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Matthew G. Mitro

Publications and source records attributed to Matthew G. Mitro.

5 recordsLinked to original sources

Resist-accept-direct (RAD) considerations for climate change adaptation in fisheries: The Wisconsin experience

Decision-makers in inland fisheries management must balance ecologically and socially palatable objectives for ecosystem services within financial or physical constraints. Climate change has transformed the potential range of ecosystem services available. The Resist-Accept-Direct (RAD) framework offers a foundation for responding to climate-induced ecosystem modification; however, ecosystem trajectories and current practices must be understood to improve future decisions. Using Wisconsin's diverse inland fisheries as a case study, management strategies for recreational and subsistence fisheries in response to climate change were reviewed within the RAD framework. Current strategies largely focus on resist actions, while future strategies may need to shift toward accept or direct actions. A participatory adaptive management framework and co-production of policies between state and tribal agencies could prioritise lakes for appropriate management action, with the goal of providing a landscape of diverse fishing opportunities. This knowledge co-production represents a process of social learning requiring substantial investments of funding and time.

Wisconsin

Broadscale population structure and hatchery introgression of Midwestern brook trout: Midwestern brook trout population genetics

Brook Trout Salvelinus fontinalis have faced significant declines throughout their native range and have been stocked in Midwestern waters since the late 1800s to offset such losses. Several studies have investigated the genetic effects of these stockings, but these efforts have been confined to relatively small spatial scales. In this study, we compiled 8,454 Brook Trout microsatellite genotypes from 188 wild Midwestern populations and 26 hatchery strains to provide novel insights of broadscale population structure, regional patterns of genetic diversity, and estimates of hatchery introgression for inland Wisconsin populations. Our results indicate high levels of differentiation among our study populations, a lack of hydrological population structuring, lower estimates of genetic diversity in the Driftless Area, and that hatchery introgression has been largely confined to regions of inland Wisconsin that have been heavily affected by anthropogenic disturbances (i.e., the Driftless Area). We also provide evidence that populations may be able to purge hatchery‐derived alleles, discuss possible mechanisms behind this phenomenon, and consider their relevance to accurate estimation of hatchery introgression. Collectively, these results summarize the genetic effects of over a century of anthropogenic disturbance on native Brook Trout populations and emphasize the importance of integrating historical data into contemporary genetic research of intensively managed species.

Iowa, Minnesota, Wisconsin

A model for evaluating stream temperature response to climate change in Wisconsin

Expected climatic changes in air temperature and precipitation patterns across the State of Wisconsin may alter future stream temperature and flow regimes. As a consequence of flow and temperature changes, the composition and distribution of fish species assemblages are expected to change. In an effort to gain a better understanding of how climatic changes may affect stream temperature, an approach was developed to predict and project daily summertime stream temperature under current and future climate conditions for 94,341 stream kilometers across Wisconsin. The approach uses a combination of static landscape characteristics and dynamic time-series climatic variables as input for an Artificial Neural Network (ANN) Model integrated with a Soil-Water-Balance (SWB) Model. Future climate scenarios are based on output from downscaled General Circulation Models (GCMs). The SWB model provided a means to estimate the temporal variability in groundwater recharge and provided a mechanism to evaluate the effect of changing air temperature and precipitation on groundwater recharge and soil moisture. The Integrated Soil-Water-Balance and Artificial Neural Network version 1 (SWB-ANNv1) Model was used to simulate daily summertime stream temperature under current (1990–2008) climate and explained 76 percent of the variation in the daily mean based on validation at 67 independent sites. Results were summarized as July mean water temperature, and individual stream segments were classified by thermal class (cold, cold transition, warm transition, and warm) for comparison of current (1990–2008) with future climate conditions. Integrating the SWB Model with the ANN Model provided a mechanism by which downscaled global or regional climate model results could be used to estimate the potential effects of climate change on future stream temperature on a daily time step. To address future climate scenarios, statistically downscaled air temperature and precipitation projections from 10 GCMs and 2 time periods were used with the SWB-ANNv1 Model to project future stream temperature. Projections of future stream temperatures at mid- (2046–65) and late- (2081–2100) 21st century showed the July mean water temperature increasing for all stream segments with about 80 percent of stream kilometers increasing by 1 to 2 degrees Celsius (°C) by mid-century and about 99 percent increasing by 1 to 3 °C by late-century. Projected changes in stream temperatures also affected changes in thermal classes with a loss in the total amount of cold-water, cold-transition, and warm-transition thermal habitat and a gain in warm-water and very warm thermal habitat for both mid- and late-21st century time periods. The greatest losses occurred for cold-water streams and the greatest gains for warm-water streams, with a contraction of cold-water streams in the Driftless Area of western and southern Wisconsin and an expansion of warm-water streams across northern Wisconsin. Results of this study suggest that such changes will affect the composition of fish assemblages, with a loss of suitable habitat for cold-water fishes and gain in suitable habitat for warm-water fishes. In the end, these projected changes in thermal habitat attributable to climate may result in a net loss of fisheries, because many warm-water species may be unable to colonize habitats formerly occupied by cold-water species because of other habitat limitations (e.g., stream size, gradient). Although projected stream temperatures may vary greatly, depending on the emissions scenario and models used, the results presented in this report represent one possibility. The relative change in stream temperature can provide useful information for planning for potential climate impacts to aquatic ecosystems. Model results can be used to help identify vulnerabilities of streams to climate change, guide stream surveys and thermal classifications, prioritize the allocation of scarce financial resources, identify approaches to climate adaptation to best protect and enhance resiliency in stream thermal habitat, and provide information to make quantitative assessments of statewide stream resources.

Wisconsin

Influences of riparian vegetation on trout stream temperatures in central Wisconsin

Summer stream temperatures limit the distribution of Brook Trout Salvelinus fontinalis and are affected by riparian vegetation. We used riparian and instream habitat surveys along with stream temperature loggers placed throughout streams to determine the potential for riparian vegetation shading to increase the length of stream that is thermally suitable for Brook Trout. Twelve streams located throughout central Wisconsin were evaluated in the summers of 2007 and 2008. Across all streams, nonparametric ANCOVA modeling was used to identify spatial temperature patterns within a year for individual stream segments. Riparian tree-vegetated segments had a significantly lower mean change in stream temperature per kilometer of stream compared with grass-vegetated segments during the periods of maximum daily and weekly average temperatures, when we accounted for upstream temperature. Riparian grass-vegetated segments increased on average 1.19°C/km (SE, 0.44) during the maximum daily average temperature period and 0.93°C/km (SE, 0.39) during the maximum weekly average temperature period, whereas tree-vegetated segments decreased 0.48°C/km (SE, 0.39) and 0.30°C/km (SE, 0.25) during those respective time periods. Maximum weekly average temperatures were also modeled with different shading levels using a heat budget temperature model, U.S. Fish and Wildlife Service's Stream Segment Temperature Model. Across 11 study streams (one stream model could not be calibrated), modeled stream temperatures in equilibrium with their environmental conditions ranging from 23.2°C to 28.3°C at 0% shading could be reduced to 18.8–23.5°C with 75% shading. Modeled increases in shade up to 75% from the current average of 34% increased the length of surveyed stream thermally suitable to Brook Trout by 4.9 km on Sucker Creek. We conclude that riparian forests are important for maintaining thermal conditions suitable for Brook Trout in central Wisconsin streams and can be managed to increase the amount of stream habitat thermally suitable for Brook Trout.

Wisconsin

A model for evaluating stream temperature response to climate change scenarios in Wisconsin

Global climate change is expected to alter temperature and flow regimes for streams in Wisconsin over the coming decades. Stream temperature will be influenced not only by the predicted increases in average air temperature, but also by changes in baseflow due to changes in precipitation patterns and amounts. In order to evaluate future stream temperature and flow regimes in Wisconsin, we have integrated two existing models in order to generate a water temperature time series at a regional scale for thousands of stream reaches where site-specific temperature observations do not exist. The approach uses the US Geological Survey (USGS) Soil-Water-Balance (SWB) model, along with a recalibrated version of an existing artificial neural network (ANN) stream temperature model. The ANN model simulates stream temperatures on the basis of landscape variables such as land use and soil type, and also includes climate variables such as air temperature and precipitation amounts. The existing ANN model includes a landscape variable called DARCY designed to reflect the potential for groundwater recharge in the contributing area for a stream segment. SWB tracks soil-moisture and potential recharge at a daily time step, providing a way to link changing climate patterns and precipitation amounts over time to baseflow volumes, and presumably to stream temperatures. The recalibrated ANN incorporates SWB-derived estimates of potential recharge to supplement the static estimates of groundwater flow potential derived from a topographically based model (DARCY). SWB and the recalibrated ANN will be supplied with climate drivers from a suite of general circulation models and emissions scenarios, enabling resource managers to evaluate possible changes in stream temperature regimes for Wisconsin.

Wisconsin