Headwater Influences on Downstream Water Quality We investigated the influence of riparian and whole watershed land use as a function of stream size on surface water chemistry and assessed regional variation in these relationships . Sixty-eight watersheds in four level III U.S. EPA ecoregions in eastern Kansas were selected as study sites . Riparian land cover and watershed land use were quantified for the entire watershed , and by Strahler order . Multiple regression analyses using riparian land cover classifications as independent variables explained among-site variation in water chemistry parameters , particularly total nitrogen -LRB- 41 % -RRB- , nitrate -LRB- 61 % -RRB- , and total phosphorus -LRB- 63 % -RRB- concentrations . Whole watershed land use explained slightly less variance , but riparian and whole watershed land use were so tightly correlated that it was difficult to separate their effects . Water chemistry parameters sampled in downstream reaches were most closely correlated with riparian land cover adjacent to the smallest -LRB- first-order -RRB- streams of watersheds or land use in the entire watershed , with riparian zones immediately upstream of sampling sites offering less explanatory power as stream size increased . Interestingly , headwater effects were evident even at times when these small streams were unlikely to be flowing . Relationships were similar among ecoregions , indicating that land use characteristics were most responsible for water quality variation among watersheds . These findings suggest that nonpoint pollution control strategies should consider the influence of small upland streams and protection of downstream riparian zones alone is not sufficient to protect water quality . Introduction Nonpoint source pollution is a serious problem that degrades surface waters and aquatic ecosystems . Loading of nutrients , sediment , and other pollutants from the landscape may compromise the integrity of freshwaters -LRB- Hunsaker and Levine 1995 -RRB- . In particular , excessive inputs of nitrogen and phosphorus result in eutrophication and fundamental changes in trophic state of lakes and streams -LRB- Carpenter and others 1998 ; Dodds and others 2002 ; Dodds 2006 -RRB- and the impairment of surface waters for uses such as drinking , recreation , and support of aquatic life -LRB- Dodds and Welch 2000 -RRB- . These problems are pervasive ; almost 40 % of classified stream miles in the United States may be impaired , with diffuse pollutants responsible for a large percentage of impairments -LRB- U.S. Environmental Protection Agency -LSB- EPA -RSB- 2000 -RRB- . In response to these problems , research has focused on identifying and testing practices that reduce excessive pollutant loading and help restore the health of aquatic ecosystems . The development of remote sensing and geographic information systems -LRB- GIS -RRB- technologies has facilitated quantitative assessment of landscape influences on aquatic ecosystems and watershed-scale approaches to the study of water quality -LRB- Johnson and Gage 1997 -RRB- . Watershed land cover is strongly correlated with water chemistry parameters , especially nutrient concentrations -LRB- e.g. , Hunsaker and Levine 1995 ; Johnson and others 1997 ; Jones and others 2001 ; Osborne and Wiley 1988 ; Sliva and Williams 2001 -RRB- . Riparian land use may be particularly influential and , in some cases , a better predictor of in-stream water quality than land cover in the entire catchment -LRB- Johnson and others 1997 ; Osborne and Wiley 1988 -RRB- . Intact riparian zones provide water quality benefits and help preserve the biological integrity of watersheds -LRB- Gregory and others 1991 -RRB- . In areas such as the Midwestern United States large-scale land use conversion has resulted in some of the worst water pollution in the United States -LRB- U.S. EPA 2000 -RRB- and imperilment of many native aquatic species -LRB- Fausch and Bestgen 1997 -RRB- . Establishing or protecting riparian zones or large watershed areas that mitigate impacts of human land use on water quality may be costly or politically difficult , particularly in areas where much of the land is privately owned . In such instances , it is essential that scientists and managers identify areas within watersheds where protection would produce the most substantial water quality benefits , and prioritize these areas for protection . Geographic information systems are ideally suited to provide such identification because landscape analyses encompass the full range of spatial scales across which stream processes are regulated -LRB- Allan and others 1997 -RRB- and allow for multiscale examinations of riparian -LRB- e.g. , Johnson and Gage 1997 -RRB- or headwater impacts on water quality . We examined relationships between riparian and whole watershed land cover and water chemistry metrics in streams in Kansas at spatial scales ranging from several kilometers to the entire watershed , with the objective of testing areas where land use may strongly affect water quality in downstream reaches of the watershed -LRB- herein referred to as `` downstream water quality '' -RRB- . We hypothesized that land use adjacent to small headwater streams would have a disproportionately large impact on water quality , because these streams provide the predominant hydrologic contributions to the watershed -LRB- Lowrance and others 1997 -RRB- , and substantial in-stream nutrient processing and retention in upland streams and rivers can regulate downstream water quality -LRB- Alexander and others 2000 ; Peterson and others 2001 -RRB- . Natural geological and topographic features also influence surface water quality at landscape scales , in addition to anthropogenic factors such as land use conversion -LRB- Johnson and others 1997 ; Sliva and Williams 2001 -RRB- . To assess regional differences related to these features , we compared riparian-water chemistry relationships among four U.S. EPA level III ecoregions . Ecoregions denote general similarities in ecosystem types , serve as a spatial framework for research , assessment , and management of ecosystems -LRB- Omernik 1995 -RRB- , and can correspond well with principal factors that may influence surface water quality -LRB- e.g. , Brown and Brown 1994 ; Rohm and others 2002 -RRB- . We assessed the degree to which relationships between surface water quality and land cover were affected by landscape heterogeneity -LRB- as indicated by ecoregions -RRB- by evaluating regional variation in riparian-water chemistry relationships . To our knowledge , no previous studies have examined the importance of headwater riparian zones , compared to other riparian areas within watersheds , at these scales of analysis across multiple watersheds . Methods Sixty-eight small watersheds -LRB- mean watershed area , 280 km2 ; range , 19 -- 1400 km2 -RRB- were identified in four level III U.S. EPA ecoregions -LRB- U.S. EPA 1998a -RRB- across eastern Kansas -LRB- Fig. 1 -RRB- . These ecoregions also represent 4 of the 14 regions developed for the National Nutrient Strategy -LRB- U.S. EPA 1998b -RRB- , which were classified by both anthropogenic and natural characteristics -LRB- i.e. , geology , geomorphology , land use , soils , vegetation -RRB- associated with nutrient concentrations in streams . Sites were selected across the four ecoregions so results would not be as tied to within-ecoregion characteristics . Sites were chosen from those regularly sampled by the Kansas Department of Health and Environment within the ecoregions such that the watersheds did not cross ecoregion boundaries and none of the sites were nested . Fig. 1Location of study watersheds in Kansas , grouped by level III U.S. EPA ecoregion , and example of land cover classification scheme , in which riparian and catchment land cover was quantified for the subcatchment of each stream segment in the watersheds Twenty-four watersheds were located in the Flint Hills -LRB- FH -RRB- ecoregion , characterized by rolling hills , coarse soils , and relatively intact tracts of tallgrass prairie predominantly used as cattle pasture . Because of topography and geology , little of this region has been converted to cropland agriculture . Eighteen watersheds were located in the Central Irregular Plains -LRB- CIP -RRB- , characterized by irregular topography , loam soils , and a variety of land use types , including cropland agriculture , tallgrass prairie , and oak-hickory forests . Fourteen watersheds were located in the Western Corn Belt Plains -LRB- WCBP -RRB- , a region that was historically covered with tall and mixed-grass prairie but has now been almost entirely converted to cropland agriculture . Finally , 12 watersheds were located in the eastern part of the Central Great Plains -LRB- CGP -RRB- ecoregion , characterized by reduced topography , mixed-grass prairie , and large tracts of cropland agriculture . Criteria for inclusion in the study were as follows : -LRB- 1 -RRB- watersheds were sampled for water chemistry parameters a minimum of 12 times , and -LRB- 2 -RRB- watersheds were entirely contained within one U.S. EPA level III ecoregion . Watersheds were located across a precipitation gradient , with average rainfall ranging from 610 to 1016 mm/year . No watersheds were chosen that had very large livestock feeding operations or municipal point sources . The few smaller feeding operations -LRB- ∼ 1000 animals -RRB- included were in all cases at least 0.1 km upstream of the stream chemistry site , and the total area of these operations was included in the analysis -LRB- see section Statistical Analyses , below -RRB- . Relationships between riparian land cover and water chemistry parameters were assessed at four spatial scales -LRB- Fig. 2 -RRB- . Riparian land cover throughout entire watersheds was quantified to examine cumulative impacts on water quality . Because small streams exert a large influence on downstream water quality -LRB- Alexander and others 2000 ; Peterson and others 2001 -RRB- , we examined correlations between riparian land cover adjacent to only the smallest -LRB- first-order -RRB- streams and water chemistry parameters sampled in downstream reaches of these watersheds . In addition , we examined localized riparian impacts on water quality by quantifying riparian land cover both 2 and 4 km upstream of the sampling site . The results of the above analyses were compared to correlations between water chemistry parameters and catchment-scale land cover at both the watershed and the first-order streams scales . In this way , we assessed the relative impact of riparian land cover on water chemistry parameters , compared to catchment land cover . Temporal variation was explored by partitioning water chemistry data seasonally , which allowed for examination of riparian-water chemistry relationships during both high and base flow conditions . Fig. 2Riparian land cover assessed at four spatial scales : -LRB- A -RRB- land cover in the whole watershed , -LRB- B -RRB- land cover adjacent to the first-order streams of watersheds , and -LRB- C -RRB- land cover 2 and 4 km upstream of the water chemistry sampling point We examined a subset of 39 study watersheds where water chemistry measurements were taken on a fourth-order reach of stream to directly compare the influence of riparian land cover on streams of similar sizes within watersheds . Riparian land cover was quantified by stream order -LRB- Strahler 1957 -RRB- and correlated with downstream water chemistry values separately , so comparisons could be made between stream sizes . In addition , we analyzed riparian land cover-water chemistry relationships among ecoregions to determine if differences existed , or if these relationships held constant across ecosystem types . These analyses also help to show that watershed size and natural factors captured by ecoregions -LRB- geology , precipitation , elevation , gradient , etc. -RRB- did not confound the interpretations of land use effects . Water Chemistry Data Water chemistry data were collected and analyzed by the Kansas Department of Health and Environment -LRB- KDHE -RRB- as part of their stream chemistry monitoring network -LRB- KDHE 2000 -RRB- . Total nitrogen -LRB- TN -RRB- , nitrate -LRB- NO3 − -RRB- , ammonium -LRB- NH4 + -RRB- , total phosphorus -LRB- TP -RRB- , total suspended solids -LRB- TSSs -RRB- , atrazine -LRB- AT -RRB- , fecal coliform bacteria -LRB- FC -RRB- , and dissolved oxygen -LRB- DO -RRB- data were used to assess the impact of riparian land cover on water chemistry . Samples are collected every 2 months between 0900 and 1700 hr at each site on a rotational schedule . Extreme weather -LRB- river icing , very high floods -RRB- precludes sampling occasionally . Water chemistry samples were collected from the thalweg of each stream , frozen , and stored in acid-washed bottles in the dark , prior to analysis . All TN , NH4 + , and TP samples were analyzed within 28 days of collection , NO3 − samples were analyzed within 48 hr of collection , TSS and AT samples were analyzed within 7 days of collection , FC samples were analyzed within 24 hr of collection , and DO measurements were taken in the field using a membrane electrode probe . Total nitrogen and phosphorus were analyzed by a colorimetric automated phenate method , following digestion by metal-catalyzed acid and persulfate techniques , respectively -LRB- U.S. EPA 1983 -RRB- . Nitrate was analyzed by ion chromatography ; NH4 + , by semiautomated colorimetry ; TSS , by a residue , nonfilterable and TSSs method ; and AT , by gas chromatography -LRB- U.S. EPA 1983 -RRB- . Fecal coliform bacteria samples were analyzed by a membrane filter procedure -LRB- APHA 1992 -RRB- . Field duplicate samples and internal spikes were used to assess the reliability and recovery efficiencies of the assays . Water chemistry data for NO3 − , NH4 + , TP , TSS , AT , FC , and DO were collected from 1990 to 2001 for all study watersheds . Total nitrogen data were collected from January 2000 to May 2003 for 57 of the 68 study watersheds . Collection of TN data began in 2000 to assist establishment of nutrient criteria for Kansas ' surface waters . For all analyses , mean concentrations of TN , NO3 − , NH4 + , TP , TSS , AT , and FC were taken for each watershed across sampling dates . Minimum and maximum DO concentrations were quantified by averaging minimum and maximum concentrations by year for all years in which at least five samples were taken , then taking a mean of these concentrations across years . To examine temporal variability in riparian-water chemistry relationships , we first classified seasons using mean monthly discharge measurements -LRB- 1990 -- 2001 -RRB- from 30 USGS gauging stations across the study region . Seasons were classified as the month or months in which 0 % -- 25 % , 26 % -- 50 % , 51 % -- 75 % , and 76 % -- 100 % of the annual water volume across the region was discharged . Mean water chemistry concentrations of NO3 − , NH4 + , TP , TSS , AT , and FC were taken for each of the four seasons . Insufficient data prevented analysis of total nitrogen and DO for temporal differences . Digital and Land Cover Data Digital stream networks were derived for each watershed using 30-m digital elevation models , ARCGIS -LRB- Arcview version 8.2 , 2002 -RRB- , and ArcHydro -LRB- Maidment , 2002 -RRB- software . This method accounts for permanent streams and all but the smallest intermittent streams . Catchment area above each KDHE monitoring site was delineated using catchment-processing tools in ArcHydro software . Using the same processing tools , a subcatchment was delineated for each stream segment of the watersheds . A stream segment was defined as a section of stream from its upstream confluence to its downstream confluence with other tributaries . By overlaying catchment and subcatchment layers with digitized riparian and catchment land cover data , we quantified land cover for each watershed and watershed subcatchment -LRB- Fig. 1 -RRB- . Riparian land cover was classified from the Kansas Riparian Areas Inventory dataset -LRB- NRCS 2001 -RRB- . The riparian ecotone in this dataset was defined as the 33 m adjacent to the stream and was digitized at a 1:24,000 scale from USGS Digital Orthophotograph Quarter Quadrangles that reflected land cover conditions in 1991 . Land cover was identified from the beginning of the period of water chemistry sampling . Large socioeconomic changes did not occur in Kansas over this time period -LRB- e.g. , only ∼ 10 % population increase -RRB- . This dataset contained 11 land cover classes -LRB- animal production area -LRB- holding pens or feeding areas -RRB- , barren land , cropland , crop/tree mix , forest , grassland , grass/tree mix , shrub/scrub land , urban land , urban/tree mix , water -RRB- , and riparian areas were classified by the land cover type occurring in ≥ 51 % of the 33-m ecotone . Of the 11 land cover classes , 3 -LRB- shrub/scrub land , barren land , and animal production area -RRB- did not account for more than 1 % of the riparian land cover in any watershed and were not included in the analyses . The remaining eight classifications were aggregated into five categories -LRB- cropland , forest , grassland , urban land , and water -RRB- following the level I classification scheme developed by Anderson et al. -LRB- 1976 -RRB- . Water was not included as a land cover type in analyses . While this scheme can create problems with colinearity , the primary goal of this paper was to determine the best-fit model at different spatial scales within the watershed . Colinearity influences the ability to ascribe causation by individual categories of land use -LRB- e.g. , cropland , urban , forest , or grassland -RRB- , but this was not the primary goal of our analysis . Catchment land cover was classified from the Kansas Land Cover dataset -LRB- KARS 1993 -RRB- . This dataset was digitized at a 1:100,000 scale from Landsat Thematic Mapper imagery and , also , contained 11 land cover classes that reflected conditions in 1991 . Land cover classes were reclassified in the same way as the riparian dataset . Comparison of the riparian dataset to a 33-m `` buffer '' clipped from the catchment dataset showed highly significant correlations -LRB- average Kendal τ correlation = 0.93 , p < 0.01 -RRB- between the two datasets for all land cover types . Information on permitted point sources and confined livestock feeding operations within watersheds was obtained from KDHE and incorporated into GIS to ensure that point sources were not in close proximity to sampling sites . Statistical Analyses Forward stepwise linear regression models were used to predict water chemistry parameters with land cover data -LRB- animal production area -LSB- holding pens or feeding areas -RSB- , barren land , cropland , crop/tree mix , forest , grassland , grass/tree mix , shrub/scrub land , urban land , urban/tree mix , water -RRB- at four spatial scales -LRB- watershed , first-order streams , 2 km upstream , 4 km upstream -RRB- . Separate regressions were done at each scale . F-values of 1 and 0 were used as thresholds to include and exclude land cover classifications from regression models . We investigated the predictive ability of riparian land cover independent of catchment effects by examining partial correlations -LRB- r -RRB- among riparian land cover classifications that were significant predictors in regression models and water chemistry parameters , controlling for predictor catchment land cover classifications . Analysis of variance -LRB- ANOVA -RRB- was used to test for differences among ecoregions . Since ecoregions were correlated with land use , slopes of relationships were compared among ecoregions at all four spatial scales using general linear model -LRB- GLM -RRB- analysis of variance -LRB- ANCOVA -RRB- to assess whether riparian-water chemistry relationships held constant across ecoregions . Results of comparisons of intercepts on these data were presented in a prior publication -LRB- Dodds and Oakes 2004 -RRB- . Least-squares means were used to compare slopes of regression lines . Slopes represent the fundamental response to anthropogenic effects -LRB- most relevant to this paper -RRB- and intercepts indicate the baseline nutrient or pollutant level . Response data appeared normally distributed and were not transformed prior to analyses . All relationships among the data were plotted and no clear outliers or leveraged relationships were observed . Results Riparian-Water Chemistry Relationships Strahler ordering showed the smallest -LRB- first-order -RRB- digitized streams on average comprised > 60 % of the stream miles within study watersheds , with larger streams accounting for sequentially fewer percentages of stream miles . Across all studied watersheds , riparian land cover was a significant predictor of among-site variation in water chemistry concentrations at the watershed and first-order streams scales , particularly for nutrients -LRB- Table 1 -RRB- . Less variance was explained at local scales represented as riparian cover 2 or 4 km upstream from the sampling site -LRB- Fig. 3 -RRB- . Total nitrogen , TP , and NO3 − were the parameters with the greatest R2 values related to riparian land cover , and all three had slightly greater R2 values using land cover adjacent to first-order streams of watersheds than using riparian land cover across the whole watershed . Table 1Multiple regression models showing correlations between water chemistry parameters and riparian land cover in both the whole watersheds the first-order streams of watershedsWater chemistry parameterCropForestGrasslandUrban InterceptR2Watershed TN − 0.4400.2601.932 0.355 NO3-N0.6230 .490 − 0.5000.525 NH4-N − 0.466 − 0.6620.2030.327 TP0 .2640.7120.0950.507 AT0 .4280.5580.171 FC0 .3781621.5700.199 DO -LRB- max -RRB- 0.50812.0850.247 First order TN0 .3880.5760.5510.406 NO3-N0.6500 .538 − 0.0330.606 NH4-N − 0.445 − 0.6830.1950.304 TP0 .3200.7800.0870.634 AT0 .4130.6050.158 FC0 .458798.8320.198 DO -LRB- max -RRB- 0.52212.1130.261 Note . Significant regression coefficients are presented , illustrating the magnitude and direction of importance of land cover classes in models . TN analyses based on 57 watersheds ; all other analyses based on 68 watersheds . Nutrient parameters and dissolved oxygen expressed as milligrams per liter , atrazine -LRB- AT -RRB- expressed as micrograms per liter , microbiological parameters expressed as colony forming units/100 ml , and land cover classifications expressed as percentages . All values reported were significant at p < 0.05 Fig. 3Variance in water chemistry variables -LRB- R2 values -RRB- accounted for by -LRB- A -RRB- land cover in the riparian ecotone -LRB- 33 m -RRB- at multiple scales and -LRB- B -RRB- catchment land cover at two scales , using multiple linear regression analyses . TN analyses based on 57 watersheds ; all other analyses based on 68 watersheds . Bars for R2 values were not plotted when there was not a significant relationship -LRB- p > 0.05 -RRB- Riparian land cover 2 and 4 km upstream explained no significant variance in TP concentrations , and riparian land cover 2 km upstream of the sampling point explained no significant variance in AT concentrations . Total suspended solids and minimum DO concentrations did not have significant relationships with riparian cover in any analyses and are not discussed further in this section . Catchment land cover showed similar relationships to water chemistry parameters as riparian land cover -LRB- Fig. 3 -RRB- . In all comparisons between catchment and riparian land cover , the magnitude of differences was small . Partial correlations indicated that riparian land cover classifications were still significantly correlated with some water chemistry parameters after controlling for variance explained by catchment land cover classifications that were significant predictors in regression models -LRB- Table 2 -RRB- . Removal of the effect of land use cover by using partial correlations can actually remove riparian effects from the overall correlation so these data should not be interpreted to suggest that riparian cover only explains a small portion of the variance in water quality . Table 2Partial correlations among nutrient concentrations and riparian land cover classificationsWater chemistry parameterCatchment land cover Riparian land coverrp-valueWatershed TNGrass , forestGrass , urbanGrass = − 0.060.687 Urban = 0.200.134 NO3 − Crop , urbanCrop , urbanCrop = 0.220.071 Urban = 0.480.000 NH4 + Grass , forestGrass , forestGrass = − 0.030.803 Wood = − 0.110.370 TPCrop , urban , forestCrop , urbanCrop = 0.040.779 Urban = 0.580.000 First order TNCrop , grassCrop , urbanCrop = 0.250.068 Urban = 0.330.013 NO3 − Crop , urbanCrop , urbanCrop = 0.260.033 Urban = 0.500.000 NH4 + Grass , forestGrass , forestGrass = − 0.000.994 Forest = − 0.080.543 TPCrop , urbanCrop , urbanCrop = 0.040.724 Urban = 0.680.000 Note . Correlations controlled for catchment land cover classifications that were significant predictors in regression models and were used to partition additional variance explained by riparian land cover from variance explained by catchment land cover . Partial correlations -LRB- r -RRB- for which riparian crop land -LRB- crop -RRB- , forest , grassland -LRB- grass -RRB- , and urban land -LRB- urban -RRB- explained > 30 % of the variation in water chemistry parameters among sites -LRB- see Table 1 and Fig. 3 -RRB- are presented Temporal Variation Examination of regional discharge patterns revealed that 25 % of annual water volume was discharged from January to April , 50 % by June , 75 % by August , and the remainder in the August -- December time period . Thus , the periods of January -- April , May , June -- July , and August -- December were designated as seasons in temporal analyses . Seasons in which a quarter of annual water volume was discharged in 1 or 2 months -LRB- i.e. , May , June -- July -RRB- represented periods of high flow and high connectivity across the landscape , while seasons encompassing more than 2 months -LRB- January -- April , August -- December -RRB- represented predominantly base flow conditions -LRB- with most of the upper reaches of the first-order streams dry -RRB- . Most water chemistry parameters exhibited temporal changes in the degree that they were statistically related to riparian land cover . Total P and NH4 + were significantly correlated with riparian land cover in all seasons except May -LRB- Fig. 4 -RRB- ; in particular , riparian land cover at both the watershed and the first-order streams scales explained most variance in TP concentrations in January -- April compared to other seasons . Conversely , AT and FC concentrations were best explained during the high flow period of May , and did not have significant relationships with riparian land cover during some base flow seasons . Nitrate exhibited comparatively less temporal variation ; riparian land cover at the watershed scale explained a minimum of 30 % , and at the first-order streams scale a minimum of 45 % , of among-site variance in NO3 − concentrations across seasons . Fig. 4Temporal variation -LRB- R2 values -RRB- in relationships between water chemistry parameters and -LRB- A -RRB- total riparian land cover in watersheds and -LRB- B -RRB- riparian land cover adjacent to the first-order streams of watersheds . Seasons were designated from quartiles of annual discharge occurring across the study region . Total nitrogen and DO were not analyzed for temporal differences -LRB- see Methods -RRB- . Bars for R2 values were not plotted when there was not a significant relationship -LRB- p > 0.05 -RRB- A particularly interesting aspect of these data is that even when first-order streams are not very likely to flow -LRB- August -- December -RRB- , the riparian land cover around them yielded somewhat greater R2 values than did the whole watershed riparian cover for TP and NO3 − . Impact of Stream Size Different stream sizes were used in the analyses to this point . To control for this a subset of sites was chosen from which data were taken only for fourth-order streams . Total N and NO3 − were most closely correlated with first-order riparian land cover -LRB- Fig. 5 -RRB- . In general , the most variance was explained by riparian land cover adjacent to first-order streams and less variance was explained by riparian cover near larger-order streams closer to sampling sites . Atrazine and maximum DO concentrations were not significantly correlated with riparian land cover near streams of any size in this subset of watersheds . Fig. 5Variance in water chemistry variables -LRB- R2 values -RRB- explained by riparian land cover adjacent to different sized streams within watersheds . Analyses performed with a subset of 39 fourth-order watersheds ; TN analyses preformed with 38 fourth-order watersheds . Comparisons between riparian land cover and AT and maximum DO concentrations were not significant and are not presented Ecoregion Effects ANOVA indicated some variation in TN , NO3 − , NH4 + , TP , FC , and maximum DO concentrations among ecoregions . Comparison of least-squares means showed TN and NO3 − concentrations were significantly different -LRB- p < 0.05 -RRB- among all ecoregions except the CGP and CIP -LRB- Fig. 6 -RRB- . The Western Corn Belt Plains was the only ecoregion that exhibited significantly different NH4 + , FC , and maximum DO concentrations , which were all higher than mean concentrations in other ecoregions . Fig. 6Mean values for selected water chemistry parameters and riparian cropland , grouped by ecoregion -LRB- WCBP , Western Corn Belt Plains ; CGP , Central Great Plains ; FH , Flint Hills ; CIP , Central Irregular Plains -RRB- . TN data for WCBP were available for only 3 of 12 study watersheds . Significant differences are labeled with different letters ; error bars represent 1 SE The Flint Hills was the only ecoregion that exhibited significantly different TP concentrations , which were lower than those of other ecoregions . Atrazine concentrations did not differ significantly among ecoregions . The percentage of riparian land in agricultural production also varied by ecoregion and closely mirrored nutrient concentrations . Least-squares means comparing slopes of regression lines between water chemistry parameters and significant predictor land cover classifications among the four ecoregions showed that slopes were generally similar across all water chemistry parameters -LRB- e.g. , Fig. 7 -RRB- , and differences that did exist most often occurred when comparing the Flint Hills to other ecoregions -LRB- Table 3 -RRB- . Fig. 7Example of typically observed relationships between riparian land cover and water chemistry parameters among the four ecoregions analyzed -LRB- WCBP , Western Corn Belt Plains ; CGP , Central Great Plains ; FH , Flint Hills ; CIP , Central Irregular Plains -RRB- . The percentage of riparian cropland in the watersheds is plotted versus in-stream NO3 − concentrations . Slopes of regression lines fitted through each of the four ecoregions were not significantly differentTable 3Comparisons of least-squares means using general linear model analyses to assess differences in slopes of riparian-water chemistry relationships at four spatial scales , across level III U.S. EPA ecoregionsSpatial scaleResponse variableEcoregions with different slopesp-valueWatershedTPFH & CGP0 .010 First orderTNFH & CGP0 .019 First orderTPFH & CGP0 .007 First orderTPCIP & CGP0 .007 First orderTPCIP & WCBP0 .0412 km upstreamTNFH & CGP0 .0222 km upstreamNO3 − FH & CIP0 .0142 km upstreamNO3 − FH & WCBP0 .0024 km upstreamNO3 − FH & WCBP0 .0014 km upstreamFCFH & WCBP0 .023 Note . Significantly different slope comparisons between Central Great Plains -LRB- CGP -RRB- , Central Irregular Plains -LRB- CIP -RRB- , Flint Hills -LRB- FH -RRB- , and Western Corn Belt Plains -LRB- WCBP -RRB- ecoregions are listed . All other comparisons were not significantly different at p < 0.05 Discussion Land Cover-Water Chemistry Relationships Riparian and whole watershed land cover was significantly correlated with water quality metrics , particularly nutrient concentrations . Land cover explained greater variance at landscape scales -LRB- watershed and first-order streams -RRB- than riparian cover at local scales -LRB- 2 and 4 km upstream of sampling -RRB- , which is consistent with the idea that nutrient loading and retention occurs at larger spatial scales -LRB- Allan and others 1997 -RRB- . Given that NO3 − uptake lengths are often less than 2 km in this region -LRB- O'Brien and others 2007 -RRB- , it is possible that local riparian cover would influence NO3 − concentrations , but the effect was small . Differences in correlations between nitrogen species -LRB- NO3 − and NH4 + -RRB- may have occurred because NO3 − inputs from the watershed are often greater than NH4 + inputs -LRB- Peterson and others 2001 -RRB- and NH4 + is a preferred nitrogen source for aquatic organisms that can use inorganic N and cycles more quickly than NO3 − -LRB- Dodds and others 2000 -RRB- . Seasonal differences in relationships between riparian land cover and both NH4 + and TP may be attributable to their strong relationship to particulate dynamics -LRB- Johnson and others 1997 -RRB- . Phosphate and NH4 + both adsorb readily to sediments , and are primarily transported into streams via surface runoff -LRB- Novotny and Olem 1994 -RRB- . We wanted to remove the potential problem that the proportion of length of first order streams would vary by stream order . But if we only used our fourth-order sites , then we had about half the total number of sites and our statistical power decreased . Thus we analyzed the subset of fourth-order stream sites -LRB- Fig. 5 -RRB- to be certain that our results were not an artifact of sampling sites occurring at different order streams . Since our results were similar with this subset , all other analyses used the full dataset . Variation in nutrient concentrations during high flow may have resulted from `` pulses '' of sediment-bound nutrients entering from the landscape which were not effectively captured by our method of analyzing mean seasonal concentrations . This could explain the lack of correlation between riparian land cover and NH4 + and TP in May compared to other seasons . Conversely , the primary mode of NO3 − transport to surface water is generally via subsurface flow -LRB- Hill 1996 -RRB- , and this consistent connectivity to the landscape may explain the comparatively low temporal variability seen in riparian-NO3 − relationships . Discrepancies in numbers of sampling dates and sites made it difficult to directly compare riparian-TN relationships with those of other parameters . However , we felt it was important to include TN in these analyses because of its importance in establishing nutrient criteria -LRB- Dodds and Welch 2000 -RRB- and because other available parameters , such as dissolved inorganic nitrogen , can be unsuitable substitutes -LRB- Dodds 2003 -RRB- . A disproportionate number of watersheds for which TN data were not available were primarily agricultural and contained some of the highest observed concentrations of both NO3 − and TP ; the absence of these sites in TN analyses may explain why TN was not as strongly correlated with riparian land cover compared to NO3 − or TP . Nonnutrient water chemistry parameters had weaker correlations with riparian land cover . Although AT , FC , and maximum DO concentrations were significantly correlated with riparian land cover , relationships were weak across all spatial and temporal scales and preclude conjecture into the mechanisms underlying correlations . Lack of correlation between TSS and riparian land cover contrasts with results of previous studies -LRB- Johnson and others 1997 ; Sliva and Williams 2001 -RRB- and , as with relationships observed in sediment-bound nutrients , may be a function of averaging TSS concentrations into one measurement . Although permitted livestock operations and other point sources were not substantial in each watershed , point sources falling below Kansas ' permitting regulations -LRB- e.g. , confined livestock operations under 300 animals -RRB- were likely present in some watersheds and may have accounted for unexplained variance in the observed relationships . Our results were consistent with previous studies -LRB- Johnson and others 1997 ; Jones and others 2001 ; Osborne and Wiley 1988 ; Sliva and Williams 2001 -RRB- , suggesting that agricultural and/or urban lands were the most important predictors of water quality variability . Maintaining buffers or other passive land uses in headwater streams may effectively reduce diffuse pollution downstream . The importance of these streams and their riparian zones is due in part to their sheer numbers ; small streams often comprise the majority of stream miles within a drainage network -LRB- Horton 1945 ; Leopold and others 1964 -RRB- , and in this study the smallest -LRB- first-order -RRB- streams on average comprised more than 60 % of the stream miles in the study watersheds . Riparian land cover near the first-order streams of watersheds explained greater variance in TN , NO3 − , and TP concentrations than did riparian land cover immediately upstream from sampling sites . First-order riparian land cover was statistically related to most water quality measures , even when all potential correlation related to watershed land cover was controlled for . Our results suggest that headwater riparian areas could have an important impact on downstream water quality . Our study was correlative in nature and does not unequivocally confirm causation . Such an approach is required at the spatial scales of our study . Previous work suggests several possible causes for our observed associations . First , lower-order streams have the greatest potential for interactions between water and the adjacent landscape -LRB- Lowrance and others 1997 -RRB- . Second , the large benthic surface area-to-volume ratio of small streams favors rapid in-stream uptake , processing , and retention of nitrogen -LRB- Alexander and others 2000 ; Dodds and others 2000 ; Peterson and others 2001 -RRB- , which in larger streams increases in proportion to depth -LRB- Alexander and others 2000 -RRB- or discharge -LRB- Wollheim and others 2001 -RRB- . Because high nitrogen inputs may overwhelm this ability -LRB- O'Brien and others 2007 ; Wollheim and others 2001 -RRB- , riparian zones adjacent to small streams may be particularly important in regulating nutrient inputs and allowing natural in-stream processes to significantly impact nutrient concentrations . Several studies have addressed the relative importance of riparian versus whole catchment land use in regulating water quality . Reports in the literature have been mixed ; some researchers -LRB- Hunsaker and Levine 1995 ; Sliva and Williams 2001 -RRB- found that catchment land cover was better correlated with water quality , while others -LRB- Osborne and Wiley 1988 ; Johnson and others 1997 -RRB- reported that land cover in the riparian ecotone was more influential . Likewise , although partial correlations indicated riparian land cover classifications were significantly related to TN , NO3 − , and TP even after accounting for catchment effects , this did not hold true for all water chemistry parameters . Overall , it is difficult to separate the effects of land cover in the riparian ecotone and land cover in the catchment because they are highly correlated , and in many altered landscapes , riparian land cover may simply reflect the dominant catchment land cover types . Significant partial correlations between riparian land cover and TN , NO3 − , and TP concentrations correspond with previous work -LRB- e.g. , Karr and Schlosser 1978 ; Lowrance and others 1997 -RRB- identifying riparian zones as key regulators of nutrient inputs to surface waters . These results , in addition to strong relationships among water quality metrics and riparian land use that have been previously reported at both field -LRB- e.g. , Karr and Schlosser 1978 ; Peterjohn and Correll 1984 -RRB- and landscape -LRB- e.g. , Johnson and others 1997 ; Osborne and Wiley 1988 -RRB- scales , suggest that intact riparian zones could influence landscape impacts on surface water quality . Ecoregion Effects The finding that slopes of the relationships were not significantly different in most ecoregion comparisons may be attributable to several factors . Exceptionally variable relationships could preclude the statistical power to determine differences . It is possible that the study regions were not sufficiently distinct to allow detection of differences in riparian interactions , although this is unlikely given their previous classification as both separate ecoregions -LRB- U.S. EPA 1998a -RRB- and nutrient regions -LRB- U.S. EPA 1998b -RRB- . Because U.S. EPA ecoregion designations encompass human impacts such as land use in addition to natural geological , climatic , and soil characteristics -LRB- Omernik 1995 -RRB- , observed intraregion differences in riparian land cover classification and nutrient concentrations were expected . However , since land use is often a dominant factor regulating surface water quality -LRB- Hunsaker and Levine 1995 ; Johnson and others 1997 ; Osborne and Wiley 1988 -RRB- , riparian-water chemistry relationships would be expected to remain relatively constant across ecoregions if designations were partially dependent on land use , as was the case in this study . Conclusions The data suggest that riparian cover near sampling sites is generally less well correlated with water quality parameters than riparian cover or land use in first-order streams . Because watershed cover and riparian land use were correlated , it is difficult to determine how important first-order riparian cover is related to water quality . Our results suggest a statistically significant effect of riparian cover of first-order streams on water quality because partial correlations among riparian land cover classifications were significant predictors in regression models when controlling for predictor catchment land cover classifications . We take the conservative approach in our interpretation , but it is possible that riparian cover has much stronger effects than whole-watershed land cover and that most of the correlation is driven by riparian effects . The effect of first-order land cover may not be too surprising ; first-order streams make up the majority of stream length in watersheds . Our approach shows that a correlation with land uses in small headwater streams does hold , and holds even in seasons when many of the first-order stream channels are not flowing .

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O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O B I O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O B I O O O O O O O O O O O B I O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O B I 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O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O B I O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O

water quality
geographic information systems
headwater streams
nonpoint source pollution
riparian zones


Tonsillar metastasis of oesophageal adenocarcinoma In the literature less than 100 cases of metastatic carcinoma of the palatine tonsil have been reported . Tonsillar metastasis of adenocarcinoma of the oesophagus has not been reported previously . We report a case of a 57-year-old male with a primary adenocarcinoma of the distal esophagus with a metastasis in the right palatine tonsil . Metastatic tumour involving the palatine tonsil is rare . The route of dissemination remains unclear . Hypothetically the dissemination of tumour cells could be lymphogenic or secondary by transportation due to vomiting or at the time of endoscopy , but most likely represents haematogenous spread . Introduction The vast majority of cancers in the head and neck region are of epithelial origin . Lymphoma is the next most common malignancy in this area . Metastases in the head and neck other than lymph node metastases are rare . The occurrence of tonsillar metastases from non-haematological malignant neoplasms is very rare -LSB- 10 -RSB- . We present a patient with metastasis in the right tonsil of a primary adenocarcinoma of the distal oesophagus . Case report A 57-year-old man was referred to our department of otolaryngology and head and neck surgery , because of dysphagia , pain and swelling of the right palatine tonsil . He also complained of frequent vomiting . Five months previously , an adenocarcinoma of the distal oesophagus with lymph node and liver metastases had been diagnosed . He received chemotherapy with combined capecitabine and oxaliplatin , which was stopped after two cycles because of disease progression . On physical examination an enlarged and ulcerating right palatine tonsil was seen -LRB- Fig. 1 -RRB- . A suspicious ipsilateral cervical lymph node of 2 × 4 cm was found at level II . A biopsy of the tonsillar tumour was performed and revealed intestinal-type adenocarcinoma . The histopathological picture corresponded with that of the oesophageal tumour -LRB- Fig. 2 -RRB- . Tonsillectomy was not performed because of severe clotting disorders attributed to liver metastases . The patient died 4 weeks after his first visit to our department . Fig. 1Enlarged right palatine tonsil with ulcerationFig . 2Biopsy right tonsil : adenocarcinoma -LRB- intestinal type -RRB- Discussion Second primary tumours relatively often involve the head and neck region . These tumours develop in head and neck cancer patients due to their common factors in carcinogenesis , e.g. , tobacco , alcohol and , probably , genetic susceptibility -LSB- 4 -RSB- . However , this common aetiology applies for squamous cell carcinoma and not for adenocarcinoma . Simultaneous primary adenocarcinomas are not frequently found . In our patient the corresponding histopathology indicates a common origin , suggesting metastatic disease . Primary oesophageal adenocarcinoma is a relatively uncommon tumour in western countries -LSB- 9 -RSB- . The pattern of metastasis of oesophageal adenocarcinoma can be lymphogenic , haematogenic and by transportation of tumour cells by regurgitation or endoscopes -LSB- 2 , 10 -RSB- . Lymphogenic spread of distal oesophageal adenocarcinoma generally involves the regional nodes in the lower posterior mediastinum , the paracardiac region , along the lesser curvature and the left gastric artery -LSB- 6 -RSB- . In case of extensive lymphogenic spread , lymph-node metastases can be found in the tracheal bifurcation region , the proximal mediastinum , coeliac axis and supra-clavicular region -LSB- 6 -RSB- . Lymphogenic spread of adenocarcinoma of the distal oesophagus and the gastro-oesophageal junction is present in 70 % of the patients at the time of diagnosis of the primary tumour -LSB- 9 -RSB- . Haematogenous dissemination occurs at a later stage and is less frequent . Liver and lung are the most common organs involved -LSB- 6 -RSB- . Metastatic tumour involving the palatine tonsil is distinctly rare . These metastases represent only 0.8 % of all tonsillar tumours -LSB- 5 -RSB- . Bilateral metastases of gastric carcinoma to the tonsils have been described -LSB- 7 -RSB- . Less than 100 cases of metastatic carcinoma of the palatine tonsil have been reported -LSB- 3 , 7 -RSB- . The most frequent tumours metastasizing to the tonsil are melanoma , lung carcinoma , breast carcinoma and renal cell carcinoma -LSB- 3 -RSB- . Eleven cases were associated with gastric adenocarcinoma -LSB- 2 , 7 , 8 -RSB- . Tonsillar metastasis of adenocarcinoma of the esophagus has not been reported previously . The occurrence of a tonsillar metastasis as the first manifestation of an occult neoplasm is very unusual -LSB- 8 -RSB- . In the majority of cases the occurrence of a tonsillar metastasis becomes manifest after the diagnosis of the primary tumour and is generally part of a widespread systemic disease -LSB- 2 -RSB- . Therefore , mean survival time for patients with tonsillar metastases is short , with a mean of 9 months , irrespective of the histological type of primary tumour -LSB- 3 -RSB- . In this case there are four hypothetical pathways for metastatic spread to the tonsils : Haematogenous dissemination of tumour from an esophageal carcinoma may occur via the portal circulation , the liver , the pulmonary circulation and systemic arterial vessels , thus reaching the palatine tonsil . A second haematogenous route may be through the paravertebral plexus of Batson , bypassing the lungs -LSB- 1 -RSB- . Retrograde flow via this valveless plexus occurs during elevated intra-abdominal and intrathoracic pressure , as is brought about by straining , coughing or as in this case , vomiting -LSB- 1 -RSB- . A third route of metastasis may be through the thoracic duct followed by retrograde cervical lymphatic spread to the tonsil -LSB- 3 -RSB- . This route of dissemination is very rare and is mostly seen in cases of seminomas -LSB- 3 -RSB- . Finally , some authors believe the possibility of metastasis by direct translumenal implantation , which might be favoured by a previous lesion in the mucosa of the tonsil -LSB- 2 -RSB- . The tumour cells would be transported secondary to regurgitation from the oesophagus -LSB- 8 -RSB- , or as in this case possibly because of frequent vomiting , or at the time of endoscopy -LSB- 2 -RSB- . In conclusion , when finding a tumour of the tonsil a metastasis from a distant primary malignancy should be considered , although this is very rare . The route of dissemination eventually remains unclear .

O B O O B O O O O O O O O O O O O O B O O O O O B O B O O B O O O O O O O O O O O O O O O O O B O O O O O O B O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O B O O O B O O O B O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O B O B O O O O O O O O O O O O B I I O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B O O O O O O O O O O O O O O O O O O O O O O O

tonsil
metastasis
adenocarcinoma
oesophagus
head and neck


Changes in CMDP and DPOAE during acute increased inner ear pressure in the guinea pig During and after an increase of inner ear pressure , induced by injection of artificial perilymph , the 2f1 − f2 and f2 − f1 distortion products -LRB- DPs -RRB- in cochlear microphonics -LRB- CM -RRB- and otoacoustic emissions -LRB- OAE -RRB- were recorded in the guinea pig . An inner pressure increase of ∼ 600 Pa gave only small changes in CMDP and DPOAE . Along with a decrease in f1 amplitude , a small decrease in amplitude of the 2f1 − f2 and a small increase in the f2 − f1 were measured in CM . This matches a shift from a symmetrical position of the operating point for hair cell transduction , leading to an increase in even-order distortion and a decrease in odd-order distortion . Similar , a decrease in 2f1 − f2 DPOAE was expected . This might be the case at the generation sites but this effect was then more than compensated for by a better middle ear transfer , accounting for the increase of 0.4 dB of the 2f1 − f2 DPOAE amplitude . In conclusion , changes of overall inner ear fluid pressure have minor effects on cochlear function . This is a relevant finding for further understanding of diseases with changed inner ear fluid volumes , as Ménière 's . Introduction The cochlea is a non-linear mechano-electrical transducer that transforms sound pressure waves into electrical information , the so-called mechanoelectric transduction -LRB- MET -RRB- . The reverse electromechanical transduction is performed by the outer hair cell -LRB- OHC -RRB- which mechanically influences the vibration of the cochlear partition -LSB- 7 -RSB- . When the cochlea is stimulated by two tones , distortion products -LRB- DPs -RRB- can be measured in cochlear microphonic potentials -LRB- CMDP -RRB- and in the external auditory meatus as otoacoustic emissions -LRB- DPOAE -RRB- . Both microphonic and acoustic DPs are considered to be reflections of OHC electromotility in the cochlea . Obviously , it is of interest to find a relation between these two functional modalities of the cochlea and the OHC in particular . In this study the most prominent DPs , the 2f1 − f2 and f2 − f1 , have been observed while increasing inner ear pressure . This was done by rapid injection of artificial perilymph into the scala tympani of the guinea pig 's cochlea . Measurement of specific DPs may describe changes in gain and operating point of the non-linear cochlear amplifier . Furthermore , transfer characteristics of forward and backward transmission may be clarified by using CMDP and DPOAE -LSB- 17 -RSB- . These data could help gaining insight into pathophysiological mechanisms involved in pathologically increased inner ear pressures . When pressure variation is in the normal physiological range , this does not influence cochlear function as measured by compound action potentials in the guinea pig -LSB- 2 -RSB- . In humans , during activities like coughing or sneezing , perilymphatic pressure may undergo substantial fluctuations up to 10 mmHg -LRB- 1.4 kPa -RRB- . An increased pathologic inner ear pressure may be the result of an increased intracranial pressure since the perilymphatic space is linked to the subarachnoid space via the cochlear aqueduct . Human OAE have been proven to be very sensitive to modifications of intracranial pressure -LSB- 10 -RSB- . Another clinical example of increased inner ear pressure or volume with an accompanying change of cochlear function is the endolymphatic hydrops in patients with Ménière 's disease . In a previous study -LSB- 11 -RSB- , we measured solely the 2f1 − f2 DPOAE 's in response to microinjection of artificial perilymph into the cochlea . Large changes of ∼ 500 Pa in overall inner ear pressure gave only a small mean change of 0.7 dB in 2f1 − f2 DPOAE amplitude . The magnitude of change could -LRB- partly -RRB- be explained by a change in oval window stiffness . In this study , the same experimental setup was used , with the addition of the simultaneous recording of the 2f1 − f2 and f2 − f1 CMDP . We attempt to establish a better understanding of increased inner ear pressure effects on DPs in both CM potentials and OAE 's . Materials and methods Experiments were performed in eight guinea pigs -LRB- Harlan Laboratories , The Netherlands ; body weight 350 -- 450 g -RRB- with a positive Preyer reflex . Animal care and use were in accordance with the principles of the declaration of Helsinki and approved by the animal experiment committee -LRB- protocol number 3047/3103 -RRB- . General anesthesia was induced by intramuscular administration of ketamine/xylazine -LRB- 60/3 .5 mg/kg -RRB- . Maintenance doses of the anesthetic were administered every hour . Muscle relaxation was obtained with succinylcholine -LRB- 2.5 mg/kg -RRB- . The animals were artificially ventilated through a tracheostoma -LRB- Columbus Instruments , model 7950 -RRB- . Body temperature was maintained at 38 °C with a heating blanket . Heart rate was monitored by skin electrodes placed on both sides of the thorax . The animal 's head was kept in a stationary position by means of a steel bolt fixed to the skull with dental cement . Following a retroauricular incision , the bulla and external auditory canal were exposed . Subsequently , the bulla was opened equalizing middle ear pressure to normal air pressure -LSB- 17 -RSB- . By opening of the bulla , the round window was exposed . Through the round window membrane , the tip of a double-barreled micropipette was inserted into scala tympani . The double-barreled micropipettes were drawn from borosilicate glass -LRB- 1.5 / 0.84 mm diameter per barrel -RRB- and the tips were beveled -LRB- Narishige EG-40 -RRB- . The total tip diameter was around 60 μm , which is a compromise between a low enough flow resistance for fluid injection and tip smallness . One barrel of the pipette was used to measure inner ear pressure -LRB- WPI 900A micropressure system -RRB- . Through the other barrel , artificial perilymph -LSB- 9 -RSB- was injected with a constant flow rate by applying a controllable pneumatic pressure to the barrel end . The injected volume was measured as the displacement of the fluid meniscus in the pipette , for which the inner diameter is precisely known -LRB- 0.84 mm -RRB- . The fluid injection rate was calculated as the total injected volume divided by the total injection time . During the experiment the DPOAE 's were continuously measured using an Etymotic ER-10C DPOAE probe system . The two primary frequencies were set at 6 kHz -LRB- f1 -RRB- and 7.4 kHz -LRB- f2 -RRB- , meaning a f2/f1-ratio of 1.23 . The low-level intensities were set at , respectively , 65 dB SPL -LRB- L1 -RRB- and 55 dB SPL -LRB- L2 -RRB- . Full details of the measuring equipment are described elsewhere -LSB- 11 , 12 -RSB- . Cochlear microphonic potentials were recorded with two differential Ni -- Cr electrodes with a diameter of 50 μm . One electrode was placed in scala tympani through the bony wall of the basal turn of the cochlea . The other was placed in scala vestibuli next to the oval window . The signals were routed via an amplifier to a spectrum analyzer and two lock-in amplifiers -LRB- SRS , model SR830 DSP -RRB- . The lock-in amplifiers displayed the amplitude of the 2f1 − f2 and f2 − f1 CMDP which were referenced to an electronic 2f1 − f2 and f2 − f1-DP derived from the original primaries . A measurement contained a sequence of ten microinjections of artificial perilymph of 10 s each with pauses of 40 s . The rate of microinjection was 50 nl/s . The repetitive microinjection was controlled with a precision electronic timer -LRB- Stanford DG535 -RRB- . During an experiment , National Instruments LabVIEW ® was used for recording of the following output signals : amplitude and phase of the 2f1 − f2 DPOAE , 2f1 − f2 CMDP , f2 − f1 CMDP , f1 CM , and inner ear pressure . Calculations and fits to relevant portions of the obtained recordings were made off-line with an appropriate software package . Results Successful repeated sequences of injection with a rate of 50 nl/s -LRB- n = 10 -RRB- were performed in all guinea pigs -LRB- n = 8 -RRB- . The mean steady state inner ear pressure measured prior to injection of artificial perilymph was 205 Pa. . To determine the rise and fall times of the curves from the measured signals , proper fits were obtained with a simple exponential function : In some cases -LRB- Figs. 1c , 2c , 4c -RRB- the curves needed an extra term in the formula for a proper fit : According to Wit et al. -LSB- 13 -RSB- time constants τ were calculated from the fits . Fig. 1a Averaged changes -LRB- n = 8 -RRB- in inner ear pressure -LRB- Pa -RRB- during and after injection of 0.5 μl of artificial perilymph into scala tympani . The gray area depicts the injection period . Standard error bars are shown at t = 5 , 15 , and 40 s. b The shape of the mean inner ear pressure curve at the start of injection -LRB- time axis corresponds with Fig. 1a -RRB- . The recording -LRB- filled circles -RRB- is fitted -LRB- broken line -RRB- with an exponential function , yielding a time constant τ . c The same is done for inner ear pressure recovery directly after injectionFig . 2a Averaged changes -LRB- n = 8 -RRB- in f1 CM amplitude -LRB- μV -RRB- during and after injection of 0.5 μl of artificial perilymph into scala tympani . The gray area depicts the injection period . Standard error bars are shown at t = 5 , 15 , and 40 s. b The shape of the mean f1 CM amplitude curve at the start of injection -LRB- time axis corresponds with Fig. 2a -RRB- . The recording -LRB- filled circles -RRB- is fitted -LRB- broken line -RRB- with an exponential function , yielding a time constant τ . c The same is done for f1 CM amplitude recovery directly after injection In Fig. 1a , the averaged recorded inner ear pressure during and after injection of 0.5 μl of artificial perilymph is shown . At the start of injection the mean pressure increased to an ∼ 600 Pa higher level within seconds . At the end of injection , the pressure immediately decreased , returning to its initial value within seconds . This pattern was consistently observed in all individual experiments . The time constant for increase and subsequent decrease of inner ear pressure were 1.25 and 1.16 s , respectively -LRB- Fig. 1b , c -RRB- . The averaged f1 signal in the CM -LRB- Fig. 2a -RRB- showed a mirrored behavior in respect to the inner ear pressure . Directly after the start of injection , the f1 CM decreased by 30 μV . The corresponding time constant was 1.17 s -LRB- Fig. 2b -RRB- , which is very close to the time constant for pressure increase . Conversely , at the end of injection the f1 amplitude returned to its initial value with τ = 3.49 s -LRB- Fig. 2c -RRB- , which is slow with respect to the corresponding τ for pressure . The averaged DPOAE 2f1 − f2-amplitude showed a similar typical course as the inner ear pressure -LRB- Fig. 3a -RRB- . Almost directly after the start of injection the 2f1 − f2-amplitude increased to reach a maximum of 0.4 dB above its original value at the end of the injection period . When the injection was instantaneously terminated , the amplitude dropped and returned to slightly above its onset level . There was a small observable time lag with respect to the pressure curve . The time constant for increase and subsequent decrease of the 2f1 − f2-amplitude were 1.52 and 3.43 s , respectively -LRB- Fig. 3b , c -RRB- . Fig. 3a Averaged changes -LRB- n = 8 -RRB- in 2f1 − f2 DPOAE amplitude -LRB- dB SPL -RRB- during and after injection of 0.5 μl of artificial perilymph into scala tympani . The gray area depicts the injection period . Standard error bars are shown at t = 5 , 15 , and 40 s. b The shape of the mean 2f1 − f2 DPOAE amplitude -LRB- μPa -RRB- curve at the start of injection -LRB- time axis corresponds with Fig. 3a -RRB- . The recording -LRB- filled circles -RRB- is fitted -LRB- broken line -RRB- with an exponential function , yielding a time constant τ . c The same is done for 2f1 − f2 DPOAE amplitude recovery directly after injection In Fig. 4a , the typical temporary decrease for the averaged 2f1 − f2 CMDP amplitude relative to the f1 CM is shown . The time constant for decrease in amplitude at the onset of injection was 1.12 s -LRB- Fig. 4b -RRB- , which corresponds with τ for pressure . The recovery is somewhat slower -LRB- 2.28 s , Fig. 4c -RRB- , but still faster than the time constant for 2f1 − f2 DPOAE recovery . Fig. 4a Averaged changes -LRB- n = 8 -RRB- in 2f1 − f2 CMDP relative to f1 CM amplitude during and after injection of 0.5 μl of artificial perilymph into scala tympani . The gray area depicts the injection period . Standard error bars are shown at t = 5 , 15 , and 40 s. b The shape of the mean 2f1 − f2 CMDP -LRB- relative to f1 CM -RRB- amplitude curve at the start of injection -LRB- time axis corresponds with Fig. 4a -RRB- . The recording -LRB- filled circles -RRB- is fitted -LRB- broken line -RRB- with an exponential function , yielding a time constant τ . c The same is done for 2f1 − f2 CMDP -LRB- relative to f1 CM -RRB- amplitude recovery directly after injection Finally , in Fig. 5 , the averaged results of the f2 − f1 CMDP amplitude relative to f1 CM depict an increase during injection of artificial perilymph . When the injection was terminated , the f2 − f1 CMDP amplitude returned to the pre-injection level . Unfortunately , due to a low signal-to-noise ratio for the f2 − f1 CMDP , the obtained curve could not be fitted properly and no time constants could be derived . Fig. 5Averaged changes -LRB- n = 8 -RRB- in f2 − f1 CMDP relative to f1 CM amplitude during and after injection of 0.5 μl of artificial perilymph into scala tympani . The gray area depicts the injection period Discussion The most striking result of this study is the minimal change in amplitude of the DPs in both OAE and CM during an acute increase of inner ear pressure . Besides , amplitudes changed to normal when inner ear pressure returned to its initial level . These results indicate a dynamically stable inner ear which is able to cope with a pressure increase of 600 Pa with only minimal and reversible cochlear function loss . According to Böhmer -LSB- 2 -RSB- this level of pressure increase would still be in the physiological range of the guinea pig ear varying between − 100 and +700 Pa. . The inner ear is an elastic structure completely encompassed by bone , in which pressure changes depend on the compliance of the membranous structures -LSB- 14 -RSB- . In normal ears , hydrostatic pressure in the perilymph equals pressure in the endolymph , and pressure changes applied to one compartment are immediately transmitted to the other through the elastic walls . The perilymph is in a dynamic equilibrium with the cerebrospinal fluid via the cochlear aqueduct . An excess of perilymph will escape through the cochlear aqueduct restoring inner ear fluid level . When increasing inner ear pressure , a cochlear disturbance with functional loss is expected . The observed decrease in CM f1 amplitude thus seems obvious . An increased cerebrospinal fluid pressure also suppresses the CM -LSB- 16 -RSB- . The increase in 2f1 − f2 DPOAE is counterintuitive , but in accordance with a previous publication in which we demonstrated the same change in cochlear function as measured by 2f1 − f2 DPOAE 's -LSB- 11 -RSB- . According to Büki et al. -LSB- 3 -RSB- a change in stiffness of the oval window might slightly improve middle ear transfer and thus explain the small increase in DPOAE amplitude . In contrast to the 2f1 − f2 DPOAE , the 2f1 − f2 CMDP showed a decrease in amplitude during injection . Unfortunately , in literature very little can be found about the relation between DPOAE and CMDP . Still , it were Kemp and Brown -LSB- 6 -RSB- who found close parallels in the behavior of the 2f1 − f2 DPOAE and CMDP during and after anoxia in the guinea pig . Group latencies and third-tone suppression were found to be very similar , linking both signals to have a common origin . The DPOAE and CMDP are generated in response to the same acoustic stimuli . The acoustic primaries are transferred through the external and middle ear to eventually reach the sensory epithelia in the cochlea . The cochlea as a non-linear mechano-electrical transducer transforms sound pressure waves into electrical information . This forward transduction process is called the MET . The CM potential is a direct result of this process and is thought to be mainly produced by OHCs . On the other hand , there is also a reverse electromechanical transduction in which the OHC mechanically influences the vibration of the cochlear partition -LSB- 7 -RSB- . Sound is transmitted back to the external ear where the acoustic DPOAE can be measured ; the backward transmission . The rise and fall times of the DPs in response to changes in inner ear pressure were derived from the fitted curves -LRB- Figs. 2 , 3 , 4 -RRB- . As both CMDP and DPOAE were measured , this yielded information on forward and backward transmission . As anticipated , the time constants for the CMDP were smaller than the time constants for the DPOAE . Indeed , the latter would travel back and forth the middle ear which understandably costs more time . However , the difference has not the form of a simple longer delay . The explanation for this observation remains tentative . The averaged differences were 0.4 and 1.15 s for the 2f1 − f2 DP during increase and decrease of inner ear pressure , respectively . At pressure increase all measured signals almost directly followed the change in inner ear pressure . Time constants varied from 1.17 to 1.52 s with respect to 1.25 s for the inner ear pressure curve . However , with pressure decrease there was a delay of 1 -- 2 s for all measured signals . Measured differences can not be accounted for by delay in measuring equipment , for this was < 0.18 s. Assumed that the overall stiffness of the stapes-oval window-system governs the behavior of the DPOAE 2f1 − f2 amplitude , it is expected that it would follow stiffness changes directly and not 2 s later , as observed . It is conceivable that a delayed change in the endocochlear potential -LRB- EP -RRB- could be the cause of difference in τ values . However , in experiments by Salt and DeMott -LSB- 9 -RSB- the EP followed a temporary pressure change with a delay of < 0.1 s. So , the mechanisms for the observed delays in inner ear pressure recovery remain to be elucidated . Two-tone distortions are generated during non-linear mechanical amplification in the cochlea . Generation of the 2f1 − f2 depends on asymmetric component of a non-linear transfer function whereas the f2 − f1 depends on symmetric components . A change of the operating point is reflected in the level of the f2 − f1 distortion . In the gerbil low-frequency tones of 5 Hz were used to bias the position of the cochlear partition by Frank and Kossl -LSB- 4 , 5 -RSB- . By low-frequency modulation of the 2f1 − f2 DPOAE , Bian et al. -LSB- 1 -RSB- described the forward MET by a sigmoid-shaped function , which related the displacement of the basilar membrane to the response of the hair cells . By injecting artificial perilymph into scala tympani of the cochlea , the basilar membrane is temporarily displaced . Thus , by this displacement toward scala media , the operating state of the cochlear amplifier is also influenced . We measured a small decrease in the amplitude of the 2f1 − f2 distortion in CM -LRB- with respect to the amplitude of f1 in CM -RRB- and a small increase in the f2 − f1 in CM . Using the model by Bian et al. -LSB- 1 -RSB- this leads to the conclusion that the operating point for hair cell transduction is somewhat shifted from a symmetric position . This shift leads to an increase in even-order distortion and a decrease in odd-order distortion . Along these lines of reasoning we would also expect the 2f1 − f2 DPOAE to decrease . This might be the case at the generation sites -LSB- 15 -RSB- , but this effect is then more than compensated for by an improved middle ear transfer . Anyhow , the observed changes are small . Changes of overall inner ear fluid pressure have minor effects on cochlear function . It may be that creating an artificial endolymphatic hydrops , by injecting artificial endolymph into scala media instead of scala tympani , has a larger effect . This is currently tested in further research , which will hopefully give insight into diseases with pathologically changed inner ear fluid volumes , as in Ménière 's disease .

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perilymph
injection
inner ear pressure
2f1 − f2
f2 − f1
cmdp
dpoae
guinea pig