Regional Climate Data Research Articles

Predicting plant species distributions using climate‐based model ensembles with corresponding measures of congruence and uncertainty

AbstractAimThe increasing availability of regional and global climate data presents an opportunity to build better ecological models; however, it is not always clear which climate dataset is most appropriate. The aim of this study was to better understand the impacts that alternative climate datasets have on the modelled distribution of plant species, and to develop systematic approaches to enhancing their use in species distribution models (SDMs).LocationVictoria, southeast Australia and the Himalayan Kingdom of Bhutan.MethodsWe compared the statistical performance of SDMs for 38 plant species in Victoria and 12 plant species in Bhutan with multiple algorithms using globally and regionally calibrated climate datasets. Individual models were compared against one another and as SDM ensembles to explore the potential for alternative predictions to improve statistical performance. We develop two new spatially continuous metrics that support the interpretation of ensemble predictions by characterizing the per‐pixel congruence and variability of contributing models.ResultsThere was no clear consensus on which climate dataset performed best across all species in either study region. On average, multi‐model ensembles (across the same species with different climate data) increased AUC/TSS/Kappa/OA by up to 0.02/0.03/0.03/0.02 in Victoria and 0.06/0.11/0.11/0.05 in Bhutan. Ensembles performed better than most single models in both Victoria (AUC = 85%; TSS = 68%) and Bhutan (AUC = 86%; TSS = 69%). SDM ensembles using models fitted with alternative algorithms and/or climate datasets each provided a significant improvement over single model runs.Main conclusionsOur results demonstrate that SDM ensembles, built using alternative models of the same climate variables, can quantify model congruence and identify regions of the highest uncertainty while mitigating the risk of erroneous predictions. Algorithm selection is known to be a large source of error for SDMs, and our results demonstrate that climate dataset selection can be a comparably significant source of uncertainty.

A working guide to spatial mechanistic modelling in Julia

Abstract Models that can predict the dynamics of larger scale ecological processes are increasingly important in a rapidly changing world. The Julia language gives a unique opportunity to produce new, generic tools to develop spatial mechanistic models, and to simultaneously increase their performance, resolution and predictive power. Here, we describe two new Julia software packages, DynamicGrids.jl and Dispersal.jl, that facilitate the development of spatial mechanistic models that are concise, extensible and performant, with several key attributes. First, they allow arbitrary spatially and temporally heterogeneous inputs (e.g. regional climatic data to drive population dynamics). Second, they apply rules to discrete spatial grids, including: (a) single grid cells (e.g. population growth, Allee effects, land‐use change), (b) neighborhoods (e.g. local dispersal); and (c) arbitrary locations (e.g. long‐distance wind dispersal, human‐mediated dispersal). Finally, they allow interactions between multiple grids (e.g. predator–prey models, management/environmental feedbacks). Through in‐line examples, we explore how these properties can be used to develop simple and complex grid‐based mechanistic models that run on both CPUs and GPUs. We demonstrate models of population growth, wind and self‐directed dispersal and host–parasitoid dynamics. We also demonstrate the ease by which custom rules can be combined with rules provided by packages, and the potential for use in other fields and interdisciplinary research. These Julia packages provide concise, extensible and performant tools for a wide range of grid‐based spatial models in ecology and beyond. More broadly, they highlight new opportunities for ecological modelling using the Julia language, with its combination of clear syntax, extensibility from its solution to the expression problem and its performance on CPUs and GPUs.

Reliability Assessment of Regional Climate Modeling: Case study in Johor State, Malaysia

This paper presents the work of statistically downscaling the CAN ESM 2 (Canada Earth System Model 2) climate data into regional climate data to produce the future climate scenario using the RCP (Representative Concentration Pathways) 2.6,4.5 and 8.5 green-house gas concentration trajectory suggested by Intergovernmental Panel on Climate Change Fifth Assessment Reports (IPCC-AR5). Selected location for regional climate downscaling includes Batu Pahat (1° 52’ N 102° 59’ E) and Kulai (1° 38’ N 103° 40’ E), downscaled outcome of monthly rainfall (mm), daily maximum (Tmax) and daily minimum (Tmin) temperature (°C) was produced by using SDSM (Statistical Downscaling Model) software to calibrate the CANESM2 output with the historical data. Quantile-mapping bias correction by using exponential distribution function was done to obtain bias corrected rainfall data. Reliability test using Pearson correlation coefficient was done by comparing between actual historical data. Based on Pearson correlation applied on bias corrected results, for Batu Pahat, the most suitable RCP model for both Tmax and Tmin is RCP 2.6, with correlation of 0.74 and 0.72, most suitable model for rainfall is RCP 4.5 with correlation of 0.24. For Kulai, the most suitable RCP model for Tmin is RCP 8.5, with correlation of 0.63, for Tmax and rainfall the suitable model is RCP 2.6, with correlation of 0.73 and 0.36. In overall, the more appropriate model to describe the climate for both Batu Pahat and Kulai based on Pearson correlation from year 2006 to 2019 is RCP 2.6, as the RCP 2.6 model are having higher correlation to the historical data.

Foredune dynamics at a Lake Michigan site during rising and high lake levels

On Great Lakes dunes, the link between foredune dynamics and coastal processes is seen in dune responses to changing lake levels. This paper investigates foredune dynamics during a recent period of rising and high lake levels. The study location was an active foredune in P.J. Hoffmaster State Park on the east coast of Lake Michigan, where field data were collected from 2000 through the final destruction of the foredune by wave removal in November 2019. Foredune dynamics were studied with erosion pins, direct observations, photographs, mapping, and on-site wind measurements. Regional climate and lake-level data were obtained from established data collection programs. The response of the foredune to rising lake levels was compared to several models of foredune behavior. During the study, the Lake Michigan-Huron level rose 1.89 m from January 2013 to July 2020. After an early transitional period, foredune activity was characterized by scarp retreat (4–19 m per year) and dune narrowing from 2014 to 2019. When the foredune completely disappeared in November 2019, erosion/scarping began on the next landward dune. The foredune activity fits Olson’s (1958) model for foredune growth and erosion through lake-level cycles. The foredune migration predicted by the revised Davidson-Arnott (2021) model of foredune response to relative water level rise did not occur, most likely because the rate of lake-level rise was too high. The six years of foredune narrowing before wave erosion started affecting the next landward dune represent a time-lag in Lake Michigan dune history models of increased dune activity during high lake-level stands.

Hydrological Evolution of a Lake Recharged by Groundwater in the Badain Jaran Desert Over the Past 140 years

Understanding the evolution of lakes in arid areas is very important for water resource management. Previous studies have mainly focused on lakes with runoff recharge, while the evolution of groundwater recharge lakes in hyper-arid areas is still less known. In this study, an 86 cm-long sediment core was extracted from Sayinwusu Lake, one of groundwater-recharge lakes in the southeastern Badain Jaran Desert, Northwest China. 210Pb and 137Cs dating, total organic carbon (TOC) and total nitrogen (TN) contents, and mineral content analysis were used to reconstruct the lake evolution over the past 140 years. The evolution of Sayinwusu Lake since 1880 can be divided into two periods. In the first period from 1880 to 1950, the TOC and TN contents were low, and the minerals consisted of all detrital minerals, which indicate that the lake’s primary productivity and salinity were low. During the second period from 1950 to 2018, the contents of TOC, TN, and carbonate minerals increased rapidly at the beginning of the 1950s, indicating that the lake’s primary productivity and salinity increased. Comprehensive analysis of regional climate data suggests that the increase in evaporation caused by rising temperature is an important factor affecting lake evolution in the desert. Although precipitation has increased in the arid region of Northwest China in recent decades with increasing temperature, the enhancement of the evaporation effect is much greater. As a record from groundwater recharge lakes in deserts, our study provides new insight into projecting future lake changes in hyper-arid areas.

Subarctic landscape adaptations and paleodemography: A 14,000-year history of climate change and human settlement in central Alaska and Yukon

Central Alaska and Yukon represent the longest continuously inhabited region in the Americas, with a rich record of research on technology, subsistence, and decision-making spanning over 14,000 years. Still, archaeologists debate whether the changes observed in the material and paleodemographic record can be interpreted as the result of environmental influences. This paper presents a multivariate analysis of regional occupation chronology, paleodemography, site placement, and climate data to investigate how past populations were affected by climate change. This research shows that populations were larger than expected at some of the earliest periods and that significant climatic and environmental events do not correspond with significant population decreases as researchers have previously argued. Changes in land use were gradual and unidirectional, with decreases in average site slope, increases in average site size, and consistent average site elevation through time. Trends in land use and paleodemography correspond to cultural phases assigned by regional experts, though environmental shifts undoubtedly played a role in shaping land use and culture throughout the past. This research has possible implications for our understanding of important cultural moments in the region's history, such as initial and subsequent migrations throughout the Americas.

Financial inclusion may limit sustainable development under economic globalization and climate change

Financial inclusion is a key policy for achieving the UN Sustainable Development Goals worldwide. However, emerging evidence has challenged the universal effectiveness of this policy. Combining a cross-sectional socio-economic and ecological survey with regional macro-economic and climatic data, we undertook an integrated causal analysis of the impact of financial inclusion policy on the Inner Mongolian herder social-ecological system. Exposure to economic globalization and climate change threatened herder livelihoods via increased feed costs and reduced livestock sales prices. Financial inclusion loans were beneficial for herders with large grassland plot size who used their traditional ecological knowledge to adapt via seasonal herd mobility. However, most herders were sedentary, constrained by small plot size, and used financial inclusion loans to reserve livestock and maintain high stocking densities. This strategy exposed them to inflated feed costs, increased their debt, and led to widespread grassland degradation. The results illustrate the limitations of financial inclusion policy in achieving sustainable development when people are trapped in poverty, subject to novel social-ecological contexts, and their ability to adapt is compromised. Transformative adaptations based on community cooperation, traditional knowledge and institutions, complementary public policies, and technological innovation are crucial to support financial inclusion policy and enhance sustainable development.

Analysis of Climate Change Projections for Mozambique under the Representative Concentration Pathways

Despite having contributed the least to global warming and having the lowest emissions, the African region is the most vulnerable continent to climate change impacts. To reduce the levels of risk arising from climate change, it is mandatory to combine both mitigation and adaptation. While mitigation can reduce global warming, not all impacts can be avoided. Therefore, adaptation is essential to advance strategic interventions and reduce the impacts. As part of the international effort to cope with changing climate, a set of Coordinated Regional Downscaling Experiment (CORDEX) domains have been established worldwide. The CORDEX-Africa initiative has been developed to analyze downscaled regional climate data over the African domain for climate data analysis techniques and engage users of climate information in both sector-specific and region/space-based applications. This study takes outputs of high-resolution climate multi-models from the CORDEX-Africa initiative constructed at a spatial resolution of 50 km to assess climate change projections over Mozambique. Projected spatial and temporal changes (three 30-year time periods, the present (2011–2040), mid (2041–2070), and the end (2071–2100)) in temperature and precipitation under the Representative Concentration Pathways RCP2.6, RCP4.5, and RCP8.5 are analyzed and compared relative to the baseline period (1961–1990). Results show that there is a tendency toward an increase in annual temperature as we move toward the middle and end of the century, mainly for RCP4.5 and RCP8.5 scenarios. This is evident for the Gaza Province, north of the Tete Province, and parts of Niassa Province, where variations will be Tmax (0.92 to 4.73 °C), Tmin (1.12 to 4.85 °C), and Tmean (0.99 to 4.7 °C). In contrast, the coastal region will experience less variation (values < 0.5 °C to 3 °C). At the seasonal scale, the pattern of temperature change does not differ from that of the annual scale. The JJA and SON seasons present the largest variations in temperature compared with DJF and MAM seasons. The increase in temperature may reach 4.47 °C in DJF, 4.59 °C in MAM, 5.04 °C in JJA, and 5.25 °C in SON. Precipitation shows substantial spatial and temporal variations, both in annual and seasonal scales. The northern coastal zone region shows a reduction in precipitation, while the entire southern region, with the exception of the coastal part, shows an increase up to 40% and up to 50% in some parts of the central and northern regions, in future climates for all periods under the three reference scenarios. At the seasonal scale (DJF and MAM), the precipitation in much of Mozambique shows above average precipitation with an increase up to more than 40% under the three scenarios. In contrast, during the JJA season, the three scenarios show a decrease in precipitation. Notably, the interior part will have the largest decrease, reaching a variation of −60% over most of the Gaza, Tete, and Niassa Provinces.

Microclimate and habitat heterogeneity as important drivers of soil Collembola in a karst collapse doline in the temperate zone

AbstractChanges in well‐delimited Collembola communities along a steep microclimatic gradient at the entrance of Silická ľadnica Ice Cave, Slovakia, were investigated after 10 years (2007, 2017). We focused on the occurrence of psychrophilic and endemic species occupying this unique karst collapse doline and their response to climatic singularities in the given years as well as the increasing trend in regional air temperature. The soil temperature means at sites across the doline slope corresponded with climatic trends in the periods 2006–2007 and 2016–2017. Significantly lower average soil temperatures but significantly higher mean abundances, species richness, and diversity indices of the collembolan communities were recorded at sites during the second study period, which was characterized by more favorable soil microclimatic conditions (temperature and moisture content) compared to the first period. The dominance structure and community composition of the studied assemblages appeared to be relatively constant after 10 years, indicating stable collembolan communities, especially at cold sites at the bottom of the doline. Redundancy ordination analysis documented a clear delimitation of the communities in relation to the soil temperature, pH, and C:N ratio in both periods. Long‐term (30‐year) regional climatic data showed an increasing trend of annual air temperature means and precipitation. However, an increase in the number and abundance of xerothermophilous species and a decline in psychrophilic species (mostly endemic) along the gradient as a potential response of the increasing regional temperature were not observed, suggesting the high resilience of these communities. Microclimate and habitat heterogeneity are probably major drivers of soil Collembola communities along the steep microclimatic gradient of a karst collapse doline, which was observed by the repeated sampling after 10 years. Karst dolines as potentially important local sources of ɑ‐diversity will likely become increasingly indispensable refugia for local biodiversity under ongoing global warming, thus deserving reliable conservation.

Designing an irrigation system using photovoltaic energy by considering crop type in Fergana Valley

Today, the importance of energy cost and efficiency is gradually increase. The decrease in drinking water and agricultural water resources, increases the interest in drip irrigation systems in agricultural irrigation. Environmentally friendly photovoltaic drip irrigation systems (PVDIS) are the appropriate solution in regions where there is no electricity distribution network, where it is far away, or where power cuts are frequently. This study is carried out in the Fergana Valley of Uzbekistan. Regional climate data obtained from Climwat 2.0 software are processed in Cropwat 8.0 software. Crops that are both the source of livelihood of the people of the region and that can be used in this study have been determined. Annual and daily water needs are analyzed so that these crops are irrigated every seven days. A system is designed by taking the data of the crop with the highest water requirement as a reference. The drip irrigation system is set up in a PVsyst 7.1.7 simulation environment to pump 114.24 m3 of water daily from a 5-meter-deep river with a 1.8 kW photovoltaic system. The efficiency of the system is 58.7% and the efficiency of the pump is 34.5%. Crop water need is met at the rate of 98.87%. It is predicted that the designed and analyzed PVDIS will provide efficiency in energy and water resources.

지자체 기후변화 대응을 위한 지역별 기후변화의 특성분석: 장기 관측자료를 중심으로

We investigated regional climate changes in South Korea over the last 40 years (1980 ~ 2019). The country was divided into 10 areas of Seoul, Gyeonggi, Gangwon, Chungbuk, Chungnam, Jeonbuk, Jeonnam, Gyeongbuk, Gyeongnam, and Jeju. We used the regional climate data (daily temperature and precipitation) measured by Korea Meteorological Administration (KMA) at 61 sites. There has been an annual average temperature increase of 1.4℃ for the last 40 years in Korea, with a range of +1.0℃ (Jeonnam) ~ +1.8℃ (Gangwon). The increases in annual minimum and maximum temperatures were even larger; the increase in annual maximum temperature was as high as 2.2℃ over a broad range of trends (+0.2℃ (Jeonnam) ~ +5.6℃ (Gyeonggi)). The change of annual total precipitation was not clear, but the southern part of Korea showed an increasing trend (Jeju(+206.4 mm/40years)), and the central part of Korea showed a decreasing trend (Chungnam (-119.6mm/40years)). The trend of annual temperature variability was negative in central Korea (Gyeonggi (-4.2℃/40 years)) and positive in southern Korea (Gyeongnam (+1.0℃ /40years)). The changes in the trends of monthly temperature variabilitiy differed by season; March (Gangwon (+0.1℃/40years) ~ Seoul (+3.6℃/40years)) and August (Jeju (-0.9℃/40 years) ~ Chungbuk (+2.9℃/40 years)) showed increasing trends due to the greater increase in maximum monthly temperatures. In comparison, September (Gyeongnam (-0.6℃/40 years) ~ Jeju (-3.5℃/40years)) and December (Seoul (+0.2℃/40 years) ~ Jeonbuk (-4.4℃/40 years)) showed decreasing trends due to the greater increase in minimum monthly temperatures. Those changes might cause different seasonal health impacts. Warming trends were noted in climate extreme indices over the last 40 years. For example, there was an almost one-month increase in the number of summer days (Tmax ≥ 25℃) in Seoul and 15-day increase in the number of tropical nights (Tmin ≥ 25℃) in Jeju. There was a similar decrease (14 days) in cold days (Tmin ≤ -12℃) in Gangwon. Our results show that regional differences in climate change over the last 40 years should be considered for establishing and implementing regional climate change adaptation policies.

Changes in intra-annual runoff and its response to climate variability and anthropogenic activity in the Lake Issyk-Kul Basin, Kyrgyzstan

An attribute study of the runoff changes due to climate change and anthropogenic activities is of great value to determining the best response to runoff changes. This study investigates the evolution of the intra-annual runoff and evaluates the effects of changes in climate and anthropogenic activities on runoff variations in the Lake Issyk-Kul Basin (LIKB). The monotonic trend test and wavelet transform analysis were used to characterize the trends and periods of the hydro-meteorological variables in the LIKB. In addition, the periodicity-trend superposition model and double-mass curves were used to assess the contributions of climate change and anthropogenic activities to runoff variations. The analyses were conducted using regional climate data combined with runoff data derived from 13 different river stations in the LIKB for the period between 1943 and 2012. The results indicate the following. (1) The monthly runoff trends in the three groups of tributaries (northern, southeastern, and southern tributaries) exhibit distinct differences, and the percentage of the data sets with no pattern gradually increased (from 26% to 38%) from north to south. There is a positive trend, with a similar decrease (from 50% to 24%) from north to south. (2) The air temperature, precipitation, and runoff in the LIKB increased throughout the low and high flow periods. The statistical index of the runoff concentration degree (RCD) decreased at most stations (Chong-Koi-Suu, Chong-Ak-Suu, Chong-Urykty, Pzhergalan, Ak-Sai, Tossor, Ton, Chong-Kyzyl-Suu, Tamga, and Karakol), except for the Cholpon-Ata, Ak-Suu, and Dzhuuku stations. (3) In addition, the periodic characteristics of the RCD show that the RCD has a 12-year significant period over the low flow period, which is similar to that for precipitation but varies from that for air temperature. (4) Climate variability and anthropogenic activities are two different contributors to runoff reduction in the LIKB. The respective contributions of anthropogenic activities to the runoff determined using the two methods were 35.3% and 18%, whereas the climate change contributions were 64.7% and 82%, respectively. Climate change was the main reason for the runoff variations. These results provide a basis for the scientific management and sustainable allocation of water resources in the LIKB.

The effects of regional climatic condition on the spread of COVID-19 at global scale

The pandemic outbreak of the novel coronavirus epidemic disease (COVID-19) is spreading like a diffusion-reaction in the world and almost 208 countries and territories are being affected around the globe. It became a sever health and socio-economic problem, while the world has no vaccine to combat this virus. This research aims to analyze the connection between the fast spread of COVID-19 and regional climate parameters over a global scale. In this research, we collected the data of COVID-19 cases from the time of 1st reported case to the 5th June 2020 in different affected countries and regional climatic parameters data from January 2020 to 5th June 2020. It was found that most of the countries located in the relatively lower temperature region show a rapid increase in the COVID-19 cases than the countries locating in the warmer climatic regions despite their better socio-economic conditions. A correlation between metrological parameters and COVID-19 cases was observed. Average daylight hours are correlated to total the COVID-19 cases with a coefficient of determination of 0.42, while average high-temperature shows a correlation of 0.59 and 0.42 with total COVID-19 cases and death cases respectively. The finding of the study will help international health organizations and local administrations to combat and well manage the spread of COVID-19.

Hotspots and ecoregion vulnerability driven by climate change velocity in Southern South America

Any conservation strategy must deal with the uncertainty caused by anthropogenic climate change. In order to forecast such changes, the climate change velocity approach has been used to measure ecosystem exposure to this phenomenon. The Tropical Andes and the Chilean Winter Rainfall-Valdivian Forests (Central Chile) hotspots are priority for conservation due to their high species richness and threats, where climate change is one of the serious pressures to their ecosystems. Even though previous studies have forecasted future climate velocity patterns across the globe, these biodiversity hotspots lack a regional evaluation of the vulnerability to climate change to inform conservation decisions. In this study, we evaluated the vulnerability of terrestrial ecosystems to climate change velocity at the Southern South America ecoregional system, by using regional climatic data that improves the accuracy of predictions. We estimated forward and backward velocities for temperature and precipitation, and we performed a protected area-level analysis of climate change vulnerability. Also, we compared our results with previous evaluations. We found that forward velocity was higher in the Tropical Andes hotspot for both climatic variables analyzed, whereas backward velocity was higher in the Central Chile hotspot considering just the temperature variable. Finally, we found that in the Central Chile hotspot, smaller protected areas are more vulnerable to climate change as measured by climate change velocity, whereas in the Tropical Andes hotspot, larger protected areas are more vulnerable. Several rapid change areas are expected along the two hotspots. These findings have important conservation implications in the region, especially for the protected areas.

Late Holocene glacier fluctuations in the Bhutanese Himalaya

Abstract Reconstructing high-resolution glacial fluctuation is critical for understanding glaciers response to climate change. Here, we present a detailed Late Holocene glacial record from the Bhutanese Himalaya based on 27 10Be surface exposure ages. This record includes a glacial event 4180 ± 270 yr, followed by four glacial events at 2990 ± 190, 1780 ± 110, 1230 ± 80 and 500 ± 70 yr, respectively. These glacial events are synchronous with those in the Tibetan Plateau (TP) and its surrounding mountains, which likely reflect regional climatic forcing. The comparisons of regional climate data indicate that these Late Holocene glacial events occured in relatively cold and dry climatic conditions, reflecting the glacial fluctuations were more sensitive to temperature than to precipitation. In addition, the timing of these glacial events is roughly in agreement with the North Atlantic (NA) region's cooling events. It seems that the glacial fluctuations were teleconnected with the NA region's cooling events by the Westerlies, which acts as a cold-air conveyer between the NA and the TP during the cold intervals. Although the weakening of Indian summer monsoon would reduce the precipitation and glacier accumulation in the study area, the low temperature brought by the Westerlies greatly reduces the amount of glacial ablation, resulting in an increase in the net accumulation of glaciers.

Respiratory dysbiosis and population-wide temporal dynamics in canine chronic bronchitis and non-inflammatory respiratory disease.

The lungs of people and companion animals are now recognized to harbor diverse, low biomass bacterial communities. While these communities are difficult to characterize using culture-based approaches, targeted molecular methods such as 16S rRNA amplicon sequencing can do so using DNA extracted from samples such as bronchoalveolar lavage fluid (BALF). Previous studies identified a surprisingly uniform composition of the microbiota in the lungs of healthy research dogs living in a controlled environment, however there are no reports of the lung microbiota of client-owned dogs. Moreover, compositional changes in the lung microbiota depending on disease status have been reported in people, suggesting that similar events may occur in dogs, a species subject to several respiratory disease mechanisms analogous to those seen in people. To address these knowledge gaps, BALF samples from client-owned dogs presenting to the University of Missouri Veterinary Health Center for respiratory signs between 2014 and 2017 were processed for and subjected to 16S rRNA sequencing. Based on specific diagnostic criteria, dogs were categorized as Chronic Bronchitis (CB, n = 53) or non-CB (n = 11). Community structure was compared between groups, as well as to historical data from healthy research dogs (n = 16) of a uniform breed and environment. The lung microbiota detected in all client-owned dogs was markedly different in composition from that previously detected in research dogs and contained increased relative abundance of multiple canine fecal and environmental bacteria, likely due to aspiration associated with their clinical signs. While inter-sample diversity differed significantly between samples from CB and non-CB dogs, the variability within both groups made it difficult to discern reproducible bacterial classifiers of disease. During subsequent analyses to identify other sources of variability within the data however, population-wide temporal dynamics in community structure were observed, with substantial changes occurring in late 2015 and again in early 2017. A review of regional climate data indicated that the first change occurred during a historically warm and wet period, suggesting that changes in environmental conditions may be associated with changes in the respiratory microbiota in the context of respiratory disease. As the lung microbiota in humans and other animals is believed to result from repetitive micro-aspirations during health and in certain disease states associated with dyspnea and laryngeal dysfunction, these data support the increased colonization of the lower airways during compromised airway function, and the potential for temporal effects due to putative factors such as climate.

Circumferential and Longitudinal δ13C Variability in a Larix decidua Trunk from the Swiss Alps

Tree-ring stable isotopes are insightful proxies providing information on pre-instrumental climate fluctuations, yet the variability of these data within a tree trunk has not been fully explored. Here, we analyze longitudinal and circumferential changes in tree-ring δ13C values from 1991–2010, considering seven height levels from 1 to 13 m above ground and six sampling directions (radii) separated by 60° around the stem. The disk samples were taken from a 360-year old European larch (Larix decidua Mill.) that grew at 1675 m above sea level in the Simplon Valley, Switzerland. Results show that the circumferential δ13C variability, defined as the difference between the minimum and maximum isotope values within a single ring at a certain height, ranges from 0.5 to 2.8‰. These differences appear substantial as they match the range of year-to-year variations retained in long tree-ring δ13C time series used for climate reconstruction. The assessment of longitudinal variability demonstrated a systematic change of ~0.1‰ m−1 towards isotopically heavier (less negative) δ13C values with increasing tree height, likely reflecting a vertical gradient towards isotopically heavier needle tissue due to changing microclimatic conditions and CO2 stratification within the canopy. Calibration against regional climate data indicates no substantial signal changes in δ13C values within the trunk. We conclude that the longitudinal isotope gradient adds uncertainty to long δ13C chronologies derived from subfossil material of unknown (and changing) sampling heights. The large circumferential variability recorded in the sub-alpine larch suggests that more than two cores are needed to analyze absolute δ13C values representative for each tree.

ЙМОВІРНІ ЗМІНИ КЛІМАТИЧНИХ УМОВ УКРАЇНИ ДО СЕРЕДИНИ ХХІ СТ.

In Ukraine, as in the world, substantial climatic changes have happened throughout past decades. It is a fact that they are manifested in changing of parameters of the thermal regime, regimes of wind and humidity. It is expected that they will be observed also in future that will lead to aggravation of negative effects and risks due to climate change. That determines the relevance of the problem of forecasting such changes in future both globally and regionally. After all, knowledge of climate’s behavior in future is very important in the development of strategies, program and measures to adapt to climate change. The article is devoted to assessing spatio-temporal distribution main climatic indicators (air temperature, wind speed and relative humidity) in Ukraine, their variability and the probable values to the middle of the 21st century (2021-2050). Projection of changes in meteorological conditions was made for A1B scenario of SRES family using data of the regional climate model REMO and data from the hydrometeorological observation network of Ukraine (175 stations). Estimated data obtained from the European FP-6 ENSEMBLES project with a resolution of 25 km. For spatial distribution (mapping) we used open-source Geographic Information System QGIS, type of geographic coordinate system for project is WGS84. In the middle of the XXI century, if A1B scenario is released, it is expected a significant changes of climatic parameters regarding the 1981-2010 climatic norm: air temperature is rise by 1,5 °C, average wind speed is decrease by 5-8%, relative humidity in winter probably drop by 2%, but in summer it rises by 1,5%. The unidirectionality of the changes is characteristic only of air temperature, for wind speed and relative humidity the changes are in different directions. The intensity of changes is also not uniform across the country for all climatic parameters, has its regional and seasonal features. Statistical likelihood for most of highlighted changes for all climatic parameters is 66 % and more, the air temperature change is virtually certain (p-level <0.001).

Encounters Between Experiences and Measurements: The Role of Local Knowledge in Climate Change Research

Innovative approaches could enhance scientific insights into how climate change affects mountain ecosystems and livelihoods and enrich climate action. Using an inter- and transdisciplinary approach in a remote tropical dry forest region of the Andes in southern Ecuador, this article combines local knowledge about climate change and adaptation, based on perceptions and experiences, with quantitative climate measurements. Our theoretical framework is based on the concept of vulnerability and sustainable livelihoods perspectives. Methodologically, we draw on the Participatory Rural Appraisal approach. Participatory workshops and qualitative interviews were carried out in the canton of Macara between 2015 and 2017. Local and regional climate data series were analyzed for climate trends and extreme events. Our study improves understanding of the social and physical dimension of climate change. Especially in mountain areas, differing scales of climate data must be considered to capture local climate conditions and changes. Thus, local knowledge could make a major contribution to selecting representative climate datasets, estimating local impacts of climate change, and developing adaptation policies.

Effects of climate and land-use change scenarios on fire probability during the 21st century in the Brazilian Amazon.

The joint and relative effects of future land-use and climate change on fire occurrence in the Amazon, as well its seasonal variation, are still poorly understood, despite its recognized importance. Using the maximum entropy method (MaxEnt), we combined regional land-use projections and climatic data from the CMIP5 multimodel ensemble to investigate the monthly probability of fire occurrence in the mid (2041-2070) and late (2071-2100) 21st century in the Brazilian Amazon. We found striking spatial variation in the fire relative probability (FRP) change along the months, with October showing the highest overall change. Considering climate only, the area with FRP≥0.3 (a threshold chosen based on the literature) in October increases 6.9% by 2071-2100 compared to the baseline period under the representative concentration pathway (RCP) 4.5 and 27.7% under the RCP 8.5. The best-case land-use scenario ("Sustainability") alone causes a 10.6% increase in the area with FRP≥0.3, while the worse-case land-use scenario ("Fragmentation") causes a 73.2% increase. The optimistic climate-land-use projection (Sustainability and RCP 4.5) causes a 21.3% increase in the area with FRP≥0.3 in October by 2071-2100 compared to the baseline period. In contrast, the most pessimistic climate-land-use projection (Fragmentation and RCP 8.5) causes a widespread increase in FRP (113.5% increase in the area with FRP≥0.3), and prolongs the fire season, displacing its peak. Combining the Sustainability land-use and RCP 8.5 scenarios causes a 39.1% increase in the area with FRP≥0.3. We conclude that avoiding the regress on land-use governance in the Brazilian Amazon (i.e., decrease in the extension and level of conservation of the protected areas, reduced environmental laws enforcement, extensive road paving, and increased deforestation) would substantially mitigate the effects of climate change on fire probability, even under the most pessimistic RCP 8.5 scenario.