Cryptic interference competition in swans foraging on cryptic prey

Gyimesi, Abel; Stillman, Richard A.; Nolet, Bart A.

doi:10.1016/j.anbehav.2010.07.006

Cited by 21 publications

(32 citation statements)

References 51 publications

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“…The rate of foraging success decreased in each habitat with abundant food but high disturbance to ensure more secure access to food. In addition, disturbances reduced the intake rate (Gyimesi et al 2010). When food sources were lacking in their traditional foraging habitats, waterbirds are more likely to feed in higher risk areas, such as paddy fields (Inger et al 2006;Godvik et al 2009).…”

Section: Discussionmentioning

confidence: 99%

Shifts in foraging behavior of wintering Hooded Cranes (Grus monacha) in three different habitats at Shengjin Lake, China

2016

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Background: Wetland loss and degradation result in a reduction in the availability and quality of food for wintering waterbirds. Birds normally modify their foraging behavior to adapt to variations in food availability. In this study, we compared shifts in foraging behavior of Hooded Cranes (Grus monacha) in three different habitats at Shengjin Lake, China to understand the response of these cranes to changes in habitat. Methods:We investigated the food density and foraging behavior of Hooded Cranes in Shengjin Lake National Nature Reserve from November 2014 to April 2015. We used regression equations to describe the changes in food density. A total of 397 behavioral observations were used in the analyses of their foraging efforts. We fitted a candidate set of generalized mixed linear models to analyze the relationship of foraging efforts and food density. We used a method of information theory to guide the selection of the model and Akaike's Information Criterion to calculate the value of each model. The relationship between food density, disturbances and foraging behavior was illustrated using a generalized linear model. Results:Along with the temporal variation and exploitation of food biomass, the food density varied widely among foraging sites. During the early winter period, foraging efforts were more pronounced in the paddy fields and meadows but not significantly different among the three habitats. The cranes spent more foraging effort in the paddy fields and meadows during the middle stage and in the meadows and mudflats during the late winter. The results of the generalized linear model showed that food density and disturbances had different effects on the rate of foraging success during the winter, while the effect of foraging effort was not significant. Furthermore, the rate of feeding success was markedly affected by disturbances in the paddy fields. The combined action of food density and disturbances had a significant effect on the rate of foraging success in the meadows, while the effect of foraging effort was also not significant in three habitats. Conclusions:Changes in foraging behavior were significant in three habitats, which were affected by food density and disturbances. The rate of foraging success increased in the habitat with low food density and low disturbances to increase the foraging efficiency in the lake. With abundant food and a high level of disturbance, the rate of foraging success decreased to ensure more secure access to food.

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Section: Discussionmentioning

confidence: 99%

Shifts in foraging behavior of wintering Hooded Cranes (Grus monacha) in three different habitats at Shengjin Lake, China

2016

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“…However, birds may not be able to find all pondweed patches. In addition, foraging in a group may bring about reduced efficiencies (Gyimesi et al 2010), and thus birds may quit foraging earlier than estimated by functional response models. Finally, some inlets of the Lauwersmeer are open to recreational activities, and may not always be available for swans (Gyimesi, Franken, Feige and Nolet, unpubl.…”

Section: Discussionmentioning

confidence: 99%

“…However, competition may also influence site selection because interference likely reduce food intake rates (Sutherland 1983;Janson and Goldsmith 1995;Gyimesi et al 2010). In addition, deeper inlets may be abandoned earlier than shallower ones if water level increases.…”

Section: Discussionmentioning

confidence: 99%

Net Energy Intake Rate as a Common Currency to Explain Swan Spatial Distribution in a Shallow Lake

et al. 2012

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Animal distribution is usually predicted from the spatial variation in food biomass, whereas foraging theory commonly uses net energy intake rate as the currency to be maximized. We tested whether net energy intake rate better predicted the distribution and abundance of tundra swans than food biomass. In a shallow lake, we mapped the density of sago pondweed tubers during 2 years, and calculated the foraging benefits and costs to tundra swans. Swan residence was expressed in bird-days, i.e. the sum of daily counts. We used four measures of increasing complexity to predict bird-days per inlet: total food biomass (B), total food biomass above giving-up density (B+), total accessible food biomass above giving-up density (aB+), and total achievable net energy intake rate above giving-up energy intake rate (NEI+). Considering both years, observed bird-days of inlets correlated only with NEI+, and not with B, B+, or aB+. In both years, our predictions of bird-days based on the NEI+model better matched observed relationships than the predictions of the other three models. Our case study suggests that in heterogeneous wetlands, correcting for givingup density, food accessibility and foraging costs may be necessary in order to predict bird distribution and abundance.

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“…Despite recent efforts to quantify the effects of interference (Gyimesi et al 2010;Nakayama and Fuiman 2010;Rutten et al 2010;Ping et al 2011), little is known about how these effects are influenced by external factors that may be biotic (e.g., prey density) or abiotic (e.g., environmental temperature). Most previous studies-either theoretical (Stillman et al 2000) or empirical (Sih 1981;Dolman 1995;Cresswell 1998;Triplet et al 1999)-support the notion that interference is stronger at lower prey densities (or reduced encounter rates).…”

Section: Introductionmentioning

confidence: 99%

“…The majority of studies that have attempted to test the effect of interference alone have approached the issue indirectly using either statistical (Scharf et al 2008) or mathematical (Stillman et al 2000) tools, including models based on field observations (Gyimesi et al 2010), or a complex description of diet versus space use with measurements of both prey availability and risk of intraspecific interactions (Post et al 1999). A simple direct measurement of the level of interference competition can only be achieved in a few specific systems where competition is coupled with the excretion of allelochemicals: toxins or growth inhibitors (Steinwascher 1978;Folt and Goldman 1981).…”

Section: Introductionmentioning

confidence: 99%

Interference competition in a planktivorous fish (Rutilus rutilus) at different prey densities and temperatures

et al. 2014

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The effect of interference competition can be assessed by comparing the capture rate of a predator foraging alone with that of the predator within a group. Since such an effect could be prey density dependent, a constant density of prey must be maintained while assessing this effect, irrespective of the elimination of prey by predation. However, when studying a predator-harvester, such as a planktivorous fish, which collects zooplankton at a rate of up to 1 prey s -1 , instantaneous replacement of each consumed prey item is not feasible. This problem was solved in short-lasting mesocosm experiments by minute-byminute supplementation to replace eliminated Daphnia and maintain a constant average prey density. Such experiments were performed with different numbers of foraging roach (Rutilus rutilus) at three prey densities and in two ranges of ambient temperature. The number of Daphnia required at the start of each experiment to establish the initial prey density and the number that it was necessary to add per minute were determined in experiments conducted without prey supplementation and in preliminary experiments with prey supplementation. The results of this study revealed that fish foraging in a group eat less, due to both exploitation and non-aggressive competition for space. Moreover, the effect of interference competition was stronger at higher temperatures, irrespective of the prey density, indicating that natural populations of roach foraging in shoals may suffer more from competitive interactions in warmer waters.

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Cryptic interference competition in swans foraging on cryptic prey

Cited by 21 publications

References 51 publications

Shifts in foraging behavior of wintering Hooded Cranes (Grus monacha) in three different habitats at Shengjin Lake, China

Shifts in foraging behavior of wintering Hooded Cranes (Grus monacha) in three different habitats at Shengjin Lake, China

Net Energy Intake Rate as a Common Currency to Explain Swan Spatial Distribution in a Shallow Lake

Interference competition in a planktivorous fish (Rutilus rutilus) at different prey densities and temperatures

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