Evolutionary Ecology Research Articles

Highlighted articles for June 2022

Highlighted articles for June 2022

Phylogenomic analyses in Phrymaceae reveal extensive gene tree discordance in relationships among major clades.

PremisePhylogenomic datasets using genomes and transcriptomes provide rich opportunities beyond resolving bifurcating phylogenetic relationships. Monkeyflower (Phrymaceae) is a model system for evolutionary ecology. However, it lacks a well‐supported phylogeny as a basis for a stable taxonomy and for macroevolutionary comparisons.MethodsWe sampled 24 genomes and transcriptomes in Phrymaceae and closely related families, including eight newly sequenced transcriptomes. We reconstructed the phylogeny using IQ‐TREE and ASTRAL, evaluated gene tree discordance using PhyParts, Quartet Sampling, and a cloudogram, and carried out reticulation analyses using PhyloNet and HyDe. We searched for whole genome duplication (WGD) events using chromosome numbers, synonymous distances, and gene duplication events as evidence.ResultsMost gene trees support the monophyly of Phrymaceae and each of its tribes. Most gene trees also support tribe Mimuleae being sister to Phrymeae + Diplaceae + Leucocarpeae, with extensive gene tree discordance among the latter three. Despite the discordance, the monophyly of Mimulus s.l. is rejected, and no individual reticulation event among the Phrymaceae tribes is well‐supported. Reticulation likely occurred among Erythranthe bicolor and closely related species. No ancient WGD was detected in Phrymaceae. Instead, small‐scale duplications are among potential drivers of macroevolutionary diversification of Phrymaceae.ConclusionsWe show that analysis of reticulate evolution is sensitive to taxon sampling and methods used. We also demonstrate that phylogenomic datasets using genomes and transcriptomes present rich opportunities to investigate gene family evolution and genome duplication events involved in lineage diversification and adaptation.

Spatial-Temporal Evolution and Driving Forces of NDVI in China's Giant Panda National Park.

Identifying the ecological evolution trends and vegetation driving mechanisms of giant panda national parks can help to improve the protection of giant panda habitats. Based on the research background of different geomorphological zoning, we selected the MODIS NDVI data from 2000 to 2020 to analyze the NDVI trends using a univariate linear model. A partial correlation analysis and multiple correlation analysis were used to reveal the influence of temperature and precipitation on NDVI trends. Fourteen factors related to meteorological factors, topographic factors, geological activities, and human activities were selected, and the Geographically Weighted Regression model was used to study the mechanisms driving NDVI change. The results were as follows: (1) The NDVI value of Giant Panda National Park has fluctuated and increased in the past 21 years, with an annual growth rate of 4.7%/yr. Affected by the Wenchuan earthquake in 2008, the NDVI value fluctuated greatly from 2008 to 2012, and reached its peak in 2018. (2) The NDVI in 94% of the study area improved, and the most significant improvement areas were mainly distributed in the northern and southern regions of Southwest Subalpine and Middle Mountain and the Xiaoxiangling area. Affected by the distribution of fault zones and their local activities, vegetation degradation was concentrated in the Dujiangyan–Anzhou area of Hengduan Mountain Alpine Canyon. (3) The Geographically Weighted Regression analysis showed that natural factors were dominant, with climate and elevation having a double-factor enhancement effect, the peak acceleration of ground motion and fault zone having a superimposed effect, and river density and slope having a double effect, all of which had a significant impact on the NDVI value of the surrounding area. To optimize the ecological security pattern of the Giant Panda National Park, we recommended strengthening the construction of ecological security projects through monitoring meteorological changes, preventing, and controlling geo-hazards, and optimizing the layout and intensity of human activities.

Internal Prices and Optimal Exploitation of Natural Resources

Within the framework of traditional fishery management, we propose an interpretation of natural resource prices. It leads to an economic taxation mechanism based on internal prices and reduces a complex problem of optimal long-term exploitation to a sequence of one-year optimization problems. Internal prices obey natural, economic patterns: the increase in resource amount diminishes taxes, and the rise in the number of “fishers” raises taxes. These taxes stimulate cooperative agent behavior. We consider new problems of optimal fishing, taking into account an adaptive migration of the fish population in two regions. To analyze these problems, we use evolutionary ecology models. We propose a paradoxical method to increase the catch yield through the so-called fish “luring” procedure. In this case, a kind of “giveaway” game occurs, where the region with underfishing becomes more attractive for fish and for catches in the future.

Phylogenetic, Microbiome, and Diet Characterisation of Wall Lizards in the Columbretes Archipelago (Spain): Clues for Their Conservation

The Columbretes archipelago consists of a group of small volcanic islets located in the western Mediterranean near the east of the Iberian Peninsula. Four of its islands are inhabited by the wall lizard Podarcis liolepis, whose populations have been considered vulnerable. The purpose of this study was to assess the level of genetic diversity across the archipelago and the possible evolutionary origin of the Columbretes lizard populations. Additionally, we investigated the evolutionary ecology of these populations using a DNA-based metabarcoding approach to characterise both their microbiota and trophic interactions. The genetic results reported very low genetic diversity and corroborated the conspecificity between insular populations and P. liolepis from the mainland (Peñagolosa region). The results of the metabarcoding analyses based on faecal samples were in accordance with an omnivorous ecology, suggesting that specific microbiota communities in the insular populations might be correlated with differences in host ecology and phylogeny. These results are a valuable contribution to the current understanding of the evolution of Columbretes’ lizards and provide important information for conservation management.

Telomeres, the loop tying cancer to organismal life-histories.

Recent developments in telomere and cancer evolutionary ecology demonstrate a very complex relationship between the need of tissue repair and controlling the emergence of abnormally proliferating cells. The trade-off is balanced by natural and sexual selection and mediated via both intrinsic and environmental factors. Here, we explore the effects of telomere-cancer dynamics on life history traits and strategies as well as on the cumulative effects of genetic and environmental factors. We show that telomere-cancer dynamics constitute an incredibly complex and multifaceted process. From research to date, it appears that the relationship between telomere length and cancer risk is likely nonlinear with good evidence that both (too) long and (too) short telomeres can be associated with increased cancer risk. The ability and propensity of organisms to respond to the interplay of telomere dynamics and oncogenic processes, depends on the combination of its tissue environments, life history strategies, environmental challenges (i.e., extreme climatic conditions), pressure by predators and pollution, as well as its evolutionary history. Consequently, precise interpretation of telomere-cancer dynamics requires integrative and multidisciplinary approaches. Finally, incorporating information on telomere dynamics and the expression of tumour suppressor genes and oncogenes could potentially provide the synergistic overview that could lay the foundations to study telomere-cancer dynamics at ecosystem levels.

Abstract A001: Modeling cancer’s ecological and evolutionary dynamics

Abstract We present a theoretical modeling framework, called the G function, to understand cancer speciation, diversification, and environmental adaptation. The G function integrates both the ecology and evolution of cancer and has been used in evolutionary ecology. However, the G function has not yet been widely applied to problems in cancer. Here, we build the G-function framework from fundamental Darwinian principles and discuss how cancer is inherently an evolutionary game. We begin with a simple model of cancer growth and add on components of cancer cell competition and drug resistance. To aid in exploration of eco-evolutionary modeling with this approach, we also present a user-friendly online tool. We argue that G-functions are useful to understand the games cancer plays in a biologically mechanistic fashion. Citation Format: Anuraag Bukkuri, Kenneth J. Pienta, Ian Hockett, Robert H. Austin, Emma U. Hammarlund, Sarah R. Amend, Joel S. Brown. Modeling cancer’s ecological and evolutionary dynamics [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr A001.

Impacts of changing conditions on the ecological environment of the Shiyang River Basin, China

Abstract The effect of climate change and human activities on water resources, glaciers, and land use/cover has been widely studied. The Shiyang River Basin is an important natural reserve in the Hexi Corridor of Gansu Province. Global warming and human activities have led to extreme ecological changes in this region. Exploring the response of the ecological environment of the Shiyang River Basin to a changing climate is important for studying the sustainable development of the fragile ecological environment in this basin. The meteorological data for this study was obtained from the China Meteorological Data Service Center, and the average temperature and precipitation data were acquired from four meteorological stations. By investigating the changes in the watershed climate and social environment in the Shiyang River Basin, the corresponding changes in glacial and surface water resources, landscape patterns, and natural and anthropogenic factors in the basin under changing environment were analysed. The results show that the temperature in different seasons has increased in the past 60 years, and the inclination rate of air temperature was 0.56 °C/10a. In addition, precipitation increased slightly at 0.737 mm/10a. Natural conditions and climate change have reduced the supply of glacial meltwater in the Qilian Mountains, and the regulation of glacial snow in downstream rivers is poor. The distribution of the water production rate in each river was similar to that of precipitation. The runoff modulus of the deep mountain area was greater than that of the shallow mountainous area. The western region is larger than the eastern region, and the rationalisation of the land use structure in the basin has a decisive effect on optimising the landscape pattern of the basin. The spatial evolution of the vegetation cover in the basin is generally stable; under the combined action of climate change and human activities, downstream water resources are reducing, and landscape vegetation is shifting to a high risk in the Shiyang River Basin. Among the influencing factors, anthropogenic factors play a dominant role in the runoff variation in this basin. Climate warming and unregulated human activities are the main causes of regional environmental deterioration. The study findings can contribute to understanding the coupling relationship between the natural and ecological evolution process of the inland river basin and human activities in the arid zone. Further, exploring the change trend of the ecological environment of the Shiyang River Basin can help determine the human adaptation countermeasures to mitigate ecological deterioration and ensure sustainable development of ecologically fragile areas.

Effect of Operating Parameters and Energy Expenditure on the Biological Performance of Rotating Biological Contactor for Wastewater Treatment

The rotating biological contactor (RBC) is resistant to toxic chemical and shock loadings, and this results in significant organic and nutrient removal efficiencies. The RBC system offers a low-energy footprint and saves up to 90% in energy costs. Due to the system’s low-energy demand, it is easily operable with renewable energy sources, either solar or wind power. An RBC was employed to degrade pollutants in domestic wastewater through biodegradation mechanisms in this study. The high microbial population in the RBC bioreactor produced excellent biological treatment capacity and higher effluent quality. The results showed that the RBC bioreactor achieved an average removal efficiency of 73.9% of chemical oxygen demand (COD), 38.3% of total nitrogen (TN), 95.6% of ammonium, and 78.9% of turbidity. Investigation of operational parameters, disk rotational speed, HRT, and SRT, showed the biological performance impact. Disk rotational speed showed uniform effluent quality at 30–40 rpm, while higher values of disk rotational speed (>40 rpm) resulted in lower effluent quality in COD, TN, and turbidity. The longer hydraulic retention time and sludge retention time (SRT) facilitated higher biological performance efficiency. The longer SRTs enabled the higher TN removal efficiency because of the higher quantity of microbial biomass retention. The longer SRT also resulted in efficient sludge-settling properties and reduced volume of sludge production. The energy evaluation of the RBC bioreactor showed that it consumed only 0.14 kWh/m3, which is significantly lower than the conventional treatment methods; therefore, it is easily operable with renewable energy sources. The RBC is promising substitute for traditional suspended growth processes as higher microbial activity, lower operational and maintenance costs, and lower carbon foot print enhanced the biological performance, which aligns with the stipulations of ecological evolution and environment-friendly treatment.

The high diversity and phylogenetic signal of antipredator mechanisms of the horned frog species of Proceratophrys Miranda-Ribeiro, 1920 (Amphibia: Anura: Odontophrynidae)

Phylogenetic signals indicate the phenotypic similarity of antipredator mechanisms among related species. Herein, we assessed the antipredator mechanisms of the horned frog Proceratophrys laticeps, compiled a database including closely phylogenetically-related species, and evaluated their phylogenetic signals. Our dataset comprises 80 records for 13 species of Proceratophrys, totalizing 11 antipredator mechanisms and 15 variations of these mechanisms. Six antipredator mechanisms show high similarity in the trees’ roots within Proceratophrys (e.g., aggression, aposematism, camouflage, distress call, immobility, and interrupt calling). Our observations show the first records of antipredator mechanisms for P. laticeps, and the first report of interrupt calling for Proceratophrys genus, contributing to the knowledge on the behavioural ecology of Proceratophrys species, addressing new insights for ecological trait evolution by multiple ancestral states of amphibians.

Evolution of the human pathogenic lifestyle in fungi.

Fungal pathogens cause more than a billion human infections every year, resulting in more than 1.6 million deaths annually. Understanding the natural history and evolutionary ecology of fungi is helping us understand how disease-relevant traits have repeatedly evolved. Different types and mechanisms of genetic variation have contributed to the evolution of fungal pathogenicity and specific genetic differences distinguish pathogens from non-pathogens. Insights into the traits, genetic elements, and genetic and ecological mechanisms that contribute to the evolution of fungal pathogenicity are crucial for developing strategies to both predict emergence of fungal pathogens and develop drugs to combat them.

Engineering artificial photosynthetic life-forms through endosymbiosis

The evolutionary origin of the photosynthetic eukaryotes drastically altered the evolution of complex lifeforms and impacted global ecology. The endosymbiotic theory suggests that photosynthetic eukaryotes evolved due to endosymbiosis between non-photosynthetic eukaryotic host cells and photosynthetic cyanobacterial or algal endosymbionts. The photosynthetic endosymbionts, propagating within the cytoplasm of the host cells, evolved, and eventually transformed into chloroplasts. Despite the fundamental importance of this evolutionary event, we have minimal understanding of this remarkable evolutionary transformation. Here, we design and engineer artificial, genetically tractable, photosynthetic endosymbiosis between photosynthetic cyanobacteria and budding yeasts. We engineer various mutants of model photosynthetic cyanobacteria as endosymbionts within yeast cells where, the engineered cyanobacteria perform bioenergetic functions to support the growth of yeast cells under defined photosynthetic conditions. We anticipate that these genetically tractable endosymbiotic platforms can be used for evolutionary studies, particularly related to organelle evolution, and also for synthetic biology applications.

Evolutionary Ecology of Plant-Arthropod Interactions in Light of the "Omics" Sciences: A Broad Guide.

Aboveground plant-arthropod interactions are typically complex, involving herbivores, predators, pollinators, and various other guilds that can strongly affect plant fitness, directly or indirectly, and individually, synergistically, or antagonistically. However, little is known about how ongoing natural selection by these interacting guilds shapes the evolution of plants, i.e., how they affect the differential survival and reproduction of genotypes due to differences in phenotypes in an environment. Recent technological advances, including next-generation sequencing, metabolomics, and gene-editing technologies along with traditional experimental approaches (e.g., quantitative genetics experiments), have enabled far more comprehensive exploration of the genes and traits involved in complex ecological interactions. Connecting different levels of biological organization (genes to communities) will enhance the understanding of evolutionary interactions in complex communities, but this requires a multidisciplinary approach. Here, we review traditional and modern methods and concepts, then highlight future avenues for studying the evolution of plant-arthropod interactions (e.g., plant-herbivore-pollinator interactions). Besides promoting a fundamental understanding of plant-associated arthropod communities’ genetic background and evolution, such knowledge can also help address many current global environmental challenges.

EPPO Datasheet: Naupactus xanthographus

EPPO Datasheet: <i>Naupactus xanthographus</i>

Научный базис экономических стратегий

The scientific basis of energy strategies is represented by the sciences of natural-humanitarian synthesis that study the "nature-man-society" system: ergodynamics, system theory of capital, the science of harmony, synthetic evolutionary ecology. Method of their construction is a deductive one: from the laws of socio-natural development to the society and an individual. National wealth, or country (national) capital, is the main indicator of the state of societies. It is considered as the structural energy (energy potential) of societies in value terms. Country capital is calculated as the sum of physical, human, social and natural capital. Natural capital includes reproducible (ecocapital) and non-reproducible (paleocapital) components. Index of the life quality of societies (changes from 0 to 1) is the arithmetic mean of the ratio of the private capital production of each society to the maximum values of the production of these capitals among all the societies under consideration. The purpose of economic strategies is to ensure the systemic progress of societies. It is implemented with the growth over time of the specific (per person) country capital and, accordingly, the quality of life index. Maximum progress takes place with harmonious resolution of the opposites existing in societies. The article proposes a method for calculating country capital, its components and the life quality index.

Machine learning models identify gene predictors of waggle dance behaviour in honeybees.

The molecular characterization of complex behaviours is a challenging task as a range of different factors are often involved to produce the observed phenotype. An established approach is to look at the overall levels of expression of brain genes-or 'neurogenomics'-to select the best candidates that associate with patterns of interest. However, traditional neurogenomic analyses have some well-known limitations: above all, the usually limited number of biological replicates compared to the number of genes tested-known as the "curse of dimensionality." In this study we implemented a machine learning (ML) approach that can be used as a complement to more established methods of transcriptomic analyses. We tested three supervised learning algorithms (Random Forests, Lasso and Elastic net Regularized Generalized Linear Model, and Support Vector Machine) for their performance in the characterization of transcriptomic patterns and identification of genes associated with honeybee waggle dance. We then matched the results of these analyses with traditional outputs of differential gene expression analyses and identified two promising candidates for the neural regulation of the waggle dance: boss and hnRNP A1. Overall, our study demonstrates the application of ML to analyse transcriptomics data and identify candidate genes underlying social behaviour. This approach has great potential for application to a wide range of different scenarios in evolutionary ecology, when investigating the genomic basis for complex phenotypic traits, and can present some clear advantages compared to the established tools of gene expression analysis, making it a valuable complement for future studies.

Evolutionary Ecology of Fixed Alternative Male Mating Strategies in the Ruff (Calidris pugnax)

A few empirical examples document fixed alternative male mating strategies in animals. Here we focus on the polymorphism of male mating strategies in the ruff (Calidris pugnax, Aves Charadriiformes). In ruffs, three fixed alternative male mating strategies coexist and are signaled by extreme plumage polymorphism. We first present relevant data on the biology of the species. Then we review the available knowledge of the behavioral ecology of ruffs during the breeding season, and we detail the characteristics of each of the three known fixed male mating strategies. We next turn to the results of exceptional quality accumulated on both the structural and functional genomics of the ruff over the past few years. We show how much these genomic data can shed new, mechanistic light on the evolution and maintenance of the three fixed alternative male mating strategies. We then look if there is sufficient indication to support frequency-dependent selection as a key mechanism in maintaining these three strategies. Specifically, we search for evidence of equal fitness among individuals using each of the three strategies. Finally, we propose three lines of research avenues that will help to understand the eco-evolutionary dynamics of phenotypic differences within natural populations of this iconic model species.

Adaptation to climate change through seasonal migration revealed by climatic versus demographic niche models.

Predicting the geographic range of species and their response to climatic variation and change are entwined goals in conservation and evolutionary ecology. Species distribution models (SDMs) are foundational in this effort and used to visualize the geographic range of species as the spatial representation of its realized niche. SDMs are also used to forecast range shifts under climate change, but often in the absence of empirical evidence that climate limits population growth. We explored the influence of climate on demography, seasonal migration, and the extent of the geographic range in song sparrows (Melospiza melodia), a species thought to display marked local adaptation to regional climate. To do so, we developed SDMs to predict the demographic and climate niches of migratory and resident song sparrows across our study area in western North America from California to Alaska, using 48years of demographic data from a focal population in British Columbia and 1.2million continental-scale citizen science observations. Spatial agreement of our demographic and climate niche models in the region of our focal population was strong (76%), supporting the hypothesis that demographic performance and the occurrence of seasonal migration varied predictably with climatic conditions. In contrast, agreement at the northern (58%) and southern (40%) extents of our study area was lower, as expected if the factors limiting population growth vary regionally. Our results support the hypothesis that local climate drives spatial variation in the occurrence of seasonal migration in song sparrows by limiting the fitness of year-round residents, and suggest that climate warming has favored range expansions and facilitated an upward shift in elevational range song sparrows that forgo seasonal migration. Our work highlights the potential role of seasonal migration in climate adaptation and limits on the reliability of climate niche models not validated with demographic data.

Clonal thermal preferences affect the strength of the temperature-size rule

The issue of trade-offs among traits is of special interest in evolutionary ecology. We hypothesized that the temperature-size rule (TSR) may be affected by the level of thermal specialization and that this pattern may be traded off with the temperature-dependent potential for population growth rate. We used six parthenogenetic rotifer clones previously exposed to different thermal conditions. We tested hypotheses on the relationships between (i) thermal acclimation and clone body size, (ii) thermal preference and fitness, and (iii) thermal specialization and strength of the TSR (the slope of response). Positive verification of (i) makes it justifiable to refer the other investigated traits as thermal preference. Addressing the issues (ii) and (iii) is our pioneering contribution to the question of whether the strength of the size-to-temperature response differs across life strategies. Interclonal differences in female body size were examined in common garden conditions at 25 °C. We estimated the population growth rate and strength (= slope) of the size-to-temperature response across four thermal regimes: 15, 20, 25, and 30 °C. Thermal acclimation of the clones was related to body size, with clones acclimated to higher temperatures being smaller. Warm-acclimated clones had a narrower thermal range (= were more specialized). The TSR was stronger in rotifers acclimated to intermediate thermal conditions than in specialists.

Allometric model of brain morphology of Hemiculter leucisculus and its variation along climatic gradients.

Prior studies on Hemiculter leucisculus, which is a widespread native fish in China, mainly focused on its growth, feeding habits, and individual fecundity, but few have investigated the brain. In this research, we explored the developmental patterns of the Hemiculter leucisculus brain and found the brain showed allometry through sample time points and three age groups. At the same time, we found that the brain varied along climatic gradients. The volumes of the olfactory bulbs, telencephalic lobes, optic tectum, corpus cerebelli, and total brain in the south were larger than those in the north, while the volume of the hypothalamus in the north was larger than in the south. This study provides a view for the in-depth study of the acclimatized mechanism of the teleost brain, lays a foundation for the further study of evolutionary ecology, and provides a reference for the phenotypic plasticity of the teleost brain.