The prediction accuracy of estimated breeding values using traditional best linear unbiased prediction (PBLUP) and single-step genomic BLUP (ssGBLUP) methods was investigated in two breeding populations of Litopenaeus vannamei, using simulated data with varying levels of marker density. Additionally, the impact of the number of generations with phenotypic and genotypic data on the prediction accuracy was also investigated.The simulated breeding populations consisted of 25 families with 40 animals each, or 50 families with 20 animals each. Each population consisted of 20 non-overlapping generations, with 1000 animals per generation. Only the last ten generations were genotyped, and phenotypes and pedigrees were available for all the animals. Phenotypes from the 20th generation were masked in data analysis to mimic the selection of young animals without phenotypes. A trait with a heritability of 0.1 was simulated, and 100 % of the genetic variance was explained by 1000 QTLs evenly distributed across chromosomes and randomly located across the genome. Genomic information consisted of 44 chromosomes that mimicked the genome structure of L. vannamei, with 6, 11, 22, 45, and 90 K markers evenly distributed across the 44 chromosomes.Results indicated that expanding family sizes with fewer family numbers improved the prediction accuracy in both PBLUP and ssGBLUP. In all scenarios, ssGBLUP outperformed PBLUP in terms of the prediction accuracy. The greater the number of generations of data in which genotypes and phenotypes were included in the ssGBLUP approach, the better the prediction accuracy. However, genotyping for more than six generations did not substantially improve prediction accuracy. Additionally, maximum accuracy was achieved with 45 K SNPs in both scenarios, with no substantial improvement in accuracy by increasing the marker density to 90 K. Overall, more accurate predictions were obtained with ssGBLUP with more genotyped animals per family and could be a suitable method for genomic selection for traits with low heritability in L. vannamei.

We’ve now seen the principles underlying Wright’s F -statistics. I should point out that Gustave Malécot developed very similar ideas at about the same time as Wright, but since Wright’s notation stuck, population geneticists generally refer to statistics like those we’ve discussed as Wright’s F -statistics. Neither Wright nor Malécot worried too much about the problem of estimating F statistics from data. Both realized that any inferences about population structure are based on a sample and that the characteristics of the sample may differ from those of the population from which it was drawn, but neither developed any explicit way of dealing with those differences. Wright develops some very ad hoc approaches in his book [9], but they have been forgotten, which is good because they aren’t very satisfactory and they shouldn’t be used. There are now two reasonable approaches available:

ABSTRACTPlants differ from one another in size, architecture, water relations, and resource uptake, and these differences often lead to differences in performance. Yet within a community species that differ markedly in these traits often have similar performance. Here we use a simple model to show that when the major axes of trait covariation do not align with the axis of performance variation, large differences among species in structural traits may have similar performance, i.e., ‘alternative designs.’ We further illustrate this phenomenon using trait and performance data from co-occurringProteaspecies in the Cape Floristic Region, South Africa. Long-term coexistence of species within a community requires both similar levels of performance, so that some species are not excluded by competition, and niche differentiation, so that multiple species can coexist. Thus, misalignment between the axis of performance variation and the major axes of trait variation may be common, just as genetic variation may be maintained within a population when the selection gradient does not align with the major axes of the genetic variance-covariance matrix.

Climate change is affecting species composition and diversity across the globe. Phenological changes provide a sensitive indicator of biological responses to changes in climate. Recent studies using herbarium records in Europe and North America have shown changes in flowering time and other phenological events in response to changing climate conditions, such as warming temperatures and chilling winters, but few studies have been carried out in the southern hemisphere. We examined changes in flowering time from 1901–2009 in South Africa in the widespread, diverse genus Pelargonium. We combined records from more than 6,200 herbarium specimens of 129 species with historical weather data on temperature to examine the impact of climate change on flowering phenology. Data from over 464 weather stations in South Africa was used to estimate historical climate conditions for each of the 4,600 geographic sites included in our sample. During this time period there was a 2.9 ± 0.53 °C increase in mean annual temperature across South Africa. Flowering date advanced by nearly two weeks (11.6 days), with nearly all of the advance associated with the increase in temperature during this time. Thus, Pelargonium species are showing similar phenological responses when compared to species in the northern hemisphere. This study adds more evidence to the limited number of studies of climate change responses within Mediterranean climate regions that assess large-scale climate and phenological patterns. It also illustrates that herbarium records provide an effective method for detecting effects of climate change on flowering phenology across large geographic scales.

PREMISE:The distribution of genetic diversity on the landscape has critical ecological and evolutionary implications. This may be especially the case on a local scale for foundation plant species because they create and define ecological communities, contributing disproportionately to ecosystem function.METHODS:We examined the distribution of genetic diversity and clones, which we defined first as unique multilocus genotypes (MLG), and then by grouping similar MLGs into multilocus lineages. We used 186 markers from inter-simple sequence repeats (ISSR) across 358 ramets from 13 patches of the foundation grass Leymus chinensis. We examined the relationship between genetic and clonal diversities, their variation with patch size, and the effect of the number of markers used to evaluate genetic diversity and structure in this species.RESULTS:Every ramet had a unique MLG. Almost all patches consisted of individuals belonging to a single multilocus lineages. We confirmed this with a clustering algorithm to group related genotypes. The predominance of a single lineage within each patch could be the result of the accumulation of somatic mutations, limited dispersal, some sexual reproduction with partners mainly restricted to the same patch, or a combination of all three.CONCLUSIONS:We found strong genetic structure among patches of L. chinensis. Consistent with previous work on the species, the clustering of similar genotypes within patches suggests that clonal reproduction combined with somatic mutation, limited dispersal, and some degree of sexual reproduction among neighbors causes individuals within a patch to be more closely related than among patches.

Conserving biodiversity in an era of rapid climate change requires understanding the mechanisms that influence dispersal, gene flow and, ultimately, species persistence. This information is becoming critical for conserving key species in rapidly warming places such as the Arctic. Arctic freshwater fish not only face warmer conditions, but also the drying of tundra streams due to climate change. Here, we examined population structure, gene flow, and the influence of landscape features on the neutral genetic variation of the Arctic grayling on Alaska's North Slope. We estimated the number of genetically distinct clusters and determined effective population sizes for and patterns of gene flow among geographic regions. We predicted that river distance, river drying, distance to the coast, and elevational gradient would influence genetic differentiation for Arctic grayling. Bayesian clustering and discriminant analysis of principal components found support for five or six genetic clusters roughly corresponding to downstream and headwater subwatersheds. Estimates of gene flow revealed asymmetric downstream bias. River distance and river dry zones were significantly associated with increasing genetic differentiation among sampling locations despite this species' high dispersal capability and the temporary nature of dry zones. Isolation and downstream-biased dispersal could contribute to high levels of inter-population genetic variation among the headwaters of the North Slope Arctic grayling metapopulation, which might be particularly important for species conservation during rapid climate change. More generally, small, isolated populations might drive particular alleles to higher frequencies due to selection or drift, thus promoting the genetic potential for rapid evolutionary changes under future climate change.

BACKGROUND AND AIMS:Global plant trait datasets commonly identify trait relationships that are interpreted to reflect fundamental trade-offs associated with plant strategies, but often these trait relationships are not identified when evaluating them at smaller taxonomic and spatial scales. In this study we evaluate trait relationships measured on individual plants for five widespread Protea species in South Africa to determine whether broad-scale patterns of structural trait (e.g. leaf area) and physiological trait (e.g. photosynthetic rates) relationships can be detected within natural populations, and if these traits are themselves related to plant fitness. METHODS:We evaluated the variance structure (i.e. the proportional intraspecific trait variation relative to among-species variation) for nine structural traits and six physiological traits measured in wild populations. We used a multivariate path model to evaluate the relationships between structural traits and physiological traits, and the relationship between these traits and plant size and reproductive effort. KEY RESULTS:While intraspecific trait variation is relatively low for structural traits, it accounts for between 50 and 100 % of the variation in physiological traits. Furthermore, we identified few trait associations between any one structural trait and physiological trait, but multivariate regressions revealed clear associations between combinations of structural traits and physiological performance (R2 = 0.37-0.64), and almost all traits had detectable associations with plant fitness. CONCLUSIONS:Intraspecific variation in structural traits leads to predictable differences in individual-level physiological performance in a multivariate framework, even though the relationship of any particular structural trait to physiological performance may be weak or undetectable. Furthermore, intraspecific variation in both structural and physiological traits leads to differences in plant size and fitness. These results demonstrate the importance of considering measurements of multivariate phenotypes on individual plants when evaluating trait relationships and how trait variation influences predictions of ecological and evolutionary outcomes.

PREMISE OF THE STUDY Plant traits are often associated with the environments in which they occur, but these associations often differ across spatial and phylogenetic scales. Here we study the relationship between microenvironment, microgeographical location, and traits within populations using co-occurring populations of two closely related evergreen shrubs in the genus Protea. METHODS We measured a suite of functional traits on 147 plants along a single steep mountainside where both species occur, and we used data-loggers and soil analyses to characterize the environment at 10 microsites spanning the elevational gradient. We used Bayesian path analyses to detect trait-environment relationships in the field for each species. We used complementary data from greenhouse grown seedlings derived from wild collected seed to determine whether associations detected in the field are the result of genetic differentiation. KEY RESULTS Microenvironmental variables differed substantially across our study site. We found strong evidence for six trait-environment associations, although these differed between species. We were unable to detect similar associations in greenhouse-grown seedlings. CONCLUSIONS Several leaf traits were associated with temperature and soil variation in the field, but the inability to detect these in the greenhouse suggests that differences in the field are not the result of genetic differentiation.

Evolutionary radiations are responsible for much of Earth's diversity, yet the causes of these radiations are often elusive. Determining the relative roles of adaptation and geographic isolation in diversification is vital to understanding the causes of any radiation, and whether a radiation may be labeled as "adaptive" or not. Across many groups of plants, trait-climate relationships suggest that traits are an important indicator of how plants adapt to different climates. In particular, analyses of plant functional traits in global databases suggest that there is an "economics spectrum" along which combinations of functional traits covary along a fast-slow continuum. We examine evolutionary associations among traits and between trait and climate variables on a strongly supported phylogeny in the iconic plant genus Protea to identify correlated evolution of functional traits and the climatic-niches that species occupy. Results indicate that trait diversification in Protea has climate associations along two axes of variation: correlated evolution of plant size with temperature and leaf investment with rainfall. Evidence suggests that traits and climatic-niches evolve in similar ways, although some of these associations are inconsistent with global patterns on a broader phylogenetic scale. When combined with previous experimental work suggesting that trait-climate associations are adaptive in Protea, the results presented here suggest that trait diversification in this radiation is adaptive.

PREMISE OF THE STUDY Estimating phylogenetic relationships in relatively recent evolutionary radiations is challenging, especially if short branches associated with recent divergence result in multiple gene tree histories. We combine anchored enrichment next-generation sequencing with species tree analyses to produce a robust estimate of phylogenetic relationships in the genus Protea (Proteaceae), an iconic radiation in South Africa. METHODS We sampled multiple individuals within 59 out of 112 species of Protea and 6 outgroup species for a total of 163 individuals, and obtained sequences for 498 low-copy, orthologous nuclear loci using anchored phylogenomics. We compare several approaches for building species trees, and explore gene tree-species tree discrepancies to determine whether poor phylogenetic resolution reflects a lack of informative sites, incomplete lineage sorting, or hybridization. KEY RESULTS Phylogenetic estimates from species tree approaches are similar to one another and recover previously well-supported clades within Protea, in addition to providing well-supported phylogenetic hypotheses for previously poorly resolved intrageneric relationships. Individual gene trees are markedly different from one another and from species trees. Nonetheless, analyses indicate that differences among gene trees occur primarily concerning clades supported by short branches. CONCLUSIONS Species tree methods using hundreds of nuclear loci provided strong support for many previously unresolved relationships in the radiation of the genus Protea. In cases where support for particular relationships remains low, these appear to arise from few informative sites and lack of information rather than strongly supported disagreement among gene trees.

Better understanding and prediction of tree growth is important because of the many ecosystem services provided by forests and the uncertainty surrounding how forests will respond to anthropogenic climate change. With the ultimate goal of improving models of forest dynamics, here we construct a statistical model that combines complementary data sources – tree-ring and forest inventory data. A Bayesian hierarchical model is used to gain inference on the effects of many factors on tree growth – individual tree size, climate, biophysical conditions, stand-level competitive environment, tree-level canopy status, and forest management treatments – using both diameter at breast height (DBH) and tree-ring data. The model consists of two multiple regression models, one each for the two data sources, linked via a constant of proportionality between coefficients that are found in parallel in the two regressions. The model was applied to a dataset developed at a single, well-studied site in the Jemez Mountains of north-central New Mexico, U. S. A. Inferences from the model included positive effects of seasonal precipitation, wetness index, and height ratio, and negative effects of seasonal temperature, southerly aspect and radiation, and plot basal area. Climatic effects inferred by the model compared well to results from a dendroclimatic analysis. Combining the two data sources did not lead to higher predictive accuracy (using the leave-one-out information criterion, LOOIC), either when there was a large number of increment cores (129) or under a reduced data scenario of 15 increment cores. However, there was a clear advantage, in terms of parameter estimates, to the use of both data sources under the reduced data scenario: DBH remeasurement data for ~500 trees substantially reduced uncertainty about non-climate fixed effects on radial increments. We discuss the kinds of research questions that might be addressed when the high-resolution information on climate effects contained in tree rings are combined with the rich metadata on tree- and stand-level conditions found in forest inventories, including carbon accounting and projection of tree growth and forest dynamics under future climate scenarios.

PREMISE OF THE STUDY:The Cape Floristic Region (CFR) of South Africa is renowned for its botanical diversity, but the evolutionary origins of this diversity remain controversial. Both neutral and adaptive processes have been implicated in driving diversification, but population-level studies of plants in the CFR are rare. Here, we investigate the limits to gene flow and potential environmental drivers of selection in Protea repens L. (Proteaceae L.), a widespread CFR species.METHODS:We sampled 19 populations across the range of P. repens and used genotyping by sequencing to identify 2066 polymorphic loci in 663 individuals. We used a Bayesian FST outlier analysis to identify single-nucleotide polymorphisms (SNPs) marking genomic regions that may be under selection; we used those SNPs to identify potential drivers of selection and excluded them from analyses of gene flow and genetic structure.RESULTS:A pattern of isolation by distance suggested limited gene flow between nearby populations. The populations of P. repens fell naturally into two or three groupings, which corresponded to an east-west split. Differences in rainfall seasonality contributed to diversification in highly divergent loci, as do barriers to gene flow that have been identified in other species.CONCLUSIONS:The strong pattern of isolation by distance is in contrast to the findings in the only other widespread species in the CFR that has been similarly studied, while the effects of rainfall seasonality are consistent with well-known patterns. Assessing the generality of these results will require investigations of other CFR species.

PREMISE OF THE STUDY: American bipolar plant distributions characterize taxa at various taxonomic ranks but are most common in the bryophytes at infraspecific and infrageneric levels. A previous study on the bipolar disjunction in the dung moss genus Tetraplodon found that direct long‐distance dispersal from North to South in the Miocene–Pleistocene accounted for the origin of the Southern American endemic Tetraplodon fuegianus , congruent with other molecular studies on bipolar bryophytes. The previous study, however, remained inconclusive regarding a specific northern hemisphere source region for the transequatorial dispersal event that gave rise to T. fuegianus . METHODS: To estimate spatial genetic structure and phylogeographic relationships within the bipolar lineage of Tetraplodon , which includes T. fuegianus , we analyzed thousands of restriction‐site‐associated DNA (RADseq) loci and single nucleotide polymorphisms using Bayesian individual assignment and maximum likelihood and coalescent model based phylogenetic approaches. KEY RESULTS: Northwestern North America is the most likely source of the recent ancestor to T. fuegianus . CONCLUSIONS: Tetraplodon fuegianus , which marks the southernmost populations in the bipolar lineage of Tetraplodon , arose following a single long‐distance dispersal event involving a T. mnioides lineage that is now rare in the northern hemisphere and potentially restricted to the Pacific Northwest of North America. Furthermore, gene flow between sympatric lineages of Tetraplodon mnioides in the northern hemisphere is limited, possibly due to high rates of selfing or reproductive isolation.

File List Supplement2Code.r Description The code is commented throughout (following pound signs, ###). A path must be specified to the Bugs output files.

BACKGROUND AND AIMS:Trait-environment relationships are commonly interpreted as evidence for local adaptation in plants. However, even when selection analyses support this interpretation, the mechanisms underlying differential benefits are often unknown. This study addresses this gap in knowledge using the broadly distributed South African shrub Protea repens. Specifically, the study examines whether broad-scale patterns of trait variation are consistent with spatial differences in selection and ecophysiology in the wild.METHODS:In a common garden study of plants sourced from 19 populations, associations were measured between five morphological traits and three axes describing source climates. Trait-trait and trait-environment associations were analysed in a multi-response model. Within two focal populations in the wild, selection and path analyses were used to test associations between traits, fecundity and physiological performance.KEY RESULTS:Across 19 populations in a common garden, stomatal density increased with the source population's mean annual temperature and decreased with its average amount of rainfall in midsummer. Concordantly, selection analysis in two natural populations revealed positive selection on stomatal density at the hotter, drier site, while failing to detect selection at the cooler, moister site. Dry-site plants with high stomatal density also had higher stomatal conductances, cooler leaf temperatures and higher light-saturated photosynthetic rates than those with low stomatal density, but no such relationships were present among wet-site plants. Leaf area, stomatal pore index and specific leaf area in the garden also co-varied with climate, but within-population differences were not associated with fitness in either wild population.CONCLUSIONS:The parallel patterns of broad-scale variation, differences in selection and differences in trait-ecophysiology relationships suggest a mechanism for adaptive differentiation in stomatal density. Densely packed stomata may improve performance by increasing transpiration and cooling, but predominately in drier, hotter climates. This study uniquely shows context-dependent benefits of stomatal density--a trait rarely linked to local adaptation in plants.

A hierarchical analysis of simulated movement data.

Understanding the environmental and genetic mechanisms underlying locally adaptive trait variation across the ranges of species is a major focus of evolutionary biology. Combining transcriptome sequencing with common garden experiments on populations spanning geographical and environmental gradients holds promise for identifying such mechanisms. The South African shrub Protea repens displays diverse phenotypes in the wild along drought and temperature gradients. We grew plants from seeds collected at 19 populations spanning this species' range, and sequenced the transcriptomes of these plants to reveal gene pathways associated with adaptive trait variation. We related expression in co-expressed gene networks to trait phenotypes measured in the common garden and to source population climate. We found that expression in gene networks correlated with source-population environment and with plant traits. In particular, the activity of gene networks enriched for growth related pathways correlated strongly with source site minimum winter temperature and with leaf size, stem diameter and height in the garden. Other gene networks with enrichments for photosynthesis related genes showed associations with precipitation. Our results strongly suggest that this species displays population-level differences in gene expression that have been shaped by source population site climate, and that are reflected in trait variation along environmental gradients.