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Pontarp, Mikael
Publications (6 of 6) Show all publications
diva2:1316863
Open this publication in new window or tab >>Inferring community assembly processes from macroscopic patterns using dynamic eco-evolutionary models and Approximate Bayesian Computation (ABC)
2019 (English)In: Methods in Ecology and Evolution, ISSN 2041-210X, E-ISSN 2041-210X, Vol. 10, no 4, p. 450-460Article, review/survey (Refereed) Published
Abstract [en]

Statistical techniques exist for inferring community assembly processes from community patterns. Habitat filtering, competition, and biogeographical effects have, for example, been inferred from signals in phenotypic and phylogenetic data. The usefulness of current inference techniques is, however, debated as a mechanistic and causal link between process and pattern is often lacking, and evolutionary processes and trophic interactions are ignored.

Here, we revisit the current knowledge on community assembly across scales and, in line with several reviews that have outlined challenges associated with current inference techniques, we identify a discrepancy between the current paradigm of eco-evolutionary community assembly and current inference techniques that focus mainly on competition and habitat filtering. We argue that trait-based dynamic eco-evolutionary models in combination with recently developed model fitting and model evaluation techniques can provide avenues for more accurate, reliable, and inclusive inference. To exemplify, we implement a trait-based, spatially explicit eco-evolutionary model and discuss steps of model modification, fitting, and evaluation as an iterative approach enabling inference from diverse data sources.

Through a case study on inference of prey and predator niche width in an eco-evolutionary context, we demonstrate how inclusive and mechanistic approaches-eco-evolutionary modelling and Approximate Bayesian Computation (ABC)-can enable inference of assembly processes that have been largely neglected by traditional techniques despite the ubiquity of such processes.

Much literature points to the limitations of current inference techniques, but concrete solutions to such limitations are few. Many of the challenges associated with novel inference techniques are, however, already to some extent resolved in other fields and thus ready to be put into action in a more formal way for inferring processes of community assembly from signals in various data sources.

Place, publisher, year, edition, pages
John Wiley & Sons, 2019
Keywords
biogeography, community assembly, community structure, ecology, evolution, process inference
National Category
Bioinformatics (Computational Biology) Evolutionary Biology
Identifiers
urn:nbn:se:umu:diva-158737 (URN)10.1111/2041-210X.13129 (DOI)000463036400001 ()
Available from: 2019-05-21 Created: 2019-05-21 Last updated: 2019-05-21Bibliographically approved
Pennekamp, F., Pontarp, M., Tabi, A., Altermatt, F., Alther, R., Choffat, Y., . . . Petchey, O. L. (2018). Biodiversity increases and decreases ecosystem stability [Letter to the editor]. Nature, 563(7729), 109-+
Open this publication in new window or tab >>Biodiversity increases and decreases ecosystem stability
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2018 (English)In: Nature, ISSN 0028-0836, E-ISSN 1476-4687, Vol. 563, no 7729, p. 109-+Article in journal, Letter (Refereed) Published
Abstract [en]

Losses and gains in species diversity affect ecological stability(1-7) and the sustainability of ecosystem functions and services(8-13). Experiments and models have revealed positive, negative and no effects of diversity on individual components of stability, such as temporal variability, resistance and resilience(2,3,6,11,12,14). How these stability components covary remains poorly understood(15). Similarly, the effects of diversity on overall ecosystem stability(16), which is conceptually akin to ecosystem multifunctionality(17,18), remain unknown. Here we studied communities of aquatic ciliates to understand how temporal variability, resistance and overall ecosystem stability responded to diversity (that is, species richness) in a large experiment involving 690 micro-ecosystems sampled 19 times over 40 days, resulting in 12,939 samplings. Species richness increased temporal stability but decreased resistance to warming. Thus, two stability components covaried negatively along the diversity gradient. Previous biodiversity manipulation studies rarely reported such negative covariation despite general predictions of the negative effects of diversity on individual stability components(3). Integrating our findings with the ecosystem multifunctionality concept revealed hump- and U-shaped effects of diversity on overall ecosystem stability. That is, biodiversity can increase overall ecosystem stability when biodiversity is low, and decrease it when biodiversity is high, or the opposite with a U-shaped relationship. The effects of diversity on ecosystem multifunctionality would also be hump- or U-shaped if diversity had positive effects on some functions and negative effects on others. Linking the ecosystem multifunctionality concept and ecosystem stability can transform the perceived effects of diversity on ecological stability and may help to translate this science into policy-relevant information.

Place, publisher, year, edition, pages
Nature Publishing Group, 2018
National Category
Ecology
Identifiers
urn:nbn:se:umu:diva-153553 (URN)10.1038/s41586-018-0627-8 (DOI)000448900900054 ()30333623 (PubMedID)
Available from: 2018-11-22 Created: 2018-11-22 Last updated: 2018-11-22Bibliographically approved
Logares, R., Tesson, S. V. M., Canback, B., Pontarp, M., Hedlund, K. & Rengefors, K. (2018). Contrasting prevalence of selection and drift in the community structuring of bacteria and microbial eukaryotes. Environmental Microbiology, 20(6), 2231-2240
Open this publication in new window or tab >>Contrasting prevalence of selection and drift in the community structuring of bacteria and microbial eukaryotes
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2018 (English)In: Environmental Microbiology, ISSN 1462-2912, E-ISSN 1462-2920, Vol. 20, no 6, p. 2231-2240Article in journal (Refereed) Published
Abstract [en]

Whether or not communities of microbial eukaryotes are structured in the same way as bacteria is a general and poorly explored question in ecology. Here, we investigated this question in a set of planktonic lake microbiotas in Eastern Antarctica that represent a natural community ecology experiment. Most of the analysed lakes emerged from the sea during the last 6000 years, giving rise to waterbodies that originally contained marine microbiotas and that subsequently evolved into habitats ranging from freshwater to hypersaline. We show that habitat diversification has promoted selection driven by the salinity gradient in bacterial communities (explaining approximate to 72% of taxa turnover), while microeukaryotic counterparts were predominantly structured by ecological drift (approximate to 72% of the turnover). Nevertheless, we also detected a number of microeukaryotes with specific responses to salinity, indicating that albeit minor, selection has had a role in the structuring of specific members of their communities. In sum, we conclude that microeukaryotes and bacteria inhabiting the same communities can be structured predominantly by different processes. This should be considered in future studies aiming to understand the mechanisms that shape microbial assemblages.

Place, publisher, year, edition, pages
Wiley-Blackwell, 2018
National Category
Microbiology
Identifiers
urn:nbn:se:umu:diva-151409 (URN)10.1111/1462-2920.14265 (DOI)000441876900035 ()29727053 (PubMedID)
Funder
Swedish Research Council, 349-2007-8690Swedish Research Council, 621-2012-3726
Available from: 2018-09-03 Created: 2018-09-03 Last updated: 2018-09-03Bibliographically approved
Pontarp, M. & Petchey, O. L. (2018). Ecological opportunity and predator-prey interactions: linking eco-evolutionary processes and diversification in adaptive radiations. Proceedings of the Royal Society of London. Biological Sciences, 285(1874), Article ID 20172550.
Open this publication in new window or tab >>Ecological opportunity and predator-prey interactions: linking eco-evolutionary processes and diversification in adaptive radiations
2018 (English)In: Proceedings of the Royal Society of London. Biological Sciences, ISSN 0962-8452, E-ISSN 1471-2954, Vol. 285, no 1874, article id 20172550Article in journal (Refereed) Published
Abstract [en]

Much of life's diversity has arisen through ecological opportunity and adaptive radiations, but the mechanistic underpinning of such diversification is not fully understood. Competition and predation can affect adaptive radiations, but contrasting theoretical and empirical results show that they can both promote and interrupt diversification. A mechanistic understanding of the link between microevolutionary processes and macroevolutionary patterns is thus needed, especially in trophic communities. Here, we use a trait-based eco-evolutionary model to investigate the mechanisms linking competition, predation and adaptive radiations. By combining available micro-evolutionary theory and simulations of adaptive radiations we show that intraspecific competition is crucial for diversification as it induces disruptive selection, in particular in early phases of radiation. The diversification rate is however decreased in later phases owing to interspecific competition as niche availability, and population sizes are decreased. We provide new insight into how predation tends to have a negative effect on prey diversification through decreased population sizes, decreased disruptive selection and through the exclusion of prey from parts of niche space. The seemingly disparate effects of competition and predation on adaptive radiations, listed in the literature, may thus be acting and interacting in the same adaptive radiation at different relative strength as the radiation progresses.

Place, publisher, year, edition, pages
The Royal Society, 2018
Keywords
adaptive radiation, macroevolution, community patterns, competition, predation, ecological speciation
National Category
Evolutionary Biology
Identifiers
urn:nbn:se:umu:diva-148654 (URN)10.1098/rspb.2017.2550 (DOI)000428940300005 ()29514970 (PubMedID)2-s2.0-85043577692 (Scopus ID)
Funder
Swedish Research Council
Available from: 2018-06-25 Created: 2018-06-25 Last updated: 2018-06-25Bibliographically approved
Pontarp, M. & Petchey, O. L. (2016). Community trait overdispersion due to trophic interactions: concerns for assembly process inference. Proceedings of the Royal Society of London. Biological Sciences, 283(1840), Article ID 20161729.
Open this publication in new window or tab >>Community trait overdispersion due to trophic interactions: concerns for assembly process inference
2016 (English)In: Proceedings of the Royal Society of London. Biological Sciences, ISSN 0962-8452, E-ISSN 1471-2954, Vol. 283, no 1840, article id 20161729Article in journal (Refereed) Published
Abstract [en]

The expected link between competitive exclusion and community trait over-dispersion has been used to infer competition in local communities, and trait clustering has been interpreted as habitat filtering. Such community assembly process inference has received criticism for ignoring trophic interactions, as competition and trophic interactions might create similar trait patterns. While other theoretical studies have generally demonstrated the importance of predation for coexistence, ours provides the first quantitative demonstration of such effects on assembly process inference, using a trait-based ecological model to simulate the assembly of a competitive primary consumer community with and without the influence of trophic interactions. We quantified and contrasted trait dispersion/clustering of the competitive communities with the absence and presence of secondary consumers. Trophic interactions most often decreased trait clustering (i.e. increased dispersion) in the competitive communities due to evenly distributed invasions of secondary consumers and subsequent competitor extinctions over trait space. Furthermore, effects of trophic interactions were somewhat dependent on model parameters and clustering metric. These effects create considerable problems for process inference from trait distributions; one potential solution is to use more process-based and inclusive models in inference.

Keywords
community assembly, community structure, process inference, trophic interactions, trait distribution
National Category
Ecology Evolutionary Biology
Identifiers
urn:nbn:se:umu:diva-130050 (URN)10.1098/rspb.2016.1729 (DOI)000386490000015 ()
Available from: 2017-01-16 Created: 2017-01-11 Last updated: 2018-06-09Bibliographically approved
Petchey, O. L., Pontarp, M., Massie, T. M., Kefi, S., Ozgul, A., Weilenmann, M., . . . Pearse, I. S. (2015). The ecological forecast horizon, and examples of its uses and determinants. Ecology Letters, 18(7), 597-611
Open this publication in new window or tab >>The ecological forecast horizon, and examples of its uses and determinants
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2015 (English)In: Ecology Letters, ISSN 1461-023X, E-ISSN 1461-0248, Vol. 18, no 7, p. 597-611Article in journal (Refereed) Published
Abstract [en]

Forecasts of ecological dynamics in changing environments are increasingly important, and are available for a plethora of variables, such as species abundance and distribution, community structure and ecosystem processes. There is, however, a general absence of knowledge about how far into the future, or other dimensions (space, temperature, phylogenetic distance), useful ecological forecasts can be made, and about how features of ecological systems relate to these distances. The ecological forecast horizon is the dimensional distance for which useful forecasts can be made. Five case studies illustrate the influence of various sources of uncertainty (e.g. parameter uncertainty, environmental variation, demographic stochasticity and evolution), level of ecological organisation (e.g. population or community), and organismal properties (e.g. body size or number of trophic links) on temporal, spatial and phylogenetic forecast horizons. Insights from these case studies demonstrate that the ecological forecast horizon is a flexible and powerful tool for researching and communicating ecological predictability. It also has potential for motivating and guiding agenda setting for ecological forecasting research and development.

Keywords
Dynamics, ecosystems, environmental change, forecasting, futures, prediction, scenarios
National Category
Ecology
Identifiers
urn:nbn:se:umu:diva-106315 (URN)10.1111/ele.12443 (DOI)000356606100001 ()25960188 (PubMedID)
Funder
EU, FP7, Seventh Framework Programme, 283068
Available from: 2015-07-17 Created: 2015-07-10 Last updated: 2018-06-07Bibliographically approved
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