Building a multi-scaled geospatial temporal ecology database from disparate data sources: fostering open science and data reuse
Tóm tắt
Although there are considerable site-based data for individual or groups of ecosystems, these datasets are widely scattered, have different data formats and conventions, and often have limited accessibility. At the broader scale, national datasets exist for a large number of geospatial features of land, water, and air that are needed to fully understand variation among these ecosystems. However, such datasets originate from different sources and have different spatial and temporal resolutions. By taking an open-science perspective and by combining site-based ecosystem datasets and national geospatial datasets, science gains the ability to ask important research questions related to grand environmental challenges that operate at broad scales. Documentation of such complicated database integration efforts, through peer-reviewed papers, is recommended to foster reproducibility and future use of the integrated database. Here, we describe the major steps, challenges, and considerations in building an integrated database of lake ecosystems, called LAGOS (LAke multi-scaled GeOSpatial and temporal database), that was developed at the sub-continental study extent of 17 US states (1,800,000 km2). LAGOS includes two modules: LAGOSGEO, with geospatial data on every lake with surface area larger than 4 ha in the study extent (~50,000 lakes), including climate, atmospheric deposition, land use/cover, hydrology, geology, and topography measured across a range of spatial and temporal extents; and LAGOSLIMNO, with lake water quality data compiled from ~100 individual datasets for a subset of lakes in the study extent (~10,000 lakes). Procedures for the integration of datasets included: creating a flexible database design; authoring and integrating metadata; documenting data provenance; quantifying spatial measures of geographic data; quality-controlling integrated and derived data; and extensively documenting the database. Our procedures make a large, complex, and integrated database reproducible and extensible, allowing users to ask new research questions with the existing database or through the addition of new data. The largest challenge of this task was the heterogeneity of the data, formats, and metadata. Many steps of data integration need manual input from experts in diverse fields, requiring close collaboration.
Tài liệu tham khảo
Downing J. Limnology and oceanography: two estranged twins reuniting by global change. Inland Waters. 2014;4:215–32.
Cole JJ, Prairie YT, Caraco NF, McDowell WH, Tranvik LJ, Striegl RG, et al. Plumbing the global carbon cycle: integrating inland waters into the terrestrial carbon budget. Ecosystems. 2007;10:171–84.
Downing JA. Plenary lecture - Global limnology: up-scaling aquatic services and processes to planet Earth. Verh Intern Ver Limnol. 2009;30:1149–66.
Tallis H, Mooney H, Andelman SJ, Balvanera P, Cramer W, Karp D, et al. A global system for monitoring ecosystem service change. Bioscience. 2012;62:977–86.
Moe SJ, Schmidt-Kloiber A, Dudley BJ, Hering D. The WISER way of organizing ecological data from European rivers, lakes, transitional and coastal waters. Hydrobiol. 2013;704:11–28.
Dornelas M, Gotelli NJ, McGill B, Shimadzu H, Moyes F, Sievers C, et al. Assemblage time series reveal biodiversity change but not systematic loss. Science. 2014;344:296–9.
Poelen JH, Simons JD, Mungall CJ. Global biotic interactions: an open infrastructure to share and analyze species-interaction datasets. Ecol Inform. 2014;24:148–59.
Soranno PA, Cheruvelil KS, Bissell EG, Bremigan MT, Downing JA, Fergus CE, et al. Cross-scale interactions: quantifying multi-scaled cause-effect relationships in macrosystems. Front Ecol Environ. 2014;12:65–73.
Magnuson JJ. The challenge of unveiling the invisible present. In: Waller DM, Rooney TP, editors. The Vanishing Present: Wisconsin’s Changing Lands, Waters, and Wildlife. Chicago: University of Chicago Press; 2008. p. 31–40.
Heffernan JB, Soranno PA, Angilletta MJ, Buckley LB, Gruner DS, Keitt TH, et al. Macrosystems ecology: understanding ecological patterns and processes at continental scales. Front Ecol Environ. 2014;12:5–14.
Hampton SE, Strasser CA, Tewksbury JJ, Gram WK, Budden AE, Batcheller AL, et al. Big data and the future of ecology. Front Ecol Environ. 2013;11:156–62.
Peters DPC, Havstad KM, Cushing J, Tweedie C, Fuentes O, Villanueva-Rosales N. Harnessing the power of big data: infusing the scientific method with machine learning to transform ecology. Ecosphere. 2014;5:1–15.
Michener WK, Jones MB. Ecoinformatics: supporting ecology as a data-intensive science. Trends Ecol Evol. 2012;27:85–93.
Porter JH, Hanson PC, Lin C-C. Staying afloat in the sensor data deluge. Trends Ecol Evol. 2012;27:121–9.
Soranno PA, Schimel DS. Macrosystems ecology: big data, big ecology. Front Ecol Environ. 2014;12:3.
Heidorn PB. Shedding light on the dark data in the long tail of science. Libr Trends. 2008;57:280–99.
United States Environmental Protection agency. STORET. http://www.epa.gov/storet/dbtop.html (2015). Accessed 18 May 2015.
United States Geological Survey. NWIS. http://waterdata.usgs.gov/nwis/qw (2015). Accessed 18 May 2015.
Rigler FH, Peters RH. Science and limnology. In: Kinne O, editor. Excellence in Ecology, 6. Oldendoft: Ecology Institute; 1995.
Downing JA, Osenberg CW, Sarnelle O. Meta-analysis of marine nutrient-enrichment experiments: variation in the magnitude of nutrient limitation. Ecology. 1999;80:1157.
Downing JA, McCauley E. The nitrogen: phosphorus relationship in lakes. Limnol Oceanogr. 1992;37:936–45.
Gill RA, Jackson RB. Global patterns of root turnover for terrestrial ecosystems. New Phytol. 2000;147:13–31.
Bond-Lamberty B, Thomson A. A global database of soil respiration data. Biogeosciences. 2010;7:1915–26.
Carpenter SR, Armbrust EV, Arzberger PW, Chappin III FS, Elser JJ, Hackett EJ, et al. Accelerate synthesis in ecology and environmental sciences. Bioscience. 2009;59:699–701.
Rodrigo A, Alberts S, Cranston K, Kingsolver J, Lapp H, McClain C, et al. Science incubators: synthesis centers and their role in the research ecosystem. PLoS Biol. 2013;11, e1001468.
Schenk HJ, Jackson RB. The global biogeography of roots. Ecol Monogr. 2002;72:311–28.
Scurlock JMO, Cramer W, Olson RJ, Parton WJ, Prince SD. Terrestrial NPP: toward a consistent data set for global model evaluation. Ecol Appl. 1999;9:913–9.
Wagner T, Bence JR, Bremigan MT, Hayes DB, Wilberg MJ. Regional trends in fish mean length at age: components of variance and the power to detect trends. Can J Fish Aquat Sci. 2007;64:968–78.
National Center for Biotechnology Information. GenBank. http://www.ncbi.nlm.nih.gov/genbank/ (2015). Accessed 18 May 2015.
Wong PB, Wiley EO, Johnson WE, Ryder OA, O’Brien SJ, Haussler D, et al. G10KCOS. Tissue sampling methods and standards for vertebrate genomics. Gigascience. 2012;1:8.
Sharma S, Gray DK, Read JS, O’Reilly CM, Schneider P, Qudrat A, et al. A global database of lake surface temperatures collected by in situ and satellite methods from 1985–2009. Sci Data. 2015;2.
Cheruvelil KS, Soranno PA, Weathers KC, Hanson PC, Goring SJ, Filstrup CT, et al. Creating and maintaining high-performing collaborative research teams: the importance of diversity and interpersonal skills. Front Ecol Environ. 2014;12:31–8.
Pennington DD. Collaborative, cross-disciplinary learning and co-emergent innovation in eScience teams. Earth Sci Inform. 2011;4:55–68.
Duke CS, Porter JH. The ethics of data sharing and reuse in biology. Bioscience. 2013;63:483–9.
Soranno PA, Cheruvelil KS, Webster KE, Bremigan MT, Wagner T, Stow CA. Using landscape limnology to classify freshwater ecosystems for multi-ecosystem management and conservation. Bioscience. 2010;60:440–54.
Tarboton DG, Horsburgh JS, Maidment DR. CUAHSI community observations data model (ODM) design specifications document: Version 1.1. http://his.cuahsi.org/odmdatabases.html (2008). Accessed 18 May 2015.
R Core Team. R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing; 2014.