Monitoring dynamic spatio-temporal ecological processes optimally.

Population dynamics vary in space and time. Survey designs that ignore these dynamics may be inefficient and fail to capture essential spatio-temporal variability of a process. Alternatively, dynamic survey designs explicitly incorporate knowledge of ecological processes, the associated uncertainty in those processes, and can be optimized with respect to monitoring objectives. We describe a cohesive framework for monitoring a spreading population that explicitly links animal movement models with survey design and monitoring objectives. We apply the framework to develop an optimal survey design for sea otters in Glacier Bay. Sea otters were first detected in Glacier Bay in 1988 and have since increased in both abundance and distribution; abundance estimates increased from 5 otters to >5,000 otters, and they have spread faster than 2.7 km/yr. By explicitly linking animal movement models and survey design, we are able to reduce uncertainty associated with forecasting occupancy, abundance, and distribution compared to other potential random designs. The framework we describe is general, and we outline steps to applying it to novel systems and taxa.

An integrated data model to estimate spatiotemporal occupancy, abundance, and colonization dynamics.

Ecological invasions and colonizations occur dynamically through space and time. Estimating the distribution and abundance of colonizing species is critical for efficient management or conservation. We describe a statistical framework for simultaneously estimating spatiotemporal occupancy and abundance dynamics of a colonizing species. Our method accounts for several issues that are common when modeling spatiotemporal ecological data including multiple levels of detection probability, multiple data sources, and computational limitations that occur when making fine-scale inference over a large spatiotemporal domain. We apply the model to estimate the colonization dynamics of sea otters (Enhydra lutris) in Glacier Bay, in southeastern Alaska.

Using variance components to estimate power in a hierarchically nested sampling design.

We used variance components to assess allocation of sampling effort in a hierarchically nested sampling design for ongoing monitoring of early life history stages of the federally endangered Devils Hole pupfish (DHP) (Cyprinodon diabolis). Sampling design for larval DHP included surveys (5 days each spring 2007-2009), events, and plots. Each survey was comprised of three counting events, where DHP larvae on nine plots were counted plot by plot. Statistical analysis of larval abundance included three components: (1) evaluation of power from various sample size combinations, (2) comparison of power in fixed and random plot designs, and (3) assessment of yearly differences in the power of the survey. Results indicated that increasing the sample size at the lowest level of sampling represented the most realistic option to increase the survey's power, fixed plot designs had greater power than random plot designs, and the power of the larval survey varied by year. This study provides an example of how monitoring efforts may benefit from coupling variance components estimation with power analysis to assess sampling design.

Recursive Bayesian computation facilitates adaptive optimal design in ecological studies.

Optimal design procedures provide a framework to leverage the learning generated by ecological models to flexibly and efficiently deploy future monitoring efforts. At the same time, Bayesian hierarchical models have become widespread in ecology and offer a rich set of tools for ecological learning and inference. However, coupling these methods with an optimal design framework can become computationally intractable. Recursive Bayesian computation offers a way to substantially reduce this computational burden, making optimal design accessible for modern Bayesian ecological models. We demonstrate the application of so-called prior-proposal recursive Bayes to optimal design using a simulated data binary regression and the real-world example of monitoring and modeling sea otters in Glacier Bay, Alaska. These examples highlight the computational gains offered by recursive Bayesian methods and the tighter fusion of monitoring and science that those computational gains enable.

An introduced and a native vertebrate hybridize to form a genetic bridge to a second native species.

The genetic impacts of hybridization between native and introduced species are of considerable conservation concern, while the possibility of reticulate evolution affects our basic understanding of how species arise and shapes how we use genetic data to understand evolutionary diversification. By using mitochondrial NADH dehydrogenase subunit 2 (ND2) sequences and 467 amplified fragment-length polymorphism nuclear DNA markers, we show that the introduced white sucker (Catostomus commersoni) has hybridized with two species native to the Colorado River Basin--the flannelmouth sucker (Catostomus latipinnis) and the bluehead sucker (Catostomus discobolus). Hybrids between the flannelmouth sucker and white sucker have facilitated introgression between the two native species, previously isolated by reproductive barriers, such that individuals exist with contributions from all three genomes. Most hybrids had the mitochondrial haplotype of the introduced white sucker, emphasizing its pivotal role in this three-way hybridization. Our findings highlight how introduced species can threaten the genetic integrity of not only one species but also multiple previously reproductively isolated species. Furthermore, this complex three-way reticulate (as opposed to strictly bifurcating) evolution suggests that seeking examples in other vertebrate systems might be productive. Although the present study involved an introduced species, similar patterns of hybridization could result from natural processes, including stream capture or geological formations (e.g., the Bering land bridge).

Infection by a black spot-causing species of Uvulifer and associated opercular alterations in fishes from a high-desert stream in Wyoming.

Black spot is a common disease syndrome of freshwater fishes. This study provides information on the rank of density of the black spot agent and opercular bone alterations associated with at least one digenean, Uvulifer sp., infecting native and non-native catostomids and cyprinids of the Upper Colorado River Basin. We evaluated the density rank of pigmented metacercariae and associated alterations in the operculum of the bluehead sucker Catostomus discobolus, flannelmouth sucker C. latipinnis, white sucker C. commersoni, catostomid hybrids, roundtail chub Gila robusta, and creek chub Semotilus atromaculatus, sampled from Muddy Creek, Wyoming, USA in 2003 or 2004. All fish species contained individuals that exhibited gross signs of the black spot agent. Bluehead and flannelmouth suckers had 100% prevalence of infection. Although the other suckers and chubs contained encysted metacercariae in at least one individual, the presence of pigmented metacercariae was not apparent (i.e. based on gross observations) in many individuals. Catostomids had higher densities of metacercariae than cyprinids, as shown by frequency distributions of density ranks. Opercular holes (i.e. holes that completely penetrated the opercle and were in direct association with the pigment associated metacercariae) and pockets (depressions on the external surface of the opercle associated with metacercariae) were abundant among catostomids but rare among cyprinids.