The recovery of wading bird populations has been identified as a key component of successful Everglades restoration (Walters et al. 1992). Proposed causes for the decline in wading bird numbers (Frederick and Collopy 1989, Bancroft et al. 1990, Walters et al. 1992) have in common the notion that current hydropatterns have altered the availability of prey. The relative importance of each component of food availability (i.e., food abundance and vulnerability to capture) is a precursor to understanding the effects of specific water management regimes on wading birds. Ongoing modeling efforts in south Florida such as the ATLSS program, integrate such information and provide predictive power for future management decisions. Currently, the biggest information gap limiting the wading bird component of ATLSS is foraging success as a function of prey availability and water depths (United States Geological Survey 1997).

The conceptual model for this study is that hydroperiod is a long-term process that primarily influences the abundance and structure of the prey community whereas water depth has immediate effects on individual birds by influencing their ability to capture prey. This study reports prey intake rates for four wading bird species feeding at various water depths and prey densities. The species of wading birds examined in this study are those in the ATLSS wading bird model: the Wood Stork ( Mycteria americana), White Ibis ( Eudocimus albus), Great Egret ( Casmerodius albus), and Great Blue Heron ( Ardea herodias).

MATERIALS AND METHODS

The field portion of this study was conducted in the Everglades Nutrient Removal Project adjacent to the northwest boarder of A.R.M. Loxahatchee National Wildlife Refuge, Palm Beach County, Florida. The experiment was conducted from 4 March, 1996 when ponds were stocked with golden shiners ( Notemigonus crysoleucas), to 21 March, 1996 when bird use nearly ceased. Treatments were assigned randomly among 12 ponds using a 3x2 (water depth 10 cm, 19 cm, 28 cm; fish density 3 fish/m², 10 fish/m²) factorial arrangement with two replicates. Before stocking with fish, ponds were drained and a screen with 1-cm mesh size was placed over the water inflow pipe to exclude prey-sized fish from entering through the water supply when ponds were refilled with water. Similar screens were placed over each outflow to keep the stocked fish from escaping.

Although ponds were initially stocked at known fish densities, those densities decreased quickly as a result of bird predation. Fish densities were determined during four sampling periods based on 1-m² throw-trap samples (Kushlan 1974). A test of sampling efficiency indicated the numbers of fish captured in throw traps represents an average of 55% of the actual fish density in the experimental ponds. All fish density values reported here are the number of golden shiners captured in throw traps uncorrected for sampling efficiency. A linear regression model was fitted to the data from each pond where the response was the number of fish/m² transformed as y(ln +1). The predicted values were back-transformed to get estimated densities of golden shiners for each pond each day of the experiment with the constraint that no predicted value could be less than zero. The estimated values were used in subsequent analyses of bird foraging success. See Gawlik (1996) for a detailed description of the experiment. Fish densities were classified into four quantiles based on the range of observed fish densities (0 - 3.17 fish/m²) during the experiment. Quantile 1 was 0 - 0.79 fish/m², quantile 2 was 0.8 - 1.59 fish/m², quantile 3 was 1.6 - 2.38 fish/m², and quantile 4 was 2.39 - 3.17 fish/m². However, because fish densities decreased rapidly, no birds were filmed when fish densities were in the range of quantiles 3 or 4.

Wading birds were censused at all ponds twice per morning with censuses separated by at least one hour. Following each census, foraging flocks in several ponds were filmed with a Hi-8mm video camera mounted on a vehicle. A pilot study indicated that filming from a parked vehicle with cloth-covered windows disturbed birds less than a portable blind. Selection of a flock to film was based on where the largest group of birds were foraging and whether data were lacking for a given combination of bird species, water depth and prey density. Flocks were allowed several minutes to re-settle and resume feeding before filming was initiated. Filming was concluded if flock size changed by more than 25%. Our aim was to get 15 min of film on each bird (with a minimum time limit of 5 min) and a maximum of 15 birds per species per film session. If no individuals in a film session met that criterion then the minimum time limit was reduced to 2 min. During feeding activities, birds would sometimes travel to the edge of a pond or leave the pond momentarily. Because of the sloped edge of the pond, water depths in those areas were less than treatment levels. Thus, we excluded from time-activity budgets any period where a bird was at the edge or outside of a pond. This criterion resulted in a further shortening of some time-activity budgets.

Following the field portion of the study, time-activity budgets of focal birds (Altmann 1974) were constructed from videotapes. Tapes were viewed using a Hi-8 VCR connected to a high-resolution video monitor. Data were entered into the Oracle® database through a personal computer connected to an interoffice-network.

To eliminate the possibility of constructing time-activity budgets on the same individual more than once in a session, we did not use as focal birds, individuals of the focal species that appeared in view after the first focal bird left the screen. However, before a focal bird left the field of view, any new birds that appeared could have been used as focal birds. A foraging bout ended when a focal bird left the field of view, became obscured in a flock, or the film session ended (usually about 15 minutes). Capture rates were calculated as the number of prey consumed divided by the length of time (min) of the time-activity budget. Birds that never consumed a prey item were excluded from the analysis. Prey was classified as a golden shiner if it was a fish longer than 3 cm, which was the approximate size allowed through the inflow screens. Prey was classified as a non-golden shiner if it was not a fish or if it was a fish smaller than 3 cm. Prey was classified as unknown if it was not clearly a golden shiner and it was not clearly a non-golden shiner. Because it was much more common for the prey items to be golden shiners than non-golden shiners, in the analysis we included both unknowns and golden shiners as prey.

To identify factors that affect capture rate, full and reduced statistical models were fit to the data using PROC GLM in SAS® version 6.12 for Windows®. Because of small sample sizes for the Great Blue Heron, only a reduced main-effects model was used. For the Wood Stork, White Ibis, and Great Egret, the full model contained depth as a class variable, fish density as a continuous variable, and the interaction term. If the interaction was not significant, a reduced model containing only main effects for water depth and fish density was constructed.

Giving-up density (GUD) is the amount of food remaining in a patch after an animal quits feeding in it (Brown 1988). If animals are foraging optimally, then GUD is an indirect measure of the foraging costs incurred by the animal in that patch because animals will leave a patch when their foraging costs equal their gains (Brown 1988). In this study, we calculated GUD for each species at each pond (1) the day that bird abundance for a given species decreased below 50% of the max (GUD_50%max) and (2) the last day a bird of a given species was seen in a pond (GUD_min). Ponds where a species never occurred were excluded for that species. Standard deviations reflect variation among ponds within a depth treatment. GUD values are uncorrected for sampling efficiency, which is approximately 55%.

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Related information:

How will research on fishes and wading birds guide and evaluate Everglades restoration? (poster from the South Florida Restoration Science Forum)

South Florida Wading Bird Report (hosted by the South Florida Water Management District)

Across Trophic Level System Simulation (ATLSS) project page (from the SOFIA website)

Across Trophic Level System Simulation (ATLSS) homepage

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