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 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 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.

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.

scholarly journals Recent Advances in Unmanned Aerial Vehicle Forest Remote Sensing—A Systematic Review. Part I: A General Framework

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 327 ◽  
Author(s):  
Riccardo Dainelli ◽  
Piero Toscano ◽  
Salvatore Filippo Di Gennaro ◽  
Alessandro Matese
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicle ◽  
Relevant Information ◽  
Forest Monitoring ◽  
Machine Learning Techniques ◽  
Planted Forests ◽  
Systematic Analysis ◽  
Aerial Photogrammetry ◽  
Wide Range ◽  
Aerial Vehicle

Natural, semi-natural, and planted forests are a key asset worldwide, providing a broad range of positive externalities. For sustainable forest planning and management, remote sensing (RS) platforms are rapidly going mainstream. In a framework where scientific production is growing exponentially, a systematic analysis of unmanned aerial vehicle (UAV)-based forestry research papers is of paramount importance to understand trends, overlaps and gaps. The present review is organized into two parts (Part I and Part II). Part II inspects specific technical issues regarding the application of UAV-RS in forestry, together with the pros and cons of different UAV solutions and activities where additional effort is needed, such as the technology transfer. Part I systematically analyzes and discusses general aspects of applying UAV in natural, semi-natural and artificial forestry ecosystems in the recent peer-reviewed literature (2018–mid-2020). The specific goals are threefold: (i) create a carefully selected bibliographic dataset that other researchers can draw on for their scientific works; (ii) analyze general and recent trends in RS forest monitoring (iii) reveal gaps in the general research framework where an additional activity is needed. Through double-step filtering of research items found in the Web of Science search engine, the study gathers and analyzes a comprehensive dataset (226 articles). Papers have been categorized into six main topics, and the relevant information has been subsequently extracted. The strong points emerging from this study concern the wide range of topics in the forestry sector and in particular the retrieval of tree inventory parameters often through Digital Aerial Photogrammetry (DAP), RGB sensors, and machine learning techniques. Nevertheless, challenges still exist regarding the promotion of UAV-RS in specific parts of the world, mostly in the tropical and equatorial forests. Much additional research is required for the full exploitation of hyperspectral sensors and for planning long-term monitoring.

scholarly journals The Fecal Bacterial Microbiota in Horses with Equine Recurrent Uveitis

Animals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 745
Author(s):  
Michelle Martin de Bustamante ◽  
Diego Gomez ◽  
Jennifer MacNicol ◽  
Ralph Hamor ◽  
Caryn Plummer
Keyword(s):  
Beta Diversity ◽  
High Throughput Sequencing ◽  
Illumina Miseq ◽  
Diversity Indices ◽  
Rrna Gene ◽  
Linear Discriminant ◽  
Alpha And Beta Diversity ◽  
Bacterial Microbiota ◽  
Healthy Control ◽  
Equine Recurrent Uveitis

The objective of this study was to describe and compare the fecal bacterial microbiota of horses with equine recurrent uveitis (ERU) and healthy horses using next-generation sequencing techniques. Fecal samples were collected from 15 client-owned horses previously diagnosed with ERU on complete ophthalmic examination. For each fecal sample obtained from a horse with ERU, a sample was collected from an environmentally matched healthy control with no evidence of ocular disease. The Illumina MiSeq sequencer was used for high-throughput sequencing of the V4 region of the 16S rRNA gene. The relative abundance of predominant taxa, and alpha and beta diversity indices were calculated and compared between groups. The phyla Firmicutes, Bacteroidetes, Verrucomicrobia, and Proteobacteria predominated in both ERU and control horses, accounting for greater than 60% of sequences. Based on linear discriminant analysis effect size (LEfSe), no taxa were found to be enriched in either group. No significant differences were observed in alpha and beta diversity indices between groups (p > 0.05 for all tests). Equine recurrent uveitis is not associated with alteration of the gastrointestinal bacterial microbiota when compared with healthy controls.

Landscape patterns influence communities of medium- to large-bodied vertebrates in undisturbed terra firme forests of French Guiana

2015 ◽  
Vol 31 (5) ◽  
pp. 423-436 ◽  
Author(s):  
Cécile Richard-Hansen ◽  
Gaëlle Jaouen ◽  
Thomas Denis ◽  
Olivier Brunaux ◽  
Eric Marcon ◽  
...  
Keyword(s):  
Beta Diversity ◽  
Amazon Basin ◽  
French Guiana ◽  
Forest Ecology ◽  
Habitat Preferences ◽  
Diversity Indices ◽  
Landscape Patterns ◽  
Line Transect ◽  
Terra Firme ◽  
Association Index

Abstract:Whereas broad-scale Amazonian forest types have been shown to influence the structure of the communities of medium- to large-bodied vertebrates, their natural heterogeneity at smaller scale or within the terra firme forests remains poorly described and understood. Diversity indices of such communities and the relative abundance of the 21 most commonly observed species were compared from standardized line-transect data across 25 study sites distributed in undisturbed forests in French Guiana. We first assessed the relevance of a forest typology based on geomorphological landscapes to explain the observed heterogeneity. As previously found for tree beta-diversity patterns, this new typology proved to be a non-negligible factor underlying the beta diversity of the communities of medium- to large bodied vertebrates in French Guianan terra firme forests. Although the species studied are almost ubiquitous across the region, they exhibited habitat preferences through significant variation in abundance and in their association index with the different landscape types. As terra firme forests represent more than 90% of the Amazon basin, characterizing their heterogeneity – including faunal communities – is a major challenge in neotropical forest ecology.

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