Dataset Information

Individual and seasonal variation in the movement behavior of two tropical nectarivorous birds.

ABSTRACT:

Background

Movement of animals directly affects individual fitness, yet fine spatial and temporal resolution movement behavior has been studied in relatively few small species, particularly in the tropics. Nectarivorous Hawaiian honeycreepers are believed to be highly mobile throughout the year, but their fine-scale movement patterns remain unknown. The movement behavior of these crucial pollinators has important implications for forest ecology, and for mortality from avian malaria (Plasmodium relictum), an introduced disease that does not occur in high-elevation forests where Hawaiian honeycreepers primarily breed.

Methods

We used an automated radio telemetry network to track the movement of two Hawaiian honeycreeper species, the 'apapane (Himatione sanguinea) and 'i'iwi (Drepanis coccinea). We collected high temporal and spatial resolution data across the annual cycle. We identified movement strategies using a multivariate analysis of movement metrics and assessed seasonal changes in movement behavior.

Results

Both species exhibited multiple movement strategies including sedentary, central place foraging, commuting, and nomadism , and these movement strategies occurred simultaneously across the population. We observed a high degree of intraspecific variability at the individual and population level. The timing of the movement strategies corresponded well with regional bloom patterns of 'ōhi'a (Metrosideros polymorpha) the primary nectar source for the focal species. Birds made long-distance flights, including multi-day forays outside the tracking array, but exhibited a high degree of fidelity to a core use area, even in the non-breeding period. Both species visited elevations where avian malaria can occur but exhibited little seasonal change in elevation (< 150 m) and regularly returned to high-elevation roosts at night.

Conclusions

This study demonstrates the power of automated telemetry to study complex and fine-scale movement behaviors in rugged tropical environments. Our work reveals a system in which birds can track shifting resources using a diverse set of movement behaviors and can facultatively respond to environmental change. Importantly, fidelity to high-elevation roosting sites minimizes nocturnal exposure to avian malaria for far-ranging individuals and is thus a beneficial behavior that may be under high selection pressure.

SUBMITTER: Smetzer JR

PROVIDER: S-EPMC8264974 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Animal movement comes in a variety of 'types' including small foraging movements, larger one-way dispersive movements, seasonally-predictable round-trip migratory movements, and erratic nomadic movements. Although most individuals move at some point throughout their lives, movement patterns can vary widely across individuals within the same species: differing within an individual over time (intra-individual), among individuals in the same population (inter-individual), or among populations (inter-population). Yet, studies of movement (theoretical and empirical alike) more often focus on understanding 'typical' movement patterns than understanding variation in movement. Here, I synthesize current knowledge of movement variation (drawing parallels across species and movement types), describing the causes (what factors contribute to individual variation), patterns (what movement variation looks like), consequences (why variation matters), maintenance (why variation persists), implications (for management and conservation), and finally gaps (what pieces we are currently missing). By synthesizing across scales of variation, I span across work on plasticity, personality, and geographic variation. Individual movement can be driven by factors that act at the individual, population, community and ecosystem level and have ramifications at each of these levels. Generally the consequences of movement are less well understood than the causes, in part because the effects of movement variation are often nested, with variation manifesting at the population level, which in turn affects communities and ecosystems. Understanding both cause and consequence is particularly important for predicting when variation begets variation in a positive feedback loop, versus when a negative feedback causes variation to be dampened successively. Finally, maintaining standing variation in movement may be important for facilitating species' ability to respond to future environmental change.

Project description:Animal movement is the mechanism connecting landscapes to fitness, and understanding variation in seasonal animal movements has benefited from the analysis and categorization of animal displacement. However, seasonal movement patterns can defy classification when movements are highly variable. Hidden Markov movement models (HMMs) are a class of latent-state models well-suited to modeling movement data. Here, we used HMMs to assess seasonal patterns of variation in the movement of pronghorn (Antilocapra americana), a species known for variable seasonal movements that challenge analytical approaches, while using a population of mule deer (Odocoileus hemionus), for whom seasonal movements are well-documented, as a comparison. We used population-level HMMs in a Bayesian framework to estimate a seasonal trend in the daily probability of transitioning between a short-distance local movement state and a long-distance movement state. The estimated seasonal patterns of movements in mule deer closely aligned with prior work based on indices of animal displacement: a short period of long-distance movements in the fall season and again in the spring, consistent with migrations to and from seasonal ranges. We found seasonal movement patterns for pronghorn were more variable, as a period of long-distance movements in the fall was followed by a winter period in which pronghorn were much more likely to further initiate and remain in a long-distance movement pattern compared with the movement patterns of mule deer. Overall, pronghorn were simply more likely to be in a long-distance movement pattern throughout the year. Hidden Markov movement models provide inference on seasonal movements similar to other methods, while providing a robust framework to understand movement patterns on shorter timescales and for more challenging movement patterns. Hidden Markov movement models can allow a rigorous assessment of the drivers of changes in movement patterns such as extreme weather events and land development, important for management and conservation.

Project description:Teleost fishes occupy a range of ecosystem, and habitat types subject to large seasonal fluctuations. Temperate fishes, in particular, survive large seasonal shifts in temperature, light availability, and access to certain habitats. Mobile species such as lake trout (Salvelinus namaycush) can behaviorally respond to seasonal variation by shifting their habitat deeper and further offshore in response to warmer surface water temperatures during the summer. During cooler seasons, the use of more structurally complex nearshore zones by lake trout could increase cognitive demands and potentially result in a larger relative brain size during those periods. Yet, there is limited understanding of how such behavioral responses to a seasonally shifting environment might shape, or be shaped by, the nervous system.Here, we quantified variation in relative brain size and the size of five externally visible brain regions in lake trout, across six consecutive seasons in two different lakes. Acoustic telemetry data from one of our study lakes were collected during the study period from a different subset of individuals and used to infer relationships between brain size and seasonal behaviors (habitat use and movement rate).Our results indicated that lake trout relative brain size was larger in the fall and winter compared with the spring and summer in both lakes. Larger brains coincided with increased use of nearshore habitats and increased horizontal movement rates in the fall and winter based on acoustic telemetry. The telencephalon followed the same pattern as whole brain size, while the other brain regions (cerebellum, optic tectum, olfactory bulbs, and hypothalamus) were only smaller in the spring.These findings provide evidence that flexibility in brain size could underpin shifts in behavior, which could potentially subserve functions associated with differential habitat use during cold and warm seasons and allow fish to succeed in seasonally variable environments.