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Litter decomposition is a key ecosystem function in forests and varies in response to a range of climatic, edaphic, and local stand characteristics. Disentangling the relative contribution of these factors is challenging, especially along large environmental gradients. In particular, knowledge of the effect of management options, such as tree planting density and species composition, on litter decomposition would be highly valuable in forestry. In this study, we made use of 15 tree diversity experiments spread over eight countries and three continents within the global TreeDivNet network. We evaluated the effects of overstory composition (tree identity, species/mixture composition and species richness), plantation conditions (density and age), and climate (temperature and precipitation) on mass loss (after 3 months and 1 year) of two standardized litters: high-quality green tea and low-quality rooibos tea. Across continents, we found that early-stage decomposition of the low-quality rooibos tea was influenced locally by overstory tree identity. Mass loss of rooibos litter was higher under young gymnosperm overstories compared to angiosperm overstories, but this trend reversed with age of the experiment. Tree species richness did not influence decomposition and explained almost no variation in our multi-continent dataset. Hence, in the young plantations of our study, overstory composition effects on decomposition were mainly driven by tree species identity on decomposer communities and forest microclimates. After 12 months of incubation, mass loss of the high-quality green tea litter was mainly influenced by temperature whereas the low-quality rooibos tea litter decomposition showed stronger relationships with overstory composition and stand age. Our findings highlight that decomposition dynamics are not only affected by climate but also by management options, via litter quality of the identity of planted trees but also by overstory composition and structure.

It is widely admitted that changes in land use land cover (LULC) influence the hydrology of the catchment. However, how these changes affect hydrological model prediction uncertainty is still a raising question. In this paper we addressed this question by investigating the impacts of the rapid change in LULC in the Siliana catchment in Tunisia on monthly flow and magnitude of flow extremes using the SWAT hydrological model while quantifying the contribution of LULC to the model parameter and prediction uncertainty. At a first step, the SWAT model parameter and prediction uncertainty were estimated using the GLUE method and acceptable parameter sets were identified. Subsequently, the SWAT model was fed with historical LULC as derived from Landsat 5 and 8 satellite images for the years 1990, 2000, 2013 and 2019, and run with the acceptable parameter sets. The results show that the increase in olive plantations (+380 %), urban area (+200 %), and irrigated lands (+309 %) from 1990 to 2019, has LULC decreased monthly flow, high flows magnitude but did not impact low flows in particular over the previous two decades. The findings also suggest that model prediction uncertainty can mask LULC effects, suggesting that model results can be misleading without explicit consideration of uncertainty when assessing the hydrological impacts of changes in LULC.

Mineral organic carbon (OC) interactions in soils and ice-rich sediments are key to stabilize OC and mitigate greenhouse gas emissions upon permafrost thaw. However, changes in soil water pathways upon permafrost thaw are likely to affect the stability of mineral OC interactions. Dissolution of mineral surfaces can release associated OC which contributes to carbon loss, whereas precipitation of new mineral surfaces can promote loci for OC interactions limiting carbon loss. Here we use radiogenic Sr isotopes to locate in situ dissolution-precipitation processes of mineral OC interactions along a gradient of permafrost thaw in soils and ice-rich sediments. In these materials, about 20% of OC is stabilized as organo-mineral associations (association between ferrihydrite and OC) and organo-metallic complexes (associations between Fe, Mn, Al, Ca polyvalent cations and organic acids). We target Sr adsorbed or occluded to metal oxides or participating in organo-metallic complexes. We hypothesize that a change in the Sr isotopic signature of such mineral OC interactions upon permafrost thaw indicates a destabilization of the binding between mineral surfaces and Sr, and hence OC. We show that it is in saturated layers that mineral OC interactions have remained undissociated and preserved since their formation. At the redox interface, the data highlight processes of dissolution and precipitation of the mineral OC interactions, supporting loci for the loss and gain in OC stabilization potential. Given the importance of stabilizing surfaces and cations involving Fe for the stabilization of OC in permafrost environments, we propose an approach to estimate at larger scale in the Arctic the proportion of this “reactive iron” in permafrost soils.

Between 30 and 80% of soil organic carbon (OC) in permafrost environments can be stabilized by interactions with mineral surfaces or metals such as iron. Iron-OC interactions may be modified by changing hydrological conditions upon permafrost thaw resulting in local subsidence. The challenge is to identify the early stage of thermokarst landforms, and to quantify the influence of thermokarst development on Fe and OC released in soil pore water upon thawing. We monitored the soil water content (SWC), soil temperature and soil electrical conductivity (EC) together with the chemical composition of the soil pore water along a gradient of thermokarst development and subsequent permafrost degradation at Abisko, Sweden (palsa-bog-fen). More specifically, we combined geophysical parameters (elevation, active layer depth, SWC and soil EC) and physico-chemical parameters (pH and soil pore water EC) at the profile and slope scales, with concentrations of Fe and dissolved organic carbon (DOC) in soil pore water at the profile scale. The results highlight that (i) at the profile scale, elevation, active layer depth and SWC are relevant geophysical criteria to discriminate between palsa, bog and fen; (ii) permafrost degradation leads to the mobilization of Fe and DOC in soil pore water; (iii) at the slope scale, landscape areas can be classified as palsa, intermediate or fen based on the three geophysical criteria and this can be used to derive the conditions for the mobility of Fe and DOC. These data support that physical degradation of permafrost and subsequent changes in SWC with thermokarst landform development from palsa to fen likely influences the geochemical conditions for the stability of Fe-OC interactions.

Upon permafrost thaw, the volume of soil accessible to plant roots increases which modifies the acquisition of plant-available resources. Tundra vegetation is actively responding to the changing environment with two major directions for vegetation shift across the Arctic: the expansion of deep-rooted sedges and the widespread increase in shallow-rooted shrubs. Changes in vegetation composition, density and distribution have large implications on the Arctic warming and permafrost stability by influencing the albedo, the snow accumulation and the litter decomposition rate. A better understanding of these cumulated effects of changing vegetation on warming and permafrost requires assessing the changes in plant nutrient sources upon permafrost thaw, nutrient access being a limiting factor for the Arctic tundra vegetation development. In this study, we determined the influence of permafrost degradation on the base cation sources for plant uptake by using the radiogenic Sr isotope ratio as a tracer of source, along a permafrost thaw gradient at Eight Mile Lake in Interior Alaska (USA). As plants take up Sr from the exchangeable soil fraction with no measurable fractionation, we determined the differences in 87Sr/86Sr ratio of the exchangeable Sr between shallow and deeper soil horizons, and we compared the 87Sr/86Sr ratio of foliar samples for three Arctic tundra species with contrasted rooting depths (Betula nana, Vaccinium vitisidaea, and Eriophorum vaginatum) upon different permafrost thaw conditions. The higher foliar 87Sr/86Sr ratios of shallow-rooted Arctic tundra shrubs (B. nana, V. vitis-idaea) was consistent with a shallow source of soil exchangeable Sr from surface soil horizons, whereas the lower foliar 87Sr/86Sr ratios of deep-rooted Arctic tundra sedges (E. vaginatum) reflected a source of Sr from deeper soil horizons. There is a shift between poorly and highly thawed soil profiles towards lower foliar 87Sr/86Sr ratios in both deep- and shallow-rooted plant s

In drylands, water availability is the main limiting factor for plant growth. Topographic depressions in the Sahel that reveal a more favorable water balance display greater tree diversity compared to their surroundings. However, the environmental factors that drive differences in botanical composition between depressions remain unknown. Here, we investigated the depression features, and the landscape and connectivity metrics responsible for woody vegetation composition in a savanna of Senegal. We mapped depressions in a 700 km2 area and inventoried woody vegetation in 61 depressions varying in area. Simple linear models were applied between (i) indicators of richness and botanical composition and (ii) depression attributes, landscape and connectivity metrics. We found that the area of a depression increased species richness. The number of vegetation strata and the presence of a temporary pond also positively influenced species richness. Yet, while large depressions always had high richness, some small depressions did too. We were not able to identify additional factors to explain this diversity between small depressions. In the context of decreasing richness and composition shift observed in the Sahel over recent decades, depressions, as biodiversity hotspots, are key elements in ecosystem functioning. Further studies are needed to understand other potential drivers of species diversity, such as soil water availability.

More than 20% of global liquefied natural gas (LNG) exports and almost all of Qatar’s drinking water production originate from three industrial sites on Qatar’s eastern coast. They are all vulnerable to oil spills, and this vulnerability remains largely unquantified. Here we model oil-spill dispersal in the shallow maritime waters surrounding Qatar to identify which offshore areas and times of the year pose the greatest threat to the nation’s LNG export and seawater desalination facilities. By combining oil transport simulations with marine traffic data, we identify two high-risk areas, sizing up to ~15% of Qatar’s maritime exclusive economic zone. Ras Laffan’s LNG terminal has the highest vulnerability to oil spills all year, and its desalination plant, producing 30% of the national water supply, has a seasonal vulnerability peaking to an alarming level twice a year during spring and fall. Both LNG export and desalination facilities could be impacted by oil spills occurring outside of Qatar’s maritime borders in less than three days. We suggest that offshore high-risk areas be closely monitored with airborne and satellite synthetic-aperture radar providing early warning for oil spills that could severely disrupt Qatar’s LNG exports, further aggravating the global gas crisis.

The persistence of the woody vegetation of the Sahelian savannas, and their supported ecosystem functions, have been questioned since the great drought of 1970s–1980s. To assess the resilience of this vegetation to drought and grazing, we undertook a trait‐based approach using field inventory, historical survey databases, and traits data literature. Using a hierarchical clustering approach, we gathered the species present from 1970 to 2015 into functional groups according to their effect traits related to primary productivity and biogeochemical cycles. First, we studied the evolution of functional redundancy (FRe) and response diversity (RDiv) of the functional effect groups to drought and grazing, two indicators of resilience, since the 1970s. Second, we looked at the spatial variation of these two indices in 2015, according to local topography. FRe and RDiv of 80% of the functional groups examined declined since 1970, endangering the persistence of the studied functions. Local topography strongly influenced current FRe and RDiv, with depressions presenting higher values. Finally, by examining species’ abundances, their regeneration, and the functional group to which they belong, we determined some key species that could benefit from protection to ensure the persistence of the ecosystem functions supported by the woody vegetation. This study has expanded knowledge about the savanna’s response to pressures and has shown how a functional traits‐based approach could be an effective tool to guide the management of tropical savannas.

As more and more people live near the sea, future flood risk must be properly assessed for sustainable urban planning and coastal protection. However, this is rarely the case in developing countries where there is a lack of both in-situ data collection and forecasting tools. Here, we consider the case of the Kapuas River Delta (KRD), a data-scarce delta on the west coast of Borneo Island, Indonesia. We assessed future flood risk under three climate change scenarios (RCP2.6, RCP4.5, and RCP8.5). We combined the multiple linear regression and the GIS-based bathtub inundation models to assess the future flood risk. The former model was implemented to model the river’s water-level dynamics in the KRD, particularly in Pontianak, under the influence of rainfall changes, surface wind changes, and sea-level rise. The later model created flood maps with inundated areas under a 100-year flood scenario, representing Pontianak’s current and future flood extent. We found that about 6.4%–11.9% more buildings and about 6.8%–12.7% more roads will be impacted by a 100-year flood in 2100. Our assessment guides the local water manager in preparing adequate flood mitigation strategies.

The Arabian/Persian Gulf (hereafter, the “Gulf”) is one the busiest and fastest changing sea in the World. Its circulation is primarily driven by the surface water inflow from the Sea of Oman and density-driven and wind-driven flows within the Gulf. The regional circulation in its central part, particularly around Qatar, could not be explored because of unavailability of measured current data and the coarse resolution opted for the entire Gulf modelling. In the present study, we developed a high-resolution ocean modelling system of the entire Gulf with a particular focus on Qatar coastal waters. The model uses an unstructured mesh with different resolutions ranging from 5 km in the open ocean to 150 m along the coast of Qatar and less than 40 m around artificial structures. The model results have been validated with in situ data collected off Qatar. It allows seamless simulations of hydrodynamic processes from the entire basin scale down to the scale of coastal structures. The study identifies seasonal variability in currents and eddies in the central part of the Gulf. It also suggests the existence of four prominent anticyclonic eddies in the Gulf of Salwa, south of Bahrain. At the structure scale, the flow is mostly tidally driven and can be intensified beyond 1 m/s through narrow passages such as between breakwaters or within artificial waterways. By explicitly representing the effect of ocean sprawl on the coastal circulation, our model has the potential to greatly improve the environmental impact assessment of coastal developments in the Gulf area.

Since the 1980s, populations of Acropora cervicornis and A. palmata have experienced severe declines due to disease and anthropogenic stressors; resulting in their listing as threatened, and their need for restoration. In this study, larval survival and competency data were collected and used to calibrate a very high-resolution hydrodynamic model (up to 100m) to determine the dispersal patterns of Acropora species along the Florida’s Coral Reef. The resulting connectivity matrices was incorporated into a metapopulation model to compare strategies for restoring Acropora populations. This study found that Florida’s Coral Reef was historically a well-connected system, and that spatially selective restoration may be able to stimulate natural recovery. Acropora larvae are predominantly transported northward along the Florida’s Coral Reef, however southward transport also occurs, driven by tides and baroclinic eddies. Local retention and self-recruitment processes were strong for a broadcast spawner with a long pelagic larval duration. Model simulations demonstrate that it is beneficial to spread restoration effort across more reefs, rather than focusing on a few reefs. Differences in population patchiness between the Acropora cervicornis and A. palmata drive the need for different approaches to their management plans. This model can be used as a tool to address the species-specific management to restore genotypically diverse Acropora populations on the Florida’s Coral Reef, and its methods could be expanded to other vulnerable populations.

Ground-Penetrating Radar (GPR) has been widely used in the backfill grouting detections of shield tunnel construction. The proposed approach of automatic annular thickness measurement based on GPR monitoring system and BBP-XGBoost algorithm has been demonstrated to be an effective and efficient technique for detecting the backfill grouting of shield tunnel construction. The advantages include: (1) high accuracy: the proposed model is able to achieve high coefficients of regression R2 (0.943) for training sets and comparatively low RMSE values (0.421 and 1.32 cm) for both training and testing datasets, respectively; (2) high efficiency: the proposed XGBoost algorithm outscores other models in both accuracy and efficiency; (3) real-time output: the trained models were applied to automatically measure the annular grouting thickness of the Tianjin Metro tunnel constructions (China), with consistent real-time outputs for the engineers on site. The proposed approach provides real-time and efficient guidance for the construction of shield tunnels.

Rain-fed agriculture is the main source of livelihood for most of Burundi’s population, especially in the northeastern part of the country. This research is aimed at examining how smallholder farmers in the Northeastern region of Burundi perceive climate change and variability and at identifying the methods that are used to adapt, based on data from 200 small farmers and on actual weather data recorded between 1986 and 2017. We find that the majority of farmers (54%) perceive significant increases in temperature and unpredictability of rainfall duration and intensity and are making adjustments to adapt their agriculture in response to changes in climate. Over 80% of farmers have implemented at least one adaptation strategy among the nine evaluated. Changing crop varieties, changing fertilizers, and planting shade trees are the main adaptation strategies that were being implemented by farmers across the study area. The results of a binary regression model showed that the agricultural education and experience of farmers, as well as farm and family size, livestock ownership, climate information access, credit access, and farm income, strongly influence smallholder farmers’ decisions to adapt to climate change. The main obstacles are the lack of information on climate and adaptation strategies, and poverty, which makes it difficult to cope with the increased costs of farming. Understanding farmers’ perceptions of climate change and variability on a local level would provide information on how to develop adaptation strategies. The present study suggests the need for strengthening farmers’ capacities and improving the policy framework for adaptation to climate change in order to improve farmers’ livelihoods. Implications for policymakers will, therefore, include making flexible credit facilities, and investing in training extension agents on both climate change outreach and coping strategies.

Urban gullies are a rapidly growing concern in many tropical cities of the Global South. Various measures are already implemented for their stabilization. However, an overview of these measures and their overall effectiveness is currently lacking. We aim at addressing this gap by documenting existing initiatives to stabilize urban gullies in D.R. Congo and assessing their overall effectiveness. To this end we conducted extensive field campaigns in Kinshasa, Kikwit and Bukavu and combined our terrain observations with data on gully expansion rates (derived from series of satellite imagery). In total, we characterized present and past stabilization initiatives for 398 urban gullies. For 69 of these gullies, the effect of a specific measure on gully expansion rates could be estimated. Results show that for the large majority of gullies, various measures have been implemented. Yet, these are mainly ad-hoc measures installed by the affected population. More structural measures based on larger engineering works were observed for only 20–30% of gullies. The huge efforts invested in the installation of measures strongly contrast with their overall low impact. Among all strategies, only the deviation of runoff resulted in significantly lower expansion rates after installation. The numerous initiatives that rely on the sparse means available seem to have limited effects. This does not imply, however, that they are completely ineffective and should be abandoned. Based on our findings, we formulate recommendations for further research on how to effectively prevent and stabilize urban gullies, taking into account the difficult environmental and socio-economic context

La Belgique a enregistré de nombreux progrès sur le plan environnemental. Mais l’empreinte écologique globale du pays soulève bien d’autres questions.

Whitings, or occurrences of fine-grained carbonate in the water column, have been observed in modern environments with salinities ranging from fresh to marine conditions, and thick deposits of lime mud are described throughout the geological record. Despite their ubiquity, the trigger for whitings has been debated for more than eighty years. Satellite data reveal that most whitings are restricted to the northwestern part of Great Bahama Bank (GBB) which occupies , 10% of the platform area. Even here, whitings are further focused. More than 35% of them occur in a zone which occupies just 1% of the platform. We propose a three-step process for the existence of this zone of peak whitings and why the whitings in it are both more frequent and larger in winter than summer. First, the temperature differential between on- and off-platform waters is highest in the winter, setting up a disparity between dissolved CO2 concentrations in the two water masses. Second, hydrodynamic mixing of these two water masses increases the degree of aragonite saturation of the platform-top waters, as colder on-platform waters with theoretically higher concentrations of dissolved gases are warmed via mixing with the warmer off-platform waters. Finally, spatial heterogeneity in the degree of aragonite saturation is higher in the winter, and the zone of peak whitings is situated in an area of locally enhanced saturation state. Hydrodynamic simulation suggests that the whitings zone is located by tidal inflow of off-platform waters across the western margin of GBB, as well as inflow from the Tongue of the Ocean to the north of Andros Island. Despite thermodynamic forcing mechanisms that predict higher frequency of whitings in the summer, the environmental, hydrodynamic, geochemical, and kinetic conditions in the whitings zone appear to support the Goldilocks configuration that enhances the formation of wintertime whitings on Great Bahama Bank. This phenomenon has implications for the interpretati

Flood forecasting based on water level modeling is an essential non-structural measure against compound flooding over the globe. With its vulnerability increased under climate change, every coastal area became urgently needs a water level model for better flood risk management. Unfortunately, for local water management agencies in developing countries building such a model is challenging due to the limited computational resources and the scarcity of observational data. Here, we attempt to solve the issue by proposing an integrated hydrodynamic and machine learning approach to predict compound flooding in those areas. As a case study, this integrated approach is implemented in Pontianak, the densest coastal urban area over the Kapuas River delta, Indonesia. Firstly, we built a hydrodynamic model to simulate several compound flooding scenarios, and the outputs are then used to train the machine learning model. To obtain a robust machine learning model, we consider three machine learning algorithms, i.e., Random Forest, Multi Linear Regression, and Support Vector Machine. The results show that this integrated scheme is successfully working. The Random Forest performs as the most accurate algorithm to predict flooding hazards in the study area, with RMSE = 0.11 m compared to SVM (RMSE = 0.18 m) and MLR (RMSE = 0.19 m). The machine-learning model with the RF algorithm can predict ten out of seventeen compound flooding events during the testing phase. Therefore, the random forest is proposed as the most appropriate algorithm to build a reliable ML model capable of assessing the compound flood hazards in the area of interest.

The Kapuas River delta is a unique estuary system on the west coast of Borneo Island, Indonesia. Its hydrodynamics is driven by an interplay between storm surges, tides, and rivers discharge. These interactions are likely to be exacerbated by global warming, leading to more frequent compound flooding in the area. The mechanisms driving compound flooding events in the Kapuas River Delta remain, however, poorly known. Here we attempt to fill this gap by assessing the interactions between river discharges, tides, and storm surges and how they can drive a compound inundation over the riverbanks, particularly within Pontianak, the main city along the Kapuas River. We simulated these interactions using the multi-scale hydrodynamic model SLIM. Our model correctly reproduces the Kapuas River’s hydrodynamics and its interactions with tides and storm surge from the Karimata Strait. We considered several extreme scenario test cases to evaluate the impact of tide-storm-discharge interactions on the maximum water level profile from the river mouth to the upstream part of the river. Based on the maximum water level profiles, we could divide the main branch of the Kapuas River’s stream into three zones, i.e., the tidally-dominated region (from the river mouth to about 4 km upstream), the mixed-energy region (from about 4 km to about 30 km upstream) and the river-dominated region (beyond 30 km upstream). Thus, the local water management can define proper mitigation for handling compound flooding hazards along the riverbanks by using this zoning category. The model also successfully reproduced a compound inundation event in Pontianak, which occurred on 29 December 2018. For this event, the wind-generated surge appeared to be the dominant trigger.

Drone-borne ground-penetrating radar (GPR) has proven to be efficient and promising for high-resolution topsoil moisture mapping at the field scale. However, in practice, the radar incident angle may change as a function of the terrain slope as well as unstable flying conditions. In this respect, we analysed the effect of radar incident angle on full-wave inversion for soil permittivity characterization. Specifically, using the frequency-domain radar equation, antenna characteristic functions with different incident angles were determined for a horn antenna as an example. Then numerical analyses and field measurements were performed to quantify the errors on the retrieved permittivity resulting from incident angle drifts. In agreement with the radar equation concept, we observed that the angle- and frequency-dependent global transmission functions of the antenna correspond well to its radiation pattern. Numerical and field results show that errors in the permittivity estimation can be very significant as a function of the antenna radiation pattern and incident angle. Nevertheless, if the incident angle is known and the characteristic antenna functions are determined as a function of the incident angle, full-wave modelling and inversion remain accurate provided the signal-to-noise ratio remains sufficient.

Global warming is killing corals; however, the effects of warming on population connectivity, a process fundamental to reef recovery, are largely unexplored. Using a high-resolution (as high as 200 m), empirically calibrated biophysical model of coral larval dispersal for the southern Great Barrier Reef, we show that the increased larval mortality and reduced competency duration under a 2 °C warming alter dispersal patterns, whereas projected changes in large-scale currents have limited effects. Overall, there was on average a 7% decrease in the distance larvae disperse (among-reef interquartile range (IQR), −10% to −4%), an 8% decrease in the number of connections into each reef (IQR, −11% to −3%) and a 20% increase in local retention (IQR, 0% to +49%). Collectively, these shifts imply that 2 °C of warming will reduce inter-reef connectivity, hampering recovery after disturbances and reducing the spread of warm-adapted genes. Such changes make protections more effective locally, but may require reducing spacing between protected areas.

For the last seven years, Florida’s Coral Reef (FCR) has suffered from widespread and severe coral loss caused by stony coral tissue loss disease (SCTLD). First observed off the coast of Miami-Dade county in 2014, the outbreak has since spread throughout the entirety of FCR and some areas of the Caribbean. However, the propagation of the disease through FCR seemed to slow down when it reached the western end of the Marquesas in August 2020. Despite being present about 30 km (~20 miles) from the Dry Tortugas (DRTO), SCTLD was not reported in this area before May 2021. As SCTLD transmission is likely to be waterborne, here we suggest that this apparently delayed propagation is related to eddy activity near the DRTO under the influence of the Loop Current/Florida Current system. To quantify the impact of the local ocean circulation on the spread of SCTLD from the Marquesas and the DRTO, we evaluated the hydrodynamic-predicted connectivity between these two regions using a high-resolution hydro-epidemiological model between May 2018 and May 2021. Our results suggest that the Marquesas and the DRTO were not connected during February-October 2020 and January-May 2021. These periods coincided with either the occurrence of Tortugas gyres and mean circulation with an eastward component between the Marquesas and the DRTO or the presence of southward currents. Our results suggest that disease agents probably reached the DRTO in November 2020 and that they most likely originated from southern or northwestern reefs of the Marquesas. This study provides novel insight into the role played by the hydrodynamics in the spread of SCTLD within the western-most edge of FCR, and in propagating the disease to uninfected locations.

The intensity of major tropical cyclones has increased during the past decade. Their effect is particularly acute in coastal areas where they cause extensive damage leading to an influx of debris, sediments and waste to the sea. However, most operational coastal ocean models do not represent heavy-wind transport processes correctly \modif{if} the hydrodynamics is not coupled with the wind-generated waves. This may lead to significant errors in ocean simulations under tropical cyclone conditions. Here, we investigate current-wave interactions during a major hurricane and assess their impact on transport processes. We do that by coupling the unstructured-mesh coastal ocean model SLIM with the spectral wave model SWAN, and applying it to the Florida Reef Tract during Hurricane Irma (September 2017). We show that the coupled model successfully reproduces the wave behavior, the storm surge and the ocean currents during the passage of the hurricane. We then use the coupled and uncoupled wave-current model to simulate the transport of passive drifters. We show that the wave radiation stress gradient alone can lead to changes of up to 1 m/s in the modeled currents, which in turn leads to differences of up to 5 km in the position of drifting material over the duration of the hurricane. The Stokes drift however appears to cause deflections up to 4 times larger and hence dominates wave-induced transport. Wave-current interactions therefore strongly impact the transport of drifting material such as sediments and debris in the aftermath of a hurricane. They should thus be taken into account in order to correctly assess its overall impact.

Water users in northwestern Tunisia, like the Medjerda watershed, are increasingly withdrawing water from hydro-systems. This is a response to the effects of climate change that are causing strong variability. These water withdrawals result in an increase in the state of stress over time (Fehri et al., 2020). The involvement of citizens, in a participatory manner, is likely to help raise awareness among water users. The use of Mobile application has been validated in the region of Medjez El Bab by the involvement of different citizen groups (Fehri et al., 2020a; Fehri, 2021). The objective of this sheet is to capitalize on these achievements and to be used in the north-west of Tunisia for monitoring droughts or floods.

In this chapter, we discuss the issue of balance between spatial resolution and computational efficiency in the context of the R-SWMS model. Based on the equations governing the water fluxes within the model, we propose here an objective and quantitative criterion which can help fix root segment size to both minimize computational load and achieve simulation according to a given accuracy degree.

In this chapter, we present the Root and Soil Water Movement and Solute transport model R-SWMS, which can be used to simulate flow and transport in the soil–plant system. The equations describing water flow in soil–root systems are presented and numerical solutions are provided. An application of R-SWMS is then briefly discussed, in which we combine in vivo and in silico experiments in order to decrypt water flow in the soil–root domain. More precisely, light transmission imaging experiments were conducted to generate data that can serve as input for the R-SWMS model. These data include the root system architecture, the soil hydraulic properties and the environmental conditions (initial soil water content and boundary conditions, BC). Root hydraulic properties were not acquired experimentally, but set to theoretical values found in the literature. In order to validate the results obtained by the model, the simulated and experimental water content distributions were compared. The model was then used to estimate variables that were not experimentally accessible, such as the actual root water uptake distribution and xylem water potential.

Toxoplasma gondii (T. gondii) is a parasitic pathogen that causes serious brain diseases in fetuses and patients with immunodeficiency, particularly AIDS patients. In the field of immunology, a large number of studies have shown that effector CD8+ T cells can respond to T. gondii infection in the brain tissue through controlling the proliferation of intracellular parasites and killing infected brain cells. These protective mechanisms do not occur without T cell movement and searching for infected cells, as a fundamental feature of the immune system. Following infection with a pathogen in a tissue, in their search for infected cells, CD8+ T cells can perform different stochastic searches, including Lévy and Brownian random walks. Statistical analysis of CD8+ T cell movement in the brain of T. gondii-infected mouse has determined that the search strategy of CD8+ T cells in response to infected brain cells could be described by a Lévy random walk. In this work, by considering a Lévy distribution for the displacements, we propose a space fractional-order diffusion equation for the T cell density in the infected brain tissue. Furthermore, we derive a mathematical model representing CD8+ T cell response to infected brain cells. By solving the model equations numerically, we perform a comparison between Lévy and Brownian search strategies. we demonstrate that the Lévy search pattern enables CD8+ T cells to spread over the whole brain tissue and hence they can rapidly destroy infected cells distributed throughout the brain tissue. However, with the Brownian motion assumption, CD8+ T cells travel through the brain tissue more slowly, leading to a slower decline of the infected cells faraway from the source of T cells. Our results show that a Lévy search pattern aids CD8+ T cells in accelerating the elimination of infected cells distributed broadly within the brain tissue. We suggest that a Lévy search strategy could be the result of natural evolution, as CD8+ T cells learn t

Ouvrir son robinet et se servir un verre d'eau, prendre une douche, ou encore laver son linge… Des gestes anodins du quotidien dans les pays développés. Et si un jour on ne pouvait plus le faire aussi facilement ? Depuis le début du siècle, les organisations mondiales alertent : la majeure partie de la population mondiale sera soumise à une pénurie d’eau d’ici quelques années, en raison de l’accroissement démographique, mais surtout du réchauffement climatique, qui perturbe le cycle de l’eau. Cette ressource essentielle pour le monde vivant pourrait-elle venir à manquer ? Dans le cadre de son dossier "C’est pour demain", La Libre dresse un état des lieux.

Mineral elements bind to dissolved organic carbon (DOC) in permafrost soils, and this may contribute to the stabilisation or the degradation of organic carbon along the soil to river continuum. Permafrost thaw enlarges the pool of soil constituents available for soil to river transfer. The unknown is how changes in hydrology upon permafrost degradation affect the connection between soil-derived mineral element-bound DOC and headwater streams. Here, we study Al, Fe, Ca and DOC concentrations in water from a headwater stream at Eight Mile Lake, Alaska, USA (colloidal (0.22 µm–1 kDa) and truly dissolved (< 1 kDa) fractions) and in soil pore waters sampled across a gradient of permafrost degradation at the same location. We target the peak flow to base flow transition to show that there is a narrow window of mineral element-bound DOC colloid transport from soils to streams. We show that during spring thaw and maximum thaw there is an enhanced lateral transfer of mineral element-bound DOC colloids in extensively degraded sites compared to minimally degraded sites. This is explained by a more rapid response of hydrology at peak flow to base flow transition at degraded sites. Our results suggest that ongoing permafrost degradation and the associated response of soils to changing hydrology can be detected by targeting the composition and size of mineral element-DOC associations in soil waters and headwater streams during peak flow-baseflow transitions.

Phytolith carbon (C) sequestration plays a key role in mitigating global climate change at a centennial to millennial time scale. However, previous estimates of phytolith-occluded carbon (PhytOC) storage and potential in China's grasslands have large uncertainties mainly due to multiple data sources. This contributes to the uncertainty in predicting long-term C sequestration in terrestrial ecosystems using Earth System Models. In this study, we carried out an intensive field investigation (79 sites, 237 soil profiles [0–100 cm], and 61 vegetation assessments) to quantify PhytOC storage in China's grasslands and to better explore the biogeographical patterns and influencing factors. Generally, PhytOC production flux and soil PhytOC density in both the Tibetan Plateau and the Inner Mongolian Plateau had a decreasing trend from the Northeast to the Southwest. The aboveground PhytOC production rate in China's grassland was 0.48 × 106 t CO2 a–1, and the soil PhytOC storage was 383 × 106 t CO2. About 45% of soil PhytOC was stored in the deep soil layers (50–100 cm), highlighting the importance of deep soil layers for C stock assessments. Importantly, the Tibetan Plateau had the greatest contribution (more than 70%) to the PhytOC storage in China's grasslands. The results of multiple regression analysis indicated that altitude and soil texture significantly influenced the spatial distribution of soil PhytOC, explaining 78.1% of the total variation. Soil phytolith turnover time in China's grasslands was mainly controlled by climatic conditions, with the turnover time on the Tibetan Plateau being significantly longer than that on the Inner Mongolian Plateau. Our results offer more accurate estimates of the potential for phytolith C sequestration from ecological restoration projects in degraded grassland ecosystems. These estimates are essential to parameterizing and validating global C models.

Agriculture is an economic pillar for the least developed countries. When these regions host explosive volcanoes, a serious risk for agricultural production arises as crops endure various injuries from tephra fall. However, our knowledge of crop vulnerability to ashfall is still fragmentary and new information is needed in order to strengthen the capacities of governments, response and recovery organizations, communities and individuals to effectively anticipate, respond to and recover from the agricultural impacts of a volcanic eruption. In order to gain new insights into the factors that govern tephra impacts on crops, we collected the farmers’ perceptions of crop damage and production losses by tephra in 15 villages affected by the 1999-2014 eruptions of Tungurahua volcano, Ecuador. The level of tephra-induced damage depends highly on crop morphological characteristics and development stage; the timing of the latter is dependent, among other factors, on altitude. Using these observations, we illustrate how crop vulnerability fluctuates spatially and temporarily in the surveyed area. The study also reveals that fine tephra (< 63 µm) is more harmful to crops than tephra containing coarser particles. The farmers responded to the tephra hazard by favouring crops more resistant to tephra, a practice that has reduced crop diversity.

Purpose Simultaneously interacting rhizosphere processes determine emergent plant behaviour, including growth, transpiration, nutrient uptake, soil carbon storage and transformation by microorganisms. However, these processes occur on multiple scales, challenging modelling of rhizosphere and plant behaviour. Current advances in modelling and experimental methods open the path to unravel the importance and interconnectedness of those processes across scales. Methods We present a series of case studies of state-of-the art simulations addressing this multi-scale, multi-process problem from a modelling point of view, as well as from the point of view of integrating newly available rhizosphere data and images. Results Each case study includes a model that links scales and experimental data to explain and predict spatial and temporal distribution of rhizosphere components. We exemplify the state-of-the-art modelling tools in this field: image-based modelling, pore-scale modelling, continuum scale modelling, and functional-structural plant modelling. We show how to link the pore scale to the continuum scale by homogenisation or by deriving effective physical parameters like viscosity from nano-scale chemical properties. Furthermore, we demonstrate ways of modelling the links between rhizodeposition and plant nutrient uptake or soil microbial activity. Conclusion Modelling allows to integrate new experimental data across different rhizosphere processes and scales and to explore more variables than is possible with experiments. Described models are tools to test hypotheses and consequently improve our mechanistic understanding of how rhizosphere processes impact plant-scale behaviour. Linking multiple scales and processes including the dynamics of root growth is the logical next step for future research.

This article aims at investigating the hidden Markov model (HMM) approach for the automated processing of classified satellite images for land cover and land-use change (LCLUC). HMM’s account for transitions between classes at the same location, but that cannot be directly observed due to classification errors. Using a set of transition and emission probabilities, HMM’s allow filtering out errors and recovering the actual sequence of LCLUC, which are typically overestimated when directly estimated from the classified images. After presenting the HMM framework, the methodology is illustrated on three 300-m annual time series of classified images from 2003 to 2019 over 756 × 756 km2 areas in Brazil, People’s Republic of China, and Mali. It is shown how the emission and transition probabilities can be estimated from these time series using a simple Viterbi training, alleviating computationally demanding algorithms. Special attention is paid to the processing of missing observations caused by clouds. Combining these three datasets with a simulation study, it is concluded that the HMM emission and transition probabilities can be estimated with low biases and variances thanks to the vast number (hundreds of thousands) of pixels at hand. The speed of the Viterbi training and decoding steps makes it possible to consider large-scale land cover mapping at moderate or even high spatial resolution as long as the legend of the LCLUC involves a reasonable number of classes like the six main Intergovernmental Panel on Climate Change (IPCC)land categories.

Aim Soil microorganisms are essential for the functioning of terrestrial ecosystems. Although soil microbial communities and functions are linked to tree species composition and diversity, there has been no comprehensive study of the generality or context dependence of these relationships. Here, we examine tree diversity–soil microbial biomass and respiration relationships across environmental gradients using a global network of tree diversity experiments. Location Boreal, temperate, subtropical and tropical forests. Time period 2013. Major taxa studied Soil microorganisms. Methods Soil samples collected from 11 tree diversity experiments were used to measure microbial respiration, biomass and respiratory quotient using the substrate-induced respiration method. All samples were measured using the same analytical device, method and procedure to reduce measurement bias. We used linear mixed-effects models and principal components analysis (PCA) to examine the effects of tree diversity (taxonomic and phylogenetic), environmental conditions and interactions on soil microbial properties. Results Abiotic drivers, mainly soil water content, but also soil carbon and soil pH, significantly increased soil microbial biomass and respiration. High soil water content reduced the importance of other abiotic drivers. Tree diversity had no effect on the soil microbial properties, but interactions with phylogenetic diversity indicated that the effects of diversity were context dependent and stronger in drier soils. Similar results were found for soil carbon and soil pH. Main conclusions Our results indicate the importance of abiotic variables, especially soil water content, for maintaining high levels of soil microbial functions and modulating the effects of other environmental drivers. Planting tree species with diverse water-use strategies and structurally complex canopies and high leaf area might be crucial for maintaining high soil microbial biomass and respiration. Given that gr

Mapping crop within-field yield variability provide an essential piece of information for precision agriculture applications. Leaf Area Index (LAI) is an important parameter that describes maize growth, vegetation structure, light absorption and subsequently maize biomass and grain yield (GY). The main goal for this study was to estimate maize biomass and GY through LAI retrieved from hyperspectral aerial images using a PROSAIL model inversion and compare its performance with biomass and GY estimations through simple vegetation index approaches. This study was conducted in two separate maize fields of 12 and 20 ha located in north-west Mexico. Both fields were cultivated with the same hybrid. One field was irrigated by a linear pivot and the other by a furrow irrigation system. Ground LAI data were collected at different crop growth stages followed by maize biomass and GY at the harvesting time. Through a weekly/biweekly airborne flight campaign, a total of 19 mosaics were acquired between both fields with a micro-hyperspectral Vis-NIR imaging sensor ranging from 400 to 850 nanometres (nm) at different crop growth stages. The PROSAIL model was calibrated and validated for retrieving maize LAI by simulating maize canopy spectral reflectance based on crop-specific parameters. The model was used to retrieve LAI from both fields and to subsequently estimate maize biomass and GY. Additionally, different vegetation indices were calculated from the aerial images to also estimate maize yield and compare the indices with PROSAIL based estimations. The PROSAIL validation to retrieve LAI from hyperspectral imagery showed a R2 value of 0.5 against ground LAI with RMSE of 0.8 m2/m2. Maize biomass and GY estimation based on NDRE showed the highest accuracies, followed by retrieved LAI, GNDVI and NDVI with R2 value of 0.81, 0.73, 0.73 and 0.65 for biomass, and 0.83, 0.69, 0.73 and 0.62 for GY estimation, respectively. Furthermore, the late vegetative growth stage at V16 was found

Between 60 and 90% of terrestrial precipitations go back to the atmosphere through plant transpiration stream and this huge flux is controlled by plant stomata. Yet, stomatal functioning is not fully understood and there is no consensus on a universal model for stomatal regulation. Recent studies have hypothesized that there is an intimate relationship between the hydraulics of the soil-plant continuum and the stomatal response to drought. It has been shown in silico that it is the drop in rhizosphere hydraulic conductance that is the main driver of leaf water potential decrease that leads to stomatal closure to protect the plant against cavitation. The soil conductance would be one of the first factors limiting the transfer of water to the plant under conditions of water deficit. On the other hand, physiologists have demonstrated that the stomatal regulation could differ between plant species and genotypes due to different sensitivities of stomata to chemical or hydraulic signals and have classified plant stomatal regulation into iso- or anisohydric regulation classes. In this project, we hypothesize that the degree of anisohydricity will be a function of the environment. The objective of this research is to elucidate the impact of soil hydraulics on plant transpiration regulation under drought. Two main experiments will be conducted on two genotypes of Zea mays L. with contrasted stomatal behavior. First, we will use small pressure ecotron to characterize the relationship between leaf potential, soil potential and transpiration from different combinations of vapor pressure deficit and soil hydric status (without any stomatal control). Then, we will perform a series of pot experiments with similar combinations of VPD and soil conditions to characterize the stomatal control and link it with the shape of the soil-plant conductance obtained from pressure ecotron. Finally, we will aim to validate our hypothesis that the degree of iso/anisohydricity is a function of the

Transfer of trace elements from soil to plant is a corner stone for risk assessment. Rare earth elements (REE) are frequently used as geochemical tracers for element transfer to plant. In this study, we evaluated biogeochemical behaviors of trace elements and REE in the soil–plant continuum to assess to what extend the REE monitoring allows identifying preferential pathway from soil to plant. We quantified 11 trace elements and 14 REE in soil, root, shoot, soil solution, and soil water-extract samples of an intercropping cover crop. Evaluation of the element mobility was performed using both soil extractability and transfer factors. Results showed distinct soil–plant transfer of trace elements according to their biological roles or substitution potential. Soil, root, and shoot REE patterns were similar, indicating a large influence of soil REE composition on plant one. Compared to light REE (LREE), heavy REE (HREE) were more extractable and thus transferred to plants. We also observed differences in Ce and Eu behavior concerning soil extractability and transfer from root to shoot. Soil solution and soil water-extract samples are not chemically representative of the fraction that can be uptaken by plants. However, LREE/HREE and Ce/Eu ratios in soil solution and soil water-extract samples can be used as indicators of environmental conditions.

Glyphosate is among the most broadly used herbicides around the world and has become controversial due to human health risks. In addition to its well-known herbicidal function, glyphosate has the capacity to chelate trace elements. Yet, agricultural soils may be contaminated by trace elements to various degrees raising the question of a possible enhancement of their mobility because of glyphosate and his major degradation product aminomethylphosphonic acid (AMPA). The potentially enhanced extractability of trace elements with glyphosate and AMPA has been studied by batch experiments where the trace elements are extracted from the soil (transferred from soil to solution) using an extracting solution containing an active substance. In our study, four agricultural soils have been selected: one soil is uncontaminated, two soils are anthropogenically contaminated, and the last one is naturally contaminated. While glyphosate enhanced the extractability of many elements (Cu, As, Zn, Cd…), AMPA mainly enhanced the extractability of As and decreased the mobility of other elements (Ba, Zn, Sn). Results depend on the considered soil and active substance concentration. Results also show that the commercial glyphosate-based pesticide is leading to a higher extractability of the trace elements than glyphosate alone in all soils except the uncontaminated one. Thus, glyphosate can be considered as a possible cause of the increase of trace element mobility, especially in the top layers where pesticide concentrations can be relatively high.

Theoretical studies have shown that the use of simultaneous mono- and bistatic synthetic aperture radar (SAR) data could be beneficial to agriculture and soil moisture monitoring. This study makes use of extensive ground-truth measurements and synchronous high-resolution fully polarimetric mono- and bistatic airborne SAR data in L-band to assess and compare the sensitivity of mono- and multistatic systems to the maize canopy row structure and biophysical variables, as well as to soil moisture, and surface roughness in both vegetated and bare fields. The effect of the row structure of maize crops is assessed through the impact of the orientation of the planting rows relative to the sensor beam on microwave scattering measurements. The results of this analysis suggest that the row orientation of maize crops has a significant influence on both mono- and bistatic scattering measurements in both co-polarizations, and especially in HH, while the cross-polarizations are not affected. Furthermore, the study also shows through a linear regression analysis that bistatic data, even with a very small bistatic baseline, can provide valuable additional information for maize crop biophysical variable retrieval, which however does not appear to be the case for soil moisture retrieval over bare soils.

The interest in bistatic SAR systems for soil moisture monitoring has grown over recent years, since theoretical studies suggest that the impact of surface roughness on the retrieval of soil moisture decreases when multistatic, i.e., simultaneous mono- and bistatic, radar measurements are used. This paper presents a semi-empirical method to retrieve soil moisture over bare agricultural fields, based on effective roughness modeling, and applies it to a series of L-band fully-polarized SAR backscatter and bistatic scattering observations. The main advantage of using effective roughness parameters is that surface roughness no longer needs to be measured in the field, what is known to be the main source of error in soil moisture retrieval applications. By means of cross-validation, it is shown that the proposed method results in accurate soil moisture retrieval with an RMSE well below 0.05 m3/m3, with the best performance observed for the cross-polarized backscatter signal. In addition, different experimental SAR monostatic and bistatic configurations are evaluated in this study using the proposed retrieval technique. Results illustrate that the soil moisture retrieval performance increases by using backscatter data in multiple polarizations simultaneously, compared to the case where backscatter observations in only one polarization mode are used. Furthermore, the retrieval performance of a multistatic system has been evaluated and compared to that of a traditional monostatic system. The recent BELSAR campaign (in 2018) provides time-series of experimental airborne SAR measurements in two bistatic geometries, i.e., the across-track (XTI) and along-track (ATI) flight configuration. For both configurations, bistatic observations are available in the backward region. The results show that the simultaneous use of backscatter and bistatic scattering data does not result in a profound increase in retrieval performance for the bistatic configuration flown during BELSAR 2018. A

While the impacts of forest management options on carbon (C) storage are well documented, the way they affect C distribution among ecosystem components remains poorly investigated. Yet, partitioning of total forest C stocks, particularly between aboveground woody biomass and the soil, greatly impacts the stability of C stocks against disturbances in forest ecosystems. This study assessed the impact of species composition and stand density on C storage in aboveground woody biomass (stem + branches), coarse roots, and soil, and their partitioning in pure and mixed forests in Europe. We used 21 triplets (5 beech-oak, 8 pine-beech, 8 pine-oak mixed stands, and their respective monocultures at the same sites) in seven European countries. We computed biomass C stocks from total stand inventories and species-specific allometric equations, and soil organic C data down to 40 cm depth. On average, the broadleaved species stored more C in aboveground woody biomass than soil, while C storage in pine was equally distributed between both components. Stand density had a strong effect on C storage in tree woody biomass but not in the soil. After controlling for stand basal area, the mixed stands had, on average, similar total C stocks (in aboveground woody biomass + coarse roots + soil) to the most performing monocultures. Although species composition and stand density affect total C stocks and its partitioning between aboveground woody biomass and soil, a large part of variability in soil C storage was unrelated to stand characteristics.

For a conventional potato crop, splitting nitrogen (N) application is recognised as an efficient strategy to improve tuber yield and quality and to mitigate N losses to the environment. This approach requires the assessment of in-season crop N status for decisions on supplemental mineral N fertiliser application. This study focuses on the assessment of potato crop biophysical variables useful to establish crop N status. Field, satellite and meteorological data were collected in farmer’s fields during 3 years (2017– 2019) with contrasted meteorological conditions. Degree days (DD) and water balance from planting date were computed from meteo data, and a selection of relevant vegetation indices (VIs) was derived from Sentinel-2 reflectance. Multiple linear regression (MLR) and random forest regression (RFR) models predicting shoots biomass, shoots N content and shoots N uptake from a combination of meteo and/or satellite-based variables were defined and evaluated. The best combinations integrate DD and two to four VIs and perform with cross-validation RMSE of about 0.38 DM t ha−1, 0.41%, 21 kg ha−1 for MLR and 0.32 DM t ha−1, 0.31%, 19 kg ha−1 for RFR. Despite these performances, MLR was shown to be more robust. From these estimated variables, two methods are proposed to derive total N uptake and nitrogen nutrition index. The most relevant method uses shoots N uptake and biomass. It allows future estimation of in-season supplemental N fertiliser to be applied to reach a targeted tuber yield.

The productivity of ecosystems and their capacity to support life depends on access to reactive nitrogen (N). Over the past century, humans have more than doubled the global supply of reactive N through industrial and agricultural activities. However, long-term records demonstrate that N availability is declining in many regions of the world. Reactive N inputs are not evenly distributed, and global changes—including elevated atmospheric carbon dioxide (CO2) levels and rising temperatures—are affecting ecosystem N supply relative to demand. Declining N availability is constraining primary productivity, contributing to lower leaf N concentrations, and reducing the quality of herbivore diets in many ecosystems. We outline the current state of knowledge about declining N availability and propose actions aimed at characterizing and responding to this emerging challenge.

Compte tenu de leurs impacts négatifs sur l'environnement et la santé, de plus en plus de pesticides sont interdits chaque année. Pourtant, la quantité totale de pesticides utilisés en Belgique n'a pas diminué de manière significative au cours de la dernière décennie (SPW, 2022). Dans la province de Luxembourg, un nombre croissant de prairies permanentes sont converties en cultures, augmentant la quantité totale de pesticides et les surfaces concernées par l'utilisation de pesticides, faisant du thème de la réduction de l'utilisation des pesticides un sujet d'actualité pour l'autorité politique provinciale. Dans cette thèse, nous étudions le rôle des pesticides et leur importance dans le système agroalimentaire à trois niveaux ontologiques (réductionnisme vs. holisme) et épistémologiques (objectivisme vs. relativisme) différents (Bawden, 1997) : (1) à un niveau technocentrique (objectivisme et réductionnisme) nous quantifions les résidus de pesticides dans les sols agricoles à l'échelle de la parcelle, (2) à un niveau écocentrique (objectivisme et holisme) nous étudions l'(arché)tyologie de la diversité des pratiques de succession des pesticides et des cultures, et (3) à un niveau holocentrique (relativisme et holisme) nous analysons le rôle des pesticides dans le système agricole et les verrous de réduction de l'utilisation des pesticides à l'échelle du territoire de la Province du Luxembourg. En adoptant le cadre du Farming System Research (Darnhofer et al., 2012), nous espérons élever le débat actuel sur les pesticides d'un large agribashing à une reconnaissance du besoin de transitions systémiques considérant un panel d'acteurs beaucoup plus large que les seuls agriculteurs. Traduit avec www.DeepL.com/Translator (version gratuite)

We investigate the potential of causal inference methods (CIMs) to reveal hydrological connections from time series. Four CIMs are selected from two criteria, linear or nonlinear and bivariate or multivariate. A priori, multivariate, and nonlinear CIMs are best suited for revealing hydrological connections because they fit nonlinear processes and deal with confounding factors such as rainfall, evapotranspiration, or seasonality. The four methods are applied to a synthetic case and a real karstic case study. The synthetic experiment confirms our expectation: unlike the other methods, the multivariate nonlinear framework has a low false-positive rate and allows for ruling out a connection between two disconnected reservoirs forced with similar effective precipitation. However, for the real case study, the multivariate nonlinear method was unstable because of the uneven distribution of missing values affecting the final sample size for the multivariate analyses, forcing us to cope with the results' robustness. Nevertheless, if we recommend a nonlinear multivariate framework to reveal actual hydrological connections, all CIMs bring valuable insights into the system's dynamics, making them a cost-effective and recommendable comparative tool for exploring data. Still, causal inference remains attached to subjective choices, operational constraints, and hypotheses challenging to test. As a result, the robustness of the conclusions that the CIMs can draw always deserves caution, especially with real, imperfect, and limited data. Therefore, alongside research perspectives, we encourage a flexible, informed, and limit-aware use of CIMs without omitting any other approach that aims at the causal understanding of a system.

Climate change affects the Arctic and sub-Arctic regions by exposing previously frozen permafrost to thaw, unlocking soil nutrients, changing hydrological processes, and boosting plant growth. As a result, sub-Arctic tundra is subject to a shrub expansion, called “shrubification”, at the expense of sedge species. Depending on the intrinsic foliar properties of these plant species, changes in foliar mineral element fluxes with shrubification in the context of permafrost degradation may influence topsoil mineral element composition. Despite the potential implications of changes in topsoil mineral element concentrations for the fate of organic carbon, this remains poorly quantified. Here, we investigate vegetation foliar and topsoil mineral element composition (Si, K, Ca, P, Mn, Zn, Cu, Mo, V) across a natural gradient of permafrost degradation at a typical sub-Arctic tundra at Eight Mile Lake (Alaska, USA). Results show that foliar mineral element concentrations are higher (up to 9 times; Si, K, Mo for all species, and for some species Zn) or lower (up to 2 times; Ca, P, Mn, Cu, V for all species, and for some species Zn) in sedge than in shrub species. As a result, a vegetation shift over ~40 years has resulted in lower topsoil concentrations in Si, K, Zn, and Mo (respectively of 52, 24, 20, and 51%) in highly degraded permafrost sites compared to poorly degraded permafrost sites due to lower foliar fluxes of these elements. For other elements (Ca, P, Mn, Cu, and V), the vegetation shift has not induced a marked change in topsoil concentrations at this current stage of permafrost degradation. A modeled amplified shrubification associated with a further permafrost degradation is expected to increase foliar Ca, P, Mn, Cu, and V fluxes, which will likely change these element concentrations in topsoil. These data can serve as a first estimate to assess the influence of other shifts in vegetation in Arctic and sub-Arctic tundra such as sedge expansion under wetter soil co

Various efforts to reverse the increasing concentration of nitrates and pesticides in our groundwaters such as the Programme de Gestion Durable de l’Azote (PGDA) have been implemented in Wallonia (Belgium), driven by the EU Nitrates Directive (91/676/CEE), the Water Framework Directive (2000/60/EC) and the Groundwater Directive (2006/118/EC). The effects of these efforts on groundwater quality are complex to assess because of the non-linearity and the spatial heterogeneity of the hydrological fluxes, the numerous potential pollution sources, and the temporal delays due to the infiltration time in the vadose zone. The objective of our research is to define the environmental and anthropogenic factors affecting the effectiveness of the regulations and management practices. We use the monitoring data of 52 groundwater wells and galleries to assess the evolution of nitrate and pesticide concentration in four different water bodies. We use as indicators the contamination levels before and after the introduction of regulations and good management practices, as well as the actual trend. We then seek to predict these indicators and explain their variability by looking into characteristics which could support or undermine the regulations and good practices such as water depth, soil type, crop area or urban development. Our results should contribute to a better understanding and prediction of the groundwater quality trends at the catchment scale in Wallonia, providing guidance to catchment management.

Arctic warming and permafrost degradation are modifying northern ecosystems through changes in microtopography, soil water dynamics, nutrient availability, and vegetation succession. Upon permafrost degradation, the release of deep stores of nutrients, such as nitrogen and phosphorus, from newly thawed permafrost stimulates Arctic vegetation production. More specifically, wetter lowlands show an increase in sedges (as part of graminoids), whereas drier uplands favor shrub expansion. These shifts in the composition of vegetation may influence local mineral element cycling through litter production. In this study, we evaluate the influence of permafrost degradation on mineral element foliar stocks and potential annual fluxes upon litterfall. We measured the foliar elemental composition (Al, Ca, Fe, K, Mn, P, S, Si, and Zn) of ∼ 500 samples of typical tundra plant species from two contrasting Alaskan tundra sites, i.e., an experimental sedge-dominated site (Carbon in Permafrost Experimental Heating Research, CiPEHR) and natural shrub-dominated site (Gradient). The foliar concentration of these mineral elements was species specific, with sedge leaves having relatively high Si concentration and shrub leaves having relatively high Ca and Mn concentrations. Therefore, changes in the species biomass composition of the Arctic tundra in response to permafrost thaw are expected to be the main factors that dictate changes in elemental composition of foliar stocks and maximum potential foliar fluxes upon litterfall. We observed an increase in the mineral element foliar stocks and potential annual litterfall fluxes, with Si increasing with sedge expansion in wetter sites (CiPEHR), and Ca and Mn increasing with shrub expansion in drier sites (Gradient). Consequently, we expect that sedge and shrub expansion upon permafrost thaw will lead to changes in litter elemental composition and therefore affect nutrient cycling across the sub-Arctic tundra with potential implications for fur

Over the last decades, various regulations and good management practices have been implemented to reverse the increasing concentration of nitrates and pesticides in our groundwaters. The effects of these efforts on groundwater quality are complex to assess because of the non-linearity and the spatial heterogeneity of the hydrological fluxes, the numerous potential pollution sources, and the temporal delays due to the infiltration time in the vadose zone. We use the information encoded in the monitoring data of 52 groundwater wells and galleries in Wallonia (Belgium) to assess the effectiveness of the regulations and management practices. We analyze the trends of the time series and subsequently seek to explain their spatial and temporal variability by looking into the characteristics likely to support or undermine the regulations and good practices such as water depth or urban development. Our results should contribute to a better understanding and prediction of the groundwater quality trends at the catchment scale in Wallonia, providing guidance to catchment management.

Dissolved organic matter is a key compartment for biogeochemical cycles in the Arctic and Subarctic terrestrial environments. With changing vegetation ecosystems, the chemical composition of organic matter is expected to shift and thus, the most labile part of it, namely the extractable fraction. To this date, few studies have focused on the fingerprinting of DOM fraction from different primary sources, and even less on its potential repercussions on the environment. In this study, we jointly characterized the chemical composition of bulk and water-extractable organic matter (WEOM) from different vegetation species typical of Subarctic ecosystems. Through a multi-analyses approach, including elementary analysis, solid state 13C nuclear magnetic resonance, UV and 3D fluorescence spectroscopy, and high-resolution mass spectrometry, our results highlighted that the quantity and composition of produced WEOM significantly differed between vegetation sources and specifically between plant functional types (PFT, e.g., lichens, graminoids, and trees and shrubs). The relevance of optical indices was questioned, and the use of several of them was discarded for unprocessed WEOM study. However, the DOM proxies (optical indices, molecular composition, and stoichiometry) enabled to conclude that the lichen WEOM was likely less degradable than vascular plants WEOM, and among the latter group, graminoids produced more degradable WEOM than trees and shrubs. This work reported specific organic fingerprints for the different PFT. Consequently, the ongoing changes of vegetation in Arctic and Subarctic regions may greatly affect the composition of DOM that enters the soil and the hydrosystems, as well as the biogeochemical processes it is involved in.