Geology topics

Nicholas Som

Publications and source records attributed to Nicholas Som.

3 recordsLinked to original sources

USGS2014

Applications of spatial statistical network models to stream data

Streams and rivers host a significant portion of Earth's biodiversity and provide important ecosystem services for human populations. Accurate information regarding the status and trends of stream resources is vital for their effective conservation and management. Most statistical techniques applied to data measured on stream networks were developed for terrestrial applications and are not optimized for streams. A new class of spatial statistical model, based on valid covariance structures for stream networks, can be used with many common types of stream data (e.g., water quality attributes, habitat conditions, biological surveys) through application of appropriate distributions (e.g., Gaussian, binomial, Poisson). The spatial statistical network models account for spatial autocorrelation (i.e., nonindependence) among measurements, which allows their application to databases with clustered measurement locations. Large amounts of stream data exist in many areas where spatial statistical analyses could be used to develop novel insights, improve predictions at unsampled sites, and aid in the design of efficient monitoring strategies at relatively low cost. We review the topic of spatial autocorrelation and its effects on statistical inference, demonstrate the use of spatial statistics with stream datasets relevant to common research and management questions, and discuss additional applications and development potential for spatial statistics on stream networks. Free software for implementing the spatial statistical network models has been developed that enables custom applications with many stream databases.

WIREs Water↗

USGS2013

Modelling dendritic ecological networks in space: anintegrated network perspective

Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of ecological networks, or in 2-D space, may be inadequate for studying the influence of structure and connectivity on ecological processes within DENs. We propose a conceptual taxonomy of network analysis methods that account for DEN characteristics to varying degrees and provide a synthesis of the different approaches within the context of stream ecology. Within this context, we summarise the key innovations of a new family of spatial statistical models that describe spatial relationships in DENs. Finally, we discuss how different network analyses may be combined to address more complex and novel research questions. While our main focus is streams, the taxonomy of network analyses is also relevant anywhere spatial patterns in both network and 2-D space can be used to explore the influence of multi-scale processes on biota and their habitat (e.g. plant morphology and pest infestation, or preferential migration along stream or road corridors).

Ecology Letters↗

USGS2012

Fatality estimator user’s guide

This publication is the User's Guide for software developed to estimate wildlife fatalities at wind-power facilities, although the software is applicable to a variety of circumstances in which the objective is to estimate the size of a superpopulation and the probability of detection of the individuals is less than one. Simple counts of carcasses do not accurately reflect fatality and do not allow comparison among locations because carcasses may be detected at different rates. This software uses data collected during carcass searches and knowledge of detection rates to accurately estimate the number of fatalities and to provide a measure of precision associated with the estimate. These estimates are fundamental to understanding acute and cumulative effects of wind power on wildlife populations. Only carcasses judged to have been killed after the previous search should be included in the fatality data set submitted to this estimator software. This estimator already corrects for carcasses missed in previous searches, so carcasses judged to have been missed at least once should be considered “incidental” and not included in the fatality data set used to estimate fatality. Note: When observed carcass count is <5 (including 0 for species known to be at risk, but not observed), USGS Data Series 881 ( https://pubs.usgs.gov/ds/0881/ ) is recommended for fatality estimation.

Data Series↗