Impact Of Future Climate Research Articles

Climate change is predicted to cause population collapse in a cooperative breeder.

It has been suggested that animals may have evolved cooperative breeding strategies in response to extreme climatic conditions. Climate change, however, may push species beyond their ability to cope with extreme climates, and reduce the group sizes in cooperatively breeding species to a point where populations are no longer viable. Predicting the impact of future climates on these species is challenging as modelling the impact of climate change on their population dynamics requires information on both group- and individual-level responses to climatic conditions. Using a single-sex individual-based model incorporating demographic responses to ambient temperature in an endangered species, the African wild dog Lycaon pictus, we show that there is a threshold temperature above which populations of the species are predicted to collapse. For simulated populations with carrying capacities equivalent to the median size of real-world populations (nine packs), extinction risk increases once temperatures exceed those predicted in the best-case climate warming scenario (Representative Concentration Pathway [RCP] 2.6). The threshold is higher (between RCP 4.5 and RCP 6.0) for larger simulated populations (30 packs), but 84% of real-world populations number <30 packs. Simulated populations collapsed because, at high ambient temperatures, juvenile survival was so low that packs were no longer recruiting enough individuals to persist, leading them to die out. This work highlights the importance of social dynamics in determining impacts of climatic variables on social species, and the critical role that recruitment can play in driving population-level impacts of climate change. Population models parameterised on long-term data are essential for predicting future population viability under climate change.

Comprehensive approaches for assessing extinction risk of endangered tropical pitcher plant Nepenthes talangensis.

It has been 23 years since the conservation status of highland tropical pitcher plant Nepenthes talangensis was assessed in 2000. A number of existing threats (anthropogenic and environmental) may be increasing the risk of extinction for the species. A better understanding of the ecology and conservation needs of the species is required to manage the wild populations. Specifically, better information related to population distributions, ecological requirements, priority conservation areas, the impact of future climate on suitable habitat, and current population structure is needed to properly assess extinction risks. A better understanding of the requirements of the species in its natural habitat would benefit for successfully securing the species at Botanic Gardens. We have identified 14 new occurrence records of N. talangensis in Mount Talang. Study on the ecological requirement using Random Forest (RF) and Artificial Neural Network (ANN) suggested that elevation, canopy cover, soil pH, and slope are four important variables. The population of N. talangensis was dominated by juvenile and mature (sterile) individuals, we found only a few mature males (7 individuals) and females (4 individuals) in the sampled areas. Our modelling of current conditions predicted that there were 1,076 ha of suitable habitat to very highly suitable habitat in Mount Talang, which is 14.7% of the total area. Those predicted habitats ranged in elevation from 1,740-2,558 m. Suitable habitat in 2100 was predicted to decrease in extent and be at higher elevation in the less extreme climate change scenario (SSP 1-2.6) and extreme climate change scenario (SSP 5-8.5). We projected larger habitat loss in the SSP 5-8.5 compared to the SSP 1-2.6 climate change scenario.. We proposed the category CR B1ab(iii,v), C2a(ii) as the new conservation status of N. talangensis. The status is a higher category of threat compared to the current status of the species (EN C2b, ver 2.3). Nepenthes talangensis seedlings and cuttings established in a Botanic Garden have relatively high survival rate at about 83.4%. Sixty percent of the seeds germinated in growth media successfully grew to become seedlings.

Impacts of future climate on the distribution of 4 bumblebee species in the Qinghai-Tibet Plateau.

Climate warming threatens dozens of bumblebee species across the world, including alpine areas. In plateaus with vast and continuous high-altitude areas, bumblebees' response to climate warming may be relatively optimistic. To study the species' responses to future climate in the Qinghai-Tibet Plateau, we quantified the suitable areas for 4 local bumblebee indicator species under current and future climate scenarios (Shared Socio-economic Pathway 126, 245, 370, and 585 in 2,100) using MaxEnt models. Suitable areas of indicator species were stacked to obtain the species richness layer. According to the acreage and connectivity of suitable areas and the acreage of the high richness area, a warmed climate will be more suitable for bumblebees' distribution compared to the current climate. The SSP 126 and SSP 245 scenario will be the 2 most suitable. Meanwhile, with climate warming, suitable areas and the high richness areas will move to high altitudes and their altitude range will decrease. The greater suitability in warmed climates may be caused by the topography of plateaus, which provides an opportunity for bumblebees to migrate to cooler areas. However, mitigation of warming is still necessary because an excessively warm climate will decrease bumblebees' habitat suitability. In plateaus, species in lower altitudes will migrate to higher altitudes, conservation in high altitudes should pay attention to not only original species, but also immigrated species. In lower altitudes, many species will migrate to higher altitudes, then local bumblebee diversity will decrease. Local conservation should be focused on these lower altitude areas.

The impact of future climate on orange-fleshed sweet potato production in arid areas of Northern Ethiopia. A case study in Afar region

Sweet potato is in its introductory phase as a food-based approach to alleviate malnutrition in the Afar region, where, due to climate change, agricultural drought impedes crop production. This study assesses the impact of climate change on orange-fleshed sweet potato (OFSP) fresh storage root yield production over the Afar region using the Aqua Crop model. This model was fed with daily rainfall and minimum and maximum temperature datasets, for the baseline climate (1980–2009) as well as future (2010–2099) climate projections under two representative concentration pathways: RCP 4.5 and RCP 8.5. These datasets were statistically downscaled from twenty (20) general circulation models that are used in the Coupled Model Intercomparison Project Phase 5 (CMIP5). The impact of climate change on sweet potatoes was assessed by comparing the change in average sweet potato yields in the baseline climate condition against the average of simulated sweet potato yields in the Near-term (NT) (2010–2039), Mid-term (MT) (2040–2069), and End-term (ET) (2070–2099) under RCP 8.5 and RCP 4.5. Simulation shows increased future storage root yield production for NT (3.23%), MT (3.90%), and ET (7.25%) under RCP 4.5 and MT (5.88%) and NT (6.71%) from the observed yield data (32.0 t/ha) except for Near-term (−9.59%) under RCP 8.5. Similarly, projected climate shows increase in temperature Tmax (0.93–4.10 °C), Tmin (0.88–4.54 °C) and precipitation (28.9–37.8%) under both RCPs which will favor sweet potato yield production increase in near-term, mid-term reaching climax in end-term. Simulation with planting dates shows that normal planting date (July 01), gives better yields than early (April 22) or late planting (01 August). This finding may perhaps be used as preliminary data in adoption and upscaling of orange-fleshed sweet potato in Afar region.

Impact of Future Climate and Land Use Changes on Runoff in a Typical Karst Basin, Southwest China

Climate change and land use change are the two main factors affecting the regional water cycle and water resources management. However, runoff studies in the karst basin based on future scenario projections are still lacking. To fill this gap, this study proposes a framework consisting of a future land use simulation model (FLUS), an automated statistical downscaling model (ASD), a soil and water assessment tool (SWAT) and a multi-point calibration strategy. This frameword was used to investigate runoff changes under future climate and land use changes in karst watersheds. The Chengbi River basin, a typical karst region in southwest China, was selected as the study area. The ASD method was developed for climate change projections based on the CanESM5 climate model. Future land use scenarios were projected using the FLUS model and historical land use data. Finally, the SWAT model was calibrated using a multi-site calibration strategy and was used to predict future runoff from 2025–2100. The results show that: (1) the developed SWAT model obtained a Nash efficiency coefficient of 0.83, which can adequately capture the spatial heterogeneity characteristics of karst hydro-climate; (2) land use changes significantly in all three future scenarios, with the main phenomena being the interconversion of farmland and grassland in SSPs1-2.6, the interconversion of grassland, farmland and artificial surfaces in SSPs2-4.5 and the interconversion of woodland, grassland and artificial surfaces in SSPs5-8.5; (3) the average annual temperature will show an upward trend in the future, and the average annual precipitation will increase by 11.53–14.43% and (4) the future annual runoff will show a significant upward trend, with monthly runoff mainly concentrated in July–September. The variability and uncertainty of future runoff during the main-flood period may increase compared to the historical situation. The findings will benefit future water resources management and water security in the karst basin.

Ultra‐long‐distance transport of aeolian sand: The provenance of an intermontane desert, south‐east China

AbstractIntermontane deserts are an important type of arid‐climate sedimentary system. Although rare at present, the sedimentary records of intermontane deserts reveal their widespread development in past greenhouse periods, and they might develop in the near future in response to ongoing global warming. Determination of the provenance of sand supplied for the construction of intermontane deserts is important to gain improved understanding of the potential impact of future climate on environmental evolution in arid and semi‐arid regions. During the Cretaceous, a typical intermontane desert developed in the Xinjiang Basin, south‐east China. In this study, the origin, spatial variability, and transport pathways of both aeolian and alluvial–fluvial sediments in the Xinjiang intermontane desert are investigated by analyses of bulk‐rock petrography and detrital‐zircon U–Pb geochronology. These results demonstrate that the sand in the Xinjiang intermontane desert succession was mainly of extraneous origin and wind‐derived. The nearby South China Block and South China Magmatic Belt were primary sources, and the 1000 km distant western margin of Yangtze Block was an important secondary source. During the Late Cretaceous, the westerlies were stronger in the northern than in the southern hemisphere with doubled wind speeds. In such a climatic context, the results herein suggest that the ultra‐long‐distance aeolian sediment transport was likely further enabled by two factors: (i) the strengthening of intermittent westerly winds during short‐lived glacial episodes; and (ii) the presence of a low‐relief corridor that served as a transport pathway from source to sink.

Opening Pandora's box: reducing global circulation model uncertainty in Australian simulations of the carbon cycle

Abstract. Climate projections from global circulation models (GCMs), part of the Coupled Model Intercomparison Project 6 (CMIP6), are often employed to study the impact of future climate on ecosystems. However, especially at regional scales, climate projections display large biases in key forcing variables such as temperature and precipitation. These biases have been identified as a major source of uncertainty in carbon cycle projections, hampering predictive capacity. In this study, we open the proverbial Pandora's box and peer under the lid of strategies to tackle climate model ensemble uncertainty. We employ a dynamic global vegetation model (LPJ-GUESS) and force it with raw output from CMIP6 to assess the uncertainty associated with the choice of climate forcing. We then test different methods to either bias-correct or calculate ensemble averages over the original forcing data to reduce the climate-driven uncertainty in the regional projection of the Australian carbon cycle. We find that all bias correction methods reduce the bias of continental averages of steady-state carbon variables. Bias correction can improve model carbon outputs, but carbon pools are insensitive to the type of bias correction method applied for both individual GCMs and the arithmetic ensemble average across all corrected models. None of the bias correction methods consistently improve the change in simulated carbon over time compared to the target dataset, highlighting the need to account for temporal properties in correction or ensemble-averaging methods. Multivariate bias correction methods tend to reduce the uncertainty more than univariate approaches, although the overall magnitude is similar. Even after correcting the bias in the meteorological forcing dataset, the simulated vegetation distribution presents different patterns when different GCMs are used to drive LPJ-GUESS. Additionally, we found that both the weighted ensemble-averaging and random forest approach reduce the bias in total ecosystem carbon to almost zero, clearly outperforming the arithmetic ensemble-averaging method. The random forest approach also produces the results closest to the target dataset for the change in the total carbon pool, seasonal carbon fluxes, emphasizing that machine learning approaches are promising tools for future studies. This highlights that, where possible, an arithmetic ensemble average should be avoided. However, potential target datasets that would facilitate the application of machine learning approaches, i.e., that cover both the spatial and temporal domain required to derive a robust informed ensemble average, are sparse for ecosystem variables.

Streams in the Mediterranean Region are not for mussels: Predicting extinctions and range contractions under future climate change

Climate change is becoming the leading driver of biodiversity loss. The Mediterranean region, particularly southwestern Europe, is already confronting the consequences of ongoing global warming. Unprecedented biodiversity declines have been recorded, particularly within freshwater ecosystems. Freshwater mussels contribute to essential ecosystem services but are among the most threatened faunal groups on Earth. Their poor conservation status is related to the dependence on fish hosts to complete the life cycle, which also makes them particularly vulnerable to climate change. Species Distribution Models (SDMs) are commonly used to predict species distributions, but often disregard the potential effect of biotic interactions. This study investigated the potential impact of future climate on the distribution of freshwater mussel species while considering their obligatory interaction with fish hosts. Specifically, ensemble models were used to forecast the current and future distribution of six mussel species in the Iberian Peninsula, including environmental conditions and the distribution of fish hosts as predictors. We found that climate change is expected to severely impact the future distribution of Iberian mussels. Species with narrow ranges, namely Margaritifera margaritifera and Unio tumidiformis, were predicted to have their suitable habitats nearly lost and could potentially be facing regional and global extinctions, respectively. Anodonta anatina, Potomida littoralis, and particularly Unio delphinus and Unio mancus, are expected to suffer distributional losses but may gain new suitable habitats. A shift in their distribution to new suitable areas is only possible if fish hosts are able to disperse while carrying larvae. We also found that including the distribution of fish hosts in the mussels' models avoided the underprediction of habitat loss under climate change. This study warns of the imminent loss of mussel species and populations and the urgent need of management actions to reverse current trends and mitigate irreversible damage to species and ecosystems in Mediterranean regions.

Local and remote climate impacts of future African aerosol emissions

Abstract. The potential future trend in African aerosol emissions is uncertain, with a large range found in future scenarios used to drive climate projections. The future climate impact of these emissions is therefore uncertain. Using the Shared Socioeconomic Pathway (SSP) scenarios, transient future experiments were performed with the UK Earth System Model (UKESM1) to investigate the effect of African emissions following the high emission SSP370 scenario as the rest of the world follows the more sustainable SSP119, relative to a global SSP119 control. This isolates the effect of Africa following a relatively more polluted future emissions pathway. Compared to SSP119, SSP370 projects higher non-biomass-burning (non-BB) aerosol emissions, but lower biomass burning emissions, over Africa. Increased shortwave (SW) absorption by black carbon aerosol leads to a global warming, but the reduction in the local incident surface radiation close to the emissions is larger, causing a local cooling effect. The local cooling persists even when including the higher African CO2 emissions under SSP370 than SSP119. The global warming is significantly higher by 0.07 K when including the non-BB aerosol increases and higher still (0.22 K) when including all aerosols and CO2. Precipitation also exhibits complex changes. Northward shifts in the Inter-tropical Convergence Zone (ITCZ) occur under relatively warm Northern Hemisphere land, and local rainfall is enhanced due to mid-tropospheric instability from black carbon absorption. These results highlight the importance of future African aerosol emissions for regional and global climate and the spatial complexity of this climate influence.

Water quality modeling of a eutrophic drinking water source: Impact of future climate on Cyanobacterial blooms

Cyanobacterial blooms are becoming more frequent in freshwater sources, causing concern throughout the world. Cyanobacterial blooms affect human health and the entire environment. Numerical modeling is an effective tool for investigating aquatic systems. In this study, a 3D hydrodynamic and water quality (ecological) model was used to simulate eutrophication of a drinking water source, Lake Vomb, in Sweden under present and future scenarios. The hydrodynamic model was set-up in MIKE 3 FM software based on meteorological, hydrological, and water quality data. The hydrodynamic model performance was satisfactory in terms of the water temperature simulation, with root-mean-square-error (RMSE) ranging from 0.38 to 1.2 °C. In the ecological model, Chlorophyll-a (Chl-a) was used as a proxy for Cyanobacteria, and the model proved acceptable in simulating the Chl-a concentrations, with a Nash-Sutcliffe efficiency (NSE) of 0.93 and 0.87 for calibration and validation respectively. The findings revealed that external nitrogen loading and internal phosphorus loading had significant impact on the nutrient concentrations in Lake Vomb. The findings also showed a correlation between Chl-a levels and total phosphorus levels in the lake. To simulate future water quality in the lake, two Representative Concentration Pathways (RCP) for the year 2050 were used to make projections for changes in air temperature and precipitation. Under the projected future climate, the simulations showed a considerable rise in Cyanobacteria biomass independent of the changes in external nutrient loading. The model findings can assist water managers in planning mitigation strategies by identifying major nutrient sources.

The Impact of Current and Future Climates on Spatiotemporal Dynamics of Influenza in a Tropical Setting

The Impact of Current and Future Climates on Spatiotemporal Dynamics of Influenza in a Tropical Setting

Projecting Future Climate Impact on National Australian Respiratory-Related Intensive Care Unit Demand.

A robust climate-health projection model has the potential to improve health care resource allocation. We aim to explore the relationship between Australian intensive care unit (ICU) demand and various measures of the long-lived large-scale climate and to develop a future nationwide climate-health projection model. We investigated patients admitted to ICUs in Australia between January 2003 and December 2019 who were exposed to long-lived large-scale combined climatic measures of temperature and humidity. We analysed the projected demand for respiratory-related ICU average length of stay (in days) per capita (ICUD/C) with four historical and one future projection dataset. These datasets included: i) Australian and New Zealand Intensive Care Society adult patient database, ii) Socioeconomic Data and Applications Center gridded global historical population, iii) Australian Bureau of Statistics national historical population, iv) Japanese 55-year Reanalysis historical climate (JRA55), and v) the fifth Coupled Model Inter-comparison Project future climate projections. 148,638 patients with respiratory issues required intensive care between 2003 and 2019. The annual growth in the population density-weighted wet-bulb-globe temperature-a combined measure of temperature and humidity-is strongly correlated with the annual per capita growth ICUD/C for respiratory-related conditions (r=0.771; p<0.001). This relationship was applied to develop a model projecting future respiratory-related ICU demand with three possible future Representative Concentration Pathways (RCP). RCP2.6 (lowest carbon emission climate scenario) showed only a 33.4% increase in Australian ICUD/C demand by 2090, while the RCP8.5 (highest carbon emission climate scenario) demonstrated almost two-fold higher demand (66.1%) than RCP2.6 by2090. The annual growth in population density-weighted wet-bulb-globe temperature correlates with the annual growth in Australian ICUD/C for respiratory-related conditions. A model based on possible future climate scenarios can be developed to predict changes in ICU demand in response to CO2 changes over the coming decades.

Climatological Characteristics of Cold Fronts and Their Impacts on Air Quality in Cold Seasons Over the Eastern China

AbstractEastern China has been frequently suffering from air pollution problems in the past decades. Besides the intensive emissions, weather‐system evolution is generally regarded as an important factor influencing air quality, among which cold fronts are of great importance in regulating the synoptic‐scale variations of regional pollution. Despite numerous case studies conducted, the long‐term climatological behaviors of cold front depicting their overall impacts on air quality remain unrevealed. In this study, an objective front identification approach has been performed to construct a 42‐year climatology of cold‐front activities in eastern China. It is found that the cold fronts and pollution events usually coincide in cold seasons, and have great impacts on air quality in metropolitan regions. A significant accumulation (cleansing) effect on surface air pollutants in the Beijing‐Tianjin‐Hebei (BTH) region before (after) the passage of the front has been observed in autumn and winter, with mean fine particles (PM2.5) concentrations varying by 40–80 μg/m3 during the processes. The cold fronts that go through the Yangtze River Delta region in winter also lead to the decrease of the PM2.5 concentration after the passages of about 15 μg/m3. Major influencing factors include the changes in meteorological conditions and regional transport driven by frontal circulation, which are favorable for pollutants dispersion and advection. On the interannual scale, the cleansing effect of the cold fronts dominates in BTH regions. The statistical relationship between cold fronts and regional air quality highlighted would help understand the impact of both past and future climate on regional pollution from a synoptic perspective.

Future climate conditions accelerate wheat straw decomposition alongside altered microbial community composition, assembly patterns, and interaction networks

Although microbial decomposition of plant litter plays a crucial role in nutrient cycling and soil fertility, we know less about likely links of specific microbial traits and decomposition, especially in relation to climate change. We study here wheat straw decomposition under ambient and manipulated conditions simulating a future climate scenario (next 80 years) in agroecosystems, including decay rates, macronutrient dynamics, enzyme activity, and microbial communities. We show that future climate will accelerate straw decay rates only during the early phase of the decomposition process. Additionally, the projected climate change will increase the relative abundance of saprotrophic fungi in decomposing wheat straw. Moreover, the impact of future climate on microbial community assembly and molecular ecological networks of both bacteria and fungi will strongly depend on the decomposition phase. During the early phase of straw decomposition, stochastic processes dominated microbial assembly under ambient climate conditions, whereas deterministic processes highly dominated bacterial and fungal communities under simulated future climate conditions. In the later decomposition phase, similar assembly processes shaped the microbial communities under both climate scenarios. Furthermore, over the early phases of decomposition, simulated future climate enhanced the complexity of microbial interaction networks. We concluded that the impact of future climate on straw decay rate and associated microbial traits like assembly processes and inter-community interactions is restricted to the early phase of decomposition.

Climate change implications for olive flowering in Crete, Greece: projections based on historical data

Climate change is expected to pose major challenges for olive cultivation in many Mediterranean countries. Predicting the development phases of olive trees is important for agronomic management purposes to foresee future climate impact and proactively act toward adaptation and mitigation strategies. In this study, a statistical model was developed based on winter chill accumulation and, in sequence, on heat accumulation to assess the changes in flowering occurrence for Olea europaea cv. Koroneiki, in the island of Crete, Greece. The model was based on and calibrated with long-term phenological observations and temperature data from four different sites in the island, spanning an elevation gradient between 45 and 624 m a.s.l. This model was used to assess the changes in flowering emergence under two Representative Concentration Pathway scenarios, RCP4.5 and RCP8.5, as projected by seven high-resolution Euro-CORDEX Regional Climate Models. Changes in chill accumulation were determined using the Dynamic Model. Reduction rates in chill accumulation for the whole chilling season ranged between 12.0 and 28.3% for the near future (2021–2060) and 22.7 and 70.9% for the far future (2061–2100), in comparison to the reference period of 1979–2019. Flowering was estimated to occur between 6 and 10 days earlier in the near future and between 12 and 26 days earlier in the far future, depending on the elevation and the climate change scenario.

Analysis of Quadratic Correlation between Dryness Indices and Wine Grape Yield to Estimate Future Climate Impacts in Hungary

In many regions, water availability influences grape yield fluctuations more than thermal conditions. This study analyzes dryness indices calculated from observed and simulated RCM data to establish statistical relationships with observed yield data, considered an indicator of food safety. Five dryness indices were analyzed: the number of days without rain, the maximum number of consecutive dry days, climatic water balance, dryness index, and vineyard water indicator. These indices were analyzed for three periods: 1986–2005 (recent past), 2016–2035 (near future) and 2081–2100 (distant future). After this analysis, quadratic regression connections were established between the indices and available wine grape yields in the 22 wine regions of Hungary for 2005–2021 without information on grape varieties and for 2017–2021 with data on grape varieties. Linear agro-technological trends were extracted from these wine grape yield series, whereas the residuals exhibited significant quadratic regression in slightly over 50% of the indices and regions, according to the F-test for the 17 year series. For the short series, these proportions are 29 and 27% for the selected seven white and seven red wine grapes. According to the most significant quadratic regressions, combined with the projected dryness indices, we can expect less average yields with higher interannual variability in the future.

Predicting Maize (Zea mays) productivity under projected climate change with management options in Amhara region, Ethiopia

Maize is an important cereal crop in Ethiopia. Maize yield has been declined in Ethiopia mainly due to water scarcity, low soil fertility and heat stress. Currently, limited technologies are available in the study region that increases maize productivity. If crop models are properly calibrated, they are effective tools to study crops responses to environmental factors. Assessing impact of future climate on maize crop may help to develop adaptation strategies. The objectives of this study were (1) to calibrate and evaluate the CERES maize model in DSSAT technology for simulating phenology and yield of maize (2) to assess impact of projected climate change on maize productivity (3) to develop promising management practices for maize. The impact of projected climate change was assessed using the 17 GCMs (CMIP5) run under RCP4.5 and RCP8.5 climate scenarios. Two water regimes treatments (rainfed and irrigated) and four rates of nitrogen (0, 46, 92 and 138 kg ha−1) were evaluated individually and in combinations for their effectiveness to increase maize productivity under the projected climate conditions. The model evaluation result revealed that the RMSE values were 2.5 days for anthesis, 4.4 days for physiological maturity, 258.3 kg ha−1 for grain yield and 1034 kg ha−1for above ground biomass yield with nRMSE values of 3%, 4%, 4.7% and 10%, respectively. The d-index values were 0.87, 0.80, 0.88 and 0.71 for the respective parameters. The good agreement between the simulated and the measured values indicated the maize genetic coefficients in the model were properly calibrated. The simulation results at Tehuledere site showed that maize grain yield may decrease by 11% and 20% in 2030s and by 26% and 29% in 2050s under RCP4.5 and RCP8.5 scenarios, respectively whereas in Kallu site yield may decrease by 13% and 15% in 2030s and by 17% and 19% in 2050s for the respective RCP scenarios. However, the management scenarios have shown that maize yield may substantially increase by the use of optimum nitrogen fertilizer and supplemental irrigation. Thus, it can be generalized that climate change may adversely affect maize production in the Semi-arid regions of Ethiopia but the impact could be reversed by using sound crop management practices.

Impact of a Warming Climate on Hospital Energy Use and Decarbonization: An Australian Building Simulation Study

The high energy use of hospitals and healthcare facilities globally contributes to greenhouse gas emissions. At the same time, a large percentage of this energy use is attributed to space heating, cooling and ventilation, and is hence correlated to the climate. While the energy performance of Australian hospitals at the design stage is evaluated using historical weather data, the impact of the warming climate on Australian hospitals into the future remains unknown. The research question addressed is: What is the impact of future climates on the energy use of Australian hospitals built with the current design conditions? Two archetype hospital models were developed (a small single-story healthcare facility and a large multi-story hospital). DesignBuilder was used to simulate the performance of these models in 10 locations, ranging from the tropics to cool temperate regions in Australia. Current (1990–2015) and future climate files (2030, 2050, 2070 and 2090) were used. The results show that with the warming climate, the heating demand decreased, while the cooling demand increased for both hospital models for all sites. Cooling dominated climates, such as Darwin and Brisbane, were significantly impacted by the changing climates due to a substantial increase in cooling energy use. Heating based climates, such as Hobart and Canberra, resulted in an overall small reduction in total building energy use. In addition, the single-story facility was more impacted by the change in climate (in terms of energy use intensity) than the multi-story facility. The study highlights the importance of future climate files in building simulation and decarbonization planning.

Climate induced phenological shifts in pears – A crop of economic importance in the UK

Phenological advancements in flowering have been well documented in many food crop, ornamental, and native plant species. However, there is lack of information on how flowering times in crop species, especially fruit trees will react to future climate scenarios. This is important as changes in phenology could have significant implications for ecosystem services and function, biological interactions and agronomic outputs. Using 60 years of data from pear (Pyrus communis L.) orchards in two research organisations in Kent, UK we explored temporal changes in flowering phenology, identified the weather variables driving this change, and predicted how flowering times may be altered by 2080 with respect to future emissions scenarios. We show pear flowering (1990–2020) in the last 30 years has advanced 11.44 days compared to historical data (1960–1989). Furthermore, we highlight this advancement is apparent in all twelve pear cultivars and the four phenological stages analysed, including Conference, the most common UK pear cultivar. Our results indicate that this advancement in flowering began after 1982; that air temperature and frost days significantly impact pear flowering; and this change in flowering phenology is likely to continue under future climate scenarios. Four Representative Concentration Pathways from the UK Climate Projections 2018 report were used to model the impact of future climate, including low, medium, medium-high and high emission scenarios. Under all scenarios a phenological advancement in flowering time was predicted by 2080 with the greatest advancement in flowering time observed under the high emission scenario. Earlier flowering and budburst could result in phenological mismatches between plant and pollinators, alter agricultural spraying regimes, increase risk of frost exposure and exacerbate impacts of pest populations within an agroecosystem, thus it is vital to monitor advancements in flowering phenology.

Reducing future climate impact on rural transport infrastructure in developing countries; the role of engineering geology

Hard-won development gains are under real threat due to climate change impacts on rural transport infrastructure (RTI) and it is a major challenge, within normally available budgets, to ensure that rural access is made sustainably climate resilient. The ability of engineers and engineering geologists to identify problems and to devise solutions that provide sustainable cost-effective access for the rural poor is a key factor in overarching aims of poverty reduction and socio-economic development in lower and middle-income countries (LMICs). Engineering geology, through its inherent wide-ranging and inclusive approach to earth science, has an important role to play in providing a holistic and cross-sectorial framework to meet this challenge in a sustainable manner. This paper firstly emphasizes the importance of RTI, then outlines the climate change risks to RTI and hence to socio-economic development in LMICs. The paper then describes the key contribution that engineering geology can make to combatting this challenge through cost-effective climate-strengthening measures aided by the practical application of sound earth-science principles in a budget-constrained environment. Illustrative examples are taken from recent and ongoing LMIC projects funded by the UKAID Department for International Development, the Word Bank, the Asian Development Bank and Kreditanstaltfür Wiederaufbau – the German Development Bank. Thematic collection: This article is part of the Climate change and resilience in Engineering Geology and Hydrogeology collection available at: https://www.lyellcollection.org/cc/climate-change-and-resilience-in-engineering-geology-and-hydrogeology