6 References

6.1 Literature

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[2] V. Barve. “Discovering and developing primary biodiversity data from social networking sites: A novel approach”. In: Ecological Informatics 24 (2014), pp. 194-199.

[3] J. Bascompte and P. Jordano. “Plant-animal mutualistic networks: the architecture of biodiversity”. In: Annual Review of Ecology, Evolution, and Systematics (2007), pp. 567-593.

[4] H. Beck. “A review of peccary-palm interactions and their ecological ramifications across the Neotropics”. In: Journal of Mammalogy 87.3 (2006), pp. 519-530.

[5] P. Betzholtz, L. B. Pettersson, N. Ryrholm, et al. “With that diet, you will go far: trait-based analysis reveals a link between rapid range expansion and a nitrogen-favoured diet”. In: Proceedings of the Royal Society of London B: Biological Sciences 280.1750 (2013), p. 20122305.

[6] F. A. Bisby. “The quiet revolution: biodiversity informatics and the internet”. In: Science 289.5488 (2000), pp. 2309-2312.

[7] B. Björk, P. Welling, M. Laakso, et al. “Open access to the scientific journal literature: situation 2009”. In: PloS one 5.6 (2010), p. e11273.

[8] D. M. Blei. “Probabilistic topic models”. In: Communications of the ACM 55.4 (2012), pp. 77-84.

[9] G. Ceballos, P. R. Ehrlich, A. D. Barnosky, et al. “Accelerated modern human-induced species losses: Entering the sixth mass extinction”. In: Science advances 1.5 (2015), p. e1400253.

[10] B. Dalsgaard, E. Magaard, J. Fjeldsa, et al. “Specialization in plant-hummingbird networks is associated with species richness, contemporary precipitation and quaternary climate-change velocity”. In: PLoS One 6.10 (2011), p. e25891.

[11] B. Dalsgaard, K. Trøjelsgaard, A. M. Martín-González, et al. “Historical climate-change influences modularity and nestedness of pollination networks”. In: Ecography 36.12 (2013), pp. 1331-1340.

[12] J. L. Edwards, M. A. Lane and E. S. Nielsen. “Interoperability of biodiversity databases: biodiversity information on every desktop”. In: Science 289.5488 (2000), pp. 2312-2314.

[13] P. Flombaum, J. L. Gallegos, R. A. Gordillo, et al. “Present and future global distributions of the marine Cyanobacteria Prochlorococcus and Synechococcus”. In: Proceedings of the National Academy of Sciences 110.24 (2013), pp. 9824-9829.

[14] J. O. A. Gamboa and F. R. R. Espinosa. “La revista acade?mica iberoamericana en Latindex Una visio?n de 15 an?os”. In: Biblioteca universitaria 15.2 (2012), pp. 123-138.

[15] L. N. Hudson, T. Newbold, S. Contu, et al. “The PREDICTS database: a global database of how local terrestrial biodiversity responds to human impacts”. In: Ecology and evolution 4.24 (2014), pp. 4701-4735.

[16] P. Jordano. “Chasing ecological interactions”. In: PLoS Biol 14.9 (2016), p. e1002559.

[17] P. Jordano, J. Bascompte and J. M. Olesen. “Invariant properties in coevolutionary networks of plant-animal interactions”. In: Ecology letters 6.1 (2003), pp. 69-81.

[18] W. D. Kissling and M. Schleuning. “Multispecies interactions across trophic levels at macroscales: retrospective and future directions”. In: Ecography 38.4 (2015), pp. 346-357.

[19] L. P. Koh, R. R. Dunn, N. S. Sodhi, et al. “Species coextinctions and the biodiversity crisis”. In: science 305.5690 (2004), pp. 1632-1634.

[20] I. Korkontzelos, A. Nikfarjam, M. Shardlow, et al. “Analysis of the effect of sentiment analysis on extracting adverse drug reactions from tweets and forum posts”. In: Journal of Biomedical Informatics 62 (2016), pp. 148-158.

[21] M. Krallinger and A. Valencia. “Text-mining and information-retrieval services for molecular biology”. In: Genome biology 6.7 (2005), p. 1.

[22] K. Krippendorff. Content analysis: An introduction to its methodology. Sage, 2012.

[23] C. H. Lyal. “Digitising legacy zoological taxonomic literature: Processes, products and using the output”. In: ZooKeys (2016), p. 189.

[24] A. M. Martin-González, B. Dalsgaard, D. Nogués-Bravo, et al. “The macroecology of phylogenetically structured hummingbird-plant networks”. In: Global Ecology and Biogeography 24.11 (2015), pp. 1212-1224.

[25] L. J. Martin, B. Blossey and E. Ellis. “Mapping where ecologists work: biases in the global distribution of terrestrial ecological observations”. In: Frontiers in Ecology and the Environment 10.4 (2012), pp. 195-201.

[26] E. B. Miranda, C. Strüssmann and others. “The ecology of human-anaconda conflict: a study using internet videos”. In: Tropical Conservation Science 9.1 (2016), pp. 43-77.

[27] J. M. Montoya and D. Raffaelli. “Climate change, biotic interactions and ecosystem services”. In: Philosophical Transactions of the Royal Society of London B: Biological Sciences 365.1549 (2010), pp. 2013-2018.

[28] M. J. Novacek and E. E. Cleland. “The current biodiversity extinction event: scenarios for mitigation and recovery”. In: Proceedings of the National Academy of Sciences 98.10 (2001), pp. 5466-5470.

[29] G. C. Nunez-Mir, B. V. Iannone, B. C. Pijanowski, et al. “Automated content analysis: addressing the big literature challenge in ecology and evolution”. In: Methods in Ecology and Evolution 7.11 (2016), pp. 1262-1272.

[30] J. D. Olden and T. P. Rooney. “On defining and quantifying biotic homogenization”. In: Global Ecology and Biogeography 15.2 (2006), pp. 113-120.

[31] H. M. Pereira, S. Ferrier, M. Walters, et al. “Essential biodiversity variables”. In: Science 339.6117 (2013), pp. 277-278.

[32] S. C. Pilsk, M. R. Kalfatovic and J. M. Richard. “Unlocking Index Animalium: From paper slips to bytes and bits”. In: ZooKeys (2016), p. 153.

[33] T. Poisot, D. Gravel, S. Leroux, et al. “Synthetic datasets and community tools for the rapid testing of ecological hypotheses”. In: Ecography (2015).

[34] T. Poisot, D. B. Stouffer and D. Gravel. “Beyond species: why ecological interaction networks vary through space and time”. In: Oikos 124.3 (2015), pp. 243-251.

[35] V. Proença, L. J. Martin, H. M. Pereira, et al. “Global biodiversity monitoring: from data sources to essential biodiversity variables”. In: Biological Conservation (2016).

[36] O. J. Reichman, M. B. Jones and M. P. Schildhauer. “Challenges and opportunities of open data in ecology”. In: Science 331.6018 (2011), pp. 703-705.

[37] F. R. Reyna Espinosa. “La Bibliografía Latinoamericana de la UNAM, a prop'osito de los 350 a~nos de la primera revista científica”. In: Ibersid 9 (2015), pp. 47-52.

[38] M. Schleuning, J. Fründ, A. Klein, et al. “Specialization of mutualistic interaction networks decreases toward tropical latitudes”. In: Current biology 22.20 (2012), pp. 1925-1931.

[39] P. Shanmughavel. “An overview on biodiversity information in databases”. In: Bioinformation 1.9 (2007), p. 367.

[40] D. Stouffer, J. Camacho, R. Guimera, et al. “Quantitative patterns in the structure of model and empirical food webs”. In: Ecology 86.5 (2005), pp. 1301-1311.

[41] A. E. Thessen. Adoption of machine learning techniques in Ecology and Earth Science. Tech. rep. PeerJ PrePrints, 2016.

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[43] A. E. Thessen and C. S. Parr. “Knowledge extraction and semantic annotation of text from the encyclopedia of life”. In: PLoS One 9.3 (2014), p. e89550.

[44] W. Thuiller, T. Münkemüller, S. Lavergne, et al. “A road map for integrating eco-evolutionary processes into biodiversity models”. In: Ecology letters 16.s1 (2013), pp. 94-105.

[45] K. Trøjelsgaard and J. M. Olesen. “Macroecology of pollination networks”. In: Global Ecology and Biogeography 22.2 (2013), pp. 149-162.

[46] J. M. Tylianakis, R. K. Didham, J. Bascompte, et al. “Global change and species interactions in terrestrial ecosystems”. In: Ecology letters 11.12 (2008), pp. 1351-1363.

[47] W. H. Van der Putten, M. Macel and M. E. Visser. “Predicting species distribution and abundance responses to climate change: why it is essential to include biotic interactions across trophic levels”. In: Philosophical Transactions of the Royal Society B: Biological Sciences 365.1549 (2010), pp. 2025-2034.

6.2 Packages

[1] M. Bouchet-Valat. SnowballC: Snowball stemmers based on the C libstemmer UTF-8 library. R package version 0.5.1. 2014. <URL: https://CRAN.R-project.org/package=SnowballC>.

[2] S. Chamberlain. fulltext: Full Text of ‘Scholarly’ Articles Across Many Data Sources. R package version 0.1.8. 2016. <URL: https://CRAN.R-project.org/package=fulltext>.

[3] S. Chamberlain, E. Szocs, C. Boettiger, et al. taxize: Taxonomic information from around the web. R package version 0.7.4. 2016. <URL: https://github.com/ropensci/taxize>.

[4] J. Cheng and Y. Xie. leaflet: Create Interactive Web Maps with the JavaScript ‘Leaflet’ Library. R package version 1.0.1. 2016. <URL: https://CRAN.R-project.org/package=leaflet>.

[5] I. Feinerer and K. Hornik. tm: Text Mining Package. R package version 0.6-2. 2015. <URL: https://CRAN.R-project.org/package=tm>.

[6] I. Feinerer, K. Hornik and D. Meyer. “Text Mining Infrastructure in R”. In: Journal of Statistical Software 25.5 (Mar. 2008), pp. 1-54. <URL: http://www.jstatsoft.org/v25/i05/>.

[7] J. Friedman, T. Hastie and R. Tibshirani. “Regularization Paths for Generalized Linear Models via Coordinate Descent”. In: Journal of Statistical Software 33.1 (2010), pp. 1-22. <URL: http://www.jstatsoft.org/v33/i01/>.

[8] K. Hornik. NLP: Natural Language Processing Infrastructure. R package version 0.1-9. 2016. <URL: https://CRAN.R-project.org/package=NLP>.

[9] D. Kahle and H. Wickham. “ggmap: Spatial Visualization with ggplot2”. In: The R Journal 5.1 (2013), pp. 144-161. <URL: http://journal.r-project.org/archive/2013-1/kahle-wickham.pdf>.

[10] D. Meyer, E. Dimitriadou, K. Hornik, et al. e1071: Misc Functions of the Department of Statistics, Probability Theory Group (Formerly: E1071), TU Wien. R package version 1.6-7. 2015. <URL: https://CRAN.R-project.org/package=e1071>.

[11] J. Ooms. pdftools: Extract Text and Data from PDF Documents. R package version 0.5. 2016. <URL: https://CRAN.R-project.org/package=pdftools>.

[12] T. W. Rinker. qdap: Quantitative Discourse Analysis Package. 2.2.5. University at Buffalo/SUNY. Buffalo, New York, 2013. <URL: http://github.com/trinker/qdap>.

[13] M. Salmon. monkeylearn: Accesses the Monkeylearn API for Text Classifiers and Extractors. R package version 0.1.1. 2016. <URL: https://CRAN.R-project.org/package=monkeylearn>.

[14] Scott Chamberlain and Eduard Szocs. “taxize - taxonomic search and retrieval in R”. In: F1000Research (2013). <URL: http://f1000research.com/articles/2-191/v2>.

[15] D. Selivanov. text2vec: Modern Text Mining Framework for R. R package version 0.4.0. 2016. <URL: https://CRAN.R-project.org/package=text2vec>.

[16] N. Simon, J. Friedman, T. Hastie, et al. “Regularization Paths for Cox’s Proportional Hazards Model via Coordinate Descent”. In: Journal of Statistical Software 39.5 (2011), pp. 1-13. <URL: http://www.jstatsoft.org/v39/i05/>.

[17] H. Wickham. “Reshaping Data with the reshape Package”. In: Journal of Statistical Software 21.12 (2007), pp. 1-20. <URL: http://www.jstatsoft.org/v21/i12/>.

[18] H. Wickham. stringr: Simple, Consistent Wrappers for Common String Operations. R package version 1.1.0. 2016. <URL: https://CRAN.R-project.org/package=stringr>.

[19] H. Wickham and W. Chang. devtools: Tools to Make Developing R Packages Easier. R package version 1.12.0. 2016. <URL: https://CRAN.R-project.org/package=devtools>.

[20] Y. Xie. bookdown: Authoring Books and Technical Documents with R Markdown. ISBN 978-1138700109. Boca Raton, Florida: Chapman and Hall/CRC, 2017. <URL: https://github.com/rstudio/bookdown>.

[21] Y. Xie. bookdown: Authoring Books and Technical Documents with R Markdown. R package version 0.3. 2016. <URL: https://github.com/rstudio/bookdown>.

[22] Y. Xie. DT: A Wrapper of the JavaScript Library ‘DataTables’. R package version 0.2. 2016. <URL: https://CRAN.R-project.org/package=DT>.