Genetic variation and environmental variation: expectations and experiments

1988 ◽  
pp. 275-303 ◽  
Author(s):  
Janis Antonovics ◽  
Norman C. Ellstrand ◽  
Robert N. Brandon
Keyword(s):  
Genetic Variation ◽  
Environmental Variation

scholarly journals Testing for local adaptation and evolutionary potential along 1 altitudinal gradients in rainforest Drosophila: beyond laboratory estimates

2016 ◽  
Author(s):  
Eleanor K. O’Brien ◽  
Megan Higgie ◽  
Alan Reynolds ◽  
Ary A. Hoffmann ◽  
Jon R. Bridle
Keyword(s):  
Genetic Variation ◽  
Environmental Change ◽  
High Altitude ◽  
Local Adaptation ◽  
Biotic Interactions ◽  
Environmental Variation ◽  
Species Range ◽  
Altitudinal Gradients ◽  
Low Altitude ◽  
The Relationship

ABSTRACTPredicting how species will respond to the rapid climatic changes predicted this century is an urgent task. Species Distribution Models (SDMs) use the current relationship between environmental variation and species’ abundances to predict the effect of future environmental change on their distributions. However, two common assumptions of SDMs are likely to be violated in many cases: (1) that the relationship of environment with abundance or fitness is constant throughout a species’ range and will remain so in future, and (2) that abiotic factors (e.g. temperature, humidity) determine species’ distributions. We test these assumptions by relating field abundance of the rainforest fruit fly Drosophila birchii to ecological change across gradients that include its low and high altitudinal limits. We then test how such ecological variation affects the fitness of 35 D. birchii families transplanted in 591 cages to sites along two altitudinal gradients, to determine whether genetic variation in fitness responses could facilitate future adaptation to environmental change. Overall, field abundance was highest at cooler, high altitude sites, and declined towards warmer, low altitude sites. By contrast, cage fitness (productivity) increased towards warmer, lower altitude sites, suggesting that biotic interactions (absent from cages) drive ecological limits at warmer margins. In addition, the relationship between environmental variation and abundance varied significantly among gradients, indicating divergence in ecological niche across the species’ range. However, there was no evidence for local adaptation within gradients, despite greater productivity of high altitude than low altitude populations when families were reared under laboratory conditions. Families also responded similarly to transplantation along gradients, providing no evidence for fitness trade-offs that would favour local adaptation. These findings highlight the importance of (1) measuring genetic variation of key traits under ecologically relevant conditions, and (2) considering the effect of biotic interactions when predicting species’ responses to environmental change.

scholarly journals GENETIC VARIATION IN A HETEROGENEOUS ENVIRONMENT. I. TEMPORAL HETEROGENEITY AND THE ABSOLUTE DOMINANCE MODEL

Genetics ◽  
1974 ◽  
Vol 78 (2) ◽  
pp. 757-770
Author(s):  
Philip W Hedrick
Keyword(s):  
Genetic Variation ◽  
Temporal Variation ◽  
Gene Frequency ◽  
Environmental Heterogeneity ◽  
Finite Population ◽  
Environmental Variation ◽  
Dominance Model ◽  
Infinite Population ◽  
The Absolute ◽  
Absolute Dominance

ABSTRACT The conditions for a stable polymorphism and the equilibrium gene frequency in an infinite population are compared when there is spatial or temporal environmental heterogeneity for the absolute dominance model. For temporal variation the conditions for stability are more restrictive and the equilibrium gene frequency is often at a low gene frequency. In a finite population, temporal environmental heterogeneity for the absolute dominance model was found to be quite ineffective in maintaining genetic variation and is often less effective than no selection at all. For comparison, the maximum maintenance for temporal variation is related to the overdominant model. In general, cyclic environmental variation was found to be more effective at maintaining genetic variation than where the environment varies stochastically. The importance of temporal environmental variation and the maintenance of genetic variation is discussed.

Genetic and Environmental Variation of Ridge-Counts on Fingers, Palms, Soles and Toes: A Twin Study

1990 ◽  
Vol 33 (4) ◽  
pp. 531-546 ◽  
Author(s):  
R.L. Jantz ◽  
H. Brehme ◽  
K. Bender
Keyword(s):  
Genetic Variation ◽  
Genetic Correlation ◽  
Twin Study ◽  
Environmental Variation ◽  
Covariance Matrices ◽  
Twin Data ◽  
Correlation Matrices ◽  
Reciprocal Interaction ◽  
Genetic Components

AbstractA multivariate procedure for estimating heritable components from twin data was applied to ridge counts obtained from the entire dermatoglyphic system. Covariance matrices of MZ and DZ within-pair differences were used to estimate genetic correlation matrices for 20 finger ridge counts, 6 palmar interdigital counts, 20 toe counts, 4 hallucal counts, and 6 sole interdigital counts. The proportion of genetic variation was found to be greater in ridge counts of patterns than in ridge counts of interdigital areas. On digits, finger counts are more highly heritable than toe counts. Each of the dermatoglyphic areas yielded several independent genetic components, ranging from general to specific. Environmental variation was found to be local and to frequently involve reciprocal interaction between twin pairs.

Genotype-by-Environment Interactions for Seed Composition Traits of Breeding Lines in The Uniform Peanut Performance Test

2008 ◽  
Vol 35 (2) ◽  
pp. 130-138 ◽  
Author(s):  
T. G. Isleib ◽  
B. L. Tillman ◽  
H. E. Pattee ◽  
T. H. Sanders ◽  
K. W. Hendrix ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Fatty Acid ◽  
Oil Content ◽  
Environmental Variation ◽  
Genetic Influence ◽  
Environment Interaction ◽  
Genotype By Environment ◽  
Main Effects ◽  
Estimation Of Variance ◽  
Restricted Maximum Likelihood Estimation

Abstract Peanut composition is influenced by several groups of factors: environmental, genetic, and their interaction. This study evaluated the relative contributions of these factors using data from the USDA-ARS quality testing program using samples from the multi-state Uniform Peanut Performance Tests (UPPT). Data were subjected to restricted maximum likelihood estimation of variance components reflecting the main effects of year, production region, location within region, genotype (cultivar or breeding line), and kernel grade (“seed size”) within genotype, and the interactions among these main effects. Genetic variation in oil content was low (9% of total variation); however, fatty acid composition of the oil was highly influenced by genotype (34–77%) with the exception of lignoceric acid (1%). Genetic influence on tocopherols was generally less than that of fatty acids. Environmental variation of tocopherols was greater than the variation attributable to genotype-by-environment interaction. The lowest genetic variation was observed in sugar content; however, environmental variation was high (68%). The magnitude of genetic influence on oil content and fatty acid concentrations suggests that these traits are amenable to improvement through breeding.

scholarly journals Genetic variation in varying environments

1981 ◽  
Vol 37 (1) ◽  
pp. 79-93 ◽  
Author(s):  
Trudy F. C. Mackay
Keyword(s):  
Body Weight ◽  
Genetic Variation ◽  
Spatial Heterogeneity ◽  
Temporal Variation ◽  
Genetic Variance ◽  
Environmental Variability ◽  
Additive Genetic Variance ◽  
Environmental Variation ◽  
Heterogeneous Environments ◽  
Varying Environments

SUMMARYIn order to assess the relationship between genetic and environmental variability, a large natural population of Drosophila melanogaster was replicated as eight subpopulations, which were subjected to four different patterns of environmental variation. The environmental variable imposed was presence of 15% ethanol in the culture medium. Experimental treatments of the populations were intended to simulate constant environmental conditions, spatial heterogeneity in the environment, and two patterns of temporal environmental variation with different periodicity (long- and short-term temporal variation). Additive genetic and phenotypic variation in sternopleural and abdominal chaeta number, and body weight, were estimated in two successive years, and measurements were taken of the genotype–environment correlation of body weight and sternopleural bristle score with medium type.Additive genetic variance of sternopleural chaeta number and of body weight was significantly greater in the three populations experiencing environmental heterogeneity than in the control population, but additive genetic variance of abdominal bristle score was not clearly affected by exposing populations to varying environments. Temporal environmental variation was equally, if not more, efficient in promoting the maintenance of genetic variation than spatial heterogeneity, but the cycle length of the temporal variation was of no consequence. Specific genotype–environment interactions were not present, therefore adaptation to heterogeneous environments is by selection of heterozygosity per se, rather than by differential survival of genotypes in the alternate niches.

scholarly journals Does marine geospatial/environmental variation affect genetic variation? A meta-analysis

2021 ◽  
Author(s):  
◽  
Daniel Cárcamo
Keyword(s):  
Genetic Diversity ◽  
Genetic Variation ◽  
New Zealand ◽  
Genetic Variability ◽  
Genetic Distance ◽  
Meta Analysis ◽  
Environmental Variation ◽  
Environmental Data ◽  
Seascape Genetics ◽  
Species Specific

<p>Genetic information is important to inform management and conservation. However, few studies have tested the relationship between genetic variation and geospatial/environmental variation across marine species. Here, I test two genetics-based ideas in evolutionary theory using data from 55 New Zealand coastal marine taxa. The Core-Periphery Hypothesis (CPH) states that populations at the centre of a species’ distribution exhibit greater genetic variability than populations at the periphery (the ‘normal’ model). Variants of this model include the ‘ramped north’ (greatest variation in the north), the ‘ramped south’ (greatest variation in the south), and the ‘abundant edge’ (greatest variation at the distributional edges, least variation at the centre). The Seascape Genetics Test (SGT) null hypothesis predicts no association between genetic variation and environmental variation. I conducted a meta-analysis of published/unpublished material on population genetic connectivity and diversity and marine environmental data to test both hypotheses. To assess the CPH, genetic data were fitted to four models (Normal, Ramped North, Ramped South, Abundant Edge). I also conducted a descriptive analysis between the genetic outcomes of the CPH and abundance records for a subset of species. The SGT involved GLM analyses using eleven geospatial/environmental variables and species-specific FST-ΦST (genetic distance) estimates plus a smaller subset of genetic diversity data. The CPH results showed that 55 of 249 tests (evaluating on average 2.9 ± 1.3 genetic indices in each of the 84 studies) fitted at least one of the four models: Ramped North (10%), Ramped South (8%), Normal (2%) and Abundant Edge (2.4%). Species-specific abundance records followed the same patterns detected by the CPH. These results indicate that edge populations (Ramped North, Ramped South, Abundant Edge) exhibit greater genetic variability than central populations amongst marine taxa from New Zealand, but that most taxa do not conform to any model (~78% of all tests were not statistically significant). For the seascape genetics multi-species analysis (comprising 498 individual tests), the FST-ΦST estimates (genetic distance estimates between pairs of populations) were mostly affected by four factors related to sea surface temperature. For genetic diversity indices the most significant predictors were latitude and longitude. Whilst different factors (e.g., physical oceanography, food availability, life-history traits and harvesting), either acting alone or acting synergistically, are likely to be important in explaining patterns of genetic diversity in New Zealand’s marine coastal species, my results indicate that variables including SST and to a lesser extent the geospatial variables (latitude and longitude) explain much of the variation in the genetic indices tested here.</p>

scholarly journals Variability of Anthoxanthum species in Poland in relation to geographical-historical and environmental conditions: isozyme variation

2013 ◽  
Vol 30 (1) ◽  
pp. 63-93 ◽  
Author(s):  
Maria Drapikowska
Keyword(s):  
Genetic Variation ◽  
Gene Flow ◽  
Reproductive Isolation ◽  
Environmental Conditions ◽  
Habitat Type ◽  
Environmental Variation ◽  
Small Extent ◽  
Isozyme Variation ◽  
Isozyme Markers ◽  
Isozyme Variability

Abstract Variation of 9 isozyme systems was studied in Polish populations of 3 species of the genus Anthoxanthum: the native A. odoratum s. str. L. and A. alpinum Á. Löve & D. Löve, as well as the alien A. aristatum Boiss. Results of this study show that A. odoratum is characterized by a high isozyme variability of lowland populations, weakly correlated with habitat type, and partial genetic distinctness of montane populations. Moreover, 5 isozyme markers have been identified (Pgi-2, Dia-2, Mdh, Idh, Pgm) for the allopolyploid A. odoratum. Populations of A. aristatum are highly polymorphic (P = 98%). The observed isozyme differentiation of its populations (FST = 0.087) is low and gene flow between them (Nm = 5.314) is high. The genetic variation reflects environmental variation only to a small extent and is not significantly related to the phase of chorological expansion of this species. Altitudinal vicariants, A. alpinum and A. odoratum, are characterized by morphological and isozymatic distinctness, indicating their reproductive isolation. In populations of A. alpinum, polymorphism is high (P = 76.92%), differentiation among populations is moderate (FST = 0.198), and gene flow between populations along the altitudinal transect (Nm = 1.709) is relatively low

scholarly journals Genetic analysis of environmental variation

2010 ◽  
Vol 92 (5-6) ◽  
pp. 381-395 ◽  
Author(s):  
WILLIAM G. HILL ◽  
HAN A. MULDER
Keyword(s):  
Genetic Variation ◽  
Genetic Control ◽  
Genetic Variance ◽  
Environmental Variation ◽  
Alternative Methods ◽  
Trait Variation ◽  
Environmental Variance ◽  
Breeding Programmes ◽  
Genetic Coefficient Of Variation ◽  
Genetic Coefficient

SummaryEnvironmental variation (VE) in a quantitative trait – variation in phenotype that cannot be explained by genetic variation or identifiable genetic differences – can be regarded as being under some degree of genetic control. Such variation may be either between repeated expressions of the same trait within individuals (e.g. for bilateral traits), in the phenotype of different individuals, where variation within families may differ, or in both components. We consider alternative models for defining the distribution of phenotypes to include a component due to heterogeneity ofVE. We review evidence for the presence of genetic variation inVEand estimates of its magnitude. Typically the heritability ofVEis under 10%, but its genetic coefficient of variation is typically 20% or more. We consider experimental designs appropriate for estimating genetic variance inVEand review alternative methods of estimation. We consider the effects of stabilizing and directional selection onVEand review both the forces that might be maintaining levels ofVEand heritability found in populations. We also evaluate the opportunities for reducingVEin breeding programmes. Although empirical and theoretical studies have increased our understanding of genetic control of environmental variance, many issues remain unresolved.

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