Simulated Biomass, Climate Change Impacts, and Nitrogen Management to Achieve Switchgrass Biofuel Production at Diverse Sites in U.S.

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.

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Bias correction of extreme values of high resolution climate simulations for risk analysis.

10.21203/rs.3.rs-264479/v1 ◽

2021 ◽

Author(s):

luis Augusto sanabria ◽

Xuerong Qin ◽

Jin Li ◽

Robert Peter Cechet

Keyword(s):

Climate Change ◽

Bias Correction ◽

Extreme Values ◽

The Body ◽

Future Climate ◽

Return Periods ◽

Climate Conditions ◽

Mitigation And Adaptation ◽

Climate Simulations ◽

The Impact

Abstract Most climatic models show that climate change affects natural perils' frequency and severity. Quantifying the impact of future climate conditions on natural hazard is essential for mitigation and adaptation planning. One crucial factor to consider when using climate simulations projections is the inherent systematic differences (bias) of the modelled data compared with observations. This bias can originate from the modelling process, the techniques used for downscaling of results, and the ensembles' intrinsic variability. Analysis of climate simulations has shown that the biases associated with these data types can be significant. Hence, it is often necessary to correct the bias before the data can be reliably used for further analysis. Natural perils are often associated with extreme climatic conditions. Analysing trends in the tail end of distributions are already complicated because noise is much more prominent than that in the mean climate. The bias of the simulations can introduce significant errors in practical applications. In this paper, we present a methodology for bias correction of climate simulated data. The technique corrects the bias in both the body and the tail of the distribution (extreme values). As an illustration, maps of the 50 and 100-year Return Period of climate simulated Forest Fire Danger Index (FFDI) in Australia are presented and compared against the corresponding observation-based maps. The results show that the algorithm can substantially improve the calculation of simulation-based Return Periods. Forthcoming work will focus on the impact of climate change on these Return Periods considering future climate conditions.

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Evaluating catchment response to artificial rainfall from four weather generators for present and future climate

Water Science & Technology ◽

10.2166/wst.2018.217 ◽

2018 ◽

Vol 77 (11) ◽

pp. 2578-2588 ◽

Cited By ~ 3

Author(s):

Hjalte Jomo Danielsen Sørup ◽

Steffen Davidsen ◽

Roland Löwe ◽

Søren Liedtke Thorndahl ◽

Morten Borup ◽

...

Keyword(s):

Climate Change ◽

Future Climate ◽

Control Measures ◽

Rainfall Time Series ◽

Urban Water ◽

Combined Sewer Overflows ◽

Climate Conditions ◽

Artificial Rainfall ◽

Weather Generators ◽

Catchment Responses

Abstract The technical lifetime of urban water infrastructure has a duration where climate change has to be considered when alterations to the system are planned. Also, models for urban water management are reaching a very high complexity level with, for example, decentralized stormwater control measures being included. These systems have to be evaluated under as close-to-real conditions as possible. Long term statistics (LTS) modelling with observational data is the most close-to-real solution for present climate conditions, but for future climate conditions artificial rainfall time series from weather generators (WGs) have to be used. In this study, we ran LTS simulations with four different WG products for both present and future conditions on two different catchments. For the present conditions, all WG products result in realistic catchment responses when it comes to the number of full flowing pipes and the number and volume of combined sewer overflows (CSOs). For future conditions, the differences in the WGs representation of the expectations to climate change is evident. Nonetheless, all future results indicate that the catchments will have to handle more events that utilize the full capacity of the drainage systems. Generally, WG products are relevant to use in planning of future changes to sewer systems.

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Trading space for time: Assessment of tree habitat shifts under climate change using bioclimatic envelopes

10.5194/egusphere-egu21-2135 ◽

2021 ◽

Author(s):

Katharina Enigl ◽

Matthias Schlögl ◽

Christoph Matulla

Keyword(s):

Climate Change ◽

Tree Species ◽

Ips Typographus ◽

Future Climate ◽

Forest Damage ◽

Climate Conditions ◽

North East ◽

Bioclimatic Variables ◽

The Future ◽

Forest District

Climate change constitutes a main driver of altering population dynamics of spruce bark beetles (Ips typographus) all over Europe. Their swarming activity as well as development rate are strongly dependent on temperature and the availability of brood trees. Especially over the last years, the latter has substantially increased due to major drought events which led to a widespread weakening of spruce stands. Since both higher temperatures and longer drought periods are to be expected in Central Europe in the decades ahead, foresters face the challenges of maintaining sustainable forest management and safeguarding future yields. One approach used to foster decision support in silviculture relies on the identification of possible alternative tree species suitable for adapting to expected future climate conditions in threatened regions.&#160;In this study, we focus on the forest district of Horn, a region in Austria&#8216;s north east that is beneficially influenced by the mesoclimate of the Pannonian basin. This fertile yet dry area has been severely affected by mass propagations of Ips typographus due to extensive droughts since 2017, and consequently has suffered from substantial forest damage in recent years. The urgent need for action was realized and has expedited the search for more robust alternative species to ensure sustainable silviculture in the area.The determination of suitable tree species is based on the identification of regions whose climatic conditions in the recent past are similar to those that are to be expected in the forest district of Horn in the future. To characterize these conditions, we consider 19 bioclimatic variables that are derived from monthly temperature and rainfall values. Using downscaled CMIP6 projections with a spatial resolution of 2.5 minutes, we determine future conditions in Horn throughout the 21st century. By employing 20-year periods from 2021 to 2100 for the scenarios SSP1-26, SSP2-45, SSP3-70 and SSP5-85,&#160; and comparing them to worldwide past climate conditions, we obtain corresponding bioclimatic regions for four future time slices until the end of the century. The Euclidian distance is applied as measure of similarity, effectively yielding similarity maps on a continuous scale. In order to account for the spatial variability within the forest district, this procedure is performed for the colder northwest and the warmer southeast of the area, individually seeking similar bioclimatic regions for each of these two subregions. Results point to Eastern Europe as well as the Po Valley in northern Italy as areas exhibiting the highest similarity to the future climate in this North-Eastern part of Austria.

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A comparison between direct and indirect frameworks to evaluate impacts of climate change on streamflows: case study of Karkheh River basin in Iran

Journal of Water and Climate Change ◽

10.2166/wcc.2017.043 ◽

2017 ◽

Vol 8 (4) ◽

pp. 652-674 ◽

Cited By ~ 6

Author(s):

Mohsen Nasseri ◽

Banafsheh Zahraie ◽

Leila Forouhar

Keyword(s):

Climate Change ◽

River Basin ◽

Hydrological Modeling ◽

Future Climate ◽

Multivariate Adaptive Regression Splines ◽

Group Method ◽

Climate Projections ◽

Climate Conditions ◽

Karkheh River Basin ◽

Impacts Of Climate Change

Abstract In this paper, two approaches to assess the impacts of climate change on streamflows have been used. In the first approach (direct), a statistical downscaling technique was utilized to predict future streamflows based on large-scale data of general circulation models (GCMs). In the second approach (indirect), GCM outputs were downscaled to produce local climate conditions which were then used as inputs to a hydrological simulation model. In this article, some data-mining methods such as model-tree, multivariate adaptive regression splines and group method of data handling were utilized for direct downscaling of streamflows. Projections of HadCM3 model for A2 and B2 SRES scenarios were also used to simulate future climate conditions. These evaluations were done over three sub-basins of Karkheh River basin in southwest Iran. To achieve a comprehensive assessment, a global uncertainty assessment method was used to evaluate the results of the models. The results indicated that despite simplifications included in the direct downscaling, this approach is accurate enough to be used for assessing climate change impacts on streamflows without computational efforts of hydrological modeling. Furthermore, comparing future climate projections, the uncertainty associated with elimination of hydrological modeling is estimated to be high.

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Projecting future vegetation change for northeast China using CMIP6

10.5194/egusphere-egu2020-9639 ◽

2020 ◽

Author(s):

Wei Yuan ◽

Shuang-ye Wu ◽

Shugui Hou

Keyword(s):

Climate Change ◽

Vegetation Change ◽

Management Strategies ◽

Future Climate ◽

Future Climate Change ◽

Vegetation Changes ◽

Emission Scenarios ◽

Climate Data ◽

Climate Conditions ◽

Temperature And Precipitation

This study aims to establish future vegetation changes in the east and central of northern China (ECNC), an ecologically sensitive region in the transition zonal from humid monsoonal to arid continental climate. The region has experienced significant greening in the past several decades. However, few studies exist on how vegetation will change with future climate change, and great uncertainties exist due to complex, and often spatially non-stationary, relationships between vegetation and climate. In this study, we first used historical NDVI and climate data to model this spatially variable relationship with Geographically Weighted Logit Regression. We found that temperature and precipitation could explain, on average, 43% of NDVI variance, and they could be used to&#160;model NDVI fairly well. We then establish future climate change using the output of 11 CMIP6 models for the medium (SSP245) and high (SSP585) emission scenarios for the mid-century (2041-2070) and late-century (2071-2100). The results show that for this region, both temperature and precipitation will increase under both scenarios. By late-century under SSP585, precipitation is projected to increase by 25.12% and temperature is projected to increase 5.87oC in ECNC. Finally, we used future climate conditions as input for the regression models to project future vegetation (indicated by NDVI). We found that NDVI will increase under climate change. By mid-century, the average NDVI in ECNC will increase by 0.024 and 0.021 under SSP245 and SSP585. By late-century, it will increase by 0.016 and 0.006 under SSP245 and SSP585&#160;respectively. Although NDVI is projected to increase, the magnitude of increase is likely to diminish with higher emission scenarios, possibly due to the benefit of precipitation increase being gradually encroached by the detrimental effects of temperature increase. Moreover, despite the overall NDVI increase, the area likely to suffer vegetation degradation will also expands, particularly in the western part of ECNC. With higher emissions and later into the century, region with low NDVI is likely to shift and/or expand north-forward. Our results could provide important information on possible&#160;vegetation changes, which could help to develop effective management strategies to ensure ecological and economic sustainability&#160;in the future.

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Forecasting the impacts of chemical pollution and climate change interactions on the health of wildlife

Current Zoology ◽

10.1093/czoolo/61.4.669 ◽

2015 ◽

Vol 61 (4) ◽

pp. 669-689 ◽

Cited By ~ 59

Author(s):

Pamela D. Noyes ◽

Sean C. Lema

Keyword(s):

Climate Change ◽

Environmental Changes ◽

Global Climate ◽

Climatic Conditions ◽

Future Climate ◽

Chemical Pollution ◽

Climate Scenarios ◽

Chemical Toxicity ◽

Climate Conditions ◽

Chemical Exposures

Abstract Global climate change is impacting organisms, biological communities and ecosystems around the world. While most research has focused on characterizing how the climate is changing, including modeling future climatic conditions and predicting the impacts of these conditions on biodiversity, it is also the case that climate change is altering the environmental impacts of chemical pollution. Future climate conditions are expected to influence both the worldwide distribution of chemicals and the toxicological consequences of chemical exposures to organisms. Many of the environmental changes associated with a warming global climate (e.g., increased average – and possibly extreme – temperatures; intense periods of drier and wetter conditions; reduced ocean pH; altered salinity dynamics in estuaries) have the potential to enhance organism susceptibility to chemical toxicity. Additionally, chemical exposures themselves may impair the ability of organisms to cope with the changing environmental conditions of the shifting climate. Such reciprocity in the interactions between climate change and chemicals illustrates the complexity inherent in predicting the toxicological consequences of chemical exposures under future climate scenarios. Here, we summarize what is currently known about the potential reciprocal effects of climate change and chemical toxicity on wildlife, and depict current approaches and ongoing challenges for incorporating climate effects into chemical testing and assessment. Given the rapid pace of new man-made chemistries, the development of accurate and rapid methods to evaluate multiple chemical and non-chemical stressors in an ecologically relevant context will be critical to understanding toxic and endocrine-disrupting effects of chemical pollutants under future climate scenarios.

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The challenges and opportunities for wheat production under future climate in Northern Ethiopia

The Journal of Agricultural Science ◽

10.1017/s0021859616000460 ◽

2016 ◽

Vol 155 (3) ◽

pp. 379-393 ◽

Cited By ~ 5

Author(s):

A. ARAYA ◽

I. KISEKKA ◽

A. GIRMA ◽

K. M. HADGU ◽

F. N. TEGEBU ◽

...

Keyword(s):

Climate Change ◽

Model Calibration ◽

Wheat Yield ◽

Planting Date ◽

N Fertilizer ◽

Future Climate ◽

Northern Ethiopia ◽

Short Term ◽

Adaptation Practices ◽

Impacts Of Climate Change

SUMMARYWheat is an important crop in the highlands of Northern Ethiopia and climate change is expected to be a major threat to wheat productivity. However, the potential impacts of climate change and adaptation on wheat yield has not been documented for this region. Wheat field experiments were carried out during the 2011–2013 cropping seasons in Northern Ethiopia to: (1) calibrate and evaluate Agricultural Production Systems sIMulator (APSIM)-wheat model for exploring the impacts of climate change and adaptation on wheat yield; (2) explore the response of wheat cultivar/s to possible change in climate and carbon dioxide (CO2) under optimal and sub-optimal fertilizer application and (3) assess the impact of climate change and adaptation practices on wheat yield based on integration of surveyed field data with climate simulations using multi-global climate models (GCMs; for short- and mid-term periods) for the Hintalo-Wajrat areas of Northern Ethiopia. The treatments were two levels of fertilizer (optimal and zero fertilization); treatments were replicated three times and arranged in a randomized complete block design. All required information for model calibration and evaluation were gathered from experimental studies. In addition, a household survey was conducted in 2012 in Northern Ethiopia. Following model calibration and performance testing, response of wheat to various nitrogen (N) fertilizer rates, planting date, temperature and combinations of other climate variables and CO2 were assessed. Crop simulations were conducted with future climate scenarios using 20 different GCMs and compared with a baseline. In addition, simulations were carried out using climate data from five different GCM with and without climate change adaptation practices. The simulated yield showed clear responses to changes in temperature, N fertilizer and CO2. Regardless of choice of cultivar, increasing temperatures alone (by up to 5 °C compared with the baseline) resulted in reduced yield while the addition of other factors (optimal fertilizer with elevated CO2) resulted in increased yield. Considering optimal fertilizer (64 kg/ha N) as an adaptation practice, wheat yield in the short-term (2010–2039) and mid-term (2040–2069) may increase at least by 40%, compared with sub-optimal N levels. Assuming CO2 and present wheat management is unchanged, simulation results based on 20 GCMs showed that median wheat yields will reduce by 10% in the short term and by 11% in the mid-term relative to the baseline data, whereas under changed CO2 with present management, wheat yield will increase slightly, by up to 8% in the short term and by up to 11% in the mid-term period, respectively. Wheat yield will substantially increase, by more than 100%, when simulated based on combined use of optimal planting date and fertilizer applications. Increased temperature in future scenarios will cause yield to decline, whereas CO2 is expected to have positive impacts on wheat yield.

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Assessment of future climate change impacts on the hydrological regime of selected Greek areas with different climate conditions

Hydrology Research ◽

10.2166/nh.2016.018 ◽

2016 ◽

Vol 48 (5) ◽

pp. 1327-1342 ◽

Cited By ~ 3

Author(s):

Spyridon Paparrizos ◽

Andreas Matzarakis

Keyword(s):

Climate Change ◽

Climate Models ◽

Hydrological Cycle ◽

Meteorological Data ◽

Hydrological Regime ◽

Future Climate ◽

Future Climate Change ◽

Water Losses ◽

Climate Conditions ◽

The Future

Assessment of future variations of streamflow is essential for research regarding climate and climate change. This study is focused on three agricultural areas widespread in Greece and aims to assess the future response of annual and seasonal streamflow and its impacts on the hydrological regime, in combination with other fundamental aspects of the hydrological cycle in areas with different climate classification. ArcSWAT ArcGIS extension was used to simulate the future responses of streamflow. Future meteorological data were obtained from various regional climate models, and analysed for the periods 2021–2050 and 2071–2100. In all the examined areas, streamflow is expected to be reduced. Areas characterized by continental climate will face minor reductions by the mid-century that will become very intense by the end and thus these areas will become more resistant to future changes. Autumn season will face the strongest reductions. Areas characterized by Mediterranean conditions will be very vulnerable in terms of future climate change and winter runoff will face the most significant decreases. Reduced precipitation is the main reason for decreased streamflow. High values of actual evapotranspiration by the end of the century will act as an inhibitor towards reduced runoff and partly counterbalance the water losses.

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Life in the Wheat Litter: Effects of Future Climate on Microbiome and Function During the Early Phase of Decomposition

10.21203/rs.3.rs-377061/v1 ◽

2021 ◽

Author(s):

Sara Wahdan ◽

Shakhawat Hossen ◽

Benjawan Tanunchai ◽

Chakriya Sansupa ◽

Martin Schädler ◽

...

Keyword(s):

Climate Change ◽

Mass Loss ◽

Wheat Straw ◽

Litter Decomposition ◽

Early Phase ◽

Future Climate ◽

Fungal Communities ◽

Climate Conditions ◽

Physicochemical Factors ◽

Bacteria And Fungi

Abstract Even though it is widely acknowledged that litter decomposition can be impacted by climate change, the feedback of the corresponding functional roles of decomposing microbes to climate change is understood to a lesser extent. Litter decomposition is linked to the corresponding functioning of the microbiome, but the feedback to climate change is so far scarcely studied. This study used a field experimental facility settled in Central Germany to analyze the effects of ambient climate vs. future climate, which is expected in 50 – 70 years, on mass loss and physicochemical parameters of wheat straw in agricultural cropland at the early phase of litter decomposition process. Additionally, the effects of climate change were assessed on microbial richness, community compositions, interactions and their functions (production of extracellular enzymes), as well as litter physicochemical factors shaping their colonization. The initial physicochemical properties of wheat litter did not change between both climate conditions, however, future climate significantly accelerated litter mass loss as compared with ambient one. Using MiSeq Illumina sequencing, we found that future climate significantly increased fungal richness and altered fungal communities over time, while bacterial communities were more resistant in wheat residues. Fungi corresponded to different physicochemical factors of litter under ambient (C, Ca2+ and pH) and future (C/N, N, P, K+, Ca2+ and pH) climate conditions. Moreover, a highly correlative interactions between richness of bacteria and fungi were detected under future climate. Furthermore, the co-occurrence network patterns among dominant microorganisms inhabiting wheat residues were strongly distinct between future and ambient climates. Activity of microbial β-glucosidase and N-acetylglucosaminidase in wheat straw were significantly higher under future climate. Such high enzymatic activities were coupled with a significant positive correlation between microbial (both bacteria and fungi) richness and community compositions with these two enzymatic activities only under future climate. Overall, we provide evidence that future climate significantly impacted the early-phase of wheat litter decomposition through direct effects on fungal communities and through indirect effects on microbial interactions and corresponding enzymes production.

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Assessment of rice yield gap under a changing climate in India

Journal of Water and Climate Change ◽

10.2166/wcc.2020.086 ◽

2020 ◽

Author(s):

Subhankar Debnath ◽

Ashok Mishra ◽

D. R. Mailapalli ◽

N. S. Raghuwanshi ◽

V. Sridhar

Keyword(s):

Climate Change ◽

Explicit Knowledge ◽

Rice Yield ◽

Management Strategies ◽

Temporal Analysis ◽

Future Climate ◽

Historical Period ◽

Change Scenario ◽

Yield Gap ◽

Climate Conditions

Abstract Climate change evokes future food security concerns and needs for sustainable intensification of agriculture. The explicit knowledge about crop yield gap at country level may help in identifying management strategies for sustainable agricultural production to meet future food demand. In this study, we assessed the rice yield gap under projected climate change scenario in India at 0.25° × 0.25° spatial resolution by using the Decision Support System for Agrotechnology Transfer (DSSAT) model. The simulated spatial yield results show that mean actual yield under rainfed conditions (Ya) will reduce from 2.13 t/ha in historical period 1981–2005 to 1.67 t/ha during the 2030s (2016–2040) and 2040s (2026–2050), respectively, under the RCP 8.5 scenario. On the other hand, mean rainfed yield gap shows no change (≈1.49 t/ha) in the future. Temporal analysis of yield indicates that Ya is expected to decrease in the considerably large portion of the study area (30–60%) under expected future climate conditions. As a result, yield gap is expected to either stagnate or increase in 50.6 and 48.7% of the study area during the two future periods, respectively. The research outcome indicates the need for identifying plausible best management strategies to reduce the yield gap under expected future climate conditions for sustainable rice production in India.

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