Multiscale Variability and the Comparison of Ground and Satellite Radar Based Measures of Peatland Surface Motion for Peatland Monitoring

Peatland surface motion is highly diagnostic of peatland condition. Interferometric Synthetic Aperture Radar (InSAR) can measure this at the landscape scale but requires ground validation. This necessitates upscaling from point to areal measures (80 × 90 m) but is hampered by a lack of data regarding the spatial variability of peat surface motion characteristics. Using a nested precise leveling approach within two areas of upland and low-lying blanket peatland within the Flow Country, Scotland, we examine the multiscale variability of peat surface motion. We then compare this with InSAR timeseries data. We find that peat surface motion varies at multiple scales within blanket peatland with decreasing dynamism with height above the water table e.g., hummocks < lawn < hollows. This trend is dependent upon a number of factors including ecohydrology, pool size/density, peat density, and slope. At the site scale motion can be grouped into central, marginal, and upland peatlands with each showing characteristic amplitude, peak timing, and response to climate events. Ground measurements which incorporate local variability show good comparability with satellite radar derived timeseries. However, current limitations of phase unwrapping in interferometry means that during an extreme drought/event InSAR readings can only qualitatively replicate peat movement in the most dynamic parts of the peatland e.g., pool systems, quaking bog.

Satellite evidence of canopy-height dependence of forest drought resistance in southwestern China

The frequency and intensity of drought events are increasing with warming climate, which has resulted in worldwide forest mortality. Previous studies have reached a general consensus on the size-dependency of forest resistance to drought, but further understanding at a local scale remains ambiguous with conflicting evidence. In this study, we assessed the impact of canopy height on forest drought resistance in the broadleaf deciduous forest of southwestern China for the 2010 extreme drought event using linear regression and a random forest model. Drought condition was quantified with SPEI (standardized precipitation evapotranspiration index) and drought resistance was measured with the ratio of NDVI (normalized difference vegetation index) during (i.e. 2010) and before (i.e. 2009) the drought. At the regional scale we found that 1) drought resistance of taller canopies (30m and up) declined drastically more than that of canopies with lower height under extreme drought (SPEI < -2); 2). Random forest model showed that the importance of canopy height increased from 17.08% to 20.05% with the increase of drought intensities from no drought to extreme drought. Our results suggest that canopy structure plays a significant role in forest resistance to extreme drought, which has a broad range of implications in forest modeling and resource management.

Comparative and Phylogenetic Analysis of Complete Plastomes among Aristidoideae Species (Poaceae)

Aristidoideae is a subfamily in the PACMAD clade of family Poaceae, including three genera, Aristida, Stipagrostis, and Sartidia. In this study, the plastomes of Aristida adscensionis and Stipagrostis pennata were newly sequenced, and a total of 16 Aristidoideae plastomes were compared. All plastomes were conservative in genome size, gene number, structure, and IR boundary. Repeat sequence analysis showed that forward and palindrome repeats were the most common repeat types. The number of SSRs ranged from 30 (Sartidia isaloensis) to 54 (Aristida purpurea). Codon usage analysis showed that plastome genes preferred to use codons ending with A/T. A total of 12 highly variable regions were screened, including four protein coding sequences (matK, ndhF, infA, and rpl32) and eight non-coding sequences (rpl16-1-rpl16-2, ccsA-ndhD, trnY-GUA-trnD-GUC, ndhF-rpl32, petN-trnC-GCA, trnT-GGU-trnE-UUC, trnG-GCC-trnfM-CAU, and rpl32-trnL-UAG). Furthermore, the phylogenetic position of this subfamily and their intergeneric relationships need to be illuminated. All Maximum Likelihood and Bayesian Inference trees strongly support the monophyly of Aristidoideae and each of three genera, and the clade of Aristidoideae and Panicoideae was a sister to other subfamilies in the PACMAD clade. Within Aristidoideae, Aristida is a sister to the clade composed of Stipagrostis and Sartidia. The divergence between C4 Stipagrostis and C3 Sartidia was estimated at 11.04 Ma, which may be associated with the drought event in the Miocene period. Finally, the differences in carbon fixation patterns, geographical distributions, and ploidy may be related to the difference of species numbers among these three genera. This study provides insights into the phylogeny and evolution of the subfamily Aristidoideae.

An evapotranspiration deficit-based drought index to detect variability of terrestrial carbon productivity in the Middle East

The primary driver of the land carbon sink is gross primary productivity (GPP), the gross absorption of carbon dioxide (CO2) by plant photosynthesis, which currently accounts for about one-quarter of anthropogenic CO2 emissions per year. This study aimed to detect the variability of carbon productivity using the Standardized Evapotranspiration Deficit Index (SEDI). Sixteen countries in the Middle East (ME) were selected to investigate drought. To this end, the yearly GPP dataset for the study area, spanning the 35 years (1982–2017) was used. Additionally, the Global Land Evaporation Amsterdam Model (GLEAM, version 3.3a), which estimates the various components of terrestrial evapotranspiration (annual actual and potential evaporation), was used for the same period. The main findings indicated that productivity in croplands and grasslands was more sensitive to the SEDI in Syria, Iraq, and Turkey by 34, 30.5, and 29.6% of cropland area respectively, and 25 31.5 and 30.5% of grass land area. A significant positive correlation against the long-term data of the SEDI was recorded. Notably, the GPP recorded a decline of >60% during the 2008 extreme drought in the north of Iraq and the northeast of Syria, which concentrated within the agrarian ecosystem and reached a total vegetation deficit with 100% negative anomalies. The reductions of the annual GPP and anomalies from 2009 to 2012 might have resulted from the decrease in the annual SEDI at the peak 2008 extreme drought event. Ultimately, this led to a long delay in restoring the ecosystem in terms of its vegetation cover. Thus, the proposed study reported that the SEDI is more capable of capturing the GPP variability and closely linked to drought than commonly used indices. Therefore, understanding the response of ecosystem productivity to drought can facilitate the simulation of ecosystem changes under climate change projections.

Management of Water Resources in the Semiarid Region of Rio Grande do Norte: a case study on the municipality of Lucrécia

This research aimed to identify water resources management strategies in extreme drought event scenarios in the municipality of Lucrécia, in the state of Rio Grande do Norte (RN), in the period 2012 to 2018. As a methodological procedure, a bibliographical and documentary, in addition to field research, with interviews with municipal managers and residents. A photographic record of the study area was also carried out. It was found that, in the city, there is a folder dedicated to water resources that guides water management and is the basis for the adoption of measures aimed at municipal supply in times of difficult access to water, due to the reduction in water availability. It was observed that part of the interviewed population understands the drought as responsible for the difficulties faced in the city, mainly about the reduction of the water level in the reservoir. It was found that, of the 52 towns belonging to the hydrographic basin of the Apodi-Mossoró river, only 10 participate in the meetings of the basin committee, the municipality of Lucrécia does not have representatives on the Committee. This finding deserves special consideration since water and the administration of its multiple applications are generators of conflicts, it highlights the importance of understanding how municipalities in the Semiarid region carry out the management of water resources and how they understand the challenges of coexistence with its area, aiming at the sustainable use of water.

DroughtCast: A Machine Learning Forecast of the United States Drought Monitor

Drought is one of the most ecologically and economically devastating natural phenomena affecting the United States, causing the U.S. economy billions of dollars in damage, and driving widespread degradation of ecosystem health. Many drought indices are implemented to monitor the current extent and status of drought so stakeholders such as farmers and local governments can appropriately respond. Methods to forecast drought conditions weeks to months in advance are less common but would provide a more effective early warning system to enhance drought response, mitigation, and adaptation planning. To resolve this issue, we introduce DroughtCast, a machine learning framework for forecasting the United States Drought Monitor (USDM). DroughtCast operates on the knowledge that recent anomalies in hydrology and meteorology drive future changes in drought conditions. We use simulated meteorology and satellite observed soil moisture as inputs into a recurrent neural network to accurately forecast the USDM between 1 and 12 weeks into the future. Our analysis shows that precipitation, soil moisture, and temperature are the most important input variables when forecasting future drought conditions. Additionally, a case study of the 2017 Northern Plains Flash Drought shows that DroughtCast was able to forecast a very extreme drought event up to 12 weeks before its onset. Given the favorable forecasting skill of the model, DroughtCast may provide a promising tool for land managers and local governments in preparing for and mitigating the effects of drought.

The Interdecadal Variations and Causes of the Relationship Between Autumn Precipitation Anomalies in Eastern China and SSTA Over the Southeastern Tropical Indian Ocean

Eastern China has a large population with rapid development of the economy, where is the important crop producing region. In this region, the spatial and temporal distribution of autumn rainfall in Eastern China is uneven, which has important societal impact. Using the NCEP–NCAR reanalysis and other observational datasets, it is found that the spatial distribution of the first EOF mode of autumn rainfall anomalies in eastern China is consistent across the region, with significant interannual variabilities. Pronounced interdecadal variations are presented in the relationship between autumn rainfall anomalies in eastern China and sea-surface temperature anomalies (SSTA) over the southeastern tropical Indian Ocean (SETIO). The interdecadal changes have been analyzed by considering two epochs: one during 1979-2004 and the other during 2005-2019. It shows weak and insignificant correlations between the autumn rainfall anomalies in eastern China and SSTA over SETIO during the first epoch. On the other hand, they are remarkable and positively correlated with each other during the second epoch. The inter-decadal changes of the above relationship are related to the warming of SST over SETIO during the second epoch. It causes stronger low-level convergence and ascending motion over SETIO, with the co-occurrence of enhanced western Pacific subtropical high and anomalous abundant moisture over eastern China carried by a low-level southerly anomaly originating from the South China Sea. Simultaneously, the local Hadley circulation over eastern China becomes weak, corresponding to the anomalous ascending motion. The collaboration of anomalous water vapour transport and ascending motion strengthens the connection between the SETIO SSTA and the autumn precipitation anomalies in eastern China, and vice versa. In the boreal autumn of 2019, entire eastern China suffered extreme drought. It suggests that this drought event in eastern China is strongly affected by the negative SSTA over SETIO, which is consistent with the statistical results.

Comparative evaluation of precipitation-temperature based drought indices (DIs): A case study of Moroccan Lower Sebou basin

Due to the lack of studies on drought in the Lower Sebou basin (LSB), the complexity of drought event and the difference in climate conditions. The identification of the most appropriate drought indices (DIs) to assess drought conditions has become a priority. Therefore, assessing the performance of different drought indices was considered in order to identify the universal drought indices that are well adapted to the LSB. Based on data availability, five DIs were used: Standardized Precipitation Index (SPI), Standardized Precipitation and Evapotranspiration Index (SPEI), Reconnaissance Drought Index (RDI), self-calibrated Palmer Drought Severity Index (sc-PDSI) and Streamflow Drought Index (SDI). The DIs were calculated on an annual scale using monthly time series of precipitation, temperature and river flow from 1984-2016. Thornthwaite's method was used to calculate potential evapotranspiration (PET). Pearson's correlation (r) were analyzed. Furthermore, five decision criteria namely robustness, traceability, transparency, sophistication and scalability were used to evaluate the performance of these indices. The results proved the fact that SPI is suitable to detect the drought duration and intensity compared to other indices with high correlation coefficients especially in sub humid regions, knowing that it tends to give more results that are humid in stations with semi-arid climates. SPI, SPEI and RDI follow the same trend during the period studied. However, sc-PDSI appears to be the most sensitive to temperature and precipitation by overestimating the drought conditions. Eventually, the results of the performance evaluation criteria revealed that SPEI classified first (total score = 137) among other meteorological drought indices, followed by SPI, RDI and sc-PDSI.

A Shift From Competition To Facilitation With Abiotic Stress is Limited For Two Codominant Grass Species

It remains unclear how competitive exclusion is avoided between two ecologically, economically, and culturally important codominant grass species in the tallgrass prairie of the Great Plains, Andropogon gerardii and Sorghastrum nutans. These functionally similar C4 grasses appear to coexist despite considerable niche overlap, and asymmetric competition and drought tolerance in favor of A. gerardii. According to the stress gradient hypothesis, it may be that the sum of interactions between these species, which is typically negative (competitive) due to similar resource requirements, shifts to positive (facilitative) as abiotic stress increases. For instance, if the canopy cover of the stronger competitor reduces losses of subcanopy humidity or shallow soil moisture, recruitment of S. nutans tillers may be extended further into the drought event than would occur in the absence of A. gerardii. As later months of the growing season are drier on average where these species are codominant, such a mechanism may enable S. nutans to recover from early season asymmetric competition and stabilize their codominance. We tested this hypothesis in a greenhouse experiment in which we manipulated community composition and water availability in the latter half of the growing season. We found no evidence that a shift from a negative to positive interaction occurs, with each species performing similarly in mixed communities and monocultures. The similarities of the two species in their functional traits and responses to water limitations may limit such a shift in interaction net effects and suggests that other mechanisms are determining coexistence of these co-occuring C4 grasses.

Origin of Intra-annual Density Fluctuations in a Semi-arid Area of Northwestern China

Intra-annual density fluctuation (IADF) is a structural modification of the tree ring in response to fluctuations in the weather. The expected changes in monsoon flow would lead to heterogeneous moisture conditions during the growing season and increase the occurrence of IADF in trees of the arid ecosystems of continental Asia. To reveal the timings and physiological mechanisms behind IADF formation, we monitored cambial activity and wood formation in Chinese pine (Pinus tabuliformis) during 2017–2019 at three sites in semi-arid China. We compared the dynamics of xylem formation under a drought event, testing the hypothesis that drought affects the process of cell enlargement and thus induces the production of IADF. Wood microcores collected weekly from April to October were used for anatomical analyses to estimate the timings of cambial activity, and the phases of enlargement, wall thickening, and lignification of the xylem. The first cells started enlargement from late April to early May. The last latewood cells completed differentiation in mid-September. Trees produced IADF in 2018. During that year, a drought in June limited cell production in the cambium, only 36% of the xylem cells being formed in IADF trees, compared to 68% in normal tree rings. IADF cells enlarged under drought in early July and started wall thickening during the rainfall events of late July. The drought restricted cell enlargement and affected wall thickening, resulting in narrow cells with wide walls. Cambium and cell enlargement recovered from the abundant rainfall, producing a new layer with large earlywood tracheids. IADF is a specific adaptation of trees to cope with water deficit events occurring during xylem formation. Our findings confirmed the hypothesis that the June-July drought induces latewood-like IADFs by limiting the process of cell enlargement in the xylem. Our finding suggests a higher occurrence of IADF in trees of arid and semi-arid climates of continental Asia if the changes to monsoon flows result in more frequent drought events during the earlywood formation in June.