Geology topics

D.S. Johnson

Publications and source records attributed to D.S. Johnson.

3 recordsLinked to original sources

USGS2021

A Bayesian Dirichlet process community occupancy model to estimate community structure and species similarity

Community occupancy models estimate species‐specific parameters while sharing information across species by treating parameters as sampled from a common distribution. When communities consist of discrete groups, shrinkage of estimates towards the community mean can mask differences among groups. Infinite mixture models using a Dirichlet process (DP) distribution, in which the number of latent groups is estimated from the data, have been proposed as a solution. In addition to community structure, these models estimate species similarity, which allows testing hypotheses about whether traits drive species response to environmental conditions. We develop a community occupancy model (COM) using a DP distribution to model species‐level parameters. Because clustering algorithms are sensitive to dimensionality and distinctiveness of clusters, we conducted a simulation study to explore performance of the DP‐COM with different dimensions (i.e., different numbers of model parameters with species‐level DP random effects) and under varying cluster differences. Because the DP‐COM is computationally expensive, we compared its estimates to a COM with a normal random species effect. We further applied the DP‐COM model to a bird dataset from Uganda. Estimates of the number of clusters and species cluster identity improved with increasing difference among clusters and increasing dimensions of the DP; but the number of clusters was always overestimated. Estimates of number of sites occupied and species and community level covariate coefficients on occupancy probability were generally unbiased with (near‐) nominal 95% Bayesian Credible Interval coverage. Accuracy of estimates from the normal and the DP‐COM were similar. The DP‐COM clustered 166 bird species into 27 clusters regarding their affiliation with open or woodland habitat and distance to oil wells. Estimates of covariate coefficients were similar between a normal and the DP‐COM. Except sunbirds, species within a family were not more similar in their response to these covariates than the overall community. Given that estimates were consistent between the normal and the DP‐COM, and considering the computational burden for the DP models, we recommend using the DP‐COM only when the analysis focuses on community structure and species similarity, as these quantities can only be obtained under the DP‐COM.

Ecological Applications↗

USGS2013

Temporal variation and scale in movement-based resource selection functions

A common population characteristic of interest in animal ecology studies pertains to the selection of resources. That is, given the resources available to animals, what do they ultimately choose to use? A variety of statistical approaches have been employed to examine this question and each has advantages and disadvantages with respect to the form of available data and the properties of estimators given model assumptions. A wealth of high resolution telemetry data are now being collected to study animal population movement and space use and these data present both challenges and opportunities for statistical inference. We summarize traditional methods for resource selection and then describe several extensions to deal with measurement uncertainty and an explicit movement process that exists in studies involving high-resolution telemetry data. Our approach uses a correlated random walk movement model to obtain temporally varying use and availability distributions that are employed in a weighted distribution context to estimate selection coefficients. The temporally varying coefficients are then weighted by their contribution to selection and combined to provide inference at the population level. The result is an intuitive and accessible statistical procedure that uses readily available software and is computationally feasible for large datasets. These methods are demonstrated using data collected as part of a large-scale mountain lion monitoring study in Colorado, USA.

Statistical Methodology↗

USGS2009

Environmental and human influences on trumpeter swan habitat occupancy in Alaska

Approximately 70-80% of the entire population of the Trumpeter Swan (Cygnus huccinator) depends for reproduction on wetlands in Alaska. This makes the identification of important habitat features and the effects of human interactions important for the species' long-term management. We analyzed the swan's habitat preferences in five areas throughout the state and found that swan broods occupied some wetland types, especially larger closed-basin wetlands such as lakes and ponds, at rates much higher than they occupied other wetland types, such as shrubby or forested wetlands. We also found a negative effect of transportation infrastructure on occupancy by broods in and around the Minto Flats State Game Refuge, Kenai National Wildlife Refuge, and Tetlin National Wildlife Refuge. This finding is of particular interest because much of the Minto Flats refuge has recently been licensed for oil and gas exploration and parts of the Kenai refuge have been developed in the past. We also investigated the potential effects of the shrinkage of closed-basin ponds on habitat occupancy by nesting Trumpeter Swans. We compared nesting swans' use of ponds with changes in the ponds' size and other characteristics from 1982 to 1996 and found no relationships between occupancy and changes in pond size. However, we believe that the recent and rapid growth of Trumpeter Swan populations in Alaska may become limited by available breeding habitat, and anthropogenic and climate-induced changes to the swan's breeding habitats have the potential to limit future production. ?? 2009 by The Cooper Ornithological Society. All rights reserved.

Condor↗