cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.3563847
title: Supplement 1. R script containing all data analyses, and functional, phylogenetic, and taxonomic trees in Newick format.

description: File List ChesMMAP_Analysis.R (MD5: 76c1bf2a66778c549c104f1f981f3344) Functional_dendrogram.txt (MD5: 150ae02926a1d4019fbbb62a8389622f) Phylogenetic_tree.txt (MD5: 86896bc31f31d11d3fdf77f33b3ddb62) Taxonomic_tree.txt (MD5: 4dcd4fa2bf8eb6db567b7a1ff7dcb236) Description The code included in ChesMMAP Analysis.R reports all analyses run in the paper, including building functional, phylogenetic, and taxonomic trees, kriging interpolation, and construction of generalized additive models. The three text files include the functional, phylogenetic, and taxonomic trees in Newick format.
DOI: 10.6084/m9.figshare.3563847.v1
title: Supplement 1. R script containing all data analyses, and functional, phylogenetic, and taxonomic trees in Newick format.

description: File List ChesMMAP_Analysis.R (MD5: 76c1bf2a66778c549c104f1f981f3344) Functional_dendrogram.txt (MD5: 150ae02926a1d4019fbbb62a8389622f) Phylogenetic_tree.txt (MD5: 86896bc31f31d11d3fdf77f33b3ddb62) Taxonomic_tree.txt (MD5: 4dcd4fa2bf8eb6db567b7a1ff7dcb236) Description The code included in ChesMMAP Analysis.R reports all analyses run in the paper, including building functional, phylogenetic, and taxonomic trees, kriging interpolation, and construction of generalized additive models. The three text files include the functional, phylogenetic, and taxonomic trees in Newick format.
DOI: 10.6084/m9.figshare.3563844
title: Supplement 1. R scripts for conducting statistical analysis described in the main text.

description: File List stats.R (MD5: 0d325f87062962d7fe1f60dea39a3a9b) Description The code included in stats.R gives example of how to conduct the statistical analysis conducted in the main text.
DOI: 10.6084/m9.figshare.3563844.v1
title: Supplement 1. R scripts for conducting statistical analysis described in the main text.

description: File List stats.R (MD5: 0d325f87062962d7fe1f60dea39a3a9b) Description The code included in stats.R gives example of how to conduct the statistical analysis conducted in the main text.
DOI: 10.6084/m9.figshare.3563838
title: Supplement 1. Annotated R code to run simulation model used to predict responses of multi-species communities to varying disturbance intensity and frequency.

description: File List simulations.R (MD5: 1d6fbd0622c58e9a3825206f3b079638) Description The code included in simulations.R creates a function called sim.mod that runs the simulation model described in the main text. The resulting output is the number of species in the estimated community called “Richness” and distinct from the total potential number of species, which is a constant in the model. User-supplied disturbance intensity and frequency are also reported.
DOI: 10.6084/m9.figshare.3563838.v1
title: Supplement 1. Annotated R code to run simulation model used to predict responses of multi-species communities to varying disturbance intensity and frequency.

description: File List simulations.R (MD5: 1d6fbd0622c58e9a3825206f3b079638) Description The code included in simulations.R creates a function called sim.mod that runs the simulation model described in the main text. The resulting output is the number of species in the estimated community called “Richness” and distinct from the total potential number of species, which is a constant in the model. User-supplied disturbance intensity and frequency are also reported.
DOI: 10.6084/m9.figshare.3563835
title: Supplement 1. Tables listing all captured moth species, known host-plant species, and environmental and ecological values for the twenty trap sites utilized in this study.

description: File List CapturedMothSpecies.csv (MD5: 8e65af7c2839185069ff260b90a6ed2c) MothTrapCharacteristics.csv (MD5: 2fb4f42be8de31d1f010b11ba94b3726) KnownHostPlantPresence.csv (MD5: 355103116d8bd572919f0d46fe183683) Description The file Captured MothSpecies.csv provides abundances for all moth species captured in each trap by year. MothTrapCharacteristics.csv lists all environmental characteristics and ecological indices used in the analysis of the moth communities. KnownHostPlantPresence.csv lists the presence/absence all known host-plants within 100 m of each trap location.
DOI: 10.6084/m9.figshare.3563835.v1
title: Supplement 1. Tables listing all captured moth species, known host-plant species, and environmental and ecological values for the twenty trap sites utilized in this study.

description: File List CapturedMothSpecies.csv (MD5: 8e65af7c2839185069ff260b90a6ed2c) MothTrapCharacteristics.csv (MD5: 2fb4f42be8de31d1f010b11ba94b3726) KnownHostPlantPresence.csv (MD5: 355103116d8bd572919f0d46fe183683) Description The file Captured MothSpecies.csv provides abundances for all moth species captured in each trap by year. MothTrapCharacteristics.csv lists all environmental characteristics and ecological indices used in the analysis of the moth communities. KnownHostPlantPresence.csv lists the presence/absence all known host-plants within 100 m of each trap location.
DOI: 10.6084/m9.figshare.3563832
title: Supplement 1. An R-script and data file for the analysis conducted in the main paper.

description: File List Data.txt (md5: 98f606cc561c67f3c31fffc54687162b)<br> CT_Method_(User_Version).r (md5: 4b9125ece816c25f69503000707f1031)<br> Description Data.txt – A data set containing species abundances for <i>Pseudo-nitzschia australis</i> and <i>Prorocentrum micans</i> along with surface water temperatures, collected at the Scripps Institute of Oceanography station for the time period 1930 to 1937. No column headers are given in the file for coding purposes, however the columns, in order, correspond to: the day number on which observations were made, the log-abundance for <i>Pseudo-nitzschia australis</i>, the log abundance for <i>Prorocentrum micans</i> and finally the surface temperature. CT_Method_(User_Version).r – R source code of approximately 475 lines (comments included) for implementation of the methodology introduced in the paper. The code is set to run the analysis presented in the paper. The R code should run so long as Data.txt is kept in the current R working directory. Comments in the script indicate, where necessary, what the applicable lines of code do and how they pertain to the main paper. MCMC output is automatically analyzed and figures are saved in .pdf format in the working directory. It is advised that an open source editor such as Tinn-R be used in order to aid readability of the code.
DOI: 10.6084/m9.figshare.3563832.v1
title: Supplement 1. An R-script and data file for the analysis conducted in the main paper.

description: File List Data.txt (md5: 98f606cc561c67f3c31fffc54687162b)<br> CT_Method_(User_Version).r (md5: 4b9125ece816c25f69503000707f1031)<br> Description Data.txt – A data set containing species abundances for <i>Pseudo-nitzschia australis</i> and <i>Prorocentrum micans</i> along with surface water temperatures, collected at the Scripps Institute of Oceanography station for the time period 1930 to 1937. No column headers are given in the file for coding purposes, however the columns, in order, correspond to: the day number on which observations were made, the log-abundance for <i>Pseudo-nitzschia australis</i>, the log abundance for <i>Prorocentrum micans</i> and finally the surface temperature. CT_Method_(User_Version).r – R source code of approximately 475 lines (comments included) for implementation of the methodology introduced in the paper. The code is set to run the analysis presented in the paper. The R code should run so long as Data.txt is kept in the current R working directory. Comments in the script indicate, where necessary, what the applicable lines of code do and how they pertain to the main paper. MCMC output is automatically analyzed and figures are saved in .pdf format in the working directory. It is advised that an open source editor such as Tinn-R be used in order to aid readability of the code.
DOI: 10.6084/m9.figshare.3563826
title: Supplement 1. R script file to run spotted knapweed density model simulations for each scenario.

description: File List knapweed_models.R (MD5: 684ed8ec5450f03f796e9313d2218bf9) Description The code included in knapweed_models.R to run model simulations for models discussed in paper. It contains a function to run the model and a function to choose which model scenario to use to parameterize the model. The script also contains permanent transect data to plot against model predictions. Missing data is denoted as NA.
DOI: 10.6084/m9.figshare.3563826.v1
title: Supplement 1. R script file to run spotted knapweed density model simulations for each scenario.

description: File List knapweed_models.R (MD5: 684ed8ec5450f03f796e9313d2218bf9) Description The code included in knapweed_models.R to run model simulations for models discussed in paper. It contains a function to run the model and a function to choose which model scenario to use to parameterize the model. The script also contains permanent transect data to plot against model predictions. Missing data is denoted as NA.
DOI: 10.6084/m9.figshare.3563823
title: Supplement 1. Effect sizes and species traits used in the species abundance meta-analysis.

description: File List species_effect_sizes.csv (MD5: 814d3f03927e6dcb0a9cf28c7ea4b5da) Description The file, species effect sizes.csv, presents data utilized in the species abundance meta-analysis. Included are details on the publications used for the analysis (record ‘ID’, ‘Author’, ‘Year’, ‘City’, ‘Country’). Species names are given as per the original publication (‘Given.Name’) along with any modifications to the name due to spelling errors, synonyms, or taxonomic revisions (‘Binomial.Accepted’). All names were verified using Lorenz (2005); an asterisk in the Binomial. Accepted column indicates names that were not listed as accepted names in Lorenz (2005). ‘Subfamily,’ ‘Tribe,’ and ‘Subtribe’ are given, again using Lorenz (2005). Ecological traits were recorded at the species-level: ‘Body.Size’ (median length, in mm), ‘Wing.Morph’, ‘Habitat.Specific’ (listing particular details on habitat use), ‘Habitat.Category’ (used for the analysis), and ‘Trophic.Level.’ The effect size used in the analysis is given as the log response ratio (‘LRR’).
DOI: 10.6084/m9.figshare.3563820
title: Supplement 1. BUGS code of the fitted model.

description: File List model.txt (MD5: ac128bed81ade7038df84eb14e3990dd) Description The code included in model.txt was used to fit the hierarchical Bayesian model described in the main text using WinBUGS.
DOI: 10.6084/m9.figshare.3563820.v1
title: Supplement 1. BUGS code of the fitted model.

description: File List model.txt (MD5: ac128bed81ade7038df84eb14e3990dd) Description The code included in model.txt was used to fit the hierarchical Bayesian model described in the main text using WinBUGS.
DOI: 10.6084/m9.figshare.3563817
title: Supplement 1. R code to implement mortality risk analysis for North Atlantic right whales as a function of vessel speed.

description: File List RightWhale.r (MD5: ce849c7999f214f7c4b2c22717d5c69a)Description RightWhale.R – R script to conduct mortality risk analysis for North Atlantic right whales.
DOI: 10.6084/m9.figshare.3563817.v1
title: Supplement 1. R code to implement mortality risk analysis for North Atlantic right whales as a function of vessel speed.

description: File List RightWhale.r (MD5: ce849c7999f214f7c4b2c22717d5c69a)Description RightWhale.R – R script to conduct mortality risk analysis for North Atlantic right whales.
DOI: 10.6084/m9.figshare.3563814
title: Supplement 1. R package (Windows and cross-platform) including all data and analysis.

description: File List foRthood.zip (MD5: 52fd9a6dc2b8f59901a40e602de70668) foRthood.tar.gz (MD5: da915abaed3c94d3d04bd1f08eeccc65) Description foRthood.zip – Windows binary package and documentation for the R package containing all data and analysis foRthood.tar.gz – Cross-platform source code and documentation for the R package containing all data and analysis
DOI: 10.6084/m9.figshare.3563811
title: Supplement 1. R script for species and community distribution models described in the main text.

description: File List Rcode.R (MD5: 7c9cb0c49550b2de57b07c6368df79c5) Description The code in Rcode.R executes the species and community distribution models described in the main text. Accompanying data files can be downloaded online from the Harvard Forest Data Archives at http://harvardforest.fas.harvard.edu/data-archives.
DOI: 10.6084/m9.figshare.3563811.v1
title: Supplement 1. R script for species and community distribution models described in the main text.

description: File List Rcode.R (MD5: 7c9cb0c49550b2de57b07c6368df79c5) Description The code in Rcode.R executes the species and community distribution models described in the main text. Accompanying data files can be downloaded online from the Harvard Forest Data Archives at http://harvardforest.fas.harvard.edu/data-archives.
DOI: 10.6084/m9.figshare.3563808
title: Supplement 1. Rainfall sample data including the measured stable isotope values, rainfall amounts, collection dates and times, and meteorological data at the collection site.

description: File List tableS1.csv (MD5: 306d75dd4671708b43a7f0157d0de694) Description This file provides the original data for the rainfall samples (tableS1.csv) that forms the basis of the analysis presented in the main article. This supplemental data is provided here to give additional detail to the analysis. Variable descriptions are in Supplement 2, column 2. Additionally, for the “Season” variable (tableS1.csv, column 2), “D” refers to the Dry Season, “L” to the Long Rains, “C” to the Continental Rains, and “S” to Short Rains (see the main text for the season cutoff dates). The date and time provided for each rain sample (tableS1.csv, columns 3 through 6, in local time for Kenya which is GMT +3) represents the first hour of the rain event and the “Event Duration [hr]” column provides the length of the rain event represented by the each sample. The “NAN” flag appears where no data is available. In Supplement 2, the values represent the Pearson correlation coefficient for the corresponding row and column variables, and an absolute value greater than 0.31 is statistically significant (<i>P</i> &lt; 0.05, two-tailed).
DOI: 10.6084/m9.figshare.3563808.v1
title: Supplement 1. Rainfall sample data including the measured stable isotope values, rainfall amounts, collection dates and times, and meteorological data at the collection site.

description: File List tableS1.csv (MD5: 306d75dd4671708b43a7f0157d0de694) Description This file provides the original data for the rainfall samples (tableS1.csv) that forms the basis of the analysis presented in the main article. This supplemental data is provided here to give additional detail to the analysis. Variable descriptions are in Supplement 2, column 2. Additionally, for the “Season” variable (tableS1.csv, column 2), “D” refers to the Dry Season, “L” to the Long Rains, “C” to the Continental Rains, and “S” to Short Rains (see the main text for the season cutoff dates). The date and time provided for each rain sample (tableS1.csv, columns 3 through 6, in local time for Kenya which is GMT +3) represents the first hour of the rain event and the “Event Duration [hr]” column provides the length of the rain event represented by the each sample. The “NAN” flag appears where no data is available. In Supplement 2, the values represent the Pearson correlation coefficient for the corresponding row and column variables, and an absolute value greater than 0.31 is statistically significant (<i>P</i> &lt; 0.05, two-tailed).
DOI: 10.6084/m9.figshare.3563805
title: Supplement 2. A matrix of correlation coefficients for variables considered in the construction of the RIST and RISR regression models.

description: File List tableS2.csv (MD5: d459597c2c8623761591c062858f2821) Description This file provides the matrix of correlation coefficients that guided the selection of variables for the linear regression analysis. This supplemental data is provided here to give additional detail to the analysis. Variable descriptions are in column 2. In tableS2.csv, the values represent the Pearson correlation coefficient for the corresponding row and column variables, and an absolute value greater than 0.31 is statistically significant (<i>P</i> &lt; 0.05, two-tailed).
DOI: 10.6084/m9.figshare.3563805.v1
title: Supplement 2. A matrix of correlation coefficients for variables considered in the construction of the RIST and RISR regression models.

description: File List tableS2.csv (MD5: d459597c2c8623761591c062858f2821) Description This file provides the matrix of correlation coefficients that guided the selection of variables for the linear regression analysis. This supplemental data is provided here to give additional detail to the analysis. Variable descriptions are in column 2. In tableS2.csv, the values represent the Pearson correlation coefficient for the corresponding row and column variables, and an absolute value greater than 0.31 is statistically significant (<i>P</i> &lt; 0.05, two-tailed).
DOI: 10.6084/m9.figshare.3563802
title: Supplement 1. R script and resulting output for estimating the potential surface described in Eq. 3 with data on elk during ATV treatment days.

description: File List Rcode.txt (MD5: 3a4be4656cbeaf094a3f6d4e6dfebba6) Description The R-code included shows how the linear mixed model lme may be used to estimate the coefficients in Eq. 8 in the main text necessary for evaluating the potential surface in Eq. 7 with results given in Figs. 5 and 6.
DOI: 10.6084/m9.figshare.3563799
title: Supplement 1. Water isotope data from Konza bison project.

description: File List bison_data_for_supplemental.csv (MD5: 862a49c8dddac2180bc320d3647a5ea8) – Water isotope data collected from bison fecal samples, streamwater samples, and precipitation samples from Jan 2010 to March 2011 on the Konza Prairie, KS USA. Description Sample_ID_bison refers to the unique animal ID for each animal in the Konza herd<br> Sample_date refers to the collection date of bison fecal samples<br> Days_since_rain refers to the time (days) between sample collection and the last previous rainfall event on site<br> Year_born refers to year of animal birth. ‘UNK’ signifies an unknown birth year<br> Gender is animal gender<br> Age_class refers to the animal’s age class at the date of sample collection.<br> Location_collected refers to the Konza watershed where the sample was collected. UNK signifies that watershed ID was not recorded when collected.<br> dD is the hydrogen isotopic ratio of the bison fecal water sample<br> d18o is the oxygen isotopic ratio of the bison fecal water sample<br> sample_date_stream is the date of sampling from the Konza stream ‘King’s Creek’.<br> d18O_stream is the oxygen isotopic ratio of water from the stream<br> dD_stream is the hydrogen isotopic ratio of water from the stream<br> sample_date_precip is the date of sampling of precipitation from the Konza headquarters station<br> dD_precip is the hydrogen isotopic ratio of precipitation<br> d18O_precip is the oxygen isotopic ratio of precipitation
DOI: 10.6084/m9.figshare.3563799.v1
title: Supplement 1. Water isotope data from Konza bison project.

description: File List bison_data_for_supplemental.csv (MD5: 862a49c8dddac2180bc320d3647a5ea8) – Water isotope data collected from bison fecal samples, streamwater samples, and precipitation samples from Jan 2010 to March 2011 on the Konza Prairie, KS USA. Description Sample_ID_bison refers to the unique animal ID for each animal in the Konza herd<br> Sample_date refers to the collection date of bison fecal samples<br> Days_since_rain refers to the time (days) between sample collection and the last previous rainfall event on site<br> Year_born refers to year of animal birth. ‘UNK’ signifies an unknown birth year<br> Gender is animal gender<br> Age_class refers to the animal’s age class at the date of sample collection.<br> Location_collected refers to the Konza watershed where the sample was collected. UNK signifies that watershed ID was not recorded when collected.<br> dD is the hydrogen isotopic ratio of the bison fecal water sample<br> d18o is the oxygen isotopic ratio of the bison fecal water sample<br> sample_date_stream is the date of sampling from the Konza stream ‘King’s Creek’.<br> d18O_stream is the oxygen isotopic ratio of water from the stream<br> dD_stream is the hydrogen isotopic ratio of water from the stream<br> sample_date_precip is the date of sampling of precipitation from the Konza headquarters station<br> dD_precip is the hydrogen isotopic ratio of precipitation<br> d18O_precip is the oxygen isotopic ratio of precipitation
DOI: 10.6084/m9.figshare.3563796
title: Supplement 1. Fortran and Matlab files for conducting model calculations described in the main text.

description: File ListSupplement, original calcB7_5curve.for (md5: 4d88e7313e582d7eb41e272f536467cd) B7.inc (md5: 6b4d6683acd1765f93fce9fefd2b7ff3) calcB7_5curve.exe (md5: c46092f613abb3cb6c0b69c735d132ef) B_and_NPP_of_Trantime.m (md5: b02746500c7f393645567eb995a8997c) <br> Supplement, Revision 1 (posted 23 January 2013) calcB7_5curve.for – <b>corrected</b>, (md5: b7233a525e671cf016281c86913aee91) calcB7_5curve.exe – <b>corrected</b>, (md5: 42f4844387a0c2f5d9cfcdaa26c1d8a9) B_and_NPP_of_Trantime.m – <b>corrected</b>, (md5: b31358b099d3038809795cacd1a9ff7a) Description The Fortran code “calcB7_5curve.for” and accompanying include file “B7.inc” contain the model used to test Hypothesis #1 in Lucas and Thompson (2012), i.e., to explore the relationship between phytoplankton biomass and productivity and water depth, and how that relationship changes as a function of benthic grazing rate. The include file, B7.inc, contains and describes all changeable model parameters. We include an executable version of the code “calcB7_5curve.exe”. However, if any changes are made to the include file, the code needs to be recompiled before running in order for changes to take effect. To produce the results presented in Lucas and Thompson (2012), the model was compiled with Compaq Visual Fortran Standard Edition 6.6.a. See Appendix and Table 1 in main manuscript and comments in source code for more detail. The Matlab script “B_and_NPP_of_Trantime.m” contains the model used to test Hypothesis #2 in Lucas and Thompson (2012), i.e., to explore the relationship between phytoplankton biomass and productivity and transport time, and how that relationship changes as a function of benthic grazing rate. In this model, net phytoplankton growth rate, inflowing algal biomass concentration, zooplankton grazing rate, water depth, and cellular C:Chl ratio are specified by the user and assumed uniform and constant. In addition, a range of benthic grazing rates and transport times are specified. This model calculates steady-state habitat averaged phytoplankton biomass and productivity two ways: (1) via analytical expressions provided in the Appendix (see Eqs. 5 and 6) of Lucas and Thompson (2012); (2) via numerical integration along the streamwise habitat axis. This script also plots and compares results in various ways. See comments in script and Appendix and Table 1 in main manuscript for more detail.