The removal of conifers through commercial timber harvesting has been successful in restoring aspen, however many aspen stands are located near streams, and there are concerns about potential aquatic ecosystem impairment. We examined the effects of management-scale conifer removal from aspen stands located adjacent to streams on water quality, solar radiation, canopy cover, temperature, aquatic macroinvertebrates, and soil moisture. This 8-year study (2003–2010) involved two projects located in Lassen National Forest. The Pine-Bogard Project consisted of three treatments adjacent to Pine and Bogard Creeks: (i) Phase 1 in January 2004, (ii) Phase 2 in August 2005, and (iii) Phase 3 in January 2008. The Bailey Project consisted of one treatment adjacent to Bailey Creek in September 2006. Treatments involved whole tree removal using track-laying harvesters and rubber tire skidders. More than 80% of all samples analyzed for NO3-N, NH4-N, and PO4-P at Pine, Bogard, and Bailey Creeks were below the detection limit, with the exception of naturally elevated PO4-P in Bogard Creek. All nutrient concentrations (NO3-N, NH4-N, PO4-P, K, and SO4-S) showed little variation within streams and across years. Turbidity and TSS exhibited annual variation, but there was no significant increase in the difference between upstream and downstream turbidity and TSS levels. There was a significant decrease in stream canopy cover and increase in the potential fraction of solar radiation reaching the streams in response to the Pine-Bogard Phase 3 and Bailey treatments; however, there was no corresponding increase in stream temperatures. Macroinvertebrate metrics indicated healthy aquatic ecosystem conditions throughout the course of the study. Lastly, the removal of vegetation significantly increased soil moisture in treated stands relative to untreated stands. These results indicate that, with careful planning and implementation of site-specific best management practices, conifer removal to restore aspen stands can be conducted without degrading aquatic ecosystems.
Citation: Jones BE, Krupa M, Tate KW (2013) Aquatic Ecosystem Response to Timber Harvesting for the Purpose of Restoring Aspen. PLoS ONE 8(12): e84561. https://doi.org/10.1371/journal.pone.0084561
Editor: Samuel St. Clair, Brigham Young University, United States of America
Received: July 20, 2013; Accepted: November 15, 2013; Published: December 20, 2013
This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
Funding: This research was funded by the USDA Forest Service, Pacific Southwest Region. The funders did assist in study design, provided field data collection assistance, and input on the methods section during preparation of the manuscript. The funders had no role in data analysis or in the decision to publish.
Competing interests: The authors have declared that no competing interests exist.
Trembling aspen (Populus tremuloides Michx.) occurs throughout North America, including the montane zone of California’s Sierra Nevada and southern Cascade ranges . Aspen is considered a keystone species providing crucial habitat to support a high diversity of local and landscape plant species , bird communities [3-5], mammals , and insects and other invertebrates . Additionally, aspen stands provide important ecosystem services such as increased water yields and soil moisture , and act as natural firebreaks [9,10].
Declines in the health and distribution of aspen stands across western North America have been observed over the past century to the present day [11-14]. Much of this decline is attributable to conifer encroachment stimulated by the absence of natural fire regimes, as well as historic and current heavy browsing of aspen suckers by domestic and native herbivores [15-17]. Aspen is a clonal species and disturbance stimulates its vegetative reproduction . When fire return intervals are lengthened, the disturbance of aspen and their resultant vegetative reproduction is reduced [11,19]. Additionally, fire suppression places aspen at a competitive disadvantage to shade-tolerant conifers, as aspen require sunlight and warm soil for successful regeneration [13,20,21]. The results of an aspen inventory conducted from 2000 - 2011 that assessed the current status and risk of loss of 700 live aspen stands (approximately 99 % of known stands) totaling 1,540 ha on the Eagle Lake Ranger District, Lassen National Forest, documented that 79 % of stands were at high risk of being lost. At least 45 known stands have expired with no living aspen present and no means of recruitment. Conifer encroachment was the major risk factor associated with 96 % of inventoried stands .
Recent studies have found that the use of commercial timber harvest techniques to remove conifers is an effective treatment for stimulating aspen regeneration [10,22,23], and that long-term success of aspen stand restoration can be achieved when this treatment is coupled with management of ungulate herbivory [16,24]. The broad-scale implementation of silvicultural treatments in this region is of concern however, because a significant number of conifer encroached aspen stands are associated with streams . Timber harvest activities that occur adjacent to rivers and streams have the potential to affect soil moisture dynamics [25,26], water quality [27-33], stream temperature through increased solar radiation inputs [34-36], and aquatic communities [37-39]. However, conifer encroached aspen stands that are not released will expire and overall landscape habitat complexity and biodiversity will continue to decline. Previous studies have found that the implementation of best management practices (BMPs) during timber harvest can prevent or limit aquatic ecosystem degradation [40-42]. Such studies also indicate that, when BMPs are followed, any changes in the aquatic ecosystem that have occurred often return to pre-harvest conditions within 5 years [42-45].
The purpose of this study was to quantify the occurrence and magnitude of the impacts of management-scale prescriptive conifer removal through commercial timber harvest on aquatic habitat quality in streams adjacent to the conifer removal activities and on soil moisture dynamics within the treated aspen stands. To this end, we performed water quality, stream temperature, solar radiation, canopy cover, aquatic macroinvertebrate, and soil moisture tension monitoring, both before and after the implementation of each of four conifer removal treatments in Lassen National Forest (Figure 1). We hypothesized that conifer removal would cause: (1) an increase in nutrient concentrations, total suspended solids, and turbidity levels, (2) an increase in stream temperatures as a result of decreased canopy cover allowing more solar radiation to reach the streams, (3) a decrease in aquatic ecosystem health as indicated by macroinvertebrate metrics, and (4) an increase in soil moisture.
Materials and Methods
2.1: Ethics statement
This field study was conducted in collaboration with the USDA Forest Service, and so all permissions for site access were granted and no permits were required. An Environmental Impact Statement addressing the timber harvest treatments was completed by the USDA Forest Service in accordance with National Environmental Policy Act requirements. Macroinvertebrate sampling was performed following approved protocols described by Barbour et al. .
2.2: Study Area
This study was carried out at two locations: (1) the confluence of Pine and Bogard Creeks (Bogard Creek is a tributary to Pine Creek) (40°34’42.66” N, 121°05’49.18” W) in the Eagle Lake Ranger District, which is located on the eastern side of Lassen National Forest at an elevation of approximately 1,740 m, and (2) at the South Fork of Bailey Creek (40°28’46.48” N, 121°35’45.84” W) in the Hat Creek Ranger District, which is located on the western side of Lassen National Forest at an elevation of approximately 1,920 m. The Pine Creek and Bailey Creek watersheds have total surface areas of approximately 591 and 154 km2, respectively.
Vegetation in the Pine and Bogard Creek study area is dominated by Ponderosa pine (Pinus ponderosa Laws.), sagebrush (Artemisia tridentata Nutt.), and aspen. The area has slopes from 0 to 4 %, with a northeast aspect at the uppermost reaches, and level at the valley floor. Geology is dominated by basalt. Soils in the valley floor are dominated by loamy-skeletal, mixed, frigid Ultic Haploxerolls, and soils in the upper slopes are dominated by fine-loamy, mixed, frigid Pachic Ultic Argixerolls. Both Pine and Bogard Creeks are spring fed, but receive a substantial amount of snowmelt, particularly in May and June. Pine Creek has a much larger watershed area than Bogard Creek, and as a result, a larger fraction of its water is derived from snowmelt. From the months of May through September, the average width of Bogard Creek along the stream reach that was monitored in this study was approximately 1 m, and the average width of Pine Creek was approximately 3 m. During summer months, Pine Creek becomes intermittent approximately 1,500 m below its confluence with Bogard Creek. The Mediterranean climate consists of dry, warm summers, and wet, cool winters. Precipitation primarily occurs as snowfall from November through May . Based on models from the PRISM Climate Group, long-term average annual precipitation is 630 mm, and ranged from 460 to 1,070 mm during the study period . The primary land uses in the area are recreation (camping, hunting, snowmobiling), cattle grazing, which occurs annually from approximately June 1 through September 30, and vegetation management.
Vegetation in the Bailey Creek study area is dominated by perennial meadow herbaceous species, Lodgepole pine (Pinus contorta Dougl.),White fir (Abies concolor (Gordon & Glend) Lindley), Willow (Salix lucida Muhl. ssp. lasiandra (Benth.) E. Murray), and aspen. The area has slopes from 0 to 4 %. The geology is typified by moraine complexes with well-preserved morphology and a weakly oxidized soil zone approximately 50 cm thick. Soils are dominated by Aquolls. Bailey Creek is spring fed but receives a substantial amount of snowmelt, particularly in May and June. From the months of May through September, the average width of Bailey Creek along the stream reach that was monitored in this study was approximately 4 m. Similarly to the Pine and Bogard Creek study area, the climate is Mediterranean and precipitation primarily occurs as snowfall from November through May . Based on models from the PRISM Climate Group, long-term average annual precipitation is 1,590 mm, and ranged from 810 to 1,870 mm during the study period . The primary land uses in the area are recreation (camping, fishing, hunting) and vegetation management. Historically the area was grazed by livestock, but has not been grazed for more than 30 years.
2.3: Project Design
This study involved two different management-scale conifer removal projects (Figures 2 and 3). The Pine-Bogard Project consisted of conifer removal treatments in three phases: (i) Phase 1 in January 2004, (ii) Phase 2 in August 2005, and (iii) Phase 3 in January 2008. The Bailey Project consisted of conifer removal at Bailey Creek, which was implemented as one treatment in September 2006. Both project areas were chosen for restoration because the aspen stands were at high risk of loss due to extensive conifer encroachment.
The following parameters were measured in order to understand the impacts of management-scale conifer removal on aquatic ecosystems and soil moisture dynamics: (i) soil moisture tension, (ii) stream and air temperature, (iii) stream discharge and water quality, including nitrate as N (NO3-N), ammonium as N (NH4-N), phosphate as P (PO4-P), sulfate as S (SO4-S), potassium (K), total suspended solids (TSS), and turbidity, (iv) stream canopy cover and solar radiation inputs, and (v) aquatic macroinvertebrates. Soil moisture was investigated through the establishment of discrete soil moisture tension monitoring stations along transects located within treatment and reference aspen stands (Figures 2 and 3). Treatment stands are conifer encroached aspen stands in which conifer removal took place, while reference stands are untreated conifer encroached aspen stands. Streamwater quality, discharge, temperature, and aquatic macroinvertebrates, were measured at stream monitoring stations. Each stream included at least one station immediately upstream and one station immediately downstream of the treatment stands (Figures 2 and 3). Canopy cover and solar radiation measurements were made along the stream reaches located between the upstream and downstream stations for each treatment (refer to tables in Figures 2 and 3).
2.3.1: Conifer Removal Implementation.
Pine-Bogard Phase 1 treatment occurred in January of 2004 between Pine Creek stations PC3 and PC4 and Bogard Creek stations BO3 and BO5 (Figure 2). The total treatment area for this phase was approximately 24 ha, with 720 m of Pine Creek and 430 m of Bogard Creek affected by the treatment. Timber harvest was implemented over snow with a minimum requirement of 60 cm of snow or 10 cm of frozen ground. Whole tree removal using track-laying harvesters and rubber tire skidders was used to remove conifers more than 25 m from stream. Whole tree removal is the standard practice used because it creates less slash, and over snow was used to protect the soil surface. Trees within 25 m of stream were hand felled and end-lined to reduce compaction and sedimentation within areas closest to the streams. Typically, all conifers less than 75 cm diameter at breast height (dbh) were removed, except for conifers directly contributing to streambank stability or other site-specific benefits. Hand-felling of conifers less than 30 cm dbh occurred post-harvest. The treatment area before and after Phase 1 conifer removal is illustrated in Photos S1, S2, and S3.
Pine-Bogard Phase 2 treatment was designed to maximize the amount of dry season harvest in order to avoid the excessive slash that was observed during Phase 1 over snow harvest. Phase 2 treatment occurred from August 10, 2005 through September 12, 2005 between Pine Creek stations PC1 and PC4 and Bogard Creek stations BO1 and BO5 (Figure 2). The total treatment area for this phase was approximately 80 ha, with 1,800 m of Pine Creek and 1,090 m of Bogard Creek affected by the treatment. Whole tree removal using track-laying harvesters and rubber tire skidders was used to remove conifers within 4 to 40 m from stream. This distance was identified on the ground using site specific factors including slope and ground cover. Photo S4 illustrates an area where conifer removal took place during Phase 2 treatment adjacent to an untreated area.
Pine-Bogard Phase 3 treatment was designed to treat the remaining areas adjacent to streams that could not be accessed during Phase 2 treatment. The treatment occurred in January 2008 between Pine Creek stations PC1 and PC4 and Bogard Creek stations BO1 and BO5 (Figure 2). The total treatment area for this phase was approximately 13 ha, with 1,800 m of Pine Creek and 1,090 m of Bogard Creek affected by the treatment. Timber harvest was implemented over snow with a minimum requirement of 60 cm of snow or 10 cm of frozen ground. Whole tree removal using track-laying harvesters and rubber tire skidders was used. A mechanical equipment boundary was delineated from the water’s edge to the area with complete and continuous vegetation. No equipment was allowed to enter this area but conifers that did not contribute to streambank stability and were less than 75 cm dbh were removed through hand felling or reaching with a mechanical harvester boom. The treatment area before and after Phase 3 conifer removal is illustrated in Photos S5, S6, and S7.
A dry-season conifer removal project occurred in September 2006 between stations BR1 and BR6 along Bailey Creek (Figure 3). The total treatment area for this project was approximately 4.5 ha, with 560 m of the total BR1 to BR6 reach length (1,970 m) affected by the treatment. Whole tree removal using track-laying harvesters and rubber tire skidders was used between 1.5 to 90 m from stream depending upon slope and ground cover. Skid trails were designated in areas that did not contain riparian vegetation. Typically, all conifers 10 to 75 cm dbh were removed except for conifers located within 8 meters of the stream and contributing to stream bank stability. Conifers less than 50 cm dbh were hand felled. All conifers 10 cm dbh or smaller were cut, hand piled and burned outside of the aspen clone root zone to prevent damage to the root system. The treatment area before and after conifer removal is illustrated in Photos S8, S9, and S10.
2.3.2: Stream discharge and water quality.
Stream water samples were grab sampled every 2 weeks at each stream monitoring station. Pine-Bogard samples were collected from 2003 through 2010. Bailey samples were collected from 2003 through 2004, and from 2006 through 2010. Sampling was focused on both the peak flow period, which occurs in late May/early June and is the period of most rapid snowmelt, and the summer base flow period. Sampling began as early as May 19 and ended as late as October 12 at Pine and Bogard Creek stations, and began as early as June 3 and ended as late as October 7 at Bailey Creek stations. Sampling did not occur from about October to May because the streams are largely frozen and flows are low. The sampling periods for this study are similar to that of other studies performed in areas where much of the year is characterized by precipitation falling as snow and by freezing temperatures [28,32,33,44]. Historic stream discharge data from USGS Station 10359250 (1961-1978), which was located on Pine Creek near sampling location PC1 (Figure 2), indicates that the May through September sampling period generally captured at least 80 percent of annual discharge at Pine and Bogard Creeks. Readings started relatively later in the year at the Bailey Creek study area because it is located at a higher elevation than the Pine-Bogard study area and consequently snow melt occurs approximately 1 month later.
Stream discharge was measured at the same time as grab samples were collected using the area-velocity method. With this method, discharge was calculated as: mean velocity × stream width × mean stream depth . A minimum of 3 stream depth readings were taken across each stream cross-section – at thalawag and at mid-point between thalawag and each streambank. Water velocity was measured at each of these three depth reading locations. A Global Waters flow meter (Global Waters Inc., Gold River, California, USA) was used to estimate velocity whenever water depth was greater than 10 cm. The float method was used whenever water depth was < 10 cm and thus could not accommodate the flow meter . Velocity meter readings were collected at 0.6 of stream depth. A correction factor of 0.85 was used to adjust surface velocities when the float method was used.
Grab samples were refrigerated (4 °C) and transported to UC Davis for analysis. Nephelometric turbidity units (ntu) and pH were measured on non-filtered subsamples using standard methods SM2130 and SM4500-H+, respectively . To measure TSS, a 170 mL subsample was passed through a 0.45 µm membrane filter. The filters were dried in a desiccator until a stable weight was achieved (typically 5 to 7 days). The filter mass was measured on an analytical balance accurate to 0.001 g. The levels of TSS were then determined as the change in mass of the filter before and after filtration of the known volume of water. The concentrations of NO3-N, NH4-N, PO4-P, K, and SO4-S were measured using ion chromatography (Dionex 500x; CS12 cations; AS4A anions) on subsamples filtered through a 0.45 µm membrane filter.
2.3.3: Stream and air temperature.
Stream temperature data was collected at all monitoring stations on Pine, Bogard, and Bailey Creeks (Figures 2 and 3) using Onset Optic StowAway temperature loggers. Additionally, air temperature data was collected using Onset Optic StowAway temperature loggers at one location in the Pine-Bogard Project area, and at one location at the Bailey Project area. All loggers were set to record temperature every 0.5 hours. Pine-Bogard temperature data was collected from 2003 through 2010. Bailey temperature data was collected from 2003 through 2004, and from 2006 through 2010. Loggers were deployed as early as May 19 and retrieved as late as October 12 at Pine and Bogard Creek stations, and deployed as early as June 3 and retrieved as late as October 7 at Bailey Creek stations. Daily maximum and average temperatures, as well as 7-day running average maximum and average temperatures were calculated using the recorded data.
2.3.4: Canopy cover and solar radiation.
Percent stream canopy cover was measured with a convex spherical densiometer and represents the amount of sky above a point on the stream channel which is blocked from view by vegetation. At each sample point along a given stream reach, measurements were made facing downstream, right bank, upstream, and left bank, and then the average of these values was calculated .
The potential fraction of solar radiation reaching each stream was estimated based on measurements collected with a solar pathfinder (Solar Pathways, Hartford, South Dakota). Solar pathfinder measurements integrate the effects of the sun’s path, vegetative canopy cover, topographic shading, and stream channel aspect to estimate the potential fraction of available solar radiation (0 to 100%) reaching a site at a given latitude for each month of the year. Solar pathfinder measurements can overestimate the quantity of solar radiation reaching a site because they do not take cloud cover and atmospheric turbidity into account. A detailed description of solar pathfinders can be found in Platts et al. . We concern ourselves with the months of May through September, which represent the warmest period in the region, when elevated stream water temperatures might be of concern.
There was no canopy cover or solar radiation data collected for Pine-Bogard Phase 1. Pine-Bogard Phase 2 canopy cover and solar radiation measurements were taken at the stream reach between stations BO1 and BO5, and at the stream reach between stations PC1 and PC4, before (June 2005) and after (September 2005) treatment implementation. Following Pine-Bogard Phase 3 treatment implementation, canopy cover and solar radiation measurements were taken in June 2008 at the stream reach between stations BO1 and BO5, and at the stream reach between stations PC1 and PC4. These measurements were compared to the September 2005 measurements taken following Pine-Bogard Phase 2 treatment. Measurements along Pine and Bogard Creeks were taken every 40 m during each data collection event (n= 45 and 28 for Pine and Bogard Creeks, respectively). Bailey Project canopy cover and solar radiation readings were taken at the stream reach between stations BR1 and BR6, before (September 2003) and after (July 2007) treatment implementation. Measurements along Bailey Creek were taken every 55 m (n= 36).
2.3.5: Aquatic macroinvertebrates.
Stream macroinvertebrate collections were made at midstream (BO3) and upstream (BO5) stations along Bogard Creek, at midstream (PC3) and upstream (PC4) stations along Pine Creek, and at midstream (BR4) and upstream (BR6) stations along Bailey Creek in June-July of 2003, 2004, 2007, 2008, and 2010. Samples were collected according to the single habitat approach for riffles described by Barbour et al. . At each sample station, two sub-samples were collected along a transect perpendicular to streamflow (center-right and center-left from banks) and composited as 1 sample for analysis. Transects were established across riffle areas. All sub-samples were collected with a D-ring kick net (500 micron mesh) from a sample area of 0.09 m2 for a sample time of 3 minutes per sample. Collections were immediately stabilized with 95 % ethanol. Taxonomic analysis was conducted at the BLM BugLab on the campus of Utah State University following the methods described by Moulton et al.  and Cuffney et al. . Samples were taxonomically analyzed to genus and species where possible and standard metrics describing macroinvertebrate assemblage characteristics were calculated from the raw taxa data.
2.3.6: Soil Moisture.
Soil moisture, measured as soil moisture tension in centibars, was investigated using permanently established gypsum blocks . Higher values of soil moisture tension indicate drier soil conditions. Soil moisture tension measurements were taken approximately every 2 weeks from as early as May 19 to as late as October 12 from 2003 through 2010 at Pine and Bogard Creeks, and from as early as June 3 to as late as October 7 in 2004, and from 2006 through 2010, at Bailey Creek. Soil moisture tension monitoring stations were located in areas that provided a representative sample of the whole stand, excluding skid trails and landings.
At Pine and Bogard Creeks, 2 transects of 4 monitoring stations were established from near stream to uplands in the treatment area, and in a nearby reference area, in order to capture a gradient of soil moisture conditions, as illustrated in Figure 2. Gypsum blocks were permanently established at 15 and 45 cm in depth at each monitoring station (n = 16 at each depth, 8 treatment, 8 reference). These depths were chosen because they correspond to the bottom and mid-depths of herbaceous plant root mass in the Pine-Bogard and Bailey project areas. Phase 1 treatment did not affect the treatment transects. Phase 2 treatment affected stations C and D in both treatment transects, which were then compared to stations C and D in the reference transects (Figure 2). Phase 3 treatment affected stations A and B in both treatment transects, which were then compared to stations A and B in the reference transects (Figure 2).
At Bailey Creek, 2 transects of 5 monitoring stations were established from near stream to uplands in the treatment area, and in a nearby reference area, as illustrated in Figure 3. Gypsum blocks were permanently established at 15 and 45 cm in depth at each monitoring station (n = 20 at each depth, 10 treatment, 10 reference).
2.3.7: Data Analysis.
Statistical analysis was designed to test the hypotheses that the various aquatic ecosystem parameters we measured were degraded (i.e. increased nutrient concentrations, decreased macroinvertebrate diversity) following conifer removal treatments. We used linear mixed effects (LME) and generalized linear mixed effects (GLMM) analyses to determine the occurrence and magnitude of change in each aquatic ecosystem parameter between treated/downstream and reference/upstream sample locations before versus after treatment [56-58]. A separate analysis was conducted for each parameter. The specific parameters analyzed were: NO3-N, NH4-N, PO4-P, K, SO4-S, turbidity, TSS, canopy cover, solar radiation, stream temperature, macroinvertebrate metrics (% Tolerant, % Intolerant , Shannon Diversity Index, number of families), and soil moisture tension. For soil moisture tension, separate mixed effects models were used for the 15 and 45 cm depths at (i) the Bailey transects, (ii) stations A and B of the Pine-Bogard transects, and (iii) stations C and D of the Pine-Bogard transects. The fixed effects variables in each mixed effects model were Location (downstream vs upstream; or treated vs reference area), Time (before vs after conifer removal), and the interaction of Location and Time (Time x Location). A significant interaction would indicate the presence of a treatment effect. Because there was no reference area for canopy cover and solar radiation, the mixed effects models for these parameters included only the Time variable. The two random effects variables in each mixed effects model were Sample Unit and Year, as crossed random effects. Sample Unit was used as a random term in order to account for the autocorrelation introduced by repeated measures made at each stream monitoring location or soil moisture tension sensor. Year was used as a random term to account for the annual variation in the parameters driven by environmental factors that vary across years and can be expected to affect the variables similarly across all stations (e.g. temperature and precipitation), but which were not of interest to this study. LMEs (normal distribution, homogenous variance) were used for solar radiation, canopy cover, stream temperature, and soil moisture tension analysis. GLMMs (Poisson distribution) were used for all other parameters. Conformity to the assumptions associated with these analyses was confirmed with standard diagnostic tests and graphs. All analyses were conducted with Stata/SE software .
Results and Discussion
3.1: Water Quality
The modification of nutrient concentrations in streams through commercial timber harvest activities can alter aquatic ecosystem structure and function [34,43,45]. In particular, the levels of NO3-N, NH4-N, and PO4-P are of concern because increases in these nutrients have been found to cause eutrophication [60-62]. Additionally, increases of sediment levels in streams as a result of timber harvest activities have been found to modify streambed surface conditions, decrease light penetration, and alter primary production, which can have detrimental impacts on all forms of stream biota .
There were no statistically significant relationships between nutrient, turbidity, and TSS levels and the Time x Location interaction (P > 0.1 for all analyses; n = 275, 362, and 315 for each analysis at Pine, Bogard, and Bailey Creeks, respectively). This is in contrast to previous studies in which nutrient concentrations and sediment levels increased substantially following timber harvest activities [30,32,33,45,64,65]. These studies however involved the clear-cutting of large portions of the watershed. Our finding are consistent with studies on partial harvesting adjacent to streams and rivers with the implementation of BMPs, in which there are limited to no effects on nutrient concentrations or sediment levels [31-33,40-42,66].
The evaluation of NO3-N, NH4-N, and PO4-P across all stations and years at Pine, Bogard, and Bailey Creeks revealed extremely clean water conditions both before and after treatment implementation (Table 1). More than 80 % of all samples analyzed for NO3-N, NH4-N, and PO4-P were below the detection limit, with the exception of PO4-P in Bogard Creek, for which 14 % of samples were below the detection limit. The concentrations of nutrients measured across all stations from 2003 through 2010 are consistently below regulatory standards and similar to levels measured in unimpaired streams in the United States [67-69]. Such low levels of nutrients are characteristic of western montane forests [67,70-72].
|Creek||Nutrient||No. samples collected||No. samples < DLa||% Samples < DL||Mean of all samples||Mean of samples > DL|
Tables 2-7 report the TSS, turbidity, discharge, temperature, and nutrient levels observed on Pine, Bogard, and Bailey Creeks immediately upstream and downstream of treatment areas. Turbidity and TSS levels did rise and fall across years, however these changes were not associated with treatment implementation (Turbidity and TSS levels are illustrated in Figures S1, S2, S3, S4, S5 and S6) (Tables 2, 4, and 6). For example, the highest turbidity levels over the entire study period at Bailey Creek were observed in 2004, before conifer removal took place (Table 6). High temporal variability in sediments has been detected in previous studies on the effects of timber harvesting on water quality [27,45,66]. Such variation is a result of the fact that all streams naturally gain and lose sediment along their length, and this gain-loss will vary from year to year [73,74]. A functioning stream will ultimately achieve a balance between sediment gain and loss. Lastly, although peaks in turbidity and TSS do occur, such as at station BO5 in 2004 (Table 4), it should be noted that these relatively elevated turbidity and TSS levels consistently return to normal levels in stations located immediately downstream and do not reappear in following years. This indicates that the peaks in turbidity and TSS levels, whatever their cause, are limited both spatially and temporally.
|TSS||Turbidity||Discharge||Daily Water Temp|
|% Average annual||(mg L-1)||(ntu)||(m3 sec-1)||(°C)|
|Post Phase 1||2004||10||98||PC4||3.4||7.1||0.57||1.48||3||5||10||10||13|
|Post Phase 1||2005||12||110||PC4||2.4||9.4||0.29||1.03||5||8||14||10||14|
|Post Phase 2||2006||9||170||PC4||2.0||4.1||0.13||0.35||10||17||44||10||12|
|Post Phase 2||2007||9||73||PC4||2.4||10.0||0.28||1.08||2||3||10||11||16|
|Post Phase 3||2008||8||76||PC4||3.3||11.8||0.81||2.42||2||3||5||13||18|
|Post Phase 3||2009||9||99||PC4||3.8||5.3||0.32||0.76||3||5||7||12||16|
|Post Phase 3||2010||7||102||PC4||3.5||5.9||0.57||1.58||5||8||12||11||15|
|Treatment||Year||n=||Stationa||mg L-1||%<DLf||mg L-1||%<DL||mg L-1||%<DL||mg L-1||%<DL||mg L-1|
|Pre||2003||9||PC4||0.0025 (0)||100||0.025 (0)||100||0.005 (0)||100||0.01 (0)||67||1.39 (0.08)|
|PC3||0.003 (0.001)||88||0.025 (0)||100||0.01 (0)||75||0.01 (0)||25||1.38 (0.10)|
|PC1||0.0025 (0)||100||0.025 (0)||100||0.005 (0)||100||0.01 (0)||44||1.42 (0.10)|
|Post Phase 1||2004||10||PC4||0.003 (0)||90||0.025 (0)||100||0.005 (0)||100||0.10 (0.01)||0||1.28 (0.05)|
|PC3||0.0025 (0)||100||0.025 (0)||100||0.01 (0)||90||0.09 (0.01)||0||1.32 (0.08)|
|PC1||0.0025 (0)||100||0.025 (0)||100||0.005 (0)||100||0.08 (0.02)||30||1.36 (0.07)|
|Post Phase 1||2005||12||PC4||0.003 (0.001)||92||0.025 (0)||100||0.01 (0)||67||0.06 (0)||0||1.51 (0.07)|
|PC3||0.003 (0.001)||83||0.025 (0)||100||0.01 (0)||67||0.06 (0.01)||0||1.60 (0.14)|
|PC1||0.004 (0.001)||90||0.025 (0)||100||0.01 (0)||80||0.04 (0.01)||20||1.52 (0.08)|
|Post Phase 2||2006||9||PC4||0.019 (0.016)||89||0.025 (0)||100||0.005 (0)||100||0.11 (0.02)||22||1.30 (0.05)|
|PC3||0.0025 (0)||100||0.025 (0)||100||0.05 (0.04)||89||0.15 (0.02)||11||1.31 (0.05)|
|PC1||0.0025 (0)||100||0.025 (0)||100||0.005 (0)||100||0.11 (0.02)||22||1.29 (0.06)|
|Post Phase 2||2007||9||PC4||0.0025 (0)||100||0.04 (0.01)||89||0.005 (0)||100||0.08 (0.02)||33||1.50 (0.10)|
|PC3||0.0025 (0)||100||0.025 (0)||100||0.005 (0)||100||0.08 (0.01)||11||1.50 (0.09)|
|PC1||0.0025 (0)||100||0.025 (0)||100||0.005 (0)||100||0.07 (0.02)||20||1.86 (0.41)|
|Post Phase 3||2008||8||PC4||0.049 (0.032)||25||0.025 (0)||100||0.01 (0)||88||0.09 (0.01)||13||1.46 (0.08)|
|PC3||0.032 (0.013)||38||0.025 (0)||100||0.01 (0)||75||0.07 (0.02)||38||1.41 (0.07)|
|PC1||0.016 (0.011)||50||0.025 (0)||100||0.02 (0.01)||75||0.27 (0.13)||25||1.31 (0.09)|
|Post Phase 3||2009||9||PC4||0.003 (0)||89||0.025 (0)||100||0.01 (0)||89||0.09 (0.01)||0||1.32 (0.05)|
|PC3||0.0025 (0)||100||0.025 (0)||100||0.005 (0)||100||0.09 (0.01)||0||1.32 (0.04)|
|PC1||0.003 (0.001)||86||0.025 (0)||100||0.005 (0)||100||0.07 (0.02)||29||1.33 (0.12)|
|Post Phase 3||2010||7||PC4||0.004 (0.001)||71||0.025 (0)||100||0.01 (0.01)||86||0.10 (0.01)||0||1.29 (0.11)|
|PC3||0.008 (0.002)||43||0.04 (0.01)||86||0.01 (0)||86||0.09 (0.01)||0||1.30 (0.09)|
|PC1||0.006 (0.002)||67||0.025 (0)||100||0.005 (0)||100||0.04 (0.01)||33||1.46 (0.20)|
|TSS||Turbidity||Discharge||Daily Water Temp|
|% Average annual||mg L-1||ntu||(m3 sec-1)||(°C)|
|Post Phase 1||2004||10||98||BO5||16.3||35.3||2.71||5.23||0.8||1.5||2.4||9||14|
|Post Phase 1||2005||12||110||BO5||4.5||14.7||0.66||2.44||0.8||1.2||1.7||8||14|
|Post Phase 2||2006||10||170||BO5||3.3||8.8||0.38||0.88||3.1||4.9||7.1||8||10|
|Post Phase 2||2007||9||73||BO5||10.3||24.7||2.26||4.01||0.5||0.7||0.8||10||13|
|Post Phase 3||2008||8||76||BO5||5.3||15.9||2.01||5.71||0.2||0.2||0.3||12||18|
|Post Phase 3||2009||9||99||BO5||8.0||17.7||2.55||5.57||0.2||0.2||0.3||12||17|
|Post Phase 3||2010||7||102||BO5||5.2||10.0||1.26||2.99||0.2||1.0||2.2||11||16|
|Treatment||Year||n=||Stationa||mg L-1||%<DLf||mg L-1||%<DL||mg L-1||%<DL||mg L-1||%<DL||mg L-1|
|Pre||2003||9||BO5||0.0025 (0)||100||0.025 (0)||100||0.03 (0.01)||13||0.02 (0)||13||2.16 (0.10)|
|BO3||0.0025 (0)||100||0.025 (0)||100||0.03 (0.01)||11||0.03 (0)||0||2.25 (0.07)|
|BO1||0.0025 (0)||100||0.025 (0)||100||0.05 (0.02)||11||0.03 (0)||0||2.29 (0.20)|
|Post Phase 1||2004||10||BO5||0.003 (0.001)||80||0.025 (0)||100||0.01 (0)||40||0.18 (0.01)||0||1.99 (0.06)|
|BO3||0.0025 (0)||100||0.025 (0)||100||0.01 (0)||44||0.18 (0.01)||0||1.91 (0.04)|
|BO1||0.0025 (0)||100||0.025 (0)||100||0.01 (0)||44||0.16 (0.01)||0||1.95 (0.05)|
|Post Phase 1||2005||12||BO5||0.0025 (0)||100||0.025 (0)||100||0.04 (0)||0||0.13 (0.01)||0||2.27 (0.04)|
|BO3||0.004 (0.001)||83||0.025 (0)||100||0.04 (0)||0||0.12 (0.01)||0||2.16 (0.08)|
|BO1||0.003 (0)||92||0.025 (0)||100||0.04 (0)||0||0.13 (0.01)||0||2.12 (0.06)|
|Post Phase 2||2006||10||BO5||0.0025 (0)||100||0.025 (0)||100||0.04 (0.01)||0||0.23 (0.02)||0||2.06 (0.04)|
|BO3||0.0025 (0)||100||0.025 (0)||100||0.05 (0.01)||0||0.24 (0.02)||0||2.05 (0.05)|
|BO1||0.0025 (0)||100||0.025 (0)||100||0.04 (0.01)||0||0.25 (0.01)||0||2.03 (0.04)|
|Post Phase 2||2007||9||BO5||0.004 (0.001)||78||0.025 (0)||100||0.04 (0)||0||0.20 (0.01)||0||2.44 (0.31)|
|BO3||0.005 (0.003)||89||0.025 (0)||100||0.04 (0.01)||0||0.19 (0.01)||0||2.51 (0.26)|
|BO1||0.0025 (0)||100||0.025 (0)||100||0.03 (0)||0||0.20 (0.02)||0||2.34 (0.23)|
|Post Phase 3||2008||8||BO5||0.007 (0.003)||75||0.025 (0)||100||0.06 (0.01)||0||0.21 (0.01)||0||2.01 (0.04)|
|BO3||0.013 (0.006)||63||0.025 (0)||100||0.07 (0.01)||0||0.23 (0.02)||0||2.00 (0.11)|
|BO1||0.005 (0.002)||75||0.025 (0)||100||0.04 (0.01)||13||0.20 (0.01)||0||1.99 (0.11)|
|Post Phase 3||2009||9||BO5||0.019 (0.007)||44||0.025 (0)||100||0.03 (0.01)||22||0.17 (0.01)||0||1.86 (0.09)|
|BO3||0.016 (0.006)||56||0.025 (0)||100||0.01 (0)||56||0.18 (0.01)||0||1.87 (0.12)|
|BO1||0.021 (0.014)||67||0.025 (0)||100||0.01 (0)||44||0.16 (0.02)||11||1.82 (0.13)|
|Post Phase 3||2010||7||BO5||0.005 (0.001)||57||0.025 (0)||100||0.04 (0.01)||14||0.17 (0.02)||0||1.98 (0.10)|
|BO3||0.006 (0.002)||57||0.025 (0)||100||0.05 (0.01)||14||0.19 (0.01)||0||1.90 (0.13)|
|BO1||0.004 (0.001)||71||0.025 (0)||100||0.04 (0.01)||14||0.16 (0.01)||0||1.87 (0.14)|
|TSS||Turbidity||Discharge||Daily Water Temp|
|% Average annual||mg L-1||ntu||(m3 sec-1)||(°C)|
|Treatment||Year||n=||Stationa||mg L-1||%<DLg||mg L-1||%<DL||mg L-1||%<DL||mg L-1||mg L-1|
|Pre||2003||6||BR6||0.004 (0.001)||67||0.06 (0.02)||50||0.005 (0)||100||3.65 (0.52)||0.91 (0.22)|
|BR1||0.0025 (0)||100||0.06 (0.02)||60||0.005 (0)||100||3.19 (0.45)||0.74 (0.07)|
|Pre||2004||8||BR6||0.003 (0.001)||88||0.03 (0.01)||88||0.005 (0)||100||4.46 (0.59)||0.69 (0.07)|
|BR1||0.004 (0.001)||88||0.025 (0)||100||0.005 (0)||100||4.22 (0.51)||0.70 (0.07)|
|Pre||2006||7||BR6||0.009 (0.007)||86||0.025 (0)||100||0.005 (0)||100||3.99 (0.55)||0.75 (0.06)|
|September||BR1||0.0025 (0)||100||0.025 (0)||100||0.005 (0)||100||3.88 (0.50)||0.77 (0.07)|
|Post||2007||8||BR6||0.035 (0.032)||88||0.025 (0)||100||0.005 (0)||100||5.72 (0.54)||0.79 (0.06)|
|BR1||0.0025 (0)||100||0.04 (0.01)||75||0.005 (0)||100||5.35 (0.42)||0.86 (0.07)|
|Post||2008||9||BR6||0.0025 (0)||100||0.025 (0)||100||0.01 (0.01)||78||5.48 (0.65)||0.79 (0.05)|
|BR1||0.014 (0.010)||67||0.025 (0)||100||0.005 (0)||100||5.04 (0.53)||0.84 (0.06)|
|Post||2009||8||BR6||0.0025 (0)||100||0.025 (0)||100||0.005 (0)||100||4.85 (0.56)||0.74 (0.06)|
|BR1||0.0025 (0)||100||0.025 (0)||100||0.005 (0)||100||4.55 (0.50)||0.77 (0.07)|
|Post||2010||7||BR6||0.007 (0.003)||57||0.025 (0)||100||0.005 (0)||100||3.18 (0.57)||0.70 (0.07)|
|BR1||0.005 (0.001)||33||0.025 (0)||100||0.005 (0)||100||2.89 (0.51)||0.75 (0.08)|
Nutrient concentrations exhibited little variation between years and between stations (Tables 3, 5, and 7; Figures S7, S8, S9, S10, S11, S12, S13, S14, and S15). With the exception of PO4-P in Bogard Creek, the spatial and temporal consistency observed in nutrient concentrations is likely the result of the overall nutrient limitation of the creeks. The lack of variation in PO4-P levels between stations and years at Bogard Creek (Table 5; Figure S14) implies that the elevated PO4-P concentrations are a natural characteristic of Bogard Creek rather than the result of a treatment effect. As described in Section 2.1, Bogard Creek flow consists of a high fraction of sub-surface inputs, which can derive substantial quantities of P from soils and bedrock [67,75,76]. However, despite relatively elevated PO4-P concentrations, the low levels of N in Bogard Creek likely limit the potential of P to cause eutrophication .
3.2: Solar Radiation and Canopy Cover
Vegetative canopy cover is a critical factor in aquatic ecosystems because it blocks solar radiation reaching stream surfaces and thus moderates water temperature  and influences in-stream primary production [78,79]. Additionally, vegetative canopy cover also serves as an input of nutrients and organic matter to stream systems and provides physical habitat for stream biota [34,80].
There were no statistically significant changes in canopy cover along the treatment reaches of Pine Creek (PC4 to PC1) or Bogard Creek (BO5 to BO1)in response to Pine-Bogard Phase 2 conifer removal (P > 0.1; n = 74 and 76 at Pine and Bogard Creeks, respectively). Mean canopy cover at Pine Creek was 66 % before treatment and 64 % after treatment. Mean canopy cover at Bogard Creek was 64 % before treatment and 62 % after treatment. Correspondingly, there were no significant changes in the potential fraction of solar radiation arriving at each creek (P > 0.1; n = 74 and 76 at Pine and Bogard Creeks, respectively). Mean solar radiation values for the months of May through September at Pine Creek were 31, 33, 32, 26, and 21 % before treatment and 33, 33, 33, 31, and 25 % after treatment. Mean solar radiation values for the months of May through September at Bogard Creek were 36, 38, 37, 30, and 22 % before treatment and 40, 44, 42, 31, 20 % after treatment. The lack of significant change is not surprising, given that Phase 2 conifer removal occurred primarily outside of areas immediately adjacent to Pine and Bogard Creeks (Figure 2).
There were significant decreases in canopy cover along the treatment reaches of Pine Creek (PC1 to PC4) and Bogard Creek (BO1 to BO5) in response to Pine-Bogard Phase 3 conifer removal (P < 0.002; n = 106 at both Pine and Bogard Creeks ). Canopy cover decreased from a mean of 64 to 55 % along Pine Creek and from a mean of 64 to 39 % along Bogard Creek. Correspondingly, there was a significant increase in the potential fraction of solar radiation arriving at each reach (P < 0.005; n = 75 and 81 at Pine and Bogard Creeks, respectively). Figures 4a and b report the mean solar radiation results before and after January 2008 conifer removal. The magnitude of the increase in the potential fraction of solar radiation arriving at Pine Creek from the months of May through September ranged from 12 % in September to 25 % in June and July. The magnitude of the increase in the potential fraction of solar radiation arriving at Bogard Creek from the months of May through September ranged from 21 % in September to 27 % in June and July. The significant decreases in canopy cover and increases in solar radiation were expected, as Phase 3 conifer removal was carried out directly adjacent to Pine and Bogard Creeks.
(a) Pine Creek between stations PC4 and PC1 before (2005) and after (2008) January 2008 Phase 3 conifer removal, (b) Bogard Creek between stations BO5 and BO1 before (2005) and after (2008) January 2008 Phase 3 conifer removal, and (c) Bailey Creek between stations BR6 and BR1 before (2003) and after (2007) September 2006 conifer removal. * indicates significantly different at P<0.05. ** indicates significantly different at P<0.005.
Canopy cover significantly decreased from a mean of 64 to 55 % along the treatment reach of Bailey Creek (BR1 to BR6) in response to conifer removal (P < 0.005; n = 82). Correspondingly, there was a significant increase in the potential fraction of solar radiation arriving at Bailey Creek following treatment for the months of May through August (P < 0.01; n = 82). Figure 4c reports the mean solar radiation results before and after the September 2006 conifer removal. The magnitude of the increase in the potential fraction of solar radiation ranged from 5 % in August to 11 % in June. The significant decreases in canopy cover and increases solar radiation were expected, as portions of Bailey Creek conifer removal were carried out directly adjacent to the stream.
3.3: Stream Temperature
There was no statistically significant relationship between stream temperature and the Time x Location interaction in any of the creeks (P > 0.1 for all analyses; n = 276, 334, and 305 at Pine, Bogard, and Bailey Creeks, respectively). Figures 5-7 report the 7-day running average daily maximum water temperatures observed on the upstream and downstream stations of Pine, Bogard, and Bailey Creeks. Annual stream temperature patterns appear to be driven primarily by discharge, with higher temperatures occurring in years with lower flow. The data indicates a general pattern of increased temperature from upstream to downstream stations along each creek. Although the rate of increase in stream temperature from upstream to downstream stations varied annually, Figures 5-7 confirm that it was not associated with conifer removal treatments. For example, there was no change in the rate of increase from PC4 to PC1 or from BO5 to BO1 following Phase 3 conifer removal (Figures 5 and 6). Additionally, the rate of increase at Bailey Creek was similar both before (2003-2006) and after (2007) treatment (Figure 7). It then rose in 2008, but declined again in 2009 and 2010. The lack of correspondence between the rate of increase and treatment implementation implies that fluctuations in the primary drivers of stream temperature, including groundwater inputs, hyporheic flow, air temperature and discharge , are the source of variation in the rates of temperature change across years.
Station PC4 was located immediately upstream of the areas treated during Phases 1-3. Station PC3 was located immediately downstream of the areas treated during Phase 1, and station PC1 was located immediately downstream of the areas treated during Phases 2 and 3. Q = mean discharge (m3 min-1) from Jun 15 – Aug 31, P = percent of mean annual precipitation, Max AT = mean of daily maximum air temperature (°C) from Jun 15 – Aug 31, AT = mean of average daily air temperature (°C) from Jun 15 – Aug 31.
Station BO5 was located immediately upstream of the areas treated during Phases 1-3. Station BO3 was located immediately downstream of the areas treated during Phase 1, and station BO1 was located immediately downstream of the areas treated during Phases 2 and 3. Q = mean discharge (m3 min-1) from June 15 - August 31, P = percent of mean annual precipitation, Max AT = mean of daily maximum air temperature (°C) from June 15 - August 31, AT = mean of average daily air temperature (°C) from June 15 - August 31. Note: the temperature logger for station BO1 in 2004 was broken, so the 2004 figure shows data collected at station BO2.
Stations BR6 and BR1 were located immediately upstream and downstream of the areas treated during the Bailey Project, respectively. Q = mean discharge (m3 min-1) from Jun 15 – Aug 31, P = percent of mean annual precipitation, Max AT = mean of daily maximum air temperature (°C) from Jun 15 – Aug 31, AT = mean of average daily air temperature (°C) from Jun 15 – Aug 31.
A response in stream temperature to treatment implementation was not expected to Pine-Bogard Phase 1 and Phase 2 conifer removal, as these treatments occurred primarily outside of areas immediately adjacent to the creeks (Figure 2) and Phase 2 was found to have no significant impact on canopy cover or the potential fraction solar radiation reaching the creeks. However, the Pine-Bogard Phase 3 and Bailey treatments significantly decreased canopy cover and increased the potential fraction of solar radiation reaching the creeks, and therefore had the potential to increase downstream temperatures. There are several possible reasons for the lack of response. First, the decrease in canopy cover was minimal at Pine and Bailey Creeks (9 % and 7 % decrease, respectively). Previous studies with similar reductions in canopy cover also found no temperature response [36,66,81,82]. Second, there was still a substantial amount of canopy cover remaining at Pine Creek (55 %), Bogard Creek (39 %), and Bailey Creek (45 %) which likely provided sufficient shading to continue to moderate stream temperature. Third, at Bailey Creek, stream temperature change is likely buffered by the relatively high, cool flows that characterize the creek all season-long (Table 7). Fourth, as discussed below, the soil moisture tension data indicates that soil moisture increased as a result of vegetation removal, and this implies that there may have been an increase in water inputs to the streams that helped to buffer stream temperature from potential increases in solar radiation inputs [8,36,83]. Lastly, it is likely that the affected reach lengths at each creek were not long enough to allow for a water residence time that could result in increased temperatures. This may particularly be the case at Bogard Creek, where there was a 35 % decrease in canopy cover, and therefore an increase in temperature was expected. A shorter residence time lessens the potential for water passing through a reach to be influenced by solar radiation arriving at that reach. Chizinski et al.  and Hemstad et al.  also hypothesized that the relatively short reach lengths impacted by harvest activities adjacent to streams are one of the reasons that they found no adverse effects on aquatic ecosystem parameters.
For the purposes of aspen restoration, the scale of the timber harvest areas in this study would likely be among the largest that would be carried out should this method be applied throughout this region. This implies that the future application of these aspen restoration treatments would be unlikely to increase stream temperatures; however, projects that involve timber harvesting along longer stream reaches than those investigated in this study should monitor stream temperatures and take measures to limit potential impacts, such as leaving ample understory for shading [36,66]. In general, studies in which the clear-cutting of watersheds took place both with and without riparian buffers have shown significant increases in temperature [84,85]. In contrast, the results of our project are consistent with studies in which partial harvesting in areas adjacent to streams and rivers was carried out following BMPs, which prevented or significantly limited stream temperature changes [36,41,66,86,87].
Minimizing increases in stream temperature is a critical part of maintaining aquatic ecosystem health for stream biota. Increases in stream temperature have been found to alter macroinvertebrate abundance and community structure [43,88]. Additionally, high temperatures can substantially decrease cold-water fish populations . Studies have found that the optimal temperatures for rainbow trout (Oncorhynchus mykiss), which is the native trout species in the region, range from 16 to 18 °C, and that the upper incipient lethal temperature for rainbow trout is approximately 25 °C . Tables 2, 4, and 6 indicate mean stream temperatures did not exceed the optimal range during the course of this study, and Figures 5-7 indicate that maximum stream temperatures did not exceed the upper incipient lethal temperature. The highest temperatures observed at any of the sites throughout the course of this study occurred in Bogard Creek during the low-flow years from 2007 through 2009 (Figure 6). Despite these elevated temperatures, there was an abundance of trout in Bogard Creek during this time period, reflecting the suitability of these creeks to provide habitat for cold water fish even with timber harvesting activities .
3.4: Aquatic Macroinvertebrate Metrics
Table 8 reports key aquatic macroinvertebrate metrics calculated from collections made on Pine, Bogard, and Bailey Creeks. A high value of the percent of the macroinvertebrate community tolerant of pollution (% Tolerant) is an indicator of poor aquatic ecosystem health. Conversely, high values of (i) the percent of the macroinvertebrate community not tolerant of pollution (% Intolerant), (ii) of the Shannon Diversity Index, and (iii) of the number of families detected (No. Families) are indicators of good aquatic ecosystem health. There were no statistically significant relationships between these metrics and the Time x Location interaction (P > 0.1; n = 10 for the analysis of each parameter at each creek).
|Midstream stationb||Upstream stationc|
The results indicate healthy in-stream habitat conditions across all three creeks throughout the course of this study. The value of % Tolerant was zero in 93 % of the samples collected across all stations and years. The highest value of % Tolerant was 0.2 % measured in 2003 at midstream station PC3 prior to treatment implementation. At each creek, the Shannon Diversity Index, No. Families, and % Intolerant varied from year to year, but variation of similar magnitudes occurred at all stations (upstream and midstream), and the annual changes were not indicative of a decline in aquatic ecosystem health in response to conifer removal treatments. These results parallel the findings of the Kreutzweiser et al.  study, which found that most changes in macroinvertebrate community metrics before versus after partial timber harvesting adjacent to two watershed streams were similar in magnitude to the changes detected at the reference watershed and concluded that the timber harvest activities studied did not cause degradation of macroinvertebrate community structure and function. Similarly, studies by Chizinski et al.  and Gravelle et al.  found high annual variation in macroinvertebrate metrics but no treatment effect in response to partial timber harvesting or clear cutting activities. Strong temporal variability in macroinvertebrate metrics has been commonly observed in aquatic ecosystems, particularly in response to high annual variation in rainfall, which is characteristic of Mediterranean climates [92-94]. This implies that the variability detected in this study reflects site specific responses to annual climatic variation rather than the effects of conifer removal treatments.
Although strong temporal variability can mask treatment effects [95,96], the apparent lack of response of macroinvertebrate metrics to conifer removal treatments is likely the result of a lack of treatment effect on key stream characteristics. Timber harvest activities affect stream macroinvertebrate communities through several mechanisms. Aquatic macroinvertebrate community structure and function has been found to be degraded by increases in stream temperature due to reductions in canopy cover, by nutrient enrichment due to soil disturbance, and by fine inorganic sediment loading following timber harvesting [34,97,98]. Previous studies in which temperatures, sediments, and algae increased following timber harvest activities found negative impacts on the stream macroinvertebrate communities [38,78,99]. In contrast, stream parameters showed little to no response to the timber harvest activities carried out in the studies by Chizinski et al. , Hemstad et al. , and Kreutzweiser et al. . Correspondingly, there were no adverse effects detected on stream biota. In this study, stream temperature, nutrient concentrations, and TSS and turbidity levels did not respond to treatment implementation. As a result, the lack of response of macroinvertebrate metrics to conifer removal treatments is not surprising.
3.5: Soil Moisture Tension
The statistical analysis results show that the difference between soil moisture tension in treatment and reference transects increased significantly at both depths in response to the Bailey Project (P < 0.001; n = 725 and 690 at the 15 and 45 cm depths, respectively) and in response to Phase 2 (P < 0.001; n = 666 and 662 at the 15 and 45 cm depths, respectively) and Phase 3 (P < 0.001; n = 677 and 678 at the 15 and 45 cm depths, respectively) of the Pine-Bogard Project. In response to Phase 2 conifer removal, the difference between treatment and reference soil moisture tension increased by 48 and 38 kPa at the 15 and 45 cm depths, respectively. Similarly, in response to Phase 3 conifer removal, the difference between treatment and reference soil moisture tension increased by 31 and 87 kPa at the 15 and 45 cm depths, respectively. Lastly, in response to Bailey Project conifer removal, the difference between treatment and reference soil moisture tension increased by 47 and 67 kPa at the 15 and 45 cm depths, respectively.
The soil moisture tension data illustrated in Figures 8-10 corroborates the results of the statistical analysis and shows that soil moisture in treatment transects increased relative to soil moisture in reference transects at both soil depths. At the Pine-Bogard location, soil moisture tension at both depths was lower (i.e. soil moisture was higher) in the treatment transects than in the reference transects throughout the course of this study (Figures 8 and 9). However, the reference transects exhibited a higher rate of drying relative to treatment transects following both Phase 2 and Phase 3 conifer removal. This trend is particularly evident in the lowest precipitation years from 2007 through 2009 following Phase 2 treatment (Figure 8). During this period, soil moisture tension in reference transects increased (i.e. soil moisture decreased) at a rapid rate relative to previous years, while soil moisture tension in treatment transects showed relatively little response to the drought conditions. At Bailey Creek, soil moisture tension at both depths was higher (i.e. soil moisture was lower) in the treatment transects than in the reference transects prior to treatment implementation (Figure 10). Following conifer removal in September 2006 however, soil moisture tension was lower (i.e. soil moisture was higher) in the treatment transects than in the reference transects.
Measurements were made at the 15 and 45 cm depths at Stations C and D of the reference and treatment transects. % P = percent of mean annual precipitation. Lower values of soil moisture tension correspond to wetter soils.
Measurements were made at the 15 and 45 cm depths at Stations A and B of the reference and treatment transects. % P = percent of mean annual precipitation. Lower values of soil moisture tension correspond to wetter soils.
Measurements were made at the 15 and 45 cm depths. % P = percent of mean annual precipitation. Lower values of soil moisture tension correspond to wetter soils.
The greater retention of soil moisture within treatment transects is most likely the result of the removal of vegetation causing a reduction in transpiration , which sustains high soil moisture levels into the dry season. Additionally, the increase in soil moisture could be the result of a decrease in snow sublimation and increase in snow water equivalent (i.e. snow accumulation) that occurs when forest canopy cover decreases [100-103]. Increases in soil moisture in response to timber harvesting have been observed in multiple studies, though, in the long-term, soil moisture levels decrease as vegetation regrows [25,26]. Within conifer-encroached aspen stands however, high soil moisture levels have the potential to be sustained if the site is successfully recolonized by aspen, because mature conifer forests use more water than mature aspen forests [8,104] and because, as a result of higher canopy interception by confers, conifer forests have lower snow water equivalent than deciduous forests [8,103,105,106]. Elevated soil moisture relative to conifer stands is one of the potential factors causing high diversity and productivity in the herbaceous understory of aspen stands [2,107].
The results of this study suggest that, with careful consideration of site specific conditions and implementation of appropriate best management practices, conifer removal through commercial timber harvesting for the purposes of restoring aspen stands in the southern Cascades can be implemented without degrading the aquatic ecosystem parameters measured. More than 80 % of all stream water samples analyzed for NO3-N, NH4-N, and PO4-P at Pine, Bogard, and Bailey Creeks were below the detection limit, with the exception of PO4-P in Bogard Creek, in which concentrations were elevated due to the spring source of the streamwater. There was no significant increase in the difference between upstream and downstream turbidity, TSS, NO3-N, NH4-N, PO4-P, K, and SO4-S levels before versus after treatment. There was a significant decrease in canopy cover and increase in the potential fraction of solar radiation reaching the creeks in response to the Pine-Bogard Phase 3 and Bailey treatments; however, there was no corresponding increase in the difference between upstream and downstream temperatures. Macroinvertebrate metrics confirmed the water quality results, with the highest level of % Tolerant species being 0.2 % at Pine Creek prior to treatment implementation. Lastly, soil moisture tension measurements indicate that there was a significant increase in soil moisture in treated aspen stands relative to untreated stands. Although a large body of literature exists in which timber harvest activities were found to impair water quality and aquatic ecosystem functions, the findings of this study concur with recent studies in which the partial harvesting of areas near streams and rivers with the implementation of BMPs was conducted without the degradation of aquatic ecosystems.
Mean and standard error of turbidity levels for Pine Creek sample stations (2003-2010). Q = mean annual discharge (m3 min-1) measured from June 15 through August 31. P = percent of mean annual precipitation.
Mean and standard error of turbidity levels for Bogard Creek sample stations (2003-2010). Q = mean annual discharge (m3 min-1) measured from June 15 through August 31. P = percent of mean annual precipitation.
Mean and standard error of turbidity levels for Bailey Creek sample stations (2003-2004, 2006-2010). Q = mean annual discharge (m3 min-1) measured from June 15 through August 31. P = percent of mean annual precipitation.
Mean and standard error of total suspended sediment (TSS) concentrations for Pine Creek sample stations (2003-2010). Q = mean annual discharge (m3 min-1) measured from June 15 through August 31. P = percent of mean annual precipitation.
Mean and standard error of total suspended sediment (TSS) concentrations for Bogard Creek sample stations (2003-2010). Q = mean annual discharge (m3 min-1) measured from June 15 through August 31. P = percent of mean annual precipitation.
Mean and standard error of total suspended sediment (TSS) concentrations for Bailey Creek sample stations (2003-2004, 2006-2010). Q = mean annual discharge (m3 min-1) measured from June 15 through August 31. P = percent of mean annual precipitation.
Mean and standard error of NO3-N concentrations for Pine Creek sample stations (2003-2010). Q = mean annual discharge (m3 min-1) measured from June 15 through August 31. P = percent of mean annual precipitation.
Mean and standard error of NO3-N concentrations for Bogard Creek sample stations (2003-2010). Q = mean annual discharge (m3 min-1) measured from June 15 through August 31. P = percent of mean annual precipitation.
Mean and standard error of NO3-N concentrations for Bailey Creek sample stations (2003-2004, 2006-2010). Q = mean annual discharge (m3 min-1) measured from June 15 through August 31. P = percent of mean annual precipitation.
Mean and standard error of NH4-N concentrations for Pine Creek sample stations (2003-2010). Q = mean annual discharge (m3 min-1) measured from June 15 through August 31. P = percent of mean annual precipitation.
Mean and standard error of NH4-N concentrations for Bogard Creek sample stations (2003-2010). Q = mean annual discharge (m3 min-1) measured from June 15 through August 31. P = percent of mean annual precipitation.
Mean and standard error of NH4-N concentrations for Bailey Creek sample stations (2003-2004, 2006-2010). Q = mean annual discharge (m3 min-1) measured from June 15 through August 31. P = percent of mean annual precipitation.
Mean and standard error of PO4-P concentrations for Pine Creek sample stations (2003-2010). Q = mean annual discharge (m3 min-1) measured from June 15 through August 31. P = percent of mean annual precipitation.
Mean and standard error of PO4-P concentrations for Bogard Creek sample stations (2003-2010). Q = mean annual discharge (m3 min-1) measured from June 15 through August 31. P = percent of mean annual precipitation.
Mean and standard error of PO4-P concentrations for Bailey Creek sample stations (2003-2004, 2006-2010). Q = mean annual discharge (m3 min-1) measured from June 15 through August 31. P = percent of mean annual precipitation.
Pine-Bogard Project Phase 1 treatment area (pre-treatment). Photo taken in 2003.
Pine-Bogard Project Phase 1 treatment area (post-treatment). Photo taken in 2004, during the first summer after treatment.
Pine-Bogard Project Phase 1 treatment area (post-treatment). Photo taken in 2007, 4 years after treatment.
Pine-Bogard Project Phase 2 treatment area. Right side of photo illustrates untreated conifer density, and left side of photo illustrates post-treatment conditions. Photo taken September 2005, immediately following treatment implementation.
Pine-Bogard Project Phase 3 treatment area prior to conifer thinning. All blue marked trees were removed, as we all small unmarked trees (< 30 cm DBH). The green of Pine Creek’s riparian area can be seen directly behind the conifer trees marked for removal. Photo taken in 2005.
Pine-Bogard Project Phase 3 treatment area (post-treatment). Photo taken in 2008, during the first summer after treatment.
Pine-Bogard Project Phase 3 treatment area (post-treatment). Photo taken in 2013, 5 years after treatment.
Bailey Project (pre-treatment). Photo taken in 2003.
Bailey Project (post-treatment). Photo taken in 2008, 2 years after treatment.
We thank the many field assistants who collected all the valuable data, especially, Shannon Cler and Sarah Hubert; Natalie Stoddard, Betsy Huang, and Yukako Sado for sample analysis and data management; Melanie McFarland, Tom Rickman, Coye Burnett, Dave Burton, and Alfred Vazquez for their contributions, support, advice, and encouragement throughout this project; and the Quincy Library Group for their support.
Conceived and designed the experiments: BEJ KWT. Performed the experiments: BEJ KWT. Analyzed the data: KWT MK. Contributed reagents/materials/analysis tools: KWT BEJ. Wrote the manuscript: MK.
- 1. Perala DA (1991) Populus tremuloides Michx. In: RM BurnsBH Honkala. Handbook 654, Silvics of North America, Volume 2, Hardwoods. Washington DC: U.S. Department of Agriculture. pp. 555-569.
- 2. Kuhn TJ, Safford HD, Jones BE, Tate KW (2011) Aspen (Populus tremuloides) stands and their contribution to plant diversity in a semiarid coniferous landscape. Plant Ecology 212: 1451-1463. doi:https://doi.org/10.1007/s11258-011-9920-4.
- 3. Johns BW (1993) The influence of grove size on bird species richness in aspen parklands. Wilson Bulletin 105: 256-264.
- 4. Griffis-Kyle KL, Beier P (2003) Small isolated aspen stands enrich bird communities in southwestern ponderosa pine forests. Biological Conservation 110: 375-385. doi:https://doi.org/10.1016/S0006-3207(02)00237-9.
- 5. Richardson TW, Heath SK (2004) Effects of conifers on aspen-breeding bird communities in the Sierra Nevada. Trans Western Sect Wildlife Soc 40: 68-81.
- 6. Debyle NV (1985) Wildlife. In: NV DeByleRP Winokur. Aspen: ecology and management in the western United States. General Technical Report RM-119. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky . Mountain Forest and Range Experiment Station. pp. 135-152.
- 7. Jones JR, DeByle NV, Bowers DM (1985) Insects and other invertebrates. In: NV DeByleRP Winokur. Aspen: ecology and management in the western United States. General Technical Report RM-119. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky . Mountain Forest and Range Experiment Station. pp. 107-114.
- 8. LaMalfa EM, Ryle R (2008) Differential snowpack accumulation and water dynamics in aspen and conifer communities: implications for water yield and ecosystem function. Ecosystems 11: 569-581. doi:https://doi.org/10.1007/s10021-008-9143-2.
- 9. Fechner GH, Barrows HS (1976) Aspen stands as wildfire fuel breaks. Eisenhower Consortium Bulletin 4. Available: . http://digitalcommons.usu.edu/aspen_bib/5029/. Accessed 5 December 2013.
- 10. Kilpatrick S, Clause D, Scott D (2003) Aspen response to prescribed fire, mechanical treatments, and ungulate herbivory. In: PN OmiLA Joyce. Fire, fuel treatments, and ecological restoration: conference proceedings 16-18 April 2002. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky . Mountain Forest and Range Experiment Station. pp. 93-102.
- 11. Smith AE, Smith FW (2005) Twenty-year change in aspen dominance in pure aspen and mixed aspen/conifer stands on the Uncompahgre Plateau, Colorado, USA. Forest Ecology and Management 213: 338-348. doi:https://doi.org/10.1016/j.foreco.2005.03.018.
- 12. Rogers P (2002) Using Forest Health Monitoring to assess aspen forest cover change in the southern Rockies ecoregion. Forest Ecology and Management 155: 223-236. doi:https://doi.org/10.1016/S0378-1127(01)00560-6.
- 13. Calder WJ, Horn KJ, St Clair SB (2011) Conifer expansion reduces the competitive ability and herbivore defense of aspen by modifying light environment and soil chemistry. Tree Physiol 31: 582-591. doi:https://doi.org/10.1093/treephys/tpr041. PubMed: 21602559.
- 14. Rehfeldt GE, Ferguson DE, Crookston NL (2009) Aspen, climate, and sudden decline in western USA. Forest Ecology and Management 258: 2353-2364. doi:https://doi.org/10.1016/j.foreco.2009.06.005.
- 15. Bartos DL, Campbell RB Jr. (1998) Decline of quaking aspen in the Interior West: examples from Utah. Rangelands 20: 17-24.
- 16. Jones BE, Lile DF, Tate KW (2009) Effect of simulated browsing on aspen regeneration: implications for restoration. Rangeland Ecology and Management 62: 557-56310.2111/.1/REM-D-09-00082.1.
- 17. Pierce AD, Taylor AH (2010) Competition and regeneration in quaking aspen-white fir (Populus tremuloides-Abies concolor) forests in the Northern Sierra Nevada, USA. Journal of Vegetation Science 21: 507-519. doi:https://doi.org/10.1111/j.1654-1103.2009.01158.x.
- 18. Shepperd WD, Rogers PC, Burton D, Bartos DL (2006) Ecology, biodiversity, management, and restoration of aspen in the Sierra Nevada, General Technical Report RMRS-GTR-178. Fort Collins, CO: U.S. Department of Agriculture Forest Service, Rocky Mountain Forest and Range Experiment Station. p. 122.
- 19. Smith EA, O’Loughlin D, Buck JR, St Clair SB (2011) The influences of conifer succession, physiographic conditions and herbivory on quaking aspen regeneration after fire. Forest Ecology and Management 262: 325-330. doi:https://doi.org/10.1016/j.foreco.2011.03.038.
- 20. Doucet R (1989) Regeneration silviculture of aspen. Forestry Chronicle 65: 23-27.
- 21. Fraser EC, Lieffers VJ, Landhausser SM, Frey BR (2002) Soil nutrition and temperature as drivers of root suckering in trembling aspen. Canadian Journal Forest Research-Revue Canadienne de Recherche Forestiere 32: 1685-1691. doi:https://doi.org/10.1139/x02-080.
- 22. Jones BE, Rickman TH, Vazquez A, Sado Y, Tate KW (2005) Removal of encroaching conifers to regenerate degraded aspen stands in the Sierra Nevada. Restoration Ecology 13: 373-379. doi:https://doi.org/10.1111/j.1526-100X.2005.00046.x.
- 23. Shepperd WD (2001) Techniques to restore aspen forests in the western U.S. Trans Western Sect Wildlife Soc 40: 52-60.
- 24. White CA, Olmsted CE, Kay CE (1998) Aspen, elk, and fire in the Rocky Mountain national parks of North America. Wildlife Society Bulletin 26: 449-462.
- 25. Adams PW, Flint AL, Fredriksen RL (1991) Long-term patterns in soil-moisture and revegetation after a clear-cut of a douglas-fir forest in Oregon. Forest Ecology and Management 41: 249-263. doi:https://doi.org/10.1016/0378-1127(91)90107-7.
- 26. Gray AN, Spies TA, Easter MJ (2002) Microclimatic and soil moisture responses to gap formation in coastal Douglas-fir forests. Canadian Journal Forest Research-Revue Canadienne de Recherche Forestiere 32: 332-343. doi:https://doi.org/10.1139/x01-200.
- 27. Croke JC, Hairsine PB (2006) Sediment delivery in managed forests: a review. Environmental Reviews 14: 59-87. doi:https://doi.org/10.1139/a05-016.
- 28. Tremblay Y, Rousseau AN, Plamondon AP, Levesque D, Prevost M (2009) Changes in stream water quality due to logging of the boreal forest in the Montmorency Forest, Quebec. Hydrological Processes 23: 764-776. doi:https://doi.org/10.1002/hyp.7175.
- 29. Bolda KS, Meyers WJ (1997) Conducting a long-term water quality monitoring project: A case study on the McCloud River. California. Journal-- Journal of Soils and Water Conservation 52: 49-54.
- 30. Klein RD, Lewis J, Buffleben MS (2012) Logging and turbidity in the coastal watersheds of northern California. Geomorphology 139: 136-144.
- 31. Litschert SE, MacDonald LH (2009) Frequency and characteristics of sediment delivery pathways from forest harvest units to streams. Forest Ecology and Management 259: 143-150. doi:https://doi.org/10.1016/j.foreco.2009.09.038.
- 32. Karwan DL, Gravelle JA, Hubbart JA (2007) Effects of timber harvest on suspended sediment loads in Mica Creek, Idaho. Forest Science 53: 181-188.
- 33. Gravelle JA, Ice G, Link TE, Cook DL (2009) Nutrient concentration dynamics in an inland Pacific Northwest watershed before and after timber harvest. Forest Ecology and Management 257: 1663-1675. doi:https://doi.org/10.1016/j.foreco.2009.01.017.
- 34. Campbell IC, Doeg TJ (1989) Impact of timber harvesting and production on streams - a review. Australian Journal of Marine and Freshwater Research 40: 519-539. doi:https://doi.org/10.1071/MF9890519.
- 35. Poole GC, Berman CH (2001) An ecological perspective on in-stream temperature: Natural heat dynamics and mechanisms of human-caused thermal degradation. Environ Manage 27: 787-802. doi:https://doi.org/10.1007/s002670010188. PubMed: 11393314.
- 36. Gravelle JA, Link TE (2007) Influence of timber harvesting on headwater peak stream temperatures in a northern Idaho watershed. Forest Science 53: 189-205.
- 37. Herlihy AT, Gerth WJ, Li J, Banks JL (2005) Macroinvertebrate community response to natural and forest harvest gradients in western Oregon headwater streams. Freshwater Biology 50: 905-919. doi:https://doi.org/10.1111/j.1365-2427.2005.01363.x.
- 38. Reid DJ, Quinn JM, Wright-Stow AE (2010) Responses of stream macroinvertebrate communities to progressive forest harvesting: Influences of harvest intensity, stream size and riparian buffers. Forest Ecology and Management 260: 1804-1815. doi:https://doi.org/10.1016/j.foreco.2010.08.025.
- 39. Gravelle JA, Link TE, Broglio JR, Braatne JH (2009) Effects of Timber Harvest on Aquatic Macroinvertebrate Community Composition in a Northern Idaho. Watershed - Forest Science 55: 352-366.
- 40. Hotta N, Kayama T, Suzuki M (2007) Analysis of suspended sediment yields after low impact forest harvesting. Hydrological Processes 21: 3565-3575. doi:https://doi.org/10.1002/hyp.6583.
- 41. Kreutzweiser DR, Capell SS, Good KP (2005) Macroinvertebrate community responses to selection logging in riparian and upland areas of headwater catchments in a northern hardwood forest. Journal of the North American Benthological Society 24: 208-222. doi:https://doi.org/10.1899/0887-3593(2005)024.
- 42. Wang X, Burns DA, Yanai RD, Briggs RD, Germain RH (2006) Changes in stream chemistry and nutrient export following a partial harvest in the Catskill Mountains, New York, USA. Forest Ecology and Management 223: 103-112. doi:https://doi.org/10.1016/j.foreco.2005.10.060.
- 43. Hutchens JJ Jr., Batzer DP, Reese E (2003) Bioassessment of silvicultural impacts in streams and wetlands of the eastern United States. Water Air, Soil Pollut 00: 1-17.
- 44. Macdonald JS, Beaudry PG, MacIsaac EA, Herunter HE (2003) The effects of forest harvesting and best management practices on streamflow and suspended sediment concentrations during snowmelt in headwater streams in sub-boreal forests of British Columbia, Canada. Canadian Journal Forest Research-Revue Canadienne de Recherche Forestiere 33: 1397-1407. doi:https://doi.org/10.1139/x03-110.
- 45. Martin CW, Hornbeck JW (2000) Impacts of intensive harvesting on hydrology and nutrient dynamics of northern hardwood forests. Canadian Journal of Fisheries and Aquatic Sciences 57: 19-29. doi:https://doi.org/10.1139/f00-106.
- 46. Barbour MT, Gerritsen J, Snyder BD, Stribling JB (1999) Chapter 7.1 single habitat approach: 1-meter kick net. Rapid bioassessment protocols for use in streams and wadeable rivers: periphyton, benthic macroinvertebrates and fish - Second Edition EPA 841-B-99-002. Washington DC: United States Environmental Protection Agency, Office of Water.
- 47. Western Regional Climate Center (2012) Manzanita Lake Period of Record General Climate Summary - Precipitation. Available: . http://www.wrcc.dri.edu/cgi-bin/cliMAIN.pl?ca5311. Accessed 4 July 2013.
- 48. PRISM Climate Group (2010) PRISM Data Explorer. Oregon State University. Available: . http://prismmap.nacse.org/nn/index.phtml. Accessed 24 February 2012.
- 49. Mosley MP, McKercher AI (1993) Streamflow. In: DR Maidment. Handbook of hydrology. New York: McGraw-Hill. pp. 8.1-8.39.
- 50. Eaton AD, Clesceri LS, Rice EW, Greenberg AE, Franson MAH (2005) Standard methods for the examination of water and wastewater: centennial edition. Washington DC: American Public Health Association. 1368 pp.
- 51. Flosi G, Downie S, Hopelain J, Bird M, Coey R, et al. (1998) California salmonid stream habitat restoration handbook: Appendix M, specialty instruments. California Department of Fish and Game. Available: . http://www.dfg.ca.gov/fish/resources/habitatmanual.asp. Accessed 25 May 2012.
- 52. Platts WS, Armour C, Booth GD, Bryant M, Bufford JL et al. (1987) Methods for evaluating riparian habitats with applications to management. USDA Forest Service General Technical Report INT-221. Available: . http://www.fort.usgs.gov/Products/Publications/3581/3581.pdf. Accessed 17 Febuary 2012.
- 53. Moulton SR II, Carter JL, Grotheer SA, Cufney TF, Short TM (2000) Methods of analysis by the U.S. Geological Survey National Water Quality Laboratory - processing, taxonomy, and quality control of benthic macroinvertebrate samples. United States Geological Survey Open-File Report 00-212. Available: . http://nwql.usgs.gov/OFR-00-212.shtml. Accessed 17 Febuary 2012.
- 54. Cuffney TF, Gurtz ME, Meador MR (1993) Methods for collecting benthic invertebrate samples as part of the National Water-Quality Assessment Program. United States Geological Survey Open-File Report 93-406. Available: . http://nc.water.usgs.gov/reports/abstracts/ofr93406.html. Accessed 17 Febuary 2012.
- 55. Fowler WB, Lopushinsky W (1989) An economical, digital meter for gypsum soil-moisture blocks. Soil Science Society Of America Journal 53: 302-305. doi:https://doi.org/10.2136/sssaj1989.03615995005300010057x.
- 56. Pinheiro JC, Bates DM (2000) Mixed-Effects Models in S and S-PLUS. New York: Springer.
- 57. Rabe-Hesketh S, Skrondal A (2008) Multilevel and Longitudinal Modeling Using Stata. College Station, TX: Stata Press.
- 58. Roche LM, Allen-Diaz B, Eastburn DJ, Tate KW (2012) Cattle grazing and Yosemite toad (Bufo canorus Camp) breeding habitat in Sierra Nevada meadows. Rangeland Ecology and Management 65: 56-65. doi:https://doi.org/10.2111/REM-D-11-00092.1.
- 59. StataCorp (2009) Stata/SE 11.1 for Windows. College Station, TX: StataCorp LP.
- 60. Fenn ME, Baron JS, Allen EB, Rueth HM, Nydick KR et al. (2003) Ecological effects of nitrogen deposition in the western United States. Journal of Biosciences 53: 404-420. Available online at: doi:https://doi.org/10.1641/0006-3568(2003)053[0404:EEONDI]2.0.CO;2
- 61. Nijboer RC, Verdonschot PFM (2004) Variable selection for modelling effects of eutrophication on stream and river ecosystems. Ecological Modelling 177: 17-39. doi:https://doi.org/10.1016/j.ecolmodel.2003.12.050.
- 62. Sickman JO, Melack JM, Clow DW (2003) Evidence for nutrient enrichment of high-elevation lakes in the Sierra Nevada, California. Limnology and Oceanography 48: 1885-1892. doi:https://doi.org/10.4319/lo.2003.48.5.1885.
- 63. Wood PJ, Armitage PD (1997) Biological effects of fine sediment in the lotic environment. Environ Manage 21: 203-217. doi:https://doi.org/10.1007/s002679900019. PubMed: 9008071.
- 64. Jewett K, Daugharty D, Krause HH, Arp PA (1995) Watershed responses to clear-cutting: Effects on soil solutions and stream water discharge in central New Brunswick. Canadian Journal of Soil Science 75: 475-490. doi:https://doi.org/10.4141/cjss95-069.
- 65. Swank WT, Vose JM, Elliott KJ (2001) Long-term hydrologic and water quality responses following commercial clearcutting of mixed hardwoods on a southern Appalachian catchment. Forest Ecology and Management 143: 163-178. doi:https://doi.org/10.1016/S0378-1127(00)00515-6.
- 66. Kreutzweiser D, Capell S, Good K, Holmes S (2009) Sediment deposition in streams adjacent to upland clearcuts and partially harvested riparian buffers in boreal forest catchments. Forest Ecology and Management 258: 1578-1585. doi:https://doi.org/10.1016/j.foreco.2009.07.005.
- 67. Binkley D, Ice GG, Kaye J, Williams CA (2004) Nitrogen and phosphorus concentrations in forest streams of the United States. J Am Water Resour As 40: 1277-1291. doi:https://doi.org/10.1111/j.1752-1688.2004.tb01586.x.
- 68. Dubrovsky NM, Burow KR, Clark GM, Gronberg JM, et al H. (2010) The quality of our nation’s waters - nutrients in the nation’s streams and groundwater, 1992–2004. United States Geological Survey Circular 1350.
- 69. Powlson DS, Addiscott TM, Benjamin N, Cassman KG, de Kok TM et al. (2008) When does nitrate become a risk for humans? J Environ Qual 37: 291-295. doi:https://doi.org/10.2134/jeq2007.0177. PubMed: 18268290.
- 70. Johnson DW, Susfalk RB, Dahlgren RA (1997) Nutrient fluxes in forests of the eastern Sierra Nevada mountains, United States of America. Global Biogeochemical Cycles 11: 673-681. doi:https://doi.org/10.1029/97GB01750.
- 71. Sickman JO, Melack JM, Stoddard JL (2002) Regional analysis of inorganic nitrogen yield and retention in high-elevation ecosystems of the Sierra Nevada and Rocky Mountains. Biogeochemistry 57: 341-374. doi:https://doi.org/10.1023/A:1016564816701.
- 72. Roche LM, Kromschroeder L, Atwill ER, Dahlgren RA, Tate KW (2013) Water Quality Conditions Associated with Cattle Grazing and Recreation on National Forest Lands. PLOS ONE 8: e68127. PubMed: 23826370.
- 73. Gomi T, Moore RD, Hassan MA (2005) Suspended sediment dynamics in small forest streams of the Pacific Northwest. Journal of the American Water Resources Association 41: 877-898. doi:https://doi.org/10.1111/j.1752-1688.2005.tb03775.x.
- 74. Hassan MA, Church M, Lisle TE, Brardinoni F, Benda L et al. (2005) Sediment transport and channel morphology of small, forested streams. Journal of the American Water Resources Association 41: 853-876. doi:https://doi.org/10.1111/j.1752-1688.2005.tb03774.x.
- 75. Cooper AB, Thomsen CE (1988) Nitrogen and phosphorus in streamwaters from adjacent pasture, pine, and native forest catchments. New Zealand Journal of Marine and Freshwater Research 22: 279-291. doi:https://doi.org/10.1080/00288330.1988.9516300.
- 76. Walker TW, Syers JK (1976) Fate of phosphorus during pedogenesis. Geoderma 15: 1-19. doi:https://doi.org/10.1016/0016-7061(76)90066-5.
- 77. Elser JJ, Bracken MES, Cleland EE, Gruner DS, Harpole WS et al. (2007) Global analysis of nitrogen and phosphorus limitation of primary producers in freshwater, marine and terrestrial ecosystems. Ecol Lett 10: 1135-1142. doi:https://doi.org/10.1111/j.1461-0248.2007.01113.x. PubMed: 17922835.
- 78. Kiffney PM, Richardson JS, Bull JP (2003) Responses of periphyton and insects to experimental manipulation of riparian buffer width along forest streams. Journal of Applied Ecology 40: 1060-1076. doi:https://doi.org/10.1111/j.1365-2664.2003.00855.x.
- 79. Kiffney PM, Richardson JS, Bull JP (2004) Establishing light as a causal mechanism structuring stream communities in response to experimental manipulation of riparian buffer width. Journal of the North American Benthological Society 23: 542-555. doi:https://doi.org/10.1899/0887-3593(2004)023.
- 80. Wallace JB, Eggert SL, Meyer JL, Webster JR (1997) Multiple trophic levels of a forest stream linked to terrestrial litter inputs. Science 277: 102-104. doi:https://doi.org/10.1126/science.277.5322.102.
- 81. Chizinski CJ, Vondracek B, Blinn CR, Newman RM, Atuke DM et al. (2010) The influence of partial timber harvesting in riparian buffers on macroinvertebrate and fish communities in small streams in Minnesota, USA. Forest Ecology and Management 259: 1946-1958. doi:https://doi.org/10.1016/j.foreco.2010.02.006.
- 82. Hemstad NA, Merten EC, Newman RM (2008) Effects of riparian forest thinning by two types of mechanical harvest on stream fish and habitat in northern Minnesota. Canadian Journal Forest Research-Revue Canadienne de Recherche Forestiere 38: 247-256. doi:https://doi.org/10.1139/X07-157.
- 83. Hubbart JA, Link TE, Gravelle JA, Elliot WJ (2007) Timber harvest impacts on water yield in the continental/maritime hydroclimatic region of the United States. Forest Science 53: 169-180.
- 84. Beschta RL, Bilby RE, Brown GW, Holtby LB, Hofstra TD (1987) Stream temperature and aquatic habitat: fisheries and forestry interactions. In: EO SaloT.W. Cundy. Streamside Management: Forestry and Fishery Interactions, Contribution 57. Seattle, WA: Univ. of Wash., Inst. of Forest Res. pp. 191-232.
- 85. Moore RD, Spittlehouse DL, Story A (2005) Riparian microclimate and stream temperature response to forest harvesting: A review. Journal of the American Water Resources Association 41: 813-834. doi:https://doi.org/10.1111/j.1752-1688.2005.tb04465.x.
- 86. Bourque CPA, Pomeroy JH (2001) Effects of forest harvesting on summer stream temperatures in New Brunswick, Canada: an inter-catchment, multiple-year comparison. Hydrology and Earth System Sciences 5: 599-613. doi:https://doi.org/10.5194/hess-5-599-2001. Available online at:
- 87. Wilkerson E, Hagan JM, Siegel D, Whitman AA (2006) The effectiveness of different buffer widths for protecting headwater stream temperature in Maine. Forest Science 52: 221-231.
- 88. Rempel RS, Carter JCH (1986) An experimental-study on the effect of elevated-temperature on the heterotrophic and autotrophic food resources of aquatic insects in a forested stream. Canadian Journal Zoology-Revue Canadienne de Zoologie 64: 2457-2466. doi:https://doi.org/10.1139/z86-366.
- 89. Barton DR, Taylor WD, Biette RM (1985) Dimensions of riparian buffer strips required to maintain trout habitat in southern Ontario Canada streams. North American Journal of Fisheries Management 5: 364-378. doi:https://doi.org/10.1577/1548-8659(1985)5.
- 90. Hokanson KEF, Kleiner CF, Thorslund TW (1977) Effects of constant temperatures and diel temperature-fluctuations on specific growth and mortality-rates and yield of juvenile rainbow-trout, salmo-gairdneri. Journal of the Fisheries Research Board of Canada 34: 639-648. doi:https://doi.org/10.1139/f77-100.
- 91. Carmona-Catot G, Moyle PB, Aparicio E, Crain PK, Thompson LC et al. (2010) Brook trout removal as a conservation tool to restore Eagle Lake rainbow trout. North American Journal of Fisheries Management 30: 1315-1323. doi:https://doi.org/10.1577/M10-077.1.
- 92. Beche LA, McElravy EP, Resh VH (2006) Long-term seasonal variation in the biological traits of benthic-macroinvertebrates in two Mediterranean-climate streams in California, USA. Freshwater Biology 51: 56-75. doi:https://doi.org/10.1111/j.1365-2427.2005.01473.x.
- 93. Beche LA, Resh VH (2007) Short-term climatic trends affect the temporal variability of macroinvertebrates in California 'Mediterranean' streams. Freshwater Biology 52: 2317-2339. doi:https://doi.org/10.1111/j.1365-2427.2007.01859.x.
- 94. Mykra H, Heino J, Muotka T (2008) Concordance of stream macroinvertebrate assemblage classifications: How general are patterns from single-year surveys? Biological Conservation 141: 1218-1223. doi:https://doi.org/10.1016/j.biocon.2008.02.017.
- 95. Olden JD, Jensen OP, Vander Zanden MJ (2006) Implications of long-term dynamics of fish and zooplankton communities for among-lake comparisons. Canadian Journal of Fisheries and Aquatic Sciences 63: 1812-1821. doi:https://doi.org/10.1139/f06-082.
- 96. Wiens JA (1981) Single-sample surveys of communities - are the revealed patterns real. American Naturalist 117: 90-98. doi:https://doi.org/10.1086/283689.
- 97. Hawkins CP, Murphy ML, Anderson NH (1982) Effects of canopy, substrate composition, and gradient on the structure of macroinvertebrate communities in Cascade Range streams of Oregon. Ecology 63: 1840-1856. doi:https://doi.org/10.2307/1940125.
- 98. Murphy ML, Hawkins CP, Anderson NH (1981) Effects of canopy modification and accumulated sediment on stream communities. Transactions of the American Fisheries Society 110: 469-478. doi:https://doi.org/10.1577/1548-8659(1981)110.
- 99. Quinn JM, Boothroyd IKG, Smith BJ (2004) Riparian buffers mitigate effects of pine plantation logging on New Zealand streams 2. Invertebrate communities. Forest Ecology and Management 191: 129-146. doi:https://doi.org/10.1016/j.foreco.2003.11.013.
- 100. Jost G, Weiler M, Gluns DR, Alila Y (2007) The influence of forest and topography on snow accumulation and melt at the watershed-scale. Journal of Hydrology 347: 101-115. doi:https://doi.org/10.1016/j.jhydrol.2007.09.006.
- 101. Storck P, Kern T, Bolton S (1999) Measurement of differences in snow accumulation, melt, and micrometeorology due to forest harvesting. Northwest Science 73: 87-101.
- 102. Winkler RD, Spittlehouse DL, Golding DL (2005) Measured differences in snow accumulation and melt among clearcut, juvenile, and mature forests in southern British Columbia. Hydrological Processes 19: 51-62. doi:https://doi.org/10.1002/hyp.5757.
- 103. Pomeroy JW, Gray DM, Hedstrom NR, Janowicz JR (2002) Prediction of seasonal snow accumulation in cold climate forests. Hydrological Processes 16: 3543-3558. doi:https://doi.org/10.1002/hyp.1228.
- 104. Kaufmann MR (1985) Annual transpiration in sub-alpine forests - large differences among 4 tree species. Forest Ecology and Management 13: 235-246. doi:https://doi.org/10.1016/0378-1127(85)90037-4.
- 105. Dunford EG, Niederhof CH (1944) Influence of aspen, young lodgepole pine, and open grassland types upon factors affecting water yield. Jour Forest 42: 673-677.
- 106. Pomeroy JW, Parviainen J, Hedstrom N, Gray DM (1998) Coupled modelling of forest snow interception and sublimation. Hydrological Processes 12: 2317-2337. doi:https://doi.org/10.1002/(SICI)1099-1085(199812)12:15.
- 107. Jones BE, Lile DF, Tate KW (2011) Cattle selection for aspen and meadow vegetation: implications for restoration. Rangeland Ecology and Management 64: 625-632. doi:https://doi.org/10.2111/REM-D-10-00089.1.