scholarly journals The Poisson-lognormal model as a versatile framework for the joint analysis of species abundances

2020 ◽  
Author(s):  
Julien Chiquet ◽  
Mahendra Mariadassou ◽  
Stéphane Robin
Keyword(s):  
Species Abundance ◽  
Habitat Type ◽  
Joint Analysis ◽  
Species Competition ◽  
Ecological Interactions ◽  
Variational Techniques ◽  
Species Abundances ◽  
Species Abundance Models ◽  
Potential Interactions ◽  
Multivariate Sample

AbstractJoint Species Abundance Models (JSDM) provide a general multivariate framework to study the joint abundances of all species from a community. JSDM account for both structuring factors (environmental characteristics or gradients, such as habitat type or nutrient availability) and potential interactions between the species (competition, mutualism, parasitism, etc.), which is instrumental in disentangling meaningful ecological interactions from mere statistical associations.Modeling the dependency between the species is challenging because of the count-valued nature of abundance data and most JSDM rely on Gaussian latent layer to encode the dependencies between species in a covariance matrix. The multivariate Poisson-lognormal (PLN) model is one such model, which can be viewed as a multivariate mixed Poisson regression model. The inference of such models raises both statistical and computational issues, many of which were solved in recent contributions using variational techniques and convex optimization.The PLN model turns out to be a versatile framework, within which a variety of analyses can be performed, including multivariate sample comparison, clustering of sites or samples, dimension reduction (ordination) for visualization purposes, or inference of interaction networks. This paper presents the general PLN framework and illustrates its use on a series a typical experimental datasets. All the models and methods are implemented in the R package PLNmodels, available from cran.r-project.org.

scholarly journals The Poisson-Lognormal Model as a Versatile Framework for the Joint Analysis of Species Abundances

2021 ◽  
Vol 9 ◽  
Author(s):  
Julien Chiquet ◽  
Mahendra Mariadassou ◽  
Stéphane Robin
Keyword(s):  
Species Distribution Models ◽  
Habitat Type ◽  
Joint Analysis ◽  
Species Competition ◽  
Ecological Interactions ◽  
Distribution Models ◽  
Variational Techniques ◽  
Species Abundances ◽  
Potential Interactions ◽  
Multivariate Sample

Joint Species Distribution Models (JSDM) provide a general multivariate framework to study the joint abundances of all species from a community. JSDM account for both structuring factors (environmental characteristics or gradients, such as habitat type or nutrient availability) and potential interactions between the species (competition, mutualism, parasitism, etc.), which is instrumental in disentangling meaningful ecological interactions from mere statistical associations. Modeling the dependency between the species is challenging because of the count-valued nature of abundance data and most JSDM rely on Gaussian latent layer to encode the dependencies between species in a covariance matrix. The multivariate Poisson-lognormal (PLN) model is one such model, which can be viewed as a multivariate mixed Poisson regression model. Inferring such models raises both statistical and computational issues, many of which were solved in recent contributions using variational techniques and convex optimization tools. The PLN model turns out to be a versatile framework, within which a variety of analyses can be performed, including multivariate sample comparison, clustering of sites or samples, dimension reduction (ordination) for visualization purposes, or inferring interaction networks. This paper presents the general PLN framework and illustrates its use on a series a typical experimental datasets. All the models and methods are implemented in the R package PLNmodels, available from cran.r-project.org.

scholarly journals A new method to analyze species abundances in space using generalized dimensions

2015 ◽  
Author(s):  
Leonardo A Saravia
Keyword(s):  
Species Abundance ◽  
Abundance Distribution ◽  
Community Patterns ◽  
Information Dimension ◽  
Generalized Dimension ◽  
Species Abundances ◽  
Species Abundance Distributions ◽  
Species Area ◽  
Generalized Dimensions ◽  
Relationship Of

Species-area relationships (SAR) and species abundance distributions (SAD) are among the most studied patterns in ecology, due to their application to both theoretical and conservation issues. One problem with these general patterns is that different theories can generate the same predictions, and for this reason they cannot be used to detect different mechanisms of community assembly. A solution is to search for more sensitive patterns, for example by extending the SAR to the whole species abundance distribution. A generalized dimension ($D_q$) approach has been proposed to study the scaling of SAD, but to date there has been no evaluation of the ability of this pattern to detect different mechanisms. An equivalent way to express SAD is the rank abundance distribution (RAD). Here I introduce a new way to study SAD scaling using a spatial version of RAD: the species-rank surface (SRS), which can be analyzed using $D_q$. Thus there is an old $D_q$ based on SAR ($D_q^{SAD}$), and a new one based on SRS ($D_q^{SRS}$). I perform spatial simulations to examine the relationship of $D_q$ with SAD, spatial patterns and number of species. Finally I compare the power of both $D_q$, SAD, SAR exponent, and the fractal information dimension to detect different community patterns using a continuum of hierarchical and neutral spatially explicit models. The SAD, $D_q^{SAD}$ and $D_q^{SRS}$ all had good performance in detecting models with contrasting mechanisms. $D_q^{SRS}$, however, had a better fit to data and allowed comparisons between hierarchical communities where the other methods failed. The SAR exponent and information dimension had low power and should not be used. SRS and $D_q^{SRS}$ could be interesting methods to study community or macroecological patterns.

scholarly journals Self–organized instability in complex ecosystems

2002 ◽  
Vol 357 (1421) ◽  
pp. 667-681 ◽  
Author(s):  
Ricard V. Solé ◽  
David Alonso ◽  
Alan McKane
Keyword(s):  
Rare Species ◽  
Scaling Law ◽  
Species Abundance ◽  
Field Studies ◽  
Species Number ◽  
Neotropical Forests ◽  
Species Abundances ◽  
Long Tails ◽  
Critical Boundary ◽  
Species Area

Why are some ecosystems so rich, yet contain so many rare species? High species diversity, together with rarity, is a general trend in neotropical forests and coral reefs. However, the origin of such diversity and the consequences of food web complexity in both species abundances and temporal fluctuations are not well understood. Several regularities are observed in complex, multispecies ecosystems that suggest that these ecologies might be organized close to points of instability. We explore, in greater depth, a recent stochastic model of population dynamics that is shown to reproduce: (i) the scaling law linking species number and connectivity; (ii) the observed distributions of species abundance reported from field studies (showing long tails and thus a predominance of rare species); (iii) the complex fluctuations displayed by natural communities (including chaotic dynamics); and (iv) the species–area relations displayed by rainforest plots. It is conjectured that the conflict between the natural tendency towards higher diversity due to immigration, and the ecosystem level constraints derived from an increasing number of links, leaves the system poised at a critical boundary separating stable from unstable communities, where large fluctuations are expected to occur. We suggest that the patterns displayed by species–rich communities, including rarity, would result from such a spontaneous tendency towards instability.

scholarly journals Assessment of congruence between co-occurrence and functional networks: A new framework for revealing community assembly rules

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Gaëlle Legras ◽  
Nicolas Loiseau ◽  
Jean-Claude Gaertner ◽  
Jean-Christophe Poggiale ◽  
Dino Ienco ◽  
...  
Keyword(s):  
Network Theory ◽  
Species Abundance ◽  
Species Traits ◽  
Functional Networks ◽  
Global Changes ◽  
Assembly Rules ◽  
Spatial And Temporal Scales ◽  
Assembly Rule ◽  
Species Abundances ◽  
New Framework

AbstractDescribing how communities change over space and time is crucial to better understand and predict the functioning of ecosystems. We propose a new methodological framework, based on network theory and modularity concept, to determine which type of mechanisms (i.e. deterministic versus stochastic processes) has the strongest influence on structuring communities. This framework is based on the computation and comparison of two networks: the co-occurrence (based on species abundances) and the functional networks (based on the species traits values). In this way we can assess whether the species belonging to a given functional group also belong to the same co-occurrence group. We adapted the Dg index of Gauzens et al. (2015) to analyze congruence between both networks. This offers the opportunity to identify which assembly rule(s) play(s) the major role in structuring the community. We illustrate our framework with two datasets corresponding to different faunal groups and ecosystems, and characterized by different scales (spatial and temporal scales). By considering both species abundance and multiple functional traits, our framework improves significantly the ability to discriminate the main assembly rules structuring the communities. This point is critical not only to understand community structuring but also its response to global changes and other disturbances.

Epibenthic community structure in Port Phillip Bay, Victoria, Australia

2000 ◽  
Vol 51 (7) ◽  
pp. 689 ◽  
Author(s):  
Brian F. Cohen ◽  
David R. Currie ◽  
Matthew A. McArthur
Keyword(s):  
Community Structure ◽  
Species Abundance ◽  
Habitat Type ◽  
Demersal Fish ◽  
Asterias Amurensis ◽  
Styela Plicata ◽  
Strong Trend ◽  
Epifaunal Community ◽  
Inshore Waters ◽  
Total Species

Epibenthic community structure in Port Phillip Bay was examined from quantitative diver samples collected at 30 depth-stratified stations during 1998. Analysis of variance showed a strong trend of decreasing epibenthic abundance, biomass and species diversity with depth. Reductions in these three parameters were most pronounced over shallow inshore waters and could be attributed largely to decreases in the abundance of the heavy, mat-forming ascidian Pyura stolonifera with depth. Four epifaunal community groupings, closely reflecting differences in sediment and habitat type within the bay, were identified from ordinations of species abundance and biomass data. The four epifaunal groupings also closely matched distributional patterns observed in other studies in both demersal fish and infaunal communities. Epifaunal communities in the bay were dominated by filter-feeding organisms which accounted for nearly 95% of the total species abundance and 98% of the total species biomass. Seven of the 63 epibenthic organisms collected during the survey are exotic introductions to the bay (Sabella spallanzanii, Ascidiella aspersa, Styela clava, Styela plicata, Ciona intestinalis, Pyromaia tuberculata and Asterias amurensis). As many of these species are widespread and abundant (35% of all individuals), their effects on the ecology of Port Phillip Bay are likely to be significant.

scholarly journals Interactions among ecosystem stressors and their importance in conservation

2016 ◽  
Vol 283 (1824) ◽  
pp. 20152592 ◽  
Author(s):  
Isabelle M. Côté ◽  
Emily S. Darling ◽  
Christopher J. Brown
Keyword(s):  
Biological Processes ◽  
Additive Effects ◽  
Ecological Interactions ◽  
The Past ◽  
Ecological Literature ◽  
Adaptive Monitoring ◽  
Ecosystem Stressors ◽  
Meta Analyses ◽  
Potential Interactions ◽  
Near Future

Interactions between multiple ecosystem stressors are expected to jeopardize biological processes, functions and biodiversity. The scientific community has declared stressor interactions—notably synergies—a key issue for conservation and management. Here, we review ecological literature over the past four decades to evaluate trends in the reporting of ecological interactions (synergies, antagonisms and additive effects) and highlight the implications and importance to conservation. Despite increasing popularity, and ever-finer terminologies, we find that synergies are (still) not the most prevalent type of interaction, and that conservation practitioners need to appreciate and manage for all interaction outcomes, including antagonistic and additive effects. However, it will not be possible to identify the effect of every interaction on every organism's physiology and every ecosystem function because the number of stressors, and their potential interactions, are growing rapidly. Predicting the type of interactions may be possible in the near-future, using meta-analyses, conservation-oriented experiments and adaptive monitoring. Pending a general framework for predicting interactions, conservation management should enact interventions that are robust to uncertainty in interaction type and that continue to bolster biological resilience in a stressful world.

Selection of vertebrate wildlife indicators for monitoring sustainable forest management in Ontario

1998 ◽  
Vol 74 (2) ◽  
pp. 241-248 ◽  
Author(s):  
Margaret A. McLaren ◽  
Ian D. Thompson ◽  
James A. Baker
Keyword(s):  
Forest Management ◽  
Indicator Species ◽  
Biological Diversity ◽  
Sustainable Forest Management ◽  
Species Abundance ◽  
Habitat Type ◽  
General Hypothesis ◽  
The Matrix ◽  
Criteria For Selection ◽  
Selection Of

Part of a recently advocated method of sustainable forest development employs indicator species as fine filters to assess changes within ecosystems and landscapes. We used a series of criteria based on biology, sampling methods, and legal or particular status to select vertebrate indicator species for the province of Ontario. The criteria for selection were applied in a hierarchical manner, with species ecology given primary importance, followed by sampling considerations, and status criteria. The latter represented certain societal weightings and political or featured management concerns. Species fitting the selection criteria were placed in a four-dimensional matrix (with axes: broad habitat type, age class, trophic level, and spatial scale), and species were then chosen from among the matrix cells. The exercise reduced the total vertebrate species in two forest biomes (Boreal and Great-Lakes St. Lawrence) to a relative few, from which the final choices were made primarily based on expert opinion. In Ontario, the species selected as indicators of biological diversity will be used to test the underlying general hypothesis that forest management has no effect on species richness and species abundance, or the distribution of species in time and space.

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