Scholarly Work - Ecology

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    Estimating apparent survival of sub-adult and adult white sharks (Carcharodon carcharias) in central California using mark-recapture methods
    (2015-04) Kanive, Paul Edward, Jr.; Rotella, Jay J.; Jorgensen, Salvador J.; Chapple, Taylor K.; Anderson, Scot D.; Klimley, A. Peter; Block, Barbara A.
    Quantifying life history parameters of marine top predators is challenging, as observations are difficult and uncertainty in sex assignment can confound the determination of sex specific parameters. However, these parameters are critical for accurate population assessments and understanding of population dynamics. Using mark recapture observations at white shark foraging aggregation sites, we tested for differences in survival between sexes and estimated apparent survival for sub-adult and adult white sharks in neritic waters off central California. We used 6 years of mark-recapture data and a model that accounted for imperfect detection and imperfect sex assignment. Empirical information based on direct observations suggests that there are no sex-specific or temporal differences in survival during the study period and that survival was estimated to be 0.90; SE = 0.04. Additionally, after animals whose sex was unknown throughout the study period were probabilistically assigned to sex, the ratio in this sample is estimated to be 2.1 males for every female observed. This estimated ratio is lower than the observed ratio of 3:1. We demonstrate that the estimated capture probability for males was roughly twice as high as that for females (0.41, SE = 0.06 and 0.19, SE = 0.07 respectively). Together these results suggest (1) that the sex ratio is uneven but not as skewed as uncorrected observation data would suggest and (2) that unequal mortality in older age classes are not the cause of the observed sex bias but more likely results from disparate mortality earlier in life or differences in behavior. Future research is needed to explore the potential causes of the observed sex bias.
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    Using pedigree reconstruction to estimate population size: genotypes are more than individually unique marks
    (2013-04) Creel, Scott; Rosenblatt, Elias G.
    Estimates of population size are critical for conservation and management, but accurate estimates are difficult to obtain for many species. Noninvasive genetic methods are increasingly used to estimate population size, particularly in elusive species such as large carnivores, which are difficult to count by most other methods. In most such studies, genotypes are treated simply as unique individual identifiers. Here, we develop a new estimator of population size based on pedigree reconstruction. The estimator accounts for individuals that were directly sampled, individuals that were not sampled but whose genotype could be inferred by pedigree reconstruction, and individuals that were not detected by either of these methods. Monte Carlo simulations show that the population estimate is unbiased and precise if sampling is of sufficient intensity and duration. Simulations also identified sampling conditions that can cause the method to overestimate or underestimate true population size; we present and discuss methods to correct these potential biases. The method detected 2–21% more individuals than were directly sampled across a broad range of simulated sampling schemes. Genotypes are more than unique identifiers, and the information about relationships in a set of genotypes can improve estimates of population size.
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    Neonatal mortality of elk driven by climate, predator phenology and predator community composition
    (2011-05) Griffin, K.; Hebblewhite, Mark; Robinson, H.; Zager, Peter; Barber-Meyer, S.; Christianson, David A.; Creel, Scott; Harris, N.; Hurley, M.; Jackson, D.
    Understanding the interaction among predators and between predation and climate is critical to understanding the mechanisms for compensatory mortality. We used data from 1999 radio-marked neonatal elk (Cervus elaphus) calves from 12 populations in the north-western United States to test for effects of predation on neonatal survival, and whether predation interacted with climate to render mortality compensatory. Weibull survival models with a random effect for each population were fit as a function of the number of predator species in a community (3–5), seven indices of climatic variability, sex, birth date, birth weight, and all interactions between climate and predators. Cumulative incidence functions (CIF) were used to test whether the effects of individual species of predators were additive or compensatory. Neonatal elk survival to 3 months declined following hotter previous summers and increased with higher May precipitation, especially in areas with wolves and/or grizzly bears. Mortality hazards were significantly lower in systems with only coyotes (Canis latrans), cougars (Puma concolor) and black bears (Ursus americanus) compared to higher mortality hazards experienced with gray wolves (Canis lupus) and grizzly bears (Ursus horribilis). In systems with wolves and grizzly bears, mortality by cougars decreased, and predation by bears was the dominant cause of neonatal mortality. Only bear predation appeared additive and occurred earlier than other predators, which may render later mortality by other predators compensatory as calves age. Wolf predation was low and most likely a compensatory source of mortality for neonatal elk calves. Functional redundancy and interspecific competition among predators may combine with the effects of climate on vulnerability to predation to drive compensatory mortality of neonatal elk calves. The exception was the evidence for additive bear predation. These results suggest that effects of predation by recovering wolves on neonatal elk survival, a contentious issue for management of elk populations, may be less important than the composition of the predator community. Future studies would benefit by synthesizing overwinter calf and adult-survival data sets, ideally from experimental studies, to test the roles of predation in annual compensatory and additive mortality of elk.
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    A survey of the effects of wolf predation risk on pregnancy rates and calf recruitment in elk
    (2011-12) Creel, Scott; Christianson, David A.; Winnie, John A. Jr.
    We have previously found that the behavioral responses of elk to the risk of predation by wolves are correlated with changes in habitat selection, altered diets, reduced food intake, decreased fecal progesterone concentrations, and decreased calf recruitment. P. J. White et al. recently questioned these results, concluding that “multiple lines of evidence and/or strong validation should be brought to bear before relying on indirect measures of how predators affect pregnancy rates.” Here, we systematically surveyed available data and found that five studies (with data from 10 widely distributed populations) have directly detected decreases of 24–43% in elk pregnancy rates in response to increased predation risk. This survey includes data not discussed by White et al. from their own research, which reveal a 32% decrease in pregnancy rates following wolf recolonization in central Yellowstone. Following the survey of available data, we discuss several methodological and statistical problems in White et al.'s study that would be expected to mask the effects of predation risk. While other factors also clearly affect elk recruitment, multiple lines of evidence using a broad array of methods have detected an association between predation risk and reduced reproduction in elk.
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    Toward a predictive theory of risk effects: hypotheses for prey attributes and compensatory mortality
    (2011-12) Creel, Scott
    Risk effects, or the costs of antipredator behavior, can comprise a large proportion of the total effect of predators on their prey. While empirical studies are accumulating to demonstrate the importance of risk effects, there is no general theory that predicts the relative importance of risk effects and direct predation. Working toward this general theory, it has been shown that functional traits of predators (e.g., hunting modes) help to predict the importance of risk effects for ecosystem function. Here, I note that attributes of the predator, the prey, and the environment are all important in determining the strength of antipredator responses, and I develop hypotheses for the ways that prey functional traits might influence the magnitude of risk effects. In particular, I consider the following attributes of prey: group size and dilution of direct predation risk, the degree of foraging specialization, body mass, and the degree to which direct predation is additive vs. compensatory. Strong tests of these hypotheses will require continued development of methods to identify and quantify the fitness costs of antipredator responses in wild populations.
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    Inferential consequences of modeling rather than measuring snow accumulation in studies of animal ecology
    (2013-04)
    It is increasingly common for studies of animal ecology to use model-based predictions of environmental variables as explanatory or predictor variables, even though model prediction uncertainty is typically unknown. To demonstrate the potential for misleading inferences when model predictions with error are used in place of direct measurements, we compared snow water equivalent (SWE) and snow depth as predicted by the Snow Data Assimilation System (SNODAS) to field measurements of SWE and snow depth. We examined locations on elk (Cervus canadensis) winter ranges in western Wyoming, because modeled data such as SNODAS output are often used for inferences on elk ecology. Overall, SNODAS predictions tended to overestimate field measurements, prediction uncertainty was high, and the difference between SNODAS predictions and field measurements was greater in snow shadows for both snow variables compared to non-snow shadow areas. We used a simple simulation of snow effects on the probability of an elk being killed by a predator to show that, if SNODAS prediction uncertainty was ignored, we might have mistakenly concluded that SWE was not an important factor in where elk were killed in predatory attacks during the winter. In this simulation, we were interested in the effects of snow at finer scales (<1 km2) than the resolution of SNODAS. If bias were to decrease when SNODAS predictions are averaged over coarser scales, SNODAS would be applicable to population-level ecology studies. In our study, however, averaging predictions over moderate to broad spatial scales (9–2200 km2) did not reduce the differences between SNODAS predictions and field measurements. This study highlights the need to carefully evaluate two issues when using model output as an explanatory variable in subsequent analysis: (1) the model's resolution relative to the scale of the ecological question of interest and (2) the implications of prediction uncertainty on inferences when using model predictions as explanatory or predictor variables.
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