Average Annual Mean Temperature Research Articles

Forest fires social and climate change in Cyprus

Forest fires and wildfires are increasing in many regions of the world and give the big impact on the environment, local economies, livelihoods, and societies. Cyprus is an island member of the European Union in the south-eastern Mediterranean and it is severely affected by wild fires. The aim of this paper is to review the pertinent, recent literature (which although not exhaustive, identifies the main contributing factors) mostly in the Mediterranean region and to identify the variables that affect the rise in the number and intensity of forest fires, wildfires and how these variables are affecting Cyprus. This research was conducted by using statistical data made by the Cyprus Statistical Service. By compiling the data of climatology, demography, agricultural production, and forest fire incidents, some results were found. The increased forest fires were caused by the rise of the average annual mean temperature in the period of 1990-2021, the change in social conditions and agricultural land use with the urbanization of people living around the forest areas, and the conservative policies adopted by successive administrations with reference to forest management and conservation.

Drivers of the time-varying heat-cold-mortality association in Spain: A longitudinal observational study

BackgroundA number of studies have reported reductions in mortality risk due to heat and cold over time. However, questions remain about the drivers of these adaptation processes to ambient temperatures. We aimed to analyse the demographic and socioeconomic drivers of the downward trends in vulnerability to heat- and cold-related mortality observed in Spain during recent decades (1980–2018). MethodsWe collected data on all-cause mortality, temperature and relevant contextual indicators for 48 provinces in mainland Spain and the Balearic Islands between Jan 1, 1980, and Dec 31, 2018. Fourteen contextual indicators were analysed representing ageing, isolation, urbanicity, heating, air conditioning (AC), house antiquity and ownership, education, life expectancy, macroeconomics, socioeconomics, and health investment. The statistical analysis was separately performed for the range of months mostly causing heat- (June-September) and cold- (October-May) related mortality. We first applied a quasi-Poisson generalised linear regression in combination with distributed lag non-linear models (DLNM) to estimate province-specific temperature-mortality associations for different periods, and then we fitted univariable and multivariable multilevel spatiotemporal meta-regression models to evaluate the effect modification of the contextual characteristics on heat- and cold-related mortality risks over time. FindingsThe average annual mean temperature has risen at an average rate of 0·36 °C per decade in Spain over 1980–2012, although the increase in temperature has been more pronounced in summer (0·40 °C per decade in June-September) than during the rest of the year (0·33 °C per decade). This warming has been observed, however, in parallel with a progressive reduction in the mortality risk associated to both hot and cold temperatures. We found independent associations for AC with heat-related mortality, and heating with cold-related mortality. AC was responsible for about 28·6% (31·5%) of the decrease in deaths due to heat (extreme heat) between 1989 and 1993 and 2009–2013, and heating for about 38·3% (50·8%) of the reductions in deaths due to cold (extreme cold) temperatures. Ageing (ie, proportion of population over 64 years) attenuated the decrease in cold-related mortality. InterpretationAC and heating are effective societal adaptive measures to heat and cold temperatures. This evidence holds important implications for climate change health adaptation policies, and for the projections of climate change impacts on human health.

Climate change and malaria: some recent trends of malaria incidence rates and average annual temperature in selected sub-Saharan African countries from 2000 to 2018

BackgroundMalaria is still a disease of massive burden in Africa, also influenced by climate change. The fluctuations and trends of the temperature and precipitation are well-known determinant factors influencing the disease’s vectors and incidence rates. This study provides a concise account of malaria trends. It describes the association between average temperature and malaria incidence rates (IR) in nine sub-Saharan African countries: Nigeria, Ethiopia, South Africa, Kenya, Uganda, Ghana, Mozambique, Zambia and Zimbabwe. The incidence of malaria can vary both in areas where the disease is already present, and in regions where it is present in low numbers or absent. The increased vulnerability to the disease under increasing average temperatures and humidity is due to the new optimal level for vector breeding in areas where vector populations and transmission are low, and populations are sensitive due to low acquired immunity.MethodsA second source trend analysis was carried out of malaria cases and incidence rates (the number of new malaria cases per 1000 population at risk per year) with data from the World Health Organization (WHO) and average annual mean temperature from 2000 to 2018 from the World Bank’s Climate Change Knowledge Portal (CCKP). Additionally, descriptive epidemiological methods were used to describe the development and trends in the selected countries. Furthermore, MS Excel was chosen for data analysis and visualization.ResultsFindings obtained from this article align with the recent literature, highlighting a declining trend (20–80%) of malaria IR (incidence rate) from 2000 to 2018. However, malaria IR varies considerably, with high values in Uganda, Mozambique, Nigeria and Zambia, moderate values in Ghana, Zimbabwe, and Kenya, and low values in South Africa and Ethiopia in 2018. Evidence suggests varying IRs after average temperature fluctuations in several countries (e.g., Zimbabwe, Ethiopia). Also, an inverse temperature-IR relationship occurs, the sharp decrease of IR during 2012–2014 and 2000–2003, respectively, occurred with increasing average temperatures in Ghana and Nigeria. The decreasing trends and fluctuations, partly accompanying the temperature, should result from the intervention programmes and rainfall variability. The vulnerability and changing climate could arrest the recent trends of falling IR.ConclusionThus, malaria is still a crucial public health issue in sub-Saharan Africa, although a robust decreasing IR occurred in most studied countries.

The Relationship between the Built Environment and Climate Change: The Case of Turkish Provinces

The relationship between the built environment and climate change has been discussed from many perspectives. This study examines the effect of the built environment on climate change indicators in Turkish provinces over the last 18 years, contributing to the literature on built environment analyses regarding both urban and rural areas, unlike other studies that have focused mostly on urban areas. The study discusses the changes in climate indicators using maps and analyzes the effects of the built environment on climate change using linear regression. The results indicate that provinces in Türkiye have experienced climate change effects such as increased annual mean temperature, maximum temperature, maximum precipitation, extreme weather events, and drought. These effects differed both in terms of geography and the subperiods over the examined period. The results also demonstrate the increase in the built environment to have a positive correlation with the increases in annual maximum temperature and the annual number of extreme weather events. The built environment in Türkiye increased 63% between 1990 and 2018, and the average number of extreme weather events per province increased from 0.3 to 8 over this same period. At the same time, the average annual mean temperature increased from 12.9 to 15.1 °C, the average maximum temperature went up from 24.6 to 25.8 °C, the average annual maximum precipitation increased from 125.6 to 157.7 mm, and the average number of dry months per year increased from 3.4 to 3.8.

Life-history characteristics and climate correlates of dioecious plant species in central southern Australia

Context The proportion of dioecious species can vary considerably among climates and habitats. However, studies often involve isolated communities or large diverse areas and fail to capture how proportions vary across diverse landscapes.Aims To identify (1) life-history associations of terrestrial dioecious plant species in central southern Australia, (2) whether proportion of dioecy varies spatially across central southern Australia, and (3) whether proportion of dioecy is correlated with life-history and/or climate factors.Methods Species growth form, pollination mechanisms and seed-dispersal features were extracted from herbarium databases to determine potential dioecy-linked traits. Distribution data for native terrestrial species in 66 Interim Biogeographical Regionalisation of Australia subregions were extracted from the Australasian Virtual Herbarium to calculate the proportion of total native species richness that are dioecious. Climate data for each subregion were also obtained from Terrestrial Ecology Research Network databases to investigate relationships among climate, life-history traits and dioecy.Key results Woodiness, abiotic pollination and endozoochory were more prevalent in dioecious than non-dioecious taxa. Proportion of dioecy ranged from 1.7% to 8.5% among subregions and correlated negatively with annual temperature range, January to March rainfall and precipitation seasonality and with average annual daily mean, minimum, maximum and average annual minimum temperature. The highest-ranked models of dioecy incorporated the additive effects of the relative proportion of woody species and either annual temperature ranges, January to March rainfall or average annual daily maximum temperature.Conclusions Dioecy was associated with woodiness, abiotic pollination and endozoochory, in line with studies of other flora, with the model of stable temperature range and woodiness being the highest-ranked model of dioecy.Implications Areas with higher proportions of dioecy can be targeted for future investigations into dioecious plant ecology to aid conservation and ecosystem management.

Long-term changes in surface air temperature over the Chinese mainland during 1901-2020

The magnitude of long-term surface climate warming over some regions, such as the Chinese mainland, is still uncertain due to the lack of observational data early in the 20th century. In this study, the monthly data series of the average, maximum, and minimum temperatures in the Chinese mainland during 1901-2020 were constructed based on the daily surface air temperature observations from 60 stations across the country, and the characteristics of the average, maximum, and minimum temperature, and diurnal temperature range (DTR) changes were analyzed. Results show that (1) regional average annual mean temperature in the Chinese mainland rose by 0.14°C per decade, maximum temperature rose by 0.07°C per decade, minimum temperature rose by 0.19°C per decade, and DTR decreased by 0.13°C per decade. All these trends are statistically significant (p < 0.01); (2) the largest annual mean maximum temperature increase occurred in spring, followed by winter and autumn/summer, and the largest annual mean minimum temperature increase was in winter and spring, followed by autumn and summer; (3) annual mean DTR decreased significantly at a rate of -0.08, -0.12, -0.12, and -0.13°C per decade (p < 0.01) in spring, summer, autumn, and winter, respectively; (4) the stations with drops in maximum temperature were mainly in Central China, southern North China, the southeastern coastal areas, and the middle and lower reaches of the Yangtze River, and the stations with significant increases in minimum temperature were located in North China, Northeast China, and Northwest China; (5) the areas with the fastest dropping DTR were mainly located in Northeast China and North China. The maximum and minimum temperature series for China based on climate anomalies are comparable to those based on other currently available datasets.

Seasonal variation in mortality and the role of temperature: a multi-country multi-city study

BACKGROUND AND AIM: Although seasonal variations in mortality have been recognised for a long time, the role of temperature remains unclear. We aimed to assess seasonal variation in mortality and to examine the contribution of temperature. METHODS: We compiled daily data on all-cause, cardiovascular, and respiratory mortality, temperature, and indicators on location-specific characteristics from 719 locations in tropical, dry, temperate and continental climate zones. We fitted time-series regression models to estimate the amplitude of seasonal variation in mortality on a daily basis, defined as the peak-to-trough ratio (PTR) of maximum mortality estimates to minimum mortality estimates at day-of-year. Random-effects multivariate meta-analysis was used to summarise location-specific estimates for each climate zone. We estimated PTR with and without temperature adjustment, with the differences representing the seasonal effect attributable to temperature. We also evaluated the effect of location-specific characteristics on PTR across locations by using random-effects meta-regression models. RESULTS:Seasonality estimates and responses to temperature adjustment varied across locations. Unadjusted-PTR for all-cause mortality was 1.05 (95% confidence interval (CI): 1.00–1.11) in the tropical zone and 1.23 (95% CI: 1.20–1.25) in the temperate zone; adjusting for temperature reduced the PTR estimates to 1.02 (95% CI: 0.95–1.09) and 1.10 (95% CI: 1.07–1.12), respectively. Furthermore, unadjusted-PTR was positively associated with average annual mean temperature, and adjusting for temperature in PTR moved the estimate towards the null. CONCLUSIONS:This study suggests that seasonality of mortality is importantly driven by temperature, most evidently in temperate/continental climate zones, and that warmer locations show stronger seasonal variations in mortality, which is related to a stronger effect of temperature. On behalf of the MCC collaborative research network. KEYWORDS: Seasonality of mortality, temperature, a multi-country multi-city study

Warm early Mars surface enabled by high-altitude water ice clouds

Despite receiving just 30% of the Earth's present-day insolation, Mars had water lakes and rivers early in the planet's history, due to an unknown warming mechanism. A possible explanation for the >102-y-long lake-forming climates is warming by water ice clouds. However, this suggested cloud greenhouse explanation has proved difficult to replicate and has been argued to require unrealistically optically thick clouds at high altitudes. Here, we use a global climate model (GCM) to show that a cloud greenhouse can warm a Mars-like planet to global average annual-mean temperature ([Formula: see text]) ∼265 K, which is warm enough for low-latitude lakes, and stay warm for centuries or longer, but only if the planet has spatially patchy surface water sources. Warm, stable climates involve surface ice (and low clouds) only at locations much colder than the average surface temperature. At locations horizontally distant from these surface cold traps, clouds are found only at high altitudes, which maximizes warming. Radiatively significant clouds persist because ice particles sublimate as they fall, moistening the subcloud layer so that modest updrafts can sustain relatively large amounts of cloud. The resulting climates are arid (area-averaged surface relative humidity ∼25%). In a warm, arid climate, lakes could be fed by groundwater upwelling, or by melting of ice following a cold-to-warm transition. Our results are consistent with the warm and arid climate favored by interpretation of geologic data, and support the cloud greenhouse hypothesis.

Multi-year ocean thermal variability

Numerous indicators show that multi-annual and longer oceanic baroclinic variability retains a complicated spatial structure out to decades and longer. With time-averaging, the sub-basin scales connected to abyssal topography and meteorological structures emerge in the fields. Here, using 26-years of an oceanic state estimate (ECCO), an attempt is made to extract simpler patterns from the vertical average (whole water column) annual mean temperature anomalies and, separately, the vertical structures at each horizontal position. Singular vectors (SVs)/empirical orthogonal functions (EOFs) successfully simplify vertical and horizontal fields, but principal observation patterns (POPs) do not do so. About 3 horizontal spatial patterns account for more than 95% of the interannual and longer variances. A breakdown of the purely vertical structure at each grid point leads in contrast to an intricate variability with depth. Results have implications both for future sampling strategies, and for estimates, e.g. of the accuracy of any mean oceanic scalar.

Impacts of land use/land cover detection on climate variability of Gumara Watershed, Ethiopia

Land use/land cover (LU/LC) detection on climate variability has been conducted using satellite image and weather data in the study area. LU/LC analysis was done using supervised classification and the categories used were built-up area, forest, grassland, agriculture and waterbody. From the analysis, built-up area is shown as increasing from 1997 to 2017. Climate variability assessment done using the Mann-Kendall and Sen's slope estimator shows that average annual maximum temperature and mean temperature have positive trends, average annual minimum temperature shows a decreasing trend. Annual rainfall showed positive trend in the Bega season and decreasing trends in, Belg season and Kiremt season. Percentage changes were observed as 0.4%, 2.4% and 2.6% for average annual minimum, maximum and average annual temperature, respectively. Average annual rainfall, in Bega season, Belg season and Kiremt seasons was −1.7%, 3.5%, 6.5% and −6.4% respectively. Hence percentage changes show LU/LC change affects climate.

Quantitative reconstruction of paleoclimate in central Japan for the past 158,000 years based on a modern analogue technique of pollen composition

In this study, quantitative climate information for central Japan for the past 158 ka is reconstructed on the basis of pollen composition data of NJ88 core from Lake Nojiri and those of TKN-2004 core from the lacustrine Takano Formation using a modern analogue technique. Reconstructed values at the sites around 36.6°N and 700 m altitude are as follows.In marine isotope stage (MIS) 6, the average annual mean temperature was about 2.1 °C, with a coldest month temperature of −11.8 °C, which suggest very cold climate conditions. The climates of MIS 4 and 2 were similarly cold, and the precipitation was low with ∼1050 mm for mean annual precipitations during these cold periods. In contrast, the annual mean temperatures of MIS 5e and MIS 1, among the warmest periods, averaged about 5.5 °C and 9.1 °C, respectively. The annual mean temperature of MIS 5e was significantly lower than that of the Holocene. We estimate that an intensely cold winter controlled the vegetation, which resulted in the lower temperature reconstruction for MIS 5e. The annual mean temperatures of intermediately warm periods such as MIS 5c and 5a were a slightly high, with averages of 4.4 °C and 5.1 °C, respectively. Annual precipitations increased up to ∼1400 mm on average in these warmer periods. Annual mean temperatures of MIS 5d and 5b were low with averages of about 3.0 °C.Annual mean temperatures reconstructed for MIS 3 fluctuated over short periodicities that correspond to Dansgaard–Oeschger cycles. For example, the annual mean temperature of the interstadial GI-8 (Greenland Interstadial 8), 38–39 cal ka BP (calendar ka before 1950 CE) was about 4.0 °C, and that of the stadial HE 4 (Heinrich event 4) in 42–43 cal ka BP was about 2.6 °C. From 14 to 12 cal ka BP, annual mean temperature increased significantly in a relatively short period, from 1.3 to 9.5 °C, and annual precipitation also increased from 1040 to 1380 mm. A cool event corresponding to the Younger Dryas was identified in this deglaciation process, but its intensity was much weaker than that in the North Atlantic region. The climate in the Holocene (MIS 1) was warm, with an average annual mean temperature of 9.0 °C with wide variation, by a maximum of about 2 °C, which suggests temporal change of the Arctic polar front situated in mid-latitude regions.

The Origin and Development of the Central European Man-made Landscape, Habitat and Species Diversity as Affected by Climate and its Changes – a Review

The Origin and Development of the Central European Man-made Landscape, Habitat and Species Diversity as Affected by Climate and its Changes – a Review

Assessing vulnerability and adaptation strategies of forest dependent people to climate change in the Mid-hills of Nepal

Climate change is now recognized as one of the most serious challenges facing the world– its people, the environment and its economies. Rural people are more vulnerable to the effects of climate change due to its high dependence on climate-sensitive sectors like glaciers, agriculture and forestry, and its low financial adaptive capacity. This study was carried out with the aim of assessing and documenting vulnerability and adaptation strategies of forest-dependent people to climate change effects in Mid-hills of Nepal. Primary data were collected from household survey, interview with key informants, and focused group discussion. The results showed that the average annual rainfall was decreasing at the rate of 18.02 mm whereas the average annual mean temperature was increasing at the rate of 0.07°c per year. The major climatic hazards, of the study area, identified were long drought and landslide. The chi-square test shows that the poor forest-dependent people are more vulnerable to long drought, landslide and floods as compared to the rich rural people. Indigenous adaptation practices such as cultivation of vegetables and other crops that are less susceptible to droughts, and rearing of hybrid-varieties of livestock are mostly used to cope with climate change impacts. The results indicate that 15% of the respondents have changed their cropping pattern from paddy to off-seasonal vegetables crops because of more income from vegetable farming. Raising awareness and sharing information as well as increasing income from farming among the locals by applying new technologies should be done in order to build their capacity to cope with climate change impact.Banko Janakari, A Journal of Forestry Information for NepalVol. 25, No. 1Page: 55-62

A Comparison of Two Methods on the Climatic Effects of Urbanization in the Beijing-Tianjin-Hebei Metropolitan Area

Both the “urban minus rural” (UMR) and the “observation minus reanalysis” (OMR) methods were used to quantify the potential impacts of urbanization on regional temperature changes in the Beijing-Tianjin-Hebei metropolitan area in China. DMSP/OLS nighttime light imagery and population census data were used to classify stations into four classes: rural, small city, medium city, and large city groups. The regional average annual mean temperature was estimated to increase by 0.12°C decade−1derived from urban warming, accounting for 40% of total climate warming from 1960 to 2009 using the UMR method. The OMR method also indicates that rapid urbanization has a significant influence on surface warming trend although the urban warming intensity is dependent on reanalysis dataset. The seasonal cycle patterns from all three datasets are consistent with each other, which is contrary to the UMR result owing to the cooling effect of agriculture activity in the rural stations confusing the UMR result. So in this paper we found a deficiency of the UMR method where it would underestimate the effects of urbanization in summer. In this regard, the results from the OMR method are relatively more convincing although we admit it still has many other problems.

Sensitivity of regional climate simulations to land-surface schemes on the Tibetan Plateau

To investigate the effects of land-surface schemes in 2 regional climate models (RegCM3 and RegCM4.3.4) on the Tibetan Plateau (TP) climate simulation, 3 groups of 10 yr (1992-2001) simulation experiments were performed based on 2 land-surface schemes (BATS and CLM3.5). The simulations (RegCM3_BATS, RegCM4_BATS, and RegCM4_CLM) were compared with observed data by setting the same domain and initial and lateral atmospheric boundary conditions and using 30 km spatial resolution. The results showed that, compared to observed data, regional average annual mean temperature was underestimated by 1.22, 2.11, and 1.32 degrees C, and regional average annual precipitation was overestimated by 43.2, 49.8, and 18.4% in RegCM3_BATS, RegCM4_BATS, and RegCM4_CLM respectively. There were significant differences in simulated energy and water budget components among the 3 models resulting from the influence of the 2 different land-surface parameterization schemes, which impacted the simulated precipitation and temperature results through interaction between the land surface and the atmosphere. Therefore, climate simulation over the TP is very sensitive to the use of different land-surface schemes in regional climate models. Overall, use of RegCM4_CLM instead of RegCM_BATS resulted in a warmer and drier land surface and a better simulation of annual average spatial patterns of temperature and precipitation.

Climate changes for the past 52 ka clarified by total organic carbon concentrations and pollen composition in Lake Biwa, Japan

Total organic carbon (TOC) and total nitrogen (TN) analyses have been performed for three core samples obtained recently from Lake Biwa, which include BIW07-5, BIW07-6, and BIW08-B cores. The TOC and TN data from these cores show similar stratigraphic changes and can be regarded as reliable records of biological productivity occurring in the lake during the past 52 ka. Pollen analysis data are also used to determine climate change during the past 40 ka by reconstructing meteorological parameters such as annual temperature and precipitation. Temporal changes in TOC concentration show detailed climate changes in tens-year intervals. Climate change of orbital scale are well recognized, demonstrating the change from MIS 3 to 1 associated with severe cold periods known as Heinrich events 1 to 5 and warm periods known as Greenland interstadials (GIS 1–13). These climate events in millennial time scale are also well supported by pollen characteristics and by modern analogue analysis. The good concordance of climate change between North Atlantic region and Japan is explained by a hypothesis that the intensity of the Arctic air mass controls the climate in both the North Atlantic and East Asia regions through the migration of the Arctic polar front. Although the average annual mean temperature in MIS 3 was 8.2 ± 0.8 (2σ) °C, it varied largely and frequently among its substages. For example, 9.4 ± 2.0 °C was detected in a warm interstadial (GIS 8), and 6.3 ± 1.5 °C indicated in a cold stadial (Heinrich event 4). The average annual temperature was 4.5 ± 0.3 °C in MIS 2, when the average temperature of the coldest month was −7.3 ± 0.2 °C and that of the warmest month was 16.8 ± 0.2 °C. Through Termination 1, the annual mean temperature suddenly increased more than 5 °C, and the annual mean temperature became 11.2 ± 0.8 °C in early MIS 1, which is much lower than that of the present temperature. This low temperature estimation is attributed to the delay in expansion of evergreen broadleaf trees. The annual mean temperature in the late MIS 1 was as same as that of present meteorological observation.

Predicting fire occurrence patterns with logistic regression in Heilongjiang Province, China

Prediction of forest fire ignition may aid in forest fire vigilance and monitoring, and in prioritizing forest fuel treatments. In this paper, we chose easily obtained spatial variables pertaining to topography, vegetation types, meteorological conditions, climate, and human activity to predict forest fire ignition in Heilongjiang province, China, using logistic regression. Results showed fire ignition prediction through logistic regression had good accuracy. Climatic variables (e.g., average annual mean temperature and precipitation) and meteorological conditions (e.g., daily minimum temperature, daily minimum humidity, daily mean humidity, and mean wind speed) are the main determinants of natural forest fires. In the case of anthropogenic fires, vegetation types and human activity as indicated by distances to roads and settlements combined with suitable meteorological conditions (e.g., daily mean humidity) are the main driving factors. The fire ignition probability map can be easily used to prioritize areas for vigilance, to make decisions on allocating firefighting resources, and to select vulnerable spots for forest fuel treatments. It was found that forest fuel treatments should be focused on the Great Xing’an Mountains.

대표농도경로 시나리오에 의한 한반도 주요 평야지역 논벼 소비수량 추정

The paddy rice consumptive use in the six plains of the Korean peninsula was projected with changing climate under the representative concentration pathway (RCP) scenarios. High resolution climate data for the baseline (1961-1990) was obtained from the International water management institute (IWMI) and future high resolution climate projection was obtained from the Korea Meteorological Administration. Reference evapotranspiration (ET) was calculated by using Hargreaves equation. The results of this study showed that the average annual mean temperature would increase persistently in the future. Temperatures were projected to increase more in RCP8.5 than those in RCP4.5 scenario. The rice consumptive use during the growing period was projected to increase slightly in the 2020s and then more significantly in the 2050s and 2080s. It showed higher values for RCP8.5 than for RCP4.5. The rice consumptive use after transplanting in the study areas would increase by 2.2 %, 5.1 % and 7.2 % for RCP4.5 and 3.0 %, 7.6 %, and 13.3 % for RCP8.5, in the 2020s, 2050s, and 2080s, respectively, from the baseline value of 534 mm. The results demonstrated the effects of climate change on rice consumptive use quite well, and can be used in the future agricultural water planning in the Korean peninsula.

Widespread Climate Change in the Himalayas and Associated Changes in Local Ecosystems

BackgroundClimate change in the Himalayas, a biodiversity hotspot, home of many sacred landscapes, and the source of eight largest rivers of Asia, is likely to impact the well-being of ∼20% of humanity. However, despite the extraordinary environmental, cultural, and socio-economic importance of the Himalayas, and despite their rapidly increasing ecological degradation, not much is known about actual changes in the two most critical climatic variables: temperature and rainfall. Nor do we know how changes in these parameters might impact the ecosystems including vegetation phenology.Methodology/Principal FindingsBy analyzing temperature and rainfall data, and NDVI (Normalized Difference Vegetation Index) values from remotely sensed imagery, we report significant changes in temperature, rainfall, and vegetation phenology across the Himalayas between 1982 and 2006. The average annual mean temperature during the 25 year period has increased by 1.5°C with an average increase of 0.06°C yr−1. The average annual precipitation has increased by 163 mm or 6.52 mmyr−1. Since changes in temperature and precipitation are immediately manifested as changes in phenology of local ecosystems, we examined phenological changes in all major ecoregions. The average start of the growing season (SOS) seems to have advanced by 4.7 days or 0.19 days yr−1 and the length of growing season (LOS) appears to have advanced by 4.7 days or 0.19 days yr−1, but there has been no change in the end of the growing season (EOS). There is considerable spatial and seasonal variation in changes in climate and phenological parameters.Conclusions/SignificanceThis is the first time that large scale climatic and phenological changes at the landscape level have been documented for the Himalayas. The rate of warming in the Himalayas is greater than the global average, confirming that the Himalayas are among the regions most vulnerable to climate change.

Tree species richness and diversity of the seasonally dry forest in Central Depression of Chiapas

Tree diversity in the Central Depression of Chiapas was evaluated through 96 circular plots (0.1 ha each) distributed along to altitudinal range between 441 and 1740 m. Hierarchical cluster analysis helped to identify five plant associations; three of them corresponds to the tropical dry forests (TDF), and two Quercus forest. Regional richness included a total of 233 species, 152 genera and 57 botanical families. The contribution of local plots to the total diversity was highest in the TDF associations than in the Quercus forest associations. Species composition was dominated by individuals of late successional stages in the TDF (40-56%), while greatest contribution was secondary species in the Quercus forests (46-54%). Ordination showed a significant correlation plots with 10 of 12 climatic variables, which the average annual mean temperature of warmest month (r2 = 0.74, P <0.001) and mean annual precipitation (r2 = 0.85, P <0.001) were the most important. Although the Central Depression of Chiapas remains less than 2% of its forest cover, tree diversity is relatively high due to environmental heterogeneity which promotes species turnover at the regional level.