bluuebunny/crossref_metadata_2025_split huggingface dataset:
Seminal tissue factor revisited
Authors: LWALEED B. , JACKSON C. , GREENFIELD R. , STEWART A. , DELVES G. , BIRCH B. , COOPER A. 
Published: December 2005

SummaryStudies of seminal tissue factor (TF) are few and mostly based on small numbers. Due to the reported lack of factor (F) X in semen, it has been suggested that TF may not have a role in seminal coagulum formation. However, recent identification of a number of haemostatic factors in semen justifies a re‐evaluation of its occurrence. Semen specimens were collected from sub‐fertile (n = 19), normally fertile (n = 33), semen donors (n = 30) and vasectomized subjects (n = 62), some fractionated into sperm, a prostasome‐rich fraction and seminal plasma. Functional and antigenic TF levels were measured and related to conventional fertility parameters. Semen contains high concentration of functional and antigenic TF. Most TF was found in seminal plasma prepared by low‐speed centrifugation. When further fractionated by ultracentrifugation much of this may reside in the pellet (prostasomal fraction). It was also detectable on sperm. TF antigen levels were higher in vasectomized subjects than sub‐fertile, normally fertile, donor (p = 0.02) and a ‘pooled normal semen parameters’ (PNSP) stratification (derived from a combination of measurements) (p = 0.06). The sub‐fertile group showed a wider variation than normal, donor or the PNSP subjects. Seminal TF antigen levels correlated significantly with sperm agglutination (p = 0.03) and abnormal sperm morphology (p = 0.04). Subjects with anti‐sperm antibodies also showed high TF antigen levels. In conclusion, semen contains functional and antigenic TF at high concentrations. A full complement of clotting factors probably exists in semen, so some pro‐coagulant role for TF should not be excluded. Decreased seminal TF levels appear to be associated with seminal parameters that are known to favour male fertility.
In utero exposure to persistent organic pollutants in relation to testicular cancer risk
Authors: HARDELL LENNART , VAN BAVEL BERT , LINDSTRÖM GUNILLA , ERIKSSON MIKAEL , CARLBERG MICHAEL 
Published: December 2005

SummaryTesticular cancer is the most common tumour type in young men. In Sweden the annual age‐adjusted incidence increased significantly by 2.4% during the time period 1984–1993 and during 1994–2003 by 1.4%. Exposure to endocrine disrupting chemicals during the foetal period has been postulated to be a risk factor. In this investigation we studied the concentrations of chlorinated biphenyls (PCBs), p,p′‐dichlorodiphenyl‐dichloroethylene (pp′‐DDE), hexachlorobenzene (HCB), chlordanes and polybrominated diphenylethers (PBDEs) in 58 cases with testicular cancer and 61 age‐matched controls. Furthermore, case and control mothers were also asked to participate and 44 case mothers and 45 control mothers agreed. No significant differences were found between cases and controls. Case mothers had in general higher concentrations of these chemicals. For the sum of PCBs an odds ratio (OR) = 3.8, 95% confidence interval (CI) = 1.4–10 was calculated using the median concentration for the controls as cut‐off value. For HCB OR = 4.4, CI = 1.7–12 and for PBDE OR = 2.5, 95% CI = 1.02–6.0 were obtained, whereas OR was not significantly increased for pp′‐DDE and sum of chlordanes. The cases were born during a period with high concentrations of persistent organic pollutants (POPs) in humans. The decline of the increasing incidence of testicular cancer during recent years may reflect decreasing body burden of certain POPs since the 1980s.
A spatially explicit approach to estimating species occupancy and spatial correlation
Authors: HUI CANG , McGEOCH MELODIE A. , WARREN MARIÉ 
Published: December 2005

Summary

Understanding and predicting the form of species distributions, or occupancy patterns, is fundamental to macroecology and is dependent on the identification of scaling relationships that underlie the patterns observed.
Occupancy–abundance models based on the negative binomial distribution and Taylor's power law are spatially implicit, rather than explicit, as they include no information on the relative positions of individuals. Here we present a spatially explicit model, the spatial scaling occupancy (SSO) model, to estimate species occupancy and spatial correlation, based on join‐count statistics, or a pair approximation, approach. This model provides a spatially explicit description of species range size and aspects of range structure.
Occupancy data from Drosophilidae species inhabiting a decaying fruit mesocosm were used to test the SSO model. Predictions from the spatially implicit and explicit models were largely equally accurate. The SSO model is thus more efficient as it is less data demanding, and more informative as it provides an estimation of spatial correlation.
The results also showed that species distribution patterns differ when examined with spatially implicit vs. explicit approaches; the scaling relationship between occupancy and local density identifies a focal grain for studying the scale‐dependent nature of ecological relationships; and the longer the length of the sample edge, the higher the occupancy observed under conditions of spatial aggregation.
The SSO model presents a step towards a general scaling model for occupancy, and demonstrates that the inclusion of spatially explicit information in macroecological models warrants further attention.
Intraguild indirect effects through trophic cascades between stream‐dwelling fishes
Authors: KATANO OSAMU , NAKAMURA TOMOYUKI , YAMAMOTO SHOICHIRO 
Published: December 2005

SummaryTo examine the strength and role of indirect effects through trophic cascades by omnivorous fish on algal biomass in streams, we introduced one of four fish species (ayuPlecoglossus altivelis altivelis, pike gudgeonPseudogobio esocinus esocinus, Japanese daceTribolodon hakonensisand pale chubZacco platypus) in experimental pools. We also investigated the indirect effects of gudgeon, dace and chub on the growth of ayu.We chose the four fish species across a continuum of omnivory. Ayu fed mainly on benthic algae, and gudgeon predominantly on invertebrates. Dace and chub fed on both algae and invertebrates, but dace preyed on invertebrates more than chub.The presence of gudgeon, dace and chub reduced the number of algal‐feeding invertebrates and increased the algal biomass through trophic cascades. Consequently, ayu growth rate over the experimental period in pools with one of the three fish species was 25·9–44·1 times greater than the growth rate in pools with only ayu.The positive indirect effect on ayu growth was large for gudgeon and dace and small for chub, whereas the addition of ayu reduced ayu growth considerably due to intraspecific competition.The relative intensity of indirect effects on ayu growth through trophic cascades was predictable from the food overlap between ayu and the other fishes. However, the similar strength of indirect effects by gudgeon and dace that fed differently on algae and invertebrates suggests that feeding behaviour, prey preference and trait‐mediated indirect interactions were also important in the prediction.
Hunt warm, rest cool: bioenergetic strategy underlying diel vertical migration of a benthic shark
Authors: SIMS DAVID W. , WEARMOUTH VICTORIA J. , SOUTHALL EMILY J. , HILL JACQUELINE M. , MOORE PIPPA , RAWLINSON KATE , HUTCHINSON NEIL , BUDD GEORGINA C. , RIGHTON DAVID , METCALFE JULIAN D. , NASH JON P. , MORRITT DAVID 
Published: December 2005

Summary

Diel vertical migration (DVM) is a widespread phenomenon among marine and freshwater organisms and many studies with various taxa have sought to understand its adaptive significance. Among crustacean zooplankton and juveniles of some fish species DVM is accepted widely as an antipredator behaviour, but little is known about its adaptive value for relatively large‐bodied, adult predatory fish such as sharks. Moreover, the majority of studies have focused on pelagic forms, which raises the question of whether DVM occurs in bottom‐living predators.
To investigate DVM in benthic predatory fish in the marine environment and to determine why it might occur we tracked movements of adult male dogfish (Scyliorhinus canicula) by short‐ and long‐term acoustic and archival telemetry. Movement studies were complemented with measurements of prey abundance and availability and thermal habitat within home ranges. A thermal choice experiment and energy budget modelling was used to investigate trade‐offs between foraging and thermal habitat selection.
Male dogfish undertook normal DVM (nocturnal ascent) within relatively small home ranges (∼100 × 100 m) comprising along‐bottom movements up submarine slopes from deeper, colder waters occupied during the day into warmer, shallow prey‐rich areas above the thermocline at night. Few daytime vertical movements occurred. Levels of activity were higher during the night above the thermocline compared to below it during the day indicating they foraged in warm water and rested in colder depths.
A thermal choice experiment using environmentally realistic temperatures supported the field observation that dogfish positively avoided warmer water even when it was associated with greater food availability. Males in laboratory aquaria moved into warm water from a cooler refuge only to obtain food, and after food consumption they preferred to rest and digest in cooler water.
Modelling of energy budgets under different realistic thermal‐choice scenarios indicated dogfish adopting a ‘hunt warm − rest cool’ strategy could lower daily energy costs by just over 4%. Our results provide the first clear evidence that are consistent with the hypothesis that a benthic marine‐fish predator utilizes DVM as an energy conservation strategy that increases bioenergetic efficiency.
Density‐dependent body growth reduces the potential of marine reserves to enhance yields
Authors: GÅRDMARK ANNA , JONZÉN NICLAS , MANGEL MARC 
Published: December 2005

Summary

Some models of marine no‐take reserves predict that reserves can enhance fishery yield. However, empirical evidence of this remains inconclusive. One reason for this may be the disregard for density‐dependent body growth in most models. Density‐dependent body growth links the number and size of individuals, and thus could influence the biomass of fishery yield.
We developed an age‐ and size‐structured model of an exploited population and analysed the effect of implementing a no‐take reserve of varying size.
Protecting part of a population from exploitation in a no‐take reserve results in a rapid build‐up of biomass inside the reserve because of increased survival. However, when body growth is density‐dependent it also results in reduced length at a given age within the no‐take reserve because of crowding effects. This prediction is backed up by empirical observations.
If there is export of individuals (here larvae) from the no‐take reserve, length at a given age will also decrease in the fished part of the population outside the reserve. An increase in the number of exploitable individuals thus results in decreased individual body mass. The positive effect of larval drift on fished population size and catch numbers will therefore rarely translate into an increase in equilibrium yield biomass.
Synthesis and applications. When body growth is density‐dependent, implementation of no‐take reserves affects the body size of both protected and exploitable individuals. Although reserves can have several benefits besides increasing yields, our study shows that, if density‐dependent somatic effects are important, a general increase in yield biomass cannot be expected. In populations with density‐dependent body growth, reserves are more likely to decrease yield biomass unless the population is severely overexploited. Analyses of the efficiency of marine reserves as a means of enhancing the yield of fisheries need to account for ecological processes, and density‐dependent body growth is likely to be key.
Pollen dispersal of oilseed rape: estimation of the dispersal function and effects of field dimension
Authors: KLEIN ETIENNE K. , LAVIGNE CLAIRE , PICAULT HERVE , RENARD MICHEL , GOUYON PIERRE‐HENRI 
Published: December 2005

Summary

Debate continues regarding the ecological impacts of genetically modified (GM) crops and their coexistence with non‐GM crops in Europe. In this debate, quantitative predictions of gene dispersal by pollen are necessary, and as a result numerous plot‐to‐plot gene flow experiments have been performed with various crops. However, plot‐to‐plot cross‐pollination rates (CPR) depend on spatial configuration of plots, implying that (i) they are difficult to compare among experiments and (ii) functions directly fitted on CPR data are inappropriate for predictions in other spatial contexts.
Modelling pollen dispersal via an individual dispersal function (IDF) circumvents these problems by accounting for spatial designs. We detail for oilseed rape how this approach can be used to both estimate an IDF from field data and predict CPR between two neighbouring fields of various sizes and shapes. Predictions were used to investigate the sensitivity of CPR to the family of IDF, the uncertainty in parameter estimates and the effects of field dimensions and isolation distances.
We fitted a range of families of IDF, including several types of tails, on previously published data. The best IDF was a fat‐tailed power‐law function, meaning frequent long‐distance dispersal.
The choice of IDF appeared crucial when predicting CPR between fields, occasionally being even more important than the distance between fields. Width of the source field and depth of the recipient field were next in importance. When approximated CPR were calculated without considering field dimensions, using distance between field centres gave better performance than field margins.
Synthesis and applications. This study demonstrates the value of IDF for quantitative predictions of pollen flow in variable spatial configurations. A spatially explicit model of agro‐ecosystems used to define management rules for the commercial release of GM crops in Europe already employs IDF but underestimates long‐distance dispersal for oilseed rape. These new parameter estimates will refine the performance of these models. Moreover, the detailed guidelines for estimating an IDF should encourage such statistical analysis of other dispersal data, enabling comparisons of dispersal data obtained for different environments and species and providing new IDF for management models.
Soil carbon addition affects plant growth in a species‐specific way
Authors: ESCHEN RENÉ , MÜLLER‐SCHÄRER HEINZ , SCHAFFNER URS 
Published: December 2005

Summary

Restoration of ex‐arable land to species‐rich habitats has become common practice in Europe as a result of Agri‐Environment Regulations. The results, however, are highly variable and often disappointing. Competition from weedy species as a result of high soil inorganic nitrogen levels can negatively affect the establishment and growth of desirable grassland plant species. One method that has been put forward to alter competitive interactions among plant species on restoration sites is the addition of carbon (C) to the soil. To make C addition a tool for successful restoration of species rich grassland, it should affect plant growth in a species‐specific way.
We present results of a greenhouse study to assess the species‐specific responses of 29 plant species to a range of C volumes added to the soil. Specifically, we tested whether functional group affiliation (legumes, other forbs and grasses), life form (annual and perennial) or nitrophilic status could explain parts of the variation in the response of the selected plant species to C addition.
Amending soil with increasing levels of C resulted in a log‐linear reduction in biomass accumulation of all plant species tested, but the responses varied significantly between the plant species. Functional group and life form explained a significant amount of variation observed among the plant species tested. The response of legumes to C addition was less pronounced than that of other forbs and grasses. Grasses showed a decrease in shoot : root ratio in response to C addition, while the shoot : root ratio of legumes and forbs remained constant. A greater shoot biomass reduction in response to C addition was found for annual species than for perennial species.
No correlation was found between the slope of the regression of log biomass vs. the amount of C added and the Ellenberg N‐values, indicating that there is no simple relationship between the nitrophilic status of a plant species and its response to C addition.
Synthesis and applications. The results suggest that adding C to soil is a promising tool in grassland restoration. C addition disproportionately reduced above‐ground biomass accumulation by annual plant species and grasses, which often dominate early succession on ex‐arable land. This may facilitate the establishment and growth of late‐seral species and thus the restoration of species‐rich grassland on ex‐arable land.
Estimating species richness: calibrating a large avian monitoring programme
Authors: KÉRY MARC , SCHMID HANS 
Published: December 2005

Summary

Species richness is the most widely used measure for the diversity of a biological community. Unfortunately, the number of species counted is usually a biased measure, as not all species present may be detected. Use of species counts as a proxy for true species richness requires the assumption of constant (over space and time) species detectability. This index assumption is hardly ever tested and, if violated, comparisons over time, space or other dimensions, for example different habitats, will be distorted. In monitoring programmes one therefore needs to know the proportion of species present that are detected and how this proportion is affected by external factors.
We used capture–recapture techniques to calibrate the Swiss breeding bird survey, where species richness is recorded annually in c. 270 1‐km2 quadrats during two to three visits and interest is focused on annual trends and regional comparisons. Hitherto, analysis has been restricted to species counts, while species detectability and its determinants are not known. We used the interpolated jackknife estimator to compute mean species detectability for 268 quadrats in 2001–03 and tested determinants of detectability related to space, time, observer, survey effort and biology.
Mean species detectability averaged 0·89 (SD 0·06, range 0·72–1·00), with no significant difference among years and significant, but small, regional differences. Observers differed, but surprisingly not in relation to their experience in a quadrat. Detectability was positively related to mean visit duration. Larger communities had a lower mean species detectability. A slight violation of population closure because of staggered arrival of migrants did not introduce any measurable bias into our results.
Synthesis and applications. Species detectability in the Swiss programme was high and varied little in relation to recognized sources of heterogeneity. Nevertheless, increased standardization should be considered for mean visit duration. While these results are pleasing for the Swiss programme and show that using counts as indices of species diversity need not always induce serious bias, conditions in other programmes, and in the future in the Swiss programme, may be quite different. Both in monitoring programmes and in ecological studies, as a way of risk minimization, species richness ought to be rigorously estimated whenever possible to avoid detection of spurious effects because of changes in species detectability.
Modelling distribution and abundance with presence‐only data
Authors: PEARCE JENNIE L. , BOYCE MARK S. 
Published: December 2005

SummaryPresence‐only data, for which there is no information on locations where the species is absent, are common in both animal and plant studies. In many situations, these may be the only data available on a species. We need effective ways to use these data to explore species distribution or species use of habitat.Many analytical approaches have been used to model presence‐only data, some inappropriately. We provide a synthesis and critique of statistical methods currently in use to both estimate and evaluate these models, and discuss the critical importance of study design in models where only presence can be identifiedProfile or envelope methods exist to characterize environmental covariates that describe the locations where organisms are found. Predictions from profile approaches are generally coarse, but may be useful when species records, environmental predictors and biological understanding are scarce.Alternatively, one can build models to contrast environmental attributes associated with known locations with a sample of random landscape locations, termed either ‘pseudo‐absences’ or ‘available’. Great care needs to be taken when selecting random landscape locations, because the way in which they are selected determines the modelling techniques that can be applied.Regression‐based models can provide predictions of the relative likelihood of occurrence, and in some situations predictions of the probability of occurrence. The logistic model is frequently applied, but can rarely be used directly to estimate these models; instead, case–control or logistic discrimination should be used depending on the sample design.Cross‐validation can be used to evaluate model performance and to assess how effectively the model reflects a quantity proportional to the probability of occurrence. However, more research is needed to develop a single measure or statistic that summarizes model performance for presence‐only data.Synthesis and applications.A number of statistical procedures are available to explore patterns in presence‐only data; the choice among them depends on the quality of the presence‐only data. Presence‐only records can provide insight into the vulnerability, historical distribution and conservation status of species. Models developed using these data can inform management. Our caveat is that researchers must be mindful of study design and the biases inherent in presence data, and be cautious in the interpretation of model predictions.