scholarly journals Beta diversity patterns derived from island biogeography theory

2018 ◽  
Author(s):  
Muyang Lu ◽  
David Vasseur ◽  
Walter Jetz
Keyword(s):  
Community Composition ◽  
Beta Diversity ◽  
Island Biogeography ◽  
Species Abundance ◽  
Alpha Diversity ◽  
Species Level ◽  
Neutral Model ◽  
Diversity Patterns ◽  
Species Abundance Distributions ◽  
Species Area

AbstractThe Theory of Island Biogeography (TIB) has been successful in predicting alpha diversity patterns such as species-area relationships and species-abundance distributions. Although beta diversity (i.e. the dissimilarity of community composition) has long been recognized as an important element of the TIB and is crucial for understanding community assembly processes, it has never been formally incorporated into the theory. Here we derive theoretical predictions for the expected pairwise beta diversity values under a species-level neutral scenario where all species have equal colonization and extinction rates. We test these predictions for the avian community composition of 42 islands (and 93 species) in the Thousand Island Lake, China. We find that alpha diversity patterns alone do not distinguish a species-level neutral model from a non-neutral model. In contrast, beta diversity patterns clearly reject a species-level neutral model. We suggest that the presented theoretical integration beta diversity offers a powerful path for testing the presence of neutral processes in ecology and biogeography.

scholarly journals Vaginal bacterial community composition and concentrations of estradiol at the time of artificial insemination in Brangus heifers

2020 ◽  
Vol 98 (6) ◽  
Author(s):  
Riley D Messman ◽  
Zully E Contreras-Correa ◽  
Henry A Paz ◽  
George Perry ◽  
Caleb O Lemley
Keyword(s):  
Bacterial Community ◽  
Community Composition ◽  
Artificial Insemination ◽  
Beta Diversity ◽  
Bacterial Community Composition ◽  
Alpha Diversity ◽  
Species Level ◽  
Rrna Gene ◽  
Microbial Composition ◽  
Vaginal Tract

Abstract The knowledge surrounding the bovine vaginal microbiota and its implications on fertility and reproductive traits remains incomplete. The objective of the current study was to characterize the bovine vaginal bacterial community and estradiol concentrations at the time of artificial insemination (AI). Brangus heifers (n = 78) underwent a 7-d Co-Synch + controlled internal drug release estrus synchronization protocol. At AI, a double-guarded uterine culture swab was used to sample the anterior vaginal tract. Immediately after swabbing the vaginal tract, blood samples were collected by coccygeal venipuncture to determine concentrations of estradiol. Heifers were retrospectively classified as pregnant (n = 29) vs. nonpregnant (n = 49) between 41 and 57 d post-AI. Additionally, heifers were classified into low (1.1 to 2.5 pg/mL; n = 21), medium (2.6 to 6.7 pg/mL; n = 30), and high (7.2 to 17.6 pg/mL; n = 27) concentration of estradiol. The vaginal bacterial community composition was determined through sequencing of the V4 region from the 16S rRNA gene using the Illumina Miseq platform. Alpha diversity was compared via ANOVA and beta diversity was compared via PERMANOVA. There were no differences in the Shannon diversity index (alpha diversity; P = 0.336) or Bray–Curtis dissimilarity (beta diversity; P = 0.744) of pregnant vs. nonpregnant heifers. Overall, bacterial community composition in heifers with high, medium, or low concentrations of estradiol did not differ (P = 0.512). While no overall compositional differences were observed, species-level differences were present within pregnancy status and estradiol concentration groups. The implications of these species-level differences are unknown, but these differences could alter the vaginal environment thereby influencing fertility and vaginal health. Therefore, species-level changes could provide better insight rather than overall microbial composition in relation to an animal’s reproductive health.

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.

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.

Environmental correlates of herpetofaunal diversity in Costa Rica

2010 ◽  
Vol 26 (5) ◽  
pp. 521-531 ◽  
Author(s):  
David Laurencio ◽  
Lee A. Fitzgerald
Keyword(s):  
Costa Rica ◽  
Species Diversity ◽  
Beta Diversity ◽  
Geographic Distance ◽  
Alpha Diversity ◽  
High Elevation ◽  
Diversity Patterns ◽  
Regional Diversity ◽  
Environmental Correlates ◽  
High Elevation Site

Abstract:Disentangling local and historical factors that determine species diversity patterns at multiple spatial scales is fundamental to elucidating processes that govern ecological communities. Here we investigated how environmental correlates may influence diversity at local and regional scales. Primarily utilizing published species lists, amphibian and reptile alpha and beta diversity were assessed at 17 well-surveyed sites distributed among ecoregions throughout Costa Rica. The degree to which regional species diversity patterns were related to environmental variables and geographic distance was determined using Canonical Correspondence Analysis and Mantel tests. Amphibian alpha diversity was highest in lowland Pacific sites (mean = 43.3 species) and lowest at the high elevation site (9 species). Reptile alpha diversity values were high for both lowland Atlantic (mean = 69.5 species) and lowland Pacific (mean = 67 species) sites and lowest for the high elevation site (8 species). We found high species turnover between local sites and ecoregions, demonstrating the importance of beta diversity in the determination of regional diversity. For both amphibians and reptiles, beta diversity was highest between the high-elevation site and all others, and lowest among lowland sites within the same ecoregion. The effect of geographic distance on beta diversity was minor. Ecologically significant climatic variables related to rain, temperature, sunshine and insolation were found to be important determinants of local and regional diversity for both amphibians and reptiles in Costa Rica.

scholarly journals Robust, data-driven bioregionalizations emerge from diversity concordance

2021 ◽  
Author(s):  
Cristian S. Montalvo-Mancheno ◽  
Jessie Buettel ◽  
Stefania Ondei ◽  
Barry W. Brook
Keyword(s):  
Species Diversity ◽  
Beta Diversity ◽  
Alpha Diversity ◽  
Data Driven ◽  
Conservation Units ◽  
Conservation Action ◽  
Diversity Patterns ◽  
Alpha And Beta Diversity ◽  
Terrestrial Vertebrates ◽  
Site Diversity

Aim: Despite the increasing interest in developing new bioregionalizations and assessing the most widely accepted biogeographic frameworks, no study to date has sought to systematically define a system of small bioregions nested within larger ones that better reflect the distribution and patterns of biodiversity. Here, we examine how an algorithmic, data-driven model of diversity patterns can lead to an ecologically interpretable hierarchy of bioregions. Location: Australia. Time period: Present. Major taxa studied: Terrestrial vertebrates and vascular plants. Methods: We compiled information on the biophysical characteristics and species occupancy of Australia′s geographic conservation units (bioregions). Then, using cluster analysis to identify groupings of bioregions representing optimal discrete-species areas, we evaluated what a hierarchical bioregionalization system would look like when based empirically on the within- and between-site diversity patterns across taxa. Within an information-analytical framework, we then assessed the degree to which the World Wildlife Fund′s (WWF) biomes and ecoregions and our suite of discrete-species areas are spatially associated and compared those results among bioregionalization scenarios. Results: Information on biodiversity patterns captured was moderate for WWF′s biomes (50–58% for birds′ beta, and plants′ alpha and beta diversity, of optimal discrete areas, respectively) and ecoregions (additional 4–25%). Our plants and vertebrate optimal areas retained more information on alpha and beta diversity across taxa, with the two algorithmically derived biogeographic scenarios sharing 86.5% of their within- and between-site diversity information. Notably, discrete-species areas for beta diversity were parsimonious with respect to those for alpha diversity. Main conclusions: Nested systems of bioregions must systematically account for the variation of species diversity across taxa if biodiversity research and conservation action are to be most effective across multiple spatial or temporal planning scales. By demonstrating an algorithmic rather than subjective method for defining bioregionalizations using species-diversity concordances, which reliably reflects the distributional patterns of multiple taxa, this work offers a valuable new tool for systematic conservation planning.

The Ecology of Echo

1997 ◽  
Vol 3 (3) ◽  
pp. 165-190 ◽  
Author(s):  
Peter T. Hraber ◽  
Terry Jones ◽  
Stephanie Forrest
Keyword(s):  
Significant Contribution ◽  
Species Abundance ◽  
Ecosystem Model ◽  
Ecological Diversity ◽  
Good Qualitative Agreement ◽  
Simulation Experiments ◽  
Naturally Occurring ◽  
Resource Limited ◽  
Species Abundance Distributions ◽  
Species Area

Echo is a generic ecosystem model in which evolving agents are situated in a resource-limited environment. The Echo model is described, and the behavior of Echo is evaluated on two well-studied measures of ecological diversity: relative species abundance and the species-area scaling relation. In simulation experiments, these measures are used to compare the behavior of Echo with that of a neutral model, in which selection on agent genotypes is random. These simulations show that the evolutionary component of Echo makes a significant contribution to its behavior and that Echo shows good qualitative agreement with naturally occurring species abundance distributions and species-area scaling relations.

Macroalgal canopies reduce beta diversity in intertidal communities

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Ricardo A. Scrosati ◽  
Alexis M. Catalán ◽  
Nelson Valdivia
Keyword(s):  
Species Composition ◽  
Beta Diversity ◽  
Species Abundance ◽  
Canopy Cover ◽  
Alpha Diversity ◽  
Intertidal Communities ◽  
Alpha And Beta Diversity ◽  
Curtis Dissimilarity ◽  
Using Data ◽  
Opposing Effects

Abstract Species diversity in a habitat is often termed alpha diversity. As it influences various community properties, many studies have investigated its drivers. For instance, intertidal macroalgal canopies limit understory thermal stress during low tides and thus often increase alpha diversity. More recently, beta diversity has also become of interest. Beta diversity measures the change in species composition across space and is another important attribute of communities because it influences their multifunctionality, productivity, and resilience. Using data from a field experiment done in Atlantic Canada, we tested the hypothesis that fucoid macroalgal canopies limit beta diversity in intertidal communities. This prediction stems from previous evidence that such canopies limit thermal variation across the substrate during low tides, an important consideration because spatial thermal changes influence spatial variability in species composition. To test our hypothesis, we compared two treatments (full canopy cover and canopy removal) created the year before on intertidal areas that were originally all fully covered by canopies. Separately for each treatment, we calculated beta diversity as the Bray-Curtis dissimilarity between nearby quadrats using species abundance data. Overall, fucoid macroalgal canopies significantly reduced beta diversity, showing that these foundation species can have opposing effects on alpha and beta diversity.

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

2014 ◽  
Author(s):  
Leonardo A Saravia
Keyword(s):  
Species Abundance ◽  
Abundance Distribution ◽  
Community Patterns ◽  
Information Dimension ◽  
Spatially Explicit Models ◽  
Generalized Dimension ◽  
Species Abundances ◽  
Species Abundance Distributions ◽  
Species Area ◽  
Generalized Dimensions

Species-area relationships (SAR) and species abundance distributions (SAD) are among the most studied patterns in ecology, due to their application in 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 can not be used to detect different mechanisms. A solution for this is to search for more sensitive patterns. One possibility is to extend the SAR to the whole species abundance distribution. A generalized dimension (\(D_q\)) approach has been proposed to study the scaling of SAD, but 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 scaling of SAD 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 relate both \(D_q\) 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. \(D_q^{SRS}\) had a better fit to data and a strong ability to compare 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 an interesting addition to study community or macroecological patterns.

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

2014 ◽  
Author(s):  
Leonardo A Saravia
Keyword(s):  
Species Abundance ◽  
Abundance Distribution ◽  
Community Patterns ◽  
Information Dimension ◽  
Spatially Explicit Models ◽  
Generalized Dimension ◽  
Species Abundances ◽  
Species Abundance Distributions ◽  
Species Area ◽  
Generalized Dimensions

Species-area relationships (SAR) and species abundance distributions (SAD) are among the most studied patterns in ecology, due to their application in 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 can not be used to detect different mechanisms. A solution for this is to search for more sensitive patterns. One possibility is to extend the SAR to the whole species abundance distribution. A generalized dimension ($D_q$) approach has been proposed to study the scaling of SAD, but 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 scaling of SAD 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 relate both $D_q$ 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. $D_q^{SRS}$ had a better fit to data and a strong ability to compare 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 an interesting addition to study community or macroecological patterns.

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