Potential Effects Of Climate Change Research Articles

EXPLORE THE CLIMATE CHANGE IMPACT SCENARIO OF URBAN CITIES IN BANGLADESH: A QUALITATIVE APPROACH

Bangladesh is one of the vulnerable countries which is mostly exposed to the influences of climate change and along with urban areas being particularly at-risk severity. This paper explores the climate change effect scenario of lower and middle-income (LMIC) urban cities in Bangladesh using a qualitative approach. The study aims to categorize the current and potential forthcoming effects of climate change on LMIC urban cities in Bangladesh, as well as the coping and adaptation approaches adopted by the municipal communities. This study was conducted in three LMIC urban cities of Bangladesh, namely Dhaka, Chattogram, and Khulna, using semi-structured key informant interviews (KIIs) and focus group discussions (FGDs) with local government officials, community leaders and key representatives from relevant NGOs. The results of the study show that LMIC urban municipalities in Bangladesh are already experiencing various influences of natural calamities and hazards, such as cyclone, heavy rainfall, flooding, waterlogging, heatwaves, cold wave and sea-level rise high & low tide etc. These include the expansion of early warning systems, flood control measures, and the promotion of sustainable urban development practices. The study also exposes that local communities have developed various coping and adaptation strategies, including the construction of flood-resistant structures, water management systems, and awareness-raising campaigns on climate change. Overall, the study highlights on the urgent requirement for policymakers, urban planners, and others key stakeholders to take proactive procedures to address the impacts of climate change on LMIC urban cities in Bangladesh. The study underscores the importance of accepting a multi-stakeholder approach that contains the active participation of all relevant stakeholders in developing and executing effective adaptation tactics. The findings of this study have important suggestions for policy and practice in Bangladesh and other LMIC countries. The study highlights the need for more comprehensive and integrated approaches to climate change adaptation in LMIC urban cities, which should take into account the social, economic, and political context of these areas. The study also emphasizes the importance of community-based and participatory methods to climate change adaptation, which can increase the resilience and adaptive capacity of urban local communities.

Modelling the climate change impacts on river discharge and inundation extent in the Magdalena River basin – Colombia

ABSTRACT Climate change may have significant impacts on water balance and may considerably influence flooding dynamics of river systems by increasing extreme precipitation. This study evaluates the potential effects of climate change on river discharge and inundation in the Magdalena River basin, the main river in Colombia, using the synergy between the MGB (Modelo de Grandes Bacias) hydrological–hydrodynamic model and downscaled Eta-regional climate model (RCM) projections based on four global climate models (GCMs): BESM (Brazilian Earth System Model), CanESM2 (Canadian Earth System Model), MIROC5 (Model for Interdisciplinary Research on Climate Version Five), and HadGEM2-ES (Hadley Centre Global Environment Model version 2). We used two different greenhouse gas scenarios (RCP4.5 and RCP8.5 (Representative Concentration Pathway)) for the “historical” (1986–2005) and “mid-term prospective” (2046–2065) periods. Model results for the “mid-term prospective” period under scenarios RCP4.5 and RCP8.5 indicate increase in mean river discharges in the east portion of the basin, decreased river discharges (mainly in the dry season) in the upper Magdalena basin, and increased inundation extent. By coupling hydrological–hydrodynamic and GCMs/RCMs models, modelling frameworks like the one used in this study provide an effective management tool for stakeholders interested in potential climate change impacts on tropical river basins.

Investigating the Effects of Climate and Land Use Changes on Rawal Dam Reservoir Operations and Hydrological Behavior

In order to assess the effects of climate change and land use change on Rawal Dam, a major supply of water for Rawalpindi and Islamabad, this study uses hydrological modeling at the watershed scale. The HEC-HMS model was used to simulate the hydrological response in the Rawal Dam catchment to historical precipitation. The calibrated model was then used to determine how changes in land use and climate had an impact on reservoir inflows. The model divided the Rawal Dam watershed into six sub-basins, each with unique features, and covered the entire reservoir’s catchment area using data from three climatic stations (Murree, Islamabad Zero Point and Rawal Dam). For the time spans of 2003–2005 and 2006–2007, the model was calibrated and verified, respectively. An excellent fit between the observed and predicted flows was provided by the model. The GCM (MPI-ESM1-2-HR) produced estimates of temperature and precipitation under two Shared Socioeconomic Pathways (SSP2 and SSP5) after statistical downscaling with the CMhyd model. To evaluate potential effects of climate change and land use change on Rawal Dam, these projections, along with future circumstances for land use and land cover, were fed to the calibrated model. The analysis was carried out on a seasonal basis over the baseline period (1990–2015) and over future time horizon (2016–2100), which covers the present century. The findings point to a rise in precipitation for both SSPs, which is anticipated to result in an increase in inflows throughout the year. SSP2 projected a 15% increase in precipitation across the Rawal Dam catchment region until the end of the twenty-first century, while SSP5 forecasted a 17% increase. It was determined that higher flows are to be anticipated in the future. The calibrated model can also be utilized successfully for future hydrological impact assessments on the reservoir, it was discovered.

Potential Effects of Climate Change on Agricultural Water Resources in Riyadh Region, Saudi Arabia

The water supply in Saudi Arabia is already depleted. Climate change will exacerbate the demand for these resources. This paper examines how climate change affects the water demands of Saudi Arabia’s most important food crops: wheat, clover, vegetables, and dates. To reduce the adverse climate change impacts on these crops’ productivity, as well as their irrigation water requirements (IWR), a number of adaptation techniques were investigated. The study was carried out for the Ar Riyadh region, Saudi Arabia, with a cultivated area of 179,730 ha. In this study, five climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) for two Shared Socio-economic Pathways (SSPs), SSP2-4.5 and SSP5-8.5, were used to forecast and investigate the potential impacts of climate change on agricultural water resources in the Al-Riyadh Region of Saudi Arabia. To simulate IWRs under the present and projected climate change scenarios, CROPWAT8.0 was used. The results showed that the maximum increase ratio in 2100 under SSP2-4.5 and SSP5-8.5, respectively, will be 4.46% and 12.11% higher than in the current case (2020). The results showed that the projected maximum temperatures in 2100 will be increased by 4.46% and 12.11%, respectively, under SSP2-4.5 and SSP5-8.5, compared to the current case (2020), supporting past research on the Arabian Peninsula that revealed that both short- and long-term temperature increases are anticipated to be considerable. Under SSP2-4.5 and SSP5-8.5, the projected ETo was found to be increased by 2.18% and 6.35% in 2100, respectively. Given that evapotranspiration closely mirrors the temperature behavior in the study region from June to August, our data suggest that crop and irrigation demand may increase in the mid to long term. The findings indicate that Riyadh, Saudi Arabia’s capital and commercial hub, will require more water to irrigate agricultural land because of the expanding ETo trend. Under SSP2-4.5 and SSP5-8.5, the projected growth irrigation water requirement (GIWR) will be increased by 3.1% and 6.7% in 2100, respectively. Under SSP5-8.5, crop areas of wheat, clover, dates, maize, citrus, tomato, potato, and other vegetables in Ar Riyadh will decrease by 6.56%, 7.17%, 5.90%, 6.43%, 5.47%, 6.99%, 5.21%, and 5.5%, respectively, in 2100. Conversely, under SSP2-4.5, the crop areas will decrease by 3.10%, 3.67%, 2.35%, 3.83%, 2.32%, 4.18%, 1.72%, and 2.38% in 2100, respectively. This research could aid in clarifying the adverse climate change impacts on GIWR in Ar Riyad, as well as improving water resource management planning.

The implications of seasonal climatic effects for managing disturbance dependent populations under a changing climate

Abstract The frequency of ecological disturbances, such as fires, is changing due to changing land use and climatic conditions. Disturbance‐adapted species may thus require the manipulation of disturbance regimes to persist. However, the effects of changes in other abiotic factors, such as climatic conditions, are frequently disregarded in studies of such systems. Where climatic effects are included, relatively simple approaches that disregard seasonal variation in the effects are typically used. We compare predictions of population persistence using different fire return intervals (FRIs) under recent and predicted future climatic conditions for the rare fire‐dependent herb Eryngium cuneifolium. We used functional linear models (FLMs) to estimate the cumulative effect of climatic variables across the annual cycle, allowing the strength and direction of the climatic impacts to differ over the year. We then estimated extinction probabilities and minimum population sizes under past and forecasted future climatic conditions and a range of FRIs. Under forecasted climate change, E. cuneifolium is predicted to persist under a much broader range of FRIs, because increasing temperatures are associated with faster individual growth. Climatic impacts on fecundity do not result in a temporal trend in this vital rate due to antagonistic seasonal effects operating through winter and summer temperatures. These antagonistic seasonal climatic effects highlight the importance of capturing the seasonal dependence of climatic effects when forecasting their future fate. Synthesis. Awareness of the potential effects of climate change on disturbance‐adapted species is necessary for developing suitable management strategies for future environmental conditions. However, our results suggest that widely used simple methods for modelling climate impacts, that disregard seasonality in such effects, may produce misleading inferences.

Investigating Drought Events and Their Consequences in Wildfires: An Application in China

Understanding the impact of drought on fire dynamics is crucial for assessing the potential effects of climate change on wildfire activity in China. In this study, we present a series of multiple linear regression (MLR) models linking burned area (BA) during mainland China’s fire season from 2001 to 2019, across seven regions, to concurrent drought, antecedent drought, and time trend. We estimated burned area using Collection 6 Moderate Resolution Imaging Spectradiometer (MODIS) and drought indicators using either the Standardized Precipitation Evapotranspiration Index (SPEI) or the self-calibrated Palmer Drought Severity Index (sc-PDSI). Our findings indicate that the wildfire season displays a spatial variation pattern that increases with latitude, with the Northeast China (NEC), North China (NC), and Central China (CC) regions identified as the primary areas of wildfire occurrence. Concurrent and antecedent drought conditions were found to have varying effects across regions, with concurrent drought as the dominant predictor for NEC and Southeast China (SEC) regions and antecedent drought as the key predictor for most regions. We also found that the Northwest China (NWC) and CC regions exhibit a gradual decrease in burned area over time, while the NEC region showed a slight increase. Our multiple linear regression models exhibited a notable level of predictive power, as evidenced by the average correlation coefficient of 0.63 between the leave-one-out cross-validation predictions and observed values. In particular, the NEC, NWC, and CC regions demonstrated strong correlations of 0.88, 0.80, and 0.76, respectively. This indicates the potential of our models to contribute to the prediction of future wildfire occurrences and the development of effective wildfire management and prevention strategies. Nevertheless, the intricate relationship among fire, climate change, human activities, and vegetation distribution may limit the generalizability of these findings to other conditions. Consequently, future research should consider a broad range of factors to develop more comprehensive models.

Safeguarding plant genetic resources in the United States during global climate change

AbstractPlant genetic resources (PGR) underpin the security of global agriculture. Rapid global climate change presents formidable challenges for ex situ and in situ PGR management programs that operate over extended timeframes. The U.S. Department of Agriculture National Plant Germplasm System (NPGS) maintains more than 605,000 PGR accessions representing over 16,300 plant species in 20 genebank locations. These PGR are maintained in cold storage as seeds and vegetative tissues that must be periodically regenerated; or as actively growing plants in fields, greenhouses, screenhouses, and in vitro; or in some cases within in situ reserves. The complicated relationships between crops and their growth environments present unique challenges regarding PGR maintenance under a changing climate. Here we present potential effects of climate change on ex situ PGR maintenance and reproductive success, pollinators and beneficial insects, pathogens and pests, infrastructure considerations, and wild populations within NPGS in situ reserves. We provide a novel tool that summarizes past US temperature and precipitation data alongside future climate projections to guide ongoing planning for the effects of climate change for NPGS genebanks throughout the United States. A series of case studies exemplify instances where climate change has already impacted NPGS PGR management. Ongoing improvements to NPGS PGR management in response to climate change require continued observations of the current effects, careful and innovative planning, and creative approaches to ensure that PGR are successfully conserved for future generations.

The legacy of one hundred years of climate change for organic carbon stocks in global agricultural topsoils

Soil organic carbon (SOC) of agricultural soils is observed to decline in many parts of the world. Understanding the reasons behind such losses is important for SOC accounting and formulating climate mitigation strategies. Disentangling the impact of last century’s climate change from effects of preceding land use, management changes and erosion is difficult and most likely impossible to address in observations outside of warming experiments. However, the record of last century’s climate change is available for every part of the globe, so the potential effect of climate change on SOC stocks can be modelled. In this study, an established and validated FAO framework was used to model global agricultural topsoil (0–30 cm) SOC stock dynamics from 1919 to 2018 as attributable to climate change. On average, global agricultural topsoils could have lost 2.5 ± 2.3 Mg C ha−1 (3.9 ± 5.4%) with constant net primary production (NPP) or 1.6 ± 3.4 Mg C ha−1 (2.5 ± 5.5%) when NPP was considered to be modified by temperature and precipitation. Regional variability could be explained by the complex patterns of changes in temperature and moisture, as well as initial SOC stocks. However, small average SOC losses have been an intrinsic and persistent feature of climate change in all climatic zones. This needs to be taken into consideration in reporting or accounting frameworks and halted in order to mitigate climate change and secure soil health.

Spatial analysis of future climate risk to stormwater infrastructure.

Climate change is expected to result in more intense precipitation events that will affect the performance and design requirements of stormwater infrastructure. Such changes will vary spatially, and climate models provide a range of estimates of the effects on events of different intensities and recurrence. Infrastructure performance should be evaluated against the expected range of events, not just rare extremes. We present a national-scale, spatially detailed screening assessment of the potential effects of climatic change on precipitation, stormwater runoff, and associated design requirements. This is accomplished through adjustment relative to multiple future climate scenarios of precipitation intensity-duration-frequency analyses presented in NOAA Atlas 14, which are commonly used in infrastructure design. Future precipitation results are estimated for each Atlas 14 station (these currently omit the Pacific Northwest). Results are interpolated using a geographically conditioned regression kriging approach to provide information about potential climate change impacts in a format more directly useful to local stormwater managers. The intensity of 24-h events with 2-year or greater recurrence is likely to increase in most areas of the United States leading to increased runoff and potential need for increased storage volumes. Changes in more frequent events (e.g., the 90th percentile event) commonly used in design of green infrastructure are relatively less.

Light, ammonium, pH, and phytoplankton competition as environmental factors controlling nitrification

AbstractThe biogeochemical cycling of nitrogen (N) plays a critical role in supporting marine ecosystems and controlling primary production. Nitrification, the oxidation of ammonia (NH3) by microorganisms, is an important process in the marine N cycle, supplying nitrate (), the primary source of N that fuels new phytoplankton growth, and the primary substrate for the microbial process of denitrification. Understanding nitrification in the Chukchi Sea, the shallow sea overlying the continental shelf north of Alaska and the Bering Strait, is particularly important as phytoplankton growth there has been shown to be limited by N. However, the controls on nitrification in the water column and potential effects of climate change remain unknown. This study seeks to characterize the controls on nitrification in the Chukchi Sea. We found light to be a strong control on nitrification rates. Nitrification was undetectable at light levels above 23 μmol photons m−2 s−1. Subsequently, sea ice concentration was related to nitrification, with rates being higher at stations with high ice cover where light transmission to the water column was reduced. High ammonium () concentrations also enhanced nitrification, suggesting that nitrifying organisms were substrate‐limited, likely due to competition for from phytoplankton. Unlike previous experimental studies, we found that nitrification rates were higher under low pH conditions. As the effects of ocean acidification and warming disproportionately impact the Arctic, nitrification rates will undoubtedly be affected. Our results will help guide future studies on potential implications of climate change on the biogeochemistry of N in the Chukchi Sea.

Diapause of the Western cherry fruit fly, Rhagoletis indifferens (Diptera: Tephritidae): metabolic rate and overwintering adaptations.

The Western cherry fruit fly, Rhagoletis indifferens (Curran), is a Tephritid fly in the Pacific Northwest and is known to infest native bitter cherry, Prunus emarginata (Douglas ex Hooker), which is distributed throughout the Cascade Mountain range. This species occupies temperate to alpine climates and exhibits overwintering adaptations of diapause and supercooling. Isothermal and differential scanning calorimetry were used to determine the effects of diapause chilling duration and post-chilling warm rearing on the metabolic rate and supercooling point of R. indifferens. Previous studies have included the effects of chilling duration on post-diapause development and emergence as well as on the levels of metabolic reserves. Metabolic rate of R. indifferens, was used to calculate the ability of this species to remain in diapause for more than 1 yr as well as predicting the potential effects of climate change on the future abundance and distribution. It was determined that R. indifferens could diapause for more than 1 yr based on the levels of metabolic reserves and metabolic rate.

The effects of climate change on cytotype distributions of endemic genera in the North American Coastal Plain

ABSTRACT Background Approximately 33% of plant species face extinction due to climate change. Polyploidisation, a process resulting in more than two complete sets of chromosomes, may be promoted by periods of climate fluctuations. Ecological niche modelling (ENM) using occurrences of endemic plants in the North American Coastal Plain (NACP) biodiversity hotspot could be used to evaluate the potential effects of climate change on cytotype distributions. Aims We used known diploid and polyploid taxa endemic to the NACP to test hypotheses that diploids and polyploids differed in habitat preferences, considerable overlap existed between cytotypes, and polyploid distributions would increase under climate change projections. Methods We examined niche identity and overlap of 28 congeneric ploidy level pairs and performed ENM to evaluate how climate change could affect these groups. Results Congeneric ploidy level pairs differed significantly in niche identity, and overlap varied across genera. Eleven genera showed greater than 100% increases in habitat suitability and six genera showed almost no remaining suitable habitat in at least one future climate scenario. Conclusions With 70% of the species that showed substantial declines in projected suitable habitat being of conservation concern, we propose that future studies of these genera should be a primary focus in the NACP.

Assessing Potential Effects of Climate Change on Highway-Runoff Flows and Loads in Southern New England by Using Planning-Level Space-for-Time Analyses

Transportation agencies need information about the potential effects of climate change on the volume, quality, and treatment of stormwater to mitigate potential effects of runoff on receiving waters. To address these concerns, the U.S. Geological Survey and the Federal Highway Administration used the Coupled Model Intercomparison Project tool and the Stochastic Empirical Loading and Dilution Model to perform space-for-time stormwater quality analyses. This study indicated that spatial variations in precipitation statistics within and adjacent to southern New England are greater than projected climate-related changes for the centroid of this region. A dilution-factor analysis indicated that highway runoff would become a greater proportion of downstream flows if average event volumes or time between event midpoints increase and would become a smaller proportion of downstream flows if event durations increase. Highway-runoff yield analyses for total phosphorus (TP) indicate that uncertainty in water quality statistics results in variations in long-term average yields from about 1.69 to 7.96 times higher than the lowest TP values simulated. In comparison, variations in precipitation statistics cause yield variations that ranged from 1.41 to 1.76 for the different simulated concentrations. An analysis of stormwater treatment indicated that uncertainties in runoff treatment variables are also larger than the magnitude of climate variations. This study does not question the potentially large climate-related changes in hydrologic and hydraulic variables expected to occur in the foreseeable future. It does indicate that uncertainties in the current data and potential effects of land use change on stormwater quality and treatment variables are larger than the projected effects of climate change.

Quantifying the Potential Vegetation Distribution under Climate Change: The Case of Cryptomeria fortunei in Dongting Lake Watershed, China

Potential vegetation distribution is an important study in environmental sciences. We utilized the Mixed Least Squares–Total Least Squares (MLS-TLS) method and the Signal Mode Decomposition method and the Ecological Niche model to identify the inter-correlations of internal climate change factors and constructed an environmental factor response regression model. We identified the resonance periods and trend relationships among climate factors (temperature, precipitation, and evapotranspiration) and found that the evapotranspiration of the watershed interferes with the correlation between temperature and precipitation on a five-year scale. The specific change degree of extreme climate indicators in the region was quantified by the Range of Variability Approach, among which the precipitation indicators were all below 33% (low change). There were significant differences between the key bioclimatic variables and Aspect of the development of suitable vegetation habitats. The difference between the Aspect and average daily air temperature is the main contributor to the spatial distribution of vegetation, and the mutual contribution is 76.19%. Our regression model can effectively simulate the potential distribution of vegetation (r = 0.854). Compared to the MaxEnt model, our regression model can quantitatively and intuitively provide suitable habitat values for Cryptomeria fortunei at any given location in the basin. Under future scenarios (2021–2040), suitable habitat for Cryptomeria fortunei in the eastern and western regions of the basin is projected to deteriorate further. The research results can provide some help for policymakers to eliminate the potential adverse effects of future climate change on regional ecology.

Extreme drought disrupts plant phenology: Insights from 35 years of cloud forest data in Venezuela.

The potential effects of climate change on plant reproductive phenology include asynchronies with pollinators and reductions in plant fitness, leading to extinction and loss of ecosystem function. In particular, plant phenology is sensitive to extreme weather events, which are occurring with increasing severity and frequency in recent decades and are linked to anthropogenic climate change and shifts in atmospheric circulation. For 15 plant species in a Venezuelan cloud forest, we documented dramatic changes in monthly flower and fruit community composition over a 35-year time series, from 1983 to 2017, and these changes were linked directly to higher temperatures, lower precipitation, and decreased soil water availability. The patterns documented here do not mirror trends in temperate zones but corroborate results from the Asian tropics. More intense droughts are predicted to occur in the region, which will cause dramatic changes in flower and fruit availability.

Multiscale ecological niche modeling exhibits varying climate change impacts on habitat suitability of Madrean Pine-Oak trees

Anthropogenic climate change and increasing greenhouse gas emissions are expected to globally impact the biological function, community structure, and spatial distribution of biodiversity. Many existing studies explore the effect of climate change on biodiversity, generally at a single spatial scale. This study explores the potential effects of climate change on the habitat suitability of seven tree species at two distinct spatial scales: the Coronado National Forest (CNF), a local management area, and the Sierra Madre Occidental (SMO), an ecoregional extent. Habitat suitability was determined by extrapolating Ecological Niche Models (ENMs) based on citizen-science tree occurrence records into future climatic conditions using projected 30-year normals for two anthropogenic emissions scenarios through the end of the century. These ENMs, examined at a spatial resolution of 1 km2, are constructed using a mean average ensemble of three commonly used machine learning algorithms. The results show that habitat suitability is expected to decrease for all seven tree species at varying degrees. Results also show that climate-forcing scenario choice appears to be far less important for understanding changes in species habitat suitability than the spatial scale of modeling extent. Additionally, we observed non-linear changes in tree species habitat suitability within the SMO and CNF dependent on forest community type, latitude, and elevational gradient. The paper concludes with a discussion of the necessary steps to verify the estimated alters of these tree species under climate change. Most importantly, provides a framework for characterizing habitat suitability across spatial scales.

Review of policies and actions on tackling global climate change - COP26 - is this the last chance?

The world is facing the visible and potential consequences of climate change. No place on the Earth is immune to these changes. Current policy applied worldwide anticipates global warming of about 2.7oC compared to pre-industrial level by the end of the century. By implementation of Nationally Determined Contributions (NDCs), warming will be kept to 2.4oC. If long-term commitment targets or net-zero targets are included, then warming would be kept to about 2.1oC above the pre-industrial levels. The warming projections dropped by 0.3oC after the made pledges and established targets by the USA and Peoples’ Republic of China. According to the “optimistic” scenario, if the 140 analysed countries reach the zero emission targets, then the average warming will be 1.8oC, or below 2oC. There is a significant gap between the pledges made by the governments and the total level of actions they have undertaken so far.With the new economic challenges, it is clear that we are at a crossroads. The impact of COVID-19 crisis will be crucial for the future of the climate policy. Climate changes will not wait. Their threat is over our heads and each and every day we face them. Every individual has a role to play in dealing with global climate change and we all can contribute to this threat if we all work together in a synchronous way. A greater political involvement is needed along with collective actions taken by all social actors. Over the last two years, the World Health Organization has advocated for greater inclusion of health authorities and services in Nationally determined contributions through activities to reduce the implications on health by climate change.

Assessing the impact of wildfires on water quality using satellite remote sensing: the Lake Baikal case study

Lakes have been observed as sentinels of climate change. In the last decades, global warming and increasing aridity has led to an increase in both the number and severity of wildfires. This has a negative impact on lake catchments by reducing forest cover and triggering cascading effects in freshwater ecosystems. In this work we used satellite remote sensing to analyse potential fire effects on lake water quality of Lake Baikal (Russia), considering the role of runoff and sediment transport, a less studied pathway compared to fire emissions transport. The main objectives of this study were to analyse time series and investigate relationships among fires (i.e., burned area), meteo-climatic parameters and water quality variables (chlorophyll-a, turbidity) for the period 2003–2020. Because Lake Baikal is oligotrophic, we expected detectable changes in water quality variables at selected areas near the three mains tributaries (Upper Angara, Barguzin, Selenga) due to river transport of fire-derived burned material and nutrients. Time series analysis showed seasonal (from April to June) and inter-annual fire occurrence, precipitation patterns (high intensity in summer) and no significant temporal changes for water quality variables during the studied periods. The most severe wildfires occurred in 2003 with the highest burned area detected (36,767 km2). The three lake sub-basins investigated have shown to respond differently according to their morphology, land cover types and meteo-climatic conditions, indicating their importance in determining the response of water variables to the impact of fires. Overall, our finding suggests that Lake Baikal shows resilience in the medium-long term to potential effects of fires and climate change in the region.

Predicting the Impact of Climate Change on the Distribution of Rhipicephalus sanguineus in the Americas

Climate change may influence the incidence of infectious diseases including those transmitted by ticks. Rhipicephalus sanguineus complex has a worldwide distribution and transmits Rickettsial infections that could cause high mortality rates if untreated. We assessed the potential effects of climate change on the distribution of R. sanguineus in the Americas in 2050 and 2070 using the general circulation model CanESM5 and two shared socioeconomic pathways (SSPs), SSP2-4.5 (moderate emissions) and SSP2-8.5 (high emissions). A total of 355 occurrence points of R. sanguineus and eight uncorrelated bioclimatic variables were entered into a maximum entropy algorithm (MaxEnt) to produce 50 replicates per scenario. The area under the curve (AUC) value for the consensus model (>0.90) and the partial ROC value (>1.28) indicated a high predictive capacity. The models showed that the geographic regions currently suitable for R. sanguineus will remain stable in the future, but also predicted increases in habitat suitability in the Western U.S., Venezuela, Brazil and Bolivia. Scenario 4.5 showed an increase in habitat suitability for R. sanguineus in tropical and subtropical regions in both 2050 and 2070. Habitat suitability is predicted to remain constant in moist broadleaf forests and deserts but is predicted to decrease in flooded grasslands and savannas. Using the high emissions SSP5-8.5 scenario, habitat suitability in tropical and subtropical coniferous forests and temperate grasslands, savannas, and shrublands was predicted to be constant in 2050. In 2070, however, habitat suitability was predicted to decrease in tropical and subtropical moist broadleaf forests and increase in tropical and subtropical dry broadleaf forests. Our findings suggest that the current and potential future geographic distributions can be used in evidence-based strategies in the design of control plans aimed at reducing the risk of exposure to zoonotic diseases transmitted by R. sanguineus.

기후변화에 따른 멸종위기 야생생물 2급 백부자의 잠재서식처 변화와 파편화 예측

Climate change influences various aspects of life on earth including distribution shifts, phenology, and interaction with other organisms. Endangered species respond more sensitively to changes within their limited distribution range. In this study, we analyzed and modeled the current distribution habitat of Aconitum coreanum, which is classified as an endangered species level 2, and further projected potential distribution changes and habitat fragmentation under climate change scenarios (Shared Socio-economic Pathway, SSP). For species distribution modeling (SDM), current habitat coordinates were collected from the national ecosystem survey and the national survey on the distribution of endangered species, and environmental data were obtained from Worldclim. An ensemble model was used as a SDM for potential habitat analysis, and landscape metrics were used for fragmentation analysis. The potential habitat area was about 15,216 km2 and the distribution included the Yeongseo region of Gangwon-do and some areas of Chungcheongbuk-do in the current climate. Modeling revealed potential habitat decreases of at least 80% and complete disappearance in SSP3-7.0. The number of patches, mean patch area, total core area, and patch cohesion index showed a decreasing trend compared to the current climate. Our results provide fundamental information for understanding the potential effects of climate change on the distribution of Aconitum coreanum. Adding ecological processes such as dispersal and population dynamics to such an analysis will make it possible to accurately predict the future impacts of climate change on the distribution of endangered species.