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@article{Boose2007,
abstract = {At the dawn of the 21st century, environmental scientists are collecting more data more rapidly than at any time in the past. Nowhere is this change more evident than in the advent of sensor networks able to collect and process (in real time) simultaneous measurements over broad areas and at high sampling rates. At the same time there has been great progress in the development of standards, methods, and tools for data analysis and synthesis, including a new standard for descriptive metadata for ecological datasets (Ecological Metadata Language) and new workflow tools that help scientists to assemble datasets and to diagram, record, and execute analyses. However these developments (important as they are) are not yet sufficient to guarantee the reliability of datasets created by a scientific process - the complex activity that scientists carry out in order to create a dataset. We define a dataset to be reliable when the scientific process used to create it is (1) reproducible and (2) analyzable for potential defects. To address this problem we propose the use of an analytic web, a formal representation of a scientific process that consists of three coordinated graphs (a data-flow graph, a dataset-derivation graph, and a process-derivation graph) originally developed for use in software engineering. An analytic web meets the two key requirements for ensuring dataset reliability: (1) a complete audit trail of all artifacts (e.g., datasets, code, models) used or created in the execution of the scientific process that created the dataset, and (2) detailed process metadata that precisely describe all sub-processes of the scientific process. Construction of such metadata requires the semantic features of a high-level process definition language. In this paper we illustrate the use of an analytic web to represent the scientific process of constructing estimates of ecosystem water flux from data gathered by a complex, real-time multi-sensor network. We use Little-JIL, a high-level process definition language, to precisely and accurately capture the analytical processes involved. We believe that incorporation of this approach into existing tools and evolving metadata specifications (such as EML) will yield significant benefits to science. These benefits include: complete and accurate representations of scientific processes; support for rigorous evaluation of such processes for logical and statistical errors and for propagation of measurement error; and assurance of dataset reliability for developing sound models and forecasts of environmental change. ?? 2007 Elsevier B.V. All rights reserved.},
annote = {NULL},
author = {Boose, Emery R. and Ellison, Aaron M. and Osterweil, Leon J. and Clarke, Lori a. and Podorozhny, Rodion and Hadley, Julian L. and Wise, Alexander and Foster, David R.},
doi = {10.1016/j.ecoinf.2007.07.006},
isbn = {1574-9541},
issn = {15749541},
journal = {Ecol. Inform.},
keywords = {Analytic web,Little-JIL,Metadata,Process,Sensor network,Water flux},
pages = {237--247},
title = {{Ensuring reliable datasets for environmental models and forecasts}},
volume = {2},
year = {2007}
}
@misc{HFDataArchive,
annote = {NULL},
title = {{Harvard Forest Data Archive}},
url = {http://harvardforest.fas.harvard.edu/data-archive/guidelines-for-submission},
urldate = {2017-03-08}
}
@article{Baker2016,
author = {Baker, Monya},
journal = {Nature},
pages = {452--454},
title = {1,500 scientists lift the lid on reproducibility},
volume = {533},
year = {2016}
}
@book{Forman1986,
abstract = {Includes index. Part I. Overview : Landscape and principles : Perceptions of the landscape ; A landscape from an ecological perspective ; Concept areas and principles of landscape ecology ; The emergence of landscape ecology: major literature -- Ecological concepts in brief : The physical environment ; Aquatic environments ; Populations and their regulation ; Evolutionary ecology ; Ecological communities ; Energy and matter in ecosystems -- Part II. Landscape structure : Patches : Patch origins and change ; Patch size ; Patch shape ; Patch number and configuration -- Corridors : Corridors and their origins ; Corridor structure ; Line corridors ; Strip corridors ; Stream corridors -- Matrix and network : Distinguishing a matrix ; Porosity and boundary shape ; Networks ; Matrix heterogeneity -- Appendix: Measures of patch characteristics in a matrix -- Overall structure : microheterogeneity and macroheterogeneity ; Configuration of patches, corridor, and matrix ; Contrast in the landscape ; Grain size of the landscape ; Additional structural considerations -- Appendix: A method of measuring for landscape heterogeneity -- Part III. Landscape dynamics : Natural processes in landscape development : Geormorphology ; Establishment of life forms ; Soil development ; Natural disturbance ; Appendix: Geological time -- The human role in landscape development : Modification of natural rhythms ; Methods or tools used in landscape modification ; A landscape modification gradient -- Flows between adjacent landscape elements : Mechanism underlying linkages ; Airflow and locomotion ; Soil flows ; Interaction between land and stream ; Hedgerow interactions with adjacent landscape elements -- Animal and plant movement across a landscape : Patterns of movement ; Movement of animals ; Movement of plants ; Some species movements in agriculture and pest control -- Landscape functioning : Corridors and flows ; Flows and the matrix ; Networks -- Landscape change : Stability ; Metastability ; Patterns of overall landscape change ; Landscape dynamics ; Linkages among landscapes -- Part IV. Heterogeneity and management : Heterogeneity and typology : Landscape heterogeneity ; Animal response to heterogeneity ; Guidelines for landscape typology ; The inherent hierarchy in nature ; Ascending typology ; Toward a phylogenetic typology -- Landscape management : Where humans grow ; Production in landscapes ; Planning and management of major landscape types ; Landscape quality ; Modelling and landscape management ; Some broader perspectives -- Glossary.},
annote = {NULL},
author = {Forman, Richard T. T. and Godron, Michel.},
isbn = {0471870374},
publisher = {Wiley},
title = {{Landscape ecology}},
year = {1986}
}
@article{Hirsch1996,
abstract = {Weekly values of the net 03 production efficiency (OPE), defined as the net number of 03 molecules produced per molecule of NOx (NO + NO2) consumed, are estimated from a 1990-1994 record of 03, NOx, NOy, CO, and C2H 2 concentrations at Harvard Forest, Massachusetts. The OPE is inferred from the slope AO3/A(NOy-NOx) of the linear regression between 03 and NOy-NO x concentrations (NOy is the sum of NOx and its oxidation products); and alternatively from the slopes AO3/ACO and AO3/AC2H2 multiplied by regional estimates of the CO/NO • and C2H2/NOx emission ratios. The mean OPE values inferred from AO3/A(NOy-NOx) are 3-5 times higher than those inferred from AO3/ACO or AO3/AC 2H2; the discrepancy may be due to the effects of HNO3 and 03 deposition and also to uncertainties in the CO/NOx and C2H2/NOx emission ratios. The relative seasonal trends of the OPE derived from AO3/A(NOy-NOx), AO3/ACO, and AO3/AC2H 2 are, however, similar. Thus AO3/A(NOy-NOx) increases from about 4 reel/reel in May to 8 mol/mol in June-July, and gradually decreases back to 4 reel/reel by early October. The sharp rise of the OPE from May to June is attributed to onset of emission of the biogcnic hydrocarbon isoprene. The decline from July to October is attributed to decreases in isoprcnc emission and in solar radiation. The 03 background at Harvard Forest, defined by the y intercept of the 03 versus NOy-NOx regression line, decreases from 40 ppbv in May to 25 ppbv in September, consistent with observations at remote sites in northern midlatitudes. The seasonal trend in the background explains why mean 03 concentrations at Harvard Forest peak in May-June even though the OPE peaks in June-July.},
annote = {NULL},
author = {Hirsch, Adam I and Munger, @bullet J William and Jacob, Daniel J and Horowitz, Larry W and Goldstein, Allen H},
file = {:Users/hermes/Library/Application Support/Mendeley Desktop/Downloaded/Hirsch et al. - 1996 - Seasonal variation of the ozone production efficiency per unit NOx at Harvard Forest, Massachusetts(2).pdf:pdf},
journal = {J. Geophys. Res.},
number = {20},
pages = {659--12},
title = {{Seasonal variation of the ozone production efficiency per unit NOx at Harvard Forest, Massachusetts}},
url = {http://harvardforest.fas.harvard.edu/sites/harvardforest.fas.harvard.edu/files/publications/pdfs/Hirsch{\_}JGeophysicalResearch{\_}1996.pdf},
volume = {101666},
year = {1996}
}
@article{Ellison2010,
annote = {NULL},
author = {Ellison, Aaron M},
file = {:Users/hermes/Library/Application Support/Mendeley Desktop/Downloaded/Ellison - 2010 - Repeatability and transparency in ecological research.pdf:pdf},
journal = {Ecology},
number = {9},
pages = {2536--2539},
title = {{Repeatability and transparency in ecological research}},
url = {http://harvardforest.fas.harvard.edu/sites/harvardforest.fas.harvard.edu/files/ellison-pubs/2010/ellison{\_}2010{\_}ecology.pdf},
volume = {91},
year = {2010}
}
@article{Clark2017,
annote = {NULL},
author = {Clark, Timothy D.},
doi = {10.1038/542139a},
issn = {0028-0836},
journal = {Nature},
month = {feb},
number = {7640},
pages = {139--139},
title = {{Science, lies and video-taped experiments}},
url = {http://www.nature.com/doifinder/10.1038/542139a},
volume = {542},
year = {2017}
}
@article{Wilkinson2016a,
author = {Wilkinson, Mark D. and Dumontier, Michel and Aalbersberg, IJsbrand Jan and Appleton, Gabrielle and Axton, Myles and Baak, Arie and Blomberg, Niklas and Boiten, Jan-Willem and {da Silva Santos}, Luiz Bonino and Bourne, Philip E. and Bouwman, Jildau and Brookes, Anthony J. and Clark, Tim and Crosas, Merc{\`{e}} and Dillo, Ingrid and Dumon, Olivier and Edmunds, Scott and Evelo, Chris T. and Finkers, Richard and Gonzalez-Beltran, Alejandra and Gray, Alasdair J.G. and Groth, Paul and Goble, Carole and Grethe, Jeffrey S. and Heringa, Jaap and {'t Hoen}, Peter A.C and Hooft, Rob and Kuhn, Tobias and Kok, Ruben and Kok, Joost and Lusher, Scott J. and Martone, Maryann E. and Mons, Albert and Packer, Abel L. and Persson, Bengt and Rocca-Serra, Philippe and Roos, Marco and van Schaik, Rene and Sansone, Susanna-Assunta and Schultes, Erik and Sengstag, Thierry and Slater, Ted and Strawn, George and Swertz, Morris A. and Thompson, Mark and van der Lei, Johan and van Mulligen, Erik and Velterop, Jan and Waagmeester, Andra and Wittenburg, Peter and Wolstencroft, Katherine and Zhao, Jun and Mons, Barend},
doi = {10.1038/sdata.2016.18},
file = {:Users/hermes/Library/Application Support/Mendeley Desktop/Downloaded/Wilkinson et al. - 2016 - The FAIR Guiding Principles for scientific data management and stewardship.pdf:pdf},
issn = {2052-4463},
journal = {Sci. Data},
month = {mar},
pages = {160018},
publisher = {Nature Publishing Group},
title = {{The FAIR Guiding Principles for scientific data management and stewardship}},
url = {http://www.nature.com/articles/sdata201618},
volume = {3},
year = {2016}
}
@article{Boose,
abstract = {At the dawn of the 21st century, environmental scientists are collecting more data more rapidly than at any time in the past. Nowhere is this change more evident than in the advent of sensor networks able to collect and process (in real time) simultaneous measurements over broad areas and at high sampling rates. At the same time there has been great progress in the development of standards, methods, and tools for data analysis and synthesis, including a new standard for descriptive metadata for ecological datasets (Ecological Metadata Language) and new workflow tools that help scientists to assemble datasets and to diagram, record, and execute analyses. However these developments (important as they are) are not yet sufficient to guarantee the reliability of datasets created by a scientific process — the complex activity that scientists carry out in order to create a dataset. We define a dataset to be reliable when the scientific process used to create it is (1) reproducible and (2) analyzable for potential defects. To address this problem we propose the use of an analytic web, a formal representation of a scientific process that consists of three coordinated graphs (a data-flow graph, a dataset-derivation graph, and a process-derivation graph) originally developed for use in software engineering. An analytic web meets the two key requirements for ensuring dataset reliability: (1) a complete audit trail of all artifacts (e.g., datasets, code, models) used or created in the execution of the scientific process that created the dataset, and (2) detailed process metadata that precisely describe all sub-processes of the scientific process. Construction of such metadata requires the semantic features of a high-level process definition language. In this paper we illustrate the use of an analytic web to represent the scientific process of constructing estimates of ecosystem water flux from data gathered by a complex, real-time multi-sensor network. We use Little-JIL, a high-level process definition language, to precisely and accurately capture the analytical processes involved. We believe that incorporation of this approach into existing tools and evolving metadata specifications (such as EML) will yield significant benefits to science. These benefits include: complete and accurate representations of scientific processes; support for rigorous evaluation of such processes for logical and statistical errors and for propagation of measurement error; and assurance of dataset reliability for developing sound models and forecasts of environmental change.},
annote = {NULL},
author = {Boose, Emery R and Ellison, Aaron M and Osterweil, Leon J and Clarke, Lori A and Podorozhny, Rodion and Hadley, Julian L and Wise, Alexander and Foster, David R},
doi = {10.1016/j.ecoinf.2007.07.006},
file = {:Users/hermes/Library/Application Support/Mendeley Desktop/Downloaded/Boose et al. - Unknown - Author's personal copy Ensuring reliable datasets for environmental models and forecasts.pdf:pdf},
keywords = {Analytic web,Little-JIL,Metadata,Process,Sensor network,Water flux},
number = {2},
pages = {3--7},
title = {{Author's personal copy Ensuring reliable datasets for environmental models and forecasts}},
url = {http://harvardforest.fas.harvard.edu/sites/harvardforest.fas.harvard.edu/files/ellison-pubs/2007/boose{\_}etal{\_}2007{\_}EI.pdf},
volume = {2}
}
@article{Boose2007,
abstract = {At the dawn of the 21st century, environmental scientists are collecting more data more rapidly than at any time in the past. Nowhere is this change more evident than in the advent of sensor networks able to collect and process (in real time) simultaneous measurements over broad areas and at high sampling rates. At the same time there has been great progress in the development of standards, methods, and tools for data analysis and synthesis, including a new standard for descriptive metadata for ecological datasets (Ecological Metadata Language) and new workflow tools that help scientists to assemble datasets and to diagram, record, and execute analyses. However these developments (important as they are) are not yet sufficient to guarantee the reliability of datasets created by a scientific process - the complex activity that scientists carry out in order to create a dataset. We define a dataset to be reliable when the scientific process used to create it is (1) reproducible and (2) analyzable for potential defects. To address this problem we propose the use of an analytic web, a formal representation of a scientific process that consists of three coordinated graphs (a data-flow graph, a dataset-derivation graph, and a process-derivation graph) originally developed for use in software engineering. An analytic web meets the two key requirements for ensuring dataset reliability: (1) a complete audit trail of all artifacts (e.g., datasets, code, models) used or created in the execution of the scientific process that created the dataset, and (2) detailed process metadata that precisely describe all sub-processes of the scientific process. Construction of such metadata requires the semantic features of a high-level process definition language. In this paper we illustrate the use of an analytic web to represent the scientific process of constructing estimates of ecosystem water flux from data gathered by a complex, real-time multi-sensor network. We use Little-JIL, a high-level process definition language, to precisely and accurately capture the analytical processes involved. We believe that incorporation of this approach into existing tools and evolving metadata specifications (such as EML) will yield significant benefits to science. These benefits include: complete and accurate representations of scientific processes; support for rigorous evaluation of such processes for logical and statistical errors and for propagation of measurement error; and assurance of dataset reliability for developing sound models and forecasts of environmental change. ?? 2007 Elsevier B.V. All rights reserved.},
annote = {NULL},
author = {Boose, Emery R. and Ellison, Aaron M. and Osterweil, Leon J. and Clarke, Lori a. and Podorozhny, Rodion and Hadley, Julian L. and Wise, Alexander and Foster, David R.},
doi = {10.1016/j.ecoinf.2007.07.006},
isbn = {1574-9541},
issn = {15749541},
journal = {Ecol. Inform.},
keywords = {Analytic web,Little-JIL,Metadata,Process,Sensor network,Water flux},
pages = {237--247},
title = {{Ensuring reliable datasets for environmental models and forecasts}},
volume = {2},
year = {2007}
}
@article{Parker2016,
abstract = {To make progress scientists need to know what other researchers have found and how they found it. However, transparency is often insufficient across much of ecology and evolution. Researchers often fail to report results and methods in detail sufficient to permit interpretation and meta-analysis, and many results go entirely unreported. Further, these unreported results are often a biased subset. Thus the conclusions we can draw from the published literature are themselves often biased and sometimes might be entirely incorrect. Fortunately there is a movement across empirical disciplines, and now within ecology and evolution, to shape editorial policies to better promote transparency. This can be done by either requiring more disclosure by scientists or by developing incentives to encourage disclosure.},
annote = {NULL},
author = {Parker, Timothy H and Forstmeier, Wolfgang and Koricheva, Julia and Fidler, Fiona and Hadfield, Jarrod D and Chee, Yung En and Kelly, Clint D and Gurevitch, Jessica and Nakagawa, Shinichi},
doi = {10.1016/j.tree.2016.07.002},
issn = {1872-8383},
journal = {Trends Ecol. Evol.},
keywords = {P-hacking,confirmation bias,inflated effect size,preregistration,replication,selective reporting},
language = {English},
month = {sep},
number = {9},
pages = {711--719},
pmid = {27461041},
publisher = {Elsevier},
title = {{Transparency in Ecology and Evolution: Real Problems, Real Solutions.}},
url = {http://www.cell.com/article/S0169534716300957/fulltext},
volume = {31},
year = {2016}
}
@article{Fitzpatrick2012,
abstract = {Range expansion by native and exotic species will continue to be a major component of global change. Anticipating the potential effects of changes in species distributions requires models capable of forecasting population spread across realistic, heterogeneous landscapes and subject to spatiotemporal variability in habitat suitability. Several decades of theory and model development, as well as increased computing power and availability of fine-resolution GIS data, now make such models possible. Still unanswered, however, is the question of how well this new generation of dynamic models will anticipate range expansion. Here we develop a spatially explicit stochastic model that combines dynamic dispersal and population processes with fine-resolution maps characterizing spatiotemporal heterogeneity in climate and habitat to model range expansion of the hemlock woolly adelgid (HWA; Adelges tsugae). We parameterize this model using multiyear data sets describing population and dispersal dynamics of HWA and apply it to eastern North America over a 57-year period (1951–2008). To evaluate the model, the observed pattern of spread of HWA during this same period was compared to model predictions. Our model predicts considerable heterogeneity in the risk of HWA invasion across space and through time, and it suggests that spatiotemporal variation in winter temperature, rather than hemlock abundance, exerts a primary control on the spread of HWA. Although the simulations generally matched the observed current extent of the invasion of HWA and patterns of anisotropic spread, it did not correctly predict when HWA was observed to arrive in different geographic regions. We attribute differences between the modeled and observed dynamics to an inability to capture the timing and direction of long-distance dispersal events that substantially affected the ensuing pattern of spread.},
annote = {NULL},
author = {Fitzpatrick, Matthew C and Preisser, Evan L and Porter, Adam and Elkinton, Joseph and Ellison, Aaron M},
file = {:Users/hermes/Library/Application Support/Mendeley Desktop/Downloaded/Fitzpatrick et al. - 2012 - Modeling range dynamics in heterogeneous landscapes invasion of the hemlock woolly adelgid in eastern Nor(2).pdf:pdf},
journal = {Ecol. Appl.},
keywords = {Adelges tsugae,bioclimate envelopes,biological invasions,climate change,global warming,hemlock woolly adelgid,landscape epidemiology,metapopulation model,population dynamics,range shift,species distribution models,species migration,spread model},
number = {2},
pages = {472--486},
title = {{Modeling range dynamics in heterogeneous landscapes: invasion of the hemlock woolly adelgid in eastern North America}},
url = {http://harvardforest.fas.harvard.edu/sites/harvardforest.fas.harvard.edu/files/publications/pdfs/Fitzpatrick{\_}EcoApplications{\_}2012.pdf},
volume = {22},
year = {2012}
}
@article{Mcnutt,
annote = {NULL},
author = {Mcnutt, Marcia and Lehnert, Kerstin and Hanson, Brooks and Nosek, Brian A and Ellison, Aaron M and King, John Leslie},
file = {:Users/hermes/Library/Application Support/Mendeley Desktop/Downloaded/Mcnutt et al. - Unknown - INSIGHTS PERSPECTIVES.pdf:pdf},
title = {{INSIGHTS PERSPECTIVES}},
url = {http://harvardforest.fas.harvard.edu/sites/harvardforest.fas.harvard.edu/files/publications/pdfs/McNutt{\_}Science{\_}2016.pdf}
}
@article{Wilkinson2016,
annote = {NULL},
author = {Wilkinson, Mark D. and Dumontier, Michel and Aalbersberg, IJsbrand Jan and Appleton, Gabrielle and Axton, Myles and Baak, Arie and Blomberg, Niklas and Boiten, Jan-Willem and {da Silva Santos}, Luiz Bonino and Bourne, Philip E. and Bouwman, Jildau and Brookes, Anthony J. and Clark, Tim and Crosas, Merc{\`{e}} and Dillo, Ingrid and Dumon, Olivier and Edmunds, Scott and Evelo, Chris T. and Finkers, Richard and Gonzalez-Beltran, Alejandra and Gray, Alasdair J.G. and Groth, Paul and Goble, Carole and Grethe, Jeffrey S. and Heringa, Jaap and {'t Hoen}, Peter A.C and Hooft, Rob and Kuhn, Tobias and Kok, Ruben and Kok, Joost and Lusher, Scott J. and Martone, Maryann E. and Mons, Albert and Packer, Abel L. and Persson, Bengt and Rocca-Serra, Philippe and Roos, Marco and van Schaik, Rene and Sansone, Susanna-Assunta and Schultes, Erik and Sengstag, Thierry and Slater, Ted and Strawn, George and Swertz, Morris A. and Thompson, Mark and van der Lei, Johan and van Mulligen, Erik and Velterop, Jan and Waagmeester, Andra and Wittenburg, Peter and Wolstencroft, Katherine and Zhao, Jun and Mons, Barend},
doi = {10.1038/sdata.2016.18},
file = {:Users/hermes/Library/Application Support/Mendeley Desktop/Downloaded/Wilkinson et al. - 2016 - The FAIR Guiding Principles for scientific data management and stewardship.pdf:pdf},
issn = {2052-4463},
journal = {Sci. Data},
month = {mar},
pages = {160018},
publisher = {Nature Publishing Group},
title = {{The FAIR Guiding Principles for scientific data management and stewardship}},
url = {http://www.nature.com/articles/sdata201618},
volume = {3},
year = {2016}
}
@article{Baker2017,
annote = {NULL},
author = {Baker, Monya and Dolgin, Elie},
doi = {10.1038/541269a},
issn = {0028-0836},
journal = {Nature},
month = {jan},
number = {7637},
pages = {269--270},
title = {{Cancer reproducibility project releases first results}},
url = {http://www.nature.com/doifinder/10.1038/541269a},
volume = {541},
year = {2017}
}
@article{Parker2016,
abstract = {To make progress scientists need to know what other researchers have found and how they found it. However, transparency is often insufficient across much of ecology and evolution. Researchers often fail to report results and methods in detail sufficient to permit interpretation and meta-analysis, and many results go entirely unreported. Further, these unreported results are often a biased subset. Thus the conclusions we can draw from the published literature are themselves often biased and sometimes might be entirely incorrect. Fortunately there is a movement across empirical disciplines, and now within ecology and evolution, to shape editorial policies to better promote transparency. This can be done by either requiring more disclosure by scientists or by developing incentives to encourage disclosure.},
author = {Parker, Timothy H and Forstmeier, Wolfgang and Koricheva, Julia and Fidler, Fiona and Hadfield, Jarrod D and Chee, Yung En and Kelly, Clint D and Gurevitch, Jessica and Nakagawa, Shinichi},
doi = {10.1016/j.tree.2016.07.002},
issn = {1872-8383},
journal = {Trends Ecol. Evol.},
keywords = {P-hacking,confirmation bias,inflated effect size,preregistration,replication,selective reporting},
language = {English},
month = {sep},
number = {9},
pages = {711--719},
pmid = {27461041},
publisher = {Elsevier},
title = {{Transparency in Ecology and Evolution: Real Problems, Real Solutions.}},
url = {http://www.cell.com/article/S0169534716300957/fulltext},
volume = {31},
year = {2016}
}
@article{Michener2015,
annote = {NULL},
author = {Michener, William K.},
doi = {10.1016/j.ecoinf.2015.06.010},
issn = {15749541},
journal = {Ecol. Inform.},
month = {sep},
pages = {33--44},
title = {{Ecological data sharing}},
url = {http://linkinghub.elsevier.com/retrieve/pii/S1574954115001004},
volume = {29},
year = {2015}
}
@article{Brown2016,
annote = {NULL},
author = {Brown, Tim B and Hultine, Kevin R and Steltzer, Heidi and Denny, Ellen G and Denslow, Michael W and Granados, Joel and Henderson, Sandra and Moore, David and Nagai, Shin and SanClements, Michael and S{\'{a}}nchez-Azofeifa, Arturo and Sonnentag, Oliver and Tazik, David and Richardson, Andrew D},
doi = {10.1002/fee.1222},
file = {:Users/hermes/Library/Application Support/Mendeley Desktop/Downloaded/Brown et al. - 2016 - Using phenocams to monitor our changing Earth toward a global phenocam network.pdf:pdf},
issn = {15409295},
journal = {Front. Ecol. Environ.},
month = {mar},
number = {2},
pages = {84--93},
title = {{Using phenocams to monitor our changing Earth: toward a global phenocam network}},
url = {http://doi.wiley.com/10.1002/fee.1222},
volume = {14},
year = {2016}
}
@article{Parker2016,
abstract = {To make progress scientists need to know what other researchers have found and how they found it. However, transparency is often insufficient across much of ecology and evolution. Researchers often fail to report results and methods in detail sufficient to permit interpretation and meta-analysis, and many results go entirely unreported. Further, these unreported results are often a biased subset. Thus the conclusions we can draw from the published literature are themselves often biased and sometimes might be entirely incorrect. Fortunately there is a movement across empirical disciplines, and now within ecology and evolution, to shape editorial policies to better promote transparency. This can be done by either requiring more disclosure by scientists or by developing incentives to encourage disclosure.},
annote = {NULL},
author = {Parker, Timothy H and Forstmeier, Wolfgang and Koricheva, Julia and Fidler, Fiona and Hadfield, Jarrod D and Chee, Yung En and Kelly, Clint D and Gurevitch, Jessica and Nakagawa, Shinichi},
doi = {10.1016/j.tree.2016.07.002},
issn = {1872-8383},
journal = {Trends Ecol. Evol.},
keywords = {P-hacking,confirmation bias,inflated effect size,preregistration,replication,selective reporting},
language = {English},
month = {sep},
number = {9},
pages = {711--719},
pmid = {27461041},
publisher = {Elsevier},
title = {{Transparency in Ecology and Evolution: Real Problems, Real Solutions.}},
url = {http://www.cell.com/article/S0169534716300957/fulltext},
volume = {31},
year = {2016}
}
@article{Stanton-Geddes,
abstract = {Background: The distributions of species and their responses to climate change are in part determined by their thermal tolerances. However, little is known about how thermal tolerance evolves. To test whether evolutionary extension of thermal limits is accomplished through enhanced cellular stress response (enhanced response), constitutively elevated expression of protective genes (genetic assimilation) or a shift from damage resistance to passive mechanisms of thermal stability (tolerance), we conducted an analysis of the reactionome: the reaction norm for all genes in an organism's transcriptome measured across an experimental gradient. We characterized thermal reactionomes of two common ant species in the eastern U.S, the northern cool-climate Aphaenogaster picea and the southern warm-climate Aphaenogaster carolinensis, across 12 temperatures that spanned their entire thermal breadth. Results: We found that at least 2 {\%} of all genes changed expression with temperature. The majority of upregulation was specific to exposure to low temperatures. The cool-adapted A. picea induced expression of more genes in response to extreme temperatures than did A. carolinensis, consistent with the enhanced response hypothesis. In contrast, under high temperatures the warm-adapted A. carolinensis downregulated many of the genes upregulated in A. picea, and required more extreme temperatures to induce down-regulation in gene expression, consistent with the tolerance hypothesis. We found no evidence for a trade-off between constitutive and inducible gene expression as predicted by the genetic assimilation hypothesis. Conclusions: These results suggest that increases in upper thermal limits may require an evolutionary shift in response mechanism away from damage repair toward tolerance and prevention.},
annote = {NULL},
author = {Stanton-Geddes, John and Nguyen, Andrew and Chick, Lacy and Vincent, James and Vangala, Mahesh and Dunn, Robert R and Ellison, Aaron M and Sanders, Nathan J and Gotelli, Nicholas J and {Helms Cahan}, Sara},
doi = {10.1186/s12864-016-2466-z},
file = {:Users/hermes/Library/Application Support/Mendeley Desktop/Downloaded/Stanton-Geddes et al. - Unknown - Thermal reactionomes reveal divergent responses to thermal extremes in warm and cool-climate ant speci.pdf:pdf},
keywords = {Aphaenogaster,Gene expression,Plasticity,Reactionome,Transcriptome Background},
title = {{Thermal reactionomes reveal divergent responses to thermal extremes in warm and cool-climate ant species}}
}
@article{Csiszar2016,
author = {Csiszar, Alex},
doi = {10.1038/532306a},
issn = {0028-0836},
journal = {Nature},
month = {apr},
number = {7599},
pages = {306--308},
title = {{Peer review: Troubled from the start}},
url = {http://www.nature.com/doifinder/10.1038/532306a},
volume = {532},
year = {2016}
}
@article{Stodden2018,
abstract = {A key component of scientific communication is sufficient information for other researchers in the field to reproduce published findings. For computational and data-enabled research, this has often been interpreted to mean making available the raw data from which results were generated, the computer code that generated the findings, and any additional information needed such as workflows and input parameters. Many journals are revising author guidelines to include data and code availability. This work evaluates the effectiveness of journal policy that requires the data and code necessary for reproducibility be made available postpublication by the authors upon request. We assess the effectiveness of such a policy by (i) requesting data and code from authors and (ii) attempting replication of the published findings. We chose a random sample of 204 scientific papers published in the journalScienceafter the implementation of their policy in February 2011. We found that we were able to obtain artifacts from 44{\%} of our sample and were able to reproduce the findings for 26{\%}. We find this policy-author remission of data and code postpublication upon request-an improvement over no policy, but currently insufficient for reproducibility.},
author = {Stodden, Victoria and Seiler, Jennifer and Ma, Zhaokun},
doi = {10.1073/pnas.1708290115},
file = {:Users/hermes/Library/Application Support/Mendeley Desktop/Downloaded/Stodden, Seiler, Ma - 2018 - An empirical analysis of journal policy effectiveness for computational reproducibility.pdf:pdf},
issn = {1091-6490},
journal = {Proc. Natl. Acad. Sci. U. S. A.},
keywords = {code access,data access,open science,reproducibility policy,reproducible research},
month = {mar},
number = {11},
pages = {2584--2589},
pmid = {29531050},
publisher = {National Academy of Sciences},
title = {{An empirical analysis of journal policy effectiveness for computational reproducibility.}},
url = {http://www.ncbi.nlm.nih.gov/pubmed/29531050},
volume = {115},
year = {2018}
}
@article{Santori2016,
author = {Santori, Gregorio},
doi = {10.1038/535355b},
issn = {0028-0836},
journal = {Nature},
month = {jul},
number = {7612},
pages = {355--355},
publisher = {Nature Research},
title = {{Research papers: Journals should drive data reproducibility}},
url = {http://www.nature.com/doifinder/10.1038/535355b},
volume = {535},
year = {2016}
}
@article{Santori2016a,
author = {Santori, Gregorio},
doi = {10.1038/535355b},
issn = {0028-0836},
journal = {Nature},
month = {jul},
number = {7612},
pages = {355--355},
publisher = {Nature Research},
title = {{Research papers: Journals should drive data reproducibility}},
url = {http://www.nature.com/doifinder/10.1038/535355b},
volume = {535},
year = {2016}
}
@article{Brown2016,
annote = {NULL},
author = {Brown, Tim B and Hultine, Kevin R and Steltzer, Heidi and Denny, Ellen G and Denslow, Michael W and Granados, Joel and Henderson, Sandra and Moore, David and Nagai, Shin and SanClements, Michael and S{\'{a}}nchez-Azofeifa, Arturo and Sonnentag, Oliver and Tazik, David and Richardson, Andrew D},
doi = {10.1002/fee.1222},
file = {:Users/hermes/Library/Application Support/Mendeley Desktop/Downloaded/Brown et al. - 2016 - Using phenocams to monitor our changing Earth toward a global phenocam network.pdf:pdf},
issn = {15409295},
journal = {Front. Ecol. Environ.},
month = {mar},
number = {2},
pages = {84--93},
title = {{Using phenocams to monitor our changing Earth: toward a global phenocam network}},
url = {http://doi.wiley.com/10.1002/fee.1222},
volume = {14},
year = {2016}
}
@article{Peng2015,
author = {Peng, Roger},
doi = {10.1111/j.1740-9713.2015.00827.x},
file = {:Users/hermes/Library/Application Support/Mendeley Desktop/Downloaded/Peng - 2015 - The reproducibility crisis in science A statistical counterattack.pdf:pdf},
issn = {17409705},
journal = {Significance},
month = {jun},
number = {3},
pages = {30--32},
title = {{The reproducibility crisis in science: A statistical counterattack}},
url = {http://doi.wiley.com/10.1111/j.1740-9713.2015.00827.x},
volume = {12},
year = {2015}
}
@article{Allison2016,
author = {Allison, David B. and Brown, Andrew W. and George, Brandon J. and Kaiser, Kathryn A.},
doi = {10.1038/530027a},
issn = {0028-0836},
journal = {Nature},
month = {feb},
number = {7588},
pages = {27--29},
title = {{Reproducibility: A tragedy of errors}},
url = {http://www.nature.com/doifinder/10.1038/530027a},
volume = {530},
year = {2016}
}
@article{Ellison2010,
annote = {NULL},
author = {Ellison, Aaron M},
file = {:Users/hermes/Library/Application Support/Mendeley Desktop/Downloaded/Ellison - 2010 - Repeatability and transparency in ecological research.pdf:pdf},
journal = {Ecology},
number = {9},
pages = {2536--2539},
title = {{Repeatability and transparency in ecological research}},
url = {http://harvardforest.fas.harvard.edu/sites/harvardforest.fas.harvard.edu/files/ellison-pubs/2010/ellison{\_}2010{\_}ecology.pdf},
volume = {91},
year = {2010}
}
@article{Mcnutt,
annote = {NULL},
author = {Mcnutt, Marcia and Lehnert, Kerstin and Hanson, Brooks and Nosek, Brian A and Ellison, Aaron M and King, John Leslie},
file = {:Users/hermes/Library/Application Support/Mendeley Desktop/Downloaded/Mcnutt et al. - Unknown - INSIGHTS PERSPECTIVES.pdf:pdf},
title = {{INSIGHTS PERSPECTIVES}},
url = {http://harvardforest.fas.harvard.edu/sites/harvardforest.fas.harvard.edu/files/publications/pdfs/McNutt{\_}Science{\_}2016.pdf}
}
@article{Hirsch1996,
abstract = {Weekly values of the net 03 production efficiency (OPE), defined as the net number of 03 molecules produced per molecule of NOx (NO + NO2) consumed, are estimated from a 1990-1994 record of 03, NOx, NOy, CO, and C2H 2 concentrations at Harvard Forest, Massachusetts. The OPE is inferred from the slope AO3/A(NOy-NOx) of the linear regression between 03 and NOy-NO x concentrations (NOy is the sum of NOx and its oxidation products); and alternatively from the slopes AO3/ACO and AO3/AC2H2 multiplied by regional estimates of the CO/NO • and C2H2/NOx emission ratios. The mean OPE values inferred from AO3/A(NOy-NOx) are 3-5 times higher than those inferred from AO3/ACO or AO3/AC 2H2; the discrepancy may be due to the effects of HNO3 and 03 deposition and also to uncertainties in the CO/NOx and C2H2/NOx emission ratios. The relative seasonal trends of the OPE derived from AO3/A(NOy-NOx), AO3/ACO, and AO3/AC2H 2 are, however, similar. Thus AO3/A(NOy-NOx) increases from about 4 reel/reel in May to 8 mol/mol in June-July, and gradually decreases back to 4 reel/reel by early October. The sharp rise of the OPE from May to June is attributed to onset of emission of the biogcnic hydrocarbon isoprene. The decline from July to October is attributed to decreases in isoprcnc emission and in solar radiation. The 03 background at Harvard Forest, defined by the y intercept of the 03 versus NOy-NOx regression line, decreases from 40 ppbv in May to 25 ppbv in September, consistent with observations at remote sites in northern midlatitudes. The seasonal trend in the background explains why mean 03 concentrations at Harvard Forest peak in May-June even though the OPE peaks in June-July.},
annote = {NULL},
author = {Hirsch, Adam I and Munger, @bullet J William and Jacob, Daniel J and Horowitz, Larry W and Goldstein, Allen H},
file = {:Users/hermes/Library/Application Support/Mendeley Desktop/Downloaded/Hirsch et al. - 1996 - Seasonal variation of the ozone production efficiency per unit NOx at Harvard Forest, Massachusetts(2).pdf:pdf},
journal = {J. Geophys. Res.},
number = {20},
pages = {659--12},
title = {{Seasonal variation of the ozone production efficiency per unit NOx at Harvard Forest, Massachusetts}},
url = {http://harvardforest.fas.harvard.edu/sites/harvardforest.fas.harvard.edu/files/publications/pdfs/Hirsch{\_}JGeophysicalResearch{\_}1996.pdf},
volume = {101666},
year = {1996}
}
@article{Stanton-Geddes,
abstract = {Background: The distributions of species and their responses to climate change are in part determined by their thermal tolerances. However, little is known about how thermal tolerance evolves. To test whether evolutionary extension of thermal limits is accomplished through enhanced cellular stress response (enhanced response), constitutively elevated expression of protective genes (genetic assimilation) or a shift from damage resistance to passive mechanisms of thermal stability (tolerance), we conducted an analysis of the reactionome: the reaction norm for all genes in an organism's transcriptome measured across an experimental gradient. We characterized thermal reactionomes of two common ant species in the eastern U.S, the northern cool-climate Aphaenogaster picea and the southern warm-climate Aphaenogaster carolinensis, across 12 temperatures that spanned their entire thermal breadth. Results: We found that at least 2 {\%} of all genes changed expression with temperature. The majority of upregulation was specific to exposure to low temperatures. The cool-adapted A. picea induced expression of more genes in response to extreme temperatures than did A. carolinensis, consistent with the enhanced response hypothesis. In contrast, under high temperatures the warm-adapted A. carolinensis downregulated many of the genes upregulated in A. picea, and required more extreme temperatures to induce down-regulation in gene expression, consistent with the tolerance hypothesis. We found no evidence for a trade-off between constitutive and inducible gene expression as predicted by the genetic assimilation hypothesis. Conclusions: These results suggest that increases in upper thermal limits may require an evolutionary shift in response mechanism away from damage repair toward tolerance and prevention.},
annote = {NULL},
author = {Stanton-Geddes, John and Nguyen, Andrew and Chick, Lacy and Vincent, James and Vangala, Mahesh and Dunn, Robert R and Ellison, Aaron M and Sanders, Nathan J and Gotelli, Nicholas J and {Helms Cahan}, Sara},
doi = {10.1186/s12864-016-2466-z},
file = {:Users/hermes/Library/Application Support/Mendeley Desktop/Downloaded/Stanton-Geddes et al. - Unknown - Thermal reactionomes reveal divergent responses to thermal extremes in warm and cool-climate ant speci.pdf:pdf},
keywords = {Aphaenogaster,Gene expression,Plasticity,Reactionome,Transcriptome Background},
title = {{Thermal reactionomes reveal divergent responses to thermal extremes in warm and cool-climate ant species}}
}
@article{Boose,
abstract = {At the dawn of the 21st century, environmental scientists are collecting more data more rapidly than at any time in the past. Nowhere is this change more evident than in the advent of sensor networks able to collect and process (in real time) simultaneous measurements over broad areas and at high sampling rates. At the same time there has been great progress in the development of standards, methods, and tools for data analysis and synthesis, including a new standard for descriptive metadata for ecological datasets (Ecological Metadata Language) and new workflow tools that help scientists to assemble datasets and to diagram, record, and execute analyses. However these developments (important as they are) are not yet sufficient to guarantee the reliability of datasets created by a scientific process — the complex activity that scientists carry out in order to create a dataset. We define a dataset to be reliable when the scientific process used to create it is (1) reproducible and (2) analyzable for potential defects. To address this problem we propose the use of an analytic web, a formal representation of a scientific process that consists of three coordinated graphs (a data-flow graph, a dataset-derivation graph, and a process-derivation graph) originally developed for use in software engineering. An analytic web meets the two key requirements for ensuring dataset reliability: (1) a complete audit trail of all artifacts (e.g., datasets, code, models) used or created in the execution of the scientific process that created the dataset, and (2) detailed process metadata that precisely describe all sub-processes of the scientific process. Construction of such metadata requires the semantic features of a high-level process definition language. In this paper we illustrate the use of an analytic web to represent the scientific process of constructing estimates of ecosystem water flux from data gathered by a complex, real-time multi-sensor network. We use Little-JIL, a high-level process definition language, to precisely and accurately capture the analytical processes involved. We believe that incorporation of this approach into existing tools and evolving metadata specifications (such as EML) will yield significant benefits to science. These benefits include: complete and accurate representations of scientific processes; support for rigorous evaluation of such processes for logical and statistical errors and for propagation of measurement error; and assurance of dataset reliability for developing sound models and forecasts of environmental change.},
annote = {NULL},
author = {Boose, Emery R and Ellison, Aaron M and Osterweil, Leon J and Clarke, Lori A and Podorozhny, Rodion and Hadley, Julian L and Wise, Alexander and Foster, David R},
doi = {10.1016/j.ecoinf.2007.07.006},
file = {:Users/hermes/Library/Application Support/Mendeley Desktop/Downloaded/Boose et al. - Unknown - Author's personal copy Ensuring reliable datasets for environmental models and forecasts.pdf:pdf},
keywords = {Analytic web,Little-JIL,Metadata,Process,Sensor network,Water flux},
number = {2},
pages = {3--7},
title = {{Author's personal copy Ensuring reliable datasets for environmental models and forecasts}},
url = {http://harvardforest.fas.harvard.edu/sites/harvardforest.fas.harvard.edu/files/ellison-pubs/2007/boose{\_}etal{\_}2007{\_}EI.pdf},
volume = {2}
}
@article{Wilkinson2016b,
author = {Wilkinson, Mark D. and Dumontier, Michel and Aalbersberg, IJsbrand Jan and Appleton, Gabrielle and Axton, Myles and Baak, Arie and Blomberg, Niklas and Boiten, Jan-Willem and {da Silva Santos}, Luiz Bonino and Bourne, Philip E. and Bouwman, Jildau and Brookes, Anthony J. and Clark, Tim and Crosas, Merc{\`{e}} and Dillo, Ingrid and Dumon, Olivier and Edmunds, Scott and Evelo, Chris T. and Finkers, Richard and Gonzalez-Beltran, Alejandra and Gray, Alasdair J.G. and Groth, Paul and Goble, Carole and Grethe, Jeffrey S. and Heringa, Jaap and {'t Hoen}, Peter A.C and Hooft, Rob and Kuhn, Tobias and Kok, Ruben and Kok, Joost and Lusher, Scott J. and Martone, Maryann E. and Mons, Albert and Packer, Abel L. and Persson, Bengt and Rocca-Serra, Philippe and Roos, Marco and van Schaik, Rene and Sansone, Susanna-Assunta and Schultes, Erik and Sengstag, Thierry and Slater, Ted and Strawn, George and Swertz, Morris A. and Thompson, Mark and van der Lei, Johan and van Mulligen, Erik and Velterop, Jan and Waagmeester, Andra and Wittenburg, Peter and Wolstencroft, Katherine and Zhao, Jun and Mons, Barend},
doi = {10.1038/sdata.2016.18},
file = {:Users/hermes/Library/Application Support/Mendeley Desktop/Downloaded/Wilkinson et al. - 2016 - The FAIR Guiding Principles for scientific data management and stewardship.pdf:pdf},
issn = {2052-4463},
journal = {Sci. Data},
month = {mar},
pages = {160018},
publisher = {Nature Publishing Group},
title = {{The FAIR Guiding Principles for scientific data management and stewardship}},
url = {http://www.nature.com/articles/sdata201618},
volume = {3},
year = {2016}
}
@article{Fitzpatrick2012,
abstract = {Range expansion by native and exotic species will continue to be a major component of global change. Anticipating the potential effects of changes in species distributions requires models capable of forecasting population spread across realistic, heterogeneous landscapes and subject to spatiotemporal variability in habitat suitability. Several decades of theory and model development, as well as increased computing power and availability of fine-resolution GIS data, now make such models possible. Still unanswered, however, is the question of how well this new generation of dynamic models will anticipate range expansion. Here we develop a spatially explicit stochastic model that combines dynamic dispersal and population processes with fine-resolution maps characterizing spatiotemporal heterogeneity in climate and habitat to model range expansion of the hemlock woolly adelgid (HWA; Adelges tsugae). We parameterize this model using multiyear data sets describing population and dispersal dynamics of HWA and apply it to eastern North America over a 57-year period (1951–2008). To evaluate the model, the observed pattern of spread of HWA during this same period was compared to model predictions. Our model predicts considerable heterogeneity in the risk of HWA invasion across space and through time, and it suggests that spatiotemporal variation in winter temperature, rather than hemlock abundance, exerts a primary control on the spread of HWA. Although the simulations generally matched the observed current extent of the invasion of HWA and patterns of anisotropic spread, it did not correctly predict when HWA was observed to arrive in different geographic regions. We attribute differences between the modeled and observed dynamics to an inability to capture the timing and direction of long-distance dispersal events that substantially affected the ensuing pattern of spread.},
annote = {NULL},
author = {Fitzpatrick, Matthew C and Preisser, Evan L and Porter, Adam and Elkinton, Joseph and Ellison, Aaron M},
file = {:Users/hermes/Library/Application Support/Mendeley Desktop/Downloaded/Fitzpatrick et al. - 2012 - Modeling range dynamics in heterogeneous landscapes invasion of the hemlock woolly adelgid in eastern Nor(2).pdf:pdf},
journal = {Ecol. Appl.},
keywords = {Adelges tsugae,bioclimate envelopes,biological invasions,climate change,global warming,hemlock woolly adelgid,landscape epidemiology,metapopulation model,population dynamics,range shift,species distribution models,species migration,spread model},
number = {2},
pages = {472--486},
title = {{Modeling range dynamics in heterogeneous landscapes: invasion of the hemlock woolly adelgid in eastern North America}},
url = {http://harvardforest.fas.harvard.edu/sites/harvardforest.fas.harvard.edu/files/publications/pdfs/Fitzpatrick{\_}EcoApplications{\_}2012.pdf},
volume = {22},
year = {2012}
}