Camera trap technology has galvanized the study of predator-prey ecology in wild animal communities by expanding the scale and diversity of predator-prey interactions that can be analyzed. While observational data from systematic camera arrays have informed inferences on the spatiotemporal outcomes of predator-prey interactions, the capacity for observational studies to identify mechanistic drivers of species interactions is limited. Experimental study designs that utilize camera traps uniquely allow for testing hypothesized mechanisms that drive predator and prey behavior, incorporating environmental realism not possible in the lab while benefiting from the distinct capacity of camera traps to generate large data sets from multiple species with minimal observer interference. However, such pairings of camera traps with experimental methods remain underutilized. We review recent advances in the experimental application of camera traps to investigate fundamental mechanisms underlying predator-prey ecology and present a conceptual guide for designing experimental camera trap studies. Only 9% of camera trap studies on predator-prey ecology in our review mention experimental methods, but the application of experimental approaches is increasing. To illustrate the utility of camera trap-based experiments using a case study, we propose a study design that integrates observational and experimental techniques to test a perennial question in predator-prey ecology: how prey balance foraging and safety, as formalized by the risk allocation hypothesis. We discuss applications of camera trap-based experiments to evaluate the diversity of anthropogenic influences on wildlife communities globally. Finally, we review challenges to conducting experimental camera trap studies. Experimental camera trap studies have already begun to play an important role in understanding the predator-prey ecology of free-living animals, and such methods will become increasingly critical to quantifying drivers of community interactions in a rapidly changing world. We recommend increased application of experimental methods in the study of predator and prey responses to humans, synanthropic and invasive species, and other anthropogenic disturbances.
MULTIFILE
The QuickScan CBM (Circular Business Model) offers an approach to develop a circular business model. It focuses primarily on the manufacturing industry, even though it can be used in other sectors. It consists of three parts: (1) an introduction with an explanation of backgrounds and central concepts, (2) knowledge maps of seven business models that together form a classification and (3) the actual QuickScan.An interactive application can be found at Business Model Lab. This last version is bilingual (Dutch and English). Regardless of the version, it can be used to develop a new CBM or adapt an existing business model based on a qualitative approach. The starting point is that better design and organisation of a CBM contributes to the transformation and transition towards a sustainable and circular economy.
MULTIFILE
Large floating projects have the potential to overcome the challenge of land scarcity in urban areas and offer opportunities for energy and food production, or even for creating sustainable living environments. However, they influence the physical, chemical, biological and ecological characteristics of water bodies. The interaction of the floating platforms affect multiple complex aquatic processes, and the potential (negative/positive) effects are not yet fully understood. Managing entities currently struggle with lack of data and knowledge that can support adequate legislation to regulate future projects.In the Netherlands the development of small scale floating projects is already present for some years (e.g. floating houses, restaurants, houseboats), and more recently several large scale floating photovoltaic plants (FPV) have been realized. Several floating constructions in the Netherlands were considered as case-studies for a data-collection campaign.To obtain data and images from underneath floating buildings, underwater drones were equipped with cameras and sensors. The drones were used in multiple locations to scan for differences in concentrations of basic water quality parameters (e.g. dissolved oxygen, electrical conductivity, algae, light intensity) from underneath/near the floating structures, which were then compared with data from locations far from the influence of the buildings. Continuous data was also collected over several days using multi-parameter water quality sensors permanently installed under floating structures.
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