cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.3560751.v1
title: Appendix A. A table showing seed production of Saussurea nigrescens depends strongly on animal pollinators.

description: A table showing seed production of Saussurea nigrescens depends strongly on animal pollinators.
DOI: 10.6084/m9.figshare.3560748.v1
title: Appendix B. A diagram showing the relative position of apiaries, roads, transects, sampling sites, and the bee density gradient for the nectar measurements in Saussurea nigrescens.

description: A diagram showing the relative position of apiaries, roads, transects, sampling sites, and the bee density gradient for the nectar measurements in Saussurea nigrescens.
DOI: 10.6084/m9.figshare.3560745
title: Appendix C. A table showing soil physical-chemical properties and bee visitation rate per capitulum of Saussurea nigrescens.

description: A table showing soil physical-chemical properties and bee visitation rate per capitulum of Saussurea nigrescens.
DOI: 10.6084/m9.figshare.3560745.v1
title: Appendix C. A table showing soil physical-chemical properties and bee visitation rate per capitulum of Saussurea nigrescens.

description: A table showing soil physical-chemical properties and bee visitation rate per capitulum of Saussurea nigrescens.
DOI: 10.6084/m9.figshare.3560742
title: Appendix D. A figure showing white anthers as an indicator of maximum flower nectar volume of Saussurea nigrescens.

description: A figure showing white anthers as an indicator of maximum flower nectar volume of Saussurea nigrescens.
DOI: 10.6084/m9.figshare.3560742.v1
title: Appendix D. A figure showing white anthers as an indicator of maximum flower nectar volume of Saussurea nigrescens.

description: A figure showing white anthers as an indicator of maximum flower nectar volume of Saussurea nigrescens.
DOI: 10.6084/m9.figshare.3560739
title: Appendix E. A table showing sample sizes for nectar volume and concentration measurements of Saussurea nigrescens at each site of each transect.

description: A table showing sample sizes for nectar volume and concentration measurements of Saussurea nigrescens at each site of each transect.
DOI: 10.6084/m9.figshare.3560739.v1
title: Appendix E. A table showing sample sizes for nectar volume and concentration measurements of Saussurea nigrescens at each site of each transect.

description: A table showing sample sizes for nectar volume and concentration measurements of Saussurea nigrescens at each site of each transect.
DOI: 10.6084/m9.figshare.3560736
title: Appendix F. A figure showing bivariate relationships between flower number per capitulum mass and nectar volume per flower of Saussurea nigrescens.

description: A figure showing bivariate relationships between flower number per capitulum mass and nectar volume per flower of Saussurea nigrescens.
DOI: 10.6084/m9.figshare.3560736.v1
title: Appendix F. A figure showing bivariate relationships between flower number per capitulum mass and nectar volume per flower of Saussurea nigrescens.

description: A figure showing bivariate relationships between flower number per capitulum mass and nectar volume per flower of Saussurea nigrescens.
DOI: 10.6084/m9.figshare.3560733
title: Appendix G. A figure showing the effects of pollen supplementation and site (distance relative to apiary along the first gradient) on seed set ratio of Saussurea nigrescens.

description: A figure showing the effects of pollen supplementation and site (distance relative to apiary along the first gradient) on seed set ratio of Saussurea nigrescens.
DOI: 10.6084/m9.figshare.3560733.v1
title: Appendix G. A figure showing the effects of pollen supplementation and site (distance relative to apiary along the first gradient) on seed set ratio of Saussurea nigrescens.

description: A figure showing the effects of pollen supplementation and site (distance relative to apiary along the first gradient) on seed set ratio of Saussurea nigrescens.
DOI: 10.6084/m9.figshare.3560730
title: Supplement 1. JAGS model code for fitting the spatially explicit occupancy model (SEOM) and R code for simulating 50-year projections of metapopulation dynamics, including stage-specific elevated extinction risk under the SEOM.

description: File List Jags_code.txt (MD5: ac63c97de0f01aac1d9f4cd8b974b604) Simulation_code.r (MD5: bb557217ac732762fbc5f3a9d52d4dcf) Description The file DSEOM_jags_code.txt is the jags code to fit the demographic, spatially explicit metapopulation model. The file DSEOM_simulation_code.r is the R code used to simulate future metapopulation dynamics including the addition of stage specific elevated extinction risk scenarios. The simulation requires an MCMC output from the fitted model including a pairwise (patch-to-patch) distance matrix which is available upon request.
DOI: 10.6084/m9.figshare.3560727
title: Appendix A. Structure of missing data (see data analysis of Methods section).

description: Structure of missing data (see data analysis of Methods section).
DOI: 10.6084/m9.figshare.3560727.v1
title: Appendix A. Structure of missing data (see data analysis of Methods section).

description: Structure of missing data (see data analysis of Methods section).
DOI: 10.6084/m9.figshare.3560724
title: Appendix A. Additional details of methods (specifically, choice of weather variables), more detailed discussion of the effects of weather on individual traits, tables with additional model information, and figures showing the changes in population size and in annual weather variables across the study period.

description: Additional details of methods (specifically, choice of weather variables), more detailed discussion of the effects of weather on individual traits, tables with additional model information, and figures showing the changes in population size and in annual weather variables across the study period.
DOI: 10.6084/m9.figshare.3560724.v1
title: Appendix A. Additional details of methods (specifically, choice of weather variables), more detailed discussion of the effects of weather on individual traits, tables with additional model information, and figures showing the changes in population size and in annual weather variables across the study period.

description: Additional details of methods (specifically, choice of weather variables), more detailed discussion of the effects of weather on individual traits, tables with additional model information, and figures showing the changes in population size and in annual weather variables across the study period.
DOI: 10.6084/m9.figshare.3560721
title: Appendix A. The distribution of cameras and photographs of land cover types in White Sands National Monument, New Mexico, USA.

description: The distribution of cameras and photographs of land cover types in White Sands National Monument, New Mexico, USA.
DOI: 10.6084/m9.figshare.3560721.v1
title: Appendix A. The distribution of cameras and photographs of land cover types in White Sands National Monument, New Mexico, USA.

description: The distribution of cameras and photographs of land cover types in White Sands National Monument, New Mexico, USA.
DOI: 10.6084/m9.figshare.3560718
title: Appendix B. The factors and environmental covariates hypothesized to influence the probability of detection and occupancy for both coyotes (Canis latrans) and kit foxes (Vulpes macrotis) in White Sands National Monument, New Mexico, USA, and the sampling methods and analytical approaches used to estimate them.

description: The factors and environmental covariates hypothesized to influence the probability of detection and occupancy for both coyotes (Canis latrans) and kit foxes (Vulpes macrotis) in White Sands National Monument, New Mexico, USA, and the sampling methods and analytical approaches used to estimate them.
DOI: 10.6084/m9.figshare.3560718.v1
title: Appendix B. The factors and environmental covariates hypothesized to influence the probability of detection and occupancy for both coyotes (Canis latrans) and kit foxes (Vulpes macrotis) in White Sands National Monument, New Mexico, USA, and the sampling methods and analytical approaches used to estimate them.

description: The factors and environmental covariates hypothesized to influence the probability of detection and occupancy for both coyotes (Canis latrans) and kit foxes (Vulpes macrotis) in White Sands National Monument, New Mexico, USA, and the sampling methods and analytical approaches used to estimate them.
DOI: 10.6084/m9.figshare.3560715
title: Appendix C. Model selection results from program DISTANCE used to identify covariates that influence lagomorph density.

description: Model selection results from program DISTANCE used to identify covariates that influence lagomorph density.
DOI: 10.6084/m9.figshare.3560715.v1
title: Appendix C. Model selection results from program DISTANCE used to identify covariates that influence lagomorph density.

description: Model selection results from program DISTANCE used to identify covariates that influence lagomorph density.
DOI: 10.6084/m9.figshare.3560712
title: Appendix D. Model selection results from single-species single-season occupancy models used to identify covariates that influence the probability of detection (p) for both coyotes (Canis latrans) and kit foxes (Vulpes macrotis) along with the model-averaged beta coefficients of the covariates.

description: Model selection results from single-species single-season occupancy models used to identify covariates that influence the probability of detection (p) for both coyotes (Canis latrans) and kit foxes (Vulpes macrotis) along with the model-averaged beta coefficients of the covariates.
DOI: 10.6084/m9.figshare.3560712.v1
title: Appendix D. Model selection results from single-species single-season occupancy models used to identify covariates that influence the probability of detection (p) for both coyotes (Canis latrans) and kit foxes (Vulpes macrotis) along with the model-averaged beta coefficients of the covariates.

description: Model selection results from single-species single-season occupancy models used to identify covariates that influence the probability of detection (p) for both coyotes (Canis latrans) and kit foxes (Vulpes macrotis) along with the model-averaged beta coefficients of the covariates.
DOI: 10.6084/m9.figshare.3560709
title: Appendix E. Model selection results from single-species single-season occupancy models used to identify covariates that influence the probability of occupancy (ψ) for both coyotes (Canis latrans) and kit foxes (Vulpes macrotis) along with the model-averaged beta coefficients of the covariates.

description: Model selection results from single-species single-season occupancy models used to identify covariates that influence the probability of occupancy (ψ) for both coyotes (Canis latrans) and kit foxes (Vulpes macrotis) along with the model-averaged beta coefficients of the covariates.
DOI: 10.6084/m9.figshare.3560706
title: Appendix A. Additional description of field sampling, specification of SEMs, and means, data ranges, and bivariate correlations among variables in SEMs.

description: Additional description of field sampling, specification of SEMs, and means, data ranges, and bivariate correlations among variables in SEMs.
DOI: 10.6084/m9.figshare.3560709.v1
title: Appendix E. Model selection results from single-species single-season occupancy models used to identify covariates that influence the probability of occupancy (ψ) for both coyotes (Canis latrans) and kit foxes (Vulpes macrotis) along with the model-averaged beta coefficients of the covariates.

description: Model selection results from single-species single-season occupancy models used to identify covariates that influence the probability of occupancy (ψ) for both coyotes (Canis latrans) and kit foxes (Vulpes macrotis) along with the model-averaged beta coefficients of the covariates.
DOI: 10.6084/m9.figshare.3560706.v1
title: Appendix A. Additional description of field sampling, specification of SEMs, and means, data ranges, and bivariate correlations among variables in SEMs.

description: Additional description of field sampling, specification of SEMs, and means, data ranges, and bivariate correlations among variables in SEMs.
DOI: 10.6084/m9.figshare.3560703
title: Appendix B. Additional results from SEMs: Standardized and unstandardized path coefficients, the standard error of the unstandardized coefficients, t test results, and associated P values.

description: Additional results from SEMs: Standardized and unstandardized path coefficients, the standard error of the unstandardized coefficients, t test results, and associated P values.
DOI: 10.6084/m9.figshare.3560703.v1
title: Appendix B. Additional results from SEMs: Standardized and unstandardized path coefficients, the standard error of the unstandardized coefficients, t test results, and associated P values.

description: Additional results from SEMs: Standardized and unstandardized path coefficients, the standard error of the unstandardized coefficients, t test results, and associated P values.
DOI: 10.6084/m9.figshare.3560700
title: Appendix C. Supplementary statistical table from general linear mixed models (GLMMs).

description: Supplementary statistical table from general linear mixed models (GLMMs).
DOI: 10.6084/m9.figshare.3560700.v1
title: Appendix C. Supplementary statistical table from general linear mixed models (GLMMs).

description: Supplementary statistical table from general linear mixed models (GLMMs).
DOI: 10.6084/m9.figshare.3560697
title: Appendix A. Primers used for strain quantification by qPCR.

description: Primers used for strain quantification by qPCR.
DOI: 10.6084/m9.figshare.3560697.v1
title: Appendix A. Primers used for strain quantification by qPCR.

description: Primers used for strain quantification by qPCR.
DOI: 10.6084/m9.figshare.3560694
title: Appendix B. Parameter estimates for strain quantification.

description: Parameter estimates for strain quantification.
DOI: 10.6084/m9.figshare.3560694.v1
title: Appendix B. Parameter estimates for strain quantification.

description: Parameter estimates for strain quantification.
DOI: 10.6084/m9.figshare.3560691
title: Appendix C. Quantification of strain abundances via molecular markers.

description: Quantification of strain abundances via molecular markers.
DOI: 10.6084/m9.figshare.3560691.v1
title: Appendix C. Quantification of strain abundances via molecular markers.

description: Quantification of strain abundances via molecular markers.
DOI: 10.6084/m9.figshare.3560688
title: Appendix D. Population dynamics in the presence and absence of rotifers.

description: Population dynamics in the presence and absence of rotifers.
DOI: 10.6084/m9.figshare.3560688.v1
title: Appendix D. Population dynamics in the presence and absence of rotifers.

description: Population dynamics in the presence and absence of rotifers.
DOI: 10.6084/m9.figshare.3560682
title: Supplement 1. Annotated proteomics data.

description: File List AnnotatedProteomics.csv (md5: 7986a16b33ef97935ce62cafcc39ef8f)Description AnnotatedProteomics.csv -Overview of the expression strength log2 fold change compared to nearest neighbor or to the corresponding control, respectively of significantly (<i>p</i>
DOI: 10.6084/m9.figshare.3560682.v1
title: Supplement 1. Annotated proteomics data.

description: File List AnnotatedProteomics.csv (md5: 7986a16b33ef97935ce62cafcc39ef8f)Description AnnotatedProteomics.csv -Overview of the expression strength log2 fold change compared to nearest neighbor or to the corresponding control, respectively of significantly (<i>p</i>
DOI: 10.6084/m9.figshare.3560679
title: Appendix A. Somatic growth rates of Daphnia magna.

description: Somatic growth rates of Daphnia magna.
DOI: 10.6084/m9.figshare.3560679.v1
title: Appendix A. Somatic growth rates of Daphnia magna.

description: Somatic growth rates of Daphnia magna.
DOI: 10.6084/m9.figshare.3560676
title: Appendix A. Detailed results and additional figures of logistic regressions of mortality of C. parasema and D. melanurus.

description: Detailed results and additional figures of logistic regressions of mortality of C. parasema and D. melanurus.
DOI: 10.6084/m9.figshare.3560676.v1
title: Appendix A. Detailed results and additional figures of logistic regressions of mortality of C. parasema and D. melanurus.

description: Detailed results and additional figures of logistic regressions of mortality of C. parasema and D. melanurus.
DOI: 10.6084/m9.figshare.3560673
title: Appendix B. Additional figures of behavior (interspecific agonistic interactions and distance to shelter) of C. parasema and D. melanurus on experimental reefs.

description: Additional figures of behavior (interspecific agonistic interactions and distance to shelter) of C. parasema and D. melanurus on experimental reefs.
DOI: 10.6084/m9.figshare.3560670
title: Appendix A. Summary stratigraphic diagram of the Diablas lagoon diatom, stable carbon-isotope (δ13C) and Ti influx data used in this study.

description: Summary stratigraphic diagram of the Diablas lagoon diatom, stable carbon-isotope (δ13C) and Ti influx data used in this study.
DOI: 10.6084/m9.figshare.3560673.v1
title: Appendix B. Additional figures of behavior (interspecific agonistic interactions and distance to shelter) of C. parasema and D. melanurus on experimental reefs.

description: Additional figures of behavior (interspecific agonistic interactions and distance to shelter) of C. parasema and D. melanurus on experimental reefs.
DOI: 10.6084/m9.figshare.3560670.v1
title: Appendix A. Summary stratigraphic diagram of the Diablas lagoon diatom, stable carbon-isotope (δ13C) and Ti influx data used in this study.

description: Summary stratigraphic diagram of the Diablas lagoon diatom, stable carbon-isotope (δ13C) and Ti influx data used in this study.
DOI: 10.6084/m9.figshare.3560667
title: Appendix B. Summary of AMS radiocarbon calibration results and summary of age-depth modeling results.

description: Summary of AMS radiocarbon calibration results and summary of age-depth modeling results.
DOI: 10.6084/m9.figshare.3560667.v1
title: Appendix B. Summary of AMS radiocarbon calibration results and summary of age-depth modeling results.

description: Summary of AMS radiocarbon calibration results and summary of age-depth modeling results.
DOI: 10.6084/m9.figshare.3560664
title: Appendix C. Methods to test for temporal autocorrelation in the residuals on unevenly samples in nonlinear regressions.

description: Methods to test for temporal autocorrelation in the residuals on unevenly samples in nonlinear regressions.
DOI: 10.6084/m9.figshare.3560664.v1
title: Appendix C. Methods to test for temporal autocorrelation in the residuals on unevenly samples in nonlinear regressions.

description: Methods to test for temporal autocorrelation in the residuals on unevenly samples in nonlinear regressions.
DOI: 10.6084/m9.figshare.3560661
title: Appendix D. Tables denoting AIC scores for nonlinear regressions.

description: Tables denoting AIC scores for nonlinear regressions.
DOI: 10.6084/m9.figshare.3560661.v1
title: Appendix D. Tables denoting AIC scores for nonlinear regressions.

description: Tables denoting AIC scores for nonlinear regressions.
DOI: 10.6084/m9.figshare.3560658
title: Appendix E. Species codes used in Fig. 2.

description: Species codes used in Fig. 2.
DOI: 10.6084/m9.figshare.3560658.v1
title: Appendix E. Species codes used in Fig. 2.

description: Species codes used in Fig. 2.
DOI: 10.6084/m9.figshare.3560655
title: Supplement 1. Annotated R scripts and sediment core data used to investigate regime shift dynamics in a Galapagos coastal lagoon.

description: File List data.csv (MD5: a6d684a54a17794fa0a79c739d403b63) Diablas lagoon diatom (%), stable carbon isotope (‰) and interpolated Ti influx data (µg.cm<sup>-2</sup>.yr<sup>-1</sup>). Four minor data handling errors have been corrected in the stable carbon isotope data from Seddon et al. 2011. Script.R (MD5: 4b2c776d9ead3f85f9a3bb37af7a77a3) Example R script to apply regime shift detection techniques and non-linear regressions in this study for analysis of data.csv. STARS.R (MD5: 99bcf013e9a5738843813b7815ce74e9) R script required to implement Sequential T-test Analysis of Regime Shifts Algorithm (Rodionov 2004, 2006) in script.R. Description The supplements are designed to provide an example of the framework used to investigate regime shifts in this study. The main file script.R is annotated and split into two parts: STEP 1 investigates whether regime shifts can be identified in diatom assemblages, STEP 2 provides an example of fitting non-linear regressions on the PC1 axis of the diatom data across Regime Shift 1. This can be repeated across other time steps and other datasets (e.g., Ti influx, δ<sup>13</sup>C) in the way. A number of other packages are required, documented within the script.R file. See R documentation for more information. To run the script, place all data files into the same directory, open R and set the working directory to that folder. Open up the file script.R and follow the annotations (marked with #) to detect regime shifts in the diatom data and then statistically model the changes in the temporal series.
DOI: 10.6084/m9.figshare.3560655.v1
title: Supplement 1. Annotated R scripts and sediment core data used to investigate regime shift dynamics in a Galapagos coastal lagoon.

description: File List data.csv (MD5: a6d684a54a17794fa0a79c739d403b63) Diablas lagoon diatom (%), stable carbon isotope (‰) and interpolated Ti influx data (µg.cm<sup>-2</sup>.yr<sup>-1</sup>). Four minor data handling errors have been corrected in the stable carbon isotope data from Seddon et al. 2011. Script.R (MD5: 4b2c776d9ead3f85f9a3bb37af7a77a3) Example R script to apply regime shift detection techniques and non-linear regressions in this study for analysis of data.csv. STARS.R (MD5: 99bcf013e9a5738843813b7815ce74e9) R script required to implement Sequential T-test Analysis of Regime Shifts Algorithm (Rodionov 2004, 2006) in script.R. Description The supplements are designed to provide an example of the framework used to investigate regime shifts in this study. The main file script.R is annotated and split into two parts: STEP 1 investigates whether regime shifts can be identified in diatom assemblages, STEP 2 provides an example of fitting non-linear regressions on the PC1 axis of the diatom data across Regime Shift 1. This can be repeated across other time steps and other datasets (e.g., Ti influx, δ<sup>13</sup>C) in the way. A number of other packages are required, documented within the script.R file. See R documentation for more information. To run the script, place all data files into the same directory, open R and set the working directory to that folder. Open up the file script.R and follow the annotations (marked with #) to detect regime shifts in the diatom data and then statistically model the changes in the temporal series.
DOI: 10.6084/m9.figshare.3560652
title: Appendix A. Data for the observed fish species and their numbers in the study site in autumn 2008 and spring 2009.

description: Data for the observed fish species and their numbers in the study site in autumn 2008 and spring 2009.
DOI: 10.6084/m9.figshare.3560652.v1
title: Appendix A. Data for the observed fish species and their numbers in the study site in autumn 2008 and spring 2009.

description: Data for the observed fish species and their numbers in the study site in autumn 2008 and spring 2009.
DOI: 10.6084/m9.figshare.3560649
title: Appendix B. Description of the method used to collect herbivores, data for herbivore species and their densities in the study site, and results on herbivore density variation.

description: Description of the method used to collect herbivores, data for herbivore species and their densities in the study site, and results on herbivore density variation.
DOI: 10.6084/m9.figshare.3560649.v1
title: Appendix B. Description of the method used to collect herbivores, data for herbivore species and their densities in the study site, and results on herbivore density variation.

description: Description of the method used to collect herbivores, data for herbivore species and their densities in the study site, and results on herbivore density variation.