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35 results for “foraging success”
Foraging behavior and extended phenotype independently affect foraging success in spiders
<p>Multiple phenotypic traits often interact with each other to determine an individual's fitness. Behavioral and extended phenotypic traits, such as architectural constructions, can contribute to fitness in an integrated way. The goal of this study was to understand how the interaction between behavioral and extended phenotypic traits can affect foraging success. We tested this question using black widow spiders, where spiders that are aggressive in a foraging context tend to build more gumfooted silk lines that aid in prey capture, while non-aggressive spiders build webs with fewer gumfooted lines. We repeatedly assessed behavior and web structure to quantify relationships between these traits, and then allowed spiders to forage for live prey on their own web or the web of a conspecific that differed in structure. Thus, we assessed how varying combinations of behavior and web structure affect foraging success, and if correlational selection might act on them. We confirmed that aggressiveness and number of gumfooted lines are positively correlated and found that capture success increased with both aggressiveness and the number of gumfooted lines. Yet, we did not find any evidence for correlational selection: aggressiveness and number of gumfooted lines appeared to affect foraging success independently of each other. These findings highlight that a correlation between traits that contribute towards the same ecological function does not necessarily imply correlational selection. Taking advantage of the experimental convenience afforded by extended phenotypic traits can provide insight into the functional consequences of phenotypic variation within and between individuals.</p>
Data from: Reproductive effort and success of males in scramble competition polygyny: evidence for trade-offs between foraging and mate-search
1. Patterns of male reproductive allocation provide insight into life-history characteristics. The trade-offs associated with resource and female group defense are well-defined. However, less is understood about trade-offs in species that practice scramble-competition polygyny, where successful strategies may favor competitive mate-searching rather than contest competition and fighting. 2. White-tailed deer (Odocoileus virginianus) practice scramble-competition polygyny where solitary males search for and assess receptivity of females scattered across the landscape. Physically mature males are expected to do most of the breeding because of the high energetic costs of reproduction and high social status. However, young males may collectively sire one-third of offspring. To gain a better understanding of trade-offs associated with scramble-competition polygyny, we quantified metrics associated with reproductive effort and success. 3. We quantified changes in body mass of harvested males, energetic costs of locomotion based on movements of GPS radio-collared males, and timing of reproduction via temporal genetic parentage assignments. 4. Young males (1.5 and 2.5 years old) sired offspring, but their mating success was mainly limited to peak rut, when most females were in estrus. Furthermore, multiple paternity was common, indicating opportunistic reproduction. Reproductive effort, indexed by body mass loss, was highest in prime-age males (5.5-6.5 years old). Surprisingly, young and post-prime males also exhibited significant body mass loss, indicative of investment in reproductive effort. Movement rates increased 2 to 4-fold during rut as a function of mate-search activities, but cost of locomotion would cause only about one-third of observed body mass loss. Because males are capital breeders, we infer most of body mass loss is due to reduced foraging. 5. In scramble-competition polygyny, the repeated location of potential mates and assessment of their estrous status appear to be important constituents of male mating strategies. Therefore mating success may be influenced by time management and spatial memory, and not based solely on social dominance. Thus, reproductive effort should be greater for individuals capable of reducing time foraging. For those that cannot, opportunistic mating opportunities may arise when operative adult sex ratios are low. Our analyses reveal valuable insight into the trade-offs associated with scramble-competition polygyny.
Males miss and females forgo: auditory masking from vessel noise impairs foraging efficiency and success in killer whales - ALL 2011 & 2014 AUDIO DATA
<p><strong>Description of the data and file structure<br></strong>This record contains all 2011 & 2014 audio data from animal-borne biologging instruments (Dtags) temporarily affixed to fish-eating killer whales, supporting the analyses presented in the following article:</p> <p> Tennessen. J.B., Holt, M.M., Wright, B.M., Hanson, M.B., Emmons, C.K., Giles, D.A., Hogan, J.T., Thornton, S.J., Deecke, V.B. 2024. Males miss and females forgo: auditory masking from vessel noise impairs foraging efficiency and success in killer whales. <em>Global Change Biology</em>.<strong> </strong>In press.</p> <p>The data include the following: the 2011 & 2014 audio files from analyzed Dtag depoyments. All methodological details necessary to contextualize analysis procedures are provided in the methods section of the article. The following data files are available under separate DOIs: 10.5281/zenodo.13333019 - all 2009 & 2010 audio data; 10.5281/zenodo.13308835 - (1) all calibrated movement data from analyzed Dtag deployments, and (2) a spreadsheet containing the variables included in the fully-saturated and final models listed in Table 2 in the article cited above.</p> <p>These data are provided by NOAA Fisheries' Northwest Fisheries Science Center, and Fisheries and Oceans Canada, to support reproducibility of all statistical analyses presented in the article. Please cite your usage of our data. For inquiries about data use, or for general questions, please contact Dr. Jennifer B. Tennessen, at jtenness@uw.edu.</p> <p> </p> <p><strong>Description of audio data files</strong><br>The data files contain the .dtg extension. This is the compressed raw data from all analyzed deployments. Once files are downloaded, they will need to be decompressed, which is done using the tagtools tool kit for Matlab, R or Octave, available at https://github.com/animaltags .</p> <p>Each deployment is named using the first letter of the genus and species name ("oo" for Orcinus orca), followed by the two-digit year (e.g., 09 for 2009), followed by the 3-digit Julian day (e.g., 246), followed by a letter denoting the population (a-d for Northern Residents, m for Southern Residents), followed by a series of numbers that denote the specific block (on the tag memory board) from which the data came. All files from a deployment should be put within a folder for that deployment, so that the functions within the tagtools tool kit can locate them.</p> <p>Once the .dtg files are decompressed, there will be 4 new files for every decompressed file, with extensions as follows: .wav (audio) as well as .pk, .swv, .txt. The audio files are ready to use in .wav form, and can be viewed using any audio software. We recommend using Matlab with the tagtools tool kit, or viewing the files in batch mode within RavenPro (https://store.birds.cornell.edu/collections/raven-sound-software).</p> <p>We provide calibrated movement data (see DOI: 10.5281/zenodo.13308835). However, if users wish to run their own calibration from raw movement data, the .swv files are used for this purpose along with the tagtools tool kit in Matlab, R or Octave, available at https://github.com/animaltags .</p>
Males miss and females forgo: auditory masking from vessel noise impairs foraging efficiency and success in killer whales - ALL 2009 & 2010 AUDIO DATA
<p><strong>Description of the data and file structure<br></strong>This record contains all 2009 & 2010 audio data from animal-borne biologging instruments (Dtags) temporarily affixed to fish-eating killer whales, supporting the analyses presented in the following article:</p> <p> Tennessen. J.B., Holt, M.M., Wright, B.M., Hanson, M.B., Emmons, C.K., Giles, D.A., Hogan, J.T., Thornton, S.J., Deecke, V.B. 2024. Males miss and females forgo: auditory masking from vessel noise impairs foraging efficiency and success in killer whales. <em>Global Change Biology</em>.<strong> </strong>In press.</p> <p>The data include the following: the 2009 & 2010 audio files from analyzed Dtag depoyments. All methodological details necessary to contextualize analysis procedures are provided in the methods section of the article. The following data files are available under separate DOIs: 10.5281/zenodo.13328931 - all 2011 & 2014 audio data; 10.5281/zenodo.13308835 - (1) all calibrated movement data from analyzed Dtag deployments, and (2) a spreadsheet containing the variables included in the fully-saturated and final models listed in Table 2 in the article cited above.</p> <p>These data are provided by NOAA Fisheries' Northwest Fisheries Science Center, and Fisheries and Oceans Canada, to support reproducibility of all statistical analyses presented in the article. Please cite your usage of our data. For inquiries about data use, or for general questions, please contact Dr. Jennifer B. Tennessen, at jtenness@uw.edu.</p> <p> </p> <p><strong>Description of audio data files</strong><br>The data files contain the .dtg extension. This is the compressed raw data from all analyzed deployments. Once files are downloaded, they will need to be decompressed, which is done using the tagtools tool kit for Matlab, R or Octave, available at https://github.com/animaltags .</p> <p>Each deployment is named using the first letter of the genus and species name ("oo" for Orcinus orca), followed by the two-digit year (e.g., 09 for 2009), followed by the 3-digit Julian day (e.g., 246), followed by a letter denoting the population (a-d for Northern Residents, m for Southern Residents), followed by a series of numbers that denote the specific block (on the tag memory board) from which the data came. All files from a deployment should be put within a folder for that deployment, so that the functions within the tagtools tool kit can locate them.</p> <p>Once the .dtg files are decompressed, there will be 4 new files for every decompressed file, with extensions as follows: .wav (audio) as well as .pk, .swv, .txt. The audio files are ready to use in .wav form, and can be viewed using any audio software. We recommend using Matlab with the tagtools tool kit, or viewing the files in batch mode within RavenPro (https://store.birds.cornell.edu/collections/raven-sound-software).</p> <p>We provide calibrated movement data (see DOI: 10.5281/zenodo.13308835). However, if users wish to run their own calibration from raw movement data, the .swv files are used for this purpose along with the tagtools tool kit in Matlab, R or Octave, available at https://github.com/animaltags .</p>
Age-related breeding success in little penguins: A result of selection and ontogenetic changes in foraging and phenology
<p>Reproductive performance typically improves with age, reaching a plateau at middle age and subsequently declining in older age classes (senescing individuals). Three potential non-exclusive mechanisms can explain the improvement in reproductive performance with age: (1) selection (poor quality individuals are removed from the population with increasing age), (2) constraint (individual efficiency increases through experience) and (3) restraint (reproductive investment increases with age as the residual reproductive value decreases). While all three mechanisms received strong empirical support, few studies have aimed at teasing apart those hypotheses and understanding their underlying functioning. In little penguins (Eudyptula minor), we used a 19-year longitudinal dataset on breeding and foraging of more than 450 individuals to investigate the effect of age on breeding success. We separated within- from among-individual age-effects using state-of-the-art statistical methods (within-subject centering and population change decomposition). We then assessed whether within-individual changes in breeding resulted from ontogenetic changes in foraging performances, breeding phenology or access to mates and nest sites. Fidelity and assortative pairing explained the high correlation in male and female ages within a pair. Breeding performances followed a typical bell-shaped curve with performance increasing up to 8 years-old, before reaching a plateau and subsequently declining after age 16. Both selection and within-individual processes occurred, although within-individual changes dominated differences in age-dependent breeding success. The selective appearance had almost no effect (apart from ages 2 to 3), and selective disappearance mostly affected changes at old ages (above 16), although they were also responsible for the slight increase in reproductive performances from ages 5 to 8. Focusing on within-individual changes, birds exhibited higher performances at middle ages, with birds foraging better, laying earlier and changing partner and nest less often. Their reproductive investment did not vary with age for females and slightly decreased for males. This supports the constraint hypothesis but not the restraint one. Finally, the increase in breeding performances at young ages was explained by the age-related increase in foraging performances during chick-rearing and advancement of laying. In contrast, reproductive senescence was defined by a general decrease in bird performances.</p>
Data from: Environmental heterogeneity decreases reproductive success via effects on foraging behaviour
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Data from: Mating success and body condition not related to foraging specializations in male fur seals
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Age-related breeding success in little penguins: A result of selection and ontogenetic changes in foraging and phenology
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Data from: Reproductive effort and success of males in scramble competition polygyny: evidence for trade-offs between foraging and mate-search
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Data from: Social effects on foraging behaviour and success depend on local environmental conditions
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Foraging behavior and extended phenotype independently affect foraging success in spiders
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Data from: Local prey shortages drive foraging costs and breeding success in a declining seabird, the Atlantic puffin
<p>As more and more species face anthropogenic threats, understanding causes of population declines in vulnerable taxa is essential. However, long-term datasets, ideal to identify lasting or indirect effects on fitness measures such as those caused by environmental factors, are not always available. </p> <p>Here we use a single year but multi-population approach on populations with contrasting demographic trends to identify possible drivers and mechanisms of seabird population changes in the north-east Atlantic, using the Atlantic puffin, a declining species, as a model system. </p> <p>We combine miniature GPS trackers with camera traps and DNA metabarcoding techniques on four populations across the puffins' main breeding range to provide the most comprehensive study of the species' foraging ecology to date. </p> <p>We find that puffins use a dual foraging tactic combining short and long foraging trips in all four populations, but declining populations in southern Iceland and north-west Norway have much greater foraging ranges, which require more (costly) flight, as well as lower chick-provisioning frequencies, and a more diverse but likely less energy-dense diet, than stable populations in northern Iceland and Wales. </p> <p>Together, our findings suggest that the poor productivity of declining puffin populations in the north-east Atlantic is driven by breeding adults being forced to forage far from the colony, presumably because of low prey availability near colonies, possibly amplified by intraspecific competition. Our results provide valuable information for the conservation of this and other important North-Atlantic species and highlight the potential of multi-population approaches to answer important questions about the ecological drivers of population trends.</p>
Data from: Individual learning performance and exploratory activity are linked to colony foraging success in a mass-recruiting ant
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Data from: Local prey shortages drive foraging costs and breeding success in a declining seabird, the Atlantic puffin
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Galapagos sea lion foraging success
<p>Data set for paper on Galapagos sea lion foraging success.</p>
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