cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.xsuc8z
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Isoetes wormaldii R.Sim)",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 2000",
 "BasisOfRecord is one of (Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 100",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0093179-240626123714530/datasets/export for details.
DOI: 10.25582/data.2021-07.2270948/2435344
title: Data for EMSL Project 51375 from July 2021
DOI: 10.25582/data.2022-03.2451399/2435345
title: Data for EMSL Project 51375 from March 2022
DOI: 10.25582/data.2022-03.2451519/2435346
title: Data for EMSL Project 51375 from March 2022
DOI: 10.15468/dl.3ra8va
title: Occurrence Download

description: A dataset containing 2134 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "SpeciesKey is Haliplus immaculatus Gerhardt, 1877",
 "Year is greater than or equal to 2004",
 "Year is less than or equal to 2023"
 ]
}

 The dataset includes 2134 records from 80 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0093180-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.3511733.v1
title: Appendix A. Photographs of parts of the study site.

description: Photographs of parts of the study site.
DOI: 10.6084/m9.figshare.3511730
title: Appendix B. Details of the model parameters, their values, and sources.

description: Details of the model parameters, their values, and sources.
DOI: 10.6084/m9.figshare.3511730.v1
title: Appendix B. Details of the model parameters, their values, and sources.

description: Details of the model parameters, their values, and sources.
DOI: 10.6084/m9.figshare.3511727
title: Appendix A. Summary statistics for the first two axes in CCA and intraset correlations for variables that were used to constrain the ordination.

description: Summary statistics for the first two axes in CCA and intraset correlations for variables that were used to constrain the ordination.
DOI: 10.6084/m9.figshare.3511727.v1
title: Appendix A. Summary statistics for the first two axes in CCA and intraset correlations for variables that were used to constrain the ordination.

description: Summary statistics for the first two axes in CCA and intraset correlations for variables that were used to constrain the ordination.
DOI: 10.6084/m9.figshare.3511724
title: Appendix B. Alternative candidate models (AICc2 of the minimum AICc) for multiple linear regressions.

description: Alternative candidate models (AICc2 of the minimum AICc) for multiple linear regressions.
DOI: 10.6084/m9.figshare.3511721
title: Index Files

description: Index Files
DOI: 10.6084/m9.figshare.3511721.v1
title: Index Files

description: Index Files
DOI: 10.6084/m9.figshare.3511715
title: Appendix A. A table of all bird species captured during the study, and their presence or absence within each habitat.

description: A table of all bird species captured during the study, and their presence or absence within each habitat.
DOI: 10.6084/m9.figshare.3511715.v1
title: Appendix A. A table of all bird species captured during the study, and their presence or absence within each habitat.

description: A table of all bird species captured during the study, and their presence or absence within each habitat.
DOI: 10.6084/m9.figshare.3511712
title: Appendix B. Species accumulation curves and Lorenz's k-dominance curves for all bird species and for all understory and terrestrial species in the three disturbance treatments.

description: Species accumulation curves and Lorenz's k-dominance curves for all bird species and for all understory and terrestrial species in the three disturbance treatments.
DOI: 10.5281/zenodo.4014400
title: Helminths, polyparasitism, and the gut microbiome in the Philippines

description: fastaq files for asssociated paper Helminths, polyparasitism, and the gut microbiome in the Philippines 0.1016/j.ijpara.2019.12.008
DOI: 10.6084/m9.figshare.3511712.v1
title: Appendix B. Species accumulation curves and Lorenz's k-dominance curves for all bird species and for all understory and terrestrial species in the three disturbance treatments.

description: Species accumulation curves and Lorenz's k-dominance curves for all bird species and for all understory and terrestrial species in the three disturbance treatments.
DOI: 10.5281/zenodo.4014399
title: Helminths, polyparasitism, and the gut microbiome in the Philippines

description: fastaq files for asssociated paper Helminths, polyparasitism, and the gut microbiome in the Philippines 0.1016/j.ijpara.2019.12.008
DOI: 10.6084/m9.figshare.3511709
title: Appendix A. A description of the terrestrial ecosystem model.

description: A description of the terrestrial ecosystem model.
DOI: 10.6084/m9.figshare.3511706
title: Appendix A. A description of the process of fitting an empirical function to CO2 eddy flux data.

description: A description of the process of fitting an empirical function to CO2 eddy flux data.
DOI: 10.6084/m9.figshare.3511706.v1
title: Appendix A. A description of the process of fitting an empirical function to CO2 eddy flux data.

description: A description of the process of fitting an empirical function to CO2 eddy flux data.
DOI: 10.6084/m9.figshare.3511703
title: Appendix A. The Kalman filter for maximum likelihood estimation given corrupted observations.

description: The Kalman filter for maximum likelihood estimation given corrupted observations.
DOI: 10.6084/m9.figshare.3511703.v1
title: Appendix A. The Kalman filter for maximum likelihood estimation given corrupted observations.

description: The Kalman filter for maximum likelihood estimation given corrupted observations.
DOI: 10.6084/m9.figshare.3511700
title: Appendix B. The development of a general method for correcting for age-specific inputs into the censused population.

description: The development of a general method for correcting for age-specific inputs into the censused population.
DOI: 10.6084/m9.figshare.3511700.v1
title: Appendix B. The development of a general method for correcting for age-specific inputs into the censused population.

description: The development of a general method for correcting for age-specific inputs into the censused population.
DOI: 10.6084/m9.figshare.3511697
title: Supplement 1. The Splus code for estimating parameters and calculating the posterior probability distributions for DA risk metrics.

description: File List S-Plus code: ParameterEst.ssc<br> kalman_ests.m<br> PostPDFPlots.ssc<br> All files are in ASCII text. Description The file ParameterEst.ssc contains Splus code to estimate m and s<sup>2</sup> using ML, running sums, and slope methods. The ML method allows missing data; the running sum and slope methods do not. For these methods, missing data points should be replaced with interpolated values. I use simple linear interpolation. Basic diagnostics are done also: normality, trend and autocorrelation tests. Outliers are tested for and removed using DFFITS criteria. The file kalman_ests.m contains matlab code to estimate m and s<sup>2</sup> using the Kalman filter algorithm. The file PostPDFPlots.ssc calculates posterior probability distributions for the parameters, m, s<sup>2</sup>, and s<sup>2</sup><sub>np</sub>, and the risk metrics, l, probability of eventual 90% decline, and expected total probability of 90% decline within given time frames. This code implements the algorithm given in the section <i>Posterior probability distributions</i> in the text and produces Figs. 8 and 9.
DOI: 10.6084/m9.figshare.3511697.v1
title: Supplement 1. The Splus code for estimating parameters and calculating the posterior probability distributions for DA risk metrics.

description: File List S-Plus code: ParameterEst.ssc<br> kalman_ests.m<br> PostPDFPlots.ssc<br> All files are in ASCII text. Description The file ParameterEst.ssc contains Splus code to estimate m and s<sup>2</sup> using ML, running sums, and slope methods. The ML method allows missing data; the running sum and slope methods do not. For these methods, missing data points should be replaced with interpolated values. I use simple linear interpolation. Basic diagnostics are done also: normality, trend and autocorrelation tests. Outliers are tested for and removed using DFFITS criteria. The file kalman_ests.m contains matlab code to estimate m and s<sup>2</sup> using the Kalman filter algorithm. The file PostPDFPlots.ssc calculates posterior probability distributions for the parameters, m, s<sup>2</sup>, and s<sup>2</sup><sub>np</sub>, and the risk metrics, l, probability of eventual 90% decline, and expected total probability of 90% decline within given time frames. This code implements the algorithm given in the section <i>Posterior probability distributions</i> in the text and produces Figs. 8 and 9.
DOI: 10.6084/m9.figshare.3511694
title: Supplement 2. The Matlab code for running a stochastic matrix model and generating diagnostic plots.

description: File List Matlab code: gensimests.m <br> marshmat.m <br> paramperf.m <br> SimpleRun.m All files are in ASCII text. DescriptionThe following are matlab files (in ascii format) to run 1000 simulations of a stochastic matrix model and then graph diagnostic plots of the parameter and risk metric estimates using ML, running sum, Heyde-Cohen, Kalman and slope parameterization methods. To run, copy the files to a directory and run the "SimpleRun.m" script. This calls functions to run simulations and make plots described in the other files. The file SimpleRun.m calls marshmat.m to specify the stochastic model. It then calls gensimests.m to make 1000 simulated time series, estimate the diffusion approximation parameters using the ML, running sum, Heyde-Cohen, Kalman and slope methods, and saves the results to a file. Finally, SimpleRun.m calls paramperf.m which makes diagnostic plots of the different parameterization methods. The file marshmat.m specifies the matrix model, the level of stochasticity for each matrix element, and what segment of the population is censused. The file gensimests.m runs the model specified in marshmat.m to create simulated time series. To each time series, it adds either none or one of the three levels of sampling error. From this time series, it then estimates diffusion approximation parameters via ML, running sum, Heyde-Cohen, Kalman or slope methods. It saves the results in a data file. The file paramperf.m takes the data file created by gensimests.m and makes diagnostic plots of the percentage error in estimation of m, s<sup>2</sup>, l, and the probability of 90% decline.
DOI: 10.6084/m9.figshare.3511694.v1
title: Supplement 2. The Matlab code for running a stochastic matrix model and generating diagnostic plots.

description: File List Matlab code: gensimests.m <br> marshmat.m <br> paramperf.m <br> SimpleRun.m All files are in ASCII text. DescriptionThe following are matlab files (in ascii format) to run 1000 simulations of a stochastic matrix model and then graph diagnostic plots of the parameter and risk metric estimates using ML, running sum, Heyde-Cohen, Kalman and slope parameterization methods. To run, copy the files to a directory and run the "SimpleRun.m" script. This calls functions to run simulations and make plots described in the other files. The file SimpleRun.m calls marshmat.m to specify the stochastic model. It then calls gensimests.m to make 1000 simulated time series, estimate the diffusion approximation parameters using the ML, running sum, Heyde-Cohen, Kalman and slope methods, and saves the results to a file. Finally, SimpleRun.m calls paramperf.m which makes diagnostic plots of the different parameterization methods. The file marshmat.m specifies the matrix model, the level of stochasticity for each matrix element, and what segment of the population is censused. The file gensimests.m runs the model specified in marshmat.m to create simulated time series. To each time series, it adds either none or one of the three levels of sampling error. From this time series, it then estimates diffusion approximation parameters via ML, running sum, Heyde-Cohen, Kalman or slope methods. It saves the results in a data file. The file paramperf.m takes the data file created by gensimests.m and makes diagnostic plots of the percentage error in estimation of m, s<sup>2</sup>, l, and the probability of 90% decline.
DOI: 10.6084/m9.figshare.3511691
title: Index Files

description: Index Files
DOI: 10.6084/m9.figshare.3511691.v1
title: Index Files

description: Index Files
DOI: 10.6084/m9.figshare.3511688
title: Appendix A. A table showing the AIC, AICc, and BIC values for all 40 models fit to the data.

description: A table showing the AIC, AICc, and BIC values for all 40 models fit to the data.
DOI: 10.6084/m9.figshare.3511688.v1
title: Appendix A. A table showing the AIC, AICc, and BIC values for all 40 models fit to the data.

description: A table showing the AIC, AICc, and BIC values for all 40 models fit to the data.
DOI: 10.6084/m9.figshare.3511685
title: Appendix A. A table summarizing the 146 experimental cases (plot–nurse shrub–target species combination) integrating the meta-analysis.

description: A table summarizing the 146 experimental cases (plot–nurse shrub–target species combination) integrating the meta-analysis.
DOI: 10.6084/m9.figshare.3511685.v1
title: Appendix A. A table summarizing the 146 experimental cases (plot–nurse shrub–target species combination) integrating the meta-analysis.

description: A table summarizing the 146 experimental cases (plot–nurse shrub–target species combination) integrating the meta-analysis.
DOI: 10.6084/m9.figshare.3511682
title: Appendix A. A color photograph showing two monarch subspecies, Danaus plexippus plexippus in North America and D. plexippus megalippe in the Caribbean and northern South America (both collected in Cuba).

description: A color photograph showing two monarch subspecies, Danaus plexippus plexippus in North America and D. plexippus megalippe in the Caribbean and northern South America (both collected in Cuba).
DOI: 10.6084/m9.figshare.3511679
title: Appendix A. An explanation of the calculation of the ECOPATH parameters.

description: An explanation of the calculation of the ECOPATH parameters.
DOI: 10.6084/m9.figshare.3511676
title: Appendix A. A table showing fungal species occurring on the 180 experimental logs during 1997–2002.

description: A table showing fungal species occurring on the 180 experimental logs during 1997–2002.
DOI: 10.6084/m9.figshare.3511679.v1
title: Appendix A. An explanation of the calculation of the ECOPATH parameters.

description: An explanation of the calculation of the ECOPATH parameters.
DOI: 10.6084/m9.figshare.3511676.v1
title: Appendix A. A table showing fungal species occurring on the 180 experimental logs during 1997–2002.

description: A table showing fungal species occurring on the 180 experimental logs during 1997–2002.
DOI: 10.6084/m9.figshare.3511673
title: Appendix A. A table showing biomass and energetics of the four 30-compartment flow models of the Neuse River Estuary representing early and late summer of 1997 and 1998 respectively.

description: A table showing biomass and energetics of the four 30-compartment flow models of the Neuse River Estuary representing early and late summer of 1997 and 1998 respectively.
DOI: 10.6084/m9.figshare.3511670
title: Supplement 1. :Information on the rate of carbon transfer between the compartments of each flow model.

description: File List nes97.dat<br> nls97.dat<br> nes98.dat<br> nls98.dat Description The files contain data on carbon flow in the Neuse River estuary ecosystem representing the early and late summer seasons of 1997 and 1998 respectively. All files are in the SCOR (Scientific Committee on Oceanic Research) recommended format for the application of network analysis to food web networks. They give information on the living and non-living components present in the ecosystem during each of the time periods, and consist essentially of 5 sections each. The first is a list of the compartments which are numbered in column D from 1–30. The second section gives the biomass/standing stock of each compartment with the units of measurement in column E. The third section contains the imports from outside the system into the relevant compartments; units in column E. The third section gives information on the exports from each compartment, while the fourth section gives the respiration energy of each living component in the system; units in column E. The last section gives the flows from prey compartment i to consumer compartment j, units in column E. These files can be directly used in network analysis, the program of which can be downloaded from the web site http://www.cbl.umces.edu/~ulan/ntwk/network.html. All entries in columns D and E must be deleted before the analysis can proceed. The data files can be downloaded in Microsoft Excel before being used in the network analysis routines (i.e., NETWRK 4). The information contained in the data files were entered by means of DATAIN.EXE, a routine embedded in NETWRK 4 at the web address given above. Biomass is expressed in milligrams of C per square meter, whilst imports, exports, respiration, and flows between the compartments are given in milligrams of C per square meter per day. Instructions pertaining to the use of the supplement files in the execution of NETWRK 4 (or network analysis) are given on the web page. Output results from NETWRK 4 are discussed in the paper quoted above.
DOI: 10.6084/m9.figshare.3511673.v1
title: Appendix A. A table showing biomass and energetics of the four 30-compartment flow models of the Neuse River Estuary representing early and late summer of 1997 and 1998 respectively.

description: A table showing biomass and energetics of the four 30-compartment flow models of the Neuse River Estuary representing early and late summer of 1997 and 1998 respectively.
DOI: 10.6084/m9.figshare.3511670.v1
title: Supplement 1. :Information on the rate of carbon transfer between the compartments of each flow model.

description: File List nes97.dat<br> nls97.dat<br> nes98.dat<br> nls98.dat Description The files contain data on carbon flow in the Neuse River estuary ecosystem representing the early and late summer seasons of 1997 and 1998 respectively. All files are in the SCOR (Scientific Committee on Oceanic Research) recommended format for the application of network analysis to food web networks. They give information on the living and non-living components present in the ecosystem during each of the time periods, and consist essentially of 5 sections each. The first is a list of the compartments which are numbered in column D from 1–30. The second section gives the biomass/standing stock of each compartment with the units of measurement in column E. The third section contains the imports from outside the system into the relevant compartments; units in column E. The third section gives information on the exports from each compartment, while the fourth section gives the respiration energy of each living component in the system; units in column E. The last section gives the flows from prey compartment i to consumer compartment j, units in column E. These files can be directly used in network analysis, the program of which can be downloaded from the web site http://www.cbl.umces.edu/~ulan/ntwk/network.html. All entries in columns D and E must be deleted before the analysis can proceed. The data files can be downloaded in Microsoft Excel before being used in the network analysis routines (i.e., NETWRK 4). The information contained in the data files were entered by means of DATAIN.EXE, a routine embedded in NETWRK 4 at the web address given above. Biomass is expressed in milligrams of C per square meter, whilst imports, exports, respiration, and flows between the compartments are given in milligrams of C per square meter per day. Instructions pertaining to the use of the supplement files in the execution of NETWRK 4 (or network analysis) are given on the web page. Output results from NETWRK 4 are discussed in the paper quoted above.
DOI: 10.6084/m9.figshare.3511667
title: Appendix A. Data on life cycles and hosts used by larval trematodes infecting Cerithidea californica.

description: Data on life cycles and hosts used by larval trematodes infecting Cerithidea californica.
DOI: 10.6084/m9.figshare.3511667.v1
title: Appendix A. Data on life cycles and hosts used by larval trematodes infecting Cerithidea californica.

description: Data on life cycles and hosts used by larval trematodes infecting Cerithidea californica.
DOI: 10.6084/m9.figshare.3511664
title: Appendix B. Data on larval trematodes infecting Cerithidea californica at control and restored sites by year.

description: Data on larval trematodes infecting Cerithidea californica at control and restored sites by year.
DOI: 10.6084/m9.figshare.3511664.v1
title: Appendix B. Data on larval trematodes infecting Cerithidea californica at control and restored sites by year.

description: Data on larval trematodes infecting Cerithidea californica at control and restored sites by year.
DOI: 10.6084/m9.figshare.3511661
title: Appendix A. A complete list of plant species present at the 75 wetland sites and their coefficients of conservatism and intensity coefficient scores (to supplement the data presented in Table 3).

description: A complete list of plant species present at the 75 wetland sites and their coefficients of conservatism and intensity coefficient scores (to supplement the data presented in Table 3).
DOI: 10.6084/m9.figshare.3511661.v1
title: Appendix A. A complete list of plant species present at the 75 wetland sites and their coefficients of conservatism and intensity coefficient scores (to supplement the data presented in Table 3).

description: A complete list of plant species present at the 75 wetland sites and their coefficients of conservatism and intensity coefficient scores (to supplement the data presented in Table 3).
DOI: 10.6084/m9.figshare.3511658
title: Appendix A. A description of the status on nonnative brook trout (Salvelinus fontinalis) in four streams in north central Colorado, USA, inhabited by Colorado River cutthroat trout (Oncorhynchus clarki pleuriticus).

description: A description of the status on nonnative brook trout (Salvelinus fontinalis) in four streams in north central Colorado, USA, inhabited by Colorado River cutthroat trout (Oncorhynchus clarki pleuriticus).
DOI: 10.6084/m9.figshare.3511658.v1
title: Appendix A. A description of the status on nonnative brook trout (Salvelinus fontinalis) in four streams in north central Colorado, USA, inhabited by Colorado River cutthroat trout (Oncorhynchus clarki pleuriticus).

description: A description of the status on nonnative brook trout (Salvelinus fontinalis) in four streams in north central Colorado, USA, inhabited by Colorado River cutthroat trout (Oncorhynchus clarki pleuriticus).
DOI: 10.6084/m9.figshare.3511655
title: Appendix B. A table of parameter estimates for apparent survival, population size, and electrofishing capture probabilities for trout in the four study streams during 1998–2001.

description: A table of parameter estimates for apparent survival, population size, and electrofishing capture probabilities for trout in the four study streams during 1998–2001.
DOI: 10.6084/m9.figshare.3511655.v1
title: Appendix B. A table of parameter estimates for apparent survival, population size, and electrofishing capture probabilities for trout in the four study streams during 1998–2001.

description: A table of parameter estimates for apparent survival, population size, and electrofishing capture probabilities for trout in the four study streams during 1998–2001.