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Ecosystem Theories: The Hierarchy Theory in Ecology

University of Kiel, Ecology Centre, MSc Environmental Science, a seminar paper
1st version completed 11/10/2009 by Ruy Perez de Francisco (ciudadanoruy@hotmail.com)
2nd version (adapted, changes) 2010 by Alexander Strehmel (alex@strehmel-muc.de)
Status: completed

Ecosystem Theories: The Hierarchy Theory in Ecology

Using Systems Theory’s concept to be able to summarize and synthesize the incredibly complex, non-linear relationships within an ecosystem.

Summary

When people started studying ecosystems and landscapes in a scientific and holistic approach it was inevitable to realize the enormous complexity of these systems. There are huge numbers of individuals interacting continuously with each others and with their biotic and abiotic surroundings; trying to determine how each of these interactions plays a role on the macro scale is nearly impossible. To be able to handle this huge complexity scientist started looking for tools to simplify and aggregate information and they found that an old systems theory dialect, the Hierarchy Theory, could well perform such simplification. The Hierarchy Theory enunciates that the information flow between different hierarchy levels follows a certain, well-defined structure between the emitters and the receivers of such information; by studying the signals emitted by a certain hierarchy level it is possible to deduct the signals this level received previously and thus, reacted to them. Applying this last feature to a set of three contiguous hierarchy levels, placing the one to be studied right in the middle of these three levels, makes possible to restrict all the analysis and study to these three levels alone while still keeping into account all the possible interactions between the whole upper and lower levels that are also part of the entire system. This wiki summarizes in a user-friendly manner the basic concepts of the Hierarchy Theory directly applied to ecology with the aid of some examples, in order to allow the reader grab a sense of how this theory can be applied and be able to go to a deeper layer of knowledge, if desired, on more specialized sources.

Key words: hierarchy theory, self organization, emergent properties, landscape ecology, ecology complexity, scale and resolution.

Content

  1. The Hierarchy Theory in Ecology
  2. Epistemological Background
  3. What is a hierarchy?
  4. How to construct Hierarchy levels?
  5. Who is controlling whom?
  6. How does the information flow?
  7. Critical reception
  8. Conclusions and discussion
  9. References
  10. Useful links
 

 

1. The Hierarchy Theory in Ecology

The growth of environmental problems leads to a further urgency of sustainably managing ecosystems. Does an earlier bloom of some flowers in North Africa due to our present climate change have some relation with the decrease in a bird population in the North Sea? (Gordo et al. 2004) How can a factory’s emissions in China contribute to a climate change that lately alters the bloom period of some flowers in Africa? If we now have the capability to understand that human actions in one part of the world can produce some changes or effects on the other side of the world then we must consider those actions related to our study around the globe when we analyze something in this other side of the world. Furthermore: how can we even realize which actions across the whole world can be influencing our area of study?

Ecosystems, on the other hand, are incredibly complex, non-linear structures and self-organized entities; they cannot be described by simple models or by statistical approaches. Complete ecosystem models are nearly impossible to create because not all relations between the organisms are fully understood or not yet discovered; and even if we were able to build such a model with all the information we do know it will take ages to analyze; time we obviously can’t afford.

Furthermore different scales have to be considered when analyzing ecosystems. These scales include spatial differences in the extent of ecological entities as well as temporal differences in the processes within and between these entities. Considering the spatial scales where ecosystem processes can be observed it is helpful to have a look at landscape ecology and its spatial dimensions as they were defined by Loeffler (2002):

These dimensions range from the topic dimension which only overlooks a single spot or a small area with uniform structure and a defined range of interrelationships over the choric and regional dimensions to a planetaric dimension which considers processes that cover the extent of whole continents or even the whole globe. The choric dimension is defined as a mosaic of areas that have to be viewed on the topic dimension to be able to see the links and interconnections between them. It includes for example smaller river catchments, plateaus or escarpments in the landscape. The regional dimension covers whole geographic regions that can be defined as more or less uniform concerning certain factors like morphology, climate etc. On this dimension for example regions like the Alps or the North Sea can be examined. With these four dimensions it becomes clear that relevant ecological processes can be found at different spatial resolutions and therefore have to be viewed at different extents.

But ecological processes also happen in different timescales ranging from single events lasting only a few seconds or minutes over events with seasonal course or covering whole biologic, climatic or even geologic periods – lasting then over millions of years. Therefore also the timescale – additionally to the above mentioned spatial scale - cannot be neglected during the analysis of ecosystems.

Furthermore the spatial and temporal scales correspond very often. Processes that take place at large timescales also cover high spatial extents and vice versa (see Figure 1). Therefore the consideration of spatial and temporal scales cannot be performed apart from each other but the connections between the scales must taken into account when analyzing complex systems.

Now we can identify mainly two different main problems when dealing with ecosystems and their analysis. First the very high complexity which is regularly found in these systems and second the fact that ecosystem processes have to be viewed at different timescales and spatial extents. Given that these problems belong to the most challenging problems when it comes to ecosystem analysis scientists have been seeking for solutions to cope with complexity and scale issues.

Figure 1. Physical and ecological phenomena tend to line up along the diagonal direction in the space-time-diagram. This shows the relation between spatial and temporal scales that is found very often in nature (WU, 1999)

This complicated problems analysis in environmental management can be eased by using one of the Systems Theory general concepts, the Hierarchy Theory. Hierarchy Theory states that the study of a relationship between a certain identity and its surroundings can be simplified by studying the signals and constrains imposed by its upper hierarchical levels and the buffered signals it receives from all the lower hierarchical levels. So, instead of analyzing the whole structure to understand the functions of the system, Hierarchy Theory recommends to analyze three hierarchical levels only and the interactions between them.

Below I will go step-by-step explaining each sub-concept mentioned above and explaining how Hierarchy Theory can be applied to an ecosystem or landscape with the aid of some examples. But at first a little light shall be brought to the evolution and the development of Hierarchy Theory out of General System Theory from an epistemological viewpoint.

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2. Epistemological Background

As already elaborated ecological systems are usually characterized by a very high degree of complexity. At the same time ecology is often still seen as an under-developed science whose progress compared to other disciplines has been very low within the past 100 years. ALLEN & STARR (1982), who were the first ones to dedicate a whole monograph to the Hierarchy Theory, stated that there is a connection between the special character of ecosystems as complex systems and the fact that ecology is still very often considered to be the ‘poor cousin’ of other disciplines like geography or biology. According to their argumentation it lies in the nature of ecological systems to be so called ‘medium-number-systems’. Medium-number-systems are characterized as systems with too many elements to examine them one-by-one and on the other hand with too few elements to express them in statistical averages. In astronomy for example it is easy to calculate all interdependencies between the objects of the solar systems because there are only nine objects of research – the sun and eight planets – that have to be considered. In ecology there are a lot more objects which depend on each other and interact in manifold different ways. But these objects are too few to describe their behavior statistically, like it would be for example possible considering gas dynamics where most of the laws and equations which describe the behavior of gases do not consider the interactions between all the single gas molecules, but only consider the average behavior of the gas. Therefore there is no simple way so far available to describe and analyze ecological systems properly and this makes it according to the argumentation of Allen & Starr (1982) difficult to make huge forward leaps in the development of ecology as a science.

But what are ways to deal with the complexity of ecosystems? What ways are there for scientists to observe, analyze and describe complex systems in order to build hypotheses and theories? Generally there are two different paradigms to deal with complexity in scientific theory. These paradigms seem to be very contradictory at the first glance; nevertheless Hierarchy Theory tries to combine these two different approaches by only extracting the most useful features of these paradigms.

The first approach is called reductionism. Within the reductionistic paradigm complexity is handled in a first step by applying simplifications to a complex system to reduce the amount of data that has to be handled. In the second step the whole complex system is broken down in several subsystems which are then examined one-by-one. After their examination it is tried to integrate the results and to apply them to the whole complex system in order to formulate hypotheses. This reductionistic method is highly appreciated by scientists because the scientist has always the control and the overview over his research due to the breakdown of the complex system in subsystems and the structure that is created automatically by this step. But for ecology this approach has to be seen very critically, given that a breakdown into subsystems always also implies a change of the research scale, which is as we have seen very crucial in ecosystem analysis. Furthermore it is possible that the researcher misses out on relevant interactions between the subsystems that influence the whole complex system in a critical way. This may then in the end lead to erratic or irrelevant research results. Therefore reductionism alone is not an optimal way of dealing with complexity.

The other approach to deal with complexity is called Holism. Its way of approaching complexity can be summed up by the sentence: ‘The whole is more than the sum of its parts’. Holism explicitly considers the connections between entities of complex systems and also tries to examine the systems on all different relevant scales. This approach is especially relevant when it comes to the detection of emergent properties between system elements which can lead to very relevant and innovative research results and views on the research object. The problem with holism on the other hand is that the scientist examining a system in a holistic way has to put a lot of effort and time in his research to consider, observe, analyze and describe all interconnections between all different elements. If this additionally should be performed on different scales holistic research becomes a task that is nearly impossible to fulfill. This is mainly due to the fact that the human brain is only capable to a limited amount of abstraction and additionally there is also always the risk of simply overseeing and forgetting something important in the research due to the plethora of information that has to be considered. Moreover the holistic approach is not feasible as soon as it comes to the falsification of hypotheses or theories. In order to do that properly the holistic paradigm requires the researcher to look always at the whole complex system and all entities and interactions, looking for relevant properties to falsify this one hypothesis. Therefore also the holistic approach alone is not feasible for the research of complex system, especially when it comes to theory building and criticism of this theory involving the falsification of hypotheses.

Considering these preceding elaborations about Reductionism and Holism, for ecosystem analysis an epistemological approach which only combines the best features of both these paradigms would be desirable. And the general ideas of Hierarchy Theory rely on exactly this desire. This approach where holism and reductionism are combined in order to analyze complex systems is called complementarity. According to Salthe (1993) this complementarity approach which uses those non-equivalent explanatory strategies is especially feasible for systems that can be described in many non-equivalent ways which is especially true for ecosystems.

So how does this complementarity refer to Hierarchy Theory now? Hierarchy theory on the one hand reduces the amount of data the researcher has to deal with, on the other hand it explicitly considers the relevant entities and interconnections of a larger complex system according to a specific research question. The reduction of the amount of data is achieved by focusing only on one single research question and therefore only on some critical parts of a whole complex system. And with this reduction of data amount the evaluation of the interdependences between the relevant entities is made more effective. At the same time Hierarchy Theory introduces different hierarchical levels which are represented by different spatiotemporal scales. The interactions between these levels are explicitely considered, representing the holistic approach, and follow certain rules. But how hierarchy theory exactly works shall be described now on the following pages.

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3. What is a hierarchy?

Hierarchy means rank, and with rank comes power and control. To build a simple example, let us think of a Captain in the Army, this particular soldier has a rank inside the Army organization and that rank is “Captain”. This Captain has several lower rank soldiers at his command and also he must follow the orders of his superior commanders. Each one of these ranks is then a Hierarchy Level, all the Captains are responsible for their subordinates, the soldiers beneath them in the hierarchical structure and must obey the orders from anyone with a superior rank; from that point of view alone, all Captains perform the same function within the system. But there could be other soldiers in that same Rank that are not necessarily named a Captain and do not necessarily perform the same function as a captain but have the same authority as the Captain in the Army organization.

 

Figure 2. Typical unit hierarchy structure (after T.L. Eichman 2007)

 

Each and every one of these individuals and ranks within the Army organization is a sub-system of the general Army system; they are self-regulating because they are free to act but they are also constrained not to do something that is prohibited and have to perform certain mandatory functions and are self-organized, which means that all individuals are capable to live and reason by themselves however they all aim for the same goal and a common purpose. When I talk about a certain individual that belongs to a rank or hierarchical level and have these previous two, very special characteristics I can refer to it as a Holon. By definition a Holon is an entity of a self-organized system, self-regulated and linked to a particular hierarchical level (Allen et al. 1992). Is not the purpose of this wiki to explain in detail what self-organization means, however I strongly recommend the further reading of this concept if the readers pursue a fully understanding of Hierarchy Theory and some intrinsic concepts that I will go through in the Discussion section.

There are two types of hierarchy structures: nested and non-nested. In a non-nested structure the Holons in the upper level do not physically contain the Holons of the lower levels; a General has several soldiers at his command but none of these soldiers lives inside the General. Another common example of non-nested structures are food webs; a rabbit eats a carrot, and now the components of the carrot are part of the rabbit, but the carrot no longer exists as a Holon. Nested structures, on the other hand, do contain all the Holons of the lower hierarchical levels, a tick that lives on a dog can be seen living on the dog, furthermore, if we look at the yard where the dog lives in we could see the dog there, and in a very close look, the tick and so forth. These Holons don’t cease to exist as they become part of the higher hierarchical levels. Find below a figure illustrating these two structures types.

 

Figure 3. Comparison between a nested and a non-nested structure. In a nested structure on the left, the bacteria live on the plant and the plant in the landscape, they don’t cease to exist as the form part of the superior hierarchical level. In the non-nested structure on the right hand side, the plant ceases to exist when the rabbit eats it.

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4. How to construct Hierarchy levels?

When the observer determines which will be the entity to be analyzed, the Holon, the observer is also determining the characteristics and attributes that matter to the study of this Holon; then it can be noticed that some other entities around our original Holon perform kind of the similar functions on a different scale. The author can then assign certain conditions and functional performance to the Holon hierarchical level, organisms other that the Holon that perform the same tasks in the ecosystem, belong to the same trophic level or have the same habitat, just to mention some examples; and thus, the upper and lower hierarchical levels must be an extrapolation of these same conditions and functions at a lower and upper scale respectively, in order to maintain a congruent hierarchy structure. The hierarchical structure can then be filled according to these last criteria. In the case of the Army example, one possible definition of the hierarchy level to be assigned is how many soldiers under its command a certain individual has, the more rank the more soldiers under his or her command. In the case of certain garden, just to mention another example, I chose to assign hierarchy levels based only on the habitat of each Holon, like the tick-dog example; the tick, the first hierarchical level as I chose to define, lives on the dog, my second hierarchical level, and they both live in my garden, my third hierarchical level. Hierarchy levels can also be constructed based on the trophic level, who is eating whom or the complexity of the DNA chain of the organisms for example.

In the tick-dog example notice how the magnitudes of the entities grow proportional to the scale, the tick is a very small organism with a very short life-span compared to the dog, many tick’s generations can grow and live throughout a single dog’s life span, and many dogs can grow and live on a single field. The scale in Hierarchy Theory plays a crucial role; it tells us the spatial and temporal boundaries we fix for that very particular study. These two dimensions have two qualities each; the extent: that tells us numerically the magnitude of the time span and the physical area that our study will cover; and the resolution: which tells us the minimum unit of these two extent issues. Very high resolution is needed to study very little things or very quick events, but having a very high resolution also means handle a high amount of data. If your boundaries are very big a lower resolution can be helpful to study the elements without being overwhelmed by data. The size and life span of the tick are very small; the resolution of both scales must be very high in order to make a proper study of these organisms, say hours and millimeters for example, during the tick life span. A single day in the tick’s life can provide an important amount of crucial events that dramatically alter its life, however it is very unlikely (unless a major disaster occurs) that a single day can be enough for the entire field to be changed dramatically. Find below a figure that illustrates the relationship between size and lifespan of different hierarchical levels organisms in the sea.

 

Figure 4. Relationship between the body size and the life-span of different organisms in the sea (after Steele, 1992), each of these different organisms correspond to a different hierarchical level.

 

Hierarchy levels impose certain constrains or boundaries to their lower levels. A Lieutenant can’t be a Captain unless promoted, thus prove himself being capable of perform the functions of their new rank, but in certain cases these boundaries cannot simply be crossed ever, because it is impossible that a certain Holon suddenly has the necessary attributes to be part of the upper level, a plant cannot be “promoted” to a field, just to illustrate the idea.

What is very interesting, and lately, very helpful is that when the hierarchy levels are structured, some unexpected, additional features emerge among the individual hierarchical levels. These are totally unpredictable by the study of its components and can only be perceived when this sub-system, or Holon, self-organizes itself; when this happens, these new properties and functions are called emergent properties. The concept of synergy states that the sum of two or more components does not always result in the exact magnitude sum of the components value, sometimes the result is much higher in magnitude because additional properties, features, are created by the interactions between the components while been summed up. In nature this is very much true when these individual components are being added in an organized way, in a self-organized way, and the result of these components will create these new features, these emergent properties. It would have been impossible to predict the creation of these new properties by the sole study of the components alone without taking the interactions between them, especially if these interactions are being made in an organized way. Felix Müller and Søren Nors Nielsen stated in their paper Ecosystems as Subjects of Self-Organizing Processes that “Self-organization is a consequence of emergence and emergence is a consequence of self-organization” (Müller et al. 2002).

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5. Who is controlling whom?

As I mentioned before, upper hierarchical levels impose certain constrains on their lower hierarchical levels, but: is this the only type of control in a hierarchy structure? It is relatively easy to see hierarchical boundaries in society so I’ll build an example directly applied to a certain landscape. In my example a carrot will be chosen as a Holon. This carrot grows on a certain field and since the carrot “feeds” on the field’s soil the features of this field correspond to a lower hierarchical level than the carrot. So the carrot feeds from the available nutrients of the soil, water from the rain and energy from the sun. However there cannot be an unlimited number of carrots living on this field unless there is an unlimited amount of nutrients available in the soil and all the other necessary abiotic elements that the carrot needs to grow. But let us focus only on the nutrient availability of the soil, logically this nutrient availability is not unlimited therefore, since the soil is somehow restricting the number of carrots that can grow in a field and the soil belong to a lower level in this hierarchy we say that the soil is exercising a Bottom-Up Control over the carrots population. Now let me introduce another entity to this structure in a superior hierarchical level; an animal that feeds on the carrots, a rabbit. Suppose that there are a large number of rabbits eating all the carrots, even though there could be more than enough nutrients available in the soil to sustain a higher population of carrots, there aren’t that many because the rabbits are eating them, thus maintaining the carrots population on a low level. We can then say that the rabbits are exercising a Top-Down Control over the carrots population. In nature, there is no absolute control of one hierarchy level over the others, in fact the control is always and permanently changing from bottom-up to top-down and vice versa; if the rabbit population becomes ill, for example, then the fields turns to control the carrot population and so forth. And this constant change in the controlling situation, this constant set of limitations from above or below is what creates a certain balance throughout the whole system, yet again, a self-organization.

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6. How does the information flow?

One of the back-bone properties of Hierarchy Theory is how the information is flowing throughout the hierarchy levels and it is precisely this property that makes the Hierarchy Theory such an incredible, easy to use yet very reliable tool to help us understand and model nature. As I explained previously, hierarchical upper levels impose barriers or constrains to the lower levels and the temporal and dimensional scales vary proportionally with the hierarchy levels; well, the information flow also varies while jumping hierarchical levels while changing in frequency and intensity depending on the rank of the emitter and if the receiver is on an upper or lower hierarchical level.

The rate of events in a certain hierarchy level is dependent on the scale and resolution of that particular level, since the scale and resolution of the higher hierarchy levels are bigger, as explained before, the rate of events on these upper hierarchy levels will be at a much lower pace; the life span of a parasite living inside a rabbit is a lot shorter than the life span of the rabbit, and the rabbit will not be able to realize everything that happens to all the parasites living on it. If a single parasite dies or reproduces, the rabbit will not even notice. However, if the parasite colony grows big enough, to some critical level which the rabbit cannot tolerate, then the rabbit can fall ill or even die. Somehow the information produced and emitted at the parasite level is not perceived entirely by the rabbit but only when all these small signals reach a critical level. The information emitted was buffered or filtered by the rabbit’s nervous system, it doesn’t mean the information was lost, only that the rabbit summarizes the information emitted by its lower hierarchical levels. The same is true for the relation between the rabbit and the population it lives in. If only one rabbit is affected by the parasites and is therefore maybe not able to reproduce anymore, it will not affect the whole rabbit population. But if many rabbits suffer from the parasites then the consequences affect the whole population of rabbits. The population would start to shrink.

If we want to take a look at the rabbit’s parasite colony in a field we might go searching with a microscope the entire field trying to find and analyze them, or we might check the rabbit’s population health. Furthermore, if a large number of rabbits die because a huge infestation of parasites in the rabbit’s habitat, probably the entire field will feel the consequences, having a short unbalance due to the lack of the rabbit’s unique functions in this ecosystem. Therefore the effect of the parasites within the rabbits might have an effect on the population which could not be discovered examining just the parasites, the rabbits or the population alone. The resulting pattern of the change in the rabbit population because of the parasite infections of many rabbits can therefore be seen as an emergent property in this example.

Find below a figure that helps understanding the filtering capacity, in this case representing three different scenarios where the same filter reacts to three different signals.

Figure 5. Three different cases where the same filter reacts only when the signals received reach certain condition, in this case: the signals received should be at least 3x for the filter to emit a single signal.

So this particular Holon, this rabbit, is going to ignore this vast amount of information emitted by the organisms living inside it at a very high speed (because the short life span and fast reproduction time of the parasite) until it reaches a critical level; when the rabbit will become ill. But when this occurs, when the rabbit’s body finally realizes that something is going really wrong, it is going to counter attack, and send all available sources to fight back the infection, probably killing a huge number of parasites. So, when the rabbit emitted a signal back to its lower level, a single, very strong signal in response to all the small, high frequency signals emitted by the parasites, this first signal is going to have an enormous effect on the parasite colony. This last information transmission property is very, very important in Hierarchy Theory; signals emitted at a very high frequency by the Holon’s lower level are being buffered while reaching it and have little to no effect until they reach a critical level, however, when the Holon emits a signal back, usually in a much lower frequency, this single to few signals produce a huge effect on the lower level and are not buffered at all. Find below a figure that represents such information exchange.

Figure 5. Diagram (after Jørgensen and Müller 2000) showing the frequency of the signal transmission from below to top and vice versa along the different hierarchy levels.

So, even though all the information signals are not transmitted entirely across the hierarchical levels, because of this buffering function, every hierarchical level does have the aggregation of the main signals from their respective lower levels, a sort of summary of the information up to that level and the big signal effects imposed by the upper hierarchical levels.

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7. Critical reception

Probably the biggest advantage of hierarchy theory is that it deals with medium-number-systems by taking advantage of their organized complexity (O’Neill et al., 1986). And with this approach of identifying the structure of complex systems hierarchy theory is an instrument which is most useful during the beginning of research studies in order to get a clear picture on the system which is examined and its components, its scales and interactions.

At the same time hierarchy theory contains still the reductionistic element of considering only one hierarchy at a time. Therefore some elements of the whole complex system have to be omitted or can only be considered in separate hierarchies. This already leads to the first limitation of the hierarchy theory: Hierarchy theory is not a strong tool to explain interactions on adjacent hierarchical levels very well. For instance it usually does not consider the case that a holon on the Level 0 is constrained by more than just one holon on the upper Level +1, nor it can explain interactions between these upper level holons very well. But these interactions may also have a considerable impact and therefore could be able to influence also the Level 0 dynamics. Therefore it must be stated that some interactions and how they affect certain holons are not represented very well by the hierarchy theory. Maybe an integrative approach with network theory can provide a sufficient solution here.

Another problem is that the interactions between the different hierarchical levels rely on undisturbed signal flows between the elements of the hierarchy. Only when the signal exchange happens unaffected by influences from outside the hierarchical system is able to self-organize and to self-regulate and it remains in a stable state so that the emergent properties between the different levels can be observed. But as soon as the system suffers from a disturbance, there is no way for hierarchy theory to explain how the system can cope with this disturbance from outside. Therefore the system then cannot be analyzed in a proper way anymore using the hierarchy theory. Whenever the hierarchy theory shall be applied for the analysis of a complex system it is therefore important to pay attention to unwanted disturbances from outside to the system that might be capable to influence the hierarchical system in an undesired way and in the end might be able to produce misleading research results.

One of the main problems during the application of the hierarchy theory nevertheless is the phase where the relevant hierarchy according to the research question has to be defined. This phase is on the one hand the most crucial phase of research because all further analysis will be based on the assigned hierarchy. On the other hand the assignment of the ‘best’ hierarchy is a difficult task, especially when the connectedness between the entities of the complex system is very high. In this case the behavior of one element of the system may depend on many different other elements. It is therefore important for the researcher to think about the fundamentals of his research desire in order to extract the relevant hierarchy according to the research question. With this problem it becomes obvious that hierarchy theory can lead to a very efficient framework for research but the researcher does still have a lot of freedom which he has to cope with responsibly. The theory itself does not dictate which hierarchies on which scales are most promising for fruitful research results. Nevertheless the process that the researcher has to think about these kinds of questions before he is able to apply hierarchy theory to his problem can be a very important basis to lead the research about an ecosystem in the most useful directions. Therefore hierarchy theory can be seen not only as a tool for the analysis of complex ecosystem structures, but also as a method to determine how to approach a complex system in the best manner and therefore as a help to find the most relevant and fruitful research questions.

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8. Conclusions and discussion

But the reason why Hierarchy Theory is especially an excellent tool to approach a problem in nature in a holistic view is because the aggregation of all the properties I explained previously but mainly because of two properties: the self-regulation and self-organization of the Holons and the buffered information that each Holon receives from its lower hierarchical levels and, likewise, the restrictions imposed by its upper hierarchical levels. When we attempt to study a certain entity and the interaction between all its surrounding, biotic or abiotic, since each of these sub-systems is a representation and aggregation of the hierarchy levels above and below each one of them, it is enough to study the chosen Holon and the immediate upper and lower hierarchical level. That’s it, there is no need to extend the research beyond these boundaries because, even though the rips of the Holon’s effect cross along some other levels, the information these rips can generate along all the system are aggregated, buffered and summarized by the immediate levels. So by studying the interactions between these three hierarchy levels we can get an accurate representation of the interactions below and above throughout all the system or in the ecology case, the landscape.

Although the hierarchy levels are being assigned and filled up by the observer in this theory, it is impossible to take notice that natural processes and subsystems also follow certain hierarchical structure; my brain drags my attention to what is vital for me for example, if my foot itches and my belly hurts, my brain will focus my attention on my belly and I probably will not even feel the itch in my foot. But this hierarchical structure is created by the subsystems, the Holon of my brain, only when they organize themselves and this last concept is very important. Hierarchy structures are assembled while the system self-organizes, if the system self-organizes then emergent properties can emerge due to the organized interrelations of its components, and only when emergent properties emerge the hierarchical structures become of use, and obvious. But these three concepts, self-organization, emergent properties and hierarchy structures are not components of a loop, or pre-requisites of Nature but exactly what was necessary for some independent molecules to be organized in the first cell or me having the capability to write this paper; for the live to ‘emerge’ or the solar system to maintain its shape.

For many centuries we have believed that the human kind was above the Nature itself, that we were capable to create better things. And we were proven wrong, very wrong, hopefully with enough time to amend or errors; but now we realize that a very successful idea is to imitate nature or natural processes. Hierarchy Theory is part of the Systems Theory concept and we can use it as a tool to better understand nature. It is very gratifying then, noticing that Nature uses hierarchy structures as well.

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References

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Useful links
  1. A summary of the principles of hierarchy theory: http://www.isss.org/hierarchy.htm
  2. Landscape ecology in Wikipedia: http://en.wikipedia.org/wiki/Landscape_ecology
  3. Systems Theory: http://pespmc1.vub.ac.be/systheor.html
  4. The Rise of the Concept of Scale in Ecology: http://www.mun.ca/biology/dschneider/Publications/2001DCS_AIBS_RiseOfScale.pdf
  5. Ecology of Disturbance: http://tiee.ecoed.net/vol/v1/figure_sets/disturb/disturb_overview.html
  6. Quantifying Scale In Ecology: Lessons From A Wave-Swept Shore:  http://www.biol.sc.edu/~helmuthlab/Publications/InJournals/2004/Dennyetal2004.pdf 
  7. An Ecosystem Approach for Sustainability: Addressing the Challenge of Complexity:  http://www.nesh.ca/jameskay/www.fes.uwaterloo.ca/u/jjkay/pubs/SOHO/index.html
  8. Self-Organization in Living systems: http://www.nesh.ca/jameskay/www.fes.uwaterloo.ca/u/jjkay/pubs/thesis/toc.html

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Last modified at 4/5/2011 4:28 PM  by Claudia Henneberg 
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