Sensitivity of species-distribution models to error,bias, and model design: An application to resource selection functions for woodland caribou

Models that predict distribution are now widely used to understand the patterns and processes of plant and animal occurrence as well as to guide conservation and management of rare or threatened species. Application of these methods has led to corresponding studies evaluating the sensitivity of model performance to requisite data and other factors that may lead to imprecise or false inferences. We expand upon these works by providing a relative measure of the sensitivity of model parameters and prediction to common sources of error, bias, and variability. We used a one-at-a-time sample design and GPS location data for woodland caribou (Rangifer tarandus caribou) to assess one common species-distribution model: a resource selection function. Our measures of sensitivity included change in coefficient values, prediction success, and the area of mapped habitats following the systematic introduction of geographic error and bias in occurrence data, thematic misclassification of resource maps, and variation in model design. Results suggested that error, bias and model variation have a large impact on the direct interpretation of coefficients. Prediction success and definition of important habitats were less responsive to the perturbations we introduced to the baseline model. Model coefficients, prediction success, and area of ranked habitats were most sensitive to positional error in species locations followed by sampling bias, misclassification of resources, and variation in model design. We recommend that researchers report, and practitioners consider, levels of error and bias introduced to predictive species-distribution models. Formal sensitivity and uncertainty analyses are the most effective means for evaluating and focusing improvements on input data and considering the range of values possible from imperfect models.     

Thought self-leadership: The influence of self-talk and mental imagery on performance

Self-leadership theory can be described as the ‘process of influencing oneself ’as opposed to the influence of leaders over followers (Manz, 1983, 1986). We focus on and develop a model for a particular aspect of self-leadership — thought self-leadership — emphasizing two primary elements, self-talk and mental imagery. The major thrust of this model is that employees can influence or lead themselves by utilizing specific cognitive strategies that focus on individual self-dialogue and mental imagery. It is proposed that constructive thought management through the effective application of cognitive strategies can lead to enhanced individual and organizational performance.     

Sound Survey Designs Can Facilitate Integrating Stream Monitoring Data Across Multiple Programs1

Abstract: Multiple agencies in the Pacific Northwest monitor the condition of stream networks or their watersheds. Some agencies use a stream “network” perspective to report on the fraction or length of the network that either meets or violates particular criteria. Other agencies use a “watershed” perspective to report on the health or condition of watersheds. The agencies often use the same indicators and measurement protocols for data collection and often conduct monitoring in overlapping geographic regions. In these situations, agencies would like to combine data across different monitoring studies in a statistically sound manner to make regional estimates of condition. Three statistical survey design principles will facilitate combining such studies: (1) a clearly specified statistical target population of interest, including elements that comprise the population, (2) a consistent representation of that target population (such as a digital map of the stream network and watersheds), and (3) rules that incorporate randomization to guide the selection of the sample of sites on which measurements will be made. A case study illustrates the application of these design principles using two agency monitoring programs interested in combining stream channel data for different purposes: one for making network summaries and the other for evaluating watershed condition.     

Disturbance cues in freshwater prey fishes: do juvenile convict cichlids and rainbow trout respond to ammonium as an ‘early warning’ signal?

Summary.  Several freshwater invertebrate and vertebrate prey species rely on chemosensory cues, including non-injury released disturbance cues, to assess and avoid local predation threats. The prevailing hypothesis is that a pulse of ammonia released by disturbed or stressed prey functions as the disturbance cue. Here, we test this hypothesis in two phylogenetically distant freshwater prey fishes, convict cichlids and rainbow trout. In our first experiment, we measured NH₄ ⁺ concentration in tanks containing shoals of cichlid or trout before and after exposure to a realistic model predator (or left undisturbed). We failed to find an increase in ambient NH₄ ⁺ concentration for either cichlids or trout. In our second experiment, we exposed cichlids or trout to NH₄ ⁺ at 0.1 or 0.5 mg L⁻¹ (or a distilled water control) and measured the change in antipredator behaviour (time moving, foraging rate and area use). We found no consistent increase in antipredator behaviour in response to NH₄ ⁺. In our third study, we exposed cichlids and trout to the disturbance cues of cichlids or trout (versus the odour of undisturbed donors). We found significant increases in antipredator behaviour, regardless of donor species, for both cichlids and trout. Thus, the results of our first two experiments do not support the hypothesis that ammonium functions as a disturbance cue in prey fishes. However, the results of our final experiment do confirm the use of disturbance cues in convict cichlids and rainbow trout and support that hypothesis that the disturbance cue is indeed some generalized metabolic byproduct.     

The invasion paradox: reconciling pattern and process in species invasions

The invasion paradox describes the co-occurrence of independent lines of support for both a negative and a positive relationship between native biodiversity and the invasions of exotic species. The paradox leaves the implications of native-exotic species richness relationships open to debate: Are rich native communities more or less susceptible to invasion by exotic species? We reviewed the considerable observational, experimental, and theoretical evidence describing the paradox and sought generalizations concerning where and why the paradox occurs, its implications for community ecology and assembly processes, and its relevance for restoration, management, and policy associated with species invasions. The crux of the paradox concerns positive associations between native and exotic species richness at broad spatial scales, and negative associations at fine scales, especially in experiments in which diversity was directly manipulated. We identified eight processes that can generate either negative or positive native-exotic richness relationships, but none can generate both. As all eight processes have been shown to be important in some systems, a simple general theory of the paradox, and thus of the relationship between diversity and invasibility, is probably unrealistic. Nonetheless, we outline several key issues that help resolve the paradox, discuss the difficult juxtaposition of experimental and observational data (which often ask subtly different questions), and identify important themes for additional study. We conclude that natively rich ecosystems are likely to be hotspots for exotic species, but that reduction of local species richness can further accelerate the invasion of these and other vulnerable habitats.     

Generation of Ensemble Streamflow Forecasts Using an Enhanced Version of the Snowmelt Runoff Model1

Harshburger, Brian J., Von P. Walden, Karen S. Humes, Brandon C. Moore, Troy R. Blandford, and Albert Rango, 2012. Generation of Ensemble Streamflow Forecasts Using an Enhanced Version of the Snowmelt Runoff Model. Journal of the American Water Resources Association (JAWRA) 48(4): 643‐655. DOI: 10.1111/j.1752‐1688.2012.00642.x Abstract: As water demand increases in the western United States, so does the need for accurate streamflow forecasts. We describe a method for generating ensemble streamflow forecasts (1‐15 days) using an enhanced version of the snowmelt runoff model (SRM). Forecasts are produced for three snowmelt‐dominated basins in Idaho. Model inputs are derived from meteorological forecasts, snow cover imagery, and surface observations from Snowpack Telemetry stations. The model performed well at lead times up to 7 days, but has significant predictability out to 15 days. The timing of peak flow and the streamflow volume are captured well by the model, but the peak‐flow value is typically low. The model performance was assessed by computing the coefficient of determination (R²), percentage of volume difference (Dv%), and a skill score that quantifies the usefulness of the forecasts relative to climatology. The average R² value for the mean ensemble is >0.8 for all three basins for lead times up to seven days. The Dv% is fairly unbiased (within ±10%) out to seven days in two of the basins, but the model underpredicts Dv% in the third. The average skill scores for all basins are >0.6 for lead times up to seven days, indicating that the ensemble model outperforms climatology. These results validate the usefulness of the ensemble forecasting approach for basins of this type, suggesting that the ensemble version of SRM might be applied successfully to other basins in the Intermountain West.     

A meta-ethnography to synthesise household cultural research for climate change response

Cultural change is critical to climate change responses, but the in-depth qualitative research that investigates culture is necessarily conducted at scales difficult to integrate with policy. A focus of climate change mitigation and adaptation is affluent developed world households. Adapting methods used elsewhere in social science, we report and assess a meta-ethnography of household sustainability research, scaling up findings from 12 studies encompassing 276 Australian households. Seven themes are dominant: family concerns are central to household practice; adaptiveness is contingent but more pervasive than often assumed; households make sense of climate change not through abstract arguments, but through physical resources and materials; boundaries of the home space are dynamic and subjective; daily time is an important currency; paradoxes abound among everyday practice; and privacy and a sense of autonomy are prioritised. Insights from the method include new light on familiar themes when seen through an environmental lens, thickening and triangulation of existing research, and a stronger basis for international comparisons. Some findings have straightforward application to policy, others identify potential areas of risk and resistance, others still are more conceptual. We conclude the method has considerable potential and is worth developing further, providing a critical perspective is maintained.