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.
759
datasets available to search
ShareScore release 0.9.0
Dataset results
759 results for “Plant–plant interactions”
Figs. 3 A-E in Copper and zinc interactions: morphophysiological responses in sweet potato plants (Ipomoea batatas L.)
Figs. 3 A-E. Effects of treatments with different Cu and Zn concentrations on antioxidant metabolism in sweet potato plants (Ipomoea batatas L.). A. Superoxide dismutase (SOD); B. Ascorbate peroxidase (APX); C. Catalase (CAT); D. Lipid peroxidation (MDA); E. Hydrogen peroxide (H2O2) content. Means followed by the same lowercase letters, associated with either leaf or root tissues, do not differ significantly from one another based on Tukey's test (p <0.05).
Figs. 1 A-G in Copper and zinc interactions: morphophysiological responses in sweet potato plants (Ipomoea batatas L.)
Figs. 1 A-G. Effects treatments with Cu and Zn concentrations on morphological parameters of sweet potato plants (Ipomoea batatas L.). A. Shoot length (cm); B. Leaf number; C. Leaf area (cm2 plant-1); D. Shoot-fresh weight (mg); E. Shoot-dry weight (mg); F. Root-fresh weight (mg); G. Root-dry weight (mg). Means followed by the same letter among treatments do not differ significantly according to Tukey's test (p<0.05).
Figure 1a from: Eisenhauer N (2018) Aboveground-belowground interactions drive the relationship between plant diversity and ecosystem function. Research Ideas and Outcomes 4: e23688. https://doi.org/10.3897/rio.4.e23688
Figure 1a - Importance of the duration of the experiment for its outcome. <br> The effect of plant diversity on plant productivity and on the performance of decomposers increases over time. Regression between the R² of the relationship between plant diversity and plant productivity and the R² of the relationship between plant diversity and decomposer biomass/density. Data from the Jena Experiment from different years [plant productivity in 2003 – 2009; microbial biomass in 2003 – 2009 (white circles); meso- (gray circles) and macroinvertebrate densities (black circles) in 2004, 2006 and 2008].
Figure 3 from: Eisenhauer N (2018) Aboveground-belowground interactions drive the relationship between plant diversity and ecosystem function. Research Ideas and Outcomes 4: e23688. https://doi.org/10.3897/rio.4.e23688
Figure 3 - Plant diversity effects on soil microbes more pronounced at elevated [CO2]. Microbial biomass (µg Cmic g-1 soil dry mass) and basal respiration (BR; µl O2 h-1 g-1 soil dry mass) as affected by plant species richness (SR) and CO2 concentrations. Dashed lines indicate ambient CO2 levels, solid lines elevated CO2 levels (+180 ppm). SR x CO2 for Cmic: p=0.007; SR x CO2 for BR: p=0.03). Data from August 2010. Means with SE. Redrawn after Eisenhauer et al. (2013).
Figure 4 from: Eisenhauer N (2018) Aboveground-belowground interactions drive the relationship between plant diversity and ecosystem function. Research Ideas and Outcomes 4: e23688. https://doi.org/10.3897/rio.4.e23688
Figure 4 - Conceptual figure showing how global change drivers like temperature increase and drought may increase plant diversity–ecosystem function relationships.
Figure 2 from: Eisenhauer N (2018) Aboveground-belowground interactions drive the relationship between plant diversity and ecosystem function. Research Ideas and Outcomes 4: e23688. https://doi.org/10.3897/rio.4.e23688
Figure 2 - Conceptual scheme of how aboveground–belowground interactions may influence the positive relationship between plant diversity and ecosystem functioning. The left part of the scheme illustrates how lower quantity and quality of plant inputs to the soil in species-poor plant communities (being low in resource use complementarity) may induce negative soil feedback effects. The right part of the scheme shows that higher quantity and quality of plant inputs in species-rich plant communities (being high in resource use complementarity) may cause the dominance of positive soil feedback effects. Mutualists will decrease (Wurst et al. 2008, Latz et al. 2012) and/or superimpose (Eisenhauer et al. 2012a) detrimental effects of antagonists on plants. The four proposed projects complement each other to explore the underlying mechanisms of this scheme across different experimental contexts.
Figure 1b from: Eisenhauer N (2018) Aboveground-belowground interactions drive the relationship between plant diversity and ecosystem function. Research Ideas and Outcomes 4: e23688. https://doi.org/10.3897/rio.4.e23688
Figure 1b - Importance of the duration of the experiment for its outcome. <br> Long-term plant diversity studies on soil biota are rare. Relationship between sampling time since the establishment of the biodiversity experiment, number of studies investigating soil biota and percentage of significant plant diversity effects on soil biota (Eisenhauer et al. 2012a). Size of the bubbles and respective numbers indicate percentage of significant plant diversity effects (regression between number of studies and time: R²=0.56, p=0.033, between time and significant plant diversity effects: R²=0.66, p=0.014, n=20 studies).
Fig. 2 in Review paper Stimulation of Plant Growth through Interactions of Bacteria and Protozoa: Testing the Auxiliary Microbial Loop Hypothesis
Fig. 2. Effects of Acanthamoeba castellanii on root diameter size classes of a grass (Lolium perenne). Grass plants were grown for 20 days in presence (+ Amo) and absence (– Amo) of amoebae on 1% agar with ½ Murashigge and Skoog medium in Petri dishes with a diverse soil bacterial community (Kreuzer, unpublished).
Interaction between biocrusts and vascular plants shape semiarid dryland multifunctionality
Open the record for dataset details and reuse information.
Plant-Caterpillar-Parasitoid Interactions (myspecies): Resource (485) DwCA
Open the record for dataset details and reuse information.
Data from: Is there a temperate bias in our understanding of how climate change will alter plant-herbivore interactions? A meta-analysis of experimental studies
Climate change can drive major shifts in community composition and interactions between resident species. However, the magnitude of these changes depends on the type of interactions and the biome in which they take place. We review the existing conceptual framework for how climate change will influence tropical plant-herbivore interactions and formalize a similar framework for the temperate zone. We then conduct the first biome-specific tests of how plant-herbivore interactions change in response to climate-driven changes in temperature, precipitation, ambient CO2, and ozone. We used quantitative meta-analysis to compare predicted and observed changes in experimental studies. Empirical studies were heavily biased toward temperate systems, so testing predicted changes in tropical plant-herbivore interactions was virtually impossible. Furthermore, most studies investigated the effects of CO2 with limited plant and herbivore species. Irrespective of location, most studies manipulated only one climate change factor despite the fact that different factors can act in synergy to alter responses of plants and herbivores. Finally, studies of belowground plant-herbivore interactions were also rare; those conducted suggest that climate change could have major effects on belowground subsystems. Our results suggest that there is a disconnection between the growing literature proposing how climate change will influence plant-herbivore interactions and the studies testing these predictions. General conclusions will also be hampered without better integration of above- and belowground systems, assessing the effects of multiple climate change factors simultaneously, and using greater diversity of species in experiments.
Figure 1 in Community-level plant-pollinator interactions in a Palaeotropical montane evergreen oak forest ecosystem
Figure 1. Map of study sites S1–S5 in Laos. See Table 1 for details of the sites.
Data from: The interaction between ambush predators, search patterns of herbivores and aggregations of plants
<p>While predators benefit from spatial overlap with their prey, prey strive to avoid predators. I used an individual-based simulation comprising sit-and-wait predators, widely-foraging herbivores, and plants, to examine the link between predator ambush location, herbivore movement, and plant aggregation. I used a genetic algorithm to reach the best strategies for all players. The predators could ambush herbivores either inside or outside plant patches. The herbivores could use movement of varying directionality levels, with a change in directionality following the detection of plants. When the predators were fixed outside plant patches, the herbivores were selected to use a directional movement before plant encounter followed by a tortuous movement afterwards. When predators were fixed inside patches, herbivores used a continuous directional movement. Predators maintained within-patch positions when the herbivores were fixed to use the directional-tortuous movement. The predator location inside patches led to higher plant aggregations, by changing the herbivore movement. Finally, I allowed half of the predators to search for herbivores and let them compete with sit-and-wait predators located inside plant patches. When plants were clumped and herbivores used a directional-tortuous movement, with a movement shift after plant detection, ambush predators had a higher success relative to widely-foraging predators. In all other scenarios, widely-foraging predators did much better than ambush predators. The findings from my simulation suggest a behavioral mechanism for several observed phenomena of predator-prey interactions, such as a shorter stay by herbivores in patches when predators ambush them nearby, and a more directional movement of herbivores in riskier habitats.</p>
Data from: Modulation of plant-mediated interactions between herbivores of different feeding guilds: effects of parasitism and belowground interactions
Herbivory affects subsequent herbivores, mainly regulated by the phytohormones jasmonic (JA) and salicylic acid (SA). Additionally, organisms such as soil microbes belowground or parasitoids that develop inside their herbivorous hosts aboveground, can change plant responses to herbivory. However, it is not yet well known how organisms of trophic levels other than herbivores, below- and above-ground, alter the interactions between insect species sharing a host plant. Here, we investigated whether the parasitoid Aphidius colemani and different soil microbial communities (created through plant-soil feedbacks) affect the JA and SA signalling pathways in response to the aphid Myzus persicae and the thrips Frankliniella occidentalis, as well as subsequent thrips performance. Our results show that the expression of the JA-responsive gene CaPINII in sweet pepper was more suppressed by aphids than by parasitised aphids. However, parasitism did not affect the expression of CaPAL1, a biosynthetic gene of SA. Furthermore, aphid feeding enhanced thrips performance compared with uninfested plants, but this was not observed when aphids were parasitised. Soils where different plant species were previously grown, did not affect plant responses or the interaction between herbivores. Our study shows that members of the third trophic level can modify herbivore interactions by altering plant physiology.
Capabilities and limitations of using DNA metabarcoding to study plant-pollinator interactions
<p>Many pollinator populations are experiencing declines, emphasizing the need for a better understanding of the complex relationship between bees and flowering plants. Using DNA metabarcoding to describe plant-pollinator interactions eliminates many challenges associated with traditional methods and has the potential to reveal a more comprehensive understanding of foraging behavior and pollinator life history. Here we use DNA metabarcoding of ITS2 and<i> rbcL</i> gene regions to identify plant species present in pollen loads of 404 bees from three habitats in eastern Oregon. Our specific objectives were to 1) determine whether plant species identified using DNA metabarcoding are consistent with plant species identified using observations, 2) compare characterizations of diet breadth derived from foraging observations to those based on plant species assignments obtained using DNA metabarcoding, and 3) compare plant species assignments produced by DNA metabarcoding using a "regional" reference database to those produced using a "local" database. At the three locations, 31-86% of foraging observations were consistent with DNA metabarcoding data, 8-50% of diet breadth characterizations based on observations differed from those based on DNA metabarcoding data, and 22-25% of plant species detected using the regional database were not known to occur in the study area in question. Plant-pollinator networks produced from DNA metabarcoding data had higher sampling completeness and significantly lower specialization than networks based on observations. Here, we examine some strengths and limitations of using DNA metabarcoding to identify plant species present in bee pollen loads, make ecological inferences about foraging behavior, and provide guidance for future research.</p>
Revealing cryptic interactions between large mammalian herbivores and plant-dwelling arthropods via DNA metabarcoding
<p><span>In the past decade, it has become clear that omnivory, feeding on more than one trophic level, is important in natural and agricultural systems. Large mammalian herbivores (LMH) frequently encounter plant-dwelling arthropods (PDA) on their food plants. Yet, ingestion of PDA by LMH is only rarely addressed and the extent of this direct trophic interaction, especially at the PDA community level, remains unknown. Using a DNA metabarcoding analysis on feces of free-ranging cattle from a replicated field experiment of heavily and moderately grazed paddocks, we reveal that feeding cattle (incidentally) ingest an entire food-chain of PDA including herbivores, predators and parasites. Overall, 25 families of insects and 4 families of arachnids were ingested, a pattern that varied over the season, but not with grazing intensity. We identified the functional groups of PDA vulnerable to ingestion, such as sessile species and immature life stages. Most of the fecal samples (76%) contained sequences belonging to PDA, indicating that direct interactions are frequent. This study highlights the complex trophic connections between LMH and PDA. It may even be appropriate to consider LMH as omnivorous enemies of PDA. </span></p>
Pollen transport networks reveal highly diverse and temporally stable plant-pollinator interactions in an Appalachian floral community
<p>Floral visitation alone has been typically used to characterize plant-pollinator interaction networks even though it ignores differences in the quality of floral visits (e.g. transport of pollen) and thus may overestimate the number and functional importance of pollinating interactions. However, how network structural properties differ between floral visitation and pollen transport networks is not well understood. Furthermore, the strength and frequency of plant-pollinator interactions may vary across fine temporal scales (within a single season) further limiting our predictive understanding of the drivers and consequences of plant-pollinator network structure. Thus, evaluating the structure of pollen transport networks and how they change within a flowering season may help increase our predictive understanding of the ecological consequences of plant-pollinator network structure. Here we compare plant-pollinator network structure using floral visitation and pollen transport data and evaluate within-season variation in pollen transport network structure in a diverse plant-pollinator community. Our results show that pollen transport networks provide a more accurate representation of the diversity of plant-pollinator interactions in a community but that floral visitation and pollen transport networks do not differ in overall network structure. Pollen transport network structure was relatively stable throughout the flowering season despite changes in plan and pollinator species composition. Overall, our study highlights the need to improve our understanding of the drivers of plant-pollinator network structure in order to more fully understand the process that govern the assembly of these interactions in nature.</p>
Datasets of Fornoni et al. FREQUENCY DEPENDENT SELECTION AND THE EVOLUTION OF RECIPROCAL EXPLOITATION IN PLANT-ANIMAL INTERACTIONS.
<p>Datasets and RMarkdown</p> <p><span lang="EN-GB">Paper title: FREQUENCY DEPENDENT SELECTION AND THE EVOLUTION OF RECIPROCAL EXPLOITATION IN PLANT-ANIMAL INTERACTIONS.</span></p> <p><span lang="EN-GB">Authors: </span><span lang="ES-MX">Juan Fornoni, </span><span lang="EN-GB">Sergio Ramos, Roberto Alvarez-Martínez, Carlos Cordero, </span><span lang="EN-GB">and César A. Domínguez</span></p>
Data from: Phylogenetic and functional mechanisms of direct and indirect interactions among alien and native plants
Open the record for dataset details and reuse information.
Data from: Woody plant biomass and carbon exchange depend on elephant-fire interactions across a productivity gradient in African savanna
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.