Aspects of religion and society in the province of Zeeland (Netherlands) in the nineteenth century

The body of the thesis has three major components: an assessment of the state of historical work and historical thinking concerning Zeeland since 1800; a study of church affiliation, and reactions to secularization; and an attempt to gauge the effects of religious attitudes on the socioeconomic development of the province in the nineteenth century. An examination of the existing literature reveals a 'received opinion' on the socio-economic history of Zeeland, namely that there was a conservative, traditional mentality among the inhabitants, expressed in religious attitudes, which was a significant contributory cause of the province's mediocre economic performance since 1800. There follows a survey of nineteenth century Zeeland in its demographic, social, economic, and political aspects.A systematic examination of the growth and/or decline of the various religious denominations is conducted. In the face of secularization, the orthodox Calvinist groups and the Roman Catholics were better able to maintain their position than the mainstream Calvinist Hervormde Kerk or the smaller Protestant denominations. This conclusion is confirmed by a number of secondary sources concerning secularization.In order to determine the effects of religious principles on socio-economic affairs, certain issues in Zeeland are selected for analysis. These include relations between Protestants and Catholics, certain principles held by the orthodox Calvinists, the role of the churches as a (service) sector in the local economy, and religious intervention in local politics. The conclusion is reached that although it was indeed possible for religious principles to affect -detrimentally - the local economy, this was not the case in the nineteenth century in Zeeland.In conclusion, a modest contribution is made to several wide-ranging historical debates, and a number of subjects for further research are designated

Optical Absorption by Indirect Excitons in a Transition Metal Dichalcogenide Double Layer

We calculate the binding energy, transition energies, oscillator strength, and absorption coefficient of indirect excitons in transition metal dichalcogenide (TMDC) double layers separated by an integer number of hexagonal boron nitride (h-BN) monolayers. The absorption factor, a dimensionless quantity which gives the fraction of incoming photons absorbed by the indirect excitons in the double layer, is evaluated. The aforementioned optical quantities are obtained for transitions from the ground state to the first two excited states. All quantities are studied as a function of the interlayer separation, which may be experimentally controlled by varying the number of h-BN monolayers between the TMDC layers. Calculations are performed by using the exciton wave function and eigenenergies obtained for the Keldysh potential. For each material, we choose a combination of the exciton reduced mass and the dielectric screening length from the existing literature which give the largest and the smallest indirect exciton binding energy. These combinations of material parameters provide upper and lower bounds on all quantities presented. Our findings can be examined experimentally via two-photon spectroscopy.Comment: 13 pages, 3 figure

Active adaptive conservation of threatened species in the face of uncertainty

Adaptive management has a long history in the natural resource management literature, but despite this, few practitioners have developed adaptive strategies to conserve threatened species. Active adaptive management provides a framework for valuing learning by measuring the degree to which it improves long-run management outcomes. The challenge of an active adaptive approach is to find the correct balance between gaining knowledge to improve management in the future and achieving the best short-term outcome based on current knowledge. We develop and analyze a framework for active adaptive management of a threatened species. Our case study concerns a novel facial tumor disease affecting the Australian threatened species Sarcophilus harrisii: the Tasmanian devil. We use stochastic dynamic programming with Bayesian updating to identify the management strategy that maximizes the Tasmanian devil population growth rate, taking into account improvements to management through learning to better understand disease latency and the relative effectiveness of three competing management options. Exactly which management action we choose each year is driven by the credibility of competing hypotheses about disease latency and by the population growth rate predicted by each hypothesis under the competing management actions. We discover that the optimal combination of management actions depends on the number of sites available and the time remaining to implement management. Our approach to active adaptive management provides a framework to identify the optimal amount of effort to invest in learning to achieve long-run conservation objectives

Bayesian Estimation of Animal Movement from Archival and Satellite Tags

The reliable estimation of animal location, and its associated error is fundamental to animal ecology. There are many existing techniques for handling location error, but these are often ad hoc or are used in isolation from each other. In this study we present a Bayesian framework for determining location that uses all the data available, is flexible to all tagging techniques, and provides location estimates with built-in measures of uncertainty. Bayesian methods allow the contributions of multiple data sources to be decomposed into manageable components. We illustrate with two examples for two different location methods: satellite tracking and light level geo-location. We show that many of the problems with uncertainty involved are reduced and quantified by our approach. This approach can use any available information, such as existing knowledge of the animal's potential range, light levels or direct location estimates, auxiliary data, and movement models. The approach provides a substantial contribution to the handling uncertainty in archival tag and satellite tracking data using readily available tools

Diel Variations in Survey Catch Rates and Survey Catchability of Spiny Dogfish and their Pelagic Prey in the Northeast US Continental Shelf Large Marine Ecosystem

This study examines the potential uncertainty in survey biomass estimates of Spiny Dogfish Squalus acanthias in the Northeast U.S. Continental Shelf Large Marine Ecosystem (NES LME). Diel catch-per-unit-effort (CPUE) estimates are examined from the Northeast Fisheries Science Center bottom trawl surveys conducted during autumn (1963-2009) and spring (1968-2009). Influential environmental variables on survey catchability are identified for Spiny Dogfish life history stages and five pelagic prey species: Butterfish Peprilus triacanthus, Atlantic Herring Clupea harengus, shortfin squid Illex spp., longfin squid Doryteuthis spp., and Atlantic Mackerel Scomber scombrus. Daytime survey catchability was significantly higher than nighttime catchability for most species during autumn and for mature male Spiny Dogfish, shortfin squid, and longfin squid during spring in the NES LME. For most stages and species examined, breakpoint analyses identified significant increases in CPUE in the morning, peak CPUE during the day, and significant declines in CPUE in the late afternoon. Seasonal probabilities of daytime catch were largely driven by solar zenith angle for most species, with stronger trends identified during autumn. Unadjusted CPUE estimates appear to overestimate absolute abundance, with adjustments resulting in reductions in absolute abundance ranging from 41% for Spiny Dogfish to 91% for shortfin and longfin squids. These findings have important implications for Spiny Dogfish regarding estimates of population consumption of key pelagic prey species and their ecological footprint within the NES LME

Planning for robust reserve networks using uncertainty analysis

Planning land-use for biodiversity conservation frequently involves computer-assisted reserve selection algorithms. Typically such algorithms operate on matrices of species presence–absence in sites, or on species-specific distributions of model predicted probabilities of occurrence in grid cells. There are practically always errors in input data—erroneous species presence–absence data, structural and parametric uncertainty in predictive habitat models, and lack of correspondence between temporal presence and long-run persistence. Despite these uncertainties, typical reserve selection methods proceed as if there is no uncertainty in the data or models. Having two conservation options of apparently equal biological value, one would prefer the option whose value is relatively insensitive to errors in planning inputs. In this work we show how uncertainty analysis for reserve planning can be implemented within a framework of information-gap decision theory, generating reserve designs that are robust to uncertainty. Consideration of uncertainty involves modifications to the typical objective functions used in reserve selection. Search for robust-optimal reserve structures can still be implemented via typical reserve selection optimization techniques, including stepwise heuristics, integer-programming and stochastic global search