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Effects of Prey Availability on Sarracenia Physiology at Harvard Forest 2005
Allometric relationships exist between maximal mass-based net photosynthetic rates, leaf mass per unit area, and foliar Nitrogen (N) and Phosphorus (P) content, which hold across a diverse spectrum of over 2500 plant species worldwide. Carnivorous plants depart from this spectrum because they dedicate substantial leaf area to capturing prey, from which they derive N and P under very nutrient-limiting situations. We conducted a manipulative feeding experiment to test whether morphological and physiological allometric relationships of carnivorous plants when nutrients are not limiting are more similar to allometric relationships of non-carnivorous plants. We examined the effects of prey availability on photosynthetic rate (Amass), chlorophyll fluorescence, growth, architecture, and foliar nutrient and chlorophyll content of ten pitcher plant (Sarracenia) species. We tested the hypothesis that increased prey availability would stimulate Amass of one or more leaves, increase photosynthetic N- and P-use efficiencies (PNUEN, PNUEP), increase relative biomass allocation to photosynthetically efficient, non-predatory phyllodes rather than pitchers, increase overall plant biomass, and reduce stress-related chlorophyll fluorescence. This is the first multi-species, controlled feeding experiment using realistic prey treatments, measuring these physiological parameters directly, and elucidating mechanisms of nutrient stoichiometry and allometry in carnivorous plants. Increased prey availability increased chlorophyll content, Amass and photosystem efficiency (the Fv/Fm ratio) across the 10 Sarracenia species. These increases were most evident in younger leaves, as older leaves rapidly translocated nutrients to newer, growing tissues. Better-fed plants produced a significantly higher proportion of phyllodes than controls. Higher prey availability was associated with lower N:P ratios, and a shift from P- to N-limitation. PNUEP was significantly enhanced by supplementary feeding, w
Effect of Prey Availability on Sarracenia Purpurea Stoichiometry at Belvidere Bog, Vermont 2002
The carnivorous pitcher plant Sarracenia purpurea receives nutrients from both captured prey and atmospheric deposition, making it a good subject for the study of ecological stoichiometry and nutrient limitation. We added prey in a manipulative field experiment and measured nutrient accumulation in pitcher-plant tissue and pitcher liquid, as well as changes in plant morphology, growth, and photosynthetic rate. Prey addition had no effect on traditional measures of nutrient limitation (leaf morphology, growth, or photosynthetic rate). However, stoichiometric measures of nutrient limitation were affected, as the concentration of both N and P in the leaf tissue increased with the addition of prey. Pitcher fluid pH and nitrate concentration did not vary among treatments, although dissolved oxygen levels decreased and ammonia levels increased with prey addition. Ratios of N:P, N:K, and K:P in pitcher-plant tissues suggest that prey additions shifted these carnivorous plants from P limitation under ambient conditions to N limitation with the addition of prey.
Dynamic landscapes of fear and safety alter prey refuge use in freshwater habitats
The non-consumptive effects of predators on prey behavior have been studied in many different systems. However, predator-prey ecology has placed a bulk of emphasis on how fear alters prey behavior, and new studies have begun to shift focus to the importance that safety in the form of refuges has in structuring prey behavioral responses. This project focuses on changes in the safety landscape as well as changes in the fear landscape and how these changes impact crayfish behavior. Using an established bass-crayfish predator prey system, we altered shelter quality and location in relation to the presence of bass odor signals. We measured shelter use by the crayfish in response to this changing landscape.
Data from “Larval and juvenile Longfin Smelt diets as a function of fish size and prey density in the San Francisco Estuary”
This publication includes the raw data from the manuscript: Lojkovic Burris, Z. P., R. D. Baxter, and C. E. Burdi. 2022. Larval and juvenile Longfin Smelt diets as a function of fish size and prey density in the San Francisco Estuary. California Fish and Wildlife Journal 108:e11. http://www.doi.org/10.51492/cfwj.108.11 Data includes the diets of larval and juvenile Longfin Smelt in the San Francisco Estuary from 2005 to 2008 in the form of diet by number, diet by weight, macroinvertebrate prey lengths, prey length-weight equations, and prey weight conversions.
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
Sarracenia Purpurea Prey Capture at Harvard Forest 2008
We experimentally demonstrate that nectar, not color, is the primary attractant of prey to carnivorous pitcher plants in their native habitats. Prey capture (either all taxa summed or individual common taxa considered separately) was not associated with total red area or patterning on pitchers of living pitcher plants. We separated effects of nectar availability and coloration using painted "pseudopitchers", half of which were coated with sugar solution. Unsugared pseudopitchers captured virtually no prey, whereas pseudopitchers with sugar solution captured the same amount of prey as living pitchers. In contrast to a recent study that associated red coloration with prey capture but that lacked appropriate controls for nectar availability, we conclude that nectar, not color, is the primary means by which pitcher plants attract prey.
Migratory shorebird habitat use, diet, and prey selection on mudflats in the Virginia barrier island and lagoon system, 2023-2024
Migratory shorebirds require access to heterogenous resources during migration. Understanding how shorebirds utilize different foraging substrates and food resources across the coastal landscape is important for informing conservation. We compared shorebird habitat use and invertebrate prey communities between barrier island and mudflat foraging substrates. We counted shorebirds and collected prey samples at random points on sand, peat, and mudflat substrates during spring migration (May 14 - June 2), 2023 - 2024. We opportunistically collected fecal samples on mudflats in our study area and used fecal DNA metabarcoding with 18S (invertebrates) and 23S (biofilm) primers to describe the diets of dunlin (Calidris alpina), red knots (Calidris canutus rufa) and semipalmated sandpipers (Calidris pusilla). We then used network null modeling to determine if our focal species were selectively consuming invertebrates on mudflats. Peat banks were the most heavily used intertidal substrate and mudflats supported similar shorebird abundances and species richness to sand. Dunlin and semipalmated sandpipers were more abundant on peat and mudflats, while red knots were more abundant on sand and peat. Invertebrate density was highest on peat banks and similar between mudflat and sand substrate, though mudflats supported a more diverse prey community. Amphipod crustaceans, blue mussels (Mytilus edulis), and polychaete worms were main prey consumed by all species on mudflats. Dunlin and semipalmated sandpipers fed primarily on crustaceans whereas red knots mainly fed on bivalves. All species consumed biofilm and a high proportion of diatoms were observed in fecal samples collected from semipalmated sandpipers. Red knots and dunlin selectively consumed bivalves on mudflats while semipalmated sandpipers showed no dietary preferences. Managing staging sites to preserve a diversity of intertidal habitats is critical for meeting the variable foraging requirements of migratory shorebirds.
Red knot occurrence, prey density, island morphology, and climate change in the Virginia Barrier Islands (2009-2023)
Global climate change is reshaping dynamic coastal ecosystems, with uncertain consequences for migratory shorebirds such as the federally threatened red knot (Calidris canutus rufa) that rely on coastal staging sites during migration. Understanding how sea-level rise and changing climate drivers affect red knot foraging ecology is critical for informing conservation and management at coastal staging sites. We integrated long-term biological, geomorphological, and climatological data to examine the direct and indirect pathways influencing red knots and their prey at intertidal foraging sites on the Virginia Barrier Islands during spring migration (May 21 - 28, 2009-2023). Using piecewise structural equation modeling, we tested hypothesized two causal networks linking 1) red knot occurrence and 2) densities of their main invertebrate prey to habitat characteristics, island morphology, geomorphic change, and climate drivers of ecosystem change. Red knots were indirectly affected by geomorphic change and climate drivers through bottom-up effects on invertebrate communities mediated by island morphology. Accelerated shoreline change narrowed islands, reducing invertebrate density and richness and indirectly decreasing red knot occurrence. Storms interacted with global climate oscillations to drive erosion or accretion of beaches, with variable effects on invertebrate density and red knot occurrence. Invertebrate responses were taxon-specific: shoreline change directly increased blue mussel density but indirectly reduced coquina clam and crustacean densities by narrowing island width, while storms impacts on crustacean density were mediated by beach width. Our findings suggest that accelerated ecosystem change under future climate scenarios may alter foraging conditions for red knots and other migratory shorebirds in the Virginia Barrier Islands, with broader implications for long-term population resilience.
Barn owl diet and prey fluctuations in the Jura mountains, eastern France
<p>Based on pellet collection, the diet of the Barn Owl (<em>Tyto alba</em>) was studied over a 8-year period in the Jura mountains, eastern France, during two population surges of its main prey (common vole, <em>Microtus arvalis </em>and montane water vole, <em>Arvicola amphibius</em>); Small mammals were sampled by trapping and index methods. Results have been published in the Canadian Journal of Zoology (<a href="http://doi.org/10.1139/z10-011">Bernard et al. 2010</a>). Dominique Michelat collected Barn Owl pellets and identified prey items, Pierre Delattre, Jean-Pierre Quéré Jean-Pierre Damange and Patrick Giraudoux sampled small mammals. Patrick Giraudoux managed the data.</p> <p><a href="https://zenodo.org/record/6945677/files/Small_mammals_trapping.txt?download=1">Small_mammals_trapping.txt </a>is the file of the raw trapping results for small mammals (instant abundance index i<sub>t</sub> in the article)</p> <p><a href="https://zenodo.org/record/6945677/files/diet_smm.txt?download=1">diet_smm.txt</a> is a file with:</p> <ul> <li>the small mammal density computed by season (d<sub>t</sub> in the article, rough estimate of densities in number of individuals per ha for <em>Apodemus spp.</em>, <em>Myodes glareolus</em>, <em>Microtus arvalis</em>, or weighted interpolated i<sub>t</sub> for the other species)</li> <li>the ratios of each category of prey items on the total number of items collected in the church tower of three sites, <a href="https://www.openstreetmap.org/#map=16/46.9536/6.1189">Levier</a>, <a href="https://www.openstreetmap.org/search?whereami=1&query=46.9321%2C6.1666#map=16/46.9321/6.1666">Chapelle d'Huin</a> and <a href="https://www.openstreetmap.org/search?whereami=1&query=46.9382%2C6.1976#map=16/46.9382/6.1976">Le Souillot</a>.</li> </ul> <p>For details see the material and methods of the article.</p> <p><strong>FILE DESCRIPTION</strong></p> <p><a href="https://zenodo.org/record/6945677/files/diet_smm.txt?download=1">diet_smm.txt</a></p> <ul> <li>date, year and season: year on two digits, then P, E, A, H respectively for<em> Printemps</em> (Spring), <em>Été</em> (Summer), <em>Automne</em> (Autumn), <em>Hiver</em> (Winter)</li> <li>at_t, abundance index of <em>Arvicola amphibius</em> (ex A.<em> terrestris</em>)</li> <li>ap_t, rough density estimate of <em>Apodemus sp.</em></li> <li>cg_t, rough density estimate of <em>Myodes glareolus</em></li> <li>ma_t, rough density estimate of <em>Microtus arvalis</em></li> <li>sa_t, relative abundance of <em>Sorex spp.</em></li> <li>n_l, number of prey items at Levier</li> <li>ma_p_l, ratio of <em>M. arvalis prey</em> items at Levier</li> <li>at_p_l, ratio of <em>A. amphibius</em> prey items at Levier</li> <li>apcg_p_l, ratio of <em>Apodemus spp.</em> or <em>Myodes glareolus</em> prey items at Levier</li> <li>sa_p_l, ratio of <em>Sorex spp.</em> prey items at Levier</li> <li>au_p_l, ratio of other prey items at Levier</li> <li>n_ch, number of prey items at Chapelle d'Huin</li> <li>map_ch, ratio of <em>M. arvalis prey</em> items at Chapelle d'Huin</li> <li>at_p_ch, ratio of <em>A. amphibius</em> prey items at Chapelle d'Huin</li> <li>apcg_p_ch, ratio of <em>Apodemus spp.</em> or <em>Myodes glareolus</em> prey items at Chapelle d'Huin</li> <li>sa_p_ch, ratio of <em>Sorex spp. </em>prey items at Chapelle d'Huin</li> <li>au_p_ch, ratio of other prey items at Chapelle d'Huin</li> <li>n_ls, number of prey items at Le Souillot</li> <li>ma_p_ls, ratio of <em>M. arvalis prey</em> items at Le Souillot</li> <li>at_p_ls, ratio of <em>A. amphibius</em> prey items at Le souillot</li> <li>apcg_p_ls, ratio of <em>Apodemus spp.</em> or <em>Myodes glareolus</em> prey items at Le Souillot</li> <li>sa_p_ls, ratio of <em>Sorex spp.</em> prey items at Le Souillot</li> <li>au_p_ls, ratio of other prey items at Le Souillot</li> </ul> <p><a href="https://zenodo.org/record/6945677/files/Small_mammals_trapping.txt?download=1">Small_mammals_trapping.txt </a></p> <ul> <li>date, trapping period: digit 1-2, year; digit 3-4, month. Example: 8704 = April 1987.</li> <li>n_traplines_f, number of traplines in forest</li> <li>ap_f, average number of <em>Apodemus spp</em>. captured in forest</li> <li>cg_f, average number of <em>Myodes glareolus</em> captured in forest</li> <li>sa_f, average number of <em>Sorex spp</em>. captured in forest</li> <li>n_traplines_hfb, number of traplines in hedges and forest borders</li> <li>ap_hfb, average number of <em>Apodemus spp</em>. captured in hedges and forest borders</li> <li>cg_hfb, average number of <em>Myodes glareolus</em> captured in hedges and forest borders</li> <li>sa_hfb, average number of <em>Sorex spp.</em> captured in hedges and forest borders</li> <li>n_traplines_g, number of traplines in grassland</li> <li>ma_g, average number of Microtus arvalis captured in grassland</li> <li>sa_g, average number of <em>Sorex spp.</em> captured in grassland</li> </ul> <p><a href="https://zenodo.org/record/6945677/files/SmallMammalSamplingArea.kml?download=1">SmallMammalSamplingArea.kml</a> kml file locating the small mammal sampling area<br> </p>
Supplemental Information to Climate-driven habitat shifts of high-ranked prey species structure Late Upper Paleolithic hunting
<p>The data provided here are the supplemental information accompanying Yaworsky et al, 2023 in the journal <em>Scientific Reports</em>. These data represent the following, which are referenced in the published work at DOI: 10.1038/s41598-023-31085-x.</p> <p><strong>Below is the legend for the Supplementary Information</strong>, including how it is referenced within the text of the publication, the file name, and a brief description. More thorough descriptions of the data can be found within the publication in <em>Scientific Reports</em>.</p> <p><strong>Supplementary 1</strong> – <em>UpperPaleoDietV4.html</em> – HTML document of the analyses performed and presented in the paper. This is a Markdown document compiled in R with R code chunks and descriptions.</p> <p><strong>Supplementary 2</strong> – <em>Support Information 2.docx</em> – Word document containing supplementary tables 2 and 3.</p> <p><strong>Supplementary 3</strong> – <em>ArchaeoloigcalDataset_v8.csv</em> – Archaeological data referenced in the Material and Methods. These data are necessary for running the code presented in SI 1.</p> <p><strong>Supplementary 4</strong> – <em>EuroUpperPaleoFaunas_v6.csv</em> – Zooarchaeological data referenced in the Material and Methods. These data are necessary for running the code presented in SI 1.</p> <p><strong>Supplementary 5 </strong>– <em>Lupo2016.csv</em> – Data of Arficant fauna weight derived from table in Lupo and Schmitt 2016 (Table 2). These data are necessary for running the code presented in SI 1.</p> <p><strong>Supplementary 6</strong> – <em>PushkinaRaia_FaunaWeights.csv</em> – Data of Pleistocene fauna weights derived from table in Pushkina and Raia 2008 (Table 1). These data are necessary for running the code presented in SI 1.</p> <p><strong>Supplementary 7</strong> – <em>environmental_BG.csv</em> – Data representing background environmental conditions derived from the CHELSA TRaCE21k data. These data are necessary for running the code in SI 1.</p> <p>For more information on the data, methods, and results, please see the main paper. </p> <p> </p> <p> </p>
California's Central Valley Project Improvement Act Predation Contact Point Study - 2022: Predator-prey interactions under low artificial lighting in a laboratory setting
The highest rates of piscivorous predation in the field have been recorded during crepuscular light levels associated with sunrise and sunset or artificial lighting at night (ALAN). We conducted a laboratory study where groups of predator-naïve, hatchery-raised juvenile rainbow trout (Oncorhynchus mykiss) were exposed to natural-origin piscivorous largemouth bass (Micropterus salmoides) under three light treatments representative of brighter crepuscular periods or direct ALAN illumination (“high” treatment), dimmer crepuscular periods or sky glow from ALAN (“medium” treatment), and night or no ALAN (“low” treatment). We then statistically evaluated potential associations between light treatment, prey group cohesion, and predator activity.
Standard Lengths and Mean Weights for Prey-base Fishes from Taylor River and Joe Bay Sites, Everglades National Park (FCE), South Florida from January 2000 to April 2004
Prey-base fishes. The small demersal fishes of the coastal wetlands are a keystone element in this ecosystem. They are the primary and secondary consumers of the plants mentioned above and they are the primary food resource for myriad piscine (e.g. game species of fish), reptilian (e.g. juvenile crocodiles) and avian (e.g. wading birds) predators. The community dynamics of these fishes are dictated by hydrologic and hydrographic parameters so they also respond predictably to water management practices. Because they are a bottle-neck in the food web, their abundance and availability dictate the success of higher trophic levels. Fish are sampled in June, September and monthly from November through April at five locations. A 9m2 drop trap designed specifically for this habitat are used to quantify fish use. Nine traps are used at each site.
Density independent prey choice, taxonomy, life history and web characteristics determine the diet and biocontrol potential of spiders (Linyphiidae and Lycosidae) in cereal crops - Dataset
<p>Materials and Methods</p> <p>Fieldwork</p> <p>Money spiders (Araneae: Linyphiidae) and wolf spiders (Araneae: Lycosidae) were the two most common families present in these field surveys, so were prioritised for collection. Spiders were visually located along transects in two adjacent barley fields at Burdons Farm, Wenvoe in South Wales (51°26'24.8"N, 3°16'17.9"W) and collected from occupied webs and the ground, between April and September 2018. Surveys and sampling were conducted five days per week across this period. Each transect was adjacent to a randomly selected tramline and they were distributed across the entire field. The areas searched were 4 m<sup>2</sup> quadrats at least 10 m apart and all observed linyphiids and lycosids were collected in approximately 15-minute searches. The spiders included in this study were taken from 64 locations across 24 days (Supplementary Table 3) along the aforementioned transects. Spiders were individually placed into 1.5 ml microcentrifuge tubes containing 100 % ethanol using an aspirator, regularly changing meshing, at least every five spiders, to limit potential cross-contamination between spiders (spiders were also subsequently washed during transferral to fresh ethanol at the identification and, separately, dissection stages). Linyphiids occupying webs were prioritised for collection, but ground-active linyphiid spiders were also collected. For each spider taken from a web, the height of the web from the ground and its approximate dimensions were recorded, the latter calculated as approximate web area. Spiders were taken to Cardiff University, transferred to fresh ethanol, adults identified to species-level and juveniles to genus, and stored at -80 °C in 100 % ethanol until subsequent DNA extraction. To obtain data on local prey density, 4 m<sup>2</sup> of ground and crop stems were suction sampled using a ‘G-vac’ for 30 seconds at each quadrat from which spiders were collected, with the collected material emptied into a bag, any organisms immediately killed with ethyl-acetate and material frozen for storage before sorting into 70 % ethanol in the lab.</p> <p>All invertebrates were identified to family level due to the restriction of many of the metabarcoding-derived dietary data to this level, and the difficulty associated with finer taxonomic resolution of many taxa. Exceptions included springtails of the superfamily Sminthuroidea (Sminthuridae and Bourletiellidae, which were often indistinguishable following suction sampling and preservation due to the fine features necessary to distinguish them) which were left at super-family, mites (many of which were immature or in poor condition) which were identified to order level and wasps of the superfamily Ichneumonoidea (which were identified no further due to obscurity of wing venation due to damage).</p> <p> </p> <p>Extraction and high-throughput sequencing of spider gut DNA</p> <p>Given their prevalence in field collections, dietary analysis was carried out for the linyphiid genera <em>Erigone</em>, <em>Tenuiphantes</em>, <em>Bathyphantes</em> and <em>Microlinyphia </em>(Araneae: Linyphiidae), and the Lycosidae genus <em>Pardosa</em>. Spiders were transferred to and washed in fresh 100 % ethanol to reduce external contaminants prior to identification via morphological key <sup>1</sup>. Abdomens were removed from spiders and again washed in and transferred to fresh 100 % ethanol. DNA was extracted from the abdomens via Qiagen TissueLyser II and DNeasy Blood & Tissue Kit (Qiagen) as per the manufacturer protocol, but with an extended lysis time of 12 hours to account for the complex and branched gut system in spider abdomens <sup>2</sup>. At least one extraction negative (blank tubes treated identically to samples) was included per 12 spiders (each extraction typically contained 24 spiders, thus two extraction negatives), which was included in subsequent PCR and high-throughput sequencing to detect instances of lab/reagent contamination.</p> <p>For amplification of DNA, two primer pairs were used. BerenF-LuthienR <sup>3</sup> amplified a broad range of invertebrates including spiders, and TelperionF-LaureR, amplified a range of invertebrates but fewer spiders (modified from TelperionF-LaurelinR <sup>3</sup> via one base-pair change from Laurelin; 5’-ggrtawacwgttcawccagt-3’). Primers were labelled with unique 10 bp molecular identifier tags (MID-tags) so that each individual had a unique pairing of forward and reverse tags for identification of each spider post-sequencing. PCR reactions of 25 µl contained 12.5 µl Qiagen PCR Multiplex kit, 0.2 µmol (2.5 µl of 2 µM) of each primer and 5 µl template DNA. Reactions were carried out in the same thermocycler, optimised via temperature gradient, with an initial 15 minutes at 95 °C, 35 cycles of 95 °C for 30 seconds, the primer-specific annealing temperature for 90 seconds and 72 °C for 90 seconds, respectively, followed by a final extension at 72 °C for 10 minutes. BerenF-LuthienR and TelperionF-LaureR used annealing temperatures of 52 °C and 42 °C, respectively.</p> <p>Within each PCR 96-well plate, 12 negative controls (extraction and PCR), 2 blank controls and 2 positive controls were included (i.e. 80 samples per plate), based on Taberlet <em>et al. </em>(2018). Positive controls were mixtures of invertebrate DNA comprised of non-native Asiatic species in four different proportions (Supplementary Table 1) and blanks were empty wells within each plate to identify tag-jumping into unused MID-tag combinations. PCR negative controls were DNase-free water treated identically to DNA samples. A negative control was present for each MID-tag to identify any contamination of primers. All PCR products were visualised in a 2 % agarose gel with SYBRSafe (Thermo Fisher Scientific, Paisley, UK) and placed in categories based on their relative brightness. The concentration of these brightness categories was quantified via Qubit dsDNA High-sensitivity Assay Kits (Thermo Fisher Scientific, Waltham, MA, USA) with at least three representatives of each category per plate. The PCR products were then proportionally pooled according to these concentrations. Each pool was cleaned via SPRIselect beads (Beckman Coulter, Brea, USA), with a left-side size selection using a 1:1 ratio (retaining ~300-1000 bp fragments). The concentration of the pooled DNA was then determined via Qubit dsDNA High-sensitivity Assay Kits and pooled together into one library per primer pair. Library preparation for Illumina sequencing was carried out on the cleaned libraries via NEXTflex Rapid DNA-Seq Kit (Bioo Scientific, Austin, USA) and samples were sequenced on an Illumina MiSeq via a V3 chip with 300-bp paired-end reads (expected capacity ≤25,000,000 reads). Bioinformatic analysis followed (Drake et al., 2021; Supplementary Information 1).</p> <p> </p> <p>Statistical analysis</p> <p>All analyses were conducted in R v4.0.0 <sup>6</sup>. Initial multivariate analyses used binary data (i.e., presence/absence) given the various problems inherent to quantifying metabarcoding data <sup>7,8</sup>. Prey species that occurred only once across all of the dietary samples were removed before further analyses to prevent outliers skewing the results, which is particularly problematic for non-metric multidimensional scaling. Spider diets were compared between variables using multivariate generalized linear models (MGLMs) via ‘manyglm’ in the ‘mvabund’ package <sup>9</sup> with a binomial error family and Monte Carlo resampling. Model independent variables included spider genus, spider life stage (juvenile or adult, the latter defined by fully developed genitalia), spider sex and all two-way interactions between these variables. Pairwise two-way interactions were also included between the aforementioned variables and Julian day to account for how seasonality may affect these relationships.</p> <p>Coarse dietary differences were visualised by non-metric multidimensional scaling (NMDS) via metaMDS in the ‘vegan’ package <sup>10</sup> with Jaccard distance in two dimensions and 999 tries. For NMDS, outliers (usually samples containing rare taxa) were identified by plotting and subsequently removed to facilitate separation of samples and achieve minimum stress. For visualisation of the effect of categorical variables against the dietary NMDS, spider plots were created using ‘ordispider’ with ‘ggplot’ and the ‘RColorBrewer’ ‘Accent’ colour palette <sup>11</sup>. Spider diet was compared against web characteristics for spiders for which both data were available using the MGLM process outlined above, but with starting models containing web height, web area, an interaction between the two, and pairwise interactions between genus, life stage and sex with the two web variables. This model used the same binomial error family as above, but with a ‘cloglog’ link function. For visualisation of the effect of continuous variables against the NMDS, surf plots were created with scaled coloured contours using the function “ordisurf” of the “ggplot” package in R.</p> <p>All prey taxa were classified as agricultural pests, natural enemies or excluded from subsequent analyses of intraguild predation and biocontrol (Supplementary Table 2). Intraguild predation and biocontrol variables were created by counting the number of natural enemy taxa, and, separately, of agriculturally relevant “pest” taxa (taxa containing species that commonly adversely affect agricultural productivity; Supplementary Table 2) in each spider’s diet. These resultant count data (effectively the diversity of pests and natural enemies predated by each individual spider) were separately analysed against spider genus, life stage and sex via GLM. “Site” (denoting the 4 m<sup>2</sup> area from which spiders were collected within fields) was initially included as a random effect in generalized linear mixed-models, but no significant effect was observed when comparing this model against a standard GLM via a likelihood ratio test of nested models using the ‘lrtest’ command in the ‘lmtest’ package <sup>12</sup>. Standard GLMs were thus used to avoid issues relating to singularity in the mixed models. The assumptions for the resultant Poisson error family GLMs were tested using the “testResiduals” function of the ‘DHARMa’ package <sup>13</sup>. Intraguild predation and biocontrol differences between significant terms were visualised using violin plots with the quartiles, median and 95 % upper limit annotated using the ‘geom_violin’ function in ‘ggplot2’.</p> <p><em>In situ</em> spider prey choice was analysed using network-based null models in the ‘econullnetr’ package <sup>14</sup> with the ‘generate_null_net’ command, visually represented with the ‘plot_preferences’ command. Binary dietary data were used alongside suction sample count data to represent prey availability. These suction sample data, as described above, were collected at the same sites as the spiders three days after spider collection. Prior to the taxonomic prey choice analysis, an hemipteran identified no further than order level through dietary analysis was removed due to the inability to pair it to any present prey taxa with certainty. Standardised effect sizes (SES) were extracted for all comparisons for each individual spider and compared between genera, life stages and sexes using permutational multivariate analysis of variance (PerMANOVA) using the ‘adonis’ function of the ’vegan’ package with 9999 permutations and a Euclidean distance matrix to determine overall differences in prey choice.</p> <p> </p> <p>References</p> <p>1. Roberts, M. J. <em>The Spiders of Great Britain and Ireland (Compact Edition)</em>. (Harley Books, 1993).</p> <p>2. Krehenwinkel, H., Kennedy, S., Pekár, S. & Gillespie, R. G. A cost-efficient and simple protocol to enrich prey DNA from extractions of predatory arthropods for large-scale gut content analysis by Illumina sequencing. <em>Methods Ecol. Evol.</em> <strong>8</strong>, 126–134 (2017).</p> <p>3. Cuff, J. P. <em>et al.</em> Money spider dietary choice in pre- and post-harvest cereal crops using metabarcoding. <em>Ecol. Entomol.</em> <strong>46</strong>, 249–261 (2021).</p> <p>4. Taberlet, P., Bonin, A., Zinger, L. & Coissac, E. <em>Environmental DNA</em>. (Oxford University Press, 2018).</p> <p>5. Drake, L. E. <em>et al.</em> An assessment of minimum sequence copy thresholds for identifying and reducing the prevalence of artefacts in dietary metabarcoding data. <em>Methods Ecol. Evol.</em> <strong>in press</strong>, (2021).</p> <p>6. R Core Team. R: A language and environment for statistical computing. (2020).</p> <p>7. Deagle, B. E., Thomas, A. C., Shaffer, A. K. & Trites, A. W. Quantifying sequence proportions in a DNA-based diet study using Ion Torrent amplicon sequencing: which counts count? <em>Mol. Ecol. Resour.</em> <strong>13</strong>, 620–633 (2013).</p> <p>8. Deagle, B. E. <em>et al.</em> Counting with DNA in metabarcoding studies: How should we convert sequence reads to dietary data? <em>Mol. Ecol.</em> <strong>28</strong>, 391–406 (2019).</p> <p>9. Wang, Y., Naumann, U., Wright, S. T. & Warton, D. I. mvabund – an R package for model-based analysis of multivariate abundance data. <em>Methods Ecol. Evol.</em> <strong>3</strong>, 471–474 (2012).</p> <p>10. Oksanen, J. <em>et al.</em> vegan: Community Ecology Package. (2016).</p> <p>11. Neuwirth, E. RColorBrewer: ColorBrewer palettes. (2014).</p> <p>12. Zeileis, A. & Hothorn, T. Diagnostic checking in regression relationships. <em>R News</em> <strong>2</strong>, 7–10 (2002).</p> <p>13. Hartig, F. DHARMa: residual diagnostics for hierarchical (multi-level/mixed) regression models. (2020).</p> <p>14. Vaughan, I. P. <em>et al.</em> econullnetr: an r package using null models to analyse the structure of ecological networks and identify resource selection. <em>Methods Ecol. Evol.</em> <strong>9</strong>, 728–733 (2018).</p>
Predator effects on metamorphosis: The effects of scaring versus thinning at high prey densities.
Organisms with complex life cycles face the challenge of when to switch between habitats and foraging strategies over ontogeny in ways that improve their fitness. Metamorphosis is a well-studied life history event in animals and ecologists have spent decades trying to understand how the size at and time to metamorphosis are altered by natural stressors such as competition and predation. The challenges in interpreting the effects of predators on metamorphic decisions include the need to compare predator species that pose different levels of risk, compare the roles of predators inducing fear versus thinning of the density of prey, and examine prey life history traits and behavior over ontogeny. We addressed these challenges in a mesocosm experiment in which we introduced a high initial density of hatchling Northern Leopard Frogs (Rana pipiens) and exposed them to three different species of caged predators (to induce three different levels of fear), three rates of hand-thinning (to mimic the thinning effect of each predator), or three species of lethal predators (to cause induction and thinning). Under these initial high densities, we found that caged predators had no effects on tadpole activity, growth, and development. This outcome was likely due to the high density of tadpoles causing high competition, which can inhibit anti-predator responses. High rates of hand thinning caused decreased tadpole activity, greater mass, and faster development. Interestingly, lethal predators caused phenotypic changes that were largely in line with the hand thinning effects alone. These results suggest that at high initial prey densities, the thinning process of predation appears plays a much more important role in prey metamorphosis than induction from predatory chemical cues.
Dissecting the smell of fear from conspecific and heterospecific prey: Investigating the processes that induce anti-predator defenses.
Prey use chemical cues from predation events to obtain information about predation risk to alter their phenotypes. Though we know how many prey respond to predators, we still have a poor understanding of the processes and chemical cues involved during a predation event. We examined how gray treefrog tadpoles (Hyla verisciolor) altered their behavior and morphology when raised with cues from different stages of predator attack, predators fed different amounts of prey, and predators consuming different combinations of treefrog tadpoles or snails (Helisoma trivolvis). We found that starved predators and predators fed snails induced no defensive responses whereas tadpoles exposed to a predator consuming gray treefrogs induced greater hiding, lower activity, and relatively deeper tails. We also found that the tadpoles did not respond to crushed, chewed, or digested conspecifics, but they did respond to consumed (i.e. chewed + digested) conspecifics. When we increased the treefrog biomass consumed by predators, tadpoles frequently increased their defenses when only tadpoles were consumed and always increased their defenses when the total diet biomass was held constant via the inclusion of snails. When predators experienced temporal variation in diet composition, including cues from snails to cause additional digestive cues or chemical noise, there was no effect on tadpole phenotypes. Our results suggest that amphibian prey rely on cues from both chewing and digestion of conspecifics and that the presence of cues from digested heterospecifics play little or no role in adding chemical noise or increased digestive enzymes and by-products that interfere with induced defenses.
CBS04 Sweep sample data: prey estimates for Grasshopper Sparrows on Konza Prairie
This data set includes data on the contents of sweep samples. We collected sweeps in select years during May, June, and/or July in 3 locations on each of the focal watersheds. Sweeps were 80m long and centered at veg points. Data consist of information about the sampling events, and sample wet mass, edible mass (combined mass of selected orders listed below). Additionally, the dataset includes the number of individuals in each of a series of size categories, total N, and mass (in grams) of the following groups: Tettigoniidae, Acrididae, other Orthoptera, Gryllidae, Odonata, Ephemeroptera, Coleoptera, Hymenoptera, Lepidoptera, Arachnida, Hemiptera, Neuroptera, Diptera, Phasmatidae, Mantidae, and “other”.
North Temperate Lakes LTER: Pelagic Prey - Sonar Data 2001 - current
Total pelagic fish abundance data were collected annually in mid-summer (following stratification) using hydroacoustic surveys along a set of transects in each of eight lakes (Allequash, Big Muskellunge, Crystal, Sparkling, Trout, Mendota, Monona, and Fish), from 1981-1999 (Lakes Monona and Fish from 1995). Hydroacoustic data were not collected in 2000, but collection resumed in 2001 on Crystal, Sparkling, and Trout and continues to the present (with the exception of Crystal in 2004). In 2005, Lake Mendota was included in the annual sampling rotation. This dataset includes data from lakes Crystal, Sparkling, Trout and Mendota from 2001 through present. Lake Mendota was not surveyed in 2020 due to COVID-19. Big Muskellunge Lake was included back into the sampling rotation in 2020 and continues to be surveyed annually. Sonar data represent 1) species-specific whole lake density estimates and average length (target strength (dB)); 2) depth-stratified (1m) species-specific density estimates and average length by 200m transects; and 3) individual depth-specific target length (not assigned to species). Dataset names for the aforementioned are below. 1) North Temperate Lakes LTER: Pelagic Prey Whole Lake Density - Sonar Data 2) North Temperate Lakes LTER: Pelagic Prey Interval Density - Sonar Data 3) North Temperate Lakes LTER: Pelagic Prey Single Target - Sonar Data Although rare, large targets representing predatory species were excluded from the density estimation for pelagic prey species (when n<3 were caught in vertical gillnets) using the proportion of large targets identified during single target analysis on each lake. Pelagic fish densities for lakes Sparkling, Crystal, Big Muskellunge, and Mendota are for the entire basin of each lake. The data shown for Trout Lake represent densities in the south basin only. Number of current sites: 5
Adelie penguin diet composition, secondary prey items, 1991-2020
The fundamental long-term objective of the seabird component of the Palmer LTER (PAL) has been to identify and understand the mechanistic processes that regulate the mean fitness (population growth rate) of regional penguin populations. Since the inception of PAL, Adélie penguin populations have effectively collapsed, gentoo penguin populations have increased dramatically and chinstrap penguin populations have remained relatively stable. These trends are spatially and temporally coherent with regional warming and decreasing sea ice duration. Adélie penguins are an ice-obligate polar species whose life history is intimately linked to the presence of sea ice, while chinstrap and gentoo penguins are ice-intolerant species whose life histories evolved in the sub-Antarctic, where sea ice is a less permanent feature of the marine ecosystem. The PAL study region includes five main islands on which Adélie penguin colonies have historically occurred, with each island containing a different number of spatially segregated sub-colonies. These colonies are censused to determine the total number of nests and chicks produced each year, and breeding success. Diet samples are acquired to understand diet composition (e.g., krill, fish) and krill length-frequencies. In general, krill constitute the most important component of the summer diets by mass of these three penguin species, but changes in PAL krill abundances have exhibited no long-term trends and thus far, have failed to explain the divergent patterns in penguin populations evident in our time series. Chick fledging masses are recorded as a cumulative measure of climate, weather, diet, and parental influences on chick health at the end of the breeding season. These data have provided valuable insights into the marine and terrestrial factors that influence Adélie penguin population fitness. No data were collected during the 2021-2022 season due to the Palmer Station pier rebuild.
SBC LTER: Beach: Sandy beach prey resource use by surfperch across tidal phase
These data describe trophic links between sandy beach and an associated surf zone fish species. The datasets are the result of a short-term study investigating the effect of tidal phase on a local sandy beach macroinvertebrate community and the diet of barred surfperch (Amphistichus argenteus) during the summer and fall of 2020. The beach invertebrate population dataset details the abundance and biomass of taxon within each beach intertidal zone across three paired neap and spring tidal phases. The diet datasets report the counts and sizes of prey taxon observed in barred surfperch stomach samples taken at the time of each beach sampling event. Data are contained in three tables: 1) the beach macroinvertebrate population data, 2) prey counts from barred surfperch stomach content samples, and 3) the sizes of prey in stomach samples.
SBC LTER: Santa Cruz Island: Aggregated mean abundance of black surfperch (Embiotoca jacksoni) and prey availability, 1994-2008
These data are the annual mean abundances of three age-classes of black surfperch and their prey at each of 11 sites at Santa Cruz Island, California. Reported values are a) the average number of adult black surfperch, young-of-year black surfperch, and one year-old black surfperch per 40m x 2m transect (for all transects), and b) total food availability (grams per 0.1 m squared) at each site. Food availability includes biomass of caprellid and gammarid amphipods and is calculated from the mean density within Gelidium spp. (for caprellids) and all other foliose or turfing algae (for gammarids). The data also include one year lags for each variable, i.e. the value of the variable at that site in the previous year.
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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.