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Summary: The dominance effect is a kind of non‐additive effect due to the interaction between alleles at the same locus. Quantitative traits such as growth traits in farm animals have been found to be influenced by dominance effects. However, dominance effects are usually ignored in the genome‐wide association study (GWAS) of complex traits for farm animals. In this study, we performed GWAS and genetic parameters estimation for the two traits age at 100 kg (AGE) and backfat thickness at 100 kg (BF) of 3572 Large White pigs. The pigs were from three breeding farms of China and were genotyped by an in‐house designed 50k SNP chip. Our results showed significant non‐zero variance for the dominance effect of AGE, while the dominance effect of BF was not significant. Using a GWAS model accounting for both additive and dominance effects, we identified three additive and two dominance significant SNPs for the trait AGE. For the trait BF, three genome‐wide significant additive SNPs were detected, but no significant SNP was found for the dominance effect. In total, six important functional genes (NPAS3, USP16, PARN, ARL15, GPC3, ABHD4) near significant SNPs were identified as candidate genes associated with AGE or BF. Notably, ARL15 and PARN were associated with AGE near the dominance association signals. Overall, the newly detected SNPs and newly identified candidate genes in our study added new information about the genetic architectures of growth and fatness traits in pigs, and have the potential to be applied to the pig breeding program in the future. [ABSTRACT FROM AUTHOR]

Nearly all organisms participate in multiple mutualisms, and complementarity within these complex interactions can result in synergistic fitness effects. However, it remains largely untested how multiple mutualisms impact eco‐evolutionary dynamics in interacting species. We tested how multiple microbial mutualists—N‐fixing bacteria and mycorrrhizal fungi—affected selection and heritability of traits in their shared host plant (Medicago truncatula), as well as fitness alignment between partners. Our results demonstrate for the first time that multiple mutualisms synergistically affect the selection and heritability of host traits and enhance fitness alignment between mutualists. Specifically, we found interaction with multiple microbial symbionts doubled the strength of natural selection on a plant architectural trait, resulted in 2‐ to 3‐fold higher heritability of plant reproductive success, and more than doubled fitness alignment between N‐fixing bacteria and plants. These findings show synergism generated by multiple mutualisms extends to key components of microevolutionary change, emphasising the importance of multiple mutualism effects on evolutionary trajectories. [ABSTRACT FROM AUTHOR]

Abstract: Humans are altering nutrient dynamics through myriad pathways globally. Concurrent with the addition of nutrients via municipal, industrial, and agricultural sources, widespread consumer exploitation is changing consumer‐mediated nutrient dynamics drastically. Thus, altered nutrient dynamics can occur through changes in the supply of multiple nutrients, as well as through changes in the sources of these nutrients. Seagrass ecosystems are heavily impacted by human activities, with highly altered nutrient dynamics from multiple causes. We simulate scenarios of altered nutrient supply and ratios, nitrogen:phosphorus (N:P), from two nutrient sources in seagrass ecosystems: anthropogenic fertilizer and fish excretion. In doing so we tested expectations rooted in ecological theory that suggest the importance of resource dynamics for predicting primary producer dynamics. Ecosystem functions were strongly altered by artificial fertilizer (e.g., seagrass growth increased by as much as 140%), whereas plant/algae community structure was most affected by fish‐mediated nutrients or the interaction of both treatments (e.g., evenness increased by ~140% under conditions of low fish nutrients and high anthropogenic nutrients). Interactions between the nutrient sources were found for only two of six response variables, and the ratio of nutrient supply was the best predictor for only one response. These findings show that seagrass structure and function are well predicted by supply of a single nutrient (either N or P). Importantly, no single nutrient best explained the majority of responses—measures of community structure were best explained by the primary limiting nutrient to this system (P), whereas measures of growth and density of the dominant producer in the system were best explained by N. Thus, while our findings support aspects of theoretical expectations, the complexity of producer community responses belies broad generalities, underscoring the need to manage for multiple simultaneous nutrients in these imperiled coastal ecosystems. [ABSTRACT FROM AUTHOR]

Abstract: Aim: Ecological models that do not account for interactions among stressors, if interactions are important, could be inaccurate and lead to inefficient conservation strategies. Conversely, if interactions are not important (i.e., stressors operate largely independently), then actions concentrating on a stressor‐by‐stressor basis would be warranted. Here, we investigated whether interactions among multiple stressors affected widely used indices of freshwater macroinvertebrate biodiversity, which are sensitive to environmental change at management‐relevant scales (i.e., reaches and catchments). Location: State of Victoria, south‐eastern Australia. Methods: We used a 7,418‐sample dataset for stream macroinvertebrates from 2,165 sites distributed over 237,630 km2 for 20 years. We calculated the interactive effects on stream macroinvertebrates of stressors operating at different scales, namely vegetation loss at the catchment and reach scales and hydrological change and salinization at the local scale. The importance of interactions among multiple stressors was assessed by comparing the cross‐validated predictive performance of models with and without multiple stressor interaction terms. Results: Cross‐validated models explained 31%–63% of the variation in the macroinvertebrate responses. The most important stressors were catchment vegetation loss (the proportion of remaining native vegetation cover) and salinity. The inclusion of interaction terms did not increase cross‐validated predictive performance, which indicates that there was little evidence that interactions among stressors were important for explaining variation in commonly used freshwater macroinvertebrate condition indices. Main conclusions: Interactions among vegetation, salinity and hydrological change stressors may not always be of importance for determining patterns of stream macroinvertebrate biodiversity, so that such interactions may not necessarily be critical considerations for catchment and reach scale management, at least if based on these or comparable condition indices. The mitigation of the impacts of vegetation loss, salinization and hydrological change stressors one‐by‐one probably is sufficient to guide conservation activities and might be advantageous if socio‐political contexts make it difficult to address interactions among stressors. [ABSTRACT FROM AUTHOR]

Juvenile Atlantic salmon Salmo salar from three allopatric populations ( LaHave, Sebago and Saint-Jean) were placed into artificial streams with combinations of four non-native salmonids: brown trout Salmo trutta, rainbow trout Oncorhynchus mykiss, Chinook salmon Oncorhynchus tshawytscha and coho salmon Oncorhynchus kisutch. Non-additive effects, as evidenced by lower performance than predicted from weighted summed two-species competition trials, were detected for S. salar fork length ( LF) and mass, but not for survival, condition factor or riffle use. These data support emerging theory on niche overlap and species richness as factors that can lead to non-additive competition effects. [ABSTRACT FROM AUTHOR]

It is often recognized, but seldom addressed, that a quantitative assessment of the cumulative effects, both additive and non-additive, of multiple stressors on fish survival would provide a more realistic representation of the factors that influence fish migration. This review presents a compilation of analytical methods applied to a well-studied fish migration, a more general review of quantitative multivariable methods, and a synthesis on how to apply new analytical techniques in fish migration studies. A compilation of adult migration papers from Fraser River sockeye salmon Oncorhynchus nerka revealed a limited number of multivariable methods being applied and the sub-optimal reliance on univariable methods for multivariable problems. The literature review of fisheries science, general biology and medicine identified a large number of alternative methods for dealing with cumulative effects, with a limited number of techniques being used in fish migration studies. An evaluation of the different methods revealed that certain classes of multivariable analyses will probably prove useful in future assessments of cumulative effects on fish migration. This overview and evaluation of quantitative methods gathered from the disparate fields should serve as a primer for anyone seeking to quantify cumulative effects on fish migration survival. [ABSTRACT FROM AUTHOR]