The scale of effect of landscape context varies with the species’ response variable measured

2019 ◽  
Vol 34 (4) ◽  
pp. 703-715 ◽  
Author(s):  
Andrew D. Moraga ◽  
Amanda E. Martin ◽  
Lenore Fahrig
2021 ◽  
Author(s):  
Lazaro Carneiro ◽  
Milton Cezar Ribeiro ◽  
Willian Moura de Aguiar ◽  
Camila de Fátima Priante ◽  
Wilson Frantine-Silva ◽  
...  

Abstract ContextMultiscale approaches are essential for understanding ecological processes and detecting the scale of effect. However, nested multiscale approaches retain the effect of the landscape attributes from the smaller spatial scales into the larger ones. Thus, decoupling local vs. regional scales can reveal detailed ecological responses to landscape context, but this multiscale approach is poorly explored. ObjectivesWe evaluated the scale of effect of the forest cover (%) and landscape heterogeneity on Euglossini bees combining coupled and decoupled multiscale approaches. MethodsThe Euglossini males were sampled in forest patches from 15 landscapes within the Atlantic Forest, southeast Brazil. For simplicity, we defined that the coupled approaches represented the local scales and decoupled approaches the regional scales. We decoupled the scales by cutting out the smaller scales inserted into larger ones. We estimated the relationship of the bee community attributes with forest cover (%) and landscape heterogeneity in local and regional scales using Generalized Linear Models. ResultsWe found positive effects of landscape heterogeneity on species richness for regional scales. Forest cover and landscape heterogeneity in local scales showed positive effects on the euglossine abundances. The scale of effect for euglossine richness was higher than species abundances. ConclusionsCombining coupled and decoupled multiscale approaches showed adequate capture of the scale of effect of the landscape composition on bee communities. Therefore, it is of paramount importance to measure the influence of the landscape context on biodiversity. Maintaining landscapes with larger forest cover and spatial heterogeneity is essential to keep euglossine species requirements.


2018 ◽  
Vol 3 (2) ◽  
pp. 207-216 ◽  
Author(s):  
David Fisher ◽  
Lionel Sims

Claims first made over half a century ago that certain prehistoric monuments utilised high-precision alignments on the horizon risings and settings of the Sun and the Moon have recently resurfaced. While archaeoastronomy early on retreated from these claims, as a way to preserve the discipline in an academic boundary dispute, it did so without a rigorous examination of Thom’s concept of a “lunar standstill”. Gough’s uncritical resurrection of Thom’s usage of the term provides a long-overdue opportunity for the discipline to correct this slippage. Gough (2013), in keeping with Thom (1971), claims that certain standing stones and short stone rows point to distant horizon features which allow high-precision alignments on the risings and settings of the Sun and the Moon dating from about 1700 BC. To assist archaeoastronomy in breaking out of its interpretive rut and from “going round in circles” (Ruggles 2011), this paper evaluates the validity of this claim. Through computer modelling, the celestial mechanics of horizon alignments are here explored in their landscape context with a view to testing the very possibility of high-precision alignments to the lunar extremes. It is found that, due to the motion of the Moon on the horizon, only low-precision alignments are feasible, which would seem to indicate that the properties of lunar standstills could not have included high-precision markers for prehistoric megalith builders.


2020 ◽  
Vol 8 (1) ◽  
pp. 157-171 ◽  
Author(s):  
Himchan Jeong ◽  
Emiliano A. Valdez

AbstractFor observations over a period of time, Bayesian credibility premium may be used to predict the value of a response variable for a subject, given previously observed values. In this article, we formulate Bayesian credibility premium under a change of probability measure within the copula framework. Such reformulation is demonstrated using the multivariate generalized beta of the second kind (GB2) distribution. Within this family of GB2 copulas, we are able to derive explicit form of Bayesian credibility premium. Numerical illustrations show the application of these estimators in determining experience-rated insurance premium. We consider generalized Pareto as a special case.


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