In today's fast-shifting climate change scenario, crops are exposed to environmental pressures, abiotic and biotic stress. Hence, these will affect the production of agricultural products and give rise to a worldwide economic crisis. The increase in world population has exacerbated the situation with increasing food demand. The use of chemical agents is no longer recommended due to adverse effects towards the environment and health. Biocontrol agents (BCAs) and biostimulants, are feasible options for dealing with yield losses induced by plant stresses, which are becoming more intense due to climate change. BCAs and biostimulants have been recommended due to their dual action in reducing both stresses simultaneously. Although protection against biotic stresses falls outside the generally accepted definition of biostimulant, some microbial and non-microbial biostimulants possess the biocontrol function, which helps reduce biotic pressure on crops. The application of synergisms using BCAs and biostimulants to control crop stresses is rarely explored. Currently, a combined application using both agents offer a great alternative to increase the yield and growth of crops while managing stresses. This article provides an overview of crop stresses and plant stress responses, a general knowledge on synergism, mathematical modelling used for synergy evaluation and type of in vitro and in vivo synergy testing, as well as the application of synergism using BCAs and biostimulants in reducing crop stresses. This review will facilitate an understanding of the combined effect of both agents on improving crop yield and growth and reducing stress while also providing an eco-friendly alternative to agroecosystems.
The influences of climate on the retention capability of green roof have been widely discussed in existing literature. However, knowledge on how the retention capability of green roof is affected by the tropical climate is limited. This paper highlights the retention performance of the green roof situated in Kuching under hot-humid tropical climatic conditions. Using the green roof water balance modelling approach, this study simulated the hourly runoff generated from a virtual green roof from November 2012 to October 2013 based on past meteorological data. The result showed that the overall retention performance was satisfactory with a mean retention rate of 72.5% from 380 analysed rainfall events but reduced to 12.0% only for the events that potentially trigger the occurrence of flash flood. By performing the Spearman rank's correlation analysis, it was found that the rainfall depth and mean rainfall intensity, individually, had a strong negative correlation with event retention rate, suggesting that the retention rate increases with decreased rainfall depth. The expected direct relationship between retention rate and antecedent dry weather period was found to be event size dependent.
Urban sewer networks (SNs) are increasingly facing water quality issues as a result of many challenges, such as population growth, urbanization and climate change. A promising way to addressing these issues is by developing and using water quality models. Many of these models have been developed in recent years to facilitate the management of SNs. Given the proliferation of different water quality models and the promise they have shown, it is timely to assess the state-of-the-art in this field, to identify potential challenges and suggest future research directions. In this review, model types, modeled quality parameters, modeling purpose, data availability, type of case studies and model performance evaluation are critically analyzed and discussed based on a review of 110 papers published between 2010 and 2019. The review identified that applications of empirical and kinetic models dominate those of data-driven models for addressing water quality issues. The majority of models are developed for prediction and process understanding using experimental or field sampled data. While many models have been applied to real problems, the corresponding prediction accuracies are overall moderate or, in some cases, low, especially when dealing with larger SNs. The review also identified the most common issues associated with water quality modeling of SNs and based on these proposed several future research directions. These include the identification of appropriate data resolutions for the development of different SN models, the need and opportunity to develop hybrid SN models and the improvement of SN model transferability.
Nowadays, the world is confronting the increasing energy demand, reduction of emissions and security of energy supply. The high energy demand leads to a severe problem, and we need to reduce the usage of non-renewable energy to avoid adverse climate change. Thus, renewable energy is an important role obtained from the natural environment and can be replenished naturally from those sources without environmental degradation. Water energy is one of the most promising renewable energy sources today, especially in the aquaculture industry. Hydropower played a vital role in producing large scale power and electricity. This study was set up to determine the electrical energy output depending on the different sizes and shapes of tanks. It is also to measure the water flow rate based on different size and shape tanks. Besides, the Pelton type of water turbine generator micro-hydroelectric DC 12V output was used in this experiment. Two types of tanks (rectangular and circular) with three different sizes (0.5 ton, 1.0 ton and 2.0 ton) were tested to measure high value of output energy (V) and flow rate (m3/s) by using clear water and wastewater. The result significantly shows that the circular tank had a higher water flow rate and output energy than the rectangular tank due to higher gravitational force, where the outlet placed in the middle and edge of the tank, respectively. The finding of this study benefits the aquaculture industry, where it introduced an alternative and cheaper method of reusing wastewater, reducing the cost maintenances and enhancing the profit of the business.
This study focuses on the parasites in Dascyllus trimaculatus fish in Bidong Island. Though D. trimaculatus is a common reef fish, there is lack on parasites studies of this fish in Malaysia. The objectives of this study are to identify metazoan parasites and analyse the prevalence and mean intensity the parasites in D. trimaculatus. Sampling was randomly conducted on a coral colony of 100 meters within a 15m depth at Pantai Pasir Cina,BidongIsland.ThisresearchresultedintheidentificationofacopepodLernaeocera branchialis and a nematode from the family Camallanidae. The copepods collected in this study infected 20 out of 42 D. trimaculatus specimens, whereas the nematode-like parasites collected infected 18 of out of 42 D. trimaculatus. All copepods found in the gills of D. trimaculatus had a prevalence of 4.95 and mean intensity of 47.62%, while the nematode-like parasite, which were found in the brain, had 2.72 prevalence and 42.86% mean intensity. This elucidates that both parasites are categorised as having light levelbut common frequency of infection, and the current IUCN status of D. trimaculatus has not been reported to be harmedby parasites. Though the mean intensity of both parasites isnot harmful, the prevalence are concerning and might increase in the future, with further incorporation and monitoring of climate change factors that may affect the damselfish.
The oil palm seed production unit that generates germinated oil palm seeds is the first link in the palm oil supply chain, followed by the nursery to produce seedling, the plantation to produce fresh fruit bunches (FFB), the mill to produce crude palm oil (CPO) and palm kernel, the kernel crushers to produce crude palm kernel oil (CPKO), the refinery to produce refined palm oil (RPO) and finally the palm biodiesel plant to produce palm biodiesel. This assessment aims to investigate the life cycle assessment (LCA) of germinated oil palm seeds and the use of LCA to identify the stage/s in the production of germinated oil palm seeds that could contribute to the environmental load. The method for the life cycle impact assessment (LCIA) is modelled using SimaPro version 7, (System for Integrated environMental Assessment of PROducts), an internationally established tool used by LCA practitioners. This software contains European and US databases on a number of materials in addition to a variety of European- and US-developed impact assessment methodologies. LCA was successfully conducted for five seed production units and it was found that the environmental impact for the production of germinated oil palm was not significant. The characterised results of the LCIA for the production of 1000 germinated oil palm seeds showed that fossil fuel was the major impact category followed by respiratory inorganics and climate change.
The prediction is that food supply must double by 2050 to cope with the impact of climate change and population pressure on global food systems. The diversification of staple crops and the systems in which they grow is essential to make future agriculture sustainable, resilient, and suitable for local environments and soils.
Climate change exposes vegetation to unusual levels of drought, risking a decline in productivity and an increase in mortality. It still remains unclear how trees and forests respond to such unusual drought, particularly Southeast Asian tropical rain forests. To understand leaf ecophysiological responses of tropical rain forest trees to soil drying, a rainfall exclusion experiment was conducted on mature canopy trees of Dryobalanops aromatica Gaertn.f. (Dipterocarpaceae) for 4 months in an aseasonal tropical rain forest in Sarawak, Malaysia. The rainfall was intercepted by using a soft vinyl chloride sheet. We compared the three control and three treatment trees with respect to leaf water use at the top of the crown, including stomatal conductance (gsmax), photosynthesis (Amax), leaf water potential (predawn: Ψpre; midday: Ψmid), leaf water potential at turgor loss point (πtlp), osmotic potential at full turgor (π100) and a bulk modulus of elasticity (ε). Measurements were taken using tree-tower and canopy-crane systems. During the experiment, the treatment trees suffered drought stress without evidence of canopy dieback in comparison with the control trees; e.g., Ψpre and Ψmid decreased with soil drying. Minimum values of Ψmid in the treatment trees decreased during the experiment, and were lower than πtlp in the control trees. However, the treatment trees also decreased their πtlp by osmotic adjustment, and the values were lower than the minimum values of their Ψmid. In addition, the treatment trees maintained gs and Amax especially in the morning, though at midday, values decreased to half those of the control trees. Decreasing leaf water potential by osmotic adjustment to maintain gs and Amax under soil drying in treatment trees was considered to represent anisohydric behavior. These results suggest that D. aromatica may have high leaf adaptability to drought by regulating leaf water consumption and maintaining turgor pressure to improve its leaf water relations.
Climate change is primarily manifested by elevated temperature and carbon dioxide (CO2) levels and is projected to provide suitable cultivation grounds for pests and pathogens in the otherwise unsuitable regions. The impacts of climate change have been predicted in many parts of the world, which could threaten global food safety and food security. The aim of the present work was therefore to examine the interacting effects of water activity (aw) (0.92, 0.95, 0.98 aw), CO2 (400, 800, 1200 ppm) and temperature (30, 35 °C and 30, 33 °C for Fusarium verticillioides and F. graminearum, respectively) on fungal growth and mycotoxin production of acclimatised isolates of F. verticillioides and F. graminearum isolated from maize. To determine fungal growth, the colony diameters were measured on days 1, 3, 5, and 7. The mycotoxins produced were quantified using a quadrupole-time-of-flight mass spectrometer (QTOF-MS) combined with ultra-high-performance liquid chromatography (UHPLC) system. For F. verticillioides, the optimum conditions for growth of fumonisin B1 (FB1), and fumonisin B2 (FB2) were 30 °C + 0.98 aw + 400 ppm CO2. These conditions were also optimum for F. graminearum growth, and zearalenone (ZEA) and deoxynivalenol (DON) production. Since 30 °C and 400 ppm CO2 were the baseline treatments, it was hence concluded that the elevated temperature and CO2 levels tested did not seem to significantly impact fungal growth and mycotoxin production of acclimatised Fusarium isolates. To the best of our knowledge thus far, the present work described for the first time the effects of simulated climate change conditions on fungal growth and mycotoxin production of acclimatised isolates of F. verticillioides and F. graminearum.
The relationship between greenhouse gas emission and climate change has led to research to identify and manage the natural sources and sinks of the gases. CO2, CH4, and N2O have an anthropic source and of these CO2 is the least effective in trapping long wave radiation. Soil carbon sequestration can best be described as a process of removing carbon dioxide from the atmosphere and relocating into soils in a form that is not readily released back into the atmosphere. The purpose of this study is to estimate carbon stocks available under current conditions in Sarawak, Malaysia. SOC estimates are made for a standard depth of 100 cm unless the soil by definition is less than this depth, as in the case of lithic subgroups. Among the mineral soils, Inceptisols tend to generally have the highest carbon contents (about 25 kg m(-2) m(-1)), while Oxisols and Ultisols rate second (about 10-15 kg m(-2) m(-1)). The Oxisols store a good amount of carbon because of an appreciable time-frame to sequester carbon and possibly lower decomposition rates for the organic carbon that is found at 1m depths. Wet soils such as peatlands tend to store significant amounts of carbon. The highest values estimated for such soils are about 114 kg m(-2) m(-1). Such appreciable amounts can also be found in the Aquepts. In conclusion, it is pertinent to recognize that degradation of the carbon pool, just like desertification, is a real process and that this irreversible process must be addressed immediately. Therefore, appropriate soil management practices should be instituted to sequester large masses of soil carbon on an annual basis. This knowledge can be used effectively to formulate strategies to prevent forest fires and clearing: two processes that can quickly release sequestered carbon to the atmosphere in an almost irreversible manner.
Drought forecasting with a long lead time is essential for early warning systems and risk management strategies. The use of machine learning algorithms has been proven to be beneficial in forecasting droughts. However, forecasting at long lead times remains a challenge due to the effects of climate change and the complexities involved in drought assessment. The rise of deep learning techniques can solve this issue, and the present work aims to use a stacked long short-term memory (LSTM) architecture to forecast a commonly used drought measure, namely, the Standard Precipitation Evaporation Index. The model was then applied to the New South Wales region of Australia, with hydrometeorological and climatic variables as predictors. The multivariate interpolated grid of the Climatic Research Unit was used to compute the index at monthly scales, with meteorological variables as predictors. The architecture was trained using data from the period of 1901-2000 and tested on data from the period of 2001-2018. The results were then forecasted at lead times ranging from 1 month to 12 months. The forecasted results were analysed in terms of drought characteristics, such as drought intensity, drought onset, spatial extent and number of drought months, to elucidate how these characteristics improve the understanding of drought forecasting. The drought intensity forecasting capability of the model used two statistical metrics, namely, the coefficient of determination (R2) and root-mean-square error. The variation in the number of drought months was examined using the threat score technique. The results of this study showed that the stacked LSTM model can forecast effectively at short-term and long-term lead times. Such findings will be essential for government agencies and can be further tested to understand the forecasting capability of the presented architecture at shorter temporal scales, which can range from days to weeks.
Many cities across the world are facing many problems climate change poses to their populations, communities and infrastructure. These vary from increased exposures to floods, to discomfort due to urban heat, depending on their geographical locations and settings. However, even though some cities have a greater ability to cope with climate change challenges, many struggle to do so, particularly in cities in developing countries. In addition, there is a shortage of international studies which examine the links between climate change adaptation and cities, and which at the same time draw some successful examples of good practice, which may assist future efforts. This paper is an attempt to address this information need. The aim of this paper is to analyse the extent to which cities in a sample of developing countries are attempting to pursue climate change adaptation and the problems which hinder this process. Its goal is to showcase examples of initiatives and good practice in transformative adaptation, which may be replicable elsewhere. To this purpose, the paper describes some trends related to climate change in a set of cities in developing countries across different continents, including one of the smallest capital cities (Georgetown, Guyana) and Shanghai, one the world's most populous cities. In particular, it analyses their degree of vulnerability, how they manage to cope with climate change impacts, and the policies being implemented to aid adaptation. It also suggests the use of transformative approaches which may be adopted, in order to assist them in their efforts towards investments in low-carbon and climate-resilient infrastructure, thereby maximizing investments in urban areas and trying to address their related poverty issues. This paper addresses a gap in the international literature on the problems many cities in developing countries face, in trying to adapt to a changing climate.
Air pollution and atmospheric deposition have adverse effects on tree and forest health. We reviewed studies on tree and forest decline in Northeast and Southeast Asia, Siberia, and the Russian Far East (hereafter referred to as East Asia). This included studies published in domestic journals and languages. We identified information about the locations, causes, periods, and tree species exhibiting decline. Past air pollution was also reviewed. Most East Asian countries show declining trends in SO2 concentration in recent years, although Mongolia and Russia show increasing trends. Ozone (O3) concentrations are stable or gradually increasing in the East Asia region, with high maxima. Wet nitrogen (N) deposition was high in China and tropical countries, but low in Russia. The decline of trees and forests primarily occurred in the mid-latitudes of Japan, Korea, China, and Russia. Long-term large N deposition resulted in the N saturation phenomenon in Japan and China, but no clear forest health response was observed. Thereafter, forest decline symptoms, suspected to be caused by O3, were observed in Japan and China. In East Russia, tree decline occurred around industrial centers in Siberia. Haze events have been increasing in tropical and boreal forests, and particulate matter inhibits photosynthesis. In recent years, chronically high O3 concentrations, in conjunction with climate change, are likely have adverse effects on tree physiology. The effects of air pollution and related factors on tree decline are summarized. Recently, the effects of air pollution on tree decline have not been apparent under the changing climate, however, monitoring air pollution is indispensable for identifying the cause of tree decline. Further economic growth is projected in Southeast Asia and therefore, the monitoring network should be expanded to tropical and boreal forest zones. Countermeasures such as restoring urban trees and rural forests are important for ensuring future ecosystem services.
Species invasion is an important cause of global biodiversity decline and is often mediated by shifts in environmental conditions such as climate change. To investigate this relationship, a mechanistic Dynamic Energy Budget model (DEB) approach was used to predict how climate change may affect spread of the invasive mussel Mytilopsis sallei, by predicting variation in the total reproductive output of the mussel under different scenarios. To achieve this, the DEB model was forced with present-day satellite data of sea surface temperature (SST) and chlorophyll-a concentration (Chl-a), and SST under two warming RCP scenarios and decreasing current Chl-a levels, to predict future responses. Under both warming scenarios, the DEB model predicted the reproductive output of M. sallei would enhance range extension of the mussel, especially in regions south of the Yangtze River when future declines in Chl-a were reduced by less than 10%, whereas egg production was inhibited when Chl-a decreased by 20-30%. The decrease in SST in the Yangtze River may, however, be a natural barrier to the northward expansion of M. sallei, with colder temperatures resulting in a strong decrease in egg production. Although the invasion path of M. sallei may be inhibited northwards by the Yangtze River, larger geographic regions south of the Yangtze River run the risk of invasion, with subsequent negative impacts on aquaculture through competition for food with farmed bivalves and damaging aquaculture facilities. Using a DEB model approach to characterise the life history traits of M. sallei, therefore, revealed the importance of food availability and temperature on the reproductive output of this mussel and allowed evaluation of the invasion risk for specific regions. DEB is, therefore, a powerful predictive tool for risk management of already established invasive populations and to identify regions with a high potential invasion risk.
Climate change is one of the major challenges societies round the world face at present. Apart from efforts to achieve a reduction of emissions of greenhouse gases so as to mitigate the problem, there is a perceived need for adaptation initiatives urgently. Ecosystems are known to play an important role in climate change adaptation processes, since some of the services they provide, may reduce the impacts of extreme events and disturbance, such as wildfires, floods, and droughts. This role is especially important in regions vulnerable to climate change such as the African continent, whose adaptation capacity is limited by many geographic and socio-economic constraints. In Africa, interventions aimed at enhancing ecosystem services may play a key role in supporting climate change adaptation efforts. In order to shed some light on this aspect, this paper reviews the role of ecosystems services and investigates how they are being influenced by climate change in Africa. It contains a set of case studies from a sample of African countries, which serve the purpose to demonstrate the damages incurred, and how such damages disrupt ecosystem services. Based on the data gathered, some measures which may assist in fostering the cause of ecosystems services are listed, so as to cater for a better protection of some of the endangered Africa ecosystems, and the services they provide.
The threat posed by invasive non-native species worldwide requires a global approach to identify which introduced species are likely to pose an elevated risk of impact to native species and ecosystems. To inform policy, stakeholders and management decisions on global threats to aquatic ecosystems, 195 assessors representing 120 risk assessment areas across all six inhabited continents screened 819 non-native species from 15 groups of aquatic organisms (freshwater, brackish, marine plants and animals) using the Aquatic Species Invasiveness Screening Kit. This multi-lingual decision-support tool for the risk screening of aquatic organisms provides assessors with risk scores for a species under current and future climate change conditions that, following a statistically based calibration, permits the accurate classification of species into high-, medium- and low-risk categories under current and predicted climate conditions. The 1730 screenings undertaken encompassed wide geographical areas (regions, political entities, parts thereof, water bodies, river basins, lake drainage basins, and marine regions), which permitted thresholds to be identified for almost all aquatic organismal groups screened as well as for tropical, temperate and continental climate classes, and for tropical and temperate marine ecoregions. In total, 33 species were identified as posing a 'very high risk' of being or becoming invasive, and the scores of several of these species under current climate increased under future climate conditions, primarily due to their wide thermal tolerances. The risk thresholds determined for taxonomic groups and climate zones provide a basis against which area-specific or climate-based calibrated thresholds may be interpreted. In turn, the risk rankings help decision-makers identify which species require an immediate 'rapid' management action (e.g. eradication, control) to avoid or mitigate adverse impacts, which require a full risk assessment, and which are to be restricted or banned with regard to importation and/or sale as ornamental or aquarium/fishery enhancement.
Seagrasses have the ability to contribute towards climate change mitigation, through large organic carbon (Corg) sinks within their ecosystems. Although the importance of blue carbon within these ecosystems has been addressed in some countries of Southeast Asia, the regional and national inventories with the application of nature-based solutions are lacking. In this study, we aim to estimate national coastal blue carbon stocks in the seagrass ecosystems in the countries of Southeast Asia including the Andaman and Nicobar Islands of India. This study further assesses the potential of conservation and restoration practices and highlights the seagrass meadows as nature-based solution for climate change mitigation. The average value of the total carbon storage within seagrass meadows of this region is 121.95 ± 76.11 Mg ha-1 (average ± SD) and the total Corg stock of the seagrass meadows of this region was 429.11 ± 111.88 Tg, with the highest Corg stock in the Philippines (78%). The seagrass meadows of this region have the capacity to accumulate 5.85-6.80 Tg C year-1, which accounts for $214.6-249.4 million USD. Under the current rate of decline of 2.82%, the seagrass meadows are emitting 1.65-2.08 Tg of CO2 year-1 and the economic value of these losses accounts for $21.42-24.96 million USD. The potential of the seagrass meadows to the offset current CO2 emissions varies across the region, with the highest contribution to offset is in the seagrass meadows of the Philippines (11.71%). Current national policies and commitments of nationally determined contributions do not include blue carbon ecosystems as climate mitigation measures, even though these ecosystems can contribute up to 7.03% of the countries' reduction goal of CO2 emissions by 2030. The results of this study highlight and promote the potential of the southeast Asian seagrass meadows to national and international agencies as a practical scheme for nature-based solutions for climate change mitigation.
While droughts and floods have intensified in recent years, only a handful of studies have assessed their impacts on croplands and production in Southeast Asia. Here, we used the Google Earth Engine to assess the droughts and floods and their impacts on croplands and crop production over 40 years from 1980 to 2019. Using the Palmer Drought Severity Index (PDSI) as the basis for determining the drought and flood levels, and crop damage levels, crop production loss in both the Monsoon Climate Region (MCR) and the Equatorial Climate Region (ECR) of Southeast Asia was assessed over 47,192 grid points with 10 × 10-kilometer resolution. We found that rainfed crops were severely affected by droughts in the MCR and floods in the ECR. About 9.42 million ha and 3.72 million ha of cropland was damaged by droughts and floods, respectively. We estimated a total loss of 20.64 million tons of crop production between 2015 and 2019. Rainfed crops in Thailand, Cambodia, and Myanmar were strongly affected by droughts, whereas Indonesia, the Philippines, and Malaysia were more affected by floods over the same period. Accordingly, four levels of policy interventions were prioritized by considering the geolocated crop damage levels.
Deforestation, climate change and invasive species constitute three global threats to biodiversity that act synergistically. However, drivers and rates of loss of freshwater biodiversity now and in the future are poorly understood. Here we focus on the potential impacts of global change on freshwater mussels (Order Unionida) in Sundaland (SE Asia), a vulnerable group facing global declines and recognized indicators of overall freshwater biodiversity. We used an ensemble of distribution models to identify habitats potentially suitable for freshwater mussels and their change under a range of climate, deforestation and invasion scenarios. Our data and models revealed that, at present, Sundaland features 47 and 32 Mha of habitat that can be considered environmentally suitable for native and invasive freshwater mussels, respectively. We anticipate that by 2050, the area suitable for palm oil cultivation may expand between 8 and 44 Mha, representing an annual increase of 2-11%. This is expected to result in a 20% decrease in suitable habitat for native mussels, a drop that reaches 30% by 2050 when considering concomitant climate change. In contrast, the habitat potentially suitable for invasive mussels may increase by 44-56% under 2050 future scenarios. Consequently, native mussels may compete for habitat, food resources and fish hosts with invasive mussels across approximately 60% of their suitable range. Our projections can be used to guide future expeditions to monitor the conservation status of freshwater biodiversity, and potentially reveal populations of endemic species on the brink of extinction. Future conservation measures-most importantly the designation of nature reserves-should take into account trends in freshwater biodiversity generally, and particularly species such as freshwater mussels, vital to safeguard fundamental ecosystem services.
Climate change in Asia is affecting farmers' daily routines. Much of the focus surrounding climate change has targeted the economic and environmental repercussions on farming. Few systematic reviews have been carried out on the social impacts of climate change among farmers in Asia. The present article set out to analyse the existing literature on Asian farmers' adaptation practices towards the impacts of climate change. Guided by the PRISMA Statement (Preferred Reporting Items for Systematic reviews and Meta-Analyses) review method, a systematic review of the Scopus and Web of Science databases identified 38 related studies. Further review of these articles resulted in six main themes - crop management, irrigation and water management, farm management, financial management, physical infrastructure management and social activities. These six themes further produced a total of 35 sub-themes. Several recommendations are highlighted related to conducting more qualitative studies, to have specific and a standard systematic review method for guide research synthesis in context of climate change adaptation and to practice complimentary searching techniques such as citation tracking, reference searching, snowballing and contacting experts.