Population variability across geographical ranges: perspectives and challenges.

Proc Biol Sci

Department of Biological Sciences, University of South Carolina, Columbia, SC 29208, USA.

Published: January 2025

Populations fluctuate over time and across geographical space, and understanding how different factors contribute to population variability is a central goal in population ecology. There is a particular interest in identifying trends of population variability within geographical ranges as population densities of species can fluctuate substantially across geographical space. A common assumption is that populations vary more near species geographical range edges because of unsuitable environments and higher vulnerability to environmental variability in these areas. However, empirical data rarely support this expectation, suggesting that population variability is not related to its position within species geographical ranges. We propose that performance curves, which describe the relationship between population growth rates and environmental conditions, can be used to disentangle geographical patterns of population variability. Performance curves are important for understanding population variability because populations fluctuate more in locations where they have lower growth rates owing to unsuitable environmental conditions. This is important for the assessment of these geographical patterns in population variability because geographical edges often do not reflect environmental edges. Considering species performance curves when evaluating geographical patterns of population variability would also allow researchers to detect populations that are more susceptible to future changes in environmental conditions.

Download full-text PDF

Source
http://dx.doi.org/10.1098/rspb.2024.1644DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11775592PMC

Publication Analysis

Top Keywords

population variability
32
variability geographical
12
geographical ranges
12
performance curves
12
environmental conditions
12
geographical patterns
12
patterns population
12
population
11
geographical
10
populations fluctuate
8

Similar Publications

Use of the FHTHWA Index as a Novel Approach for Predicting the Incidence of Diabetes in a Japanese Population Without Diabetes: Data Analysis Study.

JMIR Med Inform

January 2025

Department of Endocrinology and Metabolism, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.

Background: Many tools have been developed to predict the risk of diabetes in a population without diabetes; however, these tools have shortcomings that include the omission of race, inclusion of variables that are not readily available to patients, and low sensitivity or specificity.

Objective: We aimed to develop and validate an easy, systematic index for predicting diabetes risk in the Asian population.

Methods: We collected the data from the NAGALA (NAfld [nonalcoholic fatty liver disease] in the Gifu Area, Longitudinal Analysis) database.

View Article and Find Full Text PDF

Background: The systemic immune-inflammation index (SII) is an emerging marker of inflammation, and the onset of psoriasis is associated with inflammation. The aim of our study was to investigate the potential impact of SII on the incidence rate of adult psoriasis.

Methods: We conducted a cross-sectional study based on the National Health and Nutrition Examination Survey (NHANES) 2011-2014 data sets.

View Article and Find Full Text PDF

Background & Aim: Metabolic and cardiovascular health outcomes are strongly influenced by diet. Dietary habits established in early childhood may persist into adulthood. This study aimed to examine the association between dietary patterns at both 2 and 8 years of age, explaining the maximum variability of high- and low-quality fats, sugars, and fibre, and cardiometabolic markers at age 8 years.

View Article and Find Full Text PDF

Background: A common practice in assessment development, fundamental for fairness and consequently the validity of test score interpretations and uses, is to ascertain whether test items function equally across test-taker groups. Accordingly, we conducted differential item functioning (DIF) analysis, a psychometric procedure for detecting potential item bias, for three preclinical medical school foundational courses based on students' sex and race.

Methods: The sample included 520, 519, and 344 medical students for anatomy, histology, and physiology, respectively, collected from 2018 to 2020.

View Article and Find Full Text PDF

Background: The diagnosis of depression or anxiety treated by SSRIs has become relatively common in women of childbearing age. However, the impact of gestational SSRI treatment on newborn thyroid function is lacking. We explored the impact of gestational SSRI treatment on newborn thyroid function as measured by the National Newborn Screening (NBS) Program and identified contributory factors.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!