1
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Strube LF, Elgart S, Childs LM. Infection-induced increases to population size during cycles in a discrete-time epidemic model. J Math Biol 2024; 88:60. [PMID: 38600396 PMCID: PMC11006791 DOI: 10.1007/s00285-024-02074-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 11/11/2023] [Accepted: 02/18/2024] [Indexed: 04/12/2024]
Abstract
One-dimensional discrete-time population models, such as those that involve Logistic or Ricker growth, can exhibit periodic and chaotic dynamics. Expanding the system by one dimension to incorporate epidemiological interactions causes an interesting complexity of new behaviors. Here, we examine a discrete-time two-dimensional susceptible-infectious (SI) model with Ricker growth and show that the introduction of infection can not only produce a distinctly different bifurcation structure than that of the underlying disease-free system but also lead to counter-intuitive increases in population size. We use numerical bifurcation analysis to determine the influence of infection on the location and types of bifurcations. In addition, we examine the appearance and extent of a phenomenon known as the 'hydra effect,' i.e., increases in total population size when factors, such as mortality, that act negatively on a population, are increased. Previous work, primarily focused on dynamics at fixed points, showed that the introduction of infection that reduces fecundity to the SI model can lead to a so-called 'infection-induced hydra effect.' Our work shows that even in such a simple two-dimensional SI model, the introduction of infection that alters fecundity or mortality can produce dynamics can lead to the appearance of a hydra effect, particularly when the disease-free population is at a cycle.
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Affiliation(s)
- Laura F Strube
- Department of Mathematics, Virginia Tech, 225 Stanger St, Blacksburg, VA, 24061, USA
- Department of Immunology, University of Pittsburgh Medical School, The Assembly, 5051 Centre Avenue, Pittsburgh, PA, 15213, USA
- Department of Computational and Systems Biology, University of Pittsburgh Medical School, 800 Murdoch I building, 3420 Forbes Avenue, Pittsburgh, PA, 15213, USA
| | - Shoshana Elgart
- Laurel Springs School, 302 El Paseo Rd, Ojai, CA, 93023, USA
| | - Lauren M Childs
- Department of Mathematics, Virginia Tech, 225 Stanger St, Blacksburg, VA, 24061, USA.
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2
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Draghi JA, McGlothlin JW, Kindsvater HK. Demographic feedbacks during evolutionary rescue can slow or speed adaptive evolution. Proc Biol Sci 2024; 291:20231553. [PMID: 38351805 PMCID: PMC10865011 DOI: 10.1098/rspb.2023.1553] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 01/16/2024] [Indexed: 02/16/2024] Open
Abstract
Populations declining toward extinction can persist via genetic adaptation in a process called evolutionary rescue. Predicting evolutionary rescue has applications ranging from conservation biology to medicine, but requires understanding and integrating the multiple effects of a stressful environmental change on population processes. Here we derive a simple expression for how generation time, a key determinant of the rate of evolution, varies with population size during evolutionary rescue. Change in generation time is quantitatively predicted by comparing how intraspecific competition and the source of maladaptation each affect the rates of births and deaths in the population. Depending on the difference between two parameters quantifying these effects, the model predicts that populations may experience substantial changes in their rate of adaptation in both positive and negative directions, or adapt consistently despite severe stress. These predictions were then tested by comparison to the results of individual-based simulations of evolutionary rescue, which validated that the tolerable rate of environmental change varied considerably as described by analytical results. We discuss how these results inform efforts to understand wildlife disease and adaptation to climate change, evolution in managed populations and treatment resistance in pathogens.
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Affiliation(s)
- Jeremy A. Draghi
- Department of Biological Sciences, Virginia Tech, Blacksburg, VA 24060, USA
| | - Joel W. McGlothlin
- Department of Biological Sciences, Virginia Tech, Blacksburg, VA 24060, USA
| | - Holly K. Kindsvater
- Department of Fish and Wildlife Conservation, Virginia Tech, Blacksburg, VA 24060, USA
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3
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Bagawade R, van Benthem KJ, Wittmann MJ. Multi-scale effects of habitat loss and the role of trait evolution. Ecol Evol 2024; 14:e10799. [PMID: 38187921 PMCID: PMC10766568 DOI: 10.1002/ece3.10799] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 11/09/2023] [Accepted: 11/22/2023] [Indexed: 01/09/2024] Open
Abstract
Habitat loss (HL) is a major cause of species extinctions. Although the effects of HL beyond the directly impacted area have been previously observed, they have not been modelled explicitly, especially in an eco-evolutionary context. To start filling this gap, we study a two-patch deterministic consumer-resource model, with one of the patches experiencing loss of resources as a special case of HL. Our model allows foraging and mating within a patch as well as between patches. We then introduce heritable variation in consumer traits related to resource utilization and patch use to investigate eco-evolutionary dynamics and compare results with constant and no trait variation scenarios. Our results show that HL in one patch can indeed reduce consumer densities in the neighbouring patch but can also increase consumer densities in the neighbouring patch when the resources are overexploited. Yet at the landscape scale, the effect of HL on consumer densities is consistently negative. Patch isolation increases consumer density in the patch experiencing HL but has generally negative effects on the neighbouring patch, with context-dependent results at the landscape scale. With high cross-patch dependence and coupled foraging and mating preferences, local HL can sometimes even lead to landscape-level consumer extinction. Eco-evolutionary dynamics can rescue consumers from such extinction in some cases if their death rates are sufficiently small. More generally, trait evolution had positive or negative effects on equilibrium consumer densities after HL, depending on the evolving trait and the spatial scale considered. In summary, our findings show that HL at a local scale can affect the neighbouring patch and the landscape as a whole, where heritable trait variation can, in some cases, alleviate the impact of HL. We thus suggest joint consideration of multiple spatial scales and trait variation when assessing and predicting the impacts of HL.
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Affiliation(s)
- Rishabh Bagawade
- Department of Theoretical Biology, Faculty of BiologyBielefeld UniversityBielefeldGermany
| | - Koen J. van Benthem
- Department of Theoretical Biology, Faculty of BiologyBielefeld UniversityBielefeldGermany
- Groningen Institute for Evolutionary Life SciencesFaculty of Science and Engineering, University of GroningenGroningenThe Netherlands
| | - Meike J. Wittmann
- Department of Theoretical Biology, Faculty of BiologyBielefeld UniversityBielefeldGermany
- Joint Institute for Individualisation in a Changing Environment (JICE), University of Münster and Bielefeld UniversityBielefeldGermany
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4
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Simon MW, Barfield M, Holt RD. When growing pains and sick days collide: infectious disease can stabilize host population oscillations caused by stage structure. THEOR ECOL-NETH 2022. [DOI: 10.1007/s12080-022-00543-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
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5
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Bisschop K, Alzate A, Bonte D, Etienne RS. The demographic consequences of adaptation: evidence from experimental evolution. Am Nat 2022; 199:729-742. [DOI: 10.1086/719183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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6
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Vuorinen KEM, Oksanen T, Oksanen L, Vuorisalo T, Speed JDM. Why don't all species overexploit? OIKOS 2021. [DOI: 10.1111/oik.08358] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Katariina E. M. Vuorinen
- Dept of Natural History, NTNU Univ. Museum, Norwegian Univ. of Science and Technology Trondheim Norway
| | - Tarja Oksanen
- Dept of Arctic and Marine Biology, UiT, The Arctic Univ. of Norway, Campus Alta Alta Norway
- Dept of Biology, Ecology Section, Univ. of Turku Turku Finland
| | - Lauri Oksanen
- Dept of Arctic and Marine Biology, UiT, The Arctic Univ. of Norway, Campus Alta Alta Norway
- Dept of Biology, Ecology Section, Univ. of Turku Turku Finland
| | - Timo Vuorisalo
- Dept of Biology, Ecology Section, Univ. of Turku Turku Finland
| | - James D. M. Speed
- Dept of Natural History, NTNU Univ. Museum, Norwegian Univ. of Science and Technology Trondheim Norway
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7
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Barbier M, Wojcik L, Loreau M. A macro‐ecological approach to predation density‐dependence. OIKOS 2021. [DOI: 10.1111/oik.08043] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
- Matthieu Barbier
- Centre for Biodiversity Theory and Modelling, Theoretical and Experimental Ecology Station, UMR 5321, CNRS and Paul Sabatier Univ. Moulis France
| | - Laurie Wojcik
- Centre for Biodiversity Theory and Modelling, Theoretical and Experimental Ecology Station, UMR 5321, CNRS and Paul Sabatier Univ. Moulis France
| | - Michel Loreau
- Centre for Biodiversity Theory and Modelling, Theoretical and Experimental Ecology Station, UMR 5321, CNRS and Paul Sabatier Univ. Moulis France
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8
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How intra-stage and inter-stage competition affect overcompensation in density and hydra effects in single-species, stage-structured models. THEOR ECOL-NETH 2020. [DOI: 10.1007/s12080-020-00488-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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9
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Mendes PB, Faria LD. The eco-evolutionary dynamics of a predator-prey system across an r/K continuum. Ecol Modell 2020. [DOI: 10.1016/j.ecolmodel.2020.109269] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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10
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Engen S, Wright J, Araya-Ajoy YG, Saether BE. Phenotypic evolution in stochastic environments: The contribution of frequency- and density-dependent selection. Evolution 2020; 74:1923-1941. [PMID: 32656772 DOI: 10.1111/evo.14058] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2019] [Revised: 06/24/2020] [Accepted: 07/02/2020] [Indexed: 02/06/2023]
Abstract
Understanding how environmental variation affects phenotypic evolution requires models based on ecologically realistic assumptions that include variation in population size and specific mechanisms by which environmental fluctuations affect selection. Here we generalize quantitative genetic theory for environmentally induced stochastic selection to include general forms of frequency- and density-dependent selection. We show how the relevant fitness measure under stochastic selection relates to Fisher's fundamental theorem of natural selection, and present a general class of models in which density regulation acts through total use of resources rather than just population size. In this model, there is a constant adaptive topography for expected evolution, and the function maximized in the long run is the expected factor restricting population growth. This allows us to generalize several previous results and to explain why apparently " K -selected" species with slow life histories often have low carrying capacities. Our joint analysis of density- and frequency-dependent selection reveals more clearly the relationship between population dynamics and phenotypic evolution, enabling a broader range of eco-evolutionary analyses of some of the most interesting problems in evolution in the face of environmental variation.
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Affiliation(s)
- Steinar Engen
- Department of Mathematical Sciences, Centre for Biodiversity Dynamics, Norwegian University of Science and Technology, Trondheim, N-7491, Norway
| | - Jonathan Wright
- Department of Biology, Centre for Biodiversity Dynamics, Norwegian University of Science and Technology, Trondheim, N-7491, Norway
| | - Yimen G Araya-Ajoy
- Department of Biology, Centre for Biodiversity Dynamics, Norwegian University of Science and Technology, Trondheim, N-7491, Norway
| | - Bernt-Erik Saether
- Department of Biology, Centre for Biodiversity Dynamics, Norwegian University of Science and Technology, Trondheim, N-7491, Norway
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11
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Faillace CA, Morin PJ. Evolution alters post-invasion temporal dynamics in experimental communities. J Anim Ecol 2019; 89:285-298. [PMID: 31556097 DOI: 10.1111/1365-2656.13113] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2019] [Accepted: 09/08/2019] [Indexed: 12/30/2022]
Abstract
The causes and consequences of temporal variation in the abundance of organisms constitute central themes in ecological inquiry. Rapid evolution can occur over ecological time-scales, potentially resulting in altered temporal variation in abundance and complicating inferences about the consequences of temporal variation. We assessed whether evolution altered the temporal variability in species' abundances in simple assemblages of species. We then compared experimental results to predictions from two-species models to better understand our results in the context of competitive and predator-prey interactions. We compared founder populations and their evolved descendants in experimental communities of ciliates and rotifers. Using a series of orthogonal contrasts, we then evaluated whether: (a) evolutionary history of invaders or (b) residents, (c) co-evolution among invaders and residents, and (d) invasion itself altered temporal variability in species abundances following invasion by a novel species. Using two-species competition and predator-prey models, we also generated predictions to better understand the effects of evolution on temporal variation in the abundances of interacting species. Finally, we compared experimental and modelling results to aid in the interpretation of which interspecific interactions might be affected by ongoing evolution in our communities. In experimental populations, differing evolutionary histories resulted in significant differences among treatments in abundances and temporal variation in abundances of both resident and invading species. For the contrasts, we found evidence that evolutionary history of the invader and residents, co-evolution among invaders and residents, and invasion itself affected temporal variability in abundance, but the importance of each differed for the two communities and the species within those communities. When comparing experimental results to model predictions, the increased abundance and decreased temporal variation in one invader, Euplotes daidaleos, are potentially consistent with evolution resulting in reduced attack rates in the novel community. Evolutionary history alone can affect temporal variation in the abundances of species, generating important consequences for interspecific interactions among species and complicating inferences about the consequences of temporal variability in biological communities.
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Affiliation(s)
- Cara A Faillace
- Graduate Program in Ecology and Evolution, Dept. of Ecology, Evolution, and Natural Resources, Rutgers, The State University of New Jersey, New Brunswick, New Jersey
| | - Peter J Morin
- Graduate Program in Ecology and Evolution, Dept. of Ecology, Evolution, and Natural Resources, Rutgers, The State University of New Jersey, New Brunswick, New Jersey
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12
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Brady SP, Bolnick DI, Barrett RDH, Chapman L, Crispo E, Derry AM, Eckert CG, Fraser DJ, Fussmann GF, Gonzalez A, Guichard F, Lamy T, Lane J, McAdam AG, Newman AEM, Paccard A, Robertson B, Rolshausen G, Schulte PM, Simons AM, Vellend M, Hendry A. Understanding Maladaptation by Uniting Ecological and Evolutionary Perspectives. Am Nat 2019; 194:495-515. [PMID: 31490718 DOI: 10.1086/705020] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Evolutionary biologists have long trained their sights on adaptation, focusing on the power of natural selection to produce relative fitness advantages while often ignoring changes in absolute fitness. Ecologists generally have taken a different tack, focusing on changes in abundance and ranges that reflect absolute fitness while often ignoring relative fitness. Uniting these perspectives, we articulate various causes of relative and absolute maladaptation and review numerous examples of their occurrence. This review indicates that maladaptation is reasonably common from both perspectives, yet often in contrasting ways. That is, maladaptation can appear strong from a relative fitness perspective, yet populations can be growing in abundance. Conversely, resident individuals can appear locally adapted (relative to nonresident individuals) yet be declining in abundance. Understanding and interpreting these disconnects between relative and absolute maladaptation, as well as the cases of agreement, is increasingly critical in the face of accelerating human-mediated environmental change. We therefore present a framework for studying maladaptation, focusing in particular on the relationship between absolute and relative fitness, thereby drawing together evolutionary and ecological perspectives. The unification of these ecological and evolutionary perspectives has the potential to bring together previously disjunct research areas while addressing key conceptual issues and specific practical problems.
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13
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Brady SP, Bolnick DI, Angert AL, Gonzalez A, Barrett RD, Crispo E, Derry AM, Eckert CG, Fraser DJ, Fussmann GF, Guichard F, Lamy T, McAdam AG, Newman AE, Paccard A, Rolshausen G, Simons AM, Hendry AP. Causes of maladaptation. Evol Appl 2019; 12:1229-1242. [PMID: 31417611 PMCID: PMC6691215 DOI: 10.1111/eva.12844] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
Evolutionary biologists tend to approach the study of the natural world within a framework of adaptation, inspired perhaps by the power of natural selection to produce fitness advantages that drive population persistence and biological diversity. In contrast, evolution has rarely been studied through the lens of adaptation's complement, maladaptation. This contrast is surprising because maladaptation is a prevalent feature of evolution: population trait values are rarely distributed optimally; local populations often have lower fitness than imported ones; populations decline; and local and global extinctions are common. Yet we lack a general framework for understanding maladaptation; for instance in terms of distribution, severity, and dynamics. Similar uncertainties apply to the causes of maladaptation. We suggest that incorporating maladaptation-based perspectives into evolutionary biology would facilitate better understanding of the natural world. Approaches within a maladaptation framework might be especially profitable in applied evolution contexts - where reductions in fitness are common. Toward advancing a more balanced study of evolution, here we present a conceptual framework describing causes of maladaptation. As the introductory article for a Special Feature on maladaptation, we also summarize the studies in this Issue, highlighting the causes of maladaptation in each study. We hope that our framework and the papers in this Special Issue will help catalyze the study of maladaptation in applied evolution, supporting greater understanding of evolutionary dynamics in our rapidly changing world.
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Affiliation(s)
- Steven P. Brady
- Biology DepartmentSouthern Connecticut State UniversityNew HavenCTUSA
| | - Daniel I. Bolnick
- Department of Ecology and Evolutionary BiologyUniversity of ConnecticutMansfieldCTUSA
| | - Amy L. Angert
- Departments of Botany and ZoologyUniversity of British ColumbiaVancouverBCCanada
| | - Andrew Gonzalez
- Department of BiologyMcGill UniversityMontréalQCCanada
- Quebec Centre for Biodiversity Science, Stewart BiologyMcGill UniversityMontréalQCCanada
| | - Rowan D.H. Barrett
- Department of BiologyMcGill UniversityMontréalQCCanada
- Quebec Centre for Biodiversity Science, Stewart BiologyMcGill UniversityMontréalQCCanada
- Redpath MuseumMcGill UniversityMontréalQCCanada
| | - Erika Crispo
- Department of BiologyPace UniversityNew YorkNYUSA
| | - Alison M. Derry
- Quebec Centre for Biodiversity Science, Stewart BiologyMcGill UniversityMontréalQCCanada
- Département des sciences biologiquesUniversité du Québec à MontréalMontréalQCCanada
| | | | | | - Gregor F. Fussmann
- Department of BiologyMcGill UniversityMontréalQCCanada
- Quebec Centre for Biodiversity Science, Stewart BiologyMcGill UniversityMontréalQCCanada
| | - Frederic Guichard
- Department of BiologyMcGill UniversityMontréalQCCanada
- Quebec Centre for Biodiversity Science, Stewart BiologyMcGill UniversityMontréalQCCanada
| | - Thomas Lamy
- Département de sciences biologiquesUniversité de MontréalMontréalQCCanada
- Marine Science InstituteUniversity of CaliforniaSanta BarbaraCAUSA
| | - Andrew G. McAdam
- Department of Integrative BiologyUniversity of GuelphGuelphONCanada
| | - Amy E.M. Newman
- Department of Integrative BiologyUniversity of GuelphGuelphONCanada
| | | | - Gregor Rolshausen
- Senckenberg Biodiversity and Climate Research Centre (SBiK‐F)Frankfurt am MainGermany
| | | | - Andrew P. Hendry
- Department of BiologyMcGill UniversityMontréalQCCanada
- Quebec Centre for Biodiversity Science, Stewart BiologyMcGill UniversityMontréalQCCanada
- Redpath MuseumMcGill UniversityMontréalQCCanada
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