scholarly journals Sampling requirements and approaches to detect ecosystem shifts

2020 ◽  
Author(s):  
Rosalie Bruel ◽  
Easton R. White
Keyword(s):  
Statistical Power ◽  
Ice Cores ◽  
Ecosystem Change ◽  
Sample Collection ◽  
Labor Costs ◽  
Sample Processing ◽  
Community Assemblage ◽  
Monitoring Programs ◽  
High Statistical Power

AbstractEnvironmental monitoring is a key component of understanding and managing ecosystems. Given that most monitoring efforts are still expensive and time-consuming, it is essential that monitoring programs are designed to be efficient and effective. In many situations, the expensive part of monitoring is not sample collection, but instead sample processing, which leads to only a subset of the samples being processed. For example, sediment or ice cores can be quickly obtained in the field, but they require weeks or months of processing in a laboratory setting. Standard sub-sampling approaches often involve equally-spaced sampling. We use simulations to show how many samples, and which types of sampling approaches, are the most effective in detecting ecosystem change. We test these ideas with a case study of Cladocera community assemblage reconstructed from a sediment core. We demonstrate that standard approaches to sample processing are less efficient than an iterative approach. For our case study, using an optimal sampling approach would have resulted in savings of 195 person-hours—thousands of dollars in labor costs. We also show that, compared with these standard approaches, fewer samples are typically needed to achieve high statistical power. We explain how our approach can be applied to monitoring programs that rely on video records, eDNA, remote sensing, and other common tools that allow re-sampling.

scholarly journals The use of pseudo-multivariate standard error to improve the sampling design of coral monitoring programs

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8429
Author(s):  
Luis M. Montilla ◽  
Emy Miyazawa ◽  
Alfredo Ascanio ◽  
María López-Hernández ◽  
Gloria Mariño-Briceño ◽  
...  
Keyword(s):  
Community Structure ◽  
Coral Reef ◽  
Standard Error ◽  
Scleractinian Coral ◽  
Statistical Power ◽  
Sampling Design ◽  
Sampling Effort ◽  
Monitoring Programs ◽  
Coral Monitoring

The characteristics of coral reef sampling and monitoring are highly variable, with numbers of units and sampling effort varying from one study to another. Numerous works have been carried out to determine an appropriate effect size through statistical power; however, these were always from a univariate perspective. In this work, we used the pseudo multivariate dissimilarity-based standard error (MultSE) approach to assess the precision of sampling scleractinian coral assemblages in reefs of Venezuela between 2017 and 2018 when using different combinations of number of transects, quadrats and points. For this, the MultSE of 36 sites previously sampled was estimated, using four 30m-transects with 15 photo-quadrats each and 25 random points per quadrat. We obtained that the MultSE was highly variable between sites and is not correlated with the univariate standard error nor with the richness of species. Then, a subset of sites was re-annotated using 100 uniformly distributed points, which allowed the simulation of different numbers of transects per site, quadrats per transect and points per quadrat using resampling techniques. The magnitude of the MultSE stabilized by adding more transects, however, adding more quadrats or points does not improve the estimate. For this case study, the error was reduced by half when using 10 transects, 10 quadrats per transect and 25 points per quadrat. We recommend the use of MultSE in reef monitoring programs, in particular when conducting pilot surveys to optimize the estimation of the community structure.

Evaluation of the statistical power for multiple tests: a case study

2009 ◽  
Vol 8 (1) ◽  
pp. 5-11 ◽  
Author(s):  
Adeline Yeo ◽  
Yongming Qu
Keyword(s):  
Statistical Power ◽  
Multiple Tests

Using confidence intervals to estimate the response of salmon populations (Oncorhynchus spp.) to experimental habitat alterations

2005 ◽  
Vol 62 (12) ◽  
pp. 2716-2726 ◽  
Author(s):  
Michael J Bradford ◽  
Josh Korman ◽  
Paul S Higgins
Keyword(s):  
Confidence Intervals ◽  
Effect Size ◽  
Null Hypothesis ◽  
Statistical Power ◽  
Habitat Restoration ◽  
Coho Salmon ◽  
Fish Habitat ◽  
Monitoring Program ◽  
Considerable Uncertainty ◽  
Monitoring Programs

There is considerable uncertainty about the effectiveness of fish habitat restoration programs, and reliable monitoring programs are needed to evaluate them. Statistical power analysis based on traditional hypothesis tests are usually used for monitoring program design, but here we argue that effect size estimates and their associated confidence intervals are more informative because results can be compared with both the null hypothesis of no effect and effect sizes of interest, such as restoration goals. We used a stochastic simulation model to compare alternative monitoring strategies for a habitat alteration that would change the productivity and capacity of a coho salmon (Oncorhynchus kisutch) producing stream. Estimates of the effect size using a freshwater stock–recruit model were more precise than those from monitoring the abundance of either spawners or smolts. Less than ideal monitoring programs can produce ambiguous results, which are cases in which the confidence interval includes both the null hypothesis and the effect size of interest. Our model is a useful planning tool because it allows the evaluation of the utility of different types of monitoring data, which should stimulate discussion on how the results will ultimately inform decision-making.

scholarly journals The Impacts of Biotechnology on Biodiversity in Global Health: A Case Study on Avian Influenza in Bangladesh

2015 ◽  
Vol 4 (2) ◽  
pp. 102
Author(s):  
Muhiuddin Haider ◽  
Milind Patel ◽  
Priyanka Bhattacharjee ◽  
Maariya Bassa
Keyword(s):  
Biological Control ◽  
Avian Influenza ◽  
Artificial Insemination ◽  
Specific Region ◽  
Food Sources ◽  
Ecosystem Change ◽  
Animal Biotechnology ◽  
Living Organisms

Biodiversity is the variability of between genetics, species, or ecosystems of living organisms within a specific region. Biodiversity is essential for sustaining healthy living networks and systems because it allows for a variety of food sources, medicine, and biological control, while also playing a significant role in atmospheric regulation, nutrient cycling, and pollination. Loss of biodiversity and ecosystem change increases the risk of the emergence or spreading of infectious diseases and global pandemics such as the Avian Influenza (AI H5N1). Biotechnology is one solution for reducing, and ultimately eliminating, the transmission of avian influenza. Traditional methods of treating infected animals, such as common vaccines, are temporary solutions that have no effect on the biodiversity of an ecosystem. Methods in animal biotechnology such as artificial insemination, embryo transfer, and <em>in vitro </em>fertilization have led to developments of cheaper, safer, and more effective vaccines. Livestock that have been treated for H5N1, as well as those that are healthy and have never been infected have proven to increase the diversity, leading to the elimination of specific issues. Similar effects are attainable if these animal biotechnology methods were to be used on poultry infected with the avian influenza virus.

scholarly journals Minimum time required to detect population trends: the need for long-term monitoring programs

2018 ◽  
Author(s):  
Easton R White
Keyword(s):  
Time Series ◽  
Statistical Power ◽  
Conservation Status ◽  
Species Conservation ◽  
Population Data ◽  
Iucn Red List ◽  
Series Length ◽  
Large Variability ◽  
Monitoring Programs

Long-term time series are necessary to better understand population dynamics, assess species' conservation status, and make management decisions. However, population data are often expensive, requiring a lot of time and resources. What is the minimum population time series length required to detect significant trends in abundance? I first present an overview of the theory and past work that has tried to address this question. As a test of these approaches, I then examine 822 populations of vertebrate species. I show that 72% of time series required at least 10 years of continuous monitoring in order to achieve a high level of statistical power. However, the large variability between populations casts doubt on commonly used simple rules of thumb, like those employed by the IUCN Red List. I argue that statistical power needs to be considered more often in monitoring programs. Short time series are likely under-powered and potentially misleading.

scholarly journals Transects, quadrats, or points? What is the best combination to get a precise estimation of a coral community?

2019 ◽  
Author(s):  
Luis M. Montilla ◽  
Emy Miyazawa ◽  
Alfredo Ascanio ◽  
María López-Hernández ◽  
Gloria Mariño-Briceño ◽  
...  
Keyword(s):  
Community Structure ◽  
Coral Reef ◽  
Effect Size ◽  
Standard Error ◽  
Scleractinian Coral ◽  
Statistical Power ◽  
Coral Community ◽  
Sampling Effort ◽  
Precise Estimation

ABSTRACTThe characteristics of coral reef sampling and monitoring are highly variable, with numbers of units and sampling effort varying from one study to another. Numerous works have been carried out to determine an appropriate effect size through statistical power, however, always from a univariate perspective. In this work, we used the pseudo multivariate dissimilarity-based standard error (MultSE) approach to assess the precision of sampling scleractinian coral assemblages in reefs of Venezuela between 2017 and 2018 when using different combinations of number of transects, quadrats and points. For this, the MultSE of 36 sites previously sampled was estimated, using four 30m-transects with 15 photo-quadrats each and 25 random points per quadrat. We obtained that the MultSE was highly variable between sites and is not correlated with the univariate standard error nor with the richness of species. Then, a subset of sites was re-annotated using 100 uniformly distributed points, which allowed the simulation of different numbers of transects per site, quadrats per transect and points per quadrat using resampling techniques. The magnitude of the MultSE stabilized by adding more transects, however, adding more quadrats or points does not improve the estimate. For this case study, the error was reduced by half when using 10 transects, 10 quadrats per transect and 25 points per quadrat. We recommend the use of MultSE in reef monitoring programs, in particular when conducting pilot surveys to optimize the estimation of the community structure.

Estimating the diffusion length in the deepest section of ice cores; A case study for MIS19 in Dome-C

2021 ◽  
Author(s):  
Thomas Laepple ◽  
Thomas Münch ◽  
Torben Kunz ◽  
Mathieu Casado ◽  
Maria Hoerhold
Keyword(s):  
Diffusion Length ◽  
Ice Core ◽  
Ice Cores ◽  
Climate Information ◽  
Climate Signal ◽  
A Value ◽  
Recovery Strategies ◽  
Length Estimate ◽  
And Diffusion

&lt;p&gt;To recover very old climate information from ice core records, one needs to interpret the deepest part of an ice core. As the oldest record, the Dome-C ice core can serve as an analogue for the Beyond EPICA Oldest Ice Core that is currently being drilled.&lt;br&gt;&lt;br&gt;Pol et al., EPSL 2010 analyzed high resolution water isotope data from the Dome-C ice core and found evidence for a limited preservation of climate variability in the deep section of the core due to mixing and diffusion. For instance, for Marine Isotope Stage 19, the study estimated a mixing/diffusion length between 40 and 60 cm, a value more than double than&amp;#160;what is&amp;#160;predicted by current firn and&amp;#160;ice diffusion&amp;#160;models. Knowing the diffusion length is important to interpret the isotope signal and is the basis to deconvolve climate records. As a result, it is key to bridge the gap in the estimation of the diffusion length between potentially biased statistical methods and firn and ice diffusion models.&lt;br&gt;We review this diffusion length estimate for MIS19, and also outline a new&amp;#160;general&amp;#160;method how to estimate the diffusion length in&amp;#160;highly thinned deep ice.&amp;#160; This approach presents&amp;#160;an important tool for better characterizing the preservation of the climate signal in old ice&amp;#160;and thus&amp;#160;for&amp;#160;designing optimal sampling and recovery strategies.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

Improved moth flame optimization algorithm to optimize cost-oriented two-sided assembly line balancing

2019 ◽  
Vol 37 (2) ◽  
pp. 638-663
Author(s):  
Mohd Fadzil Faisae Ab. Rashid ◽  
Ahmad Nasser Mohd Rose ◽  
Nik Mohd Zuki Nik Mohamed ◽  
Fadhlur Rahman Mohd Romlay
Keyword(s):  
Assembly Line ◽  
Assembly Line Balancing ◽  
Line Balancing ◽  
Benchmark Problems ◽  
Labor Costs ◽  
Power Cost ◽  
Content Type ◽  
Set Up ◽  
Line Design

Purpose This paper aims to propose an improved Moth Flame Optimization (I-MFO) algorithm to optimize the cost-oriented two-sided assembly line balancing (2S-ALB). Prior to the decision to assemble a new product, the manufacturer will carefully study and optimize the related cost to set up and run the assembly line. For the first time in ALB, the power cost is modeled together with the equipment, set up and labor costs. Design/methodology/approach I-MFO was proposed by introducing a global reference flame mechanism to guide the global search direction. A set of benchmark problems was used to test the I-MFO performance. Apart from the benchmark problems, a case study from a body shop assembly was also presented. Findings The computational experiment indicated that the I-MFO obtained promising results compared to comparison algorithms, which included the particle swarm optimization, Cuckoo Search and ant colony optimization. Meanwhile, the results from the case study showed that the proposed cost-oriented 2S-ALB model was able to assist the manufacturer in making better decisions for different planning periods. Originality/value The main contribution of this work is the global reference flame mechanism for MFO algorithm. Furthermore, this research introduced a new cost-oriented model that considered power consumption in the assembly line design.

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