Posted on Authorea 24 Jan 2021 | The copyright holder is the author/funder. All rights reserved. No reuse without permission. | https://doi.org/10.22541/au.161148258.83074885/v1 | This a preprint and has not been peer reviewed. Data may be preliminary. ucs fclnzto fnwhssb oe aaiepplto u otayt h rviigbelief, prevailing the parameters all to of contrary Maximization but factor. important population least parasite the novel is mutations) the a influence (e.g. by positively emergence the novelty hosts parameters and of three new all rate population of that the pathogen suggest colonization the simulations of of of The dynamics emergence Fitting. Paradigmsuccess evolutionary the Stockholm Ecological the to the of of understand leading role framework better process possible theoretical to fundamental the simulations under most on analyzed IBM the size) are using putatively propagule results – The and diseases. species emergence; infectious novelty host new of new rate of rate; colonization (reproduction the pathogens of parameters populational +554199985055 fone: Summary: [email protected], Boeger, A Walter author: *Corresponding 3 2 1 infectious Feronato G. of Sofia emergence the on model Title: simple Running a from hosts. insights new – in agents happen” to are Paradigm waiting Stockholm SARS-CoV-2. “Accidents the in from observed and as simulations exploration, the host from of derived dynamics Diseases new the Infectious of and Emergent emergence opportunity - discussed. the of that to Diseases dynamics observations determinant Infectious the fundamental empirical Emergent an on the of is Insights support isolation) special ecological results in for the - mechanisms Hence, in associations fitting. breakdown anticipate. ecological the by can species/lineage (i.e. we host encounter than previous of their larger retro-colonize much novelty the to thus, of of lineages support facilitation rate is, fast-evolving theoretical provide synergetic of Capacity the also capacity a simulations belief, the in The prevailing of result influence retention the microorganisms. parameters the positively pathogenic to all for for of contrary parameters theoretical scenario Maximization but three expected the the population factor. all emulates important parasite and under that least novel colonization the suggest analyzed a is by simulations mutations) pathogen are hosts The the (e.g. new results of emergence Fitting. of dynamics The colonization Ecological evolutionary of the of success understand diseases. role the better most possible infectious to the the putatively simulations new – IBM and species of using population host Paradigm emergence new Stockholm of the the colonization of the to framework on leading pathogens size) of propagule process parameters and populational emergence; fundamental three novelty of of effect combined rate and rate; individual (reproduction possible the modeling through evaluates study This Abstract 2021 24, January 1 hosts. Feronato on new Sofia model in agents simple infectious a of from insights emergence – the happen” to waiting “Accidents nvriaeFdrld Paran´a do Federal Universidade etd olga nvriaeFdrld aa´,CiaPsa 92,Crtb,P 13-8,Brazil. 81531-980, PR Curitiba, 19020, Postal Paran´a, Caixa do Federal Universidade Zoologia, Brazil. de 81531-980, Dept PR Paran´a, Curitiba, do Federal F´ısica, Brazil. Universidade de 81531-980, Dept PR Paran´a, Curitiba, do Federal Universidade Interactions, Biological hssuyeautstruhmdln h osbeidvda n obndeeto three of effect combined and individual possible the modeling through evaluates study This 1 1 arn Araujo Sabrina , ipemdlfrtesceso mrec fifciu pathogens infectious of emergence of success the for model simple A arn Araujo Sabrina , 1,2 1 atrA Boeger A. Walter , n atrA Boeger A. Walter and , 1 1,3* 1 Posted on Authorea 24 Jan 2021 | The copyright holder is the author/funder. All rights reserved. No reuse without permission. | https://doi.org/10.22541/au.161148258.83074885/v1 | This a preprint and has not been peer reviewed. Data may be preliminary. a uvv nanwhs ept en nasbotmmcniin hra hyddntepiil explore explicitly not did they success. whereas colonization pathogens condition, pathogen’s adapted sub-optimum the a poorly influence in that might being indicate of that despite also empirical compatibility parameters host (2015) by of new populational revealed al. recently degree a et been high in has Araujo survive a perspective 2020). can to this al., for limited et Support not Araujo (Khokhlova host. are conclusions, the new experimentation model colonizations other the support to successful Among mathematical simulations population that ubiquitous. The a pathogen likely suggested the population. developed is also evolving Fitting (2015) (2015) an Ecological al. by al. by et species colonization et host host Araujo new that Paradigm, of postulate colonization Stockholm al., the et the evaluated Brooks of that 2008; framework Klemens, ability the and the the Agosta of under Under 2006; properties - (Janz al., environment emergent et the Hypothesis represent Brooks or Oscillation to 1985; species thought (Janzen, the other 2019). Fitting are with - Ecological – - by Paradigm 1985a; interact 1985) change that (Janzen, the (Erwin, to species Fitting the of of Pulse Taxon composed is elements Ecological system the associations two through complex and of other occur 2008) ecology The changes Nylin, and 2008). ecological and evolution frame- Klemens, of the theoretical and on a majority such vast perspective Agosta provides new the 2019) this al., that of et 2018). recognition element Brooks al., fundamental 2015; et Brooks, The (Nylin and work. the associations (Hoberg symbiotic accommodate Paradigm of cannot Stockholm century, evolution The a pathogen and widely for in origin the dominant dynamic that the that primary conceptually out on sustain a been knowledge points strongly is has present evidence associations 2018) which host-pathogen historical al. paradigm, 2008; of and et evolutionary structure Brooks Braga phylogenetic held complex and to Increasing The Hoberg according ecology. 2013). 2002; repertoire and al. Shenbrot (=host evolution et and range of Vienne (Krasnov host amount host-switching in large De last a expansion as 2010; the detected date al. in still this et evolution al., co-speciation, to host-parasite et towards Agosta called biased (Agosta on been Paradox strongly studies selective has Parasite protocols of strong what the utilizing accumulation of even - the context that, paradox a from years a in results 40 generated Paradox relation vision Parasite 1:1 This a The 1998). under 2010). Shykoff, parasites built that and interaction associations perspective host-parasite/pathogen selective (Kaltz theoretical the of symmetrically pressures by nature a accepted and influenced the Traditionally, as Brooks often its 2010). regarded 2018; 2020), al., is al. of Brooks et et and (Agosta Nylin perspective Agosta specialists in ultimate 2019; researcher’s perspective are al. historical et the a Brooks under to by 2019; this waiting of Boeger influences ”accidents summary are a strongly (see EIDs framework are that evolutionary and prediction studies studies present the These such (EIDs), of 2014). Diseases fulfilling However, al., the Infectious 2005). security, et is Ferrao, Emerging food crisis and Brooks of This and (Brooks 2005; crisis 2019). agriculture, happen” al., so-called al., health, et the et human Woolhouse (Brooks considering in future interest, 1995; research special Hauser, of of and area are (Heard vigorous associations years a host-pathogen recent of became evolution during it and and origin fundamental the influencing is mechanisms ecological the Understanding Introduction from derived explo- Diseases discussed. host Infectious are of Emergent Paradigm dynamics Keywords: of Stockholm the dynamics the and the the from - on Diseases to and Insights Infectious determinant simulations SARS-CoV-2. Emergent fundamental that the of in an observations observed special is empirical in as isolation) the - ration, ecological associations support for new mechanisms results of in emergence the fitting. breakdown Hence, ecological the fast-evolving anticipate. by (i.e. of encounter can species/lineage capacity the we host of than previous retention micro- pathogenic larger their the for for retro-colonize scenario support expected to theoretical the lineages provide emulates also and colonization simulations the The of organisms. facilitation synergetic a in result niiulbsdmdl otsicig mrigifciu iess tchl Paradigm. Stockholm diseases, infectious emerging host-switching, model, Individual-based 2 Capacity opportunity s hs much thus, is, of Posted on Authorea 24 Jan 2021 | The copyright holder is the author/funder. All rights reserved. No reuse without permission. | https://doi.org/10.22541/au.161148258.83074885/v1 | This a preprint and has not been peer reviewed. Data may be preliminary. h piu au ftecmon hntp moe nptoes ti xdtruhu h simulation. the ( throughout number fixed single a is a It by pathogens. characterized on is imposed phenotype host compound the the (2015), of value al. optimum et the Araujo in as simplicity, For phenotype compound populational host. standard the a set to compatibility or its locus to as same according n This labeled selection the is G. under phenotype (= within and and compound phenotype generations, 0 traits The over between compound distinct change vary individual’s two to can the subjected of which defines features, expression 2020), either characters the Brooks of all values and as of the Agosta understood sum assume can The be phenotypes loci. can binary of which The phenotypes. zero, individual or binary one G of 2020) Brooks and pathogen Each descriptions: host and Pathogen and (https://github.com/sofiagalvao2020/SimpleHost_- The symbioses Github interaction. new of through host-pathogen the available types the is as different that switching). Fortran) these several pressure designate in spe- to selection will (written host applied we the model hereafter new be propagule to simplicity, by can variable for related challenged associations; system with are were ecological consumer-resource (which pathogens novelties The compatibility simulations, phenotypic represents). of of During host levels emergence species. different of host representing rates parameters new cies and populational a rates, some of of reproduction influence success sizes, the colonization investigate to the designed on was (IBM) model individual-based An et model Mondragon 2015; The Brooks, and Hoberg 2014; 2001; al., (Fauci, et diseases simulations and Brooks Figui´e, infectious the 2018). 2005; and - new of Ferrao, Morand of result perspective and 2018; overall emergence ecological Brooks al., The of 2004; an crisis diseases. al., under recognized et infectious the associations Morens emerging to environ- host-pathogens of support new new process instrumental of the of provides colonization into of case et insights process this Briski new the in 2010; provides on al., - accounts 2017). et previous conditions Stinchcombe, Hurford support mental and 2010; strongly Gould Hoberg, simulations 2016; Lockwood 2006; resulting Mason, The Flatt, 2004; 2015; tested and Dobson, al., population Braendle The et key 2001; 2005; Johnson as (Woolhouse, the al., 2012; considered 2003). epidemiology et and frequently al., and Woolhouse Pkalski rate), are invasion 2005; mutation which Although biological al., to of (e.g. et of all (analogous (2015). species population, studies emergence that invasive novelty pathogen in studies al. of founder instance, parameters similar t the rate for as of the Araujo study, such size rate, as propagule changes, to reproduction colonization systems, an ecological the models of host-pathogens on equivalent are of success in based to parameters the type focused simulations applied for other is be using important can model developed (2015) considered it significance The be the different, al. explore could species. methodologically et to that host Araujo Paradigm parameters new of Stockholm selected of study the of of the interaction elements expand and considering we ecological (see (IBM) work mutations and model present releasing individual-based environmental preceding the to ancestral immediately in by the association Hence, frequently from in less change fitting far 2001). reflecting and ecological plant–bird Morse 2019) conditions, by also and al., new 2004), et occur of (Brooks (Wilkinson, likely disruptions Colonization structuring most community 2006; pressure, and 2020). (Agosta, selective insects associations al., phytophagous ecological (Janeˇcek et 2010), evolution 2018), pollination in (Hoberg, change al., species ecological invasive et of including process Nylin 2020), any Brooks, incorporate to and expanded (Agosta recently was Paradigm Stockholm The o h einn ftesmlto,tesmo l lc”i dnia o l rpgl niiul-creating individuals- propagule all for identical is “loci” all of sum the simulation, the of beginning the For . i sdsrbdb opudpeoye(= phenotype compound a by described is p i,n nwihtesbcit dniytepathogen the identify subscripts the which in , p 0 ttesato h ooiainattempt. colonization the of start the at 3 udmna aaiyspace capacity fundamental aaiyspace capacity scmoe yinheritable by composed is elzdcpct space capacity realized p sdfie nAgosta in defined as h i hc represents which ) ftegeneration the of of Posted on Authorea 24 Jan 2021 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.161148258.83074885/v1 — This a preprint and has not been peer reviewed. Data may be preliminary. sdi h oenSnhss(e rosadAot 02 aade l 05 gsaadBok 2020). Brooks and Agosta 2015; al. op- et as expression Laland - the 2012; of rate” Agosta meaning “mutation and genetic using strictly Brooks from the (see refrain avoid We Synthesis to Modern - 2020). novelty” the Brooks evolutionary in and of used Agosta comprising emergence of also mechanisms, “rate see to 2019; inheritance posed al. simulating et Brooks generations emerge, 2014, can and throughout novelties die evolutionary maintained These progenitors the be host. the the and events, to fitness reproduction accumulate, pathogen’s the all influencing ( After indirectly individual, emergence novelty 0). new the rate to to The 1 subjected from be will or 1). that probability 1 generation (Fig a to next cycle with descendant the 0 Each progenitor constitute from achieved. descendants its is the changing of descendants of characters number (i.e. selected of total be locus chain the can until progenitor same repeated the the - is reposition process inherits with This offspring one once. generate than generation to more next selected are the population for surviving descendants the of ( number The step N reproduction. previous asexual the assume survived we simplicity, that ( pathogens rate the reproduction step, this At ( Reproduction survivors the and individual, every compound on same to surviving the 1) of presenting step, capable (Eq. individuals probability are all survival that with this phenotypes - imposes of population diversity propagule the the For is larger phenotype 1). the (Fig rate, host deviation specific the that ( larger rate the deviation - the host ( of phenotype units compound in pathogen ) the between distance the is d where pathogen P each of probability survival distribution: the normal as a imposed is selection The Selection phenotypes compound undergo identical will but present defined, they randomly considered, distinct are is phenotypes individual their pathogen simplicity, = For one simulation. than per more attempt when colonization of one size propagule only a is with starts dynamics The of population Dynamics pathogen the on capacity carrying a by represented also assume we Here i,n survival s,n p 0 aaiyspace capacity *b = [?] Reproduction p fti au osntexceed not does value this if i,n i udmna aaiyspace capacity fundamental = hti,te aetesm tesi h e otbtcrydffrn hntps(..represent (i.e. phenotypes different carry but host new the in fitness same the have they is, that – σ − exp p p 0 Selection h h nta hntp itnefo h rpgl otehs is host the to propagule the from distance phenotype initial the - h (2) − p d h 2 2 fteptoe (called pathogen the of ,the b, i,n . /.Bsdsdfiiga neato rsueaon hsotmmvle h otis host the value, optimum this around pressure interaction an defining Besides G/2. = i and (1) , vrg ubro ecnat e aetl n h arigcpct ( capacity carrying the and parental) per descendants of number average Reproduction μ) σ .Tedvainrt ersnsteslcinsrnt moe ytenew the by imposed strength selection the represents rate deviation The ). eest n ido oet nrdcdit h olo aaiyo the of capacity of pool the into introduced novelty of kind any to refers K .Ec trto tprpeet generation a represents step iteration Each ). tews,tenme fdsednsis descendants of number the otherwise, , Fg1,a ealdbelow. detailed as 1), (Fig nomto space information N 0 ahgnidvdascalne oclnz h ot-there - host the colonize to challenged individuals pathogen 4 p i,n nBok n gsa21,Jbok tal. et Jablonka 2012, Agosta and Brooks in Ns,n n h piu moe ytehs ( host the by imposed optimum the and ) i rdc ffpigdpnigo the on depending offspring produce ) nagvngeneration given a in K individuals. μ ficroaiganvlyper novelty a incorporating of d 0 N K = Selection s,n admidvdasof individuals Random . ( n p ot h etmodel next the to go ) 0 hr h pathogens the where - p h and )/ n σ. n tfollows it and Reproduction n+1 h model The K ilbe will p .For ). i,n=0 p h Posted on Authorea 24 Jan 2021 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.161148258.83074885/v1 — This a preprint and has not been peer reviewed. Data may be preliminary. opnnsalwdabte nesadn fteidvda n obndiflec fdsic ae of rates distinct of influence these Parsing combined and pressure. individual selective new the the of and, under understanding ( host phenotype emergence new better novelty a compound of a its colonization allowed of during components population evolution pathogen the the pertinent, of establishment when of success the simulated We Results parameters the for and invariable qualitatively were simulations ihmtto ae bevdi iue eg rk n oln 99.Frhroe lhuhbiologically although Furthermore, 1999). Holland for and ( value Drake rate null (e.g. viruses the in unreal, observed rates mutation high iuain aesonta ml nraei h rpgl ie(rm1t 0 ral xaddthe expanded greatly 10) pathogens to for 1 90% than (from greater size success of propagule probability the a in in a resulted increase with which phenotypes small compound a of diversity that shown when have simulations Simulations non-synergic the growth; for population 2b). detected the was (Fig. on rate evident success when more establishment faster is twice of values about 10% these capacity between carrying rate the novelty reaches increasing population (Fig the probability of the effect on The 10 effect low and same 0.0 the between for practically rates had novelty rate For novelty of of probability 2b). variations the other (10 all and values - - establishment rate simulation novelty the of high of effect event Only the reproductive on first only the depend until will surviving survival (in individual as species single curve host a black new for the the approaching of curves forces probability selective (e.g. non-black the 1). surviving compare Figure individual 2a; in one curve the Fig. of black probability for (the the 1 reproduction recovered approaches probability success first survival the ( Eq. the until rates represent reproduction than persist Greater lower to 2 is individual ( establishment colonizing Figs. of propagule single probability in a single the for curves a therefore (black - For events distance selection 2). this following (Fig. decays propagule propagule, the host probability of survival new distance the the variable in under evaluated population colonization d were following pathogen ( pathogen parameters the of host analyzed population of the All the from of phenotype resource. size and compound host fitness new the a of behavior of the and association new to0 according varied 10 host the on are from only values distance depends fixed (the 1) ones remaining (Eq. the ( parameter fixing The fittest and them the 1). of two Table it varying in defined by highlighted and calculated extinction was without parameter simulations each of to pathogen proportion the the until the calculated or then generations as We 1,000 for extinct. repetitions went simulation 700 population ran we combination, parameter each For analyses data and Simulations 0 rdal eue h rbblt fetbihet(i.2 n )–wihwsa xetdrsl since result expected an was which – b) and 2a (Fig. establishment of probability the reduces gradually -6 d d ,10 0 0 b b ≈ r presented. are rbblt fscesu establishment successful of probability -5 d .) h rbblt fetbiheto h ahgnpplto ilb h aea htexpected that as same the be will population pathogen the of establishment of probability the 7.5), = ,poauesz ( size propagule ), poauecmon hntp p.oesadr eito itn rmteotmmimposed). optimum the from distant deviation standard one app. phenotype compound (propagule 1 0 10 , < d p . Fg c.Frlre rpgl ie,ti ucs xed pto up extends success this sizes, propagule larger For 2c). (Fig. 0.9 -4 i,n 0 10 , = = p h d -3 =G/2 0 10 , μ .Frteptoe ouaint ooietenwhs,i ed osriesuccessive survive to needs it host, new the colonize to population pathogen the For ). ,poauesz ( size propagule ), -2, n 10 and otelatfi au ( value fit least the to ) N μ d 0 0 b ersnsteifro ii foraayi.W lovre h reproduction the varied also We analysis. our of limit inferior the represents efixed we , ) opudpeoyesz ( size phenotype compound ,), ao h ahgnetbihet(i.2) As 2a). (Fig. establishment pathogen the favor ) -1 ihrnvlyvle,sc s10 as such values, novelty Higher . -2 n 10 and d σ 0 N p n eeldteriflec ntepoaiiyo establishment of probability the on influence their revealed and ) 0 0ad sacneune h rpgl opudphenotype compound propagule the consequence, a as and, 10 = 0 d -3 0 ,adrpoutv ae( rate reproductive and ), ≤ a lasoeo h aidprmtr n tvre between varied it and parameters varied the of one always was h rbblt fscespatclyddntdffr ecig0 reaching differ, not did practically success of probability the , -1 . h esblt ftepoaiiyo ucsflestablishment successful of probability the of sensibility The . a esrbeeeto h ouainlpoaiiyof probability populational the on effect measurable a had ) d 0 ≤ p G/ 0 5 = 0 h netgtdvle fnvlyrt ( rate novelty of values investigated The 20. G .Gvnta h rpgl uvvlprobability survival propagule the that Given ). 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Data may be preliminary. nteecutro ae uigrpouto seHfae ta.21) oee,tert fincrease of rate the However, 2013). al. et limitation Hufbauer nor (see processes reproduction collaborative during social model mates not with of did associated relative encounter we be the the to as simulation and appears stochastic, in every novelty colonization likely during evolutionary Since most sizes of issues, propagule (same increasing demographic emergence distribution. by observed unchanged of conferred geographic advantage processes kept rate the 2007) were and low loci), Darling a propagules ecologic and used (Hufbauer of in size Roman effects) fitness changes propagule 2009; Allee during in of (Simberloff and usually variation case size effect) stochasticity are involving the sizes (founder’s population propagule in (e.g. genetic Large small communities demographic and 2018). corresponding in of 2013) al. and consequences et areas Cassey al. of geographic 2009; et reduction species or al. host the et - new Lockwood with 2012) 2007; of linked al. colonization al. et et the the (Sax Hatcher influence species to invasive 10 2001; positively due to of al. fitness, known host, et composed suboptimal extensively (May under new is population persist pressure the initial and ( propagule an of thrive compatibility Indeed, to small selection model, was probability relatively the the the the impact representing of of hosts by significant to increase values in most imposed adapting significant even different novelties the a not the in of far, even resulted simulations, By emergence colonizers propagules; the success. of of of this absence number novel on scope complete a the impacts the by distinct hosts for within new in However, observed of resulted colonization emergence, 2). parameters of novelty success evolutionary explored of the (Fig. rate positively the population influence in size pathogen increase propagule the and that suggests rate, simulations reproductive the of result general The also Discussion is expan- phenotypes the ancestral parameter, of other maintenance variability, every increased besides phenotypic maximizing the parameters smaller that By populational indicating depict other 4b). larger, (Fig. that by even influenced 1970) (Fig. populations is Wallace phenotypes phenotypes in load; pre-existing of resulted genetic sion of emergence of loss novelty concept greater of the of with rates to growth, retention Lower analogous populational the during (something in populations 4a). resulted quali- load previous emergence the larger and of on initial correspondingly rates outcome the with High in unexpected present an colonization. (variants) following also phenotypes revealed populations, compound host novelties the evolutionary colonized of of 3, profile newly emergence tative the (Fig. the in novelties of capacity rates of Varying absence carrying the the in achieved ( even and Surprisingly, rate persisted species. novelty 3). populations the pathogen (Fig. greater simulated 3, scenarios The all (Fig. for phenotypes 3). compound stabilization of of diversity (Fig. values the higher host increasing also stabilize the optimum, and by towards the =10 imposed evolve towards evolution to value the phenotypes fitness faster compound non-null optimal the a allowed the with colonization around scenario following simulated generations every the of in in parameters repre- based populational lineages the expected, host for As 2). even observed (Fig. probability scenario, have independently the this requirements/capacity) exceeding tested pathogen Under far pathogens the colonization, the with 2). of compatible probability (Fig. less high are colonization a that of (resources success resources of distant senting probability (B=7.5; the parameters on all of effect maximization probabilities simultaneous survival the phenotypes This Finally, for increases. pattern size cliff-like propagule a the as depicting than imposed phenotypes diminishes, optimum higher neighboring the quickly the meet effect of not rate probability do survival that high the phenotypes compound maximizing the host, of the rate by survival the for significant was effect -2 .Drn iuain,pplto ierpdyrahsteetbihdcryn aaiy vnthough Even capacity. carrying established the reaches rapidly size population simulations, During ). d 0 ≈ .,idpneto h rpgl size. propagule the of independent 1.2, μ aospplto rwh h arigcpct sahee uherirta phenotype than earlier much achieved is capacity carrying the growth, population favors d 0 μ 6 ept ulttv ieecsi h obnto of combination the in differences qualitative despite . d 0 ≈ 1). μ μ , =0.1; h mrec fpeoyi novelties phenotypic of emergence the N 0 20 eutdi synergetic a in resulted =200) μ=0 μ many ) ,the ), μ Posted on Authorea 24 Jan 2021 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.161148258.83074885/v1 — This a preprint and has not been peer reviewed. Data may be preliminary. 02 n h aiblt fteptoe n ot a nuneas h ucm ftecolonization the of outcome the also influence may hosts and of pathogen value McLennan the the and for and of (Brooks proxy host resources variability accessible of both the al. convergence only to et evolutionary and according the Streicker because vary 2002) 2015; of be parsimoniously compatibility al. to host distance considered defining et the be appear the the resources Braga should influence distances in 2013; the and that phylogenetic involved Since al. quality traits species, et species 2007). relative of (Martiny pathogen Webb host lineage space the and pathogen multidimensional the Gilbert describe specific the - between 2010; a to estimate distance reference and and/or to - host Phylogenetic imperfect limits, of properties), time compatibility within an pathogen. host this appears, represents the at expansion species to (i.e. range accessible host resources imperfect resource one (likely new original the only matching the the the pathogen, new suitable Therefore, of perhaps, the when emergence expected but, of the meet. is 2020) requirements conditions - Brooks between environments and environmental perfect) Agosta new 2019; than of exploring al. continuously colonization rather are et or pathogens (Brooks of organisms - species) variants associations of the host Gubler of groups representatives (e.g. 2007; real-world resources common Gaunt the accessible in most and that Woolhouse bacteria the expect pathogenic 2001; we are Since of al. bacteria perhaps et and and (Cleaveland general 2019). viruses diseases in Duarte-Neto Pekala-Safi´nska that viruses 2018; infectious 2010; coronaviruses understandable of emergent of property thus, with feature a is, instance, biological associated likely For intrinsically It is ” . an it well. . frequently. as but as less suggested 2017), viruses, near occurring al. were co-divergence a for et virus-host species is observed (Menachery with host transmission those compatible , of . “cross-species is . to . oscillations that outcome of viruses continuous compares This (2017) evolution the Holmes likely diseases. of Duchˆene, the and infectious values feature Geoghegan, understanding of universal of of emergence in conclusions combination corresponding significant the the this especially and with that organisms is of fact 2009) group (grey The (Holmes this synergism RNA-viruses pronounced 2). among generate simulations particularly the Fig. in maximized, variability in are the considered line of emergence parameters degree three of the all rates and individuals When actual of reproduction, number scenario, of the population. rate this than the donor under important pressure), original Consequently, (see less (=propagule the of variants are 2019). host mutations) capable higher-fitness new al. are the (e.g. originally et novelties colonizing that than evolutionary variants Brooks hosts) inheritable pathogen 2015; 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importance accessible et in Boeger secondary of and evolutionary (Pepin suggested has accumulation of Brooks viruses) associate emergence The as 2007; of as Hoberg consumer rate species, and such the the (Brooks organisms host that Paradigm of indicate infectious simple new results rates for as our of such rates mutation Hence, successful colonization mutation - high 2015). of associations (e.g. al. to probability et new alone many the Viana novelties of 2012; by in emergence linked al. increase the (from et expressive often Selman novelties that more is of considering in a emergence - especially rate in of diseases result, reproductive resulted rate unexpected in 7.5) the an increases to in is size, 1.5 increases propagule 1000-fold (from variable than fold colonization with – simulations 10 (Fig. the than relationship less than linear new evident direct the a less of displayin 7 nomto space information μ =10 yBok n Agosta and Brooks by -6 to μ =10 d 0 -3 u it but , .This ). Posted on Authorea 24 Jan 2021 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.161148258.83074885/v1 — This a preprint and has not been peer reviewed. 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However, mixing and Brooks, faunal and scales for (Hoberg opportunities across of associations determinant complex evolutionary central over structured a disruptions environmental host been accompanying different have or pathogens. of independent time in and encounter exchange oscillation of climate intense general, rate fostering In the clade, promote augmenting same and communities, the barriers 2017). of organismic ecological al. many of et pre-existing the lineages, Hoberg composition of in 2015; the 2008, permeability fluctuations Brooks in the climatological and shuffling change Hoberg with 2007; usually during associated Hoberg frequent fluctuations and more are Brooks Climatological are which 2002; opportunities Klassen of And and 2020). many (Hoberg Brooks associations past disruptions, the and new Agosta environmental of is 2019; emergence of al. the it et to periods Brooks determinant and essential 2015; more al. anticipate, a et is (Araujo can 2002). that McLennan isolation) we when ecological and hosts for than related Brooks mechanisms distantly in most larger among specilization is possible much on “emerging also disease, is discussion infectious is that it in (see new but convergent increase assertion hosts, a is(are) of An resource(s) of the species 2005). the related emergence Ferrao for closely the among and support with occur (Brooks to associated theoretical likely happen” potentially further to pathogens, waiting by provide accidents host-repertoire study evolutionary are this EIDs. diseases of of infectious re-emergence Gonz´alez-Salazar, results the Stephens, and and combined of that emergence 2020, recent Bevins The retro-colonization idea epidemiological 2014; of e of the Franklin in cases al. process 2019, element in just et al. the important especially than S´anchez-Cordero Jablonka et an 2017), on Favoretto e more 1995; by be understanding suggested Lamb should includes better (as retro-colonization and which a monitoring Hence, Jablonka (i.e. provide species/lineages. - may emergence host mutations novelty 2020) original random Brooks of with Celorio-Mancera and nature perspective of associated Agosta well real that This solely are as the variants species. is SARS-CoV-2, (such of and animal data as adaptation retention other 2016) empirical such the available into viruses, al. and with spillover RNA 1982), along et recent ). analyzed al. from conservatism 2019 et humans phylogenetic (Holland al. in of hybridization et retro-colonizing and Brooks of mutation facilitate 2001; retention by may fitting the al. rapidly ecological for et evolve by to support Janz species/lineage host known theoretical 1998; previous provides Nylin their quantitatively frequency outcome retro-colonize and low and to This at (Janz variants qualitatively lineages C). “ancestral” fast-evolving changing 4B, retain of although putatively capacity (Fig. mutation - the - fitness resource (e.g. pathogen host novelties supposed new evolutionary lower the the of despite of of emergence pressure profile of selective simula- genetic rate the The the under the EIDs. of viruses), for values surveillance for higher health at rates in that important suggest above-proposed particularly the strongly makes humans tions that of dynamics host-exploration retro-colonization this of synanthropic of scenario aspect surveillance. or another active domestic yet 9 opportunity fecutr(..tebekonin breakdown the (i.e. encounter of Capacity Posted on Authorea 24 Jan 2021 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.161148258.83074885/v1 — This a preprint and has not been peer reviewed. Data may be preliminary. rg,M . ruo .B,Aot,S,Bok,D,Hbr,E,Nln . ogr .A,21:Host 2018: A., W. diversification. Boeger, and . range . . host S., in Nylin, oscillations E., generates Hoberg, landscape D., fitness Brooks, heterogeneous S., a Agosta, in B., dynamics S. evolution?use Araujo, in P., accommodation M. genetic Braga, for role 10.1002/bies.20456 A doi: 2006: for 10.1002/bies.20456. T., Implications DOI: Flatt, diversity: & population C., virus Braendle, RNA 2011: M., Vignuzzi, & transmission. A., inter-species and K. host-switching, Stapleford, transmission, (Monogenoidea). of V., gyrodactylids Border´ıa, Mode A. viviparous 2005: by B., K. queen 10.1645/ge-515r.1 Engers, red DOI: & 1000–1007. the R., M. from Pie, escape C., the W. D. Kritsky, Boeger, A., & W., W. F. Boeger, Hartenthal, von P., E. of Hoberg, emergence fitting. 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N p p μ b rqec fcmon hntp safnto ftedsac fteptoe opudpeoyefrom phenotype compound pathogen ( the host, of the distance ( by the size: of imposed function value each a optimum as for the phenotype emergence compound novelty of respective frequency of the rates to 4. respective correspond - Figure plots The 1. line Table two blue in last 3. a presented the as Figure those ( in are drawn in following: lines size, the depicted vertical population are colors) The the graphic (same phenotype represents 1). greater axis time (Table indicate vertical generation 1,000 colors right = warmer The capacity imposed generation, value carrying population. given optimum the the the in in from frequency frequency phenotype phenotype compound compound pathogen depicts the ( of host, the the distance by in the 1) indicate Table axis in vertical values highest (the 3. maximized Figure are surviving parameters of all individual when pathogen in pathogen single simulations. a defined the of of are each probability establishment at used the colonization of values represents following graph parameter event every reproductive simulation in first remaining the line the black The graph, each 1. Table in parameter tested specifically ( size propagule ) generations of number ( pre-determined distance a ( for novelties 2. evolutionary sequences Figure of cyclic emergence these of to rate subjected pre-defined are a populations to according phenotype parental undergo the then will to population pathogen subjected is phenotype, pound 1. Figure figures to Legends σ K Definition G Short Parameters rtfu eprleeet clrdlns fec itaehglgtdb h etcllnsi iue3 and 3b Figure in lines vertical the by highlighted are list each of lines) respectively. (colored 3c, elements temporal four first ( ( and follow: as times generation 0 h 0 c a 1 ylo ie,1 lgtoag ie,2 dr-rneln) 5(e ie,50(rw ie.The line). (brown 500 line), (red 35 line), (dark-orange 25 line), (light-orange 13 line), (yellow =10 ) ) d μ 0 rbblt fetbiheto h ahgnpplto safnto ftepoauephenotype propagule the of function a as population pathogen the of establishment of Probability vlto fcmon hntp iest/rqec n ouainsz vrgnrtos Left generations. over size population and diversity/frequency phenotype compound of Evolution lwhr ftemdldnmc.Teiiilpplto,wt niiul fietclcom- identical of individuals with population, initial The dynamics. model the of Flowchart aneac foiia hntpsacrigt h aeo vltoaynvlis Relative novelties. evolutionary of rate the to according phenotypes original of Maintenance .Tegah rsn h ffc f( of effect the present graphs The ). =10 d i,n ubro iuainrpttoso ie e fparameters. of set given a of run was repetitions simulation simulation each of that Number generations of number Maximum rpgl hntp.I enstepeoyedistance phenotype size the Propagule defines It phenotype. Propagule piu hntp moe ytehost the by imposed Phenotype Optimum oet aeprlcs rbblt ftatsaechange state trait of probability step locus, reproduction per per rate growth Novelty population average rate; Reproduction opudpeoyesz;Lnt ftebnr hrcesta en ahptoe.3,4,5,6,7,80, 70, 60, 50, 40, 30, pathogens on host the by imposed pressure selection the lower the value its support higher can the host probability; pathogen. the survivor each size for define population rate that maximum Deviation characters pathogen’s binary The the capacity; of Carrying Length size; phenotype Compound -4 N ,weestehrzna xsidct eeaintm nsmltos h rnepalette orange The simulations. in time generation indicate axes horizontal the whereas ), 0 n ( and ntepoaiiyo salsmn o ayn eoredsacs( distances resource varying for establishment of probability the on ) )μ β) a a ) =10 5(elwln) 2 dr-rneln) 0 rdln) 0 bonln) ( line); (brown 500 line), (red 200 line), (dark-orange 120 line), (yellow 45 ) μ .;( 0.0; = -2 , N Reproduction Selection 0 1( =1 b d ) i,n μ c o w eeso vltoaynvlyrtsadpropagule and rates novelty evolutionary of levels two for ) 10 = ) a μ ntenwyclnzdhs.Uo uvvl h simulated the survival, Upon host. newly-colonized the in erdcinrt,( rate, reproduction ) =10 h agtrcmon hntp ildffrfo the from differ will phenotype compound daughter The . -4 16 n ( and ; -2 d , 0 N q() h ryln ersnsteprobability the represents line grey The (1). Eq - 0 c =200, ) μ 10 = b 75.Ec uv ersnsspecific represents curve Each =7.5). b -2 d vltoaynvlyrt,ad( and rate, novelty evolutionary ) 0 h eann aaee values parameter remaining the - ewe rpgl n oti h rtgnrto fteclnzto seE.)0 Eq.1) (see colonization the of generation first the in host and propagule between d 0 .Ecp o the for Except ). μ .Descendent ). b c ) 700 1000 1 G/2 10 1.5 10 1000 tnadvle applied values Standard < 0 0 0,200 100, 50, 10, , -6 d .,55 7.5 5.5, 3.5, , ,10 0 00 00 00 5000 4000, 3000, 2000, , < -5 G/20 , 10 -4 10 , -3 10 , 100 -2 ,10 -1 0.0. , Posted on Authorea 24 Jan 2021 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.161148258.83074885/v1 — This a preprint and has not been peer reviewed. Data may be preliminary. 17 Posted on Authorea 24 Jan 2021 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.161148258.83074885/v1 — This a preprint and has not been peer reviewed. Data may be preliminary. 18