Species Diversity

Insects represent the vast majority of species in terrestrial and aquatic ecosystems. For example, in most ecosystems where diversity of insect or arthropod species has been inventoried, along with plants and vertebrates, arthropods account for 70-90% of the total number of recorded species (see Table 9.1), roughly the same proportion as the total number of described species of organisms. Given that plant and vertebrate inventories are relatively complete, whereas currently described insect species represent only a fraction of the estimated total number of species (May 1988, Sharkey 2001, E. Wilson 1992), the proportional representation of invertebrates likely will increase.

Species diversity is a central theme in ecology. An enormous amount of research has addressed how diversity develops under different environmental conditions, how anthropogenic changes are affecting diversity, and how diversity affects the stability of natural communities (see Chapters 10 and 15). Clearly, the measurement of diversity is fundamental to meeting these objectives.

Diversity can be represented in various ways (Magurran 2004). The simplest representation is a catalog of species, or the total number of species (richness), a measure that indicates the variety of species in a community (a diversity). Rarely can all species be detected and documented. Usually the number of species recorded increases with the number of samples collected. The total number of species can be estimated by extrapolating from a species abundance curve that plots cumulative species against cumulative sample number or area. Alternatively, several parametric and nonparametric estimators can be used (Magurran 2004). Species richness can be standardized for various ecosystems by measuring the number of species per unit area or per 1000 individuals.

TABLE 9.1

Numbers of species of vascular plants, vertebrates, and arthropods in desert, grassland, forest, and aquatic ecosystems.

Ecosystem Vascular Vertebrates Arthropods % Arthropods

Plants

Desert

USSRa 125

Southwestern United 174

States 1a Southwestern United >600

States 2a

Grassland/Savanna

Hungaryb 1311

Hungary0 1762

Central United Statesd 521

Forest

Conifer, western 600

United Statese Deciduous, eastern 2816

United Statesf Tropical, Puerto Ricog 470

Marsh

Hungaryh 804

Stream

Tropical, Puerto Ricoi 0

Lake

Balaton, Hungary' >9

98 >1360 75

145 >1100 77

201 >2640 77

347 8496 93

289 7095 78

355 >1750 67

88 >3500 84

450 >4300 57

78 >1500 73

118 5332 85

7 50 88

51 >1200 95

aData from Polis (1991b).

bData from Mahunka (1986,1987) and Szujko-Lacza and Kovacs (1993). cData from Mahunka (1981,1983) and Szujko-Lacza (1982).

dData from Hazlett (1998) and Lavigne et al. (1991); arthropod data are for insects only. eData from G. Parsons et al. (1991). fData from Sharkey (2001).

gData from Garrison and Willig (1996), W. Lawrence (1996), and Reagan et al. (1996). hData from Mahunka (1991).

'Data from Covich and McDowell (1996); no vascular plants represented in this headwater stream.

jData from Benedek (1988).

This measure of diversity accounts for the typical increase in number of species with increasing sample area or number of individuals.

Species richness for many plant and animal groups increases from high latitudes to lower latitudes and from smaller, more isolated islands to larger islands near continents (MacArthur and Wilson 1967, Magurran 2004, Stiling 1996). Richness also increases from harsh or frequently disturbed ecosystems that restrict richness to more productive ecosystems that provide a greater number of niches but usually declines again in very productive ecosystems (Tilman and Pacala 1993). Species diversity appears generally to peak at intermediate levels of disturbance (the intermediate disturbance hypothesis) as the result of a combination of sufficient resources and insufficient time for competitive exclusion (Connell 1978, Huston 1979, Lubchenco 1978, Pickett and White 1985, Sousa 1979). Insect diversity may reflect primarily the diversity of plants, which affects diversity of host resources and habitat structure (Curry 1994, Magurran 2004, Stiling 1996).

The various species in a community are not equally abundant. Usually a few species are abundant and many species are represented by only one or a few individuals. The distribution of numbers of individuals among species (evenness) is a measure of each species' importance. Rank-abundance curves are a commonly used method of presenting species abundance data (Magurran 2004). Four rank-abundance patterns are most commonly used for comparison among different communities (Fig. 9.1). The geometric model (or niche-preemption hypothesis) describes a community in which successively less abundant species use the same proportion of resources available after preemption by the more abundant species. This situation is predicted to occur when species arrive in an unsaturated community at regular time intervals and exploit a fraction of the remaining resources. The log series model is closely related to the geometric model but is predicted to occur when the time intervals between species arrival are random rather than regular. The log normal model has been shown to be widely applicable because this distribution results mathematically from random variation

Rank Abundance Species

Typical shapes of four rank-abundance models. Species are ranked from most to least abundant. Redrawn from Magurran (1988).

Typical shapes of four rank-abundance models. Species are ranked from most to least abundant. Redrawn from Magurran (1988).

among a large number of factors producing a normal distribution. In natural communities, the large number of environmental factors affecting species abundances fulfills this condition. This condition also can be met by increasing numbers of species randomly partitioning available niches. The broken stick model reflects relatively uniform use of resources among species in the community. Generally, as richness and evenness increase, the rank-abundance pattern shifts from a geometric pattern to a log pattern and finally to a broken stick pattern. Disturbances and other environmental changes can alter rank-abundance patterns (Figs. 9.2 and 9.3) (Bazzaz 1975, Kempton 1979).

Richness and evenness have been combined mathematically in various ways to calculate diversity indices based on proportional abundances of species (e.g., Magurran 2004, Stiling 1996). Two indices have been used widely, the ShannonWiener, or Shannon (often incorrectly referred to as the Shannon-Weaver) index, and Simpson's index. The two indices differ in their emphasis on species richness (Shannon-Wiener) or abundance (Simpson's).

The Shannon-Wiener index assumes that individuals are randomly sampled from an effectively infinite population and that all species are represented in the sample. Diversity (H) is calculated as follows:

Rank Species Abundance Curves

ICr2"-

Species Sequence

| Rank-abundance curves for old fields representing five postabandonment ages in southern Illinois. Open symbols are herbs, half-open symbols are shrubs, and closed symbols are trees. From Bazzaz (1975) with permission of the Ecological Society of America.

ICr2"-

Species Sequence

| Rank-abundance curves for old fields representing five postabandonment ages in southern Illinois. Open symbols are herbs, half-open symbols are shrubs, and closed symbols are trees. From Bazzaz (1975) with permission of the Ecological Society of America.

Rank Abundance Plots

Change over time in rank abundance of plant species in an experimental plot of permanent pasture at Rothamsted, United Kingdom, following continuous application of nitrogen fertilizer since 1856. Species with abundances < 0.01% were recorded as 0.01%. From Kempton (1979) with permission from the International Biometric Society.

Change over time in rank abundance of plant species in an experimental plot of permanent pasture at Rothamsted, United Kingdom, following continuous application of nitrogen fertilizer since 1856. Species with abundances < 0.01% were recorded as 0.01%. From Kempton (1979) with permission from the International Biometric Society.

where pi is the proportion of individuals found in the ith species. Values generally fall in the range 1.5-3.5, rarely surpassing 4.5. If the rank-abundance pattern follows a log normal model, 105 species are necessary to produce a value of H'> 5. If the index is calculated for a number of samples, the indices will be normally distributed and amenable to use of parametric statistics, including ANOVA (analysis of variance), to compare diversities among sets of samples (Magurran 2004) (e.g., to evaluate the effects of ecosystem change; Fukami et al. 2001). If all species were equally abundant, a maximum diversity (Hmax) can be calculated as ln S, where S is the total number of species. The ratio of observed to maximum diversity is a measure of evenness.

When randomness cannot be assured (e.g., data from light trapping, with species representation based on differential attraction to light), the Brillouin index is a more appropriate measure of diversity (Magurran 2004). This index (HB) is calculated as follows:

where N is the total number of individuals and ni is the number of individuals in the ith species. Values of this index rarely exceed 4.5 and generally are correlated with, but lower than, Shannon indices for the same data.

Simpson's index differs from the Shannon-Wiener and Brillouin indices in being weighted toward the abundances of the most common species, rather than species richness (Magurran 2004). This index (D) is calculated as follows:

where ni is the number of individuals in the ith species and N is the total number of individuals. Diversity decreases as D increases, so Simpson's index generally is expressed as 1 - D or 1/D. Once the number of species exceeds 10, the underlying rank-abundance pattern is important in determining the value of D.

Diversity indices have been a tool for comparing taxonomically distinct communities based on their rank-abundance patterns. However, important information is lost when species diversities are reduced to an index (Magurran 2004). For example, a larger diversity index can reflect the influence of increased abundances of invasive or exotic species without conveying important information about the change in community integrity or function. Very different community structures can produce the same diversity index. Furthermore, ecologically unique communities are not necessarily diverse and would be lost if conservation decisions were made on the basis of diversity alone (Magurran 2004).

The large number of species represented by single individuals ("singletons") poses a dilemma (Novotny and Basset 2000). Should these be included in diversity calculations? Their presence may be accidental or reflect inadequate or biased sampling. Novotny and Basset (2000) found that singletons consistently represented 45% of herbivores sampled among plant species. Some singletons represented species that were more common on other plant species, whereas others represented species that were relatively rare on numerous host plants. Novotny and Basset (2000) concluded that singletons are an important component of communities and should not be excluded from community studies as an artifact or a group of negligible importance.

Diversity also can be measured as variation in species composition among communities or areas (b diversity). Several techniques have been developed to compare communities, based on their species compositions and rank-abundance patterns, across environmental gradients or between areas (Magurran 2004).

The simplest of these similarity measures are indices based on species presence or absence in the communities being compared. The Jaccard index (Cj) is calculated as follows:

and the Sorenson index (CS) is calculated as follows:

where j is the number of species found in both sites, a is the number of species in the first site, and b is the number of species in the second site. Neither of these indices accounts for species abundances.

Three quantitative similarity indices have been used widely. A modified version of the Sorenson index (CN) is calculated as follows:

where jN is the sum of the lower of the two abundances for each species found in both sites, aN is the total number of individuals in the first site, and bN is the total number of individuals in the second site. Most quantitative similarity indices are influenced strongly by species richness and sample size. The Morisita-Horn index (CmH) is influenced less by species richness and sample size but is sensitive to the abundance of the dominant species. Nevertheless, it may be generally a satisfactory similarity index (Magurran 2004). This index is calculated as follows:

where aN is the total number of individuals in the first site, ani is the number of individuals of the ¿th species in the first site, and da = Sani2/aN2. The Bray-Curtis Similarity Index also has been shown to be effective and robust (Minchin 1987). This index is calculated as follows:

where n is the number of species and Xij and Xik are the number of individuals of the ¿th species at sites j and k, respectively (Cartron et al. 2003).

More recently, multivariate statistical techniques have been applied to comparison of communities. Cluster analysis can be performed using either presence-absence or quantitative data. Each pair of sites is evaluated on the degree of similarity, then combined sequentially into clusters to form a dendrogram with the branching point representing the measure of similarity (Figs. 9.4 and 9.5). Ordination compares sites on their degree of similarity, then plots them in Euclidian space, with the distance between points representing their degree of similarity (Figs. 9.6 and 9.7). Ordination techniques include principal components analysis (PCA), detrended correspondence analyses (DCA), and nonmetric multidimensional scaling (NMS).

Minchin (1987) evaluated several commonly used ordination techniques for sensitivity to sampling pattern, data distribution, and geometric distortion. PCA and principle coordinates analysis both suffered from curvilinear distortion, and DCA lacked robustness to variation in sampling pattern and response model. NMS was shown to be the most robust ordination method and is becoming more widely used in ecological studies.

Both cluster and ordination techniques can indicate which species or environmental factors contribute most to the discrimination of groupings. Indicator species analysis (Dufrene and Legendre 1997) is another method that can be used to identify species or groups of species that characterize groups of sites, based on ecological gradients or treatments, by combining the frequency of a species occurrence in a particular site category and its degree of restriction to that site category. Dufrene and Legendre (1997) compared this method with

Dendrogram of similarity for dung beetles in clearcuts, 1 ha and 10 ha forest fragments, and contiguous forest. From Klein (1989) with permission from the Ecological Society of America.

Dendrogram of arthropod community similarity in canopies of four old-growth conifer species at the Wind River Canopy Crane Research Facility in southwestern Washington. AB, Abies grandis (grand fir); PS, Pseudotsuga menziesii (Douglas fir); TS, Tsuga heterophylla (western hemlock); and TH, Thuja plicata (western redcedar). Data from Schowalter and Ganio (1998).

Detrended correspondence analysis ordination of dung beetle assemblages in clearcuts, 1 ha and 10 ha forest fragments, and contiguous forest. From Klein (1989) with permission from the Ecological Society of America.

H

H

H

G

C

G r G G

DD

C

C

C

Second Principal Component

Principle components analysis ordination of arthropod communities in canopies of four old-growth conifer species at the Wind River Canopy Crane Research Facility in southwestern Washington. G, grand fir (Abies grandis); D, Douglas fir (Pseudotsuga menziesii); H, western hemlock (Tsuga heterophylla); and C, western red cedar (Thuja plicata). From Schowalter and Ganio (1998) with permission from CAB International.

clustering and ordination techniques to identify carabid beetle species characterizing combinations of soil moisture and alkalinity represented by 69 sites in Belgium.

The significance of differences among groups of points representing sites, treatments, etc., can be analyzed using multiple response permutation procedures (MRPP) (Biondini et al. 1988). This method measures the separation among weighted means of points in a priori groups and tests the probability of occurrence of this mean relative to other possible separations with the same size structure that could have occurred for these points (Biondini et al. 1988).

Oplan Termites

Oplan Termites

You Might Start Missing Your Termites After Kickin'em Out. After All, They Have Been Your Roommates For Quite A While. Enraged With How The Termites Have Eaten Up Your Antique Furniture? Can't Wait To Have Them Exterminated Completely From The Face Of The Earth? Fret Not. We Will Tell You How To Get Rid Of Them From Your House At Least. If Not From The Face The Earth.

Get My Free Ebook


Responses

  • auli
    How to calculate the data of insect biodiversity?
    7 years ago
  • gilda
    Are arthropods the least abundant species?
    6 years ago
  • peony
    How to do a rank abundance curve?
    5 years ago

Post a comment