Experimental calibration of trapping methods for addressing bias in arthropod biodiversity monitoring
McNamara Manning, K.; Bahlai, C.
Show abstract
Sampling approaches are commonly adapted to reflect the study objectives in biodiversity monitoring projects. This approach optimizes findings to be locally relevant but comes at the cost of generalizability of findings. Here, we detail a comparison study directly examining how researcher choice of arthropod trap and level of specimen identification affects observations made in small-scale arthropod biodiversity studies. Sampling efficiency of four traps: pitfall traps, yellow ramp traps, yellow sticky cards, and a novel jar ramp trap were compared with respect to an array of biodiversity metrics associated with the arthropods they captured at three levels of identification. We also outline how to construct, deploy, and collect jar ramp traps. Trapping efficiency and functional groups of arthropods (flying, crawling, and intermediate mobility) varied by trap type. Pitfalls and jar ramp traps performed similarly for most biodiversity metrics measured, suggesting that jar ramp traps provide a more comparable measurement of ground-dwelling arthropod communities to pitfall sampling than the yellow ramp traps. The jar ramp trap is a simple, inexpensive alternative when the physical aspects of an environment do not allow the use of pitfalls. This study illustrates the implications for biodiversity sampling of arthropods in environments with physical constraints on trapping, and the importance of directly comparing adapted methods to established sampling protocol. Future biodiversity monitoring schemes should conduct comparison experiments to provide important information on performance and potential limitations of sampling methodology.
Matching journals
The top 1 journal accounts for 50% of the predicted probability mass.
Similar papers in this journal
- Seasonal phenology of Coffee Berry Borer (Hypothenemus hampei Ferrari) in Hawaii and the influence of weather on flight activity 96%
- Effects of scent lure on camera trap detections vary across mammalian predator and prey species 95%
- Automated flight interception traps for interval sampling of insects 94%
Similar papers in this journal
- Crop and Semi-Natural Habitat Configuration affects Diversity and Abundance of Native Bees (Hymenoptera: Anthophila) in a Large-Scale Cotton Agroecosystem 94%
- Where have all the spiders gone? Observations of a dramatic population density decline in the once very abundant garden spider, Araneus diadematus (Araneae: Araneidae), in the Swiss midland 92%
- Real-time feeding behavior monitoring by electrical penetration graph rapidly reveals host plant susceptibility to crapemyrtle bark scale (Hemiptera: Eriococcidae) 92%
Similar papers in this journal
- Eat or Be Eaten: Implications of potential exploitative competition between wolves and humans across predator- savvy and -naive deer populations 94%
- Numerical response of predators to large variations of grassland vole abundance, long-term community change and prey switches 92%
- Differential phoretic host use among sympatric Caenorhabditis nematodes and an association with invasive nitidulid beetles in southwestern Germany 91%
Similar papers in this journal
- Vigilance response of a key prey species to anthropogenic and natural threats in Detroit 92%
- Microclimate, CO2 and CH4 concentration on Blue tits (Cyanistes caeruleus) nests: effects of brood size, nestling age and on ectoparasites 90%
- Selective logging shows no impact on the dietary breadth of the fawn leaf-nosed bat (Hipposideros cervinus) 90%
Similar papers in this journal
- Novel eDNA approaches to monitor Western honey bee (Apis mellifera) microbial and arthropod communities 92%
- 31° South: Dietary niche of an arid-zone endemic passerine 92%
- Environmental variables and species traits as drivers of wild bee pollination in intensive agroecosystems -a metabarcoding approach 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.