Index to Patch Quality (IPQ) Applied to Yearling Steller Sea Lions in AlaskaIndex to Patch Quality (IPQ) Applied to Yearling Steller Sea Lions in Alaska

ResultsResultsafa

J Ward TestaWard TestaNational Marine Mammal Laboratory

c/o Biological Sciences - UAA

3211 Providence Dr

Anchorage, AK 99508

Jennifer M BurnsJennifer M BurnsDepartment of Biological Sciences

University of Alaska Anchorage

3211 Providence Dr

Anchorage, AK 99508

WhatWhat’’s an IPQ?s an IPQ?This This ““Index of Patch QualityIndex of Patch Quality”” was formulated for diving birds and mammals to explain the lengwas formulated for diving birds and mammals to explain the lengths of foraging dives in terms of ths of foraging dives in terms of

optimal foraging theory (Mori et al. 2002, Mori and Boyd 2004). optimal foraging theory (Mori et al. 2002, Mori and Boyd 2004). It assumes that a diving animal is constrained by the It assumes that a diving animal is constrained by the time it takes to reach a prey patch at depth (t), the quality oftime it takes to reach a prey patch at depth (t), the quality of that patch in terms of expected rate of energy gain (g), that patch in terms of expected rate of energy gain (g), and the time it will take to physiologically recover from each dand the time it will take to physiologically recover from each dive (s). The critical components of Mori and Boydive (s). The critical components of Mori and Boyd’’s IPQ s IPQ are:are:

•• The relationship between dive duration (u) and required surface The relationship between dive duration (u) and required surface interval (s) during foraginginterval (s) during foraging……we use a power function:we use a power function:s = A + B*s = A + B*uuCC

•• A power function describing the amount of energy taken in duringA power function describing the amount of energy taken in during bottom time (f) of a dive: bottom time (f) of a dive:

g = a*g = a*ffIPQIPQ ……the larger the IPQ, the more energy harvested from a patch the larger the IPQ, the more energy harvested from a patch

•• Net rate of energy intake during a dive cycle is energy intake rNet rate of energy intake during a dive cycle is energy intake rate (J /s) minus metabolic rate, mate (J /s) minus metabolic rate, mE = E = g/(u+sg/(u+s) ) –– mm

Mori and BoydMori and Boyd’’s IPQ assumes that an animal attempts to maximize E in any givens IPQ assumes that an animal attempts to maximize E in any given patch by adjusting its foraging time at the patch by adjusting its foraging time at the bottom of the dive. It is constrained by the physiological relatbottom of the dive. It is constrained by the physiological relationship between dive duration and surface interval. This ionship between dive duration and surface interval. This requires estimating a and m for the calculation, but IPQ does norequires estimating a and m for the calculation, but IPQ does not depend on their values. t depend on their values.

The relative value of E at different times and places may serve The relative value of E at different times and places may serve as an index of habitat quality, as it reflects the rate of energas an index of habitat quality, as it reflects the rate of energy y gain during foraging dives, where IPQ should overestimate the vagain during foraging dives, where IPQ should overestimate the value to the diver of high quality patches that require lue to the diver of high quality patches that require deep diving with long surface intervals. deep diving with long surface intervals.

It is instructive to illustrate the properties of E in relation It is instructive to illustrate the properties of E in relation IPQ and bottom time for two different relationships of surface iIPQ and bottom time for two different relationships of surface interval nterval to dive duration in order to understand how an animal might maxito dive duration in order to understand how an animal might maximize energy gain by adjusting its bottom time. mize energy gain by adjusting its bottom time.

Main Lessons: Main Lessons: •• As IPQ increases for any given travel time or as travel time incAs IPQ increases for any given travel time or as travel time increases for any given IPQ, the reases for any given IPQ, the

optimum bottom time increases. optimum bottom time increases. •• For a broad range of IPQ values the optimum bottom time exists oFor a broad range of IPQ values the optimum bottom time exists on a relatively flat surface. This n a relatively flat surface. This

means that an animal would require perfect information about patmeans that an animal would require perfect information about patch quality to optimize every dive. ch quality to optimize every dive. Therefore, it is likely that calculating IPQ values from dive daTherefore, it is likely that calculating IPQ values from dive data will be useful only for large ta will be useful only for large numbers of dives, and may have fairly coarse spatial and temporanumbers of dives, and may have fairly coarse spatial and temporal resolution. l resolution.

•• More theoretical work is needed on the sensitivity of IPQ to varMore theoretical work is needed on the sensitivity of IPQ to various durationious duration--interval relationships, interval relationships, and on the best way to characterize that relationship from divinand on the best way to characterize that relationship from diving datag data

Yearling Steller Sea Lions

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MethodsMethods

Data come from 12 yearling Steller sea lions instrumented with satellite-linked dive recorders (SLDRs) in Nov 2001 & 2003 and Mar 2005 in Prince William Sound, and one yearling near Kagalaska Island in Mar 2003. SLDRs provided duration and surface interval data from 99,890 dives, and time-depth profiles with 4 inflection points (Fedak et al. 2001) from 13,917 of these. Bottom time was defined as time spent at 80% of maximum depth. Location was interpolated between Argos locations at sea.

We derived a power function relationship between duration and surface interval based on the lower 30th percentile of surface intervals in 34 duration categories (13-488 s) for all individuals. This relationship captured features we expected a priori: a moderate surface interval for durations under the theoretical aerobic dive limit (ADL~130 s) for juvenile Steller sea lions, and increasing intervals past the ADL (Curve B, above). We calculated IPQ (Mori and Boyd 2004, explained above) and rate of net energy gain (E) that is maximized in the IPQ function for each dive over 15 m and 10 s bottom time. We assumed the allometric field metabolic rate for marine mammals reported by Williams et al (2005), which was consistent with the energetic models of Winship et al. (2002) for yearling Steller sea lions. Temporal pattern was modeled with polynomial regression in BUGS with independent intercept values for each sea lion. The intercepts were used to rescale IPQ’s before plotting their locations in ArcView and obtaining average values within grid squares.

ReferencesFedak et al. 2001. Two approaches to compressing and interpreting time-depth information as collected by time-depth recorders and satellite-linked data recorders. Mar.Mamm. Sci. 17: 94-110.Mori, Y., et al. 2002. An application of optimal diving models to diving behaviour in Brünnich’s guillemots. Animal Behaviour 64: 737-743.Mori, Y. and I.L. Boyd. 2004. The behavioral basis for nonlinear functional responses and optimal foraging in Antarctic fur seals. Ecology 85: 398-410.Williams, T.M. et al. 2004. Killer appetites: assessing the role of predators in ecological communities. Ecology 85:3373-3384.Winship, A.J. 2002. A bioenergetic model for estimating the food requirements of Steller sea lions Eumetopias jubatus in Alaska. Marine Ecology Progress Ser. 229: 291-312.

IntroductionIntroduction

Mori and Boyd (2004) formulated and applied an IPQ to foraging Antarctic fur seals and found good correlation between seasonal averages of fur seal IPQs and independent acoustic assessments of krill abundance. They also found that measured IPQ conformed well with some intuitive expectations: IPQ declined during foraging bouts consistent with prey depletion or dispersion in response to foraging, and reached similar “bout-ending” values when fur seals should abandon a patch and search for better patches, consistent with optimal foraging theory.

This approach has potential utility in assessment of critical habitat for endangered Steller sea lions. Survival of juvenile sea lions is believed to be a critical element in the decline of the western stock, as well as to their recovery. Direct measurement of prey availability and foraging success over this important part of their life history is difficult to impossible, but an analytical tool that extracts information about their foraging success using satellite telemetry from instrumented animals could be extremely valuable for identifying critical seasons and areas where habitat protection (e.g., fishing restrictions) might enhance foraging success for juvenile sea lions.

ObjectivesObjectives

Our objective was to evaluate whether Mori and Boyd’s IPQ metric could be usefully applied to satellite telemetry data from juvenile Steller sea lions and aid in identifying potentially critical habitat. Such telemetry imposes certain constraints relative to the TDR data used thus far for estimating IPQ, but might allow temporal and spatial patterns to be discovered. In particular we were interested in whether IPQ, and its associated metric E (net rate of energy gain during diving) produced sufficient variation, and spatial or temporal patterns that might indicate important feeding areas for juvenile Steller sea lions. Results are preliminary.

DiscussionDiscussion The seasonal pattern matches earlier conclusions

for average dive depth and bottom time, raising the possibility that the IPQ and predicted E either are not capturing new information about habitat quality, or result from an artifact in calculation. There is some empirical support for the theoretical conclusion that patches of equal quality should provoke a longer bottom time during deeper dives. The IPQ measure accommodates that prediction, so our result suggests either that it does not compensate enough for that effect when sea lions follow a shift in prey depths in winter, or that Steller sea lions forage deeper in winter because patch quality and foraging success improves at deeper depths.

Mean IPQ in a much-used area N of Glacier Island in winter (below) was only slightly above average. In this shallow area, an overestimate of surface interval could lead to an underestimate in the calculated IPQ (see central box).

Much more needs to be done to understand and improve on the IPQ. This includes theoretical questions about the dive duration to surface recovery function, and the influence of it and other assumptions on the IPQ. Any index to habitat quality derived from dive data will also require sophisticated field techniques to validate the measure against divers foraging in a known prey-field.

SummarySummary

Mori and Boyd’s (2004) Index of Patch Quality was applied to dive shapes obtained by satellite telemetry from 14 yearling Steller sea lions. In a record lasting from Nov-July, there was a significant seasonal peak in IPQ and predicted net rate of energy intake during dives in Nov-Jan, and a nadir in Apr-Jun. Results suggest the approach is worth pursuing, particularly toward better understanding of the performance and potential for artifacts in IPQ calculations, and field validation of IPQ measures.

ResultsResults

Mean IPQ in yearling sea lions was 0.32 (range 0.29-0.36), but varied as a 3rd order polynomial from Nov-July (Fig 1, fitted value in red).

Predicted net rate of energy intake (E) during dives followed the same pattern, peaking in Nov-Jan and reaching a nadir in Apr-June (Fig 2).

The mean IPQ among dives grouped by grid squares in Prince William Sound showed above-average values in the area most used (Fig top-right) in winter N of Glacier Island.

In spring, mean IPQ was not associated with any clear pattern of dive locations, although three the 25 km2 blocks near the main haul-out for N Prince William Sound had the lowest calculated IPQ’s.

Figure 2

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Acknowledgments

We wish to thank the Steller sea lion research program at Alaska Department of Fish and Game for field support of this project. Mike Rehberg (ADF&G) and George Esslinger (USGS) assisted with GIS analyses.