Having an extreme topography and heterogeneous climate, the Upper Indus Basin (UIB) is more likely to be affected by climate change and it is a crucial area for climatological studies. Based on the monthly minimum temperature (T_min), maximum temperature (T_max) and precipitation from nine meteorological stations, the spatiotemporal variability of temperature and precipitation were analyzed on monthly, seasonal, and annual scales. Results show a widespread significant increasing trend of 0.14 °C/decade for T_max, but a significant decreasing trend of −0.08 °C/decade for T_min annually, during 1955–2016 for the UIB. Seasonally, warming in T_max is stronger in winter and spring, while the cooling in T_min is greater in summer and autumn. Results of seasonal T_max indicate increasing trends in winter, spring and autumn at rates of 0.38, 0.35 and 0.05 °C/decade, respectively, while decreasing in summer with −0.14 °C/decade. Moreover, seasonal T_min results indicate increasing trends in winter and spring at rates of 0.09 and 0.08 °C/decade, respectively, while decreasing significantly in summer and autumn at rates of −0.21 and −0.22 °C/decade respectively for the whole the UIB. Precipitation exhibits an increasing trend of 2.74 mm/decade annually, while, increasing in winter, summer and autumn at rates of 1.18, 2.06 and 0.62 mm/decade respectively. The warming in T_max and an increase in precipitation have been more distinct since the mid-1990s, while the cooling in T_min is observed in the UIB since the mid-1980s. Warming in the middle and higher altitude (1500–2800 m and >2800 m) are much stronger, and the increase is more obvious in regions with elevation >2800 m. The wavelet analysis illustrated sporadic inter-annual covariance of seasonal T_max, T_min and precipitation with ENSO, NAO, IOD and PDO in the UIB. The periodicities were usually constant over short timescales and discontinuous over longer timescales. This study offers a better understanding of the local climate characteristics and provides a scientific basis for government policymakers.

The effects of climate change are unparalleled in magnitude, ranging from changing weather patterns that endanger food production to increasing sea levels that increase the likelihood of catastrophic flooding. Therefore, determining the extent of such variations on regional and local scales is imperative. We used monthly precipitation data from 25 meteorological stations in northern Pakistan (NP) to document the observed changes in seasonal and annual precipitation. The station density in the NP is small and unevenly distributed; therefore, ERA-5 reanalysis data were used to supplement the observed dataset to assess the spatial trends in NP. The non-parametric Mann–Kendall (MK), Sen’s Slope estimator (SSE), and Sequential Mann–Kendall (SQMK) tests were performed to assess the trends. In addition, the wavelet analysis technique was used to determine the association of precipitation with various oceanic indices from 1960 to 2016. Results indicate that maximum precipitation was shown in the annual and summer seasons. In NP, annual, winter, spring, and summer precipitation declined, while an increase in autumn was observed at a rate of 0.43 mm/decade between 1989 and 2016. The spatial trends for observed and ERA-5 reanalysis datasets were almost similar in winter, spring, and autumn; however, some disagreement was observed in both datasets in the summer and annual precipitation trends in NP during 1960–2016. Between 1989 and 2016, summer and annual precipitation increased significantly in Region III. However, seasonal and annual precipitation decreased in NP between 1960 and 2016. Moreover, there were no prominent trends in annual precipitation until the mid-1980s, but an apparent increase from 1985 onwards. Annual precipitation increased in all elevations except at the 500–1000 m zone. The ENSO (El Niño–Southern Oscillation) shared notable interannual coherences among all indices above 16–64 months. Inter-decadal coherence with the ENSO, AO (Arctic Oscillation), and PDO (Pacific Decadal Oscillation) in NP for 128 months and above. Generally, AO, AMO (Atlantic Multidecadal Oscillation), and NAO (North Atlantic Oscillation) exhibited less coherence with precipitation in NP. The regression of seasonal and annual precipitation revealed that winter and spring precipitation levels had higher linear regression with the AO and ENSO, respectively, while both the AO and ENSO also dominated at the annual scale. Similarly, the IOD and PDO indices had a higher influence in summer precipitation. The findings may help water resource managers and climate researchers develop a contingency plan for better water resource management policies in the face of changing climate change in Pakistan, particularly in NP.

In recent years, heavy metal pollution has caused immeasurable harm to the environment. As an emerging technology, phytoremediation technology has gained a place in the treatment of heavy metal pollution with its unique advantages. This study analyzes the toxic effects of mulberry (Morus alba) seeds, seedling growth and silkworm under heavy metal stress of lead (Pb) and cadmium (Cd), and explore the accumulation and migration of Pb and Cd in the soil-mulberry tree-silkworm system. The main results were as follows: (1) Seed germination and potted seedling experiments were conducted under heavy metal Pb and Cd stresses, and it was found that Pb and Cd had inhibitory effects on mulberry seed germination, growth and photosynthesis of mulberry seedlings, and as the concentration of heavy metals increased, the stronger the inhibitory effect. Moreover, Pb and Cd have a synergistic effect under compound stress. (2) The accumulation and transfer rules of Pb and Cd ions in mulberry were different. The content of Pb in mulberry was root > leaf > stem and the content of Cd was root > stem > leaf. The combined stress promoted the transfer of Pb and Cd from the underground part to the aerial portion of mulberry. (3) The silkworm feeds on mulberry leaves contaminated with heavy metals in this experiment and found that: with the increase of silkworm feeding, the heavy metal content in the silkworm body increased significantly, but the content remained in the silkworm body was less, most of it was excreted with silkworm excrement. Combined stress has no significant effect on the detoxification mechanism of silkworm. It is indispensable to think of the synergistic effect of heavy metals on plants germination when seeds are used for phytoremediation.

In recent decades, temperature variations have significantly affected the ecosystem and human livelihood in Pakistan. The wavelet analysis is employed to identify the associations between regional temperature change and global teleconnections, i.e. Atlantic Multidecadal Oscillation (AMO), Arctic Oscillation (AO), North Atlantic Oscillation (NAO), El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Tropical Northern Atlantic Index (TNA), Pacific/North American Index (PNA), North Pacific Pattern (NP), Western Pacific Index (WP), and Western Hemisphere Warm Pool (WHWP). This paper first uses monotonic modified Mann–Kendall and Sen’s slope estimator to compute the temperature changes in Pakistan and its homogenous climatic regions during 1960–2020. It is found that the temperature in Pakistan has increased significantly at 0.23 °C dec⁻¹ in the last 62 years, which is also higher than the global average increase. This increase is more evident in region IV and V in spring at 0.63 and 0.43 °C dec⁻¹ respectively, followed by summer and autumn. Temperature changes in Pakistan and its sub-regions are mainly associated with NP, WP and WHWP with higher mean significant coherences. Overall, temperature changes are significantly influenced by multiple interactions of global teleconnections, and these combinations indicate that the integrated influence of teleconnections can better explain the regional temperature changes. The teleconnections with broader significant influence over Pakistan are NP + WP + WHWP, followed by Pacific-based (ENSO, PDO, and PNA), and Atlantic-based (AMO, AO, and NAO) indices as revealed by the mean significant coherences of 0.82, 0.82 and 0.72 respectively. Annually, AMO, TNA and WHWP showed significant correlation with higher magnitudes of 0.44, 0.42 and 0.20 respectively, indicating the modulation effect of these teleconnections on temperature changes over Pakistan. The combined impacts from the various teleconnections represent a considerable advancement in the accuracy of significant temperature variations over the country. These findings have significant implications for policymakers in terms of better planning and policies in light of climate change as well as atmospheric circulation variability.