in all months, and mean precipitation increased in most months (Fig. 2a). 68Spatial variability in climatic change (Fig. 2b,c), necessitates local matching of phenological 69 and climatic datasets rather than the use of regionally-averaged climate data (e.g. Central 70England Temperatures) or large-scale climatic indicators (e.g. North Atlantic Oscillation). 71We did not make the restrictive assumption that biological events would be related to annual CSP precip varied less among trophic levels than the upper limit (Fig. 3d,f) consumers were less than those for primary consumers (Fig. 5a). This occurred because, 195averaged across species, the opposing climate responses of primary producers and secondary 196consumers are more similar in magnitude than are those for primary consumers (Fig. 3), 197 effectively "cancelling each other out". Our models suggest greater average advances for 198 crustacea, fish and insects than for other groups, such as freshwater phytoplankton, birds and 199 mammals (Fig. 5b). However, response-variation is high for crustacea (Fig. 5b). not estimated for marine plankton data (see above), and so the second-phase LME models 441 were run twice: once to examine correlations with temperature and precipitation for all but 442 the marine plankton phenological series (9,800 series), and once to examine only correlations 443 with temperature for the whole data set (10,003 series).

Atlantic salmon Salmo salar, brown trout Salmo trutta (including the anadromous form, sea trout) and Arctic charr Salvelinus alpinus (including anadromous fish) provide important commercial and sports fisheries in Western Europe. As water temperature increases as a result of climate change, quantitative information on the thermal requirements of these three species is essential so that potential problems can be anticipated by those responsible for the conservation and sustainable management of the fisheries and the maintenance of biodiversity in freshwater ecosystems. Part I compares the temperature limits for survival, feeding and growth. Salmo salar has the highest temperature tolerance, followed by S. trutta and finally S. alpinus. For all three species, the temperature tolerance for alevins is slightly lower than that for parr and smolts, and the eggs have the lowest tolerance; this being the most vulnerable life stage to any temperature increase, especially for eggs of S. alpinus in shallow water. There was little evidence to support local thermal adaptation, except in very cold rivers (mean annual temperature <6·5° C). Part II illustrates the importance of developing predictive models, using data from a long-term study (1967-2000) of a juvenile anadromous S. trutta population. Individual-based models predicted the emergence period for the fry. Mean values over 34 years revealed a large variation in the timing of emergence with c. 2 months between extreme values. The emergence time correlated significantly with the North Atlantic Oscillation Index, indicating that interannual variations in emergence were linked to more general changes in climate. Mean stream temperatures increased significantly in winter and spring at a rate of 0·37° C per decade, but not in summer and autumn, and led to an increase in the mean mass of pre-smolts. A growth model for S. trutta was validated by growth data from the long-term study and predicted growth under possible future conditions. Small increases (<2·5° C) in winter and spring would be beneficial for growth with 1 year-old smolts being more common. Water temperatures would have to increase by c. 4° C in winter and spring, and 3° C in summer and autumn before they had a marked negative effect on trout growth.

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Brown trout of similar length and weight were fed a standard meal which contained a known number of food organisms of the same size-group and taxon (seven taxa were used). The weight of digestible organic matter in a trout stomach decreased exponentially with time. i.e. at a constant relative rate. At a particular water temperature, the food organisms were either evacuated from the stomach at similar rates (Group 1: Gammarus pulex, Baetis rhodani, Chironomidae, Oligochaetes) or at progressively slower rates (Group 2: Protonemura meyeri, Hydropsyche spp., Tenebrio molitor). Rates of gastric evacuation were not significantly different for food organisms of different size groups of the same taxon, or for different sized meals, or for different sizes of trout (range 20-30 cm), or for mixed and multiple meals (three meals over 16 h). Times are given for the gastric evacuation of 50%, 75%, 90% and 99% of the digestible organic matter in a meal.Starvation periods of 1, 2, 3,4 and 5 days prior to feeding did not affect evacuation rates. The rates were slightly, but not significantly, slower for starvation periods of 6 and 7 days, and were often significantly slower for starvation periods of 10, 15 and 20 days.Evacuation rates increased exponentially with increasing water temperature. It was possible to estimate both the rate and time for the gastric evacuation of different meals at water temperatures between 3-8''C and 19'1°C.

1. The chief objective was to develop a functional model for the growth of parr (0+, 1+) of Atlantic Salmon, Salmo salar, from two populations (Rivers Leven and Lune in northwest England), using a model similar to that developed previously for Brown Trout, Salmo trutta. Parr bred from Leven parents were acclimatized to nine fairly constant temperatures (two 0+, two 1+ parr per temperature) in the range 3·8–21·7 °C (variation ± 0·3 at 3·8 °C to ± 1·0 at 21·7 °C). Each fish was kept in a separate tank and fed to satiation on shrimps. The mass and length of each fish was recorded at the start and finish of a growth period of 30 days. Parr (0+, 1+) bred from Lune parents were separated into slow and fast growers, and acclimatized to six very constant temperatures. There were three slow and three fast growers at each of 5·0, 10·0, 15·0 °C for 0+ parr and each of 5·0, 10·0, 13·0, 15·0, 18·0, 20·0 °C for 1+ parr. Procedures were the same as for Leven parr except that the growth period lasted 30 days for the 18 0+ parr and 42 days for the 36 1+ parr. 2. The growth model was an excellent fit (P < 0·001) with no significant differences between parr from the two rivers, fast‐growing parr of different ages (0+, 1+), or fast‐ and slow‐growing 1+ parr. The optimum temperature for the combined data (81 parr) was 15·9 °C with a range for growth of 6·0–22·5 °C. The model failed to fit the data for slow‐growing 0+ Lune parr in experiments from November to February. Growth was reduced in these fish, even though the temperatures were suitable for growth (10, 15°C). 3. The model described approximately the growth of three year‐classes of Atlantic Salmon parr in the River Eden in northwest England. Some of the discrepancies between actual masses and those predicted from the model were consistent and possible reasons for this are discussed.

The distances travelled by drifting invertebrates of 18 taxa were investigated at sites 3 and 4 in the Wilfin Beck, a small stony stream in the English Lake District. Fifty invertebrates of the same taxon were released into the stream at increasing distances upstream from a large net which caught all invertebrates drifting downstream.The relationship between the catch in the net (Y ) and the distance from the release point to the net (X m) was well described by the regression equation:[Formula: see text] whereR is the constant relative rate of return of invertebrates to the bottom of the stream, andA=Y=number of invertebrates released at each point=50. Values ofR, the mean drift distance ([Formula: see text] m), and the distance (X m) travelled byP% (1%, 10%, 50%) of the drifting invertebrates were calculated for each taxon at different modal water velocities. Values ofR,[Formula: see text] andX were fairly constant for each taxon at a particular modal water velocity, and were not significantly affected by the source of the experimental animals (benthos or drift), by changes in illumination (daylight or darkness), or by seasonal changes, including water temperature.The experimental taxa at site 4 were divided into the following three groups according to their ability to return to the bottom: 1. Polycelis felina, Ancylus fluviatilis, Chironomidae, Eliminthidae, andAmphinemura sulcicollis. Values ofR,[Formula: see text],X not significantly different from those obtained for dead invertebrates, which were removed from the drift by chance effects. 2. Protonemura meyeri, Leuctra spp.,Chloroperla spp.,Rhithrogena semicolorata, Simulium spp. Values ofR,[Formula: see text],X not significantly different from those obtained for dead invertebrates at modal water velocities ≧19 cm/sec. At low velocities (10-12 cm/sec),R was significantly greater and[Formula: see text],X significantly smaller than values obtained for dead invertebrates. 3. Erpobdella octoculata, Gammarus pulex, Hydropsyche spp.,Ecdyonurus venosus, Ephemerella ignita, Baëtis rhodani. Values ofR,[Formula: see text],X significantly different (R greater,[Formula: see text] andX smaller) from those obtained for dead invertebrates. The exponential law was not a good model for experiments with cased caddis larvae (Agapetus fuscipes and a mixed group ofSericostoma personatum, Drusus annulatus, Potamophylax cingulatus). Larvae sank rapidly after release and drifted over very short distances.Values ofR for each taxon were significantly higher at site 3 than at site 4, and the more rapid return at site 3 was presumably due to dense stands of aquatic macrophytes. The increase inR was greatest forSimulium spp. andE. ignita.The relationship between[Formula: see text] and modal water velocity (V cm/sec) was well described by the regression equation:[Formula: see text] wherea andb are constants. The relationship betweenR andV, orX andV, was described by similar equations. Values ofa andb were calculated for each taxon at sites 3 and 4.The drift distance was also investigated ...

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SUMMARY. 1. The chief objective was to construct a thermal tolerance polygon for juvenile Atlantic salmon, Salmo salar L., using fish from four groups and two populations: two age groups from one population (0+, 1+ parr from River Leven), two size groups from the other population (slow and Fast growing 1+ parr from River Lune). 2. Fish were acclimated to constant temperatures of 5, 10, 15, 20, 25 and 27°C; then the temperature was raised or lowered at 1°C h−1 to determine the upper and lower limits for feeding and survival over 10 min, 100 min, 1000 min and 7 days. As they were not significantly different between the four groups of fish, values at each acclimation temperature were pooled to provide arithmetic means (with SE) for the thermal tolerance polygon. 3. Incipient lethal levels (survival over 7 days) defined a tolerance zone within which salmon lived for a considerable time; upper mean incipient values increased with increasing acclimation temperature to reach a maximum of 27.8±0.2°C, lower mean incipient values were below 0°C and were therefore undetermined at acclimation temperatures <20°C but increased at higher acclimation temperatures to 2.2±0.4°C. Resistance to thermal stress outside the tolerance zone was a function of time; the ultimate lethal level (survival for 10 min) increased with acclimation temperature to a maximum of 33°C whilst the minimum value remained close to 0°C. Temperature limits for feeding increased slightly with acclimation temperature to upper and lower mean values of 22.5±0.3°C and 7.0±0.3°C. 4. In spite of different methodologies, values in the present investigation are similar to those obtained in previous, less comprehensive studies in the laboratory. They also agree with field observations on the temperature limits for feeding and survival. Thermal tolerance polygons are now available for eight species of salmonids and show that the highest temperature limits for feeding and survival are those recorded for juvenile Atlantic salmon.