Average Monthly Minimum Research Articles

Spatial Variability of Average Annual and Monthly Minimum River Flow in Poland

The aim of this article is to analyse the spatial variability of SNQ, the average annual minimum river flow, as well as SNQm (m = 1, 2, …12), the average monthly minimum river flow in Poland. The data were obtained from the Institute of Meteorology and Water Management – National Research Institute (IMWM-NRI) in the form of the daily flow series from the period between 01 Nov 1990 and 31 Oct 2020 from 433 gauging cross-sections located within the territory of Poland. The results of the analyses are presented on maps of the physiographic regions of Poland (the Coastlands, the Lakelands, the Lowlands, the Highlands, the Carpathians and the Sudety Mountains). In order to compare SNqm – the unit average minimum monthly flow between the physiographic regions, the Kruskal-Wallis test with the Dunn (Bonferroni) adjustment was performed. In order to evaluate the spatial variability of the SNqm, the hypothesis was verified for each gauging station that the Spearman correlation coefficient between the SNqm and the zero point of the gauge was different from zero. The SNqm flow changed over the year. As expected, the highest values were observed in March and April, and the lowest in July and August. Regardless of the month, the rivers in the central part of Poland (the Lowlands) were less water abundant than those in other regions of the country while the greatest flows were observed in the mountain rivers. Statistically, no difference was observed between the SNqm in the Coastlands, the Carpathians and the Sudety Mts., and in nearly all of the months between the SNqm in the Lakelands and the Lowlands. In the whole territory of Poland, the river flow was dependent on the altitude of the catchment, while the strongest correlation was observed in the mountain regions.

Minimum Temperature Forecasting Using Gated Recurrent Unit

Aim: To forecast the monthly average Minimum Temperature (ºC) in Coimbatore district.
 Study Design: Gated Recurrent Unit (GRU) has been employed to forecast the Minimum Temperature.
 Place and Duration of Study: Time series data for average month wise Minimum Temperature from January 1982 to September 2022 was collected from Agro Climate Research Centre, TNAU for Coimbatore District.
 Methodology: GRU which belongs to the field of deep learning has been employed to anticipate the average monthly Minimum Temperature by analyzing time series data from January 1982 to September 2022 in the district of Coimbatore. The model was trained using data from 1982 January to 2019 December and tested on data from 2020 January to 2022 September. After training and testing the algorithm was deployed to forecast Minimum Temperature for the lead time ahead.
 Results: The GRU model generated RMSE and MAE scores of 0.694ºC and 0.523ºC, respectively, for Minimum Temperature. GRU model had a Willmott’s Index of Agreement (WI) value as 0.943 that is very close to 1. This demonstrates the effectiveness of the model built to effectively predict the Minimum Temperature. The study's evaluation of the RMSE, MAE, and Willmott Index value made it readily evident that the GRU model performed quite accurately for forecasting Minimum Temperature. Gated Recurrent Unit algorithm was used to forecast the Minimum Temperature from October 2022 till December 2023 that is for the next 15 months.

ON THE POSSIBILITY OF USING REANALYSIS DATA TO ESTIMATE THE WATER TEMPERATURE OF THE CASPIAN SEA

Water temperature is one of the important hydrometeorological characteristics of large bodies of water, because of its influence on biological and chemical processes. In this work, water temperature data from coastal observation points of Kazakhstan and remote sensing data of the Earth, such as satellite images, and reanalysis, were considered. In the longterm context, in the Kazakh sector of the Caspian Sea, the water temperature ranged from 10.8 ⁰С (Peshnoi) to 12.7 ⁰С (Kulaly Island). The effectiveness of the use of reanalysis data with the use of statistical criteria was evaluated. These quality criteria characterize the reliability of the results, and ERA5 realism data are effective and can be used for analysis, and research. All the databases under consideration showed that SST the average monthly minimum values are observed in January, and the maximum values are observed in the summer period. The change in water temperature over the years has a positive trend.

Ten years of monitoring malaria trend and factors associated with malaria test positivity rates in Lower Moshi

BackgroundHigh altitude settings in Eastern Africa have been reported to experience increased malaria burden due to vector habitat expansion. This study explored possible associations between malaria test positivity rates and its predictors including malaria control measures and meteorological factors at a high-altitude, low malaria transmission setting, south of Mount Kilimanjaro.MethodsMalaria cases reported at the Tanganyika Plantation Company (TPC) hospital’s malaria registers, meteorological data recorded at TPC sugar factory and data on bed nets distributed in Lower Moshi from 2009 to 2018 were studied. Correlation between bed nets distributed and malaria test positivity rates were explored by using Pearson correlation analysis and the associations between malaria test positivity rates and demographic and meteorological variables were determined by logistic regression and negative binomial regression analyses, respectively.ResultsMalaria cases reported at TPC hospital ranged between 0.48 and 2.26% per year and increased slightly at the introduction of malaria rapid diagnostic tests. The risk of testing positive for malaria were significantly highest among individuals aged between 6 and 15 years (OR = 1.65; 1.65 CI = 1.28–2.13; p = 0.001) and 16–30 years (OR = 1.49; CI = 1.17–1.89; p = 0.001) and when adjusted for age, the risk were significantly higher among male individuals when compared to female individuals (OR = 1.54; 1.00–1.31; p = 0.044). Malaria test positivity rates were positively associated with average monthly minimum temperatures and negatively associated with average monthly maximum temperatures (incidence rate ratio (IRR) = 1.37, 95% confidence interval (CI) = 1.05–1.78, p = 0.019 and IRR = 0.72, 95% CI = 0.58–0.91, p = 0.005, respectively). When analysed with one month lag for predictor variables, malaria test positivity rates were still significantly associated with average monthly minimum and maximum temperatures (IRR = 1.67, 95% CI = 1.28–2.19, p = 0.001 and IRR = 0.68, 95% CI = 0.54–0.85, p = 0.001, respectively). Average monthly rainfall and relative humidity with or without a one month lag was not associated with malaria test positivity rates in the adjusted models. Explopring possible associations between distribution of long-lasting insecticidal nets, (LLINs) and malaria test positivity rates showed no apparent correlation between numbers of LLINs distributed in a particular year and malaria test positivity rates.ConclusionIn Lower Moshi, the risk of being tested positive for malaria was highest for older children and male individuals. Higher minimum and lower maximum temperatures were the strongest climatic predictors for malaria test positivity rates. In areas with extensive irrigation activity as in Lower Moshi, vector abundance and thus malaria transmission may be less dependent on rainfall patterns and humidity. Mass distribution of LLINs did not have an effect in this area with already very low malaria transmission.

Assessment of regional weather and climatic conditions as health risk factors according to the wind-cold index

Determined the cold periods of the year in different weather and climatic conditions of the Krasnoyarsk Territory. We assessed the health risk of the population under the influence of temperature and wind speed in an open area according to the wind-cold index (which determines the comfort and discomfort of the weather). The average monthly daily, average monthly minimum temperatures and wind speeds were estimated for 10 years (2010–2019). Wind speed was assessed using the Bothford scale. In terms of ambient temperature, the cold period lasted: subarctic zone (Norilsk) — 5, moderate continental (Krasnoyarsk and Minusinsk) — 3 months. According to the wind-cold index (in terms of average temperature and wind speed), the period of severe weather in the subarctic zone lasted from 6 to 7 months a year. Three months of the year, the meteorological perception was assessed as «very» and 1 month — as «extremely cold». In the region of Krasnoyarsk, as well as in Minusinsk, the cold «uncomfortable period» was lengthened by 1 month. The health risk under the combined influence of the minimum temperature and maximum wind increased in the subarctic zone up to 8, moderate continental up to 5 (Krasnoyarsk) — 5–6 (Minusinsk) months. In the area of Norilsk, the period, assessed as «extremely cold, exposed parts of the body can be supercooled by 10 minutes,» extended by 4 months, in Krasnoyarsk such a period was possible in January, Minusinsk was recorded in January and February. In the conditions of one climatic zone (Krasnoyarsk, Minusinsk), regional features of weather and climatic characteristics (duration of cold and warm periods, temperature, wind speed, severity and duration of periods of severe weather), which can affect the well-being and state of health of the population, have been identified.

Modified BBCH codification and correlation of phenological characteristics with climatic variables in jamun (Syzigium cuminii Skeels)

Jamun (Syzigium cuminii Skeels) is gradually gaining importance due to its extraordinary medicinal properties and enhanced demand for fresh fruit, which is buttressed by the growth of the processing industry. Curative property of Jamun fruits against Diabetes mellitus type 2 has boosted its commercial orcharding, which necessitates gathering precise information on phenological responses to changing temperature and precipitation. A modified three digit extended Biologische Bundesanstalt Bundessortenamt and Chemische Industrie (BBCH) scale was developed and assigned 3 digit codes to describe the important phenological stages. Eight principal growth stages and 36 secondary stages have been described with illustrations that occur sequentially in Jamun under subtropics. Interestingly the primary phenophases of vegetative phenology i.e. bud development, leaf development and shoot development showed a large overlap and the interrupted phenostages are attributed to the inclemental weather conditions. Thus, under a warm temperate subtropical climate in the northern hemisphere, Jamun canopies presented two vegetative flushes (represented as mesostage 1 and 2), the second flush registering highest frequency (60–80 %) in months of September to October. This is in contrast to continuous growth under tropical climate conditions, wherein growth cessation does not occur. While vegetative growth flush occurred twice a year in a major part of canopy, flower-bearing panicles emerged on mature shoots in the months of February and March. Floral induction characterized by the inflorescence emergence and subsequent blooming closely followed the upswing of average monthly minimum and maximum temperature curve under subtropics, while average temperature downturn coupled with high precipitation released the vegetative flush episode. The phenostage (5) involving inflorescence emergence and growth occurred once in the subtropical climate, sustaining for around 8 weeks, followed by flowering (6) and fruit development(7). As with other evergreen trees, vegetative growth did not depict cessation and dormancy was observed after harvest and onset of winter. The correlation of emerging phenological events with temperature and humidity established the utility of the BBCH code for forecasting the outcomes of the canopy shoots. Early fruit production and synchronous shoot growth can be targeted by imposing shoot pruning strategy immediately after harvest at dormancy. The study establishes interplay of ecogeography and germplasm for expression of standard phenostages and the impact of climate change on fruit productivity.

Through space and time: Predicting numbers of an eruptive pine tree pest and its predator under changing climate conditions

Forest biotic populations and communities are undergoing irreversible changes due to climatic perturbations, and these effects may be exacerbated by insect pests. In the southeastern United States (U.S.), Dendroctonus frontalis is one of the most important forest pests that can cause substantial tree mortality over large geographic areas. As life-history of D. frontalis is dependent on environmental conditions, our objective was to determine the effects of climatic variables on the species occurrence of D. frontalis and their main predator, Thanasimus dubius. U.S. Department of Agriculture - Forest Service beetle trapping data (proxy for true abundance) for 2014–2018 were assessed with nine climatic variables including: (1) average monthly minimum, maximum, and mean temperatures; (2) mean winter temperature; (3) minimum, maximum and mean annual temperature; and (4) cumulative winter and annual precipitation. Variable selection was performed using least absolute selection and shrinkage operator (LASSO), and selected variables were fit to varying coefficient generalized additive models (GAMs). Minimum temperatures for February and March and maximum temperatures for January and prior year August were found to have a significant effect on D. frontalis numbers, and model accuracy was ~89%. Beetle suitability was assessed for 1981–2100 under three different shared socioeconomic pathways (SSP). The model indicated that the suitability of D. frontalis has increased from 1981 to 2019 in certain regions of Alabama, Mississippi, and Georgia, while Arkansas, Kentucky, Louisiana, North Carolina, Tennessee, East Texas, and Virginia had low suitability. Future projections indicated comparable D. frontalis numbers to current numbers under the lowest SSP of 2.1 °C by year 2100, but D. frontalis may decrease under higher warming projections. The same climatic predictors influenced T. dubius, except average September maximum temperature replaced August maximum temperatures in the model. Understanding how these abiotic factors influence forest pest populations may better guide prevention and management practices aimed at identifying high risk areas and reducing pest outbreaks.

Air temperature and precipitation regime in Ukraine in 2021-2050 by CORDEX model ensemble

Global temperatures over the period of 2081–2100 are expected to rise by 0.3–4.8 °C compared to the period of 1986–2005. According to the previous studies, the average annual air temperature in all regions of Ukraine will keep increasing in the near future and the maximum increase in precipitation is expected mainly in the western and northern regions during winter and spring, whereas the decrease in precipitation will be registered in the central, eastern and southern regions during summer and autumn. This article aims to identify the features of changes in air temperature and precipitation for different regions of Ukraine in 2021–2050 based on the modelling results of the ensemble of CORDEX models as per the RCP4.5 scenario. 16 simulation runs for 7 regional climate models were selected for the analysis and the results were presented for five regional centers of Ukraine: Kyiv, Lviv, Kropyvnytskyi, Kharkiv and Odesa.
 It is shown that future monthly precipitation in all regions tends to increase by an average of 20–40 mm during autumn, winter and spring, whereas the decrease is expected to occur in summer. According to some models, the monthly precipitation will be close to zero in the Southern Ukraine in July and August, which is typical for the Mediterranean climate. Compared to the period of 1961–1990, the average monthly temperature will undergo small changes (up to 1 °C) in spring and autumn, while the temperature in summer and winter will increase by 2.5–3.5 °C. In Odesa, in contrast to the present-day situation, a positive average monthly air temperature will be expected to be recorded throughout the whole year, and only 25% of the runs show negative average monthly minimum temperatures. In the Northern Ukraine, the average monthly minimum and maximum temperatures in winter will increase by 2.0–2.5 °C, and in summer only the maximum air temperature will increase significantly.
 Thus, we can assume a change in the regime of moisture supply in Ukraine over the next thirty years. One can also assume a high probability of snow cover absence throughout the whole winter in the Southern Ukraine as a result of positive temperatures.

Sensitivity of vegetation to climate variability and its implications for malaria risk in Baringo, Kenya.

The global increase in vector borne diseases has been linked to climate change. Seasonal vegetation changes are known to influence disease vector population. However, the relationship is more theoretical than quantitatively defined. There is a growing demand for understanding and prediction of climate sensitive vector borne disease risks especially in regions where meteorological data are lacking. This study aimed at analyzing and quantitatively assessing the seasonal and year-to-year association between climatic factors (rainfall and temperature) and vegetation cover, and its implications for malaria risks in Baringo County, Kenya. Remotely sensed temperature, rainfall, and vegetation data for the period 2004–2015 were used. Poisson regression was used to model the association between malaria cases and climatic and environmental factors for the period 2009–2012, this being the period for which all datasets overlapped. A strong positive relationship was observed between the Normalized Difference Vegetation Index (NDVI) and monthly total precipitation. There was a strong negative relationship between NDVI and minimum temperature. The total monthly rainfall (between 94 -181mm), average monthly minimum temperatures (between 16–21°C) and mean monthly NDVI values lower than 0.35 were significantly associated with malaria incidence rates. Results suggests that a combination of climatic and vegetation greenness thresholds need to be met for malaria incidence to be significantly increased in the county. Planning for malaria control can therefore be enhanced by incorporating these factors in malaria risk mapping.

An Exploration on the Effective Factors of Tourism Industry on Protection of the Environment in the Historical City Ghoumas

According to the world tourism organization (WHO) in 2005, the number of tourists has increased up to 36 times. In a way that it has maximized from 25 million in 1950 to 1018 million in 2010. The sustainable tourism, thus, because of making a balance between different environmental, economic, cultural and social dimensions of the tourism development, plays a considerable role in protection of species diversity, and benefits the tourism activists in order to reduce its destructive impact on the environment and the local cultures and being kept for the future generations. Accordingly, the present research first examines the relationship between tourism, sustainable development and the ecology, for measurement of different aspects of the industry effect on the environment. Secondly, the present study uses from some parameters like the average monthly minimum and maximum temperatures, the average relative humidity, the average maximum and minimum temperatures in day and at night in the Semnan station as well as using the common diagram in the experimental methods like Olegi to assess day and night Climatourism in the region. Finally, on the basis of the performed analysis, the strengths and weak points of tourist attractions for the protection of the environment are considered.

Respiratory Syncytial Virus Circulation in Seven Countries With Global Disease Detection Regional Centers

Respiratory syncytial virus (RSV) is the leading cause of lower respiratory tract infections in young children globally, with the highest burden in low- and middle-income countries where the association between RSV activity and climate remains unclear. Monthly laboratory-confirmed RSV cases and associations with climate data were assessed for respiratory surveillance sites in tropical and subtropical areas (Bangladesh, China, Egypt, Guatemala, Kenya, South Africa, and Thailand) during 2004-2012. Average monthly minimum and maximum temperatures, relative humidity, and precipitation were calculated using daily local weather data from the US National Climatic Data Center. RSV circulated with 1-2 epidemic periods each year in site areas. RSV seasonal timing and duration were generally consistent within country from year to year. Associations between RSV and weather varied across years and geographic locations. RSV usually peaked in climates with high annual precipitation (Bangladesh, Guatemala, and Thailand) during wet months, whereas RSV peaked during cooler months in moderately hot (China) and arid (Egypt) regions. In South Africa, RSV peaked in autumn, whereas no associations with seasonal weather trends were observed in Kenya. Further understanding of RSV seasonality in developing countries and various climate regions will be important to better understand the epidemiology of RSV and for timing the use of future RSV vaccines and immunoprophylaxis in low- and middle-income countries.

Predicting the distribution of the air pollution sensitive lichen species Usnea hirta

AbstractUsnea hirta, an important member of the lichen family Parmeliaceae, has long been used as a bio-monitor of air pollution, particularly of sulphur dioxide in North America. Although U. hirta has a wide geographical distribution, it is important to be able to identify accurately the optimal habitat conditions for air pollution-sensitive species, thus making it possible to more effectively and efficiently establish air quality bio-monitoring stations. We modelled the distribution of U. hirta as a function of nine variables, five macroclimatic variables: average monthly precipitation, average monthly minimum temperature, average monthly maximum temperature, solar radiation, and integrated moisture index, and four topographic variables: elevation, slope, aspect, and land forms and uses for the White River National Forest, Colorado. The response variable was developed based on the presence or absence of U. hirta at each of 72 bio-monitoring baseline sites established in selected portions of four intermountain area states. Our model was developed using Non-Parametric Multiplicative Regression (NPMR) analysis, a modelling approach that analyzes environmental gradients, or predictor variables, against known locations for individuals of the model species. Finally, we evaluated our model on the basis of log β values and overall improvement over a naïve model and the Monte Carlo Permutation Test with 1000 randomized runs. The best model for U. hirta included four variables – solar radiation, average monthly precipitation, and average monthly minimum and maximum temperatures (log β=3·68). Among these four variables, average monthly maximum temperature was the most influential predictor (sensitivity=0·71) for the distribution of U. hirta. The occurrence rate for U. hirta, based on field validation, was 45·5%, 65·4%, and 70·4% for low, medium, and high probability areas, respectively. This study showed that our model was successful in predicting the distribution of U. hirta in the White River National Forest. Based on these results, the north-eastern and western portions of the forest appear to offer the most favourable conditions for the installation of future air quality bio-monitoring baseline sites.

Ridge regression technique to determine the environmental influences on tef (Eragrostis tef) grain yield

Tef grain yield is dependent on a number of component characters such as plant height and panicle length. These characters and consequently yield are governed by a large number of factors including environmental factors. The objective of this paper was to determine the environmental influences on tef grain yield. The effects of eleven environmental variables on tef yield were studied using least squares and ridge regression analyses. The results revealed that the least squares estimates of regression coefficients for seven environmental variables did not give a correct indication of the influence of the variables on tef yield but that the estimates from ridge regression were stable. In addition, the ridge regression model has a lower mean square error. Tef grain yield is positively correlated to rainfall, average monthly minimum temperatures, soils dominated by silt with adequate quantities of available nitrogen while it is negatively influenced by average monthly maximum temperatures and clay soils. The results obtained from this study are in accordance with previous literature about the effects of environmental factors on yield of tef cultivars.

Treeline dynamics in relation to climatic variability in the central Tianshan Mountains, northwestern China

ABSTRACTAim Climate variability may be an important mediating agent of ecosystem dynamics in cold, arid regions such as the central Tianshan Mountains, north‐western China. Tree‐ring chronologies and the age structure of a Schrenk spruce (Picea schrenkiana) forest were developed to examine treeline dynamics in recent decades in relation to climatic variability. Of particular interest was whether tree‐ring growth and population recruitment patterns responded similarly to climate warming.Location The study was conducted in eight stands that ranged from 2500 m to 2750 m a.s.l. near the treeline in the Tianchi Nature Reserve (43°45′−43°59′ N, 88°00′−88°20′ E) in the central Xinjiang Uygur Autonomous Region, northwestern China.Methods Tree‐ring cores were collected and used to develop tree‐ring chronologies. The age of sampled trees was determined from basal cores sampled as close as possible to the ground. Population age structure and recruitment information were obtained using an age–d.b.h. (diameter at breast height) regression from the sampled cores and the d.b.h. measured on all trees in the plots. Ring‐width chronologies and tree age structure were both used to investigate the relationship between treeline dynamics and climate change.Results Comparisons with the climatic records showed that both the radial growth of trees and tree recruitment were influenced positively by temperature and precipitation in the cold high treeline zone, but the patterns of their responses differed. The annual variation in tree rings could be explained largely by the average monthly minimum temperatures during February and August of the current year and by the monthly precipitation of the previous August and January, which had a significant and positive effect on tree radial growth. P. schrenkiana recruitment was influenced mainly by consecutive years of high minimum summer temperatures and high precipitation during spring. Over the last several decades, the treeline did not show an obvious upward shift and new recruitment was rare. Some trees had established at the treeline at least 200 years ago. Recruitment increased until the early 20th century (1910s) but then decreased with poor recruitment over the past several decades (1950–2000).Main conclusions There were strong associations between climatic change and ring‐width patterns, and with recruitments in Schrenk spruce. Average minimum temperatures in February and August, and total precipitation in the previous August and January, had a positive effect on tree‐ring width, and several consecutive years of high minimum summer temperature and spring precipitation was a main factor favouring the establishment of P. schrenkiana following germination within the treeline ecotone. Both dendroclimatology and recruitment analysis were useful and compatible to understand and reconstruct treeline dynamics in the central Tianshan Mountains.

Koeleria macrantha (Ledeb.) Schultes (K. alpigena Domin, K. cristata (L.) Pers. pro parte, K. gracilis Pers., K. albescens auct. non DC.)

<i>Koeleria macrantha</i> (Ledeb.) Schultes (<i>K. alpigena</i> Domin, <i>K. cristata</i> (L.) Pers. pro parte, <i>K. gracilis</i> Pers., <i>K. albescens</i> auct. non DC.)

A simple climagraph for characterizing regional suitability for greenhouse cropping in Greece

A Flimatic analysis is presented for the rational development of crops under cover in Greece. From the climatic requirements of thermophile species commonly grown in greenhouses in Greece, we have characterised the corresponding outside climate requirements and constructed the climagraphs for different regions of Greece. These graphs combine the average monthly minimum and maximum air temperatures versus the corresponding global irradiance and allows delimiting the appropriate climatic periods for cultivation of thermophile species, with and without air conditioning. These climagraphs may be used for the primary assessment of suitability for the development of crops under cover in a given area. From its application over different regions in Greece it can be concluded that: (1) natural ventilation is insufficient from May to September over the whole of the country; (2) summer greenhouse crops can only be grown in Crete without evaporative cooling where dynamic ventilation and shading are sufficient; (3) winter cultivation in unheated greenhouses is only possible in Crete and (4) spring cropping under cover would be the principal use of greenhouses with autumn cultivation envisioned as a merely complementary cropping season.

Climatic Assessment of the Arid Southwestern United States for Use in Predicting Evapotranspiration of Turfgrass

Climatic conditions were assessed at three locations in the arid southwestern United States over a two year period. The three locations were Las Vegas, NV, Tucson, AZ and Palm Desert, CA. Automated weather stations monitored maximum and minimum temperature, relative humidity, solar radiation, wind run and rainfall. Data were input into the empirical based Penman combination equation to predict potential evapotranspiration (ETo). Surveys were conducted at all three locations to evaluate the soil conditions, water availability, turfgrass management and crop coefficients used. Only slight differences existed beween average monthly minimum temperatures, maximum temperatures and solar radiation at the three sites. However, differences in average monthly wind run and relative humidity at the three sites led to greater separation in the ETo estimates during summer months. These differences resulted in a 7% and 13% error in estimating monthly ETo at the Palm Desert and Tucson sites respectively, based on using th...

Effects of Microhabitat, Flocking, Climate and Migratory Goal on Energy Expenditure in the Annual Cycle of Red Knots

We quantify seasonal changes in the maintenance energy requirements of Red Knots (Calidris canutus islandica). This subspecies breeds on the tundra of northeast Canada and north Greenland, migrates through Iceland and spends the winter in the coastal regions of western Europe. Maintenance Metabolism (Mmaint) is defined as Basal Metabolic Rate plus extra costs for thermoregulation at environmental temperatures below the thermoneutral zone. Mmaint of Red Knots resting in different microhabitats was estimated on the basis of measurements with heated taxidermic mounts, which were calibrated with forced convection against postabsorptive live birds resting over a range of air temperatures (i.e., against their Standard Metabolic Rate). Based on a physically realistic regression model for heat loss, we established the relationships between the electric power consumption of the mounts and three critical weather variables affecting dry heat loss: air temperature, wind speed and global solar radiation. Observations of Red Knots' use of different microhabitats (including their occurrence in flocks of different bird density) and orientation into the wind were collected on the wintering and on the breeding grounds. At lower standard operative temperatures on the coastal wintering grounds they foraged in tighter flocks and more often faced into the wind, saving 8% compared to solitary birds standing with their flanks exposed. We then used (1) microhabitat-specific equations, (2) long-term meterological data sets, and (3) estimates of habitat use and wind orientation of free-living Red Knots at the different locations and times of the year, to reconstruct the seasonal patterns in Mmaint in the field. Average predicted Mmaint varied between 2.93 W in January and 1.64 W in August on the Dutch wintering areas. The maximum monthly Mmaint in winter was higher than that reached on the Canadian breeding grounds (2.28 W, or 0.78 times the Dutch January cost) and on the Icelandic staging grounds (2.27 W, or 0.77× the Dutch cost in January, in spring, and 1.98 W, or 0.68×, in fall). Based on 31 years of weather data from the Dutch Wadden Sea in the period 1960-1991 (assuming that Red Knots have not changed their behavior), the long-term overwinter average of Mmaint was 2.57 W, with an average monthly minimum of 1.87 W and a maximum of 3.05 W. The west-central coast of France, 900 km more to the south, offers energetically cheaper conditions (0.76× values for the Dutch coast in January) in the nonbreeding season than the Wadden Sea. If islandica knots moved on to West Africa during the nonbreeding season they would incur a saving of 1.13 W on Mmaint, and pay an extra 0.13-0.22 W to cover the cost of travel.

Wintering Biology of Ruby-Crowned Kinglets in the Lower Colorado River Valley

The Ruby-crowned Kinglet (Regulus calendula) was studied from October-April during four years, 1975-1979, among six major plant communities in the riparian corridor of the lower Colorado River valley. Kinglets were most abundant in cottonwood-willow and least abundant in arrowweed. Within each community, the greatest density of kinglets generally occurred in areas of tall, dense vegetation. Density differed significantly among the four years in November, the month of peak abundance, and in February, winter's end. Populations decreased significantly through the winter in each year and decreases were not uniform among plant communities. Differences in relative abundances and winter population decreases were related to winter weather conditions. During the study period, kinglets were subject to marked seasonality as determined by decreases in average monthly minimum temperatures, changes in tree phenology, and changes in insect abundance and biomass. Kinglet responses to seasonality were most apparent in population dynamics, distribution among plant communities, foraging substrate utilization and choice of prey. Analysis of these data emphasizes the selective importance of the nonbreeding season ecology to kinglets and implies that these birds may be winter-limited.

The effect of low temperatures on banana yields

Banana yields from four regions in Israel have been correlated with low temperatures over a period of eleven years. It was found that the average monthly minimum temperatures during the winter season affect primarily the yield of the current year, while the "quantity of cold" i.e. a measure of temperatures below 5°C affects the yield of the following year. Mild cold weather during November and March have a beneficial effect. The model used fitted the data fairly well, explaining 98% to 61% of the total variation in yield, depending on the climatic region.