Results and Discussion

We found evidence that restoration efforts have improved Potomac River water quality and were linked to important SAV habitat improvements and lesser proportion of exotic species. Multidimensional species composition and RAD similarity were significantly correlated to environmental and water-quality similarity, with both species-composition and RAD similarities having TN WTP, in situ TN, and TSS as the top three most explanatory variables for change over time (R > 0.57, P < 0.001). Of those, TN WTP is itself an anthropogenic variable, whereas in situ TN and TSS are related to natural and anthropogenic inputs through point and nonpoint sources that ultimately limit light. The multivariate analysis suggests that the species composition and relative abundance and structure (RADs) were influenced by differential responses to these light-limiting factors.

Relationships observed in the multidimensional analysis were corroborated by results from bivariate correlations. Indices of species composition and RAD similarity, native abundance, total abundance, evenness, and Shannon diversity increased over time (r_s = 0.59 to 0.78, P ≤ 0.03), whereas TN WTP, in situ TN, TP, and TSS decreased over time (r_s = −0.69 to −0.79, P ≤ 0.01) (Fig. 2 B–G). Higher values in the index of species composition [multidimensional scaling (MDS) x-ordinate] were significantly correlated to total abundance, the abundances of native and exotic species, the ratio of native to exotic species, Shannon diversity, RAD (MDS x-ordinate), and evenness (r_s ≥ 0.66, P ≤ 0.01) (Fig. 3A). Decreases in TN WTP, in situ TN, TP, and TSS were significantly correlated to increases in total abundance and species-composition index (MDS x-ordinate; r_s = −0.52 to −0.84, P ≤ 0.05) (Fig. 3B) as well as increases in Shannon diversity and RAD index (MDS x-ordinate) (Table S1 and Fig. S2). In 2007, for example, when TSS concentration and nutrient loads were relatively low, there were 11 species, and the first seven ranks ranged across an order of magnitude in abundance (Fig. 2 H and I). Conversely, in 1994, when those loads were higher, nine species were detected with lower evenness, and the first seven ranks spanned nearly four orders of magnitude with a greater dominance of exotics.

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Fig. 3.

Scatter plots of (A) species-composition similarity index (MDS x-ordinates) and total abundance, native and exotic abundance, the ratio of native to exotic abundance, Shannon diversity, RAD similarity index (MDS x-ordinates), and evenness and (B) total abundance and species-composition similarity index (MDS x-ordinates) vs. river discharge and water-quality factors, illustrating the interactions of the plotted variables (n = 14). Lines are only shown as a visual aid, with significant Spearman-rank correlations (P ≤ 0.05) denoted by a solid line, whereas nonsignificant correlations are denoted with a dotted line. Native species are denoted by black triangles, and exotic species are denoted by open triangles.

Secchi depth (21) was negatively correlated to TSS (r_s = −0.54, P = 0.04). Correlations between Secchi depth and SAV community parameters were sensible in sign, but none were significant (Table S1 and Fig. S2) (Fig. 3B). TN WTP was highly correlated to in situ TN (r_s = 0.84, P < 0.001), but in situ TP was not correlated to TP WTP. Total N and TP load at Little Falls was not significantly correlated to in situ TN, in situ TP, or any of the SAV parameters. The ratio of TN WTP to TN load at Little Falls ranges between 0.07 and 0.68, with an average of 0.30. According to that measure of WTP nutrient dominance, TN WTP loading could almost double overall TN loading during some years. TP WTP was unrelated to SAV community parameters in all cases. The ratio of TP WTP to TP load at Little Falls loading ranges between 0.01 and 0.14, with an average of 0.06, which may be related to the perceived lesser influence of TP WTP.

Decreased water-column chlorophyll a was significantly correlated to increased total abundance (r_s = −0.60, P = 0.02) and exotic abundance (r_s = −0.67, P = 0.01; Table S1 and Fig. S2 and Fig. 3B). Other SAV community correlations with chlorophyll a were not significant, which might be related to epiphytic algal growth. In situ nutrients can stimulate the growth of algal epiphytes. Algal and invertebrate epiphytes can cover SAV tissue and limit light in a way that would not be necessarily discerned from water-quality data from the channel, but no epiphyte time-series data were available for the study area.

Many of the studied parameters had significant correlations with time. We, therefore, repeated the bivariate correlation analysis with any significant temporal trends removed from the data and found that, although not all previously significant correlations remained significant, TSS was still similarly correlated to total abundance, species composition, and RADs (r_s ≥ −0.69 to −0.82, P ≤ 0.006) (SI Materials and Methods).

Higher river-discharge years can be associated with cooler temperatures and greater nutrient and TSS loading from nonpoint sources. In 1936, the SAV cover in the study area was potentially decimated by a high discharge of about three times that observed during our study period (22). In our study, river discharge was not correlated to in situ temperature, TN, TP, or TSS. Variations in river discharge were also not correlated to SAV community parameters, and no long-term change in growing-season water temperature was observed. However, low SAV abundances were observed in 1996 and 2003, years with tropical storms and resulting average daily river discharge >400 m³s⁻¹ during the growing season (Fig. 2). Such climate perturbations provide an example of how thresholds in factors other than nutrients can have a clear impact on SAV.

Variation in species composition and RADs are widely believed to be driven by niche-based differences in environmental tolerances or competition for resources (23–25). Correlations between temporal shifts in water quality, species composition, and RADs may be related to differential responses between species to changing conditions. Differences in species-specific responses to TSS, nutrients and other factors in terms of growth rates, photosynthetic efficiencies, depth of colonization in various light conditions, and production and transport of propagules (16, 19, 26, 27) may be explanatory factors in the observed changes in species composition.

This study provides a rare quantification of long-term exotic species dynamics many years after the invasion and establishment of several exotic species. Both stabilizing differences (niche partitioning that leads to coexistence) and fitness differences (one taxon has competitive advantage over another) between exotics and natives may have important roles in this system. According to invasion theory, exotic species should either be lost or exclude resident species if fitness differences dominate over stabilizing differences in the community (28). Although the ratio of native to exotic abundance was not directly correlated to TN WTP, TN, or TSS, species-composition was significantly correlated to the relative dominance of natives. When nitrogen loads decreased, species composition shifted such that natives became more dominant and diversity, evenness, and total SAV abundance increased. The ratio of exotics to natives had similar variation in the upper, middle, and lower reaches of the study area, with a notable exception when the ratio dropped in the upper reach only in 2000. These relationships suggest that native species fitnesses increased relative to exotic species fitnesses when nitrogen and TSS were reduced and that species composition consequently shifted, with native species increasing in abundance.

Competition seems to have played an important, albeit less than dominant, role in SAV community dynamics. Compensatory dynamics were not found here (as measured by negative covariance between species) (24); however, the apparent differential responses to water quality between exotics and natives suggest a role for competition (fitness differences) (Fig. 3). If competitive interaction without substantial negative covariance between species is common, it could explain the ostensible paradox between the apparent rigor of competition theory and its lack of dominance in observations.

Environmental variables like nutrients and TSS have apparent influences on SAV community structure and SAV abundance, but other factors probably contribute to unexplained variation in correlations. For example, negative impacts from river discharge and positive feedbacks from the water-clarifying ecosystem functions of bivalves and SAV have been observed (3, 8, 29). Filter-feeding bivalves and SAV itself can improve water clarity and provide positive feedback for SAV abundances (14), but the limited bivalve biomass time-series data for the study area were not correlated to SAV dynamics (SI Materials and Methods). Both positive and negative feedback mechanisms have been suggested between SAV and waterfowl, with greater waterfowl counts linked to greater SAV abundance in the study area (4). Spatial differences between water-quality sample stations in the main channel and the shores and embayments where SAV often resides probably also explain some variation (30).

Although long time-series data on species-specific SAV community dynamics are unavailable bay-wide, the relationships observed in this study may be representative of SAV habitats throughout the Chesapeake Bay. Because nutrient and environmental conditions across the bay are not uniform, the responses to restoration in terms of SAV cover can be masked in bay-wide analyses (8, 18). Areas like the Potomac River study area, which has had reductions in nutrients and TSS, show signs of SAV recovery (13, 18). However, water quality has recently been declining for other parts of the Chesapeake Bay, possibly explaining why bay-wide SAV abundance has not improved appreciably in the last decade (13, 14, 17, 18). Although the certainty with which nutrients can be asserted as a causal factor varies from study to study, a recent review of 215 studies worldwide found that estuaries with reduced nutrients generally had increases in SAV abundance (5).

Our results suggest that reduced nutrient inputs and improved water clarity result in improvements in SAV habitat abundance with reductions in the proportion of exotic species. Other estuaries globally that have substantially reduced nutrients have also documented increases in SAV cover (5, 31–37). The Chesapeake Bay Program has had a three-tier set of threshold goals for restoring SAV. Tier I is the maximum historical cover of SAV as determined by aerial photography. It has been hypothesized that, with comprehensive restoration, the Tier III goal of SAV extending to nearly all areas shallower than 2-m depth in the Chesapeake Bay could be reached (27). The Tier I threshold of recovery to maximum historical extent is approximately met in the study area with SAV coverage of 37 km² in 2007.

Greater SAV cover would increase SAV ecosystem functionality and habitat availability and likely benefit invertebrates and waterfowl as well as important fisheries. If continued restoration to Tier III is successful, it could approximately double the 2007 SAV coverage in the study area (Fig. 1) and increase coverage severalfold bay-wide. Although nitrogen loading seems to have importance for SAV coverage, other factors such as river discharge and ecological interactions may also have important implications for SAV coverage in the future, which seemed to be the case with discharge in 1996 and 2003.