PLOS ONE: [sortOrder=DATE_NEWEST_FIRST, sort=Date, newest first, q=subject:"Drought"]PLOShttps://journals.plos.org/plosone/webmaster@plos.orgaccelerating the publication of peer-reviewed sciencehttps://journals.plos.org/plosone/search/feed/atom?sortOrder=DATE_NEWEST_FIRST&unformattedQuery=subject:%22Drought%22&sort=Date,+newest+firstAll PLOS articles are Open Access.https://journals.plos.org/plosone/resource/img/favicon.icohttps://journals.plos.org/plosone/resource/img/favicon.ico2024-03-28T11:58:05ZAn invisible water surcharge: Climate warming increases crop water demand in the San Joaquin Valley’s groundwater-dependent irrigated agricultureKelley MoyersJohn T. AbatzoglouAlvar Escriva-BouJosué Medellín-AzuaraJoshua H. Viers10.1371/journal.pwat.00001842024-03-13T14:00:00Z2024-03-13T14:00:00Z<p>by Kelley Moyers, John T. Abatzoglou, Alvar Escriva-Bou, Josué Medellín-Azuara, Joshua H. Viers</p>
California’s bountiful San Joaquin Valley (SJV), a critical region for global fruit and nut production, has withstood two severe, multi-year droughts in the past decade, exacerbated by record-breaking high temperature and evaporative demand. We employed climate data and crop coefficients to estimate the crop water demand in the SJV over the past forty years. Our approach, using crop coefficients for Penman-Montieth modeled evapotranspiration, focused on the climate effects on crop water demand, avoiding the confounding factors of changing land use and management practices that are present in actual evapotranspiration. We demonstrate that increases in crop water demand explain half of the cumulative deficits of the agricultural water balance since 1980, exacerbating water reliance on depleting groundwater supplies and fluctuating surface water imports. We call this phenomenon of climate-induced increased crop water demand an <i>invisible water surcharge</i>. We found that in the past decade, this <i>invisible water surcharge</i> on agriculture has increased the crop water demand in the SJV by 4.4% with respect to the 1980–2011 timeframe—more than 800 GL per year, a volume as large as a major reservoir in the SJV. Despite potential agronomic adaptation and crop response to climate warming, increased crop water demand adds a stressor to the sustainability of the global fruit and nut supply and calls for changes in management and policies to consider the shifting hydroclimate.Photosynthetic gas exchange, plant water relations and osmotic adjustment of three tropical perennials during drought stress and re-wateringJie HeKlaudia NgLin QinYuanjie ShenHarianto RahardjoChien Looi WangHuiling KewYong Chuan ChuaChoon Hock PohSubhadip Ghosh10.1371/journal.pone.02989082024-02-28T14:00:00Z2024-02-28T14:00:00Z<p>by Jie He, Klaudia Ng, Lin Qin, Yuanjie Shen, Harianto Rahardjo, Chien Looi Wang, Huiling Kew, Yong Chuan Chua, Choon Hock Poh, Subhadip Ghosh</p>
Planting vegetation on slopes is an effective way of improving slope stability while enhancing the aesthetic appearance of the landscape. However, plants growing on slopes are susceptible to natural drought stress (DS) conditions which commonly lead to water deficit in plant tissues that affect plant health and growth. This study investigated the photosynthetic gas exchange, plant water status and proline accumulation of three tropical perennials namely <i>Clerodendrum paniculatum</i>, <i>Ipomoea pes-caprae</i> and <i>Melastoma malabathricum</i> after being subjected to DS and re-watering (RW). During DS, there was a significant decrease in light-saturated photosynthetic CO<sub>2</sub> assimilation rate (<i>A</i><sub>sat</sub>), stomatal conductance (<i>g</i><sub>s sat</sub>), and transpiration rate (<i>T</i><sub>r</sub>) for all three plant species. Leaf relative water content, shoot water potential, and leaf, stem and root water content also declined during DS. Proline concentration increased for all three species during DS, reaching especially high levels for <i>C</i>. <i>paniculatum</i>, suggesting that it heavily relies on the accumulation of proline to cope with DS. Most of the parameters recovered almost completely to levels similar to well-watered plants after RW, apart from <i>M</i>. <i>malabathricum</i>. Strong linear correlations were found between <i>A</i><sub>sat</sub> and <i>g</i><sub>s sat</sub> and between <i>g</i><sub>s sat</sub> and <i>T</i><sub>r</sub>. Ultimately, <i>C</i>. <i>paniculatum</i> and <i>I</i>. <i>pes-caprae</i> had better drought tolerance than <i>M</i>. <i>malabathricum</i>.Irish surface water response to the 2018 droughtDevin F. SmithW. Berry LyonsTiernan HenryRaymond FlynnAnne E. Carey10.1371/journal.pwat.00001972023-11-14T14:00:00Z2023-11-14T14:00:00Z<p>by Devin F. Smith, W. Berry Lyons, Tiernan Henry, Raymond Flynn, Anne E. Carey</p>
Intense weather events are projected to increase as a consequence of climate change. The summer 2018 drought in Europe impacted human health, ecosystems, and economic prosperity. Even locations with an abundance of fresh water, like Ireland, faced water restrictions due to depleted supplies. To characterize the effect of the 2018 drought on Irish rivers, we collected surface water samples from rivers across the island at the drought onset and termination. We analyzed samples for stable water isotopes δ<sup>18</sup>O and δ<sup>2</sup>H and calculated the fraction of evaporation from river groundwater and precipitation inflow (E/I) of rivers. We extended river δ<sup>18</sup>O and δ<sup>2</sup>H analysis to 2020 for rivers in two catchments, Corrib and Shannon, to investigate how Irish river systems respond to high precipitation events, and the role of loughs (lakes) in the system. River δ<sup>18</sup>O and δ<sup>2</sup>H values showed progressive depletion from west to east in response to precipitation depletion from airmasses arriving off the Atlantic Ocean. From onset to termination of the 2018 drought, river δ<sup>18</sup>O and δ<sup>2</sup>H values were enriched and the calculated E/I value increased for most rivers. D-excess were negatively correlated with E/I value, providing support for E/I calculations. Extended analysis of loughs along the Corrib and Shannon river systems showed that lough Corrib consistently induced isotopic enrichment, while loughs in the Shannon catchment inconsistently caused isotopic enrichment. Both systems exert control over river isotopic composition in hydrologic extremes. Findings promote additional research in hydrologic patterns in response to increasing frequency of floods and droughts.Drought trends projection under future climate change scenarios for Iran regionMaryam BayatavrkeshiMonzur Alam ImteazOzgur KisiMohammad FarahaniMohammad GhabaeiAhmed Mohammed Sami Al-JanabiBassim Mohammed HashimBaqer Al-RamadanZaher Mundher Yaseen10.1371/journal.pone.02906982023-11-09T14:00:00Z2023-11-09T14:00:00Z<p>by Maryam Bayatavrkeshi, Monzur Alam Imteaz, Ozgur Kisi, Mohammad Farahani, Mohammad Ghabaei, Ahmed Mohammed Sami Al-Janabi, Bassim Mohammed Hashim, Baqer Al-Ramadan, Zaher Mundher Yaseen</p>
The study highlights the potential characteristics of droughts under future climate change scenarios. For this purpose, the changes in Standardized Precipitation Evapotranspiration Index (SPEI) under the A1B, A2, and B1 climate change scenarios in Iran were assessed. The daily weather data of 30 synoptic stations from 1992 to 2010 were analyzed. The HadCM3 statistical model in the LARS-WG was used to predict the future weather conditions between 2011 and 2112, for three 34-year periods; 2011–2045, 2046–2079, and 2080–2112. In regard to the findings, the upward trend of the potential evapotranspiration in parallel with the downward trend of the precipitation in the next 102 years in three scenarios to the base timescale was transparent. The frequency of the SPEI in the base month indicated that 17.02% of the studied months faced the drought. Considering the scenarios of climate change for three 34-year periods (i.e., 2011–2045, 2046–2079, and 2080–2112) the average percentages of potential drought occurrences for all the stations in the next three periods will be 8.89, 16.58, and 27.27 respectively under the B1 scenario. While the predicted values under the A1B scenario are 7.63, 12.66, and 35.08%respectively. The relevant findings under the A2 scenario are 6.73, 10.16, 40.8%. As a consequence, water shortage would be more serious in the third period of study under all three scenarios. The percentage of drought occurrence in the future years under the A2, B1, and A1B will be 19.23%, 17.74%, and 18.84%, respectively which confirms the worst condition under the A2 scenario. For all stations, the number of months with moderate drought was substantially more than severe and extreme droughts. Considering the A2 scenario as a high emission scenario, the analysis of SPEI frequency illustrated that the proportion of dry periods in regions with humid and cool climate is more than hot and warm climates; however, the duration of dry periods in warmer climates is longer than colder climates. Moreover, the temporal distribution of precipitation and potential evapotranspiration indicated that in a large number of stations, there is a significant difference between them in the middle months of the year, which justifies the importance of prudent water management in warm months.Machine learning models development for accurate multi-months ahead drought forecasting: Case study of the Great Lakes, North AmericaMohammed Majeed HameedSiti Fatin Mohd RazaliWan Hanna Melini Wan MohtarNorinah Abd RahmanZaher Mundher Yaseen10.1371/journal.pone.02908912023-10-31T14:00:00Z2023-10-31T14:00:00Z<p>by Mohammed Majeed Hameed, Siti Fatin Mohd Razali, Wan Hanna Melini Wan Mohtar, Norinah Abd Rahman, Zaher Mundher Yaseen</p>
The Great Lakes are critical freshwater sources, supporting millions of people, agriculture, and ecosystems. However, climate change has worsened droughts, leading to significant economic and social consequences. Accurate multi-month drought forecasting is, therefore, essential for effective water management and mitigating these impacts. This study introduces the Multivariate Standardized Lake Water Level Index (MSWI), a modified drought index that utilizes water level data collected from 1920 to 2020. Four hybrid models are developed: Support Vector Regression with Beluga whale optimization (SVR-BWO), Random Forest with Beluga whale optimization (RF-BWO), Extreme Learning Machine with Beluga whale optimization (ELM-BWO), and Regularized ELM with Beluga whale optimization (RELM-BWO). The models forecast droughts up to six months ahead for Lake Superior and Lake Michigan-Huron. The best-performing model is then selected to forecast droughts for the remaining three lakes, which have not experienced severe droughts in the past 50 years. The results show that incorporating the BWO improves the accuracy of all classical models, particularly in forecasting drought turning and critical points. Among the hybrid models, the RELM-BWO model achieves the highest level of accuracy, surpassing both classical and hybrid models by a significant margin (7.21 to 76.74%). Furthermore, Monte-Carlo simulation is employed to analyze uncertainties and ensure the reliability of the forecasts. Accordingly, the RELM-BWO model reliably forecasts droughts for all lakes, with a lead time ranging from 2 to 6 months. The study’s findings offer valuable insights for policymakers, water managers, and other stakeholders to better prepare drought mitigation strategies.Visitation to national parks in California shows annual and seasonal change during extreme drought and wet yearsJeffrey S. JenkinsJohn T. AbatzoglouEmily J. WilkinsElizabeth E. Perry10.1371/journal.pclm.00002602023-08-09T14:00:00Z2023-08-09T14:00:00Z<p>by Jeffrey S. Jenkins, John T. Abatzoglou, Emily J. Wilkins, Elizabeth E. Perry</p>
This study examines the influence of drought indicators on recreational visitation patterns to National Park Service units in California (USA) from 1980 to 2019. We considered mountain, arid, and coastal park types across a climate gradient where seasonal recreational opportunities are directly or indirectly dependent on water resources. Significant departures from the normal hydroclimate, reflected by drought or unusually wet conditions, can lead visitors to change their behavior, including recreating at a different time or place. Drought conditions can facilitate earlier seasonal access at higher elevation parks, but displace visitors in other seasons and parks. Wetter-than-average conditions can displace visitors due to snowpack or flooding, but also facilitate other activities. We found a decrease in annual visitation at popular mountain parks including Yosemite (-8.6%) and Sequoia and Kings Canyon (-8.2%) during extreme drought years due to lower-than-average attendance in peak summer and fall months. Extreme wet years also had significantly reduced annual visitation in Sequoia and Kings (-8.5%) and Lassen Volcanic (-13.9%) due to declines in spring and summer use as snowpack restricts road access. For arid parks, drought status did not have a statistically significant effect on annual visitation, although extreme drought led to less use during the hottest months of summer at Death Valley, and extreme wet conditions at Pinnacles led to less visitation throughout the year (-16.6%), possibly from impacts to infrastructure associated with flooding. For coastal park units, extreme drought led to year-round higher levels of use at Redwood (+27.7%), which is typically wet, and less year-round use at Channel Islands (-23.6%), which is relatively dry, while extreme wet years led to higher levels of annual use at Channel Islands (+29.4%). Collectively, these results indicate the effect of extreme drought or wet years on park visitation varies by park depending on geography and recreational activities offered.Facing old and new risks in arid environments: The case of pastoral communities in Northern KenyaJanpeter SchillingLuise Werland10.1371/journal.pclm.00002512023-07-13T14:00:00Z2023-07-13T14:00:00Z<p>by Janpeter Schilling, Luise Werland</p>
Pastoralism is an important form of livelihood in Kenya, particularly in northern Kenya. While pastoralists have always faced risks such as political marginalization, harsh climate conditions and violent conflict, pastoral communities are increasingly exposed to new risks such as wildlife conservancies as well as large-scale wind and oil projects. The growing climate security literature has provided some insights into how changing rainfall patterns are affecting pastoralist conflicts, but we know little about the compound nature of multiple risks. This paper seeks to narrow this knowledge gap. It aims to better understand new and old risks and their combined impact on pastoral communities in the counties of Turkana, Samburu and Marsabit. The study is based on a comprehensive and structured review of the scientific literature. The findings show that all pastoral communities in northern Kenya face the old risks while the newer ones are county-specific. In Turkana, potential oil spills threaten land and water resources upon which pastoralist communities depend. In Samburu, wildlife conservancies have changed the land-use system, and in Marsabit a pastoral community is exposed to noise and visible emissions from a wind park. Common to these risks are that they: (1) are caused by top-down governance processes with little to no community involvement; (2) reduce the mobility and access to water and pasture of (some) pastoral communities; (3) change the security situation. A rethinking of wildlife conservancies and energy projects is needed that involves pastoral communities from the outset and makes them the primary beneficiaries of any measure implemented in northern Kenya.Spatio-temporal variability and rainfall trend affects seasonal calendar of maize production in southern central Rift Valley of EthiopiaDaniel MarkosWalelign WorkuGirma Mamo10.1371/journal.pclm.00002182023-06-29T14:00:00Z2023-06-29T14:00:00Z<p>by Daniel Markos, Walelign Worku, Girma Mamo</p>
Understanding rainfall variability is important to establish crop calendar related agronomic decisions. To this end, we defined start and end of seasons, analyzed dry spell and evaluated conditional risks of alternative planting dates using a thirty years daily rainfall data across southern central rift valley of Ethiopia. Results showed that the probability of annual rainfall being greater than 1000 mm was 97, 24, 94, and 61%, in Dilla, Bilate, Shamana, and Hawassa clusters, respectively. The variability of annual total rainfall in the lowland areas of Dilla and Bilate was above 25%, whereas for Shamana and Hawassa was below 20%. Variability of seasonal rainfall during FMAM was 33.7%, which is higher than ONDJ (27.1%) and JJAS (27.9%), which could lead to maize plants suffering moisture stress during FMAM season. The onset of rains had variability of 29.2, 19.5, 17.5 and 26.5%, and also LGP showed variability of 22.8, 22.1, 21.2 and 20.3% in Shamana, Bilate, Hawassa, and Dilla clusters, respectively. Moreover Shamana, Bilate, Hawassa and Dilla clusters are hit by agricultural drought in one out of 2.61, 2.3, 2.5 and 2.5 years, respectively. Model based analysis of conditional risk of farmers planting dates also showed a success rate of less than 10, 7, 40 and 63% for maize variety in Shamana, Bilate, Hawassa and Dilla clusters, respectively. However, the success rate of risk taker farmers’ is higher than anticipated by the model. The farmers who take risk were encouraged in Shamana cluster by local edaphic, physiographic, socioeconomic and climatic differences. Hence, there is a need to seek real time local agro-metrological advisory and follow the necessary tactical and strategic farming decisions. Moreover, there is also a need to incorporate local factors with modern climate models to obtain synchronized calendar estimates.Climate change scenario projections and their implications on food systems in Taita Taveta County, KenyaFrancis Kibagendi NyambarigaAlfred Owuor OpereEvans KituyiDorothy Akinyi Amwata10.1371/journal.pclm.00001142023-06-22T14:00:00Z2023-06-22T14:00:00Z<p>by Francis Kibagendi Nyambariga, Alfred Owuor Opere, Evans Kituyi, Dorothy Akinyi Amwata</p>
This study explored how Taita Taveta County could use the power of climate scenarios in planning agricultural activities on food systems to enhance sustainable food. The study involved the use of climate scenarios to model the past, present and future climate with the view of predicting probable changes in climate and how these changes may impact on food production, transformation and utilization and the ultimate handling of ensuing food wastes to mitigate the looming climate change scenarios. The research was conducted in Taita Taveta County that is characterized into three agro-ecological zones based on altitude and an ensemble of the top two models (ICHEC-EC-EARTH and MPI-M-MPI-ESM-LR) was used to analyse climate projections following RCP4.5 and RCP8.5 pathways. Rainfall and temperature from the Kenya Meteorological Department and supplemented with datasets from Kenya Agricultural and Livestock Research Organization (KALRO), Climate Hazard Group Infrared Precipitation with Stations (CHIRPS) and European Centre for Medium-Range Weather Forecast Reanalysis v5 (ERA5) respectively for the period 1981–2021 were used. The results exhibited occurrences of climate variability and change, and the seasons when the rainfall amounts were highest and lowest. Projected temperatures up to 2065 revealed likelihood of significant future warming and predicted future rainfall variations indicated insignificant increase. The study concluded by predicting a significant rise in temperatures and insignificant increase in rainfall leading to probable decrease in food production. The study recommended adoption climate smart technologies and early warning systems by the communities and policy makers to mainstream climate information in food systems, particularly production, transformation and utilization to enhance efficiency and avoid unnecessary wastage. State and non-state actors and other stakeholders could leverage these results to devise suitable adaptation and mitigation measures in the county.Genome-wide association mapping for component traits of drought tolerance in dry beans (<i>Phaseolus vulgaris</i> L.)Bruce MutariJulia SibiyaAdmire ShayanowakoCharity ChidzangaPrince M. MatovaEdmore Gasura10.1371/journal.pone.02785002023-05-18T14:00:00Z2023-05-18T14:00:00Z<p>by Bruce Mutari, Julia Sibiya, Admire Shayanowako, Charity Chidzanga, Prince M. Matova, Edmore Gasura</p>
Understanding the genetic basis of traits of economic importance under drought stressed and well-watered conditions is important in enhancing genetic gains in dry beans (<i>Phaseolus vulgaris</i> L.). This research aims to: (i) identify markers associated with agronomic and physiological traits for drought tolerance and (ii) identify drought-related putative candidate genes within the mapped genomic regions. An andean and middle-american diversity panel (AMDP) comprising of 185 genotypes was screened in the field under drought stressed and well-watered conditions for two successive seasons. Agronomic and physiological traits, <i>viz</i>., days to 50% flowering (DFW), plant height (PH), days to physiological maturity (DPM), grain yield (GYD), 100-seed weight (SW), leaf temperature (LT), leaf chlorophyll content (LCC) and stomatal conductance (SC) were phenotyped. Principal component and association analysis were conducted using the filtered 9370 Diversity Arrays Technology sequencing (DArTseq) markers. The mean PH, GYD, SW, DPM, LCC and SC of the panel was reduced by 12.1, 29.6, 10.3, 12.6, 28.5 and 62.0%, respectively under drought stressed conditions. Population structure analysis revealed two sub-populations, which corresponded to the andean and middle-american gene pools. Markers explained 0.08–0.10, 0.22–0.23, 0.29–0.32, 0.43–0.44, 0.65–0.66 and 0.69–0.70 of the total phenotypic variability (<i>R</i><sup>2</sup>) for SC, LT, PH, GYD, SW and DFW, respectively under drought stressed conditions. For well-watered conditions, <i>R</i><sup>2</sup> varied from 0.08 (LT) to 0.70 (DPM). Overall, 68 significant (p < 10<sup>−03</sup>) marker-trait associations (MTAs) and 22 putative candidate genes were identified across drought stressed and well-watered conditions. Most of the identified genes had known biological functions related to regulating the response to drought stress. The findings provide new insights into the genetic architecture of drought stress tolerance in common bean. The findings also provide potential candidate SNPs and putative genes that can be utilized in gene discovery and marker-assisted breeding for drought tolerance after validation.Impact of climatic conditions on radial growth of non-native <i>Cedrus libani</i> compared to native conifers in Central EuropeNikola ZsolnayAnna WalentowitzGregor Aas10.1371/journal.pone.02753172023-05-12T14:00:00Z2023-05-12T14:00:00Z<p>by Nikola Zsolnay, Anna Walentowitz, Gregor Aas</p>
Ongoing climate change increasingly affects growth conditions of native conifers such as <i>Picea abies</i> (Norway spruce) and <i>Pinus sylvestris</i> (Scots pine) in Central Europe. These conifers are primarily cultivated for wood production. To obtain ecologically and economically stable forests, forestry seeks alternative species that might be less prone to novel climatic conditions, such as <i>Cedrus libani</i> (Lebanon cedar). We aim at investigating growth responses to climatic factors of <i>C</i>. <i>libani</i> compared to native <i>P</i>. <i>abies</i> and <i>P</i>. <i>sylvestris</i> in Central Europe for 25 years (1994–2019). Growth responses were used as a proxy for tolerance towards climatic stress events, such as heat and drought. Height, diameter at breast height (DBH) and radial increment were measured for 40-year-old tree stands of <i>C</i>. <i>libani</i> and native conifers. Radial growth responses to selected climate parameters were analysed using bootstrapped correlations with detrended growth index chronologies and growth response indices for drought years (2003, 2012, 2015, 2018). For <i>C</i>. <i>libani</i>, radial growth was positively correlated with high water availability in late winter and spring, while for <i>P</i>. <i>abies</i>, February and summer and for <i>P</i>. <i>sylvestris</i>, July showed such a relationship. <i>Cedrus libani</i> exhibited the highest resistance, recovery, and resilience in response to climatic extremes. Against the background of climate change, <i>C</i>. <i>libani</i> could serve as an alternative conifer species to establish climate-resistant viable forests in Central Europe.Evaluation of bread wheat (<i>Triticum aestivum</i> L.) genotypes for drought tolerance using morpho-physiological traits under drought-stressed and well-watered conditionsBirhanu Mecha SeworeAyodeji AbeMandefro Nigussie10.1371/journal.pone.02833472023-05-04T14:00:00Z2023-05-04T14:00:00Z<p>by Birhanu Mecha Sewore, Ayodeji Abe, Mandefro Nigussie</p>
Increasing frequency of drought spells occasioned by changing climatic conditions, coupled with rise in demand for bread wheat, calls for the development of high yielding drought resilient genotypes to enhance bread wheat production in areas with moisture deficit. This study was designed to identify and select drought-tolerant bread wheat genotypes using morpho-physiological traits. One hundred and ninety-six bread wheat genotypes were evaluated in greenhouse and field experiments, under well-watered (80% of field capacity) and drought-stressed (35% of field capacity) conditions, for two years. Data were collected on five morphological traits (flag leaf size, flag leaf angle, flag leaf rolling, leaf waxiness and resistance to diseases) and 14 physiological traits. Relative water content (RWC), Excised leaf water retention (ELWR), Relative water loss (RWL), Leaf membrane stability index (LMSI), as well as Canopy temperature depression (CTD) at heading (CTDH), anthesis (CTDA), milking (CTDM), dough stage (CTDD) and ripening (CTDR) were estimated. Similarly, leaf chlorophyll content (SPAD reading) was recorded at heading (SPADH), anthesis (SPADA), milking (SPADM), dough stage (SPADD), and ripening (SPADR). Significant (p<0.01) genotypic differences were found for the traits under both well-watered and drought-stressed conditions. Associations of RWL with SPADH, SPADA, SPADM, SPADD and SPADR were significant (p<0.01) and negative under both watering regimes. The first three principal components accounted for 92.0% and 88.4% of the total variation under well-watered and drought-stressed conditions, respectively and comprised all the traits. The traits CTDD, CTDM, CTDR, SPADH, SPADA, SPADM, SPADD and SPADR with genotypes Alidoro, ET-13A2, Kingbird, Tsehay, ETBW 8816, ETBW 9027, ETBW9402, ETBW 8394 and ETBW 8725 were associated under both conditions. Genotypes with narrow flag leaves, erect flag leaf angles, fully rolled flag leaves, heavily waxed leaves, and resistant to disease manifested tolerance to drought stress. The identified traits and genotypes could be exploited in future breeding programmes for the development of bread wheat genotypes with tolerance to drought.An urgent call to address climate change-related human health impacts in Southern AfricaCaradee Y. WrightThandi Kapwata10.1371/journal.pclm.00002042023-05-02T14:00:00Z2023-05-02T14:00:00Z<p>by Caradee Y. Wright, Thandi Kapwata</p>Comparing households’ perception of flood hazard with historical climate and hydrological data in the Lower Mono River catchment (West Africa), Benin and TogoNadège I. P. DossoumouMasamaéya D. T. GnazouGrace B. VillamorEuloge K. AgbossouSophie ThiamSimon WagnerMohamed Idrissou10.1371/journal.pclm.00001232023-04-24T14:00:00Z2023-04-24T14:00:00Z<p>by Nadège I. P. Dossoumou, Masamaéya D. T. Gnazou, Grace B. Villamor, Euloge K. Agbossou, Sophie Thiam, Simon Wagner, Mohamed Idrissou</p>
The comparison of local perception of flood hazards, with hydrological and climate parameters, can give more insight and understanding on the causes of flood, its impacts and the strategies to effectively address the problem. This study examines whether households’ perception of rainfall and flood occurrence are consistent with observed variation in climate parameter (rainfall) and hydrological (discharge) data in the Lower Mono River catchment (Togo-Benin, West Africa). Perceptions of the 744 households from the catchment were collected and compared to historical climatic and hydrological data using correlation analysis. The Standardized Precipitation Index was utilized to identify the extreme years in terms of precipitation. Chi-test and binary regression analyses were performed to identify the most affected communes within the catchment, and the factors that influence household perceptions on rainfall change, respectively. Findings reveal that 85% of the respondents perceived an excess in rainfall during the last 20 years and identify two particular years as the most affected by flood, which correspond to the climate data analysis. Households’ perceptions on flooded months are correlated with the monthly precipitation and discharge at the upper part of the catchment while the ones at down part are not correlated. Furthermore, the chi-test analysis shows that in the perception of households, the communes at the down part are more affected by flood than those at the upper part of the catchment. It is then important for decision maker to consider local communities’ perception for having insight regarding climate parameters, the causes of flood and in the decision making for implementing measures to cope with this phenomenon.Modelling and predicting forced migrationHaodong QiTuba Bircan10.1371/journal.pone.02844162023-04-13T14:00:00Z2023-04-13T14:00:00Z<p>by Haodong Qi, Tuba Bircan</p>
Migration models have evolved significantly during the last decade, most notably the so-called flow Fixed-Effects (FE) gravity models. Such models attempt to infer how human mobility may be driven by changing economy, geopolitics, and the environment among other things. They are also increasingly used for migration projections and forecasts. However, recent research shows that this class of models can neither explain, nor predict the temporal dynamics of human movement. This shortcoming is even more apparent in the context of forced migration, in which the processes and drivers tend to be heterogeneous and complex. In this article, we derived a Flow–Specific Temporal Gravity (FTG) model which, compared to the FE models, is theoretically similar (informed by the random utility framework), but empirically less restrictive. Using EUROSTAT data with climate, economic, and conflict indicators, we trained both models and compared their performances. The results suggest that the predictive power of these models is highly dependent on the length of training data. Specifically, as time-series migration data lengthens, FTG’s predictions can be increasingly accurate, whereas the FE model becomes less predictive.