18 research outputs found
How Group Size Affects Vigilance Dynamics and Time Allocation Patterns: The Key Role of Imitation and Tempo
In the context of social foraging, predator detection has been the subject of numerous studies, which acknowledge the adaptive response of the individual to the trade-off between feeding and vigilance. Typically, animals gain energy by increasing their feeding time and decreasing their vigilance effort with increasing group size, without increasing their risk of predation (‘group size effect’). Research on the biological utility of vigilance has prevailed over considerations of the mechanistic rules that link individual decisions to group behavior. With sheep as a model species, we identified how the behaviors of conspecifics affect the individual decisions to switch activity. We highlight a simple mechanism whereby the group size effect on collective vigilance dynamics is shaped by two key features: the magnitude of social amplification and intrinsic differences between foraging and scanning bout durations. Our results highlight a positive correlation between the duration of scanning and foraging bouts at the level of the group. This finding reveals the existence of groups with high and low rates of transition between activies, suggesting individual variations in the transition rate, or ‘tempo’. We present a mathematical model based on behavioral rules derived from experiments. Our theoretical predictions show that the system is robust in respect to variations in the propensity to imitate scanning and foraging, yet flexible in respect to differences in the duration of activity bouts. The model shows how individual decisions contribute to collective behavior patterns and how the group, in turn, facilitates individual-level adaptive responses
Absence of progesterone receptor associated with secondary breast cancer in postmenopausal women
The relationship between expression of receptors for oestrogen and progesterone (ER and PR) and disease progression in breast cancer was investigated by comparing immunocytochemical determinations of ER and PR in fine needle aspirates from primary and secondary breast tumours. Rates of receptor expression were significantly higher in primary than in secondary lesions: for ER 63.3% (n = 689) compared with 45.3% (n = 223), and for PR 53.7% (n = 443) compared with 33.1% (n = 121). The effect of menopausal status was examined by subdividing the patient cohort into those over or under the age of 50 years. In both instances, ER expression in secondary tumours was relatively low; however, only postmenopausal patients had significantly lower rates of PR expression in secondary tumours. Consistent with this, an increase in the ER+PR– profile in secondary tumours compared with primary cases from postmenopausal patients was seen, and in a multivariate analysis, a specific absence of PR expression in secondary tumours was revealed. Comparison of ER and PR expression in simultaneously sampled primary tumours and lymph node metastases from the same patient showed that receptor expression was stable with progression to a metastatic site as results were concordant for ER in 92% (n = 88) and PR in 93.8% of cases (n = 65). These results suggest that absence of PR expression in primary breast cancer is associated with disease progression and may be a marker of an aggressive tumour phenotype. © 1999 Cancer Research Campaig
Variability in storm climate along the Gulf of Cadiz: the role of large scale atmospheric forcing and implications to coastal hazards
In the context of increased coastal hazards due
to variability in storminess patterns, the danger of coastal
damages and/or morphological changes is related to the
sum of sea level conditions, storm surge, maximum wave
height and run up values. In order to better understand the
physical processes that cause the variability of the above
parameters a 44 years reanalysis record (HIPOCAS) was
used. The HIPOCAS time-series was validated with real
wave and sea-level data using linear and vector correlation
methods. In the present work changes in the magnitude,
duration, frequency and approach direction of the Atlantic
storms over the Gulf of Cadiz (SW Iberian Peninsula)
were identified by computing various storm characteristics
such as maximum wave height, total energy per storm wave
direction and storm duration. The obtained time-series were
compared with large-scale atmospheric indices such as the
North Atlantic Oscillation (NAO) and the East Atlantic pattern.
The results show a good correlation between negative
NAO values and increased storminess over the entire Gulf of Cadiz. Furthermore, negative NAO values were correlated
with high residual sea level values. Finally, a joint
probability analysis of storm and sea level analysis resulted
in increased probabilities of the two events happening at
the same time indicating higher vulnerability of the coast
and increased coastal risks. The above results were compared
with coastal inundation events that took place over
the last winter seasons in the province of Cadiz.info:eu-repo/semantics/publishedVersio
Effects of extreme surges.
Extreme value analysis of sea levels is an essential component of risk analysis and protection strategy for many coastal regions. Since the tidal component of the sea level is deterministic, it is the stochastic variation in extreme surges that is the most important to model. Historically, this modelling has been accomplished by fitting classical extreme value models to series of annual maxima data. Recent developments in extreme value modelling have led to alternative procedures that make better use of available data, and this has led to much refined estimates of extreme surge levels. However, one aspect that has been routinely ignored is seasonality. In an earlier study we identified strong seasonal effects at one of the number of locations along the eastern coastline of the United Kingdom. In this article, we discuss the construction and inference of extreme value models for processes that include components of seasonality in greater detail. We use a point process representation of extreme value behaviour, and set our inference in a Bayesian framework, using simulation-based techniques to resolve the computational issues. Though contemporary, these techniques are now widely used for extreme value modelling. However, the issue of seasonality requires delicate consideration of model specification and parameterization, especially for efficient implementation via Markov chain Monte Carlo algorithms, and this issue seems not to have been much discussed in the literature. In the present paper we make some suggestions for model construction and apply the resultant model to study the characteristics of the surge process, especially in terms of its seasonal variation, on the eastern UK coastline. Furthermore, we illustrate how an estimated model for seasonal surge can be combined with tide records to produce return level estimates for extreme sea levels that accounts for seasonal variation in both the surge and tidal processes
Climate change impact on wave energy in the Persian Gulf
Excessive usage of fossil fuels and high emission of greenhouse gases have increased the earth’s temperature, and consequently have changed the patterns of natural phenomena such as wind speed, wave height, etc. Renewable energy resources are ideal alternatives to reduce the negative effects of increasing greenhouse gases emission and climate change. However, these energy sources are also sensitive to changing climate. In this study, the effect of climate change on wave energy in the Persian Gulf is investigated. For this purpose, future wind data obtained from CGCM3.1 model were downscaled using a hybrid approach and modification factors were computed based on local wind data (ECMWF) and applied to control and future CGCM3.1 wind data. Downscaled wind data was used to generate the wave characteristics in the future based on A2, B1, and A1B scenarios, while ECMWF wind field was used to generate the wave characteristics in the control period. The results of these two 30-yearly wave modelings using SWAN model showed that the average wave power changes slightly in the future. Assessment of wave power spatial distribution showed that the reduction of the average wave power is more in the middle parts of the Persian Gulf. Investigation of wave power distribution in two coastal stations (Boushehr and Assalouyeh ports) indicated that the annual wave energy will decrease in both stations while the wave power distribution for different intervals of significant wave height and peak period will also change in Assalouyeh according to all scenarios.Full Tex