Maximum Summer Temperatures Research Articles

Interplay of temperature and woody cover shapes herb communities along an elevational gradient in a temperate forest in Beijing, China

Abiotic and biotic factors have the potential to alter herb communities, however, few studies consider feedback between them. This study explores how variation of species interaction and climatic conditions associated with changes in altitude affect herb community composition. We sampled accumulated temperatures of growth duration (June-November) (ATGD), maximum summer temperatures (MST) and herb community composition (herb height, abundance, richness) on non-gaps and forest-gaps site across an elevational gradient. A significant negative relationship was detected between MST and herb richness. The temperature of non-gaps was cooler than that of forest gaps, and overstory cover positively correlated with herb abundance. However, the ATGD exhibited a negative relationship with overstory cover, in that overstory cover decreased with ATGD. We suggested that temperature has a profound effect on height and richness of herb communities, while the overstory cover is moderating the effect of temperature on herb community structure and influence the abundance of herb community. Conversely, decreases in ATGD weakened the relative importance of overstory cover. We concluded that the interaction of temperature and overstory cover shapes the morphology, abundance and richness of herb communities.

Are American Pikas (<em>Ochotona princeps</em>) in the Canadian Rockies vulnerable to climate change?

The American Pika (Ochotona princeps) is vulnerable to climate change as a result of its dependence on cool, moist conditions. Most research on climatic determinants of American Pika distribution has been done in the United States where conditions are different from those in the higher-latitude pika ranges of the Canadian Rockies. I examined recent (1980–2009) and future (2050s and 2080s) average and maximum mean summer temperatures for 114 current American Pika locations in Alberta to assess whether future conditions are likely to place these animals at risk. At all current sites, mean summer temperatures (MSTs) in the 2050s are expected to be below that chosen by the United States Fish and Wildlife Service as a threshold for at-risk status of O. princeps. By the 2050s, most current American Pika locations have sufficient elevation within 5 km to allow individuals to migrate vertically to reach habitat with MST similar to that of their current location. Even in the 2080s, almost all current sites have sufficient elevation within 5 km to maintain extreme single-year and average MSTs lower than the highest values recorded at those sites in the recent past (13.9°C and 12.5°C respectively). However, by the 2080s under an extreme greenhouse gas emissions scenario, only 34% of current pika sites will allow for such migration. Although considerable uncertainty remains, particularly with respect to availability of habitat, these results suggest that American Pika populations in Alberta will likely be capable of persisting throughout this century, although their survival will depend increasingly on successful vertical migration.

Projected changes in extreme temperature events based on the NARCCAP model suite

AbstractOnce‐per‐year (annual) maximum temperature extremes in North American Regional Climate Change Assessment Program (NARCCAP) models are projected to increase more (less) than mean daily maximum summer temperatures over much of the eastern (western) United States. In contrast, the models almost everywhere project greater warming of once‐per‐year minimum temperatures as compared to mean daily minimum winter temperatures. Under projected changes associated with extremes of the temperature distribution, Baltimore's maximum temperature that was met or exceeded once per year historically is projected to occur 17 times per season by midcentury, a 28% increase relative to projections based on summer mean daily maximum temperature change. Under the same approach, historical once‐per‐year cold events in Baltimore are projected to occur once per decade. The models are generally able to capture observed geopotential height anomalies associated with temperature extremes in two subregions. Projected changes in extreme temperature events cannot be explained by geopotential height anomalies or lower boundary conditions as reflected by soil moisture anomalies or snow water equivalent.

Thermal refugia in cleared temperate Australian woodlands: Coarse woody debris moderate extreme surface soil temperatures

Extensive tree clearing and agriculture has exposed surface soils of former Australian temperate woodlands to more extreme temperature fluctuations. Given the highly variable climate in these regions, and increasing temperature overall, amelioration of extreme surface soil temperatures would have implications for soil-dependent biological activity. Reintroduction of coarse woody debris (CWD) to these woodlands may moderate surface soil temperatures. Diurnal surface soil temperatures at a depth of 2.5cm were monitored during summer and winter at different distances from CWD with varying diameters. CWD samples were located beyond the edge of neighbouring tree canopies. The result of the initial analysis showed that CWD reduced the durations of time at extremely high summer and low winter surface soil temperatures. Soil temperatures near CWD were largely maintained below the summer high of 30°C and above the winter low of 5°C. The duration of time above 30°C in summer was reduced by 93% near CWD and the duration of time below 5°C in winter was reduced by 77%, compared with reference distances. Simple nonlinear statistical models were developed to explain the observed daily summer maximum and winter minimum surface soil temperatures as functions of distance from CWD and CWD diameter. The forms of these models reflected different dominant physical processes in each season. Mean summer daily maximum surface soil temperatures were significantly cooler by 11.1°C and mean winter daily minimum temperatures were significantly warmer by 1.9°C near CWD compared to the respective mean maximum and minimum temperatures at reference distances. Increasing CWD diameter increased the range of the impact over distance from CWD in both summer and winter. During the summer maxima, larger diameter CWD also increased the magnitude of the reduction in surface soil temperature near CWD. The results of this study demonstrate that CWD can be effective in protecting surface soils from sustained exposure to extreme surface soil temperatures. Therefore, at a landscape scale, CWD could create thermal refuges better suited to soil-dependent biological activity, such as for the germination and growth of the plant understorey in woodlands. This impact of CWD may be valuable for supporting understorey productivity and diversity in cleared lands.

Relationship between the summer NAO and maximum temperatures for the Iberian Peninsula

The Summer North Atlantic Oscillation (SNAO) index is strongly linked to temperatures in the north and west of Europe although it also has a weaker relationship of an opposite sign with the temperature of the eastern Mediterranean area. The objective of this work is to determine if it is possible to find a relationship between the SNAO and daily maximum temperatures (Tx) in the Iberian Peninsula (IP) for the months of July and August. The correlation between the SNAO and the daily maximum temperatures in the IP is very weak, except for a part of the southeast of the IP and a region in the northwest of the IP where we found statistically significant correlations with opposite signs for both regions. We found that the Tx distribution of the NW region (TxNW) shows positive correlations with the SNAO as is the case with Northern Europe, while in the case of the SE region (TxSE) this distribution shows negative correlations similar to those seen in Italy and the Balkans. We found a strong relationship between the difference TxNW-TxSE and SNAO: when the SNAO is high, the absolute value of TxNW-TxSE is significantly lower (gentler Tx gradient) than average, and the opposite occurs when the SNAO is low (steeper Tx gradient). We also found that the strong increase in the SNAO from the late-1960s until the mid-1980s is reflected in the asymmetric Tx trends of the NW and SE of the IP: while the SNAO was rising, the absolute value of the difference TxNW-TxSE dropped significantly.

Spatio-temporal analysis of warming in Bangladesh using recent observed temperature data and GIS

This study focused on the annual and seasonal warming at local scale by analysing the trends, anomalies, change points and shifting of isotherm in temperature from 34 meteorological stations distributed over Bangladesh, spanning 40 years from the year 1971–2010. For trends, a linear regression using least square model was applied. Anomalies were calculated as a difference between the reference (1971–2000 mean) and actual occurrence value. Inverse distance weighted interpolation and GIS techniques were used to find out the spatial pattern of warming. Besides, the sequential version of the Mann–Kendall test was applied to detect the changing point of warming. Direction of shifting of warming was detected by the decadal distribution pattern of specific isotherms which were generated using GIS. The result reveals that the climate of Bangladesh undergone a significant warming during the period 1971–2010, 0.020 °C per year (for annual mean) and the maximum temperature warmed more than the minimum temperature (0.022 vs. 0.018 °C per year). On a seasonal basis, hot summer, humid summer and dry winter also show significant warming, 0.022, 0.026 and 0.011 °C per year, respectively. The warming of maximum temperature (0.032 °C per year) in humid summer was greater than other seasons, contributed more on annual warming. Spatial patterns indicate that geographically the warming varied significantly and some places warming exit 2.0 °C and reached up to 3.2 °C. The north western, north eastern, southern and south eastern parts of the country are more susceptible to rising temperature. In 2010, mean annual temperature was 0.84 °C warmer than the base period (1971–2000) mean. The significant warmest period was spread across the year 1995–2010, with 2010 being the warmest year. Statistically significant warming was began in early 1990’s and the years 1990, 1994 and 1997 identified as important abrupt change points of warming. Moreover, a remarkably northward and north eastward warming was identified, denoting the north, north western and north eastern belts of the country are more susceptible to the warming. Praiseworthy of note, Bangladesh is indeed warming strongly and warming pattern is broadly consistent with the existing global warming.

Landscape genomics of Sphaeralcea ambigua in the Mojave Desert: a multivariate, spatially-explicit approach to guide ecological restoration

Local adaptation influences plant species’ responses to climate change and their performance in ecological restoration. Fine-scale physiological or phenological adaptations that direct demographic processes may drive intraspecific variability when baseline environmental conditions change. Landscape genomics characterize adaptive differentiation by identifying environmental drivers of adaptive genetic variability and mapping the associated landscape patterns. We applied such an approach to Sphaeralcea ambigua, an important restoration plant in the arid southwestern United States, by analyzing variation at 153 amplified fragment length polymorphism loci in the context of environmental gradients separating 47 Mojave Desert populations. We identified 37 potentially adaptive loci through a combination of genome scan approaches. We then used a generalized dissimilarity model (GDM) to relate variability in potentially adaptive loci with spatial gradients in temperature, precipitation, and topography. We identified non-linear thresholds in loci frequencies driven by summer maximum temperature and water stress, along with continuous variation corresponding to temperature seasonality. Two GDM-based approaches for mapping predicted patterns of local adaptation are compared. Additionally, we assess uncertainty in spatial interpolations through a novel spatial bootstrapping approach. Our study presents robust, accessible methods for deriving spatially-explicit models of adaptive genetic variability in non-model species that will inform climate change modelling and ecological restoration.

Spatial clustering of summer temperature maxima from the CNRM-CM5 climate model ensembles & E-OBS over Europe

Reducing the dimensionality of the complex spatio-temporal variables associated with climate modeling, especially ensembles of climate models, is a challenging and important objective. For studies of detection and attribution, it is especially important to maintain information related to the extreme values of the atmospheric processes. Typical methods for data reduction involve summarizing climate model output information through means and variances, which does not preserve any information about the extremes. In order to help solve this challenge, a dependence summary measure appropriate for extreme values must be inferred. Here, we adapt one such measure from a recent study to a larger domain with a different variable and gridded data from observations and climate model ensembles, i.e. E-OBS observations and the CNRM-CM5 model. The handling of such ensembles of data is proposed, as well as a comparison of the spatial clusterings between two different ensembles, here a present-day and a future ensemble of climate simulations. This method yields valid information concerning extremes, while greatly reducing the data set.

Lean‐season primary productivity and heat dissipation as key drivers of geographic body‐size variation in a widespread marsupial

Geographic body‐size variation characterises many mammal species. Hypotheses centring around heat conservation, heat dissipation, primary productivity and seasonality have been advanced to explain geographic body‐size patterns. However, identification of the primary body‐size drivers has often been hampered by a paucity of data for broadly distributed species and the application of regression models that have not explicitly accounted for the spatial clustering inherent in such datasets. We used Australia's most widespread marsupial, the common brushtail possum Trichosurus vulpecula, as a model species with which to test five proposed drivers of geographic body‐size variation. Using geo‐referenced skull measurements from 588 specimens and a suite of putative environmental covariates, we employed spatial simultaneous autoregressive models, together with information criteria, to evaluate these different hypotheses. Our analysis identified a strong, positive relationship between possum body size and primary productivity during the least productive season, whereas the relationship with mean annual productivity received less support. Consistent with the heat‐dissipation hypothesis, T. vulpecula body size also decreased with increasing mean summer maximum temperature. Spatial autoregression coefficients estimated from the simultaneous autoregressive models were always high, suggesting that additional abiotic or biotic factors might contribute to the spatial patterns observed. We argue that the analysis of geographic body‐size variation should consider multi‐causal possibilities rather than treating the numerous hypotheses as competing, mutually exclusive alternatives.

Global analysis of seasonality in the shell flux of extant planktonic Foraminifera

Abstract. Shell fluxes of planktonic Foraminifera species vary intra-annually in a pattern that appears to follow the seasonal cycle. However, the variation in the timing and prominence of seasonal flux maxima in space and among species remains poorly constrained. Thus, although changing seasonality may result in a flux-weighted temperature offset of more than 5° C within a species, this effect is often ignored in the interpretation of Foraminifera-based paleoceanographic records. To address this issue we present an analysis of the intra-annual pattern of shell flux variability in 37 globally distributed time series. The existence of a seasonal component in flux variability was objectively characterised using periodic regression. This analysis yielded estimates of the number, timing and prominence of seasonal flux maxima. Over 80% of the flux series across all species showed a statistically significant periodic component, indicating that a considerable part of the intra-annual flux variability is predictable. Temperature appears to be a powerful predictor of flux seasonality, but its effect differs among species. Three different modes of seasonality are distinguishable. Tropical and subtropical species (Globigerinoides ruber (white and pink varieties), Neogloboquadrina dutertrei, Globigerinoides sacculifer, Orbulina universa, Globigerinella siphonifera, Pulleniatina obliquiloculata, Globorotalia menardii, Globoturborotalita rubescens, Globoturborotalita tenella and Globigerinoides conglobatus) appear to have a less predictable flux pattern, with random peak timing in warm waters. In colder waters, seasonality is more prevalent: peak fluxes occur shortly after summer temperature maxima and peak prominence increases. This tendency is stronger in species with a narrower temperature range, implying that warm-adapted species find it increasingly difficult to reproduce outside their optimum temperature range and that, with decreasing mean temperature, their flux is progressively more focussed in the warm season. The second group includes the temperate to cold-water species Globigerina bulloides, Globigerinita glutinata, Turborotalita quinqueloba, Neogloboquadrina incompta, Neogloboquadrina pachyderma, Globorotalia scitula, Globigerinella calida, Globigerina falconensis, Globorotalia theyeri and Globigerinita uvula. These species show a highly predictable seasonal pattern, with one to two peaks a year, which occur earlier in warmer waters. Peak prominence in this group is independent of temperature. The earlier-when-warmer pattern in this group is related to the timing of productivity maxima. Finally, the deep-dwelling Globorotalia truncatulinoides and Globorotalia inflata show a regular and pronounced peak in winter and spring. The remarkably low flux outside the main pulse may indicate a long reproductive cycle of these species. Overall, our analysis indicates that the seasonality of planktonic Foraminifera shell flux is predictable and reveals the existence of distinct modes of phenology among species. We evaluate the effect of changing seasonality on paleoceanographic reconstructions and find that, irrespective of the seasonality mode, the actual magnitude of environmental change will be underestimated. The observed constraints on flux seasonality can serve as the basis for predictive modelling of flux pattern. As long as the diversity of species seasonality is accounted for in such models, the results can be used to improve reconstructions of the magnitude of environmental change in paleoceanographic records.

Climate‐related spatial and temporal variation in bill morphology over the past century in Australian parrots

AbstractAimAllen's rule posits that the appendages of endothermic organisms will be larger in warmer climates to allow for dumping of heat loads. Given a link between appendage size and climate, we tested the prediction that climate change has driven the evolution of larger bills in birds, resulting in measurable changes over the recent past.LocationAustralia.MethodsWe explored geographical and temporal variation in bill surface area of five Australian parrot species to determine whether individuals from warmer climates have larger bills, and whether there have been increases in bill surface area over time, consistent with climatic warming. Measurements were obtained from museum specimens dating from 1871 to 2008. These data were then related to geographical location, collection date and locality‐specific climate data, in order to construct and compare models of spatio‐temporal and climate‐related variation in bill morphology.ResultsThere have been increases in bill surface area in mulga parrots (Psephotus varius), gang‐gang cockatoos (Callocephalon fimbriatum), red‐rumped parrots (Psephotus haematonotus) and male crimson rosellas (Platycercus elegans), equating to a c. 4–10% increase in bill surface area since 1871. Average maximum summer temperature in the 5 years prior to specimen collection also positively predicted bill surface area in mulga parrots, red‐rumped parrots and crimson rosellas, consistent with Allen's rule. With the exception of red‐rumped parrots, however, models with geographical location and year of collection were still better predictors of bill surface area than local climate at the date of collection.Main conclusionsOur analysis provides evidence that four species of parrot have exhibited adaptive change in bills over the past century potentially mitigating the thermal stress caused by climatic warming. Although consistent with the predicted effects of climate change, the temporal patterns we observe may have additional causes, however, such as changes in primary productivity, habitat or food availability.

Genetic diversity is related to climatic variation and vulnerability in threatened bull trout.

Understanding how climatic variation influences ecological and evolutionary processes is crucial for informed conservation decision-making. Nevertheless, few studies have measured how climatic variation influences genetic diversity within populations or how genetic diversity is distributed across space relative to future climatic stress. Here, we tested whether patterns of genetic diversity (allelic richness) were related to climatic variation and habitat features in 130 bull trout (Salvelinus confluentus) populations from 24 watersheds (i.e., ~4-7th order river subbasins) across the Columbia River Basin, USA. We then determined whether bull trout genetic diversity was related to climate vulnerability at the watershed scale, which we quantified on the basis of exposure to future climatic conditions (projected scenarios for the 2040s) and existing habitat complexity. We found a strong gradient in genetic diversity in bull trout populations across the Columbia River Basin, where populations located in the most upstream headwater areas had the greatest genetic diversity. After accounting for spatial patterns with linear mixed models, allelic richness in bull trout populations was positively related to habitat patch size and complexity, and negatively related to maximum summer temperature and the frequency of winter flooding. These relationships strongly suggest that climatic variation influences evolutionary processes in this threatened species and that genetic diversity will likely decrease due to future climate change. Vulnerability at a watershed scale was negatively correlated with average genetic diversity (r=-0.77; P<0.001); watersheds containing populations with lower average genetic diversity generally had the lowest habitat complexity, warmest stream temperatures, and greatest frequency of winter flooding. Together, these findings have important conservation implications for bull trout and other imperiled species. Genetic diversity is already depressed where climatic vulnerability is highest; it will likely erode further in the very places where diversity may be most needed for future persistence.

Assessing tree-ring carbon and oxygen stable isotopes for climate reconstruction in the Canadian northeastern boreal forest

Abstract In this study, we analyzed stable isotopes of oxygen (δ18O) and carbon (δ13C) of five black spruce (Picea mariana (Mill.) BSP) trees growing in the Quebec boreal forest. We then produced the first dendroisotopic series covering the last two centuries (1800–2003) for this region where climatic records are particularly scarce and of short duration. Our aim was to evaluate the isotope sensitivity to climate and their potential as proxies for past climate conditions. The δ18O results show a strong coherence between all trees indicating that these values express a homogenous response at the site scale. For the δ13C series, slight inter-tree differences suggest the influence of micro-site conditions. Isotopic values were compared to climatic data for the period 1944–2003. These statistical analyses indicate that the δ13C and δ18O ratios are directly influenced by summer maximum temperatures but also correlate with parameters that integrate temperatures and moisture status. In all cases, the climate effects on δ13C values are weaker than the ones recorded by the δ18O series. Moreover, because the δ18O and δ13C values are sensitive to climatic variables that are linked and commonly associated in typical subarctic climate ambiances (warm-dry, cold-wet), the patterns of their joint response show stronger correlations with climatic parameters. Then, a temperature reconstruction was developed based on a regression model that calibrates the combined δ13C and δ18O series against summer maximum temperature (TmaxJJA). The reconstructed summer temperatures indicates that the first half of the 19th century was the coldest period in the past 200 years and that a steadily change throughout milder conditions started in the early 1940's. These trends are consistent with other reconstructed values from independent proxies available for the same region. This research confirms that C and O dendroisotopic series of black spruce trees in high latitudes can document adequately past climatic conditions.

Testing the use of viscous remanent magnetisation to date flood events

Using erratics associated with large flood events, this paper assesses whether their viscous remanent magnetisation (VRM) can be used to date the flood events. We tested this method using flood erratics from three large events: (1) the Late Pleistocene Bonneville mega-flood in Idaho, USA, (~14-18 ka), (2) the 1918 A.D. Mt. Katla, Iceland, eruption and associated jokulhaup (meltwater flood) at Mýrdalssandur, and (3) the Markarfljot jokulhaup due to an earlier eruption of Mt. Katla (~2.5 ka). We measured 236 specimens, 66 of which yielded clear identifiable and measurable viscous magnetisation signals from erratics with clustered VRM directions. From the VRM unblocking temperatures, age estimates were made. The age estimate for the most recent event (Mýrdalssandur) worked well, with a median estimated age of 80 years (with individual erratic estimates distributed between 61 – 105 years) compared to the known age of 91 years. The ages of the other two events were over-estimated. The estimates for Markarfljot (15 ka (7 – 33 ka)) were based on the results of just one erratic. For the Bonneville flood the estimates were too old, however, this locality had the largest uncertainty in the ambient temperature used in the age determination; the VRM acquired is strongly dependent on the ambient temperature, the older the event the greater the uncertainty. Southern Idaho currently has hot summers, with average summer maximum temperatures of ~31 ˚C, but a mean annual temperature of only ~ 9 ˚C. It is suggested that the VRM dating method works best for recent events (< 2-3 ka) where the ambient temperature history can be constrained.

Recent changes in Georgia׳s temperature means and extremes: Annual and seasonal trends between 1961 and 2010

Sixteen temperature minimum and maximum series are used to quantify annual and seasonal changes in temperature means and extremes over Georgia (Southern Caucasus) during the period 1961 and 2010. Along with trends in mean minimum and maximum temperature, eight indices are selected from the list of climate extreme indices as defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) of the Commission for Climatology of the World Meteorological Organization (WMO), for studying trends in temperature extremes. Between the analysis periods 1961–2010, 1971–2010 and 1981–2010 pronounced warming trends are determined for all Georgia-averaged trends in temperature means and extremes, while all magnitudes of trends increase towards the most recent period. During 1981 and 2010, significant warming trends for annual minimum and maximum temperature at a rate of 0.39°C (0.47°C) days/decade and particularly for the warm temperature extremes, summer days, warm days and nights and the warm spell duration index are evident, whereas warm extremes show larger trends than cold extremes. The most pronounced trends are determined for summer days 6.2 days/decade, while the warm spell duration index indicates an increase in the occurrence of warm spells by 5.4 days/decade during 1981 and 2010. In the comparison of seasonal changes in temperature means and extremes, the largest magnitudes of warming trends can be observed for temperature maximum in summer and temperature minimum in fall. Between 1981 and 2010, summer maximum temperature shows a significant warming at a rate of 0.84°C/decade, increasing almost twice as fast as its annual trend (0.47°C/decade). The Georgia-averaged trends for temperature minimum in fall increase by 0.59°C/decade. Strongest significant trends in temperature extremes are identified during 1981 and 2010 for warm nights (4.6 days/decade) in summer and fall as well as for warm days (5.6 days/decade) in summer. Analyses demonstrate that there have been increasing warming trends since the 1960s, particularly for warm extremes during summer and fall season, accompanied by a constant warming of temperature means in Georgia.

Climatic effects on sugarcane productivity in India: a stochastic production function application

The present study estimates the influence of climatic and non-climatic factors on mean yield and yield variability of sugarcane crop in different weather seasons (e.g., rainy, winter and summer) in India. Sugarcane mean-yield for fourteen major sugarcane growing states from different agro-ecological zones are delimitated in panel data during 1971-2009. Regression coefficient for mean yield and yield variability production function (i.e. risk increasing or decreasing inputs) has been estimated through log-linear regression model with the help of Just and Pope (stochastic) production function specification. Empirical results based on feasible generalise least square (FGLS) estimations shows a significant effect of rainfall, maximum and minimum temperatures on sugarcane mean yield and yield variability. Whereas, average maximum temperature in summer and average minimum temperature in rainy season have a negative and statistically significant impact on sugarcane mean yield. Sugarcane mean yield positively gets affected with average maximum temperature during rainy and winter season.

The Variability of Seasonal and Annual Extreme Temperature Trends of the Latest Three Decades in Romania

Abstract In the latest IPCC report (2014) it was estimated that since the mid-20th century, the number of cold days and nights has decreased and the number of warm days and nights has increased in large parts of Europe. Some recent analyses have found that mean summer maximum temperature change over Europe was +1.6 ± 0.4 °C during 1880 to 2005. It seems that human influence has contributed to the observed global scale changes in the frequency and intensity of daily temperature extreme. The objective of this work was to identify spatial variations of the seasonal and annual extreme temperature variability and trends over Romania in the period 1985-2014. Starting with a large climatological database (30 years of daily data for 29 locations from Romania), daily minimum, maximum and amplitude temperature data were condensed into normal probability functions for which the assumption of normal distribution was accepted by the Shapiro-Wilk statistical test. These functions were then used to calculate the appearance probability of annual and monthly temperatures values. Temperatures which appear with different probabilities all year long were computed with “NORMDIST” function from Microsoft Office Excel. Based on these values data thematic maps were generated with isolines drawn by geo-statistical interpolation (kriging method of Surfer®, Golden Software, 2012). Comparing the increasing trend per decade expressed by probabilities, we found that the minimum temperature had almost the same rate (21.6% in a decade) as the maximum ones (21.0% in a decade) and mean daily temperature amplitude remained unchanged from 1985 to 2014. We identified the presence of an increased variability of annual mean temperature trends between the different climatological stations. It was noted that the level of statistical significance of maximum and minimum temperature linear trends per decade was low during winter, spring and autumn. But this level of significance was very high for June, July and August months.

Daily temperature changes and variability in ENSEMBLES regional models predictions: Evaluation and intercomparison for the Ebro Valley (NE Iberia)

We employ a suite of regional climate models (RCMs) to assess future changes in summer (JJA) maximum temperature (Tmax) over the Ebro basin, the largest hydrological division in the Iberian Peninsula. Under the A1B emission scenario, future changes in both mean values and their corresponding time varying percentiles were examined by comparing the control period (1971–2000) with two future time slices: 2021–2050 and 2071–2100. Here, the rationale is to assess how lower/upper tails of temperature distributions will change in the future and whether these changes will be consistent with those of the mean. The model validation results demonstrate significant differences among the models in terms of their capability to representing the statistical characteristics (e.g., mean, skewness and asymmetry) of the observed climate. The results also indicate that the current substantial warming observed in the Ebro basin is expected to continue during the 21st century, with more intense warming occurring at higher altitudes and in areas with greater distance from coastlines. All models suggest that the region will experience significant positive changes in both the cold and warm tails of temperature distributions. However, the results emphasize that future changes in the lower and upper tails of the summer Tmax distribution may not follow the same warming rate as the mean condition. In particular, the projected changes in the warm tail of the summer Tmax are shown to be significantly larger than changes in both mean values and the cold tail, especially at the end of the 21st century. The finding suggests that much of the changes in the summer Tmax percentiles will be driven by a shift in the entire distribution of temperature rather than only changes in the central tendency. Better understanding of the possible implications of future climate systems provides information useful for vulnerability assessments and the development of local adaptation strategies for multi-disciplinary investigations.

Thermotherapy for HLB Management - Historical perspective, anecdotal evidences, and recent research progress

Although Asian type HLB is regarded as heat-tolerant, our literature review and analysis of climate data suggest that high summer temperature appears to restrict HLB distribution and occurrence. HLB worldwide distribution and severity appear to be impacted by high summer temperature - HLB is the most severe in the subtropical and tropical regions with moderate summer temperature maxima. Florida in the US, São Paulo in Brazil, Guangdong in China, and severe HLB occurrence regions share this climate characteristic.

Influence of thermal regime and land use on benthic invertebrate communities inhabiting headwater streams exposed to contrasted shading

Headwaters account for a high proportion of total freshwater stream-channel length in a drainage basin and are critical habitats for rare, endangered, and specialized species. In the context of climate warming, increasing water temperatures may be an ultimate threat to cold-adapted species even in temperate ecosystems. Climate change effects on streams may interact with other pressures such as pollution or habitat fragmentation, confounding their real impact on biological communities.Three headwater streams exposed to contrasted shading and land use conditions were sampled over a three-year period in spring and autumn (2010–2012). Five stations distributed along the longitudinal continuum were chosen in the upstream part of each stream. In addition to benthic invertebrate sampling, water temperature was recorded continuously using data loggers.Results showed that the riparian woodland associated with forested land use throughout the catchment clearly moderated winter temperature minima, summer temperature maxima and thermal variability compared to open river channels with narrow or absent riparian tree cover. Although, the variability in macroinvertebrate species distribution was mainly attributed to anthropogenic land use in the catchment, a significant part of the variability was explained by temperature descriptors such as the number of cumulative degree-days in summer and extremes in winter temperature. Trichoptera species preferring headwaters and cold water temperatures were found exclusively in the forested unimpacted stream. Conservation issues are discussed in relation to the predicted loss of the potential future distributions of these Trichoptera cold-adapted species.