4.5 Article

Spatial characterization of forest ecosystem services and human-induced complexities in Himalayan biodiversity hotspot area

Journal

ENVIRONMENTAL MONITORING AND ASSESSMENT
Volume 195, Issue 11, Pages -

Publisher

SPRINGER
DOI: 10.1007/s10661-023-11902-6

Keywords

Aglar watershed; Analytical hierarchial process; Geographically weighted regression; Human activities; Ordinary least square regression; Spatial analysis

Ask authors/readers for more resources

The forest ecosystem of Indian Himalayan Region provides crucial ecosystem services for human sustenance, but the rapid expansion of human activities poses a threat to these services. This study used indicators and geospatial techniques to evaluate the relationship between the forest ecosystem services and human activities, finding an inverse relationship between the two.
The forest ecosystem of Indian Himalayan Region offers various ecosystem services (ESs) that are crucial for the sustenance of human beings. However, the rapid expansion of human activities (HA) poses a significant threat to the provision of the forest ecosystem services (FES). For simple and definitive assessments of FES and HA, the use of indicators has become an indispensable approach. In the present study, we performed: (i) indicator-based mapping of FES and HA, and (ii) evaluated the impact of HA on FES with the aid of geospatial techniques. Village-level analysis was conducted for FES and HA in the Aglar watershed of Uttarakhand, India for 2015. Four dominant forest types in the watershed-Quercus mixed, Pinus roxburghii, Cedrus deodara, and mixed forest were considered. For spatial characterization of FES, indicators such as forest carbon stock, net primary productivity, total water retention, and sediment yield were assessed, whereas human activity index (HAI) was evaluated using indicators of HAs, namely population density, road density, farmland, and habitation ratio. The integration of normalized values of FES indicators generated multiple ecosystem services indicator (MESI), and HAI was contructed using analytical hierarchical process based assignment of weights to HA indicators. Spatial analysis techniques such as ordinary least-square regression (OLS) and geographically weighted regression (GWR) models were used to derive the spatial relationship between them. The adjusted R-2 and AIC were utilized to evaluate the effectiveness of the model. The GWR model had a better fit with an adjusted R(2 )of 0.68 and a lower AIC of 42.940, compared to the OLS model with an adjusted R-2 of 0.21 and an AIC of 60.52. The statistics showed that GWR performed better than OLS and ably captured the heteroscedasticity of the phenomena. An inverse relation was observed between MESI and HAI. The findings of the study highlight the close link between the supply of FES and the impact of human-induced disturbances over the provision of FES, which has the potential to increase over time. The study provides a scientific basis for structuring policy dialogues to coordinate the long-term regional sustainability of FES provisioned from the Himalayan regions.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available