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Figure 3 from: Houghton DC, Lardner R (2020) Ash-free dry mass values for northcentral USA caddisflies (Insecta, Trichoptera). ZooKeys 951: 37-46. https://doi.org/10.3897/zookeys.951.49790
Figure 3 Comparison of mean specimen abundance (% of total specimens) and AFDM biomass (% of total biomass) for the caddisfly FFGs of a Michigan first order stream, based on 13 blacklight samples from each of 5 sites collected weekly from June to August 2012 (Houghton and Wasson 2013). AFDM biomass determined by multiplying determined AFDM values reported herein for each species by the number of specimens of that species in each sample.
Figure 2 from: Houghton DC, Lardner R (2020) Ash-free dry mass values for northcentral USA caddisflies (Insecta, Trichoptera). ZooKeys 951: 37-46. https://doi.org/10.3897/zookeys.951.49790
Figure 2 The Log10 high, low, and mean biomass values for each of the 20 different caddisfly families measured. Number of species measured within each family above each bar.
Figure 1 from: Houghton DC, Lardner R (2020) Ash-free dry mass values for northcentral USA caddisflies (Insecta, Trichoptera). ZooKeys 951: 37-46. https://doi.org/10.3897/zookeys.951.49790
Figure 1 The northcentral US, showing localities from where our AFDM-determined specimens were collected.
The global value of water in agriculture
<p>This repository contains supporting data for: "<strong>The global value of water in agriculture"</strong></p> <p>Cite: D’Odorico, P., Chiarelli, D.D., Rosa L., Bini A., Zilberman D., Rulli, M.C. The value of water in agriculture in a global high-resolution analysis. PNAS. 2020<br> Email: paolododo@berkeley.edu </p> <p>This file contains the value of irrigation water withdrawals (USD per cubic meter) based on circa year 2000 crop distribution. </p>
Data (D2H values) from: Generational shift in the migratory common noctule bat: first-year males lead the way to hibernacula at higher latitudes
<p>Supplementary_Table_3_D2H values noctules_Kravchenko et al</p> <p>The dataset contains stable hydrogen values (D2H) (column "sample_value") in fur keratin of 413 common noctule bats (Nyctalus noctula) from Kharkiv (Ukraine). Samples were collected in winter colonies over 12 years (2004-2015). Each row is one individual. Column "sample_ID" is an ID of an individual. Columns "lat" and "long" are coordinates of Kharkiv city (sampling site). Column "sex" is sex of individuals. Column "age1" shows the age of individuals: ad - adult individuals, sad -subadult individuals (younger than one year). Column "Status" assign origin status of individuals to either 0 - regional or 1 - migratory. Column "Year3" represents the year of sample collection in a format of time in the past from the first year of the collection (-11) till the last year of the collection (0). Column "Year" is the year of sample collection.</p>
Maximizing the value of forest restoration for tropical mammals by detecting three-dimensional habitat associations
<b>Description: </b><p>Species detection data for 28 medium-large mammal species obtained using camera trap methods across a logging-induced degradation gradient. Cameras were deployed using a paired design across 74 sampling locations. Data were used to explore species-habitat associations with LiDAR-derived measures of forest structure.</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/26"><b>Understanding covariation between mammalian diversity and forest carbon across a human-modified tropical landscape</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>NERC (Standard grant, NE/K016407/1, <a href="http://gotw.nerc.ac.uk/list_full.asp?pcode=NE%2FK016407%2F1&classtype=ENRIs&classification=Biodiversity&cookieConsent=A">http://gotw.nerc.ac.uk/list_full.asp?pcode=NE%2FK016407%2F1&classtype=ENRIs&classification=Biodiversity&cookieConsent=A</a>)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=4010757">here</a></p><p><b>Files: </b>This consists of 1 file: DeereEtAl2020_PNAS.xlsx</p><p><b>DeereEtAl2020_PNAS.xlsx</b></p><p>This file contains dataset metadata and 2 data tables:</p><ol><li><p><b>Site metadata and deployment details</b> (described in worksheet Deployment)</p><p>Description: Details of sampling locations, operational dates and survey effort for each camera trap station (N=126)</p><p>Number of fields: 9</p><p>Number of data rows: 126</p><p>Fields: </p><ul><li><b>Site_ID</b>: Unique alphanumeric identifier of the location camera traps were deployed (Field type: location)</li><li><b>Habitat_Class</b>: Forest condition relative to logging-indiced degradation. Follows Putz and Redford Classification scheme (Putz, Francis E., and Kent H. Redford. "The importance of defining 'forest': tropical forest degradation, deforestation, long‐term phase shifts, and further transitions." Biotropica 42.1 (2010): 10-20) (Field type: categorical)</li><li><b>Latitude</b>: Geographic coordinate of camera trap location (Field type: latitude)</li><li><b>Longitude</b>: Geographic coordinate of camera trap location (Field type: longitude)</li><li><b>Date_On</b>: Date camera traps were deployed (Field type: date)</li><li><b>Time_On</b>: Time camera traps were deployed (Field type: time)</li><li><b>Date_Off</b>: Date camera traps were collected (Field type: date)</li><li><b>Time_Off</b>: Time camera traps were collected (Field type: time)</li><li><b>CTNs</b>: Total survey effort for camera trap station (Field type: numeric)</li></ul></li><li><p><b>Species detection data</b> (described in worksheet Detection)</p><p>Description: Raw camera trap detection data for 28 medium-large mammal species obtained from 126 camera trap stations deployed using a paired design across 74 sampling locations </p><p>Number of fields: 7</p><p>Number of data rows: 29008</p><p>Fields: </p><ul><li><b>Site</b>: Unique alphanumeric identifier of the location camera traps were deployed (Field type: location)</li><li><b>common_name</b>: Mammal species identifier (Field type: taxa)</li><li><b>Sp_ID</b>: Numeric species identifier, used to coerce dataframe into a 4D array (Field type: id)</li><li><b>Site_ID</b>: Numeric site identifier, used to coerce dataframe into a 4D array (Field type: id)</li><li><b>Spatial_Rep</b>: Spatial replicate indicative of the number of camera trap stations deployed at a site. Also used to coerce dataframe into a 4d array (Field type: replicate)</li><li><b>Temporal_Rep</b>: Temporal replicate, each comprising six camera trap nights (Field type: replicate)</li><li><b>Detection</b>: Presence/absence of species during survey period (Field type: abundance)</li></ul></li></ol><p><b>Date range: </b>2014-06-20 to 2017-10-09</p><p><b>Latitudinal extent: </b>4.5536 to 4.8121</p><p><b>Longitudinal extent: </b>117.4122 to 117.7398</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div> -  Animalia <br> -  -  Chordata <br> -  -  -  Mammalia <br> -  -  -  -  Rodentia <br> -  -  -  -  -  Sciuridae <br> -  -  -  -  -  -  <i>Rheithrosciurus</i> <br> -  -  -  -  -  -  -  <i>Rheithrosciurus macrotis</i> <br> -  -  -  -  -  Hystricidae <br> -  -  -  -  -  -  <i>Hystrix</i> <br> -  -  -  -  -  -  -  <i>Hystrix brachyura</i> <br> -  -  -  -  -  -  -  <i>Hystrix crassispinis</i> <br> -  -  -  -  -  -  <i>Trichys</i> <br> -  -  -  -  -  -  -  <i>Trichys fasciculata</i> <br> -  -  -  -  Proboscidea <br> -  -  -  -  -  Elephantidae <br> -  -  -  -  -  -  <i>Elephas</i> <br> -  -  -  -  -  -  -  <i>Elephas maximus</i> <br> -  -  -  -  Carnivora <br> -  -  -  -  -  Viverridae <br> -  -  -  -  -  -  <i>Viverra</i> <br> -  -  -  -  -  -  -  <i>Viverra tangalunga</i> <br> -  -  -  -  -  -  <i>Arctictis</i> <br> -  -  -  -  -  -  -  <i>Arctictis binturong</i> <br> -  -  -  -  -  -  <i>Paradoxurus</i> <br> -  -  -  -  -  -  -  <i>Paradoxurus hermaphroditus</i> <br> -  -  -  -  -  -  <i>Hemigalus</i> <br> -  -  -  -  -  -  -  <i>Hemigalus derbyanus</i> <br> -  -  -  -  -  -  <i>Paguma</i> <br> -  -  -  -  -  -  -  <i>Paguma larvata</i> <br> -  -  -  -  -  Felidae <br> -  -  -  -  -  -  <i>Pardofelis</i> <br> -  -  -  -  -  -  -  <i>Pardofelis marmorata</i> <br> -  -  -  -  -  -  <i>Prionailurus</i> <br> -  -  -  -  -  -  -  <i>Prionailurus bengalensis</i> <br> -  -  -  -  -  -  <i>Neofelis</i> <br> -  -  -  -  -  -  -  <i>Neofelis diardi</i> <br> -  -  -  -  -  Mustelidae <br> -  -  -  -  -  -  <i>Martes</i> <br> -  -  -  -  -  -  -  <i>Martes flavigula</i> <br> -  -  -  -  -  Ursidae <br> -  -  -  -  -  -  <i>Helarctos</i> <br> -  -  -  -  -  -  -  <i>Helarctos malayanus</i> <br> -  -  -  -  -  Herpestidae <br> -  -  -  -  -  -  <i>Herpestes</i> <br> -  -  -  -  -  -  -  <i>Herpestes brachyurus</i> <br> -  -  -  -  -  Mephitidae <br> -  -  -  -  -  -  <i>Mydaus</i> <br> -  -  -  -  -  -  -  <i>Mydaus javanensis</i> <br> -  -  -  -  Primates <br> -  -  -  -  -  Cercopithecidae <br> -  -  -  -  -  -  <i>Macaca</i> <br> -  -  -  -  -  -  -  <i>Macaca fascicularis</i> <br> -  -  -  -  -  -  -  <i>Macaca nemestrina</i> <br> -  -  -  -  -  Hominidae <br> -  -  -  -  -  -  <i>Pongo</i> <br> -  -  -  -  -  -  -  <i>Pongo pygmaeus</i> <br> -  -  -  -  Artiodactyla <br> -  -  -  -  -  Suidae <br> -  -  -  -  -  -  <i>Sus</i> <br> -  -  -  -  -  -  -  <i>Sus barbatus</i> <br> -  -  -  -  -  Tragulidae <br> -  -  -  -  -  -  <i>Tragulus</i> <br> -  -  -  -  -  -  -  <i>Tragulus napu</i> <br> -  -  -  -  -  -  -  <i>Tragulus kanchil</i> <br> -  -  -  -  -  Cervidae <br> -  -  -  -  -  -  <i>Muntiacus</i> <br> -  -  -  -  -  -  -  <i>Muntiacus atherodes</i> <br> -  -  -  -  -  -  -  <i>Muntiacus muntjak</i> <br> -  -  -  -  -  -  <i>Rusa</i> <br> -  -  -  -  -  -  -  <i>Rusa unicolor</i> <br> -  -  -  -  Pholidota <br> -  -  -  -  -  Manidae <br> -  -  -  -  -  -  <i>Manis</i> <br> -  -  -  -  -  -  -  <i>Manis javanica</i> <br> -  -  -  -  Erinaceomorpha <br> -  -  -  -  -  Erinaceidae <br> -  -  -  -  -  -  <i>Echinosorex</i> <br> -  -  -  -  -  -  -  <i>Echinosorex gymnura</i> <br></div><p></p>
Dataset to study "Social dynamics of values, taboos, and perceived threats around sacred groves in Kurdistan, Iran"
<p>This dataset includes the raw data of a survey of 205 local residents in Kurdistan province, Iran. The "Dataset" sheet presents respondents' socio-demographic characteristics (distance to Baneh city, age group, gender, formal education, traditional lifestyle) and Likert-scale answers (ranging from 1 to 5) on agreement with several statements on values, taboos, and perceived threats around sacred groves in Kurdistan. The full statements are cited in the "Statements" sheet. The complete method is described in: Plieninger, T., Quintas-Soriano, C., Torralba, M., Samani, M.K. & Shakeri, Z. (2020): Social dynamics of values, taboos, and perceived threats around sacred groves in Kurdistan, Iran. People and Nature, in press.</p>
CpG methylation beta values and sample age for the advanced forensic biology lesson
<p>This dataset should be used for the practical of the "Advanced Forensic Biology" lesson. It has been slightly modified from the initial source (see below). It consists of two parts:</p> <p><strong>1) CpG methylation beta values</strong>: tabulated separated methylation beta values in a file called <a href="https://zenodo.org/api/files/9ba3592f-ebe3-442f-9dc6-8b9b29fb170d/cpg_methylation_beta_values.tsv?versionId=5c6942cf-cbfe-4249-a3d9-e2b8b475aa88">cpg_methylation_beta_values.tsv</a>.</p> <p><strong>2) Samples to chronological age </strong>: the relationship between sample identifiers and their chronological age in a tabulated separated file called <a href="https://zenodo.org/api/files/9ba3592f-ebe3-442f-9dc6-8b9b29fb170d/cpg_methylation_sample_age.tsv?versionId=49252b02-9066-4acc-baff-d892320acafc">cpg_methylation_sample_age.tsv</a>.</p> <p><strong>3) CpG identifier to gene symbol and annotation:</strong> a tabulated separated file containing the relationship between CpG island identifier, the corresponding gene and its functional annotation. <a href="https://zenodo.org/api/files/9ba3592f-ebe3-442f-9dc6-8b9b29fb170d/cpg_methylation_cpg_to_annotation.tsv">cpg_methylation_cpg_to_annotation.tsv </a><br> </p> <p> </p> <p><strong>Dataset provenance:</strong></p> <ul> <li>Bocklandt S, Lin W, Sehl ME, Sánchez FJ, Sinsheimer JS, Horvath S, Vilain E. Epigenetic predictor of age. PLoS One. 2011;6(6):e14821. doi: <a href="https://pubmed.ncbi.nlm.nih.gov/21731603/">10.1371/journal.pone.0014821.</a> Epub 2011 Jun 22. PMID: 21731603; PMCID: PMC3120753.</li> <li>GEO link: <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28746">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28746</a></li> </ul>
Data from: The value of the species interaction-abiotic stress hypothesis (SIASH) for invasion biology: using native latitude to explain non-native latitudinal range sizes
<p>Establishment and spread of introduced species are difficult to predict because they are subject to a myriad of factors. A hypothesis which integrates multiple ecological processes, such as the species interaction-abiotic stress hypothesis (SIASH), may improve our ability to predict introduction success (i.e. establishment and spread). SIASH postulates that, along an environmental gradient, species' range limits are set by abiotic stress at the environmentally harsh end of that gradient and by species interactions at the environmentally benign end of the gradient. Given that species richness increases nearer the equator and that climate becomes harsher (colder) nearer the poles, latitude represents a useful gradient with which to test simple predictions of SIASH. In order to test whether non-native ranges conform to the predictions of SIASH, we evaluated non-native latitudinal range size data for 195 cross-continental, naturalized introductions of 140 animal and plant species. Median latitude of native range was positively related to range size in the introduced zone, such that species native to high latitudes occupied larger introduced ranges than species native to low latitudes. Furthermore, temperate native species occupied larger latitudinal ranges when introduced to tropical and subtropical zones than did tropical native species introduced to temperate zones. Our results suggest that where a species originates is as important as where it is introduced for predicting introduction success. Abiotic stress from cold more strongly constrains the range extents of introduced species than species interactions, which is particularly pronounced for species originating from tropical regions. Future work should determine how species interactions and abiotic stress jointly explain other components of non-native species' success across different spatial gradients to better integrate SIASH into invasion biology.</p>
Exploring the predictive value of lesion topology on motor function outcomes in a porcine ischemic stroke model
<p>Dataset to accompany manuscript currently in review at Scientific Reports (12/17/2020)</p>
High-value plant metabolite production in synthetic biosystems
<p><i>Ephedra sinica</i> is a high-value medicinal plant that produces important phenylpropylamino alkaloids pseudoephedrine and ephedrine. Few genomics resources exist for <i>E. </i>sinica, which has been characterized as a tetraploid with a monoploid genome size of 8.56 Gb. Here we reported a partial genome assembly of <i>E. sinica</i> (12.8 Gb) based on Illumina short-read sequencing technology at low coverage.</p>
Data from: The strategy of psychopathy: primary psychopathic traits predict defection on low-value relationships
Recent evidence suggests that psychopathy is a trait continuum. This has unappreciated implications for understanding the selective advantage of psychopathic traits. Whereas clinical psychopathy is typically construed as a strategy of unconditional defection, subclinical psychopathy may promote strategic conditional defection, broadening the adaptive niche of psychopathy within human societies. To test this, we focus on a ubiquitous real-life source of conditional behaviour: the expected relational value of social partners, both in terms of their quality and the likely quantity of future interactions with them. We allow for conversational interaction among participants prior to their playing an unannounced, one-shot prisoner's dilemma game, which fosters naturalistic interpersonal evaluation and conditional behavior, while controlling punishment and reputation effects. Individuals scoring higher on Factor 1 (callous affect, interpersonal manipulation) of the Levenson Self-Report Psychopathy Scale show two forms of conditional defection: one after being interrupted more frequently during the conversation, the other after failing to discover cues to future meetings with an interlocutor. Both interaction effects support the hypothesis that primary subclinical psychopathy potentiates defection on those with low expected relational value. These data clarify the function and form of psychopathic traits, while highlighting adaptive variation in human social strategies.
Data from: How does environment influence fighting? The effects of tidal flow on resource value and fighting costs in sea anemones
An animal's decision to enter into a fight depends on the interaction between perceived resource value (V) and fighting costs (C). Both could be altered by predictable environmental fluctuations. For intertidal marine animals, such as the sea anemone Actinia equina, exposure to high flow during the tidal cycle may increase V by bringing more food. It may also increase C via energy expenditure needed to attach to the substrate. We asked whether simulated tidal cycles would alter decisions in fighting A. equina. We exposed some individuals to still water and others to simulated tidal cycles. To gain insights into V, we measured their startle responses before and after exposure to the treatments, before staging dyadic fights. Individuals exposed to flow present shorter startle responses, suggesting that flowing water indicates high V compared with still water. A higher probability of winning against no-flow individuals and longer contests between flow individuals suggests that increased V increases persistence. However, encounters between flow individuals were less likely to escalate, suggesting that C is not directly related to V. Therefore, predictable environmental cycles alter V and C, but in complex ways.
Data from: A comment on the use of stochastic character maps to estimate evolutionary rate variation in a continuously valued trait
Phylogenetic comparative biology has progressed considerably in recent years. One of the most important developments has been the application of likelihood-based methods to fit alternative models for trait evolution in a phylogenetic tree with branch lengths proportional to time. An important example of this type of method is O'Meara et al.'s (2006) "noncensored" test for variation in the evolutionary rate for a continuously valued character trait through time or across the branches of a phylogenetic tree. According to this method, we first hypothesize evolutionary rate regimes on the tree (called "painting" in Butler and King, 2004); and then we fit an evolutionary model, specifically the popular Brownian model, in which the instantaneous variance of the Brownian random diffusion process has different values in different parts of the phylogeny. The authors suggest that to test a hypothesis that the state of a discrete character influenced the rate of a continuous character, one could use the approach of Neilsen (2002) to first stochastically map the discretely valued trait, and then "test to see whether the portions of the tree with one state for the discrete character have a different rate of evolution for the continuous character than portions of the tree to which the other discrete state has been mapped" (O'Meara et al., 2006, p. 931). Indeed, this has become common practice for this and other closely related methods. Here, I examine this practice. In particular, I show that evolutionary rates estimated this way (i.e., by using maximum likelihood [ML] to fit a multirate model on each stochastically mapped tree; and then averaging across trees) are systematically biased to be more similar to each other than are the underlying generating parameters. My analysis also reveals that this effect is dependent on the rate of evolution for the discrete trait. Specifically, if the rate of evolution for the discrete character is low then the difference between the true history and any stochastically mapped 1 history is generally small. This results in evolutionary rates for the continuous trait that are estimated with little bias. Conversely, if the rate of evolution for the discrete character is very high, then the true and hypothesized character histories are often extremely dissimilar, evolutionary rate estimates are biased to be more similar to each other than their underlying generating values, and we lose power to distinguish evolutionary rates on the tree.
Data from: Prognostic value of ki67 in BCG-treated non-muscle invasive bladder cancer: a meta-analysis and systematic review
Objectives: The aim of this study was to explore the prognostic value of ki67 as a marker in non-muscle-invasive bladder cancer (NMIBC) patients treated with Bacillus Calmette–Guérin (BCG). Methods: Studies were systematically retrieved from the relevant databases (Web of Science, PubMed, Cochrane Library, and Embase), and the expiry date was May 2017. The research steps referred to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis statement. Results: A total of 11 studies that complied with the inclusion criteria were enrolled. The expression of ki67 was not statistically significantly associated with recurrence-free survival (RFS) [hazard ratio (HR): 1.331; 95% CI: 0.980–1.809)]. No significant heterogeneity was found among all included studies (I2 = 36.7%, P = 0.148). The expression of ki67 was statistically significantly associated with progression-free survival (PFS) (HR: 2.567; 95% CI: 1.562–4.219), and the overexpression of ki67 was the risk factor for PFS. Significant heterogeneity was noted among all the included studies (I2 = 55.6%, P = 0.021). The studies that might cause heterogeneity were excluded using the Galbraith plot, and then the meta-analysis was performed again. The results showed that the expression of ki67 was still associated with PFS (HR: 2.922; 95% CI: 2.002–4.266). Conclusions: The overexpression of ki67 was the risk factor for PFS, and the relationship between the expression of ki67 and RFS was not statistically significant in patients with NMIBC treated with BCG intravesical immunotherapy. Well-designed, prospective, randomized controlled trials with a large sample size are still needed to validate the findings.
Data from: When to monitor and when to act: value of information theory for multiple management units and limited budgets
1.The question of when to monitor and when to act is fundamental to applied ecology, and notoriously difficult to answer. Value of information (VOI) theory holds great promise to help answer this question for many management problems. However, VOI theory in applied ecology has only been demonstrated in single-decision problems, and has lacked explicit links between monitoring and management costs. 2.Here, we present an extension of VOI theory for solving multi-unit decisions of whether to monitor before managing, while explicitly accounting for monitoring costs. Our formulation helps to choose the optimal monitoring/management strategy among groups of management units (e.g. species, habitat patches), and can be used to examine the benefits of partial and repeat monitoring. 3.To demonstrate our approach, we use case simulated studies of single-species protection that must choose among potential habitat areas, and classification and management of multiple species threatened with extinction. We provide spreadsheets and code to illustrate the calculations and facilitate application. Our case studies demonstrate the utility of predicting the number of units with a given outcome for problems with probabilities of discrete states, and the efficiency of having a flexible approach to manage according to monitoring outcomes. 4.Synthesis and applications. The decision to act or gather more information can have serious consequences for management. No decision, including the decision to monitor, is risk-free. Our multi-unit expansion of Value of Information (VOI) theory can reduce the risk in monitoring/acting decisions for many applied ecology problems. While our approach cannot account for the potential value of discovering previously unknown threats or ecological processes via monitoring programs, it can provide quantitative guidance on whether to monitor before acting, and which monitoring/management actions are most likely to meet management objectives.
Data from: Data for evaluation of fast kurtosis imaging, b-value optimization and exploration of diffusion MRI contrast
Here we describe and provide diffusion magnetic resonance imaging (dMRI) data that was acquired in neural tissue and a physical phantom. Data acquired in biological tissue includes: fixed rat brain (acquired at 9.4T) and spinal cord (acquired at 16.4T) and in normal human brain (acquired at 3T). This data was recently used for evaluation of diffusion kurtosis imaging (DKI) contrasts and for comparison to diffusion tensor imaging (DTI) parameter contrast. The data has also been used to optimize b-values for ex vivo and in vivo fast kurtosis imaging. The remaining data was obtained in a physical phantom with three orthogonal fiber orientations (fresh asparagus stems) for exploration of the kurtosis fractional anisotropy. However, the data may have broader interest and, collectively, may form the basis for image contrast exploration and simulations based on a wide range of dMRI analysis strategies.
Data from: Improving estimates of environmental change using multilevel regression models of Ellenberg indicator values
Ellenberg indicator values (EIVs) are a widely used metric in plant ecology comprising a semi-quantitative description of species' ecological requirements. Typically, point estimates of mean EIV scores are compared to infer differences in the environmental conditions structuring plant communities – particularly in resurvey studies with no historical environmental data available. However, the use of point estimates as a basis for inference does not take into account variance among species EIVs within sampled plots, and gives equal weighting to means calculated from sites with differing numbers of species. We present a set of multilevel models – fitted with and without group-level predictors – to improve precision and accuracy of site mean EIV scores, and to provide more reliable inference on changing environmental conditions over spatial and temporal gradients in re-visitation studies. We compare multilevel model performance to GLMM's fitted to point estimates of site mean EIVs. We also test the reliability of this method to improve inferences with incomplete species lists in some or all sample sites. Hierarchical modelling led to more accurate and precise estimates of site-level differences in mean EIV scores between time-periods, particularly for datasets with incomplete records of species occurrence. They also revealed directional environmental change within ecological habitat types, which estimates from GLMM's were inadequate to detect. Multilevel models also highlighted a prominent role of hydrological differences as a driver of community change in our case study, which traditional use of EIVs failed to reveal. We have demonstrated that multilevel modelling of EIVs allows for a nuanced estimation of environmental change underlying ecological communities from plant assemblage data, leading to a better understanding of temporal dynamics of ecosystems. Further, the ability of these methods to perform well with missing data should increase the total set of historical data which can be used to this end.
Data from: Communication value of mistakes in dark-eyed junco song
Sexual signals contain information on individual quality or motivation, and most explanations for their reliability are based on signal costs. A recent suggestion is that signaling mistakes, defined as deviations from typical signal design, provide cues on individual quality, contributing to reliable communication even when signal design is not costly. We describe several atypical song traits in dark-eyed juncos (Junco hyemalis) that may be mistakes during song production or development and occur in up to 6% of songs. These putative mistakes were more frequent in an urban versus a wildland population, and individuals differed in their frequency of mistakes. Some atypical signals were more frequent in younger males or were negatively related to paternity success, supporting the hypothesis that fewer mistakes indicate individual quality. We also discuss unexpected results, such as some atypical signals being more frequent in more ornamented males and in songs with lower performance demands. Song consistency (similarity across syllable renditions) was positively related to male age and paternity success; nonetheless, relations with paternity were stronger when looking at the most deviant syllable renditions, suggesting that the perceptual salience of large mistakes may mediate receiver responses to song consistency. Results indicate that signaling mistakes reveal relevant information to play a role in communication.
Data from: Phylogeny of Selaginellaceae: there is value in morphology after all!
PREMISE OF THE STUDY: The cosmopolitan lycophyte family Selaginellaceae, dating back to the Late Devonian–Early Carboniferous, is notorious for its many species with a seemingly undifferentiated gross morphology. This morphological stasis has for a long time hampered our understanding of the evolutionary history of the single genus Selaginella. Here we present a large-scale phylogenetic analysis of Selaginella, and based on the resulting phylogeny, we discuss morphological evolution in the group. METHODS: We sampled about one-third of the approximately 750 recognized Selaginella species. Evolutionary relationships were inferred from both chloroplast (rbcL) and single-copy nuclear gene data (pgiC and SQD1) using a Bayesian inference approach. The morphology of the group was studied and important features mapped onto the phylogeny. KEY RESULTS: We present an overall well-supported phylogeny of Selaginella, and the phylogenetic positions of some previously problematic taxa (i.e., S. sinensis and allies) are now resolved with strong support. We show that even though the evolution of most morphological characters involves reversals and/or parallelisms, several characters are phylogenetically informative. Seven major clades are identified, which each can be uniquely diagnosed by a suite of morphological features. There is value in morphology after all! CONCLUSIONS: Our hypothesis of the evolutionary relationships of Selaginella is well founded based on DNA sequence data, as well as morphology, and is in line with previous findings. It will serve as a firm basis for further studies on Selaginella with respect to, e.g., the poorly known alpha taxonomy, as well as evolutionary questions such as historical biogeographic reconstructions.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.