spsurvey: Spatial Sampling Design and Analysis in R.

spsurvey is an R package for design-based statistical inference, with a focus on spatial data. spsurvey provides the generalized random-tessellation stratified (GRTS) algorithm to select spatially balanced samples via the grts() function. The grts() function flexibly accommodates several sampling design features, including stratification, varying inclusion probabilities, legacy (or historical) sites, minimum distances between sites, and two options for replacement sites. spsurvey also provides a suite of data analysis options, including categorical variable analysis (cat_analysis()), continuous variable analysis cont_analysis()), relative risk analysis (relrisk_analysis()), attributable risk analysis (attrisk_analysis()), difference in risk analysis (diffrisk_analysis()), change analysis (change_analysis()), and trend analysis (trend_analysis()). In this manuscript, we first provide background for the GRTS algorithm and the analysis approaches and then show how to implement them in spsurvey. We find that the spatially balanced GRTS algorithm yields more precise parameter estimates than simple random sampling, which ignores spatial information.

Physical habitat in conterminous US streams and Rivers, part 2: A quantitative assessment of habitat condition.

Rigorous assessments of the ecological condition of water resources and the effect of human activities on those waters require quantitative physical, chemical, and biological data. The U.S. Environmental Protection Agency's river and stream surveys quantify river and stream bed particle size and stability, instream habitat complexity and cover, riparian vegetation cover and structure, and anthropogenic disturbance activities. Physical habitat is strongly controlled by natural geoclimatic factors that co-vary with human activities. We expressed the anthropogenic alteration of physical habitat as O/E ratios of observed habitat metric values divided by values expected under least-disturbed reference conditions, where site-specific expected values vary given their geoclimatic and geomorphic context. We set criteria for good, fair, and poor condition based on the distribution of O/E values in regional least-disturbed reference sites. Poor conditions existed in 22-24% of the 1.2 million km of streams and rivers in the conterminous U.S. for riparian human disturbance, streambed sediment and riparian vegetation cover, versus 14% for instream habitat complexity. Based on the same four indicators, the percentage of stream length in poor condition within 9 separate U.S. ecoregions ranged from 4% to 42%. Associations of our physical habitat indices with anthropogenic pressures demonstrate the scope of anthropogenic habitat alteration; habitat condition was negatively related to the level of anthropogenic disturbance nationally and in nearly all ecoregions. Relative risk estimates showed that streams and rivers with poor sediment, riparian cover complexity, or instream habitat cover conditions were 1.4 to 2.6 times as likely to also have fish or macroinvertebrate assemblages in poor condition. Our physical habitat condition indicators help explain deviations in biological conditions from those observed among least-disturbed sites and inform management actions for rehabilitating impaired waters and mitigating further ecological degradation.