Summary: Resource selection estimated by logistic regression is used increasingly in studies to identify critical resources for animal populations and to predict species occurrence. Most frequently, individual animals are monitored and pooled to estimate population‐level effects without regard to group or individual‐level variation. Pooling assumes that both observations and their errors are independent, and resource selection is constant given individual variation in resource availability. Although researchers have identified ways to minimize autocorrelation, variation between individuals caused by differences in selection or available resources, including functional responses in resource selection, have not been well addressed. Here we review random‐effects models and their application to resource selection modelling to overcome these common limitations. We present a simple case study of an analysis of resource selection by grizzly bears in the foothills of the Canadian Rocky Mountains with and without random effects. Both categorical and continuous variables in the grizzly bear model differed in interpretation, both in statistical significance and coefficient sign, depending on how a random effect was included. We used a simulation approach to clarify the application of random effects under three common situations for telemetry studies: (a) discrepancies in sample sizes among individuals; (b) differences among individuals in selection where availability is constant; and (c) differences in availability with and without a functional response in resource selection. We found that random intercepts accounted for unbalanced sample designs, and models with random intercepts and coefficients improved model fit given the variation in selection among individuals and functional responses in selection. Our empirical example and simulations demonstrate how including random effects in resource selection models can aid interpretation and address difficult assumptions limiting their generality. This approach will allow researchers to appropriately estimate marginal (population) and conditional (individual) responses, and account for complex grouping, unbalanced sample designs and autocorrelation.

Current research targeting filtered macrobial environmental DNA (eDNA) often relies upon cold ambient temperatures at various stages, including the transport of water samples from the field to the laboratory and the storage of water and/or filtered samples in the laboratory. This poses practical limitations for field collections in locations where refrigeration and frozen storage is difficult or where samples must be transported long distances for further processing and screening. This study demonstrates the successful preservation of eDNA at room temperature (20 °C) in two lysis buffers, CTAB and Longmire's, over a 2‐week period of time. Moreover, the preserved eDNA samples were seamlessly integrated into a phenol–chloroform–isoamyl alcohol (PCI) DNA extraction protocol. The successful application of the eDNA extraction to multiple filter membrane types suggests the methods evaluated here may be broadly applied in future eDNA research. Our results also suggest that for many kinds of studies recently reported on macrobial eDNA, detection probabilities could have been increased, and at a lower cost, by utilizing the Longmire's preservation buffer with a PCI DNA extraction.

Three mantras often guide species and ecosystem management: (i) for preventing invasions by harmful species, ‘early detection and rapid response’; (ii) for conserving imperilled native species, ‘protection of biodiversity hotspots’; and (iii) for assessing biosecurity risk, ‘an ounce of prevention equals a pound of cure.’ However, these and other management goals are elusive when traditional sampling tools (e.g. netting, traps, electrofishing, visual surveys) have poor detection limits, are too slow or are not feasible. One visionary solution is to use an organism’s DNA in the environment (eDNA), rather than the organism itself, as the target of detection. In this issue of Molecular Ecology, Thomsen et al. (2012) provide new evidence demonstrating the feasibility of this approach, showing that eDNA is an accurate indicator of the presence of an impressively diverse set of six aquatic or amphibious taxa including invertebrates, amphibians, a fish and a mammal in a wide range of freshwater habitats. They are also the first to demonstrate that the abundance of eDNA, as measured by qPCR, correlates positively with population abundance estimated with traditional tools. Finally, Thomsen et al. (2012) demonstrate that next‐generation sequencing of eDNA can quantify species richness. Overall, Thomsen et al. (2012) provide a revolutionary roadmap for using eDNA for detection of species, estimates of relative abundance and quantification of biodiversity.

Environmental DNA (eDNA) is a sensitive technique for early detection of rare species, including bighead (Hypophthalmichthys nobilis) and silver (Hypophthalmichthys molitrix) carp, which are incipient invaders of the Great Lakes. Since 2009, 2822 samples have been collected from the Great Lakes basin to delimit the extent of Asian carp incursions. Samples collected in the Chicago Area Waterway System and in the western basin of Lake Erie indicate the presence of Asian carp DNA in the Great Lakes. These positive eDNA detections are within 6 and 4 km from where bighead carps were recovered in Lake Calumet, near Lake Michigan (2010), and from Sandusky Bay, Lake Erie (2000), respectively. To implement a Great Lakes surveillance plan for protecting imperiled species and reducing damages from invasive species, federal, state, and provincial agencies will need to cooperatively plan and implement a surveillance program that employs the unique strengths of multiple sampling tools, including eDNA methods.