Is scuba sampling a relevant method to study microhabitat in lakes? Examples and comparisons for three European species

We compared fish microhabitat use patterns in the littoral zone of a lake using a new direct method (i.e. Point Abundance Sampling by Scuba, PASS) and the widely used Point Abundance Sampling by Electrofishing technique (PASE). We collected microhabitat data for age 0+ roach (Rutilus rutilus L.), perch (Perca fluviatilis L.), and pike (Esox lucius L.). The two methods yelded different results for fish assemblage structure and microhabitat patterns. Using PASE, fish were mainly found in "shelter habitats" such as shallow waters and dense vegetation. It is likely that this behaviour is caused by the disturbance of the observer stamping around. Using PASS, fish escapement behaviour was rarely observed. Therefore, we concluded that this direct and non-destructive sampling technique is able to provide an accurate microhabitat estimation of a fish community and is assumed to be more suitable than PASE for fish habitat studies

Flood mapping in vegetated areas using an unsupervised clustering approach on Sentinel-1 and-2 imagery

The European Space Agency's Sentinel-1 constellation provides timely and freely available dual-polarized C-band Synthetic Aperture Radar (SAR) imagery. The launch of these and other SAR sensors has boosted the field of SAR-based flood mapping. However, flood mapping in vegetated areas remains a topic under investigation, as backscatter is the result of a complex mixture of backscattering mechanisms and strongly depends on the wave and vegetation characteristics. In this paper, we present an unsupervised object-based clustering framework capable of mapping flooding in the presence and absence of flooded vegetation based on freely and globally available data only. Based on a SAR image pair, the region of interest is segmented into objects, which are converted to a SAR-optical feature space and clustered using K-means. These clusters are then classified based on automatically determined thresholds, and the resulting classification is refined by means of several region growing post-processing steps. The final outcome discriminates between dry land, permanent water, open flooding, and flooded vegetation. Forested areas, which might hide flooding, are indicated as well. The framework is presented based on four case studies, of which two contain flooded vegetation. For the optimal parameter combination, three-class F1 scores between 0.76 and 0.91 are obtained depending on the case, and the pixel- and object-based thresholding benchmarks are outperformed. Furthermore, this framework allows an easy integration of additional data sources when these become available

Land Use as a Predictor of Water Hyacinth (Eichhornia crassipes) Presence on the Entebbe Coast of Lake Victoria, Uganda

Lake Victoria is shared amongst Tanzania, Kenya, and Uganda and has tremendous ecological, economical, and cultural significance. Within the lake system, there are several problems, including the proliferation of an invasive weed, water hyacinth (Eichhornia crassipes). Therefore, this study aims to assess several factors that may correlate with water hyacinth proliferation. The specific objectives are (1) to identify possible correlations of water hyacinth density and land use around Entebbe, Uganda, and (2) to identify annual trends in water hyacinth coverage, to better inform policy and conservation efforts. Entebbe has a coastline of six land cover types: flooded vegetation, trees, grasses, shrub/scrub, crops, and built area. It was hypothesized that coastal areas adjacent to agriculture have a higher density of water hyacinth due to agricultural nutrient runoffs and flooded vegetation and built areas have higher abundances of water hyacinth due to a high amount of waste. The first specific objective employed a systematic sampling method, counting 41,615 water hyacinth around the coast of Entebbe, and was compared in QGIS with Sentinel-2 land use/land cover satellite imagery. The second specific objective employed remote sensing with a normalized difference vegetation index (NDVI). Twelve eMODIS satellite images were created on QGIS to map the percent coverage of water hyacinth in the Ugandan part of Lake Victoria. Flooded vegetation was found to have the highest density of water hyacinth, followed by crops, trees, built area, grass, and scrub/shrub. Additionally, 94% of water hyacinth was found on the left side of Entebbe. The most intense water hyacinth blooms occurred during June and July reaching 10.7% coverage, following the rainy season and maximumannual temperatures. The high densities within flooded vegetation and croplands are likely due to organic pollution runoffs. These results support previous research which found high temperatures and eutrophication to cause water hyacinth proliferation. This study theorizes that several unknown factors cause water hyacinth proliferation and thus control solely through mechanical, chemical, and biological means is treating a symptom, not the cause. Future research can explore this, adding to this study’s sample size, analyzing the different water dynamics for each land cover type, and further assessing the observation that water hyacinth presence may act as an indicator of organic pollution runoff

Integrating fish resources to agro-ecosystem analyses

In October 2005, a consortium of partners led by the International Water Management Institute (IWMI) proposed a project aimed at integrating fish resources management in agricultural management in the Tonle Sap area. This 2-years project assistance was accepted for funding by the Challenge Program on Water and Food and started in January 2008. The overall goal of this project is to improve allocation and use of water in combined farming and fishing systems in order to enhance food security of rural communities and water productivity. The general objectives of the Fisheries component are: 1) to contribute to the review of existing fisheries and aquaculture information, assessment and data collection systems and existing databases from a fisheries perspective 2) to determine key questions that could be asked at the commune level that would enable the identification of fisheries issues for different agroecosystem zones. These would include both threats and potential threats to fisheries based on key ecological variables and opportunities that fisheries and aquaculture could represent in local livelihoods.Research, Lake fisheries, Agropisciculture, Ecosystems, Analysis, Cambodia, Tonle Sap L.,

Automated wetland delineation from multi-frequency and muliti-polarized SAR Images in high temporal and spatial resolution

Water scarcity is one of the main challenges posed by the changing climate. Especially in semi-arid regions where water reservoirs are filled during the very short rainy season, but have to store enough water for the extremely long dry season, the intelligent handling of water resources is vital. This study focusses on Lac Bam in Burkina Faso, which is the largest natural lake of the country and of high importance for the local inhabitants for irrigated farming, animal watering, and extraction of water for drinking and sanitation. With respect to the competition for water resources an independent area-wide monitoring system is essential for the acceptance of any decision maker. The following contribution introduces a weather and illumination independent monitoring system for the automated wetland delineation with a high temporal (about two weeks) and a high spatial sampling (about five meters). The similarities of the multispectral and multi-polarized SAR acquisitions by RADARSAT-2 and TerraSAR-X are studied as well as the differences. The results indicate that even basic approaches without pre-classification time series analysis or post-classification filtering are already enough to establish a monitoring system of prime importance for a whole region

Detection of temporarily flooded vegetation using time series of dual polarised C-band synthetic aperture radar data

The intense research of the last decades in the field of flood monitoring has shown that microwave sensors provide valuable information about the spatial and temporal flood extent. The new generation of satellites, such as the Sentinel-1 (S-1) constellation, provide a unique, temporally high-resolution detection of the earth's surface and its environmental changes. This opens up new possibilities for accurate and rapid flood monitoring that can support operational applications. Due to the observation of the earth's surface from space, large-scale flood events and their spatiotemporal changes can be monitored. This requires the adaptation of existing or the development of new algorithms, which on the one hand enable precise and computationally efficient flood detection and on the other hand can process a large amounts of data. In order to capture the entire extent of the flood area, it is essential to detect temporary flooded vegetation (TFV) areas in addition to the open water areas. The disregard of temporary flooded vegetation areas can lead to severe underestimation of the extent and volume of the flood. Under certain system and environmental conditions, Synthetic Aperture Radar (SAR) can be utilized to extract information from under the vegetation cover. Due to multiple backscattering of the SAR signal between the water surface and the vegetation, the flooded vegetation areas are mostly characterized by increased backscatter values. Using this information in combination with a continuous monitoring of the earth's surface by the S-1 satellites, characteristic time series-based patterns for temporary flooded vegetation can be identified. This combination of information provides the foundation for the time series approach presented here. This work provides a comprehensive overview of the relevant sensor and environmental parameters and their impact on the SAR signal regarding temporary open water (TOW) and TFV areas. In addition, existing methods for the derivation of flooded vegetation are reviewed and their benefits, limitations, methodological trends and potential research needs for this area are identified and assessed. The focus of the work lies in the development of a SAR and time series-based approach for the improved extraction of flooded areas by the supplementation of TFV and on the provision of a precise and rapid method for the detection of the entire flood extent. The approach developed in this thesis allows for the precise extraction of large-scale flood areas using dual-polarized C-band time series data and additional information such as topography and urban areas. The time series features include the characteristic variations (decrease and/or increase of backscatter values) on the flood date for the flood-related classes compared to the whole time series. These features are generated individually for each available polarization (VV, VH) and their ratios (VV/VH, VV-VH, VV+VV). The generation of the time series features was performed by Z-transform for each image element, taking into account the backscatter values on the flood date and the mean value and standard deviation of the backscatter values from the nonflood dates. This allowed the comparison of backscatter intensity changes between the image elements. The time series features constitute the foundation for the hierarchical threshold method for deriving flood-related classes. Using the Random Forest algorithm, the importance of the time series data for the individual flood-related classes was analyzed and evaluated. The results showed that the dual-polarized time series features are particularly relevant for the derivation of TFV. However, this may differ depending on the vegetation type and other environmental conditions. The analyses based on S-1 data in Namibia, Greece/Turkey and China during large-scale floods show the effectiveness of the method presented here in terms of classification accuracy. Theiv supplementary integration of temporary flooded vegetation areas and the use of additional information resulted in a significant improvement in the detection of the entire flood extent. It could be shown that a comparably high classification accuracy (~ 80%) was achieved for the flood extent in each of study areas. The transferability of the approach due to the application of a single time series feature regarding the derivation of open water areas could be confirmed for all study areas. Considering the seasonal component by using time series data, the seasonal variability of the backscatter signal for vegetation can be detected. This allows for an improved differentiation between flooded and non-flooded vegetation areas. Simultaneously, changes in the backscatter signal can be assigned to changes in the environmental conditions, since on the one hand a time series of the same image element is considered and on the other hand the sensor parameters do not change due to the same acquisition geometry. Overall, the proposed time series approach allows for a considerable improvement in the derivation of the entire flood extent by supplementing the TOW areas with the TFV areas

Simple data analysis for biologists

This document provides a simple introduction to research methods and analysis tools for biologists or environmental scientists, with particular emphasis on fish biology in devleoping countries

Monitoring wetlands and water bodies in semi-arid Sub-Saharan regions

Surface water in wetlands is a critical resource in semi-arid West-African regions that are frequently exposed to droughts. Wetlands are of utmost importance for the population as well as the environment, and are subject to rapidly changing seasonal fluctuations. Dynamics of wetlands in the study area are still poorly understood, and the potential of remote sensing-derived information as a large-scale, multi-temporal, comparable and independent measurement source is not exploited. This work shows successful wetland monitoring with remote sensing in savannah and Sahel regions in Burkina Faso, focusing on the main study site Lac Bam (Lake Bam). Long-term optical time series from MODIS with medium spatial resolution (MR), and short-term synthetic aperture radar (SAR) time series from TerraSAR-X and RADARSAT-2 with high spatial resolution (HR) successfully demonstrate the classification and dynamic monitoring of relevant wetland features, e.g. open water, flooded vegetation and irrigated cultivation. Methodological highlights are time series analysis, e.g. spatio-temporal dynamics or multitemporal-classification, as well as polarimetric SAR (polSAR) processing, i.e. the Kennaugh elements, enabling physical interpretation of SAR scattering mechanisms for dual-polarized data. A multi-sensor and multi-frequency SAR data combination provides added value, and reveals that dual-co-pol SAR data is most recommended for monitoring wetlands of this type. The interpretation of environmental or man-made processes such as water areas spreading out further but retreating or evaporating faster, co-occurrence of droughts with surface water and vegetation anomalies, expansion of irrigated agriculture or new dam building, can be detected with MR optical and HR SAR time series. To capture long-term impacts of water extraction, sedimentation and climate change on wetlands, remote sensing solutions are available, and would have great potential to contribute to water management in Africa

Wetland Monitoring and Mapping Using Synthetic Aperture Radar

Wetlands are critical for ensuring healthy aquatic systems, preventing soil erosion, and securing groundwater reservoirs. Also, they provide habitat for many animal and plant species. Thus, the continuous monitoring and mapping of wetlands is necessary for observing effects of climate change and ensuring a healthy environment. Synthetic Aperture Radar (SAR) remote sensing satellites are active remote sensing instruments essential for monitoring wetlands, given the possibility to bypass the cloud-sensitive optical instruments and obtain satellite imagery day and night. Therefore, the purpose of this chapter is to provide an overview of the basic concepts of SAR remote sensing technology and its applications for wetland monitoring and mapping. Emphasis is given to SAR systems with full and compact polarimetric SAR capabilities. Brief discussions on the latest state-of-the-art wetland applications using SAR imagery are presented. Also, we summarize the current trends in wetland monitoring and mapping using SAR imagery. This chapter provides a good introduction to interested readers with limited background in SAR technology and its possible wetland applications