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

Author:

Dabral Aman1ORCID,Shankhwar Rajeev1,Martins-Ferreira Marco Antonio Caçador2ORCID,Pandey Shailesh3,Kant Rama1ORCID,Meena Rajendra K.1ORCID,Chandra Girish4ORCID,Ginwal Harish S.1,Thakur Pawan Kumar5ORCID,Bhandari Maneesh S.1ORCID,Sahu Netrananda6ORCID,Nayak Sridhara7ORCID

Affiliation:

1. Division of Genetics & Tree Improvement, ICFRE-Forest Research Institute, Dehradun 248195, India

2. Faculdade de Ciências e Tecnologia, Universidade Federal de Goiás, Rua Mucuri, Aparecida de Goiania 74968755, Brazil

3. Forest Pathology Discipline, Division of Forest Protection, ICFRE-Forest Research Institute, Dehradun 248006, India

4. Department of Statistics, University of Allahabad, Prayagraj 211002, India

5. Forest Ecology and Climate Change Division, ICFRE-Himalayan Forest Research Institute, Shimla 171013, India

6. Department of Geography, Delhi School of Economics, University of Delhi, Delhi 110007, India

7. Research and Development Center, Japan Meteorological Corporation, Osaka 5300011, Japan

Abstract

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.

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction

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