TL;DR: In this paper, a model and likelihood-based method for estimating site occupancy rates when detection probabilities are 0.3 was proposed for American toads (Bufo americanus) and spring peepers (Pseudacris crucifer).
Abstract: Nondetection of a species at a site does not imply that the species is absent unless the probability of detection is 1. We propose a model and likelihood-based method for estimating site occupancy rates when detection probabilities are 0.3). We estimated site occupancy rates for two anuran species at 32 wetland sites in Maryland, USA, from data collected during 2000 as part of an amphibian monitoring program, Frogwatch USA. Site occupancy rates were estimated as 0.49 for American toads (Bufo americanus), a 44% increase over the proportion of sites at which they were actually observed, and as 0.85 for spring peepers (Pseudacris crucifer), slightly above the observed proportion of 0.83.
TL;DR: In this paper, the authors used the SWAT (Soil and Water Assessment Tool) to simulate all related processes affecting water quantity, sediment, and nutrient loads in the Thur River basin, which is a direct tributary to the Rhine.
TL;DR: Treated wastewater effluents were the main contributors to PPCPs concentrations in the rivers studied, and the effect of WWTP effluent on the quality of river water is significant and cannot be underestimated.
TL;DR: It is suggested that a golden age of animal tracking science has begun and that the upcoming years will be a time of unprecedented exciting discoveries.
Abstract: BACKGROUND The movement of animals makes them fascinating but difficult study subjects. Animal movements underpin many biological phenomena, and understanding them is critical for applications in conservation, health, and food. Traditional approaches to animal tracking used field biologists wielding antennas to record a few dozen locations per animal, revealing only the most general patterns of animal space use. The advent of satellite tracking automated this process, but initially was limited to larger animals and increased the resolution of trajectories to only a few hundred locations per animal. The last few years have shown exponential improvement in tracking technology, leading to smaller tracking devices that can return millions of movement steps for ever-smaller animals. Finally, we have a tool that returns high-resolution data that reveal the detailed facets of animal movement and its many implications for biodiversity, animal ecology, behavior, and ecosystem function. ADVANCES Improved technology has brought animal tracking into the realm of big data, not only through high-resolution movement trajectories, but also through the addition of other on-animal sensors and the integration of remote sensing data about the environment through which these animals are moving. These new data are opening up a breadth of new scientific questions about ecology, evolution, and physiology and enable the use of animals as sensors of the environment. High–temporal resolution movement data also can document brief but important contacts between animals, creating new opportunities to study social networks, as well as interspecific interactions such as competition and predation. With solar panels keeping batteries charged, “lifetime” tracks can now be collected for some species, while broader approaches are aiming for species-wide sampling across multiple populations. Miniaturized tags also help reduce the impact of the devices on the study subjects, improving animal welfare and scientific results. As in other disciplines, the explosion of data volume and variety has created new challenges and opportunities for information management, integration, and analysis. In an exciting interdisciplinary push, biologists, statisticians, and computer scientists have begun to develop new tools that are already leading to new insights and scientific breakthroughs. OUTLOOK We suggest that a golden age of animal tracking science has begun and that the upcoming years will be a time of unprecedented exciting discoveries. Technology continues to improve our ability to track animals, with the promise of smaller tags collecting more data, less invasively, on a greater variety of animals. The big-data tracking studies that are just now being pioneered will become commonplace. If analytical developments can keep pace, the field will be able to develop real-time predictive models that integrate habitat preferences, movement abilities, sensory capacities, and animal memories into movement forecasts. The unique perspective offered by big-data animal tracking enables a new view of animals as naturally evolved sensors of environment, which we think has the potential to help us monitor the planet in completely new ways. A massive multi-individual monitoring program would allow a quorum sensing of our planet, using a variety of species to tap into the diversity of senses that have evolved across animal groups, providing new insight on our world through the sixth sense of the global animal collective. We expect that the field will soon reach a transformational point where these studies do more than inform us about particular species of animals, but allow the animals to teach us about the world.
TL;DR: The necessity and usefulness of multivariate statistical assessment of large and complex databases in order to get better information about the quality of surface water, the design of sampling and analytical protocols and the effective pollution control/management of the surface waters is presented.