The hormone receptor-like protein Gpr1p physically interacts with phosphatidylinositol-specific phospholipase C (Plc1p) and with the G␣ protein Gpa2p, as shown by two-hybrid assays and co-immune precipitation of epitope-tagged proteins. Plc1p binds to Gpr1p in either the presence or absence of Gpa2, whereas the Gpr1p/Gpa2p association depends on the presence of Plc1p. Genetic interactions between the null mutations plc1⌬, gpr1⌬, gpa2⌬, and ras2⌬ suggest that Plc1p acts together with Gpr1p and Gpa2p in a growth control pathway operating in parallel to the Ras2p function. Diploid cells lacking Gpr1p, Plc1p, or Gpa2p fail to form pseudohyphae upon nitrogen depletion, and the filamentation defect of gpr1⌬ and plc1⌬ strains is rescued by activating a mitogen-activated protein kinase pathway via STE11-4 or by activating a cAMP pathway via overexpressed Tpk2p. Plc1p is also required for efficient expression of the FG(TyA)::lacZ reporter gene under nitrogen depletion.In conclusion, we have identified two physically interacting proteins, Gpr1p and Plc1p, as novel components of a nitrogen signaling pathway controlling the developmental switch from yeast-like to pseudohyphal growth. Our data suggest that phospholipase C modulates the interaction of the putative nutrient sensor Gpr1p with the G␣ protein Gpa2p as a downstream effector of filamentation control.

Drought is a severe threat, especially in the arid regions of Pakistan, such as the Balochistan Province. The aim of this study is to analyze drought trends in Balochistan using Standard Precipitation Index (SPI) at the 3-month accumulation timescale. The monthly rainfall data of 10 stations were collected from the Pakistan Meteorological Department (PMD) for 37 years (1980–2017). Drought trends were analyzed at each station using the Mann-Kendall test. The SPI identified extreme drought events in 1996, 2001, 2002, 2004, 2009, and 2014. Barkhan was the station that most frequently experienced extreme to severe drought events, as defined using SPI. A statistically significant decreasing precipitation trend was found in four stations (Dalbandin, Jiwani, Quetta, and Zhob). The analysis of drought characteristics showed Barkhan faced the most prolonged drought, of 22 months from 1999 to 2001. The findings from the present study can give guidance on how strategies of water management should be adjusted based on the changing patterns of droughts in the Balochistan Province.

Featured Application:The following research has a potential to provide a scientific basis for the management of drought mitigation strategies. The trends in drought characteristics in each zone throughout the study period can help decision-makers with more information on resource planning. The identification of contiguous zones with similar drought characteristics across Pakistan is the first step towards developing an integrated and holistic policy to minimize the impacts of droughts. This study will help achieve this goal.Abstract: Pakistan is among the top ten countries adversely affected by climate change. More specifically, there is concern that climate change may cause longer and severer spells of droughts. To quantify the change in the characteristics of droughts in Pakistan over the years, we have evaluated spatio-temporal trends of droughts in Pakistan over the period 1902-2015 using Standardized Precipitation Evapotranspiration Index (SPEI). Additionally, the Spatial "K" luster Analysis using Tree Edge Removal (SKATER) method was employed to regionalize droughts into five contiguous zones. The run theory was then applied to each zone to identify drought events and characterize them in terms of duration, severity, intensity, and peak. Moreover, the Modified Mann-Kendall trend test was applied to identify statistically significant trends in SPEI and drought characteristics in each zone. It was found that the southern areas of Pakistan, encompassing Sindh and most of Baluchistan, have experienced a decrease in SPEI, indicating a drying trend. Central Pakistan has witnessed a wetting trend as demonstrated by an increase in SPEI over time, whereas no statistically significant trend was observed for the northern areas of Pakistan. On a zonal basis, the longest duration drought to occur in Pakistan lasted 22 months in zone 5 (Sindh) from 1968 to 1970. In addition, the droughts of 1920 and 2000 can be said to be the worst drought in the history of the region as it affected all the zones and lasted for more than 10-months in three zones.

In the wake of a rapidly changing climate, droughts have intensified, in both duration and severity, across the globe. The Germanwatch long-term Climate Risk Index ranks Pakistan among the top 10 countries most affected by the adverse effects of climate change. Within Pakistan, the province of Balochistan is among the most vulnerable regions due to recurring prolonged droughts, erratic precipitation patterns, and dependence on agriculture and livestock for survival. This study aims to explore how the characteristics of droughts have evolved in the region from 1902–2015 using 3-month and 12-month timescales of a popular drought index, the Standardized Precipitation Evapotranspiration Index (SPEI). The region was divided into six zones using Spatial “K”luster Analysis using Tree Edge Removal (SKATER) method, and run theory was applied to characterize droughts in terms of duration, severity, intensity, and peak. The results of the non-parametric Mann–Kendall trend test applied to SPEI indicate prevailing significant negative trends (dryer conditions) in all the zones. Balochistan experienced its most severe droughts in the 1960s and around 2000. The effects of climate change are also evident in the fact that all the long duration droughts occurred after 1960. Moreover, the number of droughts identified by 3-month SPEI showed a significant increase after 1960 for all six zones. The same trend was found in the 12-month SPEI but for only three zones.

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Investigating the trends in the major climatic variables over the Upper Indus Basin (UIB) region is difficult for many reasons, including highly complex terrain with heterogeneous spatial precipitation patterns and a scarcity of gauge stations. The Weather Research and Forecasting (WRF) model was applied to simulate the spatiotemporal variability of precipitation and temperature over the Indus Basin from 2000 through 2015 with boundary conditions derived from the Climate Forecast System Reanalysis (CFSR) data. The WRF model was configured with three nested domains (d01–d03) with horizontal resolutions increasing inward from 36 km to 12 km to 4 km horizontal resolution, respectively. These simulations were a continuous run with a spin-up year (i.e., 2000) to equilibrate the soil moisture, snow cover, and temperature at the beginning of the simulation. The simulations were then compared with TRMM and station data for the same time period using root mean squared error (RMSE), percentage bias (PBIAS), mean bias error (MBE), and the Pearson correlation coefficient. The results showed that the precipitation and temperature simulations were largely improved from d01 to d03. However, WRF tended to overestimate precipitation and underestimate temperature in all domains. This study presents high-resolution climatological datasets, which could be useful for the study of climate change and hydrological processes in this data-sparse region.

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