United States Department of Agriculture

Forest 

Service

Pacific Northwest 

Research Station

Research Note 

PNW-RN-579

May

2019

Scale of Monitoring Influences Interpretation 

of Stream Habitat Restoration Results for 

Juvenile Chinook Salmon

Carlos M. Polivka, Rhiannon A. Volking, Shannon M. Claeson, 

and Rachel D. Hosman1

Abstract

Stream habitat restoration in the Entiat River, Washington, has increased juvenile 

Chinook abundance in pools with engineered logjams (ELJs); however, high spatial, 

temporal, and inter-species variation complicates distinguishing treatment effects 

between restored and unrestored habitat. Here we show that the scale of post restoration effectiveness monitoring can also be a confounding factor in such studies. 

In three stream reaches, we conducted snorkel surveys of (1) spatially randomized 

untreated habitat in which we also randomized survey area, and (2) restored (ELJ) 

habitat that included varying amounts of the surrounding stream area. Although 

we regularly observed more young-of-the-year Chinook salmon in restored than 

in unrestored habitat, this effect was very localized. After controlling for reach 

effects, fish density in untreated habitat was not affected by proximity to ELJs. 

Increasing the survey area increased total fish abundance, however, fish density 

decreased regardless of habitat type, indicating that ELJ structures did not necessarily increase fish abundance at the whole-reach scale. Specifically, increasing the 

survey area around a pool created by an ELJ by two to three times the restored pool 

area resulted in density measurements indistinguishable from unrestored habitat 

surveys. We conclude that whole-reach scale effectiveness monitoring surveys may 

give misleading results that dilute the effect of ELJs; therefore, monitoring should 

match the scale of specific restoration treatments.

Keywords: Habitat capacity, restoration, engineered logjam, Chinook salmon, 

Entiat River.

1 Carlos M. Polivka is a research fish biologist and Shannon M. Claeson is an aquatic 

ecologist, U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 1133 N. Western Avenue, Wenatchee WA 98801; Rhiannon A. Volking and Rachel 

D. Hosman are resource specialists, Cascadia Conservation District, 14 N Mission Street

Wenatchee, WA 98801.
2

RESEARCH NOTE PNW-RN-574

Introduction

To return Pacific salmon populations to historical levels, recovery actions are 

focused on each of their major life stages, with much effort directed toward the 

juvenile stages in streams (Roni et al. 2010). Habitat restoration techniques include 

the addition of instream structures such as rock barbs, engineered logjams (ELJs), 

or fish passage structures; the removal of levees, dams, and other disruptions that 

block access; bank stabilization or replanting; beaver introduction; rechannelization; side channel and floodplain restoration; sediment reduction or addition; and 

flow augmentation (Roni et al. 2002, 2008). In the interior Columbia River basin 

(ICRB), several subbasins are monitored for fish population status and trends 

(McClure et al. 2003), and managers have, thus far, implemented restoration 

projects in a few of these subbasins to improve rearing habitat for subyearling 

Chinook salmon (Oncorhynchus tshawytscha) and steelhead trout (O. mykiss). Both 

species have evolutionarily significant subpopulations throughout the ICRB listed 

as threatened or endangered under the Endangered Species Act.

To have the highest probability of successful recovery within a subbasin, the 

recommended approach is a combination of restoration techniques throughout the 

watershed, not just on a focused section (Beechie et al. 2010, Roni et al. 2008). 

This has led to the establishment of programs known as intensively monitored 

watersheds (IMWs) (PNAMP 2005). In IMWs, rigorous effectiveness monitoring 

is undertaken in conjunction with restoration actions (Bennett et al. 2016). Whole 

reaches within subbasins may be targeted for one or more types of restoration, 

and monitoring includes assessments of restoration efficacy in terms of biological 

responses (Block et al. 2001). Monitoring of IMWs is often focused on whether 

restoration actions went according to scheduling and design; whether there has been 

a change to the long-term status and trends of the subpopulation as a whole; or to 

evaluate the overall biological effectiveness of restoration with a response detected 

at the project, reach, or population scales (Roni et al. 2013, 2018b). 

Use of large wood or other material to build ELJs is widely implemented 

across the ICRB region (Hillman et al. 2016, Roni et al. 2015). ELJs are designed to 

diversify channel morphology via hydrologic processes (Davidson and Eaton 2013), 

increase pool frequency for rearing (Roni et al. 2010), provide cover (Bond and 

Lake 2003), and increase macroinvertebrate prey availability (e.g., Hilderbrand et 

al. 1997, Kail et al. 2007). Multiple ELJs at different frequencies may be placed in a 

restoration reach depending on the results of assessments that weigh the hydrologic 

properties of the reach in question with likely fish responses. The recommended 

monitoring design is rigorous enough to detect changes in fish abundance at the 

reach scale because the whole reach is considered the unit of restoration (Roni et 

al. 2010). However, it may be necessary to consider past restoration effectiveness 

studies to determine the appropriate scale of a monitoring design.
3

Scale of Monitoring Influences Interpretation of Stream Habitat Restoration Results for Juvenile Chinook Salmon

Post-restoration effectiveness monitoring is challenging owing to the difficulty of capturing temporally or spatially consistent responses in fish abundance, 

even with multiple treated and reference stream reaches (Polivka et al. 2015, 

Smokorowski and Pratt 2007, Whiteway et al. 2010). In many cases, small or no 

restoration effects are apparent (Hillman et al. 2016, Roni et al. 2008, Stranko et al. 

2012), and even when responses are positive they can vary greatly by species, year, 

and time period within a rearing season (Polivka et al. 2015). This may not necessarily be because restoration projects are poorly designed, but because fish-habitat 

relationships are complex, particularly for salmon (Beechie et al. 2005, Bradford 

and Higgins 2001). This complexity can occur because good habitat is underused 

(Polivka 2005), or correlative analyses may overestimate the importance of habitat 

variables as predictors of fish abundance because correlation coefficients are weak 

(Lammert and Allan 1999, Shirvell 1989).

Polivka et al. (2015) showed that when fish abundance in pools created by ELJs 

is high, and fish abundance in untreated habitat in the same reach remains the same 

as in untreated reaches elsewhere, then overall capacity increases can be inferred 

to be the result of restoration in that reach. This method, however, requires separate 

surveys of treated and untreated habitat within a treated reach at a relatively small 

(microhabitat) scale. If effectiveness monitoring is conducted at the reach scale, 

as is the goal of many monitoring programs (Roni et al. 2013b, 2018a), total fish 

density will integrate all habitats combined (Beechie et al. 2005). Depending on the 

ratio of restored to unrestored area, the increased fish density in restored habitats 

might be diluted quickly, especially if the ELJs have very localized effects. Using 

three restored reaches in an IMW subbasin, we ask whether monitoring surveys at 

larger scales reduce the observed impact of specific restoration actions. Specifically, 

we ask: (1) Are the effects of restoration with ELJs on Chinook salmon density 

localized? (2) Does restoration with ELJs affect the Chinook abundance or density 

relationship with the survey area? (3) Does increasing the survey area around ELJs 

dilute the Chinook density measured at restoration structures? 

Here we show that young-of-the-year Chinook salmon density was higher in 

pools created or restored with ELJs than in unrestored habitat, although with some 

among-site variation. However, a short distance from ELJs, fish density quickly 

declined to zero. Increasing the survey area increased the number of Chinook 

encountered, but decreased fish density, independent of whether the surveys 

included restored habitat. In fact, once the total area surveyed reached two to three 

times the area of the ELJ pool, total density was indistinguishable from unrestored 

habitat. Thus, we show that ELJ restoration has a very localized effect, and wholereach surveys in treated reaches that include counts of fish from large sections of 

untreated habitat may fail to detect small increases in habitat capacity resulting 

from restoration.
4

RESEARCH NOTE PNW-RN-574

Methods

Study Site

The Entiat River in north-central Washington, United States, is one of four major 

subbasins of the Upper Columbia River evolutionarily significant unit for Chinook 

salmon. Its headwaters are in the Cascade Mountains and run ~ 69 river km to its 

confluence with the Columbia River (river km 778; 49.6567 N, 120.2244 W), draining a watershed area of about 1085 km2

 (Bookter et al. 2009). Restoration began 

in 2005, with several projects implemented by 2008 when it was designated as an 

IMW (Sixta 2010). Three major geomorphic valley segments are in the Entiat River 

(Godaire et al. 2009). The lower valley segment (river km 0–26) is a high-gradient 

segment with large cobble substrate and laterally eroded finer particles of sand and 

gravel. Relatively fast-flowing water, given a slope of 1.04 percent, occupies an 

average wetted width of 25.4 m. Three reaches in the lower valley segment were 

selected for this study (fig. 1). The Milne reach (river km 4.5–5.1) was treated first 

in 2008 with 11 ELJ and rock structures, and again in 2014 with six ELJ structures. 

The Yakama reach (river km 4.0–4.3) and the Keystone reach (river km 2.4–2.7) 

were treated in 2014 with eight and six ELJs, respectively (fig. 1). 

Surveys of Fish Abundance

We counted young-of-the-year Chinook salmon in both treated and untreated habitat 

in the Milne, Yakama, and Keystone reaches on separate days in July 2018 via 

snorkel surveys. Visibility in the Entiat River was very good, such that fish could 

be visually enumerated while snorkeling. The number and species of other fish 

observed were also recorded. In addition to surface area (m2) surveyed at each location, the water depth (m), current velocity (m/s), and temperature (°C) were recorded.

Untreated habitat was randomly selected by starting at the upstream end of each 

reach and following the method of Polivka et al. (2015). Fifteen untreated habitats 

were surveyed in the Milne reach, while ten untreated habitats were surveyed in 

each of the Yakama and Keystone reaches. The randomization procedure consisted 

of dividing the length of the reach (L) by 15 and using a random number generator to 

select a distance that ranged from 10 m to L/15 m to locate a subsequent survey point 

relative to the previous, thus the untreated habitat surveys were at least 10 m apart but 

could not fall outside the defined treatment reach. The survey took place on either the 

left or right river margin, selected via coin toss. Only margin habitat was surveyed 

because mid-channel surveys provide little additional information in other salmonid 

streams (Beechie et al. 2005), and the ELJs were built along the river margins.

At untreated habitat, the area to be surveyed was randomly generated from a 

range of 10 to 60 m2 prior to field work. In addition to the physical habitat variables 

mentioned above, these surveys included measurements of the distance to the 
5

Scale of Monitoring Influences Interpretation of Stream Habitat Restoration Results for Juvenile Chinook Salmon Figure 1—Map of study area in the Entiat River, Washington State, USA. Study reaches are Milne (magenta), Yakama (orange), and Keystone (yellow), with locations of engi- neered logjams (circles) and river kilometers (rkm) marked at the upstream end of each reach.
6

RESEARCH NOTE PNW-RN-574

nearest ELJ, upstream or downstream, to evaluate specifically whether fish density 

in untreated habitat was affected by proximity to restoration structures. Treated 

habitat surveys were conducted at each pool created or restored by an ELJ. The 

survey area for each pool was randomly predetermined to be one, two, or three 

times the area of the ELJ pool. 

Data Analysis

Localized restoration effects—

All fish-habitat relationships were analyzed using generalized linear models 

(GLMs). Although many species abundance-habitat relationships are manifestly 

nonlinear (e.g., James and McCulloch 1990, Olden and Jackson 2001), GLMs are 

still strong tools for quantification of ecological relationships (Guisan et al. 2002) 

and have proven to provide reasonable, robust descriptions of this study system 

(Polivka et al. 2015). To describe the relationship between Chinook density in 

untreated habitat and the distance of a survey point to the nearest ELJ, while 

incorporating the effect of varying the survey area, the GLM included all measured 

habitat variables (area, depth, current velocity, temperature) and reach effects. The 

survey area was log-transformed prior to the analysis. We also included interaction 

terms to determine whether any physical differences between survey points affected 

fish density. Because the response variable was fish density, we assumed a Gaussian 

error distribution. We tested the significance of terms using an ANOVA with c2 tests 

on terms in the a priori fitted model following the method of Polivka et al. (2015).

Restoration effects on abundance- and density-area relationships—

To analyze whether the relationship between either Chinook abundance or density 

and survey area differs in restored habitat vs. untreated habitat, we used a GLM 

relating total number of Chinook to all measured habitat characteristics, including 

the presence of ELJs. For fish abundance (counts), the model assumed a Poisson 

error distribution. After each model run, nonsignificant terms were removed, and 

the new model was tested. The best model was selected using the Akaike Information Criterion (AIC) (Burnham and Anderson 2002). When competing models 

differed by ∆AIC <3, the model with the fewest nonsignificant terms was selected. 

We used the same analysis procedure with fish density as the response variable, 

only assuming a Gaussian error distribution.

Increasing survey area effect on Chinook density—

To analyze the extent to which fish density at structures was affected by widening 

the survey area around a structure, we constructed GLMs to compare fish density 

across reaches and across the varying extent, or multiples (one to three times), of 

survey area relative to the dimensions of the pool associated with the structure. The 

best model was selected by AIC as described above. 
7

Scale of Monitoring Influences Interpretation of Stream Habitat Restoration Results for Juvenile Chinook Salmon

Results

Localized Restoration Effects 

Chinook density declined with distance to structure, but distance did not produce a 

strong effect in the model (table 1), suggesting that fish were very clustered in ELJ 

pools. The untreated habitats with high density were usually within 20 to 25 m of an 

ELJ pool, but other habitats the same distance from ELJ pools had zero fish (fig. 2). 

Densities in untreated habitats were correlated with slower current velocity, and measured density declined with increasing survey area. In untreated habitats, the Milne site 

had significantly higher fish density than in the Yakama or Keystone reaches (table 1). 

Table 1—Deviance values and significance from analysis of variance (ANOVA) with c2 tests on the best fit 

generalized linear model, indicating significant variables determining density of young-of-the-year Chinook 

salmon in untreated habitat of varying area 

Coefficient

Degrees of 

freedom (df) Deviance Residual df

Residual 

deviance P-value

Area - 1 0.200 34 1.36 0.036

Reach Milne 2 0.392 31 1.99 0.014

Distance to structure - 1 0.170 33 2.38 0.053

Pool depth + 1 0.130 30 1.86 0.091

Current velocity - 1 0.305 29 1.56 0.010

Temperature - 1 0.129 28 1.23 0.092

Analysis included data from all three study reaches and considered all measured physical habitat variables. Coefficients are derived from GLMs 

and represent positive (+) or negative (-) coefficients for physical variables, or significant categorical variables (i.e., reach). Fish density declines are 

marginally significantly with distance to structure, indicating localization of fish density.

0 20 40 60 80 100 120

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Distance to nearest structure (m)

Fish • m-2

Figure 2—Density of youngof-the-year Chinook salmon 

observed in untreated habitat 

in randomly selected locations 

at increasing distances from 

the nearest engineered logjam 

structure from snorkel surveys 

conducted over varying area (10 

to 60 m2, randomly selected) at 

all three reaches combined.
8

RESEARCH NOTE PNW-RN-574

Restoration effects on abundance- and density-area relationships—

More Chinook were observed in untreated habitat as survey area increased (fig. 3A); 

however, the presence of ELJs at pools did not affect the abundance-area relationship (table 2). Similarly, when only untreated habitat was considered, Chinook 

abundance in both habitat types combined was correlated with deeper, slower 

flowing water. The best model included a significant interaction between survey 

area and reach (table 2A), related to high total abundance at the Yakama reach with 

both habitat types combined. No interaction between reach and survey area resulted 

in no differences among reaches in the abundance-area relationship.

As area increased, density (fish/m2) decreased, again regardless of whether 

restoration structures were present at the habitat (fig. 3B; table 2). Thus, the rate at 

which more fish are encountered (fig. 3A) is not proportional to increases in area. 

This is also consistent with substantial decreases in density with increasing distance 

from an ELJ pool (fig. 2). Slower current velocity predicted Chinook density across 

both habitat types, but no other predictor was meaningful. 

Table 2—Deviance values and significance from analysis of variance (ANOVA) with c2 tests on 

the best fit generalized linear model indicating significant variables determining abundance 

and density of young-of-the year Chinook salmon in restored pools and unrestored habitats of 

varying area in all three study reaches combined 

Coefficient

Degrees of 

freedom (df) Deviance Residual df

Residual 

deviance P-value

Abundance:

Area + 1 40.57 64 583.28 <0.0001

Reach Yakama 2 11.56 62 571.71 0.004

ELJ present NS 1 0.026 59 372.06 0.873

Pool depth + 1 8.11 61 563.60 0.004

Current velocity - 1 191.52 60 372.08 <0.0001

Area × reach NS 2 3.66 57 368.40 0.160

Density:

Area - 1 1.10 64 8.13 0.002

Reach NS 2 0.036 60 6.94

ELJ present NS 1 0.280 59 6.66 0.116

Pool depth NS 1 0.109 63 8.02 0.328

Current velocity - 1 1.04 62 6.98 0.003

Area × ELJ NS 1 0.211 58 6.60 0.474

Note: Direction of association between fish abundance or density and model parameters indicated by (+/-), except where parameters are 

not significant (NS). ELJ = engineered logjam. 
9

Scale of Monitoring Influences Interpretation of Stream Habitat Restoration Results for Juvenile Chinook Salmon

Figure 3—The (A) number and (B) density of young-of-the-year Chinook salmon as a function of the log-transformed survey area from 

engineered logjam structures (the survey area [black circles] varied from one to three times the pool area) and from untreated habitat 

(survey area [white circles] varied from 10 to 60 m2), at all three study reaches combined.

35

30

25

20

15

10

5

0

Number of fish

3.0

2.5

2.0

1.5

1.0

0.5

0

Fish per square meter

Ln survey area (m2)

3 4 5 6

Ln survey area (m2)

3 4 5 6

A

B

Structures

Untreated

Structures

Untreated
10

RESEARCH NOTE PNW-RN-574

Increasing survey area effect on fish density—

With all reaches combined, increasing the sampling area to two to three times the 

dimensions of a pool created by a restoration structure resulted in a rapid decline 

in measured Chinook density (fig. 4; table 3). From the nonsignificant term representing ELJ presence in GLM analyses above (table 2), it is clear that varying the 

survey area extent makes surveys around structures indistinguishable from the 

untreated habitat surveys. The presence of a significant, negative reach-by-area 

multiplier interaction term is difficult to explain except that at the Milne reach, 

untreated habitat had higher density than at the other sites, similar to the mean density in restored pools. This is in contrast with several past years of published data 

from Milne showing higher fish density at restored pools than unrestored habitat; 

however, this was likely due, in both current cases, to one or two data points from 

the randomly selected untreated habitats each day consisting of deep pools with 

very high densities of fish (see figs. 2 and 3). 

1X 2X 3X Untreated

Total survey area

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Fish per square meter

Figure 4—Mean (± 1 SE) young-of-the-year Chinook salmon density observed in snorkel surveys of 

pools restored with, or created by, engineered logjams (ELJs) in all three study reaches combined. 

For each ELJ pool, the total survey area was randomly selected as a multiple of 1 (actual pool area 

only), 2, or 3 times the ELJ pool area, with the pool in the center of the total area. Mean density for 

all untreated habitat (fig. 2) is provided for reference.
11

Scale of Monitoring Influences Interpretation of Stream Habitat Restoration Results for Juvenile Chinook Salmon

Discussion

Frequently with instream habitat restoration, post-treatment effectiveness studies 

first show positive results, but with subsequent observations, spatial and temporal 

variation in the response becomes apparent (Roni et al. 2013, Smokorowski and 

Pratt 2007). This is particularly true in restoration targeting the spawning streams 

for Pacific salmon, where positive responses may differ among species (Pess et al. 

2012, Polivka et al. 2015). We report here that one cause of inconclusive results is 

that the scale of posttreatment monitoring might be mismatched with the effects of 

the treatments. Although installation of ELJs increases the proportion of pool area 

in a given reach, which may even increase the capacity of the reach (Polivka and 

Claeson, n.d; Polivka et al. 2015), the observed fish density increase is localized.

The number of individuals observed logically increases with the sampling 

area, as is the case in the reaches surveyed here. If individuals are evenly distributed across the sampling area, then density (individuals/unit area) should remain 

constant as the sampling area gets larger. This would be the case if restoration 

structures either had no effect on fish abundance and fish remained relatively 

evenly distributed among treated and untreated habitat, or if restoration structures 

increased fish density not only in restored pools but in the reach as a whole. Our 

samples in untreated habitat of these three reaches in the Entiat River showed that 

Chinook density declined with increasing area; therefore, individuals were not 

evenly distributed within reaches. Varying habitat types in reaches, even on the 

margins (Beechie et al. 2005), makes this result unsurprising. The lack of ELJ 

effects on fish abundance or density in our variable-area surveys further demonstrates that the density increases in ELJ-enhanced pools are highly localized. 

Table 3—Deviance values and significance from analysis of variance (ANOVA) 

with c2 tests on the best fit generalized linear model indicating significant 

variables determining differences in mean young-of-the-year Chinook salmon 

density in pools restored or created by engineered logjams (ELJs) 

Coefficient

Degrees of 

freedom (df) Deviance

Residual 

df

Residual 

deviance P-value

Reach NS 2 0.750 28 5.88 0.073

Extent 1× 2 1.20 26 4.69 0.015

Reach × extent 4 1.54 22 3.15 0.030

Note: Extent of the surveyed area around ELJ pools (multiples of 1, 2, or 3) resulted in a significant decline in 

observed density.
12

RESEARCH NOTE PNW-RN-574

Whole-reach responses are one of the major objectives in IMW programs; 

therefore, a standard protocol is to conduct effectiveness monitoring surveys at 

the reach scale (Roni 2005). However, whole-reach surveys might underestimate 

or overlook the effects of structures. As we have shown here, fish density declines 

significantly only a few meters away from a restored pool, and widening the survey 

area around a restored pool quickly reduces density as fish outside that pool are not 

added in proportion to increased area.

Nevertheless, a reach-scale increase in habitat capacity for fish, as a result of 

installing ELJs, can be demonstrated by survey methods similar to those used here. 

Polivka et al. (2015) emphasized the importance of sampling untreated habitat in 

treated reaches combined with sampling untreated habitat in control reaches with 

no restoration structures. Comparison of these two categories of untreated habitat 

indicates whether fish abundance has changed at the reach scale. If pools created 

or restored by structures have higher fish density than untreated habitat within the 

same reach, and untreated habitat in that reach has the same average fish density as 

untreated habitat in untreated reaches, then structures have added capacity to the 

reach (Polivka and Claeson, n.d.; Polivka et al. 2015), even if the effect is localized. Use of the randomization procedure in multiple (untreated) reference reaches 

ensures that other physical properties of the habitat are considered for their influence on fish density (Beechie et al. 2005). Untreated reaches in the lower valley 

segment generally do not differ in mean fish density (Polivka et al. 2015); thus, 

small changes in substrate, gradient, or riparian condition from reach to reach do 

not affect comparisons of untreated habitat. 

Inconsistent or ambiguous results found in post-restoration effectiveness studies 

are not necessarily indicative that restoration did not work. Past work has shown 

that they can result from differences in the positive effect among sites (Smokorowski and Pratt 2007, Whiteway et al. 2010), the timing of sampling surveys 

(Bond and Lake 2003), species (Pess et al. 2012), or all of the above (Polivka et al. 

2015). We have shown here that, in addition to spatiotemporal and species differences, it may also be the result of combining observations of density in relatively 

few restored pools with those in a large area of untreated habitat in a treated reach. 

It may simply be necessary to design studies of effectiveness in a way that the 

scale of effects on fish abundance is reflected in the data. It may also be necessary 

to examine behavioral (Polivka, n.d.) or life history traits (e.g., survival or growth) 

(Polivka et al., n.d.; Roni 2005) to augment studies of distribution and abundance 

for the characterization of positive effects of instream habitat restoration.
13

Scale of Monitoring Influences Interpretation of Stream Habitat Restoration Results for Juvenile Chinook Salmon

Acknowledgments

We thank Jessica Johnson, Sydney Kaech, and Chandler White for additional 

technical support during this study. Rebecca Flitcroft, Alison Hunter, and Amanda 

Rosenberger provided reviews. We also thank the U.S. Bureau of Reclamation and 

Chelan County Natural Resources Division for funding and technical support of 

this research. MarySutton Carruthers at Cascadia Conservation District assisted 

with obtaining landowner permission for access to the field sites. An earlier draft 

of this manuscript was submitted by Rhiannon Volking as a thesis in partial fulfillment of the requirements for NATR 210 at Wenatchee Valley College.

U. S. Equivalents

When you know: Multiply by: To get:

Meters (m) 3.28 Feet

Kilometers (km) .621 Miles

Square meters (m2) 10.76 Square feet

Degrees Celsius (°C) 1.8 °C + 32 Degrees Fahrenheit

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