Predicting the future trend and viability of populations is an essential task in ecology. Because many populations respond to changing environments, uncertainty surrounding environmental responses must be incorporated into population assessments. However, understanding the effects of environmental variation on population dynamics requires information on several important demographic parameters that are often difficult to estimate. Integrated population models facilitate the integration of time series data on population size and all existing demographic information from a species, allowing the estimation of demographic parameters for which limited or no empirical data exist. Although these models are ideal for assessments of population viability, they have so far not included environmental uncertainty. We incorporated environmental variation in an integrated population model to account for both demographic and environmental uncertainty in an assessment of population viability. In addition, we used this model to estimate true juvenile survival, an important demographic parameter for population dynamics that is difficult to estimate empirically. We applied this model to assess the past and future population trend of a rare island endemic songbird, the Montserrat Oriole Icterus oberi, which is threatened by volcanic activity. Montserrat Orioles experienced lower survival in years with volcanic ashfall, causing periodic population declines that were compensated by higher seasonal fecundity in years with high pre-breeding season rainfall. Due to the inclusion of both demographic and environmental uncertainty in the model, the estimated population growth rate in the immediate future was highly imprecise (95% credible interval 0.844-1.105), and the probability of extinction after three generations (in the year 2028) was low (2.1%). This projection demonstrates that accounting for both demographic and environmental sources of uncertainty provides a more realistic assessment of the viability of populations under unknown future environmental conditions.
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http://dx.doi.org/10.1890/13-0733.1 | DOI Listing |
Genet Epidemiol
January 2025
Department of Population and Public Health Sciences, Keck School of Medicine of the University of Southern California, Los Angeles, California, USA.
Gene-environment interactions have been observed for childhood asthma, however few have been assessed in ethnically diverse populations. Thus, we examined how polygenic risk score (PRS) modifies the association between ambient air pollution exposure (nitrogen dioxide [NO], ozone, particulate matter < 2.5 and < 10 μm) and childhood asthma incidence in a diverse cohort.
View Article and Find Full Text PDFArch Public Health
January 2025
Department of Biostatistics & Epidemiology, School of Public Health, Infectious Ophthalmologic Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Background: Cigarette smoking remains a significant public health concern, with detrimental effects on both smokers and those exposed to secondhand smoke. This study investigates the factors influencing smoking behaviors in Iranian households, focusing on households with children under five years old.
Methods: We conducted a cross-sectional analysis of 8751 Iranian households using data from the Iranian Household Income and Expenditure Survey (HIES) collected by the Statistical Center of Iran (SCI) in 2021.
BMC Nurs
January 2025
Department of Nursing Science, Faculty of Medicine, University of Malaya, Kuala Lumpur, 50603, Malaysia.
Background: Nursing is a caring profession for which compassion is a core value. Increasing stress and declining job satisfaction are among the major challenges in nursing. Demographic and work-related factors may influence nurses' compassion satisfaction and compassion fatigue (i.
View Article and Find Full Text PDFBMC Anesthesiol
January 2025
Kaiser Permanente Division of Research, 2000 Broadway, Oakland, CA, 94612, USA.
Background: Clinical determination of patients at high risk of poor surgical outcomes is complex and may be supported by clinical tools to summarize the patient's own personalized electronic health record (EHR) history and vitals data through predictive risk models. Since prior models were not readily available for EHR-integration, our objective was to develop and validate a risk stratification tool, named the Assessment of Geriatric Emergency Surgery (AGES) score, predicting risk of 30-day major postoperative complications in geriatric patients under consideration for urgent and emergency surgery using pre-surgical existing electronic health record (EHR) data.
Methods: Patients 65-years and older undergoing urgent or emergency non-cardiac surgery within 21 hospitals 2017-2021 were used to develop the model (randomly split: 80% training, 20% test).
Sci Rep
January 2025
British Trust for Ornithology, The Nunnery, Thetford, Norfolk, IP24 2PU, UK.
Understanding the distribution of breeding populations of migratory animals in the non-breeding period (migratory connectivity) is important for understanding their response to environmental change. High connectivity (low non-breeding population dispersion) may lower resilience to climate change and increase vulnerability to habitat loss within their range. Very high levels of connectivity are reportedly rare, but this conclusion may be limited by methodology.
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