cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.3557034.v1
title: Data Paper. Data Paper

description: File List Individuals.csv (MD5: ): Height, condition, location of individual saguaros at plot X NurseInfo.csv (MD5: ): Nurse plant information at plot X Species.csv (MD5: ): Summary of plant codes and nomenclature of species detected Boundaries.shp (MD5: ): Layer depicting plot boundaries PlotX1908.shp: Layer depicting saguaros surveyed in 1908 that are within plot X (see ShpFiles.zip) All *.shp files are provided as the .zip file ShpFiles.zip (MD5: ); all *.csv files can be downloaded at once using CsvFiles.zip (MD5: ). Description The saguaro cactus (<i>Carnegiea gigantea</i>) is one of the most iconic perennials in the Sonoran Desert. The ecological importance of this species has motivated studies that explored its physiological adaptations to deserts, factors controlling its recruitment and distribution, and changes in its population density and extent over time. The population of saguaros on Tumamoc Hill (Tucson, Arizona) is one of the best studied. Saguaros on and nearby Tumamoc Hill were mapped in 1908, and in 1964 R. M. Turner and J. R. Hastings established four 250-m wide plots within the original census area. Plots were established on the north, south, east, and west-facing slopes of Tumamoc Hill, and each plot extends from the top to the base of the hill. Plots were resurveyed in 1970, 1987, 1993, and between 2010 and 2012. In this data paper, we present all information associated with this monitoring program, which includes digital versions of Spalding’s original 1908 saguaro map as well as information regarding individual saguaros located in each of the four plots. Collected data include plant height, number of branches, and plant condition, as well as plant location. Starting in 1993, we also noted the identity and condition of plant species growing in close proximity to each saguaro. The archived data set described here contains information pertaining to &gt;5800 saguaros.<br> Past analyses of these data include reconstructions of regeneration patterns from observed age structures and the determination of the average height-specific growth rates for plants on each slope. The findings from these studies have broadened our understanding of the relationship between saguaro regeneration patterns and climate. These data have also provided pivotal information regarding regional trends of saguaro populations throughout the Sonoran Desert. As a group, the Tumamoc Hill censuses constitute one of the longest spatially explicit monitoring efforts for a single species in the world. They provide an observational baseline for future comparisons relating individual growth and population demographics to rising CO2 levels, climate change, vegetation change, or changes in other biotic or abiotic factors. <i>Key words</i>: Carnegiea gigantea;<i> long-term monitoring; permanent plots; population dynamics; saguaro cactus; Sonoran Desert; spatially explicit data</i>.
DOI: 10.6084/m9.figshare.3557031
title: Data Paper. Data Paper

description: File List Indo-Pacific Coral Range Boundaries.RData (MD5: 5a64b3116aeda4a828ed16fa1e5e3d02)Description Information on geographic ranges and the location of range boundaries of individual species is key to studies of biogeography, evolution, macroecology, and conservation biology. Traditionally, marine biogeography has emphasized patterns in contours of species or generic richness, based on counts of species collected from different locations. To understand more fully why these and other patterns occur requires data on the geographic extent of individual species, and how their ranges overlap. We compiled a spatial database of geographic range boundaries from the primary literature and from our own records for Indo-Pacific reef-building scleractinian corals (726 species in 17 families: Acroporidae, Agariciidae, Astrocoeniidae, Caryophylliidae, Dendrophylliidae, Euphyllidae, Faviidae, Fungiidae, Meandrinidae, Merulinidae, Oculinidae, Pocilloporidae, Poritidae, Mussidae, Pectiniidae, Siderastreidae, and Trachyphylliidae). Corals have strongly skewed range distributions, with many species being pandemics. The data show little support for Rapoport’s Rule (smaller ranges near the equator), or for the more general hypothesis that range sizes are smaller, on average, where species richness peaks. The unusual disparity between species richness and endemicity in locations such as the Coral Triangle hotspot challenges conservation priorities that tend to focus on hotspots and neglect depauperate locations. The empirically observed locations of ranges diverge from predictions of mid-domain models in ways that are consistent with the hypothesis that westward-flowing equatorial currents influence the species distributions of Indo-Pacific corals. The spatial database also can be used to examine species turnover at faunal boundaries, facilitating new studies that can explore barriers to dispersal and the evolution of geographic range size. <i>Key words</i>: <i>coral triangle hotspot; corals; endemics; geographic range; Indo-Pacific; pandemics; range boundaries; species richness.</i>
DOI: 10.6084/m9.figshare.3557028
title: Data Paper. Data Paper

description: File List PhytoDataBase.zip (MD5: ab5cf44ef2e8854d41e51a2aaf0a3ed5) consisting of: Table1.csv (MD5: ca6261c88bfb388e0c3e4d58efac7a21) Table2.csv (MD5: 0b3f4292975807b5f4ca6acc161cc17b) Table3.csv (MD5: 6b068b352637f7108b648011af2aec27) Description Many macroecological theories have been developed to study the diversity on our planet. All these theories require the existence of consistent databases to test their predictions. In this work, we compiled a data set of marine microplankton species abundances at 788 stations with an extensive geographical coverage. Data were collected on different oceanographic cruises between 1992 and 2002. This database consists of abundances (cells/mL) for each species at each station and depth, together with estimates of the biomass and biovolume for each species. One of the key strengths in this database is that species identifications were made by the same taxonomist, which provides greater strength to the collection and ensures that estimates of species diversity are reliable. Environmental information has also been compiled at each station (chlorophyll, temperature, photosynthetically active radiation (PAR), nutrients) in order to have a characterization of the study area and to be used in studies on the environmental and biological controls of marine biodiversity. <i>Key words</i>: <i>abundance; chlorophyll; diversity; microplankton; nutrients; photosynthetically active radiation; phytoplankton; temperature.</i>
DOI: 10.6084/m9.figshare.3557025
title: Appendix A. A table of study site locations.

description: A table of study site locations.
DOI: 10.6084/m9.figshare.3557025.v1
title: Appendix A. A table of study site locations.

description: A table of study site locations.
DOI: 10.6084/m9.figshare.3557022
title: Appendix B. Results of experiment comparing the effect of regrowth vegetation on sediment characteristics relative to die-off and experimental areas with regrowth removed.

description: Results of experiment comparing the effect of regrowth vegetation on sediment characteristics relative to die-off and experimental areas with regrowth removed.
DOI: 10.6084/m9.figshare.3557022.v1
title: Appendix B. Results of experiment comparing the effect of regrowth vegetation on sediment characteristics relative to die-off and experimental areas with regrowth removed.

description: Results of experiment comparing the effect of regrowth vegetation on sediment characteristics relative to die-off and experimental areas with regrowth removed.
DOI: 10.6084/m9.figshare.3557019
title: Appendix A. Urchin treatment assignments.

description: Urchin treatment assignments.
DOI: 10.6084/m9.figshare.3557019.v1
title: Appendix A. Urchin treatment assignments.

description: Urchin treatment assignments.
DOI: 10.6084/m9.figshare.3557016
title: Appendix B. Change in cover of different taxonomic groups of organisms plotted against species richness from the low-urchin-density trial.

description: Change in cover of different taxonomic groups of organisms plotted against species richness from the low-urchin-density trial.
DOI: 10.6084/m9.figshare.3557016.v1
title: Appendix B. Change in cover of different taxonomic groups of organisms plotted against species richness from the low-urchin-density trial.

description: Change in cover of different taxonomic groups of organisms plotted against species richness from the low-urchin-density trial.
DOI: 10.6084/m9.figshare.3557013
title: Supplement 1. R code used for all analyses and figures in the manuscript.

description: File List subtidal_diversity_consumption_analyses.R (MD5: 003d7f7c4cc9bebaff23cf1d67b2ac1f) Description R code used for all analyses and figures in the manuscript. Data and metadata can be found at http://sbc.lternet.edu/cgi-bin/showDataset.cgi?docid=knb-lter-sbc.59.1
DOI: 10.6084/m9.figshare.3557013.v1
title: Supplement 1. R code used for all analyses and figures in the manuscript.

description: File List subtidal_diversity_consumption_analyses.R (MD5: 003d7f7c4cc9bebaff23cf1d67b2ac1f) Description R code used for all analyses and figures in the manuscript. Data and metadata can be found at http://sbc.lternet.edu/cgi-bin/showDataset.cgi?docid=knb-lter-sbc.59.1
DOI: 10.6084/m9.figshare.3557010
title: Appendix A. Supplementary statistical methods.

description: Supplementary statistical methods.
DOI: 10.6084/m9.figshare.3557010.v1
title: Appendix A. Supplementary statistical methods.

description: Supplementary statistical methods.
DOI: 10.6084/m9.figshare.3557007
title: Appendix B. Species in the analysis, trait data, and sources.

description: Species in the analysis, trait data, and sources.
DOI: 10.6084/m9.figshare.3557004
title: Appendix C. Coefficient estimates for the 25-species occurrence model, the 13-species abundance model, and the 13-species occurrence model.

description: Coefficient estimates for the 25-species occurrence model, the 13-species abundance model, and the 13-species occurrence model.
DOI: 10.6084/m9.figshare.3557004.v1
title: Appendix C. Coefficient estimates for the 25-species occurrence model, the 13-species abundance model, and the 13-species occurrence model.

description: Coefficient estimates for the 25-species occurrence model, the 13-species abundance model, and the 13-species occurrence model.
DOI: 10.6084/m9.figshare.3557001
title: Appendix D. Supplemental figures showing environmental covariation and species-specific responses to environmental predictors.

description: Supplemental figures showing environmental covariation and species-specific responses to environmental predictors.
DOI: 10.6084/m9.figshare.3557001.v1
title: Appendix D. Supplemental figures showing environmental covariation and species-specific responses to environmental predictors.

description: Supplemental figures showing environmental covariation and species-specific responses to environmental predictors.
DOI: 10.6084/m9.figshare.3556998
title: Appendix A. Determining the genuine importance of algae and algal exudates in microcosms.

description: Determining the genuine importance of algae and algal exudates in microcosms.
DOI: 10.6084/m9.figshare.3556998.v1
title: Appendix A. Determining the genuine importance of algae and algal exudates in microcosms.

description: Determining the genuine importance of algae and algal exudates in microcosms.
DOI: 10.6084/m9.figshare.3556995
title: Appendix A. Details on litter chemical analyses.

description: Details on litter chemical analyses.
DOI: 10.6084/m9.figshare.3556995.v1
title: Appendix A. Details on litter chemical analyses.

description: Details on litter chemical analyses.
DOI: 10.6084/m9.figshare.3556992
title: Appendix B. Details on mass-adjustment methodology.

description: Details on mass-adjustment methodology.
DOI: 10.6084/m9.figshare.3556992.v1
title: Appendix B. Details on mass-adjustment methodology.

description: Details on mass-adjustment methodology.
DOI: 10.6084/m9.figshare.3556989
title: Appendix A. Model-selection results for the effects of age and year on juvenile survival.

description: Model-selection results for the effects of age and year on juvenile survival.
DOI: 10.6084/m9.figshare.3556989.v1
title: Appendix A. Model-selection results for the effects of age and year on juvenile survival.

description: Model-selection results for the effects of age and year on juvenile survival.
DOI: 10.6084/m9.figshare.3556986
title: Appendix B. Model-selection results for the effects of candidate variables on annual variation in juvenile survival.

description: Model-selection results for the effects of candidate variables on annual variation in juvenile survival.
DOI: 10.6084/m9.figshare.3556986.v1
title: Appendix B. Model-selection results for the effects of candidate variables on annual variation in juvenile survival.

description: Model-selection results for the effects of candidate variables on annual variation in juvenile survival.
DOI: 10.6084/m9.figshare.3556983
title: Appendix C. Model-selection results for the effects of body mass and fledge date on individual variation in juvenile survival.

description: Model-selection results for the effects of body mass and fledge date on individual variation in juvenile survival.
DOI: 10.6084/m9.figshare.3556983.v1
title: Appendix C. Model-selection results for the effects of body mass and fledge date on individual variation in juvenile survival.

description: Model-selection results for the effects of body mass and fledge date on individual variation in juvenile survival.
DOI: 10.6084/m9.figshare.3556980
title: Appendix A. A figure showing colony areas over time and relative colony size relationships.

description: A figure showing colony areas over time and relative colony size relationships.
DOI: 10.6084/m9.figshare.3556977
title: Appendix B. A figure showing results of sensitivity analyses for initial conditions of the simulations.

description: A figure showing results of sensitivity analyses for initial conditions of the simulations.
DOI: 10.6084/m9.figshare.3556977.v1
title: Appendix B. A figure showing results of sensitivity analyses for initial conditions of the simulations.

description: A figure showing results of sensitivity analyses for initial conditions of the simulations.
DOI: 10.6084/m9.figshare.3556974
title: Appendix C. A figure showing the distribution of AUC for model fits by the two different methods of simulation.

description: A figure showing the distribution of AUC for model fits by the two different methods of simulation.
DOI: 10.6084/m9.figshare.3556974.v1
title: Appendix C. A figure showing the distribution of AUC for model fits by the two different methods of simulation.

description: A figure showing the distribution of AUC for model fits by the two different methods of simulation.
DOI: 10.6084/m9.figshare.3556971
title: Appendix D. A figure summarizing extinction patterns over time from simulations.

description: A figure summarizing extinction patterns over time from simulations.
DOI: 10.6084/m9.figshare.3556971.v1
title: Appendix D. A figure summarizing extinction patterns over time from simulations.

description: A figure summarizing extinction patterns over time from simulations.
DOI: 10.6084/m9.figshare.3556968
title: Supplement 1. Code for parameter estimation and simulation with the stochastic patch-occupancy model.

description: File List SPOMcode.txt (MD5: e9aca88ace4c6c59761eb5cffe061f70) Description The MATLAB script SPOMcode.txt generates the likelihood equation to be maximized for parameter estimation. The script also contains a function (pdogoptTMC) for conducting the estimation and script for conducting simulations with the estimated parameters.
DOI: 10.6084/m9.figshare.3556968.v1
title: Supplement 1. Code for parameter estimation and simulation with the stochastic patch-occupancy model.

description: File List SPOMcode.txt (MD5: e9aca88ace4c6c59761eb5cffe061f70) Description The MATLAB script SPOMcode.txt generates the likelihood equation to be maximized for parameter estimation. The script also contains a function (pdogoptTMC) for conducting the estimation and script for conducting simulations with the estimated parameters.
DOI: 10.6084/m9.figshare.3556965
title: Appendix A. Archive methods and results providing further detail on Ochotona princeps, field-sampling procedures, how we quantified relative abundance and density, predictor variables, and estimation of productivity, as well as results on detectability and summaries of abundance and density data.

description: Archive methods and results providing further detail on Ochotona princeps, field-sampling procedures, how we quantified relative abundance and density, predictor variables, and estimation of productivity, as well as results on detectability and summaries of abundance and density data.
DOI: 10.6084/m9.figshare.3556965.v1
title: Appendix A. Archive methods and results providing further detail on Ochotona princeps, field-sampling procedures, how we quantified relative abundance and density, predictor variables, and estimation of productivity, as well as results on detectability and summaries of abundance and density data.

description: Archive methods and results providing further detail on Ochotona princeps, field-sampling procedures, how we quantified relative abundance and density, predictor variables, and estimation of productivity, as well as results on detectability and summaries of abundance and density data.
DOI: 10.6084/m9.figshare.3556962
title: Appendix B. Topographic illustration of the study region and the sites used in analyses of pika population size or relative density.

description: Topographic illustration of the study region and the sites used in analyses of pika population size or relative density.
DOI: 10.6084/m9.figshare.3556962.v1
title: Appendix B. Topographic illustration of the study region and the sites used in analyses of pika population size or relative density.

description: Topographic illustration of the study region and the sites used in analyses of pika population size or relative density.
DOI: 10.6084/m9.figshare.3556959
title: Appendix C. Information on individual predictors and top models for pika persistence to the present (i.e., as observed at the end of 2000s surveys) since the end of the 1990s surveys.

description: Information on individual predictors and top models for pika persistence to the present (i.e., as observed at the end of 2000s surveys) since the end of the 1990s surveys.
DOI: 10.6084/m9.figshare.3556959.v1
title: Appendix C. Information on individual predictors and top models for pika persistence to the present (i.e., as observed at the end of 2000s surveys) since the end of the 1990s surveys.

description: Information on individual predictors and top models for pika persistence to the present (i.e., as observed at the end of 2000s surveys) since the end of the 1990s surveys.
DOI: 10.6084/m9.figshare.3556956
title: Appendix D. Full list of models used to understand which combination of factors best predicted number of animals detected within each site in the 1990s and 2000s surveys of pikas across the hydrographic Great Basin.

description: Full list of models used to understand which combination of factors best predicted number of animals detected within each site in the 1990s and 2000s surveys of pikas across the hydrographic Great Basin.
DOI: 10.6084/m9.figshare.3556956.v1
title: Appendix D. Full list of models used to understand which combination of factors best predicted number of animals detected within each site in the 1990s and 2000s surveys of pikas across the hydrographic Great Basin.

description: Full list of models used to understand which combination of factors best predicted number of animals detected within each site in the 1990s and 2000s surveys of pikas across the hydrographic Great Basin.
DOI: 10.6084/m9.figshare.3556953
title: Appendix E. Top-ranked models for information-theoretic analyses of pika abundance reported in Table 1.

description: Top-ranked models for information-theoretic analyses of pika abundance reported in Table 1.
DOI: 10.6084/m9.figshare.3556953.v1
title: Appendix E. Top-ranked models for information-theoretic analyses of pika abundance reported in Table 1.

description: Top-ranked models for information-theoretic analyses of pika abundance reported in Table 1.
DOI: 10.6084/m9.figshare.3556950
title: Appendix F. Example of a diagnostic plot suggested by Ver Hoef and Boveng (2007) to evaluate the use of a quasi-Poisson vs. negative-binomial model.

description: Example of a diagnostic plot suggested by Ver Hoef and Boveng (2007) to evaluate the use of a quasi-Poisson vs. negative-binomial model.
DOI: 10.6084/m9.figshare.3556950.v1
title: Appendix F. Example of a diagnostic plot suggested by Ver Hoef and Boveng (2007) to evaluate the use of a quasi-Poisson vs. negative-binomial model.

description: Example of a diagnostic plot suggested by Ver Hoef and Boveng (2007) to evaluate the use of a quasi-Poisson vs. negative-binomial model.
DOI: 10.6084/m9.figshare.3556947
title: Appendix G. Comparison of model-averaged coefficients of pika abundance in the 1990s vs. 2000s surveys, using the identical model suite.

description: Comparison of model-averaged coefficients of pika abundance in the 1990s vs. 2000s surveys, using the identical model suite.
DOI: 10.6084/m9.figshare.3556947.v1
title: Appendix G. Comparison of model-averaged coefficients of pika abundance in the 1990s vs. 2000s surveys, using the identical model suite.

description: Comparison of model-averaged coefficients of pika abundance in the 1990s vs. 2000s surveys, using the identical model suite.
DOI: 10.6084/m9.figshare.3556944
title: Appendix H. Ranks of average variable weight per model of O. princeps persistence, for each of two time periods in the hydrographic Great Basin, western USA, 1898–2008.

description: Ranks of average variable weight per model of O. princeps persistence, for each of two time periods in the hydrographic Great Basin, western USA, 1898–2008.
DOI: 10.6084/m9.figshare.3556944.v1
title: Appendix H. Ranks of average variable weight per model of O. princeps persistence, for each of two time periods in the hydrographic Great Basin, western USA, 1898–2008.

description: Ranks of average variable weight per model of O. princeps persistence, for each of two time periods in the hydrographic Great Basin, western USA, 1898–2008.
DOI: 10.6084/m9.figshare.3556941
title: Appendix I. Comparison of variable weights, average Akaike weight per model, number of models in which the variable had positive and negative coefficients, and coefficient of variation across the fitted coefficients of the variable for each predictor of pika persistence at sites across the hydrographic Great Basin, for each of two periods.

description: Comparison of variable weights, average Akaike weight per model, number of models in which the variable had positive and negative coefficients, and coefficient of variation across the fitted coefficients of the variable for each predictor of pika persistence at sites across the hydrographic Great Basin, for each of two periods.
DOI: 10.6084/m9.figshare.3556941.v1
title: Appendix I. Comparison of variable weights, average Akaike weight per model, number of models in which the variable had positive and negative coefficients, and coefficient of variation across the fitted coefficients of the variable for each predictor of pika persistence at sites across the hydrographic Great Basin, for each of two periods.

description: Comparison of variable weights, average Akaike weight per model, number of models in which the variable had positive and negative coefficients, and coefficient of variation across the fitted coefficients of the variable for each predictor of pika persistence at sites across the hydrographic Great Basin, for each of two periods.