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Using hierarchical bayes to understand movement, health, and survival in the endangered north atlantic right whale.

Schick RS, Kraus SD, Rolland RM, Knowlton AR, Hamilton PK, Pettis HM, Kenney RD, Clark JS - PLoS ONE (2013)

Bottom Line: We also included the effect of reproductive status and entanglement status on health.The resulting time series of individual health highlight both normal variations in health status and how anthropogenic stressors can affect the health and, ultimately, the survival of individuals.This modeling approach provides information for monitoring of health in right whales, as well as a framework for integrating observational data at the level of individuals up through the health status of the population.

View Article: PubMed Central - PubMed

Affiliation: Nicholas School of the Environment, Duke University, Durham, North Carolina, United States of America. rss5@st-andrews.ac.uk

ABSTRACT
Body condition is an indicator of health, and it plays a key role in many vital processes for mammalian species. While evidence of individual body condition can be obtained, these observations provide just brief glimpses into the health state of the animal. An analytical framework is needed for understanding how health of animals changes over space and time.Through knowledge of individual health we can better understand the status of populations. This is particularly important in endangered species, where the consequences of disruption of critical biological functions can push groups of animals rapidly toward extinction. Here we built a state-space model that provides estimates of movement, health, and survival. We assimilated 30+ years of photographic evidence of body condition and three additional visual health parameters in individual North Atlantic right whales, together with survey data, to infer the true health status as it changes over space and time. We also included the effect of reproductive status and entanglement status on health. At the population level, we estimated differential movement patterns in males and females. At the individual level, we estimated the likely animal locations each month. We estimated the relationship between observed and latent health status. Observations of body condition, skin condition, cyamid infestation on the blowholes, and rake marks all provided measures of the true underlying health. The resulting time series of individual health highlight both normal variations in health status and how anthropogenic stressors can affect the health and, ultimately, the survival of individuals. This modeling approach provides information for monitoring of health in right whales, as well as a framework for integrating observational data at the level of individuals up through the health status of the population. This framework can be broadly applied to a variety of systems - terrestrial and marine - where sporadic observations of individuals exist.

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Graphical depiction of the statistical model.Graphical model depicting the dependency structure. We have observation models for the visual health parameters H, for survey effort E, and for sightings Y (top panel). The middle panel comprises two process models for the latent states of health h, and movement, z. Lastly, survival, s, is estimated as a function of latent health and movement.
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pone-0064166-g004: Graphical depiction of the statistical model.Graphical model depicting the dependency structure. We have observation models for the visual health parameters H, for survey effort E, and for sightings Y (top panel). The middle panel comprises two process models for the latent states of health h, and movement, z. Lastly, survival, s, is estimated as a function of latent health and movement.

Mentions: To make inference on the movement patterns, relative health status, and ultimately survival of individuals, we built a hierarchical Bayesian model. The temporal resolution of the model is monthly dating from 1980 to present; the spatial resolution is at the level of the primary geographic regions that comprise right whale habitat (Figure 1). The model assimilates aerial and vessel survey information, locations of identified individual right whales, photographic evidence of health status across several health parameters comprised of ordinal classes, and prior knowledge. The three process models in the main model provide inference on movement, health, and survival of individual right whales (Figure 4). Class, or population-level, summaries can be inferred.


Using hierarchical bayes to understand movement, health, and survival in the endangered north atlantic right whale.

Schick RS, Kraus SD, Rolland RM, Knowlton AR, Hamilton PK, Pettis HM, Kenney RD, Clark JS - PLoS ONE (2013)

Graphical depiction of the statistical model.Graphical model depicting the dependency structure. We have observation models for the visual health parameters H, for survey effort E, and for sightings Y (top panel). The middle panel comprises two process models for the latent states of health h, and movement, z. Lastly, survival, s, is estimated as a function of latent health and movement.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3675107&req=5

pone-0064166-g004: Graphical depiction of the statistical model.Graphical model depicting the dependency structure. We have observation models for the visual health parameters H, for survey effort E, and for sightings Y (top panel). The middle panel comprises two process models for the latent states of health h, and movement, z. Lastly, survival, s, is estimated as a function of latent health and movement.
Mentions: To make inference on the movement patterns, relative health status, and ultimately survival of individuals, we built a hierarchical Bayesian model. The temporal resolution of the model is monthly dating from 1980 to present; the spatial resolution is at the level of the primary geographic regions that comprise right whale habitat (Figure 1). The model assimilates aerial and vessel survey information, locations of identified individual right whales, photographic evidence of health status across several health parameters comprised of ordinal classes, and prior knowledge. The three process models in the main model provide inference on movement, health, and survival of individual right whales (Figure 4). Class, or population-level, summaries can be inferred.

Bottom Line: We also included the effect of reproductive status and entanglement status on health.The resulting time series of individual health highlight both normal variations in health status and how anthropogenic stressors can affect the health and, ultimately, the survival of individuals.This modeling approach provides information for monitoring of health in right whales, as well as a framework for integrating observational data at the level of individuals up through the health status of the population.

View Article: PubMed Central - PubMed

Affiliation: Nicholas School of the Environment, Duke University, Durham, North Carolina, United States of America. rss5@st-andrews.ac.uk

ABSTRACT
Body condition is an indicator of health, and it plays a key role in many vital processes for mammalian species. While evidence of individual body condition can be obtained, these observations provide just brief glimpses into the health state of the animal. An analytical framework is needed for understanding how health of animals changes over space and time.Through knowledge of individual health we can better understand the status of populations. This is particularly important in endangered species, where the consequences of disruption of critical biological functions can push groups of animals rapidly toward extinction. Here we built a state-space model that provides estimates of movement, health, and survival. We assimilated 30+ years of photographic evidence of body condition and three additional visual health parameters in individual North Atlantic right whales, together with survey data, to infer the true health status as it changes over space and time. We also included the effect of reproductive status and entanglement status on health. At the population level, we estimated differential movement patterns in males and females. At the individual level, we estimated the likely animal locations each month. We estimated the relationship between observed and latent health status. Observations of body condition, skin condition, cyamid infestation on the blowholes, and rake marks all provided measures of the true underlying health. The resulting time series of individual health highlight both normal variations in health status and how anthropogenic stressors can affect the health and, ultimately, the survival of individuals. This modeling approach provides information for monitoring of health in right whales, as well as a framework for integrating observational data at the level of individuals up through the health status of the population. This framework can be broadly applied to a variety of systems - terrestrial and marine - where sporadic observations of individuals exist.

Show MeSH
Related in: MedlinePlus