Temperate Subantarctic Forests: A Huge Natural Laboratory

Marchelli, Paula; Pastorino, Mario J.; Gallo, Leonardo

doi:10.1007/978-3-030-56462-9_2

Cited by 3 publications

(1 citation statement)

References 84 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Notably, a genetic resources assessment includes the relative abundance, richness, size variation, and spatial variation, which might facilitate reliable, precise, and verifiable evidence on the expected size class of trees within its ecological niche [45,46], commonly described by frequency distribution and expressed on a unit area basis [47]. According to Pastorino et al (2021) [48], "Genetic resources from any biological organism-complete genomes, genes, or even portions of genes that have actual or potential relevance to humans". Thus, in tree species, it becomes necessary to categorize and characterize the morphological traits in which phenotypic plasticity may play a significant role to predict global climate change and the ecological consequences.…”

Section: Introductionmentioning

confidence: 99%

Phenotypic, Geological, and Climatic Spatio-Temporal Analyses of an Exotic Grevillea robusta in the Northwestern Himalayas

et al. 2023

View full text Add to dashboard Cite

The last five decades (since 1980) have witnessed the introduction of exotic trees as a popular practice in India to fulfill the demand of forest-based products for utilization in afforestation programmes. This study examines the distribution and habitat suitability of exotic Grevillea robusta trees in the northwestern Himalayas (state: Uttarakhand), focusing on the interaction between G. robusta and abiotic factors, such as climate, soil, and habitat suitability. This multipurpose agroforestry species is mainly grown by farmers as a boundary tree, windbreak, or shelterbelt and among intercrops on small farms in agroforestry systems worldwide. The results indicate that phenotypic plasticity is determined by tree height and diameter, indicating a higher frequency of young and adult trees. The study also highlights spatio-temporal modeling coupled with geological analysis to address the current distribution pattern and future habitat suitability range through MaxEnt modeling. The AUC ranged from 0.793 ± 3.6 (RCP 6.0_70) to 0.836 ± 0.008 (current) with statistical measures, such as K (0.216), NMI (0.240), and TSS (0.686), revealing the high accuracy of the model output. The variables, which include the minimum temperature of the coldest month (Bio 6), the slope (Slo), the mean temperature of the driest quarter (Bio 9), and the precipitation of the driest quarter (Bio 17), contribute significantly to the prediction of the distribution of the species in the Himalayan state. The model predicts a significant habitat suitability range for G. robusta based on bio-climatic variables, covering an area of approximately ~1641 km2 with maximal occurrence in Pauri (~321 km2) and Almora (~317 km2). Notably, the future prediction scenario corroborates with the regions of Tons (Upper Yamuna, Uttarkashi), Kalsi (Mussoorie, Dehradun), the Kedarnath Wildlife Sanctuary, and the Badrinath Forest Division for the potentially suitable areas. The climate was found to have a strong influence on the species’ distribution, as evidenced by its correlation with the Köppen–Geiger climate classification (KGCC) map. While the species demonstrated adaptability, its occurrence showed a high correlation with bedrocks containing an elevated iron content. Furthermore, the study also provides the first trees outside forests (TOF) map of G. robusta in the region, as well as insight into its future habitat suitability.

show abstract

Section: Introductionmentioning

confidence: 99%