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Composite estimation to combine spatially overlapping environmental monitoring surveys

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  • Steven L Garman
  • Cindy L Yu
  • Yuyang Li

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 monitoring surveys administered by the Bureau of Land Management (BLM) that entirely overlap. Using 2015–18 data and 13 land-health indicators, we obtained and compared survey and composite indicator estimates of percent area meeting land-health standards for sagebrush communities in Wyoming’s Greater Sage-Grouse (Centrocercus urophasianus) Core and NonCore conservation areas on BLM-managed lands. We statistically assessed differences in indicator estimates between the conservation areas using composite estimates and estimates of the two surveys individually. We found composite variance to be about six to 24 units lower than 37% of the survey variances and composite estimates to differ by about six to 10 percentage points from six survey estimates. The composite improvements resulted in finding 11 indicators to statistically differ (p

Suggested Citation

  • Steven L Garman & Cindy L Yu & Yuyang Li, 2024. "Composite estimation to combine spatially overlapping environmental monitoring surveys," PLOS ONE, Public Library of Science, vol. 19(3), pages 1-20, March.
    • Handle: RePEc:plo:pone00:0299306
    DOI: 10.1371/journal.pone.0299306
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    References listed on IDEAS

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    1. Stevens, Don L. & Olsen, Anthony R., 2004. "Spatially Balanced Sampling of Natural Resources," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 262-278, January.
    2. J.N.K. Rao, 2008. "Some Methods for Small Area Estimation," Rivista Internazionale di Scienze Sociali, Vita e Pensiero, Pubblicazioni dell'Universita' Cattolica del Sacro Cuore, vol. 116(4), pages 387-405.
    3. Albert Satorra & Eva Ventura & Alex Costa, 2006. "Improving small area estimation by combining surveys: new perspectives in regional statistics," Economics Working Papers 969, Department of Economics and Business, Universitat Pompeu Fabra.
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