Classical biomonitoring techniques have focused primarily on measures linked to various biodiversity metrics and indicator species. Next-generation biomonitoring (NGB) describes a suite of tools and approaches that allow the examination of a broader spectrum of organizational levels-from genes to entire ecosystems. Here, we frame 10 key questions that we envisage will drive the field of NGB over the next decade. While Makiola et al. Questions for Next-Generation Biomonitoring not exhaustive, this list covers most of the key challenges facing NGB, and provides the basis of the next steps for research and implementation in this field. These questions have been grouped into current-and outlook-related categories, corresponding to the organization of this paper.
Many nematode species are parasitic and threaten the health of plants and animals, including humans, on a global scale. Advances in DNA sequencing techniques have allowed for the rapid and accurate identification of many organisms including nematodes. However, the steps taken from sample collection in the field to molecular analysis and identification can take many days and depend on access to both immovable equipment and a specialized laboratory. Here, we present a protocol to genetically identify nematodes using 18S SSU rRNA sequencing using the MinION, a portable third generation sequencer, and proof that it is possible to perform all the molecular preparations on a fully portable molecular biology lab-the Bentolab. We show that both parasitic and free-living nematode species (Anisakis simplex, Panagrellus redivivus, Turbatrix aceti, and Caenorhabditis elegans) can be identified with a 96-100% accuracy compared to Sanger sequencing, requiring only 10-15 min of sequencing. This protocol is an essential first step toward genetically identifying nematodes in the field from complex natural environments (such as feces, soil, or marine sediments). This increased accessibility could in turn improve global information of nematode presence and distribution, aiding near-real-time global biomonitoring.
Summary1. Mechanistic insights and predictive understanding of the spatial distributions of foragers are typically derived by fitting either field measurements on intake rates and food abundance, or observations from controlled experiments, to functional response models. It has remained unclear, however, whether and why one approach should be favoured above the other, as direct comparative studies are rare. 2. The field measurements required to parameterize either single or multi-species functional response models are relatively easy to obtain, except at sites with low food densities and at places with high food densities, as the former will be avoided and the second will be rare. Also, in foragers facing a digestive bottleneck, intake rates (calculated over total time) will be constant over a wide range of food densities. In addition, interference effects may depress intake rates further. All of this hinders the appropriate estimation of parameters such as the 'instantaneous area of discovery' and the handling time, using a type II functional response model also known as 'Holling's disc equation'. 3. Here we compare field-and controlled experimental measurements of intake rate as a function of food abundance in female bar-tailed godwits Limosa lapponica feeding on lugworms Arenicola marina. 4. We show that a fit of the type II functional response model to field measurements predicts lower intake rates (about 2Á5 times), longer handling times (about 4 times) and lower 'instantaneous areas of discovery' (about 30-70 times), compared with measurements from controlled experimental conditions. 5. In agreement with the assumptions of Holling's disc equation, under controlled experimental settings both the instantaneous area of discovery and the handling time remained constant with an increase in food density. The field data, however, would lead us to conclude that although handling time remains constant, the instantaneous area of discovery decreased with increasing prey densities. This will result into highly underestimated sensory capacities when using field data. 6. Our results demonstrate that the elucidation of the fundamental mechanisms behind prey detection and prey processing capacities of a species necessitates measurements of functional response functions under the whole range of prey densities on solitary feeding individuals, which is only possible under controlled conditions. Field measurements yield 'consistency tests' of the distributional patterns in a specific ecological context.
Observing and quantifying primate behavior in the wild is challenging. Human presence affects primate behavior and habituation of new, especially terrestrial, individuals is a time-intensive process that carries with it ethical and health concerns, especially during the recent pandemic when primates are at even greater risk than usual. As a result, wildlife researchers, including primatologists, have increasingly turned to new technologies to answer questions and provide important data related to primate conservation. Tools and methods should be chosen carefully to maximize and improve the data that will be used to answer the research questions. We review here the role of four indirect methods—camera traps, acoustic monitoring, drones, and portable field labs—and improvements in machine learning that offer rapid, reliable means of combing through large datasets that these methods generate. We describe key applications and limitations of each tool in primate conservation, and where we anticipate primate conservation technology moving forward in the coming years.
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