Lakeshore and littoral physical habitat structure in a national lakes assessment

Figures & data

Figure 1 NLA lakes sampled in 2007, showing (A) 9 aggregated ecoregions and (B) multivariate classification of sample lake types used to screen least-disturbed lakes (see Table 1). Three major geoclimatic regions were defined as the Eastern Highlands (NAP + SAP), the Coastal Plains and Lowlands (CPL + NPL + SPL + TPL + UMW), and the West (WMT + XER).

Table 1 Multivariate classification of lakes within 3 major ecoregions used in deriving expectations for littoral habitat characteristics in least-disturbed lakes of the NLA. The aggregated Omernik ecoregions are shown in Fig. 1A; multivariate cluster classification of sample lakes is shown in Fig. 1B.

Climatic Region: (Aggregated Omernik Level III ecoregions^1) Variables used in lake classification	Lake Type	Description
Eastern Highlands: (NAP, SAP) shoreline development index, elevation, dissolved calcium, precipitation, latitude and longitude	A	Primarily reservoirs in the SAP. Warm and wet climate, generally buffered by higher calcium concentrations.
	B	Primarily NAP drainage lakes; also other lakes in the SAP. Cool climate, low-moderate precipitation, generally low calcium.
Plains and Lowlands: (CPL, NPL, SPL, TPL, UMW) elevation, maximum depth, dissolved calcium, water temperature, and precipitation	C	Lakes of the eastern plains and Upper Midwest. Somewhat higher precipitation than for western plains lakes. Considerably deeper than other lakes in this region.
	D	Lakes of the southern temperate and eastern coastal plains. Generally shallower, and lower in calcium than other lakes in the Plains and Lowlands, but with particularly warmer, wetter climate.
	E	Generally shallow lakes of the plains and Upper Midwest. Higher calcium concentrations and lower precipitation than for other Plains and Lowland lakes.
West: (WMT, XER) latitude, longitude, precipitation, water temperature and dissolved calcium	F	Low calcium, deep, largely natural lakes of the intermountain west.
	G	Reservoirs and natural lakes of the arid west.

¹NAP = Northern Appalachians, SAP = Southern Appalachians, UMW = Upper Midwest, CPL = Coastal Plains, NPL = Northern Plains, SPL = Southern Plains, TPL = Temperate Plains, WMT = Western Mountains, XER = Xeric West.

Table 2 Number of NLA sample lakes classified by anthropogenic disturbance stress as least-disturbed, intermediate, and most-disturbed, based on region-specific low- and high-disturbance screens. Parentheses show subtotals for the Central Plains and Western US regions formed by combining 2 or more of the 9 NLA aggregated ecoregions.

	SITE CLASS
Aggregated Ecoregion	least-disturbed		intermediate		most-disturbed
Northern Appalachians - NAP		28		77		15
Southern Appalachians - SAP		14		79		28
Upper Midwest - UMW		41		116		5
Coastal Plains - CPL		13		74		15
(Central Plains - CENPL):	(12)		(271)		(69)
Northern Plains - NPL		1		43		21
Southern Plains - SPL		6		105		24
Temperate Plains - TPL		5		123		24
(Western US - WEST):	(41)		(158)		(45)
Western Mountains - WMT		38		108		14
Xeric - XER		3		50		31
Total		149		775		177

Table 3 Assignment of Riparian Vegetation Cover Complexity, Littoral Cover Complexity, and Littoral–Riparian Habitat Complexity index variants by aggregated ecoregion (Fig. 1A) and multivariate lake type (Fig. 1B; Table 1).

Aggregated Omernik Ecoregion	Lake Type	% of region sample lakes	Riparian Vegetation Cover Complexity Index (RVegQ)	Littoral Cover Complexity Index (LitCvrQ)	Littoral–Riparian Habitat Complexity Index (LitRipCvQ)
NAP	B	100	RVegQ_2	LitCvrQ_d	LitRipCvQ_2d
SAP	A	75	RVegQ_2	LitCvrQ_c	LitRipCvQ_2c
	B	25	RVegQ_2	LitCvrQ_d	LitRipCvQ_2d
CPL	C	1	RVegQ_2	LitCvrQ_d	LitRipCvQ_2d
	D	99	RVegQ_2	LitCvrQ_b	LitRipCvQ_2b
UMW	C	68	RVegQ_2	LitCvrQ_d	LitRipCvQ_2d
	E	32	RVegQ_2	LitCvrQ_d	LitRipCvQ_2d
TPL	C	47	RVegQ_7	LitCvrQ_d	LitRipCvQ_7d
	D	2	RVegQ_7	LitCvrQ_b	LitRipCvQ_7b
	E	51	RVegQ_7	LitCvrQ_d	LitRipCvQ_7d
NPL	C	2	RVegQ_7	LitCvrQ_d	LitRipCvQ_7d
	E	98	RVegQ_7	LitCvrQ_d	LitRipCvQ_7d
SPL	C	28	RVegQ_7	LitCvrQ_d	LitRipCvQ_7d
	D	8	RVegQ_7	LitCvrQ_b	LitRipCvQ_7b
	E	64	RVegQ_7	LitCvrQ_d	LitRipCvQ_7d
WMT	F	76	RVegQ_8	LitCvrQ_d	LitRipCvQ_8d
	G	24	RVegQ_8	LitCvrQ_d	LitRipCvQ_8d
XER	F	23	RVegQ_8	LitCvrQ_d	LitRipCvQ_8d
	G	77	RVegQ_8	LitCvrQ_d	LitRipCvQ_8d

Table 4 Multiple linear regression models used for calculating expectations for indices of Riparian Vegetation Cover Complexity, Littoral Cover Complexity, and Littoral–Riparian Habitat Complexity for lakes in the Western Mountain and Xeric aggregated ecoregions. Highly disturbed lakes were excluded from calculations.

Index	Predictors	Regression Coefficients	R^2	df: model/error	RMSE	Prob > F
Riparian Vegetation Cover Complexity:
Log10(RVegQ_8)	Intercept	−1.2108
	Lake elevation (m)	−0.000037
	Latitude	0.0126
	Ecoregion category (= 1 if WMT)	0.1112	0.236	3/122^1	0.172	<0.0001
Littoral Cover Complexity:
Log10(LitCvrQ_d)	Intercept	−0.9738
	Lake elevation (m)	−0.000073	0.050	1/140^2	0.314	0.0075
Littoral–Riparian Habitat Complexity:
Log10(LitRipCvQ_8d)	Intercept	−1.0751
	Lake elevation (m)	−0.000038
	Latitude	0.0083
	Interaction of lake elevation and ecoregion; where Ecoregion = 1 if XER	0.000079	0.193	3/129^3	0.187	<0.0001

¹Excludes the most-disturbed lakes, lakes with water level change >10 m (horizontal), and 16 low Log₁₀(RVegQ_8) outliers (>3 SD from mean of residuals).²Excludes the most-disturbed lakes and those with water level change >10 m.³Excludes the most-disturbed lakes, lakes with water level change >10 m, and 9 low Log₁₀(LitRipCvQ_8d) outliers (>3 SD from mean of residuals).

Table 5 Mean and standard deviation of habitat index values in regional sets of least-disturbed reference lakes in the aggregated ecoregions of the NLA. Geometric mean and standard deviation are antilogs of mean and SD of log₁₀-transformed index values (LogMean and LogSD). Parentheses enclose the minimum values (i.e., the most precise models for each index). Bold text marks the least precise models. SDs calculated from log-transformed variables are expressions of the proportional variance of these distributions and so are directly comparable among regions with different geometric means. A range of ±1SD is calculated by multiplying and dividing the geomMean by the geomSD. For example, the LogMean ± 1LogSD for the Riparian Vegetation Cover Complexity Index in least-disturbed lakes of the NAP (−0.571 ± 0.128) translates to a range of habitat index values from 0.200 to 0.359: the geometric mean habitat index value of 0.268 multiplied and divided by 1.34, the antilog of 0.128. The multiple 1.34 in this case is equivalent to a CV of 134%.

Aggregated ecoregion	Index	Ref LogMean	Ref LogSD	Ref geomMean	Ref geomSD
Riparian Vegetation Cover Complexity:
NAPNULL Model	RVegQ	−0.571	(0.128)	0.268	(1.34)
SAPNULL Model	RVegQ	−0.629	0.158	0.235	1.44
UMWNULL Model	RVegQ	−0.598	0.139	0.252	1.38
CPLNULL Model	RVegQ	−0.538	0.169	0.290	1.48
CENPLNULL Model	RVegQ	−0.755	0.158	0.176	1.44
West NULL Model	RVegQ	−0.589	0.198	0.258	1.58
WestMLR Model*	RVegQ_OE	0.0603	0.183	1.149	1.52
Littoral Cover Complexity:
NAPNULL Model	LitCvrQ	−0.834	(0.199)	0.147	(1.58)
SAPNULL Model	LitCvrQ	−0.719	0.285	0.191	1.93
UMWNULL Model	LitCvrQ	−0.773	0.231	0.169	1.70
CPLNULL Model	LitCvrQ	−0.524	0.200	0.299	1.58
CENPLNULL Model	LitCvrQ	−0.943	0.338	0.114	2.18
West NULL Model	LitCvrQ	−1.118	0.345	0.076	2.21
WestMLR Model**	LitCvrQ_OE	0.0031	0.344	1.007	2.20
Littoral–Riparian Habitat Complexity:
NAPNULL Model	LitRipCvQ	−0.669	(0.106)	0.214	(1.28)
SAPNULL Model	LitRipCvQ	−0.637	0.117	0.236	1.31
UMWNULL Model	LitRipCvQ	−0.657	0.120	0.220	1.32
CPLNULL Model	LitRipCvQ	−0.515	0.140	0.305	1.38
CENPLNULL Model	LitRipCvQ	−0.815	0.177	0.153	1.50
West NULL Model	LitRipCvQ	−0.756	0.190	0.175	1.55
WestMLR Model***	LitRipCvQ_OE	0.0531	0.176	1.130	1.50

*Lake-specific f(Elevation, Latitude, Ecoregion) see Table 4.**Lake-specific f(Elevation) see Table 4.***Lake-specific f(Elevation, Latitude, and interaction of Ecoregion × Elevation) see Table 4.

Table 6 Condition criteria for habitat index values and scaled habitat index values based on the distribution of index values in least-disturbed lakes within each region. The 5th and 25th percentiles, respectively, were set as the upper bounds for poor and fair condition, respectively. These percentiles were estimated, respectively, as the mean of log-transformed index values minus 1.65 and 0.67 times the SD of log-transformed habitat index values (see Table 5 for the least-disturbed means and SDs, and see Table 3 for the variant of each index used). All percentiles are expressed as antilogs of log-transformed values. For the null models, percentiles are in the units of the physical habitat indices (the O/E percentiles are not). Scaled percentiles in the last 2 columns are directly comparable between null and O/E models. Parentheses denote null model estimates that were replaced by lake-specific regression O/E model estimates in the West.

Region (model)	Index	Ref 5th Percentile	Ref 25th Percentile	Scaled Ref 5th Percentile	Scaled Ref 25th Percentile
Riparian Vegetation Cover Complexity:
NAP (null)	RVegQ	0.165	0.220	0.616	0.821
SAP (null)	RVegQ	0.129	0.184	0.549	0.784
UMW (null)	RVegQ	0.149	0.204	0.591	0.807
CPL (null)	RVegQ	0.153	0.224	0.527	0.771
CENPL (null)	RVegQ	0.096	0.138	0.549	0.784
West (null)	RVegQ not used	(0.035)	(0.190)	(0.137)	(0.736)
West (MLR)	RVegQ _OE	0.573	0.866	0.499	0.753
Littoral Cover Complexity:
NAP (null)	LitCvrQ	0.069	0.108	0.469	0.735
SAP (null)	LitCvrQ	0.065	0.123	0.339	0.644
UMW (null)	LitCvrQ	0.070	0.118	0.416	0.700
CPL (null)	LitCvrQ	0.140	0.220	0.468	0.735
CENPL (null)	LitCvrQ	0.032	0.068	0.277	0.594
West (null)	LitCvrQ not used	(0.021)	(0.045)	(0.270)	(0.588)
West (MLR)	LitCvrQ _OE	0.271	0.588	0.272	0.592
Littoral–Riparian Habitat Complexity:
NAP (null)	LitRipCvQ	0.143	0.182	0.668	0.849
SAP (null)	LitRipCvQ	0.148	0.193	0.641	0.835
UMW (null)	LitRipCvQ	0.140	0.183	0.634	0.831
CPL (null)	LitRipCvQ	0.179	0.245	0.586	0.805
CENPL (null)	LitRipCvQ	0.078	0.116	0.510	0.761
West (null)	LitRipCvQ not used	(0.085)	(0.131)	(0.486)	(0.746)
West (MLR)	LitRipCvQ _OE	0.578	0.861	0.512	0.762

Figure 2 Comparison of Lakeshore Anthropogenic Disturbance Index (RDis_IX) values in sample lakes across 9 NLA aggregated ecoregions. Unweighted sample statistics are shown; box midline and lower and upper ends show median and 25th and 75th percentile values, respectively; whiskers show maximum and minimum observations within 1.5 times the interquartile range above/below box ends. See Fig. 1 for definitions of aggregated ecoregions.

Figure 3 Comparison of (A) Riparian Vegetation Cover Complexity Index (RVegQ), and (B) scaled values of the same index (log₁₀-transformed) in sample lakes across 9 NLA aggregated ecoregions (RVegQ_scaled = RVegQ divided by its geometric mean in least-disturbed lakes within the same region). Unweighted sample statistics are shown. Box midline and lower and upper ends show median and 25th and 75th percentile values, respectively; whiskers show maximum and minimum observations within 1.5 times the interquartile range above/below box ends; dots show outliers. See Fig. 1 for definitions of aggregated ecoregions.

Figure 4 Comparison of (A) Littoral Cover Complexity Index (LitCvrQ), and (B) scaled values of the same index (log₁₀-transformed) in sample lakes across 9 NLA aggregated ecoregions (LitCvrQ_scaled = LitCvrQ divided by its geometric mean in least-disturbed lakes within the same region). Unweighted sample statistics are shown. Box midline and lower and upper ends show median and 25th and 75th percentile values, respectively; whiskers show maximum and minimum observations within 1.5 times the interquartile range above/below box ends; dots show outliers. See Fig. 1 for definitions of aggregated ecoregions.

Figure 5 Comparison of (A) Littoral–Riparian Habitat Complexity Index (LitRipCvQ), and (B) scaled values of the same index (log₁₀-transformed) in sample lakes across 9 NLA aggregated ecoregions (LitRipCvQ_scaled = LitRipCvQ divided by its geometric mean in least-disturbed lakes within the same region). Unweighted sample statistics are shown. Box midline and lower and upper ends show median and 25^th and 75^th percentile values, respectively; whiskers show maximum and minimum observations within 1.5 times the interquartile range above/below box ends; dots show outliers. See Fig. 1 for definitions of aggregated ecoregions.

Figure 6 Contrasts in physical habitat index values among least-disturbed reference (R), intermediate (M), and highly disturbed (D) lakes in aggregated ecoregions of the US. Unweighted sample statistics are shown; Box midline and lower and upper ends show median and 25th and 75th percentile values, respectively; whiskers show maximum and minimum observations within 1.5 times the interquartile range above/below box ends; dots show outliers. (A) NAP, SAP, CPL, and UMW ecoregions; (B) NPL, SPL, TPL, WMT, and XER ecoregions. See Fig. 1 for definitions of aggregated ecoregions.

Figure 7 Contrasts in integrated Lakeshore Physical Habitat Quality Index (LkShoreHQ) values among least-disturbed reference (R), intermediate (M), and highly disturbed (D) lakes in aggregated ecoregions of the US. Unweighted sample statistics are shown. Box midline and lower and upper ends show median and 25^th and 75^th percentile values, respectively; whiskers show maximum and minimum observations within 1.5 times the interquartile range above/below box ends; dots show outliers. West = Western US (WMT + XER), CENPL = Central Plains (NPL + SPL + TPL), CPL = Coastal Plains, UMW = Upper Midwest, and EHIGH = Eastern US Highlands (NAP + SAP) ecoregions. See Fig. 1 for definitions of aggregated ecoregions.

Table 7 Population estimates of the percentage of lakes (standard errors in parentheses) in good, fair, or poor condition with respect to NLA indices of near-shore anthropogenic disturbance and habitat cover complexity. Estimates are provided for the conterminous 48 US states for natural lakes, for manmade lakes (reservoirs), and for 9 aggregated Omernik ecoregions (adapted from USEPA 2009). Highest and lowest percentages of the 2 polar condition classes are shown in bold font. Underlined percentages indicate highest disturbance or poorest condition. National and regional lake sample and population numbers are shown on the bottom 2 rows. Only probability sample lakes are included in the sample size for population estimates. Physical habitat field measurements and observations were not made on lakes with surface areas >5000 ha (number of lakes shown in last row) resulting in a percentage of the lake population for which habitat condition was not assessed. “No data” represent lakes that were sampled, but habitat data were not collected or were determined to be invalid after review.

				Aggregated Omernik Ecoregions
Condition	US 48	US	US
Class	States	Natural	Man-Made	NAP	SAP	CPL	UMW	TPL	NPL	SPL	WMT	XER
Lakeshore Anthropogenic Disturbance Index (RDis_IX)
Low	34.8 (2.74)	46.4 (3.69)	18.1 (3.40)	42.2 (7.86)	7.7 (4.35)	16.4 (6.18)	53.9 (5.01)	38.7 (8.29)	0.3 (0.19)	9.3 (5.57)	56.3 (7.89)	9.8 (3.55)
Medium	47.6 (2.70)	41.3 (3.56)	56.9 (3.89)	42.9 (7.72)	66.2 (7.79)	64.6 (7.68)	36.8 (4.75)	41.8 (6.83)	64.4 (10.66)	59.8 (9.58)	31.3 (6.84)	57.1 (6.79)
High	16.9 (1.73)	11.9 (1.84)	24.1 (3.11)	14.5 (3.75)	24.3 (6.99)	18.2 (5.83)	9.0 (2.22)	18.2 (5.10)	35.1 (10.59)	30.3 (8.98)	12.0 (4.57)	32.2 (8.10)
Not assessed	0.4 (0.08)	0.3 (0.12)	0.6 (0.11)	0.3 (0.21)	0.6 (0.24)	0.7 (0.23)	0.2 (0.20)	0.2 (0.14)	0.2 (0.19)	0.6 (0.23)	0.2 (0.12)	1.0 (0.49)
No data	0.26 (0.13)	0.2 (0.16)	0.3 (0.21)	0	1.2 (0.90)	0	0	1.1 (0.76)	0	0	0.2 (0.16)	0
Riparian Vegetation Cover Complexity Index (RVegQ)
Good	45.5 (2.71)	50.4 (3.73)	38.4 3.71)	65.9 (7.34)	41.8 (8.63)	22.2 (5.30)	54.4 (5.39)	56.1 (6.98)	7.1 (4.75)	36.8 (9.22)	47.5 (8.54)	34.0 (8.20)
Fair	17.8 (2.16)	16.4 (2.92)	19.7 (3.20)	8.4 (2.76)	27.6 (8.27)	24.3 (6.60)	20.3 (4.67)	2.7 (0.95)	7.8 (4.08)	22.1 (7.39)	24.2 (7.31)	20.2 (7.98)
Poor	35.9 (2.52)	32.6 (3.33)	40.8 (3.72)	25.3 (7.05)	28.8 (7.85)	52.8 (7.05)	25.0 (4.26)	40.0 (6.70)	84.5 (6.52)	40.5 (9.71)	27.3 (7.20)	44.9 (7.91)
Not assessed	0.4 (0.08)	0.3 (0.12)	0.6 (0.11)	0.3 (0.21)	0.6 (0.25)	0.7 (0.23)	0.2 (0.20)	0.2 (0.14)	0.2 (0.19)	0.6 (0.23)	0.2 (0.12)	1.0 (0.49)
No data	0.3 (0.14)	0.2 (0.16)	0.5 (0.24)	0	1.2 (0.90)	0	0	1.08 (0.76)	0.4 (0.27)	0	0.9 (0.60)	0
Littoral Cover Complexity Index (LitCvrQ)
Good	58.7 (2.67)	61.6 (3.44)	54.6 (4.09)	46.1 (7.64)	62.0 (8.49)	57.0 (7.38)	58.5 (5.17)	61.9 (7.05)	47.4 (8.59)	57.6 (8.59)	76.0 (7.02)	68.5 (7.00)
Fair	20.5 (2.15)	20.8 (2.88)	20.0 (3.26)	29.2 (7.85)	20.2 (7.03)	11.9 (3.88)	26.1 (4.62)	16.0 (5.26)	20.1 (7.26)	20.5 (7.56)	11.9 (4.46)	10.4 (3.02)
Poor	20.1 (2.16)	17.1 (2.45)	24.5 (3.70)	24.3 (7.13)	16.0 (6.06)	30.4 (7.59)	15.1 (3.24)	20.8 (6.40)	31.7 (10.06)	21.4 (7.22)	11.7 (5.95)	20.2 (6.71)
Not assessed	0.4 (0.08)	0.3 (0.12)	0.6 (0.11)	0.3 (0.21)	0.6 (0.24)	0.7 (0.23)	0.2 (0.20)	0.2 (0.14)	0.2 (0.19)	0.6 (0.23)	0.2 (0.12)	1.0 (0.49)
No data	0.3 (0.13)	0.2 (0.16)	0.4 (0.21)	0	1.2 (0.90)	0	0	1.1 (0.76)	0.6 (0.37)	0	0.2 (0.16)	0
Littoral–Riparian Habitat Complexity Index (LitRipCvQ)
Good	46.8 (2.84)	52.3 (3.79)	38.8 3.98)	50.9 (8.03)	43.8 (9.04)	38.1 (7.37)	50.3 (5.62)	60.7 (6.76)	9.6 (5.61)	41.5 (9.48)	55.9 (8.43)	31.5 (7.36)
Fair	20.1 (2.36)	18.7 (3.10)	22.2 (3.54)	17.8 (7.76)	6.2 (1.72)	27.3 (7.11)	24.1 (4.56)	7.4 (2.38)	31.4 (15.56)	39.1 (9.67)	9.7 (3.77)	17.0 (7.46)
Poor	32.4 (2.47)	28.5 (3.08)	37.9 (3.89)	30.9 (7.33)	48.2 (8.73)	33.9 (7.02)	25.3 (4.40)	30.5 (6.33)	57.9 (14.06)	18.8 (6.30)	33.3 (8.14)	50.6 (8.32)
Not assessed	0.6 (0.08)	0.3 (0.12)	0.6 (0.11)	0.3 (0.21)	1.8 (0.26)	0.7 (0.23)	0.2 (0.20)	1.3 (0.14)	0.2 (0.19)	0.6 (0.23)	0.4 (0.12)	1.0 (0.49)
No data	0.4 (0.14)	0.2 (0.16)	0.6 (0.24)	0	1.2 (0.90)	0	0	1.1 (0.76)	1.0 (0.48)	0	0.9 (0.60)	0
Lake Population and Sample Sizes
Population Size	49,546	29,308	20,238	5226	4690	7009	15,562	6327	2660	3148	4122	802
No. lakes sampled	1028	437	591	93	116	104	148	137	67	129	155	84
No. lakes not assessed	44	10	34	2	6	15	1	2	2	8	4	4

[USEPA] US Environmental Protection Agency. 2009. National lakes assessment: A collaborative survey of the nation's lakes. Washington (DC) : US Environmental Protection Agency, Office of Water and Office of Research and Development. . EPA 841-R-09-001.

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