Effects of Landscape and Weather on Winter Survival of Ring-Necked Pheasant Hens

Perkins, Anjeanette L.; Clark, William R.; Riley, Terry Z.; Vohs, Paul A.

doi:10.2307/3802171

Cited by 35 publications

(48 citation statements)

References 23 publications

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“…One release pen in Ireland suffered the highest rate of loss (48%) in the first 10 days after the birds left the release pen (Robertson 1988). Likewise, in the USA, pheasants were predominantly killed by foxes over their first winter, with 68% of 146 confirmed hen mortalities attributed to mammalian predators (especially red foxes) and 14% to raptors (Perkins et al 1997).…”

Section: Causes Of Loss and Mitigating Interventions Predationmentioning

confidence: 99%

“…In many cases, starvation itself does not kill the individual, but hunger can make them engage in risky foraging or dispersal behaviour or depresses their immune system. However, in especially harsh conditions such as US winters, birds may die directly from starvation, with high mortality in snowy years (Errington 1939;Perkins et al 1997). At the end of the shooting season, supplementary feed is often withdrawn (Draycott et al 1998), and changes from spring to autumn sowing of cereals (O'Connor and Shrubb, 1986) have reduced the amount or winter stubble and wasted grain available to pheasants (Hoodless et al 2001).…”

Section: Starvationmentioning

confidence: 99%

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Why do many pheasants released in the UK die, and how can we best reduce their natural mortality?

2018

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Around 60% of pheasants released for shooting in the UK, an estimated 21 million birds, do not end up at their intended fate: being shot. This constitutes wastage, raising economic, environmental and ethical questions. We review what is known of the fates of released pheasants and consider why they do not directly contribute to the numbers harvested. We focus on four main explanations: predation, disease, starvation and dispersal, and highlight other important causes of mortality. For each explanation, we attempt to attribute levels of loss and identify timings or conditions when such losses may be heaviest. We review factors that exacerbate losses and methods available to mitigate them. Opportunities for amelioration may arise at all stages of the rearing and release of pheasants and involve changes to the conditions under which eggs are produced, the way young pheasants are reared or the management of the environment into which they are released. We found few studies investigating impacts of post-release management techniques on pheasant survival outside of the breeding season within a UK context. We found that a number of less commonly deployed practices focusing on early-life, pre-release management may improve survival. Given the scale of pheasant releasing in the UK, even improvements in survival of 1% would mean that~350,000 fewer birds die of natural causes. Complementing current post-release management with proven novel pre-release management interventions could reduce the number of pheasants required for release, whilst maintaining current shooting levels. Lowering release numbers would lower financial costs, benefit the environment and reduce some ethical concerns over the release and shooting of reared pheasants.

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Section: Causes Of Loss and Mitigating Interventions Predationmentioning

confidence: 99%

Section: Starvationmentioning

confidence: 99%

Why do many pheasants released in the UK die, and how can we best reduce their natural mortality?

2018

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“…Intensive study aimed at understanding the local-and landscape-scale complexities that make up the mechanisms by which pheasant populations respond to changing ecological conditions is costly and necessarily restricted in geographic extent. Biologists from states in the northern part of the range frequently report that interactions between habitat and snowy, cold winters may be important to the survival of adults (Larsen et al 1994, Bogenschutz et al 1995, Perkins et al 1997, Gabbert et al 1999, whereas more southerly states have noted that changes in land management practices have particularly influenced the ecology of broods (Rodgers 1999). Often management of pheasants has focused on the abundance and quality of nesting habitat, along with patterns of spring temperature and rainfall, that influence nesting, chick survival, and ultimately recruitment of pheasants, as it does other gallinaceous birds (Farris et al 1977, Potts 1986, Aebischer 1990, Riley et al 1998).…”

mentioning

confidence: 99%

Sensitivity Analyses of a Population Projection Model of Ring-Necked Pheasants

Clark¹,

Bogenschutz

Tessin

2008

J Wildl Manage

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A large literature exists on population dynamics of ring‐necked pheasant (Phasianus colchicus) in North America, but there has not been an attempt to formulate a matrix model nor a sensitivity analysis of the relationships between vital rates and population finite growth rate (Λ) that can be used to guide management. We summarized demographic data available from a 5‐year field study in Iowa, USA, collected in Kossuth County (low composition of perennial habitat) and Palo Alto County (high composition of perennial habitat) into a 2‐stage (young and adult) matrix projection model. We estimated Λ1 (the dominant eigenvalue of the deterministic matrix), the stable age distribution (ω), relative reproductive value vector (n̈), other demographic parameters, and Λiid, a bootstrap estimate of growth that includes interannual variation in life history parameters. We analyzed the relative importance of vital rates on population growth rate using sensitivity and elasticity of both matrix elements and lower‐level parameters such as winter survival and nest success. We first characterized general life history using averaged data from both areas and all years that yielded Λ1 = 1.086, and a stable stage distribution of. Minimum success of the initial nesting attempt (H1) that would maintain Λ ≥ 1 under average conditions was estimated to be 42%. Changes in Λ1 were most sensitive to survival of chicks during brood rearing (SB), followed in importance by survival during the subsequent winter (SW), followed by H1. We followed the general analyses with analyses that helped us to focus on the differences in the landscapes of northwest Iowa. Λiid was ≥1 in only 9% of simulations of data from Kossuth whereas estimated Λiid was ≥1 in 88% of simulations from Palo Alto. Our analyses of the relative importance and interactions between SB, SW, and total recruitment (M, including H1 and renesting), if combined with data more specific to a local area, would guide management aimed at affecting multiple life history stages whose relative importance will vary across the landscape.

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“…Periodic (i.e., seasonal, disturbance) mortality events can have a major influence on population dynamics. For example, large snow events can cause mortality in ring-necked pheasant hens (Phasianus colchicus; Perkins et al 1997) or high flow events can cause mortality in juvenile coho salmon (Oncorhynchus kisutch; Ebersole et al 2006). Winter-and summer-fish kills where large mortality occurs over a short period of time owing to decreased dissolved oxygen levels (Hurst 2007) could be accommodated in BDMs as discrete events.…”

Section: Discussionmentioning

confidence: 99%

Semidiscrete biomass dynamic modeling: an improved approach for assessing fish stock responses to pulsed harvest events

Colvin

Pierce

Stewart

2012

Can. J. Fish. Aquat. Sci.

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Continuous harvest over an annual period is a common assumption of continuous biomass dynamics models (CBDMs); however, fish are frequently harvested in a discrete manner. We developed semidiscrete biomass dynamics models (SDBDMs) that allow discrete harvest events and evaluated differences between CBDMs and SDBDMs using an equilibrium yield analysis with varying levels of fishing mortality (F). Equilibrium fishery yields for CBDMs and SDBDMS were similar at low fishing mortalities and diverged as F approached and exceeded maximum sustained yield (F MSY ). Discrete harvest resulted in lower equilibrium yields at high levels of Frelative to continuous harvest. The effect of applying harvest continuously when it was in fact discrete was evaluated by fitting CBDMs and SDBDMs to time series data generated from a hypothetical fish stock undergoing discrete harvest and evaluating parameter estimates bias. Violating the assumption of continuous harvest resulted in biased parameter estimates for CBDM while SDBDM parameter estimates were unbiased. Biased parameter estimates resulted in biased biological reference points derived from CBDMs. Semidiscrete BDMs outperformed continuous BDMs and should be used when harvest is discrete, when the time and magnitude of harvest are known, and when F is greater than F MSY . RightsWorks produced by employees of the U.S. Government as part of their official duties are not copyrighted within the U.S. The content of this document is not copyrighted. Continuous harvest over an annual period is a common assumption of continuous biomass dynamics models (CBDMs); however, fish are frequently harvested in a discrete manner. We developed semidiscrete biomass dynamics models (SDBDMs) that allow discrete harvest events and evaluated differences between CBDMs and SDBDMs using an equilibrium yield analysis with varying levels of fishing mortality (F). Equilibrium fishery yields for CBDMs and SDBDMS were similar at low fishing mortalities and diverged as F approached and exceeded maximum sustained yield (FMSY). Discrete harvest resulted in lower equilibrium yields at high levels of F relative to continuous harvest. The effect of applying harvest continuously when it was in fact discrete was evaluated by fitting CBDMs and SDBDMs to time series data generated from a hypothetical fish stock undergoing discrete harvest and evaluating parameter estimates bias. Violating the assumption of continuous harvest resulted in biased parameter estimates for CBDM while SDBDM parameter estimates were unbiased. Biased parameter estimates resulted in biased biological reference points derived from CBDMs. Semidiscrete BDMs outperformed continuous BDMs and should be used when harvest is discrete, when the time and magnitude of harvest are known, and when F is greater than FMSY.Résumé : Si les modèles continus de dynamique de la biomasse (CBDM) partent souvent du principe que la capture est continue au cours d'une période annuelle, les prises de poissons s'effectuent fréquemment de manière discrète. Nous avon...

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Effects of Landscape and Weather on Winter Survival of Ring-Necked Pheasant Hens

Cited by 35 publications

References 23 publications

Why do many pheasants released in the UK die, and how can we best reduce their natural mortality?

Why do many pheasants released in the UK die, and how can we best reduce their natural mortality?

Sensitivity Analyses of a Population Projection Model of Ring-Necked Pheasants

Semidiscrete biomass dynamic modeling: an improved approach for assessing fish stock responses to pulsed harvest events

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