scholarly journals Effects of negative density dependence and habitat filtering on temporal variation in phylogenetic community structure of seedlings in a mid-subtropical forest

2014 ◽  
Vol 59 (19) ◽  
pp. 1844-1850 ◽  
Author(s):  
ShengWen CHEN ◽  
DaHai ZHU ◽  
MiDe RAO ◽  
JinTun ZHANG ◽  
XiangCheng MI ◽  
...  
Keyword(s):  
Community Structure ◽  
Temporal Variation ◽  
Density Dependence ◽  
Subtropical Forest ◽  
Habitat Filtering ◽  
Phylogenetic Community Structure ◽  
Negative Density Dependence

Differential soil fungus accumulation and density dependence of trees in a subtropical forest

Science ◽  
2019 ◽  
Vol 366 (6461) ◽  
pp. 124-128 ◽  
Author(s):  
Lei Chen ◽  
Nathan G. Swenson ◽  
Niuniu Ji ◽  
Xiangcheng Mi ◽  
Haibao Ren ◽  
...  
Keyword(s):  
Density Dependence ◽  
Demographic Data ◽  
Soil Fungus ◽  
Pathogenic Fungi ◽  
Interspecific Variation ◽  
Subtropical Forest ◽  
Forest Plot ◽  
Accumulation Rates ◽  
Community Data ◽  
Negative Density Dependence

The mechanisms underlying interspecific variation in conspecific negative density dependence (CNDD) are poorly understood. Using a multilevel modeling approach, we combined long-term seedling demographic data from a subtropical forest plot with soil fungal community data by means of DNA sequencing to address the feedback of various guilds of soil fungi on the density dependence of trees. We show that mycorrhizal type mediates tree neighborhood interactions at the community level, and much of the interspecific variation in CNDD is explained by how tree species differ in their fungal density accumulation rates as they grow. Species with higher accumulation rates of pathogenic fungi suffered more from CNDD, whereas species with lower CNDD had higher accumulation rates of ectomycorrhizal fungi, suggesting that mutualistic and pathogenic fungi play important but opposing roles.

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 Phylogenetic turnover during subtropical forest succession across environmental and phylogenetic scales

2017 ◽  
Author(s):  
Oliver Purschke ◽  
Stefan G. Michalski ◽  
Helge Bruelheide ◽  
Walter Durka
Keyword(s):  
Community Structure ◽  
Community Assembly ◽  
Deterministic Model ◽  
Species Turnover ◽  
Subtropical Forest ◽  
List Type ◽  
Spatial And Temporal Patterns ◽  
Species Sorting ◽  
Phylogenetic Community Structure ◽  
Successional Stages

SummaryAlthough spatial and temporal patterns of phylogenetic community structure during succession are inherently interlinked and assembly processes vary with environmental and phylogenetic scale, successional studies of community assembly have yet to integrate spatial and temporal components of community structure, while accounting for scaling issues. To gain insight into the processes that generate biodiversity after disturbance, we combine analyses of spatial and temporal phylogenetic turnover across phylogenetic scales, accounting for covariation with environmental differences.We compared phylogenetic turnover, at the species-and individual-level, within and between five successional stages, representing woody plant communities in a subtropical forest chronosequence. We decomposed turnover at different phylogenetic depths and assessed its covariation with between-plot abiotic differences.Phylogenetic turnover between stages was low relative to species turnover and was not explained by abiotic differences. However, within the late successional stages, there was high presence/absence-based turnover (clustering) that occurred deep in the phylogeny and covaried with environmental differentiation.Our results support a deterministic model of community assembly where (i) phylogenetic composition is constrained through successional time, but (ii) towards late succession, species sorting into preferred habitats according to niche traits that are conserved deep in phylogeny, becomes increasingly important.

scholarly journals Phylogenetic community structure: temporal variation in fish assemblage

2014 ◽  
Vol 4 (11) ◽  
pp. 2146-2153 ◽  
Author(s):  
Sergio Santorelli ◽  
William Magnusson ◽  
Efrem Ferreira ◽  
Erica Caramaschi ◽  
Jansen Zuanon ◽  
...  
Keyword(s):  
Community Structure ◽  
Temporal Variation ◽  
Fish Assemblage ◽  
Phylogenetic Community Structure

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.

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