Wetlands (2014) 34:67–77 DOI 10.1007/s13157-013-0483-0
ARTICLE
Recent Trends in Satellite Vegetation Index Observations Indicate Decreasing Vegetation Biomass in the Southeastern Saline Everglades Wetlands Douglas O. Fuller & Yu Wang
Received: 4 June 2013 / Accepted: 17 September 2013 / Published online: 5 October 2013 # Society of Wetland Scientists 2013
Abstract We analyzed trends in time series of the normalized difference vegetation index (NDVI) from multitemporal satellite imagery for 2001–2010 over the southeastern Everglades where major changes in vegetation structure and type have been associated with sea-level rise and reduced freshwater flow since the 1940s. Non-parametric trend analysis using the Theil-Sen slope revealed that 84.4 % of statistically significant trends in NDVI were negative, mainly concentrated in scrub mangrove, sawgrass (Cladium jamaicense) and spike rush (Eleocharis cellulosa) communities within 5 km of the shoreline. Observed trends were consistent with trends in sawgrass biomass measurements made from 1999 to 2010 in three Long-term Ecological Research (LTER) sites within our study area. A map of significant trends overlaid on a RapidEye high-resolution satellite image showed large patches of negative trends parallel to the shoreline in and around the “white zone,” which corresponds to a low-productivity band that has moved inland over the past 70 years. Significantly positive trends were observed mainly in the halophytic prairie community where highly salt tolerant species are typically found. Taken as a whole, the results suggest that increased saline intrusion associated with sea-level rise continues to reduce the photosynthetic biomass within freshwater and oligohaline marsh communities of the southeastern Everglades.
Keywords MODIS NDVI . Non-parametric trend analysis . Sawgrass marsh . Mangroves . Above-ground biomass production
D. O. Fuller (*) : Y. Wang Department of Geography and Regional Studies, University of Miami, Coral Gables, FL 33124-2221, USA e-mail:
[email protected]
Introduction Coastal wetlands provide a range of essential ecosystem services such as carbon sequestration, protection from erosion, and maintenance of water quality (Webb et al. 2013). Sea-level rise and associated intrusion of salt-water into oligohaline wetland systems can negatively affect primary productivity of wetland plants such that organic accretion rates in marshes may not keep pace with rising water levels and increased salinities (Neubauer 2008, 2013; Barendregt and Swarth 2013). The inundation of coastal wetlands by rising seas may affect as much as 195,000 km2 of tropical and temperate tidal marshes globally (Greenberg et al. 2006; Spalding et al. 2010). A number of large coastal wetland areas are considered especially vulnerable to increased salinity, subsidence, and reduced plant productivity, including the Nile Delta (Hassaan and Abdrabo 2013), major river deltas of China such as the Pearl and Yangtze (Wang et al. 2012), the Sundarbans of Bangladesh and India (Loucks et al. 2010), as well as large areas of eastern North America, Europe and the Gulf of Mexico (Baldwin and Mendelssohn 1998; Neubauer 2008; Couvillion and Beck 2013). One of the most well-studied coastal wetland ecosystems is the Everglades located on the southern tip of the Florida Peninsula, USA (Egler 1952; Craighead 1968; Davis et al. 2001; Childers et al. 2003; Foti et al. 2013). Vegetation productivity in this oligotrophic subtropical wetland is closely linked to a variety of factors including salinity, nutrient loading, hydroperiod, and surrounding land uses (Ross et al. 2000; Childers et al. 2006). Since 1930, the rate of sea-level rise in South Florida has increased above historical rates and is expected to result in sea-level rise of approximately 60 cm later this century (Wanless et al. 1994). Over the same time period, South Florida’s water management system has greatly reduced the freshwater flow in the major sloughs through which the bulk of freshwater flows to Florida Bay and the
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Gulf of Mexico (Fig. 1). The freshwater marshes within and around the sloughs typically contain significant areas of sawgrass (Cladium jamaicense ), spike rush (Eleocharis cellulosa ), tropical hardwood hammocks, and bayheads, which are comprised mainly of freshwater shrubs such as Annona glabra, Chrysobalanus icaco, and Ilex cassine. In the oligohaline estuarine zone, scrub and tall mangrove communities with red mangroves (Rhizophora mangle), white mangroves (Laguncularia racemosa), and black mangroves (Avicennia germinans), which are interspersed with buttonwood (Conocarpus erectus) stands, salt marshes, and woody hammocks (Sternberg et al. 2007). This mangrove-dominated zone constitutes a significant area of bio-sedimentary substrate accumulation. However, with increasing rates of sea-level rise expected this century, Davis et al. (2005) hypothesized that saline intrusion will result in further inland migration of the so-called “white zone”—a band of diminished vegetation productivity consisting of sparse mixed mangroves and graminoid vegetation that represents the inland edge of the oligohaline ecotone, which runs roughly parallel to the shoreline (Ross et al. 2000). Near shore, elevated salinity in surface and soil water is associated with halophytic prairies dominated by herbaceous species such as Salicornia spp., Batis maritima, and Blutaparon vermiculare, which may also become established when tropical storms have damaged and killed mangrove and buttonwood stands (Armentano et al. 1995; Davis et al. 2005). Further, salinity increases have been noted in the formerly oligohaline mangrove zone and as well as saline intrusion in the former freshwater marshes and ground water of the southern Everglades (Ross et al. 2000, 2002). Thus, the productivity of Everglades marsh and mangrove species is strongly influenced by salinity gradients and flushing by fresh and saltwater over different time scales (Childers et al. 2006; Barr et al. 2013). For example, Macek and Rejmánková (2007) found that plant height and shoot/root biomass decreased in C. jamaicense and Eleocharis cellulosa under conditions of elevated salinity. Barr et al. (2009) showed that carbon assimilation in mangrove leaves was limited when salinity exceeded 35 parts per thousand. In the absence of regular flushing by either fresh or brackish waters, Wanless and Vlaswinkel (2005) observed that marsh communities can collapse—a phenomenon has also been noted in mangrove communities that have been migrating inland in recent decades (Davis et al. 2005). Therefore, even relatively salt-tolerant communities may decline as a result of elevated salinity in the southern Everglades. Systematic estimates of above-ground biomass and culm density have been made in 16 marsh sites in the southern Everglades since 1998 as part of the Florida Coastal Everglades Long-term Ecological Research (FCE LTER) sampling network (Childers et al. 2006; Ewe et al. 2006). These data provide an important baseline for understanding long-term behavior of sawgrass and spike rush communities in relation
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to salinity, nutrient loading, and hydrological drivers. For example, Childers et al. (2006) showed that above-ground net primary productivity (ANPP) in these sawgrassdominated communities was negatively related to surface water salinity measured continuously in the Taylor Slough, while more the more hydric spike rush communities possessed higher biomass in sites with long hydroperiods and elevated water levels. While site-level monitoring of biomass has provided critical understanding of ecosystem processes that control photosynthesis in the southern Everglades, productivity data from satellite observations may be used to assess recent fluctuations and trends in biomass and vegetation cover. In particular, sums of the normalized difference vegetation index (NDVI) obtained from red and near infrared reflectance provide a direct measurement of the fraction of absorbed photosynthetic activity (Goetz et al. 1999) as well as indirect measures of gross and net primary productivity, biomass, and green leaf area in a variety of grassland and forest ecosystems (Green et al. 1997; Paruelo et al. 1997; Myneni et al. 2001; Pineiro et al. 2006; Wessels et al. 2008; An et al. 2013; Barr et al. 2013). Since mid-2000, global NDVI data have been available at 250 m spatial resolution from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the polarorbiting Terra Satellite operated by the National Aeronautics and Atmospheric Administration (NASA). As NDVI image archives have grown over the past three decades, various timeseries techniques have been applied to these data to identify multi-year trends that may relate to variety of anthropogenic and biophysical factors (Fuller 1998; Herrmann et al. 2005; de Jong et al. 2011, 2013). In this study, we exploit 10 years of MODIS 250 m NDVI imagery covering South Florida to map decadal-scale trends, which we relate to vegetation type and ground-level measurements made in sawgrass sites in the southern Everglades National Park (NP). Our objective, therefore, was to identify statistically significant trends and explain these in terms of current understanding of environmental factors that control ANPP in the southern Everglades ecosystems. Our study area is centered over the Taylor Slough, which is the second-largest flow-way for surface water in the Everglades and stretches approximately 30 km along the eastern boundary of the Everglades NP (Fig. 1).
Data and Methods We obtained 2001–2008 version 5 MOD09Q1 250 m 8-day reflectance imagery for MODIS bands 1 (620–670 nm) and 2 (841–876 nm) covering South Florida from the Website https://lpdaac.usgs.gov/get_data/reverb. These data were used to create a temporal sequence of 8-day NDVI images such that each year in our time series contained 46 NDVI
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Fig. 1 Map of the study area showing the location of the Taylor Slough, Everglades National Park, and biomass sites used to assess signifiance of Sen-Theil Slope applied to NDVI images from 2001 to 2010
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composite images, thus providing sufficient temporal resolution to evaluate changes in photosynthetic activity throughout the year. The annual sum of NDVI, which is used as a proxy for ANPP (Wessels et al. 2008), was calculated for each year (as the growing season is 12 months in the Everglades) and the Theil-Sen slope was calculated for each pixel along with slope significance (Theil 1950, Sen 1968). TS slope is the median of slopes calculated between observations X j and X i at pairwise time steps t j and t i X j −X i TS Slope ¼ Median t j −t i The TS slope is therefore non-parametric and robust against outliers (Neeti and Eastman 2011). We therefore did not attempt to smooth the NDVI time series, which is sometimes done to eliminate high-frequency noise (e.g., de Jong et al. 2011). Further, we calculated trends based on annual sums, which eliminated any serial autocorrelation present in the 8-day time step. To assess the significance of TS slopes, we employed a modification of the Mann-Kendall test, which uses Kendall’s S : s¼
n n−1 X X
sign xi −x j
i¼1 j¼iþ1
and 8 < 1 if xi −x j < 0 0 if xi −x j ¼ 0 sign xi −x j ¼ : −1 if xi −x j > 0 where n is the length of the time series and x i and x j are observations at time i and j respectively The equations for Mann Kendall significance (Z and p) are: 8 S−1 > pffiffiffiffiffiffiffiffiffiffiffiffiffiffi for S > 0 > > > Var ðS Þ > > < Z¼ 0 for S ¼ 0 > > > > Sþ1 > > : pffiffiffiffiffiffiffiffiffiffiffiffiffiffi for S < 0 VarðS Þ and p ¼ 2½1−∅ðjZ jÞ where ∅ () is the cumulative distribution function of a standard normal variate such that
2 ∅ðjZ jÞ ¼ pffiffiffi π
ZjZ j 0
e−t dt 2
Neeti and Eastman (2011) introduced a contextual Mann Kendall (CMK) approach as a way to incorporate local spatial variation of individual pixels with respect to their neighbors. The logic behind contextual analysis is that similar behavior (i.e., spatial autocorrelation) within small neighborhoods of pixels (e.g., 3 x 3) should produce greater confidence in trends. Neeti and Eastman (2011) also showed that this approach increased the number of pixels in satellite time series that have significant slopes. They define the CMK statistic Sm as Sm−E Sm Zm ¼ σ pffiffiffi = m
and 1X Sj m j¼1 m
Sm ¼
where m is the neighborhood size and Sj is Kendall’s coefficient for the jth neighbor, so that for a 3×3 neighborhood used here nðn−1Þð2n þ 5Þ Var Sm ¼ 18m Implementation of TS slope and CMK was done in Earth Trends Modeler software, which is part of the Idrisi Selva GIS software (Eastman 2012). To evaluate trends within different vegetation types, we utilized a highly detailed (1:15,000) digital vegetation map produced by Welch et al. (1999). Within our study area, the map contains 57 different dominant vegetation types, so to simplify the analysis we concentrated on seven major vegetation types that cover approximately 95 % of the terrestrial portion of our study area within Everglades National Park (shown in Fig. 1). These major vegetation types include mangrove forest (trees>5 m), mangrove scrub (trees and shrubs
