Exponential & logistic growt

How populations grow when they have unlimited resources (and how resource limits change that pattern).

Introduction

In theory, any kind of organism could take over the Earth just by reproducing. For instance, imagine that we started with a single pair of male and female rabbits. If these rabbits and their descendants reproduced at top speed ("like bunnies") for $7$77 years, without any deaths, we would have enough rabbits to cover the entire state of Rhode Island$^{1,2,3}$​1,2,3​​start superscript, 1, comma, 2, comma, 3, end superscript. And that's not even so impressive – if we used E. coli bacteria instead, we could start with just one bacterium and have enough bacteria to cover the Earth with a $1$11-foot layer in just $36$3636 hours$^4$​4​​start superscript, 4, end superscript!

As you've probably noticed, there isn't a $1$11-foot layer of bacteria covering the entire Earth (at least, not at my house), nor have bunnies taken possession of Rhode Island. Why, then, don't we see these populations getting as big as they theoretically could? E. coli, rabbits, and all living organisms need specific resources, such as nutrients and suitable environments, in order to survive and reproduce. These resources aren’t unlimited, and a population can only reach a size that match the availability of resources in its local environment.

Population ecologists use a variety of mathematical methods to model population dynamics (how populations change in size and composition over time). Some of these models represent growth without environmental constraints, while others include "ceilings" determined by limited resources. Mathematical models of populations can be used to accurately describe changes occurring in a population and, importantly, to predict future changes.

Finally, ecologists often want to calculate the growth rate of a population at a particular instant in time (over an infinitely small time interval), rather than over a long period. So, we can use differential calculus to represent the “instantaneous” growth rate of the population:

$\frac{\mathrm{The\; equation\; above\; is\; very\; general,\; and\; we\; can\; make\; more\; specific\; forms\; of\; it\; to\; describe\; two\; different\; kinds\; of\; growth\; models:\; exponential\; and\; logistic.}}{}$

• When the per capita rate of increase ($r$rr) takes the same positive value regardless of the population size, then we get exponential growth.
• When the per capita rate of increase ($r$rr) decreases as the population increases towards a maximum limit, then we get logistic growth.

Here's a sneak preview – don't worry if you don't understand all of it yet:

We'll explore exponential growth and logistic growth in more detail below.

Exponential growth

Bacteria grown in the lab provide an excellent example of exponential growth. In exponential growth, the population’s growth rate increases over time, in proportion to the size of the population.

Let’s take a look at how this works. Bacteria reproduce by binary fission (splitting in half), and the time between divisions is about an hour for many bacterial species. To see how this exponential growth,

Image credit: "Environmental limits to population growth: Figure 1," by OpenStax College, Biology, CC BY 4.0.

How do we model the exponential growth of a population? As we mentioned briefly above, we get exponential growth when $r$rr (the per capita rate of increase) for our population is positive and constant. While any positive, constant $r$rr can lead to exponential growth, you will often see exponential growth represented with an $r$rr of $r_{max}$r​max​​r, start subscript, m, a, x, end subscript.

$r_{max}$r​max​​r, start subscript, m, a, x, end subscript is the maximum per capita rate of increase for a particular species under ideal conditions, and it varies from species to species. For instance, bacteria can reproduce much faster than humans, and would have a higher maximum per capita rate of increase. The maximum population growth rate for a species, sometimes called its biotic potential,

Exponential growth is not a very sustainable state of affairs, since it depends on infinite amounts of resources (which tend not to exist in the real world).

Exponential growth may happen for a while, if there are few individuals and many resources. But when the number of individuals gets large enough, resources start to get used up, slowing the growth rate. Eventually, the growth rate will plateau, or level off, making an S-shaped curve. The population size at which it levels off, which represents the maximum population size a particular environment can support, is called the carrying capacity, or $K$KK.

Image credit: "Environmental limits to population growth: Figure 1," by OpenStax College, Biology, CC BY 4.0.

What factors determine carrying capacity?

Basically, any kind of resource important to a species’ survival can act as a limit. For plants, the water, sunlight, nutrients, and the space to grow are some key resources. For animals, important resources include food, water, shelter, and nesting space. Limited quantities of these resources results in competition between members of the same population, or intraspecific competition (intra- = within; -specific = species).

Intraspecific competition for resources may not affect populations that are well below their carrying capacity—resources are plentiful and all individuals can obtain what they need. However, as population size increases, the competition intensifies. In addition, the accumulation of waste products can reduce an environment’s carrying capacity.

Examples of logistic growth

Yeast, a microscopic fungus used to make bread and alcoholic beverages, can produce a classic S-shaped curve when grown in a test tube. In the graph shown below, yeast growth levels off as the population hits the limit of the available nutrients. (If we followed the population for longer, it would likely crash, since the test tube is a closed system – meaning that fuel sources would eventually run out and wastes might reach toxic levels).

     

     

Image credit: "Environmental limits to population growth: Figure 2," by OpenStax College, Biology, CC BY 4.0.

In the real world, there are variations on the “ideal” logistic curve. We can see one example in the graph below, which illustrates population growth in harbor seals in Washington State. In the early part of the 20th century, seals were actively hunted under a government program that viewed them as harmful predators, greatly reducing their numbers$^5$​5​​start superscript, 5, end superscript. Since this program was shut down, seal populations have rebounded in a roughly logistic pattern$^6$​6​​start superscript, 6, end superscript.

Image credit: "Environmental limits to population growth: Figure 2," by OpenStax College, Biology, CC BY 4.0. Data in graph appears to be from Huber and Laake$^5$​5​​start superscript, 5, end superscript, as reported in Skalski et al$^6$​6​​start superscript, 6, end superscript.

A shown in the graph above, population size may bounce around a bit when it gets to carrying capacity, dipping below or jumping above this value. It’s common for real populations to oscillate (bounce back and forth) continually around carrying capacity, rather than forming a perfectly flat line.

Resources : khan academy.2016.(online) (https://www.khanacademy.org/science/biology/ecology/population-growth-and-regulation/a/exponential-logistic-growth), diakses 3 April 2017