Plant hydraulic modelling of leaf and canopy fuel moisture content reveals increasing vulnerability of a Mediterranean forest to wildfires under extreme drought.

Fuel moisture content (FMC) is a crucial driver of forest fires in many regions world-wide. Yet, the dynamics of FMC in forest canopies as well as their physiological and environmental determinants remain poorly understood, especially under extreme drought. We embedded a FMC module in the trait-based, plant-hydraulic SurEau-Ecos model to provide innovative process-based predictions of leaf live fuel moisture content (LFMC) and canopy fuel moisture content (CFMC) based on leaf water potential ( ψ Leaf ). SurEau-Ecos-FMC relies on pressure-volume (p-v) curves to simulate LFMC and vulnerability curves to cavitation to simulate foliage mortality. SurEau-Ecos-FMC accurately reproduced ψ Leaf and LFMC dynamics as well as the occurrence of foliage mortality in a Mediterranean Quercus ilex forest. Several traits related to water use (leaf area index, available soil water, and transpiration regulation), vulnerability to cavitation, and p-v curves (full turgor osmotic potential) had the greatest influence on LFMC and CFMC dynamics. As the climate gets drier, our results showed that drought-induced foliage mortality is expected to increase, thereby significantly decreasing CFMC. Our results represent an important advance in our capacity to understand and predict the sensitivity of forests to wildfires.

Tree xylem water isotope analysis by Isotope Ratio Mass Spectrometry and laser spectrometry: A dataset to explore tree response to drought.

Water isotopes from plant xylem and surrounding environment are increasingly used in eco-hydrological studies. Carrière et al. [1] analyzed a dataset of water isotopes in (i) the xylem of three different tree species, (ii) the surrounding soil and drainage water and (iii) the underlying karst groundwater, to understand tree water uptake during drought in two different Mediterranean forests on karst setting. The xylem and soil water were extracted by cryogenic distillation. The full dataset was obtained with Isotope Ratio Mass Spectrometry (IRMS) and Isotope Ratio Infrared Spectrometer (IRIS), and included 219 measurements of δ2H and δ18O. Prompted by unexpected isotopic data characterized by a very negative deuterium excess, a subsample of 46 xylem samples and 9 soil water samples were double checked with both analytical techniques. IRMS and IRIS analyses yielded similar data. Therefore, the results reveal that laser spectrometry allows an accurate estimation of xylem and soil water isotopes. The dataset highlights a strong 2H depletion in xylem water for all species. Deuterium does not seem adequate to interpret ecological processes in this dataset given the strong fractionation.

The role of deep vadose zone water in tree transpiration during drought periods in karst settings - Insights from isotopic tracing and leaf water potential.

Karst environments are unusual because their dry, stony and shallow soils seem to be unfavorable to vegetation, and yet they are often covered with forests. How can trees survive in these environments? Where do they find the water that allows them to survive? This study uses midday and predawn water potentials and xylem water isotopes of branches to assess tree water status and the origin of transpired water. Monitoring was conducted during the summers of 2014 and 2015 in two dissimilar plots of Mediterranean forest located in karst environments. The results show that the three monitored tree species (Abies alba Mill, Fagus sylvatica L, and Quercus ilex L.) use deep water resources present in the karst vadose zone (unsaturated zone) more intensively during drier years. Quercus ilex, a species well- adapted to water stress, which grows at the drier site, uses the deep water resource very early in the summer season. Conversely, the two other species exploit the deep water resource only during severe drought. These results open up new perspectives to a better understanding of ecohydrological equilibrium and to improved water balance modeling in karst forest settings.

Karst recharge-discharge semi distributed model to assess spatial variability of flows.

Aquifer recharge assessment is a key factor for sustainable groundwater resource management. Although main factors of the spatial and temporal variability of recharge are known, taking them into account in a distributed or semi-distributed model is still a challenging task. This difficulty is increased in karst environments. Indeed, recharge of karst aquifers also depends on the organization of the karst network, which is both highly heterogeneous and difficult to characterize. We developed a reservoir model to simulate the spatial and temporal variability of recharge on karst watersheds. Special attention was paid to the link between model parameters and measurable or qualitative environmental factors of recharge. The spatial variability of soil reservoir capacity was estimated by multifactorial modelling (neural network). Intrinsic vulnerability indices were used to constrain the partitioning between slow and fast flows within the karst aquifer. Comparison of simulated and measured discharge at the outlet was used to calibrate and assess recharge model. The karst hydrosystem of the Fontaine de Vaucluse is renowned for its significant heterogeneity and anisotropy, which has so far limited the application of 2D or 3D modelling. The model developed was successfully applied to this system. Our results showed that the annual recharge is very heterogeneous on the test site. Spatialization of recharge improves discharge modelling as evidenced by increased KGE (from 0.8 to 0.9) and more realistic flows during drought periods. It is therefore essential to spatialize recharge in karst hydrogeological modelling to improve predictive capacity and better understand functioning of the whole hydrosystem.

Simple and robust methods for remote sensing of canopy chlorophyll content: a comparative analysis of hyperspectral data for different types of vegetation.

Canopy chlorophyll content (CCC) is an essential ecophysiological variable for photosynthetic functioning. Remote sensing of CCC is vital for a wide range of ecological and agricultural applications. The objectives of this study were to explore simple and robust algorithms for spectral assessment of CCC. Hyperspectral datasets for six vegetation types (rice, wheat, corn, soybean, sugar beet and natural grass) acquired in four locations (Japan, France, Italy and USA) were analysed. To explore the best predictive model, spectral index approaches using the entire wavebands and multivariable regression approaches were employed. The comprehensive analysis elucidated the accuracy, linearity, sensitivity and applicability of various spectral models. Multivariable regression models using many wavebands proved inferior in applicability to different datasets. A simple model using the ratio spectral index (RSI; R815, R704) with the reflectance at 815 and 704 nm showed the highest accuracy and applicability. Simulation analysis using a physically based reflectance model suggested the biophysical soundness of the results. The model would work as a robust algorithm for canopy-chlorophyll-metre and/or remote sensing of CCC in ecosystem and regional scales. The predictive-ability maps using hyperspectral data allow not only evaluation of the relative significance of wavebands in various sensors but also selection of the optimal wavelengths and effective bandwidths.

The PRECOS framework: Measuring the impacts of the global changes on soils, water, agriculture on territories to better anticipate the future.

In a context of increased land and natural resources scarcity, the possibilities for local authorities and stakeholders of anticipating evolutions or testing the impact of envisaged developments through scenario simulation are new challenges. PRECOS's approach integrates data pertaining to the fields of water and soil resources, agronomy, urbanization, land use and infrastructure etc. It is complemented by a socio-economic and regulatory analysis of the territory illustrating its constraints and stakes. A modular architecture articulates modeling software and spatial and temporal representations tools. It produces indicators in three core domains: soil degradation, water and soil resources and agricultural production. As a territory representative of numerous situations of the Mediterranean Basin (urban pressures, overconsumption of spaces, degradation of the milieus), a demonstration in the Crau's area (Southeast of France) has allowed to validate a prototype of the approach and to test its feasibility in a real life situation. Results on the Crau area have shown that, since the beginning of the 16th century, irrigated grasslands are the cornerstones of the anthropic-system, illustrating how successfully men's multi-secular efforts have maintained a balance between environment and local development. But today the ecosystem services are jeopardized firstly by urban sprawl and secondly by climate change. Pre-diagnosis in regions of Emilia-Romagna (Italy) and Valencia (Spain) show that local end-users and policy-makers are interested by this approach. The modularity of indicator calculations and the availability of geo-databases indicate that PRECOS may be up scaled in other socio-economic contexts.

How is water-use efficiency of terrestrial ecosystems distributed and changing on Earth?

A better understanding of ecosystem water-use efficiency (WUE) will help us improve ecosystem management for mitigation as well as adaption to global hydrological change. Here, long-term flux tower observations of productivity and evapotranspiration allow us to detect a consistent latitudinal trend in WUE, rising from the subtropics to the northern high-latitudes. The trend peaks at approximately 51°N, and then declines toward higher latitudes. These ground-based observations are consistent with global-scale estimates of WUE. Global analysis of WUE reveals existence of strong regional variations that correspond to global climate patterns. The latitudinal trends of global WUE for Earth's major plant functional types reveal two peaks in the Northern Hemisphere not detected by ground-based measurements. One peak is located at 20° ~ 30°N and the other extends a little farther north than 51°N. Finally, long-term spatiotemporal trend analysis using satellite-based remote sensing data reveals that land-cover and land-use change in recent years has led to a decline in global WUE. Our study provides a new framework for global research on the interactions between carbon and water cycles as well as responses to natural and human impacts.

Preferential cooling of hot extremes from cropland albedo management.

Changes in agricultural practices are considered a possible option to mitigate climate change. In particular, reducing or suppressing tillage (no-till) may have the potential to sequester carbon in soils, which could help slow global warming. On the other hand, such practices also have a direct effect on regional climate by altering the physical properties of the land surface. These biogeophysical effects, however, are still poorly known. Here we show that no-till management increases the surface albedo of croplands in summer and that the resulting cooling effect is amplified during hot extremes, thus attenuating peak temperatures reached during heat waves. Using a regional climate model accounting for the observed effects of no-till farming on surface albedo, as well as possible reductions in soil evaporation, we investigate the potential consequences of a full conversion to no-till agriculture in Europe. We find that the summer cooling from cropland albedo increase is strongly amplified during hot summer days, when surface albedo has more impact on the Earth's radiative balance due to clear-sky conditions. The reduced evaporation associated with the crop residue cover tends to counteract the albedo-induced cooling, but during hot days the albedo effect is the dominating factor. For heatwave summer days the local cooling effect gained from no-till practice is of the order of 2 °C. The identified asymmetric impact of surface albedo change on summer temperature opens new avenues for climate-engineering measures targeting high-impact events rather than mean climate properties.

Assessing the Potentialities of FORMOSAT-2 Data for Water and Crop Monitoring at Small Regional Scale in South-Eastern France.

Water monitoring at the scale of a small agricultural region is a key point to insure a good crop development particularly in South-Eastern France, where extreme climatic conditions result in long dry periods in spring and summer with very sparse precipitation events, corresponding to a crucial period of crop development. Remote sensing with the increasing imagery resolution is a useful tool to provide information on plant water status over various temporal and spatial scales. The current study focussed on assessing the potentialities of FORMOSAT-2 data, characterized by high spatial (8m pixel) and temporal resolutions (1-3 day/time revisit), to improve crop modeling and spatial estimation of the main land properties. Thirty cloud free images were acquired from March to October 2006 over a small region called Crau-Camargue in SE France, while numerous ground measurements were performed simultaneously over various crop types. We have compared two models simulating energy transfers between soil, vegetation and atmosphere: SEBAL and PBLs. Maps of evapotranspiration were analyzed according to the agricultural practices at field scale. These practices were well identified from FORMOSAT-2 images, which provided accurate input surface parameters to the SVAT models.