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Iskalni niz: "ključne besede" (random forest) .

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1.
Machine learning approaches identify male body size as the most accurate predictor of species richness
Klemen Čandek, Urška Pristovšek, Matjaž Kuntner, 2020, izvirni znanstveni članek

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
Objavljeno v DiRROS: 22.07.2024; Ogledov: 3; Prenosov: 4
.pdf Celotno besedilo (1,78 MB)
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2.
Climate–growth relationships in Laurus azorica - a dominant tree in the Azorean Laurel forest
Diogo C. Pavão, Jernej Jevšenak, Lurdes Borges Silva, Rui Bento Elias, Luis Silva, 2023, izvirni znanstveni članek

Povzetek: Forests on oceanic islands, such as the Azores archipelago, enable interesting dendroclimatic research, given their pronounced climatic gradients over short geographical distances, despite the less pronounced seasonality. The Lauraceae play an essential ecological role in Macaronesian natural forests. An example is Laurus azorica (Seub.) Franco, a relevant species given its high frequency and physiognomic dominance in Azorean laurel forests. This study aims to quantify climate–growth relationships in L. azorica using a dendroecological approach. We sampled four stands at São Miguel and two stands at Terceira islands, for a total of 206 trees. Following standard dendrochronological methods and rigorous sample selection procedures, we obtained relatively low rbar values and high temporal autocorrelation. Using a stepwise Random Forest analysis followed by Generalized Linear Models calculation, we found prominent effects of present and previous year temperature, but a low precipitation signal on growth rings, with some model variation between stands. Our results agreed with previous observations for broad-leaved species with diffuse porous wood, contributing to increase the baseline dendroecological knowledge about Azorean forests. Due to the high levels of within- and between-stand variation, and to refine the climatic signal analysis, complementary approaches should be explored in the future.
Ključne besede: Azores, dendroclimatology, generalized linear models, laurel forest, Macaronesia, random forest
Objavljeno v DiRROS: 18.01.2023; Ogledov: 477; Prenosov: 336
.pdf Celotno besedilo (11,11 MB)
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