Perry, Stephen

October 2012 NFH Board Meeting Book: This document contains materials associated with the National Fish Habitat Board's October 16 - 17, 2012 in-person meeting.
Located in About EBTJV / National Fish Habitat Board Meetings / 2012 NFH Board Meetings
October 2013 NFH Board Meeting Book: This document contains materials associated with the National Fish Habitat Board's October 22 - 23, 2013 in-person meeting.
Located in About EBTJV / National Fish Habitat Board Meetings / 2013 NFH Board Meetings
October 2015 NFH Board Meeting Book: This document contains materials associated with the National Fish Habitat Board's October 20 - 21, 2015 in-person meeting.
Located in About EBTJV / National Fish Habitat Board Meetings / 2015 NFH Board Meetings
October 2016 NFH Board Meeting Book: This document contains materials associated with the National Fish Habitat Board's October 26-27, 2016 in-person meeting.
Located in About EBTJV / National Fish Habitat Board Meetings / 2016 NFH Board Meetings
October 2017 NFH Board Meeting Book: This document contains materials associated with the National Fish Habitat Board's October 18 - 19, 2017 in-person meeting.
Located in About EBTJV / National Fish Habitat Board Meetings / 2017 NFH Board Meetings
October 2018 NFH Board Meeting Book: This document contains materials associated with the National Fish Habitat Board's October 17 - 18, 2018 in-person meeting.
Located in About EBTJV / National Fish Habitat Board Meetings / 2018 NFH Board Meetings
October 2019 NFH Board Meeting Summary: This document summarizes the National Fish Habitat Board's October 23 - 24, 2019 in-person meeting.
Located in About EBTJV / National Fish Habitat Board Meetings / 2019 NFH Board Meetings
Patch Metrics: A Cost Effective Method for Monitoring Brook Trout Populations - Hudy et al. 2013: This paper describes a cost effective method for monitoring short and long term trends of Chesapeake Bay's Brook Trout populations.
Located in Science and Data / Brook Trout Related Publications / Chesapeake Bay Brook Trout Management Strategy-References
Patch-Based Metrics: A Cost Effective Method for Short- and Long-Term Monitoring of EBTJV Wild Brook Trout Populations? - Whiteley et al. 2012: This document describes a methodology for monitoring Brook Trout population trends.
Located in Science and Data / Brook Trout Related Publications / Chesapeake Bay Brook Trout Management Strategy-References
Population regulation of brook trout (Salvelinus fontinalis) in Hunt Creek, Michigan: a 50-year study: 1. Fisheries models generally are based on the concept that strong density dependence exists in fish populations. Nonetheless, there are few examples of long-term density dependence in fish populations. 2. Using an information theoretical approach (AIC) with regression analyses, we examined the explanatory power of density dependence, flow and water temperature on the per capita rate of change and growth (annual mean total length) for the whole population, adults, 1+ and young-of-the-year (YOY) brook trout (Salvelinus fontinalis) in Hunt Creek, Michigan, USA, between 1951 and 2001. This time series represents one of the longest quantitative population data sets for fishes. 3. Our analysis included four data sets: (i) Pooled (1951–2001), (ii) Fished (1951–65), (iii) Unfished (1966–2001) and (iv) Temperature (1982–2001). 4. Principle component analyses of winter flow data identified a gradient between years with high mean daily winter flows, high daily maximum and minimum flows and frequent high flow events, and years with an opposite set of flow characteristics. Flows were lower during the Fished Period than during the Unfished Period. Winter temperature analyses elucidated a gradient between warm mean, warm minimum and maximum daily stream temperatures and a high number of minimum daily temperatures >6.1 C, and years with the opposite characteristics. Summer temperature analyses contrasted years with warm summer stream temperatures vs years with cool summer stream temperatures. 5. Both YOY and adult densities varied several-fold during the study. Regression analysis did not detect a significant linear or nonlinear stock–recruitment relationship. AIC analysis indicated that density dependence was present in 15 of 16 cases (four population segments · four data sets) for both per capita rate of increase (wi values 0.46–1.00) and growth data (wi values 0.28–0.99). The almost ubiquitous presence of density dependence in both population and growth data is concordant with results from other trout populations and other studies in Michigan.
Located in Science and Data / Brook Trout Related Publications

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