Childhood respiratory infection and adult chronic bronchitis in England and Wales.

The high mortality from chronic bronchitis in England and Wales and the excess of urban over rural mortality are unexplained. On dividing England and Wales into 212 local authority areas a strong geographical relation was found between death rates from chronic bronchitis and emphysema in 1959-78 and infant mortality from bronchitis and pneumonia during 1921-5. It was concluded that this relation provided strong evidence of a direct casual link between acute lower respiratory infection in early childhood and chronic bronchitis in adult life. Regression analysis suggested that infection in early childhood had a greater influence than cigarette smoking in determining the geographical distribution of chronic bronchitis. National time trends reflected the influence of both factors. Chronic air pollution in adult life may be less important a cause of chronic bronchitis than previously supposed.     

Multiple regression in geographical mortality studies, with allowance for spatially correlated errors

In order to provide clues to the aetiology of a disease, mortality indices for different areas are often related to explanatory variables by using multiple regression. However, mortality in nearby areas may be similar for reasons not attributable to the covariates, so the errors will not be independent. This paper suggests a way of finding a parameterized form for the correlated error structure by examining the residuals from an ordinary least squares regression. Such a model is then fitted by using maximum likelihood. An example based on cardiovascular mortality in British towns is used to illustrate the problem and our solution.     

Mortality from cardiovascular disease among interregional migrants in England and Wales.

OBJECTIVE--To investigate the extent to which geographical variations in mortality from ischaemic heart disease and stroke in Britain are influenced by factors in early life or in adulthood. DESIGN--Longitudinal study of migrants. SUBJECTS--1% sample of residents in England and Wales born before October 1939 and enumerated at the 1971 census (the Office of Population Censuses and Surveys'' longitudinal study). MAIN OUTCOME MEASURE--18,221 deaths from ischaemic heart disease and 9899 deaths from stroke during 1971-88 were analysed by areas of residence in 1939 and 1971. These included 2928 deaths from ischaemic heart disease and 1608 deaths from stroke among individuals moving between 14 areas defined by the major conurbations and nine standard administrative regions of England and Wales. RESULTS--The southeast to northwest gradient in mortality from ischaemic heart disease was related significantly to both the 1939 area (chi 2 = 6.09, df = 1) and area in 1971 (chi 2 = 5.05, df = 1). Geographical variations in mortality from stroke were related significantly to the 1939 area (chi 2 = 4.09, df = 1) but the effect of area in 1971 was greater (chi 2 = 8.07, df = 1). The effect of 1971 area on mortality from stroke was largely due to a lower risk of death from stroke among individuals moving into Greater London compared with migrants to the rest of the South East region (chi 2 = 4.54, df = 1). CONCLUSIONS--Geographical variations in mortality from cardiovascular disease in Britain may be partly determined by genetic factors, environmental exposures, or lifestyle acquired early in life, but the risk of fatal ischaemic heart disease and stroke changes on migration between areas with differing mortality. The low risk of death from stroke associated with residence in Greater London is acquired by individuals who move there.     

Association between an Internet-Based Measure of Area Racism and Black Mortality

Racial disparities in health are well-documented and represent a significant public health concern in the US. Racism-related factors contribute to poorer health and higher mortality rates among Blacks compared to other racial groups. However, methods to measure racism and monitor its associations with health at the population-level have remained elusive. In this study, we investigated the utility of a previously developed Internet search-based proxy of area racism as a predictor of Black mortality rates. Area racism was the proportion of Google searches containing the “N-word” in 196 designated market areas (DMAs). Negative binomial regression models were specified taking into account individual age, sex, year of death, and Census region and adjusted to the 2000 US standard population to examine the association between area racism and Black mortality rates, which were derived from death certificates and mid-year population counts collated by the National Center for Health Statistics (2004–2009). DMAs characterized by a one standard deviation greater level of area racism were associated with an 8.2% increase in the all-cause Black mortality rate, equivalent to over 30,000 deaths annually. The magnitude of this effect was attenuated to 5.7% after adjustment for DMA-level demographic and Black socioeconomic covariates. A model controlling for the White mortality rate was used to further adjust for unmeasured confounders that influence mortality overall in a geographic area, and to examine Black-White disparities in the mortality rate. Area racism remained significantly associated with the all-cause Black mortality rate (mortality rate ratio = 1.036; 95% confidence interval = 1.015, 1.057; p = 0.001). Models further examining cause-specific Black mortality rates revealed significant associations with heart disease, cancer, and stroke. These findings are congruent with studies documenting the deleterious impact of racism on health among Blacks. Our study contributes to evidence that racism shapes patterns in mortality and generates racial disparities in health.     

A multistage theory of age-specific acceleration in human mortality

Background  

Humans die at an increasing rate until late in life, when mortality rates level off. The causes of the late-life mortality plateau have been debated extensively over the past few years. Here, I examine mortality patterns separately for each of the leading causes of death. The different causes of death show distinct mortality patterns, providing some clues about the varying acceleration of mortality at different ages.     

Demographic, social, and economic effects on Mexican causes of death in 1990

This study examined spatial geographic patterns of cause of death and 28 demographic and socioeconomic influences on causes of death for 31 Mexican states plus the Federal District for 1990. Mortality data were obtained from the state death registration system and are age standardized. The 28 socioeconomic variables were obtained from Census records. Analysis included 2 submodels: one with all 28 socioeconomic variables in a stepwise regression, and one with each of the 4 groups of factors. The conceptual model is based on epidemiological transition theory and empirical findings. There are 4 stages in mortality decline. Effects are grouped as demographic, sociocultural, economic prosperity, and housing, health, and crime factors. Findings indicate that cancer and cardiovascular disease were strongly correlated and consistently high in border areas as well as the Federal District and Jalisco. Respiratory mortality had higher values in the Federal District, Puebla, and surrounding states, as well as Jalisco. The standardized total mortality rate was only in simple correlations associated inversely with underemployment. All cause specific mortality was associated with individual factors. Respiratory mortality was linked with manufacturing work force. Cardiovascular and cancer mortality were associated with socioeconomic factors. In submodel I, cause specific mortality was predicted by crowding, housing characteristics, marriage and divorce, and manufacturing work force. In submodel II, economic group factors had the strongest model fits explaining 33-60% of the "r" square. Hypothesized effects were only partially validated.     

Geographic Disparity in Chronic Obstructive Pulmonary Disease (COPD) Mortality Rates among the Taiwan Population

Chronic obstructive pulmonary disease (COPD) causes a high disease burden among the elderly worldwide. In Taiwan, the long-term temporal trend of COPD mortality is declining, but the geographical disparity of the disease is not yet known. Nationwide COPD age-adjusted mortality at the township level during 1999–2007 is used for elucidating the geographical distribution of the disease. With an ordinary least squares (OLS) model and geographically weighted regression (GWR), the ecologic risk factors such as smoking rate, area deprivation index, tuberculosis exposure, percentage of aborigines, density of health care facilities, air pollution and altitude are all considered in both models to evaluate their effects on mortality. Global and local Moran’s I are used for examining their spatial autocorrelation and identifying clusters. During the study period, the COPD age-adjusted mortality rates in males declined from 26.83 to 19.67 per 100,000 population, and those in females declined from 8.98 to 5.70 per 100,000 population. Overall, males’ COPD mortality rate was around three times higher than females’. In the results of GWR, the median coefficients of smoking rate, the percentage of aborigines, PM₁₀ and the altitude are positively correlated with COPD mortality in males and females. The median value of density of health care facilities is negatively correlated with COPD mortality. The overall adjusted R-squares are about 20% higher in the GWR model than in the OLS model. The local Moran’s I of the GWR’s residuals reflected the consistent high-high cluster in southern Taiwan. The findings indicate that geographical disparities in COPD mortality exist. Future epidemiological investigation is required to understand the specific risk factors within the clustering areas.     

Local Breast Cancer Spatial Patterning: A Tool for Community Health Resource Allocation to Address Local Disparities in Breast Cancer Mortality

Despite available demographic data on the factors that contribute to breast cancer mortality in large population datasets, local patterns are often overlooked. Such local information could provide a valuable metric by which regional community health resources can be allocated to reduce breast cancer mortality. We used national and statewide datasets to assess geographical distribution of breast cancer mortality rates and known risk factors influencing breast cancer mortality in middle Tennessee. Each county in middle Tennessee, and each ZIP code within metropolitan Davidson County, was scored for risk factor prevalence and assigned quartile scores that were used as a metric to identify geographic areas of need. While breast cancer mortality often correlated with age and incidence, geographic areas were identified in which breast cancer mortality rates did not correlate with age and incidence, but correlated with additional risk factors, such as mammography screening and socioeconomic status. Geographical variability in specific risk factors was evident, demonstrating the utility of this approach to identify local areas of risk. This method revealed local patterns in breast cancer mortality that might otherwise be overlooked in a more broadly based analysis. Our data suggest that understanding the geographic distribution of breast cancer mortality, and the distribution of risk factors that contribute to breast cancer mortality, will not only identify communities with the greatest need of support, but will identify the types of resources that would provide the most benefit to reduce breast cancer mortality in the community.     

Demographic response to environmental variation in breeding,stopover and non-breeding areas in a migratory passerine

Demographic rates of migratory species passing through several areas during their annual cycle may be affected by environmental conditions at each of these areas. Recent studies provide evidence that their impact is not necessarily immediate, but can be delayed. We studied survival, reproductive success and arrival date at the breeding grounds of red-backed shrikes Lanius collurio, a trans-Saharan migrant, in relation to weather and vegetation on the breeding grounds, the stopover sites during migration and in the wintering areas. These environmental factors are used as proxy of the shrike’s food supply. We analysed detailed demographic data of some 4,600 individuals from 25 years with multistate capture–recapture and mixed models. Survival probabilities of juveniles and breeders of both sexes varied in parallel across time, suggesting that all cohorts were sensitive to similar causes of mortality. Reproductive performance increased with temperature and decreased with rainfall on the breeding area. Moreover, it increased with vegetation cover in the Sahelian stopover area used on autumn migration suggesting a carry-over effect. Arrival date was negatively affected by spring temperatures in the breeding area. Hence, demographic rates were affected by environmental factors on the breeding grounds, but also outside and elsewhere. This suggests that the shrike’s population dynamics are driven by environmental factors operating at various scales of space and time. However, only a small amount of the temporal variation in demographic rates is explained by the environmental factors considered, suggesting that additional factors, such as those operating during migration, might be important.     

BaySTDetect: detecting unusual temporal patterns in small area data via Bayesian model choice

Space-time modeling of small area data is often used in epidemiology for mapping chronic disease rates and by government statistical agencies for producing local estimates of, for example, unemployment or crime rates. Although there is typically a general temporal trend, which affects all areas similarly, abrupt changes may occur in a particular area, e.g. due to emergence of localized predictors/risk factor(s) or impact of a new policy. Detection of areas with "unusual" temporal patterns is therefore important as a screening tool for further investigations. In this paper, we propose BaySTDetect, a novel detection method for short-time series of small area data using Bayesian model choice between two competing space-time models. The first model is a multiplicative decomposition of the area effect and the temporal effect, assuming one common temporal pattern across the whole study region. The second model estimates the time trends independently for each area. For each area, the posterior probability of belonging to the common trend model is calculated, which is then used to classify the local time trend as unusual or not. Crucial to any detection method, we provide a Bayesian estimate of the false discovery rate (FDR). A comprehensive simulation study has demonstrated the consistent good performance of BaySTDetect in detecting various realistic departure patterns in addition to estimating well the FDR. The proposed method is applied retrospectively to mortality data on chronic obstructive pulmonary disease (COPD) in England and Wales between 1990 and 1997 (a) to test a hypothesis that a government policy increased the diagnosis of COPD and (b) to perform surveillance. While results showed no evidence supporting the hypothesis regarding the policy, an identified unusual district (Tower Hamlets in inner London) was later recognized to have higher than national rates of hospital readmission and mortality due to COPD by the National Health Service, which initiated various local enhanced services to tackle the problem. Our method would have led to an early detection of this local health issue.     

Small area inequalities in breast cancer mortality and screening

Despite the unfavourable epidemiological status, the Hungarian breast cancer control is a non-appropriately developed system having considerable geographical inequalities. The study objective was to describe the small-area pattern of breast cancer mortality and of frequency of mammographical examination. The influence of socio-economical status on these patterns was also studied. The standardised mortality ratios and the standardised relative frequency of mammography was determined for settlements, zipcode areas and small regions. Their correlations were analysed with education, unemployment ratio, ratio of Gypsy and German ethnic minorities, population size, smoking, distance to the nearest hospital. The South-Transdanubian Region (STR, consisting of three counties, 22 small regions, 444 zipcode areas and 643 settlements) with 1 million inhabitants was the study area. All the studied parameters had significant spatial variability at all levels of aggregation. Beyond the relatively low average mortality risk in the STR, mortality clusters and increasing time trend were identified in certain areas. The mortality and the usage of mammography were inversely correlated with the indices of deprivation. These factors explain 64.5 and 17.5% of the whole variability of local mortality risks at the level of settlements and small regions. The explanatory role of these factors was similarly high for usage of mammography as well (40.2 and 52.6% for small regions and zipcode areas). The factors having the strongest influence were the population size (in settlement level mortality model), ratio of gypsies (in small region level mortality and mammography usage models) and ratio of Germans (in mammography usage model for zipcode areas). Inserting the counties' approaches for screening organisation into the model, it revealed that the population based screening organisation applied in Tolna county has the highest influence being 4.4 times stronger than the most important socio-economic factors.Altogether,it seems that the monitoring of spatial inequalities could improve the performance of breast cancer control identifying the populations with special needs, and there is a need to explore the pathways by which the socio-economic factors can exert their profound influence on the epidemiological status. Moreover, since the results clearly demonstrated that it is possible to achieve relatively high screening participation rates in Hungarian economical and legislative circumstances, the application of this successful method should be encouraged in other areas with low performance screening system.     

Species turnover in Amazonian frogs: low predictability and large differences among forests

The factors explaining species turnover at different spatial scales have been intensively studied, but most work in Amazonia has mainly focused on plants. For animals, it is not as obvious which environmental variables most affect differences in species composition among sites. We sought to identify what causes anuran turnover in Amazonian terra firme forests, and how the effectiveness of these factors varies among regions and across spatial scales. We sampled frogs in 56 plots along ponds and streams distributed over three terra firme forest areas in Eastern Amazonia. Using multiple regressions on distance matrices, we partitioned the variation in species turnover into components explained by variation in environmental and spatial distances. This was done in parallel for each area separately, and for all areas together, to assess the consistency of results between scales and across areas at the same scale. Each community seemed to respond to a set of factors specific to that area, and the identity of the variables that emerged as significant differed among areas and scales. Both geographical distances and environmental differences had larger explanatory power at the regional scale than at the local scale. The large differences among results from different areas caution against making broad generalizations about species turnover patterns from a single community, as real differences may exist among areas.     

Fine-scale genetically based differentiation of life-history traits in the perennial shrub Lupinus arboreus

Across large spatial scales, plants often exhibit genetically based differentiation in traits that allow adaptation to local sites. At smaller spatial scales, sharp boundaries between edaphic conditions also can create strong gradients in selection that counteract gene flow and result in local adaptation. Few studies, however, have examined the degree to which continuous populations of perennial plants exhibit genetically based differentiation in life-history traits over small spatial scales. We quantified the degree of genetically based differentiation in adaptive traits among bush lupine (Lupinus arboreus) from nearby dune and grassland sites (sites separated by < 0.75 km) that formed part of a larger continuous population of L. arboreus. We also investigated the spatial genetic structure of bush lupine by examining how genetic structure differed between seeds and juvenile plants that were less than two years old. We calculated F-statistics from gel electrophoresis of 10 polymorphic loci. We then used these values to infer levels of gene flow. To examine differentiation in adaptive traits, we created full-sibling/half-sibling families of lupine within each area and established reciprocal common gardens at each site. Across two years, we measured canopy volume, flowering time, seed set, and mortality of progeny planted in each garden. Spatial genetic structure among seeds was virtually nonexistent (F(ST) = 0.002), suggesting that gene flow between the three areas could be quite high. However, genetic structure increased 20-fold among juvenile plants (F(ST) = 0.041). We found strong evidence for fine-scale genetically based differentiation and local adaptation in adaptive traits such as plant size, flowering phenology, fecundity, and mortality. Thus, it is likely that strong but differing selection regimes within each area drive spatial differentiation in lupine life-history traits.     

Explaining grass-nutrient patterns in a savanna rangeland of southern Africa

Aim The search for possible factors influencing the spatial variation of grass quality is an important step towards understanding the distribution of herbivores, as well as a step towards identifying crucial areas for conservation and restoration. A number of studies have shown that grass quality at a regional scale is influenced by climatic variables. At a local scale, site factors and their interaction are considered important. In this study, we aimed at examining environmental correlates of grass quality at a local scale. The study also sought to establish if biotic factors interact significantly with abiotic factors in influencing a variation in grass quality. Location The study area is located in the Kruger National Park of South Africa. The study area stretches from west (22°49′ S and 31°01′ E) to east, (22°44′ S and 31°22′ E) covering an area of about 25 × 6 km in the far northern region of the Kruger National Park. Methods We collected environmental data such as soil texture, percentage grass cover and biomass as well as grass samples for chemical analysis from specific locations in the study area. In addition, a digital elevation model (DEM) with a resolution of 5 m was used to derive elevation, slope and aspect using a geographic information system (GIS), which were related to grass quality. We used correlation analysis and anova to relate environmental variables to grass quality. Multivariate analysis techniques were used to simultaneously analyse and explore the complex interactions between variables. Results and conclusions Our results indicate that there is a significant relationship between grass quality parameters and site‐specific factors such as slope, altitude, percentage grass cover, aspect and soil texture. Relatively, percentage grass cover and soil texture were more critical in explaining a variation in grass quality. Plant characteristics such as species type interact significantly with slope, altitude and geology in influencing nutrient distribution. The results of this study may give a better insight on foliar nutrient distribution patterns at a landscape scale in savanna rangelands. Furthermore, the results of this study may help in the selection of ancillary information, which could be used in conjunction with other data such as remotely sensed data to map grass quality – an important step towards understanding the distribution and feeding patterns of wildlife. However, we acknowledge that this study is based on one seasonal snapshot, therefore some slightly different findings may be obtained during other times of the year. Nevertheless, the study has revealed that under the conditions experienced during the study period, nutrient distribution varies with varying biotic and abiotic factors.     

Wartime evacuation and mortality from childhood leukaemia in England and Wales in 1945-9.

OBJECTIVE--To discover whether the wartime government evacuation of children from London and other population centres to rural districts was associated with any increase in childhood leukaemia. DESIGN--Observational study of mortality from leukaemia among the childhood population of England and Wales in relation to the unique population movements during the second world war. The 476 rural districts of England and Wales were ranked according to the ratio of government evacuees (two thirds of them children) to local children in September 1941. The districts were divided into three categories, each with similar numbers of children in 1947 but with different ratios of evacuees to local children ("low," "intermediate," "high"). Mortality from childhood leukaemia was examined in these three rural categories in 1945-9. Urban areas were also examined according to their exposure to evacuees. SETTING--Local authority areas of England and Wales. SUBJECTS--Children aged under 15. RESULTS--47% excess of leukaemia at ages 0-14 years occurred in 1945-9 in the rural "high" category for evacuees relative to the "low" category, with a significant trend across the three categories. There were increases in both the 0-4 and 5-14 year age groups, but these were larger in the older age group. Rates 25% lower than average occurred in rural areas with few evacuees. CONCLUSION--These findings suggest that wartime evacuation increased the incidence of childhood leukaemia in rural areas and that other forms of population mixing may have contributed to the increases in past decades. Overall, they add to the appreciable evidence for an infective basis in childhood leukaemia.     

Drought-Induced Multifactor Decline of Scots Pine in the Pyrenees and Potential Vegetation Change by the Expansion of Co-occurring Oak Species

Episodes of drought-induced tree dieback have been recently observed in many forest areas of the world, particularly at the dry edge of species distributions. Under climate change, those effects could signal potential vegetation shifts occurring over large geographical areas, with major impacts on ecosystem form and function. In this article, we studied the effect of a single drought episode, occurred which in summer 2005, on a Scots pine population in central Pyrenees (NE Spain). Our main objective was to study the environmental correlates of forest decline and vegetation change at the plot level. General and generalized linear models were used to study the relationship between canopy defoliation, mortality and recruitment, and plot characteristics. A drought-driven multifactor dieback was observed in the study forest. Defoliation and mortality were associated with the local level of drought stress estimated at each plot. In addition, stand structure, soil properties, and mistletoe infection were also associated with the observed pattern of defoliation, presumably acting as long-term predisposing factors. Recruitment of Scots pine was low in all plots. In contrast, we observed abundant recruitment of other tree species, mostly Quercus ilex and Q. humilis, particularly in plots where Scots pine showed high defoliation and mortality. These results suggest that an altitudinal upwards migration of Quercus species, mediated by the dieback of the currently dominant species, may take place in the studied slopes. Many rear-edge populations of Scots pine sheltered in the mountain environments of the Iberian Peninsula could be at risk under future climate scenarios.     

Inference of Cross-Level Interaction between Genes and Contextual Factors in a Matched Case-Control Metabolic Syndrome Study: A Bayesian Approach

Genes, environment, and the interaction between them are each known to play an important role in the risk for developing complex diseases such as metabolic syndrome. For environmental factors, most studies focused on the measurements observed at the individual level, and therefore can only consider the gene-environment interaction at the same individual scale. Indeed the group-level (called contextual) environmental variables, such as community factors and the degree of local area development, may modify the genetic effect as well. To examine such cross-level interaction between genes and contextual factors, a flexible statistical model quantifying the variability of the genetic effects across different categories of the contextual variable is in need. With a Bayesian generalized linear mixed-effects model with an unconditional likelihood, we investigate whether the individual genetic effect is modified by the group-level residential environment factor in a matched case-control metabolic syndrome study. Such cross-level interaction is evaluated by examining the heterogeneity in allelic effects under various contextual categories, based on posterior samples from Markov chain Monte Carlo methods. The Bayesian analysis indicates that the effect of rs1801282 on metabolic syndrome development is modified by the contextual environmental factor. That is, even among individuals with the same genetic component of PPARG_Pro12Ala, living in a residential area with low availability of exercise facilities may result in higher risk. The modification of the group-level environment factors on the individual genetic attributes can be essential, and this Bayesian model is able to provide a quantitative assessment for such cross-level interaction. The Bayesian inference based on the full likelihood is flexible with any phenotype, and easy to implement computationally. This model has a wide applicability and may help unravel the complexity in development of complex diseases.     

Late reproduction behaviour in Sardinia: spatial analysis suggests local aptitude towards reproductive longevity

Evolution in human life-history traits is influenced by environmental factors and, when genetic components underlie the relations, by micro-evolutionary forces. Age at reproduction is largely influenced by the familial cultural context and socioeconomic level, besides the maternal well-being and genetic background. The Sardinian population is characterized by historico-geographical isolation and differentiates from Italian mainland and other European populations in bio-demographic and cultural characteristics, among which the tendency to delay maternity persisting through generations. In our study, we investigated whether, in Sardinia, areas of “reproductive longevity” exist, where a higher-than-average incidence of late maternities combines with a lower-than-average cost in terms of perinatal death. Data from the Italian Central Institute of Statistics regard all 1980–1996 Sardinian births. Using spatial analysis of late maternity (proportion of babies born to mothers aged ≥35 years) and associated perinatal mortality (proportion of babies stillborn and dead within 0–6 days born to mothers aged ≥35 years), we aimed at singling out areas where the indicators run high and low, respectively. The perinatal mortality cost associated with the advanced maternal age [odds ratios (95% CI)] was evaluated through multiple logistic regression models. We identified central inland excess areas qualified by higher incidence of late maternities (27% vs. 22% in nonexcess area) and lower cost in perinatal mortality [OR=1.38 (1.04–1.84) vs. OR=1.74 (1.55–1.96) in nonexcess area]. In these “reproductive longevity” areas, the inbreeding coefficient was 3.7-fold higher than in the nonexcess areas, suggesting possible population homozygosity in genetic factors affecting the trait. Further and deeper investigations on biological and environmental determinants could focus on these target areas.     

Post-dispersal seed fates of four prairie species

After dispersal, seeds can germinate and establish as seedlings, persist as seeds, or die. Knowledge of these three seed fates is crucial for understanding the abundance and distribution of plant populations and ultimately, community composition and diversity. Few studies, however, have simultaneously measured these fates, while also examining the factors causing mortality. The goal of this research was to simultaneously quantify the three seed fates and factors causing death (predation and fungal disease) for four species found in prairies in western Oregon, USA. The most common seed fate for the four study species was death (44-80%). Fungal disease, which has seldom been quantified in natural ecosystems, generally caused less than 10% mortality for each of the four species. Vertebrate predation substantially reduced seed numbers only for Bromus carinatus (21%). Of the unmeasured mortality factors, indirect evidence showed invertebrate predation was a cause of death for seeds of only one species, Prunella vulgaris. In addition, competitive pressures caused seedling death for only the two grass species, Bromus carinatus and Cynosurus echinatus. Survival as established seedlings was generally much more common than survival as persistent seed, with the exception of Daucus carota, in which 14% of the sown seeds persisted the first year.     

Environmental determinants of recruitment and their influence on the population dynamics of stream-living brown trout Salmo trutta

The relative importance of endogenous feedback mechanism vs environmental factors in the dynamics of animal populations is a long-standing, but not fully resolved yet, issue in ecology. We have addressed this subject by examining the dynamics of a stream-resident population of Salmo trutta in a northwestern Spain stream. Recruitment was the major determinant of population size and the abundance of recruits resulted from a combination of regional and local environmental factors. Stream discharge in March determined the amount of stream area suitable for newly emerged trout (r²=0.59–0.79%), that in turn determined the abundance of recruits at each site (r²=0.51–0.77%). Stream discharge determines the overall strength of annual recruitment. Discharge, however, combines with stream morphology at the site scale to result in a site-specific area suitable for juveniles and, hence, site-specific recruitment. Thus, our study exemplifies how an environmentally driven animal population may persist on time with little or no operation of endogenous regulatory mechanisms.