Assessing the significance of climate and community factors on urban water demand

Ensuring adequate water supply to urban areas is a challenging task due to factors such as rapid urban growth, increasing water demand and climate change. In developing a sustainable water supply system, it is important to identify the dominant water demand factors for any given water supply scheme. This paper applies principal components analysis to identify the factors that dominate residential water demand using the Blue Mountains Water Supply System in Australia as a case study. The results show that the influence of community intervention factors (e.g. use of water efficient appliances and rainwater tanks) on water demand are among the most significant. The result also confirmed that the community intervention programmes and water pricing policy together can play a noticeable role in reducing the overall water demand. On the other hand, the influence of rainfall on water demand is found to be very limited, while temperature shows some degree of correlation with water demand. The results of this study would help water authorities to plan for effective water demand management strategies and to develop a water demand forecasting model with appropriate climatic factors to achieve sustainable water resources management. The methodology developed in this paper can be adapted to other water supply systems to identify the influential factors in water demand modelling and to devise an effective demand management strategy.

Toxigenic molds on fish feeds-1: impact of climatic change

The present communication is a survey report carried out to assess the incidence of toxic mycoflora on seven types of agriculture products/by products incorporated during fish culture as supplementary dietary items. Samples were obtained from various sources at Darbhanga, Madhubani and Samashtipur districts during summer, winter and monsoon months. Out of the total 1774 samples, only 894 appeared to be fresh visually reflecting average incidence of contamination around 46.6%. However, the apparently fresh samples, when subjected to culture, 26.9% of them were found to be contaminated. Thus, degree of fungal spoilage in feed ingredients in parts of north Bihar appears to be significantly high (73.5%). The present study illustrates the facts with special reference to Aspergillus flavus, A. parasiticus (elaborating aflatoxins) A. ochraceous, Penicilium viradicatuin (elaborating ochratoxins) and A. versicolor (elaborating sterigmatocystin). The other strains already known for their toxigenic potentials that appeared on the present substrates included A. niger, A. fumigatus, A. candidus, P. islandicum, Rhizopus spp. and Mucur spp. Studies indicate that the prevalent climatic factors like temperature and relative humidity facilitate a congenial condition almost all through the year and in particular during summer and monsoon months. But water content of the substrates is a vital factor that further accelerates the pace of mycobial spoilage. A thorough sun-drying of the agricultural commodities before prolonged storage to bring water content below the "low risk limit" may significantly reduce the incidence of molds.

Climatic drivers of hourly to yearly tree radius variations along a 6°C natural warming gradient

Climate affects the timing, rate and dynamics of tree growth, over time scales ranging from seconds to centuries. Monitoring how a tree's stem radius varies over these time scales can provide insight into intra-annual stem dynamics and improve our understanding of climate impacts on tree physiology and growth processes. Here, we quantify the response of radial conifer stem size to environmental fluctuations via a novel assessment of tree circadian cycles. We analyze four years of sub-hourly data collected from 56 larch and spruce trees growing along a natural temperature gradient of ∼6 °C in the central Swiss Alps. During the growing season, tree stem diameters were greatest at mid-morning and smallest in the late evening, reflecting the daily cycle of water uptake and loss. Along the gradient, amplitudes calculated from the stem radius cycle were ∼50% smaller at the upper site (∼2200 m a.s.l.) relative to the lower site (∼800 m a.s.l.). We show changes in precipitation, temperature and cloud cover have a substantial effect on typical growing season diurnal cycles; amplitudes were nine times smaller on rainy days (>10 mm), and daily amplitudes are approximately 40% larger when the mean daily temperature is 15–20 °C than when it is 5–10 °C. We find that over the growing season in the sub-alpine forests, spruce show greater daily stem water movement than larch. However, under projected future warming, larch could experience up to 50% greater stem water use, which may severely affect future growth on already dry sites. Our data further indicate that because of the confounding influences of radial growth and short-term water dynamics on stem size, conventional methodology probably overstates the effect of water-linked meteorological variables (i.e. precipitation and relative humidity) on intra-annual tree growth. We suggest future studies use intra-seasonal measurements of cell development and consider whether climatic factors produce reversible changes in stem diameter. These study design elements may help researchers more accurately quantify and attribute changes in forest productivity in response to future warming.

How do various maize crop models vary in their responses to climate change factors?

Comments This article is a U.S. government work, and is not subject to copyright in the United States. Abstract Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly 0.5 Mg ha 1 per °C. Doubling [CO2] from 360 to 720 lmol mol 1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.

Factors determining lobe growth in foliose lichen thalli

This study investigates the relative importance of climate, lobe morphology and lobe interactions in determining the radial growth of individual lobes in foliose lichen thalli. The radial growth of 75 lobes from thalli of Parmelia conspersa (Ehrh. Ex Ach.) Ach. and Parmelia glabratula ssp. fuliginosa (Fr. ex Duby) Laund. was measured over 22 successive months in relation to climatic factors. Individual lobes showed a fluctuating pattern of radial growth with alternating periods of fast and slow growth. In 17/75 (23%) of lobes studied, monthly radial growth was correlated with a climatic factor, usually total rainfall or the frequency of sunshine hours. In addition, the radial growth of 54 lobes of P. conspersa was measured over four months in relation to lobe morphology and the radial growth and morphology of adjacent lobes. Radial growth was correlated with lobe length and with the radial growth of adjacent lobes. In addition, the pattern of lobe branching appeared to be related to lobe width and to a lesser extent to lobe length and the width of adjacent lobes. The radial growth in one year of exceptionally long lobes which had grown beyond the thallus margin was similar to more normal lobes, but experimentally bisected lobes had significantly reduced radial growth compared with control lobes. These results suggested that the fluctuating pattern of radial growth in individual lobes may be determined by climate and the pattern of lobe branching. In addition, the pattern of lobe branching was related to lobe width and may be influenced by adjacent lobes.

An analysis and comparison of rural land sales

Rural land prices, in developed, free trade real estate markets, are influenced not only by prevailing economic conditions but also physical factors such as climate, topography and soil type. In broad acre farming and grazing operations, both commodity price and yields determine farm income. Yields, in turn, are a function of climate, topography and soil type. The strength of a rural land market is influenced by the overall rural economy in a Country, State or region. These differences in rural land markets can also vary within smaller regions. It has been held that rural land, in relative safe production areas, is less effected by adverse economic and climatic factors than land in more marginal agricultural areas. This paper will analyse rural land sales in both traditional cropping areas and marginal cropping areas for the period 1975 to 1996. The analysis will determine the overall trend in rural land prices over the period, compare the average annual return between marginal and established farming areas and determine which economic and production factors have influenced this change. The impact of this analysis will also be discussed in relation to rural land appraisal.

Regional contingencies in the relationship between aboveground biomass and litter in the world’s grasslands

Based on regional-scale studies, aboveground production and litter decomposition are thought to positively covary, because they are driven by shared biotic and climatic factors. Until now we have been unable to test whether production and decomposition are generally coupled across climatically dissimilar regions, because we lacked replicated data collected within a single vegetation type across multiple regions, obfuscating the drivers and generality of the association between production and decomposition. Furthermore, our understanding of the relationships between production and decomposition rests heavily on separate meta-analyses of each response, because no studies have simultaneously measured production and the accumulation or decomposition of litter using consistent methods at globally relevant scales. Here, we use a multi-country grassland dataset collected using a standardized protocol to show that live plant biomass (an estimate of aboveground net primary production) and litter disappearance (represented by mass loss of aboveground litter) do not strongly covary. Live biomass and litter disappearance varied at different spatial scales. There was substantial variation in live biomass among continents, sites and plots whereas among continent differences accounted for most of the variation in litter disappearance rates. Although there were strong associations among aboveground biomass, litter disappearance and climatic factors in some regions (e.g. U.S. Great Plains), these relationships were inconsistent within and among the regions represented by this study. These results highlight the importance of replication among regions and continents when characterizing the correlations between ecosystem processes and interpreting their global-scale implications for carbon flux. We must exercise caution in parameterizing litter decomposition and aboveground production in future regional and global carbon models as their relationship is complex.

Predicting invasion in grassland ecosystems: is exotic dominance the real embarrassment of richness?

Invasions have increased the size of regional species pools, but are typically assumed to reduce native diversity. However, global-scale tests of this assumption have been elusive because of the focus on exotic species richness, rather than relative abundance. This is problematic because low invader richness can indicate invasion resistance by the native community or, alternatively, dominance by a single exotic species. Here, we used a globally replicated study to quantify relationships between exotic richness and abundance in grass-dominated ecosystems in 13 countries on six continents, ranging from salt marshes to alpine tundra. We tested effects of human land use, native community diversity, herbivore pressure, and nutrient limitation on exotic plant dominance. Despite its widespread use, exotic richness was a poor proxy for exotic dominance at low exotic richness, because sites that contained few exotic species ranged from relatively pristine (low exotic richness and cover) to almost completely exotic-dominated ones (low exotic richness but high exotic cover). Both exotic cover and richness were predicted by native plant diversity (native grass richness) and land use (distance to cultivation). Although climate was important for predicting both exotic cover and richness, climatic factors predicting cover (precipitation variability) differed from those predicting richness (maximum temperature and mean temperature in the wettest quarter). Herbivory and nutrient limitation did not predict exotic richness or cover. Exotic dominance was greatest in areas with low native grass richness at the site- or regional-scale. Although this could reflect native grass displacement, a lack of biotic resistance is a more likely explanation, given that grasses comprise the most aggressive invaders. These findings underscore the need to move beyond richness as a surrogate for the extent of invasion, because this metric confounds monodominance with invasion resistance. Monitoring species' relative abundance will more rapidly advance our understanding of invasions.

Impact of climate variability on Plasmodium vivax and Plasmodium falciparum malaria in Yunnan Province, China

BACKGROUND Malaria remains a public health problem in the remote and poor area of Yunnan Province, China. Yunnan faces an increasing risk of imported malaria infections from Mekong river neighboring countries. This study aimed to identify the high risk area of malaria transmission in Yunnan Province, and to estimate the effects of climatic variability on the transmission of Plasmodium vivax and Plasmodium falciparum in the identified area. METHODS We identified spatial clusters of malaria cases using spatial cluster analysis at a county level in Yunnan Province, 2005-2010, and estimated the weekly effects of climatic factors on P. vivax and P. falciparum based on a dataset of daily malaria cases and climatic variables. A distributed lag nonlinear model was used to estimate the impact of temperature, relative humidity and rainfall up to 10-week lags on both types of malaria parasite after adjusting for seasonal and long-term effects. RESULTS The primary cluster area was identified along the China-Myanmar border in western Yunnan. A 1°C increase in minimum temperature was associated with a lag 4 to 9 weeks relative risk (RR), with the highest effect at lag 7 weeks for P. vivax (RR = 1.03; 95% CI, 1.01, 1.05) and 6 weeks for P. falciparum (RR = 1.07; 95% CI, 1.04, 1.11); a 10-mm increment in rainfall was associated with RRs of lags 2-4 weeks and 9-10 weeks, with the highest effect at 3 weeks for both P. vivax (RR = 1.03; 95% CI, 1.01, 1.04) and P. falciparum (RR = 1.04; 95% CI, 1.01, 1.06); and the RRs with a 10% rise in relative humidity were significant from lag 3 to 8 weeks with the highest RR of 1.24 (95% CI, 1.10, 1.41) for P. vivax at 5-week lag. CONCLUSIONS Our findings suggest that the China-Myanmar border is a high risk area for malaria transmission. Climatic factors appeared to be among major determinants of malaria transmission in this area. The estimated lag effects for the association between temperature and malaria are consistent with the life cycles of both mosquito vector and malaria parasite. These findings will be useful for malaria surveillance-response systems in the Mekong river region.

Projecting future transmission of malaria under climate change scenarios : challenges and research needs

There has been an intense debate about climatic impacts on the transmission of malaria. It is vitally important to accurately project future impacts of climate change on malaria to support effective policy–making and intervention activity concerning malaria control and prevention. This paper critically reviewed the published literature and examined both key findings and methodological issues in projecting future impacts of climate change on malaria transmission. A literature search was conducted using the electronic databases MEDLINE, Web of Science and PubMed. The projected impacts of climate change on malaria transmission were spatially heterogeneous and somewhat inconsistent. The variation in results may be explained by the interaction of climatic factors and malaria transmission cycles, variations in projection frameworks and uncertainties of future socioecological (including climate) changes. Current knowledge gaps are identified, future research directions are proposed and public health implications are assessed. Improving the understanding of the dynamic effects of climate on malaria transmission cycles, the advancement of modelling techniques and the incorporation of uncertainties in future socioecological changes are critical factors for projecting the impact of climate change on malaria transmission.

A continent-wide study reveals clear relationships between regional abiotic conditions and post-dispersal seed predation

Aim Large-scale patterns linking energy availability, biological productivity and diversity form a central focus of ecology. Despite evidence that the activity and abundance of animals may be limited by climatic variables associated with regional biological productivity (e.g. mean annual precipitation and annual actual evapotranspiration), it is unclear whether plant–granivore interactions are themselves influenced by these climatic factors across broad spatial extents. We evaluated whether climatic conditions that are known to alter the abundance and activity of granivorous animals also affect rates of seed removal. Location Eleven sites across temperate North America. Methods We used a common protocol to assess the removal of the same seed species (Avena sativa) over a 2-day period. Model selection via the Akaike information criterion was used to determine a set of candidate binomial generalized linear mixed models that evaluated the relationship between local climatic data and post-dispersal seed predation. Results Annual actual evapotranspiration was the single best predictor of the proportion of seeds removed. Annual actual evapotranspiration and mean annual precipitation were both positively related to mean seed removal and were included in four and three of the top five models, respectively. Annual temperature range was also positively related to seed removal and was an explanatory variable in three of the top four models. Main conclusions Our work provides the first evidence that energy and precipitation, which are known to affect consumer abundance and activity, also translate to strong, predictable patterns of seed predation across a continent. More generally, these findings suggest that future changes in temperature and precipitation could have widespread consequences for plant species composition in grasslands, through impacts on plant recruitment.

Exploration of diarrhoea seasonality and its drivers in China

This study investigated the diarrhoea seasonality and its potential drivers as well as potential opportunities for future diarrhoea control and prevention in China. Data on weekly infectious diarrhoea cases in 31 provinces of China from 2005 to 2012, and data on demographic and geographic characteristics, as well as climatic factors, were complied. A cosinor function combined with a Poisson regression was used to calculate the three seasonal parameters of diarrhoea in different provinces. Regression tree analysis was used to identify the predictors of diarrhoea seasonality. Diarrhoea cases in China showed a bimodal distribution. Diarrhoea in children <5 years was more likely to peak in fall-winter seasons, while diarrhoea in persons > = 5 years peaked in summer. Latitude was significantly associated with spatial pattern of diarrhoea seasonality, with peak and trough times occurring earlier at high latitudes (northern areas), and later at low latitudes (southern areas). The annual amplitudes of diarrhoea in persons > = 5 years increased with latitude (r = 0.62, P<0.001). Latitude 27.8° N and 38.65° N were the latitudinal thresholds for diarrhoea seasonality in China. Regional-specific diarrhoea control and prevention strategies may be optimal for China. More attention should be paid to diarrhoea in children <5 years during fall-winter seasons.

Spatiotemporal pattern of bacillary dysentery in China from 1990 to 2009: What is the driver behind?

BACKGROUND Little is known about the spatiotemporal pattern of bacillary dysentery (BD) in China. This study assessed the geographic distribution and seasonality of BD in China over the past two decades. METHODS Data on monthly BD cases in 31 provinces of China from January 1990 to December 2009 obtained from Chinese Center for Disease Control and Prevention, and data on demographic and geographic factors, as well as climatic factors, were compiled. The spatial distributions of BD in the four periods across different provinces were mapped, and heat maps were created to present the seasonality of BD by geography. A cosinor function combined with Poisson regression was used to quantify the seasonal parameters of BD, and a regression analysis was conducted to identify the potential drivers of morbidity and seasonality of BD. RESULTS Although most regions of China have experienced considerable declines in BD morbidity over the past two decades, Beijing and Ningxia still had high BD morbidity in 2009. BD morbidity decreased more slowly in North-west China than other regions. BD in China mainly peaked from July to September, with heterogeneity in peak time between regions. Relative humidity was associated with BD morbidity and peak time, and latitude was the major predictor of BD amplitude. CONCLUSIONS The transmission of BD was heterogeneous in China. Improved sanitation and hygiene in North-west China, and better access to clean water and food in the big floating population in some metropolises could be the focus of future preventive interventions against BD. BD control efforts should put more emphasis on those dry areas in summer.

Do motor vehicle crashes arise from single or multiple unique risk processes? An inquiry into crash causes and modelling

Crashes at any particular transport network location consist of a chain of events arising from a multitude of potential causes and/or contributing factors whose nature is likely to reflect geometric characteristics of the road, spatial effects of the surrounding environment, and human behavioural factors. It is postulated that these potential contributing factors do not arise from the same underlying risk process, and thus should be explicitly modelled and understood. The state of the practice in road safety network management applies a safety performance function that represents a single risk process to explain crash variability across network sites. This study aims to elucidate the importance of differentiating among various underlying risk processes contributing to the observed crash count at any particular network location. To demonstrate the principle of this theoretical and corresponding methodological approach, the study explores engineering (e.g. segment length, speed limit) and unobserved spatial factors (e.g. climatic factors, presence of schools) as two explicit sources of crash contributing factors. A Bayesian Latent Class (BLC) analysis is used to explore these two sources and to incorporate prior information about their contribution to crash occurrence. The methodology is applied to the state controlled roads in Queensland, Australia and the results are compared with the traditional Negative Binomial (NB) model. A comparison of goodness of fit measures indicates that the model with a double risk process outperforms the single risk process NB model, and thus indicating the need for further research to capture all the three crash generation processes into the SPFs.

A lesson from cyclone Larry: An untold story of the success of good coastal planning

When tropical cyclone Larry crossed the Queensland coast on 20 March 2006, commercial, recreational and naval vessels in the port of Cairns, 60 km north of the eye of the cyclone and others closer to the eye, were protected from the destructive winds by sheltering in deep mangrove creeks in Trinity Inlet and off other coastal rivers. The Trinity Inlet mangroves are protected under the comprehensive multi-use Trinity Inlet Management Plan, agreed by the local and state government agencies (Cairns City Council, the Cairns Port Authority and the Queensland Government). Using this Australian example and one from the town of Palompon in Leyte province, central Philippines, we show how long-term mangrove habitat protection resulting from well-conceived coastal planning can deliver important economic and infrastructure benefits.