cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.3515351
title: Appendix B. Independent and overall effects of nitrogen, sediment, and their interaction as well as plot (location) on nitrogen fixation rates and diazotroph richness in surface sediments (0–1 cm) in Experiment 1, based on multiple-factor ANOVA tests.

description: Independent and overall effects of nitrogen, sediment, and their interaction as well as plot (location) on nitrogen fixation rates and diazotroph richness in surface sediments (0–1 cm) in Experiment 1, based on multiple-factor ANOVA tests.
DOI: 10.6084/m9.figshare.3515351.v1
title: Appendix B. Independent and overall effects of nitrogen, sediment, and their interaction as well as plot (location) on nitrogen fixation rates and diazotroph richness in surface sediments (0–1 cm) in Experiment 1, based on multiple-factor ANOVA tests.

description: Independent and overall effects of nitrogen, sediment, and their interaction as well as plot (location) on nitrogen fixation rates and diazotroph richness in surface sediments (0–1 cm) in Experiment 1, based on multiple-factor ANOVA tests.
DOI: 10.6084/m9.figshare.3515348
title: Appendix A. Algorithm description and additional results.

description: Algorithm description and additional results.
DOI: 10.6084/m9.figshare.3515348.v1
title: Appendix A. Algorithm description and additional results.

description: Algorithm description and additional results.
DOI: 10.6084/m9.figshare.3515345
title: Appendix A. Summary of fishery stock information used to obtain values of the fraction of lifetime egg production (FLEP) and critical replacement threshold (CRT).

description: Summary of fishery stock information used to obtain values of the fraction of lifetime egg production (FLEP) and critical replacement threshold (CRT).
DOI: 10.6084/m9.figshare.3515345.v1
title: Appendix A. Summary of fishery stock information used to obtain values of the fraction of lifetime egg production (FLEP) and critical replacement threshold (CRT).

description: Summary of fishery stock information used to obtain values of the fraction of lifetime egg production (FLEP) and critical replacement threshold (CRT).
DOI: 10.6084/m9.figshare.3515342
title: Appendix B. Life history parameters for California North Central Coast species.

description: Life history parameters for California North Central Coast species.
DOI: 10.6084/m9.figshare.3515342.v1
title: Appendix B. Life history parameters for California North Central Coast species.

description: Life history parameters for California North Central Coast species.
DOI: 10.6084/m9.figshare.3515339
title: Appendix C. Proposed marine protected areas in the California North Central Coast Region and description of one-dimensional representation of two-dimensional coastal habitat maps.

description: Proposed marine protected areas in the California North Central Coast Region and description of one-dimensional representation of two-dimensional coastal habitat maps.
DOI: 10.6084/m9.figshare.3515339.v1
title: Appendix C. Proposed marine protected areas in the California North Central Coast Region and description of one-dimensional representation of two-dimensional coastal habitat maps.

description: Proposed marine protected areas in the California North Central Coast Region and description of one-dimensional representation of two-dimensional coastal habitat maps.
DOI: 10.6084/m9.figshare.3515336
title: Appendix A. Functional characterization of fishes.

description: Functional characterization of fishes.
DOI: 10.6084/m9.figshare.3515333
title: Appendix B. Computation of the functional diversity indices.

description: Computation of the functional diversity indices.
DOI: 10.6084/m9.figshare.3515330
title: Appendix C. Summary of data analysis and randomization procedure.

description: Summary of data analysis and randomization procedure.
DOI: 10.6084/m9.figshare.3515327
title: Appendix D. Dominant fish species in the northern part of the Terminos lagoon.

description: Dominant fish species in the northern part of the Terminos lagoon.
DOI: 10.6084/m9.figshare.3515324
title: Supplement 1. R script for computation of functional diversity and functional specialization indices.

description: File List FDind.R -- R source code for indices computation Description The FDind.R R program computes the 3 functional diversity indices presented in Villéger et al. 2008 (Ecology 89:2290–2301), and the functional specialization index proposed by Bellwood et al. 2006 (Proc. R. Soc. B. 273:101–107). Computation requires R libraries « ape » and « geometry » and two matrices as inputs: « traits » (S*T): T traits values for the S species (at least 2 quantitative continuous traits, i.e., numeric values) « abundances » (C*S) : abundances for the S species in C communities (NA allowed) The function returns a dataframe (C*5) with Species richness (Nbsp), functional richness (FRic), functional evenness (FEve), functional divergence (FDiv) and functional specialization (FSpe) values for each of the C communities. A basic example is provided at the end of the script. Details on indices computation are presented in Appendix B.
DOI: 10.6084/m9.figshare.3515321
title: Appendix A. Characteristics of the 12 plant–pollinators webs analyzed.

description: Characteristics of the 12 plant–pollinators webs analyzed.
DOI: 10.6084/m9.figshare.3515318
title: Appendix B. Description of the extent of the invasion and the dominant interaction link for the complete webs and among natives.

description: Description of the extent of the invasion and the dominant interaction link for the complete webs and among natives.
DOI: 10.6084/m9.figshare.3515315
title: FM B2

description: the CMR findings of FM(B2)
DOI: 10.6084/m9.figshare.3515315.v1
title: FM B2

description: the CMR findings of FM(B2)
DOI: 10.6084/m9.figshare.3515312
title: Appendix C. Multiple linear regressions of number of links, number of species, and number of flower visitors on the area of the focal sierra and proximity to other sierras for entire webs and native sub-matrices.

description: Multiple linear regressions of number of links, number of species, and number of flower visitors on the area of the focal sierra and proximity to other sierras for entire webs and native sub-matrices.
DOI: 10.6084/m9.figshare.3515309
title: Appendix D. Multiple linear regressions of number of alien species, invasion index and proportion of honey bees on the area of the focal sierra and proximity to other sierras.

description: Multiple linear regressions of number of alien species, invasion index and proportion of honey bees on the area of the focal sierra and proximity to other sierras.
DOI: 10.6084/m9.figshare.3515306
title: Appendix A. Maximum-likelihood estimation of parameters of species co-occurrence models.

description: Maximum-likelihood estimation of parameters of species co-occurrence models.
DOI: 10.6084/m9.figshare.3515306.v1
title: Appendix A. Maximum-likelihood estimation of parameters of species co-occurrence models.

description: Maximum-likelihood estimation of parameters of species co-occurrence models.
DOI: 10.6084/m9.figshare.3515303
title: Supplement 1. R and WinBUGS code for fitting species co-occurrence models to treefrog data.

description: File List occupancyModelTwoPrey.R - R and WinBUGS source code<br> counts.txt - Input file containing site- and survey-specific counts of 3 treefrog species<br> sites.txt - Input file containing site-specific, habitat covariates<br> temp.txt - Input file containing site- and survey-specific covariates Description The file occupancyModelTwoPrey.R contains R and WinBUGS source code for conducting a Bayesian analysis of the southern Florida treefrog data. Copy this file and three data files (counts.txt, sites.txt, temp.txt) to the R working directory; then simply execute the R function occupancyModelTwoPrey() to fit the species co-occurrence model to the data.
DOI: 10.6084/m9.figshare.3515300
title: Appendix A. Markov process for detections, model .

description: Markov process for detections, model .
DOI: 10.6084/m9.figshare.3515294
title: Appendix B. Computing expression for probabilities associated with detection histories, Pr(hj), under model .

description: Computing expression for probabilities associated with detection histories, Pr(hj), under model .
DOI: 10.6084/m9.figshare.3515288
title: Appendix C. Simulation results comparing maximum-likelihood estimates with those obtained using the Markov chain Monte Carlo method.

description: Simulation results comparing maximum-likelihood estimates with those obtained using the Markov chain Monte Carlo method.
DOI: 10.6084/m9.figshare.3515288.v1
title: Appendix C. Simulation results comparing maximum-likelihood estimates with those obtained using the Markov chain Monte Carlo method.

description: Simulation results comparing maximum-likelihood estimates with those obtained using the Markov chain Monte Carlo method.
DOI: 10.6084/m9.figshare.3515285
title: Supplement 1. WinBUGS code for model .

description: File List spatial_dep_model.txt -- WinBugs model definition file <br> spatial_dep_script.txt -- WinBugs script file <br> spatial_dep_data.txt -- Sample data file Description Input data consists of the matrix <i>h<sub>ij</sub></i>, the detection/nondetectin data for site <i>i</i>, survey <i>j</i>. In the code, <i>z<sub>i</sub></i> denotes presence (<i>z<sub>i</sub></i> =1) or absence (<i>z<sub>i</sub></i>=0) at the level of the sample unit, <i>i</i>; <i>y<sub>ij</sub></i> denotes local presence (<i>y<sub>ij</sub></i> = 1) or absence (<i>y<sub>ij</sub></i> = 0) on segment <i>j</i>; and <i>h<sub>ij</sub></i> denotes detection (<i>h<sub>ij</sub></i> =1) or not (<i>h<sub>ij</sub></i> =0) on segment <i>j</i> of sample unit <i>i</i>. Each of these random variables is modeled as a Bernoulli trial, the latter two conditional on occupancy at sample unit and segment scale: All model parameters were given uniform prior distributions, U(0,1). -- IMAGE: Please see in attached file. --
DOI: 10.6084/m9.figshare.3515282
title: Index Files

description: Index Files
DOI: 10.6084/m9.figshare.3515279
title: Appendix A. A table showing that fecundity is generally the most sensitive and least elastic life-cycle trait across invertebrates.

description: A table showing that fecundity is generally the most sensitive and least elastic life-cycle trait across invertebrates.
DOI: 10.6084/m9.figshare.3515279.v1
title: Appendix A. A table showing that fecundity is generally the most sensitive and least elastic life-cycle trait across invertebrates.

description: A table showing that fecundity is generally the most sensitive and least elastic life-cycle trait across invertebrates.
DOI: 10.6084/m9.figshare.3515273
title: Appendix B. A table showing that fecundity is generally the most sensitive and least elastic life-cycle trait in Daphnia magna.

description: A table showing that fecundity is generally the most sensitive and least elastic life-cycle trait in Daphnia magna.
DOI: 10.6084/m9.figshare.3515273.v1
title: Appendix B. A table showing that fecundity is generally the most sensitive and least elastic life-cycle trait in Daphnia magna.

description: A table showing that fecundity is generally the most sensitive and least elastic life-cycle trait in Daphnia magna.
DOI: 10.6084/m9.figshare.3515270
title: Appendix A. Details of prior distributions used in change point and associated regression models.

description: Details of prior distributions used in change point and associated regression models.
DOI: 10.6084/m9.figshare.3515270.v1
title: Appendix A. Details of prior distributions used in change point and associated regression models.

description: Details of prior distributions used in change point and associated regression models.
DOI: 10.6084/m9.figshare.3515267
title: Supplement 1. WinBUGS and R code to fit change point and variable selection models.

description: File List trend model with changepoints.txt - WinBUGS model file for trend model with change points<br> R code to fit trend model with change-points.R - R script for fitting trend model via R2WinBUGS<br> varselect model.txt - WinBUGS model file for non-linear variable selection model<br> R code to fit variable selection model.R - R script for fitting variable selection model via R2WinBUGS<br> CCCP model.txt - WinBUGS model file for covariate conditioned change point model<br> R code to fit cccp model.R - R script for fitting covariate conditioned change point model via R2WinBUGS<br> multispecies changepoint.txt - WinBUGS model file for multi-species covariate conditioned change point model<br> R code to fit multispecies cccp model.R - R script for fitting multi-species covariate conditioned change point model via R2WinBUGS<br> Data.zip - Data saved as R objects to demonstrate use of R scripts and WinBUGS models <br> Download all files.zip Description The .txt files are WinBUGS model codes for the models described in the paper. These models require the reversible "jump" add-on for WinBUGS (available from WinBUGS development website). The R scripts can be used to generate required data files and run the WinBUGS models from R. Data.zip contains example input data for all models. The R scripts require all files to be in the R working directory and the R2WinBUGS package must be installed.
DOI: 10.6084/m9.figshare.3515267.v1
title: Supplement 1. WinBUGS and R code to fit change point and variable selection models.

description: File List trend model with changepoints.txt - WinBUGS model file for trend model with change points<br> R code to fit trend model with change-points.R - R script for fitting trend model via R2WinBUGS<br> varselect model.txt - WinBUGS model file for non-linear variable selection model<br> R code to fit variable selection model.R - R script for fitting variable selection model via R2WinBUGS<br> CCCP model.txt - WinBUGS model file for covariate conditioned change point model<br> R code to fit cccp model.R - R script for fitting covariate conditioned change point model via R2WinBUGS<br> multispecies changepoint.txt - WinBUGS model file for multi-species covariate conditioned change point model<br> R code to fit multispecies cccp model.R - R script for fitting multi-species covariate conditioned change point model via R2WinBUGS<br> Data.zip - Data saved as R objects to demonstrate use of R scripts and WinBUGS models <br> Download all files.zip Description The .txt files are WinBUGS model codes for the models described in the paper. These models require the reversible "jump" add-on for WinBUGS (available from WinBUGS development website). The R scripts can be used to generate required data files and run the WinBUGS models from R. Data.zip contains example input data for all models. The R scripts require all files to be in the R working directory and the R2WinBUGS package must be installed.
DOI: 10.6084/m9.figshare.3515264
title: Appendix A. Details of parameter estimates for the multivariate autoregressive (MAR) model including credible intervals of odds ratios (all model parameters are listed).

description: Details of parameter estimates for the multivariate autoregressive (MAR) model including credible intervals of odds ratios (all model parameters are listed).
DOI: 10.6084/m9.figshare.3515264.v1
title: Appendix A. Details of parameter estimates for the multivariate autoregressive (MAR) model including credible intervals of odds ratios (all model parameters are listed).

description: Details of parameter estimates for the multivariate autoregressive (MAR) model including credible intervals of odds ratios (all model parameters are listed).
DOI: 10.6084/m9.figshare.3515261
title: Appendix B. Details of parameter estimates for multivariate autoregressive (MAR) model with and without distinct variables suggested by other analyses (only parameters with large odds ratios are listed).

description: Details of parameter estimates for multivariate autoregressive (MAR) model with and without distinct variables suggested by other analyses (only parameters with large odds ratios are listed).
DOI: 10.6084/m9.figshare.3515258
title: Appendix C. Details of parameter estimates for multivariate autoregressive (MAR) models underlain by Ricker and Gompertz population-dynamic formulations (only parameters with large odds ratios are listed).

description: Details of parameter estimates for multivariate autoregressive (MAR) models underlain by Ricker and Gompertz population-dynamic formulations (only parameters with large odds ratios are listed).
DOI: 10.6084/m9.figshare.3515258.v1
title: Appendix C. Details of parameter estimates for multivariate autoregressive (MAR) models underlain by Ricker and Gompertz population-dynamic formulations (only parameters with large odds ratios are listed).

description: Details of parameter estimates for multivariate autoregressive (MAR) models underlain by Ricker and Gompertz population-dynamic formulations (only parameters with large odds ratios are listed).
DOI: 10.6084/m9.figshare.3515252
title: Appendix A. Sample survey for a kelp forest ecosystem is provided, except that Part III for both coastal and offshore ecosystems is included to show where scenario names were changed between these two expert groups.

description: Sample survey for a kelp forest ecosystem is provided, except that Part III for both coastal and offshore ecosystems is included to show where scenario names were changed between these two expert groups.
DOI: 10.6084/m9.figshare.3515252.v1
title: Appendix A. Sample survey for a kelp forest ecosystem is provided, except that Part III for both coastal and offshore ecosystems is included to show where scenario names were changed between these two expert groups.

description: Sample survey for a kelp forest ecosystem is provided, except that Part III for both coastal and offshore ecosystems is included to show where scenario names were changed between these two expert groups.
DOI: 10.6084/m9.figshare.3515249
title: Appendix B. Number of surveys completed per ecosystem per region and subtotals per ecosystem and region.

description: Number of surveys completed per ecosystem per region and subtotals per ecosystem and region.
DOI: 10.6084/m9.figshare.3515249.v1
title: Appendix B. Number of surveys completed per ecosystem per region and subtotals per ecosystem and region.

description: Number of surveys completed per ecosystem per region and subtotals per ecosystem and region.
DOI: 10.6084/m9.figshare.3515246
title: Appendix C. Respondents’ years of experience per chosen ecosystem and per chosen subregion.

description: Respondents’ years of experience per chosen ecosystem and per chosen subregion.
DOI: 10.6084/m9.figshare.3515246.v1
title: Appendix C. Respondents’ years of experience per chosen ecosystem and per chosen subregion.

description: Respondents’ years of experience per chosen ecosystem and per chosen subregion.
DOI: 10.6084/m9.figshare.3515243
title: Appendix D. Threats listed by participants in the survey that were not on our stressor list.

description: Threats listed by participants in the survey that were not on our stressor list.
DOI: 10.6084/m9.figshare.3515243.v1
title: Appendix D. Threats listed by participants in the survey that were not on our stressor list.

description: Threats listed by participants in the survey that were not on our stressor list.
DOI: 10.6084/m9.figshare.3515240
title: Appendix A. List of variables and their definitions for natural environmental setting, soils, topography, and ecoregions.

description: List of variables and their definitions for natural environmental setting, soils, topography, and ecoregions.
DOI: 10.6084/m9.figshare.3515240.v1
title: Appendix A. List of variables and their definitions for natural environmental setting, soils, topography, and ecoregions.

description: List of variables and their definitions for natural environmental setting, soils, topography, and ecoregions.
DOI: 10.6084/m9.figshare.3515237
title: Appendix B. List of variables and their definitions for landcover, infrastructure, and census.

description: List of variables and their definitions for landcover, infrastructure, and census.
DOI: 10.6084/m9.figshare.3515234
title: Appendix C. List of variables and their definitions for hydrology, water temperature, water chemistry and pesticide indices, SPMD chemistry, and habitat.

description: List of variables and their definitions for hydrology, water temperature, water chemistry and pesticide indices, SPMD chemistry, and habitat.
DOI: 10.6084/m9.figshare.3515234.v1
title: Appendix C. List of variables and their definitions for hydrology, water temperature, water chemistry and pesticide indices, SPMD chemistry, and habitat.

description: List of variables and their definitions for hydrology, water temperature, water chemistry and pesticide indices, SPMD chemistry, and habitat.
DOI: 10.6084/m9.figshare.3515231
title: Appendix D. List of variables and their definitions for invertebrate metrics.

description: List of variables and their definitions for invertebrate metrics.
DOI: 10.6084/m9.figshare.3515231.v1
title: Appendix D. List of variables and their definitions for invertebrate metrics.

description: List of variables and their definitions for invertebrate metrics.
DOI: 10.6084/m9.figshare.3515228
title: Appendix A. Migratory movements of stream-reared transgenic and wild-type coho salmon.

description: Migratory movements of stream-reared transgenic and wild-type coho salmon.
DOI: 10.6084/m9.figshare.3515228.v1
title: Appendix A. Migratory movements of stream-reared transgenic and wild-type coho salmon.

description: Migratory movements of stream-reared transgenic and wild-type coho salmon.
DOI: 10.6084/m9.figshare.3515225
title: Appendix B. Migratory movements of hatchery-reared transgenic and wild-type coho salmon.

description: Migratory movements of hatchery-reared transgenic and wild-type coho salmon.
DOI: 10.6084/m9.figshare.3515225.v1
title: Appendix B. Migratory movements of hatchery-reared transgenic and wild-type coho salmon.

description: Migratory movements of hatchery-reared transgenic and wild-type coho salmon.
DOI: 10.6084/m9.figshare.3515222
title: Appendix A. Temporal sequence of stream temperature records from the Boise River basin (BRB) used to parameterize temperature models.

description: Temporal sequence of stream temperature records from the Boise River basin (BRB) used to parameterize temperature models.
DOI: 10.6084/m9.figshare.3515222.v1
title: Appendix A. Temporal sequence of stream temperature records from the Boise River basin (BRB) used to parameterize temperature models.

description: Temporal sequence of stream temperature records from the Boise River basin (BRB) used to parameterize temperature models.
DOI: 10.6084/m9.figshare.3515219
title: Appendix B. Changes in riparian vegetation determined from Thematic Mapper satellite imagery relative to wildfire perimeters within the BRB between 1989 and 2002.

description: Changes in riparian vegetation determined from Thematic Mapper satellite imagery relative to wildfire perimeters within the BRB between 1989 and 2002.
DOI: 10.6084/m9.figshare.3515219.v1
title: Appendix B. Changes in riparian vegetation determined from Thematic Mapper satellite imagery relative to wildfire perimeters within the BRB between 1989 and 2002.

description: Changes in riparian vegetation determined from Thematic Mapper satellite imagery relative to wildfire perimeters within the BRB between 1989 and 2002.
DOI: 10.6084/m9.figshare.3515216
title: Appendix C. An example of riparian vegetation classifications derived from Thematic Mapper satellite imagery before a wildfire in 1989 and after fire in 2002.

description: An example of riparian vegetation classifications derived from Thematic Mapper satellite imagery before a wildfire in 1989 and after fire in 2002.
DOI: 10.6084/m9.figshare.3515216.v1
title: Appendix C. An example of riparian vegetation classifications derived from Thematic Mapper satellite imagery before a wildfire in 1989 and after fire in 2002.

description: An example of riparian vegetation classifications derived from Thematic Mapper satellite imagery before a wildfire in 1989 and after fire in 2002.