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Michaletz S.T.,University of Arizona | Michaletz S.T.,Los Alamos National Laboratory | Weiser M.D.,University of Oklahoma | Zhou J.,University of Oklahoma | And 9 more authors.
Trends in Ecology and Evolution | Year: 2015

Building a more predictive trait-based ecology requires mechanistic theory based on first principles. We present a general theoretical approach to link traits and climate. We use plant leaves to show how energy budgets (i) provide a foundation for understanding thermoregulation, (ii) explain mechanisms driving trait variation across environmental gradients, and (iii) guide selection on functional traits via carbon economics. Although plants are often considered to be poikilotherms, the data suggest that they are instead limited homeotherms. Leaf functional traits that promote limited homeothermy are adaptive because homeothermy maximizes instantaneous and lifetime carbon gain. This theory provides a process-based foundation for trait-climate analyses and shows that future studies should consider plant (not only air) temperatures. Plants are generally considered to be poikilotherms that do not thermoregulate. However, empirical data show that plants are actually limited homeotherms that do thermoregulate.Plant thermoregulation and limited homeothermy decouples physiological functioning from climatic variation to promote metabolic homeostasis and maximize carbon assimilation and fitness.Energy budgets and carbon economics provide a mechanistic theory for understanding and predicting these relationships. Specifically, theory suggests that thermoregulation evolved via natural selection on traits to maximize lifetime carbon gain, growth, production, and fitness across climate gradients.Future studies need to consider plant tissue (and not only air) temperatures. © 2015. Source


Martin L.,University of Warwick | Cook C.,University of Warwick | Matasci N.,Thomas W Keating Bioresearch Building | Williams J.,Learning Center | Bastow R.,University of Warwick
Journal of Experimental Botany | Year: 2015

High-throughput sequencing technologies have rapidly moved from large international sequencing centres to individual laboratory benchtops. These changes have driven the 'data deluge' of modern biology. Submissions of nucleotide sequences to GenBank, for example, have doubled in size every year since 1982, and individual data sets now frequently reach terabytes in size. While 'big data' present exciting opportunities for scientific discovery, data analysis skills are not part of the typical wet bench biologist's experience. Knowing what to do with data, how to visualize and analyse them, make predictions, and test hypotheses are important barriers to success. Many researchers also lack adequate capacity to store and share these data, creating further bottlenecks to effective collaboration between groups and institutes. The US National Science Foundation-funded iPlant Collaborative was established in 2008 to form part of the data collection and analysis pipeline and help alleviate the bottlenecks associated with the big data challenge in plant science. Leveraging the power of high-performance computing facilities, iPlant provides free-to-use cyberinfrastructure to enable terabytes of data storage, improve analysis, and facilitate collaborations. To help train UK plant science researchers to use the iPlant platform and understand how it can be exploited to further research, GARNet organized a four-day Data mining with iPlant workshop at Warwick University in September 2013. This report provides an overview of the workshop, and highlights the power of the iPlant environment for lowering barriers to using complex bioinformatics resources, furthering discoveries in plant science research and providing a platform for education and outreach programmes. © The Author 2014. All rights reserved. Source


Morueta-Holme N.,University of Aarhus | Enquist B.J.,University of Arizona | Enquist B.J.,Santa Fe Institute | Mcgill B.J.,University of Maine, United States | And 18 more authors.
Ecology Letters | Year: 2013

Despite being a fundamental aspect of biodiversity, little is known about what controls species range sizes. This is especially the case for hyperdiverse organisms such as plants. We use the largest botanical data set assembled to date to quantify geographical variation in range size for ~ 85 000 plant species across the New World. We assess prominent hypothesised range-size controls, finding that plant range sizes are codetermined by habitat area and long- and short-term climate stability. Strong short- and long-term climate instability in large parts of North America, including past glaciations, are associated with broad-ranged species. In contrast, small habitat areas and a stable climate characterise areas with high concentrations of small-ranged species in the Andes, Central America and the Brazilian Atlantic Rainforest region. The joint roles of area and climate stability strengthen concerns over the potential effects of future climate change and habitat loss on biodiversity. © 2013 The Authors. Ecology Letters published by John Wiley & Sons Ltd and CNRS. Source


Boyle B.,University of Arizona | Boyle B.,Thomas W Keating Bioresearch Building | Hopkins N.,Thomas W Keating Bioresearch Building | Hopkins N.,BIO5 Institute | And 21 more authors.
BMC Bioinformatics | Year: 2013

Background: The digitization of biodiversity data is leading to the widespread application of taxon names that are superfluous, ambiguous or incorrect, resulting in mismatched records and inflated species numbers. The ultimate consequences of misspelled names and bad taxonomy are erroneous scientific conclusions and faulty policy decisions. The lack of tools for correcting this 'names problem' has become a fundamental obstacle to integrating disparate data sources and advancing the progress of biodiversity science.Results: The TNRS, or Taxonomic Name Resolution Service, is an online application for automated and user-supervised standardization of plant scientific names. The TNRS builds upon and extends existing open-source applications for name parsing and fuzzy matching. Names are standardized against multiple reference taxonomies, including the Missouri Botanical Garden's Tropicos database. Capable of processing thousands of names in a single operation, the TNRS parses and corrects misspelled names and authorities, standardizes variant spellings, and converts nomenclatural synonyms to accepted names. Family names can be included to increase match accuracy and resolve many types of homonyms. Partial matching of higher taxa combined with extraction of annotations, accession numbers and morphospecies allows the TNRS to standardize taxonomy across a broad range of active and legacy datasets.Conclusions: We show how the TNRS can resolve many forms of taxonomic semantic heterogeneity, correct spelling errors and eliminate spurious names. As a result, the TNRS can aid the integration of disparate biological datasets. Although the TNRS was developed to aid in standardizing plant names, its underlying algorithms and design can be extended to all organisms and nomenclatural codes. The TNRS is accessible via a web interface at http://tnrs.iplantcollaborative.org/ and as a RESTful web service and application programming interface. Source code is available at https://github.com/iPlantCollaborativeOpenSource/TNRS/. © 2013 Boyle et al.; licensee BioMed Central Ltd. Source

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