cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh141154.07fu
title: SH141154.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh141155.07fu
title: SH141155.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh141156.07fu
title: SH141156.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh141157.07fu
title: SH141157.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh141158.07fu
title: SH141158.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh141159.07fu
title: SH141159.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh141160.07fu
title: SH141160.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh141161.07fu
title: SH141161.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.6084/m9.figshare.3516035.v1
title: Appendix C. Summary statistics for response and predictor variables involved in the best predictive model for the risk of wetland habitat loss.

description: Summary statistics for response and predictor variables involved in the best predictive model for the risk of wetland habitat loss.
DOI: 10.6084/m9.figshare.3516029
title: Appendix A. Figure of the study area showing the transect used for sampling.

description: Figure of the study area showing the transect used for sampling.
DOI: 10.6084/m9.figshare.3516029.v1
title: Appendix A. Figure of the study area showing the transect used for sampling.

description: Figure of the study area showing the transect used for sampling.
DOI: 10.6084/m9.figshare.3516026
title: Appendix B. Table showing the main predictors of Black Grouse and snow-sports occurrence derived from a principal-component analysis, and their correlations with the original variables.

description: Table showing the main predictors of Black Grouse and snow-sports occurrence derived from a principal-component analysis, and their correlations with the original variables.
DOI: 10.6084/m9.figshare.3516026.v1
title: Appendix B. Table showing the main predictors of Black Grouse and snow-sports occurrence derived from a principal-component analysis, and their correlations with the original variables.

description: Table showing the main predictors of Black Grouse and snow-sports occurrence derived from a principal-component analysis, and their correlations with the original variables.
DOI: 10.6084/m9.figshare.3516023
title: Appendix C. Figure showing the continuous Boyce curve, calculated from the independently collected Black Grouse data, and the cut off value for suitable Black Grouse habitat.

description: Figure showing the continuous Boyce curve, calculated from the independently collected Black Grouse data, and the cut off value for suitable Black Grouse habitat.
DOI: 10.6084/m9.figshare.3516020
title: Appendix A. Unpublished data sources for population status of green crabs in California, Oregon, Washington, British Columbia, and Alaska 1994–2006.

description: Unpublished data sources for population status of green crabs in California, Oregon, Washington, British Columbia, and Alaska 1994–2006.
DOI: 10.6084/m9.figshare.3516023.v1
title: Appendix C. Figure showing the continuous Boyce curve, calculated from the independently collected Black Grouse data, and the cut off value for suitable Black Grouse habitat.

description: Figure showing the continuous Boyce curve, calculated from the independently collected Black Grouse data, and the cut off value for suitable Black Grouse habitat.
DOI: 10.6084/m9.figshare.3516020.v1
title: Appendix A. Unpublished data sources for population status of green crabs in California, Oregon, Washington, British Columbia, and Alaska 1994–2006.

description: Unpublished data sources for population status of green crabs in California, Oregon, Washington, British Columbia, and Alaska 1994–2006.
DOI: 10.6084/m9.figshare.3516017
title: Appendix B. Data used in the invasion probability model.

description: Data used in the invasion probability model.
DOI: 10.6084/m9.figshare.3516017.v1
title: Appendix B. Data used in the invasion probability model.

description: Data used in the invasion probability model.
DOI: 10.6084/m9.figshare.3516014
title: Appendix C. Economic analysis.

description: Economic analysis.
DOI: 10.6084/m9.figshare.3516014.v1
title: Appendix C. Economic analysis.

description: Economic analysis.
DOI: 10.6084/m9.figshare.3516011
title: Appendix D. Predicted probability of invasions.

description: Predicted probability of invasions.
DOI: 10.6084/m9.figshare.3516011.v1
title: Appendix D. Predicted probability of invasions.

description: Predicted probability of invasions.
DOI: 10.6084/m9.figshare.3516002
title: Appendix E. Modeling commercial harvest losses.

description: Modeling commercial harvest losses.
DOI: 10.6084/m9.figshare.3516002.v1
title: Appendix E. Modeling commercial harvest losses.

description: Modeling commercial harvest losses.
DOI: 10.6084/m9.figshare.3515990
title: Appendix A. Derivation of model for sea lice and juvenile salmon population dynamics.

description: Derivation of model for sea lice and juvenile salmon population dynamics.
DOI: 10.6084/m9.figshare.3515990.v1
title: Appendix A. Derivation of model for sea lice and juvenile salmon population dynamics.

description: Derivation of model for sea lice and juvenile salmon population dynamics.
DOI: 10.6084/m9.figshare.3515987
title: Appendix A. Details of compilation of ecological and life history traits.

description: Details of compilation of ecological and life history traits.
DOI: 10.6084/m9.figshare.3515987.v1
title: Appendix A. Details of compilation of ecological and life history traits.

description: Details of compilation of ecological and life history traits.
DOI: 10.6084/m9.figshare.3515981
title: Appendix B. Parameter estimates for best-fit occupancy models.

description: Parameter estimates for best-fit occupancy models.
DOI: 10.6084/m9.figshare.3515981.v1
title: Appendix B. Parameter estimates for best-fit occupancy models.

description: Parameter estimates for best-fit occupancy models.
DOI: 10.6084/m9.figshare.3515978
title: Appendix A. The annual percent area burned for the period 1980–2005 at spatial scales of 102, 103, 104, and 105 km2.

description: The annual percent area burned for the period 1980–2005 at spatial scales of 102, 103, 104, and 105 km2.
DOI: 10.6084/m9.figshare.3515978.v1
title: Appendix A. The annual percent area burned for the period 1980–2005 at spatial scales of 102, 103, 104, and 105 km2.

description: The annual percent area burned for the period 1980–2005 at spatial scales of 102, 103, 104, and 105 km2.
DOI: 10.6084/m9.figshare.3515972
title: Appendix B. Raw data for the 14 explanatory variables used in the multiscale statistical wildfire models.

description: Raw data for the 14 explanatory variables used in the multiscale statistical wildfire models.
DOI: 10.6084/m9.figshare.3515972.v1
title: Appendix B. Raw data for the 14 explanatory variables used in the multiscale statistical wildfire models.

description: Raw data for the 14 explanatory variables used in the multiscale statistical wildfire models.
DOI: 10.6084/m9.figshare.3515963
title: Appendix C. The minimum, mean, median, maximum, and standard deviation of each variable by spatial scale.

description: The minimum, mean, median, maximum, and standard deviation of each variable by spatial scale.
DOI: 10.6084/m9.figshare.3515963.v1
title: Appendix C. The minimum, mean, median, maximum, and standard deviation of each variable by spatial scale.

description: The minimum, mean, median, maximum, and standard deviation of each variable by spatial scale.
DOI: 10.6084/m9.figshare.3515957
title: Appendix D. The relationship between the observed values used in the boosted regression trees and those predicted by the models.

description: The relationship between the observed values used in the boosted regression trees and those predicted by the models.
DOI: 10.6084/m9.figshare.3515957.v1
title: Appendix D. The relationship between the observed values used in the boosted regression trees and those predicted by the models.

description: The relationship between the observed values used in the boosted regression trees and those predicted by the models.
DOI: 10.6084/m9.figshare.3515948
title: Appendix E. Partial-dependence plots showing variation of the response in area burned (y-axis) as a function of the seven explanatory variables not shown in Fig. 4 at each spatial scale of study.

description: Partial-dependence plots showing variation of the response in area burned (y-axis) as a function of the seven explanatory variables not shown in Fig. 4 at each spatial scale of study.
DOI: 10.6084/m9.figshare.3515948.v1
title: Appendix E. Partial-dependence plots showing variation of the response in area burned (y-axis) as a function of the seven explanatory variables not shown in Fig. 4 at each spatial scale of study.

description: Partial-dependence plots showing variation of the response in area burned (y-axis) as a function of the seven explanatory variables not shown in Fig. 4 at each spatial scale of study.
DOI: 10.6084/m9.figshare.3515942
title: Appendix F. Maps of selected explanatory variables (top map of each pair) and the corresponding maps of partial dependence of area burned (bottom map of each pair) for the 104-km2 spatial scale for the variables not presented in Fig. 5.

description: Maps of selected explanatory variables (top map of each pair) and the corresponding maps of partial dependence of area burned (bottom map of each pair) for the 104-km2 spatial scale for the variables not presented in Fig. 5.
DOI: 10.6084/m9.figshare.3515942.v1
title: Appendix F. Maps of selected explanatory variables (top map of each pair) and the corresponding maps of partial dependence of area burned (bottom map of each pair) for the 104-km2 spatial scale for the variables not presented in Fig. 5.

description: Maps of selected explanatory variables (top map of each pair) and the corresponding maps of partial dependence of area burned (bottom map of each pair) for the 104-km2 spatial scale for the variables not presented in Fig. 5.
DOI: 10.6084/m9.figshare.3515939
title: Appendix A. Creating historical land use reconstructions for Mato Grosso, Brazil (1901–2006).

description: Creating historical land use reconstructions for Mato Grosso, Brazil (1901–2006).
DOI: 10.6084/m9.figshare.3515933
title: Appendix A. Native and invasive populations of Triadica sebifera that were used in this study.

description: Native and invasive populations of Triadica sebifera that were used in this study.
DOI: 10.6084/m9.figshare.3515933.v1
title: Appendix A. Native and invasive populations of Triadica sebifera that were used in this study.

description: Native and invasive populations of Triadica sebifera that were used in this study.
DOI: 10.6084/m9.figshare.3515930
title: Appendix B. Repeated-measures ANOVAs for effects of plant origin, population, light, initial insect density, and time on the weevil population size.

description: Repeated-measures ANOVAs for effects of plant origin, population, light, initial insect density, and time on the weevil population size.
DOI: 10.6084/m9.figshare.3515930.v1
title: Appendix B. Repeated-measures ANOVAs for effects of plant origin, population, light, initial insect density, and time on the weevil population size.

description: Repeated-measures ANOVAs for effects of plant origin, population, light, initial insect density, and time on the weevil population size.
DOI: 10.6084/m9.figshare.3515927
title: Appendix C. Nested ANOVAs (three-way) for effects of weevil adult density, plant origin, population, and light on the growth of Triadica seedlings.

description: Nested ANOVAs (three-way) for effects of weevil adult density, plant origin, population, and light on the growth of Triadica seedlings.
DOI: 10.6084/m9.figshare.3515927.v1
title: Appendix C. Nested ANOVAs (three-way) for effects of weevil adult density, plant origin, population, and light on the growth of Triadica seedlings.

description: Nested ANOVAs (three-way) for effects of weevil adult density, plant origin, population, and light on the growth of Triadica seedlings.
DOI: 10.6084/m9.figshare.3515924
title: Appendix D. Slope and intercept comparisons in the weevil experiment: differences in slopes and intercepts between treatments.

description: Slope and intercept comparisons in the weevil experiment: differences in slopes and intercepts between treatments.
DOI: 10.6084/m9.figshare.3515924.v1
title: Appendix D. Slope and intercept comparisons in the weevil experiment: differences in slopes and intercepts between treatments.

description: Slope and intercept comparisons in the weevil experiment: differences in slopes and intercepts between treatments.
DOI: 10.6084/m9.figshare.3515921
title: Appendix E. Nested ANOVAs (three-way) for effects of moth larval density, plant origin, population, and light on the growth of Triadica seedlings.

description: Nested ANOVAs (three-way) for effects of moth larval density, plant origin, population, and light on the growth of Triadica seedlings.
DOI: 10.6084/m9.figshare.3515921.v1
title: Appendix E. Nested ANOVAs (three-way) for effects of moth larval density, plant origin, population, and light on the growth of Triadica seedlings.

description: Nested ANOVAs (three-way) for effects of moth larval density, plant origin, population, and light on the growth of Triadica seedlings.
DOI: 10.6084/m9.figshare.3515918
title: Appendix F. Slope and intercept comparisons in the moth experiment: differences in slopes and intercepts between treatments.

description: Slope and intercept comparisons in the moth experiment: differences in slopes and intercepts between treatments.
DOI: 10.6084/m9.figshare.3515918.v1
title: Appendix F. Slope and intercept comparisons in the moth experiment: differences in slopes and intercepts between treatments.

description: Slope and intercept comparisons in the moth experiment: differences in slopes and intercepts between treatments.
DOI: 10.6084/m9.figshare.3515912
title: Appendix A. Abundance and diversity of native, exotic, and unclassifiable plants in 11 California grassland blocks at the Hastings Natural History Reservation, sampled for five years.

description: Abundance and diversity of native, exotic, and unclassifiable plants in 11 California grassland blocks at the Hastings Natural History Reservation, sampled for five years.
DOI: 10.6084/m9.figshare.3515912.v1
title: Appendix A. Abundance and diversity of native, exotic, and unclassifiable plants in 11 California grassland blocks at the Hastings Natural History Reservation, sampled for five years.

description: Abundance and diversity of native, exotic, and unclassifiable plants in 11 California grassland blocks at the Hastings Natural History Reservation, sampled for five years.
DOI: 10.6084/m9.figshare.3515909
title: Appendix B. Ratios of native to exotic abundance and diversity in 11 California grassland blocks at the Hastings Natural History Reservation, sampled for five years.

description: Ratios of native to exotic abundance and diversity in 11 California grassland blocks at the Hastings Natural History Reservation, sampled for five years.
DOI: 10.6084/m9.figshare.3515909.v1
title: Appendix B. Ratios of native to exotic abundance and diversity in 11 California grassland blocks at the Hastings Natural History Reservation, sampled for five years.

description: Ratios of native to exotic abundance and diversity in 11 California grassland blocks at the Hastings Natural History Reservation, sampled for five years.