Relatedness and the composition of communities over time: Evaluating phylogenetic community structure in the late Cenozoic record of bivalves

Paleobiology ◽  
2020 ◽  
pp. 1-13
Author(s):  
Lucy M. Chang ◽  
Phillip L. Skipwith
Keyword(s):  
Community Structure ◽  
Competitive Exclusion ◽  
Critical Role ◽  
Environmental Filtering ◽  
Influential Factors ◽  
Phylogenetic Distance ◽  
Late Cenozoic ◽  
Phylogenetic Community Structure ◽  
Historical Perspectives ◽  
Over Time

Abstract Understanding the mechanisms that prevent or promote the coexistence of taxa at local scales is critical to understanding how biodiversity is maintained. Competitive exclusion and environmental filtering are two processes thought to limit which taxa become established in a community. However, determining the relative importance of the two processes is a complex task, especially when the critical initial stages of colonization cannot be directly observed. Here, we explore the use of phylogenetic community structure for identifying filtering mechanisms in a fossil community. We integrated a time-calibrated molecular phylogeny of bivalve genera with a spatial dataset of late Cenozoic bivalves from the Pacific coast of North America to characterize how the community that was present in the semirestricted San Joaquin Basin (SJB) embayment of present-day California was phylogenetically structured. We employed phylogenetic distance-based metrics across six time bins spanning 27–2.5 Ma and found no evidence of significant clustering or evenness in the SJB community when compared with communities randomly assembled from the regional source pool. Additionally, we found that new colonizers into the SJB were not significantly more or less closely related to native taxa than expected by chance. These findings suggest that neither competitive exclusion nor environmental filtering were overwhelmingly influential factors shaping the composition of the SJB community over time. We further discuss interpretations of these patterns in light of current understandings in community phylogenetics and reiterate the critical role historical perspectives play in how community assembly rules are assessed.

scholarly journals Spatial analysis of phylogenetic community structure: New version of a classical method

2015 ◽  
Author(s):  
Carlo Ricotta ◽  
Eszter EA Ari ◽  
Giuliano Bonanomi ◽  
Francesco Giannino ◽  
Duncan Heathfield ◽  
...  
Keyword(s):  
Community Structure ◽  
Spatial Scales ◽  
Point Pattern ◽  
Maximum Deviation ◽  
Individual Plant ◽  
Phylogenetic Distance ◽  
Phylogenetic Structure ◽  
Phylogenetic Community Structure ◽  
Point Patterns ◽  
Wide Range

The increasing availability of phylogenetic information facilitates the use of evolutionary methods in community ecology to reveal the importance of evolution in the species assembly process. However, while several methods have been applied to a wide range of communities across different spatial scales with the purpose of detecting non-random phylogenetic patterns, the spatial aspects of phylogenetic community structure have received far less attention. Accordingly, the question for this study is: can point pattern analysis be used for revealing the phylogenetic structure of multi-species assemblages? We introduce a new individual-centered procedure for analyzing the scale-dependent phylogenetic structure of multi-species point patterns based on digitized field data. The method uses nested circular plots with increasing radii drawn around each individual plant and calculates the mean phylogenetic distance between the focal individual and all individuals located in the circular ring delimited by two successive radii. This scale-dependent value is then averaged over all individuals of the same species and the observed mean is compared to a null expectation with permutation procedures. The method detects particular radius values at which the point pattern of a single species exhibits maximum deviation from the expectation towards either phylogenetic aggregation or segregation. Its performance is illustrated using data from a grassland community in Hungary and simulated point patterns. The proposed method can be extended to virtually any distance function for species pairs, such as functional distances.

scholarly journals A new dispersal-informed null model for community ecology shows strong performance

2016 ◽  
Author(s):  
Eliot Miller
Keyword(s):  
Community Structure ◽  
Competitive Exclusion ◽  
Null Model ◽  
Error Rates ◽  
Null Models ◽  
Type I ◽  
Habitat Filtering ◽  
Exclusion Processes ◽  
Phylogenetic Community Structure ◽  
Structure Metrics

AbstractNull models in ecology have been developed that, by maintaining some aspects of observed communities and repeatedly randomizing others, allow researchers to test for the action of community assembly processes like habitat filtering and competitive exclusion. Such processes are often detected using phylogenetic community structure metrics. When biologically significant elements, such as the number of species per assemblage, break down during randomizations, it can lead to high error rates. Realistic dispersal probabilities are often neglected during randomization, and existing models make the oftentimes empirically unreasonable assumption that all species are equally probable of dispersing to a given site. When this assumption is unwarranted, null models need to incorporate dispersal probabilities. I do so here, and present a dispersal null model (DNM) that strictly maintains species richness, and approximately maintains species occurrence frequencies and total abundance. I tested its statistical performance when used with a wide breadth of phylogenetic community structure metrics across 3,000 simulated communities assembled according to neutral, habitat filtering, and competitive exclusion processes. The DNM performed well, exhibiting low error rates (both type I and II). I also implemented it in a re-analysis of a large empirical dataset, an abundance matrix of 696 sites and 75 species of Australian Meliphagidae. Although the overall signal from that study remained unchanged, it showed that statistically significant phylogenetic clustering could have been an artifact of dispersal limitations.

scholarly journals Spatial analysis of phylogenetic community structure: New version of a classical method

2015 ◽  
Author(s):  
Carlo Ricotta ◽  
Eszter EA Ari ◽  
Giuliano Bonanomi ◽  
Francesco Giannino ◽  
Duncan Heathfield ◽  
...  
Keyword(s):  
Community Structure ◽  
Spatial Scales ◽  
Point Pattern ◽  
Maximum Deviation ◽  
Individual Plant ◽  
Phylogenetic Distance ◽  
Phylogenetic Structure ◽  
Phylogenetic Community Structure ◽  
Point Patterns ◽  
Wide Range

The increasing availability of phylogenetic information facilitates the use of evolutionary methods in community ecology to reveal the importance of evolution in the species assembly process. However, while several methods have been applied to a wide range of communities across different spatial scales with the purpose of detecting non-random phylogenetic patterns, the spatial aspects of phylogenetic community structure have received far less attention. Accordingly, the question for this study is: can point pattern analysis be used for revealing the phylogenetic structure of multi-species assemblages? We introduce a new individual-centered procedure for analyzing the scale-dependent phylogenetic structure of multi-species point patterns based on digitized field data. The method uses nested circular plots with increasing radii drawn around each individual plant and calculates the mean phylogenetic distance between the focal individual and all individuals located in the circular ring delimited by two successive radii. This scale-dependent value is then averaged over all individuals of the same species and the observed mean is compared to a null expectation with permutation procedures. The method detects particular radius values at which the point pattern of a single species exhibits maximum deviation from the expectation towards either phylogenetic aggregation or segregation. Its performance is illustrated using data from a grassland community in Hungary and simulated point patterns. The proposed method can be extended to virtually any distance function for species pairs, such as functional distances.

scholarly journals Phylogenetic community structure metrics and null models: a review with new methods and software

2015 ◽  
Author(s):  
Eliot T Miller ◽  
Damien R Farine ◽  
Christopher H Trisos
Keyword(s):  
Community Structure ◽  
Community Assembly ◽  
Competitive Exclusion ◽  
Null Model ◽  
Error Rates ◽  
Null Models ◽  
Type I ◽  
Habitat Filtering ◽  
Phylogenetic Community Structure ◽  
Structure Metrics

Competitive exclusion and habitat filtering are believed to have an important influence on the assembly of ecological communities, but ecologists and evolutionary biologists have not reached a consensus on how to quantify patterns that would reveal the action of these processes. No fewer than 22 phylogenetic community structure metrics and nine null models can be combined, providing 198 approaches to test for such patterns. Choosing statistically appropriate approaches is currently a daunting task. First, given random community assembly, we assessed similarities among metrics and among null models in their behavior across communities varying in species richness. Second, we developed spatially explicit, individual-based simulations where communities were assembled either at random, by competitive exclusion or by habitat filtering. Third, we quantified the performance (type I and II error rates) of all 198 approaches against each of the three assembly processes. Many metrics and null models are functionally equivalent, more than halving the number of unique approaches. Moreover, an even smaller subset of metric and null model combinations is suitable for testing community assembly patterns. Metrics like mean pairwise phylogenetic distance and phylogenetic diversity were better able to detect simulated community assembly patterns than metrics like phylogenetic abundance evenness. A null model that simulates regional dispersal pressure on the community of interest outperformed all others. We introduce a flexible new R package, metricTester, to facilitate robust analyses of method performance. The package is programmed in parallel to readily accommodate integration of new row-wise matrix calculations (metrics) and matrix-wise randomizations (null models) to generate expectations and quantify error rates of proposed methods.

scholarly journals Plant DNA barcodes and assessment of phylogenetic community structure of a tropical mixed dipterocarp forest in Brunei Darussalam (Borneo)

PLoS ONE ◽  
2017 ◽  
Vol 12 (10) ◽  
pp. e0185861 ◽  
Author(s):  
Jacqueline Heckenhauer ◽  
Kamariah Abu Salim ◽  
Mark W. Chase ◽  
Kyle G. Dexter ◽  
R. Toby Pennington ◽  
...  
Keyword(s):  
Community Structure ◽  
Dna Barcodes ◽  
Dipterocarp Forest ◽  
Plant Dna ◽  
Phylogenetic Community Structure ◽  
Brunei Darussalam ◽  
Mixed Dipterocarp Forest

scholarly journals Emergent Simplicity in Microbial Community Assembly

2017 ◽  
Author(s):  
Joshua E. Goldford ◽  
Nanxi Lu ◽  
Djordje Bajic ◽  
Sylvie Estrela ◽  
Mikhail Tikhonov ◽  
...  
Keyword(s):  
Community Structure ◽  
Microbial Community ◽  
Community Assembly ◽  
Competitive Exclusion ◽  
Ex Situ ◽  
Coarse Grained ◽  
Natural Environments ◽  
Complex Dynamic ◽  
Microbial Community Assembly ◽  
Consumer Resource

AbstractMicrobes assemble into complex, dynamic, and species-rich communities that play critical roles in human health and in the environment. The complexity of natural environments and the large number of niches present in most habitats are often invoked to explain the maintenance of microbial diversity in the presence of competitive exclusion. Here we show that soil and plant-associated microbiota, cultivated ex situ in minimal synthetic environments with a single supplied source of carbon, universally re-assemble into large and dynamically stable communities with strikingly predictable coarse-grained taxonomic and functional compositions. We find that generic, non-specific metabolic cross-feeding leads to the assembly of dense facilitation networks that enable the coexistence of multiple competitors for the supplied carbon source. The inclusion of universal and non-specific cross-feeding in ecological consumer-resource models is sufficient to explain our observations, and predicts a simple determinism in community structure, a property reflected in our experiments.

Measurement and Prediction of Sound Exposure Levels by University Wind Bands

2010 ◽  
Vol 25 (1) ◽  
pp. 29-34 ◽  
Author(s):  
Kris Chesky
Keyword(s):  
Linear Regression Analysis ◽  
Critical Role ◽  
Significant Proportion ◽  
Sound Exposure ◽  
Sound Levels ◽  
Wind Bands ◽  
Exposure Levels ◽  
The Mean ◽  
Over Time

The purpose of this study was to determine sound exposure levels generated in two college wind bands. Dosimeter data from a large sample of ensemble-based instructional activities (n = 43) was collected over time and processed to assess associations with predictor variables that may be relevant to this context, including indicators of time spend at various intensity levels, maximum and peak sound levels, degree of variability of sound levels over time, and the percentage of time playing music. The mean dose per event for the entire sample was 109.5% and ranged from 53.8% to 166.9%. Results of linear regression analysis revealed that regressors accounted for a significant proportion of the variance in dose (F = 128.42, p < 0.000) and a statistically significant and very large (96% variance accounted for) contribution to the prediction of dose. Findings implicate the critical role of the instructor and teaching pedagogy.

Feature Detectors and Descriptors Generations With Numerous Images and Video Applications

2018 ◽  
pp. 571-600 ◽  
Author(s):  
Nilanjan Dey ◽  
Amira S. Ashour ◽  
Aboul Ella Hassanien
Keyword(s):  
Object Recognition ◽  
Video Retrieval ◽  
Critical Role ◽  
Medical Applications ◽  
Visual Feature ◽  
Interest Points ◽  
Feature Detectors ◽  
Computational Speed ◽  
Real Time Applications ◽  
Over Time

Feature detectors have a critical role in numerous applications such as camera calibrations, object recognition, biometrics, medical applications and image/video retrieval. One of its main tasks is to extract point correspondences “Interest points” between two similar scenes, objects, images or video shots. Extensive research has been done concerning the progress of visual feature detectors and descriptors to be robust against image deformations and achieve reduced computational speed in real-time applications. The current chapter introduced an overview of feature detectors such as Moravec, Hessian, Harris and FAST (Features from Accelerated Segment Test). It addressed the feature detectors' generation over time, the principle concept of each type, and their use in image/video applications. Furthermore, some recent feature detectors are addressed. A comparison based on these points is performed to illustrate their respective strengths and weaknesses to be a base for selecting an appropriate detector according to the application under concern.

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