scholarly journals Optimizing a stratified sampling design when faced with multiple objectives

2006 ◽  
Vol 64 (1) ◽  
pp. 97-109 ◽  
Author(s):  
Timothy J. Miller ◽  
John R. Skalski ◽  
James N. Ianelli
Keyword(s):  
Fish Species ◽  
Quantitative Methods ◽  
Sampling Design ◽  
Multiple Objectives ◽  
Stratified Sampling ◽  
Sampling Effort ◽  
Annual Data ◽  
Sample Sizes ◽  
Analytical Results ◽  
Coverage Rates

Abstract Miller, T. J., Skalski, J. R., and Ianelli, J. N. 2007. Optimizing a stratifield sampling design when faced with multiple objectives – ICES Journal of Marine Science, 64, 97–109. For many stratified sampling designs, the data collected are used by multiple parties with different estimation objectives. Quantitative methods to determine allocation of sampling effort to different strata to satisfy the often disparate estimation objectives are lacking. Analytical results for the sampling fractions and sample sizes for primary units within each stratum of a stratified (multi-stage) sampling design that are optimal with respect to a weighted sum of relative variances for the estimation objectives are presented. Further, an approach for assessing gains or losses for each estimation objective by changing allocation of sample sizes to each stratum is provided. As an illustration, the analytical results are applied to determine optimal observer sampling fractions (coverage rates) for the North Pacific Groundfish Observer Programme (NPGOP), for which the multiple objectives are assumed to be bycatch (seabird, marine mammal, and non-targeted fish species) and total catch, and catch-at-length and -age of targeted fish species. Simultaneously optimizing a criterion that defines the strata of the NPGOP sampling design is also considered. When observer coverage rates are allowed to be gear-specific for the NPGOP design, the optimized objective function is between 10% and 28% less than the value corresponding to current sampling for annual data (2000–2003) and 12% less when optimized over all years combined.

Advances in Understanding Landscape Influences on Freshwater Habitats and Biological Assemblages

2019 ◽  
Keyword(s):  
Species Richness ◽  
Site Selection ◽  
Catchment Area ◽  
Sampling Design ◽  
Environmental Gradients ◽  
Large Sample Size ◽  
Sample Sizes ◽  
Assemblage Composition ◽  
Landscape Gradients ◽  
Freshwater Habitats

<i>Abstract.</i>—Linking landscape features, both natural and human-altered, to aquatic ecosystem structure and function is a fundamental objective in landscape ecology and freshwater science, but this process is data- and resource-intensive. Quantifying how landscape stressors influence aquatic communities requires balancing logistic and financial constraints with effectively sampling the landscape to capture gradients of interest. There are a variety of ways to balance these constraints, such as using existing data, handpicked site selection, or a statistical site-selection scheme. Poor sampling design reduces statistical power; however, we do not know how differences in site-selection designs influence our ability to measure ecological responses to landscape gradients. We quantified how the distribution of sample sites across landscape gradients affected the measured responses of stream fish assemblages to these gradients at different sample sizes. Specifically, we used randomization tests to compare the variability in the responses of fish assemblage structure (species richness and composition) to catchment area and land use (agricultural land) with manipulated distributions (random, highly skewed, and uniform) of sites across these landscape gradients. Assemblage composition was more sensitive than species richness to sampling design, and we observed less variability in the detected response of assemblage composition when samples were distributed uniformly across landscape gradients, especially when sample sizes were small. Although strong responses to environmental gradients, such as species richness to catchment area, are robust to sampling distributions, large sample size and a uniform distribution of samples might help elucidate more subtle responses to environmental gradients.

Watershed-level sampling effort requirements for determining riverine fish species composition

2005 ◽  
Vol 62 (7) ◽  
pp. 1580-1588 ◽  
Author(s):  
Katherine L Smith ◽  
Michael L Jones
Keyword(s):  
Species Richness ◽  
Species Composition ◽  
Fish Species ◽  
Correlation Coefficients ◽  
Sampling Effort ◽  
Species Accumulation Curves ◽  
Targeted Sampling ◽  
Weak Negative Correlation ◽  
Fish Species Composition ◽  
Riverine Fish

Accurate assessments of watershed-level species composition are necessary for comparative ecological studies, ecosystem health assessments, monitoring, and aquatic conservation prioritization. Several studies have addressed sampling effort requirements for characterizing fish species composition at a section of stream, but none have examined watershed-level requirements. In the spring and summer of 2002, we extensively sampled nine Great Lakes watersheds to assess sampling-effort requirements. Sampling requirements increased with the targeted percentage of estimated species richness. Sampling 15–119 randomly selected reaches of stream, stratified by stream order, was on average sufficient to detect 80%–100% of estimated species richness. Watershed size (km2) and estimated species richness each showed a weak, negative correlation with sampling-effort requirements in our study streams, with Pearson's correlation coefficients of –5.06 and –0.590, respectively. Because of among-watershed variability in sampling effort requirements, field crews should plot species accumulation curves onsite to determine adequate inventory completion. Based on the difficulty of detecting the last 10% of species, random sampling should be conducted in conjunction with targeted sampling of rare species.

scholarly journals Improved spatial ecological sampling using open data and standardization: an example from malaria mosquito surveillance

2019 ◽  
Vol 16 (153) ◽  
pp. 20180941 ◽  
Author(s):  
Luigi Sedda ◽  
Eric R. Lucas ◽  
Luc S. Djogbénou ◽  
Ako V. C. Edi ◽  
Alexander Egyir-Yawson ◽  
...  
Keyword(s):  
Sampling Design ◽  
Model Fitting ◽  
Open Data ◽  
Environmental Data ◽  
Sample Sizes ◽  
Vector Surveillance ◽  
Mosquito Abundance ◽  
Mosquito Sampling ◽  
Similar Accuracy ◽  
Ecological Sampling

Vector-borne disease control relies on efficient vector surveillance, mostly carried out using traps whose number and locations are often determined by expert opinion rather than a rigorous quantitative sampling design. In this work we propose a framework for ecological sampling design which in its preliminary stages can take into account environmental conditions obtained from open data (i.e. remote sensing and meteorological stations) not necessarily designed for ecological analysis. These environmental data are used to delimit the area into ecologically homogeneous strata. By employing Bayesian statistics within a model-based sampling design, the traps are deployed among the strata using a mixture of random and grid locations which allows balancing predictions and model-fitting accuracies. Sample sizes and the effect of ecological strata on sample sizes are estimated from previous mosquito sampling campaigns open data. Notably, we found that a configuration of 30 locations with four households each (120 samples) will have a similar accuracy in the predictions of mosquito abundance as 200 random samples. In addition, we show that random sampling independently from ecological strata, produces biased estimates of the mosquito abundance. Finally, we propose standardizing reporting of sampling designs to allow transparency and repetition/re-use in subsequent sampling campaigns.

scholarly journals Evaluating and benchmarking biodiversity monitoring: Metadata-based indicators for sampling design, sampling effort and data analysis

2018 ◽  
Vol 85 ◽  
pp. 624-633 ◽  
Author(s):  
Szabolcs Lengyel ◽  
Beatrix Kosztyi ◽  
Dirk S. Schmeller ◽  
Pierre-Yves Henry ◽  
Mladen Kotarac ◽  
...  
Keyword(s):  
Data Analysis ◽  
Sampling Design ◽  
Sampling Effort ◽  
Biodiversity Monitoring

An optimum multivariate-multiobjective stratified sampling design

METRON ◽  
2011 ◽  
Vol 69 (3) ◽  
pp. 227-250 ◽  
Author(s):  
Athar Hussain Ansari ◽  
Rahul Varshney ◽  
Najmussehar ◽  
Mohammad Jameel Ahsan
Keyword(s):  
Sampling Design ◽  
Stratified Sampling

scholarly journals Stratified Sampling Design Based on Data Mining

2013 ◽  
Vol 19 (3) ◽  
pp. 186 ◽  
Author(s):  
Yeonkook J. Kim ◽  
Yoonhwan Oh ◽  
Sunghoon Park ◽  
Sungzoon Cho ◽  
Hayoung Park
Keyword(s):  
Data Mining ◽  
Sampling Design ◽  
Stratified Sampling

scholarly journals Low-density koala (Phascolarctos cinereus) populations in the mulgalands of south-west Queensland. II. Distribution and diet

2003 ◽  
Vol 30 (4) ◽  
pp. 331 ◽  
Author(s):  
B. J. Sullivan ◽  
W. M. Norris ◽  
G. S. Baxter
Keyword(s):  
Sampling Design ◽  
Faecal Pellet ◽  
Stratified Sampling ◽  
Annual Rainfall ◽  
Dietary Composition ◽  
Low Density ◽  
Phascolarctos Cinereus ◽  
Faecal Pellets ◽  
South West ◽  
Biogeographic Region

This study used faecal pellets to investigate the broadscale distribution and diet of koalas in the mulgalands biogeographic region of south-west Queensland. Koala distribution was determined by conducting faecal pellet searches within a 30-cm radius of the base of eucalypts on 149 belt transects, located using a multi-scaled stratified sampling design. Cuticular analysis of pellets collected from 22 of these sites was conducted to identify the dietary composition of koalas within the region. Our data suggest that koala distribution is concentrated in the northern and more easterly regions of the study area, and appears to be strongly linked with annual rainfall. Over 50% of our koala records were obtained from non-riverine communities, indicating that koalas in the study area are not primarily restricted to riverine communities, as has frequently been suggested. Cuticular analysis indicates that more than 90% of koala diet within the region consists of five eucalypt species. Our data highlights the importance of residual Tertiary landforms to koala conservation in the region.

scholarly journals Feasibility Study on Biomonitoring of Microplastics in Fish Gastrointestinal Tracts

2022 ◽  
Vol 8 ◽  
Author(s):  
Bavo De Witte ◽  
Ana I. Catarino ◽  
Loes Vandecasteele ◽  
Michael Dekimpe ◽  
Nelle Meyers ◽  
...  
Keyword(s):  
North Sea ◽  
Marine Environment ◽  
Fish Species ◽  
Nile Red ◽  
Species Selection ◽  
Polymer Composition ◽  
Sampling Effort ◽  
Advantages And Disadvantages ◽  
Nile Red Staining ◽  
Selection Of

Monitoring the occurrence and trends of microplastic contamination in the marine environment is key to establish microplastic (MP) data baselines, to work out policy mitigation measures, and to assess the effectiveness of waste regulations. To establish MP contamination baselines in the marine environment, marine biota species can be selected as monitoring matrices to track plastic pollution in the environment. The aim of this work was to evaluate the feasibility of biomonitoring MPs in fish gastrointestinal tract (GIT). A selection of suitable fish species was performed, based on species distribution, sampling effort, commercial value of species, sustainable development of fish populations, migration behaviour, and scientific evidence for occurrence of MPs in the fish GIT. Sampling and MP extraction protocols were developed and validated on fish GIT samples acquired in the Southern North Sea. The fish species selection protocol enabled the selection of ubiquitous distributed and non-endangered fish species relevant for MP monitoring in the North Sea. The fish GIT sampling protocol considered background contamination measures and sampling fillet as procedural blanks. Advantages and disadvantages of onboard dissection were discussed. The MPs extraction protocol was based on matrix digestion, density separation, and Nile red staining of particles followed by fluorescent microscopy observation. The confirmation of MPs identification and the analysis of the polymer composition was done using micro-Fourier transform infrared (μFTIR) spectroscopy. The MP analysis indicated a low number of MPs in the fish GIT. The mean number of particles per single fish GIT was 0.48 ± 0.81 (Nile red staining observations) to 0.26 ± 0.64 (corrected for background contamination). A power analysis (sampling effort) indicated that to detect significant differences, in a balanced-ANOVA type of analysis, between species and/or sampling areas, the sample size would require a minimum of 109 up to 370 individual fish. The feasibility of MP biomonitoring in fish GIT was assessed by a SWOT-analysis, which indicated that fish GIT is a suitable matrix for biomonitoring of MPs, but that the large number of samples needed to identify significant differences can be a major drawback. A potential implementation strategy for MP biomonitoring within Europe was suggested.

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