Upper Mississippi River Restoration Program

Upper Mississippi River Restoration Program

Long Term Resource Monitoring

 

Developing Indicators of Southern Bottomland Hardwood Forest Condition within the Upper Mississippi River Ecosystem


Introduction/Background:

The Upper Mississippi River (UMR) and its floodplain were hydrologically connected prior to European settlement (Sparks et al. 1998) and periodic floods linked the river channel to the floodplain (Galat et al. 1998), contributing to high ecosystem productivity and diversity (Junk et al. 1989, Ward et al. 2002). Further, these floodwaters supplied the floodplain with nutrients, water, and sediments, which influenced the fluvial geomorphological processes of this system (National Resource Council 2002). Because of this historic connectivity between the UMR main channel and its floodplain, species inhabiting this system are highly adapted to and dependent upon hydrologic regimes. The timing, periodicity, and extent of flooding events for nutrient cycling, migration corridors (Junk et al. 1989), dispersal avenues (Schneider and Sharitz 1988), and regeneration opportunities (Sharitz and Mitsch 1993, Yin and Nelson 1995, Sparks 1998) are important selective mechanisms that have shaped the evolution of floodplain species complexes. In forested portions of the floodplain, tree growth (Keeland and Sharitz 1995, Young et al. 1995), as well as litterfall and forest productivity are strongly related to hydroperiod, while net primary productivity of floodplain plant communities contributes a substantial portion of the detrital food web base, which supports both the aquatic and terrestrial components of the river-floodplain system (Vannote et al. 1980).

Today, many floodplain areas are no longer connected with the main river channel because of channel maintenance structures and levee systems (Rasmussen 1979; Barko et al. 2004a). This has caused erratic flood pulses ranging from continuous (e.g., impoundments) to inverted (Sparks 1998; Barko et al. 2004b). Forests in floodplains immediately upstream of a lock-and-dam station are often permanently flooded (Sparks et al. 1990), with reduced productivity (Young et al. 1995, Megonigal et al. 1997), shifts in species composition, loss of diversity (Yin and Nelson 1995), and high mortality if the stand is semi-permanently or permanently flooded (King 1995). Other areas have been dewatered and may no longer function as wetlands. Further, species that depend upon replenishment of sediments during flood pulses are declining (English et al. 1997), such as plants that require moist soil on mudflats to germinate and some shade-intolerant trees that require open sandbars for seedling establishment. Altered hydrologic regimes can also facilitate invasion of exotic species.

The goal of this project is to develop biological indicators for forested floodplains using structural and functional attributes of floodplain vegetation. Specific objectives include 1) development of vegetation-based indicators of bottomland hardwood forest condition using data collected from bottomlands located between UMR RM 0 - 364.4 and 2) field-testing these indicators for assessing bottomland forest health across the lower UMRS (IL, and MO). We define a healthy bottomland hardwood forest as one that maintains characteristic plant community structure and ecosystem function, has a high proportion of native to exotic species, and retains some degree of connectivity with the river.

Relevance of research to UMRS/LTRM:

The lack of bioassessment criteria, combined with a poor understanding of the ecological condition of UMRS bottomland forests, is a major impediment to our ability to assess the condition of this system. Development and application of flooded forest health indicators will enhance adaptive resource management (ARM) decision-making with respect to the needs of and the major threats to the UMRS by providing managers and researchers a means to quantify resources and evaluate their degree of function. Moreover, neither the LTRMP nor the EPA E-MAP routinely assesses floodplain forest health, so development of indicators would greatly facilitate biological assessments of these resources for both monitoring programs. Our goal is to identify metrics that will have general applicability for the southern portion of the UMRS focus area. We will include several HREP sites located within our focal reach, such as Bay Island (Pool 22) and Gardner Division (Pool 21), to evaluate their bottomland forest restoration success. The results of our project will provide a bottomland forest assessment tool that is essential to apply ARM in the UMRS.

Methods:

Site Selection

A criterion in choosing our set of sites for indicator development is that they include representatives of quasi-natural forest areas as reference sites, as well as those that have been moderately to highly degraded or disturbed (Brinson 1993). Indicators should prove useful for both identifying ecological characteristics of sites and describing the current range of bottomland forest conditions. Indicators we develop will be used to establish the current status against which future change, restoration efforts, and ARM can be evaluated. Study sites will be located within an area extending from UMR RM 0 - 364.4 and sites will be stratified based on impoundment status and whether they fit into reference or disturbed categories.

Proposed conservation areas based on the above criteria include Gardner Division, Adams Co., MO (Pool 21), Fox Island, Clark Co, MO (Pool 20), Horseshoe Lake Conservation Area, Alexander Co., IL (unimpounded), and Donaldson Point Conservation Area, New Madrid Co., MO (unimpounded). Gardner Division is an HREP site totaling 2549 hectares (ha) along river miles 332.5-340.2. Fox Island is an HREP site totaling 850 ha along river miles 353.6-358.5. Horseshoe Lake Conservation area is 4308 ha. Donaldson Point Conservation area is 2341 ha.

Field Sampling

There are few existing published data sets on floodplain plant communities in the UMRS, and indicators of the ecological integrity of the floodplain are needed to assess the condition of our current resources and provide a benchmark for future bottomland forest evaluation, restoration, and ARM. The first phase of vegetation indicator development will consist of data collection from field sites. Using aerial photos of each conservation area, we will grid the bottomland areas and divide them into two categories: reference and disturbed stands. We will randomly select five grid cells containing reference stands at each area (total = 20). Similarly, we will randomly select ten grid cells containing disturbed stands (i.e., not reference; total = 40). At each of the 60 selected grid cells, we will establish a 20 x 50 m plot, each with nested 100 m2, 9 m2, and 1 m2 subplots (Peet et al. 1998) for sampling structural and functional bottomland attributes. Use of nested plots is widespread in vegetation sampling and is considered to be an efficient approach for quantifying and comparing community structure and diversity.

Structural and compositional attributes are useful indicators for evaluating the ecological health of a system (NRC 2000). In each plot, we will measure plant community attributes including native species richness and number and abundance of exotic invaders. Stems of saplings (>1.5m height) and trees will be counted and measured (diameter at breast height DBH). In addition, we will identify all species present in the nested subplots and compile a complete species list. Based on these data from the nested subplots, we will construct a species-area curve for each plot and then use the curves to compare the scale at which richness plateaus. Severely impaired sites generally have reduced native richness, low abundance of rare and sensitive species, and higher abundance of exotic species. We will also calculate the Floristic Quality Index (FQI), which combines several of these measures (e.g., species richness, number and abundance of exotic species). This index has been used effectively in wetlands and other communities to assess the "naturalness" of a site (U.S. EPA 2002ab, Lopez and Fennessy 2002). The FQI requires a "coefficient of conservatism" for each species. Many states have begun to assemble these coefficients, and we will work with state agencies to compile these coefficients for species in the UMRS focus area so that we may include FQI as a candidate metric.

Functional attributes will also be measured at each site. These measures of ecosystem function have been shown to be useful indicators (Day et al. 1997), particularly for assessing cumulative impacts of stressors (Gosselink and Lee 1989). We will examine annual growth rates for long-lived forest species using tree-ring analysis. Twenty trees will be randomly selected from each plot, ten that are < 15 cm DBH and ten that are = 15 cm DBH will be selected. A cross section will be taken from the smaller trees, and individuals = 15 cm DBH will be cored. Annual growth increments will be measured under a stereoscope using an Incremental Measuring Machine. Rings will be measured from the center outward and to the nearest 0.01 mm. Production will be estimated at each site using annual growth ring increments and published allometric regression equations for bottomland species (see Megonigal et al. 1997).

Soil indicators, including organic matter (OM) content and nutrient content (total Nitrogen (N) and Phosphorus (P)) will also be assessed. Two soil samples will be taken at each site using an AMS Standard Soil Auger Bucket (5.08 cm diameter). One of these samples will be used to determine organic matter, measured as loss on ignition in a muffle furnace. Organic matter content has been successfully used as a measure of forest development and ecosystem maturity (Giese et al. 2003). The other soil sample will be used to determine total N and P. Bottomland forests typically have high nutrient levels, but they may exhibit nutrient enrichment in response to land use changes in the watershed, particularly in agricultural landscape (U.S. EPA 2002ab). These techniques will be useful for detection of shifts in composition and site productivity (U.S. EPA 2002ab) that might occur, for example, because of altered hydrology.
Indicator development

Once the data have been collected, we will analyze the candidate metrics (Table 1) and determine which ones (or a combination thereof) are the most useful for assessment of the biological health of our selected floodplain communities. Ideally, we want metrics that are consistently predictive of ecological condition. Low variability among reference sites is another desirable feature. We will directly compare reference to disturbed sites for most metrics (denoted by an "*", Table 1). Where there are statistical differences, we will quantify the degree to which disturbed and reference sites differ. We will then divide the disturbed sites into three categories (good, fair, and poor) according to how much they deviate from the average reference condition. It is possible that we some categories will not be represented, e.g., there are no poor sites.

Trends in species composition will be explored using non-metric multidimensional scaling (NMDS), a widely used ordination technique. Groups that are revealed by ordination analysis will be statistically compared using analysis of similarity (ANOSIM; Clarke 1993), a non-parametric multivariate technique. Connectivity to the river will be assessed based on management records of each area and interviews with site managers. Sites will be assigned to one of four categories: 0 = no overbank connection to river; 1 = infrequent and unpredictable connection; 2 = periodic overbank flooding; and 3 = annual, seasonal overbank flooding.

This work represents, to our knowledge, the first attempt to develop ecological indicators for bottomland hardwood ecosystems. We will use four steps to evaluate our candidate metrics, as recommended by EMAP (Barber 1994). We will assess each metric according to the following criteria: 1) conceptual soundness, 2) implementation, 3) response variability, and 4) interpretation and utility. This scheme should help us to identify the most informative, useful, and efficient metrics. Ultimately, we hope to identify and construct indicators that are useful for the assessment of ecological condition of UMRS floodplain communities. Budget: $80,676 Budget includes full cost accounting.

Literature Cited

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King, S. L. 1995. Effects of flooding regime on two impounded bottomland hardwood stands. Wetlands 15:272-284.

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Megonigal, J. P., W. H. Conner, S. Kroeger and R. R. Sharitz. 1997. Aboveground production in Southeastern floodplain forests: a test of the subsidy-stress hypothesis. Ecology 78:370-384.

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Principal investigator/Project leader:

Dr. Loretta L. Battaglia; Dept. of Plant Biology, Southern Illinois University, Carbondale
LTRM contact: Dr. Valerie Barko

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