From Star Charts to Stoneflies: Detecting Relationships in Continuous Bivariate Data

Garvey, James E.; Marschall, Elizabeth A.; Wright, Richard

doi:10.2307/176944

Cited by 36 publications

(55 citation statements)

References 8 publications

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“…We used a two-dimensional Kolmogorov-Smirnov (2DKS) test to search for threshold relationships between flow and chlorophyll a in the dammed and undammed reaches (Garvey et al 1998). The 2DKS test searches for the maximum change in bivariate distributions relative to random expectations generated by 5,000 rerandomizations of the data.…”

Section: Discussionmentioning

confidence: 99%

Linking silver carp habitat selection to flow and phytoplankton in the Mississippi River

2011

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Invasive silver carp (Hypothalmichthys molitrix) occurs throughout much of the Mississippi River and threatens the Laurentian Great Lakes. To quantify habitat selection relative to river flow and potential phytoplankton food, 77 adult silver carp were implanted with ultrasonic transmitters during spring 2008 through spring 2009 in adjacent upstream dammed and downstream undammed reaches (48 km total) of the Mississippi River. Sixty-seven percent of the fish were located. Selection of major river habitat features (dammed vs. undammed, backwaters, channel border, wing dikes, island side channels, and the main channel) was quantified. Flow rates and chlorophyll a concentration were compared between silver carp locations and random sites. Foregut chlorophyll a concentrations plus presence of macrozooplankton and detritus of 240 non-tagged silver carp were quantified. About 30% of silver carp moved upstream into the dammed reach, where average flow was slower and chlorophyll a concentration was higher. Silver carp selected wing dike areas of moderate flow (about 0.3 m/s) and elevated chlorophyll a (about 7 lg/L) relative to random sites. No silver carp occurred in areas where flow was absent. Wing dikes were preferred while the main channel was avoided. Chlorophyll a concentrations in guts were positively related to temperature and were unrelated to flow or river chlorophyll a concentration. Macrozooplankton and detritus were rare in guts. Silver carp seek areas of low flow and successfully forage across a range of temperatures, flows, and chlorophyll a concentrations that occur in rivers and large lakes.

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Section: Discussionmentioning

confidence: 99%

Linking silver carp habitat selection to flow and phytoplankton in the Mississippi River

2011

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“…For our most conservative tests we compared negative slopes to an expected slope of 0. We also tested for a bivariate distribution of the relationship between C:N and Nspecific uptake rates using a non-parametric, 2-dimensional Kolmogorov-Smirnov test (Garvey et al 1998) and with piecewise linear regression using Statistica 6.1 (Statsoft, Tulsa, Oklahoma).…”

Section: Methodsmentioning

confidence: 99%

Carbon and nitrogen stoichiometry and nitrogen cycling rates in streams

et al. 2004

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Stoichiometric analyses can be used to investigate the linkages between N and C cycles and how these linkages influence biogeochemistry at many scales, from components of individual ecosystems up to the biosphere. N-specific NH4+ uptake rates were measured in eight streams using short-term 15N tracer additions, and C to N ratios (C:N) were determined from living and non-living organic matter collected from ten streams. These data were also compared to previously published data compiled from studies of lakes, ponds, wetlands, forests, and tundra. There was a significant negative relationship between C:N and N-specific uptake rate; C:N could account for 41% of the variance in N-specific uptake rate across all streams, and the relationship held in five of eight streams. Most of the variation in N-specific uptake rate was contributed by detrital and primary producer compartments with large values of C:N and small values for N-specific uptake rate. In streams, particulate materials are not as likely to move downstream as dissolved N, so if N is cycling in a particulate compartment, N retention is likely to be greater. Together, these data suggest that N retention may depend in part on C:N of living and non-living organic matter in streams. Factors that alter C:N of stream ecosystem compartments, such as removal of riparian vegetation or N fertilization, may influence the amount of retention attributed to these ecosystem compartments by causing shifts in stoichiometry. Our analysis suggests that C:N of ecosystem compartments can be used to link N-cycling models across streams.

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“…We also calculated the annual coefficient of variation (CV) for sediment denitrification rates and independent variables and evaluated the relationship between the two with regression analysis. Because independent variables span such a broad range of values temporally, and the response of denitrification along this range can vary greatly, a two-dimensional Kolmogorov-Smirnov test was used to determine the threshold at which a nonrandom pattern between denitrification and the independent variable dissipates (Garvey et al 1998).…”

Section: Statistical Analysesmentioning

confidence: 99%

Spatial and Temporal Variability in Sediment Denitrification Within an Agriculturally Influenced Reservoir

et al. 2005

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Reservoirs are intrinsically linked to the rivers that feed them, creating a river-reservoir continuum in which water and sediment inputs are a function of the surrounding watershed land use. We examined the spatial and temporal variability of sediment denitrification rates by sampling longitudinally along an agriculturally influenced river-reservoir continuum monthly for 13 months. Sediment denitrification rates ranged from 0 to 63 lg N 2 O g ash free dry mass of sediments (AFDM) À1 h À1 or 0-2.7 lg N 2 O g dry mass of sediments (DM) À1 h À1 at reservoir sites, vs. 0-12 lg N 2 O gAFDM À1 h À1 or 0-0.27 lg N 2 O gDM À1 h À1 at riverine sites. Temporally, highest denitrification activity traveled through the reservoir from upper reservoir sites to the dam, following the load of high nitrate (NO 3 À -N) water associated with spring runoff. Annual mean sediment denitrification rates at different reservoir sites were consistently higher than at riverine sites, yet significant relationships among theses sites differed when denitrification rates were expressed per gDM vs. per gAFDM. There was a significant positive relationship between sediment denitrification rates and NO 3 À -N concentration up to a threshold of 0.88 mg NO 3 À -N l À1 , above which it appeared NO 3 À -N was no longer limiting. Denitrification assays were amended seasonally with NO 3 À -N and an organic carbon source (glucose) to determine nutrient limitation of sediment denitrification. While organic carbon never limited sediment denitrification, all sites were significantly limited by NO 3 À -N during fall and winter when ambient NO 3 À -N was low.

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From Star Charts to Stoneflies: Detecting Relationships in Continuous Bivariate Data

Cited by 36 publications

References 8 publications

Linking silver carp habitat selection to flow and phytoplankton in the Mississippi River

Linking silver carp habitat selection to flow and phytoplankton in the Mississippi River

Carbon and nitrogen stoichiometry and nitrogen cycling rates in streams

Spatial and Temporal Variability in Sediment Denitrification Within an Agriculturally Influenced Reservoir

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