Reading the landscape: temporal and spatial changes in a patterned peatland

Transcription

1 Wetlands Ecol Manage (211) 19: DOI 1.17/s z ORIGINAL PAPER Reading the landscape: temporal and spatial changes in a patterned peatland M. K. Nungesser Received: 29 June 29 / Accepted: 2 August 211 / Published online: 7 October 211 Ó Springer Science+Business Media B.V. 211 Abstract The Everglades of south Florida is a patterned peatland that has undergone major hydrologic modification over the last century, including both drainage and impoundment. The Everglades ridge and slough patterns were originally characterized by regularly spaced elevated ridges and tree islands oriented parallel to water flow through interconnected sloughs. Many areas of the remaining Everglades have lost this patterning over time. Historical aerial photography for the years 194, 1953, 1972, 1984, and 24 provides source data to measure these changes over six decades. Maps were created by digitizing the ridges, tree islands, and sloughs in fifteen 24 km 2 study plots located in the remaining Everglades, and metrics were developed to quantify the extent and types of changes in the patterns. Pattern metrics of length/width ratios, number of ridges, and perimeter/ area ratios were used to define the details and trajectories of pattern changes in the study plots from 194 through 24. These metrics characterized elongation, smoothness, and abundance of ridges and tree islands. Hierarchical agglomerative cluster analysis was used to categorize these 75 maps (15 plots by 5 years) into five categories based on a suite of metrics M. K. Nungesser (&) Applied Sciences Bureau, Water Resources Division, South Florida Water Management District, West Palm Beach, FL, USA mnunges@sfwmd.gov of pattern quality. Nonmetric multidimensional scaling, an ordination technique, confirmed that these categories were distinct with the primary axis distinguished primarily by the abundance of elongated ridges in each study plot. Strong patterns like those described historically were characterized by numerous, long ridges while degraded patterns contained few large, irregularly shaped patches. Pattern degradation usually occurred with ridges fusing into fewer, less linear patches of emergent vegetation. Patterning improved in some plots, probably through wetter conditions facilitating expression of the underlying microtopography. Trajectories showing responses of individual study plots over the six decades indicated that ridge and slough patterns can degrade or improve over time scales of a decade or less. Changes in ridge and slough patterns indicate that (1) patterns can be lost quickly following severe peat dryout, yet (2) patterns appear resilient at least over multi-decadal time periods; (3) patterns can be maintained and possibly strengthened with deeper water depths, and (4) the sub-decadal response time of pattern changes visible in aerial imagery is highly useful for change detection within the landscape. This analysis suggests that restoration of some aspects of these unique peatland patterns may be possible within relatively short planning time frames. Use of aerial photography in future Everglades restoration efforts can facilitate restoration and adaptive management by documenting sub-decadal pattern changes in response to altered hydrology and water management.

2 47 Wetlands Ecol Manage (211) 19: Keywords Everglades Patterned peatland Landscape ecology Hierarchical clustering Wetland restoration Historical analysis Nonmetric multidimensional scaling Restoration ecology Introduction The Everglades wetlands of south Florida (USA) (Fig. 1) are unique in the Americas and the world partly because they are a tropical patterned peatland. Patterns in natural environments consist of a few primary elements that are repeated regularly and nonrandomly across the landscape, occurring in both mineral soils and in peat soils. Patterned peatlands are common in boreal regions (Heinselman 193, 195, 197; Moore and Bellamy 1974; National Wetlands Working Group 1988; Rydin and Jeglum 2), but rare elsewhere. In boreal peatlands, linear ridges lie perpendicular to water flow, whereas linear ridges and tree islands in the Everglades are aligned parallel to water flow. This patterned south Florida landscape was first described as ridge and slough in 1915 (Baldwin and Hawker 1915) and extended throughout most of the landscape south of Lake Okeechobee (Harshberger 1914; Baldwin and Hawker 1915; SCT 23). Figure 2 represents the original pre-drainage landscapes of southern Florida showing the original extent of the ridge and slough patterning in this simulated satellite image. Peatlands are wetlands that develop in an environment where decomposition rates are slower than primary production, resulting in a gradual net accumulation of organic soils over time (Ingram 1983; Frenzel 1983; Moore and Bellamy 1974; Crum 1992). The Ridge and Slough landscape consisted of parallel, elongated ridges of sawgrass (Cladium jamaicensis) peat, elevated above open water sloughs inhabited by floating water lilies (Nymphaea odorata) and submerged bladderwort (Utricularia spp.). Tree islands were a third component of the landscape, typically long, teardrop-shaped forms, forested at the more elevated upstream ends and tapering to shrub and sawgrass communities along their downstream tails. These three landscape elements were distinguished both by vegetation and by slight elevation differences of a few decimeters (Wright 1912; Baldwin and Hawker 1915). Historically, water flowed into the Everglades annually as overflow from Lake Okeechobee in the wet season (May through November), then drained gradually during the dry season (Leach et al. 1971). The Everglades drained naturally southwards to Florida Bay or Biscayne Bay (Fig. 2). Details of the pre-drainage Everglades are derived from both original observations and from paleoecological analyses. Early explorers and surveyors indicated that the area defined as Ridge and Slough in Fig. 2 was characterized by ridges and sloughs extending throughout the region, with sloughs deep enough to allow them to paddle boats throughout the region (Ives 185; Dix and MacGonigle 195; Baldwin and Hawker 1915; McVoy et al. 211). They did not observe notable differences in landscape patterns that existed even as early as the 194s. These observers also indicated that the landscape linearity could be readily discerned from ground level (Smith 1848; Ives 185; Dix and MacGonigle 195; Harshberger 1914; Baldwin and Hawker 1915; SCT 23; McVoy et al. 211). It is assumed here that this pre-drainage (pre-188) Everglades landscape was configured relatively uniformly across its extent, consistent with these records. Palynological analyses of peat cores indicate that sloughs date back over 1 years ago and the ridges to four centuries ago (Bernhardt and Willard 29). They also indicate that responses to variations in climate were similar in all sub-regions of the Everglades (Willard et al. 21). Hydrological alterations initiated in the late 188s and continuing since have interrupted the natural seasonality, depths, and flow of fresh water, simultaneously disrupting this regionally synchronized response to climate. The Ridge and Slough landscape variously has been drained, dried, burned, compartmentalized, flooded, and enriched by nutrients before it was studied systematically by scientists (Alexander and Crook 1973; Doren et al. 1997; Richardson et al. 1999; Stephens and Johnson 1951; SCT 23; McVoy et al. 211), preventing detailed quantitative analysis of the pre-drainage system. To understand the history and impacts of hydrologic change on the Ridge and Slough landscape, it is necessary to present a brief summary of water management in the Everglades. Beginning in the 188s, the Everglades were heavily modified for drainage. Canals were constructed to reduce water levels in Lake Okeechobee (Leach et al. 1971;

3 Wetlands Ecol Manage (211) 19: Fig. 1 South Florida study area identifying Water Conservation Areas (WCAs) 1, 2A, 2B, 3A, 3B (managed by South Florida Water Management District), and Everglades National Park and Big Cypress Preserve (federal lands). Major canals, roads, and levees are delineated Alexander and Crook 1973) and to drain the region south of Lake Okeechobee. Three canals, including the Miami Canal, bisected the Ridge and Slough landscape (Fig. 1). These canals lowered water levels in the marsh with effects on the peat extending outward far from the canal (Stephens and Johnson 1951; Leach et al. 1971). The previous annual overflow into the peatlands from Lake Okeechobee ceased after construction of a flood protection levee around the south end of the Lake in Farther to the south, a highway connecting Florida s east and west coasts (Tamiami Trail) was constructed, obstructing southward flow (Fig. 1). Ecosystem damage from peat drainage was compounded by droughts and extensive muck fires throughout the peatlands (Alexander and Crook 1973). Increasing demand for water storage for the region s growing human population of the region coupled with the desire to reduce muck fires subsequently led to compartmentalization of the wetlands in the 19s, creating shallow reservoirs (water conservation areas) out of the formerly continuous wetlands (Fig. 1). The two southern Water Conservation Areas (WCAs), WCA-3A and WCA-3B, were completed by

4 478 Wetlands Ecol Manage (211) 19: water upstream of the impoundments at the southern ends (Sklar et al. 22a; SCT 23; McVoy et al. 211). These altered conditions continue to impact this patterned landscape while water management practices have changed over time. Consistent with the early descriptions of the Everglades, photos dating from the early 19s show the marked linearity of the landscape (SCT 23; McVoy et al. 211). The earliest set of aerial photos covering most of the Everglades was dated 194 (Foster et al. 24). Even after a half century of drainage, these images show a landscape with linear patterns extending throughout most of southern and southeastern Florida, suggesting resilience of the patterns. Visual comparisons of 194 and 24 imagery reveal that many formerly patterned areas are now dominated by shallow wetlands of thick emergent species and discontinuous patches of water. These changes prompt the following questions: (1) How similar were the patterns across WCA-3 in 194? (2) When and how did the Ridge and Slough patterns change between 194 and today? (3) Did patterns change in similar ways over the six decades? (4) Were pattern changes synchronous? These questions can be addressed by an analysis of pattern changes from historic aerial photographs and by relating these changes to preceding hydrologic and environmental conditions. Fig. 2 The pre-drainage landscape of south Florida shown in the center with the linear ridges and tree islands visible (McVoy et al. 211). The Ridge and Slough landscape extended throughout most of the area south and southeast of Lake Okeechobee to Florida Bay mid-197 (Leach et al. 1971) and are the focus of this analysis. A new east west highway (I-75) was constructed through northern WCA-3A, and the Miami Canal was degraded at regular intervals to allow water movement southward. Other than rainfall, inflow to these compartments has been restricted to flow through the northern canals and water control structures, the breaks in the Miami Canal, and some inflow from the west and from newly constructed stormwater treatment areas to the north. Because these compartments retained water, southward landscape slope and flow impedance produced dryer conditions in the northern areas of the compartments and deeper Methods Study sites and pattern data Water Conservation Area 3, the focus of this analysis, is a primary target of flow and ecological restoration in the Everglades (C&SF 1999; USACE and SFWMD 22) including Everglades National Park. The dimensions of WCA-3 are approximately 3. km long by 38 km wide. Qualitative aspects of the patterning can be readily discerned when they are strong, as in Fig. 3, or when they have degraded severely. Patterns are considered strong, as shown in the maps in Fig. 3a, if ridges are elongated, numerous, aligned parallel to each other, regularly spaced horizontally and vertically, separated by linear sloughs, and defined by a distinct ridgeslough boundary. Sloughs in strongly patterned areas are linear and interconnected, of similar widths, with few impediments to flow other than occasional

5 Wetlands Ecol Manage (211) 19: Fig. 3 Comparisons of good and poor patterning in the study plots based upon the maps generated from aerial photographs. Dark areas are open water, light areas are ridges/tree islands and emergent vegetation patches. The top images (a) represent strongly patterned study plots (G1-194, N3-194, and G3-1972) and the lower (b) represent fully degraded patterns (I4-1984, I1-24, and N1-1984) horizontal bridges between ridges. In contrast, degraded patterns in this system, shown in Fig. 3b, are defined by undifferentiated stands of emergent vegetation generally covering the entire study plot, with few open water patches. Simple visual inspection of photos may not detect early changes because of the complexity of the patterns themselves and because of the relatively subjective nature of pattern quality assessment. Quantitative metrics, on the other hand, can discern changes that may identify improvement or degradation of patterns over a time frame useful for feedback to restoration practices. Therefore, using a time-series of pattern maps, multivariate assessment methods were developed to detect temporal and spatial changes in the Everglades patterned landscapes. It is important to note that pattern strength does not translate directly to the health of the ecosystem; because of decades of drainage and altered hydrology, the remaining patterns even in the 194s do not represent the pristine Everglades. Instead, nearly all of the Ridge and Slough landscape was affected by drainage by 194, as described in the introduction. Within the boundary of WCA-3, three spatially distinct flow paths were identified based upon estimated elevations and landscape orientation (Sklar et al. 2). These transects were labeled as G, N, and I from west to east in WCA-3, respectively (Fig. 4). Fifteen study plots were superimposed along these paths oriented along the landscape directionality from north to south through WCA-3 (Rutchey et al. 29). The plots were laid out along each flow path orientated parallel to the local landscape directionality with adjustments made largely to avoid major barriers, such as levees and large canals. Each plot was 4 km by km, sized to fit multiple ridges vertically and horizontally. Four plots were located along transect G, six along N, and five along I. These rectangular plots each provided focused but spatially distributed sub-regions of the local landscape. By tracking the same location across time, these plots were used to determine trajectories of past changes and can be

6 48 Wetlands Ecol Manage (211) 19: Fig. 4 Locations of study plots in WCA-3. Flow transects are labeled G, N, and I from west to east, and numbered from north to south (G 1 4, N 1, and I 1 5, respectively). Each plot is 4 km by km in size incorporated into monitoring plans for future management and restoration activities. Patterns were digitized from historic aerial photography taken at intervals representing most decades from 194 through 24. The aerial photography used in this analysis was flown in the dry seasons (January through April) of 194, 1953, 1972, 1984, and 24, which experience clearer conditions and lower humidity than at other times of the year. The early imagery was black and white (194 and 1953), while subsequent images were color infrared or natural color. The 194 images were U.S. Department of Agriculture Soil Survey aerial photographs at a resolution of 1:4,, scanned to a 1-m resolution available in jpeg format (Foster et al. 24). Images from the early 195s were photographed at 1:2, scale and digitally scanned at a.3 m resolution. The next available set of images was from 1972/1973, available as tiff files digitally scanned at a.1 m resolution from original 1:8, scale images. The 1984 images were scanned digitally at 1.5 m resolution from the 1984 National High Altitude Photography five-foot resolution color infrared tiff files. The 24 images were Digital Ortho Quarter Quads (DOQQs) one-meter resolution color infrared jpeg files. All images were spatially georeferenced to the 24 DOQQs (T. Schall, SFWMD, pers. comm.). A bimodal map of ridges/tree islands and sloughs was created for each plot for the years 194, 1953, 1972, 1984, and 24. Automated methods of classification could not be used because of the highly variable quality of the original photographs. Therefore, ridges and tree islands appearing in each study plot were digitized manually at a 1:5 resolution to create a bimodal map of ridges (tree islands are considered a special case of ridges) and sloughs by delineating the edges of emergent vegetation; water extent is not directly delineated in this process. Ridges and other vegetation patches longer than 3 m comprised the longest 25% of the ridges in the 194 photos and were used for the analysis because these landscape elements visually define the linearity of the patterns (Sklar et al. 24). Paleoecological studies (Bernhardt and Willard 29; Sklar et al. 28) have revealed that these large structures represent long-enduring structures in the landscape. The resulting maps (5 years for each of the 15 plots) provided a uniform data set of 75 plots for analysis. The naming convention for each plot is the plot name with the year of the map (e.g., N2-1972). A copy of the full set of maps is available from the author. Shape and directional metrics (length, width, area, perimeter, and orientation) were recorded for each ridge or tree island. Length was defined as the maximum distance between points in the ridges; orientation was calculated from the maximum length arc. Individual ridge values included area, perimeter, mean width, and ratios of length/width (L/W) and perimeter/area (P/A). The L/W ratio represents elongation of the plot s elements (larger numbers indicate longer, thinner shapes), while the P/A ratio generally represents smoothness of the elongated elements (higher values indicate smoother shapes). Plot-level summaries included mean ridge length (L), width (W), perimeter (P), and area (A), variability of the orientation, and the total number of ridges (n). Plot-level means of the L/W and P/A ratios were created (LW and PA, respectively). Two additional metrics were calculated at the plot level: the LeWN index (Length width-number) and the PAN index

7 Wetlands Ecol Manage (211) 19: (Perimeter-area-number) (Sklar et al. 24). LeWN is defined as: LeWN ¼ Xn i¼1 L=W ð1þ where n is the number of polygons [3 m long and L/W is the length/width ratio of each ridge in the plot. PAN is defined as: PAN ¼ Xn i¼1 P=A ð2þ where n is the number of polygons[3 m long and P/A is the perimeter/area ratio of each ridge in the plot. The LeWN and PAN indices account for the abundance of these shapes in the plots. For example, a study plot could have one long smooth ridge, producing high L/W and P/A values, but lack the patterning resulting from the frequency and regularity of these ridges in a patterned peatland. LeWN and PAN correct for that mean by accounting for the abundance of the ridges in a plot. Plots with numerous elongated or smooth ridges then have higher LeWN and PAN indices than those with fewer ridges of similar proportions or those lacking ridges. Features that extend beyond the edges of the plot boundaries were identified as edge features to contribute to the total cover, but were not used to calculate other plot values with a few exceptions. Because some plots contained only edge elements, it was necessary to retain at least one feature for the analysis; the largest vegetation patches (covering greater than 5% of the plot area, m 2 ) were retained and used for all analyses. Of the 75 plots, 22 contained only one or two features under this constraint and 53 contained three or more features. Because orientation did not add useful information, these values were removed from further analysis. Plot summary data determined previously to relate to pattern quality throughout the Everglades (Sklar et al. 24) (Table 1) were used for subsequent analyses. Analytical methods Basic descriptive and multivariate analyses were conducted for five variables: n, LW, PA, LeWN, and PAN (representing plot level statistics). Hierarchical agglomerative cluster analysis was used to define relatively homogeneous groups across time and space using the pattern metrics. Clustering was performed with PCOrd (McCune and Mefford 2) using the Sorensen (Bray-Curtis) distance measure with group average linkage. Ordination helped identify the important variables that define relationships among the shape metrics. Nonmetric multidimensional scaling (NMDS) (Kruskal 194) was selected for ordination because it uses rank distances, does not require linear relationships between variables, and is generally effective for ecological data (McCune and Grace 22). The original data and the cluster groups were used as the primary and secondary matrices, respectively. A Monte Carlo test compared the final stress produced by the real versus randomized data. Post-analysis tests (analysis of variance, means comparisons, and correlations) were conducted to determine the variables that dominated the ordination axis, which incorporates information from all the variables. Two graphics illustrate the temporal and spatial changes in pattern quality in the study plots. Local changes in pattern over the study period (194 through 24) were displayed as linear plots of category by year. Spatial distributions of pattern quality of the study plots in each year across the landscape were mapped using Inverse Distance Weighted interpolation. Results The plot level metrics in Table 1 indicate that study plots varied widely by year and by plot, often by several orders of magnitude: the number of ridges in a plot ranged from one to 12; mean perimeter/area ratios (PA) varied from.72 to.324; mean length/width ratios (LW) were to ; LeWN ranged between and 95. and PAN values from.72 to 2.4. The strongest correlations (Table 2) were between the number of ridges (n) and LeWN (r =.952) and PA with PAN (r =.941). The number of ridges (n) was only moderately correlated with PAN (r =.525), even though both PAN and LeWN include n as a component. LW and LeWN were moderately correlated (r =.488) as were PAN with LeWN (r =.5448). All other correlations were less than.5. Relationships with the ordination axis are discussed below with the NMDS results. Because the Ridge and Slough patterns are highly regular and anisotropic, high correlation between most variables was expected. Strong patterns are long, linear, and relatively smooth, while weak patterns are

8 482 Wetlands Ecol Manage (211) 19: Table 1 Plot summary data for study plots in Water Conservation Area 3 Study plot, year n LW PA LeWN PAN Study plot, year n LW PA LeWN PAN Study plot, year n LW PA LeWN PAN G N G N G N G N G N G N G N G N G N G N G N G N G N G N G N G N G N G I N G N G N I N N I N N I N N I N N I N N n number of ridges/tree islands, LW mean length/width ratio, PA mean perimeter/area ratio, LeWN LeWN index, and PAN PAN index (see Eqs. 1 and 2)

9 Wetlands Ecol Manage (211) 19: Table 2 Correlations between variables (all plots, all years) and the Nonmetric Multidimensional Scaling axis 1 for the pattern metrics in Water Conservation Area 3 n PA LW LeWN PAN Axis 1 n 1. PA LW LeWN PAN Axis E- 2.8E-1 Distance (Objective Function) 5.7E-1 8.5E-1 1.1E Information Remaining (%) 5 25 Strong (5) Good (4) Moderate (3) Poor (2) Degraded (1) G1_194 G4_194 G1_24 G4_1953 G3_1972 G3_1984 N5_24 G2_194 I1_194 I5_194 N3_194 G3_24 G4_24 G1_1953 G1_1984 G1_1972 G2_1972 G4_1984 N2_1984 I3_24 N4_1972 N_194 G2_1953 N2_24 G4_1972 N3_1953 G2_1984 N5_1972 G2_24 N2_194 N3_1984 N2_1972 N3_1972 N4_24 I2_24 N_1953 N4_1984 N5_1984 G3_194 I4_194 N5_194 I3_1953 N4_194 I1_1984 I4_1984 I4_1972 I1_24 N1_1984 I3_194 G3_1953 N5_1953 N1_1953 I2_1972 I3_1984 N_24 I1_1972 I2_1984 N4_1953 N_1972 I3_1972 N1_194 I2_1953 N1_1972 I4_24 N2_1953 I1_1953 I5_1972 I2_194 I5_1953 N1_24 I4_1953 N_1984 I5_1984 I5_24 N3_24 Fig. 5 Tree diagram of study plots and pattern categories produced by hierarchical agglomerative cluster analysis of the variables n, LW, PA, LeWN, and PAN (see Table 1). relatively irregular in shape and random in dimensions (for very low n, patch dimensions are defined by the dimensions of the study plot). In an unpatterned system, one would expect lack of correlation between shape, smoothness, length/width ratios, and perimeter/ area ratios. The hierarchical cluster analysis was used to define groups containing from four to 25 members (Fig. 5; Table 3) composed of mixes of plots from multiple Correspondence of the pattern categories is identified along the left axis of the diagram. The study plots in each category are listed in Table 3 years and hydrological flow paths. The analysis showed very low chaining (2.9%). In this type of dendogram, chaining is the addition of an item to an existing group because it is not sufficiently different to generate a new group. This hierarchical cluster analysis shows low chaining, suggesting that the groups identified in this analysis are distinct. Results of a means comparison test for variables by category appear in Table 4. Categories 1 and 5 differed

10 484 Wetlands Ecol Manage (211) 19: Table 3 Pattern categories derived from agglomerative hierarchical cluster analysis of variables shown in Table 1, and memberships of each category for study plots by year G3-194 G I2-24 G G1-194 I I N G G1-24 I1-24 I N G G2-194 I3-194 I2-194 N-1953 G G I I G G I4-194 I G G3-24 I I G2-24 G4-194 I I G G N I G G4-24 N4-194 I I3-24 I1-194 N5-194 I4-24 N2-194 I5-194 I N N3-194 I N N5-24 I N2-24 I5-24 N N1-194 N N N N N N1-24 N4-24 N N N3-24 N-194 N N N-1972 N-1984 N-24 significantly for all variables, but had different relationships with variables in the other categories; some variables varied distinctly between categories, while others did not. The number of ridges in a plot differed between categories 5, 4, and 3 or under. Similar patterns occurred for LeWN and LW. PA fell into two groups with category 5 and 1 being distinct. PAN values differed for category 5, but not for the other four categories (1 through 4). The strongly patterned plots share high values among the pattern metrics and the poorly patterned plots share low values. The top cluster in Fig. 5 contains fourteen plots with high LeWN, PAN, and n values (Table 3). These plots exhibit strongly linear vegetation patches, even spacing between patches, and elongated and interconnected open water patches. The cluster second from the bottom in Fig. 5 consists of eleven plots with the lowest values of n, PA, LW, LeWN, and PAN. These plots contain scattered patches of open water among a continuous stand of emergent vegetation. The three other categories fall numerically in between the two extremes. The second cluster from the top in Fig. 5 has n, LeWN, and PAN values less than half those of the top cluster, and LW is a bit larger than that of the top cluster. Emergent vegetation in this second cluster retains linearity but some of the patches have coalesced, and open water sloughs have become somewhat less connected. The bottom cluster in Fig. 5 contains 25 plots with low values of n, PA, PAN, and LeWN, with moderate LW, suggesting that they have some linear structures but these are degraded. The middle cluster in Fig. 5 has only four plots with intermediate values of n, PA, LW, LeWN, and PAN. These contain a mix of less linear ridges and sloughs showing expansion and increased interconnection of ridges with a resulting loss of connected sloughs. From these metrics and visual inspection, these clusters were ranked from 1 through 5, representing poor to strong patterning, respectively. The classes noted along the left side of the cluster diagram (Fig. 5) indicate the pattern categories. Table 4 Means comparisons of variables used in classifications of pattern quality n plots Ridges/plot PA LW LeWN PAN (a). (a).48 (a) (a) (a) (b).37 (a,b). (a) (b) (b) (c).453 (a,b) 5.34 (a,b) 7.54 (c).594 (a,b) (c).271 (a,b) 4.98 (b) 15.9 (c).941 (b) (c).158 (b) 2.77 (c) 2.77 (c).158 (b) Letters in parentheses indicate the group memberships; those that are the same indicate no significant differences for that variable in the category

11 Wetlands Ecol Manage (211) 19: Means comparison tests indicated that each category consisted of significantly different values of many of the component variables (Table 4). The values of LeWN and n for categories 5 and 4 differ from those in categories 1 through 3. PAN values for categories 5 and 3 differ from those in categories 1, 2, and 4. Categories 1 and 5 differ for PA, and LW of categories 4 and 5 differ from categories 1 and 2. It should be noted that the number of ridges per patch (n) is not significantly different from each other in categories 1 and 2 (Table 4); some of the increase in values of the variables in these two categories results from canals, roads, and utility lines that divide what would otherwise be one single patch of emergent vegetation into several. The G flow-way (western WCA-3) plots dominated categories 4 and 5, representing good to strong patterning. Three of the four plots in category 3 were in the southern N flow-way, while category 2 (poor patterning) contained members predominantly from 1953 and 1972 in the I and N flow-ways. Nearly all of the degraded plots (category 1) were in the I flow-way, located the farthest east in the WCA. Patterns in the 194 plots were most commonly classified as either degraded or strong: six were classified as strongly patterned (category 5) and five were classified as degraded (category 1) in 194 (Table 3). The best ordination using NMDS produced a single axis (Fig. a) that organized the plots and retained the groups created by the cluster analysis. These categories were distinct and lacked overlap. A Monte Carlo test comparing real versus randomized data indicated that the real data produced a much lower stress value (1.139 after 17 iterations; final instability.) (Fig. b). The first axis accounted for almost 9% of the variance in the data (r 2 =.894), suggesting that the combined variables produced a generally linear structure. The NMDS axis was highly correlated with the LeWN index (r =.8739) and n (r =.8544) (Table 2). The correlation with LW was also high (r =.58). The strength of the correlations with PA and PAN were lower (r \.5). These correlations indicate that patterning strength is dominated by both the linearity of the ridges and the higher number of ridges per unit area measured in these plots. Smoothness of the edges alone does not contribute as much as the linearity to the assessment of pattern strength, although it also characterizes the Ridge and Slough Rank Stress Distance in Ordination Space landscape. The ordination confirmed and clarified the validity of the pattern classes (1 5) produced by the cluster analysis (Fig. 5; Table 3). In general, pattern quality can be estimated by the number of ridges and the value of LeWN in a plot. Plots with 2 or more long ridges tended to be those with good to strong patterns (categories 4 and 5; Tables 1, 3). When plots contained fewer than ten long ridges, their pattern quality was poor or degraded (categories 1 and 2). Plots with LeWN values greater than 1 showed good or strong patterns, while those under 5 were poor or degraded. Similarly, values of PAN that exceeded 1. were strongly patterned, and 3 Dimensions 4 Real Data Randomized Data Maximum Mean Minimum Fig. Ordination diagram from nonmetric multi-dimensional scaling analysis (a). The input matrix contained the same metrics used for the hierarchical clustering (Fig. 5) plus a variable defining the cluster categories 1 5 for each study plot. The diagram represents the distances in ordination space (xaxis) plotted against the rank order of each study plot (1 through 75) (y-axis), with the categories identified by symbol. Stress (b), an inverse measure of fit to the data (McCune and Grace 22), compares the real data to randomized data using a Monte Carlo test. Stress is nearly monotonic and significantly different from random (P \.5). NMDS supports the associations produced by hierarchical clustering 5

12 48 Wetlands Ecol Manage (211) 19: those below.1 were poorly patterned. For both n and LeWN, 1 2 ridges or LeWN values of 5 1 were moderately patterned. Temporal trends Time series of pattern changes in each plot were illustrated with temporal trajectories of each plot using the categories derived from the hierarchical clusters. These trajectories provide information about the stability of patterns since 194 and identify individual plot responses to changing environmental conditions. These temporal trajectories are displayed in Fig. 7. Patterns in all plots changed over time by at least one category, and most show a combination of both improvement and degradation (Fig. 7). From 194 to 24, overall pattern quality in five plots declined, four remained unchanged, and six improved. By 24, most individual plots fell into different categories than they had in 194. Over the six decades, eight plots (G3, N3, N4, N5, N, I1, I3, and I5) moved among two or more categories from either good to poor or poor to good patterning. The other seven plots (G1, G2, G4, N1, N2, I2, and I4) changed by only one category. Plots G1, G2, and G4 remained in the strongly patterned categories 4 and 5 from 194 through 24. Plots N1, I2, and I4 remained in the lowest categories 1 and 2 throughout the years. Plots N3, N, I1, and I5 were classified with good or strong patterns in 194 but their patterns degraded over time. In contrast, plots G3, N4, N5, I2, and I3 improved in patterning from 194 through 24. These trajectories indicate that pattern quality was dynamic in most of the Ridge and Slough peatland over the six decades. To some extent, pattern categories grouped together along flow-ways. Most of the G flow-way plots were classified as categories 4 and 5 across all time periods. Plots G1, G2, and G4 retained patterning over the six decades while those in the N and I flowways changed markedly. The N flow-way plots were evenly distributed among declining, improving, and no change. Most of the I plots fell into the lowest categories, 1 and 2 (Table 3; Fig. 8). Spatial trends The spatial relationships of pattern quality (Fig. 8) show regions where the Ridge and Slough patterns were better or poorer than others and suggest potential environmental conditions affecting patterns. In 194, plots with good patterns appeared in two regions, one at the south end of WCA-3 immediately north of the Tamiami Trail (plots G4, N5, and I5). The second area of good patterning ranged from plots G1 and G2 northeastward to N2, N3, and I1 (Fig. 8). The other seven plots had poor patterning (categories 1 or 2) in the first aerial photographs and were located away from Tamiami Trail and to the east and to the far north. Plot I1 remained in the lowest categories consistently from 194 through 24. The divergence of pattern quality in 194 indicated that the earliest photos captured a Ridge and Slough landscape that was already significantly altered from pre-drainage conditions (McVoy et al. 211). By 1952, patterning had degraded throughout the eastern flow-ways; all of the I plots fell into categories 1 and 2, and most of the N flow-way plots were also classified as category 2. Only plots G1, G2, G4, and N3 remained in categories 4 or 5. Plot I5 just north of Tamiami Trail had degraded from category 5 to 2 and N had declined from category 4 to category 3. Following compartmentalization in the mid-19s, the 1972 patterns in N2, N4, N5, and G3 had improved from 1953, although N had degraded in what became WCA-3B. All four G flow-way plots and four of the six plots in the N flow-way had good or strong patterning (G1 G4 and N2 N5), while all the eastern plots, I1 I5, plus N1 and N were classified as poor or degraded patterns. During the 19s, newly constructed openings in the Miami Canal allowed additional water to flow southward again, which would have rehydrated plot N2. The L-7 levees and canal impounded water to the north, where G4 and N5 would have been most affected by higher water depths. Both of these structural changes increased water depths in portions of the WCA. South of the newly constructed L-7 levee, the peatland grew increasingly dry, and from then through 24, all three plots in WCA-3B (N, I4, and I5) remained in the poor or degraded categories. In 1984, poor patterns remained east of Miami Canal and south of the L-7 levee, while the G flowway and the middle four plots of the N flow-way continued in the moderate to strong categories. Pattern categories had improved again by 24 even in some of the eastern plots (I2 and I3), and four plots were characterized with good or strong patterns (G1, G3, G4, and N5). Only N3 in central WCA-3A degraded

13 Wetlands Ecol Manage (211) 19: N N2 I1 G1 N3 I2 G2 N4 I3 G3 N5 I4 G N I Fig. 7 Trajectories of patterns over time. Categorical values are displayed from 1 to 5, with higher numbers indicating stronger patterns. Categories were derived from hierarchical by two categories from 1984 to 24, having already declined from category 5 in 194. Discussion Paleoecological evidence indicates that sloughs and ridges have remained in place for at least four agglomerative clustering and ordination for the years 194, 1953, 1972, 1984, and 24 centuries (Bernhardt and Willard 29). Additional evidence suggests that before the landscape was modified by drainage, broad-scale sub-environments in the Everglades responded similarly to climate fluctuations (Willard et al. 21). Both of these conditions appear to have changed over the last century. Distinctions between ridges and sloughs disappeared in large portions of the former patterned

14 488 Wetlands Ecol Manage (211) 19: Fig. 8 Spatial distribution of pattern quality by year. Light areas represent higher values (5 = white) and dark represents low values (1 = black). Mapping used inverse distance weighted interpolation to indicate spatial distributions of study plot patterns by year landscape, and those patterns that remain have responded very differently across the landscape. As noted in the introduction, early written records in the pre-drainage period indicate that the patterns in the Ridge and Slough landscape were similar throughout its extent. From this evidence, one can reasonably assume that neighboring plots in the Ridge and Slough landscape would have resembled each other in the original system. After 5 or more years of severely altered natural flow into the Everglades, only a few of the study plots in 194 resembled their neighbors (Fig. 8). Over the next six decades, many plots differed from their neighbors in pattern quality and most adjacent plots differed in their pattern trajectories (Figs. 7, 8). For example, while plots N2 and I1 displayed good to strong patterning in 194, their trajectories diverged after 1953; plot N2 improved again following the opening of gaps in the Miami Canal, which was designed to improve hydration southward, while I1 continued to degrade. In adjacent plots G4 and N, G4 remained well-patterned while N degraded. In contrast, N4 and N5 had almost identical trajectories from 194 to 24, improving greatly from degraded conditions; N and I5 resembled each other in starting as patterned then degrading rapidly and remaining degraded. G1, G2, and G4 remained strongly patterned over this period. These findings confirm observations made by Willard and colleagues (21) that sub-environments in the Everglades are now responding to localized fluctuations in hydroperiod rather than their original synchronized responses to climate shifts. Pre-drainage patterns may have varied over time, but information for a wide variety of sites is not available. Annual precipitation variability may have played a role in altering Ridge and Slough patterns, though minor, because highly variable rainfall is typical of the south Florida climate. Climate records for WCA-3 show 1 years of below-normal rainfall prior to 194 and a continuing dryer than average period into the 195s (Leach et al. 1971; SFWMD 2). The 194 and 1953 patterns may show evidence of these drier climate periods, exacerbating changes produced by the 5 years of drainage leading up to 194. Rainfall in

15 Wetlands Ecol Manage (211) 19: the 3 years immediately prior to 1972, 1984, and 24 was somewhat higher than century average (SFWMD 2), and these remaining patterns may reflect elements of higher water depths on vegetation patterns. It is likely that the landscape responds to rainfall within a few years, but if rainfall were the main driver of landscape pattern shifts, then the entire landscape should have improved or degraded in synchrony, shifts that are not supported by this analysis. Bernhardt and Willard (29) have reported that vegetation in the Everglades, including WCA-3, shifted to a dryer community in the early 19s in spite of rainfall generally producing a relatively wetter climate overall. They concluded that hydrologic modifications were responsible for the dryer regional conditions. The lack of temporal and spatial synchronicity in pattern changes among adjacent study plots and those along the same flow paths suggests several hypotheses. One is that these pattern shifts are driven primarily by local environmental conditions (e.g., distance to canal or levee, local water depths) rather by than a single regional driver such as droughts in south Florida. Locations of plots with poor and degraded patterning (N1, I1, I2, I3, and I4, categories 1 and 2) in northern WCA-3A generally correspond to areas reported to have experienced substantial peat subsidence from drainage, oxidation, and burning (Stephens and Johnson 1951). Peat loss of up to.7 m has been estimated throughout northern and eastern WCA- 3A and northern WCA-3B (Komlos et al. 28; Desmond 27). Hydrologic data extending through the period covered by this analysis are rare. However, historic depth data from stage gauge 5 in southwestern WCA- 3 are available beginning in 1953; this gauge measures stages that would influence plots G3, G4, and N5. These stage data, smoothed and adjusted for ground elevation to produce water depths (Fig. 9), suggest three different ongoing depth regimes in southern WCA-3 from 1953 through 24. The first depths of approximately 15 cm from 1953 to 192 predate compartmentalization and reflect the severe drainage of the Everglades. Following compartmentalization in 195, average depths at this gauge were maintained at approximately 35 cm through 199. After 199, modified hydrologic operations produced depths of approximately 5 cm from 199 through 24. In the nearly flat Everglades, these slight differences in water depths support significantly different vegetation communities (Kushlan 199) which can be detected on aerial imagery and were used to define ridge-slough boundaries. The timing of these increasing depths corresponds to the improving pattern qualities reflected in this analysis for southern WCA-3A, particularly for plots G3, G4, and N5. Compartmentalization increased water depths in southern WCA-3A; by 1972, structures had been in place for 8 years or longer. Ridge and Slough patterns improved in areas associated with deeper water in 1972, particularly in the plots upstream of the L-7 canals (G3, N4, and N5). While the ridge, slough, and tree island patterns themselves appear to have Fig. 9 Annual water depths at gauge 4 ( , 8 4 1, NGVD), near study plot G3 in WCA-3A (see Fig. 4). The point values are estimated from historical data (McVoy, pers. comm.) for pre- and post-drainage dates; the smoothed curve represents a 24-day running mean depth based on monitoring data (SFWMD 2). The arrows indicate years for which aerial photos were mapped for use in this analysis

16 49 Wetlands Ecol Manage (211) 19: strengthened based upon their edge boundaries, deeper water from impoundment has been implicated for destruction of tree islands (Sklar and Van der Valk 22b). It is possible that tree island vegetation, particularly the longer-lived forest species, had adapted to lower water depths. With a time lag for various species to adapt to higher water levels or to be replaced by more flood-tolerant species, forests may eventually adjust to the deeper water. It is also possible that tree island vegetation communities require a regular periodicity of seasonal high and low water depths to thrive, which the present water management schedules do not provide. The present analysis considers only the shapes of the structures and their changes over time. Further research is needed to characterize detailed features of the vegetation on the ridges and tree islands and in the sloughs in these study plots. Additional traits may need to be considered for more detailed pattern quality assessment. Another hypothesis is that the patterning responses may be related to varying resilience or to environmental drivers that differ geographically. Some drivers may be difficult to discern, such as localized upwelling of groundwater from highly porous surface rock formations. Others may relate to unexpected or presently unknown feedback mechanisms, as they do in boreal bogs (e.g., retention of ice cores inside hummocks; Nungesser 23). At present, relationships between the patterns and hydrology in the Everglades are proceeding through investigations of driving mechanisms and feedbacks (e.g., Larsen et al. 27, 211; Larsen and Harvey 211, 21; Noe et al. 21; Ross et al. 2; Watts et al. 21). Paleoecological investigations are attempting to decipher predrainage ecosystem structures (e.g., Willard et al. 2; Bernhardt and Willard 29; Rutchey et al. 29) and their changes and driving factors. This analysis indicates that the ridge-slough boundaries can change over a few years (less than a decade) as measured by the length, width, perimeter, area, and abundance metrics. The potential for these relatively long-lived landscape features (centuries long; Willard et al. 21) to vary rapidly enough in their shape metrics to be easily measured at a decadal or shorter time frame is helpful for restoration monitoring and for adaptive management. While the exact physical and biological mechanisms responsible for pattern generation and maintenance at these scales have yet to be determined, the rapid response of vegetation and landscape features to changes in the environment, particularly water depths, has been seen elsewhere in the remaining Everglades in slough vegetation communities (Zweig and Kitchens 28) and in tree islands (K. Rutchey, pers. comm.). Research suggests that this microtopography is sensitive to hydroperiod and flow (Larsen et al. 211; Larsen and Harvey 21, 211; Harvey et al. 29; Noe et al. 21; SCT 23; Watts et al. 21) and possibly to nutrient distribution (Larsen et al. 211; Ross et al. 2). It is not clear why emergent vegetation patterns in WCA-3 have expanded and contracted, but interactions between vegetation and water depths are probably responsible. Research on expansion and contraction of boreal hummocks and hollows, microtopographic features in bogs, have indicated that microtopography responded to long-term climatic shifts of wetter and dryer periods (Walker and Walker 191; Conway 1948). The elevated hummocks contracted and wet hollows expanded in wetter periods and the reverse occurred in dryer periods. Similar results have been reported for ridge and tree island expansion and contraction in the Everglades (Bernhardt and Willard 29; Willard et al. 21). The Everglades landscape has retained some microtopographic differentiation (McVoy, pers. comm.), so these slight elevation differences may contribute to the rapid response of pattern changes to water depths in several ways. Dryer conditions may allow sawgrass and other predominantly ridge species to expand into former sloughs, while wetter conditions can drive the plants back to their former sites on peat ridges; these shifts have been observed in paleoecological analyses in the southern Everglades (Rutchey et al. 29). Anecdotally, fire scars on the aerial photographs occasionally reveal the underlying microtopography (ridges that were visible in earlier photographs; pers. obs.) even though surface vegetation communities do not appear to differ noticeably. These elevation differences may also contribute to rebuilding microrelief. If the microtopography is produced by autogenic properties of the vegetation species interacting with hydrology, as it is in boreal peatlands (Nungesser 23), then the remnant microtopography may expedite restoration of the patterning under appropriate hydrologic conditions when peat-generating species are present. The remaining peat microtopography in the Ridge and Slough landscape may provide a platform to restore the original sloughs and ridges/