scholarly journals Statistical methods for temporal and space–time analysis of community composition data

2014 ◽  
Vol 281 (1778) ◽  
pp. 20132728 ◽  
Author(s):  
Pierre Legendre ◽  
Olivier Gauthier
Keyword(s):  
Statistical Methods ◽  
Community Composition ◽  
Beta Diversity ◽  
Variation Partitioning ◽  
Regression Tree ◽  
Space Time ◽  
Time Variability ◽  
Ecological Data ◽  
Canonical Ordination ◽  
Temporal Beta Diversity

This review focuses on the analysis of temporal beta diversity, which is the variation in community composition along time in a study area. Temporal beta diversity is measured by the variance of the multivariate community composition time series and that variance can be partitioned using appropriate statistical methods. Some of these methods are classical, such as simple or canonical ordination, whereas others are recent, including the methods of temporal eigenfunction analysis developed for multiscale exploration (i.e. addressing several scales of variation) of univariate or multivariate response data, reviewed, to our knowledge for the first time in this review. These methods are illustrated with ecological data from 13 years of benthic surveys in Chesapeake Bay, USA. The following methods are applied to the Chesapeake data: distance-based Moran's eigenvector maps, asymmetric eigenvector maps, scalogram, variation partitioning, multivariate correlogram, multivariate regression tree, and two-way MANOVA to study temporal and space–time variability. Local (temporal) contributions to beta diversity (LCBD indices) are computed and analysed graphically and by regression against environmental variables, and the role of species in determining the LCBD values is analysed by correlation analysis. A tutorial detailing the analyses in the R language is provided in an appendix.

scholarly journals Degrees of compositional shift in tree communities vary along a gradient of temperature change rates over one decade: Application of an individual-based temporal beta-diversity concept

2020 ◽  
Author(s):  
Ryosuke Nakadai
Keyword(s):  
Temperature Change ◽  
Community Composition ◽  
Beta Diversity ◽  
Temporal Patterns ◽  
Diversity Indices ◽  
Temporal Changes ◽  
Individual Identity ◽  
Relative Speed ◽  
Identity Information ◽  
Temporal Beta Diversity

AbstractTemporal patterns in communities have gained widespread attention recently, to the extent that temporal changes in community composition are now termed “temporal beta-diversity”. Previous studies of beta-diversity have made use of two classes of dissimilarity indices: incidence-based (e.g., Sørensen and Jaccard dissimilarity) and abundance-based (e.g., Bray–Curtis and Ružička dissimilarity). However, in the context of temporal beta-diversity, the persistence of identical individuals and turnover among other individuals within the same species over time have not been considered, despite the fact that both will affect compositional changes in communities. To address this issue, I propose new index concepts for beta-diversity and the relative speed of compositional shifts in relation to individual turnover based on individual identity information. Individual-based beta-diversity indices are novel dissimilarity indices that consider individual identity information to quantitatively evaluate temporal change in individual turnover and community composition. I applied these new indices to individually tracked tree monitoring data in deciduous and evergreen broad-leaved forests across the Japanese archipelago with the objective of quantifying the effect of climate change trends (i.e., rates of change of both annual mean temperature and annual precipitation) on individual turnover and compositional shifts at each site. A new index explored the relative contributions of mortality and recruitment processes to temporal changes in community composition. Clear patterns emerged showing that an increase in the temperature change rate facilitated the relative contribution of mortality components. The relative speed of compositional shift increased with increasing temperature change rates in deciduous forests but decreased with increasing warming rates in evergreen forests. These new concepts provide a way to identify novel and high-resolution temporal patterns in communities.

scholarly journals Individual-based multiple-unit dissimilarity: novel indices for assessing temporal variability in community composition

2021 ◽  
Author(s):  
Ryosuke Nakadai
Keyword(s):  
Community Composition ◽  
Beta Diversity ◽  
Temporal Dynamics ◽  
Diversity Indices ◽  
Barro Colorado Island ◽  
Forest Monitoring ◽  
List Type ◽  
Wide Range ◽  
Multiple Unit ◽  
Temporal Beta Diversity

AbstractBeta-diversity was originally defined spatially, i.e., as variation in community composition among sites in a region. However, the concept of beta-diversity has since been expanded to temporal contexts. This is referred to as “temporal beta-diversity”, and most approaches are simply an extension of spatial beta-diversity.The persistence and turnover of individuals over time is a unique feature of temporal beta-diversity. Nakadai (2020) introduced the “individual-based beta-diversity” concept, and provided novel indices to evaluate individual turnover and compositional shift by comparing individual turnover between two periods at a given site. However, the proposed individual-based indices are applicable only to pairwise dissimilarity, not to multiple-temporal (or more generally, multiple-unit) dissimilarity.Here, individual-based beta-diversity indices are extended to multiple-unit cases.To demonstrate the usage the properties of these indices compared to average pairwise measures, I applied them to a dataset for a permanent 50-ha forest dynamics plot on Barro Colorado Island in Panama.Information regarding “individuals” is generally missing from community ecology and biodiversity studies of temporal dynamics. In this context, the method proposed here is expected to be useful for addressing a wide range of research questions regarding temporal changes in biodiversity, especially studies using individual-tracked forest monitoring data.

scholarly journals Individual-based multiple-unit dissimilarity: novel indices and null model for assessing temporal variability in community composition

Oecologia ◽  
2021 ◽  
Author(s):  
Ryosuke Nakadai
Keyword(s):  
Community Composition ◽  
Beta Diversity ◽  
Temporal Dynamics ◽  
Null Model ◽  
Diversity Indices ◽  
Barro Colorado Island ◽  
Forest Monitoring ◽  
Wide Range ◽  
Multiple Unit ◽  
Temporal Beta Diversity

AbstractBeta-diversity was originally defined spatially, i.e., as variation in community composition among sites in a region. However, the concept of beta-diversity has since been expanded to temporal contexts. This is referred to as “temporal beta-diversity”, and most approaches are simply an extension of spatial beta-diversity. The persistence and turnover of individuals over time is a unique feature of temporal beta-diversity. Nakadai (2020) introduced the “individual-based beta-diversity” concept, and provided novel indices to evaluate individual turnover and compositional shift by comparing individual turnover between two periods at a given site. However, the proposed individual-based indices are applicable only to pairwise dissimilarity, not to multiple-temporal (or more generally, multiple-unit) dissimilarity. Here, individual-based beta-diversity indices are extended to multiple-unit cases. In addition, a novel type of random permutation criterion related to these multiple-unit indices for detecting patterns of individual persistence is introduced in the present study. To demonstrate the usage the properties of these indices compared to average pairwise measures, I applied them to a dataset for a permanent 50-ha forest dynamics plot on Barro Colorado Island in Panama. Information regarding “individuals” is generally missing from community ecology and biodiversity studies of temporal dynamics. In this context, the methods proposed here are expected to be useful for addressing a wide range of research questions regarding temporal changes in biodiversity, especially studies using traditional individual-tracked forest monitoring data.

scholarly journals Examining residual spatial correlation in variation partitioning of beta diversity in a subtropical forest

2019 ◽  
Vol 12 (4) ◽  
pp. 636-644 ◽  
Author(s):  
Ke Cao ◽  
Xiangcheng Mi ◽  
Liwen Zhang ◽  
Haibao Ren ◽  
Mingjian Yu ◽  
...  
Keyword(s):  
Spatial Correlation ◽  
Beta Diversity ◽  
Variation Partitioning ◽  
Subtropical Forest ◽  
Residual Variance ◽  
Spatial Structures ◽  
Data Set ◽  
Strong Argument ◽  
Canonical Ordination ◽  
Spatial Variables

Abstract Aims The relative roles of ecological processes in structuring beta diversity are usually quantified by variation partitioning of beta diversity with respect to environmental and spatial variables or gamma diversity. However, if important environmental or spatial factors are omitted, or a scale mismatch occurs in the analysis, unaccounted spatial correlation will appear in the residual errors and lead to residual spatial correlation and problematic inferences. Methods Multi-scale ordination (MSO) partitions the canonical ordination results by distance into a set of empirical variograms which characterize the spatial structures of explanatory, conditional and residual variance against distance. Then these variance components can be used to diagnose residual spatial correlation by checking assumptions related to geostatistics or regression analysis. In this paper, we first illustrate the performance of MSO using a simulated data set with known properties, thus making statistical issues explicit. We then test for significant residual spatial correlation in beta diversity analyses of the Gutianshan (GTS) 24-ha subtropical forest plot in eastern China. Important Findings Even though we used up to 24 topographic and edaphic variables mapped at high resolution and spatial variables representing spatial structures at all scales, we still found significant residual spatial correlation at the 10 m × 10 m quadrat scale. This invalidated the analysis and inferences at this scale. We also show that MSO provides a complementary tool to test for significant residual spatial correlation in beta diversity analyses. Our results provided a strong argument supporting the need to test for significant residual spatial correlation before interpreting the results of beta diversity analyses.

Scale sensitivity of environmental effects on the temporal beta diversity of fishes in tropical coastal lagoons

2020 ◽  
Author(s):  
E Martins Camara ◽  
Tubino Andrade Andrade-Tub ◽  
T Pontes Franco ◽  
LN dos Santos ◽  
AFGN dos Santos ◽  
...  
Keyword(s):  
Environmental Effects ◽  
Beta Diversity ◽  
Coastal Lagoons ◽  
Scale Sensitivity ◽  
Temporal Beta Diversity

scholarly journals Forecasting the SST Space-time variability of the Alboran Sea with genetic algorithms

2000 ◽  
Vol 27 (17) ◽  
pp. 2709-2712 ◽  
Author(s):  
Alberto Álvarez ◽  
Cristóbal López ◽  
Margalida Riera ◽  
Emilio Hernández-García ◽  
Joaquín Tintoré
Keyword(s):  
Genetic Algorithms ◽  
Space Time ◽  
Time Variability ◽  
Alboran Sea ◽  
Alborán Sea

scholarly journals Modeling the Variability of Drop Size Distributions in Space and Time

2007 ◽  
Vol 46 (6) ◽  
pp. 742-756 ◽  
Author(s):  
Gyu Won Lee ◽  
Alan W. Seed ◽  
Isztar Zawadzki
Keyword(s):  
Drop Size ◽  
Temporal Structure ◽  
Space Time ◽  
Cascade Model ◽  
Time Variability ◽  
Size Distributions ◽  
Precipitation Field ◽  
Stochastic Fluctuations ◽  
Taylor Hypothesis ◽  
Drop Size Distributions

Abstract The information on the time variability of drop size distributions (DSDs) as seen by a disdrometer is used to illustrate the structure of uncertainty in radar estimates of precipitation. Based on this, a method to generate the space–time variability of the distributions of the size of raindrops is developed. The model generates one moment of DSDs that is conditioned on another moment of DSDs; in particular, radar reflectivity Z is used to obtain rainfall rate R. Based on the fact that two moments of the DSDs are sufficient to capture most of the DSD variability, the model can be used to calculate DSDs and other moments of interest of the DSD. A deterministic component of the precipitation field is obtained from a fixed R–Z relationship. Two different components of DSD variability are added to the deterministic precipitation field. The first represents the systematic departures from the fixed R–Z relationship that are expected from different regimes of precipitation. This is generated using a simple broken-line model. The second represents the fluctuations around the R–Z relationship for a particular regime and uses a space–time multiplicative cascade model. The temporal structure of the stochastic fluctuations is investigated using disdrometer data. Assuming Taylor hypothesis, the spatial structure of the fluctuations is obtained and a stochastic model of the spatial distribution of the DSD variability is constructed. The consistency of the model is validated using concurrent radar and disdrometer data.

An island biogeography model for beta diversity and endemism: The roles of speciation, extinction and dispersal

2015 ◽  
Vol 08 (01) ◽  
pp. 1550011 ◽  
Author(s):  
Youhua Chen
Keyword(s):  
Numerical Simulation ◽  
Community Composition ◽  
Beta Diversity ◽  
Island Biogeography ◽  
Positive Relationship ◽  
Community Patterns ◽  
Speciation Rate ◽  
Immigration Rate ◽  
Extinction Rates

A community composition island biogeography model was developed to explain and predict two community patterns (beta diversity and endemism) with the consideration of speciation, extinction and dispersal processes. Results showed that rate of speciation is positively and linearly associated with beta diversity and endemism, that is, increasing species rates typically could increase the percentage of both endemism and beta diversity. The influences of immigration and extinction rates on beta diversity and endemism are nonlinear, but with numerical simulation, I could observe that increasing extinction rates would lead to decreasing percentage of endemism and beta diversity. The role of immigration rate is very similar to that of speciation rate, having a positive relationship with beta diversity and endemism. Finally, I found that beta diversity is closely related to the percentage of endemism. The slope of this positive relationship is determined jointly by different combinations of speciation, extinction and immigration rates.

Sign in / Sign up

Export Citation Format

Share Document