Disentangling the drivers of urban bird diversity in the non-breeding season: A general synthesis.

Current knowledge about the impacts of urbanisation on bird assemblages is based on evidence from studies partly or wholly undertaken in the breeding season. In comparison, the non-breeding season remains little studied, despite the fact that winter conditions at higher latitudes are changing more rapidly than other seasons. During the non-breeding season, cities may attract or retain bird species because they offer milder conditions or better feeding opportunities than surrounding habitats. However, the range of climatic, ecological and anthropogenic mechanisms shaping different facets of urban bird diversity in the non-breeding season are poorly understood. We explored these mechanisms using structural equation modelling to assess how urbanisation affects the taxonomic, phylogenetic and functional diversity of avian assemblages sampled worldwide in the non-breeding season. We found that minimum temperature, elevation, urban area and city age played a critical role in determining taxonomic diversity while a range of factors-including productivity, precipitation, elevation, distance to coasts and rivers, socio-economic (as a proxy of human facilitation) and road density-each contributed to patterns of phylogenetic and functional diversity. The structure and function of urban bird assemblages appear to be predominantly shaped by temperature, productivity and city age, with effects of these factors differing across seasons. Our results underline the importance of considering multiple hypotheses, including seasonal effects, when evaluating the impacts of urbanisation on biodiversity.

Variability in the minimum temperature over two centuries in the overlap region between the fringe of the Asian westerly region and the temperate continental-monsoon climate transition zone.

The overlap region between the eastern fringe of the Asian westerly region and the temperate continental-monsoon climate transition zone is sensitive to climate changes and is characterized by fragile ecosystems. Uncovering the long-term historical climate variability patterns in this region is necessary. A standardized tree-ring width chronology was constructed based on the tree-ring samples collected from four representative tree species in four typical areas in the overlap region, and the 203- to 343-year annual mean minimum temperature series in the overlap region were reconstructed. The reconstructed series overlapped well with extreme climate events and low-temperature periods recorded in historical data. Therefore, the reconstructed model is stable and reliable. As suggested by the reconstructed series, the annual average minimum temperature in the overlap region changes sharply from east to west, and the periodicity change in the overlap region shows a trend of gradually weakening from the east and west ends to the middle. In the nineteenth century, the high-latitude area was in the high-temperature period, and the entire overlap region experienced significant low-temperature periods lasting 20-45 years until the 1950s. The western part had an earlier low-temperature period start time, a longer cooling duration, and a slower cooling rate than the central part. The overlap region experienced a significant warming period in approximately the last half-century, with temperatures increasing faster in the western and eastern parts than in the central part. The temperature variability in the overlap region was more intense in the last two centuries, with shorter periodicities and a larger proportion of cold periods. The central and western parts of the Asian westerly region, the mid- to high-latitude regions of the transition zone, and the overlap region experienced significant low-temperature periods or drastic cooling trends (the Little Ice Age) in the first half of the nineteenth century and significant warming trends afterwards due to global warming. The influences of these changes may have been exacerbated by the westerly circulation. The results of this study provide new insights into the use of dendroclimatology to extract temperature series in the Asian westerly region and the transition zone and a reference for research on global climate change.

Cold indoor temperatures and their association with health and well-being: a systematic literature review.

OBJECTIVE: The study aimed to identify, appraise and update evidence on the association between cold temperatures (i.e. <18°C) within homes (i.e. dwellings) and health and well-being outcomes. STUDY DESIGN: This study was a systematic review. METHODS: Seven databases (MEDLINE, Embase, Cochrane Database of Systematic Reviews, CINAHL, APA PsycInfo, Applied Social Sciences Index and Abstracts, Coronavirus Research Database) were searched for studies published between 2014 and 2022, which explored the association between cold indoor temperatures and health and well-being outcomes. Studies were limited to those conducted in temperate and colder climates due to the increased risk of morbidity and mortality during winter in those climatic zones. Studies were independently quality assessed using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. RESULTS: Of 1209 studies, 20 were included for review. Study outcomes included cardiovascular (blood pressure, electrocardiogram abnormalities, blood platelet count), respiratory (chronic obstructive pulmonary disease symptoms, respiratory viral infection), sleep, physical performance and general health. Seventeen studies found exposure to cold indoor temperatures was associated with negative effects on health outcomes studied. Older individuals and those with chronic health problems were found to be more vulnerable to negative health outcomes. CONCLUSION: Evidence suggests that indoor temperatures <18°C are associated with negative health effects. However, the evidence is insufficient to allow clear conclusions regarding outcomes from specific temperature thresholds for different population groups. Significant gaps in the current evidence base are identified, including research on the impacts of cold indoor temperatures on mental health and well-being, studies involving young children, and the long-term health effects of cold indoor temperatures.

Effect of abnormal values of three temperature indicators on ischemic stroke hospital admissions in Guangzhou, China.

Abnormal temperature has important effects on the occurrence of ischemic stroke (IS). However, relatively less efforts have been taken to systematically unravel the association between various abnormal temperature and IS hospital admission. Focusing on three temperature indicators (i.e., mean temperature, maximum temperature, and minimum temperature), this study attempts to analyse how their abnormal values affect IS hospital admission. The dataset covers the period between September 17, 2012 and August 28, 2018, and includes a total of 1464 cases who were admitted to the hospital for the first onset of IS and lived in the main urban area of Guangzhou. The study adopts the time-stratified case-crossover analysis. Abnormal values of temperature were measured using the 2.5th and 97.5th quantile values of each temperature indicator, with the former refers to a low value whereas the latter a high one. The effects of abnormal temperature on IS hospital admission were assessed through calculating the relative risks induced by the low and high values (the median values of each temperature indicators were taken as the references). The results show that the risk window periods for IS hospital admission associated with the low values of the temperature indicators are the lags of 3-7 days and 18-19 days. The risks of high temperature values on IS admission, however, are insignificant with either one-day lag or cumulative lag. As to different population groups, females show higher risks of IS hospital admission at low temperature values than males; and elderly people, compared with young people, are more vulnerable to low temperature values. To cities with similar climate of Guangzhou, particular attention should be paid to the impact of low temperature values, especially the low value of minimum temperature, on IS admission, and to females and elderly people who are more sensitive to abnormal temperatures.

Substantial warming of Central European mountain rivers under climate change.

Water bodies around the world are currently warming with unprecedented rates since observations started, but warming occurs highly variable among ecoregions. So far, mountain rivers were expected to experience attenuated warming due to cold water input from snow or ice. However, air temperatures in mountain areas are increasing faster than the global average, and therefore warming effects are expected for cold riverine ecosystems. In decomposing multi-decadal water temperature data of two Central European mountain rivers with different discharge and water source regime, this work identified so far unreported (a) long-term warming trends (with river-size dependent rates between +0.24 and +0.44 °C decade-1); but also (b) seasonal shifts with both rivers warming not only during summer, but also in winter months (i.e., up to +0.52 °C decade-1 in November); (c) significantly increasing minimum and maximum temperatures (e.g., temperatures in a larger river no longer reach freezing point since 1996 and maximum temperatures increased at rates between +0.4 and +0.7 °C decade-1); and (d) an expanding of warm-water periods during recent decades in these ecosystems. Our results show a substantial warming effect of mountain rivers with significant month-specific warming rates not only during summer but also in winter, suggesting that mountain river phenology continues to change with ongoing atmospheric warming. Furthermore, this work demonstrates that apart from a general warming, also seasonal shifts, changes in extreme temperatures, and expanding warm periods will play a role for ecological components of mountain rivers and should be considered in climate change assessments and mitigation management. Supplementary Information: The online version contains supplementary material available at 10.1007/s10113-023-02037-y.

Daily Estimation of Global Solar Irradiation and Temperatures Using Artificial Neural Networks through the Virtual Weather Station Concept in Castilla and León, Spain.

In this article, the interpolation of daily data of global solar irradiation, and the maximum, average, and minimum temperatures were measured. These measurements were carried out in the agrometeorological stations belonging to the Agro-climatic Information System for Irrigation (SIAR, in Spanish) of the Region of Castilla and León, in Spain, through the concept of Virtual Weather Station (VWS), which is implemented with Artificial Neural Networks (ANNs). This is serving to estimate data in every point of the territory, according to their geographic coordinates (i.e., longitude and latitude). The ANNs of the Multilayer Feed-Forward Perceptron (MLP) used are daily trained, along with data recorded in 53 agro-meteorological stations, and where the validation of the results is conducted in the station of Tordesillas (Valladolid). The ANN models for daily interpolation were tested with one, two, three, and four neurons in the hidden layer, over a period of 15 days (from 1 to 15 June 2020), with a root mean square error (RMSE, MJ/m2) of 1.23, 1.38, 1.31, and 1.04, respectively, regarding the daily global solar irradiation. The interpolation of ambient temperature also performed well when applying the VWS concept, with an RMSE (°C) of 0.68 for the maximum temperature with an ANN of four hidden neurons, 0.58 for the average temperature with three hidden neurons, and 0.83 for the minimum temperature with four hidden neurons.

Not so robust: Robusta coffee production is highly sensitive to temperature.

Coffea canephora (robusta coffee) is the most heat-tolerant and 'robust' coffee species and therefore considered more resistant to climate change than other types of coffee production. However, the optimum production range of robusta has never been quantified, with current estimates of its optimal mean annual temperature range (22-30°C) based solely on the climatic conditions of its native range in the Congo basin, Central Africa. Using 10 years of yield observations from 798 farms across South East Asia coupled with high-resolution precipitation and temperature data, we used hierarchical Bayesian modeling to quantify robusta's optimal temperature range for production. Our climate-based models explained yield variation well across the study area with a cross-validated mean R2  = .51. We demonstrate that robusta has an optimal temperature below 20.5°C (or a mean minimum/maximum of ≤16.2/24.1°C), which is markedly lower, by 1.5-9°C than current estimates. In the middle of robusta's currently assumed optimal range (mean annual temperatures over 25.1°C), coffee yields are 50% lower compared to the optimal mean of ≤20.5°C found here. During the growing season, every 1°C increase in mean minimum/maximum temperatures above 16.2/24.1°C corresponded to yield declines of ~14% or 350-460 kg/ha (95% credible interval). Our results suggest that robusta coffee is far more sensitive to temperature than previously thought. Current assessments, based on robusta having an optimal temperature range over 22°C, are likely overestimating its suitable production range and its ability to contribute to coffee production as temperatures increase under climate change. Robusta supplies 40% of the world's coffee, but its production potential could decline considerably as temperatures increase under climate change, jeopardizing a multi-billion dollar coffee industry and the livelihoods of millions of farmers.

Risk of Out-of-Hospital Cardiac Arrest in Aged Individuals in Relation to Cold Ambient Temperature　- A Report From North Tochigi Experience.

BACKGROUND: The impact of cold ambient temperature on out-of-hospital cardiac arrest (OHCA) in aged individuals caused by cardiovascular events in indoor environments has not been investigated sufficiently.Methods and Results:We conducted a case-crossover study. The relationship between OHCA caused by cardiovascular events and exposure to minimum temperature <0℃ was analyzed. Conditional logistic regression analysis was performed to estimate the odds ratios for the relationship between exposure to minimum temperature <0℃ and the risk of OHCA. Between January 1, 2011, and December 31, 2015, a total of 1,452 cases of OHCA were documented, and patients were screened for enrollment. A total of 458 individuals were enrolled in this analysis, and were divided into 2 groups of 110 (elderly group: 65-74 years old) and 348 (aged group: ≥75 years old). The aged individuals had a significant increased risk of OHCA after exposure to minimum temperature <0℃ (odds ratio [OR]: 1.528, 95% confidence interval [CI] 1.009-2.315, P=0.045). Cold ambient temperature was an especially significant increased risk for OHCA occurrence for males (OR: 1.997, 95% CI 1.036-3.773, P=0.039) and during winter (OR: 2.391, 95% CI 1.312-4.360, P=0.004) in the aged group. CONCLUSIONS: Cold ambient temperature significantly affected aged individuals (≥75 years old) experiencing an OHCA caused by cardiovascular events in indoor environments.

Prediction of annual dengue incidence by hydro-climatic extremes for southern Taiwan.

Dengue is one of the most rapidly spreading mosquito-borne viral diseases in the world. An increase in the incidence of dengue is commonly thought to be a consequence of variability of weather conditions. Taiwan, which straddles the Tropic of Cancer, is an excellent place to study the relationship between weather conditions and dengue fever cases since the island forms an isolated geographic environment. Therefore, clarifying the association between extreme weather conditions and annual dengue incidence is one of important issues for epidemic early warning. In this paper, we develop a Poisson regression model with extreme weather parameters for prediction of annual dengue incidence. A leave-one-out method is used to evaluate the performance of predicting dengue incidence. Our results indicate that dengue transmission has a positive relationship with the minimum temperature predictors during the early summer while a negative relationship with all the maximum 24-h rainfall predictors during the early epidemic phase of dengue outbreaks. Our findings provide a better understanding of the relationships between extreme weather and annual trends in dengue cases in Taiwan and it could have important implications for dengue forecasts in surrounding areas with similar meteorological conditions.

Functional biogeography of angiosperms: life at the extremes.

Nonlinear relationships between species and their environments are believed common in ecology and evolution, including during angiosperms' rise to dominance. Early angiosperms are thought of as woody evergreens restricted to warm, wet habitats. They have since expanded into numerous cold and dry places. This expansion may have included transitions across important environmental thresholds. To understand linear and nonlinear relationships between angiosperm structure and biogeographic distributions, we integrated large datasets of growth habits, conduit sizes, leaf phenologies, evolutionary histories, and environmental limits. We consider current-day patterns and develop a new evolutionary model to investigate processes that created them. The macroecological pattern was clear: herbs had lower minimum temperature and precipitation limits. In woody species, conduit sizes were smaller in evergreens and related to species' minimum temperatures. Across evolutionary timescales, our new modeling approach found conduit sizes in deciduous species decreased linearly with minimum temperature limits. By contrast, evergreen species had a sigmoidal relationship with minimum temperature limits and an inflection overlapping freezing. These results suggest freezing represented an important threshold for evergreen but not deciduous woody angiosperms. Global success of angiosperms appears tied to a small set of alternative solutions when faced with a novel environmental threshold.

Bud break responds more strongly to daytime than night-time temperature under asymmetric experimental warming.

Global warming is diurnally asymmetric, leading to a less cold, rather than warmer, climate. We investigated the effects of asymmetric experimental warming on plant phenology by testing the hypothesis that daytime warming is more effective in advancing bud break than night-time warming. Bud break was monitored daily in Picea mariana seedlings belonging to 20 provenances from Eastern Canada and subjected to daytime and night-time warming in growth chambers at temperatures varying between 8 and 16 °C. The higher advancements of bud break and shorter times required to complete the phenological phases occurred with daytime warming. Seedlings responded to night-time warming, but still with less advancement of bud break than under daytime warming. No advancement was observed when night-time warming was associated with a daytime cooling. The effect of the treatments was uniform across provenances. Our observations realized under controlled conditions allowed to experimentally demonstrate that bud break can advance under night-time warming, but to a lesser extent than under daytime warming. Prediction models using daily timescales could neglect the diverging influence of asymmetric warming and should be recalibrated for higher temporal resolutions.

Earlier nesting by generalist predatory bird is associated with human responses to climate change.

Warming temperatures cause temporal changes in growing seasons and prey abundance that drive earlier breeding by birds, especially dietary specialists within homogeneous habitat. Less is known about how generalists respond to climate-associated shifts in growing seasons or prey phenology, which may occur at different rates across land cover types. We studied whether breeding phenology of a generalist predator, the American kestrel (Falco sparverius), was associated with shifts in growing seasons and, presumably, prey abundance, in a mosaic of non-irrigated shrub/grasslands and irrigated crops/pastures. We examined the relationship between remotely-sensed normalized difference vegetation index (NDVI) and abundance of small mammals that, with insects, constitute approximately 93% of kestrel diet biomass. We used NDVI to estimate the start of the growing season (SoGS) in irrigated and non-irrigated lands from 1992 to 2015 and tested whether either estimate of annual SoGS predicted the timing of kestrel nesting. Finally, we examined relationships among irrigated SoGS, weather and crop planting. NDVI was a useful proxy for kestrel prey because it predicted small mammal abundance and past studies showed that NDVI predicts insect abundance. NDVI-estimated SoGS advanced significantly in irrigated lands (ß = -1·09 ± 0·30 SE) but not in non-irrigated lands (ß = -0·57 ± 0·53). Average date of kestrel nesting advanced 15 days in the past 24 years and was positively associated with the SoGS in irrigated lands, but not the SoGS in non-irrigated lands. Advanced SoGS in irrigated lands was related to earlier planting of crops after relatively warm winters, which were more common in recent years. Despite different patterns of SoGS change between land cover types, kestrel nesting phenology shifted with earlier prey availability in irrigated lands. Kestrels may preferentially track prey in irrigated lands over non-irrigated lands because of higher quality prey on irrigated lands, or earlier prey abundance may release former constraints on other selective pressures to breed early, such as seasonal declines in fecundity or competition for high-quality mates. This is one of the first examples of an association between human adaptation to climate change and shifts in breeding phenology of wildlife.

The effect of extreme cold temperatures on the risk of death in the two major Portuguese cities.

It is well known that meteorological conditions influence the comfort and human health. Southern European countries, including Portugal, show the highest mortality rates during winter, but the effects of extreme cold temperatures in Portugal have never been estimated. The objective of this study was the estimation of the effect of extreme cold temperatures on the risk of death in Lisbon and Oporto, aiming the production of scientific evidence for the development of a real-time health warning system. Poisson regression models combined with distributed lag non-linear models were applied to assess the exposure-response relation and lag patterns of the association between minimum temperature and all-causes mortality and between minimum temperature and circulatory and respiratory system diseases mortality from 1992 to 2012, stratified by age, for the period from November to March. The analysis was adjusted for over dispersion and population size, for the confounding effect of influenza epidemics and controlled for long-term trend, seasonality and day of the week. Results showed that the effect of cold temperatures in mortality was not immediate, presenting a 1-2-day delay, reaching maximum increased risk of death after 6-7 days and lasting up to 20-28 days. The overall effect was generally higher and more persistent in Lisbon than in Oporto, particularly for circulatory and respiratory mortality and for the elderly. Exposure to cold temperatures is an important public health problem for a relevant part of the Portuguese population, in particular in Lisbon.

Historical changes in flowering phenology are governed by temperature × precipitation interactions in a widespread perennial herb in western North America.

For most species, a precise understanding of how climatic parameters determine the timing of seasonal life cycle stages is constrained by limited long-term data. Further, most long-term studies of plant phenology that have examined relationships between phenological timing and climate have been local in scale or have focused on single climatic parameters. Herbarium specimens, however, can expand the temporal and spatial coverage of phenological datasets. Using Trillium ovatum specimens collected over > 100 yr across its native range, we analyzed how seasonal climatic conditions (mean minimum temperature (Tmin ), mean maximum temperature and total precipitation (PPT)) affect flowering phenology. We then examined long-term changes in climatic conditions and in the timing of flowering across T. ovatum's range. Warmer Tmin advanced flowering, whereas higher PPT delayed flowering. However, Tmin and PPT were shown to interact: the advancing effect of warmer Tmin was strongest where PPT was highest, and the delaying effect of higher PPT was strongest where Tmin was coldest. The direction of temporal change in climatic parameters and in the timing of flowering was dependent on geographic location. Tmin , for example, decreased across the observation period in coastal regions, but increased in inland areas. Our results highlight the complex effects of climate and geographic location on phenology.

Influence of meteorological conditions on RSV infection in Portugal.

Acute viral bronchiolitis is a common cause for infant hospital admissions. Of all etiological agents, respiratory syncytial virus (RSV) is commonly the most frequent. The present study assesses relationships between atmospheric factors and RSV infections in under 3-year-old patients admitted to the Inpatient Paediatric Service of Vila Real (North of Portugal). For this purpose, (1) clinical files of children admitted with a diagnosis of acute bronchiolitis from September 2005 to December 2015 (>10 years) were scrutinised and (2) local daily temperature/precipitation series, as well as six weather types controlling meteorological conditions in Portugal, were used. Fifty-five percent of all 770 admitted children were effectively infected with a given virus, whilst 48 % (367) were RSV+, i.e. 87 % of virus-infected children were RSV+. The bulk of incidence is verified in the first year of age (82 %, 302), slightly higher in males. RSV outbreaks are typically from December to March, but important inter-annual variability is found in both magnitude and shape. Although no clear connections were found between monthly temperatures/precipitation and RSV outbreaks apart from seasonality, a linkage to wintertime cold spells is apparent on a daily basis. Anomalously low minimum temperatures from the day of admittance back to 10 days before are observed. This relationship is supported by anomalously high occurrences of the E and AA weather types over the same period, which usually trigger dry and cold weather. These findings highlight some predictability in the RSV occurrences, revealing potential for modelling and risk assessments.

Nowcasting daily minimum air and grass temperature.

Site-specific and accurate prediction of daily minimum air and grass temperatures, made available online several hours before their occurrence, would be of significant benefit to several economic sectors and for planning human activities. Site-specific and reasonably accurate nowcasts of daily minimum temperature several hours before its occurrence, using measured sub-hourly temperatures hours earlier in the morning as model inputs, was investigated. Various temperature models were tested for their ability to accurately nowcast daily minimum temperatures 2 or 4 h before sunrise. Temperature datasets used for the model nowcasts included sub-hourly grass and grass-surface (infrared) temperatures from one location in South Africa and air temperature from four subtropical sites varying in altitude (USA and South Africa) and from one site in central sub-Saharan Africa. Nowcast models used employed either exponential or square root functions to describe the rate of nighttime temperature decrease but inverted so as to determine the minimum temperature. The models were also applied in near real-time using an open web-based system to display the nowcasts. Extrapolation algorithms for the site-specific nowcasts were also implemented in a datalogger in an innovative and mathematically consistent manner. Comparison of model 1 (exponential) nowcasts vs measured daily minima air temperatures yielded root mean square errors (RMSEs) <1 °C for the 2-h ahead nowcasts. Model 2 (also exponential), for which a constant model coefficient (b = 2.2) was used, was usually slightly less accurate but still with RMSEs <1 °C. Use of model 3 (square root) yielded increased RMSEs for the 2-h ahead comparisons between nowcasted and measured daily minima air temperature, increasing to 1.4 °C for some sites. For all sites for all models, the comparisons for the 4-h ahead air temperature nowcasts generally yielded increased RMSEs, <2.1 °C. Comparisons for all model nowcasts of the daily grass and grass-surface minima yielded increased RMSEs compared to those for air temperature at 2 m. The sufficiently small RMSEs using the 2-h ahead nowcasts of the air temperature minimum, for the exponential model, demonstrate that the methodology used may be applied operationally but with increased errors for grass minimum temperature and the 4-h nowcasts.

Recent warming evidence inferred from a tree-ring-based winter-half year minimum temperature reconstruction in northwestern Yichang, South Central China, and its relation to the large-scale circulation anomalies.

High-resolution winter temperature reconstructions in China are rare, yet vital for the comprehensive understanding of past climate change. In the present work, the first winter-half year minimum mean temperature from previous November to current April in northwestern Yichang, South Central China, was reconstructed back to 1875 based on tree-ring material. The reconstruction can explain 55 % of the variance over the calibration period during 1955-2011. The temperature maintained at comparatively low level before 1958, and an abnormal warming was seen since 1959. However, the warming trend stagnated after 2000 AD. 2001-2010 was the warmest decade not only during the instrumental period but also during the whole reconstructed period. The reconstruction indicates good spatial resemblance to other temperatures series in adjacent areas and Northern Hemisphere, yet the recent warming in this study is earlier and more prominent than that of Southeast China. This work also manifests that the winter-half year minimum temperature in study area has good agreement with summer (June-September) maximum temperature variation in Southeast China at decadal scale, except that the winter-half year warming in recent decades is more evident than summer. This reconstruction is not only useful in improving our knowledge of long-term temperature variation but also useful in predicting the tree growth dynamics in the future in the study area.

The role of vegetation-microclimate feedback in promoting shrub encroachment in the northern Chihuahuan desert.

Many arid and semi-arid landscapes around the world are affected by a shift from grassland to shrubland vegetation, presumably induced by climate warming, increasing atmospheric CO2 concentrations, and/or changing land use. This major change in vegetation cover is likely sustained by positive feedbacks with the physical environment. Recent research has focused on a feedback with microclimate, whereby cold intolerant shrubs increase the minimum nocturnal temperatures in their surroundings. Despite the rich literature on the impact of land cover change on local climate conditions, changes in microclimate resulting from shrub expansion into desert grasslands have remained poorly investigated. It is unclear to what extent such a feedback can affect the maximum extent of shrub expansion and the configuration of a stable encroachment front. Here, we focus on the case of the northern Chihuahuan desert, where creosotebush (Larrea tridentata) has been replacing grasslands over the past 100-150 years. We use a process-based coupled atmosphere-vegetation model to investigate the role of this feedback in sustaining shrub encroachment in the region. Simulations indicate that the feedback allows juvenile shrubs to establish in the grassland during average years and, once established, reduce their vulnerability to freeze-induced mortality by creating a warmer microclimate. Such a feedback is crucial in extreme cold winters as it may reduce shrub mortality. We identify the existence of a critical zone in the surroundings of the encroachment front, in which vegetation dynamics are bistable: in this zone, vegetation can be stable both as grassland and as shrubland. The existence of these alternative stable states explains why in most cases the shift from grass to shrub cover is found to be abrupt and often difficult to revert.

High night temperatures during grain number determination reduce wheat and barley grain yield: a field study.

Warm nights are a widespread predicted feature of climate change. This study investigated the impact of high night temperatures during the critical period for grain yield determination in wheat and barley crops under field conditions, assessing the effects on development, growth and partitioning crop-level processes driving grain number per unit area (GN). Experiments combined: (i) two contrasting radiation and temperature environments: late sowing in 2011 and early sowing in 2013, (ii) two well-adapted crops with similar phenology: bread wheat and two-row malting barley and (iii) two temperature regimes: ambient and high night temperatures. The night temperature increase (ca. 3.9 °C in both crops and growing seasons) was achieved using purpose-built heating chambers placed on the crop at 19:000 hours and removed at 7:00 hours every day from the third detectable stem node to 10 days post-flowering. Across growing seasons and crops, the average minimum temperature during the critical period ranged from 11.2 to 17.2 °C. Wheat and barley grain yield were similarly reduced under warm nights (ca. 7% °C(-1) ), due to GN reductions (ca. 6% °C(-1) ) linked to a lower number of spikes per m(2) . An accelerated development under high night temperatures led to a shorter critical period duration, reducing solar radiation capture with negative consequences for biomass production, GN and therefore, grain yield. The information generated could be used as a starting point to design management and/or breeding strategies to improve crop adaptation facing climate change.

Climate change in Lagos state, Nigeria: what really changed?

Our study revealed periodicities of 2.3 and 2.25 years in wet and dry seasons and periodicities of 2 to 5 years on seasonal and annual timescales. Minimum temperature (Tmin), maximum temperature (Tmax) and evaporation recorded increases of 2.47, 1.37 and 28.37 %, respectively, but a reduction of 19.58 % in rainfall on decadal timescale. Periodicity of 8 to 12 years was also observed in annual Tmax. Cramer's test indicated a warming trend with significant Tmax increase in February, April, July, August, October and November during 2000-2009 on decadal monthly timescale, a significant decline in Summer rainfall but significant Tmax increase in Spring, Autumn and Winter on decadal seasonal timescale. The low correlation of rainfall with temperature parameters and evaporation indicates that advection of moisture into Lagos State seems to be the dominant mechanism controlling rainfall within the State alongside other tropical and extra-tropical factors. In addition, our study revealed that the persistent state of minimum temperature often precedes the arrival and reversal of the phase of maximum temperature. Furthermore, our study also revealed that extreme and high variable rainfalls, which are associated with the increased warming trend, had periodicities of 1 to 3 years with a probability of 86.45 % of occurring every 3 years between April and September. It is recommended that government and private sector should give financial and technical supports to climate researches in order to appropriately inform policy making to improve the adaptive capacity and resilience of Lagos State against climate change impacts and guard against maladaptation.