Geology topics

Michelle A. LaRue

Publications and source records attributed to Michelle A. LaRue.

6 recordsLinked to original sources

USGS2026

An Antarctic ecosystem value index to quantify ecological value across trophic levels and over time

The Southern Ocean around Antarctica is one of the fastest changing regions on the planet and an emerging resource frontier for fisheries. Here, we present the Antarctic Ecosystem Value Index created by merging ecosystem information across food web trophic levels, from phytoplankton to fish and penguins, to quantify the ecological value of marine areas around the Antarctic continent. We find that coastal polynyas - areas of reduced sea-ice - have Index values 31–72% higher than surrounding areas, suggesting that these areas are biologically valuable hot spots for a number of ice-dependent Antarctic Species. Using output from an Earth system model to generate future projections of the Index, we find that high-value locations, often within polynyas, are likely to continue to be valuable throughout the 21st century despite environmental changes. The Antarctic Ecosystem Value Index indicates that penguins lose importance as their habitat becomes increasingly unsuitable, so protecting high-value habitat areas may be critical for these species. This study also shows that while many high-value Index areas are within existing or proposed Marine Protected Areas, there are several opportunities for adopting additional protection, particularly in East Antarctica and the Amundsen Sea.

Nature Communications↗

USGS2025

Temporal and spatial equivalence in demographic responses of emperor penguins (Aptenodytes forsteri) to environmental change

1. Population ecology and biogeography applications often necessitate the transfer of models across spatial and/or temporal dimensions to make predictions outside the bounds of the data used for model fitting. However, ecological data are often spatiotemporally unbalanced such that the spatial or the temporal dimension tends to contain more data than the other. This unbalance frequently leads model transfers to become substitutions, which are predictions to a different dimension than the predictive model was built on. Despite the prevalence of substitutions in ecology, studies validating their performance and their underlying assumptions are scarce. 2. Here, we present a successful case study demonstrating both space-for-time and time-for-space substitutions using emperor penguins (Aptenodytes forsteri) as the focal species. Using abundance-based species distribution models (aSDM) of adult emperor penguins in attendance during spring across 50 colonies, we predict long-term annual fluctuations in fledgling abundance and breeding success at a single colony, Pointe Géologie. Subsequently, we construct statistical models from time series of extended counts on Pointe Géologie to predict average fledgling abundance across 50 colonies. 3. Our analysis reveals that distance to nearest open water (NOW) exhibits the strongest association with both temporal and spatial data. aSDM’s space-for-time substitution performance, as measured by Pearson correlation coefficient was 0.63 and 0.56 when predicting breeding success and fledgling abundance time series, respectively. Linear regression of fledgling abundance on NOW yields similar time-for-space substitution performance when predicting abundance distribution of emperor penguin colonies with a correlation coefficient of 0.58. 4. We posit that such space-time equivalence arises because: 1) emperor penguins colonies conform to their existing fundamental niche; 2) there is not yet any environmental novelty when comparing the spatial vs temporal variation of distance to nearest open water; and 3) models of more specific components of life histories, such as fledgling abundance, rather than occurrence or total population abundance, are more transferable. Identifying these conditions empirically can enhance the qualitative validation of substitutions in cases where direct validation data are lacking.

Journal of Animal Ecology↗

USGS2024

Detecting stochasticity in population time series using a non-parametric test of intrinsic predictability

1. Many ecological systems dominated by stochastic dynamics can produce complex time series that inherently limit forecast accuracy. The ‘intrinsic predictability’ of these systems can be approximated by a time series complexity metric called weighted permutation entropy (WPE). While WPE is a useful metric to gauge forecast performance prior to model building, it is sensitive to noise and may be biased depending on the length of the time series. Here, we introduce a simple randomized permutation test (rWPE) to assess whether a time series is intrinsically more predictable than white noise. 2. We apply rWPE to both simulated and empirical data to assess its performance and usefulness. To do this, we simulate population dynamics under various scenarios, including a linear trend, chaotic, periodic and equilibrium dynamics. We further test this approach with observed abundance time series for 932 species across four orders of animals from the Global Population Dynamics Database. Finally, using Adélie ( Pygoscelis adeliae ) and emperor penguin ( Aptenodytes forsteri ) time series as case studies, we demonstrate the application of rWPE to multiple populations for a single species. 3. We show that rWPE can determine whether a system is significantly more predictable than white noise, even with time series as short as 10 years that show an apparent trend under biologically realistic stochasticity levels. Additionally, rWPE has statistical power close to 100% when time series are at least 30 time steps long and show chaotic or periodic dynamics. Power decreases to ~10% under equilibrium dynamics, irrespective of time series length. Among four classes of animal taxa, mammals have the highest relative frequency (28%) of time series that are both longer than 30 time steps and indistinguishable from white noise in terms of complexity, followed by insects (16%), birds (16%) and bony fishes (11%). 4. rWPE is a straightforward and useful method widely applicable to any time series, including short ones. By informing forecasters of the inherent limitations to a system's predictability, it can guide a modeller's expectations for forecast performance.

Methods in Ecology and Evolution↗

USGS2015

Testing methods for using high-resolution satellite imagery to monitor polar bear abundance and distribution

High-resolution satellite imagery is a promising tool for providing coarse information about polar species abundance and distribution, but current applications are limited. With polar bears ( Ursus maritimus ), the technique has only proven effective on landscapes with little topographic relief that are devoid of snow and ice, and time-consuming manual review of imagery is required to identify bears. Here, we evaluated mechanisms to further develop methods for satellite imagery by examining data from Rowley Island, Canada. We attempted to automate and expedite detection via a supervised spectral classification and image differencing to expedite image review. We also assessed what proportion of a region should be sampled to obtain reliable estimates of density and abundance. Although the spectral signature of polar bears differed from nontarget objects, these differences were insufficient to yield useful results via a supervised classification process. Conversely, automated image differencing—or subtracting one image from another—correctly identified nearly 90% of polar bear locations. This technique, however, also yielded false positives, suggesting that manual review will still be required to confirm polar bear locations. On Rowley Island, bear distribution approximated a Poisson distribution across a range of plot sizes, and resampling suggests that sampling >50% of the site facilitates reliable estimation of density (CV <15%). Satellite imagery may be an effective monitoring tool in certain areas, but large-scale applications remain limited because of the challenges in automation and the limited environments in which the method can be effectively applied. Improvements in resolution may expand opportunities for its future uses.

Rowley Island↗

USGS2014

Polar bears from space: Assessing satellite imagery as a tool to track Arctic wildlife

Development of efficient techniques for monitoring wildlife is a priority in the Arctic, where the impacts of climate change are acute and remoteness and logistical constraints hinder access. We evaluated high resolution satellite imagery as a tool to track the distribution and abundance of polar bears. We examined satellite images of a small island in Foxe Basin, Canada, occupied by a high density of bears during the summer ice-free season. Bears were distinguished from other light-colored spots by comparing images collected on different dates. A sample of ground-truthed points demonstrated that we accurately classified bears. Independent observers reviewed images and a population estimate was obtained using mark- recapture models. This estimate (N: 94; 95% Confidence Interval: 92-105) was remarkably similar to an abundance estimate derived from a line transect aerial survey conducted a few days earlier (N: 102; 95% CI: 69-152). Our findings suggest that satellite imagery is a promising tool for monitoring polar bears on land, with implications for use with other Arctic wildlife. Large scale applications may require development of automated detection processes to expedite review and analysis. Future research should assess the utility of multi-spectral imagery and examine sites with different environmental characteristics.

PLoS ONE↗

USGS2013

Climate change winners: receding ice fields facilitate colony expansion and altered dynamics in an Adélie penguin metapopulation

There will be winners and losers as climate change alters the habitats of polar organisms. For an Adélie penguin (Pygoscelis adeliae) colony on Beaufort Island (Beaufort), part of a cluster of colonies in the southern Ross Sea, we report a recent population increase in response to increased nesting habitat as glaciers have receded. Emigration rates of birds banded as chicks on Beaufort to colonies on nearby Ross Island decreased after 2005 as available habitat on Beaufort increased, leading to altered dynamics of the metapopulation. Using aerial photography beginning in 1958 and modern satellite imagery, we measured change in area of available nesting habitat and population size of the Beaufort colony. Population size varied with available habitat, and both increased rapidly since the 1990s. In accord with glacial retreat, summer temperatures at nearby McMurdo Station increased by ~0.50°C per decade since the mid-1980s. Although the Ross Sea is likely to be the last ocean with an intact ecosystem, the recent retreat of ice fields at Beaufort that resulted in increased breeding habitat exemplifies a process that has been underway in the Ross Sea during the entire Holocene. Furthermore, our results are in line with predictions that major ice shelves and glaciers will retreat rapidly elsewhere in the Antarctic, potentially leading to increased breeding habitat for Adélie penguins. Results further indicated that satellite imagery may be used to estimate large changes in Adélie penguin populations, facilitating our understanding of metapopulation dynamics and environmental factors that influence regional populations.

PLoS ONE↗