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Understanding small rodent population cycles requires knowledge about what initiates the population decline and what other factors are involved in driving the population to extreme lows. During winter severe subnivean conditions prevent photosynthetic activity (Tieszen 1974; Kappen 1993; Hamerlynck & Smith 1994) and plant growth (Eurola, Kyllönen & Laine 1984), and small rodents most probably have a fixed amount of low-quality food available throughout the winter (Hanski et al. 1993). The lack of food resource replenishment necessarily makes winter carrying capacity lower than in summer. Therefore, a healthy small rodent population might thrive and increase in an area during summer but the lower winter carrying capacity cannot support the same population size during the following winter, and a decline is the result. Such a decline would result in a higher predator–prey ratio in spring, a situation that would drive the population down further (Pearson 1966; Fitzgerald 1977; Goszczynski 1977; Korpimäki, Norrdahl & Rinta-Jaskari 1991; Hanski & Korpimäki 1995). The limited amount of food resources during winter should make the overwinter survival dependent on food availability.
In winter the temperature gradient within a snow cover, between the cold surface air and the relatively warmer ground, causes water vapour to migrate upwards (Pruitt 1984; Marchand 1996). This process results in the formation of a stratum of fragile and loosely arranged snow crystals at the base of the snow cover called the subnivean space. In winter small rodents spend most of their time here, where they can find refuge from the harsh elements and most predators, and gain access to food (Fuller 1967; Pruitt 1984). The nature of the stratum facilitates movement and exploration of new areas for feeding (Marchand 1996), but the subnivean space is probably not continuous. In the 1960s and 1970s E. Østbye and colleagues measured snow conditions in alpine Norway every winter with a special focus on the subnivean space. They found that it was not a uniform habitat but was broken into accessible and inaccessible patches by ice covering the ground (Østbye personal communication). The presence of ice might reduce the amount of plant biomass available to small rodents (Hanski et al. 1993), and ultimately reduce carrying capacity to extremely low levels. The ice may also be responsible for the razor sharp boundaries between ungrazed and winter-grazed vegetation patches observed after snow melt (personal observation). Models have shown that inclusion of seasonal change in carrying capacity greatly enhances the ability to mimic cyclic population dynamics in voles (Hanski et al. 1993; Hanski & Korpimäki 1995) and time-series analysis has further shown that density-dependent regulation of population growth during winter appears to be important to produce multi-annual cycles (Hansen, Stenseth & Henttonen 1999). Therefore, ice may well explain the existence of ungrazed patches, and it will reduce the winter carrying capacity to even lower levels than those dictated by just the lack of plant growth.
Studies show that natural populations of voles can experience shortage of food during the winter in peak years (Hansson 2002) and in experiments vole populations under predator-free conditions crash due to overgrazing (Krebs, Keller & Tamarin 1969; Krebs et al. 1973; Klemola et al. 2000; Klemola, Norrdahl & Korpimäki 2000). Another experiment using food supplementation during winter has shown that winter food supply limits vole population growth and winter survival in the absence of predation (Huitu et al. 2003). These results, however, do not distinguish between population densities being reduced by initial food shortage caused by summer and autumn overgrazing (Bergeron & Jodoin 1995), and the carrying capacity being reduced by snow cover limiting access to otherwise abundant food resources.
For arvicoline rodents (voles and lemmings) there exists several biogeographical gradients in amplitude and degree of cyclicity: Fennoscandia (Henttonen, McGuire & Hansson 1985; Hanski et al. 1993; Bjørnstad, Falck & Stenseth 1995), Hokkaido, Japan (Bjørnstad et al. 1996; Stenseth, Bjørnstad & Falck 1996; Stenseth, Bjørnstad & Saitoh 1996; Saitoh, Stenseth & Bjørnstad 1998) and central Europe (Tkadlec & Stenseth 2001), and these gradients seem to follow a seasonality gradient (Tkadlec & Stenseth 2001). Within the Fennoscandian gradient, cycles is found primarily north of 60° N (Hansson 1971; Hansson & Henttonen 1985, 1988; Turchin 1993; Bjørnstad et al. 1995), and this has been explained by the long-lasting snow cover protecting small rodents from generalist predators, thus facilitating overwinter survival (Erlinge et al. 1983, 1984; Hansson & Henttonen 1985; Lindström & Hörnfeldt 1994; Hansson 2002). However, the snow will, most probably, also reduce the food access, and such strengthening of density dependence can also destabilize the dynamics (Hassell 1975; Hassell, Lawton & May 1976; May 1979).
The aim of this study was to assess experimentally how winter food availability and vole survival is affected by the extent of the subnivean space. We hypothesized that the properties of the snow cover reduces winter food availability and that the amount of available subnivean space limits vole space use and thus overwinter survival. Such factors limiting survival might also limit body mass growth. To test for this we ran a replicated field experiment where we increased artificially the amount of subnivean space by placing a network of corrugated aluminium sheets on the ground prior to the onset of winter. Our predictions were that the increased subnivean space would lead to higher individual space use together with increased grazing, a consequent increase in small rodent winter survival and a positive effect on body mass.
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Our objective was to assess whether the snow cover limits the access to subnivean food by physically enclosing patches of vegetation resources and if this reduces winter survival. By adding a network of corrugated aluminium sheets on the ground before onset of winter we obtained a way to counteract this possible detrimental effect. We expected that the corrugated profile of the sheets would create space mimicking the natural occurring subnivean space, thus giving the root voles access to more natural forage. The results support our hypotheses regarding survival and space use as animals living within the treatment grids survived better, had higher space use and grazed larger areas. The larger areas grazed underneath the sheets and the higher space use indicates that the physical properties of the snow cover limits access within the subnivean environment. The hypothesis regarding limitations in body mass change could not be tested due to few data points.
It can be argued that the size of the trapping grids was small compared to the distances root voles are known to move during summer (Steen 1994). However, we found it necessary to ensure high enough recapture probabilities and this was only possible by minimizing the distance between trap stations, thus limiting grid size. Increasing the grid size would also reduce comparability owing to the highly variable vegetation and topography. From the 103 animals introduced in January we documented that more than 70% never left the grid, and this indicates that the animals stayed mainly in the area, even though the grids were not fenced to stop migration. Therefore, we believe that the grid size chosen was reasonable.
The animals whose tags were not recovered either died within the grid without this being recorded, or they managed to leave. Any migrations were probably motivated by food limitation, and migrating animals probably had higher mortality, as observed among dispersers during summer (Steen 1994) Thus any difference in emigration between treatments might have effected the results of the survival analysis, as all animals not recovered were included in the analysis. However, there was no significant difference in proportion of tags not recovered between treatment and control grids (LRT: χ2 = 2·12, d.f. = 1, P < 0·15). Predation on possible migrating animals might have affected the general level of estimated survival but not the difference between treatments. Therefore, including non-recovered animals in the analysis should not affect our main conclusions.
To introduce animals into the subnivean space might seem an unnatural situation. The quality of the subnivean environment is probably enhanced by resident animals maintaining runways as the snow cover is forming, and animals introduced through a stable snow cover in January might be exposed to a subnivean environment of poorer quality. However, basing the experiment on naturally occurring animals would be too risky. We wanted to stress food limitation similar to ‘peak years’, and the population density in the area was obviously too low to provide high enough and equal densities of natural occurring animals in all grids (Fig. 1). To introduce animals earlier was not found suitable either. In an experiment, in which field voles (M. agrestis Linnaeus) were transplanted between open systems in the absence of snow, only about a third of the introduced animals was ever recaptured (Ergon, Lambin & Stenseth 2001). This loss of animals was due probably both to mortality and emigration. We believe an introduction of animals before onset of winter would be almost useless due to the surroundings acting as a sink, and we deliberately chose to study a non-enclosed system to avoid unnatural snowdrifts forming around fences. Introduction into the subnivean obviously involved moving around on the top of the snow cover, and initiating this process before the snow cover was stable enough to carry a man wearing snow shoes would probably do more harm to the subnivean space (Schmid 1981) than would the lack of resident animals. The low rate of movement within the control grids (Fig. 4) might be a direct effect of unmaintained subnivean environment, but even with seven naturally occurring animals living within one control grid and none within the other (Fig. 1), no significant difference in space use between these two grids was detected (2·03 ± 0·25 and 1·33 ± 0·66 for grid 1 and grid 3, respectively). As far as we know there exists no information indicating whether this observed rate of movement under the snow cover is unnaturally low or is actually representative for the overwinter situation experienced by small rodents in alpine habitats.
The survival modelling revealed that monthly winter survival of M. oeconomus was limited by the subnivean fragmentation. Animals from the treatment grids had monthly survival probabilities two times higher than control animals during the 2 first months after introduction (Fig. 2). Natural mortality during these 2 months, in addition to loss due to predation, reduced the population sizes of the first introduction cohort to one to three animals in each grid. These population densities seemed well below carrying capacity at treatment as well as control grids because these few animals remained alive for the rest of the winter, and a further introduction of a second cohort did not appear to reduce their survival. These densities were also well below the highest densities of naturally occurring animals observed by trapping prior to the experiment.
While the survival probabilities of the established animals from introduction cohort 1 were stable at 100%, survival of the animals from the second cohort varied with time. The first period of low survival, during the first half of May (Fig. 2), can be explained possibly by extreme subnivean conditions. Large amounts of water were observed in the subnivean space at this time (up to a third of the trap chimneys in the grids were flooded) and it is likely that the presence of water reduced survival indirectly by reducing the amount of available subnivean space and possibly also directly by drowning of animals. Aars & Ims (2002) found a negative correlation between winter survival rates and mean winter temperature, a relationship they ascribed to melting and freezing of vole habitats. Other studies have also suggested similar phenomena effecting vole survival (Merritt & Merritt 1978; Boonstra & Rodd 1983). The proportion of the subnivean space that is inaccessible due to water is likely to vary between years due to climatic variation, but periods of such low survival, especially as low as in the control populations, even if temporary, would greatly reduce the probability of an individual surviving the whole winter by acting as a temporal bottleneck.
The second drop in survival, during the first half of June (Fig. 2), coincides with snow melt. The disappearance of snow is likely to be associated with the onset of dispersal (Boonstra & Rodd 1983), a situation that would be interpreted as a decrease in survival as we cannot account for permanent emigration. In addition, due to more available space individuals would, by pure chance, be less likely to pass through the antennas. Such a reduction in capture probability would result in reduced survival estimates in models already constraining capture probability as constant. Another possibility explaining the sudden drop in survival could be increased predation due to the lack of protecting snow and the return of migratory birds of prey.
The higher survival probability of animals living within treatment grids should entail higher population densities here compared to the control grids. This, however, was not the case (Fig. 1). The population densities were not significantly different, and this seems to be due to a higher predation pressure within the treatment grids counteracting the effect of higher survival. In the survival analysis, mortality due to predation was censored out and thus the population densities at the treatment grids were lower than what the survival estimates should dictate. Predation was the main reason to introduce a second cohort of animals in April (Steen & Korslund, in preparation).
The majority of small mammals experience weight loss during winter (Iverson & Turner 1974; Hansson 1990; Hansson 1991; Aars & Ims 2002), and our observations support these findings. An optimal intermediate size (26·3 and 33·8 g for females and males, respectively; Fig. 5) is apparent from the negative correlation between weight at introduction and weight change. However, in males the negative correlation was caused by extreme weight loss of one large male (−22 g), while all other males increased in body mass. Removing this outlier would result in negligible negative effects of large body mass among males. This is supported by the male survival function (Fig. 3), which indicates no effect of size on survival. On the other hand, we cannot exclude the possibility that this large male displayed a true survival trade-off between body mass at introduction and body mass change, as such large males do occur in the population at the onset of winter. One could expect a negative correlation between change in body mass and initial body mass due to the variation in body mass (Blomquist 1977), producing a spurious effect. However, the variation seems constant and the regression is based equally on positive and negative weight changes on opposite sides of the intermediate values. The results also confirm earlier findings (Aars & Ims 2002), and hence we find the observed relationship between body mass at introduction and change in body mass to be credible.
Survival was correlated positively with introduction body mass among females but constant among males (Fig. 3). The positive effect among females seems to contradict earlier results on M. oeconomus presented by Aars & Ims (2002), in which, in both sexes, individuals of intermediate sizes had the highest survival probabilities. However, the negative effect of size in that experiment was caused mainly by low survival of post-reproductive individuals (Aars & Ims 2002), whereas we used only non-reproductive animals. None the less, our heaviest females were considerably larger than the optimal size (25 g) determined by Aars & Ims (2002), apparently without experiencing any detrimental effect on survival. Perhaps winter survival is not only a function of size but also of reproductive history, where non-reproductive individuals have an initially higher probability of survival. The weight loss in winter is believed to be due partly to it being hard to sustain the required energy intake (Iverson & Turner 1974; Stenseth 1978; Hansson 1990; Hansson 1992), and this contradicts the high survival of heavy females we observed. However, if both small and large individuals must adjust their size to survive, both extremes must undergo a critical phase of adjustment. It is possible that the cost of weight adjustment is higher for small individuals than for large ones and that this cost compromises survival.
We expected two related effects of grazing due to our treatment: a direct effect underneath the sheets and a more widespread effect resulting in higher grazing on the whole grid. The direct effect of artificial subnivean space was obvious. Under the sheets the level of grazing was higher than on any other parts of the grids, both treatment and control. Within the treatment grids the difference was more than fourfold between covered and uncovered areas and the difference between covered areas on the treatment grids and the equivalent areas on the control grid was twofold. This suggests that the sheets prevented the snow from blocking access to otherwise inaccessible vegetation. As expected, there was no significant difference within the control grids, but the overall grazing here was higher than expected and thus the overall effect on grazing was not significant between treatments. This is mainly an effect of heavy grazing on grid 3 (0·39 ± 0·05, compared to 0·11 ± 0·03 on the other control grid). Here the terrain was more rugged and this seems to increase the possibility of movement and hence grazing in the consequent depressions (personal observation). The relatively high number of animals living within this grid prior to January (Fig. 1) has probably also contributed to increase the grazing, and we cannot guarantee that one or several animals managed to escape the removal and thus contributed to the grazing. However, no such untagged animals were live-trapped after the introduction.
Prior to the introduction there were animals living on one of the treatment grids as well (Fig. 1). These animals most probably had the same effect on the existing vegetation as on grid 3. Here, however, the space use of animals, and thus the grazing, might have been concentrated underneath the sheets, especially early in winter when such sheets may act as a refuge, and this may have contributed to the large difference within the grid. However, the same relative within-grid pattern of grazing was also seen on the other treatment grid and here no pre-experimental animals were detected.
Models including a reduction in carrying capacity in winter can mimic cyclic population dynamics in voles more effectively (Hanski et al. 1993; Hanski & Korpimäki 1995), and density-dependent regulation of population growth during winter appears to be an important element in production of multi-annual cycles (Hansen et al. 1999). Our study suggests that the reduced carrying capacity during winter is caused by the physical properties of the snow cover and the consequent fragmentation of the subnivean space. This is additional to an already reduced food quality due to the lack of vegetation replenishment during winter. Because the process creating the subnivean space is highly dependent on climatic factors, such as temperature (Pruitt 1984; Marchand 1996), winter climate may have a considerable effect on the population dynamics of small rodents. Long-term changes in climate may lead to a permanent aggravation of the subnivean conditions and lead most probably to a further decrease of winter carrying capacity. Erlinge et al. (1983, 1984) has shown how high winter predation can outweigh the summer production of vole populations. We expect that more severe subnivean conditions will lead to higher winter mortality, and this might have an effect similar to winter predation, resulting in a stabilization of population dynamics and a dampening of vole cyclisity.