Invertebrates are declining in boreal aquatic habitat : The effect of brownification?

Surface water browning affects boreal lakes in the Northern Hemisphere. This process is expected to increase with global warming. Boreal lakes are the most numerous lakes on Earth. These ecosystems are particularly sensitive to disturbances due to their low biodiversity compared to other aquatic environments. The recent darkening of surface water is expected to hinder key ecosystem processes, particularly through lower primary productivity and loss of biodiversity. However, studies based on long-term data collections have rarely been conducted on the ecological consequences of water browning on aquatic food webs, especially concerning its impacts on invertebrate communities. For the first time, our analysis based on two decades of data collection in Finnish lakes highlighted a relation between water browning and a decline in aquatic macroinvertebrate abundances. Aquatic invertebrates are the main food resource for many secondary predators such as fish and waterbirds, hence such effect on their populations may have major consequences for boreal ecosystem functioning.Peer reviewe

Invertebrates are declining in boreal aquatic habitat: the effect of brownification?

Surface water browning affects boreal lakes in the Northern Hemisphere. This process is expected to increase with global warming. Boreal lakes are the most numerous lakes on Earth. These ecosystems are particularly sensitive to disturbances due to their low biodiversity compared to other aquatic environments. The recent darkening of surface water is expected to hinder key ecosystem processes, particularly through lower primary productivity and loss of biodiversity. However, studies based on long-term data collections have rarely been conducted on the ecological consequences of water browning on aquatic food webs, especially concerning its impacts on invertebrate communities.For the first time, our analysis based on two decades of data collection in Finnish lakes highlighted a relation between water browning and a decline in aquatic macroinvertebrate abundances. Aquatic invertebrates are the main food resource for many secondary predators such as fish and waterbirds, hence such effect on their populations may have major consequences for boreal ecosystem functioning.</p

Ecology and extent of freshwater browning - What we know and what should be studied next in the context of global change

Water browning or brownification refers to increasing water color, often related to increasing dissolved organic matter (DOM) and carbon (DOC) content in freshwaters. Browning has been recognized as a significant physicochemical phenomenon altering boreal lakes, but our understanding of its ecological consequences in different freshwater habitats and regions is limited. Here, we review the consequences of browning on different freshwater habitats, food webs and aquatic-terrestrial habitat coupling. We examine global trends of browning and DOM/DOC, and the use of remote sensing as a tool to investigate browning from local to global scales. Studies have focused on lakes and rivers while seldom addressing effects at the catchment scale. Other freshwater habitats such as small and temporary waterbodies have been overlooked, making the study of the entire network of the catchment incomplete. While past research investigated the response of primary producers, aquatic invertebrates and fishes, the effects of browning on macrophytes, invasive species, and food webs have been understudied. Research has focused on freshwater habitats without considering the fluxes between aquatic and terrestrial habitats. We highlight the importance of understanding how the changes in one habitat may cascade to another. Browning is a broader phenomenon than the heretofore concentration on the boreal region. Overall, we propose that future studies improve the ecological understanding of browning through the following research actions: 1) increasing our knowledge of ecological processes of browning in other wetland types than lakes and rivers, 2) assessing the impact of browning on aquatic food webs at multiple scales, 3) examining the effects of browning on aquatic-terrestrial habitat coupling, 4) expanding our knowledge of browning from the local to global scale, and 5) using remote sensing to examine browning and its ecological consequences.</p

Suivi de la gestion des zones humides camarguaises par télédétection en référence à leur intérêt avifaunistique

In spite of the numerous functions and services they provide, wetlands are among the most threatened habitats in the world. The Camargue wetlands do not escape from the impacts of global changes and are increasingly managed to improving yield of agricultural and socio-economic activities. Remote sensing has long been considered as a promising complementary tool for wetland monitoring. Here we show that multi spectral and temporal data issued from high-resolution satellite images combined with a single field campaign permit a wetland follow-up that is replicable over time without re-sampling. We developed robust and reliable models to characterize the evolution of vegetation and flooded areas within marshes enclosing helophytes and hydrophytes, which are well-represented habitats supporting bird species of conservation or economic concern in the Camargue. We used two statistical approaches. The first one is qualitative and determines the presence of certain vegetation types and the presence of water in differing conditions of vegetation density. The second approach is quantitative and permits the monitoring of vegetation parameters that are associated with ecological requirements of vulnerable birds in reed marshes. These models will be most useful for proposing management practices conciliating the preservation and durable use of Mediterranean wetlands.Au rang des milieux naturels les plus menacés, les zones humides remplissent pourtant un grand nombre de fonctions utiles à l'homme. Les milieux naturels de Camargue n'échappent pas aux impacts des changements globaux et subissent une artificialisation croissante de leur gestion, motivée par l'intensification des pratiques agricoles et des usages socio-économiques. La télédétection a été présentée comme un outil complémentaire prometteur pour le monitoring des zones humides. Nous montrons dans cette étude qu'elle permet, aujourd'hui, grâce au mode multitemporel et multispectral des satellites de dernière génération, de s'affranchir d'un ré-échantillonnage jusque là nécessaire à la reproductibilité des méthodes traditionnelles. Pour deux habitats naturels dominants de Camargue abritant des populations d'oiseaux vulnérables ou à fort intérêt cynégétique, nous avons élaboré des formules fiables et reproductibles permettant de caractériser l'évolution de communautés végétales et d'obtenir une vision mensuelle des zones inondées sur l'ensemble du delta. La méthodologie employée se base sur deux types de méthodes statistiques. La première, qualitative, détermine la présence de groupements végétaux, puis de l'eau à travers une végétation plus ou moins dense. La seconde, quantitative, permet de suivre des paramètres déterminant la qualité et l'intérêt avifaunistique des roselières de Camargue. Les modèles élaborés dans cette étude seront d'une grande valeur pour proposer des modes de gestion adaptés aux objectifs de préservation et de développement durable des zones humides méditerranéennes

Space based tools to monitor the habitats of migratory waterbirds

International audienceNatural fluctuations in the availability of suitable habitat coupled with anthropogenic activities (hunting, agriculture, tourism, urbanism) and anticipated modifications due to climate change confront migratory waterbirds with a formidable challenge. Among them, dabbling ducks, greatly rely on local exogenous resources to fulfil their energy requirements. Habitat suitability along their flyway is of primary importance as any change might induce dramatic effects on individual survival and breeding success. Although, the monitoring of such sensitive flooded areas that are wetlands stopover sites is usually complex, space based techniques, with an exhaustive and systematic covering of the territory and a periodical data acquisition, can explore cost-efficiently the ecological conditions for migratory species in these environments. Hence, multiseason reflectance data from radiometrically and geometrically corrected multispectral SPOT-5 scenes, combined with thorough field campaigns and land cover digitizing using data mining, can provide robust tools for habitat monitoring and help the conservation of wetlands for migrants.</p

Les changements d’occupation et d’usage du sol, des processus multidimensionnels complexes qui affectent la biodiversité

International audienceDifférents exemples localisés en Afrique de l’Ouest montrent l’intérêt de combiner des approches des dimensions humaine et physique et des entrées par le paysage, c’est-à-dire en combinant les dimensions matérielle et sensible, pour approfondir l’analyse de l’occupation des sols et de leurs dynamiques d’évolution. Ils montrent aussi l’intérêt de l’analyse des changements à différentes échelles d’étude, et la nécessité de définir la résolution des données en adéquation avec l’objectif social ou écologique de l’analyse spatiale. Les conclusions qui diffèrent profondément de celles qui, par exemple, sont purement orientées par l’écologie de la conservation et habituellement énoncées sur les transformations des milieux et des paysages. Ces approches permettent de réaliser la distinction impérative entre usage et occupation des sols « remettant en cause les états de référence à travers une lecture dynamique des processus environnementaux », aidées en cela par l’utilisation combinée de données discrètes et continues, et ouvrant ainsi de nouvelles voies à la modélisation LULCC

Wetland monitoring using classification trees and SPOT-5 seasonal time series

International audienceMultiseason reflectance data from radiometrically and geometrically corrected multispectral SPOT-5 images of 10-m resolution were combined with thorough field campaigns and land cover digitizing using a binary classification tree algorithm to estimate the area of marshes covered with common reeds (Phragmites australis) and submerged macrophytes (Potamogeton pectinatus, P. pusillus, Myriophyllum spicatum, Ruppia maritima, Chara sp.) over an area of 145,000 ha. Accuracy of these models was estimated by cross-validation and by calculating the percentage of correctly classified pixels on the resulting maps. Robustness of this approach was assessed by applying these models to an independent set of images using independent field data for validation. Biophysical parameters of both habitat types were used to interpret the misclassifications. The resulting trees provided a cross-validation accuracy of 98.7% for common reed and 97.4% for submerged macrophytes. Variables discriminating reed marshes from other land covers were the difference in the near-infrared band between March and June, the Optimized Soil Adjusted Vegetation Index of December, and the Normalized Difference Water Index (NDWI) of September. Submerged macrophyte beds were discriminated with the shortwave-infrared band of December, the NDWI of September, the red band of September and the Simple Ratio index of March. Mapping validations provided accuracies of 98.6% (2005) and 98.1% (2006) for common reed, and 86.7% (2005) and 85.9% (2006) for submerged macrophytes. The combination of multispectral and multiseasonal satellite data thus discriminated these wetland vegetation types efficiently. Misclassifications were partly explained by digitizing inaccuracies, and were not related to biophysical parameters for reedbeds. The classification accuracy of submerged macrophytes was influenced by the proportion of plants showing on the water surface, percent cover of submerged species, water turbidity, and salinity. Classification trees applied to time series of SPOT-5 images appear as a powerful and reliable tool for monitoring wetland vegetation experiencing different hydrological regimes even with a small training sample (N=25) when initially combined with thorough field measurements

Reedbed monitoring using classification trees and SPOT-5 seasonal time series

International audienceThe Rhône river delta (Camargue) in south of France, has lost 40,000 ha of natural areas, including 33,000 ha of wetlands over the last 60 years, following the extension of agriculture, salt exploitation and industry. Reed development and density in Camargue marshes is influenced by physical factors such as salinity, water depth, and water level fluctuations, which have an effect on reflectance spectra. Classification trees applied to time series of SPOT-5 images appear as a powerful and reliable tool for monitoring wetland vegetation experiencing different hydrological regimes. The resulting tree provided a cross-validation accuracy of 98.7% and a mapping accuracy of 98.6% (2005) and 98.1% (2006). Misclassifications were partly explained by digitizing inaccuracies, and were not related to biophysical parameters of reedbeds. The resolution of SPOT-5 scenes provides an adequate scale for acquiring detailed field data within homogeneous stands, allowing to optimize the time spent for data collecting and to properly locate the sampled plots on the ground and on the scenes. Our results demonstrate that it is possible with a good field campaign to avoid repeated sampling for a long-term cost-efficient monitoring of reed marshes. The accuracy and reliability of our models provide a vision where the roles are reversed: the field campaigns become a complementary tool in wetland monitoring using satellite remote sensing

Ecological assessment of Phragmites australis wetlands using multi-season SPOT-5 scenes

International audienceEcologists and conservationists need accurate and replicable tools for monitoring wetland conditions in order to develop and implement adaptive management strategies efficiently. The Rhone Delta (Camargue) in southern France encloses 9200 ha of fragmented reed marshes actively managed for reed harvesting, waterfowl hunting or cattle grazing, and holding significant numbers of vulnerable European birds. We used multi-season SPOT-5 data in conjunction with ground survey to assess the predictive power of satellite imagery in modelling indicators of reed structure (height, diameter, density and cover of green/dry stems) relevant to ecosystem management and bird ecology. All indicators could be predicted accurately with a combination of bands (SWIR, NIR) and indices (SAVI, OSAVI, NDWI, DVI, DVW, MSI) issued from scenes of March, June, July, September or December and subtraction between these. All models were robust when validated with an independent set of satellite and field data. The high spatial resolution of SPOT-5 scenes (pixel of 10 × 10 m) permits the monitoring of detailed attributes characterizing the reed ecosystem across a large spatial extent, providing a scientifically-based, replicable tool for managers, stakeholders and decision-makers to follow wetland conditions in the short and long-term. Combined with models on the ecological requirements of vulnerable bird species, these tools can provide maps of potential species ranges at spatial extents that are relevant to ecosystem functioning and bird populations

Mapping flooding regimes in Camargue wetlands using seasonal multispectral data

International audienceReflectance data from multiseasonal SPOT-5 imagery was combined with monthly measures of water levels collected in the Rhône river delta (Camargue) in 2005 and 2006. Classification tree and regression models using monthly values of 17 multispectral indices and 4 bands, as well as their seasonal variations, were used for predicting the presence and levels of water, independently of vegetation type and density in shallow marshes. Accuracy of the classification model was estimated by cross-validation and by calculating the percentage of correctly classified pixels on the resulting maps using an independent sampling. Goodness-of-fit of the regression model was assessed by calculating the coefficient of correlation between predicted and observed values. Predictive accuracy of both models was estimated by calculating NRMSE for the independent validation sample. Regression model robustness was also tested using Scheffé post-hoc analyses on the residuals. Biophysical parameters of Camargue marsh vegetation were used to interpret misclassifications and model deficiency. Both models were composed of a single variable consisting of a multispectral index using the mid-infrared band. The resulting classification tree provided a cross-validation accuracy of 76% and a map validation accuracy of 83%. With an R = 0.5, the regression model predicted water level with a 6-cm precision up to 20 cm of water depth. For both approaches, the predictive power of model was most affected by close canopy. This study highlights the usefulness of data mining for long-term monitoring of wetland hydrology based on multispectral indices using the mid-infrared band