Forested Vernal Pond Vegetation Monitoring in Cape Cod National Seashore Summary of 2011 Field Work and Comparisons to 1997 and 2006 Data

National Park Service U.S. Department of the Interior

Natural Resource Stewardship and Science Forested Vernal Pond Vegetation Monitoring in Cape Cod National Seashore Summary of 2011 Field Work and Comparisons to 1997 and 2006 Data

Natural Resource Technical Report NPS/CACO/NRTR—2013/786

ON THE COVER Forested vernal pond in Cape Cod National Seashore (photo by Stephen Smith).

Forested Vernal Pond Vegetation Monitoring in Cape Cod National Seashore Summary of 2011 Field Work and Comparisons to 1997 and 2006 Data

Natural Resource Technical Report NPS/CACO/NRTR—2013/786

Stephen M. Smith, Mark Esposito, and Matthew Cox

National Park Service Cape Cod National Seashore Wellfleet, MA 02667

August 2013

U.S. Department of the Interior National Park Service Natural Resource Stewardship and Science Fort Collins, Colorado

The National Park Service, Natural Resource Stewardship and Science office in Fort Collins, Colorado, publishes a range of reports that address natural resource topics. These reports are of interest and applicability to a broad audience in the National Park Service and others in natural resource management, including scientists, conservation and environmental constituencies, and the public.

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Please cite this publication as:

Smith, S. M., M. Esposito, and M. Cox. 2013. Forested vernal pond vegetation monitoring in Cape Cod National Seashore: summary of 2011 field work and comparisons to 1997 and 2006 data. Natural Resource Technical Report NPS/CACO/NRTR—2013/786. National Park Service, Fort Collins, Colorado.

NPS 609/121890, August 2013

Contents Page

Figures...... v

Tables ...... vii

Introduction ...... 1

Methods...... 3

Broad Vegetation Surveys ...... 3

Intensive Subset (IS) Monitoring ...... 3

Environmental Variables in the IS Wetlands ...... 5

Statistical Analysis ...... 5

Results ...... 7

Broad Vegetation Survey - 2011 ...... 7

Comparisons Between the 2006 and 2011 Broad Vegetation Surveys ...... 12

Intensive Subset (IS) Vegetation Survey - 2011 ...... 19

Changes in Species Composition in the Nine IS Wetlands Common to the 2006 and 2011Surveys ...... 23

Changes in Wetland Indicator Status in the Nine IS Wetlands Common to the 2006 and 2011 Surveys ...... 24

Changes in Growth Form in the Nine IS Wetlands Common to the 2006 and 2011 Surveys ...... 25

Changes in Abundance of Individual Species at Individual Sites ...... 30

Changes in Plant Communities in the Three IS Wetlands (Permanent Transects) Common to the 1997, 2006, and 2011 Surveys ...... 31

Environmental Variables ...... 35

Relationships among Wetland Vegetation and Environmental Variables ...... 40

iii

Contents (continued) Page

Discussion ...... 45

Temporal Changes in Vegetation...... 45

Ability to Detect Changes in Vegetation ...... 45

Plant Community Characteristics in 2011 ...... 45

Vegetation and Surface Water pH in 2011 ...... 46

Vegetation and Conductivity ...... 46

Vegetation and Peat Thickness and Soil Organic Matter in 2011 ...... 46

Vegetation and Hydrology in 2011 ...... 47

Environmental Variables in 2011 ...... 47

GIS Variables ...... 48

Conclusions ...... 49

Comments on Monitoring Methodology ...... 49

References ...... 51

Figures

Page

Figure 1. Map of intensively monitored (left) vernal wetland sites and all 107 known wetlands (n=145) (right)...... 4

Figure 2. Diagram showing the orientation of transects in the IS wetlands...... 4

Figure 3. NMDS of wetland sites based on species composition (cover scores) in 2011...... 8

Figure 4. PCA depicting variability in species composition among all 107 known wetlands in 2011...... 8

Figure 5. NMDS of all 107 known wetlands based on summed cover class values of species belonging to OBL, FACW, and FAC wetland indicator categories for 2011...... 9

Figure 6. PCA of species belonging to the OBL, FACW, and FAC wetland indicator categories based on summed cover class values for 2011...... 9

Figure 7. NMDS of all 107 known wetlands based on summed cover class values of species belonging to specific growth form categories in 2011...... 10

Figure 8. PCA of species belonging to specific growth form categories based on summed cover class values of species for 2011...... 11

Figure 9. NMDS of species composition changes in all wetlands between 2006 and 2011...... 16

Figure 10. NMDS of wetland indicator species categories in all 107 known wetlands surveyed in both 2006 and 2011...... 17

Figure 11. NMDS of plant communities in 2006 and 2011 based on growth form...... 18

Figure 12. NMDS of 15 IS wetlands based on species composition (summed cover class values) in 2011...... 19

Figure 13. NMDS of 15 IS wetlands based on wetland indicator categories, 2011...... 20

Figure 14. NMDS of 15 IS wetlands based on growth form, 2011...... 22

Figure 15. NMDS depicting changes between 2006 and 2011 in the nine common IS wetlands based species composition...... 23

Figure 16. NMDS of plant communities of the nine wetlands common to the 2006 and 2011 survey years based on wetland indicator categories...... 24

Figures (continued) Page

Figure 17. NMDS of plant communities in the nine IS wetlands common to the 2006 and 2011 surveys based on growth forms...... 25

Figure 18. NMDS of E2, E8, and E9 species composition in 1997, 2006, and 2011 based on summed cover class data...... 31

Figure 19. Surface water pH in 94 wetlands surveyed in 2011 (dotted line represents mean value; note that 13 wetlands were dry and could not be sampled)...... 35

Figure 20. Surface water conductivity µS in 94 wetlands surveyed in 2011 (dotted line represents mean value; note that 13 wetlands were dry and could not be sampled)...... 35

Figure 21. Peat depth (i.e., thickness) in 98 wetlands surveyed in 2011 (dotted line represents mean value; note that 9 wetlands have no values where peat depth could not be measured due to very deep water)...... 36

Figure 22. Mean soil organic matter (%) in cores collected from the 15 IS wetlands in 2011 (n=3 cores per wetland; error bars are standard errors of means)...... 36

Figure 23. HOBO water levels in eight IS wetlands from June 23 through August 3, 2011...... 39

Figure 24. Subset of 2011 HOBO data to show finer-scale resolution of water level fluctuations in the eight IS wetlands...... 39

Figure 25. Correlations of elevation vs. water level range (HOBO) (left) and conductivity (µS) vs. distance to the coast + elevation*1E04 (right)...... 44

Figure 26. Correlation of abundance of OBL species with distance to the USGS- modeled groundwater table...... 44

Figure 27. P-values of non-parametric Wilcoxen signed rank statistical tests for temporal vegetation change vs. the abundance (summed cover class values) of individual taxa...... 45

Tables

Page

Table 1. Eigenvectors of the PCA on wetland indicator categories for all 107 known wetlands in the 2011 broad vegetation survey...... 10

Table 2. Mean, minimum, and maximum numbers of species per wetland belonging to specific growth form categories...... 10

Table 3. Eigenvectors of the PCA on growth forms for all 107 known wetlands in the 2011 broad vegetation survey...... 11

Table 4. Summed cover class (sumCC) and frequency of occurrence (freq) changes in all 107 known wetlands for which vegetation data were collected in 2006 and 2011 (highlighted rows indicate species exhibiting the most positive or negative change between years)...... 13

Table 5. SIMPER analysis of species composition in all 107 known wetlands surveyed in 2006 and 2011 (AA06=average abundance in 2006, AA11-average abundance scores in 2011, ADiss=average dissimilarity value, Contrib%=percent contribution of taxon to overall dissimilarity between years)...... 16

Table 6. SIMPER analysis of wetland indicator categories in all 107 known wetlands surveyed in both 2006 and 2011 (AA06=average abundance in 2006, AA11-average abundance in 2011, ADiss=average dissimilarity value, Contrib%=percent contribution of taxon to overall dissimilarity between years)...... 17

Table 7. SIMPER analysis of growth form categories in all 107 known wetlands surveyed in both 2006 and 2011 (AA06=average abundance in 2006, AA11- average abundance in 2011, ADiss=average dissimilarity value, Contrib%=percent contribution of taxon to overall dissimilarity between years)...... 18

Table 8. Frequency of wetland vegetation in 2011 in the 15 IS wetlands based on wetland indicator category and growth form...... 21

Table 9. Species richness changes in the nine IS wetlands common to the 2006 and 2011 surveys...... 22

Table 10. SIMPER analysis of species composition changes between 2006 and 2011 in the nine common IS wetlands that were surveyed in these years (AA06=average abundance in 2006, AA11-average abundance in 2011, ADiss=average dissimilarity value, Contrib%=percent contribution of taxon to overall dissimilarity between years)...... 23

vii

Tables (continued) Page

Table 11. SIMPER analysis of changes in the abundance of taxa belonging to specific wetland indicator categories between 2006 and 2011 in the nine common IS wetlands (AA06=average abundance in 2006, AA11-average abundance in 2011, ADiss=average dissimilarity value, Contrib%=percent contribution of taxon to overall dissimilarity between years)...... 24

Table 12. SIMPER analysis of changes in the abundance of taxa belonging to specific growth form categories between 2006 and 2001 in the nine common IS wetlands (AA06=average abundance in 2006, AA11-average abundance in 2011, ADiss=average dissimilarity value, Contrib%=percent contribution of taxon to overall dissimilarity between years)...... 25

Table 13. ANOSIM and SIMPER analysis of species composition in VP41 (2006 vs. 2011) (AA06=average abundance in 2006, AA11-average abundance in 2011, ADiss=average dissimilarity value, Contrib%=percent contribution of taxon to overall dissimilarity between years)...... 26

Table 14. ANOSIM and SIMPER analysis of species composition in VP38 (2006 vs. 2011) (AA06=average abundance in 2006, AA11-average abundance in 2011, ADiss=average dissimilarity value, Contrib%=percent contribution of taxon to overall dissimilarity between years)...... 26

Table 15. ANOSIM and SIMPER analysis of species composition in VP33 (2006 vs. 2011) (AA06=average abundance in 2006, AA11-average abundance in 2011, ADiss=average dissimilarity value, Contrib%=percent contribution of taxon to overall dissimilarity between years)...... 27

Table 16. ANOSIM and SIMPER analysis of species composition in VP3 (2006 vs. 2011) (AA06=average abundance in 2006, AA11-average abundance in 2011, ADiss=average dissimilarity value, Contrib%=percent contribution of taxon to overall dissimilarity between years)...... 27

Table 17. ANOSIM and SIMPER analysis of species composition in VP20 (2006 vs. 2011) (AA06=average abundance in 2006, AA11-average abundance in 2011, ADiss=average dissimilarity value, Contrib%=percent contribution of taxon to overall dissimilarity between years)...... 27

Table 18. ANOSIM and SIMPER analysis of species composition in VP59 (2006 vs. 2011) (AA06=average abundance in 2006, AA11-average abundance in 2011, ADiss=average dissimilarity value, Contrib%=percent contribution of taxon to overall dissimilarity between years)...... 28

viii

Tables (continued) Page

Table 19. ANOSIM and SIMPER analysis of species composition in VP2 (2006 vs. 2011) (AA06=average abundance in 2006, AA11-average abundance in 2011, ADiss=average dissimilarity value, Contrib%=percent contribution of taxon to overall dissimilarity between years)...... 28

Table 20. ANOSIM and SIMPER analysis of species composition in VP73 (2006 vs. 2011) (AA06=average abundance in 2006, AA11-average abundance in 2011, ADiss=average dissimilarity value, Contrib%=percent contribution of taxon to overall dissimilarity between years)...... 28

Table 21. ANOSIM and SIMPER analysis of species composition in VP120 (2006 vs. 2011) (AA06=average abundance in 2006, AA11-average abundance in 2011, ADiss=average dissimilarity value, Contrib%=percent contribution of taxon to overall dissimilarity between years)...... 29

Table 22. Taxa in each of the nine IS wetlands that showed significant change in abundance between 2006 and 2011 (Wilcoxen sign-rank tests, α=0.05) (because each wetland had a different number of plots, summed cover class data were normalized to sum of the rank values/number of plots)...... 30

Table 23. SIMPER analysis of the three original IS wetlands, 2006 vs. 2011. (AA06=average abundance in 2006, AA11-average abundance in 2011, ADiss=average dissimilarity value, Contrib%=percent contribution of taxon to overall dissimilarity between years)...... 31

Table 26. Mean and maximum water level measurements (cm) along the transects in the 15 IS wetlands, August 2011 (E2, E8, and E9 are original names of these wetlands)...... 37

Table 27. HOBO-derived water level variables (in cm) for eight IS wetlands between June 23 and August 3, 2011...... 40

Tables (continued) Page

Table 28. Correlations between abundance of plants belonging to specific wetland indicator categories and surface water pH, conductivity (Cond), and wetland peat thickness (Peat)...... 41

Table 29. Correlations between the abundance of plants belonging to specific growth form categories and surface water pH, conductivity (cond), and wetland peat thickness (peat)...... 41

Table 30. Correlations between surface water pH, conductivity (cond), and wetland peat thickness (peat)...... 41

Table 31. Correlations between abundances of plants belonging to specific wetland indicator categories...... 41

Table 32. Correlations between abundances of plants belonging to specific growth form categories...... 41

Table 33. Number and proportion of species of various growth forms (2011) that are classified as FAC, FACW, and OBL species...... 41

Table 34. Correlations between abundance of plants (summed CC) belonging to specific wetland indicator categories and mean and maximum water depths measured during transect surveys...... 42

Table 35. Correlations between abundance of plants (summed CC) belonging to specific wetland indicator categories and mean percent soil oragnic matter and variables calculated from HOBO water level logger data...... 42

Table 36. Correlations between abundance of plants belonging to specific growth form categories vs. soil organic matter and variables calculated from HOBO water level logger data (WL-SE values are the standard error of the WL-means)...... 42

Table 37. Correlations between abundance of plants belonging to specific growth form categories and mean and maximum water depths measured during transect surveys...... 43

Table 38. Correlations between combinations of all environmental variables for the 15 IS wetlands, 2011...... 43

Introduction

Vegetation of vernal ponds across the glaciated region of Cape Cod National Seashore (CACO) was surveyed in 1997, 2006, and 2011. This report summarizes the most recent data (2011) and contains analyses of temporal changes among years. The monitoring was conducted as a precursor to developing a long-term protocol for tracking the vegetation communities in these systems through time.

For context, general information on CACO forested vernal ponds and the history of monitoring has been excerpted from the previous vernal pond vegetation monitoring report (Smith et al. 2006).

“Description of resource

Scattered across the glacial outwash plain of outer Cape Cod are discrete, variable-sized depressions in the ground surface. These depressions were originally formed by the weight of ice blocks left behind by the retreating glacier almost 18,000 yrs. ago. Sea level rise since that time forced a concurrent rise in the fresh groundwater lens, which floats atop of the denser seawater below. This resulted in the permanent flooding of deep depressions (i.e., lakes or “kettle ponds”) and seasonal flooding of shallow ones. The latter are vernal wetlands, also known as vernal pools or ponds.

While annual variability in flood duration (hydroperiod) can be substantial depending on precipitation and antecedent groundwater elevation, these wetlands generally have standing water from early spring to mid-summer but little to none by the end of August (Colburn 2005). The seasonal flooding and drying cycle of vernal wetlands fosters the development of distinctive assemblages of plants and animals. Herbaceous plants, particularly annuals, respond rapidly to water level. As such, vastly different plant communities can develop from year to year depending upon precipitation and the rate of drawdown (Roman and Barrett 2004). Aside from the floodplains of major river systems such as the Herring River (Wellfleet) and the Pamet River (Truro), vernal wetlands constitute the principal habitat for many freshwater wetland taxa. From a wildlife perspective, vernal wetlands are critical habitat in a number of ways. The State Endangered water-willow stem borer depends upon Decodon verticillatus (water- willow), which is a common species in many vernal wetlands. For a wide variety of insects and amphibians such as wood frogs (Rana sylvatica) and spotted salamanders (Ambystoma maculatum) vernal wetlands provide critical breeding habitat. Along with a lesser number of permanent ponds, they are also an important source of fresh drinking water.

Vernal wetlands on the glacial outwash plain are referred to in this document as “forested vernal wetlands”. This terminology is based on the surrounding landscape of pine woodland or mixed pine-oak forest, something that distinguishes them from dune slack wetlands (also vernal). They are further distinguished from the latter by their geologic origin. Dune slack wetlands occur at the northern tip of Cape Cod, a region that formed by post-glacial erosion and re-deposition of sediments from Atlantic-side beaches. In

addition, dune slack wetlands were not formed by glacial processes. Rather, they were (and still are) created by wind scour in the wake of migrating dunes.”

This report describes the monitoring methods and results, and analysis of change between 1997 and 2011 for three wetlands and between 2006 and 2011 for nine wetlands. There is also analysis of data from six new wetland sites that were added to the monitoring network in 2011.

For the sake of brevity, and to avoid excessive redundancy, some text references the last forested vernal ponds report (Smith 2007, http://www.nps.gov/caco/naturescience/cape-cod-ecosystem- monitoring-program-reports-and-publications.htm) that contains further details on background objectives, development of methodology, and prior findings.

Methods

Broad Vegetation Surveys Wetland vegetation was assessed in 2006 and 2011 at 107 known sites (Figure 1) throughout CACO (note: this not done in 1997) based on visual estimates of cover by species within the entire forested wetland. Each wetland site is designated by “VP” followed by a number. The vegetation surveys were accomplished by thoroughly exploring each site on foot. In many cases, where high ground surrounded a wetland, the field crew viewed the wetland from above. Due to its size and constraints on the field crew’s time, a large vernal wetland known as the Red Maple Swamp could not be surveyed.

All species found within each wetland were recorded and assigned a modified Braun-Blanquet (1932) cover class value (0=0%, 1=<1%, 2=1–<5%, 3=5–<10%, 4=10–<25%, 5=25–<50%, 6=50–<75%. 7=75–100%) indicating its relative abundance (note that abundance throughout this report always refers to cover). Nomenclature is based on the USDA Plants database (USDA, NRCS 2006). The wetlands were surveyed during July and August. Only vegetation belonging to the wetland indicator categories of obligate (OBL), facultative wet (FACW), and facultative (FAC) (USACO 1987) were recorded. All other species were considered “upland” vegetation (i.e., occurs in non-wetland habitats 67–99% of the time).

Intensive Subset (IS) Monitoring A more intensive survey of vegetation was conducted in three wetlands (VP33, VP38, and VP41) in 1997 by Roman and Barrett (2004). In 2006, another six wetlands (VP2, VP3, VP20, VP59, VP73, and VP120) were added to this group, and in 2011, an additional six wetlands (VP12, VP35, VP63, VP81, VP97, and VP139) were added for a total of fifteen intensively monitored sites that are a subset of the 82 known wetlands. The additional sites were added to expand the geographic extent of this more intensive monitoring and elevate the statistical power to detect change. All new sites in 2006 and 2011 were randomly chosen from the known extent of forested vernal wetlands using ARCGIS randomization tools (Figure 1).

For VP33, VP38, and VP41, permanent transect markers were already in place from previous surveys, which were set up in a manner similar to that described below. To establish transects in the other 12 wetlands (six in 2006 and six in 2011), the field crew walked to the perceived “middle” of the wetland. There, a PVC stake was hammered in to serve as the permanent marker for three transect end points. From this interior center point, one crew member would walk with a tape measure along the following pre-determined (randomly chosen) bearings to delineate the three transects (1st transect = 5º from center point, 2nd transect = 160º from center point, 3rd transect = 240º from center point) (Figure 2). The endpoints of transects (demarcated by PVC stakes) were determined by the upslope limits of vegetation belonging to the wetland indicator categories of obligate (OBL), facultative wet (FACW), and facultative (FAC). The 1997 cover data were collected in August using a point-intercept technique. In 2006 and 2011, vegetation cover by species was recorded in August within 1-m2 contiguous plots along the entire transect (defined by meter intervals along the field tape) beginning at the upland boundary of the wetland (as in Smith et al. 2007).

Figure 1. Map of intensively monitored (left) vernal wetland sites and all 107 known wetlands (n=145) (right).

Figure 2. Diagram showing the orientation of transects in the IS wetlands.

Environmental Variables in the IS Wetlands The following environmental variables were characterized in 2011. No data is available from 2006 or earlier for these parameters.

i) Hydrology (IS Wetlands Only) At the time of the 2011 vegetation sampling, water depths along each meter interval of each transect in the 15 IS wetlands were measured using a meter stick. In addition, eight HOBO pressure loggers (the total number of units available), the data from which can be translated into water depths, were deployed in the deepest part of each wetland in VP33, VP41, VP3, VP39, VP59, VP73, VP20, and VP120. The loggers recorded data from June 23 to August 3, 2011. The exception was E9 where it was too deep. From these data, mean, minimum, and maximum water depths were calculated.

ii) Soil Organic Matter, and Soil Bulk Density (IS Wetlands Only) Soil cores (10-cm depth) were extracted from the end points of each transect (n=3) using a 4-cm diameter butyrate coring tube from each IS wetland. Soil organic matter (SOM) was determined by thoroughly drying and homogenizing the sample and then by weight loss after combustion of the organic matter in a subsample using a muffle furnace set to 550ºC for five hours. Bulk density was calculated as the weight of dry soil per unit volume in g/cm3.

iii) Surface Water pH and Conductivity (94 Wetlands where Surface Water was Present) Water samples were collected from the surface of the ponds and tested for pH and conductivity using a portable water quality meter (Oakton Multi-Parameter PCSTestr™35).

iv) Peat Depth (107 Wetlands where Peat Depths were <1.55 m) A 1.55-m long iron probe was taken to the perceived “middle” of each wetland and pushed in until the bottom sand layer was struck. The length of probe was recorded. Note: organic matter offers very little resistence to insertion, whereas it is very difficult to push through inorganic layers (primarily sand).

v) GIS Variables (All 107 Wetlands) Using ARCGIS 9.3, the following variables were calculated from 2009 MASSGIS georectified aerial images, the vernal pond location shapefile (created from GPSed locations of each wetland during surveys), 2010 Army Corps of Engineers LIDAR elevation data, and a USGS groundwater lens topography model (Masterson 2004): a) the shortest distance to the coast; b) wetland surface elevation; and c) depth to groundwater surface. Wetland surface elevations were determined by averaging the LIDAR-derived bare-earth elevations across the entire area of each wetland, as delineated by hand-drawn polygons. To calculate proximity to groundwater, mean wetland elevations were compared to the groundwater model elevations and the difference between the two used in further analyses.

Statistical Analysis For the broad vegetation surveys, differences in the cover of individual species between specific years were evaluated by non-parametric Wilcoxen signed-ranks tests (Statistica ver. 6). Analysis of similarities (ANOSIM) was used to compare whole-site plant community composition between years (Primer ver. 6). Non-metric multidimensional non-metric scaling (NMDS) of cover values was used to illustrate variability in taxonomic composition among sites and years (Clarke 1993). While Principle Components Analysis (PCA) is best suited for analyzing

continuous, linear data, the technique is commonly used to illustrate the contributions of individual variables to patterns of ordinal data. Accordingly, multivariate datasets were subjected to PCA in order to reveal variables contributing most to the spatial patterns in ordinal space.

Vegetation data collected in August 1997, 2006, and 2011 from along permanent transects in the three IS wetlands that are common to these survey years (VP33, 38, and 41) were analyzed to assess temporal change over this time period. Because the 1997 cover data were collected using the point-intercept technique, each percent value was converted to its corresponding cover class rank for comparison with 2006 and 2011 data. Statistical differences between the various datasets were assessed by ANOSIM for whole communities (based on both summed cover values and presence/absence). Wilcoxen signed-rank tests allowed for comparisons in the cover of specific taxa by year (α=0.05). Non-parametric correlation tests (specific) were used to assess relationships among species belonging to specific wetland indicator categories and growth forms and various environmental variables. Environmental data were also analyzed non-parametrically using the Kendall’s rank correlation test, which is the non-parametric equivalent to linear regression.

Results

Broad Vegetation Survey - 2011 Rare and Invasive Species One rare, state-listed species, Sagittaria teres (slender arrowhead; Special Concern), was found at one site in the 2011 survey. Three invasive exotics, Phragmites australis (common reed) (one wetland), Typha angustifolia (narrowleaf cattail) (three wetlands), and Salix cinerea (gray willow) (11 wetlands), were found.

Species Richness The number of wetland plant taxa (those belonging to OBL, FACW, or FAC indicator categories) per site in 2011 ranged between three and 25 with a mean value of 12. Total wetland species (all sites pooled) was 112.

Species Composition There was a fairly wide scatter of wetlands in ordinal space based on species composition in 2011 (Figure 3). A PCA analysis generated eigenvalues that suggest that it was the abundance of Acer rubrum (red maple), Decodon verticilatus (water willow), Chamaedaphne calyculata (leatherleaf), Lyonia ligustrina (maleberry), and Vaccinium corymbosum (highbush blueberry) that accounted for the highest proportion of dissimilarity among sites (Figure 4). In general, however, there were no strong spatial trends in any direction or distinct clusters of sites. This means that the forested vernal ponds throughout CACO are comprised of a wide variety of plant communities, representing many different physiognomies.

Wetland Indicator Status The average number of species per wetland categorized as OBL was five, with minimum and maximum values of 0 and 16, respectively. FACW species averaged three per wetland, with a minimum of 0 and a maximum of 8, and FAC species averaged three per wetland, with a minimum of 0 and a maximum of 6. An NMDS plot of all 107 known wetlands based on summed cover class values of species belonging to OBL, FACW, and FAC wetland indicator categories for 2011 shows a wide scattering of sites with no distinct clusters, which reflects a fairly even distribution of these categories according to their relative proportions (Figure 5). Eigenvector values from the PCA showed that the abundance of OBL species accounted for most of the dissimilarities among wetlands, although the data show a fairly heterogeneous scattering in ordinal space (Figure 6, Table 1).

Growth Forms A summary of mean, minimum, and maximum values for the number of species per wetland belonging to specific growth forms is presented in Table 2. Shrubs included the highest number of species; submerged aquatic vegetation (SAV) had the lowest.

The MDS plot by growth form also shows a broad array of structural characteristics (Figure 7). As indicated by the eigenvector values from PCA (Figure 8, Table 3), shrub abundance contributed most to dissimilarities among wetlands (PC2), while ferns contributed the least.

Resemblance: S17 Bray Curtis similarity 2D Stress: 0.25

98 120 54 121 14 97 72 73 70 107 63 125 146 64 66 59 118963 3 74 123 105 576 1062 9 71 96 81 88 92140127 16 20 68119691366714187 61 137 142 138143139127 42 44 28 53 591 122 803738 39 33 8651 79 47 3534 56 5248 45 2 21 145 50 41 40 58144 7894 36 25 32 19 24 29 130 46 1 49 43 30 31 103 100 26 27 95 131 15 106 102 104

Figure 3. NMDS of wetland sites based on species composition (cover scores) in 2011.

146 5 Acer rubrum 14 63 14212072 1064 6311 21 73 121 14528 25 12 70 86 106 29 140 1399 97 144 125 1598 141 7 137 Viburnum13081 dentatum 5 891222 16SalixRubus96Onoclea cinerea flagellaris131 sensibilis35 19 119NyssaUtricularia68 3 sylvatica gibba ViburnumCarexOsmundaSpiraeaScutellariaLysimachiaBetulaLemnaSpiraeaLycopusJuncusThelypterisBidensScirpus59 54 lurida populifolia minor albaeffususconnatatomentosa nudumvirginicuscyperinuscinnamomea galericulata terrestrispalustris 69 AmelanchierOsmundaBetula papyrifera regalis laevis74 HypericumPhragmitesEupatoriumEuthamiaGaliumLeersiaCarexNajasPontederiaSolidagoEleocharisAcorusProserpinacaPolygonumGaliumChamaecyparisEupatoriumLudwigiaSolanumCalamagrostisSiumPoaCephalanthus sp.scopariapalustris suave 44tinctoriumoryzoidesamericanusboreale rugosa palustrisdulcamaratenuifolia(guadalupensis?) canadensis 123palustrisborealecordata australissphydropiperdubium palustris canadensisoccidentalisthyoides 0 61 71 32 34 27 24 PC2 Eriophorum13667Rynchospora 92 angustifoliumUnk.Carex Grass alba sp PotamogetonSalixCeratophyllumNuphar31 nigra3349 lutea ssp.amplifolius demersum variegata VacciniumVacciniumWoodwardiaKalmia 87corymbosumSmilaxDroseraSaggitaria angustifolia macrocarpon CarexMyricarotundifolia 14391 intermediavirginica latifolia longii gale 107JuncusBraseniaMyricaGlyceriaUtriculariaTriadenumSchoenoplectusPotamogetonRosaTypha4258 palustris 88 pennsylvanicaangustifoliaacuminatuscanadensis canadensisschreberi 100 spvirginicum epihydrus30 pongens Clethra62 138alnifolia66 6 CarexDulichiumSparganiumIlex comosa laevigata arundinaceum Americanum 127 57 79 105NymphaeaPhotinia 46floribunda 104odorata26 Rhododendron viscosum37 36 43102 Sphagnum sp. 45 80 39 53 47 95 Chamaedaphne calyculata38 48 20 Lyonia ligustrina 9441Decodon verticillatus 51 40 -5 56 50 78 103 1 52

-10 -10 -5 0 5 10 PC1 Figure 4. PCA depicting variability in species composition among all 107 known wetlands in 2011.

Resemblance: S17 Bray Curtis similarity 2D Stress: 0.16 98

125 130 131 104107 105 56 54 19 106 5153 102 49 142 72 35 50 103 137 4616 73 96 24 74 121 5715 34 81 94 20 45 71 5979 42 4052293395 14380 120 12214410 11 28 27582 41 6837 89 145 91973 671197 5 25 70 38 136 127 6 8712 69 63 9 61 139 64 63 78 31 32 86140 1 123 4426 141 30 43 138 92 21 14 47 62 66 39

Figure 5. NMDS of all 107 known wetlands based on summed cover class values of species belonging to OBL, FACW, and FAC wetland indicator categories for 2011.

FAC 39 10 62 123 21 OBL 32 6386 6414187139 14 140 13812 6 12730 78 25 5136639269 38 2670 1 11979 67 397 6131 8911 6691 145 20 101441226837 120 4341 25847 28 0 80143 PC2 1557 27 95 2933 40 4642 44 52 1211650 94 5979 45 71 142106 53 81 34 105 51 49 74 131 35 24 88 130 13796 103 73 56 5419 72 107 -10 104 FACW 98 102 125

-20 -20 -10 0 10 20 30 40 PC1 Figure 6. PCA of species belonging to the OBL, FACW, and FAC wetland indicator categories based on summed cover class values for 2011.

Table 1. Eigenvectors of the PCA on wetland indicator categories for all 107 known wetlands in the 2011 broad vegetation survey. PC1 PC2 FAC -0.214 0.645 FACW 0.377 -0.638 OBL 0.901 0.420

Table 2. Mean, minimum, and maximum numbers of species per wetland belonging to specific growth form categories. Species Mean Minimum Maximum Fern 0.9 0.0 4.0 Floating 0.1 0.0 2.0 Forb 1.7 0.0 12.0 Grass 0.4 0.0 3.0 Rush 0.8 0.0 4.0 SAV 0.3 0.0 4.0 Sedge 0.8 0.0 4.0 Shrub 4.5 0.0 9.0 Tree 0.9 0.0 4.0 Vine 0.7 0.0 1.0

Resemblance: S17 Bray Curtis similarity 2D Stress: 0.22 98

88 105

54 130 120 44 72 131106 66 49 73 53 14 6 64 89 5714263 11 35 107 9 125 1213 97 63 42 74 10 34 70 61 92 25 1612215 43 671415 145 71 19 87138127 28 584759 137 46 9113914069 29 2 51 86136119144 80 626821 123 14312737 33 4524 39 30 94 81 26 50 793832 40 78 4131 56 20 52 96 95 127 104 103 102

Figure 7. NMDS of all 107 known wetlands based on summed cover class values of species belonging to specific growth form categories in 2011.

Shrub

95 40 28 10 20 145 25 Forb 102103 79 41 24 29 3238 3127781 30 9410456 96 34 39 12371 12726143 2 GrassRush 52 Floating 375080 81 1959 Fern SAV 6862 4513747583342 0 2111913986 917043 125 73 72 PC2 144136 4651 1406987 74 Vine35 1411381256771516 61 121107 1229297 5463 10613113053 49 10 89 64 Tree44 57105 63 111426688 9 6314 -10 98 120

-20 -10 0 10 20 30 PC1 Figure 8. PCA of species belonging to specific growth form categories based on summed cover class values of species for 2011.

Table 3. Eigenvectors of the PCA on growth forms for all 107 known wetlands in the 2011 broad vegetation survey. Vegetation PC1 PC2 Fern -0.004 0.033 Floating 0.029 0.069 Forb 0.749 0.471 Grass 0.163 0.135 Rush 0.210 0.134 SAV 0.107 0.031 Shrub -0.564 0.815 Tree -0.194 -0.265 Vine -0.011 -0.034

Comparisons Between the 2006 and 2011 Broad Vegetation Surveys Rare and Invasive Species The one rare, state-listed species, Sagittaria teres (slender arrowhead; Special Concern) found in the 2011 survey was also present in 2006 in the same wetland. Exotics found in 2011, Phragmites australis (one wetland), Typha angustifolia (three wetlands), and Salix cinerea (11 wetlands) were also recorded in 2006 in the same wetlands. In contrast, Lythrum salicaria (purple loosestrife) was found in 2006 in VP98, but not in 2011.

Species Richness Species richness increased between 2006 and 2011. In 2006, the number of species per site ranged between three and 22, with an average value of 9. Total species richness (all wetlands) was 89. In 2011, species richness per wetland ranged between three and 25, with a mean value of 12 and a total of 112.

Species Composition As indicated by the cover class values summed over all of the 145 known wetlands in Table 4, there were some notable changes in abundance of particular species between 2006 and 2011. The largest increases in abundance occurred in the following species: Acer rubrum, Decodon verticillatus, Vaccinium corymbosum, Lyonia ligustrina, and Bidens connata (beggartick). The largest decreases were observed in Utricularia spp. (bladderworts), Glyceria canadensis (rattlesnake grass), Cephalanthus occidentalis (buttonbush), Toxicodendron radicans (poison ivy), and Dryopteris cristata (crested woodfern). Frequency values (% of wetlands in which the species was present) were slightly different, but it should be noted that abundance data are greatly simplified in the conversion to presence/absence. The largest increases in frequency occurred in Triadenum virginicum (marsh St. Johnswort), Poa palustris (fowl bluegrass) Lycopus spp. (bugleweed), Sparganium americanum (American bur-reed), and Bidens connata. The largest decreases occurred in Utricularia spp., Osmunda cinnamomea (cinnamon fern), Glyceria canadensis, Dryopteris cristata, and Spiraea tomentosa (steeplebush). However, the vast majority of species changes were minor when the entire species list is considered.

Based on cover class values, an NMDS scatterplot shows substantial variability in spatial locations of individual sites, with some showing minor shifts (e.g., VP30) and some showing larger shifts (e.g., VP88) (Figure 9, see circled sites). ANOSIM indicated that there was a significant difference in plant community composition between 2006 and 2011. Global R=0.056, p=0.1%. SIMPER analysis revealed that it was differences in the average abundance of Acer rubrum (increased), Vaccinium corymbosum (increased), Clethra alnifolia (pepperbush) (decreased), Decodon verticillatus (increased), and Smilax rotundifolia (roundleaf greenbrier) (increased) that contributed most to dissimilarities between years (Table 5).

SumCC SumCC Freq Freq Species 2006 2011 Change Species 2006 2011 Change Utricularia spp. 69 25 -44 Utricularia spp. 22% 8% -15% Glyceria canadensis 38 3 -35 Osmunda cinnamomea 50% 36% -14% Cephalanthus occidentalis 27 0 -27 Glyceria canadensis 14% 2% -12% Toxicodendron radicans 20 0 -20 Dryopteris cristata 9% 0% -9% Dryopteris cristata 15 0 -15 Spiraea tomentosa 18% 12% -7% Osmunda cinnamomea 92 77 -15 Toxicodendron radicans 7% 0% -7% Calamagrostis canadensis 57 43 -14 Carex sp. 7% 1% -6% Solidago rugosa 21 7 -14 Cephalanthus occidentalis 6% 0% -6% Spiraea alba 35 22 -13 Myrica pensylvanica 6% 1% -5% Spiraea tomentosa 44 33 -11 Viburnum dentatum 23% 18% -5% Clethra alnifolia 164 154 -10 Salix sp. 5% 0% -5% Carex sp. 11 2 -9 Fragaria virginiana 4% 0% -4% 13 Myrica pensylvanica 10 2 -8 Carex spp. 16% 12% -4% Salix sp. 7 0 -7 Nyssa sylvatica 16% 12% -4% Potamogeton sp. 5 0 -5 Agrostis hyemalis 3% 0% -3% Agrostis hyemalis 4 0 -4 Amelanchier canadensis 3% 0% -3% Nymphaea odorata 31 27 -4 Nymphaea odorata 12% 9% -3% Nyssa sylvatica 40 36 -4 Solidago rugosa 7% 4% -3% Ceratophyllum demersum 7 4 -3 Spiraea alba 11% 8% -3% Panicum capillare 3 0 -3 Juncus spp. 38% 35% -3% Viburnum dentatum 67 64 -3 Ceratophyllum demersum 3% 1% -2% Cicuta maculata 2 0 -2 Eleocharis spp. 4% 2% -2% Panicum clandestinum 2 0 -2 Phragmites australis 3% 2% -1% Rhus capallinum 2 0 -2 Carex canescens 1% 0% -1% Typha angustifolia 15 13 -2 Carex hormathodes 1% 0% -1% Carex canescens 1 0 -1 Cicuta maculata 1% 0% -1% Carex hormathodes 1 0 -1 Justicia americana 1% 0% -1% Eleocharis spp. 9 5 -4 Lycopus sp 1% 0% -1% Euthamia graminifolia 2 1 -1 Lythrum salicaria 1% 0% -1% Justicia americana 1 0 -1 Panicum capillare 1% 0% -1% Lycopus sp 1 0 -1 Panicum clandestinum 1% 0% -1%

SumCC SumCC Freq Freq Species 2006 2011 Change Species 2006 2011 Change Lythrum salicaria 1 0 -1 Potamogeton sp. 1% 0% -1% Rhynchospora alba 2 1 -1 Typha latifolia 1% 0% -1% Typha latifolia 1 0 -1 Utricularia cornuta 1% 0% -1% Utricularia cornuta 1 0 -1 Calamagrostis canadensis 18% 17% -1% Carex longii 1 1 0 Carex lurida 7% 6% -1% Carex spp. 26 26 0 Osmunda regalis 10% 9% -1% Polygonum hydropiper 8 8 0 Typha angustifolia 4% 3% -1% Carex lurida 10 11 1 Carex longii 1% 1% 0% Eupatorium sp 0 1 1 Euthamia graminifolia 1% 1% 0% Leersia oryzoides 6 7 1 Leersia oryzoides 3% 3% 0% Osmunda regalis 10 11 1 Lyonia ligustrina 41% 41% 0% Sagittaria latifolia 0 1 1 Rhynchospora alba 1% 1% 0% Brasenia schreberi 0 2 2 Salix nigra 1% 1% Carex scoparia 2 4 2 Clethra alnifolia 42% 43% 1% Eriophorum angustifolium 0 2 2 Onoclea sensibilis 10% 11% 1%

14 Hypericum boreale 0 2 2 Vaccinium macrocarpon 7% 8% 1%

Juncus spp. 77 79 2 Brasenia schreberi 0% 1% 1% Pontederia cordata 0 2 2 Eupatorium sp 0% 1% 1% Salix nigra 1 3 2 Myrica gale 0% 1% 1% Drosera intermedia 1 4 3 Najas sp. 0% 1% 1% Hypericum canadensis 0 3 3 Pontederia cordata 0% 1% 1% Myrica gale 0 3 3 Sagittaria latifolia 0% 1% 1% Phragmites australis 3 6 3 Scripus pungens 1% 2% 1% Scripus pungens 2 5 3 Carex scoparia 2% 3% 1% Solanum dulacamara 4 7 3 Rosa palustris 5% 6% 1% Amelanchier spp. 5 9 4 Carex comosa 0% 2% 2% Ludwigia palustre 2 6 4 Eriophorum angustifolium 0% 2% 2% Potamogeton spp. 6 10 4 Hypericum boreale 0% 2% 2% Proserpinaca palustris 0 4 4 Nuphar luteum 2% 4% 2% Rosa palustris 10 14 4 Potamogeton spp. 2% 4% 2% Vaccinium macrocarpon 13 17 4 Solanum dulacamara 2% 4% 2% Scutellaria galericulata 0 5 5 Utricularia gibba 2% 4% 2% Galium spp. 0 6 6 Drosera intermedia 1% 3% 2% Najas sp. 0 6 6 Ludwigia palustre 1% 3% 2%

SumCC SumCC Freq Freq Species 2006 2011 Change Species 2006 2011 Change Onoclea sensibilis 19 25 6 Photinia spp. 10% 12% 2% Utricularia gibba 10 16 6 Vaccinium corymbosum 87% 89% 2% Lysimachia terrestris 4 11 7 Scirpus cyperinus 41% 44% 3% Photinia spp. 19 26 7 Eupatorium dubium 0% 3% 3% Carex comosa 0 8 8 Hypericum canadensis 0% 3% 3% Eupatorium dubium 0 8 8 Lysimachia terrestris 3% 6% 3% Nuphar luteum 2 10 8 Proserpinaca palustris 0% 3% 3% Sium suave 3 11 8 Scutellaria galericulata 0% 3% 3% Amelanchier laevis 0 9 9 Acer rubrum 50% 54% 4% Scirpus cyperinus 85 95 10 Amelanchier spp. 3% 7% 4% Smilax rotundifolia 185 196 11 Sium suave 1% 5% 4% Woodwardia virginica 7 18 11 Galium spp. 0% 5% 5% Dulichium arundinaceum 16 29 13 Polygonum hydropiper 2% 7% 5% Viburnum nudum 25 39 14 Dulichium arundinaceum 8% 13% 5% Thelypteris palustris 27 43 16 Woodwardia virginica 3% 9% 6%

15 Lycopus spp. 2 24 22 Smilax rotundifolia 68% 75% 7%

Triadenum virginicum 22 49 27 Thelypteris palustris 15% 21% 7% Poa palustris 0 29 29 Viburnum nudum 12% 18% 7% Salix cineria 4 33 29 Salix cineria 3% 11% 8% Sparganium americanum 0 36 36 Decodon verticillatus 33% 43% 10% Bidens connata 1 40 39 Triadenum virginicum 17% 27% 11% Lyonia ligustrina 104 144 40 Poa palustris 0% 11% 11% Vaccinium corymbosum 356 397 41 Lycopus spp. 2% 16% 14% Decodon verticillatus 105 159 54 Sparganium americanum 0% 15% 15% Acer rubrum 172 293 121 Bidens connata 1% 19% 18%

Resemblance: S17 Bray Curtis similarity 2D Stress: 0.26 year 104 30 2006 104 103 103 2011 88 30 41 2727 31 31 32 40 24 21 26 95 29 88 78 78 26 1 24 145 14 3957 138213258 33 25 9 62 2 39 4342 4745 40 120 64 2 46434633 35 14 38 944150 44 19 20 28 145 917964 9115 565250 1 34123 1395 9491385 141388061127 42 25 62 10373713987 79127 5874 47 14014112140868680 61 119686712 357 14371 5245 11681191366967122 143 20 34 1301063 7 6 19 28 11 928963763 876137 95 81 6914212216 49 71 142136 51 53 44 35 16 5651 53 59 3 107 107 70 92 74 125 123 66 14489 144 137 65 70 96 72 98 66 8196 73 73 102 59 120 72 49 106 130 131 106 121 102 105 97 121 54 29 131 54 98 105 15 125 97

Figure 9. NMDS of species composition changes in all wetlands between 2006 and 2011.

AA06 AA11 ADiss Contrib% Acer rubrum 1.67 2.84 6.58 9.54 Vaccinium corymbosum 3.46 3.85 4.81 6.97 Clethra alnifolia 1.59 1.5 4.67 6.77 Decodon verticillatus 1.02 1.54 4.11 5.96 Smilax rotundifolia 1.8 1.9 3.9 5.65 Lyonia ligustrina 1.01 1.4 3.85 5.57

Wetland Indicator Species Status The NMDS plot in Figure 10 shows a wide scatter of data points for both survey years and it is difficult to decipher true shifts in plant communities based on indicator status; however, there was a statistical difference according to ANOSIM testing (R=0.028, p=0.006). SIMPER analysis showed that OBL species (increased) accounted for most of the observed dissimilarities in ordinal space, followed by FACW (increased), then FAC (increased) (Table 6).

Resemblance: S17 Bray Curtis similarity 2D Stress: 0.18 year 39 2006 62138 2 39 123 21 2766 5830 2011 11 69138 3078 6231 47 1 14 92141 92 26436678 641186 32 31 127 14 631406364 139 661 127 25 89 38 69 1287 67 44145 28 914194140 136 14138 70 44 689 1191197 67 97 120 332 79 7112347 36837 91 251434146 58 120 33 40 512237 6 80 10227 95 2952 20 20 5 10144122 42 52 4534 1079 65106 808770269474 8159 2440 34 9 139 1557 86121 143 73 21 166332 574346 96 1 10335 98 15 81 1031650 49137 372 96 42 145 3572 74 45 102 12144142 61 49 130 7 5350 71 51 24 95 73 142 89 5329 13654 19 131106 5451 137 104 10597 5656 28107 107 19 104 88 121 131 59 125

105 130 125 88

Figure 10. NMDS of wetland indicator species categories in all 107 known wetlands surveyed in both 2006 and 2011.

AA06 AA11 ADiss Contrib% OBL 10.93 14.35 14.98 43.20 FACW 6.45 6.9 9.95 28.71 FAC 7.46 8.81 9.74 28.09

Growth Form Analysis The NMDS plot for growth form analysis (Figure 11) is very similar to that above for wetland indicator species status. ANOSIM suggested that there was a significant difference in the overall plant communities between 2006 and 20011 (Global R= 0.039, p= 0.1%). SIMPER analysis indicates that shrubs and trees (both increased) accounted for the most dissimilarity (Table 7).

Resemblance: S17 Bray Curtis similarity 2D Stress: 0.22 2006 102 102 2006 20 1 40 271035278 28 137523178 96 2011 145 39 6231 95104 49 7941 138 25 29 24 308139 56 2926 8650 33 45 95 94503832130 123 143 15575167105 71 3 127 1279662 80 34 70 137662 37 98 121 20 47 80 51926821 98 58 5919 646 795611914427 72 58 14343 911393786136 123 72 107 42 53 87 14013669 7 70 4630 67141104121387 145 125 74 614326 51615 73 4728 611413812292 74 142 125 25 71 3 42 16 107121 97 106122 418889 10 73 120 35 6 130 2 8753 121408969 131 24 49 64 6311957 4019 3259 64 94 68 1021142 34 45 131 106 631391414 11 44 54 103 63 9111 9 81 66 5 33 54 1 97 144 35 105 65 88 44 9 120

Figure 11. NMDS of plant communities in 2006 and 2011 based on growth form.

Table 7. SIMPER analysis of growth form categories in all 107 known wetlands surveyed in both 2006 and 2011 (AA06=average abundance in 2006, AA11-average abundance in 2011, ADiss=average dissimilarity value, Contrib%=percent contribution of taxon to overall dissimilarity between years).

AA06 AA11 ADiss Contrib% Shrub 11.53 14.57 12.43 27.31 Tree 2.31 3.74 7.02 15.42 Forb 1.68 3.12 6.34 13.93 Rush 1.61 1.63 4.4 9.66 Fern 1.65 1.69 3.87 8.5 SAV 1.52 0.83 3.64 7.99 Vine 1.99 1.9 3.56 7.83

Intensive Subset (IS) Vegetation Survey - 2011 General Species Composition Because vegetation transects are different lengths within and among wetlands, summed cover score data first had to be divided by number of plots within each wetland to normalize the data. From the standpoint of species composition, the 15 IS wetlands do not show a very distinct pattern of groupings in ordinal space. VP97 is spatially separated from the rest based on its high cover of the shrubs Gaylusaccia baccata (black huckleberry) and Kalmia angustifolia (lamb’s kill) and the presence of Vaccinium macrocarpon (cranberry), which is absent from all other wetlands. Sagittaria teres, found in only one of the IS wetlands, was the only Species of Special Concern documented. No exotic taxa were found in any of the IS wetland transect plots. VP2, VP3, VP12, and VP139 cluster together (indicating high similarity) based on the fact that they all have a high abundance of Acer rubrum (Figure 12).

Standardise Samples by Total Resemblance: S17 Bray Curtis similarity 2D Stress: 0.13

VP20 VP33

VP35 VP38 VP81 VP97 VP41 VP120 VP59 VP3 VP2 VP73 VP139VP12 VP63

Figure 12. NMDS of 15 IS wetlands based on species composition (summed cover class values) in 2011.

MDS plots based on wetland indicator categories (Figure 13) again show the separation of VP97 (due to the abundance of FAC species). VP20 is most distant in the other direction, based on the abundance of OBL taxa at this site (Table 8). When the data are subjected to NMDS according to growth form, VP41 stands out from the rest based on the dominance, and equal proportions, of shrubs and vines, with very few taxa falling into other categories (Figure 14, Table 8). VP97 and VP20 constitute the far ends of the scatter plot in other directions for the same reasons described above.

Resemblance: S17 Bray Curtis similarity 2D Stress: 0.03

VP35

VP33 VP38VP12 VP63 VP41VP139 VP20 VP2

VP59 VP97 VP3 VP120

VP81

VP73

Figure 13. NMDS of 15 IS wetlands based on wetland indicator categories, 2011.

Table 8. Frequency of wetland vegetation in 2011 in the 15 IS wetlands based on wetland indicator category and growth form.

Wetland ID OBL FACW FAC (All) VP41 4.5% 1.5% 3.0% VP38 16.7% 7.6% 3.0% VP33 7.6% 3.0% 6.1% VP3 9.1% 4.5% 4.5% VP20 22.7% 10.6% 3.0% VP59 10.6% 12.1% 3.0% VP2 16.7% 3.0% 4.5% VP73 7.6% 12.1% 3.0% VP120 13.6% 4.5% 4.5% VP12 6.1% 3.0% 6.1% VP35 9.1% 3.0% 3.0% VP63 1.5% 1.5% 6.1% VP81 4.5% 6.1% 4.5% VP97 9.1% 3.0% 4.5% VP139 6.1% 0.0% 4.5%

Wetland ID Fern Forb Grass Rush Sedge SAV Shrub Tree Vine VP41 0.0% 3.0% 0.0% 0.0% 3.0% 0.0% 7.6% 0.0% 7.6% VP38 1.5% 1.5% 0.0% 4.5% 6.1% 0.0% 12.1% 0.0% 12.1% VP33 0.0% 1.5% 3.0% 1.5% 6.1% 1.5% 6.1% 0.0% 7.6% VP3 0.0% 9.1% 1.5% 4.5% 15.2% 1.5% 4.5% 1.5% 7.6% VP20 4.5% 4.5% 1.5% 6.1% 12.1% 1.5% 10.6% 1.5% 13.6% VP59 4.5% 3.0% 3.0% 0.0% 6.1% 1.5% 10.6% 0.0% 12.1% VP2 0.0% 9.1% 1.5% 0.0% 10.6% 0.0% 10.6% 3.0% 13.6% VP73 1.5% 4.5% 0.0% 3.0% 7.6% 1.5% 4.5% 1.5% 7.6% VP120 1.5% 1.5% 1.5% 3.0% 6.1% 0.0% 6.1% 3.0% 9.1% VP12 1.5% 4.5% 0.0% 0.0% 4.5% 0.0% 7.6% 1.5% 9.1% VP35 0.0% 0.0% 1.5% 0.0% 1.5% 0.0% 6.1% 0.0% 6.1% VP63 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 6.1% 3.0% 9.1% VP81 3.0% 1.5% 0.0% 3.0% 4.5% 0.0% 7.6% 0.0% 7.6% VP97 3.0% 0.0% 0.0% 3.0% 3.0% 0.0% 7.6% 0.0% 7.6% VP139 1.5% 0.0% 0.0% 0.0% 0.0% 0.0% 6.1% 1.5% 7.6%

Resemblance: S17 Bray Curtis similarity

2 D S tre ss: 0

VP41

VP33 VP20 VP38 VP59VP2VP12 VP3VP73 VP81 VP139 VP63 VP120

VP35

VP97

Figure 14. NMDS of 15 IS wetlands based on growth form, 2011.

Changes in Species Richness in the Nine Common IS Wetlands Cetween 2006 and 2011 From the standpoint of species richness, very little change occurred between 2006 and 2011, with the exception of VP33 where six additional species were recorded. The rest of the sites had change values between two and negative three (Table 9).

Table 9. Species richness changes in the nine IS wetlands common to the 2006 and 2011 surveys. 2006 2011 Change VP41 6 7 +1 VP38 20 19 -1 VP33 6 12 +6 VP3 14 13 -1 VP20 25 27 +2 VP59 19 19 0 VP2 16 17 +1 VP73 16 16 0 VP120 23 20 -3 means 16 17 +1 SE 2.2 1.9

Changes in Species Composition in the Nine IS Wetlands Common to the 2006 and 2011Surveys Although shifts in the position of individual wetlands in ordinal space are evident in the NMDS plot, these changes were negligible (i.e., no significant difference) with respect to the entire group of wetlands as a whole (ANOSIM Global R= -0.038; p=0.63) (Figure 15). Based on SIMPER analysis, Clethra alnifolia, Acer rubrum, Nymphaea odorata (white waterlily), Decodon verticillatus, and Vaccinium corymbosum, all of which increased, contributed most to dissimilarities between years (Table 10). From the NMDS plot, one can see that VP33 changed the most between 2006 and 2011, while VP73 and VP120 changed the least (specific reasons for changes in individual wetlands are discussed below in the section on “individual wetlands”).

Resemblance: S17 Bray Curtis similarity 2D Stress: 0.19 year VP2 2006 2011

VP120 VP3 VP38 VP3 VP120 VP2 VP41 VP41 VP38

VP73 VP73

VP20 VP20 VP59

VP33 VP59 VP33

Figure 15. NMDS depicting changes between 2006 and 2011 in the nine common IS wetlands based species composition.

AA06 AA11 ADiss Contrib% Clethra alnifolia 66.11 72.11 7.84 10.77 Acer rubrum 46.89 73.44 7.55 10.38 Nymphaea odorata 28.56 64.33 6.00 8.24 Decodon verticillatus 37.78 55.56 5.22 7.17 Vaccinium corymbosum 65.22 100.67 4.61 6.33

Changes in Wetland Indicator Status in the Nine IS Wetlands Common to the 2006 and 2011 Surveys Even though there was large spatial separation between years for certain individual sites (e.g., VP33), ANOSIM revealed that, collectively, there was no significant difference in the cover of species belonging to specific wetland indicator categories between 2006 and 2011 (ANOSIM R= -0.08, p=0.87) (Figure 16). Of the dissimilarities that did exist, OBL species accounted for the most (increased), followed by FAC (increased), and then FACW (decreased) (Table 11).

Resemblance: S17 Bray Curtis similarity 2D Stress: 0.06 year VP59 2006 VP20 2011

VP59 VP73 VP20 VP33 VP73

VP38 VP120 VP38 VP33

VP2

VP3 VP2

VP120 VP3 VP41

VP41

Figure 16. NMDS of plant communities of the nine wetlands common to the 2006 and 2011 survey years based on wetland indicator categories.

AA06 AA11 ADiss Contrib% OBL 364.67 447.33 21.26 55.46 FAC 127.67 160.44 11.51 30.03 FACW 80.00 57.56 5.56 14.50

Changes in Growth Form in the Nine IS Wetlands Common to the 2006 and 2011 Surveys Similar to wetland indicator status, there were no significant differences in the abundances of taxa with specific growth forms between 2006 and 2011 (ANOSIM R= -0.086, p=0.89) (Figure 17). SIMPER analysis indicated that trees and shrubs (increased) accounted for the most dissimilarity (although small overall) among all growth form types (Table 12).

Resemblance: S17 Bray Curtis similarity 2D Stress: 0.15 year VP73 VP38 VP73 2006 2011

VP20 VP38 VP33 VP120 VP20 VP3 VP120

VP2 VP59VP59 VP3 VP2 VP33

VP41 VP41

Figure 17. NMDS of plant communities in the nine IS wetlands common to the 2006 and 2011 surveys based on growth forms.

AA06 AA11 ADiss Contrib% Tree 62.11 79.44 10.96 19.11 Shrub 119.33 155.56 9.7 16.91 Floating 28.56 64.78 7.49 13.07 Rush 54.56 34.33 6.47 11.28 Sedge 54.67 48.22 6.34 11.05 SAV 23.67 44.33 5.77 10.05 Forb 47.67 49.89 5.66 9.86

Individual IS Wetland Sites The following tables (Tables 13–21) summarize ANOSIM and SIMPER analysis results from comparisons of plant communities in individual IS wetlands (the nine wetlands common to the 2006 and 2011 survey years). In contrast to the analysis of change between years of the nine IS wetlands as a group, every individual site changed significantly. The statistical details of these changes are provided below.

VP41

AA06 AA11 AD Contrib% Decodon verticillatus 1.92 3.2 10.7 20.38 Clethra alnifolia 4.33 5.55 9.15 17.43 Smilax rotundifolia 1.39 1.02 6.7 12.76 Vaccinium corymbosum 0.71 1.51 6.44 12.27 Lyonia ligustrina 0.8 0.59 4.24 8.07

VP38

AA06 AA11 ADiss Contrib% Clethra alnifolia 1.9 1.71 13.07 16.53 Decodon verticillatus 1.13 1.75 11.19 14.15 Juncus acuminatus 1.55 0.95 10.42 13.18 Dulichium arundinaceum 0.74 0.66 6.76 8.55 Smilax rotundifolia 0.82 0.71 6.05 7.66

VP 33

AA06 AA11 ADiss Contrib% Nymphaea odorata 1.41 4.74 40.03 47.03 Poa palustris 0 2.73 25.06 29.45 Glyceria canadensis 0.5 0 3.77 4.43 Smilax rotundifolia 0.19 0.3 3.7 4.34 Calamagrostis canadensis 0.36 0.11 3.36 3.95 Vaccinium corymbosum 0.21 0.16 2.41 2.83

VP3

AA06 AA11 ADiss Contrib% Acer rubrum 3.06 4.42 10.39 16.78 Chamaedaphne calyculata 3.69 3.11 9.92 16.02 Clethra alnifolia 1.66 1.68 7.84 12.66 Smilax rotundifolia 1.39 1.6 6.53 10.55 Vaccinium corymbosum 0.9 1.44 6.08 9.82

VP20

AA06 AA11 ADiss Contrib% Nymphaea odorata 1.71 1.42 9.42 11.47 Vaccinium corymbosum 1.87 1.41 9.12 11.1 Dulichium arundinaceum 1.57 1.82 7.69 9.36 Decodon verticillatus 1.14 1.44 7.17 8.74 Ilex verticillata 0.59 1.43 6.82 8.31

VP59

AA06 AA11 ADiss Contrib% Vaccinium corymbosum 1.08 4.67 15.73 20.76 Smilax rotundifolia 2.88 2.06 6.65 8.78 Lyonia ligustrina 1.60 0 5.92 7.81 Calamagrostis canadensis 1.33 0.27 5.1 6.74 Ilex glabra 0.79 0.67 4.75 6.27

VP2

AA06 AA11 ADiss Contrib% Acer rubrum 3.39 5.08 10 14.54 Rhododendron viscosum 2.72 1.78 8.09 11.76 Vaccinium corymbosum 1.69 2.17 7.45 10.83 Smilax rotundifolia 1.33 1.78 5.89 8.56 Kalmia angustifolia 0 1.17 3.52 5.12

VP73

AA06 AA11 ADiss Contrib% Utricularia sp 3.44 3.05 13.33 18.15 Vaccinium corymbosum 1.67 1.64 9.36 12.75 Spiraea alba 1.23 1.72 7.17 9.77 Scirpus cyperinus 1.82 0.9 7.05 9.6

VP120

AA06 AA11 ADiss Contrib% Acer rubrum 1.67 3.14 11.18 15.88 Carex lurida 2.46 1.23 8.25 11.72 Rubus flagellaris 2.16 1.56 6.4 9.1 Vaccinium corymbosum 0.88 1.7 6.14 8.72 Juncus effusus 1.49 0.74 5.72 8.13

Changes in Abundance of Individual Species at Individual Sites Many species showed statistically significant changes in abundance in each of the IS wetlands common to the 2006 and 2011 vegetation surveys. Table 22 lists the specific taxa that exhibited such changes.

VP41 Clethra alnifolia VP20 Amelanchier laevis VP73 Bidens connata Decodon verticillatus Chamaedaphne calyculata Kalmia angustifolia Dulichium arundinaceum Scirpus cyperinus VP38 Cephalanthus occidentalis Ilex verticillata Decodon verticillatus Juncus canadensis VP120 Acer rubrum Juncus spp Juncus effusus Calamagrostis canadensis Nymphaea odorata Potamogeton epihydrus Carex spp. Phontinia floribunda Spiraea tomentosa Dryopteris cristata Toxicodendron radicans Gaultheria procumbens VP33 Glyceria canadensis Viburnum nudum Juncus effusus Nymphaea odorata Pinus rigida Potamogeton epihydrus VP59 Bidens connata Rubus flagellaris Poa palustris Gaylussacia baccata Smilax rotundifolia Smilax rotundifolia Ilex glabra Thelypteris palustris Vaccinium corymbosum Ilex verticillata Tridenum virginicum Kalmia angustifolia Vaccinium corymbosum VP3 Acer rubrum Leersia oryzoides Calamagrostis canadensis Lyonia ligustrina Chamaedaphne calyculata Smilax rotundifolia Clethra alnifolia Vaccinium corymbosum Juncus acuminatus Lysimachia terrestris VP2 Bidens connata Scirpus cyperinus Cicuta maculata Spiraea tomentosa Glyceria canadensis Tridenum virginicum Ilex glabra Utricularia sp Kalmia angustifolia Vaccinium corymbosum Rhododendron viscosum

Changes in Plant Communities in the Three IS Wetlands (Permanent Transects) Common to the 1997, 2006, and 2011 Surveys Despite the fact that large changes in the abundance of specific taxa were evident, no overall significant differences among years were detected in the three wetlands as a single group (i.e., collectively) (ANOSIM; Global R= -0.235, p=0.89) (Figure 18). SIMPER analysis indicated that Nymphaea odorata (increased), Clethra alnifolia (decreased), Smilax spp. (decreased), Decodon verticillatus (increased), and Potamogeton spp. (increased) accounted for the highest proportion of taxonomic dissimilarities between 2006 and 2011 (Table 23).

Resemblance: S17 Bray Curtis similarity 2D Stress: 0.01 year 1997 2006 2011

VP33 VP41VP38 VP33 VP38VP41VP41VP38

Figure 18. NMDS of E2, E8, and E9 species composition in 1997, 2006, and 2011 based on summed cover class data.

AA06 AA11 ADiss Contrib% Nymphaea odorata 38 150.33 10.55 16.47 Clethra alnifolia 175.67 174.33 8.55 13.34 Smilax spp. 159.67 27.67 8.35 13.02 Decodon verticillatus 86.33 120.67 6.69 10.45 Potamogeton sp. 0 72.67 5.22 8.15

Changes in the Individual Wetlands Common to the 1997, 2006, and 2011 Surveys Each of the three wetlands common to the 1997, 2006, and 2011 surveys exhibited a significant change in species composition over time. A summary of species shifts is presented in Table 24. In general, more species declined in abundance over this time period than increased. Fluctuations between years were highly variable with some species apparently increasing then decreasing and vice versa. Ten species documented in the 1997 survey have not been recorded during the last two surveys, and six have appeared only in the last survey.

Table 24. Summed cover class values for the 1997, 2006, and 2011 surveys, trends in changes between survey years, summed cover class value change between 1997 and 2011 by species for each of the three wetlands common to the three surveys, and a summary of the trends between 1997 and 2011. VP41 97–11 1997 2006 2011 97–06 06–11 97–11 Summary Clethra alnifolia 242 279 272 ↑ ↓ 30 Decodon verticillatus 184 127 157 ↓ ↑ -27 Deschampsia sp. 2 1 0 ↓ ↓ -2 Gaylussacia baccata 0 7 0 ↑ ↓ 0 Lyonia lingustrina 56 39 29 ↓ ↓ -27 Rhododendron viscosum 27 5 22 ↓ ↑ -5 2↑,8↓,1- Scirpus sp. 2 0 0 ↓ - -2 Smilax rotundifolia 95 68 50 ↓ ↓ -45 Triadenum virginicum 15 0 0 ↓ - -15 Utricularia sp. 22 0 0 ↓ - -22 Vaccinium corymbosum 57 35 74 ↓ ↑ 17

VP39 97–11 1997 2006 2011 97–06 06–11 97–11 Summary Amelanchier canadensis 6 0 0 ↓ - -6 Brasenia schreberi 0 0 4 - ↑ 4 Cephalanthus occidentalis 15 20 78 ↑ ↑ 63 Chamaedaphne calyculata 89 79 0 ↓ ↓ -89 Clethra alnifolia 220 222 200 ↑ ↓ -20 Decodon verticillatus 113 132 205 ↑ ↑ 92 Dulichium arundinaceum 48 87 77 ↑ ↓ 29 Glyceria canadensis 9 1 0 ↓ ↓ -9 Ilex verticillata 33 6 15 ↓ ↑ -18 Juncus spp. 599 248 111 ↓ ↓ -488 Lycopodium obscurum 2 0 0 ↓ - -2 Lyonia lingustrina 27 0 4 ↓ ↑ -23 8↑,15↓,0- Lysimachia terrestris 4 0 0 ↓ - -4 Nymphaea odorata 50 1 68 ↓ ↑ 18 Osmunda cinnamomea 9 5 4 ↓ ↓ -5 Parthenocissus quinquefolia 5 0 0 ↓ - -5 Phontinia floribunda 0 0 20 - ↑ 20 Rhododendron viscosum 62 0 36 ↓ ↑ -26 Rubus spp. 3 24 0 ↑ ↓ -3 Sagittaria sp. 2 0 15 ↓ ↑ 13 Smilax spp. 137 479 83 ↑ ↓ -54 Triadenum virginicum 55 17 58 ↓ ↑ 3 Vaccinium corymbosum 115 0 91 ↓ ↑ -24

VP33 97–11 1997 2006 2011 97–06 06–11 97–11 Summary Amelanchier sp. 9 0 0 ↓ - -9 Aronia floribunda 6 0 0 ↓ - -6 Calamagrostis canadensis 5 35 28 ↑ ↓ 23 Clethra alnifolia 56 26 51 ↓ ↑ -5 Deschampsia flexuosa 12 0 0 ↓ - -12 Dulichium arundinaceum 127 0 0 ↓ - -127 Eleocharis sp 0 0 3 - ↑ 3 Gaylussacia baccata 30 14 0 ↓ ↓ -30 Glyceria canadensis 50 43 0 ↓ ↓ -50 6↑,11↓,0- Kalmia angustifolia 23 0 10 ↓ ↑ -13 Leucobryum glaucum 7 0 0 ↓ - -7 Nymphaea odorata 147 113 383 ↓ ↑ 236 Poa palustris 0 0 19 - ↑ 19 Potamogeton sp. 321 0 218 ↓ ↑ -103 Toxicodendron radicans 0 0 6 - ↑ 6 Sparganium americanum 0 0 3 - ↑ 3 Vaccinium corymbosum 63 52 62 ↓ ↑ -1

When these data are grouped by growth form, the trends are similar in that there were more reductions in cover across more groups than there were increases (Table 25). Changes in the cover of floating and forb species were highly variable among wetlands, whereas graminoids and shrubs decreased in all wetlands.

Table 25. Summed cover class values for the 1997, 2006, and 2011 surveys and summed cover class value change between 1997 and 2011 by growth form category for each of the three wetlands common to the three surveys. VP41 1997 2006 2011 97–11 SAV 0 0 0 0 floating 22 0 0 -22 forbs 15 0 0 -15 graminoids 2 0 0 -2 shrubs 566 492 554 -12 trees 0 1 2 2

VP39 1997 2006 2011 97–11 SAV 0 0 0 0 floating 50 1 72 22 forbs 143 153 232 89 graminoids 608 249 111 -497 shrubs 659 439 571 -88 trees 6 0 0 -6

VP33 1997 2006 2011 97–11 SAV 321 0 218 -103 floating 147 113 601 454 forbs 134 0 3 -131 graminoids 182 78 47 -135 shrubs 178 92 129 -49 trees 9 0 0 -9

VP41 VP39 VP33 VP41 VP39 VP33 SAV 0 0 -103 - - ↓ floating -22 22 454 ↓ ↑ ↑ forbs -15 89 -131 ↓ ↑ ↓ graminoids -2 -497 -135 ↓ ↓ ↓ shrubs -12 -88 -49 ↓ ↓ ↓ trees 2 -6 -9 ↑ ↓ ↓

Environmental Variables The 2011 survey year was the first time that these environmental variables were measured in the wetlands. Accordingly, there are no comparisons to previous data.

Surface Water Chemistry (All 94 Sites that had Surface Water at the Time of Sampling; 13 Sites were Dry) Surface water pH ranged between 3.64 and 6.16 with a mean value of 4.65, indicating the acidic nature of these ponds in general (Figure 19). Conductivity had a minimum value of 26.1 µS, a maximum of 449.3 µS, and a mean value of 116.2 µS (Figure 20). With the exception of one wetland (VP143), all of the sites that had conductivity values >250 were located very close to the coastline, suggesting that these wetlands receive more salt spray than sites further inland.

Figure 19. Surface water pH in 94 wetlands surveyed in 2011 (dotted line represents mean value; note that 13 wetlands were dry and could not be sampled).

Figure 20. Surface water conductivity µS in 94 wetlands surveyed in 2011 (dotted line represents mean value; note that 13 wetlands were dry and could not be sampled).

Peat Thickness (All 107 Sites) Peat thickness values ranged between 4.8 cm and 138.3 cm with a mean of 46.3 cm (Figure 21). With the exception of one site (VP5), the thirteen sites that were dry at the time of sampling had peat layers <15 cm.

Soil Organic Matter (15 IS Wetlands Only) Soil organic matter was highly variable, ranging between 3.6% (VP73) and 93.8% (VP41), with a mean value of 41.8% (Figure 22).

Figure 22. Mean soil organic matter (%) in cores collected from the 15 IS wetlands in 2011 (n=3 cores per wetland; error bars are standard errors of means).

Hydrology (IS Wetlands Only) Instantaneous Water Levels (All 15 IS Wetlands) Water depths recorded with a meter stick along transects in the 15 IS wetlands reflect a broad hydrologic spectrum. For example, mean and maximum depths of individual wetlands ranged between 0 and 58.9 cm and 0 and 112 cm, respectively (Table 26).

Table 26. Mean and maximum water level measurements (cm) along the transects in the 15 IS wetlands, August 2011 (E2, E8, and E9 are original names of these wetlands).

SITE Mean (cm) Max (cm) VP63 0.0 0.0 VP120 0.0 0.0 VP97 1.1 35.0 VP59 1.1 26.0 VP139 2.4 20.0 VP12 3.1 46.0 VP81 4.0 18.0 VP41-E2 8.4 30.0 VP3 11.8 29.0 VP2 13.7 63.0 VP73 14.0 45.0 VP20 18.8 75.5 VP35 28.5 69.0 VP39-E8 37.6 65.0 VP33-E9 58.9 112.0

Continuous Water Level Data (Eight IS Wetlands Only) Data from the HOBO pressure loggers placed in eight of the 15 IS wetlands between June 23 and August 3, 2011 show that the rate of rise and fall of water levels can vary substantially among different wetlands (Figures 23 and 24). For example, VP120 shows very rapid and large increases in water level, coupled with quick declines. However, other wetlands, such as VP 39 and VP41, exhibit much less temporal variability. VP120 also shows much more daily variation in water level than do most other wetlands.

The eight different vernal ponds showed remarkable variation in some water level parameters (Table 27). While mean values were relatively similar, minimum and maximum depths were vastly different, as were the total ranges. With respect to the latter, one wetland showed a water level fluctuation of 63 cm during the sampling period while other fluctuations were <20 cm.

Figure 23. HOBO water levels in eight IS wetlands from June 23 through August 3, 2011.

Figure 24. Subset of 2011 HOBO data to show finer-scale resolution of water level fluctuations in the eight IS wetlands.

Table 27. HOBO-derived water level variables (in cm) for eight IS wetlands between June 23 and August 3, 2011.

Wetland ID mean minimum maximum range VP3 8 -2 17 19 VP20 8 -39 16 55 VP33 7 -6 18 24 VP39 13 5 18 23 VP41 10 3 16 19 VP59 8 0 19 19 VP73 6 -29 15 44 VP120 9 -34 29 63

Relationships among Wetland Vegetation and Environmental Variables All Wetlands A number of significant relationships among vegetation and environmental factors measured in 2011 are evident. These are summarized in Tables 28–33 that show values of Kendall’s rank correlation tests (i.e., non-parametric linear regression). Highlighted values (red) are statistically significant and the sign of the value, positive or negative, indicates the nature of the correlation (for example, the abundance of forb species was positively correlated with pH, meaning that forbs had higher cover in wetlands with higher surface water pH values; conversely, the abundance of shrubs and trees combined was negatively correlated with pH, meaning that shrubs and trees combined had higher cover in wetlands with lower surface water pH values). The meaning of these relationships is explored in the Discussion section.

FAC species abundance was positively correlated with conductivity, whereas OBL taxa exhibited the opposite trend. FACW species were negatively correlated with peat thickness (Table 28).

Tree abundance was positively correlated with conductivity and peat thickness (Table 29). Shrubs and trees combined were negatively correlated with pH and positively correlated with conductivity and peat thickness. Sedges were positively correlated with pH and negatively correlated with conductivity and peat thickness. Herbaceous taxa were positively correlated with pH and negatively with conductivity.

Surface water pH was negatively correlated with conductivity and peat thickness (Table 30).

The abundance of FAC species was negatively correlated with the prevalence of FACW and OBL taxa (Table 31).

Forbs were negatively correlated with shurbs (Table 32). Shrubs and trees were negatively correlated with herbaceous taxa.

Of note is that most FAC species are categorized as tress and shribs whereas most OBL and FACW species are categorized as “other” (i.e., non-woody taxa (Table 33).

Table 28. Correlations between abundance of plants belonging to specific wetland indicator categories and surface water pH, conductivity (Cond), and wetland peat thickness (Peat).

Variable FAC FACW OBL pH -0.034662 0.131302 0.097432 Cond 0.287938 -0.128940 -0.187730 Peat 0.112060 -0.178781 -0.020255

Table 29. Correlations between the abundance of plants belonging to specific growth form categories and surface water pH, conductivity (cond), and wetland peat thickness (peat).

Variable Floating Forb Grass Rush Sav Shrub Tree S/T Vine Sedge Herb pH -0.188742 -0.038417 -0.020050 -0.212512 0.153148 -0.147356 -0.019394 -0.205854 0.039422 0.150408 0.240783 Cond 0.054815 -0.054424 -0.045112 0.015179 -0.004641 0.109677 0.309069 0.416829 0.167936 -0.163893 -0.243792 Peat -0.082223 -0.123534 0.047673 0.121697 -0.060331 -0.010133 0.242669 0.222548 0.124296 -0.198058 -0.113802

Table 30. Correlations between surface water pH, conductivity (cond), and wetland peat thickness (peat).

Variable pH Cond Peat pH 1.000000 -0.224282 -0.150657 Cond -0.224282 1.000000 0.000927 Peat -0.150657 0.000927 1.000000

Table 31. Correlations between abundances of plants belonging to specific wetland indicator categories.

Variable FAC FACW OBL FAC 1.000000 -0.186804 -0.231475 FACW -0.186804 1.000000 0.219181 OBL -0.231475 0.219181 1.000000

Table 32. Correlations between abundances of plants belonging to specific growth form categories.

Variable Fern Floating Forb Grass Rush Sav Shrub Tree S/T Herb Fern 1.000000 -0.069955 -0.010969 0.211334 0.058387 -0.281787 -0.046055 0.151578 -0.091699 -0.176669 Floating -0.069955 1.000000 0.150677 -0.245677 -0.350438 -0.168585 0.250026 0.026043 0.013704 -0.048616 Forb -0.010969 0.150677 1.000000 -0.123288 -0.218218 -0.169311 -0.290790 -0.116230 -0.152297 0.052500 Grass 0.211334 -0.245677 -0.123288 1.000000 0.249330 0.055420 -0.026401 0.238828 -0.055263 -0.113172 Rush 0.058387 -0.350438 -0.218218 0.249330 1.000000 -0.060282 0.074009 0.086321 0.025354 -0.018083 Sav -0.281787 -0.168585 -0.169311 0.055420 -0.060282 1.000000 0.024876 -0.092701 0.065113 -0.023670 Shrub -0.046055 0.250026 -0.290790 -0.026401 0.074009 0.024876 1.000000 0.049422 0.106283 -0.181005 Tree 0.151578 0.026043 -0.116230 0.238828 0.086321 -0.092701 0.049422 1.000000 0.252376 -0.261230 S/T -0.091699 0.013704 -0.152297 -0.055263 0.025354 0.065113 0.106283 0.252376 1.000000 -0.134961 Herb -0.176669 -0.048616 0.052500 -0.113172 -0.018083 -0.023670 -0.181005 -0.261230 -0.134961 1.000000

Table 33. Number and proportion of species of various growth forms (2011) that are classified as FAC, FACW, and OBL species.

Number Proportion Species Tree Shrub Other Total Tree Shrub Other FAC 4 9 6 19 21% 47% 32% FACW 0 7 16 23 0% 30% 70% OBL 3 11 61 75 4% 15% 81%

IS Wetlands In 2011, species richness was only correlated significantly (positively) with conductivity (R2=0.28) and only in the 15 IS wetlands. This relationship deteriorated when data from all the wetlands were analyzed collectively.

Species belonging to specific wetland indicator categories did not exhibit any statistically significant correlations with mean or maximum water depths measured along transects, although the trends are worth noting (OBL and FACW species positively correlated with both depth variables; FAC species negatively correlated with both) (Table 34).

Numbers of wetland species exhibited very few significant correlations with percent soil organic matter or HOBO-derived water level variables (Table 35). In fact, only FAC was significantly correlated (positively) with maximum water levels and ranges.

Only two significant correlations were evident between the abundance of the various growth forms and percent soil organic matter or HOBO-derived water level variables (Table 36). SAV was negatively correlated with water level means while trees were negatively correlated with water level minimums.

Table 34. Correlations between abundance of plants (summed CC) belonging to specific wetland indicator categories and mean and maximum water depths measured during transect surveys.

Variable OBL FACW FAC Mean depth 0.208013 0.173795 -0.312019 Max depth 0.326877 0.112456 -0/219569

Variable OBL FACW FAC Mean % Organic 0.253546 -0.114332 0.166667 WL Means (HOBO) 0.366234 0.000000 0.166667 WL Min (HOBO) -0.197203 -0.171499 -0.233333 WL Max (HOBO) 0.422577 0.171499 0.500000 WL-Range (HOBO) 0.366234 0.342997 0.500000

Variable Fern Forb Grass Rush Sedge SAV Shrub Tree S+T Vine Mean % Organic -0.123718 -0.354650 -0.041239 -0.188982 -0.564076 -0.439155 0.566947 -0.563621 0.385758 0.206197 WL Means -0.123718 -0.275839 -0.371154 -0.037796 -0.322329 -0.731925 0.415761 -0.130066 0.308607 0.123718 WL Min -0.288675 -0.197028 -0.206197 -0.340168 -0.402911 -0.341565 0.264575 -0.650332 0.077152 -0.123718 WL Max 0.123718 -0.512272 0.371154 -0.188982 -0.241747 -0.341565 0.188982 -0.130066 0.154302 0.206197 WL-SE 0.206197 0.039406 0.453632 0.264575 0.322329 0.243975 -0.113389 0.563621 0.000000 0.206197

Species belonging to specific growth forms did not correlated significantly with mean or maximum instantaneous water depths, although certain trends are notable (Table 37). For example, tree taxa were negatively correlated with both depth variables, while grasses, rushes, and sedges were positively correlated with both.

Table 38 summarizes relationships among all environmental variables for the 15 IS wetlands. Mean percent soil organic matter (SOM) was positively correlated with instantaneous mean and maximum depths and soil organic matter, and HOBO-derived minimum water levels were negatively correlated with HOBO-derived water level ranges. Not surprisingly, instantaneous mean depths were positively correlated with instantaneous maximum depths. Surface water pH was negatively correlated with SOM and the same was true between pH and conductivity. Peat thickness was negatively correlated with conductivity.

Table 37. Correlations between abundance of plants belonging to specific growth form categories and mean and maximum water depths measured during transect surveys.

Variable Fern Forb Grass Rush Sedge SAV Shrub Tree S/T Vine Mean depth -0.188749 0.219514 0.229332 0.223495 0.270216 0.305085 0.116995 -0.290934 -0.197489 -0.099292 Max depth -0.099926 0.198607 0.253472 0.134097 0.250200 0.249615 0.223354 -0.244384 -0.031182 0.055162

Table 38. Correlations between combinations of all environmental variables for the 15 IS wetlands, 2011.

Environmental Mean % HOBO HOBO HOBO HOBO Mean Max Peat Bulk Variables Organic Means Min Max Range Depth Depth pH Cond Depth SOM Density Mean % Organic 1.00 0.29 0.36 0.07 -0.50 0.71 0.57 -0.50 -0.21 0.47 0.93 -0.86 HOBO Means 0.36 1.00 0.50 0.36 -0.36 0.29 0.14 -0.21 0.21 -0.07 0.36 -0.43 HOBO Min 0.07 0.50 1.00 0.14 -0.86 0.07 0.07 -0.29 -0.29 0.47 0.29 -0.21 HOBO Max -0.50 0.36 0.14 1.00 0.00 0.07 0.07 0.43 0.14 -0.33 0.00 -0.07 HOBO Range 0.71 -0.36 -0.86 0.00 1.00 -0.21 -0.07 0.43 0.43 -0.60 -0.43 0.36 Mean Depth 0.57 0.29 0.07 0.07 -0.21 1.00 0.71 -0.36 0.07 0.20 0.64 -0.71 Max Depth -0.50 0.14 0.07 0.07 -0.07 0.71 1.00 -0.21 0.21 0.20 0.50 -0.57 pH -0.50 -0.21 -0.29 0.43 0.43 -0.36 -0.21 1.00 0.00 -0.33 -0.57 0.50 Cond -0.21 0.21 -0.29 0.14 0.43 0.07 0.21 0.00 1.00 -0.73 -0.14 0.07 Peat Depth 0.47 -0.07 0.47 -0.33 -0.60 0.20 0.20 -0.33 -0.73 1.00 0.47 -0.33 SOM 0.93 0.36 0.29 0.00 -0.43 0.64 0.50 -0.57 -0.14 0.47 1.00 -0.93 Bulk Density -0.86 -0.43 -0.21 -0.07 0.36 -0.71 -0.57 0.50 0.07 -0.33 -0.93 1.00

GIS Variables Among the 107 known wetlands, 2010 LIDAR-derived mean elevations were negatively correlated with HOBO-derived hydrologic ranges in the subset of eight IS wetlands (F=5.55, p=0.05). The higher the elevation of the wetland, the lower the hydrologic range (and vice versa, wetlands near the coast fluctuate more) (Figure 25). Conductivity was negatively correlated with distance to the coast+(elevation*1E04) (F=6.41, p= 0.01) (Figure 26) and the abundance of OBL species was negatively correlated with distance to the groundwater table modeled by Masterson (2004) (F=4.19, p=0.04) (Figure 25).

Figure 25. Correlations of elevation vs. water level range (HOBO) (left) and conductivity (µS) vs. distance to the coast + elevation*1E04 (right).

Figure 26. Correlation of abundance of OBL species with distance to the USGS-modeled groundwater table.

Discussion

Temporal Changes in Vegetation In the broad surveys of 82 wetlands, species richness increased by 23 taxa (overall) between 2006 and 2011 and, in general, more taxa exhibited an increase in cover and frequency than a decrease. In particular, common woody shrub species (such as Vaccinium corymbosum, Decodon verticilatus, Clethra alinifolia, Lyonia ligistrina) had elevated cover values in 2011 compared to 2006. Whether this is a successional trend or a consequence of 2011 and certain years between 2006 and 2011 being quite dry (or both) is unclear.

Ability to Detect Changes in Vegetation Analysis of the data on statistical test values with taxon abundance shows that the probability that a significant difference is detected with individual species from one survey to the next is somewhat dependent upon its abundance (Figure 27). The relationship has a high degree of scatter; nonetheless it is evident. In this regard, the more common species (high abundance) is apparently prone to show more change and vice versa.

Figure 27. P-values of non-parametric Wilcoxen signed rank statistical tests for temporal vegetation change vs. the abundance (summed cover class values) of individual taxa.

Plant Community Characteristics in 2011 Grouping species into wetland indicator categories and growth forms allowed for further assessment of general trends in plant community structure and this kind of analysis revealed some interesting patterns. In terms of wetland indicator categories, FAC species are comprised of mostly trees and shrubs (68%), whereas FACW and particularly OBL species are dominated by herbaceous types (70% and 81%, respectively). Thus, we can surmise that wetlands with a higher abundance of FAC species are either in a later stage of succession or situated in a location where hydrology (shorter hydroperiod) permits the establishment of species that are less tolerant of prolonged flooding or both.

In terms of relationships among the different wetland indicator species, FAC species richness was negatively correlated with both FACW and OBL species richness. FACW species richness was positively correlated with OBL species richness. This implies that wetlands with a higher proportion of FAC species have conditions that are less suitable for the establishment and persistence of FACW and OBL species. These wetlands are likely drier than those with more FACW and OBL taxa.

Growth forms exhibited few significant correlations with each other. Notwithstanding, forb and herbaceous species richness in general was lower where shrub and tree species richness was higher; again demonstrating the type of community change that occurs when open, graminoid- and forb-dominated wetlands evolve into shrub- and tree-dominated wetlands.

Vegetation and Surface Water pH in 2011 No significant correlations were found between wetland indicator categories and surface water pH. With respect to growth forms, wetlands with lower pH values had higher abundances of shrubs and trees combined but lower abundances of sedge and herbaceous vegetation. Low pH values are typically associated with later successional stages (Grootjans et al. 2004); thus, the finding that woody vegetation predominates in acidic wetlands is logical.

Vegetation and Conductivity FAC species richness was higher in wetlands with higher conductivities, while the opposite was true for OBL species richness. It is known that conductivity increases with proximity to the coast, although the gradient is sharp; meaning that only wetlands that are very close to the bluff edge received substantial amounts of salt spray (Griffins et al. 2005, Smith 2006). Moreover, conductivity increases with decreasing volume of pond water, as dissolved constituents are more concentrated. Thus, the correlation between FAC species richness and conductivity makes sense, given that FAC species are less tolerant of flooding and therefore indicative of drier wetlands. Tree and shrub species (largely FAC-designated) richness was also positively correlated with conductivity while the opposite was true for sedge and herbaceous species richness. In this way, conductivity seems to be a fairly good indicator of successional stage and/or vegetation structure, although this variable is also influenced by groundwater inputs (groundwater has higher conductivities than precipitation) and salt spray (distance from coast). Sloan (1972) reported that low conductivity in waters suggests that the wetland is recharging the underlying aquifer, whereas high conductivities indicate that groundwater is discharging to the wetland (Sloan 1972). To what extent conductivities are influenced by groundwater infiltration, salt spray, and drawdown is not known. Conductivities measured in the IS wetlands corroborate this finding in that wetlands with shallower water depths at the time of sampling (indicative of shorter hydroperiod) had higher conductivity values.

Vegetation and Peat Thickness and Soil Organic Matter in 2011 There were only two significant relationships between peat thickness and soil organic matter and vegetation structure. In this regard, FACW species were less abundant where peat thicknesses were higher (it is notable that OBL species exhibited the same trend although the results were not statistically significant). Conversely, the prevalence of trees was positively correlated with peat thickness. No wetland indicator categories or growth forms were correlated with soil organic matter.

Vegetation and Hydrology in 2011 i) Instantaneous water levels (15 IS wetlands) - While expected trends were evident in relationships between wetland indicator categories and growth forms with water levels (e.g., OBL species abundance increased with higher mean and maximum water depths, and vice versa for FAC species), they were not statistically significant. Similarly, growth forms showed expected correspondance (e.g., shrubs and trees combined decreased and herbaceous species with mean and maximum water levels) but without statistical significance. ii) HOBO water levels (eight IS wetlands) - Only two significant relationships were found between plant communities and hydrologic variables calculated from the HOBO pressure logger data. The abundance of trees was negatively correlated with minimum water depths and FAC species were more abundant in wetlands with greater water level fluctuation (i.e., range). SAV was negatively correlated with water level means; however, this relationship is based on only two values for SAV that were >0.

The HOBO data are intriguing in that they demonstrate that individual wetlands have unique hydrologic signatures. In other words, water levels within these wetlands do not collectively rise and fall synchronously with the groundwater table. The disparities among wetlands may be, in part, a consequence of peat thickness, which regulates hydraulic connectivity with the surrounding groundwater table and the character of the plant communities. In addition, wetlands with a large proportion of woody species, particularly trees, will have higher rates of evapotranspiration. iii) Annual variation in hydrology - In terms of broad trends, the 107 wetlands that comprise the known forested vernal ponds within CACO showed significant changes in the overall composition and structure of vegetation communities. However, the data are somewhat puzzling in that it seems that the cover of all species, wetland indicator categories, and growth forms increased between 2006 and 2011. This may be a real trend due to the difference in water level in 2006 vs. 2011. The former was a very wet year while the latter was a very dry year. Pond stage data from CACO’s hydrologic monitoring program shows that there was a 0.5-m mean difference between the two years. As such, the emergence of aquatic vegetation would have been diminished in 2006 since high water levels inhibit the growth of many wetland taxa (Kozlowski 1985). Notwithstanding, this variability emphasizes the need for continued monitoring since it may take many years of data collection before directional trends can truly be elucidated.

Environmental Variables in 2011 Surface water pH was negatively correlated with conductivity and peat depth. The latter two variables were significantly correlated with each other and with water depth. Conductivity was negatively correlated with both mean and maximum water depth. Soil organic matter was negatively correlated with pH and postively correlated with mean water depth. These relationships suggest that the development of a thick, peat-based bottom layer in these wetlands is a product of prolonged flooding and/or that flooding may be prolonged in wetlands that have this characteristic. Although not statistically significant, the relationship between wetlands with low soil organic matter and water level fluctuation is interesting. Theoretically, sand-bottom wetlands may allow water levels to rise rapidly due to advective flow and upwelling from the groundwater table but also fall rapidly as a result of enhanced percolation (peat acts as a

semi-permeable or impermeable boundary layer between wetland water and the groundwater table). More data points are needed to fully explore this idea.

The wetlands with the largest ranges of water depths had relatively low amounts of peat and soil organic matter. These sandier soils are more permeable and may therefore be more prone to both inflow and outflow from the surrounding groundwater table, which would theoretically accentuate fluctuation within the wetland itself.

GIS Variables Broad-scale landscape variables calculated using GIS software were also informative in characterizing wetlands. For example, wetland elevation (LIDAR data) of the wetland was negatively correlated with hydrologic range. Generally speaking, this suggests that water levels in wetlands near the coast (which are typically closer to sea level elevation) tend to fluctuate more. Distance to the coast, which is a rough proxy for salt spray influence, was negatively correlated with conductivity, meaning that wetlands close to either Cape Cod Bay or the Atlantic Ocean had higher condutivities than those further inland. Finally, the abundance of OBL species was roughly correlated with distance to the groundwater table. Given the low level of accuracy of this variable with respect to actual hydroperiod, it is remarkable that this relationship could be detected. The entire dataset is subtended by a line showing the inverse relationship of OBL species with distance to the groundwater table. The variablity within the enclosed area is due to many of the other factors discussed above.

Conclusions

The plant communities of all known forested vernal wetlands were inventoried in 2011, providing an important second dataset on species and vegetation structure and changes in these parameters since 2006, when the first dataset was acquired. In general, these wetlands exhibit substantial variability in size, structure, and species composition, although a number of woody shrub species are almost ubiquitous. In addition, the wetlands are almost completely devoid of problem exotic taxa. Since 2006, many wetlands have exhibited an increase in the abundance of many taxa, particularly woody shrubs. Temporal change analysis conducted on data from three wetlands that were originally characterized in 1997 reveals a fluctuating pattern of change that is difficult to interpret without extensive analysis of many different variables. This finding, however, has made it clear that higher resolution hydrologic data may be a necessary component to monitoring forest vernal ponds - not just within the year of survey, but between them as well, since plants respond to hydrologic conditions on both short- and long-time scales. Using HOBO pressure loggers in a subset of ponds for multiple years is likely to be very useful in this regard.

Vernal pond vegetation is influenced by a variety of biotic and abiotic factors. These factors will either accelerate rates of succession or slow them. Infrequent, episodic events such as hurricanes could alter plant communities in a very short period of time, but, generally speaking, it will be the net effect of many different variables interacting with each other over long time periods that regulates the character, and change in character, of these systems. In the future, various aspects of climate change are certain to influence the vegetation of vernal ponds. For example, although an increased frequency of drought is predicted for the Northeast U.S. (IPCC 2007), rising sea level will force the groundwater table upward, which may result in a slow rate of increase in wetland hydroperiod. This, in turn, would set back successional processes, since woody plants tend to be less tolerant of flooding. In any event, predicting trajectories of vernal pond vegetation change in response to climate change is far beyond the scope of this report.

Comments on Monitoring Methodology While the general methodology of monitoring vernal pond vegetation seems reasonable, there are some apparent problems with plant species identification. For example, it is difficult to believe that V. corymbosum was present in VP39 in 1997, completely disappeared in 2006, and then reappeared in 2011, since woody shrub vegetation is fairly persistent over these relatively short time scales and through hydrologic fluctuations (Table 23). There are some other examples of this and it is likely that certain species (particularly shrubs and probably other types) were misidentified. Accordingly, it may be more informative to analyze vegetation data by growth form categories rather than species composition. These categories are very simple and are very difficult to confuse with one another. More vigorous training on species identification may also be necessary for future work. Aside from this problem, however, the methodology seems like a reasonable approach to developing a long-term protocol. The combination of broad surveys, combined with more intensive monitoring along transects, provides different levels of detail. The methods are generally straightforward and easy to undertake under typical field conditions.

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