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74 results for “prey selection”
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.
Prey nutrient content is associated with the trophic interactions of spiders and their prey selection under field conditions
<h2>Materials and Methods</h2> <h2><a name="_Toc58843581"></a><em><span>Fieldwork</span></em></h2> <p><a name="_Hlk173879015"></a><a name="_Hlk56335325"></a><span><span>Money spiders (Araneae: Linyphiidae) and wolf spiders (Araneae: Lycosidae), the two most abundant spider groups in this study, 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 in daylight hours between April and September 2018. Each belt transect was adjacent to a randomly selected crop tramline and were distributed across the entire field and ran its length. The areas searched were 4 m<sup>2</sup> quadrats at least 10 m apart and all observed linyphiids and lycosids were collected. The 300 spiders taken forward for molecular dietary analysis in this study were taken from 64 randomly selected locations along the aforementioned transects. </span></span><span><span>Following collection of spiders, 4 m<sup>2</sup> of ground and crop stems was suction sampled <a name="_Hlk173879230"></a>in each of these 64 sampling locations for approximately 30 seconds, with the collected material emptied into a bag and any organisms immediately killed with ethyl-acetate. Suction sampling used a ‘G-vac’ modified garden leaf-blower. All material was later frozen at -20 ºC for storage before sorting in the lab. Sticky trap data were also collected, but were not used in this study as suction sampling was found to represent the interactions of spiders more closely (Cuff, Tercel et al., 2024). These invertebrates were collected for background population densities and macronutrient analysis, not for molecular dietary analysis.</span></span></p> <p><span>All invertebrates were identified to family level using morphological keys: Araneae </span><span><span>(Roberts, 1993)</span></span><span>, Diptera </span><span><span>(Ball, 2008)</span></span><span>, Coleoptera </span><span><span>(Duff, 2012)</span></span><span>, Hymenoptera </span><span><span>(Goulet & Huber, 1993)</span></span><span>, Hemiptera </span><span><span>(Unwin, 2001)</span></span><span>, Collembola </span><span><span>(Dallimore & Shaw, 2013)</span></span><span> and Chilopoda </span><span><span>(Barber, 2008)</span></span><span>. Further identifications were not carried out due to the inability to identify some of the invertebrate groups further via the associated metabarcoding-derived dietary data (e.g., Sciaridae), and the difficulty associated with finer taxonomic resolution of many damaged or immature specimens. The only taxa not identified to family level were springtails of the superfamily Sminthuroidea (Sminthuridae and Bourletiellidae, which were often indistinguishable following suction sampling and preservation due to the fine features necessary to differentiate them) which were left at super-family, mites (many of which were immature or in poor condition, or lacked appropriate taxonomic keys) 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); in these cases, these taxonomic assignments were pooled to family-level for later analyses. <a name="_Hlk96098198"></a></span></p> <p><span><span>Extraction, amplification and sequencing of DNA from the individually collected spiders, and its bioinformatic analysis are described by </span></span><span><span><span>Cuff, Tercel, et al. (2022)</span></span></span><span><span> and </span></span><span><span><span>Drake et al. (2022)</span></span></span><span><span> and are also detailed in Supplementary Information 1. In short, dietary metabarcoding was carried out using two primer pairs, one excluding predator DNA and the other amplifying it, to overcome the problem of overamplification of predator DNA </span></span><span><span><span>(Cuff, Kitson, et al., 2023)</span></span></span><span><span>. Amplified DNA was sequenced on an Illumina MiSeq V3 2x300 cartridge, and resultant data screened for false positives following bioinformatic processing via minimum sequence copy thresholds applied according to read counts in controls and control DNA counts present in samples </span></span><span><span><span>(Drake et al., 2022)</span></span></span><span><span>.</span></span></p> <p><span> </span></p> <h2><a name="_Toc58843582"></a><em><span>Macronutrient determination</span></em></h2> <p><span>Specimens were taken for macronutrient analysis from the same suction samples collected for invertebrate community identification. Representatives were taken from each family found in the community samples for which specimens were intact, in visually good condition and relatively clean of soil and other contaminants. If specimens were from a relatively uncommon family but unclean, soil and other surface contaminants were physically removed, and the specimen then momentarily dipped in water to remove remaining surface contaminants without greatly dislodging surface lipids. <a name="_Hlk173879439"></a>Macronutrient contents were determined following the MEDI protocol </span><span><span><span>(Cuff, Wilder, et al., 2021; Cuff & Wilder, 2021)</span></span></span><span><span> with minor alterations to account for the small size of most of the invertebrates processed </span></span><span><span><span>(Cuff, 2021)</span></span></span><span><span> and with the omission of exoskeletal measurement. </span></span><span>During extraction, half volumes (i.e., 500 µl) of solvents were used. For the lipid assays, 15 µl of sulfuric acid was added for a 15 min incubation, followed by only 200 µl of vanillin reagent to increase the concentration and development of analyte for more accurate readings from smaller invertebrates. Lipid and protein standard series were diluted to 50% of the concentration specified in the original protocol (i.e., 0-1 mg ml<sup>-1</sup>). Carbohydrate assays used 140 µl of reagent with 30 min incubation at 92 °C followed by a further 30 min at room temperature. Carbohydrate standard series were diluted to 1 % of the concentrations specified in the original protocol (i.e., 0-0.02 mg ml<sup>-1</sup>) to ensure signals overcame the higher limit of detection relative to typical invertebrate carbohydrate content. <span> </span><a name="_Hlk173926384"></a>Mean macronutrient contents were calculated for each taxon and converted into proportions of the total macronutrient mass detected for each taxon (i.e., macronutrient values are given as % total macronutrient mass). Macronutrient data were allocated to each prey taxon. Where macronutrient data were not available for a family (due to no or very few individuals being present in vacuum samples), average data for that order were used.</span></p> <p><span> </span></p> <h2><a name="_Toc58843584"></a><em><span>Statistical analysis</span></em></h2> <p><span>We have assessed nutritional dynamics through a combination of multivariate models and network-based null modelling. All analyses were conducted in R v.4.0.3 </span><span><span>(R Core Team, 2020)</span></span><span>. </span></p> <p><span>To compare the nutritional balance of prey consumed by different spider groups, the mean nutrient contents of all prey consumed by each spider were calculated and compared using a multivariate linear model (MLM) via the ‘manylm’ command in mvabund </span><span><span>(Wang et al., 2012)</span></span><span>.<span> </span><span>Differences were visualised using ternary plots via ‘ggtern’ </span></span><span><span>(Hamilton & Ferry, 2018)</span></span><span> and ‘ggplot2’ </span><span><span>(Wickham, 2016)</span></span><span>. How spider diets differ between spider groups (genera, sexes and life stages) and how this is related to the nutrient contents of those prey was assessed using a fourth corner analysis (FCA). Fourth corner analyses assess how the relationship between the presence of species (or consumed resources in a dietary context) and environmental (or consumer) traits relates to species traits (or prey traits; </span><span><span>(Brown et al., 2014)</span></span><span>. </span><span>First, overall relationships between dietary composition and spider traits were assessed using a multivariate generalized linear model (MGLM) via the ‘manyglm’ command in the ‘mvabund’ package </span><span><span>(Wang et al., 2012)</span></span><span> with a binomial error family<span>. </span>These relationships were identified via likelihood ratio test using the ‘anova.manyglm’ command. A fourth corner analysis was performed using the ‘trait.glm’ command in mvabund with the ‘R’, ‘Q’ and ‘L’ matrices representing dietary detections of prey families in each spider, spider trait data (genus (a proxy for many unmeasured traits such as morphology), sex and life stage) and prey proportional macronutrient contents, respectively, with a binomial error family. Log-likelihood ratio tests were carried out using the ‘anova.traitglm’ command with 999 bootstrap iterations and Monte-Carlo resampling. The model was repeated with the least absolute shrinkage and selection operator (LASSO) applied, which is a method of penalised likelihood that reduces model terms to zero if they lack predictive power (i.e., do not reduce the Bayesian information criterion), thereby selecting models with greater predictive accuracy </span><span><span>(Brown et al., 2014)</span></span><span>. </span></p> <p><span>To assess whether the proportions of mean prey nutrient contents deviated from those expected based on random foraging, null diets were simulated using network-based null models in ‘econullnetr’ </span><span><span>(Vaughan et al., 2018)</span></span><span> with the ‘generate_null_net’ command. The ‘generate_null_net_indiv’ function </span><span><span>(Cuff, Windsor, et al., 2023)</span></span><span> was used to generate null diets for each individual spider based on local prey communities determined via suction sampling. The mean prey macronutrient contents of spider diets were compared between expected and observed diets </span><span>using a MLM in mvabund, and significant differences visually represented through a ternary plot using ggtern<span>. To ascertain how differences between spider groups factor into any deviations from random nutrient intake, the difference in macronutrient proportions between expected and observed spider diets was also compared between spider genera, life stages and sexes in a MLM.</span></span></p> <p><span>To relate prey preferences of different spider groups to different prey and their macronutrient contents, observed interactions were compared against null models based on prey abundances using the ‘generate_null_net’ command in econullnetr (as above) for each of the spider groups and, separately, for individual spiders. Ternary plots representing preference effect sizes for prey of varying macronutrient contents were generated using the group-specific data via ‘ggtern’. The observed interactions of individual spiders were divided by the interactions expected in the null model; infinite values (i.e., zero interactions expected and more than zero observed) and NAs (e.g., no interactions expected nor observed) were converted to zero. These observed/expected values were compared between spider groups via permutational multivariate analysis of variance (PerMANOVA). These results were visualised by plotting mean standardised effect sizes for each spider genus, sex and life stage from the prey choice null models via ggplot2. </span></p>
Supplementary data for "Influence of prey availability on habitat selection during the non-breeding period in a resident bird of prey"
<p><strong>Abstract</strong></p> <p>Background: For resident birds of prey in the temperate zone, the cold non-breeding period can have strong impacts on survival and reproduction with implications for population dynamics. Therefore, the non-breeding period should receive the same attention as other parts of the annual life cycle. Birds of prey in intensively managed agricultural areas are repeatedly confronted with unpredictable, rapid changes in their habitat due to agricultural practices such as mowing, harvesting, and ploughing. Such a dynamic landscape likely affects prey distribution and availability and may even result in changes in habitat selection of the predator throughout the annual cycle.</p> <p>Methods: In the present study, we 1) quantified barn owl prey availability in different habitats across the annual cycle, 2) quantified the size and location of barn owl breeding and non-breeding home ranges using GPS-data, 3) assessed habitat selection in relation to prey availability during the non-breeding period, and 4) discussed differences in habitat selection during the non-breeding period to habitat selection during the breeding period.</p> <p>Results: The patchier prey distribution during the non-breeding period compared to the breeding period led to habitat selection towards grassland during the non-breeding period. The size of barn owl home ranges during breeding and non-breeding were similar, but there was a small shift in home range location which was more pronounced in females than males. The changes in prey availability led to a mainly grassland-oriented habitat selection during the non-breeding period. Further, our results showed the importance of biodiversity promotion areas and undisturbed field margins within the intensively managed agricultural landscape. </p> <p>Conclusions: We showed that different prey availability in habitat categories can lead to changes in habitat preference between the breeding and the non-breeding period. Given these results we show how important it is to maintain and enhance structural diversity in intensive agricultural landscapes, to effectively protect birds of prey specialised on small mammals. Hereafter we provide the datasets and R script to reproduce the resource selection functions.</p>
Figure 2 in Reptiles as principal prey? Adaptations for durophagy and prey selection by jaguar (Panthera onca)
Figure 2. Percentage of Jaguar (Panthera onca) diet composed by peccaries or armadillos compared with cougars (Puma concolor). Jaguar prey more extensively over armoured and dangerous prey. Data were pooled from reviewed literature where faeces of cougars and jaguars were collected at the same site. Bars represents means while whiskers represent standard errors for each prey group.
Fig. 2 in Diet, Prey Selection and Biomass Consumption of the Great Cormorant (Phalacrocorax carbo) in Algeria
Fig. 2. Monthly variation of the biomass of consumed fish by the great cormorant in Beni Haroun Dam Lake in Algeria.
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>
Data from: Human avoidance, selection for darkness and prey activity explain wolf diel activity in a highly cultivated landscape
<p>Wildlife that share habitats with humans with limited options for spatial avoidance must either tolerate frequent human encounters or concentrate their activity on those periods with the least risk of encountering people. Based on 5,259 camera trap images of adult wolves from eight territories, we analyzed the extent to which diel activity patterns in a highly cultivated landscape with extensive public access (Denmark) could be explained by diel variation in darkness, human activity, and prey (deer) activity. A resource selection function that contrasted every camera observation (use) with 24 alternative hourly observations from the same day (availability), revealed that diel activity correlated with all three factors simultaneously with human activity having the strongest effect (negative), followed by darkness (positive) and deer activity (positive). A model incorporating these three effects had lower parsimony and classified use and availability observations just as well as a 'circadian' model that smoothed the use-availability ratio as a function of time of the day. Most of the selection for darkness was explained by variation in human activity, supporting the notion that nocturnality (proportion of observations registered at night vs. day at the equinox) is a proxy for temporal human avoidance. Contrary to our expectations, wolves were no more nocturnal in territories with unrestricted public access than in territories where public access was restricted to roads, possibly because wolves in all territories had few possibilities to walk more than a few hundred meters without crossing roads. Overall, Danish wolf packs were 6.5 (95% CI: 4.6-9.6) times more active at night than at daylight, which makes them amongst the most nocturnally active wolves reported so far. These results confirm the prediction that wolves in habitats with limited options for spatial human avoidance, invest more in temporal avoidance.</p>
Fig. 3 in Habitat Preference And Prey Selection Of Marsh Harrier (Circus Aeruginosus) In Overwintering Area Of Southeast China
Fig. 3. Abundances of passerines (), pheasant () and marsh harrier (+) of the four years in the four habitats in Shahu Nature Reserve, China, with line transects 2000 m × 200 m (A, autumn; W,
Fig. 2 in Habitat Preference And Prey Selection Of Marsh Harrier (Circus Aeruginosus) In Overwintering Area Of Southeast China
Fig. 2. Wintering marsh harrier's abundance in different habitats in Shahu Nature Reserve, China in autumn and winter of 2001, 2003, 2004 and 2006
Fig. 1 in Habitat Preference And Prey Selection Of Marsh Harrier (Circus Aeruginosus) In Overwintering Area Of Southeast China
Fig. 1. Shahu Nature Reserve (SNR, autumn and winter). The up left shows the location of SNR; HB, Hubei Province; BWH, Beiwu Lake; NWH, Nanwu Lake; DC, Daocao Lake; DJ, Dongji River; YR, Yangtze River
FIGURE 2 in Prey selectivity of the invasive largemouth bass towards native and non-native prey: an experimental approach
FIGURE 2 | Relationship between the Manly-Chesson selectivity and prey availability for Micropterus salmoides. Higher values indicate preference for non-native species. Shading represents 95% confidence intervals. Note that because the index fluctuates between 0 and 1, with 2 types of prey and equal availability of prey for both types, the result of the index for one prey is exactly the opposite of the other. For this reason, the graph only shows the results of the index for the non-native species. The graph for the other type of prey would be the spectral image of this one.
FIGURE 1 in Prey selectivity of the invasive largemouth bass towards native and non-native prey: an experimental approach
FIGURE 1 | Relative consumption of non-native (Oreochromis niloticus and Coptodon rendalli) and native (Geophagus iporangensis) prey, considering different prey availability for Micropterus salmoides.
Data from: Human avoidance, selection for darkness and prey activity explain wolf diel activity in a highly cultivated landscape
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Data from: Predators drive selection for adaptive plasticity in prey defense behavior
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Data from: Interplay of trophic relaxation and directional selection shapes eco-evolutionary responses to selective harvest in predator-prey systems
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Data from: Predator life history and prey ontogeny limit natural selection on the major armour gene, Eda, in threespine stickleback
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Data from: Antagonistic species interaction drives selection for sex in a predator-prey system
<p>The evolutionary maintenance of sexual reproduction has long challenged biologists as the majority of species reproduce sexually despite inherent costs. Providing a general explanation for the evolutionary success of sex has thus proven difficult and resulted in numerous hypotheses. A leading hypothesis suggests that antagonistic species interaction can generate conditions selecting for increased sex due to the production of rare or novel genotypes that are beneficial for rapid adaptation to recurrent environmental change brought on by antagonism. To test this ecology-based hypothesis, we conducted experimental evolution in a predator (rotifer) - prey (algal) system by using continuous cultures to track predator-prey dynamics and in-situ rates of sex in the prey over time and within replicated experimental populations. Overall, we found that predator-mediated fluctuating selection for competitive versus defended prey resulted in higher rates of genetic mixing in the prey. More specifically, our results showed that fluctuating population sizes of predator and prey, coupled with a trade-off in the prey, drove the sort of recurrent environmental change that could provide a benefit to sex in the prey, despite inherent costs. We end with a discussion of potential population genetic mechanisms underlying increased selection for sex in this system, based on our application of a general theoretical framework for measuring the effects of sex over time, and interpreting how these effects can lead to inferences about the conditions selecting for or against sexual reproduction in a system with antagonistic species interaction.</p>
Data from: Behavioral hypervolumes of predator groups and predator-predator interactions shape prey survival rates and selection on prey behavior
Predator-prey interactions often vary on the basis of the traits of the individual predators and prey involved. Here we examine whether the multidimensional behavioral diversity of predator groups shapes prey mortality rates and selection on prey behavior. We ran individual sea stars (Pisaster ochraceus) through three behavioral assays to characterize individuals' behavioral phenotype along three axes. We then created groups that varied in the volume of behavioral space that they occupied. We further manipulated the ability of predators to interact with one another physically via the addition of barriers. Prey snails (Chlorostome funebralis) were also run through an assay to evaluate their predator avoidance behavior before their use in mesocosm experiments. We then subjected pools of prey to predator groups and recorded the number of prey consumed and their behavioral phenotypes. We found that predator-predator interactions changed survival selection on prey traits: when predators were prevented from interacting, more fearful snails had higher survival rates, whereas prey fearfulness had no effect on survival when predators were free to interact. We also found that groups of predators that occupied a larger volume in behavioral trait space consumed 35% more prey snails than homogeneous predator groups. Finally, we found that behavioral hypervolumes were better predictors of prey survival rates than single behavioral traits or other multivariate statistics (i.e., principal component analysis). Taken together, predator-predator interactions and multidimensional behavioral diversity determine prey survival rates and selection on prey traits in this system.
Habitat complexity dampens selection on prey activity level
<p>Conspecific prey individuals often exhibit persistent differences in behavior (i.e., animal personality) and consequently vary in their susceptibility to predation. How this form of selection varies across environmental contexts is essential to predicting ecological and evolutionary dynamics, yet remains currently unresolved. Here, we use three separate predator–prey systems (sea star–snail, wolf spider–cricket, and jumping spider–cricket) to independently examine how habitat structural complexity influences the selection that predators impose on prey behavioral types. Prior to conducting staged predator–prey interaction encounters, we ran prey individuals through multiple behavioral assays to determine their average activity level. We then allowed individual predators to interact with groups of prey in either open or structurally complex habitats and recorded the number and individual identity of prey that were eaten. Habitat complexity had no effect on overall predation rates in any of the three predator–prey systems. Despite this, we detected a pervasive interaction between habitat structure and individual prey activity level in determining individual prey survival. In open habitats, all predators imposed strong selection on prey behavioral types: sea stars preferentially consumed sedentary snails, while spiders preferentially consumed active crickets. Habitat complexity dampened selection within all three systems, equalizing the predation risk that active and sedentary prey faced. These findings suggest a general effect of habitat complexity that reduces the importance of prey activity level in determining individual predation risk. We reason this occurs because activity level (i.e., movement) is paramount in determining risk within open environments, whereas in complex habitats, other behavioral traits (e.g., escape ability to a refuge) may take precedence.</p>
Fig. 1 in Diet, Prey Selection and Biomass Consumption of the Great Cormorant (Phalacrocorax carbo) in Algeria
Fig. 1. Geographical location of Beni-Haroun Dam Lake in Algeria.
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