Drought footprint on European ecosystems between 1999 and 2010 assessed by remotely sensed vegetation phenology and productivity

Tracking effects of extreme drought on coniferous forests from space using dynamic habitat indices

Terrestrial ecosystems such as coniferous forests in Central Europe are experiencing changes in health status following extreme droughts compounding with severe heat waves. The increasing temporal resolution and spatial coverage of earth observation data offer new opportunities to assess these dynamics. Dense time-series of optical satellite data allow for computing Dynamic Habitat Indices (DHIs), which have been predominantly used in biodiversity studies. However, DHIs cover three aspects of vegetation changes that could be affected by drought: annual productivity, minimum cover, and seasonality. Here, we evaluate the health status of coniferous forests in the federal state of Hesse in Germany over the period 2017-2020 including the severe drought year of 2018 using DHIs based on the Normalized Difference Vegetation Index (NDVI) for drought assessment. To identify the most important variables affecting coniferous forest die-off, a series of environmental variables together with the three DHIs components were used in a logistic regression (LR) model. Each DHI component changed significantly across non-damaged and damaged sites in all years (p-value 0.05). When comparing 2017 to 2019, DHI-based annual productivity decreased and seasonality increased. Most importantly, none of the DHI components had reached pre-drought conditions, which likely indicates a change in ecosystem functioning. We also identified spatially explicit areas highly affected by drought. The LR model revealed that in addition to common environmental parameters related to temperature, precipitation, and elevation, DHI components were the most important factors explaining the health status. Our analysis demonstrates the potential of DHIs to capture the effect of drought events on Central European coniferous forest ecosystems. Since the spaceborne data are available at the global level, this approach can be applied to track the dynamics of ecosystem conditions in other regions, at larger spatial scales, and for other Land Use/Land Cover types.

Impacts of altitudinal ecohydrological dynamic changes on water balance under warming climate in a watershed of the Qilian Mountains, China

In alpine areas of northwest China, one of the major concerns is the rapid warming and stimulated vegetation growth consume more water and reduce available water for downstream oasis development. Investigating the response of these ecohydrological dynamics to climate change is thus crucial, but is also challenging because of tremendous variability of vegetation, hydrology, and climate in elevation and complex interactions between them. Here, we performed numerical simulations in a mountainous watershed covering a range of contrasting climatic conditions and vegetation characteristics representative of the Qilian Mountains, China. The simulations were run with a dynamic global vegetation model LPJ-WHyMe to quantify spatiotemporal changes of vegetation (e.g., species and net primary production (NPP)) and hydrological components (e.g., runoff and evapotranspiration (ET)) in recent decades (1982-2018). The simulated results were compared with those derived from MODIS and observations. Results show that the favorable climate condition for vegetation growth appears around the freezing altitude (3000-3250 m asl) where the NPP, ET, and water use efficiency (WUE = NPP/ET) exhibit a 'humped' peak value while runoff increases with precipitation towards higher altitudes. The warming and moistening climate and elevated CO2 since 1982 have favored vegetation growth, leading to uphill migration of the treeline and the 'humped' peak to higher elevation (3250-4000 m asl). The climate warming and stimulated vegetation growth consumed 83 % of the increased precipitation (34.6 mm) in the whole catchment. The greatly increased ET and thus decreased runoff were found at high elevation (above 4000 m asl) due to the reduced freezing days (up to 43 days) in the warming climate. Meanwhile, the substantially elevated WUE and moistening climate can balance the increased ET in the vegetation occupation areas below 4000 m asl, leading to increased runoff. The results indicate that despite a little increase of runoff in the recent decades, stimulated vegetation growth and climate warming could reduce water resources availability in the mountains if climate warming continues and/or climate wetting ceases in future.

Spatiotemporal dynamic of subtropical forest carbon storage and its resistance and resilience to drought in China

Subtropical forests are rich in vegetation and have high photosynthetic capacity. China is an important area for the distribution of subtropical forests, evergreen broadleaf forests (EBFs) and evergreen needleleaf forests (ENFs) are two typical vegetation types in subtropical China. Forest carbon storage is an important indicator for measuring the basic characteristics of forest ecosystems and is of great significance for maintaining the global carbon balance. Drought can affect forest activity and may even lead to forest death and the stability characteristics of different forest ecosystems varied after drought events. Therefore, this study used meteorological data to simulate the standardized precipitation evapotranspiration index (SPEI) and the Biome-BGC model to simulate two types of forest carbon storage to quantify the resistance and resilience of EBF and ENF to drought in the subtropical region of China. The results show that: 1) from 1952 to 2019, the interannual drought in subtropical China showed an increasing trend, with five extreme droughts recorded, of which 2011 was the most severe one; 2) the simulated average carbon storage of the EBF and ENF during 1985-2019 were 130.58 t·hm^-2 and 78.49 t·hm^-2, respectively. The regions with higher carbon storage of EBF were mainly concentrated in central and southeastern subtropics, where those of ENF mainly distributed in the western subtropic; 3) The median of resistance of EBF was three times higher than that of ENF, indicating the EBF have stronger resistance to extreme drought than ENF. Moreover, the resilience of two typical forest to 2011 extreme drought and the continuous drought events during 2009 - 2011 were similar. The results provided a scientific basis for the response of subtropical forests to drought, and indicating that improve stand quality or expand the plantation of EBF may enhance the resistance to drought in subtropical China, which provided certain reference for forest protection and management under the increasing frequency of drought events in the future.

Non-growing season drought legacy effects on vegetation growth in southwestern China

Water availability influences terrestrial ecosystems' composition, structure, and function. Recently, climate change increased drought periods frequency and length in many parts of the world, including southwestern China, a biodiversity hotspot. Although the drought impacts on ecosystems are well known, studies are scarce in subtropical areas of China. This work studied the drought legacy effects on vegetation growth in southwestern China using Normalized Difference Vegetation Index (NDVI) and the Standardized Precipitation Evapotranspiration Index (SPEI), with a particular focus on non-growing season extreme drought events. Pervasive non-growing season drought legacy effects were found in the first growing season in most parts of southwestern China. The highest impacts were identified in forests, while the effects in grass were less severe. At the regional scale, horizontal and vertical spatial patterns of drought legacy effects were heterogeneous, and the highest impacts were found in warmer and wetter forests and alpine grasslands. Our study highlights that severe drought conditions may dramatically affect vegetation growth in southwestern China.

Assessment of sal (Shorea robusta) forest phenology and its response to climatic variables in India

Remote sensing-based observation provides an opportunity to study the spatiotemporal variations of plant phenology across the landscapes. This study aims to examine the phenological variations of different types of sal (Shorea robusta) forests in India and also to explore the relationship between phenology metrics and climatic parameters. Sal, one of the main timber-producing species of India, can be categorized into dry, moist, and very moist sal. The phenological metrics of different types of sal forests were extracted from Moderate Resolution Imaging Spectroradiometer (MODIS)-derived Enhanced Vegetation Index (EVI) time series data (2002-2015). During the study period, the average start of season (SOS) was found to be 16 May, 17 July, and 29 June for very moist, moist, and dry sal forests, respectively. The spatial distribution of mean SOS was mapped as well as the impact of climatic variables (temperature and rainfall) on SOS was investigated during the study period. In relation to the rainfall, values of the coefficient of determination (R²) for very moist, moist, and dry sal forests were 0.69, 0.68, and 0.76, respectively. However, with temperature, R² values were found higher (R² = 0.97, 0.81, and 0.97 for very moist, moist, and dry sal, respectively). The present study concluded that MODIS EVI is well capable of capturing the phenological metrics of different types of sal forests across different biogeographic provinces of India. SOS and length of season (LOS) were found to be the key phenology metrics to distinguish the different types of sal forests in India and temperature has a greater influence on SOS than rainfall in sal forests of India.

Assessing Freshwater Changes over Southern and Central Africa (2002–2017)

In large freshwater river basins across the globe, the composite influences of large-scale climatic processes and human activities (e.g., deforestation) on hydrological processes have been studied. However, the knowledge of these processes in this era of the Anthropocene in the understudied hydrologically pristine South Central African (SCA) region is limited. This study employs satellite observations of evapotranspiration (ET), precipitation and freshwater between 2002 and 2017 to explore the hydrological patterns of this region, which play a crucial role in global climatology. Multivariate methods, including the rotated principal component analysis (rPCA) were used to assess the relationship of terrestrial water storage (TWS) in response to climatic units (precipitation and ET). The use of the rPCA technique in assessing changes in TWS is warranted to provide more information on hydrological changes that are usually obscured by other dominant naturally-driven fluxes. Results show a low trend in vegetation transpiration due to deforestation around the Congo basin. Overall, the Congo (r2 = 76%) and Orange (r2 = 72%) River basins maintained an above-average consistency between precipitation and TWS throughout the study region and period. Consistent loss in freshwater is observed in the Zambezi (−9.9 ± 2.6 mm/year) and Okavango (−9.1 ± 2.5 mm/year) basins from 2002 to 2008. The Limpopo River basin is observed to have a 6% below average reduction in rainfall rates which contributed to its consistent loss in freshwater (−4.6 ± 3.2 mm/year) from 2006 to 2012.Using multi-linear regression and correlation analysis we show that ET contributes to the variability and distribution of TWS in the region. The relationship of ET with TWS (r = 0.5) and rainfall (r = 0.8) over SCA provides insight into the role of ET in regulating fluxes and the mechanisms that drive precipitation in the region. The moderate ET–TWS relationship also shows the effect of climate and anthropogenic influence in their interactions.

Local climate and biodiversity affect the stability of China's grasslands in response to drought

The stability of ecosystems is of great significance to the supply of ecosystem services and human well-being. Frequently occurring drought events seriously threaten the stability of terrestrial ecosystems. In particular, in grasslands with low rainfall, ecosystems are more vulnerable to drought. To date, most studies have focused on forest ecosystems, while the difference in the stability of various types of grassland ecosystems under drought is less studied. Here, we selected China's grasslands as the study system and used the standardized precipitation evapotranspiration index (SPEI) to identify drought years and drought events (2001-2015) that occurred in China. Subsequently, we used the satellite-based enhanced vegetation index (EVI) to calculate the resistance (the ability to maintain the original EVI level in a drought year), resilience (the capacity of ecosystem functioning to recover to its normal state after a drought year), and recovery time (how long an ecosystem requires to recover to its predrought EVI) of different grassland types in China from 2001 to 2015. Finally, random forest analysis was used to identify the factors affecting the spatial patterns of the three indicators of stability. The results showed that the grassland ecosystem vulnerability to drought was significantly different among grassland types. The alpine steppe and alpine meadow ecosystems located on the Qinghai-Tibet Plateau have the strongest resistance, the weakest resilience, and the longest recovery time. The meadow steppe and typical steppe ecosystems located in Inner Mongolia have the weakest resistance, the strongest resilience, and the shortest recovery time. The stability of grassland ecosystems is mainly affected by the characteristics of drought events (drought severity and duration), local climate factors (precipitation and temperature), and biodiversity. These results provide a scientific basis for taking appropriate management measures to address the impacts of future drought events on various types of grassland ecosystems.

Monitoring drought events and vegetation dynamics in relation to climate change over mainland China from 1983 to 2016

Due to the present drought events and dynamics of vegetation, the circumstances in mainland China could become even more serious. Therefore, we study the impact of drought on vegetation trends in mainland China, with the aim of discovering the temporal and spatial differences in vegetation dynamics caused by seasonal drought. Our method is based on the use of data from the AVHRR Normalized Difference Vegetation Index (NDVI) from 1983 to 2016 and temperature and precipitation data from Modern Era Retrospective Analysis for Research and Applications (NASA's MERRA). Due to the sparse vegetation and low drought, NDVI is the most useful for describing drought conditions in mainland China. The NDVI, TCI, VHI, NVSWI, VCI, TVDI, and NAP from April to October increased rapidly, while the NDVI, TCI, VHI, NVSWI, NAP, TVDI, and VCI are stable every month in September, improve again in October, and then show in December a downward trend. The NDVI, TCI, VHI, NVSWI, NAP, TVDI, and VCI monthly values indicate that mainland China suffered from severe drought in 1984 and 1993, which lasted until 2007, which were the most drought years. For monitoring drought in mainland China, the NDVI, TVDI, NAP, VCI, and NVSWI values were selected as a tool for reporting drought events during different growing seasons. The seasonal values of TVDI, NDVI, NAP, NVSWI, and VCI confirmed that mainland China suffered from severe drought in 1984, 1993, and 2007 and led the durations of severe drought. Spatial correlation is generated between NDVI, TCI, VHI, NVSWI, NAP, TVDI, and VCI. The correlation between NDVI, TCI, VHI, NAP, and VCI showed a significantly positive correlation while significantly negative correlation between NVSWI and TVDI, TVDI and VHI, which showed a good indication for the assessment of drought, especially for the agricultural regions of mainland China. This shows that the positive sign to support NAP, NVSWI, and TVDI is a good monitoring of the drought indices. During the summer, it appears that compared to the southeastern part of mainland China, drought is more likely to occur in the northwestern areas. There is no doubt that these drought indices are comprehensive indicators of monitoring drought events in mainland China.

Spatiotemporal Characteristics and Trend Analysis of Two Evapotranspiration-Based Drought Products and Their Mechanisms in Sub-Saharan Africa

Drought severity still remains a serious concern across Sub-Saharan Africa (SSA) due to its destructive impact on multiple sectors of society. In this study, the interannual variability and trends in the changes of the self-calibrating Palmer Drought Severity Index (scPDSI) based on the Penman–Monteith (scPDSIPM) and Thornthwaite (scPDSITH) methods for measuring potential evapotranspiration (PET), precipitation (P), normalized difference vegetation index (NDVI), and sea surface temperature (SST) anomalies were investigated through statistical analysis of modeled and remote sensing data. It was shown that scPDSIPM and scPDSITH differed in the representation of drought characteristics over SSA. The regional trend magnitudes of scPDSI in SSA were 0.69 (scPDSIPM) and 0.2 mm/decade (scPDSITH), with a difference in values attributed to the choice of PET measuring method used. The scPDSI and remotely sensed-based anomalies of P and NDVI showed wetting and drying trends over the period 1980–2012 with coefficients of trend magnitudes of 0.12 mm/decade (0.002 mm/decade). The trend analysis showed increased drought events in the semi-arid and arid regions of SSA over the same period. A correlation analysis revealed a strong relationship between the choice of PET measuring method and both P and NDVI anomalies for monsoon and pre-monsoon seasons. The correlation analysis of the choice of PET measuring method with SST anomalies indicated significant positive and negative relationships. This study has demonstrated the applicability of multiple data sources for drought assessment and provides useful information for regional drought predictability and mitigation strategies.

Concurrent and Lagged Effects of Extreme Drought Induce Net Reduction in Vegetation Carbon Uptake on Tibetan Plateau

Climatic extremes have adverse concurrent and lagged effects on terrestrial carbon cycles. Here, a concurrent effect refers to the occurrence of a latent impact during climate extremes, and a lagged effect appears sometime thereafter. Nevertheless, the uncertainties of these extreme drought effects on net carbon uptake and the recovery processes of vegetation in different Tibetan Plateau (TP) ecosystems are poorly understood. In this study, we calculated the Standardised Precipitation–Evapotranspiration Index (SPEI) based on meteorological datasets with an improved spatial resolution, and we adopted the Carnegie–Ames–Stanford approach model to develop a net primary production (NPP) dataset based on multiple datasets across the TP during 1982–2015. On this basis, we quantised the net reduction in vegetation carbon uptake (NRVCU) on the TP, investigated the spatiotemporal variability of the NPP, NRVCU and SPEI, and analysed the NRVCUs that are caused by the concurrent and lagged effects of extreme drought and the recovery times in different ecosystems. According to our results, the Qaidam Basin and most forest regions possessed a significant trend towards drought during 1982–2015 (with Slope of SPEI < 0, P < 0.05), and the highest frequency of extreme drought events was principally distributed in the Qaidam Basin, with three to six events. The annual total net reduction in vegetation carbon uptake on the TP experienced a significant downward trend from 1982 to 2015 (−0.0018 ± 0.0002 PgC year−1, P < 0.001), which was negatively correlated with annual total precipitation and annual mean temperature (P < 0.05). In spatial scale, the NRVCU decrement was widely spread (approximately 55% of grids) with 17.86% of the area displaying significant declining trends (P < 0.05), and the sharpest declining trend (Slope ≤ −2) was mainly concentrated in southeastern TP. For the alpine steppe and alpine meadow ecosystems, the concurrent and lagged effects of extreme drought induced a significant difference in NRVCU (P < 0.05), while forests presented the opposite results. The recovery time comparisons from extreme drought suggest that forests require more time (27.62% of grids ≥ 6 years) to recover their net carbon uptakes compared to grasslands. Therefore, our results emphasise that extreme drought events have stronger lagged effects on forests than on grasslands on the TP. The improved resilience of forests in coping with extreme drought should also be considered in future research.

Drought Impacts on Vegetation in Southeastern Europe

We evaluated the response of vegetation’s photosynthetic activity to drought conditions from 1998 to 2014 over Romania and the Republic of Moldova. The connection between vegetation stress and drought events was assessed by means of a correlation analysis between the monthly Standardized Precipitation Evaporation Index (SPEI), at several time scales, and the Normalized Difference Vegetation Index (NDVI), as well as an assessment of the simultaneous occurrence of extremes in both indices. The analysis of the relationship between drought and vegetation was made for the growing season (from April to October of the entire period), and special attention was devoted to the severe drought event of 2000/2001, considered as the driest since 1961 for the study area. More than three quarters (77%) of the agricultural land exhibits a positive correlation between the two indices. The sensitivity of crop areas to drought is strong, as the impacts were detected from May to October, with a peak in July. On the other hand, forests were found to be less sensitive to drought, as the impacts were limited mostly to July and August. Moreover, vegetation of all land cover classes showed a dependence between the sign of the correlation and the elevation gradient. Roughly 60% (20%) of the study domain shows a concordance of anomalously low vegetation activity with dry conditions of at least 50% (80%) in August. By contrast, a lower value of concordance was observed over the Carpathian Mountains. During the severe drought event of 2000/2001, a decrease in vegetation activity was detected for most of the study area, showing a decrease lasting at least 4 months, between April and October, for more than two thirds (71%) of the study domain.

Bedrock geochemistry influences vegetation growth by regulating the regolith water holding capacity

Although low vegetation productivity has been observed in karst regions, whether and how bedrock geochemistry contributes to the low karstic vegetation productivity remain unclear. In this study, we address this knowledge gap by exploring the importance of bedrock geochemistry on vegetation productivity based on a critical zone investigation across a typical karst region in Southwest China. We show silicon and calcium concentrations in bedrock are strongly correlated with the regolith water loss rate (RWLR), while RWLR can predict vegetation productivity more effectively than previous models. Furthermore, the analysis based on 12 selected karst regions worldwide further suggest that lithological regulation has the potential to obscure and distort the influence of climate change. Our study implies that bedrock geochemistry could exert effects on vegetation growth in karst regions and highlights that the critical role of bedrock geochemistry for the karst region should not be ignored in the earth system model.

The impact of drought spells on forests depends on site conditions: The case of 2017 summer heat wave in southern Europe

A major component of climate change is an increase in temperature and precipitation variability. Over the last few decades, an increase in the frequency of extremely warm temperatures and drought severity has been observed across Europe. These warmer and drier conditions may reduce productivity and trigger compositional shifts in forest communities. However, we still lack a robust, biogeographical characterization of the negative impacts of climate extremes, such as droughts on forests. In this context, we investigated the impact of the 2017 summer drought on European forests. The normalized difference vegetation index (NDVI) was used as a proxy of forest productivity and was related to the standardized precipitation evapotranspiration index, which accounts for the temperature effects of the climate water balance. The spatial pattern of NDVI reduction in 2017 was largely driven by the extremely warm summer for parts of the central and eastern Mediterranean Basin (Italian and Balkan Peninsulas). The vulnerability to the 2017 summer drought was heterogeneously distributed over Europe, and topographic factors buffered some of the negative impacts. Mediterranean forests dominated by oak species were the most negatively impacted, whereas Pinus pinaster was the most resilient species. The impact of drought on the NDVI decreased at high elevations and mainly on east and north-east facing slopes. We illustrate how an adequate characterization of the coupling between climate conditions and forest productivity (NDVI) allows the determination of the most vulnerable areas to drought. This approach could be widely used for other extreme climate events and when considering other spatially resolved proxies of forest growth and health.

Studying of drought phenomena and vegetation trends over South Asia from 1990 to 2015 by using AVHRR and NASA's MERRA data

Drought is a severe climate fact that mainly results from low rainfall leading to serious threat of water shortages an ecological system of South Asia. Due to the current drought conditions and vegetation dynamics, the situation could further be intensified over South Asia. Thus, we study the drought impacts on vegetation dynamics over South Asia, aimed to find out the spatiotemporal differences in vegetation dynamics and seasons at which vegetation is determined by drought. Our approach is based on the using of advanced very high resolution radiometer (AVHRR) normalized difference vegetation index (NDVI) data and (NASA's MERRA) air temperature and rainfall data (1990-2015). Due to the low vegetation and dryness in South Asia, the NDVI is more helpful in describing the drought condition. From April to October, there were fast improvements in NDVI, VHI, and VCI. During September, the monthly VHI and VCI were stabilized and enhanced in October once more and in December again indicated a declining trend. The PCI, TCI, VCI, and VHI monthly values confirmed that in 2001, an extreme drought year, and continuous up to 2003, which lead the maximum drought in the South Asia regions. A considerably significantly correlation value in summer (JJA) and autumn (SON) seasons are showed between precipitation and NDVI. While the relationship between NVSWI and NDVI presented considerably high relationship in DJF, JJA, and SON, which specify an excellent indication for monitoring water stress. From 1990 to 2015, the difference of vegetation trend was obvious showed among various regions. The drought frequency was reducing trends from 1990 to 2015 over South Asia.

High ecosystem stability of evergreen broadleaf forests under severe droughts

Global increase in drought occurrences threatens the stability of terrestrial ecosystem functioning. Evergreen broadleaf forests (EBFs) keep leaves throughout the year, and therefore could experience higher drought risks than other biomes. However, the recent temporal variability of global vegetation productivity or land carbon sink is mainly driven by non-evergreen ecosystems, such as semiarid grasslands, croplands, and boreal forests. Thus, we hypothesize that EBFs have higher stability than other biomes under the increasingly extreme droughts. Here we use long-term Standardized Precipitation and Evaporation Index (SPEI) data and satellite-derived Enhanced Vegetation Index (EVI) products to quantify the temporal stability (ratio of mean annual EVI to its SD), resistance (ability to maintain its original levels during droughts), and resilience (rate of EVI recovering to pre-drought levels) at biome and global scales. We identified significantly increasing trends of annual drought severity (SPEI range: -0.08 to -1.80), area (areal fraction range: 2%-19%), and duration (month range: 7.9-9.1) in the EBF biome over 2000-2014. However, EBFs showed the highest resistance of EVI to droughts, but no significant differences in resilience of EVI to droughts were found among biomes (forests, grasslands, savannas, and shrublands). Global resistance and resilience of EVI to droughts were largely affected by temperature and solar radiation. These findings suggest that EBFs have higher stability than other biomes despite the greater drought exposure. Thus, the conservation of EBFs is critical for stabilizing global vegetation productivity and land carbon sink under more-intense climate extremes in the future.

The Effect of Droughts on Vegetation Condition in Germany: An Analysis Based on Two Decades of Satellite Earth Observation Time Series and Crop Yield Statistics

Central Europe experienced several droughts in the recent past, such as in the year 2018, which was characterized by extremely low rainfall rates and high temperatures, resulting in substantial agricultural yield losses. Time series of satellite earth observation data enable the characterization of past drought events over large temporal and spatial scales. Within this study, Moderate Resolution Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) (MOD13Q1) 250 m time series were investigated for the vegetation periods of 2000 to 2018. The spatial and temporal development of vegetation in 2018 was compared to other dry and hot years in Europe, like the drought year 2003. Temporal and spatial inter- and intra-annual patterns of EVI anomalies were analyzed for all of Germany and for its cropland, forest, and grassland areas individually. While vegetation development in spring 2018 was above average, the summer months of 2018 showed negative anomalies in a similar magnitude as in 2003, which was particularly apparent within grassland and cropland areas in Germany. In contrast, the year 2003 showed negative anomalies during the entire growing season. The spatial pattern of vegetation status in 2018 showed high regional variation, with north-eastern Germany mainly affected in June, north-western parts in July, and western Germany in August. The temporal pattern of satellite-derived EVI deviances within the study period 2000–2018 were in good agreement with crop yield statistics for Germany. The study shows that the EVI deviation of the summer months of 2018 were among the most extreme in the study period compared to other years. The spatial pattern and temporal development of vegetation condition between the drought years differ.

Analysis of vegetation dynamics, drought in relation with climate over South Asia from 1990 to 2011

Drought is the most complex climate-related disaster issue in South Asia, because of the various land-cover changes, vegetation dynamics, and climates. The aims of the current research work were to analyze the performance of AVHRR Normalized Difference Vegetation Index (NDVI) and spatiotemporal differences in vegetation dynamics on a seasonal basis by correlating the results with NASA's MERRA precipitation and air temperature for monitoring vegetation dynamics and drought over South Asia. Our approach is based on the use of AVHRR NDVI data and NASA's MERRA rainfall and air temperature data (1990-2011). Due to the low vegetation and dryness, the NDVI is more helpful in describing the drought condition in South Asia. There were rapid increases in NDVI, VHI, and VCI from April to October. Monthly NDVI, VHI, and VCI stabilize in September and improved once more in October and then show a declining trend in December. The monthly PCI, TCI, VHI, and VCI values showed that the South Asia goes through an extreme drought in 2000, which continues up to 2002, which lead the highest water stress. Spatial correlation maps among NDVI, precipitation, air temperature, VHI, and VCI on a seasonal basis. The correlation between NDVI and precipitation showed a significantly higher correlation value in JJA and SON seasons; the spatial correlation between NDVI and air temperature showed significant high values in DJF, JJA, and SON periods, while the correlation between VHI and TCI showed a significantly higher values in MAM and SON seasons, which indicated a good sign for dryness monitoring, mainly for farming regions during these seasons in South Asia. It was confirmed that these indexes are a comprehensive drought monitoring indicator and a step to monitoring the climate change in South Asia, which will play a relevant role ongoing studies on vegetation types, monitoring climate change, and drought over South Asia.

Climate-phenology-hydrology interactions in northern high latitudes: Assessing the value of remote sensing data in catchment ecohydrological studies

We assessed the hydrological implications of climate effects on vegetation phenology in northern environments by fusion of data from remote-sensing and local catchment monitoring. Studies using satellite data have shown earlier and later dates for the start (SOS) and end of growing seasons (EOS), respectively, in the Northern Hemisphere over the last 3 decades. However, estimates of the change greatly depend on the satellite data utilized. Validation with experimental data on climate-vegetation-hydrology interactions requires long-term observations of multiple variables which are rare and usually restricted to small catchments. In this study, we used two NDVI (normalized difference vegetation index) products (at ~25 & 0.5 km spatial resolutions) to infer SOS and EOS for six northern catchments, and then investigated the likely climate impacts on phenology change and consequent effects on catchment water yield, using both assimilated data (GLDAS: global land data assimilation system) and direct catchment observations. The major findings are: (1) The assimilated air temperature compared well with catchment observations (regression slopes and R² close to 1), whereas underestimations of summer rainstorms resulted in overall underestimations of precipitation (regression slopes of 0.3-0.7, R² ≥ 0.46). (2) The two NDVI products inferred different vegetation phenology characteristics. (3) Increased mean pre-season temperature significantly influenced the advance of SOS and delay of EOS. The precipitation influence was weaker, but delayed SOS corresponding to increased pre-season precipitation at most sites can be related to later snow melting. (4) Decreased catchment streamflow over the last 15 years could be related to the advance in SOS and extension of growing seasons. Greater streamflow reductions in the cold sites than the warm ones imply stronger climate warming impacts on vegetation and hydrology in colder northerly environments. The methods used in this study have potential for better understanding interactions between vegetation, climate and hydrology in observation-scarce regions.

Modelling the impacts of global multi-scale climatic drivers on hydro-climatic extremes (1901-2014) over the Congo basin

The knowledge of interactions between oceanic and atmospheric processes and associated influence on drought episodes is a key step toward designing robust measure that could support government and institutional measures for drought preparedness to promote region-specific drought risk-management policy solutions. This has become necessary for the Congo basin where the preponderance of evidence from few case studies shows long-term drying and hydro-climatic extremes attributed to perturbations of the nearby oceans. In this study, statistical relationships are developed between observed standardised precipitation index (SPI) and global sea surface temperature using principal component analysis as a regularization tool prior to the implementation of a canonical scheme. The connectivity between SPI patterns and global ocean-atmosphere phenomena was thereafter examined using the output from this scheme in a predictive framework based on non-linear autoregressive standard neural network. The Congo basin is shown to have been characterized by persistent and severe multi-year droughts during the earlier (1901-1930) and latter (1991-2014) decades of the last century. The impacts of these droughts were extensive affecting more than 50% of the basin between 1901 and 1930 and about 40% during the 1994-2006 period. Analysis of the latest decades (1994-2014) shows that relative to the two climatological periods between 1931 and 1990, the Congo basin has somewhat become drier. This likely contributed to the observed change in the hydrological regimes of the Congo river (after 1994) as indicated by the relationship between SPI and runoff index (r = 0.69 and 0.64 for 1931-1990 and 1961-1990 periods, respectively as opposed to r = 0.38 for 1991-2010 period). Pacific ENSO influences large departures in precipitation (r = 0.89) but prediction skill metrics demonstrate that multi-scale ocean-atmosphere phenomena (R² = 84%, 78%, and 77% for QBO, AMO, and ENSO, respectively) significantly impact on hydro-climatic extremes, especially droughts over the Congo basin.

Pathways and Network Based Analysis of Candidate Genes to Reveal Cross-Talk and Specificity in the Sorghum (Sorghum bicolor (L.) Moench) Responses to Drought and It's Co-occurring Stresses

Drought alone or in combination with other stresses forms the major crop production constraint worldwide. Sorghum, one of the most important cereal crops is affected by drought alone or in combination with co-occurring stresses; notwithstanding, sorghum has evolved adaptive responses to combined stresses. Furthermore, an impressive number of sorghum genes have been investigated for drought tolerance. However, the molecular mechanism underling drought response remains poorly understood. We employed a systems biology approach to elucidate regulatory and broad functional features of these genes. Their interaction network would provide insight into understanding the molecular mechanisms of drought tolerance and underpinning signal pathways. Functional analysis was undertaken to determine significantly enriched genesets for pathways involved in drought tolerance. Analysis of distinct pathway cross-talk network was performed and drought-specific subnetwork was extracted. Investigation of various data sources such as gene expression, regulatory pathways, sorghumCyc, sorghum protein-protein interaction (PPI) and Gene Ontology (GO) revealed 14 major drought stress related hub genes (DSRhub genes). Significantly enriched genesets have shown association with various biological processes underlying drought-related responses. Key metabolic pathways were significantly enriched in the drought-related genes. Systematic analysis of pathways cross-talk and gene interaction network revealed major cross-talk pathway modules associated with drought tolerance. Further investigation of the major DSRhub genes revealed distinct regulatory genes such as ZEP, NCED, AAO, and MCSU and CYP707A1. These were involved in the regulation of ABA biosynthesis and signal transduction. Other protein families, namely, aldehyde and alcohol dehydrogenases, mitogene activated protein kinases (MAPKs), and Ribulose-1,5-biphosphate carboxylase (RuBisCO) were shown to be involved in the drought-related responses. This shows a diversity of complex functional features in sorghum to respond to various abiotic stresses. Finally, we constructed a drought-specific subnetwork, characterized by unique candidate genes that were associated with DSRhub genes. According to our knowledge, this is the first in sorghum drought investigation that introduces pathway and network-based candidate gene approach for analysis of drought tolerance. We provide novel information about pathways cross-talk and signaling networks used in further systems level analysis for understanding the molecular mechanism behind drought tolerance and can, therefore, be adapted to other model and non-model crops.

Root traits of European Vicia faba cultivars-Using machine learning to explore adaptations to agroclimatic conditions

Faba bean (Vicia faba L.) is an important source of protein, but breeding for increased yield stability and stress tolerance is hampered by the scarcity of phenotyping information. Because comparisons of cultivars adapted to different agroclimatic zones improve our understanding of stress tolerance mechanisms, the root architecture and morphology of 16 European faba bean cultivars were studied at maturity. Different machine learning (ML) approaches were tested in their usefulness to analyse trait variations between cultivars. A supervised, that is, hypothesis-driven, ML approach revealed that cultivars from Portugal feature greater and coarser but less frequent lateral roots at the top of the taproot, potentially enhancing water uptake from deeper soil horizons. Unsupervised clustering revealed that trait differences between northern and southern cultivars are not predominant but that two cultivar groups, independently from major and minor types, differ largely in overall root system size. Methodological guidelines on how to use powerful ML methods such as random forest models for enhancing the phenotypical exploration of plants are given.

The impact of drought on vegetation conditions within the Damqu River Basin, Yangtze River Source Region, China

Drought and vegetation conditions within the Damqu River Basin, part of the Yangtze River Source Region (YRSR), are assessed here using the standardized precipitation index (SPI), the standardized precipitation evapotranspiration index (SPEI), the normalized difference vegetation index (NDVI), and the leaf area index (LAI). We utilized Sen’s method, least squares regression method, linear regression and Pearson’s correlation analysis to study variations in drought and vegetation indices and the drought effect on vegetation between 1988 and 2015. Results reveal that droughts occurred at a 25% frequency over this period; SPI and SPEI analyses show that 1994, 1999, 2005, and 2010 were change points and that the basin was characterized by varying drought and humidity trends. Subsequent to 2010, both SPI and SPEI decreased within the basin, while 1995, 2000, 2004, and 2010 were change points for NDVI and LAI while the watershed exhibited variable trends in vegetation reduction and increase. The NDVI-annual values of 63.36% regions and the LAI-summer values of 68.39% areas within the basin were decreased during 1988–2015 and 2000–2015, respectively. Subsequent to 2010, both NDVI and LAI decreased within the basin and significant positive correlations at inter-annual and inter-summer time scales were seen in both drought and vegetation indices; drought has exerted a lag effect on vegetation as shown by significant positive correlations between annual SPI/SPEI values and following year NDVI/LAI values.

Drought timing influences the legacy of tree growth recovery

Whether and how the timing of extreme events affects the direction and magnitude of legacy effects on tree growth is poorly understood. In this study, we use a global database of Ring-Width Index (RWI) from 2,500 sites to examine the impact and legacy effects (the departure of observed RWI from expected RWI) of extreme drought events during 1948-2008, with a particular focus on the influence of drought timing. We assessed the recovery of stem radial growth in the years following severe drought events with separate groupings designed to characterize the timing of the drought. We found that legacies from extreme droughts during the dry season (DS droughts) lasted longer and had larger impacts in each of the 3 years post drought than those from extreme droughts during the wet season (WS droughts). At the global scale, the average integrated legacy from DS droughts (0.18) was about nine times that from WS droughts (0.02). Site-level comparisons also suggest stronger negative impacts or weaker positive impacts of DS droughts on tree growth than WS droughts. Our results, therefore, highlight that the timing of drought is a crucial factor determining drought impacts on tree recovery. Further increases in baseline aridity could therefore exacerbate the impact of punctuated droughts on terrestrial ecosystems.

Temporal Changes in Coupled Vegetation Phenology and Productivity are Biome-Specific in the Northern Hemisphere

Global warming has greatly stimulated vegetation growth through both extending the growing season and promoting photosynthesis in the Northern Hemisphere (NH). Analyzing the combined dynamics of such trends can potentially improve our current understanding on changes in vegetation functioning and the complex relationship between anthropogenic and climatic drivers. This study aims to analyze the relationships (long-term trends and correlations) of length of vegetation growing season (LOS) and vegetation productivity assessed by the growing season NDVI integral (GSI) in the NH (>30°N) to study any dependency of major biomes that are characterized by different imprint from anthropogenic influence. Spatial patterns of converging/diverging trends in LOS and GSI and temporal changes in the coupling between LOS and GSI are analyzed for major biomes at hemispheric and continental scales from the third generation Global Inventory Monitoring and Modeling Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) dataset for a 32-year period (1982–2013). A quarter area of the NH is covered by converging trends (consistent significant trends in LOS and GSI), whereas diverging trends (opposing significant trends in LOS and GSI) cover about 6% of the region. Diverging trends are observed mainly in high latitudes and arid/semi-arid areas of non-forest biomes (shrublands, savannas, and grasslands), whereas forest biomes and croplands are primarily characterized by converging trends. The study shows spatially-distinct and biome-specific patterns between the continental land masses of Eurasia (EA) and North America (NA). Finally, areas of high positive correlation between LOS and GSI showed to increase during the period of analysis, with areas of significant positive trends in correlation being more widespread in NA as compared to EA. The temporal changes in the coupled vegetation phenology and productivity suggest complex relationships and interactions that are induced by both ongoing climate change and increasingly intensive human disturbances.

Identification of drought-responsive microRNAs in tomato using high-throughput sequencing

Drought is a major abiotic stress affecting crop productivity and quality. As a class of noncoding RNA, microRNA (miRNA) plays important roles in plant growth, development, and stress response. However, their response and roles in tomato drought stress is largely unknown. Here, by using high-throughput sequencing, we compared the miRNA profiles before and after drought treatment in two tomato genotypes: M82, a drought-sensitive cultivated tomato (Solanum lycopersicum), and IL2-5, a drought-tolerant introgression line derived from M82 and the tomato wild species S. pennellii (LA0716). A total of 108 conserved and 208 novel miRNAs were identified, among them, 32 and 68 were significantly changed in expression after stress. Further, 1936 putative target genes were predicted for those differentially-expressed miRNAs. Gene ontology and pathway analysis showed that many of the target genes were involved in stress resistance, such as genes in GO terms including response to stress, defense response, response to stimulus, phosphorylation, and signal transduction. Our results suggested that miRNAs play an essential role in the drought response of tomato. This work will help to further characterize specific miRNAs functioning in drought tolerance.

Are the traditional large-scale drought indices suitable for shallow water wetlands? An example in the Everglades

Numerous drought indices have been developed over the past several decades. However, few studies have focused on the suitability of indices for studies of ephemeral wetlands. The objective is to answer the following question: can the traditional large-scale drought indices characterize drought severity in shallow water wetlands such as the Everglades? The question was approached from two perspectives: the available water quantity and the response of wetland ecosystems to drought. The results showed the unsuitability of traditional large-scale drought indices for characterizing the actual available water quantity based on two findings. (1) Large spatial variations in precipitation (P), potential evapotranspiration (PE), water table depth (WTD) and the monthly water storage change (SC) were observed in the Everglades; notably, the spatial variation in SC, which reflects the monthly water balance, was 1.86 and 1.62 times larger than the temporal variation between seasons and between years, respectively. (2) The large-scale water balance measured based on the water storage variation had an average indicating efficiency (IE) of only 60.01% due to the redistribution of interior water. The spatial distribution of variations in the Normalized Different Vegetation Index (NDVI) in the 2011 dry season showed significantly positive, significantly negative and weak correlations with the minimum WTD in wet prairies, graminoid prairies and sawgrass wetlands, respectively. The significant and opposite correlations imply the unsuitability of the traditional large-scale drought indices in evaluating the effect of drought on shallow water wetlands.

Contrasting impacts of continuous moderate drought and episodic severe droughts on the aboveground-biomass increment and litterfall of three coexisting Mediterranean woody species

Climate change is predicted to increase the aridity in the Mediterranean Basin and severely affect forest productivity and composition. The responses of forests to different timescales of drought, however, are still poorly understood because extreme and persistent moderate droughts can produce nonlinear responses in plants. We conducted a rainfall-manipulation experiment in a Mediterranean forest dominated by Quercus ilex, Phillyrea latifolia, and Arbutus unedo in the Prades Mountains in southern Catalonia from 1999 to 2014. The experimental drought significantly decreased forest aboveground-biomass increment (ABI), tended to increase the litterfall, and decreased aboveground net primary production throughout the 15 years of the study. The responses to the experimental drought were highly species-specific. A. unedo suffered a significant reduction in ABI, Q. ilex experienced a decrease during the early experiment (1999-2003) and in the extreme droughts of 2005-2006 and 2011-2012, and P. latifolia was unaffected by the treatment. The drought treatment significantly increased branch litterfall, especially in the extremely dry year of 2011, and also increased overall leaf litterfall. The drought treatment reduced the fruit production of Q. ilex, which affected seedling recruitment. The ABIs of all species were highly correlated with SPEI in early spring, whereas the branch litterfalls were better correlated with summer SPEIs and the leaf and fruit litterfalls were better correlated with autumn SPEIs. These species-specific responses indicated that the dominant species (Q. ilex) could be partially replaced by the drought-resistant species (P. latifolia). However, the results of this long-term study also suggest that the effect of drought treatment has been dampened over time, probably due to a combination of demographic compensation, morphological and physiological acclimation, and epigenetic changes. However, the structure of community (e.g., species composition, dominance, and stand density) may be reordered when a certain drought threshold is reached.

Assessments of Drought Impacts on Vegetation in China with the Optimal Time Scales of the Climatic Drought Index

Drought is expected to increase in frequency and severity due to global warming, and its impacts on vegetation are typically extensively evaluated with climatic drought indices, such as multi-scalar Standardized Precipitation Evapotranspiration Index (SPEI). We analyzed the covariation between the SPEIs of various time scales and the anomalies of the normalized difference vegetation index (NDVI), from which the vegetation type-related optimal time scales were retrieved. The results indicated that the optimal time scales of needle-leaved forest, broadleaf forest and shrubland were between 10 and 12 months, which were considerably longer than the grassland, meadow and cultivated vegetation ones (2 to 4 months). When the optimal vegetation type-related time scales were used, the SPEI could better reflect the vegetation’s responses to water conditions, with the correlation coefficients between SPEIs and NDVI anomalies increased by 5.88% to 28.4%. We investigated the spatio-temporal characteristics of drought and quantified the different responses of vegetation growth to drought during the growing season (April–October). The results revealed that the frequency of drought has increased in the 21st century with the drying trend occurring in most of China. These results are useful for ecological assessments and adapting management steps to mitigate the impact of drought on vegetation. They are helpful to employ water resources more efficiently and reduce potential damage to human health caused by water shortages.