Published figures arising directly out
of FISH554: Beautiful graphics in R
Figure 4. (a) Contour plot of LSD (linear
selection differential) values, the product of
different exploitation rates and length
selectivity values (the difference in the
average length of fish caught vs. those not
caught), of a fishery. LSD values are the
difference in length of fish before fishing vs.
after fishing (not caught). Actual (b) female
and (c) male annual exploitation rates and
length selectivity values, along with the
resulting LSDs, produced in a total of 283
years by the nine Alaskan sockeye salmon
fisheries examined in our study. The
grayscale legend refers to these LSD values
produced. Background contour lines in
panels (b) and (c) show where the product
of a fishery’s exploitation rate and lengthselectivity value equals a given LSD value.
Created by Neala Kendall as part of the
2011 course.
Kendall, N. W. and T. P. Quinn. 2012.
Quantifying and comparing size selectivity
among Alaskan sockeye salmon fisheries.
Ecological Applications 22:804-816.
Figure 3 Directional differences between (a) free-flowing and flow-regulated rivers for per cent opportunistic and
equilibrium life history strategies and (b) a principal components ordination summarising variation among rivers according
to the six major flow metrics. Dam types are coded by line type where solid lines indicate hydropower, dashed lines indicate
flood control, and dotted lines indicate locks. Sites are labelled at the base of each arrow, and labels correspond to Fig. 1.
Created by student Meryl Mims as part of the 2011 course.
Mims MC, and Olden JD (2013) Fish assemblages respond to altered flow regimes via ecological filtering of life history
strategies. Freshwater Biology 58:50-62. doi: 10.1111/fwb.12037
Figure 4 Pairwise per cent differences of (a) opportunistic, (b) periodic and (c) equilibrium proportional life history strategies
and (d) % nonnative species versus the Flow Alteration Index. Symbols indicate dam type, and symbol fill indicates release
type.
Created by student Meryl Mims as part of the 2011 course.
Mims MC, and Olden JD (2013) Fish assemblages respond to altered flow regimes via ecological filtering of life history
strategies. Freshwater Biology 58:50-62. doi: 10.1111/fwb.12037
Figure 1. (a) Map of Wood River
basin showing sockeye salmon
spawning locations and
corresponding average summer
water temperature as indicated by
dot colour. (b) Relationship between
water temperature and sockeye
salmon spawning date. (c,d)
Cumulative distribution functions
(cdf), representing the proportion
of the cumulative seasonal activity
observed at any site on a specific
date, for (c) gulls and (d ) bears at
sockeye salmon spawning locations.
Colours of lines correspond to water
temperatures, and insets show
relationship between the mean of
the cdf for gulls and bears, and
sockeye salmon spawn timing among
study sites (see the electronic
supplementary material, table S1).
Created by student Peter Lisi as part
of the 2011 course.
Schindler DE et al. 2013. Rising the
crimson tide: mobile terrestrial
consumers track phenological
variation in spawning of an
anadromous fish. Biology Letters
9:20130048. doi:
10.1098/rsbl.2013.0048
Figure 6. This figure shows how hole
proportion can lower the degree
mean of forest landscapes. Loesssmoothed degree means (d) from 20
000 simulations are plotted in the
top graph with sample landscapes
below. The order of the lines in the
top graph, from top to bottom,
is uniform, cluster, SSI, and lattice.
This ordering is consistent
throughout the domain, with
landscapes generated using the
lattice method having noticeably
lower degree means than landscapes
generated from other point
processes. This example uses
landscapes generated using each
point process exclusively to highlight
the differences between them. In
practice, landscapes will generally
use a mixture of point processes. The
shaded filled polygons indicate
management units that have been
deleted during the editing process.
Created by Gregor Passolt as part of
the 2011 course.
Passolt, G. et al. 2013. A Voronoi
tessellation-based approach to
generate hypothetical forest
landscapes. Canadian Journal of
Forest Research. 43:78-89. doi:
10.1139/cjfr-2012-0265