Miles D. Roberts, Olivia Davis, Emily B. Josephs, Robert J. Williamson
Many commonly studied species now have more than one chromosome-scale genome assembly, revealing a large amount of genetic diversity previously missed by approaches that map short reads to a single reference. However, many species still lack multiple reference genomes and correctly aligning references to build pangenomes is challenging, limiting our ability to study this missing genomic variation in population genetics. Here, we argue that $k$-mers are a crucial stepping stone to bridging the reference-focused paradigms of population genetics with the reference-free paradigms of pangenomics. We review current literature on the uses of $k$-mers for performing three core components of most population genetics analyses: identifying, measuring, and explaining patterns of genetic variation. We also demonstrate how different $k$-mer-based measures of genetic variation behave in population genetic simulations according to the choice of $k$, depth of sequencing coverage, and degree of data compression. Overall, we find that $k$-mer-based measures of genetic diversity scale consistently with pairwise nucleotide diversity ($pi$) up to values of about $pi = 0.025$ ($R^2 = 0.97$) for neutrally evolving populations. For populations with even more variation, using shorter $k$-mers will maintain the scalability up to at least $pi = 0.1$. Furthermore, in our simulated populations, $k$-mer dissimilarity values can be reliably approximated from counting bloom filters, highlighting a potential avenue to decreasing the memory burden of $k$-mer based genomic dissimilarity analyses. For future studies, there is a great opportunity to further develop methods to identifying selected loci using $k$-mers.
{"title":"k-mer-based approaches to bridging pangenomics and population genetics","authors":"Miles D. Roberts, Olivia Davis, Emily B. Josephs, Robert J. Williamson","doi":"arxiv-2409.11683","DOIUrl":"https://doi.org/arxiv-2409.11683","url":null,"abstract":"Many commonly studied species now have more than one chromosome-scale genome\u0000assembly, revealing a large amount of genetic diversity previously missed by\u0000approaches that map short reads to a single reference. However, many species\u0000still lack multiple reference genomes and correctly aligning references to\u0000build pangenomes is challenging, limiting our ability to study this missing\u0000genomic variation in population genetics. Here, we argue that $k$-mers are a\u0000crucial stepping stone to bridging the reference-focused paradigms of\u0000population genetics with the reference-free paradigms of pangenomics. We review\u0000current literature on the uses of $k$-mers for performing three core components\u0000of most population genetics analyses: identifying, measuring, and explaining\u0000patterns of genetic variation. We also demonstrate how different $k$-mer-based\u0000measures of genetic variation behave in population genetic simulations\u0000according to the choice of $k$, depth of sequencing coverage, and degree of\u0000data compression. Overall, we find that $k$-mer-based measures of genetic\u0000diversity scale consistently with pairwise nucleotide diversity ($pi$) up to\u0000values of about $pi = 0.025$ ($R^2 = 0.97$) for neutrally evolving\u0000populations. For populations with even more variation, using shorter $k$-mers\u0000will maintain the scalability up to at least $pi = 0.1$. Furthermore, in our\u0000simulated populations, $k$-mer dissimilarity values can be reliably\u0000approximated from counting bloom filters, highlighting a potential avenue to\u0000decreasing the memory burden of $k$-mer based genomic dissimilarity analyses.\u0000For future studies, there is a great opportunity to further develop methods to\u0000identifying selected loci using $k$-mers.","PeriodicalId":501044,"journal":{"name":"arXiv - QuanBio - Populations and Evolution","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142247365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mikhail Prokopenko, Paul C. W. Davies, Michael Harré, Marcus Heisler, Zdenka Kuncic, Geraint F. Lewis, Ori Livson, Joseph T. Lizier, Fernando E. Rosas
We study open-ended evolution by focusing on computational and information-processing dynamics underlying major evolutionary transitions. In doing so, we consider biological organisms as hierarchical dynamical systems that generate regularities in their phase-spaces through interactions with their environment. These emergent information patterns can then be encoded within the organism's components, leading to self-modelling "tangled hierarchies". Our main conjecture is that when macro-scale patterns are encoded within micro-scale components, it creates fundamental tensions (computational inconsistencies) between what is encodable at a particular evolutionary stage and what is potentially realisable in the environment. A resolution of these tensions triggers an evolutionary transition which expands the problem-space, at the cost of generating new tensions in the expanded space, in a continual process. We argue that biological complexification can be interpreted computation-theoretically, within the G"odel--Turing--Post recursion-theoretic framework, as open-ended generation of computational novelty. In general, this process can be viewed as a meta-simulation performed by higher-order systems that successively simulate the computation carried out by lower-order systems. This computation-theoretic argument provides a basis for hypothesising the biological arrow of time.
{"title":"Biological arrow of time: Emergence of tangled information hierarchies and self-modelling dynamics","authors":"Mikhail Prokopenko, Paul C. W. Davies, Michael Harré, Marcus Heisler, Zdenka Kuncic, Geraint F. Lewis, Ori Livson, Joseph T. Lizier, Fernando E. Rosas","doi":"arxiv-2409.12029","DOIUrl":"https://doi.org/arxiv-2409.12029","url":null,"abstract":"We study open-ended evolution by focusing on computational and\u0000information-processing dynamics underlying major evolutionary transitions. In\u0000doing so, we consider biological organisms as hierarchical dynamical systems\u0000that generate regularities in their phase-spaces through interactions with\u0000their environment. These emergent information patterns can then be encoded\u0000within the organism's components, leading to self-modelling \"tangled\u0000hierarchies\". Our main conjecture is that when macro-scale patterns are encoded\u0000within micro-scale components, it creates fundamental tensions (computational\u0000inconsistencies) between what is encodable at a particular evolutionary stage\u0000and what is potentially realisable in the environment. A resolution of these\u0000tensions triggers an evolutionary transition which expands the problem-space,\u0000at the cost of generating new tensions in the expanded space, in a continual\u0000process. We argue that biological complexification can be interpreted\u0000computation-theoretically, within the G\"odel--Turing--Post recursion-theoretic\u0000framework, as open-ended generation of computational novelty. In general, this\u0000process can be viewed as a meta-simulation performed by higher-order systems\u0000that successively simulate the computation carried out by lower-order systems.\u0000This computation-theoretic argument provides a basis for hypothesising the\u0000biological arrow of time.","PeriodicalId":501044,"journal":{"name":"arXiv - QuanBio - Populations and Evolution","volume":"190 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142247364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Suman Bhowmick, Patrick Irwin, Kristina Lopez, Megan Lindsay Fritz, Rebecca Lee Smith
Even as the incidence of mosquito-borne diseases like West Nile Virus (WNV) in North America has risen over the past decade, effectively modelling mosquito population density or, the abundance has proven to be a persistent challenge. It is critical to capture the fluctuations in mosquito abundance across seasons in order to forecast the varying risk of disease transmission from one year to the next. We develop a process-based mechanistic weather-driven Ordinary Differential Equation (ODE) model to study the population biology of both aqueous and terrestrial stages of mosquito population. The progression of mosquito lifecycle through these stages is influenced by different factors, including temperature, daylight hours, intra-species competition and the availability of aquatic habitats. Weather-driven parameters are utilised in our work, are a combination of laboratory research and literature data. In our model, we include precipitation data as a substitute for evaluating additional mortality in the mosquito population. We compute the textit{Basic offspring number} of the associated model and perform sensitivity analysis. Finally, we employ our model to assess the effectiveness of various adulticides strategies to predict the reduction in mosquito population. This enhancement in modelling of mosquito abundance can be instrumental in guiding interventions aimed at reducing mosquito populations and mitigating mosquito-borne diseases such as the WNV.
{"title":"A weather-driven mathematical model of Culex population abundance and the impact of vector control interventions","authors":"Suman Bhowmick, Patrick Irwin, Kristina Lopez, Megan Lindsay Fritz, Rebecca Lee Smith","doi":"arxiv-2409.11550","DOIUrl":"https://doi.org/arxiv-2409.11550","url":null,"abstract":"Even as the incidence of mosquito-borne diseases like West Nile Virus (WNV)\u0000in North America has risen over the past decade, effectively modelling mosquito\u0000population density or, the abundance has proven to be a persistent challenge.\u0000It is critical to capture the fluctuations in mosquito abundance across seasons\u0000in order to forecast the varying risk of disease transmission from one year to\u0000the next. We develop a process-based mechanistic weather-driven Ordinary\u0000Differential Equation (ODE) model to study the population biology of both\u0000aqueous and terrestrial stages of mosquito population. The progression of\u0000mosquito lifecycle through these stages is influenced by different factors,\u0000including temperature, daylight hours, intra-species competition and the\u0000availability of aquatic habitats. Weather-driven parameters are utilised in our\u0000work, are a combination of laboratory research and literature data. In our\u0000model, we include precipitation data as a substitute for evaluating additional\u0000mortality in the mosquito population. We compute the textit{Basic offspring\u0000number} of the associated model and perform sensitivity analysis. Finally, we\u0000employ our model to assess the effectiveness of various adulticides strategies\u0000to predict the reduction in mosquito population. This enhancement in modelling\u0000of mosquito abundance can be instrumental in guiding interventions aimed at\u0000reducing mosquito populations and mitigating mosquito-borne diseases such as\u0000the WNV.","PeriodicalId":501044,"journal":{"name":"arXiv - QuanBio - Populations and Evolution","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142247366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yawo Ezunkpe, Cynthia T. Nnolum, Rachidi B. Salako, Shuwen Xue
This study examines the behavior of solutions in a multi-patch epidemic model that includes a saturation incidence mechanism. When the fatality rate due to the disease is not null, our findings show that the solutions of the model tend to stabilize at disease-free equilibria. Conversely, when the disease-induced fatality rate is null, the dynamics of the model become more intricate. Notably, in this scenario, while the saturation effect reduces the basic reproduction number $mathcal{R}_0$, it can also lead to a backward bifurcation of the endemic equilibria curve at $mathcal{R}_0=1$. Provided certain fundamental assumptions are satisfied, we offer a detailed analysis of the global dynamics of solutions based on the value of $mathcal{R}_0$. Additionally, we investigate the asymptotic profiles of endemic equilibria as population dispersal rates tend to zero. To support and illustrate our theoretical findings, we conduct numerical simulations.
{"title":"Dynamics of solutions to a multi-patch epidemic model with a saturation incidence mechanism","authors":"Yawo Ezunkpe, Cynthia T. Nnolum, Rachidi B. Salako, Shuwen Xue","doi":"arxiv-2409.11443","DOIUrl":"https://doi.org/arxiv-2409.11443","url":null,"abstract":"This study examines the behavior of solutions in a multi-patch epidemic model\u0000that includes a saturation incidence mechanism. When the fatality rate due to\u0000the disease is not null, our findings show that the solutions of the model tend\u0000to stabilize at disease-free equilibria. Conversely, when the disease-induced\u0000fatality rate is null, the dynamics of the model become more intricate.\u0000Notably, in this scenario, while the saturation effect reduces the basic\u0000reproduction number $mathcal{R}_0$, it can also lead to a backward bifurcation\u0000of the endemic equilibria curve at $mathcal{R}_0=1$. Provided certain\u0000fundamental assumptions are satisfied, we offer a detailed analysis of the\u0000global dynamics of solutions based on the value of $mathcal{R}_0$.\u0000Additionally, we investigate the asymptotic profiles of endemic equilibria as\u0000population dispersal rates tend to zero. To support and illustrate our\u0000theoretical findings, we conduct numerical simulations.","PeriodicalId":501044,"journal":{"name":"arXiv - QuanBio - Populations and Evolution","volume":"45 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142247367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We use generating functionals to derive a dynamic mean-field description for generalised Lotka-Volterra systems with higher-order quenched random interactions. We use the resulting single effective species process to determine the stability diagram in the space of parameters specifying the statistics of interactions, and to calculate the properties of the surviving community in the stable phase. We find that the behaviour as a function of the model parameters is often similar to the pairwise model. For example, the presence of more exploitative interactions increases stability. However we also find differences. For instance, we confirm in more general settings an observation made previously in model with third-order interactions that more competition between species can increase linear stability, and the diversity in the community, an effect not seen in the pairwise model. The phase diagram of the model with higher-order interactions is more complex than that of the model with pairwise interactions. We identify a new mathematical condition for a sudden onset of diverging abundances.
{"title":"Higher-order interactions in random Lotka-Volterra communities","authors":"Laura Sidhom, Tobias Galla","doi":"arxiv-2409.10990","DOIUrl":"https://doi.org/arxiv-2409.10990","url":null,"abstract":"We use generating functionals to derive a dynamic mean-field description for\u0000generalised Lotka-Volterra systems with higher-order quenched random\u0000interactions. We use the resulting single effective species process to\u0000determine the stability diagram in the space of parameters specifying the\u0000statistics of interactions, and to calculate the properties of the surviving\u0000community in the stable phase. We find that the behaviour as a function of the\u0000model parameters is often similar to the pairwise model. For example, the\u0000presence of more exploitative interactions increases stability. However we also\u0000find differences. For instance, we confirm in more general settings an\u0000observation made previously in model with third-order interactions that more\u0000competition between species can increase linear stability, and the diversity in\u0000the community, an effect not seen in the pairwise model. The phase diagram of\u0000the model with higher-order interactions is more complex than that of the model\u0000with pairwise interactions. We identify a new mathematical condition for a\u0000sudden onset of diverging abundances.","PeriodicalId":501044,"journal":{"name":"arXiv - QuanBio - Populations and Evolution","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142247368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aggregation-diffusion equations are foundational tools for modelling biological aggregations. Their principal use is to link the collective movement mechanisms of organisms to their emergent space use patterns in a rigorous, non-speculative way. However, most existing studies implicitly assume that organism movement is not affected by the underlying environment. In reality, the environment is a key determinant of emergent space use patterns, albeit in combination with collective aspects of motion. This work studies aggregation-diffusion equations in a heterogeneous environment in one spatial dimension. Under certain assumptions, it is possible to find exact analytic expressions for the steady-state solutions to the equation when diffusion is quadratic. Minimising the associated energy functional across these solutions provides a rapid way of determining the likely emergent space use pattern, which can be verified via numerics. This energy-minimisation procedure is applied to a simple test case, where the environment consists of a single clump of attractive resources. Here, self-attraction and resource-attraction combine to shape the emergent aggregation. Two counter-intuitive results emerge from the analytic results: (a) a non-monotonic dependence of clump width on the aggregation width, (b) a positive correlation between self-attraction strength and aggregation width when the resource attraction is strong. These are verified through numerical simulations. Overall, the study shows rigorously how environment and collective behaviour combine to shape organism space use, sometimes in counter-intuitive ways.
{"title":"Aggregation-diffusion in heterogeneous environments","authors":"Jonathan R. Potts","doi":"arxiv-2409.10147","DOIUrl":"https://doi.org/arxiv-2409.10147","url":null,"abstract":"Aggregation-diffusion equations are foundational tools for modelling\u0000biological aggregations. Their principal use is to link the collective movement\u0000mechanisms of organisms to their emergent space use patterns in a rigorous,\u0000non-speculative way. However, most existing studies implicitly assume that\u0000organism movement is not affected by the underlying environment. In reality,\u0000the environment is a key determinant of emergent space use patterns, albeit in\u0000combination with collective aspects of motion. This work studies\u0000aggregation-diffusion equations in a heterogeneous environment in one spatial\u0000dimension. Under certain assumptions, it is possible to find exact analytic\u0000expressions for the steady-state solutions to the equation when diffusion is\u0000quadratic. Minimising the associated energy functional across these solutions\u0000provides a rapid way of determining the likely emergent space use pattern,\u0000which can be verified via numerics. This energy-minimisation procedure is\u0000applied to a simple test case, where the environment consists of a single clump\u0000of attractive resources. Here, self-attraction and resource-attraction combine\u0000to shape the emergent aggregation. Two counter-intuitive results emerge from\u0000the analytic results: (a) a non-monotonic dependence of clump width on the\u0000aggregation width, (b) a positive correlation between self-attraction strength\u0000and aggregation width when the resource attraction is strong. These are\u0000verified through numerical simulations. Overall, the study shows rigorously how\u0000environment and collective behaviour combine to shape organism space use,\u0000sometimes in counter-intuitive ways.","PeriodicalId":501044,"journal":{"name":"arXiv - QuanBio - Populations and Evolution","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142247402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Joao U. F. Lizarraga, Flavia M. D. Marquitti, Marcus A. M. de Aguiar
We investigate the role of assortative mating in speciation using the sympatric model of Derrida and Higgs. The model explores the idea that genetic differences create incompatibilities between individuals, preventing mating if the number of such differences is too large. Speciation, however, only happens in this mating system if the number of genes is large. Here we show that speciation with small genome sizes can occur if assortative mating is introduced. In our model individuals are represented by three chromosomes: one responsible for reproductive compatibility, one for coding the trait on which assortativity will operate, and a neutral chromosome. Reproduction is possible if individuals are genetically similar with respect to the first chromosome, but among these compatible mating partners, the one with the most similar trait coded by the second chromosome is selected. We show that this type of assortativity facilitates speciation, which can happen with a small number of genes in the first chromosome. Species, classified according to reproductive isolation, dictated by the first chromosome, can display different traits values, as measured by the second and the third chromosomes. Therefore, species can also be identified based on similarity of the neutral trait, which works as a proxy for reproductive isolation.
{"title":"Assortativity in sympatric speciation and species classification","authors":"Joao U. F. Lizarraga, Flavia M. D. Marquitti, Marcus A. M. de Aguiar","doi":"arxiv-2409.10466","DOIUrl":"https://doi.org/arxiv-2409.10466","url":null,"abstract":"We investigate the role of assortative mating in speciation using the\u0000sympatric model of Derrida and Higgs. The model explores the idea that genetic\u0000differences create incompatibilities between individuals, preventing mating if\u0000the number of such differences is too large. Speciation, however, only happens\u0000in this mating system if the number of genes is large. Here we show that\u0000speciation with small genome sizes can occur if assortative mating is\u0000introduced. In our model individuals are represented by three chromosomes: one\u0000responsible for reproductive compatibility, one for coding the trait on which\u0000assortativity will operate, and a neutral chromosome. Reproduction is possible\u0000if individuals are genetically similar with respect to the first chromosome,\u0000but among these compatible mating partners, the one with the most similar trait\u0000coded by the second chromosome is selected. We show that this type of\u0000assortativity facilitates speciation, which can happen with a small number of\u0000genes in the first chromosome. Species, classified according to reproductive\u0000isolation, dictated by the first chromosome, can display different traits\u0000values, as measured by the second and the third chromosomes. Therefore, species\u0000can also be identified based on similarity of the neutral trait, which works as\u0000a proxy for reproductive isolation.","PeriodicalId":501044,"journal":{"name":"arXiv - QuanBio - Populations and Evolution","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142247398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Approximately one billion years (Gyr) in the future, as the Sun brightens, Earth's carbonate-silicate cycle is expected to drive CO$_2$ below the minimum level required by vascular land plants, eliminating most macroscopic land life. Here, we couple global-mean models of temperature- and CO$_2$-dependent plant productivity for C$_3$ and C$_4$ plants, silicate weathering, and climate to re-examine the time remaining for terrestrial plants. If weathering is weakly temperature-dependent (as recent data suggest) and/or strongly CO$_2$-dependent, we find that the interplay between climate, productivity, and weathering causes the future luminosity-driven CO$_2$ decrease to slow and temporarily reverse, averting plant CO$_2$ starvation. This dramatically lengthens plant survival from 1 Gyr up to $sim$1.6-1.86 Gyr, until extreme temperatures halt photosynthesis, suggesting a revised kill mechanism for land plants and potential doubling of the future lifespan of Earth's land macrobiota. An increased future lifespan for the complex biosphere may imply that Earth life had to achieve a smaller number of ``hard steps'' (unlikely evolutionary transitions) to produce intelligent life than previously estimated. These results also suggest that complex photosynthetic land life on Earth and exoplanets may be able to persist until the onset of the moist greenhouse transition.
{"title":"Substantial extension of the lifetime of the terrestrial biosphere","authors":"R. J. Graham, Itay Halevy, Dorian Abbot","doi":"arxiv-2409.10714","DOIUrl":"https://doi.org/arxiv-2409.10714","url":null,"abstract":"Approximately one billion years (Gyr) in the future, as the Sun brightens,\u0000Earth's carbonate-silicate cycle is expected to drive CO$_2$ below the minimum\u0000level required by vascular land plants, eliminating most macroscopic land life.\u0000Here, we couple global-mean models of temperature- and CO$_2$-dependent plant\u0000productivity for C$_3$ and C$_4$ plants, silicate weathering, and climate to\u0000re-examine the time remaining for terrestrial plants. If weathering is weakly\u0000temperature-dependent (as recent data suggest) and/or strongly\u0000CO$_2$-dependent, we find that the interplay between climate, productivity, and\u0000weathering causes the future luminosity-driven CO$_2$ decrease to slow and\u0000temporarily reverse, averting plant CO$_2$ starvation. This dramatically\u0000lengthens plant survival from 1 Gyr up to $sim$1.6-1.86 Gyr, until extreme\u0000temperatures halt photosynthesis, suggesting a revised kill mechanism for land\u0000plants and potential doubling of the future lifespan of Earth's land\u0000macrobiota. An increased future lifespan for the complex biosphere may imply\u0000that Earth life had to achieve a smaller number of ``hard steps'' (unlikely\u0000evolutionary transitions) to produce intelligent life than previously\u0000estimated. These results also suggest that complex photosynthetic land life on\u0000Earth and exoplanets may be able to persist until the onset of the moist\u0000greenhouse transition.","PeriodicalId":501044,"journal":{"name":"arXiv - QuanBio - Populations and Evolution","volume":"29 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142247397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Biological evolution is realised through the same mechanisms of birth and death that underlie change in population density. The deep interdependence between ecology and evolution is well-established, but much theory in each discipline has been developed in isolation. While recent work has accomplished eco-evolutionary synthesis, a gap remains between the logical foundations of ecology and evolution. We bridge this gap with a new equation that defines a summed value for a characteristic across individuals in a population, from which the fundamental equations of population ecology and evolutionary biology (the Price equation) are derived. We thereby unify the fundamental equations of population ecology and biological evolution under a general framework. Our unification further demonstrates the equivalence between mean population growth rate and evolutionary fitness, shows how ecological and evolutionary change are reflected in the first and second statistical moments of fitness, respectively, and links this change to ecosystem function.
{"title":"Foundations of ecological and evolutionary change","authors":"A. Bradley Duthie, Victor J. Luque","doi":"arxiv-2409.10766","DOIUrl":"https://doi.org/arxiv-2409.10766","url":null,"abstract":"Biological evolution is realised through the same mechanisms of birth and\u0000death that underlie change in population density. The deep interdependence\u0000between ecology and evolution is well-established, but much theory in each\u0000discipline has been developed in isolation. While recent work has accomplished\u0000eco-evolutionary synthesis, a gap remains between the logical foundations of\u0000ecology and evolution. We bridge this gap with a new equation that defines a\u0000summed value for a characteristic across individuals in a population, from\u0000which the fundamental equations of population ecology and evolutionary biology\u0000(the Price equation) are derived. We thereby unify the fundamental equations of\u0000population ecology and biological evolution under a general framework. Our\u0000unification further demonstrates the equivalence between mean population growth\u0000rate and evolutionary fitness, shows how ecological and evolutionary change are\u0000reflected in the first and second statistical moments of fitness, respectively,\u0000and links this change to ecosystem function.","PeriodicalId":501044,"journal":{"name":"arXiv - QuanBio - Populations and Evolution","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142247369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sebastian Towers, Aleksandra Kalisz, Alicia Higueruelo, Francesca Vianello, Ming-Han Chloe Tsai, Harrison Steel, Jakob N. Foerster
Anti-viral therapies are typically designed or evolved towards the current strains of a virus. In learning terms, this corresponds to a myopic best response, i.e., not considering the possible adaptive moves of the opponent. However, therapy-induced selective pressures act on viral antigens to drive the emergence of mutated strains, against which initial therapies have reduced efficacy. To motivate our work, we consider antibody designs that target not only the current viral strains but also the wide range of possible future variants that the virus might evolve into under the evolutionary pressure exerted by said antibodies. Building on a computational model of binding between antibodies and viral antigens (the Absolut! framework), we design and implement a genetic simulation of the viral evolutionary escape. Crucially, this allows our antibody optimisation algorithm to consider and influence the entire escape curve of the virus, i.e. to guide (or ''shape'') the viral evolution. This is inspired by opponent shaping which, in general-sum learning, accounts for the adaptation of the co-player rather than playing a myopic best response. Hence we call the optimised antibodies shapers. Within our simulations, we demonstrate that our shapers target both current and simulated future viral variants, outperforming the antibodies chosen in a myopic way. Furthermore, we show that shapers exert specific evolutionary pressure on the virus compared to myopic antibodies. Altogether, shapers modify the evolutionary trajectories of viral strains and minimise the viral escape compared to their myopic counterparts. While this is a simple model, we hope that our proposed paradigm will enable the discovery of better long-lived vaccines and antibody therapies in the future, enabled by rapid advancements in the capabilities of simulation tools.
{"title":"Opponent Shaping for Antibody Development","authors":"Sebastian Towers, Aleksandra Kalisz, Alicia Higueruelo, Francesca Vianello, Ming-Han Chloe Tsai, Harrison Steel, Jakob N. Foerster","doi":"arxiv-2409.10588","DOIUrl":"https://doi.org/arxiv-2409.10588","url":null,"abstract":"Anti-viral therapies are typically designed or evolved towards the current\u0000strains of a virus. In learning terms, this corresponds to a myopic best\u0000response, i.e., not considering the possible adaptive moves of the opponent.\u0000However, therapy-induced selective pressures act on viral antigens to drive the\u0000emergence of mutated strains, against which initial therapies have reduced\u0000efficacy. To motivate our work, we consider antibody designs that target not\u0000only the current viral strains but also the wide range of possible future\u0000variants that the virus might evolve into under the evolutionary pressure\u0000exerted by said antibodies. Building on a computational model of binding\u0000between antibodies and viral antigens (the Absolut! framework), we design and\u0000implement a genetic simulation of the viral evolutionary escape. Crucially,\u0000this allows our antibody optimisation algorithm to consider and influence the\u0000entire escape curve of the virus, i.e. to guide (or ''shape'') the viral\u0000evolution. This is inspired by opponent shaping which, in general-sum learning,\u0000accounts for the adaptation of the co-player rather than playing a myopic best\u0000response. Hence we call the optimised antibodies shapers. Within our\u0000simulations, we demonstrate that our shapers target both current and simulated\u0000future viral variants, outperforming the antibodies chosen in a myopic way.\u0000Furthermore, we show that shapers exert specific evolutionary pressure on the\u0000virus compared to myopic antibodies. Altogether, shapers modify the\u0000evolutionary trajectories of viral strains and minimise the viral escape\u0000compared to their myopic counterparts. While this is a simple model, we hope\u0000that our proposed paradigm will enable the discovery of better long-lived\u0000vaccines and antibody therapies in the future, enabled by rapid advancements in\u0000the capabilities of simulation tools.","PeriodicalId":501044,"journal":{"name":"arXiv - QuanBio - Populations and Evolution","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142247396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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