scholarly journals Ranked tree shapes, non-random extinctions and the loss of phylogenetic diversity

2017 ◽  
Author(s):  
Odile Maliet ◽  
Fanny Gascuel ◽  
Amaury Lambert
Keyword(s):  
Species Diversity ◽  
Phylogenetic Diversity ◽  
Extinction Risk ◽  
Simulated Data ◽  
Random Trees ◽  
Monte Carlo Algorithm ◽  
Conservation Priorities ◽  
Parameter Estimates ◽  
Relative Depth ◽  
As Species

AbstractPhylogenetic diversity (PD) is a measure of the evolutionary legacy of a group of species, which can be used to define conservation priorities. It has been shown that an important loss of species diversity can sometimes lead to a much less important loss of PD, depending on the topology of the species tree and on the distribution of its branch lengths. However, the rate of decrease of PD strongly depends on the relative depths of the nodes in the tree and on the order in which species become extinct. We introduce a new, sampling-consistent, three-parameter model generating random trees with covarying topology, clade relative depths and clade relative extinction risks. This model can be seen as an extension to Aldous’ one parameter splitting model β, which controls for tree balance) with two additional parameters: a new parameter α quantifying the correlation between the richness of a clade and its relative depth, and a parameter η quantifying the correlation between the richness of a clade and its frequency (relative abundance or range), taken herein as a proxy for its overall extinction risk. We show on simulated phylogenies that loss of PD depends on the combined effect of all three parameters, β, α and η. In particular, PD may decrease as fast as species diversity when high extinction risks are clustered within small, old clades, corresponding to a parameter range that we term the ‘thin ice zone’ (β < –1 or α < 0; η > 1). Besides, when high extinction risks are clustered within large clades, the loss of PD can be higher in trees that are more balanced (β > 0), in contrast to the predictions of earlier studies based on simpler models. We propose a Monte-Carlo algorithm, tested on simulated data, to infer all three parameters. Applying it to a real dataset comprising 120 bird clades (class Aves) with known range sizes, we show that parameter estimates precisely fall close to close to a ‘thin ice zone’: the combination of their ranking tree shape and non-random extinctions risks makes them prone to a sudden collapse of PD.

scholarly journals Spatial and species-level metrics reveal global patterns of irreplaceable and imperiled gecko phylogenetic diversity

2020 ◽  
Vol 66 (3-4) ◽  
pp. 239-252
Author(s):  
Rikki Gumbs ◽  
Rachel C Williams ◽  
Anthony M Lowney ◽  
Darrell Smith
Keyword(s):  
Phylogenetic Diversity ◽  
Extinction Risk ◽  
Conservation Status ◽  
Species Level ◽  
Conservation Priorities ◽  
Human Pressure ◽  
Increased Risk ◽  
Data Deficient ◽  
Anthropogenic Threats ◽  
Conservation Prioritisation

Abstract Phylogenetic Diversity (PD) is increasingly recognised as a useful tool for prioritising species and regions for conservation effort. Increased availability of spatial and phylogenetic data for reptiles now facilitates their inclusion in phylogenetically-informed conservation prioritisation efforts. Geckos are a highly divergent and diverse clade that comprises almost 20% of global reptile diversity. Their global distribution is coincident with numerous anthropogenic threats, making them worthy of conservation prioritisation. Here, we combine phylogenetic, spatial distribution and extinction risk data for geckos with global human encroachment data to identify both regions and species representing irreplaceable gecko diversity at risk from human pressure. We show that high levels of irreplaceable gecko diversity are restricted to regions under intense human pressure, such as India, Sri Lanka and the Caribbean. There is a lack of extinction risk data for the western regions of Angola and Namibia, and yet these regions harbour high levels of irreplaceable diversity. At the species level, geckos display more unique PD than other lizards and snakes and are of greater conservation concern under our metric. The PD represented by Data Deficient geckos is at comparable risk to that of Endangered species. Finally, estimates of potential gecko diversity loss increase by up to 300% when species lacking extinction risk data are included. Our analyses show that many evolutionarily unique gecko species are poorly known and are at an increased risk of extinction. Targeted research is needed to elucidate the conservation status of these species and identify conservation priorities.

scholarly journals Estimating Simultaneous Equation Models through an Entropy-Based Incremental Variational Bayes Learning Algorithm

Entropy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 384
Author(s):  
Rocío Hernández-Sanjaime ◽  
Martín González ◽  
Antonio Peñalver ◽  
Jose J. López-Espín
Keyword(s):  
Statistical Theory ◽  
Learning Algorithm ◽  
Real Life ◽  
Simulated Data ◽  
Simultaneous Equation ◽  
Variational Bayes ◽  
Parameter Estimates ◽  
Step Method ◽  
The One ◽  
Simultaneous Equation Models

The presence of unaccounted heterogeneity in simultaneous equation models (SEMs) is frequently problematic in many real-life applications. Under the usual assumption of homogeneity, the model can be seriously misspecified, and it can potentially induce an important bias in the parameter estimates. This paper focuses on SEMs in which data are heterogeneous and tend to form clustering structures in the endogenous-variable dataset. Because the identification of different clusters is not straightforward, a two-step strategy that first forms groups among the endogenous observations and then uses the standard simultaneous equation scheme is provided. Methodologically, the proposed approach is based on a variational Bayes learning algorithm and does not need to be executed for varying numbers of groups in order to identify the one that adequately fits the data. We describe the statistical theory, evaluate the performance of the suggested algorithm by using simulated data, and apply the two-step method to a macroeconomic problem.

scholarly journals Conservation Status of Marine Biodiversity in Oceania: An Analysis of Marine Species on the IUCN Red List of Threatened Species

2011 ◽  
Vol 2011 ◽  
pp. 1-14 ◽  
Author(s):  
Beth A. Polidoro ◽  
Cristiane T. Elfes ◽  
Jonnell C. Sanciangco ◽  
Helen Pippard ◽  
Kent E. Carpenter
Keyword(s):  
Threatened Species ◽  
Environmental Changes ◽  
Extinction Risk ◽  
Conservation Status ◽  
Marine Species ◽  
Iucn Red List ◽  
Red List ◽  
Marine Biodiversity ◽  
Conservation Priorities ◽  
Conservation Action

Given the economic and cultural dependence on the marine environment in Oceania and a rapidly expanding human population, many marine species populations are in decline and may be vulnerable to extinction from a number of local and regional threats. IUCN Red List assessments, a widely used system for quantifying threats to species and assessing species extinction risk, have been completed for 1190 marine species in Oceania to date, including all known species of corals, mangroves, seagrasses, sea snakes, marine mammals, sea birds, sea turtles, sharks, and rays present in Oceania, plus all species in five important perciform fish groups. Many of the species in these groups are threatened by the modification or destruction of coastal habitats, overfishing from direct or indirect exploitation, pollution, and other ecological or environmental changes associated with climate change. Spatial analyses of threatened species highlight priority areas for both site- and species-specific conservation action. Although increased knowledge and use of newly available IUCN Red List assessments for marine species can greatly improve conservation priorities for marine species in Oceania, many important fish groups are still in urgent need of assessment.

scholarly journals Comparison of several non-linear-regression methods for fitting the Michaelis-Menten equation

1985 ◽  
Vol 231 (1) ◽  
pp. 171-177 ◽  
Author(s):  
L Matyska ◽  
J Kovář
Keyword(s):  
Simulated Data ◽  
Confidence Regions ◽  
Parameter Estimates ◽  
Interval Parameter ◽  
Variance Matrix ◽  
Regression Methods ◽  
Parameter Estimations ◽  
Data Points ◽  
Relative Weighting

The known jackknife methods (i.e. standard jackknife, weighted jackknife, linear jackknife and weighted linear jackknife) for the determination of the parameters (as well as of their confidence regions) were tested and compared with the simple Marquardt's technique (comprising the calculation of confidence intervals from the variance-co-variance matrix). The simulated data corresponding to the Michaelis-Menten equation with defined structure and magnitude of error of the dependent variable were used for fitting. There were no essential differences between the results of both point and interval parameter estimations by the tested methods. Marquardt's procedure yielded slightly better results than the jackknives for five scattered data points (the use of this method is advisable for routine analyses). The classical jackknife was slightly superior to the other methods for 20 data points (this method can be recommended for very precise calculations if great numbers of data are available). The weighting does not seem to be necessary in this type of equation because the parameter estimates obtained with all methods with the use of constant weights were comparable with those calculated with the weights corresponding exactly to the real error structure whereas the relative weighting led to rather worse results.

scholarly journals MGMM: An R Package for fitting Gaussian Mixture Models on Incomplete Data

2019 ◽  
Author(s):  
Zachary R. McCaw ◽  
Hanna Julienne ◽  
Hugues Aschard
Keyword(s):  
Missing Data ◽  
Mixture Models ◽  
Gaussian Mixture Models ◽  
Model Fitting ◽  
Simulated Data ◽  
R Package ◽  
Gaussian Mixture ◽  
Parameter Estimates ◽  
Cluster Assignment ◽  
Underlying Distribution

AbstractAlthough missing data are prevalent in applications, existing implementations of Gaussian mixture models (GMMs) require complete data. Standard practice is to perform complete case analysis or imputation prior to model fitting. Both approaches have serious drawbacks, potentially resulting in biased and unstable parameter estimates. Here we present MGMM, an R package for fitting GMMs in the presence of missing data. Using three case studies on real and simulated data sets, we demonstrate that, when the underlying distribution is near-to a GMM, MGMM is more effective at recovering the true cluster assignments than state of the art imputation followed by standard GMM. Moreover, MGMM provides an accurate assessment of cluster assignment uncertainty even when the generative distribution is not a GMM. This assessment may be used to identify unassignable observations. MGMM is available as an R package on CRAN: https://CRAN.R-project.org/package=MGMM.

Biodiversity Along Core–Periphery Clines

2005 ◽  
Author(s):  
Sergei Volis ◽  
Salit Kark
Keyword(s):  
Genetic Diversity ◽  
Species Diversity ◽  
Biological Diversity ◽  
Morphological Diversity ◽  
Spatial Location ◽  
Convention On Biological Diversity ◽  
Conservation Priorities ◽  
Past Century ◽  
Geographical Patterns ◽  
Local Populations

The study of biodiversity has received wide attention in recent decades. Biodiversity has been defined in various ways (Gaston and Spicer, 1998, Purvis and Hector 2000, and chapters in this volume). Discussion regarding its definitions is dynamic, with shifts between the more traditional emphasis on community structure to emphasis on the higher ecosystem level or the lower population levels (e.g., chapters in this volume, Poiani et al. 2000). One of the definitions, proposed in the United Nations Convention on Biological Diversity held in Rio de Janeiro (1992) is “the diversity within species, between species and of ecosystems.” The within-species component of diversity is further defined as “the frequency and diversity of different genes and/or genomes . . .” (IUCN 1993) as estimated by the genetic and morphological diversity within species. While research and conservation efforts in the past century have focused mainly on the community level, they have recently been extended to include the within-species (Hanski 1989) and the ecosystem levels. The component comprising within-species genetic and morphological diversity is increasingly emphasized as an important element of biodiversity (UN Convention 1992). Recent studies suggest that patterns of genetic diversity significantly influence the viability and persistence of local populations (Frankham 1996, Lacy 1997, Riddle 1996, Vrijenhoek et al. 1985). Revealing geographical patterns of genetic diversity is highly relevant to conservation biology and especially to explicit decision-making procedures allowing systematic rather than opportunistic selection of populations and areas for in situ protection (Pressey et al. 1993). Therefore, studying spatial patterns in within-species diversity may be vital in defining and prioritizing conservation efforts (Brooks et al. 1992). Local populations of a species often differ in the ecological conditions experienced by their members (Brown 1984, Gaston 1990, Lawton et al. 1994). These factors potentially affect population characteristics, structure, and within-population genetic and morphological diversity (Brussard 1984, Lawton 1995, Parsons 1991). The spatial location of a population within a species range may be related to its patterns of diversity (Lesica and Allendorf 1995). Thus, detecting within-species diversity patterns across distributional ranges is important for our understanding of ecological and evolutionary (e.g., speciation) processes (Smith et al. 1997), and for the determination of conservation priorities (Kark 1999).

scholarly journals Inferring the Demographic History of Inbred Species from Genome-Wide SNP Frequency Data

2020 ◽  
Vol 37 (7) ◽  
pp. 2124-2136
Author(s):  
Paul D Blischak ◽  
Michael S Barker ◽  
Ryan N Gutenkunst
Keyword(s):  
Puma Concolor ◽  
Demographic History ◽  
Random Mating ◽  
Simulated Data ◽  
Conservation Agriculture ◽  
Model Fit ◽  
Parameter Estimates ◽  
History Of ◽  
Demographic Inference ◽  
Inbred Populations

Abstract Demographic inference using the site frequency spectrum (SFS) is a common way to understand historical events affecting genetic variation. However, most methods for estimating demography from the SFS assume random mating within populations, precluding these types of analyses in inbred populations. To address this issue, we developed a model for the expected SFS that includes inbreeding by parameterizing individual genotypes using beta-binomial distributions. We then take the convolution of these genotype probabilities to calculate the expected frequency of biallelic variants in the population. Using simulations, we evaluated the model’s ability to coestimate demography and inbreeding using one- and two-population models across a range of inbreeding levels. We also applied our method to two empirical examples, American pumas (Puma concolor) and domesticated cabbage (Brassica oleracea var. capitata), inferring models both with and without inbreeding to compare parameter estimates and model fit. Our simulations showed that we are able to accurately coestimate demographic parameters and inbreeding even for highly inbred populations (F = 0.9). In contrast, failing to include inbreeding generally resulted in inaccurate parameter estimates in simulated data and led to poor model fit in our empirical analyses. These results show that inbreeding can have a strong effect on demographic inference, a pattern that was especially noticeable for parameters involving changes in population size. Given the importance of these estimates for informing practices in conservation, agriculture, and elsewhere, our method provides an important advancement for accurately estimating the demographic histories of these species.

scholarly journals Analysis of algebraic weighted least-squares estimators for enzyme parameters

1992 ◽  
Vol 288 (2) ◽  
pp. 533-538 ◽  
Author(s):  
M E Jones
Keyword(s):  
Least Squares ◽  
Coefficient Of Variation ◽  
Constant Coefficient ◽  
Weighted Least Squares ◽  
Simulated Data ◽  
Standard Errors ◽  
Parameter Estimates ◽  
Spreadsheet Program ◽  
Least Squares Estimators ◽  
Constant Coefficient Of Variation

An algorithm for the least-squares estimation of enzyme parameters Km and Vmax. is proposed and its performance analysed. The problem is non-linear, but the algorithm is algebraic and does not require initial parameter estimates. On a spreadsheet program such as MINITAB, it may be coded in as few as ten instructions. The algorithm derives an intermediate estimate of Km and Vmax. appropriate to data with a constant coefficient of variation and then applies a single reweighting. Its performance using simulated data with a variety of error structures is compared with that of the classical reciprocal transforms and to both appropriately and inappropriately weighted direct least-squares estimators. Three approaches to estimating the standard errors of the parameter estimates are discussed, and one suitable for spreadsheet implementation is illustrated.

scholarly journals A third of the tropical African flora is potentially threatened with extinction

2019 ◽  
Vol 5 (11) ◽  
pp. eaax9444 ◽  
Author(s):  
T. Stévart ◽  
G. Dauby ◽  
P. P. Lowry ◽  
A. Blach-Overgaard ◽  
V. Droissart ◽  
...  
Keyword(s):  
Plant Species ◽  
Extinction Risk ◽  
Vascular Plant ◽  
Terrestrial Ecosystems ◽  
Iucn Red List ◽  
Conservation Priorities ◽  
Conservation Assessment ◽  
Continental Scale ◽  
Tropical Plant ◽  
African Flora

Preserving tropical biodiversity is an urgent challenge when faced with the growing needs of countries. Despite their crucial importance for terrestrial ecosystems, most tropical plant species lack extinction risk assessments, limiting our ability to identify conservation priorities. Using a novel approach aligned with IUCN Red List criteria, we conducted a continental-scale preliminary conservation assessment of 22,036 vascular plant species in tropical Africa. Our results underline the high level of extinction risk of the tropical African flora. Thirty-three percent of the species are potentially threatened with extinction, and another third of species are likely rare, potentially becoming threatened in the near future. Four regions are highlighted with a high proportion (>40%) of potentially threatened species: Ethiopia, West Africa, central Tanzania, and southern Democratic Republic of the Congo. Our approach represents a first step toward data-driven conservation assessments applicable at continental scales providing crucial information for sustainable economic development prioritization.

Preserving the tree of life of the fish family Cyprinidae in Africa in the face of the ongoing extinction crisis

Genome ◽  
2019 ◽  
Vol 62 (3) ◽  
pp. 170-182 ◽  
Author(s):  
Mariam Adeoba ◽  
Solomon G. Tesfamichael ◽  
Kowiyou Yessoufou
Keyword(s):  
Threatened Species ◽  
Phylogenetic Diversity ◽  
Extinction Risk ◽  
Phylogenetic Signal ◽  
Distinct Species ◽  
Tree Of Life ◽  
Fish Family ◽  
The Face ◽  
Taxonomic Confusion ◽  
Coi Sequences

Our understanding of how the phylogenetic tree of fishes might be affected by the ongoing extinction risk is poor. This is due to the unavailability of comprehensive DNA data, especially for many African lineages. In addition, the ongoing taxonomic confusion within some lineages, e.g., Cyprinidae, makes it difficult to contribute to the debate on how the fish tree of life might be shaped by extinction. Here, we combine COI sequences and taxonomic information to assemble a fully sampled phylogeny of the African Cyprinidae and investigate whether we might lose more phylogenetic diversity (PD) than expected if currently threatened species go extinct. We found evidence for phylogenetic signal in extinction risk, suggesting that some lineages might be at higher risk than others. Based on simulated extinctions, we found that the loss of all threatened species, which approximates 37% of total PD, would lead to a greater loss of PD than expected, although highly evolutionarily distinct species are not particularly at risk. Pending the reconstruction of an improved multi-gene phylogeny, our results suggest that prioritizing high-EDGE species (evolutionary distinct and globally endangered species) in conservation programmes, particularly in some geographic regions, would contribute significantly to safeguarding the tree of life of the African Cyprinidae.

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