Abstract
Macrophytes are a critical component of lake ecosystems affecting nutrient and contaminant cycling, food web structure, and lake biodiversity. The long-term (decades to centuries) dynamics of macrophyte cover are, however, poorly understood and no quantitative estimates exist for pre-industrial (pre-1850) macrophyte cover in northeastern North America. Using a 215 lake dataset, we tested if surface sediment diatom assemblages significantly differed among lakes that have sparse (<10% cover; group 1), moderate (10–40% cover; group 2) or extensive (>40% cover; group 3) macrophyte cover. Analysis of similarity indicated that the diatom assemblages of these a priori groups of macrophyte cover were significantly different from one another (i.e., difference between: groups 1 and 3, R statistic = 0.31, P < 0.001; groups 1 and 2, R statistic = 0.049, P < 0.01; groups 3 and 2, R statistic = 0.112, P < 0.001). We then developed an inference model for macrophyte cover from lakes classified as sparse or extensive cover (145 lakes) based on the surface sediment diatom assemblages, and applied this model using the top-bottom paleolimnological approach (i.e., comparison of recent sediments to pre-disturbance sediments). We used the second axis of our correspondence analysis, which significantly divided sparse and extensive macrophyte cover sites, as the independent variable in a logistic regression to predict macrophyte cover as either sparse or extensive. Cross validation, using 48 randomly chosen sites that were excluded from model development, indicated that our model accurately predicts macrophyte cover 79% of the time (r 2 = 0.32, P < 0.001). When applied to the top and bottom sediment samples, our model predicted that 12.5% of natural lakes and 22.4% of reservoirs in the dataset have undergone a ≥30% change in macrophyte cover. For the sites with an inferred change in macrophyte cover, the majority of natural lakes (64.3%) increased in cover, while the majority of reservoirs (87.5%) decreased in macrophyte cover. This study demonstrates that surface sediment diatom assemblages from profundal zones differ in lakes based on their macrophyte cover and that diatoms are useful indicators for quantitatively reconstructing changes in macrophyte cover.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Bachmann RW, Horsburgh CA, Hoyer MV, Mataraza LK, Canfield DE Jr (2002) Relations between trophic state indicators and plant biomass in Florida lakes. Hydrobiologia 470:219–234
Baker JR, Peck DV, Sutton DW (eds) (1997) Environmental monitoring and assessment program surface waters: field operations manual for lakes. EPA/620/R-97/001. U.S. Environmental Protection Agency, Washington, DC
Birks HH (2000) Aquatic macrophyte vegetation development in Kråkenes Lake, western Norway, during the late-glacial and early Holocene. J Paleolimnol 23:7–19
Brenner M, Hodell D, Leyden B, Curtis J, Kenney W, Gu B, Newman J (2006) Mechanisms for organic matter and phosphorus burial in sediments of a shallow, subtropical, macrophyte dominated lake. J Paleolimnol 35:129–148
Brodersen KP, Odgaard BV, Vestergaard O, Anderson NJ (2001) Chironomid stratigraphy in the shallow and eutrophic Lake Søbygaard, Denmark: chironomid-macrophyte co-occurrence. Freshwater Biol 46:253–267
Carpenter SR, Lodge DM (1986) Effects of submersed macrophytes on ecosystem processes. Aquat Bot 26:341–370
Clarke KR, Warwick RM (2001) Change in marine communities: an approach to statistical analysis and interpretation, 2nd edition. PRIMER-E, Plymouth
Davidson TA (2006) Zooplankton ecology and palaeoecology in nutrient enriched shallow lakes. PhD thesis, University College of London, 191 pp
Davidson TA, Sayer CD, Bennion H, David C, Rose N, Wade MP (2005) A year comparison of historical, macrofossil and pollen records of aquatic plants in a shallow lake. Freshwater Biol 50:1671–1686
Denys L (2006) Calibration of littoral diatoms to water chemistry in standing fresh waters (Flanders, Lower Belgium): inference models for historical sediment assemblages. J Paleolimnol 35:763–787
Dixit SS, Smol JP, Charles DF, Hughes RM, Paulsen SG, Collins GB (1999) Assessing water quality changes in the lakes of the northeastern United States using sediment diatoms. Can J Fish Aquat Sci 56:131–152
Downing JA, Prairie YT, Cole JJ, Duarte CM, Tranvik LJ, Striegl RG, McDowell WH, Kortelainen P, Caraco NF, Melack JM, Middelburg JJ (2006) The global abundance and size distribution of lakes, ponds, and impoundments. Limnol Oceanogr 51:2388–2397
Egertson JC, Kopaska JA, Downing JA (2004) A century of change in macrophyte abundance and composition in response to agricultural eutrophication. Hydrobiologia 524:145–156
Glew JR (1989) A new trigger mechanism for sediment samplers. J Paleolimnol 2:241–243
Jeppesen E, Søndergaard M, Søndergaard M, Christoffersen K (eds) (1998) The structuring role of submerged macrophytes in lakes. Ecological studies, Vol. 131. Springer, New York, 423 pp
Larsen DP, Stevens DL, Selle AR, Paulsen SG (1991) Environmental monitoring and assessment program, EMAP-Surface Waters: a northeast lakes pilot. Lake Reservoir Manage 7:1–11
McGowan S, Leavitt PR, Hall RI, Anderson NJ, Jeppesen E, Odgaard BV (2005) Controls of algal abundance and community composition during ecosystem state change. Ecology 86:2200–2211
Moss B (1978) The ecological history of a mediaeval man-made lake. Hickling Broad, Norfolk, United Kingdom. Hydrobiologia 60:23–32
Odgaard BV, Rasmussen P (2001) The occurrence of egg-cocoons of the leech Piscicola geometra (L.) in recent lake sediments and their relationship with remains of submerged macrophytes. Arch Hydrobiol 152:671–686
OECD (1982) Eutrophication of waters. Monitoring, assessment and control. OECD, Paris, 154 pp
Oertli B, Joye DA, Castella E, Juge R, Cambin D, Lachavanne J-B (2002) Does size matter? The relationship between pond area and biodiversity. Biol Conserv 104:59–70
Ogden RW (2000) Modern and historical variation in aquatic macrophyte cover of billabongs associated with catchment development. Regul Rivers: Res Manage 16:497–512
Osborne PE, Tigar BJ (1992) Interpreting bird atlas data using logistic models: an example from Lesotho, Southern Africa. J Appl Ecol 29:55–62
RAPPEL (2004) Un portrait alarmant de l’état des lacs et des limitations d’usages reliées aux plantes aquatiques et aux sediments Bilan (1996–2003). 366 pp
Rasmussen P, Anderson NJ (2005) Natural and anthropogenic forcing of aquatic macrophyte development in a shallow Danish lake during the last 7000 years. J Biogeogr 32:1993–2005
Reavie ED, Smol JP (1997) Diatom-based model to infer past littoral habitat characteristics in the St. Lawrence River. J Great Lakes Res 23:339–348
Reavie ED, Smol JP, Carigan R, Lorrain S (1998) Diatom paleolimnology of two fluvial lakes in the St. Lawrence River: a reconstruction of environmental changes during the last century. J Phycol 34:446–456
Sand-Jensen K, Riis T, Vestergaard O, Larsen SE (2000) Macrophyte decline in Danish lakes and streams over the past 100 years. J Ecol 88:1030–1040
Sayer C, Roberts N, Sadler J, David C, Wade PM (1999) Biodiversity changes in a shallow lake ecosystem: a multi-proxy palaeolimnological analysis. J Biogeogr 26:97–114
Scheffer M (1989) Alternative stable states in eutrophic, shallow freshwater systems: a minimal model. Hydrobiol Bull 23:73–83
Scheffer M (1998) Ecology of shallow lakes. Chapman & Hall, London, 357 pp
Scheffer M, Hosper SH, Meijer M-L, Moss B, Jeppesen E (1993) Alternative equilibria in shallow lakes. Trends Ecol Evol 8:275–279
Scheffer M, van Geest GJ, Zimmer K, Jeppesen E, Søndergaard M, Butler MG, Hanson MA, Declerck S, De Meester L (2006) Small habitat size and isolation can promote species richness: second-order effects on biodiversity in shallow lakes and ponds. Oikos 112:227–231
Smol JP (2002) Pollution of lakes and rivers: a paleoenvironmental perspective. Arnold Publisher, London, UK. Co-published by Oxford University Press, New York, NY
Tan OC, Özesmi U (2006) A generic shallow lake ecosystem model based on collective expert knowledge. Hydrobiologia 563:125–142
ter Braak CJF, Šmilauer P (2002) CANOCO Reference manual and CanoDraw for Windows user’s guide: software for canonical community ordination (version 4.5). Microcomputer Power, Ithaca, NY, USA, 500 pp
Väliranta MM (2006) Long-term changes in aquatic plant species composition in North-eastern European Russia and Finnish Lapland, as evidenced by plant macrofossil analysis. Aquat Bot 85:224–232
van Dam H, Mertens A (1993) Diatoms on herbarium macrophytes as indicators for water quality. Hydrobiologia 269/270:437–445
Waisanen PJ, Bliss NB (2002) Changes in population and agricultural land in conterminous United States counties, 1790 to 1997. Global Biogeochem Cycles 16:1137
Wetzel RG (2001) Limnology: lake and river ecosystems. 3rd ed. Academic Press, San Diego, USA
Zhao Y, Sayer CD, Birks HH, Hughes M, Peglar SM (2006) Spatial representation of aquatic vegetation by macrofossils and pollen in a small and shallow lake. J Paleolimnol 35:335–350
Acknowledgements
We would like to thank Drs. Sushil Dixit and John Stoddard for answering our questions about the EMAP-SW dataset and Drs. Yves Prairie and Euan Reavie for stimulating discussions. We would also like to acknowledge Dr. Carl Sayer and an anonymous reviewer for providing comments that improved an original version of this manuscript. This project was funded through grants from the Natural Sciences and Engineering Research Council, le Fonds Quebecois de Recherche sur la Nature et les Technologies and McGill University awarded to I. Gregory-Eaves and a Vineberg graduate scholarship awarded to J. Vermaire. This study is a contribution to the Groupe de Recherche Interuniversitaire en Limnologie. Although some data described in this article have been funded wholly or in part by the U.S. Environmental Protection Agency through its EMAP Surface Waters Program, it has not been subjected to Agency review, and therefore does not necessarily reflect the views of the Agency and no official endorsement of the conclusions should be inferred.
Author information
Authors and Affiliations
Corresponding author
Appendix 1
Appendix 1
Common diatom taxa and their maximum and mean relative abundance (%) along with number of occurrences in lakes with extensive (Ext, >40% cover) and sparse (Spar, <10% cover) macrophyte cover. Correspondence analysis axis 2 species scores (CA axis 2) and the effective number of occurrences of each taxa for all sites (N2) are also shown
# | Taxon name | Maximum occurrences | Mean occurrence | Number of occurrences | CA axis 2 | N2 | |||
|---|---|---|---|---|---|---|---|---|---|
Ext | Spar | Ext | Spar | Ext | Spar | ||||
1 | Achnanthes austriaca var. helvetica | 0.6 | 2.9 | 0.1 | 0.1 | 9 | 9 | −0.9 | 8.6 |
2 | Achnanthes bicapitata | 0.6 | 1.8 | 0.0 | 0.1 | 6 | 19 | −1.0 | 12.8 |
3 | Achnanthes detha | 6.3 | 4.9 | 0.7 | 0.7 | 33 | 72 | −0.6 | 49.8 |
4 | Achnanthes didyma | 0.4 | 1.2 | 0.0 | 0.1 | 5 | 22 | −1.8 | 15.5 |
5 | Achnanthes exigua | 6.3 | 1.6 | 0.3 | 0.1 | 14 | 14 | 2.0 | 13.9 |
6 | Achnanthes flexella | 0.5 | 2.1 | 0.0 | 0.1 | 7 | 21 | 0.3 | 14.1 |
7 | Achnanthes helvetica | 1.6 | 2.6 | 0.2 | 0.2 | 18 | 42 | −0.5 | 32.0 |
8 | Achnanthes lanceolata | 17.2 | 7.8 | 0.6 | 0.2 | 23 | 20 | 1.5 | 17.7 |
9 | Achnanthes lanceolata var. rostrata | 7.5 | 1.2 | 0.2 | 0.1 | 10 | 11 | 2.1 | 7.0 |
10 | Achnanthes levanderi | 1.0 | 1.4 | 0.0 | 0.1 | 3 | 11 | −2.4 | 6.3 |
11 | Achnanthes linearis | 3.8 | 4.5 | 0.6 | 0.3 | 30 | 41 | 0.2 | 38.5 |
12 | Achnanthes marginulata | 1.7 | 2.7 | 0.2 | 0.2 | 18 | 45 | −0.7 | 33.9 |
13 | Achnanthes microcephala | 2.6 | 1.2 | 0.1 | 0.0 | 5 | 7 | 0.8 | 5.7 |
14 | Achnanthes minutissima | 56.0 | 44.7 | 11.3 | 5.7 | 43 | 87 | 0.4 | 62.7 |
15 | Achnanthes suchlandtii | 1.8 | 1.5 | 0.1 | 0.1 | 7 | 22 | −1.1 | 18.7 |
16 | Actinella punctata | 2.1 | 3.7 | 0.2 | 0.1 | 9 | 7 | 1.0 | 9.2 |
17 | Amphipleura pellucida | 1.2 | 0.4 | 0.1 | 0.0 | 12 | 8 | 1.9 | 15.4 |
18 | Amphora ovalis | 15.2 | 3.0 | 0.7 | 0.2 | 27 | 31 | 1.9 | 21.8 |
19 | Amphora perpusilla | 6.8 | 5.2 | 0.3 | 0.1 | 11 | 8 | 2.5 | 8.8 |
20 | Anomoeoneis serians | 1.9 | 0.7 | 0.1 | 0.0 | 6 | 7 | 0.6 | 7.4 |
21 | Anomoeoneis serians var. brachysira | 6.1 | 12.6 | 0.6 | 0.5 | 21 | 40 | 0.1 | 27.4 |
22 | Anomoeoneis vitrea | 11.2 | 16.9 | 1.9 | 1.3 | 34 | 69 | 0.3 | 45.1 |
23 | Asterionella formosa | 50.4 | 55.7 | 1.9 | 6.7 | 15 | 75 | −1.3 | 41.5 |
24 | Asterionella ralfsii var. americana >45 μm | 25.9 | 67.3 | 1.0 | 2.6 | 11 | 40 | −1.0 | 15.5 |
25 | Aulacoseira ambigua | 33.1 | 44.3 | 3.3 | 5.1 | 34 | 74 | −0.7 | 54.0 |
26 | Aulacoseira crassipunctata | 24.0 | 15.6 | 1.1 | 0.2 | 5 | 1 | 1.6 | 2.5 |
27 | Aulacoseira distans | 21.4 | 10.3 | 1.4 | 0.8 | 20 | 46 | −0.7 | 30.4 |
28 | Aulacoseira distans var. humilis | 3.4 | 3.3 | 0.1 | 0.1 | 5 | 8 | −0.5 | 7.2 |
29 | Aulacoseira distans var. nivalis | 1.5 | 2.6 | 0.1 | 0.1 | 3 | 6 | −2.0 | 5.2 |
30 | Aulacoseira distans var. nivaloides | 6.9 | 16.4 | 0.6 | 0.5 | 16 | 31 | −1.1 | 18.9 |
31 | Aulacoseira distans var. tenella | 10.3 | 30.8 | 1.1 | 3.1 | 19 | 59 | −1.5 | 32.0 |
32 | Aulacoseira granulata | 1.8 | 1.4 | 0.1 | 0.1 | 5 | 8 | −0.6 | 10.1 |
33 | Aulacoseira italica subsp. subarctica | 16.4 | 13.4 | 0.4 | 0.6 | 4 | 31 | −2.2 | 15.5 |
34 | Aulacoseira italica subsp. subarctica f. tenussima | 0.6 | 9.5 | 0.0 | 0.3 | 1 | 6 | −2.0 | 4.7 |
35 | Aulacoseira italica var. valida | 2.3 | 0.4 | 0.1 | 0.0 | 4 | 7 | 0.6 | 5.4 |
36 | Aulacoseira lirata | 16.3 | 17.6 | 1.1 | 1.4 | 21 | 54 | −1.2 | 34.0 |
37 | Aulacoseira lirata var. lacustris | 10.8 | 1.2 | 0.4 | 0.0 | 7 | 4 | 1.0 | 4.6 |
38 | Aulacoseira nygaardii | 7.1 | 9.5 | 0.6 | 0.2 | 18 | 14 | 0.4 | 19.4 |
39 | Aulacoseira perglabra var. floriniae | 3.4 | 3.0 | 0.2 | 0.1 | 11 | 14 | −0.5 | 15.5 |
40 | Caloneis ventricosa | 0.2 | 1.9 | 0.0 | 0.1 | 3 | 14 | −0.3 | 8.8 |
41 | Cocconeis placentula | 19.5 | 9.1 | 2.2 | 0.4 | 31 | 35 | 1.0 | 28.8 |
42 | Cyclotella comta | 9.0 | 24.4 | 0.5 | 3.8 | 17 | 66 | −1.9 | 34.2 |
43 | Cyclotella meneghiniana | 1.2 | 26.7 | 0.1 | 0.6 | 4 | 11 | 0.9 | 4.8 |
44 | Cyclotella michiganiana | 5.2 | 45.4 | 0.5 | 1.1 | 11 | 40 | −0.9 | 23.3 |
45 | Cyclotella ocellata | 20.6 | 17.4 | 0.4 | 0.7 | 2 | 11 | −2.5 | 4.8 |
46 | Cyclotella stelligera | 27.5 | 58.8 | 3.0 | 18.2 | 33 | 84 | −1.3 | 55.6 |
47 | Cymbella amphicephala var. hercynica | 1.7 | 0.4 | 0.1 | 0.0 | 13 | 10 | 0.7 | 13.9 |
48 | Cymbella cesatii | 0.7 | 1.4 | 0.1 | 0.0 | 10 | 10 | 1.6 | 11.5 |
49 | Cymbella cf. aequalis | 2.2 | 3.8 | 0.2 | 0.2 | 13 | 21 | 1.1 | 15.4 |
50 | Cymbella cf. gaeumannii | 1.2 | 1.4 | 0.1 | 0.1 | 8 | 15 | −0.4 | 13.8 |
51 | Cymbella cf. schubartii | 0.4 | 1.2 | 0.0 | 0.0 | 6 | 12 | 0.2 | 10.7 |
52 | Cymbella cistula | 3.4 | 1.8 | 0.1 | 0.0 | 8 | 15 | 1.8 | 12.8 |
53 | Cymbella delicatula | 2.6 | 1.2 | 0.1 | 0.0 | 3 | 4 | 2.7 | 4.0 |
54 | Cymbella descripta | 1.2 | 1.0 | 0.0 | 0.0 | 3 | 9 | 1.2 | 6.9 |
55 | Cymbella hebridica | 5.0 | 2.0 | 0.2 | 0.1 | 14 | 27 | 0.9 | 18.6 |
56 | Cymbella lunata | 2.0 | 1.1 | 0.2 | 0.1 | 19 | 35 | 0.0 | 30.3 |
57 | Cymbella microcephala | 3.7 | 4.3 | 0.4 | 0.2 | 25 | 33 | 1.2 | 27.0 |
58 | Cymbella minuta | 2.0 | 2.2 | 0.3 | 0.2 | 31 | 42 | 0.7 | 43.1 |
59 | Cymbella sp. 1 PIRLA | 2.8 | 2.6 | 0.1 | 0.1 | 7 | 9 | 0.5 | 7.0 |
60 | Diploneis marginestriata | 4.4 | 0.6 | 0.1 | 0.1 | 6 | 21 | −0.9 | 16.1 |
61 | Diploneis ovalis | 1.6 | 0.3 | 0.1 | 0.0 | 6 | 18 | −0.5 | 11.0 |
62 | Epithemia spp. | 0.4 | 0.6 | 0.0 | 0.0 | 6 | 4 | 1.4 | 6.5 |
63 | Eunotia bidentula | 0.8 | 10.8 | 0.1 | 0.2 | 12 | 16 | 0.6 | 10.9 |
64 | Eunotia carolina var. 1 PIRLA | 4.2 | 6.4 | 0.2 | 0.1 | 11 | 16 | 0.4 | 11.5 |
65 | Eunotia curvata | 5.9 | 2.6 | 0.6 | 0.2 | 28 | 33 | 0.4 | 30.5 |
66 | Eunotia exigua | 10.2 | 3.2 | 0.4 | 0.2 | 17 | 29 | 0.4 | 22.0 |
67 | Eunotia fallax | 1.9 | 2.2 | 0.1 | 0.0 | 4 | 6 | −0.1 | 3.7 |
68 | Eunotia flexuosa | 2.1 | 14.8 | 0.4 | 0.2 | 28 | 35 | 0.3 | 25.9 |
69 | Eunotia hemicyclus | 3.0 | 1.9 | 0.2 | 0.0 | 8 | 5 | 1.0 | 7.7 |
70 | Eunotia implicata | 1.6 | 0.2 | 0.1 | 0.0 | 6 | 7 | 0.3 | 5.6 |
71 | Eunotia incisa | 5.6 | 3.4 | 1.1 | 0.4 | 36 | 56 | 0.2 | 49.6 |
72 | Eunotia intermedia | 0.8 | 2.1 | 0.1 | 0.1 | 7 | 12 | −0.2 | 8.9 |
73 | Eunotia lunaris var. attenuata | 6.0 | 1.8 | 0.5 | 0.1 | 24 | 18 | 0.7 | 25.6 |
74 | Eunotia microcephala | 0.6 | 0.4 | 0.0 | 0.0 | 6 | 1 | 0.8 | 3.7 |
75 | Eunotia monodon | 1.5 | 1.4 | 0.2 | 0.1 | 25 | 20 | 0.5 | 25.3 |
76 | Eunotia naegelii | 7.6 | 7.2 | 0.4 | 0.2 | 19 | 16 | 0.6 | 15.9 |
77 | Eunotia pectinalis | 1.6 | 1.9 | 0.1 | 0.1 | 15 | 24 | 0.1 | 20.9 |
78 | Eunotia pectinalis var. minor | 1.6 | 1.9 | 0.2 | 0.1 | 20 | 18 | 0.6 | 23.1 |
79 | Eunotia pectinalis var. ventricosa | 9.2 | 4.8 | 1.2 | 0.3 | 32 | 40 | 0.1 | 32.0 |
80 | Eunotia praerupta | 1.0 | 1.0 | 0.1 | 0.1 | 15 | 18 | 0.0 | 18.9 |
81 | Eunotia rhomboidea | 2.2 | 5.3 | 0.2 | 0.2 | 17 | 31 | 0.2 | 20.9 |
82 | Eunotia serra | 0.6 | 3.4 | 0.0 | 0.1 | 4 | 7 | 0.7 | 5.0 |
83 | Eunotia sp. 2 PIRLA | 1.0 | 0.6 | 0.1 | 0.0 | 6 | 1 | 0.9 | 3.7 |
84 | Eunotia spp. | 0.8 | 2.8 | 0.1 | 0.0 | 7 | 5 | 1.1 | 8.5 |
85 | Eunotia vanheurckii | 2.0 | 1.4 | 0.2 | 0.1 | 17 | 24 | 0.3 | 19.8 |
86 | Eunotia zasuminensis | 6.3 | 3.7 | 0.3 | 0.2 | 7 | 19 | −1.4 | 13.8 |
87 | Fragilaria brevistriata | 21.9 | 5.1 | 1.8 | 0.5 | 35 | 45 | 1.5 | 31.7 |
88 | Fragilaria brevistriata var. capitata | 0.6 | 1.2 | 0.0 | 0.1 | 5 | 18 | −0.6 | 13.7 |
89 | Fragilaria capucina var. mesolepta | 29.0 | 3.6 | 1.1 | 0.1 | 6 | 6 | 2.2 | 5.8 |
90 | Fragilaria cf. oldenburgiana | 1.7 | 0.8 | 0.1 | 0.1 | 9 | 23 | 0.0 | 17.3 |
91 | Fragilaria constricta | 0.7 | 1.6 | 0.1 | 0.1 | 12 | 16 | 0.9 | 15.8 |
92 | Fragilaria construens | 30.9 | 31.3 | 2.0 | 1.0 | 18 | 27 | 1.9 | 15.3 |
93 | Fragilaria construens var. binodis | 4.4 | 1.0 | 0.1 | 0.1 | 9 | 20 | −0.5 | 17.5 |
94 | Fragilaria construens var. venter | 10.7 | 15.6 | 0.3 | 0.2 | 7 | 2 | 4.4 | 4.3 |
95 | Fragilaria crotonensis | 29.7 | 34.3 | 2.2 | 2.8 | 23 | 55 | −0.1 | 30.1 |
96 | Fragilaria hungarica var. tumida | 1.7 | 11.6 | 0.1 | 0.2 | 7 | 9 | 0.7 | 10.8 |
97 | Fragilaria pinnata | 58.7 | 34.7 | 7.1 | 2.3 | 40 | 68 | 0.8 | 46.8 |
98 | Fragilaria pinnata var. acuminata | 13.3 | 6.8 | 0.7 | 0.3 | 24 | 39 | 0.5 | 26.4 |
99 | Fragilaria pinnata var. intercedens | 6.9 | 0.6 | 0.1 | 0.0 | 1 | 3 | 2.6 | 1.9 |
100 | Fragilaria pinnata var. lancettula | 8.1 | 1.8 | 0.3 | 0.1 | 9 | 11 | 1.3 | 8.7 |
101 | Fragilaria sp. 2 PIRLA | 28.1 | 1.1 | 0.7 | 0.0 | 6 | 7 | 3.4 | 3.2 |
102 | Fragilaria vaucheriae | 2.9 | 8.7 | 0.4 | 0.4 | 28 | 46 | 0.1 | 34.5 |
103 | Fragilaria virescens | 1.1 | 3.0 | 0.1 | 0.1 | 12 | 10 | 0.3 | 10.5 |
104 | Fragilaria virescens var. exigua | 5.9 | 11.4 | 0.7 | 0.4 | 26 | 42 | −0.1 | 33.3 |
105 | Frustulia cf. magaliesmontana | 16.3 | 5.3 | 0.6 | 0.2 | 9 | 10 | 0.9 | 7.3 |
106 | Frustulia rhomboides | 4.4 | 1.7 | 0.3 | 0.2 | 21 | 30 | 0.1 | 23.7 |
107 | Frustulia rhomboides var. saxonica | 15.1 | 9.7 | 1.7 | 0.7 | 28 | 51 | 0.2 | 32.1 |
108 | Gomphonema acuminatum | 1.2 | 2.0 | 0.1 | 0.1 | 14 | 27 | 0.2 | 23.8 |
109 | Gomphonema angustatum | 4.4 | 4.7 | 0.6 | 0.3 | 36 | 50 | 0.5 | 47.2 |
110 | Gomphonema gracile | 4.2 | 0.8 | 0.3 | 0.1 | 19 | 22 | 0.9 | 19.6 |
111 | Gomphonema spp. | 2.0 | 0.7 | 0.1 | 0.0 | 5 | 9 | 0.1 | 7.3 |
112 | Gyrosigma acuminatum | 24.9 | 0.4 | 0.6 | 0.0 | 9 | 14 | 1.9 | 5.2 |
113 | Meridion circulare var. constrictum | 1.2 | 2.0 | 0.1 | 0.1 | 10 | 12 | 0.1 | 15.1 |
114 | Navicula arvensis | 2.1 | 3.0 | 0.1 | 0.1 | 10 | 20 | −0.8 | 16.2 |
115 | Navicula bacillum | 8.0 | 1.5 | 0.2 | 0.0 | 8 | 4 | 2.0 | 6.1 |
116 | Navicula bremensis | 0.8 | 1.5 | 0.1 | 0.0 | 10 | 9 | 0.5 | 10.6 |
117 | Navicula capitata | 0.8 | 0.8 | 0.1 | 0.0 | 9 | 7 | 1.7 | 10.1 |
118 | Navicula cf. heimansii | 8.3 | 16.7 | 0.7 | 0.5 | 17 | 24 | 0.5 | 19.1 |
119 | Navicula cryptocephala | 14.0 | 4.2 | 0.7 | 0.1 | 13 | 19 | 1.6 | 14.7 |
120 | Navicula disjuncta | 0.5 | 1.7 | 0.1 | 0.1 | 14 | 21 | 0.4 | 20.9 |
121 | Navicula globosa | 3.4 | 1.5 | 0.1 | 0.0 | 6 | 3 | 3.7 | 5.9 |
122 | Navicula gysingensis | 2.1 | 0.8 | 0.1 | 0.0 | 5 | 12 | −0.6 | 8.3 |
123 | Navicula halophila | 5.6 | 0.8 | 0.1 | 0.0 | 6 | 6 | 2.6 | 7.3 |
124 | Navicula laevissima | 1.4 | 0.8 | 0.0 | 0.0 | 3 | 7 | 0.4 | 7.5 |
125 | Navicula mediocris | 1.8 | 4.0 | 0.1 | 0.2 | 11 | 21 | 0.3 | 12.2 |
126 | Navicula minima | 3.6 | 2.2 | 0.5 | 0.4 | 26 | 46 | −0.4 | 38.8 |
127 | Navicula modica | 10.9 | 5.7 | 0.8 | 0.3 | 25 | 28 | 1.5 | 24.8 |
128 | Navicula mutica | 1.0 | 0.4 | 0.0 | 0.0 | 8 | 3 | 0.6 | 4.9 |
129 | Navicula pupula | 2.4 | 3.6 | 0.6 | 0.5 | 34 | 61 | 0.4 | 54.1 |
130 | Navicula pupula var. rectangularis | 0.6 | 3.4 | 0.1 | 0.1 | 7 | 11 | 1.2 | 8.4 |
131 | Navicula radiosa | 2.6 | 4.2 | 0.2 | 0.1 | 17 | 19 | 1.8 | 19.4 |
132 | Navicula radiosa var. parva | 7.0 | 4.9 | 0.7 | 0.4 | 27 | 52 | 0.9 | 36.5 |
133 | Navicula radiosa var. tenella | 7.5 | 3.0 | 0.5 | 0.1 | 18 | 27 | 1.8 | 22.1 |
134 | Navicula rhynchocephala | 3.8 | 7.2 | 0.3 | 0.2 | 15 | 25 | 0.8 | 19.9 |
135 | Navicula seminuloides | 3.6 | 8.1 | 0.5 | 0.5 | 19 | 39 | 0.2 | 27.5 |
136 | Navicula seminulum | 3.0 | 3.7 | 0.4 | 0.2 | 25 | 34 | 0.6 | 30.8 |
137 | Navicula sp. 2 PIRLA | 0.2 | 0.2 | 0.0 | 0.0 | 2 | 2 | 4.4 | 2.0 |
138 | Navicula sp. 25 PIRLA | 1.1 | 0.9 | 0.0 | 0.0 | 2 | 8 | −1.8 | 6.5 |
139 | Navicula spp. | 7.6 | 7.0 | 1.4 | 0.8 | 27 | 53 | 0.8 | 45.7 |
140 | Navicula submolesta | 3.6 | 1.0 | 0.2 | 0.1 | 11 | 20 | 0.2 | 16.9 |
141 | Navicula subtilissima | 6.0 | 6.2 | 0.5 | 0.3 | 15 | 20 | 0.7 | 15.7 |
142 | Navicula tenuicephala | 2.7 | 2.9 | 0.1 | 0.1 | 3 | 6 | 1.1 | 4.6 |
143 | Navicula trivialis | 2.2 | 1.2 | 0.1 | 0.0 | 4 | 3 | 1.5 | 5.1 |
144 | Navicula vitiosa | 6.0 | 11.4 | 0.7 | 0.8 | 22 | 51 | −0.4 | 33.8 |
145 | Navicula vulpina | 0.2 | 5.2 | 0.0 | 0.1 | 1 | 6 | 1.8 | 4.0 |
146 | Neidium affine | 1.5 | 1.3 | 0.2 | 0.1 | 25 | 26 | 0.8 | 30.7 |
147 | Neidium iridis | 1.8 | 1.5 | 0.2 | 0.1 | 17 | 25 | 0.4 | 25.8 |
148 | Neidium iridis var. amphigomphus | 2.5 | 1.0 | 0.2 | 0.1 | 21 | 25 | 0.4 | 23.3 |
149 | Nitzschia acicularis | 2.2 | 2.3 | 0.1 | 0.0 | 8 | 8 | 1.1 | 10.3 |
150 | Nitzschia amphibia | 1.4 | 2.0 | 0.0 | 0.1 | 3 | 8 | 1.9 | 6.8 |
151 | Nitzschia denticula | 4.2 | 3.0 | 0.2 | 0.1 | 8 | 6 | 2.4 | 8.3 |
152 | Nitzschia dissipata | 5.0 | 2.5 | 0.2 | 0.1 | 16 | 38 | 0.4 | 23.4 |
153 | Nitzschia fonticola | 1.6 | 12.1 | 0.1 | 0.4 | 13 | 30 | 0.9 | 16.9 |
154 | Nitzschia gracilis | 6.2 | 4.4 | 1.0 | 0.5 | 31 | 60 | 0.2 | 45.8 |
155 | Nitzschia palea | 3.6 | 9.2 | 0.2 | 0.3 | 15 | 37 | 0.5 | 26.5 |
156 | Nitzschia perminuta | 0.7 | 1.2 | 0.1 | 0.0 | 6 | 10 | −0.2 | 7.4 |
157 | Nitzschia spp. | 4.0 | 8.9 | 0.5 | 0.3 | 19 | 23 | 1.5 | 21.2 |
158 | Pinnularia abaujensis | 1.1 | 0.8 | 0.1 | 0.1 | 11 | 23 | 0.0 | 18.0 |
159 | Pinnularia abaujensis var. 2 PIRLA | 16.3 | 5.5 | 0.4 | 0.2 | 10 | 17 | 0.8 | 9.2 |
160 | Pinnularia abaujensis var. rostrata | 1.4 | 2.8 | 0.1 | 0.0 | 6 | 8 | 0.8 | 7.2 |
161 | Pinnularia biceps | 5.9 | 5.0 | 0.3 | 0.3 | 19 | 37 | 0.5 | 27.2 |
162 | Pinnularia braunii | 4.4 | 3.6 | 0.1 | 0.1 | 11 | 16 | 0.5 | 12.2 |
163 | Pinnularia hilseana | 0.2 | 1.2 | 0.0 | 0.0 | 2 | 7 | −0.2 | 4.4 |
164 | Pinnularia maior | 0.2 | 1.5 | 0.0 | 0.0 | 3 | 6 | 0.5 | 3.3 |
165 | Pinnularia mesolepta | 0.6 | 4.2 | 0.0 | 0.1 | 7 | 11 | 1.3 | 11.2 |
166 | Pinnularia microstauron | 0.6 | 1.9 | 0.1 | 0.0 | 10 | 11 | 0.3 | 11.9 |
167 | Pinnularia pogoii | 3.0 | 1.3 | 0.2 | 0.0 | 9 | 5 | 0.6 | 6.3 |
168 | Pinnularia sp. 11 PIRLA | 4.1 | 1.9 | 0.1 | 0.0 | 3 | 6 | 1.6 | 3.8 |
169 | Pinnularia subcapitata | 2.3 | 2.3 | 0.1 | 0.1 | 12 | 15 | 0.9 | 12.6 |
170 | Pinnularia viridis | 1.3 | 0.8 | 0.1 | 0.1 | 17 | 21 | 0.4 | 26.3 |
171 | Stauroneis anceps | 0.4 | 0.9 | 0.0 | 0.1 | 11 | 20 | 0.5 | 16.7 |
172 | Stauroneis anceps f. gracilis | 0.6 | 3.1 | 0.1 | 0.1 | 19 | 34 | −0.6 | 34.1 |
173 | Stauroneis nobilis var. baconiana | 0.6 | 4.6 | 0.0 | 0.1 | 7 | 7 | −0.2 | 10.3 |
174 | Stauroneis phoenicenteron | 0.8 | 1.9 | 0.2 | 0.2 | 24 | 43 | 0.2 | 36.7 |
175 | Stenopterobia intermedia | 1.3 | 1.5 | 0.2 | 0.1 | 22 | 32 | −0.2 | 32.6 |
176 | Stephanodiscus hantzschii | 14.7 | 54.4 | 0.4 | 1.2 | 5 | 5 | 0.2 | 4.2 |
177 | Stephanodiscus niagarae | 6.1 | 3.6 | 0.2 | 0.2 | 3 | 11 | −1.2 | 8.9 |
178 | Surirella delicatissima | 3.5 | 2.5 | 0.3 | 0.1 | 16 | 25 | 0.3 | 18.1 |
179 | Surirella linearis | 13.9 | 0.5 | 0.4 | 0.1 | 14 | 23 | 1.0 | 11.8 |
180 | Surirella sp. 2 PIRLA | 0.6 | 8.3 | 0.0 | 0.1 | 3 | 4 | −1.5 | 2.7 |
181 | Synedra acus | 1.3 | 1.3 | 0.1 | 0.0 | 4 | 8 | 0.2 | 6.9 |
182 | Synedra acus var. angustissima | 1.4 | 2.0 | 0.1 | 0.1 | 6 | 12 | 0.1 | 9.6 |
183 | Synedra delicatissima | 8.6 | 6.4 | 0.3 | 0.3 | 11 | 20 | −0.6 | 12.0 |
184 | Synedra famelica | 1.8 | 30.2 | 0.2 | 0.5 | 17 | 33 | −0.5 | 15.3 |
185 | Synedra filiformis var. exilis | 1.4 | 2.4 | 0.1 | 0.1 | 7 | 9 | −1.5 | 7.8 |
186 | Synedra parasitica | 1.0 | 4.4 | 0.1 | 0.1 | 14 | 14 | 1.3 | 14.5 |
187 | Synedra pulchella | 6.8 | 5.0 | 0.2 | 0.1 | 7 | 11 | 1.4 | 8.0 |
188 | Synedra rumpens | 2.4 | 2.6 | 0.1 | 0.1 | 6 | 18 | −0.3 | 15.6 |
189 | Synedra rumpens var. familiaris | 9.7 | 5.2 | 0.5 | 0.3 | 19 | 30 | 0.3 | 26.2 |
190 | Synedra spp. | 3.5 | 3.0 | 0.1 | 0.1 | 2 | 6 | −0.1 | 6.3 |
191 | Synedra subrhombica | 1.6 | 2.6 | 0.1 | 0.1 | 7 | 12 | 0.0 | 9.6 |
192 | Synedra ulna | 2.4 | 5.1 | 0.3 | 0.2 | 27 | 43 | 0.1 | 37.8 |
193 | Tabellaria fenestrata | 2.6 | 2.1 | 0.2 | 0.1 | 16 | 28 | −0.3 | 24.0 |
194 | Tabellaria flocculosa strain III | 11.0 | 5.1 | 0.8 | 0.6 | 26 | 66 | −0.6 | 44.8 |
195 | Tabellaria flocculosa strain IIIp | 19.5 | 42.9 | 1.2 | 7.9 | 27 | 74 | −1.8 | 39.6 |
196 | Tabellaria flocculosa strain IV | 2.9 | 4.3 | 0.7 | 0.4 | 29 | 50 | −0.2 | 41.0 |
197 | Tabellaria flocculosa var. linearis | 6.4 | 1.5 | 0.5 | 0.2 | 29 | 48 | −0.5 | 37.8 |
198 | Tabellaria quadriseptata | 29.8 | 17.0 | 1.7 | 0.3 | 12 | 15 | 1.1 | 10.8 |
Rights and permissions
About this article
Cite this article
Vermaire, J.C., Gregory-Eaves, I. Reconstructing changes in macrophyte cover in lakes across the northeastern United States based on sedimentary diatom assemblages. J Paleolimnol 39, 477–490 (2008). https://doi.org/10.1007/s10933-007-9125-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10933-007-9125-y