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.
52
datasets available to search
ShareScore release 0.9.0
Dataset results
52 results for “carnivorous plant”
Prey Capture by Carnivorous Plants Worldwide 1923-2007
Available phylogenetic data illustrate that in all carnivorous lineages, the ancestral trap type is a sticky, flypaper-type trap (Ellison and Gotelli, 2001). In the Caryophyllales, pitfall traps (Nepenthes) and snap traps (Dionaea and Aldrovanda) are derived relative to the sticky pads of Drosera. Similarly, in the Lamiales, the sticky-leaved Pinguicula is ancestral to Genlisea with its eel (or lobster-pot) traps and Utricularia with its vacuum traps. In the Ericales, the Sarraceniaceae with its pitfall traps are derived relative to Roridula, another species with flypaper traps. Muller et al. (2004) hypothesed that carnivorous genera with rapidly evolving genomes (Genlisea and Utricularia) have more predictable and frequent captures of prey than do genera with more slowly evolving genomes; by extension it could be hypothesized that in general, carnivorous plants with more complex traps should have more predictable and frequent captures of prey than do those with relatively simple traps. Increases in predictability and frequency of prey capture could be achieved by evolving more elaborate mechanisms for attracting prey, by specializing on particular types of prey, or, as Darwin suggested, by specializing on particular (large) sizes of prey. In all cases, one would expect that prey actually captured would not be a random sample of the available prey. Furthermore, when multiple species of carnivorous plants co-occur, one would predict, again following Darwin that interspecific competition would lead to specialization on particular kinds of prey. Because the traps of carnivorous plants accumulate identifiable remains of prey, analysis of trap contents can provide an aggregate record of the prey that have been successfully "sampled" by the plant. Such samples could be used to begin to test the hypothesis that carnivorous plant genera differ in prey composition and to look for evidence of specialization in prey capture. Over the past 80 years, numerous ecologists have gat
Construction Costs of Carnivorous and Non-Carnivorous Plants at Harvard Forest 2006-2008
Leaf traits, including photosynthetic rates, leaf mass area, and leaf nutrient content covary in a coordinated way for a wide range of plant taxa. This covariation results from trade-offs between the costs of constructing plant tissues and the benefits accrued from photosynthesis. Carnivorous plants have been found to be outliers in the "universal spectrum of leaf traits" because they have very low photosynthetic rates for the amount of nitrogen in their leaves and traps. But no studies have measured simultaneously the actual construction costs of carnivorous traps and rates of photosynthesis to determine the amortization required to recover the investment (the "payback time") and thereby calculate the "marginal gain" of "investing" in carnivorous structures. The objective of this study was to measure construction costs (CCmass, grams of glucose required to build 1g of ash-free dry mass of tissue) and photosynthesis (Amass, nmol CO2 g-1 s-1) for traps, leaves, roots, and rhizomes of 15 carnivorous plant species with differing mechanisms of prey capture and consumption (pitfall traps, snap-traps, sticky pads) grown under greenhouse conditions. Payback time (h) was calculated as the quotient of CCmass and Amass after conversion to nmol of carbon per gram of ash-free dry mass. There were highly significant differences amongst species for CCmass of traps but there were no significant differences for CCmass amongst traps, roots and rhizomes. Mean (+- SD) CCmass for traps (1.14 +- 0.24 g glucose g-1) was significantly lower than the mean CCmass of leaves of 267 non-carnivorous plant species (1.47 +- 0.17 g glucose g-1). However, all 15 carnivorous plants examined in this study had low Amass and thus, the marginal gain of carnivory is small with a long payback time (524-1641 h). Our results of low CCmass for carnivorous traps is contrary to the oft-stated expectation of a high cost to construct elaborate carnivorous traps. Payback time integrates traits used to assess leaf
Ecophysiology of Carnivorous Plants Worldwide 1980-2011
Identification of trade-offs among physiological and morphological traits and their use in cost-benefit models and ecological or evolutionary optimization arguments have been hallmarks of ecological analysis for at least 50 years. Carnivorous plants are model systems for studying a wide range of ecophysiological and ecological processes and the application of a cost-benefit model for the evolution of carnivory by plants has provided many novel insights into trait-based cost-benefit models. Central to the cost-benefit model for the evolution of botanical carnivory is the relationship between nutrients and photosynthesis; of primary interest is how carnivorous plants efficiently obtain scarce nutrients that are supplied primarily in organic form as prey, digest and mineralize them so that they can be readily used, and allocate them to immediate versus future needs. Most carnivorous plants are terrestrial - they are rooted in sandy or peaty wetland soils - and most studies of cost-benefit trade-offs in carnivorous plants are based on terrestrial carnivorous plants. However more than 10% of carnivorous plants are unrooted aquatic plants. By examining data published between 1980 and 2011, we ask whether the cost-benefit model applies equally well to aquatic carnivorous plants and what general insights into trade-off models are gained by this comparison. Nutrient limitation is more pronounced in terrestrial carnivorous plants, which also have much lower growth rates and much higher ratio of dark respiration to photosynthetic rates than aquatic carnivorous plants. Phylogenetic constraints on ecophysiological trade-offs among carnivorous plants remain unexplored. Despite differences in detail, the general cost-benefit framework continues to be of great utility in understanding the evolutionary ecology of carnivorous plants. We provide a research agenda that if implemented would further our understanding of ecophysiological trade-offs in carnivorous plants and also would pro
Species Distribution Modeling of Carnivorous Plants Worldwide
Forecasting how carnivorous plant species will respond to climatic change is a key issue in their conservation and management but presents a number of challenges. These challenges derive from interactions between the relatively simplistic statistical methods typically used to forecast species responses to climatic change, which to date have been limited mainly to species distribution models (“SDMs) and particular aspects of the ecology of carnivorous plants, including their rarity, habitat specialization, and limited dispersal ability. The small ranges and oftentimes low local abundance of carnivorous plants provide few occurrence records, which increase the potential for poorly or over-fitted SDMs and misspecification of relationships with their “optimal” environments. The unique habitats in which carnivorous plants often grow also are difficult to characterize using the basic temperature and precipitation data that often undergird SDMs. Rather, habitats in which carnivorous plants are common often are decoupled from broader climatic patterns (e.g., many retain high soil moisture even during seasonal drought) and may be associated with frequent disturbance. Last, dispersal limitation also may constrain range shifts of carnivorous plants as the climate changes. These three issues raise two related questions that are critical for understanding and forecasting the future of carnivorous plants. First, to what extent are current carnivorous plants distributions constrained by climate; and second, how readily, if at all, might carnivorous plants disperse to colonize new habitat as it becomes climatically suitable? We estimated the vulnerability of carnivorous plants to climatic change in light of challenges identified with SDMs in general and their particular application to these unique species. We combined two approaches: “ensembles of small models”, which attempt to deal with the challenges of fitting SDMs for data-limited species; and “bioclimatic velocity”, which is
The terrestrial carnivorous plant Utricularia reniformis sheds light on environmental and life-form genome plasticity: Annotation, Gene Ontology and raw data
<p><strong>Description:</strong> In this work, we deeply sequenced (genome and transcriptome of different organs), assembled, and analyzed the 311-Mbp genome of the terrestrial carnivorous plant <em>U. reniformis</em> (Lentibulariaceae). This project presents great importance to the understanding of genomic, evolutive and functional aspects of<em> U. reniformis</em>, which may, with the next-generation sequencing and computational biology approaches shed light to a better understanding not only for the biology and evolution of <em>Utricularia</em> genus, but also for other genera and lineages of the Lentibulariaceae family. Here we present all the raw data generated, including annotation and gene ontology files.</p> <p><strong>External Information</strong></p> <p><a href="https://genomevolution.org/coge/GenomeInfo.pl?gid=54799">Genome Browser</a> avaliable at CoGe Portal (https://genomevolution.org/coge/GenomeInfo.pl?gid=54799)</p> <p><a href="http://https://www.ncbi.nlm.nih.gov/bioproject/290588">GenBank </a><a href="http://https://www.ncbi.nlm.nih.gov/bioproject/290588">Bioproject</a> (https://www.ncbi.nlm.nih.gov/bioproject/290588) for raw genomic and transcriptomic reads</p> <p><a href="https://bv.fapesp.br/en/auxilios/84264/genomics-and-transcriptomics-of-utricularia-reniformis-lentibulariaceae-an-evolutive-and-function/">FAPESP grant website</a> contaning the project abstract and other information.</p> <p><strong>Papers published related to <em>Utricularia reniformis</em> genome</strong></p> <pre><strong>[1]</strong> Silva SR, Diaz YC, Penha HA, Pinheiro DG, Fernandes CC, Miranda VF, MichaelTP, Varani AM. <strong>The Chloroplast Genome of Utricularia reniformis Sheds Light on the Evolution of the ndh Gene Complex of Terrestrial Carnivorous Plants from the Lentibulariaceae Family</strong>. PLoS One. 2016 Oct 20;11(10):e0165176. doi:<strong><a href="https://www.ncbi.nlm.nih.gov/pubmed/27764252">10.1371/journal.pone.0165176</a></strong>. </pre> <pre><strong>[2] </strong>Silva SR, Alvarenga DO, Aranguren Y, Penha HA, Fernandes CC, Pinheiro DG, Oliveira MT, Michael TP, Miranda VFO, Varani AM. <strong>The mitochondrial genome of the terrestrial carnivorous plant Utricularia reniformis (Lentibulariaceae): Structure, comparative analysis and evolutionary landmarks.</strong> PLoS One. 2017 Jul19;12(7):e0180484. doi: <strong><a href="https://www.ncbi.nlm.nih.gov/pubmed/28723946">10.1371/journal.pone.0180484</a></strong>.</pre> <pre><strong>[3] </strong>Silva SR, Moraes AP, Penha HA, Julião MHM, Domingues DS, Michael TP, Miranda VFO, Varani AM. <strong>The Terrestrial Carnivorous Plant Utricularia reniformis Sheds Light on Environmental and Life-Form Genome Plasticity.</strong> Int J Mol Sci. 2019 Dec 18;21(1). pii: E3. doi: <strong><a href="https://www.ncbi.nlm.nih.gov/pubmed/31861318">10.3390/ijms21010003</a></strong>.</pre> <p><strong>Acknowledgements</strong></p> <p>This work was supported by Sao Paulo Research Foundation FAPESP, Grant ID: [1325164-6]</p> <p> </p> <p><strong>---------------------------------------------------------</strong><br> <strong>FILES DESCRIPTION</strong><br> <strong>---------------------------------------------------------</strong><br> <br> ----------------<br> <strong>ANNOT-vFinal.sql: </strong>MySQL database containing all integrated annotation information of Urenif and Ugibba<br> ----------------<br> <strong>TABLE fields description</strong><br> gene_name gene name generated by EVidence Modeler + PASA<br> length gene lenght<br> status duplicate_gene_classifier status (0:singleton, 1:dispersed, 2:proximal, 3: tandem, 4:WGD)<br> product gene product <br> GOterms Blast2GO/OmicsBox GOterms<br> GO_mapping Blast2GO/OmicsBox GOterms derived from direct mapping (UniProt)<br> GO_annotation Blast2GO/OmicsBox annotated GOterms<br> GO_interpro Blast2GO/OmicsBox derived from InterProScan<br> EC Blast2GO/OmicsBox EC number<br> EC_name Blast2GO/OmicsBox enzyme name<br> NOG_annot EggNOG annotation description<br> NOG_EC EggNOG EC number<br> NOG_GO EggNOG GOterms<br> NOG_class EggNOG COG/KOG classfication<br> KEGG_Pathway EggNOG KEGG pathyways<br> KEGG_ko EggNOG KEGG ko<br> CAZy EggNOG CAZy enzymes<br> TAIR_gene Closest A. thaliana gene name (homologous) TAIR database lasted version<br> TAIR_annot Closest A. thaliana gene product (homologous) TAIR database lasted version <br> ortho MCL clustering among Vvinifera, Athaliana, and Slycopersicum (S:singleton, C: clustered, Y: shared)<br> ortho_two MCL clustering among Urenif and Ugibba (S:singleton, C: clustered, Y: shared)<br> -<br> -<br> ----------------<br> <strong>CEGs.zip </strong> 336 shared and concatenated CEGs from Urenif, U. gibba, Genlisea nigrocaulis, G. hispidula, G. aurea, G. pygmaea, and G. repens.<br> ----------------</p> <p><strong>ProcessRepeats_mod</strong> Modified version of RepeatMasker, ProcessRepeats script for detection of plant evolutionary lineages<br> ----------------</p> <p><strong>----------------------------------------------------------------------------------------------------------------------------------------------<br> <em>Utricularia gibba</em> files<br> ----------------------------------------------------------------------------------------------------------------------------------------------</strong><br> <strong>Ugibba</strong><strong>-no-masked.fa </strong> Ugibba genome excluding organellar genomes (provided by Lan et al., 2017)<br> <strong>Ugibba-softmasked.fa</strong> Ugibba genome RepeatMasker softmasked and excluding organellar genomes (provided by Lan et al., 2017)<br> <strong>Ug.collinearity </strong> MCScanX collinearity file<br> <strong>Ug-duplicates.txt</strong> MCScanX duplicate_gene_classifier short report<br> <strong>Ug.gene_type </strong> MCScanX duplicate_gene_classifier full report<br> <strong>Ug.tandem </strong> Ugibba tandem genes generated by MCScanX tool<br> <strong>Ugibba_annot.annot </strong> Blast2GO/OmicsBox annotation file (eudicotyledons filtered and Viridiplantae GOSlim) <strong>Ugibba_annot-</strong><strong>noclean</strong><strong>.</strong><strong>annot</strong><strong> </strong> Blast2GO/OmicsBox annotation file (not filtered)<br> <strong>Ugibba</strong><strong>.cDNA</strong> Ugibba cDNAs fasta file<br> <strong>Ugibba</strong><strong>.CDS </strong> Ugibba CDSs fasta file<br> <strong>Ugibba</strong><strong>-EVM.all-no-TEs-PASA-ANNOTATED.gff3</strong> Ugibba GFF3 file fully annotated (including gene products and GO terms)</p> <p><strong>Ugibba</strong><strong>-EVM.all-no-TEs-PASA.gff3</strong> Ugibba GFF3 file fully annotated (genes only)<br> <strong>Ugibba_export.txt</strong> Blast2GO/OmicsBox full exported table<br> <strong>Ugibba_fasta.fasta</strong> Blast2GO/OmicsBox Ugibba fasta proteins containg annotation (product and GO terms)<br> <strong>ugibba_frozen_cleaned-validated.box</strong> Full Blast2GO/OmicsBox file</p> <p><strong>ugibba_frozen.box</strong> Full Blast2GO/OmicsBox file (containing TEs genes annotation)</p> <p><strong>ugibba_nogs_emapper_annotations.box</strong> Full Blast2GO/OmicsBox EggNOG file (containing TEs genes annotation)</p> <p><strong>Ugibba_GAF.txt</strong> GAF file<br> <strong>Ugibba</strong><strong>.gene</strong> Ugibba gene fasta file<br> <strong>Ugibba_GOstat.txt </strong> GOstat file<br> <strong>Ugibba</strong><strong>-PASA-assemblies.fasta </strong> Ugibba PASA assemblies<br> <strong>Ugibba</strong><strong>-PASA.stats </strong> Ugibba annotation STATS<br> <strong>Ugibba</strong><strong>.</strong><strong>prot</strong><strong> </strong> Ugibba protein fasta file<br> <strong>Ugibba</strong><strong>-RepeatMasker.gff </strong> Ugibba RepeatMasker gff file<br> <strong>Ugibba</strong><strong>-RepeatMasker.gff3 </strong> Ugibba RepeatMasker gff3 file<br> <strong>Ugibba</strong><strong>-RepeatMasker.tbl </strong> Ugibba RepeatMasker results<br> <strong>Ugibba</strong><strong>-RepeatMasker-v2.gff3</strong> Ugibba RepeatMasker gff3 second version file<br> <strong>Ugibba</strong><strong>-RNAseq-assembled.fasta </strong> Ugibba RNAseq assembled transcriptome (Trinity)<br> <strong>Ugibba_TEs_DANTE_2019.fa </strong> Ugibba TEs library, detected by REPET and annotated by PASTEC and DANTE<br> <strong>Ugibba_WEGO.txt </strong> WEGO file</p> <p><strong>----------------------------------------------------------------------------------------------------------------------------------------------<br> <em>Utricularia reniformis</em> files<br> ----------------------------------------------------------------------------------------------------------------------------------------------</strong><br> <strong>Urenif</strong><strong>-no-masked.fa </strong> Urenif genome excluding organellar genomes<br> <strong>Urenif</strong><strong>-</strong><strong>softmasked</strong><strong>.fa</strong> Urenif genome RepeatMasker softmasked and excluding organellar genomes<br> <strong>Ur.collinearity </strong> MCScanX collinearity file<br> <strong>Ur-duplicates.txt </strong> MCScanX duplicate_gene_classifier short report<br> <strong>Ur.gene_type</strong> MCScanX duplicate_gene_classifier full report<br> <strong>Ur.tandem</strong> Urenif tandem genes generated by MCScanX tool<br> <strong>Urenif_annot.annot</strong> Blast2GO/OmicsBox annotation file (eudicotyledons filtered and Viridiplantae GOSlim)<br> <strong>Urenif_annot-</strong><strong>noclean</strong><strong>.</strong><strong>annot</strong> Blast2GO/OmicsBox annotation file (not filtered)<br> <strong>Urenif</strong><strong>.cDNA</strong> Urenif cDNAs fasta file<br> <strong>Urenif</strong><strong>.CDS </strong> Urenif cDNAs fasta file<br> <strong>Urenif</strong><strong>-EVM.all-no-TEs-PASA-ANNOTATED.gff3</strong> Urenif GFF3 file fully annotated (including gene products and GO terms)</p> <p><strong>Urenif</strong><strong>-EVM.all-no-TEs-PASA.gff3</strong> Urenif GFF3 file fully annotated (genes only)<br> <strong>Urenif_export.txt</strong> Blast2GO/OmicsBox full exported table<br> <strong>Urenif_fasta.fasta</strong> Blast2GO/OmicsBox Urenif fasta proteins containg annotation (product and GO terms)<br> <strong>urenif_frozen_cleaned-validated.box</strong> Full Blast2GO/OmicsBox file</p> <p><strong>urenif_frozen.box</strong> Full Blast2GO/OmicsBox file (containing TEs genes annotation)</p> <p><strong>urenif_nogs_emapper_annotations.box</strong> Full Blast2GO/OmicsBox EggNOG file (containing TEs genes annotation)<br> <strong>Urenif_GAF.txt </strong> GAF file<br> <strong>Urenif</strong><strong>.gene</strong> Urenif gene fasta file<br> <strong>Urenif_GOStat.txt </strong> GOstat file<br> <strong>Urenif</strong><strong>-PASA-assemblies.fasta</strong> Urenif PASA assemblies<br> <strong>Urenif</strong><strong>-PASA.stats </strong> Urenif annotation STATS<br> <strong>Urenif</strong><strong>.</strong><strong>prot</strong><strong> </strong> Urenif protein fasta file<br> <strong>Urenif</strong><strong>-RepeatMasker.gff </strong> Urenif RepeatMasker gff file<br> <strong>Urenif</strong><strong>-RepeatMasker.gff3 </strong> Urenif RepeatMasker gff3 file<br> <strong>Urenif</strong><strong>-RepeatMasker.tbl </strong> Urenif RepeatMasker results<br> <strong>Urenif</strong><strong>-RepeatMasker-v2.gff3 </strong> Urenif RepeatMasker gff3 second version file<br> <strong>Urenif</strong><strong>-RNAseq-assembled.fasta </strong> Urenif RNAseq assembled transcriptome (Trinity)<br> <strong>Urenif_TEs_DANTE_2019.fa </strong> Urenif TEs library, detected by REPET and annotated by PASTEC and DANTE<br> <strong>Urenif_WEGO.txt </strong> WEGO file<br> <strong>----------------------------------------------------------------------------------------------------------------------------------------------<br> ----------------------------------------------------------------------------------------------------------------------------------------------</strong></p>
Data from: Metabarcoding analysis provides insight into the link between prey and plant intake in a large alpine cat carnivore, the snow leopard
<p>Species of the family Felidae (a group represented by cats) are thought to be obligate carnivores, specialized for hunting and consuming other animals. However, the detection of plants in the feces of felids raises questions about the role of plants in their diet. This is particularly true for the snow leopard (Panthera uncia), a big cat native to central and South Asia's high mountains. Our study aimed to comprehensively identify the prey and plants consumed by snow leopards as well as six other sympatric mammals. We applied DNA metabarcoding methods on 126 fecal samples collected from the Sarychat-Ertash Nature Reserve in Kyrgyzstan. We found that among the three most common plant families in snow leopard feces, Tamaricaceae (genus Myricaraia) was consumed often by snow leopards. The genus Myricaria frequently appeared in samples lacking any animal prey DNA, indicating that snow leopards might have consumed this plant especially when their digestive tracts were empty. We also observed a significant difference in plant composition between male and female snow leopards, and potentially between sampling seasons. We provide a comprehensive overview of the prey and plants detected in the feces of snow leopards and sympatric mammals. We believe our findings will help in formulating hypotheses and guiding future research to understand the adaptive significance of plant-eating behavior in felids and animal-plant relationships in the ecosystem.</p>
Selection against early flowering in geothermally heated soils is associated with pollen but not prey availability in a carnivorous plant
<p>This data set includes data on flowering phenology, rosette diameters and fitness of the perennial herb Pinguicula vulgaris, as well as data on soil temperature and experimental treatment applied. The data was collected during the summer of 2020 in 287 plant individuals located in a sub-arctic geothermal area in Ölfus municipality in SW-Iceland, Hengill (64°03’N; 21°18’W, ~360 m.a.s.l.).</p>
Plant‐eating carnivores: Multispecies analysis on factors influencing the frequency of plant occurrence in obligate carnivores
<p>Plant-eating behavior is one of the greatest mysteries in obligate carnivores. Despite unsuitable morphological and physiological traits for plant consumption, the presence of plants in scat or stomach contents has been reported in various carnivorous species. However, researchers' interpretations of this subject are varied, and knowledge about it is scarce, without any multispecies studies. This study assessed the extent of variation in the frequency of plant occurrence in scat and stomach contents, as well as its relationship with various factors in 24 felid species using data from 213 published articles. Since the frequency of plant occurrence has not always been reported, we created two-part models and estimated parameters in a Bayesian framework. We found a significant negative relationship between the frequency of plant occurrence and body mass. This may be because plant-eating behavior reduces the energy loss caused by parasites and increases the efficiency of energy intake, which has a greater importance in smaller animals that have relatively high metabolic rates. This exploratory study highlights the importance of considering plant consumption in dietary studies on carnivorous species to understand the adaptive significance of this behavior and the relationship between obligate carnivores and plants.</p>
Data from: Pitcher geometry facilitates extrinsically powered 'springboard trapping' in carnivorous Nepenthes gracilis pitcher plants
<div> <p>Carnivorous pitcher plants capture insects in cup-shaped leaves that function as motionless pitfall traps. <em>Nepenthes gracilis</em>, evolved a unique 'springboard' trapping mechanism that exploits the impact energy of falling raindrops to actuate a fast pivoting motion of the canopy-like pitcher lid. We superimposed multiple computerized micro-tomography images of the same pitcher to reveal distinct deformation patterns in lid-trapping <em>N. gracilis</em> and closely related pitfall-trapping <em>N. rafflesiana</em>. We found prominent differences between downward and upward lid displacement in <em>N. gracilis </em>only. Downward displacement was characterised by bending in two distinct deformation zones while upward displacement was accomplished by evenly distributed straightening of the entire upper rear section of the pitcher. This suggests an anisotropic impact response, which may help to maximize initial jerk forces for prey capture, as well as the subsequent damping of the oscillation. Our results point to a key role of pitcher geometry for effective 'springboard' trapping in <em>N. gracilis</em>.</p> </div>
Review of Recent Trends in Measuring the Computing Systems Intelligence-Figure 1. Intelligence of different simple living creature (accessed 01.11.2017). 1.1. A carnivorous plants catching an insect (https://phys.org/news/2016-05-colombia-peace-reveal-jungle-species.html); 1.2. A colony of ants solving a very complex task (https://mappingignorance.org/2016/05/27/rafting-ants); 1.3. The collective behaviour of a school of fish (https://simple.wikipedia.org/wiki/Shoaling_and_schooling)
<p>The biological intelligence of different life forms, ranging from very simple (such as plants) to very complex (such as humans) is the subject of many studies and a large amount of research. Frequent studies related to different kind of biological intelligence include: the intelligence of horses (Krueger, & Heinze, 2008; Krueger, Farmer, & Heinze, 2014; Schuetz, Farmer, & Krueger, 2016), intelligence of pigs (Broom, Sena, & Moynihan, 2009), intelligence of dogs (Coren, 1995), intelligence of primates (Reader, Hager, & Laland, 2011) and so one. Figures 1, 2, and 3 present some biological life forms that are frequently considered intelligent. Trewavas (2002; 2005) considered that plants intelligence should be based on principles such as their ability to adjust their morphology, and phenotype accordingly to ensure self- preservation and reproduction. Figure 1.1 presents an intelligent plant (carnivorous) that uses a strategy for catching very fast flying insects. In order to eat the insect, it makes a movement. Figure 1.1 presents the catching of an insect by a carnivorous plant. The intelligence of colonies of ants, termites and other insects that live in large colonies is considered at the colony level (Brady, Fisher, Schultz, & Ward, 2014; Johnson, Borowiec, Chiu, Lee, Atallah, & Ward, 2013). Figure 1.2 presents the coherent intelligent surviving behaviour of a colony of a species of ants. The ants make a structural reorganization in order to move on the surface of the water. Figure 1.3 presents a very large school of fish with an intelligent coherent collective feeding and self-protecting behaviour. Each individual fish has a very simple behavior. Based on this it cannot be considered intelligent. The intelligence in large schools of fish emerges at the collective level (Shaw, 1978; Parrish, Viscedo, & Grunbaum, 2002).</p>
Data from: Pitcher geometry facilitates extrinsically powered ‘springboard trapping’ in carnivorous Nepenthes gracilis pitcher plants
Open the record for dataset details and reuse information.
Anthocyanin impacts multiple plant-insect interactions in a carnivorous plant
Open the record for dataset details and reuse information.
Leaf litter capture in the carnivorous pitcher plant, <em>Sarracenia purpurea</em>: a preliminary study
Open the record for dataset details and reuse information.
Multiple signaling increases both prey response and diversity in a carnivorous pitcher plant
Open the record for dataset details and reuse information.
Data from: Metabarcoding analysis provides insight into the link between prey and plant intake in a large alpine cat carnivore, the snow leopard
Open the record for dataset details and reuse information.
Plant‐eating carnivores: Multispecies analysis on factors influencing the frequency of plant occurrence in obligate carnivores
Open the record for dataset details and reuse information.
Plant-animal interactions between carnivorous plants, sheet-web spiders, and ground-running spiders as guild predators in a wet meadow community
<p>Plant-animal interactions are diverse and wide-spread shaping ecology, evolution and biodiversity of most ecological communities. Carnivorous plants are unusual in that they can be simultaneously engaged with animals in multiple mutualistic and antagonistic interactions including reversed plant-animal interactions where they are the predator. Competition with animals is a potential antagonistic plant-animal interaction unique to carnivorous plants when they and animal predators consume the same prey.</p> <p>The goal of this field study was to test the hypothesis that under natural conditions, sundews and spiders are predators consuming the same prey thus creating an environment where interkingdom competition can occur.</p> <p>Over 12 months, we collected data on 15 dates in the only protected Highland Rim Wet Meadow Ecosystem in Kentucky where sundews, sheet-web spiders and ground-running spiders co-exist. One each sampling day, we attempted to locate fifteen sites with: 1) both sheet-web spiders and sundews; 2) sundews only; and where neither occurred. Sticky traps were set at each of these sites to determine prey (springtails) activity-density. Ground-running spiders were collected on sampling days. DNA extraction was performed on all spiders to determine which individuals had eaten springtails and comparing this to the density of sundews where the spiders were captured. </p> <p>Sundews and spiders consumed springtails. Springtail activity-densities were lower the higher the density of sundews. Both sheet-web and ground-running spiders were found less often where sundew densities were high. Sheet-web size was smaller where sundews densities were high. </p> <p>The results of this study suggest that asymmetrical exploitative competition occurs between sundews and spiders. Sundews appear to have a greater negative impact on spiders, where spiders probably have little impact on sundews. In this example of interkingdom competition where the asymmetry should be most extreme, amensalism where one competitor experiences no cost of interaction may be occurring. </p>
Raw data and Matlab code for: Convergence in carnivorous pitcher plants reveals a mechanism for composite trait evolution
<p>Composite traits involve multiple components that, only when combined, gain a new synergistic function. Thus, how they evolve remains a puzzle. We combined field experiments, microscopy, chemical analyses and laser Doppler vibrometry with comparative phylogenetic analyses to show that two carnivorous <em>Nepenthes</em> pitcher plant species convergently evolved identical adaptations in three distinct traits to acquire a new, composite trapping mechanism. Comparative analyses suggest that this new trait arose convergently via 'spontaneous coincidence' of the required trait combination, rather than directional selection in the component traits. Our results indicate a plausible mechanism for composite trait evolution and highlight the importance of stochastic phenotypic variation as a facilitator of evolutionary novelty.</p>
Predation risk can modify the foraging behaviour of frugivorous carnivores: implications of rewilding apex predators for plant-animal mutualisms
<p>Apex predators play key roles in food webs and their recovery can trigger trophic cascades in some ecosystems. Intra-guild competition can reduce the abundances of smaller predators and perceived predation risk can alter their foraging behaviour thereby limiting seed dispersal by frugivorous carnivores. However, little is known about how plant-frugivore mutualism could be disturbed in the presence of larger predators.</p> <p>We evaluated the top-down effect of the regional superpredator, the Iberian lynx (Lynx pardinus), on the number of visits and fruits consumed by medium-sized frugivorous carnivores, as well as the foraging behaviour of identified individuals, by examining the consumption likelihood and the foraging time.</p> <p>We carried out a field experiment in which we placed Iberian pear (Pyrus bourgaeana) fruits beneath fruiting trees and monitored pear removal by frugivorous carnivores, both inside and outside of lynx ranges. Using camera traps, we recorded the presence of the red fox (Vulpes vulpes), the Eurasian badger (Meles meles) and the stone marten (Martes foina), as well as the number of fruits they consumed and their time spent foraging.</p> <p>Red fox was the most frequent fruit consumer carnivore. We found there were fewer visits and less fruit consumed by foxes inside of lynx ranges, but lynx presence did not seem to affect badgers. We did not observe any stone marten visits inside of lynx territories. The foraging behaviour of red foxes was also altered when inside of lynx ranges whereby foxes were less efficient, consuming less fruit per unit of time and having shorter visits. Local availability of fruit resources, forest coverage and individual personality also were important variables to understand visitation and foraging in a landscape of fear. 5. Our results show a potential trophic cascade from apex predators to primary producers. The presence of lynx can reduce frugivorous carnivore numbers and induce shifts in their feeding behaviour that may modify the seed dispersal patterns with likely consequences for the demography of many fleshy-fruited plant species. We conclude that knowledge of the ecological interactions making up trophic webs is anasset to design effective conservation strategies, particularly in rewilding programs.</p>
Carnivorous Plants Database
Jan Schlauer, Rick Walker. 2019. The Carnivorous Plant Database. <p></p>http://www.omnisterra.com/bot/cp_home.cgi. Accessed on 2019-10-06<p></p>
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.