Anthropogenic perturbations such as harvesting often select against a large body size, and are predicted to induce rapid evolution towards smaller body sizes and earlier maturation. However, the evolvability of body size and size-correlated traits remains seldom evaluated in wild populations. Here, we use a laboratory experiment over 6 generations to measure the ability of wild-caught medaka fish (Oryzias latipes) to evolve in response to bidirectional size-dependent selection mimicking opposite harvest regimes. Specifically, we imposed selection against a small body size (Large line), against a large body size (Small line) or random selection (Control line), and measured correlated responses across multiple phenotypic, life-history and endocrine traits. As expected, the Large line evolved faster somatic growth and delayed maturation, but also evolved smaller body sizes at hatch, with no change in average levels of pituitary gene expressions of luteinizing, follicle-stimulating or growth (GH) hormones. In contrast, the Small medaka line was unable to evolve smaller body sizes or earlier maturation, but showed marginally-significant signs of increased reproductive investment, including larger egg sizes and elevated pituitary GH production. Natural selection on medaka body size was too weak to significantly hinder the effect of artificial selection, indicating that the asymmetric body-size response to size-dependent selection reflected an asymmetry in body-size evolvability. Our results show that trait evolvability may be contingent upon the direction of selection, and that a detailed knowledge of trait evolutionary potential is needed to forecast population response to anthropogenic change.
1. Plant leaf stomata are the gatekeepers of the atmosphere-plant interface and are essential building blocks of land surface models as they control transpiration and photosynthesis. Although more stomatal trait data is needed to significantly reduce the error in these model predictions, recording these traits is time-consuming and no standardized protocol is currently available. Some attempts were made to automate stomatal detection from photomicrographs, however, these approaches have the disadvantage of using classic image processing or targeting a narrow taxonomic entity which makes these technologies less robust and generalizable to other plant species. We propose an easy-to-use and adaptable workflow from leaf to label. A methodology for automatic stomata detection was developed using deep neural networks according to the state-of-the-art and its applicability demonstrated across the phylogeny of the angiosperms. 2. We used a patch-based approach for training/tuning three different deep learning architectures. For training, we used 431 micrographs taken from leaf prints made according the nail polish method from herbarium specimens of 19 species. The best performing architecture was tested on 595 images of 16 additional species spread across the angiosperm phylogeny. 3. The nail polish method was successfully applied in 78% of the species sampled here. The VGG19 architecture slightly outperformed the basic shallow and deep architectures, with a confidence threshold equal to 0.7 resulting in an optimal trade-off between precision and recall. Applying this threshold the VGG19 architecture obtained an average F-score of 0.87, 0.89 and 0.67 on the training, validation and unseen test set, respectively. The average accuracy was very high (94%) for computed stomatal counts on unseen images of species used for training. 4. The leaf-to-label pipeline is an easy-to-use workflow for researchers of different areas of expertise interested in detecting stomata more efficiently. The described methodology was based on multiple species and well-established methods so that it can serve as a reference for future work.
Recurrent sea urchin mass mortality has recently affected eastern Atlantic populations of the barren-forming sea urchin Diadema africanum. This new episode of die-off affords the opportunity to determine common meteorological and oceanographic conditions that may promote disease outbreaks. The population dynamics of this sea urchin species are well known—urchin barrens have persisted for many decades along most of the coastlines off the archipelagos of Madeira, Selvages and the Canary Islands, where they limit macroalgae biomass growth. However, this new and explosive mortality event decimated the sea urchin population by 93% on Tenerife and La Palma Islands. Two severe episodes of southwestern rough sea that lead to winter storms, in February 2010 (Xynthia) and February 2018 (Emma), preceded both mass mortality events. The autumn and winter months of those years were anomalous and characterized by swells with an average wave height above 2 m that hit the south and southwest sides of the islands. The amoeba Paramoeba brachiphila was the only pathogen isolated this time from the moribund and dead sea urchins, suggesting that the amoeba was the primary cause of the mortality. This new sea urchin die-off event supports the “killer-storm” hypothesis that has been already described for western Atlantic coasts. These anomalous southwest storms during winters generate pronounced underwater sediment movement and large-scale vertical mixing, detected in local tide gauge, which may promote paramoebiasis. This study presents valuable insights about climate-mediated changes in disease frequency and its impacts on the future of coastal marine ecosystems in the Atlantic.
Fungi are a key component of tropical biodiversity. Due to their inconspicuous and largely subterranean nature, they are however usually neglected in biodiversity inventories. The goal of this study was to identify the key determinants of fungal richness, community composition, and turnover in tropical rainforests. We tested specifically for the effect of soil properties, habitat, and locality in Amazonia. For these analyses, we used high-throughput sequencing data of short and long reads of fungal DNA present in soil and organic litter samples, combining existing and novel genomic data. Habitat type (phytophysiognomies) emerges as the strongest factor in explaining fungal community composition. Naturally open areas – campinas – are the richest habitat overall. Soil properties have different effects depending on the soil layer (litter or mineral soil) and the choice of genetic marker. We suggest that campinas could be a neglected hotspot of fungal diversity. An underlying cause for their rich diversity may be the overall low soil fertility, which increases the reliance on biotic interactions essential for nutrient absorption in these environments, notably ectomycorrhizal fungi–plant associations. Our results highlight the advantages of using both short and long DNA reads produced through high-throughput sequencing to characterize fungal diversity. While short-reads can suffice for diversity and community comparison, long-reads add taxonomic precision and have the potential to reveal population diversity.
Over thirty species of littoral marine Gammaridea occur along the coasts of the North Atlantic. From one to several species can coexist in a single region. There is an evident, inverse relationship between egg incubation time and temperature (from 14 to > 120 days) and consequent trends in the size of the animals on reaching maturity (from 5 mm in warmer waters to 30 mm in the coldest ones) and in lifespan (from < 6 months to > 5 years). Littoral gammarids are a good example of the shrinking size effect of increasing temperatures and size-related species diversity. In large species the annual cohorts of the population (3 to 5 annual size groups) functionally replace the adults of smaller species. The ongoing warming of the European Arctic seas may extend the distribution limits of boreal species so that more Gammarus species may appear on northern coasts hitherto occupied by just one or at most two species.
The Southern Ocean is one of the most isolated marine ecosystems, characterized by high levels of endemism, diversity, and biomass. Ascidians are among the dominant groups in Antarctic benthic assemblages, thus recording the evolutionary patterns of this group is crucial to improve our current understanding of the assembly of this polar ocean. We studied the genetic variation within Cnemidocarpa verrucosa sensu lato, one of the most widely distributed abundant and studied ascidian species in Antarctica. Using a mitochondrial and a nuclear gene (COI and 18S), the phylogeography of fifteen populations distributed along the Antarctic Peninsula and South America (Burdwood Bank/MPA Namuncurá) was characterized, where the bimodal distribution of the genetic distance suggested the existence of two species within the nominal C. verrucosa. When re-evaluating morphological traits to distinguish between genetically defined species, the presence of a basal disc in one of the genotypes could be a morphological trait to differentiate the species. These results are surprising due to the large research that has been carried out with the conspicuous C. verrucosa with no differentiation between species. Furthermore, it provides important tools to distinguish species in the field and laboratory. But also, these results give new insights to patterns of differentiation between closely related species that are distributed in sympatry, where the permeability of species boundaries still needs to be well understood.
Population dynamics models combine density-dependence and environmental effects. Ignoring sampling uncertainty might lead to biased estimation of the strength of density-dependence. This is typically addressed using state-space model approaches, which integrate sampling error and population process estimates. Such models seldom include an explicit link between the sampling procedures and the true abundance, which is common in capture-recapture settings. However, many of the models proposed to estimate abundance in the presence of heterogeneity lead to incomplete likelihood functions and cannot be straightforwardly included in state-space models. We assessed the importance of estimating sampling error explicitly by taking an intermediate approach between ignoring uncertainty in abundance estimates and fully specified state-space models for density-dependence estimation based on autoregressive processes. First, we estimated individual capture probabilities based on a heterogeneity model, using a conditional multinomial likelihood, followed by a Horvitz-Thompson estimate for abundance. Second, we estimated coefficients of autoregressive models for the log abundance. Inference was performed using the methodology of integrated nested Laplace approximation (INLA). We performed an extensive simulation study to compare our approach with estimates disregarding capture history information, and using R-package VGAM, for different parameter specifications. The methods were then applied to a real dataset of gray-sided voles Myodes rufocanus from Northern Norway. We found that density-dependence estimation was improved when explicitly modelling sampling error in scenarios with low innovation variances, in which differences in coverage reached up to 8% in estimating the coefficients of the autoregressive processes. In this case, the bias also increased assuming a Poisson distribution in the observational model. For high innovation variances, the differences between methods were small and it appeared less important to model heterogeneity.
1. The reduction of plant diversity following eutrophication threatens many ecosystems worldwide. Yet, the mechanisms by which species are lost following nutrient enrichment are still not completely understood, nor are the details of when such mechanisms act during the growing season, which hampers understanding and the development of mitigation strategies. 2. Using a common garden competition experiment, we found that early-season differences in growth rates among five perennial grass species measured in monoculture predicted short-term competitive dominance in pairwise combinations and that this effect was stronger under a fertilisation treatment. 3. We also examined the role of early-season growth rate in determining the outcome of competition along an experimental nutrient gradient in an alpine meadow. Early differences in growth rate between species predicted short-term competitive dominance under both ambient and fertilized conditions and competitive exclusion under fertilized conditions. 4. The results of these two studies suggests that plant species growing faster during the early stage of the growing season gain a competitive advantage over species that initially grow more slowly, and that this advantage is magnified under fertilisation. This finding is consistent with the theory of asymmetric competition for light in which fast-growing species can intercept incident light and hence outcompete and exclude slower-growing (and hence shorter) species. We predict that the current chronic nutrient inputs into many terrestrial ecosystems worldwide will reduce plant diversity and maintain low biodiversity state by continuously favouring fast-growing species. Biodiversity management strategies should focus on controlling nutrient inputs and reducing the growth of fast-growing species early in the season.
We use adaptive dynamics models to study how changes in the abiotic environment affect patterns of evolutionary dynamics and diversity in evolving communities of organisms with complex phenotypes. The models are based on the logistic competition model and environmental changes are implemented as a temporal change of the carrying capacity as a function of phenotype. In general we observe that environmental changes cause a reduction in the number of species, in total population size, and in phenotypic diversity. The rate of environmental change is crucial for determining whether a community survives or undergoes extinction. Until some critical rate of environmental changes, species are able to follow evolutionarily the shifting phenotypic optimum of the carrying capacity, and many communities adapt to the changing conditions and converge to new stationary states. When environmental changes stop, such communities gradually restore their initial phenotypic diversity.
The biogeographical distribution of diversity among populations of threatened mammalian species is generally investigated through population genetics. However, intraspecific phenotypic diversity is rarely assessed beyond taxonomy-focused linear measurements or qualitative descriptions. Here, we use a technique widely used in the evolutionary sciences – geometric morphometrics – to characterize shape diversity in the skull of an endangered marsupial, the northern quoll, across its 5,000 km distribution range along the northern Australian coast. Skull shape is a proxy of feeding, behaviour, and phenotypic differentiation, allowing us to ask if populations can be distinguished and if patterns of variation indicate adaptability to changing environmental conditions. We analysed skull shape in 101 individuals across the four mainland populations and several islands. We assessed the contribution of population, size, sex, rainfall, temperature, and latitude/longitude to skull shape variation through Principal Components, Procrustes ANOVA, and variation partitioning analyses. Regardless of land area inhabited, northern quoll populations harbour similar amounts of broadly overlapping skull shape variation. Size predicted skull shape best, coinciding with braincase size variation and differences in the cheekbone shape. Size-adjusted population differences explained less variation with far smaller effect sizes, relating to changes in insertion areas of masticatory muscles, as well as the upper muzzle and incisor region. Climatic and geographic variables contributed little or nothing. Strikingly, the vast majority of shape variation - 76% - remained unexplained. Our results suggest a uniform within-species scope for shape variation, possibly due to phenotypic plasticity or allometric constraints. The lack of local adaptation indicates that cross-breeding between populations will not reduce local morphological skull (and probably general musculoskeletal) adaptation because none exists. However, the potential for heritable morphological variation (e.g. specialization to local diets) seems exceedingly limited. We conclude that 3D geometric morphometrics can provide a comprehensive, statistically rigorous phenomic contribution to genetics-based conservation studies.
The Sanjiang Plain is the biggest freshwater wetland locating within northeastern China. Due to climate change and human activities, that wetland has degraded to a successional gradient from the original flooded wetland to dry shrub vegetation and a forest area with lower ground water level, resulting in changes in soil microbiologic structure and functions. The present study investigated the microbial diversity and community structure in relation to soil properties along this gradient. The soil physic-chemical properties changed significantly with degradation. The Shannon variety of soil fungi as well as bacteria varied significantly with successional stage (both P < 0.05). The community structures of soil bacteria and fungi in the early successional stages (i.e., the wetland) were significantly structured via total phosphorus, available nitrogen and total nitrogen concentrations in soils, while those in the later successional stages (i.e., forests) were significantly structured by soil organic carbon, soil pH and available phosphorus concentrations. Our results indicated that variations in the soil environment affected soil microbial communities along a successional gradient from wetland to forests are mainly. These outcomes indicate that above ground plant composition is a forceful determinant of the structure as well as functions of bacterial and fungal communities, might finally causing substantial alterations in ecosystem activity.
Phenotypic diversity, or disparity, can be explained by simple genetic drift or, if functional constraints are strong, by selection for ecologically relevant phenotypes. We here studied phenotypic disparity in head shape in aquatic snakes. We investigated whether conflicting selective pressures related to different functions have driven shape diversity and explore whether similar phenotypes may give rise to the same functional output (i.e. many-to-one mapping of form to function). We focused on the head shape of aquatically foraging snakes as they fulfil several fitness-relevant functions and show a large amount of morphological variability. We used 3D surface scanning and 3D geometric-morphometrics to compare the head shape of 62 species in a phylogenetic context. We first tested whether diet specialization and size are drivers of head shape diversification. Next, we tested for many-to-one mapping by comparing the hydrodynamic efficiency of head shapes characteristic of the main axis of variation in the dataset. We 3D printed these shapes and measured the forces at play during a frontal strike. Our results show that diet and size explain only a small amount of shape variation. Shapes did not functionally converge as more specialized aquatic species evolved a more efficient head shape than others. The shape disparity observed could thus reflect a process of niche specialization under a stabilizing selective regime.
Many eusocial insects, including ants, show complex colony structures, distributions, and reproductive strategies. In the ant Vollenhovia emeryi Wheeler (Hymenoptera: Myrmicinae), queens and males are produced clonally, while sterile workers arise sexually, unlike other ant species and Hymenopteran insects in general. Furthermore, there is a wing length polymorphism in the queen caste. Despite its ecological and evolutionary importance, little is known about the population dynamics and structure of this ant species, which may provide insight into its unique reproductive mode and polymorphic traits. We performed in-depth analyses of ant populations from Korea, Japan, and North America using three mitochondrial genes (COI, COII, and Cytb). The long-winged (L) morph is predominant in Korean populations, and the short-winged (S) morph is very rare. Interestingly, all L morphs were infected with Wolbachia, while all Korean S morphs lacked Wolbachia, demonstrating a novel association between a symbiont and a phenotypic trait. A phylogenetic analysis revealed that the S morph is derived from the L morph. We propose that the S morph is associated with potential resistance to Wolbachia infection, and that Wolbachia infection does not influence clonal reproduction.
The identification of the mechanisms underlying co-occurrence patterns of species is a way to identify which processes (niche, neutral or both) structure metacommunities. In this paper, our goals are to identify patterns of co-occurrence in neotropical stream fish and determine which processes structure the metacommunity and the gradients that underlie this structure. Our results pointed out that the metacommunity formed by the total pool of species is structured by a nested pattern (Hyperdispersed Species Loss) of co-occurrence and the mass effect mechanism. On the other hand, a set of core species displays a Clementisian pattern and is structured by the species sorting mechanism. Both, hyperdispersed species loss and the Clementisian patterns point to a discrete set of communities in the metacommunity. These communities could be isolated by physicochemical conditions, or physical barriers, like dams or waterfalls.
Marine food webs are highly compartmentalized and characterizing the trophic niches among consumers is important for predicting how impact from human activities affect the structuring and functioning of marine food webs. Biomarkers such as bulk stable isotopes have proven to be powerful tools to elucidate trophic niches, but they may lack in resolution, particularly when spatio-temporal variability in a system is high. To close this gap, we investigated whether carbon isotope (δ13C) patterns of essential amino acids (EAAs), also termed δ13AA fingerprints, can characterize niche differentiation in a highly dynamic marine system. We tested the ability of δ13AA fingerprints to differentiate trophic niches among six functional groups and ten individual species in the Baltic Sea. We also tested whether fingerprints of the common zooplanktivorous fishes, herring and sprat, differ among four Baltic Sea regions with different biochemical conditions and phytoplankton assemblages. Additionally, we investigated how these results compared to bulk C and N isotope data for the same sample set. We found significantly different δ13AA fingerprints among all six functional groups. Species differentiation was in comparison less distinct, due to partial convergence of the species’ fingerprints within functional groups. Herring and sprat displayed region specific δ13AA fingerprints indicating that this approach could be used as a migratory marker. Bulk isotope data had a lower power to differentiate between trophic niches, but may provide more easily interpretable information about relative trophic position than the fingerprints. We conclude that δ13AA fingerprinting has a strong potential to advance our understanding of ecological niches, and trophic linkages from producers to higher trophic levels in dynamic marine systems. Given how management practices of marine resources and habitats are reshaping the structure and function of marine food webs, implementing new and powerful tracer methods are urgently needed to improve the knowledge base for policy makers.
Coral reef fish larvae are tiny, exceedingly numerous, and hard to track. They are also highly capable, equipped with swimming and sensory abilities that may influence their dispersal trajectories. Despite the importance of larval input to the dynamics of a population, we remain reliant on indirect insights to the processes influencing larval behaviour and transport. Here, we used genetic data (300 independent single nucleotide polymorphisms) derived from a light trap sample of a single recruitment event of Dascyllus abudafur in the Red Sea (N=168 settlers). We analysed the genetic composition of the larvae and assessed whether kinship among these was significantly different from random as evidence for cohesive dispersal during the larval phase. We simulated many iterations of similar-sized recruitment cohorts to compare the expected kinship composition relative to our empirical data. The high number of siblings within the empirical cohort strongly suggests cohesive dispersal among larvae. This work highlights the utility of kinship analysis as a means of inferring dynamics during the pelagic larval phase.
The sharp rise in anthropogenic activities and climate change have caused the extensive degradation of grasslands worldwide, jeopardising ecosystem function and threatening human well-being. Toxic weeds have been constantly spreading in recent decades; indeed, their occurrence is considered to provide an early sign of land degeneration. Policy makers and scientific researchers often focus on the negative effects of toxic weeds, such as how they inhibit forage growth, kill livestock and cause economic losses. However, toxic weeds can have several potentially positive ecological impacts on grasslands, such as promoting soil and water conservation, improving nutrient cycling and biodiversity conservation, and protecting pastures from excessive damage by livestock. We reviewed the literature to detail the adaptive mechanisms underlying toxic weeds and to provide new insight into their roles in degraded grassland ecosystems. The findings highlight that the establishment of toxic weeds may provide a self-protective strategy of degenerated pastures that does not require special interventions. Consequently, policy makers, managers and other personnel responsible for managing grasslands need to take appropriate actions to assess the long-term trade-offs between the development of animal husbandry and the maintenance of ecological services provided by grasslands.
Fluorescent pseudomonads represent one of the largest groups of bacteria inhabiting the surfaces of plants, but their genetic composition in planta is poorly understood. Here, we examined the population structure and diversity of fluorescent pseudomonads isolated from sugar beet grown at two geographic locations (Oxford, UK and Auckland, New Zealand). To seek evidence for niche adaptation, bacteria were sampled from three types of leaves (immature, mature and senescent) and then characterized using a combination of genotypic and phenotypic analysis. We first performed multilocus sequence analysis (MLSA) of three housekeeping genes (gapA, gltA, acnB) in a total of 152 isolates (96 from Oxford, 56 from Auckland). The concatenated sequences were grouped into 81 sequence types and 22 distinct operational taxonomic units (OTUs). Significant levels of recombination were detected, particularly for the Oxford isolates (rate of recombination to mutation (r/m) = 5.23 for the whole population). Subsequent ancestral analysis performed in STRUCTURE found evidence of six ancestral populations, and their distributions significantly differed between Oxford and Auckland strains. Next, the ability to grow on 95 carbon sources was assessed using the BiologTM GN2 microtiter plates. A distance matrix was generated from the raw growth data (A660) and subjected to multidimensional scaling (MDS) analysis. There was a significant correlation between the substrate utilization profiles and MLSA genotypes. Both phenotypic and genotypic analyses indicated presence of a geographic structure for strains from Oxford and Auckland. Significant differences were genotypically detected between strains isolated from immature versus mature/senescent leaves. The fluorescent pseudomonads thus showed an ecotypic population structure, suggestive of adaptation to both geographical and local plant environments.