Tracking the long-term decline and recovery of an isolated population

Effects of small population size and reduced genetic variation on the viability of wild animal populations remain controversial. During a 35-year study of a remnant population of greater prairie chickens, population size decreased from 2000 individuals in 1962 to fewer than 50 by 1994. Concurrently, both fitness, as measured by fertility and hatching rates of eggs, and genetic diversity declined significantly. Conservation measures initiated in 1992 with translocations of birds from large, genetically diverse populations restored egg viability. Thus, sufficient genetic resources appear to be critical for maintaining populations of greater prairie chickens.     

Effect of Early Postpartum Ovulation on Fertility in Dairy Cows

Our objectives were to determine the effects of early ovulation on fertility and uterine health of dairy cows. Four hundred and forty‐five Holstein cows (185 primiparous and 260 multiparous) from five herds were used. Blood samples were collected at 21, 35 and 49 days in milk (DIM) and cows were considered to be cyclic at 21 DIM (Cyc21) if serum progesterone (P4) concentration was above 1 ng/ml, cyclic by 49 DIM (Cyc49) if P4 concentration was above 1 ng/ml at 35 or 49 DIM, or not cyclic (NotCyc) if P4 concentration was below 1 ng/ml at all sample times. Endometrial cytology for diagnosis of subclinical endometritis was examined at 49 DIM in a subset of 414 cows. Cows in the group Cyc21 had increased hazard of insemination, for the first service, compared with cows in Cyc49 [hazard ratio (HR) = 1.40; 95% CI = 1.10–1.79; p = 0.006] and NotCyc (HR = 2.07; 95% CI = 1.52–2.82; p < 0.001). Cows in the Cyc49 group also had increased hazard of insemination compared with cows in the NotCyc group (HR = 1.47; 95% CI = 1.13–1.93; p = 0.005). Median days to insemination were, respectively, 71, 76 and 96 for cows in Cyc21, Cyc49 and NotCyc groups. Cows in Cyc21 had greater first service pregnancy per AI than Cyc49 [38.6 vs 28.1%; adjusted odds ratio (AOR) = 1.67; 95% CI = 1.01–2.75; p = 0.04] and NotCyc (38.6 vs 23.6%; AOR = 2.08; 95% CI = 1.08–4.00; p = 0.03). Pregnancy per AI was similar in Cyc49 and NotCyc cows (28.1 vs 23.6%; AOR = 1.25; 95% CI = 0.70–2.24; p = 0.45). Cows in Cyc21 had increased hazard of pregnancy up to 300 DIM compared with Cyc49 (HR = 1.52; 95% CI = 1.17–1.96; p = 0.002) and NotCyc (HR = 1.98; 95% CI = 1.41–2.78; p < 0.001). Cows in Cyc49 tended to have increased hazard of pregnancy compared with NotCyc (HR = 1.31; 95% CI = 0.96–1.77; p = 0.09). Median days to pregnancy were, respectively, 103, 147 and 173 for cows in Cyc21, Cyc49 and NotCyc groups. Cows in the Cyc21 group had decreased prevalence of subclinical endometritis compared with cows in the NotCyc group (29.9 vs 43.7%; AOR = 0.53; 95% CI = 0.29–0.97; p = 0.04); however, the prevalence did not differ from the Cyc49 group (29.9 vs 39.1%; AOR = 0.68; 95% CI = 0.41–1.14; p = 0.15). Cyc49 cows had similar prevalence of subclinical endometritis compared with NotCyc cows (AOR = 0.77; 95% CI = 0.46–1.29; p = 0.32). Early postpartum ovulation was associated with improved uterine health and fertility.     

Nondestructive Estimation of Standing Crop and Fuel Moisture Content in Tallgrass Prairie

Accurate estimation of standing crop and herbaceous fuel moisture content (FMC) are important for grazing management and wildfire preparedness. Destructive sampling techniques have been used to accurately estimate standing crop and FMC, but those techniques are laborious and time consuming. Existing nondestructive methods for estimating standing crop in tallgrass prairie have limitations, and few studies have examined nondestructive estimation techniques for FMC in this environment. Therefore, our objective was to develop robust models for nondestructive estimation of standing crop and FMC in tallgrass prairie. We calibrated and validated stepwise multiple linear regression (SMLR) and artificial neural network (ANN) models for standing crop and FMC using data collected in tallgrass prairies near Stillwater, Oklahoma. Day of year (DOY), canopy height (CH), Normalized Difference Vegetation Index (NDVI), and percent reflectance in five wavelength bands were candidate input variables for the models. The study spanned two growing seasons and nine patches located within three pastures under patch burn management, and the resulting data set with > 3 000 observations was split randomly with 85% for model calibration and 15% withheld for validation. Standing crop ranged from 0 to 852 g m^? 2, and FMC ranged from 0% to 204%. With DOY, CH, and NDVI as predictors, the SMLR model for standing crop produced a root mean squared error (RMSE) of 119 g m^? 2 on the validation data, while the RMSE of the corresponding ANN model was 116 g m^? 2. With the same predictors, the SMLR model for FMC produced an RMSE of 26.7% compared with 23.8% for the corresponding ANN model. Thus, the ANN models provided better prediction accuracy but at the cost of added computational complexity. Given the large variability in the underlying datasets, the models developed here may prove useful for nondestructive estimation of standing crop and FMC in other similar grassland environments.     

Factors Affecting Synchronization and Conception Rate after the Ovsynch Protocol in Lactating Holstein Cows

Objectives were to evaluate risk factors affecting ovulatory responses and conception rate to the Ovsynch protocol. Holstein cows, 466, were submitted to the Ovsynch protocol [day 0, GnRH‐1; day 7, prostaglandin (PG) F_2α; day 9, GnRH‐2] and 103 cows were inseminated 12 h after GnRH‐2. Information on parity, days in milk at GnRH‐1, body condition, milk yield, exposure to heat stress, pre‐synchronization with PGF_2α and the use of progesterone insert from GnRH‐1 to PGF_2α was collected. Ovaries were scanned to determine responses to treatments. Overall, 54.7%, 10.6%, 2.2%, 81.1%, 9.0%, 91.5% and 36.9% of the cows ovulated to GnRH‐1, multiple ovulated to GnRH‐1, ovulated before GnRH‐2, ovulated to GnRH‐2, multiple ovulated to GnRH‐2, experienced corpus luteum (CL) regression and conceived, respectively. Ovulation to GnRH‐1 was greater in cows without a CL at GnRH‐1, cows with follicles >19 mm and cows not pre‐synchronized with PGF_2α 14 days before GnRH‐1. Multiple ovulations to GnRH‐1 increased in cows without CL at GnRH‐1 and cows with follicles ≤19 mm at GnRH‐1. Ovulation before GnRH‐2 was greater in cows without CL at PGF_2α. Ovulation to GnRH‐2 increased in cows that received a progesterone insert, cows with a CL at GnRH‐1, cows with follicles not regressing from the PGF_2α to GnRH‐2, cows with larger follicles at GnRH‐2, cows that ovulated to GnRH‐1 and cows not pre‐synchronized. Multiple ovulations after GnRH‐2 increased in cows with no CL at GnRH‐1, multiparous cows and cows that multiple ovulated to GnRH‐1. Conception rate at 42 days after AI increased in cows with body condition score > 2.75 and cows that ovulated to GnRH‐2. Strategies that optimize ovulation to GnRH‐2, such as increased ovulation to GnRH‐1, should improve response to the Ovsynch protocol.