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Correction to ‘Blood does not buy goodwill: allowing culling increases poaching of a large carnivore’

Correction to ‘Blood does not buy goodwill: allowing culling increases poaching of a large... Correction to ‘Blood does not buy goodwill: allowing culling increases rspb.royalsocietypublishing.org poaching of a large carnivore’ Guillaume Chapron and Adrian Treves Correction GC, 0000-0002-6727-1070 Cite this article: Chapron G, Treves A. 2016 Proc. R. Soc. B 283, 20152939. (2016; Published online 11 May 2016) (doi:10. Correction to ‘Blood does not buy goodwill: 1098/rspb.2015.2939) allowing culling increases poaching of a large We recently discovered an error in [1] due to a misalignment of rows between carnivore’. Proc. R. Soc. B 283: 20162577. columns in the dataset. Specifically, we misaligned by 1 year the population http://dx.doi.org/10.1098/rspb.2016.2577 size with the number of wolves culled and the policy signal. The correct results are slightly different than the ones we presented: the effect we report becomes slightly stronger and some parameters see minor adjustments of their posterior values. The conclusion of our paper is still supported by the correct results. The correct results indicate that with no culling policy signal, the annual potential growth rate was r ¼ 0.17+ 0.02 95% credible interval (CI) ¼ 0.13– 0.21 in Wisconsin (r ¼ 0.15+ 0.02 95% CI ¼ 0.11–0.19 in Michigan). However, with a year-long culling policy signal, we found annual growth rate had a 92% probability to be lower (figure 1 in this article) with r ¼ 0.12+ 0.03 95% CI ¼ 0.06–0.18 in Wisconsin (r ¼ 0.10+ 0.03 95% CI ¼ 0.04–0.16 in Michigan). Cor- rected prior and posterior values for all model parameters are given in table 1. In the electronic supplementary material, we provide a commented R code with both the mis-aligned and the properly aligned datasets so that the reader can replicate both the original results and the corrected ones. Running this code requires the software JAGS [2] with the package R2jags [3]. −0.20 −0.10 0 0.10 b = −0.05 ± 0.03 95% CI = (−0.12,0.02) Figure 1. The posterior density distribution b shows a decline of growth rate is 12 times more r r likely Pðb , 0Þ¼ 0:92 (light grey area) than an increase Pðb . 0Þ¼ 0:08 (dark grey area). 1 1 Two other typographical errors were not detected during the proof process. D was the proportion (and not the number) of days that culling was allowed in state S during year t. The equation describing area as a linear function of population size should indicate we took the logarithm of area: A A W A logðA Þ  Norm(b þ b  N , t Þ which explains the very small (but positive) 0 1 t values for b . Electronic supplementary material is available online at https://dx.doi.org/10.6084/m9.fig- share.c.3634499. & 2016 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. Table 1. Prior and posterior values for the dynamic model parameters. posterior distribution prior choice median+++++ s.d. 95% credible interval population dynamic s  unifð0,0:5Þ 0.06+ 0.02 0.03 – 0.09 proc g  Norm(m ¼ 1:06,t ¼ 14 Þ 1.06+ 0.07 0.92 – 1.2 rW 6 b  Norm(m ¼ 0,t ¼ 10 Þ 0.17+ 0.02 0.13 – 0.21 rM 6 b  Norm(m ¼ 0,t ¼ 10 Þ 0.15+ 0.02 0.11 – 0.19 r 6 b  Norm(m ¼ 0,t ¼ 10 Þ 20.05+ 0.03 20.12 – 0.02 min s  unifð0,100Þ 4.38+ 3.3 0.17 – 12.29 Nobs max s  unifð0,100Þ 5.53+ 4.4 0.23 – 16.42 Nobs o  Normðm ¼ 1,t ¼ 10 Þ MIN 0.97+ 0.02 0.93 – 1 o [ [0,1] MIN o  Norm(m ¼ 1,t ¼ 10 Þ MAX 1.03+ 0.02 1 – 1.08 o [ ½1,10 MAX W 6 6 N  Gamma(10 ,10 Þ 91.10+ 6.15 79.43 – 103.57 M 6 6 N  Gamma(10 ,10 Þ 92.06+ 7.4 78.15 – 107.39 References 1. Chapron G, Treves A. 2016 Blood does not buy goodwill: allowing culling increases poaching of a large carnivore. Proc. R. Soc. B 283, 20152939. (doi:10.1098/rspb.2015.2939) 2. Plummer M. 2003 JAGS: a program for analysis of Bayesian graphical models using Gibbs sampling. In Proc. of the 3rd International Workshop on Distributed Statistical Computing (eds K Hornik, F Leisch, A Zeileis). Vienna, Austria. 3. Yu-Sung S, Masanao Y. 2015 R2jags: Using R to Run ‘JAGS’. See https://cran.r-project.org/web/packages/R2jags/index.html. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Proceedings of the Royal Society B: Biological Sciences Pubmed Central

Correction to ‘Blood does not buy goodwill: allowing culling increases poaching of a large carnivore’

Proceedings of the Royal Society B: Biological Sciences , Volume 283 (1845) – Dec 28, 2016

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References (4)

Publisher
Pubmed Central
Copyright
© 2016 The Authors.
ISSN
0962-8452
eISSN
1471-2954
DOI
10.1098/rspb.2016.2577
Publisher site
See Article on Publisher Site

Abstract

Correction to ‘Blood does not buy goodwill: allowing culling increases rspb.royalsocietypublishing.org poaching of a large carnivore’ Guillaume Chapron and Adrian Treves Correction GC, 0000-0002-6727-1070 Cite this article: Chapron G, Treves A. 2016 Proc. R. Soc. B 283, 20152939. (2016; Published online 11 May 2016) (doi:10. Correction to ‘Blood does not buy goodwill: 1098/rspb.2015.2939) allowing culling increases poaching of a large We recently discovered an error in [1] due to a misalignment of rows between carnivore’. Proc. R. Soc. B 283: 20162577. columns in the dataset. Specifically, we misaligned by 1 year the population http://dx.doi.org/10.1098/rspb.2016.2577 size with the number of wolves culled and the policy signal. The correct results are slightly different than the ones we presented: the effect we report becomes slightly stronger and some parameters see minor adjustments of their posterior values. The conclusion of our paper is still supported by the correct results. The correct results indicate that with no culling policy signal, the annual potential growth rate was r ¼ 0.17+ 0.02 95% credible interval (CI) ¼ 0.13– 0.21 in Wisconsin (r ¼ 0.15+ 0.02 95% CI ¼ 0.11–0.19 in Michigan). However, with a year-long culling policy signal, we found annual growth rate had a 92% probability to be lower (figure 1 in this article) with r ¼ 0.12+ 0.03 95% CI ¼ 0.06–0.18 in Wisconsin (r ¼ 0.10+ 0.03 95% CI ¼ 0.04–0.16 in Michigan). Cor- rected prior and posterior values for all model parameters are given in table 1. In the electronic supplementary material, we provide a commented R code with both the mis-aligned and the properly aligned datasets so that the reader can replicate both the original results and the corrected ones. Running this code requires the software JAGS [2] with the package R2jags [3]. −0.20 −0.10 0 0.10 b = −0.05 ± 0.03 95% CI = (−0.12,0.02) Figure 1. The posterior density distribution b shows a decline of growth rate is 12 times more r r likely Pðb , 0Þ¼ 0:92 (light grey area) than an increase Pðb . 0Þ¼ 0:08 (dark grey area). 1 1 Two other typographical errors were not detected during the proof process. D was the proportion (and not the number) of days that culling was allowed in state S during year t. The equation describing area as a linear function of population size should indicate we took the logarithm of area: A A W A logðA Þ  Norm(b þ b  N , t Þ which explains the very small (but positive) 0 1 t values for b . Electronic supplementary material is available online at https://dx.doi.org/10.6084/m9.fig- share.c.3634499. & 2016 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. Table 1. Prior and posterior values for the dynamic model parameters. posterior distribution prior choice median+++++ s.d. 95% credible interval population dynamic s  unifð0,0:5Þ 0.06+ 0.02 0.03 – 0.09 proc g  Norm(m ¼ 1:06,t ¼ 14 Þ 1.06+ 0.07 0.92 – 1.2 rW 6 b  Norm(m ¼ 0,t ¼ 10 Þ 0.17+ 0.02 0.13 – 0.21 rM 6 b  Norm(m ¼ 0,t ¼ 10 Þ 0.15+ 0.02 0.11 – 0.19 r 6 b  Norm(m ¼ 0,t ¼ 10 Þ 20.05+ 0.03 20.12 – 0.02 min s  unifð0,100Þ 4.38+ 3.3 0.17 – 12.29 Nobs max s  unifð0,100Þ 5.53+ 4.4 0.23 – 16.42 Nobs o  Normðm ¼ 1,t ¼ 10 Þ MIN 0.97+ 0.02 0.93 – 1 o [ [0,1] MIN o  Norm(m ¼ 1,t ¼ 10 Þ MAX 1.03+ 0.02 1 – 1.08 o [ ½1,10 MAX W 6 6 N  Gamma(10 ,10 Þ 91.10+ 6.15 79.43 – 103.57 M 6 6 N  Gamma(10 ,10 Þ 92.06+ 7.4 78.15 – 107.39 References 1. Chapron G, Treves A. 2016 Blood does not buy goodwill: allowing culling increases poaching of a large carnivore. Proc. R. Soc. B 283, 20152939. (doi:10.1098/rspb.2015.2939) 2. Plummer M. 2003 JAGS: a program for analysis of Bayesian graphical models using Gibbs sampling. In Proc. of the 3rd International Workshop on Distributed Statistical Computing (eds K Hornik, F Leisch, A Zeileis). Vienna, Austria. 3. Yu-Sung S, Masanao Y. 2015 R2jags: Using R to Run ‘JAGS’. See https://cran.r-project.org/web/packages/R2jags/index.html.

Journal

Proceedings of the Royal Society B: Biological SciencesPubmed Central

Published: Dec 28, 2016

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