Define Endemism With An Example Of An Essay

More troubling is the endemic problem of which it is a symptom. Times, Sunday Times (2016)Our advice is that in endemic areas you should keepcatsindoors and dogs on the lead. Times, Sunday Times (2006)What is meant by the term endemic disease?McKenzie, James F. & Pinger, Robert R. An Introduction to Community Health (1995)There is another area where falseaccusations have become endemic. Times, Sunday Times (2015)The watchdog said the problem was endemic in the industry. The Sun (2014)The perceptiontoday is of an organisation in which corruption is endemic. Times, Sunday Times (2015)These diseases are referred to as endemic diseases.McKenzie, James F. & Pinger, Robert R. An Introduction to Community Health (1995)It is an endemic problem for naturalresourcescompanies. Times, Sunday Times (2013)The disease then becomes endemic and one is committed to a continuingpolicy of annualvaccination. Times, Sunday Times (2007)In this case we say the disease has become endemic. Times, Sunday Times (2009)Calling for a publicinquiry can really be the beginning of the end of this endemic national problem. The Sun (2012) Corruption remains endemic and inflation high. Times, Sunday Times (2011)By now, sabotage has become endemic. Times, Sunday Times (2012)Thusdisregard for the law, pettybribery and corruption were endemic.Grenville, J. A. S. The Collins History of the World in the 20th Century (1994)Promisedbureaucratic and ruralreformswill take effect only slowly, not least because corruption is endemic. Times, Sunday Times (2006)Knifecrime has become endemic. The Sun (2009)It now has endemic unemployment. Times, Sunday Times (2012)There is still no need to panic, but if you are in an endemic area you should keep your cats indoors. Times, Sunday Times (2006)He added: 'It is time to gettough on this endemic crime. Times, Sunday Times (2011)He said: 'It is a sort of corruption that has become endemic in the system. Times, Sunday Times (2012)Of course, by no means all victims are rich: poor on poor crime is more endemic still. Times, Sunday Times (2010)Medicalexpertstell us this could be mainlydue to the large influx into the UK of people from countries where the illness is endemic. The Sun (2014)It should stop subsidising incompetent providers and employers through the New Deal and allowfailure to become an endemic part of the system. Times, Sunday Times (2008)


Endemism and species richness are highly relevant to the global prioritization of conservation efforts in which oceanic islands have remained relatively neglected. When compared to mainland areas, oceanic islands in general are known for their high percentage of endemic species but only moderate levels of species richness, prompting the question of their relative conservation value. Here we quantify geographic patterns of endemism-scaled richness (“endemism richness”) of vascular plants across 90 terrestrial biogeographic regions, including islands, worldwide and evaluate their congruence with terrestrial vertebrates. Endemism richness of plants and vertebrates is strongly related, and values on islands exceed those of mainland regions by a factor of 9.5 and 8.1 for plants and vertebrates, respectively. Comparisons of different measures of past and future human impact and land cover change further reveal marked differences between mainland and island regions. While island and mainland regions suffered equally from past habitat loss, we find the human impact index, a measure of current threat, to be significantly higher on islands. Projected land-cover changes for the year 2100 indicate that land-use-driven changes on islands might strongly increase in the future. Given their conservation risks, smaller land areas, and high levels of endemism richness, islands may offer particularly high returns for species conservation efforts and therefore warrant a high priority in global biodiversity conservation in this century.

Worldwide loss of biodiversity requires global conservation priority setting to channel limited international conservation resources to regions of highest conservation value and need for action (1–5). Approaches for using biological data as a component of priority setting vary but can largely be divided into (i) algorithm-based assessments such as minimum-area sets or gap analyses (2, 6–8) and (ii) index-based assessments using indices such as endemism or species richness as surrogates for the conservation value of a region (1, 4, 9). While many theoretical arguments underpin the strengths of algorithm-based assessments (2, 8, 10, 11), they require detailed distribution data that are only available for few taxonomic groups—almost exclusively terrestrial vertebrates (6, 9, 12–15), on which systematic conservation planning has thus relied increasingly in the past years. Such detailed data are not available for the vast majority of taxonomic groups on the global scale including vascular plants. Although great effort is being made in digitizing existing data from natural history collections for conservation purposes (16, 17), biodiversity loss is arguably proceeding more rapidly than the documentation of species distributions. Hence, an inventory-based approach, which forms a main basis for the present study, is a workable solution if global conservation planning is to be informed by vascular plants (18), a group of organisms which is of outstanding ecological and economical importance for human well-being (19).

Islands are well-known centers of range-restricted species and thus see high levels of endemism (20). However, they are simultaneously acknowledged for their lower species richness compared to mainland areas (20). Hence, an index combining both endemism and species richness (“endemism richness”) can provide insight into the question of relative conservation value of islands and mainlands. Such an index has been calculated in a number of regional-to-continental-scale studies (21–25), which, however, have not focused on the differences between mainlands and islands. The basic concept of calculating endemism richness is to give each species the same value that is equally distributed across its range (21). For instance, when 100% of a species' range, i.e., 1 range equivalent, falls into a mapping unit (such as a grid cell or, as in the present study, a biogeographic region), its entire value is attributed to this area. When half of the species' distribution area falls into a mapping unit, only 50% of its value, or 0.5 range equivalents, are attributed to the mapping unit and so on. Summing up the fractions of range equivalents for all species within each mapping unit would then reflect both endemism and species richness (21, 26). In contrast to species richness, values of endemism richness on average show a linear relation with area at a given sampling scale and can thus be corrected for area disparity by linear conversion (21). Furthermore, unlike species richness or species endemism, the combined metric of endemism richness shows another useful property: The sum of all range equivalents of all mapping units yields the total number of species in the analysis—in our case, the global number of species in the studied taxa. Consequently, endemism richness can be interpreted as the specific contribution of an area to global biodiversity (21).

Here we calculated endemism richness of vascular plants for 90 biogeographic regions covering the entire terrestrial realm (except for Antarctica where the value is negligible). We compared our plant-based results to the spatial pattern of endemism richness of terrestrial vertebrates (amphibians, reptiles, birds, mammals) to quantify, for the first time, how well vascular plants capture the diversity of this charismatic group (and vice versa) and how taxon-specific differences might affect prioritization rankings. In this study, we specifically focused on comparing biodiversity of mainlands and islands because of the as yet undecided question of their relative conservation importance. Furthermore, islands are centers of past and imminent species extinction (27, 28), stressing even more the need for information on both biodiversity and specific threats in this part of the world.

Results and Discussion

Summing up the range equivalents of vascular plants for all 90 regions yields a total of 315,903. Given that the sum of range equivalents in the entire study area should be equal to the total number of species and assuming the data underlying our study accurately capture regional species numbers and degree of endemism, this suggests that recent estimates of global vascular plant richness ranging up to 422,000 species (29–31) may be too high. We found endemism richness of vascular plants to be geographically highly unevenly distributed (Fig. 1A) and it varied by 3 orders of magnitude (see Table S1). From a global perspective, the island of New Caledonia had by far the highest value with 1,350 range equivalents per 10,000 km2—a similar result has emerged from a coarse-scaled, grid-based study at the family level (32). Values were also high for other island regions, such as Polynesia–Micronesia, the Eastern Pacific, and the Atlantic Islands. Although accounting for only 3.6% of the terrestrial surface of the world, 26.1% of all range equivalents of plants are allotted to the 14 island regions. When standardized at 10,000 km2, we found endemism richness to be 9.5 times higher on islands than in mainland regions (172.3 and 18.2 range equivalents per 10,000 km2, respectively).

Fig. 1.

Global patterns of endemism richness (ER; range equivalents per 10,000 km2) for (A) vascular plants, (B) terrestrial vertebrates, (C) amphibians, (D) reptiles, (E) birds, and (F) mammals across 90 biogeographic regions. Map legends were classified using quantiles, i.e., each color class contains a comparable number of regions. Box-and-whisker plots illustrate rank-based differences in endemism richness between mainland (n = 76; white boxes) and island regions (n = 14; gray boxes). Boxes mark second and third quartiles; whiskers mark the range of the data.

The island regions spanned a smaller latitudinal extent and were closer to the equator, possibly distorting the overall picture as species richness increases and average range size decreases toward the equator. We therefore repeated the calculation, restricting the mainland regions to the same latitudinal extent by excluding the 5 northernmost regions. As to be expected, this led to an increase in endemism richness on mainlands, but mainland regions still showed much lower average endemism richness (23.8 range equivalents per 10,000 km2).

Half of the top 20 regions in terms of endemism richness per standard area were island regions (Fig. 1A, Fig. S1). In fact, all but one (Japan) ranked among the top third of the 90 regions and all island regions had above average ranks (F1,88 = 31.5, P < 0.001; Fig. 1A). The top 30 regions contained 51.6% of the total range equivalents of vascular plants on only 7.4% of the Earth's terrestrial surface (Fig. 3A). Qualitatively similar spatial patterns of endemism richness across the 90 regions were also found for terrestrial vertebrates (Fig. 1B–F). Island regions had significantly higher endemism richness of vertebrates (8.1 times higher than for mainland regions) and islands contained 23.2% of the range equivalents of this group (Table S2). To test whether the plant-based delineation of biogeographic regions or the relatively coarse resolution of our mapping scheme had an effect on these findings, we divided up the 867 ecoregions (33) into mainlands and islands and compared their endemism richness. Endemism richness of island ecoregions for all 4 individual vertebrate classes and terrestrial vertebrates combined was significantly higher than for mainland regions (Fig. S2), which demonstrated that these results were robust toward the geographic delineation and across spatial scales.

Endemism richness of plants showed a relatively strong correlation with the entire group of vertebrates (rs = 0.83), indicating a generally strong congruence of global patterns of endemism richness. The overall trend was similar, but stronger than recently found for patterns of richness (34). However, the degree of correlation within the 4 classes differed markedly (individual vertebrate classes: rs = 0.73−0.82; Fig. 2 and Fig. S3). Furthermore, there were also striking exceptions, especially in the case of amphibians. The 4 vertebrate classes also performed differently in the degree of their range equivalents being captured by a ranking of areas on the basis of plant endemism richness per standard area. Among all vertebrate classes, amphibians were best represented by the plant-based ranking. On the other hand, relatively fewer mammalian range equivalents were covered (Fig. 3B). For instance, 48.5% of all amphibian but only 31.9% of all mammalian range equivalents were covered by the top 30 regions in terms of plant endemism richness. Together, the results highlight a strong role of taxon-specific characteristics [e.g., the relatively poor ability of amphibians to cross saltwater barriers (35)] on patterns of cross-taxon congruence limiting the use of surrogate taxa in conservation.

Fig. 2.

Cross-taxon congruence of endemism richness (ER; range equivalents per 10,000 km2) of vascular plant and terrestrial vertebrate classes. Ranked values of (A) amphibians, (B) reptiles, (C) birds, and (D) mammals are plotted against vascular plants. Red dots indicate island regions, gray dots mainland regions. Values of Spearman's rank correlation coefficient (rs) are shown for each relationship (all P < 0.001).

Fig. 3.

Performance of a prioritization ranking on the basis of vascular plants. (A) Two different rankings are compared: For ranking 1 (blue), regions were ranked in descending order according to their total number of range equivalents. Ranking 2 (red) ranked regions in descending order on the basis of their endemism richness per 10,000 km2. Curves indicate the accumulation of range equivalents (solid lines) and area (dotted lines) across the rankings and are contrasted against a random expectation (gray lines; mean values and 95% confidence intervals for 10,000 random rankings). Islands are highlighted by orange circles. (B) Cross-taxon performance of plant-based ranking 2 (red) for terrestrial vertebrates. The ranked regions appear on the x axis; values on the y axis indicate the proportion of all range equivalents covered.

Our results clearly identified islands as global centers of endemism richness, a pattern that was consistent across plants and vertebrates (although least pronounced for amphibians) (Figs. 1, 2, and Fig. S3). The very high values of endemism richness on islands are especially noteworthy because species richness on islands is generally lower than on mainland sites with comparable climate (20, 36). Island floras and faunas are usually recognized to maintain a high degree of endemism because of their geographic isolation and the limited interchange with neighboring mainland or island biota. Moreover, volcanic archipelagos like the Canary Islands or Hawaii are good examples of relatively recent and rapid adaptive radiations that have resulted in many neoendemic taxa (20, 37, 38). On the other hand, some ancient continental fragments like New Caledonia, Madagascar, the Seychelles, or New Zealand harbor very distinct paleoendemic lineages (20). Similarly, also some oceanic islands and archipelagos also have a high proportion of relict island species and clades that show a remarkable resistance toward massive historical climatic changes that have caused their mainland relatives to become extinct (39). An intrinsic feature of islands may indeed be that they are climatically buffered by the thermally relatively unresponsive ocean masses (39). Both mechanisms, persistence of old lineages and adaptive diversifications, contribute to the high levels of insular endemism richness, but their relative importance remains to be quantified. At the same time, paleoendemic island lineages might deserve particular conservation attention, as these species are taxonomically isolated and represent a larger amount of unique evolutionary history than closely related neoendemic lineages (40).

Among mainland areas, regions with Mediterranean-type climate emerge as global centers of plant endemism richness (Fig. 1A). The South African Cape region, a prime example of exceptionally high extratropical plant richness and endemism (41–45), ranked second among all 90 biogeographic regions (Fig. S1). Interestingly, the high degree of endemism and the contribution of only a limited number of “Cape floral clades” to the astonishing richness of the region have been attributed to island-like biogeographic and evolutionary processes (42). The large peninsula of the Cape is surrounded by oceans on 3 sides and by desert regions to the north and it is thus geographically very isolated (42). A similar interplay between a unique climatic setting, geographic isolation, and high rates of in situ speciation might possibly explain the high endemism richness of plants in other “island-like” continental areas such as, e.g., the SW Australian floristic province or the Queensland tropical rainforests. Regions with wet tropical climate and complex topography emerged as mainland centers of plant endemism richness and shared centers across taxa. For instance, the northern Andes ranked ninth in terms of endemism richness of plants and seventh for terrestrial vertebrates, respectively (Fig. S1, Tables S1 and S3). This region has been previously shown to be a congruency center of different aspects of diversity such as species richness, threat, and endemism for vertebrates (15). Our results confirm this globally exceptional regional concentration of biodiversity from a plant perspective. The high values of tropical montane areas might be partly because of steep elevational and climatic gradients resulting in high species turnover (41, 46, 47). These regions are also regarded as both museums and cradles of biodiversity, where old taxa have survived, among others, because of relatively stable climates or the mitigation of climate change impacts by altitudinal range shifts. Additionally, new taxa are being rapidly generated because of new ecological opportunities caused by recent uplifts. In combination with limited gene flow and effective dispersal barriers, this has led to considerable radiations in many clades resulting in high numbers of range-restricted species (48–50).

The high values of endemism richness on islands emphasize their outstanding importance for global conservation of genetic resources. But their limited area (Fig. 4A) may make them especially vulnerable to anthropogenic impacts. We thus quantified the spatial relationship between endemism richness and various measures of past and projected future human impact. A significant relationship existed between plant endemism richness and past habitat loss (rs = 0.24, P = 0.02, Fig. S4), but no significant difference was found between island and mainland (F1,88 = 1.3; P = 0.26; Fig. 4B). While this indicates that island and mainland regions were sim-ilarly affected by habitat loss in the past, there are pronounced differences in the level of current threat and projected land cover change. The “human impact index,” an index quantifying the worldwide presence of humans per 1 km2 grid cell (51), was significantly higher for islands (15.7) than for mainlands (9.8) (F1,88 = 7.7; P < 0.01; Fig. 4C). “Human impact” showed a strong positive correlation with endemism richness (rs = 0.45, P < 0.001). When we examined projected future land cover changes driven by either direct human activity (agriculture, deforestation, urbanization) or climate change as predicted for the year 2100 by the Millennium Ecosystem Assessment (52), an apparent dichotomy surfaced between island and mainland regions. Whereas future habitat loss driven by land-use change is projected to accelerate for island regions (F1,88 = 2.8; P = 0.097; Fig. 4D), mainland regions are predicted to lose more of their original land cover because of climate change (F1,88 = 3.0; P = 0.088; Fig. 4E). Although the 2 latter observations are not statistically significant, they suggest differences which might be explained by 2 island-specific characteristics. First, their oceanic setting might buffer islands from more severe impacts caused by climate change except for sea-level rise. Second, their small area and already high degree of infrastructure (compare high human impact index for islands, Fig. 4C) make islands more vulnerable to habitat destruction as access to remote parts with remaining primary vegetation is comparatively easy. The discrepancy between past and potential future threats of biodiversity may have strong implications for conservation and represents one of the most pressing questions for conservation planners (53). Importantly, the greater risk of islands toward habitat loss and their considerably higher levels of endemism richness is currently not reflected in the protected area network where islands (8.3% of area protected) are less protected than mainlands (10.6%) (Fig. 4F). On the basis of these findings, we suggest that conservation of island biodiversity requires the expansion of existing protected area networks to counteract the threats that island diversity faces as a result of the extraordinarily high levels of human impact. Furthermore, effective measures need to be taken to address threats that cannot be mitigated by protected areas alone, including threats arising from invasive species (54, 55). Island populations have been shown to be particularly susceptible to biotic perturbations (56), which are likely to increase with climate-change induced distributional shifts and increasing global trade. Such increased threats from invasive species require thoughtful measures in addition to the designation and effective management of protected areas.

Fig. 4.

Comparison of key conservation features for mainland (green) and island regions (orange). (A) Variation in area sizes, (B) past land-cover loss (year 2000), (C) human impact (year 2000), (D) future land-cover loss (projections for the year 2100 according to ref. 52) because of land-use change and, (E) because of climate change, (F) current protection status (proportion covered by protected areas). Values in B–F represent ranks. Significance codes indicate differences (Mann-Whitney U-test) between mainlands and islands: ***, P < 0.001; **, P < 0.01; *, P < 0.1; ns, not significant.

There is high overlap between regions of highest endemism richness and “biodiversity hotspots” (5). This is not surprising given their two main criteria: ≥ 1,500 endemic plant species and the loss of ≥70% of its original vegetation because of human activities (1). Among the 20 regions with highest endemism richness per standard area, sixteen overlap with recognized hotspots (Fig. S1). When supplementing endemism richness with the criterion of habitat loss, a high overlap can also be noted (Fig. S4). However, the comparison with vertebrate endemism richness sheds critical light on the value of previously recognized plant hotspots for the conservation of animal groups (Figs. 1, 2, and Fig. S3). This is best illustrated by New Caledonia, which exhibited the world's highest plant endemism richness, but has no native extant amphibians. On the other hand, regions like the South American Pacific coastal deserts, the Guinea-Congolia/Sudania Regional Transition Zone, or the South American Chaco, are not outstanding in terms of plant endemism richness, but show consistently much higher values for vertebrates.

By calculating endemism richness for all terrestrial regions, the present study puts the hotspots into a global context and also reaffirms the procedure of prioritizing hotspots by means of a linear conversion of endemic species to a standard area (1). Of course, the resulting figures do not reflect the number of endemics present on the standard area (57, 58), but rather the minimum values of endemism richness (21, 25). A further review of hotspots should include much more detailed, taxon-based data, as performed for Africa (59) or for the Indo-Pacific (60).

A lot of data collecting and processing still needs to be accomplished to improve the accuracy of our knowledge on endemism richness on the global scale, especially for vascular plants. Only for 43 regions (48%), data quality was rated good or very good while being poor or very poor for 47 regions (Table S1). Overall, the data quality for the purpose of this study was better for island than for mainland regions: Ten of the 14 island regions (71%) had good or very good data quality. Partly, this might be attributed to the fact that islands are discrete spatial entities clearly defining the geographic extent of a study. In combination with their comparatively low species numbers, this may make islands more attractive to detailed floristic and faunistic inventorying and taxonomic work than less clearly defined, large mainland regions. It remains a great challenge that in most parts of the world, distribution data are only available for parts of the flora (45). Even the data set on Australian plant distributions, which is one of the best available continental data sets, covering about half of all known Australian plant species, has a pronounced geographic bias because of the absence of data from the Western Australian Herbarium (22). However, our approach of combining such “taxon-based” data sets with inventory data enabled us to partially address this problem by giving higher weight to inventory data whenever biases were known to exist in the taxon-based data and vice versa. Another potential source of error in the data might arise from the tendency to describe taxa as separate species on islands, artificially inflating endemism richness on islands in comparison to the mainland. However, quantitative studies testing this hypothesis are lacking and doubts remain as to whether this effect is important enough to explain the large differences in endemism richness between islands and mainlands.

Whenever priority setting and environmental impact assessments use endemism richness as a basis (e.g., when data are lacking or not of adequate quality for algorithm-based calculations), they should not rely on this criterion alone. Maximal representation and conservation of the global species pool will additionally benefit from taking into account further criteria such as biogeographic characteristics (2). Our study gives equal existence value to each species. However, for many purposes species' importance may vary and be affected by attributes such as their phylogenetic and functional uniqueness (61, 62). Further, (nonglobal) local extinctions, which our study does not quantify, may have serious repercussions for ecosystem functions and services (63, 64). Attention should also be paid to the influence of spatial scale: We here identified regions with high values of endemism richness at a rather broad spatial resolution, but it remains a future challenge to optimize conservation strategies by systematic assessments of conservation priorities within these regions (17). Finally, in an era characterized by climate change and the loss of important biological and socioeconomic functions of ecosystems (65, 66), halting or even reversing these developments should be an equally important target of a global conservation strategy.

Materials and Methods

Delineation of Regions.

Global patterns of endemism richness of vascular plants (i.e., ferns, gymnosperms, and angiosperms) and of terrestrial tetrapod vertebrates (amphibians, reptiles, birds, and mammals) were quantified across 90 biogeographic regions (14 island and 76 mainland regions). We divided the terrestrial realm into 90 regions on the basis of 4 criteria. First, we separated oceanic island areas from continental areas, but assigned islands with mainly continental floras to continents (e.g., Mediterranean islands, British Isles). The only case of a continental area assigned to an island region is Peninsular Malaysia, which was treated as a part of the Sundaland archipelago because this was deemed appropriate according to most of our delineation criteria. The other 3 criteria were biogeography, availability of data and, wherever appropriate, compatibility with boundaries of ecoregions (33) and biodiversity hotspots (5) for the data presented here to be usable within these frameworks and to enable direct comparisons with them. For a listing of the main biogeographical classifications used for the delineation of regions see Table S4. Islands were usually combined, mainly on the basis of the system of Conservation International (5). Furthermore, our aim was to avoid a delineation that results in island regions which, although biogeographically distinct, are negligible in their level of total endemism richness from a global perspective. To this end, we formed island groups with at least 500 endemic species each by combining islands and archipelagos in the Atlantic Ocean, Polynesia, Micronesia, and the Eastern Pacific Ocean. To visualize biogeographical divisions within these island regions, they were displayed on the map as dotted lines (Fig. 1). Geographic data are available from authors on request.

Calculating Endemism Richness and Spatial Congruence of Cross-Taxon Patterns.

Endemism and species richness are widely used indicators of conservation value (1, 4, 53) and an index combining both has been calculated and mapped at regional-to-continental scales (21–24, 26) but not at the global scale. Because of its property of combining endemism and species richness, it is here called an index of endemism richness (21), whereas it has also been termed “range size rarity” (26) or “weighted endemism” (22, 23) in the literature. The standard method of calculating endemism richness (“taxon-based method”) is based on distribution data for single taxa within grid cells: For each grid cell, the inverse range sizes of all species occurring in that grid cell are summed up (24). Because of a lack of adequate distribution data, this method cannot be applied to vascular plant species at the global scale across all continents and island areas. An alternative calculation method (“inventory-based method”) is based on the number of species and endemics and on the chorology, i.e., the affiliation of a species to a broader biogeographic group such as “Holarctic element,” “Mediterranean endemic,” or “endemic to the Amazon basin” (21, 25). In our assessment of plant endemism richness, we combined both approaches, for 2 reasons. First, for the majority of regions data were only available to apply 1 of the 2 methods. Second, data for both approaches can include a certain level of error (e.g., because of weakly representative samples in range map databases), so counterchecking both types of data helped to improve the reliability of our results.

(i) Taxon-based method (plants and vertebrates): For several regions, large data sets with range maps of a large number of vascular plant species were available. Endemism richness was calculated as the sum of inverse range sizes (24) and then extrapolated to the total flora (e.g., by multiplying the resulting values by 20 when range maps were available for 5% of the flora) and corrected for area, using a standard area of 10,000 km2 (21). Range size was measured as the number of grid cells or ecoregions in which a species occurs. Grid-based data sets were available for the following regions: Africa (67), Neotropics (68), Bolivia (69); a map with endemism richness values was available for Australia (22). Ecoregion-based data were available for Indo-Malayan (60). Distribution data for 26,586 terrestrial vertebrate species (4,792 amphibians, 7,506 reptiles, 9,585 birds, and 4,703 mammals) were derived from Wildfinder (70) for all 867 terrestrial ecoregions (33). Range size was measured as the total area of the ecoregions where a species was recorded. To investigate whether the plant-based delineation of the 90 regions or the rather coarse spatial resolution dictated by the limited data availability for plants had an effect on our analyses, we compared ecoregion-based values of vertebrate endemism richness separately (Fig. S2).

(ii) Inventory-based method (plants only): The flora of each region was divided into chorological groups based on the most detailed literature data available. The amount of range equivalents attributed to the region was calculated for each group as the fraction of the region compared to the assumed total distribution area of each chorological group multiplied by the number of species of the chorological group. The resulting values for all chorological groups were summed up to yield the total number of range equivalents for the region. This total figure was divided by the area size of the region in km2 and multiplied by 10,000 to yield the number of range equivalents per 10,000 km2. See ref. 21 for details.

Spatial congruence of cross-taxon patterns of endemism richness was assessed by pairwise comparisons of vascular plants and the 4 vertebrate classes using Spearman's rank correlation coefficient (Fig. 2, Fig. S3). Additionally, we investigated the representativeness of plant-based rankings in capturing diversity patterns of vertebrates (Fig. 3).

Assessing Past and Future Threat for Mainland and Island Regions.

We assessed past and future threats of island and mainland regions using different indices of land cover loss, human presence, and protection status from digitally available data sets. We used the Human Impact Index (HII) (51, 71), a composite measure of 8 global data layers referring to urban extent, population density, roads, navigable rivers, and agricultural land (spatial resolution: 1 km2). HII varies between 0 and 64 and refers largely to the year 2000. We also looked at the Human Footprint (51), which is the standardized version of HII by biome membership and obtained qualitatively and quantitatively similar results. Past habitat loss was assessed using a reclassified version of the Global Land Cover 2000 data set (72, 73) as the percentage of total land area classified as cultivated or managed, mosaics including cropland, and urban areas. As a proxy for protection status, we used the percentage of land area falling in the International Union for Conservation of Nature (IUCN) protected area categories I–VI (74). Future habitat loss was evaluated for the year 2100 using the projections of the Millennium Ecosystem Assessment (52), which were averaged across all 4 socioeconomic scenarios. This data set allowed a comparison of climate change-driven and land use-driven (53, 75) changes in land cover. Changes in land cover were classified as climate change-driven or land use-driven (53, 75) and proportional changes were calculated across the 90 regions. All data sets were processed in a geographic information system (76). Data analysis was conducted using standard spreadsheet software and the software package R (77).


>We are grateful to the following persons and institutions for granting us access to partly unpublished plant distribution data: Claudia Raedig, Gary Krupnick, Shawn Laffan, and all institutions which have built up the biogeographical information system data set on African plant distributions (BISAP). Frank La Sorte and Hamish Wilman provided valuable comments on the manuscript. We thank Henning Sommer, Wolfgang Küper, and Daud Rafiqpoor for stimulating discussions and anonymous reviewers for helpful, constructive, and critical comments. This project has been funded by the Academy of Sciences and Literature Mainz (“Biodiversity in Change” Program), the Wilhelm Lauer Foundation, and the German Federal Ministry of Education and Research (BIOLOG BIOTA Program). W. J. was supported by a National Science Foundation Grant BCS-0648733. H.K. was supported by a Feodor-Lynen Fellowship from the Alexander von Humboldt Foundation.


  • 2To whom correspondence should be addressed. E-mail: hkreft{at}
  • Author contributions: G.K., H.K., and T.M.L. designed research; G.K., H.K., and T.M.L. performed research; W.J., P.L.I., C.N., J.M., and W.B. contributed analytical data; G.K., H.K., and T.M.L. analyzed data; and G.K., H.K., T.M.L., W.J., P.L.I., C.N., J.M., and W.B. wrote the paper.

  • The authors declare no conflict of interest.

  • This article is a PNAS Direct Submission.

  • This article contains supporting information online at

  • Freely available online through the PNAS open access option.


0 Thoughts to “Define Endemism With An Example Of An Essay

Leave a comment

L'indirizzo email non verrà pubblicato. I campi obbligatori sono contrassegnati *