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Like many other regions in central Europe, Germany experienced sequential summer droughts from 2015 to 2018. As one of the environmental consequences, river nitrate concentrations have exhibited significant changes in many catchments.
However, catchment nitrate responses to the changing weather conditions have not yet been mechanistically explored.
Thus, a fully distributed, process-based catchment Nitrate model (mHM-Nitrate) was used to reveal the causal relations in the Bode catchment, of which river nitrate concentrations have experienced contrasting trends from upstream to downstream reaches. The model was evaluated using data from six gauging stations, reflecting different levels of runoff components and their associated nitrate-mixing from upstream to downstream.
Results indicated that the mHM-Nitrate model reproduced dynamics of daily discharge and nitrate concentration well, with Nash-Sutcliffe Efficiency >= 0.73 for discharge and Kling-Gupta Efficiency >= 0.50 for nitrate concentration at most stations.
Particularly, the spatially contrasting trends of nitrate con-centration were successfully captured by the model.
The decrease of nitrate concentration in the lowland area in drought years (2015-2018) was presumably due to (1) limited terrestrial export loading (ca. 40 % lower than that of normal years 2004-2014), and (2) increased in-stream retention efficiency (20 % higher in summer within the whole river network).
From a mechanistic modelling perspective, this study provided insights into spatially heterogeneous flow and nitrate dynamics and effects of sequential droughts, which shed light on water -quality responses to future climate change, as droughts are projected to be more frequent.
Review exploring the regulation of PHYTOCHROME-INTERACTING FACTORS by light, their role in abiotic stress tolerance and plant architecture, and their influence on crop productivity.
Light is a key determinant for plant growth, development, and ultimately yield. Phytochromes, red/far-red photoreceptors, play an important role in plant architecture, stress tolerance, and productivity. In the model plant Arabidopsis, it has been shown that PHYTOCHROME-INTERACTING FACTORS (PIFs; bHLH transcription factors) act as central hubs in the integration of external stimuli to regulate plant development. Recent studies have unveiled the importance of PIFs in crops. They are involved in the modulation of plant architecture and productivity through the regulation of cell division and elongation in response to different environmental cues. These studies show that different PIFs have overlapping but also distinct functions in the regulation of plant growth. Therefore, understanding the molecular mechanisms by which PIFs regulate plant development is crucial to improve crop productivity under both optimal and adverse environmental conditions. In this review, we discuss current knowledge of PIFs acting as integrators of light and other signals in different crops, with particular focus on the role of PIFs in responding to different environmental conditions and how this can be used to improve crop productivity.
The European Water Framework Directive (WFD) has identified river morphological alteration and diffuse pollution as the two main pressures affecting water bodies in Europe at the catchment scale. Consequently, river restoration has become a priority to achieve the WFD's objective of good ecological status. However, little is known about the effects of stream morphological changes, such as re-meandering, on in-stream nitrate retention at the river network scale. Therefore, catchment nitrate modeling is necessary to guide the implementation of spatially targeted and cost-effective mitigation measures. Meanwhile, Germany, like many other regions in central Europe, has experienced consecutive summer droughts from 2015-2018, resulting in significant changes in river nitrate concentrations in various catchments. However, the mechanistic exploration of catchment nitrate responses to changing weather conditions is still lacking.
Firstly, a fully distributed, process-based catchment Nitrate model (mHM-Nitrate) was used, which was properly calibrated and comprehensively evaluated at numerous spatially distributed nitrate sampling locations. Three calibration schemes were designed, taking into account land use, stream order, and mean nitrate concentrations, and they varied in spatial coverage but used data from the same period (2011–2019). The model performance for discharge was similar among the three schemes, with Nash-Sutcliffe Efficiency (NSE) scores ranging from 0.88 to 0.92. However, for nitrate concentrations, scheme 2 outperformed schemes 1 and 3 when compared to observed data from eight gauging stations. This was likely because scheme 2 incorporated a diverse range of data, including low discharge values and nitrate concentrations, and thus provided a better representation of within-catchment heterogenous. Therefore, the study suggests that strategically selecting gauging stations that reflect the full range of within-catchment heterogeneity is more important for calibration than simply increasing the number of stations.
Secondly, the mHM-Nitrate model was used to reveal the causal relations between sequential droughts and nitrate concentration in the Bode catchment (3200 km2) in central Germany, where stream nitrate concentrations exhibited contrasting trends from upstream to downstream reaches. The model was evaluated using data from six gauging stations, reflecting different levels of runoff components and their associated nitrate-mixing from upstream to downstream. Results indicated that the mHM-Nitrate model reproduced dynamics of daily discharge and nitrate concentration well, with Nash-Sutcliffe Efficiency ≥ 0.73 for discharge and Kling-Gupta Efficiency ≥ 0.50 for nitrate concentration at most stations. Particularly, the spatially contrasting trends of nitrate concentration were successfully captured by the model. The decrease of nitrate concentration in the lowland area in drought years (2015-2018) was presumably due to (1) limited terrestrial export loading (ca. 40% lower than that of normal years 2004-2014), and (2) increased in-stream retention efficiency (20% higher in summer within the whole river network). From a mechanistic modelling perspective, this study provided insights into spatially heterogeneous flow and nitrate dynamics and effects of sequential droughts, which shed light on water-quality responses to future climate change, as droughts are projected to be more frequent.
Thirdly, this study investigated the effects of stream restoration via re-meandering on in-stream nitrate retention at network-scale in the well-monitored Bode catchment. The mHM-Nitrate model showed good performance in reproducing daily discharge and nitrate concentrations, with median Kling-Gupta values of 0.78 and 0.74, respectively. The mean and standard deviation of gross nitrate retention efficiency, which accounted for both denitrification and assimilatory uptake, were 5.1 ± 0.61% and 74.7 ± 23.2% in winter and summer, respectively, within the stream network. The study found that in the summer, denitrification rates were about two times higher in lowland sub-catchments dominated by agricultural lands than in mountainous sub-catchments dominated by forested areas, with median ± SD of 204 ± 22.6 and 102 ± 22.1 mg N m-2 d-1, respectively. Similarly, assimilatory uptake rates were approximately five times higher in streams surrounded by lowland agricultural areas than in those in higher-elevation, forested areas, with median ± SD of 200 ± 27.1 and 39.1 ± 8.7 mg N m-2 d-1, respectively. Therefore, restoration strategies targeting lowland agricultural areas may have greater potential for increasing nitrate retention. The study also found that restoring stream sinuosity could increase net nitrate retention efficiency by up to 25.4 ± 5.3%, with greater effects seen in small streams. These results suggest that restoration efforts should consider augmenting stream sinuosity to increase nitrate retention and decrease nitrate concentrations at the catchment scale.
Grasslands cover ca. 30% of the global land surface and provide critical ecosystem services. Among them, carbon storage is one of the most important. However, grasslands are increasingly threatened by drought and overgrazing which might negatively affect soil carbon stocks. Despite this threat, there is a dearth of information on how drought and grazing jointly impact soil carbon stocks and CO2 fluxes in dryland grasslands. With the aid of a large field experiment, we studied the combined effects of a 5-year extreme drought and moderate grazing on soil carbon stocks, CO2 fluxes and soil chemical properties. Extreme drought was induced by reducing ambient rainfall by 66% using large rainout shelters. We found CO2 fluxes to strongly respond to the 5-year experimental drought. Extreme drought reduced CO2 emission rates by 32% compared to ambient conditions. CO2 fluxes averaged 5.7 mg m(-2)min(-1) under drought compared to 8.3 mg m(-2) min(-1) under ambient conditions. CO2 fluxes were, however, not influenced by grazing. At the end of the growth period, grazed plots under ambient rainfall had released 16.3 tons of CO2 ha(-1) which was 58% higher than observed on grazed plots subjected to severe drought. Soil carbon stocks were higher under drought conditions due to slower decomposition rates. Drought resulted in increased concentrations of primary macronutrients (N, P, and K), micronutrients (Zn and Mn) and pH in the top 30 cm of the soil relative to ambient conditions. The results also showed that grazing reduced the concentration of N and P in the topsoil compared to the ungrazed plots. This study provided insights on the soil carbon storage, CO2 emission rates and nutrient dynamics in a semi-arid dryland grassland as influenced by both drought and grazing. Our study also revealed that long-term extreme drought may be favorable in terms of preserving the existing soil carbon stocks through reduced CO2 release. This finding is critical for understanding future soil carbon dynamics in dryland grasslands in the face of climate change.
The study examined the potential future changes of drought characteristics in the Greater Lake Malawi Basin in Southeast Africa. This region strongly depends on water resources to generate electricity and food. Future projections (considering both moderate and high emission scenarios) of temperature and precipitation from an ensemble of 16 bias-corrected climate model combinations were blended with a scenario-neutral response surface approach to analyses changes in: (i) the meteorological conditions, (ii) the meteorological water balance, and (iii) selected drought characteristics such as drought intensity, drought months, and drought events, which were derived from the Standardized Precipitation and Evapotranspiration Index. Changes were analyzed for a near-term (2021-2050) and far-term period (2071-2100) with reference to 1976-2005. The effect of bias-correction (i.e., empirical quantile mapping) on the ability of the climate model ensemble to reproduce observed drought characteristics as compared to raw climate projections was also investigated. Results suggest that the bias-correction improves the climate models in terms of reproducing temperature and precipitation statistics but not drought characteristics. Still, despite the differences in the internal structures and uncertainties that exist among the climate models, they all agree on an increase of meteorological droughts in the future in terms of higher drought intensity and longer events. Drought intensity is projected to increase between +25 and +50% during 2021-2050 and between +131 and +388% during 2071-2100. This translates into +3 to +5, and +7 to +8 more drought months per year during both periods, respectively. With longer lasting drought events, the number of drought events decreases. Projected droughts based on the high emission scenario are 1.7 times more severe than droughts based on the moderate scenario. That means that droughts in this region will likely become more severe in the coming decades. Despite the inherent high uncertainties of climate projections, the results provide a basis in planning and (water-)managing activities for climate change adaptation measures in Malawi. This is of particular relevance for water management issues referring hydro power generation and food production, both for rain-fed and irrigated agriculture.
The work is designed to investigate the impacts and sensitivity of climate change on water resources, droughts and hydropower production in Malawi, the South-Eastern region which is highly vulnerable to climate change. It is observed that rainfall is decreasing and temperature is increasing which calls for the understanding of what these changes may impact the water resources, drought occurrences and hydropower generation in the region. The study is conducted in the Greater Lake Malawi Basin (Lake Malawi and Shire River Basins) and is divided into three projects. The first study is assessing the variability and trends of both meteorological and hydrological droughts from 1970-2013 in Lake Malawi and Shire River basins using the standardized precipitation index (SPI) and standardized precipitation and evaporation Index (SPEI) for meteorological droughts and the lake level change index (LLCI) for hydrological droughts. And later the relationship of the meteorological and hydrological droughts is established.
While the second study extends the drought analysis into the future by examining the potential future meteorological water balance and associated drought characteristics such as the drought intensity (DI), drought months (DM), and drought events (DE) in the Greater Lake Malawi Basin. The sensitivity of drought to changes of rainfall and temperature is also assessed using the scenario-neutral approach. The climate change projections from 20 Coordinated Regional Climate Downscaling Experiment (CORDEX) models for Africa based on two scenarios (RCP4.5 and RCP8.5) for the periods 2021–2050 and 2071–2100 are used. The study also investigates the effect of bias-correction (i.e., empirical quantile mapping) on the ability of the climate model ensemble in reproducing observed drought characteristics as compared to raw climate projections.
The sensitivity of key hydrologic variables and hydropower generation to climate change in Lake Malawi and Shire River basins is assessed in third study. The study adapts the mesoscale Hydrological Model (mHM) which is applied separately in the Upper Lake Malawi and Shire River basins. A particular Lake Malawi model, which focuses on reservoir routing and lake water balance, has been developed and is interlinked between the two basins. Similar to second study, the scenario-neutral approach is also applied to determine the sensitivity of climate change on water resources more particularly Lake Malawi level and Shire River flow which later helps to estimate the hydropower production susceptibility.
Results suggest that meteorological droughts are increasing due to a decrease in precipitation which is exacerbated by an increase in temperature (potential evapotranspiration). The hydrological system of Lake Malawi seems to have a >24-month memory towards meteorological conditions since the 36-months SPEI can predict hydrological droughts ten-months in advance. The study has found the critical lake level that would trigger hydrological drought to be 474.1 m.a.s.l.
Despite the differences in the internal structures and uncertainties that exist among the climate models, they all agree on an increase of meteorological droughts in the future in terms of higher DI and longer events (DM). DI is projected to increase between +25% and +50% during 2021-2050 and between +131% and +388% during 2071-2100. This translates into +3 to +5, and +7 to +8 more drought months per year during both periods, respectively. With longer lasting drought events, DE is decreasing. Projected droughts based on RCP8.5 are 1.7 times more severe than droughts based on RCP4.5.
It is also found that an annual temperature increase of 1°C decreases mean lake level and outflow by 0.3 m and 17%, respectively, signifying the importance of intensified evaporation for Lake Malawi’s water budget. Meanwhile, a +5% (-5%) deviation in annual rainfall changes mean lake level by +0.7 m (-0.6 m). The combined effects of temperature increase and rainfall decrease result in significantly lower flows on Shire River. The hydrological river regime may change from perennial to seasonal with the combination of annual temperature increase and precipitation decrease beyond 1.5°C (3.5°C) and -20% (-15%). The study further projects a reduction in annual hydropower production between 1% (RCP8.5) and 2.5% (RCP4.5) during 2021–2050 and between 5% (RCP4.5) and 24% (RCP8.5) during 2071–2100.
The findings are later linked to global policies more particularly the United Nations Framework Convention on Climate Change (UNFCCC)’s Paris Agreement and the United Nations (UN)’s Sustainable Development Goals (SDGs), and how the failure to adhere the restriction of temperature increase below the global limit of 1.5°C will affect drought and the water resources in Malawi consequently impact the hydropower production. As a result, the achievement of most of the SDGs will be compromised.
The results show that it is of great importance that a further development of hydro energy on the Shire River should take into account the effects of climate change. The information generation is important for decision making more especially supporting the climate action required to fight against climate change. The frequency of extreme climate events due to climate change has reached the climate emergency as saving lives and livelihoods require urgent action.
The GRACE-FO satellites launched in May 2018 are able to quantify the water mass deficit in Central Europe during the two consecutive summer droughts of 2018 and 2019. Relative to the long-term climatology, the water mass deficits were-112 +/- 10.5 Gt in 2018 and-145 +/- 12 Gt in 2019. These deficits are 73% and 94% of the mean amplitude of seasonal water storage variations, which is so severe that a recovery cannot be expected within 1 year. The water deficits in 2018 and 2019 are the largest in the whole GRACE and GRACE-FO time span. Globally, the data do not show an offset between the two missions, which proves the successful continuation of GRACE by GRACE-FO and thus the reliability of the observed extreme events in Central Europe. This allows for a joint assessment of the four Central European droughts in 2003, 2015, 2018, and 2019 in terms of total water storage deficits.
Impacts of extreme weather events on bacterial community composition of a temperate humic lake
(2020)
Extreme weather events are projected to increase in frequency and intensity as climate change continues. Heterotrophic bacteria play a critical role in lake ecosystems, yet little research has been done to determine how they are affected by such extremes. The purpose of this study was to use high-throughput sequencing to explore the bacterial community composition of a humic oligotrophic lake on the North Atlantic Irish coast and to assess the impacts on composition dynamics related to extreme weather events. Samples for sequencing were collected from Lough Feeagh on a fortnightly basis from April to November 2018. Filtration was used to separate free-living and particle-associated bacterial communities and amplicon sequencing was performed for the 16S rRNA V4 region. Two named storms, six high discharge events, and one drought period occurred during the sampling period. These events had variable, context-dependent effects on bacterial communities in Lough Feeagh. The particle-associated community was found to be more likely to respond to physical changes, such as mixing, while the free-living population responded to changes in nutrient and carbon concentrations. Generally, however, the high stability of the bacterial community observed in Lough Feeagh suggests that the bacterial community is relatively resilient to extreme weather events.
Water deficit (drought stress) massively restricts plant growth and the yield of crops; reducing the deleterious effects of drought is therefore of high agricultural relevance. Drought triggers diverse cellular processes including the inhibition of photosynthesis, the accumulation of cell-damaging reactive oxygen species and gene expression reprogramming, besides others. Transcription factors (TF) are central regulators of transcriptional reprogramming and expression of many TF genes is affected by drought, including members of the NAC family. Here, we identify the NAC factor JUNGBRUNNEN1 (JUB1) as a regulator of drought tolerance in tomato (Solanum lycopersicum). Expression of tomato JUB1 (SlJUB1) is enhanced by various abiotic stresses, including drought. Inhibiting SlJUB1 by virus-induced gene silencing drastically lowers drought tolerance concomitant with an increase in ion leakage, an elevation of hydrogen peroxide (H2O2) levels and a decrease in the expression of various drought-responsive genes. In contrast, overexpression of AtJUB1 from Arabidopsis thaliana increases drought tolerance in tomato, alongside with a higher relative leaf water content during drought and reduced H2O2 levels. AtJUB1 was previously shown to stimulate expression of DREB2A, a TF involved in drought responses, and of the DELLA genes GAI and RGL1. We show here that SlJUB1 similarly controls the expression of the tomato orthologs SlDREB1, SlDREB2 and SlDELLA. Furthermore, AtJUB1 directly binds to the promoters of SlDREB1, SlDREB2 and SlDELLA in tomato. Our study highlights JUB1 as a transcriptional regulator of drought tolerance and suggests considerable conservation of the abiotic stress-related gene regulatory networks controlled by this NAC factor between Arabidopsis and tomato.
Although hydrologic models provide hypothesis testing of complex dynamics occurring at catchments, fresh-water quality modeling is still incipient at many subtropical headwaters. In Brazil, a few modeling studies assess freshwater nutrients, limiting policies on hydrologic ecosystem services. This paper aims to compare freshwater quality scenarios under different land-use and land-cover (LULC) change, one of them related to ecosystem-based adaptation (EbA), in Brazilian headwaters. Using the spatially semi-distributed Soil and Water Assessment Tool (SWAT) model, nitrate, total phosphorous (TP) and sediment were modeled in catchments ranging from 7.2 to 1037 km(2). These head-waters were eligible areas of the Brazilian payment for ecosystem services (PES) projects in the Cantareira water supply system, which had supplied water to 9 million people in the Sao Paulo metropolitan region (SPMR). We considered SWAT modeling of three LULC scenarios: (i) recent past scenario (S1), with historical LULC in 1990; (ii) current land-use scenario (S2), with LULC for the period 2010-2015 with field validation; and (iii) future land-use scenario with PES (S2 + EbA). This latter scenario proposed forest cover restoration through EbA following the river basin plan by 2035. These three LULC scenarios were tested with a selected record of rainfall and evapotranspiration observed in 2006-2014, with the occurrence of extreme droughts. To assess hydrologic services, we proposed the hydrologic service index (HSI), as a new composite metric comparing water pollution levels (WPL) for reference catchments, related to the grey water footprint (greyWF) and water yield. On the one hand, water quality simulations allowed for the regionalization of greyWF at spatial scales under LULC scenarios. According to the critical threshold, HSI identified areas as less or more sustainable catchments. On the other hand, conservation practices simulated through the S2 + EbA scenario envisaged not only additional and viable best management practices (BMP), but also preventive decision-making at the headwaters of water supply systems.