BIOS 35502: Practicum in Field Biology A landscape position analysis of UNDERC lakes and a determination of its crayfish diversity is related to landscape position

Landscape position, generally defined as a lake’s position within the groundwater and/or surface flow system, has proven to be an effective way to explain much limnological variation. The lake order metric is a very efficient tool for explaining landscape position and is easy to measure using solely geographical information. I analyzed each of the 38 permanent lakes and bogs on the UNDERC property in order to determine how they fit into the lake order model using the following variables: lake area, perimeter, shoreline development factor, maximum depth, pH, conductivity, chlorophyll a concentration, crayfish abundance and Secchi depth. It was hypothesized that each of variables would each follow the trends predicted by the lake order model. Additionally, the relationship between crayfish richness and lake order was investigated at UNDERC as a novel variable to the model. Of the nine variables, only three (maximum depth, chlorophyll a and Secchi depth) were not significantly related to lake order, indicating that the UNDERC lakes most fit into the lake order model and further significance was limited by the small sample size of lakes on the property. In only one lake (of the highest order) was more than one crayfish species found. This indicates that more lakes need to be analyzed before any conclusive judgments of richness can be made. UNDERC may benefit from future landscape position analyses as they provide insight to proximate mechanisms, and how they may react to future external forces. Introduction Lakes within the same lake district share similar origins, climates and catchment areas but differ in many physical, chemical, and biological aspects. Understanding the underlying causes of this heterogeneity has been a recurrent theme of regional limnology. However, efforts to select the best predictors and to identify proximate causes have tended to obscure the spatial linkages among lakes in the landscape and have thus hampered a landscape perspective on lake districts (Riera et al. 2000). Only recently, in fact, have lakes been viewed along a spatial gradient, interconnected through groundwater and/or surface water pathways (Kratz et al., 1997; Soranno et al., 1999; Riera et al., 2000; Quinlan et al., 2003, Martin & Sorrano 2006). The studies that have identified and evaluated the importance of spatial structure across lakes have found that variability of some lake features follow a pattern consistent with the position of the lake within the landscape. The basis of this categorization is two-fold. First, lake features within a lake district are not randomly distributed in space but reflect a spatial pattern (Riera et al., 2000). Furthermore, each lake district displays a characteristic spatial organization, and different metrics of landscape position can reveal different aspects of this spatial pattern within a lake district, or among lake districts (Riera et al., 2000). Second, dissimilar lake features such as those included in the categories of morphological variables, water optical properties, major ions, biological variables, nutrients, and human-use variables, which may seem apparently unrelated to each other, are nonetheless related to a lake’s landscape position (Riera et al. 2000). Thus, landscape position is related to a broad array of lake properties. Lake landscape position, as defined by Kratz et al. (1997) is a “combination of the hydrologic description with information on the spatial placement of a lake within a district. ” Three predominant metrics for measuring lake landscape position have been described. The first is based on the relative position of a lake within the ground water system. The higher a lake is in the landscape the less groundwater input it has and as a result, less calcium and magnesium concentrations (Kratz et al., 1997). The second metric, developed by Soranno et al. (1999), is known as “lake chain number” and it measures lake landscape position with regard to lakes connected along a linear chain through primary surface-flow systems (Martin & Soranno 2006). Therefore, as lake chain number increased, not only did non-reactive weathering products such as calcium and magnesium increase, but so did concentrations of total nutrients and chlorophyll a (Martin & Soranno 2006). The final landscape metric, and the one focused on by this study, is known as “lake order. ” Developed by Riera et al. (2000), lake order is an extension of the river-continuum concept developed by Vannote et al. (1980) and is based on the type and strength of the connections between a lake and the surface drainage network. In a study looking at 71 lakes in northern Michigan, Marin & Soranno (2006) found that lake order was the landscape position metric that explained the most overall variation amongst limnological variables compared to three other metrics based on different aspects of lake surface hydrologic connections. Lake order provides lake researchers with a novel perspective in analyzing changes in lake characteristics along a gradient of landscape position (Quinlan 2003). Riera et al. (2000) found that 21 of 25 lake variables which included measures of lake morphometry, water optical properties, major ions, nutrients, biology, and human settlement patterns were explained by lake order. Thus, this classification can be beneficial in many ways. The first objective of this study was to determine if the lakes on the UNDERC property fit into the lake order model. As shown, this model has been used to explain many patterns of limnological properties and thus an examination of how these characteristics of UNDERC lakes compare to previously observed patterns may offer many benefits to the property as suggested by Riera et al. (2000). First, it would reveal how lakes are related to each other across the landscape. Second it would provide information of how the lakes may respond to external forces in the future. Third, it would provide a framework for regionalization, allowing better predictions and better management decisions with scant data. Finally, it would provide a framework for the synthesis of regional analyses of lakes, streams, and the terrestrial landscape. The hypothesis of this study is that the lakes on the UNDERC property fit into the lake order model, meaning that physical, chemical and biological characteristics follow a predictable pattern based on the order of the lake. The lake physical properties chosen to be analyzed in this study were: lake area, lake perimeter, shoreline development factor and maximum depth. Conductivity and pH were chosen as lake chemical properties to be analyzed. Chlorophyll a and crayfish abundance were chosen as biological properties. Finally, the Secchi depth was chosen as a water optical property. Since both Riera’s study and my own study were conducted in the Northern Highland Lake District, I hypothesized that the lakes on the UNDERC property would follow the same trends as those observed by Riera et al. (2000). The second objective of this study was to test the presence and strength of the relationship between crayfish diversity and lake order. Fish richness has been shown to be correlated with lake order (Riera et al., 2000) but crayfish diversity has not yet been examined. Capelli & Magnuson (1983) found that crayfish abundance in the Northern Highland Lake District of Wisconsin was best predicted by calcium concentration, the quality of the littoral substrate, and lake size. All three of these variables were shown by Riera et al. (2000) to be related to lake order. Whether diversity is related to these variables and therefore related to lake order has not been assessed. I hypothesized that crayfish richness will increase with increasing lake order as suitable habitat and calcium concentrations increase. Additionally, higher order drainage lakes are connected to other lakes by streams and rivers and thus crayfish should have been able to naturally colonize adjacent lakes. Methods Study area The UNDERC property resides in the Northern Highland Lake District on both sides of the state line between Wisconsin and Michigan's Upper Peninsula in Vilas County (Wisconsin) and Gogebic County (Michigan). The landscape was formed approximately 12,000 years ago as a result of the Wisconsin glaciation and the altitude of the area ranges between 500 m and 520 m. The UNDERC property encompasses a land area of 6150 acres with nearly 40 permanent lakes and bogs with a combined surface area of 1350 acres. The property also lies in an area where the glacial deposits are young and the drainage system is poorly developed although this district serves as the headwaters for many major river systems such as the Wisconsin and Menominee (UNDERC 2004) Lake order Lake order is based solely on geographical information (Riera et al. 2000). For lakes with both surface inlets and outlets, lake order was defined as the order of the stream that drains the lakes. For lakes with a surface outlet but no inlet (headwater lakes) a lake order of 0 was assigned. Lakes connected to the surface drainage network by weak or intermittent streams were assigned a lake order -1. Lakes that were connected to the drainage system by a wetland where channelized flow was absent were assigned a lake order -2. Finally, closed-basin lakes which were hydrologically unconnected to the drainage network by surface water were assigned an order -3. Lake order on the UNDERC property was obtained in two ways. The first was through the analysis of USGS (U.S. Geological Survey) topographical maps. The scale of these maps was 1:24,000 and 1:100,000. Riera et al. (2000) found however that lake order values are sensitive to map scale and accuracy. Therefore, each accessible lake to be assigned an order on the property was thoroughly examined by boat for inlets and outlets. This examination proved important in a study done by Quinlan et al. (2003) which found that a certain lake showed no outlet streams on a 1:50,000 map but fi