HIERARCHICAL SPATIAL MODELS OF ABUNDANCE AND OCCURRENCE FROM IMPERFECT SURVEY DATA

2007 ◽  
Vol 77 (3) ◽  
pp. 465-481 ◽  
Author(s):  
J. Andrew Royle ◽  
Marc Kéry ◽  
Roland Gautier ◽  
Hans Schmid
2009 ◽  
Vol 3 (3) ◽  
pp. 1052-1079 ◽  
Author(s):  
Andrew O. Finley ◽  
Sudipto Banerjee ◽  
Ronald E. McRoberts

Author(s):  
N. Samba Kumar ◽  
K. Ullas Karanth ◽  
James D. Nichols ◽  
Srinivas Vaidyanathan ◽  
Beth Gardner ◽  
...  

2019 ◽  
Vol 31 ◽  
pp. 100301 ◽  
Author(s):  
Mitzi Morris ◽  
Katherine Wheeler-Martin ◽  
Dan Simpson ◽  
Stephen J. Mooney ◽  
Andrew Gelman ◽  
...  

2019 ◽  
Vol 76 (8) ◽  
pp. 1423-1431 ◽  
Author(s):  
Priscila F.M. Lopes ◽  
Júlia T. Verba ◽  
Alpina Begossi ◽  
Maria Grazia Pennino

Many developing countries lack information to manage their endangered species, urging the need for affordable and reliable information. We used Bayesian hierarchical spatial models, with oceanographic variables, to predict the distribution range of Epinephelus marginatus, the dusky grouper, for the entire Southwest Atlantic. We ran a model using scientific information gathered from the literature and another using information gathered from fishers on species presence or absence. In both models, temperature was an important determinant of species occurrence. The predicted occurrence of the dusky grouper overlapped widely (Schoener’s D = 0.71; Warren’s I = 0.91) between the models, despite small differences on the southern and northern extremes of the distribution. These results suggest that basic information provided by fishers on species occurrence in their area can be reliable enough to predict species occurrence over large scales and can be potentially useful for marine spatial planning. Fishers’ knowledge may be an even more viable alternative to data collection than what was previously thought, for countries that both struggle with financial limitations and have urgent conservation needs.


2015 ◽  
pp. 1-10
Author(s):  
Ali Arab ◽  
Mevin B. Hooten ◽  
Christopher K. Wikle

2017 ◽  
pp. 837-846 ◽  
Author(s):  
Ali Arab ◽  
Mevin B. Hooten ◽  
Christopher K. Wikle

2010 ◽  
Vol 47 (2) ◽  
pp. 401-409 ◽  
Author(s):  
Tammy L. Wilson ◽  
James B. Odei ◽  
Mevin B. Hooten ◽  
Thomas C. Edwards Jr

2017 ◽  
Author(s):  
Jack Santucci

I fit non-parametric spatial models to a novel set of survey data on the 2016 election (N=8,000). I find two underlying dimensions: "race/identity" and "trade-plus." Attitudes toward Muslim immigration and transgender people emerge as the clearest divides between Trump and Clinton voters. Trade is nearly orthogonal to "race/identity" and cleaves both candidates' blocs. Attitudes toward redistributive policies split both parties, depending on the question asked. Supporters of Republican and Democratic candidates reflect distinct positions on "race/identity" (except those of Kasich). Sanders supporters are at least as liberal as Clinton supporters on "race/identity." They are slightly to the left of all others on "trade-plus." Those Sanders voters who voted for Trump are more conservative on "race/identity" and slightly more liberal on "trade-plus."


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