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Influence of land use on the distribution of Submerged Aquatic Vegetation and fish populations in the Rappahannock River Inia M. Soto University of Puerto Rico at Mayaguez To: REU – Program at VIMS Mentors: Marcia Berman: Director, Comprehensive Coastal Inventory Program Donna Bilkovic : Fisheries Biologist, Center for Coastal Resources Management Tami Rudnicky: GIS Programmer/Analyst - CCI August 6, 2004 Abstract During the last decades, submerged aquatic vegetation (SAV) abundance has been declining drastically. Submerged Aquatic Vegetation is considered an important essential fish habitat, thus declines in SAV might have negative consequences to fish communities. Import of nutrients and sediment into tributaries affect water clarity; and consequently, the survival of SAV. Inputs of nutrients, pollutants and sediments are directly related to land use practices. The purpose of this research is to evaluate anthropogenic impacts on SAV biomass, fish communities and water quality in the lower Rappahannock River, a major tributary of the Chesapeake Bay. We wanted to assess associations between SAV abundance and fish diversity with respect to land use; and evaluate river discharge as an indicator of water clarity. For the time period 1989-2002, we calculated fish community metrics, used Geographic Information Systems (GIS) to compute land use change, examined environmental parameters (e.g. river discharge, temperature and precipitation), and estimated SAV biomass. We found a slight increase in the amount of developed area, with decreases in agricultural and forested land use. Fish species richness and abundance were inversely correlated, while species richness and the number of dominant species were positively correlated. Environmental parameters were not correlated with the examined fish community metrics. There was evidence that stream flow may influence SAV biomass and distribution in this system. Relationships among SAV biomass, land use and fish community metrics could not be completed quantified. Examining other environmental factors and extending the study area might provide a better understanding of the impact of human activities to SAV abundance and fish communities. During the last decades, submerged aquatic vegetation (SAV) abundance has been decline drastically. Introduction Essential fish habitat is defined to include both waters and substrate necessary to fish for spawning, breeding, feeding, or growth maturity (16 US.C 1802(10)). One of the most commonly recognized essential nursery habitat is submerged aquatic vegetation (SAV), due in part to its abilities to export large quantities of carbon, nitrogen, and phosphorous to coastal food webs (Beck et al, 2001). In addition to being a nursery area, SAV provides oxygen, absorb wave energy and uptake nutrients (NMFS Web site, 16 U.S.C. 1801 (A)(9)). Researchers have shown evidence of higher fish abundance and diversity in SAV habitat versus nonvegetated subaqueous bottom (Beck et al. 2001, Hoss and Thyer 1993, Matheson et al. 1999). The distribution of SAV has been fluctuating during the past decades. Recently, the Bay Journal (June 2004) reported for 2003 a 30% decline in the abundance of SAV, especially in the lower and middle Rappahannock River, compared with the four prior years. High rainfall in 2003 caused an increase in stream flow, which delivered three times more nitrogen, five times more phosphorus, and 11 times more sediments to the tributaries (Bay Journal, 2004). Since SAV depend on sunlight to survive, large quantities of sediments and particulate matter reduce water clarity causing mortality of SAV. Also, discharge of other pollutants might be limiting factors for SAV survival. Large inputs of nutrients, pollutants and sediments are directly related to land use practices. Agriculture and development are accompanied by land disturbance that increases erosion, sedimentation, and nutrient runoff to the bay (NOAA Technical report 123, 1995). During wet years, nutrient rich sediments and particulate runoff enter streams causing turbidity, low light attenuation, and consequently a die off of SAV. The VIMS SAV Program reports an increase in abundance of SAV during dry years preceding 2003, suggesting lower turbidity and high light attenuation as primary driving factors. The NOAA Technical report 123 (1995) suggests the study of land cover change as a tool to measure the input of nutrients, sediments, pollutants and other factors that might control water quality and habitat disturbance. Studying change in land use patterns over time is a good approach to understanding the impacts of land use on SAV growth, and consequently fish habitat. A better understanding of essential fish habitat and the factors affecting them will improve management, conservation, and decisions related to fisheries (Beck et al. 2001). Objectives/ Hypothesis The objective of this research is to evaluate the anthropogenic impacts to SAV and fish populations in the lower Rappahannock River. The analyses will compare abundance of SAV and fish diversity with respect to land use. We hypothesize a decline in fish diversity and abundance during years with low SAV abundance. SAV abundance is expected to respond to changes in land use over the last several decades. Since rivers transport sediment, nutrients, and pollutants produced by anthropogenic activity on the upland, river discharge will be used in the absence of water quality data, to assess water quality condition in the river. Discharge will then be compared with SAV abundance. Low densities of SAV are expected during wet years as a consequence of high sediment discharge. SAV distribution should increase during drought years. Methods This research is divided into three components: analysis of fish community, SAV abundance and changes in land use. Each component will be analyzed individually and the compared. Fish community Data from the 1989 – 2003 VIMS striped bass seine survey was used to assess temporal patterns in abundance and diversity. The seine survey is conducted bi-weekly between July to September using 0.25 in. mesh minnow seine in shallow water. This project uses data collected from station 12 in the lower Rappahannock River (-76.525N/ 37.6117W). In addition to station 12, fish data were compared with two upriver stations: #21(-76.62N/ 37.75W), and #28(-76.73N/ 37.80W). Parameters used to measure fish population were species richness, species dominance, and fish abundance. Species richness is the total number of species minus one divided by the log abundance (Margalef’s Index). Species dominance is equal to the number of species that contribute to 90 percent of the total abundance. Abundance was calculated as the natural log of the total number of fish. Data was compiled from the seine surveys using averaged rounds for the year. A One Way ANOVA and Pearson correlation were used to statistically analyze the results. Study area An Anderson (1976) level 1 land use classification (e.g. forest, agriculture and developed areas) was applied to describe land use in the study area for three different years: 1978, 1994, and 2002. The 1978 digital imagery, a product of the United States Army Corps of Engineers (USACE) is natural color aerial photography scanned to 600 dpi, and scaled 1:12,000. The 1994 imagery is color infrared digital ortho quarter quadrangles with a resolution of 1m, obtained from the U.S. Geological Survey. The 2002 digital image is ortho corrected with a resolution of 0.61m, and scaled 1:400. This digital image was obtained from the VA Base Mapping Program. Using Geographical information system (GIS), land use change was computed for a 15,600 acre area surrounding the fish sampling point (station 12). ERDAS® Imagine image processing software was used to digitize land use boundaries from the digital imagery. ArcInfo was used to edit, label, and classify land use polygons. A frequency analysis was applied to each year to compute the occurrence of land use classes. Values obtained with the frequency analysis were compared and patterns of change observed. SAV biomass Submerged Aquatic Vegetation delineations generated by the Department of Biological Sciences at the Virginia Institute of Marine Science were used in this study. SAV biomass was calculated using a monthly biomass model (Moore, 2002) where: Monthly Biomass = Mb * Cc* Ba, and Mb = model biomass for assigned community type (grams dry mass per square meter), Cc = photo-interpreted density class to ground cover conversions, and Ba = bed area (m2). The study area used in our research is primarily populated by Ruppia maritima (Moore,2000), with a modeled biomass of 100 dgm/m 2. The photo interpreted values were obtained by an equation presented by Moore (2000): Cc = 0.69x + 17, where x = mid point of density classes (%). SAV density delineations have a scale assigned from 0 to 4, 0 to 100% bottom coverage respectively. The density range (as a percentage) is assigned for each value in the density scale where: 0=0%, 1=<10%, 2=10–40%, 3=40 – 70%, and 4=70 – 100. For example, when the density scale = 1, then bottom coverage equals 0 to 10%, and x=5; Cc = 20.45. The bed area was calculated using ArcView 3.1. Environmental Parameters Submerged Aquatic Vegetation biomass, fish population data, and land use changes over time were compared with variations in temperature, precipitation, and stream flow for similar years. Stream flow data were obtained from the USGS web site (station number p1668000, Spotsylvania County, Virginia (38º18’30N, 77º31’46’’W)). The drainage area for this station is 1596 squares miles. Stream flow was measured in cubic feet per second. Temperature and precipitation data were obtained from the National Climatic Data Center, NOAA. For 1989 to 1993 data was reported from the station located in Fredericksburg National Park (38.19N/ 77.27W). For 1993 to 2003 data from the Fredericksburg sewage treatment plant was used (38.17N/ 77.27W). Precipitation was measured in inches per day, and temperature was measured in Fahrenheit degrees. Stream flow and temperature were averaged per year, and total inches of precipitation per year were summed. Results Land use within the study area on the lower Rappahannock River did not vary significantly during the period of time studied. The frequency analysis showed a slight increase in developed areas, with a decrease in agriculture and forested land area (Figure 1). From the analysis of the fish survey data we found an inverse significant correlation (r = -0.0528, p = 0.052) between species richness and fish abundance at station 12 (Figure 2). At the same time, species richness and dominance (Figure 3) were significantly correlated (r = 0.593, p = 0.025). During years when species richness was low, the number of species dominanting was also low. Generally, dominant species were schooling fish like Atlantic menhaden (Brevoortia tyrannus), Bay anchovy (Anchoa mitchelli), spot (Leiostomus xantharus), and Atlantic silverside (Menidia menidia). However, during years where species richness was high, these species were not present. The fish community metrics varied over the period of time studied. Species richness was low during 1989, and increased in 1990. However, during the following 11 years species richness declined until 2002, when a drastic increase in occurred (Figure 2). The comparison of fish community metrics among three stations on the Rappahannock River (12, 21, 28) showed no significant difference (p = 0.112) in fish abundance, and a significant difference (p = 0.0001) in species richness (Figures 4 and 5). Species richness was highest at the uppermost station (28), possibly due to salinity regimes. Species richness at stations 12 and 28 were higher than station 21, located mid-river. The presence of SAV was not consistent during the period of time studied. In 1989, the biomass of SAV was 8.2 x 1010 dgm m-2, and during 1990 it declined to 7.8 x 107 dgm m-2. During the following eleven years no SAV were present in the study site. In 2002 SAV returned with a biomass of 6.5 x 10 8 dgm m-2. This recurrence quickly disappeared and the 2003 survey showed no SAV again. The presence of SAV during the year 2002 coincides with an increase in species richness (Figure 6). In addition, the extended period of no SAV correlates with the eleven years of low fish diversity. The environmental factors (e.g. temperature, precipitation, and stream flow) did not correlate with the species richness, dominance, and abundance (Table 1). Also, environmental factors did not correlate among each other. However, presence of SAV coincides with years of low river discharge. From 1999 to 2002 stream flow was very low, and that is very important because after eleven years (1990-2001) of SAV absence, SAV reappeared in 2002. In June 2004, the Bay Journal published a report with data from the U.S. Geological Survey that showed a drastic increase in river discharge compared to a 30% decline in SAV biomass as reported from the Maryland Department of Natural Resources. Discussion The small size of the study area contributes to the low variation in land use between years. Due to the increase in population and global movement of development toward the coast, we expected a significant increase in developed area. However, the study area seems to have an economy based on agriculture practice, which showed only a slight decline. Other factors non-related to the study area might also be influencing the results. For example, the aerial photographs used to calculate land use had different resolutions and spectral properties. These differences can influence interpretation and ultimately the designations of land use boundaries. The presence of schooling fish in the catch increased the abundance estimates, and at the same time decreased the diversity. The species dominance metric showed that during years with high abundance of fish only a few species contribute to 90% of the total abundance. Increases in diversity during 2002 suggest a possible relationship with the presence of SAV. This point is not supported with the low diversity of fish observed in 1989, where SAV was present. However, the exploration of additional years indicates possible relationships may exist. An increase in diversity occurred from 1989 to 1990, when SAV declined but did not disappear. Subsequently, low fish diversity persists over the eleven years when SAV was absent. The low abundance of fish during years of SAV presence might be related to environmental changes that influence conditions for SAV growth. For instance, an increase in diversity due to SAV presence might promote an increase in predators for the schooling fish that dominate the fish population during years of high abundance of fish and low species richness. The difference in species richness among stations along the river suggests the influence of other environmental factors besides those analyzed in this research. Neither stream flow, precipitation nor temperature correlated with fish populations. A factor that might be driving fish diversity in the river is salinity, which varies along the river. Other factors such as dissolved oxygen, water clarity, and nutrients might cause variations in diversity of fish. These factors are influenced by anthropogenic impacts. In this study, change in land use was used as a measure of anthropogenic impacts. However, effects of land use on SAV biomass and fish communities cannot be determined with the data obtained in our research due to the spatial size and scale of the study area. Our results do not limit the possible relationship between SAV abundance and consequently fish communities. Stream flow seems to influence the presence and biomass of SAV. Low river discharge yields low suspended sediment concentrations and enhances water clarity. These conditions favor the growth of SAV. On the other hand, high river discharge reduces water clarity with higher sediment loads and may induce die-off in SAV. In conclusion, relationships among SAV biomass, land use, and fish community metrics could not be completely quantified. Further research is necessary to understand the relationship of these three components: land use, SAV abundance and fish populations. This can be achieved in part by extending the study area and incorporating land use for the entire watershed. A better understanding of conditions in the upper watershed with respect to land use might explain responses in the lower river. The relationship between SAV and fish communities will be better determined if future analyses target watersheds with consistently larger SAV beds and incorporate additional fish survey stations. The study of additional environmental factors (e.g. salinity and dissolve oxygen) will provide critical information to understand the human impacts to essential fish habitats. Acknowledgements Special thanks to Marcia Berman, Donna Bilkovic, and Tami Rudnicky for intellectual contributions and support during the research. Thank you very much to Dave, Harry, Tami and Sharon for helping me with the technology and instrumentation. Thanks to the Center for Coastal Resource Management people for their support during the research. Thanks to Linda Shaffner and Rochelle Seitz for the opportunity to participate in the VIMS-REU program. This research was part of the VIMS-REU summer internship funded by the National Science Foundation. Thanks to the VIMS SAV mapping program and the Striped bass seine survey group, especially to Dr. Herb Austin and Chris Bonzek for facilitating the use of the fish survey data. Special thank to Dave Wilcox for orienting me about the distribution and ecology of SAV. Thanks to the College of William and Mary and the Virginia Institute of Marine Science for allow me to use their facilities. Thanks to the VIMS staff and personnel for offering unconditional help when I needed it. References Anderson, J.R., E.E. Hardy, J.T. Roach, and R.E. Witmer. 1976. A land use and land cover classification system for use with remote sensor data: U.S. Geol Survey Circ. 964, 1- 27. Beck, M.W, Jr. K.L.Heck, K.W. Able, and D.L. Childers. 2001. The identification, conservation, and management of estuarine and marine nurseries for fish and invertebrates. BioScience. 51 (8), 633 – 641. Blankenship, K. 2004. Bay’s SAV fell off almost 30% in 2003. Bay Journal: Alliance for the Chesapeake Bay. 14(4), 6-7. Hardy, R.W. 1995. NOAA Coastal Change Analysis Program (C-CAP): guidance for regional implementation. NOAA Technical Report NMFS 123. Pp. 1-92 Hoss, D. E., G.W.Thayer. 1993. The importance of habitat to the early life history of estuarine dependent fishes. American Fisheries Society Symposium 14, 147158. Lazzari, M. A., 2002. Epibenthic fishes and decapods crustaceans in northern estuaries: a comparison of vegetated and unvegetated habitats in Maine. Estuaries. 25(6A), 1210-1218. Matheson, Richard E, S.M. Sogard, and K.A. Bjorgo. 1999. Changes in Sea grass associated fish and crustacean communities on Florida Bay mud banks: the effects of recent ecosystem changes? Estuaries. 22(2B): 534-551. Internet Sources: NOAA- NMFS Web Page. Essential Fish Habitat. June 23, 2004. http://www.nmfs.noaa.gov/habitat/habitatprotection/essentialfishhabitat.htm. VIMS SAV Mapping Lab Web page. Submerged Aquatic Vegetation (SAV) species in Chesapeake Bay. http://www.vims.edu/bio/sav/aboutsav.html. Last modified 2/18/04. Land Use in the Lower Rappahannock River 7000 Agriculture Developed Forested Water 6000 Land use (acres) 5000 4000 6413 6361 3000 4913 6267 4905 4855 2000 3320 2837 2666 1000 1046 1481 1849 0 1978 1994 2002 YEAR Figure 1: Land use changes in Rappahannock River from 1978 to 2002. 9 4.5 8 4 7 3.5 6 3 5 2.5 4 2 3 1.5 r = -0.0528, p = 0.052 2 LN Abundance Average Diversity 1 0 Species richness LN Abundance of fish Species Richness and LN abundance in Rappahannock River Station 12 1 0.5 0 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 Year (1989 - 2003) Figure 2: Average species richness (Total # species – 1/Log total # fish) and LN abundance (LN total number of fish per year) in Rappahannock River Station 12 from 1989 to 2003. An inverse correlation between species richness and LN abundance was present. Species Richness and Dominance in Rappahannock River Station 12 8 Diversity 4 Dominance Species Richness 3.5 3 7 6 5 2.5 4 2 3 1.5 1 2 r = 0.593, p = 0.025 1 0.5 0 0 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 Year (1989 - 2003) Figure 3: Species richness and dominance (number of species that contribute to the 90% of the abundance) in Lower Rappahannock River Station 12 from 1989 to 2003. A significant correlation between species richness and dominance was present. Species Dominance 4.5 LN fish abundance by station 9 Ln Abundance 8 7 6 5 p = 0.112 4 28 21 12 3 Stations in Rappahannock River Downstream -> upriver Figure 4: LN abundance of fish for three stations in Rappahannock. No significant difference in abundance among the stations was present. Species Richness by Station 6 Species richness 5 4 3 2 p<0.0001 1 28 21 12 0 Stations in Rappahannock River Downstrean -> upriver Figure 5: Species richness for three in Rappahannock River. Station 12 is located downstream, station 21 is mid-river, and station 28 is the upper most examined. locate upper in the river. A significant difference among the stations was observed.. Comparison between SAV biomass and fish species richness in Rappahannock River Station 12 4.5 1.E+10 8.19 x 10 10 dgm m-2 4 8.E+09 3.5 7.E+09 3 6.E+09 2.5 5.E+09 2 4.E+09 1.5 3.E+09 2.E+09 SAV 1 1.E+09 Diversity 0.5 Fish Species Richness SAV Biomass (dgm m-2) 9.E+09 0 0.E+00 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2002 2003 Year (1989 - 2003) Figure 6: Comparison between SAV biomass and fish species richness in Rappahannock River station 12 from 1989 to 2003. Environmental Parameter Precipitation Temperature Stream flow Station 12 – Rappahannock River Pearson Species richness LN abundance correlation r - value 0.172 0.222 p - value 0.556 0.445 r - value 0.466 0.123 p - value 0.093 0.674 r - value -0.433 0.358 p - value 0.140 0.230 Species Dominance -0.001 0.997 0.078 0.792 0.044 0.887 Table 1: No significant correlation between the fish population parameter and environmental parameters in Rappahannock River station 12 was present. The correlation coefficient and associated p-value are depicted for each parameter.