Estimating the extent of spatial association of Mycobacterium bovis infection in badgers in Ireland

Mycobacterium bovis infects the wildlife species badgers Meles meles who are linked with the spread of the associated disease tuberculosis (TB) in cattle. Control of livestock infections depends in part on the spatial and social structure of the wildlife host. Here we describe spatial association of M. bovis infection in a badger population using data from the first year of the Four Area Project in Ireland. Using second-order intensity functions, we show there is strong evidence of clustering of TB cases in each the four areas, i.e. a global tendency for infected cases to occur near other infected cases. Using estimated intensity functions, we identify locations where particular strains of TB cluster. Generalized linear geostatistical models are used to assess the practical range at which spatial correlation occurs and is found to exceed 6 in all areas. The study is of relevance concerning the scale of localized badger culling in the control of the disease in cattle.

Spatial Management of Wildlife Disease

The spread of wildlife diseases is a major threat to livestock, human health, resource-based recreation, and biodiversity conservation (Cleaveland, Laurenson, and Taylor). The development of economically sound wildlife disease-management strategies requires an understanding of the links between ecological functions (e.g., disease transmission and wildlife dispersal) and economic choices, and the associated tradeoffs. Spatial linkages are particularly relevant. Yet while ecologists have long-argued that space is important (Hudson et al.), prior economic work has largely ignored spatial issues. For instance, Horan and Wolf analyzed a case study of bovine tuberculosis (bTB) in Michigan deer, a problem where the disease appears to be confined to a single, spatially confined, wildlife population—an island. But wildlife disease matters generally are not spatially confined. Barlow, in analyzing bTB in possums in New Zealand, accounted for immigration of susceptible possums into a disease reservoir. However, he modeled immigration as fixed and unaffected by management. Bicknell, Wilen, and Howitt, also focusing on possums in New Zealand, developed a model that incorporates simple density-dependent net migration. This allowed the authors to account for endogenous immigration when deriving optimal culling strategies.

Determining spatial and temporal scales for management: lessons from whaling

Selection of the appropriate management unit is critical to the conservation of animal populations. Defining such units depends upon knowledge of population structure and upon the timescale being considered. Here, we examine the trajectory of eleven subpopulations of five species of baleen whales to investigate temporal and spatial scales in management. These subpopulations were all extirpated by commercial whaling, and no recovery or repopulation has occurred since. In these cases, time elapsed since commercial extinction ranges from four decades to almost four centuries. We propose that these subpopulations did not recover either because cultural memory of the habitat has been lost, because widespread whaling among adjacent stocks eliminated these as sources for repopulation, and/or because segregation following exploitation produced the abandonment of certain areas. Spatial scales associated with the extirpated subpopulations are frequently smaller than those typically employed in management. Overall, the evidence indicates that: (1) the time frame for management should be at most decadal in scope (i.e., <100 yr) and based on both genetic and nongenetic evidence of population substructure, and (2) at least some stocks should be defined on a smaller spatial scale than they currently are.

Generalizing the dynamic field theory of spatial cognition across real and developmental time scales

Within cognitive neuroscience, computational models are designed to provide insights into the organization of behavior while adhering to neural principles. These models should provide sufficient specificity to generate novel predictions while maintaining the generality needed to capture behavior across tasks and/or time scales. This paper presents one such model, the Dynamic Field Theory (DFT) of spatial cognition, showing new simulations that provide a demonstration proof that the theory generalizes across developmental changes in performance in four tasks—the Piagetian A-not-B task, a sandbox version of the A-not-B task, a canonical spatial recall task, and a position discrimination task. Model simulations demonstrate that the DFT can accomplish both specificity—generating novel, testable predictions—and generality—spanning multiple tasks across development with a relatively simple developmental hypothesis. Critically, the DFT achieves generality across tasks and time scales with no modification to its basic structure and with a strong commitment to neural principles. The only change necessary to capture development in the model was an increase in the precision of the tuning of receptive fields as well as an increase in the precision of local excitatory interactions among neurons in the model. These small quantitative changes were sufficient to move the model through a set of quantitative and qualitative behavioral changes that span the age range from 8 months to 6 years and into adulthood. We conclude by considering how the DFT is positioned in the literature, the challenges on the horizon for our framework, and how a dynamic field approach can yield new insights into development from a computational cognitive neuroscience perspective.

Tiered Pricing and Cost Functions: Are Equity, Cost Recovery and Economic Efficiency Compatible Goals?

Suppliers of water and energy are frequently natural monopolies, with their pricing regulated by governmental agencies. Pricing schemes are evaluated by the efficiency of the resource allocation they lead to, the capacity of the utilities to capture their costs and the distributional effects of the policies, in particular, impacts on the poor. One pricing approach has been average cost pricing, which guarantees cost recovery and allows utilities to provide their product at relatively low prices. However, average cost pricing leads to economically inefficient consumption levels, when sources of water and energy are limited and increasing the supply is costly. An alternative approach is increasing block rates (hereafter, IBR or tiered pricing), where individuals pay a low rate for an initial consumption block and a higher rate as they increase use beyond that block. An example of IBR is shown in Figure 1 (on next page), which shows a rate structure for residential water use. With the rates in Figure 1, a household would be charged $0.46 and $0.71 per hundred gallons for consumption below and above 21,000 gallons per month, respectively.