Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modeling

Analyses of ecological data should account for the uncertainty in the process(es) that generated the data. However, accounting for these uncertainties is a difficult task, since ecology is known for its complexity. Measurement and/or process errors are often the only sources of uncertainty modeled when addressing complex ecological problems, yet analyses should also account for uncertainty in sampling design, in model specification, in parameters governing the specified model, and in initial and boundary conditions. Only then can we be confident in the scientific inferences and forecasts made from an analysis. Probability and statistics provide a framework that accounts for multiple sources of uncertainty. Given the complexities of ecological studies, the hierarchical statistical model is an invaluable tool. This approach is not new in ecology, and there are many examples (both Bayesian and non-Bayesian) in the literature illustrating the benefits of this approach. In this article, we provide a baseline for concepts, notation, and methods, from which discussion on hierarchical statistical modeling in ecology can proceed. We have also planted some seeds for discussion and tried to show where the practical difficulties lie. Our thesis is that hierarchical statistical modeling is a powerful way of approaching ecological analysis in the presence of inevitable but quantifiable uncertainties, even if practical issues sometimes require pragmatic compromises.

A Model-Based Approach for Making Ecological Inference from Distance Sampling Data

We consider a fully model-based approach for the analysis of distance sampling data. Distance sampling has been widely used to estimate abundance (or density) of animals or plants in a spatially explicit study area. There is, however, no readily available method of making statistical inference on the relationships between abundance and environmental covariates. Spatial Poisson process likelihoods can be used to simultaneously estimate detection and intensity parameters by modeling distance sampling data as a thinned spatial point process. A model-based spatial approach to distance sampling data has three main benefits: it allows complex and opportunistic transect designs to be employed, it allows estimation of abundance in small subregions, and it provides a framework to assess the effects of habitat or experimental manipulation on density. We demonstrate the model-based methodology with a small simulation study and analysis of the Dubbo weed data set. In addition, a simple ad hoc method for handling overdispersion is also proposed. The simulation study showed that the model-based approach compared favorably to conventional distance sampling methods for abundance estimation. In addition, the overdispersion correction performed adequately when the number of transects was high. Analysis of the Dubbo data set indicated a transect effect on abundance via Akaike’s information criterion model selection. Further goodness-of-fit analysis, however, indicated some potential confounding of intensity with the detection function.

Niche Specialization and Conservation Biology of Cicindela nevadica lincolniana

As with many organisms across the globe, Cicindela nevadica lincolniana is threatened with extinction. Understanding ecological factors that contribute to extinction vulnerability and what methods aid in the recovery of those species is essential in developing successful conservation programs. Here we examine behavioral mechanisms for niche partitioning along with improving techniques for captive rearing protocol and increasing public awareness about the conservation of this local insect. Ovipositional selectivity was examined for Cicindela nevadica lincolniana, Cicindela circumpicta, Cicindela togata, Cicindela punctulata, and Cicindela fulgida. Models reflect that these species of co-occurring tiger beetles select different ranges of salinity in which to oviposit thereby reducing the potential for interspecific competition. In a second study, thermoregulatory niche partitioning was examined for the same complex of tiger beetle species. Time spent in the sun, on different substrates, and engaging in various behaviors associated with thermoregulation were significantly different during different parts of the day and between species. I continued along a previous line of study to develop a viable captive rearing program. So far fourteen adult Cicindela nevadica lincolniana have been successfully reared in captivity. Overwintering mortality has been determined as a key factor in the mortality of this species in captivity. Finally, I examined the potential for using the visual arts to promote the conservation of Cicindela nevadica lincolniana and associated saline wetlands. The results from surveys conducted at the exhibit suggest that art exhibits can have a strong positive impact on members of the community.