Mean Annual Maximum Temperature Research Articles

Climate change, climatic disasters, and adaptation techniques: learnings from the lowlands of Nepal

Nepal is experiencing inevitable consequences of changing climate. Rural communities are badly suffering from these implications. Meanwhile, the rural communities are trying to acclimatize through small–scale adaptation efforts. This study aims to analyze changes in temperature and rainfall trends, identify major climatic disasters, and document current adaptation measures being adopted by rural communities. For this study, we randomly selected 220 households from a total of 4,282 Households, and seven key informants for the questionnaire survey within the study area. Meteorological data from the nearest station were used to analyze changes in temperature and rainfall trends. The study revealed that both mean annual maximum and minimum temperature increased by 0.063 °C/year and 0.072° C/year respectively, between 1991 and 2020. Similarly, mean annual rainfall increased by 12.329 mm/year. Floods, droughts, landslides, hailstorms, and forest fires were major climate disasters experienced by the locals. The adverse impact perceived were loss of crop yield, decrease in water availability, an increase of mosquitoes, and a decline in sightings of the birds and waterfowls in the area. Embankment construction along rivers, changing cropping patterns and cultivation time, forest protection, and maintaining home gardens were major adaptation measures being practiced by the locals. We believe the findings of this study will be helpful for policymakers to develop strategies and programs for communities that will promote resilience against climate– induced disasters at a local level in the lowlands of Nepal.

Intercomparison of Local Warming Trends of Shanghai and Hong Kong Based on 120-Year Temperature Observational Data

Using surface air temperature observations from 1901 to 2020, this study compared the warming trends of Shanghai and Hong Kong over a period of 120 years. The statistical results reveal the following: (1) The average temperatures of the two cities underwent fluctuating increases during the past 120 years, with linear warming rates of 0.23 °C/decade in Shanghai and 0.13 °C/decade in Hong Kong. (2) The fluctuation ranges of maximum temperature in the two cities were considerably higher than those of mean temperature. Moreover, in both cities, the annual mean maximum temperature decreased during a phase of more than a decade. The fluctuation ranges of minimum temperature were smaller, whereas the linear increases were higher than those for the mean temperature. (3) The diurnal temperature ranges (DTRs) of the two cities decreased; a certain phase of the decreases in DTR in the two cities was caused by decreases in the maximum temperature. (4) At a certain stage of urban development, owing to the shading effect of new high-rise buildings, the solar shortwave radiation reaching the Earth’s surface decreased, and anthropogenic heat generated by the energy consumption of buildings and urban human activities at that time was not sufficient to make up for the reduced shortwave radiation. This result may have led to the declines in the maximum temperature experienced by both cities. (5) Currently, the number of hot days and extremely hot days in the two cities has increased significantly compared with that a century ago, indicating that climate warming has an adverse impact on human settlements.

Cost Analysis of Seed Conservation of Commercial Pine Species Vulnerable to Climate Change in Mexico

Mexico is home to 40% of the pine species in the world. By the year 2050, 20% of the Mexican forests could be lost because of climate change and other human-related activities. In this paper, we determine the potential areas for seed collecting of four species of the genus Pinus and its ex situ economic value under different future Climate Change Scenarios (CCS). The species analyzed were Pinus oocarpa Schiede ex Schltdl, P. rudis Endl., P. culminícola Andresen et Beaman and P. leiophylla Schiede ex Schltdl. and Cham which together accounts for 19% of the timber production in Mexico. Potential areas of distribution of populations in habitats with Annual Mean Maximum Temperatures (AMMT) for seed collection were modelled through a Geographic Information System and climate database. The seed storage economic value was determined by using the Collection Cost Method. The AMMT of P. oocarpa, P. rudis, P. culminícola and P. leiophylla were 28 °C, 20 °C, 18.3 °C and 27.4 °C, respectively. The economic losses from shortages of these species due to CCS in 2050, were estimated of 88.5 million (USD) and 67.16 million (USD) with severe and conservative future CCS, respectively. The nominal investment rate would be 8.84% or more, for storing seeds of the four species and withstanding climate change. An ex situ seed bank is a medium and long-term investment; among its benefits are establishing a market price for the use and conservation of species in the face of possible adverse scenarios.

Impact of climate on vegetation in Pindari watershed of Western Himalayas, Kumaun, India, using spatiotemporal analysis: 1972-2018.

Vegetation dynamics is an important aspect for determining climate change trends. The present study delineates to examine spatiotemporal changes of vegetation cover in Pindari valley (Kumaun Himalaya) from the 1972 to 2018 timeline. The study includes the calculation of vegetation spectral indices of normalized vegetation index (NDVI), extraction of different vegetation classes, and statistical analysis of the Mann-Kendall (MK) test on historical metrological data (especially precipitation and temperature) of the study site. For the statistical analysis of metrological data, the power data access viewer datasets have been used. The central feature classes of the study are grassland, scrubland, and forest cover. The results revealed that the region's forest cover significantly decreased by 24.74 sq. km from 1972 to 2018, increased in grassland cover by 17.84 sq. km, respectively, and a slight increase in scrubland class by 3.13 sq. km for the study period. The calculated NDVI shows significant changes over the study location; it has been noticed that the maximum values of the NDVI decreased by 0.24, and the minimum values show growth of about 0.047. The analysis indicates that climatic parameters such as precipitation and temperature are the main limiting factors affecting vegetation growth. The annual mean maximum temperature showed a decreasing trend. The estimated results show an increase in annual rainfall and annual minimum temperature, while the decreasing trend is observed in the case of maximum annual temperature. Objectives of the study are (1) spatiotemporal analysis of the vegetation cover, (2) identification of the main causes of change in the vegetation cover, and (3) statistical trend analysis of long-term metrological data. The outcome of the presented research work would be beneficial for the proper management and monitoring of the forest ecosystem.

Spatio-temporal analysis of precipitation, temperature and drought from 1985 to 2020 in Penang, Malaysia

AbstractThis study aims to analyze the spatial and temporal variability of precipitation, temperature and drought in Penang from 1985 to 2020. The trend and magnitude changes in climate series were tested using the Mann–Kendall test and Sens’ slope methods. A significant increasing trend of annual precipitation was detected in the middle and northern parts of Penang mainland by 21.38 and 35.01 mm/decade. Annual mean maximum temperature increased significantly on Penang Island and the middle of Penang mainland at the rates of 0.25 and 0.34 °C/decade, while annual mean minimum temperature increased significantly for all stations from 0.36 to 0.52 °C/decade, showing increases of warm nights in the past few years. Extreme drought events (SPI-3 > −2) over Penang were mostly occurred during the strong El Niño years, e.g. 1988–1989, 1997–1998, 2010–2011 and 2014–2016. The number of drought events is higher during the 2001–2010 (4–11 events) period as compared to the 1991–2000 (6–9 events) and 2011–2020 (7–8 events). Interestingly, the 2011–2020 period tends to have a shorter drought duration, but more intense droughts have been observed, particularly on Penang Island and the northern and southern parts of Penang mainland.

Assessment of CMIP6 Model Performance for Air Temperature in the Arid Region of Northwest China and Subregions

The arid region of northwest China (ARNC) is one of the most sensitive areas to global warming. However, the performance of new Global Climate Models (GCMs) from phase 6 of the Coupled Model Intercomparison Project (CMIP6) in simulating climate in this region, especially in the subregions, is not clear yet. Based on the temperature dataset from historical runs of CMIP6, this paper analyzed and evaluated the simulation ability of 29 GCMs in reproducing the annual mean temperature (tas), annual mean maximum temperature (tasmax) and annual mean minimum temperature (tasmin) in the ARNC and subregions from 1961 to 2014. The results show that (1) the correlation coefficients (CCs) between simulation and observation time series for the mean of two model ensembles (MME for equal-weight multi-model ensemble and PME for preferred-model ensemble) are generally better than those of 29 individual GCMs, with CCs ranging from 0.38 to 0.87 (p < 0.01). (2) All the models can simulate the significant warming trend of the three temperature elements in the study area well. However, the warming magnitude simulated by most of the models (41%) is smaller than the observations except for tasmax, which is also shown in the MME. (3) The spatial pattern of the three temperature elements can be better reflected by most models. Model simulation ability for the ARNC is better compared to that of the four subregions, with a spatial CC greater than 0.7 (p < 0.01). Among the subregions, the simulation performance of the north of Xinjiang for spatial pattern is superior to that of the other regions. (4) The preferred models for each subregion are various and should be treated differently when used. Overall, the PME outperforms both the MME and the individual models; it can not only simulate the linear trend accurately but also reduce the deviation effectively.

Ecological niche modeling predicting the potential distribution of African horse sickness virus from 2020 to 2060

African horse sickness is a vector-borne, non-contagious and highly infectious disease of equines caused by African horse sickness viruses (AHSv) that mainly affect horses. The occurrence of the disease causes huge economic impacts because of its high fatality rate, trade ban and disease control costs. In the planning of vectors and vector-borne diseases like AHS, the application of Ecological niche models (ENM) used an enormous contribution in precisely delineating the suitable habitats of the vector. We developed an ENM to delineate the global suitability of AHSv based on retrospective outbreak data records from 2005 to 2019. The model was developed in an R software program using the Biomod2 package with an Ensemble modeling technique. Predictive environmental variables like mean diurnal range, mean precipitation of driest month(mm), precipitation seasonality (cv), mean annual maximum temperature (oc), mean annual minimum temperature (oc), mean precipitation of warmest quarter(mm), mean precipitation of coldest quarter (mm), mean annual precipitation (mm), solar radiation (kj /day), elevation/altitude (m), wind speed (m/s) were used to develop the model. From these variables, solar radiation, mean maximum temperature, average annual precipitation, altitude and precipitation seasonality contributed 36.83%, 17.1%, 14.34%, 7.61%, and 6.4%, respectively. The model depicted the sub-Sahara African continent as the most suitable area for the virus. Mainly Senegal, Burkina Faso, Niger, Nigeria, Ethiopia, Sudan, Somalia, South Africa, Zimbabwe, Madagascar and Malawi are African countries identified as highly suitable countries for the virus. Besides, OIE-listed disease-free countries like India, Australia, Brazil, Paraguay and Bolivia have been found suitable for the virus. This model can be used as an epidemiological tool in planning control and surveillance of diseases nationally or internationally.

Variations in temperature in a tropical town: a case study

Trend analysis of temperature on a local scale provides vital clues to the changes in amplitude with time and possibly the reasons for the changes. The present paper attempts to examine the temporal and seasonal trends in temperature of a developing township, Pattambi, Kerala in India from 1950 to 2018. We used Mann-Kendall rank statistics to examine the historical temperature data. The results show a general increase in annual temperature, especially the mean annual maximum temperature of the region across the year with a statistically significant increasing trend. The same trend could be seen in the case of southwest monsoon temperature. Another notable observation from the study is the statistically significant decrement in the winter temperature of the region. The regional changes in the temperature will have much impact on the economy and society in the area since the local livelihood is heavily dependent on agriculture.

Impact of Climate Change on the Hydrology of the Upper Awash River Basin, Ethiopia

This study investigated the impacts of climate change on the hydrology of the Upper Awash Basin, Ethiopia. A soil and water assessment tool (SWAT) model was calibrated and validated against observed streamflow using SWAT CUP. The Mann–Kendall trend test (MK) was used to assess climate trends. Meteorological drought (SPEI) and hydrological drought (SDI) were also investigated. Based on the ensemble mean of five global climate models (GCMs), projected increases in mean annual maximum temperature over the period 2015–2100 (compared with a 1983–2014 baseline) range from 1.16 to 1.73 °C, while increases in minimum temperature range between 0.79 and 2.53 °C. Increases in mean annual precipitation range from 1.8% at Addis Ababa to 45.5% over the Hombole area. High streamflow (Q5) declines at all stations except Ginchi. Low flows (Q90) also decline with Q90 equaling 0 m3 s−1 (i.e., 100% reduction) at some gauging stations (Akaki and Hombole) for individual GCMs. The SPEI confirmed a significant drought trend in the past, while the frequency and severity of drought will increase in the future. The basin experienced conditions that varied from modest dry periods to a very severe hydrological drought between 1986 and 2005. The projected SDI ranges from modestly dry to modestly wet conditions. Climate change in the basin would enhance seasonal variations in hydrological conditions. Both precipitation and streamflow will decline in the wet seasons and increase in the dry seasons. These changes are likely to have an impact on agricultural activities and other human demands for water resources throughout the basin and will require the implementation of appropriate mitigation measures.

Climate change and the suitability of local and non‐local species for ecosystem restoration

SummaryRestoring damaged, degraded and destroyed forest ecosystems to a target state often follows a local‐is‐best approach. However, rapidly changing climates may result in the local species no longer being the best now or into the future. This raises questions about whether there is a need to consider emerging ecosystems that bring together local and non‐local species that have not historically co‐occurred to ensure climate‐resilience of restored forest ecosystems; or whether non‐regional species may be needed to support ecosystem functionality in some areas. In this study, I present an experimental framework to assist decision‐making by evaluating the suitability of local and non‐local native species for ecosystem restoration under current and predicted climates. I applied this framework using the Tasmanian Midlands, Australia, as a case study, focusing of the diverse eucalypt flora of the island. Three key findings emerged. Firstly, the climate of the Midlands has rapidly changed across this biodiversity hotspot over the last century, and current mean annual maximum temperatures are already tracking worse case climate change scenarios. Secondly, using a combination of climate envelope modelling and habitat suitability modelling, I identified the degree to which the Midlands region provides suitable climate habitat for a range of local and non‐localEucalyptusspecies now and into the future. Thirdly, although the Midlands is predicted to support suitable climate habitat for 82% of the regionally local eucalypt species now and into the future, it is predicted that the local populations of these least vulnerable species may be at risk of climate maladaptation, particularly in the northern regions of the Midlands. Models suggests that mixing local seed with non‐local seed sources currently occupying habitat with a climate that is predicted for the Midlands will be required. The study provides a basis for managers to consider the suitability of regionally local species and identify potential areas where local seed may need to be supplemented with non‐local seed for ecosystem restoration in the face of climate change.

Climate change projections and trends simulated from the CMIP5 models for the Lake Tana sub-basin, the Upper Blue Nile (Abay) River Basin, Ethiopia

Climate change is mainly refers to the long-term fluctuations in the weather parameters of a large area with statistical significance. Earth's climate change is either due to natural variability or human activity, in combination. The Lake Tana basin has been studied to project future climate change using the Statistical DownSclaing Model (SDSM). The SDSM was used to downscale both temperature and precipitation from Canadian Earth System Model version 2 (CanESM2) Global Climate Models (GCMs) for Bahir Dar, Dangila, Debre Tabor and Gonder synoptic weather stations. The Manna Kendall non-parametric test was then used to examine both the baseline and projected precipitation and temperature trends. The historical or baseline data for downscaling purpose was obtained from National Meteorological Agency, Ethiopia (NMA) while large-scale predictor variables were obtained under Climate Model Intercomparison Project Phase 5 (CMIP5). Representative Concentration Pathways (RCPs) 2.6, 4.5 and 8.5 radiative forcing scenarios have been derived from the CanESM2 model. The performance of SDSM have been validated by using various statistical methods, such as RMSE, NSE, R and R2. The SDSM results are not reliablefor projecting the precipitation as compared to maximum and minimum temperatures. These findings indicated that maximum temperature tend to increase from 1.38 °C to 3.59 °C under RCP4.5 radiative forcing scenario by the year 2080s, while minimum temperature is projected to increase up to 5.92 °C under RCP8.5 by the end of the 21st century in the Lake Tana sub-basin. On the other hand, precipitation projection did not show consistent pattern over the basin. For instance, precipitation is projected to increase up to 255 mm in the northern and central parts of the basin, however, but relatively lower result (up to 200 mm) from the RCP8.5 radiative forcing scenarios by year 2080s. By considering Mann-Kendal trend test, the baseline and projected mean annual maximum and minimum temperatures show increasing trend, while baseline rainfall shows increasing trend, but projected rainfall shows a decreasing trend at Dangila and Debre Tabor stations. Whereas, an increasing trend noticed at Bahir Dar and Gonder stations. Therefore, basin or watershed scale climate change adaptation and mitigation strategies have be developed to minimize the negative impacts of climate change.

Recent trends and impacts of climate change in North-Eastern region of India-A review

The economy of North-Eastern (NE) region of India predominantly depends on farming, where only 12% of geographical area is available for cultivation out of which more than 85% is rain fed. Climate change has become a major concern in agriculture today, as farmers in many regions are struggling to cope with changing temperatures and rainfall pattern. Moreover, extreme weather situations like droughts, floods, heat and cold waves pose serious threat to food security, especially for small and marginal farmers. This review paper discusses the climate change in North-Eastern India based on the available climatic data from various published sources. Most of the analysis was performed on time series meteorological data recorded at different locations across the states of North-Eastern India namely, Assam, Arunachal Pradesh, Sikkim, Nagaland, Meghalaya, Manipur, Mizoram and Tripura. The increase in mean annual maximum temperature varied from 0.1°C per decade in Imphal (Manipur) to about 1.4°C per decade in Jharnapani (Nagaland). The changes were significant for all the states, except Sikkim. This region is one of the highest rainfall receiving regions of the world, but during February-March it faces water scarcity. The rainfall is projected to increase in 57 districts out of 78 districts, with some districts expected to experience almost 25% more rainfall than usual. The North-Eastern region of India has experienced notable changes in the pattern of major climatic variables such as rainfall and temperature. Average temperatures are projected to increase in almost all the districts of the region while annual rainfall is also reported to increase in almost 3/4th of the districts. The climate-induced natural disasters like drought, flood and hailstorms are the major threats of climate change and the incidence of these natural disasters are increasing in the recent years over the region.

Assessing the impact of climate change on crop yields in Gangetic Plains Region, India


 Against the increasing vulnerability of agriculture and farm livelihoods to climate change, the study attempted to analyse the trend in climate variables and their impact on major crop yields during the period from 1966-2011, across 4 agro-climatic zones forming Gangetic Plains Region. A rising trend was observed in annual and seasonal (kharif and rabi) mean maximum and minimum temperature across the zones. Rainfall on the other hand, showed a declining trend. Overall, climate change adversely impacted crop yield, but the magnitudes of such effects vary spatially. The results reveal that rice and wheat yield will decline in the entire Gangetic region. By 2050s, maize yield will be higher by 6 percent in Lower Gangetic Plains; pearl millet will increase by 15 percent and rapeseed & mustard by 3.8 percent in Trans-Gangetic Plains. Amongst the crops, sugarcane yield was the most impacted to climate change and is expected to reduce by 21 percent in Middle Gangetic Plains towards end of the century. Hence, there is a need to formulate sustainable adaptation measures and practices suitable to location-specific needs for enhancing climate resiliency and capacity of agricultural system to withstand climatic shocks.

Remote Impacts from El Niño and La Niña on Climate Variables and Major Crops Production in Coastal Bangladesh

El Niño and La Niña Southern Oscillation (ENSO) are major drivers that affect climatic variables in many countries. Therefore, ENSO mediated variation in climatic factors have significant consequences for crop production. We studied ENSO mediated variations in temperature and rainfall in the five coastal districts of Bangladesh during 1951–2017, and the impacts on major crops production were analyzed using growing degree day (GDD) index. Statistical analyses were performed on different climatic parameters in relation to ENSO events and locations. Results indicate that ENSO events had significant influence on monthly, seasonal and annual temperature and rainfall amounts (p < 0.05). Specifically, maximum temperature under ENSO phases were higher during Kharif-I and Kharif-II seasons than neutral years. In contrast, the minimum temperature was higher in neutral years than ENSO events during Rabi season. Averaged across stations, annual mean maximum temperature was 0.5 and 0.23 °C higher during El Niño and La Niña compared to neutral years. Rainfall was higher during neutral years compared to El Niño and La Niña. These changes in seasonal temperature variably changed crop GDD in different locations and thus, crop growth duration and crop yield. Therefore, this study provides a general understanding to ENSO mediated impacts on coastal agriculture in Bangladesh.

Impact of global climate change on temperature seasonal and annual of Arak city in the 2040s

Introduction: Global warming is the most important challenge facing man in the 21st century. Warmer weather will increase evapotranspiration, which will exacerbate droughts. One of the main causes of global warming is man himself. Humans have accelerated the Earth's climate change by producing large amounts of greenhouse gases. For this reason, information about changes in the earth's temperature in the next decades has always been considered. The results of the researchers show that climate change has obvious and significant effects on temperature and rainfall in different parts of Iran in the next decades. By predicting and estimating the extent of these effects, climate change impacts can be mitigated with adequate preparedness, low cost, and greater speed.Material and methods: In this study, the effect of climate change on the mean maximum and minimum annual and seasonal temperatures in Arak under the emission scenarios of RCP2.6, RCP4.5, RCP8.5 for the 2040s was investigated. To use the output of General Circulation Models at regional and local scales is that they are using downscaling models, are downscaled. In this study, Statistical Downscaling Model (SDSM) to downscale output of General Circulation Models CanESM2 were used. This model had an acceptable ability to simulate the average maximum and minimum seasonal and annual temperatures in the study area. Results and discussion: According to the obtained results, the mean maximum temperature in winter and spring will decrease under all three scenarios RCP2.6, RCP4.5, RCP8.5, which can indicate that the daily temperature will be cooler in these seasons. However, the mean maximum temperature will increase in summer and autumn, which may indicate that the daily temperature will be warmer in these seasons. The mean minimum temperature in winter and spring under all three scenarios RCP2.6, RCP4.5, RCP8.5 will decrease and increase in summer seasons. These results show that in the 2040s, the city of Arak has colder night temperatures in winter and spring and warmer temperatures in summer and spring. Due to the fact that warmer weather increases the demand for water and electricity, and because Arak is an industrial city with a dry climate, it can face serious challenges of water and electricity shortage in the future.Conclusion: According to the results obtained in this study, in the 2040s, Arak will have colder winters and springs, and warmer summers and autumns. The highest effect of climate change on the temperature of Arak is related to the average minimum temperature in autumn, which under the scenarios of RCP2.6, RCP4.5, RCP8.5, the average minimum temperature in autumn increased by 206.88, 196.37 and 192.27 percent, respectively. The mean annual maximum and minimum temperature under all three scenarios will increase in the 2040s. The highest increase in the mean annual maximum and minimum temperature is related to RCP8.5 and RCP2.6 scenarios, respectively, which they are equal to 4.14 and 4.38.

Evaluation of Past and Future Climate Trends under CMIP6 Scenarios for the UBNB (Abay), Ethiopia

Climate predictions using recent and high-resolution climate models are becoming important for effective decision-making and for designing appropriate climate change adaptation and mitigation strategies. Due to highly variable climate and data scarcity of the upper Blue Nile Basin, previous studies did not detect specific unified trends. This study discusses, the past and future climate projections under CMIP6-SSPs scenarios for the basin. For the models’ validation and selection, reanalysis data were used after comparing with area-averaged ground observational data. Quantile mapping systematic bias correction and Mann–Kendall trend test were applied to evaluate the trends of selected CMIP6 models during the 21st century. Results revealed that, ERA5 for temperature and GPCC for precipitation have best agreement with the basin observational data, MRI-ESM2-0 for temperature and BCC-CSM-2MR for precipitation were selected based on their highest performance. The MRI-ESM2-0 mean annual maximum temperature for the near (long)-term period shows an increase of 1.1 (1.5) °C, 1.3 (2.2) °C, 1.2 (2.8) °C, and 1.5 (3.8) °C under the four SSPs. On the other hand, the BCC-CSM-2MR precipitation projections show slightly (statistically insignificant) increasing trend for the near (long)-term periods by 5.9 (6.1)%, 12.8 (13.7)%, 9.5 (9.1)%, and 17.1(17.7)% under four SSPs scenarios.

Rainfall and Temperature Projections and their Impact Assessment Using CMIP5 Models under Different RCP Scenarios for The Eastern Coastal Region of India

Trend analysis of annual rainfall over the coastal districts of Odisha, India showed statistically nonsignificant increasing trend in all districts, except Ganjam. Whereas the maximum and minimum temperature showed significant increasing trend. Warming in these districts is mainly due to increasing minimum temperature during summer and rainy season, and maximum temperature during winter. Future climate projection results revealed, the annual mean rainfall is expected to change by 0.1–2.2%, –0.3–0.7% and 1.5–3.2% (RCP 4.5), and 3.6–7.9%, 3.7–6.6% and 8.5–14% (RCP 8.5) during the near (2011–39), mid (2040–69) and late (2070–99) centuries respectively. Anticipate climate change will have a marginal impact on total rainfall, and a major impact on its distribution. The annual mean minimum temperature is expected to increase by 0.60–0.73°C, 0.71–0.88°C, 1.20–1.42°C (RCP 4.5), and 1.77–2.14°C, 1.56–1.68°C, 3.06–3.73°C (RCP 8.5) during near, mid and late centuries respectively. Similarly, the annual mean maximum temperature is expected to increase by 0.61–0.66°C, 0.68–0.72°C and 1.35–1.55°C (RCP 4.5), and 1.79–1.97°C, 1.73–2.01°C and 3.08–3.44°C (RCP 8.5) during near, mid and late centuries respectively. Season-wise projection revealed that the change in rainfall and temperature is expected to be more in winter and summer under both the RCP scenarios. The projected future climate change will have both positive and negative impacts on agriculture. The negative impacts are expected to be more pronounced during kharif in comparison to rabi .

Substantial shifts in flowering phenology of Sternbergia vernalis in the Himalaya: Supplementing decadal field records with historical and experimental evidences

In an age of anthropocene, shifting plant phenology is one of the most striking biological indicators of global environmental change. Majority of the studies reporting shifts in plant phenology are available from the North America and Europe and largely scarce from the developing world, including the Himalaya; and studies integrating multiple methodological approaches to investigate the climate-driven phenological shifts are too rare. Here, we report the shifts in spring flowering phenology of model plant species, Sternbergia vernalis in response to the changing climate in Kashmir Himalaya, by integrating decadal field observational records with long-term herbarium and dated-photograph data, and supported with experimental evidences. Our results revealed a significant increasing trend of 0.038, 0.016 and 0.023 °C/year in the annual mean maximum temperature (Tmax), mean minimum temperature (Tmin) and diurnal temperature range (DTR) respectively; but an insignificant decreasing trend in annual precipitation of −1.24 mm/year over the last four decades (1980–2019) in this Himalayan region. The flowering phenology of S. vernalis has significantly advanced by 11.8 days/°C and 27.8 days/°C increase in Tmax and Tmin respectively, indicating that the climate warming has led to substantial shifts in flowering phenology of the model plant species. We also observed a strong association of seasonal Tmax (December–February) and DTR on the early onset of spring flowering, however precipitation had no significant effect on the timing of flowering. The greenhouse experiment results further supported a significant effect of temperature in triggering the phenological shifts, wherein the model plant grown under different temperature treatments flowered 9–20 days earlier compared to the control. Our study showcases the integrated use of multiple methodological approaches for unravelling the long-term phenological shifts in response to climate change, and contributes in filling the knowledge gaps in the phenological research from the developing world in general and the Himalaya in particular.

Does hot and dry equal more wildfire? Contrasting short‐ and long‐term climate effects on fire in the Sierra Nevada, CA

AbstractClimate and wildfire are closely linked. Climate regulates wildfire directly over short timescales through its effect on fuel aridity and indirectly over long timescales through vegetation productivity and the structure and abundance of fuels. Prediction of future wildfire regimes in a changing climate often uses empirical studies that presume current relationships between short‐term climate variables and wildfire activity will be stationary in the future. This is problematic because landscape‐scale wildfire dynamics exhibit non‐stationarity, with both positive and negative feedback loops that operate at different temporal and spatial scales. This requires that such feedbacks are accommodated in a model framework from which wildfire dynamics are emergent rather than pre‐specified. We use a new model, RHESSys‐WMFire, that integrates ecohydrology with fire spread and effects to simulate a 60‐yr time series of vegetation, fuel development, and wildfire in a 6572‐ha watershed in the Southern Sierra Nevada, USA, with a factorial design of increased temperature and severe drought. All climate scenarios had an initial pulse of elevated area burned associated with high temperature, low precipitation, and high fine fuel loading. There were positive correlations between annual area burned and mean annual maximum temperature and negative correlations with annual precipitation, consistent with understood direct effects of climate on wildfire in this system. Decreased vegetation productivity and increased fine fuel decomposition were predicted with increased temperature, resulting in long‐term reduced fine fuels and area burned relative to baseline. Repeated extreme drought increased area burned relative to baseline and over the long‐term had substantially reduced overstory biomass. Overstory biomass was resilient to repeat wildfire under baseline climate. The model system predicts that the short‐term direct effects of climate on wildfire can differ from long‐term indirect effects such that the simple maxim hotter/drier equals more wildfire can be both true and false, depending on scale.

Genomic, Habitat, and Leaf Shape Analyses Reveal a Possible Cryptic Species and Vulnerability to Climate Change in a Threatened Daisy.

Olearia pannosa is a plant species listed as vulnerable in Australia. Two subspecies are currently recognised (O. pannosa subsp. pannosa (silver daisy) and O. pannosa subsp. cardiophylla (velvet daisy)), which have overlapping ranges but distinct leaf shape. Remnant populations face threats from habitat fragmentation and climate change. We analysed range-wide genomic data and leaf shape variation to assess population diversity and divergence and to inform conservation management strategies. We detected three distinct genetic groupings and a likely cryptic species. Samples identified as O. pannosa subsp. cardiophylla from the Flinders Ranges in South Australia were genetically distinct from all other samples and likely form a separate, range-restricted species. Remaining samples formed two genetic clusters, which aligned with leaf shape differences but not fully with current subspecies classifications. Levels of genetic diversity and inbreeding differed between the three genetic groups, suggesting each requires a separate management strategy. Additionally, we tested for associations between genetic and environmental variation and carried out habitat suitability modelling for O. pannosa subsp. pannosa populations. We found mean annual maximum temperature explained a significant proportion of genomic variance. Habitat suitability modelling identified mean summer maximum temperature, precipitation seasonality and mean annual rainfall as constraints on the distribution of O. pannosa subsp. pannosa, highlighting increasing aridity as a threat for populations located near suitability thresholds. Our results suggest maximum temperature is an important agent of selection on O. pannosa subsp. pannosa and should be considered in conservation strategies. We recommend taxonomic revision of O. pannosa and provide conservation management recommendations.