Quantifying the response of surface urban heat island to urbanization using the annual temperature cycle model

Urban heat island(UHI),driving by urbanization,plays an important role in urban sustainability under climate change.However,the quantification of UHI’s response to urbanization is still challenging due to the lack of robust and continuous temperature and urbanization datasets and reliable quantification methods.This study proposed a framework to quantify the response of surface UHI(SUHI)to urban expansion using the annual temperate cycle model.We built a continuous annual SUHI series at the buffer level from 2003 to 2018 in the Jing-Jin-Ji region of China using MODIS land surface temperature and imperviousness derived from Landsat.We then investigated the spatiotemporal dynamic of SUHI under urban expansion and examined the underlying mechanism.Spatially,the largest SUHI interannual variations occurred in suburban areas compared to the urban center and rural areas.Temporally,the increase in SUHI under urban expansion was more significant in daytime compare to nighttime.We found that the seasonal variation of SUHI was largely affected by the seasonal variations of vegetation in rural areas and the interannual variation was mainly attributed to urban expansion in urban areas.Additionally,urban greening led to the decrease in summer daytime SHUI in central urban areas.These findings deepen the understanding of the long-term spatiotemporal dynamic of UHI and the quantitative relationship between UHI and urban expansion,providing a scientific basis for prediction and mitigation of UHI.

Average Annual Temperature Changes in the Holocene in China

Abstract: In 1876 Blytt proposed a post-glacial climatic classification, maintaining that the then temperature fluctuated 1–2°C higher or lower than that today. Lamb (1969) held that in Europe “the axis of the subtropical high pressure belt was generally displaced north by about 10° latitudes” during the Hypsithermal and that the temperature was three to six times higher than that in the postglacial period.

Asymmetric Mean Annual Temperature Wavelets Surface Air Layer of Berlin for 1701-2021

The regularities of the dynamics of the average annual temperature of Ber­lin from 1701 to 2021 are revealed.A total of 65 wavelets were received.The temperature has a high quantum certainty,and the change in the aver­age annual temperature of Berlin was identified by a model that contains only two components for prediction.The basis of the forecast at 320 years makes it possible to look into the future until the year 2340.The forecast confirms the conclusions made in the CMIP5 report on global warming.With an increase in the number of components in the model up to five,the forecast is possible only until 2060.Therefore,the model with only two components is workable.The trend is characterized by a modified Man­delbrot equation showing exponential growth with a high growth rate of 1.47421.The wave equation also has an amplitude in the form of the Man­delbrot law(in mathematics,the Laplace law,in biology,the Zipf-Pearl law,in econometrics,the Pareto law),when the exponential growth activity is equal to 1.For 1701,the period of oscillation was 2×60.33333≈120.7 years.By 2021,the period decreased and became equal to 87.6 years.The trend is such that by 2340 the period of oscillation will decrease to 30.2 years.Such an increase in fluctuations indicates an imbalance in climate disturbances in temperature in Berlin.For Berlin,the last three years are characterized by sharp decreases in the average annual temperature from 11.8℃ to 10.5℃,i.e.by 12.4% in 2021.Therefore,the forecast is still unstable,as a further decrease in the average annual temperature of Berlin in the near future may change the picture of the forecast.

SEASONAL AND ANNUAL TEMPERATURE VARIATIONS SINCE 1470 AD IN EAST CHINA

The ten-year mean anomalies of seasonal and annual temperatures were reconstructed on the basis of historical documents of cold events such as severe snowing and freezing of lakes and rivers.The assorted events were calibrated with instrumental observations of temperature and transformed into ten-year mean anomalies. The reconstructed temperature series show predominance of cold climate in the first four hundred years of the period examined.The centenary seasonal temperature anomalies for the 16th to the 19th century vary between -0.1 and -0.7K.The coldest decades concentrated in the middle of 17th and 19th centuries.It provided the irrefutable evidence of the occurrence of the Little Ice Age in China.The minima of ten-year mean temperature anomalies ranged about -1.5 to 2.0K in spring and winter.Meanwhile,the variance of ten-year mean tempera- ture was increased by more than 20％ in comparison to the 20th century.

Quantum Biophysics of the Atmosphere: Factor Analysis of the Annual Dynamics of Maximum, Minimum and Average Temperatures from 1879 to 2017 to Hadley English Temperature Center (Hadcet)

Factor analysis of annual dynamics from 1879 to 2017 was carried out by the method of identification of stable regularities:maximum,minimum and average air temperature of Central England according to HadCET.The sample capacity was 139 rows.In factor analysis,time is excluded,and it acts only as a system-forming factor that ensures the relationship between the three parameters of climate and weather.Therefore,the ade­quacy of the dynamics models is taken into account in the diagonal cells of the correlation matrix.In addition to time,different lists of objects are possible in factor analysis.The coefficient of correlation variation,that is,a measure of the functional relationship between the parameters of the system(annual weather at the weather station in Central England)is 0.8230 for trends,0.8603 taking into account the annual dynamics of the four-membered model obtained from the computational capabilities of the software environment CurveExpert-1.40,and 0.9578 for the full up to the error of measurement wavelet analysis of the dynamics of the values of three factors.In all three methods of factor analysis,the meteorolog­ical parameter«average Annual temperature»was in the first place as the influencing variable,the«Maximum temperature»was in the second place,and the«Minimum temperature»was in the third place.As the dependent measure in these areas there are three kinds of temperature.The comparison shows that among the binary relations between the three temperatures,the average temperature on the maximum air temperature in the surface layer of the atmosphere has the greatest influence on the correlation coefficient 0.9765.At the same time,all six equations refer to strong connections,so there is a high quantum certainty between the three types of temperature.But when predicting the most meaningful essence showed the maximum temperature.

Quantum Biophysics of the Atmosphere:Asymmetric Wavelets of the Average Annual Air Temperature of Irkutsk for 1820-2019

The regularities of the dynamics of the average annual temperature of Irkutsk from 1820 to 2019 were revealed.It is proposed to use the sum of temperatures.However,this indicator requires the continuity of the dynamic series,so for Irkutsk the sum of temperatures could be accepted only from 1873.The first three terms of the general wavelet model gave a very high correlation coefficient of 0.9996.The second indicator is a moving average,calculated as the ratio of the sum of temperatures to the current time.Here the first three wavelets gave a correlation coefficient of 0.9962.In the dynamics of the average annual temperature from 1820 to 2019,86 wavelets were obtained,of which 47 affect the future.The temperature has a high quantum certainty,and the change in the average annual temperature of Irkutsk is obtained up to a measurement error of 0.05℃,and the identification process occurs as a full wavelet analysis.The basis of the forecast in 200 years makes it possible to replace the non-linear two-term trend with an oscillatory perturbation.With an increase in the number of terms in the model,the ordinate of the average annual temperature increases:for three terms,the temperature interval is from-2.95℃ to 2.61℃;for 12 members from -4.06℃ to 4.02°C;for the forecast for 47 members for 2020-2220,from -4.62℃ to 4.40°C.

Temporal and spatial variation of annual mean air temperature in arid and semiarid region in northwest China over a recent 46 year period

We analyzed the 1961-2006 mean surface air temperature data of 138 stations in China’s northwest arid and semi-arid areas(CNASA),to measure climate change in terms of annual mean air temperature changes.We used methods of linear regression analysis,multinomial fitting,Empirical Or-thogonal Function(EOF),Rotated Empirical Orthogonal Function(REOF),Mann-Kendall,Glide T-examination,wavelet analysis and power spectrum analysis.The results show that(1) the warming rate of the annual mean air temperature in CNASA was 0.35oC/10a during the 1961-2006 study period.Some places in the west part of Xinjiang and east part of the Qinghai plateau,which is impacted by the terrain of leeward slope,exhibit smaller increasing trends.However,the majority of region has shown distinct warming in line with general global warming;(2) The standard deviation of the annual mean temperature distribution is non-uniform.The south Xinjiang and east Qinghai-south Gansu areas show relatively small standard deviations,but the inter-annual variation in annual mean air temperature in the greater part of the region is high;(3) Inner Mongolia,Shaanxi,Gansu,Ningxia and Tarim Basin are the areas where the temperature changes are most sensitive to the environment.The degree of uniformity in annual mean air temperature increase is higher in the arid and semi-arid area.From the early 1970s,the trend in tempera-ture changed from a decrease to an increase,and there was a marked increase in mean temperature in 1986.After that mean temperature went through a period of rapid increase.The entire area’s 10 hottest years all occurred in or since the 1990s,and 90% of various sub-districts’ hottest years also occurred after 1990.The process of temperature change appears to have a roughly 5-year and a 10-year cycle;(4) An-nual mean air temperature variation has regional differences.In Inner Mongolia-Xinjiang and Shaanxi-Gansu-Ningxia-Qinghai areas,the temperature variation in their northern areas was very different from that in their southern areas;(5) Using the REOF method we divided the region into 4 sub-regions:the Northern region,the Plateau region,the Southern Xinjiang region and the Eastern region.The region’s annual mean air temperature transition has regional differences.The Plateau and Southern Xinjiang re-gions got warmer steadily without any obvious acceleration in the rate of warming.The Northern region’s warming started about 5-years earlier than that of the low latitude Eastern region.The ’Startup region’ of the Qinghai-Tibet Plateau,appears to undergo temperature changes 3 to 10 years earlier than the other regions,and exhibits inter-decadal variations 1 to 2 years ahead of the other regions.

Quantification of relationship between annual daily maximum temperature and annual daily maximum rainfall in South Australia

The empirical relationship between annual daily maximum temperature(ADMT)and annual daily maximum rainfall(ADMR)was investigated.The data were collected from four weather stations located in Adelaide,South Australia,from 1988 to 2017.Due to the influence of sea surface temperature on rainfall and temperature,the distance from the weather station to the sea was considered in the selection of weather stations.Two weather stations near the sea and two inland weather stations were selected.Three non-parametric statistical tests(Kruskal–Wallis,Mann–Whitney,and correlation)were applied to perform statistical analysis on the ADMT and ADMR data.It was revealed that the temperature and rainfall in South Australia varies according to weather station location.The distance from the sea to the weather station was found to have limited influence on temperature and rainfall.Meanwhile,with the 0.05 level of significance,the association between ADMT and ADMR near sea stations is not as significant as the association between the two inland weather stations.It is relatively unrealistic to use ADMR to predict ADMT,or vice versa,since their correlation is not statistically significant(Spearman’s rank correlation coefficient:−0.106).

Global Annual Mean Surface Air Temperature Anomalies and Their Link with Indian Summer Monsoon Failures

Analysis of the global mean annual temperature anomalies based on land and marine data for the last 88 years (1901-1988) of this century has been carried out with a view to find any relationship with failures in Indian summer monsoon rainfall. On the climatological scale (i.e. 30 years) it has been noticed that there is an abnormal increase in the frequency of drought years during epochs of global warming and cooling, while it is considerably less when global temperatures are near normal. Results are unchanged even when the data are filtered out for ENSO (El-Nino Southern Oscillation) effect.It has also been noticed that during warm and cold epochs in global temperatures the amount of summer monsoon rainfall decreases as compared to the rainfall during a normal temperature epoch.

Elevational patterns of temperature and humidity in the middle Tianshan Mountain area in Central Asia

The vertical distribution of vegetation types along an elevational gradient in mountain areas largely depends on the elevational changes in air temperature and humidity. In this study, we presented the seasonal and diurnal variations in the elevational gradients of air temperature and humidity on the southern and northern slopes in the middle Tianshan Mountain Range using data collected throughout the year via HOBO data loggers. The measurements were conducted at 12 different elevations from 1548 to 3277 m from September 2004 to August 2005. The results showed that the annual mean air temperature decreased along the elevational gradients with temperature lapse rates of(0.71±0.20)°C/100 m and(0.59±0.05)°C/100 m on the northern and southern slopes, respectively. The annual mean absolute humidity significantly decreased with increasing elevation on the northern slope but showed no significant trend on the southern slope. The annual mean relative humidity did not show a significant trend on the northern slope but increased with increasing elevation on the southern slope. The mean air temperature lapse rate exhibited significant seasonal variation, which is steeper insummer and shallower in winter, and this value varied between 0.37°C/100 m and 0.75°C/100 m on the southern slope and between 0.30°C/100 m and 1.02°C/100 m on the northern slope. The mean absolute and relative humidity also exhibited significant seasonal variations on both slopes, with the maximum occurring in summer and the minimum occurring in winter or spring. The monthly diurnal range of air temperature on both slopes was higher in spring than in winter. The annual range of air temperature on the southern slope was higher than that on the northern slope. Our results suggest that significant spatiotemporal variations in humidity and temperature lapse rate are useful when analyzing the relationships between species range sizes and climate in mountain areas.

Impacts of climate change on the yields of leguminous crops in the Guinea Savanna agroecological zone of Ghana

The impacts of climate change on crop yields are receiving renewed interest,with focus on cereals and staple crops at the regional and national scales.Yet,the impacts of climate change on the yields of leguminous crops in the local context has not been explored.Thus,an in-depth understanding of climate change in the local context may support the design of locally relevant adaptation responses to current and future climate risks.This study examined the impacts of climate variables(annual rainfall,annual average temperature,rainfall indices(rainfall onset,rainfall cessation,and the length of rainy days),and the number of dry days)on the yields of leguminous crops(groundnuts,cowpeas,and soybeans)in the Guinea Savanna agroecological zone of Ghana during the period of 1989-2020.The data were analysed using Mann-Kendall’s trend,Sen’s slope test,correlation analysis,and Multiple Regression Analysis(MRA).The findings revealed that annual rainfall,annual average temperature,rainfall onset,rainfall cessation,and the length of rainy days,and the number of dry days all showed varied impacts on the yields of groundnuts,cowpeas,and soybeans.The trend analysis detected a marginal decrease in the amount of rainfall,rainfall onset,and the number of dry days from 1989 to 2020(P>0.050).Annual average temperature and the length of rainy days substantially varied(P<0.050)from 1989 to 2020,showing an increasing trend.The findings also showed a marked upward trend for the yields of groundnuts,cowpeas,and soybeans during 2005-2020.The climate variables analysed above increased the yields of groundnuts,cowpeas,and soybeans by 49.0%,55.0%,and 69.0%,respectively.The yields of groundnuts,cowpeas,and soybeans fluctuated with the variability of 30.0%,28.0%,and 27.0%from 2005 to 2020,respectively.The three leguminous crops under study demonstrated unpredictable yields due to the variations of annual rainfall,annual average temperature,rainfall onset,rainfall cessation,the length of rainy days,and the number of dry days,which stressed the need for agricultural diversification,changing planting dates,using improved seed variety,and irrigation to respond to climate change.The results of this study implied that climate change considerably impacts crop production in the Guinea Savanna agroecological zone of Ghana,emphasizing the urgency of locally based and farmer-induced adaptation measures for food security and resilient agricultural systems.

Biomass Components and Environmental Controls in Ningxia Grasslands

Grassland plays an important role in the global carbon cycle and climate regulation. However, there are still large uncertainties in grassland carbon pool and also its role in global carbon cycle due to the lack of measured grassland biomass at regional scale or global scale with a unified survey method, particular for below-ground biomass. The present study, based on a total of 44 grassland sampling plots with 220 quadrats across Ningxia, investigated the characteristics of above-ground biomass （AGB）, below-ground biomass （BGB）, litter biomass （LB）, total biomass （TB） and root：shoot ratios （R：S） for six predominantly grassland types, and their relationships with climatic factors. AGB, BGB, LB and TB varied markedly across different grassland types, the median value ranging from 28.2-692.6 g m-2 for AGB, 130.4-2 036.6 g m-： for BGB, 9.2-82.3 g m2 for LB, and 168.0-2 681.3 g m-： for TB. R：S showed less variation with median values from 3.2 to 5.3 （excluding marshy meadow）. The different grassland types showed similar patterns of biomass allocation, with more than 70% BGB for all types. There is evidence of strong positive effects associated with mean annual precipitation （MAP） and negative effects associated with mean annual temperature （MAT） on AGB, BGB, and LB, although both factors have the opposite effect on R：S.

Evaluating the grassland net primary productivity of southern China from 2000 to 2011 using a new climate productivity model

Grassland is the important component of the terrestrial ecosystems. Estimating net primary productivity （NPP） of grassland ecosystem has been a central focus in global climate change researches. To simulate the grassland NPP in southern China, we built a new climate productivity model, and validated the model with the measured data from different years in the past. The results showed that there was a logarithmic correlation between the grassland NPP and the mean annual temperature, and there was a linear positive correlation between the grassland NPP and the annual precipitation in southern China. Al these results reached a very signiifcant level （P〈0.01）. There was a good correlation between the simulated and the measured NPP, withR2 of 0.8027, reaching the very signiifcant level. Meanwhile, both root mean square errors （RMSE） and relative root-mean-square errors （RRMSE） stayed at a relatively low level, showing that the simulation results of the model were reliable. The NPP values in the study area had a decreasing trend from east to west and from south to north, and the mean NPP was 471.62 g C m？2 from 2000 to 2011. Additionaly, there was a rising trend year by year for the mean annual NPP of southern grassland and the tilt rate of the mean annual NPP was 3.49 g C m？2 yr？1 in recent 12 years. The above results provided a new method for grassland NPP estimation in southern China.

Mismatch between species distribution and climatic niche optima in relation to functional traits

Background:Forecasts of climate change impacts on biodiversity often assume that the current geographical distributions of species match their niche optima.However,empirical evidence has challenged this assumption,suggesting a mismatch.We examine whether the mismatch is related to functional traits along temperature or precipitation gradients.Methods:The observed distributions of 32 tree species in northeast China were evaluated to test this mismatch.Bayesian models were used to estimate the climatic niche optima,i.e.the habitats where the highest species growth and density can be expected.The mismatch is defined as the difference between the actual species occurrence in an assumed niche optimum and the habitat with the highest probability of species occurrence.Species’functional traits were used to explore the mechanisms that may have caused the mismatches.Results:Contrasting these climatic niche optima with the observed species distributions,we found that the distribution-niche optima mismatch had high variability among species based on temperature and precipitation gradients.However,these mismatches depended on functional traits associated with competition and migration lags only in temperature gradients.Conclusions:We conclude that more relevant research is needed in the future to quantify the mismatch between species distribution and climatic niche optima,which may be crucial for future designs of forested landscapes,species conservation and dynamic forecasting of biodiversity under expected climate change.

Study on Ann-Based Multi-Step Prediction Model of Short-Term Climatic Variation

In the context of 1905–1995 series from Nanjing and Hangzhou, study is undertaken of estab-lishing a predictive model of annual mean temperature in 1996–2005 to come over the Changjiang (Yangtze River) delta region through mean generating function and artificial neural network in combination. Results show that the established model yields mean error of 0.45°C for their abso-lute values of annual mean temperature from 10 yearly independent samples (1986–1995) and the difference between the mean predictions and related measurements is 0.156°C. The developed model is found superior to a mean generating function regression model both in historical data fit-ting and independent sample prediction. Key words Climate trend prediction. Mean generating function (MGF) - Artificial neural network (ANN) - Annual mean temperature (AMT)

Changes of annual accumulated temperature over Southern China during 1960-2011

The spatial and temporal variations of ≥10℃ annual accumulated temperature （AAT10） were analyzed by using the linear trend line method, cumulative anomaly method and the multiple linear regression model （MLRM） interpolation method based on the daily meteorological observation data from 104 meteorological stations in Southern China and surrounding 39 meteorological stations from 1960 to 2011. The results show that： （1） From time scale point of view, the climatic trend of the AAT10 increased with an average of 7.54℃/decade in Southern China since 1960. The area of AAT10〈6000℃ decreased from 1960 to 2011, and the area of 6000℃〈AAT10〈8000℃ decreased from 1960 to 1979 and increased from 1980 to 2011, and the area of AAT10〉8000℃ increased from 1960 to 2011. （2） From spatial scale point of view, the AAT10 in Southern China reduced with increasing latitude and reduced with increasing altitude. The proportion of the area with 5000℃〈 AAT10〈8000℃ accounted for 70% of the study area, followed by the area of 4000℃〈AAT10 〈5000℃; and the area of AAT10〈4000℃ and AAT10〉8000℃ was the least. Climate trend rate of the AAT10 at 99% of the meteorological stations was greater than zero, which indicated that the AAT10 increased significantly in the central Yunnan province, southern Guangdong province as well as Hainan Island. （3） Comparison of period A （1960-1989） and period B （1980-2011） with the change of temperature zones shows that the boundaries of cool temperate zone, mid-temperate zone and warm temperate zone shifted northward and shrank westward. The northern boundary of north subtropical zone and mid-subtropical zone shifted northward gradually by over 0.5° and 0.5° latitude, respectively. The western part of northern boundary of south subtropical zone and marginal tropical zone shifted northward by 0.2° and 0.4° latitude, respectively. The change of temperature zones was expanded to high altitude and latitude. （4） The increase of the AAT10 is conducive to the production of tropical crops planted, which will increase the planting area that was suitable for tropical crops, and expand the planting boundaries to high latitude and high altitude.

Climate warming over 1961–2019 and impacts on permafrost zonation in Northeast China

In boreal forest ecosystems, permafrost and forest types are mutually interdependent;permafrost degradation impacts forest ecosystem structure and functions. The Xing’an permafrost in Northeast China is on the southern margin of the Eastern Asia latitudinal permafrost body. Under a warming climate, permafrost undergoes rapid and extensive degradation. In this study, the frost-number (Fn) model based on air temperatures and ground surface temperatures was used to predict the distribution of the Xing’an permafrost, and, temporal and spatial changes in air and ground-surface temperatures from 1961 to 2019 are analyzed. The results show that Northeast China has experienced a rapid and substantial climate warming over the past 60 years. The rises in mean annual air and mean annual ground-surface temperatures were higher in permafrost zones than those in the seasonal frost zone. The frost numbers of air and ground-surface temperatures were calculated for determining the southern limit of latitudinal permafrost and for permafrost zonation. The southern limits of discontinuous permafrost, sporadic permafrost, and latitudinal permafrost moved northward significantly. According to the air-temperature frost-number criteria for permafrost zoning, compared with that in the 1960s, the extent of Xing’an permafrost in Northeast China had decreased by 40.6% by the 2010s. With an average rate of increase in mean annual air temperatures at 0.03 ℃ a^(−1), the extent of permafrost in Northeast China will decrease to 26.42 × 10^(4) by 2020, 14.69 × 10^(4) by 2040 and to 11.24 × 10^(4) km^(2) by 2050. According to the ground-surface temperature frost-number criteria, the southern limit of latitudinal permafrost was at the 0.463. From the 1960s to the 2010s, the extent of latitudinal permafrost declined significantly. Due to the nature of the ecosystem-protected Xing’an-Baikal permafrost, management and protection (e.g., more prudent and effective forest fire management and proper logging of forests) of the Xing’an permafrost eco-environment should be strengthened.

ESTIMATES OF CLIMATE NOISES OF ANNUAL MEAN TEMPERATURES OVER CHINA

In this paper,a design to estimate climate noise of annual mean temperature has been made by means of the mini- mum interannual variance and effectively independent observations in time series.By using it the climate noises of annu- al mean surface air temperatures have been estimated based on the data from 1960 to 1991 in this country.The low val- ues of climate noises of annual mean temperatures are found in the southeastern Tibet Plateau,Yunnan,the Sichuan Ba- sin and south of the middle and lower reaches of the Changjiang River Valley.The high values are seen in the northwestern and northeastern China and the rest of the Tibet Plateau.A relatively low value region is in the southern Xinjiang.

Stability evaluation of radial growth of Picea schrenkiana in different age groups in response to climate change in the eastern Tianshan Mountains

Global warming causes an unstable response in tree radial growth at high latitudes in the Northern Hemisphere.Additionally,different climatic responses of different age groups of trees have been found due to their different physiological mechanisms.In this study,the response stability and growth trend of three age groups(young<100 a,middle 100-200 a,old≥200 a)of Picea schrenkiana(Schrenk spruce)to climate change and the causes of the different responses in different age groups were analyzed in the relatively dry climate of the eastern Tianshan Mountains.The results showed that:(1)With the abrupt increase in temperature in 1989,the annual mean minimum temperature became the dominant radial growth-limiting factor of the three age groups of Schrenk spruce.(2)The radial growth of the middle and young groups was more sensitive than that of the old group based on growth-climate correlation analysis.(3)The radial growth of the different age groups had different responses to climate factors,and all age groups were unstable on time scales.(4)The trend of the linear regression simulation of the basal area increment(BAI)indicated that the Schrenk spruce had the same growth trends in different age groups with growth first increased and then decreased;however,the decreased growth rate was higher in the middle and young age groups than in the old age group after the abrupt increase in temperature.Therefore,we should pay active attention to the impact of drought on Schrenk spruce in the eastern Tianshan Mountains and should particularly strengthen the conservation and management of the middle and young age groups.

Rapid range expansion predicted for the Common Grackle(Quiscalus quiscula)in the near future under climate change scenarios

Background:Climate change due to anthropogenic global warming is the most important factor that will affect future range distribution of species and will shape future biogeographic patterns.While much effort has been expended in understanding how climate change will affect rare and declining species we have less of an understanding of the likely consequences for some abundant species.The Common Grackle(Quiscalus quiscula;Linnaeus 1758),though declining in portions of its range,is a widespread blackbird(Icteridae)species in North America east of the Rocky Mountains.This study examined how climate change might affect the future range distribution of Common Grackles.Methods:We used the R package Wallace and six general climate models(ACCESS1-0,BCC-CSM1-1,CESM1-CAM5-1-FV2,CNRM-CM5,MIROC-ESM,and MPI-ESM-LR)available for the future(2070)to identify climatically suitable areas,with an ecological niche modelling approach that includes the use of environmental conditions.Results:Future projections suggested a significant expansion from the current range into northern parts of North America and Alaska,even under more optimistic climate change scenarios.Additionally,there is evidence of possible future colonization of islands in the Caribbean as well as coastal regions in eastern Central America.The most important bioclimatic variables for model predictions were Annual Mean Temperature,Temperature Seasonality,Mean Temperature of Wettest Quarter and Annual Precipitation.Conclusions:The results suggest that the Common Grackle could continue to expand its range in North America over the next 50 years.This research is important in helping us understand how climate change will affect future range patterns of widespread,common bird species.