The Basic Model of Island Biogeography
The model is one of a dynamic equilibrium between immigration of new species onto islands and the extinction of species previously established. There are 2 things to note immediately: 1) this is a dynamic equilibrium, not a static one. Species continue to immigrate over an indefinite period, not all are successful in becoming established on the island. Some that have been resident on the island go extinct. The model predicts only the equilibrium number of species, will remain 'fixed'. The species list for the island changes; those changes are called turnover. 2) The model only explicitly applies to the non-interactive phase of island history. Initially, at least, we will consider only events and dynamics over an ecological time scale, and one which assumes ecological interactions on the island occur as a result of random filling of niches, without adaptations to the presence of interacting species developing there. Evolution is clearly excluded.
The variables used in the basic model are Is, the immigration rate, which is clearly indicated by the subscript to be species specific, i.e. to be dependent on the number of species already present on the island. Here we're not counting noses, but rather the rate at which new species (those not already present on the island) immigrate. Phrased explicitly, it is the number of species immigrating per unit time onto an island already occupied by S species. Also Es, the extinction rate, measured in species lost per unit time from an island occupied by S species. Finally, we need to know the size of the pool of species in the source area available to colonize the island.
The immigration rate Is must certainly decrease monotonically (on average) as the number of species on the island increases, since as S increases there are fewer and fewer species remaining to immigrate from the pool P of potential immigrants at the source. If all species were equally likely to immigrate successfully (i.e. had equal dispersal capabilities), but actual immigrations were chance events, then the relationship between Is and S would be linear, the probability of a new species immigrating would be directly proportional to the number of species left to arrive. There are, however, considerable differences in the dispersal abilities of species in source areas. Those with the highest dispersal capacities are likely to colonize an island rapidly (have a higher immigration rate), and later, on average, those with lower dispersal capacities will follow. They will not only immigrate later, but the rate at which they immigrate will be lower because they have lower dispersal capacities. The rate at which species accumulate on islands is, therefore, initially rapid and then slower. Also, among those species with lower dispersal capacities the successful immigration of any one species should have less effect on the immigration rates of species remaining in the source pool (we have not removed a likely immigrant from the pool) than would the earlier immigration of a highly dispersible species. Therefore, this part of the curve should be 'flatter'; the rate of immigration should be little affected by the arrival of one of these poor dispersers. The result is an observed immigration rate curve which is concave. The actual (or theoretical) curve for any island is dependent on its isolation. For any source pool, the observed rate, while similar in shape, will be lower for more distant islands than for closer ones. Immigration rates are graphed from the left hand edge of figure 1, declining from the y axis with an increasing number of species already present.
Figure 1 - The basic graphical model of equilibrium in the MacArthur-Wilson model. Figure from Brown and Gibson -Biogeography.
The extinction rate Es should be, from parallel reasoning, a monotonically increasing function of S. If area, for example, acts only through its effects on population sizes, and extinctions are the chance result of small population sizes and demographic stochasticity, then as the number of species increases, the number of species with small populations and subject to chance extinctions increases in proportion, i.e. the relationship would be linear. However, if we consider a more realistic biological scenario, then as the number of species increases, depressant interactions within and between species (competition, predation, parasitism) are more likely to occur, and extinctions are more likely as a result. Remember that these are not species that have evolved adaptations to interactions. Effects are direct and unmoderated. Since any extinctions resulting from interaction are in addition to those resulting from demographic stochasticity, the more realistic shape for the extinction curve is concave upwards. The extinction rate begins at 0 when there are no species on the island, then increases as species accumulate. At least for purposes of simplicity in looking at the basic implications of the model, the extinction curve can be thought of as a mirror image of the immigration curve.
We now have all the information to produce the basic graphical model. That model predicts that there is some value of S, which is called Ŝ, for which immigration rate and extinction rate are in balance; there is a dynamic equilibrium. At that diversity on the island species are immigrating at a rate equal to disappearances due to extinction. The result is constant change in the species list on the island; that change in names occurs at a rate called x, the turnover rate. The length of the species list, however, should remain constant. This is a stable equilibrium since, should something happen, and the number of species on the island be perturbed, the imbalance between immigration and extinction rates at the new S would tend to return island diversity toward its equilibrium value. Below Ŝ additional species accumulate; immigration rate is larger than extinction rate. Above Ŝ the reverse is true, extinctions exceed immigrations and the number of species declines to Ŝ.
Tests of the Model
To test the model, an important piece of evidence is a carefully designed manipulative experiment studying the fauna which colonize 'islands'. One of Wilson's students, Dan Simberloff, tested the model using islands which consist of mangrove mangles in the Florida Keys. Simberloff's Ph.D. thesis had consisted of measurements of the re-colonization of these islands following 'defaunation' (he had encased individual mangles in giant plastic bags, sprayed them with short acting, low persistence insecticides, then followed the rates, numbers, and species which immigrated onto them after exposure). Re-equilibration, i.e. reaching a stable number of species, had occurred within 3 years of fumigation in his earlier experiments. In a second series of studies (Simberloff 1976), the manipulations were equally inventive. After the islands had been censused, and an equilibrium number of species determined for each island (a 'control' diversity), crews moved in with chain saws, handsaws and hatchets, and each island was split into 2 or more smaller parts, with water gaps of 1m between. To the insects, apparently this 1m gap was sufficient to make crossing from one sub-island to another a jump dispersal. The smaller, sub-islands were then censused repeatedly over a time interval sufficient to permit re-equilibration to find out how species numbers changed with island area. Remember, the area censused had been part of a previous island, and should contain all habitats (plant parts, vertical structures) in the same proportions as before (i.e. the same habitat heterogeneity, however measured). Alterations were only quantitative, in the form of area reduction, no unique feature was removed.
The results were clear-cut. Each island reduced in size re-equilibrated at a lower insect diversity. Considering all the experimental islands in developing a model for the pattern in reduction, the diversity change fit a log-log relationship (i.e. a power function) between diversity and area. Thus, Simberloff's data fit the original species-area relationship. Area was the key determinant. The process of re-equilibration, however, involved extinction of species from islands supersaturated due to their reduction in size. We have already encountered the underlying biological cause of those extinctions: population sizes of 'marginal' species, that is those whose populations were already small before reduction in area, were decreased to the point where chance extinction due to demographic stochasticity became likely, and re-colonization unlikely. Such extinctions are an important component of the equilibrium model of island biogeography.
Figure 2 - Effect of island fragmentation on insect diversity in mangrove mangles. Simberloff (1976).
There are few islands that have been studied over long enough periods to test the hypothesis of equilibrium with turnover, i.e. the occurrence of a stable but dynamic equilibrium. Among those few are the California Channel Islands. The interpretation of these data is a source of continuing controversy. That's important, because the crux of the equilibrium theory is proof (or documentation) of insular turnover at equilibrium. A paper (Gilbert 1980) found 25 attempts to document turnover at equilibrium, and found few (basically just mangrove island studies by Simberloff) acceptable without question. In Simberloff's original defaunation studies, for example, one island supported 7 species of Hymenoptera prior to fumigation and 8 after equilibrium had been re-established about one year later. However, only two of these species were present both before and after fumigation. This sort of experimental study is designed to allow for rapid re-equilibration.
The Channel Island studies represent an interesting attempt to deal with the problems of scale (here time) when dealing with most real ecosystems. Recognizing that there may be difficulties (the initial, historical survey of species presences on the island used breeding records collected over many years, rather than a single survey at one time), Diamond's studies of turnover on the Channel islands are still regularly cited (Diamond 1969).
Initial data reported collections and observations indicating the fauna of individual islands in 1917. Diamond compared those species lists with a survey he did in 1968. Over the 51 years between censuses the numbers of species on islands remained almost perfectly constant, but turnover was as high as 62%, i.e. as much as 62% of the original list had been replaced by new species. The islands had the following characteristics:
Island 1917 1968 Extinctions Immigrations %turnover
Los Coronados 11 11 4 4 36
San Nicholas 11 11 6 6 50
San Clemente 28 24 9 5 25
Santa Catalina 30 34 6 10 24
Santa Barbara 10 6 7 3 62
San Miguel 11 15 4 8 46
Santa Cruz 36 37 6 7 17
Anacapa 15 14 5 4 31
These data seem initially to fit the equilibrium theory quite well. Numbers remain almost constant while turnover occurs in a significant number of species. However, the theory also suggests, as you will soon see, that turnover should be related to island area (through effects of area on extinction rates) and/or isolation (through effects on immigration rates. Neither was the case; instead turnover was approximately inversely proportional to the number of species present. That is not forecast by the model.
Figure 3 - The number of species in censuses of 3 of the California Channel Islands.
Figure 4 - % turnover in species numbers on California Channel Islands. (a) for nine of the islands. (b) for Anacapa as a function of time between pairs of surveys.
Why should turnover be related to island area or isolation? Consider first 2 islands at equal distance from the source, but differing in area. Long distance (jump) dispersal is generally assumed to be a chance event, not directed or goal oriented. In that case, dispersal probabilities and immigration rates onto the 2 islands should be the same. Area, however, does affect the extinction rate of colonists. The larger island should have 1) higher habitat heterogeneity, 2) decreased intensity of interactions due to reduced niche overlaps resulting from habitat heterogeneity and 3) larger population sizes making chance extinctions less likely.
These factors should be operative, at least in a relative way, independent of the number of species present. Therefore, the extinction curves should have similar shape, but have lower values for the larger island. Putting this comparison on a graph, but using a linearized version of immigration and extinction curves, we find a larger equilibrium number of species on the larger island, but also a lower turnover rate on that island.
To assess the effects of isolation consider 2 islands of equal size, but located at differing distances from the source. With identical sizes we assume that habitat heterogeneity, population sizes and interactions on the islands are quantitatively identical, and thus they have the same extinction rate curves. Immigration rates onto the more distant island should, however, be lower at any S since the probability of a successful dispersal decreases (possibly exponentially) with distance. We can go further, and suggest that the decrease should be most noticeable for species which tend to be among the first colonists. Later immigrants with lower dispersal capacities have only a slim chance anyways, and depend on rare, special conditions like storms for successful immigration. For these species a change in distance should mean less in shifting immigration rates. Once more we turn these suggestions into a comparison on the graph. The more distant island has a lower equilibrium number of species, but also a lower turnover rate at equilibrium than an island closer to the source.
Figure 5 - Multiple immigration and extinction curves indicating effects of differences in size and isolation on equilibria and turnover rates. Brown and Gibson (1983).
These comparisons can be combined in various interesting and complicated ways. Rather than document the possibilities, it is probably more valuable to attempt to list the assumptions and predictions of the basic MacArthur-Wilson model. Some of the ideas in this list will not be fully examined until later in this section.
Under What Conditions Does the Model Apply?
1) Islands are real isolates (rescue effect, discussed below, not important)
2) Islands have comparable habitat heterogeneity (complexity). There are no gross environmental changes over the time period of colonization
3) Species counted on islands are residents
4) There is a definable mainland species pool
What Are the Characteristics of the Equilibrium?
1) It is dynamic
2) It is approached asymptotically
3) The process is inherently stochastic
4) The model and the equilibrium are describing processes in ecological time
What Are the Characteristics of Turnover?
1) The process is not successional
2) Species replacements occur frequently
3) Immigration rates decrease with increasing species numbers. Extinction rates increase with increasing species numbers
What Influences the Equilibrium Number of Species?
1) Influenced by area through extinction rates
2) Influenced by isolation through immigration rates
3) Varies faster with area on distant islands (see below)
4) Varies faster with isolation on small islands (see below)
With this summary in mind, we return to problems. With regard to Diamond's data, no combination of size and isolation leads to the prediction that turnover rate is inversely (or in any other sense) proportional to the number of species on an island.
Since the data are repeatedly cited and classic, it's worth trying to understand why this anomalous result was reported. There are a number of possible answers, and arguments in the literature could be described by indicating that 'the fur has definitely flown'. For one thing, the interval between the censuses was very long. That may have had significant effect on the measured turnover. If the time interval is long enough it becomes likely that some of the species which had gone extinct at some time between the censuses also re-immigrated during that interval (or the converse). In either case the measured turnover would underestimate actual rates. To attempt to correct for that possibility, Diamond and his collaborators went back to the Channel Islands annually during the early 1970's, and also used thorough data gathered for Farnes Island off Great Britain. The result of differences in the interval between censuses is evident in Fig.8 (and reported in Diamond and May 1978). The result for the Farne Islands is parallel. In either case the apparent turnover decreases rapidly as the census interval increases. To show you why, consider what happened to the meadow pipit on Farnes between 1946 and 1974 (May and Diamond 1977). The pipit bred for 2 years, went extinct in the 3rd, then went through 5 more cycles of immigration and extinction over the remainder of the period. From annual census records that indicates 11 turnover events in 29 years, where a census after 30 years would have recognized only a single extinction, as well as a constant diversity of 6 species on the island. The same basic pattern applies to the Channel Islands. Instead of turnover rates ranging from 17-62% (or .34-1.24% per year), annual censuses indicate actual turnover rates of 1-10% per year, and are about an order of magnitude larger than indicated by to 51 year interval for most islands.
That's not the only corrective surgery which has been suggested for the theory. It is also evident that monotonic rate functions (particularly the immigration rate curve) may be overly simplistic. That should be evident by drawing a parallel between accumulation of species on an island and primary succession. When an island is newly formed (frequently volcanic) it has no organic content in (and frequently no) mineral soil. The first plants must be special sorts that have no requirement for nutrients from the soil (or possibly no requirement for soil at all); instead they are soil formers, leaving behind their nutrients extracted from the rock (as well as their bodies) to improve conditions for later arrivals. Krakatoa, East of Java, was not only a B movie, but a real historical event in the 1880's. What kind of immigration curve described the relationship between immigration rate and the number of species on Krakatoa after its formation. Depending on our definition of immigration (does it end with landing on the island, or require initial growth to be counted) and extinction (does a species have to reproduce at least once on an island before we consider its loss an extinction?) either immigration rate or extinction rate curves could be modified. For simplicity we'll include the modifications in the immigration rate curve. Now it isn't monotonic decreasing; instead it may have an initial rising phase representing the additional immigration possible with the formation of soil. That is the naive logic. Reality isn't quite so simple. Over the first 50-60 years since eruption (1883) the 'curves' of the number of species accumulated over time for various plant groups seem virtually straight lines; there is no decrease in rate of immigration over this time. Similar arguments could be advanced, producing a similar curve shape, with respect to other trophic levels. Equilibrium diversity and turnover rates can be affected by these modifications.
Figure 6 - Colonization rates for vascular plants on Krakatau measured in terms of total number of species (labeled 13), immigration and extinction rates (14), and as functions of the number of species present (15). From Thornton et al. (1993).
Since Diamond's data from the Channel Island studies suggested an appropriate relationship between turnover and area-isolation effects, but could not quantify them, an appropriate experimental test became important. Jim Brown and his wife Astrid attempted such a test (Brown and Brown 1977). They studied the colonization of thistle plants by assorted insects and spiders by repeated census following defaunation. Almost everything fit the basic MacArthur-Wilson model, but... The turnover rate should be inversely related to island distance (isolation) according to the theory. If we look at just distance effects on the same island (i.e. area), the nearer island should have a higher turnover rate. That's not what the Browns found. Instead, whether plant 'islands' were large or small the turnover rates were higher on more distant islands.
Site 1 Site 2
# of plants Mean # species turnover rate # of plants Mean # species turnover rate
large- 16 3.82 0.67 9 5.25 0.29
large- 7 3.78 0.78 9 4.44 0.42
small- 56 1.89 0.78 21 2.21 0.69
small- 3 1.33 1.00 11 0.80 0.91
Based upon a 5 day census interval (remember what Diamond's data ended up showing about the importance of census interval), turnover rates were consistently higher on the more isolated plants. This reversal of the expected pattern is explained as resulting from the effect of repeated immigration of species onto near islands. The original model was psychologically, if not explicitly, concerned with a degree of isolation which made such repeated immigrations unlikely. Under real conditions repeated immigration may be likely, particularly on near islands. Addition of a new immigrant member into a small population reduces the probability of extinction. This repeated immigration is, therefore, termed the 'rescue effect'. It could, as I've just suggested, be presented as affecting immigration or extinction, but since the key effect is on extinction rates, making extinction less likely on near islands, that's where the curves are usually adjusted for rescue. When the rescue effect occurs, turnover rates will tend to be directly proportional to distance. The effect may be evident in data sets as divergent as these studies of plant 'islands' and Diamond's New Guinea satellite island avifaunas.
Figure 7 - How the rescue effect modifies curves of immigration, extinction, and turnover as a function of distance.
From predictions of rescue effect occurrence we can make some general, graphical predictions of how distance effects immigration, extinction and turnover. Note that we are here graphing these rates against distance, not against species numbers. The immigration rate declines exponentially with distance, as we've previously seen in a variety of data. The extinction rate was previously considered as depending on island area, and unrelated to distance; it would have been a straight horizontal line on this graph before we considered rescue. Now we recognize that the rescue effect bends the extinction curve down at low distances. When we combine these curves to estimate turnover as a function of distance, it has an intermediate peak; turnover is highest at those distances when both immigration and extinction rates are high. Very close to the source extinction rates are low; at large distances immigration rates are low.
The next correction to the simple model is one which questions the validity of the species-area relationship. Are projections of area-dependent extinction valid for the total range of island areas studied? Of course, I wouldn't be suggesting the question unless something were amiss. There is a problem on very small islands. MacArthur and Wilson recognized that possibility in presenting the basic theory, and suggested such islands were unstable, should have very high turnover rates, and probably not have area-dependent extinction curves. Basically, they thought any area effects would be masked by the instability of the islands. The figure in the original monograph showed a split curve for extinction rates, i.e. an unpredictable area effect. The original data used to construct that graph was drawn from studies of the ecology of the Kapingamarengi atoll system in the Carolina Islands in Micronesia (Niering 1963). These small outcrops appeared to show a threshold in the species-area relationship at about 3.5 acres in area. It was suggested that the instability was not habitat destruction by physical forces, but instability in the presence of fresh water. Below the threshold area the water table on the island is saline; fresh water availability depends totally on frequent rains. Above the threshold area there is a permanent 'lens' of fresh water, and extinction of plant and animal species dependent on fresh water becomes much less likely.
Figure 8 - Predictions of extinction rate characteristics on very small islands. From MacArthur and Wilson (1967)
That explanation seemed fairly successful and biologically reasonable. However, Whitehead and Jones (1969) re- examined the same data and came to somewhat different conclusions. First, they found the data better fit by a curvilinear relationship between species and island area, rather than a threshold. That, by itself, doesn't mean too much. They also explored biological bases for the curvilinear relationship. Their rationale were:
a) Part of the problem was that the species list included a number of species introduced by man. Almost all these species were found solely on larger atolls; a number have been recent introductions. These species (particularly recent introductions) are not part of a normal biological equilibrium, and removing them from the species-area curve seems to lower the slope of the curve at larger areas without affecting the slope among smaller atolls (fewer visits by man means that there have been fewer introductions on smaller atolls). The way removals from species lists were handled left those species apparently introduced by Melanesian natives early enough to have had a reasonable opportunity to have become part of a biological equilibrium or to have gone extinct.
Figure 9 - An alternative view of characteristics of species contributing to diversity on Kapingamarangi atoll. From Whitehead and Jones (1969)
b) In addition, there is more than one kind of species introduced to the islands by natural dispersal. The different types also show different rates of numerical increase with area. One kind is what are called strand type species. Strand species are those which inhabit the relatively uniform shoreline habitat. Most are salt tolerant both in dispersing and adult phases. As adults they live in a habitat which is subject to frequent, if not continuous, salt spray. As dispersers many, if not most, are passively carried on ocean currents. These adaptations suggest that strand species do not require a lens of fresh water, and would therefore have no area threshold for occurrence. They also suggest that such species should be widespread and have a relatively high immigration rate. Thus, including the presence of a rescue effect, these species should have low extinction rates as well. In sum they should show little area effect and low endemism. The data from Kapingamarangi indicates that even the smallest atolls, only a few meters in diameter, have 5-7 species of the strand type, while the largest islands, with areas measured in the tens of square miles, have only 12-14 such species. In essence, strand species have a species- area curve which approaches a straight, horizontal line.
c) The so-called non-strand species cannot tolerate salt water and persist only where a lens of fresh water persists in the soil. Once the strand and introduced species are cropped from the species lists, the remainder (non-strand) display a species-area curve which fits quite well to the predictions of the MacArthur-Wilson model. Thus the basic theory is compromised by its inability to deal effectively (at least as a unified, simple model) with ecologically heterogeneous species groups. The basic theory arose from intensive study of avifauna and ponerine ants on widely spaced oceanic islands. Rooted in studies of homogeneous taxa of limited underlying ecological variety (particularly the ants, but in terms of dispersal and foraging methods, probably birds as well), the theory fits such groups well. When extended to a broader taxa and 'islands' the accuracy of predictions and the utility of the basic model are called into question.
There is one last criticism to aim at the basic theory before moving on to its quantification. Let's say you are studying a group of islands which should equilibrate fairly rapidly, both because of their distance from the source pool(s), their size, and the taxa under investigation. Over time you find the number of species on the islands to vary, even after it would seem that equilibrium should have been reached. What can you conclude?
1) That Sob is slowly approaching Seq, but that equilibrium has not been reached due to disturbance, possibly at an intensity subtle enough that the observer fails to note the disturbances - or -
2) That equilibrium has, in fact, been reached, but that the equilibrium itself varies due to shifting ecological conditions (e.g. climate) either on the island, affecting extinction, or at the source, affecting immigration. As a corollary of this view, even the observation of a constant number of species does not ensure equilibrium, since we have no independent estimate of S. The simple theory is simply not that quantitatively predictive as presently constituted. That, in a nutshell, is the key problem of this theory. It is extraordinarily difficult to design an experiment with appropriate controls on S, etc. to falsify the basic model. Yet the model remains very important to a broadening range of fields, subject to intensive efforts at corrective surgery, because it does have a lot of qualitative predictive ability.
Modeling Effects of Disturbance on the Equilibrium Theory
It is apparent that disturbance can have important consequences for observed equilibria or the lack thereof. What is difficult is the fact that disturbance has effects on the survival and/or reproductive success of individuals. A disturbance, unless extraordinarily massive, does not affect every member of a population. Modeling on an individual basis has been difficult or impossible until recently. An Italian group (Villa et al. 1992) attempted to evaluate the effect of regular disturbance at differing intensities on the equilibrium. The following were their conditions:
1) Island habitats were equally distant from the 'source', but differed in size, from 50 'cells' (each cell was a potential site for an individual) to 1100.
2) The were 64 species. Each had its own mean lifespan, interval between reproduction, and a range of clutch sizes from minimum to maximum, i.e. a life history. Each species also has a relative dispersal capacity.
3) A colonization species pool with relative abundances in the pool set.
4) Colonization occurs by randomly allowing individuals to disperse according to a negative exponential distribution (but distributions are affected by relative dispersal distance). They are successful if they land on an empty cell. If so their life histories determine whether the population grows or goes extinct.
5) Disturbances occur periodically. Intensity varied from 0%-75%, where this probability was applied to each individual, and determined the likelihood of the individual being killed by the disturbance.
Some results of this simulation seem about as you might have predicted. Some are 'strange'. The two figures below show you some of the key results. Figure 11 shows you their eyeball estimates of the conditions which resulted in equilibrium. Over the 120 time intervals their simulation ran, slow-growing organisms never reached equilibrium on large islands, but did on small ones when there was no disturbance (indicated by 0 on the x-axis). They could not reach equilibrium on any islands at higher levels of disturbance. Fast growing organisms (on the right) could reach equilibrium on any size island in the absence of disturbance, and with the larger population size possible on very large islands, could even reach equilibrium in the face of moderate disturbance levels (i.e. levels 2 and 3).
Figure 10 - indications of relative equilibrium (thick lines) in 10 simulation runs for islands with different numbers of cells (the y-axis) and different intensities of disturbance (the x-axis: 0-no disturbance, 1-10% effect, 2-25% effect, 3-40% effect, 5-75% effect). Part a is for organisms with 'slow' growth (low clutch size, longer interval between reproduction, longer lifespan) and part b for 'fast' growing individuals.
Figure 11 - Species-area relationships for a) slow-growing and b) fast-growing organisms affected by disturbance. The 3 curves are for no disturbance (top curves), 25% disturbance effect (middle curves) and 75% disturbance (bottom curves).
Evident in Fig. 11 is the community level effect of disturbance. Disturbance lowers the overall number of species resident, but if there is sufficient time for equilibrium to have been reached, life history makes a difference. At low levels of disturbance, the slow-growing species attain a higher diversity. At high levels of disturbance, species are not able to remain around long, and a greater diversity can be achieved by being a good colonizer (a weed, rapid population growth, etc.). Counter-intuitively, when the actual fitting values for these curves are assessed, the steepness of the species area curve increases when disturbance is present, even though overall diversity decreases. What all this tells us is we need to know more about the effects of disturbance in real communities. The real world is affected by disturbance on a more-or-less frequent basis, and conservation models based on an equilibrium paradigm need to be re-considered to incorporate some indication of the effects of disturbance.
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