Ecosystem structure, nutrient dynamics, and hydrologic relationships in tree islands of the southern Everglades, Florida, USA

Forest Ecology and Management 214 (2005) 11–27 www.elsevier.com/locate/foreco

Ecosystem structure, nutrient dynamics, and hydrologic relationships in tree islands of the southern Everglades, Florida, USA Tiffany G. Troxler Gann a,*, Daniel L. Childers a, Damon N. Rondeau b a

Department of Biological Sciences and Southeast Environmental Research Center, Florida International University, Miami, FL 33199, USA b Southeast Environmental Research Center, Florida International University, Miami, FL 33199, USA Received 13 September 2004; received in revised form 12 February 2005; accepted 16 March 2005

Abstract Tree islands are an important structural component of many graminoid-dominated wetlands because they increase ecological complexity in the landscape. Tree island area has been drastically reduced with hydrologic modifications within the Everglades ecosystem, yet still little is known about the ecosystem ecology of Everglades tree islands. As part of an ongoing study to investigate the effects of hydrologic restoration on short hydroperiod marshes of the southern Everglades, we report an ecosystem characterization of seasonally flooded tree islands relative to locations described by variation in freshwater flow (i.e. locally enhanced freshwater flow by levee removal). We quantified: (1) forest structure, litterfall production, nutrient utilization, soil dynamics, and hydrologic properties of six tree islands and (2) soil and surface water physico-chemical properties of adjacent marshes. Tree islands efficiently utilized both phosphorus and nitrogen, but indices of nutrient-use efficiency indicated stronger P than N limitation. Tree islands were distinct in structure and biogeochemical properties from the surrounding marsh, maintaining higher organically bound P and N, but lower inorganic N. Annual variation resulting in increased hydroperiod and lower wet season water levels not only increased nitrogen use by tree species and decreased N:P values of the dominant plant species (Chrysobalanus icaco), but also increased soil pH and decreased soil temperature. When compared with other forested wetlands, these Everglades tree islands were among the most nutrient efficient, likely a function of nutrient immobilization in soils and the calcium carbonate bedrock. Tree islands of our study area are defined by: (1) unique biogeochemical properties when compared with adjacent short hydroperiod marshes and other forested wetlands and (2) an intricate relationship with marsh hydrology. As such, they may play an important and disproportionate role in nutrient and carbon cycling in Everglades wetlands. With the loss of tree islands that has occurred with the degradation of the Everglades system, these landscape processes may have been altered. With this baseline dataset, we have established a long-term ecosystem-scale experiment to follow the ecosystem trajectory of seasonally flooded tree islands in response to hydrologic restoration of the southern Everglades. # 2005 Elsevier B.V. All rights reserved. Keywords: Forested wetlands; Sheet flow; Nutrient-use efficiency; Chrysobalanus icaco; Tree islands; Hot spots; Everglades

* Corresponding author. Tel.: +1 305 348 1576; fax: +1 305 348 4096. E-mail address: [email protected] (T.G. Troxler Gann). 0378-1127/$ – see front matter # 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.foreco.2005.03.065

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1. Introduction Forested islands in a freshwater wetland landscape are a ubiquitous feature of the Everglades ecosystem, Florida, USA. These ‘‘tree islands’’ increase ecological heterogeneity of the marsh landscape and provide critical structure and habitat to Everglades flora and fauna (Gawlik and Rocque, 1998; van der Valk and Sklar, 2002). Examples of this landscape mosaic are described for many regions of the world; in the tropics they include Belize and Cuba (Rejmankova et al., 1996), the Pantanal of central South America (Ponce and Cunha, 1993), the savannas of northeastern Bolivia (Langstroth, 1996), and the Okavango Delta of Botswana (Ellery et al., 1993). Everglades tree islands are believed to be formed as a result of variation in underlying limestone topography coupled with colonization by trees and inputs of nutrients via abiotic and biotic transfers in the landscape (i.e. groundwater inflow and bird deposits, respectively; van der Valk and Sklar, 2002). Past studies have suggested that forested islands occurring in graminoid-dominated and other wetland landscapes exhibit unique ecosystem functions resulting from the differentiation of the islands from the landscape and specifically associated with habitat complexity, biogeochemical transformations, and landscape-scale carbon cycling (McCarthy et al., 1993; Gawlik and Rocque, 1998; Mitsch and Gosselink, 2000; Seastedt and Adams, 2001). In central Everglades marshes, up to 60% of tree island cover has been lost as a result of either drainage or over-flooding (Patterson and Finck, 1999). It is clear that hydrologic modifications can have detrimental effects on tree island structure. However, there is little information of defining tree island ecosystem properties, ecological processes, or key relationships with landscape hydrology. Characterization of these parameters will provide baseline information with which to identify and characterize hypothesized ecological functions, and is critical for understanding the ecological resilience of tree islands to hydrologic modifications. Much of the Florida Everglades is experiencing large-scale hydrologic modifications as part of a restoration effort (Davis and Ogden, 1994; http:// www.restudy.org). In 1997, hydrologic restoration of the southern Everglades began with the removal of the southern levee of the C-111 canal along the segment of the canal that traverses the easternmost southern

Everglades (the C-111 Basin or Everglades National Park Panhandle; Fig. 1a). This was implemented to increase freshwater flow to the coastal freshwater marshes of the southern Everglades and the estuaries and near-shore coast of northeastern Florida Bay. Notably, canal inputs are currently the predominant source of water to this region, and are controlled by water management activities in the lower C-111 Basin. This area is dominated by seasonally flooded tree islands that are peat-based with an average hydroperiod of 5–10 months. We utilized the C-111 hydrologic restoration effort to initiate a landscapescale experiment to investigate how increased freshwater flow may affect seasonally flooded tree island ecosystem structure and ecological processes. Complications we encountered with this large-scale hydrologic manipulation are similar to those that characterize many landscape-scale experiments. These include: (1) no classical experimental controls, (2) the

Fig. 1. (a) Extreme south Florida and the southern Everglades (M. Rugge, Florida Coastal Everglades LTER, 2001); (b) C-111 Drainage with tree island study sites and flow experimental design.

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appearance of pseudo-replication because experimental units cannot be completely randomized in the landscape, and (3) a lack of pre-manipulation data. We will meet these potential challenges by interpreting our data in time-series to characterize ecosystem response trajectories of tree islands as a result of increased freshwater flow to the landscape. Here, we only noted differences among islands relative to canal location (flow treatment) to understand the variation that occurred at the onset of our experiment. The objectives of this study were to: (1) describe ecosystem structure and ecological processes of southern Everglades seasonally flooded tree islands; (2) compare ecosystem properties of southern Everglades tree islands with other tropical and temperate forested wetland systems; (3) relate tree island ecosystem properties to seasonal and annual variations in hydrology; (4) ecologically differentiate tree islands from the marsh matrix; (5) identify key parameters that could be used as indicators of tree island ecosystem response to hydrologic restoration. We addressed these objectives by quantifying the following in six tree islands: (1) vegetation structure and composition; (2) island geomorphology; (3) litterfall production; (4) plant nutrient-use efficiency; (5) soil biogeochemical properties; (6) key ecological and hydrologic parameters of the marsh landscape. An important goal of this study was to establish baseline data that will allow us to quantify the ecosystem trajectories in seasonally flooded tree islands in response to hydrologic restoration in the southern Everglades. By quantifying theses trajectories using measurements of wetland ecosystem properties known to be important in other forested wetland systems, we will assess ecological impacts of future changes in water management and hydrologic restoration. As such, those ecological parameters that define changing ecosystem trajectories will be valuable in assessing restoration success and adaptive management of restoration strategies.

2. Methods 2.1. Study site In August 1999 (2 years after levee removal), we selected six tree islands (based on similar island size

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and vegetation type) downstream of or adjacent to the levee removal segment of the C-111 canal (Fig. 1b). These tree islands were chosen as representative of the freshwater forested wetlands in the southern Everglades landscape; they have been classified as red bay (Persea palustris) flat-tailed islands (Egler, 1952), and later identified as cocoplum islands (Craighead, 1971) and mixed swamp tree islands (Meeder et al., 1996). The islands are elliptical in shape, aligned southsoutheast with the approximate direction of flow. The wetland matrix surrounding these tree islands is dominated by short hydroperiod (period of inundation) sawgrass (Cladium jamaicense) marsh with marl (calcium carbonate-derived) soils. The south Florida wet season is generally between June and December, and precipitation averages over 1200 mm annually (Duever et al., 1994). Our southern Everglades study region typically experiences a 3–6 month dry-down every year (January–June) that varies annually depending on rainfall and water management. To initiate our long-term experiment, we selected tree islands in two different locations relative to the C111 canal. Three of the six islands were located downstream of canal inputs (i.e. islands with maximum freshwater inputs—Flow islands) and three islands were in an area west of the canal that received minimal freshwater inputs (No Flow islands; Fig. 1b). No Flow islands experienced relatively shorter hydroperiod and minimal sheetflow or nutrient inputs from the canal. We report results from the first 2 years of our study (August 1999–July 2001) to characterize baseline conditions for a long-term experimental study where we will assess the ecosystem trajectory response of tree islands as a result of increased freshwater flow. 2.2. Island vegetation analysis We quantified vegetation cover and density in each island with a modified line-intercept method using two 40 m east–west transects and 10 cm intercept intervals (Barbour et al., 1999). Vegetation cover was separated into two layers: the canopy (height > 1.3 m) and sub-canopy (shrub and herb) layers (height < 1.3 m). We chose breast height (1.3 m) to differentiate vegetation layers to facilitate canopy tree identification. When live biomass of a plant fell within a 10 cm interval along the line, we

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recorded that as one individual count. We summed counts along each transect to approximate absolute cover (the total number of counts for each species divided by the number of 10 cm intervals) and relative cover (the number of counts for each species divided by the total number of counts for all species divided by the number of intervals). Cover of each species was averaged across both transects to represent overall island cover. To estimate stem density, seven 2 m  3 m plots were selected at stratified intervals (2–3 m apart) along two transects in each island (2–3 m apart), for a total of 14 plots per island. Stems of all species with a diameter at breast height (DBH)  1 cm were counted and DBH was recorded. Total stem density and the stem density of individual species were calculated from the average of these plots. We assessed species diversity employing Shannon index utilizing stem count data (Barbour et al., 1999). 2.3. Landscape geomorphology We quantified several tree island and marsh landscape structural parameters for each island. Soil depths were surveyed along an east–west transect that extended 15 m into the adjacent marsh, and depth (to limestone bedrock) was measured at one meter intervals along the transect with a 1.3 m soil probe. Depths >1.3 m (when the probe did not strike limestone) were recorded as >1.3 m. We calculated the area of each island using United States Geological Survey (USGS) Digital Orthophoto Quadrangles and Arc View# GIS. Each island was digitized three times and the area of each island was taken as the average of these three measurements (<3% variation among measurements). 2.4. Litterfall collection and turnover Litterfall was collected monthly (August 1999– July 2001) in ten 0.5 m2 traps that were placed randomly in each island. Litter collected from each trap was dried to constant weight at 70 8C, sorted (leaves (by species), wood, reproductive parts, and miscellaneous parts), and weighed. Litterfall data are reported as cocoplum leaf litter (dominant plant species on all islands), other species leaf litter (pooling the remaining leaves), wood, and repro-

ductive litter components. A representative sample of mature green leaves from the species most commonly represented in each month’s litterfall samples was also collected monthly. In August 1999, we made a collection of standing litter from the surface soil of each tree island in 10 0.5 m2 quadrats to determine standing stocks of litter and litter turnover rates (kt = Z/Xss; the ratio of annual litterfall to standing litter; Nye, 1966). We removed surface litter to the top soil layer within each quadrat, excluding large woody debris (>2.5 cm in diameter). Standing litter was sorted into leaf, wood, reproductive, and miscellaneous components, dried to constant weight at 70 8C, and weighed. 2.5. Tree island leaf and litterfall nutrient analyses Subsamples from each component were compiled by island, ground to a homogeneous powder (<500 mm), and analyzed for total nitrogen (TN), total phosphorus (TP), and total carbon (TC) content. Live leaf and litterfall samples were analyzed for TC and TN with a Carlo Erba elemental analyzer. The modified Solorzano and Sharp (1980) method was used to analyze TP. Total carbon, TN, and TP content of litterfall and green leaves collected in August, December, February, and April (1999–2001) were used to calculate indices of tree island nutrient economy using cocoplum (CPL), other species (OSP), and total litterfall components. These indices included N and P concentrations (mg and mg, respectively), nutrient molar ratios (N content/P content: 31/14; Redfield, 1958; Koerselman and Meuleman, 1996), nutrient resorption efficiency (% nutrients withdrawn upon senescence of leaves), and nutrient-use efficiency (g annual litterfall/g nutrients in litterfall; Vitousek, 1984). 2.6. Soil characteristics A number of island and marsh edaphic variables were also assessed. Between August 1999 and July 2001, we measured soil oxidation–reduction potential (Eh), soil pH, and soil temperature bimonthly, and island water level monthly in each island. A permanent station was located in each island for repeated measurements. Soil temperature, Eh, and

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pH were measured (10 cm soil depth) with an Orion meter (Model #250A). In August 1999, soil characteristics (bulk density, organic matter content, moisture content, TN, TP, and TC content) were quantified from three replicate cores taken from each island and from each region of the marsh. The soil was extracted with a 7 cm diameter serrated aluminum coring device. We removed roots from the top 15 cm of soil of each core and two subsamples were dried to a constant weight at 70 8C for bulk density and moisture content (g wet g dry 1 g dry 1). One subsample was then ashed at 500 8C for 4 h to determine organic matter content. The other subsample was analyzed for nutrient and carbon content. In addition to soil bulk nutrient information, we assessed soil nutrient availability by sampling island (August 1999, December 1999, February 2000, and July 2000) and marsh (August 1999 and February 2000) porewater. In both cases, porewater was extracted from porewater ‘‘sippers’’ (aquarium air stones equipped with fine Tygon1 tubing and sealed with teflon tape; Dailey, 2000) placed 10 cm into the soil. Porewater was sampled using a 120 mL syringe and filtered through Whatman GF/F filters. Filtered samples were analyzed for soluble reactive phosphorus (SRP), ammonium (NH4+), nitrate (NO3 ), nitrite (NO2 ), and dissolved organic carbon (DOC). Analyses of water samples for SRP, NH4+, NO3 , NO2 concentrations were determined on a fourchannel auto-analyzer (Alpkem model RFA 300). DOC concentration was determined using a hot platinum catalyst, direct injection analyzer (Shimadzu model TOC-5000).

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2.7. Hydrology Water level was measured monthly to the soil surface at a permanent sampling point located at the lowest observed topographic position within each island, avoiding tree tip-ups. Water levels collected in each island were used as estimates of stage. We generated continuous water level estimates for each island by relating these point measures to continuous water level recorders from nearby surface water and groundwater sampling stations in the marsh (Childers, unpublished data; www.sfnrc.ever.nps.gov), and used these values to calculate island hydroperiod values. To generate a continuous record of water levels and hydroperiod for the 2-year period, we generated simple linear regressions of monthly island water levels and nearby USGS daily water level gauges (Table 1). Values were averaged to yield water level data for both island and marsh in the Flow and No Flow areas of the C-111 Basin. We then utilized a nearby South Florida Water Management District (SFWMD) station that provided daily water levels recorded to the marsh soil surface, and generated a simple linear regression utilizing daily water levels from a USGS station that also monitored groundwater levels (below soil surface; Table 1; y = 48.064 + 0.986  x, r2 = 0.966, p < 0.0001). We determined the soil surface water level for the USGS groundwater well for each island group (Flow and No Flow), and used these estimated groundwater water levels as the independent variables in regression relationships with island water levels that were collected at monthly and daily monitoring stations as the dependent variables. Thus, from these relation-

Table 1 Regression equations to determine island elevation based on monthly island water levels, a nearby SFWMD daily surface water level gauge (W1), and USGS daily groundwater level monitoring stations (CT50 and EVER7) collected from August 1999–July 2001 Nearest station

Flow region

Island

CT50 CT50 CT50 EVER7 EVER7 EVER7

Flow Flow Flow No Flow No Flow No Flow

2.1 2.2 2.3 3.1 3.2 3.2

Intercept

Slope

r2

47.38 53.391 50.833 60.568 59.146 55.77

0.943 1.000 0.934 0.898 0.964 0.908

0.794* 0.842* 0.897* 0.752* 0.920* 0.900*

Island water level (z) (cm) 2 5 6 17 13 12

Surface water levels (W1) equal to zero were deleted from the regression equation generated for the relationship between W1 and CT50. Values in the last column were generated from regression equation described in text, which relates surface water levels to island water levels (i.e. when marsh surface water level is 0, island 2.1 water level = 2 and island 2.1 elevation is on average 2 cm greater than marsh soil surface). * p-Value  0.0001.

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ships, we estimated island elevation by taking the average difference in island water levels from marsh water levels that were corrected for landscape position (utilizing stations in Flow and No Flow areas of marsh; Table 1). In April, July, August, and October 2000, water flow was measured at the upstream end of each island using fluorescein dye as a visible tracer, and these measures were periodically calibrated with a Sontek1 acoustic Doppler flow meter. 2.8. Marsh landscape water chemistry and nutrient loads We collected grab samples (bottles submerged to the approximate middle of the water column and filled) of marsh surface water from the upstream end of each island (April, July, August, and October 2000) to quantify total and dissolved (Whatman GF/F) nutrient and carbon concentrations and loading rates to tree islands. We used collections made in the wet season months of 2000 to estimate annual marsh nutrient loads to tree islands. As there were three islands per treatment, single marsh surface water samples collected at each island were treated as treatment replicates. Unfiltered samples were analyzed for TN using an Antec 7000N total nitrogen analyzer, for TP using the dry ashing, acid-hydrolysis technique (Solorzano and Sharp, 1980), and for TOC using the method described above for DOC. Filtered samples were analyzed using the same methods. We used these sample concentrations to estimate N, P, and OC (total and dissolved) loading rates (per m2 of (vertical) landscape normal to the direction of water flow) to each island as the product of nutrient or carbon concentration, water flow rate, and marsh water level for each island. Estimating nutrient loads in this manner may have overestimated loads to islands because water flowing through the marsh also flows around islands. 2.9. Data analyses All measurements quantifying island vegetation and abiotic parameters were averaged to obtain a single value and standard error () for each island. Thus, all statistical analyses were performed with n = 6. We used Wilcoxon ranked sign test to examine inter-annual variation in tissue nutrient indices, hydrologic, and soil variables. We examined varia-

bility in tissue nutrient content, nutrient molar ratios, and nutrient resorption efficiency values among plant species groups and leaf types with two-factor ANOVA. To investigate temporal variability in litterfall production, we utilized repeated measures (RMANOVA; STATVIEW # 5.0). We analyzed differences in island and marsh parameters using onefactor ANOVA. All data were tested for normality and homogeneity of variances, and non-parametric tests were used when one of these assumptions were not satisfied. For ANOVA tests, we used Fisher’s pairwise least significant differences (PLSD) post hoc tests, with alpha = 0.05 (STATVIEW # 5.0).

3. Results 3.1. Vegetation analyses A total of 43 plant species were found on the six study islands. Absolute vegetation cover (Barbour et al., 1999) was dominated by cocoplum for both canopy and sub-canopy (shrub and herb) layers on all islands. Cocoplum canopy cover was higher in Flow islands than No Flow islands (66  2 and 50  3%). We also found variation in canopy cover of co-dominants between flow groups. Co-dominants most frequently encountered included: Salix caroliniana, Myrica cerifera, Conocarpus erectus, Magnolia virginiana, Ilex cassine, Perseapalustris, and Taxodium ascendens. Otherwise, the sub-canopy layer was composed mostly of Blechnum serrulatum and Cladium jamaicensce, with other species varying in co-dominance. Stem density averaged 3.9  0.3 stems m 2. Average stem DBH was 3.3  0.3 cm. Shannon’s diversity index was 0.33  0.04. Species richness averaged 8.0  0.4. 3.2. Landscape geomorphology Island area averaged 0.178 ha and islands were similar in size (0.006 ha). All six islands surveyed had at least one soil depth exceeding 130 cm, and a value of 130 cm was used for these points when calculating the mean soil depth. Tree island soils were deeper than marsh soils (87  3 and 60  3 cm). In addition, both average and minimum marsh soil depths were more shallow in the No Flow area of the marsh.

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3.3. Litterfall deposition and turnover in tree islands We estimated annual community production, and determined seasonal variation in community production from litterfall samples collected monthly from August 1999 through July 2001. Annual litterfall averaged over all six islands and both years was 506 (19), 77 (17), 44 (3), 22 (1), and 627 (1) g dry weight m 2 year 1 for leaves, wood, reproductive parts, miscellaneous parts and all components (except miscellaneous) combined, respectively (Fig. 2a). We found no differences between years for any litterfall component. Standing litter averaged 735 (81), 405 (60), 10 (3), 66 (18), and 1217 (131) g dry weight m 2 for leaves, wood, reproductive parts, miscellaneous parts, and total litter, respectively (Fig. 2a). Average total litter, leaf litter, and wood turnover rates were 55 (0.1), 71 (0.1), and 25 (0.1)% year 1, respectively. Total litter and leaf litter turnover rates were higher in islands of the Flow group. Because monthly litterfall production varied widely throughout the study period, we averaged

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monthly litterfall values for wet and dry seasons in Years 1 and 2. We found seasonal differences in total litterfall production only. Utilizing repeated measures ANOVA, the data showed peaks in the wet season of Year 1 and the dry season of Year 2 (F = 12.134, p = 0.0006, d.f. = 3, n = 6; Fig. 2b). We divided leaf litterfall into cocoplum or Chrysobalanus icaco and other species groups. Peaks in leaf litterfall production of CPL followed that of total litterfall (F = 19.044, p < 0.0001, d.f. = 3, n = 6; Fig. 2c). We also found higher average monthly leaf litterfall of OSP in the Year 2 dry season (F = 6.591, p = 0.0070, d.f. = 3, n = 6), translating to over all higher production in the dry season averaged over both Years 1 and 2 (F = 7.585, p = 0.0512, d.f. = l, n = 6). 3.4. Tree island leaf and litterfall nutrient economy We assessed tree island nutrient economy using tissue nutrient concentrations, molar ratios, N and P resorption efficiency, and within-stand N and P nutrient-use efficiency (NUE). We averaged monthly

Fig. 2. Tree island litterfall production: (a) tree island fine litterfall and standing litter-average of 2 years-August 1999–July 2001 (does not include miscellaneous); (b) Fine litterfall components (leaf, wood, reproductive, and miscellaneous), averaged monthly August 1999–July 2001. Wet seasons are August–January and dry seasons are February–July; (c) leaf litterfall of CPL (Chrysobalanus icaco) and trees categorized as OSP (all other tree species) averaged monthly August 1999–July 2001. Wet seasons are August–January and dry seasons are February–July. Wet seasons are August–January and dry seasons are February–July. Error bars are standard error.

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nutrient values for each island (August 1999–July 2000 and August 2000–July 2001). We found considerable variability between years, most often in CPL nutrient values (Table 2). In Year 1, we found Table 2 Nutrient characterization of live leaves, leaf litterfall, and fine litterfall as determined by patterns between years (n = 6); August 1999–July 2001

Cocoplum Live leaves %P %N %C N:P C:N C:P Litter %P %N %C N:P C:N C:P

Year 1 (S.E.)

Year 2 (S.E.)

p < 0.05

0.059 (0.001) 1.186 (0.025) 48.470 (0.141) 45 (1) 48 (1) 2175 (40)

0.045 (0.002) 1.152 (0.014) 47.016 (0.105) 59 (3) 48 (0) 2984 (237)

*

0.015 (0.001) 0.684 (0.012) 47.394 (0.114) 104 (6) 82 (1) 8600 (408)

0.016 (0.001) 0.796 (0.034) 46.933 (0.304) 120 (5) 72 (2) 8729 (394)

Resorption efficiency %P 73 (1) %N 42 (2) Other LVS Live leaves %P %N %C N:P C:N C:P Litter %P %N %C N:P C:N C:P

0.066 (0.004) 1.557 (0.044) 50.691 (0.135) 52 (4) 39 (1) 2240 (181)

66 (3) 31 (2)

0.070 (0.004) 1.431 (0.041) 49.474 (0.363) 47 (2) 42 (1) 1897 (97)

* * *

* * *

*

* *

higher P and C content, and lower N:P and C:P in CPL live leaves. In CPL litter, we found lower N content and lower N:P, but higher C:N. We also found higher N resorption and N nutrient-use efficiency of CPL in Year 1. In OSP, we found greater C content in live leaves and greater P content and lower C:P of leaf litter with lower P resorption in Year 1. We then explored the extent by which species group (CPL and OSP) and leaf type (live leaves and litter) differed within and among these groups with two-factor ANOVA by averaging values across years for each island for nutrient content and molar ratios (Table 3). We found significantly higher P and N content in OSP than CPL and in live leaves than litter. N:P of CPL leaves was not different from OSP leaves, but litter N:P greatly exceeded N:P of live leaves. We found higher C:N ratios of CPL and leaf litter, and CPL leaf litter had significantly higher C:N ratios than any other OSP*type combination (77  2). We also found higher C:P ratios in CPL and in leaf litter. We performed a similar analysis with resorption efficiency values, but replaced the second factor of leaf type with nutrient type (phosphorus and nitrogen) since these values incorporate both leaf types, and percentages give normalized values with which to compare nutrient types. We found significantly higher nutrient resorption in CPL and greater phosphorus resorption than nitrogen resorption (F = 18.39, p = 0.0004, d.f. = 1, n = 6 and F = 227.41, p = <0.0001, d.f. = 1, n = 6, respectively). There was also a species  nutrinutrient effect where CPL had the greatest P resorption (F = 5.37, 0.0312, d.f. = 1, n = 6). 3.5. Soil characteristics

0.030 (0.003) 0.995 (0.034) 50.324 (0.139) 84 (10) 61 (2) 5157 (574)

Resorption efficiency %P 50 (3) %N 35 (2) Island Nutrient use efficiency P 4005 (199) N 122 (2)

0.024 (0.003) 0.971 (0.035) 50.828 (0.265) 108 (10) 63 (3) 8035 (1499)

*

64 (4) 30 (3)

*

4300 (186) 112 (3) 1

* *

*

Nutrient-use efficiency values (g g ) are annual averages; otherwise, values represent monthly averages.

Bimonthly soil pH averaged 6.43  0.1 to 6.74  0.01 and 5.67  0.4 to 6.46  0.08 in Year 1 and Year 2, respectively. This translated into significantly higher pH in Year 1 ( p = 0.0277, n = 6). Soil temperatures in any given month were relatively consistent among islands. However, we found significantly lower soil temperature in Year 1 ( p = 0.0277, n = 6). Soil oxidation–reduction potential (Eh) values varied among wet and dry season months, but not consistently. Monthly averages of all six islands varied between 7  46 and 414  50 mV in December 1999 and July 2000 of Year 1, but varied between

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Table 3 Nitrogen, phosphorus, and N:P molar ratios of live leaves, leaf litterfall, and fine litterfall Nutrient

Species

Type

Value x (S.E.)

Species F

%P

ci Other

%N

ci Other

N:P

ci Other

C:N

ci Other

C:P

ci Other

species  type

Type P

F

P

F

P

Livelvs Litter Livelvs Litter

0.052 0.016 0.068 0.027

(0.001) (0.001) (0.003) (0.003)

40.58

<0.0001

324.42

<0.0001

1.08

0.3112

Livelvs Litter Livelvs Litter

1.169 0.740 1.494 0.983

(0.015) (0.022) (0.036) (0.026)

120.81

<0.0001

329.90

<0.0001

2.51

0.1285

Livelvs Litter Livelvs Litter

52 (2) 112 (5) 49 (3) 96 (9)

91.91

<0.0001

1.52

0.2327

Livelvs Litter Livelvs Litter

48 77 40 62

314.79

<0.0001

6.65

0.0179

Livelvs Litter Livelvs Litter

2579 8664 2068 6596

96.34

<0.0001

2.08

0.1652

(1) (2) (1) (2)

3.00

63.43

(137) (351) (130) (1005)

5.69

0.0985

<0.0001

0.0271

Island averages across island groups and years to examine patterns among and within species and leaf types (n = 6); August 1999–July 2001.

219  34 and 44  49 mV in February 2001 and June 2001 in Year 2, respectively. The high standard error for all Eh measurements was because of large differences between Flow and No Flow islands, and this variation was consistent between the island groups. The No Flow islands nearly always had positive soil Eh values, indicating less reducing conditions in these islands throughout each year. Overall, the average island soil Eh value indicated relatively oxidized conditions when compared with values for marsh soil Eh ( 200 mV; Childers, unpublished data). Tree island soils had very high organic matter content (85–91%). Soil bulk density was low (0.28  .01 g cm 3) and soil moisture content averaged 76  1% in August 1999. Island soil TP was high relative to soil marsh TP (islands: 466  34 mg P g 1 soil, marsh: 78  13 mg P g 1 soil; F = 75.675, p = 0.0010, n = 6). Correcting TP values for bulk density, island average TP content by volume was 129  15 mg P cm 3 and marsh TP content was 69  12 mg P cm 3. We also found high island soil N content (23  1 mg N g 1) when compared with

marl soils of our study area (4  l mg N g 1; F = 312.532, p < 0.0001, n = 6), and the No Flow islands had relatively higher soil N. Overall, the islands showed less variation in soil carbon concentration (430  12 mg C g 1 soil) than in N concentration. However, TC content co-varied with TN content in tree island soils (r2 = 0.55; p = 0.0005, n = 6). We also found significantly higher TC concentration in tree island soils than marsh soils (F = 239.957, p = 0.0001, n = 6). Soil nutrient ratios provide an indication of nutrient limitation to soil processes (Bedford et al., 1999). Overall, the average soil N:P molar ratio was 113  8, suggesting strong P limitation of soil processes. Soil C:N molar ratios reflected high soil organic N (average: 22  2), and were relatively higher in Flow islands. Average soil C:P molar ratios were 436  34. Porewater dissolved nutrient (NH4+, NO3 , NO2 , and SRP) and organic carbon concentrations reflected low nutrient availability (high demand) in tree island soils. Porewater NO3 and NO2 concentrations were very low (NO3 = 0.12  0.02 mM, NO2 = 0.15  0.01 mM) and NH4+ concentration, the dominant

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nitrogen constituent, was also low (NH4+ = 3.97  0.72 mM). SRP concentrations were low (0.03  0.00 mM), also indicating low P availability in soils. Porewater DOC concentrations were high (2935  521 mM), and this was the only dissolved constituent to vary among island groups—No Flow islands had consistently higher porewater DOC values throughout the year. Although porewater nutrients did not vary significantly throughout the year, we found the highest concentrations of NO2 , SRP, and DOC in August, and the highest concentrations of NH4+ and NO3 in December. 3.6. Hydrology Tree island water levels (annual average and wet season) and hydroperiod values were variable between years. Year 1 average water levels exceeded Year 2 ( p = 0.0277, n = 6), but average wet season water levels were greater in Year 2 ( p = 0.0277, n = 6). Interestingly, despite lower Year 1 wet season water levels, hydroperiod in Year 1 was 4 months longer than Year 2 ( p = 0.0277, n = 6). We calculated marsh hydroperiod from both USGS and SFWMD daily water level stations. We found longer average hydroperiod in the marsh of the No Flow islands (10 months) than the Flow islands (9 months) and longer marsh hydroperiod in Year 1 (11 months) than Year 2 (8 months). Based on regression relationships shown in Table 1 (refer to Section 2), we determined that Flow islands exhibited less difference in elevation from the marsh surface (i.e. when water level at marsh surface = 0 cm, average island water level = 4  1 cm (average zvalue for CT50 station in Table 1)). Whereas, No Flow islands averaged 14 cm above the marsh surface elevation (i.e. when water level at marsh surface = 0 cm, average island water level = 14  1 cm (average z-value for EVER7 station in Table 1)). Thus, No Flow islands were approximately 10 cm higher in elevation above marsh water levels than Flow islands. 3.7. Marsh water chemistry and nutrient loads We quantified marsh soil porewater nutrient concentrations and surface water nutrient loads relative to specific islands within the landscape to

assess how these marsh parameters related to island structure and function. As with tree islands, marsh porewater NO3 and NO2 concentrations were low (0.10  0.05 and 0.13  0.02 mM, respectively). NH4+ also dominated the dissolved inorganic nitrogen pool in marsh porewater, but was in considerably higher concentration than in tree island porewater (50.73  11.88 mM; F = 15.765, p = 0.0033, d.f. = 1, n = 6). Porewater DOC concentrations were lower and showed less spatial variability in the marsh than in tree islands (1142.43  40.47 mM; F = 9.643, p = 0.0126, d.f. = 1, n = 6). Marsh SRP concentrations were approximately half that found in islands, but these low concentrations were not significantly different from island concentrations (0.01  0.01 mM). We measured surface water nutrient concentrations (TN, TP, and TOC) throughout the wet season and calculated nutrient loading using flow rates measured at each island. The wet season average TN and TP concentrations in surface water were 33.3  1.9 mM TN and 0.23  0.01 mM, respectively. Total N concentrations tended to decrease through the wet season while TP concentrations increased, as surface water N:P molar ratios declined to the lowest values in August (64  6). Wet season TOC concentrations averaged 838.1  32.9 mM, and were relatively higher in the marsh of the No Flow group. Marsh surface water flow typically occurred from June to December, when C-111 canal water levels exceeded marsh soil level. We measured the highest marsh water flow rates at peak wet season in October (1.3  0.2 cm s 1). Average flow was 0.8  0.1 cm s 1 for months when water was flowing through the marsh, and we noted higher flow rates in the Flow island group. Total nutrient and carbon loads to tree islands increased as flow rates and water levels increased in the wet season. Total N loads averaged 1.7  0.3 g N m 2 d 1 in July, and increased to 82.6  7.3 g N m 2 d 1 in October. A similar pattern was found for TP and TOC. Total phosphorus loads averaged 0.03  0.00 g P m 2 d 1 in July and 3.0  0.2 g P m 2 d 1 in October. TOC loads in July averaged 42.2  8.0 g C m 2 d 1 and increased to 3317  243 g C m 2 d 1 in October. Average TN, TP, and TOC loads over all wet season months were 34.6  2.2 g N m 2 d 1, 1.0  0.1 g P m 2 d 1, and 1799  122 g C m 2 d 1, respectively. TP and TOC

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loads were significantly higher in the marsh of the Flow islands. Notably, however, TOC had higher concentrations in the marsh of the No Flow islands. Dissolved inorganic nutrient and organic carbon concentrations of marsh surface water were similarly measured and loads were calculated. Average NO3 concentrations were seven times greater than values measured for marsh porewater (0.74  0.07 mM) while NO2 and SJAP concentrations more closely approximated marsh porewater concentrations (0.07  0.00 mM and 0.02  0.00 mM, respectively). NH4+ concentrations were about twice the concentration of NO3 found in marsh surface water (2.03  0.24 mM), and were higher in the No Flow group. Marsh surface water NH4+ concentrations approximated tree island porewater concentrations, but were much lower than marsh porewater concentrations (25). Averages for marsh surface water DOC concentrations were 784.02  10.90 mM. Whereas dissolved inorganic nitrogen concentrations were lower in the marsh surface water of the Flow islands, nitrogen loading rates revealed an opposite trend. However, only NO2 loading rates were higher in the Flow island group. Overall, inorganic nitrogen loading represented 16% of the total nitrogen load (5.45  0.45 g N m 2 d 1). Average SRP loading rates were 0.11  0.01 g P m 2 d 1. While DOC concentrations did not vary between island locations, DOC loads to the Flow islands were relatively higher (average: 1578.67  149.04 g C m 2 d 1).

4. Discussion 4.1. Vegetation Tree islands were dominated by evergreen species suggesting that soils are characterized by relatively low fertility (Aerts, 1995; Aerts et al., 1999); the primary dominant was CPL (C. icaco). This was consistent with other species found in the Everglades, a landscape characterized as P-limited (Steward and Ornes, 1975; Noe et al., 2001; McCormick et al., 2001). CPL generated the bulk of annual leaf litterfall production. Species contribution to litterfall production varied throughout the year (Fig. 2c). There was no clear seasonal pattern in litterfall production, suggest-

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ing litterfall patterns may be controlled by other factors (e.g. maximum temperatures, Kouki and Hokkanen, 1993; prolonged dry down, Read and Lawrence, 2003). While overall vegetation cover was similar between island groups, we found relatively greater CPL canopy cover in the Flow group. CPL has been found to tolerate a range of hydrologic conditions (Nelson, 1994), but is likely one of the most water tolerant of the tree island canopy species found. Variability in species co-dominance between island groups may have followed variability in: hydroperiod or soil microtopography (suitable microsites, Duncan, 1993; Nicotra et al., 1999), seed dispersal mechanisms (Jansson et al., 2000), seed viability (Barbour et al., 1999), or successional processes of tree island species. 4.2. Within-stand phosphorus and nitrogen cycling Tree island soils were highly organic and appeared to immobilize nitrogen and phosphorus as indicated by low C:N and moderately high P relative to unenriched Everglades peat soils (Childers et al., 2003). The N:P of soils was high (113  8) because of high soil N content, but still lower than the soil N:P of Everglades peat marshes (Noe et al., 2001). In contrast, relative to adjacent marshes, porewater nutrient concentrations of NH4+, NO3 , NO2 , and SRP were very low in tree island soils but simultaneously maintained high DOC. High N and P in island soils may have been due to immobilization by microbial activity or adsorption and did not appear to be an indication of N or P availability to plants. This was supported by several indices of nutrient utilization (Killingbeck, 1996; Koerselman and Meuleman, 1996; Aerts et al., 1999) indicating efficient use of both N and P by tree island plants, but most efficient use of P (Tables 2 and 3). High N and P in island soils, low porewater N and P, and low N and P availability to plants therefore suggested ecosystem-level immobilization in these tree islands (Verhoeven, 1986). We hypothesize that phosphorus limits plant productivity in southern Everglades tree islands. The N:P ratio of CPL live leaves and litter was consistently above 36 (molar ratio threshold) suggesting that this species was P-limited (Koerselman and Meuleman, 1996; Lockaby and Conner, 1999; Table 2). This was supported by other indices, including resorption

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efficiency and phosphorus nutrient-use efficiency (P NUE; Table 2). Resorption efficiency suggested that OSP found in tree islands did not utilize P as efficiently as CPL. This may have been a result of deciduous species present in the litterfall (leaf senescence in these plants occurs while the leaf is still capable of photosynthesis; Killingbeck, 1996). Senesced leaves of OSP had higher average P than senesced leaves of CPL (0.027 and 0.016% P, respectively; Table 3). Phosphorus NUE (Vitousek, 1984) includes both annual litterfall production and litterfall nutrient content, and as such is a comprehensive, ecosystemlevel index of nutrient utilization in plants. Our values for P NUE in tree islands also supported efficient use of P in these communities (Table 2; above 2000 g g 1; Brown, 1990). Several indices suggested that plant species were also utilizing nitrogen efficiently. Although CPL showed lower N resorption efficiency than P resorption efficiency, and OSP were about half as efficient as compared with P resorption efficiency, N NUE values for total litter were approximately 120 g g 1 showing efficient use of N (Brown, 1990).

4.3. Nutrient economy and comparison with other forested wetlands We conducted a review of nutrient use and litterfall values for forested wetlands to ascertain whether tree islands exhibited typical values or followed general trends found across latitudinal gradients. Literature values for annual litterfall production, P NUE, and N NUE of subtropical/tropical and temperate swamps are given in Table 4. In the analysis, we did not consider riverine wetland types, but included those of floodplain forests that were more similar to seasonal flooding cycles in the Everglades. We found that tree islands of the southern Everglades more efficiently utilized phosphorus than did all other tropical and temperate forested wetlands, but exhibited similar nitrogen nutrient-use efficiency as the average for temperate forests. In addition, litterfall production approximated that of most other seasonally flooded wetland forests in the tropics, but exceeded average values for temperate systems.

Table 4 Litterfall and litterfall nutrient use efficiency of sub-tropical/tropical and temperate forested wetlands Forest type/location

Litterfall g m 2 year

Sub-tropical/tropical Tree Islands, Everglades Montane floodplain forest, PR Floodplain forest, Australia Varzea (seasonally flooded) forest, Brazil Igapo (blackwater) forest, Brazil Evergreen seasonal forest, Colombia Evergreen seasonal forest, Pantanal c Evergreen seasonal forest, NE Brazil

627 869 767 900 780 870 900 837

Temperate Cypress dome, N FL Cypress swamp, GA Natural swamp, LA (leaf litter) Alluvial swamp, NC Bottomland hardwood forest, SCd Temperate swamps, VAb Cedar swamp and marginal fen, MN (avg)

461 328 715 643 432 210 450

1

N NUE gg 1

P NUE gg 1

Cite

117

4200 3448 2051 2647 2294 2559 667 2462

Present study Franji and Lugo (1985) Greenway (1994) Klinge (1977) a Klinge (1977) a Folster and de las Salsas (1976) a Haase (1999) Sampaio et al. (1988) in Haase (1999)

2134 2470 1669 1195 713 1355 710

Brown (1978); Deghi et al. (1980) Schlesinger (1978) Conner and Day (1992) c Brinson et al. (1980) Burke et al. (1999) Gomez and Day (1982) b Reiners and Reiners (1970) b

113 94 71 84 62

121 167 88 104 82 104

Tropical

819

90

2541

Temperate

463

111

1464

a b c d

Vitousek (1984). Brown (1990). Lockaby and Conner (1999). Average, n = 4.

b

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With this comparison, it is clear that trends of phosphorus NUE in Everglades tree islands reflect trends more typical for tropical wetland forests. However, trends for nitrogen NUE follow those of temperate wetland forests, which, depending on substrate (organic or mineral), are generally N-limited (Bedford et al., 1999). While the P deficient status of Everglades wetlands are highly influenced by the carbonate substrate, soil pH within the islands is lower than that of the marsh (marsh often exceeding 7.5), reflecting how this wetland ecosystem modifies local soil chemistry. High organic matter accumulation and, consequently organic nutrient accumulation, may be important in controlling total soil nutrient concentrations in seasonally flooded tree island soils Verhoeven, 1986; Fig. 3). Bedford et al. (1999), in a review of temperate wetland literature, suggested that nutrient efficiency in swamps was, in part, controlled by organic matter content in the soil and soil nutrient availability. They found that leaves and litter of plants growing in peat wetlands had higher N:P ratios (28 and 26 for leaves and litter, respectively; ratio threshold = 16) than did plants growing in mineral soils (17 and 14 for leaves and litter, respectively), suggesting that plants growing on wetland peat soils more efficiently utilize phosphorus. Walbridge (1991) found high resorption of phosphorus and nitrogen of bay species in pocosin evergreen shrub bogs of North Carolina, communities existing on soils with greater than 90% organic matter. Clawson et al. (2001) showed that ‘‘poorly drained’’ and ‘‘somewhat poorly drained’’ forests more efficiently cycled N and P than ‘‘well drained’’ forests. Our results follow the generalizations of these authors as we found high

Fig. 3. Nutrient cycling in seasonally flooded tree islands: low remineralization of nutrients appears to limit the availability of inorganic nitrogen and phosphorus in soil porewater and tree island plants.

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nutrient-use efficiency on highly organic seasonally flooded tree islands. 4.4. Inter-annual hydrologic variation and nutrient dynamics: establishing baseline conditions for a large-scale, long-term ecosystem experiment In our ecosystem, scale characterization of seasonally flooded tree islands in the southern Everglades, we noted evident differences between Flow and No Flow island groups. For example, we found notable variation in island parameters including soil Eh, litter turnover rates, soil N content, soil porewater DOC, and average water levels. For marsh parameters, we found notable variation in marsh flow rates, surface water concentrations of TOC and NH4+, and marsh TP, TOC, NO2 , and DOC loads. We interpret these differences as indicators of potentially responsive tree island and marsh variables. However, we restricted our statistical comparisons of hydrologic effects to interannual hydrologic differences because islands within flow treatments could be viewed as pseudo-replicated in space. Therefore, we will address this complication in future analyses by utilizing these data to interpret the results of our long-term flow experiment in two unique ways: (1) by incorporating the results of a third flow treatment in which we experimentally block freshwater flow, and (2) by utilizing these data to establish a baseline from which to examine the trajectories of ecosystem response to the restoration of freshwater flows. We not only found significant year-to-year variation in water management that could be explicitly related to select soil properties and nutrient cycling in tree island plants. Increased hydroperiod, higher average water levels, and lower wet season water levels in Year 1 helped to explain variation we saw in phosphorus and nitrogen cycling. In Year 1, we found greater P content in CPL leaves, and lower N content (and higher N resorption and C:N ratio) in CPL leaf litter, yielding greater nitrogen NUE in Year 1. This result suggests greater N utilization with longer hydroperiod and less extreme within-year hydrologic dynamics. Extended and less dramatic hydroperiod may allow more P to be sequestered within the islands, allowing a greater pool of P to be cycled within the plants, and greater utilization of N sources (Reddy

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et al., 1999). Studies in mangrove systems of south Florida suggest a tight relationship between P and N, where higher P in soils translated to greater N use, however these findings were not explicitly tied to mangrove hydrology, but to natural P gradients (Chen and Twilley, 1999). Another plausible explanation suggests that longer hydroperiods with less dramatic shifts in water levels may reduce N mineralization (less oxidation of organic N), increase denitrification (spatially variable oxygen production with plant rhizophere oxidation), or increase N demand (more N necessary for adventitious root growth or other adaptations to water logging) necessitating greater resorption of N before senescence of CPL leaves. This alteration in CPL litter quality could have important implications for tree island development. Both longer hydroperiods and delivery of more recalcitrant CPL leaf litter (higher C:N ratio) to the forest floor may interact to reduce decomposition, allow greater peat accumulation, and may reflect an intermediate state of ecosystem succession. This process may counteract extreme hydrologic variability that could permit periodically dry conditions and, consequently, oxidation of tree island soils or infiltration of the canopy by fire. Thus, the development of island humidity levels that prevents soil oxidation and facilitates fire exclusion may characterize steady state conditions in seasonally flooded tree islands. It is important to note that in a short hydroperiod system characterized by seasonal delivery of water, periodic mineralization would be expected to occur. However, these results suggest that an important and positive indicator of tree island maintenance may be the balance of hydroperiod and wet season water levels. 4.5. Landscape context—tree island and marsh comparisons The tree islands of the southern Everglades are visually distinct from the surrounding marsh landscape. This difference was clearest in vegetation structure, which translated into striking differences in standing biomass and litter accumulation. The marsh landscape was typified by phosphorus-poor, carbonate-rich soils, and low macrophyte biomass (Childers, 2001). Most notable, however, was that these clear

structural differences were associated with significant differences in biogeochemical properties between tree islands and the marsh landscape, specifically in the relative sizes of total and available nutrient pools (Table 3). We found significantly greater soil TP and TN in island soils when compared with marsh soils, but also found lower NH4+ in island soil porewater than in marsh soil porewater. A similar pattern was found for alpine tundra tree island soils, in that, as these mobile islands moved across the landscape over time with short-term climatic processes, there was a reduction in NH4+ of landscape soils influenced by tree island passage (Seastedt and Adams, 2001). In both studies, greater nitrogen utilization (or lower N availability) may have been a result of several factors including: (1) higher nitrogen demand for plants that accumulate considerably more standing biomass than plants of the landscape matrix (Salisbury and Ross, 1992); (2) nitrogen accumulation in the organic soils of tree islands by microbial fixation or adsorption (Mitsch and Gosselink, 2000) and subsequent low mineralization of organic matter; (3) nitrogen export from tree island soils via denitrification mediated by spatially and temporally variable soil oxygen availability (i.e. rhizophere oxygenation by plants or fluctuating hydroperiod; Mitsch and Gosselink, 2000); or (4) some combination of these processes. In addition, dissolved nutrient and carbon concentrations show a clear concentration gradient in island porewater and marsh surface water. If water flowing into tree islands is predominantly marsh surface water, this concentration gradient likely indicates diffusion across this interface and shows that tree islands are a source of DOC, a sink for NO3 , and at steady state for concentrations of SRP and NH4+ (Twinch and Peters, 1984). Thus, seasonally flooded tree island ecosystems may maintain differential mechanisms for nutrient limitation. Tree island vegetation appears to be P limited resulting from the free carbonates that bind available P and the immobilization of organic P in tree island soils. Microbial processes are more likely N limited due to high organic matter accumulation and low decomposition rates (low N mineralization; Verhoeven, 1986; Fig. 3). However, the influx of carbonate-rich, high pH water via surface water and groundwater may increase nitrification rates, thus

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providing substrate for enhanced denitrification (Zhu and Ehrenfeld, 1999). In the Everglades landscape of low stature graminoids, the nutrient status of these insular systems may be influenced by the load of other externally-derived nutrients, also hydrologicallymediated, or from concentrated animal inputs, which may determine how these systems interact with the hydrology and/or nutrient cycling of the landscape (McCarthy and Ellery, 1994). 4.6. Potential ecological trajectory responses This study sets the baseline conditions for which we will examine the ecosystem trajectory response of key parameters describing tree island ecological structure and ecosystem function. Inter-annual hydrologic variation described several responsive parameters and some differences were noted relative to islands in Flow and No Flow groups. In that context, we hypothesize that the ecological structure and function of seasonally flooded Everglades tree islands are dependent on the timing, quantity, and potentially, quality of water delivery. With persistent (year-toyear) and punctuated wet season water delivery, abiotic soil conditions (increased temperature and decreased pH) may promote the mineralization of organically bound phosphorus and nitrogen in soils, increasing loads of nutrients downstream. This episodic water delivery also appears to reduce P availablity to cocoplum plants potentially because it is mineralized from soils and flushed from the system, resulting in annually lower P concentrations in live tissue, and higher N concentrations in senesced tissue (lower N utilization). Overlaying inter-annual hydrologic conditions on baseline parameters we observed to differentiate Flow and No Flow islands, episodic water delivery may have a greater effect on Flow islands (due to their lower position in landscape) than No Flow islands, but would ultimately shift No Flow islands to conditions more like baseline Flow islands. This shift may be indicated by decreased soil Eh, increased litter turnover rates, decreased soil TN, and decreased soil porewater concentrations of DOC in No Flow islands with a greater shift in the baseline conditions of Flow islands. These shifts could have significant implications for landscape nutrient cycling as the islands would likely be transformed from nutrient sinks to nutrient sources.

25

5. Conclusions Seasonally flooded tree islands are wetland habitats that exhibit biogeochemical processes not found in the wider marsh landscape. Tree islands maintain large pools of organic nutrients with low available nutrients while adjacent marshes maintain small pools of organic nutrients with relatively larger pools of inorganic nitrogen. Thus, this study lends support for hypotheses describing ‘‘hot spots’’ of biogeochemical cycling in the landscape (McClain et al., 2003), where sites of maximum biogeochemical activity occur relative to the landscape in general. This phenomenon suggests that tree islands are important in nutrient cycling in the Everglades wetland landscape. If this is a ubiquitous feature of Everglades tree islands, the tree island loss found in some area of the Everglades (Patterson and Finck, 1999) may thus have had a significant effect on the total load of nutrients that move through the system, potentially exacerbating the effects of reduced freshwater flows. This scenario is further complicated by evidence suggesting that year-to-year hydrologic variation affects nitrogen cycling within seasonally flooded tree islands. Future studies should examine mechanisms for nutrient efficiency in tree island plants, rates of nutrient cycling within tree island soils, and the biogeochemical interactions between tree islands and adjacent marshes (especially nitrogen). It will also be important to characterize ecological differences and explicit relationships among ecological structure, nutrient dynamics, and hydrology in other systems of similar tree island-wetland landscape mosaics to understand whether these results are specific to Everglades tree islands. This study is also useful as it: (1) provides baseline information with which to examine ecosystem trajectory responses of tree islands associated with hydrologic restoration in the course of long-term landscape-scale research in Everglades marshes, and (2) supports the hypothesis that tree islands increase ecological complexity in wetland landscapes.

Acknowledgments We would like to thank the Wetland Ecosystems Ecology group for field and lab support, as well as

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helpful reviews of this manuscript. We are also grateful for the comments of three anonymous reviewers. This research was supported by the South Florida Water Management District under several sequential contracts, and by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research Program (DEB-9901514). The FIU Tropical Biology Program and Graduate Student Association also provided financial assistance.

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