Temporal and spatial sampling strategies maintain tracking success of whelks to prey patches of differing distributions

2012 ◽  
Vol 84 (6) ◽  
pp. 1323-1330 ◽  
Author(s):  
Miranda L. Wilson ◽  
Marc J. Weissburg
2021 ◽  
Vol 118 (52) ◽  
pp. e2105273118
Author(s):  
Stéphane Guindon ◽  
Nicola De Maio

Statistical phylogeography provides useful tools to characterize and quantify the spread of organisms during the course of evolution. Analyzing georeferenced genetic data often relies on the assumption that samples are preferentially collected in densely populated areas of the habitat. Deviation from this assumption negatively impacts the inference of the spatial and demographic dynamics. This issue is pervasive in phylogeography. It affects analyses that approximate the habitat as a set of discrete demes as well as those that treat it as a continuum. The present study introduces a Bayesian modeling approach that explicitly accommodates for spatial sampling strategies. An original inference technique, based on recent advances in statistical computing, is then described that is most suited to modeling data where sequences are preferentially collected at certain locations, independently of the outcome of the evolutionary process. The analysis of georeferenced genetic sequences from the West Nile virus in North America along with simulated data shows how assumptions about spatial sampling may impact our understanding of the forces shaping biodiversity across time and space.


1996 ◽  
Vol 44 (12) ◽  
pp. 3085-3098 ◽  
Author(s):  
C. Chambers ◽  
T.C. Tozer ◽  
K.C. Sharman ◽  
T.S. Durrani

2016 ◽  
Vol 73 (8) ◽  
pp. 2058-2074 ◽  
Author(s):  
Miles J. G. Parsons ◽  
Chandra P. Salgado-Kent ◽  
Sarah A. Marley ◽  
Alexander N. Gavrilov ◽  
Robert D. McCauley

Abstract The diversity, intensity, and periodicity of fish sounds can provide a wealth of information on spatial and temporal distribution of soniferous fish and, on occasion, which environmental factors these choruses are driven by. Such information can help predict species presence and understand their movement patterns in the long term. At three sites in Darwin Harbour, Australia, sea-noise loggers on the harbour floor recorded ambient noise over a 2-year period. Many fish calls and nine different chorus types were detected over 50 Hz to 3 kHz. Source species were speculated for four of the choruses and source levels, a precursor to passive acoustic abundance estimates, were identified for two of these. Other calls displayed similarities to choruses detected elsewhere in Australia. All choruses displayed diel cycles with semi-lunar patterns present for three of the chorus types. Time of sunset and temperature were also significantly related to the presence of the most predominant chorus and while not statistically significant, height of high tide and salinity also appeared related. A lack of frequency and temporal partitioning in calling across the choruses in hours of darkness (after sunset) illustrates the complexity of monitoring communities of different vocal species. The study has outlined some of the patterns biological sounds exhibit, which has significant implications for sampling strategies when using soundscapes for temporal and spatial predictive modelling.


2014 ◽  
Vol 7 (7) ◽  
pp. 2313-2335 ◽  
Author(s):  
P. R. Colarco ◽  
R. A. Kahn ◽  
L. A. Remer ◽  
R. C. Levy

Abstract. We use the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite aerosol optical thickness (AOT) product to assess the impact of reduced swath width on global and regional AOT statistics and trends. Along-track and across-track sampling strategies are employed, in which the full MODIS data set is sub-sampled with various narrow-swath (~ 400–800 km) and single pixel width (~ 10 km) configurations. Although view-angle artifacts in the MODIS AOT retrieval confound direct comparisons between averages derived from different sub-samples, careful analysis shows that with many portions of the Earth essentially unobserved, spatial sampling introduces uncertainty in the derived seasonal–regional mean AOT. These AOT spatial sampling artifacts comprise up to 60% of the full-swath AOT value under moderate aerosol loading, and can be as large as 0.1 in some regions under high aerosol loading. Compared to full-swath observations, narrower swath and single pixel width sampling exhibits a reduced ability to detect AOT trends with statistical significance. On the other hand, estimates of the global, annual mean AOT do not vary significantly from the full-swath values as spatial sampling is reduced. Aggregation of the MODIS data at coarse grid scales (10°) shows consistency in the aerosol trends across sampling strategies, with increased statistical confidence, but quantitative errors in the derived trends are found even for the full-swath data when compared to high spatial resolution (0.5°) aggregations. Using results of a model-derived aerosol reanalysis, we find consistency in our conclusions about a seasonal–regional spatial sampling artifact in AOT. Furthermore, the model shows that reduced spatial sampling can amount to uncertainty in computed shortwave top-of-atmosphere aerosol radiative forcing of 2–3 W m−2. These artifacts are lower bounds, as possibly other unconsidered sampling strategies would perform less well. These results suggest that future aerosol satellite missions having significantly less than full-swath viewing are unlikely to sample the true AOT distribution well enough to obtain the statistics needed to reduce uncertainty in aerosol direct forcing of climate.


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