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Naslov:Machine learning approaches identify male body size as the most accurate predictor of species richness
Avtorji:ID Čandek, Klemen (Avtor)
ID Pristovšek, Urška (Avtor)
ID Kuntner, Matjaž (Avtor)
Datoteke:URL URL - Izvorni URL, za dostop obiščite https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-020-00835-y
 
.pdf PDF - Predstavitvena datoteka, prenos (1,78 MB)
MD5: 5938D34BE4A64EC9D804D2A5B6A642FD
 
Jezik:Angleški jezik
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:Logo NIB - Nacionalni inštitut za biologijo
Povzetek:Background A major challenge in biodiversity science is to understand the factors contributing to the variability of species richness –the number of different species in a community or region - among comparable taxonomic lineages. Multiple biotic and abiotic factors have been hypothesized to have an effect on species richness and have been used as its predictors, but identifying accurate predictors is not straightforward. Spiders are a highly diverse group, with some 48,000 species in 120 families; yet nearly 75% of all species are found within just the ten most speciose families. Here we use a Random Forest machine learning algorithm to test the predictive power of different variables hypothesized to affect species richness of spider genera. Results We test the predictive power of 22 variables from spiders’ morphological, genetic, geographic, ecological and behavioral landscapes on species richness of 45 genera selected to represent the phylogenetic and biological breath of Araneae. Among the variables, Random Forest analyses find body size (specifically, minimum male body size) to best predict species richness. Multiple Correspondence analysis confirms this outcome through a negative relationship between male body size and species richness. Multiple Correspondence analyses furthermore establish that geographic distribution of congeneric species is positively associated with genus diversity, and that genera from phylogenetically older lineages are species poorer. Of the spider-specific traits, neither the presence of ballooning behavior, nor sexual size dimorphism, can predict species richness. Conclusions We show that machine learning analyses can be used in deciphering the factors associated with diversity patterns. Since no spider-specific biology could predict species richness, but the biologically universal body size did, we believe these conclusions are worthy of broader biological testing. Future work on other groups of organisms will establish whether the detected associations of species richness with small body size and wide geographic ranges hold more broadly.
Ključne besede:biodiversity, lineage diversity, species traits, spiders, phylogenetic diversity, species distribution, random forest, multiple correspondence analysis
Status publikacije:Objavljeno
Verzija publikacije:Objavljena publikacija
Datum objave:28.08.2020
Leto izida:2020
Št. strani:str. 1-16
Številčenje:18, article no. ǂ105
PID:20.500.12556/DiRROS-19527 Novo okno
UDK:574.1
ISSN pri članku:1741-7007
DOI:10.1186/s12915-020-00835-y Novo okno
COBISS.SI-ID:27512067 Novo okno
Opomba:Nasl. z nasl. zaslona; Opis vira z dne 8. 9. 2020;
Datum objave v DiRROS:22.07.2024
Število ogledov:440
Število prenosov:324
Metapodatki:XML DC-XML DC-RDF
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Gradivo je del revije

Naslov:BMC biology
Založnik:BioMed Central
ISSN:1741-7007
COBISS.SI-ID:515673881 Novo okno

Gradivo je financirano iz projekta

Financer:ARIS - Javna agencija za znanstvenoraziskovalno in inovacijsko dejavnost Republike Slovenije
Številka projekta:J1-9163-2018
Naslov:Evolucijske slepe ulice: Pasti ekstremnih fenotipov

Financer:ARIS - Javna agencija za znanstvenoraziskovalno in inovacijsko dejavnost Republike Slovenije
Številka projekta:P1-0236-2018
Naslov:Biodiverziteta: vzorci, procesi, predikcije in ohranjanje

Financer:ARIS - Javna agencija za znanstvenoraziskovalno in inovacijsko dejavnost Republike Slovenije
Številka projekta:P1-0255-2017
Naslov:Združbe, interakcije in komunikacije v ekosistemih

Licence

Licenca:CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:biodiverziteta, diverziteta rodovniških linij, lastnosti vrst, pajki, filogenetska raznolikost, razporeditev vrst, naključni gozd, multipla korespondenčna analiza


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