Assessing Biodiversity

2.2.1 Definitions of biodiversity

Biodiversity is commonly understood to describe all aspects of variation in living organisms. To be scientifically meaningful, however, diversity has to be both qualified and quantified. The first requirement, qualification, refers to the level of assessment whether it be ecosystem complexity, species richness, or genetic variation. This last category, genetic variation, is the fundamental issue as it represents the only means of assessing the heritable properties that result from DNA variation upon which all biodiversity ultimately depends. Unfortunately, information at the molecular level is not usually available in sufficient detail for ecological field studies. Assessing biodiversity is therefore frequently carried out using various visible approximations such as ecosystem complexity, variation in life-forms and strategies within communities, numbers of species, subspecies and ecotypes or other appropriate estimations of population variation. This can also include the reproductive biology of species, whether or not they are polymorphic, inbreeding or outbreeding, or reproducing entirely vegetatively. Any or all of these characteristics can be useful when comparing differences in plant populations between regions.

A flexible and simple definition of biodiversity that can be readily applied in the field is the number of different taxonomic items that are found in any specific area (or volume). However, when using even this basic measure, some consideration has to be given to the method of sampling and not least to the species accumulation curve or species area curve as it has long been known in plant ecology. This, the oldest known pattern in ecology, describes the relationship between the area under examination and the number of species present and in most cases fits the equation:

S = cAz where S is the number of species, A the area sampled and c and z are constants. The exponent z varies between 0.15 and 0.30 independently of the biome and taxa under study (Calow, 1998). As with many mathematical relationships in ecology the concept of the species accumulation curve has been refined for comparative use under strictly defined ecological

Table 2.1. Definitions of biodiversitya

Alpha diversity The diversity of species within a particular habitat or community (S) where (S) = species • unit area

Beta diversity A measure of change in species along a gradient from one habitat to another. One possible measure of beta diversity (B) is (B) = (g(H) + l(H))/2S

where g(H) is the number of species gained along the gradient H and l(H) the number of species lost along the gradient H.

Gamma diversity The richness in species of a range of habitats in a geographical area and dependent on the alpha diversity of the habitats it contains and the extent of beta diversity between them. Thus

Sr = (Bn + 1)(Bm + 1), where Bn is beta diversity and Bm is gamma diversity.

a There are many mathematical assessments of biodiversity with varying properties. The above example was chosen as it was used in the chapter by Cowling et al. (1992) on the biodiversity of Fynbos discussed below. Source: (Lincoln et al., 1998).

conditions. For comparisons of different species, accumulation curves have to be meaningful and therefore should be based on areas which have what is termed continuum vegetation, where there is continuous plant cover and only one individual at any one point. Each individual therefore has a finite area and, when viewed from above, the ground is everywhere obscured by vegetation (Williamson, 2003). Convenient as this might be in simple agricultural situations, or hypothetical models, these necessary rigorous conditions are not readily found in the field. The extent to which the vegetation is patterned and made up of patches of varying size also has an enormous influence on the species accumulation curve (Greig-Smith, 1983). It follows therefore that in comparing biological diversity between different areas it has to be recognized that both the nature of the vegetation and the method of recording can cause significant alterations. A variety of statistical tests are available which allow an assessment to be made as to when species accumulation curves can be considered as defining a uniform sampling process for a reasonably stable situation (Colwell & Coddington, 1995). When this can be established it is possible to record species richness for specific sites in terms of alpha diversity (species per unit area; Table 2.1).

In marginal areas where vegetation cover tends to be irregular or distinctly patterned, simple estimations of alpha biodiversity may not be suitable (Fig. 2.2). More appropriate for marginal areas and fundamentally different from alpha diversity is beta diversity (Table 2.1). Here vegetation is compared along a gradient from one habitat to another. Quantification of variation between habitats is not a direct count of taxonomic richness but is a comparison of the variation between habitats using a suitable index of similarity giving a statistic that is inversely related to diversity. In a heterogeneous region with much interhabitat variation the similarity coefficients will be low and the communities of that region will be considered ecologically as showing high beta diversity. This represents a diversity that depends on the heterogeneity of the area under consideration.

Other units of diversity sometimes used in ecological studies include gamma and delta diversity. Gamma diversity is usually defined as richness of species over a range of habitats in a geographical community and is dependent on both the alpha diversity of the habitats and the extent of beta diversity between them. Some authors also attempt to differentiate between gamma and delta diversity in which gamma diversity denotes variation between different locations within a community and delta diversity refers to differences between landscapes. However, this level of distinction can confuse elements of environmental and geographical variation (Cowling et al., 1992) and the finally derived statistics are not clearly related to any physical reality.

Fig. 2.2 An extreme case of naturally patterned vegetation at Ny Alesund, Spitsbergen. A polar semi-desert community in Svalbard, Norway (78° 56.12' N, 11° 50.4' E) with clonal patches of Dryas octopetala, which has been studied in relation to the potential effects of climatic warming and increased nutrient availability (see Wookey et al., 1995).

Fig. 2.2 An extreme case of naturally patterned vegetation at Ny Alesund, Spitsbergen. A polar semi-desert community in Svalbard, Norway (78° 56.12' N, 11° 50.4' E) with clonal patches of Dryas octopetala, which has been studied in relation to the potential effects of climatic warming and increased nutrient availability (see Wookey et al., 1995).

Assessments of genetic diversity face the same problems as taxonomic diversity. At the gene level distinctions have to be made between allelic richness and evenness in allelic frequencies (Frankel et al., 1995). Formulae for estimating degrees of similarity and difference are numerous and their particular value can depend on the nature of the items being compared either in studies of genetic geography or in assessments of genetic variation (Hawksworth, 1995).

All assessments of biodiversity depend on the particular aspect of biological variation that is being sampled. It does not necessarily follow that this has always to be based merely on species. For some purposes different taxonomic levels are appropriate. This is particularly relevant in relation to plants where species are less rigidly defined than in animals. For plant communities, biodiversity can be usefully assessed and compared between sites in terms of families, genera, species, populations, gene frequencies, or other molecular markers of variation in evolutionary history. If comparisons are required at a global level, there is a case for using families or genera, but if detail is needed in relation to specific sites, attention needs to be given to subspecies and ecotypes as it is at these levels that adaptation takes place and where the potential of populations to evolve and undergo speciation resides. There are even cases where species survival in marginal areas may be enhanced by not undergoing further speciation and maintaining instead a wide range of polymorphic, interfertile populations. Examples of this aspect of biodiversity are discussed in detail in relation to some widespread and ancient diploid arctic species (Section 6.7).

With the development of molecular biology it is now possible not just to identify particular ecological races or ecotypes, but also to detect variation within species or subspecies in terms such as allelic hetero-zygosity or DNA variation as observed in the nucleus, the mitochondrion and the chloroplast. The extent of the variation at a molecular level can be mapped, and provides a quantifiable assessment of current variability. The application of cladistic methods can also reveal the genetic and biogeographical history of particular species or populations (Section 6.4.2).

2.2.2 Problems of scale and classification

Scientifically, it is difficult to make comparisons of plant biodiversity on a global scale as every region of the world has plant communities that have evolved under different circumstances. Listing of areas with the greatest number of endemic species is an indication of a long uninterrupted history of speciation. However, when as in certain cases many of the endemic species are apomictic, they are not usually contributing actively to further genetic modification and are merely testimony to past evolutionary activity.

Modern biological technology has created the possibility of having a range of different interpretations of biodiversity. Similarly, ecological studies have some degree of choice when comparing diversity in plant communities. Instead of just contemplating the species richness of the tropics as compared with temperate and arctic zones (which were issues that attracted Darwin and his contemporaries) it is now possible to look at specific examples of intrazonal variation at the community, species or subspecies level and make assessments of those factors which either favour or discourage biodiversity. In areas where differences are readily apparent in species frequencies, comparisons are made without further subdivision. In others, as for example in the Arctic, where species numbers are low, comparisons can be made at the subspecies or population level.

Ecological classifications have long been used to create order by grouping plants by their collective and often contrasting responses to defined environments. Calcicoles and calcifuges, halophytes and glycophytes, eutrophic and oligotrophic are descriptive terms which reflect contrasting and frequently incompatible adaptations to diametrically opposed habitats. Adaptation to one set of conditions usually proves maladaptive for the opposing set. Plants that inhabit dry soils need reducing conditions at their root surfaces in order to convert insoluble ferric iron to the soluble ferrous form. However, plants in flooded habitats need to have oxidizing conditions at their root surfaces to precipitate ferric iron from ferrous iron so that iron toxicity does not result from an excessive uptake of ferrous iron. These are opposing strategies and cannot coexist in the same root system.

The development of computer models to imitate plant behaviour has created renewed interest in grouping plants into functional types (Smith et al., 1997). For computer simulations of vegetation responses to changing environmental conditions some degree of functional aggregation, sometimes referred to as scaling-up, is obviously essential (Section 3.4). Even within well-defined ecological groups such as halophytes or calcicoles complications can arise from the unending variety of adaptations and evolutionary strategies that exist in response to any particular stress. Halophytes can be divided into osmo-regulators and osmo-conformers, and different calcicole species differ in their responses to the physical and chemical aspects of adapting to calcium-rich soils. Eutrophic habitats can present an equally heterogeneous set of environmental conditions. It cannot even be generalized that all populations of the same species will fall into any one category. Different ecotypes of the same species can be found in relation to drought, salt, flooding and other stresses. Most species have different ecotypes in relation to their phenology, a fact which was already well known to Roman farmers who knew that seed corn could not be transported successfully from one part of their empire to another (White, 1970).

To ignore this level of variation and to confine observations to only the more obvious phenotypic short-term responses of plants to the environment is to ignore the many subtle genotypic responses which will eventually determine the long-term evolutionary responses of species to environmental change. A striking example of the above argument has already been discussed in relation to the purple saxifrage (Saxifraga oppositifolia) which in the High Arctic occurs with distinct ecotypes which have divergent strategies in relation to differences in growing season length. This is an example where scaling-up would fail to recognize the fundamental mechanisms that allow polymorphic species to adapt readily to changing environments. Short-term phenotypic responses to environmental perturbation may be detected by the process of scaling up and looking at the effects of climate change on forest canopies or grassland productivity. The long-term effects of environmental change will, however, act on the genotype and therefore examination of the physiological and genetic responses of individual plants and populations should not be ignored (see also Section 6.6).

2.2.3 Variations in assessing genetic variation

An example of how different estimations of genetic variation can be obtained within one endemic species, surviving in a very limited area is seen in the subarctic Scottish endemic Primula scotica - a possible glacial relict species (Fig. 2.3). A study of five sites in Orkney and nine from the Scottish mainland revealed variation between individuals at only one of 15 enzyme-encoding loci examined. In addition a survey of DNA sequence variation found no genetic diversity, either within or between a subsample of four populations (Glover & Abbott, 1995). In this study of individual genes the plants exhibited a 'fixed' level of heterozygosity per individual, indicating that it is of allopolyploid origin. Thus, despite the high level of heterozygosity per individual it might be concluded that there is almost a complete lack of genetic diversity both within and between populations. However, in a separate study of the same species, within the same small areas of its occurrence in northern Scotland and Orkney, it was shown from an examination of both growth and form that plants grown from seed collected from different populations showed considerable variation (Ennos et al., 1997). This latter study of character responses looked at aspects of plant variability which

Fig. 2.3 The Scottish primrose (Primula scotica). A possible glacial relict species endemic to Scotland and Orkney possessing limited genetic diversity between and within populations when examined for specific alleles yet exhibiting marked genetic variation in multi-gene controlled variation in growth and form (see text inset of P. scotica; scale — 1 cm).

Fig. 2.3 The Scottish primrose (Primula scotica). A possible glacial relict species endemic to Scotland and Orkney possessing limited genetic diversity between and within populations when examined for specific alleles yet exhibiting marked genetic variation in multi-gene controlled variation in growth and form (see text inset of P. scotica; scale — 1 cm).

are multi-gene controlled and do not appear to be so severely limited as enzymatic variations under control from specific single genes. Assessments of genetic variability can therefore differ depending on what is being assessed, and global statements projected from any one particular facet of variation, if not properly explained, can be potentially confusing.

0 0

Post a comment