Stochastic Community Assembly: Does It Matter in Microbial Ecology?

Microbiology and Molecular Biology Reviews, Journal Year: 2017, Volume and Issue: 81(4)

Published: Oct. 12, 2017

Understanding the mechanisms controlling community diversity, functions, succession, and biogeography is a central, but poorly understood, topic in ecology, particularly microbial ecology. Although stochastic processes are believed to play nonnegligible roles shaping structure, their importance relative deterministic hotly debated. The of ecological stochasticity structure far less appreciated. Some main reasons for such heavy debates difficulty defining diverse methods used delineating stochasticity. Here, we provide critical review synthesis data from most recent studies on assembly We then describe both components embedded various processes, including selection, dispersal, diversification, drift. also different approaches inferring observational diversity patterns highlight experimental communities. In addition, research challenges, gaps, future directions research.

Language: Английский

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Quantifying community assembly processes and identifying features that impose them

The ISME Journal, Journal Year: 2013, Volume and Issue: 7(11), P. 2069 - 2079

Published: June 6, 2013

Language: Английский

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Patterns and Processes of Microbial Community Assembly

Microbiology and Molecular Biology Reviews, Journal Year: 2013, Volume and Issue: 77(3), P. 342 - 356

Published: Sept. 1, 2013

Recent research has expanded our understanding of microbial community assembly. However, the field ecology is inaccessible to many ecologists because inconsistent and often confusing terminology as well unnecessarily polarizing debates. Thus, we review recent literature on assembly, using framework Vellend (Q. Rev. Biol. 85:183-206, 2010) in an effort synthesize unify these contributions. We begin by discussing patterns biogeography then describe four basic processes (diversification, dispersal, selection, drift) that contribute also discuss different combinations where when they may be most important for shaping communities. The spatial temporal scales assembly are discussed relation processes. Throughout this paper, highlight differences between microbes macroorganisms generate hypotheses describing how end implications ecosystem function biodiversity.

Language: Английский

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Beta diversity as the variance of community data: dissimilarity coefficients and partitioning

Ecology Letters, Journal Year: 2013, Volume and Issue: 16(8), P. 951 - 963

Published: July 1, 2013

Abstract Beta diversity can be measured in different ways. Among these, the total variance of community data table Y used as an estimate beta diversity. We show how calculated either directly or through a dissimilarity matrix obtained using any index deemed appropriate for pairwise comparisons composition data. addressed question which to use by coding 16 indices 14 properties that are necessary assessment, comparability among sets, sampling issues and ordination. Our comparison analysis classified coefficients under study into five types, three assessment. approach links concept with commonly methods like ordination anova . Total partitioned Species Contributions ( SCBD : degree variation individual species across area) Local LCBD comparative indicators ecological uniqueness sites) Diversity. Moreover, broken up within‐ among‐group components manova , orthogonal axes ordination, spatial scales eigenfunction explanatory sets partitioning.

Language: Английский

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How Should Beta-Diversity Inform Biodiversity Conservation?

Trends in Ecology & Evolution, Journal Year: 2015, Volume and Issue: 31(1), P. 67 - 80

Published: Dec. 17, 2015

Language: Английский

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A general framework for quantitatively assessing ecological stochasticity

Proceedings of the National Academy of Sciences, Journal Year: 2019, Volume and Issue: 116(34), P. 16892 - 16898

Published: Aug. 7, 2019

Understanding the community assembly mechanisms controlling biodiversity patterns is a central issue in ecology. Although it generally accepted that both deterministic and stochastic processes play important roles assembly, quantifying their relative importance challenging. Here we propose general mathematical framework to quantify ecological stochasticity under different situations which factors drive communities more similar or dissimilar than null expectation. An index, normalized ratio (NST), was developed with 50% as boundary point between (<50%) (>50%) assembly. NST tested simulated by considering abiotic filtering, competition, environmental noise, spatial scales. All approaches showed limited performance at large scales very high noise. However, all of other scenarios, accuracy (0.90 1.00) precision (0.91 0.99), averages 0.37 higher (0.1 0.7) 0.33 (0.0 1.8) previous approaches. also applied estimate succession groundwater microbial response organic carbon (vegetable oil) injection. Our results shifted from (NST = 21%) 70%) right after input. As vegetable oil consumed, gradually returned be 27%). In addition, our demonstrated model algorithms similarity metrics had strong effects on stochasticity.

Language: Английский

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Why are there so many species in the tropics?

Journal of Biogeography, Journal Year: 2013, Volume and Issue: 41(1), P. 8 - 22

Published: Dec. 16, 2013

Abstract Known for centuries, the geographical pattern of increasing biodiversity from poles to equator is one most pervasive features life on Earth. A longstanding goal biogeographers has been understand primary factors that generate and maintain high diversity in tropics. Many ‘historical’ ‘ecological’ hypotheses have proposed debated, but there still little consensus. Recent discussions centred around two main phenomena: phylogenetic niche conservatism ecological productivity. These play important roles, accumulating theoretical empirical studies suggest single factor kinetics: temperature dependence evolutionary rates. The relatively temperatures tropics because ‘the Red Queen runs faster when she hot’.

Language: Английский

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Stochasticity, succession, and environmental perturbations in a fluidic ecosystem

Proceedings of the National Academy of Sciences, Journal Year: 2014, Volume and Issue: 111(9)

Published: Feb. 18, 2014

Significance The study of ecological succession remains at the core ecology. Understanding trajectories and mechanisms controlling is crucial to predicting responses ecosystems environmental change projecting their future states. By definition, deterministic expected under homogeneous abiotic biotic starting conditions. This study, however, shows that groundwater microbial communities in response nutrient amendment primarily stochastic, but drivers biodiversity are dynamic rather than static. identifying community assembly succession, this makes fundamental contribution mechanistic understanding essential for a predictive ecology many systems ranging from microbiomes humans plants natural managed ecosystems.

Language: Английский

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β-Diversity, Community Assembly, and Ecosystem Functioning

Trends in Ecology & Evolution, Journal Year: 2018, Volume and Issue: 33(7), P. 549 - 564

Published: May 26, 2018

Language: Английский

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A conceptual guide to measuring species diversity

Oikos, Journal Year: 2021, Volume and Issue: 130(3), P. 321 - 338

Published: Feb. 9, 2021

Three metrics of species diversity – richness, the Shannon index and Simpson are still widely used in ecology, despite decades valid critiques leveled against them. Developing a robust metric has been challenging because, unlike many variables ecologists measure, community often cannot be estimated an unbiased way based on random sample from that community. Over past decade, have begun to incorporate two important tools for estimating diversity: coverage Hill diversity. Coverage is method equalizing samples is, theoretical grounds, preferable other commonly methods such as equal‐effort sampling, or rarefying datasets equal size. comprises spectrum three key insights. First, richness variants indices all special cases one general equation. Second, can expressed same scale units species. Third, there no eliminate effect relative abundance estimates any these metrics, including richness. Rather, researcher must choose sensitivity towards rare common species, concept which we describe ‘leverage.' In this paper explain diversity, provide guidelines how use them together measure demonstrate their with examples our own data. We show why researchers will obtain more results when they estimate equal‐coverage samples, rather than using sampling traditional rarefaction.

Language: Английский

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