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78 results for “diet seasonality”
Fig. 3 in Gape size influences seasonal patterns of piscivore diets in three Neotropical rivers
Fig. 3. Relationship between standard length and gape width for the four predator species.
Data from: Predator-prey interactions in the Arctic: DNA-metabarcoding reveals that nestling diet of snow buntings reflects arthropod seasonality
<p>Tundra arthropods are of considerable ecological importance as a seasonal food source for many arctic-breeding birds. Dietary composition and food preferences are rarely known, complicating assessments of ecological interactions in a changing environment. In our field study, we investigated nestling diet of snow buntings (<em>Plectrophenax nivalis</em> (L., 1758)) breeding in Svalbard. We collected faecal samples from 8-day-old nestlings and assessed dietary composition by DNA-metabarcoding. Simultaneously, the availability of potential prey arthropods was measured by pitfall-trapping. Molecular analyses of nestling faeces identified 31 arthropod taxa in the diet, whose proportions changed throughout the brood-rearing period. Changes in nestling diet matched varying abundances and emergence patterns of the tundra arthropod community. Snow buntings provisioned their offspring mainly with Diptera (true flies) based on both presence/absence and relative read abundance of diet items. At the beginning of the season in June, Chironomidae (non-biting midges) and the scathophagid fly <em>Scathophaga furcata</em> (Say, 1823) dominated the diet, whereas the muscid fly <em>Spilogona dorsata </em>(Zetterstedt, 1845) dominated the diet later in July. When accounted for availability, muscid flies were selected positively amongst the most often provisioned food taxa. Our study demonstrates the ecological role of the snow bunting as a generalist arthropod predator and highlights DNA-metabarcoding as a non-invasive technique for diet analyses with high taxonomical precision if sufficient DNA-sequence libraries are available.</p>
Data from: Delineating seasonal shifts in Reindeer habitat and diet selection by integrating GPS telemetry and stable Isotope analysis
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Focal vs. faecal: Seasonal variation in the diet of wild vervet monkeys from observational and DNA metabarcoding data
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Contrasting seasonal patterns in diet and dung-associated invertebrates of feral cattle and horses in a rewilding area
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Data from: Diet of a rare herbivore based on DNA metabarcoding of feces: selection, seasonality, and survival
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Urban peregrine falcon (Falco peregrinus) breeding season diet in UK, 2020–2022
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Data from: Predator-prey interactions in the Arctic: DNA-metabarcoding reveals that nestling diet of snow buntings reflects arthropod seasonality
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Data from: Seasonal changes in diet and toxicity in the Climbing Mantella frog (Mantella laevigata)
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Fish resist temptation from junk food: State-dependent diet choice in reproductive Atlantic cod (Gadus morhua) facing seasonal fluxes of lipid-rich prey
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Endangered predators and endangered prey: seasonal diet of Southern Resident killer whales
<p>Understanding diet is critical for conservation of endangered predators. The Southern Resident killer whales (SRKW) (<em>Orcinus orca</em>) are an endangered population occurring primarily in the west coast and inland waters of Washington and British Columbia. Insufficient prey has been identified as a factor limiting their recovery, so a clear understanding of the whales' seasonal diet is a high conservation priority. Previous studies have shown that their summer diet in inland waters consists primarily of Chinook salmon (<em>Oncorhynchus tshawytscha</em>), despite this species' rarity compared to some other salmonids. During other times of year, when ranging patterns include the U.S. and Canadian west coast and the northern and southern portions of the Salish Sea, their diet is largely unknown. To address this data gap, we collected feces and prey remains from October to May 2004-2017 in both the Salish Sea and U.S. west coast waters. Using visual and genetic species identification for prey remains and genetic approaches for fecal samples, we characterized the diet of the SRKWs in fall, winter, and spring. Chinook salmon were identified as an important prey item year-round, averaging ~50% of their diet in the fall, increasing to 70-80% in the late winter/early spring, and returning to nearly 100% in the late spring. Other salmon species and non-salmonid fishes, also made substantial dietary contributions. The relatively high species diversity in winter suggested a possible lack of Chinook salmon, probably due to seasonally lower densities, based on their proclivity to selectively consume this species in other seasons. A wide diversity of Chinook salmon stocks were consumed, many of which are also at risk. Although west coast samples consisted of 14 stocks, four rivers systems accounted for 90% of the samples, predominantly the Columbia River. Increasing the abundance of Chinook salmon stocks that inhabit the whales' winter range may be an effective conservation strategy for this population.</p>
Data from: 18S rRNA metabarcoding diet analysis of the predatory fish community across seasonal changes in prey availability
Predator-prey relationships are important ecological interactions, affecting biotic community composition and energy flow through a system, and are of interest to ecologists and managers. Morphological diet analysis has been the primary method used to quantify the diets of predators, but emerging molecular techniques using genetic data can provide more accurate estimates of relative diet composition. This study used sequences from the 18S V9 rRNA barcoding region to identify prey items in the gastrointestinal (GI) tracts of predatory fishes. Predator GI samples were taken from the Black River, Cheboygan Co., MI, USA (n=367 samples, 12 predator species) during periods of high prey availability, including the larval stage of regionally threatened lake sturgeon (Acipenser fulvescens Rafinesque 1817) in late May/early June of 2015 and of relatively lower prey availability in early July of 2015. DNA was extracted and sequenced from 355 samples (96.7%), and prey DNA was identified in 286 of the 355 samples (80.6%). Prey were grouped into 33 ecologically significant taxonomic groups based on the lowest taxonomic level sequences that could be identified using sequences available on GenBank. Changes in the makeup of diet composition, dietary overlap, and predator preference were analyzed comparing the periods of high and low prey abundance. Some predator species exhibited compositional changes in diet. Dietary overlap was slightly but significantly higher during the period of high prey abundance. There was little evidence for large changes in predator preference between the two periods. This study demonstrates the utility of molecular diet analysis in understanding predator-prey interactions in complex freshwater communities.
Data from: Prairie dogs, cattle subsidies, and alternative prey: Seasonal and spatial variation in coyote diet in a temperate grassland
<p class="MsoNormal"><span>As the dominant predator on North America's grasslands, coyotes (<em>Canis latrans</em>) have a large influence on biodiversity, both on working ranches and in protected parks. Ground squirrel (sciurid) species and livestock carrion are often abundant on grasslands worldwide and have the potential to influence a predator's consumption of alternative prey. We collected 1321 scats in four seasons over two years in and adjacent to Grasslands National Park, Saskatchewan, to test the hypothesis that seasonal and spatial variation in consumption of sciurid prey and cattle (<em>Bos taurus</em>) carrion influenced coyote consumption of alternative prey.<strong> </strong>Sciurid (black-tailed prairie dog <em>Cynomy</em>s<em> ludovicianus</em> and Richardson's ground squirrel </span><em>Urocitellus richardsonii</em><span>) remains were common from spring to fall and had a strong inverse relationship with deer (mule deer <em>Odocoileus hemionus</em> and white-tailed deer <em>O. virginianus</em>), which were most common in winter scats. Cattle remains were most common during spring, fall and winter, occurring in 10.6% of scats annually. Biomass estimates indicated that cattle was the highest ranked food on cattle grazing land year-round, and the 2<sup>nd</sup> ranked food, after deer, during winter on the portion of the park from which cattle were excluded. Closer proximity of scats to a prairie dog colony increased the likelihood of prairie dog remains throughout the year and reduced the likelihood of cattle remains in scats from spring to fall, but not during winter. Individual differences in foraging and ranging behavior may explain the spatial distribution of prairie dog versus cattle in scats. </span><span>Further work is needed to determine whether </span><span>sciurid prey, deer, or livestock carrion </span><span>support large predator populations on grassland habitats to a level that may negatively affect coexisting prey species, including species at risk.</span></p>
Seasonal weighted percentage of occurrence (wPOO) of different arthropod orders in the diet of bats of northern Madagascar
<p>This table (updated from previous version) is part of the PhD thesis of Carme Tuneu-Corral, entitled '<strong>Bats and rice: promoting Integrated Pest Management to enhance biodiversity conservation</strong>'. It is the Table A4.2 of the supplementary material of the Chapter 5 '<em>Beyond borders: evaluating the role of protected areas in promoting bat-mediated pest suppression in rural areas of northern Madagascar</em>', and illustrates the weighted percentage of occurrence (wPOO) of each arthropod order in the diet of the different bat species for each season (dry and wet). The values in brackets next to each species name are the total samples collected for that species.</p> <p>Methodology: </p> <p>When focusing on the different bat species, bat diet was assessed using the weighted percentage of occurrence data (wPOO), which is similar to POO, but it weights each occurrence according to the number of food items in the sample, since it may be more biologically realistic than using POO or FOO. As discussed by Deagle et al. (2019), POO data is useful because it shows each food taxon's percentage of the total diet (unlike FOO, which does not sum to 100%). However, wPOO may be more accurate because it weights each sample equally, preventing samples with many food taxa from having stronger influence. wPOO values were also calculated for each season (dry/wet) independently, in order to perceive changes in prey preferences depending on the season. </p>
FIG. 2 in Spatial, Seasonal, and Sexual Variation in the Diet of Graptemys flavimaculata, a Threatened Turtle of the Pascagoula River System, Mississippi, USA
FIG. 2. Diets of male and female Graptemys flavimaculata from the Leaf (LR) and lower Pascagoula Rivers (PR) by season (Spring—dark gray, Summer—black, Fall—light gray). Prey items are sorted alphabetically with minor items not included.
FIG. 1 in Spatial, Seasonal, and Sexual Variation in the Diet of Graptemys flavimaculata, a Threatened Turtle of the Pascagoula River System, Mississippi, USA
FIG. 1. Percent molluscivory of male and female Graptemys flavimaculata from the Leaf River (LR) and the lower Pascagoula River (PR).
Figure 1 in Seasonal diets of Asiatic black bear (Ursus thibetanus) in the Khangchendzonga National Park, Eastern Himalaya India
Figure 1. Map showing the study area of Khangchendzonga National Park (Sikkim) and its surrounding with scat collection location points.
Figure 4 in Seasonal diets of Asiatic black bear (Ursus thibetanus) in the Khangchendzonga National Park, Eastern Himalaya India
Figure 4. Percentage of food items presence in the U. thibetanus based on the scats collected from KNP and surrounding areas.
Figure 3 in Seasonal diets of Asiatic black bear (Ursus thibetanus) in the Khangchendzonga National Park, Eastern Himalaya India
Figure 3. Altitudinal distribution pattern of recorded signs of U. thibetanus in the KNP and surrounding areas.
Seasonal Patterns of Stress, Diet and Physical Activity - Life in All Seasons (LENAS)
ClinicalTrials.gov study NCT01674296. IPD Sharing: NO. Countries: 1. Publications: 1.
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