Answer:
the maximum population size that a particular environment can support.
Explanation:
A population can be defined as the total number of living organisms living together in a particular place and sharing certain characteristics in common.
Generally, these populations may be divided into a fraction of the population (subpopulation) based on certain factors and reasons.
Population regulation can be defined as a biological process that balances limiting factors affecting the growth of a population based on density. The factors that regulate the growth of a population are divided into two (2) main categories and these includes;
I. Density-independent factors.
II. Density-dependent factors.
Density-dependent are regulating factors such as predation, diseases, and competition that affect the size of the population of living organisms through decreasing or increasing mortality and birth rate.
Furthermore, density-independent factors do not have an increasingly greater effect as a population's density increases. Thus, its effect are reduced as a population's density increases in size.
Carrying capacity is the maximum population size that a particular environment can support. The carrying capacity of an environment is denoted by the letter k.
Answer:
It's the leaf, or it is called chloroplasts.
Explanation:
To know what happens here, you need to analyze the alleles.
If the father is color blind and the daughter is not, you can suppose that is a recessive allele.
You can tell she is a carrier only, and because we received one sexual allele from each parent. If they ask you about the gender, we can suppose a cross between Xx and XY being lower x the recessive allele (color-blind vision).
When you draw the Punnett square, you'll found the probabilities are XX, XY, Xx, and xY.
So, you have a 50% chance of having a boy and 25% chance of having a color-blind boy.
The
changeable nature of models is considered a limitation because when the model alters,
the answers that were achieved from the model may also transform.<span> <span>What this
means is that outcomes that’s been extracted from changeable models can be true
at a certain moment, place or situation, but the conclusions may not be
objectively true.</span></span>
