Bayesian State-space Model Research Articles

Historical reconstruction of the population dynamics of southern right whales in the southwestern Atlantic Ocean

Understanding the recovery of whale populations is critical for developing population-management and conservation strategies. The southern right whale (SRW) Eubalena australis was one of the baleen whale species that has experienced centuries of exploitation. We assess here for the first time the population dynamics of the SRW from the southwestern Atlantic Ocean at the regional level to measure numerically the effect of whaling and estimate the population trend and recovery level after depletion. We reconstructed the catch history of whaling for the period 1670–1973 by an extensive review of different literature sources and developed a Bayesian state-space model to estimate the demographic parameters. The population trajectory indicated that the pre-exploitation abundance was close to 58,000 individuals (median = 58,212; 95% CI = 33,329–100,920). The abundance dropped to its lowest abundance levels in the 1830s when fewer than 2,000 individuals remained. The current median population abundance was estimated at 4,742 whales (95% CI = 3,853–6,013), suggesting that the SRW population remains small relative to its pre-exploitation abundance (median depletion P2021 8.7%). We estimated that close to 36% of the SRW population visits the waters of the Península Valdés, the main breeding ground, every year. Our results provide insights into the severity of the whaling operation in the southwestern Atlantic along with the population´s response at low densities, thus contributing to understand the observed differences in population trends over the distributional range of the species worldwide.

Ecological forecasting of tree growth: Regional fusion of tree-ring and forest inventory data to quantify drivers and characterize uncertainty.

Robust ecological forecasting of tree growth under future climate conditions is critical to anticipate future forest carbon storage and flux. Here, we apply three ingredients of ecological forecasting that are key to improving forecast skill: data fusion, confronting model predictions with new data, and partitioning forecast uncertainty. Specifically, we present the first fusion of tree-ring and forest inventory data within a Bayesian state-space model at a multi-site, regional scale, focusing on Pinus ponderosa var. brachyptera in the southwestern US. Leveraging the complementarity of these two data sources, we parsed the ecological complexity of tree growth into the effects of climate, tree size, stand density, site quality, and their interactions, and quantified uncertainties associated with these effects. New measurements of trees, an ongoing process in forest inventories, were used to confront forecasts of tree diameter with observations, and evaluate alternative tree growth models. We forecasted tree diameter and increment in response to an ensemble of climate change projections, and separated forecast uncertainty into four different causes: initial conditions, parameters, climate drivers, and process error. We found a strong negative effect of fall-spring maximum temperature, and a positive effect of water-year precipitation on tree growth. Furthermore, tree vulnerability to climate stress increases with greater competition, with tree size, and at poor sites. Under future climate scenarios, we forecast increment declines of 22%-117%, while the combined effect of climate and size-related trends results in a 56%-91% decline. Partitioning of forecast uncertainty showed that diameter forecast uncertainty is primarily caused by parameter and initial conditions uncertainty, but increment forecast uncertainty is mostly caused by process error and climate driver uncertainty. This fusion of tree-ring and forest inventory data lays the foundation for robust ecological forecasting of aboveground biomass and carbon accounting at tree, plot, and regional scales, including iterative improvement of model skill.

Fisheries Reference Point and Stock Status of Croaker Fishery (Sciaenidae) Exploited from the Bay of Bengal, Bangladesh

This research evaluated fisheries reference points and stock status to assess the sustainability of the croaker fishery (Sciaenidae) from the Bay of Bengal (BoB), Bangladesh. Sixteen years (2001–2016) of catch-effort data were analyzed using two surplus production models (Schaefer and Fox), the Monte Carlo method (CMSY) and the Bayesian state-space Schaefer surplus production model (BSM) method. This research applies a Stock–Production Model Incorporating Covariates (ASPIC) software package to run the Schaefer and Fox model. The maximum sustainable yield (MSY) produced by all models ranged from 33,900 to 35,900 metric tons (mt), which is very close to last year’s catch (33,768 mt in 2016). The estimated B > BMSY and F < FMSY indicated the safe biomass and fishing status. The calculated F/FMSY was 0.89, 0.87, and 0.81, and B/BMSY was 1.05, 1.07, and 1.14 for Fox, Schaefer, and BSM, respectively, indicating the fully exploited status of croaker stock in the BoB, Bangladesh. The representation of the Kobe phase plot suggested that the exploitation of croaker stock started from the yellow (unsustainable) quadrant in 2001 and gradually moved to the green (sustainable) quadrant in 2016 because of the reduction in fishing efforts and safe fishing pressure after 2012. Thus, this research suggests that the current fishing pressure needs to be maintained so that the yearly catch does not exceed the MSY limit of croaker. Additionally, specific management measures should implement to guarantee croaker and other fisheries from the BoB.

Seabird meta-Population Viability Model (mPVA) methods

The seabird meta-population viability model (mPVA) uses a generalized approach to project abundance and quasi-extinction risk for 102 seabird species under various conservation scenarios. The mPVA is a stage-structured projection matrix that tracks abundance of multiple populations linked by dispersal, accounting for breeding island characteristics and spatial distribution. Data are derived from published studies, grey literature, and expert review (with over 500 contributions). Invasive species impacts were generalized to stage-specific vital rates by fitting a Bayesian state-space model to trend data from Islands where invasive removals had occurred, while accounting for characteristics of seabird biology, breeding islands and invasive species. Survival rates were estimated using a competing hazards formulation to account for impacts of multiple threats, while also allowing for environmental and demographic stochasticity, density dependence and parameter uncertainty.•The mPVA provides resource managers with a tool to quantitatively assess potential benefits of alternative management actions, for multiple species•The mPVA compares projected abundance and quasi-extinction risk under current conditions (no intervention) and various conservation scenarios, including removal of invasive species from specified breeding islands, translocation or reintroduction of individuals to an island of specified location and size, and at-sea mortality amelioration via reduction in annual at-sea deaths

Context-dependent fitness costs of reproduction despite stable body mass costs in an Arctic herbivore.

The cost of reproduction on demographic rates is often assumed to operate through changing body condition. Several studies have found that reproduction depresses body mass more if the current conditions are severe, such as high population densities or adverse weather, than under benign environmental conditions. However, few studies have investigated the association between the fitness components and body mass costs of reproduction. Using 25years of individual-based capture-recapture data from Svalbard reindeer Rangifer tarandus platyrhynchus, we built a novel Bayesian state-space model that jointly estimated interannual change in mass, annual reproductive success and survival, while accounting for incomplete observations. The model allowed us to partition the differential effects of intrinsic and extrinsic factors on both non-reproductive mass change and the body mass cost of reproduction, and to quantify their consequences on demographic rates. Contrary to our expectation, the body mass cost of reproduction (mean=-5.8kg) varied little between years (CV=0.08), whereas the between-year variation in body mass changes, that were independent of the previous year's reproductive state, varied substantially (CV=0.4) in relation to autumn temperature and the amount of rain-on-snow in winter. This body mass loss led to a cost of reproduction on the next reproduction, which was amplified by the same environmental covariates, from a 10% reduction in reproductive success in benign years, to a 50% reduction in harsh years. The reproductive mass loss also resulted in a small reduction in survival. Our results show how demographic costs of reproduction, driven by interannual fluctuations in individual body condition, result from the balance between body mass costs of reproduction and body mass changes that are independent of previous reproductive state. We illustrate how a strong context-dependent fitness cost of reproduction can occur, despite a relatively fixed body mass cost of reproduction. This suggests that female reindeer display a very conservative energy allocation strategy, either aborting their reproductive attempt at an early stage or weaning at a relatively constant cost. Such a strategy might be common in species living in a highly stochastic and food limited environment.

High bycatch rates of manta and devil rays in the "small-scale" artisanal fisheries of Sri Lanka.

BackgroundExpanding fisheries in developing nations like Sri Lanka have a significant impact on threatened marine species such as elasmobranchs. Manta and devil (mobulid) rays have some of the most conservative life history strategies of any elasmobranch, and even low to moderate levels of bycatch from gillnet fisheries may lead to significant population declines. A lack of information on life history, demographics, population trends, and fisheries impacts hinders effective management measures for these species.MethodWe report on mobulid fishery landings over nine years between 2011 and 2020 across 38 landing sites in Sri Lanka. We collected data on catch numbers, body sizes, sex, and maturity status for five mobulid species. We used a Bayesian state-space model to estimate monthly country-wide catch rates and total annual landings of mobulid rays. We used catch curve analyses to estimate total mortality for Mobula mobular, and evaluated trends in recorded body sizes across the study period for M. mobular, M. birostris, M. tarapacana and M. thurstoni.ResultsWe find that catch rates have declined an order of magnitude for all species across the study period, and that total annual captures of mobulid rays by the Sri Lankan artisanal fishing fleet exceed the estimated annual captures of mobulids in all global, industrial purse seine fisheries combined. Catch curve analyses suggest that M. mobular is being fished at rates far above the species’ intrinsic population growth rate, and the average sizes of all mobulids in the fishery except for M. birostris are declining. Collectively, these findings suggest overfishing of mobulid ray populations in the northern Indian Ocean by Sri Lankan artisanal fisheries. We recommend strengthening the management of these species through improved implementation of CITES, CMS, and regional fisheries management actions. In addition, we report on the demographic characteristics of mobulids landed in Sri Lanka and provide the first record of M. eregoodoo in the country.

Integrating Multiple Survey Techniques to Document a Shifting Bat Community in the Wake of White-Nose Syndrome

AbstractThe long-term study of bat communities often depends on a diverse set of sampling methodologies that are chosen based on the species or habitat management priorities of the research project. Integrating the data from a diverse set of methodologies (such as acoustic monitoring and mist net sampling) would improve our ability to characterize changes in community structure or composition over time, such as one would expect following an emergent infectious disease such as white-nose syndrome. We developed a Bayesian state-space model to integrate these disparate data into a common currency (relative abundance). We collected both acoustic monitoring and mist net capture data over an 8-y period (2006–2014) to document shifts in the bat community in central New England, USA, in response to the onset of white-nose syndrome in 2009. The integrated data model shows a significant decline in the abundance of little brown bat Myotis lucifugus, northern long-eared bat Myotis septentrionalis, and hoary bat Lasiurus cinereus, and an increase in abundance of the eastern small-footed bat Myotis leibii and the eastern red bat Lasiurus borealis. There was no evidence for a change in abundance in the big brown bat Eptesicus fuscus since the onset of white-nose syndrome. The consistency of this model with regional estimates of decline over the same time period support the validity of our relative abundance estimate. This model provides the opportunity to quantify shifts in other communities where multiple sampling methodologies were employed, and therefore provides natural resource managers with a robust tool to integrate existing sampling data to quantify changes in community composition that can inform conservation and management recommendations.

Rapid quantification of extracellular neurotransmitters in mouse brain by PESI/MS/MS and longitudinal data analysis using the R and Stan-based Bayesian state-space model

We developed a methodology for rapid quantification of extracellular neurotransmitters in mouse brain by PESI/MS/MS and longitudinal data analysis using the R and Stan-based Bayesian state-space model. We performed a rapid analysis for quantifying extracellular l-glutamic acid (L-Glu) and gamma-aminobutyric acid (GABA) in the mouse striatum by combined use of probe electrospray ionization/tandem mass spectrometry (PESI/MS/MS) and in vivo brain microdialysis. We optimized the PESI/MS/MS parameters with the authentic L-Glu, GABA, L-Glu-13C5,15N1, and GABA-D6 standards. We constructed calibration curves of L-Glu and GABA with the stable isotope internal standard correction method (L-Glu-13C5,15N1, and GABA-D6), demonstrating sufficient linearity (R > 0.999). Additionally, the quantitative method for L-Glu and GABA was validated with low-, middle-, and high-quality control samples. The intra- and inter-day accuracy and precision were 0.4%–7.5% and 1.7%–5.4% for L-Glu, respectively, and 0.1%–4.8% and 2.1%–5.7% for GABA, respectively, demonstrating high reproducibility of the method. To evaluate the feasibility of this method, microdialyses were performed on free-moving mice that were stimulated by high-K+-induced depolarization under different sampling conditions: 1) every 5 min for 150 min (n = 2) and 2) every 1 min for 30 min (n = 3). We applied the R and Stan-based Bayesian state-space model to each mouse's time-series data considering autocorrelation, and the model successfully detected abnormal changes in the L-Glu and GABA levels in each mouse. Thus, the L-Glu and GABA levels in all microdialysates approximately increased up to two- and seven-fold levels through high-K+-induced depolarization. Additionally, a 1-min temporal resolution was achieved using this method, thereby successfully monitoring microenvironmental changes in the extracellular L-Glu and GABA of the mouse striatum. In conclusion, this methodology using PESI/MS/MS and Bayesian state-space model allowed easy monitoring of neurotransmitters at high temporal resolutions and appropriate data interpretation considering autocorrelation of time-series data, which will reveal hidden pathological mechanisms of brain diseases, such as Parkinson's disease and Huntington's disease in the future.

Validation of stock assessment methods: is it me or my model talking?

Abstract The adoption of the Precautionary Approach requires providing advice that is robust to uncertainty. Therefore, when conducting stock assessment alternative, model structures and data sets are commonly considered. The primary diagnostics used to compare models are to examine residuals patterns to check goodness-of-fit and to conduct retrospective analysis to check the stability of estimates. However, residual patterns can be removed by adding more parameters than justified by the data, and retrospective patterns removed by ignoring the data. Therefore, neither alone can be used for validation, which requires assessing whether it is plausible that a system identical to the model generated the data. Therefore, we use hindcasting to estimate prediction skill, a measure of the accuracy of a predicted value unknown by the model relative to its observed value, to explore model misspecification and data conflicts. We compare alternative model structures based on integrated statistical and Bayesian state-space biomass dynamic models using, as an example, Indian Ocean yellowfin tuna. Validation is not a binary process (i.e. pass or fail) but a continuum; therefore, we discuss the use of prediction skill to identify alternative hypotheses, weight ensemble models and agree on reference sets of operating models when conducting Management Strategy Evaluation.

Experimental field evidence shows milkweed contaminated with a common neonicotinoid decreases larval survival of monarch butterflies.

Neonicotinoid insecticides are the most widely used class of insecticides in the world and can have both lethal and sub-lethal effects on non-target organisms in agricultural areas. Monarch butterflies Danaus plexippus have experienced dramatic declines in recent decades and, given that a large proportion of milkweed on the landscape grows in agricultural areas, there is concern about the negative effects of neonicotinoids on this non-target insect. In the field, we exposed common milkweed Asclepias syriaca, an obligate host plant of monarch butterflies, to agriculturally realistic levels of clothianidin, a widely used neonicotinoid insecticide. We tested whether this treatment influenced the number of eggs laid and larval survival over 2years. Milkweeds were transplanted into 60 experimental plots alongside a corn crop planted with a clothianidin seed coat and 60 control plots alongside an untreated corn crop. The number of eggs, larvae at each stage (first to fifth instar), and the presence of other arthropods were recorded weekly from June to the end of August and survival from egg to fifth instar was estimated using a Bayesian state-space statistical model. We counted more eggs in treated plots compared to control plots, suggesting a preference for treated milkweed. The number of plots with arthropods did not differ between treatments, but within treated plots, there was a greater decrease in the number of arthropods throughout the season. There was no evidence that monarchs selected plots with fewer arthropods for oviposition. Larval survival was lower in clothianidin-treated plots compared to control plots. Our results suggest milkweed near clothianidin-treated crops can reduce larval survival of monarch butterflies. While we provide some evidence that clothianidin could also act as an ecological trap for this species, further work is needed to identify additional components of fitness, including individual egg-laying rates and survival beyond the pupal stage. Our findings add to a growing body of evidence that neonicotinoids can negatively affect non-target organisms. ​.

Assessing movement patterns using Bayesian state space models on Lake Winnipeg walleye

Acoustic telemetry systems technology is useful for studying fish movement patterns and habitat use; however, the data generated from omnidirectional acoustic receivers are prone to large observation errors because the tagged animal can be anywhere in the detection range of the receiver. In this study, we used the Bayesian state space modeling (SSM) approach and different smoothing methods including kernel smoothing and cross-validated local polynomial regression to reconstruct fish movement paths of walleye (Sander vitreus) using data obtained from a telemetry receiver grid in Lake Winnipeg, Manitoba, Canada. Using the SSM approach, we obtained more realistic movement paths, compared with the smoothing methods. In addition, we have highlighted the advantages of the SSM approach to estimate undetected movement paths, over simple smoothing techniques, by comparing ecological metrics such as path length and tortuosity between different reconstruction approaches. Reconstructed paths could be useful in making effective fishery management decisions on Lake Winnipeg in the future by providing information on how walleye move and distribute in Lake Winnipeg over space and time.

Increased Hippocampal Excitability and Altered Learning Dynamics Mediate Cognitive Mapping Deficits in Human Aging.

Learning the spatial layout of a novel environment is associated with dynamic activity changes in the hippocampus and in medial parietal areas. With advancing age, the ability to learn spatial environments deteriorates substantially but the underlying neural mechanisms are not well understood. Here, we report findings from a behavioral and a fMRI experiment where healthy human older and younger adults of either sex performed a spatial learning task in a photorealistic virtual environment (VE). We modeled individual learning states using a Bayesian state-space model and found that activity in retrosplenial cortex (RSC)/parieto-occipital sulcus (POS) and anterior hippocampus did not change systematically as a function learning in older compared with younger adults across repeated episodes in the environment. Moreover, effective connectivity analyses revealed that the age-related learning deficits were linked to an increase in hippocampal excitability. Together, these results provide novel insights into how human aging affects computations in the brain's navigation system, highlighting the critical role of the hippocampus.SIGNIFICANCE STATEMENT Key structures of the brain's navigation circuit are particularly vulnerable to the deleterious consequences of aging, and declines in spatial navigation are among the earliest indicators for a progression from healthy aging to neurodegenerative diseases. Our study is among the first to provide a mechanistic account about how physiological changes in the aging brain affect the formation of spatial knowledge. We show that neural activity in the aging hippocampus and medial parietal areas is decoupled from individual learning states across repeated episodes in a novel spatial environment. Importantly, we find that increased excitability of the anterior hippocampus might constitute a potential neural mechanism for cognitive mapping deficits in old age.

Using long-term data for a reintroduced population to empirically estimate future consequences of inbreeding.

Inbreeding depression is an important long-term threat to reintroduced populations. However, the strength of inbreeding depression is difficult to estimate in wild populations because pedigree data are inevitably incomplete and because good data are needed on survival and reproduction. Predicting future population consequences is especially difficult because this also requires projecting future inbreeding levels and their impacts on long-term population dynamics, which are subject to many uncertainties. We illustrate how such projections can be derived through Bayesian state-space modeling methods based on a 26-year data set for North Island Robins (Petroica longipes) reintroduced to Tiritiri Matangi Island in 1992. We used pedigree data to model increases in the average inbreeding level (F) over time based on kinship of possible breeding pairs and to estimate empirically Ne /N (effective/census population size). We used multiple imputation to model the unknown components of inbreeding coefficients, which allowed us to estimate effects of inbreeding on survival for all 1458 birds in the data set while modeling density dependence and environmental stochasticity. This modeling indicated that inbreeding reduced juvenile survival (1.83 lethal equivalents [SE 0.81]) and may have reduced subsequent adult survival (0.44 lethal equivalents [0.81]) but had no apparent effect on numbers of fledglings produced. Average inbreeding level increased to 0.10 (SE 0.001) as the population grew from 33 (0.3) to 160 (6) individuals over the 25 years, giving a ratio of 0.56 (0.01). Based on a model that also incorporated habitat regeneration, the population was projected to reach a maximum of 331-1144 birds (median 726) in 2130, then to begin a slow decline. Without inbreeding, the population would be expected stabilize at 887-1465 birds (median 1131). Such analysis, therefore, makes it possible to empirically derive the information needed for rational decisions about inbreeding management while accounting for multiple sources of uncertainty.

Puerto Rico plain pigeon, scaly-naped pigeon and red-tailed hawk: population dynamics and association patterns before and after hurricanes

Since the 1980s, 3 major hurricanes have made landfall on Puerto Rico: Hugo in September 1989 (Saffir-Simpson scale, category 4), Georges in September 1998 (category 3) and María in September 2017 (category 4). María was the most devastating hurricane since the 3 major hurricanes that occurred in 1899-�1932. Major hurricanes can cause severe abundance declines and population bottlenecks by decreasing survival and reproductive rates and increasing predation and competition for limited resources. In April to June 1986-2021, we used distance sampling to estimate abundance and monitor the population dynamics of the endangered Puerto Rico plain pigeonPatagioenas inornata wetmoreiand the abundant scaly-naped pigeonP.squamosaand red-tailed hawkButeo jamaicensis. Here, we fit a Bayesian state-space logistic model with distance sampling abundance estimates to generate posterior estimates of maximum population growth rate and population carrying capacity, and predict abundance in April to June 2020-2030. In addition, we usedN-mixture and 2-species models to assess association patterns in April to June 2015-2019. The scaly-naped pigeon and red-tailed hawk populations did not decline, or recovered faster from their declines than the plain pigeon population after the hurricanes. The association patterns between species were positive but variable for the 2 pigeon species and negative but variable for the plain pigeon and red-tailed hawk. At lowered abundance (i.e. mean ± SE estimatesN̂= 1043 ± 476 island-wide andN̂= 522 ± 157 at the centre of abundance in the east-central region in April to June 2018-2021), the plain pigeon may become extinct if another hurricane with the path and intensity of María makes landfall on the island during the current decade.

Effects of sea ice cover, temperature and predation on the stock dynamics of the key Arctic fish species polar cod Boreogadus saida

Climate change has large effects on population dynamics of fish species in high latitude ecosystems. Arctic fish stocks experience multiple pressures with changing abiotic living conditions and increased competition and predation from boreal species. However, there are many unknowns regarding how environmental change influences the dynamics of those populations. Here, we focused on the Barents Sea polar cod, a pan-Arctic zooplanktivorous key fish species physiologically and ecologically adapted to the presence of sea ice. We developed an age-resolved Bayesian state-space model of the dynamics of polar cod based on 30 yr of survey data (1986-2015). Using this model, we quantified how inter-annual changes in abundance were associated with abiotic variables (temperature and sea ice cover) and biotic variables (prey biomasses and a predation index). Using the model output, we used a hindcast scenario approach to investigate to which degree the observed variations in total population size were related to the abiotic or biotic variables. Our results showed that variation in abundance of young polar cod (ages 0 and 1) was best explained by abiotic variables while variation in the older age groups (ages 3 and 4) was best explained by predation. Hindcast scenarios showed that the abiotic variables had a more evident effect than predation on population dynamics, but none of the variables we considered could explain the drastic population decline observed in recent years. Our work shows the advantages of studying age-specific responses as a stepping stone to understand changes at the population level.

Assessment of 11 Exploited Fish and Invertebrate Populations in the Japan Sea Using the CMSY and BSM Methods

The catch-maximum sustainable yield (CMSY) method and a closely-related Bayesian state-space Schaefer surplus production model (BSM) were combined with published catch-per-unit-effort (CPUE) time series or spawning stock biomass (SSB) data to evaluate fisheries reference points for exploited resources of the Japan Sea. Eleven fish and invertebrate stocks were assessed; outcomes obtained through this analysis were the carrying capacity, biomass trajectory, maximum sustainable yield, and related parameters of each stock. Results showed that the stock of Japanese sandfish (Arctoscopus japonicus) was slightly overfished; the stocks of sohachi (Cleisthenes pinetorum), flathead flounder (Hippoglossoides dubius), bastard halibut (Paralichthys olivaceus) and snow crab (Chionoecetes opilio) were overfished; and the stocks of shotted halibut (Eopsetta grigorjewi), yellow striped flounder (Pseudopleuronectes herzensteini), red seabream (Pagrus major), Alaska pollock (Gadus chalcogrammus) and deep-sea smelt (Glossanodon semifasciatus) were grossly overfished; only Alaskan pink shrimp (Pandalus eous) was in a good condition. These results are consistent with the few previous studies on the status of fish species around Japan, where overfishing is becoming increasingly apparent. These assessments provide a basis for guiding the use of fishery resources in the Japan Sea.

Assessment and Management of Small Yellow Croaker (Larimichthys polyactis) Stocks in South Korea

We aimed to determine the appropriate annual total allowable catch (TAC) levels for the small yellow croaker (Larimichthys polyactis). A Bayesian state-space model was used to assess the species stock. This model has been widely used after research confirmed its reliability over other models. However, setting prior distributions for analyzing this model remains controversial. Therefore, a sensitivity analysis was conducted using the model with different prior distributions and biomass growth functions. Informative and non-informative prior distributions were compared using Schaefer and Fox growth functions. Considering the results of the sensitivity analysis, the assumption of inverse-gamma prior distribution of K, a non-informative distribution, with the Fox function could yield relatively superior estimates than those obtained from other assumptions. Moreover, changing the growth function could have a greater effect on the fitness of the model estimates than changing prior distribution. Therefore, future fishery stock analyses based on this model should consider the effectiveness of various growth functions in addition to the sensitivity analysis for prior distributions. Furthermore, the biomass of small yellow croaker will decrease if the catch increases by 10%. Therefore, the annual TAC levels should be set below the maximum sustainable yield (21,301 tons) for effective small yellow croaker stock management.

Migratory and diurnal activity of North Atlantic killer whales (Orcinus orca) off northern Norway

Assessing the migratory behaviour of individual and groups of animals is key to understand the function of migration, its evolution, and how it is affected by environment and human activities. In the eastern North Atlantic, killer whales (Orcinus orca) presumably track herring stocks as they migrate between across the region. However, the detailed migratory and foraging behaviour of eastern North Atlantic killer whales is poorly understood. We report on the behaviour of 15 adult male killer whales equipped with Argos satellite transmitters during the winter of 2015–2016 along the coast of Troms, northern Norway. The animals were tracked for 8–104 days (mean: 41 days), during which they migrated 302–7608 Km (mean: 2646 Km). The observed movement of killer whales south to 64.2°N along the Norwegian coast following NSS-herring to their spawning grounds is in agreement with previous studies. However, our study is the first to also document northern migration of three of the Norwegian killer whales into the Barents Sea region towards Novaya Zemlya Island about 900 km from the Norwegian coast approaching 77.0°N. Importantly, using a Bayesian state-space model, we offer new insights on killer whale searching and transit movements, as well as diurnal patterns in swimming speed, preferred foraging habitat and feeding behaviour. The 15 tagged killer whales spend 75.0% of the time in an area restricted search (ARS) mode (range: 55.2–95.2%), 3.9% of the time in a transit mode (range: 0.0–16.1%) and 21.1% (range: 4.8–36.3%) in uncertain mode. The restricted search behaviour peaked at the end of January and beginning of February, after which the killer whales gradually performing transit behaviour as they followed the migrating herring out of the region, or shifted to other prey items.

Nonlinearity in interspecific interactions in response to climate change: Cod and haddock as an example.

Climate change has profound ecological effects, yet our understanding of how trophic interactions among species are affected by climate change is still patchy. The sympatric Atlantic haddock and cod are co-occurring across the North Atlantic. They compete for food at younger stages and thereafter the former is preyed by the latter. Climate change might affect the interaction and coexistence of these two species. Particularly, the increase in sea temperature (ST) has been shown to affect distribution, population growth and trophic interactions in marine systems. We used 33-year long time series of haddock and cod abundances estimates from two data sources (acoustic and trawl survey) to analyse the dynamic effect of climate on the coexistence of these two sympatric species in the Arcto-Boreal Barents Sea. Using a Bayesian state-space threshold model, we demonstrated that long-term climate variation, as expressed by changes of ST, affected species demography through different influences on density-independent processes. The interaction between cod and haddock has shifted in the last two decades due to an increase in ST, altering the equilibrium abundances and the dynamics of the system. During warm years (ST over ca. 4°C), the increase in the cod abundance negatively affected haddock abundance while it did not during cold years. This change in interactions therefore changed the equilibrium population size with a higher population size during warm years. Our analyses show that long-term climate change in the Arcto-Boreal system can generate differences in the equilibrium conditions of species assemblages.

SsMousetrack—Analysing Computerized Tracking Data via Bayesian State-Space Models in R

Recent technological advances have provided new settings to enhance individual-based data collection and computerized-tracking data have became common in many behavioral and social research. By adopting instantaneous tracking devices such as computer-mouse, wii, and joysticks, such data provide new insights for analysing the dynamic unfolding of response process. ssMousetrack is a R package for modeling and analysing computerized-tracking data by means of a Bayesian state-space approach. The package provides a set of functions to prepare data, fit the model, and assess results via simple diagnostic checks. This paper describes the package and illustrates how it can be used to model and analyse computerized-tracking data. A case study is also included to show the use of the package in empirical case studies.