| Literature DB >> 26132204 |
Rémi Lesmerises1, Lucie Rebouillat2, Claude Dussault3, Martin-Hugues St-Laurent4.
Abstract
Studying diet is fundamental to animal ecology and scat analysis, a widespread approach, is considered a reliable dietary proxy. Nonetheless, this method has weaknesses such as non-random sampling of habitats and individuals, inaccurate evaluation of excretion date, and lack of assessment of inter-individual dietary variability. We coupled GPS telemetry and scat analyses of black bears Ursus americanus Pallas to relate diet to individual characteristics and habitat use patterns while foraging. We captured 20 black bears (6 males and 14 females) and fitted them with GPS/Argos collars. We then surveyed GPS locations shortly after individual bear visits and collected 139 feces in 71 different locations. Fecal content (relative dry matter biomass of ingested items) was subsequently linked to individual characteristics (sex, age, reproductive status) and to habitats visited during foraging bouts using Brownian bridges based on GPS locations prior to feces excretion. At the population level, diet composition was similar to what was previously described in studies on black bears. However, our individual-based method allowed us to highlight different intra-population patterns, showing that sex and female reproductive status had significant influence on individual diet. For example, in the same habitats, females with cubs did not use the same food sources as lone bears. Linking fecal content (i.e., food sources) to habitat previously visited by different individuals, we demonstrated a potential differential use of similar habitats dependent on individual characteristics. Females with cubs-of-the-year tended to use old forest clearcuts (6-20 years old) to feed on bunchberry, whereas females with yearling foraged for blueberry and lone bears for ants. Coupling GPS telemetry and scat analyses allows for efficient detection of inter-individual or inter-group variations in foraging strategies and of linkages between previous habitat use and food consumption, even for cryptic species. This approach could have interesting ecological implications, such as supporting the identification of habitats types abundant in important food sources for endangered species targeted by conservation measures or for management actions for depredating animals.Entities:
Mesh:
Year: 2015 PMID: 26132204 PMCID: PMC4489386 DOI: 10.1371/journal.pone.0129857
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Description of variables and associated measurement units.
| Variable | Description or scientific name | Unit | Variable | Description or scientific name | Unit |
|---|---|---|---|---|---|
| Secondary road | Forest road with low to high traffic | Km/km2 | Ants |
| % in feces |
| Closed road | Forest road with no traffic | km/km2 | Poplar |
| % in feces |
| River | Permanent running water | km/km2 | Willow |
| % in feces |
| Lake | Pond and lake | % in ellipses | Grass |
| % in feces |
| Swamp | Open wetland | % in ellipses | Mayflower berry |
| % in feces |
| Conifer | Mature coniferous forest (>50 years old) | % in ellipses | Raspberry |
| % in feces |
| Cut (0–5) | Forest clearcut (0–5 years old) | % in ellipses | Sarsaparilla |
| % in feces |
| Cut (6–20) | Forest clearcut (6–20 years old) | % in ellipses | Smilacina |
| % in feces |
| Regeneration | Old disturbance (20–40 years old) | % in ellipses | Creeping snowberry |
| % in feces |
| Open | Non regenerated disturbance (> 20 years old) | % in ellipses | Blueberry |
| % in feces |
| Beaver |
| % in feces | |||
| Hare |
| % in feces |
Distribution of sample sizes among groups.
| Group of individuals | Bear ( | Sites | ||||
|---|---|---|---|---|---|---|
|
| Mean | SD | Min | Max | ||
| Females with yearlings | 6 | 17 | 2.8 | 1.8 | 1 | 5 |
| Females with cubs | 6 | 26 | 4.3 | 1.5 | 2 | 6 |
| Lone females | 2 | 2 | 1.0 | 0.0 | 1 | 1 |
| Males | 6 | 26 | 4.3 | 1.8 | 3 | 7 |
| Total | 20 | 71 | 3.6 | 1.9 | 1 | 7 |
Fig 1Corrected proportion of dry matter ingested of food items found in feces.
a) Adults feces (n = 120 feces/71 sites) for spring (n = 47 feces/24 sites; May 15th–June 14th), summer (n = 32 feces/20 sites; June 15th–July 31st) and fall (n = 41 feces/27 sites August 1st–September 14th). b) Cub-of-the-year feces (n = 30 feces/13 sites) for the whole sampling season (May 15th–September 14th). Error bars represent the standard deviation.
Fig 2Graphical representations of Constrained Correspondence Analysis (CCA).
Black arrows represent significant (p < 0.05) food item variables correlated with individual characteristics (in italics, panel a), and black arrows represent habitat variables correlated with the different food items (in italics, panel b,c d). Dashed grey arrows refer to variables that were not significantly correlated. In panel a (n = 28 feces of 6 different bears), body condition index and age are not shown to lighten the graphic and ease its interpretation as they were not significantly correlated with specific food items. Other panels represent relationships between habitat types and food items (in italics) by group of individuals sharing similar diets, as shown in panel a. Panel b for lone bears (n = 28 feces of 6 different bears), c for females with yearlings (n = 17 feces of 6 different bears) and d for females with cubs-of-the-year (n = 26 of 6 different bears).