Khelifa, R. | Search bioRxiv

bioRxiv2025

Using insects for sustainable waste management of superabundant animals.

Management of fecal waste from superabundant wildlife in urban areas is a key environmental and public health concern, yet even in developed countries, sustainable solutions that implement circular economy principles are still lacking. We tested the potential of black soldier fly (BSF) larvae for valorizing organic waste of the widespread Canada goose: converting droppings into larval protein while yielding frass fertilizer. Larvae were able to survive, develop, and degrade the goose feces. For instance, larvae degraded 56% of goose feces compared to 63% of a control diet. Sterilization of feces reduced the performance of larvae. We tested the fertilization properties of the insect frass on an aquatic plant (duckweed) and we found growth enhancement of 32% at 10 g{middle dot}L-1 compared to a standard Hoaglands media. Our results provide insights into how to sustainably manage urban fecal waste from overabundant species while producing protein and a nutrient-rich fertilizer for plants.

ecology↗

bioRxiv2021

Utilizing occupancy-detection models with museum specimen data: promise and pitfalls

Historical museum records provide potentially useful data for identifying drivers of change in species occupancy. However, because museum records are typically obtained via many collection methods, methodological developments are needed in order to enable robust inferences. Occupancy-detection models, a relatively new and powerful suite of methods, are a potentially promising avenue because they can account for changes in collection effort through space and time. Here we present a methodological road-map for using occupancy models to analyze historical museum records. We use simulated data-sets to identify how and when patterns in data and/or modelling decisions can bias inference. We focus primarily on the consequences of contrasting methodological approaches for dealing with species ranges and inferring species non-detections in both space and time. We find that not all data-sets are suitable for occupancy-detection analysis but, under the right conditions (namely, data-sets that span long durations and contain a high fraction of community-wide collections, or collection events that focus on communities of organisms), models can accurately estimate trends. Finally, we present a case-study on eastern North American odonates where we calculate long-term trends of occupancy by using our most robust workflow.

ecology↗