Impacts of Stressors on Riparian Health Indicators in the Upper and Lower Indus River Basins in Pakistan

Abstract

Riparian zones along rivers and streams provide ecosystem services that may change over time as disturbances increase and deteriorate these buffer zones globally. The effect of stressors on ecosystem services along the rivers in underdeveloped countries is unclear, which impacts the environment directly in the form of riparian health indicators (RHIs). This study fills this gap and measures the impact of stressors on RHIs (parameters of habitat, plant cover, regeneration, exotics, and erosion) in the Indus River basin (IRB) in Pakistan. Data on 11 stressors and 27 RHIs were collected using a field-based approach in 269 transects in the upper and lower Indus basins (UIB and LIB) in 2020 and analyzed using multivariate statistical methods. The Kruskal–Wallis tests (p < 0.05) indicated that RHIs varied significantly under the influence of stressors in the UIB and LIB. However, their highest mean values were found in the UIB. Principal component analysis revealed the key RHIs and stressors, which explained 62.50% and 77.10% of the variance, respectively. The Pearson correlation showed that stressors had greater impacts on RHIs in LIB (with r ranging from −0.42 to 0.56). Our results also showed that stressors affected RHI indices with r ranging from −0.39 to 0.50 (on habitat), −0.36 to 0.46 (on plant cover), −0.34 to 0.35 (on regeneration), −0.34 to 0.56 (on erosion), and −0.42 to 0.23 (on exotics). Furthermore, it was confirmed by the agglomerative hierarchical cluster that indices and sub-indices of RHIs and stressors differ across the UIB and LIB. These findings may serve as guidance for managers of large rivers and ecosystem service providers to minimize the environmental impact of stressors in terms of RHIs.

Effects of riparian buffer and stream channel widths on ecological indicators in the upper and lower Indus River basins in Pakistan

“…It was found that the RHIs in LIB showed a moderate correlation with the stress indices in the IRB; however, they had a significant and strong correlation with the RHIs in LIB. There is an agreement between our findings and those of previous studies (Charles et al, 2018;Tariq et al, 2021;Hira et al, 2022).…”

“…It was determined that non-parametric Kruskal-Wallis tests showed significant differences between the RHIs and stressors within the UIB and LIB when the riparian buffer and stream channel widths were changing within the IRB (p < 0.05). This non-parametric test allows comparisons between RHIs and stressor indices or sub-indices on a broad scale (Hira et al, 2022). Principal component analysis (factor analysis) was also used to identify the essential components of both UIBs and LIBs related to RHIs and stressors.…”

“…Pakistan has five influential river basins (Indus, Chenab, Ravi, Jhelum, and Sutlej), but the IRB is one of the most famous (Ahmed et al, 2018;Hira et al, 2022). It lies between 29 °30′N and 37 °10′N, and 70 °15′E and 77 °0′E.…”

“…The lack of predetermined width limits has prevented ecologists from discovering ecological relationships in streams. Riparian buffers play an influential role in conserving degraded ecosystems (Hira et al, 2022). These buffer zones are also conducive to the spread of invasive species (Hu et al, 2022).…”

Plant community assembly is jointly shaped by environmental and dispersal filtering along elevation gradients in a semiarid area, China

“…Furthermore, knowledge of beta diversity patterns may effectively shape preservation policies (Swenson, 2011;Bergamin et al, 2017). For example, if species turnover is the dominant pattern, more protected areas are needed for biodiversity conservation (Arif et al, 2022b;Hira et al, 2022). However, when nestedness is the prevailing pattern, there is a need to establish a sufficiently large protected area with high species richness (Bergamin et al, 2017).…”