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At least 1,351 records · Page 75Linked to original sources
USGS2006

Multistate survival models and their extensions in Program MARK

Program MARK provides .100 models for the estimation of population parameters from mark?encounter data. The multistate model of Brownie et al. (1993) and Hestbeck et al. (1991) allows animals to move between states with a probability of transition. The simplest multistate model is an extension of the Cormack?Jolly?Seber (CJS) live recapture model. arameters estimated are state-specific survival rates and encounter probabilities and transition probabilities between states. The multistate model provides a valuable framework to evaluate important ecological questions. For example, estimation of state-specific survival and transition probabilities between the biological states of breeders and nonbreeders allows estimation of the cost of reproduction. Transitions between physical states, such as spatial areas, provide estimates needed for meta-population models. The basic multistate model uses only live recaptures, but 3 extensions are included in MARK. A multistate model with live and dead encounters is available, although the dead encounters are not state specific. Robust-design multistate models are also included in MARK, with both open and closed robust designs. These models assume that animals move between states only between primary sessions of the robust design. For the closed robust design, we can specify 12 different data types for the modeling of encounter probabilities during the primary session, including 6 versions of the closed model likelihood incorporating population size (N) directly in the likelihood, and 6 versions of the Huggins model in which N is estimated as a derived parameter outside the likelihood. One assumption that is generally necessary to estimate state-specific survival rates in the multistate model is that transitions take place immediately before encounter occasions. Otherwise, survival rates over the interval between encounter occasions are a mix of survival rates over multiple states. Advantages of using MARK to estimate the parameters of the various multistate models include flexibility of model specification to include group, time, and individual covariates, estimation of variance components, model averaging of parameter estimates, and Bayesian parameter estimation using Markov chain Monte Carlo procedures on the logit scale.

Journal of Wildlife Management↗
USGS2008

Combining Breeding Bird Survey and Christmas Bird Count data to evaluate seasonal components of population change in Northern Bobwhite

Annual surveys of wildlife populations provide information about annual rates of change in populations but provide no information about when such changes occur. However, by combining data from 2 annual surveys, conducted in different parts of the year, seasonal components of population change can be estimated. We describe a hierarchical model for simultaneous analysis of 2 continent-scale monitoring programs. The Christmas Bird Count is an early winter survey, whereas the North American Breeding Bird Survey is conducted in June. Combining information from these surveys permits estimation of seasonal population variance components and improves estimation of long-term population trends. The composite analysis also controls for survey-specific sampling effects. We applied the model to estimation of population change in northern bobwhites (Colinus virginianus). Over the interval 1969?2004, bobwhite populations declined, with trend estimate of -3.56% per year (95% CI = [-3.80%, -3.32%]) in the surveyed portion of their range. Our analysis of seasonal population variance components indicated that northern bobwhite populations changed more in the winter and spring portion of the year than in the summer and fall portion of the year.

Journal of Wildlife Management↗
USGS2008

Estimation and correction of visibility bias in aerial surveys of wintering ducks

Incomplete detection of all individuals leading to negative bias in abundance estimates is a pervasive source of error in aerial surveys of wildlife, and correcting that bias is a critical step in improving surveys. We conducted experiments using duck decoys as surrogates for live ducks to estimate bias associated with surveys of wintering ducks in Mississippi, USA. We found detection of decoy groups was related to wetland cover type (open vs. forested), group size (1?100 decoys), and interaction of these variables. Observers who detected decoy groups reported counts that averaged 78% of the decoys actually present, and this counting bias was not influenced by either covariate cited above. We integrated this sightability model into estimation procedures for our sample surveys with weight adjustments derived from probabilities of group detection (estimated by logistic regression) and count bias. To estimate variances of abundance estimates, we used bootstrap resampling of transects included in aerial surveys and data from the bias-correction experiment. When we implemented bias correction procedures on data from a field survey conducted in January 2004, we found bias-corrected estimates of abundance increased 36?42%, and associated standard errors increased 38?55%, depending on species or group estimated. We deemed our method successful for integrating correction of visibility bias in an existing sample survey design for wintering ducks in Mississippi, and we believe this procedure could be implemented in a variety of sampling problems for other locations and species.

Journal of Wildlife Management↗
USGS2008

Conserving waste rice for wintering waterfowl in the Mississippi Alluvial Valley

Rice lost before or during harvest operations (hereafter waste rice) provides important food for waterfowl in the Mississippi Alluvial Valley, USA, but >70% of waste rice is lost during autumn. We conducted experiments in 19 production rice fields in Arkansas and Mississippi during autumns 2003 and 2004 to evaluate the ability of common postharvest practices (i.e., burn, mow, roll, disk, or standing stubble) to conserve waste rice. We detected a postharvest treatment effect and a positive effect of initial abundance of waste rice on late-autumn abundance of waste rice (P < 0.022). Standing stubble contained the greatest abundance of waste rice followed by burned, mowed, rolled, and disked stubble. We recommend standing stubble or burning to maximize waste rice abundance for wintering waterfowl.

Journal of Wildlife Management↗
USGS2008

A double-observer method to estimate detection rate during aerial waterfowl surveys

We evaluated double-observer methods for aerial surveys as a means to adjust counts of waterfowl for incomplete detection. We conducted our study in eastern Canada and the northeast United States utilizing 3 aerial-survey crews flying 3 different types of fixed-wing aircraft. We reconciled counts of front- and rear-seat observers immediately following an observation by the rear-seat observer (i.e., on-the-fly reconciliation). We evaluated 6 a priori models containing a combination of several factors thought to influence detection probability including observer, seat position, aircraft type, and group size. We analyzed data for American black ducks (Anas rubripes) and mallards (A. platyrhynchos), which are among the most abundant duck species in this region. The best-supported model for both black ducks and mallards included observer effects. Sample sizes of black ducks were sufficient to estimate observer-specific detection rates for each crew. Estimated detection rates for black ducks were 0.62 (SE = 0.10), 0.63 (SE = 0.06), and 0.74 (SE = 0.07) for pilot-observers, 0.61 (SE = 0.08), 0.62 (SE = 0.06), and 0.81 (SE = 0.07) for other front-seat observers, and 0.43 (SE = 0.05), 0.58 (SE = 0.06), and 0.73 (SE = 0.04) for rear-seat observers. For mallards, sample sizes were adequate to generate stable maximum-likelihood estimates of observer-specific detection rates for only one aerial crew. Estimated observer-specific detection rates for that crew were 0.84 (SE = 0.04) for the pilot-observer, 0.74 (SE = 0.05) for the other front-seat observer, and 0.47 (SE = 0.03) for the rear-seat observer. Estimated observer detection rates were confounded by the position of the seat occupied by an observer, because observers did not switch seats, and by land-cover because vegetation and landform varied among crew areas. Double-observer methods with on-the-fly reconciliation, although not without challenges, offer one viable option to account for detection bias in aerial waterfowl surveys where birds are distributed at low density in remote areas that are inaccessible by ground crews. Double-observer methods, however, estimate only detection rate of animals that are potentially observable given the survey method applied. Auxiliary data and methods must be considered to estimate overall detection rate.

Journal of Wildlife Management↗
USGS1999

Survival of greater white-fronted geese: Effects of year, season, sex, and body condition

Information regarding the magnitude and variation in survival rates is necessary for understanding the causes of large changes in population size. We examined survival of greater white-fronted geese (Anser albifrons frontalis) in the Pacific Flyway during 1979-82. The population declined by 75% in the decade preceding our study but was stable during our investigation. Annual survival of adults (0.749, SE = 0.045) was 7% higher than during an earlier study. We developed a simple population model which suggests that recent (1985-96) survival rates may be as much as 10% higher in adults than the 1979-82 rate, which corresponds to population increases observed since 1985. Survival of adult females varied seasonally; monthly survival during a period of winter when no hunting or migration occurred was higher (0.986, SE = 0.015) than monthly survival at other times (0.964, SE = 0.006). Survival of adult males varied among years and with a general seasonal trend inverse to that for females. An index of body condition was positively related to survival of adult females in fall and spring, but not for adult males or immature geese. Monthly survival of immatures was lower during their first hunting season (0.886, SE = 0.026) than during all subsequent seasons (0.963, SE = 0.007). Annual survival of immatures beginning 1 October, immediately before the hunting season, was 0.471. Corresponding variations in survival rates, population numbers, and hunting regulations suggest that hunting may have influenced survival in this population of greater white-fronted geese.

Journal of Wildlife Management↗
USGS1999

Wild turkey poult survival in southcentral Iowa

Poult survival is key to understanding annual change in wild turkey (Meleagris gallopavo) populations. Survival of eastern wild turkey poults (M. g. silvestris) 0-4 weeks posthatch was studied in southcentral Iowa during 1994-97. Survival estimates of poults were calculated based on biweekly flush counts and daily locations acquired via radiotelemetry. Poult survival averaged 0.52 ?? 0.14% (?? ?? SE) for telemetry counts and 0.40 ?? 0.15 for flush counts. No within-year or across-year differences were detected between estimation techniques. More than 72% (n = 32) of documented poult mortality occurred ???14 days posthatch, and mammalian predation accounted for 92.9% of documented mortality. If mortality agents are not of concern, we suggest biologists conduct 4-week flush counts to obtain poult survival estimates for use in population models and development of harvest recommendations.

Journal of Wildlife Management↗