Using ring‐recovery and within‐season recapture data to estimate fecundity and population growth

Arnold, Todd W.

doi:10.1002/ece3.4506

Cited by 10 publications

(13 citation statements)

References 42 publications

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“…Nonetheless, band‐recovery data have been used to only inform survival, despite the fact that the numbers of banded juveniles and adults are counts of different ages and thus can provide information for productivity estimation. In this study, we utilized banding information to estimate both productivity and survival rates, as demonstrated in recent studies (Arnold, ; Specht & Arnold, ). Even though such practices violate the assumption of independent data inputted to the IPM, there is evidence that dependent data will not lead to increased bias or uncertainty in parameter estimates (Abadi, Gimenez, Arlettaz, & Schaub, ).…”

Section: Discussionmentioning

confidence: 99%

“…The proportion of juvenile females in the banding data does not necessarily represent the proportion of juvenile females in the population due to potential differences in the capture probability of juvenile and adult females. To correct for this potential bias, we created an additional parameter, denoted as

q_{i, t}^{false[obs false]}

, and let

q_{i, t}^{[obs]} = (γ_{i, t} ν) / (1 + γ_{i, t} ν)

, in which ν was the vulnerability parameter calculated as the ratio of the capture probability of juvenile females r [ jf ] to the capture probability of adult females r [ af ] (Arnold, ). The capture probability of juvenile females was estimated as

R_{t}^{[j f]} Binomial (B_{t}^{[j f]}, r^{[j f]})

, in which

B_{t}^{false[j f false]}

was the number of banded juvenile females, and

R_{t}^{false[j f false]}

was the number of live reencounters in the same year of banding, all ecostrata combined.…”

Section: Methodsmentioning

confidence: 99%

“…Similarly, the capture probability of adult females was estimated as

R_{t}^{[a f]} Binomial (B_{t}^{[a f]}, r^{[a f]})

, in which

B_{t}^{false[a f false]}

was the number of banded adult females, and

R_{t}^{false[a f false]}

was the number of same‐year live reencounters. Due to extremely limited live‐encounter data, we only considered constant r [ jf ] and r [ af ] , and used informative priors such that

logit (r^{false[j f false]})

~ Normal [logit (0.00144), 0.105] and

logit (r^{false[a f false]})

~ Normal [logit (0.00072), 0.150], according to estimates from Arnold (). We then considered the number of banded pintails as realized observations of

q_{i, t}^{false[obs false]}

such that

B_{i, t}^{[j f]} Binomial (B_{i, t}^{[j f + a f]}, q_{i, t}^{[obs]})

, in which

B_{t}^{false[j f false]}

was the number of banded juvenile females in ecostratum i and year t , and

B_{i, t}^{false[j f + a f false]}

was the number of banded juvenile and adult females combined.…”

Section: Methodsmentioning

confidence: 99%

“…Also, we first tried to fit a model with age‐ and sex‐specific survival, but juvenile survival parameters would not converge, possibly due to the small sample size of ecostratum‐specific juvenile bandings. Because previous studies did not find evidence for age‐specific survival (Arnold, ; Bartzen & Dufour, ), but see Ref. Flint, Grang, and Rockwell (, we only considered sex‐specific survival and assumed that juveniles had the same survival probabilities as adults of the same sex.…”

Section: Methodsmentioning

confidence: 99%

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Land‐use change increases climatic vulnerability of migratory birds: Insights from integrated population modelling

Zhao

Arnold

Devries

et al. 2019

Journal of Animal Ecology

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Knowledge of land‐use patterns that could affect animal population resiliency or vulnerability to environmental threats such as climate change is essential, yet the interactive effects of land use and climate on demography across space and time can be difficult to study. This is particularly true for migratory species, which rely on different landscapes throughout the year. Unlike most North American migratory waterfowl, populations of northern pintails (Anas acuta; hereafter pintails) have not recovered since the 1980s despite extended periods of abundant flooded wetlands (i.e. ponds). The mechanisms and drivers involved in this discrepancy remain poorly understood. While pintails are similar to other ducks in their dependence on ponds throughout their annual cycle, their extensive use of croplands for nesting differentiates them and makes them particularly vulnerable to changes in agricultural land use on prairie breeding grounds. Our intent was to quantify how changes in land use and ponds on breeding grounds have influenced pintail population dynamics by developing an integrated population model to analyse over five decades (1961–2014) of band‐recovery, breeding population survey, land‐use and pond count data. We focused especially on the interactive effects of pond counts and land use on pintail productivity, while accounting for density‐dependent processes. Pintail populations responded more strongly to annual variation in productivity than survival. Productivity was positively correlated with pond count and negatively correlated with agricultural intensification. Further, a positive interaction between pond count and agricultural intensification was insufficient to overcome the strong negative effect of agricultural intensification on pintail productivity across nearly all pond counts. The interaction also indicated that pintail populations were more negatively impacted by the decrease in ponds associated with climate change under higher agricultural intensification. Our results indicate that pintail populations have become more vulnerable to climate change under intensified land use, which suggests that future conservation strategies must adapt to these altered relationships. The interactive effects of land use and climate on demography should be considered more frequently in animal ecology, and integrated population models provide an adaptable framework to understand vital rates and their drivers simultaneously.

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Section: Discussionmentioning

confidence: 99%

q_{i, t}^{false[obs false]}

, and let

q_{i, t}^{[obs]} = (γ_{i, t} ν) / (1 + γ_{i, t} ν)

R_{t}^{[j f]} Binomial (B_{t}^{[j f]}, r^{[j f]})

, in which

B_{t}^{false[j f false]}

was the number of banded juvenile females, and

R_{t}^{false[j f false]}

was the number of live reencounters in the same year of banding, all ecostrata combined.…”

Section: Methodsmentioning

confidence: 99%

“…Similarly, the capture probability of adult females was estimated as

R_{t}^{[a f]} Binomial (B_{t}^{[a f]}, r^{[a f]})

, in which

B_{t}^{false[a f false]}

was the number of banded adult females, and

R_{t}^{false[a f false]}

was the number of same‐year live reencounters. Due to extremely limited live‐encounter data, we only considered constant r [ jf ] and r [ af ] , and used informative priors such that

logit (r^{false[j f false]})

~ Normal [logit (0.00144), 0.105] and

logit (r^{false[a f false]})

~ Normal [logit (0.00072), 0.150], according to estimates from Arnold (). We then considered the number of banded pintails as realized observations of

q_{i, t}^{false[obs false]}

such that

B_{i, t}^{[j f]} Binomial (B_{i, t}^{[j f + a f]}, q_{i, t}^{[obs]})

, in which

B_{t}^{false[j f false]}

was the number of banded juvenile females in ecostratum i and year t , and

B_{i, t}^{false[j f + a f false]}

was the number of banded juvenile and adult females combined.…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Land‐use change increases climatic vulnerability of migratory birds: Insights from integrated population modelling

Zhao

Arnold

Devries

et al. 2019

Journal of Animal Ecology

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“…Although survival is typically the demographic rate of interest, these data can also be used to provide indices or estimates of population sizes, productivity, and population growth rates (Arnold 2018, Wilson et al 2018; estimate demographic contributions to population growth (Pradel 1996, Nichols et al 2000a; identify spatial and temporal variability in demographic rates (Saracco et al 2010); and compare results with other sampling protocols (Saracco et al 2008). For harvested species, it is also possible to estimate the population size via the Lincoln estimator (Lincoln 1930, Alisauskas et al 2009).…”

Section: Beyond Counts: Demographicsmentioning

confidence: 99%

Monitoring boreal avian populations: how can we estimate trends and trajectories from noisy data?

Roy¹,

Michel²,

Handel³

et al. 2019

ACE

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Avian Conservation and Ecology 14(2): 8 http://www.ace-eco.org/vol14/iss2/art8/ à différents stades de leur cycle de vie annuel. Ces facteurs sont souvent structurés de manière hiérarchique et peuvent influencer les populations aux niveaux local, régional ou continental. Certains des défis associés à la délimitation des populations et l'identification des facteurs qui influencent les populations peuvent être traités à l'aide de la multitude de méthodes d'échantillonnage et d'analyse disponibles pour examiner l'évolution de la population au fil du temps. Le choix de méthodes d'analyse appropriées dépend des objectifs de l'étude et de la nature des données, par exemple des populations uniques ou multiples, les enquêtes répétées ou basées sur des comptes ou les taux démographiques. Les progrès récents des modèles de populations hiérarchiques et intégrés ont fait de certaines de ces approches analytiques les orientations les plus prometteuses pour le développement des méthodes futures. Toutefois, ces outils requièrent d'importants jeux de données ; or, l'acquisition de données suffisantes sur les populations aviaires et de variables d'explication potentielles est complexe dans la forêt boréale. Si l'on veut surmonter les défis actuels à la surveillance des oiseaux dans la forêt boréale, il convient de consacrer des efforts importants à l'intégration et à la mise à disposition des données existantes. Le renforcement des efforts d'enquête portant sur des espèces multiples jouera également un rôle important. La mise en oeuvre de programmes d'échantillonnage équilibrés avec un modèle à panel rotatif pourrait équilibrer les compromis entre réplication spatiale ou temporelle moyennant un coût raisonnable. L'amélioration de l'accès aux co-variables environnementales explicites sur le plan spatial et temporel permettrait en outre d'élaborer des modèles de population mécaniques qui amélioreront notre compréhension de la dynamique des populations d'oiseaux migrateurs. Enfin, compte tenu du fait qu'il faut parfois de nombreuses décennies pour que les programmes de surveillance à long terme produisent des tendances fiables en matière de populations et que les priorités des organisations évoluent au fil du temps, nous pensons que des efforts collaboratifs contribueront à assurer la pérennité des nouveaux programmes de surveillance.

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Population and Harvest Dynamics of Midcontinent Sandhill Cranes

et al. 2020

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Sandhill cranes (Antigone canadensis) inhabiting the midcontinent of North America have been hunted since the 1960s under management goals of maintaining abundance, retaining geographic distribution, and maximizing sustainable harvest. Some biologists have raised concerns regarding harvest sustainability because sandhill cranes have lower reproductive rates than other game birds. We summarized demographic information in an age-structured matrix model to better understand population dynamics and harvest. Population indices and recovered harvest since the early 1980s suggest midcontinent sandhill cranes have experienced an average long-term annual growth of 0.9%; meanwhile, harvest has increased 1.8% annually. Adult survival and recruitment rates estimated from field data required modest adjustments (1-3%) so that model-derived growth rates matched growth estimated from a long-term survey (0.887 adult survival and 0.199 females/breeding female). Considering 0.9% long-term annual growth, sandhill cranes could be harvested at a rate of 6.6% if harvest was additive to natural mortality (assumed to be 0.05) or 11.3% if harvest mortality compensated for natural mortality. Life-history characteristics for long-lived organisms and demographic evidence suggested that hunter harvest was primarily additive. Differential harvest rates of segments of sandhill cranes in the midcontinent population derived from differential exposure to hunting suggested potentially unsustainable harvest for greater sandhill cranes (A. c. tabida) from 2 breeding segments. Overall, demographic evidence suggests that the harvest of sandhill cranes in the midcontinent population has been managed sustainably. Monitoring activities that reduce nuisance variation and estimate vital and harvest rates by subspecies would support continued management of sandhill cranes that are of interest to hunters and bird watchers. Published 2020. This article is a U.S. Government work and is in the public domain in the USA.

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Using ring‐recovery and within‐season recapture data to estimate fecundity and population growth

Cited by 10 publications

References 42 publications

Land‐use change increases climatic vulnerability of migratory birds: Insights from integrated population modelling

Land‐use change increases climatic vulnerability of migratory birds: Insights from integrated population modelling

Monitoring boreal avian populations: how can we estimate trends and trajectories from noisy data?

Population and Harvest Dynamics of Midcontinent Sandhill Cranes

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