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Abbas, G., Ahmad, S., Ahmad, A., Nasim, W., Fatima, Z., Hussain, S., et al. (2017). Quantification the impacts of climate change and crop management on phenology of maize-based cropping system in Punjab, Pakistan. Agricultural and Forest Meteorology, 247, 42–55.
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Abdul-Aziz, O. I., & Al-Amin, S. (2016). Climate, land use and hydrologic sensitivities of stormwater quantity and quality in a complex coastal-urban watershed. Urban Water Journal, 13(3), 302–320.
Abstract: We determined reference hydro-climatic and land use/cover sensitivities of stormwater runoff and quality in the Miami River Basin of Florida by developing a dynamic rainfall-runoff model with the EPA Storm Water Management Model. Potential storm runoff in the complex coastal-urban basin exhibited high and notably different seasonal sensitivities to rainfall; with stronger responses in the drier early winter and wetter late summer months. Basin runoff and pollutant loads showed moderate sensitivities to the hydrologic and land cover parameters; imperviousness and roughness exhibited more dominant influence than slope. Sensitivity to potential changes in land use patterns was relatively low. The changes in runoff and pollutants under simultaneous hydro-climatic or climate-land use perturbations were notably different than the summations of their individual contributions. The quantified sensitivities can be useful for appropriate management of stormwater quantity and quality in complex urban basins under a changing climate, land use/cover, and hydrology around the world.
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Abiy, A. Z., & Melesse, A. M. (2017). Evaluation of watershed scale changes in groundwater and soil moisture storage with the application of GRACE satellite imagery data. Catena, 153, 50–60.
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Acevedo, M. A., Beaudrot, L., MeléndezAckerman, E. J., Tremblay, R. L., & Shefferson, R. (2020). Local extinction risk under climate change in a neotropical asymmetrically dispersed epiphyte. J Ecol, 108(4), 1553–1564.
Abstract: The long-term fate of populations experiencing disequilibrium conditions with their environment will ultimately depend on how local colonization and extinction dynamics respond to abiotic conditions (e.g. temperature and rainfall), dispersal limitation and biotic interactions (e.g. competition, facilitation or interactions with natural enemies). Understanding how these factors influence distributional dynamics under climate change is a major knowledge gap, particularly for small ranged and dispersal-limited plant species, which are at higher risk of extinction. Epiphytes are hypothesized to be particularly vulnerable to climate change and we know little about what drives their distribution and how they will respond to climate change. To address this issue, we leveraged a 10-year dataset on the occupancy dynamics of the endemic orchid Lepanthes rupestris to identify the drivers of local colonization and extinction dynamics and assess the long-term fate of this population under multiple climate change scenarios.
We compared 290 dynamic occupancy models in their ability to predict the colonization and extinction dynamics of a L. rupestris metapopulation. The model set predicted colonization-extinction dynamics as a function of asymmetric patch connectivity, moss area, elevation, temperature (minimum, maximum and variability) and/or rainfall.
The best model predicted that local colonization increases with increasing asymmetric patch connectivity but decreases as minimum temperature and maximum temperature variability increase. The best model also predicted that local extinction increases with increasing variability in maximum temperature. Negative effects were more severe in smaller patches.
Synthesis. Overall, our results demonstrate the role of asymmetric connectivity, climate and interactions with moss area as drivers of colonization and extinction dynamics. Moreover, our results suggest that asymmetrically dispersed epiphytes may struggle to persist under climate change because their limited connectivity may not be enough to counterbalance the negative effects of increasing mean or variability in temperature.
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Ahmad, I., Singh, A., Fahad, M., & Waqas, M. M. (2020). Remote sensing-based framework to predict and assess the interannual variability of maize yields in Pakistan using Landsat imagery. Computers and Electronics in Agriculture, 178.
Abstract: Predicting crop yields and their spatio-temporal variability under a changing climate is a challenging but essential undertaking for crop management and policymaking purposes. The availability of information on risks associated with effects of climatic variability on agricultural activity outcomes is critical for stakeholders ranging from individual landowners to national economists alike. This research was conducted as a pilot study to (1) develop satellite remote sensing based estimates of maize acreage in a typical Maize growing region in Pakistan, (2) to develop a statistical-empirical model for prediction of maize yields, and finally, (3) to assess the influence of temperature on inter-annual variability in maize yields across a decade. A total of eight machine learning algorithms were tested for identifying maize growing operations in the Faisalabad district of Pakistan using Landsat 8 imagery. Classification models were evaluated via 200 randomly selected ground-verified points across the study region. Results of the maize mapping exercise were used to estimate interannual maize yields using Landsat-derived multi-temporal normalized difference vegetation index (NDVI) and land surface temperature (LST) data as predictors. Predictors for the yield forecasting model were selected via principal component screening and were fed into a least absolute shrinkage and selection (LASSO) regression model. The yield model thus developed was applied to 10 years of past data (2006-2017) and validated against data recorded by government sources. Finally, predictions spanning the ten years were tested for effects of temperature variability to find evidence of influence of ambient temperature on maize yields. Results indicate that support vector machine classifiers work the best in this landscape (accuracies >90%) and reveal that maize cropping area may be underestimated in government sources by as much as 14%. The LASSO regression models also showed very good fits (validation R2 = 0.95) and were fairly accurate in tracking interannual variations in maize yields (R2 = 0.78.) Results also indicate that the maximum temperature has significant negative influence (R2 = 0.76, P < 0.0001) on maize yields in Faisalabad district. Methods presented in this study should be of use to policymakers for better formulating export-import policies and decisions governing food security issues in the larger region.
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Ahmad, S., Abbas, G., Fatima, Z., Khan, R. J., Anjum, M. A., Ahmed, M., et al. (2017). Quantification of the impacts of climate warming and crop management on canola phenology in Punjab, Pakistan. J Agro Crop Sci, 203(5), 442–452.
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Alba, C., Fahey, C., & Flory, S. L. (2019). Global change stressors alter resources and shift plant interactions from facilitation to competition over time. Ecology, 100(12), e02859.
Abstract: Global change stressors such as drought and plant invasion can affect ecosystem structure and function via mediation of resource availability and plant competition outcomes. Yet, it remains uncertain how native plants respond to drought stress that co-occurs with potentially novel resource conditions created by a nonnative invader. Further, there is likely to be temporal variation in competition outcomes between native and nonnative plant species depending on which resources are most limiting at a given time. Interacting stressors coupled with temporal variation make it difficult to predict how global change will impact native plant communities. To address this knowledge gap, we conducted a 5-yr factorial field experiment to quantify how simulated drought, plant invasion (by cogongrass, Imperata cylindrica), and these stressors combined, affected resource availability (soil moisture and light) and competition dynamics between the invader and native longleaf pine (Pinus palustris), a foundation species in southeast U.S. forests. Drought and invasion mediated the survival and performance of pine seedlings in temporally dynamic and unexpected ways. Drought and invasion alone each significantly reduced pine seedling survival. However, when the stressors occurred together, the invader offset drought stress for pine seedlings by maintaining high levels of soil moisture, humidity, and shade compared to uninvaded vegetation. This facilitative effect was pronounced for 2 yr, yet shifted to strong competitive exclusion as the invasion progressed and the limiting resource switched from soil moisture to light. After 3 yr, pine tree survival was low except for pines growing with uninvaded vegetation under ambient precipitation conditions. After 5 yr, pines experiencing a single stressor were taller and had greater height to diameter ratios than pines under no stress or both stressors. This outcome revealed a filtering effect where poorly performing trees were culled under stressful conditions, especially when pines were growing with the invader. Together, these results demonstrate that although drought and invasion suppressed a foundation tree species, the invader temporarily moderated stressful drought conditions, and at least some trees were able to survive despite increasingly strong competition. Such unpredictable effects of interacting global change stressors on native plant species highlight the need for additional long-term studies.
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Alba, C., NeSmith, J. E., Fahey, C., Angelini, C., & Flory, S. L. (2017). Methods to test the interactive effects of drought and plant invasion on ecosystem structure and function using complementary common garden and field experiments. Ecol Evol, 7(5), 1442–1452.
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Alirezaei, M., Onat, N., Tatari, O., & Abdel-Aty, M. (2017). The Climate Change-Road Safety-Economy Nexus: A System Dynamics Approach to Understanding Complex Interdependencies. Systems, 5(1), 6.
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Almeida Prado Jr., F., Athayde, S., Mossa, J., Bohlman, S., Leite, F., & Oliver-Smith, A. (2016). How much is enough? An integrated examination of energy security, economic growth and climate change related to hydropower expansion in Brazil. Renewable and Sustainable Energy Reviews, 53, 1132–1136.
Abstract: Reconciling economic growth and energy supply with the reduction of greenhouse gas emissions and other goals for environmental protection is a major challenge for emerging economies such as Brazil. Establishing energy security standards consistent with realistic economic growth projections while considering climate change requires complex calculations and relies upon risky assumptions. Yet, such calculations and decisions must be made to avoid future energy shortages and economic crises. This paper discusses the current dilemma concerning planning and decision-making for the Brazilian electric sector considering the construction of hydroelectric power plants in the Amazon region, energy security requirements, projected economic growth and climate change feedbacks.
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Alza, C. M., Donnelly, M. A., & Whitfield, S. M. (2016). Additive effects of mean temperature, temperature variability, and chlorothalonil to red-eyed treefrog (Agalychnis callidryas) larvae: Temperature variability and chlorothalonil toxicity. Environ Toxicol Chem, 35(12), 2998–3004.
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Amanambu, A. C., Obarein, O. A., Mossa, J., Li, L., Ayeni, S. S., Balogun, O., et al. (2020). Groundwater system and climate change: Present status and future considerations. Journal of Hydrology, 589.
Abstract: Climate change will impact every aspect of biophysical systems and society. However, unlike other components of the climate system, the impact of climate change on the groundwater system has only recently received attention. This focus is due to the realization that groundwater is a vital freshwater resource crucial to global food and water security, and is essential in sustaining ecosystems and human adaptation to climate variability and change. This paper synthesizes findings on the direct and indirect impacts of climate change on the entire groundwater system and each component. Also, we appraise the use of coupled groundwater-climate and land surface models in groundwater hydrology as a means of improving existing knowledge of climate change-groundwater interaction, finding that most models anticipate decreases in groundwater recharge, storage and levels, particularly in the arid/semi-arid tropics. Reducing uncertainties in future climate projections and improving our understanding of the physical processes underlying models to improve their simulation of real-world conditions remain a priority for climate and Earth scientists. Despite the enormous progress made, there are still few and inadequate local and regional aquifer studies, especially in less developed regions. The paper proposes two key considerations. First, physical basis: the need for a deeper grasp of complex physical processes and feedback mechanism with the use of more sophisticated models. Second, the need to understand the socioeconomic dimensions of climate-groundwater interaction through multidisciplinary synergy, leading to the development of better groundwater-climate change adaptation strategies and modeling
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Anandhi, A. (2016). Growing degree days - Ecosystem indicator for changing diurnal temperatures and their impact on corn growth stages in Kansas. Ecological Indicators, 61, 149–158.
Abstract: Understanding how climate change will affect plant phenology (shifts in the timing of plant activity) is central to many ecological and biogeochemical studies. This aspect of plant ecology often has been overlooked, but addressing the consequences of climate change for adaptive/mitigative management is now high on the list of priorities for funding agencies. This study is innovative because it uses growing degree days (GDD), which has existed since the 1730s, as an ecosystem indicator to study changing diurnal temperatures; their effects on different plant growth stages in the last century; and as a basis for development of future adaptive management strategies. Our results show the most recent time period (1980-2009) had the earliest emergence and the least variability among stations in the day at which the crop stage occurred for most stages except emergence and physiological maturity. 100 year linear trends in the stations indicated all seven crop stages except tassel initiation occurred earlier by one day per decade during the study period. The number of stations with significant decreases varied from 11 to 17 stations out of 23 stations in Kansas. Tassel initiation stage occurred later by one day per decade during the study period. The most recent time period (1980-2009) had the highest variability among stations and 30 year time periods. The variability in trends is higher in western Kansas when compared to eastern Kansas. This knowledge has transformative potential to improve our understanding of the occurrence and duration of the different plant growth stages, add local precision to earlier findings for changes in overall GDD that encompassed larger areas, and help explain the differences in trends from some earlier studies. These shifts in the phenology of agricultural plants as a result of climate change have implications on food production increases required to feed the growing population.
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Anandhi, A., & Bentley, C. (2018). Predicted 21st century climate variability in southeastern U.S. using downscaled CMIP5 and meta-analysis.170.
Abstract: Trends and variability of the climate in the southeastern United States, including Alabama, Florida, Georgia, Mississippi, North Carolina, South Carolina, and Tennessee was studied for an array of future scenarios in the 21st century. The region is a biodiversity hotspot affected by more billion-dollar disasters than any other region in the country. Assessing the impacts of climate change in southeastern United States is important and often requires knowledge of plausible future climate change (e.g. scenarios of temperature and precipitation change). Although several methods are available in literature to develop plausible scenarios of the changes, there exists a usability gap [gap between what scientists understand as useful information and what users recognize as usable]. A novel conceptual framework that represents the plausible future climate change scenarios in southeastern United States was developed using information from meta-analysis and outputs from similar to 19 Coupled Model Intercomparison Project (CMIP5) Global Climate Models (GCMs) [data analysis] in the form of scenario funnels (represent the plausible trajectories of changes in climate). The systematic literature review provided 33 values of precipitation changes from 15 studies and 35 for temperature changes from 14 studies. In general, the meta-analysis revealed, the precipitation changes observed ranged from -30 to + 35% and temperature changes between - 2 degrees C to 6 degrees C by 2099. Fiftieth percentile of the GCMs predicts no precipitation change and an increase of 2.5 degrees C temperature in the region by 2099. Among the GCMs, 5th and 95th percentile of precipitation changes range between - 40% to 110% and temperature changes between - 2 degrees C to 6 degrees C by 2099. Finally, the usability of scenario information to stakeholders in various southeastern United States ecosystems and guidelines for developing causal chains and feedback loops with three levels of complexity were provided. They include utilizing the information from impact assessment studies, stakeholder's expertise and requirement as well as understanding the potential impacts in ecosystems (e.g. agroecosystems, coastal, wetland) by relating the structural components of an ecosystem, their interactions with each other, within and across ecosystems for improved management and sustainable use of their resources. These would improve understanding of ecosystem functioning for better management and sustainable use of resources. Although the methodology was demonstrated for southeastern United States, it could also be applicable to other regions of the world. However, the scenario funnels, potential impacts on ecosystems and causal chain/loops are subjective to the study region, availability of literature, the changes observed in the literature and data analyzed, the characteristics of the study region, the stakeholder and their requirement.
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Anandhi, A., & Blocksome, C. E. (2017). Developing adaptation strategies using an agroecosystem indicator: Variability in crop failure temperatures. Ecological Indicators, 76, 30–41.
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Anandhi, A., Hutchinson, S., Harrington, J., Rahmani, V., Kirkham, M. B., & Rice, C. W. (2016). Changes in spatial and temporal trends in wet, dry, warm and cold spell length or duration indices in Kansas, USA. Int. J. Climatol., 36(12), 4085–4101.
Abstract: Extended periods with excessive or no rainfall or high or low temperatures have important implications on the water cycle, can stress ecosystems and can be detrimental to the economy of a region. These periods are generally studied using spell length indicators or duration indices (SDIs). Fourteen SDIs are calculated to study the changes in wet/dry/warm/cold spells using daily precipitation and maximum and minimum air temperature from 23 centennial weather stations spread across Kansas during four time periods (through 1920, 1921�1950, 1951�1980 and 1981�2009) and two temporal scales (annual and seasonal). Among the SDIs, 3 represent wet spells [wet spell length (WetSL); AvWetSL; MaxWetSL]; 3 for dry spells [dry spell length (DrySL); AvDrySL; MaxDrySL]; 4 for warm spells [warm spell length (WarmSL); average warm spell length (AvWarmSL); maximum warm spell length (MaxWarmSL); WarmSDI] and 4 are for cold spells [cold spell length (ColdSL); average cold spell length (AvColdSL); maximum cold spell length (MaxColdSL); ColdSDI]. In general, we observe that Kansas has 57�64 days year−1 in a wet spell; 302�309 days year−1 in a dry spell; ∼47 days year−1 in each warm and cold spells. The average length of a wet/dry spell is ∼1.5 days, while the warm/cold spells are for 2 days. The maximum length of a wet spell is ∼4.4 days, a dry spell is ∼35 days and warm/cold spells is ∼6 days. We found the number of wet days increasing annually. Interestingly, the warm days during winter are increasing with an overall decrease in the days in warm and cold spells across both temporal scales.
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Anandhi, A., Omani, N., Chaubey, I., Horton, R., Bader, D., & Nanjundiah, R. S. (2016). Synthetic Scenarios from CMIP5 Model Simulations for Climate Change Impact Assessments in Managed Ecosystems and Water Resources: Case Study in South Asian Countries. Transactions of the ASABE, 59(6), 1715–1731.
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Anfinson, K. (2018). How to tell the truth about climate change. Environmental Politics, 27(2), 209–227.
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Angelo, C. L., & Daehler, C. C. (2015). Temperature is the major driver of distribution patterns for C4 and C3 BEP grasses along tropical elevation gradients in Hawaii, and comparison with worldwide patterns. Botany, 93(1), 9–22.
Abstract: The distribution patterns of C4 and C3 grasses in relation to climate have attracted much attention, but few studies have examined grass distributions along tropical elevation gradients. Previous studies identified either temperature, precipitation, or both variables as the major climatic factor(s) driving these distributions. Here we investigated relative dominance of C4 grasses in relation to climate along five elevation gradients in Hawai�i. The transition temperature between C4 and C3 BEP (Bambusoideae, Ehrhartoideae, and Pooideae) grasses (where their relative dominance is equal) was determined; in our study, the subfamily Bambusoideae was not included. A worldwide synthesis of previous studies testing climatic factors and transition temperatures associated with C4 and C3 grass distributions was also carried out. Mean July maximum temperature was significantly correlated with C4 dominance along all elevation transects in Hawai�i, while precipitation was only correlated along three transects when precipitation was correlated with temperature. A spatially explicit multiple regression model indicated that C4 relative cover was best explained by temperature. Temperature appears to be the major climatic factor shaping distribution patterns of C4 and C3 BEP grasses in Hawai�i. According to the worldwide analysis, temperature primarily influenced grass distribution patterns more often in temperate studies (70%) than in tropical studies (45%). Degree of correlation or covariance between temperature and precipitation was rarely reported in previous studies, although this can strongly affect conclusions. C4-C3 BEP transition temperatures (mean July maximum) ranged from 18 to 21 °C in Hawai�i; these transition temperatures are lower than those reported in temperate localities (26�31 °C), but similar to transition temperatures for other localities at tropical latitudes (21�22 °C). A warming climate is likely to shift C4 grass dominance upward in elevation, threatening higher elevation native communities by perpetuating a grass�fire cycle.
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Arcodia, M. C., Kirtman, B. P., & Siqueira, L. S. P. (2020). How MJO Teleconnections and ENSO Interference Impacts U.S. Precipitation. J. Climate, 33(11), 4621–4640.
Abstract: A composite analysis reveals how the Madden-Julian oscillation (MJO) impacts North American rainfall through perturbations in both the upper-tropospheric flow and regional low-level moisture availability. Upper-level divergence associated with the MJO tropical convection drives a quasi-stationary Rossby wave response to the midlatitudes. This forces a midlatitude upper-level dipolar geopotential height anomaly that is accompanied by a westward retraction of the jet stream and reduced rainfall over the central-eastern North Pacific. A reverse effect is found as the MJO propagates eastward across the Maritime Continent. These large differences in the extratropical upper-level flow, combined with anomalies in the regional supply of water vapor, have a profound impact on southeastern U.S. rainfall. The low-frequency variability, including that associated with ENSO, can modify the seasonal background flow (e.g., El Nino and La Nina basic states) affecting the distribution, strength, and propagation of the intraseasonal oscillation and the extratropical teleconnection patterns. The combined effects of the ENSO and the MJO signals result in both spatial and temporal patterns of interference and modulation of North American rainfall. The results from this study show that during a particular phase of an active MJO, the extratropical response can considerably enhance or mask the interannual ENSO signal in the United States, potentially resulting in anomalies of the opposite sign than that expected during a specific ENSO phase. Analyses of specific MJO events during an El Nino or La Nina episode reveal significant contributions to extreme events via constructive and destructive interference of the MJO and ENSO signals.
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