scholarly journals 1206. Effects of Climatic Variability on Lyme Disease Outbreaks in California

2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S693-S694
Author(s):  
Raghesh Varot Kangath ◽  
Rajasree Pai Ramachandra ◽  
Buddhika Madurapperuma ◽  
Luke Scaroni
Keyword(s):  
Climate Change ◽  
Lyme Disease ◽  
Temperature Anomaly ◽  
Climatic Factors ◽  
Climatic Variables ◽  
Mean Annual Precipitation ◽  
Mean Annual Temperature ◽  
Northern Coast ◽  
Santa Cruz ◽  
Cca Ordination

Abstract Background Climate change has increased the risk of tick borne infections. The life cycle and prevalence of deer ticks are strongly influenced by temperature. Warmer temperatures associated with climate change are projected to increase the range of suitable tick habitats driving the spread of Lyme disease (LD). Short winters could also increase tick activity increasing the risk of exposure. This study examines the relationship between LD incidence and temperature-precipitation and their anomalies in CA counties. Methods Trends and relationships of Lyme Disease (LD) cases and climatic factors were analyzed among the California counties from 2000 to 2019. Lyme disease tabulate data and climatic data were obtained from Centers for Disease Control, and NOAA, and Climate Data Guide respectively. Canonical correspondence analysis (CCA) was performed using variables: (i) LD cases, (ii) precipitation & anomaly, and temperature & anomaly. The CCA ordination explained the variability between LD cases and climatic variables. Biplots were used to visualize the associations between LD cases and climatic anomalies. Results We compared the countywide LD cases in relation to climatic factors in California from 2000 to 2019. A total of 96 cases in 2000, 117 cases in 2009, and 144 cases in 2019 were reported in the 55 counties of California. Santa Clara reported the highest LD cases in 2003 (23 cases; 16%), followed by Los Angeles in 2013 (20 cases; 18%) and Santa Cruz in 2017 (19 cases; 13%). CCA ordination showed distinguishable clustering patterns between southern California counties (Santa Clara, Santa Cruz, Alameda, and San Diego) and northern coast and Klamath mountains range (Humboldt, Trinity, Shasta, and Siskiyou) regions (Fig. 1). Moderate mean annual temperature (56.5 °F - 62.5 °F) and temperature anomaly (3.8 °F - 5.5 °F) were the most important variable predictor for high LD outbreak. The CCA ordination shows the relationships between Lyme Disease and climatic variables for the 55 Counties of California. The bottom right circle represents Lyme cases positively correlated with temperature anomaly (3.8 °F - 5.5 °F) and moderate annual mean temperature (56.5 °F - 62.5 °F). The upper left circle represents Lyme cases negatively correlated with mean annual precipitation. Conclusion Moderate temperature with low moist spell anomalies in the south neighboring CA counties showed a positive influence on LD outbreak. The climatic conditions in those areas suitable for Oak trees and masting acorn resulting in the establishment of tick and host (deer) populations. We recommend robust surveillance and lab testing for patients with a history of tick bites in these regions. Disclosures All Authors: No reported disclosures

scholarly journals Assessment of Climate Change Effects on Water Resources in the Yellow River Basin, China

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Zhiyong Wu ◽  
Heng Xiao ◽  
Guihua Lu ◽  
Jinming Chen
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
River Basin ◽  
Climate Model ◽  
Yellow River ◽  
Yellow River Basin ◽  
Mean Annual Precipitation ◽  
The Yellow River ◽  
Mean Annual Temperature ◽  
The Yellow River Basin

The water resources in the Yellow River basin (YRB) are vital to social and economic development in North and Northwest China. The basin has a marked continental monsoon climate and its water resources are especially vulnerable to climate change. Projected runoff in the basin for the period from 2001 to 2030 was simulated using the variable infiltration capacity (VIC) macroscale hydrology model. VIC was first calibrated using observations and then was driven by the precipitation and temperature projected by the RegCM3 high-resolution regional climate model under the IPCC scenario A2. Results show that, under the scenario A2, the mean annual temperature of the basin could increase by 1.6°C, while mean annual precipitation could decrease by 2.6%. There could be an 11.6% reduction in annual runoff in the basin according to the VIC projection. However, there are marked regional variations in these climate change impacts. Reductions of 13.6%, 25.7%, and 24.6% could be expected in the regions of Hekouzhen to Longmen, Longmen to Sanmenxia, and Sanmenxia to Huayuankou, respectively. Our study suggests that the condition of water resources in the YRB could become more severe in the period from 2001 to 2030 under the scenario A2.

scholarly journals Climatic Rather than Edaphic Variables Determine Leaf C, N, P Stoichiometry of Deciduous Quercus Species

2021 ◽  
Author(s):  
Yutong Lin ◽  
Yuan Lai ◽  
Songbo Tang ◽  
Zhangfen Qin ◽  
Jianfeng Liu ◽  
...  
Keyword(s):  
Climate Change ◽  
Distribution Range ◽  
Climatic Variables ◽  
Annual Precipitation ◽  
Maximum Temperature ◽  
Mean Annual Precipitation ◽  
Elemental Stoichiometry ◽  
Quercus Species ◽  
Edaphic Variables ◽  
Leaf P

Abstract Purpose Leaf elemental stoichiometry is indicative of plant nutrient limitation, community composition, ecosystem function. Understanding the variations of leaf carbon (C), nitrogen (N), and phosphorus (P) stoichiometry at genus-level across large geographic regions and identifying their driving factors are important to predict species’ distribution range shifts affected by climate change.MethodsHere, we determined the patterns of leaf concentrations ([ ]) and ratios ( / ) of C, N, P of five deciduous oaks species (Quercus) across China covering ~ 20 latitude (~21–41˚ N) and longitude (~99–119˚ E) degrees, and detected their relationships with climatic, edaphic variables. ResultsLeaf [C], [N] and N/P, C/P significantly increased, while leaf [P] and C/N decreased with the increasing latitude. Leaf stoichiometry except for leaf [C] had no significant trends along the longitude. Climatic variables, i.e. mean annual temperature, mean annual precipitation, the maximum temperature of the warmest month, temperature seasonality, aridity index, and the potential evapo-transpiration were the determinants of the geographic patterns of leaf C, N, P stoichiometry. The mean annual precipitation and the maximum temperature of the warmest month indirectly regulated leaf C/N, C/P and N/P via altering leaf [P]. Edaphic variables had non-significant effects on leaf C, N, and P stoichiometry at the broad geographic range.ConclusionsClimatic variables have more important effects than edaphic properties on leaf C, N, P stoichiometry of the studied deciduous Quercus species, which imply the ongoing climate change will alter nutrient strategies and potentially shift the distribution range of this eurytopic species.

scholarly journals Variation of Net Primary Production and Its Correlation with Climate Change and Anthropogenic Activities over the Tibetan Plateau

2018 ◽  
Vol 10 (9) ◽  
pp. 1352 ◽  
Author(s):  
Zhaohui Luo ◽  
Wenchen Wu ◽  
Xijun Yu ◽  
Qingmei Song ◽  
Jian Yang ◽  
...  
Keyword(s):  
Climate Change ◽  
Tibetan Plateau ◽  
Climatic Factors ◽  
Anthropogenic Activities ◽  
Mean Value ◽  
Mean Annual Temperature ◽  
The Tibetan Plateau ◽  
Casa Model ◽  
Negative Effect ◽  
Cumulative Precipitation

Grasslands in the Tibetan Plateau are claimed to be sensitive and vulnerable to climate change and anthropogenic activities. Quantifying the impacts of climate change and anthropogenic activities on grassland growth is an essential step for developing sustainable grassland ecosystem management strategies under the background of climate change and increasing anthropogenic activities occurring in the plateau. Net primary productivity (NPP) is one of the key components in the carbon cycle of terrestrial ecosystems, and can serve an important role in the assessment of vegetation growth. In this study, a modified Carnegie–Ames–Stanford Approach (CASA) model, which considers remote sensing information for the estimation of the water stress coefficient and time-lag effects of climatic factors on NPP simulation, was applied to simulate NPP in the Tibetan Plateau from 2001 to 2015. Then, the spatiotemporal variations of NPP and its correlation with climatic factors and anthropogenic activities were analyzed. The results showed that the mean values of NPP were 0.18 kg∙C∙m−2∙a−1 and 0.16 kg∙C∙m−2∙a−1 for the original CASA model and modified CASA model, respectively. The modified CASA model performed well in estimating NPP compared with field-observed data, with root mean square error (RMSE) and mean absolute error (MAE) of 0.13 kg∙C∙m−2∙a−1 and 0.10 kg∙C∙m−2∙a−1, respectively. Relative RMSE and MAE decreased by 45.8% and 44.4%, respectively, compared to the original CASA model. The variation of NPP showed gradients decreasing from southeast to northwest spatially, and displayed an overall decreasing trend for the study area temporally, with a mean value of −0.02 × 10−2 kg∙C∙m−2∙a−1 due to climate change and increasing anthropogenic activities (i.e., land use and land cover change). Generally, 54% and 89% of the total pixels displayed a negative relationship between NPP and mean annual temperature, as well as annual cumulative precipitation, respectively, with average values of –0.0003 (kg∙C∙m−2 a−1)/°C and −0.254 (g∙C∙m−2∙a−1)/mm for mean annual temperature and annual cumulative precipitation, respectively. Additionally, about 68% of the total pixels displayed a positive relationship between annual cumulative solar radiation and NPP, with a mean value of 0.038 (g∙C∙m−2·a−1)/(MJ m−2). Anthropogenic activities had a negative effect on NPP variation, and it was larger than that of climate change, implying that human intervention plays a critical role in mitigating the degenerating ecosystem. In terms of human intervention, ecological destruction has a significantly negative effect on the NPP trend, and the absolute value was larger than that of ecological restoration, which has a significantly positive effect on NPP the trend. Our results indicate that ecological destruction should be paid more attention, and ecological restoration should be conducted to mitigate the overall decreasing trend of NPP in the plateau.

Disease–weather relationships for wheat powdery mildew under climate change in China

2017 ◽  
Vol 155 (8) ◽  
pp. 1239-1252
Author(s):  
L. ZHANG ◽  
B. Y. YANG ◽  
S. LI ◽  
A. H. GUO
Keyword(s):  
Climate Change ◽  
Powdery Mildew ◽  
Climatic Factors ◽  
Wheat Yield ◽  
Disease Process ◽  
Assessment Method ◽  
Climatic Variables ◽  
Weather Factors ◽  
Wheat Powdery Mildew ◽  
Multiple Stepwise Regression Analysis

SUMMARYLittle is known about the quantitative relationships between wheat powdery mildew (Blumeria graminis f.sp. tritici) epidemics and climatic variables at the provincial scale in China, particularly under climate change. The present study assesses the actual disease process and corresponding impact on wheat yield and addresses climatic-driven variables that affect a powdery mildew epidemic. Powdery mildew increased in frequency from 1981 to 2010, and wheat yield decreased in most regions. It was clear that differences in disease and yield loss occurred temporally and spatially. Although particular weather variables were positively or negatively related to the disease, multiple stepwise regression analysis indicated that mostly fewer than three variables affected prevalence and severity of powdery mildew in each province. In most cases, some combination of higher temperature, humidity, rainfall and wind led to higher disease severity. These weather factors had different effects on disease development. The influence of climatic variables on powdery mildew tended to decrease from 1981 to 2010, whereas the effect of non-climatic factors increased and was attributed mainly to the use of fungicides and resistant cultivars. Therefore, the results of the current study suggest that wheat powdery mildew in China will not increase consistently in the future. In addition, the quantitative assessment method used in the current study can generally provide a good way to identify disease epidemics under climate change.

CROP DIVERSIFICATION AS CLIMATE CHANGE ADAPTATION: HOW DO BANGLADESHI FARMERS PERFORM?

2019 ◽  
Vol 10 (02) ◽  
pp. 1950007
Author(s):  
SHAIKH MONIRUZZAMAN
Keyword(s):  
Climate Change ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Structural Instability ◽  
Climatic Conditions ◽  
Crop Diversity ◽  
Climatic Variables ◽  
Mean Annual Temperature ◽  
Crop Diversification ◽  
Cross Sectional

This research is based on the theoretical framework of risk in rural agricultural economy where farmers consider climate change as idiosyncratic risk of production. Under the inter-temporal household consumption smoothing model, this paper considers crop diversification as an ex ante measure to tackle permanent income shock from climate change. This paper examines empirically whether crop diversity is affected by climate change and how this diversity will respond to different climate scenarios. Negative binomial regression models are estimated from a nationally representative sample of 11,389 farmers across Bangladesh and 30-year average of seasonal climatic variables to find the effects of climatic variables on crop diversity. This paper finds that crop diversity is climate-sensitive and this diversity in different locations varies with climatic conditions. This research unveils structural instability between different single cross-sectional models to simulate the effects of climatic variables on crop diversity. It also finds that increases in mean annual temperature by [Formula: see text]C by 2030 and [Formula: see text]C by 2100 have resulted in 26.40% and 149.83% increases in crop diversity compared to its baseline of 2010, respectively. The effects of rainfall scenarios on crop diversity are much lower compared to the effects of temperature.

scholarly journals The quantitative reconstruction of the paleoclimate between 5200 and 4300 cal yr BP in the Tianshui Basin, NW China

2011 ◽  
Vol 7 (4) ◽  
pp. 2741-2762 ◽  
Author(s):  
N. Sun ◽  
X. Q. Li
Keyword(s):  
Climatic Factors ◽  
Mean Annual Precipitation ◽  
Mean Annual Temperature ◽  
Quantitative Reconstruction ◽  
Subtropical Zone ◽  
Nw China ◽  
Limit Value ◽  
Climate Event ◽  
Tianshui Basin ◽  
The Mean

Abstract. The quantitative reconstruction of the paleoclimate is the ultimate goal of studying past global change. Here, the Coexistence Approach (CA) was applied to reconstruct climatic factors quantitatively based on the fossil charcoal records between 5200 and 4300 cal yr BP in the Tianshui Basin, NW China. The climate of the Tianshui Basin belonged to the northern subtropical zone from 5200–4300 cal yr BP. The climatic tolerance ranges were selected, and the lower limit value was regarded as the logical climate factor to reflect the values of climatic factors. The CA analysis showed that the mean annual temperature (MAT) was approximately 13.2°C, and the mean annual precipitation (MAP) was approximately 778 mm between 5200 and 4900 cal yr BP. The MAT was approximately 13.2°C, and the MAP was approximately 688 mm between 4800 and 4300 cal yr BP. The MAT increased approximately 2.2°C, and the MAP increased approximately 280 mm from 5200–4900 cal yr BP. The MAT also increased approximately 2.2°C from 4800–4300 cal yr BP, while the MAP increased around 196 mm. No climate event occurred from 5200–4300 cal yr BP; however, a drought tendency appeared after 4800 cal yr BP.

Glacier Clusters identification across Chilean Andes using Topo-Climatic variables

2021 ◽  
Author(s):  
Alexis Caro ◽  
Fernando Gimeno ◽  
Antoine Rabatel ◽  
Thomas Condom ◽  
Jean Carlos Ruiz
Keyword(s):  
Climatic Variables ◽  
Mean Annual Precipitation ◽  
Mean Annual Temperature ◽  
Climate Conditions ◽  
Partitioning Around Medoids ◽  
The Andes ◽  
Southern Patagonia ◽  
Rock Glaciers ◽  
Elevation Difference ◽  
Chilean Andes

<p>This study presents a glacier clustering for the Chilean Andes (17.6-55.4°S) realized with the Partitioning Around Medoids (PAM) algorithm and using topographic and climatic variables over the 1980-2019 period. We classified ~24,000 glaciers inside thirteen different clusters (C1 to C13). These clusters show specific conditions in terms of annual and monthly amounts of precipitation, temperature, and solar radiation. In the Northern part of Chile, the Dry Andes (17-36°S) gather five clusters (C1-C5) that display mean annual precipitation and temperature differences up to 400 mm/yr and 8°C, respectively, and a mean elevation difference reaching 1800 m between glaciers in C1 and C5 clusters. In the Wet Andes (36-56°S) the highest differences were observed at the Southern Patagonia Icefield (50°S), with mean annual values for precipitation above 3700 mm/yr (C12, maritime conditions) and below 1000 mm/yr in the east of Southern Patagonia Icefield (C10), and with a difference in mean annual temperature near 4°C and mean elevation contrast of 500 m.</p><p>This classification confirms that Chilean glaciers cannot be grouped only latitudinally as it has been commonly considered, hence contributing to a better understanding of recent glacier volume changes at regional and watershed scales. An example of this was observed in the Maipo watershed (33°S), where the Echaurren Norte glacier is located, which is the reference glacier for Chile and WGMS because it has the oldest time series of mass balance monitoring in the Andes, followed by the Piloto Este glacier, since the 70's. Indeed, we identified that Echaurren Norte glacier only has similarities with 5% of the glacierized surface area of the Maipo watershed. Echaurren Norte glacier is within a glacier cluster that presents warmer and wetter climate conditions (3.1°C, 574 mm/yr) than the average of the watershed, a cluster that contains also 68% of the glacierized surface composed of rock glaciers.</p>

scholarly journals Evaluation of New CORDEX Simulations Using an Updated Köppen–Trewartha Climate Classification

Atmosphere ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 726 ◽  
Author(s):  
Armelle Reca Remedio ◽  
Claas Teichmann ◽  
Lars Buntemeyer ◽  
Kevin Sieck ◽  
Torsten Weber ◽  
...  
Keyword(s):  
Climate Change ◽  
Standard Deviation ◽  
Climatic Research Unit ◽  
Mean Annual Precipitation ◽  
Mean Annual Temperature ◽  
Climate Classification ◽  
Climate Services ◽  
Skill Scores ◽  
Observational Uncertainty ◽  
Core Framework

A new ensemble of climate and climate change simulations covering all major inhabited regions with a spatial resolution of about 25 km, from the WCRP CORDEX COmmon Regional Experiment (CORE) Framework, has been established in support of the growing demands for climate services. The main objective of this study is to assess the quality of the simulated climate and its fitness for climate change projections by REMO (REMO2015), a regional climate model of Climate Service Center Germany (GERICS) and one of the RCMs used in the CORDEX-CORE Framework. The CORDEX-CORE REMO2015 simulations were driven by the ECMWF ERA-Interim reanalysis and the simulations were evaluated in terms of biases and skill scores over ten CORDEX Domains against the Climatic Research Unit (CRU) TS version 4.02, from 1981 to 2010, according to the regions defined by the Köppen–Trewartha (K–T) Climate Classification types. The REMO simulations have a relatively low mean annual temperature bias (about ± 0.5 K) with low spatial standard deviation (about ± 1.5 K) in the European, African, North and Central American, and Southeast Asian domains. The relative mean annual precipitation biases of REMO are below ± 50 % in most domains; however, spatial standard deviation varies from ± 30 % to ± 200 %. The REMO results simulated most climate types relatively well with lowest biases and highest skill score found in the boreal, temperate, and subtropical regions. In dry and polar regions, the REMO results simulated a relatively high annual biases of precipitation and temperature and low skill. Biases were traced to: missing or misrepresented processes, observational uncertainty, and uncertainties due to input boundary forcing.

scholarly journals Predicting Suitable Habitats of Camptotheca acuminata Considering Both Climatic and Soil Variables

Forests ◽  
2020 ◽  
Vol 11 (8) ◽  
pp. 891
Author(s):  
Lei Feng ◽  
Jiejie Sun ◽  
Yuanbao Shi ◽  
Guibin Wang ◽  
Tongli Wang
Keyword(s):  
Climate Change ◽  
Climatic Factors ◽  
Camptotheca Acuminata ◽  
Mean Annual Precipitation ◽  
Climate Change Scenarios ◽  
Ecological Niche Models ◽  
Volume Percentage ◽  
Soil Variables ◽  
Suitable Habitats ◽  
The Impact

Camptotheca acuminata is considered a natural medicinal plant with antitumor activity. The assessment of climate change impact on its suitable habitats is important for cultivation and conservation. In this study, we applied a novel approach to build ecological niche models with both climate and soil variables while the confounding effects between the variables in the two categories were avoided. We found that the degree-days below zero and mean annual precipitation were the most important climatic factors, while the basic soil saturation, soil gravel volume percentage, and clay content were the main soil factors, determining the suitable habitats of C. acuminata. We found that suitable habitats of this species would moderately increase in future climates under both the RCP4.5 and RCP8.5 climate change scenarios for the 2020s, 2050s, and 2080s. However, substantial shifts among levels of habitat suitability were projected. The dual high-suitable habitats would expand, which would be favorable for commercial plantations. Our findings contribute to a better understanding of the impact of climate change on this species and provide a scientific basis for the cultivation and conservation purposes.

scholarly journals Climate Change and its Impact on Tourism Based Livelihood in High Mountain of Nepal

2017 ◽  
Vol 25 (1-2) ◽  
pp. 11-23
Author(s):  
Thakur Devkota
Keyword(s):  
Climate Change ◽  
Survey Design ◽  
Meteorological Data ◽  
Development Planning ◽  
Climatic Variables ◽  
Mountain Region ◽  
Mean Annual Temperature ◽  
High Mountain ◽  
Secondary Source ◽  
The Impact

The climate change is the major issue of the development planning in recent world. This paper focuses on the people’s understanding and experience about the climate change, its impact on tourism dependent livelihoods of the mountain community. Participatory survey design, interview, community consultation, FGD, were conducted in the field. The literature review and hydrological and meteorological data from secondary source were collected for analysis. The people of research area feel that the fluctuation of climatic variables and extremes is occurring now and they are familiar with that change in climatic variables and associated disaster. Their experience on the warming and precipitation coincides with authorized meteorological data which depicts that the mean annual temperature is increasing and average annual precipitation is decreasing. People from High mountain region said that the impact of climate change in tourism based livelihood was experienced. All types of livelihood assets are affected by climate change in mountain region. The change in frequency and intensity of climatic variables and climate change induced hazards was observed and that retard in tourism business and tourism activities in local area.

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