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 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 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 Accuracy of mutual predictions of plant and microbe communities varies along a successional gradient in an alpine glacier forefield

2021 ◽  
Author(s):  
Xie He ◽  
Maximilian Hanusch ◽  
Victoria Ruiz-Hernández ◽  
Robert R. Junker
Keyword(s):  
Environmental Factors ◽  
Community Composition ◽  
Diversity Indices ◽  
List Type ◽  
Alpine Glacier ◽  
Glacier Forefield ◽  
Successional Gradient ◽  
Direct Indication ◽  
Bacteria And Fungi ◽  
Taxonomic Groups

SummaryDue to climate warming, recently deglaciated glacier forefields create virtually uninhabited substrates waiting for initial colonization of bacteria, fungi and plants and serve as an ideal ecosystem for studying transformations in community composition and diversity over time and the interactions between taxonomic groups.In this study, we investigated the composition and diversity of bacteria, and fungi, plants and environmental factors (pH, temperature, plot age and soil nutrients) along a 1.5km glacier forefield. We used random forest analysis to detect how well the composition and diversity of taxonomic groups and environmental factors can be mutually predicted.Community composition and diversity of taxonomic groups predicted each other more accurately than environmental factors predicted the taxonomic groups; within the taxonomic groups bacteria and fungi predicted each other best and the taxa’s composition was better predicted than diversity indices. Additionally, accuracy of prediction among taxonomic groups and environmental factors considerably varied along the successional gradient.Although our results are no direct indication of interactions between the taxa investigated and the environmental conditions, the accurate predictions among bacteria, fungi, and plants do provide insights into the concerted community assembly of different taxa in response to changing environments along a successional gradient.

scholarly journals Assessing different components of biodiversity across a river network using eDNA

2019 ◽  
Author(s):  
Elvira Mächler ◽  
Chelsea J. Little ◽  
Remo Wüthrich ◽  
Roman Alther ◽  
Emanuel A. Fronhofer ◽  
...  
Keyword(s):  
Community Composition ◽  
Beta Diversity ◽  
Regional Scale ◽  
Alpha Diversity ◽  
River Network ◽  
List Type ◽  
Taxon Richness ◽  
Gamma Diversity ◽  
Catchment Scale ◽  
Novel Technique

AbstractAssessing individual components of biodiversity, such as local or regional taxon richness, and differences in community composition is a long-standing challenge in ecology. It is especially relevant in spatially structured and diverse ecosystems. Environmental DNA (eDNA) has been suggested as a novel technique to accurately measure biodiversity. However, we do not yet fully understand the comparability of eDNA-based assessments to previously used approaches.We sampled may-, stone-, and caddisfly genera with contemporary eDNA and kicknet methods at 61 sites distributed over a large river network, allowing a comparison of various diversity measures from the catchment to site levels and providing insights into how these measures relate to network properties. We extended our survey data with historical records of total diversity at the catchment level.At the catchment scale, eDNA and kicknet detected similar proportions of the overall and cumulative historically documented species richness (gamma diversity), namely 42% and 46%, respectively. We further found a good overlap (62%) between the two contemporary methods at the regional scale.At the local scale, we found highly congruent values of local taxon richness (alpha diversity) between eDNA and kicknet. Richness of eDNA was positively related with discharge, a descriptor of network position, while kicknet was not.Beta diversity between sites was similar for the two contemporary methods. Contrary to our expectation, however, beta diversity was driven by species replacement and not by nestedness.Although optimization of eDNA approaches is still needed, our results indicate that this novel technique can capture extensive aspects of gamma diversity, proving its potential utility as a new tool for large sampling campaigns across hitherto understudied complete river catchments, requiring less time and becoming more cost-efficient than classical approaches. Overall, the richness estimated with the two contemporary methods is similar at both local and regional scale but community composition is differently assessed with the two methods at individual sites and becomes more similar with higher discharge.

Comparison of Deterministic and Linear Cosine Spatial Filtering of Transmission Electron Micrographs

1972 ◽  
Vol 30 ◽  
pp. 596-597
Author(s):  
David A. Ansley
Keyword(s):  
Spherical Aberration ◽  
Focal Length ◽  
Chromatic Aberration ◽  
Spatial Filter ◽  
Operating Conditions ◽  
Objective Lens ◽  
List Type ◽  
Spatial Filters ◽  
Transmission Electron ◽  
Wide Range

The coherence of the electron flux of a transmission electron microscope (TEM) limits the direct application of deconvolution techniques which have been used successfully on unmanned spacecraft programs. The theory assumes noncoherent illumination. Deconvolution of a TEM micrograph will, therefore, in general produce spurious detail rather than improved resolution.A primary goal of our research is to study the performance of several types of linear spatial filters as a function of specimen contrast, phase, and coherence. We have, therefore, developed a one-dimensional analysis and plotting program to simulate a wide 'range of operating conditions of the TEM, including adjustment of the:(1) Specimen amplitude, phase, and separation(2) Illumination wavelength, half-angle, and tilt(3) Objective lens focal length and aperture width(4) Spherical aberration, defocus, and chromatic aberration focus shift(5) Detector gamma, additive, and multiplicative noise constants(6) Type of spatial filter: linear cosine, linear sine, or deterministic

Triply-periodic nanostructures in surfactant, block copolymer, and biomembrane systems, and simulation of TEMs

1993 ◽  
Vol 51 ◽  
pp. 884-885
Author(s):  
David M. Anderson ◽  
Tomas Landh
Keyword(s):  
Liquid Crystalline ◽  
Diblock Copolymers ◽  
Cubic Phase ◽  
List Type ◽  
Interpenetrating Networks ◽  
Triply Periodic ◽  
Wide Range ◽  
Bicontinuous Cubic ◽  
Phase Liquid ◽  
Dividing Surface

First discovered in surfactant-water liquid crystalline systems, so-called ‘bicontinuous cubic phases’ have the property that hydropnilic and lipophilic microdomains form interpenetrating networks conforming to cubic lattices on the scale of nanometers. Later these same structures were found in star diblock copolymers, where the simultaneous continuity of elastomeric and glassy domains gives rise to unique physical properties. Today it is well-established that the symmetry and topology of such a morphology are accurately described by one of several triply-periodic minimal surfaces, and that the interface between hydrophilic and hydrophobic, or immiscible polymer, domains is described by a triply-periodic surface of constant, nonzero mean curvature. One example of such a dividing surface is shown in figure 5.The study of these structures has become of increasing importance in the past five years for two reasons:1)Bicontinuous cubic phase liquid crystals are now being polymerized to create microporous materials with monodispersed pores and readily functionalizable porewalls; figure 3 shows a TEM from a polymerized surfactant / methylmethacrylate / water cubic phase; and2)Compelling evidence has been found that these same morphologies describe biomembrane systems in a wide range of cells.

Temporal dynamics of mycorrhizal fungal communities and co-associations with grassland plant communities following experimental manipulation of rainfall

2019 ◽  
Author(s):  
Coline Deveautour ◽  
Sally Power ◽  
Kirk Barnett ◽  
Raul Ochoa-Hueso ◽  
Suzanne Donn ◽  
...  
Keyword(s):  
Community Composition ◽  
Plant Community ◽  
Plant Communities ◽  
Fungal Community ◽  
Mycorrhizal Fungi ◽  
Temporal Dynamics ◽  
Arbuscular Mycorrhizal ◽  
Fungal Communities ◽  
Plant Responses ◽  
Rainfall Regimes

Climate models project overall a reduction in rainfall amounts and shifts in the timing of rainfall events in mid-latitudes and sub-tropical dry regions, which threatens the productivity and diversity of grasslands. Arbuscular mycorrhizal fungi may help plants to cope with expected changes but may also be impacted by changing rainfall, either via the direct effects of low soil moisture on survival and function or indirectly via changes in the plant community. In an Australian mesic grassland (former pasture) system, we characterised plant and arbuscular mycorrhizal (AM) fungal communities every six months for nearly four years to two altered rainfall regimes: i) ambient, ii) rainfall reduced by 50% relative to ambient over the entire year and iii) total summer rainfall exclusion. Using Illumina sequencing, we assessed the response of AM fungal communities sampled from contrasting rainfall treatments and evaluated whether variation in AM fungal communities was associated with variation in plant community richness and composition. We found that rainfall reduction influenced the fungal communities, with the nature of the response depending on the type of manipulation, but that consistent results were only observed after more than two years of rainfall manipulation. We observed significant co-associations between plant and AM fungal communities on multiple dates. Predictive co-correspondence analyses indicated more support for the hypothesis that fungal community composition influenced plant community composition than vice versa. However, we found no evidence that altered rainfall regimes were leading to distinct co-associations between plants and AM fungi. Overall, our results provide evidence that grassland plant communities are intricately tied to variation in AM fungal communities. However, in this system, plant responses to climate change may not be directly related to impacts of altered rainfall regimes on AM fungal communities. Our study shows that AM fungal communities respond to changes in rainfall but that this effect was not immediate. The AM fungal community may influence the composition of the plant community. However, our results suggest that plant responses to altered rainfall regimes at our site may not be resulting via changes in the AM fungal communities.

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 Global soil moisture data derived through machine learning trained with in-situ measurements

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Sungmin O. ◽  
Rene Orth
Keyword(s):  
Machine Learning ◽  
Soil Moisture ◽  
Large Scale ◽  
Short Term Memory ◽  
Temporal Dynamics ◽  
Soil Moisture Data ◽  
Wide Range ◽  
Global Soil

AbstractWhile soil moisture information is essential for a wide range of hydrologic and climate applications, spatially-continuous soil moisture data is only available from satellite observations or model simulations. Here we present a global, long-term dataset of soil moisture derived through machine learning trained with in-situ measurements, SoMo.ml. We train a Long Short-Term Memory (LSTM) model to extrapolate daily soil moisture dynamics in space and in time, based on in-situ data collected from more than 1,000 stations across the globe. SoMo.ml provides multi-layer soil moisture data (0–10 cm, 10–30 cm, and 30–50 cm) at 0.25° spatial and daily temporal resolution over the period 2000–2019. The performance of the resulting dataset is evaluated through cross validation and inter-comparison with existing soil moisture datasets. SoMo.ml performs especially well in terms of temporal dynamics, making it particularly useful for applications requiring time-varying soil moisture, such as anomaly detection and memory analyses. SoMo.ml complements the existing suite of modelled and satellite-based datasets given its distinct derivation, to support large-scale hydrological, meteorological, and ecological analyses.

Sign in / Sign up

Export Citation Format

Share Document