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. Biogeography is the study of the distribution of and in and through.
Organisms and biological often vary in a regular fashion along geographic gradients of, and habitat. Is the branch of biogeography that studies the distribution of plants. Is the branch that studies distribution of animals. Knowledge of spatial variation in the numbers and types of organisms is as vital to us today as it was to our early human, as we adapt to heterogeneous but geographically predictable. Biogeography is an integrative field of inquiry that unites concepts and information from, and. Modern biogeographic research combines information and ideas from many fields, from the physiological and ecological constraints on organismal to and phenomena operating at global spatial scales and time frames. The short-term interactions within a habitat and species of organisms describe the ecological application of biogeography.
Historical biogeography describes the long-term, evolutionary periods of time for broader classifications of organisms. Early scientists, beginning with, contributed to the development of biogeography as a science. Beginning in the mid-18th century, Europeans explored the world and discovered the of life. The scientific theory of biogeography grows out of the work of (1769–1859), (1804–1881), (1806–1893), (1823–1913), (1829–1913) and other biologists and explorers. Contents. Introduction The patterns of species distribution across geographical areas can usually be explained through a combination of historical factors such as:, and. Through observing the geographic distribution of species, we can see associated variations in, river routes, habitat, and.
Additionally, this science considers the geographic constraints of areas and isolation, as well as the available ecosystem energy supplies. Over periods of changes, biogeography includes the study of plant and animal species in: their past and/or present living; their interim living sites; and/or their survival locales. As writer David Quammen put it, '.biogeography does more than ask Which species? It also asks Why? And, what is sometimes more crucial, Why not?' Modern biogeography often employs the use of (GIS), to understand the factors affecting organism distribution, and to predict future trends in organism distribution.
Often mathematical models and GIS are employed to solve ecological problems that have a spatial aspect to them. Biogeography is most keenly observed on the world's. These habitats are often much more manageable areas of study because they are more condensed than larger ecosystems on the mainland. Islands are also ideal locations because they allow scientists to look at habitats that new have only recently colonized and can observe how they disperse throughout the island and change it. They can then apply their understanding to similar but more complex mainland habitats.
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Download kannada songs video. Islands are very diverse in their, ranging from the tropical to arctic climates. This diversity in habitat allows for a wide range of species study in different parts of the world. One scientist who recognized the importance of these geographic locations was, who remarked in his journal 'The Zoology of Archipelagoes will be well worth examination'. Two chapters in were devoted to geographical distribution. History 18th century The first discoveries that contributed to the development of biogeography as a science began in the mid-18th century, as Europeans explored the world and discovered the biodiversity of life. During the 18th century most views on the world were shaped around religion and for many natural theologists, the bible., in the mid-18th century, initiated the ways to classify organisms through his exploration of undiscovered territories.
When he noticed that species were not as perpetual as he believed, he developed the Mountain Explanation to explain the distribution of biodiversity. When Noah’s ark landed on Mount Ararat and the waters receded, the animals dispersed throughout different elevations on the mountain. This showed different species in different climates proving species were not constant. Linnaeus’ findings set a basis for ecological biogeography. Biffy clyro band. Through his strong beliefs in Christianity, he was inspired to classify the living world, which then gave way to additional accounts of secular views on geographical distribution.
He argued that the structure of an animal was very closely related to its physical surroundings. This was important to a George Louis Buffon’s rival theory of distribution. Distribution of four Permian and Triassic fossil groups used as biogeographic evidence for continental drift, and land bridging Moving on to the 20th century, introduced the Theory of in 1912, though it was not widely accepted until the 1960s. This theory was revolutionary because it changed the way that everyone thought about species and their distribution around the globe. The theory explained how continents were formerly joined together in one large landmass, and slowly drifted apart due to the movement of the plates below Earth’s surface.
The evidence for this theory is in the geological similarities between varying locations around the globe, fossil comparisons from different continents, and the jigsaw puzzle shape of the landmasses on Earth. Though Wegener did not know the mechanism of this concept of Continental Drift, this contribution to the study of biogeography was significant in the way that it shed light on the importance of environmental and geographic similarities or differences as a result of climate and other pressures on the planet. Importantly, late in his career Wegener recognised that testing his theory required measurement of continental movement rather than inference from fossils species distributions. The publication of by and in 1967 showed that the species richness of an area could be predicted in terms of such factors as habitat area, immigration rate and extinction rate.
This added to the long-standing interest in. The application of island biogeography theory to spurred the development of the fields of and. Classic biogeography has been expanded by the development of, creating a new discipline known as. This development allowed scientists to test theories about the origin and dispersal of populations, such as. For example, while classic biogeographers were able to speculate about the origins of species in the, phylogeography allows them to test theories of relatedness between these populations and putative source populations in and. Biogeography continues as a point of study for many life sciences and geography students worldwide, however it may be under different broader titles within institutions such as ecology or evolutionary biology.
In recent years, one of the most important and consequential developments in biogeography has been to show how multiple organisms, including mammals like monkeys and reptiles like lizards, overcame barriers such as large oceans that many biogeographers formerly believed were impossible to cross. Biogeographic regions of Europe Modern applications Biogeography now incorporates many different fields including but not limited to physical geography, geology, botany and plant biology, zoology, and general biology. A biogeographer’s main focus is on what environmental factors and what the influence of humans do to the distribution of the specific species of study. In terms of applications of biogeography as a science today, technological advances have allowed satellite imaging and processing of the Earth.
Two main types of satellite imaging that are important within modern biogeography are Global Production Efficiency Model (GLO-PEM) and Geographic Information Systems (GIS). GLO-PEM uses satellite-imaging gives “repetitive, spatially contiguous, and time specific observations of vegetation.” These observations are on a global scale. GIS can show certain processes on the earth’s surface like whale locations, sea surface temperatures, and bathymetry. Current scientists also use coral reefs to delve into the history of biogeography through the fossilized reefs. Paleobiogeography Paleobiogeography goes one step further to include data and considerations of. Using molecular analyses and corroborated by, it has been possible to demonstrate that evolved first in the region of or the adjacent (which at that time lay somewhat further north and had a temperate climate).
From there, they spread to the other continents and Southeast Asia – the part of then closest to their origin of dispersal – in the late, before achieving a global distribution in the early. Not knowing that at the time of dispersal, the Indian Ocean was much narrower than it is today, and that South America was closer to the Antarctic, one would be hard pressed to explain the presence of many 'ancient' lineages of perching birds in Africa, as well as the mainly South American distribution of the. Paleobiogeography also helps constrain hypotheses on the timing of biogeographic events such as and, and provides unique information on the formation of regional biotas. For example, data from species-level phylogenetic and biogeographic studies tell us that the fish fauna accumulated in increments over a period of tens of millions of years, principally by means of allopatric speciation, and in an arena extending over most of the area of tropical South America (Albert & Reis 2011). In other words, unlike some of the well-known insular faunas (, Hawaiian drosophilid flies, African rift lake ), the species-rich Amazonian ichthyofauna is not the result of recent. For organisms, landscapes are divided naturally into discrete by, episodically isolated and reunited by processes.
In regions like the (or more generally Greater Amazonia, the Amazon basin, basin, and ) with an exceptionally low (flat) topographic relief, the many waterways have had a highly reticulated history over. In such a context, is an important factor affecting the evolution and distribution of freshwater organisms. Stream capture occurs when an upstream portion of one river drainage is diverted to the downstream portion of an adjacent basin. This can happen as a result of (or ), natural damming created by a, or headward or lateral of the watershed between adjacent basins. Concepts and fields Biogeography is a synthetic science, related to, and.
Introduction Biogeography is the discipline interested in documenting and understanding spatial biodiversity patterns and also in explaining the evolutionary history that led to this current spatial configuration –. Detailed data regarding how organisms are distributed, the basis of biogeographical studies, enable such distribution patterns to be identified, including natural biogeographical units –. These natural biogeographical regions are fundamental units of comparison in many broad-scale ecological and evolutionary studies , and provide an essential tool for conservation planning ,–. There are several methods proposed to identify biogeographical units (e.g., ,–). A well-known method is the parsimony analysis of endemicity that is used to detect natural biogeographical units in named areas of endemism ,.
According to some authors (e.g., ,), areas of endemism have a unique biota with similar historical processes and are the basis for postulating hypotheses regarding the processes that led to their origin. However, the determination of natural biogeographical units based solely on strict endemism is effective only in cases of strict sympatry , that is not so common in natural conditions. Dispersal and extinction are natural events that can cause noise in the identification of areas of endemism and hinder the recognition of natural biogeographical units ,.
For this reason, biotic element analysis has been used in many studies as an alternative method to detect natural biogeographical units (e.g., ,–). The biotic element analysis identifies groups of taxa with geographic distributions significantly more similar to one another ,. The advantage is that biotic elements may be recognized even when part of the taxa originated by vicariance has dispersed across barriers ,. The biotic element analysis is based on the assumption of vicariance and postulates that diversification results from fragmentation of the ancestral biota by the emergence of barriers ,. Consequently, it is expected that the distributions of taxa with the same geographical origin are more similar to each other than to the distributions of taxa from distinct geographical origins, and the taxa that are closely related due to the vicariance process belong to distinct biotic elements ,. The identification of natural biogeographical units is important to understand the evolutionary history of taxa and of the areas that encompass them, and such studies in natural environments are incipient , as in the case of the biota from the sandy plains of the coastal ridges of Brazil.
The coastal sandplains are commonly known as Restingas and are included in the Tropical Atlantic Domain , which also includes the Atlantic Forest, a global biodiversity hotspot. Studies on different biological groups, especially those focused on forest habitats of the Atlantic Forest in Brazil, have been carried out to identify distributional patterns ,. Biogeographic studies have not yet addressed the distribution patterns of amphibian communities or the processes that have shaped these communities. Additionally, studies in the Restingas area of the Tropical Atlantic Domain is neglected, as most investigations have focused on the forested part of this domain –.
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For this reason, we assessed for the first time the amphibian distribution patterns in a biogeographical study of Restingas. The aims of our study were: (1) to identify distribution patterns of anuran species occurring on sandy plains of beach ridges of the eastern Brazilian coast; (2) to detect natural biogeographical units throughout the study area and to identify groups of anuran species with non-random overlapping geographical distribution (biotic elements); and (3) to provide the first formal test of two predictions of the vicariance model to evaluate the hypothesis that the diversification of these species can be a result of fragmentation of the ancestral biota by emerging barriers. Study area The east coast of Brazil is located within the Tropical Atlantic Domain and is essentially covered by the Atlantic Forest, a global biodiversity hotspot. The Restinga is a component of the Atlantic Forest habitat characterized by dunes and sandy plains covered by herbaceous and shrubby vegetation under direct sunlight (‘open Restinga’, ), having experienced extensive degradation over the past five centuries. The term Restinga has been used indiscriminately to refer to all types of vegetation that occur in quaternary coastal plains, including the forest vegetation of the lowlands and slopes of the Serra do Mar mountains. Thus, to avoid ambiguity, the term Restinga used in this study is based on topography and follows Rocha and collaborators , Souza and collaborators , and Franco and collaborators that stated: Restingas are quaternary habitats characterized by sandy soils with high salt concentration covered by predominantly herbaceous and shrubby xerophytic vegetation. Additionally, we also considered in the analysis non-forested sites represented by plains and wet lowlands adjacent to coastal sand ridges, as many amphibian species inhabiting the Restingas commonly use these areas for reproduction and foraging.
Structure of the spatial distribution of anuran species We searched the main geographical variation patterns in anuran species composition along the eastern Brazilian coast using an indirect gradient analysis. We used the non-metric multidimensional scaling method (NMDS) for reducing the anuran composition dataset (Matrix A) to one or more synthetic axes. Initially, we searched for the best dimensionality to represent the data set.
Six dimensions were generated (6D solution) from the Matrix A, by the Bray-Curtis distance coefficient. To avoid the local minima problem , we ran 40 starting configurations, using as stability criteria the instability value of 0.000010, 15 iterations to evaluate the stability of the solution and 400 as the maximum number of iterations (see ). The Monte Carlo test was used to evaluate whether NMDS extracted a stronger axis than expected by chance. The result indicated that the best solution would be reached by a two dimensional analysis.
A new analysis was performed using a two-dimensional (2D) solution with the following settings: 1000 starting configurations, using as stability criteria the instability value of 0,0005, 999 iterations to evaluate the stability of the solution and 500 as the maximum number of iterations. The Monte Carlo test (999 randomizations) was used to evaluate whether NMDS extracted a stronger axis than expected by chance. The NMDS axes were rotated to a new varimax solution. The proportion of variance represented by the NMDS axis, based on the correlation between distance in the ordination space (Euclidian distance) and distance in the original space (Bray-Curtis distance), was obtained by the standardized Mantel test (r).
As a last step, a new NMDS analysis was performed with only one dimension (1D solution), using the same 2D configuration settings, to verify whether the 1D solution would be able to synthesize the main pattern of variation in anuran species composition along the eastern Brazilian coast. We tested the presence of monotonic variation of anuran composition (quadrats; dependent variable) along the latitudinal gradient (independent variable) by single linear regression analysis. The assumption of normal distribution was tested by the Shapiro-Wilk W test and also by the projection of the normal distribution curve over a histogram distribution (observed frequencies); the assumption of linearity was checked by the projection of the variables of interest on a scatter diagram, followed by the ‘runs test’ performed in Prism software version 3.0. The level of significance was set at P ≤ 0.05. Biotic element analyses The predictions of the vicariance model regarding distribution patterns of amphibians were tested using the biotic element analysis , which searches for biogeographical units under the vicariance model perspective. Biotic elements (BE) are groups of taxa in which the distributions are significantly more similar to one another than to those of taxa from another group. This analysis was carried out with prabclus package in the statistical software R using Matrix A (see ).
Biotic element analysis is based on tests of two predictions of the vicariance model. The first prediction states that division of the ancestral biota should produce groups of taxa that are significantly regionalized ,. The second prediction states that closely related species must be found within distinct biotic elements ,.
Three measures are required to test the null hypothesis that the species distribution ranges are not significantly regionalized (first prediction): a distance measure between the distribution limits of the taxa examined, a statistical test, and a null model to generate sets of random ranges. We chose the geco distance coefficient instead of the Kulczynski distance (default in prabclus) because it considers not only the percentage of geographical units shared by taxa, but also the geographical relationships of the occupied units –. For the required geco coefficient, we used f = 0.2.
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The T test was used based on the assumption that given a significant clustering of scales, the distances between the distribution ranges of the same group will be smaller than those between the ranges of different groups. The distribution of the test statistic under the null model was estimated by a Monte Carlo test. To test the second prediction of the vicariance model, which states that closely related species must be distributed among distinct biotic elements , the chi-square test ( X 2) was used to analyze the distribution of congeneric species among biotic elements (see ,). Once it was found that amphibians in the study area are divided into groups of species with significantly regionalized ranges, the next step was to identify the biotic elements. Non-metric multidimensional scaling (NMDS) was applied to the geco distance matrix generated in the previous step.
Model-based Gaussian clustering (MBGC) was used on the same geco distance matrix to identify the biotic elements (BE). The percentage of a species distribution in each grid was calculated based on the total species distributed among the different biotic elements. The region with the highest (greater than 75%) percentage of species distribution was defined as the “core area” of each biotic element (see ,).
Structure of the spatial distribution of anuran species The NMDS axes obtained using two dimensions (2D) reflected the structuring in the distribution of the sampling units (SUs). The 2D NMDS solution resulted in a stress value of 11.7 and the extracted axes were stronger than expected by chance (Monte Carlo test, P. Projection of individual scores resulting from the non-metric multidimensional scaling method (NMDS) for 22 quadrats (sample units). The one-dimensional (1D) NMDS solution expressed a linear structure in the distribution of anuran species SUs , but with a high stress value (30.5). Even so, NMDS extracted a stronger axis than expected by chance (Monte Carlo test, P.
Biotic elements in the Restinga Biotic element analysis carried out for 63 anuran species corroborated the main vicariance model predictions: (i) the distribution was found to be significantly clustered, forming a regionalized biota along the sandy plains of the beach ridges of the eastern coast of Brazil. The T statistic obtained was 0.146, significantly smaller (P. S1 Appendix Matrix A. Anuran species (n = 63) per sample quadrat (Q1–Q22) used in the analyses. Sample units were ordered following the.
Geographic regions of biotic elements are indicated by the following abbreviations: NE—Northeastern, SE—Southeastern, and S—Southern. Biotic elements (BE) are numbered from BE1 to BE4, and N represents model-based clustering with noise. Cells with number one indicate species presence; blank cells, species absence. Anuran families are also indicated: Bu, Bufonidae; Cr, Craugastoridae; Hy, Hylidae; Le, Leptodactylidae; Mi, Microhylidae; Od, Odontophrynidae.