Field dataset of the depth to water from diverse wetland types in relation to habitat and soil.

Wetlands perform important functions and provide essential ecological services, including flood attenuation, groundwater recharge and discharge, and water purification. Human activities such as urban and rural development, drainage, and land alteration can cause major disturbances, often resulting in the drying up of wetlands. Therefore, many restoration projects aim to restore wetland hydrology. Hydrology significantly affects wetland functions by modifying and determining the wetlands physicochemical environment that allows for the development of a specific biota. Despite the importance of hydrology, monitoring efforts are mainly focused on surveying and characterizing wetland habitats or plant composition. There are few datasets available from the monitoring of the depth to water table (DTW) in wetlands and when available they are rarely shared. Collecting hydrological data can contribute to a better understanding of the relationship between hydrology, soil and habitat and can help understand the effect of climate change. From 2021 to 2023, depth to water table, soil and habitat data were collected across a variety of wetland types in France with a focus on hydrological data. Using data loggers placed in 37 monitoring wells across 17 wetlands, 469001 hourly depth to water table and water temperature data were collected. The dataset includes two files containing a total of 22 variables that describe the location of sites, habitat (EUNIS: European Nature Information System), soil hydromorphy, depth to water table, and water temperature. The dataset can be used to better understand wetland hydrology and its relationship to soil and habitat. The data collection process may be used to help restoration project achieve their goal.

A 5 m dataset of digital terrain model derivatives across mainland France.

A dataset of three digital terrain model (DTM) derivatives was produced at 5 m spatial resolution across mainland France. This dataset includes (i) a topographic wetness index (TWI) that characterizes potential soil wetness as a function of the contributing area and local slope, (ii) a multi-scale topographic position color composite (MTPCC) that describes the position of a pixel relative to its neighborhood at three spatial scales, and (iii) a vertical distance to channel network index (VDCNI) that expresses the vertical height between the elevation of a pixel and the nearest channel. These three raster layers were derived from the French national airborne DTM at 5 m spatial resolution and the vector layer of the channel network of the national hydrological database. This unprecedented fine-scale dataset opens new insights for geomorphological analysis. It can be used for several purposes, such as environmental modeling, risk assessment, or water-resource management.

National wetland mapping using remote-sensing-derived environmental variables, archive field data, and artificial intelligence.

While wetland ecosystem services are widely recognized, the lack of fine-scale national inventories prevents successful implementation of conservation policies. Wetlands are difficult to map due to their complex fine-grained spatial pattern and fuzzy boundaries. However, the increasing amount of open high-spatial-resolution remote sensing data and accurately georeferenced field data archives, as well as progress in artificial intelligence (AI), provide opportunities for fine-scale national wetland mapping. The objective of this study was to map wetlands over mainland France (ca. 550,000 km2) by applying AI to environmental variables derived from remote sensing and archive field data. A random forest model was calibrated using spatial cross-validation according to the precision-recall area under the curve (PR-AUC) index using ca. 135,000 soil or flora plots from archive databases, as well as 5 m topographical variables derived from an airborne DTM and a geological map. The model was validated using an experimentally designed sampling strategy with ca. 3000 plots collected during a ground survey in 2021 along non-wetland/wetland transects. Map accuracy was then compared to those of nine existing wetland maps with global, European, or national coverage. The model-derived suitability map (PR-AUC 0.76) highlights the gradual boundaries and fine-grained pattern of wetlands. The binary map is significantly more accurate (F1-score 0.75, overall accuracy 0.67) than existing wetland maps. The approach and end-results are of important value for spatial planning and environmental management since the high-resolution suitability and binary maps enable more targeted conservation measures to support biodiversity conservation, water resources maintenance, and carbon storage.

Field dataset of punctual observations of soil properties and vegetation types distributed along soil moisture gradients in France.

The interface between wetlands and uplands is characterized by gradients in hydrological, soil and biological components. Consequently, the exact spatial distribution of this transitional area is not well known because it often occurs as a fuzzy moisture gradient. However, ecological assessment and conservation require mapping and characterizing this interface to better understand and model biotic and abiotic interactions between wetlands and uplands. To this end, in 2021 and 2022, we observed soil properties and vegetation types along soil moisture gradients throughout the Atlantic, Continental, Mediterranean and Alpine biogeographic regions of France. The dataset contains 2 236 georeferenced plots (accuracy ± 5 m) distributed along 1 088 transects placed along the slope at 377 sites. Each plot in the database is characterized by 21 fields that describe the vegetation habitat type based on the European Nature Information System (EUNIS) and soil properties (i.e. depth of appearance and thickness of redoximorphic features in the soil profile, moisture). These data are useful for researchers and engineers in a variety of disciplines (e.g. Earth and life sciences) to calibrate and validate models to predict the spatial distribution of habitats or to analyze flows.

Annual use of man-made wetlands by the mute swan (Cygnus olor).

This is essential to understand habitat selection by wildlife to manage habitats and populations. Studying the annual use of aquatic habitats provides information on how to manage wetlands for waterfowl, and to predict possible detrimental effects associated with extended usage by these birds. This is particularly important for species like the mute swan (Cygnus olor Gmelin), given its recent dramatic demographic expansion, causing concern in both Europe and America. We studied the extent of usage (swan.days.ha(-1)) of habitat patches by mute swans in a heterogeneous and fluctuating fishpond landscape. We assessed seasonal differences of swan usage of fishponds, annual variation for a given fishpond, and determined which habitat factors drive swan usage over the year. The seasonal use pattern was regular: a similar proportion of fishponds was used heavily, moderately or lightly in all seasons. Flocking throughout the year and breeding during summer were associated with heavy use of fishponds, i.e. large number of swan.days.ha(-1). Flocking on some fishponds during several successive seasons demonstrated that some waterbody provide valuable habitats over time for swans. However, swans did not use individual fishponds to the same extent each season, mostly depending on the fluctuating ecological requirements of swans and variation in habitat properties. Agricultural practices on fishponds drastically affected swan usage during autumn and winter: formerly dried fishponds were used preferentially once reflooded. The specific agricultural crops used during the drought period had no influence though. The large-sized fishponds and fishponds within a dense network of waterbody were the most heavily used by swans throughout the year. Our results may thus be helpful to predict and prevent possible habitat damage by swans. They also provide information on habitats that are valuable for waterfowl species in general, by using mute swans as a proxy for waterfowl requirements.