Narrow-sense Heritability Estimates Research Articles

Selective breeding enhances coral heat tolerance to marine heatwaves

Marine heatwaves are becoming more frequent, widespread and severe, causing mass coral bleaching and mortality. Natural adaptation may be insufficient to keep pace with climate warming, leading to calls for selective breeding interventions to enhance the ability of corals to survive such heatwaves, i.e., their heat tolerance. However, the heritability of this trait–a prerequisite for such approaches–remains unknown. We show that selecting parent colonies for high rather than low heat tolerance increased the tolerance of adult offspring (3–4-year-olds). This result held for the response to both 1-week +3.5 °C and 1-month +2.5 °C simulated marine heatwaves. In each case, narrow-sense heritability (h2) estimates are between 0.2 and 0.3, demonstrating a substantial genetic basis of heat tolerance. The phenotypic variability identified in this population could theoretically be leveraged to enhance heat tolerance by up to 1 °C-week within one generation. Concerningly, selective breeding for short-stress tolerance did not improve the ability of offspring to survive the long heat stress exposure. With no genetic correlation detected, these traits may be subject to independent genetic controls. Our finding on the heritability of coral heat tolerance indicates that selective breeding could be a viable tool to improve population resilience. Yet, the moderate levels of enhancement we found suggest that the effectiveness of such interventions also demands urgent climate action.

Heritability and Genetic Advance Studies on Fruit Yield and It’s Attributes Traits in Brinjal (Solanum melongena L.)

The present investigation was conducted at the Main Vegetable Research Station, Anand Agricultural University, Anand during the period of 2023-2024. The experimental material comprised twelve generations viz., P1, P2, F1, F2, B1, B2, B11, B12, B21, B22, B1S and B2S of four families involving eight diverse cultivars of brinjal (Solanum melongena L.) used to study the heritability and genetic advance of brinjal for yield and shoot and fruit borer incidence. The experiment was laid out in a compact family block design with three replications. Higher magnitude of heritability along with a higher value of genetic advance as per cent mean was estimated for day to first flowering in family 2, plant height in family 1 and family 4, leaf blade length in family 4, leaf blade width in family 2, fruit length in all families, fruit girth in family 3 and 4, fruit weight in all families expect to family 2, fruits per plant in family 2, fruit yield per plant in all families expect family 4 and shoot and fruit borer incidence in family 2 which suggested preponderance of additive gene effect. The higher value of heritability coupled with the higher value of genetic advance shows higher selection efficiency, permitting plant breeders to efficiently select individuals or groups of individuals. In crops like brinjal, high narrow sense heritability estimates are particularly beneficial for developing enhanced varieties through the fixation of additive gene effects.

Genetic and environmental contributions to the development of soft tissue facial profile: a twin study.

This study aimed to determine the relative contribution of genetic and environmental factors in the phenotypic variation of the soft tissue facial profile during the mixed dentition and the permanent dentition stages. In this retrospective cohort study, standardized facial profile photographs of 139 twin pairs (55 monozygotic and 84 dizygotic) were obtained from archival records at the Adelaide Dental School. Photographic analysis used 12 angular and 14 linear facial profile measurements from the mixed dentition (7-11 years) to the permanent dentition (12-17 years) stages. A genetic analysis was performed using a univariate structural equation model adhering to the normal assumptions of a twin model. In the mixed dentition stage, the additive genetic (A) and unique environment (E) model, AE model, was the most parsimonious in explaining the observed phenotypic variance for all 26 facial traits with the narrow-sense heritability estimates ranging between 0.38 and 0.79. In the permanent dentition, the AE model was the most parsimonious for 20 out of 26 traits, however, the variance of six traits, particularly those in the lower third of the face, was best explained by the shared environmental and unique environmental factors. This study exclusively included twins of European ancestry. The soft tissue facial profile demonstrated dynamic genetic and environmental influences with a greater additive genetic influence during the mixed dentition and the early stages of the permanent dentition. However, there was evidence of increasing environmental influence in the lower third of the face during the early stages of the permanent dentition.

Soybean pod shattering resistance allele pdh1 and marker-assisted selection.

Pod shattering is a major production constraint of soybean [Glycine max (L.)]. The objectives of this study were to (i) estimate heritability for pod shattering resistance, (ii) determine the frequency of the pod shattering resistance allele pdh1 in the International Institute for Tropical Agriculture (IITA) soybean germplasm and Zambian commercial varieties, and (iii) determine the effectiveness of the DNA marker for the pod shattering resistance allele pdh1. A total of 59 genotypes were evaluated for pod shattering in field trials conducted in Malawi and Zambia and genotyped with a marker for pdh1. TGx2002-8FM and TGx2002-9FM were the most resistant among genotypes in early and medium maturity classes and can be used for genetic enhancement of pod shattering resistance in these specific maturity classes. Narrow sense heritability estimates for pod shattering ranged from 0.27 to 0.80. Of the 59 genotypes, 57 (96.6%) carried the resistance allele pdh1 while only two genotypes (3.6%) carried the susceptible allele, suggesting near-fixation of the resistance allele pdh1 in the IITA germplasm. The marker for pdh1 was highly effective in selecting resistant genotypes.

Heritability and correlations for honey yield, handling ease, brood quantity, and traits related to resilience in a French honeybee population

There is growing interest in selective breeding of the honeybee, resulting in the emergence of new breeding projects, often with an emphasis on improving resilience traits, in particular toward brood diseases. Lately, feed autonomy is also gaining importance. Here, we use data from a small breeding nucleus in France to estimate genetic parameters for common bee breeding traits and a novel trait reflecting honey reserves in the brood chamber. Open-mated queens were produced each year from inseminated dams between 2019 and 2021, and ~330 colonies were phenotyped each following year at three periods during the entire beekeeping season. Genetic parameters were estimated using ReML with an animal model. Narrow-sense heritability estimates ranged from low (around 0.15) for calmness and total capped brood surface both measured in early summer, to moderate (0.30 to 0.40) for hygienic behavior in spring, honey yield, and phoretic V. destructor load in early summer. Honey reserves in the brood chamber showed an intermediate heritability throughout the season (around 0.25). Gentleness had a null heritability. Most correlations between phenotypes adjusted for environmental fixed effects were close to zero. Among exceptions, there were honey reserves in the brood chamber in early summer with honey yield (around −0.2) and with the total capped brood surface in early summer (around −0.3). These estimates, although uncertain due to the dataset size, suggest that selection for production and resilience will be effective, even though simultaneous selection for honey yield and feed reserves might be difficult due to a possible genetic antagonism between both traits.

Family resemblance in color-patch size is not affected by stress experience in a cichlid fish.

Animal body coloration is often linked to social dominance and mating success. This is because it can carry information on an animal's body condition and competitive ability by reflecting the genetic quality of individuals or by responding to their current or past living conditions. The present study investigates genetic and environmental effects on a conspicuous color pattern of the cichlid fish Tropheus sp. black "Ikola," in which the size of a carotenoid-based yellow area on the body co-varies with social dominance. To examine environmental plasticity of the color pattern, we tested for effects of early-life stress, induced by reduced feeding of juveniles prior to color pattern formation, as well as effects of a stress treatment administered to fully colored adult fish. None of the stress treatments affected the color pattern as quantified by the width of the yellow bar. However, offspring bar width was correlated to parental values in mid-parent-mid-offspring regression analyses, and animal models estimated significant additive genetic effects on bar width, indicating heritability of the trait. Depending on the random effects structure of the animal models (i.e., whether including or excluding maternal and brood effects), narrow-sense heritability estimates for bar width ranged between 0.2 and 0.8, with the strongest statistical support for the highest estimate. In each of the alternative models, a large proportion of the total variance in bar width was explained by the included random effects, suggesting that bar width is strongly determined by genetic factors or shared maternal and brood environments, with limited scope for environmental influences later in life.

Exploring the genetic basis of resistance to Neopestalotiopsis species in strawberry.

Aggressive strains of Neopestalotiopsis sp. have recently emerged as devastating pathogens of strawberry (Fragaria × ananassa Duchesne ex Rozier), infecting nearly all plant parts and causing severe outbreaks of leaf spot and fruit rot in Florida and globally. The development of host resistance is imperative due to the absence of fungicides that effectively inhibit Neopestalotiopsis sp. growth on an infected strawberry crop. Here, we analyzed 1578 individuals from the University of Florida's (UF) strawberry breeding program to identify and dissect genetic variation for resistance to Neopestalotiopsis sp. and to explore the feasibility of genomic selection. We found that less than 12% of elite UF germplasm exhibited resistance, with narrow-sense heritability estimates ranging from 0.28 to 0.69. Through genome-wide association studies (GWAS), we identified two loci accounting for 7%-16% of phenotypic variance across four trials and 3 years. Several candidate genes encoding pattern recognition receptors, intra-cellular nucleotide-binding leucine-rich repeats, and downstream components of plant defense pathways co-localized with the Neopestalotiopsis sp. resistance loci. Interestingly, favorable alleles at the largest-effect locus were rare in elite UF material and had previously been unintentionally introduced from an exotic cultivar. The array-based markers and candidate genes described herein provide the foundation for targeting this locus through marker-assisted selection. The predictive abilities of genomic selection models, with and without explicitly modeling peak GWAS markers as fixed effects, ranged between 0.25 and 0.59, suggesting that genomic selection holds promise for enhancing resistance to Neopestalotiopsis sp. in strawberry.

Evaluation of non-additive genetic effects on carcass and meat quality traits in Korean Hanwoo cattle using genomic models

The traditional genetic evaluation methods generally consider additive genetic effects only and often ignore non-additive (dominance and epistasis) effects that may have contributed to genetic variation of complex traits of livestock species. The available dense single nucleotide polymorphisms (SNPs) panels offer to investigate the potential benefits of including non-additive genetic effects in the genomic evaluation models. Data from 16 971 genotyped (Illumina Bovine 50 K SNP chip) Korean Hanwoo cattle were used to estimate genetic variance components and prediction accuracy of genomic breeding values (GEBVs) for four carcass and meat quality traits: carcass weight (CWT), eye muscle area (EMA), back fat thickness (BFT) and marbling score (MS). Five different genetic models were evaluated through including additive, dominance and epistatic interactions (additive by additive, A × A; additive by dominance, A × D and dominance by dominance, D × D) successively in the models. The estimates of additive genetic variances and narrow sense heritabilities (ha2) were found similar across the evaluated models and traits except when additive interaction (A × A) was included. The dominance variance estimates relative to phenotypic variance ranged from 1.7–3.4% for CWT and MS traits, whereas, they were close to zero for EMA and BFT traits. The magnitude of A × A epistatic heritability (haa2) ranged between 14.8 and 27.7% in all traits. However, heritability estimates for A × D and D × D epistatic interactions (had2 and hdd2) were quite low compared to haa2 and were contributed only 0.0–9.7% of the total phenotypic variation. In general, broad sense heritability (hG2) estimates were almost twice (ranging between 0.54 and 0.68) the ha2 for all of the investigated traits. The inclusion of dominance effects did not improve the prediction accuracy of GEBV but improved 2.0–3.0% when epistatic effects were included in the model. More importantly, rank correlation revealed that partitioning of variance components considering dominance and epistatic effects in the model would enable to re-rank of top animals with better prediction of GEBV. The present result suggests that dominance and epistatic effects could be included in the genomic evaluation model for better estimates of variance components and more accurate prediction of GEBV for carcass and meat quality traits in Korean Hanwoo cattle.

Investigating pedigree- and SNP-associated components of heritability in a wild population of Soay sheep

Estimates of narrow sense heritability derived from genomic data that contain related individuals may be biased due to the within-family effects such as dominance, epistasis and common environmental factors. However, for many wild populations, removal of related individuals from the data would result in small sample sizes. In 2013, Zaitlen et al. proposed a method to estimate heritability in populations that include close relatives by simultaneously fitting an identity-by-state (IBS) genomic relatedness matrix (GRM) and an identity-by-descent (IBD) GRM. The IBD GRM is identical to the IBS GRM, except relatedness estimates below a specified threshold are set to 0. We applied this method to a sample of 8557 wild Soay sheep from St. Kilda, with genotypic information for 419,281 single nucleotide polymorphisms. We aimed to see how this method would partition heritability into population-level (IBS) and family-associated (IBD) variance for a range of genetic architectures, and so we focused on a mixture of polygenic and monogenic traits. We also implemented a variant of the model in which the IBD GRM was replaced by a GRM constructed from SNPs with low minor allele frequency to examine whether any additive genetic variance is captured by rare alleles. Whilst the inclusion of the IBD GRM did not significantly improve the fit of the model for the monogenic traits, it improved the fit for some of the polygenic traits, suggesting that dominance, epistasis and/or common environment not already captured by the non-genetic random effects fitted in our models may influence these traits.

Identification of potential elephant grass hybrids for forage production via mixed models

Elephant grass has been widely used as forage because it is easier to become silage and because it has good nutritional indices. This research aimed to estimate the combining ability and analyze the genetic components of elephant grass (Pennisetum purpureum Schum. syn. Cenchrus purpureus) hybrids got from diallel crosses. Twenty-five elephant grass hybrids were obtained by a 5 x 5 partial diallel design, which were evaluated, at three harvests (January 2013, July 2013, and January 2014). Plants were grown in the field for three months before each harvest, taken for two harvests in the wet season (October to January) and one harvest in the dry season (May to July). The experiments were carried out in a randomized block design with 3 replications. Diallel analyzes were performed using a mixed model approach. There was high environment variance and low narrow-sense heritability for most traits. Narrow-sense heritability estimates were higher than 0.5 for leaf blade width. The combinations UENF38 x UENF3, UENF49 x UENF3, UENF49 x UENF37, UENF60 x UENF3 were selected for higher forage yield.

Spatial-extent inference for testing variance components in reliability and heritability studies

Abstract Clusterwise inference is a popular approach in neuroimaging to increase sensitivity, but most existing methods are currently restricted to the General Linear Model (GLM) for testing mean parameters. Statistical methods for testing variance components, which are critical in neuroimaging studies that involve estimation of narrow-sense heritability or test-retest reliability, are underdeveloped due to methodological and computational challenges, which would potentially lead to low power. We propose a fast and powerful test for variance components called CLEAN-V (CLEAN for testing Variance components). CLEAN-V models the global spatial dependence structure of imaging data and computes a locally powerful variance component test statistic by data-adaptively pooling neighborhood information. Correction for multiple comparisons is achieved by permutations to control family-wise error rate (FWER). Through analysis of task-functional magnetic resonance imaging (fMRI) data from the Human Connectome Project across five tasks and comprehensive data-driven simulations, we show that CLEAN-V outperforms existing methods in detecting test-retest reliability and narrow-sense heritability with significantly improved power, with the detected areas aligning with activation maps. The computational efficiency of CLEAN-V also speaks of its practical utility, and it is available as an R package.

Transforming Agriculture through Nanotechnology: A Comprehensive Overview

Nanotechnology has emerged as a transformative force in agriculture, offering innovative solutions to address critical challenges in food production, sustainability, and resource management. This comprehensive overview explores the multifaceted impact of nanotechnology on agriculture, providing insights into its potential to revolutionize the sector and by elucidating the fundamental principles of nanotechnology and its applicability in agriculture, emphasizing nanomaterials’ unique properties that enable precise manipulation at the molecular and nanoscale levels. It explores diverse applications, including nanoparticle-based nutrient delivery systems, nanoencapsulation for controlled release of agrochemicals, and the development of nanosensors for real-time monitoring of crop health and environmental parameters. Furthermore, this delves into the emerging field of precision farming enabled by nanotechnology, where data-driven decision-making and targeted interventions optimize resource utilization, minimize environmental impacts, and maximize crop yields. It examines the potential of nano pesticides in integrated pest management, highlighting their eco-friendly nature and reduced environmental contamination. Nanotechnology’s role in soil management and remediation is also discussed, showcasing its capacity to improve soil health, remediate contaminated lands, and enhance nutrient availability. The review sheds light on the application of nanofertilizers, which not only enhance nutrient use efficiency but also mitigate nutrient runoff, contributing to sustainable agriculture. While nanotechnology holds immense promise, it is imperative to consider safety and environmental implications. This examines the challenges and regulatory considerations surrounding the use of nanomaterials in agriculture, emphasizing the need for responsible development and rigorous risk assessment.

Evaluation of genomic prediction considering non-additive genetic effects on fatty acid traits of Japanese Black cattle.

Genomic prediction was conducted using 2494 Japanese Black cattle from Hiroshima Prefecture and both single-nucleotide polymorphism information and phenotype data on monounsaturated fatty acid (MUFA) and oleic acid (C18:1) analyzed with gas chromatography. We compared the prediction accuracy for four models (A, additive genetic effects; AD, as for A with dominance genetic effects; ADR, as for AD with the runs of homozygosity (ROH) effects calculated by ROH-based relationship matrix; and ADF, as for AD with the ROH-based inbreeding coefficient of the linear regression). Bayesian methods were used to estimate variance components. The narrow-sense heritability estimates for MUFA and C18:1 were 0.52-0.53 and 0.57, respectively; the corresponding proportions of dominance genetic variance were 0.04-0.07 and 0.04-0.05, and the proportion of ROH variance was 0.02. The deviance information criterion values showed slight differences among the models, and the models provided similar prediction accuracy.

Non-Destructive Evaluation of Downy and Silver Birch Wood Quality and Stem Features from a Progeny Trial in Southern Sweden

This study investigated whether improved downy birch could perform as well as improved silver birch, and whether there was sufficient genetic variation and control for non-destructive testing (NDT) values to include them as selection traits in breeding programs. NDT tools were applied to a 15-year-old downy birch family trial intermixed with improved silver birch. Average diameters, fissured bark height, and grain angle were higher for silver than downy birch. The genetic analysis for downy birch provided estimates of narrow-sense heritability (h2) for acoustic velocity and Pilodyn penetration depth that were above 0.3 but had low genetic variation. Grain angle had relatively high genetic variability (18%) and an h2 of 0.20. A subsample of 49 trees had 4 mm cores x-rayed for wood density estimates, and 34 stems had 12 mm cores macerated for cell measurements. t-tests revealed that average wood density and cell measurements were not significantly different between species. For silver and downy birch, fiber length and vessel length increased between inner and outer measurement positions, and fiber length was reasonably correlated with acoustic velocity. Silver birch tended to have denser and stiffer wood, while downy birch had less rough bark and straighter grain, and these results are in agreement with existing knowledge. The h2 values were similar to those observed in other birch species and indicate there is potential to breed for improved wood density and grain angle in downy birch.

Estimation of narrow sense heritability in early segregating generations of rice introgressed with Sub1 QTL

Estimation of narrow sense heritability in early segregating generations of rice introgressed with Sub1 QTL

A comparative analysis of agronomic water-use efficiency and its proxy measures as derived from key morpho-physiological and supportive quantitative genetics attributes of perennial ryegrass under imposed drought.

Water-use efficiency (WUE) is an under-researched but very important drought tolerance trait in forage breeding. This research estimated quantitative genetic parameters of morpho-physiological traits linked to agronomic water-use efficiency (WUEA) and its proxy measures based on δ13C (WUEi) or gas exchange (evapotranspiration, WUEAET, or stomatal conductance WUEASC) of genotypes from half-sib families of Lolium perenne L. (PRG) in a simulated summer drought cycle. Principal component analysis (PCA) of trait data distinguished a group of PRG genotypes where high WUEA and dry matter yield was associated with deep rooting, leaf hydration at more negative leaf osmotic and water potential, and reduced soil moisture depletion. Plants with this trait association sustained net assimilation and postdefoliation regrowth in drought. However, WUEi, WUEASC, and WUEAET were poorly correlated with most traits of interest at p < .05. Another PCA revealed a weak association between WUEA and its proxy measures under conditions tested. Quantitative genetic parameters including high estimates of narrow-sense heritability () of WUEA and related traits emphasized the genetic potential of the key trait combination for selecting PRG for improved drought tolerance. Research findings highlight the relative importance of WUEA and its proxy measures in the broad definition of PRG drought tolerance for breeding purposes.

Genetic Variances, Heritability and Traits Association of Early Maturing Maize Hybrids under Induced Drought at Seedling and Flowering Stages

Aims: Information on traits association and inheritance are crucial to designing appropriate breeding strategies for improving maize production and productivity in drought-prone ecologies. The objectives of this study were to investigate inter-trait relationships among maize hybrids and estimate genetic variances and heritability of drought tolerance parameters under seedling and flowering drought conditions.&#x0D; Methodology: Sixty-six single cross hybrids generated using diallel mating design plus nine hybrid checks were evaluated using a 5 x 15 alpha lattice and randomized complete block designs in three replicates on the field and in the screenhouse respectively, during 2015 cropping season. Data were collected on grain yield, ears per plant, anthesis-silking interval, seedling aspect, chlorophyll content and leaf area and these data were subjected to analysis of variance as well as correlation and path coefficient analyses.&#x0D; Results: Significant mean squares (P = .05) were observed for all measured traits except leaf area and shoot fresh weight. Narrow-sense heritability estimate for grain yield was moderate (33.4%) on the field and low (0 – 25%) for all the seedling traits. The low narrow-sense heritability estimates observed for most seedling traits implied that the scope for improvement of these traits in the genotypes is limited. Seedling traits under drought stress were not directly correlated with grain yield on the field except number of dead leaves relative to the total number of leaves. Results of the path analysis revealed that number of leaves, number of dead leaves and chlorophyll content under the screenhouse conditions had significant direct effects on grain yield on the field.&#x0D; Conclusion: Number of leaves, and chlorophyll content under drought at seedling stage could therefore be used as indicator traits for grain yield improvement in maize exposed to drought stress at flowering stage.

Genotype x environment interaction and climate sensitivity in growth and wood density of European larch

European larch is an ecologically and economically important tree species planted across a wide range of environments. Understanding its response to the rapidly changing climate is essential to developing efficient gene resource management strategies in line with the assisted migration methodology. In this study, we quantified the genotype x environment interaction (GxE) of a larch provenance in a multi-environmental trial analysis using factor analytic (FA) modeling. We analyzed the mean annual height increment (MAI-H), the mean annual diameter increment (MAI-DBH), and wood density (PP). Additionally, we evaluated the effect of several environmental variables on these traits. The genetic correlations between sites varied from −0.53 to 0.99, −0.87 to 0.99, and −0.17 to 0.99 for MAI-H, MAI-DBH, and PP, respectively. This indicates the presence of low to high GxE. The growth traits showed more GxE signal than wood density. Narrow-sense heritability estimates were 0.41, 0.16, and 0.35 for MAI-H, MAI-DBH, and PP, respectively. The FA modeling of order 2 explained 77.4%, 67.9%, and 77.3% of the genetic variance for MAI-H, MAI-DBH, and PP, respectively. For MAI-H, the latent regression plots for the predicted site means indicate a significant positive correlation with the first factor loading. At the individual genotype level, the latent regression plots indicated high levels of GxE, especially for growth traits. Significant and relatively high correlations were found between several EVs and the factor loadings of the FA models, suggesting their possible influence on the genotypic performance across environments. Regarding MAI-H, elevation, averaged monthly mean temperature, precipitation seasonality, and stand age were correlated with the first factor loading. Annual temperature range with both the first and second factor loadings. For MAI-DBH, the mean diurnal range was correlated with the first factor loading. In the case of PP, we found that elevation was correlated with the second factor loading. Overall, this approach successfully modeled the GxE and identified environmental variables likely affecting it. Therefore, we conclude that this methodology is a valuable tool for selecting suitable genotypes adapted to specific environmental conditions.

Evaluating a short vs. long-term progeny test and investigating physiology associated with survival in extreme low salinity for the eastern oyster Crassostrea virginica

Low salinity negatively affects growth and survival in the eastern oyster, which decreases productivity of aquaculture operations along the mid-Atlantic and Gulf Coasts of the United States. With heavy rainfall events predicted to become more frequent, coastal aquaculture operations face increased risk of prolonged exposure to extreme low salinity conditions. While recent experimental work has determined that survival in extreme low salinity (< 3) is a moderately heritable trait in the eastern oyster, further experimental challenges were conducted to investigate the importance of challenge duration and temperature on the survival phenotype and estimation of its genetic parameters to hone the experimental challenge for potential incorporation into a breeding program. Growth (shell height) and algal removal were also assessed to investigate physiological phenotypes associated with differential survival in extreme low salinity. A subset of individuals from 51 half-sibling families were exposed to one of two experimental challenges: a short-term low salinity (2.5) challenge at constant temperature (27 °C) for 2 months, or a long-term low salinity (2.5) challenge where temperature was adjusted daily to match local ambient conditions for 6-months. Differential mortality was observed across families for both the short-term and long-term low salinity challenges, and narrow-sense heritability estimates were similar for both challenges (short-term h2 = 0.35, long-term h2 = 0.4). Strong phenotypic (rS = 0.89) and genetic (rG = 0.81) correlations for family mortality were found between challenges. Algal clearance metrics over a 24-h clearance experiment differed among families (p < 0.001), but were only weakly associated with family survival in the long-term low salinity exposure (range p = 0.08–0.23, R2 = 5–10%). Growth was negligible during the long-term challenge. However, after being returned to ambient salinities (13), there was no difference in growth rate, wet weight gain, or mortality between oysters from families with low or high survival in the long-term exposure (p > 0.05), indicating that low salinity tolerant oysters can recover following low salinity events. This work shows that a short-term (2 month) low salinity (2.5) challenge at a constant temperature captures the same patterns of family mortality as a 6-month, temperature fluctuating challenge. Additionally, measuring individual oyster clearance rate and the parameters derived from the algal removal curves provide additional insight into the physiological status of oysters under extreme low salinity stress.

Genetic variability and &lt;i&gt;ex situ&lt;/i&gt; conservation strategies for the neotropical tree &lt;i&gt;Parkia platycephala&lt;/i&gt; Benth.

Parkia platycephala, known commonly as faveira, is a native species that occurs widely throughout Brazil and has high nutritional value and ecological potential. The objective of this study was to estimate the genetic variability in a P. platycephala provenance and progeny test. The test was established using a randomized block design, with 45 progenies from three provenances. The evaluated quantitative traits included height (HEI), diameter at ground level (DGL), and diameter below the first bifurcation (DFB). The data were submitted to Restricted Maximum Likelihood/Best Linear Unbiased Prediction (REML/BLUP) analysis, from which estimates of genetic parameters, genetic correlations, BLUPs, genetic gains, and effective population size were obtained. Estimates of individual narrow sense heritability (h2a) and within progeny heritability (h2w) ranged from low to moderate (0.01 a 0.39), with the highest values observed for DGL (0.32 and 0.39, respectively). The coefficient of individual variation (CVgi(%)) and between progeny genetic variation (CVgp(%)) indicate the existence of genetic variability between and within provenances. The FST vaues demonstrate low to moderate genetic differentiation among the three populations, and genetic correlations between traits were all positive and significant. The results obtained show that there is genetic variability between the studied provenances and progenies. This ensures not only the ex situ conservation of the species, but it can also be exploited in breeding programs.