Bioinformatics, museums, and society : integrating biological data for knowledge-based decisions

Baker, Robert J.; Phillips, Carla Rahn; Bradley, Robert D.; Burns, John; Cooke, Daniel E.; Edson, Gary; Haragan, Donald R.; Jones, Clyde; Monk, Ray; Montford, John T; Schmidly, David; Parker, Nick C

doi:10.5962/bhl.title.143164

Cited by 11 publications

(7 citation statements)

References 2 publications

(2 reference statements)

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“…The great potential utility of data from natural history museums and herbaria, as well as the difficulty of making such data readily available, have been clear for many years (Anderson, 1963;Suarez and Tsutsui, 2004). Recent advances in distributed databases and biodiversity informatics facilitate information retrieval (Baker et al, 1998;Bisby, 2000;Pérez-Hernández et al, 1997;Soberón, 1999;Soberón and Peterson, 2004;Stein and Wieczorek, 2004). Furthermore, fine-resolution environmental data are becoming increasingly available.…”

Section: Future Workmentioning

confidence: 99%

Maximum entropy modeling of species geographic distributions

Phillips

Anderson

Schapire

2006

Ecological Modelling

13,770

13,748

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The availability of detailed environmental data, together with inexpensive and powerful computers, has fueled a rapid increase in predictive modeling of species environmental requirements and geographic distributions. For some species, detailed presence/absence occurrence data are available, allowing the use of a variety of standard statistical techniques. However, absence data are not available for most species. In this paper, we introduce the use of the maximum entropy method (Maxent) for modeling species geographic distributions with presence-only data. Maxent is a general-purpose machine learning method with a simple and precise mathematical formulation, and it has a number of aspects that make it well-suited for species distribution modeling. In order to investigate the efficacy of the method, here we perform a continental-scale case study using two Neotropical mammals: a lowland species of sloth, Bradypus variegatus, and a small montane murid rodent, Microryzomys minutus. We compared Maxent predictions with those of a commonly used presence-only modeling method, the Genetic Algorithm for Rule-Set Prediction (GARP). We made predictions on 10 random subsets of the occurrence records for both species, and then used the remaining localities for testing. Both algorithms provided reasonable estimates of the species' range, far superior to the shaded outline maps available in field guides. All models were significantly better than random in both binomial tests of omission and receiver operating characteristic (ROC) analyses. The area under the ROC curve (AUC) was almost always higher for Maxent, indicating better discrimination of suitable versus unsuitable areas for the species. The Maxent modeling approach can be used in its present form for many applications with presence-only datasets, and merits further research and development.

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Section: Future Workmentioning

confidence: 99%

Maximum entropy modeling of species geographic distributions

Phillips

Anderson

Schapire

2006

Ecological Modelling

13,770

13,748

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“…This data set is a product of methodological advances associated with automated DNA sequencing, polymerase chain reaction, universal primers, GenBank, human genome project, biological informatics, software to analyze such data (reviewed 3 February 2006 at http://evolution.genetics.washington.edu/phylip/software.html), and genetic resource collections associated with voucher specimens. DNA sequencing is available at nearly all research and educational institutions and with GenBank and biological informatics (Baker et al 1998), studies of local populations or favorite species are possible for many researchers even at smaller institutions with limited budgets and no museum collections.…”

Section: Cryptic Species Of Mammals Identified By Dna Sequencesmentioning

confidence: 99%

Speciation in Mammals and the Genetic Species Concept

Baker

Bradley

2006

Journal of Mammalogy

Self Cite

637

423

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We define a genetic species as a group of genetically compatible interbreeding natural populations that is genetically isolated from other such groups. This focus on genetic isolation rather than reproductive isolation distinguishes the Genetic Species Concept from the Biological Species Concept. Recognition of species that are genetically isolated (but not reproductively isolated) results in an enhanced understanding of biodiversity and the nature of speciation as well as speciation-based issues and evolution of mammals. We review criteria and methods for recognizing species of mammals and explore a theoretical scenario, the Bateson-Dobzhansky-Muller (BDM) model, for understanding and predicting genetic diversity and speciation in mammals. If the BDM model is operating in mammals, then genetically defined phylogroups would be predicted to occur within species defined by morphology, and phylogroups experiencing stabilizing selection will evolve genetic isolation without concomitant morphological diversification. Such species will be undetectable using classical skin and skull morphology (Morphological Species Concept). Using cytochrome-b data from sister species of mammals recognized by classical morphological studies, we estimated the number of phylogroups that exist within mammalian species and hypothesize that there will be >2,000 currently unrecognized species of mammals. Such an underestimation significantly affects conclusions on the nature of speciation in mammals, barriers associated with evolution of genetic isolation, estimates of biodiversity, design of conservation initiatives, zoonoses, and so on. A paradigm shift relative to this and other speciation-based issues will be needed. Data that will be effective in detecting these "morphologically cryptic genetic species" are genetic, especially DNA-sequence data. Application of the Genetic Species Concept uses genetic data from mitochondrial and nuclear genomes to identify species and species boundaries, the extent to which the integrity of the gene pool is protected, nature of hybridization (if present), and introgression. Genetic data are unique in understanding species because the use of genetic data 1) can quantify genetic divergence from different aspects of the genome (mitochondrial and nuclear genes, protein coding genes, regulatory genes, mobile DNA, microsatellites, chromosomal rearrangements, heterochromatin, etc.); 2) can provide divergence values that increase with time, providing an estimate of time since divergence; 3) can provide a population genetics perspective; 4) is less subject to convergence and parallelism relative to other sets of characters; 5) can identify monophyly, sister taxa, and presence or absence of introgression; and 6) can accurately identify hybrid individuals (kinship and source of hybrid individuals, F(1)s, backcrosses, direction of hybridization, and in concert with other data identify which hybrids are sterile or fertile). The proposed definition of the Genetic Species Concept is more compatible with a description o...

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“…Las muestras obtenidas durante las expediciones científicas son registros históricos que documentan la presencia de especies particulares en un tiempo y un espacio determinados (Proctor, 2004). A medida que la tecnología avanza es posible acceder a nuevos tipos de datos sobre las especies, el ambiente y el ecosistema en un lugar y tiempo perdidos en la historia (Baker et al, 1998;Beaman et al, 2004;Murphey et al, 2004;Crisci & Katinas, 2017).…”

Section: Nuevas Tecnologías Y Su Aporte a La Biodiversidad Y Revaloriunclassified

Tras los pasos de Frenguelli en los Esteros del Iberá: el rol de las nuevas tecnologías en la revalorización de las colecciones biológicas históricas

Lamaro¹,

Sala

Kociolek

et al. 2021

RMLP

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Joaquín Frenguelli formó parte en 1923 de una expedición a la Región del Iberá, organizada en el marco de un proyecto nacional, conocido como Proyecto Mollard. Los pormenores del viaje fueron documentados en publicaciones, aportando descripciones técnicas y paisajísticas precisas de las localidades, especialmente de aquellas donde se recolectaron muestras. Una colaboración entre el Museo de La Plata y la Universidad de Colorado (EE.UU.), vinculada a estudiar la flora de diatomeas de agua dulce de Argentina, permitió que en mayo de 2019 se organizara una campaña a esta región, casi 100 años después de la expedición de Frenguelli, posibilitando así la experiencia única de repetir su itinerario. El objetivo principal de este trabajo fue ubicar las localidades originales visitadas por Frenguelli mediante el empleo de tecnologías modernas, tales como imágenes satelitales y sistemas de información geográfica, a fin de colectar en ellas nuevos materiales que servirán para evaluar los cambios ocurridos en los 97 años que median entre ambas expediciones. Para ello, se digitalizó una carta esquemática publicada en 1924 sobre la base de las descripciones en la bibliografía, se georreferenciaron de manera aproximada las localidades visitadas por Frenguelli, ajustando su ubicación a campo mediante la interpretación de las descripciones de los parajes dadas por el autor y, además, se tomaron muestras en los mismos sitios, con registro de sus coordenadas geográficas con GPS. Finalmente, se obtuvieron y procesaron imágenes satelitales cercanas a la fecha de la campaña, a fin de analizar la cobertura vegetal y uso de la tierra actual en toda el área de estudio. El análisis comparativo de todos estos materiales permitió establecer que, si bien grandes áreas se conservan en estado natural, en otras áreas de la región hubo grandes cambios vinculados con la expansión de las áreas urbanas, la disponibilidad de caminos y rutas y, principalmente, cambios significativos en el uso del suelo relacionados mayormente con la forestación. Los resultados obtenidos constituyen, en su conjunto, información de base, muy escasa hasta el presente, para llevar a cabo futuros estudios ambientales en la región.

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Bioinformatics, museums, and society : integrating biological data for knowledge-based decisions

Cited by 11 publications

References 2 publications

Maximum entropy modeling of species geographic distributions

Maximum entropy modeling of species geographic distributions

Speciation in Mammals and the Genetic Species Concept

Tras los pasos de Frenguelli en los Esteros del Iberá: el rol de las nuevas tecnologías en la revalorización de las colecciones biológicas históricas

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