From 8d690325d46109295941d150f8f8f1dd13133867 Mon Sep 17 00:00:00 2001 From: Carl Boettiger Date: Fri, 28 Dec 2018 10:35:27 -0800 Subject: [PATCH] add license and citation to code repo --- LICENSE.md | 395 +++++++++++++++++++++++++++++++++++++ manuscripts/citations.bib | 23 +++ manuscripts/manuscript.Rmd | 2 +- manuscripts/manuscript.pdf | Bin 391827 -> 392630 bytes manuscripts/manuscript.tex | 15 +- 5 files changed, 433 insertions(+), 2 deletions(-) create mode 100644 LICENSE.md diff --git a/LICENSE.md b/LICENSE.md new file mode 100644 index 0000000..0fb847e --- /dev/null +++ b/LICENSE.md @@ -0,0 +1,395 @@ +Attribution 4.0 International + +======================================================================= + +Creative Commons Corporation ("Creative Commons") is not a law firm and +does not provide legal services or legal advice. Distribution of +Creative Commons public licenses does not create a lawyer-client or +other relationship. 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For +the avoidance of doubt, this paragraph does not form part of the +public licenses. + +Creative Commons may be contacted at creativecommons.org. diff --git a/manuscripts/citations.bib b/manuscripts/citations.bib index dc747ae..5a38b9b 100644 --- a/manuscripts/citations.bib +++ b/manuscripts/citations.bib @@ -1351,3 +1351,26 @@ @article{Mangel1985 } +@article{Marwick2018, +author = {Marwick, Ben and Boettiger, Carl and Mullen, Lincoln}, +doi = {10.1080/00031305.2017.1375986}, +issn = {0003-1305}, +journal = {The American Statistician}, +keywords = {Computational science,Data science,Open source software,Reproducible research}, +month = {jan}, +number = {1}, +pages = {80--88}, +title = {{Packaging Data Analytical Work Reproducibly Using R (and Friends)}}, +url = {https://www.tandfonline.com/doi/full/10.1080/00031305.2017.1375986}, +volume = {72}, +year = {2018} +} + +@misc{pomdp-intro, + author = {Carl Boettiger and Milad Memarzadeh}, + title = {{Supplement to: "Resolving the measurement uncertainty paradox in ecological management"}}, + year = "2018", + url = {https://github.com/boettiger-lab/pomdp-intro}, + publisher = "Zenodo", + doi = "xxxxx" +} diff --git a/manuscripts/manuscript.Rmd b/manuscripts/manuscript.Rmd index 2460b2f..092f1de 100755 --- a/manuscripts/manuscript.Rmd +++ b/manuscripts/manuscript.Rmd @@ -200,7 +200,7 @@ The optimization problem is to select the action $a_t$ that will maximize the ne ## Simulations -We consider the average fish biomass across 100 replicate simulations of the same stock dynamics (Eq 4) under three different management strategies: constant escapement (CE), total allowable catch (TAC; equal to 80% MSY), and partially observed Markov decision process (POMDP) management. Each suite of simulations is considered under three sequentially higher measurement error regimes, from $\sigma_m = 0$ (no measurement errors), $\sigma_m = 0.1$ (low error), and $\sigma_m = 0.15$ (moderate error), as indicated, while stochastic recruitment (environmental noise) is set to a moderate $\sigma_g = 0.15$. Empirical estimates of measurement error in stock sizes vary widely, with estimates often dependent upon methodological assumptions. Early estimates have put possible error as high as 50% [@Clark1986] and more recent analyses have suggested an average of closer to 36%, though with cases that may be much higher [@Ralston2011]. Consequently, range between 0 to 15% provides a probably conservative estimate of typical uncertainty ranges, which we show is nevertheless large enough to drive substantially negative ecological and economic outcomes under management strategies that do not appropriately account for that error over the long run. +We consider the average fish biomass across 100 replicate simulations of the same stock dynamics (Eq 4) under three different management strategies: constant escapement (CE), total allowable catch (TAC; equal to 80% MSY), and partially observed Markov decision process (POMDP) management. Each suite of simulations is considered under three sequentially higher measurement error regimes, from $\sigma_m = 0$ (no measurement errors), $\sigma_m = 0.1$ (low error), and $\sigma_m = 0.15$ (moderate error), as indicated, while stochastic recruitment (environmental noise) is set to a moderate $\sigma_g = 0.15$. Empirical estimates of measurement error in stock sizes vary widely, with estimates often dependent upon methodological assumptions. Early estimates have put possible error as high as 50% [@Clark1986] and more recent analyses have suggested an average of closer to 36%, though with cases that may be much higher [@Ralston2011]. Consequently, range between 0 to 15% provides a probably conservative estimate of typical uncertainty ranges, which we show is nevertheless large enough to drive substantially negative ecological and economic outcomes under management strategies that do not appropriately account for that error over the long run. We provide complete code and data files to reproduce the analysis shown here in the Appendices and as research compendium [@Marwick2018] at , archived at [@pomdp-intro]. # Results diff --git a/manuscripts/manuscript.pdf b/manuscripts/manuscript.pdf index 9b3200b955734b54d2057ec8bc8fbb0a86c99b5e..603dd928b2411b25f0b32cff55e410cf34ecdec6 100644 GIT binary patch delta 72392 zcmV)1K+V6C^%u7L7qIkw7dId+R%WS_H}~6{|4x2+7^?o$ZLX7Y zth@I1fA0U|^-sdh28lG2H-8!Y6E{MuG;=Oau!jjAkL?CWzM-MY%!h_?E>8=i7UO>5 z{@IzO3JqP0#gN}JlU-V+aH(}-G2{#P&u?G{Rypi%(!9_&uSBZh#}i>ZF{?^V=5A)4 zzPo)Ta+^G#n6XHekbio{^5l%?_E^k%0XMP&&h9(>mSurDYSt%DrGK=ckGM>9sdXyh zZAEl(St_Ivsj>ND)c920zEa92hrWBb6-oI}H}!Zck$%3td*omIiXvFIJ8Buma;z?} zS!W84wA|z=rhxo7bBcuL&Y^`#GqpU&uKt9Zu3Fq%4y>XrJ`ZEHr{|hKUE8*SS#vA@ zymX%1wvk2ZtX@o<;(w5vEG=BYy>guzkWrht)a8bH{kz|~10L1w2G~#^n(B_4n13!Q z{pF^kZf>PZp1PspahtLYH25u3=2*3xYB3zyUv27vXK<10ar%zbkI6~>q_?lM5piSP zvFDY`A?)lkZh}V-HSBtSXr6hm!*JYt9?a>(C(jF@v7m#uU4OqX8$Zm*WLpm~&Dhru 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b/manuscripts/manuscript.tex index bc6cd72..1102d01 100644 --- a/manuscripts/manuscript.tex +++ b/manuscripts/manuscript.tex @@ -698,7 +698,11 @@ \subsection{Simulations}\label{simulations}} probably conservative estimate of typical uncertainty ranges, which we show is nevertheless large enough to drive substantially negative ecological and economic outcomes under management strategies that do not -appropriately account for that error over the long run. +appropriately account for that error over the long run. We provide +complete code and data files to reproduce the analysis shown here in the +Appendices and as research compendium (Marwick et al. 2018) at +\url{https://github.com/boettiger-lab/pomdp-intro}, archived at +(Boettiger and Memarzadeh 2018). \hypertarget{results}{% \section{Results}\label{results}} @@ -1212,6 +1216,10 @@ \section*{References}\label{references}} Proceedings of the Royal Society B: Biological Sciences 282:20141631--20141631. +\leavevmode\hypertarget{ref-pomdp-intro}{}% +Boettiger, C., and M. Memarzadeh. 2018. Supplement to: "Resolving the +measurement uncertainty paradox in ecological management". Zenodo. + \leavevmode\hypertarget{ref-sarsop-pkg}{}% Boettiger, C., J. Ooms, and M. Memarzadeh. 2018. sarsop: Approximate POMDP Planning Software in R, v0.5.0, @@ -1407,6 +1415,11 @@ \section*{References}\label{references}} on stochastic dynamic programming. Methods in Ecology and Evolution 4:872--884. +\leavevmode\hypertarget{ref-Marwick2018}{}% +Marwick, B., C. Boettiger, and L. Mullen. 2018. Packaging Data +Analytical Work Reproducibly Using R (and Friends). The American +Statistician 72:80--88. + \leavevmode\hypertarget{ref-May1977}{}% May, R. M. 1977. Thresholds and breakpoints in ecosystems with a multiplicity of stable states. Nature 269:471--477.