1
|
Meuthen D, Reinhold K. On the use of antibiotics in plasticity research: Gastropod shells unveil a tale of caution. J Anim Ecol 2023; 92:1055-1064. [PMID: 36869422 DOI: 10.1111/1365-2656.13909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 02/24/2023] [Indexed: 03/05/2023]
Abstract
Through phenotypic plasticity, individual genotypes can produce multiple phenotypes dependent on the environment. In the modern world, anthropogenic influences such as man-made pharmaceuticals are increasingly prevalent. They might alter observable patterns of plasticity and distort our conclusions regarding the adaptive potential of natural populations. Antibiotics are nowadays nearly ubiquitous in aquatic environments and prophylactic antibiotic use is also becoming more common to optimize animal survival and reproductive output in artificial settings. In the well-studied plasticity model system Physella acuta, prophylactic erythromycin treatment acts against gram-positive bacteria and thereby reduces mortality. Here, we study its consequences for inducible defence formation in the same species. In a 2 × 2 split-clutch design, we reared 635 P. acuta in either the presence or absence of this antibiotic, followed by 28-day exposure to either high or low predation risk as perceived through conspecific alarm cues. Under antibiotic treatment, risk-induced increases in shell thickness, a well-known plastic response in this model system, were larger and consistently detectable. Antibiotic treatment reduced shell thickness in low-risk individuals, suggesting that in controls, undiscovered pathogen infection increased shell thickness under low risk. Family variation in risk-induced plasticity was low, but the large variation in responses to antibiotics among families suggests different pathogen susceptibility between genotypes. Lastly, individuals that developed thicker shells had reduced total mass, which highlights resource trade-offs. Antibiotics thus have the potential to uncover a larger extent of plasticity, but might counterintuitively distort plasticity estimates for natural populations where pathogens are a part of natural ecology.
Collapse
Affiliation(s)
- Denis Meuthen
- Evolutionary Biology, Bielefeld University, Bielefeld, Germany
| | - Klaus Reinhold
- Evolutionary Biology, Bielefeld University, Bielefeld, Germany
| |
Collapse
|
2
|
Stuczyńska A, Sobczyk M, Fiałkowska E, Kocerba-Soroka W, Pajdak-Stós A, Starzycka J, Walczyńska A. Clonal thermal preferences affect the strength of the temperature-size rule. ORG DIVERS EVOL 2022. [DOI: 10.1007/s13127-022-00556-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
|
3
|
Gabor CR, Kivlin SN, Hua J, Bickford N, Reiskind MOB, Wright TF. Understanding Organismal Capacity to Respond to Anthropogenic Change: Barriers and Solutions. Integr Comp Biol 2021; 61:2132-2144. [PMID: 34279616 DOI: 10.1093/icb/icab162] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Revised: 06/15/2021] [Accepted: 07/13/2021] [Indexed: 11/14/2022] Open
Abstract
Global environmental changes induced by human activities are forcing organisms to respond at an unprecedented pace. At present we have only a limited understanding of why some species possess the capacity to respond to these changes while others do not. We introduce the concept of multidimensional phenospace as an organizing construct to understanding organismal evolutionary responses to environmental change. We then describe five barriers that currently challenge our ability to understand these responses: 1) Understanding the parameters of environmental change and their fitness effects, 2) Mapping and integrating phenotypic and genotypic variation, 3) Understanding whether changes in phenospace are heritable, 4) Predicting consistency of genotype to phenotype patterns across space and time, and 5) Determining which traits should be prioritized to understand organismal response to environmental change. For each we suggest one or more solutions that would help us surmount the barrier and improve our ability to predict, and eventually manipulate, organismal capacity to respond to anthropogenic change. Additionally, we provide examples of target species that could be useful to examine interactions between phenotypic plasticity and adaptive evolution in changing phenospace.
Collapse
Affiliation(s)
- Caitlin R Gabor
- Department of Biology, Population and Conservation Biology Group, Texas State University, San Marcos, TX, 78666, USA.,The Xiphophorus Genetic Stock Center, Texas State University, San Marcos, TX, 78666, USA
| | - Stephanie N Kivlin
- Department of Ecology and Evolutionary Biology, University of Tennessee Knoxville, Knoxville, TN, 37996, USA
| | - Jessica Hua
- Biological Sciences Department, Binghamton University (SUNY), Binghamton, NY, 13902, USA
| | - Nate Bickford
- Biology Department, Colorado State University Pueblo, Pueblo, CO 81003, USA
| | | | - Timothy F Wright
- Biology Department, New Mexico State University, Las Cruces, NM, 88003, USA
| |
Collapse
|
4
|
DeVore JL, Crossland MR, Shine R. Trade‐offs affect the adaptive value of plasticity: stronger cannibal‐induced defenses incur greater costs in toad larvae. ECOL MONOGR 2020. [DOI: 10.1002/ecm.1426] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Affiliation(s)
- Jayna L. DeVore
- School of Life and Environmental Sciences The University of Sydney Sydney2006New South Wales Australia
| | - Michael R. Crossland
- School of Life and Environmental Sciences The University of Sydney Sydney2006New South Wales Australia
| | - Richard Shine
- School of Life and Environmental Sciences The University of Sydney Sydney2006New South Wales Australia
- Department of Biological Sciences Macquarie University Sydney2109 New South Wales Australia
| |
Collapse
|
5
|
Petino Zappala MA, Satorre I, Fanara JJ. Stage- and thermal-specific genetic architecture for preadult viability in natural populations of Drosophila melanogaster. J Evol Biol 2019; 32:683-693. [PMID: 30924196 DOI: 10.1111/jeb.13448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2018] [Revised: 03/18/2019] [Accepted: 03/20/2019] [Indexed: 11/29/2022]
Abstract
Studying the processes affecting variation for preadult viability is essential to understand the evolutionary trajectories followed by natural populations. This task requires focusing on the complex nature of the phenotype-genotype relationship by taking into account usually neglected aspects of the phenotype and recognizing the modularity between different ontogenetic stages. Here, we describe phenotypic variability for viability during the larval and pupal stages in lines derived from three natural populations of Drosophila melanogaster, as well as the variability for phenotypic plasticity and canalization at two different rearing temperatures. The results indicate that the three populations present significant phenotypic differences for preadult viability. Furthermore, distinct aspects of the phenotype (means, plasticity, canalization, plasticity of canalization) are affected by different genetic bases underlying changes in viability in a stage- and environment-specific manner. These findings explain the generalized maintenance of genetic variability for this fitness trait.
Collapse
Affiliation(s)
- María Alejandra Petino Zappala
- Departamento de Ecologia, Genetica y Evolucion - IEGEBA (CONICET-UBA), Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, CABA, Argentina
| | - Ignacio Satorre
- Departamento de Ecologia, Genetica y Evolucion - IEGEBA (CONICET-UBA), Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, CABA, Argentina
| | - Juan José Fanara
- Departamento de Ecologia, Genetica y Evolucion - IEGEBA (CONICET-UBA), Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, CABA, Argentina
| |
Collapse
|
6
|
Goold C, Newberry RC. Modelling personality, plasticity and predictability in shelter dogs. ROYAL SOCIETY OPEN SCIENCE 2017; 4:170618. [PMID: 28989764 PMCID: PMC5627104 DOI: 10.1098/rsos.170618] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/05/2017] [Accepted: 08/12/2017] [Indexed: 06/07/2023]
Abstract
Behavioural assessments of shelter dogs (Canis lupus familiaris) typically comprise standardized test batteries conducted at one time point, but test batteries have shown inconsistent predictive validity. Longitudinal behavioural assessments offer an alternative. We modelled longitudinal observational data on shelter dog behaviour using the framework of behavioural reaction norms, partitioning variance into personality (i.e. inter-individual differences in behaviour), plasticity (i.e. inter-individual differences in average behaviour) and predictability (i.e. individual differences in residual intra-individual variation). We analysed data on interactions of 3263 dogs (n = 19 281) with unfamiliar people during their first month after arrival at the shelter. Accounting for personality, plasticity (linear and quadratic trends) and predictability improved the predictive accuracy of the analyses compared to models quantifying personality and/or plasticity only. While dogs were, on average, highly sociable with unfamiliar people and sociability increased over days since arrival, group averages were unrepresentative of all dogs and predictions made at the individual level entailed considerable uncertainty. Effects of demographic variables (e.g. age) on personality, plasticity and predictability were observed. Behavioural repeatability was higher one week after arrival compared to arrival day. Our results highlight the value of longitudinal assessments on shelter dogs and identify measures that could improve the predictive validity of behavioural assessments in shelters.
Collapse
Affiliation(s)
- Conor Goold
- Author for correspondence: Conor Goold e-mail:
| | | |
Collapse
|
7
|
Pépino M, Magnan P, Proulx R. Field evidence for a rapid adaptive plastic response in morphology and growth of littoral and pelagic brook charr: A reciprocal transplant experiment. Funct Ecol 2017. [DOI: 10.1111/1365-2435.12929] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Affiliation(s)
- Marc Pépino
- Centre de recherche sur les interactions bassins versants – écosystèmes aquatiques (RIVE)Université du Québec à Trois‐Rivières Trois‐Rivières Québec Canada
| | - Pierre Magnan
- Centre de recherche sur les interactions bassins versants – écosystèmes aquatiques (RIVE)Université du Québec à Trois‐Rivières Trois‐Rivières Québec Canada
| | - Raphaël Proulx
- Centre de recherche sur les interactions bassins versants – écosystèmes aquatiques (RIVE)Université du Québec à Trois‐Rivières Trois‐Rivières Québec Canada
| |
Collapse
|
8
|
Bucksch A, Atta-Boateng A, Azihou AF, Battogtokh D, Baumgartner A, Binder BM, Braybrook SA, Chang C, Coneva V, DeWitt TJ, Fletcher AG, Gehan MA, Diaz-Martinez DH, Hong L, Iyer-Pascuzzi AS, Klein LL, Leiboff S, Li M, Lynch JP, Maizel A, Maloof JN, Markelz RJC, Martinez CC, Miller LA, Mio W, Palubicki W, Poorter H, Pradal C, Price CA, Puttonen E, Reese JB, Rellán-Álvarez R, Spalding EP, Sparks EE, Topp CN, Williams JH, Chitwood DH. Morphological Plant Modeling: Unleashing Geometric and Topological Potential within the Plant Sciences. FRONTIERS IN PLANT SCIENCE 2017; 8:900. [PMID: 28659934 PMCID: PMC5465304 DOI: 10.3389/fpls.2017.00900] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/05/2016] [Accepted: 05/12/2017] [Indexed: 05/21/2023]
Abstract
The geometries and topologies of leaves, flowers, roots, shoots, and their arrangements have fascinated plant biologists and mathematicians alike. As such, plant morphology is inherently mathematical in that it describes plant form and architecture with geometrical and topological techniques. Gaining an understanding of how to modify plant morphology, through molecular biology and breeding, aided by a mathematical perspective, is critical to improving agriculture, and the monitoring of ecosystems is vital to modeling a future with fewer natural resources. In this white paper, we begin with an overview in quantifying the form of plants and mathematical models of patterning in plants. We then explore the fundamental challenges that remain unanswered concerning plant morphology, from the barriers preventing the prediction of phenotype from genotype to modeling the movement of leaves in air streams. We end with a discussion concerning the education of plant morphology synthesizing biological and mathematical approaches and ways to facilitate research advances through outreach, cross-disciplinary training, and open science. Unleashing the potential of geometric and topological approaches in the plant sciences promises to transform our understanding of both plants and mathematics.
Collapse
Affiliation(s)
- Alexander Bucksch
- Department of Plant Biology, University of Georgia, AthensGA, United States
- Warnell School of Forestry and Natural Resources, University of Georgia, AthensGA, United States
- Institute of Bioinformatics, University of Georgia, AthensGA, United States
| | | | - Akomian F. Azihou
- Laboratory of Applied Ecology, Faculty of Agronomic Sciences, University of Abomey-CalaviCotonou, Benin
| | - Dorjsuren Battogtokh
- Department of Biological Sciences, Virginia Polytechnic Institute and State University, BlacksburgVA, United States
| | - Aly Baumgartner
- Department of Geosciences, Baylor University, WacoTX, United States
| | - Brad M. Binder
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, KnoxvilleTN, United States
| | | | - Cynthia Chang
- Division of Biology, University of Washington, BothellWA, United States
| | - Viktoirya Coneva
- Donald Danforth Plant Science Center, St. LouisMO, United States
| | - Thomas J. DeWitt
- Department of Wildlife and Fisheries Sciences–Department of Plant Pathology and Microbiology, Texas A&M University, College StationTX, United States
| | - Alexander G. Fletcher
- School of Mathematics and Statistics and Bateson Centre, University of SheffieldSheffield, United Kingdom
| | - Malia A. Gehan
- Donald Danforth Plant Science Center, St. LouisMO, United States
| | | | - Lilan Hong
- Weill Institute for Cell and Molecular Biology and Section of Plant Biology, School of Integrative Plant Sciences, Cornell University, IthacaNY, United States
| | - Anjali S. Iyer-Pascuzzi
- Department of Botany and Plant Pathology, Purdue University, West LafayetteIN, United States
| | - Laura L. Klein
- Department of Biology, Saint Louis University, St. LouisMO, United States
| | - Samuel Leiboff
- School of Integrative Plant Science, Cornell University, IthacaNY, United States
| | - Mao Li
- Department of Mathematics, Florida State University, TallahasseeFL, United States
| | - Jonathan P. Lynch
- Department of Plant Science, The Pennsylvania State University, University ParkPA, United States
| | - Alexis Maizel
- Center for Organismal Studies, Heidelberg UniversityHeidelberg, Germany
| | - Julin N. Maloof
- Department of Plant Biology, University of California, Davis, DavisCA, United States
| | - R. J. Cody Markelz
- Department of Plant Biology, University of California, Davis, DavisCA, United States
| | - Ciera C. Martinez
- Department of Molecular and Cell Biology, University of California, Berkeley, BerkeleyCA, United States
| | - Laura A. Miller
- Program in Bioinformatics and Computational Biology, The University of North Carolina, Chapel HillNC, United States
| | - Washington Mio
- Department of Mathematics, Florida State University, TallahasseeFL, United States
| | - Wojtek Palubicki
- The Sainsbury Laboratory, University of CambridgeCambridge, United Kingdom
| | - Hendrik Poorter
- Plant Sciences (IBG-2), Forschungszentrum Jülich GmbH, JülichGermany
| | | | - Charles A. Price
- National Institute for Mathematical and Biological Synthesis, University of Tennessee, Knoxville, KnoxvilleTN, United States
| | - Eetu Puttonen
- Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, National Land Survey of FinlandMasala, Finland
- Centre of Excellence in Laser Scanning Research, National Land Survey of FinlandMasala, Finland
| | - John B. Reese
- Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, KnoxvilleTN, United States
| | - Rubén Rellán-Álvarez
- Unidad de Genómica Avanzada, Laboratorio Nacional de Genómica para la Biodiversidad, Center for Research and Advanced Studies of the National Polytechnic Institute (CINVESTAV)Irapuato, Mexico
| | - Edgar P. Spalding
- Department of Botany, University of Wisconsin–Madison, MadisonWI, United States
| | - Erin E. Sparks
- Department of Plant and Soil Sciences and Delaware Biotechnology Institute, University of Delaware, NewarkDE, United States
| | | | - Joseph H. Williams
- Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, KnoxvilleTN, United States
| | | |
Collapse
|
9
|
Bucksch A, Atta-Boateng A, Azihou AF, Battogtokh D, Baumgartner A, Binder BM, Braybrook SA, Chang C, Coneva V, DeWitt TJ, Fletcher AG, Gehan MA, Diaz-Martinez DH, Hong L, Iyer-Pascuzzi AS, Klein LL, Leiboff S, Li M, Lynch JP, Maizel A, Maloof JN, Markelz RJC, Martinez CC, Miller LA, Mio W, Palubicki W, Poorter H, Pradal C, Price CA, Puttonen E, Reese JB, Rellán-Álvarez R, Spalding EP, Sparks EE, Topp CN, Williams JH, Chitwood DH. Morphological Plant Modeling: Unleashing Geometric and Topological Potential within the Plant Sciences. FRONTIERS IN PLANT SCIENCE 2017. [PMID: 28659934 DOI: 10.3389/978-2-88945-297-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
The geometries and topologies of leaves, flowers, roots, shoots, and their arrangements have fascinated plant biologists and mathematicians alike. As such, plant morphology is inherently mathematical in that it describes plant form and architecture with geometrical and topological techniques. Gaining an understanding of how to modify plant morphology, through molecular biology and breeding, aided by a mathematical perspective, is critical to improving agriculture, and the monitoring of ecosystems is vital to modeling a future with fewer natural resources. In this white paper, we begin with an overview in quantifying the form of plants and mathematical models of patterning in plants. We then explore the fundamental challenges that remain unanswered concerning plant morphology, from the barriers preventing the prediction of phenotype from genotype to modeling the movement of leaves in air streams. We end with a discussion concerning the education of plant morphology synthesizing biological and mathematical approaches and ways to facilitate research advances through outreach, cross-disciplinary training, and open science. Unleashing the potential of geometric and topological approaches in the plant sciences promises to transform our understanding of both plants and mathematics.
Collapse
Affiliation(s)
- Alexander Bucksch
- Department of Plant Biology, University of Georgia, AthensGA, United States
- Warnell School of Forestry and Natural Resources, University of Georgia, AthensGA, United States
- Institute of Bioinformatics, University of Georgia, AthensGA, United States
| | | | - Akomian F Azihou
- Laboratory of Applied Ecology, Faculty of Agronomic Sciences, University of Abomey-CalaviCotonou, Benin
| | - Dorjsuren Battogtokh
- Department of Biological Sciences, Virginia Polytechnic Institute and State University, BlacksburgVA, United States
| | - Aly Baumgartner
- Department of Geosciences, Baylor University, WacoTX, United States
| | - Brad M Binder
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, KnoxvilleTN, United States
| | | | - Cynthia Chang
- Division of Biology, University of Washington, BothellWA, United States
| | - Viktoirya Coneva
- Donald Danforth Plant Science Center, St. LouisMO, United States
| | - Thomas J DeWitt
- Department of Wildlife and Fisheries Sciences-Department of Plant Pathology and Microbiology, Texas A&M University, College StationTX, United States
| | - Alexander G Fletcher
- School of Mathematics and Statistics and Bateson Centre, University of SheffieldSheffield, United Kingdom
| | - Malia A Gehan
- Donald Danforth Plant Science Center, St. LouisMO, United States
| | | | - Lilan Hong
- Weill Institute for Cell and Molecular Biology and Section of Plant Biology, School of Integrative Plant Sciences, Cornell University, IthacaNY, United States
| | - Anjali S Iyer-Pascuzzi
- Department of Botany and Plant Pathology, Purdue University, West LafayetteIN, United States
| | - Laura L Klein
- Department of Biology, Saint Louis University, St. LouisMO, United States
| | - Samuel Leiboff
- School of Integrative Plant Science, Cornell University, IthacaNY, United States
| | - Mao Li
- Department of Mathematics, Florida State University, TallahasseeFL, United States
| | - Jonathan P Lynch
- Department of Plant Science, The Pennsylvania State University, University ParkPA, United States
| | - Alexis Maizel
- Center for Organismal Studies, Heidelberg UniversityHeidelberg, Germany
| | - Julin N Maloof
- Department of Plant Biology, University of California, Davis, DavisCA, United States
| | - R J Cody Markelz
- Department of Plant Biology, University of California, Davis, DavisCA, United States
| | - Ciera C Martinez
- Department of Molecular and Cell Biology, University of California, Berkeley, BerkeleyCA, United States
| | - Laura A Miller
- Program in Bioinformatics and Computational Biology, The University of North Carolina, Chapel HillNC, United States
| | - Washington Mio
- Department of Mathematics, Florida State University, TallahasseeFL, United States
| | - Wojtek Palubicki
- The Sainsbury Laboratory, University of CambridgeCambridge, United Kingdom
| | - Hendrik Poorter
- Plant Sciences (IBG-2), Forschungszentrum Jülich GmbH, JülichGermany
| | | | - Charles A Price
- National Institute for Mathematical and Biological Synthesis, University of Tennessee, Knoxville, KnoxvilleTN, United States
| | - Eetu Puttonen
- Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, National Land Survey of FinlandMasala, Finland
- Centre of Excellence in Laser Scanning Research, National Land Survey of FinlandMasala, Finland
| | - John B Reese
- Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, KnoxvilleTN, United States
| | - Rubén Rellán-Álvarez
- Unidad de Genómica Avanzada, Laboratorio Nacional de Genómica para la Biodiversidad, Center for Research and Advanced Studies of the National Polytechnic Institute (CINVESTAV)Irapuato, Mexico
| | - Edgar P Spalding
- Department of Botany, University of Wisconsin-Madison, MadisonWI, United States
| | - Erin E Sparks
- Department of Plant and Soil Sciences and Delaware Biotechnology Institute, University of Delaware, NewarkDE, United States
| | | | - Joseph H Williams
- Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, KnoxvilleTN, United States
| | | |
Collapse
|