Well-spread samples with dynamic sample sizes.

A spatial sampling design determines where sample locations are placed in a study area so that population parameters can be estimated with relatively high precision. If the response variable has spatial trends, spatially balanced or well-spread designs give precise results for commonly used estimators. This article proposes a new method that draws well-spread samples over arbitrary auxiliary spaces and can be used for master sampling applications. All we require is a measure of the distance between population units. Numerical results show that the method generates well-spread samples and compares favorably with existing designs. We provide an example application using several auxiliary variables to estimate total aboveground biomass over a large study area in Eastern Amazonia, Brazil. Multipurpose surveys are also considered, where the totals of aboveground biomass, primary production, and clay content (3 responses) are estimated from a single well-spread sample over the auxiliary space.

Ground-level Unmanned Aerial System Imagery Coupled with Spatially Balanced Sampling and Route Optimization to Monitor Rangeland Vegetation.

Rangeland ecosystems cover 3.6 billion hectares globally with 239 million hectares located in the United States. These ecosystems are critical for maintaining global ecosystem services. Monitoring vegetation in these ecosystems is required to assess rangeland health, to gauge habitat suitability for wildlife and domestic livestock, to combat invasive weeds, and to elucidate temporal environmental changes. Although rangeland ecosystems cover vast areas, traditional monitoring techniques are often time-consuming and cost-inefficient, subject to high observer bias, and often lack adequate spatial information. Image-based vegetation monitoring is faster, produces permanent records (i.e., images), may result in reduced observer bias, and inherently includes adequate spatial information. Spatially balanced sampling designs are beneficial in monitoring natural resources. A protocol is presented for implementing a spatially balanced sampling design known as balanced acceptance sampling (BAS), with imagery acquired from ground-level cameras and unmanned aerial systems (UAS). A route optimization algorithm is used in addition to solve the 'travelling salesperson problem' (TSP) to increase time and cost efficiency. While UAS images can be acquired 2-3x faster than handheld images, both types of images are similar to each other in terms of accuracy and precision. Lastly, the pros and cons of each method are discussed and examples of potential applications for these methods in other ecosystems are provided.

Spatially balanced sampling designs for environmental surveys.

Some environmental studies use non-probabilistic sampling designs to draw samples from spatially distributed populations. Unfortunately, these samples can be difficult to analyse statistically and can give biased estimates of population characteristics. Spatially balanced sampling designs are probabilistic designs that spread the sampling effort evenly over the resource. These designs are particularly useful for environmental sampling because they produce good-sample coverage over the resource, they have precise design-based estimators and they can potentially reduce the sampling cost. The most popular spatially balanced design is Generalized Random Tessellation Stratified (GRTS), which has many desirable features including a spatially balanced sample, design-based estimators and the ability to select spatially balanced oversamples. This article considers the popularity of spatially balanced sampling, reviews several spatially balanced sampling designs and shows how these designs can be implemented in the statistical programming language R. We hope to increase the visibility of spatially balanced sampling and encourage environmental scientists to use these designs.

Effects of increasing acidity on metal(loid) bioprecipitation in groundwater: column studies.

Large-scale column experiments were carried out over a period of 545 days to assess the effect of increasing acidity on bacterial denitrification, sulfate reduction, and metal(loid) bioprecipitation in groundwater affected by acid mine drainage. At a groundwater pH of 5.5, denitrification and Cu2+ removal, probably via malachite (Cu2(OH)2CO3) precipitation, were observed in the ethanol-amended column. Sulfate reduction, sulfide production, and Zn2+ removal were also observed, with Zn2+ removal observed in the zone of sulfate reduction, indicating likely precipitation as sphalerite (ZnS). Se6+ removal was also observed in the sulfate reducing zone, probably as direct bioreduction to elemental selenium via ethanol/acetate oxidation or sulfide oxidation precipitating elemental sulfur. A step decrease in groundwater pH from 5.5 to 4.25 resulted in increased denitrification and sulfate reduction half-lives, migration of both these redox zones along the ethanol-amended column, and the formation of an elevated Cu2+ plume. Additionally, an elevated Zn2+ plume formed in the previous sulfate reducing zone of the ethanol-amended column, suggesting dissolution of precipitated sphalerite as a result of the reduction in groundwater pH. As Cu2+ passed through the zone of sphalerite dissolution, SEM imaging and EDS detection suggested that Cu2+ removal had occurred via chalcocite (Cu2S) or covellite (CuS) precipitation.

Estimation of ethanol mass delivery to groundwater from silicone polymer mats.

Hollow-fiber silicone tubing, coiled and shaped as mats, has been evaluated for its potential to provide predictable delivery of ethanol to aquifers to promote reducing conditions for enhanced bioremediation of a range of contaminants in groundwater. A model was developed to predict the steady-state mass flux of diffusional ethanol delivery to an external aqueous phase from an aqueous ethanol solution present inside the polymer tubing mat, and an effective diffusion coefficient of ethanol through the silicone tubing of 1.22 x 10(-6) cm2 s(-1) was determined experimentally. The model was then validated in column-scale laboratory and field experiments where polymer mats configured as permeable reactive barriers maintained uniform diffusive delivery of ethanol. Steady-state mass flux delivery ratios of ethanol through the polymer tubing wall of 1.45 (+/-0.18) x 10(6) to 1.64 (+/-0.17) x 10(6) s cm(-1) were determined under laboratory conditions, and 2.43 (+/-1.47) x 10(6) s cm(-1) under field conditions, which were found to be statistically similar to model-predicted ethanol mass flux delivery ratios.