zoopindex.bib

@article{thorson_guidance_2019,
	title = {Guidance for decisions using the {Vector} {Autoregressive} {Spatio}-{Temporal} ({VAST}) package in stock, ecosystem, habitat and climate assessments},
	volume = {210},
	issn = {0165-7836},
	url = {http://www.sciencedirect.com/science/article/pii/S0165783618302820},
	doi = {10.1016/j.fishres.2018.10.013},
	abstract = {Fisheries scientists provide stock, ecosystem, habitat, and climate assessments to support interdisplinary fisheries management in the US and worldwide. These assessment activities have evolved different models, using different review standards, and are communicated using different vocabulary. Recent research shows that spatio-temporal models can estimate population density for multiple locations, times, and species, and that this is a “common currency” for addressing core goals in stock, ecosystem, habitat, and climate assessments. I therefore review the history and “design principles” for one spatio-temporal modelling package, the Vector Autoregressive Spatio-Temporal (VAST) package. I then provide guidance on fifteen major decisions that must be made by users of VAST, including: whether to use a univariate or multivariate model; when to include spatial and/or spatio-temporal variation; how many factors to use within a multivariate model; whether to include density or catchability covariates; and when to include a temporal correlation on model components. I finally demonstrate these decisions using three case studies. The first develops indices of abundance, distribution shift, and range expansion for arrowtooth flounder (Atheresthes stomias) in the Eastern Bering Sea, showing the range expansion for this species. The second involves “species ordination” of eight groundfishes in the Gulf of Alaska bottom trawl survey, which highlights the different spatial distribution of flathead sole (Hippoglossoides elassodon) relative to sablefish (Anoplopoma fimbria) and dover sole (Microstomus pacificus). The third involves a short-term forecast of the proportion of coastwide abundance for five groundfishes within three spatial strata in the US West Coast groundfish bottom trawl survey, and predicts large interannual variability (and high uncertainty) in the distribution of lingcod (Ophiodon elongatus). I conclude by recommending further research exploring the benefits and limitations of a “common currency” approach to stock, ecosystem, habitat, and climate assessments, and discuss extending this approach to optimal survey design and economic assessments.},
	language = {en},
	urldate = {2020-02-24},
	journal = {Fisheries Research},
	author = {Thorson, James T.},
	month = feb,
	year = {2019},
	keywords = {Distribution shift, Climate vulnerability analysis, Habitat assessment, Index standardization, Integrated ecosystem assessment, Spatio-temporal model, Stock assessment, VAST},
	pages = {143--161},
	file = {ScienceDirect Full Text PDF:/Users/sarah.gaichas/Zotero/storage/38KBWBLZ/Thorson - 2019 - Guidance for decisions using the Vector Autoregres.pdf:application/pdf;ScienceDirect Snapshot:/Users/sarah.gaichas/Zotero/storage/85BILR75/S0165783618302820.html:text/html},
}

@article{friedland_thermal_2013,
	title = {Thermal habitat constraints on zooplankton species associated with {Atlantic} cod ({Gadus} morhua) on the {US} {Northeast} {Continental} {Shelf}.},
	volume = {116},
	shorttitle = {Thermal habitat constraints on zooplankton species associated with {Atlantic} cod ({Gadus} morhua) on the {US} {Northeast} {Continental} {Shelf}.},
	journal = {Progress In Oceanography},
	author = {Friedland, K.D. and Kane, J. and Hare, J.A. and Lough, R.G. and Fratantoni, P.S. and Fogarty, M.J. and Nye, J.A.},
	year = {2013},
	pages = {1--13},
	file = {ScienceDirect Full Text PDF:/Users/sarah.gaichas/Zotero/storage/9R5TMDHR/Friedland et al. - 2013 - Thermal habitat constraints on zooplankton species.pdf:application/pdf;ScienceDirect Snapshot:/Users/sarah.gaichas/Zotero/storage/RUABZDB3/S0079661113000530.html:text/html},
}

@article{bi_decadal_2014,
	title = {Decadal {Changes} in {Zooplankton} of the {Northeast} {U}.{S}. {Continental} {Shelf}},
	volume = {9},
	issn = {1932-6203},
	url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0087720},
	doi = {10.1371/journal.pone.0087720},
	abstract = {The abundance of the subarctic copepod, Calanus finmarchicus, and temperate, shelf copepod, Centropages typicus, was estimated from samples collected bi-monthly over the Northeast U.S. continental shelf (NEUS) from 1977–2010. Latitudinal variation in long term trends and seasonal patterns for the two copepod species were examined for four sub-regions: the Gulf of Maine (GOM), Georges Bank (GB), Southern New England (SNE), and Mid-Atlantic Bight (MAB). Results suggested that there was significant difference in long term variation between northern region (GOM and GB), and the MAB for both species. C. finmarchicus generally peaked in May – June throughout the entire study region and Cen. typicus had a more complex seasonal pattern. Time series analysis revealed that the peak time for Cen. typicus switched from November – December to January - March after 1985 in the MAB. The long term abundance of C. finmarchicus showed more fluctuation in the MAB than the GOM and GB, whereas the long term abundance of Cen. typicus was more variable in the GB than other sub-regions. Alongshore transport was significantly correlated with the abundance of C. finmarchicus, i.e., more water from north, higher abundance for C. finmarchicus. The abundance of Cen. typicus showed positive relationship with the Gulf Stream north wall index (GSNWI) in the GOM and GB, but the GSNWI only explained 12–15\% of variation in Cen. typicus abundance. In general, the alongshore current was negatively correlated with the GSNWI, suggesting that Cen. typicus is more abundant when advection from the north is less. However, the relationship between Cen. typicus and alongshore transport was not significant. The present study highlights the importance of spatial scales in the study of marine populations: observed long term changes in the northern region were different from the south for both species.},
	language = {en},
	number = {1},
	urldate = {2019-02-14},
	journal = {PLOS ONE},
	author = {Bi, Hongsheng and Ji, Rubao and Liu, Hui and Jo, Young-Heon and Hare, Jonathan A.},
	month = jan,
	year = {2014},
	keywords = {Ecosystems, Maine, Seasons, Copepods, Sea water, Seasonal variations, Time series analysis, Zooplankton},
	pages = {e87720},
	file = {Full Text PDF:/Users/sarah.gaichas/Zotero/storage/R8SQIEC6/Bi et al. - 2014 - Decadal Changes in Zooplankton of the Northeast U..pdf:application/pdf;Snapshot:/Users/sarah.gaichas/Zotero/storage/PSKBJXRV/article.html:text/html},
}

@article{morse_distinct_2017,
	title = {Distinct zooplankton regime shift patterns across ecoregions of the {U}.{S}. {Northeast} continental shelf {Large} {Marine} {Ecosystem}},
	volume = {165},
	issn = {09247963},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S0924796316303098},
	doi = {10.1016/j.jmarsys.2016.09.011},
	abstract = {We investigated regime shifts in seasonal zooplankton communities of the Northeast continental shelf Large Marine Ecosystem (NES) and its subcomponent ecoregions over a multi-decadal period (1977–2013). Our cross ecoregion analysis shows that regime shifts in different ecoregions often exhibited very distinct characteristics, emphasizing more granular fluctuations in NES plankton communities relative to previous work. Shifts early in the time series generally reflected an increase in abundance levels. The response of zooplankton abundance within fall communities was more similar among ecoregions than for spring communities. The Gulf of Maine exhibited highly distinct patterns from other ecoregions, with regime shifts identified in the early 1980s, early 2000s, and mid-2000s for spring communities. Regime shifts were identified in the early to mid-1990s for the NES, Georges Bank, and the Mid-Atlantic Bight ecoregions, while the fall communities experienced shifts in the early 1990s and late 1980s for the NES and Georges Bank, but in the late 1990s in the Mid-Atlantic Bight. A constrained correspondence analysis of zooplankton community against local and basin-scale climatological indices suggests that water temperature, stratification, and the Atlantic multidecadal oscillation (AMO) were the predominant factors in driving the zooplankton community composition.},
	language = {en},
	urldate = {2019-02-14},
	journal = {Journal of Marine Systems},
	author = {Morse, R.E. and Friedland, K.D. and Tommasi, D. and Stock, C. and Nye, J.},
	month = jan,
	year = {2017},
	keywords = {Climate, Marine ecology, Seasonal variations, Zooplankton, Community composition, Long-term changes},
	pages = {77--91},
	file = {Morse et al. - 2017 - Distinct zooplankton regime shift patterns across .pdf:/Users/sarah.gaichas/Zotero/storage/TDQERQ57/Morse et al. - 2017 - Distinct zooplankton regime shift patterns across .pdf:application/pdf;ScienceDirect Snapshot:/Users/sarah.gaichas/Zotero/storage/IYMQRUU7/S0924796316303098.html:text/html},
}

@article{sorochan_north_2019,
	title = {North {Atlantic} right whale ({Eubalaena} glacialis) and its food: ({II}) interannual variations in biomass of {Calanus} spp. on western {North} {Atlantic} shelves},
	volume = {41},
	issn = {0142-7873},
	shorttitle = {North {Atlantic} right whale ({Eubalaena} glacialis) and its food},
	url = {https://doi.org/10.1093/plankt/fbz044},
	doi = {10.1093/plankt/fbz044},
	abstract = {The North Atlantic right whale (NARW), Eubalaena glacialis, feeds on zooplankton, particularly copepods of the genus Calanus. We quantified interannual variation in anomalies of abundance and biomass of Calanus spp. and near-surface and near-bottom ocean temperature and salinity from 19 subregions spanning the Gulf of Maine–Georges Bank (GoM–GBK), Scotian Shelf (SS), Gulf of St. Lawrence (GSL) and Newfoundland and Labrador Shelves. We analyzed time series from 1977 to 2016 in GoM–GBK, 1982 to 2016 in southwest GSL and 1999 to 2016 in remaining areas. Calanus finmarchicus dominated abundance and biomass, except in the GSL where Calanus hyperboreus was abundant. The biomass of Calanus spp. declined in many subregions over years 1999–2016 and was negatively correlated with sea surface temperature in GoM–GBK and on the SS. We detected ``regime shifts” to lower biomass of Calanus spp. in the GoM–GBK in 2010 and on the SS in 2011. In the GoM–GBK, shifts to lower biomass of C. finmarchicus coincided with shifts to warmer ocean temperature and with published reports of changes in spatial distribution and reduced calving rate of NARW. We hypothesize that warming has negatively impacted population levels of Calanus spp. near their southern range limit, reducing the availability of prey to NARW.},
	number = {5},
	urldate = {2021-03-01},
	journal = {Journal of Plankton Research},
	author = {Sorochan, Kevin A and Plourde, StÉphane and Morse, Ryan and Pepin, Pierre and Runge, Jeffrey and Thompson, Cameron and Johnson, Catherine L},
	month = sep,
	year = {2019},
	pages = {687--708},
	file = {Snapshot:/Users/sarah.gaichas/Zotero/storage/FBSFT4Z8/5583901.html:text/html},
}

@article{martino_recruitment_2010,
	title = {Recruitment of striped bass in {Chesapeake} {Bay}:: spatial and temporal environmental variability and availability of zooplankton prey},
	volume = {409},
	issn = {0171-8630},
	shorttitle = {Recruitment of striped bass in {Chesapeake} {Bay}},
	url = {https://www.jstor.org/stable/24873989},
	abstract = {ABSTRACT: Causes of recruitment variability in young-of-the-year (YOY) striped bass Morone saxatilis from Chesapeake Bay were investigated based on (1) surveys from 2001 to 2003 to document spatio-temporal variability in abundance of larval striped bass, zooplankton prey, and feeding success of larvae; (2) a synthetic analysis (1996, 1998, 1999, 2001 to 2003) to describe how environmental factors and prey affect recruitment success; and (3) a 10 yr analysis (1993 to 2002) of inter-annual differences in spatial and temporal patterns of copepods and cladocera eaten by striped bass larvae. Striped bass YOY recruitment levels varied {\textgreater}11-fold in the 6 years examined. In those years, mean daily freshwater flows from the Susquehanna River to the bay in March and April varied {\textgreater}2-fold and controlled distribution and apparent survival of striped bass larvae. Strong recruitments of YOY striped bass were associated with matches in space and time of larval striped bass and high concentrations of zooplankton prey, especially the copepod Eurytemora affinis and cladoceran Bosmina longirostris. The strongest year classes (1996, 2003) were produced in years of high freshwater flow, characterized by a high abundance of feeding-stage larvae and a spatio-temporal match between peak abundance of larvae and zooplankton prey. Enhanced feeding opportunities were most pronounced in high freshwater-flow years (1996, 1998, 2003), when larvae and zooplankton prey were strongly associated with, and apparently retained near, the estuarine turbidity maximum. First-feeding larvae fed more successfully in a high-flow year (2003; prey incidence 91\%) than in a drier year (2001; prey incidence 35\%). A regression model that may have forecasting potential was developed to describe recruitment of YOY striped bass for the years from 1985 to 2006. The model includes spring freshwater flow and air temperatures to predict age-0 striped bass recruitment strength (R² = 0.65). Flow and temperature control environmental and hydrographic conditions that strongly influence spatio-temporal overlap of larval striped bass and zooplankton. The model provided accurate recruitment forecasts for 2007 and 2009, but was less successful in 2008, a year of exceptionally low recruitment.},
	urldate = {2021-02-26},
	journal = {Marine Ecology Progress Series},
	author = {Martino, E. J. and Houde, E. D.},
	year = {2010},
	note = {Publisher: Inter-Research Science Center},
	pages = {213--228},
}

@article{perretti_regime_2017,
	title = {Regime shifts in fish recruitment on the {Northeast} {US} {Continental} {Shelf}},
	volume = {574},
	issn = {0171-8630, 1616-1599},
	url = {http://www.int-res.com/abstracts/meps/v574/p1-11/},
	doi = {10.3354/meps12183},
	abstract = {There is accumulating evidence for decadal-scale regime shifts at the base of the food web on the Northeast US Continental Shelf. However, less evidence exists for regime shifts in fish recruitment success, particularly for synchronized regimes across multiple species. Here, we analyzed stock assessment output and survey data to test for regimes in the recruitment success of 18 commercially important marine species over a 29 yr timespan. We then tested whether recruitment regimes coincide with regimes in the zooplankton community, and whether the abundance of large spawners could explain the patterns in recruitment. We found evidence for 3 decadal-scale recruitment regimes: low recruitment success in the 1980s, high success in the 1990s, and a return to low recruitment success in the 2000s. This general pattern was found in all datasets of recruitment. The abundance of large spawners did not appear to be a broad-scale driver of recruitment success; however, recruitment regimes coincided with regimes in copepod abundance and size structure.},
	language = {en},
	urldate = {2022-02-10},
	journal = {Marine Ecology Progress Series},
	author = {Perretti, Ct and Fogarty, Mj and Friedland, Kd and Hare, Ja and Lucey, Sm and McBride, Rs and Miller, Tj and Morse, Re and O’Brien, L and Pereira, Jj and Smith, La and Wuenschel, Mj},
	month = jul,
	year = {2017},
	pages = {1--11},
	file = {Perretti et al. - 2017 - Regime shifts in fish recruitment on the Northeast.pdf:/Users/sarah.gaichas/Zotero/storage/7QCFZSR9/Perretti et al. - 2017 - Regime shifts in fish recruitment on the Northeast.pdf:application/pdf;Perretti et al. - 2017 - Regime shifts in fish recruitment on the Northeast.pdf:/Users/sarah.gaichas/Zotero/storage/XF3MPALT/Perretti et al. - 2017 - Regime shifts in fish recruitment on the Northeast.pdf:application/pdf},
}

@article{thorson_implementing_2016,
	title = {Implementing a generic method for bias correction in statistical models using random effects, with spatial and population dynamics examples},
	volume = {175},
	issn = {0165-7836},
	url = {https://www.sciencedirect.com/science/article/pii/S0165783615301399},
	doi = {10.1016/j.fishres.2015.11.016},
	abstract = {Statistical models play an important role in fisheries science when reconciling ecological theory with available data for wild populations or experimental studies. Ecological models increasingly include both fixed and random effects, and are often estimated using maximum likelihood techniques. Quantities of biological or management interest (“derived quantities”) are then often calculated as nonlinear functions of fixed and random effect estimates. However, the conventional “plug-in” estimator for a derived quantity in a maximum likelihood mixed-effects model will be biased whenever the estimator is calculated as a nonlinear function of random effects. We therefore describe and evaluate a new “epsilon” estimator as a generic bias-correction estimator for derived quantities. We use simulated data to compare the epsilon-method with an existing bias-correction algorithm for estimating recruitment in four configurations of an age-structured population dynamics model. This simulation experiment shows that the epsilon-method and the existing bias-correction method perform equally well in data-rich contexts, but the epsilon-method is slightly less biased in data-poor contexts. We then apply the epsilon-method to a spatial regression model when estimating an index of population abundance, and compare results with an alternative bias-correction algorithm that involves Markov-chain Monte Carlo sampling. This example shows that the epsilon-method leads to a biologically significant difference in estimates of average abundance relative to the conventional plug-in estimator, and also gives essentially identical estimates to a sample-based bias-correction estimator. The epsilon-method has been implemented by us as a generic option in the open-source Template Model Builder software, and could be adapted within other mixed-effects modeling tools such as Automatic Differentiation Model Builder for random effects. It therefore has potential to improve estimation performance for mixed-effects models throughout fisheries science.},
	language = {en},
	urldate = {2022-07-29},
	journal = {Fisheries Research},
	author = {Thorson, James T. and Kristensen, Kasper},
	month = mar,
	year = {2016},
	keywords = {Stock assessment, Random effects, Template Model Builder (TMB), Bias correction, Epsilon estimator, Mixed-effects model},
	pages = {66--74},
	file = {ScienceDirect Snapshot:/Users/sarah.gaichas/Zotero/storage/EULWM2HW/S0165783615301399.html:text/html;Thorson and Kristensen - 2016 - Implementing a generic method for bias correction .pdf:/Users/sarah.gaichas/Zotero/storage/AZC44RWT/Thorson and Kristensen - 2016 - Implementing a generic method for bias correction .pdf:application/pdf},
}

@article{thorson_surprising_2021,
	title = {The surprising sensitivity of index scale to delta-model assumptions: {Recommendations} for model-based index standardization},
	volume = {233},
	issn = {01657836},
	shorttitle = {The surprising sensitivity of index scale to delta-model assumptions},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S0165783620302629},
	doi = {10.1016/j.fishres.2020.105745},
	abstract = {Delta-models (a.k.a. hurdle models) are widely used to fit biomass samples that include zeros and a skewed response for positive catches, and spatio-temporal extensions of these models are increasingly used to quantify trends in abundance (i.e., estimate abundance indices). Previous research has shown estimated indices are proportional to changes in abundance. However, little research has tested the performance of delta-models for estimating “scale”; that is, whether abundance indices are not just proportional to population changes but also have the correct absolute value. We use data for twenty species in the eastern Bering Sea and Gulf of Alaska as well as a factorial experiment conditioned on data for Gulf of Alaska Pacific cod to support five conclusions related to scale in spatio-temporal delta-models. First, we show that conventional (nonspatial) delta-models are surprisingly sensitive to the a priori choice of probability distribution for positive catches, where gamma and Tweedie models give similar scale estimates but other distributions generally differ. Second, these same distri­ butions also estimate widely different scales when using spatio-temporal delta-models, and the delta-gamma and Tweedie models provide similar scale to design-based indices. Third, model selection using marginal AIC often identifies the lognormal distribution as most parsimonious, despite it resulting in systematically higher abun­ dance than design-based indices for many species. Fourth, scale is sensitive to the spatial resolution (i.e., number of knots) used in fitting the spatio-temporal model when using a naïve “empirical Bayes” estimator, but less sensitive when applying an epsilon bias-correction estimator. Fifth, the factorial simulation experiment suggests that the Tweedie and delta-gamma distributions perform well even when applied to data simulated from an inverse-Gaussian or lognormal distribution, whereas the opposite is not true. We conclude that index scale is sensitive to delta-model specification, and we make five recommendations when using spatio-temporal deltamodels for index standardization: (1) apply the epsilon or other bias-correction methods to reduce sensitivity of index scale on spatio-temporal model resolution; either (2) compare the scale of delta-model indices with that of design-based indices when design-based indices are available or (3) use the delta-gamma or Tweedie distribution by default when design-based indices are not available; (4) do not assume that AIC will identify the model specification that results in the most appropriate scale; and (5) consider apparent mismatches in index scale depending upon whether an assessment model specifies or estimates the associated catchability coefficient and whether the design-based index is believed to measure total abundance for a fully-selected age or length-class.},
	language = {en},
	urldate = {2022-08-04},
	journal = {Fisheries Research},
	author = {Thorson, James T. and Cunningham, Curry J. and Jorgensen, Elaina and Havron, Andrea and Hulson, Peter-John F. and Monnahan, Cole C. and von Szalay, Paul},
	month = jan,
	year = {2021},
	keywords = {Stock assessment, VAST, Abundance index, Catchability coefficient, Delta model, Tweedie distribution, Vector autoregressive spatio-temporal model},
	pages = {105745},
	file = {ScienceDirect Snapshot:/Users/sarah.gaichas/Zotero/storage/SND4TRFL/S0165783620302629.html:text/html;Thorson et al. - 2021 - The surprising sensitivity of index scale to delta.pdf:/Users/sarah.gaichas/Zotero/storage/N9EVY2WT/Thorson et al. - 2021 - The surprising sensitivity of index scale to delta.pdf:application/pdf},
}

@book{thorson_spatio-temporal_2024,
	address = {New York},
	title = {Spatio-{Temporal} {Models} for {Ecologists}},
	isbn = {978-1-00-341029-4},
	abstract = {Ecological dynamics are tremendously complicated and are studied at a variety of spatial and temporal scales. Ecologists often simplify analysis by describing changes in density of individuals across a landscape, and statistical methods are advancing rapidly for studying spatio-temporal dynamics. However, spatio-temporal statistics is often presented using a set of principles that may seem very distant from ecological theory or practice. This book seeks to introduce a minimal set of principles and numerical techniques for spatio-temporal statistics that can be used to implement a wide range of real-world ecological analyses regarding animal movement, population dynamics, community composition, causal attribution, and spatial dynamics. We provide a step-by-step illustration of techniques that combine core spatial-analysis packages in R with low-level computation using Template Model Builder. Techniques are showcased using real-world data from varied ecological systems, providing a toolset for hierarchical modelling of spatio-temporal processes. Spatio-Temporal Models for Ecologists is meant for graduate level students, alongside applied and academic ecologists.
Key Features:

Foundational ecological principles and analyses
Thoughtful and thorough ecological examples
Analyses conducted using a minimal toolbox and fast computation
Code using R and TMB included in the book and available online},
	publisher = {Chapman and Hall/CRC},
	author = {Thorson, James and Kristensen, Kasper},
	month = feb,
	year = {2024},
	doi = {10.1201/9781003410294},
}

@article{richardson_development_2010,
	title = {Development of long-term larval indices for {Atlantic} herring ({Clupea} harengus) on the northeast {US} continental shelf},
	volume = {67},
	issn = {1054-3139},
	url = {https://doi.org/10.1093/icesjms/fsp276},
	doi = {10.1093/icesjms/fsp276},
	abstract = {Richardson, D. E., Hare, J. A., Overholtz, W. J., and Johnson, D. L. 2010. Development of long-term larval indices for Atlantic herring (Clupea harengus) on the northeast US continental shelf. – ICES Journal of Marine Science, 67: 617–627.The incorporation of data from ichthyoplankton programmes into the stock assessment process has lagged far behind the use of data from comparable adult-monitoring programmes. This can in part be attributed to a mismatch between established analytical approaches to larval-index development and the inconsistencies in sampling for many long-term ichthyoplankton datasets. Along the northeast US continental shelf, ichthyoplankton surveys have been carried out by the Northeast Fisheries Science Center (NMFS/NOAA) multiple times annually since 1971, but the spatial and seasonal allocation of sampling has varied substantially. Here, we present a non-linear least-squares approach to larval-index development. We use the age structure and abundance of larvae on each survey to derive the larval index, along with parameters describing the survival of larvae and the seasonal cycle of hatching. Application to Atlantic herring (Clupea harengus) revealed a large drop in the index around 1976, an increase in the index through the late 1980s, and another large drop in 2004. This index was correlated with the stock assessment estimate of Atlantic herring spawning-stock biomass from 1971 to 2003, but differed substantially during 2004. Our results demonstrate that our approach to larval-index development is flexible to the inconsistencies in sampling effort.},
	number = {4},
	urldate = {2024-08-30},
	journal = {ICES Journal of Marine Science},
	author = {Richardson, David E. and Hare, Jonathan A. and Overholtz, William J. and Johnson, Donna L.},
	month = may,
	year = {2010},
	pages = {617--627},
	file = {Full Text PDF:/Users/sarah.gaichas/Zotero/storage/9GFC2GL8/Richardson et al. - 2010 - Development of long-term larval indices for Atlant.pdf:application/pdf;Snapshot:/Users/sarah.gaichas/Zotero/storage/FAIEWLE5/680402.html:text/html},
}