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Objectives: Arid pastoralism is often understood as an adaptive strategy to marginal environments. As pastoralists become increasingly market integrated, novel dietary preferences and access to low quality market foods can erode traditional diets. These market-based dietary shifts are particularly problematic during sustained drought, where reductions in traditional foods make pastoralists increasingly reliant on a cash economy. Among the Himba of the Kunene region in Namibia, colonial policies prohibiting access to livestock markets inhibit access to a cash-based economy, leaving them vulnerable to food insecurity when nontraditional foods are needed to supplement traditional lifeways during drought. To understand the impacts of long-term drought on diet and food insecurity, we collected longitudinal survey data on diet breadth and food insecurity across 4 years during a multi-year drought., Methods: Participants completed a five-item food insecurity survey and recalled diet breadth survey over the course of 4 years (N = 191-234). Additionally, women completed a short survey of recent stressors, including health and resource stressors (N = 127). We used a set of multilevel models to estimate changes in food insecurity items and diet breadth changes over the course of the study period., Results: Multilevel models predicted score outcomes, as well as individual item responses, by year of data collection. Results indicate a 43% increase in average food insecurity and a 15% decline in average diet breadth over the study period. Dietary recall indicates that drought caused a reduction in sour milk intake, and an increase in nontraditional foods, but no change in meat or maize consumption., Conclusions: Sustained drought in the Kunene region is having long-term impacts on food insecurity, which could result in dietary shifts that outlast the current period of drought. We consider the implications of this change, especially as it relates to increasing market integration and reliance on a cash-based over a subsistence-based economy., (© 2022 Wiley Periodicals LLC.)

Numerous recent studies have argued that moisture limitation is leading to growth declines and mortality of black spruce (Picea mariana) and white spruce (Picea glauca) in the North American boreal forest. A parallel line of research suggests that increasingly common severe wildfires are altering successional pathways and leading to long‐term replacement of spruce forests with those dominated by paper birch (Betula papyrifera, Betula neoalaskana) and trembling aspen (Populus tremuloides). When both conifers and deciduous trees establish after fire, this biome shift hypothesis implicitly assumes that deciduous species will outcompete the conifers, owing to their more rapid vertical growth and because they might be less sensitive to warm and dry conditions.We established a research site in a white spruce‐paper birch forest on an east‐facing slope in interior Alaska and tested the hypothesis that Alaska paper birch are better adapted to warm and dry conditions than white spruce. Over 6 years (2013–2018), we made hourly measurements of microclimate and xylem sap flux of both species. We also collected increment cores and conducted climate‐growth analyses for both species.During our 6‐year study, growing seasons with low volumetric soil water content (SWC) were those that followed shallow winter snowpacks and had limited summer rainfall, not necessarily those with warm air temperature. Both species were sensitive to moisture limitation. The tree‐ring data revealed significant positive effects of cumulative water year precipitation on radial growth, with a steeper slope for paper birch than for white spruce. Radial growth of both species was also positively related to mean water year air temperature. Sap flux density declined progressively for white spruce over the range of observed SWC and abruptly for paper birch when SWC fell below ~15%.Synthesis. Our results show that, while paper birch might be less sensitive to mild drought than white spruce, it may be more sensitive to severe drought, raising questions about the ability of paper birch to outcompete co‐occurring white spruce in a drier climate. [ABSTRACT FROM AUTHOR]

Extensive dieback of salt marsh dominated by the perennial grass Spartina alterniflora occurred throughout the Mississippi River deltaic plain during 2000. More than 100,000 ha were affected, with 43,000 ha severely damaged. The aim of this work was to determine if sudden dieback could have been caused by a coincident drought and to assess the significance of this event with respect to long-term changes in coastal vegetation. Multiple dieback sites and reference sites were established along 150 km of shoreline in coastal Louisiana, USA. Aerial and ground surveys were conducted from June 2000 to September 2001 to assess soil conditions and plant mortality and recovery. Dieback areas ranged in size from ∼300 m2−5 km2 in area with 50–100% mortality of plant shoots and rhizomes in affected zones. Co-occurring species such as Avicennia germinans (black mangrove) and Juncus roemerianus (needlegrass rush) were unaffected. Historical records indicate that precipitation, river discharge, and mean sea level were unusually low during the previous year. Although the cause of dieback is currently unknown, plant and soil characteristics were consistent with temporary soil desiccation that may have reduced water availability, increased soil salinity, and/or caused soil acidification (via pyrite oxidation) and increased uptake of toxic metals such as Fe or Al. Plant recovery 15 months after dieback was variable (0–58% live cover), but recovering plants were vigorous and indicated no long-lasting effects of the dieback agent. These findings have relevance for global change models of coastal ecosystems that predict vegetation responses based primarily on long-term increases in sea level and submergence of marshes. Our results suggest that large-scale changes in coastal vegetation may occur over a relatively short time span through climatic extremes acting in concert with sea-level fluctuations and pre-existing soil conditions. [ABSTRACT FROM AUTHOR]

Anthropogenic climate change contributes to increased frequency and intensity of droughts, wildfires, storms, coastal sea level rise, and population displacements, in addition to causing lung and cardiovascular diseases from the emission of Criteria Air Pollutants (CAPs). The aviation sector is estimated to contribute 2%–3% of global anthropogenic Greenhouse Gas (GHG) emissions. This excludes GHG emissions from airport operation and maintenance activities due to limited research in the area. This systematic literature review examined the Life Cycle Assessment (LCA) carried out by previous studies on the environmental impacts of airport operation and maintenance activities. This allows to assess existing literature on the impacts of these activities; identify knowledge gaps in LCA based on the findings of the review; and propose areas for further research and improvement in mitigating the environmental impacts of airport operation and maintenance activities. A total of 11 papers were selected for thematic analysis and narrative synthesis following a systematic review process based on the research question which yielded a total of 263 peer‐reviewed research articles and dissertations on the topic. The findings of the review showed that knowledge gaps exist in the LCA of environmental impacts of Auxiliary Power Units (APU) and Ground Support Equipment (GSE) operations in the airport during aircraft turnaround time. Further research is suggested in the use of feasible and affordable alternative energy sources (electricity, compressed natural gas, liquefied petroleum gas, and hydrogen) at airports to reduce the environmental impacts associated with petrol‐ and diesel‐powered GSE and gate operations at airports. [ABSTRACT FROM AUTHOR]

Summary: Drought is intensifying globally with climate change, creating an urgency to understand ecosystem response to drought both during and after these events end to limit loss of ecosystem functioning. The literature is replete with studies of how ecosystems respond during drought, yet there are far fewer studies focused on ecosystem dynamics after drought ends. Furthermore, while the terms used to describe drought can be variable and inconsistent, so can those that describe ecosystem responses following drought. With this review, we sought to evaluate and create clear definitions of the terms that ecologists use to describe post‐drought responses. We found that legacy effects, resilience and recovery were used most commonly with respect to post‐drought ecosystem responses, but the definitions used to describe these terms were variable. Based on our review of the literature, we propose a framework for generalizing ecosystem responses after drought ends, which we refer to as 'the post‐drought period'. We suggest that future papers need to clearly describe characteristics of the imposed drought, and we encourage authors to use the term post‐drought period as a general term that encompasses responses after drought ends and use other terms as more specific descriptors of responses during the post‐drought period. [ABSTRACT FROM AUTHOR]

Changes in precipitation patterns with climate change could have important impacts on human and natural systems. Zhang et al. (2021, https://doi.org/10.1029/2020gl092293) report trends in daily precipitation patterns over the last five decades in the western United States, focusing on meteorological drought. They report that dry intervals (calculated at the annual or seasonal level) have increased across much of the southwestern U.S., with statistical assessment suggesting the results are statistically robust. However, Zhang et al. (2021, https://doi.org/10.1029/2020gl092293) preprocess their annual (or seasonal) averages to compute 5‐year moving window averages before using established statistical techniques for trend analysis that assume independence about some fixed trend. Here we show that the moving window preprocessing violates that independence assumption and inflates the statistical significance of their trend estimates. This raises questions about the robustness of their results. We conclude by discussing the difficulty of adjusting for spatial structure when assessing time trends in a regional context. Plain Language Summary: A recent paper reports trends in drought in the western United States, in particular increases in drought in the southwestern United States, based on changes in the lengths of time intervals without precipitation. In this "comment" we note that the preprocessing approach used in the paper artificially increases the apparent statistical signal in the data and caution that the evidence for the trends reported is not as strong as presented in the paper. We conclude by discussing the difficulty of estimating trends in a statistically rigorous fashion across multiple weather stations. Key Points: Statistical uncertainty about trends in droughts in the southwestern US is larger than reported in a recent GRL letter [ABSTRACT FROM AUTHOR]

Paciorek and Wehner raise important questions around our use of the Mann‐Kendall nonparametric trend test on smoothed data for analyzing long‐term hydrometeorological trends in Zhang et al. (2021, https://doi.org/10.1029/2020gl092293). We thank them for initiating this important conversation and their gracious cooperation in exploring the issues addressed in their comment. In this reply we confirm the inflation of significant p‐values by our choice to smooth, illustrate the relatively minor impacts on the main conclusions of our paper, and add our voices to those of Paciorek and Wehner in highlighting the lack of methodology for hypothesis testing across multiple stations that have spatial structure (i.e., testing for regionally consistent trends). Plain Language Summary: Our colleagues Drs. Paciorek and Wehner have raised concerns about our paper (Zhang et al., 2021, https://doi.org/10.1029/2020gl092293), which showed widespread increases in the duration of drought events over the last five decades in the western United States. They point out that our decision to smooth the data using a moving average inflated the number of weather stations at which the trends toward longer droughts were deemed significant by a statistical test. We agree with them on this point, and we have recomputed all our results using unsmoothed data to determine the impacts. We find that for most stations and regions, trend magnitudes remained largely unchanged, with many stations nearby one another often suggesting similar trends. Finally, we agree with Paciorek and Wehner that there is a lack of statistical methods to test such coherent regional patterns, and we caution that over‐reliance on p‐values limits the power of regional data to identify important climate trends. Key Points: We agree that smoothing to 5‐year moving windows introduced serial correlation into time series of annual statistics of daily rainfall data, inflating the number of weather stations individually showing significant trends (p < 0.05) with the Mann‐Kendall testRecomputation with unsmoothed values produced substantially the same dry intervals trend magnitude and direction at most stations individually and had only minimal impacts on dry interval trends computed for National Ecological Observatory Network domains using the Regional Kendall testNo perfect statistical approach leverages the capacity of coherent regional patterns among spatially correlated weather stations, and an over‐reliance on p‐values as a binary (significant vs. insignificant) determinant of trends limits the power of regional data [ABSTRACT FROM AUTHOR]

The article provides literary figure John Spencer's arguments defending his enclosures in his works. The commodities of pasture and considerations shown in the article prove that it is necessary to have them. In primus by enclosure there is fat iovys and moutons two times a year which cannot be past once a year in no fallow field in the best year and some fallow fields which are none. In one item of enclosure there is great breed of sheep. And the ewes going in pasture spend little hay or none by reason of coming after the danger of winter pasture. In another item when the great rain comes or great drought or other unreasonable weather the pasture sheep enjoy. In another item it is elaborated that to make new houses is not requisite for there is more houses than there be men to dwell in them in many villages and towns except in places nigh to the sea coast or the City of London in England. Another item argues that the Statutes of Laborers may be better in Execution than they have been.

Disaster Risk Management (DRM) is complex due to interacting climate risks from interacting hazards and sectors. We develop a synthetic multi‐risk test case to explore the effects of these interactions on decision‐making under deep uncertainty. The test case accounts for changes in hazard impacts and occurrence frequency due to interactions between floods and droughts. Interactions between the shipping, housing and agricultural sectors are considered as well. We use this test case to explore the utility of the Dynamic Adaptive Policy Pathways for Multi‐Risk (DAPP‐MR) framework. DAPP‐MR has been introduced to assess DRM policies' effectiveness under deep uncertainties and to develop integrated adaptive strategies considering interactions across hazards, sectors and time. With the test case, we show that the stage‐wise approach of DAPP‐MR, which gradually increases the complexity of the analysis, can facilitate the evaluation process. Earlier stages of the analysis can be used to establish the direct cause‐effect relations, later stages allow us to identify whether additional interacting factors have a significant effect on the direct cause‐effect relations. As a result, decision‐makers can gain insights into dependencies and their relevance for developing short‐to long‐term strategies under deep uncertainty. We show that multi‐risk interactions can lead to non‐linear effects that influence the outcome of the policy analysis, for example, the indirect influence of a decision in one sector on another. Future work could investigate further improving the operationalization of this staged approach as well as extending the set of uncertainties, dynamics and decision‐rules accounted for in the multi‐risk test case. Plain Language Summary: This paper addresses the complex challenge that many regions face when dealing with multiple interconnected disasters, like floods, droughts and earthquakes. Traditional Disaster Risk Management methods often fall short, particularly in long‐term planning that considers factors such as climate change. We apply a step‐by‐step approach known as "Dynamic Adaptive Policy Pathways for Multi‐Risk (DAPP‐MR)" to assist decision‐makers in better understanding and planning for these intertwined risks over time. This paper employs a hypothetical test case where different sectors (e.g., agricultural sector) seek effective ways to prepare for and respond to flood and drought risks. The DAPP‐MR method facilitates this by breaking down the process into smaller, more manageable steps. This approach allows for an easier understanding of the direct effects of disasters and gradually incorporates more complex interactions between different risks. Our findings suggest that this step‐by‐step method can aid decision‐makers in grasping the connections between various factors and their significance in formulating both short‐ and long‐term strategies. The study also reveals that interactions between different risks can produce unexpected, nonlinear effects, adding complexity to the interpretation of policy outcomes. Key Points: A multi‐risk modeling case with interacting hazards and sectors is created to explore effects for decision‐making under deep uncertaintyDynamic Adaptive Policy Pathways for Multi‐Risk has proven effective for pathway analysis to grasp interactions and their relevance through a structured, stage‐by‐stage approachMulti‐risk interactions can alter the decision‐making outcome because of changes in performance or timings of potential pathways [ABSTRACT FROM AUTHOR]

ABSTRACT Since Monteith published his seminal paper on evaporation and introduced the canopy resistance 50 years ago, evaporation research has shown great progress, such that his contribution describing evaporation as the delicate interplay between supply, demand and control, needs a tribute. We first identify the key contributions of John Monteith to this development and then identify a new set of challenges in the field of ecohydrology made possible by his breakthrough. These relate to adequate prediction of the occurrence, frequency and severity of drought, in relation to vegetation water use and resilience, and the interplay between the carbon and water cycles. Importantly, since Monteith published his paper, development of satellite remote sensing has made it possible to generalize site level processes and to investigate vegetation, carbon and water relations at global scale. This emerging field of research, tentatively called global ecohydrology, is set to address key questions related to the resilience and vulnerability of the world's ecosystems to their changing environment. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Global hydrological reanalyses are modelled datasets providing information on river discharge evolution everywhere in the world. With multi‐decadal daily timeseries, they provide long‐term context to identify extreme hydrological events such as floods and droughts. By covering the majority of the world's land masses, they can fill the many gaps in river discharge in‐situ observational data, especially in the global South. These gaps impede knowledge of both hydrological status and future evolution and hamper the development of reliable early warning systems for hydrological‐related disaster reduction. River discharge is a natural integrator of the water cycle over land. Global hydrological reanalysis datasets offer an understanding of its spatio‐temporal variability and are therefore critical for addressing the water–energy–food–environment nexus. This paper describes how global hydrological reanalyses can fill the lack of ground measurements by using earth system or hydrological models to provide river discharge time series. Following an inventory of alternative sources of river discharge datasets, reviewing their advantages and limitations, the paper introduces the Copernicus Emergency Management Service (CEMS) Global Flood Awareness System (GloFAS) modelling chain and its reanalysis dataset as an example of a global hydrological reanalysis dataset. It then reviews examples of downstream applications for global hydrological reanalyses, including monitoring of land water resources and ocean dynamics, understanding large‐scale hydrological extreme fluctuations, early warning systems, earth system model diagnostics and the calibration and training of models, with examples from three Copernicus Services (Emergency Management, Marine and Climate Change). [ABSTRACT FROM AUTHOR]

Hydrological extremes, such as droughts and floods, can trigger a complex web of compound and cascading impacts (CCI) due to interdependencies between coupled natural and social systems. However, current decision‐making processes typically only consider one impact and disaster event at a time, ignoring causal chains, feedback loops, and conditional dependencies between impacts. Analyses capturing these complex patterns across space and time are thus needed to inform effective adaptation planning. This perspective paper aims to bridge this critical gap by presenting methods for assessing the dynamics of the multi‐sector CCI of hydrological extremes. We discuss existing challenges, good practices, and potential ways forward. Rather than pursuing a single methodological approach, we advocate for methodological pluralism. We see complementary or even convergent roles for analyses based on quantitative (e.g., data‐mining, systems modeling) and qualitative methods (e.g., mental models, qualitative storylines). The data‐driven and knowledge‐driven methods provided here can serve as a useful starting point for understanding the dynamics of both high‐frequency CCI and low‐likelihood but high‐impact CCI. With this perspective, we hope to foster research on CCI to improve the development of adaptation strategies for reducing the risk of hydrological extremes. Plain Language Summary: Droughts and floods can have significant impacts on both natural and social systems. These impacts are often interconnected, resulting in a complex chain of events. In this perspective paper, we aim to assist researchers in understanding the dynamics of compound and cascading impacts (CCI) caused by hydrological extremes. We provide an overview of various methods that can be utilized to assess and analyze interconnected impacts. To begin, we address the ongoing challenges associated with CCI research, such as the limited availability of comprehensive impact data spanning multiple sectors and over extended periods. Subsequently, we present a range of qualitative and quantitative methods that can be employed to analyze CCI dynamics, supported by case study examples. Finally, we conclude with six recommendations to advance the research in this field. Key Points: Systematic efforts to collect data on impacts across multiple sectors, systems, and years are requiredMethodological pluralism is necessary to fully address the complexity of compound and cascading impacts (CCI) and their underlying risk driversInvestigation of the risks of multi‐sector impacts should be guided not only by probability but also by plausibility considerations [ABSTRACT FROM AUTHOR]

Aim: As climate change increases the frequency and severity of droughts in many regions, conservation during drought is becoming a major challenge for ecologists. Droughts are multidimensional climate events whose impacts may be moderated by changes in temperature, water availability or food availability, or some combination of these. Simultaneously, other stressors such as extensive anthropogenic landscape modification may synergize with drought. Useful observational models for guiding conservation decision‐making during drought require multidimensional, dynamic representations to disentangle possible drought impacts, and consequently, they will require large, highly resolved data sets. In this paper, we develop a two‐stage predictive framework for assessing how drought impacts vary with species, habitats and climate pathways. Location: Central Valley, California, USA. Methods: We used a two‐stage counterfactual analysis combining predictive linear mixed models and N‐mixture models to characterize the multidimensional impacts of drought on 66 bird species. We analysed counts from the eBird participatory science data set between 2010 and 2019 and produced species‐ and habitat‐specific estimates of the impact of drought on relative abundance. Results: We found that while fewer than a quarter (16/66) of species experienced abundance declines during drought, nearly half of all species (27/66) changed their habitat associations during drought. Among species that shifted their habitat associations, the use of natural habitats declined during drought while use of developed habitat and perennial agricultural habitat increased. Main Conclusions: Our findings suggest that birds take advantage of agricultural and developed land with artificial irrigation and heat‐buffering microhabitat structure, such as in orchards or parks, to buffer drought impacts. A working lands approach that promotes biodiversity and mitigates stressors across a human‐induced water gradient will be critical for conserving birds during drought. [ABSTRACT FROM AUTHOR]

Drought has a paramount impact on global agriculture and food security. However, the study on future cropland areas that can incur drought is inadequate. This paper uses input parameters from 7 CMIP6 models for 7 future scenarios (SSP1‐1.9, SSP1‐2.6, SSP4‐3.4, SSP2‐4.5, SSP4‐6.0, SSP3‐7.0, and SSP5‐8.5) to measure South Asian cropland exposure to drought and its underlying factors. Some defined epochs such as 2021–2040 (near‐term), 2041–2060 (mid‐term), 2081–2100 (long‐term), and 1995–2014 (reference period) are designed to explore diverse outlooks of the change. The Standardized Precipitation Evapotranspiration Index and the Run theory methods are applied to detect drought. Results indicate an intensified cropland (under SSP4‐3.4, SSP3‐7.0, and SSP5‐8.5) in the Indo‐Gangetic Plain region of South Asia, where mostly the variation occurs among scenarios and periods. Notably, the future cropland exposed to drought will increase in the 2021–2040, and 2041–2060 periods, but it intends to decline during the 2081–2100. Relatively, the exposed cropland will upturn highest by 49.2% (SSP3‐7.0) in the mid‐term period and decrease by −8.2% (SSP5‐8.5) in the end future. Spatially, distributed cropland in the central, south‐west, and portion of the northeast of South Asia are subjective to be exposed largely, but it can drop greatly across the eastern part by the end future. Importantly, the climate change effect plays a grounding role in future exposure change over the region during the near to mid‐term periods, while the cropland change effect is predominant in the long‐term perspectives. However, these findings signify the urgency of policymaking focusing on drought mitigation to ensure food security. Plain Language Summary: Estimating drought‐induced cropland exposure is the pivotal aspect of agricultural risk assessment for drought impacts. The purposes of this study are to explore (a) how much of the cropland area would be exposed to drought under SSP scenarios; and (b) the degree to which climate change and cropland change effects contribute to changes in exposure. In this regard, we conducted a multi‐model and multi‐scenario‐based analysis to reveal variations in the cropland area exposed to drought in South Asia. Among the seven scenario combinations, the highest percentage of cropland exposed to drought was found at 49.2% (SSP3‐7.0) in the mid‐term epoch (2041–2060). The climate change effect seems to be the key contributor in the near‐term to mid‐term period, whereas it is the cropland change effect long‐term. To reduce drought risk, we recommend focusing on strong climate change mitigation policy development in the near‐ and mid‐term periods at a global scale and strict land‐use management policy interventions in the long‐term period at the regional level. Key Points: Larger cropland area will experience drought in the 2040–2060 period, while it will decline by the end of 21st centuryThe exposed cropland will increase by 49.2% under SSP3‐7.0 than that of historical timeThe climate change effect is the pivotal contributor in exposure changes over South Asia [ABSTRACT FROM AUTHOR]

Understanding historical soil moisture (SM) variations and their relationship with temperature in high‐latitude humid regions is essential for predicting hot droughts under widespread warming. This paper presents the first‐ever annual‐resolution summer surface SM reconstruction (1736–2006 CE) in Sweden, located in northern Europe (NE). The reconstruction utilizes the paleoclimate proxy, tree‐ring δ18O, which exhibits a strong correlation with reanalysis SM data during 1948–2007 CE (r = −0.67, p < 0.001). In contrast to an unprecedented trend suggested by previous studies, our reconstruction exhibits a wetting trend in NE since the 1960s falling within the historical spectrum of trends. Both reanalysis SM data and our reconstruction show significant negative correlations with temperature at interannual timescales. However, Coupled Model Intercomparison Project Phase 6 climate models failed to capture the significant SM‐temperature relationship during the historical (1850–1947 CE) and observation periods (1948–2006 CE). This proxy‐model comparison represents a critical step toward enhancing our understanding of SM dynamics and the reliability of SM projections in high‐latitude humid regions. Plain Language Summary: Soil moisture (SM) refers to water in any form contained in soils, and it plays an important role in sustaining plant growth and influencing climate dynamics. SM deficits can result in ecological/agricultural droughts. However, our understanding of historical SM changes is limited due to the scarcity of long‐term records. Consequently, modeling historical SM changes proves challenging and prone to inaccuracies. In this study, we utilized a tree‐ring record to reconstruct centuries‐long SM changes in Sweden, located in northern Europe. Our analysis revealed a significant negative correlation between SM and temperature in both our reconstruction and SM data sets. However, state‐of‐art models failed to capture the significant relationship observed at our study site. These findings highlight the need to improve climate models to increase the accuracy of climate forecasts and better understand SM dynamics in high‐latitude humid areas. Key Points: This study presents the first 271‐year historical soil moisture (SM) reconstruction in northern Europe (NE) using the tree‐ring δ18O proxySignificant correlations between historical SM and temperature in NE were observed at interannual timescalesOur results implied that Coupled Model Intercomparison Project Phase 6 models might underestimate the SM‐temperature relationship [ABSTRACT FROM AUTHOR]

This paper investigates the extent to which households in rural Thailand across the income distribution are able to mitigate income risks in the face of shocks. It uses especially high‐quality household income and consumption data spanning 64 Thai villages over 15 years. The paper identifies income shocks by village‐level variations during drought conditions. It finds that richer households are better able to mitigate income risk than poorer households, in contrast to some studies of the South Asian subcontinent. These possibilities for managing income risk are shown to be correlated with the type of contract the head of household is likely to be employed in, the share of salaries in total household income, the education level of the head, the relative youth of the heads of richer households, and location effects. [ABSTRACT FROM AUTHOR]

Drought, widely studied as an important driver of ecosystem dynamics, is predicted to increase in frequency and severity globally. To study drought, ecologists must define or at least operationalize what constitutes a drought. How this is accomplished in practice is unclear, particularly given that climatologists have long struggled to agree on definitions of drought, beyond general variants of "an abnormal deficiency of water." We conducted a literature review of ecological drought studies (564 papers) to assess how ecologists describe and study drought. We found that ecologists characterize drought in a wide variety of ways (reduced precipitation, low soil moisture, reduced streamflow, etc.), but relatively few publications (~32%) explicitly define what are, and are not, drought conditions. More troubling, a surprising number of papers (~30%) simply equated "dry conditions" with "drought" and provided little characterization of the drought conditions studied. For a subset of these, we calculated Standardized Precipitation Evapotranspiration Index values for the reported drought periods. We found that while almost 90% of the studies were conducted under conditions quantifiable as slightly to extremely drier than average, ~50% were within the range of normal climatic variability. We conclude that the current state of the ecological drought literature hinders synthesis and our ability to draw broad ecological inferences because drought is often declared but is not explicitly defined or well characterized. We suggest that future drought publications provide at least one of the following: (a) the climatic context of the drought period based on long‐term records; (b) standardized climatic index values; (c) published metrics from drought‐monitoring organizations; (d) a quantitative definition of what the authors consider to be drought conditions for their system. With more detailed and consistent quantification of drought conditions, comparisons among studies can be more rigorous, increasing our understanding of the ecological effects of drought. [ABSTRACT FROM AUTHOR]

Drought is an important meteorological event in China and can cause severe damage to both livelihoods and socio‐ecological systems, but current seasonal prediction skill for drought is far from successful. This study used convolutional neural network (CNN) to build an effective seasonal forecast model for the summer consecutive dry days (CDD) over China. The principal components (PC) of the six leading empirical orthogonal function modes of CDD anomaly were predicted by CNN, using the previous winter precipitation, 2‐m temperature and 500 hPa geopotential height as predictors. These predicted PCs were then projected onto the observed spatial patterns to obtain the final predicted summer CDD anomaly over China. In the independent hindcast period of 2007–2018, the interannual variabilities of first six PCs were significantly predicted by CNN. The spatial patterns of CDD were then skillfully predicted with anomaly correlation coefficient skills generally higher than 0.2. The interannual variability of summer CDD over the middle and lower Yangtze River valley, northwestern China and northern China were significant predicted by our CNN model three months in advance. CNN identified that the previous winter precipitation was the important predictor for PC1–PC3, whereas the previous winter 2‐m temperature and 500 hPa geopotential height were important for the prediction of PC4–PC6. This research provides a new and effective method for the seasonal prediction of summer drought. Plain Language Summary: Drought can cause serious agricultural and ecosystem disasters, so its forecast is valuable for preventing and mitigating related natural disasters and regional socioeconomic sustainability. However, current prediction skill for drought is far from successful since its extreme feature. The gradually emerging deep learning methods offer new possibilities, but how to effectively apply deep learning models in climate prediction with a small sample size remains an open question. In this paper, we build seasonal prediction convolutional neural network model for summer consecutive dry days over China using previous winter predictors. This model achieves significant prediction skill three months in advance. The empirical orthogonal function decomposition is used to reduce the dimensionality of consecutive dry days data in our model. Our research provides a new perspective for drought prediction, and it is expected that such method will be also useful for other seasonal climate prediction problems. Key Points: Convolutional neural network (CNN) skillfully predicts summer consecutive dry days (CDD) over China three months in advanceThe principal components of CDD are predicted by CNN and then projected on the observed spatial patternsPrevious winter 2‐m temperature, geopotential height at 500 hPa and precipitation are the essential predictors in CNN [ABSTRACT FROM AUTHOR]

Problems of frequent drought stress, low soil organic carbon (SOC) concentration, low aggregation, susceptibility to compaction, salinization and accelerated soil erosion in dry regions are accentuated by removal of crop residues, mechanical methods of seedbed preparation, summer clean fallowing and overgrazing, and excessive irrigation. The attendant soil degradation and desertification lead to depletion of SOC, decline in biomass production, eutrophication/pollution of waters and emission of greenhouse gases. Adoption of conservation agriculture, based on the use of crop residue mulch and no till farming, can conserve water, reduce soil erosion, improve soil structure, enhance SOC concentration, and reduce the rate of enrichment of atmospheric CO2. The rate of SOC sequestration with conversion to conservation agriculture, elimination of summer fallowing and growing forages/cover crops may be 100 to 200 kg ha−1 y−1 in coarse‐textured soils of semiarid regions and 150 to 300 kg ha−1 y−1 in heavy‐textured soils of the subhumid regions. The potential of soil C sequestration in central Asia is 10 to 22 Tg C y−1 (16±8 Tg C y−1) for about 50 years, and it represents 20 per cent of the CO2 emissions by fossil fuel combustion. Copyright © 2004 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The water table depth (WTD) in peatlands determines the soil carbon decomposition rate and influences vegetation growth, hence the above‐ground carbon assimilation. Here, we used satellite‐observed Solar‐Induced chlorophyll Fluorescence (SIF) as a proxy of Gross Primary Production (GPP) to investigate water‐related vegetation stress over northern peatlands. A linear model with interaction effects was used to relate short‐ and long‐term anomalies in SIF with WTD anomalies and the absolute WTD. Most locations showed the occurrence of drought and waterlogging stress though regions with exclusively waterlogging or drought stress were also detected. As a spatial median, minimal water‐related vegetation stress was found for a WTD of −0.22 m (short‐term) and −0.20 m (long‐term) (±0.01 m, 95% confidence interval of statistical uncertainty). The stress response observed with SIF is supported by an analysis of in situ GPP data. Our findings provide insight into how changes in WTD of northern peatlands could affect GPP under climate change. Plain Language Summary: Water table depth is an important variable influencing the carbon cycle and vegetation growth in northern peatlands. In this paper, the impact of changing wetness conditions on vegetation growth over peatlands was studied through satellite measurements of solar‐induced fluorescence (SIF), which is a radiation signal emitted by vegetation during photosynthesis. Previous studies over ecosystems on mineral soil, that is, not over peatland, suggested a response of SIF to drought conditions. In our study, it was shown that peatland vegetation experiences moisture‐related growth stress under both very wet and very dry conditions, which might reduce the photosynthesis efficiency and the ability to capture and store CO2. Stress due to drought conditions was detected for peatlands in the south of the Western Siberian Lowlands and the Boreal Plains. Stress due to prolonged wet conditions occurred for example, in the north of the Western Siberian Lowlands and the north of the Hudson Bay Lowlands. Key Points: Spaceborne Solar‐Induced Fluorescence (SIF) data was used to analyze soil moisture‐related vegetation stress regimes in northern peatlandsFor most locations, waterlogging as well as drought stress regimes occurred and alternated depending on peatland water level dynamicsThe SIF‐based stress response observations are supported by in situ data of Gross Primary Production [ABSTRACT FROM AUTHOR]

Although a growing body of literature studies drought impacts, papers providing a comprehensive review of drought's social and economic impacts are scarce. This paper fills this gap by exploring the consequences of drought on societies based on research findings in Australia—a large country used to experiencing severe droughts. To do this, we propose a framework to categorise drought impacts in three dimensions: individuals/households (including health), productive sectors and system (including economic and ecosystem) impacts. The framework then guides a systematic literature review and discussion of studies looking at diverse drought impacts and their related costs. By analysing and discussing the findings from this literature, we emphasise different policy considerations, empirical challenges and research needs to support robust analysis and estimates of the true cost of droughts. We conclude by proposing an expanded framework to identify drought impacts and a discussion of the implications of the review for policy development. [ABSTRACT FROM AUTHOR]

This paper reviews the Flash Drought concept, the uncertainties associated with FD prediction, and the potential of Machine Learning (ML) and Deep learning (DL) for future applications. For this, 121 relevant articles covering different aspects of FD ‐ definitions, key indicators, distinguishing characteristics, and the current methods for FD assessment (i.e., ‐ monitoring, prediction, and impact assessment) are examined. FD is typically a short‐term drought event ‐ characterized by the rapid progression of heat waves and precipitation deficits, causing cascading impacts on the land and surface hydrology. FD prediction is constrained by the lack of consistent FD definitions, key indicators, the limited predictability of FD at the subseasonal‐ to‐seasonal (S2S) timescale, and uncertainties associated with the current prediction methods. Some of the uncertainties in the current methods are associated with a lack of our understanding of the physical processes. They are also related to the error in the input datasets (imperfect representation of indicators), parameter uncertainty (parameterization scheme adopted by the prediction model), multicollinearity, nonlinear, and non‐stationary interactions among different indicators. Combining traditional methods and multisource fusion data with ML and DL methods shows promise to better understand FD evolution and improves prediction. Plain Language Summary: Flash Drought (FD) events develop rapidly and have notable agricultural impacts. This paper reviews recent notable FD studies. Several studies highlight the need to develop an improved understanding and prediction of FD to manage its effects better. However, the lack of consistent definition, documentation and fragmented assessments have limited progress toward improved prediction models. This review considers questions related to FD definition, triggers, and how it is different from the more classical droughts. A summary of methods and their limitations to predict FD are considered. The review concludes that the lack of standard definition, and characterization of FD is a major stumbling block. It inhibits the development of representative data set that can capture the complex multiscale information that characterizes FDs. Without such data set and reference, resultant models could lead to divergent pathways and false predictions of FD. The review also suggests Machine Learning (ML) and Deep Learning (DL) approaches can extract information from multi‐scale complex datasets routinely used for traditional drought prediction. The addition of ML and DL methods with the current method can help FD prediction by extracting predictive information regarding the physical processes that trigger such events, their impacts and society's response. Key Points: Lack of consistent definition and related inventories for Flash Drought (FD) is a stumbling block to developing reliable prediction modelsTraditional FD prediction methods need to represent the uncertainty of key indicators, their highly correlated and time‐varying interactionsCombining ML and DL methods with traditional methods, multisource fusion data can provide a potential framework for improving FD prediction [ABSTRACT FROM AUTHOR]

Tree rings have been central to the understanding of variability of flow of the Colorado River. Spurred by steadily declining flows after the 1920s, early tree‐ring research drew attention to the importance of climate variability to water supply by identifying episodes in the past that were even drier. Application of modern statistical methods to tree‐ring data later yielded a reconstruction of annual flows at Lees Ferry back to the early 1500s that highlighted the unprecedented wetness of the base period for the 1922 Colorado River Compact. That reconstruction served as the framework for a collection of papers in a 1995 special issue of Water Resources Bulletin on coping with severe sustained drought on the Colorado River. This retrospective paper reviews historical aspects of the dendrohydrology of the Colorado River, and the updates since 1995. A constantly expanding tree‐ring network has been subjected to an array of new statistical approaches to reconstruction. Climate change and increasing demand for water have meanwhile driven increased interest in the processing and presentation of reconstructions for optimal use in water resources planning and management. While highlighting the robustness of main findings of earlier studies, recent research yields improved estimates of magnitudes of flow anomalies, extends annual flows to more than 1200 years, and underscores unmatched drought duration in the medieval period. [ABSTRACT FROM AUTHOR]

Rhizobacteria play a crucial role in plant growth and yield, stimulating primary production and improving stress resistance. Climate change has several consequences worldwide that affect arable land and agriculture. Studies on plant–soil–microorganism interactions to enhance plant productivity and/or resistance to abiotic stress may open new perspectives. This strategy aims to make agricultural‐relevant plant species able to complete their biological cycle in extreme soils with the help of inoculated or primed plant growth‐promoting rhizobacteria (PGPR).We provide an overview of the evolution of interest in PGPR research in the last 30 years through: (i) a quantitative search on the Scopus database; (ii) keyword frequencies and clustering analysis, and (iii) a keyword network and time‐gradient analysis.The review of scientific literature on PGPR highlighted an increase in publications in the last 15 years, and a specific time gradient on subtopics, such as abiotic stresses. The rise in PGPR as a keyword co‐occurring with salinity and drought stresses aligns with the growing number of papers from countries directly or partly affected by climate change.The study of PGPR, its features, and related applications will be a key challenge in the next decades, considering climate change effects on agriculture. The increased interest in PGPR leads to deeper knowledge focused specifically on researching agriculturally sustainable solutions for soils affected by salinity and drought. [ABSTRACT FROM AUTHOR]

Highly fragile small island states experience disproportionate climate impacts given their limited capacity to implement cost‐effective tools for detecting emerging signals of drying conditions and monitoring systems for sensitive sectors such as agriculture, especially for uncertain, ‘creeping’ events such as droughts. Despite the existence of open‐source Google Earth Engine datasets, untapped potential remains for their full deployment in disaster management infrastructure. Given this gap, this paper explores the utility of the Enhanced Vegetation Index (EVI) for detecting spatio‐temporal variations of Mid‐Summer Drought (MSD) impacts on vegetation in the small island of Jamaica, with emphasis on major historical drought events. Geospatial analyses of EVI datasets from the Terra Moderate‐Resolution Imaging Spectroradiometer (MODIS) between 2000−2015 archived by the United States Geological Survey (USGS), were computed, and validated by station‐based precipitation and production data for selected parishes for historical case study MSD events. Results revealed highly asymmetrical drought impacts, with Jamaica's agriculturally intense Southern coastline displaying the most stressed vegetation (EVI < 0.5). North‐Western and North‐Eastern regions had the healthiest vegetation during the MSD (EVI > 0.6). A ‘fair’ to ‘moderate’ concurrent correlation was found between EVI and precipitation (R > 0.6), with lower correlations vis‐a‐vis agricultural production (R = 0.2–0.4). The results provide evidence of EVI's utility as a drought monitoring tool in a small island context. [ABSTRACT FROM AUTHOR]

Hydrogeodesy, a relatively new field within the earth sciences, is the analysis of the distribution and movement of terrestrial water at Earth's surface using measurements of Earth's shape, orientation, and gravitational field. In this paper, we review the current state of hydrogeodesy with a specific focus on Global Navigation Satellite System (GNSS)/Global Positioning System measurements of hydrologic loading. As water cycles through the hydrosphere, GNSS stations anchored to Earth's crust measure the associated movement of the land surface under the weight of changing hydrologic loads. Recent advances in GNSS‐based hydrogeodesy have led to exciting applications of hydrologic loading and subsequent terrestrial water storage (TWS) estimates. We describe how GNSS position time series respond to climatic drivers, can be used to estimate TWS across temporal scales, and can improve drought characterization. We aim to facilitate hydrologists' use of GNSS‐observed surface deformation as an emerging tool for investigating and quantifying water resources, propose methods to further strengthen collaborative research and exchange between geodesists and hydrologists, and offer ideas about pressing questions in hydrology that GNSS may help to answer. Plain Language Summary: Hydrogeodesy is a relatively new discipline within the earth sciences that analyzes the storage and movement of water at or near Earth's surface using measurements of Earth's shape, orientation, and gravitational field. In this paper, we review the current state of hydrogeodesy, focusing on the use of Global Positioning System and Global Navigation Satellite System (GNSS) to measure water masses as they change over time and in location. GNSS stations are anchored directly to Earth's crust and measure the movement of the land surface under the weight of changing (i.e., addition, loss, or movement) water masses. Herein, we describe how GNSS position time series respond to changing inputs of rain and snow and variable water loss, how they can be used to estimate the distribution of terrestrial water storage over time, and how they can improve drought characterization. We assert that GNSS‐based hydrogeodesy is an emerging tool that hydrologists can use to investigate and quantify water resources and we seek to explain and facilitate its use, propose methods to further strengthen collaborative research and exchange between geodesists and hydrologists, and offer ideas about pressing questions in hydrology that GNSS may help to answer. Key Points: Hydrogeodesy analyzes the distribution and movement of terrestrial water using measurements of Earth's shape, orientation, and gravityWe review the current state of hydrogeodesy, focusing on Global Navigation Satellite System (GNSS) measurements of hydrologic loading and terrestrial water storageWe aim to facilitate the use of GNSS‐observed surface deformation as an emerging tool for investigating and quantifying water resources [ABSTRACT FROM AUTHOR]

Uncertainty remains over local‐scale responses of ecotonal Amazonian forests to middle Holocene drying due to the scarcity, and coarse spatial resolution, of lacustrine pollen records. This paper examines the palaeoecological potential of soil phytoliths, stable carbon isotopes and charcoal for capturing local‐scale ecotonal responses of different types of Bolivian Amazonian forest to middle Holocene climate change. Soil pits 1 m deep were dug at ecotones between rainforest, dry forest, Chaco woodland and savannah, and sampled at 5–10 cm resolution. Both phytolith and stable carbon isotope records indicate stability of dry forest–savannah ecotones over the last ca. 6000 years, despite middle Holocene drought, revealing the dominance of edaphic factors over climate in controlling this type of ecotone. In contrast, δ13C data reveal that rainforest–savannah ecotones were more responsive to climate change, with rainforest likely replaced by drought‐tolerant dry forest or savannah vegetation during the mid‐Holocene, consistent with regional‐scale lacustrine pollen records. However, such shifts are not apparent in most of our phytolith records due to insufficient taxonomic resolution in differentiating rainforest from dry forest. Charcoal data show that ecotonal dry forests experienced greater fire activity than rainforests and that recent high fire activity at all forest sites is unprecedented since at least the middle Holocene. [ABSTRACT FROM AUTHOR]

There is a need to support applied, community‐relevant hydrologic research within changing climate, population, and socioeconomic conditions to better inform water policy and management. We hypothesized that providing a rural agricultural community in a semiarid valley with the necessary monitoring tool to meet local water management needs would increase adaptive capacity within the context of long‐term drought. Through a community science approach, researchers installed a telemetry monitoring system at participating acequia irrigation diversions that remotely sent water data to a web interface every 15 min. Two surveys distributed before and after web interface access targeted seven adaptive capacity indicators. After the first season of improved data accessibility, the following adaptive capacity indicators significantly increased: information diversity, cognitive social capital, leadership, and proactivity. Rather than focusing on the water savings aspect of real‐time monitoring, this paper summarizes a novel water resources study that assessed the social impact of real‐time irrigation water delivery monitoring on adaptive capacity. This study suggests that bridging the gap between community need and hydrologic research through community science, sociologic analysis, and stakeholder engagement provides significant benefits for communities facing water management challenges, further supporting problem‐driven water resources research. [ABSTRACT FROM AUTHOR]

The article lists the books including "Adaptive Management of Social-Ecological Systems" and "Presidents and the American Environment," and websites including Drought Risk Atlas located at http://droughtatlas.unl.edu.

Risk assessment for climate‐sensitive systems often relies on the analysis of several variables measured at many sites. In probabilistic terms, the task is to model the joint distribution of several spatially distributed variables, and how it varies in time. This paper describes a Bayesian hierarchical framework for this purpose. Each variable follows a distribution with parameters varying in both space and time. Temporal variability is modeled by means of hidden climate indices (HCIs) that are extracted from observed variables. This is to be contrasted with the usual approach using predefined standard climate indices (SCIs) for this purpose. In the second level of the model, the HCIs and their effects are assumed to follow temporal and spatial Gaussian processes, respectively. Both intervariable and intersite dependencies are induced by the strong effect of common HCIs. The flexibility of the framework is illustrated with a case study in Southeast Australia aimed at modeling "hot‐and‐dry" summer conditions. It involves three physical variables (streamflow, precipitation, and temperature) measured on three distinct station networks, with varying data availability and representing hundreds of sites in total. The HCI model delivers reliable and sharp time‐varying distributions for individual variables and sites. In addition, it adequately reproduces intervariable and intersite dependencies, whereas a corresponding SCI model (where hidden climate indices are replaced with standard ones) strongly underestimates them. It is finally suggested that HCI models may be used as downscaling tools to estimate the joint distribution of several variables at many stations from climate models or reanalyzes. Plain Language Summary: The management of hydroclimatic hazards such as droughts and heatwaves relies on the estimation of probabilities of occurrence for extreme events. Standard approaches are available for this task when one given hazard is studied at one particular location. However, this is often not sufficient. For instance, the impact of droughts or heatwaves strongly depends on their spatial extent, which requires analyzing them over many sites. It is also useful to analyze droughts and heatwaves together rather than separately, because their joint occurrence creates favorable conditions for other hazards such as bushfires to occur. In this paper, we propose a methodological framework to analyze in a probabilistic way data sets describing several hazards at many sites over many years. The principle of this approach is to identify unobserved processes called "hidden climate indices" that are pulling the strings that make data vary. This is illustrated with a case study analyzing "hot‐and‐dry" summers in Southeast Australia (https://vimeo.com/600898709). Key Points: We propose a general probabilistic model for describing the space‐time variability of multivariable dataThe model is based on hidden climate indices extracted from the target data, as opposed to predefined standard climate indicesThe model is general and flexible, and can handle a wide range of hydrometeorological data sets [ABSTRACT FROM AUTHOR]

Drought produces cross-system impacts, and these interactions between multiple systems are also referred to as drought propagation. However, the complex natural processes and anthropogenic disturbances lead to the drought propagation process being non-linear and systems feedback, which is still lack of knowledge in large-scale basins. To address these challenges, we propose a hydro-economic coupled model and investigate drought propagation across meteorological-hydrological-agricultural systems. The results from the Lancang-Mekong River Basin show that drought propagates from the meteorological system to the hydrological system and is weakened by the basin buffer and storage capacity. This propagation process shows spatial heterogeneity caused by basin characteristics, highlighting that the upstream (CS location) and downstream (KR and KC locations) are more prone to hydrological drought vulnerability. As drought further propagates to the agricultural system, water abstraction behaviours can alleviate the drought situation, leading to crop yield increases ranging from 4.6% to 39.2% through irrigation pathways. Unfortunately, irrigation behaviour also worsens hydrological drought in a feedback loop, where downstream VT (annual discharge decreases by around 1346 m³/s) shows more intense variation than upstream LP (annual discharge decreases by almost 135 m³/s), illustrating the feedback among multi-systems and accumulation in spatial. Moreover, upstream hydropower and downstream agricultural water use show synergistic relationships, revealing that efficient anthropogenic interventions can positively mitigate the impact of drought on human well-being. This paper provides an in-depth understanding of the complex drought propagation process in nature-human highly coupled Lancang-Mekong, which may help policymakers and basin managers to better cope with drought. [ABSTRACT FROM AUTHOR]

Drought seriously endangers the development of agro‐pastoral ecotone in arid and semi‐arid regions. However, drought evolution characteristics of semi‐arid sandy grassland and its drivers are not well understood in the complex climate change context. Thus, in this paper, the revised standardized precipitation evaporation indices on one‐month (SPEI‐1) and growing‐season (SPEI‐6) scale, flash drought and dry spells (DS) were calculated as drought indicators, and the temporal variabilities and meteorological drivers of drought in Horqin Sandy Land during the growing period (April–September) from 2007 to 2021 were studied. The results showed that SPEI‐1 and SPEI‐6 exhibited negative trends and periodic change. This drought aggravation was manifested in increased grades and numbers of drought months. Flash droughts can occur every month during the growing season. And its occurrence was not only positively correlated with all drought events in frequency but also synchronized in time. The increased number of DS showed an asymmetrical shift towards 7‐day‐and‐longer DS. SPEI sensitivity to precipitation (P) was noticeably higher than to atmospheric evapotranspiration demand (AED) at both monthly and growing season scales. SPEI sensitivity to AED was modulated by P amounts, which was higher during low P period. Apart from the amounts of P and AED, their temporal variability also strongly determined how they affect the drought severity. P was also the main driver for flash drought and long DS, but AED with larger amount and higher variability is the reason for their aggravation. Our results demonstrate the complexity of drought intensification in semi‐arid sandy grasslands and highlight the important role of AED anomalies in it. [ABSTRACT FROM AUTHOR]

This paper shows the changes in water sorptivity (Sw) and hydrophobicity following soil contamination with petroleum hydrocarbons (PHs) under different soil moistures. Laboratory experiments were carried out to verify that contamination with PHs reduces Sw, thus affecting the infiltrability, which in practice influences the field water capacity and the availability of water for plants. Soil water repellency (SWR) was estimated by the repellency index (R) and water drop penetration time (WDPT). The increase in PHs contamination contributed to SWR and caused a significant decrease in Sw. With the decrease in moisture, the water sorptivity of the soil increased, reaching its maximum at 0.12–0.15 cm3 cm−3, which was the threshold value in the case of the analysed soil, and then decreased drastically. The R index and the WDPT revealed a similar trend, inversely related to the level of soil contamination with PHs. The increase in SWR and the accompanying decrease in Sw made the soil less resistant to drought. The total amount of water available to plants in the control soil was 19.04%, whereas contamination with PHs equal to 100 g kg−1 caused a decrease to 6.36%. The almost threefold decrease in the total amount of water has a fundamental influence on increasing the risk of soil drought. The results obtained indicated that the interrelationship presented between the level of contamination with PHs, water sorptivity, SWR and soil moisture are the keys to predicting the environmental effects of contamination with PHs. The obtained results indicate that the undertaken remediation measures aimed at restoring the hydrological function of the soil system should be preceded by an assessment of soil hydrophobicity. [ABSTRACT FROM AUTHOR]

Hydrometeorological droughts are complex hazards expressed through the relative deviation in water availability relative to long‐term average conditions. The development and propagation of drought is governed by hydrological processes at different spatial scales including precipitation, evapotranspiration, overland flow, soil moisture, groundwater storage and discharge. Detailed investigation is thus required to evaluate associated linkages among various types of hydrometeorological drought to understand the likely impacts of climate change on drought characteristics (magnitude, frequency, duration and propagation). This study explores the impact of climate change on hydrometeorological drought for 10 Irish catchments, using standardized drought indices representing different components of the hydrological system. We employ 12 Global Climate Models from the Coupled Model Inter‐comparison Project phase 6 (CMIP6), forced with SSP370 and bias corrected to catchment conditions to force a conceptual hydrological model to generate hydrological projections for each catchment. The results indicate substantial drying during summer with associated increases in summer drought magnitude and frequency. However, simulations show a wide range of change, especially for hydrological drought (discharge and baseflow). Only modest changes in the magnitude and frequency of hydrological drought events were found, with increases in winter and spring precipitation offsetting summer dryness. Similarly, the probability of meteorological drought propagating to hydrological events (Standardized Streamflow Index/Standardized Baseflow Index), shows modest increases under the climate change projections considered. Findings highlight that drought, especially during summer are a critical climate change risk for adaptation. Plain Language Summary: Climate change aggravates the impact of hydrometeorological droughts on water availability and distribution in Ireland. Rainfall, evaporation, overland flow, soil moisture, groundwater storage, and the size and strength of discharges are the main factors that cause drought extent and duration. Therefore, for the sustainable development of ecosystems and water resources in a country, it is a requirement to evaluate associated linkages among various types of hydrometeorological drought to understand the likely impacts of climate change on drought characteristics (magnitude) and propagation. This paper explores the impact of climate change on hydrometeorological drought for 10 Irish catchments. The findings indicate significant summer drying, as well as increases in the magnitude and frequency of summer droughts. The probability of meteorological drought propagating to hydrological events, shows modest increases under the climate change projections considered. Drought, particularly during the summer, is a critical climate change risk for adaptation, according to the findings. Key Points: Changes in hydrometeorological drought characteristics under changing climate conditions were estimated; and the results indicate substantial drying during summer with associated increases in summer drought magnitude and frequencyIncreases in winter and spring precipitation result in a decrease in the frequency and magnitude of drought events outside summer and are critical for maintaining baseflow during summer. This also raises the risk of extreme droughts for a dry winter/springThe probability of drought propagation from meteorological to hydrological events increases for the 2050s but decreases for the end of century, highlighting the importance of increases in winter and spring precipitation to drought risk [ABSTRACT FROM AUTHOR]

The detailed study of diatom laminations conducted by means of backscattered electron imaging serves as tool to unravel details of past ocean dynamics. In this paper we apply this method to the analysis of the diatomites of Cerro Los Quesos, Upper Miocene Pisco Fm, Peru. Numerous studies have been conducted on the Pisco Fm; however, a focus on its paleoceanographic significance is still lacking. In this work, we provide information on the oceanographic setting in the area at the time of diatomites deposition. The high abundance of deep‐living Coscinodiscus laminae, proceeded by either a mixed lamina or a terrigenous one, let us hypothesize a deep position of the thermocline during the deposition of the Pisco diatomites; together with the scarcity of Chaetoceros Hyalochaete spp. resting spores, this evidence confutes the belief that equals high biogenic silica content in marine sediments with enhanced upwelling. Conversely, the depositional setting of the Pisco Fm diatomites is more similar to what is known as "permanent El Niño" (or "El Padre") state, meaning a constant weakened upwelling (or upwelling of nutrients‐poor waters). Climate modeling warns that an increase in atmospheric CO2 may lead to this mean state in the near future. Thanks to this study we also obtained refined information on the diatomites sedimentations rates. The comparison of the Pisco diatomites sedimentation rates with those of Quaternary diatomites gave strength to the hypothesis that the formation of the vertebrate Lagerstätte may have been enhanced, among others, by the so‐called "impact‐burial" mechanism. Plain Language Summary: Some sedimentary rocks are formed by the remains of small organisms. This is the case of diatoms, microscopic algae with a siliceous exoskeleton. As we know the ecological conditions of the modern oceans in which different diatom species live, when we found them in sedimentary rocks, we can infer the ecological conditions of the oceans millions of years ago. Here, we present the species that we found in some Peruvian rocks, the so‐called Pisco Formation, which dates back to 7/6 Million of years ago. Different species are preserved in these rocks in the same order in which they bloomed, so that we can identify small "laminae" (horizontal strips in the rock with thicknesses smaller than 1 mm) for each blooming season. The species that we recognize are those that today bloom during "El‐Niño," a climatic warm condition that causes loss of large fishery stocks, inundations and droughts. This small finding helps us hypothesize how climate may evolve if the Earth's temperatures keep on rising. Also, the Pisco formation is famous because of their huge content of fossil whales and dolphins, thus the study of this rock helps us understand how these large mammals got preserved trough millions of years. Key Points: Laminae of the Upper Miocene diatomaceous Pisco Formation reveal that the fall dump mechanism regulated marine export productionThe predominance of fall dump over upwelling implies a drop of the temperature gradient between the Western and Eastern PacificEvidences highlight a need of caution when using biogenic silica as a proxy for paleo upwelling [ABSTRACT FROM AUTHOR]

Arid and semiarid areas generally face problems of natural resource degradation. In this paper, two indicators are proposed to characterize the utilization of rainwater: rainwater resource utilization quantity (RRU, mm) and rainwater resource utilization rate (RRUR, dimensionless ratio). A spatiotemporal assessment model (rainwater utilization assessment [RUA] model) for the RRUR and its influencing factors is constructed. The RUA model is based on Soil and Water Assessment Tool and Geographically Temporal Weighted Regression. The Zuli River Basin, located on the Loess Plateau in China, was selected as the study basin. The results show that the annual averages of the RRU and RRUR are 164 mm and 0.44, respectively, in the study basin. The RRU ranged from 71.4 to 243.2 mm, and the RRUR ranged from 0.32 to 0.53 during the evaluation period. Eight explanatory variables were selected, of which the leaf area index (LAI) and rainfall had a significant positive effect on RRUR, but there was spatial and temporal variability in the effects. The forest rehabilitation and crop rotations that can increase the LAI can effectively increase the RRUR, which increased by 0.10 and 0.11, respectively, and the increase in RRU was at least 36.42 mm, with a water volume of 3.85 × 108 m3. The impact of grassland rehabilitation and parallel terracing on the RRUR was small. We found that there is an interval effect and a threshold effect on rainfall utilization in the basin. The interval effect causes the RRUR to fluctuate within a certain range for rainfall intervals of 300–400 or 400–500 mm (Zuli River Basin). Threshold effects can guide the determination of the potential for rainwater utilization in different areas to ensure that the RRUR can be effectively enhanced with management measures. Recommendations for Resource ManagersWe have constructed an assessment model of rainwater resource utilization (RRU) and influencing factors.We have proposed two evaluation indices based on water balance, namely, the RRU quantity and rainwater resource utilization rate (RRUR).The leaf area index of vegetation is the most important influence on rainwater utilization, and the more severe the drought is, the more effective the regulation of water cycle processes by vegetation.The interval effect causes uncertainty in the RRUR for a certain interval of rainfall, with the RRUR fluctuating within a defined range.The threshold effect can guide us in determining the potential for rainwater utilization, and areas where the current RRUR is below the threshold can take management measures to ensure that the RRUR can be effectively increased. [ABSTRACT FROM AUTHOR]

Recovering additional historical weather observations from known archival sources will improve the understanding of how the climate is changing and enable detailed examination of unusual events within the historical record. The UK National Meteorological Archive recently scanned more than 66,000 paper sheets containing 5.28 million hand‐written monthly rainfall observations taken across the UK and Ireland between 1677 and 1960. Only a small fraction of these observations were previously digitally available for climate scientists to analyse. More than 16,000 volunteer citizen scientists completed the transcription of these sheets of observations during early 2020 using the RainfallRescue.org website, built using the Zooniverse platform. A total of 3.34 million observations from more than 6000 locations have so far been quality controlled and made openly available. This has increased the total number of monthly rainfall observations that are available for this time period and region by a factor of six. The newly rescued observations will enable longer and much improved reconstructions of past variations in rainfall across the British and Irish Isles, including for periods of significant flooding and drought. Specifically, this data should allow the official gridded monthly rainfall reconstructions for the UK to be extended back to 1836, and even earlier for some regions. [ABSTRACT FROM AUTHOR]

Analyzing the spatiotemporal characteristics and evolution of meteorological and hydrological droughts can reproduce the process of drought propagation, which helps reduce the impact of droughts and improve water resources management. While emerging studies have attempted to build drought severity index based on the cutting‐edge space geodetic observations, few have focused the propagation characteristics of meteorological to hydrological drought using geodetic data. In this paper, using global navigation satellite systems (GNSS) observations together with precipitation data, we systematically investigated drought propagation in the Yunnan province, Southwest China. We first identified seven meteorological and seven hydrological droughts in Yunnan from January 2011 to May 2021, and the meteorological drought was mainly concentrated in northern Yunnan lasting for 1–11 months. By contrast, hydrological droughts were more severe and larger than meteorological droughts, lasting for 2–16 months. The drought propagation time was 2–7 months, short in the southwest but long in the northeast. Water vapor, precipitation, and water storage demonstrated a spatiotemporal pattern of uneven distribution, with the red river fault (RRF) as the boundary, and their phase difference also presented notable regional differences, indicating that the RRF not only influences spatial variation of water resources but also affects drought propagation. Plain Language Summary: The dense global navigation satellite system (GNSS) network has become a powerful tool for monitoring atmospheric water vapor and terrestrial water storage. By analyzing the evolution and spatiotemporal patterns of meteorological and hydrological droughts through the GNSS‐based drought monitoring method, we investigated the propagation characteristics from meteorological to hydrological droughts and potential influencing factors. Our results suggest that the Yunnan province in China has experienced serious meteorological and hydrological droughts from January 2011 to May 2021, and hydrological drought was more severe than meteorological drought. The meteorological drought was mainly responsible for the hydrological drought, and the drought propagation time was 2–7 months. Furthermore, the red river fault not only influences the spatial variation of water resources but also affects drought propagation. Key Points: The global navigation satellite system was first used to study meteorological to hydrological propagation in YunnanHydrological drought was more severe than meteorological drought and the drought propagation time was 2–7 monthsThe red river fault not only influences spatial variation of water resources but also affects drought propagation [ABSTRACT FROM AUTHOR]

Water conservation in California has been a major subject of concern for agencies in their efforts to satisfy their residential demand while coping with frequent shortfalls, especially in periods of drought. During the 2012–2016 severe drought in California, the state enacted a conservation mandate that imposed specific conservation targets of 4% up to 36% for water utilities. While the utilities met those targets in 2015, water use, on average, has slowly crept up or rebounded subsequently, although not to pre‐drought levels. Understanding the manner and degree to which water use rebounds can be critically important for water utilities in their planning and investment decisions. Using a unique panel dataset on single‐family residential water use by nearly 20,000 customers of a Northern California water agency from 2013 to 2019, this paper explores the magnitude and character of the rebound effect that occurred after the cessation of a statewide conservation mandate that was imposed on water use in response a severe drought enveloping California from 2014 through 2016. Our results suggest the presence of a significant rebound in water use—of approximately 9% on average—after the conservation mandate ended. Yet, and novel to our research, we find significant heterogeneity in the rebound effects across seasons and water users, with a greater rebound in the warm season months relative to other months and among lower water use households relative to higher water use households. Our results also suggest a significant shift in water use to earlier periods of the day once the mandate was lifted. Understanding the magnitude and variation in rebound effects both temporally and across different types of water users can be useful to water agencies in their efforts to make informed decisions surrounding investments, management, and messaging in response to drought, conservation, and water scarcity. Plain Language Summary: Given the prominence of demand‐side management in the water utilities toolbox for addressing increasing water shortages driven by drought and climate change, understanding how water use changes during a drought along with how and to what extent it increases, or "rebounds," afterward can be useful if not necessary in making informed policy decisions and cost‐effective investments. This research develops a unique data set consisting of household‐level daily and hourly water use by nearly 19,500 residential accounts from a California water utility from 2013 through 2019. It explores how water use changed during and post‐drought relative to pre‐drought levels. During this period, California entered a significant drought. Its governor requested a voluntary cutback, imposed a conservation mandate, and implemented a self‐certification requirement lasting until the drought eased. We find that residential water use decreased by 26% during the conservation mandate relative to pre‐drought levels but rebounded by approximately 9% post‐mandate. The "rebound" effect varied across the season (greatest in summer months) and water user type (lower‐end water users showed a larger percentage rebound than higher‐end water users). Our results suggest that due to the mandate, the peak hour water consumption shifted to the earlier hours of the day. Key Points: Our results suggest that the 2015 California water mandate resulted in temporary and permanent reductions in water useRebound effects are more prevalent in the warm season than in other months and for lower‐end water users than high‐end water usersOur results also show that, due to the mandate, the peak hour water consumption shifted to the earlier hours of the day [ABSTRACT FROM AUTHOR]

The article reports on the announcement made by the publication entitled "Natural Resources Forum," a quarterly journal issued by the United Nations Department of Economic and Social Affairs (DESA) and published by Blackwell, urging interested parties to submit papers in the U.S. The publication calls interested parties to submit papers for a special series over the 2007-2009 period on themes to be considered by the United Nations Commission on Sustainable Development on its 16th and 17th sessions. Interested parties who wish to submit articles should follow the criteria set by the publication. Presented are the details of the deadline for submission of entries and the rules in writing the abstract.

According to the current Intergovernmental Panel of Climate Change report, climate change will increase the probability of occurrence of droughts in some areas. Recent contributions at the international level indicate that trade is expected to act as an efficient tool to mitigate the adverse effect of future climate conditions on agriculture. However, no contribution has focused on the similar capacity of trade within any country yet. The U.S. is an obvious choice given that many climate impact studies focus on its agriculture and around 90% of the U.S. crop trade is domestic. Combining a recent state‐to‐state trade flow dataset with detailed drought records at a fine spatial and temporal resolution, this paper highlights first that trade increases as the destination state experiences more drought and inversely in the origin state. As a result, crop growers' profits depend on both local and trade partners' weather conditions. Projections based on future weather data convert the crop grower's expected loss without trade into expected profit. As such, this paper challenges the estimates of the current climate impact literature and concludes that trade is expected to act as a $14.5 billion mitigation tool in the near future. [ABSTRACT FROM AUTHOR]

Tree diversity and species identity are known to play an important role in modulating forest productivity and its capacity to buffer the effects of climatic events. The FunDivEurope exploratory platform allowed us to analyse this modulating effect in a medium‐term time span, after an abrupt rise to a new stable level of the average summer temperature of ca 2°C, in Mediterranean forests in central Italy. This paper aims to answer the following questions: 1) did increasing temperature and drought events affect the growth of thermophilous deciduous forests? 2) Was this effect buffered in mixed stands compared to monocultures? 3) Did co‐occurring tree species with different ecological characteristics, from more mesophilous to more xerophilous, have different responses? In 2012 and 2017, wood cores were collected from 659 trees in 36 plots representative of thermophilous deciduous forests. The selected tree species were Castanea sativa, Ostrya carpinifolia, Quercus cerris, Quercus ilex and Quercus petraea. In the sampling plots, they were present in pure stands and mixtures from two to four species. After measuring annual rings on cores, chronologies of basal area increment were built, and inventory data were used to estimate tree growth. Results showed a strong reduction of growth, lasting at least 18 years, after the temperature rise. Tree diversity significantly reduced the growth drop after the sudden and stable rise in summer average temperature. Tree mixture effect on growth stability appeared to be dependent on the tree species present in the mixture. Temperature rise and associated drought events, even without changes in rainfall, are one of the main challenges that European forests will face in the current scenarios of climate change. Tree diversity can buffer the effects of climate change over periods of at least 15 years and should be considered in forest management plans. [ABSTRACT FROM AUTHOR]

This exploratory study proposes an original intra‐life history investigation through sequential analysis of the isotopic composition of carbon, nitrogen, and sulfur (CNS) on both primary and secondary dentin of a tooth (M1). We focus on an elderly woman from Longobard Italy (6th to 8th c. CE), who showed an unprecedented case of cranial surgery, presented in a companion paper by Micarelli and colleagues. Sequential stable CNS isotope composition of first molar dentin collagen allows us to infer diet, mobility, health, and physiological stress between approximately 3 months after birth to 9.5 years old (primary dentin) and between early adulthood until death (secondary dentin). Isotopic results on primary dentin highlight the following: (i) a long weaning period (ending at approximately 4 years), followed by (ii) a specific diet, including the contribution of C4 crops in early childhood (approximately 5.5 years), possibly concomitant with mobility. While secondary dentin shows a generally homogeneous diet during adulthood, the longitudinal analysis provided information on specific stresses that likely occurred in periods of difficult health conditions. This work emphasizes the importance of measuring complete dentin sequences (including secondary when present) for isotopic analysis to broaden intra‐life histories in ancient populations. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive picture of extreme precipitation across Nepal from 1976 to 2015 based on high‐quality daily precipitation observations from 28 precipitation stations spatially distributed across the country. We computed 11 extreme precipitation indices. The selected indices allow the analysis of extreme events (such as flood/inundation) related to heavy precipitation and evaluate the linkage with indications of agricultural production and drought (such as consecutive dry and wet days). Using a simple daily intensity index (SDII) and the number of days with daily precipitation ≥10 mm (R10), along with the total amount of annual precipitation (PRCPTOT), we summarized the distribution of the wet periods of the year at different locations. We divided the study period into two halves (T1: 1976–1995 and T2: 1996–2015) to examine the temporal mean, trends, and their shift. We emphasized the changes in those indices between these two periods across the country. Our results show that although the amount of precipitation (in terms of PRCPTOT and SDII) did not change significantly between the two periods (i.e., T1 and T2), there exists a clearly increasing trend of extreme precipitation indices in T2 compared to T1. In addition, the consecutive dry days show the rising tendency of elongated dry spells that can adversely affect plant/crop growth in the future. Our study recommends the need for effective management of both precipitation extremes (i.e., drier and wetter), for instance, by introducing irrigation facilities and flood mitigation measures. Plain Language Summary: We computed different precipitation indices using daily data from 28 precipitation stations spatially distributed across Nepal to obtain a clear picture of extreme precipitation from 1976 to 2015. We divided the study period into two halves of 20 years each. This study emphasizes the changes in magnitudes and trends of extreme precipitation between the two periods. Overall, we find that heavy precipitation indices increased significantly in the later period. Notably, dry spells (i.e., no rainfall) for consecutive days showed a remarkably increasing trend. Our results indicate the need for mitigation of this extreme precipitation to prevent both floods and drought. Key Points: We divide the study period (1976–2015) into two halves to analyze precipitation patterns and their shiftWe emphasize changes in the precipitation indices across the country between the two periodsWe find a clearly increasing trend of extreme precipitation indices in the recent period when compared to the earlier one [ABSTRACT FROM AUTHOR]

1. Adults of Aquarius paludum inhabit both temporary and permanent water surfaces; Gerris latiabdominis lives only in temporary habitats. To clarify whether adults of both species stay in position or fly when habitats dry up, overwintered adults of A. paludum and G. latiabdominis collected in spring were reared under one of the following four conditions: (A) on water with sufficient food, (B) on water, starved, (C) on wet paper with sufficient food, (D) on wet paper, starved. All rearings were at LD 15.5:8.5 h, 20 ± 2 °C, resembling natural conditions for April to June. 2. Females of A. paludum in group C had lower fecundity than the control group A and some stopped laying eggs. When a water surface was restored, females that had entered reproductive diapause began to lay eggs again. In contrast, females of G. latiabdominis continued to lay eggs even when reared on damp paper. 3. Adults of A. paludum lived longer and adopted diapause posture with high frequency when starved and reared without a water surface. There were, however, no significant differences in the longevity or in the number of adults showing diapause posture between groups A and D of G. latiabdominis. 4. Females of A. paludum collected in the middle of May had more mature oocytes (mean: 20.8) than females of G. latiabdominis (mean: 8.0), and most had histolysed their indirect flight muscles; most females of G. latiabdominis had retained their flight muscles and flew readily. 5. When water surfaces dry, with food shortage, adults of A. paludum may survive in place for a relatively long time until the water surface returns. Adults of G. latiabdominis may fly to other water surfaces and reproduce without delay. [ABSTRACT FROM AUTHOR]

The accelerating pace of climate change has led to unprecedented shifts in surface temperature and precipitation patterns worldwide, with African savannas being among the most vulnerable regions. Understanding the impacts of these extreme changes on ecosystem health, functioning and stability is crucial. This paper focuses on the detection of breakpoints, indicative of shifts in ecosystem functioning, while also determining relevant ecosystem characteristics and climatic drivers that increase susceptibility to these shifts within the semi‐arid to arid savanna biome. Utilising a remote sensing change detection approach and rain use efficiency (RaUE) as a proxy for ecosystem functioning, spatial and temporal patterns of breakpoints in the savanna biome were identified. We then employed a novel combination of survival analysis and remote sensing time series analysis to compare ecosystem characteristics and climatic drivers in areas experiencing breakpoints versus areas with stable ecosystem functioning. Key ecosystem factors increasing savanna breakpoint susceptibility were identified, namely higher soil sand content, flatter terrain and a cooler long‐term mean temperature during the wet summer season. Moreover, the primary driver of changes in ecosystem functioning in arid savannas, as opposed to wetter tropical savannas, was found to be the increased frequency and severity of rainfall events, rather than drought pressures. This research highlights the importance of incorporating wetness severity metrics alongside drought metrics to comprehensively understand climate–ecosystem interactions leading to abrupt shifts in ecosystem functioning in arid biomes. The findings also emphasise the need to consider the underlying ecosystem characteristics, including soil, topography and vegetation composition, in assessing ecosystem responses to climate change. While this research primarily concentrated on the southern African savanna as a case study, the methodological robustness of this approach enables its application to diverse arid and semi‐arid biomes for the assessment of climate–ecosystem interactions that contribute to abrupt shifts. [ABSTRACT FROM AUTHOR]

Climate change and its consequences pose significant economic and social challenges around the world. Droughts have frequently afflicted South Africa, with the most recent severe drought occurring in 2015/2016. However, there has been little empirical research estimating the impact of climate‐related shocks on individual well‐being in South Africa. In this paper, we investigate the impact of the 2015/2016 drought on individual welfare. We also examine whether access to assets helps to mitigate the negative effects of climate change‐related shocks on individual welfare. For estimating the impact of droughts on individual welfare outcomes, weather data are combined with individual panel data from the National Income Dynamics Study dataset. We use weather data from meteorological satellites to measure the extent of droughts across the country, and we measure individual welfare using real per capita consumption expenditure. Our estimation results show that the 2015/2016 drought had no significant effect on real per capita consumption expenditure in South Africa. We hypothesise that this is due in part to the structure of the labour market, with few people relying on subsistence farming, combined with social grants and remittances being the primary source of income for people at the bottom of the consumption distribution. Using anthropometric measurements as an alternative welfare indicator, we find that children living in drought‐affected areas had lower weight‐for‐height measurements than those living in areas not affected by the drought. The findings imply that when food prices increased as a result of the drought, households may have chosen welfare‐costly coping techniques such as reducing the quantity and quality of food consumed while keeping overall expenditure the same. [ABSTRACT FROM AUTHOR]

This paper analyses extreme meteorological droughts in the territory of the Pannonian Basin in central and southeastern Europe. Droughts are treated from an agricultural perspective as periods of consecutive days with very little or no rainfall at all. By using data from the historical period 1981–2010, time intervals longer than 20 days with less than 3 mm per day during the growing season April–September are examined to determine theoretical and empirical distributions of their number and durations. Related discrete stochastic process of extremes is analysed by the Zelenhasic–Todorovic (ZT) method, successfully applied in hydrology and meteorology (e.g., peak flows, low flows, meteorological droughts, etc.). The method is applied to 52 locations across Pannonia Basin. At each location, the Poisson distribution is determined for the number of droughts, exponential distribution for the duration of droughts, and double exponential distribution for the duration of the (annually) longest droughts. To validate the quality of modelling and the results obtained, standard statistical goodness of fit tests are used. Historical data from the period 1981–2010 indicate that the central and northern part of Hungary and the entire territory of Vojvodina Province in the north of Serbia experienced the longest droughts, on average 55–60 days. In statistical terms, across Pannonia Basin once in 100 years drought may occur with an average duration of 56 days. Theoretically longest 100‐year droughts could be expected in the northern part of Hungary (up to 70 days), the eastern part of Romania (up to 68 days), and Serbia (up to 69 days). The 2‐year droughts are on the average duration of 3 weeks. Generated maps of the longest droughts in the basin may help to reduce agricultural risks due to global warming and other negative impacts of climate change. [ABSTRACT FROM AUTHOR]

El Niño Southern Oscillation (ENSO) events yield precipitation deficits and ensuing droughts, often damaging regional forests, in many parts of the world. The relative roles of ENSO, other natural climate changes, and anthropogenic factors on the forest clearing of Easter Island over the last millennium are still debated. Here, we analyze Easter Island precipitation changes using in situ, satellite‐derived and reanalysis products spanning the last 4–7 decades, and 46 monthly 156‐year‐long (1850–2014) simulations derived from 25 CMIP5 and 21 CMIP6 (Coupled Model Intercomparison Project phases 5 and 6) General Circulation Models. Our analysis shows that La Niña events, the cold phases of ENSO, cause precipitation deficits of −0.2 to −0.3 standard deviation (relative to long‐term mean) in all analyzed data types. ENSO‐like events are further examined over the last millennium (850–1981). A new multiproxy reconstruction of the NINO3.4 index based on proxy records from the Past Global Changes 2k database and Random Forest method is produced. Our reconstruction reveals unusual high recurrences of La Niña‐like situations during the fifteenth to seventeenth centuries, which likely induced significant precipitation deficits on the island. These situations are compared to published vegetation reconstructions based on pollen analyses derived from sedimentary cores collected in three island sites. We conclude the environmental consequences of cumulative precipitation deficits over long‐lasting La Niña‐like situations reconstructed here over the fifteenth to seventeenth centuries were likely favoring drought and forest flammability. La Niña events should be better accounted for among the causes of forest clearing on Easter Island. Plain Language Summary: Easter Island is a small remote island located in the south‐eastern Pacific Ocean. It is home of several scientific enigmas: the origin of early settlements, the construction of the giant moai statues, and causes of the forest clearing. Was the forest clearing abrupt, gradual, homogenous in time and space, human‐induced (in line with the ecocide hypothesis), or related to natural climate variability? The question we address in this paper is related to the natural climate variability hypothesis, focusing on the El Niño Southern Oscillation (ENSO) phenomenon. We analyze ENSO effects on Easter Island precipitation from three instrumental (1950–2021) and 42‐simulation data sets (1850–2014). Our analysis shows the cold phases of ENSO, also known as La Niña, cause significant precipitation deficits over the island in all analyzed data types. Then, we provide a new up‐to‐date reconstruction of ENSO over 850–1981. We found a large number of La Niña‐like situations during the fifteenth‐seventeenth centuries. These situations are compared to vegetation reconstructions derived from sedimentary cores collected in three island sites. We conclude that the environmental consequences of cumulative precipitation deficits during long‐lasting La Niña‐like situations could be an additional cause of the forest clearing of Easter Island. Key Points: Analysis of independent data sets shows precipitation deficits over Eastern Island during La Niña events over the period 1850–2021A new reconstruction of El Niño Southern Oscillation episodes reveals a large number of La Niña‐like situations during the fifteenth to seventeenth centuriesHigh repetitions of La Niña events, favoring drought, likely played a role in the forest clearing of the island, on top of other stressors [ABSTRACT FROM AUTHOR]

Managers typically estimate wildlife abundance using surveys within a timeframe that favors increased detectability; however, the ability to account for probabilities of inclusion, detection, and/or presence within a given sampling area is often limited. Cranes provide a good opportunity to research count accuracy because they are large, conspicuous, and often congregate during part of the year, typically on staging areas (i.e., fall and spring) or on wintering grounds. The objectives of this paper are twofold: (1) to evaluate how environmental factors influence crane movement in and out of crane survey areas to identify the best window of availability for annual survey counts; and (2) to evaluate environmental factors that influence overall crane survey counts from year to year. For Objective 1, a generalized linear mixed model was selected to model the probability of crane presence within survey areas using GPS transmitter data. A binary response variable representing crane movement within and outside formal survey areas was used as the dependent variable to investigate environmental covariates that influence movement into survey areas. Probability of crane presence was explained by seven covariates plus a quadratic term for Julian day number. Interactions between Palmer drought severity index (PDSI) and normalized difference vegetation index supported higher probability of crane presence in survey areas during times of drought. Probability of crane presence increased throughout the entire study period (May–October), suggesting that formal surveys in September could be augmented or replaced by surveys in October. For Objective 2, a negative binomial model with linear parameterization was selected to model crane counts using census data compiled from 1995 to 2019. Covariates were acquired at the watershed scale using Hydrologic Unit Code 6 boundaries. Of the 17 covariates investigated, we found that 18‐month precipitation (PPTgss), PDSI, and minimum temperature (Tempmin) explained most of the variability in crane census counts. High PPTgss (antecedent moisture), low PDSI (drought conditions), and low Tempmin (cold extremes) result in higher annual crane counts. The ability to link ecological processes to wildlife movement and population abundance both locally and at landscape scales has long‐ranging implications on resource projections, conservation, and the ability to deploy adaptive management. [ABSTRACT FROM AUTHOR]