scholarly journals Multivariate methods for testing hypotheses of temporal community dynamics

2018 ◽  
Author(s):  
Hannah L. Buckley ◽  
Nicola J. Day ◽  
Bradley S. Case ◽  
Gavin Lear ◽  
Aaron M. Ellison
Keyword(s):  
Community Dynamics ◽  
Temporal Change ◽  
Change Processes ◽  
Multivariate Methods ◽  
Quantitative Review ◽  
Biological Communities ◽  
Road Map ◽  
Temporal Intervals ◽  
Underlying Mechanisms ◽  
Extinction Events

ABSTRACTFor ecological research to make important contributions towards understanding and managing temporally-variable global change processes, such as responses to land-use and climatic change, we must have effective and comparable ways to quantify and analyse compositional change over time in biological communities. These changes are the sum of local colonisation and extinction events, or changes in the biomass and relative abundance of taxa within and among samples. We conducted a quantitative review of currently available methods for the analysis of multivariate datasets collected at temporal intervals. This review identified the need for the application of quantitative, hypothesis-based approaches to understand temporal change in community composition, particularly for small datasets with less than 15 temporal replicates. To address this gap, we: (1) conceptually present how temporal patterns in community dynamics can be framed as specific, testable hypotheses; (2) provide three fully-worked case-studies, complete with R code, demonstrating multivariate analysis methods for temporal hypothesis testing and pattern visualisation; and (3) present a road map for testing specific, quantitative hypotheses relating to the underlying mechanisms of temporal community dynamics.

scholarly journals Extinction and recolonization of coastal megafauna following human arrival in New Zealand

2014 ◽  
Vol 281 (1786) ◽  
pp. 20140097 ◽  
Author(s):  
Catherine J. Collins ◽  
Nicolas J. Rawlence ◽  
Stefan Prost ◽  
Christian N. K. Anderson ◽  
Michael Knapp ◽  
...  
Keyword(s):  
New Zealand ◽  
Sea Lion ◽  
Vast Number ◽  
Biological Communities ◽  
Biological Responses ◽  
Demographic Processes ◽  
Evolutionary Radiations ◽  
Extinction Events ◽  
Mass Extinction Events ◽  
Adna Analysis

Extinctions can dramatically reshape biological communities. As a case in point, ancient mass extinction events apparently facilitated dramatic new evolutionary radiations of surviving lineages. However, scientists have yet to fully understand the consequences of more recent biological upheaval, such as the megafaunal extinctions that occurred globally over the past 50 kyr. New Zealand was the world's last large landmass to be colonized by humans, and its exceptional archaeological record documents a vast number of vertebrate extinctions in the immediate aftermath of Polynesian arrival approximately AD 1280. This recently colonized archipelago thus presents an outstanding opportunity to test for rapid biological responses to extinction. Here, we use ancient DNA (aDNA) analysis to show that extinction of an endemic sea lion lineage ( Phocarctos spp.) apparently facilitated a subsequent northward range expansion of a previously subantarctic-limited lineage. This finding parallels a similar extinction–replacement event in penguins ( Megadyptes spp.). In both cases, an endemic mainland clade was completely eliminated soon after human arrival, and then replaced by a genetically divergent clade from the remote subantarctic region, all within the space of a few centuries. These data suggest that ecological and demographic processes can play a role in constraining lineage distributions, even for highly dispersive species, and highlight the potential for dynamic biological responses to extinction.

scholarly journals Measuring change in biological communities: multivariate analysis approaches for temporal datasets with low sample size

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11096
Author(s):  
Hannah L. Buckley ◽  
Nicola J. Day ◽  
Bradley S. Case ◽  
Gavin Lear
Keyword(s):  
Time Series ◽  
Sample Size ◽  
Statistical Power ◽  
Structural Changes ◽  
Linear Models ◽  
Environmental Changes ◽  
Short Time Series ◽  
Biological Communities ◽  
Extinction Events ◽  
Short Time

Effective and robust ways to describe, quantify, analyse, and test for change in the structure of biological communities over time are essential if ecological research is to contribute substantively towards understanding and managing responses to ongoing environmental changes. Structural changes reflect population dynamics, changes in biomass and relative abundances of taxa, and colonisation and extinction events observed in samples collected through time. Most previous studies of temporal changes in the multivariate datasets that characterise biological communities are based on short time series that are not amenable to data-hungry methods such as multivariate generalised linear models. Here, we present a roadmap for the analysis of temporal change in short-time-series, multivariate, ecological datasets. We discuss appropriate methods and important considerations for using them such as sample size, assumptions, and statistical power. We illustrate these methods with four case-studies analysed using the R data analysis environment.

Stochastic Processes

Ecology ◽  
2019 ◽  
Author(s):  
Kohmei Kadowaki
Keyword(s):  
Stochastic Processes ◽  
Population Size ◽  
Community Dynamics ◽  
Random Order ◽  
Small Population ◽  
Random Fluctuation ◽  
Lightning Strikes ◽  
Tropical Biodiversity ◽  
Chance Events ◽  
Extinction Events

Chance events (such as lightning strikes or floods) occur commonly in nature. In ecology, unpredictable events that can affect population and community dynamics are called stochastic processes. Although ecologists recognize that stochastic processes occur, their importance in shaping populations and communities has been controversial. Determining when and how stochastic processes are important ecologically is critical for predicting extinction events or responses to climate change and explaining tropical biodiversity. Many population dynamics appears to be stochastic, particularly when the environment fluctuates or the population is small. For example, environmental variation that can reduce population size can increase the likelihood of stochastic extinction, because a small population is prone to go extinct due to random fluctuation in population size. Community dynamics can also be influenced by stochastic processes such as chance colonization, random order of immigration/emigration, and random fluctuations of population size. For example, community succession depends on which species arrive first, when early-arriving species outcompete later-arriving species. Modern ecologists generally agree that dynamics of most populations and communities have both deterministic (predictable) and stochastic (unpredictable) components that operate simultaneously. I thank Stacey Halpern for comments.

scholarly journals Thermodynamic constraints on the assembly and diversity of microbial ecosystems are different near to and far from equilibrium

2021 ◽  
Vol 17 (12) ◽  
pp. e1009643
Author(s):  
Jacob Cook ◽  
Samraat Pawar ◽  
Robert G. Endres
Keyword(s):  
Free Energy ◽  
Microbial Communities ◽  
Community Dynamics ◽  
Time Frame ◽  
Community Diversity ◽  
Ecosystem Level ◽  
Energy Consuming ◽  
Interaction Types ◽  
Mechanistic Basis ◽  
Underlying Mechanisms

Non-equilibrium thermodynamics has long been an area of substantial interest to ecologists because most fundamental biological processes, such as protein synthesis and respiration, are inherently energy-consuming. However, most of this interest has focused on developing coarse ecosystem-level maximisation principles, providing little insight into underlying mechanisms that lead to such emergent constraints. Microbial communities are a natural system to decipher this mechanistic basis because their interactions in the form of substrate consumption, metabolite production, and cross-feeding can be described explicitly in thermodynamic terms. Previous work has considered how thermodynamic constraints impact competition between pairs of species, but restrained from analysing how this manifests in complex dynamical systems. To address this gap, we develop a thermodynamic microbial community model with fully reversible reaction kinetics, which allows direct consideration of free-energy dissipation. This also allows species to interact via products rather than just substrates, increasing the dynamical complexity, and allowing a more nuanced classification of interaction types to emerge. Using this model, we find that community diversity increases with substrate lability, because greater free-energy availability allows for faster generation of niches. Thus, more niches are generated in the time frame of community establishment, leading to higher final species diversity. We also find that allowing species to make use of near-to-equilibrium reactions increases diversity in a low free-energy regime. In such a regime, two new thermodynamic interaction types that we identify here reach comparable strengths to the conventional (competition and facilitation) types, emphasising the key role that thermodynamics plays in community dynamics. Our results suggest that accounting for realistic thermodynamic constraints is vital for understanding the dynamics of real-world microbial communities.

scholarly journals Deviations from dynamic equilibrium in ecological communities worldwide

2019 ◽  
Author(s):  
Michael Kalyuzhny ◽  
Curtis H. Flather ◽  
Nadav M. Shnerb ◽  
Ronen Kadmon
Keyword(s):  
Community Dynamics ◽  
Local Community ◽  
Environmental Changes ◽  
Dynamic Equilibrium ◽  
Ecological Niches ◽  
Ecological Communities ◽  
Parsimonious Explanation ◽  
Primary Driver ◽  
Extinction Events

AbstractEcological communities are assembled by colonization and extinction events, that may be regulated by ecological niches1–5. The most parsimonious explanation of local community assembly is the Dynamic Equilibrium (DE) model, which assumes that community dynamics is shaped by random colonization and extinctions events, effectively ignoring the effects of niches1, 6. Despite its empirical success in explaining diversity patterns1, 5, 7, it is unknown to what extent the assembly dynamics of communities around the globe are consistent with this model. Using a newly developed methodology, we show that in 4989 communities from 49 different datasets, representing multiple taxa, biomes and locations, changes in richness and composition are larger than expected by DE. All the fundamental assumptions of DE are violated, but the large changes in species richness and composition primarily stem from the synchrony in the dynamics of different species. These results indicate that temporal changes in communities are predominantly driven by shared responses of co-occurring species to environmental changes, rather than by inter-specific competition. This finding is in sharp contrast to the long-term recognition of competition as a primary driver of species assembly8–12. While ecological niches are often thought to stabilize species diversity and composition4, 13, 14, we found that they promote large changes in ecological communities.

Responses of abundant and rare bacterioplankton to temporal change in a subtropical urban reservoir

2021 ◽  
Vol 97 (4) ◽  
Author(s):  
Pascaline Nyirabuhoro ◽  
Xiaofei Gao ◽  
Jean Claude Ndayishimiye ◽  
Peng Xiao ◽  
Yuanyuan Mo ◽  
...  
Keyword(s):  
Microbial Community ◽  
Bacterial Community ◽  
High Frequency ◽  
Community Dynamics ◽  
Temporal Change ◽  
Time Intervals ◽  
Rare Taxa ◽  
Frequency Sampling ◽  
Long Time ◽  
High Frequency Sampling

ABSTRACT Investigation of bacterial community dynamics across different time scales is important for understanding how environmental conditions drive community change over time. Bacterioplankton from the surface waters of a subtropical urban reservoir in southeast China were analyzed through high-frequency sampling over 13 months to compare patterns and ecological processes between short (0‒8 weeks), medium (9‒24 weeks) and long (25‒53 weeks) time intervals. We classified the bacterial community into different subcommunities: abundant taxa (AT); conditionally rare taxa (CRT); rare taxa (RT). CRT contributed > 65% of the alpha-diversity, and temporal change of beta-diversities was more pronounced for AT and CRT than RT. The bacterial community exhibited a directional change in the short- and medium-time intervals and a convergent dynamic during the long-time interval due to a seasonal cycle. Cyanobacteria exhibited a strong succession pattern than other phyla. CRT accounted for > 76% of the network nodes in three stations. The bacteria–environment relationship and deterministic processes were stronger for large sample size at station G (n = 116) than small sample size at stations C (n = 12) and L (n = 22). These findings suggest that a high-frequency sampling approach can provide a better understanding on the time scales at which bacterioplankton can change fast between being abundant or rare, thus providing the facts about environmental factors driving microbial community dynamics. Patterns and processes in alpha- and beta-diversities and community assembly of bacterioplankton differ among different time intervals (short-, medium- and long-time intervals) and different subcommunities (abundant, conditionally rare and rare taxa) in a subtropical urban reservoir, demonstrating the importance of temporal scale and high-frequency sampling in microbial community ecology.

scholarly journals A framework for quantifying deviations from dynamic equilibrium theory

2019 ◽  
Author(s):  
Michael Kalyuzhny ◽  
Curtis H. Flather ◽  
Nadav M. Shnerb ◽  
Ronen Kadmon
Keyword(s):  
Time Series ◽  
Community Assembly ◽  
Community Dynamics ◽  
Dynamic Equilibrium ◽  
Null Model ◽  
Simulated Data ◽  
Florida Keys ◽  
Alternative Methods ◽  
Ecological Communities ◽  
Extinction Events

AbstractCommunity assembly is governed by colonization and extinction processes, and the simplest model describing it is Dynamic Equilibrium (DE) theory, which assumes that communities are shaped solely by stochastic colonization and extinction events. Despite its potential to serve as a null model for community dynamics, there is currently no accepted methodology for measuring deviations from the theory and testing it. Here we propose a novel and easily applicable methodology for quantifying deviations from the predictions and assumptions of DE by comparing observed community time-series to a randomization-based null model. We show that this methodology has good statistical properties on simulated data, and it can detect deviations from both the assumptions and predictions of DE in the classical Florida Keys experiment. We discuss alternative methods and present guidelines for practical use of the methodology, hoping it will enhance the applicability of DE as a reference for studying changes in ecological communities.

scholarly journals Shorter neural adaptation to sounds accounts for dyslexics’ abnormal perceptual and reading dynamics

2016 ◽  
Author(s):  
Sagi Jaffe-Dax ◽  
Orr Frenkel ◽  
Merav Ahissar
Keyword(s):  
Implicit Memory ◽  
Oral Reading ◽  
Frequency Discrimination ◽  
Neural Adaptation ◽  
Time Interval ◽  
Similar Time ◽  
Complex Stimuli ◽  
Temporal Intervals ◽  
Oral Reading Rate ◽  
Underlying Mechanisms

AbstractDyslexia is a prevalent reading disability whose underlying mechanisms are still disputed. We studied the neural mechanisms underlying dyslexia using a simple frequency-discrimination task. Though participants were asked to compare the 2-tones in each trial, implicit memory of previous trials affected their responses. We hypothesized that implicit memory decays faster among dyslexics. We tested this by increasing the temporal intervals between consecutive trials, and measuring the behavioral impact and ERP responses from the auditory cortex. Dyslexics showed a faster decay of implicit memory effects on both measures, with similar time constants. Finally, faster decay also characterized dyslexics’ benefits in oral reading rate. It decreased faster as a function of the time interval from the previous reading of the same non-word. We propose that dyslexics’ shorter neural adaptation paradoxically accounts for their longer reading times, since it induces noisier and less reliable predictions for both simple and complex stimuli.

scholarly journals Changes in the analysis of temporal community dynamics data: a 29-year literature review

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11250 ◽  
Author(s):  
Hannah L. Buckley ◽  
Nicola J. Day ◽  
Gavin Lear ◽  
Bradley S. Case
Keyword(s):  
Time Series ◽  
Experimental Design ◽  
Best Practice ◽  
Community Dynamics ◽  
Temporal Dynamics ◽  
Habitat Type ◽  
Community Analysis ◽  
Median Number ◽  
Biological Communities ◽  
Short Time

Background Understanding how biological communities change over time is of increasing importance as Earth moves into the Anthropocene. A wide variety of methods are used for multivariate community analysis and are variously applied to research that aims to characterise temporal dynamics in community composition. Understanding these methods and how they are applied is useful for determining best practice in community ecology. Methodology We reviewed the ecological literature from 1990 to 2018 that used multivariate methods to address questions of temporal community dynamics. For each paper that fulfilled our search criteria, we recorded the types of multivariate analysis used to characterise temporal community dynamics in addition to the research aim, habitat type, location, taxon and the experimental design. Results Most studies had relatively few temporal replicates; the median number was seven time points. Nearly 70% of studies applied more than one analysis method; descriptive methods such as bar graphs and ordination were the most commonly applied methods. Surprisingly, the types of analyses used were only related to the number of temporal replicates, but not to research aim or any other aspects of experimental design such as taxon, or habitat or year of study. Conclusions This review reveals that most studies interested in understanding community dynamics use relatively short time series meaning that several, more sophisticated, temporal analyses are not widely applicable. However, newer methods using multivariate dissimilarities are growing in popularity and many can be applied to time series of any length.

scholarly journals Factors affecting the performance of the acoustic ground discrimination system RoxAnn™

2003 ◽  
Vol 60 (6) ◽  
pp. 1373-1380 ◽  
Author(s):  
Thomas A Wilding ◽  
Martin D.J Sayer ◽  
Paul G Provost
Keyword(s):  
Temporal Variability ◽  
Temporal Change ◽  
Apparent Magnitude ◽  
Considerable Variability ◽  
Sediment Texture ◽  
The West ◽  
Factors Affecting ◽  
Biological Communities ◽  
Speed Dependence ◽  
Vessel Speed

Abstract The resolution, temporal variability and survey vessel speed dependence of the acoustic ground discrimination system RoxAnn™ was assessed over a 1 km2 area in Loch Linnhe on the west coast of Scotland. The resolution of the system was relatively poor and of the sediment parameters quantified (stone cover and sediment texture), only stone cover was consistently and significantly related to the RoxAnn™ output. The output showed considerable variability over the same ground when sampled within the same day and between days and months. The effect of survey vessel speed on the output was also significant but highly variable during all surveys. The apparent magnitude and unpredictable nature of the variation in the RoxAnn™ output have implications for the use of such systems in habitat mapping, particularly when surveying biological communities where there are only small differences in the physical properties of the seabed and also where monitoring temporal change. These aspects are discussed.

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