Displaying publications 21 - 40 of 805 in total

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  1. Hii YL, Zaki RA, Aghamohammadi N, Rocklöv J
    Curr Environ Health Rep, 2016 Mar;3(1):81-90.
    PMID: 26931438 DOI: 10.1007/s40572-016-0078-z
    Dengue is a climate-sensitive infectious disease. Climate-based dengue early warning may be a simple, low-cost, and effective tool for enhancing surveillance and control. Scientific studies on climate and dengue in local context form the basis for advancing the development of a climate-based early warning system. This study aims to review the current status of scientific studies in climate and dengue and the prospect or challenges of such research on a climate-based dengue early warning system in a dengue-endemic country, taking Malaysia as a case study.
    Matched MeSH terms: Climate Change*
  2. Kuruppu N, Capon A
    Lancet, 2016 Jan 30;387(10017):430.
    PMID: 26869566 DOI: 10.1016/S0140-6736(16)00170-7
    Matched MeSH terms: Climate Change*
  3. Islam ARMT, Islam HMT, Shahid S, Khatun MK, Ali MM, Rahman MS, et al.
    J Environ Manage, 2021 Jul 01;289:112505.
    PMID: 33819656 DOI: 10.1016/j.jenvman.2021.112505
    Climate extremes have a significant impact on vegetation. However, little is known about vegetation response to climatic extremes in Bangladesh. The association of Normalized Difference Vegetation Index (NDVI) with nine extreme precipitation and temperature indices was evaluated to identify the nexus between vegetation and climatic extremes and their associations in Bangladesh for the period 1986-2017. Moreover, detrended fluctuation analysis (DFA) and Morlet wavelet analysis (MWA) were employed to evaluate the possible future trends and decipher the existing periodic cycles, respectively in the time series of NDVI and climate extremes. Besides, atmospheric variables of ECMWF ERA5 were used to examine the casual circulation mechanism responsible for climatic extremes of Bangladesh. The results revealed that the monthly NDVI is positively associated with extreme rainfall with spatiotemporal heterogeneity. Warm temperature indices showed a significant negative association with NDVI on the seasonal scale, while precipitation and cold temperature extremes showed a positive association with yearly NDVI. The DEA revealed a continuous increase in temperature extreme in the future, while no change in precipitation extremes. NDVI also revealed a significant association with extreme temperature indices with a time lag of one month and with precipitation extreme without time lag. Spatial analysis indicated insensitivity of marshy vegetation type to climate extremes in winter. The study revealed that elevated summer geopotential height, no visible anticyclonic center, reduced high cloud cover, and low solar radiation with higher humidity contributed to climatic extremes in Bangladesh. The nexus between NDVI and climatic extremes established in this study indicated that increasing warm temperature extremes due to global warming might have severe implications on Bangladesh's ecology and the environment in the future.
    Matched MeSH terms: Climate Change*
  4. Narinderjeet Kaur
    MyJurnal
    Some call it climate change and some global warming, regardless of the term used, it has been deemed the biggest global health threat of the 21st century. It is the 13th goal of United Nations Sustainable Developmental Goals (SDG). Multiple factors contribute to this global phenomenon including the anthropogenic causes which are man-made. The repercussions of this crisis are vast and bring effect environmentally and socioeconomically. These then ultimately lead towards an effect on individual as well as population health.
    Matched MeSH terms: Climate; Climate Change
  5. Haris SM, Mustafa FB, Raja Ariffin RN
    Environ Manage, 2020 11;66(5):816-825.
    PMID: 32893336 DOI: 10.1007/s00267-020-01355-9
    Environmental nongovernmental organizations (ENGOs) are considered key players for engendering good climate change governance to address both climate change and sustainable development. The participation of ENGOs in climate change governance occurs in a four-phase policy cycle. They include (1) identification of policy options, (2) policy formulation, (3) policy implementation, and (4) policy monitoring and evaluation. The ENGOs, however, have been criticized for their lack of effectiveness, and their roles in tackling climate change remain unclear. To date, the study on the roles and activities of Southeast Asian ENGOs in climate change governance has been under-researched. This study, therefore, applies a systematic literature review of 19 published articles from Scopus and Web of Science-indexed journal to understand the current state of the Southeast Asian ENGOs participation in climate change governance based on the four-phase policy cycle. The findings show that the ENGOs in Southeast Asia are involved directly and indirectly in climate change governance. They are significant actors in the implementation of the climate change policy, but they play a minimal role in the formulation of said policy. It implies that they could also be a vital partner to the government in the climate change governance process as they can bring effective policy improvements. Lastly, this review will recommend future avenues of research for scholars.
    Matched MeSH terms: Climate Change*
  6. Tan ALS, Cheng MCF, Giacoletti A, Chung JX, Liew J, Sarà G, et al.
    Sci Total Environ, 2021 Mar 25;762:143097.
    PMID: 33139009 DOI: 10.1016/j.scitotenv.2020.143097
    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.
    Matched MeSH terms: Climate Change*
  7. Jucker T, Bongalov B, Burslem DFRP, Nilus R, Dalponte M, Lewis SL, et al.
    Ecol Lett, 2018 07;21(7):989-1000.
    PMID: 29659115 DOI: 10.1111/ele.12964
    Topography is a key driver of tropical forest structure and composition, as it constrains local nutrient and hydraulic conditions within which trees grow. Yet, we do not fully understand how changes in forest physiognomy driven by topography impact other emergent properties of forests, such as their aboveground carbon density (ACD). Working in Borneo - at a site where 70-m-tall forests in alluvial valleys rapidly transition to stunted heath forests on nutrient-depleted dip slopes - we combined field data with airborne laser scanning and hyperspectral imaging to characterise how topography shapes the vertical structure, wood density, diversity and ACD of nearly 15 km2 of old-growth forest. We found that subtle differences in elevation - which control soil chemistry and hydrology - profoundly influenced the structure, composition and diversity of the canopy. Capturing these processes was critical to explaining landscape-scale heterogeneity in ACD, highlighting how emerging remote sensing technologies can provide new insights into long-standing ecological questions.
    Matched MeSH terms: Tropical Climate*
  8. Feeley KJ, Joseph Wright S, Nur Supardi MN, Kassim AR, Davies SJ
    Ecol Lett, 2007 Jun;10(6):461-9.
    PMID: 17498145
    The impacts of global change on tropical forests remain poorly understood. We examined changes in tree growth rates over the past two decades for all species occurring in large (50-ha) forest dynamics plots in Panama and Malaysia. Stem growth rates declined significantly at both forests regardless of initial size or organizational level (species, community or stand). Decreasing growth rates were widespread, occurring in 24-71% of species at Barro Colorado Island, Panama (BCI) and in 58-95% of species at Pasoh, Malaysia (depending on the sizes of stems included). Changes in growth were not consistently associated with initial growth rate, adult stature, or wood density. Changes in growth were significantly associated with regional climate changes: at both sites growth was negatively correlated with annual mean daily minimum temperatures, and at BCI growth was positively correlated with annual precipitation and number of rainfree days (a measure of relative insolation). While the underlying cause(s) of decelerating growth is still unresolved, these patterns strongly contradict the hypothesized pantropical increase in tree growth rates caused by carbon fertilization. Decelerating tree growth will have important economic and environmental implications.
    Matched MeSH terms: Tropical Climate*
  9. Patrick R, Dietrich U
    Ecohealth, 2016 12;13(4):808-812.
    PMID: 27650715
    In Oceania, a region challenged by rapid urbanisation and climate change, integrative frameworks are required to enable effective actions on health and sustainability. The Ecohealth approach provides a framework for practice that acknowledges human health is intrinsically linked to ecosystem health. This research communication reports on a study involving interviews with twenty-seven leading health and sustainability thinkers from Oceania and across the globe. In examining their ideas for action, the report presents the study findings in relation to the guiding principles of Ecohealth: systems thinking, transdisciplinarity, participation, sustainability, equity and knowledge-to-action. Implications for Ecohealth practitioners working in Oceania are considered.
    Matched MeSH terms: Climate Change*
  10. Ledo A, Cornulier T, Illian JB, Iida Y, Kassim AR, Burslem DF
    Ecol Appl, 2016 Dec;26(8):2374-2380.
    PMID: 27907254 DOI: 10.1002/eap.1450
    Accurate estimation of tree biomass is necessary to provide realistic values of the carbon stored in the terrestrial biosphere. A recognized source of errors in tree aboveground biomass (AGB) estimation is introduced when individual tree height values (H) are not directly measured but estimated from diameter at breast height (DBH) using allometric equations. In this paper, we evaluate the performance of 12 alternative DBH : H equations and compare their effects on AGB estimation for three tropical forests that occur in contrasting climatic and altitudinal zones. We found that fitting a three-parameter Weibull function using data collected locally generated the lowest errors and bias in H estimation, and that equations fitted to these data were more accurate than equations with parameters derived from the literature. For computing AGB, the introduced error values differed notably among DBH : H allometric equations, and in most cases showed a clear bias that resulted in either over- or under-estimation of AGB. Fitting the three-parameter Weibull function minimized errors in AGB estimates in our study and we recommend its widespread adoption for carbon stock estimation. We conclude that many previous studies are likely to present biased estimates of AGB due to the method of H estimation.
    Matched MeSH terms: Tropical Climate*
  11. Pereira, J.J., Hunt, J.C.R., Chan, J.C.L.
    ASM Science Journal, 2014;8(1):1-10.
    MyJurnal
    The role of science and technology (S&T) in preventing disasters and building resilience to climate change is featured in this paper, drawing primarily on the presentations and discussion of researchers, practitioners and policy makers from 31 institutions in 17 countries during the Workshop on Natural Disasters and Climate Change in Asia, held on 5–7 November 2012 in Bangi, Malaysia. Issues highlighted include advances in climate modelling and weather forecasts, with emphasis on information gaps; hazards and its cascading effects, focusing on current research and approaches; and the potential for land-based mitigation-adaptation strategies. Progress in mobilizing S&T to support disaster prevention and climate resilience is hindered by factors such as absence or lack of research, incomplete and non-existent scientific records, restricted access to data and capacity to innovate and transmit S&T, among others. The establishment of an Asian Network for Climate Science and Technology is proposed to provide and facilitate exchange of information and aid development of research co-ordination projects led by Asian researchers and possibly to act as a one-stop repository of global climate change related research too. The scope of the network would cover climate research with particular relevance to disaster resilience, including scientific capacity, which is all very distinct in Asia.
    Matched MeSH terms: Climate; Climate Change
  12. Supari, Tangang F, Juneng L, Cruz F, Chung JX, Ngai ST, et al.
    Environ Res, 2020 05;184:109350.
    PMID: 32179268 DOI: 10.1016/j.envres.2020.109350
    This study examines the projected precipitation extremes for the end of 21st century (2081-2100) over Southeast Asia (SEA) using the output of the Southeast Asia Regional Climate Downscaling/Coordinated Regional Climate Downscaling Experiment - Southeast Asia (SEACLID/CORDEX-SEA). Eight ensemble members, representing a subset of archived CORDEX-SEA simulations at 25 km spatial resolution, were examined for emission scenarios of RCP4.5 and RCP8.5. The study utilised four different indicators of rainfall extreme, i.e. the annual/seasonal rainfall total (PRCPTOT), consecutive dry days (CDD), frequency of extremely heavy rainfall (R50mm) and annual/seasonal maximum of daily rainfall (RX1day). In general, changes in extreme indices are more pronounced and covering wider area under RCP8.5 than RCP4.5. The decrease in annual PRCPTOT is projected over most of SEA region, except for Myanmar and Northern Thailand, with magnitude as much as 20% (30%) under RCP4.5 (RCP8.5) scenario. The most significant and robust changes were noted in CDD, which is projected to increase by as much as 30% under RCP4.5 and 60% under RCP8.5, particularly over Maritime Continent (MC). The projected decrease in PRCPTOT over MC is significant and robust during June to August (JJA) and September to November (SON). During March to May (MAM) under RCP8.5, significant and robust PRCPTOT decreases are also projected over Indochina. The CDD changes during JJA and SON over MC are even higher, more robust and significant compared to the annual changes. At the same time, a wetting tendency is also projected over Indochina. The R50mm and RX1day are projected to increase, during all seasons with significant and robust signal of RX1day during JJA and SON.
    Matched MeSH terms: Climate Change*
  13. Birkmann J, Jamshed A, McMillan JM, Feldmeyer D, Totin E, Solecki W, et al.
    Sci Total Environ, 2022 Jan 10;803:150065.
    PMID: 34525713 DOI: 10.1016/j.scitotenv.2021.150065
    Climate change is a severe global threat. Research on climate change and vulnerability to natural hazards has made significant progress over the last decades. Most of the research has been devoted to improving the quality of climate information and hazard data, including exposure to specific phenomena, such as flooding or sea-level rise. Less attention has been given to the assessment of vulnerability and embedded social, economic and historical conditions that foster vulnerability of societies. A number of global vulnerability assessments based on indicators have been developed over the past years. Yet an essential question remains how to validate those assessments at the global scale. This paper examines different options to validate global vulnerability assessments in terms of their internal and external validity, focusing on two global vulnerability indicator systems used in the WorldRiskIndex and the INFORM index. The paper reviews these global index systems as best practices and at the same time presents new analysis and global results that show linkages between the level of vulnerability and disaster outcomes. Both the review and new analysis support each other and help to communicate the validity and the uncertainty of vulnerability assessments. Next to statistical validation methods, we discuss the importance of the appropriate link between indicators, data and the indicandum. We found that mortality per hazard event from floods, drought and storms is 15 times higher for countries ranked as highly vulnerable compared to those classified as low vulnerable. These findings highlight the different starting points of countries in their move towards climate resilient development. Priority should be given not just to those regions that are likely to face more severe climate hazards in the future but also to those confronted with high vulnerability already.
    Matched MeSH terms: Climate Change*
  14. Alomar MK, Khaleel F, Aljumaily MM, Masood A, Razali SFM, AlSaadi MA, et al.
    PLoS One, 2022;17(11):e0277079.
    PMID: 36327280 DOI: 10.1371/journal.pone.0277079
    Atmospheric air temperature is the most crucial metrological parameter. Despite its influence on multiple fields such as hydrology, the environment, irrigation, and agriculture, this parameter describes climate change and global warming quite well. Thus, accurate and timely air temperature forecasting is essential because it provides more important information that can be relied on for future planning. In this study, four Data-Driven Approaches, Support Vector Regression (SVR), Regression Tree (RT), Quantile Regression Tree (QRT), ARIMA, Random Forest (RF), and Gradient Boosting Regression (GBR), have been applied to forecast short-, and mid-term air temperature (daily, and weekly) over North America under continental climatic conditions. The time-series data is relatively long (2000 to 2021), 70% of the data are used for model calibration (2000 to 2015), and the rest are used for validation. The autocorrelation and partial autocorrelation functions have been used to select the best input combination for the forecasting models. The quality of predicting models is evaluated using several statistical measures and graphical comparisons. For daily scale, the SVR has generated more accurate estimates than other models, Root Mean Square Error (RMSE = 3.592°C), Correlation Coefficient (R = 0.964), Mean Absolute Error (MAE = 2.745°C), and Thiels' U-statistics (U = 0.127). Besides, the study found that both RT and SVR performed very well in predicting weekly temperature. This study discovered that the duration of the employed data and its dispersion and volatility from month to month substantially influence the predictive models' efficacy. Furthermore, the second scenario is conducted using the randomization method to divide the data into training and testing phases. The study found the performance of the models in the second scenario to be much better than the first one, indicating that climate change affects the temperature pattern of the studied station. The findings offered technical support for generating high-resolution daily and weekly temperature forecasts using Data-Driven Methodologies.
    Matched MeSH terms: Climate Change*
  15. Russo SE, McMahon SM, Detto M, Ledder G, Wright SJ, Condit RS, et al.
    Nat Ecol Evol, 2021 Feb;5(2):174-183.
    PMID: 33199870 DOI: 10.1038/s41559-020-01340-9
    Resource allocation within trees is a zero-sum game. Unavoidable trade-offs dictate that allocation to growth-promoting functions curtails other functions, generating a gradient of investment in growth versus survival along which tree species align, known as the interspecific growth-mortality trade-off. This paradigm is widely accepted but not well established. Using demographic data for 1,111 tree species across ten tropical forests, we tested the generality of the growth-mortality trade-off and evaluated its underlying drivers using two species-specific parameters describing resource allocation strategies: tolerance of resource limitation and responsiveness of allocation to resource access. Globally, a canonical growth-mortality trade-off emerged, but the trade-off was strongly observed only in less disturbance-prone forests, which contained diverse resource allocation strategies. Only half of disturbance-prone forests, which lacked tolerant species, exhibited the trade-off. Supported by a theoretical model, our findings raise questions about whether the growth-mortality trade-off is a universally applicable organizing framework for understanding tropical forest community structure.
    Matched MeSH terms: Tropical Climate*
  16. Mogi M, Armbruster PA, Tuno N, Aranda C, Yong HS
    J Med Entomol, 2017 11 07;54(6):1615-1625.
    PMID: 28968769 DOI: 10.1093/jme/tjx156
    We compared climatic distribution ranges between Aedes albopictus (Skuse) (Diptera: Culicidae) and the five wild (nondomesticated) species of Albopictus Subgroup of Scutellaris Group of Aedes (Stegomyia) in southern Asia. Distribution sites of the wild species concentrate in seasonal forest and savannah climate zones in India, Indochina, and southern China. The distribution of Ae. albopictus is broader than the wild species under 1) tropical rain-forest climate, 2) steppe and temperate savannah climate, and 3) continental climate with large seasonal temperature variation (hot summer and cold winter) at temperate lowlands (northernmost sites 40°N in Ae. albopictus vs 32°N in the wild species). However, the distribution of Ae. albopictus is more limited at tropical and subtropical highlands where the climate is cool but less continental (small seasonal variation, mild summer, and winter). We discuss a possibility that the broader climate ranges of Ae. albopictus are ecological or eco-evolutionary consequences of adaptation to human habitats. We also propose a general scenario for the origin, dispersal, and adaptation of Ae. albopictus in Asia as a hypothesis for future research.
    Matched MeSH terms: Climate*
  17. Ahmat Zainuri N, Abd-Rahman N, Halim L, Chan MY, Mohd Bazari NN
    Int J Environ Res Public Health, 2022 Nov 30;19(23).
    PMID: 36498088 DOI: 10.3390/ijerph192316013
    Pro-environmental behavior in addressing climate change is influenced by multi-dimensional factors-knowledge, values, intention and sociodemographic background. Correlational studies between environmental values and environmental behaviors have not been able to determine values or behaviors that need to be given priority in future interventions. Therefore, this study firstly determined the environmental values and pro-environmental behavior that are easy or difficult to embrace by 152 respondents with low socioeconomic background. Secondly, we identified the extent pro-environmental behavior is triggered by environmental values. This survey study employs the Rasch analysis model. The respondents had difficulty in associating themselves with biospheric values however readily demonstrated consideration toward altruistic values, especially related to concerns for future generations. In terms of environmental conservation behavior, the respondents were not willing to relinquish comfort easily, such as giving up self-driving and taking public transportation or reducing usage of electricity. In addition, adults of low socioeconomic background find it difficult to endorse statements such as getting involved in campaigns related to environmental conservation. Thus, younger family members must be educated about conservation behaviors such as environmental campaigns commonly offered at schools, and these youngsters can be encouraged to extend their role by educating their parents.
    Matched MeSH terms: Climate Change*
  18. Yang S, Tan ML, Song Q, He J, Yao N, Li X, et al.
    J Environ Manage, 2023 Mar 15;330:117244.
    PMID: 36621311 DOI: 10.1016/j.jenvman.2023.117244
    Global climate change has led to an increase in both the frequency and magnitude of extreme events around the world, the risk of which is especially imminent in tropical regions. Developing hydrological models with better capabilities to simulate streamflow, especially peak flow, is urgently needed to facilitate water resource planning and management as well as climate change mitigation efforts in the tropics. In view of the need, this paper explores the feasibility of improving streamflow simulation performance in the tropical Kelantan River Basin (KRB) of Peninsular Malaysia through coupling a conceptual process-based hydrological model - Soil and Water Assessment Tool (SWAT) with a deep learning model - Bidirectional Long Short-Term Memory (Bi-LSTM) in two ways. All SWAT parameters were set as their default values in one hybrid model (SWAT-D-LSTM), whereas three most sensitive SWAT parameters were calibrated in the other hybrid model (SWAT-T-LSTM). Comparison of daily streamflow simulation results have shown that SWAT-T-LSTM consistently performs better than SWAT-D-LSTM as well as the stand-alone SWAT and Bi-LSTM model throughout the simulation period. Particularly, SWAT-T-LSTM performs considerably better than the other three models in simulating daily peak flow. Based on the latest projection results of five GCMs from the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6) under three emission scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5), the best-performed SWAT-T-LSTM was run to assess the potential impacts of climate change on streamflow in the KRB. Ensemble assessment results have concluded that both average and extreme streamflow is much likely to increase considerably in the already wet northeast monsoon season from November to January, which has surely raised the alarm for more frequent flood occurrence in the KRB.
    Matched MeSH terms: Climate Change*
  19. Allias Omar SM, Wan Ariffin WNH, Mohd Sidek L, Basri H, Moh Khambali MH, Ahmed AN
    Int J Environ Res Public Health, 2022 Dec 09;19(24).
    PMID: 36554413 DOI: 10.3390/ijerph192416530
    Extensive hydrological analysis is carried out to estimate floods for the Batu Dam, a hydropower dam located in the urban area upstream of Kuala Lumpur, Malaysia. The study demonstrates the operational state and reliability of the dam structure based on hydrologic assessment of the dam. The surrounding area is affected by heavy rainfall and climate change every year, which increases the probability of flooding and threatens a dense population downstream of the dam. This study evaluates the adequacy of dam spillways by considering the latest Probable Maximum Precipitation (PMP) and Probable Maximum Flood (PMF) values of the concerned dams. In this study, the PMP estimations are applied using comparison of both statistical method by Hershfield and National Hydraulic Research Institute of Malaysia (NAHRIM) Envelope Curve as input for PMF establishments. Since the PMF is derived from the PMP values, the highest design flood standard can be applied to any dam, ensuring inflow into the reservoirs and limiting the risk of dam structural failure. Hydrologic modeling using HEC-HMS provides PMF values for the Batu dam. Based on the results, Batu Dam is found to have 200.6 m3/s spillway discharge capacities. Under PMF conditions, the Batu dam will not face overtopping since the peak outflow of the reservoir level is still below the crest level of the dam.
    Matched MeSH terms: Climate Change*
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