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
Keyword(s):  
Survey Data ◽  
Spatial Models ◽  
Hierarchical Spatial Models

scholarly journals Hierarchical spatial models for predicting tree species assemblages across large domains

2009 ◽  
Vol 3 (3) ◽  
pp. 1052-1079 ◽  
Author(s):  
Andrew O. Finley ◽  
Sudipto Banerjee ◽  
Ronald E. McRoberts
Keyword(s):  
Tree Species ◽  
Spatial Models ◽  
Species Assemblages ◽  
Hierarchical Spatial Models ◽  
Large Domains

Development of Hierarchical Spatial Models for Assessing Ungulate Abundance and Habitat Relationships

2020 ◽  
pp. 35-82
Author(s):  
N. Samba Kumar ◽  
K. Ullas Karanth ◽  
James D. Nichols ◽  
Srinivas Vaidyanathan ◽  
Beth Gardner ◽  
...  
Keyword(s):  
Spatial Models ◽  
Hierarchical Spatial Models

scholarly journals Bayesian hierarchical spatial models: Implementing the Besag York Mollié model in stan

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

scholarly journals Predicting species distribution from fishers’ local ecological knowledge: a new alternative for data-poor management

2019 ◽  
Vol 76 (8) ◽  
pp. 1423-1431 ◽  
Author(s):  
Priscila F.M. Lopes ◽  
Júlia T. Verba ◽  
Alpina Begossi ◽  
Maria Grazia Pennino
Keyword(s):  
Local Ecological Knowledge ◽  
Scientific Information ◽  
Spatial Models ◽  
Marine Spatial Planning ◽  
Ecological Knowledge ◽  
Species Occurrence ◽  
Southwest Atlantic ◽  
Bayesian Hierarchical ◽  
Dusky Grouper ◽  
Hierarchical Spatial Models

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.

Hierarchical Spatial Models

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

Hierarchical Spatial Models

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

scholarly journals Hierarchical spatial models for predicting pygmy rabbit distribution and relative abundance

2010 ◽  
Vol 47 (2) ◽  
pp. 401-409 ◽  
Author(s):  
Tammy L. Wilson ◽  
James B. Odei ◽  
Mevin B. Hooten ◽  
Thomas C. Edwards Jr
Keyword(s):  
Relative Abundance ◽  
Spatial Models ◽  
Pygmy Rabbit ◽  
Hierarchical Spatial Models

scholarly journals Party and Cleavage in the 2016 Election

2017 ◽  
Author(s):  
Jack Santucci
Keyword(s):  
Survey Data ◽  
Spatial Models ◽  
Transgender People ◽  
Race Identity ◽  
Redistributive Policies ◽  
2016 Election ◽  
Muslim Immigration ◽  
Non Parametric

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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