County Cork: the experience of members of the establishment whose houses were burned in the IRA arson campaign, 1920-23

Between May 1920 and March 1923, there were seventy-three houses belonging to the County Cork establishment burnt down by IRA and anti-treaty forces. More houses were destroyed by this method in Cork than in any other Irish county in the same timeframe. The establishment were targeted by the IRA for their political, military and social persuasions that were essentially in opposition to the nationalist movement. The motivations behind these burnings is examined, the main reasons being reprisals for actions taken by Crown forces, military reasons, loyalty of house owners to the British government and agrarianism. The geographical distribution of these burnings is also provided to reveal how active individual IRA brigades were that operated within the county. Though there were few areas of the county left unaffected by the occurrence of arson attacks, there were higher concentrations of burnings in some areas. The house burnings in County Cork did not conform to the national pattern of house burnings and the reasons for this are explored. This study argues that the presence of Crown forces in Cork and their implementation of an official reprisal policy in January 1921 escalated military conflict, and arson attacks became a key tactic utilised by IRA forces in response to this policy. The aftermath of house burnings for members of the establishment is revealed through the various compensation committees that were formed after both the War of Independence and Civil War. Key sources for this study included personal papers of both the establishment and military figures, IRA witness statements, local and national newspapers, the 1901 and 1911 Irish Censuses, Colonial Office Papers, compensation claims filed with the British government and Irish Free State, and others from archives throughout Ireland and the United Kingdom.

Distribution of living benthic foraminifera in sediment cores of cruise M77 Leg 1 and 2, 63-2000 µm fraction

Recent benthic foraminifera and their distribution in surface sediments were studied on a transect through the Peruvian oxygen minimum zone (OMZ) between 10 and 12°S. The OMZ with its steep gradients of oxygen concentrations allows to determine the oxygen-dependent changes of species compositions in a relatively small area. Our results from sediments of thirteen multicorer stations from 79 to 823 m water depth demonstrate that calcareous species, especially bolivinids dominate the assemblages throughout the OMZ. The depth distribution of several species matches distinct ranges of bottom water oxygen levels. The distribution pattern inferred a proxy which allows to estimate dissolved oxygen concentrations for reconstructing oxygen levels in the geological past.

Pattern and function of woody features on the grazing itineraries of Terra Fria, Trás–os–Montes – Portugal

The trees, hedgerows and woods are current configuration of the tree network in several ecological regions of the world. In Trás–os–Montes region, Northeast of Portugal, they are a traditional component of Terra fria landscape and they could be seen in several forms: scatter trees, fencerows, small woodlots, riparian buffer strips, among others. The extensive livestock systems in this region are based on a set of circuits across the landscape. In this practice, flocks interacts with these structures using them for different functions inducing an influence on the itineraries. Our purpose will be focused on the woody features of landscape regarding their configurations, abundance and spacial distribution; in order to examine how the grazing systems depends on the currency of these formations; particularly how species flocks behaviors are related on. Depending on spatial data, The investigation attain to compare the tree network within the agriculture matrix, to the grazed territory crossed by flocks. From the other side, the importance of spatial data on interpreting the issue by suggesting different parameter that may influence the circuits. The recognition of the pressure exerciced by the occurence of the woody structures on the grazed circuits is possible. We believe that the role of these woody structures features in supporting the tradicional silvopastoral systems has been sufficiently strong for change their distribution pattern.

Genetic diversity across geographical scales in marine coastal ecosystems: Holothuria arguinensis a model species

Coastal lagoons are considered one of the most productive areas of our planet harboring a large variety of habitats. Their transitional character, between terrestrial and marine environments, creates a very particular ecosystem with important variations of its environmental conditions. The organisms that are able to survive on these ecosystems frequently experience strong selective pressures and constrictions to gene flowwith marine populations, which could contribute to genetic divergence among populations inhabiting coastal lagoon and marine environments. Therefore, the main aims of this study are to asses the genetic diversity and population structure of Holothuria arguinensis across geographical ranges, to test the hypothesis of coastal lagoons as hotspots of genetic diversity in the Ria Formosa lagoon, and to determine the role of exporting standing genetic variation from the lagoon to open sea and their implications to recent geographical expansion events. To reach these objectives, we investigate the genetic structure of H. arguinensis using two mitochondrial DNA markers (COI and 16S) at different spatial scales: i) small, inside Ria Formosa coastal lagoon, South Portugal; 2) large, including most of the geographical distribution of this species (South and Western Portuguese coast and Canary islands); these results will allow us to compare the genetic diversity of lagoonal and marine populations of H. arguinensis. On this framework, its recent geographical expansion events, recorded by Rodrigues (2012) and González-Wangüemert and Borrero-Pérez (2012), will be analyzed considering the potential contribution from lagoonal genetic pool. Non-significant genetic structure and high haplotypic diversity were found inside the Ria Formosa coastal lagoon. Both genes were unable to detect significant genetic differentiation among lagoonal and marine localities, suggesting a high rate of gene flow. The results supported our hypotheses that coastal lagoons are not only acting as hotspots of genetic diversity, but also contributing for the genetic variability of the species, working as a source of new haplotypes and enhancing adaptation to the high variable conditions. Different genetic patterns of colonization were found on H. arguinensis, but they must be studied more deeply.

Distribution patterns of endemic flora to define hotspots on Hispaniola

Nineteen areas on the island of Hispaniola (Haiti and the Dominican Republic) were studied with the aim of determining the distribution pattern of the endemic flora in these areas, and their variability with altitude. The main concentration of endemic species occurs in mountains with a medium altitude and in certain mountain sites (palaeo-islands), which coincide with hotspots; a lower number of endemics are found in low-lying areas (coldspots), due to the degradation of their habitats. A total of 1,582 endemic species were studied and were distributed in 19 areas. The whole island is of outstanding interest for its richness in endemics; it has 2,050 endemic species, representing 34.16% of its total flora. The territory in the study is home to 1,284 genera of which 31 are endemic to the island, including monotypical genera such as Tortuella abietifolia Urb. & Ekman, and endemic genera such as Hottea, containing seven endemic species. The sites with the highest rate of endemics are area A16 in the central range with a total of 440 endemic species, of which 278 are exclusive to the territory; and the Sierra de Bahoruco, la Selle, La Hotte and Tibur on in area A12, where we found 699 plants of which 482 are endemic and exclusive to the area; and A13 with 173 and 129 respectively. This work highlights the exceptional floristic diversity in endemic species and genera and analyses their distribution patterns as a tool for conservation in this area of the world, whose high endemicity rate makes it one of the most significant hotspots in the Caribbean.

Changes in the spatial distribution of tree species in a terra firme rain forest in Brazilian Amazonia after logging.

The objective of this paper was to determine changes in the spatial distribution of tree species in a logged compared to an unlogged forest of the Tapajos National Forest in the municipality of Belterra, State of Para, Brazil, over an eight-year period. The distribution pattern was determined for trees> 5 cm dbh and, also, for trees > 30 cm dbh. The relationship (a quadrate method) discussed by McGinnis was selected to be used in this study. Forty-seven percent of species with trees > 5 cm dbh showed clumped distribution in the studied forests. Geissospermwn sericeunz Benth & Hook., Minquartia guianensis Aubl., Poureria bilocularis (H. Winkler) Bachni, Protium guacayantan Cuatrec, Sclerolobium chrysophyllunz Poepp. et Endl. and the Sapotaceae family (9 species) occurred in clumps of small trees (5 cm 5 dbh < 30 cm) and big trees (dbh > 30 cm) in both the logged and undisturbed forest. Trees in all sizes of these species certainly have aggregation characteristics in different light condition's during the whole growth-cycle. Only Sclerolobium cizzysophylltan out of fourteen species that occurred aggregated in all forest conditions was light demanding. The shade-tolerant Lecythis lurida (Miers) Mori and Manilkara huberi (Ducke) Stand!. showed also aggregated distribution for small and big trees in the unlogged forest. An aggregated distribution is not always directly correlated to abundance, considering that most of the clumped species had less than seven trees per hectare.

Mapping spatial and temporal potassium balances in Brazilian soils of south-west Goias.

Introduction: Brazil, is one of the main agricultural producers in the world ranking 1st in the production of sugarcane, coffee and oranges. It is also 2nd as world producer of soybeans and a leader in the harvested yields of many other crops. The annual consumption of mineral fertilizers exceeds 20 million mt, 30% of which corresponds to potash fertilizers (ANDA, 2006). From this statistic it may be supposed that fertilizer application in Brazil is rather high, compared with many other countries. However, even if it is assumed that only one fourth of this enormous 8.5 million km2 territory is used for agriculture, average levels of fertilizer application per hectare of arable land are not high enough for sustainable production. One of the major constraints is the relatively low natural fertility status of the soils which contain excessive Fe and Al oxides. Agriculture is also often practised on sandy soils so that the heavy rainfall causes large losses of nutrients through leaching. In general, nutrient removal by crops such as sugarcane and tropical fruits is much more than the average nutrient application via fertilization, especially in regions with a long history of agricultural production. In the recently developed areas, especially in the Cerrado (Brazilian savanna) where agriculture has expanded since 1980, soils are even poorer than in the "old" agricultural regions, and high costs of mineral fertilizers have become a significant input factor in determining soybean, maize and cotton planting. The consumption of mineral fertilizers throughout Brazil is very uneven. According to the 1995/96 Agricultural Census, only in eight of the total of 26 Brazilian states, were 50 per cent or more of the farms treated "systematically" with mineral fertilizers; in many states it was less than 25 per cent, and in five states even less than 12 per cent (Brazilian Institute for Geography and Statistics; Censo Agropecuario1995/96, Instituto Brazileiro de Geografia e Estadistica; IBGE, www.ibge.gov.br). The geographical application distribution pattern of mineral fertilizers may be considered as an important field of research. Understanding geographical disparities in fertilization level requires a complex approach. This includes evaluation of the availability of nutrients in the soil (and related soil properties e.g. CEC and texture), the input of nutrients with fertilizer application, and the removal of nutrients by harvested yields. When all these data are compiled, it is possible to evaluate the balance of particular nutrients for certain areas, and make conclusions as to where agricultural practices should be optimized. This kind of research is somewhat complicated, because it relies on completely different sources of data, usually from incomparable data sources, e.g. soil characteristics attributed to soil type areas, in contrast to yields by administrative regions, or farms. A priority tool in this case is the Geographical Information System (GIS), which enables attribution of data from different fields to the same territorial units, and makes possible integration of these data in an "inputoutput" model, where "input" is the natural availability of a nutrient in the soil plus fertilization, and "output" export of the same nutrient with the removed harvested yield.

Spatial scale effects of sampling on the interpolation of species distribution models in the southwestern Amazon.

Knowledge of the geographical distribution of timber tree species in the Amazon is still scarce. This is especially true at the local level, thereby limiting natural resource management actions. Forest inventories are key sources of information on the occurrence of such species. However, areas with approved forest management plans are mostly located near access roads and the main industrial centers. The present study aimed to assess the spatial scale effects of forest inventories used as sources of occurrence data in the interpolation of potential species distribution models. The occurrence data of a group of six forest tree species were divided into four geographical areas during the modeling process. Several sampling schemes were then tested applying the maximum entropy algorithm, using the following predictor variables: elevation, slope, exposure, normalized difference vegetation index (NDVI) and height above the nearest drainage (HAND). The results revealed that using occurrence data from only one geographical area with unique environmental characteristics increased both model overfitting to input data and omission error rates. The use of a diagonal systematic sampling scheme and lower threshold values led to improved model performance. Forest inventories may be used to predict areas with a high probability of species occurrence, provided they are located in forest management plan regions representative of the environmental range of the model projection area.

Thermal requirements, field mortality and population phenology modelling of Paropsis atomaria Olivier, an emergent pest in subtropical hardwood plantations

Paropsis atomaria is a recently emerged pest of eucalypt plantations in subtropical Australia. Its broad host range of at least 20 eucalypt species and wide geographical distribution provides it the potential to become a serious forestry pest both within Australia and, if accidentally introduced, overseas. Although populations of P. atomaria are genetically similar throughout its range, population dynamics differ between regions. Here, we determine temperature-dependent developmental requirements using beetles sourced from temperate and subtropical zones by calculating lower temperature thresholds, temperature-induced mortality, and day-degree requirements. We combine these data with field mortality estimates of immature life stages to produce a cohort-based model, ParopSys, using DYMEX™ that accurately predicts the timing, duration, and relative abundance of life stages in the field and number of generations in a spring–autumn (September–May) field season. Voltinism was identified as a seasonally plastic trait dependent upon environmental conditions, with two generations observed and predicted in the Australian Capital Territory, and up to four in Queensland. Lower temperature thresholds for development ranged between 4 and 9 °C, and overall development rates did not differ according to beetle origin. Total immature development time (egg–adult) was approximately 769.2 ± S.E. 127.8 DD above a lower temperature threshold of 6.4 ± S.E. 2.6 °C. ParopSys provides a basic tool enabling forest managers to use the number of generations and seasonal fluctuations in abundance of damaging life stages to estimate the pest risk of P. atomaria prior to plantation establishment, and predict the occurrence and duration of damaging life stages in the field. Additionally, by using local climatic data the pest potential of P. atomaria can be estimated to predict the risk of it establishing if accidentally introduced overseas. Improvements to ParopSys’ capability and complexity can be made as more biological data become available.

Hierarchical models for 2D presence/absence data having ambiguous zeroes: With a biogeographical case study on dingo behaviour

This dissertation is primarily an applied statistical modelling investigation, motivated by a case study comprising real data and real questions. Theoretical questions on modelling and computation of normalization constants arose from pursuit of these data analytic questions. The essence of the thesis can be described as follows. Consider binary data observed on a two-dimensional lattice. A common problem with such data is the ambiguity of zeroes recorded. These may represent zero response given some threshold (presence) or that the threshold has not been triggered (absence). Suppose that the researcher wishes to estimate the effects of covariates on the binary responses, whilst taking into account underlying spatial variation, which is itself of some interest. This situation arises in many contexts and the dingo, cypress and toad case studies described in the motivation chapter are examples of this. Two main approaches to modelling and inference are investigated in this thesis. The first is frequentist and based on generalized linear models, with spatial variation modelled by using a block structure or by smoothing the residuals spatially. The EM algorithm can be used to obtain point estimates, coupled with bootstrapping or asymptotic MLE estimates for standard errors. The second approach is Bayesian and based on a three- or four-tier hierarchical model, comprising a logistic regression with covariates for the data layer, a binary Markov Random field (MRF) for the underlying spatial process, and suitable priors for parameters in these main models. The three-parameter autologistic model is a particular MRF of interest. Markov chain Monte Carlo (MCMC) methods comprising hybrid Metropolis/Gibbs samplers is suitable for computation in this situation. Model performance can be gauged by MCMC diagnostics. Model choice can be assessed by incorporating another tier in the modelling hierarchy. This requires evaluation of a normalization constant, a notoriously difficult problem. Difficulty with estimating the normalization constant for the MRF can be overcome by using a path integral approach, although this is a highly computationally intensive method. Different methods of estimating ratios of normalization constants (N Cs) are investigated, including importance sampling Monte Carlo (ISMC), dependent Monte Carlo based on MCMC simulations (MCMC), and reverse logistic regression (RLR). I develop an idea present though not fully developed in the literature, and propose the Integrated mean canonical statistic (IMCS) method for estimating log NC ratios for binary MRFs. The IMCS method falls within the framework of the newly identified path sampling methods of Gelman & Meng (1998) and outperforms ISMC, MCMC and RLR. It also does not rely on simplifying assumptions, such as ignoring spatio-temporal dependence in the process. A thorough investigation is made of the application of IMCS to the three-parameter Autologistic model. This work introduces background computations required for the full implementation of the four-tier model in Chapter 7. Two different extensions of the three-tier model to a four-tier version are investigated. The first extension incorporates temporal dependence in the underlying spatio-temporal process. The second extensions allows the successes and failures in the data layer to depend on time. The MCMC computational method is extended to incorporate the extra layer. A major contribution of the thesis is the development of a fully Bayesian approach to inference for these hierarchical models for the first time. Note: The author of this thesis has agreed to make it open access but invites people downloading the thesis to send her an email via the 'Contact Author' function.

Group maintenance scheduling : a case study for a pipeline network

This paper presents a group maintenance scheduling case study for a water distributed network. This water pipeline network presents the challenge of maintaining aging pipelines with the associated increases in annual maintenance costs. The case study focuses on developing an effective maintenance plan for the water utility. Current replacement planning is difficult as it needs to balance the replacement needs under limited budgets. A Maintenance Grouping Optimization (MGO) model based on a modified genetic algorithm was utilized to develop an optimum group maintenance schedule over a 20-year cycle. The adjacent geographical distribution of pipelines was used as a grouping criterion to control the searching space of the MGO model through a Judgment Matrix. Based on the optimum group maintenance schedule, the total cost was effectively reduced compared with the schedules without grouping maintenance jobs. This optimum result can be used as a guidance to optimize the current maintenance plan for the water utility.

Spatial clusters of suicide in Australia

Background: Understanding the spatial distribution of suicide can inform the planning, implementation and evaluation of suicide prevention activity. This study explored spatial clusters of suicide in Australia, and investigated likely socio-demographic determinants of these clusters. Methods: National suicide and population data at a statistical local area (SLA) level were obtained from the Australian Bureau of Statistics for the period of 1999 to 2003. Standardised mortality ratios (SMR) were calculated at the SLA level, and Geographic Information System (GIS) techniques were applied to investigate the geographical distribution of suicides and detect clusters of high risk in Australia. Results: Male suicide incidence was relatively high in the northeast of Australia, and parts of the east coast, central and southeast inland, compared with the national average. Among the total male population and males aged 15 to 34, Mornington Shire had the whole or a part of primary high risk cluster for suicide, followed by the Bathurst-Melville area, one of the secondary clusters in the north coastal area of the Northern Territory. Other secondary clusters changed with the selection of cluster radius and age group. For males aged 35 to 54 years, only one cluster in the east of the country was identified. There was only one significant female suicide cluster near Melbourne while other SLAs had very few female suicide cases and were not identified as clusters. Male suicide clusters had a higher proportion of Indigenous population and lower median socio-economic index for area (SEIFA) than the national average, but their shapes changed with selection of maximum cluster radii setting. Conclusion: This study found high suicide risk clusters at the SLA level in Australia, which appeared to be associated with lower median socio-economic status and higher proportion of Indigenous population. Future suicide prevention programs should focus on these high risk areas.

Quantitative proteomic approach to study subcellular localization of membrane proteins

As proteins within cells are spatially organized according to their role, knowledge about protein localization gives insight into protein function. Here, we describe the LOPIT technique (localization of organelle proteins by isotope tagging) developed for the simultaneous and confident determination of the steady-state distribution of hundreds of integral membrane proteins within organelles. The technique uses a partial membrane fractionation strategy in conjunction with quantitative proteomics. Localization of proteins is achieved by measuring their distribution pattern across the density gradient using amine-reactive isotope tagging and comparing these patterns with those of known organelle residents. LOPIT relies on the assumption that proteins belonging to the same organelle will co-fractionate. Multivariate statistical tools are then used to group proteins according to the similarities in their distributions, and hence localization without complete centrifugal separation is achieved. The protocol requires approximately 3 weeks to complete and can be applied in a high-throughput manner to material from many varied sources.

Correlating flow induced shear stress and chondrocytes activity in micro-porous scaffold using computational fluid dynamics and rapid prototyping

Flow induced shear stress plays an important role in regulating cell growth and distribution in scaffolds. This study sought to correlate wall shear stress and chondrocytes activity for engineering design of micro-porous osteochondral grafts based on the hypothesis that it is possible to capture and discriminate between the transmitted force and cell response at the inner irregularities. Unlike common tissue engineering therapies with perfusion bioreactors in which flow-mediated stress is the controlling parameter, this work assigned the associated stress as a function of porosity to influence in vitro proliferation of chondrocytes. D-optimality criterion was used to accommodate three pore characteristics for appraisal in a mixed level fractional design of experiment (DOE); namely, pore size (4 levels), distribution pattern (2 levels) and density (3 levels). Micro-porous scaffolds (n=12) were fabricated according to the DOE using rapid prototyping of an acrylic-based bio-photopolymer. Computational fluid dynamics (CFD) models were created correspondingly and used on an idealized boundary condition with a Newtonian fluid domain to simulate the dynamic microenvironment inside the pores. In vitro condition was reproduced for the 3D printed constructs seeded by high pellet densities of human chondrocytes and cultured for 72 hours. The results showed that cell proliferation was significantly different in the constructs (p<0.05). Inlet fluid velocity of 3×10-2mms-1 and average shear stress of 5.65×10-2 Pa corresponded with increased cell proliferation for scaffolds with smaller pores in hexagonal pattern and lower densities. Although the analytical solution of a Poiseuille flow inside the pores was found insufficient for the description of the flow profile probably due to the outside flow induced turbulence, it showed that the shear stress would increase with cell growth and decrease with pore size. This correlation demonstrated the basis for determining the relation between the induced stress and chondrocyte activity to optimize microfabrication of engineered cartilaginous constructs.