A comparison of models using removal effort to estimate animal abundance

This paper compares methods for modeling the probability of removal when variable amounts of removal effort are present. A hierarchical modeling framework can produce estimates of animal abundance and detection from replicated removal counts taken at different locations in a region of interest. A common method of specifying variation in detection probabilities across locations or replicates is with a logistic model that incorporates relevant detection covariates. As an alternative to this logistic model, we propose using a catch–effort (CE) model to account for heterogeneity in detection when a measure of removal effort is available for each removal count. This method models the probability of detection as a nonlinear function of removal effort and a removal probability parameter that can vary spatially. Simulation results demonstrate that the CE model can effectively estimate abundance and removal probabilities when average removal rates are large but both the CE and logistic models tend to produce biased estimates as average removal rates decrease. We also found that the CE model fits better than logistic models when estimating wild turkey abundance using harvest and hunter counts collected by the Minnesota Department of Natural Resources during the spring turkey hunting season.     

Detection of biomass change in a Norwegian mountain forest area using small footprint airborne laser scanner data

Different approaches for estimation of change in biomass between two points in time by means of airborne laser scanner data were tested. Both field and laser data were collected at two occasions on 52 sample plots in a mountain forest in southeastern Norway. In the first approach, biomass change was estimated as the difference between predicted biomass for the two measurement occasions. Joint models for the biomass at both occasions were fitted using different height and density variables from laser data as explanatory variables. The second approach modelled the observed change directly using the change in different variables extracted from the laser data as explanatory variables. In the third approach we modelled the relative change in biomass. The explanatory variables were also expressed as relative change between measurement occasions. In all approaches we allowed spline terms to be entered. We also investigated the aptness of models for which the residual variance was modeled by allowing it to be proportional to the area of the plot on which biomass was assessed. All alternative models were initially assessed by AIC. All models were also evaluated by estimating biomass change on the model development data. This evaluation indicated that the two direct approaches (approach 2 and 3) were better than relying on modeling biomass at both occasions and taking change as the difference between biomass estimates. Approach 2 seemed to be slightly better than approach 3 based on assessments of bias in the evaluation.     

Reducing the Effort to Comprehend Risk Models: Text Labels Are Often Preferred Over Graphical Means

Risk analysis involves people with different roles and competences. The validity of the outcome depends on that they are able to communicate; ideally between themselves, but at least with or via a risk analyst. The CORAS risk modeling language has been developed to facilitate communication between stakeholders involved in the various stages of risk analysis. This article reports the results from an empirical investigation among professionals, where the purpose was to investigate how graphical effects (size, color, shape) and text labels introduced in the CORAS risk modeling language affected the understanding. The results indicate that if graphical effects are used to illustrate important information, they should also be accompanied by informative textual labels.     

Voluntary Associations Within the Local Political Context: How Characteristics of the Organizations and the Local Governments Influence Perceptions of Success

A cornerstone of democracy is the capacity of citizens to influence political decisions either through elections or by making their will known in the periods between elections. The aim of the present study is twofold: (1) to explore what factors inherent of the voluntary associations that determine the perceived success in their attempts to influence policy and (2) to investigate what role the composition of the local government have on the perceived success. This study is based on a survey conducted among 404 local voluntary associations in four different municipalities in Sweden. The results show that the frequency contacts influence perceived success positively, while the level of civic engagement of the voluntary associations affected the perceived success negatively. Having a heterogeneous local government also contributed positively to the perceived success to influence policy.     

The impact of governmental assistance on insurance demand under ambiguity: a theoretical model and an experimental test

This article deals with the impact of governmental assistance on insurance demand under ambiguity, i.e., in situations where probabilities are uncertain. First, using a model of insurance demand under ambiguity, we derive theoretical predictions about the impact of several governmental assistance programmes on optimal insurance demand. For example, governmental assistance through a fixed public support scheme implies that partial insurance is always optimal under fair insurance with ambiguity. Second, we present the results of an experiment designed to test these predictions. We find support for several of our theoretical predictions. For example, the presence of governmental assistance through a fixed public support scheme decreases individuals’ willingness to pay to be fully insured. Finally, we compare these results with those obtained for a risk situation. We find that, regardless of the form of governmental assistance, participants in the ambiguity context are consistently willing to pay more to be fully insured than participants in the risk situation.     

Classification of Gamblers According to the NODS and a Clinical Interview1

Since the social and personal implications of excessive gambling are important, it becomes necessary to assess the extent of the problem within the population. Accordingly, the use of an instrument that evaluates gamblers accurately is essential. This study, carried out with 200 adults, investigates the potential differences in classification of gamblers when using the NORC DSM-IV Screen for gambling problems (NODS) versus a clinical interview. The results show that 50 of the 200 participants were not categorised in the same way with the NODS as with the clinical interview; 47 participants were identified as having a more severe gambling problem according to the NODS than with the clinical interview, providing a 23.5% difference in the concordance rate. This result is discussed in terms of measurement problems in assessing gambling behaviours.     

Population statistics and population registration in Norway. Part 3. Population censuses

In this history of Norwegian vital statistics, the author describes enumerations of population that have taken place in Norway, comments on the methods by which the results have been obtained and describes the material that has been collected.     

Mutuality in leader–subordinate empowerment expectation: Its impact on role ambiguity and intrinsic motivation

Drawing on leader role set theory, we examine the relationship between the congruence of leaders' and subordinates' empowerment expectations and subordinates' experiences of role ambiguity and intrinsic motivation. Based on cross-level polynomial regression analysis using 168 subordinates and 33 leaders, the results indicated that the relationship between congruence and role ambiguity and intrinsic motivation vary depending on whether leaders misevaluate subordinate empowerment expectations, as well as whether the expectations match. Specifically, subordinates had low role ambiguity and low intrinsic motivation when leaders' and subordinates' empowerment expectations matched at low levels and when leaders underestimated subordinates' empowerment expectations. However, subordinates had low role ambiguity and high intrinsic motivation when expectations matched at high levels. Furthermore, role ambiguity was high and intrinsic motivation was low when the leaders overestimated subordinates' empowerment expectations. Theoretical and practical implications are discussed.