Part 2

A roller coasting history of forest game densities in Sweden

When modern clear-cutting forestry became common practice, the extent of forest openings increased dramatically. These openings of recently cleared land regenerated abundant and easily accessible forage for the native game species. Once the forest canopy was removed, latent seed banks of woody and herbaceous plants germinated and formed a new generation of typical forest vegetation. After a few vegetation seasons (2 to 4 years), the clearings developed into extensive browsing habitats relative to prevailing densities of moose, roe deer and mountain hare during the early 1960s.

The history of culling statistics is telling

The footprints of harvest densities of moose, roe deer, and mountain hare provide insights into the importance of forage availability. Figure 2.1 shows the harvest density history for these species. They have coexisted for centuries as browsers, preferring a mixture of herbaceous and woody plants as a source of nutrition.

The roe deer is a fussy mixed forager. It is adapted to nutrient-rich, easily digestible, and tender plants low in structural fiber, such as forbs, buds, young leaves, and shoots of shrubs and trees with low lignin content. It typically avoids coarse grasses and fibrous vegetation because these foods provide insufficient nutritional return relative to its digestive capacity.

The moose, in contrast, is adapted to exploit woody vegetation with higher structural fiber content. Its diet consists primarily of twigs, shoots, and bark from deciduous trees such as willow, birch, rowan, oak, sallow, and aspen, along with the current year’s growth of shrubs and conifers. During the vegetation season, it also consumes aquatic plants and herbaceous vegetation where available. Nevertheless, it still selects relatively digestible plant parts such as young shoots and leaves, and avoids heavily woody stems whenever possible. Because of its body size and energetic requirements, moose must consume large quantities of forage, making the species particularly dependent on landscapes that provide abundant browse within reach of its feeding height. Typically, the moose forage three times over 24 hours and consequently has three bouts ruminating.

The mountain hare has a digestive system adapted to a wide range of plant materials, including relatively fibrous vegetation. During the vegetation season, it feeds primarily on grasses, sedges, and a variety of herbaceous plants, often selecting young shoots and leaves with higher nutrient content. In winter, the mountain hare shifts its diet toward woody plants, browsing twigs, bark, and buds of shrubs and small trees such as heather, willow, birch, and rowan. This strategy allows the mountain hare to survive on relatively low-quality forage, although it still benefits from habitats where young, nutrient-rich vegetation is available.

There are a couple of things worth bringing up about the harvest-density footprints presented in Figure 2.1. First up is the astonishing population expansion of roe deer, peaking in 1993 with 382,000 harvested animals, followed by a conspicuously steep decline. It almost makes the moose explosion, peaking at 174,400 harvested animals in 1982, seem modest in comparison. The mountain hare entered the timeline with decent harvest densities and had an early peak in the mid-1940s, later reaching a maximum of 196,730 harvested individuals in 1987. Moose never reached their carrying capacity because management decisions reduced population sizes to prevent browsing damage on Scots pine seedlings.

As already mentioned in part 1, moose and roe deer populations began the timeline at extremely low harvest densities, caused by too high culling rates and predation. This was likely the main reason why the mountain hare initially fared better, benefiting from relaxed interspecific competition over forage resources. This indicates that moose and roe deer densities were far below the carrying capacities typical of selection-cut forests. Add to this the stochastic effects of low population size. To escape such random effects, a moose restoration plan, launched by Svenska Jägareförbundet, became the first real wildlife management effort. After a couple of years, both roe deer and moose left the trap of random effects. Their populations became statistically more predictable as densities slowly increased. At the same time, the mountain hare entered an asymptotic decline that lasted until 1979, suggesting intensified competition over shared forage, followed by a rapid increase that peaked in 1987. After reaching this historical high in harvest density, the mountain hare began its odyssey toward near obliteration.

Memorize the order in which the native forest game entered logistic growth: moose in 1966, mountain hare in 1979, and roe deer in 1985 (Fig. 2.1). Take some time to think about possible ecological reasons behind the observed time lags before each species entered its logistic phase.

A more careful inspection of the density traces suggests differences in ruggedness among the three native browsers. What causes these short-term oscillations, and why do they seem to differ among species? Let us take a closer look at the harvest-density footprints, species by species (Fig. 2.2). What about the oscillation frequencies? What about the amplitudes of the oscillations?

Let us start with possible effects of management actions. Moose have been, and still is, by tradition the main focus in Sweden, exposed to management actions ranging from early efforts to increase population size, to reducing forestry damage in the 1980s, and to the introduction of adaptive moose management in the early 1990s. Typically, this has aimed at maintaining sustainable population sizes, balancing the interests of the hunting community with acceptable levels of forestry damage. This has led to a trade-off between maximizing harvests and limiting browsing damage.

If you are uncertain about the terminology used in population biology, we recommend reading this short thesaurus before moving on to Figure 2.3. Population density is the number of animals inhabiting a given area. By knowing the size of the area, population density is simply the number of animals divided by area size. These values are usually standardized to numbers per 1,000 hectares, which corresponds to 10 km².

Growth rate is denoted as r, which in practice describes how fast a population increases. Carrying capacity is a central concept in population biology and is usually denoted by K. In this context, carrying capacity only refers to the amount of available forage. When a population matches K, it is in equilibrium, with no growth or decline. When a population is at K/2, its reproductive capacity is at its maximum—meaning the population grows at its highest rate, with forage resources effectively not limiting growth.

The concept in Figure 2.3 illustrates the principle behind adaptive management. The relationship between population size and growth rate is key. The curve shows that growth accelerates as the population approaches an optimal size, where cows reach their maximum reproductive capacity. The peak of the curve (K/2) marks the population size at which the growth rate is maximized. Any growth above this optimal population size is regarded as a surplus that can be harvested, highlighted by the red segment on the curve. By harvesting this surplus, managers relocate the population to a size where reproductive capacity is at full potential.

When a population exceeds this optimum, the growth rate gradually slows as population density increases and competition for available forage intensifies. This is a crucial point in population biology: a population in equilibrium with the carrying capacity (K) will not change in numbers from one season to the next. In practice, K is never a fixed number. It is merely a constant developed by theoretical biologists to describe forage availability and population growth. In reality, carrying capacity is never constant. The quality of the vegetation season changes from one year to the next, often unpredictably. If forage vegetation does not recover between vegetation seasons, the population may enter a state of misery, in which numbers begin to decline. This situation will persist until the population once again matches the actual carrying capacity.

In practice, the aim of adaptive moose management is to keep the population at a level where the growth rate (r) is maximized. To achieve this, managers must harvest the annual population surplus each hunting season, effectively pushing the population back to the size at which growth peaks. At this level, only half of the carrying capacity is utilized—meaning that browsing damage is also reduced by half (Fig. 2.3). Abracadabra—we have a win–win. A brilliant objective, yet extremely difficult and costly to achieve in practice. For adaptive management to function properly, it must rely on dependable population surveys, accurate sex ratios, precise age structures, and knowledge of mortality from other sources such as predation, vehicle collisions, and disease. Based on such data, it is possible to calculate the number of animals that need to be culled to maintain maximum growth.

Everyone involved in wildlife management knows that this is theoretically possible, but in practice it remains a wishful utopia. No management unit can afford the cost in money or the time required. Lastly—and this is crucial—the carrying capacity must also be known, which is perhaps the most difficult part of all.

Now, go back to Figure 2.2 and take another look at the harvest-density footprints of moose, and compare them with the more rugged patterns of mountain hare and roe deer. These are not as smooth as the moose trajectory. The short-term ups and downs differ between the three species. At first glance, one might dismiss these oscillations as poor estimates or random noise in the harvest data. But before jumping to that conclusion, it is worth asking whether something else could be cause these fluctuations.

Summary

• Initially, modern forestry practices boosted the abundance of native game species by providing rich and diverse foraging opportunities in first-generation clearings (e.g. through seed banks reflecting the vegetation diversity present before the establishment of even-aged monoculture stands). The first species to respond to the increased carrying capacity was the moose, followed by mountain hare and roe deer.

• Roe deer, moose, and mountain hare all prefer nutrient-rich, young plant parts when available. Roe deer are the most selective, focusing on highly digestible forage and avoiding fibrous material. Moose rely mainly on woody browse and consume large volumes, though still favoring less fibrous growth. Mountain hare are the most flexible, shifting seasonally and tolerating lower-quality, more fibrous diets.

• Moose, mountain hare, and roe deer entered logistic growth at different times (1966, 1979, and 1985), suggesting species-specific delays likely caused by ecological factors. Their population trajectories also differ in short-term fluctuations, indicating responsiveness to environmental conditions.

• Adaptive management intentions emerged in the mid 1990s, aiming to keep moose populations at maximum productivity. However, as seen in Part 1 with declining reproduction and body mass, this did not result in stable populations at high harvest levels. While theoretically attractive, the approach was fundamentally limited by the lack of reliable estimates of actual carrying capacity.