Species distribution

Species distribution is the manner in which a biological taxon is spatially arranged. The geographic limits of a particular taxon's distribution is its range, often represented as shaded areas on a map. Patterns of distribution change depending the scale at which they are viewed, from the arrangement of individuals within a small family unit, to patterns within a population, or the distribution of the entire species as a whole (range). Species distribution is not to be confused with dispersal, which is the movement of individuals away from their region of origin or from a population center of high density.

Juniperus communis range map
A species range map represents the region where individuals of a species can be found. This is a range map of Juniperus communis, the common juniper.

Range

In biology, the range of a species is the geographical area within which that species can be found. Within that range, distribution is the general structure of the species population, while dispersion is the variation in its population density.

Range is often described with the following qualities:

  • Sometimes a distinction is made between a species' natural, endemic, indigenous, or native range, where it has historically originated and lived, and the range where a species has more recently established itself. Many terms are used to describe the new range, such as non-native, naturalized, introduced, transplanted, invasive, or colonized range.[1] Introduced typically means that a species has been transported by humans (intentionally or accidentally) across a major geographical barrier.[2]
  • For species found in different regions at different times of year, especially seasons, terms such as summer range and winter range are often employed.
  • For species for which only part of their range is used for breeding activity, the terms breeding range and non-breeding range are used.
  • For mobile animals, the term natural range is often used, as opposed to areas where it occurs as a vagrant.
  • Geographic or temporal qualifiers are often added, such as in British range or pre-1950 range. The typical geographic ranges could be the latitudinal range and elevational range.

Disjunct distribution occurs when two or more areas of the range of a taxon are considerably separated from each other geographically.

Factors affecting distribution

Distribution patterns may change by season, distribution by humans, in response to the availability of resources, and other abiotic and biotic factors.

Abiotic

There are three main types of abiotic factors:

  1. climatic factors consist of sunlight, atmosphere, humidity, temperature, and salinity;
  2. edaphic factors are abiotic factors regarding soil, such as the coarseness of soil, local geology, soil pH, and aeration; and
  3. social factors include land use and water availability.

An example of the effects of abiotic factors on species distribution can be seen in drier areas, where most individuals of a species will gather around water sources, forming a clumped distribution.

Researchers from the Arctic Ocean Diversity (ARCOD) project have documented rising numbers of warm-water crustaceans in the seas around Norway's Svalbard Islands. Arcod is part of the Census of Marine Life, a huge 10-year project involving researchers in more than 80 nations that aims to chart the diversity, distribution and abundance of life in the oceans. Marine Life has become largely affected by increasing effects of global warming. This study shows that as the ocean temperatures rise species are beginning to travel into the cold and harsh Arctic waters. Even the snow crab has extended its range 500 km north.

Biotic

Biotic factors such as predation, disease, and competition for resources such as food, water, and mates, can also affect how a species is distributed. For example, biotic factors in a quail’s environment would include their prey (insects and seeds), competition from other quail, and their predators, such as the coyote.[3] An advantage of a herd, community, or other clumped distribution allows a population to detect predators earlier, at a greater distance, and potentially mount an effective defense. Due to limited resources, populations may be evenly distributed to minimize competition,[4] as is found in forests, where competition for sunlight produces an even distribution of trees.[5]

Humans are one of the largest distributors due to the current trends in globalization and the expanse of the transportation industry. For example, large tankers often fill their ballasts with water at one port and empty them in another, causing a wider distribution of aquatic species.[6]

Patterns on large scales

On large scales, the pattern of distribution among individuals in a population is clumped.[7]

Bird wildlife corridors

One common example of bird species' ranges are land mass areas bordering water bodies, such as oceans, rivers, or lakes; they are called a coastal strip. A second example, some species of bird depend on water, usually a river, swamp, etc., or water related forest and live in a river corridor. A separate example of a river corridor would be a river corridor that includes the entire drainage, having the edge of the range delimited by mountains, or higher elevations; the river itself would be a smaller percentage of this entire wildlife corridor, but the corridor is created because of the river.

A further example of a bird wildlife corridor would be a mountain range corridor. In the U.S. of North America, the Sierra Nevada range in the west, and the Appalachian Mountains in the east are two examples of this habitat, used in summer, and winter, by separate species, for different reasons.

Bird species in these corridors are connected to a main range for the species (contiguous range) or are in an isolated geographic range and be a disjunct range. Birds leaving the area, if they migrate, would leave connected to the main range or have to fly over land not connected to the wildlife corridor; thus, they would be passage migrants over land that they stop on for an intermittent, hit or miss, visit.

Patterns on small scales

Population distribution
Three basic types of population distribution within a regional range are (from top to bottom) uniform, random, and clumped.

On large scales, the pattern of distribution among individuals in a population is clumped. On small scales, the pattern may be clumped, regular, or random.[7]

Clumped

Clumped distribution is the most common type of dispersion found in nature. In clumped distribution, the distance between neighboring individuals is minimized. This type of distribution is found in environments that are characterized by patchy resources. Animals need certain resources to survive, and when these resources become rare during certain parts of the year animals tend to “clump” together around these crucial resources. Individuals might be clustered together in an area due to social factors such as selfish herds and family groups. Organisms that usually serve as prey form clumped distributions in areas where they can hide and detect predators easily.

Other causes of clumped distributions are the inability of offspring to independently move from their habitat. This is seen in juvenile animals that are immobile and strongly dependent upon parental care. For example, the bald eagle's nest of eaglets exhibits a clumped species distribution because all the offspring are in a small subset of a survey area before they learn to fly. Clumped distribution can be beneficial to the individuals in that group. However, in some herbivore cases, such as cows and wildebeests, the vegetation around them can suffer, especially if animals target one plant in particular.

Clumped distribution in species acts as a mechanism against predation as well as an efficient mechanism to trap or corner prey. African wild dogs, Lycaon pictus, use the technique of communal hunting to increase their success rate at catching prey. Studies have shown that larger packs of African wild dogs tend to have a greater number of successful kills. A prime example of clumped distribution due to patchy resources is the wildlife in Africa during the dry season; lions, hyenas, giraffes, elephants, gazelles, and many more animals are clumped by small water sources that are present in the severe dry season.[8] It has also been observed that extinct and threatened species are more likely to be clumped in their distribution on a phylogeny. The reasoning behind this is that they share traits that increase vulnerability to extinction because related taxa are often located within the same broad geographical or habitat types where human-induced threats are concentrated. Using recently developed complete phylogenies for mammalian carnivores and primates it has been shown that the majority of instances threatened species are far from randomly distributed among taxa and phylogenetic clades and display clumped distribution.[9]

A contiguous distribution is one in which individuals are closer together than they would be if they were randomly or evenly distributed, i.e., it is clumped distribution with a single clump. [10]

Regular or uniform

Less common than clumped distribution, uniform distribution, also known as even distribution, is evenly spaced. Uniform distributions are found in populations in which the distance between neighboring individuals is maximized. The need to maximize the space between individuals generally arises from competition for a resource such as moisture or nutrients, or as a result of direct social interactions between individuals within the population, such as territoriality. For example, penguins often exhibit uniform spacing by aggressively defending their territory among their neighbors. The burrows of great gerbils for example are also regularly distributed,[11] which can be seen on satellite images.[12] Plants also exhibit uniform distributions, like the creosote bushes in the southwestern region of the United States. Salvia leucophylla is a species in California that naturally grows in uniform spacing. This flower releases chemicals called terpenes which inhibit the growth of other plants around it and results in uniform distribution.[13] This is an example of allelopathy, which is the release of chemicals from plant parts by leaching, root exudation, volatilization, residue decomposition and other processes. Allelopathy can have beneficial, harmful, or neutral effects on surrounding organisms. Some allelochemicals even have selective effects on surrounding organisms; for example, the tree species Leucaena leucocephala exudes a chemical that inhibits the growth of other plants but not those of its own species, and thus can affect the distribution of specific rival species. Allelopathy usually results in uniform distributions, and its potential to suppress weeds is being researched.[14] Farming and agricultural practices often create uniform distribution in areas where it would not previously exist, for example, orange trees growing in rows on a plantation.

Random

Random distribution, also known as unpredictable spacing, is the least common form of distribution in nature and occurs when the members of a given species are found in environments in which the position of each individual is independent of the other individuals: they neither attract nor repel one another. Random distribution is rare in nature as biotic factors, such as the interactions with neighboring individuals, and abiotic factors, such as climate or soil conditions, generally cause organisms to be either clustered or spread. Random distribution usually occurs in habitats where environmental conditions and resources are consistent. This pattern of dispersion is characterized by the lack of any strong social interactions between species. For example; When dandelion seeds are dispersed by wind, random distribution will often occur as the seedlings land in random places determined by uncontrollable factors. Oyster larvae can also travel hundreds of kilometers powered by sea currents, which can result in their random distribution.

Statistical determination of distribution patterns

There are various ways to determine the distribution pattern of species. The Clark–Evans nearest neighbor method[15] can be used to determine if a distribution is clumped, uniform, or random.[16] To utilize the Clark–Evans nearest neighbor method, researchers examine a population of a single species. The distance of an individual to its nearest neighbor is recorded for each individual in the sample. For two individuals that are each other's nearest neighbor, the distance is recorded twice, once for each individual. To receive accurate results, it is suggested that the number of distance measurements is at least 50. The average distance between nearest neighbors is compared to the expected distance in the case of random distribution to give the ratio:

If this ratio R is equal to 1, then the population is randomly dispersed. If R is significantly greater than 1, the population is evenly dispersed. Lastly, if R is significantly less than 1, the population is clumped. Statistical tests (such as t-test, chi squared, etc.) can then be used to determine whether R is significantly different from 1.

The variance/mean ratio method focuses mainly on determining whether a species fits a randomly spaced distribution, but can also be used as evidence for either an even or clumped distribution.[17] To utilize the Variance/Mean ratio method, data is collected from several random samples of a given population. In this analysis, it is imperative that data from at least 50 sample plots is considered. The number of individuals present in each sample is compared to the expected counts in the case of random distribution. The expected distribution can be found using Poisson distribution. If the variance/mean ratio is equal to 1, the population is found to be randomly distributed. If it is significantly greater than 1, the population is found to be clumped distribution. Finally, if the ratio is significantly less than 1, the population is found to be evenly distributed. Typical statistical tests used to find the significance of the variance/mean ratio include Student's t-test and chi squared.

However, many researchers believe that species distribution models based on statistical analysis, without including ecological models and theories, are too incomplete for prediction. Instead of conclusions based on presence-absence data, probabilities that convey the likelihood a species will occupy a given area are more preferred because these models include an estimate of confidence in the likelihood of the species being present/absent. Additionally, they are also more valuable than data collected based on simple presence or absence because models based on probability allow the formation of spatial maps that indicates how likely a species is to be found in a particular area. Similar areas can then be compared to see how likely it is that a species will occur there also; this leads to a relationship between habitat suitability and species occurrence.[18]

Species distribution models

Species distribution can be predicted based on the pattern of biodiversity at spatial scales. A general hierarchical model can integrate disturbance, dispersal and population dynamics. Based on factors of dispersal, disturbance, resources limiting climate, and other species distribution, predictions of species distribution can create a bio-climate range, or bio-climate envelope. The envelope can range from a local to a global scale or from a density independence to dependence. The hierarchical model takes into consideration the requirements, impacts or resources as well as local extinctions in disturbance factors. Models can integrate the dispersal/migration model, the disturbance model, and abundance model. Species distribution models (SDMs) can be used to assess climate change impacts and conservation management issues. Species distribution models include: presence/absence models, the dispersal/migration models, disturbance models, and abundance models. A prevalent way of creating predicted distribution maps for different species is to reclassify a land cover layer depending on whether or not the species in question would be predicted to habit each cover type. This simple SDM is often modified through the use of range data or ancillary information, such as elevation or water distance.

Recent studies have indicated that the grid size used can have an effect on the output of these species distribution models.[19] The standard 50x50 km grid size can select up to 2.89 times more area than when modeled with a 1x1 km grid for the same species. This has several effects on the species conservation planning under climate change predictions (global climate models, which are frequently used in the creation of species distribution models, usually consist of 50–100 km size grids) which could lead to over-prediction of future ranges in species distribution modeling. This can result in the misidentification of protected areas intended for a species future habitat.

Species Distribution Grids Project

The Species Distribution Grids Project is an effort led out of the University of Columbia to create maps and databases of the whereabouts of various animal species. This work is centered on preventing deforestation and prioritizing areas based on species richness.[20] As of April 2009, data are available for global amphibian distributions, as well as birds and mammals in the Americas. The map gallery Gridded Species Distribution contains sample maps for the Species Grids data set. These maps are not inclusive but rather contain a representative sample of the types of data available for download:

North America

Species richness map (amphibians)

North America birds

Species richness map (birds)

North America mammals

Species richness map (mammals)

See also

Notes

  1. ^ Colautti, Robert I.; MacIsaac, Hugh J. (2004). "A neutral terminology to define 'invasive' species" (PDF). Diversity and Distributions. 10 (2): 135–41. doi:10.1111/j.1366-9516.2004.00061.x. ISSN 1366-9516.
  2. ^ Richardson, David M.; Pysek, Petr; Rejmanek, Marcel; Barbour, Michael G.; Panetta, F. Dane; West, Carol J. (2000). "Naturalization and invasion of alien plants: concepts and definitions". Diversity and Distributions. 6 (2): 93–107. doi:10.1046/j.1472-4642.2000.00083.x. ISSN 1366-9516.
  3. ^ "Biotic factor".
  4. ^ Campbell, Reece. Biology. eight edition
  5. ^ "Abiotic factor".
  6. ^ Hülsmann, Norbert; Galil, Bella S. (2002), Leppäkoski, Erkki; Gollasch, Stephan; Olenin, Sergej (eds.), "Protists — A Dominant Component of the Ballast-Transported Biota", Invasive Aquatic Species of Europe. Distribution, Impacts and Management, Springer Netherlands, pp. 20–26, doi:10.1007/978-94-015-9956-6_3, ISBN 9789401599566, retrieved 2019-05-28
  7. ^ a b Molles, Jr., Manuel C. (2008). Ecology: concepts and applications (4th ed.). McGraw-Hill Higher Education. ISBN 9780073050829.
  8. ^ Creel, N.M. and S. (1995). "Communal Hunting and Pack Size in African Wild Dogs, Lycaon pictus". Animal Behaviour. 50: 1325–1339. doi:10.1016/0003-3472(95)80048-4.
  9. ^ Purvis, A; Agapowe, P-M; Gittleman, JL; Mace, GM (2000). "Non-random extinction and the loss of evolutionary history". Science. 288: 328–330. doi:10.1126/science.288.5464.328.
  10. ^ "Aggregated/clumped/contiguous distribution",
  11. ^ Wilschut, L.I; Laudisoit, A.; Hughes, N.K; Addink, E.A.; de Jong, S.M.; Heesterbeek, J.A.P.; Reijniers, J.; Eagle, S.; Dubyanskiy, V.M.; Begon, M. (19 May 2015). "Spatial distribution patterns of plague hosts: point pattern analysis of the burrows of great gerbils in Kazakhstan". Journal of Biogeography. 42 (7): 1281–1292. doi:10.1111/jbi.12534. PMC 4737218.
  12. ^ Wilschut, L.I; Addink, E.A.; Heesterbeek, J.A.P.; Dubyanskiy, V.M; Davis, S.A.; Laudisoit, A.; Begon, M.; Burdelov, L.A.; Atshabar, B.B.; de Jong, S.M. (2013). "Mapping the distribution of the main host for plague in a complex landscape in Kazakhstan: An object-based approach using SPOT-5 XS, Landsat 7 ETM+, SRTM and multiple Random Forests". International Journal of Applied Earth Observation and Geoinformation. 23: 81–94. doi:10.1016/j.jag.2012.11.007. PMC 4010295.
  13. ^ Mauseth, James (2008). Botany: An Introduction to Plant Biology. Jones and Bartlett Publishers. p. 596. ISBN 0-7637-5345-9.
  14. ^ Fergusen, J.J; Rathinasabapathi, B (2003). "Allelopathy: How Plants Suppress Other Plants". Retrieved 2009-04-06.
  15. ^ Philip J. Clark and Francis C. Evans (Oct 1954). "Distance to Nearest Neighbor as a Measure of Spatial Relationships in Populations". Ecology. Ecological Society of America. 35 (4): 445–453. doi:10.2307/1931034.
  16. ^ Blackith, R. E. (1958). Nearest-Neighbour Distance Measurements for the Estimation of Animal Populations. Ecology. pp. 147–150.
  17. ^ Banerjee, B. (1976). Variance to mean ratio and the spatial distribution of animals. Birkhäuser Basel. pp. 993–994.
  18. ^ Ormerod, S.J.; Vaughan, I.P. (2005). "The continuing challenges of testing species distribution models". Journal of Applied Ecology. 42 (4): 720–730. doi:10.1111/j.1365-2664.2005.01052.x. Archived from the original on 2013-01-05.
  19. ^ "Species Distribution Modeling". University of Vermont.
  20. ^ "Scientists develop Species Distribution Grids". EarthSky. Archived from the original on 2009-04-14. Retrieved 2009-04-08.

External links

Aldehyde oxidase

Aldehyde oxidase (AO) is a metabolizing enzyme, located in the cytosolic compartment of tissues in many organisms. AO catalyzes the oxidation of aldehydes into carboxylic acid, and in addition, catalyzes the hydroxylation of some heterocycles. It can also catalyze the oxidation of both cytochrome P450

(CYP450) and monoamine oxidase (MAO) intermediate products. AO plays an important role in the metabolism of several drugs.

Androctonus australis hector insect toxin

Androctonus australis hector insect toxin also known as AaHIT is a scorpion toxin which affects voltage-gated sodium channels. Four different insect toxins, namely AaHIT1, AaHIT2, AaHIT4 and AaHIT5, can be distinguished. It targets insects, except AaHIT4, which is also toxic to crustaceans and mammals.

Biological dispersal

Biological dispersal refers to both the movement of individuals (animals, plants, fungi, bacteria, etc.) from their birth site to their breeding site ('natal dispersal'), as well as the movement from one breeding site to another ('breeding dispersal').

Dispersal is also used to describe the movement of propagules such as seeds and spores.

Technically, dispersal is defined as any movement that has the potential to lead to gene flow.

The act of dispersal involves three phases: departure, transfer, settlement and there are different fitness costs and benefits associated with each of these phases.

Through simply moving from one habitat patch to another, the dispersal of an individual has consequences not only for individual fitness, but also for population dynamics, population genetics, and species distribution. Understanding dispersal and the consequences both for evolutionary strategies at a species level, and for processes at an ecosystem level, requires understanding on the type of dispersal, the dispersal range of a given species, and the dispersal mechanisms involved.

Biological dispersal may be contrasted with geodispersal, which is the mixing of previously isolated populations (or whole biotas) following the erosion of geographic barriers to dispersal or gene flow (Lieberman, 2005; Albert and Reis, 2011).

Dispersal can be distinguished from animal migration (typically round-trip seasonal movement), although within the population genetics literature, the terms 'migration' and 'dispersal' are often used interchangeably.

Cdc25

Cdc25 is a dual-specificity phosphatase first isolated from the yeast Schizosaccharomyces pombe as a cell cycle defective mutant. As with other cell cycle proteins or genes such as Cdc2 and Cdc4, the "cdc" in its name refers to "cell division cycle".

Dual-specificity phosphatases are considered a sub-class of protein tyrosine phosphatases. By removing inhibitory phosphate residues from target cyclin-dependent kinases (Cdks), Cdc25 proteins control entry into and progression through various phases of the cell cycle, including mitosis and S ("Synthesis") phase.

Freshwater biology

Freshwater biology is the scientific biological study of freshwater ecosystems and is a branch of limnology. This field seeks to understand the relationships between living organisms in their physical environment. These physical environments may include rivers, lakes, streams, or wetlands. This discipline is also widely used in industrial processes to make use of biological processes such as sewage treatment and water purification. Water flow is an essential aspect to species distribution and influence when and where species interact in freshwater environments.In the UK the Freshwater Biological Association based near Windermere in Cumbria was one of the early institutions to research te biology of freshwater and promote the concepts of trophism in lakes and demonstrated the process of migration from oligotrophic water through mesotrophic to marsh.

Freshwater biology is also used to study the effects of climate change and increased human impact on both aquatic systems and wider ecosystems.

Frizzled

Frizzled is a family of G protein-coupled receptor proteins that serves as receptors in the Wnt signaling pathway and other signaling pathways. When activated, Frizzled leads to activation of Dishevelled in the cytosol.

Fructose 1,6-bisphosphatase

Fructose bisphosphatase (EC 3.1.3.11) is an enzyme that converts fructose-1,6-bisphosphate to fructose 6-phosphate in gluconeogenesis and the Calvin cycle which are both anabolic pathways. Fructose bisphosphatase catalyses the conversion of fructose-1,6-bisphosphate to fructose-6-phosphate, which is the reverse of the reaction which is catalysed by phosphofructokinase in glycolysis. These enzymes only catalyse the reaction in one direction each, and are regulated by metabolites such as fructose 2,6-bisphosphate so that high activity of one of the two enzymes is accompanied by low activity of the other. More specifically, fructose 2,6-bisphosphate allosterically inhibits fructose 1,6-bisphosphatase, but activates phosphofructokinase-I. Fructose 1,6-bisphosphatase is involved in many different metabolic pathways and found in most organisms. FBPase requires metal ions for catalysis (Mg2+ and Mn2+ being preferred) and the enzyme is potently inhibited by Li+.

Genesis flood narrative

The Genesis flood narrative is a flood myth found in the Tanakh (chapters 6–9 in the Book of Genesis). The story tells of God's decision to return the Earth to its pre-creation state of watery chaos and then remake it in a reversal of creation. The narrative has very strong similarities to parts of the Epic of Gilgamesh which predates the Book of Genesis.

A global flood as described in this myth is inconsistent with the physical findings of geology and paleontology. A branch of creationism known as flood geology is a pseudoscientific attempt to argue that such a global flood actually occurred.

Glucose-6-phosphate dehydrogenase

Glucose-6-phosphate dehydrogenase (G6PD or G6PDH) (EC 1.1.1.49) is a cytosolic enzyme that catalyzes the chemical reaction

D-glucose 6-phosphate + NADP+ ⇌ 6-phospho-D-glucono-1,5-lactone + NADPH + H+This enzyme participates in the pentose phosphate pathway (see image), a metabolic pathway that supplies reducing energy to cells (such as erythrocytes) by maintaining the level of the co-enzyme nicotinamide adenine dinucleotide phosphate (NADPH). The NADPH in turn maintains the level of glutathione in these cells that helps protect the red blood cells against oxidative damage from compounds like hydrogen peroxide. Of greater quantitative importance is the production of NADPH for tissues involved in biosynthesis of fatty acids or isoprenoids, such as the liver, mammary glands, adipose tissue, and the adrenal glands. G6PD reduces NADP+ to NADPH while oxidizing glucose-6-phosphate.Clinically, an X-linked genetic deficiency of G6PD predisposes a person to non-immune hemolytic anemia.

Hydroxymethylglutaryl-CoA synthase

In molecular biology, Hydroxymethylglutaryl-CoA synthase or HMG-CoA synthase EC 2.3.3.10 is an enzyme which catalyzes the reaction in which Acetyl-CoA condenses with acetoacetyl-CoA to form 3-hydroxy-3-methylglutaryl-CoA (HMG-CoA). It is the second reaction in the mevalonate-dependent isoprenoid biosynthesis pathway. HMG-CoA is an intermediate in both cholesterol synthesis and ketogenesis. This reaction is over-activated in patients with diabetes mellitus type 1 if left untreated, due to prolonged insulin deficiency and the exhaustion of substrates for gluconeogenesis and the TCA cycle, notably oxaloacetate. This results in shunting of excess acetyl-CoA into the ketone synthesis pathway via HMG-CoA, leading to the development of diabetic ketoacidosis.

The 3 substrates of this enzyme are acetyl-CoA, H2O, and acetoacetyl-CoA, whereas its two products are (S)-3-hydroxy-3-methylglutaryl-CoA and CoA.

In humans, the protein is encoded by the HMGCS1 gene on chromosome 5.

Mef2

In the field of molecular biology, myocyte enhancer factor-2 (Mef2) proteins are a family of transcription factors which through control of gene expression are important regulators of cellular differentiation and consequently play a critical role in embryonic development. In adult organisms, Mef2 proteins mediate the stress response in some tissues. Mef2 proteins contain both MADS-box and Mef2 DNA-binding domains.

Mir-2 microRNA precursor

The mir-2 microRNA family includes the microRNA genes mir-2 and mir-13 (MIPF0000049). Mir-2 is widespread in invertebrates, and it is the largest family of microRNAs in the model species Drosophila melanogaster. MicroRNAs from this family are produced from the 3' arm of the precursor hairpin. Leaman et al. showed that the miR-2 family regulates cell survival by translational repression of proapoptotic factors. Based on computational prediction of targets, a role in neural development and maintenance has been suggested.

OPN5

Neuropsin is a protein that in humans is encoded by the OPN5 gene. It is a photoreceptor protein sensitive to ultraviolet (UV) light. The OPN5 gene was discovered in mouse and human genomes and its mRNA expression was also found in neural tissues. Neuropsin is bistable at 0 °C and activates a UV-sensitive, heterotrimeric G protein Gi-mediated pathway in mammalian and avian tissues.

Phytogeography

Phytogeography (from Greek φυτόν, phytón = "plant" and γεωγραφία, geographía = "geography" meaning also distribution) or botanical geography is the branch of biogeography that is concerned with the geographic distribution of plant species and their influence on the earth's surface. Phytogeography is concerned with all aspects of plant distribution, from the controls on the distribution of individual species ranges (at both large and small scales, see species distribution) to the factors that govern the composition of entire communities and floras. Geobotany, by contrast, focuses on the geographic space's influence on plants.

RFX1

MHC class II regulatory factor RFX1 is a protein that, in humans, is encoded by the RFX1 gene located on the short arm of chromosome 19.

Sirtuin

Sirtuins are a class of proteins that possess either mono-ADP-ribosyltransferase, or deacylase activity, including deacetylase, desuccinylase, demalonylase, demyristoylase and depalmitoylase activity. The name Sir2 comes from the yeast gene 'silent mating-type information regulation 2', the gene responsible for cellular regulation in yeast.

Sirtuins have been implicated in influencing a wide range of cellular processes like aging, transcription, apoptosis, inflammation and stress resistance, as well as energy efficiency and alertness during low-calorie situations. Sirtuins can also control circadian clocks and mitochondrial biogenesis.

Yeast Sir2 and some, but not all, sirtuins are protein deacetylases. Unlike other known protein deacetylases, which simply hydrolyze acetyl-lysine residues, the sirtuin-mediated deacetylation reaction couples lysine deacetylation to NAD hydrolysis. This hydrolysis yields O-acetyl-ADP-ribose, the deacetylated substrate and nicotinamide, which is an inhibitor of sirtuin activity itself. The dependence of sirtuins on NAD links their enzymatic activity directly to the energy status of the cell via the cellular NAD:NADH ratio, the absolute levels of NAD, NADH or nicotinamide or a combination of these variables.

Sirtuins that deacetylate histones are structurally and mechanistically distinct from other classes of histone deacetylases (classes I, IIA, IIB and IV), which have a different protein fold and use Zn2+ as a cofactor.

Small nucleolar RNA snR54

snR54 is a non-coding RNA that is a member of the C/D class of snoRNA which contain the C box motif (UGAUGA) and D box motif (CUGA). Most of the members of the box C/D family function in directing site-specific 2'-O-methylation of substrate RNAs. This snoRNA was first identified by a computational screen followed by experimental verification. This RNA guides the 2'-O-methylation of 18S rRNA. In yeast this snoRNA is found to reside in an intron of the IMD4 gene.

Snakefly

Snakeflies are a group of insects comprising the order Raphidioptera, which is divided into two families: Raphidiidae and Inocelliidae consisting of roughly 260 species. Together with the Megaloptera they were formerly placed within the Neuroptera, but now these two are generally regarded as separate orders. Members of this order have been considered living fossils, as the phenotype of a species from the early Jurassic period (140 million years ago) closely resembles modern-day species.

Species distribution modelling

Species distribution modelling (SDM), also known as environmental (or ecological) niche modelling (ENM), habitat modelling, predictive habitat distribution modelling, and range mapping uses computer algorithms to predict the distribution of a species across geographic space and time using environmental data. The environmental data are most often climate data (e.g. temperature, precipitation), but can include other variables such as soil type, water depth, and land cover. SDMs are used in several research areas in conservation biology, ecology and evolution. These models can be used to understand how environmental conditions influence the occurrence or abundance of a species, and for predictive purposes (ecological forecasting). Predictions from an SDM may be of a species’ future distribution under climate change, a species’ past distribution in order to assess evolutionary relationships, or the potential future distribution of an invasive species. Predictions of current and/or future habitat suitability can be useful for management applications (e.g. reintroduction or translocation of vulnerable species, reserve placement in anticipation of climate change).

There are two main types of SDMs. Correlative SDMs, also known as climate envelope models, bioclimatic models, or resource selection function models, model the observed distribution of a species as a function of environmental conditions. Mechanistic SDMs, also known as process-based models or biophysical models, use independently derived information about a species' physiology to develop a model of the environmental conditions under which the species can exist.The extent to which such modelled data reflect real-world species distributions will depend on a number of factors, including the nature, complexity, and accuracy of the models used and the quality of the available environmental data layers; the availability of sufficient and reliable species distribution data as model input; and the influence of various factors such as barriers to dispersal, geologic history, or biotic interactions, that increase the difference between the realized niche and the fundamental niche. Environmental niche modelling may be considered a part of the discipline of biodiversity informatics.

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Languages

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