Methods of quantifying a mass mortality event in freshwater wildlife within the river ecosystem.

This study introduces a comprehensive method for quantifying mass mortality events in freshwater wildlife, exemplified by the ecological disaster in the Odra River in 2022. Our approach integrates field observations, statistical analysis, and ecological assessment to measure the impact of such events on various aquatic species. Key steps include systematic counting of deceased organisms, assessing population declines, and evaluating the ecological repercussions of invasive species. Utilizing the R programming language, we developed a framework that is adaptable to similar ecological crises in different aquatic environments. This methodology facilitates a detailed understanding of the scale and implications of mass mortality events, thereby contributing to effective environmental management and conservation efforts. •The analysis and modeling methods of the disaster are presented in the R programming language.•Exclusively open-source software was used for the analysis.•The analysis includes detailed data on the disaster's impact on various species.

A dataset on quantifying a mass mortality event in freshwater wildlife within the Lower Odra River.

In response to the significant ecological disaster in the Odra River during the summer of 2022, a comprehensive data collection process was initiated to quantify the extent of mortality among aquatic species. The dataset focuses on the downstream section of the river, identified as the area with the highest accumulation of deceased organisms. The data collection involved systematic sampling and counting of dead organisms, including fish, bivalves , and aquatic snails. Special attention was given to specific species such as Unionidae mussels, Anodonta anatina, Sinanodonta woodiana, and Viviparus viviparus. Additionally, transects were designated for focused data collection on fish mortality. The dataset provides detailed mortality figures, biomass estimates, and percentage reductions for each species. This comprehensive dataset holds significant potential for reuse by researchers studying the effects of toxins on freshwater ecosystems, the impact of invasive species on native populations, and conservationists aiming to restore the affected areas.

A general deep learning model for bird detection in high-resolution airborne imagery.

Advances in artificial intelligence for computer vision hold great promise for increasing the scales at which ecological systems can be studied. The distribution and behavior of individuals is central to ecology, and computer vision using deep neural networks can learn to detect individual objects in imagery. However, developing supervised models for ecological monitoring is challenging because it requires large amounts of human-labeled training data, requires advanced technical expertise and computational infrastructure, and is prone to overfitting. This limits application across space and time. One solution is developing generalized models that can be applied across species and ecosystems. Using over 250,000 annotations from 13 projects from around the world, we develop a general bird detection model that achieves over 65% recall and 50% precision on novel aerial data without any local training despite differences in species, habitat, and imaging methodology. Fine-tuning this model with only 1000 local annotations increases these values to an average of 84% recall and 69% precision by building on the general features learned from other data sources. Retraining from the general model improves local predictions even when moderately large annotation sets are available and makes model training faster and more stable. Our results demonstrate that general models for detecting broad classes of organisms using airborne imagery are achievable. These models can reduce the effort, expertise, and computational resources necessary for automating the detection of individual organisms across large scales, helping to transform the scale of data collection in ecology and the questions that can be addressed.

Drones, automatic counting tools, and artificial neural networks in wildlife population censusing.

The use of a drone to count the flock sizes of 33 species of waterbirds during the breeding and non-breeding periods was investigated.In 96% of 343 cases, drone counting was successful. 18.8% of non-breeding birds and 3.6% of breeding birds exhibited adverse reactions: the former birds were flushed, whereas the latter attempted to attack the drone.The automatic counting of birds was best done with ImageJ/Fiji microbiology software - the average counting rate was 100 birds in 64 s.Machine learning using neural network algorithms proved to be an effective and quick way of counting birds - 100 birds in 7 s. However, the preparation of images and machine learning time is time-consuming, so this method is recommended only for large data sets and large bird assemblages.The responsible study of wildlife using a drone should only be carried out by persons experienced in the biology and behavior of the target animals.

Effectiveness of the European Natura 2000 network to sustain a specialist wintering waterbird population in the face of climate change.

Analysis of coordinated Greater Scaup (Aythya marila) count data from the last 30 years showed a 38.1% decrease in wintering numbers in North-West Europe, from 309,000 during 1988-1991 to c.192,300 individuals during 2015-2018. Annual trends in wintering numbers differed throughout the range. Numbers decreased in the UK, Ireland, and in the Netherlands, while numbers were stable in Denmark. Germany, Poland, Sweden, and Estonia showed increasing numbers, suggesting a shift in the distribution of the species within its wintering grounds towards the east and north. Higher temperatures in northern and eastern areas were correlated with the range shift of the wintering distribution. Deaths from bycatch drowning of Scaup in fishing gear have significantly decreased in recent decades in the Netherlands, where currently the greatest threat is considered the deterioration of food resources. The increasing concentration of wintering Scaup in coastal Poland and Germany (where lack of effective implementation of conservation measures fail to protect the species from the impacts of bycatch and declining food quality) pose major threats to the entire population.

Waterbird counts on large water bodies: comparing ground and aerial methods during different ice conditions.

The aerial and ground methods of counting birds in a coastal area during different ice conditions were compared. Ice coverage of water was an important factor affecting the results of the two methods. When the water was ice-free, more birds were counted from the ground, whereas during ice conditions, higher numbers were obtained from the air. The first group of waterbirds with the smallest difference between the two methods (average 6%) contained seven species: Mute Swan Cygnus olor, Whooper Swan Cygnus cygnus, Greater Scaup Aythya marila, Tufted Duck Aythya fuligula, Common Goldeneye Bucephala clangula, Smew Mergellus albellus and Goosander Mergus merganser; these were treated as the core group. The second group with a moderate difference (average 20%) included another six species: Mallard Anas platyrhynchos, Eurasian Wigeon Mareca penelope, Common Pochard Aythya ferina, Great Crested Grebe Podiceps cristatus and Eurasian Coot Fulica atra. The third group with a large difference (average 85%) included five species, all of the Anatini tribe: Gadwall Mareca strepera, Northern Pintail Anas acuta, Northern Shoveler Spatula clypeata, Eurasian Teal Anas crecca and Garganey Spatula querquedula. During ice conditions, smaller numbers of most species were counted from the ground. The exception here was Mallard, more of which were counted from the ground, but the difference between two methods was relatively small in this species (7.5%). Under ice-free conditions, both methods can be used interchangeably for the most numerous birds occupying open water (core group) without any significant impact on the results. When water areas are frozen over, air counts are preferable as the results are more reliable. The cost analysis shows that a survey carried out by volunteer observers (reimbursement of travel expenses only) from the land is 58% cheaper, but if the observers are paid, then an aerial survey is 40% more economical.

Ducks change wintering patterns due to changing climate in the important wintering waters of the Odra River Estuary.

Some species of birds react to climate change by reducing the distance they travel during migration. The Odra River Estuary in the Baltic Sea is important for wintering waterfowl and is where we investigated how waterbirds respond to freezing surface waters. The most abundant birds here comprise two ecological groups: bottom-feeders and piscivores. Numbers of all bottom-feeders, but not piscivores, were negatively correlated with the presence of ice. With ongoing global warming, this area is increasing in importance for bottom-feeders and decreasing for piscivores. The maximum range of ice cover in the Baltic Sea has a weak and negative effect on both groups of birds. Five of the seven target species are bottom-feeders (Greater Scaup Aythya marila, Tufted Duck A. fuligula, Common Pochard A. ferina, Common Goldeneye Bucephala clangula and Eurasian Coot Fulica atra), and two are piscivores (Smew Mergellus albellus and Goosander Mergus merganser). Local changes at the level of particular species vary for different reasons. A local decline of the Common Pochard may simply be a consequence of its global decline. Climate change is responsible for some of the local changes in the study area, disproportionately favoring some duck species while being detrimental to others.

The Importance of Non-Native Prey, the Zebra Mussel Dreissena polymorpha, for the Declining Greater Scaup Aythya marila: A Case Study at a Key European Staging and Wintering Site.

The European population of Greater Scaup Aythya marila has experienced an alarming, ~60% decline in numbers over the last two decades. The brackish lagoons of the Odra River Estuary (ORE) in the south-western Baltic Sea, represent an important area for the species during the non-breeding season in Europe. The lagoons regularly support over 20 000 Scaup, with peaks exceeding 100 000 (38%-70% of the population wintering in NW Europe and the highest number recorded in April 2011-105 700). In the ORE, Scaup feed almost exclusively on the non-native Zebra Mussel Dreissena polymorpha. This mussel was present in the ORE already in the 19th century and continues to be superabundant. Using the results of 22 Scaup censuses (November to April 2002/2003 to 2013/2014) from the whole ORE (523 km2 of water), we show that Scaup flocks follow areas with the greatest area of occurrence and biomass of the Zebra Mussel, while areas with low mussel densities are ignored. The numbers of Scaup in the ORE are primarily related to the area of Zebra Mussel occurrence on the lagoon's bottom (km2) in a non-linear fashion. Zebra Mussels were absolutely prevalent (97% of biomass) in the digestive tracts of birds unintentionally by-caught in fishing nets (n = 32). We estimate that Scaup alone consume an average of 5 400 tons of Zebra Mussels annually, which represents 5.6% of the total resources of the mussel in the ORE. Our results provide a clear picture of the strong dependence of the declining, migratory duck species on the non-native mussel, its primary food in the ORE. Our findings are particularly important as they can form the basis for the conservation action plan aimed at saving the north-western European populations of Scaup.