The eight main blood types are A+, A-, B+, B-, O+, O-, AB+, and AB-. The most common blood type in the United States is O-positive, with around 38 percent of the population having this type of blood. However, blood type O-positive is more common in Latino-Americans than other ethnicities, with around 53 percent of Latino-Americans with this blood type, compared to 47 percent of African Americans and 37 percent of Caucasians. Blood donation The American Red Cross estimates that every two seconds someone in the United States needs blood or platelets, highlighting the importance of blood donation. It was estimated that in 2021, around 6.5 million people in the U.S. donated blood, with around 1.7 million of these people donating for the first time. Those with blood type O-negative are universal blood donors, meaning their blood can be transfused for any blood type. Therefore, this blood type is the most requested by hospitals. However, only about seven percent of the U.S. population has this blood type. Blood transfusion Blood transfusion is a routine procedure that involves adding donated blood to a patient’s body. There are many reasons why a patient may need a blood transfusion, including surgery, cancer treatment, severe injury, or chronic illness. In 2021, there were around 10.76 million blood transfusions in the United States. Most blood transfusions in the United States occur in an inpatient medicine setting, while critical care accounts for the second highest number of transfusions.

Basque Rh project data

Means (± SEM) within a column followed by different letters are significantly different (P

This statistic illustrates the distribution of blood groups in the French population, according to the Rhesus system. It shows that less than *** percent of French people had the blood group AB negative.

The strength and direction of density-dependent mechanisms acting on individual reproduction and survival may vary across the nested levels of organization social animals live in, such that complex patterns of density dependence shape fitness and population growth. Yet knowledge of such processes of population regulation where individuals are simultaneously subjected to contrasting density effects remains limited. We quantify and contrast density effects on components of individual fitness across two nested levels of organization: the population and the social group, using 45 years of demographic data of rhesus macaques. Our analysis reveals opposing density feedback on individual reproduction and survival across levels of organization and shows that density does not affect all life stages equally. While increased population density reduced female reproduction during maturation, females in larger groups were more likely to reproduce. Infant survival was optimal at intermediate population densities, and monkeys in larger groups showed increased survival. Our work shows that population-level density effects on individual reproduction and survival can be as strong as group-level effects and suggests different roles of the philopatric (i.e. females) and dispersing (i.e. males) sexes on the regulation of individual demographic performance. In this way, our work posits testable mechanistic hypotheses for evaluating density effects on components of individual fitness and highlights the need to explicitly consider the organization and demographic structure of social animals when quantifying individual performance and population dynamics.

CDD_Ophraella_communaCalculation of cumulative degree days that Ophraella communa needs to conclude one generation.Hatching_success_Ophraella_communaData from a laboratory experiment to deduce relative humidity dependent egg mortality of Ophraella communaCombine_SDM_and_vital_ratesR script which shows how we combined a species distribution model with vital rates

Insects Two different populations of Prostephanus truncatus were used in the bioassays, one originated from the invaded range in Ghana, and the other from the native range in Mexico. Both populations were maintained in the Laboratory of Entomology and Agricultural Zoology (LEAZ), at the Department of Agriculture, Crop Production and Rural Environment, University of Thessaly, Greece, on whole maize kernels, at 26°C and 55% relative humidity (RH) and continuous darkness. European Maize Hybrids Three different maize hybrids (“PICO”, “HAMILTON”, and “AGN 672”) were obtained from American Genetics SA, Sindos, Greece. All hybrids were cultivated at Serres, in northern Greece according to the local farming practices. The hybrid “PICO” has a great production potential and it is adapted to multiple soil types and can produce high-weight grain. The hybrid “HAMILTON” is a dual-purpose hybrid, that has excellent early vigor and it is tolerant to fungi, and the hybrid “AGN 672” has excellent early vigor and it is also tolerant to fungi. Population Growth on Different Maize Hybrids Three different maize hybrids (PICO, Hamilton, and AGN 672) were used for experimentation. These hybrids were untreated and uninfested, and kept at ambient conditions until the beginning of the experiments. Before proceeding with the bioassays, grain moisture content (M.C.) was assessed, using a moisture meter (mini-GAC plus, Dickey-John Europe S.A.S., Colombes, France). Standardized plastic vials as in prior work (Quellhorst et al. 2023; Lampiri et al. 2022) were used here (3 cm in diameter, 8 cm in height). Vials were then filled with 20 g of one of the three maize hybrids with lids added after. The commodity was weighed with a Precisa XB3200D compact balance (Alpha Analytical Instruments, Gerakas, Greece). The upper rings of the vials were treated with Fluon (Northern Products Inc., Woonsocket, USA) to prevent insects from moving away from the grain and/or escaping. The top of each vial also had small holes punched to allow ventilation. Each vial then received 10 P. truncatus adults of mixed sex and age from one of two different strains. Two different populations of P. truncatus were used as mentioned above. The vials were placed inside incubators set at 30°C and 65% R.H. in continuous darkness. The vials were removed from the incubators after 45 d and adult progeny production was recorded. We also recorded the weight of frass, the number of insect-damaged kernels (IDK), and the total weight of the kernels within each vial. For each combination, i.e. hybrid × strain, there were n = 9 replicates.

Means (±SEM) within a column followed by different letters are significantly different (P

The most common blood type among the population in the United States is O-positive. Around 53 percent of the Latino-American population in the U.S. has blood type O-positive, while only around 37 percent of the Caucasian population has this blood type. The second most common blood type in the United States is A-positive. Around 33 percent of the Caucasian population in the United States has A-positive blood type. Blood type O-negative Those with blood type O-negative are universal donors as this type of blood can be used in transfusions for any blood type. O-negative blood type is most common in the U.S. among Caucasian adults. Around eight percent of the Caucasian population has type O-negative blood, while only around one percent of the Asian population has this blood type. Only around seven percent of all adults in the United States have O-negative blood type. Blood Donations The American Red Cross estimates that someone in the United States needs blood every two seconds. However, only around three percent of age-eligible people donate blood yearly. The percentage of adults who donated blood in the United States has not fluctuated much for the past two decades. In 2021, around 15 percent of U.S. adults donated blood, the same share reported in the year 2003.

Rates of confirmed COVID-19 in Ottawa Wards, excluding LTC and RH cases, and number of cases in LTCH and RH in Ottawa Wards. Data are provided for all cases (i.e. cumulative), cases reported within 30 days of the data pull (i.e. last 30 days), and cases reported within 14 days of the data pull (i.e. last 14 days). Based on the most up to date information available at 2pm from the COVID-19 Ottawa Database (The COD) on the day prior to publication.Rates of confirmed COVID-19 in Ottawa Wards, excluding LTC and RH cases, and number of cases in LTCH and RH in Ottawa Wards. Data are provided for all cases (i.e. cumulative), cases reported within 30 days of the data pull (i.e. last 30 days), and cases reported within 14 days of the data pull (i.e. last 14 days). Based on the most up to date information available at 2pm from the COVID-19 Ottawa Database (The COD) on the day prior to publication. You can see the map on Ottawa Public Health's website.Accuracy: Points of consideration for interpretation of the data:Data extracted by Ottawa Public Health at 2pm from the COVID-19 Ottawa Database (The COD) on May 12th, 2020. The COD is a dynamic disease reporting system that allow for continuous updates of case information. These data are a snapshot in time, reflect the most accurate information that OPH has at the time of reporting, and the numbers may differ from other sources. Cases are assigned to Ward geography based on their postal code and Statistics’ Canada’s enhanced postal code conversion file (PCCF+) released in January 2020. Most postal codes have multiple geographic coordinates linked to them. Thus, when available, postal codes were attributed to a XY coordinates based on the Single Link Identifier provided by Statistics’ Canada’s PCCF+. Otherwise, postal codes that fall within the municipal boundaries but whose SLI doesn’t, were attributed to the first XY coordinates within Ottawa listed in the PCCF+. For this reason, results for rural areas should be interpreted with caution as attribution to XY coordinates is less likely to be based on an SLI and rural postal codes typically encompass a much greater surface area than urban postal codes (e.i. greater variability in geographic attribution, less precision in geographic attribution). Population estimates are based on the 2016 Census. Rates calculated from very low case numbers are unstable and should be interpreted with caution. Low case counts have very wide 95% confidence intervals, which are the lower and upper limit within which the true rate lies 95% of the time. A narrow confidence interval leads to a more precise estimate and a wider confidence interval leads to a less precise estimate. In other words, rates calculated from very low case numbers fluctuate so much that we cannot use them to compare different areas or make predictions over time.Update Frequency: Biweekly Attributes:Ward Number – numberWard Name – textCumulative rate (per 100 000 population), excluding cases linked to outbreaks in LTCH and RH – cumulative number of residents with confirmed COVID-19 in a Ward, excluding those linked to outbreaks in LTCH and RH, divided by the total population of that WardCumulative number of cases, excluding cases linked to outbreaks in LTCH and RH - cumulative number of residents with confirmed COVID-19 in a Ward, excluding cases linked to outbreaks in LTCH and RHCumulative number of cases linked to outbreaks in LTCH and RH - Number of residents with confirmed COVID-19 linked to an outbreak in a long-term care home or retirement home by WardRate (per 100 000 population) in the last 30 days, excluding cases linked to outbreaks in LTCH and RH –number of residents with confirmed COVID-19 in a Ward reported in the 30 days prior to the data pull, excluding those linked to outbreaks in LTCH and RH, divided by the total population of that WardNumber of cases in the last 30 days, excluding cases linked to outbreaks in LTCH and RH - cumulative number of residents with confirmed COVID-19 in a Ward reported in the 30 days prior to the data pull, excluding cases linked to outbreaks in LTCH and RHNumber of cases in the last 30 days linked to outbreaks in LTCH and RH - Number of residents with confirmed COVID-19, reported in the 30 days prior to the data pull, linked to an outbreak in a long-term care home or retirement home by WardRate (per 100 000 population) in the last 14 days, excluding cases linked to outbreaks in LTCH and RH –number of residents with confirmed COVID-19 in a Ward reported in the 30 days prior to the data pull, excluding those linked to outbreaks in LTCH and RH, divided by the total population of that WardNumber of cases in the last 14 days, excluding cases linked to outbreaks in LTCH and RH - cumulative number of residents with confirmed COVID-19 in a Ward reported in the 30 days prior to the data pull, excluding cases linked to outbreaks in LTCH and RHContact: OPH Epidemiology Team

From 1995, the General Household Survey (GHS) is conducted in between 2 Population Censuses as a mid-decade mini-Census.

The General Household Survey (GHS) 2015 is the third in the series of mid-decade national survey. It covers a wide range of topics and provides comprehensive data on Singapore’s population and households in between the population censuses that are conducted once in ten years.

Cumulative and monthly counts and rates of confirmed COVID-19 in Ottawa neighbourhoods, excluding cases linked to outbreaks in long-term care homes (LTCH) and retirement homes (RH). Based on the most up to date information available at 2pm from the COVID-19 Ottawa Database (The COD) on the day the data is pulled to provide the monthly update.

Accuracy: Points of consideration for interpretation of the data:

• Data extracted by Ottawa Public Health at 2pm from the COVID-19 Ottawa Database (The COD) the day prior to publication. The COD is a dynamic disease reporting system that allow for continuous updates of case information. These data are a snapshot in time, reflect the most accurate information that OPH has at the time of reporting, and the numbers may differ from other sources.

• A case (an individual with laboratory-confirmed COVID-19 infection) is assigned to an Ottawa Neighbourhood Study (ONS) geography based on the individual’s residential postal code and the ONS’s postal code conversion file. As the area served by a given postal code may cross multiple neighbourhoods, the ONS postal code conversion file identifies the proportion of each postal code that falls within a neighbourhood. Thus, for cases with postal codes falling within multiple neighbourhoods, a fraction of those cases will be assigned to each neighbourhood.

• Rates calculated from very low case numbers or for neighbourhoods with very small populations are unstable and should be interpreted with caution. Low case counts have very wide 95% confidence intervals, which are the lower and upper limit within which the true rate lies 95% of the time. A narrow confidence interval leads to a more precise estimate and a wider confidence interval leads to a less precise estimate. In other words, rates calculated from very low case numbers fluctuate so much that we cannot use them to compare different areas or make predictions over time.

Update Frequency: Monthly

Attributes: Data fields

• ONS Neighbourhood – text • Cumulative rate (per 100 000 population), excluding cases linked to outbreaks in LTCH and RH – cumulative number of residents with confirmed COVID-19 in a neighbourhood, excluding those linked to outbreaks in LTCH and RH, divided by the total population of that neighbourhood • Cumulative number of cases, excluding cases linked to outbreaks in LTCH and RH - cumulative number of residents with confirmed COVID-19 in a neighbourhood, excluding cases linked to outbreaks in LTCH and RH • Monthly rates (per 100 000 population), excluding cases linked to outbreaks in LTCH and RH –number of residents with confirmed COVID-19 in a neighbourhood reported to OPH during the month of interest, excluding those linked to outbreaks in LTCH and RH, divided by the total population of that neighbourhood. • Monthly number of cases reported, excluding cases linked to outbreaks in LTCH and RH - number of residents with confirmed COVID-19 in a neighbourhood reported to OPH during the month of interest, excluding cases linked to outbreaks in LTCH and RH.

Contact: OPH Epidemiology Team & Ottawa Neighbourhood Study Team | Epidemiology & Evidence, Ottawa Public Health

Raw data for the paper "Effects of Rh negativity on wellbeing, health, fecundity, sexual desire, and sexual activity – a cross-sectional study performed on a cohort of 5,527 Czech and Slovak representatives of the internet population" by Jaroslav FlegrAbstract

Since its discovery in the 1930s, the effects of Rh phenotype on human health and wellbeing, with the exception of the effects of Rh-negativity of a mother on the risk of hemolytic anemia of Rh-positive children, has only rarely been studied. In the last few years, however, several studies have shown that Rh-negative subjects have worse health and performance in certain tests than their Rh-positive peers. Nothing is known about the effect of Rh phenotype on the quality of life of subjects as measured by a standard instrument. I hereby analyzed the data of 1768 male (24% Rh-negative) and 3759 female participants (23% Rh-negative) of an anonymous internet study using the partial Kendall test with the age and the population of the hometown of subjects controlled. The results showed that the Rh-negative women, but not men, scored worse in wellbeing measured with the WHO-BREFF. Both the Rh-negative men and women scored worse in mental health-related variables and in their reported economic situation. Additionally, the Rh-negative women scored worse in physical health-related variables. Both the Rh-negative men and women reported higher sexual activity than their Rh-positive peers. The effects of the Rh phenotype were significant after the correction for multiple tests. However, they were usually weaker and less numerous than those of smoking, consuming alcohol, and high body mass index, which were used as a sort of internal control.

Background: Rhesus macaques living in western Sichuan, China, have been separated into several isolated populations due to habitat fragmentation. Previous studies based on the neutral or nearly neutral markers (mitochondrial DNA or microsatellites) showed high levels of genetic diversity and moderate genetic differentiation in the Sichuan rhesus macaques. Variation at the major histocompatibility complex (MHC) loci is widely accepted as being maintained by balancing selection, even with a low level of neutral variability in some species. However, in small and isolated or bottlenecked populations, balancing selection may be overwhelmed by genetic drift. To estimate microevolutionary forces acting on the isolated rhesus macaque populations, we examined genetic variation at MHC-DQB1 loci in 119 wild rhesus macaques from five geographically isolated populations in western Sichuan, China, and compared the levels of MHC variation and differentiation among populations with that previously observed at neutral microsatellite markers. Results: 23 Mamu-DQB1 alleles were identified in 119 rhesus macaques in western Sichuan, China. These macaques exhibited relatively high levels of genetic diversity at Mamu-DQB1. The Hanyuan population presented the highest genetic variation, whereas the Heishui population was the lowest. Analysis of molecular variance (AMOVA) and pairwise FST values showed moderate genetic differentiation occurring among the five populations at the MHC-DQB1 locus. Non-synonymous substitutions occurred at a higher frequency than synonymous substitutions in the peptide binding region. Levels of MHC variation within rhesus macaque populations are concordant with microsatellite variation. On the phylogenetic tree for the rhesus and crab-eating macaques, extensive allele or allelic lineage sharing is observed between the two species. Conclusions: Phylogenetic analyses confirm the apparent trans-species model of evolution of the MHC-DQB1 genes in these macaques. Balancing selection plays an important role in sharing allelic lineages between species, but genetic drift may share balancing selection dominance to maintain MHC diversity. Great divergence at neutral or adaptive markers showed that moderate genetic differentiation had occurred in rhesus macaque populations in western Sichuan, China, due to the habitat fragmentation caused by long-term geographic barriers and human activity. The Heishui population should be paid more attention for its lowest level of genetic diversity and relatively great divergence from others.

Abstract

The survey was specifically designed to meet the following objectives: -to assess the current situation in Moldova concerning fertility, abortion, contraception and various other reproductive health issues; -to enable policy makers, program managers, and researchers to evaluate and improve existing programs and to develop new strategies; -to measure changes in fertility and contraceptive prevalence rates and study factors that affect these changes, such as geographic and socio-demographic factors, breast-feeding patterns, use of induced abortion, and availability of family planning; -to provide data necessary to develop sex education and health promotion programs; -to obtain data on knowledge, attitudes, and behavior of young adults 15-24 years of age; -to provide information on the level of knowledge about AIDS transmission and prevention; -to identify and focus further reproductive health studies toward high risk groups.

The survey provides data that will assist the Moldovan Government in improving services related to the health of women and children and was proposed in conjunction with the UNFPAsponsored reproductive health (RH) activities in Moldova, which consist of several components intended to increase the use of effective contraception, reduce the reliance on induced abortion as a means of fertility control, and, more generally, to improve RH. Specific projects supported by UNFPA in Moldova include ongoing support to the Government for developing a national RH plan, provisions of contraceptives, and training of family planning providers. In addition, the national RH plan is receiving support from USAID (family planning logistics management, information/ education/communication activities), IPPF (provision of contraceptives), and UNICEF.

Geographic coverage

The 1997 MRHS was designed to collect information from a representative sample of women of reproductive age throughout Moldova.

Universe

The universe from which the respondents were selected included all females between the ages of 15 and 44, regardless of marital status, who were living in Moldova when the survey was carried out.

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey employed a three-stage probability sample design and successfully interviewed 5,412 (98%) of 5,543 women identified in sample households as eligible for interview.

The survey employed a three-stage sampling design using two sampling frames (one for urban areas and one for rural areas) provided by the MSDS. The urban sampling frame was based on the 1989 census, whereas the rural sampling frame consisted of a list of the 1,607 villages in the country, recently updated for household composition in January-April 1997 for an agricultural registry.

In the first stage, 128 census sectors in urban areas and 122 villages were selected as Primary Sampling Units (PSUs) with probability proportional to the number of households in each census sector/village. In the second stage of sampling, clusters of households were randomly selected in each census sector/village chosen in the first stage. Before second-stage selection in urban areas, the Census Division of the MSDS redefined each 1989 census sector selected as a PSU for street boundaries, converted the maps and listings from Russian to Moldavian, and updated the sector's household composition in collaboration with personnel from the local health care units. A cluster of households was randomly selected from the updated sector lists of the PSUs in urban areas and from the household listings in the villages selected as PSUs in the first stage. (Since there were roughly equal numbers of urban and rural households, the sample was designed to be geographically self-weighting.) In each sample strata, urban and rural, the third stage consisted of the random selection of one woman if there were two or more eligible women (aged 15-44 years) living in the same household.

Cluster size determination was based on the number of households required to obtain an average of 20 interviews per cluster. The total number of households in each cluster took into account estimates of unoccupied households, average number of women 15-44 per household, the interview of only one woman per household, and an estimated response rate of 90% in urban areas and 92% in rural areas. In urban areas, the cluster size with a yield of 20 interviews, on average, was determined to be 45 households. In rural areas, because the average number of women 15-44 per household varies considerably by raion, the average number of households needed to obtain 20 complete interviews varied from 42 to 60.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was first drafted by CDC/DRH consultants based on a core questionnaire used in the 1993 Romanian Reproductive Health Survey. This core questionnaire was reviewed and modified by Moldovan experts in reproductive health and family planning, as well as by USAID and UNFPA. Based on these reviews, a pretest questionnaire was developed and field-tested in April 1997. The questionnaire, developed in Romanian, was translated into Russian after the pretest. All interviewers spoke these two languages.

The questionnaire had two components: (1) A short household questionnaire used to collect residential and geographic information, select information about all women of childbearing age living in sampled households, and information on interview status. This module was also used to randomly select one respondent when there was more than one eligible woman in the household; (2) The longer individual questionnaire collected information on the topics mentioned above.

The major reproductive health topics on which information was collected were: pregnancies and childbearing (a complete history of all pregnancies, including planning status of pregnancies in the last five years, a detailed history of abortions within the last five years, including postabortion counseling, and the history of all births within the last five years, including the patterns of utilization of health services during pregnancy, maternal morbidity, infant health and breast-feeding); family planning (knowledge and history of use of methods of preventing pregnancy, current use of contraception, source of contraception, reasons for not using, reasons for use of less effective methods of contraception, future fertility preferences and intentions to use voluntary sterilization); women's health (health behavior and use of women's health services, tobacco and alcohol use); reproductive health knowledge and attitudes (especially regarding birth control pills, condoms, and IUDs); knowledge about HIV/AIDS transmission and prevention; domestic violence, including violence during the most recent pregnancy; history of sexual abuse; and socioeconomic characteristics of women and their husbands/families. The young women (15-24 years of age) were asked additional questions on sex education, age and contraceptive use at first sexual intercourse, and sexual behaviors.

Most issues have been examined by geographic, demographic, and socio-economic characteristics, making it possible to identify the segments of the population with specific health needs or problems.

Response rate

Of the 11,506 households selected, 5,543 were found to include at least one 15-44 year-old woman. Of these women, 5,412 were successfully interviewed, for a response rate of 97.6%. Less than one percent of selected women refused to be interviewed, while another 1.3% could not be located. Response rates were slightly better in rural areas (98%) than in municipalities and other urban areas (97%). In Chisinau (not shown), the response rate was 96%; nearly 3% of women selected in the sample could not be located.

Data appraisal

The geographic distribution of the sample, by residence and region, is very close to official figures of the population distribution for 1996, estimated by the Moldovan State Department for Statistics.

The percent distribution of women in the sample by five-year age groups is compared with the 1994 official estimates (the most recent estimates by age group) in Table 2.3. Compared with these estimates, the survey sample has slightly over-represented adolescent women (15-19 yearolds) and under-represented women aged 40-44 by about two percentage points. However, several factors may have contributed to the differences observed: first, there is a three-year difference between the time the official estimates were calculated and the survey was implemented; second, the official estimates are projections of the age composition recorded by the 1989 census and thus dependent on assumptions used in projecting the aging of a cohort; finally, official estimates include any possible age misreporting that occured in the census.

Study History: The purpose of this study was to characterize the basic ecology, distribution, and demographics of sand lance in lower Cook Inlet. Recent declines of upper trophic level species in the northern Gulf of Alaska have been linked to decreasing availability of forage fishes. Sand lance is the most important forage fish in most nearshore areas of the northern Gulf. Despite its importance to commercial fish, seabirds, and marine mammals, little is known or published on the basic biology of this key prey species. Therefore, restoration project /306 was established to work in coordination with restoration APEX project /163M to help characterize the relationship between seabird population dynamics and forage fish abundance.

Abstract: Distinct sand lance populations occur within the relatively small geographic area of Lower Cook Inlet, Alaska. Marked meso-scale differences in abundance, growth, and mortality exist as a consequence of differing oceanographic regimes. Growth rate within populations (between years) was positively correlated with temperature. However, this did not extend to inter-population comparisons where differing growth rates were better correlated to marine productivity. Most sand lance reached maturity in their second year. Field observations and indices of maturity, gonad development, and ova-size distribution all indicated that sand lance spawn once each year. Sand lance spawned intertidally in late September and October on fine gravel/sandy beaches. Embryos developed over 67 days through periods of intertidal exposure and sub-freezing air temperatures. Mean dry-weight energy value of sand lance cycles seasonally, peaking in spring and early summer, and subsequently declining by about 25% during late summer and fall. Sand lance enter the winter with close to their minimum whole body energy content.

Publications: Robards, M.D. and J.F. Piatt. 2000. Ecology and demographics of Pacific Sand Lance, Ammodytes hexapterus Pallas, in lower Cook Inlet, Alaska. Exxon Valdez Oil Spill Restoration Project Final Report (Restoration Project 99306), U.S. Geological Survey, Alaska Science Center, Anchorage, Alaska.

Robards, M.D., J.F. Piatt, and G.A. Rose. 1999. Maturation, Fecundity, and Intertidal Spawning of Pacific Sand Lance (Ammodytes hexapterus) in the Northern Gulf of Alaska. Journal of Fish Biology 54: 1050-1068.

Robards, M.D., J.A. Anthony, G.A. Rose, and J.F. Piatt. 1999. Changes in proximate composition and somatic energy content for Pacific sand lance (Ammodytes hexapterus) relative to maturity, season, and location. Journal of Experimental Marine Biology and Ecology 242: 245-258.

Robards, M.D. G.A. Rose, and J.F. Piatt. 1999. Somatic growth and otolith development of Pacific sand lance (Ammodytes hexapterus) under different oceanographic regimes. (Submitted to Fisheries Oceanography).

Robards, M.R., J.F. Piatt, A.B. Kettle, and A.A. Abookire. 1999. Temporal and geographic variation in fish communities of Lower Cook Inlet, Alaska. Fishery Bulletin 97, 962-977.

Robards, M.R., M.F. Willson, R.H. Armstrong, and J.F. Piatt. 1999. Sand Lance: A Review of Biology and Predator Relations and Annotated Bibliography. U.S. Forest Service, Pacific Northwest Research Station, Research Paper PNW-RP 521, September, 1999.

Robards, M.D. and J.F. Piatt. 1999. Biology of the Genus Ammodytes – The Sand Lances. In: Robards, M.R., M.F. Willson, R.H. Armstrong, and J.F. Piatt (editors). Sand Lance: A Review of Biology and Predator Relations and Annotated Bibliography. U.S. Forest Service, Pacific Northwest Research Station, Research Paper PNW-RP 521, September, 1999.

Willson, M.F., R.H. Armstrong, M.D. Robards, and J.F. Piatt. 1999. Sand lance as cornerstone species for predator populations. In: Robards, M.R., M.F. Willson, R.H. Armstrong, and J.F. Piatt (editors). Sand Lance: A Review of Biology and Predator Relations and Annotated Bibliography. U.S. Forest Service, Pacific Northwest Research Station, Research Paper PNW-RP 521, September, 1999.

Willson, M.F., R.H. Armstrong, M.D. Robards, and J.F. Piatt. 1999. An annotated bibliography of sand lance. In: Robards M.R., M.F. Willson, R.H. Armstrong, and J.F. Piatt (editors). Sand Lance: A Review of Biology and Predator Relations and Annotated Bibliography. U.S. Forest Service, Pacific Northwest Research Station, Research Paper PNW-RP 521, September, 1999.

Tento datový soubor prezentuje údaje o domácnostech a rodinách (Eidgenössische Census 2000)

Number of animals (N), average genomic relationship (Ø gRel), average observed heterozygosity (Ho) and most recent effective population size (Ne5Gen) for Angler (RVA), Red-and-White dual-purpose (RDN) and Red Holstein (RH).

Inbreeding exposes deleterious recessive alleles in homozygotes, lowering fitness and generating inbreeding depression (ID). Both purging (via selection) and fixation (via drift) should reduce segregating deleterious mutations and ID in more inbred populations. These theoretical predictions are not well-tested in wild populations, which is concerning given purging/fixation have opposite fitness outcomes. We examined how individual- and population-level inbreeding and genomic heterozygosity affected maternal and progeny fitness within and among 12 wild populations of Impatiens capensis. We quantified maternal fitness in home sites, maternal multilocus heterozygosity (using 12,560 SNPs), and lifetime fitness of selfed and predominantly outcrossed progeny in a common garden. These populations spanned a broad range of individual- (fi = -0.17–0.98) and population-level inbreeding (FIS = 0.25–0.87). More inbred populations contained fewer polymorphic loci, less fecund mothers, and smaller pro..., We measured the reproductive output (a component of fitness) of Impatiens capensis plants in each of 12 home field sites (N = 808 individuals). These field sites occurred in fragmented floodplain forests and marches surrounded by an urban/agricultural matrix in Wisconsin, USA. We define reproductive output as the number of cleistogamous and chasmogamous structures on each plant during peak flower (binned into buds, open flowers, and seed capsules and bare pedicles). We also measured the height of each plant. We collected cleistogamous and chasmogamous seeds (N = 6,859) from as many of these mother plants as possible (N = 718 maternal plants with seeds collected). We germinated the seeds in a greenhouse, transplanted the seedlings into a common garden, and measured lifetime fitness (total number of ripe seed capsules produced) of each progeny (N = 2,260) in the common garden. A subset of the maternal plants (N = 296) were genotyped for a previous study (Toczydlowski and Waller, 2019, Mol..., This data package includes the files needed to reproduce the analyses for the paper: Toczydlowski, R. H., and Waller, D. M. 2023. Failure to purge: Population and individual inbreeding effects on fitness across generations of wild Impatiens capensis. Evolution, under review. More detailed methods are available in the README for this data package and in the associated scientific paper. A dynamic version of this data package is also housed in a git repository on BitBucket at:https://bitbucket.org/toczydlowski/inbreeding_effects_in_impatiens