Browsing by Author "Jiao, Yan"

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    Amphibian and reptile conservation in a changing environment: Case studies from the southeastern United States
    Chandler, Houston Cawthorn (Virginia Tech, 2023-05-22)
    The southeastern United States is a global biodiversity hotspot but has experienced severe declines of natural ecosystems. The southeast is currently facing widespread change, particularly from an increasing human population and climate change, that is likely to impact all remaining natural areas to some degree. In this work, I examine some of the challenges currently facing imperiled species of reptiles and amphibians in this region. The work is focused on two species, the Reticulated Flatwoods Salamander (Ambystoma bishopi) and the Eastern Indigo Snake (Drymarchon couperi) both of which are listed on the U.S. Endangered Species List. Chapter 1 used Light Detection and Ranging (LiDAR) data to measure wetland bathymetry (basin shape) in flatwoods salamander breeding wetlands. Bathymetry data were used to construct stage–area relationships for each wetland, and a history of water level monitoring data were applied to these relationships to build multi-year time series of flooded area metrics. These metrics were then combined with an assessment of vegetation characteristics to map potentially suitable habitat for flatwoods salamander breeding within each wetland. Chapter 2 focused on flatwoods salamander phenology (the timing of life history events) in response to climate change. I quantified flatwoods salamander movements into and out of breeding wetlands over a 10-year period (2010–2020), identifying temperature and precipitation patterns that were conducive to salamander movements. I then used future climate projections to forecast movement opportunities for flatwoods salamander from 2030–2099 and used an existing hydrologic model built on the same climate data to understand how phenology may interact with hydrology. Overall, only a small number of years are likely to have an ideal intersection of phenology and hydrology as has been observed during recent breeding seasons. Chapter 3 described the construction of a stochastic Integral Projection Model for flatwoods salamanders. I integrated the projections from Chapter 2 with the population model to estimate the viability of two flatwoods salamander populations from 2030–2099 under multiple climate change scenarios. The results indicated that approximately half of the examined scenarios resulted in a high probability (>0.5) of extinction when considering both wetland hydrology and salamander phenology. In Chapter 4, I described the creation of a stochastic Integral Projection Model for indigo snakes. I then demonstrated the utility of this model by examining the effects of initial population size, road density, and removal of individuals to support a captive colony on indigo snake populations. I found that high road densities and high collection rates would likely lead to population declines, although the rate of declines and extinction risk varied across scenarios. Taken together, these projects highlight some of the challenges currently facing herpetofauna in the southeastern United States, demonstrate the difficulty in conserving these often-overlooked species, and provide useful tools for ongoing conservation efforts focusing on these two imperiled species.
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    Assessing predictive performance and transferability of species distribution models for freshwater fish in the United States
    Huang, Jian (Virginia Tech, 2015-05-27)
    Rigorous modeling of the spatial species distributions is critical in biogeography, conservation, resource management, and assessment of climate change. The goal of chapter 2 of this dissertation was to evaluate the potential of using historical samples to develop high-resolution species distribution models (SDMs) of stream fishes of the United States. I explored the spatial transferability and temporal transferability of stream–fish distribution models in chapter 3 and chapter 4 respectively. Chapter 2 showed that the discrimination power of SDMs for 76 non-game fish species depended on data quality, species' rarity, statistical modeling technique, and incorporation of spatial autocorrelation. The area under the Receiver-Operating-Characteristic curve (AUC) in the cross validation tended to be higher in the logistic regression and boosted regression trees (BRT) than the presence-only MaxEnt models. AUC in the cross validation was also higher for species with large geographic ranges and small local populations. Species prevalence affected discrimination power in the model training but not in the validation. In chapter 3, spatial transferability of SDMs was low for over 70% of the 21 species examined. Only 24% of logistic regression, 12% of BRT, and 16% of MaxEnt had AUC > 0.6 in the spatial transfers. Friedman's rank sum test showed that there was no significant difference in the performance of the three modeling techniques. Spatial transferability could be improved by using spatial logistic regression under Lasso regularization in the training of SDMs and by matching the range and location of predictor variables between training and transfer regions. In chapter 4, testing of temporal SDM transfer on independent samples resulted in discrimination power of the moderate to good range, with AUC > 0.6 for 80% of species in all three types of models. Most cool water species had good temporal transferability. However, biases and misspecified spread occurred frequently in the temporal model transfers. To reduce under- or over-estimation bias, I suggest rescaling the predicted probability of species presence to ordinal ranks. To mitigate inappropriate spread of predictions in the climate change scenarios, I recommended to use large training datasets with good coverage of environmental gradients, and fine-tune predictor variables with regularization and cross validation.
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    Bayesian hierarchical approaches to analyze spatiotemporal dynamics of fish populations
    Bi, Rujia (Virginia Tech, 2020-09-03)
    The study of spatiotemporal dynamics of fish populations is important for both stock assessment and fishery management. I explored the impacts of environmental and anthropogenic factors on spatiotemporal patterns of fish populations, and contributed to stock assessment and management by incorporating the inherent spatial structure. Hierarchical models were developed to specify spatial and temporal variations, and Bayesian methods were adopted to fit the models. Yellow perch (Perca flavescens) is one of the most important commercial and recreational fisheries in Lake Erie, which is currently managed using four management units (MUs), with each assessed by a spatially-independent stock-specific assessment model. The current spatially-independent stock-specific assessment assumes that movement of yellow perch among MUs in Lake Erie is statistically negligible and biologically insignificant. I investigated whether the assumption is violated and the effect this assumption has on assessment. I first explored the spatiotemporal patterns of yellow perch abundance in Lake Erie based on data from a 27-year gillnet survey, and analyzed the impacts of environmental factors on spatiotemporal dynamics of the population. I found that yellow perch relative biomass index displayed clear temporal variation and spatial heterogeneity, however the two middle MUs displayed spatial similarities. I then developed a state-space model based on a 7-year tag-recovery data to explore movements of yellow perch among MUs, and performed a simulation analysis to evaluate the impacts of sample size on movement estimates. The results suggested substantial movement between the two stocks in the central basin, and the accuracy and precision of movement estimates increased with increasing sample size. These results demonstrate that the assumption on movements among MUs is violated, and it is necessary to incorporate regional connectivity into stock assessment. I thus developed a tag-integrated multi-region model to incorporate movements into a spatial stock assessment by integrating the tag-recovery data with 45-years of fisheries data. I then compared population projections such as recruitment and abundance derived from the tag-integrated multi-region model and the current spatial-independent stock-specific assessment model to detect the influence of hypotheses on with/without movements among MUs. Differences between the population projections from the two models suggested that the integration of regional stock dynamics has significant influence on stock estimates. American Shad (Alosa sapidissima), Hickory Shad (A. mediocris) and river herrings, including Alewife (A. pseudoharengus) and Blueback Herring (A. aestivalis), are anadromous pelagic fishes that spend most of the annual cycle at sea and enter coastal rivers in spring to spawn. Alosa fisheries were once one of the most valuable along the Atlantic coast, but have declined in recent decades due to pollution, overfishing and dam construction. Management actions have been implemented to restore the populations, and stocks in different river systems have displayed different recovery trends. I developed a Bayesian hierarchical spatiotemporal model to identify the population trends of these species among rivers in the Chesapeake Bay basin and to identify environmental and anthropogenic factors influencing their distribution and abundance. The results demonstrated river-specific heterogeneity of the spatiotemporal dynamics of these species and indicated the river-specific impacts of multiple factors including water temperature, river flow, chlorophyll a concentration and total phosphorus concentration on their population dynamics. Given the importance of these two case studies, analyses to diagnose the factors influencing population dynamics and to develop models to consider spatial complexity are highly valuable to practical fisheries management. Models incorporating spatiotemporal variation describe population dynamics more accurately, improve the accuracy of stock assessments, and would provide better recommendations for management purposes.
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    Behavior and population dynamics of grass carp incrementally stocked for biological control
    Stich, Daniel Stephen (Virginia Tech, 2011-06-10)
    Grass carp Ctenopharyngodon idella have been stocked throughout the world due to their utility as a biological control. In the United States, the species has been used to successfully control invasive, aquatic weeds such as hydrilla Hydrilla verticillata. Despite the large body of research surrounding the use of grass carp, few studies have demonstrated widely applicable methods for evaluating the success of weed control based on grass carp behavior and population dynamics. Classic methods of biological control using grass carp often rely on a single, large stocking of fish. Few of these studies have demonstrated success in achieving intermediate levels of weed control. Managers would be better equipped to make decisions regarding stocking and maintenance grass carp populations with better information about behavior, survival, and population structure. Improved decision making could result in reduced cost and increased effectiveness of stocking. In order to examine current knowledge gaps for management, I investigated the movements and habitat use of grass carp, post-stocking survival, age-specific survival rates, and population dynamics of grass carp in Lake Gaston, North Carolina and Virginia. I characterized relationships between grass carp behavior and environmental factors using radio-telemetry. The average rate of movement for grass carp in Lake Gaston was about 137 m/d. Rapid dispersal after stocking was followed by long periods of no movement. However, when time after stocking was held constant in models of behavior, fish moved about 200 m/d more in the second year after stocking than in the first year, and were found closer to shore. On average, grass carp were found about 40 m from shore in about 2.5-3.5 m of water, although mean depth of water at grass carp locations varied seasonally, being shallowest in summer and deepest in winter. Although depth of water at grass carp locations did not vary by stocking location, Grass carp were found closer to shorelines in the upper reservoir than in the lower reservoir. I found significant relationships between grass carp behavior and hydrological processes such as lake elevation and dam releases in the reservoir, as well as with other environmental factors such as water temperature, photoperiod, and weather conditions. The results of this study should be useful in better understanding how behavior can affect management decisions. Specifically, grass carp behavior appears to change with age and environmental conditions within large reservoir systems. Future research should focus more closely on the effects of large-scale flow dynamics on grass carp behavior. I estimated age-1 survival of grass carp from mark-recapture models designed for radio-tagged animals, and characterized relationships between age-1 survival and factors under the control of management, such as stocking locations and size at stocking. . According to the most-plausible model developed in this study, survival of age-1 grass carp in Lake Gaston varied throughout the year, and the probability of an individual grass carp surviving to the end of its first year (±SE) was 0.57(±0.10). According to the second-most-plausible model developed in this study, grass carp survival varied between stocking locations, and was twice as high in the upper reservoir (0.87±0.09) than in the lower reservoir (0.43±0.11). The differences in survival between stocking locations suggest that the cost-effectiveness of grass carp stocking could be improved by focusing stocking efforts in specific regions of Lake Gaston. Furthermore, none of the models developed in this study that incorporated the effects of size (length and weight) or condition factor accounted for a meaningful amount of the total model weights. These results suggest that costs of grass carp stocking could be reduced in Lake Gaston by using a smaller minimum size (352 mm, TL) than is commonly referred to in the literature (450 mm, TL). I used grass carp collected by bowfishers in Lake Gaston to characterize the age, growth, and survival of grass carp in the system. From these data, I characterized relationships between fish population dynamics and annual hydrilla coverage. Grass carp collected from Lake Gaston ranged in age 1-16 years. Growth of grass carp in Gaston was described by the von Bertalanffy growth function as Lt = 1297(1-e -0.1352 (t+1.52)). I estimated mortality from the von Bertalanffy growth parameters using methods based on growth, temperature, and age; and with each mortality estimate I estimated population size and standing biomass of grass carp. Use of age-specific mortality rates produced lower estimates of grass carp numbers and standing biomass in Lake Gaston than did the use of a single, instantaneous mortality rate for all ages. I determined that growth of grass carp slowed considerably after the fourth year and that slowed growth, in combination with changes in mortality, resulted in a decrease in the amount of hydrilla controlled by a given cohort after four years in Lake Gaston. This phenomenon resulted in an approximately linear relationship between the biomass of grass carp at year i and hectares of hydrilla at year i+3. Based on this relationship, I predicted that the biomass of grass carp necessary to reduce hydrilla coverage to the target level of 120 ha in Lake Gaston is about 91,184 kg (±38,146 kg) and that the current biomass of grass carp in Lake Gaston is about 108,073 kg (±3,609 kg). I conclude that grass carp biomass is at or near levels that should reduce hydrilla coverage to 120 ha between 2013 and 2018. This research provides an effective means for synthesis of information that is critical to understanding sterile, triploid grass carp populations when assumptions of other methods cannot be met. The results of this study should be of immediate utility to hydrilla management efforts in Lake Gaston and other systems. Furthermore, the age-specific mortality rates developed in this study should be useful as starting values for grass carp management in similar systems.
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    Calibrating virtual population analysis for fisheries stock assessment
    Chen, Yong; Jiao, Yan; Sun, Chi-Lu; Chen, Xinjun (EDP SCIENCES, 2008-04)
    Virtual population analysis (VPA) is often used for assessing freshwater and marine fisheries resources. One important component in VPA is to calibrate abundance estimates with a time series of abundance indices. One of the commonly used calibration processes usually includes simultaneous estimation of cohort sizes across all ages and years. This reduces the flexibility of the model in accounting for age- and year-effects, in particular in the presence of an age- specific curvilinear relationship between abundance index and stock abundance. In this study, we compared this simultaneous method tuning approach with a stepwise approach which calibrates abundance age by age in tuning VPA. The simulation study suggests that the stepwise procedure tends to perform better with no obvious retrospective errors in the estimated stock biomass compared with the simultaneous method which tends to have large positive retrospective errors. In applying the stepwise procedure and simultaneous method to a cod fishery data set, we found large differences in the stock sizes estimated for the most recent year using these two methods, with the current stock size estimated using the stepwise method being substantially smaller than that estimated with the simultaneous method. Considering the likelihood of the presence of curvilinear relationship between abundance index and stock abundance, we conclude that the stepwise method yields more reliable results, and is less risk-prone in using VPA for fisheries stock assessment.
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    Characterizing early growth and reproduction of Blueline Tilefish (Caulolatilus microps) to inform stock assessments
    Low, Jonathan (Virginia Tech, 2024-05-21)
    Blueline Tilefish is a deepwater species that is found along the United States Atlantic coast and in the Gulf of Mexico. Fisheries for the species have developed in the past five decades, and large increases in landings from the mid-2000s to 2010s have raised management interest. During the most recent stock assessment, age reading difficulties found in the past persisted, and preferred age-structured models were not used. Additionally, maturity was estimated from a meta-analysis of other species with similar life histories. Research recommendations from independent peer reviewers thus included improving age determination as well as collection of small fish. We collaborated with charter fishermen to target small (< 400 mm total length [TL]) blueline tilefish. We also collaborated with scientists at South Carolina Department of Natural Resources (SCNDR) on histological reproductive phase coding and ageing of Blueline Tilefish otoliths. We optimized the information incorporated into sex ratio, reproduction, and growth analyses by merging datasets with SCDNR and Old Dominion University (ODU), and assessed first maturity to the increase immature sample size. Overall sex ratios exhibited a female bias, displaying statistically significant deviations from the expected 1:1 ratio in both the Southeast United States Atlantic (SEUS) and United States Mid-Atlantic (USMA) regions. All immature individuals collected measured below 400 mm. Our findings aligned with previously documented spawning seasons, which extend from April to October in the SEUS and from May to November in the USMA, and may extend to November in the SEUS. The spawning peak identified for the SEUS concurred with previous studies, and suggested October as a spawning peak in the USMA—later than previously described. Sex-specific gonadosomatic index analyses indicated no significant differences between regions. Age determination remained challenging, but the level of agreement in age estimates between the VT consensus and SCDNR readings resembled the highest value from previous studies. Evaluation based on AIC and BIC scores of weight-length relationships indicated potential regional differences and sexual dimorphism within both the SEUS and USMA regions. This sexual dimorphism was further supported by von Bertalanffy growth estimates, revealing L_∞ values of 574.7 and 630.1 mm TL and values of 0.22 and 0.24 for females and males, respectively. Analysis of AIC and BIC indicated sexual dimorphic growth. Length and age at 50% maturity estimates ranged from 283 to 357 mm TL and a few months to 3.7 years, respectively. Length at maturity models also indicated that most fish are mature around 400 to 500 mm, highlighting the importance of targeting smaller individuals to increase the sample size of immature fish. Differences in AIC and BIC scores for length and age at maturity models of three maturity scenarios were low (AIC and BIC < 2). We recommend continued investigation into blueline tilefish age determination, as well as targeted efforts to collect more immature blueline tilefish. Additionally, we propose the use of first maturity and data weighting for maturity estimation of this species.
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    Climate driven spatiotemporal variations in seabird bycatch hotspots and implications for seabird bycatch mitigation
    Bi, Rujia; Jiao, Yan; Browder, Joan A. (Nature Portfolio, 2021-10-19)
    Bycatch in fisheries is a major threat to many seabird species. Understanding and predicting spatiotemporal changes in seabird bycatch from fisheries might be the key to mitigation. Inter-annual spatiotemporal patterns are evident in seabird bycatch of the U.S. Atlantic pelagic longline fishery monitored by the National Marine Fisheries Service Pelagic Observer Program (POP) since 1992. A newly developed fast computing Bayesian approximation method provided the opportunity to use POP data to understand spatiotemporal patterns, including temporal changes in location of seabird bycatch hotspots. A Bayesian model was developed to capture the inherent spatiotemporal structure in seabird bycatch and reduce the bias caused by physical barriers such as coastlines. The model was applied to the logbook data to estimate seabird bycatch for each longline set, and the mid-Atlantic bight and northeast coast were the fishing areas with the highest fleet bycatch estimate. Inter-annual changes in predicted bycatch hotspots were correlated with Gulf Stream meanders, suggesting that predictable patterns in Gulf Stream meanders could enable advanced planning of fishing fleet schedules and areas of operation. The greater the Gulf Stream North Wall index, the more northerly the seabird bycatch hotspot two years later. A simulation study suggested that switching fishing fleets from the hindcasted actual bycatch hotspot to neighboring areas and/or different periods could be an efficient strategy to decrease seabird bycatch while largely maintaining fishers’ benefit.
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    A comparison between traditional and measurement-error growth models for weakfish Cynoscion regalis
    Hatch, Joshua M.; Jiao, Yan (PeerJ, 2016-09-21)
    Inferring growth for aquatic species is dependent upon accurate descriptions of age-length relationships, which may be degraded by measurement error in observed ages. Ageing error arises from biased and/or imprecise age determinations as a consequence of misinterpretation by readers or inability of ageing structures to accurately reflect true age. A Bayesian errors-in-variables (EIV) approach (i.e., measurement-error modeling) can account for ageing uncertainty during nonlinear growth curve estimation by allowing observed ages to be parametrically modeled as random deviates. Information on the latent age composition then comes from the specified prior distribution, which represents the true age structure of the sampled fish population. In this study, weakfish growth was modeled by means of traditional and measurement-error von Bertalanffy growth curves using otolith- or scale-estimated ages. Age determinations were assumed to be log-normally distributed, thereby incorporating multiplicative error with respect to ageing uncertainty. The prior distribution for true age was assumed to be uniformly distributed between ±4 of the observed age (yr) for each individual. Measurement-error growth models described weakfish that reached larger sizes but at slower rates, with median length-at-age being overestimated by traditional growth curves for the observed age range. In addition, measurement-error models produced slightly narrower credible intervals for parameters of the von Bertalanffy growth function, which may be an artifact of the specified prior distributions. Subjectivity is always apparent in the ageing of fishes and it is recommended that measurement-error growth models be used in conjunction with otolith-estimated ages to accurately capture the age-length relationship that is subsequently used in fisheries stock assessment and management.
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    Design and Model-based Approaches for Estimating Abundance of American Horseshoe Crab
    Wong, Chad Christopher (Virginia Tech, 2024-01-24)
    The American horseshoe crab (HSC), Limulus polyphemus, is one of four species of horseshoe crabs found throughout the world, and the only one found in North America. It is an economically and ecologically important species throughout its native range from Maine to the Yucatan Peninsula. Harvested for fertilizer and livestock feed in the 19th century, the species is now harvested as bait for whelk and eel fisheries, and for their blood by the biomedical industry. The Atlantic States Marine Fisheries Commission (ASMFC) started to formally manage HSC in 1998 with its Interstate Fisheries Management Plan (IFMP). Unique emphasis and harvest limits have been placed on the Delaware Bay stock, as it is commercially exploited and a critical food source for the threatened red knot, Calidris canutus rufa. Previously, estimates of relative and total abundance of HSC in the Delaware Bay area were based on a design-based approach using a stratified random sampling design. In Chapter 1 of this work, I developed hurdle models for each of the six HSC demographic groups to standardize catch-per-unit-effort (CPUE) and estimate relative abundance using a model-based approach. It was determined that while the two approaches resulted in mostly convergent estimates of relative abundance, external factors such as month, time-of-day, and average depth have major effects on the observed CPUE of all demographic groups. Chapter 2 involved the development of hurdle models for the three species of bycatch frequently caught in our trawls, channeled whelk (Busysotypus canaliculatus), knobbed whelk (Busycon carica), and summer flounder (Paralichthys dentatus). It was found that channeled whelk relative abundance has been at a historical low since 2016, while summer flounder has been at a consistent high. Recent estimates of knobbed whelk relative abundance have been less variable than previously seen, with estimates since 2016 being similar to those seen before 2012. These results provide the first estimates for whelk population trends in the mid-Atlantic region and add to the growing knowledge of summer flounder relative abundance in the area. In Chapter 3, I applied the hurdle models developed in Chapter 1 to estimate the total abundance of HSC in the Delaware Bay area. For this work, I developed two spatio-temporal variograms to estimate bottom temperature and bottom salinity at unmeasured cells per month in the time series. The results showed that night estimates of total abundance were consistently higher than daytime estimates, and estimates from September or November resulted in the highest estimated catch for all demographic groups. The results suggest that when comparing September model-based estimates at night to those of the design-based approach, nearly a third of all previous design-based estimates significantly underestimated the total abundance of HSC in the Delaware Bay area. This result suggests that the ASMFC can recommend increased harvest limits for mature individuals if that action aligns with the goals of their adaptive resource management (ARM) framework.
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    Detection of fish movement patterns across management unit boundaries using agestructured Bayesian hierarchical models with tag-recovery data
    Bi, Rujia; Zhou, Can; Jiao, Yan (PLOS, 2020-12-07)
    Tagging studies have been widely conducted to investigate the movement pattern of wild fish populations. In this study, we present a set of length-based, age-structured Bayesian hierarchical models to explore variabilities and uncertainties in modeling tag-recovery data. These models fully incorporate uncertainties in age classifications of tagged fish based on length and uncertainties in estimated population structure. Results of a tagging experiment conducted by the Ontario Ministry of Natural Resources and Forestry (OMNRF) on yellow perch in Lake Erie was analyzed as a case study. A total of 13,694 yellow perch were tagged with PIT tags from 2009 to 2015; 322 of these were recaptured in the Ontario commercial gillnet fishery and recorded by OMNRF personnel. Different movement configurations modeling the tag-recovery data were compared, and all configurations revealed that yellow perch individuals in the western basin (MU1) exhibited relatively strong site fidelity, and individuals from the central basin (MU2 and MU3) moved within this basin, but their movements to the western basin (MU1) appeared small. Model with random effects of year and age on movement had the best performance, indicating variations in movement of yellow perch across the lake among years and age classes. This kind of model is applicable to other tagging studies to explore temporal and age-class variations while incorporating uncertainties in age classification.
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    Dynamics and Role of Non-native Blue Catfish Ictalurus furcatus in Virginia’s Tidal Rivers
    Orth, Donald J.; Jiao, Yan; Schmitt, Joseph; Hilling, Corbin; Emmel, Jason; Fabrizio, Mary (Virginia Tech, 2017-12)
    This report summarizes progress on research on the population dynamics and trophic role of nonnative Blue Catfish Ictalurus furcatus in Virginia’s tidal rivers. The research has been organized in three parts. First, we quantify the diets of Blue Catfish in terms of relative importance of diet items across freshwater, oligohaline, and mesohaline zones of the James, Pamunkey, Mattaponi, and Rappahannock Rivers and examine factors related to variability in Blue Catfish diets. Second, we analyze demographic trends and population size in Blue Catfish based on commercial harvest (VMRC) and electrofishing catch-per-unit-effort (CPUE) surveys. Finally, we integrate our findings on diet and population biomass to derive estimates of consumption of major species of concern and examine what management strategies may be appropriate.
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    The Effects of Ageing Error on Stock Assessment for Weakfish Cynoscion regalis
    Hatch, Joshua M. (Virginia Tech, 2013-06-12)
    Inherent uncertainties in the stock assessment for weakfish have precluded accurate and consistent advice concerning the management of commercial and recreational fisheries. Error within ageing techniques, used to assess relative age frequencies within commercial and recreational harvest, has been cited as a potential source for uncertainty during assessments of the weakfish fishery. The implications for age-reading error on weakfish stock assessment were explored using measurement-error growth models (i.e. Chapter 1), ageing error matrices within a statistical catch-at-age framework (i.e. Chapter 2), and Monte Carlo simulations to gauge robustness of ignoring this type of uncertainty during fisheries stock assessment (i.e. Chapter 3). Measurement-error growth models typically resulted in weakfish that grew to reach larger sizes, but at slower rates, with median length-at-age being overestimated by traditional von Bertalanffy growth curves, at least for the observed age range. Measurement-error growth models allow for incorporation of ageing uncertainty during nonlinear growth curve estimation, as well as the ability to estimate the ageing error variance. Age-reading error was further considered during statistical catch-at-age analysis of the weakfish fishery, mainly through permutations of true catch-at-age via ageing error matrices constructed from estimates of the ageing error variance, thus reflecting changes in relative age compositions as a consequence of ageing uncertainty. As a result, absolute levels of key population parameters were influenced, but general trends in those parameters tended to be similar, with strong congruency across models as to weakfish stock dynamics in most recent years. Finally, Monte Carlo simulations showed that implications for age-reading error on weakfish stock assessment are varied, depending upon the direction and magnitude of the ageing uncertainty. However, relative trends of parameter estimates over time tended to be similar, resulting in proper allocation of weakfish stock status, regardless of the type of ageing error considered. Furthermore, assuming negligible ageing uncertainty within fishery-independent surveys appears reasonable, as simulations incorporating ageing error within indices of relative abundance showed similar patterns to situations that only considered observation noise.
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    The effects of life history strategy and uncertainty on a probability-based approach to managing the risk of overfishing
    Susko, Emily Clare (Virginia Tech, 2012-02-17)
    Recent U.S. legislation applies a precautionary approach to setting catch regulations in federal fisheries management. A transparent approach to complying with federal guidelines involves calculating the catch recommendation that corresponds to a specified probability, P*, of exceeding the "true" overfishing limit (OFL) located within an estimated distribution. The P* methodology aims to manage the risk of overfishing explicitly, but choice of P* alone does not provide sufficient information on all of the risks associated with a control rule—both the probability of overfishing and the severity of overfishing. Rather, the ramifications of P* choices depend on the amount of uncertainty in the stock assessment and on the life history of the species in question. To evaluate these effects on the risks associated with P* rules, my study simulated fishing three example species under three levels of uncertainty. Trends identified among example species were consistent with predictions from life history. Periodic strategists, which have highly variable recruitment, experienced probabilities of overfishing which exceeded P* and which increased in time. Equilibrium strategists showed more predictable risks of overfishing but may have less capacity to recover from depleted biomass levels. Differences in the size of the OFL distribution—representing differences in levels of uncertainty—led to mixed results depending on whether the distribution was biased or whether uncertainty was fully characterized. Lastly, because OFL distributions are themselves estimates and subject to uncertainty in their shape and size, lower P* values closer to the tails of the estimated distribution produced more variable resulting risks.
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    Environmental and anthropogenic influences on spatiotemporal dynamics of Alosa in Chesapeake Bay tributaries
    Bi, Rujia; Jiao, Yan; Weaver, L. Alan; Greenlee, Robert S.; McClair, Genine; Kipp, Jeff; Wilke, Kate; Haas, Carola A.; Smith, Eric P. (2021-06)
    American Shad (Alosa sapidissima), Hickory Shad (A. mediocris), and river herrings (Alewife A. pseudoharengus and Blueback Herring A. aestivalis) are anadromous pelagic fishes, which as adults spend most of the annual cycle at sea, but enter the coastal rivers in spring to spawn. Once as one of the most valuable fisheries along the Atlantic coast, Alosa populations have declined in recent decades and current populations are at historic lows. Various management actions have been conducted to restore the populations, and stocks in different river systems display different demographic trends. Demonstration of synthetic diagnostics on the factors impacting these populations is important to better conserve this species group. We developed a Bayesian hierarchical spatiotemporal model to identify the population trends of these species among rivers in the Chesapeake Bay based on results of surveys conducted by the Virginia Department of Game and Inland Fisheries and Maryland Department of Natural Resources and to identify environmental and anthropogenic factors influencing their distribution and abundance. The hierarchical model structure helped to diagnose river-specific population trends and impacts of surrounding factors, and decrease uncertainties in rivers with less samples available. The results demonstrate river-specific heterogeneity of spatiotemporal dynamics of these species and indicate river-specific impacts of multiple factors, including water temperature, river flow, chlorophyll a concentration, and total phosphorus concentration, on their population dynamics. Atlantic Multidecadal Oscillation and Gulf Stream meanders displayed significant influence on the inter-annual trends of Alosa species in rivers with more data available. The results would help to develop river- and species-specific management strategies to recover these species.
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    Estimability of natural mortality within a statistical catch-at-age model: a framework and simulation study based on Gulf of Mexico red snapper
    Vincent, Matthew Timothy (Virginia Tech, 2013-11-15)
    Estimation of natural mortality within statistical catch-at-age models has been relatively unsuccessful and is uncommon within stock assessments. The models I created estimated population-dynamics parameters, including natural mortality, through Metropolis-Hastings algorithms from Gulf of Mexico red-snapper Lutjanus campechanus data. I investigated the influences of assumptions regarding model configuration of natural mortality and selectivity-at-age parameters by comparing multiple models. The results of this study are preliminary due to parameter estimates being bounded by uniform priors and thus a potential lack of convergence to the posterior distribution. Estimation of a natural-mortality parameter at age 0 or a Lorenzen natural-mortality parameter could be confounded with selectivity-at-age-1 parameters for bycatch from the shrimp fisheries. The Lorenzen natural-mortality curve was calculated by dividing the parameter by red snapper length at age. An age-1 natural-mortality parameter might not be estimable with the currently available data. Values of the natural-mortality parameter for ages 2 and older appear to be slightly less influenced by assumptions regarding selectivity-at-age parameters. We conducted a simulation study to determine the accuracy and precision of natural-mortality estimation assuming the selectivity-at-age-1 parameter for bycatch from the shrimp fisheries equaled 1.0 and a Lorenzen natural-mortality curve. The simulation study indicated that initial abundance-at-age parameters may be inestimable within the current model and may influence other parameter estimates. The preliminary simulation results showed that the Lorenzen natural-mortality parameter was consistently slightly underestimated and apical-fishing-mortality parameters were considerably underestimated. The estimation of natural mortality within a statistical catch-at-age model for Gulf of Mexico red snapper has many caveats and requires additional investigation.
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    Evaluating spatial and temporal variability in growth and mortality for recreational fisheries with limited catch data
    Li, Yan; Wagner, Tyler K.; Jiao, Yan; Lorantas, Robert; Murphy, Cheryl A. (2018-09)
    Understanding the spatial and temporal variability in life-history traits among populations is essential for the management of recreational fisheries. However, valuable freshwater recreational fish species often suffer from a lack of catch information. In this study, we demonstrated the use of an approach to estimate the spatial and temporal variability in growth and mortality in the absence of catch data and apply the method to riverine smallmouth bass (Micropterus dolomieu) populations in Pennsylvania, USA. Our approach included a growth analysis and a length-based analysis that estimates mortality. Using a hierarchical Bayesian approach, we examined spatial variability in growth and mortality by assuming parameters vary spatially but remain constant over time and temporal variability by assuming parameters vary spatially and temporally. The estimated growth and mortality of smallmouth bass showed substantial variability over time and across rivers. We explored the relationships of the estimated growth and mortality with spring water temperature and spring flow. Growth rate was likely to be positively correlated with these two factors, while young mortality was likely to be positively correlated with spring flow. The spatially and temporally varying growth and mortality suggest that smallmouth bass populations across rivers may respond differently to management plans and disturbance such as environmental contamination and land-use change. The analytical approach can be extended to other freshwater recreational species that also lack of catch data. The approach could also be useful in developing population assessments with erroneous catch data or be used as a model sensitivity scenario to verify traditional models even when catch data are available.
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    The Evolutionary Effects of Fishing: Implications for Stock Management and Rebuilding
    Leaf, Robert Thomas (Virginia Tech, 2010-06-22)
    Recent empirical studies have demonstrated inter-generational morphological and life-history changes in fish stocks that have been impacted by size-selective harvest. Evolutionary processes in biological populations occur through differential survival and reproductive success based, in part, upon individual phenotypic variability. Fishing is a source of directional selection resulting in the directed removal of some phenotypes; however, many aspects of the evolutionary effects of fishing remain have yet to be described. In order to better understand the life-history and morphological changes that occur as a result of size-selective fishing, and their effect on fishery dynamics, I first determined the suitability of Japanese medaka (Oryzias latipes) for selection experiments. I performed selection experiments using Japanese medaka and report how morphology and life-history characteristics changed over multiple generations of selection. I then used these patterns of change in life-history and morphology to validate individual-based simulation candidate models to test general mechanisms of life-history relationships. Finally, I applied the individual-based simulation modeling approach in order to describe how biological and fishery characteristics change in a large, age-structured population exposed to size-selective fishing over multiple generations. I found that the Japanese medaka has attractive characteristics for biological investigation. The selection experiments indicated large changes in the age-atmaturity, including a nearly 50% decrease over four generations in the most intense sizeselective removal regimes. However, I did not observe significant changes in length-at-age or weight-at-age over the course of the experiment. Candidate simulation models were poor at predicting some aspects of the life-history characteristics of Japanese medaka. The simulation model to determine fishery characteristics predicted large decreases in yield and egg production as a result of decreases in length-at-age. Understanding the relationships of life-history characteristics and their role in determining population resilience is a step toward understanding the importance of evolutionary processes in fishery management.
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    Exploring spatial heterogeneity of CPUE year trend and nonstationarity in fisheries stock assessment, an example based on Atlantic Weakfish (Cynoscion regalis)
    Zhang, Yafei (Virginia Tech, 2016-02-03)
    Quantitative population dynamics modeling is needed to evaluate the stock status and fisheries management plans to provide robust model and management strategies. Atlantic Weakfish (Cynoscion regalis), one important commercial and recreational fish species along the west coast of Atlantic Ocean that was found to be declining in recent years, was selected as an example species. My study aimed to explore the possible spatial heterogeneity of CPUE (catch per unit effort) year trend based on three fishery independent surveys and explore the influence of nonstationary natural mortality on the fisheries management through a MSE (Management Strategy Evaluation) algorithm based on the Weakfish stock assessment results. Five models for catch rate standardization were constructed based on the NEAMAP (NorthEast Area Monitoring and Assessment Program) survey data and the ‘best' two models were selected based on the ability to capture nonlinearity and spatial autocorrelation. The selected models were then used to fit the other two survey data to compare the CPUE year trend of Weakfish. Obvious differences in distribution pattern of Weakfish along latitude and longitude were detected from these three surveys as well as the CPUE year trend. To test the influence of the model selection on the MSE, five stock-recruitment models and two forms of statistical catch-at-age models were used to evaluate the fishery management strategies. The current biomass-based reference point tends to be high if the true population dynamics have nonstationary natural mortality. A flexible biomass based reference point to match the nonstationary process is recommended for future fisheries management.
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    Exploring spatial nonstationary environmental effects on Yellow Perch distribution in Lake Erie
    Liu, Changdong; Liu, Junchao; Jiao, Yan; Tang, Yanli; Reid, Kevin B. (PeerJ, 2019-07-25)
    Background: Global regression models under an implicit assumption of spatial stationarity were commonly applied to estimate the environmental effects on aquatic species distribution. However, the relationships between species distribution and environmental variables may change among spatial locations, especially at large spatial scales with complicated habitat. Local regression models are appropriate supplementary tools to explore species-environment relationships at finer scales. Method: We applied geographically weighted regression (GWR) models on Yellow Perch in Lake Erie to estimate spatially-varying environmental effects on the presence probabilities of this species. Outputs from GWR were compared with those from generalized additive models (GAMs) in exploring the Yellow Perch distribution. Local regression coefficients from the GWR were mapped to visualize spatially-varying species-environment relationships. K-means cluster analyses based on the t-values of GWR local regression coefficients were used to characterize the distinct zones of ecological relationships. Results: Geographically weighted regression resulted in a significant improvement over the GAM in goodness-of-fit and accuracy of model prediction. Results from the GWR revealed the magnitude and direction of environmental effects on Yellow Perch distribution changed among spatial locations. Consistent species-environment relationships were found in the west and east basins for adults. The different kinds of species-environment relationships found in the central management unit (MU) implied the variation of relationships at a scale finer than the MU. Conclusions: This study draws attention to the importance of accounting for spatial nonstationarity in exploring species-environment relationships. The GWR results can provide support for identification of unique stocks and potential refinement of the current jurisdictional MU structure toward more ecologically relevant MUs for the sustainable management of Yellow Perch in Lake Erie.
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    Feeding Ecology of Invasive Catfishes in Chesapeake Bay Subestuaries
    Schmitt, Joseph Daniel (Virginia Tech, 2018-06-05)
    Blue Catfish Ictalurus furcatus are native to tributaries of the Mississippi River but are now invasive in several Atlantic slope drainages. This includes subestuaries of the Chesapeake Bay, where their feeding ecology and potential impact on native species was largely unknown. We collected stomach contents from 16,110 Blue Catfish at 698 sites in three large subestuaries of the Chesapeake Bay (James, York, Rappahannock rivers). Cumulative prey curves revealed that sample size was sufficient for diet description, though 1,000 – 1500 stomachs were needed per river. Blue Catfish are opportunistic generalists that feed on a broad array of plant and animal material. Logistic regression models reveal that Blue Catfish undergo significant ontogenetic diet shifts to piscivory at larger sizes (P<0.01) though the lengths at which these shifts occur varies by river system (500 – 900 mm total length; TL). Over 60% of Blue Catfish stomachs contained other invasive species, primarily Hydrilla verticillata and Asian clams Corbicula fluminea. Canonical Correspondence Analysis (CCA) revealed that salinity and season explained the most variation in Blue Catfish diet, while Generalized Additive Models (GAMs) demonstrated that there is considerable spatiotemporal and length-based variation in predation of species of concern. Species of concern include American Shad, American Eel, and river herring, which are imperiled, and blue crab, which support valuable fisheries in Chesapeake Bay. Predation of American Shad, American Eel, and river herring was rare (max predicted occurrence in Blue Catfish diets = 8%), while blue crab was much more common in the diet (max predicted occurrence =28%). Predation of American Shad and river herring peaks in freshwater areas in April, while predation of blue crab peaks in brackish areas in October. Predation of all species of concern is highest for large catfish (500 – 1000 mm TL). Field and laboratory-based estimates of consumption rate revealed that Blue Catfish feed at similar rates as Channel Catfish Ictalurus punctatus, and daily ration is estimated to be 2-5% bodyweight per day during warm temperatures, while peak feeding (maximum daily ration) can approach 10% bodyweight per day. While consumption of imperiled species is rare, Blue Catfish could still have negative impacts on these species due to dense catfish populations.