Niche Theory

A couple of questions from the last nichey post prompted this post. Geoff said that:

I’m not even sure what is meant by an optimal environment for a species/genus/whatever.

while Andrew said that:

it wouldn’t surprise me if a lot of species tend to live at the margins of their “ideal” habitat.

We need a bit of abstraction to address these questions. In a laboratory, a plant would be expected to show a humped response to the main variables of temperature and water availability. The parameterisation of this function can be termed the ‘fundamental niche’ of the species, and may be equated with a physiochemical optimum unaffected by competition.

In the wild there will be gaps in this function. This can be called the ‘realized niche’, and may be due to interspecific competition, but also affected by chance dislocation of the species’ distributions that are unrelated to any physiological capacity to occupy that space. If this were not the case, then no species could ever ‘invade’ another region.

Now we can imagine a ‘niche model’ of a species as consisting of an estimate of the humped function that represents it fundamental or realized niche. That function — to a first approximation the range of temperature and rainfall where the species has been observed — is the basis of original ‘envelope’ methods such as BIOCLIM.

But consider the logic of this model, calling the range model R and the sightings of the species S. If a species occurs at a point, then that implies it lies within the range R. However, we know from basic logic that:

  S → R ≠ R → S

But R → S is what we need for predicting the distribution of the species. We need to know that if the location has certain characteristics M then the species occurs, i.e. M → S. Thought of another way, the ‘gaps’ in the fundamental niche cause inaccuracy when we try to use it to predict.

To discover the optimal description M such that M → S we need to do a different kind of search that optimises the accuracy of prediction of the model. It has been shown conclusively that methods based on the correct logical form of implication are more robust predictors of the occurrence of a species, than an envelope model composed of climatic variables temperature and rainfall.

I found that in practise, a single variable such as monthly rainfall (ie seasonality) was much better predictor of the distribution of a species than the range of temperature and rainfall. In some cases, non-climatic factors such as soil types were optimal. The notion of an optimal environment only makes sense in the lab. In the wild, it really only makes sense to talk about the optimal determinant of a species.

Why this should be the case is kind of conjectural, but it would make sense from an entropy or information viewpoint for species to ‘spread out’ over possible environmental determinants, providing they stay with their fundamental niche. This would include ‘marginal’ locations.

In this view, the effects of climate change on species would be very mixed. Some species with a determinant that is not primarily climatic would be very unaffected. Other species would be affected over only part of their range, depending on the determining factor. This has been seen, as the primary response of species to climate change has been range expansion to the north in the northern hemisphere, due to a temperature determinant up there. Some unlucky species with highly seasonal determinants, or isolated non-climatic determinants, may be severely affected.

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0 thoughts on “Niche Theory

  1. At the time I made my comment, I was thinking only on the basis of very simple considerations. This conceptual framework helps to explore the idea further. Thanks.

  2. At the time I made my comment, I was thinking only on the basis of very simple considerations. This conceptual framework helps to explore the idea further. Thanks.

  3. This is drifting off a bit, but some theoreticians of species populations come back to the need to reproduce from the strongest male as one of the primary drivers. Therefore, another determinant of distribution over the globe might be the ability to mix and select.

    There is a theory of optimal outreach, whereby it is recognised that breeding with others too close to family produces weak offspring, and likewise if the breeding is between distant parties that are developing (or have developed) into sub-species or similar, like the sterile mule case. There is theorised to be an optimum separation in both kinship and distance. I have not kept up with this and can report no measurements.

    I’m thinking that in relation to David’s comment that a single variable was often the best predictor, there could well be numerous effects of various weights that would be quite hard to model; so simplification to a single, useful predictor would be helpful.

    As a rider, there are some plants that require a specified temperature range to breed at all. However, it is not my understanding that a change of one deg C in Springtime one year would have much of an effect. Go to 10 deg C and you might notice it.

    • The ‘strongest male’ is itself a highly variable component. When nutrition is not a limiting factor (eg Qld in the 1950’s) then males with a higher maintenance requirement, and hgher growth potential, can dominate.
      Moving to a lower nutritional level (eg Qld in the 1960’s) the higher maintenance animals can be adversely affected (or may no longer be viable) and smaller animals with a lower maintenance requirement may then be the ‘strongest’.

  4. This is drifting off a bit, but some theoreticians of species populations come back to the need to reproduce from the strongest male as one of the primary drivers. Therefore, another determinant of distribution over the globe might be the ability to mix and select.There is a theory of optimal outreach, whereby it is recognised that breeding with others too close to family produces weak offspring, and likewise if the breeding is between distant parties that are developing (or have developed) into sub-species or similar, like the sterile mule case. There is theorised to be an optimum separation in both kinship and distance. I have not kept up with this and can report no measurements.I'm thinking that in relation to David's comment that a single variable was often the best predictor, there could well be numerous effects of various weights that would be quite hard to model; so simplification to a single, useful predictor would be helpful.As a rider, there are some plants that require a specified temperature range to breed at all. However, it is not my understanding that a change of one deg C in Springtime one year would have much of an effect. Go to 10 deg C and you might notice it.

  5. The 'strongest male' is itself a highly variable component. When nutrition is not a limiting factor (eg Qld in the 1950's) then males with a higher maintenance requirement, and hgher growth potential, can dominate. Moving to a lower nutritional level (eg Qld in the 1960's) the higher maintenance animals can be adversely affected (or may no longer be viable) and smaller animals with a lower maintenance requirement may then be the 'strongest'.

  6. The central requirement for climate change (warming) to have a detrimental impact on a species, particularly very slow moving ones such as plants, is that the change must be at a rate that is faster than adaptation can accomodate. Hence the endless cries from the alarmists of ‘it’s worse than we thought’ and the reliance on the rapid upswing of the hockey stick blade. Even so a lot of plants have dispersal mechanisms that are well up to coping with rapid change and are lying in wait in the seed bank for the right conditions to prevail. From so many standpoints these things just can’t be generalised.

    It seems to me that the climate change movement has been reversing the historic drive towards greater precision and detail. It’s like running a Gaussian Blur over the world to try and see a broad pattern because it can’t be seen when you look in detail. Once upon a time there were canals on Mars until we could look more closely.

  7. The central requirement for climate change (warming) to have a detrimental impact on a species, particularly very slow moving ones such as plants, is that the change must be at a rate that is faster than adaptation can accomodate. Hence the endless cries from the alarmists of 'it's worse than we thought' and the reliance on the rapid upswing of the hockey stick blade. Even so a lot of plants have dispersal mechanisms that are well up to coping with rapid change and are lying in wait in the seed bank for the right conditions to prevail. From so many standpoints these things just can't be generalised.It seems to me that the climate change movement has been reversing the historic drive towards greater precision and detail. It's like running a Gaussian Blur over the world to try and see a broad pattern because it can't be seen when you look in detail. Once upon a time there were canals on Mars until we could look more closely.

  8. Previously, I’ve drifted off-specialisation, but David’s comment “Some unlucky species with highly seasonal determinants, or isolated non-climatic determinants, may be severely affected.”

    This is how I see the main consequence of whatever climate change there might be. As an extreme example, imagine migratory birds that have flown thousands of km to an island where they have bred as long as can be recorded. If, in one rare year, the island is iced over and they are unable to make nests, then climate will have impacted on a population. Extent of each unstated in this hypothetical.

    Absolutely agree with ColinD that rate of adaptation and rate of environment change have to bear a special relationship before generalisations can be made. It seems that the time rate of adaptation, as a concept, has been steadily growing shorter in estimate as we derive info from DNA change rates, more field observation, more observers, etc., however imperfect these methods might be.

    It’s not hard to think of a lot of special cases such as Aust seeds that need fire to activate them. Again, I come back to the extinction list of Australian birds, where most had a range limited by the dimensions of small islands. There are many cases where climate is not a factor in species numbers.

  9. Previously, I've drifted off-specialisation, but David's comment “Some unlucky species with highly seasonal determinants, or isolated non-climatic determinants, may be severely affected.”This is how I see the main consequence of whatever climate change there might be. As an extreme example, imagine migratory birds that have flown thousands of km to an island where they have bred as long as can be recorded. If, in one rare year, the island is iced over and they are unable to make nests, then climate will have impacted on a population. Extent of each unstated in this hypothetical.Absolutely agree with ColinD that rate of adaptation and rate of environment change have to bear a special relationship before generalisations can be made. It seems that the time rate of adaptation, as a concept, has been steadily growing shorter in estimate as we derive info from DNA change rates, more field observation, more observers, etc., however imperfect these methods might be.It's not hard to think of a lot of special cases such as Aust seeds that need fire to activate them. Again, I come back to the extinction list of Australian birds, where most had a range limited by the dimensions of small islands. There are many cases where climate is not a factor in species numbers.

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