COYOTE PREDATION ON THE RIO GRANDE WILD TURKEY IN THE TEXAS PANHANDLE AND SOUTHWESTERN KANSAS
Bibliographic record
Abstract
From January 2000 to August 2004, we collected data on Rio Grande wild turkey \n(Meleagris gallapavo intermedia) survival, cause-specific mortality, movements, habitat \nuse, roost use, and nesting at 4 study sites (3 in the Texas Panhandle: Matador Wildlife \nManagement Area (MWMA) near Paducah, Texas, Salt Fork of the Red River private \nland holdings (SF) near Clarendon, Texas, and Gene Howe Wildlife Management Area \n(GHWMA) near Canadian, Texas, and 1 site on the Cimarron National Grasslands \n(CNG) near Elkhart, Kansas). During 2000-2002 turkey survival across the 4 sites was \nabout 50% (Ballard et al. 2002). Coyotes were the most frequently cited predators of Rio \nGrande wild turkeys during the first 3 years of our study, identified in 147 out of 313 \n(47%) predation events (Ballard et al. 2003). \nWe wanted to further study the impact of coyotes on adult (= 1 year old) and \njuvenile (6 months to 1 year old) Rio Grande wild turkeys in the Texas Panhandle and \nSouthwestern Kansas, by examining and comparing relative abundances and food habits \nof coyotes at our four study sites. To estimate relative abundance of carnivore species at \nour study sites, we used scent stations as our primary method and scat surveys as a \nsecondary method to corroborate scent stations. We examined the food habits of coyotes at our study sites through scat analysis, using scats collected from our scat surveys. \n \nProportions of prey species were expressed using percent of scats (POS) and percent of \noccurrence(POO). \nScent station visitation by coyotes was not different among sites in any season \n(Fall 2003 ?2 = 7.5067, P = 0.0574; Spring 2003 ?2 = 1.6263, P = 0.6535 Summer 2003 \nx?2 = 4.4270, P = 0.2189 and Winter 2004 ?2 = 1.6442, P = 0.6494, Table 2.1). Raccoons \n(n = 37) were the second-most frequent visitor, and were significantly different among \nsites during each period (Fall 2003 ?2 = 17.2083, P = 0.0006; Spring 2003 ?2 = 8.8584, P= 0.312 Summer 2003 ?2 = 7.9598, P = 0.0468 and Winter 2004 ?2 = 8.6458, P = \n0.0344). Raccoons were detected more frequently at the SF (?2 = 4.5, P = 0.0339) and \nMWMA (?2 = 4.5, P = 0.0339) than the CNG site during the Spring sampling period. \nDuring the Summer period, raccoons were detected more frequently at SF scent stations \nthan at MWMA (?2 = 4.35, P = 0.0370). Raccoons were detected more frequently in the \nFall period at the SF than all other sites (CNG ?2 = 10.28, P = 0.0013; MWMA ?2 = 7.02, \nP = 0.0081; GHWMA ?2 = 5.11, P = 0.0237). During the Winter period, raccoons were \ndetected more frequently at SF (?2 = 5.56, P = 0.0184) and GHWMA (?2 = 4.02, P = \n0.0450) than MWMA. \n \nDiet composition of coyote scats (n = 374) consisted of 27 prey types, primarily \nsmall mammal species (n = 11) and vegetation (n = 8), followed by large mammal \nspecies (n = 3), medium mammal species (n = 2), avian species (n = 2), reptiles (n = 1), \nand insects (n = 1). Prey occurrences were primarily small- [n = 194, 40.76 Percent of \nOccurrence (POO)] and medium-sized (n = 73, 15.33 POO) mammals. The most \ncommon prey occurrence across all sites and seasons was Eastern cottontail (Sylvilagus \nfloridanus)(n = 69, 14.50 POO), identified in scats at all sites. White-footed \n(Peromyscus leucopus), and deer mice (Peromyscus maniculatus), (n = 42, 8.82 POO), \nand hispid cotton rat (Sigmodon hispidus, n = 28, 5.88 POO) were the most common \nprey types in the small mammal prey category. We detected avian species (n = 13, 2.73 \nxi POO) in coyote scats at SF (n = 6), GHWMA (n = 2), and CNG (n = 4) sites. Turkey \nwas <1% of all food items, detected only at SF (n = 2) and CNG (n = 1).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".