Grassland Growth in Response to Climate Variability in the Upper Indus Basin, Pakistan

Leveraging the sugarcane CRISPR/Cas9 technique for genetic improvement of non-cultivated grasses

Under changing climatic scenarios, grassland conservation and development have become imperative to impart functional sustainability to their ecosystem services. These goals could be effectively and efficiently achieved with targeted genetic improvement of native grass species. To the best of our literature search, very scant research findings are available pertaining to gene editing of non-cultivated grass species (switch grass, wild sugarcane, Prairie cordgrass, Bermuda grass, Chinese silver grass, etc.) prevalent in natural and semi-natural grasslands. Thus, to explore this novel research aspect, this study purposes that gene editing techniques employed for improvement of cultivated grasses especially sugarcane might be used for non-cultivated grasses as well. Our hypothesis behind suggesting sugarcane as a model crop for genetic improvement of non-cultivated grasses is the intricacy of gene editing owing to polyploidy and aneuploidy compared to other cultivated grasses (rice, wheat, barley, maize, etc.). Another reason is that genome editing protocols in sugarcane (x = 10-13) have been developed and optimized, taking into consideration the high level of genetic redundancy. Thus, as per our knowledge, this review is the first study that objectively evaluates the concept and functioning of the CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9 technique in sugarcane regarding high versatility, target specificity, efficiency, design simplicity, and multiplexing capacity in order to explore novel research perspectives for gene editing of non-cultivated grasses against biotic and abiotic stresses. Additionally, pronounced challenges confronting sugarcane gene editing have resulted in the development of different variants (Cas9, Cas12a, Cas12b, and SpRY) of the CRISPR tool, whose technicalities have also been critically assessed. Moreover, different limitations of this technique that could emerge during gene editing of non-cultivated grass species have also been highlighted.

Bias-corrected climate change projections over the Upper Indus Basin using a multi-model ensemble

The study projects climate over the Upper Indus Basin (UIB), covering geographic areas in India, Pakistan, Afghanistan, and China, under the two Representative Concentration Pathways (RCPs), viz., RCP4.5 and RCP8.5 by the late twenty-first century using the best-fit climate model validated against the climate observations from eight meteorological stations. GFDL CM3 performed better than the other five evaluated climate models in simulating the climate of the UIB. The model bias was significantly reduced by the Aerts and Droogers statistical downscaling method, and the projections overall revealed a significant increase in temperature and a slight increase in precipitation across the UIB comprising of Jhelum, Chenab, and Indus sub-basins. According to RCP4.5 and RCP8.5, the temperature and precipitation in the Jhelum are projected to increase by 3 °C and 5.2 °C and 0.8% and 3.4% respectively by the late twenty-first century. The temperature and precipitation in the Chenab are projected to increase by 3.5 °C and 4.8 °C and  8% and 8.2% respectively by the late twenty-first century under the two scenarios. The temperature and precipitation in the Indus are projected to increase by 4.8 °C and 6.5 °C and 2.6% and 8.7% respectively by the late twenty-first century under RCP4.5 and RCP8.5 scenarios. The late twenty-first century projected climate would have significant impacts on various ecosystem services and products, irrigation and socio-hydrological regimes, and various dependent livelihoods. It is therefore hoped that the high-resolution climate projections would be useful for impact assessment studies to inform policymaking for climate action in the UIB.

Large-Scale Analysis of the Spatiotemporal Changes of Net Ecosystem Production in Hindu Kush Himalayan Region

The Hindu Kush Himalayan (HKH) region is one of the most ecologically vulnerable regions in the world. Several studies have been conducted on the dynamic changes of grassland in the HKH region, but few have considered grassland net ecosystem productivity (NEP). In this study, we quantitatively analyzed the temporal and spatial changes of NEP magnitude and the influence of climate factors on the HKH region from 2001 to 2018. The NEP magnitude was obtained by calculating the difference between the net primary production (NPP) estimated by the Carnegie–Ames Stanford Approach (CASA) model and the heterotrophic respiration (Rh) estimated by the geostatistical model. The results showed that the grassland ecosystem in the HKH region exhibited weak net carbon uptake with NEP values of 42.03 gC∙m−2∙yr−1, and the total net carbon sequestration was 0.077 Pg C. The distribution of NEP gradually increased from west to east, and in the Qinghai–Tibet Plateau, it gradually increased from northwest to southeast. The grassland carbon sources and sinks differed at different altitudes. The grassland was a carbon sink at 3000–5000 m, while grasslands below 3000 m and above 5000 m were carbon sources. Grassland NEP exhibited the strongest correlation with precipitation, and it had a lagging effect on precipitation. The correlation between NEP and the precipitation of the previous year was stronger than that of the current year. NEP was negatively correlated with temperature but not with solar radiation. The study of the temporal and spatial dynamics of NEP in the HKH region can provide a theoretical basis to help herders balance grazing and forage.

Mangrove Phenology and Environmental Drivers Derived from Remote Sensing in Southern Thailand

Vegetation phenology is the annual cycle timing of vegetation growth. Mangrove phenology is a vital component to assess mangrove viability and includes start of season (SOS), end of season (EOS), peak of season (POS), and length of season (LOS). Potential environmental drivers include air temperature (Ta), surface temperature (Ts), sea surface temperature (SST), rainfall, sea surface salinity (SSS), and radiation flux (Ra). The Enhanced vegetation index (EVI) was calculated from Moderate Resolution Imaging Spectroradiometer (MODIS, MOD13Q1) data over five study sites between 2003 and 2012. Four of the mangrove study sites were located on the Malay Peninsula on the Andaman Sea and one site located on the Gulf of Thailand. The goals of this study were to characterize phenology patterns across equatorial Thailand Indo-Malay mangrove forests, identify climatic and aquatic drivers of mangrove seasonality, and compare mangrove phenologies with surrounding upland tropical forests. Our results show the seasonality of mangrove growth was distinctly different from the surrounding land-based tropical forests. The mangrove growth season was approximately 8–9 months duration, starting in April to June, peaking in August to October and ending in January to February of the following year. The 10-year trend analysis revealed significant delaying trends in SOS, POS, and EOS for the Andaman Sea sites but only for EOS at the Gulf of Thailand site. The cumulative rainfall is likely to be the main factor driving later mangrove phenologies.