Composite estimation to combine spatially overlapping environmental monitoring surveys
Steven L. Garman, Cindy L. Yu, Yuyang Li

TL;DR
This paper introduces a statistical method called composite estimation to improve the precision of environmental monitoring data from overlapping surveys.
Contribution
The paper presents a novel composite estimator for combining overlapping environmental surveys to enhance precision and accuracy.
Findings
Composite variance was significantly lower than individual survey variances.
Composite estimates identified more statistically significant differences between conservation areas.
The method is efficient for overlapping surveys and applicable to small area analyses.
Abstract
Long-term environmental monitoring surveys are designed to achieve a desired precision (measured by variance) of resource conditions based on natural variability information. Over time, increases in resource variability and in data use to address issues focused on small areas with limited sample sizes require bolstering of attainable precision. It is often prohibitive to do this by increasing sampling effort. In cases with spatially overlapping monitoring surveys, composite estimation offers a statistical way to obtain a precision-weighted combination of survey estimates to provide improved population estimates (more accurate) with improved precisions (lower variances). We present a composite estimator for overlapping surveys, a summary of compositing procedures, and a case study to illustrate the procedures and benefits of composite estimation. The study uses the two terrestrial…
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Taxonomy
TopicsRangeland and Wildlife Management · Fire effects on ecosystems · Turfgrass Adaptation and Management
