cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.1494761
title: CAFOR Land Owner Engagement, Understanding, Risk and Management Structural Equation Model, Mail Survey 2012

description: These data and the R script provided recreate the analyses and results presented in Stevens (2015). The data were collected from forest land owners in Wallowa, Union, and Baker Counties, Oregon. Forest landowners were defined as those owning ten or more acres of forest land located within a single tax lot. Landowners were identified using a forest-non-forest classification aggregated to publicly available tax lot data from each of the three counties. The University of New Hampshire Survey Center mailed 2133 questionnaires to forest landowners (those who owned 10 acres or more forest land on a single parcel of their land), of which 454 (22%) were completed and returned. No follow-up of non-respondents occurred.
DOI: 10.6084/m9.figshare.1494757
title: Linking Levels - Runs

description: This repository includes all of the simulation runs used to generate the new 'population level' results in the following paper: van der Vaart, E., Johnston, A.S.A., & Sibly, R.M. "Predicting how many animals will be where: How to build, calibrate and evaluate individual-based models" (2015) Ecological Modelling. All the NetLogo & R code used to generate these results - as well as a guide to what they are exactly - is in a separate figshare repository, linked below.
DOI: 10.6084/m9.figshare.1512834.v329
title: Localized Protein Quantification of Blood Brain Barrier Vasculature in Brightfield IHC Images

description: In this paper, we present an objective method for locally quantifying proteins in blood brain barrier (BBB) vasculature using standard immunohistochemistry (IHC) techniques and bright-field microscopy. Images from the hippocampal region at the BBB are acquired using bright-field microscopy and subjected to our immunohistochemistry quantification (IQ) algorithm which is designed to automatically identify and segment microvessels containing the protein glucose transporter 1 (GLUT1). Gabor filtering and k-means clustering are employed to isolate potential vascular structures within cryopsectioned slabs of the hippocampus, which are subsequently subjected to feature extraction followed by classification via decision forest. The false positive rate (FPR) of microvessel classification is characterized using synthetic and non-synthetic IHC image data for image entropies ranging between 3 and 8 bits. The average FPR for synthetic and non-synthetic IHC image data was found to be 5.48% and 5.04%, respectively.
DOI: 10.6084/m9.figshare.1494752
title: The dataset for A global meta-analytic contrast of cushion-plant facilitation of plants and arthropods

description: https://peerj.com/articles/265/ <br>Nurse plant facilitation is a commonly reported plant–plant interaction and is an important factor influencing community structure in stressful environments. Cushion plants are an example of alpine nurse plants that modify microclimatic conditions within their canopies to create favourable environments for other plants. In this meta-analysis, the facilitative effects of cushion plants was expanded from previous syntheses of the topic and the relative strength of facilitation for other plants and for arthropods were compared globally.The abundance, diversity, and species presence/absence effect size estimates were tested as plant responses to nurse plants and a composite measure was tested for arthropods. The strength of facilitation was on average three times greater for arthropods relative to all plant responses to cushions. Plant species presence, i.e., frequency of occurrence, was not enhanced by nurse-plants. Cushion plants nonetheless acted as nurse plants for both plants and arthropods in most alpine contexts globally, and although responses by other plant species currently dominate the facilitation literature, preliminary synthesis of the evidence suggests that the potential impacts of nurses may be even greater for other trophic levels.
DOI: 10.6084/m9.figshare.1494757.v1
title: Linking Levels - Runs

description: This repository includes all of the simulation runs used to generate the new 'population level' results in the following paper: van der Vaart, E., Johnston, A.S.A., & Sibly, R.M. "Predicting how many animals will be where: How to build, calibrate and evaluate individual-based models" (2015) Ecological Modelling. All the NetLogo & R code used to generate these results - as well as a guide to what they are exactly - is in a separate figshare repository, linked below.
DOI: 10.6084/m9.figshare.1494761.v1
title: CAFOR Land Owner Engagement, Understanding, Risk and Management Structural Equation Model, Mail Survey 2012

description: These data and the R script provided recreate the analyses and results presented in Stevens (2015). The data were collected from forest land owners in Wallowa, Union, and Baker Counties, Oregon. Forest landowners were defined as those owning ten or more acres of forest land located within a single tax lot. Landowners were identified using a forest-non-forest classification aggregated to publicly available tax lot data from each of the three counties. The University of New Hampshire Survey Center mailed 2133 questionnaires to forest landowners (those who owned 10 acres or more forest land on a single parcel of their land), of which 454 (22%) were completed and returned. No follow-up of non-respondents occurred.
DOI: 10.6084/m9.figshare.1494733
title: Derived dataset for Curtis et al J Appl Ecol 2015

description: This is the rData object used for statstical analysis in Curtis, Brereton, Dennis, Carbone & Isaac (2015) "<em>Butterfly abundance is determined by food availability and is mediated by species trait</em>s". This file is the final data frame used for statistical analysis. It contains 1495 rows of data. Column names match closely with those used in the manuscript. The "set" column identifies the 1111 rows included in the final analysis. The "hostplant.0", "nectar.all" and "nectar.wohp" columns are derived from vegetation data which can be accessed directly from the NERC Environmental Information Data Centre (see link).
DOI: 10.6084/m9.figshare.1512834.v330
title: Localized Protein Quantification of Blood Brain Barrier Vasculature in Brightfield IHC Images

description: In this paper, we present an objective method for locally quantifying proteins in blood brain barrier (BBB) vasculature using standard immunohistochemistry (IHC) techniques and bright-field microscopy. Images from the hippocampal region at the BBB are acquired using bright-field microscopy and subjected to our immunohistochemistry quantification (IQ) algorithm which is designed to automatically identify and segment microvessels containing the protein glucose transporter 1 (GLUT1). Gabor filtering and k-means clustering are employed to isolate potential vascular structures within cryopsectioned slabs of the hippocampus, which are subsequently subjected to feature extraction followed by classification via decision forest. The false positive rate (FPR) of microvessel classification is characterized using synthetic and non-synthetic IHC image data for image entropies ranging between 3 and 8 bits. The average FPR for synthetic and non-synthetic IHC image data was found to be 5.48% and 5.04%, respectively.
DOI: 10.6084/m9.figshare.1494733.v1
title: Derived dataset for Curtis et al J Appl Ecol 2015

description: This is the rData object used for statstical analysis in Curtis, Brereton, Dennis, Carbone & Isaac (2015) "<em>Butterfly abundance is determined by food availability and is mediated by species trait</em>s". This file is the final data frame used for statistical analysis. It contains 1495 rows of data. Column names match closely with those used in the manuscript. The "set" column identifies the 1111 rows included in the final analysis. The "hostplant.0", "nectar.all" and "nectar.wohp" columns are derived from vegetation data which can be accessed directly from the NERC Environmental Information Data Centre (see link).
DOI: 10.6084/m9.figshare.1494729
title: Full Endnotes: Destruction of Cultural Heritage in 19th-century France

description: Full endnotes
DOI: 10.6084/m9.figshare.1512834.v331
title: Localized Protein Quantification of Blood Brain Barrier Vasculature in Brightfield IHC Images

description: In this paper, we present an objective method for locally quantifying proteins in blood brain barrier (BBB) vasculature using standard immunohistochemistry (IHC) techniques and bright-field microscopy. Images from the hippocampal region at the BBB are acquired using bright-field microscopy and subjected to our immunohistochemistry quantification (IQ) algorithm which is designed to automatically identify and segment microvessels containing the protein glucose transporter 1 (GLUT1). Gabor filtering and k-means clustering are employed to isolate potential vascular structures within cryopsectioned slabs of the hippocampus, which are subsequently subjected to feature extraction followed by classification via decision forest. The false positive rate (FPR) of microvessel classification is characterized using synthetic and non-synthetic IHC image data for image entropies ranging between 3 and 8 bits. The average FPR for synthetic and non-synthetic IHC image data was found to be 5.48% and 5.04%, respectively.
DOI: 10.6084/m9.figshare.1494729.v1
title: Full Endnotes: Destruction of Cultural Heritage in 19th-century France

description: Full endnotes
DOI: 10.6084/m9.figshare.1512834.v332
title: Localized Protein Quantification of Blood Brain Barrier Vasculature in Brightfield IHC Images

description: In this paper, we present an objective method for locally quantifying proteins in blood brain barrier (BBB) vasculature using standard immunohistochemistry (IHC) techniques and bright-field microscopy. Images from the hippocampal region at the BBB are acquired using bright-field microscopy and subjected to our immunohistochemistry quantification (IQ) algorithm which is designed to automatically identify and segment microvessels containing the protein glucose transporter 1 (GLUT1). Gabor filtering and k-means clustering are employed to isolate potential vascular structures within cryopsectioned slabs of the hippocampus, which are subsequently subjected to feature extraction followed by classification via decision forest. The false positive rate (FPR) of microvessel classification is characterized using synthetic and non-synthetic IHC image data for image entropies ranging between 3 and 8 bits. The average FPR for synthetic and non-synthetic IHC image data was found to be 5.48% and 5.04%, respectively.
DOI: 10.6084/m9.figshare.1494725
title: Index to species-group names, Catalogue of Palaearctic Coleoptera - Volume 2, Revised and Updated Edition, 2015

description: Catalogue of Palaearctic Coleoptera - Volume 2 The order is by species-group names and then by current genera rather than by authors. Species-group synonyms are in <em>Italics</em>.
DOI: 10.6084/m9.figshare.1512834.v333
title: Localized Protein Quantification of Blood Brain Barrier Vasculature in Brightfield IHC Images

description: In this paper, we present an objective method for locally quantifying proteins in blood brain barrier (BBB) vasculature using standard immunohistochemistry (IHC) techniques and bright-field microscopy. Images from the hippocampal region at the BBB are acquired using bright-field microscopy and subjected to our immunohistochemistry quantification (IQ) algorithm which is designed to automatically identify and segment microvessels containing the protein glucose transporter 1 (GLUT1). Gabor filtering and k-means clustering are employed to isolate potential vascular structures within cryopsectioned slabs of the hippocampus, which are subsequently subjected to feature extraction followed by classification via decision forest. The false positive rate (FPR) of microvessel classification is characterized using synthetic and non-synthetic IHC image data for image entropies ranging between 3 and 8 bits. The average FPR for synthetic and non-synthetic IHC image data was found to be 5.48% and 5.04%, respectively.
DOI: 10.6084/m9.figshare.1494725.v1
title: Index to species-group names, Catalogue of Palaearctic Coleoptera - Volume 2, Revised and Updated Edition, 2015

description: Catalogue of Palaearctic Coleoptera - Volume 2 The order is by species-group names and then by current genera rather than by authors. Species-group synonyms are in <em>Italics</em>.
DOI: 10.6084/m9.figshare.1512834.v334
title: Localized Protein Quantification of Blood Brain Barrier Vasculature in Brightfield IHC Images

description: In this paper, we present an objective method for locally quantifying proteins in blood brain barrier (BBB) vasculature using standard immunohistochemistry (IHC) techniques and bright-field microscopy. Images from the hippocampal region at the BBB are acquired using bright-field microscopy and subjected to our immunohistochemistry quantification (IQ) algorithm which is designed to automatically identify and segment microvessels containing the protein glucose transporter 1 (GLUT1). Gabor filtering and k-means clustering are employed to isolate potential vascular structures within cryopsectioned slabs of the hippocampus, which are subsequently subjected to feature extraction followed by classification via decision forest. The false positive rate (FPR) of microvessel classification is characterized using synthetic and non-synthetic IHC image data for image entropies ranging between 3 and 8 bits. The average FPR for synthetic and non-synthetic IHC image data was found to be 5.48% and 5.04%, respectively.
DOI: 10.6084/m9.figshare.1512834.v335
title: Localized Protein Quantification of Blood Brain Barrier Vasculature in Brightfield IHC Images

description: In this paper, we present an objective method for locally quantifying proteins in blood brain barrier (BBB) vasculature using standard immunohistochemistry (IHC) techniques and bright-field microscopy. Images from the hippocampal region at the BBB are acquired using bright-field microscopy and subjected to our immunohistochemistry quantification (IQ) algorithm which is designed to automatically identify and segment microvessels containing the protein glucose transporter 1 (GLUT1). Gabor filtering and k-means clustering are employed to isolate potential vascular structures within cryopsectioned slabs of the hippocampus, which are subsequently subjected to feature extraction followed by classification via decision forest. The false positive rate (FPR) of microvessel classification is characterized using synthetic and non-synthetic IHC image data for image entropies ranging between 3 and 8 bits. The average FPR for synthetic and non-synthetic IHC image data was found to be 5.48% and 5.04%, respectively.
DOI: 10.6084/m9.figshare.1494711
title: SEM-EDX soil data

description: Data represent 2D chemical maps of soil that was resin impregnating and scanned by SEM-EDX at 15.8 microns resolution.
DOI: 10.6084/m9.figshare.1494710
title: X-ray CT soil data

description: Data represent 3D X-ray CT images of soil scanned at 15.8 microns resolution.
DOI: 10.6084/m9.figshare.1512834.v336
title: Localized Protein Quantification of Blood Brain Barrier Vasculature in Brightfield IHC Images

description: In this paper, we present an objective method for locally quantifying proteins in blood brain barrier (BBB) vasculature using standard immunohistochemistry (IHC) techniques and bright-field microscopy. Images from the hippocampal region at the BBB are acquired using bright-field microscopy and subjected to our immunohistochemistry quantification (IQ) algorithm which is designed to automatically identify and segment microvessels containing the protein glucose transporter 1 (GLUT1). Gabor filtering and k-means clustering are employed to isolate potential vascular structures within cryopsectioned slabs of the hippocampus, which are subsequently subjected to feature extraction followed by classification via decision forest. The false positive rate (FPR) of microvessel classification is characterized using synthetic and non-synthetic IHC image data for image entropies ranging between 3 and 8 bits. The average FPR for synthetic and non-synthetic IHC image data was found to be 5.48% and 5.04%, respectively.
DOI: 10.6084/m9.figshare.1512834.v337
title: Localized Protein Quantification of Blood Brain Barrier Vasculature in Brightfield IHC Images

description: In this paper, we present an objective method for locally quantifying proteins in blood brain barrier (BBB) vasculature using standard immunohistochemistry (IHC) techniques and bright-field microscopy. Images from the hippocampal region at the BBB are acquired using bright-field microscopy and subjected to our immunohistochemistry quantification (IQ) algorithm which is designed to automatically identify and segment microvessels containing the protein glucose transporter 1 (GLUT1). Gabor filtering and k-means clustering are employed to isolate potential vascular structures within cryopsectioned slabs of the hippocampus, which are subsequently subjected to feature extraction followed by classification via decision forest. The false positive rate (FPR) of microvessel classification is characterized using synthetic and non-synthetic IHC image data for image entropies ranging between 3 and 8 bits. The average FPR for synthetic and non-synthetic IHC image data was found to be 5.48% and 5.04%, respectively.
DOI: 10.6084/m9.figshare.1512834.v338
title: Localized Protein Quantification of Blood Brain Barrier Vasculature in Brightfield IHC Images

description: In this paper, we present an objective method for locally quantifying proteins in blood brain barrier (BBB) vasculature using standard immunohistochemistry (IHC) techniques and bright-field microscopy. Images from the hippocampal region at the BBB are acquired using bright-field microscopy and subjected to our immunohistochemistry quantification (IQ) algorithm which is designed to automatically identify and segment microvessels containing the protein glucose transporter 1 (GLUT1). Gabor filtering and k-means clustering are employed to isolate potential vascular structures within cryopsectioned slabs of the hippocampus, which are subsequently subjected to feature extraction followed by classification via decision forest. The false positive rate (FPR) of microvessel classification is characterized using synthetic and non-synthetic IHC image data for image entropies ranging between 3 and 8 bits. The average FPR for synthetic and non-synthetic IHC image data was found to be 5.48% and 5.04%, respectively.
DOI: 10.6084/m9.figshare.1512834.v339
title: Localized Protein Quantification of Blood Brain Barrier Vasculature in Brightfield IHC Images

description: In this paper, we present an objective method for locally quantifying proteins in blood brain barrier (BBB) vasculature using standard immunohistochemistry (IHC) techniques and bright-field microscopy. Images from the hippocampal region at the BBB are acquired using bright-field microscopy and subjected to our immunohistochemistry quantification (IQ) algorithm which is designed to automatically identify and segment microvessels containing the protein glucose transporter 1 (GLUT1). Gabor filtering and k-means clustering are employed to isolate potential vascular structures within cryopsectioned slabs of the hippocampus, which are subsequently subjected to feature extraction followed by classification via decision forest. The false positive rate (FPR) of microvessel classification is characterized using synthetic and non-synthetic IHC image data for image entropies ranging between 3 and 8 bits. The average FPR for synthetic and non-synthetic IHC image data was found to be 5.48% and 5.04%, respectively.
DOI: 10.6084/m9.figshare.1512834.v340
title: Localized Protein Quantification of Blood Brain Barrier Vasculature in Brightfield IHC Images

description: In this paper, we present an objective method for locally quantifying proteins in blood brain barrier (BBB) vasculature using standard immunohistochemistry (IHC) techniques and bright-field microscopy. Images from the hippocampal region at the BBB are acquired using bright-field microscopy and subjected to our immunohistochemistry quantification (IQ) algorithm which is designed to automatically identify and segment microvessels containing the protein glucose transporter 1 (GLUT1). Gabor filtering and k-means clustering are employed to isolate potential vascular structures within cryopsectioned slabs of the hippocampus, which are subsequently subjected to feature extraction followed by classification via decision forest. The false positive rate (FPR) of microvessel classification is characterized using synthetic and non-synthetic IHC image data for image entropies ranging between 3 and 8 bits. The average FPR for synthetic and non-synthetic IHC image data was found to be 5.48% and 5.04%, respectively.
DOI: 10.6084/m9.figshare.1494672
title: Dataset for the diversity of diversity studies: retrospectives and future directions

description: Diversity is a critical concept for ecology and evolution and one of the most political. The use and delineation of this concept however is broad and applies to a wide spectrum of studies spanning genes and populations to regional and even global patterns of biotic assemblages including map- ping, measuring, interactions, phylogenetics, speciation, and conservation (Purvis and Hector 2000). Management and environmental lobbyists also use declining diversity as a means to justify policy decisions (Sarkar et al. 2006, Heller and Zavaleta 2009, Rands et al. 2010, Wong et al. 2015) yet in some instances diversity is not universally declining nor necessarily linked to function (Naeem 2002, Thomas 2013, Dornelas et al. 2014, Oliver and Morecroft 2014). Here, we do not wish to engage in the biodiversity-ecosystem func- tion debate (Huston 1997, Loreau et al. 2001, Srivastava and Vellend 2005, Weigelt et al. 2008) nor enter into a protracted conservation values discussion (Chee 2004, Brooks et al. 2006, Wong et al. 2015) but rather to identify the most important current and promising elements in the primary study of diversity – particularly since the ‘diversity of diversity studies’ has expanded profoundly in the last several years. A cursory search on Web of Science in 2015, restricted to the last 2 yr, simply for ecology, biodiversity, and evolu- tion literally lists thousands of relevant publications in almost every subdomain of these fields. Here, we have provided retrospective and future directions from a representative set of topics from within this field. These papers were derived from a set of oral presentations at the Nordic Society special symposium during the Intecol 11th INTECOL congress ‘Ecology: into the next 100 years’ in 2013.
DOI: 10.6084/m9.figshare.1494671
title: Survey Instrument to evaulate basic team performance

description: This survey is a shortened version of the Team Assessment Questionnaire (Simmering & Wilcox, 1994). It was sent to the participating students of the course (post-course & post-exam) to evaluate their team performance. This was a voluntary excercise and the response rate to this survey was around 80%.