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.
11
datasets available to search
ShareScore release 0.9.0
Dataset results
11 results for “environmental matching”
Data from:Intraspecific variability improves environmental matching, but does not increase ecological breadth along a wet-to-dry ecotone
It is widely assumed that higher levels of intraspecific variability in one or more traits should allow species to persist under a wider range of environmental conditions. However, few studies have examined whether species that exhibit high variability are found in a wider range of environmental conditions, and whether variability increases the ability of a species to adapt to prevailing ecological gradients. We used four plant functional traits, specific leaf area (SLA), leaf dry matter content (LDMC), leaf carbon to nitrogen ratio (C:N) and maximum plant height in 49 species across a strong environmental gradient to answer three questions: 1) is there evidence for 'high-variability' species (that is, species which show high variability in multiple traits, simultaneously)? 2) are species with more variable traits present across a wider range of environmental conditions than less variable species? And 3) whether more variable species show better trait-environment matching to the prevailing abiotic (soil moisture) gradient at the site? We found little evidence for a 'high-variability' species. Variability was correlated for two leaf traits, SLA and LDMC, while variability in leaf traits and plant height were not correlated. We found little evidence that more variable species were present in more diverse conditions: only variation in SLA was correlated with a wider ecological niche breadth. For plant traits along the soil-moisture gradient, higher variability led to better trait-environment matching in half of measured traits. Overall, we found little support for the existence of 'high-variability' species, but that variability in SLA is correlated with a wider ecological breadth. We also found evidence that variation in traits can improve trait-environment matching, a relationship which may facilitate our understanding ecological breadth along prevailing gradients, and community assembly on the basis of traits.
Data from: When phenotypes do not match genotypes – unexpected phenotypic diversity and potential environmental constraints in Icelandic stickleback
Divergent lateral plate phenotypes in stickleback represent one of only a few cases known where a single gene underlies the phenotype under divergent selection between different habitats. However, the selection pressures leading to the repeated loss of lateral plates in freshwater are still not well understood. By genotyping 838 individuals from nine independently colonized lakes and one marine population in Iceland, we found i) that only in some lakes are phenotypes associated with the expected genotype and ii) that the independent repeated occurrence of a rarely described plate phenotype is expressed in the absence of an allele that is usually associated with this phenotype. This suggests that either other genes such as modifiers might be under divergent selection between lakes or that lateral plate expression in these populations is restricted due to environmental constraints.
Three datasets of global monthly gross primary productivity (GPP) during 2003-2018 derived from SIF, NIRv and LAI and their best-matching environmental factors
<p>As the largest source of uncertainty in carbon cycle studies, accurate quantification of gross primary productivity (GPP) is critical for the global carbon budget in the context of global climate change. Numerous remote sensing vegetation indices (VIs) have participated in the estimation of global GPP. However, the relative performance of various VIs in estimating GPP and what additional factors should be combined with them to reveal the photosynthetic capacity of vegetation mechanistically better are still poorly understood.</p> <p>We used the Random Forest (RF) algorithm to identify the factors with the most powerful explanation of GPP and to explore the importance of these predictors. We trained six RF models to select features, i.e., two types of models (Plant Functional Type [PFT]-specific and universal) for each vegetation index (SIF, NIRv, and LAI). Each model comprised 100 decision trees, was sampled without replacement, and was trained using 70% of the data. Model performance was evaluated using out-of-bag (OOB) R-squared (R<sup>2</sup>) and root mean square error (RMSE) values. The predictor with the lowest importance score in the iteration was removed and the whole procedure was then repeated until only the vegetation index, CO<sub>2</sub>, and PFTs were left. The predictors used to estimate GPP were identified based on the performance curve of OOB R<sup>2</sup> and RMSE. The determination of the model is based on the principle that further reductions in the number of predictors would considerably reduce model performance, while increasing the number of predictors would not significantly improve model performance.</p> <p>Here we provide a set of high-spatial resolution (1/12°) global gridded products of monthly GPP for 2003-2018 generated for each vegetation index based on a generic model with an optimal configuration, i.e., an optimal combination of VI and other relevant variables using the RF algorithm. R<sup>2</sup> of three optimal VI-based GPP estimation models ranges from 0.84 to 0.85, and RMSE ranges from 1.51g C·m<sup>−2</sup>·d<sup>−1</sup> to 1.54g C·m<sup>−2</sup>·d<sup>−1</sup>. More information about the datasets can be found in Zhao and Zhu (2022) <strong><em>Remote Sensing</em></strong>.</p> <p><em>Zhao W, Zhu Z. Exploring the Best-Matching Plant Traits and Environmental Factors for Vegetation Indices in Estimates of Global Gross Primary Productivity[J]. Remote Sensing, 2022, 14(24): 6316.</em></p>
Data from: When phenotypes do not match genotypes – unexpected phenotypic diversity and potential environmental constraints in Icelandic stickleback
Open the record for dataset details and reuse information.
Data from: Genotype matching in a parasitoid-host genotypic food web: an approach for measuring effects of environmental change
Open the record for dataset details and reuse information.
Data from:Intraspecific variability improves environmental matching, but does not increase ecological breadth along a wet-to-dry ecotone
Open the record for dataset details and reuse information.
Data from: Should I change or should I go? phenotypic plasticity and matching habitat choice in the adaptation to environmental heterogeneity
It can be challenging for organisms to achieve a good match between their phenotypic characteristics and environmental requirements that vary in space and time. The evolution of adaptive phenotypes can result from genetic differentiation at the population level. Individuals, however, could also change their phenotype (adaptive plasticity) or select an environment because it matches with their phenotype (matching habitat choice). It is poorly known under which conditions these different solutions to environmental heterogeneity evolve and whether they operate together. Using an individual-based simulation model, we assessed which solutions evolved depending on degree of temporal variation, costs of multiple underlying traits, and order of dispersal and development. Population genetic divergence was superseded by plasticity or matching habitat choice as temporal variation increased. Plasticity and matching habitat choice were limited by their trait costs, even when this involved only a part of the underlying traits. Independent of the order of dispersal and development, plasticity evolved more commonly than matching habitat choice, in part because the match a phenotype can achieve by matching habitat choice is limited by the types of environments available. Our results explain the apparent relative rarity of matching habitat choice in nature. At the same time, our results can be used to look for matching habitat choice in those biological systems where the conditions for other solutions seem unfavorable.
Data from: Long-term effects of early nutrition and environmental matching on developmental and personality traits in zebra finches
Developmental plasticity is a key feature of many organisms and individuals can benefit from early programming to optimize their phenotypes for the expected environmental conditions. However, environmental conditions may sometimes change unexpectedly. Mismatches between early and adult life, for example, can have important repercussions for adult phenotypes, potentially leading to better performance under matched than mismatched conditions as predicted by the predictive adaptive response hypothesis. We conducted a long-term experimental manipulation of dietary conditions in a population of zebra finches, Taeniopygia guttata. Broods were exposed to two early nutritional treatments until independence and we used a split-brood design to independently manipulate nutritional conditions after independence to create matched and mismatched nutritional environments in later life. Developmental trajectories of all individuals were followed for more than 5 years and we scored behavioural responses in trials in a special environment and while interacting with a special object three times during adult life. Overall, we found no evidence for early programming affecting morphology. Tarsus and wing length were exclusively influenced by the early nutrition. Body weight showed lasting effects of the early treatment and independent effects of nutritional condition during adulthood, but no effects of environmental matching or mismatching. Special-object trials showed effects of the adult nutritional treatment while environmental matching affected hopping activity in special environments. These behavioural responses showed substantial long-term individual stability over a 3-month period and were only marginally smaller when measured over a period of more than 4 years. Interestingly, survival of individuals from low-quality early nutritional condition was higher compared with high-quality early condition individuals, which became evident only after years of survival monitoring. Beyond the nutritional treatment itself, we found sizable brood identity effects that slowly but steadily declined with age, indicating a significant but decaying effect of natural variation in parental provisioning on adult phenotypes.
Data from: Long-term effects of early nutrition and environmental matching on developmental and personality traits in zebra finches
Open the record for dataset details and reuse information.
Data from: Should I change or should I go? phenotypic plasticity and matching habitat choice in the adaptation to environmental heterogeneity
Open the record for dataset details and reuse information.
Data from: Ecological impacts of invasive alien species along temperature gradients: testing the role of environmental matching
Open the record for dataset details and reuse information.
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.