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Projected changes in Brook Trout and Brown Trout distribution in Wisconsin streams in the mid-twenty-first century in response to climate change

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Climate warming is a threat to the survival of fishes adapted to cold water. Brook Trout Salvelinus fontinalis and Brown Trout Salmo trutta are two cold-water species occurring in streams in Wisconsin, where climate change may make these species particularly vulnerable. Vulnerable trout populations need to be identified to aid in the development of adaptation strategies. We used web-based stream temperature and fish-distribution models in FishVis to predict current (late twentieth century) and project future (mid-twenty-first century) distributions of Brook Trout and Brown Trout. The models predict the suitability of habitat for trout in individual reaches using environmental variables in a geographic information system, including adjacent and upstream channel characteristics, surficial geology, landcover, and climate. Future projections of air temperature and precipitation were obtained from 13 general circulation models downscaled for Wisconsin. Currently, 34,251 km of streams are suitable for Brook Trout and 20,011 km for Brown Trout. The models project a decline of 68% (10,995 km) in stream habitat for Brook Trout and a decline of 32% (13,668 km) for Brown Trout. These projected declines, while substantial, were lower than earlier estimates because our models account for projected increased precipitation that may enhance groundwater inputs and partially offset higher air temperatures. https://rdcu.be/bMmX1 (link to view paper online)
a Predicted Brook Trout occurrence (black) and absence (gray) for the current (late twentieth century) period; b Brook Trout vulnerability to habitat loss (percent of GCMs that project loss) for the future (mid-twenty-first century) period. Colors indicate the percent of GCMs that project Brook Trout loss: gray = already absent in the late twentieth century period, green = 0% (not vulnerable and likely to remain present), and light red = 1–20% (less vulnerable to loss) to dark red = 81–100% (more vulnerable to loss); c Brook Trout opportunity to gain habitat (percent of GCMs that project gain) for the future (mid-twenty-first century) period. Colors indicate the percent of GCMs that project Brook Trout gain: green = already present in the late twentieth century period, gray = 0% (no opportunity to gain and likely to remain absent), and light blue = 1–20% (less opportunity to gain) to dark blue = 81–100% (more opportunity to gain); d Brook Trout sensitivity to loss or gain of habitat (percent of GCMs that project loss or gain) for the future (mid-twenty-first century) period. Colors indicate the percent of GCMs that project Brook Trout loss or gain: green = present in the late twentieth century period and not likely to disappear, gray = absent in the late twentieth century period and not likely to reappear, and light purple = 1–20% (less sensitive to loss or gain) to dark purple = 81–100% (more sensitive to loss or gain)
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CHARR III
Projected changes in Brook Trout and Brown Trout
distribution in Wisconsin streams in the mid-twenty-first
century in response to climate change
Matthew G. Mitro .John D. Lyons .Jana S. Stewart .Paul K. Cunningham .
Joanna D. T. Griffin
Received: 20 July 2018 / Revised: 24 June 2019 / Accepted: 5 July 2019 / Published online: 29 July 2019
ÓThis is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2019
Abstract Climate warming is a threat to the survival
of fishes adapted to cold water. Brook Trout Salvelinus
fontinalis and Brown Trout Salmo trutta are two cold-
water species occurring in streams in Wisconsin,
where climate change may make these species partic-
ularly vulnerable. Vulnerable trout populations need
to be identified to aid in the development of adaptation
strategies. We used web-based stream temperature and
fish-distribution models in FishVis to predict current
(late twentieth century) and project future (mid-
twenty-first century) distributions of Brook Trout
and Brown Trout. The models predict the suitability of
habitat for trout in individual reaches using environ-
mental variables in a geographic information system,
including adjacent and upstream channel
characteristics, surficial geology, landcover, and cli-
mate. Future projections of air temperature and
precipitation were obtained from 13 general circula-
tion models downscaled for Wisconsin. Currently,
34,251 km of streams are suitable for Brook Trout and
20,011 km for Brown Trout. The models project a
decline of 68% (10,995 km) in stream habitat for
Brook Trout and a decline of 32% (13,668 km) for
Brown Trout. These projected declines, while sub-
stantial, were lower than earlier estimates because our
models account for projected increased precipitation
that may enhance groundwater inputs and partially
offset higher air temperatures.
Keywords Brook Trout Brown Trout Climate
change Fish distribution Wisconsin
Introduction
Salmonids and other fishes adapted to cold water are
vulnerable to changes in thermal conditions that may
be attributable to climate warming. Streams that
support trout maintain relatively cold summer maxi-
mum water temperatures (Wehrly et al., 2007; Lyons
et al., 2010), so warming of stream temperatures from
climate change may threaten trout population persis-
tence (Lyons et al., 2010; Mitro et al., 2011; Roberts
et al., 2013). The state of Wisconsin in the north-
central United States has rich and varied cold-water
Guest editors: C. E. Adams, C. R. Bronte, M. J. Hansen,
R. Knudsen & M. Power / Charr Biology, Ecology and
Management
M. G. Mitro (&)J. D. Lyons
Fisheries Research, Office of Applied Science, Wisconsin
Department of Natural Resources, 2801 Progress Road,
Madison, WI 53716, USA
e-mail: matthew.mitro@wisconsin.gov
J. S. Stewart
U.S. Geological Survey, 8505 Research Way, Middleton,
WI 53562, USA
P. K. Cunningham J. D. T. Griffin
Bureau of Fisheries Management, Wisconsin Department
of Natural Resources, 101 South Webster Street, Madison,
WI 53703, USA
123
Hydrobiologia (2019) 840:215–226
https://doi.org/10.1007/s10750-019-04020-3(0123456789().,-volV)(0123456789().,-volV)
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
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