Small-scale geographic differences in multiple-driver environmental variability can modulate contrasting phenotypic plasticity despite high levels of gene flow.

Sci Total Environ

Coastal Ecosystems & Global Environmental Change Lab (ECCALab), Faculty of Environmental Sciences, Universidad de Concepción, Concepción, Chile; Coastal Social-Ecological Millennium Institute (SECOS), Universidad de Concepción, Concepción, Chile; Millennium Institute of Oceanography (IMO), Universidad de Concepción, Concepción, Chile.

Published: December 2024

AI Article Synopsis

  • Climate change is impacting marine environments by altering their average conditions and the variability over time, affecting the adaptability of different species.
  • A study on mussels in Chilean Patagonia found that changes in environmental conditions, including extreme events, influence their physical traits while genetic differences remain minimal due to significant mixing from aquaculture.
  • The research highlights the importance of variability and predictability in shaping biological diversity, suggesting that managing these factors is vital for species resilience and biodiversity conservation in the face of climate change.

Article Abstract

Climate change is altering not only the mean conditions of marine environments, but also their temporal variability and predictability. As these alterations are not uniform across seascapes, their biological effects are expected to accentuate intra-specific differences in the adaptive capacity (e.g., plasticity and evolutionary potential) of natural populations. To test this theoretical framework, we assessed the phenotypic and genetic profiles of mussel from three study sites across a multi-driver heterogeneous environmental mosaic in Chilean Patagonia. Our study reveals that temporal variability, predictability, and exposure to extreme events (low pH/low salinity), collectively, can modulate the plasticity and optimal conditions of mussels. Despite these phenotypic differences, we observed low genetic differentiation, likely resulting from significant gene flow induced by aquaculture, ultimately diminishing variation among individuals from different geographic areas. Our findings underscore how variability and predictability are essential factors shaping phenotypic diversity, even at small spatial scales. Balancing these factors could enhance species resilience and ecological success, crucial for biodiversity conservation amidst climate change.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.scitotenv.2024.176772DOI Listing

Publication Analysis

Top Keywords

variability predictability
12
gene flow
8
climate change
8
temporal variability
8
small-scale geographic
4
geographic differences
4
differences multiple-driver
4
multiple-driver environmental
4
variability
4
environmental variability
4

Similar Publications

Incidence of fall-from-height injuries and predictive factors for severity.

J Osteopath Med

January 2025

McAllen Department of Trauma, South Texas Health System, McAllen, TX, USA.

Context: The injuries caused by falls-from-height (FFH) are a significant public health concern. FFH is one of the most common causes of polytrauma. The injuries persist to be significant adverse events and a challenge regarding injury severity assessment to identify patients at high risk upon admission.

View Article and Find Full Text PDF

Rationale: Obesity is an increasing medical issue not responding well to behavioural treatments beyond their initial weeks/months.

Aims And Objectives: Before suggesting surgical or pharmacological interventions, medical professionals might consider referrals to cost-effective, community-based behavioural treatments if stronger theoretical/empirical bases were demonstrated. Thus, evaluation of such is warranted.

View Article and Find Full Text PDF

Aims: According to the 2023 International Consensus, glucose metrics derived from two-week-long continuous glucose monitoring (CGM) can be extrapolated up to 90 days before. However, no studies have focused on adults with type 1 diabetes (T1D) on multiple daily injections (MDIs) and with second-generation intermittently scanned CGM (isCGM) sensors in a real-world setting.

Methods: This real-world, retrospective study included 539 90-day isCGM data from 367 adults with T1D on MDI therapy.

View Article and Find Full Text PDF

Study Question: How accurately can artificial intelligence (AI) models predict sperm retrieval in non-obstructive azoospermia (NOA) patients undergoing micro-testicular sperm extraction (m-TESE) surgery?

Summary Answer: AI predictive models hold significant promise in predicting successful sperm retrieval in NOA patients undergoing m-TESE, although limitations regarding variability of study designs, small sample sizes, and a lack of validation studies restrict the overall generalizability of studies in this area.

What Is Known Already: Previous studies have explored various predictors of successful sperm retrieval in m-TESE, including clinical and hormonal factors. However, no consistent predictive model has yet been established.

View Article and Find Full Text PDF

Objectives: This study was designed to characterize the prevalence, pattern of herbal use, and related factors among diabetic patients in Tabriz, Iran.

Methods: A descriptive cross-sectional study was carried out on 322 diabetic patients with random cluster sampling of specialized and subspecialized clinics in Tabriz, Iran. Binary logistic regression analysis was performed to evaluate the association between predictor variables (sociodemographic and disease-related characteristics and patient preference for treatment type) with herb use Interviews were conducted using a structured questionnaire from October 1, 2022, to April 23, 2023.

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!