Local site variation in stopover physiology of migrating songbirds near the south shore of Lake Ontario is linked to fruit availability and quality

Birds that migrate long distances between breeding and wintering grounds are challenged to find adequate stopover sites that can provide a high-quality source of nutrition in order to refuel quickly and continue on their migratory journeys. Wild fruits are a well-documented component in the diets of many passerines during autumn migration. Thus, fruit availability and the proliferation of shrubs that bear low-quality fruits at important stopover sites may dictate the quality of food resources available for refuelling birds and present a conservation concern. We profiled plasma metabolites of two migratory passerine species at two different stopover sites near the south shore of Lake Ontario during the peak of autumn migration. We also measured diversity, availability and nutritional quality of fruits present at these sites. Site explained most of the variation in plasma triglyceride for both bird species, but was less important than other confounding variables for explaining concentrations of plasma β-hydroxybutyrate and plasma uric acid concentrations. Site differences in fat deposition, as indicated by plasma triglyceride, may in part be explained by the large differences in diversity and availability of high-quality fruits between the two sites. Our results suggest that abundant, lipid-rich native fruits with high-energy density are associated with increased fat deposition during autumn stopovers for some species, although other factors, such as proximity to the Lake Ontario shoreline and the opportunities to refuel in the surrounding landscape, are likely to play a role in stopover site use by birds. It is possible that local site characteristics that influence growing conditions may impact the quality of fruits produced by a plant species, altering the availability of critical nutrients for avian consumers.

Evaluation of methods to estimate understory fruit biomass

Fleshy fruit is consumed by many wildlife species and is a critical component of forest ecosystems. Because fruit production may change quickly during forest succession, frequent monitoring of fruit biomass may be needed to better understand shifts in wildlife habitat quality. Yet, designing a fruit sampling protocol that is executable on a frequent basis may be difficult, and knowledge of accuracy within monitoring protocols is lacking. We evaluated the accuracy and efficiency of 3 methods to estimate understory fruit biomass (Fruit Count, Stem Density, and Plant Coverage). The Fruit Count method requires visual counts of fruit to estimate fruit biomass. The Stem Density method uses counts of all stems of fruit producing species to estimate fruit biomass. The Plant Coverage method uses land coverage of fruit producing species to estimate fruit biomass. Using linear regression models under a censored-normal distribution, we determined the Fruit Count and Stem Density methods could accurately estimate fruit biomass; however, when comparing AIC values between models, the Fruit Count method was the superior method for estimating fruit biomass. After determining that Fruit Count was the superior method to accurately estimate fruit biomass, we conducted additional analyses to determine the sampling intensity (i.e., percentage of area) necessary to accurately estimate fruit biomass. The Fruit Count method accurately estimated fruit biomass at a 0.8% sampling intensity. In some cases, sampling 0.8% of an area may not be feasible. In these cases, we suggest sampling understory fruit production with the Fruit Count method at the greatest feasible sampling intensity, which could be valuable to assess annual fluctuations in fruit production.