Developmental Instability in Rhus copallinum L.: Multiple Stressors, Years, and Responses

2004 ◽  
Vol 165 (1) ◽  
pp. 53-63 ◽  
Author(s):  
D. Carl Freeman ◽  
Michelle L. Brown ◽  
Jeffrey J. Duda ◽  
John H. Graham ◽  
John M. Emlen ◽  
...  
Keyword(s):  
Multiple Stressors ◽  
Developmental Instability ◽  
Rhus Copallinum

Multiple Stressors: Literature Review and Gap analysis

2015 ◽  
Vol 3 (0) ◽  
pp. 9781780404257-9781780404257
Author(s):  
S. M. Swanson
Keyword(s):  
Literature Review ◽  
Gap Analysis ◽  
Multiple Stressors

Microbial Growth with Multiple Stressors

2013 ◽  
Vol 5 (3) ◽  
pp. 110-116
Author(s):  
Joan L. Slonczewski ◽  
James A. Coker ◽  
Shiladitya DasSarma
Keyword(s):  
Microbial Growth ◽  
Multiple Stressors

scholarly journals Effects of multiple stressors associated with agriculture on stream macroinvertebrate communities in a tropical catchment

PLoS ONE ◽  
2019 ◽  
Vol 14 (8) ◽  
pp. e0220528 ◽  
Author(s):  
Aydeé Cornejo ◽  
Alan M. Tonin ◽  
Brenda Checa ◽  
Ana Raquel Tuñon ◽  
Diana Pérez ◽  
...  
Keyword(s):  
Multiple Stressors ◽  
Macroinvertebrate Communities ◽  
Stream Macroinvertebrate

scholarly journals Fluctuating Asymmetry and Developmental Instability, a Guide to Best Practice

Symmetry ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 9
Author(s):  
John H. Graham
Keyword(s):  
Measurement Error ◽  
Best Practices ◽  
Environmental Stress ◽  
Fluctuating Asymmetry ◽  
Best Practice ◽  
Developmental Instability ◽  
The Past ◽  
Size Scaling ◽  
Research Designs

Best practices in studies of developmental instability, as measured by fluctuating asymmetry, have developed over the past 60 years. Unfortunately, they are haphazardly applied in many of the papers submitted for review. Most often, research designs suffer from lack of randomization, inadequate replication, poor attention to size scaling, lack of attention to measurement error, and unrecognized mixtures of additive and multiplicative errors. Here, I summarize a set of best practices, especially in studies that examine the effects of environmental stress on fluctuating asymmetry.

scholarly journals Nature, Nurture, and Noise: Developmental Instability, Fluctuating Asymmetry, and the Causes of Phenotypic Variation

Symmetry ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1204
Author(s):  
John H. Graham
Keyword(s):  
Fluctuating Asymmetry ◽  
Phenotypic Variation ◽  
Deterministic Chaos ◽  
Monozygotic Twins ◽  
Developmental Instability ◽  
Nonlinear Feedback ◽  
Developmental Variation ◽  
Sewall Wright ◽  
Developmental Noise ◽  
And Behavior

Phenotypic variation arises from genetic and environmental variation, as well as random aspects of development. The genetic (nature) and environmental (nurture) components of this variation have been appreciated since at least 1900. The random developmental component (noise) has taken longer for quantitative geneticists to appreciate. Here, I sketch the historical development of the concepts of random developmental noise and developmental instability, and its quantification via fluctuating asymmetry. The unsung pioneers in this story are Hugo DeVries (fluctuating variation, 1909), C. H. Danforth (random variation between monozygotic twins, 1919), and Sewall Wright (random developmental variation in piebald guinea pigs, 1920). The first pioneering study of fluctuating asymmetry, by Sumner and Huestis in 1921, is seldom mentioned, possibly because it failed to connect the observed random asymmetry with random developmental variation. This early work was then synthesized by Boris Astaurov in 1930 and Wilhelm Ludwig in 1932, and then popularized by Drosophila geneticists beginning with Kenneth Mather in 1953. Population phenogeneticists are still trying to understand the origins and behavior of random developmental variation. Some of the developmental noise represents true stochastic behavior of molecules and cells, while some represents deterministic chaos, nonlinear feedback, and symmetry breaking.

scholarly journals Cumulative Risks from Stressor Exposures and Personal Risk Factors in the Workplace: Examples from a Scoping Review

2021 ◽  
Vol 18 (11) ◽  
pp. 5850
Author(s):  
Mary A. Fox ◽  
Richard Todd Niemeier ◽  
Naomi Hudson ◽  
Miriam R. Siegel ◽  
Gary Scott Dotson
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Scoping Review ◽  
Multiple Stressors ◽  
Cumulative Risk ◽  
Real Life ◽  
Personal Factors ◽  
Exposure Limits ◽  
Personal Risk ◽  
Personal Risk Factors

Protecting worker and public health involves an understanding of multiple determinants, including exposures to biological, chemical, or physical agents or stressors in combination with other determinants including type of employment, health status, and individual behaviors. This has been illustrated during the COVID-19 pandemic by increased exposure and health risks for essential workers and those with pre-existing conditions, and mask-wearing behavior. Health risk assessment practices for environmental and occupational health typically do not incorporate multiple stressors in combination with personal risk factors. While conceptual developments in cumulative risk assessment to inform a more holistic approach to these real-life conditions have progressed, gaps remain, and practical methods and applications are rare. This scoping review characterizes existing evidence of combined stressor exposures and personal factors and risk to foster methods for occupational cumulative risk assessment. The review found examples from many workplaces, such as manufacturing, offices, and health care; exposures to chemical, physical, and psychosocial stressors combined with modifiable and unmodifiable determinants of health; and outcomes including respiratory function and disease, cancers, cardio-metabolic diseases, and hearing loss, as well as increased fertility, menstrual dysfunction and worsened mental health. To protect workers, workplace exposures and modifiable and unmodifiable characteristics should be considered in risk assessment and management. Data on combination exposures can improve assessments and risk estimates and inform protective exposure limits and management strategies.

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