scholarly journals Predicting the Geographic Range of an Invasive Livestock Disease across the Contiguous USA under Current and Future Climate Conditions

Climate ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 159
Author(s):  
Dylan Burruss ◽  
Luis L. Rodriguez ◽  
Barbara Drolet ◽  
Kerrie Geil ◽  
Angela M. Pelzel-McCluskey ◽  
...  
Keyword(s):  
Climate Change ◽  
Animal Movement ◽  
Geographic Range ◽  
Environmental Drivers ◽  
Maximum Temperature ◽  
Potential Range ◽  
Climate Change Scenarios ◽  
Seasonal Temperature ◽  
Climate Conditions ◽  
Livestock Disease

Vesicular stomatitis (VS) is the most common vesicular livestock disease in North America. Transmitted by direct contact and by several biting insect species, this disease results in quarantines and animal movement restrictions in horses, cattle and swine. As changes in climate drive shifts in geographic distributions of vectors and the viruses they transmit, there is considerable need to improve understanding of relationships among environmental drivers and patterns of disease occurrence. Multidisciplinary approaches integrating pathology, ecology, climatology, and biogeophysics are increasingly relied upon to disentangle complex relationships governing disease. We used a big data model integration approach combined with machine learning to estimate the potential geographic range of VS across the continental United States (CONUS) under long-term mean climate conditions over the past 30 years. The current extent of VS is confined to the western portion of the US and is related to summer and winter precipitation, winter maximum temperature, elevation, fall vegetation biomass, horse density, and proximity to water. Comparison with a climate-only model illustrates the importance of current processes-based parameters and identifies regions where uncertainty is likely to be greatest if mechanistic processes change. We then forecast shifts in the range of VS using climate change projections selected from CMIP5 climate models that most realistically simulate seasonal temperature and precipitation. Climate change scenarios that altered climatic conditions resulted in greater changes to potential range of VS, generally had non-uniform impacts in core areas of the current potential range of VS and expanded the range north and east. We expect that the heterogeneous impacts of climate change across the CONUS will be exacerbated with additional changes in land use and land cover affecting biodiversity and hydrological cycles that are connected to the ecology of insect vectors involved in VS transmission.

scholarly journals Projections for Mexico’s Tropical Rainforests Considering Ecological Niche and Climate Change

Forests ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 119
Author(s):  
Antonio Fidel Santos-Hernández ◽  
Alejandro Ismael Monterroso-Rivas ◽  
Diódoro Granados-Sánchez ◽  
Antonio Villanueva-Morales ◽  
Malinali Santacruz-Carrillo
Keyword(s):  
Climate Change ◽  
Ecological Niche ◽  
Potential Distribution ◽  
Tropical Rainforest ◽  
Statistical Significance ◽  
Climate Change Scenarios ◽  
Climate Conditions ◽  
Tropical Regions ◽  
Temperature And Precipitation ◽  
Ecological Importance

The tropical rainforest is one of the lushest and most important plant communities in Mexico’s tropical regions, yet its potential distribution has not been studied in current and future climate conditions. The aim of this paper was to propose priority areas for conservation based on ecological niche and species distribution modeling of 22 species with the greatest ecological importance at the climax stage. Geographic records were correlated with bioclimatic temperature and precipitation variables using Maxent and Kuenm software for each species. The best Maxent models were chosen based on statistical significance, complexity and predictive power, and current potential distributions were obtained from these models. Future potential distributions were projected with two climate change scenarios: HADGEM2_ES and GFDL_CM3 models and RCP 8.5 W/m2 by 2075–2099. All potential distributions for each scenario were then assembled for further analysis. We found that 14 tropical rainforest species have the potential for distribution in 97.4% of the landscape currently occupied by climax vegetation (0.6% of the country). Both climate change scenarios showed a 3.5% reduction in their potential distribution and possible displacement to higher elevation regions. Areas are proposed for tropical rainforest conservation where suitable bioclimatic conditions are expected to prevail.

Comparisons of Machine Learning Methods of Statistical Downscaling Method: Case Studies of Daily Climate Anomalies in Thailand

2021 ◽  
Author(s):  
Kanawut Chattrairat ◽  
Waranyu Wongseree ◽  
Adisorn Leelasantitham
Keyword(s):  
Climate Change ◽  
Statistical Downscaling ◽  
Performance Criteria ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Support Vector ◽  
Seasonal Temperature ◽  
Statistical Downscaling Method ◽  
Downscaling Method

The climate change which is essential for daily life and especially agriculture has been forecasted by global climate models (GCMs) in the past few years. Statistical downscaling method (SD) has been used to improve the GCMs and enables the projection of local climate. Many pieces of research have studied climate change in case of individually seasonal temperature and precipitation for simulation; however, regional difference has not been included in the calculation. In this research, four fundamental SDs, linear regression (LR), Gaussian process (GP), support vector machine (SVM) and deep learning (DL), are studied for daily maximum temperature (TMAX), daily minimum temperature (TMIN), and precipitation (PRCP) based on the statistical relationship between the larger-scale climate predictors and predictands in Thailand. Additionally, the data sets of climate variables from over 45 weather stations overall in Thailand are used to calculate in this calculation. The statistical analysis of two performance criteria (correlation and root mean square error (RMSE)) shows that the DL provides the best performance for simulation. The TMAX and TMIN were calculated and gave a similar trend for all models. PRCP results found that in the North and South are adequate and poor performance due to high and low precipitation, respectively. We illustrate that DL is one of the suitable models for the climate change problem.

scholarly journals Assessing runoff sensitivities to precipitation and temperature changes under global climate-change scenarios

2018 ◽  
Vol 50 (1) ◽  
pp. 24-42 ◽  
Author(s):  
Lei Chen ◽  
Jianxia Chang ◽  
Yimin Wang ◽  
Yuelu Zhu
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Yellow River ◽  
Control Variable ◽  
Maximum Temperature ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Temperature Changes ◽  
Runoff Change ◽  
Precipitation And Temperature

Abstract An accurate grasp of the influence of precipitation and temperature changes on the variation in both the magnitude and temporal patterns of runoff is crucial to the prevention of floods and droughts. However, there is a general lack of understanding of the ways in which runoff sensitivities to precipitation and temperature changes are associated with the CMIP5 scenarios. This paper investigates the hydrological response to future climate change under CMIP5 RCP scenarios by using the Variable Infiltration Capacity (VIC) model and then quantitatively assesses runoff sensitivities to precipitation and temperature changes under different scenarios by using a set of simulations with the control variable method. The source region of the Yellow River (SRYR) is an ideal area to study this problem. The results demonstrated that the precipitation effect was the dominant element influencing runoff change (the degree of influence approaching 23%), followed by maximum temperature (approaching 12%). The weakest element was minimum temperature (approaching 3%), despite the fact that the increases in minimum temperature were higher than the increases in maximum temperature. The results also indicated that the degree of runoff sensitivity to precipitation and temperature changes was subject to changing external climatic conditions.

scholarly journals Effects of Climatic Change on the Potential Distribution of Lycoriella Species (Diptera: Sciaridae) of Economic Importance

Insects ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 831
Author(s):  
Roberta Marques ◽  
Juliano Lessa Pinto Duarte ◽  
Adriane da Fonseca Duarte ◽  
Rodrigo Ferreira Krüger ◽  
Uemmerson Silva da Cunha ◽  
...  
Keyword(s):  
Climate Change ◽  
Range Expansion ◽  
Cold Climate ◽  
Future Climate Change ◽  
Economic Losses ◽  
Potential Range ◽  
Climate Change Scenarios ◽  
Ecological Niche Models ◽  
Greenhouse Production ◽  
Production Areas

Lycoriella species (Sciaridae) are responsible for significant economic losses in greenhouse production (e.g., mushrooms, strawberries, and nurseries). The current distributions of species in the genus are restricted to cold-climate countries. Three species of Lycoriella are of particular economic concern in view of their ability to invade areas in countries across the Northern Hemisphere. We used ecological niche models to determine the potential for range expansion under future climate change scenarios (RCP 4.5 and RCP 8.5) in the distribution of these three species of Lycoriella. Stable environmental suitability under climate change was a dominant theme in these species; however, potential range increases were noted in key countries (e.g., USA, Brazil, and China). Our results illustrate the potential for range expansion in these species in the Southern Hemisphere, including some of the highest greenhouse production areas in the world.

scholarly journals Predicting Current Potential Distribution and the Range Dynamics of Pomacea canaliculata in China under Global Climate Change

Biology ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 110
Author(s):  
Yingxuan Yin ◽  
Qing He ◽  
Xiaowen Pan ◽  
Qiyong Liu ◽  
Yinjuan Wu ◽  
...  
Keyword(s):  
Climate Change ◽  
Native Species ◽  
Potential Distribution ◽  
Global Climate ◽  
Social Economy ◽  
Maximum Temperature ◽  
Pomacea Canaliculata ◽  
Climate Conditions ◽  
Jackknife Test ◽  
Recent Climate

Pomacea canaliculata is one of the 100 worst invasive alien species in the world, which has significant effects and harm to native species, ecological environment, human health, and social economy. Climate change is one of the major causes of species range shifts. With recent climate change, the distribution of P. canaliculata has shifted northward. Understanding the potential distribution under current and future climate conditions will aid in the management of the risk of its invasion and spread. Here, we used species distribution modeling (SDM) methods to predict the potential distribution of P. canaliculata in China, and the jackknife test was used to assess the importance of environmental variables for modeling. Our study found that precipitation of the warmest quarter and maximum temperature in the coldest months played important roles in the distribution of P. canaliculata. With global warming, there will be a trend of expansion and northward movement in the future. This study could provide recommendations for the management and prevention of snail invasion and expansion.

scholarly journals Temperature alters the physiological response of spiny lobsters under predation risk

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Felipe A Briceño ◽  
Quinn P Fitzgibbon ◽  
Elias T Polymeropoulos ◽  
Iván A Hinojosa ◽  
Gretta T Pecl
Keyword(s):  
Climate Change ◽  
Predation Risk ◽  
Environmental Changes ◽  
Environmental Drivers ◽  
Climate Change Scenarios ◽  
Metabolic Rates ◽  
Energetic Costs ◽  
Predator Prey ◽  
Predator Prey Model ◽  
Spiny Lobsters

Abstract Predation risk can strongly shape prey ecological traits, with specific anti-predator responses displayed to reduce encounters with predators. Key environmental drivers, such as temperature, can profoundly modulate prey energetic costs in ectotherms, although we currently lack knowledge of how both temperature and predation risk can challenge prey physiology and ecology. Such uncertainties in predator–prey interactions are particularly relevant for marine regions experiencing rapid environmental changes due to climate change. Using the octopus (Octopus maorum)–spiny lobster (Jasus edwardsii) interaction as a predator–prey model, we examined different metabolic traits of sub adult spiny lobsters under predation risk in combination with two thermal scenarios: ‘current’ (20°C) and ‘warming’ (23°C), based on projections of sea-surface temperature under climate change. We examined lobster standard metabolic rates to define the energetic requirements at specific temperatures. Routine metabolic rates (RMRs) within a respirometer were used as a proxy of lobster activity during night and day time, and active metabolic rates, aerobic scope and excess post-exercise oxygen consumption were used to assess the energetic costs associated with escape responses (i.e. tail-flipping) in both thermal scenarios. Lobster standard metabolic rate increased at 23°C, suggesting an elevated energetic requirement (39%) compared to 20°C. Unthreatened lobsters displayed a strong circadian pattern in RMR with higher rates during the night compared with the day, which were strongly magnified at 23°C. Once exposed to predation risk, lobsters at 20°C quickly reduced their RMR by ~29%, suggesting an immobility or ‘freezing’ response to avoid predators. Conversely, lobsters acclimated to 23°C did not display such an anti-predator response. These findings suggest that warmer temperatures may induce a change to the typical immobility predation risk response of lobsters. It is hypothesized that heightened energetic maintenance requirements at higher temperatures may act to override the normal predator-risk responses under climate-change scenarios.

scholarly journals Impacts of projected maximum temperature extremes for C21 by an ensemble of regional climate models on cereal cropping systems in the Iberian Peninsula

2011 ◽  
Vol 11 (12) ◽  
pp. 3275-3291 ◽  
Author(s):  
M. Ruiz-Ramos ◽  
E. Sánchez ◽  
C. Gallardo ◽  
M. I. Mínguez
Keyword(s):  
Climate Change ◽  
Iberian Peninsula ◽  
High Temperatures ◽  
Climate Models ◽  
Cropping Systems ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Grain Filling ◽  
Maximum Temperature ◽  
Climate Change Scenarios

Abstract. Crops growing in the Iberian Peninsula may be subjected to damagingly high temperatures during the sensitive development periods of flowering and grain filling. Such episodes are considered important hazards and farmers may take insurance to offset their impact. Increases in value and frequency of maximum temperature have been observed in the Iberian Peninsula during the 20th century, and studies on climate change indicate the possibility of further increase by the end of the 21st century. Here, impacts of current and future high temperatures on cereal cropping systems of the Iberian Peninsula are evaluated, focusing on vulnerable development periods of winter and summer crops. Climate change scenarios obtained from an ensemble of ten Regional Climate Models (multimodel ensemble) combined with crop simulation models were used for this purpose and related uncertainty was estimated. Results reveal that higher extremes of maximum temperature represent a threat to summer-grown but not to winter-grown crops in the Iberian Peninsula. The study highlights the different vulnerability of crops in the two growing seasons and the need to account for changes in extreme temperatures in developing adaptations in cereal cropping systems. Finally, this work contributes to clarifying the causes of high-uncertainty impact projections from previous studies.

scholarly journals Analyses of temperature and precipitation in the Indian Jammu and Kashmir region for the 1980–2016 period: implications for remote influence and extreme events

2019 ◽  
Vol 19 (1) ◽  
pp. 15-37 ◽  
Author(s):  
Sumira Nazir Zaz ◽  
Shakil Ahmad Romshoo ◽  
Ramkumar Thokuluwa Krishnamoorthy ◽  
Yesubabu Viswanadhapalli
Keyword(s):  
Climate Change ◽  
Statistical Tests ◽  
Wrf Model ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Seasonal Temperature ◽  
Western Himalayas ◽  
Jammu And Kashmir ◽  
Temperature And Precipitation ◽  
Average Annual Temperature

Abstract. The local weather and climate of the Himalayas are sensitive and interlinked with global-scale changes in climate, as the hydrology of this region is mainly governed by snow and glaciers. There are clear and strong indicators of climate change reported for the Himalayas, particularly the Jammu and Kashmir region situated in the western Himalayas. In this study, using observational data, detailed characteristics of long- and short-term as well as localized variations in temperature and precipitation are analyzed for these six meteorological stations, namely, Gulmarg, Pahalgam, Kokarnag, Qazigund, Kupwara and Srinagar during 1980–2016. All of these stations are located in Jammu and Kashmir, India. In addition to analysis of stations observations, we also utilized the dynamical downscaled simulations of WRF model and ERA-Interim (ERA-I) data for the study period. The annual and seasonal temperature and precipitation changes were analyzed by carrying out Mann–Kendall, linear regression, cumulative deviation and Student's t statistical tests. The results show an increase of 0.8 ∘C in average annual temperature over 37 years (from 1980 to 2016) with higher increase in maximum temperature (0.97 ∘C) compared to minimum temperature (0.76 ∘C). Analyses of annual mean temperature at all the stations reveal that the high-altitude stations of Pahalgam (1.13 ∘C) and Gulmarg (1.04 ∘C) exhibit a steep increase and statistically significant trends. The overall precipitation and temperature patterns in the valley show significant decreases and increases in the annual rainfall and temperature respectively. Seasonal analyses show significant increasing trends in the winter and spring temperatures at all stations, with prominent decreases in spring precipitation. In the present study, the observed long-term trends in temperature (∘Cyear-1) and precipitation (mm year−1) along with their respective standard errors during 1980–2016 are as follows: (i) 0.05 (0.01) and −16.7 (6.3) for Gulmarg, (ii) 0.04 (0.01) and −6.6 (2.9) for Srinagar, (iii) 0.04 (0.01) and −0.69 (4.79) for Kokarnag, (iv) 0.04 (0.01) and −0.13 (3.95) for Pahalgam, (v) 0.034 (0.01) and −5.5 (3.6) for Kupwara, and (vi) 0.01 (0.01) and −7.96 (4.5) for Qazigund. The present study also reveals that variation in temperature and precipitation during winter (December–March) has a close association with the North Atlantic Oscillation (NAO). Further, the observed temperature data (monthly averaged data for 1980–2016) at all the stations show a good correlation of 0.86 with the results of WRF and therefore the model downscaled simulations are considered a valid scientific tool for the studies of climate change in this region. Though the correlation between WRF model and observed precipitation is significantly strong, the WRF model significantly underestimates the rainfall amount, which necessitates the need for the sensitivity study of the model using the various microphysical parameterization schemes. The potential vorticities in the upper troposphere are obtained from ERA-I over the Jammu and Kashmir region and indicate that the extreme weather event of September 2014 occurred due to breaking of intense atmospheric Rossby wave activity over Kashmir. As the wave could transport a large amount of water vapor from both the Bay of Bengal and Arabian Sea and dump them over the Kashmir region through wave breaking, it probably resulted in the historical devastating flooding of the whole Kashmir valley in the first week of September 2014. This was accompanied by extreme rainfall events measuring more than 620 mm in some parts of the Pir Panjal range in the south Kashmir.

Climate change risks to push large parts of global food production and population centres to unprecedented conditions

2020 ◽  
Author(s):  
Matti Kummu ◽  
Matias Heino ◽  
Maija Taka ◽  
Olli Varis ◽  
Daniel Viviroli
Keyword(s):  
Climate Change ◽  
Food Production ◽  
Crop Production ◽  
Ghg Emissions ◽  
Climatic Conditions ◽  
Climate Change Scenarios ◽  
Climate Conditions ◽  
Rcp 8.5 ◽  
Production Areas ◽  
Global Food

<p>The majority of global food production, as we know it, is based on agricultural practices developed within stable Holocene climate conditions. Climate change is altering the key conditions for human societies, such as precipitation, temperature and aridity. Their combined impact on altering the conditions in areas where people live and grow food has not yet, however, been systematically quantified on a global scale. Here, we estimate the impacts of two climate change scenarios (RCP 2.6, RCP 8.5) on major population centres and food crop production areas at 5 arc-min scale (~10 km at equator) using Holdridge Life Zones (HLZs), a concept that incorporates all the aforementioned climatic characteristics. We found that if rapid growth of GHG emissions is not halted (RCP 8.5), in year 2070, one fifth of the major food production areas and one fourth of the global population centres would experience climate conditions beyond the ones where food is currently produced, and people are living. Our results thus reinforce the importance of following the RCP 2.6 path, as then only a small fraction of food production (5%) and population centres (6%) would face such unprecedented conditions. Several areas experiencing these unprecedented conditions also have low resilience, such as those within Burkina Faso, Cambodia, Chad, and Guinea-Bissau. In these countries over 75% of food production and population would experience unprecedented climatic conditions under RCP 8.5. These and many other hotspot areas require the most urgent attention to secure sustainable development and equity.</p>

scholarly journals The current and future potential geographical distribution of the oriental fruit fly,Bactrocera dorsalis(Diptera: Tephritidae)

2007 ◽  
Vol 97 (4) ◽  
pp. 369-378 ◽  
Author(s):  
A.E.A. Stephens ◽  
D.J. Kriticos ◽  
A. Leriche
Keyword(s):  
Climate Change ◽  
Cold Stress ◽  
Potential Distribution ◽  
Fruit Fly ◽  
Climatic Conditions ◽  
Bactrocera Dorsalis ◽  
Potential Range ◽  
Climate Change Scenarios ◽  
Oriental Fruit Fly ◽  
The Impact

AbstractThe oriental fruit fly,Bactrocera dorsalis(Hendel), is a major pest throughout South East Asia and in a number of Pacific Islands. As a result of their widespread distribution, pest status, invasive ability and potential impact on market access,B. dorsalisand many other fruit fly species are considered major threats to many countries. CLIMEX™ was used to model the potential global distribution ofB. dorsalisunder current and future climate scenarios. Under current climatic conditions, its projected potential distribution includes much of the tropics and subtropics and extends into warm temperate areas such as southern Mediterranean Europe. The model projects optimal climatic conditions forB. dorsalisin the south-eastern USA, where the principle range-limiting factor is likely to be cold stress. As a result of climate change, the potential global range forB. dorsalisis projected to extend further polewards as cold stress boundaries recede. However, the potential range contracts in areas where precipitation is projected to decrease substantially. The significant increases in the potential distribution ofB. dorsalisprojected under the climate change scenarios suggest that the World Trade Organization should allow biosecurity authorities to consider the effects of climate change when undertaking pest risk assessments. One of the most significant areas of uncertainty in climate change concerns the greenhouse gas emissions scenarios. Results are provided that span the range of standard Intergovernmental Panel on Climate Change scenarios. The impact on the projected distribution ofB. dorsalisis striking, but affects the relative abundance of the fly within the total suitable range more than the total area of climatically suitable habitat.

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