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.
205
datasets available to search
ShareScore release 0.9.0
Dataset results
205 results for “Functional ecology”
Data from: Rewilded mammal assemblages reveal the missing ecological functions of granivores
Open the record for dataset details and reuse information.
Data from: Unrecognized coral species diversity masks differences in functional ecology
Open the record for dataset details and reuse information.
The functional diversity of marsupial limbs is influenced by both ecology and developmental constraint
Open the record for dataset details and reuse information.
Data from: Trait-based functional dietary analysis provides a better insight into the foraging ecology of bats
Open the record for dataset details and reuse information.
Data from: Functional traits reveal the expansion and packing of ecological niche space underlying an elevational diversity gradient in passerine birds
Open the record for dataset details and reuse information.
The ecological function of insect egg micropyles
Open the record for dataset details and reuse information.
Data for: Functional response metrics explain and predict high but differing ecological impacts of juvenile and adult lionfish
Open the record for dataset details and reuse information.
Data from: Adaptive landscape and functional diversity of Neotropical cichlids: implications for the ecology and evolution of Cichlinae (Cichlidae; Cichliformes)
Open the record for dataset details and reuse information.
Data from: Implications of plant functional traits and drought survival strategies for ecological restoration
Open the record for dataset details and reuse information.
Data from: Spatiotemporal variations of vegetation and its determinants in the National Key Ecological Function Area on Loess Plateau between 2000 and 2015
Open the record for dataset details and reuse information.
Plumage patterns: ecological functions, evolutionary origins, and advances in quantification
Open the record for dataset details and reuse information.
Data from: Multifaceted functional diversity for multifaceted crop yield: towards ecological assembly rules for varietal mixtures
<p>Data and code for the study "Multifaceted functional diversity for multifaceted crop yield: towards ecological assembly rules for varietal mixtures"</p> <p>Two data files are available:</p> <ul> <li>"CWM_D.csv" contains one row per experimental plot with community-weighted mean (CWM) and Rao quadratic diversity (D) indices computed on the 19 functional traits.</li> </ul> <p>The first two columns ("genotype_1" & "genotype_2") are the identity of the two genotypes in the plot, which are identical in single-variety plots. The third column ("assoc") refers to the plot type: single-variety ("M") or mixed-variety ("P") plot. Then, all trait CWMs and Ds are reported as "CWM_trait_name" and "D_trait_name" , respectively. For single-variety plots, only CWMs are reported but in this case they correspond to unweighted-averaged trait values across replicated measurements within plots. Root trait names are followed by "sem" or "adv" depending if they were measured on seminal or adventitious roots. Reported traits are: "Angle_aer" (Aerial angle, °), "Angle_root" (Root angle, °), "Diam_sem/adv" (mean root diameter, mm), "SRL_sem/adv" (specific root length, m/g), "RTD_sem/adv" (root tissue density, g/cm3), "RBI_sem/adv" (root branching intensity, nb of root tips/cm), "RLD_sem/adv" (root length density, cm root/cm3 soil), "Till_nb" (tiller number per capita), "Ear_bio" (early biomass per capita, g), "SLA" (specific leaf area, m²/kg), "LNC" (leaf nitrogen content, %), "Height" (plant height, cm), "Heading" (heading date, Growing Degree Days), and "Maturity" (maturity date, Growing Degree Days).</p> <ul> <li>"RAW_RYT.csv" contains one row per experimental plot with absolute and relative measures of performance on several agronomic variables.</li> </ul> <p>The first two columns ("genotype_1" & "genotype_2") are the identity of the two genotypes in the plot, which are identical in single-variety plots. The third column ("assoc") refers to the plot type: single-variety ("M") or mixed-variety ("P") plot. Then, all absolute and relative measures of agronomic performance are reported as "RAW_performance_variable_name" and "RYT_performance_variable_name", respectively. For single-variety plots, only absolute performances are reported. Reported performance variable are "GY" (Grain yield, g/m²), "GNb" (Grain number per m²), "SY" (Spike yield, g/m²), "SNb" (Spike number per m²), "BY" (Biomass yield, g/m²), "PY" (Protein yield, g/m²), "TKW" (Thousand kernel weight, g), "SeY" (Semolina yield, %), "GPC" (Grain protein content, %), "TW" (Test weight, kg/hL), "RLVA" (Rate of loss of vitreous aspect, %), "YI" (Yellowness index), "GPD" (Grain protein deviation, %).</p> <p>One R code file is available:</p> <ul> <li>"Mu_FD_Mu_CY_Analysis.R" contains all statistical analysis performed to produce the results presented in the main text and in the Supplementary Information of the study. It uses "CWM_D.csv" and "RAW_RYT.csv" files as inputs.</li> </ul>
Data from: Determinants of litter decomposition rates in a tropical forest: functional traits, phylogeny and ecological succession
Plant litter decomposition is one of the most important processes in terrestrial ecosystems, as it is a key factor in nutrient cycling. Decomposition rates depend on environmental factors, but also plant traits, as these determine the character of detritus. We measured litter decomposition rate for 57 common tree species displaying a variety of functional traits within four sites in primary and four sites in secondary tropical forest in Madang Province, Papua New Guinea. The phylogenetic relationships between these trees were also estimated using molecular data. The leaves collected from different tree species were dried for two days, placed into detritus bags and exposed to ambient conditions for two months. Nitrogen, carbon and ash content were assessed as quantitative traits and used together with a phylogenetic variance-covariance matrix as predictors of decomposition rate. The analysis of the tree species composition from 96 quadrats located along a successional gradient of swidden agriculture enabled us to determine successional preferences for individual species. Nitrogen content was the only functional trait measured to be significantly positively correlated with decomposition rate. Controlling for plant phylogeny did not influence our conclusions, but including phylogeny demonstrated that the mainly early successional family Euphorbiaceae is characterized by a particularly high decomposition rate. The acquisitive traits (high nitrogen content and low wood density) correlated with rapid decomposition were characteristic for early successional species. Decomposition rate thus decreased from early successional to primary forest species. However, the decomposition of leaves from the same species was significantly faster in primary than in secondary forest stands, very probably because the high humidity of primary forest environments keeps the decomposing material wetter.
Data from: Species' ecological functionality alters the outcome of fish stocking success predicted by a food-web model
Fish stocking is used worldwide in conservation and management but its effects on food-web dynamics and ecosystem stability are poorly known. To better understand these effects and predict the outcomes of stocking, we used an empirically validated network model of a well-studied lake ecosystem. We simulate two stocking scenarios with two native fish species valuable for fishing. In the first scenario, we stock planktivorous fish (whitefish) larvae in the ecosystem. This leads to 1% increase in adult whitefish biomasses and decreases the biomasses of the top predator (perch). In the second scenario, we also stock perch larvae in the ecosystem. This decreases the planktivorous whitefish and the oldest top predator age class biomasses, and destabilizes the ecosystem. Our results demonstrate that the effects of stocking depend on the species' position in the food web and thus cannot be assessed without considering interacting species. We further show that stocking can lead to undesired outcomes from both management and conservation perspectives. The gains of stocking can remain minor and have adverse effects on the entire ecosystem.
Data from: Biodiversity and thermal ecological function: the influence of freshwater algal diversity on local thermal environments
The influence of temperature on diversity and ecosystem functioning is well studied; the converse however, i.e. how biodiversity influences temperature, much less so. We manipulated freshwater algal species diversity in microbial microcosms to uncover how diversity influenced primary production, which is well documented in biodiversity research. We then also explored how visible-spectrum absorbance and the local thermal environment responded to biodiversity change. Variations in the local thermal environment, that is, in the temperature of the immediate surroundings of a community, are known to matter not only for the rate of ecosystem processes, but also for persistence of species assemblages and the very relationship between biodiversity and ecosystem functioning. In our microcosm experiment, we found a significant positive association between algal species richness and primary production, a negative association between primary production and visible-spectrum absorbance, and a positive association between visible-spectrum absorbance and the response of the local thermal environment (i.e., change in thermal infrared emittance over a unit time). These findings support an indirect effect of algal diversity on the local thermal environment pointing to a hitherto unrecognized biodiversity effect in which diversity has a predictable influence on local thermal environments.
Data from: Incorporating ecological functions in conservation decision making
Systematic conservation planning has become a standard approach globally, but prioritization of conservation efforts hardly considers species traits in decision-making. This can be important for species persistence and thus adequacy of the conservation plan. Here, we developed and validated a novel approach of incorporating trophic information into a systematic conservation planning framework. We demonstrate the benefits of this approach by using fish data from Europe´s second largest river, the Danube. Our results show that adding trophic information leads to a different spatial configuration of priority areas at no additional cost. This can enhance identification of priority refugia for species in the lower position of the trophic web while simultaneously identifying areas that represent a more diverse species pool. Our methodological approach to incorporating species traits into systematic conservation planning is generally applicable, irrespective of realm, geographical area and species composition and can potentially lead to more adequate conservation plans.
Supplementary data for: Mosquito phytophagy – sources exploited, ecological function, and evolutionary transition to haematophagy
<p>This dataset consists of two files:</p> <p><strong>Floral visitation records of mosquitoes</strong><br> Plant sugar, primarily in the form of floral nectar, is the ubiquitous basic food of adult mosquitoes. However, records of mosquito floral visitation are not usually the focus of research publications and, as such, are often reported as secondary parts of larger studies and are scattered throughout more than a century of scientific literature. Here we provide a summary of more than 500 recorded literature and field instances of floral and extra-floral nectary visitation by mosquitoes, including the plant and mosquito species involved as well as known pollination records.<br> <em>file name: Summary_of_Field_Mosquito_Floral_Visitation_Instances.xlsx</em></p> <p><strong>Summary of floral semiochemical blends that are attractive to mosquitoes</strong><br> Floral nectar is the primary food source of adult mosquitoes and mosquitoes, along with many other pollinators, use floral semiochemicals to locate this resource. Here we provide a summary of floral semiochemical blends attractive to mosquitoes that have been reported in the literature. The mosquito species involved have also been listed.<br> <em>file name: Summary_of_Floral_Semiochemical_Blends_Attractive_to_Mosquitoes.xlsx</em></p>
Supplementary material 1 from: Cerrato C, Rocchia E, Brunetti M, Bionda R, Bassano B, Provenzale A, Bonelli S, Viterbi R (2019) Butterfly distribution along altitudinal gradients: temporal changes over a short time period. In: Mazzocchi MG, Capotondi L, Freppaz M, Lugliè A, Campanaro A (Eds) Italian Long-Term Ecological Research for understanding ecosystem diversity and functioning. Case studies from aquatic, terrestrial and transitional domains. Nature Conservation 34: 91-118. https://doi.org/10.3897/natureconservation.34.30728
Supplementary data
Ecological resilience of physical plant–soil feedback to chronic deer herbivory: slow, partial but functional recovery
<p>Ecological resilience to ungulate overbrowsing is an important issue in forest ecosystem. After chronic herbivory, the recovery rate of understory vegetation and its related functions can be slow even with decreasing grazing intensity; thus, detecting elasticity during alternative successional trajectories is fundamental to understanding state perturbations. In this context, we focused on physical plant–soil feedback (functional interactions between plant growths and soil physical conditions), and evaluated elasticity and recovery processes according to deer density. The effects of 40-year chronic herbivory by sika deer (average density 14.7 individuals km<sup>-2</sup>) on the recovery of understory plant communities and associated improvements in soil physical properties in headwater catchments were assessed. Using 8 years of catchment-wide exclusion (fenced) and reduction (only culled; average 4.3 individuals km<sup>-2</sup>) treatments, plot sampling was conducted in 2010 (before treatment) and 2018 (after treatment). The recovery of vegetation and soil physical properties were evaluated, and functional plant–soil relationships and spatial variability were assessed to detect recovery processes during alternative successional trajectory. Woody species increased only under the exclusion treatment and the average soil bulk density was lower than that under reduction treatments. Soil bulk density was negatively correlated with root biomass in the fenced catchment, and root biomass was positively associated with woody species richness. Reduced soil bulk density (~0.5 g cm<sup>-3</sup>) was observed with greater root biomass and woody species richness on upper hillslopes in the deer-excluded catchment where plant coverage was minimal. Successional failure under the reduction treatment suggested slow recovery with a depressed threshold according to deer density, indicating a clockwise hysteretic response to deer density. Unlike plant coverage during the earlier period of overbrowsing, woody species root development led the recovery of functional physical plant–soil feedback; however, this was probably limited by the higher soil erosion rate in riparian areas and an underdeveloped herb layer. Our results highlight an alternative recovery trajectory of physical plant–soil feedback driven by an alternative plant element (woody roots) to degradation trajectory with decreasing plant cover. However, riparian erosion and herb layer would still suppress recovery. Therefore, recovery might be slower at landscape scale.</p>
Data from: Community functional trait composition at the continental scale: the effects of non-ecological processes
Ecological communities and their response to environmental gradients are increasingly being described by measures of trait composition at the community level – the trait-based approach. Whether ecological or non-ecological processes influence trait composition between communities has been debated. Understanding the processes that influence trait composition is important for reconstructing paleoenvironmental conditions from fossil deposits and for understanding changes in community functionality through time. Here, we assess the influence of ecological and non-ecological processes on the distribution of traits within North American mammals. We found that non-ecological processes including historical contingency, spatial autocorrelation, and evolutionary history do not influence trait composition; however, the variance in trait composition is highly explained by climate gradients. Our results suggest that habitat breadth, terrestriality, diet breadth, and reproductive traits are strong candidates as proxies for measuring functional aspects of environments in the past and present.
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.