ORCID Profile
0000-0003-0846-2819
Current Organisation
Florida International University
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Publisher: Springer Science and Business Media LLC
Date: 16-12-2022
DOI: 10.1038/S41559-021-01604-Y
Abstract: Language ersity is under threat. While each language is subject to specific social, demographic and political pressures, there may also be common threatening processes. We use an analysis of 6,511 spoken languages with 51 predictor variables spanning aspects of population, documentation, legal recognition, education policy, socioeconomic indicators and environmental features to show that, counter to common perception, contact with other languages per se is not a driver of language loss. However, greater road density, which may encourage population movement, is associated with increased endangerment. Higher average years of schooling is also associated with greater endangerment, evidence that formal education can contribute to loss of language ersity. Without intervention, language loss could triple within 40 years, with at least one language lost per month. To avoid the loss of over 1,500 languages by the end of the century, urgent investment is needed in language documentation, bilingual education programmes and other community-based programmes.
Publisher: Cold Spring Harbor Laboratory
Date: 11-01-2018
DOI: 10.1101/246611
Abstract: A major goal in microbial ecology is to understand the factors that structure bacterial communities across space and time. For microbes that have symbiotic relationships with plants, an important factor that may influence their communities is host size or age, yet this has received little attention. Using tree diameter size as a proxy for age, we quantified the ersity of rhizobia that associate with an endemic legume, Acacia acuminata , of variable size across a climate gradient in southwest Australia. We examined the 16S rRNA ersity (V1-V3 hypervariable region) of rhizobia at the taxonomic level and at higher sequence level ersity within taxonomic groups. We identified 3 major taxonomic clades that associated with Acacia acuminata: Bradyrhizobiaceae, Rhizobiaceae, and Burkholderiaceae. Within these groups, we found extensive genetic variability, especially within Bradyrhizobiaceae. Using binomial multivariate statistical models that controlled for other factors that affect plant size and rhizobia community structure (climate and local soil characteristics), we determined that soil s led at the base of larger Acacia trees was much more likely to contain a greater number of taxonomic clades and cryptic genetic variants within the Rhizobiaceae clade. Despite strong influences of climate and highly heterogeneous soil conditions on rhizobial ersity, our results show that host tree size is a prominent factor in structuring nitrogen-fixing symbionts ersity across a large landscape. The identification of a positive relationship between plant host size and microbial ersity raise interesting questions about the role of plant host size in driving ecological processes that govern microbial community assembly. Specifically, our results suggest that hosts may modify the habitat of their surrounding soil to enhance growth (niche construction hypothesis) or that symbiotic microbes have large differences in dispersal capability. Our results also suggest that host plants may be analogous to ‘islands’, where larger legume hosts may accumulate ersity over time, through migration opportunities or in situ ersification. From a practical perspective, including plant size as an additional variable may assist s ling and analyses designs of future soil microbial studies.
Publisher: Australian Housing and Urban Research Institute (AHURI)
Date: 03-2020
Publisher: Wiley
Date: 12-08-2008
Publisher: The Royal Society
Date: 06-05-2020
Abstract: Comparative models used to predict species threat status can help identify the diagnostic features of species at risk. Such models often combine variables measured at the species level with spatial variables, causing multiple statistical challenges, including phylogenetic and spatial non-independence. We present a novel Bayesian approach for modelling threat status that simultaneously deals with both forms of non-independence and estimates their relative contribution, and we apply the approach to modelling threat status in the Australian plant genus Hakea. We find that after phylogenetic and spatial effects are accounted for, species with greater evolutionary distinctiveness and a shorter annual flowering period are more likely to be threatened. The model allows us to combine information on evolutionary history, species biology and spatial data, calculate latent extinction risk (potential for non-threatened species to become threatened), estimate the most important drivers of risk for in idual species and map spatial patterns in the effects of different predictors on extinction risk. This could be of value for proactive conservation decision-making based on the early identification of species and regions of potential conservation concern.
Publisher: Wiley
Date: 30-10-2018
Publisher: Oxford University Press (OUP)
Date: 06-2021
DOI: 10.1002/EVL3.225
Abstract: Processes driving the ergence of floral traits may be integral to the extraordinary richness of flowering plants and the assembly of erse plant communities. Several models of pollinator-mediated floral evolution have been proposed floral ergence may (i) be directly involved in driving speciation or may occur after speciation driven by (ii) drift or local adaptation in allopatry or (iii) negative interactions between species in sympatry. Here, we generate predictions for patterns of trait ergence and community assembly expected under these three models, and test these predictions in Hakea (Proteaceae), a erse genus in the Southwest Australian bio ersity hotspot. We quantified functional richness for two key floral traits (pistil length and flower color), as well as phylogenetic distances between species, across ecological communities, and compared these to patterns generated from null models of community assembly. We also estimated the statistical relationship between rates of trait evolution and lineage ersification across the phylogeny. Patterns of community assembly suggest that flower color, but not floral phenology or morphology, or phylogenetic relatedness, is more ergent in communities than expected. Rates of lineage ersification and flower color evolution were negatively correlated across the phylogeny and rates of flower colour evolution were positively related to branching times. These results support a role for ersity-dependent species interactions driving floral ergence during the Hakea radiation, contributing to the development of the extraordinary species richness of southwest Australia.
Publisher: Cold Spring Harbor Laboratory
Date: 18-02-2020
DOI: 10.1101/2020.02.17.952317
Abstract: Model-based approaches are increasingly popular in ecological studies. A good ex le of this trend is the use of joint species distribution models to ask questions about ecological communities. However, most current applications of model-based methods do not include phylogenies despite the well-known importance of phylogenetic relationships in shaping species distributions and community composition. In part, this is due to lack of accessible tools allowing ecologists to fit phylogenetic species distribution models easily. To fill this gap, the R package phyr (pronounced fire) implements a suite of metrics, comparative methods and mixed models that use phylogenies to understand and predict community composition and other ecological and evolutionary phenomena. The phyr workhorse functions are implemented in C++ making all calculations and model estimations fast. phyr can fit a variety of models such as phylogenetic joint-species distribution models, spatiotemporal-phylogenetic autocorrelation models, and phylogenetic trait-based bipartite network models. phyr also estimates phylogenetically independent trait correlations with measurement error to test for adaptive syndromes and performs fast calculations of common alpha and beta phylogenetic ersity metrics. All phyr methods are united under Brownian motion or Ornstein-Uhlenbeck models of evolution and phylogenetic terms are modelled as phylogenetic covariance matrices. The functions and model formula syntax we propose in phyr serves as a simple and unified framework that ignites the use of phylogenies to address a variety of ecological questions.
Publisher: Elsevier BV
Date: 2022
DOI: 10.2139/SSRN.4274410
Publisher: Wiley
Date: 23-08-2012
DOI: 10.1111/J.1461-0248.2012.01854.X
Abstract: Large-scale habitat destruction and climate change result in the non-random loss of evolutionary lineages, reducing the amount of evolutionary history represented in ecological communities. Yet, we have limited understanding of the consequences of evolutionary history on the structure of food webs and the services provided by biological communities. Drawing on 11 years of data from a long-term plant ersity experiment, we show that evolutionary history of plant communities - measured as phylogenetic ersity - strongly predicts ersity and abundance of herbivorous and predatory arthropods. Effects of plant species richness on arthropods become stronger when phylogenetic ersity is high. Plant phylogenetic ersity explains predator and parasitoid richness as strongly as it does herbivore richness. Our findings indicate that accounting for evolutionary relationships is critical to understanding the severity of species loss for food webs and ecosystems, and for developing conservation and restoration policies.
Publisher: Public Library of Science (PLoS)
Date: 18-09-2009
Publisher: PeerJ
Date: 25-06-2013
DOI: 10.7717/PEERJ.93
Publisher: Springer Science and Business Media LLC
Date: 03-02-2022
Publisher: Authorea, Inc.
Date: 03-07-2023
DOI: 10.22541/AU.168269359.92620442/V2
Abstract: Data on the three dimensional shape of organismal morphology is becoming increasingly availability, and forms part of a new revolution in high-throughput phenomics that promises to help understand ecological and evolutionary processes that influence phenotypes at unprecedented scales. However, in order to meet the potential of this revolution we need new data analysis tools to deal with the complexity and heterogeneity of large-scale phenotypic data such as 3D shapes. In this study we explore the potential of generative Artificial Intelligence to help organise and extract meaning from complex 3D data. Specifically, we train a deep representational learning method known as DeepSDF on a dataset of 3D scans of the bills of 2,020 bird species. The model is designed to learn a continuous vector representation of 3D shapes, along with a ‘decoder’ function, that allows the transformation from this vector space to the original 3d morphological space. We find that approach successfully learns coherent representations: particular directions in latent space are associated with discernible morphological meaning (such as elongation, flattening, etc.). More importantly, learned latent vectors have ecological meaning as shown by their ability to predict the trophic niche of the bird each bill belongs to with a high degree of accuracy. Unlike existing 3D morphometric techniques, this method has very little requirements for human supervised tasks such as landmark placement, increasing it accessibility to labs with fewer labour resources. It has fewer strong assumptions than alternative dimension reduction techniques such as PCA. The computational requirements for training the model, while substantial, is still within the reasonable reach of most researchers, with a ~2000 shape model taking just over 2 days to train on only a single current generation consumer-level GPU. Once trained, 3D morphology predictions can be made from latent vectors very computationally cheaply.
Publisher: Cold Spring Harbor Laboratory
Date: 13-12-2018
DOI: 10.1101/496547
Abstract: Comparative models used to predict species threat status often combine variables measured at the species level with spatial variables, causing multiple statistical challenges, including phylogenetic and spatial non-independence. We present a novel bayesian approach for modelling threat status that simultaneously deals with both forms of non-independence and estimates their relative contribution, and we apply the approach to modelling threat status in the Australian plant genus Hakea . We find that after phylogenetic and spatial effects are accounted for, species with greater evolutionary distinctiveness and a shorter annual flowering period are more likely to be threatened. The model allows us to combine information on evolutionary history, species biology, and spatial data, to calculate latent extinction risk (potential for non-threatened species to become threatened), and estimate the most important drivers of risk for in idual species. This could be of value for proactive conservation decision-making that targets species of concern before they become threatened.
Publisher: Oxford University Press (OUP)
Date: 14-12-2022
DOI: 10.1093/AOB/MCAC151
Abstract: While genome size limits the minimum sizes and maximum numbers of cells that can be packed into a given leaf volume, mature cell sizes can be substantially larger than their meristematic precursors and vary in response to abiotic conditions. Mangroves are iconic ex les of how abiotic conditions can influence the evolution of plant phenotypes. Here, we examined the coordination between genome size, leaf cell sizes, cell packing densities and leaf size in 13 mangrove species across four sites in China. Four of these species occurred at more than one site, allowing us to test the effect of climate on leaf anatomy. We found that genome sizes of mangroves were very small compared to other angiosperms, but, like other angiosperms, mangrove cells were always larger than the minimum size defined by genome size. Increasing mean annual temperature of a growth site led to higher packing densities of veins (Dv) and stomata (Ds) and smaller epidermal cells but had no effect on stomatal size. In contrast to other angiosperms, mangroves exhibited (1) a negative relationship between guard cell size and genome size (2) epidermal cells that were smaller than stomata and (3) coordination between Dv and Ds that was not mediated by epidermal cell size. Furthermore, mangrove epidermal cell sizes and packing densities covaried with leaf size. While mangroves exhibited coordination between veins and stomata and attained a maximum theoretical stomatal conductance similar to that of other angiosperms, the tissue-level tradeoffs underlying these similar relationships across species and environments were markedly different, perhaps indicative of the unique structural and physiological adaptations of mangroves to their stressful environments.
Publisher: Informa UK Limited
Date: 14-11-2015
Publisher: Wiley
Date: 03-10-2022
DOI: 10.1111/ACV.12823
Abstract: Species vary in their vulnerability to extinction according to their biology, ecology, environmental factors and threats to which they are exposed. Diet is an important ecological trait that affects many aspects of a species' biology, including its vulnerability to extinction. Despite the importance of diet as a species' trait, its influence on extinction risk has only been studied in a coarse way, in part due to a lack of detailed diet data covering a large breadth of species or geographic areas. We examined the association between diet and extinction risk in primates, using a high‐resolution dataset covering all major primate lineages and habitats on a global scale. The resolution of the dataset allowed us to calculate multiple biologically informative metrics for diet composition and ersity, allowing us to tease apart what aspects of diet were most important for predicting the risk of extinction, whilst accounting for phylogeny, body mass and geographic range size. Our results showed that both diet disparity and diet ersity predict primate extinction risk, showing that primates that are able to consume more types of items, and items that are more disparate from one another, are less prone to extinction. Furthermore, we found that although closely related species tend to have similar dietary ersity and disparity, these metrics vary widely amongst primate families. Primates with a high diet ersity and disparity may be able to cope better with fluctuations in food availability than species with homogeneous diet items, through a portfolio effect. Understanding the degree of dietary specialization of the species may help guide new studies relating to extinction risk and threats and be useful in future species assessments.
Publisher: MDPI AG
Date: 07-09-2020
Abstract: Persons with a disability are at a far higher risk of homelessness than those without. The economic, social and health challenges faced by disabled people are addressed, in Australia, by the recently implemented National Disability Insurance Scheme (NDIS). Using nationally representative, longitudinal household panel data, we construct the Index of Relative Homelessness Risk (IRHR) to track how the risk of homelessness for disabled persons has changed since the introduction of the NDIS. We find that, overall, fewer persons with a disability face moderate risk of homelessness but that many more face high risk. We conclude that the NDIS has not effectively protected disabled people from the risk of homelessness. We reflect on the implications of these findings for policy interventions.
Publisher: Springer Science and Business Media LLC
Date: 04-02-2021
Publisher: Wiley
Date: 21-09-2020
Publisher: American Association for the Advancement of Science (AAAS)
Date: 21-04-2023
Abstract: While global patterns of human genetic ersity are increasingly well characterized, the ersity of human languages remains less systematically described. Here, we outline the Grambank database. With over 400,000 data points and 2400 languages, Grambank is the largest comparative grammatical database available. The comprehensiveness of Grambank allows us to quantify the relative effects of genealogical inheritance and geographic proximity on the structural ersity of the world’s languages, evaluate constraints on linguistic ersity, and identify the world’s most unusual languages. An analysis of the consequences of language loss reveals that the reduction in ersity will be strikingly uneven across the major linguistic regions of the world. Without sustained efforts to document and revitalize endangered languages, our linguistic window into human history, cognition, and culture will be seriously fragmented.
Publisher: Wiley
Date: 08-2012
DOI: 10.1890/11-0426.1
Publisher: MDPI AG
Date: 06-11-2019
Abstract: This paper reports on the first phase of an ambitious program of research that seeks to both understand the risk of homelessness amongst persons with a disability in Australia and shed light on the impact of a significant policy reform—the introduction of the National Disability Insurance Scheme (NDIS)—in changing the level of homelessness risk. This first paper, reports on the level of homelessness risk for persons with a disability prior to the introduction of the NDIS, with a subsequent paper providing updated data and analysis for the period post the implementation of the NDIS. In one sense, this paper provides the ‘base’ condition prior to the introduction of the NDIS but also serves a far broader role in advancing our understanding of how disability and chronic ill-health affects the risk of homelessness. Our research finds that in the period prior to the introduction of the NDIS, a large proportion of people with disabilities were at risk of homelessness, but those whose disabilities affected their schooling or employment were at the greatest risk.
Publisher: Wiley
Date: 23-10-2020
DOI: 10.1111/DDI.13179
Publisher: University of Chicago Press
Date: 10-2008
DOI: 10.1086/590963
Abstract: Much previous ecological and evolutionary theory about exploitative competition for a continuous spectrum of resources has used the Lotka-Volterra model with competition coefficients given by a Gaussian function of niche separation. Using explicit consumer-resource models, we show that the Lotka-Volterra model and the assumption of a Gaussian competition-similarity relationship both fail to reflect the impact of strong resource depletion, which typically reduces the influence of the most heavily used resources on the competitive interaction. Taking proper account of resource depletion reveals that strong exploitative competition between efficient consumers is usually a highly nonlinear interaction, implying that a single measure is no longer sufficient to characterize the process. The nonlinearity usually entails weak coupling of competing species when their abundances are high and equal. Rare invaders are likely to have effects on abundant residents much larger than those of the resident on the invader. Asymmetrical utilization curves often produce asymmetrical competition coefficients. Competition coefficients are typically non-Gaussian and are often nonmonotonic functions of niche separation. Utilization curve shape and resource growth functions can have major effects on competition-similarity relationships. A variety of previous theoretical findings need to be reassessed in light of these results.
Publisher: Cold Spring Harbor Laboratory
Date: 02-2018
DOI: 10.1101/258038
Abstract: Species distribution models (SDMs) are valuable tools to estimate species’ distributions, but are vulnerable to biases in the probability of a species being observed. One such bias is habitat loss, which has affected a substantial and increasing proportion of the Earth. In regions of severe habitat loss, data on a species’ occurrence may represent a small, non-random subset of sites it once occupied. This could cause distorted reconstructions of species distributions, and misleading inferences of evolutionary and ecological processes. We present a statistical approach for quantifying the influence on SDMs of habitat loss, and generating distribution predictions that are robust to these biases. We explored some of the effects of accounting for habitat loss on inferences from common downstream biogeographic and ecological analysis methods. We used herbarium record data to model the distribution of 325 plant species in the genera Banksia and Hakea across Australia, using point process models. We accounted for biases in the models by including a proxy variable representing habitat loss, and compared the fit of models without this variable to those with it. We explored the influence of habitat loss by mapping bio ersity patterns predicted with and without accounting for it. Generally, accounting for habitat loss in SDMs led to increases in the mean area of modelled species distributions of ~10% for Banksia and ~12% for Hakea across Australia (in some cases, up to several 100,000 km 2 increases in predicted range), with somewhat greater average increases (11% and 15%) for species in the southwest Australian bio ersity hotspot. Accounting for habitat loss leads to an increase in predicted species richness (Alpha and Gamma ersity), but a decrease in compositional turnover (Beta ersity), across most of Australia. Accounting for habitat loss in SDMs had minimal influence on a downstream macroevolutionary analysis (Age-Range Correlation) that utilizes species distributions, seemingly because exposure to habitat loss did not show a phylogenetic pattern in this taxonomic group. The influence of habitat loss on species distributions estimated with SDM is likely to be context-dependent and difficult to generalize, but will tend to cause underestimates of range sizes. This may have consequences for mapping spatial patterns of ersity and for some downstream analyses of biogeographic, evolutionary, or ecological processes, based on species distributions, as well as conservation measures that rely on accurate species mapping.
Publisher: Wiley
Date: 26-11-2019
DOI: 10.1111/JBI.13477
Publisher: Elsevier BV
Date: 05-2018
Publisher: SAGE Publications
Date: 26-05-2021
Abstract: The public areas of the hospital built environment have hardly been investigated for their age-friendliness. This exploratory, multidisciplinary pilot study investigates the relationship between the physical environment and design of hospital spaces and older people’s outpatient experience. Sixteen participants were recruited from a geriatric Outpatient Clinic at a metropolitan public hospital in Australia. Participants were engaged in a concurrent mixed-method approach, comprising a comprehensive geriatric survey, walking observation, semi-structured interview and an independent architectural audit. Several elements arising from the hospital environment were identified as facilitators and barriers for its utilization and intrinsically related to participants’ physical capacity. Age-friendly hospital design needs to consider strategies to remove barriers for older adults of different capacities, thus promoting healthy aging.
Publisher: Cold Spring Harbor Laboratory
Date: 13-06-2023
DOI: 10.1101/2023.06.12.544623
Abstract: The 19 standard bioclimatic variables available from the Worldclim dataset are some of the most used data in ecology and organismal biology. It is well know that many of the variables are correlated with each other, suggesting there is less than 19 independent dimensions of information in them. But how much information is there? Here I explore the 19 Worldclim bioclimatic variables from the perspective of the manifold hypothesis: that many high dimensional datasets are actually confined to a lower dimensional manifold embedded in an ambient space. Using a state of the art generative probabilistic model (variational autoencoder) to model the data on a non-linear manifold reveals that only 5 uncorrelated dimensions are adequate to capture the full range of variation in the bioclimatic variables. I show that these 5 variables have meaningful structure and are sufficient to produce species distribution models (SDMs) nearly as good and in some ways better than SDMs using the original 19 bioclimatic variables. I have made the 5 synthetic variables available as a raster dataset at 2.5 minute resolution in an R package that also includes functions to convert back and forth between the 5 variables and the original 19 ( dinnager/biocman ).
Publisher: Springer Science and Business Media LLC
Date: 29-06-2016
DOI: 10.1038/NATURE18315
Abstract: Interdisciplinary research is widely considered a hothouse for innovation, and the only plausible approach to complex problems such as climate change. One barrier to interdisciplinary research is the widespread perception that interdisciplinary projects are less likely to be funded than those with a narrower focus. However, this commonly held belief has been difficult to evaluate objectively, partly because of lack of a comparable, quantitative measure of degree of interdisciplinarity that can be applied to funding application data. Here we compare the degree to which research proposals span disparate fields by using a bio ersity metric that captures the relative representation of different fields (balance) and their degree of difference (disparity). The Australian Research Council's Discovery Programme provides an ideal test case, because a single annual nationwide competitive grants scheme covers fundamental research in all disciplines, including arts, humanities and sciences. Using data on all 18,476 proposals submitted to the scheme over 5 consecutive years, including successful and unsuccessful applications, we show that the greater the degree of interdisciplinarity, the lower the probability of being funded. The negative impact of interdisciplinarity is significant even when number of collaborators, primary research field and type of institution are taken into account. This is the first broad-scale quantitative assessment of success rates of interdisciplinary research proposals. The interdisciplinary distance metric allows efficient evaluation of trends in research funding, and could be used to identify proposals that require assessment strategies appropriate to interdisciplinary research.
Publisher: Australian Housing and Urban Research Institute (AHURI)
Date: 15-10-2020
Publisher: Cold Spring Harbor Laboratory
Date: 14-09-2022
DOI: 10.1101/2022.09.12.507581
Abstract: While genome size limits the minimum sizes and maximum numbers of cells that can be packed into a given leaf volume, mature cell sizes can be substantially larger than their meristematic precursors and vary in response to abiotic conditions. Mangroves are iconic ex les of how abiotic conditions can influence the evolution of plant phenotypes. Here, we examined the coordination between genome size, leaf cell sizes, and cell packing densities, and leaf size in 13 mangrove species across four sites. Four of these species occurred at more than one site, allowing us to test the effect of climate on leaf anatomy. We found that genome sizes of mangroves were very small compared to other angiosperms, and, like other angiosperms, mangrove cells were always larger than the minimum size defined by genome size. Increasing mean annual temperature of a growth site led to higher packing densities of veins ( D v ) and stomata ( D s ) and smaller epidermal cells but had no effect on stomatal size. Contrary to other angiosperms, mangroves exhibited (1) a negative relationship between guard cell size and genome size (2) epidermal cells that were smaller than stomata, and (3) coordination between D v and D s that was not mediated by epidermal cell size. Furthermore, mangrove epidermal cell sizes and packing densities covaried with leaf size. While mangroves exhibited coordination between veins and stomata and attained a maximum theoretical stomatal conductance similar to other angiosperms, the tissue-level tradeoffs underlying these similar relationships across species and environments was markedly different, perhaps indicative of the unique structural and physiological adaptations of mangroves to their stressful environments.
Publisher: Wiley
Date: 12-2017
DOI: 10.1002/ECY.2045
Abstract: Ecosystem function is the outcome of species interactions, traits, and niche overlap - all of which are influenced by evolution. However, it is not well understood how the tempo and mode of niche evolution can influence ecosystem function. In evolutionary models where either species differences accumulate through random drift in a single trait or species differences accumulate through ergent selection among close relatives, we should expect that ecosystem function is strongly related to ersity. However, when strong selection causes species to converge on specific niches or when novel traits that directly affect function evolve in some clades but not others, the relationship between ersity and ecosystem function might not be very strong. We test these ideas using a field experiment that established plant mixtures with differing phylogenetic ersities and we measured ten different community functions. We show that some functions were strongly predicted by species richness and mean pairwise phylogenetic distance (MPD, a measure of phylogenetic ersity), including biomass production and the reduction of herbivore and pathogen damage in polyculture, while other functions had weaker (litter production and structural complexity) or nonsignificant relationships (e.g., flower production and arthropod abundance) with MPD and richness. However, these ergent results can be explained by different models of niche evolution. These results show that ersity-ecosystem function relationships are the product of evolution, but that the nature of how evolution influences ecosystem function is complex.
Publisher: Wiley
Date: 19-09-2019
DOI: 10.1111/ECOG.03900
Publisher: Springer Science and Business Media LLC
Date: 07-04-2017
DOI: 10.1038/NCOMMS14790
Abstract: Microbial symbiosis is integral to plant growth and reproduction, but its contribution to global patterns of plant distribution is unknown. Legumes ( Fabaceae ) are a erse and widely distributed plant family largely dependent on symbiosis with nitrogen-fixing rhizobia, which are acquired from soil after germination. This dependency is predicted to limit establishment in new geographic areas, owing to a disruption of compatible host-symbiont associations. Here we compare non-native establishment patterns of symbiotic and non-symbiotic legumes across over 3,500 species, covering multiple independent gains and losses of rhizobial symbiosis. We find that symbiotic legume species have spread to fewer non-native regions compared to non-symbiotic legumes, providing strong support for the hypothesis that lack of suitable symbionts or environmental conditions required for effective nitrogen-fixation are driving these global introduction patterns. These results highlight the importance of mutualisms in predicting non-native species establishment and the potential impacts of microbial biogeography on global plant distributions.
Publisher: Elsevier BV
Date: 04-2023
Publisher: Wiley
Date: 19-01-2021
DOI: 10.1111/ECOG.05485
Abstract: The ENMTools software package was introduced in 2008 as a platform for making measurements on environmental niche models (ENMs, frequently referred to as species distribution models or SDMs), and for using those measurements in the context of newly developed Monte Carlo tests to evaluate hypotheses regarding niche evolution. Additional functionality was later added for model selection and simulation from ENMs, and the software package has been quite widely used. ENMTools was initially implemented as a Perl script, which was also compiled into an executable file for various platforms. However, the package had a number of significant limitations it was only designed to fit models using Maxent, it relied on a specific Perl distribution to function, and its internal structure made it difficult to maintain and expand. Subsequently, the R programming language became the platform of choice for most ENM studies, making ENMTools less usable for many practitioners. Here we introduce a new R version of ENMTools that implements much of the functionality of its predecessor as well as numerous additions that simplify the construction, comparison and evaluation of niche models. These additions include new metrics for model fit, methods of measuring ENM overlap, and methods for testing evolutionary hypotheses. The new version of ENMTools is also designed to work within the expanding universe of R tools for ecological biogeography, and as such includes greatly simplified interfaces for analyses from several other R packages.
Publisher: Cold Spring Harbor Laboratory
Date: 06-08-2021
DOI: 10.1101/2021.08.05.455258
Abstract: Software for realistically simulating complex population genomic processes is revolutionizing our understanding of evolutionary processes, and providing novel opportunities for integrating empirical data with simulations. However, the integration between simulation software and software designed for working with empirical data is currently not well developed. Here we present slimr, an R package designed to create a seamless link between standalone software SLiM 3.0, one of the most powerful population genomic simulation frameworks, and the R development environment, with its powerful data manipulation and analysis tools. We show how slimr facilitates smooth integration between genetic data, ecological data and simulation in a single environment. The package enables pipelines that begin with data reading, cleaning, and manipulation, proceed to constructing empirically-based parameters and initial conditions for simulations, then to running numerical simulations, and finally to retrieving simulation results in a format suitable for comparisons with empirical data – aided by advanced analysis and visualization tools provided by R. We demonstrate the use of slimr with an ex le from our own work on the landscape population genomics of desert mammals, highlighting the advantage of having a single integrated tool for both data analysis and simulation. slimr makes the powerful simulation ability of SliM 3.0 directly accessible to R users, allowing integrated simulation projects that incorporate empirical data without the need to switch between software environments. This should provide more opportunities for evolutionary biologists and ecologists to use realistic simulations to better understand the interplay between ecological and evolutionary processes.
No related grants have been discovered for Russell Dinnage.