Effective population size as a driver for divergence of an antimicrobial peptide (Hymenoptaecin) in two common European bumblebee species

Social insects are the target of numerous pathogens. This is because the high density of closely‐related individuals frequently interacting with each other enhances the transmission and establishment of pathogens. This high selective pressure results in the rapid evolution of immune genes, which might be counteracted by a reduced effective population size (N_e) lowering the effectiveness of selection. We tested the effect of N_e on the evolutionary rate of an important immune gene for the antimicrobial peptide Hymenoptaecin in two common central European bumblebee species: Bombus terrestris and Bombus lapidarius. Both species are similar in their biology and are expected to be under similar selective pressures because pathogen prevalence does not differ between species. However, previous studies indicated a higher N_e in B. terrestris compared to B. lapidarius. We found high intraspecific variability in the coding sequence but low variability for silent polymorphisms in B. lapidarius. Estimates of long‐ and short‐term N_e were three‐ to four‐fold higher N_e in B. terrestris, although the species did not differ in census population sizes. The difference in N_e might result in less efficient selection and suboptimal adaptation of immune genes (e.g. hymenoptaecin) in B. lapidarius, and thus this species might become less resistant and more tolerant, turning into a superspreader of diseases.     

Acclimation of leaf hydraulic conductance and stomatal conductance of Pinus taeda (loblolly pine) to long-term growth in elevated CO2 (free-air CO2 enrichment) and N-fertilization

We investigated how leaf hydraulic conductance (K_leaf) of loblolly pine trees is influenced by soil nitrogen amendment (N) in stands subjected to ambient or elevated CO₂ concentrations (CO₂^a and CO₂^e, respectively). We also examined how K_leaf varies with changes in reference leaf water potential (Ψ_leaf‐ref) and stomatal conductance (g_s‐ref) calculated at vapour pressure deficit, D of 1 kPa. We detected significant reductions in K_leaf caused by N and CO₂^e, but neither treatment affected pre‐dawn or midday Ψ_leaf. We also detected a significant CO₂^e‐induced reduction in g_s‐ref and Ψ_leaf‐ref. Among treatments, the sensitivity of K_leaf to Ψ_leaf was directly related to a reference K_leaf (K_leaf‐ref computed at Ψ_leaf‐ref). This liquid‐phase response was reflected in a similar gas‐phase response, with g_s sensitivity to D proportional to g_s‐ref. Because leaves represented a substantial component of the whole‐tree conductance, reduction in K_leaf under CO₂^e affected whole‐tree water use by inducing a decline in g_s‐ref. The consequences of the acclimation of leaves to the treatments were: (1) trees growing under CO₂^e controlled morning leaf water status less than CO₂^a trees resulting in a higher diurnal loss of K_leaf; (2) the effect of CO₂^e on g_s‐ref was manifested only during times of high soil moisture.     

INTERMITTENT BREEDING AND CONSTRAINTS ON LITTER SIZE: CONSEQUENCES FOR EFFECTIVE POPULATION SIZE PER GENERATION (Ne) AND PER REPRODUCTIVE CYCLE (Nb)

In iteroparous species, it is easier to estimate N_b (effective number of breeders in one reproductive cycle) than N_e (effective population size per generation). N_b can be used as a proxy for N_e and also can provide crucial insights into eco‐evolutionary processes that occur during reproduction. We used analytical and numerical methods to evaluate effects of intermittent breeding and litter/clutch size on inbreeding N_b and N_e. Fixed or random litter sizes ≥ 3 have little effect on either effective‐size parameter; however, in species (e.g., many large mammals) in which females can produce only one offspring per cycle, female N_b = ∞ and overall N_b = 4N_b(male). Intermittent breeding reduces the pool of female breeders, which reduces both female and overall N_b; reductions are larger in high‐fecundity species with high juvenile mortality and increase when multiple reproductive cycles are skipped. Simulated data for six model species showed that both intermittent breeding and litter‐size constraints increase N_e, but only slightly. We show how to quantitatively account for these effects, which are important to consider when (1) using N_b to estimate N_e, or (2) drawing inferences about male reproductive success based on estimates of female N_b.     

Multiple estimates of effective population size for monitoring a long‐lived vertebrate: an application to Yellowstone grizzly bears

Effective population size (N_e) is a key parameter for monitoring the genetic health of threatened populations because it reflects a population's evolutionary potential and risk of extinction due to genetic stochasticity. However, its application to wildlife monitoring has been limited because it is difficult to measure in natural populations. The isolated and well‐studied population of grizzly bears (Ursus arctos) in the Greater Yellowstone Ecosystem provides a rare opportunity to examine the usefulness of different N_e estimators for monitoring. We genotyped 729 Yellowstone grizzly bears using 20 microsatellites and applied three single‐sample estimators to examine contemporary trends in generation interval (GI), effective number of breeders (N_b) and N_e during 1982–2007. We also used multisample methods to estimate variance (N_eV) and inbreeding N_e (N_eI). Single‐sample estimates revealed positive trajectories, with over a fourfold increase in N_e (≈100 to 450) and near doubling of the GI (≈8 to 14) from the 1980s to 2000s. N_eV (240–319) and N_eI (256) were comparable with the harmonic mean single‐sample N_e (213) over the time period. Reanalysing historical data, we found N_eV increased from ≈80 in the 1910s–1960s to ≈280 in the contemporary population. The estimated ratio of effective to total census size (N_e/N_c) was stable and high (0.42–0.66) compared to previous brown bear studies. These results support independent demographic evidence for Yellowstone grizzly bear population growth since the 1980s. They further demonstrate how genetic monitoring of N_e can complement demographic‐based monitoring of N_c and vital rates, providing a valuable tool for wildlife managers.     

Extremely low genetic diversity across mangrove taxa reflects past sea level changes and hints at poor future responses

The projected increases in sea levels are expected to affect coastal ecosystems. Tropical communities, anchored by mangrove trees and having experienced frequent past sea level changes, appear to be vibrant at present. However, any optimism about the resilience of these ecosystems is premature because the impact of past climate events may not be reflected in the current abundance. To assess the impact of historical sea level changes, we conducted an extensive genetic diversity survey on the Indo‐Malayan coast, a hotspot with a large global mangrove distribution. A survey of 26 populations in six species reveals extremely low genome‐wide nucleotide diversity and hence very small effective population sizes (N_e) in all populations. Whole‐genome sequencing of three mangrove species further shows the decline in N_e to be strongly associated with the speed of past changes in sea level. We also used a recent series of flooding events in Yalong Bay, southern China, to test the robustness of mangroves to sea level changes in relation to their genetic diversity. The events resulted in the death of half of the mangrove trees in this area. Significantly, less genetically diverse mangrove species suffered much greater destruction. The dieback was accompanied by a drastic reduction in local invertebrate biodiversity. We thus predict that tropical coastal communities will be seriously endangered as the global sea level rises. Well‐planned coastal development near mangrove forests will be essential to avert this crisis.     

Effective size of density‐dependent two‐sex populations: the effect of mating systems

Density dependence in vital rates is a key feature affecting temporal fluctuations of natural populations. This has important implications for the rate of random genetic drift. Mating systems also greatly affect effective population sizes, but knowledge of how mating system and density regulation interact to affect random genetic drift is poor. Using theoretical models and simulations, we compare N_e in short‐lived, density‐dependent animal populations with different mating systems. We study the impact of a fluctuating, density‐dependent sex ratio and consider both a stable and a fluctuating environment. We find a negative relationship between annual N_e/N and adult population size N due to density dependence, suggesting that loss of genetic variation is reduced at small densities. The magnitude of this decrease was affected by mating system and life history. A male‐biased, density‐dependent sex ratio reduces the rate of genetic drift compared to an equal, density‐independent sex ratio, but a stochastic change towards male bias reduces the N_e/N ratio. Environmental stochasticity amplifies temporal fluctuations in population size and is thus vital to consider in estimation of effective population sizes over longer time periods. Our results on the reduced loss of genetic variation at small densities, particularly in polygamous populations, indicate that density regulation may facilitate adaptive evolution at small population sizes.     

Effects of population characteristics and structure on estimates of effective population size in a house sparrow metapopulation

Effective population size (N_e) is a key parameter to understand evolutionary processes and the viability of endangered populations as it determines the rate of genetic drift and inbreeding. Low N_e can lead to inbreeding depression and reduced population adaptability. In this study, we estimated contemporary N_e using genetic estimators (LDNE, ONeSAMP, MLNE and CoNe) as well as a demographic estimator in a natural insular house sparrow metapopulation. We investigated whether population characteristics (population size, sex ratio, immigration rate, variance in population size and population growth rate) explained variation within and among populations in the ratio of effective to census population size (N_e/N_c). In general, N_e/N_c ratios increased with immigration rates. Genetic N_e was much larger than demographic N_e, probably due to a greater effect of immigration on genetic than demographic processes in local populations. Moreover, although estimates of genetic N_e seemed to track N_c quite well, the genetic N_e‐estimates were often larger than N_c within populations. Estimates of genetic N_e for the metapopulation were however within the expected range (<N_c). Our results suggest that in fragmented populations, even low levels of gene flow may have important consequences for the interpretation of genetic estimates of N_e. Consequently, further studies are needed to understand how N_e estimated in local populations or the total metapopulation relates to actual rates of genetic drift and inbreeding.     

Sweepstakes reproductive success is absent in a New Zealand snapper (Chrysophrus auratus) population protected from fishing despite “tiny” Ne/N ratios elsewhere

A landmark study published in 2002 estimated a very small N_e/N ratio (around 10^–5) in a population of pink snapper (Chrysophrys auratus, Forster, 1801) in the Hauraki Gulf in New Zealand. It epitomized the tiny N_e/N ratios (<10^–3) reported in marine species due to the hypothesized operation of sweepstakes reproductive success (SRS). Here we re‐evaluate the occurrence of SRS in marine species and the potential effect of fishing on the N_e/N ratio by studying the same species in the same region, but in a population that has been protected from fishing since 1975. We combine empirical, simulation and model‐based approaches to estimate N_e (and N_b) from genotypes of 1,044 adult fish and estimate N using recapture‐probabilities. The estimated N_e/N ratio was much larger (0.33, SE: 0.14) than expected. The magnitude of estimates of population‐wide variance in individual lifetime reproductive success (10–18) suggested that the sweepstakes effect was negligible in the study population. After evaluating factors that could explain the contrast between studies – experimental design, life history differences, environmental effects and the influence of exploitation on the N_e/N ratio – we conclude that the low N_e of the Hauraki Gulf population is associated with demographic instability in the harvested compared to the protected population despite circumstantial evidence that the 2002 study may have underestimated N_e. This study has broad implications for the prevailing view that reproductive success in the sea is largely driven by chance, and for genetic monitoring of populations using the N_e/N ratio and N_b.     

Elevated CO2 and tree fecundity: the role of tree size, interannual variability, and population heterogeneity

Long‐term population effects of changes in atmospheric CO₂ will be largely determined by reproductive effort. Our research objectives were to quantify variability in seed production and rate of maturation among individual Pinus taeda L. (Pinaceae) trees growing in elevated CO₂ (ambient plus 200 μL L^?1) since 1996. Estimating tree fecundity in nature is frustrated by the difficulty of counting seeds from individual trees and the need for long‐term data. We have used a hierarchical Bayes approach to model individual tree fecundity, accounting for the complexity of experimentation in a natural setting over multiple years. The study presented here demonstrates large variability in natural fecundity rates and contributes to our understanding of how both interannual variation and population heterogeneity influence elevated CO₂ effects. We found that trees growing under elevated CO₂ matured earlier and produced more seeds and cones per unit basal area than ambient grown trees. By 2004, trees grown in high CO₂ had produced an average 300 more seeds per tree than ambient grown trees. Although there was a trend toward decreasing mean CO₂ effect (difference in fecundity between elevated and ambient treatments) over time, the hierarchical analysis indicates that this decrease comes from the emergence of a few highly fecund ambient grown trees by 2002, rather than acclimation or downregulation among the fumigated trees. The most important effect of increased CO₂ in forest ecosystems may be the increase in fecundity reported here. Although biomass responses can sometimes be large, the increase in fecundity can have long‐term impacts on forest dynamics that transcend the current generation.     

neogen: A tool to predict genetic effective population size (Ne) for species with generational overlap and to assist empirical Ne study design

Molecular genetic estimates of population effective size (N_e) lose accuracy and precision when insufficient numbers of samples or loci are used. Ideally, researchers would like to forecast the necessary power when planning their project. neogen (genetic N_e for Overlapping Generations) enables estimates of precision and accuracy in advance of empirical investigation and allows exploration of the power available in different user‐specified age‐structured sampling schemes. neogen provides a population simulation and genetic power analysis framework that simulates the demographics, genetic composition, and N_e, from species‐specific life history, mortality, population size, and genetic priors. neogen guides the user to establish a tractable sampling regime and to determine the numbers of samples and microsatellite or SNP loci required for accurate and precise genetic N_e estimates when sampling a natural population. neogen is useful at multiple stages of a study's life cycle: when budgeting, as sampling and locus development progresses, and for corroboration when empirical N_e estimates are available. The underlying model is applicable to a wide variety of iteroparous species with overlapping generations (e.g., mammals, birds, reptiles, long‐lived fishes). In this paper, we describe the neogen model, detail the workflow for the point‐and‐click software, and explain the graphical results. We demonstrate the use of neogen with empirical Australian east coast zebra shark (Stegostoma fasciatum) data. For researchers wishing to make accurate and precise genetic N_e estimates for overlapping generations species, neogen facilitates planning for sample and locus acquisition, and with existing empirical genetic N_e estimates neogen can corroborate population demographic and life history properties.     

Do estimates of contemporary effective population size tell us what we want to know?

Estimation of effective population size (N_e) from genetic marker data is a major focus for biodiversity conservation because it is essential to know at what rates inbreeding is increasing and additive genetic variation is lost. But are these the rates assessed when applying commonly used N_e estimation techniques? Here we use recently developed analytical tools and demonstrate that in the case of substructured populations the answer is no. This is because the following: Genetic change can be quantified in several ways reflecting different types of N_e such as inbreeding (N_eI), variance (N_eV), additive genetic variance (N_eAV), linkage disequilibrium equilibrium (N_eLD), eigenvalue (N_eE) and coalescence (N_eCo) effective size. They are all the same for an isolated population of constant size, but the realized values of these effective sizes can differ dramatically in populations under migration. Commonly applied N_e‐estimators target N_eV or N_eLD of individual subpopulations. While such estimates are safe proxies for the rates of inbreeding and loss of additive genetic variation under isolation, we show that they are poor indicators of these rates in populations affected by migration. In fact, both the local and global inbreeding (N_eI) and additive genetic variance (N_eAV) effective sizes are consistently underestimated in a subdivided population. This is serious because these are the effective sizes that are relevant to the widely accepted 50/500 rule for short and long term genetic conservation.  The bias can be infinitely large and is due to inappropriate parameters being estimated when applying theory for isolated populations to subdivided ones.     

PSMC analysis of effective population sizes in molecular ecology and its application to black‐and‐white Ficedula flycatchers

Climatic fluctuations during the Quaternary period governed the demography of species and contributed to population differentiation and ultimately speciation. Studies of these past processes have previously been hindered by a lack of means and genetic data to model changes in effective population size (N_e) through time. However, based on diploid genome sequences of high quality, the recently developed pairwise sequentially Markovian coalescent (PSMC) can estimate trajectories of changes in N_e over considerable time periods. We applied this approach to resequencing data from nearly 200 genomes of four species and several populations of the Ficedula species complex of black‐and‐white flycatchers. N_e curves of Atlas, collared, pied and semicollared flycatcher converged 1–2 million years ago (Ma) at an N_e of ≈ 200 000, likely reflecting the time when all four species last shared a common ancestor. Subsequent separate N_e trajectories are consistent with lineage splitting and speciation. All species showed evidence of population growth up until 100–200 thousand years ago (kya), followed by decline and then start of a new phase of population expansion. However, timing and amplitude of changes in N_e differed among species, and for pied flycatcher, the temporal dynamics of N_e differed between Spanish birds and central/northern European populations. This cautions against extrapolation of demographic inference between lineages and calls for adequate sampling to provide representative pictures of the coalescence process in different species or populations. We also empirically evaluate criteria for proper inference of demographic histories using PSMC and arrive at recommendations of using sequencing data with a mean genome coverage of ≥18X, a per‐site filter of ≥10 reads and no more than 25% of missing data.     

Breeding without breeding: minimum fingerprinting effort with respect to the effective population size

We present a probabilistic model to minimize the fingerprinting effort associated with the implementation of the “breeding without breeding” scheme under partial pedigree reconstruction. Our approach is directed at achieving a declared target population’s minimum effective population size (N _e ), following the pedigree reconstruction and genotypic selection and is based on the graph theory algorithm. The primary advantage of the proposed method is to reduce the cost associated with fingerprinting before the implementation of the pedigree reconstruction for seed parent–offspring derived from breeding arboreta and production or natural populations. Stochastic simulation was conducted to test the method’s efficiency assuming a simple polygenic model and a single trait. Hypothetical population consisted of 30 parental trees that were paired at random (selfing excluded), resulting in 600 individuals (potential candidates for forwards selection). The male parentage was assumed initially unknown. The model was used to estimate the minimum genotyping sample size needed to reaching the prescribed N _e . Results were compared with the known pedigree data. The model was successful in revealing the true relationship pattern over the whole range of N _e . Two to three offspring entered genotyping to meet the N _e  = 2 while 41 to 43 were required to satisfy the N _e  = 14. Importantly, genetic gain was affected at the lower limits of the genotyping effort. Doubling the number of parents resulted in considerable reduction of the genotyping effort at higher N _e values.     

Making sense of genetic estimates of effective population size

The last decade has seen an explosion of interest in use of genetic markers to estimate effective population size, N_e. Effective population size is important both theoretically (N_e is a key parameter in almost every aspect of evolutionary biology) and for practical application (N_e determines rates of genetic drift and loss of genetic variability and modulates the effectiveness of selection, so it is crucial to consider in conservation). As documented by Palstra & Fraser ( 2012 ), most of the recent growth in N_e estimation can be attributed to development or refinement of methods that can use a single sample of individuals (the older temporal method requires at least two samples separated in time). As with other population genetic methods, performance of new N_e estimators is typically evaluated with simulated data for a few scenarios selected by the author(s). Inevitably, these initial evaluations fail to fully consider the consequences of violating simplifying assumptions, such as discrete generations, closed populations of constant size and selective neutrality. Subsequently, many researchers studying natural or captive populations have reported estimates of N_e for multiple methods; often these estimates are congruent, but that is not always the case. Because true N_e is rarely known in these empirical studies, it is difficult to make sense of the results when estimates differ substantially among methods. What is needed is a rigorous, comparative analysis under realistic scenarios for which true N_e is known. Recently, Gilbert & Whitlock ( 2015 ) did just that for both single‐sample and temporal methods under a wide range of migration schemes. In the current issue of Molecular Ecology, Wang ( 2016 ) uses simulations to evaluate performance of four single‐sample N_e estimators. In addition to assessing effects of true N_e, sample size, and number of loci, Wang also evaluated performance under changing abundance, physical linkage and genotyping errors, as well as for some alternative life histories (high rates of selfing; haplodiploids). Wang showed that the sibship frequency (SF) and linkage disequilibrium (LD) methods perform dramatically better than the heterozygote excess and molecular coancestry methods under most scenarios (see Fig. 1, modified from figure 2 in Wang 2016 ), and he also concluded that SF is generally more versatile than LD. This article represents a truly Herculean effort, and results should be of considerable value to researchers interested in applying these methods to real‐world situations.     

Simple method for calculating confidence limits around inbreeding rate and effective population size estimates from pedigrees

An important concept in population genetics is effective population size (N_e), which describes the expected rate of loss of genetic variability from a population. One way to estimate N_e is using a pedigree. However, there are no methods for comparing the N_e estimated from a pedigree with that expected from life-history models. In the paper we show how N_e can be estimated from the change in inbreeding rate (f) estimated from a pedigree. The mean individual inbreeding rate in a population at a given time must be calculated from averaged values for males and females, where each age class is weighted by its reproductive value. We show an exact method for placing confidence intervals around f and N_e using a binomial distribution, and present a method for approximating this interval for large N_es using a Poisson distribution. These confidence intervals can be used to compare f and N_e from a pedigree to expected values from demographic models, and to compare N_es of two populations.     

Genetic variation in nuclear and mitochondrial markers supports a large sex difference in lifetime reproductive skew in a lekking species

Sex differences in skews of vertebrate lifetime reproductive success are difficult to measure directly. Evolutionary histories of differential skew should be detectable in the genome. For example, male‐biased skew should reduce variation in the biparentally inherited genome relative to the maternally inherited genome. We tested this approach in lek‐breeding ruff (Class Aves, Philomachus pugnax) by comparing genetic variation of nuclear microsatellites (θ_n; biparental) versus mitochondrial D‐loop sequences (θ_m; maternal), and conversion to comparable nuclear (N_e) and female (N_ef) effective population size using published ranges of mutation rates for each marker (μ). We provide a Bayesian method to calculate N_e (θ_n = 4N_eμ_n) and N_ef (θ_m = 2N_efμ_m) using 95% credible intervals (CI) of θ_n and θ_m as informative priors, and accounting for uncertainty in μ. In 96 male ruffs from one population, N_e was 97% (79–100%) lower than expected under random mating in an ideal population, where N_e:N_ef = 2. This substantially lower autosomal variation represents the first genomic support of strong male reproductive skew in a lekking species.     

Unexpected high genetic diversity in small populations suggests maintenance by associative overdominance

The effective population size (N_e) is a central factor in determining maintenance of genetic variation. The neutral theory predicts that loss of variation depends on N_e, with less genetic drift in larger populations. We monitored genetic drift in 42 Drosophila melanogaster populations of different adult census population sizes (10, 50 or 500) using pooled RAD sequencing. In small populations, variation was lost at a substantially lower rate than expected. This observation was consistent across two ecological relevant thermal regimes, one stable and one with a stressful increase in temperature across generations. Estimated ratios between N_e and adult census size were consistently higher in small than in larger populations. The finding provides evidence for a slower than expected loss of genetic diversity and consequently a higher than expected long‐term evolutionary potential in small fragmented populations. More genetic diversity was retained in areas of low recombination, suggesting that associative overdominance, driven by disfavoured homozygosity of recessive deleterious alleles, is responsible for the maintenance of genetic diversity in smaller populations. Consistent with this hypothesis, the X‐chromosome, which is largely free of recessive deleterious alleles due to hemizygosity in males, fits neutral expectations even in small populations. Our experiments provide experimental answers to a range of unexpected patterns in natural populations, ranging from variable diversity on X‐chromosomes and autosomes to surprisingly high levels of nucleotide diversity in small populations.     

Sexual selection has minimal impact on effective population sizes in species with high rates of random offspring mortality: An empirical demonstration using fitness distributions

The effective population size (N_e) is a fundamental parameter in population genetics that influences the rate of loss of genetic diversity. Sexual selection has the potential to reduce N_e by causing the sex‐specific distributions of individuals that successfully reproduce to diverge. To empirically estimate the effect of sexual selection on N_e, we obtained fitness distributions for males and females from an outbred, laboratory‐adapted population of Drosophila melanogaster. We observed strong sexual selection in this population (the variance in male reproductive success was ～14 times higher than that for females), but found that sexual selection had only a modest effect on N_e, which was 75% of the census size. This occurs because the substantial random offspring mortality in this population diminishes the effects of sexual selection on N_e, a result that necessarily applies to other high fecundity species. The inclusion of this random offspring mortality creates a scaling effect that reduces the variance/mean ratios for male and female reproductive success and causes them to converge. Our results demonstrate that measuring reproductive success without considering offspring mortality can underestimate N_e and overestimate the genetic consequences of sexual selection. Similarly, comparing genetic diversity among different genomic components may fail to detect strong sexual selection.     

Effective population size does not predict codon usage bias in mammals

Synonymous codons are not used at equal frequency throughout the genome, a phenomenon termed codon usage bias (CUB). It is often assumed that interspecific variation in the intensity of CUB is related to species differences in effective population sizes (N_e), with selection on CUB operating less efficiently in species with small N_e. Here, we specifically ask whether variation in N_e predicts differences in CUB in mammals and report two main findings. First, across 41 mammalian genomes, CUB was not correlated with two indirect proxies of N_e (body mass and generation time), even though there was statistically significant evidence of selection shaping CUB across all species. Interestingly, autosomal genes showed higher codon usage bias compared to X‐linked genes, and high‐recombination genes showed higher codon usage bias compared to low recombination genes, suggesting intraspecific variation in N_e predicts variation in CUB. Second, across six mammalian species with genetic estimates of N_e (human, chimpanzee, rabbit, and three mouse species: Mus musculus, M. domesticus, and M. castaneus), N_e and CUB were weakly and inconsistently correlated. At least in mammals, interspecific divergence in N_e does not strongly predict variation in CUB. One hypothesis is that each species responds to a unique distribution of selection coefficients, confounding any straightforward link between N_e and CUB.     

Photosynthetic responses of 13 grassland species across 11 years of free‐air CO2 enrichment is modest,consistent and independent of N supply

If long‐term responses of photosynthesis and leaf diffusive conductance to rising atmospheric carbon dioxide (CO₂) levels are similar or predictably different among species, functional types, and ecosystem types, general global models of elevated CO₂ effects can effectively be developed. To address this issue we measured gas exchange rates of 13 perennial grassland species from four functional groups across 11 years of long‐term free‐air CO₂ enrichment (eCO₂, +180 ppm above ambient CO₂) in the BioCON experiment in Minnesota, USA. Eleven years of eCO₂ produced consistent but modest increases in leaf net photosynthetic rates of 10% on average compared with plants grown at ambient CO₂ concentrations across the 13 species. This eCO₂‐induced enhancement did not depend on soil N treatment, is much less than the average across other longer‐term studies, and represents strong acclimation (i.e. downregulation) as it is also much less than the instantaneous response to eCO₂. The legume and C3 nonlegume forb species were the most responsive among the functional groups (+13% in each), the C4 grasses the least responsive (+4%), and C3 grasses intermediate in their photosynthetic response to eCO₂ across years (+9%). Leaf stomatal conductance and nitrogen content declined comparably across species in eCO₂ compared with ambient CO₂ and to degrees corresponding to results from other studies. The significant acclimation of photosynthesis is explained in part by those eCO₂‐induced decreases in leaf N content and stomatal conductance that reduce leaf photosynthetic capacity in plants grown under elevated compared with ambient CO₂ concentrations. Results of this study, probably the longest‐term with the most species, suggest that carbon cycle models that assume and thereby simulate long‐lived strong eCO₂ stimulation of photosynthesis (e.g.> 25%) for all of Earth's terrestrial ecosystems should be viewed with a great deal of caution.