Travis O. Brenden

Quantitative Identification of Disturbance Thresholds in Support of Aquatic Resource Management

The identification of disturbance thresholds is important for many aspects of aquatic resource management, including the establishment of regulatory criteria and the identification of stream reference conditions. A number of quantitative or model-based approaches can be used to identify disturbance thresholds, including nonparametric deviance reduction (NDR), piecewise regression (PR), Bayesian changepoint (BCP), quantile piecewise constant (QPC), and quantile piecewise linear (QPL) approaches. These methods differ in their assumptions regarding the nature of the disturbance-response variable relationship, which can make selecting among the approaches difficult for those unfamiliar with the methods. We first provide an overview of each of the aforementioned approaches for identifying disturbance thresholds, including the types of data for which the approaches are intended. We then compare threshold estimates from each of these approaches to evaluate their robustness using both simulated and empirical datasets. We found that most of the approaches were accurate in estimating thresholds for datasets with drastic changes in responses variable at the disturbance threshold. Conversely, only the PR and QPL approaches performed well for datasets with conditional mean or upper boundary changes in response variables at the disturbance threshold. The most robust threshold identification approach appeared to be the QPL approach; this method provided relatively accurate threshold estimates for most of the evaluated datasets. Because accuracy of disturbance threshold estimates can be affected by a number of factors, we recommend that several steps be followed when attempting to identify disturbance thresholds. These steps include plotting and visually inspecting the disturbance-response data, hypothesizing what mechanisms likely generate the observed pattern in the disturbance-response data, and plotting the estimated threshold in relation to the disturbance-response data to ensure the appropriateness of the threshold estimate.

Spatial and Temporal Distributions of Lake Whitefish Spawning Stocks in Northern Lakes Michigan and Huron, 2003–2008

ABSTRACT Adult lake whitefish were tagged and released from the Big Bay de Noc (BBN) and Naubinway (NAB) stocks in northern Lake Michigan, and the Detour (DET) and Cheboygan (CHB) stocks in northern Lake Huron during 2003–2006 to describe their spatial and temporal distributions. The contemporary spatial distributions were compared with past distributions of the BBN and NAB stocks. Sixty-two percent of BBN tag recoveries occurred in Wisconsin waters during winter, spring and summer, but 83% of fall tag recoveries were made near the tagging site. Eighty-eight percent of the NAB tag recoveries were made in the management unit of tagging and 7% occurred into northern Lake Huron. Over 90% of the DET stock remained in the vicinity of the tagging sites regardless of the season, while 75% of the CHB tag recoveries were made in northwestern Lake Huron and 17% were made in Ontario. Based on regression tree analysis, there were strong stock, season, and year effects on movement distances, with weaker effects due to sex and length at tagging. Spatial distribution of the BBN stock changed from 1978–1982 to 2003–2008, but spatial distribution of the NAB stock did not. Substantial differences in movement and distribution existed among the four stocks, large seasonal differences in spatial distribution were found within some stocks, and lake whitefish exhibited strong spawning site fidelity. Present management unit boundaries are inappropriate for managing three of our four stocks, and agencies should consider developing single harvest limits for both northern Lake Huron and western Lake Michigan.

Buruli ulcer disease prevalence in Benin, West Africa: associations with land use/cover and the identification of disease clusters

BackgroundBuruli ulcer (BU) disease, caused by infection with the environmental mycobacterium M. ulcerans, is an emerging infectious disease in many tropical and sub-tropical countries. Although vectors and modes of transmission remain unknown, it is hypothesized that the transmission of BU disease is associated with human activities in or around aquatic environments, and that characteristics of the landscape (e.g., land use/cover) play a role in mediating BU disease. Several studies performed at relatively small spatial scales (e.g., within a single village or region of a country) support these hypotheses; however, if BU disease is associated with land use/cover characteristics, either through spatial constraints on vector-host dynamics or by mediating human activities, then large-scale (i.e., country-wide) associations should also emerge. The objectives of this study were to (1) investigate associations between BU disease prevalence in villages in Benin, West Africa and surrounding land use/cover patterns and other map-based characteristics, and (2) identify areas with greater and lower than expected prevalence rates (i.e., disease clusters) to assist with the development of prevention and control programs.ResultsOur landscape-based models identified low elevation, rural villages surrounded by forest land cover, and located in drainage basins with variable wetness patterns as being associated with higher BU disease prevalence rates. We also identified five spatial disease clusters. Three of the five clusters contained villages with greater than expected prevalence rates and two clusters contained villages with lower than expected prevalence rates. Those villages with greater than expected BU disease prevalence rates spanned a fairly narrow region of south-central Benin.ConclusionOur analyses suggest that interactions between natural land cover and human alterations to the landscape likely play a role in the dynamics of BU disease. For example, urbanization, potentially by providing access to protected water sources, may reduce the likelihood of becoming infected with BU disease. Villages located at low elevations may have higher BU disease prevalence rates due to their close spatial proximity to high risk environments. In addition, forest land cover and drainage basins with variable wetness patterns may be important for providing suitable growth conditions for M. ulcerans, influencing the distribution and abundance of vectors, or mediating vector-human interactions. The identification of disease clusters in this study provides direction for future research aimed at better understanding these and other environmental and social determinants involved in BU disease outbreaks.

A River Valley Segment Classification of Michigan Streams Based on Fish and Physical Attributes

Abstract Water resource managers are frequently interested in river and stream classification systems to generalize stream conditions and establish management policies over large spatial scales. We used fish assemblage data from 745 river valley segments to develop a two-level, river valley segment-scale classification system of rivers and streams throughout Michigan. Regression tree analyses distinguished 10 segment types based on mean July temperature and network catchment area and 26 segment types when channel gradient was also considered. Nonmetric multidimensional scaling analyses suggested that fish assemblages differed among segment types but were only slightly influenced by channel gradient. Species that were indicative of specific segment types generally had habitat requirements that matched segment attributes. A test of classification strength using fish assemblage data from an additional 77 river valley segments indicated that the classification system performed significantly better than random...

A spatially constrained clustering program for river valley segment delineation from GIS digital river networks

River valley segments are adjacent sections of streams and rivers that are relatively homogeneous in hydrology, limnology, channel morphology, riparian dynamics, and biological communities. River valley segments have been advocated as appropriate spatial units for assessing, monitoring, and managing rivers and streams for several reasons; however, methods for delineating these spatial units have been tedious to implement or have lacked objectivity, which arguably has limited their use as river and stream management units by natural resource agencies. We describe a spatially constrained clustering program that we developed for delineating river valley segments from geographic information system digital river network databases that is flexible, easy-to-use, and improves objectivity in the river valley segment delineation process. This program, which we refer to as the valley segment affinity search technique (VAST), includes a variety of options for determining spatial adjacency in stream reaches, as well as several data transformation methods, types of resemblance coefficients, and cluster linkage methods. The usefulness of VAST is demonstrated by using it to delineate river valley segments for river network databases for Michigan and Wisconsin, USA, and by comparing river valley segments delineated by VAST to an expert-opinion delineation previously completed for a Michigan river network database.

Spatial and temporal dynamics of lake whitefish (Coregonus clupeaformis) health indicators: Linking individual-based indicators to a management-relevant endpoint

ABSTRACT We examined the spatial and temporal dynamics of health indicators in four lake whitefish (Coregonus clupeaformis) stocks located in northern lakes Michigan and Huron from 2003 to 2006. The specific objectives were to (1) quantify spatial and temporal variability in health indicators; (2) examine relationships among nutritional indicators and stock-specific spatial and temporal dynamics of pathogen prevalence and intensity of infection; and (3) examine relationships between indicators measured on individual fish and stock-specific estimates of natural mortality. The percent of the total variation attributed to spatial and temporal sources varied greatly depending on the health indicator examined. The most notable pattern was a downward trend in the concentration of highly unsaturated fatty acids (HUFAs), observed in all stocks, in the polar lipid fraction of lake whitefish dorsal muscle tissue over the three study years. Variation among stocks and years for some indicators were correlated with the prevalence and intensity of the swimbladder nematode Cystidicola farionis, suggesting that our measures of fish health were related, at some level, with disease dynamics. We did not find relationships between spatial patterns in fish health indicators and estimates of natural mortality rates for the stocks. Our research highlights the complexity of the interactions between fish nutritional status, disease dynamics, and natural mortality in wild fish populations. Additional research that identifies thresholds of health indicators, below (or above) which survival may be reduced, will greatly help in understanding the relationship between indicators measured on individual fish and potential population-level effects.

An age-structured integrated assessment of Chinook salmon population dynamics in Lake Huron's main basin since 1968.

Abstract We conducted a statistical catch-at-age (SCAA) assessment, also known as an integrated assessment, of the Chinook salmon Oncorhynchus tshawytscha population in Lake Hurons main basin to describe the dynamics and assess population abundance since the species began being stocked in 1968. The purpose of this assessment was to determine whether recent declines in Chinook salmon recreational harvest were indicative of an overall decrease in population abundance, and to estimate the magnitude of that decline. Data sources integrated into the assessment model included recreational harvest and effort, returns to the Swan River weir by year-class, age composition of recreational harvest (overall and of mature fish), and proportion mature by age. Parameters estimated included time-varying age-0 natural mortality rates and recreational fishing catchabilities, age-specific recreational fishing selectivities, and the parameters of a logistic function relating maturation probability to fish age and weight. Th...

Changes in the Salmonine Community of Lake Michigan and Their Implications for Predator–Prey Balance

AbstractWe combined statistical stock assessment methods with bioenergetic calculations to assess historical changes in abundance and consumptive demand of the hatchery-supported salmonine community in Lake Michigan, with the goal of providing information needed to examine the lakes predator–prey balance. Especially for Chinook Salmon Oncorhynchus tshawytscha, the most dominant salmonine predator in the lake, our analysis revealed density-dependent changes in growth, survival, production levels, consumptive demand, and fishery characteristics, suggesting that increased salmonine abundance possibly had substantial impacts on prey abundance that led to predators being food limited. Indeed, the estimated changes in the salmonine community were consistent with historical changes in prey abundances that were previously documented for Lake Michigan. Specifically, higher salmonine abundance and consumption were estimated for the early 1980s, during which time Alewife Alosa pseudoharengus abundance experienced a...

Estimates of Fishing and Natural Mortality Rates for Four Lake Whitefish Stocks in Northern Lakes Huron and Michigan

ABSTRACT We analyzed tag-recovery data to estimate instantaneous fishing (F) and natural mortality (M) rates of four lake whitefish stocks in lakes Michigan and Huron during 2004–2007. We tagged and released 22,452 adult lake whitefish of which 8.7% were subsequently recovered. Annual tag-reporting rates ranged from 17.8% to 56.2%. Tag retention was high for the first 5–6 months after tagging, but tag loss increased substantially thereafter. Nine tag-recovery models were evaluated with respect to whether F and/or M varied among stocks, lakes, or years. There was support for three models based on Akaike information criteria. The best model had yearly and stock-specific estimates of F of 0.03 to 0.79 and lake-specific estimates of M of 0.35 for Lake Michigan and 0.60 for Lake Huron. The second best model had yearly and stock-specific estimates of F of 0.04 to 0.71 and a constant estimate for M of 0.52. The third model had yearly and stock-specific estimates of F of 0.04 to 0.85 and stock-specific estimates of M of 0.32 to 0.67. Model-averaged estimates of F ranged from 0.04 to 0.78 and were substantially different than statistical catch-at-age estimates of F. Model-averaged estimates of M ranged from 0.40 to 0.59 and were greater than estimates obtained from prediction equations, possibly due to sea lamprey-induced mortality. We recommend that tag-recovery estimates of F and M be used as Bayesian priors in future lake whitefish stock assessments to help refine mortality estimates for the stocks.

Sensitivity of tag-recovery mortality estimates to inaccuracies in tag shedding, handling mortality, and tag reporting

ABSTRACT We used Monte Carlo simulations to evaluate the sensitivity of tag-recovery mortality estimates to inaccuracies in tag shedding, handling mortality, and tag reporting. The data-generating model used in the simulations assumed that tagging was conducted annually for 4 years with tag recoveries occurring over a 4-year period. Several different combinations of instantaneous fishing (F) and natural (M) mortality were evaluated in the simulations. The data-generating model additionally assumed that immediate-shedding and handling-mortality rates equaled 2.5% and 0%, respectively, and that chronic shedding was a sigmoidal function of months since tagging. Two spatial patterns of reporting rates were considered-one where reporting was a function of distance from the tagging site and one where reporting was a random generation across the study area. Maximum likelihood estimates of F and M were calculated from the recovery of tags from the data-generating model under different assumed rates of tag shedding, handling mortality, and tag reporting. We found that assumptions about reporting rates resulted in the most variability in mortality estimates regardless of which combination of F and M was evaluated, with assumptions about chronic shedding also contributing substantially to overall variability in mortality estimates for most mortality combinations. Assumptions about immediate tag shedding and handling mortality had relatively minor effects on mortality estimates compared to reporting rate. When planning a tag-recovery study, care should be taken to ensure that chronic shedding and tag-reporting rates are accurately measured, as inaccurate measurements in these factors can result in significant errors in mortality estimates.