Geology topics

Greg A. Breed

Publications and source records attributed to Greg A. Breed.

4 recordsLinked to original sources

USGS2023

A hierarchical modelling framework for estimating individual- and population-level reproductive success from movement data

Rapidly advancing animal telemetry technologies paired with new statistical models can provide insight into the behaviour of otherwise unobservable free-living animals. Changes in behaviour apparent from pairing telemetry with statistical models often occur as animals undertake key life-history activities, such as reproduction. For many species that are secretive or occupy remote areas, these life-history events are difficult to detect with conventional survey techniques, and consequently, vital rates are difficult to estimate. We present a hierarchical modelling framework, which integrates movement data observed via animal-borne telemetry and optional, infrequent survey data, to estimate individual- and population-level reproductive success. The approach combines a mechanistic movement model and survival model, and allows for assessing the effects of hypothesized individual and environmental covariates on reproductive success. We first tested our approach with simulated data, and then applied it to movement data from migratory golden eagles ( Aquila chrysaetos) breeding in southcentral Alaska across four breeding seasons. We show that results supported our biological hypotheses that changes in movement coincided with the timing of reproductive failures, and that changes in movement could be used to assess breeding success (and failure) at the individual and population levels. The analysis also provided evidence of inter-annual variation in population-level nest success and the timing of nesting failures. This new approach is adaptable to many species that care for young and can be tracked with telemetry devices, and can provide not only individual-level information useful for testing ecological hypotheses, but estimates of demographic parameters that can directly inform conservation and management if tagged animals are representative of the population.

Methods in Ecology and Evolution↗

USGS2021

Willow drives changes in arthropod communities of northwestern Alaska: Ecological implications of shrub expansion

Arthropods serve as complex linkages between plants and higher-level predators in Arctic ecosystems and provide key ecosystem services such as pollination and nutrient cycling. Arctic plant communities are changing as tall woody shrubs expand onto tundra, but potential effects on arthropod abundance and food web structure remain unclear. Changes in vegetation structure can alter the physical habitat, thermal environment, and food available to arthropods, thereby having the potential to induce cascading effects throughout the ecosystem. We evaluated relationships between the abundance, biomass, and community composition of arthropods and the cover of several shrub taxa across tundra–shrub gradients in northwestern Alaska. While previous research had found a general positive association between arthropod biomass and shrub cover, we found heterogeneity in this relationship with finer-scale examination of (1) shrub taxa, (2) arthropod taxa, and (3) arthropod guilds. Abundance and biomass of arthropods showed strong, positive associations with the amount of cover of willow ( Salix spp.) but were not significantly influenced by shrub birch ( Betula spp.) or ericaceous (Ericaceae) vegetation. Significant shifts in arthropod community composition were also associated with willows. Among trophic groups of arthropods, herbivores and pollinators were most positively associated with willow cover. Due to geographical variation in both dominant shrub taxa and their rates of expansion, effects on arthropod communities are likely to be heterogeneous across the Arctic. Taken together, our results suggest that shrub expansion could increase food availability for higher-level insectivores and shift Arctic food web structure.

Alaska↗

USGS2016

Predicting animal home-range structure and transitions using a multistate Ornstein-Uhlenbeck biased random walk

The home‐range concept is central in animal ecology and behavior, and numerous mechanistic models have been developed to understand home range formation and maintenance. These mechanistic models usually assume a single, contiguous home range. Here we describe and implement a simple home‐range model that can accommodate multiple home‐range centers, form complex shapes, allow discontinuities in use patterns, and infer how external and internal variables affect movement and use patterns. The model assumes individuals associate with two or more home‐range centers and move among them with some estimable probability. Movement in and around home‐range centers is governed by a two‐dimensional Ornstein‐Uhlenbeck process, while transitions between centers are modeled as a stochastic state‐switching process. We augmented this base model by introducing environmental and demographic covariates that modify transition probabilities between home‐range centers and can be estimated to provide insight into the movement process. We demonstrate the model using telemetry data from sea otters ( Enhydra lutris ) in California. The model was fit using a Bayesian Markov Chain Monte Carlo method, which estimated transition probabilities, as well as unique Ornstein‐Uhlenbeck diffusion and centralizing tendency parameters. Estimated parameters could then be used to simulate movement and space use that was virtually indistinguishable from real data. We used Deviance Information Criterion (DIC) scores to assess model fit and determined that both wind and reproductive status were predictive of transitions between home‐range centers. Females were less likely to move between home‐range centers on windy days, less likely to move between centers when tending pups, and much more likely to move between centers just after weaning a pup. These tendencies are predicted by theoretical movement rules but were not previously known and show that our model can extract meaningful behavioral insight from complex movement data.

Ecology↗

USGS2016

Shifts in the distribution of molting Spectacled Eiders (Somateria fischeri) indicate ecosystem change in the Arctic

Shifts in the distribution of benthivorous predators provide an indication of underlying environmental changes in benthic-mediated ecosystems. Spectacled Eiders ( Somateria fischeri ) are benthivorous sea ducks that spend the nonbreeding portion of their annual cycle in the Bering, Chukchi, Beaufort, and East Siberian seas. Sea ducks generally molt in biologically productive areas with abundant prey. If the distribution of eiders at molting areas matches prey abundance, spatial shifts may indicate changes in environmental conditions in the Arctic. We used a randomization procedure to test for shifts in the distribution of satellite telemetry locations received from Spectacled Eiders in the 1990s and 2008–2011 within 4 late-summer, ice-free molting areas: Indigirka–Kolyma, northern Russia; Ledyard Bay, eastern Chukchi Sea; Norton Sound, northeastern Bering Sea; and Mechigmenskiy Gulf, northwestern Bering Sea. We also tested for interannual and interdecadal changes in dive depth required to reach prey, which might affect the energetic costs of foraging during the molting period. Transmitter-marked birds used each molting area in each year, although the distribution of Spectacled Eiders shifted within each area. Interdecadal shifts in Ledyard Bay and Norton Sound decreased dive depth in recent years, although minor differences in depth were biologically negligible in relation to the energetic expense of feather growth. Shifts in Mechigmenskiy Gulf and Indigirka–Kolyma did not occur consistently within or among decades, which suggests greater interannual variability among environmental factors that influence distribution in these areas. Shifts in each molting area suggest dynamic ecosystem processes, with implications for Spectacled Eiders if changes result in novel competition or predation, or in shifting prey regimes.

The Condor↗