Drought characteristics in Mediterranean under future climate change

Essa, Yassmin H.; Hirschi, Martin; Thiery, Wim; El-Kenawy, Ahmed M.; Yang, Chunxue

doi:10.1038/s41612-023-00458-4

Cited by 20 publications

(4 citation statements)

References 74 publications

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“…Our research provides experimental and theoretical evidence that this also applies to diaspore-dispersal traits and the dispersal potential of annual species that have evolved under the Mediterranean climate. The increased aridity predicted in these areas 21 could restrict plants' ability to move to more favorable ecological environments where they can thrive and reproduce under current and future climates. Our ndings challenge the main assumption of the informed dispersal hypothesis, which states that traits related to dispersal should improve dispersal in stressful environmental conditions 16,19 .…”

Section: Discussionmentioning

confidence: 99%

Climate change impacts the dispersal of annual plants: a mechanistic approach

Manzaneda,

Valenzuela-Polo,

Bolaños-Jiménez

et al. 2024

Preprint

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Anthropogenic climate change (ACC) significantly impacts plant populations, biodiversity, and ecosystem services. The survival of plant species hinges on their ability to adapt or migrate in pace with shifting climate niches, which is key for maintaining gene flow and habitat colonization in changing environments. This study investigates the mechanistic basis of how ACC affects seed dispersal. Here, we specifically model how elevated atmospheric CO2 levels, temperature, and drought collectively influence dispersal trait plasticity and potential across multiple species. We identified essential diaspore dispersal predictors using climate chamber experiments, fluid dynamic modelling, and wind tunnel assays. Our findings indicate a predicted dispersal distance reduction of 40% for temperate annual plants in warmer, drier, and CO2-rich conditions. Our results highlight the importance of inherent limits of plasticity in multiple traits for facing environmental change and the need to consider multiple environmental factors to understand dispersal in future climates.

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Section: Discussionmentioning

confidence: 99%

Climate change impacts the dispersal of annual plants: a mechanistic approach

Manzaneda,

Valenzuela-Polo,

Bolaños-Jiménez

et al. 2024

Preprint

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“…The frequency and area of global agricultural droughts are projected to increase in the future, especially in the northern hemisphere 24 . Under climate change, the severity and frequency of droughts is reported to increase in several regions across the globe, including in the Willamette River basin, U.S. 25 ; in the upper Yangtze River basin, China 26 ; Godavari River basin, India 27 ; in South Korea 28 , 29 ; in the Lower Mekong River basin, Vietnam 30 ; in Lancang-Mekong River Basin 31 ; in the Johor River basin, Malaysia 32 ; in the Mediterranean 33 ; in Europe 34 . It is univocal from these studies that climate change will aggravate future droughts globally.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the impacts of climate change and land-use change on future droughts in northeast Thailand

Khadka,

Babel,

Tingsanchali

et al. 2024

Sci Rep

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The impacts of climate change (CC) on droughts are well documented, but the effects of land-use change (LUC) are poorly understood. This study compares the projected individual and combined impacts of these stressors on future droughts (2021–2050), with respect to baseline (1981–2010) in one of the major tributaries of the Mekong River. LUC impacts on hydrological droughts are minimal compared to CC, with the latter expected to shorten the recurrence interval of a 20-year return period event to every 14 years. Both CC and LUC have significant impacts on agricultural droughts with heightened sensitivity. ‘Once in a Decade’ agricultural droughts will be 40% (35%) longer and 88% (87%) more severe under the CC (LUC) scenario. Under both stressors, the events occurring every 20 years will be twice as frequent. Results highlight the intensification of future droughts and the urgency for actions to mitigate/adapt to climate change and manage land use. Future policy shall holistically address agricultural water management, sustainable land use management, and crop management to cope with future droughts. We recommend developing resilient agricultural practices, enhanced water resource management strategies, and incorporating drought risk into land-use planning to mitigate the compounded impacts of CC and LUC.

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“…According to recent studies on historical trends and current projections, different regions of the Earth would be under a changing climate more vulnerable to extreme events such as flash droughts (Christian et al, 2021(Christian et al, , 2023Yuan et al, 2023), meteorological and agricultural droughts (Essa et al, 2023), forest wildfires (Patacca et al, 2023), and water storage deficiency (Pokhrel et al, 2021). The expected increase in concurrence of agricultural droughts would cause crop production losses and vegetation mortality.…”

Section: Introductionmentioning

confidence: 99%

Focal-TSMP: deep learning for vegetation health prediction and agricultural drought assessment from a regional climate simulation

Shams Eddin,

Gall

2024

Geosci. Model Dev.

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Abstract. Satellite-derived agricultural drought indices can provide a complementary perspective of terrestrial vegetation trends. In addition, their integration for drought assessments under future climates is beneficial for providing more comprehensive assessments. However, satellite-derived drought indices are only available for the Earth observation era. In this study, we aim to improve the agricultural drought assessments under future climate change by applying deep learning (DL) to predict satellite-derived vegetation indices from a regional climate simulation. The simulation is produced by the Terrestrial Systems Modeling Platform (TSMP) and performed in a free evolution mode over Europe. TSMP simulations incorporate variables from underground to the top of the atmosphere (ground-to-atmosphere; G2A) and are widely used for research studies related to water cycle and climate change. We leverage these simulations for long-term forecasting and DL to map the forecast variables into normalized difference vegetation index (NDVI) and brightness temperature (BT) images that are not part of the simulation model. These predicted images are then used to derive different vegetation and agricultural drought indices, namely NDVI anomaly, BT anomaly, vegetation condition index (VCI), thermal condition index (TCI), and vegetation health index (VHI). The developed DL model could be integrated with data assimilation and used for downstream tasks, i.e., for estimating the NDVI and BT for periods where no satellite data are available and for modeling the impact of extreme events on vegetation responses with different climate change scenarios. Moreover, our study could be used as a complementary evaluation framework for TSMP-based climate change simulations. To ensure reliability and to assess the model’s applicability to different seasons and regions, we provide an analysis of model biases and uncertainties across different regions over the pan-European domain. We further provide an analysis about the contribution of the input variables from the TSMP model components to ensure a better understanding of the model prediction. A comprehensive evaluation of the long-term TSMP simulation using reference remote sensing data showed sufficiently good agreements between the model predictions and observations. While model performance varies on the test set between different climate regions, it achieves a mean absolute error (MAE) of 0.027 and 1.90 K with coefficient of determination (R2) scores of 0.88 and 0.92 for the NDVI and BT, respectively, at 0.11° resolution for sub-seasonal predictions. In summary, we demonstrate the feasibility of using DL on a TSMP simulation to synthesize NDVI and BT satellite images, which can be used for agricultural drought forecasting. Our implementation is publicly available at the project page (https://hakamshams.github.io/Focal-TSMP, last access: 4 April 2024).

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Drought characteristics in Mediterranean under future climate change

Cited by 20 publications

References 74 publications

Climate change impacts the dispersal of annual plants: a mechanistic approach

Climate change impacts the dispersal of annual plants: a mechanistic approach

Evaluating the impacts of climate change and land-use change on future droughts in northeast Thailand

Focal-TSMP: deep learning for vegetation health prediction and agricultural drought assessment from a regional climate simulation

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