USGS ScienceSearch

Geology topics

Juan M. Morales

Publications and source records attributed to Juan M. Morales.

4 recordsLinked to original sources

Forage senescence and disease influence elk pregnancy across the Greater Yellowstone Ecosystem

For various temperate ungulate species, recent research has highlighted the potential for spring vegetation phenology (“green-up”) to influence individual condition, with purported benefits to population productivity. However, few studies have been able to measure the benefit on vital rates directly, and fewer still have investigated the comparative influence of other phenological periods on ungulate vital rates. In this study, we tracked phenological changes throughout the duration of the growing season and examined how their timing affected the probability of pregnancy in an ungulate population. We did this for elk ( Cervus canadensis ) across the Greater Yellowstone Ecosystem (GYE) by sampling 1106 adult females in winter at 25 sites over a 13-year period and assessing sources of variation in pregnancy using a Bayesian hierarchical model. Pregnancy rates were generally high across the GYE (82.4%), and the primary influences on probability of pregnancy were the timing of vegetation senescence (“brown-down”) in autumn and exposure to the reproductive disease brucellosis. Earlier forage brown-down in fall negatively influenced the probability of pregnancy of elk aged 6–9 years by an estimated 17.2% within the range (ca. 32 days) of observed brown-down end dates. While summer habitat quality has been inferred to influence elk pregnancy previously, our findings specify the key influence of foraging conditions later in the seasonal cycle, immediately before the breeding season. The reproductive disease brucellosis was also an important factor, reducing the probability of pregnancy by 12.4% in elk in the 6- to 9-year age class. Because pregnancy was tested before most disease-induced abortions occur, the apparent mechanism for this effect is a prolonged reduction in fertility beyond the period of initial exposure in which fetal mortality is typically expected. Our results prompt greater scrutiny of the combined effects of late-season phenology and disease on reproductive rates and population productivity in temperate ungulates.

Idaho, Montana, Wyoming

Running on empty: Recharge dynamics from animal movement data

Vital rates such as survival and recruitment have always been important in the study of population and community ecology. At the individual level, physiological processes such as energetics are critical in understanding biomechanics and movement ecology and also scale up to influence food webs and trophic cascades. Although vital rates and population-level characteristics are tied with individual-level animal movement, most statistical models for telemetry data are not equipped to provide inference about these relationships because they lack the explicit, mechanistic connection to physiological dynamics. We present a framework for modelling telemetry data that explicitly includes an aggregated physiological process associated with decision making and movement in heterogeneous environments. Our framework accommodates a wide range of movement and physiological process specifications. We illustrate a specific model formulation in continuous-time to provide direct inference about gains and losses associated with physiological processes based on movement. Our approach can also be extended to accommodate auxiliary data when available. We demonstrate our model to infer mountain lion ( Puma concolor ; in Colorado, USA) and African buffalo ( Syncerus caffer ; in Kruger National Park, South Africa) recharge dynamics.

Ecology Letters

Animal movement: Statistical models for telemetry data

The study of animal movement has always been a key element in ecological science, because it is inherently linked to critical processes that scale from individuals to populations and communities to ecosystems. Rapid improvements in biotelemetry data collection and processing technology have given rise to a variety of statistical methods for characterizing animal movement. The book serves as a comprehensive reference for the types of statistical models used to study individual-based animal movement.

Book

When to be discrete: The importance of time formulation in understanding animal movement

Animal movement is essential to our understanding of population dynamics, animal behavior, and the impacts of global change. Coupled with high-resolution biotelemetry data, exciting new inferences about animal movement have been facilitated by various specifications of contemporary models. These approaches differ, but most share common themes. One key distinction is whether the underlying movement process is conceptualized in discrete or continuous time. This is perhaps the greatest source of confusion among practitioners, both in terms of implementation and biological interpretation. In general, animal movement occurs in continuous time but we observe it at fixed discrete-time intervals. Thus, continuous time is conceptually and theoretically appealing, but in practice it is perhaps more intuitive to interpret movement in discrete intervals. With an emphasis on state-space models, we explore the differences and similarities between continuous and discrete versions of mechanistic movement models, establish some common terminology, and indicate under which circumstances one form might be preferred over another. Counter to the overly simplistic view that discrete- and continuous-time conceptualizations are merely different means to the same end, we present novel mathematical results revealing hitherto unappreciated consequences of model formulation on inferences about animal movement. Notably, the speed and direction of movement are intrinsically linked in current continuous-time random walk formulations, and this can have important implications when interpreting animal behavior. We illustrate these concepts in the context of state-space models with multiple movement behavior states using northern fur seal ( Callorhinus ursinus ) biotelemetry data.

Movement Ecology