Population dynamics is the name for the discipline that studies how populations of living beings vary through time. Why is this relevant when assessing how nonhuman animals fare in nature? It’s because death is often, if not in most cases, linked to terrible experiences (such as fear or anxiety) and is often very painful. Population dynamics can tell us how many animals on average die in comparison to how many survive. In addition, it can tell us at which points of their lives animals’ deaths occur. The information we can collect regarding their deaths can be very useful and illuminating to the question of whether nonhuman animals in nature live good lives or not.
To address this problem we can start by considering how populations vary. They can change in different ways. For instance, new individuals from other groups can join the population we are examining or existing group members can leave it. Apart from this there are basically two very obvious ways in which populations change: when members die and when new members come into existence. For a population to be stable through time the number of deaths must be matched by the number of births. This means that those animals who have few offspring are those among whom mortality is relatively low, in particular at the beginning of their lives, before they reproduce for the first time. Unfortunately, though, most animals aren’t so lucky to be in these groups of animals. Most animals have, in fact, huge numbers of offspring. Why is this? It is because their offspring die in massive numbers, especially just after they come into existence.
There are some animals in nature who reproduce by following a strategy which consists of having very few descendants who are well taken care of. These animals may give birth to just one animal or lay just one egg each time; however the survival rate of these new animals is very high so the animal population is able to maintain its numbers.
Unfortunately, there are very few species of animals who follow this reproductive strategy. Some mammals such as great apes, cetaceans (whales, dolphins, and porpoises), bears, elephants and other herbivores, and some birds such as albatrosses are strategists of this kind. However, the overwhelming majority of animals follow a different strategy which consists of having as many descendants as possible. The cost of this is that the offspring receive little or no support at all from their parents. (These two strategies have been traditionally referred to as K-selection and r-selection, although today these terms are not used that much. The reason for this terminology of K-selection and r-selection is that in the common equations used to estimate how populations vary through time, the variable referring to the number of offspring is usually named “r,” while the variable that refers to the carrying capacity of the environment in which the population exists, that is, the one referring to how many individuals can survive, is usually named “K”.1)
If these animals had a high survival rate, such as the one enjoyed by those who just have one or a few offspring, their populations would be multiplied by millions in a matter of years. But on average only one new animal per parent survives. The rest of the animals die shortly after coming into existence.
The predominance of the strategy consisting in having large offspring has important consequences for the suffering of animals. There are strong reasons to believe that these animals experience much more suffering than wellbeing in their lives. Although many of them may not have painful deaths, many others suffer terribly when they die, such as from being eaten alive or starving to death. In addition, we must consider the fact that these animals often die when they are very young. This means that they do not have enough time to have any significant positive experiences in their lives, as in fact they may have just a few experiences in addition to the terrible experience of dying.
Since most animals who come into existence have very large numbers of offspring, the overwhelming majority of animals who are ever born experience pain and misery that is more significant than the good experiences, if any, they may enjoy. Consequently, we must conclude that, horrible as it is, suffering appears to prevail overwhelmingly over happiness in nature. We can now see why the amount of suffering in nature depends very much on population dynamics.
This doesn’t mean that there aren’t any other reasons why animals suffer in nature. An animal can survive to reach maturity and yet suffer terribly due to factors such as diseases, malnutrition and thirst, weather conditions, parasitism and predation, injuries, or psychological stress. This makes the prospects even gloomier for animals in the wild. However, even if none of these things happened to adult animals, it would still be the case that there is more suffering than happiness in nature due to the massive number of animals dying because of the prevalent reproductive strategy and the pain that accompanies these deaths.
What we have discussed so far may give the impression that happiness is prevalent for the animals who just have one offspring every time they reproduce. However, we should not assume that; despite high survival rates, there are still many animals who die before reaching maturity. Note that, even if these animals give birth to only one offspring each time, they often give birth to several different animals during their lifetime. But remember that on average only one new animal per parent survives. Although many people think that in nature the animals that die are mainly the old ones, things are, in fact, the other way around.
This can be easily confirmed if we consider some more empirical data. It’s often said that only old and sick animals die in the wild, while young and healthy animals have happy lives, and that the death of old and sick animals relieves them of pain and distress due to diseases. However, the evidence available suggests this is not the case. Here are some examples that show that young animals are more likely to die than older ones.
In the central Superior National Forest in Minnesota, 209 white-tailed deers were radiotracked from 1973 through the winter of 1983-1984; 85 deaths were recorded (this is worth noting in itself; well over a third of the deers died).
The annual survival rate for deers under 1 year old was 0.31, for females between 1 and 2 years old it was 0.80, for males between 1 and 2 years old it was 0.41, for females older than 2 years it was 0.79, and for males over 2 years it was 0.47.2 So, for males and females both, the deers in this study who were most likely to die were the youngest deers, those under 1 year old.
Another study analysed 439 Isle Royale moose deaths between 1950 and 1969. Calf deaths accounted for 29.3% of all deaths by wolf predation (45% of total deaths).3
Another study documents the huge number of deaths that occur during the winter when the population density of Soay sheep rises above 2.2 per hectare and as a result, the population density falls by about 65%. More than 90% of lambs and 70% of yearlings die under these conditions, compared with 50% of adults. While there may be more adults than lambs and yearlings, it is clearly not true that animals in the wild are generally old and sick when they die.4
This has also been noticed with birds. One study found that the death rate of yellow-eyed juncos is highest in their first year.5
We may think that a handful of studies cannot come anywhere near to giving us a good picture of life in the wild. However, the inclusion of these studies is not intended as the evidence that a problem exists. The studies simply illustrate the points above regarding why suffering is so prevalent in nature. Its prevalence is a result of the maximization of the number of sentient animals coming into existence. This is what we can base our analysis of the problem on, with case studies serving only to exemplify the problem.
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1 In a simple form, the equation can be put thus: dN/dt=rN (1- N/K), where N stands for the initial number of individuals of the population and t stands for the time at which we measure how the population varies. Verhulst, P.-F. (1838) “Notice sur la loi que la population poursuit dans son accroissement”, Correspondance Mathématique et Physique, 10, pp. 113-121.
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