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Gallagher CA, Chudzinska M, Larsen-Gray A, Pollock CJ, Sells SN, White PJC, Berger U. From theory to practice in pattern-oriented modelling: identifying and using empirical patterns in predictive models. Biol Rev Camb Philos Soc 2021; 96:1868-1888. [PMID: 33978325 DOI: 10.1111/brv.12729] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2020] [Revised: 04/14/2021] [Accepted: 04/16/2021] [Indexed: 01/21/2023]
Abstract
To robustly predict the effects of disturbance and ecosystem changes on species, it is necessary to produce structurally realistic models with high predictive power and flexibility. To ensure that these models reflect the natural conditions necessary for reliable prediction, models must be informed and tested using relevant empirical observations. Pattern-oriented modelling (POM) offers a systematic framework for employing empirical patterns throughout the modelling process and has been coupled with complex systems modelling, such as in agent-based models (ABMs). However, while the production of ABMs has been rising rapidly, the explicit use of POM has not increased. Challenges with identifying patterns and an absence of specific guidelines on how to implement empirical observations may limit the accessibility of POM and lead to the production of models which lack a systematic consideration of reality. This review serves to provide guidance on how to identify and apply patterns following a POM approach in ABMs (POM-ABMs), specifically addressing: where in the ecological hierarchy can we find patterns; what kinds of patterns are useful; how should simulations and observations be compared; and when in the modelling cycle are patterns used? The guidance and examples provided herein are intended to encourage the application of POM and inspire efficient identification and implementation of patterns for both new and experienced modellers alike. Additionally, by generalising patterns found especially useful for POM-ABM development, these guidelines provide practical help for the identification of data gaps and guide the collection of observations useful for the development and verification of predictive models. Improving the accessibility and explicitness of POM could facilitate the production of robust and structurally realistic models in the ecological community, contributing to the advancement of predictive ecology at large.
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Affiliation(s)
- Cara A Gallagher
- Department of Plant Ecology and Conservation Biology, University of Potsdam, Am Mühlenberg 3, Potsdam, 14469, Germany.,Department of Bioscience, Aarhus University, Frederiksborgvej 399, Roskilde, 4000
| | - Magda Chudzinska
- Sea Mammal Research Unit, Scottish Oceans Institute, University of St Andrews, St Andrews, KY16 9ST, U.K
| | - Angela Larsen-Gray
- Department of Integrative Biology, University of Wisconsin-Madison, 250 N. Mills St., Madison, WI, 53706, U.S.A
| | | | - Sarah N Sells
- Montana Cooperative Wildlife Research Unit, The University of Montana, 205 Natural Sciences, Missoula, MT, 59812, U.S.A
| | - Patrick J C White
- School of Applied Sciences, Edinburgh Napier University, 9 Sighthill Ct., Edinburgh, EH11 4BN, U.K
| | - Uta Berger
- Institute of Forest Growth and Computer Science, Technische Universität Dresden, Dresden, 01062, Germany
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2
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Ben-Ami F. Host Age Effects in Invertebrates: Epidemiological, Ecological, and Evolutionary Implications. Trends Parasitol 2019; 35:466-480. [PMID: 31003758 DOI: 10.1016/j.pt.2019.03.008] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Revised: 03/19/2019] [Accepted: 03/21/2019] [Indexed: 12/26/2022]
Abstract
In most species, variation in age among individuals is the strongest and most visible form of phenotypic variation. Individual-level age effects on disease traits, caused by differences in the age at exposure of the host or its parents, have been widely documented in invertebrates. They can influence diverse traits, such as host susceptibility, virulence, parasite reproduction and further transmission, and may cascade to the population level, influencing disease prevalence and within-host competition. Here, I summarize what is known about the relationship between individual-level age/stage effects and infectious disease in invertebrates. I also attempt to link age effects to the theory of aging (senescence), and highlight the importance of population age structure to disease epidemiology and evolution. I conclude by identifying gaps in our understanding of individual- and population-level age effects in invertebrates. As the age structure of populations varies across space and time, age effects have strong epidemiological, ecological, and evolutionary implications for explaining variation in infectious diseases of invertebrates.
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Affiliation(s)
- Frida Ben-Ami
- School of Zoology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.
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3
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O’Brien PP, Webber QMR, Vander Wal E. Consistent individual differences and population plasticity in network-derived sociality: An experimental manipulation of density in a gregarious ungulate. PLoS One 2018; 13:e0193425. [PMID: 29494640 PMCID: PMC5832262 DOI: 10.1371/journal.pone.0193425] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2017] [Accepted: 02/09/2018] [Indexed: 11/20/2022] Open
Abstract
In many taxa, individual social traits appear to be consistent across time and context, thus meeting the criteria for animal personality. How these differences are maintained in response to changes in population density is unknown, particularly in large mammals, such as ungulates. Using a behavioral reaction norm (BRN) framework, we examined how among- and within-individual variation in social connectedness, measured using social network analyses, change as a function of population density. We studied a captive herd of elk (Cervus canadensis) separated into a group of male elk and a group of female elk. Males and females were exposed to three different density treatments and we recorded social associations between individuals with proximity-detecting radio-collars fitted to elk. We constructed social networks using dyadic association data and calculated three social network metrics reflective of social connectedness: eigenvector centrality, graph strength, and degree. Elk exhibited consistent individual differences in social connectedness across densities; however, they showed little individual variation in their response to changes in density, i.e., individuals oftentimes responded plastically, but in the same manner to changes in density. Female elk had highest connectedness at an intermediate density. In contrast, male elk increased connectedness with increasing density. Whereas this may suggest that the benefits of social connectedness outweigh the costs of increased competition at higher density for males, females appear to exhibit a threshold in social benefits (e.g. predator detection and forage information). Our study illustrates the importance of viewing social connectedness as a density-dependent trait, particularly in the context of plasticity. Moreover, we highlight the need to revisit our understanding of density dependence as a population-level phenomenon by accounting for consistent individual differences not only in social connectedness, but likely in other ecological processes (e.g., predator-prey dynamics, mate choice, disease transfer).
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Affiliation(s)
- Paul P. O’Brien
- Department of Biology, Memorial University of Newfoundland, St. John’s, Newfoundland and Labrador, Canada
| | - Quinn M. R. Webber
- Cognitive and Behavioural Ecology Interdisciplinary Program, Memorial University of Newfoundland, St. John’s, Newfoundland and Labrador, Canada
| | - Eric Vander Wal
- Department of Biology, Memorial University of Newfoundland, St. John’s, Newfoundland and Labrador, Canada
- Cognitive and Behavioural Ecology Interdisciplinary Program, Memorial University of Newfoundland, St. John’s, Newfoundland and Labrador, Canada
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4
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Pigeon G, Festa-Bianchet M, Pelletier F. Long-term fitness consequences of early environment in a long-lived ungulate. Proc Biol Sci 2017; 284:rspb.2017.0222. [PMID: 28424347 DOI: 10.1098/rspb.2017.0222] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2017] [Accepted: 03/17/2017] [Indexed: 01/17/2023] Open
Abstract
Cohort effects can be a major source of heterogeneity and play an important role in population dynamics. Silver-spoon effects, when environmental quality at birth improves future performance regardless of the adult environment, can induce strong lagged responses on population growth. Alternatively, the external predictive adaptive response (PAR) hypothesis predicts that organisms will adjust their developmental trajectory and physiology during early life in anticipation of expected adult conditions but has rarely been assessed in wild species. We used over 40 years of detailed individual monitoring of bighorn ewes (Ovis canadensis) to quantify long-term cohort effects on survival and reproduction. We then tested both the silver-spoon and the PAR hypotheses. Cohort effects involved a strong interaction between birth and current environments: reproduction and survival were lowest for ewes that were born and lived at high population densities. This interaction, however, does not support the PAR hypothesis because individuals with matching high-density birth and adult environments had reduced fitness. Instead, individuals born at high density had overall lower lifetime fitness suggesting a silver-spoon effect. Early-life conditions can induce long-term changes in fitness components, and their effects on cohort fitness vary according to adult environment.
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Affiliation(s)
- Gabriel Pigeon
- Département de Biologie, Université de Sherbrooke, 2500 boulevard de l'Université, Sherbrooke, Québec, Canada J1 K 2R1
| | - Marco Festa-Bianchet
- Département de Biologie, Université de Sherbrooke, 2500 boulevard de l'Université, Sherbrooke, Québec, Canada J1 K 2R1
| | - Fanie Pelletier
- Département de Biologie, Université de Sherbrooke, 2500 boulevard de l'Université, Sherbrooke, Québec, Canada J1 K 2R1
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5
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Cameron TC, O'Sullivan D, Reynolds A, Hicks JP, Piertney SB, Benton TG. Harvested populations are more variable only in more variable environments. Ecol Evol 2016; 6:4179-91. [PMID: 27516873 PMCID: PMC4884197 DOI: 10.1002/ece3.2164] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2016] [Accepted: 03/20/2016] [Indexed: 11/28/2022] Open
Abstract
The interaction between environmental variation and population dynamics is of major importance, particularly for managed and economically important species, and especially given contemporary changes in climate variability. Recent analyses of exploited animal populations contested whether exploitation or environmental variation has the greatest influence on the stability of population dynamics, with consequences for variation in yield and extinction risk. Theoretical studies however have shown that harvesting can increase or decrease population variability depending on environmental variation, and requested controlled empirical studies to test predictions. Here, we use an invertebrate model species in experimental microcosms to explore the interaction between selective harvesting and environmental variation in food availability in affecting the variability of stage‐structured animal populations over 20 generations. In a constant food environment, harvesting adults had negligible impact on population variability or population size, but in the variable food environments, harvesting adults increased population variability and reduced its size. The impact of harvesting on population variability differed between proportional and threshold harvesting, between randomly and periodically varying environments, and at different points of the time series. Our study suggests that predicting the responses to selective harvesting is sensitive to the demographic structures and processes that emerge in environments with different patterns of environmental variation.
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Affiliation(s)
- Tom C Cameron
- School of Biological Sciences University of Essex Colchester CO43SQ UK
| | | | - Alan Reynolds
- School of Biological Sciences University of Leeds Leeds LS2 9JT UK
| | - Joseph P Hicks
- School of Biological Sciences University of Leeds Leeds LS2 9JT UK
| | - Stuart B Piertney
- Institute of Biological and Environmental Sciences University of Aberdeen Aberdeen AB24 2TZ UK
| | - Tim G Benton
- School of Biological Sciences University of Leeds Leeds LS2 9JT UK
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6
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Adams BK, Cote D, Fleming IA. Stochastic life history modeling for managing regional-scale freshwater fisheries: an experimental study of brook trout. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2016; 26:899-912. [PMID: 27411259 DOI: 10.1890/14-2379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Environmental heterogeneity can combine with evolutionary responses to create very dynamic and often locally independent populations across a landscape. Such complexity creates difficulties for managers trying to conserve populations across large areas. This study develops, applies, and tests the use of stochastic life history modeling and Monte Carlo simulation to assess management scenarios related to the realities of regional fisheries management and conservation. We apply this approach to the management of recreational brook trout (Salvelinus fontinalis) fishing; an activity that can severely impact species balance, abundance, and the size structure of fish communities. Specifically, the model incorporates population-specific life-history information (e.g., growth rate, reproductive effort, and survival) to allow forecasts of the impact of various management strategies and/or changes to environmental conditions on a population's ecological characteristics (e.g., size structure, abundance, and probability of persistence). Sampling was carried out in 16 water bodies spread across four sites in Atlantic Canada. Each water body was sampled in 2005 and reassessed in 2008. This sampling had two primary objectives: (1) define a significant proportion of life-history variation of brook trout in Atlantic Canada, and (2) to test the precision and accuracy of model predictions of population responses to experimental exploitation and management changes. The model successfully predicted population responses to changes in adult survival in 12 of 13 populations having sufficient data for validation testing, while also proving to be a useful tool when engaging stakeholders regarding management options and their associated risk. We suggest that such models are cost-effective and have great potential for informing proactive management of jurisdictions with numerous and diverse populations.
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7
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Moran EV, Hartig F, Bell DM. Intraspecific trait variation across scales: implications for understanding global change responses. GLOBAL CHANGE BIOLOGY 2016; 22:137-50. [PMID: 26061811 DOI: 10.1111/gcb.13000] [Citation(s) in RCA: 158] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2015] [Accepted: 05/21/2015] [Indexed: 05/03/2023]
Abstract
Recognition of the importance of intraspecific variation in ecological processes has been growing, but empirical studies and models of global change have only begun to address this issue in detail. This review discusses sources and patterns of intraspecific trait variation and their consequences for understanding how ecological processes and patterns will respond to global change. We examine how current ecological models and theories incorporate intraspecific variation, review existing data sources that could help parameterize models that account for intraspecific variation in global change predictions, and discuss new data that may be needed. We provide guidelines on when it is most important to consider intraspecific variation, such as when trait variation is heritable or when nonlinear relationships are involved. We also highlight benefits and limitations of different model types and argue that many common modeling approaches such as matrix population models or global dynamic vegetation models can allow a stronger consideration of intraspecific trait variation if the necessary data are available. We recommend that existing data need to be made more accessible, though in some cases, new experiments are needed to disentangle causes of variation.
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Affiliation(s)
- Emily V Moran
- School of Natural Sciences, UC Merced, Merced, CA, 95343, USA
| | - Florian Hartig
- Department of Biometry and Environmental System Analysis, University of Freiburg, Freiburg, 79106, Germany
| | - David M Bell
- Pacific Northwest Research Station, USDA Forest Service, Portland, OR, 97204, USA
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8
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Brooks ME, Mugabo M, Rodgers GM, Benton TG, Ozgul A. How well can body size represent effects of the environment on demographic rates? Disentangling correlated explanatory variables. J Anim Ecol 2015; 85:318-28. [PMID: 26620593 DOI: 10.1111/1365-2656.12465] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2015] [Accepted: 10/20/2015] [Indexed: 11/28/2022]
Abstract
Demographic rates are shaped by the interaction of past and current environments that individuals in a population experience. Past environments shape individual states via selection and plasticity, and fitness-related traits (e.g. individual size) are commonly used in demographic analyses to represent the effect of past environments on demographic rates. We quantified how well the size of individuals captures the effects of a population's past and current environments on demographic rates in a well-studied experimental system of soil mites. We decomposed these interrelated sources of variation with a novel method of multiple regression that is useful for understanding nonlinear relationships between responses and multicollinear explanatory variables. We graphically present the results using area-proportional Venn diagrams. Our novel method was developed by combining existing methods and expanding upon them. We showed that the strength of size as a proxy for the past environment varied widely among vital rates. For instance, in this organism with an income breeding life history, the environment had more effect on reproduction than individual size, but with substantial overlap indicating that size encompassed some of the effects of the past environment on fecundity. This demonstrates that the strength of size as a proxy for the past environment can vary widely among life-history processes within a species, and this variation should be taken into consideration in trait-based demographic or individual-based approaches that focus on phenotypic traits as state variables. Furthermore, the strength of a proxy will depend on what state variable(s) and what demographic rate is being examined; that is, different measures of body size (e.g. length, volume, mass, fat stores) will be better or worse proxies for various life-history processes.
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Affiliation(s)
- Mollie E Brooks
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland
| | - Marianne Mugabo
- School of Biology, Faculty of Biological Sciences, University of Leeds, Leeds, UK
| | - Gwendolen M Rodgers
- School of Biology, Faculty of Biological Sciences, University of Leeds, Leeds, UK
| | - Timothy G Benton
- School of Biology, Faculty of Biological Sciences, University of Leeds, Leeds, UK
| | - Arpat Ozgul
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland
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9
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Zurell D, Eggers U, Kaatz M, Rotics S, Sapir N, Wikelski M, Nathan R, Jeltsch F. Individual-based modelling of resource competition to predict density-dependent population dynamics: a case study with white storks. OIKOS 2014. [DOI: 10.1111/oik.01294] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Damaris Zurell
- Inst. of Biochemistry and Biology, Univ. of Potsdam; Maulbeerallee 2 DE-14469 Potsdam Germany
- Landscape Dynamics, Swiss Federal Research Inst. WSL; Zürcherstrasse 111 CH-8903 Birmensdorf Switzerland
| | - Ute Eggers
- Inst. of Biochemistry and Biology, Univ. of Potsdam; Maulbeerallee 2 DE-14469 Potsdam Germany
| | - Michael Kaatz
- Vogelschutzwarte Storchenhof Loburg e.V.; Chausseestr. 18 DE-39279 Loburg Germany
| | - Shay Rotics
- Dept of Ecology, Evolution and Behavior; The Hebrew Univ. of Jerusalem, Edmond J. Safra Campus; IL-91904 Jerusalem Israel
| | - Nir Sapir
- Dept of Migration and Immuno-Ecology; Max Planck Inst. for Ornithology; Schlossallee 2 DE-78315 Radolfzell Germany
| | - Martin Wikelski
- Dept of Migration and Immuno-Ecology; Max Planck Inst. for Ornithology; Schlossallee 2 DE-78315 Radolfzell Germany
- Dept of Biology; Konstanz Univ.; DE-78315 Konstanz Germany
| | - Ran Nathan
- Dept of Ecology, Evolution and Behavior; The Hebrew Univ. of Jerusalem, Edmond J. Safra Campus; IL-91904 Jerusalem Israel
| | - Florian Jeltsch
- Inst. of Biochemistry and Biology, Univ. of Potsdam; Maulbeerallee 2 DE-14469 Potsdam Germany
- Berlin-Brandenburg Inst. of Advanced Biodiversity Research (BBIB); DE-14195 Berlin Germany
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10
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11
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Zachar N, Neiman M. Profound effects of population density on fitness-related traits in an invasive freshwater snail. PLoS One 2013; 8:e80067. [PMID: 24278240 PMCID: PMC3836992 DOI: 10.1371/journal.pone.0080067] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2013] [Accepted: 10/05/2013] [Indexed: 11/18/2022] Open
Abstract
Population density can profoundly influence fitness-related traits and population dynamics, and density dependence plays a key role in many prominent ecological and evolutionary hypotheses. Here, we evaluated how individual-level changes in population density affect growth rate and embryo production early in reproductive maturity in two different asexual lineages of Potamopyrgus antipodarum, a New Zealand freshwater snail that is an important model system for ecotoxicology and the evolution of sexual reproduction as well as a potentially destructive worldwide invader. We showed that population density had a major influence on individual growth rate and early-maturity embryo production, effects that were often apparent even when comparing treatments that differed in population density by only one individual. While individual growth rate generally decreased as population density increased, we detected a hump-shaped relationship between embryo production and density, with females from intermediate-density treatments producing the most embryos and females from low- and high-density treatments producing the fewest embryos. The two lineages responded similarly to the treatments, indicating that these effects of population density might apply more broadly across P. antipodarum. These results indicate that there are profound and complex relationships between population density, growth rate, and early-maturity embryo production in at least two lineages of this important model system, with potential implications for the study of invasive populations, research on the maintenance of sex, and approaches used in ecotoxicology.
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Affiliation(s)
- Nicholas Zachar
- Department of Biology, University of Iowa, Iowa City, Iowa, United States of America
| | - Maurine Neiman
- Department of Biology, University of Iowa, Iowa City, Iowa, United States of America
- * E-mail:
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12
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Evans MR, Bithell M, Cornell SJ, Dall SRX, Díaz S, Emmott S, Ernande B, Grimm V, Hodgson DJ, Lewis SL, Mace GM, Morecroft M, Moustakas A, Murphy E, Newbold T, Norris KJ, Petchey O, Smith M, Travis JMJ, Benton TG. Predictive systems ecology. Proc Biol Sci 2013; 280:20131452. [PMID: 24089332 PMCID: PMC3790477 DOI: 10.1098/rspb.2013.1452] [Citation(s) in RCA: 99] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive.
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Affiliation(s)
- Matthew R Evans
- School of Biological and Chemical Sciences, Queen Mary University of London, , Mile End Road, London E1 4NS, UK, Department of Geography, University of Cambridge, , Downing Place, Cambridge CB2 3EN, UK, Institute of Integrative Biology, University of Liverpool, , Liverpool L69 7ZB, UK, Centre for Ecology and Conservation, College of Life and Environmental Sciences, University of Exeter, , Cornwall Campus TR10 9EZ, UK, Instituto Multidisciplinario de BiologíaVegetal (CONICET-UNC) and FCEFyN, Universidad Nacional de Córdoba, , Casilla de Correo 495, Córdoba 5000, Argentina, Computational Science Laboratory, Microsoft Research, , 21 Station Road, Cambridge CB1 2FB, UK, IFREMER, Laboratorie Ressources Halieutiques, 150 quai Gambetta, BP 699, Boulogne-sur-Mer 62321, France, Helmhotz Center for Environmental Research, Department of Ecological Modelling, Permoserstrasse 15, Leipzig 04318, Germany, Earth and Biosphere Institute, University of Leeds, , Woodhouse Lane, Leeds LS2 9JT, UK, Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment, University College London, , Darwin Building, Gower Street, London WC1E 6BT, UK, Natural England, , Cromwell House, Andover Road, Winchester SO23 7BT, UK, British Antarctic Survey, Madingley Road, High Cross, Cambridge CB3 0ET, UK, United Nations Environment Programme World Conservation Monitoring Centre, 219 Huntingdon Road, Cambridge CB3 0DL, UK, Centre for Agri-Environmental Research, School of Agriculture, Policy and Development, The University of Reading, , Earley Gate, PO Box 237, Reading RG6 6AR, UK, Institute of Evolutionary Biology and Environmental Studies, University of Zurich, , Winterhurerstrasse 190, Zurich 8057, Switzerland, Institute of Biological and Environmental Sciences, Zoology Building, Tillydrone Avenue, Aberdeen AB24 2TZ, UK, School of Biology, University of Leeds, , Leeds LS2 9JT, UK
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13
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Moustakas A, Evans MR. Integrating evolution into ecological modelling: accommodating phenotypic changes in agent based models. PLoS One 2013; 8:e71125. [PMID: 23940700 PMCID: PMC3733718 DOI: 10.1371/journal.pone.0071125] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2013] [Accepted: 06/29/2013] [Indexed: 12/05/2022] Open
Abstract
Evolutionary change is a characteristic of living organisms and forms one of the ways in which species adapt to changed conditions. However, most ecological models do not incorporate this ubiquitous phenomenon. We have developed a model that takes a 'phenotypic gambit' approach and focuses on changes in the frequency of phenotypes (which differ in timing of breeding and fecundity) within a population, using, as an example, seasonal breeding. Fitness per phenotype calculated as the individual's contribution to population growth on an annual basis coincide with the population dynamics per phenotype. Simplified model variants were explored to examine whether the complexity included in the model is justified. Outputs from the spatially implicit model underestimated the number of individuals across all phenotypes. When no phenotype transitions are included (i.e. offspring always inherit their parent's phenotype) numbers of all individuals are always underestimated. We conclude that by using a phenotypic gambit approach evolutionary dynamics can be incorporated into individual based models, and that all that is required is an understanding of the probability of offspring inheriting the parental phenotype.
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Affiliation(s)
- Aristides Moustakas
- School of Biological and Chemical Sciences, Queen Mary, University of London, London, United Kingdom.
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14
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Evans MR, Grimm V, Johst K, Knuuttila T, de Langhe R, Lessells CM, Merz M, O'Malley MA, Orzack SH, Weisberg M, Wilkinson DJ, Wolkenhauer O, Benton TG. Do simple models lead to generality in ecology? Trends Ecol Evol 2013; 28:578-83. [PMID: 23827437 DOI: 10.1016/j.tree.2013.05.022] [Citation(s) in RCA: 127] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2012] [Revised: 05/26/2013] [Accepted: 05/31/2013] [Indexed: 11/26/2022]
Abstract
Modellers of biological, ecological, and environmental systems cannot take for granted the maxim 'simple means general means good'. We argue here that viewing simple models as the main way to achieve generality may be an obstacle to the progress of ecological research. We show how complex models can be both desirable and general, and how simple and complex models can be linked together to produce broad-scale and predictive understanding of biological systems.
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Affiliation(s)
- Matthew R Evans
- School of Biological and Chemical Sciences, Queen Mary, University of London, Mile End Road, London, E1 4NS, UK.
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15
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Cameron TC, O'Sullivan D, Reynolds A, Piertney SB, Benton TG. Eco-evolutionary dynamics in response to selection on life-history. Ecol Lett 2013; 16:754-63. [PMID: 23565666 PMCID: PMC3712461 DOI: 10.1111/ele.12107] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2012] [Revised: 10/03/2012] [Accepted: 02/22/2013] [Indexed: 11/30/2022]
Abstract
Understanding the consequences of environmental change on ecological and evolutionary dynamics is inherently problematic because of the complex interplay between them. Using invertebrates in microcosms, we characterise phenotypic, population and evolutionary dynamics before, during and after exposure to a novel environment and harvesting over 20 generations. We demonstrate an evolved change in life-history traits (the age- and size-at-maturity, and survival to maturity) in response to selection caused by environmental change (wild to laboratory) and to harvesting (juvenile or adult). Life-history evolution, which drives changes in population growth rate and thus population dynamics, includes an increase in age-to-maturity of 76% (from 12.5 to 22 days) in the unharvested populations as they adapt to the new environment. Evolutionary responses to harvesting are outweighed by the response to environmental change (∼ 1.4 vs. 4% change in age-at-maturity per generation). The adaptive response to environmental change converts a negative population growth trajectory into a positive one: an example of evolutionary rescue.
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Affiliation(s)
- Tom C Cameron
- Ecology & Evolution research group, Institute of Integrative & Comparative Biology, University of Leeds, Leeds, LS2 9JT, UK.
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Forbes VE, Calow P. Promises and problems for the new paradigm for risk assessment and an alternative approach involving predictive systems models. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2012; 31:2663-2671. [PMID: 23165997 DOI: 10.1002/etc.2009] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
The need for cost-effective risk assessment of chemicals is leading to the development of a reductionist paradigm that tries to assess impacts on humans and ecosystems from molecular changes. However, the biggest challenge for this paradigm comes from the emergence of properties that arise out of the interactions of the parts that are not included and yet which are key for assessing likely impacts. Although identifying key events and adverse outcome pathways can shed light on the involvement of important metabolic processes in toxicity, this does not mean that particular molecular initiating events are likely to be robust or accurate predictors of impacts that matter. There are even greater challenges for the new paradigm applied to ecological systems than to human health because of the need to link across more levels of biological organization. The present study argues for a predictive systems approach that makes the linkages through systems models in a mechanistic way that allows for emergence and that also has the potential for reducing the costs and use of animals in ecological risk assessments.
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Affiliation(s)
- Valery E Forbes
- School of Biological Sciences, University of Nebraska-Lincoln, Lincoln, NE, USA.
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17
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Dingemanse NJ, Dochtermann NA. Quantifying individual variation in behaviour: mixed-effect modelling approaches. J Anim Ecol 2012; 82:39-54. [PMID: 23171297 DOI: 10.1111/1365-2656.12013] [Citation(s) in RCA: 670] [Impact Index Per Article: 55.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2011] [Accepted: 09/13/2012] [Indexed: 12/01/2022]
Affiliation(s)
- Niels J. Dingemanse
- Evolutionary Ecology of Variation Group; Max Planck Institute for Ornithology; Eberhard-Gwinner-Straße 82319 Seewiesen (Starnberg) Germany
- Department Biology II, Behavioural Ecology; Ludwig-Maximilians-University of Munich; Großhadener Strasse 2 82152 Planegg-Martinsried Germany
| | - Ned A. Dochtermann
- Department of Biological Sciences; North Dakota State University; 1340 Bolley Drive Fargo ND 58102 USA
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18
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Evans MR, Norris KJ, Benton TG. Predictive ecology: systems approaches. Philos Trans R Soc Lond B Biol Sci 2012; 367:163-9. [PMID: 22144379 DOI: 10.1098/rstb.2011.0191] [Citation(s) in RCA: 91] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The world is experiencing significant, largely anthropogenically induced, environmental change. This will impact on the biological world and we need to be able to forecast its effects. In order to produce such forecasts, ecology needs to become more predictive--to develop the ability to understand how ecological systems will behave in future, changed, conditions. Further development of process-based models is required to allow such predictions to be made. Critical to the development of such models will be achieving a balance between the brute-force approach that naively attempts to include everything, and over simplification that throws out important heterogeneities at various levels. Central to this will be the recognition that individuals are the elementary particles of all ecological systems. As such it will be necessary to understand the effect of evolution on ecological systems, particularly when exposed to environmental change. However, insights from evolutionary biology will help the development of models even when data may be sparse. Process-based models are more common, and are used for forecasting, in other disciplines, e.g. climatology and molecular systems biology. Tools and techniques developed in these endeavours can be appropriated into ecological modelling, but it will also be necessary to develop the science of ecoinformatics along with approaches specific to ecological problems. The impetus for this effort should come from the demand coming from society to understand the effects of environmental change on the world and what might be performed to mitigate or adapt to them.
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Affiliation(s)
- Matthew R Evans
- Centre for Ecology and Conservation, School of Biosciences, University of Exeter, Cornwall Campus, Penryn, Cornwall TR10 9EZ, UK.
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19
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Smith P, Albanito F, Bell M, Bellarby J, Blagodatskiy S, Datta A, Dondini M, Fitton N, Flynn H, Hastings A, Hillier J, Jones EO, Kuhnert M, Nayak DR, Pogson M, Richards M, Sozanska-Stanton G, Wang S, Yeluripati JB, Bottoms E, Brown C, Farmer J, Feliciano D, Hao C, Robertson A, Vetter S, Wong HM, Smith J. Systems approaches in global change and biogeochemistry research. Philos Trans R Soc Lond B Biol Sci 2012; 367:311-21. [PMID: 22144393 PMCID: PMC3223799 DOI: 10.1098/rstb.2011.0173] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Systems approaches have great potential for application in predictive ecology. In this paper, we present a range of examples, where systems approaches are being developed and applied at a range of scales in the field of global change and biogeochemical cycling. Systems approaches range from Bayesian calibration techniques at plot scale, through data assimilation methods at regional to continental scales, to multi-disciplinary numerical model applications at country to global scales. We provide examples from a range of studies and show how these approaches are being used to address current topics in global change and biogeochemical research, such as the interaction between carbon and nitrogen cycles, terrestrial carbon feedbacks to climate change and the attribution of observed global changes to various drivers of change. We examine how transferable the methods and techniques might be to other areas of ecosystem science and ecology.
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Affiliation(s)
- Pete Smith
- Institute of Biological and Environmental Sciences, University of Aberdeen, 23 St Machar Drive, Aberdeen AB24 3UU, UK.
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