Plains and wood bison fecal samples, diet content, and diet quality

Understanding ecological niche is critical to the management and conservation of any species or population. For herbivores, dietary niche is critical for understanding habitat suitability, carrying capacity, and population and community viability. In closely related species with similar morphologies, dietary niches can diverge depending on environmental and seasonal factors. Elk Island National Park in Alberta, Canada, contains populations of both American bison (Bison bison) subspecies—plains bison (B. b. bison) and wood bison (B. b. athabascae)—in similar but separate habitats located at the historical confluence of the subspecies’ distributions. Using generalized additive models and nutritional geometry, we compared the subspecies’ dietary niches in terms of content and quality continuously for one year (Dec 2020 – Nov 2021). Both subspecies consumed primarily graminoids during winter, spring, and fall and incorporated a variety of forbs and woody plants during summer. Plains bison diets contained more upland grasses and digestible organic matter in their diet and less wetland graminoids (e.g., sedges) throughout the year. We also found differing dietary niches between the subspecies during the spring and summer months. Our unique, continuous analysis of annual diet content and quality can deliver insight into the similarities and differences between subspecies’ dietary niches that should help improve management decisions, such as better matching between source populations and release areas for future translocations.

Methods
We collected fecal samples once every calendar week in both the northern and southern blocks at Elk Island National Park, Alberta, Canada. We started collecting samples in the first week of December 2020 and ended collection during the last week of November 2021. We determined bison locations via global positioning system collar data or via observations by EINP staff. We collected all samples within 6 days of known bison occurrence at a location and then froze the samples. We ensured the freshness of fecal samples by observing bison defecating and collecting the samples after the bison moved away. An EINP employee with expertise in aging bison fecal samples led collection efforts. We collected samples from mixed herds, which included adult females and juveniles, yearlings, and calves of both sexes. We used composite samples to account for potential differences in diet composition and quality between different sexes and age classes (Mooring et al. 2005, Jung 2015). We took approximately 5 mL from the center of 5 fecal samples and combined them to create a composite sample for each date of collection. 

We had composite samples sequenced for trnL chloroplast introns at Jonah Ventures (Boulder, Colorado, USA) environmental DNA (eDNA) laboratory (Craine et al. 2015). This eDNA metabarcoding method provides the number of times a trnL sequence is identified in a composite sample (i.e., a read count). Using the sequences provided, we used the Basic Local Assignment Search Tool (BLAST) through the National Center of Biotechnology Information (NCBI) database (Sayers et al. 2021) to identify plants in the bison’s diet. We identified plants to the finest operational taxonomic unit available (e.g., species, genus, family) that had a 99% similarity in trnL sequence from the fecal sample and database (King and Schoenecker 2019) and were known to occur within EINP (EINP, unpublished data). Next, we calculated the relative read abundance (RRA) as the ratio of a read count of a unique taxonomic unit to the total read count within a composite sample. To estimate subspecies and seasonal diets, we calculated the mean RRA for each trnL sequence from the composite samples for each subspecies within the appropriate timeframe. The RRA is an estimate of the proportion of diet of each taxonomic unit that is comparable to other methods estimating diet composition, such as microhistology (Craine et al. 2015, Kartzinel et al. 2015, Deagle et al. 2019, King and Schoenecker 2019). For comparison of subspecies’ diet and modeling of dietary changes throughout the year, we only included taxonomic units that had an RRA of at least 0.5% within a composite sample (Hecker et al. 2021).

To assess differences in diet quality between subspecies and changes in diet quality throughout the year within a subspecies, we used near-infrared reflectance spectrometry (NIRS). This method identifies the chemical structure of a fecal sample using the unique near-infrared spectrum signatures of botanical components in the sample (Norris et al. 1976). The technique has been widely used to assess forage quality in herbivore diets (Walker et al. 2002, André and Lawler 2003, Craine et al. 2013). One of the advantages of this technique is that it is not subject to bias based on differential digestibility of forages (Garnick et al. 2018). We shipped portions of our composite fecal samples to the Grazingland Animal Nutrition Lab (Temple, Texas, USA) for NIRS diet quality analysis. Specifically, we were interested in differences in crude protein (CP), digestible organic matter (DOM), the ratio of DOM to CP (DOM/CP), and fecal nitrogen (FN) content within the subspecies’ diets. These components are key indicators of ruminant diet quality (van Soest 1994).