Particle Backtracking Improves Breeding Subpopulation Discrimination and Natal-Source Identification in Mixed Populations

We provide a novel method to improve the use of natural tagging approaches for subpopulation discrimination and source-origin identification in aquatic and terrestrial animals with a passive dispersive phase. Our method integrates observed site-referenced biological information on individuals in mixed populations with a particle-tracking model to retrace likely dispersal histories prior to capture (i.e., particle backtracking). To illustrate and test our approach, we focus on western Lake Erie\u27s yellow perch (Perca flavescens) population during 2006-2007, using microsatellite DNA and otolith microchemistry from larvae and juveniles as natural tags. Particle backtracking showed that not all larvae collected near a presumed hatching location may have originated there, owing to passive drift during the larval stage that was influenced by strong river-and wind-driven water circulation. Re-assigning larvae to their most probable hatching site (based on probabilistic dispersal trajectories from the particle backtracking model) improved the use of genetics and otolith microchemistry to discriminate among local breeding subpopulations. This enhancement, in turn, altered (and likely improved) the estimated contributions of each breeding subpopulation to the mixed population of juvenile recruits. Our findings indicate that particle backtracking can complement existing tools used to identify the origin of individuals in mixed populations, especially in flow-dominated systems

Forecasting the combined effects of anticipated climate change and agricultural conservation practices on fish recruitment dynamics in Lake Erie

Many aquatic ecosystems are experiencing multiple anthropogenic stressors that threaten their ability to support ecologically and economically important fish species. Two of the most ubiquitous stressors are climate change and non- point source nutrient pollution.Agricultural conservation practices (ACPs, i.e. farming practices that reduce runoff, prevent erosion, and curb excessive nutrient loading) offer a potential means to mitigate the negative effects of non- point source pollution on fish populations. However, our understanding of how ACP implementation amidst a changing climate will affect fish production in large ecosystems that receive substantial upstream sediment and nutrient inputs remains incomplete.Towards this end, we explored how anticipated climate change and the implementation of realistic ACPs might alter the recruitment dynamics of three fish populations (native walleye Sander vitreus and yellow perch Perca flavescens and invasive white perch Morone americana) in the highly productive, dynamic west basin of Lake Erie. We projected future (2020- 2065) recruitment under different combinations of anticipated climate change (n = 2 levels) and ACP implementation (n = 4 levels) in the western Lake Erie catchment using predictive biological models driven by forecasted winter severity, spring warming rate, and Maumee River total phosphorus loads that were generated from linked climate, catchment- hydrology, and agricultural- practice- simulation models.In general, our models projected reduced walleye and yellow perch recruitment whereas invasive white perch recruitment was projected to remain stable or increase relative to the recent past. Our modelling also suggests the potential for trade- offs, as ACP implementation was projected to reduce yellow perch recruitment with anticipated climate change.Overall, our study presents a useful modelling framework to forecast fish recruitment in Lake Erie and elsewhere, as well as offering projections and new avenues of research that could help resource management agencies and policy- makers develop adaptive and resilient management strategies in the face of anticipated climate and land- management change.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156436/2/fwb13515.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156436/1/fwb13515_am.pd

Enumeration of islets by nuclei counting and light microscopic analysis

Author Manuscript 2011 May 1.Islet enumeration in impure preparations by conventional dithizone staining and visual counting is inaccurate and operator dependent. We examined nuclei counting for measuring the total number of cells in islet preparations, and we combined it with morphological analysis by light microscopy (LM) for estimating the volume fraction of islets in impure preparations. Cells and islets were disrupted with lysis solution and shear, and accuracy of counting successively diluted nuclei suspensions was verified with (1) visual counting in a hemocytometer after staining with crystal violet, and automatic counting by (2) aperture electrical resistance measurement and (3) flow cytometer measurement after staining with 7-aminoactinomycin-D. DNA content averaged 6.5 and 6.9 pg of DNA per cell for rat and human islets, respectively, in agreement with literature estimates. With pure rat islet preparations, precision improved with increasing counts, and samples with about greater than or equal to 160 islets provided a coefficient of variation of about 6%. Aliquots of human islet preparations were processed for LM analysis by stereological point counting. Total nuclei counts and islet volume fraction from LM analysis were combined to obtain the number of islet equivalents (IEs). Total number of IE by the standard method of dithizone staining/manual counting was overestimated by about 90% compared with LM/nuclei counting for 12 freshly isolated human islet research preparations. Nuclei counting combined with islet volume fraction measurements from LM is a novel method for achieving accurate islet enumeration.National Institutes of Health (U.S.) (Grant NCRR ICR U4Z 16606)National Institutes of Health (U.S.) (Grant R01-DK063108-01A1)National Institutes of Health (U.S.) (Grant NCRR ICR U42 RR0023244-01)Joslin Diabetes and Endocrinology Research Center (Grant DK36836)Diabetes Research & Wellness FoundationJuvenile Diabetes Research Foundation International (Islet Transplantation, Harvard Medical School

Eutrophication, water quality, and fisheries: a wicked management problem with insights from a century of change in Lake Erie

Human-driven nutrient inputs into aquatic ecosystems must be managed to preserve biodiversity and to ensure that valued fishery and water quality services are not compromised by hypoxia and harmful algal blooms. Aiming for nutrient inputs that achieve an intermediate level of ecosystem productivity is expected to provide both high fish yield and good water quality. However, we argue that such an intermediate “optimum” may not exist for many aquatic ecosystems that support multiple fisheries with differing tolerances to eutrophication and that must provide multiple water quality services. We further support this argument with an empirical case study of nearly a century (1915–2011) of change in the productivity of Lake Erie and its lake whitefish ( Coregonus clupeaformis ), walleye ( Sander vitreus ), and yellow perch ( Perca flavescens ) fisheries. We discuss and show how the harvest of each fishery has been historically maximized at different levels of ecosystem productivity. Additionally, we examine how anticipated management efforts to improve water quality by reducing nutrient inputs (i.e., oligotrophication) may favor certain fisheries over others, resulting in no single optimal range of nutrient inputs that achieves all valued fishery and water quality objectives. Our synthesis and case study illustrate how the need to balance multiple services in aquatic ecosystems can create a wicked management problem with inevitable trade-offs. To navigate these trade-offs, we recommend the use of ecosystem-based management approaches, which can help decision makers identify and resolve complex trade-offs by facilitating cooperative research and communication among water quality regulators, fisheries managers, and end users

Larval dispersal underlies demographically important intersystem connectivity in a Great Lakes yellow perch (Perca flavescens) population

Ability to quantify connectivity among spawning subpopulations and their relative contribution of recruits to the broader population is a critical fisheries management need. By combining microsatellite and age information from larval yellow perch (Perca flavescens) collected in the Lake St. Clair – Detroit River system (SC-DRS) and western Lake Erie with a hydrodynamic backtracking approach, we quantified subpopulation structure, connectivity, and contributions of recruits to the juvenile stage in western Lake Erie during 2006–2007. After finding weak (yet stable) genetic structure between the SC-DRS and two western Lake Erie subpopulations, microsatellites also revealed measurable recruitment of SC-DRS larvae to the juvenile stage in western Lake Erie (17%–21% during 2006–2007). Consideration of precollection larval dispersal trajectories, using hydrodynamic backtracking, increased estimated contributions to 65% in 2006 and 57% in 2007. Our findings highlight the value of complementing subpopulation discrimination methods with hydrodynamic predictions of larval dispersal by revealing the SC-DRS as a source of recruits to western Lake Erie and also showing that connectivity through larval dispersal can affect the structure and dynamics of large lake fish populations

Predictors of regional nodal disease in patients with thin melanomas

BACKGROUNDMost melanoma patients present with thin (0, vertical growth phase (VGP), male sex, and ulceration were statistically significant predictors of RND. Patients at the highest risk according to a classification tree analysis (VGP and MR>0) had an RND rate of 11.9%. The regression model developed predicted well the SLN status in the validation sample.CONCLUSIONSInvestigation of a large pre-SLN population identified MR>0, ulceration, VGP, and male sex as independently predictive of RND in patients with thin melanomas. These factors may help to identify subgroups of these patients that have clinically significant risks of SLN positivity

2006collectionsites

Collection site information for larval yellow perch during 200

Data from: Particle backtracking improves breeding subpopulation discrimination and natal-source identification in mixed populations

We provide a novel method to improve the use of natural tagging approaches for subpopulation discrimination and source-origin identification in aquatic and terrestrial animals with a passive dispersive phase. Our method integrates observed site-referenced biological information on individuals in mixed populations with a particle-tracking model to retrace likely dispersal histories prior to capture (i.e., particle backtracking). To illustrate and test our approach, we focus on western Lake Erie’s yellow perch (Perca flavescens) population during 2006–2007, using microsatellite DNA and otolith microchemistry from larvae and juveniles as natural tags. Particle backtracking showed that not all larvae collected near a presumed hatching location may have originated there, owing to passive drift during the larval stage that was influenced by strong river- and wind-driven water circulation. Re-assigning larvae to their most probable hatching site (based on probabilistic dispersal trajectories from the particle backtracking model) improved the use of genetics and otolith microchemistry to discriminate among local breeding subpopulations. This enhancement, in turn, altered (and likely improved) the estimated contributions of each breeding subpopulation to the mixed population of juvenile recruits. Our findings indicate that particle backtracking can complement existing tools used to identify the origin of individuals in mixed populations, especially in flow-dominated systems