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Evolution of Ecological Communities in Spatially Heterogeneous Environments
Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
2019 (English)Doctoral thesis, comprehensive summary (Other academic)Alternative title
Evolution av ekologiska samhällen i rumsligt heterogena miljöer (Swedish)
Abstract [en]

Evolutionarily stable communities are the endpoints of evolution, and ecological communities whose traits are under selection will eventually settle into them. Hence, the properties of such communities are of particular interest, as they can persist over long evolutionary time scales. The notion of an evolutionarily stable strategy - an evolved strategy that cannot be beat by any other once established - has now been part of theoretical ecology for almost 50 years, and the theory for evolutionarily stable strategies and communities, and how they are reached has become increasingly versatile. However, for environments where conditions vary in space, so-called heterogeneous environments, efficient analytical and numerical tools for studying evolutionarily stable communities and how they come about have been lacking. Hence, many questions regarding how evolutionarily stable diversity is generated and maintained when ecological and evolutionary forces vary in space remain unexplored. In particular, how spatially averaged selection and selective forces derived from spatial variability can act together to either promote or inhibit evolutionarily stable diversity is not well understood.  

In this thesis, I use a two-pronged approach towards answering such questions by developing the necessary analytical and numerical tools for assembling and analyzing evolutionarily stable communities in heterogeneous environments, and by then employing these tools to study communities of resource competitors and food webs. Specifically, I derive expressions for directional and stabilizing/disruptive selection when the spatially heterogeneous ecological dynamics of a community are described by reaction-diffusion equations. These expressions allow us to understand selection across an environment in terms of local selection pressures, and also enable efficient numerical implementations of evolutionary community assembly procedures that lead to evolutionarily stable communities.  

Applied to the communities of resource competitors and food webs I find that the selective forces derived from spatially averaged selection and those derived from spatial variability can act both in concert or in opposition. If these forces act in opposition and if the spatial variability of local selection is high, a high diversity of organisms can form even when spatially averaged selection is stabilizing. In contrast, if spatially averaged selection is disruptive, it can prevent more diverse communities from forming by creating few globally unbeatable strategies. However, these forces can also act disruptively in concert to create more diverse communities. Together, these results demonstrate a surprising variety of qualitatively different outcomes when evolutionarily stable communities are assembled in heterogeneous environments.

Abstract [sv]

Evolutionärt stabila samhällen är slutpunkten för evolution, och ekologiska samhällen vars egenskaper är under selektion kommer till slut att bli ett sådant. Således är egenskaperna hos sådana samhällen särskilt intressanta, då dessa kan bestå oförändrade under långa evolutionära tidsskalor. Idén om evolutionärt stabila strategier - strategier som är oslagbara när de väl evolverat - är sedan nästan 50 år tillbaka ett väl etablerat koncept inom teoretisk ekologi. Under dessa år har teorin för evolutionärt stabila strategier och samhällen blivit alltmer välutvecklad. Denna utveckling till trots saknas fortfarande effektiva analytiska och numeriska verktyg för att studera evolutionärt stabila samhällen i heterogena miljöer, där de ekologiska betingelserna - och således även krafterna från naturligt urval - varierar från punkt till punkt i rummet. På grund av detta har många frågor rörande hur evolutionärt stabil mångfald blir till och bevaras när ekologiska och evolutionära krafter varierar i rummet förblivit outforskade. I synnerhet är kännedomen låg om hur rumsligt genomsnittlig selektion och selektion som härstammar från rummets variabilitet samverkar för att antingen förstärka eller förhindra mångfald.

I den här avhandlingen använder jag ett dubbelt grepp för att närma mig svar på dessa frågor, dels genom att utveckla de nödvändiga analytiska och numeriska verktygen för att sätta samman och analysera evolutionärt stabila samhällen i heterogena miljöer, och dels genom att använda dessa metoder för att studera samhällen av resurskonkurenter och näringsvävar. För att åstadkomma detta härleder jag uttryck för riktad och stabiliserande/disruptiv selektion när den rumsligt heterogena ekologiska dynamiken beskrivs av reaktion-diffusion ekvationer. Dessa uttryck möjliggör förståelse för selektion i en heterogen miljö i termer av hur selektion verkar lokalt i rummet, och möjliggör effektiva numeriska implementationer av metoder för att evolutionärt sätta samman samhällen.

När dessa metoder appliceras på samhällena av resurskonkurenter och näringsvävar kan jag utröna att de selektiva krafterna som härstammar från rumsligt genomsnittlig selektion och de som härstammar från rumslig variabilitet både kan samverka och motverka varandra. Om de motverkar varandra, och graden av rumslig variabilitet är hög kan hög mångfald uppstå, även när genomsnittlig selektion är stabiliserande. I kontrast till detta kan disruptiv genomsnittlig selektion motverka mångfald genom att selektera för ett fåtal globalt dominanta strategier. Dessa krafter kan dock också samverka disruptivt och tillsammans bilda en stor mångfald. Tillsammans påvisar dessa resultat en stor variation av kvalitativt olika utfall när evolutionärt stabila samhällen sätts samman i rumsligt heterogena miljöer.

Place, publisher, year, edition, pages
Umeå: Umeå universitet , 2019. , p. 87
Series
Research report in mathematics, ISSN 1653-0810 ; 64/19
Keywords [en]
Spatial models, reaction-diffusion equations, eco-evolutionary models, adaptive dynamics, evolutionarily stable communities
National Category
Evolutionary Biology Ecology Computational Mathematics
Identifiers
URN: urn:nbn:se:umu:diva-155133ISBN: 978-91-7601-992-4 (print)OAI: oai:DiVA.org:umu-155133DiVA, id: diva2:1276466
Public defence
2019-02-01, N430, Naturvetarhuset, Umeå, 09:00 (English)
Opponent
Supervisors
Available from: 2019-01-11 Created: 2019-01-08 Last updated: 2019-01-10Bibliographically approved
List of papers
1. Determining Selection across Heterogeneous Landscapes: A Perturbation-Based Method and Its Application to Modeling Evolution in Space
Open this publication in new window or tab >>Determining Selection across Heterogeneous Landscapes: A Perturbation-Based Method and Its Application to Modeling Evolution in Space
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2017 (English)In: American Naturalist, ISSN 0003-0147, E-ISSN 1537-5323, Vol. 189, no 4, p. 381-395Article in journal (Refereed) Published
Abstract [en]

Spatial structure can decisively influence the way evolutionary processes unfold. To date, several methods have been used to study evolution in spatial systems, including population genetics, quantitative genetics, moment-closure approximations, and individual-based models. Here we extend the study of spatial evolutionary dynamics to eco-evolutionary models based on reaction-diffusion equations and adaptive dynamics. Specifically, we derive expressions for the strength of directional and stabilizing/disruptive selection that apply both in continuous space and to metacommunities with symmetrical dispersal between patches. For directional selection on a quantitative trait, this yields a way to integrate local directional selection across space and determine whether the trait value will increase or decrease. The robustness of this prediction is validated against quantitative genetics. For stabilizing/disruptive selection, we show that spatial heterogeneity always contributes to disruptive selection and hence always promotes evolutionary branching. The expression for directional selection is numerically very efficient and hence lends itself to simulation studies of evolutionary community assembly. We illustrate the application and utility of the expressions for this purpose with two examples of the evolution of resource utilization. Finally, we outline the domain of applicability of reaction-diffusion equations as a modeling framework and discuss their limitations.

Place, publisher, year, edition, pages
UNIV CHICAGO PRESS, 2017
Keywords
evolution, spatial, reaction-diffusion models, adaptive dynamics, quantitative genetics, metacommunities
National Category
Evolutionary Biology
Identifiers
urn:nbn:se:umu:diva-134209 (URN)10.1086/690908 (DOI)000398685600006 ()28350499 (PubMedID)
Available from: 2017-06-20 Created: 2017-06-20 Last updated: 2019-01-08Bibliographically approved
2. How geographic productivity patterns affect food-web evolution
Open this publication in new window or tab >>How geographic productivity patterns affect food-web evolution
(English)Manuscript (preprint) (Other academic)
Abstract [en]

It is well recognized that spatial heterogeneity and overall productivity have important consequences for the diversity and community structure of food webs. Yet, few, if any, studies have considered the effects of heterogeneous spatial distributions of primary production. Here, we theoretically investigate how the variance and autocorrelation length of primary production affect properties of evolved food webs consisting of one autotroph and several heterotrophs. We report the following findings. (1) Diversity increases with landscape variance and is unimodal in autocorrelation length. (2) Trophic level increases with high landscape variance and is unimodal in autocorrelation length. (3) The extent to which the spatial distribution of heterotrophs differ from that of the autotroph increases with variance and decreases with autocorrelation length. (4) Components of initial disruptive selection experienced by the ancestral heterotroph predict properties of the final evolved communities. Prior to our study reported here, several authors had hypothesized that diversity increases with the variance of productivity. Our results support their hypothesis and contributes new facets by providing quantitative predictions that also account for autocorrelation length and additional properties of the evolved communities.

Keywords
Spatial models, Adaptive dynamics, Productivity--diversity relationship
National Category
Evolutionary Biology
Identifiers
urn:nbn:se:umu:diva-155080 (URN)
Available from: 2019-01-08 Created: 2019-01-08 Last updated: 2019-01-08
3. Patterns of diversity in evolved metacommunities of resource competitors
Open this publication in new window or tab >>Patterns of diversity in evolved metacommunities of resource competitors
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Spatial heterogeneity in environmental conditions coupled with moderate dispersal can promote ecological persistence of diverse metacommunities. We explored whether this premise holds when metacommunities can evolve. Using a model of competition for two resources, we studied the evolution of resource-uptake specialization as a function of resource type (substitutable to essential) and the shape of the trade-off in resource uptake affinities (generalist- to specialist-favoring). In homogeneous environments, evolutionarily stable coexistence of consumers is only possible for sufficiently substitutable resources and specialist-favoring trade-offs. Remarkably, these same conditions yield comparatively low diversity in heterogeneous environments, where consumer diversity is instead maximized for clearly substitutable or clearly essential resources and intermediate trade-offs. When resources are weakly interactively essential, at most two consumers persist evolutionarily in spite of high spatial variance in resource supply ratios. We explain these patterns based on analytical results for the limiting case of a spatially homogeneous system.

Keywords
Spatial models, adaptive dynamics, consumer--resource interactions, coexistence, ESS
National Category
Evolutionary Biology
Identifiers
urn:nbn:se:umu:diva-155131 (URN)
Available from: 2019-01-08 Created: 2019-01-08 Last updated: 2019-01-08
4. How species characteristics affect extinction through habitat loss
Open this publication in new window or tab >>How species characteristics affect extinction through habitat loss
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

With an increasing number of species at risk of extinction because of habitat loss, and extinction risks varying across species with different characteristics, it becomes essential to understand which and how species with different characteristics respond to habitat loss so as to prevent species loss. Although there exists a substantive literature on this subject, studies have so far not taken into account that natural communities have been formed through evolution, and that habitat loss is both heterogeneous in space and dynamic in time. Here, we design a spatially explicit evolving food-web model and expose the evolved communities to both random and spatially contagious habitat loss. We show that: (1) species that are large, rare, at high trophic levels, with small biomass energy intake, or having small spatial distribution differences with the autotrophic species are particularly susceptible to habitat loss. (2) Large species or species at high trophic level are more vulnerable to random habitat loss, while small species or species at low trophic levels are more vulnerable to contagious habitat loss. (3) Food webs are less robust for random habitat loss than for contagious habitat loss. (4) Reduction of body sizes is warning signal for food-web collapse. Taken together, these results facilitate identifying the most vulnerable species and the most damaging kinds of habitat loss.

National Category
Ecology
Identifiers
urn:nbn:se:umu:diva-155132 (URN)
Available from: 2019-01-08 Created: 2019-01-08 Last updated: 2019-01-08

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5678910118 of 11
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