Geology topics

Shawn T. McKinney

Publications and source records attributed to Shawn T. McKinney.

9 recordsLinked to original sources

USGS2020

Testing prediction accuracy in short-term ecological studies

Applied ecology is based on an assumption that a management action will result in a predicted outcome. Testing the prediction accuracy of ecological models is the most powerful way of evaluating the knowledge implicit in this cause-effect relationship, however, the prevalence of predictive modeling and prediction testing are spreading slowly in ecology. The challenge of prediction testing is particularly acute for small-scale studies, because withholding data for prediction testing (e.g., via k -fold cross validation) can reduce model precision. However, by necessity small-scale studies are common. We use one such study that explored small mammal abundance along an elevational gradient to test prediction accuracy of models with varying degrees of information content. For each of three small mammal species, we conducted 5000 iterations of the following process: (1) randomly selected 75 % of the data to develop generalized linear models of species abundance that used detailed site measurements as covariates, (2) used an information theoretic approach to compare the top model with detailed covariates to habitat type-only and null models constructed with the same data, (3) tested those models’ ability to predict the 25 % of the randomly withheld data, and (4) evaluated prediction accuracy with a quadratic loss function. Detailed models fit the model-evaluation data best but had greater expected prediction error when predicting out-of-sample data relative to the habitat type models. Relationships between species and detailed site variables may be evident only within the framework of explicitly hierarchical analyses. We show that even with a small but relatively typical dataset ( n = 28 sampling locations across 125 km over two years), researchers can effectively compare models with different information content and measure models’ predictive power, thus evaluating their own ecological understanding and defining the limits of their inferences. Identifying the appropriate scope of inference through prediction testing is ecologically valuable and is attainable even with small datasets.

Maine, New Hampshire↗

USGS2020

Combined influence of intrinsic and environmental factors in shaping productivity in a small pelagic gull, the black-legged kittiwake Rissa tridactyla

While we have a good understanding in many systems of the effects of single variable changes on organisms, we understand far less about how variables act in concert to affect living systems, where interactions among variables can lead to unanticipated results. We used mixed-effect models to evaluate the effects of multiple variables that we expected to play a role in the early reproductive stages of a North Pacific seabird, the black-legged kittiwake Rissa tridactyla, during 1992-2008 using data collected on known-aged individuals. Our work revealed the potential for contrasting stressor effects across successive stages of reproduction. Bird age, timing of egg laying, and winter ENSO conditions best explained individual laying success, such that laying success was greater when parents were older, the average winter ENSO index was positive (as occurs during El Niño episodes), and the median laying date for the colony was earlier. Age and salmon run timing (a proxy for predator presence at the colony) best explained hatching success, such that hatching success was greater when parents were older and when salmon runs were early. Identifying such differential effects of multiple stressors across consecutive reproductive stages can greatly enhance our ability to interpret trends and manage populations in the face of changes currently occurring in living systems.

Marine Ecology Progress Series↗

USGS2019

Satellite-detected forest disturbance forecasts American marten population decline: The case for supportive space-based monitoring

Limited monitoring resources often constrain rigorous monitoring practices to species or populations of conservation concern. Insufficient monitoring can induce a tautology as lack of monitoring resources makes it difficult to determine whether a species or population deserves additional monitoring resources. When in-situ monitoring resources are limited, remote habitat monitoring could be a useful supplementary tool, as linking parameterized species distribution models to spatially explicit time-series of environmental correlates allows iterative prediction of population change. Yet the performance of predictive forecasts or hindcasts has been difficult to evaluate. We paired contemporary field data, historic population estimates, and a remotely-sensed archive of landscape change to evaluate predictions of American marten ( Martes americana ) population decline owing to habitat loss in Maine, USA. We estimated contemporary spatial patterns in marten density relative to landscape disturbance with spatial capture-recapture models. We compared current density estimates to historical density calculations to evaluate population decline, and compared historical calculations to habitat-based model predictions to evaluate the efficacy of habitat monitoring as a proxy for direct monitoring. Marten density was negatively associated with the proportion of surrounding regenerating forest, and point estimates within focal townships were 50–80% lower than historical calculations. Habitat-based hindcasts of marten density across our entire focal area interest suggested a smaller population decline (roughly 50%) within our focal area. Thus, although habitat-based predictions underpredicted marten decline, they provided correct directional inference. Habitat monitoring and predictions from species distribution models may provide useful inference about population changes given trends in habitat at limited expense when in-situ information is lacking.

Maine↗

USGS2019

Survival and recruitment dynamics of Black-legged Kittiwakes Rissa tridactyla at an Alaskan colony

The majority of seabirds breed colonially and exhibit considerable site fidelity over the course of their long lifespans. Initial colony selection can therefore have substantial fitness consequences; however, factors contributing to recruitment into colonies and subsequent fidelity remain unclear. We used multi-state capture-recapture models to test several hypotheses related to apparent fledgling survival, the probability of recruitment to natal colonies, and apparent post-recruitment survival in Black-legged Kittiwakes with data from individuals banded as chicks and subsequently resighted at a colony in south-central Alaska over a twenty-year period. Competitive models suggested that apparent fledgling survival declined throughout our study; this decline was likely driven by intrinsic, cohort-specific processes and was not explainable by post-fledging wind and climate conditions. Independent resightings at other colonies suggest the apparent decline may have been at least partially influenced by permanent emigration (natal dispersal) that occurred more frequently when the colony size was large. Recruitment was primarily age-dependent, with no detectable effect of early life experience or annual changes in colony size, colony productivity, climate, or average weather conditions. We estimated an average recruitment age of seven years, which is older than typically reported for Atlantic kittiwake populations, and supports a more conservative life history strategy for kittiwakes in the Pacific. Variation in apparent survival of recruits was cohort-specific and did not correlate with age or annual changes in the factors listed above. Instead, apparent survival of recruits was best explained by colony size during a cohort’s second year, suggesting a degree of negative density dependence in post-recruitment survival or fidelity. This information could prove useful to managers deciding how to allocate resources among small, growing colonies and large, well-established colonies.

Alaska↗

USGS2018

Experimental evidence of long-term reproductive costs in a colonial nesting seabird

Trade-offs between current and future reproduction are central to the evolution of life histories. Experiments that manipulate brood size provide an effective approach to investigating future costs of current reproduction. Most manipulative studies to date, however, have addressed only the short-term effects of brood size manipulation. Our goal was to determine whether survival or breeding costs of reproduction in a long-lived species manifest beyond the subsequent breeding season. To this end, we investigated long-term survival and breeding effects of a multi-year reproductive cost experiment conducted on black-legged kittiwakes Rissa tridactyla , a long-lived colonial nesting seabird. We used multi-state capture–recapture modeling to assess hypotheses regarding the role of experimentally reduced breeding effort and other factors, including climate phase and colony size and productivity, on future survival and breeding probabilities during the 16-yr period following the experiment. We found that forced nest failures had a positive effect on breeding probability over time, but had no effect on long-term survival. This apparent canalization of survival suggests that adult survival is the most important parameter influencing fitness in this long-lived species, and that adults should pay reproductive costs in ways that do not compromise this critical life history parameter. When declines in adult survival rate are observed, they may indicate populations of conservation concern.

Alaska↗

USGS2017

Pairing field methods to improve inference in wildlife surveys while accommodating detection covariance

It is common to use multiple field sampling methods when implementing wildlife surveys to compare method efficacy or cost efficiency, integrate distinct pieces of information provided by separate methods, or evaluate method-specific biases and misclassification error. Existing models that combine information from multiple field methods or sampling devices permit rigorous comparison of method-specific detection parameters, enable estimation of additional parameters such as false-positive detection probability, and improve occurrence or abundance estimates, but with the assumption that the separate sampling methods produce detections independently of one another. This assumption is tenuous if methods are paired or deployed in close proximity simultaneously, a common practice that reduces the additional effort required to implement multiple methods and reduces the risk that differences between method-specific detection parameters are confounded by other environmental factors. We develop occupancy and spatial capture–recapture models that permit covariance between the detections produced by different methods, use simulation to compare estimator performance of the new models to models assuming independence, and provide an empirical application based on American marten ( Martes americana ) surveys using paired remote cameras, hair catches, and snow tracking. Simulation results indicate existing models that assume that methods independently detect organisms produce biased parameter estimates and substantially understate estimate uncertainty when this assumption is violated, while our reformulated models are robust to either methodological independence or covariance. Empirical results suggested that remote cameras and snow tracking had comparable probability of detecting present martens, but that snow tracking also produced false-positive marten detections that could potentially substantially bias distribution estimates if not corrected for. Remote cameras detected marten individuals more readily than passive hair catches. Inability to photographically distinguish individual sex did not appear to induce negative bias in camera density estimates; instead, hair catches appeared to produce detection competition between individuals that may have been a source of negative bias. Our model reformulations broaden the range of circumstances in which analyses incorporating multiple sources of information can be robustly used, and our empirical results demonstrate that using multiple field-methods can enhance inferences regarding ecological parameters of interest and improve understanding of how reliably survey methods sample these parameters.

Maine↗

USGS2017

Intraspecific functional diversity of common species enhances community stability

Common species are fundamental to the structure and function of their communities and may enhance community stability through intraspecific functional diversity (iFD). We measured among-habitat and within-habitat iFD (i.e., among- and within-plant community types) of two common small mammal species using stable isotopes and functional trait dendrograms, determined whether iFD was related to short-term population stability and small mammal community stability, and tested whether spatially explicit trait filters helped explain observed patterns of iFD. Southern red-backed voles ( Myodes gapperi ) had greater iFD than deer mice ( Peromyscus maniculatus ), both among habitats, and within the plant community in which they were most abundant (their “primary habitat”). Peromyscus maniculatus populations across habitats differed significantly between years and declined 78% in deciduous forests, their primary habitat, as did the overall deciduous forest small mammal community. Myodes gapperi populations were stable across habitats and within coniferous forest, their primary habitat, as was the coniferous forest small mammal community. Generalized linear models representing internal trait filters (e.g., competition), which increase within-habitat type iFD, best explained variation in M. gapperi diet, while models representing internal filters and external filters (e.g., climate), which suppress within-habitat iFD, best explained P. maniculatus diet. This supports the finding that M. gapperi had higher iFD than P. maniculatus and is consistent with the theory that internal trait filters are associated with higher iFD than external filters. Common species with high iFD can impart a stabilizing influence on their communities, information that can be important for conserving biodiversity under environmental change.

Ecology and Evolution↗

USGS2015

Record long-distance movement of a Deer Mouse, Peromyscus maniculatus , in a New England montane boreal forest

We report a single-season, non-homing movement of 4287 ± 10 m by an adult male Deer Mouse, Peromyscus maniculatus , in western Maine, United States, in summer 2014. The movement was achieved in two stages: 927 ± 3 m in four days and an additional 3360 ± 10 m in 44 days. This is approximately 40% greater than the previously documented maximum linear movement for an individual of this species.

Maine↗

USGS2015

On theory in ecology: Another perspective

We agree with Marquet and colleagues ( 2014 ) that the balance between theory and data is an important one. However, their description of what constitutes good theory in ecology ignores the most important characteristic of successful theory—that it accurately and precisely describes the way the world works.

BioScience↗