Using low volume eDNA methods to sample pelagic marine animal assemblages

Environmental DNA (eDNA) is an increasingly useful method for detecting pelagic animals in the ocean but typically requires large water volumes to sample diverse assemblages. Ship-based pelagic sampling programs that could implement eDNA methods generally have restrictive water budgets. Studies that quantify how eDNA methods perform on low water volumes in the ocean are limited, especially in deep-sea habitats with low animal biomass and poorly described species assemblages. Using 12S rRNA and COI gene primers, we quantified assemblages comprised of micronekton, coastal forage fishes, and zooplankton from low volume eDNA seawater samples (n = 436, 380-1800 mL) collected at depths of 0-2200 m in the southern California Current. We compared diversity in eDNA samples to concurrently collected pelagic trawl samples (n = 27), detecting a higher diversity of vertebrate and invertebrate groups in the eDNA samples. Differences in assemblage composition could be explained by variability in size-selectivity among methods and DNA primer suitability across taxonomic groups. The number of reads and amplicon sequences variants (ASVs) did not vary substantially among shallow (<200 m) and deep samples (>600 m), but the proportion of invertebrate ASVs that could be assigned a species-level identification decreased with sampling depth. Using hierarchical clustering, we resolved horizontal and vertical variability in marine animal assemblages from samples characterized by a relatively low diversity of ecologically important species. Low volume eDNA samples will quantify greater taxonomic diversity as reference libraries, especially for deep-dwelling invertebrate species, continue to expand.

Spatial ecology of the Giant Sea Bass, Stereolepis gigas, in a southern California kelp forest as determined by acoustic telemetry

The fisheries history of the Giant Sea Bass, Stereolepis gigas (Telostei: Polyprionidae), is closely linked to its spatial ecology. Its overharvest is directly associated with formation of spatially distinct spawning aggregations during summer, while its subsequent recovery is hypothesized to be the result of spatially explicit gear restrictions. Understanding the spatial ecology of Giant Sea Bass is a key part of efforts to assess contemporary threats such as commercial harvest and incidental catch by recreational fisheries. In this study, we used acoustic telemetry to characterize Giant Sea Bass space use in the La Jolla kelp forest using an acoustic array that encompasses two marine protected areas (MPAs) and heavily trafficked recreational fishing grounds. Five of the seven fish we tagged remained in the La Jolla array for at least 6 months. Two fish were resident across multiple years, with one fish consistently detected for 4 years. Only one fish was detected in the broader network of regional acoustic receivers, moving north approximately 8 km to Del Mar. Most tagged fish had home ranges and core use areas indicating they spend considerable time outside MPAs, particularly in areas with high recreational fishing activity. During spawning season we detected fish less frequently in the La Jolla array and recorded higher movement rates. While the current MPA network in La Jolla by no means offers complete protection to this fish, it does appear to support long-term persistence of some individuals in a region of exceptionally high recreational fishing pressure.

Anchovy boom and bust linked to trophic shifts in larval diet

Although massive biomass fluctuations of coastal-pelagic fishes are an iconic example of the impacts of climate variability on marine ecosystems, the mechanisms governing these dynamics are often elusive. We construct a 45-year record of nitrogen stable isotopes measured in larvae of Northern Anchovy (Engraulis mordax) in the California Current Ecosystem to assess patterns in food chain length. Larval trophic efficiency associated with a shortened food chain increased larval survival and produced boom periods of high adult biomass. In contrast, when larval food chain length increased, and energy transfer efficiency decreased, the population crashed. We propose the Trophic Efficiency in Early Life (TEEL) hypothesis, which states that larval fishes must consume prey that confer sufficient energy for survival, to help explain natural boom-bust dynamics of coastal pelagic fishes. Our findings illustrate a potential for trophic indicators to generally inform larval survival and adult population dynamics of coastal-pelagic fishes.

Protected fish spawning aggregations as self-replenishing reservoirs for regional recovery

Dispersal of eggs and larvae from spawning sites is critical to the population dynamics and conservation of marine fishes. For overfished species like critically endangered Nassau grouper (Epinephelus striatus), recovery depends on the fate of eggs spawned at the few remaining aggregation sites. Biophysical models can predict larval dispersal, yet these rely on assumed values of key parameters, such as diffusion and mortality rates, which have historically been difficult or impossible to estimate. We used in situ imaging to record three-dimensional positions of individual eggs and larvae in proximity to oceanographic drifters released into egg plumes from the largest known Nassau grouper spawning aggregation. We then estimated a diffusion-mortality model and applied it to previous years' drifter tracks to evaluate the possibility of retention versus export to nearby sites within 5 days of spawning. Results indicate that larvae were retained locally in 2011 and 2017, with 2011 recruitment being a substantial driver of population recovery on Little Cayman. Export to a nearby island with a depleted population occurred in 2016. After two decades of protection, the population appears to be self-replenishing but also capable of seeding recruitment in the region, supporting calls to incorporate spawning aggregation protections into fisheries management.

Grouper source levels and aggregation dynamics inferred from passive acoustic localization at a multispecies spawning site

Four species of grouper (family Epinephlidae), Red Hind (Epinephelus guttatus), Nassau (Epinephelus striatus), Black (Mycteroperca bonaci), and Yellowfin Grouper (Mycteroperca venenosa) share an aggregation site in Little Cayman, Cayman Islands and produce sounds while aggregating. Continuous observation of these aggregations is challenging because traditional diver or ship-based methods are limited in time and space. Passive acoustic localization can overcome this challenge for sound-producing species, allowing observations over long durations and at fine spatial scales. A hydrophone array was deployed in February 2017 over a 9-day period that included Nassau Grouper spawning. Passive acoustic localization was used to find positions of the grouper-produced calls recorded during this time, which enabled the measurement of call source levels and evaluation of spatiotemporal aspects of calling. Yellowfin Grouper had the lowest mean peak-to-peak (PP) call source level, and Nassau Grouper had the highest mean PP call source level (143.7 and 155.2 dB re: 1 μPa at 1 m for 70-170 Hz, respectively). During the days that Nassau Grouper spawned, calling peaked after sunset. Similarly, when Red Hind calls were abundant, calls were highest in the afternoon and evening. The measured source levels can be used to estimate communication and detection ranges and implement passive acoustic density estimation for these fishes.

Modeling the past, present, and future distributions of endangered white abalone (Haliotis sorenseni) to inform recovery efforts in California

White abalone (Haliotis sorenseni) was once commonly found in coastal waters of the Southern California Bight (SCB) and south to Punta Abreojos, Baja California, Mexico. During the 1970s, white abalone supported a commercial fishery, which reduced the population and resulted in the closure of the fishery in 1996. When population levels continued to decline, National Marine Fisheries Service (NMFS) listed the species as endangered under the Endangered Species Act. The California Department of Fish and Wildlife and NMFS began surveying the wild populations, propagating specimens in captivity, and protecting its seabed habitat. We modeled coarse-scale (17 x 17 km) historical (using fishery-dependent data [1955–1996]) and contemporary (using fishery-independent data [1996–2017]) distributions of white abalone throughout its historical domain using random forests and maximum entropy (MaxEnt), respectively, and its fine-scale (10 x 10 m) contemporary distribution (fishery-independent data) using MaxEnt. We also investigated potential outplanting habitat farther north under two scenarios of future climate conditions. The coarse-scale models identified potential regions to focus outplanting efforts within SCB while fine-scale models can inform population monitoring and outplanting activities in these particular areas. These models predict that areas north of Point Conception may become candidate outplant sites as seawater temperatures continue to rise in the future due to climate change. Collectively, these results provide guidance on the design and potential locations for experimental outplanting at such locations to ultimately improve methods and success of recovery efforts.

The rise in climate change-induced federal fishery disasters in the United States

Commercial, recreational, and indigenous fisheries are critical to coastal economies and communities in the United States. For over three decades, the federal government has formally recognized the impact of fishery disasters via federal declarations. Despite these impacts, national syntheses of the dynamics, impacts, and causes of fishery disasters are lacking. We developed a nationwide Federal Fishery Disaster database using National Oceanic and Atmospheric Administration (NOAA) fishery disaster declarations and fishery revenue data. From 1989-2020, there were 71 federally approved fishery disasters (eleven are pending), which spanned every federal fisheries management region and coastal state in the country. To date, we estimate fishery disasters resulted in $2B (2019 USD) in Congressional allocations, and an additional, conservative estimate of $3.2B (2019 USD) in direct revenue loss. Despite this scale of impact, the disaster assistance process is largely ad hoc and lacks sufficient detail to properly assess allocation fairness and benefit. Nonetheless, fishery disasters increased in frequency over time, and the causes of disasters included a broad range of anthropogenic and environmental factors, with a recent shift to disasters now almost exclusively caused by extreme environmental events (e.g., marine heatwaves, hurricanes, and harmful algal blooms). Nationwide, 84.5% of fishery disasters were either partially or entirely attributed to extreme environmental events. As climate change drives higher rates of such extreme events, and as natural disaster assistance requests reach an all-time high, the federal system for fisheries disaster declaration and mitigation must evolve in order to effectively protect both fisheries sustainability and societal benefit.

Allele-Specific Expression and Evolution of Gene Regulation Underlying Acute Heat Stress Response and Local Adaptation in the Copepod Tigriopus californicus

Geographic variation in environmental temperature can select for local adaptation among conspecific populations. Divergence in gene expression across the transcriptome is a key mechanism for evolution of local thermal adaptation in many systems, yet the genetic mechanisms underlying this regulatory evolution remain poorly understood. Here we examine gene expression in 2 locally adapted Tigriopus californicus populations (heat tolerant San Diego, SD, and less tolerant Santa Cruz, SC) and their F1 hybrids during acute heat stress response. Allele-specific expression (ASE) in F1 hybrids was used to determine cis-regulatory divergence. We found that the number of genes showing significant allelic imbalance increased under heat stress compared to unstressed controls. This suggests that there is significant population divergence in cis-regulatory elements underlying heat stress response. Specifically, the number of genes showing an excess of transcripts from the more thermal tolerant (SD) population increased with heat stress while that number of genes with an SC excess was similar in both treatments. Inheritance patterns of gene expression also revealed that genes displaying SD-dominant expression phenotypes increase in number in response to heat stress; that is, across loci, gene expression in F1's following heat stress showed more similarity to SD than SC, a pattern that was absent in the control treatment. The observed patterns of ASE and inheritance of gene expression provide insight into the complex processes underlying local adaptation and thermal stress response.

A Bayesian nested patch occupancy model to estimate steelhead movement and abundance

Anthropogenic impacts on riverine systems have, in part, led to management concerns regarding the population status of species using these systems. In an effort to assess the efficacy of restoration actions, and in order to improve monitoring of species of concern, managers have turned to PIT (passive integrated transponder) tag studies with in-stream detectors to monitor movements of tagged individuals throughout river networks. However, quantifying movements in a river network using PIT tag data with incomplete coverage and imperfect detections presents a challenge. We propose a flexible Bayesian analytic framework that models the imperfectly detected movements of tagged individuals in a nested PIT tag array river network. This model structure provides probabilistic estimates of up-stream migration routes for each tagged individual based on a set of underlying nested state variables. These movement estimates can be converted into abundance estimates when an estimate of abundance is available for a location within the river network. We apply the model framework to data from steelhead (Oncorhynchus mykiss) in the Upper Columbia River basin and evaluate model performance (precision/variance of simulated population sizes) as a function of population tagging rates and PIT tag array detection probability densities within the river system using a simulation framework. This simulation framework provides both model validation (precision) and the ability to evaluate expected performance improvements (variance) due to changes in tagging rates or PIT receiver array configuration. We also investigate the impact of different network configurations on model estimates. Results from such investigations can help inform decisions regarding future monitoring and management.

Long-term participation in collaborative fisheries research improves angler opinions on marine protected areas

Recent marine spatial planning efforts, including the management and monitoring of marine protected areas (MPAs), increasingly focus on the importance of stakeholder engagement. For nearly 15 years, the California Collaborative Fisheries Research Program (CCFRP) has partnered volunteer anglers with researchers, the fishing industry, and resource managers to monitor groundfishes in California's network of MPAs. While the program has succeeded in generating sustained biological observations, we know little about volunteer angler demography or the impact of participation on their perceptions and opinions on fisheries data or MPAs. In this study we surveyed CCFRP volunteers to learn about (a) volunteer angler demographics and attitudes toward groundfish management and stock health, (b) volunteer angler motivations for joining and staying in the program, and (c) whether participation in the program influenced volunteer angler opinions on the quality of fisheries data used in resource management and the establishment of MPAs in California. CCFRP volunteers were older and had higher fishing avidity than average within the California recreational angling community. Many self-identified as more conservation-minded than their peers in the recreational fishing community and had positive views of California groundfish management and stock health. Participation in science and giving back to fisheries resources were major motivating factors in their decision to become and remain CCFRP volunteers. Angler opinions toward MPAs were more positive after volunteering with CCFRP. Those who had volunteered for seven or more years with CCFRP were more likely than not to gain a positive opinion of MPAs. Our survey results provide evidence that long-term engagement of stakeholders in collaborative research positively influences stakeholder opinions regarding marine resource management, and highlights CCFRP's success in engaging citizen science stakeholders in collaborative fisheries research.

A deconvolutional Bayesian mixing model approach for river basin sediment source apportionment

Increasing complexity in human-environment interactions at multiple watershed scales presents major challenges to sediment source apportionment data acquisition and analysis. Herein, we present a step-change in the application of Bayesian mixing models: Deconvolutional-MixSIAR (D-MIXSIAR) to underpin sustainable management of soil and sediment. This new mixing model approach allows users to directly account for the ‘structural hierarchy’ of a river basin in terms of sub-watershed distribution. It works by deconvoluting apportionment data derived for multiple nodes along the stream-river network where sources are stratified by sub-watershed. Source and mixture samples were collected from two watersheds that represented (i) a longitudinal mixed agricultural watershed in the south west of England which had a distinct upper and lower zone related to topography and (ii) a distributed mixed agricultural and forested watershed in the mid-hills of Nepal with two distinct sub-watersheds. In the former, geochemical fingerprints were based upon weathering profiles and anthropogenic soil amendments. In the latter compound-specific stable isotope markers based on soil vegetation cover were applied. Mixing model posterior distributions of proportional sediment source contributions differed when sources were pooled across the watersheds (pooled-MixSIAR) compared to those where source terms were stratified by sub-watershed and the outputs deconvoluted (D-MixSIAR). In the first example, the stratified source data and the deconvolutional approach provided greater distinction between pasture and cultivated topsoil source signatures resulting in a different posterior distribution to non-deconvolutional model (conventional approaches over-estimated the contribution of cultivated land to downstream sediment by 2 to 5 times). In the second example, the deconvolutional model elucidated a large input of sediment delivered from a small tributary resulting in differences in the reported contribution of a discrete mixed forest source. Overall D-MixSIAR model posterior distributions had lower (by ca 25–50%) uncertainty and quicker model run times. In both cases, the structured, deconvoluted output cohered more closely with field observations and local knowledge underpinning the need for closer attention to hierarchy in source and mixture terms in river basin source apportionment. Soil erosion and siltation challenge the energy-food-water-environment nexus. This new tool for source apportionment offers wider application across complex environmental systems affected by natural and human-induced change and the lessons learned are relevant to source apportionment applications in other disciplines.

Analyzing mixing systems using a new generation of Bayesian tracer mixing models

The ongoing evolution of tracer mixing models has resulted in a confusing array of software tools that differ in terms of data inputs, model assumptions, and associated analytic products. Here we introduce MixSIAR, an inclusive, rich, and flexible Bayesian tracer (e.g., stable isotope) mixing model framework implemented as an open-source R package. Using MixSIAR as a foundation, we provide guidance for the implementation of mixing model analyses. We begin by outlining the practical differences between mixture data error structure formulations and relate these error structures to common mixing model study designs in ecology. Because Bayesian mixing models afford the option to specify informative priors on source proportion contributions, we outline methods for establishing prior distributions and discuss the influence of prior specification on model outputs. We also discuss the options available for source data inputs (raw data versus summary statistics) and provide guidance for combining sources. We then describe a key advantage of MixSIAR over previous mixing model software-the ability to include fixed and random effects as covariates explaining variability in mixture proportions and calculate relative support for multiple models via information criteria. We present a case study of Alligator mississippiensis diet partitioning to demonstrate the power of this approach. Finally, we conclude with a discussion of limitations to mixing model applications. Through MixSIAR, we have consolidated the disparate array of mixing model tools into a single platform, diversified the set of available parameterizations, and provided developers a platform upon which to continue improving mixing model analyses in the future.

Density estimates of monarch butterflies overwintering in central Mexico

Given the rapid population decline and recent petition for listing of the monarch butterfly (Danaus plexippus L.) under the Endangered Species Act, an accurate estimate of the Eastern, migratory population size is needed. Because of difficulty in counting individual monarchs, the number of hectares occupied by monarchs in the overwintering area is commonly used as a proxy for population size, which is then multiplied by the density of individuals per hectare to estimate population size. There is, however, considerable variation in published estimates of overwintering density, ranging from 6.9–60.9 million ha⁻¹. We develop a probability distribution for overwinter density of monarch butterflies from six published density estimates. The mean density among the mixture of the six published estimates was ∼27.9 million butterflies ha⁻¹ (95% CI [2.4–80.7] million ha⁻¹); the mixture distribution is approximately log-normal, and as such is better represented by the median (21.1 million butterflies ha⁻¹). Based upon assumptions regarding the number of milkweed needed to support monarchs, the amount of milkweed (Asclepias spp.) lost (0.86 billion stems) in the northern US plus the amount of milkweed remaining (1.34 billion stems), we estimate >1.8 billion stems is needed to return monarchs to an average population size of 6 ha. Considerable uncertainty exists in this required amount of milkweed because of the considerable uncertainty occurring in overwinter density estimates. Nevertheless, the estimate is on the same order as other published estimates. The studies included in our synthesis differ substantially by year, location, method, and measures of precision. A better understanding of the factors influencing overwintering density across space and time would be valuable for increasing the precision of conservation recommendations.

Quasi-extinction risk and population targets for the Eastern, migratory population of monarch butterflies (Danaus plexippus)

The Eastern, migratory population of monarch butterflies (Danaus plexippus), an iconic North American insect, has declined by ~80% over the last decade. The monarch’s multi-generational migration between overwintering grounds in central Mexico and the summer breeding grounds in the northern U.S. and southern Canada is celebrated in all three countries and creates shared management responsibilities across North America. Here we present a novel Bayesian multivariate auto-regressive state-space model to assess quasi-extinction risk and aid in the establishment of a target population size for monarch conservation planning. We find that, given a range of plausible quasi-extinction thresholds, the population has a substantial probability of quasi-extinction, from 11–57% over 20 years, although uncertainty in these estimates is large. Exceptionally high population stochasticity, declining numbers, and a small current population size act in concert to drive this risk. An approximately 5-fold increase of the monarch population size (relative to the winter of 2014–15) is necessary to halve the current risk of quasi-extinction across all thresholds considered. Conserving the monarch migration thus requires active management to reverse population declines, and the establishment of an ambitious target population size goal to buffer against future environmentally driven variability.

Analyzing large-scale conservation interventions with Bayesian hierarchical models: a case study of supplementing threatened Pacific salmon

Myriad human activities increasingly threaten the existence of many species. A variety of conservation interventions such as habitat restoration, protected areas, and captive breeding have been used to prevent extinctions. Evaluating the effectiveness of these interventions requires appropriate statistical methods, given the quantity and quality of available data. Historically, analysis of variance has been used with some form of predetermined before-after control-impact design to estimate the effects of large-scale experiments or conservation interventions. However, ad hoc retrospective study designs or the presence of random effects at multiple scales may preclude the use of these tools. We evaluated the effects of a large-scale supplementation program on the density of adult Chinook salmon Oncorhynchus tshawytscha from the Snake River basin in the northwestern United States currently listed under the U.S. Endangered Species Act. We analyzed 43 years of data from 22 populations, accounting for random effects across time and space using a form of Bayesian hierarchical time-series model common in analyses of financial markets. We found that varying degrees of supplementation over a period of 25 years increased the density of natural-origin adults, on average, by 0-8% relative to nonsupplementation years. Thirty-nine of the 43 year effects were at least two times larger in magnitude than the mean supplementation effect, suggesting common environmental variables play a more important role in driving interannual variability in adult density. Additional residual variation in density varied considerably across the region, but there was no systematic difference between supplemented and reference populations. Our results demonstrate the power of hierarchical Bayesian models to detect the diffuse effects of management interventions and to quantitatively describe the variability of intervention success. Nevertheless, our study could not address whether ecological factors (e.g., competition) were more important than genetic considerations (e.g., inbreeding depression) in determining the response to supplementation.

Best practices for use of stable isotope mixing models in food-web studies

Stable isotope mixing models are increasingly used to quantify consumer diets, but may be misused and misinterpreted. We address major challenges to their effective application. Mixing models have increased rapidly in sophistication. Current models estimate probability distributions of source contributions, have user-friendly interfaces, and incorporate complexities such as variability in isotope signatures, discrimination factors, hierarchical variance structure, covariates, and concentration dependence. For proper implementation of mixing models, we offer the following suggestions. First, mixing models can only be as good as the study and data. Studies should have clear questions, be informed by knowledge of the system, and have strong sampling designs to effectively characterize isotope variability of consumers and resources on proper spatio-temporal scales. Second, studies should use models appropriate for the question and recognize their assumptions and limitations. Decisions about source grouping or incorporation of concentration dependence can influence results. Third, studies should be careful about interpretation of model outputs. Mixing models generally estimate proportions of assimilated resources with substantial uncertainty distributions. Last, common sense, such as graphing data before analyzing, is essential to maximize usefulness of these tools. We hope these suggestions for effective implementation of stable isotope mixing models will aid continued development and application of this field.

Population structure and phylogeography in Nassau grouper (Epinephelus striatus), a mass-aggregating marine fish

To address patterns of genetic connectivity in a mass-aggregating marine fish, we analyzed genetic variation in mitochondrial DNA (mtDNA), microsatellites, and single nucleotide polymorphisms (SNPs) for Nassau grouper (Epinephelus striatus). We expected Nassau grouper to exhibit genetic differentiation among its subpopulations due to its reproductive behavior and retentive oceanographic conditions experienced across the Caribbean basin. All samples were genotyped for two mitochondrial markers and 9 microsatellite loci, and a subset of samples were genotyped for 4,234 SNPs. We found evidence of genetic differentiation in a Caribbean-wide study of this mass-aggregating marine fish using mtDNA (F_ST = 0.206, p<0.001), microsatellites (F_ST = 0.002, p = 0.004) and SNPs (F_ST = 0.002, p = 0.014), and identified three potential barriers to larval dispersal. Genetically isolated regions identified in our work mirror those seen for other invertebrate and fish species in the Caribbean basin. Oceanographic regimes in the Caribbean may largely explain patterns of genetic differentiation among Nassau grouper subpopulations. Regional patterns observed warrant standardization of fisheries management and conservation initiatives among countries within genetically isolated regions.

Phenotypic variation and selective mortality as major drivers of recruitment variability in fishes

An individual's phenotype will usually influence its probability of survival. However, when evaluating the dynamics of populations, the role of selective mortality is not always clear. Not all mortality is selective, patterns of selective mortality may vary, and it is often unknown how selective mortality compares or interacts with other sources of mortality. As a result, there is seldom a clear expectation for how changes in the phenotypic composition of populations will translate into differences in average survival. We address these issues by evaluating how selective mortality affects recruitment of fish populations. First, we provide a quantitative review of selective mortality. Our results show that most of the mortality during early life is selective, and that variation in phenotypes can have large effects on survival. Next, we describe an analytical framework that accounts for variation in selection, while also describing the amount of selective mortality experienced by different cohorts recruiting to a single population. This framework is based on reconstructing fitness surfaces from phenotypic selection measurements, and can be employed for either single or multiple traits. Finally, we show how this framework can be integrated with models of density-dependent survival to improve our understanding of recruitment variability and population dynamics.

Assessing the effects of large mobile predators on ecosystem connectivity

Large predators are often highly mobile and can traverse and use multiple habitats. We know surprisingly little about how predator mobility determines important processes of ecosystem connectivity. Here we used a variety of data sources drawn from Palmyra Atoll, a remote tropical marine ecosystem where large predators remain in high abundance, to investigate how these animals foster connectivity. Our results indicate that three of Palmyra's most abundant large predators (e.g., two reef sharks and one snapper) use resources from different habitats creating important linkages across ecosystems. Observations of cross-system foraging such as this have important implications for the understanding of ecosystem functioning, the management of large-predator populations, and the design of conservation measures intended to protect whole ecosystems. In the face of widespread declines of large, mobile predators, it is important that resource managers, policy makers, and ecologists work to understand how these predators create connectivity and to determine the impact that their depletions may be having on the integrity of these linkages.

Permanent genetic resources added to molecular ecology resources database 1 April 2012 - 31 May 2012

This article documents the addition of 123 microsatellite marker loci to the Molecular Ecology Resources Database. Loci were developed for the following species: Brenthis ino, Cichla orinocensis, Cichla temensis, Epinephelus striatus, Gobio gobio, Liocarcinus depurator, Macrolophus pygmaeus, Monilinia vaccinii-corymbosi, Pelochelys cantorii, Philotrypesis josephi, Romanogobio vladykovi, Takydromus luyeanus and Takydromus viridipunctatus. These loci were cross-tested on the following species: Cichla intermedia, Cichla ocellaris, Cichla pinima, Epinephelus acanthistius, Gobio carpathicus, Gobio obtusirostris, Gobio sp. 1, Gobio volgensis, Macrolophus costalis, Macrolophus melanotoma, Macrolophus pygmaeus, Romanogobio albipinnatus, Romanogobio banaticus, Romanogobio belingi, Romanogobio kesslerii, Romanogobio parvus, Romanogobio pentatrichus, Romanogobio uranoscopus, Takydromus formosanus, Takydromus hsuehshanesis and Takydromus stejnegeri.

Using stable isotope analysis to understand the migration and trophic ecology of northeastern Pacific white sharks (Carcharodon carcharias)

The white shark (Carcharodon carcharias) is a wide-ranging apex predator in the northeastern Pacific (NEP). Electronic tagging has demonstrated that white sharks exhibit a regular migratory pattern, occurring at coastal sites during the late summer, autumn and early winter and moving offshore to oceanic habitats during the remainder of the year, although the purpose of these migrations remains unclear. The purpose of this study was to use stable isotope analysis (SIA) to provide insight into the trophic ecology and migratory behaviors of white sharks in the NEP. Between 2006 and 2009, 53 white sharks were biopsied in central California to obtain dermal and muscle tissues, which were analyzed for stable isotope values of carbon (δ(13)C) and nitrogen (δ(15)N). We developed a mixing model that directly incorporates movement data and tissue incorporation (turnover) rates to better estimate the relative importance of different focal areas to white shark diet and elucidate their migratory behavior. Mixing model results for muscle showed a relatively equal dietary contribution from coastal and offshore regions, indicating that white sharks forage in both areas. However, model results indicated that sharks foraged at a higher relative rate in coastal habitats. There was a negative relationship between shark length and muscle δ(13)C and δ(15)N values, which may indicate ontogenetic changes in habitat use related to onset of maturity. The isotopic composition of dermal tissue was consistent with a more rapid incorporation rate than muscle and may represent more recent foraging. Low offshore consumption rates suggest that it is unlikely that foraging is the primary purpose of the offshore migrations. These results demonstrate how SIA can provide insight into the trophic ecology and migratory behavior of marine predators, especially when coupled with electronic tagging data.

Patterns of color phase indicate spawn timing at a Nassau grouper Epinephelus striatus spawning aggregation

Nassau grouper Epinephelus striatus are a large bodied, top level predator that is ecologically important throughout the Caribbean. Although typically solitary, Nassau grouper form large annual spawning aggregations at predictable times in specific locations. In 2003, The Cayman Islands Marine Conservation Board established protection for a newly rediscovered Nassau grouper spawning aggregation on Little Cayman, British West Indies. The large size of this aggregation provides a unique opportunity to study the behavior of Nassau grouper on a relatively intact spawning aggregation. During non-spawning periods Nassau grouper display a reddish-brown-and-white barred coloration. However, while aggregating they exhibit three additional color phases: “bicolor”, “dark”, and “white belly”. We video sampled the population on multiple days leading up to spawning across five spawning years. Divers focused a laser caliper equipped video camera on individual fish at the aggregation. We later analyzed the video to determine the length of the fish and record the color phase. Our observations show that the relative proportion of fish in the bicolor color phase increases significantly on the day leading up to the primary night of spawning. The increase in the proportion of the bicolor color phase from 0.05 early in the aggregation to 0.40 on the day of spawning suggests that this color phase conveys that a fish is behaviorally and physiologically prepared to spawn. Additionally, 82.7% of fish exhibiting dark or white belly coloration early in the aggregation period suggests that these color phases are not only shown by female fish as was previously posited.

Merging resource availability with isotope mixing models: the role of neutral interaction assumptions

BACKGROUND

Bayesian mixing models have allowed for the inclusion of uncertainty and prior information in the analysis of trophic interactions using stable isotopes. Formulating prior distributions is relatively straightforward when incorporating dietary data. However, the use of data that are related, but not directly proportional, to diet (such as prey availability data) is often problematic because such information is not necessarily predictive of diet, and the information required to build a reliable prior distribution for all prey species is often unavailable. Omitting prey availability data impacts the estimation of a predator's diet and introduces the strong assumption of consumer ultrageneralism (where all prey are consumed in equal proportions), particularly when multiple prey have similar isotope values.

METHODOLOGY

We develop a procedure to incorporate prey availability data into bayesian mixing models conditional on the similarity of isotope values between two prey. If a pair of prey have similar isotope values (resulting in highly uncertain mixing model results), our model increases the weight of availability data in estimating the contribution of prey to a predator's diet. We test the utility of this method in an intertidal community against independently measured feeding rates.

CONCLUSIONS

Our results indicate that our weighting procedure increases the accuracy by which consumer diets can be inferred in situations where multiple prey have similar isotope values. This suggests that the exchange of formalism for predictive power is merited, particularly when the relationship between prey availability and a predator's diet cannot be assumed for all species in a system.

Effects of multiple levels of social organization on survival and abundance

Identifying how social organization shapes individual behavior, survival, and fecundity of animals that live in groups can inform conservation efforts and improve forecasts of population abundance, even when the mechanism responsible for group-level differences is unknown. We constructed a hierarchical Bayesian model to quantify the relative variability in survival rates among different levels of social organization (matrilines and pods) of an endangered population of killer whales (Orcinus orca). Individual killer whales often participate in group activities such as prey sharing and cooperative hunting. The estimated age-specific survival probabilities and survivorship curves differed considerably among pods and to a lesser extent among matrilines (within pods). Across all pods, males had lower life expectancy than females. Differences in survival between pods may be caused by a combination of factors that vary across the population's range, including reduced prey availability, contaminants in prey, and human activity. Our modeling approach could be applied to demographic rates for other species and for parameters other than survival, including reproduction, prey selection, movement, and detection probabilities.

Habitat structure determines resource use by zooplankton in temperate lakes

While the importance of terrestrial linkages to aquatic ecosystems is well appreciated, the degree of terrestrial support of aquatic consumers remains debated. Estimates of terrestrial contributions to lake zooplankton have omitted a key food source, phytoplankton produced below the mixed layer. We used carbon and nitrogen stable isotope data from 25 Pacific Northwest lakes to assess the relative importance of particulate organic matter (POM) from the mixed layer, below the mixed layer and terrestrial detritus to zooplankton. Zooplankton and deep POM were depleted in ¹³C relative to mixed layer POM in lakes that can support deep primary production. A Bayesian stable isotope mixing model estimated that terrestrial detritus contributed <5% to zooplankton production, and confirms the role of lake optical and thermal properties; deep POM accounted for up to 80% of zooplankton production in the clearest lakes. These results suggest terrestrial support of lake zooplankton production is trivial.

Including source uncertainty and prior information in the analysis of stable isotope mixing models

Stable isotope mixing models offer a statistical framework for estimating the contribution of multiple sources (such as prey) to a mixture distribution. Recent advances in these models have estimated the source proportions using Bayesian methods, but have not explicitly accounted for uncertainty in the mean and variance of sources. We demonstrate that treating these quantities as unknown parameters can reduce bias in the estimated source contributions, although model complexity is increased (thereby increasing the variance of estimates). The advantages of this fully Bayesian approach are particularly apparent when the source geometry is poor or sample sizes are small. A second benefit to treating source quantities as parameters is that prior source information can be included. We present findings from 9 lake food-webs, where the consumer of interest (fish) has a diet composed of 5 sources: aquatic insects, snails, zooplankton, amphipods, and terrestrial insects. We compared the traditional Bayesian stable isotope mixing model with fixed source parameters to our fully Bayesian model-with and without an informative prior. The informative prior has much less impact than the choice of model-the traditional mixing model with fixed source parameters estimates the diet to be dominated by aquatic insects, while the fully Bayesian model estimates the diet to be more balanced but with greater importance of zooplankton. The findings from this example demonstrate that there can be stark differences in inference between the two model approaches, particularly when the source geometry of the mixing model is poor. These analyses also emphasize the importance of investing substantial effort toward characterizing the variation in the isotopic characteristics of source pools to appropriately quantify uncertainties in their contributions to consumers in food webs.

Quantifying inter- and intra-population niche variability using hierarchical bayesian stable isotope mixing models

Variability in resource use defines the width of a trophic niche occupied by a population. Intra-population variability in resource use may occur across hierarchical levels of population structure from individuals to subpopulations. Understanding how levels of population organization contribute to population niche width is critical to ecology and evolution. Here we describe a hierarchical stable isotope mixing model that can simultaneously estimate both the prey composition of a consumer diet and the diet variability among individuals and across levels of population organization. By explicitly estimating variance components for multiple scales, the model can deconstruct the niche width of a consumer population into relevant levels of population structure. We apply this new approach to stable isotope data from a population of gray wolves from coastal British Columbia, and show support for extensive intra-population niche variability among individuals, social groups, and geographically isolated subpopulations. The analytic method we describe improves mixing models by accounting for diet variability, and improves isotope niche width analysis by quantitatively assessing the contribution of levels of organization to the niche width of a population.

Improving Bayesian isotope mixing models: a response to Jackson et al. (2009)

We recently described a Bayesian framework for stable isotope mixing models and provided a software tool, MixSIR, for conducting such analyses (Ecol. Lett., 2008; 11:470). Jackson et al. (Ecol. Lett., 2009; 12:E1) criticized the performance of our software based on tests using simulated data. However, their simulation data were flawed, rendering claims of erroneous behaviour inaccurate. A re-evaluation of the MixSIR source code did, however, uncover two minor coding errors, which we have fixed. When data are correctly simulated according to eqns (1)-(4) in Jackson et al. (2009), MixSIR consistently and accurately estimated the proportional contribution of prey to a predator diet, and was surprisingly robust to additional unquantified error. Jackson et al. (2009) also suggested we use a Dirichlet prior on the source proportion parameters, which we agree with. Finally, Jackson et al. (2009) propose adding additional error parameters to our mixing model framework. We caution that such increases in model complexity should be evaluated based on data support.

Conservation and management applications of the REEF volunteer fish monitoring program

The REEF Fish Survey Project is a volunteer fish monitoring program developed by the Reef Environmental Education Foundation (REEF). REEF volunteers collect fish distribution and abundance data using a standardized visual method during regular diving and snorkeling activities. Survey data are recorded on preprinted data sheets that are returned to REEF and optically digitized. Data are housed in a publicly accessible database on REEF's Web site (http://www.reef.org). Since the project's inception in 1993, over 40,000 surveys have been conducted in the coastal waters of North America, tropical western Atlantic, Gulf of California and Hawaii. The Fish Survey Project has been incorporated into existing monitoring programs through partnerships with government agencies, scientists, conservation organizations, and private institutions. REEF's partners benefit from the educational value and increased stewardship resulting from volunteer data collection. Applications of the data include an evaluation of fish/habitat interactions in the Florida Keys National Marine Sanctuary, the development of a multi-species trend analysis method to identify sites of management concern, assessment of the current distribution of species, status reports on fish assemblages of marine parks, and the evaluation of no-take zones in the Florida Keys. REEF's collaboration with a variety of partners, combined with the Fish Survey Project's standardized census method and database management system, has resulted in a successful citizen science monitoring program.