1. Global Biodiversity
… and its decline.
BCB 705:
Biodiversity

2. Oh Dear!
No one knows how much biodiversity there is or how much will be lost.
The multiple levels of biodiversity mean that no single measurement for biodiversity is possible.
This chapter briefly considers measures of ecosystem and genetic diversity before concentrating on the species inventory and estimates of global species numbers and species extinction rates.
The present species inventory contains the 1.4—1.8 million species already described but does not contain much information about most of these species.
No one knows how much biodiversity there is or how much will be lost. The multiple levels of biodiversity mean that no single measurement for biodiversity is possible (Wikipedia Contributors 2006). This chapter briefly considers measures of ecosystem and genetic diversity before concentrating on the species inventory and estimates of global species numbers and species extinction rates. The present species inventory contains the 1.4—1.8 million species already described but does not contain much information about most of these species (Dobson 1996, Lovejoy 1997, Stork 1997).

3. Biodiversity at the Ecosystem Level
It is difficult to set boundaries for an ecosystem.
There is no standard classification system for ecosystems.
Ecosystems are usually classified at two levels:
Globally
Locally/regionally.
Existing global classifications are inadequate.
Global ecosystem classification is of little value at the scales that are important for conservation.
Remote sensing provides ways to assess and monitor vegetation structure and phenology – aspects of ecosystems.
Inventorying ecosystems is complicated by the fact that it is difficult to set boundaries for an ecosystem (Hawksworth & Kalin-Arroyo 1995), so there is no standard classification system for ecosystems (Hawksworth & Kalin-Arroyo 1995). Ecosystems are usually classified at two levels: globally (with climatic determinants) and locally/regionally (with vegetation and species diversity determinants) (Hawksworth & Kalin-Arroyo 1995). The existing global classifications are inadequate (Bisby 1995). Global ecosystem classification is of little value at the scales that are important for conservation (Hawksworth & Kalin-Arroyo 1995). Remote sensing provides ways to assess and monitor vegetation structure and phenology – aspects of ecosystems (Hawksworth & Kalin-Arroyo 1995). The picture shows the Normalised Difference Vegetation Index (NDVI) for Africa for the months (starting at the top left) January, April, July and October.
Additional Notes
Extract from Wikipedia ~ Normalized Difference Vegetation Index (NDVI) is determined by measuring the ratio between visible and near infrared light reflected by the earth surface from satellites. One such satellite is employed by NOAA. It has a sensor called Advanced Very High Resolution Radiometer (AHVRR) which measures wavelengths of light ranging from 0.55–0.70 and 0.73–1.0 micrometers. If the reflecting surface is covered by green dense vegetation most of the visible light is absorbed and nearly all infrared light is reflected resulting in a high NDVI. The opposite happens if the vegetation is not green or the surface is only sparsely covered.
In general the equation for NDVI is: NDVI = (NIR – R)/(NIR + R)
Where R is the surface reflectance value for the red band and NIR is the surface reflectance value for the near infrared band.
The remote sensing course will provide more information.

4. Biodiversity at the Genetic Level
Genetic diversity may be considered/compared at three levels :
Variability between individuals within a population,
Variability between populations within a species,
Diversity between species.
Heterozygosity is used to quantify the first two levels listed above. Comparisons of heterozygosity between species do not quantify how different the species are, merely how different their internal variability is.
The proportion of heterozygosity depends on:
The evolutionary rates of the proteins or DNA used to measure the variability,
The breeding system of the organism,
The degree of connectivity between the populations.
Genetic diversity may be considered/compared at three levels (Hawksworth & Kalin-Arroyo 1995): variability between individuals within a population, variability between populations within a species and diversity between species (Hawksworth & Kalin-Arroyo 1995).
Heterozygosity (the proportion of loci that carry two or more alleles) is used to quantify the variability between individuals within a population and variability between populations within a species (Hawksworth & Kalin-Arroyo 1995). Comparisons of heterozygosity between species do not quantify how different the species are, merely how different their internal variability is. The picture shows heterozygous parents (both colours) and their homozygous (one colour) and heterozygous offspring. The picture is simplified to show only one gene expressing a single trait. The proportion of heterozygosity depends on: the evolutionary rates of the proteins or DNA used to measure the variability, the breeding system of the organism and the degree of connectivity between the populations (Hawksworth & Kalin-Arroyo 1995).

5. Problems with the Existing Species Inventory (1)
The precise number of recognized species is not known.
The lack of a single definition for a species.
It contains poor taxonomy as well as sound taxonomy.
Synonymy
No recognized central register of species.
Holotype (“type”) specimens are difficult to access.
The natural variation of a species is unknown – different forms may be given different names.
Determining the number of recognized species at any time is not given priority.
The precise number of recognized species is not known (Groombridge 1992, Hawksworth & Kalin-Arroyo 1995, Stork 1997). There are several reasons for this. One reason is the lack of a single definition for a species (Groombridge 1992, Bisby 1995, Hawksworth & Kalin-Arroyo 1995, Gaston 1996). Not all species definitions are comparable (Groombridge 1992, Gaston 1996). Using different species definitions to determine the number of species within a given taxon results in different total numbers of species for that taxon (Gaston 1996, Williamson 1997), for example using a species definition similar to that used by botanists on birds more than doubles the number of species identified (Williamson 1997). Another reason is that the quality of the taxonomy is not consistent. The inventory contains poor taxonomy as well as sound taxonomy (Groombridge 1992, Hawksworth & Kalin-Arroyo 1995). The present inventory incorporates unknown amounts of synonymy. Synonymy refers to a single species being described and named more than once (Groombridge 1992, Hawksworth & Kalin-Arroyo 1995, Stork 1997). Several factors contribute to the occurrence of synonymy. Firstly, there is no recognized central register of species though there are registers for some groups (Stork 1997). Secondly, holotype (“type”) specimens may be difficult to access as they may occur in collections geographical far from the site at which they were discovered and traveling to view relevant collections is expensive – maybe prohibitively so (Stork 1997). Finally, the natural variation of a new species is unknown – different forms may be given different names (Stork 1997). Determining the number of recognized species at any time is not given priority, possibly because there is not much biological significance in the data (Groombridge 1992).

6. Problems with the Existing Species Inventory (2)
The existing partial inventory is biased towards:
Species that appeal to humans,
Pests,
Organisms not requiring complex procedures or expensive equipment to study,
Larger size,
Easily distinguishable species that are readily sorted,
Species that are easily accessed.
The existing partial inventory is biased towards (Groombridge 1992): species that appeal to humans such as the giant panda (Ailuropoda melanoleuca), pests such as the cat flea (Ctenocephalides felis), organisms not requiring complex procedures or expensive equipment to study, larger size (the smaller the organism the less likely it is to be studied), easily distinguishable species that are readily sorted and species that are easily accessed (Groombridge 1992).

7. Gaps in the Species Inventory
Soil organisms
Tropical forest canopies
Marine benthic organisms
Parasites
Nematodes
Fungi and microorganisms
Terrestrial arthropods
Gaps in the inventory may be considered in terms of physical location and in terms of the categories of organisms. Usually the physical localities are expected to yield diversity in the categories of organisms that are not well inventoried.
Fitter et al. (2005) identified about 500 species of soil organisms (bacteria, protozoa and nematodes) at a single site in Scotland (Fitter et al. 2005). This high alpha diversity will only lead to a large contribution to the global total if the species turnover (beta and gamma diversity) is also high.
The ‘hype’ about tropical forest canopies is not backed by clear evidence (Groombridge 1992, Hawksworth & Kalin-Arroyo 1995). There is a possibility that the tropical forest floor has greater diversity than the canopy (Groombridge 1992, Stork 1997).
Marine benthic organisms show high alpha diversity but this would not lead to high global species totals unless the turnover of species (beta and gamma diversity) is also high. Range sizes that are known are larger than those found on land and do not appear to support the idea of a high species turnover (Groombridge 1992, Hawksworth & Kalin-Arroyo 1995).
The total richness of parasites and other symbionts will depend on levels of host specificity (Groombridge 1992, Hawksworth & Kalin-Arroyo 1995). Levels of parasitism depend on host size, host defenses and the population structure of the host – if the potential host is difficult to find it will not have many obligate parasites (Groombridge 1992)
Nematodes may potentially be found as parasites, in marine sediments and in soils (Groombridge 1992, Hawksworth & Kalin-Arroyo 1995) but little is known about species turnover (Groombridge 1992).
Fungi have high alpha diversity but there is insufficient information on latitudinal gradients and factors concerning turnover rates such as range size (Groombridge 1992, Hawksworth & Kalin-Arroyo 1995). Species concepts are difficult to apply to microorganisms and there is little information on range sizes (Groombridge 1992). Perceptions of potential bacterial diversity have grown from studies suggesting that the numbers of unculturable bacteria are much greater than those of culturable bacteria (Hawksworth & Kalin-Arroyo 1995).
Plenty of evidence exists of high terrestrial arthropod diversity at most scales (the smallest scale is excluded). Insects formed the largest portion of all described species (Groombridge 1992, Hawksworth & Kalin-Arroyo 1995, Erwin 1997).
Clockwise from the top left, the pictures show a soil profile, the canopy of a rainforest, marine sediments, an insect larva covered in parasitic wasp pupae and a nematode worm.

8. Numbers (in Thousands) of Described Species
The numbers quoted here are from Groombridge (1992) and Hawksworth & Kalin-Arroyo (1995). Hawksworth & Kalin-Arroyo (1995) base their figures on Groombridge (1992) with updates. Please note that Groombridge (1992) lists vertebrates and Hawksworth & Kalin-Arroyo (1995) list chordates. Since vertebrates are a subset of chordates, the latter term was preferred. Differences in the numbers reflect a combination of new species, discovered synonymies and the year to which the authors counted (Groombridge 1992, Hawksworth & Kalin-Arroyo 1995).
* Groombridge (1992) lists vertebrates, not all chordates.

9. Erwin’s Estimate of 30 million Arthropod Species
Erwin (1982) estimated that the global total of arthropod species was as large as 30 million.
Erwin’s ‘data’:
955+ beetles excluding weevils found in one tree species canopy.
Weevil numbers ≈ leaf-beetles numbers so ~ 206 weevils per tree species.
About tropical tree species.
Erwin’s assumptions:
Host specificity about 13.5 % of the total number of beetle species per tree canopy.
Beetles make up 40 % of tropical canopy arthropods.
Forest canopy to forest floor ratio = 2:1 (Erwin added a third of the number of canopy species to the total number of canopy species).
Erwin (1982) estimated that the global total of arthropod species was as large as thirty million. He based his estimate on a single study of the beetles collected by insecticide fogging the canopy of Luehea seemannii (a tropical evergreen tree) in Panama with some information from a study in Brazil (weevil numbers) (Erwin 1982, Groombridge 1992, Stork 1997). This estimate is used to demonstrate some of the problems with estimates based on single datasets.
The following data were used to make the estimate. Three seasons of sampling nineteen Luehea seemannii trees yield 955+ species of beetles excluding weevils (Stork 1997). From Brazil, he obtained information that weevil numbers ≈ leaf-beetles numbers so suggested ~206 weevils per tree species. Enquiry supplied the estimate of about tropical tree species (Stork 1997).
Erwin made three assumptions. The first was that about 13.5 % of the total number of beetle species per tree canopy were host specific. The second was that beetles make up 40 % of tropical canopy arthropods. The third was that the forest canopy to forest floor ratio is two to one. Erwin actually added a third of the number of canopy species to the total number of canopy species (Stork 1997). Erwin’s actual assumption was a tropical canopy to tropical floor arthropod species ratio of three to one though his stated assumption was at least two to one.

10. Calculating Erwin’s Estimate
955 (beetle species – weevil species) (weevil species) = beetle species per tree species canopy. Round up to beetle species per tree species canopy.
13.5 % of = 162 host specific beetle species per tree species canopy – 162 = beetle species that are transient.
162 host specific beetle species per tree species canopy * tropical tree species = host specific beetle species in the tropical tree canopy. Add transient species = beetle species in the tropical tree canopy.
Beetles = 40 % of arthropods / 4 * 10 = arthropod species in the tropical tree canopy.
Add one third for forest floor arthropods = tropical forest arthropod species .
Estimate non-tropical arthropod species about then the global total is ≈ 30 million arthropod species .
955 (beetle species minus weevil species) plus 206 (weevil species) equals beetle species per tree species canopy. Round up to beetle species per tree species canopy. If 13.5 % of the beetle species per tree species canopy are host specific then there are 162 host specific beetle species per tree species canopy. The remaining beetle species are transient (Stork 1997). Multiplying the host specific beetle species by the estimated number of tropical tree species yields host specific beetle species in the tropical tree canopy. Add the transient species and there are beetle species in the tropical tree canopy. If beetles make up 40 % of all arthropods then there are arthropod species in the tropical tree canopy. Adding one third of the total tropical tree canopy species to account for the tropical forest floor arthropods (Stork 1997) (note that this actually results in a three to one canopy to floor ratio) gives 26 935 951 tropical forest arthropod species. If the number of non-tropical arthropod species was estimated at about then the global total is approximately thirty million arthropod species.

11. More Recent Data and the Impacts on Erwin’s Estimate
Temperate and provisional tropical findings suggest that host specificity is < 5 % (Stork 1997).
Though latitudinal variation in the proportions of species from different guilds of insects is probable, the figures from widely spread studies suggest that beetles make up 20—25 % of the total number of arthropods (Stork 1997).
Raw data from two studies suggest that the canopy to forest floor arthropod species ratio should at least be reversed (1:2 not 2:1). There is also evidence to suggest that a large portion of the fauna will be found in both ecotones (Groombridge 1992, Stork 1997).
5 % of = – 60 = * = * 4 = * 3 = = arthropod species in the world.
Changing the ratios used by Erwin makes a big impact on the total estimate ( vs ).
For Erwin’s assumption of 13.5 % host specificity, temperate and provisional tropical findings suggest that host specificity is less than 5 % (Stork 1997). Though latitudinal variation in the proportions of species from different guilds of insects is probable, the figures from widely spread studies suggest that beetles make up 20—25 % of the total number of arthropods, not the 40 % assumed by Erwin (Stork 1997). Raw data from two studies suggest that the canopy to forest floor arthropod species ratio should at least be reversed (1:2 not 2:1 as Erwin suggested). There is also evidence to suggest that a large portion of the fauna will be found in both ecotones (Groombridge 1992, Stork 1997). Using these figures and following the calculations shown before, the estimate of the global total for arthropod species becomes arthropod species in the world. Changing the ratios used by Erwin makes a big impact on the total estimate ( vs ).

12. Problems with Single Sample Extrapolations
All estimates are affected by the accuracy of the figures used. The accuracy/completeness of counts from a single sample is open to question.
Calibration of ratios is generally poor or non-existent. Erwin’s estimate is a case in point.
The assumption that the relationships used in the extrapolation scale evenly is often unstated.
All estimates are affected by the accuracy of the figures used. The accuracy/completeness of counts from a single sample is open to question (Stork 1997). The calibration of ratios for single sample extrapolations is generally poor or non-existent. Erwin’s estimate is a case in point (Groombridge 1992). There is an often unstated underlying assumption that the relationships used in the extrapolation scale evenly (Groombridge 1992).

13. Useful Ratios for Estimation
All extrapolations from existing data involve one or more assumptions.
All ratios need to be calibrated to support the assumption that the ratio holds under different conditions.
Six categories of known to unknown species richness ratios are useful for extrapolation:
Group A to group B
Subgroup to group
Sample to inventory
Area A to area B
Smaller scale to larger scale
Habitat/stratum to inventory.
All extrapolations from existing data involve one or more assumptions. The main one being that a ratio occurring in a known situation is also true in an unknown situation (Groombridge 1992). All ratios need to be calibrated to support the assumption that the ratio holds under different conditions. Samples used to generate ratios are calibrated against inventories. Six categories of known to unknown species richness ratios are useful for extrapolation (Hawksworth & Kalin-Arroyo 1995): “group A to group B (e.g. butterflies to beetles), subgroup to group” (e.g. beetles to insects), “sample to inventory (e.g. of a site), area A to area B (e.g. site A to site B), smaller scale to larger scale (e.g. site to country)” and “habitat/stratum to inventory (e.g. of a site)” (p 121 Hawksworth & Kalin-Arroyo 1995).

14. Other Forms of Estimation
Time-series of species descriptions may be used to estimate future growth within groups of organisms.
The empirical rule that numbers of species increase with decreasing body size may be used to extrapolate for larger organisms but appears to break down at lengths of less than one millimetre.
The proportions of species in the different trophic levels of the food web allow fairly reliable generalization without reference to host specificity.
The data on host specificity are insufficient for reliable estimation. Vegetation structure may yield better predictions of the numbers of parasites than the number of species does.
Specialist opinion depends on exposure to data on especially the richness of poorly studied regions. Specialists’ estimates tend to be conservative.
Time-series of species descriptions may be used to estimate future growth within groups of organisms. Application to groups that form major parts of the total biodiversity has not been successful and even for well known groups, the results may be misleading (Groombridge 1992, Hawksworth & Kalin-Arroyo 1995).
The inverse relationship between body size and number of species may be used to extrapolate for larger organisms but appears to break down at lengths of less than one millimetre (Groombridge 1992, Stork 1997). For the smallest organisms, the question of species definition becomes important. Dispersal by air or water is easier for these organisms so allopatric speciation is less likely (Hawksworth & Kalin-Arroyo 1995, Stork 1997).
The proportions of species in the different trophic levels of the food web allow fairly reliable generalization without reference to host specificity. The data on host specificity are insufficient for reliable estimation. Vegetation structure may yield better predictions of the numbers of parasites than the number of species does (Groombridge 1992).
Specialist opinion has usually not been systematically collected. A specialist’s estimates depend on their exposure to data on especially the richness of poorly studied regions (Groombridge 1992). Specialists’ estimates tend to be conservative (Groombridge 1992, Hawksworth & Kalin-Arroyo 1995).

15. Global Species Estimates (in Thousands)
All the estimates are in thousands of species (i.e. 4 = species). The figures quoted here are from Groombridge (1992) and Hawksworth & Kalin-Arroyo (1995). Please note that Groombridge (1992) lists vertebrates and Hawksworth & Kalin-Arroyo (1995) list chordates. Since vertebrates are a subset of chordates, the latter term was preferred. The probable accuracy of the estimates as listed on the far right uses the following set of definitions: ‘Good’ covers estimates that are “almost certainly accurate within a factor of two”, ‘Moderate’ refers to estimates that are “almost certainly accurate within a factor of five”, estimates regarded as having ‘poor’ accuracy are “almost certainly accurate within a factor of ten” and estimates that are “not certainly within an order of magnitude” are ‘very poor’ (p 118 Hawksworth & Kalin-Arroyo 1995).
* Groombridge (1992) lists the vertebrate subset of chordates.

16. Present vs. Background Extinction Rates
Species life spans and background extinction rates are estimated from the fossil record.
For mammals, a species life span is about one million years and the background extinction rate is about one species every two hundred years.
For organisms with adequate data from the fossil record, the average species life span is between five and ten million years which means a background extinction rate of about one species every thousand years.
The present overall extinction rate is estimated to be about 500 times the background extinction rate.
For birds, the present rate is about times the background rate.
Species life spans and background extinction rates are estimated from the fossil record. Estimations from the fossil record are uncertain, as the time resolution is rarely better than 103—104 years (Barbault & Sastrapradja 1995). For mammals, a species life span is about one million years and the background extinction rate is about one species every two hundred years.
For organisms with adequate data from the fossil record, the average life span is between five and ten million years which means a background extinction rate of about one species every thousand years (Barbault & Sastrapradja 1995). The present overall extinction rate is estimated to be at least 500 times the background extinction rate (Gaston & Spicer 1998). For birds, the present rate is about a thousand times the background rate (Barbault & Sastrapradja 1995).

17. Estimating Future Extinction Rates
Two principle forms of estimation of extinction rates exist:
Estimates based on rates of habitat loss and the species-area relationships from island biogeography.
Estimates based on Red Data lists take several forms.
Rates at which species change categories,
Species-by-species assessments,
Relative extinction rates between different taxa to predict the number extinctions.
Two principle forms of estimation of extinction rates exist. The first estimates extinction rates based on rates of habitat loss and the species-area relationships from island biogeography (Groombridge 1992, Barbault & Sastrapradja 1995, Smith et al. 1995, Dobson 1996). The second group of estimates relies on Red Data lists. Rates at which species change categories on Red Data lists may be used to determine extinction rates or extinction rates may be estimated using species-by-species assessments (Barbault & Sastrapradja 1995, Stork 1997). In a well documented location such as Britain, if the accuracy of the Red Data list status is of groups such as birds and invertebrates is comparable then relative extinction rates can be estimated. In Britain the mean relative extinction rate between birds and insects is If this ratio holds then since about 1 %of birds have become extinct since 1600, the ratio suggests that about 0.14 % of insects (about species if the total number of insect species globally is eight million) have become extinct. Testing this in Britain, 99 insect species have not been seen since Using the ratio suggests that eleven bird species should have vanished in the same period. This was found to be the case though two bird species had recolonised the island between 1800 and 1949 (Stork 1997).
Additional Notes
The species-area relationship is represented by the equation S = cAz where c and z are constants, S = the number of species and A = area (Dobson 1996).
Extract from Protea Atlas website at : IUCN Red Data Book Categories
EXTINCT (X): No longer existing in the wild.
ENDANGERED (E): In immediate danger of extinction if factors causing decline continue operating.
VULNERABLE (V): Likely to become endangered soon if factors causing decline continue operating.
CRITICALLY RARE (R): Not endangered or vulnerable at present, but might be at risk by localised threats.
INDETERMINATE (I): A temporary grouping when not enough information is available to put into endangered, vulnerable or critically rare categories, but it is reasonably certain that the species does indeed belong in one of these categories. Further data are needed to determine the status.
UNCERTAIN (U): A temporary grouping for unconfirmed reports suggesting inclusion in endangered, vulnerable or critically rare categories.
NO LONGER THREATENED: No longer included in the above categories due to an increase in population sizes or numbers, or due to the discovery of more populations or more individuals.
Some new categories are also listed on the website.

18. Problems with Estimates Based on Habitat Loss and Species-Area Relationships
The accuracy of such estimates is low because:
Detailed knowledge of species distribution and endemism is lacking,
Habitat loss is not evenly distributed,
The rate of habitat loss is uncertain,
Changes at a global level are not considered,
Genetic impoverishment is not considered,
The likely survival of species in modified habitats is uncertain,
The pattern of habitat loss is uncertain,
The species-area relationship varies between taxonomic groups,
Past disturbance and habitat loss are unknown,
Changes in future human behaviour are uncertain.
The accuracy of estimates based on habitat loss and species-area relationships is low because: detailed knowledge of species distribution and endemism is lacking though they are known to be unevenly distributed, habitat loss is not evenly distributed, the rate of habitat loss is uncertain, changes at a global level (such as climate) are not considered, genetic impoverishment (loss of genetic diversity through loss of local populations and/or decreasing population size) is not considered, the likely survival of species in modified habitats is uncertain, the pattern of habitat loss is uncertain – loss resulting in fragmentation increases species loss and protection of key areas reduces species loss, the species-area relationship varies between taxonomic groups, past disturbance and habitat loss are unknown, changes in future human behaviour are uncertain (Groombridge 1992, Barbault & Sastrapradja 1995).

19. Species Most Threatened with Extinction
Based on ecological theory, species with the following traits are most threatened with extinction:
Large organisms,
Those feeding highest in the food chain,
Those with chronically small population sizes,
Those with small ranges or distributions,
Those linked by biology to threatened habitats or ecosystems,
Those that evolved in isolation (e.g. island organisms),
Those with poor dispersal and colonization abilities,
Those with colonial nesting habits,
Migratory species,
Those dependent on unreliable resources,
Those with little evolutionary experience of disturbances.
Based on ecological theory, species with the following traits are more prone to extinction: large organisms (e.g. blue whales Balaenoptera musculus and elephants (Loxodonta africana)), those feeding highest in the food chain, those with chronically small population sizes (Barbault & Sastrapradja 1995, Dobson 1996), “those with small ranges or distributions, those linked by biology to threatened habitats or ecosystems” (p. 236 Barbault & Sastrapradja 1995) (e.g. tropical forest species), “those that evolved in isolation (e.g. island” organisms), “those with poor dispersal and colonization abilities (p. 236 Barbault & Sastrapradja 1995, Dobson 1996), “those with colonial nesting habits” (e.g. cape gannets (Sula capensis)), migratory species (p. 236 Barbault & Sastrapradja 1995, Dobson 1996) (e.g. greater striped swallows (Hirundo cucullata)), “those dependent on unreliable resources and those with little evolutionary experience of disturbances” (p. 236 Barbault & Sastrapradja 1995).

20. Some Cautions
Neither global biodiversity estimates nor estimated extinction rates contribute to either conservation practice or tackling the root causes of biodiversity loss.
Data on extinction rates are optimistic in that genetic impoverishment is not taken into account.
Each species is the potential ancestor of future species so abnormal extinction rates affect future speciation.
Neither global biodiversity estimates nor estimated extinction rates contribute to either conservation practice or tackling the root causes of biodiversity loss (Groombridge 1992). Data on extinction rates are optimistic in that genetic impoverishment is not taken into account (Groombridge 1992). Each species is the potential ancestor of future species so abnormal extinction rates affect future speciation (Barbault & Sastrapradja 1995).

21. Links to Other Chapters
Chapter 1 Biodiversity: what is it?
Chapter 2 The evolution of biodiversity
Chapter 3 Biodiversity: why is it important?
Chapter 4 Global biodiversity and its decline
Chapter 5 …
Links to Other Chapters
I hope that you found chapter 4 informative and that you will enjoy chapter 5.