CHAPTER OVERVIEW 22: Biodiversity Learning Objectives Differentiate among the types of biodiversity Learn how to measure diversity using indices Understand why biodiversity is not evenly distributed Learn how rarefaction curves are used to estimate species richness 22.1: What is Biodiversity? 22.2: Diversity Indices 22.3: Patterns in Biodiversity 22.4: How many species are there? 22.5: Measuring Biodiversity using DNA Summary Genetic diversity, ecosystem diversity, and human-derived diversity are measures of biodiversity that currently define life on earth. Because it is often difficult to obtain a full list of species in any given location, various metrics are used to measure biodiversity, including Alpha, Beta, and Gamma diversity, and rarefaction curves. While around 2 million species have been scientifically described globally, estimates of the actual number of species on earth range from 10s of millions to billions. 22: Biodiversity is shared under a CC BY-NC-SA license and was authored, remixed, and/or curated by LibreTexts.
22.1: What is Biodiversity? Genetic diversity, ecosystem diversity, and human-derived diversity are measures of biodiversity that currently define life on earth. Key Points A genus with a high variety of species will have more genetic diversity; the most genetically-diverse species will have the greatest potential for evolution and preservation. The loss of ecosystem diversity results in the loss of interactions between species, unique features of co-adaptation, and biological productivity. Human-generated species diversity has decreased due to migration, market forces, and agriculture. Humans have only been able to estimate the number of species that inhabit Earth; this estimate only accounts for 20 percent of predicted species on the planet. Key Terms genetic diversity: variety of genes in a species or other taxonomic group or ecosystem; can refer to allelic diversity or genomewide diversity ecosystem diversity: variety of ecosystems in a biosphere or the variety of species and ecological processes that occur in different physical settings chemical diversity: variety of metabolic compounds in an ecosystem
Types of Biodiversity Scientists generally accept that the term biodiversity describes the number and kinds of species in a location or on the planet. Species can be difficult to define, but most biologists still feel comfortable with the concept and are able to identify and count eukaryotic species in most contexts. Biologists have also identified alternate measures of biodiversity, some of which are important for planning how to preserve biodiversity. Genetic diversity is one of those alternate concepts. Genetic diversity or variation is the raw material for adaptation in a species. A species' future potential for adaptation depends on the genetic diversity held in the genomes of the individuals in populations that make up the species. The same is true for higher taxonomic categories. A genus with very different types of species will have more genetic diversity than a genus with species that look alike and have similar ecologies. If there were a choice between one of these genera of species being preserved, the one with the greatest potential for subsequent evolution is the most genetically-diverse one. It would be ideal not to have to make such choices, but, increasingly, this may be the norm. Many genes code for proteins, which in turn carry out the metabolic processes that keep organisms alive and reproducing. Genetic diversity can be measured as chemical diversity in that different species produce a variety of chemicals in their cells, both the proteins as well as the products and by-products of metabolism. This chemical diversity has potential benefits for humans as a source of pharmaceuticals, so it provides one way to measure diversity that is important to human health and welfare. Humans have generated diversity in domestic animals, plants, and fungi. This diversity is also suffering losses because of migration, market forces, and increasing globalism in agriculture, especially in heavily-populated regions such as China, India, and Japan. The human population directly depends on this diversity as a stable food source; its decline is troubling to biologists and agricultural scientists. It is also useful to define ecosystem diversity: the number of different ecosystems on the planet or in a given geographic area. Whole ecosystems can disappear even if some of the species might survive by adapting to other ecosystems. The loss of an ecosystem means the loss of interactions between species, the loss of unique features of co-adaptation, and the loss of biological productivity that an ecosystem is able to create. An example of a largely-extinct ecosystem in North America is the prairie ecosystem. Prairies once spanned central North America from the boreal forest in northern Canada down into Mexico. Now, they have mostly disappeared, replaced by crop fields, pasture lands, and suburban sprawl. Many of the species survive, but the hugelyproductive ecosystem that was responsible for creating the most productive agricultural soils is now gone. As a consequence, soils are disappearing or must be maintained at greater expense.
Figure \(\PageIndex{1}\): Ecosystem diversity - The variety of ecosystems on earth, from (a) coral reef to (b) prairie, enables a great diversity of species to exist.
Functional Diversity and Indigenous Land Use Practices Case Study Modified from Armstrong, C. G., Miller, J. E., McAlvay, A. C., Ritchie, P. M., & Lepofsky, D. (2021). Historical indigenous land-use explains plant functional trait diversity. Ecology and Society. 26: 6. This article was published under CC BY 4.0. In addition to species diversity, ecologists are often interested in the trait or functional diversity of a community. A trait is simply any morphological, physiological or phenological feature measurable at the individual level (Reiss et al., 2009). Functional traits are those that define species in terms of their ecological roles - how they interact with the environment and with other species (Diaz & Cabido, 2001). Functional diversity is a biodiversity measure based on functional traits of the species present in a community. In ocean phytoplankton, for example, these traits usually include body size, tolerance and sensitivity to environmental conditions, motility, shape, and N-fixation ability (Reynolds et al., 2002; Weithoff G., 2003). In terrestrial plant communities, researchers have included more complex traits like rates of growth, nutrient requirements and water uptake (Walker & Langridge, 2002; Barnett et al, 2007). Functional traits are a critical tool for understanding ecological communities because they give insights into community assembly processes as well as potential species interactions and other ecosystem functions. Because there are a
greater variety of "roles" being played in a system with higher functional diversity, this measure of diversity has often been linked to higher ecosystem productivity and stability. Human land-use legacies have long-term effects on plant community composition and ecosystem function and on the diversity of functional traits. Armstrong et al. (2021) studied how plant functional trait distributions and functional diversity are affected by ancient and historical Indigenous forest management in the Pacific Northwest.
: The Village complex of Dalk Gyilakyaw consists of three discrete villages and is the ancestral home of
Gitsm'geelm (Ts'msyen) people. Note the dramatic vegetation change between the forest garden and encroaching conifers
("periphery forests"). Photograph: S. Carroll.
: Total Species Richness and Species Richness by Lifeform. Richness is indicated overall between forest gardens
and periphery forests (averaged across the four of the study areas) and among the three growth forms (trees, shrubs and herbs).
For their research into plant functional diversity, Armstrong et al. (2021) compared forest garden ecosystems - managed perennial fruit and nut communities associated exclusively with archaeological village sites - with surrounding periphery conifer forests. To characterize the functional diversity of understory plant communities, they focused on four functional traits: seed mass, shade tolerance, pollination syndrome, and dispersal syndrome. These traits represent important axes of plant lifehistory variation and can also have important consequences for ecosystem functioning, while also having relevance to ethnobotanical plant uses (Pérez-Harguindeguy et al., 2013). For example, plants with animal-dispersed seeds may be able to disperse long distances and may also contribute to wildlife habitat by providing edible fruits; these plants are also more likely to be eaten by people.
: Functional Trait Measures between Forest Gardens and Periphery Forests. Comparisons of average seed mass,
shade tolerance, pollination syndrome, and dispersal syndrome traits for herbs and shrubs across forest gardens and peripheral
forests -- all are significantly higher in the forest gardens.
Armstrong et al. (2021) found that forest gardens have substantially greater plant and functional trait diversity than periphery forests, even more than 150 years after management ceased. Forests managed by Indigenous peoples in the past now provide diverse resources and habitat for animals and other pollinators and are more rich than naturally forested ecosystems. Although ecological studies rarely incorporate Indigenous land-use legacies, the positive effects of Indigenous land use on contemporary functional and taxonomic diversity found by Armstrong et al. (2021) suggest that Indigenous management practices are tied to ecosystem health and resilience.
: Functional Diversity Measures between Forest Gardens and Periphery Forests. Functional evenness (the
evenness of functional trait distribution in niche space; Villéger et al. 2008) and functional dispersion (the average distance to
the abundance-weighted centroid of functional trait values; Laliberté, and Legendre 2010) were significantly greater in forest
gardens as compared to periphery forests. Comparisons of functional diversity at forest gardens and peripheral forests.
References Barnett, A.J., & Beisner, B.E. (2007). Zooplankton biodiversity and lake tropic state: Explanations invoking resource abundance and distribution. Ecology, 88, pp. 1675-1686 Diaz, S., & Cabido, M. (2001). Vive la difference: Plant functional diversity matters to ecosystem processes. Trends in Ecology and Evolution, 16, pp. 646-655 Pérez-Harguindeguy N., Díaz, S., Garnier, E., Lavorel, S., Poorter, H., Jaureguiberry, P., Bret-Harte, M.S., Cornwell, W.K., Craine, J.M., Gurvich, D.E., Urcelay, C., Veneklaas, E.J., Reich, P.B., Poorter, L., Wright, I.J., Ray, P., Enrico, L., Pausas, J.G., de Vos, N. Buchmann, A.C., Funes, G., Quétier, F., Hodgson, J.G., Thompson, K., Morgan, H.D., ter Steege, H., van der Heijden, M.G.A., Sack, L., Blonder, B., Poschlod, P., Vaieretti, M.V., Conti, G., Staver, A.C., Aquino, S., & Cornelissen, J.H.C. (2013). New handbook for standardised measurement of plant functional traits worldwide. Australian Journal of Botany, 61, pp. 167-234. Reiss, J., Bridle, J.R., Montoya, J.M. and Woodward, G. (2009). Emerging horizons in biodiversity and ecosystem functioning research. Trends Ecol. Evol., 24, pp. 505-514 Reynolds, C.S., Huszar, V., Kruk, C., Naselli-Flores, L. and Melo, S. (2002). Towards a functional classification of the freshwater phytoplankton. Journal of Plankton Research, 24, pp. 417-428 Villéger, S., Mason, N.W., & Mouillot, D. (2008). New multidimensional functional diversity indices for a multifaceted framework in functional ecology. Ecology, 89, pp. 2290-2301. Walker, B.H., & Langridge, J.L. (2002). Measuring functional diversity in plant communities with mixed lifeforms: A problem of hard and soft attributes. Ecosystems, 5, pp. 529-538 Weithoff, G. (2003). The concept of `plant functional types' and `functional diversity' in lake phytoplankton - new understanding of phytoplankton ecology? Freshwater Biology, 48, pp. 1669-1675 Contributors and Attributions Written and modified by A. Wilson and N. Gownaris (Gettysburg College) from the following open-access sources Chapter 47.1B: Types of Biodiversity in General Biology (Boundless) Armstrong, C. G., Miller, J. E., McAlvay, A. C., Ritchie, P. M., & Lepofsky, D. (2021). Historical indigenous land-use explains plant functional trait diversity. Ecology and Society. 26: 6. Functional Traits - Coastal Wiki 22.1: What is Biodiversity? is shared under a CC BY-NC-SA license and was authored, remixed, and/or curated by LibreTexts. 47.1B: Types of Biodiversity by Boundless (now LumenLearning) is licensed CC BY-SA 4.0.
Diversity Indices A diversity index is a quantitative measure that reflects how many different types (such as species) there are in a dataset (a community). These indices are statistical representations of biodiversity in different aspects (richness, evenness, and dominance). When diversity indices are used in ecology, the types of interest are usually species, but they can also be other categories, such as genera, families, functional types, or haplotypes. The entities of interest are usually individual plants or animals, and the measure of abundance can be, for example, number of individuals, biomass or coverage.
Richness simply quantifies how many different types the dataset of interest contains. For example, species richness (usually noted S) of a dataset is the number of species in the corresponding species list. Richness is a simple measure, so it has been a popular diversity index in ecology, where abundance data are often not available for the datasets of interest.
Although species richness (denoted S) is often used as a measure of biodiversity, of more interest to ecologists and conservation
biologists are diversity indices that include both species richness and measures of abundance. This is because richness alone does
not account for evenness across species. In Example
below, both lakes have the same richness, but Lake B is more diverse
because abundance is spread more evenly across the species present.
Many different indices of diversity are used by scientists, but below we cover the most widely used.
Simpson's Index Simpson (1949) developed an index of diversity which is a measure of probability--the less diversity, the greater the probability that two randomly selected individuals will be the same species. In the absence of diversity (1 species), the probability that two individuals randomly selected will be the same is 1. Simpson's Index is calculated as follows:
where ni is the number of individuals in species i, N = total number of individuals of all species, and ni/N = pi (proportion of individuals of species i), and S = species richness. The value of Simpson's D ranges from 0 to 1, with 0 representing infinite diversity and 1 representing no diversity, so the larger the value of D, the lower the diversity. For this reason, Simpson's index is often as its complement (1-D). Simpson's Dominance Index is the inverse of the Simpson's Index (1/D). Shannon-Weiner Index Another widely used index of diversity that also considers both species richness and evenness is the Shannon-Weiner Diversity Index, originally proposed by Claude Shannon in 1948. It is also known as Shannon's Diversity Index. The index is related to the concept of uncertainty. If for example, a community has very low diversity, we can be fairly certain of the identity of an organism we might choose by random (high certainty or low uncertainty). If a community is highly diverse and we choose an organism by random, we have a greater uncertainty of which species we will choose (low certainty or high uncertainty).
where pi = proportion of individuals of species i, and ln is the natural logarithm, and S = species richness. The value of H ranges from 0 to Hmax. Hmax is different for each community and depends on species richness. (Note: ShannonWeiner is often denoted H' ). Evenness Index Species evenness refers to how close in numbers each species in an environment is. So if there are 40 foxes and 1000 dogs, the community is not very even. But if there are 40 foxes and 42 dogs, the community is quite even. The evenness of a community can be represented by Pielou's evenness index (Pielou, 1966): The value of J ranges from 0 to 1. Higher values indicate higher levels of evenness. At maximum evenness, J = 1. J and D can be used as measures of species dominance (the opposite of diversity) in a community. Low J indicates that 1 or few species dominate the community. Exercise Calculate Simpson's Index, Shannon-Weiner Index, and the Evenness Index for waterbirds on two lakes: Lake A, and Lake B. There are 5 species and 25 individuals on both lakes, but are they equally diverse? Try to check all three indices to decide on your conclusion before you check the answers!
: Though both Lakes A and B have the same amount of birds and the same number of different species, their diversity is different.
Answer Solutions for each of the indices are shown below.
: The three blue columns show the steps to calculate D for Lake A, while the three gray columns show the
steps to calculate D for Lake B. Though the S and N values are the same for both lakes, the proportion of each species in
Note that Simpson's Index is often expressed (1-D), so the final answers are 0.29 and 0.8. This makes more intuitive sense: a higher D is more diverse--which is Lake B because it is less dominated by one species.
: The four blue columns show the steps to calculate H for Lake A, while the four gray columns show the steps to calculate H for Lake B.
Again, according to the Shannon-Weiner Index, Lake B is more diverse.
: J calculates the species evenness for Lakes A and B using the Shannon-Weiner Index calculations.
Conclusion By all three measures, Lake B is more diverse, despite the fact that the two lakes have identical species richness.
Biodiversity at different scales- Alpha, Beta, and Gamma Biologists have developed three quantitative measures of species diversity as a means of measuring and comparing species diversity: Alpha diversity (or species richness), the most commonly referenced measure of species diversity, refers to the total number of species found in a particular biological community, such as a lake or a forest. Bwindi Forest in Uganda, with an estimated 350 bird species, has one of the highest alpha diversities of all African ecosystems. Gamma diversity describes the total number of species that occur across an entire region, such as a mountain range or continent, that includes many ecosystems. The Albertine Rift, which includes Bwindi Forest, has more than 1,074 species of birds, a very high gamma diversity for such a small region. Beta diversity connects alpha and gamma diversity. It describes the rate at which species composition changes across a region. For example, if every wetland in a region was inhabited by a similar suite of plant species, then the region would have low beta diversity; in contrast, if several wetlands in a region had plants communities that were distinct and had little overlap with one another, the region would have high beta diversity. Beta diversity is calculated as gamma diversity divided by alpha diversity. The beta diversity for forest birds of the Albertine Rift is about 3.0, if each ecosystem in the area has about the same number of species as Bwindi Forest.
: Biodiversity indices for nine mountain peaks across three ecoregions. Each symbol represents a different species;
some species have populations on only one peak, while others are found on two or more peaks. The variation in species richness on
each peak results in different alpha, gamma, and beta diversity values for each ecoregion. This variation has implications for how
we divide limited resources to maximise protection. If only one ecoregion can be protected, ecoregion 3 may be a good choice
because it has high gamma (total) diversity. However, if only one peak can be protected, should a peak in ecoregion 1 (with many
widespread species) or ecoregion 3 (with several unique, range-restricted species) be protected? After Primack, 2012, CC BY 4.0.
It is important to note that alpha, beta, and gamma diversity describe only part of what is meant by biodiversity. For example, none of these three terms completely account for genetic diversity, which allows species to adapt as conditions change. It also neglects the importance of ecosystem diversity, which results from the collective response of species to their dynamic environment. However, these diversity measures are useful for comparing different regions, and identifying locations with high concentrations of native species that should be protected.
References Pielou, E.C. (1966). The measurement of diversity in different types of biological collections. Journal of Theoretical Biology, 13, pp. 131-144. doi:10.1016/0022-5193(66)90013-0. Simpson, E.H. (1949). Measurement of diversity. Nature, 163, pp. 688. doi:10.1038/163688a0 Shannon, C.E. (1948). A mathematical theory of communication. The Bell System Technical Journal, 27, pp. 379-423. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x Contributors and Attributions Written and curated by A. Wilson and N. Gownaris (Gettysburg College) with material from the following open-access sources: Conservation Biology in Sub-Saharan Africa by John W. Wilson and Richard B. Primack Diversity Index by Wikipedia, the free Encyclopedia 22.2: Diversity Indices is shared under a CC BY-NC-SA license and was authored, remixed, and/or curated by LibreTexts.
Biodiversity is not evenly distributed on the planet. For example, Lake Victoria in Africa (Figure
species from a family of fishes called cichlids before the introduction of the invasive Nile Perch in the 1980s and 1990s caused a
mass extinction. Note that this number does not include species of other fish families. Lake Huron, the second largest of North
America's Great Lakes, contains about 79 species of fish, all of which are found in many other lakes in North America.
What accounts for the difference in diversity between Lake Victoria and Lake Huron? Lake Victoria is a tropical lake, while Lake Huron is a temperate lake. Lake Huron in its present form is only about 7,000 years old, while Lake Victoria in its present form is about 15,000 years old. These two factors, latitude and age, are two of several hypotheses that biogeographers have suggested explain biodiversity patterns on Earth.
: Lake Victoria in Africa, shown in this satellite image, was the site of one of the most extraordinary evolutionary
findings on the planet, as well as a casualty of devastating biodiversity loss (credit: modification of work by Rishabh Tatiraju, using
Biogeography is the study of the distribution of the world's species both in the past and in the present. The work of biogeographers is critical to understanding our physical environment, how the environment affects species, and how changes in environment impact the distribution of a species. There are three main subfields of biogeography: ecological biogeography, historical biogeography (called paleobiogeography), and conservation biogeography. Ecological biogeography studies the current factors affecting the distribution of plants and animals. Historical biogeography, as the name implies, studies the past distribution of species. Conservation biogeography, on the other hand, is focused on the protection and restoration of species based upon the known historical and current ecological information. Understanding the global distribution of biodiversity is one of the most significant objectives for ecologists and biogeographers. Beyond purely scientific goals and satisfying curiosity, this understanding is essential for applied issues of major concern to humankind, such as the spread of invasive species, the control of diseases and their vectors, and the likely effects of global climate change on the maintenance of biodiversity (Gaston, 2000).
22.3.1 Latitudinal Gradients in Biodiversity
Source: https://en.wikipedia.org/wiki/Latitu...cies_diversity
Species richness, or biodiversity, increases from the poles to the tropics for a wide variety of terrestrial and marine organisms
. This effect is often referred to as the latitudinal diversity gradient (LDG). The LDG is one of the most widely
recognized patterns in ecology. A parallel trend has been found with elevation (elevational diversity gradient), though this is less
well-studied. Tropical areas play prominent roles in the understanding of the distribution of biodiversity, as their rates of habitat
degradation and biodiversity loss are exceptionally high.
Explaining the latitudinal diversity gradient has been called one of the great contemporary challenges of biogeography and macroecology (e.g. Willig et al., 2003; Pimm & Brown, 2004). There is a lack of consensus among ecologists about the mechanisms underlying the pattern, and many hypotheses have been proposed and debated.
: Map latitudinal gradient of living terrestrial vertebrate species richness (Mannion, 2014).
22.3.2 Hypotheses for Latitudinal Gradients Although many of the hypotheses exploring the latitudinal diversity gradient are closely related and interdependent, the major hypotheses can be split into three general hypotheses. As you will see below, all of these hypotheses have experienced considerable criticisms and debate among members of the scientific community. Spatial/Area Hypothesis Mid-domain effect Using computer simulations, Cowell and Hurt (1994) and Willig and Lyons (1998) first pointed out that if species' latitudinal ranges were randomly shuffled within the geometric constraints of a bounded biogeographical domain (e.g. the continents of the New World, for terrestrial species), species' ranges would tend to overlap more toward the center of the domain than towards its limits, forcing a mid-domain peak in species richness. Colwell and Lees (2000) called this stochastic phenomenon the mid-domain effect (MDE) and suggested the hypothesis that MDE might contribute to the latitudinal gradient in species richness, together with other explanatory factors considered here, including climatic and historical ones. Mid-domain effects have proven controversial. While some studies have found evidence of a potential role for MDE in latitudinal gradients of species richness, particularly for wide-ranging species, others report little correspondence between predicted and observed latitudinal diversity patterns. Species-energy hypothesis The species energy hypothesis suggests that the amount of available energy sets limits to the richness of the system. Thus, increased solar energy (with an abundance of water) at low latitudes causes increased net primary productivity (or photosynthesis). This hypothesis proposes the higher the net primary productivity the more individuals can be supported, and the more species there will be in an area. Put another way, this hypothesis suggests that extinction rates are reduced towards the equator as a result of the higher populations sustainable by the greater amount of available energy in the tropics. Lower extinction rates lead to more species in the tropics. One critique of this hypothesis has been that increased species richness over broad spatial scales is not necessarily linked to an increased number of individuals, which in turn is not necessarily related to increased productivity (Cardillo et al., 2005). The effect of energy has, however, been supported by several studies in terrestrial and marine taxa (Tittensor et al., 2010). The potential mechanisms underlying the species-energy hypothesis, their unique predictions and empirical support have been assessed in a major review by Currie et al. (2004).
Climate-related hypotheses Another climate-related hypothesis is the climate harshness hypothesis, which states the latitudinal diversity gradient may exist simply because fewer species can physiologically tolerate conditions at higher latitudes than at low latitudes because higher latitudes are often colder and drier than tropical latitudes. Currie et al. (2004) found fault with this hypothesis by stating that, although it is clear that climatic tolerance can limit species distributions, it appears that species are often absent from areas whose climate they can tolerate. Similarly to the climate harshness hypothesis, climate stability is suggested to be the reason for the latitudinal diversity gradient. The mechanism for this hypothesis is that while a fluctuating environment may increase the extinction rate or preclude specialization, a constant environment can allow species to specialize on predictable resources, allowing them to have narrower niches and facilitating speciation. The fact that temperate regions are more variable both seasonally and over geological timescales (discussed in more detail below) suggests that temperate regions are thus expected to have less species diversity than the tropics. Critiques for this hypothesis include the fact that there are many exceptions to the assumption that climate stability means higher species diversity. Additionally, many habitats with high species diversity do experience seasonal climates, including many tropical regions that have highly seasonal rainfall (Brown & Lomolino, 1998). Historical/Evolutionary hypotheses The historical perturbation hypothesis The historical perturbation hypothesis proposes the low species richness of higher latitudes is a consequence of an insufficient time period available for species to colonize or recolonize areas because of historical perturbations such as glaciation (Brown & Lomolino, 1998; Gaston & Blackburn, 2000). This hypothesis suggests that diversity in the temperate regions has not yet reached equilibrium and that the number of species in temperate areas will continue to increase until saturated (Clarke & Crame, 2003). The evolutionary rate hypothesis The evolutionary rate hypothesis argues that higher evolutionary rates in the tropics have caused higher speciation rates and thus increased diversity at low latitudes (Cardillo et al., 2005; Weir & Schluter, 2007; Rolland et al., 2014). Higher evolutionary rates in the tropics have been attributed to higher ambient temperatures, higher mutation rates, shorter generation time and/or faster physiological processes (Rohde, 1992; Allen et al., 2006), and increased selection pressure from other species that are themselves evolving (Schemske et al., 2009). Faster rates of microevolution in warm climates (i.e. low latitudes and altitudes) have been shown for plants (Wright et al. 2006), mammals (Gillman et al., 2009), and amphibians (Wright et al., 2010). Based on the expectation that faster rates of microevolution result in faster rates of speciation, these results suggest that faster evolutionary rates in warm climates almost certainly have a strong influence on the latitudinal diversity gradient. More research needs to be done to determine whether or not speciation rates actually are higher in the tropics. Understanding whether extinction rate varies with latitude will also be important to whether or not this hypothesis is supported (Rolland et al., 2014). The hypothesis of effective evolutionary time The hypothesis of effective evolutionary time assumes that diversity is determined by the evolutionary time under which ecosystems have existed under relatively unchanged conditions, and by evolutionary speed directly determined by effects of environmental energy (temperature) on mutation rates, generation times, and speed of selection (Rohde, 1992). It differs from most other hypotheses in not postulating an upper limit to species richness set by various abiotic and biotic factors, i.e., it is a nonequilibrium hypothesis assuming a largely non-saturated niche space. It does accept that many other factors may play a role in causing latitudinal gradients in species richness as well. The hypothesis is supported by much recent evidence, in particular, the studies of Allen et al. (2006) and Wright et al. (2006).
Biotic hypotheses Biotic hypotheses claim ecological species interactions such as competition, predation, mutualism, and parasitism are stronger in the tropics and these interactions promote species coexistence and specialization of species, leading to greater speciation in the tropics. These hypotheses are problematic because they cannot be the ultimate cause of the latitudinal diversity gradient as they fail to explain why species interactions might be stronger in the tropics. An example of one such hypothesis is the greater intensity of predation and more specialized predators in the tropics has contributed to the increase of diversity in the tropics (Pianka, 1966). This intense predation could reduce the importance of competition (see competitive exclusion) and permit greater niche overlap and promote higher richness of prey. Some recent large-scale experiments suggest predation may indeed be more intense in the tropics,[12][13] although this cannot be the ultimate cause of high tropical diversity because it fails to explain what gives rise to the richness of the predators in the tropics. Interestingly, the largest test of whether biotic interactions are strongest in the tropics, which focused on predation exerted by large fish predators in the world's open oceans, found predation to peak at mid-latitudes. Moreover, this test further revealed a negative association of predation intensity and species richness, thus contrasting the idea that strong predation near the equator drives or maintains high diversity.[14] Other studies have failed to observe consistent changes in ecological interactions with latitude altogether (Lambers et al., 2002),[1] suggesting that the intensity of species interactions is not correlated with the change in species richness with latitude. Overall, these results highlight the need for more studies on the importance of species interactions in driving global patterns of diversity.
With the enormous number of species that exist on Earth, it is remarkable that the distribution of these species is so highly concentrated in specific areas. Species richness, the total number of species found in an area, is not evenly distributed around the globe: two-thirds of all known species occur in tropical areas.
In order to prioritize the areas that should be protected, scientists look for areas that are home to a large number of species,
especially those species that are under threat of extinction. or that are currently being destroyed at a fast pace. These areas that
are particularly important for biodiversity conservation are called biodiversity hotspots. Two things are crucial when
determining that a place is a biodiversity hotspot: (i) the number of different species there; and (ii) whether species in that area
are endangered or currently being destroyed. Figure
shows the location of 36 biodiversity hotspots, according to the
: The names and locations of current biodiversity hotspots around the globe. The original 25 in green, and added regions in purple (Wikipedia, edited by Andy Wilson).
Scientists have observed that, even though biodiversity hotspots make up only approximately 1.4% of land on our planet, they are home to 60% of Earth's plant, bird, mammal, and reptile species (Possingham and Wilson 2005). Just the endangered
species in the tropics accounts for 43% of vertebrates (animals with backbones and their close relatives) and 80% of all
amphibians (Marchese 2015). Species found only in a certain geographical area are known as endemic species, and
biodiversity hotspots are full of them! For example, the Banana Tree Frog can only be found in Ethiopia, and you will only
find lemurs in Madagascar (Herrera 2017). Tropical forests are typically biodiversity hotspots and are usually filled with
endemic species. The Upper Amazonia/Guyana Shield, the Congo Basin, and the New Guinea/Melanesian Islands have the
highest number of endemic terrestrial (land-living) species on Earth (Cincotta et al. 2000). Figure
of biodiversity hotspots and some of their endemic animals and plants.
: Biodiversity hotspots and some of their endemic species. (a) Melanesian Islands ["Solomon Islands" by Jim
Lounsbury is available for open access]; (b) Emerald Lakes, New Zealand [Photo by Marcus Holland-Moritz is licensed under
CC BY-SA 2.0]; (c) Diademed sifaca, one of the endemic lemur species from Mantadia National Park,
Madagascar ["Diademed ready to push off" by Michael Hogan is available in the public domain]; (d) Maned wolf, the largest
canid of South America, a species from the Cerrado hotspot [Photo by Aguará is licensed under CC SA 3.0]; (e) Atlantic
Forest, Caparaó, Brazil ["Caparaó e a Mata Atlântica" by Heris Luiz Cordeiro Rocha is licensed under CC SA 3.0]; (f)
Rafflesia, one of the largest flowers in nature. This particular one, from Borneo, is 80 cm wide ["Rafflesia keithii bloom" by
Steve Cornish is licensed under CC BY 2.0]
In addition to land, the waters surrounding these tropical regions are just as important, and equally in danger (Marchese, 2015). Tropical coral reefs are currently being threatened by climate change. The change of weather and temperature patterns around the world cause intense habitat destruction, especially of these reefs. These areas are some of the most biodiverse ecosystems on our planet! Scientific studies of 3,235 marine species in these areas, including fishes, corals, snails, and lobsters, show that high percentages of these species are at serious risk of becoming extinct (Roberts et al., 2002). Conservation of species living in fresh or seawater is especially difficult, because many bodies of water are interconnected. For example, all the oceans are connected through sea currents that allow the movement of species, minerals, and pollution across the entire globe (Pimm et al., 2014).
Sources Allen, A.P., Gillooly, J.F., Savage, V.M., & Brown, J.H. (2006). Kinetic effects of temperature on rates of genetic divergence and speciation. PNAS, 103(24), pp. 9130-9135. doi:10.1073/pnas.0603587103. PMC 1474011. PMID 16754845. Brown, J.H., & Lomolino, M.V. (1998). Biogeography. Sinauer Associates, Sunderland. Cardillo, M., Orme, C.D. L., & Owens, I.P.F. (2005). Testing for latitudinal bias in diversification rates: An example using New World birds. Ecology, 86(9), pp. 2278-2287. doi:10.1890/05-0112. Cincotta, R.P., Wisnewski, J., & Engelman, R. (2000). Human population in the biodiversity hotspots. Nature, 404, pp. 990-2. doi: 10.1038/35010105
Clarke, A., & Crame, J.A. (2003). The importance of historical processes in global patterns of diversity. In Blackburn T.M., & Gaston, K.J. (Eds.), Macroecology concepts and consequences (pp. 130-151). Blackwell Scientific, Oxford. Colwell, R.K., & Lees, D.C. (2000). The mid-domain effect: Geometric constraints on the geography of species richness. Trends in Ecology & Evolution, 15(2), pp. 70-76. doi:10.1016/s0169-5347(99)01767-x. PMID 10652559. Currie, D.J., Mittelbach, G.G., Cornell, H.V., Kaufman, D.M., Kerr, J.T., & Oberdorff, T. (2004). Predictions and tests of climatebased hypotheses of broad-scale variation in taxonomic richness. Ecology Letters, 7(12), pp. 1121-1134. doi:10.1111/j.14610248.2004.00671.x. Gaston, K.J. (2000). Global patterns in biodiversity. Nature, 405(6783), pp. 220-227. doi:10.1038/35012228. PMID 10821282. S2CID 4337597. Gaston, K.J., & Blackburn, T.M. (2000). Pattern and processes in macroecology. Blackwell Scientific, Oxford. Herrera, J.P. (2017). Testing the adaptive radiation hypothesis for the Lemurs of Madagascar. R. Soc. Open Sci., 4, 161014. doi: 10.1098/rsos.161014 Lambers, J.H.R., Clark, J.S., & Beckage, B. (2002). Density-dependent mortality and the latitudinal gradient in species diversity. Nature, 417(6890), pp. 732-735. doi:10.1038/nature00809. Marchese, C. (2015). Biodiversity hotspots: A shortcut for a more complicated concept. Glob. Ecol. Conserv., 3, pp. 297-309. doi: 10.1016/j.gecco.2014.12.008 Pianka, E.R. (1966). Latitudinal gradients in species diversity: A review of concepts. The American Naturalist, 100(910), pp. 33- 46. doi:10.1086/282398. S2CID 84244127. Pimm, S.L., Jenkins, C.N., Abell, R., Brooks, T.M., Gittleman, J.L., Joppa, L.N., et al. (2014). The biodiversity of species and their rates of extinction, distribution, and protection. Science, 344, 1246752. doi: 10.1126/science.1246752. Possingham, H.P., & Wilson, K.A. (2005). Biodiversity: Turning up the heat on hotspots. Nature, 436, pp.919-20. doi: 10.1038/436919a. Roberts, C.M., McClean, C.J., Veron, J.E., Hawkins, J.P., Allen, G.R., McAllister, D.E., et al. (2002). Marine biodiversity hotspots and conservation priorities for tropical reefs. Science, 295, pp. 1280-4. doi: 10.1126/science.1067728. Rohde, K. (1997). The larger area of the tropics does not explain latitudinal gradients in species diversity. Oikos, 79(1), pp. 169- 172. doi:10.2307/3546102. JSTOR 3546102. Rolland, J., Condamine, F.L., Jiguet, F., & Morlon, H. (2014). Faster speciation and reduced extinction in the tropics contribute to the mammalian latitudinal diversity gradient. PLOS Biology, 12(1), e1001775. doi:10.1371/journal.pbio.1001775. PMC 3904837. PMID 24492316. Schemske, D.W., Mittelbach, G.G., Cornell, H.V., Sobel, J.M., & Kaustuv, R. (2009). Is there a latitudinal gradient in the importance of biotic interactions? Annual Review of Ecology, Evolution, and Systematics, 40(1), pp. 245- 269. doi:10.1146/annurev.ecolsys.39.110707.173430. Tittensor, D.P., Mora, C., Jetz, W., Lotze, H.K., Ricard, D., Berghe, E.V., & Worm, B. (2010). Global patterns and predictors of marine biodiversity across taxa. Nature, 466(7310), pp. 1098-1101. doi:10.1038/nature09329. Weir, J.T., & Schluter, D. (2007). The latitudinal gradient in recent speciation and extinction rates of birds and mammals. Science, 315(5818), pp. 1574-1576. Bibcode:2007Sci...315.1574W. doi:10.1126/science.1135590. PMID 17363673. S2CID 46640620. Willig, M.R., & Lyons, S.K. (1998). An analytical model of latitudinal gradients of species richness with an empirical test for marsupials and bats in the New World. Oikos, 81(1), pp. 93-98. doi:10.2307/3546471. JSTOR 3546471. Willig, M.R., Kaufmann, D.M., & Stevens, R.D. (2003). Latitudinal gradients of biodiversity: Pattern, process, scale and synthesis. Annu. Rev. Ecol. Syst., 34, pp. 273-309. doi:10.1146/annurev.ecolsys.34.012103.144032. Wright, S., Keeling, J., & Gillman, L. (2006). The road from Santa Rosalia: A faster tempo of evolution in tropical climates. Proceedings of the National Academy of Sciences, 103(20), pp. 7718-7722. doi:10.1073/pnas.0510383103.
Wright, S.D., Gillman, L.N., Ross, H.A., & Keeling, D.J. (2010). Energy and the tempo of evolution in amphibians: Energy and the tempo of evolution in amphibians. Global Ecology and Biogeography: no-no. doi:10.1111/j.1466-8238.2010.00549.x. Contributors and Attributions Written and curated by A. Wilson and N. Gownaris (Gettysburg College) from the following open-access sources: Chapter 9.4 in Environmental Science by Melissa Ha and Rachel Schleiger, licensed under CC BY - SA Latitudinal Gradients in Species Diversity by Wikipedia, the Free Encyclopedia What are Biodiversity Hotspots? on Frontiers for Young Minds By Melanie Merritt, Maria Eduarda Maldaner, and Ana Maria Rocha de Almeida and Reviewed by Songo Info 22.3: Patterns in Biodiversity is shared under a CC BY-NC-SA license and was authored, remixed, and/or curated by LibreTexts.
22.4: How many species are there? To date, taxonomists have described about 2.2 million species that share this planet with us (http://www.catalogueoflife.org/annualchecklist/2019/info/about). While this total may seem impressive, available evidence suggests that this estimate vastly underestimates the true extent of Earth's biodiversity. In fact, even now, after all the exploration in years gone by, several thousand new species are being described each year. Many new discoveries are made by skilled researchers recognizing new species by being able to discern variation in morphological characters; that includes the discoveries of a new small forest antelope from West Africa (Colyn et al., 2010) and a new species of shark off Mozambique (Ebert & Cailliet, 2011). New genetic technologies have highlighted that there are many thousands of species yet to be described. Both traditional and genetic techniques rely heavily on the availability of specimens in Natural History Museums collections to help identify and describe new species (Sforzi et al., 2018). A lack of taxonomists and natural history collections in many of the world's most biodiverse countries means there is a still a great deal of work to do (Paknia et al., 2015). The most exciting and newsworthy discoveries of new species generally involve higher-level taxa, especially living fossils. For example, in 1938, biologists across the world were stunned by the report of a strange fish caught in the Indian Ocean off South Africa. This fish, subsequently named coelacanth Latimeria chalumnae, belongs to a group of marine fishes that were common in ancient seas but were thought to have gone extinct 65 million years ago. Coelacanths are of interest to evolutionary biologists because they show certain features of muscles and bones in their fins that are comparable to the limbs of the first vertebrates that crawled onto land. Following the initial discovery, coelacanths have been found along Africa's Indian Ocean coast from South Africa to the Comoros and through to Kenya. Unfortunately, the entire coelacanth population, estimated at fewer than 500 individuals, is currently highly threatened because of ongoing fishing pressures (Musick, 2000). Although field surveys have proven to be of great importance for discovering new species and populations, perhaps the greatest taxonomic progress has come from advances in genetic analyses which help to separate cryptic species previously lumped under more widespread species. For example, advances in genetic research recently highlighted that the African clawed frog Xenopus laevis--a popular model organism in biomedical research--consists of seven distinct species (Evans et al., 2015). Similarly, using new genetic methods, scientists recently confirmed that the slender-snouted crocodile Mecistops cataphractus consists of two different species, one endemic to West Africa and the other to Central Africa (Shirley et al., 2018).
Estimates suggest there are somewhere between 1-6 billion distinct species on Earth. The most diverse group of species is bacteria.
The presence of so many undiscovered species and communities makes precise estimates of species diversity incredibly difficult,
especially in Africa where so many areas remain scientifically unexplored. Our most recent estimates, combining genetic analysis
of well-known groups with mathematical patterns, suggests there are between 1-6 billion distinct species on Earth (Table
which there are only about 163 million animals and 340 thousand plants (Larsen et al., 2017)--this is obviously much greater than
the current catalog of almost 2 million species!
Table : Estimated living biomass and number of species for each kingdom of life, following the seven-
kingdom system (Ruggiero et al., 2015). Note how plants weigh the most, but bacteria have the most species.
Kingdom Animals Fungi Plants Chromista Protozoans Archaea Bacteria
Number of species (in million) % of all speciesb
a. As gigatonnes of carbon, from Bar-On et al., 2018 b. From Larsen et al. (2017)'s Table 1, Scenario 1 c. From http://www.catalogueoflife.org
Rarefaction Curves In ecology, rarefaction is a technique to assess species richness from the results of sampling. When sampling various species in a community, the larger the number of individuals sampled, the greater number of species that will be found. Rarefaction allows the calculation of species richness for a given number of individual samples, based on the construction of so-called rarefaction curves. This curve is a plot of the number of species as a function of the number of samples. Rarefaction curves generally grow rapidly at first, as the most common species are found, but the curves plateau as only the rarest species remain to be sampled. Rarefaction curves are necessary for estimating species richness. Raw species richness counts, which are used to create accumulation curves, can only be compared when the species richness has reached a clear asymptote. Rarefaction curves also help to tell us what we don't know. If a curve hasn't yet reached its asymptote, there are additional species in that habitat still to discover.
: A simplified example of a rarefaction curve. In both habitats, the number of species observed (species richness)
increases with the number of samples taken. In Habitat B, the curve eventually saturates (reaches an asymptote), suggesting
that the actual species richness of the habitat has been reached. Habitat A, however, has not yet reached its asymptote, so additional sampling would reveal additional new species in this habitat. Case Study: The Deep Sea of the Mediterranean Basin From: Danovaro, R., Company, J.B., Corinaldesi, C., D'Onghia, G., Galil, B., Gambi, C., Gooday, A.J., Lampadariou, N., Luna, G.M., Morigi, C. and Olu, K., 2010. Deep-sea biodiversity in the Mediterranean Sea: the known, the unknown, and the unknowable. PloS one, 5(8), p.e11832. Deep-sea ecosystems represent the largest biome of the global biosphere, but knowledge of their biodiversity is still scant. The Mediterranean basin has been proposed as a hotspot of terrestrial and coastal marine biodiversity, but has been supposed to be impoverished of deep-sea species richness. Danovaro et al. (2010) summarized all available information on benthic biodiversity (Prokaryotes, Foraminifera, Meiofauna, Macrofauna, and Megafauna) in different deep-sea ecosystems of the Mediterranean Sea (200 to more than 4,000 m depth), including open slopes, deep basins, canyons, cold seeps, seamounts, deep-water corals and deep-hypersaline anoxic basins and analyzed overall longitudinal and bathymetric patterns.
: Investigated areas in the Mediterranean basin. Areas include slopes, seamounts, canyons, deep-water corals, and basin.
Danovaro et al. (2010) found that all of the biodiversity components, except Bacteria and Archaea, displayed a decreasing pattern with increasing water depth, but to a different extent for each component. Unlike patterns observed for faunal abundance, highest negative values of the slopes of the biodiversity patterns were observed for Meiofauna, followed by Macrofauna and Megafauna. Comparison of the biodiversity associated with open slopes, deep basins, canyons, and deepwater corals showed that the deep basins were the least diverse. Rarefaction curves allowed for estimation of the expected number of species for each benthic component in different bathymetric ranges. Species were unique across ecosystems, so each ecosystem contributes significantly to overall biodiversity.
: Rarefaction curves for the different components of the deep biota.
Danovaro et al. (2010) estimated that the overall deep-sea Mediterranean biodiversity (excluding prokaryotes) reaches approximately 2,805 species, of which about 66% is still undiscovered. Among the biotic components investigated (Prokaryotes excluded), most of the unknown species are within the phylum Nematoda, followed by Foraminifera, but an important fraction of macrofaunal and megafaunal species also remains unknown. The data in this study provide new insights into the patterns of biodiversity in the deep-sea Mediterranean and new clues for future investigations aimed at identifying the factors controlling and threatening deep-sea biodiversity.
References Bar-On, Y.M., Phillips, R., & Milo, R. (2018). The biomass distribution on Earth. Proceedings of the National Academy of Sciences, 25, pp. 6505-11. https://doi.org/10.1073/pnas.1711842115 Colyn, M., Hulselmans, J., Sonet, G., et al. (2010). Discovery of a new duiker species (Bovidae: Cephalophinae) from the Dahomey Gap, West Africa. Zootaxa, 2637, pp. 1-30. http://doi. org/10.11646/zootaxa.2637.1.1 Costello, M.J., Wilson, S., & Houlding, B. (2012). Predicting total global species richness using rates of species description and estimates of taxonomic effort. Systematic Biology, 61, pp. 871-83. http://doi.org/10.1093/sysbio/syr080 Danovaro, R., Company, J.B., Corinaldesi, C., D'Onghia, G., Galil, B., Gambi, C., Gooday, A.J., Lampadariou, N., Luna, G.M., Morigi, C., & Olu, K. (2010). Deep-sea biodiversity in the Mediterranean Sea: The known, the unknown, and the unknowable. PloS one, 5(8), p.e11832. Ebert, D.A., & Cailliet, G.M. (2011). Pristiophorus nancyae, a new species of sawshark (Chondrichthyes: Pristiophoridae) from southern Africa. Bulletin of Marine Science, 87, pp. 501- 12. https://doi.org/10.5343/bms.2010.1108 Paknia, O, Rajaei H., & Koch, A. (2015). Lack of well-maintained natural history collections and taxonomists in megadiverse developing countries hampers global biodiversity exploration. Organisms Diversity & Evolution, 15, pp. 619629. http://doi.org/10.1007/s13127-015-0202-1
Larsen, B.B., E.C. Miller, M.K. Rhodes, et al. (2017). Inordinate fondness multiplied and redistributed: The number of species on Earth and the new pie of life. Quarterly Review of Biology, 92, pp. 229-65. https://doi.org/10.1086/693564 Musick, J.A. (2000). Latimeria chalumnae. The IUCN Red List of Threatened Species, e.T11375A3274618. http://doi.org/10.2305/IUCN.UK.2000....375A3274618.en Ruggiero, M.A., Gordon, D.P., Orrell, T.M., et al. (2015). A higher-level classification of all living organisms. PLoS ONE 10: e0119248. http://doi.org/10.1371/journal.pone.0119248 Sforzi, A., Tweddle, J., Vogel, J., Lois, G., Wägele, W., Lakeman-Fraser, P., Makuch, Z., & Vohland, K. (2018). In Hecker, S., Haklay, M., Bowser, A., Makuch, Z., Vogel, J. & Bonn, A. (Eds.), Citizen science: Innovation in open science, society and policy. UCL Press, London. https://doi.org/10.14324 /111.9781787352339 Shirley, M.H., Carr, A.N., Nestler, J.H., et al. (2018). Systematic revision of the living African slender-snouted crocodiles (Mecistops Gray, 1844). Zootaxa, 4504, pp. 151-93. http://doi. org/10.11646/zootaxa.4504.2.1 Contributors and Attributions Written and curated by A. Wilson and N. Gownaris (Gettysburg College) with material from the following open-access sources: Conservation Biology of Sub-Saharan Africa by John W. Wilson and Richard B. Primack Rarefaction (ecology) by Wikipedia, the Free Encyclopedia Danovaro, R., Company, J.B., Corinaldesi, C., D'Onghia, G., Galil, B., Gambi, C., Gooday, A.J., Lampadariou, N., Luna, G.M., Morigi, C. and Olu, K., 2010. Deep-sea biodiversity in the Mediterranean Sea: the known, the unknown, and the unknowable. PloS one, 5(8), p.e11832. 22.4: How many species are there? is shared under a CC BY-NC-SA license and was authored, remixed, and/or curated by LibreTexts. 3.4: Patterns of Biodiversity by John W. Wilson & Richard B. Primack is licensed CC BY 4.0. Original source: https://doi.org/10.11647/OBP.0177.
22.5: Measuring Biodiversity using DNA Learning Objectives Explain how DNA barcoding aids in measuring biodiversity Measuring Biodiversity using DNA The technologies of molecular genetics, data processing, and data storage are maturing to the point where cataloging the planet's species in an accessible way is close to feasible. DNA barcoding is one molecular genetic method, which takes advantage of the rapid evolution in a mitochondrial gene present in eukaryotes, to identify species using the sequence of portions of the gene. Plants may be barcoded using a combination of chloroplast genes. DNA barcoding is a taxonomic method that uses a short genetic marker in an organism's DNA to identify it as belonging to a particular species. It differs from molecular phylogeny in that the main goal is not to determine patterns of relationship, but to identify an unknown sample in terms of a preexisting classification. The most commonly-used barcode region for animals, at least, is a segment of approximately 600 base pairs of the mitochondrial gene cytochrome oxidase I (COI). Applications include, for example, identifying plant leaves (even when flowers or fruit are not available), identifying insect larvae (which may have fewer diagnostic characters than adults and are frequently less well-known), identifying the diet of an animal (based on its stomach contents or feces), and identifying products in commerce (for example, herbal supplements or wood). Rapid, mass-sequencing machines make the molecular genetics portion of the work relatively inexpensive and quick. Computer resources store and make available the large volumes of data. Projects are currently underway to use DNA barcoding to catalog museum specimens, which have already been named and studied, as well as testing the method on less studied groups. As of mid2012, close to 150,000 named species had been barcoded. Early studies suggest there are significant numbers of undescribed species that looked too much like sibling species to previously be recognized as different. These now can be identified with DNA barcoding. Numerous computer databases now provide information about named species and a framework for adding new species. However, as already noted, at the present rate of description of new species, it will take close to 500 years before the complete catalog of life is known. Many, perhaps most, species on the planet do not have that much time. There is also the problem of understanding which species known to science are threatened and to what degree they are threatened. This task is carried out by the non-profit IUCN (International Union for Conservation of Nature) which maintains the Red List: an online listing of endangered species categorized by taxonomy, type of threat, and other criteria. The Red List is supported by scientific research. In 2011, the list contained 61,000 species, all with supporting documentation.
: IUCN Red List: This chart shows the percentage of various animal species, by group, on the IUCN Red List as of
2007. The Red List is an online listing of endangered species categorized by taxonomy, type of threat, and other criteria.
Key Points DNA barcoding is a taxonomic method that uses a short genetic marker in an organism's DNA to identify it as belonging to a particular species. Barcoding allows us to classify organisms that would otherwise be difficult to identify, such as in situations where only part of an organism is available, or is too immature to identify by conventional methods. At the present rate of description of new species, it will take close to 500 years before the complete catalog of life is known; however, most species will be extinct before this time. Even with barcoding, it is difficult to know which species are threatened and to what degree they are threatened, a task carried out by the non-profit IUCN (International Union for Conservation of Nature). Contributors and Attributions Written and curated by A. Wilson and N. Gownaris (Gettysburg College) with material from the following open-access sources: 47.4A: Measuring Biodiversity by Boundless (now LumenLearning) is licensed CC BY-SA 4.0. 22.5: Measuring Biodiversity using DNA is shared under a CC BY-NC-SA license and was authored, remixed, and/or curated by LibreTexts. 47.4A: Measuring Biodiversity by Boundless (now LumenLearning) is licensed CC BY-SA 4.0.