Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
29
datasets available to search
ShareScore release 0.7.1
Dataset results
29 results for “null model”
Data and code for the manuscript: "Varying richness need not imply non-random species co-occurrence: implications for specifying null models"
<p>Data and R code for the manuscript "Varying richness need not imply non-random species co-occurrence: implications for specifying null models".</p>
Data from: A new null model approach to quantify performance and significance for ecological niche models of species distributions
Aim: Ecological niche modelling requires robust estimation of model performance and significance, but common evaluation approaches often yield biased estimates. Null models provide a solution but are rarely used in this field. We implemented an important modification to existing null-model tests, evaluating null models with the same withheld records that were used to evaluate the real model. We built and evaluated models across a range of modelling scenarios and for various performance measures using the algorithm Maxent and the monk parakeet (Myiopsitta monachus). Location: Native range in Southern America and global invasions predominantly in North/Central America and Europe Methods: We tested the ability of models built under 15 scenarios (five sets of calibration records and three settings that varied the level of model complexity) to predict spatially independent evaluation data in the invaded range (in effect, testing the models under spatial transfer). We quantified performance with measures of discriminatory ability and overfitting based on AUC and the omission error rate. We estimated null distributions of these measures and calculated effect size and significance. We determined how these estimates varied across modelling scenarios, comparing with two tests existing in the literature. Results: Performance varied starkly across modelling scenarios. As expected, the measures of overfitting agreed with each other and provided different information than that of discriminatory ability. However, high performance per se did not show strong association with high effect size and significance. Main Conclusions: Ecological niche models should be assessed with measures of effect size and significance based on appropriate null distributions, in contrast to several approaches existing in the literature. The proposed approach using independent evaluation data, implemented with our accompanying code, allows such estimates for either the same or a different region/time period, and it merits use and continued development.
Forecasts, score summary files, target observational data and meteorological driver files to accompany the manuscript "Skill of process-based forecasts relative to multiple null models varies across time and depth for water temperature and dissolved oxygen"
<p>This data publication includes raw ensemble forecast output (forecasts.zip), as well as summary score files (scores.zip) for process-based forecasts produced with the Forecasting Lake and Reservoir Ecosystems (FLARE) framework. In addition, it includes scores for climatology (climatology_scores.csv) and random walk (RW_scores.csv) null forecasts, formatted observational data of target variables (sunp-targets-insitu.csv), and meteorological driver files required for analysis to accompany the manuscript "Skill of process-based forecasts relative to multiple null models varies across time and depth for water temperature and dissolved oxygen". Forecasts were made of water temperature and dissolved oxygen at Lake Sunapee, NH in 2021 and 2022.</p>
Assessment of the stream invertebrate β-diversity along an elevation gradient using a bidimensional null model analysis
<p><strong>Aim:</strong> β-Diversity, commonly defined as the compositional variation among localities that links local diversity (α‐diversity) and regional diversity (γ‐diversity), can arise from two different ecological phenomena, namely the spatial species turnover (i.e. species replacement) and the nestedness of assemblages (i.e. species loss). However, any assessment that does not account for stochasticity in community assembly could be biased and misinform conservation management. In this study, we aimed to provide a better understanding of the overall ecological phenomena underlying stream β-diversity along elevation gradients, and at contributing to the rich debate on null model approaches to identify non-random patterns in the distribution of taxa.</p> <p><strong>Location:</strong> Swiss Alpine region.</p> <p><strong>Methods:</strong> Based on presence-absence data of 78 stream invertebrate families from 309 sites, we analyzed the effect size of non-random spatial distribution of stream invertebrates on the β-diversity and its two components (i.e. turnover and nestedness). We used a modelling framework that allows exploring the complete range of existing algorithm sused in null model analysis, and to assess how distribution patterns vary according to an array of possible ecological assumptions.</p> <p><strong>Results:</strong> Overall, the turnover of stream invertebrates and the nestedness of assemblages were significantly lower and higher, respectively, than the ones expected by chance. This pattern increased with elevation, and the consistent trend observed along the altitudinal gradient, even in the most conservative analysis, strengthened our findings.</p> <p><strong>Main conclusions:</strong> Our study suggests that deterministic distribution of stream invertebrates in the Swiss Alpine region is significantly driven by differential dispersal capacity and environmental stress gradients. As long as the ecological assumptions for constructing the null models and their implications are acknowledged, we believe that they still represent useful tools to measure the effect size of non-random spatial distribution of taxa on β-diversity.</p>
Assessment of the stream invertebrate β-diversity along an elevation gradient using a bidimensional null model analysis
Open the record for dataset details and reuse information.
Data from: A new null model approach to quantify performance and significance for ecological niche models of species distributions
Open the record for dataset details and reuse information.
The disruption index suffers from citation inflation and is confounded by shifts in scholarly citation practice: synthetic citation networks for bibliometric null models
Open the record for dataset details and reuse information.
A graphical null model for scaling biodiversity-ecosystem functioning relationships
1. Global biodiversity is declining at rates faster than at any other point in human history. Experimental manipulations at small spatial scales have demonstrated that communities with fewer species consistently produce less biomass than higher diversity communities. Understanding how the global extinction crisis is likely to impact global ecosystem functioning requires applying these local experimental results at substantially larger spatial and temporal scales. 2. Here we propose a null model for scaling biodiversity-ecosystem functioning relationships using observed macroecological patterns. We use species-area and biomass-area curves to predict species richness – biomass relationships at multiple scales and validate these predictions with data from a Minnesota grassland and a Panamanian tropical dry forest. 3. Our null model accurately predicts species richness-biomass relationships across scales from these species-area and biomass-area relationships. However, we note two important caveats that will increase our ability to apply experimentally collected data to the global scale problem of species loss. First when ecosystem functioning is measured as per unit area (e.g., biomass m-2), as is common in biodiversity-ecosystem functioning experiments, the slope of the biodiversity ecosystem functioning relationship should decrease with increasing scale. Alternatively, when ecosystem functioning is not measured per unit area (e.g., summed total biomass), as is common in scaling studies, the slope of the biodiversity-ecosystem functioning relationship should increase with increasing spatial scale. Second, the underlying macroecological patterns of biodiversity experiments are predictably different from some naturally assembled systems. For example, in non-successional naturally assembled ecosystem, biomass is unlikely to change directionally through time. Biodiversity-ecosystem functioning experiments, however, often start from bare ground and biomass increases through time. From these underlying patterns, we would predict that the slope of the biodiversity-productivity relationship in a naturally assembled system not undergoing succession would decrease with increasing time. Alternatively, in an experiment we would predict an increase over time. 4. This paper provides a simple but novel null hypothesis for scaling any relationship between biodiversity and any ecosystem function in space and time. These predictions provide crucial insights into how and when we can extend results from small scale biodiversity experiments to naturally assembled regional and global ecosystems.
Data from: Rate heterogeneity across Squamata, misleading ancestral state reconstruction and the importance of proper null model specification
The binary-state speciation and extinction (BiSSE) model has been used in many instances to identify state-dependent diversification and reconstruct ancestral states. However, recent studies have shown that the standard procedure of comparing the fit of the BiSSE model to constant-rate birth–death models often inappropriately favours the BiSSE model when diversification rates vary in a state-independent fashion. The newly developed HiSSE model enables researchers to identify state-dependent diversification rates while accounting for state-independent diversification at the same time. The HiSSE model also allows researchers to test state-dependent models against appropriate state-independent null models that have the same number of parameters as the state-dependent models being tested. We reanalyse two data sets that originally used BiSSE to reconstruct ancestral states within squamate reptiles and reached surprising conclusions regarding the evolution of toepads within Gekkota and viviparity across Squamata. We used this new method to demonstrate that there are many shifts in diversification rates across squamates. We then fit various HiSSE submodels and null models to the state and phylogenetic data and reconstructed states under these models. We found that there is no single, consistent signal for state-dependent diversification associated with toepads in gekkotans or viviparity across all squamates. Our reconstructions show limited support for the recently proposed hypotheses that toepads evolved multiple times independently in Gekkota and that transitions from viviparity to oviparity are common in Squamata. Our results highlight the importance of considering an adequate pool of models and null models when estimating diversification rate parameters and reconstructing ancestral states.
Data from: Fauxcurrence: simulating multi-species occurrences for null models in species distribution modelling and biogeography
<p>This dataset contains GPS coordinates of occurrences from 22 species from Sulawesi, Indonesia. It was used in the manuscript "Fauxcurrence: simulating multi-species occurrences for null models in species distribution modelling and biogeography" to demonstrate the utility of the fauxcurrence R package (<a href="https://github.com/ogosborne/fauxcurrence">https://github.com/ogosborne/fauxcurrence)</a>.</p>
PATTERNS OF RICHNESS OF FRESHWATER MOLLUSCS FROM CHILE: PREDICTIONS OF ITS DISTRIBUTION BASED ON NULL MODELS
<p>Script and data for GLM analysis and co-occurrence analysis. </p>
A graphical null model for scaling biodiversity-ecosystem functioning relationships
Open the record for dataset details and reuse information.
Data from: Null model analyses of temporal patterns of bird assemblages and their foraging guilds revealed the predominance of positive and random associations
Open the record for dataset details and reuse information.
Data from: Rate heterogeneity across Squamata, misleading ancestral state reconstruction and the importance of proper null model specification
Open the record for dataset details and reuse information.
Data from: Fauxcurrence: simulating multi-species occurrences for null models in species distribution modelling and biogeography
Open the record for dataset details and reuse information.
Data from: Determining the null model for detecting adaptive convergence from genomic data: a case study using echolocating mammals
Open the record for dataset details and reuse information.
Data from: High throughput sequencing combined with null model tests reveals specific plant-fungi associations linked to seedling establishment and survival
Open the record for dataset details and reuse information.
Code and data of MS "Null models for animal social network analysis and data collected via focal sampling: pre-network or node network permutation?"
Open the record for dataset details and reuse information.
Affymetrix SNP array data for Trp53-null mammary tumors developed in a mouse model with a K8+ luminal cell origin
GEO Series GSE77497. Mus musculus. 6 samples. Type: Genome variation profiling by SNP array.
Transcriptome response to FAK1 (PTK2) targeting in a murine Nf2 null schwannoma cell line model
GEO Series GSE289387. Mus musculus. 24 samples. Type: Expression profiling by high throughput sequencing.
ScienceDex guides
Understand access before you commit
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.