[MARMAM] Paper: New insights into the diets of harbor seals (Phoca vitulina) in the Salish Sea revealed by analysis of fatty acid signatures

[Bromaghin, Jeffrey]

Bromaghin, J. F., M. M. Lance, E. W. Elliot, S. J. Jeffries, A.
Acevedo-Gutiérrez, and J. M. Kennish. 2013. New insights into the diets of
harbor seals in the Salish Sea revealed by quantitative fatty acid
signature analysis. *Fishery Bulletin* 111:13-26.
doi:10.7755/FB.111.1.2

Abstract
Harbor seals (Phoca vitulina) are an abundant predator along the west coast
of North America, and there is considerable interest in their diet
composition, especially in regard to predation on valued fish stocks.
Available information on harbor seal diets, primarily derived from scat
analysis, suggests that adult salmon (Oncorhynchus spp.), Pacific Herring
(Clupea pallasii), and gadids predominate. Because diet assessments based
on scat analysis may be biased, we investigated diet composition
through quantitative analysis of fatty acid signatures. Blubber samples
from 49 harbor seals captured in western North America from
haul-outs within the area of the San Juan Islands and southern Strait of
Georgia in the Salish Sea were analyzed for fatty acid composition, along
with 269 fish and squid specimens representing 27 potential prey
classes. Diet estimates varied spatially,  demographically, and among
individual harbor seals. Findings confirmed the prevalence of previously
identified prey species in harbor seal diets, but other species also
contributed significantly. In particular, Black (Sebastes melanops) and
Yellowtail (S. flavidus) Rockfish were estimated to compose up to 50% of
some individual seal diets. Specialization and high predation rates on
Black and Yellowtail Rockfish by a subset of harbor seals may play a role
in the population dynamics of these regional rockfish stocks that is
greater than previously realized.

---
Jeffrey F. Bromaghin, PhD
Research Statistician
USGS Alaska Science Center
4210 University Drive
Anchorage, AK 99508
907-786-7086
jbromag...@usgs.govhttps://mail.google.com/mail/?view=cmfs=1tf=1to=jbromag...@usgs.gov
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[MARMAM] Diet Estimation Paper

[Bromaghin, Jeffrey]

Dear colleagues,



I am pleased to announce the publication of research investigating the
performance of diet estimators based on quantitative fatty acid signature
analysis (QFASA), a method that has been widely utilized for marine species.



Citation:

Bromaghin, J. F., K. D. Rode, S. M. Budge, and G. W. Thiemann. 2015.
Distance measures and optimization spaces in quantitative fatty acid
signature analysis. Ecology and Evolution 5(6):1249-1262.


Abstract:

Quantitative fatty acid signature analysis has become an important method
of diet estimation in ecology, especially marine ecology. Controlled
feeding trials to validate the method and estimate the calibration
coefficients necessary to account for differential metabolism of individual
fatty acids have been conducted with several species from diverse taxa.
However, research into potential refinements of the estimation method has
been limited. We compared the performance of the original method of
estimating diet composition with that of five variants based on different
combinations of distance measures and calibration-coefficient
transformations between prey and predator fatty acid signature spaces.
Fatty acid signatures of pseudopredators were constructed using known diet
mixtures of two prey data sets previously used to estimate the diets of
polar bears *Ursus maritimus* and gray seals *Halichoerus grypus*, and
their diets were then estimated using all six variants. In addition,
previously published diets of Chukchi Sea polar bears were re-estimated
using all six methods. Our findings reveal that the selection of an
estimation method can meaningfully influence estimates of diet composition.
Among the pseudopredator results, which allowed evaluation of bias and
precision, differences in estimator performance were rarely large, and no
one estimator was universally preferred, although estimators based on the
Aitchison distance measure tended to have modestly superior properties
compared to estimators based on the Kullback–Leibler distance measure.
However, greater differences were observed among estimated polar bear
diets, most likely due to differential estimator sensitivity to assumption
violations. Our results, particularly the polar bear example, suggest that
additional research into estimator performance and model diagnostics is
warranted.


The paper is available at the following URL:

http://onlinelibrary.wiley.com/doi/10.1002/ece3.1429/abstract



Regards,

Jeff
---
Jeffrey F. Bromaghin, PhD
Research Statistician
USGS Alaska Science Center
4210 University Drive
Anchorage, AK 99508
907-786-7086
jbromag...@usgs.gov
https://mail.google.com/mail/?view=cmfs=1tf=1to=jbromag...@usgs.gov
*http://alaska.usgs.gov/science/biology/quantitative_ecology/index.php
http://alaska.usgs.gov/science/biology/quantitative_ecology/index.php*
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[MARMAM] New QFASA Paper

[Bromaghin, Jeffrey]

Dear colleagues,



I am pleased to announce the publication of an objective method to
establish bootstrap sample sizes for investigating the performance of
quantitative fatty acid signature analysis (QFASA), a method that has been
widely utilized for marine species.



Citation:

Bromaghin, J. F. 2015. Simulating realistic predator signatures in
quantitative fatty acid signature analysis.  Ecological Informatics
30:68-71.


Abstract:

Diet estimation is an important field within quantitative ecology,
providing critical insights into many aspects of ecology and community
dynamics. Quantitative fatty acid signature analysis (QFASA) is a prominent
method of diet estimation, particularly for marine mammal and bird species.
Investigators using QFASA commonly use computer simulation to evaluate
statistical characteristics of diet estimators for the populations they
study. Similar computer simulations have been used to explore and compare
the performance of different variations of the original QFASA diet
estimator. In both cases, computer simulations involve bootstrap sampling
prey signature data to construct pseudo-predator signatures with known
properties. However, bootstrap sample sizes have been selected arbitrarily
and pseudo-predator signatures therefore may not have realistic properties.
I develop an algorithm to objectively establish bootstrap sample sizes that
generates pseudo-predator signatures with realistic properties, thereby
enhancing the utility of computer simulation for assessing QFASA estimator
performance. The algorithm also appears to be computationally efficient,
resulting in bootstrap sample sizes that are smaller than those commonly
used. I illustrate the algorithm with an example using data from Chukchi
Sea polar bears (Ursus maritimus) and their marine mammal prey. The
concepts underlying the approach may have value in other areas

of quantitative ecology in which bootstrap samples are post-processed prior
to their use.


The paper is available at the following URL:

http://dx.doi.org/10.1016/j.ecoinf.2015.09.011




Regards,

Jeff
---
Jeffrey F. Bromaghin, PhD
Research Statistician
USGS Alaska Science Center
​Marine Ecosystems Office
​
4210 University Drive
Anchorage, AK 99508
907-786-7086
jbromag...@usgs.gov
*http://alaska.usgs.gov/science/biology/quantitative_ecology/index.php
*
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[MARMAM] New Publication Announcement

[Bromaghin, Jeffrey]

Colleagues,



I am pleased to announce the availability of an early-view paper that
describes a new R package, called qfasar, for the estimation of predator
diet composition using quantitative fatty acid signature analysis (QFASA).
QFASA is one of the most common methods of estimating diet composition for
marine species. The package incorporates traditional estimation methods and
several improvements drawn from a series of our recent methodology papers.



Citation:

Bromaghin, J. F. 2017. qfasar: quantitative fatty acid signature analysis
with R. Methods in Ecology and Evolution. doi: 10./2041-210X.12740.



Summary

1. Knowledge of predator diets provides essential insights into their
ecology, yet diet estimation is challenging and remains an active area of
research.

2. Quantitative fatty acid signature analysis (QFASA) is a popular method
of estimating diet composition that continues to be investigated and
extended. However, software to implement QFASA has only recently become
publicly available.

3. I summarize a new R package, qfasar, for diet estimation using QFASA
methods. The package also provides functionality to evaluate and
potentially improve the performance of a library of prey signature data,
compute goodness-of-fit diagnostics, and support simulation-based research.
Several procedures in the package have not previously been published.

4. QFASAR makes traditional and recently published QFASA diet estimation
methods accessible to ecologists for the first time. Use of the package is
illustrated with signature data from Chukchi Sea polar bears and potential
prey species.



Regards,

Jeff
---
Jeffrey F. Bromaghin, PhD
Research Statistician
USGS Alaska Science Center
Marine Ecosystems Office
4210 University Drive
Anchorage, AK 99508
907-786-7086
jbromag...@usgs.gov

*http://alaska.usgs.gov/science/biology/quantitative_ecology/index.php
*
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[MARMAM] qfasar: New R Package for Diet Estimation

[Bromaghin, Jeffrey]

I would like to announce the availability of a new R package, called
qfasar, for diet estimation using quantitative fatty acid signature
analysis (QFASA), a popular method in studies of marine species.  The
package provides basic functionality to estimate diet composition in
typical QFASA studies.  In addition, the package provides advanced
functionality to evaluate and improve diet estimation, diagnose estimation
problems, and support simulation-based research.  The package makes
traditional QFASA methods and analytical techniques drawn from our four
methodology papers published in 2015 and 2016 easily accessible to
ecologists for the first time. The package is available on the CRAN website
(https://cran.r-project.org/web/packages/qfasar/) and as a USGS Alaska
Science Center software tool (https://dx.doi.org/10.5066/F71G0JC9).



Regards,

Jeff
---
Jeffrey F. Bromaghin, PhD
Research Statistician
USGS Alaska Science Center
Marine Ecosystems Office
4210 University Drive
Anchorage, AK 99508
907-786-7086
jbromag...@usgs.gov

*http://alaska.usgs.gov/science/biology/quantitative_ecology/index.php
*
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[MARMAM] New QFASA Diet Estimation Publication

[Bromaghin, Jeffrey]

Colleagues,



I am pleased to announce a publication that presents a new clustering
method to detect hidden structure in fatty acid signature data and
potentially improve estimates of consumer diet composition using
quantitative fatty acid signature analysis, a method commonly used in
studies of marine mammals.



Citation:

Bromaghin, J. F., S. M. Budge, and G. W. Thiemann.  2017. Detect and
exploit hidden structure in fatty acid signature data. *Ecosphere* 8(7):
e01896.

Available open access at
http://onlinelibrary.wiley.com/doi/10.1002/ecs2.1896/full



Abstract:

Estimates of predator diet composition are essential to our understanding
of their ecology.  Although several methods of estimating diet are
practiced, methods based on biomarkers have become increasingly common.
Quantitative fatty acid signature analysis (QFASA) is a popular method that
continues to be refined and extended.  QFASA is based on differences in the
signatures of prey types, often species, which are recognized and
designated by investigators.  Similarly, predator signatures may be
structured by known factors such as sex or age class, and the season or
region of sample collection.  The recognized structure in signature data
inherently influences QFASA results in important and typically beneficial
ways.  However, predator and prey signatures may contain additional, hidden
structure that investigators either choose not to incorporate into an
analysis or of which they are unaware, being caused by unknown ecological
mechanisms.  Hidden structure also influences QFASA results, most often
negatively.  We developed a new method to explore signature data for hidden
structure, called divisive magnetic clustering (DIMAC).  Our DIMAC approach
is based on the same distance measure used in diet estimation, closely
linking methods of data exploration and parameter estimation, and it does
not require data transformation or distributional assumptions, as do many
multivariate ordination methods in common use.  We investigated the
potential benefits of the DIMAC method to detect and subsequently exploit
hidden structure in signature data using two prey signature libraries with
quite different characteristics.  We found that the existence of hidden
structure in prey signatures can increase the confusion between prey types
and thereby reduce the accuracy and precision of QFASA diet estimates.
Conversely, the detection and exploitation of hidden structure represents a
potential opportunity to improve predator diet estimates and may lead to
new insights into the ecology of either predator or prey.  The DIMAC
algorithm is implemented in the R diet estimation package qfasar.



Regards,

Jeff


---
Jeffrey F. Bromaghin, PhD
Research Statistician
USGS Alaska Science Center
Marine Ecosystems Office
4210 University Drive
Anchorage, AK 99508
907-786-7086
jbromag...@usgs.gov
*http://alaska.usgs.gov/science/biology/quantitative_ecology/index.php
*
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[MARMAM] New Publication Announcement

[Bromaghin, Jeffrey]

Colleagues,



I am pleased to announce the availability of an early-view paper that
presents a new model for the estimation of consumer diet composition using
quantitative fatty acid signature analysis, a method commonly used in
studies of marine species.



Citation:

Bromaghin, J. F., S. M. Budge, G. W. Thiemann, and K. D. Rode. 2017.
Simultaneous estimation of diet composition and calibration coefficients
with fatty acid signature data. Ecology and Evolution.
https://doi.org/10.1002/ece3.3179



Abstract:

Knowledge of animal diets provides essential insights into their life
history and ecology, although diet estimation is challenging and remains an
active area of research.  Quantitative fatty acid signature analysis
(QFASA) has become a popular method of estimating diet composition,
especially for marine species.  A primary assumption of QFASA is that
constants called calibration coefficients, which account for the
differential metabolism of individual fatty acids, are known.  In practice,
however, calibration coefficients are not known, but rather have been
estimated in feeding trials with captive animals of a limited number of
model species.  The impossibility of verifying the accuracy of feeding
trial derived calibration coefficients to estimate the diets of wild
animals is a foundational problem with QFASA that has generated
considerable criticism.  We present a new model that allows simultaneous
estimation of diet composition and calibration coefficients based only on
fatty acid signature samples from wild predators and potential prey.  Our
model performed almost flawlessly in four tests with constructed examples,
estimating both diet proportions and calibration coefficients with
essentially no error.  We also applied the model to data from Chukchi Sea
polar bears, obtaining diet estimates that were more diverse than estimates
conditioned on feeding-trial calibration coefficients.  Our model avoids
bias in diet estimates caused by conditioning on inaccurate calibration
coefficients, invalidates the primary criticism of QFASA, eliminates the
need to conduct feeding trials solely for diet estimation, and consequently
expands the utility of fatty acid data to investigate aspects of ecology
linked to animal diets.



Regards,

Jeff
---
Jeffrey F. Bromaghin, PhD
Research Statistician
USGS Alaska Science Center
Marine Ecosystems Office
4210 University Drive
Anchorage, AK 99508
907-786-7086
jbromag...@usgs.gov
*http://alaska.usgs.gov/science/biology/quantitative_ecology/index.php
*
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[MARMAM] New paper on the population dynamics of southern Beaufort Sea polar bears

[Bromaghin, Jeffrey F]

Dear colleagues,

My co-authors and I are pleased to announce the recent publication of a paper 
on the population dynamics of southern Beaufort Sea polar bears. The abstract 
and citation follow.

The Arctic Ocean is undergoing rapid transformation toward a seasonally 
ice-free ecosystem. As ice-adapted apex predators, polar bears (Ursus 
maritimus) are challenged to cope with ongoing habitat degradation and changes 
in their prey base driven by food-web response to climate warming. Knowledge of 
polar bear response to environmental change is necessary to understand 
ecosystem dynamics and inform conservation decisions. In the southern Beaufort 
Sea (SBS) of Alaska and western Canada, sea ice extent has declined since 
satellite observations began in 1979 and available evidence suggests that the 
carrying capacity of the SBS for polar bears has trended lower for nearly two 
decades. In this study, we investigated the population dynamics of polar bears 
in Alaska's SBS from 2001 to 2016 using a multistate Cormack-Jolly-Seber 
mark-recapture model. States were defined as geographic regions, and we used 
location data from mark-recapture observations and satellite-telemetered bears 
to model transitions between states and thereby explain heterogeneity in 
recapture probabilities. Our results corroborate prior findings that the SBS 
subpopulation experienced low survival from 2003 to 2006. Survival improved 
modestly from 2006 to 2008 and afterward rebounded to comparatively high levels 
for the remainder of the study, except in 2012. Abundance moved in concert with 
survival throughout the study period, declining substantially from 2003 and 
2006 and afterward fluctuating with lower variation around an average of 565 
bears (95% Bayesian credible interval [340, 920]) through 2015. Even though 
abundance was comparatively stable and without sustained trend from 2006 to 
2015, polar bears in the Alaska SBS were less abundant over that period than at 
any time since passage of the U.S. Marine Mammal Protection Act. The potential 
for recovery is likely limited by the degree of habitat degradation the 
subpopulation has experienced, and future reductions in carrying capacity are 
expected given current projections for continued climate warming.
Bromaghin, J.F., D.C. Douglas, G.M. Durner, K.S. Simac, and T.C. Atwood. In 
press. Survival and abundance of polar bears in Alaska's Beaufort Sea, 
2001-2016. Ecology and Evolution. https://doi.org/10.1002/ece3.8139
Regards,
Jeff

Jeffrey F. Bromaghin
Research Statistician
USGS Alaska Science Center
907-786-7086
Jeffrey Bromaghin, Ph.D. 
(usgs.gov)
Ecosystems Analytics 
(usgs.gov)

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