Concepts
• An ecological community consists of groups of species found together at the same time and space. Communities exist at any temporal or spatial scale. Species within a com- munity may or may not be interdependent.
• When researching a community, the researcher must first decide where com- munity boundaries are and what species to include. These are both fairly arbitrary deci- sions.
• Species diversity is a measure of the number of species present (richness) and their rel- ative abundances (evenness).
• Diversity exists at different scales, e.g. from the genetic variation found in individuals to the diversity of species across biomes.
• Diversity can be measured using a variety of indices; the method chosen depends on the ecological information needed.
• Scientists have long debated about whether increased species diversity leads to a more stable ecosystem (‘diversity–stability hypothesis’).
understanding the processes that cause them. Pattern is the observed structure of vegetation, for example, the zonation of veg- etation up a mountain, or weed composition in fields of different cropping systems.
Processes are the mechanisms that create the observed pattern. These include species interactions, climate, disturbance and nutri- ent availability.
This chapter addresses aspects of community structure and diversity (the number and relative abundances of species present in a community). We discuss how to define and delineate communities, whether communities are integrated units, and then discuss patterns, causes and con- sequences of diversity. Chapter 12 then addresses community dynamics and how communities change over time, while Chapter 13 addresses how and why species invade communities and their effects on community structure and dynamics. As you will see, we are beginning to integrate the information you have learned in earlier chapters on populations and interactions as we move towards examining communities as a whole.
Defining Communities
We have said that a community is a group of populations of different species that occur in the same place at the same time. Although this appears to be a simple concept, much of the ecological literature is taken up with dis- cussions on whether communities exist at all, and if they do, how will we recognize them (Clements, 1916, 1936; Gleason, 1917, 1926; Drake, 1990; Dale, 1994; Wilson, 1991, 1994)? While this appears to be a somewhat semantic argument, it does highlight the importance of considering what physical entity is being studied and what criteria are being used to define it.
We can delineate communities in a number of ways (Morin, 1999). We will pres- ent three ways: physically, taxonomically and statistically. Defining communities based on natural physical boundaries is sim- ple for a community in a pond or on a cliff because they have distinct boundaries.
However, these are the exception in natural systems. Boundaries in natural communities usually overlap one another. Managed sys- tems tend to have more distinct boundaries but this is only because edges are imposed and maintained by human activities. Such physical boundaries are usually set based upon our perception of the community structure rather than on how the communi- ty actually functions. Thus, we view a forest, field or bog as communities whether or not we know how they function (Booth and Swanton, 2002). Even in agricultural fields, there is movement of soil, plants and ani- mals across imposed field boundaries.
Though we manage them as discrete units, there will be continuous exchange among fields. We must make reasonable decisions about community boundaries, but be cog- nizant that they are not ‘real’ entities and that these decisions may affect the interpre- tation of data.
An alternative way to physically de- lineate communities is to describe them based on climatic variables. This was done by Holdridge (1967), who classified the world into life zones (large-scale com- munities) based on annual precipitation, potential evapotranspiration (water loss as vapour from surfaces and stomata) and biotemperature (mean annual temperature above zero) (Fig. 11.1). For example, a habitat with low potential and high annual precipitation would be a rainforest in a tropical climate but would be a desert if annual precipitation were low. Whittaker (1975) combined the characteristics of the dominant plants with the physical en- vironment to create vegetation biomes (Table 11.1). For example, he distinguished between temperate grasslands, shrubland, woodland, evergreen forest and deciduous forest. Numerous other schemes exist based on various combinations of biotic and abiotic factors (Hengeveld, 1990;
Heywood, 1995). These types of classi fications are useful as a general des- criptor of vegetation and allow us to make statements about large-scale community types.
The second way to define a community is based on taxonomic structure. We do this
Fig. 11.1. Holdridge’s Life Zone Classification System. Classification is based on annual precipitation, potential evapotranspiration (water loss through plant surfaces and stomata) and biotemperature (mean annual temperature above 0ºC). (Holdridge, 1967; with permission of the Tropical Science Centre.)
Table 11.1. Major biomes of the world. (From Morin, 1999.)
1. Tropical rain forests 19. Arctic-alpine semideserts 2. Tropical seasonal forests 20. True deserts
3. Temperate rain forests 21. Arctic-alpine deserts 4. Temperate deciduous forests 22. Cool temperate bogs
5. Temperate evergreen forests 23. Tropical freshwater swamp forests 6. Taiga forests 24. Temperate freshwater swamp forests
7. Elfinwoods 25. Mangrove swamps
8. Tropical broadleaf woodlands 26. Salt marshes
9. Thornwoods 27. Freshwater lentic communities (lakes and ponds) 10. Temperate woodlands 28. Freshwater lotic communities (rivers and streams) 11. Temperate shrublands 29. Marine rocky shores
12. Savannas 30. Marine sandy beaches
13. Temperate grasslands 31. Marine mudflats
14. Alpine shrublands 32. Coral reefs
15. Alpine grasslands 33. Marine surface pelagic
16. Tundras 34. Marine deep pelagic
17. Warm semidesert scrubs 35. Continental shelf benthos
18. Cool semideserts 36. Deep-ocean benthos
Source: Whittaker (1975).
when we talk about a field of maize, a tall- grass prairie or a maple–beech forest. We may not know the exact species composition
and their abundances, but we will know what species are likely to be present. We have an instinctive knowledge of how these
communities differ from each other and could probably list their dominant plant and animal species and their important eco- logical processes.
The third method for defining com- munities is based on statistically detected associations among species. Methods used for this will be described in more detail in Chapter 14, but briefly, they in- volve examining a large data set of species abundances taken from multiple sites.
Several types of statistical analysis sort this data into sites that have similar species composition. When data points are sep- arated into distinct groups, then we can say that two (or more) community types are present (see Chapter 14 and Figs 14.6 and 14.7 for an explanation of these meth- ods).
Community composition
Once we have defined the entity that we call a community, we must then decide what species we are going to include. Do we include allof the species present, only the plants or only a specific group of species?
Most ‘community’ studies only consider part of the community. We talk about a ‘plant community’, ‘bird community’ or
‘weed–crop community’. This reflects the taxonomic bias of individual researchers, but is also done for purely practical reasons.
Communities are often intractable when we attempt to examine them as a whole because we cannot control all the variables (Drake et al., 1996). This approach, of course, has limitations because the results may not be relevant to complex natural communities (Carpenter, 1996). With the exception of microcosm experiments, no studies that we know of examine the dynamics of the whole community. This will probably remain so out of necessity; however, in doing this we must remember that community dynamics may be caused by species or factors not included in the study.
When researchers ignore groups of organisms, ecological patterns might be missed, or alternatively observed patterns may not be explainable if they arise through
interactions with excluded organisms (Booth and Swanton, 2002). For example, in a situation where soil-borne organisms con- trol the community structure of plants (Jordan et al., 2000), interactions between the plant species may be incorrectly used to explain a pattern if soil-borne organisms are omitted from the study. Mycorrhizal fungi, for example, can influence the competitive outcome in a tall-grass prairie (Smith et al., 1999) and their interaction with vegetation should be considered as part of community dynamics.
Often the importance of a species will not be obvious from its size or abundance.
A ‘keystone species’ has a disproportion- ate effect on community function relative to its biomass (Paine, 1966, 1969). Keystones are not necessarily the most abundant or largest species – it is their effect that deter- mines their importance (Power et al., 1996).
For example, kangaroo rats (Dipodomys spp.) are keystone species in the Sonoran and Chihuan deserts because they preferen- tially feed on large-seeded plant species (Brown and Munger, 1985; Brown and Heske, 1990). Parasitic mistletoe can be a keystone species because of the large group of animals associated with it (Watson, 2001). Alternatively, a dominant tree species may not be a keystone. A weed could become a keystone if it alters nu- trient cycles, soil properties or provides food for invasive animals. For example, when the fire tree (Myrica faya) invaded Hawaii, it changed the nitrogen dynamics, which in turn influenced which other species could survive (Chapter 13) (Walker and Vitousek, 1991).
Are Communities Integrated Units?
One of the earliest debates in ecology cen- tred on whether a plant community is like an organism composed of interdependent species or whether a community is simply a group of species with similar environmental requirements. The two major scientists involved in the debate were Clements (1916, 1936), who proposed the organismic or holistic view, and Gleason (1917, 1926),
who proposed the continuum or individual- istic view. According to Clements, a com- munity was greater than the sum of the indi- vidual species and would have ‘emergent’
properties unforeseen based on species alone. Under this view, each community type would have a specific and predictable species composition. Gleason, on the other hand, saw communities as random collec- tions of co-occurring species. When species did have similar distributions, Gleason saw this as coincidence rather than interdepend- ence.
One way to observe whether species are independent or interdependent is to graph their abundances across an environmental gradient. The gradient could be as simple as increasing soil moisture, or as complex as an altitudinal gradient up a mountain
where many environmental factors change.
If communities are not tight associations of interacting species, then species’ distribu- tions will overlap and there will be no dis- crete boundaries between them (Fig. 11.2a).
In this case, defining a community is diffi- cult because there are no obvious species groupings. If species do occur in close association, then their distributions along a gradient will be similar and species’
boundaries will coincide (Fig. 11.2b). The area of transition between communities is called an ecotone. Ecotones usually have many species because members of both communities will be present, albeit in low abundance. In Fig. 11.2b, there are three communities with two ecotones shown.
Does the experimental evidence support
Environmental gradient
Species abundance
Environmental gradient
Species abundance
Ecotone Ecotone
(a)
(b)
Fig. 11.2.Theoretical distributions of species abundances over an environmental gradient according to: (a) Gleason’s individualistic concept and (b) Clements’ continuum concept (based on Whittaker, 1975).
Clements or Gleason? Well, neither view will adequately describe allvegetation pat- terns. There is a general consensus that both views contribute to our understanding of community structure. Gleason’s model is closer to current ideas, and most plant com- munities seem to follow Gleason’s individu- alistic model. Certainly, as Gleason suggest- ed, every species will have unique sets of environmental requirements or tolerances and will therefore have a unique distribu- tion. However, species interactions can change how and where a plant will live (Chapters 8 and 9), and therefore environ- mental tolerances alone do not determine distribution.
As Clements suggested, some species are interdependent; we have seen this in our discussion of mutualisms (Chapter 9). A keystone species may have strong interac- tions with many species and therefore the distribution of the keystone will determine the distribution of other species (Power et al., 1996). Finally, in situations where gra- dients are strong, for example between a lake and a forest, between the north and south slopes of a hill, or where the physical envi- ronment changes abruptly, then there also will be abrupt changes in community com- position and therefore the Clements model will apply. Really, both models were devel- oped from similar evidence (Booth and Larson, 1999), but were interpreted at dif- ferent scales. Clements looked at large-scale vegetation patterns, whereas Gleason was more concerned with individual species patterns.
Matters of scale
We think of ecological communities as ex- isting at scales that we can observe (e.g.
we watch a forest or field over decades), but communities exist at many temporal and spatial scales. A leaf is the substrate for a community of mites, bacteria and fungi.
It would be inappropriate to look at this community of microorganisms on a spatial scale of kilometres or on a temporal scale of decades, but these scales might be ap- propriate for forest studies. Community
ecologists are beginning to recognize the importance of scale when designing and interpreting ecological experiments (Levin, 1986; Allen and Hoekstra, 1990, 1991;
Menge and Olsen, 1990; Hoekstra et al., 1991).
We can understand communities better if we consider them at multiple scales. The effect of scale means that a community may be responding to local (e.g. succession), regional (e.g. climate) or global changes (e.g.
plate tectonics). Thus, subsequent changes in community structure may emerge from a micro-scale (1 m2) to a mega-scale (>1012 m2) (Delcourt et al., 1983; Davis, 1987). Factors that influence a community’s structure will function at many scales. Smaller-scale processes such as species interactions (e.g. competition or predation) and re- sponses to abiotic factors (nutrient levels) will determine local community patterns.
These local processes will be nested within large-scale environmental or climatic con- ditions that will either directly control species distribution or indirectly influ- ence the small-scale processes (Díaz et al., 1998; Menge and Olson, 1990; Woodward and Diament, 1991). The spatial patterns we observe in a community are the result of species responding to these multiple scales.
Patterns of community structure will emerge at a many scales. We might be inter- ested in community-level properties such as the number of species (species richness), or we may be interested in changes in species composition. However, focusing on only one of these can distort our view of the com- munity (Levin, 1986) because a pattern may emerge in one but not the other. For exam- ple, the number of species (richness) in a community may remain constant over time whereas the species make-up changes (Brown et al., 2001).
Community Attributes
In Chapter 2, we discussed the various attributes of populations that can be meas- ured: distribution, abundance and demogra-
phy. Communities, too, have specific types of attributes used to characterize and com- pare them. These attributes are based on fea- tures of a community and do not describe individuals or populations. They include species composition, physiognomy and diversity (Barbour et al., 1999).
The most basic way to describe a community is to list all the species pre- sent. However, as we have seen, it is not usually possible to list all species, there- fore this option is often not possible.
Instead, we may list the dominant species. A more general approach is to describe the general appearance of a community (phys- iognomy). Physiognomy includes such variables as:
• vertical structure of the vegetation (e.g.
canopy, shrub layer, understorey);
• spacing of individuals, (e.g. random vs.
clumped, sparse vs. dense);
• life forms of the dominant species (tree, shrub, herb).
We can go a long way towards understand- ing vegetation physiognomy by describing a few simple features. For example, we could
describe the physiognomy of a tropical rain- forest by dividing it into five stratified layers of vegetation: ground-level vegetation, the shrub and sapling layer, and three canopy layers (lower, mid-crown, emergent) (Fig.
11.3). Without knowing any species names, we could still understand the basics of how this community functions. Finally, we could use a measure or index of diversity to describe the variety of organisms in a com- munity. The remainder of the chapter will discuss diversity in detail.
Diversity
Diversity describes the wide variety of organisms found in the world. It encom- passes ways to quantify how many groups (e.g. species) are in a given community and their relative abundances. We usually think of diversity in terms of species, but we could also consider other types such as genetic or plant family diversity. In the last decade, diversity (popularly known as biodiversity) has become a political issue, and preserving diversity is seen as a good thing.
Emergent canopy of widely spaced trees
50 to >60 m
Main canopy of moderately spaced
trees forming a continuous cover
24 to 36 m
Lower canopy of juvenile trees
15-24 m
Shrubs and saplings Ground layer of ferns
and tall herbs
Figure 11.3.Physiognomy of a tropical rainforest showing five layers of vegetation: emergent canopy, main canopy, lower canopy, shrub and sapling layer, and ground layer. (Smith and Smith 2001; Copyright © 2001 by Benjamin Cummings. Reprinted by permission of Pearson Education Inc.)
If you go for a walk in the summer and look at the vegetation around you, you can get different impressions of di- versity, depending on where you are walking and how closely you look. For example, casual observation of a lawn usually leaves the impression that it is a monoculture. However, if you ask home- owners, they will probably complain about the many weeds in their lawns. The same is true if you pass a farm field or forest plantation. Farmers and plantation man- agers may want to grow a crop mono- culture, but there are likely to be many weeds as well. Conversely, we usually expect ‘natural’ areas to be teeming with different kinds of organisms. However, if you walk along a pathway in a small wood- land almost anywhere in the world and look closely, the vegetation is comprised of only a few species and a lot of these are weeds.
Some of these weeds are pleasing to the eye and many people do not mind them being there. We do not expect woodlands to look like monocultures, so a diversity of weeds does not look out of place to the untrained eye. If we compare managed and natural areas, we might find that each contains the same number of species, and many species are weeds. Only in managed areas might many people worry and try to do something about it. This perception is important because it colours our view of when and where we will accept the existence of diversity.
Basic components of diversity: richness and evenness
Diversity can be quantified simply by counting the number of species present and
comparing their relative abundances.
Species diversity in its simplest form is the number of species present in an area or in a community (species richness). You could calculate the diversity of your back- yard by counting the number of species there. It is a crude method of measurement, but it does give a good idea of how many types of ‘things’ there are in a com- munity. However, even this simple measure of diversity can be complicated when we consider sample effects. Two researchers calculating richness of a community will come to different conclusions based on the area they sampled. A researcher who sam- ples a small area will obtain a lower estimate of richness than someone who samples extensively.
The second component of species diversity is ‘species evenness’. Evenness compares the abundance of each species in a community, and tells you whether there are many rare species and a few common ones or if most species are equally common. Evenness is more informative than species richness, because it indicates whether the community is dominated by one or a few species or whether most species are represented by approximately equal numbers of individuals. For ex- ample, Table 11.2 summarized the species density data from four fields. The species richness is the same for all fields (four species in each); however, evenness differs among fields. Fields 1 and 3 have the same evenness, as all species are equally represented. Field 2 is dominated by downy brome (Bromus inermis) and field 4 is dominated by viper’s bugloss (Echium vul- gare) and therefore abundance is uneven.
That different species dominate in two fields gives us a hint about the characteristics
Table 11.2. Density of species found in four hypothetical fields.
Density (number of individuals m–2)
Species Field 1 Field 2 Field 3 Field 4
Downy brome 92 101 61 25
Canada thistle 103 13 63 12
Wild carrot 104 15 65 60
Blueweed 97 11 60 100