Seasonal Rainfall Patterns Research Articles

Using Mathematical Transmission Modelling to Investigate Drivers of Respiratory Syncytial Virus Seasonality in Children in the Philippines

We used a mathematical transmission model to estimate when ecological drivers of respiratory syncytial virus (RSV) transmissibility would need to act in order to produce the observed seasonality of RSV in the Philippines. We estimated that a seasonal peak in transmissibility would need to occur approximately 51 days prior to the observed peak in RSV cases (range 49 to 67 days). We then compared this estimated seasonal pattern of transmissibility to the seasonal patterns of possible ecological drivers of transmissibility: rainfall, humidity and temperature patterns, nutritional status, and school holidays. The timing of the seasonal patterns of nutritional status and rainfall were both consistent with the estimated seasonal pattern of transmissibility and these are both plausible drivers of the seasonality of RSV in this setting.

Seasonal patterns of rainfall and river isotopic chemistry in northern Amazonia (Guyana): From the headwater to the regional scale

We use first field-based observations of precipitation and river isotopic chemistry from a three-year study (2009–2011) in rainforest and nearby savannah in central Guyana at the northern rim of the Amazon rainforest to establish the quality of modelled or remotely-sensed datasets. Our 3 years of data capture a reduced rainfall regime in 2009 and an extended wet season in 2010, in contrast to the widely documented Amazonian floods in 2009 and droughts in 2010. Comparisons of observed precipitation with satellite derived TRMM and ECMWF ERA-Interim reanalysis precipitation show that both of these data sets capture the general pattern of seasonality, but substantially underestimate rainfall amounts in the primary wet season (by up to 50% and 72% respectively). The TRMM dataset is generally better at characterising the main dry season from September to December but the ERA-Interim model can overestimate precipitation in the dry season by up to 175%. Our new data on isotopic chemistry of river waters show that δ2H/δ18O values in this region are broadly consistent with interpolated global datasets of modelled precipitation isotopic signatures. The dominance of isotopically lighter water derived from the rains of the ITCZ during the wet season provides evidence of the close coupling of water chemistry of headwater rivers on the northern rim of Amazonia to the positioning of the ITCZ over the region. Our results highlight the challenge in understanding and representing local scale hydrological and biogeochemical characteristics using regional scale model data. We argue that combining point and local scale field data with larger scale model data is necessary to progress towards a comprehensive understanding of climate–hydrology interactions in Amazonia.

Metabolic acceleration quantifies biological systems' ability to up-regulate metabolism in response to episodic resource availability

Precipitation often arrives discretely in semi-arid ecosystems. Under these conditions, natural selection might favor rapid metabolic responses to the sudden availability of otherwise limiting resources. We introduce and define metabolic acceleration (α) as the first derivative of the metabolic rate of a living system with respect to time. As such, α describes the capacity of a biological system to up- and down-regulate metabolism and may be applied across scales and processes. To better understand the responses of roots and soil microbes to seasonal patterns of rainfall and plant activity, we compared soil respiratory acceleration (αsoil) derived from soil respiration time-series among three microhabitats (under mesquite, under bunchgrasses, and in intercanopy soils) in a semi-arid shrubland near Tucson, Arizona. Across microhabitats, αsoil was greatest during the warm, wet summer months and lowest during cool winter months. Throughout the year, αsoil beneath mesquite was greater than beneath bunchgrasses or in intercanopy soils. Finally, microhabitat-specific responses of αsoil to spring and monsoonal rainfall events were consistent with seasonal contrasts in the photosynthetic activity of deeply-rooted mesquite shrubs and warm-season bunchgrasses. By quantifying the capacity of living systems to respond to episodic resource availability, metabolic acceleration provides a new perspective and potentially unifying metric for biological responses to environmental heterogeneity.

Influence of rice straw mulching on seed yield and nitrogen use efficiency of winter oilseed rape (Brassica napus L.) in intensive rice–oilseed rape cropping system

In intensive rice–winter oilseed rape (Brassica napus L.) cropping system in China, winter oilseed rape is often planted beyond the optimum period due to late harvest of rice. Under such condition, growth of rape seedlings is adversely affected due to low temperature and seasonal drought in winter, which causes a low rapeseed yield. Considering the enormous amounts of rice straw produced in this intensive cropping system, rice straw mulching in winter oilseed rape season may be a potential practice to adjust soil micro-climate, thereby improve productivity of winter oilseed rape. A two-year field study (2010–2011 and 2011–2012) was conducted to evaluate the effect of rice straw mulching and nitrogen (N) fertilization on (i) soil water, soil temperature and yield of winter oilseed rape and, (ii) N uptake, ammonia volatilization and soil inorganic N status in rice–winter oilseed rape cropping system. In general, straw mulching improved the dry matter accumulation and N uptake of winter oilseed rape over the growing period regardless of N fertilizer application or not, which might be attributed to the higher soil water content and the lower soil temperature oscillation under straw mulching compared to no mulching. Nevertheless, the relative magnitude of the increase in dry matter accumulation and N uptake of winter oilseed rape between the mulched and un-mulched treatments reduced with progressive increase in crop growth after seedling stage. Straw mulching resulted in more N loss through ammonia volatilization from top dressed fertilizer N and a significantly lower soil inorganic N content after seedling stage, which might be an important factor that was responsible for decreased positive effects of straw mulching on oilseed rape growth and N uptake after seedling stage under the condition of N fertilization. The positive effects of straw mulching on oilseed rape yield were influenced by the amount and distribution pattern of seasonal rainfall, with a significant increase in 2010–2011 only. In summary, these results suggest that rice straw mulching has the potential to enhance the productivity of winter oilseed rape, even though some changes in method of topdressing fertilizer N may be needed to avoid negative effects of straw mulching.

Temporal dynamics of arthropods on six tree species in dry woodlands on the Caribbean Island of Puerto Rico.

The seasonal dynamics of foliage arthropod populations are poorly studied in tropical dry forests despite the importance of these studies for understanding arthropod population responses to environmental change. We monitored the abundance, temporal distributions, and body size of arthropods in five naturalized alien and one native tree species to characterize arthropod seasonality in dry novel Prosopis–Leucaena woodlands in Puerto Rico. A branch clipping method was used monthly to sample foliage arthropod abundance over 39 mo. Seasonal patterns of rainfall and abundance within various arthropod taxa were highly variable from year to year. Abundance for most taxa did not show significant seasonality over the 3 yr, although most taxa had abundance peaks each year. However, Homoptera displayed high seasonality with significant temporal aggregations in each year. Formicidae, Orthoptera, and Coleoptera showed high variation in abundance between wet and dry periods, whereas Hemiptera were consistently more abundant in the wet period. Seasonal differences in mean abundance were found only in a few taxa on Tamarindus indica L. , Bucida buceras L. , Pithecellobium dulce , and (Roxburgh) Benth. Mean arthropod abundance varied among tree species, with highest numbers on Prosopis juliflora , (Swartz) De Candolle, Pi. dulce , Leucaena leucocephala , and (Lamarck) de Wit. Abundance of Araneae, Orthoptera, Coleoptera, Lepidoptera larvae, and all arthropods showed weak relationships with one or more climatic variables (rainfall, maximum temperature, or relative humidity). Body size of arthropods was usually largest during the dry periods. Overall, total foliage arthropod abundance showed no consistent seasonality among years, which may become a more common trend in dry forests and woodlands in the Caribbean if seasonality of rainfall becomes less predictable.

Estimation of design floods in ungauged catchments using a regional index flood method. A case study of Lake Victoria Basin in Kenya

Reliable estimation of flood magnitudes corresponding to required return periods, vital for structural design purposes, is impacted by lack of hydrological data in the study area of Lake Victoria Basin in Kenya. Use of regional information, derived from data at gauged sites and regionalized for use at any location within a homogenous region, would improve the reliability of the design flood estimation. Therefore, the regional index flood method has been applied. Based on data from 14 gauged sites, a delineation of the basin into two homogenous regions was achieved using elevation variation (90-m DEM), spatial annual rainfall pattern and Principal Component Analysis of seasonal rainfall patterns (from 94 rainfall stations). At site annual maximum series were modelled using the Log normal (LN) (3P), Log Logistic Distribution (LLG), Generalized Extreme Value (GEV) and Log Pearson Type 3 (LP3) distributions. The parameters of the distributions were estimated using the method of probability weighted moments. Goodness of fit tests were applied and the GEV was identified as the most appropriate model for each site. Based on the GEV model, flood quantiles were estimated and regional frequency curves derived from the averaged at site growth curves. Using the least squares regression method, relationships were developed between the index flood, which is defined as the Mean Annual Flood (MAF) and catchment characteristics. The relationships indicated area, mean annual rainfall and altitude were the three significant variables that greatly influence the index flood. Thereafter, estimates of flood magnitudes in ungauged catchments within a homogenous region were estimated from the derived equations for index flood and quantiles from the regional curves. These estimates will improve flood risk estimation and to support water management and engineering decisions and actions.

Assessing daily and seasonal satellite rainfall estimates using local gauges for the anomalous 2012 monsoon season in the African East Sahel

Satellite rainfall estimates (SRFEs) are essential for characterizing the seasonal delivery of monsoon rainfall to sub-Saharan Africa. Such data are particularly robust when composited over sufficiently large areas of the Earth's surface (≥2500 km2), and sufficiently long time periods (≥1 month). However, the application of SRFEs to early warning flash-flood and drought-monitoring systems at the hamlet level is less well documented, particularly for areas dominated by intense, small-scale convective storms, which require a higher spatial and temporal resolution than usually expected from standard SRFE products. This report assesses the potential of one of the primary contenders for such applications – the Climate Prediction Center (CPC) Rainfall Estimation Algorithm Version 2.0 (or RFE2) product – posing the specific challenge: How well does the RFE2 product perform on a site-by-site, storm-by-storm basis as a potential tool for early warning flood and drought applications in the East Sahel? Daily gridded (0.1° × 0.1°) RFE2 estimates are compared with daily time series from nine gauges provided by local agencies in the state of Gedaref, Sudan (area of gauge coverage ≈ 160 km × 160 km). Seasonal composites of multiple gauges and multiple RFE2 cells for 2012 (1 April to 31 October) agree quite well. However, daily time series of individual pairs of gauge data and corresponding RFE2 estimates show a remarkable lack of temporal coherence − typically only 10−20% of the daily variance of the RFE2 time series is associated with the gauge data. Moreover, low-pass filtered (30 day cut-off), smoothed versions of the daily RFE2 data do not conform well to the corresponding gauge distributions over the season, and fail to capture a seasonal bimodal rainfall pattern recorded by a cluster of rain gauges. Finally, there is a characteristic difference in the intensity-versus-frequency statistics of RFE2-produced events compared with corresponding gauge observations: RFE2 estimates imply that rain should have occurred on 70% of the days, whereby gauges recorded rainfall on only 35% of the days. On the other hand, extreme storms recorded by the gauge data are typically twice as strong as those estimated by the RFE2 algorithm. These results circumscribe specific limits on the RFE2 product for the purpose of site-by-site, storm-by-storm early warning monitoring of rainfall events, and for resolving details on the intra-seasonal modulation of rainfall patterns.

Plasmodium vivax malaria incidence over time and its association with temperature and rainfall in four counties of Yunnan Province, China.

BackgroundTransmission of Plasmodium vivax malaria is dependent on vector availability, biting rates and parasite development. In turn, each of these is influenced by climatic conditions. Correlations have previously been detected between seasonal rainfall, temperature and malaria incidence patterns in various settings. An understanding of seasonal patterns of malaria, and their weather drivers, can provide vital information for control and elimination activities. This research aimed to describe temporal patterns in malaria, rainfall and temperature, and to examine the relationships between these variables within four counties of Yunnan Province, China.MethodsPlasmodium vivax malaria surveillance data (1991–2006), and average monthly temperature and rainfall were acquired. Seasonal trend decomposition was used to examine secular trends and seasonal patterns in malaria. Distributed lag non-linear models were used to estimate the weather drivers of malaria seasonality, including the lag periods between weather conditions and malaria incidence.ResultsThere was a declining trend in malaria incidence in all four counties. Increasing temperature resulted in increased malaria risk in all four areas and increasing rainfall resulted in increased malaria risk in one area and decreased malaria risk in one area. The lag times for these associations varied between areas.ConclusionsThe differences detected between the four counties highlight the need for local understanding of seasonal patterns of malaria and its climatic drivers.

Complex behaviour in a dengue model with a seasonally varying vector population

In recent decades, dengue fever and dengue haemorrhagic fever have become a substantial public health concern in many subtropical and tropical countries throughout the world. Many of these regions have strong seasonal patterns in rainfall and temperature which are directly linked to the transmission of dengue through the mosquito vector population. Our study focuses on the development and analysis of a strongly seasonally forced, multi-subclass dengue model. This model is a compartment-based system of first-order ordinary differential equations with seasonal forcing in the vector population and also includes host population demographics. Our analysis of this model focuses particularly on the existence of deterministic chaos in regions of the parameter space which potentially hinders application of the model to predict and understand future outbreaks. The numerically efficient 0–1 test for deterministic chaos suggested by Gottwald and Melbourne (2004) [18] is used to analyze the long-term behaviour of the model as an alternative to Lyapunov exponents. Various solutions types were found to exist within the studied parameter range. Most notable are the existence of isola n-cycle solutions before the onset of deterministic chaos. Analysis of the seasonal model with the 0–1 test revealed the existence of three disconnected regions in parameter space where deterministic chaos exists in the single subclass model. Knowledge of these regions and how they relate to the parameters of the model gives greater confidence in the predictive power of the seasonal model.

Environmental controls of temporal and spatial variability in CO2 and CH4 fluxes in a neotropical peatland

Tropical peatlands play an important role in the global storage and cycling of carbon (C) but information on carbon dioxide (CO2) and methane (CH4) fluxes from these systems is sparse, particularly in the Neotropics. We quantified short and long-term temporal and small scale spatial variation in CO2 and CH4 fluxes from three contrasting vegetation communities in a domed ombrotrophic peatland in Panama. There was significant variation in CO2 fluxes among vegetation communities in the order Campnosperma panamensis > Raphia taedigera > Cyperus. There was no consistent variation among sites and no discernible seasonal pattern of CH4 flux despite the considerable range of values recorded (e.g. -1.0 to 12.6 mg m(-2) h(-1) in 2007). CO2 fluxes varied seasonally in 2007, being greatest in drier periods (300-400 mg m(-2) h(-1)) and lowest during the wet period (60-132 mg m(-2) h(-1)) while very high emissions were found during the 2009 wet period, suggesting that peak CO2 fluxes may occur following both low and high rainfall. In contrast, only weak relationships between CH4 flux and rainfall (positive at the C. panamensis site) and solar radiation (negative at the C. panamensis and Cyperus sites) was found. CO2 fluxes showed a diurnal pattern across sites and at the Cyperus sp. site CO2 and CH4 fluxes were positively correlated. The amount of dissolved carbon and nutrients were strong predictors of small scale within-site variability in gas release but the effect was site-specific. We conclude that (i) temporal variability in CO2 was greater than variation among vegetation communities; (ii) rainfall may be a good predictor of CO2 emissions from tropical peatlands but temporal variation in CH4 does not follow seasonal rainfall patterns; and (iii) diurnal variation in CO2 fluxes across different vegetation communities can be described by a Fourier model.

The sensitivity of wood production to seasonal and interannual variations in climate in a lowland Amazonian rainforest

Understanding climatic controls on tropical forest productivity is key to developing more reliable models for predicting how tropical biomes may respond to climate change. Currently there is no consensus on which factors control seasonal changes in tropical forest tree growth. This study reports the first comprehensive plot-level description of the seasonality of growth in a Peruvian tropical forest. We test whether seasonal and interannual variations in climate are correlated with changes in biomass increment, and whether such relationships differ among trees with different functional traits. We found that biomass increments, measured every 3 months on the two plots, were reduced by between 40 and 55% in the peak dry season (July-September) relative to peak wet season (January-March). The seasonal patterns of biomass accumulation are significantly (p < 0.01) associated with seasonal patterns of rainfall and soil water content; however, this may reflect a synchrony of seasonal cycles rather than direct physiological controls on tree growth rates. The strength of the growth seasonality response among trees is significantly correlated to functional traits: consistent with a hypothesised trade-off between maximum potential growth rate and hydraulic safety, tall and fast-growing trees with broad stems had the most strongly seasonal biomass accumulation, suggesting that they are more productive in the wet season, but more vulnerable to water limitation in the dry season.

Seasonal variability of rainfall recorded in growth bands of the Giant African Land Snail Lissachatina fulica (Bowdich) from India

Seasonal rainfall patterns in Bangalore, India, have been reconstructed using stable isotopic ratios in the growth bands of Giant African Land Snail shells. The present study was conducted at Bangalore, India which receives rain during the summer months. The oxygen isotopic record in the rainwater samples collected during different months covering the period of the summer monsoon of the year 2008 is compared with the isotopic ratio in the gastropod growth bands deposited simultaneously. The chronology of the shell growth band is independently established assuming the growth rate observed in a chamber experiment maintaining similar relative humidity and temperature conditions. A consistent pattern observed in the isotopic ratio in the gastropod growth bands and rainwater is demonstrated and provides a novel approach for precipitation reconstruction at seasonal and weekly time scales. This approach of using isotopic ratios in the gastropod growth bands for rainfall can serve as a substitute for filling gaps in rainfall data and for cases where no rain records are available. In addition, they can be used to determine the frequencies and magnitudes of dry spells from the past records.

Improved simulation of Indian summer monsoon in latest NCEP climate forecast system free run

ABSTRACTSimulation of Indian summer monsoon features by latest coupled model of National Centers for Environmental Prediction (NCEPs) Climate Forecast System version 2 (CFSv2) is attempted in its long run. Improvements in the simulation of Indian summer monsoon as compared with previous version (CFSv1) is accessed and areas which still require considerable refinements are introduced. It is found that, spatial pattern of seasonal mean rainfall and wind circulations are more realistic in CFSv2 as compared with CFSv1. Variance and northward propagation of intraseasonal oscillation (ISO), which also contribute to the seasonal mean rainfall are remarkably improved. However, the central Indian dry bias still persists and amplified. Pervasive cold bias in surface (2 m air temperature) as well as in the whole troposphere is further increased in CFSv2. These cold biases may be partly attributed to the lack of model's ability to realistically simulate the ratio of convective and stratiform rainfall. Sea‐surface temperature (SST) over the Indian Ocean is underestimated in CFSv2. However, CFSv1 shows east–west dipole structure in the bias. The teleconnection of El Nino Southern Oscillation (ENSO) and Indian summer monsoon rainfall (ISMR) in terms of Niño3 SST and monsoon rainfall correlation is more realistic in the latest version of the model. Overall, there are substantial improvements in CFSv2 as compared with CFSv1, but it has to evolve further to realistically simulate the mean and variability of ISMR.

Influence of topography on rainfall variability in Santiago Island, Cape Verde

ABSTRACTCape Verde is a semi‐arid country conformed by a group of islands located off the west coast of Africa, with highly variable rainfall that appears during a single rainy season. Santiago Island, the biggest of the country, is characterized for abrupt changes of relief within small distances. The influence of geographic location and topographic parameters, such as slope gradient, exposition and elevation on the variability of rainfall in Santiago Island was studied using monthly rainfall data of 30 seasons (1981 to 2010), with daily rainfall data for 14 seasons (1997 to 2010). The number of rainfall days and the percentage of maximum daily rainfall within the monthly and seasonal totals were evaluated. Few rainy days can control the monthly and seasonal rainfall patterns of Santiago Island. Multivariate linear regressions among daily, monthly and seasonal rainfall and elevation, slope gradient, aspect, and geographic east and west coordinates as predictors were carried out. Elevation explains most of the variance in the rainfall. The coefficients of determination show an inverse relationship with the rainfall depth: moderate rainfall totals (120–150 mm monthly, 250–300 mm seasonal) produced the best correlations for seasonal and monthly rainfall, while very low (&lt;50 mm for monthly, &lt;200 mm for seasonal) and very high amounts (&gt;250 mm for monthly, &gt;350 mm for seasonal) resulted in poor correlations. Long‐term mean rainfall was interpolated using ordinary kriging and kriging with external drift. In Santiago Island, high and more extreme rainfall events are less influenced by elevation, while low and medium rainfall events are significantly influenced by orography, with most of the rainfall appearing on high elevations. Copyright © 2013 Royal Meteorological Society

Spatial and temporal distribution of native fish larvae in seasonal and perennial tributaries of the Sacramento River, CA, USA

Mediterranean climates with their pattern of seasonal rainfall and predictable annual flooding produce a wide variety of seasonally inundated aquatic habitats. Many studies have shown the benefits of these temporary habitats, such as floodplains, for the early life stages of fishes but little work has examined the use of seasonal streams or the differences in the abundance and distribution of native fish larvae between seasonal and perennial stream habitats. We compared the spatial and temporal distribution of fish larvae among two seasonal and two perennial tributaries of the Sacramento River, CA, USA during the winter and spring of 2004 and conducted a detailed examination of the distribution of fish larvae in Mud Creek, a seasonal stream, in 2006 and 2007. In 2004, both seasonal streams had higher average water temperatures (19.0°C and 16.8°C) and an earlier initial appearance of fish larvae (early March) than the perennial streams (15.5°C and 13.3°C; late March and early May). One of the seasonal streams (Mud Creek) yielded significantly higher catch per unit effort (CPUE) of fish larvae (1131 larvae per 10 m3, 95.6% of total CPUE) as well as the highest diversity (0.92 compared to 0.09 or less) and species richness (seven compared to two or fewer) among the four streams sampled. Our detailed study of Mud Creek in 2006 and 2007 yielded a CPUE of 3856 and 18,626 (larvae per 10 m3), respectively. Samples in Mud Creek for all years yielded five to six native species of Cyprinidae, a family currently recognized as declining in California. Our findings suggest that seasonal streams in the Central Valley are used as spawning and rearing habitat for native fishes. The associated higher water temperatures may induce earlier spawning by adults and the increased temperatures, when coupled with high prey abundances, may increase somatic growth and survival rates.

Precipitation trends using in-situ and gridded datasets

Six in situ precipitation time series of varying time periods in the northwestern region and the Global Precipitation Climatology Centre (GPCC) v6 0.5° monthly dataset (1901–2010) were statistically examined for monotonic trends in Trinidad. The Pettit test was used to investigate the abrupt changes in the mean while the Mann–Kendall test was employed to assess the monotonic trends. It was found that three in situ stations and the six grids experienced abrupt changes in the rainfall patterns and that there was an apparent shift in the seasons. In addition, for five out of the six in situ stations no monotonic change was detected in the monthly, seasonal, and annual rainfall patterns. Gradual decreases were detected in the calculated weighted area average for five stations, the GPCCv6 dataset and St. Ann’s time series. The GPCCv6 data indicated that the dry season in the southern Trinidad is becoming drier. Results also suggested that the range between the greatest and lowest recorded rainfall values for some months have increased while others decreased. The gridded dataset appears to give a good representation of the dry season (January to May) rainfall compared with the wet season (June to December) and was found to be negatively biased for the north-western region but may not necessarily be so for the entire island. The results suggested that in the north-western region mirco-climates may exist. It is recommended that further investigations are needed using in situ data.

Streamflow trends in the Mahanadi River basin (India): Linkages to tropical climate variability

Summary Mahanadi River basin is one of the recognized climatic vulnerable regions of India. Recent occurrences of the extreme climatic events in this basin underscore the importance of evaluating the trend and variability of hydroclimatic variables in order to understand the potential impact of future change. In this study, the monthly streamflow data for the period 1972–2007 and the daily rainfall data for the period 1972–2005 have been analyzed using the Mann–Kendall nonparametric test after removing serial correlation. The results reveal a substantial spatial and subseasonal difference in the monsoon season streamflow and rainfall patterns, with a predominance of the increasing trends in June and decreasing trends in August. However, a marked increase is observed in the streamflow and rainfall of the pre- and post-monsoon season. The correlation coefficients show a direct correspondence of the rainfall and streamflow series with the El Nino–Southern Oscillation (ENSO), which is contrary to the established inverse relationship over India. The noteworthy feature of this study is the observed climate uncertainty in terms of large variability in the extreme indices since the 1990s, consistent with the warming induced intensification of the hydrological cycle. Strong evidences have emerged regarding the basin-wide increases in extreme rainfall indices. In particular, the coastal sector of the basin is more vulnerable to the heavy rainfall, whereas the southern Eastern Ghats region is susceptible to the moisture stress. The discharge at the basin outlet has declined at a rate of 3388 × 106 m3 decade−1, suggesting the need of environmental flow assessment. The results of this study would help the reservoir managers and policy makers in planning and management of water resources of the Mahanadi River basin.

The hydroclimatology of Gorgona Island: seasonal and ENSO-related Patternsa

Most small watersheds in the Tropical Eastern Pacific remain ungauged, and discharge analyses using gauge and simulated data have been published only for a few large rivers. I analyzed a 20-yr record of rainfall and stream discharge from Gorgona Island, a natural national park located 30 km offshore in the Pacific Ocean of Colombia to explore intra- and inter-annual patterns and drivers. Gorgona Island receives &gt; 6.600 mm of annual rainfall thus feeding numerous permanent streams. Inter Tropical Convergence Zone-driven seasonal rainfall patterns (unimodal) were consistent regardless of interannual variability. However, a large yearly variation was observed between May and August. Monthly and annual rainfall in Gorgona Island was greater than at a neighboring continental-coastal area, suggesting the occurrence of orographic and convective rain. El Niño Southern Oscillation slightly influenced interannual variation in rainfall, but it strongly influenced stream discharge. The importance of the Chocó Jet Current and Meso-Scale Stationary Systems is discussed

Drivers of songbird productivity at a restored gravel pit: Influence of seasonal flooding and rainfall patterns and implications for habitat management

The restoration of riparian sites following aggregate extraction frequently aims to expand the wetland habitat, and enhance the wetland wildlife community. However, aggregate extraction sites, typically on river flood plains, are subject to unpredictable flooding along with climate variability and other factors beyond the control of local management that may be equally important in determining the success or failure of a restoration project. Here we report on an 18-year study tracking songbird productivity and changes in the avian community following the restoration of a gravel pit on the flood plain of the River Great Ouse, Cambridgeshire. As part of the British Trust for Ornithology's Constant Effort Site ringing scheme, the productivity (ratio of young: adult captured) of 5 migrant and 6 resident species was measured systematically. Capture data along with environmental variables pertinent to the flood plain habitat were analysed using generalised linear models. For some migrant species (e.g. willow warbler Phylloscopus trochilus and reed warbler Acrocephalus scirpaceus) breeding success was predicted by maximum winter flood. The productivity of resident species (e.g. dunnock Prunella modularis) was predicted not only by the overall amount of rain (positively related to production) but also the extent of spring downpours (negatively related to production). We expected that a major influence on the avian community would be the passage of time and associated vegetation succession. However, winter flood was found to be particularly important, as to a lesser extent was spring rain and unseasonal cold snaps. Detrended correspondence analysis of the total numbers of birds captured (adults+young) for 16 species showed that the changing avian community was shaped by winter floods more than by patterns in precipitation. It would appear that the avian community is influenced by patterns of habitat change, shaped as much by climate variability as local land management.

Epidemiology of malaria in the Papua New Guinean highlands

To conduct an in-depth investigation of the epidemiology of malaria in the Papua New Guinea (PNG) highlands and provide a basis for evidence-based planning and monitoring of intensified malaria control activities. Between December 2000 and July 2005, 153 household-based, rapid malaria population surveys were conducted in 112 villages throughout the central PNG highlands. The presence of malaria infections was determined by light microscopy and risk factors assessed using a structured questionnaire.The combined dataset from all individually published surveys was reanalysed. The prevalence of malaria infections in the different surveys ranged from 0.0% to 41.8%(median 4.3%) in non-epidemic surveys and 6.6% to 63.2% (median 21.2%, P < 0.001) during epidemics. Plasmodium falciparum was the predominant infection below 1400 m and during epidemics, Plasmodium vivax at altitudes >1600 m. Outside epidemics, prevalence decreased significantly with altitude, was reduced in people using bed nets [odds ratio (OR) = 0.8, P < 0.001] but increased in those sleeping in garden houses (OR = 1.34, P < 0.001) and travelling to highly endemic lowlands (OR = 1.80, P < 0.001). Below 1400 m, malaria was a significant source of febrile illness. At higher altitudes, malaria was only a significant source of febrile illness during epidemic outbreaks, but asymptomatic malaria infections were common in non-epidemic times. Malaria is once again endemic throughout the PNG highlands in areas below 1400–1500 m of altitude with a significant risk of seasonal malaria outbreaks in most area between 1400–1650 m. Ongoing control efforts are likely to result in a substantial reduction in malaria transmission and may even result in local elimination of malaria in higher lying areas.