Climate Change-Related Temperature Impacts on Warm Season Heat Mortality: A Proof-of-Concept Methodology Using BenMAP

2011 ◽  
Vol 45 (4) ◽  
pp. 1450-1457 ◽  
Author(s):  
A. Scott Voorhees ◽  
Neal Fann ◽  
Charles Fulcher ◽  
Patrick Dolwick ◽  
Bryan Hubbell ◽  
...  
Agronomy ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 503 ◽  
Author(s):  
Sumin Kim ◽  
Sojung Kim ◽  
Jaepil Cho ◽  
Seonggyu Park ◽  
Fernando Xavier Jarrín Perez ◽  
...  

Switchgrass (Panicum virgatum L.) is a C4, warm season, perennial native grass that has been strongly recommended as an ideal biofuel feedstock. Accurate forecasting of switchgrass yield across a geographically diverse region and under future climate conditions is essential for determining realistic future ethanol production from switchgrass. This study compiled a switchgrass database through reviewing the existing literature from field trials across the U.S. Using observed switchgrass data, a process-based model (ALMANAC) was developed. The ALMANAC simulation results showed that crop management had more effect on yield than location. The ALMANAC model consists of functional relationships that provide a better understanding of interactions among plant physiological processes and environmental factors (water, soil, climate, and nutrients) giving realistic predictions in different climate conditions. This model was used to quantify the impacts of climate change on switchgrass yields. Simulated lowland switchgrass would have more yield increases between Illinois and Ohio in future (2021–2050) under both Representative Concentration Pathway (RCP) 4.5 and 8.5 pathways with low N fertilizer inputs than high N fertilizer inputs. There was no significant effect of climate variability on upland simulated yields, which means that N fertilization is a key factor in controlling upland switchgrass yields under future climate conditions.


Climate ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 29 ◽  
Author(s):  
Augusta Williams ◽  
Joseph Allen ◽  
Paul Catalano ◽  
John Spengler

Climate change is resulting in heatwaves that are more frequent, severe, and longer lasting, which is projected to double-to-triple the heat-related mortality in Boston, MA if adequate climate change mitigation and adaptation strategies are not implemented. A case-only analysis was used to examine subject and small-area neighborhood characteristics that modified the association between hot days and mortality. Deaths of Boston, Massachusetts residents that occurred from 2000–2015 were analyzed in relation to the daily temperature and heat index during the warm season as part of the case-only analysis. The modification by small-area (census tract, CT) social, and environmental (natural and built) factors was assessed. At-home mortality on hot days was driven by both social and environmental factors, differentially across the City of Boston census tracts, with a greater proportion of low-to-no income individuals or those with limited English proficiency being more highly represented among those who died during the study period; but small-area built environment features, like street trees and enhanced energy efficiency, were able to reduce the relative odds of death within and outside the home. At temperatures below current local thresholds used for heat warnings and advisories, there was increased relative odds of death from substance abuse and assault-related altercations. Geographic weighted regression analyses were used to examine these relationships spatially within a subset of at-home deaths with high-resolution temperature and humidity data. This revealed spatially heterogeneous associations between at-home mortality and social and environmental vulnerability factors.


Author(s):  
Yihao Zhang ◽  
Jianzhong Yan ◽  
Xian Cheng ◽  
Xinjun He

Wetland ecosystems play one of the most crucial roles in the world. Wetlands have the functions of ecological water storage, water supply, and climate regulation, which plays an indispensable role in global environmental security. The Pumqu River Basin (PRB) is located in an area with extremely vulnerable ecological environment, where climate change is obvious. Understanding wetland distribution, changes and causes in the PRB are of great importance to the rational management and protection of wetlands. Using the Landsat series satellite images, wetlands of this area in 2000, 2010, and 2018 were extracted. The results showed that (1) there were obvious regional differences in wetland types and their distribution patterns in the basin. Wetlands were mainly distributed in areas with slopes less than 12° and at elevations between 4000 m and 5500 m. (2) During the past 20 years, the wetland area in the basin decreased, and the changing trend of wetlands was different. Palustrine wetlands decreased tremendously, riverine and lacustrine wetlands first decreased and then increased, while floodplain wetlands first increased and then decreased. Palustrine wetlands were reclaimed to cultivated land, but the proportion of reclamation is small. (3) Climate dominated wetland changes in the PRB. The changes in riverine and lacustrine wetlands were mainly affected by the warm-season average temperature, the change in palustrine wetlands was mainly related to the annual precipitation and the warm-season average temperature, and the change in floodplain wetlands was related to the warm-season precipitation. To achieve sustainable development, the government plays a guiding role and actively formulates and implements wetland protection policies, such as restricting or prohibiting grazing on wetlands, which play an important role in wetland protection and restoration.


2009 ◽  
Vol 97 (3-4) ◽  
pp. 529-541 ◽  
Author(s):  
Terry L. Mader ◽  
Katrina L. Frank ◽  
John A. Harrington ◽  
G. Leroy Hahn ◽  
John A. Nienaber

2017 ◽  
Author(s):  
Kerstin Kretschmer ◽  
Lukas Jonkers ◽  
Michal Kucera ◽  
Michael Schulz

Abstract. Species of planktonic foraminifera exhibit specific seasonal production patterns and different preferred vertical habitats. The seasonality and vertical habitats are not constant throughout the range of the species and changes therein must be considered when interpreting paleoceanographic reconstructions based on fossil foraminifera. Accounting for the effect of vertical and seasonal habitat tracking on foraminifera proxies at times of climate change is difficult because it requires independent fossil evidence. An alternative that could reduce the bias in paleoceanographic reconstructions is to predict species-specific habitat shifts under climate change using an ecosystem modeling approach. To this end, we present a new version of a planktonic foraminifera model, PLAFOM2.0, embedded into the ocean component of the Community Earth System Model, version 1.2.2. This model predicts monthly global concentrations of the planktonic foraminiferal species: Neogloboquadrina pachyderma, N. incompta, Globigerina bulloides, Globigerinoides ruber (white), and Trilobatus sacculifer throughout the world ocean, resolved in 24 vertical layers to 250 m depth. The resolution along the vertical dimension has been implemented by applying the previously used spatial parameterization of biomass as a function of temperature, light, nutrition, and competition on depth-resolved parameter fields. This approach alone results in the emergence of species-specific vertical habitats, which are spatially and temporally variable. Although an explicit parameterization of the vertical dimension has not been carried out, the seasonal and vertical distribution patterns predicted by the model are in good agreement with sediment trap data and plankton tow observations. In the simulation, the colder-water species N. pachyderma, N. incompta, and G. bulloides show a pronounced seasonal cycle in their depth habitat in the polar and subpolar regions, which appears to be controlled by food availability. During the warm season, these species preferably occur in the subsurface, while towards the cold season they ascend through the water column and are found closer to the sea surface. The warm-water species G. ruber (white) and T. sacculifer exhibit a less variable shallow depth habitat with highest biomass concentrations within the top 40 m of the water column. Nevertheless, even these species show vertical habitat variability and their seasonal occurrence outside the tropics is limited to the warm surface layer that develops at the end of the warm season. The emergence in PLAFOM2.0 of species-specific vertical habitats that are consistent with observations indicates that the population dynamics of planktonic foraminifera species may be driven by the same factors in time, space, and with depth, in which case the model can provide a reliable and robust tool to aid the interpretation of proxy records.


Energy Policy ◽  
2014 ◽  
Vol 73 ◽  
pp. 524-539 ◽  
Author(s):  
Wendy S. Jaglom ◽  
James R. McFarland ◽  
Michelle F. Colley ◽  
Charlotte B. Mack ◽  
Boddu Venkatesh ◽  
...  

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
José Ignacio Nazif-Munoz ◽  
Pablo Martínez ◽  
Augusta Williams ◽  
John Spengler

Abstract Background There remains a dearth of cross-city comparisons on the impact of climate change through extreme temperature and precipitation events on road safety. We examined trends in traffic fatalities, injuries and property damage associated with high temperatures and heavy rains in Boston (USA) and Santo Domingo (Dominican Republic). Methods Official publicly available data on daily traffic outcomes and weather conditions during the warm season (May to September) were used for Boston (2002–2015) and Santo Domingo (2013–2017). Daily maximum temperatures and mean precipitations for each city were considered for classifying hot days, warm days, and warm nights, and wet, very wet, and extremely wet days. Time-series analyses were used to assess the relationship between temperature and precipitation and daily traffic outcomes, using a quasi-Poisson regression. Results In Santo Domingo, the presence of a warm night increased traffic fatalities with a rate ratio (RR) of 1.31 (95% CI [confidence interval]: 1.00,1.71). In Boston, precipitation factors (particularly, extremely wet days) were associated with increments in traffic injuries (RR 1.25, 95% CI: 1.18, 1.32) and property damages (RR 1.42, 95% CI: 1.33, 1.51). Conclusion During the warm season, mixed associations between weather conditions and traffic outcomes were found across Santo Domingo and Boston. In Boston, increases in heavy precipitation events were associated with higher traffic injuries and property damage. As climate change-related heavy precipitation events are projected to increase in the USA, the associations found in this study should be of interest for road safety planning in a rapidly changing environment.


Water ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 978 ◽  
Author(s):  
Marco D’Oria ◽  
Maria Tanda ◽  
Valeria Todaro

This study provides an up-to-date analysis of climate change over the Salento area (southeast Italy) using both historical data and multi-model projections of Regional Climate Models (RCMs). The accumulated anomalies of monthly precipitation and temperature records were analyzed and the trends in the climate variables were identified and quantified for two historical periods. The precipitation trends are in almost all cases not significant while the temperature shows statistically significant increasing tendencies especially in summer. A clear changing point around the 80s and at the end of the 90s was identified by the accumulated anomalies of the minimum and maximum temperature, respectively. The gradual increase of the temperature over the area is confirmed by the climate model projections, at short—(2016–2035), medium—(2046–2065) and long-term (2081–2100), provided by an ensemble of 13 RCMs, under two Representative Concentration Pathways (RCP4.5 and RCP8.5). All the models agree that the mean temperature will rise over this century, with the highest increases in the warm season. The total annual rainfall is not expected to significantly vary in the future although systematic changes are present in some months: a decrease in April and July and an increase in November. The daily temperature projections of the RCMs were used to identify potential variations in the characteristics of the heat waves; an increase of their frequency is expected over this century.


2021 ◽  
Vol 12 (3) ◽  
pp. 997-1013
Author(s):  
Pascal Yiou ◽  
Nicolas Viovy

Abstract. Estimating the risk of forest collapse due to extreme climate events is one of the challenges of adapting to climate change. We adapt a concept from ruin theory, which is widely used in econometrics and the insurance industry, to design a growth–ruin model for trees which accounts for climate hazards that can jeopardize tree growth. This model is an elaboration of a classical Cramer–Lundberg ruin model that is used in the insurance industry. The model accounts for the interactions between physiological parameters of trees and the occurrence of climate hazards. The physiological parameters describe interannual growth rates and how trees react to hazards. The hazard parameters describe the probability distributions of the occurrence and intensity of climate events. We focus on a drought–heatwave hazard. The goal of the paper is to determine the dependence of the forest ruin and average growth probability distributions on physiological and hazard parameters. Using extensive Monte Carlo experiments, we show the existence of a threshold in the frequency of hazards beyond which forest ruin becomes certain to occur within a centennial horizon. We also detect a small effect of the strategies used to cope with hazards. This paper is a proof of concept for the quantification of forest collapse under climate change.


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