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The castles of the late medieval period represent some of the finest medieval monuments in Britain, with an almost infinite capacity to fascinate and draw controversy. They are also a source of considerable academic debate. The contents of this volume represent key works in castle scholarship. Topics discussed include castle warfare, fortress customs, architectural design and symbolism, spatial planning and the depiction of castles in medieval romance. The contributions also serve to highlight the diversity of approaches to the medieval castle, ranging from the study of documentary and literary sources, analysis of fragmentary architectural remains and the recording of field archaeology. The result is a survey that offers an in-depth analysis of castle building from the thirteenth to the fifteenth centuries, and places castles within their broader social, architectural and political contexts.
Robert Liddiard is Professor of History, University of East Anglia.
Contributors: Nicola Coldstream, Charles Coulson, Philip Dixon, Graham Fairclough, P.A. Faulkner, John Goodall, Beryl Lott, Charles McKean, T.E. McNeill, Richard K. Morris, Michael Prestwich, Christopher Taylor, Muriel A. Whitaker.
Late Medieval Castles is a companion to Anglo-Norman Castles (2003), a volume that brought together a series of historiographically significant articles on castles and castle-building in the period from the Norman Conquest to the early thirteenth century. The format and themes of the present collection are broadly comparable with the earlier book, but with the focus on those castles dating to the period c.1250–1500.
In the course of bringing Anglo-Norman Castles to publication the somewhat arbitrary cut-off date of c.1225 seemed unsatisfactory for a number of reasons. On a practical level, there were highly relevant articles that could not be included because the subject matter fell outside the chronological range of the volume. A more scholarly concern was the fact that a number of issues pertinent to castle-building in the eleventh and twelfth centuries could not be satisfactorily addressed without reference to subsequent developments in the thirteenth and fourteenth. Allied to this, a focus on Anglo-Norman building (no matter how justifiable in historical terms) does perhaps contribute, albeit unwittingly, to the erroneous idea that the eleventh and twelfth centuries are the most important centuries for castle-building, a time when the ‘true’ castle is to be found, and that the period that follows, particularly after 1300, is something of an anti-climax. The present volume should therefore be seen as a continuation of the broad themes discussed in the introduction to Anglo-Norman Castles, with the aim of pursuing them in a late medieval context.
In the years since 2003 there have been a number of important publications in the field of castle studies, and castles continue to be a source of controversy and to provoke debate. Despite the fact that the availability of some secondary material has been made easier through electronic access, I have been consistently reminded by academic colleagues that a compilation such as this is worthwhile, both for the student reader and those seeking a path into the specialist secondary literature. This author at least also believes that there is value in bringing together in one place a series of important contributions that have defined the subject and which also illustrate a diversity of approaches.
We present optical and IR observations of the dwarf nova OY Car during the May 1985 superoutburst. From them we find that the superhump has a temperature of ~8000K and an area of order half the size of the red dwarf or accretion disk. We also compare the behaviour during two simultaneous optical/IR observations. Whilst the light curves in the two pass bands are similar during one observation, in the other observation they show marked differences that may be due to a cool region in the outer disk.
Maladaptive cognitive biases such as negative attributional style and hopelessness have been implicated in the development and maintenance of depression. According to the hopelessness theory of depression, hopelessness mediates the association between attributional style and depression. The aetiological processes underpinning this influential theory remain unknown. The current study investigated genetic and environmental influences on hopelessness and its concurrent and longitudinal associations with attributional style and depression across adolescence and emerging adulthood. Furthermore, given high co-morbidity between depression and anxiety, the study investigated whether these maladaptive cognitions constitute transdiagnostic cognitive content common to both internalizing symptoms.
A total of 2619 twins/siblings reported attributional style (mean age 15 and 17 years), hopelessness (mean age 17 years), and depression and anxiety symptoms (mean age 17 and 20 years).
Partial correlations revealed that attributional style and hopelessness were uniquely associated with depression but not anxiety symptoms. Hopelessness partially mediated the relationship between attributional style and depression. Hopelessness was moderately heritable (A = 0.37, 95% confidence interval 0.28–0.47), with remaining variance accounted for by non-shared environmental influences. Independent pathway models indicated that a set of common genetic influences largely accounted for the association between attributional style, hopelessness and depression symptoms, both concurrently and across development.
The results provide novel evidence that associations between attributional style, hopelessness and depression symptoms are largely due to shared genetic liability, suggesting developmentally stable biological pathways underpinning the hopelessness theory of depression. Both attributional style and hopelessness constituted unique cognitive content in depression. The results inform molecular genetics research and cognitive treatment approaches.
Sheep were domesticated in the Near East around 10 000 years ago and spread into Western Europe from there (J. Clutton-Brock 1981). Sheep similar to Soays had reached the Orkneys by 4000 bc and the sheep population of St Kilda may have originated around that date. In many aspects of their anatomy and physiology, they appear to be intermediate between contemporary domestic sheep and wild sheep (Boyd and Jewell 1974; Jewell 1986).
To understand the unusual dynamics of Soay sheep and their consequences for selection and adaptation, it is important to know something of their history as well as of the human inhabitants of St Kilda. The first two sections of this chapter describe the islands of St Kilda (section 2.2) and their history (section 2.3). Subsequent sections describe the appearance and anatomy of Soay sheep (section 2.4), their feeding ecology (section 2.5) and their reproductive system (section 2.6). Since variation in fecundity and neonatal survival affect the growth rate of the population, we describe the factors affecting the early development of lambs (section 2.7) as well as the factors affecting winter survival in juveniles and yearlings (section 2.8). Finally section 2.9 reviews the costs of reproduction and other factors affecting mortality in adults.
The islands of St Kilda
The four main islands of the St Kilda archipelago lie 160 km to the north-west of the Scottish mainland (Fig. 1.1).
Life tables provide information on the mean survival and reproductive rates of animals of different ages and sex (Keyfitz 1968; Pollard 1973; Caughley 1977). These rates can be presented in many ways, but the key information in any life table is the proportion of animals that survive to age x(lx) and the number of recruits to the population that an animal of age x produces (mx). Life tables can easily be used to calculate the mean number of progeny per individual per generation (R0 = σlxmx), generation length (Tc = σlxmxx/R0) and the population growth rate (r = ln(R0)/Tc). When R0 = 1 each individual replaces itself and the population growth rate (r) is zero. When R0 < 1 individuals are failing to replace themselves, the population is declining and r < 0. Finally when R0 > 1 individuals are more than replacing themselves and the population increases in size (r > 0). Life tables now exist for a wide range of species and are much used in population and evolutionary ecology to construct models of population dynamics, to estimate whether a population is increasing or decreasing in size and to estimate the strength of selection (Caswell 1989, 2001; Brault and Caswell 1993). If a population biologist wanted to find out details about a species' population biology he would almost certainly look for an available life table before doing anything else.
A conspicuous feature of many naturally limited populations of long-lived vertebrates is their relative stability. Both in populations that are regulated by predation or culling and in food-limited populations, population size can persist at approximately the same level for decades or even centuries (Runyoro et al. 1995; Waser et al. 1995; Clutton-Brock et al. 1997a; Newton 1998). The persistent fluctuations shown by Soay sheep and by some other island populations of ungulates (Boyd 1981; Leader-Williams 1988; Boussès 1991) raise general questions about the causes and consequences of variation in the stability of populations (see section 1.2). How regular are they? How are they related to population density? What are their immediate causes? To what extent do fluctuations in food availability, parasite number or predator density contribute to them? And what are their effects on development and on the phenotypic quality of animals born at contrasting population densities? And how much do changes in phenotype contribute to changes in dynamics?
As yet, there are very few cases where we understand either the ecological causes or the demographic consequences of persistent fluctuations in the size of naturally regulated populations of mammals (Hanski 1987; Saether 1997). Since we are able to monitor the growth, movements, breeding success and survival of large samples of individuals as population density changes, the Soay sheep offer an opportunity to investigate the causes and consequences of changes in population size with unusual precision (see Chapter 1).
Recent increases in the number of time-series long enough to provide an adequate description of population fluctuations clearly show that population stability varies widely among animals with similar longevities and rates of reproduction, as well as between species with contrasting life histories (Caughley & Krebs 1983; Gaillard et al. 2000). For example, among grazing ungulates, populations may either show little variation in size across years, irregular oscillations, semi-regular oscillations resembling the stable limit cycles found in some smaller mammals or dramatic oscillations occasionally leading to extinction (Peterson et al. 1984; Fowler 1987b; Coulson et al. 2000). While many ecological differences probably contribute to these differences (including predation, disease and human interference), the fact that stability varies widely among naturally regulated ungulate populations living in environments where human intervention is minimal and predators are absent (Boyd 1981a,b; Boussès et al. 1991; Clutton-Brock et al. 1997a), suggests that variation in population dynamics may often be caused by interactions between populations and their food supplies.
Theoreticians have explored the possibility that contrasts in population dynamics may be consistently related to differences in life histories or in the temporal or spatial distribution of resources (e.g. Peterson et al. 1984; Sinclair 1989; Sæther 1997; Illius & Gordon 2000; Owen-Smith 2002). While it is likely that both these differences may contribute to variation in dynamics, attempts to explain observed variation mostly assume that the causes of contrasts are sufficiently simple to be explained by general models derived from first principles (Caughley 1977).
Most species-specific conservation efforts require estimates of population size to establish priorities and to
monitor management activities. Yet obtaining reliable estimates of animal populations is often difficult, especially
given time and funding limitations experienced by
many research programmes. Consequently, there is a
great need for practical methods to provide indices of
animal density. Ideally, accurate estimates of populations
would be obtained through mark-recapture data
collected from recognizable individuals over multiple
censuses that cover the entire population range. Such
data are rarely available, so conservation biologists have
no alternative but to resort to analyses of less perfect
data, ranging from permanent-point censuses from cameras
through to transect data on sightings and spoor
encounters. The importance of census and monitoring
data makes the development, and validation, of new
techniques a priority. Because we do not live in a perfect
world, there is a need to develop methods that can
give an estimate of population sizes. It would be naïve
to assume that these will give hugely accurate estimates
of population size, but these techniques can prove useful
in identifying areas that are likely to benefit from
We present a case study of the use of simulation modelling to develop and test strategies for managing populations under uncertainty. Strategies that meet a stock conservation criterion under a base case scenario are subjected to a set of robustness trials, including biased and highly variable abundance estimates and poaching. Strategy performance is assessed with respect to a conservation criterion, the revenues achieved and their variability. Strategies that harvest heavily, even when the population is apparently very large, perform badly in the robustness trials. Setting a threshold below which harvesting does not take place, and above which all individuals are harvested, does not provide effective protection against over-harvesting. Strategies that rely on population growth rates rather than estimates of population size are more robust to biased estimates. The strategies that are most robust to uncertainty are simple, involving harvesting a relatively small proportion of the population each year. The simulation modelling approach to exploring harvesting strategies is suggested as a useful tool for the assessment of the performance of competing strategies under uncertainty.