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bioRxiv2021

Genetic diversity of wild and cultivated Coffea canephora in northeastern DR Congo and the implications for conservation.

PremiseMany cultivated coffee varieties descend from Coffea canephora, commonly known as Robusta coffee. The Congo Basin has a century long history of Robusta coffee cultivation and breeding, and is hypothesized to be the region of origin of many of the cultivated Robusta varieties. Since little is known about the genetic composition of C. canephora in this region, we assessed the genetic diversity of wild and cultivated C. canephora shrubs in the Democratic Republic of the Congo. MethodsUsing 18 microsatellite markers, we studied the genetic composition of wild and backyard-grown C. canephora shrubs in the Tshopo and Ituri provinces, and from the INERA Yangambi Coffee Collection. We assessed genetic clustering patterns, genetic diversity, and genetic differentiation between populations. Key resultsGenetic differentiation was relatively strong between wild and cultivated C. canephora shrubs, and both gene pools harbored multiple unique alleles. Strong genetic differentiation was also observed between wild populations. The level of genetic diversity in wild populations was similar to that of the INERA Yangambi Coffee Collection, but local wild genotypes were mostly missing from that collection. Shrubs grown in the backyards were genetically similar to the breeding material from INERA Yangambi. ConclusionsMost C. canephora that is grown in local backyards originated from INERA breeding programs, while a few shrubs were obtained directly from surrounding forests. The INERA Yangambi Coffee Collection could benefit from an enrichment with local wild genotypes, to increase the genetic resources available for breeding purposes, as well as to support ex situ conservation.

genetics↗

bioRxiv2021

Evaluating the efficacy of a consumer-centric method for ecological sampling: Using bonobo (Pan paniscus) feeding patterns as an instrument for tropical forest characterization

O_LICharacteristics of food availability and distribution are a key component of a species ecology. Objective measurement of food resources, such as vegetation plot sampling, do not consider aspects of selection by the consumer and therefore may produce imprecise measures of availability. Further, in most animal ecology research, traditional ecological surveying often is time-intensive and supplementary to ongoing behavioral observation. We propose a method to integrate ecological sampling of an animals environment into existing behavioral data collection systems by using the consumer as the surveyor. Here, we introduce the consumer-centric method (CCM) of assessing resource availability for its ability to measure food resource abundance, distribution, and dispersion. This method catalogues feeding locations observed during behavioral observation and uses aggregated data to characterize these ecological metrics. C_LIO_LIWe evaluated the CCM relative to traditional vegetation plot surveying using accumulated feeding locations across three years visited by a tropical frugivore, the bonobo (Pan paniscus), and compared it with data derived from over 200 vegetation plots across their 50km2+ home range. C_LIO_LIWe demonstrate that food species abundance estimates derived from the CCM are comparable to those derived from traditional vegetation plot sampling after approximately 600 observation days or 60 spatially explicit feeding locations. The agreement between the methods further improved when accounting for aspects of consumer selectivity in objective vegetation plot sampling (e.g., size minima). Estimates of density from CCM correlated with plot-derived estimates and were relatively insensitive to home range inclusion and other species characteristics, but were sensitive to sampling frequency (e.g., consumption frequency). Agreement between the methods in relative distribution of resources performed better across species than expected by chance, although measures of dispersion correlated poorly. C_LIO_LIWe demonstrate that while providing a robust measure to quantify local food availability, the CCM has an advantage over traditional sampling methods as it incorporates sampling biases relevant to the consumer. Therefore, as this method can be incorporated into existing observational data collection and does not require additional ecological surveying, it serves as a promising method for behavioral ecological data collection for animal species who re-use space and consume immobile food items. C_LI

ecology↗