HDP_survey.csv and HDP_plots.csv *** ## Associated Data Paper The complete metadata for these data sets, including detailed descriptions of why and how the data were collected and validated, are in the following Data Paper: Bruna,E.M., M.Uriarte, M.Rosa Darrigo, P.Rubim, C.F.Jurinitz, E.R.Scott, O.Ferreira da Silva, & W.John Kress. 2023. Demography of the understory herb Heliconia acuminata (Heliconiaceae) in an experimentally fragmented tropical landscape. Ecology. ## Overview This file comprises 11 years (1998-2009) of demographic data from populations of the Amazonian understory herb Heliconia acuminata (LC Rich.) found at Brazil's Biological Dynamics of Forest Fragments Project (BDFFP). The dataset comprises >66,000 plant x year records of 8586 plants, including 3464 seedlings established after the first census. Seven populations were in experimentally isolated fragments (one in each of four 1-ha fragments and one in each of three 10-ha fragments), with the remaining six populations in continuous forest. Each population was in a 50xx 100 m permanent plot, with the distance between plots ranging from 500 m-60 km. The plants in each plot were censused annually, at which time we recorded, identified, marked, and measured new seedlings, identified any previously marked plants that died, and recorded the size of surviving individuals. Each plot was also surveyed 4-5 times during the flowering season to identify reproductive plants and record the number of inflorescences each produced. This data set describes the demographic plots in which surveys were conducted (HDP_plots.csv) and the demographic survey data (HDP_survey.csv). ## Description of the data and file structure: HDP_survey.csv * Format and storage mode: ASCII text, comma delimited. No compression scheme used. * Header information: The first row of the file contains the variable names. * Variables: -- plot_id: Plot in which plant is located (values: FF1-FF7\, CF1-CF6) -- subplot: Subplot in which plant is located (values: A1-E10 except in CF3\, where F6-J101) -- plant_id: Unique ID no. assigned to plant (values: range = 1-8660\, units: number\, precision: 1) -- tag_number: Number on tag attached to plant (values: range = 1-3751\, units: number\, precision: 1) -- year: Calendar year of survey (values: range = 1998-2009\, units: year\, precision: 1)) -- shts: No. of shoots when surveyed (values: range = 0-24\, units: shoots\, precision: 1\, NA: data missing) -- ht: Plant height when surveyed (values: range = 0-226\, units: cm\, precision: 1\, NA: data missing) -- infl: No. of inflorescences (if flowering) (values: range = 1-7\, units: shoots\, precision: 1\, NA: data missing) -- recorded_sdlg: New seedling (values: TRUE\, FALSE) -- adult_no_tag: Established (i.e.\, post-seedling) individual without tag (values: TRUE\, FALSE) -- treefall_status: Plant found under fallen tree crown\, branches\, or leaf litter at time of survey (values: branch = under fallen tree limbs tree = under tree crown or fallen trees litter = under accumulated leaf-litter NA = not relevant or no observation recorded) -- census_status: Plant status in a census (values: measured = alive\, measured dead = died prior to census missing = not found during census) ## Description of the data and file structure: HDP_plots.csv * Format and storage mode: ASCII text, comma delimited. No compression scheme used. * Header information: The first row of the file contains the variable names. * Variables: -- plot_id: Code used to identify a plot (Values: FF1-FF7 = plots in fragments\, CF1-CF6 = plots in continuous forest) -- habitat: Habitat in which a plot is located (Values: one = 1-ha fragment\, ten = 10-ha fragment\, forest = continuous forest) -- ranch: Ranch in which a plot is located (Values: porto alegre\, esteio\, dimona) -- bdffp_no: BDFFPs Reserve ID Number (Values: 1104\, 1202\, 1301\, 1501\, 2107\, 2108\, 2206\, 3209\, 3402\, NA) -- yr_isolated: for fragments\, the year they were initially isolated by felling (and in some cases burning) the trees surrounding them ## Describe relationships between data files, missing data codes, other abbreviations used. Be as descriptive as possible. * Missing values are represented with NA. ## Sharing/Access information * Though we welcome opportunities to collaborate with interested users, there are no restrictions on the use this data set. However, we do request that those using the data for teaching or research inform us of how they are doing so and cite the Bruna et al. Data Paper in Ecology and this Dryad archive. * Any publication using the data must include a BDFFP Technical Series Number in the Acknowledgments. Authors can request this series number upon the acceptance of their article by contacting the BDFFP's Scientific Coordinator or E. M. Bruna....

Approximately 25% of mammals are currently threatened with extinction, a risk that is amplified under climate change. Species persistence under climate change is determined by the combined effects of climatic factors on multiple demographic rates (survival, development, reproduction), and hence, population dynamics. Thus, to quantify which species and regions on Earth are most vulnerable to climate-driven extinction, a global understanding of how different demographic rates respond to climate is urgently needed. Here, we perform a systematic review of literature on demographic responses to climate, focusing on terrestrial mammals, for which extensive demographic data are available. To assess the full spectrum of responses, we synthesize information from studies that quantitatively link climate to multiple demographic rates. We find only 106 such studies, corresponding to 87 mammal species. These 87 species constitute < 1% of all terrestrial mammals. Our synthesis reveals a strong mismatch between the locations of demographic studies and the regions and taxa currently recognized as most vulnerable to climate change. Surprisingly, for most mammals and regions sensitive to climate change, holistic demographic responses to climate remain unknown. At the same time, we reveal that filling this knowledge gap is critical as the effects of climate change will operate via complex demographic mechanisms: a vast majority of mammal populations display projected increases in some demographic rates but declines in others, often depending on the specific environmental context, complicating simple projections of population fates. Assessments of population viability under climate change are in critical need to gather data that account for multiple demographic responses, and coordinated actions to assess demography holistically should be prioritized for mammals and other taxa.

Methods For each mammal species i with available life-history information, we searched SCOPUS for studies (published before 2018) where the title, abstract, or keywords contained the following search terms:

Scientific species namei AND (demograph* OR population OR life-history OR "life history" OR model) AND (climat* OR precipitation OR rain* OR temperature OR weather) AND (surv* OR reprod* OR recruit* OR brood OR breed* OR mass OR weight OR size OR grow* OR offspring OR litter OR lambda OR birth OR mortality OR body OR hatch* OR fledg* OR productiv* OR age OR inherit* OR sex OR nest* OR fecund* OR progression OR pregnan* OR newborn OR longevity).

We used the R package taxize (Chamberlain and Szöcs 2013) to resolve discrepancies in scientific names or taxonomic identifiers and, where applicable, searched SCOPUS using all scientific names associated with a species in the Integrated Taxonomic Information System (ITIS; http://www.itis.gov).

We did not extract information on demographic-rate-climate relationships if:

A study reported on single age or stage-specific demographic rates (e.g., Albon et al. 2002; Rézoiki et al. 2016)
A study used an experimental design to link demographic rates to climate variation (e.g., Cain et al. 2008)
A study considered the effects of climate only indirectly or qualitatively. In most cases, this occurred when demographic rates differed between seasons (e.g., dry vs. wet season) but were not linked explicitly to climatic factors (e.g., varying precipitation amount between seasons) driving these differences (e.g., de Silva et al. 2013; Gaillard et al. 2013).

We included several studies of the same population as different studies assessed different climatic variables or demographic rates or spanned different years (e.g., for Rangifer tarandus platyrhynchus, Albon et al. 2017; Douhard et al. 2016).

We note that we can miss a potentially relevant study if our search terms were not mentioned in the title, abstract, or keywords. To our knowledge, this occurred only once, for Mastomys natalensis (we included the relevant study [Leirs et al. 1997] into our review after we were made aware that it assesses climate-demography relationships in the main text).

Lastly, we checked for potential database bias by running the search terms for a subset of nine species in Web of Science. The subset included three species with > three climate-demography studies published and available in SCOPUS (Rangifer tarandus, Cervus elaphus, Myocastor coypus); three species with only one climate-demography study obtained from SCOPUS (Oryx gazella, Macropus rufus, Rhabdomys pumilio); and another three species where SCOPUS did not return any published study (Calcochloris obtusirostris, Cynomops greenhalli, Suncus remyi). Species in the three subcategories were randomly chosen. Web of Science did not return additional studies for the three species where SCOPUS also failed to return a potentially suitable study. For the remaining six species, the total number of studies returned by Web of Science differed, but the same studies used for this review were returned, and we could not find any additional studies that adhered to our extraction criteria.

Description of key collected data

From all studies quantitatively assessing climate-demography relationships, we extracted the following information:

Geographic location - The center of the study area was always used. If coordinates were not provided in a study, we assigned coordinates based on the study descriptions of field sites and data collection.
Terrestrial biome - The study population was assigned to one of 14 terrestrial biomes (Olson et al. 2001) corresponding to the center of the study area. As this review is focused on general climatic patterns affecting demographic rates, specific microhabitat conditions described for any study population were not considered.
Climatic driver - Drivers linked to demographic rates were grouped as either local/regional precipitation & temperature values or derived indices (e.g., ENSO, NAO). The temporal extent (e.g., monthly, seasonal, annual, etc.) and aggregation type (e.g., minimum, maximum, mean, etc.) of drivers was also noted.
Demographic rate modeled - To facilitate comparisons, we grouped the demographic rates into either survival, reproductive success (i.e., whether or not reproduction occurre, reproductive output (i.e., number or rate of offspring production), growth (including stage transitions), or condition that determines development (i.e., mass or size). 
Stage or sex modeled - We retrieved information on responses of demographic rates to climate for each age class, stage, or sex modeled in a given study.
Driver effect - We grouped effects of drivers as positive (i.e., increased demographic rates), negative (i.e., reduced demographic rate), no effect, or context-dependent (e.g., positive effects at low population densities and now effect at high densities). We initially also considered nonlinear effects (e.g., positive effects at intermediate values and negative at extremes of a driver), but only 4 studies explicitly tested for nonlinear effects, by modelling squared or cubic climatic drivers in combination with driver interactions. We therefore considered nonlinear demographic effects as context dependent.  
Driver interactions - We noted any density dependence modeled and any non-climatic covariates included (as additive or interactive effects) in the demographic-rate models assessing climatic effects.
Future projections of climatic driver - In studies that indicated projections of drivers under climate change, we noted whether drivers were projected to increase, decrease, or show context-dependent trends. For studies that provided no information on climatic projections, we quantified projections as described in Detailed description of climate-change projections below (see also climate_change_analyses_mammal_review.R).

Six metrics were used to determine Population Vulnerability: global population size, annual occurrence in the California Current System (CCS), percent of the population present in the CCS, threat status, breeding score, and annual adult survival. Global Population size (POP)—to determine population size estimates for each species we gathered information tabulated by American Bird Conservancy, Birdlife International, and other primary sources. Proportion of Population in CCS (CCSpop)—for each species, we generated the population size within the CCS by averaging region-wide population estimates, or by combining state estimates for California, Oregon, and Washington for each species (if estimates were not available for a region or state, “NA” was recorded in place of a value) and then dividing the CCSpop value by the estimated global population size (POP) to yield the percentage of the population occurring in the CCS. Annual Occurrence in the CCS (AO)—for each species, we estimated the number of months per year within the CCS and binned this estimate into three categories: 1–4 months, 5–8 months, or 9–12 months. Threat Status (TS)—for each species, we used the International Union for Conservation of Nature (IUCN) species threat status (IUCN 2014) and the U.S. Fish and Wildlife national threat status lists (USFWS 2014) to determine TS values for each species. If available, we also evaluated threat status values from state and international agencies. Breeding Score (BR)—we determined the degree to which a species breeds and feeds its young in the CCS according to 3 categories: breeds in the CCS, may breed in the CCS, or does not breed in the CCS. Adult Survival (AS)—for each species, we referenced information to estimate adult annual survival, because adult survival among marine birds in general is the most important demographic factor that can affect population growth rate and therefore inform vulnerability. These data support the following publication: Adams, J., Kelsey, E.C., Felis J.J., and Pereksta, D.M., 2016, Collision and displacement vulnerability among marine birds of the California Current System associated with offshore wind energy infrastructure: U.S. Geological Survey Open-File Report 2016-1154, 116 p., https://doi.org/10.3133/ofr20161154. These data were revisied in June 2017 and the revision published in August 2017. Please be advised to use CCS_vulnerability_FINAL_VERSION_v9_PV.csv

1. Increased anthropogenic influence on the environment has accentuated the need to assess how climate and other environmental factors drive vital rates and population dynamics of different types of organisms. However, to allow distinction between effects of multiple correlated variables, and to capture the effects of rare and extreme climatic conditions, studies extending over decades are often necessary.

2. In this study we used an individual-based dataset collected in three populations of Pulsatilla vulgaris subsp. gotlandica during 34 years, to explore the effects of variation in precipitation and temperature on vital rates and population dynamics.

3. Most of the observed conspicuous variation in flowering among years was associated with differences in precipitation and temperature in the previous summer and autumn with a higher incidence of flowering following summers with high precipitation and low temperatures. In contrast, climatic variables had no significant effects on individual growth or survival.

4. Although the weather-driven variation in flowering had only moderate absolute effects on the population growth rate, simulated persistent changes in average precipitation and temperature resulted in considerable reductions in population sizes compared with current conditions. Analyses carried out with with subsets of data consisting of 5 and 10 years yielded results that strongly deviated from those based on the full data set.

5. Synthesis: The results of this study illustrate the importance of long-term demographic monitoring to identify key climatic variables affecting vital rates and driving population dynamics in long-lived organisms.

SummaryWe modified a bi-seasonal Ricker model previously developed by Betini et al. (2013) to examine the effects of season-specific habitat loss in either the breeding or non-breeding period and different strengths of density dependence on the production of experimentally-derived signals of population decline. The bi-seasonal habitat loss model is parameterized using the r-K formulation of the Ricker model, with separate values of growth rate (r) and carrying capacity (K) for each season (i.e., rb = reproductive output, rnb = non-breeding mortality, Kb = carrying capacity in the breeding period, Knb = carrying capacity in the non-breeding period). Exponential habitat decay is simulated in either season using two additional terms: Hb (the proportion of initial food remaining in the breeding period) and Hnb (the proportion of initial food remaining in the non-breeding period). The code here is used to simulate five different rates of habitat loss in either the breeding or non-breeding period over breeding or non-breeding of 50 generations, with habitat loss commencing after 20 generations. We ran 1,000 replicates simulations for each scenario/parameterization (see below). Initial starting parameters for a particular simulation are sampled from a distribution to allow for some degree of variability (but not strictly stochasticity) in population dynamics. We randomly sampled 25 replicates from each parameterization for subsequent plotting and analysis, data from which are provided in the CSV file.A complete description of the simulation methods and analysis is available in the pre-print on EcoEvoRxiv.Contentsbiseasonal_Ricker_code.R — R code to produce a bi-seasonal Ricker model in which habitat loss is simulated in either the breeding or non-breeding period.biseasonal_Ricker_simdata.csv — a sample of 25 simulated time series of bi-seasonal population abundance under different seasons and rates of habitat loss and strengths of density dependence.Variable definitionsnitt_t_DD = unique replicate identifier (factor) combining the replicate number (nitt), treatment type (t), and strength of density dependence (DD) simulated (e.g., "14_control_flies" references simulation 14 for the control treatment with the strength of density dependence based on values derived from an experimental population of fruit flies) — see variables below.nitt = replicate identification number (not strictly unique to different treatments)strength_DD = four-level factor (flies, weak, moderate, strong) indicating the initial strength of density dependence used to parameterize the model. In all cases, the strength was the same in both the breeding and non-breeding period (i.e., weak and weak, moderate and moderate, etc.). See values in the methods section of the paper or in the specific code for each model parameterization.treat = 11-level factor (control, b02, b5, b10, b20, b25, n02, n05, n10, n20, n25) indicating the season and rate of habitat loss being simulated where "control" indicates no habitat loss and "bXX" and "nXX" indicate breeding habitat and non-breeding habitat loss, respectively, at 2, 5, 10, 20, or 25% per generation.seasonT = three-level factor (c, b, n) indicating the season of treatment (c = control = no habitat loss, b = breeding, n = non-breeding).lossT = 6-level factor (0, 2, 5, 10, 20, 25) indicating the rate of habitat loss as a percent decrease per generation. A value of zero (0) indicates no habitat loss applied (i.e., for controls).time = integer (range = 1 to 100) indicating the time step in the model. Each generation (see below) consists of two timesteps (one each for the non-breeding and breeding seasons).gen = integer (range = 1 to 50) indicating the generation in each simulation. Each generation is repeated twice (with one row for each season). Each replicate was simulated for 20 generations under control conditions before the commencement of habitat loss in generation 21.season = two-level factor (n = non-breeding, b = breeding) indicating the season within each generation.count = integer value indicating the population size simulated in each season of each generation.rate = continuous value expressing the change in population size from the previous timestep to the current (e.g., if the previous (non-breeding) population size was 189 and the current (breeding) value is 249, then rate = 249/189 = 1.32). For rows where season = b = breeding, this value represents the breeding growth rate; when season = n = non-breeding, this value indicates non-breeding survival.first_match = integer indicates the first timestep in which population size reached zero (0) indicating the season and generation in which a simulation became extinct.ReferencesBetini, G.S., Griswold, C.K., and Norris, D.R. (2013), Carry-over effects, sequential density dependence and the dynamics of populations in a seasonal environment. Proceedings of the Royal Society B 280: 20130110. https://doi.org/10.1098/rspb.2013.0110

Population structure can significantly affect genetic-based demographic inferences, generating spurious bottleneck-like signals. Previous studies have typically assumed island or stepping-stone models, which are characterized by symmetric gene flow. However, many organisms are characterized by asymmetric gene flow. Here, we combined simulated and empirical data to test whether asymmetric gene flow affects the inference of past demographic changes. Through the analysis of simulated genetic data with three methods (i.e. bottleneck, M-ratio and msvar), we demonstrated that asymmetric gene flow biases past demographic changes. Most biases were towards spurious signals of expansion, albeit their strength depended on values of effective population size and migration rate. It is noteworthy that the spurious signals of demographic changes also depended on the statistical approach underlying each of the three methods. For one of the three methods, biases induced by asymmetric gene flow were confirmed in an empirical multispecific data set involving four freshwater fish species (Squalius cephalus, Leuciscus burdigalensis, Gobio gobio and Phoxinus phoxinus). However, for the two other methods, strong signals of bottlenecks were detected for all species and across two rivers. This suggests that, although potentially biased by asymmetric gene flow, some of these methods were able to bypass this bias when a bottleneck actually occurred. Our results show that population structure and dispersal patterns have to be considered for proper inference of demographic changes from genetic data.

Data set of a community based cross-sectional survey done to find the prevalence , its correlates and patterns in a population of a district in southern Kerala, IndiaBackground: Multi-morbidity is the coexistence of multiple chronic conditions in the same individual. With advancing epidemiological and demographic transitions, the burden of multi-morbidity is expected to increase India. The state of Kerala in India is also in an advanced phase of epidemiological transition. However, very limited data on prevalence of multi-morbidity are available in the Kerala population.

Methods: A cross sectional survey was conducted among 410 participants in the age group of 30-69 years. A multi-stage cluster sampling method was employed to identify the study participants. Every eligible participant in the household were interviewed to assess the household prevalence. A structured interview schedule was used to assess socio-demographic variables, behavioral risk factors and prevailing clinical conditions, PHQ-9 questionnaire for screening of depression and active measurement of blood sugar and blood pressure. Co-existence of two or more conditions out of 11 was used as multi-morbidity case definition. Bivariate analyses were done to understand the association between socio-demographic factors and multi-morbidity. Logistic regression analyses were performed to estimate the effect size of these variables on multi-morbidity.

Results: Overall, the prevalence of multi-morbidity was 45.4% (95% CI: 40.5-50.3%). Nearly a quarter of study participants (25.4%) reported only one chronic condition (21.3-29.9%). Further, 30.7% (26.3-35.5), 10.7% (7.9-14.2), 3.7% (2.1-6.0) and 0.2% reported two, three, four and five chronic conditions, respectively. Nearly seven out of ten households (72%, 95%CI: 65-78%) had at least one person in the household with multi-morbidity and one in five households (22%, 95%CI: 16.7-28.9%) had more than one person with multi-morbidity. With every year increase in age, the propensity for multi-morbidity increased by 10 percent (OR=1.1; 95% CI: 1.1-1.2). Males and participants with low levels of education were less likely to suffer from multi-morbidity while unemployed and who do recommended level of physical activity were significantly more likely to suffer from multi-morbidity. Diabetes and hypertension was the most frequent dyad.

Conclusion: One of two participants in the productive age group of 30-69 years report multi-morbidity. Further, seven of ten households have at least one person with multi-morbidity. Preventive and management guidelines for chronic non-communicable conditions should focus on multi-morbidity especially in the older age group. Health-care systems that function within the limits of vertical disease management and episodic care (e.g., maternal health, tuberculosis, malaria, cardiovascular disease, mental health etc.) require optimal re-organization and horizontal integration of care across disease domains in managing people with multiple chronic conditions.

Key words: Multi-morbidity, cross-sectional, household, active measurement, rural, India, pattern

Variation in age structure influences population dynamics, yet we have limited understanding of the spatial scale at which its fluctuations are synchronised between populations. Using 32 great tit populations, spanning 4○W–33○E and 35–65○N involving >130,000 birds across 67 years, we quantify spatial synchrony in breeding demographic structure (subadult vs. adult breeders) and its drivers. We show that larger clutch sizes, colder winters, and larger beech crops lead to younger populations. We report distance-dependent synchrony of demographic structure, maintained at approximately 650km. Despite covariation with demographic structure, we do not find evidence for environmental variables influencing the scale of synchrony, except for beech masting. We suggest that local ecological and density-dependent dynamics impact how environmental variation interacts with demographic structure, influencing estimates of the environment’s effect on synchrony. Our analyses demonstrate the operation o..., Study systems and data collection The great tit Parus major is a passerine bird found in mixed woodlands across much of the Western Palearctic. Their reproductive lifespan ranges from 1–9, averaging 1.8 years (Bouwhuis et al. 2009; Woodman et al. 2022). Although there are some continuous changes with age (Bouwhuis et al. 2009), the main age effects on individual-level traits and population processes are captured by two age-classes: 1-year-olds (hereafter subadults) and older (hereafter adults, Gosler 1993; Harvey et al. 1979; Perrins 1979; Gamelon et al. 2016, 2019; Woodman et al. 2022). Great tits generally undertake one breeding attempt during a single annual breeding season April–June (in some parts of their range second clutches can occur, Verhulst 1998; Visser et al. 2003). Data used here are from 32 populations, the geographical range of which represents a large part of the species’ breeding range (Sullivan et al. 2009). Generally, data collection at these sites included regular v..., , # Continent-wide drivers of spatial synchrony in breeding demographic structure across wild great tit populations

Access this dataset on Dryad

Presented here is the raw data ("bred_dem_synchrony.RData") and annotated R Script ("Continent-wide drivers of spatial synchrony in breeding demographic structure across wild great tit populations.R") needed to run analyses for the project "Continent-wide drivers of spatial synchrony in breeding demographic structure across wild great tit populations".

Description of the data and file structure

"bred_dem_synchrony.RData": R-data file needed to run analyses. Descriptions of the three datasets within this file are found in the R script, and also below.

1. "bred_dem_variables" = Base data for annual breeding demographic structure variables of great tit populations. Only includes populations with annual population size equal or greater than 20 individuals and where 25% or more of individuals have be...

Abstract

The Armenia Demographic and Health Survey (ADHS) was a nationally representative sample survey designed to provide information on population and health issues in Armenia. The primary goal of the survey was to develop a single integrated set of demographic and health data, the first such data set pertaining to the population of the Republic of Armenia. In addition to integrating measures of reproductive, child, and adult health, another feature of the DHS survey is that the majority of data are presented at the marz level.

The ADHS was conducted by the National Statistical Service and the Ministry of Health of the Republic of Armenia during October through December 2000. ORC Macro provided technical support for the survey through the MEASURE DHS+ project. MEASURE DHS+ is a worldwide project, sponsored by the USAID, with a mandate to assist countries in obtaining information on key population and health indicators. USAID/Armenia provided funding for the survey. The United Nations Children’s Fund (UNICEF)/Armenia provided support through the donation of equipment.

The ADHS collected national- and regional-level data on fertility and contraceptive use, maternal and child health, adult health, and AIDS and other sexually transmitted diseases. The survey obtained detailed information on these issues from women of reproductive age and, on certain topics, from men as well. Data are presented by marz wherever sample size permits.

The ADHS results are intended to provide the information needed to evaluate existing social programs and to design new strategies for improving the health of and health services for the people of Armenia. The ADHS also contributes to the growing international database on demographic and health-related variables.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men age 15-54

Kind of data

Sample survey data

Sampling procedure

The sample was designed to provide estimates of most survey indicators (including fertility, abortion, and contraceptive prevalence) for Yerevan and each of the other ten administrative regions (marzes). The design also called for estimates of infant and child mortality at the national level for Yerevan and other urban areas and rural areas.

The target sample size of 6,500 completed interviews with women age 15-49 was allocated as follows: 1,500 to Yerevan and 500 to each of the ten marzes. Within each marz, the sample was allocated between urban and rural areas in proportion to the population size. This gave a target sample of approximately 2,300 completed interviews for urban areas exclusive of Yerevan and 2,700 completed interviews for the rural sector. Interviews were completed with 6,430 women. Men age 15-54 were interviewed in every third household; this yielded 1,719 completed interviews.

A two-stage sample was used. In the first stage, 260 areas or primary sampling units (PSUs) were selected with probability proportional to population size (PPS) by systematic selection from a list of areas. The list of areas was the 1996 Data Base of Addresses and Households constructed by the National Statistical Service. Because most selected areas were too large to be directly listed, a separate segmentation operation was conducted prior to household listing. Large selected areas were divided into segments of which two segments were included in the sample. A complete listing of households was then carried out in selected segments as well as selected areas that were not segmented.

The listing of households served as the sampling frame for the selection of households in the second stage of sampling. Within each area, households were selected systematically so as to yield an average of 25 completed interviews with eligible women per area. All women 15-49 who stayed in the sampled households on the night before the interview were eligible for the survey. In each segment, a subsample of one-third of all households was selected for the men's component of the survey. In these households, all men 15-54 who stayed in the household on the previous night were eligible for the survey.

Note: See detailed description of sample design in APPENDIX A of the survey report.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires were used in the ADHS: a Household Questionnaire, a Women’s Questionnaire, and a Men’s Questionnaire. The questionnaires were based on the model survey instruments developed for the MEASURE DHS+ program. The model questionnaires were adapted for use during a series of expert meetings hosted by the Center of Perinatology, Obstetrics, and Gynecology. The questionnaires were developed in English and translated into Armenian and Russian. The questionnaires were pretested in July 2000.

The Household Questionnaire was used to list all usual members of and visitors to a household and to collect information on the physical characteristics of the dwelling unit. The first part of the household questionnaire collected information on the age, sex, residence, educational attainment, and relationship to the household head of each household member or visitor. This information provided basic demographic data for Armenian households. It also was used to identify the women and men who were eligible for the individual interview (i.e., women 15-49 and men 15-54). The second part of the Household Questionnaire consisted of questions on housing characteristics (e.g., the flooring material, the source of water, and the type of toilet facilities) and on ownership of a variety of consumer goods.

The Women’s Questionnaire obtained information on the following topics: - Background characteristics - Pregnancy history - Antenatal, delivery, and postnatal care - Knowledge and use of contraception - Attitudes toward contraception and abortion - Reproductive and adult health - Vaccinations, birth registration, and health of children under age five - Episodes of diarrhea and respiratory illness of children under age five - Breastfeeding and weaning practices - Height and weight of women and children under age five - Hemoglobin measurement of women and children under age five - Marriage and recent sexual activity - Fertility preferences - Knowledge of and attitude toward AIDS and other sexually transmitted infections.

The Men’s Questionnaire focused on the following topics: - Background characteristics - Health - Marriage and recent sexual activity - Attitudes toward and use of condoms - Knowledge of and attitude toward AIDS and other sexually transmitted infections.

Cleaning operations

After a team had completed interviewing in a cluster, questionnaires were returned promptly to the National Statistical Service in Yerevan for data processing. The office editing staff first checked that questionnaires for all selected households and eligible respondents had been received from the field staff. In addition, a few questions that had not been precoded (e.g., occupation) were coded at this time. Using the ISSA (Integrated System for Survey Analysis) software, a specially trained team of data processing staff entered the questionnaires and edited the resulting data set on microcomputers. The process of office editing and data processing was initiated soon after the beginning of fieldwork and was completed by the end of January 2001.

Response rate

A total of 6,524 households were selected for the sample, of which 6,150 were occupied at the time of fieldwork. The main reason for the difference is that some of the dwelling units that were occupied during the household listing operation were either vacant or the household was away for an extended period at the time of interviewing. Of the occupied households, 97 percent were successfully interviewed.

In these households, 6,685 women were identified as eligible for the individual interview (i.e., age 15-49). Interviews were completed with 96 percent of them. Of the 1,913 eligible men identified, 90 percent were successfully interviewed. The principal reason for non-response among eligible women and men was the failure to find them at home despite repeated visits to the household. The refusal rate was low.

The overall response rates, the product of the household and the individual response rates, were 94 percent for women and 87 percent for men.

Note: See summarized response rates by residence (urban/rural) in Table 1.1 of the survey report.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2000 Armenia Demographic and Health Survey (ADHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the ADHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey

Many populations, especially in insects, fluctuate in size and periods of particularly low population size can have strong effects on genetic variation. Effects of demographic bottlenecks on genetic diversity of single populations are widely documented. Effects of bottlenecks on genetic structure among multiple inter-connected populations are less studied, as are genetic changes across multiple cycles of demographic collapse and recovery. We take advantage of a long-term dataset comprising demographic, genetic, and movement data from a network of populations of the butterfly, Parnassius smintheus, to examine the effects of fluctuating population size on spatial genetic structure. We build on a previous study that documented increased genetic differentiation and loss of spatial genetic patterns (isolation by distance and by intervening forest cover) after a network-wide bottleneck event. Here, we show that genetic differentiation was reduced again and spatial patterns returned to the system extremely rapidly, within three years (i.e., generations). We also show that a second bottleneck had similar effects to the first, increasing differentiation and erasing spatial patterns. Thus, bottlenecks consistently drive random divergence of allele frequencies among populations in this system, but these effects are rapidly countered by gene flow during demographic recovery. Our results reveal a system in which the relative influence of genetic drift and gene flow continually shift as populations fluctuate in size, leading to cyclic changes in genetic structure. Our results also suggest caution in the interpretation of patterns of spatial genetic structure, and its association with landscape variables, when measured at only a single point in time.

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These data examine the effects on total crime rates of changes in the demographic composition of the population and changes in criminality of specific age and race groups. The collection contains estimates from national data of annual age-by-race specific arrest rates and crime rates for murder, robbery, and burglary over the 21-year period 1965-1985. The data address the following questions: (1) Are the crime rates reported by the Uniform Crime Reports (UCR) data series valid indicators of national crime trends? (2) How much of the change between 1965 and 1985 in total crime rates for murder, robbery, and burglary is attributable to changes in the age and race composition of the population, and how much is accounted for by changes in crime rates within age-by-race specific subgroups? (3) What are the effects of age and race on subgroup crime rates for murder, robbery, and burglary? (4) What is the effect of time period on subgroup crime rates for murder, robbery, and burglary? (5) What is the effect of birth cohort, particularly the effect of the very large (baby-boom) cohorts following World War II, on subgroup crime rates for murder, robbery, and burglary? (6) What is the effect of interactions among age, race, time period, and cohort on subgroup crime rates for murder, robbery, and burglary? (7) How do patterns of age-by-race specific crime rates for murder, robbery, and burglary compare for different demographic subgroups? The variables in this study fall into four categories. The first category includes variables that define the race-age cohort of the unit of observation. The values of these variables are directly available from UCR and include year of observation (from 1965-1985), age group, and race. The second category of variables were computed using UCR data pertaining to the first category of variables. These are period, birth cohort of age group in each year, and average cohort size for each single age within each single group. The third category includes variables that describe the annual age-by-race specific arrest rates for the different crime types. These variables were estimated for race, age, group, crime type, and year using data directly available from UCR and population estimates from Census publications. The fourth category includes variables similar to the third group. Data for estimating these variables were derived from available UCR data on the total number of offenses known to the police and total arrests in combination with the age-by-race specific arrest rates for the different crime types.

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This dataset covers ballots 420-432 spanning January-December 1979. The dataset contains the data resulting from these polls in ASCII. The ballots are as follows: 420 - January This Gallup poll seeks the opinions of Canadians, on predominantly political issues. The questions ask opinions about political leaders and political issues within the country such as the threat of Quebec separation and the government's handling of the economy. There are also questions on other topics of interest and importance to the country and government, including inflation, ratings of public schools and credit investigations. The respondents were also asked questions so that they could be grouped according to geographic and social variables. Topics of interest include: the types of activities participated in the last year; Canada's biggest threat; dealing with inflation; governmental control of cults; the government's handling of the economy; popular beliefs; the problems facing public schools; rating public schools in the community; voting on Quebec separation; voting on Quebec sovereignty; and worries over credit investigations. Basic demographic variables are also included. 421a - February This Gallup poll seeks the opinions of Canadians, on predominantly political issues. The questions ask opinions about political leaders and political issues within the country such as admitting refugees, provincial power and opinions about the Governor General. The respondents were also asked questions so that they could be grouped according to geographic and social variables. Topics of interest include: admitting Indo-China refugees; the amount of spare money; the opinion of Ed Schreyer as Governor General; population levels in Canada; the reasons why certain provinces have more power; union involvement in political activities; and the use of seatbelts. Basic demographic variables are also included. 421b - February This Gallup poll seeks the opinions of Canadians, on both social and political issues. The questions ask opinions about political leaders, Canadian population and abortion. It also asks questions regarding a better economy under the lead of which party. The respondents were also asked questions so that they could be grouped according to geographical variables. Topics of interest include: abortion; a better economy under which party; future of the family; and the size of the Canadian population. Basic demographic variables are also included. 422 - March This Gallup poll seeks the opinions of Canadians, on predominantly political issues. The questions ask opinions about future elections and agreements between Federal and Provincial politicians as well as other important political issues within the country. There are also questions on other topics of interest including welfare, family income and the chances of nuclear war. The respondents were also asked questions so that they could be grouped according to geographic and social variables. Topics of interest include: allowing price and wage controls; the chances of nuclear war; the direction of future prices; direction that Canada is going in; the effects of a cashless society; the effects of having two official languages; the effects of using French in Quebec on business relations; Federal-Provincial agreements; foods that can cause cancer; international growth of the English language; having a cashless society; job opportunities for married women; making amendments to the Constitution; making individuals on welfare work; the minimum amount of income a family needs; political predictions; taking cancer reports seriously; and taking advantage of the welfare system. Basic demographic variables are also included. 423a - April This Gallup poll seeks the opinions of Canadians, on predominantly political issues. The questions ask opinions about political leaders and political issues within the country. There are also questions on other topics of interest and importance to the country and government, such as discipline in schools and the use of seatbelts. The respondents were also asked questions so that they could be grouped according to geographic and social variables. Topics of interest includes: which party is the best to handle problems; discipline in schools; the ideal number of children to have; influencing voting decisions; level of interest in the Federal election; Medicare fees; opinions about Broadbent; opinions about Clark; opinions about the teaching profession; opinions about Trudeau; political predictions; problems facing Canada; using a seatbelt; and who would make the best Prime Minister. Basic demographic variables are also included. 424a - May This Gallup poll seeks the opinions of Canadians, on solely political issues. The questions ask opinions about the upcoming elections, including eligibility to vote and interest. The respondents were also asked questions so that they could be grouped according to geographic and social variables. Topics of interest include: eligibility to vote in next election and interest in the upcoming election. Basic demographic variables are also included. 424b2 - May This Gallup poll seeks the opinions of Canadians, on solely political issues. The questions ask opinions about the interest in the upcoming election. The respondents were also asked questions so that they could be grouped according to geographic and social variables. Topics of interest include: the interest in the upcoming election. Basic demographic variables are also included. 424 b2&3 - May This Gallup poll seeks the opinions of Canadians, on solely political issues. The questions ask opinions about the interest in the upcoming election. The respondents were also asked questions so that they could be grouped according to geographic and social variables. Topics of interest include: the interest in the upcoming election. Basic demographic variables are also included. Questions 1 and 2 are from 424B 2 & 3 (2,088 cases); questions 3 to 9 are from 24B 2 ONLY (1,038 cases). 425 - May This Gallup poll seeks the opinions of Canadians, on solely political issues. The questions ask opinions about the upcoming election and the certainty of voting in it. The respondents were also asked questions so that they could be grouped according to geographic and social variables. Topics of interest include: the certainty of voting in the upcoming election; eligibility to vote; and interest in coming election. Basic demographic variables are also included. 426 - June This Gallup poll seeks the opinions of Canadians, on both political and social issues. The questions ask opinions about political leaders and political issues within the country. There are also questions on other topics of interest and importance to the country and government, such as the preferred area to live in, nudes in art and who benefits the most from marriage. The respondents were also asked questions so that they could be grouped according to geographic variables. Topics of interest include: benefiting from marriage; confidence in institutions; government imposed price control; government imposed wage control; issues the government will have to deal with; leader with the best campaign; length of new the Parliament; opinions about nudes in art; preferred area to live in; publicly showing sex; Quebec separating from Canada; reasons for the minority government; reasons for voting for a particular party; and religion's influence on life. Basic demographic variables are also included. 427a - July This Gallup poll seeks the opinions of Canadians on the selling of the Crown corporation PetroCan to the private sector. The respondents were also asked questions so that they could be grouped according to geographic and social variables. Topics of interest: whether or not PetroCan should be sold to the private sector. Basic demographic variables are also included. 427b - July This Gallup poll seeks the opinions of Canadians, on predominantly political issues. The questions ask opinions about political leaders and their parties as well as the effects of moving a Canadian Embassy; allowing Vietnam refugees and the Strategic Arms Limitation Treaty. There are also questions on other topics of interest and importance to the country and government, including the rising prices of food and the safety of air travel. The respondents were also asked questions so that they could be grouped according to geographic and social variables. Topics of interest include: allowing Vietnam refugees; air safety precautions; the causes of rising food prices; changing cooking and eating habits; confidence in oil firms; effects of labour unions; effects of moving the Canadian Embassy; frequency of air travel; moving the Canadian Embassy in Israeli; opinions about the Conservative party; opinions about the Liberal party; opinions about the NDP party; the amount of power labour unions have; rising food prices; selling PetroCan to the private sector; the severity of gas shortages; and the Strategic Arms Limitation Treaty (SALT II). Basic demographic variables are also included. 428a - August This Gallup poll seeks the opinions of Canadians, on predominately political issues. The questions ask opinions about political leaders and political issues within the country. There are also questions on other topics of interest and importance to the country and government such as diets; objectionable sex in the media and sports participation. The respondents were also asked questions so that they could be grouped according to geographic and social variables. Topics of interest include: making amendments to Canada's Constitution; Canada's most important problems; Canada's energy crisis; current personal weight; following a diet; impact of regional differences; objectionable sex in the media; opinions about Broadbent; opinions about Clark; opinions about Trudeau; privately owned energy; satisfaction with family income; sports participation; traveling to work; whether or not there

Introduction and Background. Minorities are less likely to report rapes. The Post Coital DNA Recovery (PCDR) study (2009-14) subjects were white (93%) where expanded collection times were not generalizable to minority populations. Evidence reports health and medical differences between races necessitating duplication of previous research in minority populations. Aims. (1) What is the time period in which it is possible to collect post-coital DNA in minority women using Y-STR laboratory methods? and (2) when compared to the former study sample of minority and non-minority, what are the physiological conditions, factors, or activities in minority couples that influence post-coital DNA recovery? Design. The design includes mixed methods duplication perfected in the first study, embracing descriptive and inferential techniques. Qualitative research used semi-structured interviews. Aim 1 analysis used PCDR-M data only. Aim 2 combined data from both PCDR and PCDR-M studies. Combined, DNA recovery, a binary outcome accounting for repeated methods in population regression analysis, used Generalized Estimating Equation (GEE) methods. Fidelity. The strict criteria for adherence included considerable outreach and support of study personnel. PCDR and PCDR-M data combined and compared the two samples, which had specific homogeneity, including same inclusion and elimination criteria in both studies; fidelity to the validated protocol; laboratory method and interpretation for inclusion; duplicate statistical analysis; and interpretation of data. Any variation in key variables met elimination criteria. Assumptions and Limitations. Assumptions included (1) motivation is altruistic; (2) motivation is incentives and coercion for some; (3) negotiating coitus is difficult and stressful; and (4) similar fidelity and dropout rates. The limitations included (1) a lack of representation for the diverse experiences of rape victims; (2) sample size; (3) self-selection bias; (4) protocol adherence; and (4) advances in laboratory science and DNA kits. Demographics. Demographic variables included gender, race, and age. Major categories in the dataset included participants' reproductive history, data on female participants' reproductive organs, and childhood abuse.

This data package is comprised of three datasets all pertaining to two dominant palmetto species, Serenoa repens and Sabal etonia, at Archbold Biological Station in south-central Florida. The first dataset, palmetto_data, contains survival and growth data across multiple years, habitats and experimental treatments. The second dataset, seedlings_data, follows the fate of marked putative palmetto seedlings in the field to assess survivorship and growth. The final dataset, harvested_palmetto_data, contains size data and estimated dry mass (biomass in grams) of 33 destructively harvested palmetto plants (17 S. repens and 16 S. etonia) of varying sizes and across habitats. Thirty-two of these were used to calculate estimated biomass, using regression equations, for palmettos sampled in the palmetto_data. Below we summarize experimental setup and data collected for each dataset. Palmetto data Demographic data were collected as three separate components. The first component compared growth among habitats. Starting in 1981, equal numbers of both palmetto species were marked across scrubby flatwoods (oak scrub) and flatwoods habitats (3 sites per habitat) for a total of 240 marked plants. These habitats had not burned within the last decade, but historically had experienced a natural fire return interval of 5 - 20 years prior to this studies initiation. The second component added an additional 400 palmettos (200 of each species), which were marked in sand pine scrub (n = 200) in 1985 and sandhill habitat (n = 200) in 1989 on Archbold's Red Hill. At the time of this project's initiation, all Red Hill management units were last burned in 1927 and were considered long unburned. Part of Archbold's management plan included restoring fire into some management units while leaving others long unburned to serve as reference units. Therefore, for our second component, we were able to create a 2x2 factorial design using habitat types on Red Hill and fire management as factors, with 100 palmettos in each category (50 of each species). The third component involved an experiment to examine the factorial effects of clipping and fertilizing on palmetto flowering. We marked 300 palmettos (150 of each species), all in sand pine scrub habitat on Red Hill, and used the 100 palmettos marked in 1985 as controls. Annual data measures included height, canopy length and width (all in cm), number of new and green leaves and flowering scapes. Data were collected continuously (not for all variables or sites) from 1981 through 1997 then again in 2001 and 2017. Data collection is ongoing at 5-year intervals. Data on the 100 plants in the experimental sandhill on Red Hill were not collected in 2017 due to the removal of marked stakes from roller chopping of the site as part of more recent sandhill restoration efforts. A subset of the plants in the clipping and fertilizing experiment were lost in 2013 when a plow line was established to stop the spread of a wildfire. The locations of all remaining plants were taken in 2017 using a Trimble GPS unit and are included as a separate data file (palmetto_location_data) and shapefile (palmetto_shape). Seedling data In January 1989, we marked 100 putative seedlings in flatwoods habitats and 87 in scrubby flatwoods habitats. Putative seedlings typically cannot be identified using morphology as either S. repens or S. etonia so sample sizes of each are unknown. Annual data recorded included survival, standing height (cm) and maximum crown diameter (cm). In 1991, we started measuring basal stem diameter (cm) with calipers. During annual visits, we noted if the species could be identified as S. repens or S. etonia. Data were collected continuously starting in 1989 through 1997, then again in 2001 and 2008. Data collection is not ongoing for this dataset. Harvested Palmetto data Thirty-three palmettos, 17 S. repens and 16 S. etonia, were destructively harvested at three different sites, from two habitats (scrubby flatwoods and sand pine scrub) in 1985. Basic size measures as taken for palmetto demography data were recorded including height, canopy length and width (all in cm) and the number of green leaves. Additional data measures were recorded on the largest leaf blade including maximum length and width of the palmetto leaf and petiole length and width. Finally, basal diameter at the ground level was recorded. Only 32 palmettos were used to develop biomass regressions (17 S. repens and 15 S. etonia). Biomass is the estimated dry mass (g) of each harvested palmetto. Fresh palmettos were divided into leaf and stem (both above- and below-ground), but roots were not harvested since they grow to depths of several meters, making recovery of all root tissues virtually impossible for fresh-mass determination. Subsamples of fresh mass were oven dried at 80C to constant mass for estimation of dry mass equivalent, which in turn was used to estimate the dry mass of the harvested palmettos.

Global human exposure to wildland fires dataset: 2002-2021

Seyd Teymoor Seydi¹, John T. Abatzoglou², Matthew W. Jones³, Mojtaba Sadegh^1,4

¹Department of Civil Engineering, Boise State University, Boise, ID, USA

²Management of Complex Systems Department, University of California, Merced, Merced, CA, USA

³Tyndall Centre for Climate Change Research, School of Environmental Sciences, University of East Anglia (UEA), Norwich, UK

⁴United Nations University Institute for Water, Environment and Health, Richmond Hills, ON, Canada

1. Dataset Overview

This dataset contains comprehensive information on global fire events from 2002 to 2021, including fire characteristics, environmental variables, land cover properties, and detailed population exposure estimates separated by age group and gender. The data is organized into two separate dataset series:

1. Fire Events Series (df_Fire_Events_2002 to df_Fire_Events_2021): Contains fire characteristics, environmental variables, land cover properties, and summary exposure information for each fire event. Each file includes global fire events for one year, as indicated in the file name.

2. Age Groups Series (df_Fire_Age_Groups_2002 to df_Fire_Age_Groups_2021): Contains detailed demographic breakdowns of populations exposed to individual fire events by age group and gender. Each file includes global fire events for one year, as indicated in the file name.

2. Data Structure

Each annual dataset contains the following information:

• Temporal Coverage: Individual years from 2002 to 2021 (20 datasets total x 2 [environmental variables and summary exposure + exposures broken down by age and gender structures])
• Spatial Coverage: Global
• Unit of Analysis: Individual fire events identified by unique fire_ID
• Fire Metrics: Location, size, duration, spread characteristics, active fire days, and fire radiative power
• Environmental Variables: Vegetation indices (EVI, NDVI) and land cover fractions
• Population Metrics: Total exposure and detailed breakdowns by 5-year age groups and gender
• Geographic Context: Country and continent information

Column Definitions

Fire Characteristics

• fire_ID: Unique identifier for each fire event
• Latitude: Latitude coordinate of fire ignition point (decimal degrees)
• Longitude: Longitude coordinate of fire ignition point (decimal degrees)
• size: Fire area
• perimeter: Fire perimeter length
• start_date: Fire start date
• duration: Fire duration (days)
• spread: Fire spread rate
• speed: Fire speed rate
• Active_Fire_Days: Number of active fire days in each pixel within fire polygon, averaged for each fire polygon (Source: MOD14A1)
• total_frp: Total fire radiative power summed from start to end date of fire, aggregated by sum for each fire polygon (Source: MOD14A1)

3. Geographic Information

• Country: Name of country where fire occurred
• Continent: Name of continent where fire occurred

4. Land Cover Characteristics (Source: MCD12Q1)

• Agriculture-Fraction: Fraction of agricultural land cover within fire polygon
• Urban-Fraction: Fraction of urban areas within fire polygon

5. Vegetation Indices (Source: MOD13A1)

• EVI: Enhanced Vegetation Index - maximum annual value for each pixel averaged across fire polygon
• NDVI: Normalized Difference Vegetation Index - maximum annual value for each pixel averaged across fire polygon

6. Population Exposure (Source: WorldPop)

• Exposure: Total population exposure to fire, aggregated by sum for each individual fire event using contemporary population data for each year
• Scenario-Exposure: Total population exposure to fire using constant 2002 population data across all years, with dynamic fire data for each year, aggregated by sum for each individual fire event. This is also referred to as counterfactual exposure.

6.1. Female Population Exposure (SUM_f_*)

• SUM_f_0: Number of females aged <1 year exposed to fire
• SUM_f_1: Number of females aged ≥1 to <5 years exposed to fire
• SUM_f_5: Number of females aged ≥5 to <10 years exposed to fire
• SUM_f_10: Number of females aged ≥10 to <15 years exposed to fire
• SUM_f_15: Number of females aged ≥15 to <20 years exposed to fire
• SUM_f_20: Number of females aged ≥20 to <25 years exposed to fire
• SUM_f_25: Number of females aged ≥25 to <30 years exposed to fire
• SUM_f_30: Number of females aged ≥30 to <35 years exposed to fire
• SUM_f_35: Number of females aged ≥35 to <40 years exposed to fire
• SUM_f_40: Number of females aged ≥40 to <45 years exposed to fire
• SUM_f_45: Number of females aged ≥45 to <50 years exposed to fire
• SUM_f_50: Number of females aged ≥50 to <55 years exposed to fire
• SUM_f_55: Number of females aged ≥55 to <60 years exposed to fire
• SUM_f_60: Number of females aged ≥60 to <65 years exposed to fire
• SUM_f_65: Number of females aged ≥65 to <70 years exposed to fire
• SUM_f_70: Number of females aged ≥70 to <75 years exposed to fire
• SUM_f_75: Number of females aged ≥75 to <80 years exposed to fire
• SUM_f_80: Number of females aged ≥80 years exposed to fire

6.2. Male Population Exposure (SUM_m_*)

• SUM_m_0: Number of males aged <1 year exposed to fire
• SUM_m_1: Number of males aged ≥1 to <5 years exposed to fire
• SUM_m_5: Number of males aged ≥5 to <10 years exposed to fire
• SUM_m_10: Number of males aged ≥10 to <15 years exposed to fire
• SUM_m_15: Number of males aged ≥15 to <20 years exposed to fire
• SUM_m_20: Number of males aged ≥20 to <25 years exposed to fire
• SUM_m_25: Number of males aged ≥25 to <30 years exposed to fire
• SUM_m_30: Number of males aged ≥30 to <35 years exposed to fire
• SUM_m_35: Number of males aged ≥35 to <40 years exposed to fire
• SUM_m_40: Number of males aged ≥40 to <45 years exposed to fire
• SUM_m_45: Number of males aged ≥45 to <50 years exposed to fire
• SUM_m_50: Number of males aged ≥50 to <55 years exposed to fire
• SUM_m_55: Number of males aged ≥55 to <60 years exposed to fire
• SUM_m_60: Number of males aged ≥60 to <65 years exposed to fire
• SUM_m_65: Number of males aged ≥65 to <70 years exposed to fire
• SUM_m_70: Number of males aged ≥70 to <75 years exposed to fire
• SUM_m_75: Number of males aged ≥75 to <80 years exposed to fire
• SUM_m_80: Number of males aged ≥80 years exposed to fire

7. Data Sources

• Population Data: WorldPop Project demographic datasets

o Source URL: https://hub.worldpop.org/project/categories?id=8

o Population estimates are provided in 5-year age groups by gender at high spatial resolution

• Land Cover Data: MODIS MCD12Q1 Land Cover Type product

o Used to calculate agricultural and urban land cover fractions within fire polygons

• Vegetation Indices: MODIS MOD13A1 Vegetation Indices product

o Used to derive maximum annual EVI and NDVI values, averaged across fire polygons

• Fire Activity Data: MODIS MOD14A1 Thermal Anomalies and Fire Daily product

o Used to calculate active fire days and total fire radiative power within fire polygons

• Fire Data: Global fire atlas is available at: https://doi.org/10.5281/zenodo.11400062" href="https://doi.org/10.5281/zenodo.11400062" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.11400062

8. Usage Notes

1. Exposure Definition: Exposure is defined as population within fire polygon boundaries
2. Exposure Scenarios:

o Exposure: Uses contemporary population data for each year, allowing analysis of changing demographics over time

o Scenario-Exposure: Uses constant 2002 population data across all years to isolate the effect of changing fire patterns while holding population constant

1. Age Group Structure: Age groups follow standard demographic categories with the first year of life separate (0)

Human activities catalyze risk avoidance behaviors in wildlife across taxa and systems. However, the broader ecological significance of human-induced risk perception remains unclear, with a limited understanding of how phenotypic responses scale up to affect population or community dynamics. We conducted a comprehensive literature review of non-consumptive effects (NCE; population effects) and trait-mediated indirect effects (TMIE; community effects) of anthropogenic disturbances. This dataset includes all papers identified from the comprehensive review of the different types of human-induced behavioral and physiological phenotypic change and their influence on vital rates and population parameters in wildlife. All papers in this database tested for a human-induced NCE or TMIE in wildlife but not all found evidence for an effect. Many of the papers did not explicitly measure the presumed phenotypic change linking human activity to vital rates or population parameters. The authors, paper title, journal, publication year, type of human disturbance, species, system, phenotypic response measured, demographic response measured, if a demographic effect was found, and whether an NCE or TMIE was tested are all included in the dataset. In addition, we include the source of the paper in our dataset (i.e. whether it came up in our Web of Science search, as a citing paper of Frid and Dill (2002), or in a review paper on human-induced fear in wildlife; column A). The papers in which multiple NCE or TMIE pathways were tested may have multiple values in a single cell. Papers are sorted alphabetically by author. Evidence for human-induced NCEs and TMIEs is mixed, with half of published studies finding a relationship between human activities, phenotypic change, and population outcomes. Strong research biases in taxa, systems, human disturbance type, and demographic measures prevent unified inference about the prevalence of population responses to human activities. Coexistence with and conservation of wildlife requires additional research linking human-induced phenotypic change to population and community outcomes. Methods To evaluate the evidence linking perceived risk from humans and associated phenotypic responses to downstream ecological consequences, we comprehensively reviewed the literature on human-induced NCEs and TMIEs. Papers evaluated in our comprehensive review were identified from three sources: 1) two Web of Science searches; 2) papers citing Frid and Dill (2002; https://doi.org/10.5751/ES-00404-060111*), 3) relevant papers found within review papers identified from (1) and (2). The specifics of the Web of Science searches are provided below. We initially scanned all papers for three criteria in a progressive manner; to advance, each paper had to be empirical, examine an effect of anthropogenic disturbance, and reference a topic related to risk. Papers meeting all three criteria were further filtered to those that evaluated a human-induced risk effect and tested for an effect beyond a phenotypic response (i.e. a change in fitness, fecundity, survival, density, abundance, or population growth). For these papers, we recorded the nature of the response, type of human-induced cue, species, system, and if a demographic effect was found. The scoring of these papers was led by one author and evaluated for accuracy by two other authors (including the lead author). Where disagreements arose, papers were further co-reviewed, with final decisions made by the lead author. Of 1769 papers reviewed, 92 tested for an NCE or TMIE, and only 57 linked this effect to an explicitly measured phenotypic response. Web of Science Search 1 "nonconsumptive" OR "non-consumptive" OR "ecology of fear" OR "landscape of fear" OR "trait mediated" OR "trait-mediated" OR "behaviorally mediated" OR "behaviorally-mediated" OR "interaction modification" OR "interaction-modification" OR "non-trophic interaction" OR "nontrophic interaction" AND: human OR anthropogenic OR recreat* OR hunt* OR disturbance OR "human footprint" OR roads OR "energy development" or infrastructure Web of Science Search 2 "sublethal" OR "sub-lethal" AND: human OR anthropogenic OR recreat* OR hunt* OR disturbance OR "human footprint" OR roads OR "energy development" or infrastructure AND: predat* OR risk OR fear NOT: pestic* OR herbic* OR toxi* OR chemic* OR salin* OR drug* OR radiat* OR nitr* OR lead OR caffeine OR pharma* OR plastic OR hypox* OR mercury NOT: "nonconsumptive" OR "non-consumptive" OR "ecology of fear" OR "landscape of fear" OR "trait-mediated" OR "trait mediated" OR "behaviorally mediated" OR "behaviorally-mediated" OR "interaction modification" OR "interaction-modification" OR "Non-trophic interaction" OR "nontrophic interaction" *Citations of: Frid, A. & Dill, L.M. (2002). Human-caused disturbance stimuli as a form of predation risk. Conservation Ecology, 6(1):11.

Demographic processes can substantially affect a species’ response to changing ecological conditions, necessitating the combined consideration of genetic responses to environmental variables and neutral genetic variation. Using a seascape genomics approach combined with population demographic modelling, we explored the interplay of demographic and environmental factors that shaped the current population structure in Indo-Pacific bottlenose dolphins (Tursiops aduncus) along most of the Western Australian coastline. We combined large-scale environmental data gathered via remote sensing with RADseq genomic data from 133 individuals at 19 sampling sites. Using population genetic and outlier detection anaylses, we identified three distinct genetic clusters, coinciding with tropical, subtropical and temperate provincial bioregions. In contrast to previous studies, our demographic models indicated that populations occupying the paleo-shoreline split into two demographically independent lineages before the last glacial maximum (LGM). A subsequent split after the LGM gave rise to the Shark Bay population, thereby creating the three currently observed clusters. Although multi-locus heterozygosity declined from north to south, dolphins from the southernmost cluster inhabiting temperate waters had higher heterozygosity in potentially adaptive loci, compared to dolphins from subtropical and tropical waters. These findings suggest ongoing adaptation to cold temperate waters in the southernmost cluster, possibly linked to distinct selective pressures between the different bioregions. Our study demonstrated that in the marine realm, without apparent physical boundaries, only a combined approach can fully elucidate the intricate environmental and genetic interactions shaping the evolutionary trajectory of marine mammals.

This dataset covers ballots 372-83 spanning January-December 1975. The dataset contains the data resulting from these polls in ASCII. The ballots are as follows: 372 - January This Gallup poll seeks the opinions of Canadians, on predominantly social issues. The questions ask opinions on topics such as pollution, married women and daycare. The respondents were also asked questions so that they could be grouped according to geographical variables. Topics of interest include: the amount of taxes; bad retail service; CBC programming; complaining about bad retail service; the dangers of pollution; whether or not daycare should be the responsibility of the government; liberalization of drinking laws; married women working; the perceived value of government services; the problems facing families; provinces separating from Canada; satisfaction with customer service; and the seriousness of pollution. Basic demographic variables are also included. 373 - February This Gallup poll seeks the opinions of Canadians, on both social and political issues. The questions ask opinions about political leaders and political issues within the country. There are also questions regarding farmers; Lent and drivers. The respondents were also asked questions so that they could be grouped according to geographical variables. Topics of interest include: the approval of labour unions; how fairly the government treat farmers; giving something up for Lent; government's record to date; opinions about Stanfield; opinions about Trudeau; pre-marital sex between couples; and preparing children for the future. Basic demographic variables are also included. 374 - March This Gallup poll seeks the opinions of Canadians, on predominantly social issues. The questions ask opinions about courts and capital punishment within the country. There are also questions on other topics of interest and importance to the country and government, such as racial intolerance, unemployment and inflation. The respondents were also asked questions so that they could be grouped according to geographical variables. Topics of interest include: bail for sex offenders; the benefits of the Syncrude project; community business conditions; fairness of courts; favouring capital punishment; the increase in racial intolerance; the minimum amount of income needed; the opinions about the Syncrude project; reducing inflation and unemployment; secret ballot voting for labour union strikes; and the use of corporal punishment. Basic demographic variables are also included. 375 - April This Gallup poll seeks the opinions of Canadians, on predominantly social issues. The questions ask opinions about whether or not Canada is heading towards a depression; violence on television and the emphasis of the 3 R's in high school. The respondents were also asked questions so that they could be grouped according to geographical variables. Topics of interest include: Arab investments in Canada; children watching violence on television; financial conditions; financial expectations; the emphasis high schools place on the 3 R's; House of Commons television coverage; permitting essential workers to strike; the personal effects of strikes; and the probability of having another depression in Canada. Basic demographic variables are also included. 376 - May This Gallup poll seeks the opinions of Canadians, on both political and social issues. The questions ask opinions about political leaders and political issues within the country. Questions regarding strikes, housework and Socialism are included. The respondents were also asked questions so that they could be grouped according to geographical variables. Topics of interest include: Canada becoming socialistic; the criticism of the Conservative opposition; the criticism of the Liberal government; husbands sharing in housework; irritating high priced purchases; opinions about the union leaders; who is responsible for the postal strike; the services that shouldn't be allowed to strike; strength of unions in 10 years; United Nations problem solving abilities; the U.S. financing Canadian development and Zionism as a form of racism. Basic demographic variables are also included. 377 - June This Gallup poll seeks the opinions of Canadians, on both political and social issues. The questions ask opinions about international topics such as U.S capital as well as preference for foreign countries. There are also questions on other topics of interest and importance to the country and government, such as inflation, shorter work weeks and curfews. The respondents were also asked questions so that they could be grouped according to geographical variables. Topics of interest include: the amount of money spent on food; approval of a shorter work week; Canada becoming a Republic; curfews for children under 16; the fairness of courts; fighting inflation; increasing immigration; liking of foreign countries; morality of birth control; having neighbours of a different descent; opposing immigrants from certain countries; parole for prisoners with records; preferred historical period; and U.S. capital investment in Canada. Basic demographic variables are also included. 378 - July This Gallup poll seeks the opinions of Canadians, on both political and social issues. The questions ask opinions about political leaders and political issues within the country, as well as throughout the world. There are also questions on other topics of interest and importance to the country and government, such as having a cashless society, abortions and strikes. The respondents were also asked questions so that they could be grouped according to geographical variables. Topics of interest include: having a cashless society; allowing teachers to go on strike; approving legal abortions; confidence in U.S. problem solving; the effectiveness of economic policies; the most important problem facing Canada; opinions about Turner; prohibiting small arms possession; registering of firearms; and the size of Canada's population. Basic demographic variables are also included. 379 - August This Gallup poll seeks the opinions of Canadians, on predominantly social issues. The questions ask opinions about the chances of atomic war; housing and night school. There are also questions on other topics of interest and importance to the country and government, such as political preferences and governmental spending. The respondents were also asked questions so that they could be grouped according to geographical variables. Topics of interest include: attending night school/part-time school; the biggest mistake ever made; the biggest threat to Canada; worker's productivity; the chances of atomic war; the closeness of student-teacher relationships; government cuts to programs; the most admired women; perception of relations between Canada and the United States; the quality of schools; recommendations for types of jobs; reducing government spending; satisfaction with current housing situation; types of courses taken in school; and type of employment. Basic demographic variables are also included. 380 - September This Gallup poll seeks the opinions of Canadians, on both political and social issues. The questions ask opinions about political leaders and political issues within the country. There are also questions on other topics of interest and importance to the country and government, such as metric conversions, religion and alternative energy resources. The respondents were also asked questions so that they could be grouped according to geographical variables. Topics of interest include: the approval of the maple leaf flag; approval of Trudeau as Prime Minister; the best alternative energy resource; causes of increased crime; difficulty of metric conversions; the influence of religion; level of interest in the Olympics; plans to attend the Olympic games; retirement plans; rising food prices; spelling tests; and types of beliefs. Basic demographic variables are also included. 381 - October This Gallup poll seeks the opinions of Canadians, on predominantly social issues. The questions ask opinions about the economy, rising prices and important problems within the country. There are also questions on other topics of interest and importance to the country and government, such as having a maximum highway speed and no fault divorce. The respondents were also asked questions so that they could be grouped according to geographical variables. Topics of interest include: the approval of no fault divorce; the causes of rising prices; compulsory price restraint; compulsory wage restraint; maximum highway speed; the most important problems facing Canada; whether or not the oil companies should setting gas prices; satisfaction levels; voluntary arbitration prior to striking; and women's liberation. Basic demographic variables are also included. 382 - November This Gallup poll seeks the opinions of Canadians, on both political and social issues. The questions ask opinions about having a female as the head of the Liberal party, as well as the PC candidates and other important political issues within the country. There are also questions on other topics of interest and importance to the country and government, such who produces the best television programs and future predictions for 1976. The respondents were also asked questions so that they could be grouped according to geographical variables. Topics of interest include: the Anti-Inflation Review Board; Christmas images; confidence in the government's handling of inflation; declared PC candidates; predictions for 1976; producing the best television programs; whether or not there would be support for the Federal party if their leader was a women; and wage and price controls. Basic demographic variables are also included. 383 - December This Gallup poll seeks the opinions of Canadians, on both political and social issues. The questions ask opinions about political leaders and political issues