Understanding the Relationship Between Natural Conditions and Loadings on Eutrophication: Algal Indicators of Eutrophication for New Jersey Streams

Transcription

1 Undestanding the Relationship Between Natual Conditions and Loadings on Eutophication: Algal Indicatos of Eutophication fo New Jesey Steams Final Repot Yea 2 Repot No. 3-4 Submitted to the New Jesey Depatment of Envionmental Potection Division of Science, Reseach and Technology by Kain Ponade and Donald Chales Patick Cente fo Envionmental Reseach The Academy ofnatual Sciences 19 Benjamin Fanklin Pakway Philadelphia, PA Apil23

2 Executive Summay Nuisance levels of algae inn ew Jesey ives and steams esult pimaily fom high levels of nutients coming fom a vaiety of agicultual, esidential and uban souces. This epot pesents esults of the fist two yeas of a poject to develop algal indicatos fo steams and ives in the Piedmont ecoegion ofn ew Jesey. These indicatos ae designed to assess levels and causes of cultual eutophication. All sites (37) studied fo this poject ae pat of the NJ Ambient Monitoing Netwok. They wee sampled in 2 and 21 fo diatoms, soft-algae and wate chemisty. Measuements of algal biomass, algal species composition, physical steam conditions and wate chemisty wee used to develop models and metics fo quantifying algal biomass and infeing nutient concentations fom diatoms and soft-algae. The following summaizes findings of the eseach pesented in this epot : The elationships between algal biomass measues ( Chl a and AFD M) and nutient concentations wee not stong o significant, based on Speaman's ank-ode coelations that included data fom all the sites. Howeve, vaiations in contents of Chl a can be explained though a combination of basin size (also eflecting ive width and light conditions) and nitogen (N 3 -N) (highly coelated with phosphous). Thee hunded and nine diatom taxa wee found in the samples. Most wee pollutiontoleant species. Only a few soft-algae species, the most common being Cladophoa, a filamentous geen alga, wee found often in high abundance in nutient eniched steams. Multivaiate analysis of species and envionmental vaiables shows that total phosphous (TP), othophosphate (-P), nitogen (N 3 -N) and ammonia (NH 3 -N) explain significant diffeences in diatom assemblage composition. This finding povides statistical justification fo developing diatom-based models and indices of nutient conditions. Nutient infeence models and indices will be useful as wate quality management tools. A model fo infeing TP (?(appaent)=.72; RMSE (boot)=.33 log jlg TP) developed using the complete 2 dataset (n=85), has good pedictive ability with a bootstapped 2 =.55, and when tested on the samples collected in 21 (=.61). Thee indices developed fo Euopean ives (Biological Diatom Index, the Polluosensitivity Index and the Tophic Diatom Index) all coelated elatively well with eithe -P and/o TP. This suggests that all thee methods would povide good nutient monitoing tools fo the ives of the NJ Piedmont. Simple community metics (e.g., species divesity) wee geneally not good indicatos of nutient conditions. A combination of indicatos is best fo monitoing nuisance levels of algae and nutients in NJ ives. Fo monitoing algal biomass, use the EPA Rapid Bioassessment Potocol and measue Chl a. To assess levels of phosphous concentation and thei influence on algae, The Academy of Nat ual Sciences Patick Cente fo Envionmental Reseach

3 we ecommend using diatom infeence models and the Euopean Tophic Diatom Index (TDI). In Yea 3 of this poject a lage data set will be used to futhe exploe the elationships between biomass and nutients, and to develop and test additional metics and models. The oles of ive size, light and nitogen concentations as influences on biomass-nutient elationships will be futhe quantified and be accounted fo in developing and applying models and metics. The Academy of Nat ual Sciences ii Patick Cente fo Envionmental Reseach

4 Table of Contents Executive Summay i List of Tables vi List of Figues... vii List of Abbeviations viii 1 Intoduction Study hypotheses, goals and appoach Study aea Methods Site selection Sampling peiod Collection of samples/data Site chaacteization/establishment of sampling eaches Wate chemisty samples Diatom and biomass/soft algae samples Visual biomass estimate (EPA apid bioassessment potocol) Additional data (wate chemisty, landuse) Algal sample ps;maation and analysis Data stoage and documentation Data analysis Wate chemisty: PCA to exploe gadients and vaiability among sites Algal biomass Speaman's ank-ode coelation (coelations between nutients, algal biomass and algal species composition) Fowad stepwise egession (analysis of pincipal factos influencing algal biomass) Diatom assemblages Detended Coespondence Analysis (DCA) to detemine pincipal pattens of vaiation in diatom species composition Data sceening: envionmental vaiable with exteme influence on species composition Odination analysis: CCA (influence of envionmental vaiables on diatom species composition) The Academy of Nat ual Sciences iii Patick Cente fo Envionmental Reseach

5 WA-egession and calibation (development and testing of nutient iifeence models) Calculation of diatom metics Divesity metics and othe simple metics Euopean diatom indices Results Envionmental data Wate chemisty, biomass concentations and summay of site chaacteistics PCA: gadients and vaiability in envionmental data Algal biomass Speaman's ank-ode coelation Compaison between esults of diffeent biomass measues/estimates (Chl a, AFDM, visual estimate (RBA) and % biomass estimate (semiquantitative count method) Relationships between algal biomass measues and nutient conditions Analysis of pincipal factos influencing algal biomass (fowad stepwise egession) Algal floa- species composition Composition of algal floa in biomass samples (soft-algae floa) Pincipal pattens in the vaiation of diatom assemblage composition (DCA) Relationship between species composition and envionmental vaiables, especially nutients Soft algae: Speaman's ank-ode coelation Diatoms: odination analysis; influence of envionmental vaiables on diatom species composition Development of nutient infeence models based on diatom species composition Data sceening Weighted aveaging- nutient infeence models Evaluation of the pefomance of the TP model Evaluation of diatom metics, indices and infeence models Test of the NJ Piedmont nutient infeence model on the yea 2 samples Divesity metics and othe simple metics Euopean Indices (TDI, IBD and IPS) Discussion Pincipal factos influencing algal biomass Pincipal vaiables influencing algal biomass Nutient-biomass elationships as assessed by coelations Compaison and evaluation of methods fo estimating algal biomass Compaison and evaluation of diatom metics and models Nutient-infeence models Simple metics The Academy of Nat ual Sciences iv Patick Cente fo Envionmental Reseach

6 6.3.3 Euopean indices Compaison diatom infeed TP and impaiment classifications based on macoinvetebate metics (AMNET) Evaluation of the EPA pecentile method fo detemining efeence conditions Conclusion: Recommendation fo use of the ideal algal indicato monitoing pogam fo the NJ Piedmont... 4 Refeences Appendix 1: Summay of site chaacteistics Appendix 2: Diatom species list Appendix 3: Speaman's ank-ode coelation Appendix 4: Results of fowad stepwise egession fo dependent vaiables Chl a and AFDM The Academy of Nat ual Sciences v Patick Cente fo Envionmental Reseach

7 List of Tables Table 1 List of sites sampled in Table 2 List of sites sampled in Table 3 Summay of nutient data chaacteistics and concentations at all sampling sites Table 4 Vaiables significantly influencing algal biomass, as detemined by Fowad Stepwise egession Table 5 Pecentage estimates of the most common species of algae that make up the lagest popotion of algal cells and algal biomass Table 6 Pedictive powe of diatom infeence models fo TP, -P NH 3 -N and N3-N, as detemined using WA-egession and calibation Table 7 Speaman's ank-ode coelation between diatom metics and diffeent vaiables expessing nutient impaiment Table 8 Peason's poduct-moment coelation matix compaing Euopean diatom indices with diffeent measues of nutient impaiment The Academy of Nat ual Sciences vi Patick Cente fo Envionmental Reseach

8 List of Figues Figue 1 Figue 2 Figue 3 Figue 4 Figue 5 Figue 6 Figue 7 Figue 8 Figue 9 Figue 1 Figue 11 Figue 12 Figue 13 Location of the NJ Nothen Piedmont physiogaphic povince within Omenik's Level III ecoegion 64, the "nothen Piedmont"... 6 Site locations in the Piedmont physiogaphic povince ofnew Jesey fo sampling yeas 2 and TP and Chl a concentations measued in 2 and Main algal goups and thei contibution to pecent estimated algal cove, odeed by inceasing Chl a content measued at the site PCA including 24 sites and 16 vaiables sampled in 2 and Coelations ofo-p and TP with Chl a concentations DCA showing site scoes CCA of diatom assemblage scoes Obseved vesus pedicted TP fo the W A infeence model developed based on 85 diatom samples collected in Test oftp infeence model: plot of measued vesus diatom- infeed TP... 3 Scatteplot of measued -P vesus the indices calculated by Specific Polluosensitivity index (IPS) fo a112 and 21 samples Map showing the diffeence in the atings of ive quality as calculated by two Euopean diatom indices, the Specific Polluosensitivity index (IPS) and the Biological Diatom Index (IBD) Box-plots compaing diatom infeed TP to AMNET macoinvetebate impaiment atings The Academy of Nat ual Sciences vii Patick Cente fo Envionmental Reseach

9 List of Abbeviations AFDM AMNET ANSP boot CCA Chla DCA IBI NAWQA NJDEP -P PCA PCER RBA RMSEP SWQS TN TKN TP USGS U.S. EPA WA ash fee dy mass Ambient Biomonitoing Netwok The Academy ofnatual Sciences, Philadelphia bootstapped Canonical Coespondence Analysis chloophyll a Detended Coespondence Analysis index ofbiotic integity National Wate-Quality Assessment New Jesey Depatment of Envionmental Potection othophosphate Pincipal Component Analysis Patick Cente fo Envionmental Reseach apid bioassessment oot mean squae eo ofpediction Suface Wate Quality Standads total nitogen total Kjeldahl nitogen total phosphous United States Geological Suvey United States Envionmental Potection Agency weighted aveaging The Academy of Nat ual Sciences viii Patick Cente fo Envionmental Reseach

10 1 Intoduction Nuisance levels of algae in New Jesey (NJ) ives and steams esult pimaily fom high levels of inoganic nutients coming fom a vaiety of natual, agicultual, esidential and uban souces. Excessive algal gowth can cause wate quality poblems and can ham the designated use ofives and steam in diffeent ways (Dodds and Welch 2, U.S. EPA 2b, ENSR 21). Nutient enichment has been shown to incease benthic algal biomass in ives though addition ofboth nitogen and phosphous (Blum 1956, Fancoeu 21). Many ecent studies focus on undestanding the effect of nutient enichment on excessive peiphyton gowth in ives in ode to develop management stategies fo steam and ive eutophication (Dodds and Welch 2, Dodds et al. 22, Biggs 2, Smith et al 1999). Nationwide thee is a continuous discussion concening the establishment of nutient limits and thesholds; thei implementation is diffeent fom state to state. The U.S. EPA technical guidance manual fo ives and steams (U.S. EPA 2a) ecommends thee appoaches fo development of nutient and algal citeia: (1) the use of efeence steams, (2) applying pedictive elationships to select nutient concentations that will esult in appopiate levels of algal biomass and (3) developing citeia fom thesholds established in the liteatue. Also, in the Ambient Wate Quality ecommendations fo U.S. EPA Rives and Steams Aggegate Nutient Ecoegion IX (U.S. EPA 2b), U.S. EPA ecommends establishing nutient efeence conditions in ives and steams, using two methods: 1) establishing efeence conditions based on the uppe 25th pecentile (75th pecentile) of all nutient data fom all eaches sampled, o 2) detemining the lowe 25th pecentile of the population of all steams within a egion. A eview of this appoach fo the New England Intestate Wate Pollution Contol Commission evealed that the anges of pedicted biomass poduction esponses to nutients, as tested fo the subecoegions 59 and 84, would be below consensus theshold values (ENSR 21). Nevetheless, the establishment of efeence conditions based on pecentiles will set diffeent theshold values in diffeent egions, depending on the ange of oveall wate quality in the ives of each paticula egion. These thesholds will be too high in ecoegions with ives having pedominantly high nutient concentations as compaed to ecoegions with mainly low nutient ives and vice vesa. The applicability of this method to the NJ Piedmont ecoegion needs futhe eview. In this study, we apply the poposed U.S. EPA pecentile method to the NJ Nothen Piedmont dataset, in ode to calculate efeence conditions. We compae ou esults to the suggested Level III Subecoegion 64 efeence conditions, Ecoegion IX (U.S. EPA 2b) (see Discussion). The cuent NJ Suface Wate Quality Standads (SWQS) N.J.A.C. 7:9B-1.14(c) state that ''phosphous as total P shall not exceed.1 (mg/l) in any steam, unless it can be demonstated that total Pis not a limiting nutient and will not othewise ende the wates unsuitable fo the designated uses." (NJ DEP 21). The SWQS futhe state as a nutient policy, N.J.A.C. 7:9B-1.5(g)2: "Except as due to natual conditions, nutients shall not be allowed in concentations that cause objectionable algal densities, nuisance aquatic vegetation, o othewise ende the wates unsuitable fo the designated uses." Theefoe, cuent NJ Suface Wate Quality Standads ae ecommending a theshold of.1 mg/l TP in steams. Nevetheless, The Academy of Nat ual Sciences Patick Cente fo Envionmental Reseach

11 the validity of this theshold value and the impact of nutient inputs on algal gowth in NJ ives has not been studied in detail. The NJ DEP theefoe needs a bette undestanding of the impact of the nutients nitogen and phosphoous on ive and steam systems. Futhemoe, nutientalgal biomass elationships need to be investigated in moe detail to develop altenative nutient citeia and thesholds that can be applied to the state's ives and steams. The state ofnj monitos ive quality though an extensive Suface Wate Quality Monitoing Netwok, oiginally measuing chemisty paametes 5 times a yea at 2 stations fom 1976 to the mid 199s. Since 1997, 115 stations ae measued 4 times a yea statewide (NJ DEP 2). Also, biological indicatos ae used to monito ive health though the state's Ambient Biomonitoing Netwok (AMNET) established in AMNET is an extensive netwok of 82 stations statewide. Macoinvetebates ae used to assess the biological impaiment and geomophologic conditions ofnj ives (NJ DEP 2). Macoinvetebates ae widely used as indicatos fo oganic pollution (Babou et al. 1999), but they do not eflect inoganic nutient levels well (Kelly and Whitton 1998, Schwoebel1999). Theefoe the NJ DEP has a need fo application of diffeent additional biological indicatos to assess eutophication and elationships between nutient conditions and elated excessive algal gowth in NJ steams. Algae, especially diatoms, ae known to be good indicatos of wate quality and have been used in the United States since the 195s (Patick 1951). Algae ae impotant ecosystem components and they ae widely distibuted in many habitats. The main advantages of using diatoms as indicatos ae the following: taxa ae numeous and lage numbes of individuals can be collected easily; diatoms can be identified to the lowest taxonomic level and stongly coelate with envionmental chaacteistics; they ae sensitive to stess, and espond apidly to envionmental change; and fmally, they can be stoed efficiently. Fo all these easons diatoms ae valuable and cost-effective indicatos fo monitoing wate quality (Babou et al. 1999, Dixit et al.1992, Stevenson and Pan 1999). This study was designed as a two-yea poject, initiated in July 2. The pupose of this poject was to develop algal indicatos of steam and ive eutophication that can be applied in a egulatoy context as seconday citeia fo identifying nutient impaiment. These indicatos ae based on elationships between extant wate quality citeia (e.g., phosphous and nitogen concentations) and ovet signs of eutophication. They ae based on an undestanding of algal dynamics in New Jesey steams, and help to distinguish between situations in which nutient concentations ae high due to natual envionmental conditions and those that esult fom anthopogenic influences. The Academy of Nat ual Sciences 2 Patick Cente fo Envionmental Reseach

12 2 Study hypotheses, goals and appoach Hypotheses: This study is based on the following woking hypotheses: 1) nuisance levels ofbenthic algal gowth in NJ Piedmont ives ae caused by high concentations of nutients, especially phosphous and nitogen; 2) benthic algal biomass and species composition can be used as indicatos of levels and causes of ecological impaiment, pimaily those elated to the nutients phosphous and nito gen. Goals: To addess these woking hypotheses, the geneal objectives ofthis study wee to: 1) exploe the elationships between algal biomass as well as algal species composition and nutients; 2) develop and test algal indicatos of nutients and wate quality applicable to NJ Piedmont ives; 3) make ecommendations to the NJ DEP as to which indicatos ae best fo monitoing nutient impaiment in NJ Piedmont ives. Appoach: In ode to meet these objectives, the following appoach was used in the analysis of the collected data. 1) Fist, all data wee assembled in a database and files wee ceated fo data analysis and to pesent basic data in tables and appendices. 2) We examined site envionmental data and ceated tables. We an a PCA of envionmental vaiables to undestand the elative impotance of majo gadients and vaiability among sites. 3) The algal biomass data wee summaized and chaacteized. Basic data wee pepaed in tables, gaphics and appendices, and statistical pogams wee used to do coelations and egessions among the diffeent measues and to detemine how well they agee with each othe. The Academy of Nat ual Sciences 3 Patick Cente fo Envionmental Reseach

13 4) The elationships among algal biomass measues and envionmental chaacteistics, especially nutients, wee evaluated. We used odination and coelation techniques to evaluate the potential fo pedictive elationships between nutients, othe envionmental chaacteistics and algal biomass. 5) Biomass indicatos of nutient concentations wee developed and evaluated using simple and multiple egessions. 6) The elationships among algal species composition and envionmental chaacteistics, especially nutients, wee evaluated using odination methods and egessions with diatoms and soft-algae goups. 7) We developed and evaluated species composition-based indicatos of nutient concentations. We used indicato taxa, simple metics, Euopean metics, infeence models, a Nothen Piedmont TP model and othe metics/indicatos. 8) Potential indicatos fo estimating algal biomass and fo infeing elative phosphous concentations and oveall wate quality wee compaed. 9) Based on ou esults, we ecommended the optimal set of available indicatos fo use in a monitoing pogam. The Academy of Nat ual Sciences 4 Patick Cente fo Envionmental Reseach

14 3 Study aea The study aea was esticted to the Piedmont physiogaphic povince in New Jesey. This limitation helps to minimize the natual vaiability in geochemisty, a majo facto affecting algal species assemblage composition. In this study we efe to the ''NJ Piedmont physiogaphic povince" following the geophysical povinces concept based on taditional geological featues (Wolfe 1977) used by the state ( We decided to follow this concept, because the delimitation of the Piedmont aea follows the bedock geology, which in tun influences steam geochemisty. The NJ Piedmont physiogaphic povince foms the notheasten extension ofomenik's Level III ecoegion 64, the "nothen Piedmont" (Omenik 1987) (Fig. 1). All of ou site selection was based on a NJ GIS ARC/INFO Geogaphic Infomation Systems (GIS) shapeftle (geophysical.shp) eceived though the NJ DEP, and NJ DEP geological map ( (NJ DEP 1999). The geomophology of the NJ Piedmont is chaacteized by iegula plains with low to modeately high hills and tableland, with elevations inceasing to the nothwest (US EPA 2b, Tedow 1986). The geology of the Piedmont is mainly late Tiassic and Ealy Juassic age sedimentay ocks, siltstone, shale, sandstone and conglomeate. Resistant gneiss and ganites fom a 2- to 8-ft (61- to 244-m) high escapment in the Nothwest Piedmont. Gay Sandstone (Stockton fomation), ed and gay agillite (Lockatong Fomation), and ed sandstone, including conglomeate (Bunswick Fomation), cove most of the Notheast and the southen pat of the Piedmont (Tedow 1986). In the Notheast, volcanic activity associated with ifting of the ock layes of the Piedmont esulted in basalt and diabase intusions intelayeed with sandstone and shale. Both basalt and diabase, being moe esistant to eosion, fom idges and uplands in the notheast ( The climate in the NJ Piedmont is tempeate and continental (Tedow 1986). The aveage annual pecipitation anges between 43 and 4 7 in ( 192 to 1194 mm) ( and appoximately half fulls duing the summe season. Annual snowfall aveages 25 in (635 mm) (expessed as snow) in cental New Jesey. The annual mean tempeatue is appoximately 54 F (12.2 C) at Tenton (4-yea aveage), with 15-2 days usually ecoding tempeatues above 9 F (32.2 C) (Tedow 1986). In the cental Piedmont (Plainfield, NJ) the aveage July tempeatue is 7YF (24 C) and the aveage Januay tempeatue is 3. F ( -1 C) (ONJSC ; I climate.utges. edu/ stateclim/noms/monthly/mean.html). The aveage numbe of fost fee days is 179 in the cental and southen inteio (ONJSC , and the gowing season lasts fom mid-mach to Octobe (Tedow 1986). The Academy of Nat ual Sciences 5 Patick Cente fo Envionmental Reseach

15 Pennsylvania flllllllllll N.J Pledmon c c::::::::l sludv aea Figue 1: Location of the NJ Nothen Piedmont physiogaphic povince within Omenik's Level III ecoegion 64, the "nothen Piedmont." Landuse in the NJ Piedmont is pimaily a mix of famland and uban aeas. The uban and industial aeas ae concentated in the notheasten, and to a lesse degee, the southwesten potion of the Piedmont. Nutient inputs into the ives of the NJ Piedmont come fom a vaiety of natual, agicultual, esidential and uban souces and make this aea an ideal egion to investigate impacts of nutient input fom diffeent souces. The ives and steams of this aea fall within the U.S. EPA Rives and Steams Aggegate Nutient Ecoegion IX, the southeasten tempeate foested plains and hills. This Aggegate Ecoegion contains 11 subecoegions, including the Nothen Piedmont as subecoegion 64 (Omenik's Level III ecoegion) (US. EPA 2b ). The ives in this subecoegion have elatively high nutient concentations. The median total phosphoous (TP) values, calculated ove one decade, ange fom 2.5 to 176 ).lg/l, with a summe mean of 15 ).lg/l and a median of 7 ).lg/l. Median total nitogen (TN) values ange fom.5 to 12 mg/l with a summe mean of 4.8 mg/l and a median of 4.2 mg/l (U.S. EPA 2b). The Academy of Nat ual Sciences 6 Patick Cente fo Envionmental Reseach

16 4 Methods 4.1 Site selection We selected an initial set of3 study sites to be sampled in fall2 in coopeation with NJ DEP staff, mainly Tom Belton. Because a goal of this study was to develop algal indicatos of anthopogenic nutient inceases, it was impotant to select a suite of sites with elatively simila natual envionmental conditions, but with a wide ange of nutient concentations. The sites ae esticted to the Piedmont physiogaphic povince in nothen New Jesey, and have a elatively limited ange of hydology, mophology and substate type. This limitation helps to minimize the vaiability in geochemisty, a majo facto affecting algal species composition. In addition, we used nutient concentation data fom the NJ DEP as an indication of wateshed souces of anthopogenic phosphous and nitogen. Fo all sites, chemisty data wee available eithe though the NJ monitoing netwok pogam o though the USGS fo thei monitoing stations. All sites ae pat of the NJ Ambient Monitoing Netwok. We selected sites with a ange of impaiment fom no impaiment to sevee impaiment, based on AMNET Macoinvetebate classifications made in 1992/93 and 1998/99 (Table 1). About one-thid ofthe selected sites wee studied in the same yea (2) by the NJ DEP to develop a fish IBI. Thee sites (AN215, AN318 and AN321) sampled duing 2 wee accidentally located in the Highlands and two sites (AN382, AN439) wee sampled in the Inne Coastal Plains physiogaphic povinces (Fig. 2), due to initially inaccuate intepetation of the NJ Piedmont povince delimitation. This eo was coected late, and the samples wee excluded fom development of indicato metics. Duing the second study yea (2 1) we selected 13 sites (in coopeation with NJ DEP staff), classified in thee categoies: 1) "new sites" to fill in data gaps in the gadient of phosphous concentations, and to supplement the "calibation" set chosen duing the fist yea, 2) "test sites" to evaluate indicatos developed duing the fst yea and, 3) "duplicate sites" to investigate vaiation in algal biomass and diatom assemblage composition between yeas one and two. Selection citeia wee the same as those used duing yea one with an alteed focus within each categoy: "new sites" have high concentations oftp (as ecoded by the NJ DEP and/o USGS). "Test sites" cove a ange fom no- to sevee-impaiment based on AMNET esults and have a USGS gaging station. We selected as "duplicate sites," AMNET sites with sevee impaiment in 1998 and/o that wee planned to be Fish IBI sites in 21 (see Table 2). All ives selected fo both yeas ae 1st to 6th ode wadeable steams. The classification is based on infomation fom the NJ DEP' s GIS hydogaphy steam netwok line shape files fo New Jesey counties, geneated as line Aclnfo coveages fom USGS 1:24, Digital Line Gaph (DLG) files ( maps). The sites sampled ae located in the following USGS Wateshed Management Aeas: Cental Delawae, Millstone, Lowe Raitan, Noth and South Banch Raitan Rive, Uppe Passaic, Whippany and Rockaway, Athu Kill, Lowe Passaic and Saddle, Hackensack and Packsack and Pompton, Wanaque and Ramapo. Most of them ae located in Someset, Mois and Begen counties, and a lesse potion ae distibuted ove Mece, Huntedon, Middlesex, Union, Passaic and Essex counties. The Academy of Nat ual Sciences 7 Patick Cente fo Envionmental Reseach

17 Legend 2 sites 21 sites Figue 2: Site locations in the Piedmont physiogaphic povince of New Jesey fo sampling yeas 2 and 21. Site numbes coespond to New Jesey AMNET site location IDs. See Tables 1 and 2 fo site names and locations. The Academy of Nat ual Sciences 8 Patick Cente fo Envionmental Reseach

18 Table 1: List of sites sam led in 2. NJ Site ID I Wate body I Impaiment 1992/93 I Impaiment 1998/99 AN81 INishisakawick Ck IN on-impaied IN on-impaied AN115 IMiyRun!Modeate!Modeate AN118 IAssunpink Ck!Modeate!Modeate AN194 IRahwayR!Modeate!sevee AN195 IRahwayR!Modeate!Sevee AN211 IVan SaunBk!Modeate!Modeate AN215 I Pimose Bk IN on-impaied IN on-impaied AN227 IDeadR!Modeate!Modeate AN238 IWhippanyR!Modeate!Modeate AN274!Passaic R I Modeate!Non-Impaied AN318!Spuce Run IN on-impaied IN on-impaied AN321 I Mulhockaway Ck IN on-impaied IN on-impaied AN341!Raitan R S B!Modeate IN on-impaied AN37 I Lamington R IN on-impaied IN on-impaied AN374 I Raitan R N B IN on-impaied IN on-impaied AN382 I Millstone R!Modeate!Modeate AN396 I Heathcote Bk!sevee IN on-impaied AN414 I Millstone R!Modeate!Modeate AN424 IBoundBk!Modeate!Modeate AN439!Manalapan Bk I sevee!modeate ANOlll I Shipetaukin Ck!sevee!Modeate AN234!Whippany Rive I sevee IN on-impaied AN267!Ramapo Rive!Modeate IN on-impaied AN281 I Saddle Rive IN on-impaied!modeate AN291 I Saddle Rive I sevee I Modeate AN326 IS B Raitan Rive IN on-impaied I Modeate AN339 I Pleasant Run I Modeate IN on-impaied AN45 I Pike Run!Modeate I sevee AN413!Royce Bk!Modeate!sevee AN429 I Mile Run!Modeate I sevee Table 2: List of sites sam led in 21. NJ Site ID I AN115 AN192!Rahway Rive!Modeate!Modeate AN27 IPascack Bk!Modeate IN on-impaied AN29 ITenakill Bk I sevee I sevee AN211 IVan SaunBk!Modeate!Modeate AN231!Passaic Rive!Modeate!Sevee AN235!Whippany Rive!Modeate!Modeate AN237!Toy Bk!Modeate IN one AN274!Passaic Rive!Modeate IN on-impaied AN333!Neshanic Rive!Modeate!Modeate AN374 IN B Raitan Rive IN on-impaied IN on-impaied AN45 IPike Run!Modeate I sevee The Academy of Nat ual Sciences 9 Patick Cente fo Envionmental Reseach

19 4.2 Sampling peiod Duing both yeas, samples wee collected by ANSP staffmike Hoffmann, Diane Winte and Kain Ponade fom August though Octobe. The fist yea sites wee sampled fom 9 August though 3 Octobe 2. In the second yea, sampling was completed between 2 and 26 August 21. Duing the 2 field season, sampling was suspended fo two weeks to wait fo ives to ecove fom the scouing effect of high flow conditions caused by vey heavy ainfall events duing the second week in August. We chose to sample in late summe because the influence of highe steamflow velocity and dischage on algal assemblage composition is lowest duing this peiod. Based on the aveage of monthly mean steamflow calculated fo 77 yeas (since 1925), the lowest flow ecods in NJ ives wee measued in August, Septembe and Octobe ( Samples collected duing this time ae also most diectly compaable with sample data fom othe studies conducted in the aea, such as the National Wate-Quality Assessment Pogam (NAWQA), the EPA Ripaian Refoestation Poject and the Gowing Geene Poject all conducted at the PCER ( All these pojects wee conducted at the ANSP and follow USGS NAWQA Peiphyton sampling potocols ecommending sampling peiods to be conducted duing nomal low- o stable-flow peiods (Moulton et al. 22, Pote et al. 1993). 4.3 Collection of samples/data Site chaacteization/establishment of sampling eaches All sites sampled ae located at NJ DEP AMNET monitoing stations, which ae defined as the intesection of a oad and the ive to be sampled. Accoding to NJ DEP field sampling potocols, we sampled on the upsteam side of the bidge to minimize the effect of inputs fom automobile use/taffic and steet maintenance. Some exceptions wee made at sites whee conditions did not allow sampling upsteam and whee the downsteam side was consideed moe epesentative of the ive habitat. Pio to collection of wate chemisty and algal samples, we took detailed notes on geneal physical site chaacteistics, geomophology, weathe conditions, ovet signs ofhuman impact, etc. The sampling aea was divided into thee sampling eaches, so that vaiability among diffeent sections ofthe ives could be assessed. The thee sections wee detemined using the following citeia: each section should contain a minimum of2 iffies and 2 pools and the length of each each should be appoximately 1 times the channel width. Commonly used guidelines (Fitzpatick et a1.1998) ecommend a minimum each length of 15m fo wadeable steams. We did not follow these guidelines and established shote eaches because of the geneally smalle width of the ives sampled in the NJ Piedmont aea. The aveage width of the ives sampled was 13 m (ange of 3-5 m) and the aveage length of the established sampling eaches was 44 m (see Appendix 1a). We believe ou citeia wee satisfactoy fo establishing eaches that epesented the local vaiability within the ive. Once the eaches wee established, we ecoded infomation on all thee sections, made site dawings, and measued the physical chaacteistics of the sampling sites. Sites ae documented with digital images (Sony MVC-CD1), bunt on a CD and submitted to the NJ DEP. Fo each section, we made a visual The Academy of Nat ual Sciences 1 Patick Cente fo Envionmental Reseach

20 estimate of pecent substate type (boulde, cobble, gavel, sand, silt, bedock) and flow velocity. Light conditions (pecent open canopy cove) wee measued using a spheical densiomete Wate chemisty samples Wate chemisty samples wee taken pio to algal sampling to avoid distubance of the wate column and sediments. Samples wee taken using a plastic syinge with an attached filtation device. Laboatoy analysis ofn 3 -N, NH 3 -N, -P and TP was pefomed by the PCER Geochemisty Section (V elinsky 2). In 21, we took additional samples fo analysis of chloide, total alkalinity, total hadness and conductivity. Samples wee cooled immediately on ice in the field and shipped to the ANSP whee samples fo nutient analysis wee fozen immediately. Results ofthese analyses wee used to supplement those collected by the NJ DEP. Samples collected diectly by ANSP in the field bette epesent conditions nea the time that algal samples wee collected, and povide infomation ofthe natue and magnitude of vaiation in wate chemisty Diatom and biomass/soft algae samples Samples wee collected fom natual ock substates using techniques consistent with those used in the USGS NAWQA pogam (Moulton et al. 22) and the EPA Rapid Bioassessment potocols fo peiphyton (Babou et al. 1999). All sampling pocedues ae documented in a PCER potocol (Chales et al. 22). Two types of samples wee taken. One, a composite diatom sample, was ceated by andomly selecting 4-5 ocks of ca. 5 em diamete. The ocks wee caefully selected fom mid-steam and wee fee of visible filamentous algae. In 2, samples fom sticks, gavel o sand wee collected at five sites whee no ocks wee available (AN194, AN227, AN238, AN382, AN414). Algae wee emoved fom the ocks by scaping and bushing, placed in plastic containes and peseved in the field by keeping them on ice in a coole. The second type of sample was a quantitative composite biomass sample collected fo measuement of chloophyll a and ash-fee dy mass (AFDM). These samples wee analyzed by the Patick Cente fo Envionmental Reseach's (PCER) Geochemisty Section. Thee bigge ocks (with an aveage diamete of ca.1 em) wee selected andomly to epesent the distibution of algal coveage within each each section. Rock sufaces wee scaped, and outlines of ocks wee dawn on watepoof pape. Suface aea was measued using an aluminum foil method (Moulton et al. 22, Ennis and Albight 1982). NJ DEP guidelines wee followed fo pesevation and stoage ofchl a samples. All samples (diatoms and Chl a) wee peseved by keeping them on ice in a coole and wee shipped to the ANSP ove night fo immediate teatment in the laboatoy the next moning. In total, 85 diatom samples wee taken duing 2. Only 71 samples wee collected fo biomass in 2; biomass samples wee not collected at 6 sites with sandy substate. In 21, we only sampled ock substate, collecting 35 diatom and biomass samples in total. Both yea's datasets combined contain a total of 12 diatom samples and 16 biomass samples Visual biomass estimate (EPA apid bioassessment potocol) In addition to algal sample collection, the pecent cove and thickness of algal gowth was measued using the Rapid Peiphyton Suvey Method (EPA Rapid Bioassessment Potocol) developed by the U.S. EPA (Babou et al. 1999). This method povides a quantitative estimate of The Academy of Nat ual Sciences 11 Patick Cente fo Envionmental Reseach

21 filamentous and othe types of algae that often have patchy distibutions and whose biomass is difficult to quantify. Fo each sampling section, we measued pecent biomass cove fo each algal goup along thee tansects acoss the ive. Length of filamentous stains and thickness of algal mats pe algal goup wee also ecoded. Fo each section, an aveage was calculated fom the thee tansects and used in data analysis. We collected additional samples fo algal identification and examination unde the micoscope when identification in the field was not possible Additional data (wate chemisty, landuse) In addition to the wate chemisty and biomass data poduced at the PCER, all othe data wee povided by the NJ DEP though Tom Belton. Landuse data fo each wateshed wee assembled by Jack Pflaume (NJ DEP). Also, Jack Pflaume sent ANSP most of the additional chemisty data ecods collected by USGS and NJ DEP at the suface wate monitoing stations. He assembled available data fo the sampled peiphyton sites fo each sampling yea. Additional data wee etieved by Kain Ponade though the USGS "wate quality samples fo USA" webpage ( and the NJ 21 Wate-Resouces Data epot (Reed et al. 22). Because sampling was not necessaily done at the same time by USGS and PCER staff, all USGS/NJ DEP data used in ou analysis wee measued within a maximum of 4 weeks fom algal sampling in the same yea. 4.4 Algal sample pepaation and analysis Samples wee pepaed fo algal analysis using standad potocols (Velinsky and DeAlteis 2). Chloophyll a and ash-fee dy mass (AFDM) samples wee analyzed by the PCER Geochemisty Section using methods as descibed in Standad Methods and US EPA method 445 (APHA, AWWA AND WPCF 1992, U.S. EPA 1992). Diatoms wee pemanently mounted on micoscope slides following outine potocols (Chales et al. 22). A total of 85 slides was pepaed fo yea 1 and a total of35 slides was pepaed fo yea 2. Pe slide, 6 valves wee identified to lowest taxonomic level and counted using USGS NA WQA potocols (Chales et al. 22). Identification was done using common taxonomic efeences available at the ANSP as well as type mateial fom the ANSP Diatom Hebaium. Ove 9 digital images wee taken, ecoding nealy all identified and unidentified taxa. Taxonomic poblems wee discussed with PCER Phycology Section membes, and poblematic and unknown species wee descibed and ecoded in the ANSP Algae Image database ( Also, the active paticipation ofkainponade in the Fouth though the Eighth NAWQA Taxonomy Wokshops on Hamonization of Algal Taxonomy held at the Academy ofnatual Sciences in Octobe 2, June and Octobe 21 and May and Octobe 22 helped in solving taxonomic issues in the NJ Piedmont diatom floa. Diatoms wee counted and ecoded diectly into a database using the compute po gam Tabulato, vesion 3.7. (Cotte , Cotte 21). Count epots ae ceated fo each count, including infomation on assemblage composition, taxonomic notes, etc. The common filamentous algae wee identified and semi-quantitative estimates wee made of thei abundance using a new count method developed specifically fo this poject (Ponade and Winte 22). This semi-quantitative pocedue is designed to povide pecentage estimates of the most common The Academy of Nat ual Sciences 12 Patick Cente fo Envionmental Reseach

22 species of algae that make up the lagest popotion of the algal biomass fo each sample. The method consists of two steps. The fst step involves identifying the most common genea/species and estimating the elative pecentage of each of these in the algal assemblage. In the second step, the elative pecentage that each genus/species contibutes to the algal biovolume in the sample is estimated. Because this is a semi-quantitative method, cells ae not counted o measued, but a geneal estimate is made, which descibes the elative popotions of the common genea and species obseved in the sample though examination of seveal tansects. 4.5 Data stoage and documentation All data collected duing this poject wee popely stoed in the PCER Phycology section's database management system, the Noth Ameican Diatom Ecological Database (NADED) using Micosoft Access 2. The field sheets wee scanned and all digital images of sites and samples wee bunt on CDS. Copies ae available on equest. All image documentation and site infomation wee achived in the database. 4.6 Data analysis Wate chemisty: PCA to exploe gadients and vaiability among sites Pio to examining the elationships among algal biomass, species composition and envionmental vaiables, we pefomed a Pincipal Component Analysis (PCA) using Canoco fo Windows vesion 4.2 (te Baak and Pentice1998). The envionmental vaiables wee centeed and standadized. The aim of unning a PCA was to discove the pincipal pattens of vaiation within the envionmental vaiables measued and how they elate to sampling sites. Outlies wee defined as samples with scoes falling outside the 95% confidence limit about the sample scoe means in a PCA of the envionmental vaiables (Hall and Smol1992, Biks et al. 199b) Algal biomass Speaman's ank-ode coelation (coelations between nutients, algal biomass and algal species composition) A Speaman's ank-ode coelation was un using the pogam SPSS vesion 11. fo Windows. We chose to un this analysis because many of the algal biomass vaiables listed below ae not measued on a continuous scale and none ofthemhad nomal distibution (Dytham 1999). Included in this analysis wee the following data fo all1 6 samples collected duing both yeas: Chl a and AFDM data, nutient measuements (TP, -P, NH 3 -N, N 3 -N), pecent open canopy cove and substate type, soft algal species composition data obtained though the semiquantitative analysis fo all 16 samples, as well as diffeent measues of algal biomass. The latte wee ceated though combination of diffeent categoies, e.g., diffeent algae types and thei abundances multiplied by estimated algal thickness and length ank. In total, 11 vaiables and combinations of vaiables/categoies wee used in the analysis. Because of the size of the complete epot file (ove 1 pages) we only list hee (Appendix 3) the esults of a educed set of 67 selected vaiables, excluding the combinations (e.g., algal type multiplied with length ank The Academy of Nat ual Sciences 13 Patick Cente fo Envionmental Reseach

23 o thickness etc.). The esults of the stongest and most significant elationships ae listed in sections and Fowad stepwise egession (analysis of pincipal factos influencing algal biomass) To help detemine the pincipal factos influencing algal biomass, we examined coelations among algal biomass, nutients, geomophology and light conditions, unning a Fowad Stepwise egession with Sigma Stat 2.3. All chemical vaiables (except ph) wee loglo tansfomed. The substate categoies wee analyzed both sepaately and combined into diffeent categoies. We sepaated bigge had substate types into two categoies, one including only bedock and boulde and the othe containing cobble and gavel. We ceated two othe categoies, one including all bigge substate fom bedock to gavel and anothe combining all smalle and soft substate (sand, silt and clay) Diatom assemblages Numeical analyses wee pefomed to investigate the factos affecting diatom species composition, and to detemine whethe species composition was influenced by nutients stongly enough to justify development of infeence models. We used Canoco fo Windows vesion 4.2 (te Baak and Pentice1998) to pefom these analyses. Because thei distibutions wee skewed, we log 1 tansfomed all wate-quality vaiables included in the analysis, except ph. All diatom species identified in the counts fom all the sites sampled in 2 wee included in the odinations Detended Coespondence Analysis (DCA) to detemine pincipal pattens of vaiation in diatom species composition A detended coespondence analysis (DCA) was pefomed to detemine the gadient length as a measue of the maximum amount of vaiation in the diatom data. The gadient length was 2.6 fo the fist axis, exceeding the value of 2 standad deviation (SD) units, ecommended as the point above which unimodal techniques should be used fo futhe analysis and development of calibation sets (Jongmann et al. 1995, te Baak and Pentice 1998). In the same DCA ofthe species data, outlies wee detemined as samples with sample scoes falling outside the 95% confidence limit about the sample scoe means (Hall and Smol1992) Data sceening: envionmental vaiable with exteme influence on species composition All methods fo sceening data to emove outlies pio to developing diatom infeence models follow standad pocedues used in seveal publications (Fallu et al. 2, Hall and Smol 1992, Winte and Duthie 2). In ou study, afte outlies wee detemined in a PCA of the envionmental vaiables and/o in a DCA of the species data (see sections and ), the second step was to delete samples that had an envionmental vaiable with an exteme influence othe than eithe TP, -P, N 3 -N o NH 3 -N on the diatom species composition (Biks et al. 199b, Hall and Smol1992). In this case, samples wee deleted if thei esidual length on the envionmental vaiable axis fell outside a 95% confidence limit as detected in a CCA constained to the vaiable to be econstucted (Hall and Smol1992). The Academy of Nat ual Sciences 14 Patick Cente fo Envionmental Reseach

24 Odination analysis: CCA (influence of envionmental vaiables on diatom species composition) To identify the vaiables that explained a significant amount of vaiation in diatom species composition and that had an independent influence on diatom species distibution, we an a seies ofccas constained to one vaiable at a time. We calculated the atio of the sum of the fist constained eigenvalues (A. 1 ) to the sum of the second unconstained eigenvalues (A. 2 ). The vaiables with highest values of A 1 /A. 2 wee selected as likely to have the most influence on diatom species distibution (Winte and Duthie 2). Also, as pat of the same CCAs that wee constained to one vaiable, the statistical significance of each vaiable on the fist canonical odination axis was evaluated using Monte Calo pemutation tests (199 pemutations, p::.5) (Fallu et al. 2). Vaiables that did not explain a significant amount of vaiation in diatom composition wee excluded fom the dataset used fo development of infeence models W A-egession and calibation (development and testing of nutient infeence models) Nutient infeence models wee developed with weighted aveaging (W A) egession and calibation techniques using WACALIB vesion 3.5 (Biks 21, Line et al. 1994). Diatom species optima and toleances wee calculated fo the nutient vaiables TP, -P, NH 3 -N and N 3 -N. The models included all diatom species. Species abundance(%) was tansfomed by calculating the squae oot of each value. Species toleances wee coected by deshinking with an invese egession pocedue (te Baak and van Dam 1989). We used bootstapping (1 OOOx) (Biks et al. 199b) to estimate the oot mean squae eo of pediction (RMSEP) of each model developed. The pedictive powe of the developed models was assessed based on the (bootland the RMSEP(boot). The model with the highest pedictive powe and the lowest RMSEP is the best model calculated. To evaluate the pefomance of the TP model developed, we tested them on samples collected in 21, pefoming WA-calibation using CALIBRATE vesion.61 (Juggins and te Baak 1997, Juggins and te Baak 21). The pefomance of the model applied was assessed using statistics descibing the coelation between the obseved vesus infeed values (Biks et al. 199b) Calculation of diatom metics Divesity metics and othe simple metics Diatom divesity indices and othe simple metics wee calculated using 98 diatom samples fom both yeas, following Babou et al. (1999). We calculated the numbe of diatom taxa in the sample(# Taxa), the Shannon-Weine divesity index (S-W Index), the pecent oftotal diatom valves made up of taxa that occued in> 1% abundance (Pecent Dominants), the pecent of total diatom valves made up by the most abundant taxon (% Dominant Taxon), the atio Centales /Pennales C/P), and finally, the Siltation Index(% Siltation Index), which is the sum of the pecent abundances of all species in the genea Navicula, Nitzschia, Cylindotheca, and Suiella. These ae common genea of pedominantly motile taxa that ae able to maintain thei positions on the substate suface in depositional envionments (Bahls 1993). We evaluated the use of these The Academy of Nat ual Sciences 15 Patick Cente fo Envionmental Reseach

25 indices in conjunction with diffeent types oflanduse, unning a Speaman's ank-ode coelation using Sigma Stat Euopean diatom indices Twelve diffeent diatom indices, widely used in Euope, wee calculated fo the NJ diatom dataset. In ou study we wee specifically inteested in the esults of the Tophic Diatom Index (TDI) (Kelly and Whitton 1995, Kelly 1998), mainly eflecting nutient conditions (especially TN and TP), as well as in the Biological Diatom Index (IBD) (Pygiel and Coste 1999) and the Specific Polluosensitivity index (IPS) (Coste in Cemagef 1982), both eflecting oveall impaiment conditions. The calculations wee done by Luc Ecto (Cente de Recheche Gabiel Littmann, Luxemboug) with OMNIDIA, a pogam specifically designed fo calculations of diatom indices (Lecointe et al ). The Academy of Nat ual Sciences 16 Patick Cente fo Envionmental Reseach

26 5 Results 5.1 Envionmental data Wate chemisty, biomass concentations and summay of site chaacteistics Table 3 summaizes the nutient and biomass chaacteistics measued at all sites in both yeas. TN concentations wee calculated fo 25 samples only, due to missing TKN measues in the available USGS data. Fo infomation on the full dataset used and all vaiables measued, see Appendices la and lb. Table 3: Statistical summay of nutient and biomass concentations at all sampling sites. Data include 2 and 21 samples. TP, -P, N 3 -N, NH 3 -N, Chl a and AFDM wee measued at the PCER. TN is calculated combining PCER data (N 3 -N) and USGS data (TKN available fom 25 stations only). Vaiable Minimum Maximum n samples TP (mg/l) P (mg/l).11.4 < TN (mg/l) N 3 -N (mg/l) NH 3 -N (mg/l).5.3 < Chi a (mg/nt) AFDM (g/m 2 ) Figue 3 shows TP and Chl a concentations measued fo both sampling yeas. The sites ae odeed by inceasing TP concentations. In compaison, the sites sampled in 21 have geneally highe TP concentations than in 2, which was one of ou goals when selecting sites fo 21. Compaison oftp and Chl a values at sites that wee esampled in 21 does not show significant diffeences between both sampling yeas. Figue 3 also shows that Chl a values do not incease significantly with inceasing TP, eflecting challenges of using Chl a as an indicato of inceased nutient contents. This is discussed futhe in the statistical analysis and the discussion. In ou dataset, 46% of the samples that wee collected fom sites with concentations of.1 mg/l oftp in the wate column show Chl a concentations geate than 1 mg/m 2 The mean fo all samples collected in 21 and 22 is 19 mg/m 2 Chl a. Obsevations in the field have shown that samples with Chl a > 15 mg/m 2 wee taken fom sites with exteme algal gowth based on visual estimates. The Academy of Nat ual Sciences 17 Patick Cente fo Envionmental Reseach

27 ,... 8 ~ ~------~ 6 1:... Ol E 2 TP (mgll) Chi a median value/ lte (m 1m 2 ) ---- ChI a co ncentation of 1 mg 1m 2.8.6, C) o.4 E a Figue 3: TP and Chi a concentations measued in 2 and 21. Sites odeed by inceasing TP (black cicles). At each site thee Chl a measuements wee taken (one pe each). Geen cicles epesent median Chl a concentations and eo bas indicate maximum and minimum Chl a concentations pe site. Site numbes a and b indicate that sites wee sampled in both yeas ( a=2 and b=2 1 ). The visual estimates of algal cove along tansects (see desciption of method unde section 3.3.4) ae summaized in Figue 4. To highlight the majo tends, only samples with Chl a concentation exceeding 1 mg/m 2 ae epesented in this gaph. Sites ae odeed by inceasing Chl a content. Estimates of filamentous algal cove showed that at most sites% estimated diatom (chain-foming) cove was most impotant, followed by% Cladophoa. The thid impotant goup was % thin diatom cove, epesented by thin diatom mats that do not fom chains o filaments. Finally, % blue-geen algae was the next most abundant cove, followed by % geen algae cove. Thee was no clea coelation between pecent visual estimate of algal cove of individual algal goups and measued Chl a. Theefoe, we futhe investigated whethe the visual estimate of total biomass shows any significant elationship with measued biomass (Chl a and AFDM) using coelation analyses as descibed in section 5.2. The Academy of Nat ual Sciences 18 Patick Cente fo Envionmental Reseach

28 '- ~ 8 u " Ql... 1'1 6 E ~ Ql ~ "'E,.5. til :c 2 1 % Blue-geen % Diatoms (chain-foming) %Diatom (thin laye) % Geen (filamentous) % Chlad ophoa Chi a (m g/m) Figue 4: Main algal goups and thei contibution to pecent estimated algal cove, odeed by inceasing Chi a content measued at the site. Only samples with Chl a contents exceeding 1 mg/m 2 ae epesented. Samples collected at the same site, but in diffeent yeas ae maked on the x-axis with "a" (fo 2) and and ''b" (fo 21). The thee diffeent sections pe site ae indicated by 1, 2 and PCA: gadients and vaiability in envionmental data A PCA was un to identify pincipal pattens of vaiation among the measued envionmental vaiables. We included the maximum numbe of vaiables in the analysis, but only a limited numbe of sites contained ecods fo all vaiables. Theefoe, 16 vaiables and a total of The Academy of Nat ual Sciences 19 Patick Cente fo Envionmental Reseach

29 24 samples in 2 and 21 wee included. The PCA shows that the sites ae distibuted along thee main axes (Fig. 5). The pecentage ofvaiance explained by the fist two axes was 54%, with eigenvalues of A. 1 =.34 and A 2 =.2, espectively. Axis 1 eflected a gadient of seveal nutients (TKN, TN, -P, TP, N 3 -N) and sepaated sites with low nutient concentations fom sites with highe nutient values. The second axis is mainly influenced by a combination of ph, basin size, DO, and DOC. This axis eflects mainly ive width and elated DOC loadings, sepaating naowe ives with highe DOC loadings fom wide ives with lowe DOC concentation. The thid axis is influenced mainly by % uban, conductivity and % agicultue, showing that sites ae mainly distibuted along an uban gadient. Agicultue does not show a stong gadient, as most sites in the NJ Piedmont wee sampled in uban aeas. Geneally, this analysis shows that the sites follow a stong nutient gadient. The following samples wee detemined to be outlies: Sites AN291 and AN231 showed exteme -P, TP and N 3 -N concentations. Site ANO 118 was identified to have exteme Chl a and nutient values. en. ph BA IN SIZ~ I oforest ! 21 1 b : 3 195! 192 io! I 'Yo TKN NH3- N RB- N en I!234! DOC Figue 5: PCA including 24 sites (cicles) and 16 vaiables (aows) sampled in 2 and 21. Numbes epesent the last thee digits of the NJ site ID (see Table 1). The length of each aow expesses the "stength" of the influence of the vaiable on site distibution. Each axis is detemined by a combination of vaiables. The vaiables ae colo-coded coesponding to the axes: axis1 =blue, axis 2 =ed, axis 3 =geen. The Academy of Nat ual Sciences 2 Patick Cente fo Envionmental Reseach

30 5.2. Algal biomass The diffeent methods of assessing biomass in the field and in the laboatoy poduced a multitude of vaiables, all expessing algal biomass in a diffeent way. One ofthe main goals of this studywas to identify the stength ofnutient-biomass elationships and thei use fo development of indicatos. Theefoe, we needed to know: a) How well do the diffeent measues ofbiomass coelate? and b) How well does measued/estimated biomass eflect nutient conditions? To answe both questions a Speaman's ank-ode coelation was pefomed, as descibed below. The esults ae pesented in sections and , answeing the above two questions. Finally, we exploed how stongly othe envionmental factos influence algal biomass measues by unning a Fowad Stepwise egession Speaman's ank-ode coelation Relationships among all nutient vaiables and biomass data fo the full data set fom both yeas' (n=16) data wee exploed using a Speaman's ank-ode coelation matix. To fmd out what type of coelation was appopiate to un, we needed to detemine if vaiables in the dataset wee nomally distibuted. We tested each vaiable using Kolmogoov-Sminov (K-S) tests (Dytham 1999) using the pocedue in Sigma-Stat 2.3. Nomality tests failed fo all vaiables when tested on untansfomed data, showing that all data wee skewed. Afte log tansfomation, anothe K-S nomality test was un. The esults showed that only Chl a (log) passed the test, and that the data wee still skewed fo most of the vaiables. Scatteplots using log tansfomed nutient data (Fig. 6) show no significant tend in coelations ofo-p o TP with Chl a concentations. Theefoe we decided to un a Speaman's ank-ode coelation, to investigate if nutients showed a significant influence on biomass concentations =.93 N 8..._ E Ul 6 E ltl 4 J: 2, :..._ Ul 6 E - ltl 4 J: 2 ' =.87 I.; TP (IJg/1) log P 4 (IJg/1) log1 o Figue 6: Coelations of P 4 and TP with 3 Chi a concentations. All samples fom 2 and 21 ae included. P 4 and TP values ae log tansfomed. The vaiables in the Speaman's ank-ode coelation included all measues of algal biomass (Chl a and AFDM data, RBA visual estimate and semi-quantitative count pocedue) fo all16 samples collected duing both yeas, and all nutient measuements (TP, -P, NH 3 -N, The Academy of Nat ual Sciences 21 Patick Cente fo Envionmental Reseach

31 N 3 -N). Fo explanation of the diffeent vaiables included in the coelation, and esults of the coelation matix, see Appendix 3. We used the following abbeviations to identify the method o analysis fom which the data wee deived: Rapid bioassessment (RBA) and semi-quantitative count method (SQCM) Compaison between esults of diffeent biomass measues/estimates (Chl a, AFDM, visual estimate (RBA) and % biomass estimate (semiquantitative count method) The following coelations ae significant at the.1level using Speaman's ank-ode coelation, two-tailed test. Chl a is significantly coelated with% visually estimated Cladophoa sp. cove (RBA) (=.4), with visually estimated % Cladophoa sp. cove multiplied by its length ank (RBA) =.41), and with visually estimated% blue-geen cove multiplied by its length ank (RBA) =.26). In contast, AFDM is not significantly coelated at the.1level (two-tailed) with any% biomass estimate. Coelations at the.5 level ae moe fequent but less stong showing the following esults: Chl a coelates with estimated % Cladophoa sp. biomass (SQCM) =.24), with % estimate blue-geen algae cove (RBA) (=.25) and with estimated % cove of geen algae (RBA) =.21). AFDM is coelated (at the. 5 level, twotailed) with estimated % Oegodonium sp. biomass (SQCM) (=.22), estimated % biomass geen filamentous algae (RBA) ( =.19), and estimated % biomass geen filamentous algae multiplied by its maximum length ank (RBA) =.19). AFDM is negatively coelated with diatom estimated biomass (SQCM) = -.2), estimate of% thin laye of diatoms (RBA) (= -.19) and estimate of %thin laye of diatoms multiplied by thei thickness ank (RBA) (= -.23). In summay, the esults of the Speaman's ank-ode coelation show that both,% estimate of Cladophoa sp. biomass (RBA) and % estimate of Cladophoa sp. biomass multiplied by its length ank (RBA), and visually estimated % blue-geen cove multiplied by its length ank (RBA) ae the two goups that ae coelated stongest and most significantly (at the.1 level) with Chl a. AFDM coelates with mainly Oegodonium sp. biomass (RBA) and cell counts (SQCM), and geen filamentous algae thickness and maximum length (RBA), but the coelations ae weake and less significant. In geneal, biomass measues (Chl a and AFDM) show stonge coelations with the esults of the RBA than with the semi-quantitative count method. This study shows that the Rapid Bioassessment method is a good tool to estimate biomass impaiment in ives ofnj, and especially seems to eflect well exteme gowths of Cladophoa sp. Nevetheless, besides the coelation with Cladophoa sp., none ofthe coelations is vey stong and intepetations should be made with caution Relationships between algal biomass measues and nutient conditions We exploed the elationships between algal biomass measues and nutient conditions using Speaman's ank-ode coelation, two-tailed test (Appendix 3). The only coelation that was significant at the.1level was a positive elationship between AFDM and nitate (N 3 -N) =.26), and a negative elationship between estimated% blue-geen cove (RBA) =-.31) and estimated% blue-geen cove multiplied by its thickness ank (RBA) =-.29) and NH 4 -N. In summay, except fo AFDM and N 3 -N, we did not find significant tends o stong positive elationships between amount ofchl a, AFDM, visual biomass estimate and nutient The Academy of Nat ual Sciences 22 Patick Cente fo Envionmental Reseach

32 measuements. The esults of the data analysis pefomed duing the fst two yeas of ou study eveal that nutient concentations measued in NJ Piedmont ives do not show stong and significant coelations with any of the diffeent biomass measues. Howeve, the esults of fowad stepwise egession (section ) suggest that if the influence of ive width (light conditions) and substate ae accounted fo, nutient concentations will have a stonge elationship with algal biomass. We will pefom detailed analysis of a bigge dataset (including yea 3 data fom this study) to investigate this elationship futhe Analysis of pincipal factos influencing algal biomass (fowad stepwise egession) We analyzed algal biomass (AFDM an Chl a) and its elationship with nutients (TP, -P, NH 3 -N, N 3 -N), othe chemical vaiables (dissolved oxygen, ph, conductivity), geomophic vaiables (ive basin size, ive width, section length, pecent type of substate) and light conditions (pecent open canopy cove) with Fowad Stepwise egession using Sigma Stat vesion 2.3. Table 4 summaizes the esults of the egession. The full esults of the egession ae attached in Appendix 4. The analysis was un twice, once each with eithe Chl a o AFDM as dependent vaiables. The esults show that the dependent vaiables Chl a and AFDM can both be pedicted fom a linea combination of the independent vaiables N 3 -N and ive basin size. In the case of Chl a only, size of substate (sum of pecent bedock, boulde, cobble and gavel) had a significant influence on algal biomass. The coelations ae significant at the.1level fo N 3 -N in both egessions, indicating that this vaiable shows the stongest influence. In the egession with Chl a as the dependent vaiable, N 3 -N is stongly coelated with TP and -P, wheeas in the second egession with AFDM as dependent vaiable, N 3 -N is independently having the stongest influence (stongest F-value of 18.62) in the dataset. In both egessions, basin size is stongly coelated with pecent open canopy cove and aveage ive width and section length (see esults in Appendix 4). Basin size is coelated with light, ive with, and section length and is theefoe an indiect vaiable expessing light conditions. This shows that in ou analysis, a bigge ive basin eflects a wide ive, with moe light eaching the ive bottom and theefoe causing highe algal biomass. 5.3 Algal floa- species composition Composition of soft-algae floa in biomass samples (soft-algae floa) The soft algal floa is composed mainly of Cladophoa sp. and Audouinella sp. Othe algal goups like Oscillatoia sp., Oegodonium sp., Rhizoclonium, Spiogya sp. and Meismopedia sp. ae epesented in much lowe abundances and lowe numbe of occuences (see Table 5). The pecentage estimates (o popotions) ofthe most common species of algae, identified though the semi-quantitative analysis (see section 4.4), showed the following composition (Table 5). The assemblages wee stongly dominated by diatoms thoughout the whole dataset. The second most impotant goups wee Cladophoa sp. and Audouinella sp. with n of 11 and 12 and median pecentages of estimated biomass of 18 and 2 espectively. Finally Oscillatoia sp., Oegodonium sp., and Rhizoclonium sp. occued less often ( n = 2 to 4) but with elatively high medians. The least common goups, Spiogya sp. and Meismopedia sp., wee The Academy of Nat ual Sciences 23 Patick Cente fo Envionmental Reseach

33 Table 4: Vaiables significantly influencing algal biomass, as detemined by Fowad Stepwise egession. Dependent Step Vaiables F- to ente p Vaiable Enteed I Chla 1 I Basin size < I I 2 I N3-N 9.14 < I bigge substate I AFDM 1 I N3-N < I 2 I Basin size Table 5: Pecentage estimates of the most common species of algae that make up the lagest popotion of algal cells and algal biomass. I Median Diatoms (% # cells) 85.!Diatoms (%biomass) !Cladophoa sp.(% # cells) !Cladophoa sp.(%biomass) ;4udouinella sp.(% # cells) ;4udouinella sp.(%biomass) loscillatoia sp.(% # cells) loscillatoia sp.(%biomass) loedogonium sp.(% # cells) loedogonium sp.(%biomass) IRhizoclonium sp.(% # cells) IRhizoclonium sp.(%biomass) lscenedesmus sp.(% # cells) lscenedesmus sp.(%biomass) ISpiogya sp.(% # cells) ISpiogya sp.(%biomass) IMeismopedia sp.(% #cells) IMeismo[!_edia SQ.(%biomass} The Academy of Nat ual Sciences 24 Patick Cente fo Envionmental Reseach

34 obseved in samples fom one site each. Despite its low occuence, Spiogya sp. was estimated to contibute up to 18% ofthe estimate ofbiomass, in contast to Meismopedia sp., with.5% estimated biomass Pincipal pattens in the vaiation of diatom assemblage composition (DCA) The diatom floa is composed of 36 taxa (Appendix 2) dominated by pollution-toleant species. The 1 most abundant species, detemined by high abundances and high numbes of occuences (see Appendix 2), ae Navicula minima Gun., Rhoicosphenia cuvata, (Kiitz.) Gun. ex Rabh, Nitzschia inconspicua Gun., Planothidiumfequentissimum (L-B) Round & Bukht., Nitzschia amphibia Gun., Sellaphoa seminulum (Gun.) Mann, Melosia vaians Ag., Cocconeis placentula va. lineata (Eh.) V. H., Navicula lanceolata (Ag.) Eh. and Navicula gegaia Donk. The DCA analysis of species seved to measue the maximum amount of vaiation in the diatom data, and also to help identify outlies (see section ). Figue 7 shows samples with sample scoes falling outside the 95% confidence limit about the sample scoe means on axis 1 and 2 (Hall and Smol1992): site AN115 section 1, 2 and 3, site AN439 section 1, site AN227 section 1, 2 and 3 and site AN318 section 1, 2 and Relationship between species composition and envionmental vaiables, especially nutients Soft algae: Speaman's ank-ode coelation Relationships among the semi-quantitative algal counts and nutients and othe envionmental vaiables wee examined by unning a second Speaman's ank-ode coelation (see section ). Detailed esults ae given in Appendix 3. The following coelations wee significant: the estimated numbe of Cladophoa sp. cells coelate at the.5 level with Chl a =.25), aveage width of the ive =22) and sampling section length =.23). Futhemoe, the estimated numbe of Cladophoa sp. cells coelated significantly (at the. 1level) with dissolved oxygen =.25), ph =.33) and% open canopy (=light) =.29). Fo diatom cells, estimated numbes coelate significantly (at the.1 level) with amount ofchl a =.22), the aveage width of the ive =27) and section length =.27), and at the (.5 level) with% open canopy (=light) =.21). Futhemoe, the estimated numbe of cells of Oegodonium sp. (=.22) is coelated significantly with AFDM (at the.5 level). Estimated numbe of cells of Audouinella sp. =.22) is coelated at the.5 level with NH 3 -N. In summay, the stongest and most significant coelations between soft algal species composition and envionmental vaiables wee found between abundance of Cladophoa sp. cells and ph and% open canopy, and also between abundance of diatom cells and aveage width of the ive and section length. Coelation between abundance of Cladophoa sp. and ph might expess high ates of photosynthesis, which influence the ph conditions in the wate column, but could also be elated to a pefeence by Cladophoa sp fo ph-neutal wates. Theefoe, oveall light conditions seem to have stongest influence on abundance of diatoms and Cladophoa sp. The Academy of Nat ual Sciences 25 Patick Cente fo Envionmental Reseach

35 . NJ NJ_318_1 - - NJ_318_2 NJ NJ_215_2 - NJ_215_3 NJ enj_115_1 enj_115_2 NJ_439_3 NJ_396_3 ~J NJ_439_2 NJ NJ LO NJ_227_1 I ~----~----~ ~------~----~----~ Figue 7: DCA showing site scoes. Samples indicated with filled cicles wee identified as outlies. Nevetheless, all coelations found ae athe weak. Finally, except fo Audouinella sp., which is coelated at the.5 level with NH 3 -N, no significant coelations wee found between soft algal species composition and nutients Diatoms: odination analysis; influence of envionmental vaiables on diatom species composition Development of nutient infeence models equies a stong statistical elationship between diatom species composition and the vaiable to be modeled (Winte and Duthie 2, Biks et al. 199a). Theefoe, we identified the vaiables that explained a significant amount of vaiation in diatom species composition, unning CCAs constained to each vaiable sepaately (see section ). The 'A/'A 2 atio was high fo TP (.467) and -P (.474). These vaiables wee theefoe detemined to have stong influence on diatom species distibution (Winte and Duthie 2). The 'A/'A 2 atios fo conductivity (.331 ), N 3 -N (.298), NH 3 -N (.264) and ph (.263) showed some influence, but wee weake. Monte Calo Pemutation tests (199 pemutations) The Academy of Nat ual Sciences 26 Patick Cente fo Envionmental Reseach

36 evealed that significant (p<.5) amounts of the vaiability in diatom assemblage composition ae explained by all measued inoganic nutients (TP, -P and N 3 -N, NH 3 -N). A fmal CCA was poduced to show the stength ofthe influence of each vaiable mentioned above on diatom species composition (Fig. 8) ~96 A 66 b. NH3-N TP O-P tlj co I -.4 ' 6 i~f H [fjy ' I Conductivity 1. Figue 8: CCA of diatom assemblages, including 85 samples (outlies included) and 6 envionmental vaiables having stong influence on the 36 the species included. Tiangles epesent samples and numbes epesent species names as listed in Appendix2. The Academy of Nat ual Sciences 27 Patick Cente fo Envionmental Reseach

37 5.4 Development of nutient infeence models based on diatom species composition Data sceening In ode to select the vaiables that have independent and significant influence on species composition, we an a seies of specialized analyses. The pupose of these analyses was to sceen the data fo unusual samples, and to emove those fom the dataset to be used fo development of models. Unusual samples ("ogues" o "outlies") wee defined as samples that have eithe unusual diatom assemblages that ae weakly elated to the vaiable to be econstucted, that have an unusual combination of envionmental vaiables, o that have envionmental vaiables that have a stonge influence than the vaiable to be econstucted (Biks et al. 199b, Hall and Smol 1992). Because they wee taken fom sandy substate, the following samples wee deleted fom the dataset used fo diatom infeence models: AN194, AN227, AN238, AN382 and AN414. Futhemoe, all samples fom the five sites that wee not located in the Piedmont wee excluded fom the dataset (AN215, AN318 and AN321, N382, AN439). Due to exteme envionmental vaiables and species scoes, as peviously descibed, the samples coming fom site AN291 sections 1, 2 and 3, fom site AN118 sections!, 2 and 3 and fom site AN115 section 1, 2 and 3 wee deleted fom the dataset used fo infeence models (see sections and 5.3.2). Based on the above data sceening pocess, 3 7 diatom samples wee deleted fom the oiginal dataset. The fmal taining set to be used fo development of infeence models contained 54 out of the 85 diatom samples, all collected in 2. Nevetheless, as the sceened dataset was educed by nealy 5%, we decided to use both datasets, the full dataset (n= 85) and the educed dataset (n= 54), as taining sets fo compaison of development of infeence models Weighted aveaging- nutient infeence models In ode to develop nutient infeence models, a stong statistical elationship between diatom species composition and the vaiable to be modeled is equied (Winte and Duthie 2, Biks et al. 199a). As identified though CCAs constained to each vaiable sepaately, we detemined that -P and TP have stong influence and that N 3 -N and NH 3 -N have modeately stong influence on diatom species distibution. Based on the esults of the Monte Calo pemutation tests, development of nutient infeence models was possible fo all fou vaiables (see section ). We developed infeence models fo the nutient vaiables -P, TP, NH 3 -N and N 3 -N using weighted aveaging egession and calibation on 2 diffeent datasets: the fist set included all85 samples, and all species; the second set included only 54 samples (see section 4.5.2). The esults indicate that all models have elatively high pedictive powe, and that the oot mean squae eos of pediction ae elatively low (see Table 6). The two best models developed using the full dataset (n=84) ae: the TP infeence model (n=84), with an appaent 2 of.72 and a RMSEP (boot) (log) of.33 ).lg/l and the N 3 -N infeence model (n=84) with an appaent 2 of.68 and an RMSEP (boot) (log) of.26 ).lg/l. The two best models developed using the educed dataset (n=54) ae: the TP infeence model (n=54), with an appaent 2 of.69 and a RMSEP (boot) (log) of.22 ).lg/l and the N 3 -N infeence model (n=54) with an appaent 2 of.64 and an RMSEP (boot) (log) of.21 ).lg/l. The Academy of Nat ual Sciences 28 Patick Cente fo Envionmental Reseach

38 Table 6: Pedictive powe of diatom infeence models fo TP, -P NH 3 -N and N 3 -N, as detemined using W A-egession and calibation. n=85 n=54 Paamete 2 RMSEp(boot) (log) 2 RMSEp(boot) (log) (appaent) ~-tg/l (appaent) ~-tg/l TP P Evaluation of the pefomance of the TP model The TP model (n=85) has elatively high pedictive powe 2 (boot)=.55) (Fig. 9). 3.5 ::::::- 2: ) 2 (boot)=.55 RMSEp =.325 n n = 85 ~ I ) 2. "'... ~ 1.5 u "' ~ I ~ 1. I n Obseved log 1 TP (JLQ/1) Figue 9: Obseved vesus pedicted TP fo the W A infeence model developed based on 85 diatom samples collected in 2. Tbe Academy of Nat ual Sciences 29 Patick Cente fo EnvionmentalReseacb

39 5.5 Evaluation of diatom metics, indices and infeence models Seveal diffeent diatom indices and infeence models wee applied to the NJ Piedmont dataset to assess weathe any of the existing indices could poduce eliable esults when applied to NJ ive diatoms. The diffeent indices and the esults obtained ae descibed below Test of the NJ Piedmont nutient infeence model on the yea 2 samples To evaluate the pefomance of the TP model developed, it was tested on the full yea 2 dataset (12 sites) including the 5 duplicate sites AN374, AN274, AN115, AN211 and AN45. To un the test, we pefomed WA-calibations using CALIBRATE vesion.61 (Juggins and te Baak 1997, 21) and applied the model developed using sites sampled in 2 to the samples collected in 21. The pefomance of the TP model was assessed by evaluating the distibution of the obseved vesus infeed values (Biks et al. 199b). With a coelation coefficient of.78 ( =.61) ou test showed good esults (Fig. 1). This analysis demonstates that the developed TP model could be applied successfully to othe diatom samples collected in the ives of the NJ Piedmont to eliably pedict TP concentations. 35 "'C C1) =.78 C1) 25 "t- : a.. 5 t- C) ::l 1 ' TP (JLQ/1 ) measued Figue 1: Test oftp infeence model: plot of measued (samples taken in 21) vesus diatom- infeed TP (TP model based on samples taken in 2). The Academy of Nat ual Sciences 3 Patick Cente fo Envionmental Reseach

40 5.5.2 Divesity metics and othe simple metics Six diffeent diatom divesity indices and othe simple metics wee calculated based on 98 diatom samples collected in 2 and 21. A Speaman's ank-ode coelation was un to evaluate how stongly these indices wee coelated with diffeent envionmental vaiables expessing ive impaiment, e.g. types oflanduse, nutient and biomass concentations. The main goal of this analysis was to identify metics that can be used to assess nutient impaiment in NJ Piedmont ives. The main esults ae shown in Table 7; the diffeent types ofmetics ae explained in section Consideing the indiect elationship between the metics and the vaiables they wee coelated with, we conside that any coelations with an geate than.4 ae elatively stong, that coelations between =.2 and.4 ae modeate and that any coelations below an of.2 ae weak. The following indices showed significant (at.1 level) and stong coelations. Numbe of taxa was stongly coelated with N 3 -N and TP, and modeately coelated with basin size and NH 3 -N and -P. S-W divesity was modeately coelated with basin size, -P and TP. Centics/Pennates is stongly coelated with -P and T -P and modeately coelated with basin size, N 3 -N and NH 3 -N and% uban landuse. The Siltation Index is stongly coelated with basin size, -P and T-P and modeately coelated with Chl a. In summay, the Siltation Index, the Centics/Pennates and numbe of taxa, showed the stongest coelations with basin size, N 3 -N, -P and TP (p <.1). Theefoe, these diatom indicatos could be used to monito ive impaiment, especially of the nutients N 3 -N, -P and TP Euopean indices (TDI, IBD and IPS) The esults of the Tophic Diatom Index (TDI), the Biological Diatom Index (IBD) and the Specific Polluosensitivity index (IPS) wee calculated fo samples taken in 2 and 21 and the esults wee tested fo coelation with nutient measuements. The Euopean diatom floa used fo the development of the indices diffes fom the NJ floa in species composition, hence we could only include 8% of the diatom species contained in ou counts in the calculation of the Euopean diatom indices. In paticula, thee Noth Ameican species, Gomphonema kobayassii, Gomphonema patickii and Achnanthes sp.1 wee abundant and eached high numbes of occuences in ou dataset, but ae not included in the Euopean index. We used a Peason's poduct-moment coelation matix to assess how well the diffeent indices eflect nutient impaiment (-P, TP, Chl a, AFDM,% Uban,% Agicultue) in NJ Piedmont ives (Table 8). The stongest coelation =-.65) was obtained fo the IPS vesus measued -P, also pesented in a scatteplot (Fig. 11 ). Because the TDI was developed mainly to eflect tophic conditions, it shows stong coelation with -P =.64) and TP =.54), but a athe weak coelation with N 3 -N =.27) and NH 3 -N =.8). The IPS and the IBD wee both developed to eflect oveall impaiment conditions, using the same appoach. The diffeence between the two indices is that the IPS is based on a bigge dataset of diatom species (Pygiel and Coste 1999). When compaing the esults of both indices, we found that the IPS shows stonge coelation with -P and TP and NH 3 -N but the IBD showed slightly stonge coelation with N 3 -N. Figue 12 shows that, in geneal, the IBD gives highe atings fo NJ ive quality than the IPS. The Academy of Nat ual Sciences 31 Patick Cente fo Envionmental Reseach

41 Table 7: Speaman's ank-ode coelation between diatom metics and diffeent vaiables expessing nutient impaiment. Fo explanation ofmetics see section :** significant at.1 level and *significant at.5 level. Diatom #Taxa S-W /o /o C/P Siltation Metic/ Index Dominants Dominant Index Envionmen- Taxon tal Vaiable %Uban ** % Agicultue O.ol %Foest Basin size.324**.36** -.259** -.24*.344**.413** N 3 -N.423**.319** -.25* * NH 3 -N.28** ** P.366**.333** -.244* -.34 **.431 **.445** TP.43**.326** -.235* -.326**.482**.449** Chla ** AFDM Table 8: Peason's poduct-moment coelation matix compaing Euopean diatom indices with diffeent measues of nutient impaiment. I I NO,-N I NH,-N I -P I TP I Chi a IAFDM I %URB I %AGR I TDI I IPS I IBD The Academy of Nat ual Sciences 32 Patick Cente fo Envionmental Reseach

42 Othophoshate vesus IPS 22 en a = -.65 I = I 16 I 12 I log -P {micog/l) Figue 11: Scatteplot of measued -P vesus the indices calculated by Specific Polluosensitivity index (IPS) fo all 2 and 21 samples. In summay, the thee Euopean diatom indices wee good pedictos of othophosphate and total phosphous. Nevetheless, these esults should be intepeted with caution due to diffeences between the Euopean diatom floa used fo the development of the indices and the diatom floa in NJ. Oveall the esults show that thee is potential fo expanding the existing Euopean diatom models by including data fo Noth Ameican species. The Academy of Nat ual Sciences 33 Patick Cente fo Envionmental Reseach

43 LEGEND WATER QUALITY IBD VERY GOOD.6. GOOD.6. FAIR 6 POOR Figue 12: Map showing the diffeence in the atings of ive quality as calculated by two Euopean diatom indices, the Specific Polluosensitivity index (IPS) and the Biological Diatom Index (ffid). The numbes coespond to NJ site ID's (see Tables 1 and 2). The Academy of Nat ual Sciences 34 Patick Cente fo Envionmental Reseach

44 6 Discussion A main goal of this study was to exploe the elationships among algal biomass, algal species composition and nutients. A futhe goal was to identify the most pomising indicatos fo assessing excess nutients in NJ ives and steams using biomass and algal species composition (soft algae and diatoms). In the following paagaphs we summaize nutient-algal elationships identified fom this study and discuss the outcome of all diffeent methods used. Finally, we discuss applicability of the indicatos developed and povide ecommendations towads thei use and futhe development. 6.1 Pincipal factos influencing algal biomass Pincipal vaiables influencing algal biomass A multitude of ecent studies have been conducted to undestand which combination of factos detemines algal biomass. A lage amount of liteatue is available on this subject and a compehensive eview is published in a epot pesented by the New England Intestate Wate Pollution Contol Commission (ENSR 21). The main factos influencing biomass accual ae nutients, light, tempeatue, substate availability and steam velocity (Biggs 1996). To detemine the pincipal vaiables influencing algal biomass in ou study, we analyzed all vaiables measued in the field and in the lab using fowad stepwise egession. All factos mentioned above wee included in this analysis, except fo tempeatue measuements. To include tempeatue measuements we would need a long-temecod of aveage daily tempeatues fo weeks befoe each sampling date. No such detailed ecod was available fo most sites sampled. The esults of a stepwise egession showed that the dependent vaiables Chl a and AFDM can both be pedicted fom a linea combination of the independent vaiables N 3 - N and ive basin size. In the case of Chl a only, bigge substate size (sum of pecent bedock, boulde, cobble and gavel) also has a significant influence on algal biomass. These esults show that algal biomass in the NJ dataset is influenced by a combination of light conditions (eflected though basin size) nitogen (N 3 -N) and factos closely associated with these. In ou dataset TP and -P ae stongly coelated with N 3 -N, theefoe coelation ofchl a with N 3 -N also eflects coelation with phosphous. Also, in the case of Chl a, the size of the type of substate, and the availability of algae to attach is an additional impotant facto. In summay, we can deduce fom this analysis that in the NJ Piedmont ives a combination of thee factos togethe- high light levels, high nutient concentation, and high popotion oflage-sized substate - lead to the geatest quantities of algal biomass in NJ Piedmont ives. These esults suggest that thee is potential fo development of a metic fo biomass combining all of these factos. We will exploe the possibility of developing such a metic futhe, especially in combination with the thid yea data of this study Nutient-biomass elationships as assessed by coelations Afte detemining the main factos influencing algal biomass, we investigated the stength ofthe elationship of individual nutients on diffeent measues ofbiomass. Speaman's coelation analyses showed that thee is no significant and stong elationship between measued biomass concentations ofchl a, AFDM o estimate ofbiomass as assessed though the RBA with the nutients TP, -P, N 3 -N and NH 3 -N. Only the coelation betweenafdm and nitate The Academy of Nat ual Sciences 35 Patick Cente fo Envionmental Reseach

45 (N 3 -N) shows a significant tend, but the coelation is weak =.26). As shown in section 6.1.1, biomass can only be explained though a combination of factos including nutients. Thee is need fo moe detailed analysis of this dataset including the lage dataset with yea 3 samples to exploe the stength of the elationship between biomass and nutients. A ecent study on lage datasets (national and intenational) on tempeate steams evealed that a significant potion of vaiance in annual mean and maximum biomass can be explained by total nitogen and total phosphous concentations (Dodds et al. 22). The same study also shows that such elationships ae vey weak at the egional scale. Ou study is consistent with this obsevation, and demonstates the challenges offmding clea elationships at smalle (egional) scales, such as the NJ Piedmont. It demonstates that a stong coelation between nutient and biomass is at best difficult to establish, and that othe factos such as light (as a function of ive basin size) and substate must be taken into account when estimating nutient-biomass elationships (see section6.1.1). Theefoe, commonly used biomass measues (Chl a, AFDM) must be intepeted with caution, and infeences of nutient levels in ives based on these measues should be made only in conjunction with analyzing othe vaiables. 6.2 Compaison and evaluation of methods fo estimating algal biomass Algal biomass was measued in thee diffeent ways: a) we measued the contents of Chl a and AFDM contained in the composite biomass samples collected in the field; b) we estimated the popotion of cells making up most of the biomass in the composite biomass samples, using a specially designed semi-quantitative analysis and fmally c) we visually estimated popotions of abundance and thickness of algal cove in the ives as assessed though the Rapid Bioassessment (RBA). Speaman's ank-ode coelation between the diffeent measues of biomass shows significant coelations between Chl a and with RBA estimates of biomass, with the stongest coelation between Chl a and Cladophoa sp.( = 4). In contast, both the measues of AFDM and the estimates ofbiomass though the semi-quantitative analysis do not show significant and stong coelations with any othe measues ofbiomass. Theefoe, we do not ecommend the use of the semi-quantitative analysis method fo estimating biomass. Also, when given the choice between measuing eithe Chl a o AFDM as a vaiable to be used fo biomass-algal goup elationships, Chl a should be given pioity. Ou study shows that a combination of measuing Chl a fom composite diatom samples and using the RBA method seems to assess the amount of algal biomass best. When using those two appoaches in combination, a good assessment of the biomass impaiment in ives of the NJ Piedmont can be achieved. Cladophoa sp. is, based on ou esults, the species that coelates most closely with Chl a and is theefoe the algal goup that needs to be monitoed most. The assessment though the RBA in combination with measuing Chl a fom composite biomass samples povides a good tool fo monitoing gowth of Cladophoa sp. Nevetheless, none of the coelations found between the diffeent measues of biomass is vey stong and theefoe a combination of diffeent methods should be used to assess biomass. The Academy of Nat ual Sciences 36 Patick Cente fo Envionmental Reseach

46 6.3 Compaison and evaluation of diatom metics and models In the following sections we compae the esults ofthe diatommetics and models with the objective of detemining the best method fo estimating phosphous concentations and oveall wate quality in NJ Piedmont ives. The elative advantages and disadvantages of each method ae discussed. Pefomance of all ae potentially limited by how well the envionmental measuements, especially nutient concentations, epesent the vaiability of conditions to which the algae ae exposed. It would be useful fo evaluating metic effectiveness if the vaiability of these conditions could be quantified Nutient-infeence models The diatom species composition found in the NJ Piedmont dataset was stongly influenced by the measued nutient vaiables (-P, TP, N 3 -N and NH4-N). Theefoe, development of W A - infeence models fo nutients was possible. We developed 4 diffeent nutient infeence models based on the full (n=85) and a educed dataset (n= 54). All models have elatively high pedictive powe. The best models developed ae the TP and the N 3 -N infeence models fo the full (n=85) and a educed dataset (n= 54). Fo both vaiables, the model developed with the full dataset (n=85) has a highe, but the model based on the educed dataset (n= 54) has a lowe RMSEP (boot)' espectively. This means that the eos obtained fo the values infeed using the TP and N 3 -N models developed fo the full dataset will be highe than those based on the educed dataset. Nevetheless, when we tested obseved vesus pedicted TP fo the full dataset infeence model (n=85), we found that the model has elatively high pedictive powe 2 (boot) =.55. Also, testing of the same model on the yea 2 samples poduced eliable esults ( 2 =. 61). In the futue, diffeent techniques will be applied to impove the model to incease its pedictive powe. Also, we plan on including samples taken duing the second (21) and the thid yea (22) of this poject to incease the pedictive powe of these two WA-infeence models fo N 3 -N and TP. In summay, in contast to soft algal species composition, we found good coelation between diatom assemblage composition and nutients. The WA nutient-infeence models developed showed eliable esults when tested, and we intend to impove them futhe. The diatom infeence models seem to be bette indicatos fo nutients and ive eutophication than biomass. In geneal, species composition based indicatos coelate bette with nutient concentations, because the ecological infomation fom diatoms is not as vaiable as biomass (e. g., Chl a) concentations ove time. The application of diatom infeence models to N J Piedmont ives and steams is highly ecommended as a tool fo monitoing eutophication. Nutient infeence models ae elatively easy to apply as a egula monitoing tool. Nevetheless, thei use equies appopiate softwae and expetise Simple metics The usefulness of the of the six divesity and simple metics was evaluated by compaing thei coelations with nutient impaiment measues. Siltation Index, the Centics/Pennates and numbe of taxa index, showed modeate, but significant coelations with N 3 -N, -P and TP. Theefoe, it is possible to use these diatom indicatos to monito ive impaiment, especially of The Academy of Nat ual Sciences 37 Patick Cente fo Envionmental Reseach

47 the nutients N 3 -N, -P and TP. The fomulas fo the indices ae simple and calculation is easy. They could be included in the list ofmetics in the EDAS database and analysis system used by the NJ DEP. Nevetheless the coelations obtained between the indices and the nutient vaiables ae not vey stong and the significance of the esults is questionable. We conside the esults obtained though the nutient infeence models by fa moe eliable and ecommend using simple metics only as complementay method Euopean indices The thee Euopean diatom indices (TDI, IBD, IPS) showed good esults and elatively stong coelation with othophosphate and total phosphous in the NJ Piedmont dataset. It is inteesting to note that the stength of the coelation of the Nothen Piedmont Diatom TP index and the Bitish Tophic Diatom Index with Othophosphate is simila =.66 and =.64 espectively). Nevetheless, we do not ecommend using the Euopean indices solely, because of impotant diffeences between the Euopean diatom floa used fo the development of the indices and the diatom floa in the NJ Piedmont. 6.4 Compaison of diatom infeed TP and impaiment classifications based on macoinvetebate metics (AMNET) We compaed TP calculated using the diatom TP diatom infeence model (n=85) to macoinvetebate impaiment atings based on the 1998/99 assessment. The esults (Fig. 13) show that the diatom infeed TP values do not coespond stongly to the macoinvetebate impaiment goups of "non-impaied," "modeately impaied" and " seveely impaied." No significant sepaation is found between atings, as all goups' loth and 9th pecentiles ovelap to a high degee with the adjacent categoy. The"modeately impaied" categoy in paticula includes a lage numbe of sites that ae indicated by the diatoms to have a wide ange of TP values. Nevetheless, the sites ated "non-impaied" and "seveely impaied" do show a tend ofhaving lowe and highe diatom infeed TP, espectively. Moe detailed analysis compaing diatom infeed nutient concentations with macoinvetebate metics that best eflect nutient (e.g., % EPT etc.) will be pefomed in collaboation with the NJ Integated Assessment (Howitz and Flindes 23) including Yea 3 data of this study. 6.5 Evaluation of the EPA pecentile method fo detemining efeence conditions We applied the poposed U.S. EPA pecentile method (U.S. EPA 2b) to the NJ Nothen Piedmont dataset to calculate efeence conditions. In ou study, the 25th pecentile was calculated using all nutient data fom all eaches (Appendix 1 b). We compaed ou value to those fo the aggegate of all Level III Subecoegions ofnutient Ecoegion IX, and to the Nothen Piedmont subecoegion (64) only, as given in the Ambient Wate Quality Citeia Recommendations (U.S. EPA 2b). The ange oftp efeence conditions given fo all subecoegions is J..Lg/1; fo the Nothen Piedmont subecoegion it is 4 ).lg/l. We calculated a efeence condition of 51 ).lg/l fo the NJ Nothen Piedmont, which is only 1 ).lg/l geate than the one poposed in the EPA document. The ange of EPA total nitogen efeence conditions is.7-1. mg/l; it is 1.3 fo the Nothen Piedmont. Ou dataset shows a The Academy of Nat ual Sciences 38 Patick Cente fo Envionmental Reseach

48 C> C> N 35 -~ 3 C') ::::&. 25 -Q '" G> 15 t::.! 1 c: E 5 t;s - c _l_ AMNET atings n- lmpaied odent ly imp "e d Seveely impaied Figue 13: Box-plots compaing diatom infeed TP to AMNET macoinvetebate impaiment atings. Uppe limit of eo bas indicate the 1Oth and the 9th pecentile. Filled cicles indicate outlies. 25th pecentile of total nitogen of 1.28 mg/l, which is elatively nea EPA's value fo the Nothen Piedmont. Also, the peiphyton chloophyll a measued in ou dataset shows a 25th pecentile of 48.7 mg/m 2 which substantially exceeds the ange given by EPA of mg/m 2 and the value fo the Nothen Piedmont of2.35. This compaison shows that, using the pecentile method, thee is easonable good ageement between TP and TN efeence values deived fom data in the EPA study and this study, but that thee is a substantial diffeence fo Chl a values. The Academy of Nat ual Sciences 39 Patick Cente fo Envionmental Reseach

49 7 Conclusion: Recommendation fo use of the ideal algal indicato monitoing pogam fo the NJ Piedmont Based on ou study, we ecommend the use of a combination of algal indicatos and metics fo monitoing nutients and biomass. Fo monitoing biomass, we ecommend using the EPA Rapid bioassessment Potocol in combination with measuing chloophyll a. Ou esults show that chloophyll a coelates especially well with Cladophoa sp. cove and that measuing both of these vaiables povides a good monitoing tool. Biomass can be explained by a combination of factos, such as nutients and light conditions and thee is potential fo developing a biomass metic that incopoates these factos. Moe detailed analysis of ou dataset is needed to develop such a metic, especially in combination with the thid yea data of this study. Diatom assemblage composition is stongly influenced by nutients, especially phosphous (-P and TP), we wee theefoe able to develop phosphous infeence models and indices. Infeed values and metics wee tested by compaing them with measued phosphous values. The best esults wee achieved with the TP diatom infeence models developed fo the NJ Piedmont. We compaed the esults obtained fo the Euopean indices, the Biological Diatom Index, the Polluosensitivity Index and the Tophic Diatom index. All thee indices showed elatively good coelations with eithe -P and/o TP, suggesting that all thee methods could potentially be applied and the esults compaed, when using diatoms as indicatos of ive phosphous in the NJ Piedmont. The biggest limitation to futhe development of models and metics is pobably the epesentativeness of nutient values that ae based on vey few samples pe site. Inceasing the numbe of samples pe site is ecommended fo futue studies. In summay, this study shows that algae can be used as indicatos of nutient impaiment fo the NJ Piedmont. Diatoms especially show good esponse to nutients and thei use as monitoing tool is highly ecommended. Biomass metics need futhe analysis, the possibility of developing metics combining diffeent factos influencing algal gowth, especially nutients is pomismg. The Academy of Nat ual Sciences 4 Patick Cente fo Envionmental Reseach

50 Refeences Ameican Public Health Association, Ameican Wate Woks Association and Wate Pollution Contol Fedeation (APHA, A WW A and WPCF) Standad Methods fo the Examination of Wate and Wastewate, 19th ed. Washington, DC. Bahls, L. L Peiphyton bioassessment methods fo Montana steams. Montana Wate Quality Bueau, Depatment ofhealth and Envionmental Science, Helena, MT. Babou, M. T., J. Geitsen, B. D. Snyde, and J. B. Stibling Rapid bioassessment potocols fo use in steams and wadeable ives: Peiphyton, benthic maco invetebates, and fish, Second Edition. EPA 841-B-99-2, Washington, D.C., U.S. Envionmental Potection Agency, Office ofwate. Biggs, B. J. F Pattens in benthic algae of steams. In Algal Ecology, Feshwate Benthic Ecosystems. R. J. Stevenson, M. L. Bothwell, and R. L. Lowe (eds.). Academic Pess, NY. Biggs, B. J. F. 2. Eutophication of steams and ives: Dissolved nutient-chloophyll elationships fo benthic algae. Jounal ofnoth Ameican Benthological Society 19: Biks, H. J. B., S. Juggins, and J. M. Line. 199a. Lake suface-wate chemistyeconstuction fom paleolimnological data. In: The Suface Wate Acidification Pogamme. Edited by B.J. Mason. Cambidge Pess, Cambidge. Pp.: Biks, H. J. B., J. M. Line, S. Juggins, A C. Stevenson, and C. J. F. te Baak. 199b. Diatoms and ph econstuctions. Philosophical Tansactions of the Royal Society oflondon, seies B 327: Biks, H. J. B. 21. Maximum likelihood calibation and the compute pogam WACALIB a coection. Jounal of Paleolimnology 25(1): Blum, J. L The ecology ofive algae. Botanical Review 22: Chales, D., D. Winte, and M. Hoffman. 2. Field Sampling pocedues fo the New Jesey Algae Indicatos poject. PCER Pocedue P Patick Cente fo Envionmental Reseach, Academy ofnatual Sciences, Philadelphia, PA. 18 pp. Chales, D. F., C. Knowles, R. Davis ( eds.). 22. Potocols fo the analysis of algal samples collected as pat ofthe U.S. Geological Suvey, National Wate-Quality Assessment Pogam. Repot No The Academy ofnatual Sciences. Patick Cente fo Envionmental Reseach, Academy ofnatual Sciences, Philadelphia, PA. 124 pp. The Academy of Nat ual Sciences 41 Patick Cente fo Envionmental Reseach

51 Cemagef Etude des methodes biologiques quantitatives d'appeciation de la qualite des eaux. Rappot Division Qualite des eaux Lyon- Agence fmanciee de Bassin Rhone Mediteanee- Cose, Piee-Benite, 28 pp. Cotte, P Tabulato, vesion Patick Cente fo Envionmental Reseach, ANSP, Philadelphia, P A Cotte, P. 21. Tabulato Installation and Uses Guide. Patick Cente fo Envionmental Reseach, ANSP, Philadelphia, P A. 24 pp. Cuffuey, T. F., Gutz, M.. E., andm. R. Meado Methods fo collecting benthic invetebate samples as pat of the National Wate-Quality Assessment Pogam. Open-File Repot U.S. Geological Suvey, Raleigh, NC. 66 pp. Dixit, S. S., Smol, J.P., Kingston, J. C., and D. F. Chales Diatoms: Poweful indicatos of envionmental change. Envionmental Science and Technology 26 (1 ): Dodds, W. K, V. H. Smith, and K Lohman. 22. Nitogen and phosphous elationships to benthic algal biomass in tempeate steams. Canadian Jounal of Fisheies and Aquatic Sciences 59: Dodds, W. K, and E. B. Welch. 2. Establishing nutient citeia in steams. Jounal of the Noth Ameican Benthological Society 19: Dytham, C Choosing and Using Statistics. A Biologist's Guide. Blackwell. Oxfod. Ennis, G. L., and L. J. Albight Distibution and abundance ofpeiphyton and phytoplankton species in two Subactic Canadian ives. Canadian Jounal of Botany 6: Envionmental and Enegy Development Solutions (ENSR). 21. The Relationships Between Nutient Concentations and Peiphyton Levels in Rives and Steams- A Review of Scientific Liteatue. New England Intestate Wate Pollution Contol Commission. Document Numbe Fallu, M.A., N. Allaie, and R. Pienitz. 2. Feshwate diatoms fom nothen Quebec and Labado (Canada). Bibliotheca Diatomologica, Band 45: 1-2. Fitzpatick, F. A., Waite, I. R., D'Aconte, P. J., Meado, M. R., Maupin, M.A., and Gutz, M. E Revised Methods fo Chaacteizing Steam Habitat in the National Wate-Quality Assessment Pogam: U.S. Geological Suvey Wate-Resouces Investigations Repot pp. Fancoeu, S.N. 21. Meta-analysis oflotic nutient amendment expeiments: Detecting and quantifying subtle esponses. Jounal of Noth Ameican Benthological Society 2(3): The Academy of Nat ual Sciences 42 Patick Cente fo Envionmental Reseach

52 Hall, R. L., and J. P. Smol A weighted aveaging egession and calibation model fo infeing total phosphoous concentation fom diatoms in Bitish Columbia (Canada) lakes. Feshwate Biology27: Howitz, R. and C. Flindes. 23. Bioassessment Integation Study: Systems Ecology Evaluation ofus EPA Rapid Bioassessment Potocols in New Jesey (Macoinvetebates, Peiphyton, Fish and Habitat) Quality ContoVQuality Assuance Poject Plan. Jongman, R. H. G., C. J. F. te Baak, ando. F. R. van Tongeen DataAnalysis in Community and Landscape Ecology. Cambidge Univesity Pess, Cambidge. Juggins, S., and C. J. F. te Baak CALIBRATE- a compute pogam fo speciesenvionmental calibation by Weighted aveaging Patial least squae egession..81. Univesity ofnewcastle. Newcastle, UK. Juggins, S., and C. J. F. te Baak. 21. CALIBRATE Vesion 1.. A C++ Pogam fo analysing and visualising species envionment elationships and fo pedicting envionmental values fom species assemblages. Use Guide Vesion 1.. Depatment of Geogaphy. Univesity ofnewcastle. Newcastle, UK. Kelly, M.G Use of the tophic diatom index fo monitoing eutophication in ives. Wate Resouces 32: Kelly, M. G., and B. A. Whitton, The tophic diatom index. A new index fo monitoing eutophication in ives. Jounal of Applied Phycology: 7: Kelly, M. G., and B. A. Whitton Biological monitoing of eutophication in ives. Hydobiologia 384: Kiy, P., D. Velinsky, and A.-M. Compton Detemination of dy weight and pecent oganic matte fo sediments, tissues and benthic algae. PCER Pocedue P Patick Cente fo Envionmental Reseach, Academy ofnatual Sciences, Philadelphia, PA. 3 pp. Lecointe, C., M. Coste. and J. Pygiel OMNIDIA: A softwae fo taxonomy, calculation of diatom indices and inventoies management. Hydobiologia 269/27: Line, J. M., C. J. F. te Baak, and H. J. B. Biks WACALIB vesion 3.3- a compute pogam to econstuct envionmental vaiables fom fossil assemblages by weighted aveaging and to deive sample-specific eos of pediction. Jounal of Paleolimnology 1: New Jesey Depatment of Envionmental Potection (NJ DEP) Geologic Map ofnew Jesey. NJ DEP, Division of Science and Reseach, Geological Suvey. The Academy of Nat ual Sciences 43 Patick Cente fo Envionmental Reseach

53 New Jesey State Depatment of Envionmental Potection (NJ DEP) The establishment of ecoegion biological efeence sites fo New Jesey steams. Incopoating Habitat Quality and Benthic Macoinvetebate Communities Monitoing Data. State ofnew Jesey, Chistine Todd Whitman Goveno, Robet C. Shinn, J. Commissione. Tenton, NJ. New Jesey Depatment of Envionmental Potection. (NJ DEP). 2. Wate Quality Monitoing Netwoks 2. NJ DEP Division of Wateshed Management. Tenton, NJ. New Jesey Depatment of Envionmental Potection (NJ DEP). 21. Suface wate quality standads. N.J.A.C. 7:9B. Tenton, NJ. 129 pp. Moulton, S. R., J. G. Kennen, R. M. Goldstein, and J. A. Hambook. 22. Revised Potocols fo Sampling Algal, Invetebate and Fish Communities as Pat of the National Wate-Quality Assessment Pogam. Open-File Repot US Geological Suvey, Reston, VA. 75 pp. Omenik, J. M Ecoegions of the conteminous United States. Annals ofthe Association of Ameican Geogaphes. 77(1): Office ofthe New Jesey State Climatologist (ONJSC) Rutges Univesity. Patick Cente fo Envionmental Reseach. 2. Quality Assuance Poject Plan, Poject Name: Undestanding the Relationship Between Natual Conditions And Loadings on Eutophication: Algal Indicatos ofeutophication fo New Jesey Steams, The Academy of Natual Sciences, Philadelphia, P A. Patick, R A poposed biological measue of steam conditions. Vehandlungen. Intenationale Veeinigung fu Theoetische und Angewandte Limnologie 11: Ponade, K., and D. Winte. 22. Pocedue fo semi-quantitative analysis of soft-algae and diatoms. Patick Cente fo Envionmental Reseach. Pocedue No. P Patick Cente fo Envionmental Reseach, The Academy ofnatual Sciences, Philadelphia, PA. 6 pp. Pote, S.D., T. F. Cuffuey, M. E. Gutz, and M. R. Meado Methods fo Collecting Algal Samples as Pat of the National Wate-Quality Assessment Pogam. Open-File Repot U.S. Geological Suvey, Raleigh, NC. 39 pp. Pygiel J. and M. Coste Pogess in the use of diatoms fo monitoing ives in Fance. In: J. Pygiel, B. A Whitton. and J. Bukowska ( eds.), Use of Algae fo Monitoing Rives III. Agence de l'eau Atois-Picadie, Douai, (Fance). pp Reed, T. J., B. T. White, G. L. Centinao, J. F. Dudek, V. Cocino, A. B Speha, and A. R. Potz. 22. Wate Resouces Data, New Jesey, Wate Yea 21. Volume 1. Suface-Wate Data. Wate-Data Repot, NJ-1-1. West Tenton, NJ. 297 pp. The Academy of Nat ual Sciences 44 Patick Cente fo Envionmental Reseach

54 Schwoebel, J Einfiihung in die Limnologie. Gustav Fische Velag. Stuttgat. Smith, V. H., Tilman, G. D., and J. C. Nekola Eutophication: Effects of excess nutient inputs on feshwate, maine, and teestial ecosystems. Envionmental Pollution 1: Stevenson, R. J. andy. Pan Assessing envionmental conditions in ives and steams with diatoms. In: Stoeme E. F. and J. P. Smol (eds.). The Diatoms: Applications fo the Envionmental and Eath Sciences. Cambidge Univesity Pess, Cambidge, UK. Pp Tedow, J. C. F Soils ofnew Jesey. Robet E. Kiege Publishing Company, Inc., Malaba, FL. te Baak, C. J. F. and I. C. Pentice, A theoy of gadient analysis. Advances in Ecological Reseach 18: te Baak, C. J. F. and H. Van Dam Infeing ph fom diatoms: A compaison of old and new calibation methods. Hydobiologia 178: U.S. EPA Methods fo the detemination of chemical substances in maine and estuaine envionmental samples. EPA/6/R-92/121, Office ofreseach and Development, U.S. EPA, Washington, D.C. US. EPA. 2a. Nutient Citeia Technical Guidance Manual: Rives and Steams, U.S. Envionmental Potection Agency, Washington, DC. EPA-822-B--2. US. EPA. 2b. Ambient Wate Quality Citeia Recommendations: Rives and Steams in Nutient Ecoegion IX. U.S. Envionmental Potection Agency, Washington, DC. EPA-822-B Velinsky, D. 2. Syinge wate sampling and filtation fo the collection of filteed nutient samples and unfilteed nutient samples. PCER Pocedue P Patick Cente fo Envionmental Reseach, Academy of Natual Sciences, Philadelphia, P A. 4 pp. Velinsky, D., and J. DeAlteis. 2. Benthic algae and sediment chloophyll a pepaation and analysis. PCER Pocedue P Patick Cente fo Envionmental Reseach, Academy of Natual Sciences, Philadelphia, PA. 4 pp. Winte, J. G. and H. C. Duthie. 2. Epilithic diatoms as indicatos of steam total N and total P concentation. Jounal of the Noth Ameican Benthological Society 19(1): Wolfe, P. E The Geology and Landscapes ofn ew Jesey. Cane, Russak and Company, Inc., N.Y. 351 pp. The Academy of Nat ual Sciences 45 Patick Cente fo Envionmental Reseach

55 Appendix 1 Summay of site chaacteistics. All sites sampled in 2 and 21. la) Raw envionmental data fo vaiables measued at each site each. Note: All vaiables wee measued by PCER staff in the field at time of algal sampling and/o in the laboatoy. Geneal site chaacteistics: S_no, site each numbe; S_date, algae sampling date; B_size, basin size; %, pecent open canopy cove; R _len, each length; R _wid, aveage ive width at each; Flow, flow estimate in categoies (1 =slow; 2=modeate; 3=fast); Substate: %Bed, %bedock; %Bo, %boulde; %Cob, % cobble; %Ga, % gavel; %S, % sand; %Si/Cl, % silt and clay. Biomass: AFDM, Ash fee dy mass; Chl_ a, chloophyll a; SitelD S_no S_date % %Bed %Bo %Cob %Ga %San %Si/Cl IIAN81 NJ_81 1:22 am IIAN81 NJ_81_2 1:22 am IIAN81 llano! II llano! II IIANOII5 IIANOII5 NJ_81_3 1:22 am NJ_lll_l 1:22 am NJ_lll_2 1:22 am NJ_ll5_1 1:22 am NJ_ll5_2 1:22 am I IIANOII5 NJ_ll5_3 1:22 am I IIANOII5 IIANOII5 NJ_ll5_1 1:22 am NJ_ll5_2 1:22 am l IIANOII5 IIAN118 IIAN118 NJ_ll5_3 1:22 am NJ_ll8_1!:22am NJ_ll8_2!:22am lll IIAN118 IIAN192 IIAN192 IIAN192 IIAN194 IIAN194 IIAN194 IIANOI95 NJ_ll8_3!:22am NJ_l92_1 1:22 am NJ_l92_2 1:22 am NJ_l92_3 1:22 am NJ_l94_1 1:22 am NJ_l94_2 1:22 am NJ_l94_3 1:22 am NJ_l95_1 1:22 am I --I --I IIANOI95 NJ_l95_2 1:22 am I IIANOI95 NJ_l95_3 1:22 am IIAN27 NJ_27 _I 1:22 am IIAN27 IIAN27 NJ_27 _2 NJ_27 _3 1:22 am 1:22 am IIAN29 NJ_29_1 1:22 am IIAN29 NJ_29_2 1:22 am IIAN29 NJ_29_3 1:22 am IIAN211 IIAN211 IIAN211 NJ_211_1!:22am NJ_211_2!:22am NJ_211_3!:22am 5.2 I ol 8.91 IIAN211 IIAN211 NJ_211_1!:22am NJ_211_2!:22am l IIAN211 NJ_211_3!:22am IIAN215 NJ_215_1 1:22 am IIAN215 IIAN215 IIAN227 IIAN227 IIAN227 IIAN231 NJ_215_2 1:22 am NJ_215_3 1:22 am NJ_227_1 1:22 am NJ_227_2 1:22 am NJ_227_3 1:22 am NJ_231_1 1:22 am I --I --I IIAN234 NJ_234_1 1:22 am IIAN234 NJ_234_2 1:22 am Tbe Academy of Nat ual Sciences 46 Patick Cente fo EnvionmentalReseacb

56 SitelD S_no S_date % %Bed %Bo %Cob %Ga %San %Si/Cl IIAN234 NJ_234 1:22 am IIAN234 NJ_234_1 1:22 am IIAN234 NJ_234_2 1:22 am IIAN234 NJ_234_3 1:22 am 1 IIAN235 NJ_235_1 1:22 am IIAN235 NJ_235_2 1:22 am IIAN235 NJ_235_3 1:22 am IIAN237 NJ_237_1 1:22 am 2.83 IIAN237 NJ_237_2 1:22 am IIAN237 NJ_237_3 1:22 am 3.21 IIAN238 NJ 238 I 1:22 am 46.8 IIAN238 NJ :22 am 6.24 IIAN238 NJ :22 am IIAN267 NJ_267 _I 1:22 am 8.8 IIAN267 NJ_267_2 1:22 am 88.4 IIAN267 NJ_267_3 1:22 am IIAN274 NJ_274_1 1:22 am 1 IIAN274 NJ 274 I 1:22 am IIAN281 NJ_281_1 1:22 am 5.2 IIAN281 NJ_281_2 1:22 am IIAN281 NJ_281_3 1:22 am 79.4 IIAN291 NJ_291_1 1:22 am IIAN291 NJ_291_2 1:22 am 78 IIAN291 NJ_291_3 1:22 am IIAN318 NJ_318_1 1:22 am IIAN318 NJ_318_2 1:22 am IIAN318 NJ_318_3 1:22 am IIAN321 NJ_321_1 1:22 am 4.56 IIAN321 NJ_321_2 1:22 am IIAN321 NJ_321_3 1:22 am 16.2 IIAN326 NJ_326_1 1:22 am IIAN326 NJ_326_2 1:22 am IIAN326 NJ_326_3 1:22 am IIAN333 NJ_333_1 1:22 am IIAN333 NJ_333_2 1:22 am IIAN333 NJ_333_3 1:22 am IIAN339 NJ_339_1 1:22 am IIAN339 NJ_339_2 1:22 am IIAN339 NJ_339_3 1:22 am IIAN341 NJ_341_1 1:22 am 1 IIAN341 NJ_341_2 1:22 am 1 IIAN341 NJ_341_3 1:22 am II II II I ol I --I --I I d ol IIAN37 NJ_37_1 1:22 am 1 IIAN37 NJ_37_2 1:22 am 1 IIAN37 NJ_37_3 1:22 am 1 IIAN374 NJ_374_1 1:22 am 1 IIAN374 NJ_374_2 1:22 am 1 IIAN374 NJ_374_3 1:22 am d IIAN374 NJ_374_1 1:22 am IIAN374 NJ_374_2 1:22 am 75 IIAN374 NJ_374_3 1:22 am 87.5 IIAN3 82 NJ 3 82 I I :22 am 87 IIAN382 NJ :22 am I I 115. I --I --I Tbe Academy of Nat ual Sciences 47 Patick Cente fo EnvionmentalReseacb

57 SitelD S_no S_date % %Bed %Bo %Cob %Ga %San %Si/Cl IIAN382 NJ 382 1:22 am 1 IIAN396 NJ_396_1 1:22 am IIAN396 NJ_396_2 1:22 am 8.32 IIAN396 NJ_396_3 1:22 am 9.88 IIAN45 NJ_ 45_1 1:22 am IIAN45 NJ_ 45_2 1:22 am IIAN45 NJ_ 45_3 1:22 am IIAN45 NJ_45_1!:22am 12.5 IIAN45 NJ_ 45_2 1:22 am IIAN45 NJ_ 45_3 1:22 am 2.83 IIAN413 NJ_ 413_1 1:22 am 15.8 IIAN413 NJ_ 413_2 1:22 am IIAN413 NJ_ 413_3 1:22 am IIAN414 NJ 414 I 1:22 am 57.5 IIAN424 NJ_ 424_1 1:22 am IIAN424 NJ_ 424_2 1:22 am IIAN424 NJ_ 424_3 1:22 am 3.68 IIAN429 NJ_429_1!:22am IIAN429 NJ_ 429_2 1:22 am IIAN429 NJ_429_3!:22am IIAN439 NJ_439_1!:22am IIAN439 NJ_ 439_2 1:22 am 18.2 AN439 NJ :22 am I d ol I I 23.I sui d M~ d Max Mean Median sui 25'h pec! d 75th ect 'h pec!= 25'h pecentile 75'h pec!= 75'h pecentile (uppe 25'h pecentile) Tbe Academy of Nat ual Sciences 48 Patick Cente fo EnvionmentalReseacb

58 Appendix 1 Summay of site chaacteistics. All sites sampled in 2 and b) Raw envionmental data fo vaiables measued at each site. Note: S_date, algae sampling date 2 l; Landuse: Ub %, pecent uban 1 l; Ag %, pecent agicultue 1 l; Fo%, pecent foesty 1 l; Watechemisty: Cond, specific conductivity); NH 3 -N 2 l; N 3 -N 2 ); TN, total nitogen 1 l (*TN calculated fom combination oftkn 1 ) and N 3 -N 2 )); TKN, total Kjeldahl nitogen 1 ); P 4, othophospate 2 ); TP, total phosphous 2 ); ph 1 ); Alk, alkalinity); Had, hadness 2 ); t) data povided bynj DEP and/o data ecods collected by NJ DEP and USGS at suface wate monitoing stations, measued within a maxiumum of 4 weeks fom algal sampling. 2 ) vaiable measued by PCER Geochemisty section. Site ID Lat Long S_date Aea Ub Ag Fo Cond NH,-N NO,-N TN TKN IAN81 IANOIII IANOII5 IANOII5 IANOII8 IANOI92 IANOI94 IANOI95 IAN27 IAN29 IAN211 IAN211 IAN215 IAN227 IAN231 IAN234 IAN234 IAN235 IAN237 IAN238 IAN267 IAN274 IAN274 IAN281 IAN291 IAN318 IAN321 IAN326 IAN333 IAN339 IAN341 IAN37 IAN374 IAN374 IAN382 IAN396 IAN45 IAN45 IAN413 IAN414 N W 4" 32' 75" 2' 4" 17' 74" 42' 4" 14' 74" 41' 4" 14' 74" 41' 4" 13' 74" 45' 4" 46' 74" 16' 4" 4' 74" 18' 4" 37' 74" 16' 4" 59' 74" 1' 4" 58' 73" 58' 4" 54' 74. 2' 4" 54' 74. 2' 4" 46' ' 4" 38' 74" 31' 4" 49' 74. 2' 4" 48' ' 4" 48' ' 4" 49' ' 4" 51' 74" 23' 4" 5' 74. 2' 41" 2' 74" 14' 4" 53' 74" 13' 4" 53' 74" 13' 41"1' 74"6' 4" 51' 74" 6' 4" 43' ' 4" 38' 74" 58' 4" 34' " 28' ' 4" 33' 74" 47' 4" 32' 74" 41 4"38' 74"41' 4" 34' 74. 4' 4" 34' 74. 4' 4" 19' 74" 36' 4" 22' ' 4" 25' 74" 38' 4" 25' 74" 38' 4" 32' ' 4" 32' ' km' I I % % % II II I l.ll * * * * * * * I * * PO, TP ph Alk I -I -I 551 -I 281 -I -I ol -I 651 -I -I 15ol I I -I -I 121 -I -I -I -I -I 151 -I -I -I -I 151 -I -I -I 171 -I -I Tbe Academy of Nat ual Sciences 49 Patick Cente fo EnvionmentaiReseacb

59 SitelD Lat Long S_date Aea Ub Ag Fo Cond NH,-N NO,-N TN TKN PO, TP ph Alk N w km' % % % /L IAN424 4" 34' 74" 29' I IAN429 4" 3' 74" 28' AN439 4" 17' 74" 23' :I IMin 4" 13' ' IMax 41" 2' 75" 2' !Mean ml!median l25'h pect 'h Eect ol 25'h pec!= 25'h pecentile 75'h pec!= 75'h pecentile (uppe 25'h pecentile) Tbe Academy of Nat ual Sciences 5 Patick Cente fo EnvionmentalReseacb

60 Appendix 2: Diatom species list Taxonomic index of 36 diatom species fom samples collected in 2 and 21, used fo development of models and metics. Numbes coespond to numbes used in gaphs in the text. No. Taxon name Achnanthidium minutissimum (Kiitzing) Czanecki 2 Achnanthes exigua Gunow 3 Achnanthes lanceolata (Bebisson in Kiitzing) Gunow 4 Achnanthes lapidosa Kasske 5 Achnanthes lineais (Smith) Gunow 6 Achnanthes sp.1 NEW JERSEY KCP 7 Achnanthes peagalli Bun et Heibaud 8 Achnanthes pinnata Hustedt 9 Achnanthes lanceolata va. apiculata Patick 1 Achnanthes delicatula (Kiitzing) Gunow 11 Achnanthes lanceolata subsp. ostata (estup) Lange-Betalot 12 Achnanthes chlidanos Hohn et HeUemann 13 Achnanthes lanceolata va. abbeviata Reime 14 Achnanthes subhudsonis va. kaeuselii Cholnoky 15 Achnanthes minutissima va. sapophila Kobayasi et Mayama 16 Achnanthes haveyi Reime 17 Achnanthes exigua va. consticta Toka 18 Achnanthes petesonii Hustedt 19 Achnanthes upestoides Hohn 2 Achnanthes minutissima va. scotica (Cate) Lange-Betalot 21 Achnanthes subatomus Hustedt 22 Achnanthes daui Foged 23 Achnanthes gana Hohn & HeUemann 24 Achnanthes lanceolata subsp. fequentissima Lange-Betalot 25 Amphoa ovalis (Kiitzing) Kiitzing 26 Amphoa libyca Ehenbeg 27 Amphoa montana Kasske 28 Amphoa pediculus (Kiitzing) Gun. 29 Asteionella fomosa Has sal 3 Aulacoseia pfaffiana (Reinsch) Kamme 31 Aulacoseia ambigua (Gunow) Simonsen 32 Aulacoseia distans (Ehenbeg) Simonsen 33 Aulacoseia subatica (. Mulle) Hawoth 34 Aulacoseia ganulata (Ehenbeg) Simonsen 35 Aulacoseia italica (Ehenbeg) Simonsen 36 Caloneis bacillum (Gunow) Cleve 37 Caloneis hyalina Hustedt 38 Caloneis silicula (Ehenbeg) Cleve 39 Capatogamma cucicula (Gunow ex Cleve) Ross 4 Cocconeis placentula va. lineata (Ehenbeg) Van Heuck 41 Cocconeis placentula va. euglypta (Ehenbeg) Cleve The Academy of Nat ual Sciences 51 Patick Cente fo Envionmental Reseach

61 42 Cocconeis fluviatilis Wall ace 43 Cocconeis pediculus Ehenbeg 44 Cyclostephanos tholifomis Stoeme, Hakansson et Theiot 45 Cyclostephanos invisitatus (Hohn et Hellemann) Theiot, Stoeme et Hakansson 46 Cyclotella atomus Hustedt 47 Cyclotella meneghiniana Kiitzing 48 Cyclotella ocellata Pantosek 49 Cyclotella stelligea (Cleve et Gunow) Van Heuck 5 Cyclotella pseudostelligea Hustedt 51 Cyclotella opeculata (Agadh) Kiitzing 52 Cyclotella sp. 1 ANS NEW JERSEY KCP 53 Caticula cuspidata (Kiitzing) Mann 54 Cymatopleua solea (Bebisson) Smith 55 Cymbella naviculifomis Aueswald ex Heibaud 56 Cymbella aspea (Ehenbeg) Peagallo 57 Cymbella tumida (Bebisson ex Kiitzing) Van Heuck 58 Cymbella poxima Reime 59 Cymbella tumidula Gunow ex Schmidt 6 Denticula elegans Kiitzing 61 Diatoma mesodon (Ehenbeg) Kiitzing 62 Diatoma vulgais Boy 63 Diploneis oblongella (Naegeli ex Kiitzing) Ross 64 Diploneis puella (Schumann) Cleve 65 Epithemia tugida va. westemannii (Ehenbeg) Gunow 66 Eunotia exigua (Bebisson ex Kiitzing) Rabenhost 67 Eunotia fomica Ehenbeg 68 Eunotia pectinalis va. mino (Kiitzing) Rabenhost 69 Eunotia paeupta Ehenbeg 7 Eunotia paeupta va. bidens (Ehenbeg) Gunow 71 Eunotia mino (Kiitzing) Gunow 72 Eunotia bilunais (Ehenbeg) Mills 73 Fagilaia capucina Desmaziees 74 Fagilaia constuens (Ehenbeg) Gunow 75 Fagilaia cotonensis Kitton 76 Fagilaia pinnata Ehenbeg 77 Fagilaia pinnata va. lancettula (Schumann) Hustedt 78 Fagilaia vaucheiae (Kiitzing) Petesen 79 Fagilaia bevistiata va. inflata (Pantocsek) Hustedt 8 Fagilaia fasciculata (Agadh) Lange-Betalot 81 Fagilaia nanana Lange-Betalot 82 Fagilaia capucina va. gacilis (Oestup) Hustedt 83 Fagilaia capucina va. umpens (Kiitzing) Lange-Betalot 84 Fagilaia paasitica va. subconsticta Gunow 85 Fagilaia sp. 1 ANS NEW JERSEY KCP 86 Fagilaia sp. 1? 87 Fustulia homboides (Ehenbeg) De Toni 88 Fustulia homboides va. amphipleuoides (Gun.) DeT. 89 Fustulia vulgais (Thwaites) DeT. The Academy of Nat ual Sciences 52 Patick Cente fo Envionmental Reseach

62 9 Fustulia weinholdii Hustedt 91 Fustulia cassinevia (Bebisson) Lange-Betalot et Kamme 92 Gomphoneis heculean a (Eh.) Cl. 93 Gomphoneis minuta Kociolek & Stoeme 94 Gomphonema affine Kiitzing 95 Gomphonema angustatum (Kiitz.) Rabh. 96 Gomphonema gacile Eh. emend. V. H. 97 Gomphonema pavulum (Kiitz.) Kiitz. 98 Gomphonema tuncatum Ehenbeg 99 Gomphonema sphaeophoum Ehenbeg 1 Gomphonema tuis Ehenbeg 11 Gomphonema olivaceoides Hustedt 12 Gomphonema manubium Ficke 13 Gomphonema pumilum (Gun.) Reich. & Lange-Bet. 14 Gomphonema sacophagus Geg. 15 Gomphonema mico pus Kiitzing 16 Gomphonema minutum (Ag.) Ag. 17 Gomphonema lingulatifome Lange-Betalot & Reichadt 18 Gomphonema patickii Kociolek & Stoeme 19 Gomphonema kobayasii Kociolek & Kingston 11 Gomphonema af pavulum va. sapophilum ANS NEW JERSEY KCP Ill Gomphonema sp. 1 ANS NEW JERSEY KCP 112 Gomphonema sp. 2 ANS NEW JERSEY KCP 113 Gyosigma acuminatum (Kiitz.) Rabh. 114 Gyosigma obscuum (W. Sm.) Giff. & Henf. 115 Hantzschia amphioxys (Eh.) Gun. 116 Melosia vaians Ag. 117 Meidian ciculae (Gev.) Ag. 118 Navicula angusta Gunow 119 Navicula avensis Hustedt 12 Navicula atomus (Kiitz.) Gun. 121 Navicula biconica Pat. 122 Navicula cyptocephala Kiitzing 123 Navicula difficillima Hustedt 124 Navicula gegaia Donk. 125 Navicula kotschyi Gunow 126 Navicula minima Gunow 127 Navicula mutica Kiitzing 128 Navicula notha Wallace 129 Navicula paucivisitata Pat. 13 Navicula pupula Kiitzing 131 Navicula tipunctata (. F. Miill.) Boy 132 Navicula hynchocephala Kiitzing 133 Navicula capitata Ehenbeg 134 Navicula cyptocephala va. veneta (Kiitz.) Rabh. 135 Navicula decussis st. 136 Navicula hustedtii Kass. 137 Navicula capitata va. hungaica (Gun.) Ross The Academy of Nat ual Sciences 53 Patick Cente fo Envionmental Reseach

63 138 Navicula peegina (Eh.) Kiitz. 139 Navicula tivia/is Lange-Bet. 14 Navicula canalis Pat. 141 Navicula capitata va. luenebugensis (Gun.) Pat. 142 Navicula ingenua Hustedt 143 Navicula intega (W. Sm.) Ra1fs 144 Navicula menisculus Schum. 145 Navicula placenta Ehenbeg 146 Navicula schoetei va. escambia Pat. 147 Navicula seceta va. apiculata Pat. 148 Navicula salinaum Gunow 149 Navicula symmetica Pat. 15 Navicula tenelloides Hustedt 151 Navicula tenea Hustedt 152 Navicula viidula va. ostellata (Kiitz.) Cl. 153 Navicula agestis Hustedt 154 Navicula potacta (Gun.) Cl. 155 Navicula minuscula Gunow 156 Navicula heuflei va. leptocephala (Beb ex Gun.) Peag. 157 Navicula bacilloides Hustedt 158 Navicula absoluta Hustedt 159 Navicula veneta Kiitzing 16 Navicula longicephala Hustedt 161 Navicula molestifomis Hustedt 162 Navicula ignota va. acceptata (Hust.) Lange-Bet. 163 Navicula cyptotenella L.B. in Kamm. & L.-B. 164 Navicula peminuta Gunow 165 Navicula subminuscula Mang. 167 Navicula gemainii Wallace 168 Navicula eifuga Lange-Bet. 169 Navicula ecens Lange-Bet. 17 Navicula capitatoadiata Gemain 171 Navicula atomus va. pemitis (Hust.) Lange-Bet. 172 Navicula suchlandtii Hustedt 173 Navicula longicephala va. vilaplanii Lange-Beta1ot & Sa bate 175 Navicula lanceolata (Ag.) Eh. 176 Navicula menisculus va. gunowii Lange-Beta1ot 177 Navicula uttneii va. capitata Hustedt 178 Navicula paabilis Hohn & Helleman 179 Navicula sp. 1 ANS NEW JERSEY KCP 18 Neidium affine (Eh.) Pfitz. 181 Neidium alpinum Hustedt 182 Nitzschia aciculaioides Hustedt 183 Nitzschia aciculais (Kiitz.) W. Sm. 184 Nitzschia amphibia Gunow 185 Nitzschia capitellata Hustedt 186 Nitzschia dissipata (Kiitz.) Gun. 187 Nitzschia fonticola Gunow The Academy of Nat ual Sciences 54 Patick Cente fo Envionmental Reseach

64 188 Nitzschia fustulum (Kiitz.) Gun. 189 Nitzschia gacilis Hantz. ex Rabh. 19 Nitzschia heufleiana Gunow 191 Nitzschia lineais (Ag. ex W. Sm.) W. Sm. 192 Nitzschia micocephala Gunow 193 Nitzschia palea (Kiitz.) W. Sm. 194 Nitzschia palea va. tenuiostis Gunow 195 Nitzschia ecta Hantz. ex Rabh. 196 Nitzschia sigma (Kiitz.) W. Sm. 197 Nitzschia dissipata va. media (Hantz.) Gun. 198 Nitzschia hungaica Gunow 199 Nitzschia inconspicua Gunow 2 Nitzschia peminuta (Gun.) Peagallo 21 Nitzschia clausii Hantz. 22 Nitzschia consticta va. subconsticta Gun. in Cl. et Gun. 23 Nitzschia filifomis (W. Sm.) V. H. 24 Nitzschia gacilis va. mino Skabitschevsky in Poschkina-Lavenko 25 Nitzschia intemedia Hantz. ex Cl. et Gun. 26 Nitzschia liebethuthii Rabenhost 27 Nitzschia littoalis Gun. incl. et Gun. 28 Nitzschia loenziana va. subtilis Gun. incl. et Gun. 29 Nitzschia paleacea Gun. in V. H. 21 Nitzschia osenstockii Lange-Beta1ot 211 Nitzschia tyblionella va. debilis (Anott) Hust. 212 Nitzschia vemiculais (Kiitz.) Hantz. in Rabh. 213 Nitzschia bevissima Gun. in V. H. 214 Nitzschia commutata Gunow 215 Nitzschia sociabilis Hustedt 216 Nitzschia palea va. debilis (Kiitz.) Gun. 217 Nitzschia angustatula Lange-Bet. 218 Nitzschia sinuata va. delognei (Gun.) Lange-Bet. 219 Nitzschia flex aides Geit1e 22 Nitzschia acidoclinata Lange-Bet. 221 Nitzschia tubicola Gun. incl. et Gun. 222 Nitzschia teestis (Peteson) Hust. 223 Nitzschia coactata Gunow 224 Nitzschia levidensis va. salinaum Gunow 225 Nitzschia loenziana Gunow 226 Nitzschia levidensis va. victoiae Gunow 227 Nitzschia tyblionella va. salinaum Gun. incl. et Gun. 228 Nitzschia aff.jonticola ANS NEW JERSEY KCP 229 Nitzschia achibaldii Lange-Beta1ot 23 Nitzschia sp. 1 ANS NEW JERSEY KCP 231 Nitzschia subconsticta Gunow 232 Pinnulaia divegens W. Sm. 233 Pinnulaia maio (Kiitz.) Rabh. 234 Pinnulaia mesolepta (Eh.) W. Sm. 235 Pinnulaia micostauon (Eh.) Cl. The Academy of Nat ual Sciences 55 Patick Cente fo Envionmental Reseach

65 236 Pinnulaia obscua Kass. 237 Pinnulaia upestis Hautz. 238 Pinnulaia subcapitata Geg. 239 Pinnulaia lundii Hustedt 24 Pinnulaia inteupta W. Sm. 241 Pinnulaia pavulissima Kam. 242 Plagiotopis Iepidoptea va. poboscidea (Cl.) Reim. 243 Pleuosigma angulatum (Quek.) W. Sm. 244 Reimeia sinuata (Geg.) Kociolek & Stoeme 245 Rhoicosphenia cuvata (Kiitz.) Gun. ex Rabh. 246 Stauoneis anceps Ehenbeg 247 Stauoneis smithii Gunow 248 Stauoneis phoenicenteon (Nitz.) Eh. 249 Stauoneis agestis Petes. 25 Stenopteobia intemedia (Lewis) V. H. 251 Stephanodiscus niagaae Ehenbeg 252 Stephanodiscus hantzschii Gunow 253 Stephanodiscus minutus H. L. Sm. 254 Suiella angusta Kiitzing 255 Suiella lineais W. Sm. 256 Suiella obusta Ehenbeg 257 Suiella stalagma Hohn & Hellem. 258 Suiella minuta Beb. 259 Suiella bebissonii va. kuetzingii Kamm. & Lange-Bet. 26 Suiella bebissonii Kamm. & Lange-Bet. 261 Suiella amphioxys W. Sm. 262 Suiella splendida (Eh.) Kiitz. 263 Syneda paasitic a (W. Sm.) Hust. 264 Syneda umpens va. familiais (Kiitz.) Hust. 265 Syneda ulna (Nitz.) Eh. 266 Syneda ulna va. oxyhynchus fo. mediocontacta (Fonti) Hust. 267 Syneda delicatissima va. angustissima Gunow 268 Syneda paasitica va. subconsticta (Gun.) Hust. 269 Tabellaiaflocculosa (Roth) Kiitz. 27 Thalassiosia weissflogii (Gun.) Fyxell & Hasle 271 Pseudostauosia bevistiata (Gun. in V.H.) Williams & Round 272 Bacillaia paadoxa Gmelin 273 Nupela neglecta Ponade, Lowe & Potapova 274 Nupela wellnei (Lange-Bet.) Lange-Bet. 275 Navicula sp. 2 ANS NEW JERSEY KCP 276 Navicula sp. 3 ANS NEW JERSEY KCP 277 Encyonema minutum (Hilse) Mann 278 Encyonema silesiacum (Bleisch) Mann 279 Encyonema postatum (Bekeley) Kiitzing 28 Fallacia pygmaea (Kiitzing) Stickle et Mann 281 Fallacia auiculata (Hustedt) Mann 282 Fallacia omissa (Hustedt) Mann 283 Fallacia tenea (Hustedt) Mann The Academy of Nat ual Sciences 56 Patick Cente fo Envionmental Reseach

66 284 Kaayevia clevei (Gunow) Round & Buktyiaova 285 Kaayevia lateostata (Hant.) Round and Bukt. 286 Luticola goeppetiana (Bleisch) Mann 287 Sellaphoa seminulum (Gun.) Mann 288 Stauosia constuens va. binodis (Ehenbeg) Hamilton 289 Stauosia constuens va. vente (Eh.) Hamilton 29 Stauosiella leptostauon (Ehenbeg) Williams et Round 291 Stauosiella pinnata (He.) Williams & Round 292 Tyblionella apiculata Geg. 293 Tyblionella levidensis Wm. Sm. 294 Tyblionella aeophila 295 Psammothidium bioetii (Gem.) Bukht. et Round 296 Psammothidium subatomoides (Hustedt) Bukhtiyaova et Round 297 Psammothidium ventalis (Kas.) Bukht. et Round 298 Eucocconeis laevis (Oestup) Lange-Betalot 299 Fagilaifoma consticta (Ehenbeg) Williams et Round 3 Fagilaifoma viescens (Ralfs) Williams et Round 31 Placoneis clementis (Gun) Cox 32 Placoneis elginensis (Geg.) Cox 33 Placoneis explanata (Hust.) Cox 34 Cavinula pseudoscutifomis (Gunow ex Schmidt) Mann et Stickle 35 Diadesmis confevacea Kiitzing 36 Diadesmis contenta (Gunow ex Van Heuck) Mann The Academy of Nat ual Sciences 57 Patick Cente fo Envionmental Reseach

67 Appendix 3: Speaman's ank-ode coelation fo full dataset fo both yeas (n=16) Note: Watechemisty: Cond, specific conductivity); NH 3 -N 2 ); N 3 -N 2 ); TN, total nitogen 1 ) (*TN calculated fom combination of TKN 1 ) and N 3 -N 2 ) ); TKN, total Kjeldahl nitogen 1 ); P 4, othophospate 2 ); TP, total phosphous 2 l; Alk, alkalinitfl; Had, hadness 2 l; pwl; DO, dissoved oxygen 1 l; Geneal site chaacteistics: B _size, basin size; %, pecent open canopy cove; R_len, each length; R_wid, aveage ive width at each; Flow, flow estimate in categoies (1 =slow; 2=modeate; 3=fust); Substate: %Bed, pecent bedock; %Bo, pecent boulde; %Cob, pecent cobble; %Ga, pecent gavel; %S, pecent sand; %Si/Cl, pecent silt and clay, BRBDCOG, pecent bedock, boulde, cobble and gavel combined; SDSTCL, pecent sand, silt and clay combined; BRBD, pecent bedock and boulde combined; CBGR, pecent cobble and gavel combined; Biomass: AFDM, Ash fee dy mass; Chl_a, chloophyll a; 1 ldata povided bynj DEP and/o data ecods collected by NJ DEP and USGS at suface wate monitoing stations, measued within a maxiumum of 4 weeks fom algal sampling; 2 lvaiable measued by PCER Geochemisty section. Algal cove/biomass estimate: Rapid biomass assessment (REA). visual estimate o(pecent cove ('Y stimated cove): %DGCov, %Dak Geen (%estimated cove); %LsSCov, %Long spiny Spiogia (%estimated cove); %MdbCov, %Moss-like (Dak bown) (%estimated cove); %Bgs1Cov, blue-geen (slimey) (%estimated cove), BlgCov, %blue-geen (%estimated cove); %BCCov, %Bown Coating (%estimated cove); %ChldCov, %Chladophoa (%estimated cove); %Dfi1Cov, %Diatoms (filamentous) (%estimated cove); %DTBCov, %Diatoms (thin laye)+ Bae (%estimated cove); %GFthCov, %Geen (Feathey) (%estimated cove); %GF1Cov, %Geen Filamentous #1 (%estimated cove); %GF2Cov, %Geen Filamentous #2 (%estimated cove); %GFBCov, %Geen Filamentous (Bushy) (%estimated cove); %GFCov, %geen filamentous (moss-like) (%estimated cove); %GFsCov, %Geen Fliamentous (Segemented banches) (%estimated cove); %HBCov, %Honey-Bown (%estimated cove); %LlGCov, %Long light geen (%estimated cove); %gcov, %Oange (%estimated cove); %TgLCov, %thin geen laye (%estimated cove); %TsCdCov, %Thin shot Cladophea (%estimated cove); %GBGCov, %Geen (blue-geen) (%estimated cove). Semi-quantitative count method (SQCM): pecent estimate o(numbes o(cells (% #cells): %DiatC, Diatoms(%# cell); %ChladC, Cladophoa sp.(% #cell); %egodc, Oedogonium sp.(% #cells); %RhizC, Rhizoclonium sp.(% #cells); %Scene, Scenedesmus sp.(% #cells); %SpiogC, Spiogya sp.(% #cells); %MeismopC, Meismopedia sp.(% #cells); %scillc, Oscillatoia sp.(% #cells); %AudouC, Audouinella sp.(% #cells); p- value: ** coelation significant at the.1 level (2-tailed test) * coelation significant at the.5 level (2-tailed test) NH,_N PO, TP Chl_a AFDM R_wid R_len Flow NO,-N.32 **.45 4**.383** ** * NH,-N.233*.36 6** * PO,.95 ** **.27*.236* TP ** * Chl_a. 716**.4 8**.341 ** AFDM.251 **.222* R_wid. 75 7**.28 **.373 R_len The Academy of Nat ual Sciences 58 Patick Cente fo Envionmental Reseach