We tested whether the spatial variation in resource depletion by Tundra Swans (Cygnus columbianus) foraging on belowground tubers of sago pondweed (Potamogeton pectinatus) was caused by differences in net energy intake rates. The variation in givingup densities within the confines of one lake was nearly eightfold, the giving-up density being positively related to water depth and, to a lesser extent, the silt content of the sediment. The swans' preference (measured as cumulative foraging pressure) was negatively related to these variables. We adjusted a model developed for diving birds to predict changes in the time allocation of foraging swans with changes in power requirements and harvest rate. First, we compared the behavior of free-living swans foraging in shallow and deep water, where they feed by head-dipping and up-ending, respectively. Up-ending swans had 1.3-2.1 times longer feeding times than head-dipping swans. This was contrary to our expectation, since the model predicted a decrease in feeding time with an increase in feeding power. However, up-ending swans also had 1.9 times longer trampling times than headdipping swans. The model predicted a strong positive correlation between trampling time and feeding time, and the longer trampling times may thus have masked any effect of an increase in feeding power. Heart rate measurements showed that trampling was the most energetically costly part of foraging. However, because the feeding time and trampling time changed concurrently, the rate of energy expenditure was only slightly higher in deep water (1.03-1.06 times). This is a conservative estimate since it does not take into account that the feeding costs of up-ending are possibly higher than that of head-dipping. Second, we compared captive swans foraging on sandy and clayey sediments. We found that the harvest rate on clayey sediment was only 0.6 times that on sandy sediment and that the power requirements for foraging were 1.2-1.4 times greater. Our results are in qualitative agreement with the hypothesis that the large spatial variation in giving-up densities was caused by differences in net rates of energy intake. This potentially has important implications for the prey dynamics, because plant regrowth has been shown to be related to the same habitat factors (water depth and sediment type).

Summary 1.In a system where depletion drives a habitat shift, the hypothesis was tested that animals switch habitat as soon as the average daily net energy intake (or gain) drops below that attainable in the alternative habitat. 2. The study was performed in the Lauwersmeer area. Upon arrival during the autumn migration, Bewick's swans first feed on below-ground tubers of fennel pondweed on the lake, but subsequently switched to feeding on harvest remains in sugar beet fields. 3. The daily energy intake was estimated by multiplying the average time spent foraging per day with the instantaneous energy intake rate while foraging. In the case of pondweed feeding, the latter was estimated from the functional response and the depletion of tuber biomass. In the case of beet feeding, it was estimated from dropping production rate. Gross energy intake was converted to metabolizable energy intake using the assimilation as determined in digestion trials. The daily energy expenditure was estimated by the time-energy budget method. Energetic costs were determined using heart rate. 4. The daily gain of pondweed feeding at the median date of the habitat switch (i.e. when 50% of the swans had switched) was compared with that of beet feeding. The daily gain of beet feeding was calculated for two strategies depending on the night activity on the lake: additional pondweed feeding (mixed feeding) or sleeping (pure beet feeding). 5. The majority of the swans switched when the daily gain they could achieve by staying on the pondweed bed fell just below the average daily gain of pure beet feeders. However, mixed feeders would attain an average daily gain considerably above that of pondweed feeders. A sensitivity analysis showed that this result was robust. 6. We therefore reject the hypothesis that the habitat switch by swans can be explained by simple long-term energy rate maximization. State-dependency, predation risk, and protein requirements are put forward as explanations for the delay in habitat switch.

evolution and 100 replications for maximum likelihood. Shape parameters for the gamma distribution were estimated from minimum length trees 26 and were 0.32 (mtDNA), 0.59 (vWF) and 0.52 (A2AB). Divergence times. 12S rRNA transversions accumulated linearly as far back as the eutherian-metatherian split 24 . Nine independent cladogenic events were selected based on 12S rRNA sequence availability and paleostratigraphic data 10,24,30 (for example, Rattus to Mus (14 Myr); Sus to Tayassu (45 Myr); ruminants to Cetacea (60 Myr); Erinaceus to Metatheria (130 Myr)). Relative rates were calculated in reference to xenarthrans. Tamura-Nei transversion distances (transversions only) were adjusted for relative rate differences 30 against the xenarthran standard. Rate-adjusted estimates of sequence divergence were regressed against paleostratigraphic divergence estimates for each of the nine calibration points (origin forced through zero; r 2 ¼ 0:97; P ¼ 0:0000002). The resulting equation ðdivergence time ðin MyrÞ ¼ sequence divergence=0:00063Þ was used to estimate interordinal divergence times after making similar adjustments for relative rates. Additional details will be presented elsewhere (M.S., manuscript in preparation).

We tested whether the spatial variation in resource depletion by Tundra Swans (Cygnus columbianus) foraging on belowground tubers of sago pondweed (Potamogeton pectinatus) was caused by differences in net energy intake rates. The variation in giving‐up densities within the confines of one lake was nearly eightfold, the giving‐up density being positively related to water depth and, to a lesser extent, the silt content of the sediment. The swans' preference (measured as cumulative foraging pressure) was negatively related to these variables. We adjusted a model developed for diving birds to predict changes in the time allocation of foraging swans with changes in power requirements and harvest rate. First, we compared the behavior of free‐living swans foraging in shallow and deep water, where they feed by head‐dipping and up‐ending, respectively. Up‐ending swans had 1.3–2.1 times longer feeding times than head‐dipping swans. This was contrary to our expectation, since the model predicted a decrease in feeding time with an increase in feeding power. However, up‐ending swans also had 1.9 times longer trampling times than head‐dipping swans. The model predicted a strong positive correlation between trampling time and feeding time, and the longer trampling times may thus have masked any effect of an increase in feeding power. Heart rate measurements showed that trampling was the most energetically costly part of foraging. However, because the feeding time and trampling time changed concurrently, the rate of energy expenditure was only slightly higher in deep water (1.03–1.06 times). This is a conservative estimate since it does not take into account that the feeding costs of up‐ending are possibly higher than that of head‐dipping. Second, we compared captive swans foraging on sandy and clayey sediments. We found that the harvest rate on clayey sediment was only 0.6 times that on sandy sediment and that the power requirements for foraging were 1.2–1.4 times greater. Our results are in qualitative agreement with the hypothesis that the large spatial variation in giving‐up densities was caused by differences in net rates of energy intake. This potentially has important implications for the prey dynamics, because plant regrowth has been shown to be related to the same habitat factors (water depth and sediment type).

Preface 262 1 Aims of this report 263 2 Telemetry and data logging 263 3 How to use this report 264 4 Harms and bene ts associated with telemetry 264 4.1 Potential harms associated with telemetry 265 4.2 Opportunities for re nement using telemetry 266 4.2.1 Re ning procedures using telemetry 266 4.2.2 Using telemetry to re ne housing and care 267 4.2.3 The potential for reduction 267 4.2.4 Data quality 267 5 Legal issues 268 6 Experimental design 268 6.1 Data and sampling 268 6.2 Physical arrangement of hardware 269 7 Selecting or designing a device 270 7.1 Mass of the device 270 WORKING PARTY REPORT # Laboratory Animals Ltd. Laboratory Animals (2003) 37, 261-299 7.2 Shape and dimensions 7.3 Location 7.4 Attachment or implantation? 7.4.1 Total implants 7.4.2 External devices-jackets and backpacks 7.4.3 Internal devices with exterior components, including skin buttons 8 Basic principles of surgical implantation 8.1 Surgery-general considerations 8.1.1 Expertise and training 8.1.2 The use of animals to gain manual skills 8.1.3 Asepsis 8.1.4 Fitting implants, cables and catheters 8.1.5 Inserting transducers into blood vessels 8.1.6 Checking and closing 8.1.7 Standard Operating Procedures 8.2 Anaesthesia 8.3 Pain management 8.3.1 Analgesia 8.3.2 Postoperative husbandry and care 8.4 Monitoring animals following surgery 8.5 Potential postoperative complications and repairing surgery 8.6 Long-term monitoring 9 Re-use of animals 10 Removing implanted devices and rehoming or releasing 11 Telemetry studies in the eld or using wild animals 11.1 Surgical facilities at eld research stations 11.2 External attachment in the eld 11.3 Releasing instrumented animals to the wild 12 Writing up projects involving telemetry 13 Keeping up with new developments References Appendix 1: Selected useful information Appendix 2: Score sheet for postoperative monitoring of rats following laparotomy and telemeter placement Preface Whenever animals are used in research, minimizing pain and distress and promoting good welfare must be as important an objective as achieving the experimental results. This is important for humanitarian reasons, for good science, for economic reasons and in order to satisfy broad legal principles such as those stated in the European Convention and Directive on animals used for experimental and other scienti c purposes (Council of Europe 1986, European Community 1986),