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An integrated population model for bird monitoring in North America

Overview of attention for article published in Ecological Applications, March 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

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18 tweeters
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2 Facebook pages

Citations

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19 Dimensions

Readers on

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97 Mendeley
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Title
An integrated population model for bird monitoring in North America
Published in
Ecological Applications, March 2017
DOI 10.1002/eap.1493
Pubmed ID
Authors

Farshid S. Ahrestani, James F. Saracco, John R. Sauer, Keith L. Pardieck, J. Andrew Royle

Abstract

Integrated population models (IPMs) provide a unified framework for simultaneously analyzing data sets of different types to estimate vital rates, population size, and dynamics; assess contributions of demographic parameters to population changes; and assess population viability. Strengths of an IPM include the ability to estimate latent parameters and improve the precision of parameter estimates. We present a hierarchical IPM that combines two broad-scale avian monitoring data sets; count data from the North American Breeding Bird Survey (BBS) and capture-recapture data from the Monitoring Avian Productivity and Survivorship (MAPS) program. These data sets are characterized by large numbers of sample sites and observers, factors capable of inducing error in the sampling and observation processes. The IPM integrates the data sets by modeling the population abundance as a first-order autoregressive function of the previous year's population abundance and vital rates. BBS counts were modeled as a log-linear function of the annual index of population abundance, observation effects (observer identity and first-survey-year), and overdispersion. Vital rates modeled included adult apparent survival, estimated from a transient Cormack-Jolly-Seber model using MAPS data, and recruitment (surviving hatched birds from the previous season + dispersing adults) estimated as a latent parameter. An assessment of the IPM demonstrated it could recover true parameter values from 200 simulated data sets. The IPM was applied to data sets (1992-2008) of two bird species, gray catbird (Dumetella carolinensis) and wood thrush (Hylocichla mustelina) in the New England/Mid-Atlantic coastal Bird Conservation Region of the USA. The gray catbird population was relatively stable (trend 0.4% yr(-1) ), while the wood thrush population nearly halved (trend -4.5% yr(-1) ) over the 17-yr study period. IPM estimates of population growth rates, adult survival, and detection and residency probabilities were similar and as precise as estimates from the stand-alone BBS and CJS models. A benefit of using the IPM was its ability to estimate the latent recruitment parameter. Annual growth rates for both species correlated more with recruitment than survival, and the relationship for wood thrush was stronger than for gray catbird. The IPM's unified modeling framework facilitates integration of these important data sets. This article is protected by copyright. All rights reserved.

Twitter Demographics

The data shown below were collected from the profiles of 18 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 97 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 2 2%
Unknown 95 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 29 30%
Student > Ph. D. Student 20 21%
Unspecified 12 12%
Student > Master 12 12%
Student > Postgraduate 7 7%
Other 17 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 58 60%
Environmental Science 18 19%
Unspecified 14 14%
Business, Management and Accounting 2 2%
Medicine and Dentistry 2 2%
Other 3 3%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 May 2017.
All research outputs
#1,307,164
of 13,277,512 outputs
Outputs from Ecological Applications
#364
of 2,173 outputs
Outputs of similar age
#50,728
of 371,326 outputs
Outputs of similar age from Ecological Applications
#11
of 57 outputs
Altmetric has tracked 13,277,512 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,173 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.8. This one has done well, scoring higher than 83% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 371,326 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 57 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.