mechanisms driving harvest efficiency. We questioned each hunter about their demographics and behaviors, collected observations from their hunts, and used 2-stage hurdle models to relate these variables to individual CPUE. Hunter attributes had variable effects on hunt outcomes. Hunter age had a significant positive effect on the probability of harvesting at least one turkey (an approximate 2% gain in success per year of age) yet was only weakly associated with CPUE of successful hunters. When considering only successful hunters, the percentage of hunts in which a turkey was heard, and the standardized index of total turkey observations were related to CPUE. Additionally, we determined the tendency for hunters to miss a turkey during the hunting season decreased with increasing hunter age. Our results indicate individual characteristics subject to temporal change play a role in determining CPUE and thereby have the potential to mask

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“…births, deaths, immigration, and emigration), and for population estimation at discrete periods across time, in line with how invasive species management is often conducted. This advance, similar to Link et al (2018) and Stevens et al (2020), lets us match the monitoring method with the management method, and continually track population changes in time. The standard removal model would need to be run separately for different removal periods that do not have demographic closure.…”

Section: Discussionmentioning

confidence: 99%

An efficient method of evaluating multiple concurrent management actions on invasive populations

Davis

Farrar

Jump

et al. 2021

Preprint

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Evaluation of the efficacy of management actions to control invasive species is crucial for maintaining funding and to provide feedback for the continual improvement of management efficiency. However, it is often difficult to assess the efficacy of control methods due to limited resources for monitoring. To evaluate management actions there is often a trade-off in effort aimed at performing management actions and effort aimed at collecting monitoring data to evaluate management actions. We developed a method to estimate invasive species abundance, evaluate management effectiveness, and evaluate population growth overtime from a combination of removal activities (e.g., aerial gunning, trapping, ground shooting) using only data collected during removal efforts (the method of removal, the date, location, number of animals removed, and the effort). This dynamic approach allows for estimating abundance at discrete time points and the estimation of population growth between removal periods. We applied this method to removal data from Mingo National Wildlife Refuge in Missouri from December 2015 to September 2019, where the management objective is elimination. Populations of feral swine on Mingo NWR have fluctuated over time but have shown more marked declines in the last 3-6 months. More dramatic declines were observed in the center of the refuge. To counteract population growth (from both births and immigration) the percent of the population of feral swine removed monthly must be greater than the growth rate. On average, we found that removing 10% of the population monthly had only a 50% chance of causing a population decline, whereas removing 15% of the population monthly had a 95% chance of causing a population decline. Our method provides advancement over traditional removal modeling approaches because it can be applied to evaluate management programs that use a broad range of removal techniques concurrently and whose management effort and spatial coverage vary across time.

show abstract

A hierarchical framework for estimating abundance and population growth from imperfectly observed removals

Cited by 3 publications

References 52 publications

An efficient method of evaluating multiple concurrent management actions on invasive populations

An efficient method of evaluating multiple concurrent management actions on invasive populations

Connecting hunt outcomes to the demographics, behaviors, and experiences of wild turkey hunters in Mississippi

An efficient method of evaluating multiple concurrent management actions on invasive populations

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